Impact Of Disruption Research Articles

Mixed-Effects Model to Assess the Effect of Disengagements on Speed of an Automated Shuttle with Sensors for Localization, Navigation, and Obstacle Detection.

The focus of this study is to investigate the underexplored operational effects of disengagements on the speed of an automated shuttle, providing novel insights into their disruptive impact on performance metrics. For this purpose, global positioning system data, disengagement records, weather reports, and roadway geometry data from an automated shuttle pilot program, from July to December 2023, at the University of North Carolina in Charlotte, were collected. The automated shuttle uses sensors for localization, navigation, and obstacle detection. A multi-level mixed-effects Gaussian regression model with a log-link function was employed to analyze the effect of disengagement events on the automated shuttle speed, while accounting for control variables such as roadway geometry, weather conditions, time-of-the-day, day-of-the-week, and number of intermediate stops. When these variables are controlled, disengagements significantly reduce the automated shuttle speed, with the expected log of speed decreasing by 0.803 units during such events. This reduction underscores the disruptive impact of disengagements on the automated shuttle's performance. The analysis revealed substantial variability in the effect of disengagements across different route segments, suggesting that certain segments, likely due to varying traffic conditions, road geometries, and traffic control characteristics, pose greater challenges for autonomous navigation. By employing a multi-level mixed-effects model, this study provides a robust framework for quantifying the operational impact of disengagements. The findings serve as vital insights for advancing the reliability and safety of autonomous systems through targeted improvements in technology and infrastructure.

Large Language Models and Large Multimodal Models in Medical Imaging: A Primer for Physicians.

Large language models (LLMs) are poised to have a disruptive impact on health care. Numerous studies have demonstrated promising applications of LLMs in medical imaging, and this number will grow as LLMs further evolve into large multimodal models (LMMs) capable of processing both text and images. Given the substantial roles that LLMs and LMMs will have in health care, it is important for physicians to understand the underlying principles of these technologies so they can use them more effectively and responsibly and help guide their development. This article explains the key concepts behind the development and application of LLMs, including token embeddings, transformer networks, self-supervised pretraining, fine-tuning, and others. It also describes the technical process of creating LMMs and discusses use cases for both LLMs and LMMs in medical imaging.

For better or for worse: differential effects of the emotional valence of words on children’s recall

ABSTRACT Recent research has revealed the widespread effects of emotion on cognitive functions and memory. However, the influence of emotional valence on verbal short-term memory remains largely unexplored, especially in children. This study measured the effect of emotional valence on word immediate serial recall in 4–6-year-old French children (N = 124). Results show a robust effect of emotional valence on recall performances and recall errors. More precisely, we observed a facilitating effect of the positive valence of words: it allows better performance and causes few recall errors. On the contrary, the data indicated a disruptive impact of negative word valence: the latter causes very low recall performance and is associated with a high proportion of recall errors. These findings add new evidence of the influence of emotion on children’s verbal short-term memory. Our results are discussed in relation to current semantic and attentional explanations of the emotional enhancement of memory.

Assessing the price effects of African swine fever in the China market

Aim: African swine fever is a viral disease that has affected the pig business in several nations worldwide. One of the most serious diseases affecting the hog business significantly influences China’s meat sector, as the country is one of the biggest pork consumers. The main objective of the current study is to examine the impact of the breakdown on hog meat output and prices in the China region. Several factors, such as market supply and demand, disease outbreaks, and governmental policies, have caused fluctuations in the price of pigs in China since 2018. Methods: The acquired data was first evaluated using a descriptive technique. The price fluctuation caused by African swine disease during the studied time was then evaluated using a t-test, Pearson’s correlation coefficient system, and polynomial regression. Results: In the analyzed period from 2015 to 2021, African swine fever outbreak impacts were detected in pork supply and price distribution. The outbreak lowers the output of hog meat, raising the stock price and influencing other meat products’ prices. Polynomial regression analysis employs the correlation between the decreased level of pork supply and the increased price of live pigs. The price of live pigs ranged from 10.57 RMB/kg to 37.10 RMB/kg, with a median of 15.60 RMB/kg and a mean of 21.43 RMB/kg. This suggests a significant increase in prices in comparison to stock levels, which could be a sign of the impact of exogenous disruptions of African swine fever on market dynamics. Conclusions: Findings emphasize that such disruption has a negative effect on the supply and demand balance. Moreover, it negatively affects pork production and price distribution. The results highlight that prices are increasing significantly as a consequence of viral outbreaks and decreased pork production.

