Body Morph: Feasibility Testing of an Interactive CD-ROM to Teach Young Adolescents about Puberty

The aim of this pilot study was to examine the feasibility of an interactive computer program among 34 sixth and seventh grade children and to assess the potential for knowledge acquisition about puberty. Based on a developmental self-esteem approach to teach children about their bodies, the Body Morph program was designed to maximize the educational experience by: (1) tailoring puberty information to boys or girls, and (2) creating a confidential experience. Preliminary results indicated that students significantly improved their knowledge about puberty after using the program. Satisfaction among boys and girls for this type of educational approach suggests that it is a compelling format from which to learn about puberty.This research project was funded with the support of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) 1R43DK061269-01A2 to develop an educational computer program to improve body image in middle schoolers.     

论我国农民土地财产权益的保护

目前,农民土地财产权益在土地调整、土地流转、国家征用土地、农业企业化经营、城乡建设用地等过程中,都不同程度地受到侵害。文章认为,只有不断完善农民土地财产权益的保护,才能增加农民收入,繁荣农村经济,建设现代农业。具体措施有:坚持和完善农村土地集体所有制;规范和完善农民土地承包权流转;完善农民土地交易市场;依法保护农民土地财产权益;建立农民权益保护组织。     

政府公共危机处置的阶段划分与管理对策

公共危机管理是现代政府亟待加强的重要职能之一,为了提高政府公共危机的管理能力, 应当科学认识政府危机管理的全过程,正确处置危机管理程序。政府危机管理依据工作重点的不同可 分为储备、预警、控制和恢复四大阶段,针对政府危机处置的程序,可以从十个方面加强管理。     

农村文化建设刍议

有中国特色的农村文化建设,是有中国特色的社会主义建设的重要组成部分。文化所体现的是国家综合国力的强弱,是一种民族精神。而“三农”问题又是事关现代化建设进程的重点和难点。基于文化所特有的引导作用,作者从农村文化建设的主要特征、构成要素和基本内容着笔,着重探讨了加强农村文化建设的几个值得思考的问题。     

越南生物多样性保护问题与启示

从长期战争泥潭中解脱出来、在世界经济体系中处于边缘地位的越南,由于缺乏资金和技术,为了尽快摆脱贫困,接纳了发达国家和新兴经济体转移的夕阳产业.由于过度开发自然资源,结果造成环境污染,生物多样性减少.近年来越南的环境保护取得一定成效,但是如何处理好经济发展与环境保护的关系仍将是越南政府的一项长期课题.     

应当重视对中国外交的哲学研究

“冷战”后国际形势发生了重大变化,中国外交既面临机遇也面临挑战,有许多问题需要从哲学上认真研究。这些问题包括中国外交的时代观、全球发展观、价值观、主体观、方法论、思维观、人权观和前进观等。作为泱泱大国,中国应当特别重视对外交哲学的研究。     

Evaluation and classification of fentanyl-related compounds using EC-SERS and machine learning

Multiple analytical techniques for the screening of fentanyl-related compounds exist. High discriminatory methods such as GC–MS and LC–MS are expensive, time-consuming, and less amenable to onsite analysis. Raman spectroscopy provides a rapid, inexpensive alternative. Raman variants such as electrochemical surface-enhanced Raman scattering (EC-SERS) can provide signal enhancements with 10¹⁰ magnitudes, allowing for the detection of low-concentration analytes, otherwise undetected using conventional Raman. Library search algorithms embedded in instruments utilizing SERS may suffer from accuracy when multicomponent mixtures involving fentanyl derivatives are analyzed. The complexing of machine learning techniques to Raman spectra demonstrates an improvement in the discrimination of drugs even when present in multicomponent mixtures of various ratios. Additionally, these algorithms are capable of identifying spectral features difficult to detect by manual comparisons. Therefore, the goal of this study was to evaluate fentanyl-related compounds and other drugs of abuse using EC-SERS and to process the acquired data using machine learning—convolutional neural networks (CNN). The CNN was created using Keras v 2.4.0 with Tensorflow v 2.9.1 backend. In-house binary mixtures and authentic adjudicated case samples were used to evaluate the created machine-learning models. The overall accuracy of the model was 98.4 ± 0.1% after 10-fold cross-validation. The correct identification for the in-house binary mixtures was 92%, while the authentic case samples were 85%. The high accuracies achieved in this study demonstrate the advantage of using machine learning to process spectral data when screening seized drug materials comprised of multiple components.     

