AIM:To develop a novel 3-dimensional(3D) virtual hepatectomy simulation software,Liversim,to visualize the real-time deformation of the liver.METHODS:We developed a novel real-time virtual hepatectomy simulation softw...AIM:To develop a novel 3-dimensional(3D) virtual hepatectomy simulation software,Liversim,to visualize the real-time deformation of the liver.METHODS:We developed a novel real-time virtual hepatectomy simulation software program called Liversim. The software provides 4 basic functions:viewing 3D models from arbitrary directions,changing the colors and opacities of the models,deforming the models based on user interaction,and incising the liver parenchyma and intrahepatic vessels based on user operations. From April 2010 through 2013,99 patients underwent virtual hepatectomies that used the conventional software program SYNAPSE VINCENT preoperatively. Between April 2012 and October 2013,11 patients received virtual hepatectomies using the novel software program Liversim; these hepatectomies were performed both preoperatively and at the same that the actual hepatectomy was performed in an operating room. The perioperative outcomes were analyzed between the patients for whom SYNAPSE VINCENT was used and those for whom Liversim wasused. Furthermore,medical students and surgical residents were asked to complete questionnaires regarding the new software.RESULTS:There were no obvious discrepancies(i.e.,the emergence of branches in the portal vein or hepatic vein or the depth and direction of the resection line) between our simulation and the actual surgery during the resection process. The median operating time was 304 min(range,110 to 846) in the VINCENT group and 397 min(range,232 to 497) in the Liversim group(P = 0.30). The median amount of intraoperative bleeding was 510 m L(range,18 to 5120) in the VINCENT group and 470 m L(range,130 to 1600) in the Liversim group(P = 0.44). The median postoperative stay was 12 d(range,6 to 100) in the VINCENT group and 13 d(range,9 to 21) in the Liversim group(P = 0.36). There were no significant differences in the preoperative outcomes between the two groups. Liversim was not found to be clinically inferior to SYNAPSE VINCENT. Both students and surgical residents reported that th展开更多
Recent studies have revealed that bile acids(BAs)are not only facilitators of dietary lipid absorption but also important signaling molecules exerting multiple physiological functions.Some major signaling pathways inv...Recent studies have revealed that bile acids(BAs)are not only facilitators of dietary lipid absorption but also important signaling molecules exerting multiple physiological functions.Some major signaling pathways involving the nuclear BAs receptor farnesoid X receptor and the G protein-coupled BAs receptor TGR5/M-BAR have been identified to be the targets of BAs.BAs regulate their own homeostasis via signaling pathways.BAs also affect diverse metabolic pathways including glucose metabolism,lipid metabolism and energy expenditure.This paper suggests the mechanism of controlling metabolism via BA signaling and demonstrates that BA signaling is an attractive therapeutic target of the metabolic syndrome.展开更多
Nature is an information sourcebook of behaviour, function, colour and shape which can inspire visual design and invention. Studying the form and functional characteristics of a natural object can provide inspiration ...Nature is an information sourcebook of behaviour, function, colour and shape which can inspire visual design and invention. Studying the form and functional characteristics of a natural object can provide inspiration for product design and help to improve the marketability of manufactured products. The inspiration can be triggered either by direct observation or captured by three-dimensional （3D） digitising techniques to obtain superficial information （geometry and colour）. An art designer often creates a concept in the form of a two-dimensional （2D） sketch while engineering methods lead to a point cloud in 3D. Each has its limitations in that the art designer commonly lacks the knowledge to build a final product from a 2D sketch and the engi- neering designer＇s 3D point clouds may not be very beautiful. We propose a method for Product Design from Nature （PDN）, coupling aesthetic intent and geometrical characteristics, exploring the interactions between designers and nature＇s systems in PDN. We believe that this approach would considerably reduce the lead time and cost of product design from nature.展开更多
AIM: To summarize the evidence available for the clinical effectiveness of insulin sensitizers in the treatment of nonalcoholic fatty liver disease (NAFLD) systematically. METHODS: Relevant articles were located using...AIM: To summarize the evidence available for the clinical effectiveness of insulin sensitizers in the treatment of nonalcoholic fatty liver disease (NAFLD) systematically. METHODS: Relevant articles were located using computer-assisted searches of Medline (1966-March 2006), EMBASE (1988-March 2006), CINAHL (1982-March 2003), Educational Resource Information Center (1966-March 2006), Library, Information Science & Technology Abstracts (1967-March 2006), Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects (1994-2006), dissertations in ProQuest and FirstSearch databases. Manual searches were made in the abstracts from meetings of the American Gastroenterological Association (1999-2006), and the American Association for the Study of Liver Diseases (2003-2005). Studies were retrieved using the following selection criteria: (1) clinical trials using insulin sensitizers in subjects with NAFLD, (2) adult patients, (3) published as full manuscripts or abstracts, and (4) English, Spanish, German, and French languages only. Data were abstracted independently by two reviewers following standardized procedures. A face-to- face comparison of data was conducted to ensure the completeness and reliability of the abstraction process. RESULTS: Nine studies were included, six using metformin and three using thiazolidinediones. Only two studies were placebo-controlled trials. The mediansample size for all studies was 18 subjects. In the placebo-controlled trials, metformin improved insulin resistance markers and liver function tests, but not histological scores. In the single-arm trials, metformin and thiazolidinediones improved insulin resistance markers and liver function tests, and beneficial histological changes were reported. There is limited high-quality information available from which to draw categorical conclusions about the clinical use of insulin sensitizers in NAFLD.CONCLUSION: Current information indicates that the use of insulin sensitizers in NAFLD improves insulin resistance and liver 展开更多
