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关键词： 监管科学   计算机建模与仿真   虚拟临床试验  

摘要： 计算机建模与仿真在提升药物研发效能、创新监管科学发展中具有重要意义。本文首先从战略视角分析了计算机建模与仿真在全球主要国家和地区的监管科学发展中的战略地位,剖析了其在药物研发与监管科学发展中的战略意义。其次,本文以“科学界针对各种应用场景开发有价值的建模仿真科学工具,监管机构将有价值的科学工具转变为有价值的监管科学工具,并形成更多数字化证据的运行机制”为牵引,对近期全球的创新探索进行了分类总结。最后,为了推动我国计算机建模与仿真在监管科学、医药研发中深化应用,提出了面向未来的行动建议,即加快弥合跨学科思维方式差异,打造虚拟临床试验样板,建立中国的应用场景清单,促进有价值的科学工具转变为有价值的监管科学工具。

关键词： 水生动植物   配合饲料   套养   养殖产量   养殖池塘   养殖效益   生态效益   大宗淡水鱼  

摘要： 在目前传统的青鱼养殖池塘中主要套养品种为鲢、鳙、鲫等大宗淡水鱼,本试验引入太阳鱼进行套养。太阳鱼具有生长速度快、抗病力强、经济价值高等优点,且太阳鱼食性杂,既食浮游动物、又食小型水生动植物,同时也可摄食配合饲料,是1种较为理想的套养品种。通过全过程的太阳鱼套养试验,从养殖产量、养殖效益及生态效益等方面探讨了该模式的可行性,以期丰富本区域的青鱼主养模式。

关键词： Insanity defense   mental health   Pakistani law   capital punishment   Islamic law  

摘要： This Article analyzes the 2021 judgment of the Supreme Court of Pakistan in the case of Mst. Safia Bano v. Home Department, Government of Punjab. The case has garnered significant local and international attention due to the Court's ruling that a death sentence may not be carried out on a defendant who has a mental illness. Setting the case against the backdrop of Pakistan's Islamic and colonial contexts, this article argues that the Supreme Court has reshaped the insanity defense in Pakistani law by placing the determination of a defendant's mental state mainly in the hands of medical professionals. However, the Court's reliance on medical professionals and the subsequent downplaying of the "moral capacity" element of the insanity defense-a determination of law made by courts-has created an obstacle for courts to punish offenders more stringently in future cases due to the popular belief that mental health professionals are ill-equipped to answer broader questions of justice for victims and society. The article recommends that this issue can be remedied by establishing an objective legal test for insanity that considers Islamic law, Pakistani precedent, and advances in medical science.

关键词： capital punishment   death penalty   court of law   public opinion   social justice  

摘要： This study tested the hypothesis that presenting people with information about wrongful convictions that are considered an unacceptable cost of administering justice lowers support for the death penalty. We recruited 815 participants using an online crowdsourcing service in Japan, randomly assigned them to eight groups with varying combinations of presence or absence of information emphasizing losses caused by wrongful convictions and asked them to answer questions on the death penalty. Results of the preregistration experiment showed no effect of loss emphasis, but the groups provided with information on wrongful conviction rates were less likely to support the death penalty than those with no information;the higher the wrongful conviction rate, the lower was the support. This study's findings, which replicated a previous study's findings with non-U.S. participants, support the acceptability hypothesis and confirm the institutional and cultural universality of the effect of wrongful conviction information on public attitude toward capital punishment.

关键词： data analysis   person-centered approaches   quantitative   race   ethnicity   undergraduate   underrepresented students  

摘要： BackgroundThere have been calls to shift how engineering education researchers investigate the experiences of engineering students from racially minoritized groups. These conversations have primarily involved qualitative researchers, but an echo of equal magnitude from quantitative inquiry has been largely absent. PurposeThis paper examines the data analysis practices used in quantitative engineering education research related to broadening participation. We highlight practical issues and promising practices focused on "racial difference" during analysis. Scope/MethodWe conducted a systematic literature review of methods employed by quantitative studies related to Black students participating in engineering and computer science at the undergraduate level. Person-centered analyses and variable-centered analyses, coined by Jack Block, were used as our categorization framework, backdropped with the principles of QuantCrit. ResultsForty-nine studies qualified for review. Although each article involved some variable-centered analysis, we found strategies authors used that aligned and did not align with person-centered analyses, including forming groups based on participant attitudes and using race as a variable, respectively. We highlight person-centered approaches as a tangible step for authors to engage meaningfully with QuantCrit in their data analysis decision-making. ConclusionsOur findings highlight four areas of consideration for advancing quantitative data analysis in engineering education: operationalizing race and racism, sample sizes and data binning, claims with race as a variable, and promoting descriptive studies. We contend that engaging in deeper thought with these four areas in quantitative inquiry can help researchers engage with the difficult choices inherent to quantitative analyses.

