Response Measures Research Articles

The Use of Big Data to Improve Disaster Response and Preparedness Efforts

Disasters pose significant challenges to societies worldwide, necessitating effective response and preparedness measures. With the advent of big data technologies and the increasing availability of diverse data sources, there is a growing opportunity to leverage these resources to enhance disaster management. This research paper explores the utilization of big data in improving disaster response and preparedness efforts. It examines the potential benefits, challenges, and future directions of employing big data analytics in disaster management. By analyzing case studies and existing literature, this paper highlights the impact of big data on enhancing situational awareness, decision making, resource allocation, and community engagement. It also addresses privacy and ethical considerations associated with big data usage in disaster contexts. The findings suggest that leveraging big data can significantly enhance the effectiveness and efficiency of disaster response and preparedness activities, leading to improved outcomes and resilience in the face of future disasters

Amplitude Modulation Perception and Cortical Evoked Potentials in Children With Listening Difficulties and Their Typically Developing Peers.

Amplitude modulations (AMs) are important for speech intelligibility, and deficits in speech intelligibility are a leading source of impairment in childhood listening difficulties (LiD). The present study aimed to explore the relationships between AM perception and speech-in-noise (SiN) comprehension in children and to determine whether deficits in AM processing contribute to childhood LiD. Evoked responses were used to parse the neural origins of AM processing. Forty-one children with LiD and 44 typically developing children, ages 8-16 years, participated in the study. Behavioral AM depth thresholds were measured at 4 and 40 Hz. SiN tasks included the Listening in Spatialized Noise-Sentences Test (LiSN-S) and a coordinate response measure (CRM)-based task. Evoked responses were obtained during an AM change detection task using alternations between 4 and 40 Hz, including the N1 of the acoustic change complex, auditory steady-state response (ASSR), P300, and a late positive response (late potential [LP]). Maturational effects were explored via age correlations. Age correlated with 4-Hz AM thresholds, CRM separated talker scores, and N1 amplitude. Age-normed LiSN-S scores obtained without spatial or talker cues correlated with age-corrected 4-Hz AM thresholds and area under the LP curve. CRM separated talker scores correlated with AM thresholds and area under the LP curve. Most behavioral measures of AM perception correlated with the signal-to-noise ratio and phase coherence of the 40-Hz ASSR. AM change response time also correlated with area under the LP curve. Children with LiD exhibited deficits with respect to 4-Hz thresholds, AM change accuracy, and area under the LP curve. The observed relationships between AM perception and SiN performance extend the evidence that modulation perception is important for understanding SiN in childhood. In line with this finding, children with LiD demonstrated poorer performance on some measures of AM perception, but their evoked responses implicated a primarily cognitive deficit. https://doi.org/10.23641/asha.25009103.

Tropical cyclone intensity estimation through convolutional neural network transfer learning using two geostationary satellite datasets

Accurate prediction and monitoring of tropical cyclone (TC) intensity are crucial for saving lives, mitigating damages, and improving disaster response measures. In this study, we used a convolutional neural network (CNN) model to estimate TC intensity in the western North Pacific using Geo-KOMPSAT-2A (GK2A) satellite data. Given that the GK2A data cover only the period since 2019, we applied transfer learning to the model using information learned from previous Communication, Ocean, and Meteorological Satellite (COMS) data, which cover a considerably longer period (2011–2019). Transfer learning is a powerful technique that can improve the performance of a model even if the target task is based on a small amount of data. Experiments with various transfer learning methods using the GK2A and COMS data showed that the frozen–fine-tuning method had the best performance due to the high similarity between the two datasets. The test results for 2021 showed that employing transfer learning led to a 20% reduction in the root mean square error (RMSE) compared to models using only GK2A data. For the operational model, which additionally used TC images and intensities from 6 h earlier, transfer learning reduced the RMSE by 5.5%. These results suggest that transfer learning may represent a new breakthrough in geostationary satellite image–based TC intensity estimation, for which continuous long-term data are not always available.

