Exploring criminal responsibility of PTSD patients; findings from a survey in Chinese Mainland courts
بررسی مسئولیت کیفری بیماران مبتلا به PTSD؛ یافته های یک نظرسنجی در دادگاه های سرزمین اصلی چین-2019
Background. – The Wenchuan Earthquake in Sichuan Province is China’s deadliest natural disaster in a generation; after such disturbance, a kind of mental illness named post-traumatic stress disorder (PTSD, also called delayed psychogenic reaction) raises concern in Mainland China, but probably not rapidly sufficient. Different from that in the USA, earthquake is both the reason and focus of PTSD research in China. Methods. – In order to find out the relationship between the PTSD defense and criminal responsibility in Mainland China, the authors decided to use certain academic tools and analysis judicial decisions (816 cases). The authors identified key information from government official websites. Results. – Data demonstrated that research regarding PTSD increases considerably after the Wenchuan earthquake in 2008. However, data also showed that Chinese courts are hesitant in accepting PTSD as a mental defense for criminals, despite relevant existing rules. Some legal ambiguities, such as lack of procedures or instructions for the connection between diagnosis and judgment, can be observed when courts encounter criminals with PTSD. Conclusions. – PTSD patients occur in all races, classes, religions, and nationalities and some would unfortunately be criminals. This pattern reveals concern for the boundary between the reasonable use and abuse of PTSD in view of medico-legal expertise practice. Expert testimony or opinion cannot replace the judges’ decision. Chinese courts should learn from the American Bar Association and accept the three-part analysis for forensic consideration of PTSD. Further details regarding the regulations for resolving the criminal responsibility of PTSD patients should be obtained.
Keywords: Criminal Responsibility | Legal Identification | Mainland China | Post-traumatic Stress Disorder
Estimating monthly wet sulfur (S) deposition flux over China using an ensemble model of improved machine learning and geostatistical approach
برآورد شار رسوب ماهانه گوگرد مرطوب (S) بر روی چین با استفاده از مدل گروهی از یادگیری ماشین پیشرفته و روش زمین آماری-2019
The wet S deposition was treated as a key issue because it played the negative on the soil acidification, biodiversity loss, and global climate change. However, the limited ground-level monitoring sites make it difficult to fully clarify the spatiotemporal variations of wet S deposition over China. Therefore, an ensemble model of improved machine learning and geostatistical method named fruit fly optimization algorithm-random forestspatiotemporal Kriging (FOA-RF-STK) model was developed to estimate the nationwide S deposition based on the emission inventory, meteorological factors, and other geographical covariates. The ensemble model can capture the relationship between predictors and S deposition flux with the better performance (R2=0.68, root mean square error (RMSE)=7.51 kg ha−1 yr−1) compared with the original RF model (R2=0.52, RMSE=8.99 kg ha−1 yr−1). Based on the improved model, it predicted that the highest and lowest S deposition flux were mainly concentrated on the Southeast China (69.57 kg S ha−1 yr−1) and Inner Mongolia (42.37 kg S ha−1 yr−1), respectively. The estimated wet S deposition flux displayed the remarkably seasonal variation with the highest value in summer (22.22 kg S ha−1 sea−1), follwed by ones in autumn (18.30 kg S ha−1 sea−1), spring (16.27 kg S ha−1 sea−1), and the lowest one in winter (14.71 kg S ha−1 sea−1), which was closely associated with the rainfall amounts. The study provides a novel approach for the S deposition estimation at a national scale.
