Severe Harm Research Articles

Toxicity prediction based on PAHs in fruits and vegetables − A machine learning approach

This study analyses the toxicity levels of fruits and vegetables by identifying the presence of polycyclic aromatic hydrocarbons (PAHs), particularly in areas affected by industrial and vehicle pollution. The presence of PAHs on plant surfaces, caused mostly by air pollution particulate matter, raises serious concerns about the nutritional value of these foods. Traditional techniques for measuring PAH levels include Gas Chromatography/Mass Spectrometry (GC/MS) and High-Performance Liquid Chromatography (HPLC). Although successful, these procedures are expensive and time-consuming. Toxicity detection is often based on expert knowledge or experimental analysis relative to the European Food Safety Authority’s (EFSA) limits. In response to these challenges, this work uses artificial intelligence approaches to determine toxicity levels using 16 PAHs. Data on PAH concentrations in fruits and vegetables were collected from a variety of sources, classified as safe or harmful, and verified using statistical analysis. The validated dataset was subsequently classified using several machine learning techniques. The level of toxicity is scaled and compared to the expected outputs using the results obtained from the neural network. An experimental investigation validates the promising findings of level of toxicity classification using artificial intelligence approaches, which are then evaluated statistically. The study shows that machine learning algorithms obtained classification accuracies of over 90 %, including the evaluation of harmfulness. The accuracy for the two-class (Safe and Unsafe) category was 98.27 %, while the accuracy for the four-class (No harm, Low harm, Moderate Harm, and Severe harm) category was 98.68 %. These findings highlight the potential of artificial intelligence in improving food safety and public health by presenting an innovative multidisciplinary method to assessing the impacts of environmental pollutants on the edibility of fruits and vegetables in the context of climate change.

Making a Murderer

Abstract Algorithmic risk assessment tools, such as COMPAS, are increasingly used in criminal justice systems to predict the risk of defendants to reoffend in the future. This paper argues that these tools may not only predict recidivism, but may themselves causally induce recidivism through self-fulfilling predictions. We argue that such “performative” effects can yield severe harms both to individuals and to society at large, which raise epistemic-ethical responsibilities on the part of developers and users of risk assessment tools. To meet these responsibilities, we present a novel desideratum on algorithmic tools, called explainability-in-context, which requires clarifying how these tools causally interact with the social, technological, and institutional environments they are embedded in. Risk assessment practices are thus subject to high epistemic standards, which haven't been sufficiently appreciated to date. Explainability-in-context, we contend, is a crucial goal to pursue in addressing the ethical challenges surrounding risk assessment tools.

Self-validating photoelectrochemical/photoelectrochromic visual sensing platform for ciprofloxacin precise detection in milk

BackgroundIn the process of food production, ciprofloxacin (CIP), a highly prescribed fluoroquinolone antibiotic, is often excessively used to reduce the risk of bacterial infection. However, this overuse can cause severe harm to human health, including allergic responses, gastrointestinal complications, and potential renal dysfunction. The development of a robust and precise detection method for CIP is crucial, given the interconnection between food security and human health. Compared to the single-mode detection methods currently in use, dual-mode detection provides enhanced accuracy in detecting results due to its inherent self-validation and self-correction capabilities. ResultsHerein, a photoelectrochemical and photoelectrochromic self-validated dual-mode sensing platform was developed to detect CIP in milk by laser etching method, signal generation (SG) region, signal output (SO) region and conductive channel was integrated on the same fluoide-doped tin oxide electrode and Ti3C2/ZnO composite was modified in the electron SG region, and Prussian blue (PB) was electrodeposited in the SO region. By irradiating the SG region, photogenerated electrons are generated and injected into the SO region through the conductive pathway, resulting in the reduction of the PB to Prussian white (PW). Because the binding of CIP to its specifically recognized aptamers hinders electron transfer, a “Signal-Off” response mechanism can be used for simultaneous quantitative detection of CIP using photocurrent or color changes, which presents a great advantage in the detection process. SignificanceBy integrating different detection mechanisms within a single linear range, the constructed dual-mode sensor has a wide detection range and low detection limit in milk samples. Additionally, it shows good selectivity in anti-interference experiments, providing a new idea for the development of visual analysis and detection platforms for food safety.