Pengembangan Sistem Informasi Arsip Surat Berbasis Website di Desa Hegarmanah

The new archiving system in Hegarmanah Village, in operation for one year, is currently limited to storing formal letters. It does not yet cover incoming and outgoing letters or memos, is not integrated with Gmail, and lacks alternatives for server disruptions. Web- based technology facilitates secure and efficient archive storage. This research aims to address the shortcomings of the letter archiving system in Hegarmanah Village by adding memo features, integrating the application with Gmail, and providing alternatives during server disruptions. The goal is to enhance the efficiency and effectiveness of archive management in the village, including disposition notifications and minimizing the impact of server disruptions. The system analysis and design utilize Object-Oriented Analysis and Design (OOAD) and the Rational Unified Process (RUP) model, which includes initiation, design, construction, and deployment. The system is designed using Unified Modeling Language (UML), incorporating Use Case, Class Diagram, Activity Diagram, and Sequence Diagram to create an efficient archiving system in Hegarmanah Village. Based on the research and design of the Archiving Information System in Hegarmanah Village, the archiving system now includes the management of general letters and memos, expanding its archiving functions. Letter disposition is equipped with notifications integrated with Gmail, enabling the village head and staff to receive information more quickly. Additionally, an import file feature is provided as an alternative during server disruptions, allowing data to continue functioning and be imported once the server is restored, ensuring operational continuity.

Antimicrobial Potentials of Haliclona fibulata Derived Compounds for Combatting Drug-Resistant Bacterial Infections in Zebrafish Model.

The rising threat of antimicrobial resistance among pathogens highlights the critical need for novel antimicrobial agents. This study explores the potential of natural products by investigating hexane extracts from the marine sponge Haliclona fibulata (HF) for their antibacterial efficacy. The well diffusion method of HF extract showed significant antibacterial activity against P. aeruginosa, E. coli and S. aureus with inhibition zones of 20 ± 0.66 mm, 27 ± 0.58 mm, and 22 ± 0.33 mm, respectively. Scanning electron microscopy investigations confirmed the disruptive impact of the extracts on bacterial cell morphology. Further investigations using P. aeruginosa-infected zebrafish model revealed that HF treatment improved survival rates in a dose-dependent manner. Additionally, oxidative stress and apoptosis were significantly reduced in the 100 μg/mL (HF100) treatment group, alongside down-regulation of inflammatory markers such as il-1β, nf-kβ, tnf-α, and inos. Histological assessments showed reduced intestinal damage and fewer circulating macrophages in HF100-treated zebrafish larvae. Identifying potent bioactive compounds within the extracts suggests that HFcould be a valuable source of natural antimicrobials, warranting further exploration for developing treatments against pathogenic infections.

