Level Of Risk Research Articles

Effects of immunosuppressive therapy on renal prognosis in primary membranous nephropathy

BackgroundImmunosuppressive therapy plays a crucial role in treating membranous nephropathy, with previous studies highlighting its benefits for patients with primary membranous nephropathy (PMN). Guidelines suggest that the management of membranous nephropathy should be tailored to individual risk levels. However, there is a lack of real-world studies examining the effects of immunosuppressive therapy on renal outcomes in PMN patients. This study aimed to investigate the relationship between immunosuppressive therapy and renal prognosis in PMN patients.MethodsThis was a real-world retrospective study including patients diagnosed with PMN in Shenzhen Second People’s Hospital and Hechi People’s Hospital. Univariate and multivariate Cox regression analysis and Kaplan-Meier survival analysis were used.ResultsAfter propensity score-matching, 464 PMN patients were included and they were assigned to conservative and immunosuppressive group in a 1:1 ratio. Immunosuppressive therapy was the protective factor of renal composite outcome (HR = 0.65, p < 0.01). Separately, the effect was significant in moderate- and high-risk but not in low-risk patients. Key influencing factors including age, blood pressure, albumin and total cholesterol levels, with slight differences among patients at different risk.ConclusionsThis study demonstrates the efficacy of immunosuppressive therapy in non-low-risk PMN patients. The key factors affecting renal prognosis in patients with different risk levels are emphasized to help provide individualized treatment.

Susceptibility of hydraulic structures to internal erosion: modeling of suffusion process

Internal erosion is a primary cause of hydraulic structure failure, manifesting as two key phenomena: piping erosion and suffusion. These processes differ in their geometrical and hydraulic boundary conditions, resulting in varying levels of failure risk. Piping erosion is the more hazardous and rapid process, often leading to immediate failure if not promptly addressed. In contrast, suffusion gradually alters the permeability of the medium, potentially culminating in failure after a prolonged period of development. In this study, we propose a model for suffusion based on Darcy’s law, Papamichos' erosion law, and Einstein's viscosity evolution relation. The model describes the temporal evolution of the average porosity in the porous medium, the concentration of eroded particles in the fluid, and the mass of particles eroded, while highlighting the impact of hydraulic and mechanical parameters, such as the erosion coefficient and maximum porosity, on this evolution. The numerical solution is obtained using the finite difference method, with the sample discretized into elementary layers. For discretization, an explicit off-centered scheme was adopted. The simulation results reveal that suffusion is strongly influenced by soil hydraulic and mechanical parameters, particularly the erosion coefficient (λ) and final porosity (Ømax).

Chance-constrained stochastic optimal control of epidemic models: A fourth moment method-based reformulation

This work proposes a methodology for the reformulation of chance-constrained stochastic optimal control problems that ensures reliable uncertainty management of epidemic outbreaks. Specifically, the chance constraints are reformulated in terms of the first four moments of the stochastic state variables through the so-called fourth moment method for reliability. Moreover, a spectral technique is employed to obtain surrogate models of the stochastic state variables, which enables the efficient computation of the required statistics. The practical implementation of the proposed approach is demonstrated via the optimal control of two different stochastic mathematical models of the COVID-19 transmission. The numerical experiments confirm that, unlike those reformulations based on the Chebyshev–Cantelli’s inequality, the proposed method does not exhibit the undesired outcomes that are typically observed when a higher precision is required for the risk level associated to the given chance constraints.

The use and usefulness of the Peninsula Health Falls Risk Assessment Tool (PHFRAT) process in residential aged care: a mixed methods study across 25 aged care facilities