Artificial intelligence-powered chatbots in search engines: a cross-sectional study on the quality and risks of drug information for patients

BackgroundSearch engines often serve as a primary resource for patients to obtain drug information. However, the search engine market is rapidly changing due to the introduction of artificial intelligence (AI)-powered...

Association Between Internet Gaming Disorder and Suicidal Ideation Mediated by Psychosocial Resources and Psychosocial Problems Among Adolescent Internet Gamers in China: Cross-Sectional Study.

Adolescent internet gaming disorder (IGD) was associated with severe harm, including suicidal ideation. While suicidal ideation was predictive of completed suicides, further research is required to clarify the association between IGD and suicidal ideation among adolescents, as well as the mechanisms involved. This study aimed to investigate the understudied association between IGD and suicidal ideation, as well as novel mechanisms associated with it, among Chinese adolescent internet gamers through psychosocial coping resources and psychosocial problems. An anonymous, self-administered, cross-sectional survey was conducted among secondary school students who had played internet games in the past year in Guangzhou and Chengdu, China (from October 2019 to January 2020). In total, 1693 adolescent internet gamers were included in this study; the mean age was 13.48 (SD 0.80) years, and 60% (n=1016) were males. IGD was assessed by the 9-item Internet Gaming Disorder Checklist of the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition]), while a single item assessed suicidal ideation: "Have you ever considered committing suicide in the past 12 months?" Univariate and multivariate logistic regression associations were conducted to test the significance and directions of the potential factors for suicidal ideation. The mediation mechanism was examined by structural equation modeling. Among all participants, the prevalence of IGD and suicidal ideation was 16.95% (287/1693) and 43.06% (729/1693), respectively. IGD cases were 2.42 times more likely than non-IGD cases to report suicidal ideation (adjusted odds ratio [OR] 2.42, 95% CI 1.73-3.37). Other significant factors of suicidal ideation included psychosocial coping resources (resilience and social support, both adjusted OR 0.97, 95% CI 0.96-0.98) and psychosocial problems (social anxiety: adjusted OR 1.07, 95% CI 1.05-1.09; loneliness, adjusted OR 1.13, 95% CI 1.10-1.16). The association between IGD and suicidal ideation was partially mediated by 3 indirect paths, including (1) the 2-step path that IGD reduced psychosocial coping resources, which in turn increased suicidal ideation; (2) the 2-step path that IGD increased psychosocial problems, which in turn increased suicidal ideation; and (3) the 3-step path that IGD reduced psychosocial coping resources which then increased psychosocial problems, which in turn increased suicidal ideation, with effect sizes of 10.7% (indirect effect/total effect: 0.016/0.15), 30.0% (0.05/0.15), and 13.3% (0.02/0.15), respectively. The direct path remained statistically significant. IGD and suicidal ideation were alarmingly prevalent. Evidently and importantly, IGD was a significant risk factor for suicidal ideation. The association was partially explained by psychosocial coping resources of resilience and social support and psychosocial problems of social anxiety and loneliness. Longitudinal studies are needed to confirm the findings. Pilot randomized controlled trials are recommended to evaluate the effectiveness of interventions in reducing suicidal ideation by reducing IGD, improving psychosocial coping resources, and reducing psychosocial problems investigated in this study.

Benefits and Harms of Hepatocellular Carcinoma Screening Outreach in Patients with Cirrhosis: A Multi-Center Randomized Clinical Trial.

The value of hepatocellular carcinoma (HCC) screening is defined by the balance of benefits from early tumor detection vs harms due to false positive results. We evaluated the value of a mailed outreach strategy for HCC screening in patients with cirrhosis. We conducted a multi-center pragmatic randomized clinical trial comparing mailed outreach for HCC screening (n = 1436) and usual care with visit-based screening (n = 1436) among patients with cirrhosis at three health systems from March 2018 to September 2021. Outcomes of interest were early-stage HCC detection (ie, screening benefit) and diagnostic evaluation for false positive or indeterminate results (ie, screening harm). Screening harm was categorized as mild, moderate, and severe based on number and type of diagnostic exams. All patients were included in intention-to-screen analyses. Of 125 patients diagnosed with HCC (67 outreach and 58 usual care), 71.2% were found at an early stage per the Milan Criteria. Early tumor detection did not significantly differ between the outreach and usual care arms (64.2% vs 79.3%, p = .06). The proportion of patients with physical harms also did not differ between the outreach and usual care arms (10.8% vs 10.7%, p = .95) with 5.9% in both arms having mild harms, 4.0% and 3.8% respectively with moderate harms, and 0.9% and 1.0% respectively with severe harms. Most patients enrolled in HCC screening were detected at an early stage, and a minority experienced physical harms. A mailed outreach strategy did not significantly increase early HCC detection or physical harms compared to usual care. NCT02582918 and NCT03756051.