The Impact of Circadian Rhythm Disruption on Breast Cancer: Mechanistic Insights into Hormonal Dysregulation, Gene Expression Alterations, and Potential Therapeutic Strategies

The Impact of Circadian Rhythm Disruption on Breast Cancer: Mechanistic Insights into Hormonal Dysregulation, Gene Expression Alterations, and Potential Therapeutic Strategies

Impact of Circadian Rhythm Disruption on Breast Cancer: Mechanisms and Therapeutic Approaches

Circadian rhythm disruption plays a critical role in breast cancer pathogenesis, influencing key biological processes such as cell cycle regulation, DNA repair, and apoptosis. This review investigates the molecular mechanisms linking circadian misalignment, often caused by factors such as shift work and irregular light exposure, with increased cancer risk. Dysregulation of circadian genes, including PER and BMAL1, compromises cellular homeostasis, contributing to tumorigenesis. Through a comprehensive secondary analysis of existing literature and experimental data, this review explores therapeutic strategies that harness circadian biology. Hormonal treatments, such as melatonin and aromatase inhibitors, alongside light therapy aimed at realigning circadian rhythms, represent promising interventions. Chronotherapy, which involves synchronizing treatment with the bodys intrinsic biological clock, has demonstrated potential to enhance therapeutic efficacy and reduce adverse effects. This review underscores the significance of circadian regulation in breast cancer and highlights the potential of circadian-based therapeutic strategies to optimize treatment outcomes and improve patient care.

Penetration of linezolid and tedizolid in cerebrospinal fluid of mouse and impact of blood-brain barrier disruption.

Penetration of antimicrobial treatments into the cerebrospinal fluid is essential to successfully treat infections of the central nervous system. This penetration is hindered by different barriers, including the blood-brain barrier, which is the most impermeable. However, inflammation may lead to structural alterations of these barriers, modifying their permeability. The impact of blood-brain barrier disruption on linezolid and tedizolid (antibiotics that may be alternatives to treat nosocomial meningitis) penetration in cerebrospinal fluid (CSF) remains unknown. The aim of this study is to evaluate the impact of blood brain barrier disruption on CSF penetration of linezolid and tedizolid. Female C57BI/6 J mice were used. Blood-brain barrier disruption was induced by an intraperitoneal administration of lipopolysaccharide. Linezolid (40 mg/kg) or tedizolid-phosphate (20 mg/kg) were injected intraperitoneally. All the plasma and CSF samples were analyzed with a validated UPLC-MS/MS method. Pharmacokinetic parameters were calculated using a non-compartmental approach based on the free drug concentration. The penetration ratio from the plasma into the CSF was calculated by the AUC0-8h (Area Under Curve) ratio (AUC0-8hCSF/AUC0-8hplasma). Linezolid penetration ratio was 46.5% in control group and 46.1% in lipopolysaccharide group. Concerning tedizolid, penetration ratio was 5.5% in control group and 15.5% in lipopolysaccharide group. In conclusion, CSF penetration of linezolid is not impacted by blood-brain barrier disruption, unlike tedizolid, whose penetration ratio increased.

Arterial hypertension and COVID-19 in Arctic rotating shift work: the impact of chronostructure disruptions on circadian blood pressure rhythm in relation to echocardiographic parameters