BackgroundFalls remain a persistent problem in residential aged care (RAC) facilities. Fall screening and assessment tools such as the Peninsula Health Falls Risk Assessment Tool (PHFRAT) are widely used to inform falls risk and guide fall prevention interventions. However, it is unclear how it is used in practice and whether clinicians believe it supports resident care. This study aimed to measure the extent of use of PHFRAT to understand clinicians’ perceptions of its value and usefulness.MethodsThis mixed method study involved an analysis of PHFRAT assessment from 25 RAC facilities in New South Wales, Australia, and interviews with seven RAC staff about how PHFRAT information is used in practice. In the quantitative component, descriptive statistics were applied to PHFRAT data to summarise how RAC staff use the PHFRAT including the completeness and content of the three parts. In the qualitative component, thematic analysis techniques were applied to interview data.ResultsThe sample included 215 RAC residents with 703 PHFRATs, of which 617 documented fall prevention interventions. Among these 617 PHFRATs, 593 (96.1%) included strategies related to staff assistance and 283 (45.9%) recorded strategies related to device provision. While nearly all residents (96.74%) received at least one PHFRAT assessment over the study period, many PHFRAT assessments were incomplete (part 1: 11.5% of information missing; part 2: 10.8%; part 3: 17.1%). There were few variations in fall interventions prescribed to individual residents by their fall risk level. Interviews with RAC staff indicated that PHFRAT assessments are the responsibility of registered nurses with limited input from other staff or residents. While the structured process was viewed positively in guiding risk assessment and intervention assessment, a lack of input from others prevented strategies from being tailored to residents’ specific needs and preferences. A shortage of resources, lack of communication, and limited staff education were identified as the main barriers to PHFRAT guideline implementation.ConclusionThe PHFRAT provides a useful structure for clinicians to assess falls risk factors and plan falls prevention strategies. In the future, increased multidisciplinary input into fall prevention strategy development may improve the comprehensiveness of fall prevention plans.

Optimizing the Measurement of Information on the Context of Alcohol Consumption Within the Drink Less App Among People Drinking at Increasing and Higher Risk Levels: Mixed-Methods Usability Study.

There is a growing public health evidence base focused on understanding the links between drinking contexts and alcohol consumption. However, the potential value of developing context-based interventions to help people drinking at increasing and higher risk levels to cut down remains underexplored. Digital interventions, such as apps, offer significant potential for delivering context-based interventions as they can collect contextual information and flexibly deliver personalized interventions while addressing barriers associated with face-to-face interventions, such as time constraints. This early phase study aimed to identify the best method for collecting information on the contexts of alcohol consumption among users of an alcohol reduction app by comparing 2 alternative drinking diaries in terms of user engagement, data quality, usability, and acceptability. Participants were recruited using the online platform Prolific and were randomly assigned to use 1 of the 2 adapted versions of the Drink Less app for 14 days. Tags (n=31) included tags for location, motivation, and company that participants added to drink records. Occasion type (n=31) included a list of occasion types that participants selected from when adding drink records. We assessed engagement and data quality with app data, usability with a validated questionnaire, and acceptability with semistructured interviews. Quantitative findings on engagement, data quality, and app usability were good overall, with participants using the app on most days (tags: mean 12.23, SD 2.46 days; occasion type: mean 12.39, SD 2.12 days). However, around 40% of drinking records in tags did not include company and motivation tags. Mean usability scores were similar across app versions (tags: mean 72.39, SD 8.10; occasion type: mean 74.23, SD 6.76). Qualitative analysis found that both versions were acceptable to users and were relevant to their drinking occasions, and participants reported increased awareness of their drinking contexts. Several participants reported that the diary helped them to reduce alcohol consumption in some contexts (eg, home or lone drinking) more than others (eg, social drinking) and suggested that they felt less negative affect recording social drinking contexts out of their home. Participants also suggested the inclusion of "work drinks" in both versions and "habit" as a motivation in the tags version. There was no clearly better method for collecting data on alcohol consumption as both methods had good user engagement, usability, acceptability, and data quality. Participants recorded sufficient data on their drinking contexts to suggest that an adapted version of Drink Less could be used as the basis for context-specific interventions. The occasion type version may be preferable owing to lower participant burden. A more general consideration is to ensure that context-specific interventions are designed to minimize the risk of unintended positive reinforcement of drinking occasions that are seen as sociable by users.