Protecting Our Innocence: Addressing Child Pornography in India

The internet has revolutionised educational methodologies and facilitated day-to-day learning experiences. It has also unveiled its darker facets, including the proliferation of child abuse in various forms, such as trafficking, prostitution and kidnapping. Amidst these atrocities, child pornography emerges as one of the most abhorrent manifestations of exploitation, inflicting severe physical and psychological harm upon its victims. In India, where the protection of children is paramount, stringent legal measures have been enacted to address this issue. This paper provides an analysis of the critical landscape of child pornography in the digital age, examining the multifaceted challenges it presents and the proactive measures undertaken by governmental and non-governmental entities. Through an exploration of the legal framework, landmark cases regarding child abuse in India, and initiatives aimed at child protection, the paper investigates the role of internet service providers in combating the dissemination of child sexual abuse material (CSAM). Furthermore, the importance of international cooperation in addressing this grave issue is emphasised. It is crucial to protect our children from this harmful practice; it is necessary to ban the practice of child pornography and protect their fundamental rights.

The lived experience of gambling-related harm in natural language.

Gambling-related harms can have a significant negative impact on disordered gamblers, lower risk gamblers, and affected others. Yet, most disordered and lower risk gamblers will never seek formal treatment, often due to the stigma and shame surrounding gambling. Online self-help forums are a popular alternative way for gamblers to anonymously seek help from others. Analysis of these interactions can provide a deeper understanding of gambling than more commonly used research methodologies. In the present study, we leverage recent developments in natural language processing to analyze posts on a U.K.-based online self-help gambling forum. Using correlated topic modeling, we canvass the various types of discussions among forum members. We also combine this approach with semantic similarity analysis based on sentence embeddings, to map first the posts, and then the 10 topics, onto six previously established gambling-related harm domains. The topic modeling revealed a cluster of discussions of many negative emotions, a topic regarding the positive emotions underlying the potential for change, a distinct topic regarding gambling's relationship harms, and numerous environmental factors that contributed to harm. Emotional/psychological and health harms were most strongly associated with users' posts, illustrating the multidimensionality of severe gambling-related harm. Our results reveal the co-occurrence of different harms, such as the frequent mentions of financial harms and concomitant emotional/psychological harms. The analysis of the lived experiences of gambling-related harm in natural language represents a useful tool for gambling research and can provide a different perspective to inform policy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The pharmacologic management of status epilepticus in pregnant patients: a scoping review

AbstractBackgroundStatus epilepticus (SE) is defined as 5 min or more of seizure activity or two recurrent seizures without a return to baseline. Healthcare providers encounter a challenge when a patient with SE is pregnant. SE is not only detrimental to the mother but can also put the baby at risk of severe harm. SE must be treated rapidly and therefore healthcare providers have very little time to thoroughly review the risk and benefits of available antiseizure medication in this population.AimTo evaluate the current available evidence related to the management of SE in pregnancy.DesignA literature search of PubMed, CINAHL, ProQuest Nursing & Allied Health Source, and Web of Science databases was conducted (2012–2022) using the following search terms: ‘pregnancy’, ‘pregnant women’ OR ‘gestation’ AND ‘status epilepticus’, ‘generalized status epilepticus’, ‘generalized convulsive status epilepticus’, ‘non convulsive status epilepticus’ OR ‘non‐convulsive status epilepticus’. Full‐text randomised controlled trials, clinical trials, observational studies, and case reports published in English were included. Data were extracted and the quality of the studies was evaluated using the Mixed Methods Appraisal Tool.ResultsThe literature described 29 pregnancies and 30 total foetuses. Intravenous benzodiazepine use for emergent control was reported in 45% of patients. Phenytoin and levetiracetam were primarily utilised for urgent control, with a variety of agents used for refractory SE. Ninety‐seven percent of maternal outcomes were reported as positive. The most common outcome was the birth of a healthy term infant. There were seven cases of pregnancy loss.ConclusionPublications pertaining to the treatment of SE in pregnancy are limited to case reports and small observational studies. Use of a benzodiazepine followed by levetiracetam or phenytoin is appropriate, whereas valproic acid should be utilised only when necessary due to the risk of major congenital malformation.

