BACKGROUND Desmoid tumors(DT) are locally advanced but histologically benign monoclonal neoplasms that can occur from any musculoaponeurotic structure. The aim of this report is to analyze a rare clinical case of an a...BACKGROUND Desmoid tumors(DT) are locally advanced but histologically benign monoclonal neoplasms that can occur from any musculoaponeurotic structure. The aim of this report is to analyze a rare clinical case of an aggressive intra-abdominal DT successfully treated with sorafenib.CASE SUMMARY A 36-year-old man presented with increasing colicky abdominal pain and a selfpalpable mass in his left abdomen. Fourteen years earlier he was diagnosed with a large intra-abdominal tumor, which adhered to the left colonic flexure, part of the major gastric curvature and the spleen. Subsequent exploratory laparotomy revealed a voluminous mass in the epigastrium, arising from the posterior surface of the stomach and invading the superior mesenteric vessels, transverse mesocolon and the small bowel mesentery. As the tumor was unresectable, a jejunojejunal bypass was performed. Traditional therapeutic interventions proved insufficient, and the patient was started on sorafenib with a subsequent fulldisease response.CONCLUSIONDT's pathogenesis has been associated with mutations in the adenomatous polyposis coli(APC) gene or beta-catenin gene CTNNB1, sex steroids or previous surgical trauma. Local treatment modalities, such as surgery or radiotherapy, are implemented in aggressively progressing or symptomatic patients. Sorafenib is a hopeful therapeutic option against DTs, while several pharmacological agents have been successfully used.展开更多
The problems of online pricing with offline data,among other similar online decision making with offline data problems,aim at designing and evaluating online pricing policies in presence of a certain amount of existin...The problems of online pricing with offline data,among other similar online decision making with offline data problems,aim at designing and evaluating online pricing policies in presence of a certain amount of existing offline data.To evaluate pricing policies when offline data are available,the decision maker can either position herself at the time point when the offline data are already observed and viewed as deterministic,or at the time point when the offline data are not yet generated and viewed as stochastic.We write a framework to discuss how and why these two different positions are relevant to online policy evaluations,from a worst-case perspective and from a Bayesian perspective.We then use a simple online pricing setting with offline data to illustrate the constructions of optimal policies for these two approaches and discuss their differences,especially whether we can decompose the searching for the optimal policy into independent subproblems and optimize separately,and whether there exists a deterministic optimal policy.展开更多
Both unit and integration testing are incredibly crucial for almost any software application because each of them operates a distinct process to examine the product.Due to resource constraints,when software is subject...Both unit and integration testing are incredibly crucial for almost any software application because each of them operates a distinct process to examine the product.Due to resource constraints,when software is subjected to modifications,the drastic increase in the count of test cases forces the testers to opt for a test optimization strategy.One such strategy is test case prioritization(TCP).Existing works have propounded various methodologies that re-order the system-level test cases intending to boost either the fault detection capabilities or the coverage efficacy at the earliest.Nonetheless,singularity in objective functions and the lack of dissimilitude among the re-ordered test sequences have degraded the cogency of their approaches.Considering such gaps and scenarios when the meteoric and continuous updations in the software make the intensive unit and integration testing process more fragile,this study has introduced a memetics-inspired methodology for TCP.The proposed structure is first embedded with diverse parameters,and then traditional steps of the shuffled-frog-leaping approach(SFLA)are followed to prioritize the test cases at unit and integration levels.On 5 standard test functions,a comparative analysis is conducted between the established algorithms and the proposed approach,where the latter enhances the coverage rate and fault detection of re-ordered test sets.Investigation results related to the mean average percentage of fault detection(APFD)confirmed that the proposed approach exceeds the memetic,basic multi-walk,PSO,and optimized multi-walk by 21.7%,13.99%,12.24%,and 11.51%,respectively.展开更多