The intervention of behaviors, including physical activity (PA), has become a strategy for many hospitals dealing with patients with chronic diseases. Given the limited evidence available about PA and healthcare use w...The intervention of behaviors, including physical activity (PA), has become a strategy for many hospitals dealing with patients with chronic diseases. Given the limited evidence available about PA and healthcare use with chronic diseases, this study explored the association between different levels of PA and annual hospital service use and expenditure for inpatients with coronary heart disease (CHD) in China. We analyzed PA information from the first follow-up survey (2013) of the Dongfeng-Tongji cohort study of 1460 CHD inpatients. We examined factors such as PA exercise volume and years of PA and their associations with the number of inpatient visits, number of hospital days, and inpatient costs and total medical costs. We found that the number of hospital days and the number of inpatient visits were negatively associated with intensity of PA level. Similarly, total inpatient and outpatient costs declined when the PA exercise volume levels increased. Furthermore, there were also significant associations between the number of hospital days, inpatient costs or total medical costs and levels of PA years. This study provides the first empirical evidence about the effects of the intensity and years of PA on hospital service use and expenditure of CHD in China. It suggests that the patients' PA, especially the vigorous PA, should be promoted widely to the public and patients in order to relieve the financial burden of CHD.展开更多
Background:As internet and social media use have skyrocketed,epidemiologists have begun to use online data such as Google query data and Twitter trends to track the activity levels of influenza and other infectious di...Background:As internet and social media use have skyrocketed,epidemiologists have begun to use online data such as Google query data and Twitter trends to track the activity levels of influenza and other infectious diseases.In China,Weibo is an extremely popular microblogging site that is equivalent to Twitter.Capitalizing on the wealth of public opinion data contained in posts on Weibo,this study used Weibo as a measure of the Chinese people’s reactions to two different outbreaks:the 2012 Middle East Respiratory Syndrome Coronavirus(MERS-CoV)outbreak,and the 2013 outbreak of human infection of avian influenza A(H7N9)in China.Methods:Keyword searches were performed in Weibo data collected by The University of Hong Kong’s Weiboscope project.Baseline values were determined for each keyword and reaction values per million posts in the days after outbreak information was released to the public.Results:The results show that the Chinese people reacted significantly to both outbreaks online,where their social media reaction was two orders of magnitude stronger to the H7N9 influenza outbreak that happened in China than the MERS-CoV outbreak that was far away from China.Conclusions:These results demonstrate that social media could be a useful measure of public awareness and reaction to disease outbreak information released by health authorities.展开更多
Deep learning with convolutional neural networks(CNNs)has achieved great success in the classification of various plant diseases.However,a limited number of studies have elucidated the process of inference,leaving it ...Deep learning with convolutional neural networks(CNNs)has achieved great success in the classification of various plant diseases.However,a limited number of studies have elucidated the process of inference,leaving it as an untouchable black box.Revealing the CNN to extract the learned feature as an interpretable form not only ensures its reliability but also enables the validation of the model authenticity and the training dataset by human intervention.In this study,a variety of neuron-wise and layer-wise visualization methods were applied using a CNN,trained with a publicly available plant disease image dataset.We showed that neural networks can capture the colors and textures of lesions specific to respective diseases upon diagnosis,which resembles human decision-making.While several visualizationmethods were used as they are,others had to be optimized to target a specific layer that fully captures the features to generate consequential outputs.Moreover,by interpreting the generated attention maps,we identified several layers that were not contributing to inference and removed such layers inside the network,decreasing the number of parameters by 75%without affecting the classification accuracy.The results provide an impetus for the CNN black box users in the field of plant science to better understand the diagnosis process and lead to further efficient use of deep learning for plant disease diagnosis.展开更多
Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features,as well as its easy burying in the complex,non-stationary structural vibrations and strong bac...Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features,as well as its easy burying in the complex,non-stationary structural vibrations and strong background noises.In this paper,a method based on the flexible analytical wavelet transform(FAWT)possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings.During the route of the proposed method,the proper FAWT bases are constructed via genetic optimization algorithm(GA)based on maximizing the spectral correlated kurtosis(SCK)which is firstly presented and proved to be efficient and effective in indicating interested fault mode.Via using the customized FAWT bases for each interested fault mode,the original vibration measurements are decomposed into fine frequency subbands,and the sensitive subband which enhances the signal-to-noise ratio(SNR)is selected to exhibit the fault signature on its envelope spectrum.The proposed method is tested via simulated signals,and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace,inner-race and roller defects.The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.展开更多
We investigate whether large language models can perform the creative hypothesis generation that human researchers regularly do.While the error rate is high,generative AI seems to be able to effectively structure vast...We investigate whether large language models can perform the creative hypothesis generation that human researchers regularly do.While the error rate is high,generative AI seems to be able to effectively structure vast amounts of scientific knowledge and provide interesting and testable hypotheses.The future scientific enterprise may include synergistic efforts with a swarm of“hypothesis machines”,challenged by automated experimentation and adversarial peer reviews.展开更多
Mobile health applications, or mHealth apps, have gained popularity due to their practical functions and strengthening the connection between patients and healthcare professionals. These apps are designed for managing...Mobile health applications, or mHealth apps, have gained popularity due to their practical functions and strengthening the connection between patients and healthcare professionals. These apps are designed for managing health and well-being on portable devices, allowing individuals to self-manage their health or healthcare practitioners to enhance patient care. Key features include personalized recommendations, data synchronization with other health devices, and connectivity with healthcare professionals. The research describes how mobile health applications support healthy behaviors, facilitate communication between patients and physicians, and empower individuals in the United States to take charge of their health. This study also examines how adults in the US use mobile health applications, or mHealth apps, on their tablets or smartphones for health-seeking purposes. The information was taken from Cycle 4 of the Health Information National Trends Survey (HINTS 4). The challenges regarding these mobile health apps have also been evaluated with possible remedies. Around 100 university students participated in a cross-sectional study by answering questions on their eating habits, physical activity, lifestyle choices related to health, and use of mobile health apps. The data was then analyzed and concluded as a result. Mobile health applications have brought about a significant shift in the way patients connect with their healthcare providers by providing them with convenient access to health services and information. By keeping track of health markers like diet, exercise, and medication compliance, patients may use these tools to help better manage their chronic conditions. Mobile health applications can improve patient outcomes and save healthcare costs by empowering patients to take charge of their health. Through the facilitation of communication between patients and healthcare professionals, mobile health apps also offer virtual consultations and remote monitoring.展开更多