Foot Tumor: Comprehensive Collation and Evaluation

Background: Considerable evidence showed that foot tumors can cause severe harm to people across various age groups, though they have relatively low incidence rate. Currently, substantial research articles provide thorough discoveries among diagnosis, treatment, reconstruction, and other related areas. However, a comprehensive literature evaluation of current study findings is required. Methods: A search approach implementing the PICOS principle was utilized to acquire the literature from mainly three databases—PubMed, NCBI and SpringerLink. All the included studies underwent independent screening and evaluations of quality and risk of bias. The outcomes covered evaluation and comparison of various tumor kinds, diagnostic techniques, treatment modalities, and reconstructive procedures. Results: The location of the foot is characterized by the presence of three primary bone tumor types — osteosarcoma (OS), chondrosarcoma (CDS) and Ewing sarcoma (ES)— and four forms of soft tissue tumor—Synovial sarcoma (SS), epithelioid sarcoma (EPS), clear cell (CC) sarcoma and melanoma. Diagnosis involves the utilization of four approaches—CT, MRI, X-ray and biopsy, either singly or in combination. Out of all the options, biopsy is the most effective and accurate. Surgery and immunotherapy are widely used to treat foot tumor. The advancement of immunotherapy can significantly improve the efficiency and effectiveness of foot tumor treatment due to its specific targets and better established adjustment mechanism. Combining various types of immunotherapy with additional medicines such as chemotherapy and radiotherapy can help improve the progression of foot tumor treatment. For the reconstruction methods, Structural allograft Plastic surgery is widely used for bone tumor and soft tissue sarcoma respectively. Conclusion: The clinical significance of foot tumors is attributed to their infrequency, resulting high possibility of delayed detection and difficulties in proper treatment. The text that provides a comprehensive discussion and analysis of the diagnostic, therapeutic tactics, and repair approaches for the foot tumor can be highly beneficial to the development of foot tumor in the medical area. The methodical collation on characteristics, data of foot tumor categories is therefore equally significant. By obtaining and analyzing such information, researchers and physicians can better identify certain pattern in foot tumor. For the treatment, Immunotherapy stands out among the existing methods since it has the highest potential to selectively target certain types of foot tumors depending on their distinct needs. The evaluation of immunotherapy and reconstruction methods still contain some limitations due to the lack of the latest and adequate research.

Fluorescent probe for imaging N2H4 in plants, food, and living cells and for quantitative detection of N2H4 in soil and water using a smartphone

Hydrazine is volatile and highly toxic, causing severe harm to water, soil, air, and organisms. Therefore, real-time detection and long-term monitoring of hydrazine are crucial for environmental protection and human health. Herein, an “OFF−ON” fluorescent probe 5-((10-ethyl-2-methoxy-10 H-phenothiazin-3-yl)methylene)−2,2-dimethyl-1,3-dioxane-4,6-dione (MPD) for hydrazine detection through a nucleophilic addition reaction was developed. MPD could exclusively identify hydrazine through colorimetric and fluorescent dual-channel responses within 30 s, which also demonstrated high sensitivity (detection limit, 12 nM) and a wide pH range (6 −12). The sensing mechanism of MPD was confirmed using theoretical calculations, where fluorescence was emitted following the recognition of hydrazine because of the disappearance of the photoinduced electron transfer (PET) process. Using a smartphone, MPD enabled the quantitative detection of hydrazine in real water samples and sandy soil. Notably, in the process of detecting hydrazine in actual water samples, the establishment of analytical methods and the completion of rapid quantitative detection only required a smartphone and built-in apps. Additionally, we showed that MPD could recognize hydrazine in various environmental samples, including plants, food, hydrazine vapors, and cells. We believe that the fluorescent probe MPD developed in this study and the established smartphone visualization platform will provide a convenient and effective tool for detecting hydrazine in environmental monitoring, food safety assessment, biological system safety, and other fields.