This study investigated the effects of chronostructure disruptions on circadian blood pressure (BP) rhythms and their association with echocardiographic parameters in men with arterial hypertension (AH) who contracted COVID-19 while engaged in rotating shift work in the Arctic. Methods – A random sample of 166 men with arterial hypertension (AH) was selected from the medical records database of patients treated at the hospital of the Medical Unit of Gazprom Dobycha Yamburg LLC in Yamburg (Nadymsky District, Russia, 68° 21’ 40” N) between June 2020 and March 2021. Randomization was achieved using a random number method. These patients underwent echocardiography (ECHO) and 24-hour ambulatory blood pressure monitoring (ABPM) before the COVID-19 pandemic (November 2019 to March 2020) and again in 2021. The group was then divided into those who had contracted COVID-19 (n=94) and those who had not (n=72). ABPM was performed using a BPLab v.3.2 device (BPlab, Russia). Chronobiological analysis was performed to identify the main hypertensive BP chronotypes (CT) based on the P. Cugini classification: “MESOR AH”, characterized by a 24-hour rhythm period (T); and “Aperiodic AH”, characterized by a predominance of oscillations with periods (T) of 4.0, 4.8, 6.0, and 8.0 hours within the circadian rhythm. Echocardiography (ECHO) was performed using a Philips CX 50 scanner (Netherlands). Results – Logistic regression analysis showed that the presence of the “Aperiodic AH” chronotype was associated with a threefold increase in the odds of contracting COVID-19, while a 1 g/m² increase in the left ventricular mass index (LVMI) increased these odds by a factor of 1.02. One year post-COVID-19, individuals with “Aperiodic AH”, in contrast to those with “MESOR AH”, exhibited increases in right atrial and inferior vena cava diameters, systolic pulmonary artery pressure, tricuspid regurgitation velocity, stroke volume, and cardiac output, as well as a more pronounced increase in left ventricular mass and LVMI. Associations were observed between structural alterations in the heart and parameters that reflect disruptions in the circadian BP rhythm. Conclusion — Within the context of Arctic rotating shift work, men with arterial hypertension (AH) exhibiting a disrupted chronostructure of the circadian BP rhythm, characterized by a predominance of irregular, short-term oscillations, and structural alterations in the heart, are more susceptible to COVID-19. This increased susceptibility is associated with more pronounced alterations in echocardiographic parameters following the infection.

Discovering metro passenger flow recovery patterns under unplanned disruptions: a disruption impact quantification-based clustering approach

ABSTRACT Discovering metro passenger flow recovery patterns from historical unplanned disruptions enables operators to better prepare for a new disruption. The task is challenging as passenger flow recovery patterns are generated by different types of disruptions at different locations and times. We start with the Robust Principal Component Analysis (RPCA), a dimensionality reduction technique to calculate passenger flow change under disruption and quantify disruption impact. With this information, we modify the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) model with the tailor-made discrete input module and distance metric module, to discover the typical passenger flow recovery patterns with different shapes and sizes. Our approach is validated in the Hong Kong Mass Transit Railway system. The results show that our approach can discover interpretable recovery patterns that are easily neglected by other clustering methods, because of its ability to quantify and distinguish disruption impact on normal passenger flow.

Family planning, pregnancy, and parenthood during surgical training: Experiences and perspectives from trainees and early career surgeons in Australia and New Zealand.

To identify and address areas for improvement within the current surgical training model in Australia and New Zealand relating to family planning and inflexible training as top barriers to gender equity in surgery. A cross-sectional study of accredited surgical trainees and early career surgeons in Australia and New Zealand was conducted between September and October 2023. Participants were recruited by the RACS Fax Mentis, the Urological Society of Australia and New Zealand (USANZ) e-newsletter, and medical social media networks. Qualitative and quantitative data were collated by the electronic survey and thematically analyzed. There was a total of 146 participants. Approximately two-thirds of respondents identified as mothers and one-third as fathers, with representation from all surgical specialties. We identified four key themes including the disruptive impact of poor work-life balance on family planning, an absence of workplace systemic supports, a need for structured support program upon return-to-work from parental leave, and challenges in balancing professional and parental identities and responsibilities. To promote a culture of equity, inclusivity, and acceptance, restructuring of surgical training programs are necessary to support trainees as they navigate family planning and parenthood. Promotion of flexible training options and recruitment of additional clinical supports around parental leave period may reduce negative biases toward trainees simultaneously balancing family and work. Systemic change is required to lower barriers to entry and achieve gender equality in surgery.

The role of a structured community health worker network in achieving malaria elimination goals in the Dominican Republic: An impact evaluation amid COVID-19 disruptions.

