Substantial Harm Research Articles

Statistical analysis plan for the LAST ACT clinical trial; a Leukotriene A4 hydrolase Stratified non-inferiority Trial of Adjunctive Corticosteroids for HIV-negative adults with Tuberculous meningitis

Tuberculous meningitis (TBM) is the most severe form of tuberculosis. Corticosteroids are currently recommended as an adjunctive therapy in HIV-negative adults with TBM. However, benefit from corticosteroids in TBM may depend upon host leukotriene A4 hydrolase (LTA4H) genotype and the corresponding inflammatory phenotypes. This article describes the planned analyses for the primary publication of the results of the LAST ACT clinical trial (NCT03100786): ‘Leukotriene A4 hydrolase Stratified Trial of Adjunctive Corticosteroids for HIV-negative adults with Tuberculous meningitis’. The primary hypothesis addressed by the trial is that LTA4H genotype, in particular CC or CT genotype, determines whether adjunctive dexamethasone benefits or harms adults with TBM. The trial was an LTA4H genotype stratified, parallel group, randomised, double blind, placebo-controlled multi-centre Phase III trial of dexamethasone given for 6–8 weeks in addition to standard anti-tuberculosis drugs. LTA4H genotype (CC, CT, TT) was determined in all participants prior to randomisation; only those with CC or CT genotype were randomised to dexamethasone or placebo. All TT genotype participants received dexamethasone because prior data indicated survival was increased by dexamethasone in this genotype. The primary endpoint was all-cause death or new neurological event over the first 12 months after randomisation. We took a hybrid trial-design approach which aims to prove non-inferiority of placebo first but also allows claiming superiority of placebo in case dexamethasone causes substantial harm. This statistical analysis plan expands upon and updates the analysis plan outlined in the published study protocol.

How Do Satellite Precipitation Products Affect Water Quality Simulations? A Comparative Analysis of Rainfall Datasets for River Flow and Riverine Nitrate Load in an Agricultural Watershed

Excessive nitrate loading from agricultural runoff leads to substantial environmental and economic harm, and although hydrological models are used to mitigate these effects, the influence of various satellite precipitation products (SPPs) on nitrate load simulations is often overlooked. This study addresses this research gap by evaluating the impacts of using different satellite precipitation products—ERA5, IMERG, and gridMET—on flow and nitrate load simulations with the Soil and Water Assessment Tool Plus (SWAT+), using the Tar-Pamlico watershed as a case study. Although agricultural activities are higher in the summer, this study found the lowest nitrate load during this season due to reduced runoff. In contrast, the nitrate load was higher in the winter because of increased runoff, highlighting the dominance of water flow in driving riverine nitrate load. This study found that although IMERG predicts the highest annual average flow (120 m3/s in Pamlico Sound), it unexpectedly results in the lowest annual average nitrate load (1750 metric tons/year). In contrast, gridMET estimates significantly higher annual average nitrate loads (3850 metric tons/year). This discrepancy underscores the crucial impact of rainfall datasets on nitrate transport predictions and highlights how the choice of dataset can significantly influence nitrate load simulations.

Efficient detection of wheat mold degree using novel nano-composite colorimetric sensor

Wheat is one of the most significant food crops globally, and the aflatoxin B1 (AFB1) produced by wheat mold has the potential to cause substantial harm to humans and livestock. This study employed mesoporous silica nanoparticles (MSNs) to modify colorimetric sensing arrays (CSA) for the preparation of nano-composite colorimetric sensors (Nano-CSA) for the identification of the degree of wheat mold. Twelve metal porphyrin reagents were selected as chemical response dyes for the construction of the CSA. To enhance the sensor's sensitivity, the MSNs were individually combined with the 12 chemical response dyes, and the homogeneous integration of the MSNs and dyes was facilitated through techniques such as ultrasonic oscillation and magnetic stirring. The sensor is designed to react with the volatile gas the fungus produces in a closed reaction chamber. The MSNs effectively capture gas molecules, causing significant color changes in the chemical dyes, thereby enabling the characterization of the gas fingerprints of wheat with different degrees of mold through a colorimetric sensing system. The data were subjected to characterization techniques and data analysis to demonstrate the effectiveness of the nano-modified sensor array. The CSA demonstrated an accuracy of 87.50 % in identifying wheat samples with varying degrees of mildew, while the Nano-CSA classification model exhibited an accuracy of 97.50 %. These findings indicate that nano-modification can enhance the responsiveness of chemical response dyes to gas molecules. Nano-CSA can effectively and sensitively distinguish the degree of wheat mildew, suggesting potential applications in predicting the degree of wheat mildew.