Consumer Risk in the Purchasing Process in the Organic Food Market

Risk is an inherent part of our lives and every action we take. It accompanies us in various areas of our lives. Each of us encounters risk in everyday life by undertaking and performing specific activities or actions. Risk is not always perceived by us; there are situations when we do not notice it in our actions. The main objective of this article is to identify and assess the factors influencing the level of risk in consumer purchasing decisions in the organic products market. Additionally, it aims to indicate the desired directions of actions taken by producers and suppliers of organic food to reduce the risk associated with the purchasing process perceived by consumers. The research process took into account existing scientific achievements and the survey method, chosen due to the subject and nature of the research. The survey was addressed to consumers from the Lubuskie Voivodeship and was anonymous. The conducted research shows that the greatest risk perceived by consumers is in the case of online purchases, and the way to reduce this risk is through buyer loyalty to the place of purchase. The empirical research also provides grounds to assume that there is a relationship between individual types of risk. The research shows that respondents are most afraid of safety and social risk, and the least afraid of the risk of losing too much time. Consumers who want to reduce the risk use their own experiences or positive opinions about the product. The results provide valuable information for producers and suppliers of organic food who want to build lasting relationships with consumers based on trust and loyalty. The higher the trust, the greater the customer loyalty, and the lower the perceived risk.

Risk Factors for Developing Occupational Back Pain in Electronics Industry Workers: A Cross-Sectional Study

Back pain is an occupation-related problem among workforces. This cross-sectional study aimed to identify the prevalence of back pain and the risk factors of occupational back pain among workers in the electronics industry. In total, 354 electronics workers in Thailand participated in the study. Data were collected using the Musculoskeletal Disorders Severity and Frequency Questionnaire, the Job Content Questionnaire, and ergonomics risk assessment via the Rapid Upper Limb Assessment (RULA). Risk factors of back pain were identified by multiple logistic regression analysis, providing adjusted odds ratios (ORadj) and 95% confidence intervals (95% CI). The study found that most workers were operators (92.09%) and had repetitive work (83.62%). A high ergonomics risk was observed in workers who stood during work (68.49%) and operated machines (71.70%). The 1-month prevalence of developing back pain was 20.62% and the significant factors correlated with back pain were low levels of job control and decision-making (ORadj = 2.26; 95% CI [1.26 ,4.05]), lack of exercise (ORadj = 8.30; 95% CI [1.35, 24.28]), repetitive work (ORadj = 2.94; 95% CI [1.19, 7.29]), and high ergonomic risk level (ORadj = 2.81; 95% CI [1.16, 5.07]). These findings suggest that measures should be implemented by empowering electronics workers to make decisions and control their jobs, as well as promoting health through muscle-stretching exercise, to support back pain prevention.

Ruxolitinib plus steroids for acute graft versus host disease: a multicenter, randomized, phase 3 trial

Newly diagnosed patients with high-risk acute graft-versus-host disease (aGVHD) often experience poor clinical outcomes and low complete remission rates. Ruxolitinib with corticosteroids showed promising efficacy in improving response and failure free survival in our phase I study. This study (ClinicalTrials.gov: NCT04061876) sought to evaluate the safety and effectiveness of combining ruxolitinib (RUX, 5 mg/day) with corticosteroids (1 mg/kg/day methylprednisolone, RUX/steroids combined group) versus using methylprednisolone alone (2 mg/kg/day, steroids-only group). Newly diagnosed patients with intermediate- or high-risk aGVHD were included, with risk levels classified by either the Minnesota aGVHD Risk Score or biomarker assessment. Patients were randomized in a ratio of 1:1 into 2 groups: 99 patients received RUX combined with methylprednisolone, while the other 99 received methylprednisolone alone as the initial treatment. The RUX/steroids group showed a significantly higher overall response rate (ORR) on day 28 (92.9%) compared to the steroids-only group (70.7%, Odds Ratio [OR] = 5.8; 95% Confidence Interval [CI], 2.4–14.0; P < 0.001). Similarly, the ORR on day 56 was higher in the RUX/steroids group (85.9% vs. 46.5%; OR = 7.07; 95% CI, 3.36–15.75; P < 0.001). Additionally, the 18-month failure-free survival was significantly better in the RUX/steroids group (57.2%) compared to the steroids-only group (33.3%; Hazard Ratio = 0.46; 95% CI, 0.31–0.68; P < 0.001). Adverse events (AEs) frequencies were comparable between both groups, with the exception of fewer grade 4 AEs in the RUX/steroids group (26.3% vs. 50.5% P = 0.005). To our knowledge, this study is the first prospective, randomized controlled trial to demonstrate that adding ruxolitinib to the standard methylprednisolone regimen provides an effective and safe first-line treatment for newly diagnosed high-risk acute GVHD.