Community health workers (CHWs) can play a key role in malaria elimination through expanding access to malaria testing and treatment. The Dominican Republic, a low endemic country committed to eliminate malaria by 2025, implemented a structured malaria CHW network in the three main urban foci of Greater Santo Domingo. This research quantifies the networks' contributions towards malaria elimination from its implementation in 2019 until 2022. The study highlights the impact of COVID-19 disruptions on CHWs' performance and explores the network's ability to bounce back from health systems' shocks. The performance of the malaria CHW network was evaluated using weekly data collected from CHWs and routinely collected surveillance data from the Ministry of Public Health (MoH). We assess performance of CHWs by analyzing key variables including (1) reporting compliance, (2) household visitation rates, (3) malaria rapid diagnostic tests performed, (4) malaria cases detected, and (5) time between symptom onset and malaria diagnosis. To evaluate the impact of COVID-19 on the network, CHW's performance indicators are evaluated across three time periods (prior to, during, and after COVID-19 interruptions). Over the evaluation period, reported malaria cases in study foci decreased from 1,243 cases in 2019 to 6 cases in 2022. CHWs diagnosed and treated over 43% of malaria cases in study foci before COVID-19 interruptions and 14% during interruptions. 83% of cases detected by CHWs were detected through active case detection, with 17% detected passively. CHWs detected malaria cases and initiated treatment 1.5 days earlier than health facilities and MoH personnel performing active case detection. This evaluation provides evidence that a structured CHW network with clearly defined responsibilities and management protocol can help curb local malaria transmission. It adds to a growing body of research on the feasibility and benefits of CHW-led proactive household visitation.

Text-to-Video Models and Sora in Plastic Surgery: Pearls, Pitfalls, and Prospectives.

After the groundbreaking release of the highly acclaimed chatbot ChatGPT, which revolutionized the field of artificial intelligence (AI) last year, OpenAI has once again astounded the world with the unveiling of their latest generative AI model, Sora, on February 16, 2024. This cutting-edge model has the remarkable ability to generate videos up to a duration of 60 seconds solely through text instructions. With a series of AI-generated contents, such as AI chat, AI drawing, and AI music, emerging one after another, the era of "AI revolution" that had a disruptive impact on modern life has arrived. Meanwhile, AI has made significant achievements in the medical field, especially in diagnosing based on medical imaging. This article briefly describes the development history of text-to-video models and provides a detailed introduction to the Sora model, including its portrayal of the human face and contour, inspiring its potential applications in plastic surgery. It also provides a prospect for other AI-generated content technologies, such as text-to-holography and text-to-material objects.Level of Evidence VThis journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

New Challenges in Bladder Cancer Diagnosis: How Biosensing Tools Can Lead to Population Screening Opportunities.

Bladder cancer is one of the most common cancers worldwide. Despite its high incidence, cystoscopy remains the currently used diagnostic gold standard, although it is invasive, expensive and has low sensitivity. As a result, the cancer diagnosis is mostly late, as it occurs following the presence of hematuria in urine, and population screening is not allowed. It would therefore be desirable to be able to act promptly in the early stage of the disease with the aid of biosensing. The use of devices/tools based on genetic assessments would be of great help in this field. However, the genetic differences between populations do not allow accurate analysis in the context of population screening. Current research is directed towards the discovery of universal biomarkers present in urine with the aim of providing an approach based on a non-invasive, easy-to-perform, rapid, and accurate test that can be widely used in clinical practice for the early diagnosis and follow-up of bladder cancer. An efficient biosensing device may have a disruptive impact in terms of patient health and disease management, contributing to a decrease in mortality rate, as well as easing the social and economic burden on the national healthcare system. Considering the advantage of accessing population screening for early diagnosis of cancer, the main challenges and future perspectives are critically discussed to address the research towards the selection of suitable biomarkers for the development of a very sensitive biosensor for bladder cancer.

Impact of pandemic-induced service disruptions and behavioral changes on HCV and HIV transmission amongst people who inject drugs: a modeling study.

