Risk-and-Resiliency-Intelligent Supply Chain (RRiSC)

This work proposes a risk-and-resiliency-intelligent supply chain (RRiSC) tool which is an SC risk management framework that leverages cutting-edge technologies in Artificial Intelligence (AI), Big Data Analytics (BDA), and Digital Twins (DT) to develop specific capabilities for SC risk management. RRiSC is a convergence of mature tools and techniques embedded in three modules: Modeling, Simulation, and Visualization – all together integrate the optimization, simulation, and data analytics to test the performance of the whole supply network under different scenarios through measuring the vital KPIs, identifying the vulnerabilities, and setting proactive plans to diminish risks consequences

Assessing the Frequency and Severity of Malware Attacks: An Exploratory Analysis of the Advisen Cyber Loss Dataset

In today\u27s business landscape, cyberattacks present a significant threat that can lead to severe financial losses and damage to a company\u27s reputation. To mitigate this risk, it is essential for stakeholders to have an understanding of the latest types and patterns of cyberattacks. The primary objective of this research is to provide this knowledge by utilizing the Advisen cyber loss dataset, which comprises over 137,000 cyber incidents that occurred across various industry sectors from 2013 to 2020. By using text mining techniques, this paper will conduct an exploratory data analysis to identify the most common types of malware, including ransomware. Furthermore, the study will include a likelihood and severity analysis to evaluate the financial impact of these cyberattacks on businesses. Ultimately, this study aims to shed light on the prevalence and financial repercussions of malware incidents and provide businesses with valuable insights to help develop effective cybersecurity strategies

Quality Assessment of Published Systematic Reviews in High Impact Cardiology Journals: Revisiting the Evidence Pyramid

Objective: Systematic reviews are increasingly used as sources of evidence in clinical cardiology guidelines. In the present study, we aimed to assess the quality of published systematic reviews in high impact cardiology journals.Methods: We searched PubMed for systematic reviews published between 2010 and 2019 in five general cardiology journals with the highest impact factor (according to Clarivate Analytics 2019). We extracted data on eligibility criteria, methodological characteristics, bias assessments, and sources of funding. Further, we assessed the quality of retrieved reviews using the AMSTAR tool.Results: A total of 352 systematic reviews were assessed. The AMSTAR quality score was low or critically low in 71% (95% CI: 65.7–75.4) of the assessed reviews. Sixty-four reviews (18.2%, 95% CI: 14.5–22.6) registered/published their protocol. Only 221 reviews (62.8%, 95% CI: 57.6–67.7) reported adherence to the EQUATOR checklists, 208 reviews (58.4%, 95% CI: 53.9–64.1) assessed the risk of bias in the included studies, and 177 reviews (52.3%, 95% CI: 45.1–55.5) assessed the risk of publication bias in their primary outcome analysis. The primary outcome was statistically significant in 274 (79.6%, 95% CI: 75.1–83.6) and had statistical heterogeneity in 167 (48.5%, 95% CI: 43.3–53.8) reviews. The use and sources of external funding was not disclosed in 87 reviews (24.7%, 95% CI: 20.5–29.5). Data analysis showed that the existence of publication bias was significantly associated with statistical heterogeneity of the primary outcome and that complex design, larger sample size, and higher AMSTAR quality score were associated with higher citation metrics.Conclusion: Our analysis uncovered widespread gaps in conducting and reporting systematic reviews in cardiology. These findings highlight the importance of rigorous editorial and peer review policies in systematic review publishing, as well as education of the investigators and clinicians on the synthesis and interpretation of evidence

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Scheduling External Trucks Appointments in Container Terminals to Minimize Cost and Truck Turnaround Times

Background: Scheduling the arrival of external trucks in container terminals is a critical operational decision that faces both terminal managers and trucking companies. This issue is crucial for both stakeholders since the random arrival of trucks causes congestion in the terminals and extended delays for the trucks. The objective of scheduling external truck appointments is not only to control the workload inside the terminal and the costs resulting from the excessive waiting times of trucks but also, to reduce the truck turnaround time. Methods: A binary programming model was proposed to minimize the waiting time cost, demurrage cost, and container delivery cost. Moreover, a sensitivity analysis was performed to compare various scenarios in terms of cost and to study to what extent the workload level is affected. The mathematical model was solved using Gurobi© 8.1.0 software. Results: 30 instances found in the literature were solved and evaluated in terms of the objective function value (i.e., cost) and truck turnaround time before and after controlling the workload inside the container terminal using the new proposed constraint. Conclusions: The obtained results showed a better distribution of the terminal workload, as well as a lower truck turnaround time that reduces the total cost

Scheduling External Trucks Appointments in Container Terminals to Minimize Cost and Truck Turnaround Times