Outcomes of primary transobturator mid-urethral sling surgery in women of different ages

IntroductionOlder age is associated with greater likelihood of urinary incontinence and unmet care needs. It was hypothesized that age might influence clinical and ultrasound outcomes of transobturator mid-urethral sling (TOS) surgery. The aim of this study was to compare 1-year postoperative clinical and ultrasonographic outcomes of TOS surgery among women of different ages. MethodsA retrospective analysis of a cohort of women who underwent primary and isolated TOS surgery for uncomplicated urodynamic stress incontinence was undertaken. All women underwent pre-operative and 1-year postoperative evaluations including clinical interview, pelvic examination, urodynamic studies and introital four-dimensional ultrasound. To be eligible for surgery, women needed to be independent in their daily life, and to have an acceptable level of surgical risk on pre-operative assessment. The primary outcome was the rate of stress urinary incontinence (SUI) after surgery. The secondary outcomes comprised postoperative adverse events and ultrasound findings. ResultsIn total, 162, 213, 60 and 29 women aged <51, 51–64, 65–74 and ≥75 years, respectively, were included in this study. At 1-year postoperative assessment, older women were more likely to report SUI and bothersome SUI, while the severity of SUI and postoperative adverse events were similar in older women compared with other age groups. Ultrasound revealed that the sling tended to be looser and higher in older women. ConclusionTOS surgery is effective and safe for women of all ages who are independent in their daily life and who have an acceptable level of surgical risk. The sling tended to be looser and higher in older women.

Do enhanced school zone policies improve pedestrians' safety? A deep learning-based case study of Osan City, South Korea

This study investigates the effectiveness of strengthened penalty policies in South Korean school zones by analyzing the changes in road users' behaviors, focusing on pedestrian-vehicle interactions. This study employed three surrogate safety measurements: vehicle speed, Pedestrian Safety Margins (PSM), and Predicted Collision Risk (PCR) level. The comprehensive analysis covers a spectrum of behaviors, from simple to complex, assessing the policy's impact in urban environments. The findings reveal several important insights. First, the policy enforcement resulted in a positive impact on vehicle speeds, with average speeds aligning with posted speed limits. Second, an increase was observed in yielding behaviors, particularly in school zones. However, much of this behavior appeared to be cosmetic, emphasizing the need for more safety-oriented yielding practices. Finally, the policy enforcement had a mixed impact on PCR levels, with a reduction in danger levels in school zones, yet an unexpected increase in danger levels in non-school zones. This study provides valuable insights into the effectiveness of strengthened penalty policies in school zones, particularly the development of a safe and sustainable urban environment.

Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost

With the rapid development of electric vehicles, the infrastructure for charging stations is also expanding quickly, and the failure rate of charging piles is increasing. To address the effective operation and maintenance of charging stations, a method based on the XGBoost algorithm for electric vehicle DC charging stations is proposed. An operation and maintenance system is constructed based on state analysis, considering the operational status of the charging stations and users’ charging habits. Factors such as driving and charging habits, road traffic, and charging station equipment are taken into account. The training sample data are established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. Based on the condition assessment results, a risk assessment model is established in combination with fault parameters. Risk tracking of the charging stations is conducted using the energy not charged (ENC), evaluating the risk level of each station and determining the operation and maintenance order. The optimal operation and maintenance model for DC charging stations, aimed at achieving both economic and reliability goals, is constructed to determine the operation and maintenance schedule for each station. The results of the case study demonstrate that the state evaluation and operation and maintenance strategy can significantly improve the reliability of the system and the overall benefits of operation and maintenance while meeting the required standards.