Exploring the risks of fragmentation in health care markets – An analysis of inpatient care in Georgia

Private providers play an important role in health systems in low-and middle-income countries. In many such contexts, markets are characterized by a high number of relatively small private facilities. The potential risks from highly concentrated healthcare markets are well-researched, and feature in the “Theories of Harm” investigated by competition regulators. However, there is limited evidence on markets that exhibit substantial harms as a result of very low concentration. This paper explores the risks associated with such market fragmentation, drawing on the example of Georgia, which has a largely privatized provider network.We used a mixed-method study design to analyze the inpatient market in Georgia. Market structure was described using administrative data on bed capacity and discharge numbers and geo-location data on travel time between facilities. The implications of the market structure were explored through in-depth interviews (n = 35) with policymakers, healthcare managers, and local experts and an anonymous online survey of similar groups (n = 97).Georgia's inpatient sector is characterized by a high number of small hospitals in terms of bed numbers and inpatient volumes, mitigated to a limited degree by the presence of provider networks. Travel time to the 3rd nearest competitor was extremely short, ranging from 3 to 5 min in big cities to 10 min in small towns and 33 min in remote locations. The fragmented nature of the market, together with inadequate regulatory and purchasing mechanisms, was argued to exacerbate challenges in the availability and competence of clinical staff, while the financial challenges caused by intense competition encouraged wasteful marketing, harmful cost-cutting measures, and demand inducement.We present “Theories of Harm” from market fragmentation, and argue that an effective policy response requires market-shaping activities using regulatory, financing, and purchasing mechanisms to encourage appropriate levels of market consolidation and so enhance quality, efficiency, and effective governance.

Investigating Sortase A inhibitory potential of herbal compounds using integrated computational and biochemical approaches

Multi-drug resistance in bacteria is emerging as a major global health challenge, causing substantial harm in terms of mortality, morbidity, and financial strain on healthcare systems. These bacteria are constantly acquiring new virulence factors and drug-resistance mechanisms, which highlights the critical need for innovative antimicrobial medicines and identification of new therapeutic targets, such as Sortase A (EfSrtAΔN59). EfSrtAΔN59, a transpeptidase significant for the adhesion and virulence of Enterococcus faecalis (E. faecalis), presents an attractive target for disrupting biofilm formation—a key factor in persistent infections. This study investigates the inhibitory effects of two natural flavonoids- Rutin Trihydrate and Quercetin, on EfSrtAΔN59 and biofilm formation in E. faecalis. With in vitro enzymatic assays and biofilm quantification techniques, we demonstrate that both compounds significantly attenuate EfSrtAΔN59 activity, thereby hindering bacterial biofilm formation. Rutin Trihydrate and Quercetin exhibited strong binding affinities to the EfSrtAΔN59 enzyme, as confirmed by molecular docking and MD simulation studies. This was further substantiated by a notable reduction in biofilm biomass in bacterial cultures treated with these compounds. These findings highlight the potential of Rutin Trihydrate and Quercetin as promising candidates for the development of novel anti-virulence therapies aimed at mitigating E. faecalis infections, thereby offering a compelling alternative to traditional antibiotics.