Evaluation of a Natural Language Processing Approach to Identify Diagnostic Errors and Analysis of Safety Learning System Case Review Data: Retrospective Cohort Study.

Diagnostic errors are an underappreciated cause of preventable mortality in hospitals and pose a risk for severe patient harm and increase hospital length of stay. This study aims to explore the potential of machine learning and natural language processing techniques in improving diagnostic safety surveillance. We conducted a rigorous evaluation of the feasibility and potential to use electronic health records clinical notes and existing case review data. Safety Learning System case review data from 1 large health system composed of 10 hospitals in the mid-Atlantic region of the United States from February 2016 to September 2021 were analyzed. The case review outcome included opportunities for improvement including diagnostic opportunities for improvement. To supplement case review data, electronic health record clinical notes were extracted and analyzed. A simple logistic regression model along with 3 forms of logistic regression models (ie, Least Absolute Shrinkage and Selection Operator, Ridge, and Elastic Net) with regularization functions was trained on this data to compare classification performances in classifying patients who experienced diagnostic errors during hospitalization. Further, statistical tests were conducted to find significant differences between female and male patients who experienced diagnostic errors. In total, 126 (7.4%) patients (of 1704) had been identified by case reviewers as having experienced at least 1 diagnostic error. Patients who had experienced diagnostic error were grouped by sex: 59 (7.1%) of the 830 women and 67 (7.7%) of the 874 men. Among the patients who experienced a diagnostic error, female patients were older (median 72, IQR 66-80 vs median 67, IQR 57-76; P=.02), had higher rates of being admitted through general or internal medicine (69.5% vs 47.8%; P=.01), lower rates of cardiovascular-related admitted diagnosis (11.9% vs 28.4%; P=.02), and lower rates of being admitted through neurology department (2.3% vs 13.4%; P=.04). The Ridge model achieved the highest area under the receiver operating characteristic curve (0.885), specificity (0.797), positive predictive value (PPV; 0.24), and F1-score (0.369) in classifying patients who were at higher risk of diagnostic errors among hospitalized patients. Our findings demonstrate that natural language processing can be a potential solution to more effectively identifying and selecting potential diagnostic error cases for review and therefore reducing the case review burden.

The influence of adverse events on inpatient outcomes in a tertiary hospital using a diagnosis-related group database

Adverse events (AEs) are a significant concern for healthcare systems. However, it is difficult to evaluate their influence because of the complexity of various medical services. This study aimed to assess the influence of AEs on the outcomes of hospitalized patients using a diagnosis-related group (DRG) database. We conducted a case–control study of hospitalized patients at a multi-district tertiary hospital with 2200 beds in China, using data from a DRG database. An AE refers to an unintended physical injury caused or contributed to by medical care that requires additional hospitalization, monitoring, treatment, or even death. Relative weight (RW), a specific indicator of DRG, was used to measure the difficulty of diagnosis and treatment, disease severity, and medical resources utilized. The primary outcomes were hospital length of stay (LOS) and hospitalization costs. The secondary outcome was discharge to home. This study applied DRG-based matching, Hodges–Lehmann estimate, regression analysis, and subgroup analysis to evaluate the influence of AEs on outcomes. Two sensitivity analyses by excluding short LOS and changing adjustment factors were performed to assess the robustness of the results. We identified 2690 hospitalized patients who had been divided into 329 DRGs, including 1345 patients who experienced AEs (case group) and 1345 DRG-matched normal controls. The Hodges–Lehmann estimate and generalized linear regression analysis showed AEs led to prolonged LOS (unadjusted difference, 7 days, 95% confidence interval [CI] 6–8 days; adjusted difference, 8.31 days, 95% CI 7.16–9.52 days) and excess hospitalization costs (unadjusted difference, $2186.40, 95% CI: $1836.87-$2559.16; adjusted difference, $2822.67, 95% CI: $2351.25-$3334.88). Logistic regression analysis showed AEs were associated with lower odds of discharge to home (unadjusted odds ratio [OR] 0.66, 95% CI 0.54–0.82; adjusted OR 0.75, 95% CI 0.61–0.93). The subgroup analyses showed that the results for each subgroup were largely consistent. LOS and hospitalization costs increased significantly after AEs in complex diseases (RW ≥ 2) and in relation to high degrees of harm subgroups (moderate harm and above groups). Similar results were obtained in sensitivity analyses. The burden of AEs, especially those related to complex diseases and severe harm, is significant in China. The DRG database serves as a valuable source of information that can be utilized for the evaluation and management of AEs.