The COVID-19 pandemic may have disproportionally impacted vulnerable groups such as people who inject drugs (PWID) through reduced healthcare services as well as social changes from pandemic mitigation measures. Understanding how the COVID-19 pandemic and associated mitigation strategies subsequently changed the trajectory of hepatitis C virus (HCV) and HIV transmission is critical to estimating disease burdens, identifying outbreak risk, and developing informed intervention strategies. Using behavioral data from the AIDS Linked to the IntraVenous Experience (ALIVE) study, an ongoing community-based cohort of PWID in Baltimore, USA, and an individual-based network model, we explored the impacts of service disruptions combined with changes in social networks and injecting behaviors of PWID on HCV and HIV transmission. Analyses of ALIVE data showed that during the pandemic, there was an acceleration in injection cessation trajectories overall, but those who continued injecting increased the frequency of injection; at the same time, individual drug-use networks became smaller and the probability of injecting with others decreased. Simulation results demonstrated that HCV and HIV prevalence increased from service disruptions alone, but these effects were mitigated when including observed behavior changes in addition. Model results combined with rich individual behavioral data indicated that pandemic-induced behavioral changes of PWID that lasted longer than service disruptions could have offset the increasing disease burden caused by disrupted service access during the pandemic.

REV-ERBα Inhibits Osteoclastogenesis and Protects against Alveolar Bone Loss

Circadian rhythm disruption is thought to be associated with periodontitis, and molecular clock genes play critical roles in regulating bone homeostasis. However, the specific contribution of molecular clock genes to alveolar bone resorption caused by periodontitis is poorly understood. In this study, we introduced a novel Periodontitis Circadian Rhythm Score (PeriCRS) model that was established through machine learning using periodontal transcriptomic data from periodontitis clinical cohorts in the Gene Expression Omnibus (GEO) database. This approach revealed the potential regulatory role of circadian rhythm disruption in periodontitis and identified key molecular clock genes associated with alveolar bone destruction. Moreover, we established an experimental periodontitis model with circadian rhythm disturbance via periodontal ligation in mice exposed to a 6-h advanced LD12:12 cycle every 2 d. Our bioinformatics analysis revealed that NR1D1, which encodes REV-ERBα, is a pivotal factor in the impact of circadian rhythm disruption on periodontitis in periodontal tissues. Next, we confirmed the abnormal expression of the molecular clock gene Rev-erbα in inflammatory periodontal tissue in mice and confirmed that circadian rhythm disruption altered REV-ERBα expression. Furthermore, the activation of REV-ERBα with the agonist SR9009 notably decreased RANKL-induced osteoclast differentiation and suppressed the expression of osteoclast-related factors. Subsequent in vivo experiments demonstrated that SR9009 mitigated alveolar bone loss caused by periodontitis. Mechanistically, we found that the IL-22-STAT3 pathway inhibited REV-ERBα expression and modulated RANKL-induced osteoclast differentiation in vitro. Our results elucidate the role of REV-ERBα in osteoclastogenesis and suggest a potential new therapeutic avenue for addressing alveolar bone resorption associated with periodontitis.

Disaster resilience of household-level food-energy-water nexus

This study examines the resilience and sustainability of household-level Food-Energy-Water (FEW) systems in the face of increasing natural disasters exacerbated by climate change. With the backdrop of escalating natural hazards and heightened vulnerabilities, this research explores innovative approaches to enhancing household resilience through the implementation of sustainable FEW systems such as rainwater harvesting, sand filtration, solar energy, geothermal energy, gas-powered and solar generators, hydroponic food production, and small greenhouses. Three primary scenarios, food disruption, energy scarcity, and water shortage are analyzed to evaluate the effectiveness of various household-level FEW systems within a residential context. These systems are compared in terms of cost-effectiveness and performance, highlighting their capacity to supply essential needs during crises. The paper also introduces an integrated nexus approach, considering the interdependencies among food, energy, and water systems, and evaluates the compounded impact of simultaneous disruptions. This comprehensive analysis aims to provide actionable insights into the development of resilient infrastructures at a micro-scale, which can significantly mitigate the adverse effects of global environmental changes on local scales.