Global environmental problems have been increasing with the growth of the world economy and have become a crucial issue.To replace fossil fuels,sustainable and eco-friendly catalysts are required for the removal of or...Global environmental problems have been increasing with the growth of the world economy and have become a crucial issue.To replace fossil fuels,sustainable and eco-friendly catalysts are required for the removal of organic pollutants.In this study,nickel ferrite(NiFe_(2)O_(4))was prepared using a simple wet-chemical synthesis,followed by calcination;bismuth phosphate(BiPO_(4))was also prepared using a hydrothermal method.Further,NiFe_(2)O_(4)/BiPO_(4)nanocomposites were prepared using a hydrothermal technique.Numerous characterization studies,such as structural,morphology,surface area,optical,photoluminescence,and photoelectrochemical investigations,were used to analyze NiFe_(2)O_(4)/BiPO_(4)nanocomposites.The morphology analysis indicated a successful decoration of BiPO_(4)nanorods on the surface of Ni Fe_(2)O_(4)nanoplate.Further,the bandgap of the NiFe_(2)O_(4)/BiPO_(4)nanocomposites was modified owing to the formation of a heterostructure.The as-prepared NiFe_(2)O_(4)/BiPO_(4)nanocomposite exhibited promising properties to be used as a novel heterostructure for tetracycline(TC)and Rhodamine B(Rh B)removal.The NiFe_(2)O_(4)/BiPO_(4)nanocomposite degrades TC(98%)and Rh B(99%)pollutants upon solar-light irradiation within 100 and 60 min,respectively.Moreover,the trapping experiments confirmed the Z-scheme approach of the prepared nanocomposites.The efficient separation and transfer of photogenerated electron-hole pairs rendered by the heterostructure were confirmed by utilizing electrochemical impedance spectroscopy,photocurrent experiments,and photoluminescence.Mott–Schottky measurements were used determine the positions of the conduction and valence bands of the samples,and the detailed mechanism of photocatalytic degradation of toxic pollutants was projected and discussed.展开更多
Objective:To study the chemical constituents in leaves of Cebera manghas.Methods:Chemical constituents were isolated by using various column chromatography and tho structures were elucidated on basis of physicochemica...Objective:To study the chemical constituents in leaves of Cebera manghas.Methods:Chemical constituents were isolated by using various column chromatography and tho structures were elucidated on basis of physicochemical constants and spectral data analysis.Results:Nine compounds were obtained including p-hydroxybenzaldehyde(1),benzamide(2),n-hexadecane acid monoglyceride(3),loliolide(4),β-sitosterol(5),cerberin(6),neriifolin(7),cerleaside A(8), daucosterol(9).Conclusions:Compounds 1-4 are obtained from this genus for the first time.展开更多
Bird fauna checklists are important tools in ecology, biology, and conservation planning for scientists, stakeholders, and decision-makers. Despite its small area, the Gaza Strip (365 km<sup>2</sup>) has a...Bird fauna checklists are important tools in ecology, biology, and conservation planning for scientists, stakeholders, and decision-makers. Despite its small area, the Gaza Strip (365 km<sup>2</sup>) has a relatively large variety of resident and migratory bird fauna. Therefore, the current study aimed to provide an updated checklist of all bird fauna living in or inhabiting the Gaza Strip. Direct field observations using binoculars, continuous visits to zoos, pet stores and biology museums, discussion with bird hunters, follow-up of news and social networking sites, review of scientific publications and photography were the main tools to satisfy the purpose of the study. At least 250 bird species collected from different sources occur in the Gaza Strip and are included in the checklist. This list will not be static, but is inevitably subject to additions and changes in the face of times. The current 250 bird species of the Gaza Strip represent 45.4% of the 551 species of birds living in Palestine. The bird species were found to belong to 21 orders and 61 families. The Passeriformes (passerines) represented the largest order with 96 species of birds (38.4%), followed by the Charadriiformes 54 (21.6%), the Accipitriformes 18 (7.2%), Anseriformes 17 (6.8%) and Pelecaniformes 14 (5.6%), while the other orders represented the remaining percentage (20.4%). With regard to families, the Scolopacidae represented the largest family with 22 species of birds (8.8%), followed by the Anatidae and Accipitridae 17 for each (6.8%), the Muscicapidae 16 (6.4%) and Chariidridae and Fringillidae 11 for each (4.4%), while the other families represented the remaining percentage (62.4%). According to the IUCN regional threat categories, 226 species (90.4%) were Least Concern (LC), 12 (4.8%) were Near Threatened (NT), 6 (2.4%) were Vulnerable (VU), 4 (1.6%) were Endangered (EN) and 2 (0.8%) were Critically Endangered (CR). In conclusion, the study recommends a sustainable control of bird hunting and trafficking in addition to building p展开更多
Nowadays,the usage of socialmedia platforms is rapidly increasing,and rumours or false information are also rising,especially among Arab nations.This false information is harmful to society and individuals.Blocking an...Nowadays,the usage of socialmedia platforms is rapidly increasing,and rumours or false information are also rising,especially among Arab nations.This false information is harmful to society and individuals.Blocking and detecting the spread of fake news in Arabic becomes critical.Several artificial intelligence(AI)methods,including contemporary transformer techniques,BERT,were used to detect fake news.Thus,fake news in Arabic is identified by utilizing AI approaches.This article develops a new hunterprey optimization with hybrid deep learning-based fake news detection(HPOHDL-FND)model on the Arabic corpus.The HPOHDL-FND technique undergoes extensive data pre-processing steps to transform the input data into a useful format.Besides,the HPOHDL-FND technique utilizes long-term memory with a recurrent neural network(LSTM-RNN)model for fake news detection and classification.Finally,hunter prey optimization(HPO)algorithm is exploited for optimal modification of the hyperparameters related to the LSTM-RNN model.The performance validation of the HPOHDL-FND technique is tested using two Arabic datasets.The outcomes exemplified better performance over the other existing techniques with maximum accuracy of 96.57%and 93.53%on Covid19Fakes and satirical datasets,respectively.展开更多