“Hospitals respond to demand. Public health needs to respond to risk”: health system lessons from a case study of northern Queensland’s COVID-19 surveillance and response

BackgroundThe vast region of northern Queensland (NQ) in Australia experiences poorer health outcomes and a disproportionate burden of communicable diseases compared with urban populations in Australia. This study examined the governance of COVID-19 surveillance and response in NQ to identify strengths and opportunities for improvement.MethodsThe manuscript presents an analysis of one case-unit within a broader case study project examining systems for surveillance and response for COVID-19 in NQ. Data were collected between October 2020–December 2021 comprising 47 interviews with clinical and public health staff, document review, and observation in organisational settings. Thematic analysis produced five key themes.ResultsStudy findings highlight key strengths of the COVID-19 response, including rapid implementation of response measures, and the relative autonomy of NQ’s Public Health Units to lead logistical decision-making. However, findings also highlight limitations and fragility of the public health system more generally, including unclear accountabilities, constraints on local community engagement, and workforce and other resourcing shortfalls. These were framed by state-wide regulatory and organisational incentives that prioritise clinical health care rather than disease prevention, health protection, and health promotion. Although NQ mobilised an effective COVID-19 response, findings suggest that NQ public health systems are marked by fragility, calling into question the region’s preparedness for future pandemic events and other public health crises.ConclusionsStudy findings highlight an urgent need to improve governance, resourcing, and political priority of public health in NQ to address unmet needs and ongoing threats.

Preoperative aerobic fitness and perioperative outcomes in patients undergoing cystectomy before and after implementation of a national lockdown

BackgroundLower fitness is a predictor of adverse outcomes after radical cystectomy. Lockdown measures during the COVID-19 pandemic affected daily physical activity. We hypothesised that lockdown during the pandemic was associated with a reduction in preoperative aerobic fitness and an increase in postoperative complications in patients undergoing radical cystectomy. MethodsWe reviewed routine preoperative cardiopulmonary exercise testing (CPET) data collected prior to the pandemic (September 2018 to March 2020) and after lockdown (March 2020 to July 2021) in patients undergoing radical cystectomy. Differences in CPET variables, Postoperative Morbidity Survey (POMS) data, and length of hospital stay were compared. ResultsWe identified 267 patients (85 pre-lockdown and 83 during lockdown) who underwent CPET and radical cystectomy. Patients undergoing radical cystectomy throughout lockdown had lower ventilatory anaerobic threshold (9.0 [7.9–10.9] vs 10.3 [9.1–12.3] ml kg−1 min−1; P=0.0002), peak oxygen uptake (15.5 [12.9–19.1] vs 17.5 [14.4–21.0] ml kg−1 min−1; P=0.015), and higher ventilatory equivalents for carbon dioxide (34.7 [31.4–38.5] vs 33.4 [30.5–36.5]; P=0.030) compared with pre-lockdown. Changes were more pronounced in males and those aged >65 yr. Patients undergoing radical cystectomy throughout lockdown had a higher proportion of day 5 POMS-defined morbidity (89% vs 75%, odds ratio [OR] 2.698, 95% confidence interval [CI] 1.143–6.653; P=0.019), specifically related to pulmonary complications (30% vs 13%, OR 2.900, 95% CI 1.368–6.194; P=0.007) and pain (27% vs 9%, OR 3.471, 95% CI 1.427–7.960; P=0.004), compared with pre-lockdown on univariate analysis. ConclusionsLockdown measures in response to the COVID-19 pandemic were associated with a reduction in fitness and an increase in postoperative morbidity among patients undergoing radical cystectomy.

Experience of financial toxicity and coping strategies in young and middle-aged patients with stroke: a qualitative study

BackgroundWhile financial toxicity (FT) is prevalent in patients with cancer, young and middle-aged patients with stroke are also affected by FT, which can exacerbate their physical and psychological challenges. Understanding the patient’s experience and response measures can further understand the impact of FT on patients with stroke, to help alleviate FT. However, little is known concerning the experience of patients with stroke with FT or their coping strategies. Therefore, this study aimed to describe the experiences of FT in young and middle-aged patients with stroke and their coping strategies.MethodsA phenomenological method was utilized. Semi-structured interviews were conducted with 21 young and middle-aged stroke patients (aged 18–59) between October 2022 and March 2023. The participants were recruited from a tertiary hospital in Shanghai, China. The research team used NVivo 12.0 software. Giorgi’s phenomenological analysis method was used to analyse the interview data.ResultsThe interview results were divided into two categories in terms of patients’ experiences of FT and their coping strategies. Nine subthemes were constructed. The experience category included four subthemes: (1) taking on multifaceted economic pressure, (2) dual choice of treatment, (3) decline in material living standards, and (4) suffering from negative emotions such as anxiety and depression. The coping strategy category included five subthemes: (1) reducing expenses, (2) improving living habits, (3) proactive participation in medical decision-making, (4) making a job position choice, and (5) seeking social support.ConclusionsFT in young and middle-aged patients with stroke, which affected their physical and mental health, led them to implement strategies for dealing with FT. The Chinese government needs to broaden the reach of health insurance coverage and advance the fairness of healthcare policies. Healthcare professionals must pay active attention to FT in such patients in terms of strengthening their health education and considering their needs and preferences. Patients need to improve their sense of self-efficacy, actively reintegrate into society, and adhere to rehabilitation and treatment. Individuals at a high risk of stroke are recommended to purchase health insurance. Multifaceted efforts are needed to reduce the impact of FT in young and middle-aged patients with stroke.