Energetic activity for depression in young people aged 13-17 years: the READY feasibility RCT.

Prevalence of depression is increasing in young people. Behaviour change interventions providing benefits equal to or greater than talking therapies or pharmacological alternatives are needed. Exercise could be beneficial for young people with depression, but we lack robust trials of its effectiveness. To test whether an exercise intervention targeting young people with depression is feasible, including recruitment and retention of young people, recruitment and training of exercise professionals and intervention delivery. Three-arm cluster feasibility randomised controlled trial with embedded process evaluation and health economic data collection. Local community venues in Hertfordshire, Bedfordshire and Norfolk. Young people aged 13-17 years experiencing mild to moderate low mood or depression (indicated by scoring 17-36 on the Child Depression Inventory version 2) identified by mental health services, schools or self-referral. Participants were randomised to one of three groups: high-intensity exercise, low-intensity exercise or a social activity control. Group sessions ran twice-weekly for 12 weeks delivered by registered exercise professionals, supported by mental health support workers. Referral, recruitment and retention rates; attendance at group sessions; adherence to and ability to reach intensity during exercise sessions; proportions of missing data, and adverse events measured at baseline and at 3 and 6 months; resource use; and reach and representativeness. Of 321 referrals to the study, 173 were assessed for eligibility, and of the target sample size of 81, 15 were recruited and 14 were randomised (one withdrew). The retention rate was 71.4% and attendance at intervention sessions was > 67%; data completeness was > 80% for baseline assessments. Follow-up completion rate at 14 weeks was > 80% for most outcomes, with 50% for accelerometer data in the low-intensity group. Trial processes and the intervention were acceptable to young people. Barriers to and facilitators of intervention delivery were identified. Findings highlighted challenges around recruitment, delivery of exercise interventions and informed ways of addressing barriers to recruitment for future studies. The study was conducted between October 2020 and August 2022 and consequently the COVID-19 pandemic had a disruptive impact on implementation. A large randomised trial of the effectiveness of the intervention is not feasible using the current study design, but issues relating to recruitment could be addressed with further work. Developing appropriate recruitment strategies via triage services, general practitioner practices, schools and social media and early engagement with the local Clinical Research Network to support recruitment to the study would address the significant shortfalls identified. Young people who are deemed unsuitable for mental health services should be followed up to be offered participation in such interventions. Collaborations between the NHS services and sports delivery partners should consider in-person contact with young people rather than remote consultations. Recruiting through general practitioner practices is effective and relatively inexpensive. The role of community engagement (socialmedia, public health agencies, community groups) needs to be further explored. Strong public and patient involvement and engagement via young people advisory groups is important to ensure that research is relevant to young people. This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number 17/78/10.

Building resilience in LNG marine terminal operations: a comprehensive socio-technical risk analysis utilizing the resilience assessment grid (RAG) method

Abstract In the face of rising global energy demand, LNG terminals play an essential role in the energy supply chain. However, the complexity of terminal operations, combined with the risk of catastrophic events, necessitates a robust resilience framework. This paper presents a comprehensive socio-technical resilience analysis that uses the Resilience Assessment Grid (RAG) methodology to measure resilience in LNG terminal operations. We examine the complex interplay of human elements, organizational culture, and technological systems in the terminal environment. Our approach uses the RAG methodology to identify vulnerabilities, assess the potential impact of disruptions, and assess the effectiveness of current safety and risk management practices. The results of this study show that the implementation of the safety concept at the LNG Marine Terminal is quite optimal, as indicated by the compliance figures for each resilience aspect, which exceed three as a benchmark. The highest score in the entire system is found in the ability to respond aspect, namely 4.38, which shows that the organization, in implementing this concept, still focuses on preventing and controlling accidents. This condition differs from the ability to monitor aspect, which has the lowest value, 3.97. However, this item cannot be called an inhibiting factor because its value exceeds the expected standard. In response, there is still room for improvement from existing achievements in the future.