Capturing the context of drug use for college students: A contextual behavioural science informed qualitative analysis of harm reduction practices using network feedback loops simulation modelling

Drug use during college can have substantial harm on students' lives and impacts the institutions' functioning and local communities. Yet existing interventions for drug use at college poorly address the concurrent dynamic influences of the experiences in earlier developmental periods of young adults and the proximal contextual triggers of college life; both risk factors that can contribute to drug use. To address this, we leveraged system dynamic methods and contextual-behavioural science (CBS) approaches to support the development of interventions focusing at addressin these risk factors. Using Causal Loop Diagram methods (Vensim PLE), we collected qualitative data from college students to generate Network Feedback Loops (NFLs) (n = 24, Maged 22 years old), during the development phase of the MyUse: a contextual behavioural change intervention for harm reduction practices at college students. The findings underscored central nodes (determinants within an intervention) that support our previous identified three CBS-harm-reduction practices for college students (targeted edges: mindful drug-use decision making, value-based activities, context-sensitive personalized plan of harm reduction). Analyses revealed 4 NFLs for students with previous drug use, consisting of 13 edges (4 positive, 2 negative, and 4 balancing reinforcing relationships) and 3 NFLs for students with no previous drug use, consisting of 4 positives, one negative, and one balancing relationship. All the NFLs were nested with the three CBS-related targeted outcomes. College students who use drugs need drug-related knowledge about the unpredictable and adverse effects of drugs, presented in a compassionate way and distributed from credible resources (e.g., students’ unions/club). Students with no previous drug use need education about the effects of drugs and awareness of how drugs can devaluate value-based activities (e.g. sports, friendships, social life). These should be delivered via proxy cue reminders and mobile-text approaches conveying messages about drug use susceptibility, distributed in real-time. Idiosyncratic, dynamic, and contextual-bound factors of lapse risks or preventive practices should account for each person-specific vulnerabilities via personalized harm reduction plans.

Measuring and improving the cradle-to-grave environmental performance of urological procedures.

An urgent need for societal transformation exists to reduce the environmental impact of humanity, because environmental healthaffects human health. Health care causes ~5% of global greenhouse gas emissions and other substantial and ongoing environmental harms. Thus, health-care professionals and managers must lead ongoing efforts to improve the environmental performance of health systems. Life-cycle assessment (LCA) is a methodology that enables estimation of environmental impacts of products and processes. It models environmental effects from 'cradle' (raw material extraction) to 'grave' (end of useful life) and conventionally reports a range of different impact categories. LCA is a valuable tool when used appropriately. Maximizing its utility requires rational assumptions alongside careful consideration of system boundaries and data sources. Well-executed LCAs are detailed and transparently reported, enabling findings to be adapted or generalized to different settings. Attention should be given to modelling mitigation solutions in LCAs. This important step can guide health-care systems towards new and innovative solutions that embed progress towards international climate agreements. Many urological conditions are common, recurrent or chronic, requiring resource-intensive management with large associated environmental impacts. LCAs in urology have predominantly focussed on greenhouse gas emissions and have enabled identification of modifiable 'hotspots' including electricityuse, travel, single-use items, irrigation, reprocessing and waste incineration. However, the methodological and reporting quality of published urology LCAs generally requires improvement and standardization. Health-care evaluation and commissioning frameworks that value LCA findings alongside clinical outcomes and cost could accelerate sustainable innovations. Rapid implementation strategies for known environmentally sustainable solutions are also needed.

Проблема оценки существенности вреда в составе самоуправства

Introduction. The aarticle deals with the issue of legislative regulation, establishment and assessment of the consequences of arbitrariness. The issues of determining the materiality of harm as a feature of the objective side of the offence under Article 330 of the Criminal Code of the Russian Federation. Based on the analysis of judicial practice, the varieties of substantial harm caused in the commission of arbitrary actions are determined. It is noted that the materiality of harm is a necessary condition for qualification of a deed under Article 330 of the Criminal Code of the Russian Federation. The purpose of the research is to characterise the criteria used by law enforcers in determining the essential harm as part of arbitrariness. Methods. The author used the following methods: dialectical method of cognition, a set of general scientific methods (analysis, synthesis, induction, deduction), as well as a number of special methods (formal-legal, comparativelegal, systemic, functional). Results. The analysis of judicial practice on the problem under study allowed to determine the influence of the subjective factor due to the creative nature of the law enforcer in determining the materiality of the harm caused by unlawful actions. It is concluded that the lack of criteria for assessing the materiality of harm, as well as the lack of specification of the range of social relations that may be harmed as a result of arbitrariness, may cause such harm, entails uncertainty in the emerging law enforcement judicial practice.