Background Leprosy is an infectious disease caused by Mycobacterium leprae and remains a source of preventable disability if left undetected.Case detection delay is an important epidemiological indicator for progress ...Background Leprosy is an infectious disease caused by Mycobacterium leprae and remains a source of preventable disability if left undetected.Case detection delay is an important epidemiological indicator for progress in interrupting transmission and preventing disability in a community.However,no standard method exists to effectively analyse and interpret this type of data.In this study,we aim to evaluate the characteristics of leprosy case detection delay data and select an appropriate model for the variability of detection delays based on the best fitting distribution type.Methods Two sets of leprosy case detection delay data were evaluated:a cohort of 181 patients from the post exposure prophylaxis for leprosy(PEP4LEP)study in high endemic districts of Ethiopia,Mozambique,and Tanzania;and self-reported delays from 87 individuals in 8 low endemic countries collected as part of a systematic literature review.Bayesian models were fit to each dataset to assess which probability distribution(log-normal,gamma or Weibull)best describes variation in observed case detection delays using leave-one-out cross-validation,and to estimate the effects of individual factors.Results For both datasets,detection delays were best described with a log-normal distribution combined with covariates age,sex and leprosy subtype[expected log predictive density(ELPD)for the joint model:-1123.9].Patients with multibacillary(MB)leprosy experienced longer delays compared to paucibacillary(PB)leprosy,with a relative difference of 1.57[95%Bayesian credible interval(BCI):1.14-2.15].Those in the PEP4LEP cohort had 1.51(95%BCI:1.08-2.13)times longer case detection delay compared to the self-reported patient delays in the systematic review.Conclusions The log-normal model presented here could be used to compare leprosy case detection delay datasets,including PEP4LEP where the primary outcome measure is reduction in case detection delay.We recommend the application of this modelling approach to test different probability distributions and covariate展开更多
In this paper,we present a family of gradient projection method with arbitrary initialpoint.The formula of search direction in the method is unitary.The convergent conditions ofthe method are given.When the initial po...In this paper,we present a family of gradient projection method with arbitrary initialpoint.The formula of search direction in the method is unitary.The convergent conditions ofthe method are given.When the initial point is feasible,the family of the method contains severalknown algorithms.When the initial point is infeasible,the method is exactly that given in[6].Finally,we give a new method which has global convergence property.展开更多
文摘BACKGROUND Desmoid tumors(DT) are locally advanced but histologically benign monoclonal neoplasms that can occur from any musculoaponeurotic structure. The aim of this report is to analyze a rare clinical case of an aggressive intra-abdominal DT successfully treated with sorafenib.CASE SUMMARY A 36-year-old man presented with increasing colicky abdominal pain and a selfpalpable mass in his left abdomen. Fourteen years earlier he was diagnosed with a large intra-abdominal tumor, which adhered to the left colonic flexure, part of the major gastric curvature and the spleen. Subsequent exploratory laparotomy revealed a voluminous mass in the epigastrium, arising from the posterior surface of the stomach and invading the superior mesenteric vessels, transverse mesocolon and the small bowel mesentery. As the tumor was unresectable, a jejunojejunal bypass was performed. Traditional therapeutic interventions proved insufficient, and the patient was started on sorafenib with a subsequent fulldisease response.CONCLUSIONDT's pathogenesis has been associated with mutations in the adenomatous polyposis coli(APC) gene or beta-catenin gene CTNNB1, sex steroids or previous surgical trauma. Local treatment modalities, such as surgery or radiotherapy, are implemented in aggressively progressing or symptomatic patients. Sorafenib is a hopeful therapeutic option against DTs, while several pharmacological agents have been successfully used.
文摘The problems of online pricing with offline data,among other similar online decision making with offline data problems,aim at designing and evaluating online pricing policies in presence of a certain amount of existing offline data.To evaluate pricing policies when offline data are available,the decision maker can either position herself at the time point when the offline data are already observed and viewed as deterministic,or at the time point when the offline data are not yet generated and viewed as stochastic.We write a framework to discuss how and why these two different positions are relevant to online policy evaluations,from a worst-case perspective and from a Bayesian perspective.We then use a simple online pricing setting with offline data to illustrate the constructions of optimal policies for these two approaches and discuss their differences,especially whether we can decompose the searching for the optimal policy into independent subproblems and optimize separately,and whether there exists a deterministic optimal policy.