ASES and UCLA Are Responsive Patient-Reported Outcome Measures After Rotator Cuff Repair: A Systematic Review and Meta-analysis.

Multiple patient-reported outcome measures (PROMs) have been used to assess shoulder function, but it is unknown which are the most effective. The purpose of this study was to report the multiple PROMs used after rotator cuff repair (RCR) and to compare the responsiveness between them. It was hypothesized that the Western Ontario Rotator Cuff PROM would be the most responsive and commonly used in patients undergoing RCR. Meta-analysis; Level of evidence, 4. A systematic review was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PRISMA-Searching extension guidelines via PubMed/MEDLINE, Embase (Elsevier), and Web of Science (Clarivate). Patient and study characteristics were extracted. From the studies that met inclusion criteria for responsiveness analysis (≥2 PROMs reported, 1-year minimum follow-up, and pre- and postoperative PROM means and standard deviations reported), the authors compared the responsiveness between PROM instruments using effect size and relative efficiency (RE) if a PROM could be compared with another in ≥10 articles. A total of 252 studies met inclusion criteria (32,072 patients; mean age, 59.6 years; mean body mass index, 28.7; mean follow-up time, 27.8 months). Range of motion was reported in 131 (52%) studies and imaging findings were reported in 123 (49%) studies. There were 67 PROM instruments identified; the most commonly used were the American Shoulder and Elbow Surgeon (ASES) (n = 183; 73%), Visual Analog Scale (VAS) (n = 163; 65%), and Constant (n = 118; 47%) scores. The 3 PROMs with the highest effect sizes were the University of California, Los Angeles (UCLA) (2.51), Western Ontario Rotator Cuff (2.42), and ASES (2.00) scores. Overall, UCLA and ASES scores were the most responsive PROMs. The ASES PROM was more responsive than the VAS (RE, 1.70), Constant (RE, 2.76), Simple Shoulder Test (RE, 1.67), and Single Assessment Numeric Evaluation (RE, 2.14) scores. The UCLA PROM was more responsive than the ASES (RE, 1.03), VAS (RE, 3.66), Constant (RE, 1.72), and Simple Shoulder Test (RE, 1.66) scores. ASES and UCLA scores were the most responsive PROMs after RCR. The authors recommend widespread adoption of ASES and UCLA scores for clinical and research standardization; however, the UCLA PROM requires in-person range of motion and strength testing, which is a practical limitation and barrier to long-term follow-up.

Research on Huawei's Digital Transformation and Market Adaptation in the Post-epidemic Era

With the spread of global epidemic, Huawei, as a leading enterprise in the field of information and communication technology, is facing many challenges, such as supply chain uncertainty, market demand changes, network security challenges and so on. This paper makes an in-depth analysis of Huawei's response measures in product innovation, marketing strategy adjustment, supply chain management, employee security and so on, and summarizes Huawei's achievements and experiences in digital transformation and market adaptation. It is found that Huawei has successfully achieved stable development during the epidemic period by increasing investment in key technical fields, flexibly adjusting marketing strategies, optimizing supply chain management, and paying attention to the health and safety of employees. However, with the advent of the post-epidemic era, it is still necessary to further strengthen the innovation ability and enhance the level of digital transformation in order to better meet the market demand and maintain the competitive advantage. The purpose of this study is to provide reference and enlightenment for other enterprises and promote the sustainable development and transformation and upgrading of the industry.