Capturing high-resolution digital images for use in forensic document examination

In the past, pattern disciplines within forensic science have periodically faced criticism due to their subjective and qualitative nature and the perceived absence of research evaluating and supporting the foundations of their practices. Recently, however, forensic scientists and researchers in the field of pattern evidence analysis have developed and published approaches that are more quantitative, objective, and data driven. This effort includes automation, algorithms, and measurement sciences, with the end goal of enabling conclusions to be informed by quantitative models. Before employing these tools, forensic evidence must be digitized in a way that adequately balances high-quality detail and content capture with minimal background noise imparted by the selected technique. While the current work describes the process of optimizing a method to digitize physical documentary evidence for use in semi-automated trash mark examinations, it could be applied to assist other disciplines where the digitization of physical items of evidence is prevalent. For trash mark examinations specifically, it was found that high-resolution photography provided optimal digital versions of evidentiary items when compared to high-resolution scanning.     

Additional predictions for forensic DNA phenotyping of externally visible characteristics using the ForenSeq and Imagen kits

Multiplex DNA typing methods using massively parallel sequencing can be used to predict externally visible characteristics (EVCs) in forensic DNA phenotyping through the analysis of single-nucleotide polymorphisms. The focus of EVC determination has focused on hair color, eye color, and skin tone as well as visible biogeographical ancestry features. In this study, we researched off-label applications beyond what is currently marketed by the manufacturer of the Verogen ForenSeq kit primer set B and Imagen primer set E SNP loci. We investigated additional EVC predictions by examining published genome wide sequencing studies and reported allele-specific gene expression and predictive values. We have identified 15 SNPs included in the ForenSeq kit panel and Imagen kits that have additional EVC prediction capabilities beyond what is published in the Verogen manuals. The additional EVCs that can be predicted include hair graying, ephelides hyperpigmented spots, dermatoheliosis, facial pigmented spots, standing height, pattern balding, helix-rolling ear morphology, hair shape, hair thickness, facial morphology, eyebrow thickness, sarcoidosis, obesity, vitiligo, and tanning propensity. The loci can be used to augment and refine phenotype predictions with software such as MetaHuman for missing persons, cold case, and historic case investigations.     

Lipophilicity of fentalogs: Comparison of experimental and computationally derived data

Although fentanyl and a small number of derivatives used for medical or veterinary procedures are well characterized, physiochemical properties have not been determined for many of the newer fentanyl analogs. Partition coefficients (Log P) were determined for 19 fentalogs using the shake-flask method and liquid chromatography–tandem mass spectrometry (LC–MS/MS). Experimentally determined partition coefficients were compared with computationally derived data using six independent software sources (ACD/LogP, LogKOWWIN v 1.69, miLogP 2.2, OsirisP, XLOGP 3.0, ALogPS 2.1). Fentalogs with a wide variety of structural modifications were intentionally selected, yielding Log P values ranging from 1.21 to 4.90. Comparison of experimental and computationally derived Log P values were highly correlated (R² 0.854–0.967). Overall, substructure-based modeling using fragmental methods or property-based topological approaches aligned more closely with experimentally determined Log P values. LC–MS/MS was also used to estimate pK_a values for fentalogs with no previously reported data. Lipophilicity and pK_a are important considerations for analytical detection and toxicological interpretation. In silico methods allow the determination of physicochemical information prior to certified reference materials being readily available for in vitro or in vivo studies. Computationally derived data can provide insight regarding physiochemical characteristics of future fentalogs and other classes of synthetic analogs that have yet to emerge.