This paper takes initial steps towards developing a theoretical framework of contemplative neuroaesthetics through sensorimotor dynamics.We first argue that this new area has been largely omitted from the contemporary...This paper takes initial steps towards developing a theoretical framework of contemplative neuroaesthetics through sensorimotor dynamics.We first argue that this new area has been largely omitted from the contemporary research agenda in neuroaesthetics and thus remains a domain of untapped potential.We seek to define this domain to foster a clear and focused investigation of the capacity of the arts and architecture to induce phenomenological states of a contemplative kind.By proposing a sensorimotor account of the experience of architecture,we operationalize how being attuned to architecture can lead to contemplative states.In contrasting the externally-induced methods with internally-induced methods for eliciting a contemplative state of mind,we argue that architecture may spontaneously and effortlessly lead to such states as certain built features naturally resonate with our sensorimotor system.We suggest that becoming sensible of the resonance and attunement process between internal and external states is what creates an occasion for an externallyinduced contemplative state.Finally,we review neuroscientific studies of architecture,elaborate on the brain regions involved in such aesthetic contemplative responses,provide architectural examples,and point at the contributions that this new area of inquiry may have in fields such as the evidence-based design movement in architecture.展开更多
Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance o...Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed.This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence.An annotated image dataset trains the proposed system and predicts the camera pose in real-time.The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera pose.It also recognizes the scene changes during the sequence and evaluates the effects of these changes.This system achieved high accuracy and real-time performance.The scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact evaluation.Overall,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.展开更多
Ionic liquids have negligibly low vapor pressure, high stability and polarity. They are regarded as green solvents. Enzymes, especially lipases, as well as whole-cell of microbe, are catalytically active in ionic liqu...Ionic liquids have negligibly low vapor pressure, high stability and polarity. They are regarded as green solvents. Enzymes, especially lipases, as well as whole-cell of microbe, are catalytically active in ionic liquids or aqueous-ionic liquid biphasic systems. Up to date, there have been many reports on enzyme-exhibited features and enzyme-mediated reactions in ionic liquids. In many cases, remarkable results with respect to yield, catalytic activity, stability and (enantio-, regio-) selectivity were obtained in ionic liquids in comparison with those observed in conventional media. Accordingly, ionic liquids provide new possibilities for the application of new type of solvent in biocatalytic reactions.展开更多
Background Proper parent-child interaction is crucial for child development, but an assessment tool in Chinese is currently lacking. This study aimed to develop and validate a parent-reported parent-child interaction ...Background Proper parent-child interaction is crucial for child development, but an assessment tool in Chinese is currently lacking. This study aimed to develop and validate a parent-reported parent-child interaction scale for Chinese preschool children. Methods The Chinese parent-child interaction scale (CPCIS) was designed by an expert panel based on the literature and clinical observations in the Chinese context. The initial CPCIS had 14 parent-child interactive activity items. Psychometric properties of the CPCIS were examined using the Rasch model and confirmatory factor analysis (CFA). Convergent validity was investigated by the associations between CPCIS and family income, maternal education level, and children's school readiness. Results The study recruited 567 Chinese parent-child pairs from diverse socioeconomic backgrounds, who completed the CPCIS. Six out of the 14 items in the initial CPCIS were dropped due to suboptimal fi t values. The refined 8-item CPCIS was shown to be valid and reliable by Rasch models and CFA. The person separation reliability and Cronbach's α of the CPCIS were 0.81 and 0.82, respectively. The CPCIS scores were positively associated with family's socioeconomic status (η2 = 0.05,P < 0.001), maternal education level (η2 = 0.08,P < 0.001), and children's school readiness (η2 = 0.01,P < 0.01). Conclusion CPCIS is an easily administered, valid, and reliable tool for the assessment of parent-child interactions in Chinese families.展开更多
Objective:This study protocol identifies the basic research route and framework of psychological and behavioral surveys among Chinese residents,aims establishing a database through a multicenter,large-sample cross-sec...Objective:This study protocol identifies the basic research route and framework of psychological and behavioral surveys among Chinese residents,aims establishing a database through a multicenter,large-sample cross-sectional survey in China to provide strong data support for research development in various fields and a more comprehensive and systematic understanding of the physical and mental health status of the public.Method:The study was conducted from June 20,2022 to August 31,2022,using stratified sampling and quota sampling methods,a total of 148 cities,202 districts and counties,390 townships/towns/sub-districts,and 780 communities/villages(excluding Hong Kong,Macao,and Taiwan)from 23 provinces,5 autonomous regions,and 4 municipalities directly under the central government in China were selected.The questionnaire was distributed one-on-one and face-to-face to the public by trained investigators,and the questionnaire included eight aspects:personal basic information,personal health status,family basic information,social environment in which they were located,psychological level scale,behavioral level scale,other scales,and attitude towards social hot issues.Data analysis will be performed after questionnaire return.Results:Data collection is ongoing.These findings will support physical and mental health research and strategy development in China and even globally,guiding policy-makers and health care organizations to reform their programs to ensure the best interests of residents and their families.展开更多
The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection.This is especially applicable in the case of elderly or disabled people who live sel...The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection.This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes.These sensors produce a huge volume of physical activity data that necessitates real-time recognition,especially during emergencies.Falling is one of the most important problems confronted by older people and people with movement disabilities.Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people.But,the costs incurred upon installation and operation are high,whereas the technology is relevant only for indoor environments.Currently,commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s movements.Against this background,the current study develops an Improved WhaleOptimizationwithDeep Learning-Enabled Fall Detection for Disabled People(IWODL-FDDP)model.The presented IWODL-FDDP model aims to identify the fall events to assist disabled people.The presented IWODLFDDP model applies an image filtering approach to pre-process the image.Besides,the EfficientNet-B0 model is utilized to generate valuable feature vector sets.Next,the Bidirectional Long Short Term Memory(BiLSTM)model is used for the recognition and classification of fall events.Finally,the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method,which shows the novelty of the work.The experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.展开更多