Keywords: Wet S deposition | Machine learning | Geostatistical approach | China
Conservation of data deficient species under multiple threats: Lessons from an iconic tropical butterfly (Teinopalpus aureus)
حفاظت از گونه های کمبود داده در معرض تهدیدات متعدد: درسهایی از یک پروانه گرمسیری نمادین (Teinopalpus aureus)-2019
With increasing pressure from wildlife trade, conservation eﬀorts must balance deﬁciencies in distribution data for species (the Wallacean shortfall) with the risk of increasing accessibility of locality for collectors. The Golden Kaiser-I-Hind (Teinopalpus aureus Mell) is an iconic butterﬂy restricted to Southeast Asia, popular in trade markets but lacking in ecological and conservation information. We compiled occurrence records and used them to assess multiple threats of T. aureus distribution-wide and at the national level. Results of species distribution models suggest that suitable habitats of T. aureus are montane forests in mid to high elevations in Southern China, Laos and Vietnam. However, habitat networks for the species are poorly connected, with some portions of its distribution experiencing intensive deforestation and threatened by climate change. The trade assessment results showed specimens of T. aureus were available for sale with high prices, indicating potential pressure from trade markets. We also found diﬀerent conservation statuses and eﬀorts to protect T. aureus across countries; the species is under strict protection in China, moderate protection in Vietnam and has no protection in Laos. Both recorded locations and projected distribution in the three countries were poorly covered by protected areas. These results together demonstrate the importance of distribution data in conservation management of threa- tened species while highlighting trade-oﬀs inherent in not making location information widely available when trade pressure is present. Finally, we strongly encourage cross-border cooperation in sharing ecological in- formation for consistent conservation management of species under multiple threats from habitat loss, climate change and illegal wildlife trade.
Keywords: Climate change | Cross-border conservation | Habitat loss | Insect conservation | Southeast Asia | Wildlife trade
پیش بینی ورود گردشگران از طریق یادگیری ماشین و شاخص جستجوی اینترنتی
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 38
مطالعات قبلی نشان داده است که داده های آنلاین، مانند پرس وجوهای انجام شده در موتورهای جستجو، یک منبع اطلاعاتی جدید محسوب می شوند که می توانند برای پیش بینی تقاضای گردشگری مورد استفاده قرار گیرند. در این مطالعه، ما چارچوبی را برای این پیش بینی ارائه می دهیم که با استفاده از یادگیری ماشین و شاخص های جستجوی اینترنتی، ورود گردشگران به مکان های محبوب چین را پیش بینی می کند و عملکرد این پیش بینی، را به ترتیب با نتایج جستجوی تولید شده توسط گوگل و بایدو مقایسه می کنیم. این تحقیق، علیت گرانجر و همبستگیِ میانِ شاخص جستجوی اینترنتی و ورود گردشگران به پکن را تایید می کند. نتایج تجربی ما نشان می دهد که عملکردِ پیش-بینیِ مدل های پیشنهادیِ هسته ی ماشین یادگیری افراطی (KELM )، که مجموعه هایی از گردشگران را با شاخص بایدو و شاخص گوگل ادغام می کنند، در مقایسه با مدل های معیار، به میزان قابل توجهی از نظر دقت پیش بینی و قدرت تحلیل ، بهتر بوده اند.
کلمه های کلیدی: پیش بینی تقاضای گردشگری | هسته ی ماشین یادگیری افراطی | جستجوی داده-های پرس وجو | تحلیل داده های بزرگ | شاخص جستجوی ترکیبی.
|مقاله ترجمه شده|
Gender differences among homicide offenders with schizophrenia in Hunan Province, China
تفاوت های جنسیتی در بین مجرمین قتل با اسکیزوفرنی در استان هونان ، چین-2019
This study aimed to understand the demographic, clinical and criminological characteristics of Chinese homicide offenders with schizophrenia from a gender-based perspective. Information on all homicide offenders with schizophrenia who received forensic psychiatric assessment between 2010 and 2016 in Hunan Province, China, was systematically retrieved (n=669). Gender differences in the above characteristics were analyzed, and independent correlates of homicide were explored. The male to female ratio of homicide offenders was about 4:1. Proportionally more males were single, unemployed and younger when committing their first crime than was apparent in females. Male perpetrators were more often influenced by delusions. Females were more likely to target their close family members. For males, living in rural areas and having a family history of mental disorder were positively associated with homicide, while having a criminal history and being unemployed were negatively associated. For females, younger age was positively, while being unmarried and unemployment were negatively associated with homicide. Our results indicate significant gender differences among Chinese homicide offenders with schizophrenia in demographic, clinical and criminological characteristics and in independent correlates of homicide. Further research in this field, especially aims at determining risk factors for crime in this population, should take the gender differences into account.