Multi-hazard risk assessment analysis in La Palma: an approach for risk mitigation

BackgroundLa Palma, like many regions of the world, may be affected by various hazards, with different levels of susceptibility, which have a greater or lesser impact on society. In this context, a multi-risk approached model capable of estimating the total risk faced by the territory is required, considering the different hazards to which it is exposed (floods, earthquakes, volcanic eruptions and landslides) and the different conditions of vulnerability of both the population and the exposed assets.MethodsThe methodology employed in this study has been referred to as "multilayer single hazard", which consists of the aggregation or superposition of hazards located in the same space. As usual, the identification of the individual hazard of each one of them was carried out using heterogeneous methods, which is why an index is proposed to homogenize the hazards and make them comparable with each other. On the other hand, the model also integrates a prototype to evaluate vulnerability from a multiple perspective (vulnerability by hazard) and shows the aggregated information in maps at a medium representation scale (definition of 250 m).ResultsThe risk integration results show that 5% of the island is at high risk levels. Simultaneously, the south of the island is presented as the area that shows the highest risk by combining a high hazard, especially related to volcanic hazards, and a high exposure, as it is home to a significant volume of population.ConclusionsThe proposed methodology is also interesting because it can be replicated in other areas of study.

Weighted Naïve Bayes Multi-User Classification for Adaptive Authentication

Abstract Machine learning classification algorithms have been extensively utilized in addressing user authentication challenges. Nonetheless, a majority of solutions categorize users into three classes, whereas adaptive authentication scenarios necessitate classification beyond this threshold. The rationale behind this limitation has not been thoroughly explored. The current study leveraged the Naive Bayes theorem for user authentication endeavors to assess the risk associated with login attempts. The Naive Bayes Machine Learning algorithm, along with its variations such as Gaussian, Categorical, and Bernoulli, was applied on both weighted and unweighted datasets to ascertain risk levels and categorize them into six classes. Additionally, the classification task was executed using alternative algorithms. The outcomes of cross-validation and comparative analyses revealed that the performance was commendable for up to three classes, after which a decrease was observed in certain Naive Bayes and SVM classifiers. Among the Naïve Bayes family, the Bernoulli NB algorithm exhibited superior performance but was surpassed by Decision Trees, SVM, XGB, and Random Forests. Notably, the weighted dataset consistently outperformed the unweighted counterpart, with the allocation of weights significantly influencing algorithmic efficacy. The 80:20 split strategy yielded the most favorable outcomes in contrast to the 70:30 and 60:40 splits, albeit no significant variances were detected during cross-validation. Non-Naïve Bayes algorithms demonstrated superior performance compared to Naïve Bayes algorithms. For Naïve Bayes, optimal performance is achieved with three classes, highlighting its utility in conditional risk calculation, while non-Naïve Bayes multi-classification algorithms are more suitable for classification tasks due to the problem's inherent compatibility with conditional probabilities. In conclusion, it is imperative to acknowledge that the characteristics of the data, the use of weights, and the data splitting methodology significantly influence the accuracy of machine learning algorithms in multi-class user classification.

Can an Expert Opinion Mitigate Racially Biased Diversion Decisions? An Empirical Examination in the Context of Re-Offense Risk Assessment

Using a vignette-based experimental design, this study tested whether the racial or ethnic identity of a justice-impacted person influences jury-eligible individuals’ perceptions of post-conviction risk, placement (incarceration vs. community supervision), and need for mandated treatment. Furthermore, we examined whether the inclusion of data from a reoffense risk tool could mitigate racial bias. Participants recruited through Amazon’s MTurk ( N = 448) were randomly assigned to conditions varying by race/ethnicity of an examinee (Black, Latino, White) and if/how risk assessment data were included (no risk data, risk data only, and risk data reported by a qualified examiner). There was no statistically significant effect of the examinee’s racial/ethnic identity on ratings of reoffense risk or placement decisions; however, the Black examinee was more likely to be mandated with treatment. Regardless of examinee identity, participants exposed to risk information proffered by an expert more often calibrated their risk decisions to the examinee’s actual risk level.