Prediction of Forest-Fire Occurrence in Eastern China Utilizing Deep Learning and Spatial Analysis

Forest fires are a major natural calamity that inflict substantial harm on forest resources and the socio-economic landscape. The eastern region of China is particularly susceptible to frequent forest fires, characterized by high population density and vibrant economic activities. Precise forecasting in this area is essential for devising effective prevention strategies. This research utilizes a blend of kernel density analysis, autocorrelation analysis, and the standard deviation ellipse method, augmented by geographic information systems (GISs) and deep-learning techniques, to develop an accurate prediction system for forest-fire occurrences. The deep-learning model incorporates data on meteorological conditions, topography, vegetation, infrastructure, and socio-cultural factors to produce monthly forecasts and assessments. This approach enables the identification of spatial patterns and temporal trends in fire occurrences, enhancing both the precision and breadth of the predictions. The results show that global and local autocorrelation analyses reveal high-incidence areas mainly concentrated in Guangdong, Fujian, and Zhejiang provinces, with cities like Jiangmen exhibiting distinct concentration characteristics and a varied spatial distribution of fire occurrences. Kernel density analysis further pinpoints high-density fire zones primarily in Meizhou, Qingyuan, and Jiangmen in Guangdong Province, and Dongfang City in Hainan Province. Standard deviation ellipse and centroid shift analysis indicate a significant northward shift in the fire-occurrence centroid over the past 20 years, with an expanding spatial distribution range, decreasing flattening, and relatively stable fire-occurrence direction. The model performs effectively on the validation set, achieving an accuracy of 80.6%, an F1 score of 81.6%, and an AUC of 88.2%, demonstrating its practical applicability. Moreover, monthly fire zoning analysis reveals that high-incidence areas in spring and winter are mainly concentrated in Guangdong, Fujian, Zhejiang, and Hainan, while autumn shows widespread medium-incidence areas, and summer presents lower fire occurrences in most regions. These findings illustrate the influence of seasonal climate variations on fire occurrences and highlight the necessity for enhanced fire monitoring and prevention measures tailored to different seasons.

Learning in the gray zone: Harmful organizational learning from safety deviations in nuclear power plants

Organizations often encounter safety deviations, events that diverge from established safety standards without causing substantial harm. Despite their critical role in preventing severe safety incidents, organizational learning from safety deviations has been understudied. We propose that safety deviations lead to harmful learning due to decision-makers’ self-enhancement tendencies and normalization of these deviations, which facilitates future safety incidents. Our analysis of global nuclear power plants from 1990 to 2017, representing high-reliability organizations, supports this argument. Additionally, we demonstrate that institutional factors significantly mitigate the harmful effects of learning from safety deviations. This study advances the organizational learning literature by distinguishing learning from safety deviations from that derived from safety failures. Finally, we discuss practical implications for fostering safer organizations and societies.

Elucidating the harm potential of brorphine analogues as new synthetic opioids: Synthesis, in vitro, and in vivo characterization

The emergence of new synthetic opioids (NSOs) has added complexity to recreational opioid markets worldwide. While NSOs with diverse chemical structures have emerged, brorphine currently remains the only NSO with a piperidine benzimidazolone scaffold. However, the emergence of new generations of NSOs, including brorphine analogues, can be anticipated. This study explored the pharmaco-toxicological, opioid-like effect profile of brorphine alongside its non-brominated analogue (orphine) and three other halogenated analogues (fluorphine, chlorphine, iodorphine). In vitro, radioligand binding assays in rat brain tissue indicated that all analogues bind to the μ-opioid receptor (MOR) with nM affinity. While analogues with smaller-sized substituents showed the highest MOR affinity, further in vitro characterization via two cell-based (HEK 293T) MOR activation (β-arrestin 2 and mini-Gαi recruitment) assays indicated that chlorphine, brorphine, and iodorphine were generally the most active MOR agonists. None of the compounds showed significant in vitro biased agonism compared to hydromorphone. In vivo, we investigated the effects of intraperitoneal (IP) administration of the benzimidazolones (0.01–15 mg/kg) on mechanical and thermal antinociception in male CD-1 mice. Chlorphine and brorphine overall induced the highest levels of antinociception. Furthermore, the effects on respiratory changes induced by a fixed dose (15 mg/kg IP) of the compounds were investigated using non-invasive plethysmography. Fluorphine-, chlorphine-, and brorphine-induced respiratory depressant effects were the most pronounced. For some compounds, pretreatment with naloxone (6 mg/kg IP) could not reverse respiratory depression. Taken together, brorphine-like piperidine benzimidazolones are opioid agonists that have the potential to cause substantial harm to users should they emerge as NSOs.This article is part of the Special Issue on "Novel Synthetic Opioids (NSOs)".