文摘AIM:To develop a novel 3-dimensional(3D) virtual hepatectomy simulation software,Liversim,to visualize the real-time deformation of the liver.METHODS:We developed a novel real-time virtual hepatectomy simulation software program called Liversim. The software provides 4 basic functions:viewing 3D models from arbitrary directions,changing the colors and opacities of the models,deforming the models based on user interaction,and incising the liver parenchyma and intrahepatic vessels based on user operations. From April 2010 through 2013,99 patients underwent virtual hepatectomies that used the conventional software program SYNAPSE VINCENT preoperatively. Between April 2012 and October 2013,11 patients received virtual hepatectomies using the novel software program Liversim; these hepatectomies were performed both preoperatively and at the same that the actual hepatectomy was performed in an operating room. The perioperative outcomes were analyzed between the patients for whom SYNAPSE VINCENT was used and those for whom Liversim wasused. Furthermore,medical students and surgical residents were asked to complete questionnaires regarding the new software.RESULTS:There were no obvious discrepancies(i.e.,the emergence of branches in the portal vein or hepatic vein or the depth and direction of the resection line) between our simulation and the actual surgery during the resection process. The median operating time was 304 min(range,110 to 846) in the VINCENT group and 397 min(range,232 to 497) in the Liversim group(P = 0.30). The median amount of intraoperative bleeding was 510 m L(range,18 to 5120) in the VINCENT group and 470 m L(range,130 to 1600) in the Liversim group(P = 0.44). The median postoperative stay was 12 d(range,6 to 100) in the VINCENT group and 13 d(range,9 to 21) in the Liversim group(P = 0.36). There were no significant differences in the preoperative outcomes between the two groups. Liversim was not found to be clinically inferior to SYNAPSE VINCENT. Both students and surgical residents reported that th
文摘Recent studies have revealed that bile acids(BAs)are not only facilitators of dietary lipid absorption but also important signaling molecules exerting multiple physiological functions.Some major signaling pathways involving the nuclear BAs receptor farnesoid X receptor and the G protein-coupled BAs receptor TGR5/M-BAR have been identified to be the targets of BAs.BAs regulate their own homeostasis via signaling pathways.BAs also affect diverse metabolic pathways including glucose metabolism,lipid metabolism and energy expenditure.This paper suggests the mechanism of controlling metabolism via BA signaling and demonstrates that BA signaling is an attractive therapeutic target of the metabolic syndrome.
文摘Nature is an information sourcebook of behaviour, function, colour and shape which can inspire visual design and invention. Studying the form and functional characteristics of a natural object can provide inspiration for product design and help to improve the marketability of manufactured products. The inspiration can be triggered either by direct observation or captured by three-dimensional （3D） digitising techniques to obtain superficial information （geometry and colour）. An art designer often creates a concept in the form of a two-dimensional （2D） sketch while engineering methods lead to a point cloud in 3D. Each has its limitations in that the art designer commonly lacks the knowledge to build a final product from a 2D sketch and the engi- neering designer＇s 3D point clouds may not be very beautiful. We propose a method for Product Design from Nature （PDN）, coupling aesthetic intent and geometrical characteristics, exploring the interactions between designers and nature＇s systems in PDN. We believe that this approach would considerably reduce the lead time and cost of product design from nature.
基金Supported by a Fogarty International Center Training Grant, No. 5 D43 TW00644
文摘AIM: To summarize the evidence available for the clinical effectiveness of insulin sensitizers in the treatment of nonalcoholic fatty liver disease (NAFLD) systematically. METHODS: Relevant articles were located using computer-assisted searches of Medline (1966-March 2006), EMBASE (1988-March 2006), CINAHL (1982-March 2003), Educational Resource Information Center (1966-March 2006), Library, Information Science & Technology Abstracts (1967-March 2006), Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects (1994-2006), dissertations in ProQuest and FirstSearch databases. Manual searches were made in the abstracts from meetings of the American Gastroenterological Association (1999-2006), and the American Association for the Study of Liver Diseases (2003-2005). Studies were retrieved using the following selection criteria: (1) clinical trials using insulin sensitizers in subjects with NAFLD, (2) adult patients, (3) published as full manuscripts or abstracts, and (4) English, Spanish, German, and French languages only. Data were abstracted independently by two reviewers following standardized procedures. A face-to- face comparison of data was conducted to ensure the completeness and reliability of the abstraction process. RESULTS: Nine studies were included, six using metformin and three using thiazolidinediones. Only two studies were placebo-controlled trials. The mediansample size for all studies was 18 subjects. In the placebo-controlled trials, metformin improved insulin resistance markers and liver function tests, but not histological scores. In the single-arm trials, metformin and thiazolidinediones improved insulin resistance markers and liver function tests, and beneficial histological changes were reported. There is limited high-quality information available from which to draw categorical conclusions about the clinical use of insulin sensitizers in NAFLD.CONCLUSION: Current information indicates that the use of insulin sensitizers in NAFLD improves insulin resistance and liver
文摘The intervention of behaviors, including physical activity (PA), has become a strategy for many hospitals dealing with patients with chronic diseases. Given the limited evidence available about PA and healthcare use with chronic diseases, this study explored the association between different levels of PA and annual hospital service use and expenditure for inpatients with coronary heart disease (CHD) in China. We analyzed PA information from the first follow-up survey (2013) of the Dongfeng-Tongji cohort study of 1460 CHD inpatients. We examined factors such as PA exercise volume and years of PA and their associations with the number of inpatient visits, number of hospital days, and inpatient costs and total medical costs. We found that the number of hospital days and the number of inpatient visits were negatively associated with intensity of PA level. Similarly, total inpatient and outpatient costs declined when the PA exercise volume levels increased. Furthermore, there were also significant associations between the number of hospital days, inpatient costs or total medical costs and levels of PA years. This study provides the first empirical evidence about the effects of the intensity and years of PA on hospital service use and expenditure of CHD in China. It suggests that the patients' PA, especially the vigorous PA, should be promoted widely to the public and patients in order to relieve the financial burden of CHD.