文摘Both unit and integration testing are incredibly crucial for almost any software application because each of them operates a distinct process to examine the product.Due to resource constraints,when software is subjected to modifications,the drastic increase in the count of test cases forces the testers to opt for a test optimization strategy.One such strategy is test case prioritization(TCP).Existing works have propounded various methodologies that re-order the system-level test cases intending to boost either the fault detection capabilities or the coverage efficacy at the earliest.Nonetheless,singularity in objective functions and the lack of dissimilitude among the re-ordered test sequences have degraded the cogency of their approaches.Considering such gaps and scenarios when the meteoric and continuous updations in the software make the intensive unit and integration testing process more fragile,this study has introduced a memetics-inspired methodology for TCP.The proposed structure is first embedded with diverse parameters,and then traditional steps of the shuffled-frog-leaping approach(SFLA)are followed to prioritize the test cases at unit and integration levels.On 5 standard test functions,a comparative analysis is conducted between the established algorithms and the proposed approach,where the latter enhances the coverage rate and fault detection of re-ordered test sets.Investigation results related to the mean average percentage of fault detection(APFD)confirmed that the proposed approach exceeds the memetic,basic multi-walk,PSO,and optimized multi-walk by 21.7%,13.99%,12.24%,and 11.51%,respectively.
基金the European Union awarded to NLR/LM(grant number RIA2017NIM-1839-PEP-4LEP),and the Leprosy Research Initiative(LRIwww.lepro syres earch.org)awarded to NLR/LM(grant number 707.19.58.).
文摘Background Leprosy is an infectious disease caused by Mycobacterium leprae and remains a source of preventable disability if left undetected.Case detection delay is an important epidemiological indicator for progress in interrupting transmission and preventing disability in a community.However,no standard method exists to effectively analyse and interpret this type of data.In this study,we aim to evaluate the characteristics of leprosy case detection delay data and select an appropriate model for the variability of detection delays based on the best fitting distribution type.Methods Two sets of leprosy case detection delay data were evaluated:a cohort of 181 patients from the post exposure prophylaxis for leprosy(PEP4LEP)study in high endemic districts of Ethiopia,Mozambique,and Tanzania;and self-reported delays from 87 individuals in 8 low endemic countries collected as part of a systematic literature review.Bayesian models were fit to each dataset to assess which probability distribution(log-normal,gamma or Weibull)best describes variation in observed case detection delays using leave-one-out cross-validation,and to estimate the effects of individual factors.Results For both datasets,detection delays were best described with a log-normal distribution combined with covariates age,sex and leprosy subtype[expected log predictive density(ELPD)for the joint model:-1123.9].Patients with multibacillary(MB)leprosy experienced longer delays compared to paucibacillary(PB)leprosy,with a relative difference of 1.57[95%Bayesian credible interval(BCI):1.14-2.15].Those in the PEP4LEP cohort had 1.51(95%BCI:1.08-2.13)times longer case detection delay compared to the self-reported patient delays in the systematic review.Conclusions The log-normal model presented here could be used to compare leprosy case detection delay datasets,including PEP4LEP where the primary outcome measure is reduction in case detection delay.We recommend the application of this modelling approach to test different probability distributions and covariate
基金Project supported by the National Natural Science Foundation of China
文摘In this paper,we present a family of gradient projection method with arbitrary initialpoint.The formula of search direction in the method is unitary.The convergent conditions ofthe method are given.When the initial point is feasible,the family of the method contains severalknown algorithms.When the initial point is infeasible,the method is exactly that given in[6].Finally,we give a new method which has global convergence property.