Keywords: Violence | Murder | Severe mental disorder | Sex difference | Independent correlates | Risk factors | Chinese
Oil price shocks and Chinese banking performance: Do country risks matter?
شوک قیمت نفت و عملکرد بانکی چین: آیا ریسک های کشور مهم است؟-2019
This paper contributes to the existing literature by investigating the impacts of oil prices on bank performance through a broad array of CAMEL (Capital adequacy, Asset quality, Management, Earnings, and Liquidity) indicators in China over the period 2000–2014. To gain further insights into this issue, we also discuss whether the correlations changewith different dimensions of country risk, i.e., economic, financial, and political,which extant studies ignored. The results reveal that oil prices have a significant impact on banking performance, as their increase triggers a reduction in banking performance in terms of capitalization, management efficiency, earning power, and liquidity. However, these adverse effects are mitigated by country stability, especially economic stability and political stability. These results are important for policy makers who should be cautious when formulating a strategy for macroeconomic stability. From the managerial perspective, bank managers should consider establishing early warning and response mechanisms on the back of oil price shocks in order to operate under better performance
Keywords : Oil price shock | Banking performance | CAMEL ratings | Country risks
Chinas campaign-style Internet finance governance: Causes, effects, and lessons learned for new information-based approaches to governance
حاکمیت تأمین مالی اینترنت به سبک تبلیغات در چین: علل ، پیامدها و درسهایی که برای رویکردهای جدید مبتنی بر اطلاعات در مورد حاکمیت کسب شده است-2019
China’s Internet companies and citizens are now world leaders in developing and using the Internet and related information technologies for financial transactions. Accordingly, it is important that China becomes a world leader in identifying challenges posed by Internet finance, and providing law and governance solutions to address these challenges. While the Internet and its associated technologies are now globally available, a core question is whether, and to what extent, regulatory challenges and opportunities are common across different jurisdictions, or whether they reflect local circumstances. In short, an interesting question is what can the world learn from China as it takes the lead in addressing Internet finance challenges, and what can China learn from the world as it seeks to do so? This article first identifies the landscape of China’s burgeoning Internet finance market, including key technologies and services and government and nongovernment players. The article then turns to key regulatory challenges, with a focus on factors especially significant in China. The article then examines the “top down”“campaign style” approach to regulation, which is China government’s initial response to emerging challenges. Following an analysis of the campaign, some suggestions are then made for future possible governance strategies. We explain how emerging “information” based and experiment-based approaches to gov- ernance are drawing on both global and Chinese experiences to harness the capabilities of the Internet and the collective energies of Internet finance enterprises and users to advance the regulation of the China Internet finance system in a way that is conducive to the public interest.
Keywords: Internet finance | Campaign-style law enforcement | Information-based regulation ( xinxi gongkai ) | Experiment-based regulation ( shidian)
A comparative assessment of flood susceptibility modeling using Multi- Criteria Decision-Making Analysis and Machine Learning Methods
ارزیابی مقایسه ای مدل سازی حساسیت به سیل با استفاده از روش های تصمیم گیری چند معیاره و روشهای یادگیری ماشین-2019
Floods around the world are having devastating effects on human life and property. In this paper, three Multi-Criteria Decision-Making (MCDM) analysis techniques (VIKOR, TOPSIS and SAW), along with two machine learning methods (NBT and NB), were tested for their ability to model flood susceptibility in one of China’s most flood-prone areas, the Ningdu Catchment. Twelve flood conditioning factors were used as input parameters: Normalized Difference Vegetation Index (NDVI), lithology, land use, distance from river, curvature, altitude, Stream Transport Index (STI), Topographic Wetness Index (TWI), Stream Power Index (SPI), soil type, slope and rainfall. The predictive capacity of the models was evaluated and validated using the Area Under the Receiver Operating Characteristic curve (AUC). While all models showed a strong flood prediction capability (AUC > 0.95), the NBT model performed best (AUC=0.98), suggesting that, among the models studied, the NBT model is a promising tool for the assessment of flood-prone areas and can allow for proper planning and management of flood hazards.