Perceived Impact of Gambling Advertising can Predict Gambling Severity among Patients with Gambling Disorder

There is growing evidence that gambling advertising disproportionately affects those experiencing more severe gambling harm. Such association has been studied by recruiting gamblers using online panels, by analysing registered users’ data from gambling websites, and through surveys and focus group interviews. However, it is thought that these methods tend to overestimate gambling severity. The present study employed a sample of gamblers with a verified gambling disorder diagnosis (N = 210, 7.1% females, Mage = 39.4 years) recruited for a period of under two years at a large public hospital. It examined the relationship between self-reported impact of gambling advertising, gambling preference (strategic versus non-strategic) and gambling modality (online versus in-person). The results indicated that higher perceived impact of gambling advertising predicted higher gambling severity, which supports previous findings obtained from non-clinical settings. However, contrary to what was expected, strategic gambling and online gambling were not associated with higher perceived impact of gambling advertising, even though these groups are believed to be exposed to more gambling marketing and advertising from gambling operators. The study aligns well with available scientific evidence proposing further restrictions on gambling advertising regulation due to their disproportionate impact on those already experiencing gambling harm.

Strategies and Pathways for High-Quality Development in Primary-level Governance of Campus Security in Higher Education Institutions from a High-Level Security Perspective

At present, China s development is at a critical juncture where strategic opportunities coexist with risks and challenges. Against the backdrop of a risk society, the sudden and frequent occurrence of safety incidents in Chinese universities is evident, characterized by complex causes, severe harm, and far-reaching impacts. To integrate high-level safety throughout all fields and processes of campus safety work, and to strengthen the foundation for campus environmental stability on a broader scale, at a higher starting point, and at a higher level, the governance philosophy should first shift to multi-dimensional co-governance, proactively enhancing systemic resilience, and precise feedback loop governance. Secondly, the framework construction should focus on content expansion, the cultivation of stakeholders, and mechanism construction. Finally, through key strategies and optimization paths, promote high-quality development of Primary-level governance in university campus safety and maintain a safe and stable campus environment.

Accessing supports due to others' harmful drinking.

Alcohol's harm to others (AHTO) refers to harms caused to those other than the drinker. The current paper estimates the prevalence of formal and informal supports sought due to AHTO and examines whether the type of support accessed varies by sociodemographic, economic and harm-related characteristics. An Australian sample of 2574 people completed the 2021 AHTO survey, out of which 888 perceived they experienced harm from another's drinking. Prevalence of accessing services and supports was measured. Additionally, several sociodemographic factors, economic factors and harm-related factors were included in multivariable logistic regression models predicting service/support use. Specifically, four models were constructed probing use of any service/support, use of police, use of counselling services and use of family/friend support. Of the survey sample, 12.4% accessed any support/service. Seeking support from family and/or friends was most common, followed by police, counselling, healthcare services and being admitted to hospital. Women had higher odds of accessing counselling and family/friend support. Respondents with a higher education level and two or more financial stressors had higher odds of accessing police and counselling. Respondents harmed by a stranger had higher odds of accessing police, whereas respondents harmed by someone they know had higher odds of seeking support from family/friends. Experiencing more severe harm was associated with greater odds of accessing any support. Several sociodemographic and economic factors were associated with accessing different supports. These findings may inform service development, interventions and policy changes for people affected by others' drinking.

