小城镇服务业人才培养问题研究

劳动力市场人才资源的配置问题是小城镇服务业发展中急需解决的重要问题之一。本文从用人单位满意度分析的基础上,采用模糊综合评价法对当前小城镇服务业劳动力需求与人才培养对接问题现状进行了评价,发现劳动力市场人才资源的配置与人才培养供给之间出现了严重的失衡。人才培养只有遵循劳动力市场需求,动态地调整培训方案与体系,才能够健康持续地发展。     

Analyzing Concepts of Human Rights with an Asian Accent

Let’s suppose we were in the early Twentieth Century,trying to answer the question:What will be the most important things that will happen in this century?You may think about the"rise of the United States,"or the long-lived British Empire.     

A Critical Analysis of Global Governance vs.Protection and Development of Human Rights

Human rights merit global attention in the current era of globalization.The realization and protection of human rights is an important part of the process of global governance.Meanwhile,global governance     

The suitability of using domestic pigs (Sus spp.) as human proxies in the geophysical detection of clandestine graves

Research in many forensic science fields commonly uses domestic pigs (Sus spp.) as proxies for human remains, due to their physiological and anatomical similarities, as well as being more readily available. Unfortunately, previous research, especially that which compares the decompositional process, has shown that pigs are not appropriate proxies for humans. To date, there has not been any published research that specifically addresses whether domestic pigs are adequate human proxies for the geophysical detection of clandestine graves. As such, the aim of this paper was to compare the geophysical responses of pig cadavers and human donor graves, in order to determine if pigs can indeed be used as adequate human proxies. To accomplish this, ground penetrating radar (GPR) and electrical resistivity tomography (ERT) responses on single and multiple pig cadaver graves were compared to single and multiple human donor graves, all of which are in known locations within the same geological environment. The results showed that under field conditions, both GPR and ERT were successful at observing human and pig burials, with no obvious differences between the detected geophysical responses. The results also showed that there were no differences in the geophysical responses of those who were clothed and unclothed. The similarity of the responses may reflect that the geophysical techniques can detect graves despite what their contents are. The study implications suggest that experimental studies in other soil and climate conditions can be easily replicated, benefiting law enforcement with missing persons cases.     

An innovative transfer DNA experimental design and qPCR assay to identify primary,secondary, and tertiary DNA transfer

“Touch DNA” is a form of trace DNA that is presumed to be deposited when an individual touches something and leaves behind DNA-containing skin cells, sweat, or other fluids. While touch DNA is often the result of direct contact (i.e., primary transfer), it can also be indirectly transferred between surfaces or individuals (e.g., secondary or tertiary transfer). Even experts cannot distinguish between different types of transfer and do not fully understand which variables affect direct versus indirect transfer or how often each type of transfer occurs. In this study, we utilize an innovative protocol that combines a paired male and female transfer DNA experimental design with an Amelogenin qPCR assay to generate data on primary, secondary, and tertiary DNA transfer. We report frequencies of indirect DNA transfer and also investigate the potential effects of participant age, self-identified ethnicity, and skin conditions on DNA transfer. Out of 22 experimental trials, we detected primary transfer (male + female) in 71% of trials, secondary DNA transfer in 50% of trials, and tertiary DNA transfer in 27% of trials. No significant associations were found between primary DNA transfer and age, self-identified ancestry, or skin conditions, however, all individuals with sloughing skin conditions demonstrated primary DNA transfer and we suggest this variable be explored in larger samples. These results contribute to a better understanding of the conditions under which secondary and tertiary DNA transfer occurs and can be used to propose realistic DNA transfer scenarios in court cases.     

Comparison of feature selection and data fusion of Fourier transform infrared and Raman spectroscopy for identifying watercolor ink

The identification of different kinds of watercolor inks is an important work in the field of forensic science. Four different kinds of watercolor ink Spectroscopy data fusion strategies (Fourier Transform Infrared spectroscopy and Raman spectroscopy) combined with a non-linear classification model (Extreme Learning Machine) were used to identify the brand of watercolor inks. The study chose Competitive Adaptive Reweighted Sampling (CARS), Random Frog (RF), Variable Combination Population Analysis-Genetic Algorithm (VCPA-GA), and Variable Combination Population Analysis-Iteratively Retains Informative Variables (VCPA-IRIV) to extract characteristic variables for mid-level data fusion. The Cuckoo Search (CS) algorithm is used to optimize the extreme learning machine classification model. The results showed that the classification capacity of the mid-level fusion spectra model was more satisfactory than that of single Infrared spectroscopy or Raman spectroscopy. The CS-ELM models based on infrared spectroscopy used to recognize the watercolor ink according to brands (ZHENCAI, DELI, CHENGUANG, and STAEDTLER) obtained an accuracy of 66.67% in the test set using all spectral datasets. The accuracy of CS-ELM models based on Raman spectroscopy was 67.39%. The characteristic wavelength selection algorithms effectively improved the accuracy of the CS-ELM models. The classification accuracy of the mid-level spectroscopy fusion model combined with the VCPA-IRIV algorithm was 100%. The data fusion method increased effectively spectral information. The method could satisfactorily identify different brands of watercolor inks and support the preservation of artifacts, paintings, and forensic document examination.     