Modeling risky portfolios with guaranteed maximize returns under a patent race

This paper studies the patent race problem of communication enterprises investing in communication technologies, and constructs a portfolio optimization model which considers the expected returns, investment risks, and replacement costs, in order to achieve the dual goals of maximizing the net investment income of backward enterprises and minimizing the expected investment risk. Through numerical experimental analysis, the optimal investment portfolio strategy under different risk levels and the impact of different risk levels on the net income of lagging company are obtained. The research results show that due to the backward research in the first stage of the backward enterprises, when their own investment decision-making power is relatively high, they can focus on the development of self-interested key technology areas in order to achieve the victory of the patent race.

The structured assessment of violence risk in youth demonstrates measurement invariance between Black and White justice-referred youths.

Identification and implementation of effective methods for reducing racial/ethnic bias and disparities in legal settings are paramount in the United States and other countries. One procedure originally thought to reduce bias in legal decisions is the use of risk assessment instruments, which is now being heavily scrutinized. Measurement invariance, a latent trait technique, is a robust method for assessing one form of bias. Measurement invariance involves determining whether risk items in an instrument appear to be functioning the same between racial or other groups. Thus, the present study examined measurement invariance of the Structured Assessment of Violence Risk in Youth (SAVRY) between non-Latino Black and White youths to examine racial bias. We expected the SAVRY to be invariant (lacking measurement bias) between Black and White youths. The sample included 687 Black and 361 White youths, and the study used a large, multistate data set of SAVRYs conducted by probation officers. We conducted measurement invariance testing in a series of hierarchical steps including testing configural and scalar invariance. The SAVRY demonstrated scalar invariance (equal thresholds for ratings from "low" to "moderate" and "moderate" to "high") for all items except one-community disorganization. The findings lend further credibility to the SAVRY, and the structured professional judgment approach, as a method to assess violence risk and case planning needs among youths involved in the legal system. These findings provide more confidence that significant differences in SAVRY risk level or items between Black and White youths are not based in measurement bias, with the exception of the community disorganization item. Potential fixes discussed include eliminating or deemphasizing this item in final risk level ratings. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Candidemia in Pediatric-Clinic: Frequency of Occurrence, Candida Species, Antifungal Susceptibilities, and Effects on Mortality (2020-2024).

Objective: Invasive candidiasis is defined as an important infection that increases the duration of patients' hospital stay, costs, mortality and morbidity. In this study, we aimed to investigate the frequency of candidiasis in blood cultures of pediatric hematology patients, Candida species, antifungal susceptibilities, and their effects on mortality. Materials and Methods: Patients with Candida growth in their blood cultures at follow-up in the pediatric hematology clinic of our hospital between 2020 and 2024 were included in the study. Age, gender, primary diseases and risk levels, subtypes and antifungal susceptibilities of Candida grown in blood cultures, the presence of neutropenia in patients, the antifungals used for prophylaxis and treatment, the duration of infection, other bacteria grown additionally during the fungal infection period, the local infection source and the patients' discharge status were obtained from medical records. These constituted the study data. Results: Blood cultures were requested for 594 patients from the Pediatric hematology Clinic, and Candida was grown in only 37 (6.7%) of them. A total of 43.2% of them were the Candida parapsilosis complex, 29.7% were Candida albicans and 8.1% were the Candida haemulonii complex. Antifungal susceptibilities were over 90% for anidulafungin, micafungin, caspofungin, posaconazole, itraconazole and amphotericin B, followed by 86.7% for fluconazole and 84.4% for voriconazole. The mean age of the patient group was 6.8 years, 50.5% of whom were female and 40.5% of whom were male. The Candida infections developed on the 12.1th day of the neutropenia process on average. The mean invasive Candida infection period was 7 days. A total of 18.9% had a second bacterial infection and 13.5% had a local infection. A total of 51.4% had a single antifungal, 18.9% had two antifungals and 2.1% had more than two antifungals. A total of 35.1% of the patients with invasive candidiasis died. The primary diagnosis of the disease, Patient risk level, and the female gender were important factors affetting mortality. Conclusions: In a pediatric hematology clinic, the non-albicans group in invasive candidiasis infections was notable, with the C. parapsilosis complex occurring most frequently. There was still a high sensitivity to echinocandin antifungals and a decreased sensitivity to triazoles. It was found that the factor of the clinical diagnosis, being in the high-risk group and being female had significant effects on the survival rate of patients with candidiasis infections.