Background: Scheduling the arrival of external trucks in container terminals is a critical operational decision that faces both terminal managers and trucking companies. This issue is crucial for both stakeholders since the random arrival of trucks causes congestion in the terminals and extended delays for the trucks. The objective of scheduling external truck appointments is not only to control the workload inside the terminal and the costs resulting from the excessive waiting times of trucks but also, to reduce the truck turnaround time. Methods: A binary programming model was proposed to minimize the waiting time cost, demurrage cost, and container delivery cost. Moreover, a sensitivity analysis was performed to compare various scenarios in terms of cost and to study to what extent the workload level is affected. The mathematical model was solved using Gurobi© 8.1.0 software. Results: 30 instances found in the literature were solved and evaluated in terms of the objective function value (i.e., cost) and truck turnaround time before and after controlling the workload inside the container terminal using the new proposed constraint. Conclusions: The obtained results showed a better distribution of the terminal workload, as well as a lower truck turnaround time that reduces the total cost

Soy Consumption, but Not Dairy Consumption, Is Inversely Associated with Fatty Acid Desaturase Activity in Young Adults

Past research using hepatic rat microsomes showed that soy protein suppressed delta-6 desaturase activity (D6D) compared to casein (a dairy protein). The effects of soy and dairy on desaturase pathway activity in humans remain poorly investigated. The objective of this analysis was to investigate the association between soy and dairy consumption with plasma fatty acids and estimate the desaturase pathway activity in a multiethnic Canadian population of young adults. We analyzed data from men (n = 319) and women (n = 764) previously collected for the Toronto Nutrigenomics and Health Study. Food frequency questionnaires and plasma fatty acids were assessed. Relationships between soy and dairy beverages and food consumption with estimated desaturase activities were assessed by regression models and by grouping participants according to beverage and food intake data. Weak inverse associations (p ≤ 0.05) were found between soy consumption and the overall desaturation pathway activity, specifically D6D activity. When participants were grouped based on soy and dairy consumption habits, omega-6 LC-PUFAs, as well as various estimates of the desaturase pathway activity, were significantly lower in individuals consuming soy (with or without dairy) compared to individuals consuming only fluid milk and dairy products. In conclusion, soy consumption, not dairy consumption, appears to suppress desaturase pathway activity

The impact of proteostasis dysfunction secondary to environmental and genetic causes on neurodegenerative diseases progression and potential therapeutic intervention

International audienceAggregation of particular proteins in the form of inclusion bodies or plaques followed by neuronal death is a hallmark of neurodegenerative proteopathies such as primary Parkinsonism, Alzheimer’s disease, Lou Gehrig’s disease, and Huntington’s chorea. Complex polygenic and environmental factors implicated in these proteopathies. Accumulation of proteins in these disorders indicates a substantial disruption in protein homeostasis (proteostasis). Proteostasis or cellular proteome homeostasis is attained by the synchronization of a group of cellular mechanisms called the proteostasis network (PN), which is responsible for the stability of the proteome and achieves the equilibrium between synthesis, folding, and degradation of proteins. In this review, we will discuss the different types of PN and the impact of PN component dysfunction on the four major neurodegenerative diseases mentioned earlier

The Association between Plasma Omega-6/Omega-3 Ratio and Anthropometric Traits Differs by Racial/Ethnic Groups and <i>NFKB1</i> Genotypes in Healthy Young Adults

Evidence for a relationship between omega-6/omega-3 (n-6/n-3) polyunsaturated fatty acid (PUFA) ratio and obesity in humans is inconsistent, perhaps due to differences in dietary intake or metabolism of PUFAs between different subsets of the population. Since chronic inflammation is central to obesity and inflammatory pathways are regulated by PUFAs, the objective of this study was to examine whether variants in the NFKB1 gene, an upstream regulator of the inflammatory response, modify the association between the n-6/n-3 ratio (from diet and plasma) and anthropometric traits in a multiethnic/multiracial population of young adults. Participants&#8217; (n = 898) dietary PUFA intake was assessed using a food frequency questionnaire and plasma PUFA concentrations by gas chromatography. Nine tag single nucleotide polymorphisms (SNP) in NFKB1 were genotyped. Significant interactions were found between racial/ethnic groups and plasma n-6/n-3 ratio for body mass index (BMI) (p = 0.02) and waist circumference (WC) (p = 0.007). Significant interactions were also observed between racial/ethnic groups and three NFKB1 genotypes (rs11722146, rs1609798, and rs230511) for BMI and WC (all p &#8804; 0.04). Significant interactions were found between two NFKB1 genotypes and plasma n-6/n-3 ratio for BMI and WC (rs4648090 p = 0.02 and 0.03; rs4648022 p = 0.06 and 0.04, respectively). Our findings suggest that anthropometric traits may be influenced by a unique combination of n-6/n-3 ratio, racial/ethnic background, and NFKB1 genotypes