基金CHC’s Postgraduate Scholarship is partially supported by the HKU-SPACE Research FundThe graduate assistant positions of BS and YH are supported by Jiann-Ping Hsu College of Public Health,Georgia Southern University.
文摘Background:As internet and social media use have skyrocketed,epidemiologists have begun to use online data such as Google query data and Twitter trends to track the activity levels of influenza and other infectious diseases.In China,Weibo is an extremely popular microblogging site that is equivalent to Twitter.Capitalizing on the wealth of public opinion data contained in posts on Weibo,this study used Weibo as a measure of the Chinese people’s reactions to two different outbreaks:the 2012 Middle East Respiratory Syndrome Coronavirus(MERS-CoV)outbreak,and the 2013 outbreak of human infection of avian influenza A(H7N9)in China.Methods:Keyword searches were performed in Weibo data collected by The University of Hong Kong’s Weiboscope project.Baseline values were determined for each keyword and reaction values per million posts in the days after outbreak information was released to the public.Results:The results show that the Chinese people reacted significantly to both outbreaks online,where their social media reaction was two orders of magnitude stronger to the H7N9 influenza outbreak that happened in China than the MERS-CoV outbreak that was far away from China.Conclusions:These results demonstrate that social media could be a useful measure of public awareness and reaction to disease outbreak information released by health authorities.
基金This research was supported by Japan Science and Tech-nology Agency (JST) PRESTO[Grants nos.JPMJPR17O5(Yosuke'Toda) and JPMJPR17O3(Fumio Okura)].
文摘Deep learning with convolutional neural networks(CNNs)has achieved great success in the classification of various plant diseases.However,a limited number of studies have elucidated the process of inference,leaving it as an untouchable black box.Revealing the CNN to extract the learned feature as an interpretable form not only ensures its reliability but also enables the validation of the model authenticity and the training dataset by human intervention.In this study,a variety of neuron-wise and layer-wise visualization methods were applied using a CNN,trained with a publicly available plant disease image dataset.We showed that neural networks can capture the colors and textures of lesions specific to respective diseases upon diagnosis,which resembles human decision-making.While several visualizationmethods were used as they are,others had to be optimized to target a specific layer that fully captures the features to generate consequential outputs.Moreover,by interpreting the generated attention maps,we identified several layers that were not contributing to inference and removed such layers inside the network,decreasing the number of parameters by 75%without affecting the classification accuracy.The results provide an impetus for the CNN black box users in the field of plant science to better understand the diagnosis process and lead to further efficient use of deep learning for plant disease diagnosis.
基金co-supported by the Fundamental Research Funds for the Central Universities of China,China Postdoctoral Science Foundation(No.2018M631196)the National Natural Foundation of China(No.51705420).
文摘Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features,as well as its easy burying in the complex,non-stationary structural vibrations and strong background noises.In this paper,a method based on the flexible analytical wavelet transform(FAWT)possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings.During the route of the proposed method,the proper FAWT bases are constructed via genetic optimization algorithm(GA)based on maximizing the spectral correlated kurtosis(SCK)which is firstly presented and proved to be efficient and effective in indicating interested fault mode.Via using the customized FAWT bases for each interested fault mode,the original vibration measurements are decomposed into fine frequency subbands,and the sensitive subband which enhances the signal-to-noise ratio(SNR)is selected to exhibit the fault signature on its envelope spectrum.The proposed method is tested via simulated signals,and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace,inner-race and roller defects.The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.
基金supported by a grant from the National Research Foundation of Korea(NRF)funded by the Korean government,Ministry of Science and ICT(MSIT)(No.2021R1A6A3A01086766)。
文摘We investigate whether large language models can perform the creative hypothesis generation that human researchers regularly do.While the error rate is high,generative AI seems to be able to effectively structure vast amounts of scientific knowledge and provide interesting and testable hypotheses.The future scientific enterprise may include synergistic efforts with a swarm of“hypothesis machines”,challenged by automated experimentation and adversarial peer reviews.
文摘Mobile health applications, or mHealth apps, have gained popularity due to their practical functions and strengthening the connection between patients and healthcare professionals. These apps are designed for managing health and well-being on portable devices, allowing individuals to self-manage their health or healthcare practitioners to enhance patient care. Key features include personalized recommendations, data synchronization with other health devices, and connectivity with healthcare professionals. The research describes how mobile health applications support healthy behaviors, facilitate communication between patients and physicians, and empower individuals in the United States to take charge of their health. This study also examines how adults in the US use mobile health applications, or mHealth apps, on their tablets or smartphones for health-seeking purposes. The information was taken from Cycle 4 of the Health Information National Trends Survey (HINTS 4). The challenges regarding these mobile health apps have also been evaluated with possible remedies. Around 100 university students participated in a cross-sectional study by answering questions on their eating habits, physical activity, lifestyle choices related to health, and use of mobile health apps. The data was then analyzed and concluded as a result. Mobile health applications have brought about a significant shift in the way patients connect with their healthcare providers by providing them with convenient access to health services and information. By keeping track of health markers like diet, exercise, and medication compliance, patients may use these tools to help better manage their chronic conditions. Mobile health applications can improve patient outcomes and save healthcare costs by empowering patients to take charge of their health. Through the facilitation of communication between patients and healthcare professionals, mobile health apps also offer virtual consultations and remote monitoring.