Critical Drop Height Prediction of Loquat Fruit Based on Some Engineering Properties with Machine Learning Approach

The lowest height at which a product can fall without suffering severe harm is known as the “critical drop height” for agricultural products. It is a crucial factor to take into account for crops like loquats that are prone to bruising or damage upon impact. By establishing the minimum altitude at which the product can be dropped without experiencing substantial harm, suitable processing procedures may be established from harvest to the end consumer, thereby preserving product quality and worth. The critical drop height can be ascertained through swift, affordable, non-destructive, and non-traditional methods, rather than time-consuming and expensive laboratory trials. In the study, we aimed to estimate the critical drop height for loquat fruit using machine learning methods. Three different machine learning methods with different operating principles were applied. R2, MAE, RMSE, and MAPE metrics were used to assess the models. There were no obvious differences in both the comparisons within the models, namely the training and test results and the mutual comparisons of the models. However, with a slight difference, the SVMs model performed better in the training data set, and the ETs model performed better in the test data set. Plots were drawn to visualize model performances, and the results obtained from the plots and metrics support each other.

Alcohol, Violence, and Injury-Induced Mortality: Evidence from a Modern-Day Prohibition

Abstract This paper evaluates the impact of a sudden and unexpected nationwide alcohol sales ban in South Africa. We find that this policy causally reduced injury-induced mortality in the country by at least 14%. We argue that this estimate constitutes a lower bound on the true impact of alcohol on injury-induced mortality. We also document a sharp drop in violent crimes, indicating a tight link between alcohol and aggressive behavior in society. Our results underscore the severe harm that alcohol can cause and point toward a role for policy measures that target the heaviest drinkers in society.

‘Let’s excuse abusive men from abusing and enable sexual abuse’: child sexual abuse investigations in England’s private family courts

ABSTRACT Child Sexual Abuse (CSA) is an ongoing scourge upon society. There is minimal understanding of the experiences of mothers and children in private law family court proceedings (PLP), when CSA is reported. A qualitative study was conducted and a feminist-informed Foucauldian Discourse Analysis was applied to understand ten life-stories from within a larger sample of 45. Five themes are presented. CSA was overwhelmingly reported as being minimised, with harmful outcomes for children and mothers reported. Pro-father and ‘parental alienation’ narratives were a facilitator of severe harm and continued male violence to victim-survivor mothers and children. Further research into the scale and prevalence of CSA within PLP is urgently required.

National burden of gambling in Japan: an estimation from an online-based cross-sectional investigation and national epidemiological survey

BackgroundGambling is a popular leisure activity in many countries, often expected to boost regional economies. Nevertheless, its negative impacts remain a significant concern. Gambling disorder is recognized as the most severe consequence; however, even non- or low-risk gamblers may also face negative impacts. This study aimed to estimate the number of Japanese gamblers experiencing gambling-related harm (GRH) and its distribution across six life domains, financial, relational, emotional, health, social and other aspects, based on the severity of their problem gambling risk.MethodsThis cross-sectional study relied on an online survey conducted between August 5 and 11, 2020. Participants aged 20 years and above, who engaged in gambling during 2019 were recruited via a market research company. The survey assessed the prevalence of GRH 72 items among four gambler risk groups (non-problem, low-, moderate-, and high-risk), as categorized by the Problem Gambling Severity Index. The data was adjusted for population weighting using representative national survey data: the 2017 Comprehensive Survey of Living Conditions and the 2017 Epidemiological Survey on Gambling Addictions.ResultsOut of the 28,016 individuals invited to the survey, 6,124 participated in the screening, 3,113 in the main survey, and 3,063 provided valid responses. After adjusting the survey data, it was estimated that 39.0 million (30.8%) of Japan’s 126.8 million citizens gambled in 2019. Among them, 4.44 million (11.4%) experienced financial harm, 2.70 million (6.9%) health harm, 2.54 million (6.5%) emotional harm, 1.31 million (3.4%) work/study harm, 1.28 million (3.3%) relationship harm, and 0.46 million (1.2%) other harm. Although high-risk gamblers experienced severe harm at the individual level, over 60% of gamblers who experienced GRHs were non- and low-risk gamblers, with the exception of other harm, at the population level.ConclusionsThe study highlighted the prevention paradox of gambling in Japan. While national gambling policies primarily focus on the prevention and intervention for high-risk gamblers, a more effective approach would involve minimizing GRH across the entire population.