Drug administration errors among anaesthesia providers in South Africa: a cross-sectional descriptive study

BackgroundDrug administration errors (DAEs) in anaesthesia are common, the aetiology multifactorial and though mostly inconsequential, some lead to substantial harm. The extend of DAEs remain poorly quantified and effective implementation of prevention strategies sparse.MethodA cross-sectional descriptive study was conducted using a peer-reviewed survey questionnaire, circulated to 2217 anaesthetists via a national communication platform. The aim was to determine the self-reported frequency, nature, contributing factors and reporting patterns of DAEs among anaesthesia providers in South Africa.ResultsOur cohort had a response rate was 18.9%, with 420 individuals populating the questionnaire. 92.5% of surveyed participants have made a DAE and 89.2% a near-miss. Incorrect route of administration, potentially resulting in serious harm, accounted for 8.2% (n = 23/N = 279) of these errors. DAEs mostly reported in cases involving adult patients (80.5%, n = 243/N = 302), receiving a general anaesthetic (71.8%, n = 216/N = 301), where the drug-administrator prepared the drugs themselves (78.7%, n = 218/N = 277), during normal daytime hours (69.9%, n = 202/N = 289) with good lightning conditions (93.0%, n = 265/N = 285). 26% (n = 80/N = 305) of DAEs involved ampoule misidentification, whilst syringe identification error reported in 51.6% (n = 150/N = 291) of cases. DAEs are often not reported (40.3%, n = 114/N = 283), with knowledge of correct reporting procedures lacking. 70.5% (n = 198/N = 281) of DAEs were never discussed with the patient.ConclusionsDAEs in anaesthesia remain prevalent. Known error traps continue to drive these incidents. Implementation of system based preventative strategies are paramount to guard against human error. Efforts should be made to encourage scrupulous reporting and training of anaesthesia providers, with the aim of rendering them proficient and resilient to handle these events.

Extraction of vegetation disturbance range using aboveground biomass estimated from Sentinel-2 imagery in coal mining areas with high groundwater table.

Coal mining in regions characterized by high groundwater table markedly predisposes to surface subsidence and water accumulation, thereby engendering substantial harm to surface vegetation, soil, and hydrological resources. Developing effective methods to extract surface disturbance information aids in quantitatively assessing the comprehensive impacts of coal mining on land, ecology, and society. Due to the shortcomings of traditional indicators in reflecting mining disturbance, vegetation aboveground biomass (AGB) is introduced as the primary indicator for extracting the mining disturbance range. Taking the Huaibei Coal Base as an example, Sentinel-2 MSI imagery is firstly used to calculate spectral factors and vegetation indices. Multiple machine learning algorithms are coupled to perform remote sensing estimation and spatial inversion of vegetation AGB based on measured samples of vegetation AGB. Secondly, an Orientation Distance-AGB (OD-AGB) curve is constructed outward from the center of subsidence water areas (SWA), with the Boltzmann function used for curve fitting. According to the location of the inflection point of the curve, the boundary points of vegetation disturbance are identified, and then the disturbance range is divided. The results show that (1) the TV-SVM model, utilizing total variables and support vector machine, achieves the highest estimation accuracy, with σMAE and σRMSE values of 208.47g/m2 and 290.19g/m2, respectively, for the validation set. (2) Thirty-six effective disturbance areas, totaling 29.89 km2, are identified; the Boltzmann function provides a good fit for the OD-AGB curve, with an R2 exceeding 0.8 for typical disturbance areas. (3) Analysis of general statistical laws indicates that disturbance distance conforms to the general characteristics of normal distribution, exhibiting boundedness and directional heterogeneity. The research is expected to provide scientific guidance for hierarchical zoning management, land reclamation, and ecological restoration in coal mining areas with high groundwater table.