Deep learning-based chatbot by natural language processing for supportive risk management in river dredging projects

Dredging projects play a vital role in water conservation, especially for flood control, but they often encounter natural and human-induced risks. This study addresses these challenges by creating a comprehensive knowledge base for dredging risks. This knowledge base serves several essential functions: it aids in immediate and thorough risk prevention, provides practical risk management recommendations, and assists dredging personnel in making informed decisions when dealing with risks. Furthermore, the study introduces an advanced deep-learning model that enhances access to critical information. Users can quickly find relevant risk prevention strategies by inputting keywords. The model's distinctive feature is its ability to analyze unforeseen risks through natural language processing, predict the potential impact and frequency of unexpected events, and propose appropriate risk response measures. This empowers dredging personnel to conduct preliminary risk assessments confidently. The deep learning model seamlessly integrates into LINE's communication platform, creating a river dredging project risk knowledge chatbot. This user-friendly chatbot is accessible to personnel at all project stages, enabling real-time interaction. It offers a practical way to develop and implement risk prevention plans and response measures. In summary, this research presents an innovative approach that enhances the efficiency and safety of dredging projects. By merging a knowledge base with cutting-edge technology and real-time communication, it equips dredging personnel to manage known and unforeseen risks proficiently, ultimately contributing to the success of water conservancy and flood control projects.

Effect of walnut consumption on markers of endothelial function in adults: A systematic review and meta-analysis of randomized controlled trials.

Findings on the effect of walnut consumption on endothelial function are conflicting. Therefore, the present systematic review and meta-analysis summarized available trials in this regard. A systematic search was performed in online databases including PubMed-Medline, Scopus, and ISI Web of Science up to October 2023. Articles that reported the effect of walnut intake on flow-mediated dilation (FMD), intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), and stimulus-adjusted response measure (SARM) were included. Random effects models for a weighted mean difference (WMD) or standardized mean difference (SMD) were used to test for the overall effect. Six eligible trials were analyzed (250 participants). Walnut intake significantly increased FMD (WMD: 0.94%, 95% CI: 0.12 to 1.75; p = 0.02). However, meta-analysis could not show any beneficial effect of walnut intake on ICAM-1 (SMD: -0.23, 95% CI: -0.68 to 0.22; p = 0.31), VCAM-1 (SMD: -0.02, 95% CI: -1.38 to 1.34; p = 0.97), and SARM (WMD: 0.01%, 95% CI: -0.01 to 0.04; p = 0.28). In conclusion, the present meta-analysis suggests that walnuts may reduce cardiovascular disease risk by improving FMD. However, further studies should be performed on adults to determine the effect of walnut intake on endothelial function.

The Effect of Jittered Stimulus Onset Interval on Electrophysiological Markers of Attention in a Brain-Computer Interface Rapid Serial Visual Presentation Paradigm.

Brain responses to discrete stimuli are modulated when multiple stimuli are presented in sequence. These alterations are especially pronounced when the time course of an evoked response overlaps with responses to subsequent stimuli, such as in a rapid serial visual presentation (RSVP) paradigm used to control a brain-computer interface (BCI). The present study explored whether the measurement or classification of select brain responses during RSVP would improve through application of an established technique for dealing with overlapping stimulus presentations, known as irregular or "jittered" stimulus onset interval (SOI). EEG data were collected from 24 healthy adult participants across multiple rounds of RSVP calibration and copy phrase tasks with varying degrees of SOI jitter. Analyses measured three separate brain signals sensitive to attention: N200, P300, and occipitoparietal alpha attenuation. Presentation jitter visibly reduced intrusion of the SSVEP, but in general, it did not positively or negatively affect attention effects, classification, or system performance. Though it remains unclear whether stimulus overlap is detrimental to BCI performance overall, the present study demonstrates that single-trial classification approaches may be resilient to rhythmic intrusions like SSVEP that appear in the averaged EEG.