基金supported by the National Research Foundation of Korea(NRF)funded by the Korean Government,Republic of Korea(Nos.2020R1A2C1012439,2020R1A4A1019227,and 2018R1A2B6002849)。
文摘Global environmental problems have been increasing with the growth of the world economy and have become a crucial issue.To replace fossil fuels,sustainable and eco-friendly catalysts are required for the removal of organic pollutants.In this study,nickel ferrite(NiFe_(2)O_(4))was prepared using a simple wet-chemical synthesis,followed by calcination;bismuth phosphate(BiPO_(4))was also prepared using a hydrothermal method.Further,NiFe_(2)O_(4)/BiPO_(4)nanocomposites were prepared using a hydrothermal technique.Numerous characterization studies,such as structural,morphology,surface area,optical,photoluminescence,and photoelectrochemical investigations,were used to analyze NiFe_(2)O_(4)/BiPO_(4)nanocomposites.The morphology analysis indicated a successful decoration of BiPO_(4)nanorods on the surface of Ni Fe_(2)O_(4)nanoplate.Further,the bandgap of the NiFe_(2)O_(4)/BiPO_(4)nanocomposites was modified owing to the formation of a heterostructure.The as-prepared NiFe_(2)O_(4)/BiPO_(4)nanocomposite exhibited promising properties to be used as a novel heterostructure for tetracycline(TC)and Rhodamine B(Rh B)removal.The NiFe_(2)O_(4)/BiPO_(4)nanocomposite degrades TC(98%)and Rh B(99%)pollutants upon solar-light irradiation within 100 and 60 min,respectively.Moreover,the trapping experiments confirmed the Z-scheme approach of the prepared nanocomposites.The efficient separation and transfer of photogenerated electron-hole pairs rendered by the heterostructure were confirmed by utilizing electrochemical impedance spectroscopy,photocurrent experiments,and photoluminescence.Mott–Schottky measurements were used determine the positions of the conduction and valence bands of the samples,and the detailed mechanism of photocatalytic degradation of toxic pollutants was projected and discussed.
基金supported by Hainan Provicinal Key Course Foundation of Medicinal Chemistry
文摘Objective:To study the chemical constituents in leaves of Cebera manghas.Methods:Chemical constituents were isolated by using various column chromatography and tho structures were elucidated on basis of physicochemical constants and spectral data analysis.Results:Nine compounds were obtained including p-hydroxybenzaldehyde(1),benzamide(2),n-hexadecane acid monoglyceride(3),loliolide(4),β-sitosterol(5),cerberin(6),neriifolin(7),cerleaside A(8), daucosterol(9).Conclusions:Compounds 1-4 are obtained from this genus for the first time.
文摘Bird fauna checklists are important tools in ecology, biology, and conservation planning for scientists, stakeholders, and decision-makers. Despite its small area, the Gaza Strip (365 km<sup>2</sup>) has a relatively large variety of resident and migratory bird fauna. Therefore, the current study aimed to provide an updated checklist of all bird fauna living in or inhabiting the Gaza Strip. Direct field observations using binoculars, continuous visits to zoos, pet stores and biology museums, discussion with bird hunters, follow-up of news and social networking sites, review of scientific publications and photography were the main tools to satisfy the purpose of the study. At least 250 bird species collected from different sources occur in the Gaza Strip and are included in the checklist. This list will not be static, but is inevitably subject to additions and changes in the face of times. The current 250 bird species of the Gaza Strip represent 45.4% of the 551 species of birds living in Palestine. The bird species were found to belong to 21 orders and 61 families. The Passeriformes (passerines) represented the largest order with 96 species of birds (38.4%), followed by the Charadriiformes 54 (21.6%), the Accipitriformes 18 (7.2%), Anseriformes 17 (6.8%) and Pelecaniformes 14 (5.6%), while the other orders represented the remaining percentage (20.4%). With regard to families, the Scolopacidae represented the largest family with 22 species of birds (8.8%), followed by the Anatidae and Accipitridae 17 for each (6.8%), the Muscicapidae 16 (6.4%) and Chariidridae and Fringillidae 11 for each (4.4%), while the other families represented the remaining percentage (62.4%). According to the IUCN regional threat categories, 226 species (90.4%) were Least Concern (LC), 12 (4.8%) were Near Threatened (NT), 6 (2.4%) were Vulnerable (VU), 4 (1.6%) were Endangered (EN) and 2 (0.8%) were Critically Endangered (CR). In conclusion, the study recommends a sustainable control of bird hunting and trafficking in addition to building p
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Small Groups Project under Grant Number(120/43)Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R281)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4331004DSR32).
文摘Nowadays,the usage of socialmedia platforms is rapidly increasing,and rumours or false information are also rising,especially among Arab nations.This false information is harmful to society and individuals.Blocking and detecting the spread of fake news in Arabic becomes critical.Several artificial intelligence(AI)methods,including contemporary transformer techniques,BERT,were used to detect fake news.Thus,fake news in Arabic is identified by utilizing AI approaches.This article develops a new hunterprey optimization with hybrid deep learning-based fake news detection(HPOHDL-FND)model on the Arabic corpus.The HPOHDL-FND technique undergoes extensive data pre-processing steps to transform the input data into a useful format.Besides,the HPOHDL-FND technique utilizes long-term memory with a recurrent neural network(LSTM-RNN)model for fake news detection and classification.Finally,hunter prey optimization(HPO)algorithm is exploited for optimal modification of the hyperparameters related to the LSTM-RNN model.The performance validation of the HPOHDL-FND technique is tested using two Arabic datasets.The outcomes exemplified better performance over the other existing techniques with maximum accuracy of 96.57%and 93.53%on Covid19Fakes and satirical datasets,respectively.
