Solving multiple-criteria R&D project selection problems with a data-driven evidential reasoning rule

In this paper, a likelihood based evidence acquisition approach is proposed to acquire evidence from experts'assessments as recorded in historical datasets. Then a data-driven evidential reasoning rule based model is introduced to R&D project selection process by combining multiple pieces of evidence with different weights and reliabilities. As a result, the total belief degrees and the overall performance can be generated for ranking and selecting projects. Finally, a case study on the R&D project selection for the National Science Foundation of China is conducted to show the effectiveness of the proposed model. The data-driven evidential reasoning rule based model for project evaluation and selection (1) utilizes experimental data to represent experts' assessments by using belief distributions over the set of final funding outcomes, and through this historic statistics it helps experts and applicants to understand the funding probability to a given assessment grade, (2) implies the mapping relationships between the evaluation grades and the final funding outcomes by using historical data, and (3) provides a way to make fair decisions by taking experts' reliabilities into account. In the data-driven evidential reasoning rule based model, experts play different roles in accordance with their reliabilities which are determined by their previous review track records, and the selection process is made interpretable and fairer. The newly proposed model reduces the time-consuming panel review work for both managers and experts, and significantly improves the efficiency and quality of project selection process. Although the model is demonstrated for project selection in the NSFC, it can be generalized to other funding agencies or industries.Comment: 20 pages, forthcoming in International Journal of Project Management (2019

A TIME SERIOUS ANALYSIS OF THE DYNAMIC INFLUENCE OF FEMALE'S MENSTRUAL CYCLE TO SPORT PERFORMANCE

This research uses Cross Correlation Function, C.C.F., as a dynamic relationship evaluation model to study the dynamic influences of the menstrual cycle on sport performances. This research takes females with a regular menstrual cycle to be the test subjects. Their basic body temperatures were recorded every day. A Kistler Quattro Jump force plate was used to record continuously for sixty days the parameters of muscular strength, jump performance, and fatigue index during the subjects performance of a counter-movement Jump (CMJ), squat Jump (SJ), and thirty-second continuous bent leg jumps (CJB). The late stage of the follicular phase and the early stage of the luteal phase have a positive influence on sport performance. This also illustrates that sport performance for female athletes will be varied dynamically in accordance with the time of menstrual cycle

LLM for Test Script Generation and Migration: Challenges, Capabilities, and Opportunities

This paper investigates the application of large language models (LLM) in the domain of mobile application test script generation. Test script generation is a vital component of software testing, enabling efficient and reliable automation of repetitive test tasks. However, existing generation approaches often encounter limitations, such as difficulties in accurately capturing and reproducing test scripts across diverse devices, platforms, and applications. These challenges arise due to differences in screen sizes, input modalities, platform behaviors, API inconsistencies, and application architectures. Overcoming these limitations is crucial for achieving robust and comprehensive test automation. By leveraging the capabilities of LLMs, we aim to address these challenges and explore its potential as a versatile tool for test automation. We investigate how well LLMs can adapt to diverse devices and systems while accurately capturing and generating test scripts. Additionally, we evaluate its cross-platform generation capabilities by assessing its ability to handle operating system variations and platform-specific behaviors. Furthermore, we explore the application of LLMs in cross-app migration, where it generates test scripts across different applications and software environments based on existing scripts. Throughout the investigation, we analyze its adaptability to various user interfaces, app architectures, and interaction patterns, ensuring accurate script generation and compatibility. The findings of this research contribute to the understanding of LLMs' capabilities in test automation. Ultimately, this research aims to enhance software testing practices, empowering app developers to achieve higher levels of software quality and development efficiency.Comment: Accepted by the 23rd IEEE International Conference on Software Quality, Reliability, and Security (QRS 2023

Examining Low-Income Single-Mother Families’ Experiences with Family Benefit Packages during and after the Great Recession in the United States