Use of the Pesticide Toxicity Index to Determine Potential Ecological Risk in the Santiago-Guadalajara River Basin, Mexico

The Santiago-Guadalajara River Basin (SGRB), located in western Mexico, is one of the most polluted rivers in the country. A pesticide monitoring program was carried out from January 2022 to September 2022, during which time water samples collected at 25 sites in the main stem and tributaries revealed the presence of 13 of the 24 pesticides analyzed, including α-BHC, β-BHC, γ-BHC (Lindane), γ-Chlordane, Hexachlorobenzene, Heptachlor, Aldrin, α-Endosulfan, DDT, -4,4, Methoxychlor, Chlorpyrifos-methyl, Endosulfan sulfate, and Dicofol. A high level of correlation was found between the identified pesticides, which could mean that several of these pesticides reached a stable level within the monitored water bodies. Most of the identified pesticides are classified as high environmental risk according to the Stockholm Convention because of their persistence and high degree of toxicity to the environment and human health. A Pesticide Toxicity Index (PTI) was applied to identify the streams considered to be of concern due to the presence of pesticides exceeding the threshold limits established by national and international guidelines. Performing a calculation for the entire Santiago-Guadalajara River Basin, the PTI reached a value of 0.833, which, according to the criteria of this method, classifies it as a “Moderate” level of risk for aquatic life. Increased regulatory and surveillance measures by state and federal authorities are required to prevent the use of these pesticides, which have been restricted globally.

Frontier AI developers need an internal audit function.

This article argues that frontier artificial intelligence (AI) developers need an internal audit function. First, it describes the role of internal audit in corporate governance: internal audit evaluates the adequacy and effectiveness of a company's risk management, control, and governance processes. It is organizationally independent from senior management and reports directly to the board of directors, typically its audit committee. In the Institute of Internal Auditors' Three Lines Model, internal audit serves as the third line and is responsible for providing assurance to the board, whereas the combined assurance framework highlights the need to coordinate the activities of internal and external assurance providers. Next, the article provides an overview of key governance challenges in frontier AI development: Dangerous capabilities can arise unpredictably and undetected; it is difficult to prevent a deployed model from causing harm; frontier models can proliferate rapidly; it is inherently difficult to assess frontier AI risks; and frontier AI developers do not seem to follow best practices in risk governance. Finally, the article discusses how an internal audit function could address some of these challenges: Internal audit could identify ineffective risk management practices; it could ensure that the board of directors has a more accurate understanding of the current level of risk and the adequacy of the developer's risk management practices; and it could serve as a contact point for whistleblowers. But frontier AI developers should also be aware of key limitations: Internal audit adds friction; it can be captured by senior management; and the benefits depend on the ability of individuals to identify ineffective practices. In light of rapid progress in AI research and development, frontier AI developers need to strengthen their risk governance. Instead of reinventing the wheel, they should follow existing best practices. Although this might not be sufficient, they should not skip this obvious first step.

Infection risk factor measurement based on spatial and temporal distribution of COVID-19 nucleic acid test sites: an example from Shenzhen

COVID-19 has profoundly impacted global daily life, emphasizing the need for effective virus suppression strategies. In response, China has established numerous nucleic acid testing sites to facilitate rapid testing and curb outbreaks. However, these sites often experience congestion, increasing transmission risks and reducing testing efficiency. This study focuses on the spatial–temporal analysis of testing site distribution and associated infection risks in Shenzhen, China. Data from all Shenzhen testing sites were analyzed for the week of October 24–30, 2022, noting the percentage of busy hours per site and incorporating a population size factor by district to assess regional infection risks. Findings indicate three daily peak testing times—primarily in the evening—with the highest risk of transmission in Longgang District, followed by Yantian and Luohu, and the lowest in Futian. The risk coefficient varied from 0.040 to 0.349, with most areas showing stable risk levels between 0.06 and 0.20. This research underlines the necessity for policymakers to alleviate congestion at testing sites and suggests increasing site availability in Longgang District to mitigate COVID-19 spread, offering methodological guidance for managing infection risks in other major Chinese cities.