文摘This paper takes initial steps towards developing a theoretical framework of contemplative neuroaesthetics through sensorimotor dynamics.We first argue that this new area has been largely omitted from the contemporary research agenda in neuroaesthetics and thus remains a domain of untapped potential.We seek to define this domain to foster a clear and focused investigation of the capacity of the arts and architecture to induce phenomenological states of a contemplative kind.By proposing a sensorimotor account of the experience of architecture,we operationalize how being attuned to architecture can lead to contemplative states.In contrasting the externally-induced methods with internally-induced methods for eliciting a contemplative state of mind,we argue that architecture may spontaneously and effortlessly lead to such states as certain built features naturally resonate with our sensorimotor system.We suggest that becoming sensible of the resonance and attunement process between internal and external states is what creates an occasion for an externallyinduced contemplative state.Finally,we review neuroscientific studies of architecture,elaborate on the brain regions involved in such aesthetic contemplative responses,provide architectural examples,and point at the contributions that this new area of inquiry may have in fields such as the evidence-based design movement in architecture.
文摘Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed.This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence.An annotated image dataset trains the proposed system and predicts the camera pose in real-time.The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera pose.It also recognizes the scene changes during the sequence and evaluates the effects of these changes.This system achieved high accuracy and real-time performance.The scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact evaluation.Overall,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.
基金the Natural Science Foundation of Guangdong Province (No. 020839).
文摘Ionic liquids have negligibly low vapor pressure, high stability and polarity. They are regarded as green solvents. Enzymes, especially lipases, as well as whole-cell of microbe, are catalytically active in ionic liquids or aqueous-ionic liquid biphasic systems. Up to date, there have been many reports on enzyme-exhibited features and enzyme-mediated reactions in ionic liquids. In many cases, remarkable results with respect to yield, catalytic activity, stability and (enantio-, regio-) selectivity were obtained in ionic liquids in comparison with those observed in conventional media. Accordingly, ionic liquids provide new possibilities for the application of new type of solvent in biocatalytic reactions.
文摘Background Proper parent-child interaction is crucial for child development, but an assessment tool in Chinese is currently lacking. This study aimed to develop and validate a parent-reported parent-child interaction scale for Chinese preschool children. Methods The Chinese parent-child interaction scale (CPCIS) was designed by an expert panel based on the literature and clinical observations in the Chinese context. The initial CPCIS had 14 parent-child interactive activity items. Psychometric properties of the CPCIS were examined using the Rasch model and confirmatory factor analysis (CFA). Convergent validity was investigated by the associations between CPCIS and family income, maternal education level, and children's school readiness. Results The study recruited 567 Chinese parent-child pairs from diverse socioeconomic backgrounds, who completed the CPCIS. Six out of the 14 items in the initial CPCIS were dropped due to suboptimal fi t values. The refined 8-item CPCIS was shown to be valid and reliable by Rasch models and CFA. The person separation reliability and Cronbach's α of the CPCIS were 0.81 and 0.82, respectively. The CPCIS scores were positively associated with family's socioeconomic status (η2 = 0.05,P < 0.001), maternal education level (η2 = 0.08,P < 0.001), and children's school readiness (η2 = 0.01,P < 0.01). Conclusion CPCIS is an easily administered, valid, and reliable tool for the assessment of parent-child interactions in Chinese families.
文摘Objective:This study protocol identifies the basic research route and framework of psychological and behavioral surveys among Chinese residents,aims establishing a database through a multicenter,large-sample cross-sectional survey in China to provide strong data support for research development in various fields and a more comprehensive and systematic understanding of the physical and mental health status of the public.Method:The study was conducted from June 20,2022 to August 31,2022,using stratified sampling and quota sampling methods,a total of 148 cities,202 districts and counties,390 townships/towns/sub-districts,and 780 communities/villages(excluding Hong Kong,Macao,and Taiwan)from 23 provinces,5 autonomous regions,and 4 municipalities directly under the central government in China were selected.The questionnaire was distributed one-on-one and face-to-face to the public by trained investigators,and the questionnaire included eight aspects:personal basic information,personal health status,family basic information,social environment in which they were located,psychological level scale,behavioral level scale,other scales,and attitude towards social hot issues.Data analysis will be performed after questionnaire return.Results:Data collection is ongoing.These findings will support physical and mental health research and strategy development in China and even globally,guiding policy-makers and health care organizations to reform their programs to ensure the best interests of residents and their families.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups Project under grant number(158/43)Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R77)+1 种基金Princess Nourah bint Abdulrahman University,Riyadh,Saudi ArabiaThe authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4310373DSR52).
文摘The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection.This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes.These sensors produce a huge volume of physical activity data that necessitates real-time recognition,especially during emergencies.Falling is one of the most important problems confronted by older people and people with movement disabilities.Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people.But,the costs incurred upon installation and operation are high,whereas the technology is relevant only for indoor environments.Currently,commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s movements.Against this background,the current study develops an Improved WhaleOptimizationwithDeep Learning-Enabled Fall Detection for Disabled People(IWODL-FDDP)model.The presented IWODL-FDDP model aims to identify the fall events to assist disabled people.The presented IWODLFDDP model applies an image filtering approach to pre-process the image.Besides,the EfficientNet-B0 model is utilized to generate valuable feature vector sets.Next,the Bidirectional Long Short Term Memory(BiLSTM)model is used for the recognition and classification of fall events.Finally,the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method,which shows the novelty of the work.The experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.