Hybrid Digital Certificate Management System with QR Code and IoT Integrated on Hyperledger Fabric Blockchain

In contemporary society, management of physical documents such as educational certificates, identity proofs, vehicle registrations, and marriage certificates is an integral part of daily life. However, in present online world, there is a pressing need for digital transformation and the management of these documents. One significant challenge associated with this transformation is the susceptibility of original documents to replication or duplication. This vulner- ability is particularly concerning in the case of educational certificates, where fraud is prevalent. Fraudulent activities in the education sector can influence the proliferation of counterfeit educational and skill certificates, posing serious risks to society. For instance, individuals holding fraudulent degrees in professions such as engineering, medicine, law, and pharmacy may lack genuine competence, thereby posing substantial societal harm. To address the issue of certificate oversight and deter forgery, various approaches have been employed. Traditional methods typically involve the use of centralized databases or web servers for certificate storage, which introduces vulnerabilities because they represent single points of failure that leads to forgery and information loss. An optimal solution lies in the adoption of a Blockchain system that leverages a decentralized database structure to enhance data storage capacity and security. Blockchain technology has demonstrated disruptive potential and in- novative capabilities across multiple sectors because of its decentralized, transparent, and secure attributes. Its impact spans various domains, including banking, supply chain management, healthcare, education, and finance. Notably, in the education sector, Blockchain technology holds promise in enhancing security, transparency, and efficiency across different educational processes. In this study, we explore existing Blockchain oriented certificate management systems, critically analyze their limitations, and propose a novel hybrid educational certificate management model. The proposed model integrates Hyperledger Fabric, IoT, and 2D Barcode to develop a robust and secure framework for managing educational certificates.

Identification and Functional Analysis of Odorant Binding Proteins in Apriona germari (Hope).

Apriona germari (Hope) presents a significant threat as a dangerous wood-boring pest, inflicting substantial harm to forest trees. Investigating the olfactory sensory system of A. germari holds substantial theoretical promise for developing eco-friendly control strategies. To date, however, the olfactory perception mechanism in A. germari remains largely unknown. Therefore, we performed transcriptome sequencing of A. germari across four distinct body parts: antennae, foreleg tarsal segments, mouthparts (maxillary and labial palps), and abdomen terminals, pinpointing the odorant binding protein (OBP) genes and analyzing their expression. We found eight AgerOBPs (5, 19, 23, 25, 29, 59, 63, 70) highly expressed in the antennae. In our competitive binding experiments, AgerOBP23 showed strong binding abilities to the pheromone component fuscumol acetate, eight plant volatiles (farnesol, cis-3-hexenal, nerolidol, myristol acetate, cis-3-hexenyl benzoate, (-)-α-cedrene, 3-ethylacetophenone, and decane), and four insecticides (chlorpyrifos, phoxim, indoxacarb, and cypermethrin). However, AgerOBP29 and AgerOBP63 did not show prominent binding activities to these tested chemicals. Through homology modeling and molecular docking, we identified the key amino acid sites involved in the binding process of AgerOBP23 to these ligands, which shed light on the molecular interactions underlying its binding specificity. Our study suggests that AgerOBP23 may serve as a potential target for future investigations of AgerOBP ligand binding. This approach is consistent with the reverse chemical ecology principle, establishing the groundwork for future studies focusing on attractant or repellent development by exploring further the molecular interactions between OBP and various compounds.

Is high exposure to antisocial media content associated with increased participation in malicious online trolling? exploring the moderated mediation model of hostile attribution bias and empathy

Malicious online trolling is prevalent among Chinese college students and has recently garnered extensive attention from researchers due to the substantial harm it causes to the victims and the damage it inflicts on the online environment. Most previous studies have focused on examining how personal traits related to malicious online trolling. Further comprehensive research is needed to explore the mechanisms linking external environmental factors (antisocial media exposure) and malicious online trolling. A total of 1259 Chinese college students completed questionnaires regarding malicious online trolling, antisocial media exposure, hostile attribution bias, and empathy. The results indicated a positive association between antisocial media exposure and malicious online trolling among Chinese college students, with hostile attribution bias serving as a mediating factor. Furthermore, the direct and mediated paths between antisocial media exposure and malicious online trolling were moderated by empathy. Specifically, as the level of empathy increased among college students, the relations between the variables all weakened. Excessive exposure to antisocial media content among college students may trigger hostile attribution bias and lead to more malicious online trolling behavior. However, the relation between antisocial media exposure and malicious online trolling, hostile attribution bias and malicious online trolling, was attenuated when college students’ empathy levels were high.