The recent economic recession triggered by the global pandemic has renewed scholarly interest in the role of social welfare systems in supporting economically vulnerable families when they experience employment instability. This article unpacks the patterns of the cash and in-kind components of the monthly family benefit packages that US low-income single mothers accessed during and after the Great Recession. We used the 2008 Survey of Income and Program Participation and an innovative analytic procedure involving family benefit package plots, group-based trajectory modeling, and logistic regression modeling. We found that low-income single mothers more often used in-kind basic-needs packages and less often used packages that bundle a cash benefit or a childcare subsidy, regardless of their dynamic employment status. Our findings challenge the effectiveness of the US work-based welfare system in ensuring the economic security of economically vulnerable families and contribute to the policy discussions on unconditional basic income and President Biden’s American Families Plan.Ope

Distribution patterns of small-molecule ligands in the protein universe and implications for origin of life and drug discovery

Ligand-protein mapping was found to follow a power law and the preferential attachment principle, leading to the identification of the molecules, mostly nucleotide-containing compounds, that are likely to have evolved earliest

Three lanthanide complexes with mixed salicylate and 1,10-phenanthroline: syntheses, crystal structures, and luminescent/magnetic properties

Three new lanthanide complexes incorporating salicylate (HSA or SA) and 1,10-phenanthroline (phen), Ln(3)(HSA)(5)(SA)(2)(phen)(3) [Ln=Ho (1) and Er (2)], and Sm-2(HSA)(2)(SA)(2)(phen)(3) (3), have been synthesized. X-ray structural analysis reveals that 1 and 2 are isostructural with a trinuclear pattern, and 3 exhibits a binuclear structure. Comparison of the structural differences between 1/2 and 3 suggests that the identity of metal plays an important role in construction of such complexes. The magnetic properties of 1 are discussed. Moreover, 2 and 3 are both photoluminescent materials, and their emission properties are closely related to their corresponding Ln(III) centers

Screening, identification and degrading gene assignment of a chrysene-degrading strain

A predominant chrysene-degrading strain named CT was isolated from the activated sludge of Zhenjiang coking plant. The strain was initially identified as Paracoccus aminovorans by the results of morphological observation, physio-biochemical test and 16S rDNA gene sequence analysis. Under the conditions of initial chrysene concentration of 40 mg/l, inoculation amount of 10% (V/V) at pH 7.0 and temperature of 35°C, the degradation efficiency of chrysene by the strain CT reached 85.2% within 8 days. Alkaline lysis was applied to the extract plasmids from strain CT to confirm the location of chrysene-degrading genes. A plasmid, greater than 15 kb, was detected. The transformants obtained the ability to degrade chrysene when the plasmid of strain CT was transformed to competent cell of Escherichia coli DH10B, and could remove 43% of chrysene in the solutions with concentration of 30 mg/l within 8 days. But the mutation lost the ability to degrade chrysene when its plasmid was eliminated by sodium dodecyl sulfonate (SDS) and high temperature. This indicated that the plasmid of strain CT carried chrysene-degrading genes.Key words: Chrysene, degrading strain, Paracoccus, degrading gene,  plasmid

Duration of untreated bipolar disorder: A multicenter study

Little is known about the demographic and clinical differences between short and long duration of untreated bipolar disorder (DUB) in Chinese patients. This study examined the demographic and clinical features of short (≤2 years) and long DUB (\u3e2 years) in China. A consecutively recruited sample of 555 patients with bipolar disorder (BD) was examined in 7 psychiatric hospitals and general hospital psychiatric units across China. Patients’ demographic and clinical characteristics were collected using a standardized protocol and data collection procedure. The mean DUB was 3.2 ± 6.0 years; long DUB accounted for 31.0% of the sample. Multivariate analyses revealed that longer duration of illness, diagnosis of BD type II, and earlier misdiagnosis of BD for major depressive disorder or schizophrenia were independently associated with long DUB. The mean DUB in Chinese BD patients was shorter than the reported figures from Western countries. The long-term impact of DUB on the outcome of BD is warranted