关键词： Electronic mail   Additives   Standards   Recurrent neural networks   Long short term memory   Computer science   Text categorization   Aggregation functions   Choquet integral   LSTM   recurrent neural networks (RNNs)   vector Choquet integral (VCI)  

摘要： Choquet integral is a widely used aggregation operator on 1-D and interval-valued information, since it is able to take into account the possible interaction among data. However, there are many cases where the information taken into account is vectorial, such as long short-term memories (LSTM). LSTM units are a kind of recurrent neural networks that have become one of the most powerful tools to deal with sequential information since they have the power of controlling the information flow. In this article, we first generalize the standard Choquet integral to admit an input composed by n-dimensional vectors, which produces an n-dimensional vector output. We study several properties and construction methods of vector Choquet integrals (VCIs). Then, we use this integral in the place of the summation operator, introducing in this way the new VCI-LSTM architecture. Finally, we use the proposed VCI-LSTM to deal with two problems: 1) sequential image classification;2) text classification.

摘要： The words "Programming is the second literacy" were coined more than 40 years ago [13], but never came to life. The paper develops and details that old slogan by proposing that the mainstream mathematics education in schools should merge with education in computer science/programming. Of course, this means a deep structural reform of school mathematics education. We are not talking about adapting the 20th century mathematics to the 21st century-as it outlined in [10, 19], we mean the 21st century mathematics education for the 21st century mathematics. To the best of our knowledge, this paper is perhaps the first known attempt to start a proper feasibility study for this reform. The scope of the paper does not allow us to touch the delicate socio-political (and financial) sides of the reform, we are looking only at general curricular and didactic aspects and possible directions of the reform. In particular, we indicate approaches to development of a Domain Specifiic Language (DSL) as a basis for all programming aspects of a new course.

关键词： Big Data   Data models   Unsolicited e-mail   Smoothing methods   Context modeling   Computer science   Computational modeling   Big data   e-commerce   review spammer detection   spam reviews  

摘要： The growing consumerism has led to the importance of online reviews on the Internet. Opinions voiced by these reviews are taken into consideration by many consumers for making financial decisions online. This has led to the development of opinion spamming for profitable motives or otherwise. This work has been done to tackle the challenge of identifying such spammers, but the scale of the real-world review systems demands this problem to be tackled as a big data challenge. So, an effort has been made to detect online review spammers using the principle of big data. In this article, a rating-based model has been studied under the light of large-scale datasets (more than 80 million reviews by 20 million reviewers) using the Hadoop and Spark frameworks. Scale effects have been identified and mitigated to provide better context to large review systems. An improved computational framework has been presented to compute the overall spamcity of reviewers using exponential smoothing. The value of the smoothing factor was set empirically. Finally, future directions have been discussed.

关键词： natural product   machine learning   intractable disease  

摘要： Computational approaches to drug development are rapidly growing in popularity and have been used to produce significant results. Recent developments in information science have expanded databases and chemical informatics knowledge relating to natural products. Natural products have long been well-studied, and a large number of unique structures and remarkable active substances have been reported. Analyzing accumulated natural product knowledge using emerging computational science techniques is expected to yield more new discoveries. In this article, we discuss the current state of natural product research using machine learning. The basic concepts and frameworks of machine learning are summarized. Natural product research that utilizes machine learning is described in terms of the exploration of active compounds, automatic compound design, and application to spectral data. In addition, efforts to develop drugs for intractable diseases will be addressed. Lastly, we discuss key considerations for applying machine learning in this field. This paper aims to promote progress in natural product research by presenting the current state of computational science and chemoinformatics approaches in terms of its applications, strengths, limitations, and implications for the field.