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.

Mapping the shoreline risk assessment of oil spill in the eastern region of Qeshm channel

The northern shores of the Strait of Hormuz constitute one of the most diverse shorelines in the Persian Gulf, characterized by both utility and environmental richness. Situated in the Qeshm channel, which hosts the largest mangrove habitat, major industries, and commercial port, these shores are subject to the occurrence of oil spills, posing potential substantial harm. This study employs General NOAA Operational Modeling Environment (GNOME) and numerical modeling to assess the potential risks to shorelines from hypothetical oil spills, considering the distinctive features of the shores and their environmental sensitivity. The results indicate that high-risk levels are not excessively prevalent overall and are confined to approximately 24 km. The shape of the channel and hydrodynamic conditions highlight the eastern sector of the Bandar Abbas urban area as particularly susceptible to oil spill entrapment. The findings indicate that high-risk areas are predominantly located away from industrial-oil shores and primarily consist of muddy shores. Therefore, internal strategies of Oil Spill Contingency Plan (OSCP) of companies are deemed insufficient and necessitate comprehensive planning initiatives.

The Dilemma of Achieving "Same Case, Same Sentence" in Cases of "Knowing and Buying Counterfeits" in the Field of Food and Drugs and Its Legal Progress

The frequent disparity in judicial rulings for identical cases of "Knowingly Purchasing Counterfeit Goods" within the food and drug sector has significantly undermined the authority of the law and compromised judicial fairness. An empirical study of 100 randomly selected judicial decisions from Shandong Province reveals that the current level of uniformity in judgments for equivalent cases is less than ideal. To delve deeper into the factors influencing these inconsistencies, this paper conducts an analysis of the suspicion of counterfeit awareness, the burden of proof, and the nature of the appellate case, utilizing the chi-square test for independence. Challenges such as establishing consumer identity, defining fraudulent behavior, and evaluating the standards of food safety are pivotal issues that impede the equitable treatment of knowingly purchasing counterfeit goods within the food and drug sector. In this distinct domain, the act of knowingly purchasing counterfeit goods, despite potential associations with professional racketeering, often yields a more constructive outcome. If it is determined that the parties involved are not engaged in commercial operations, their status as consumers should be acknowledged. When assessing food safety standards, emphasis should be placed on substantive criteria rather than mere formalities. Moreover, the presence of substantial harm should not be a mandatory threshold for the application of punitive damages. Additionally, if an operator fails to fulfill their evidentiary responsibilities or demonstrates "knowledge" of the counterfeit goods, the consumer's claim for compensation should be upheld.

Volatile vs Total intravenous Anaesthesia for major non-cardiac surgery: a pragmatic randomised triaL (VITAL)

BackgroundImproving outcomes after surgery is a major public health research priority for patients, clinicians and the NHS. The greatest burden of perioperative complications, mortality and healthcare costs lies amongst the population of patients aged over 50 years who undergo major non-cardiac surgery. The Volatile vs Total Intravenous Anaesthesia for major non-cardiac surgery (VITAL) trial specifically examines the effect of anaesthetic technique on key patient outcomes: quality of recovery after surgery (quality of recovery after anaesthesia, patient satisfaction and major post-operative complications), survival and patient safety.MethodsA multi-centre pragmatic efficient randomised trial with health economic evaluation comparing total intravenous anaesthesia with volatile-based anaesthesia in adults (aged 50 and over) undergoing elective major non-cardiac surgery under general anaesthesia.DiscussionGiven the very large number of patients exposed to general anaesthesia every year, even small differences in outcome between the two techniques could result in substantial excess harm. Results from the VITAL trial will ensure patients can benefit from the very safest anaesthesia care, promoting an early return home, reducing healthcare costs and maximising the health benefits of surgical treatments.Trial registrationISRCTN62903453. September 09, 2021.