Keywords: Flood susceptibility | Machine Learning | Multi-Criteria Decision-Making | GIS | China
A retrospective analysis of data from forensic toxicology at the Academy of Forensic Science in 2017
تجزیه و تحلیل گذشته نگر از داده های مربوط به سمیت شناسی پزشکی قانونی در آکادمی علوم پزشکی قانونی در سال 2017-2019
Knowing the specific pattern of forensic toxicology cases in a region is vital to help the local government establish an effective prevention and treatment system; currently, there have been no published reports investigating various types of forensic toxicology cases based on a large autopsy series and city size. The data in this study were obtained from records kept at the Academy of Forensic Science (AFS) between February 2017 and December 2017, and the cases were mainly from the Public Security Organs People’s Police in Shanghai, China. There were 299 autopsies; the leading cause of death was traffic accidents (37.1%), and the manners of death were mainly accidental (54.8%). From a total of 9083 cases, 1992 involved traffic accidents, 6787 were drug abuse, 269 were poisonings, and 35 were drug-facilitated sexual assaults (DFSAs). We also investigated the pattern of unnatural deaths and the alcohol-positive (with a blood alcohol concentration (BAC) 0.20 mg/ml) rate among the various cases. The BAC ranged from 0.08 to 7.24 mg/ml in traffic cases, and the mean BAC of the total alcohol-positive drivers was 1.44 mg/ml. It was found that 80.8% of the drivers involved had a BAC 0.20 mg/ml (limit of civil offense), and 72.8% had a BAC 0.80 mg/ml (limit of criminal offense). Among the drug abuse cases, there were 4073 cases (60.0%) that were positive for at least one euphoriant; the most frequently abused drug group was amphetamine-type stimulants (ATS). Poisonings by natural toxins (such as scopolamine and tetrodotoxin) account for a significant portion of accidental deaths. Pesticide poisoning was also constituted a large portion, and organophosphorus were the cause of the majority of those cases. Suicide by pesticide showed the highest frequency in the present study. Among the 35 DFSA cases, dexmedetomidine was frequently detected in our study, which has rarely been reported previously in DFSA cases.
Keywords: Driving | Drug abuse | Poisoning | Drug-facilitated sexual assault | Retrospective study | Shanghai
Determinants of the competitive advantage of dairy supply chains: Evidence from the Chinese dairy industry
عوامل تعیین کننده مزیت رقابتی در زنجیره های تامین فراورده های لبنی: شواهدی از صنعت لبنی چینی-2019
In this study, we use an evidence-based approach to examine the factors that determine the competitive advantage of dairy supply chains using evidence from the Chinese dairy industry. We focus on the quality assurance of dairy products, which is considered one of the fundamental influential factors. We investigate interrelationships among the identified determinants, which include dairy production behavior, dairy cow culture model, government regulations, corporate social responsibility, and quality assurance, and examine how these determinants influence the competitive advantage of dairy supply chains. We employ the structural equation modeling approach in which grouped observable variables that represent the identified determinants are extrapolated from primary data collected through a questionnaire survey. Our key findings show that by mediating the effects of dairy production behavior and the dairy cow culture model, government regulation and corporate social responsibility significantly affect the quality assurance of dairy products. In turn, dairy production behavior and the dairy cow culture model significantly affect the competitive advantage of the dairy supply chain via the fully mediated effects of the quality assurance of dairy products. Specifically, the dairy cow culture model helps ensure the safety and quality of milk supply, allowing core dairy firms to control product quality throughout the dairy supply chain. Our empirical study shows that the identified determinants interact to assure the quality of dairy products and enhance the competitive advantage of the dairy supply chain in China.
Keywords: Dairy | Supply chain | Competitive advantage | Quality assurance | Structural equation model