Use of thermal drone in detection and assessment of larval mass temperature in decomposed rabbit carcasses

Manual ground searches and cadaver dogs are traditional methods for locating remains, but they can be time- and resource-intensive, resulting in the decomposition of bodies and delay in victim identification. Therefore, thermal imaging has been proposed as a potentially useful tool for detecting remains based on their temperature. This study investigated the potential of a novel search technique of thermal drones to detect surface remains through the detection of maggot mass temperatures. Two trials were carried out at Selangor, Malaysia, each utilizing 12 healthy male Oryctolagus cuniculus European white rabbits and DJI Matrice 300 RTK drone China, equipped with a thermal camera; Zenmuse H20T to record the thermal imaging footage of the carcasses at various heights (15, 30, 60–100 m) for 14 days for each trial. Our results demonstrated that the larval masses and corresponding heat emissions were at their largest during the active decay stage; therefore, all the carcasses were observable in thermal images on day 5 and remained until day 7. Statistical analyses showed that (1) no statistically significant differences in thermal images between clothed and unclothed subjects (p > 0.05); (2) 15 m above ground level was proven to be the optimal height, as it showed the greatest contrast between the carcass heat signature and the background (p < 0.005). Our data suggested the potential window of detection of thermal signatures was detectable up to 7 days post-deposition. This could be an important guideline for the search and recovery teams for operational implementation in this tropical region.     

Toward multidimensional information: A derivatization-free UHPLC-QqQ MS/MS method for amino acid components of fingerprint

The analysis of fingerprint chemical composition is a meaningful way to excavate the multidimensional information of fingerprint, including the donor profiling information and the age of a fingerprint, which broadens the evidential values of fingerprint, especially for the partial and distorted fingerprint. But the research remains still in the pilot phases or is ongoing. Amino acids are the dominant organic substances in latent sweat fingerprint and influenced by many donor factors. Hence, their content reflects personal information of donors. Forensic science will be revolutionized if suspects can be individualized by their amino acid content. The diverse nature, distinct physicochemical properties, and ultra-micro levels of amino acids present in fingerprints make it hard to detect. A high sensitivity method for detecting and quantifying multiple amino acid components is required. UHPLC-QqQ MS/MS offers high sensitivity, high separation, simultaneous multicomponents detection, and no derivatization, making it an ideal method for detecting and analyzing amino acids in fingerprints. Therefore, in this study, we propose and validate an efficient UHPLC-QqQ MS/MS method for the extraction and analysis of 13 amino acids from fingerprint. We compared the results of amino acids of 10 different substrates and found that the inherent amino acids in most porous substrates would have been extracted along with the fingerprint amino acids, making them unsuitable for quantitative amino acid analysis. Instead, plastic sheets are ideal substrates for laboratory studies. Then, extensive experiments were conducted among 30 donors for multidimensional information analysis. The type of samples analyzed were eccrine-rich fingerprints. A Binary Logistic Regression (BLR) model was developed, and the female and male donors were successfully differentiated by amino acids in fingerprints. Two other mathematical models were also developed to verify the accuracy, and all three different mathematical models were able to identify donors of different genders with over 90% accuracy. This demonstrates that amino acids have the potential to provide more information for donors as metabolic markers. In the future, we will conduct a series of experiments to analyze more multidimensional information for individual identification by amino acid content in the fingerprint.     

Experimental results on data analysis algorithms for extracting and interpreting edge feature data for duct tape and textile physical fit examinations

A physical fit is an important observation that can result from the forensic analysis of trace evidence as it conveys a high degree of association between two items. However, physical fit examinations can be time-consuming, and potential bias from analysts may affect judgment. To overcome these shortcomings, a data analysis algorithm using mutual information and a decision tree has been developed to support practitioners in interpreting the evidence. We created these tools using data obtained from physical fit examinations of duct tape and textiles analyzed in previous studies, along with the reasoning behind the analysts' decisions. The relative feature importance is described by material type, enhancing the knowledge base in this field. Compared with the human analysis, the algorithms provided accuracies above 90%, with an improved rate of true positives for most duct tape subsets. Conversely, false positives were observed in high-quality scissor cut (HQ-HT-S) duct tape and textiles. As such, it is advised to use these algorithms in tandem with human analysis. Furthermore, the study evaluated the accuracy of physical fits when only partial sample lengths are available. The results of this investigation indicated that acceptable accuracies for correctly identifying true fits and non-fits occurred when at least 35% of a sample length was present. However, lower accuracies were observed for samples prone to stretching or distortion. Therefore, the models described here can provide a valuable supplementary tool but should not be the sole means of evaluating samples.