A Study on Machine Learning-Enhanced Roadside Unit-Based Detection of Abnormal Driving in Autonomous Vehicles

Ensuring the safety of autonomous vehicles is becoming increasingly important with ongoing technological advancements. In this paper, we suggest a machine learning-based approach for detecting and responding to various abnormal behaviors within the V2X system, a system that mirrors real-world road conditions. Our system, including the RSU, is designed to identify vehicles exhibiting abnormal driving. Abnormal driving can arise from various causes, such as communication delays, sensor errors, navigation system malfunctions, environmental challenges, and cybersecurity threats. We simulated exploring three primary scenarios of abnormal driving: sensor errors, overlapping vehicles, and counterflow driving. The applicability of machine learning algorithms for detecting these anomalies was evaluated. The Minisom algorithm, in particular, demonstrated high accuracy, recall, and precision in identifying sensor errors, vehicle overlaps, and counterflow situations. Notably, changes in the vehicle’s direction and its characteristics proved to be significant indicators in the Basic Safety Messages (BSM). We propose adding a new element called linePosition to BSM Part 2, enhancing our ability to promptly detect and address vehicle abnormalities. This addition underpins the technical capabilities of RSU systems equipped with edge computing, enabling real-time analysis of vehicle data and appropriate responsive measures. In this paper, we emphasize the effectiveness of machine learning in identifying and responding to the abnormal behavior of autonomous vehicles, offering new ways to enhance vehicle safety and facilitate smoother road traffic flow.

Towards stratified treatment of JIA: machine learning identifies subtypes in response to methotrexate from four UK cohorts

Methotrexate (MTX) is the gold-standard first-line disease-modifying anti-rheumatic drug for juvenile idiopathic arthritis (JIA), despite only being either effective or tolerated in half of children and young people (CYP). To facilitate stratified treatment of early JIA, novel methods in machine learning were used to i) identify clusters with distinct disease patterns following MTX initiation; ii) predict cluster membership; and iii) compare clusters to existing treatment response measures. Discovery and verification cohorts included CYP who first initiated MTX before January 2018 in one of four UK multicentre prospective cohorts of JIA within the CLUSTER consortium. JADAS components (active joint count, physician (PGA) and parental (PGE) global assessments, ESR) were recorded at MTX start and over the following year. Clusters of MTX 'response' were uncovered using multivariate group-based trajectory modelling separately in discovery and verification cohorts. Clusters were compared descriptively to ACR Pedi 30/90 scores, and multivariate logistic regression models predicted cluster-group assignment. The discovery cohorts included 657 CYP and verification cohorts 1241 CYP. Six clusters were identified: Fast improvers (11%), Slow Improvers (16%), Improve-Relapse (7%), Persistent Disease (44%), Persistent PGA (8%) and Persistent PGE (13%), the latter two characterised by improvement in all features except one. Factors associated with clusters included ethnicity, ILAR category, age, PGE, and ESR scores at MTX start, with predictive model area under the curve values of 0.65-0.71. Singular ACR Pedi 30/90 scores at 6 and 12 months could not capture speeds of improvement, relapsing courses or diverging disease patterns. Six distinct patterns following initiation of MTX have been identified using methods in artificial intelligence. These clusters demonstrate the limitations in traditional yes/no treatment response assessment (e.g., ACRPedi30) and can form the basis of a stratified medicine programme in early JIA. Medical Research Council, Versus Arthritis, Great Ormond Street Hospital Children's Charity, Olivia's Vision, and the National Institute for Health Research.

Research Advanced on the Influence of Green Credit Policy on Companies: A Case Study of Industrial Structure, Firm Performance, and Response Measures

Nowadays, the traditional economic development mode and development power have caused a series of problems such as waste of factor input, serious environmental pollution, and low economic efficiency. Green finance is thus sprouting. With the rapid economic development, more and more companies at home and abroad have begun to use Green Credit Policy (GCP) to promote sustainable development. Based on official publication databases, we delve into a deep analysis of the impact of the Green Credit Policy on companies, focusing on their industrial structure, firm performance, and response measures. Through empirical analysis and theoretical discussions, we reveal that the Green Credit Policy positively influences industrial upgrading, enhances firms environmental performance, and stimulates strategic responses to Green Credit Policy. Additionally, empirical data substantiates the notion that GCP exerts a "detrimental impact" on companies exhibiting subpar environmental practices. These results underscore the importance of policies geared towards sustainability in fostering a more eco-friendly and robust economy.

ROMANIA’S SPACE ASPIRATIONS AND THE EU SPACE STRATEGY FOR SECURITY AND DEFENCE

The article explores the interplay between European Union’s Space Strategy for Security and Defence and Romania’s space aspirations, analysing its key facets and their potential effects. As space gains significance for security and defence of the EU as a whole, understanding its opportunities and challenges is crucial. Investigating elements such as shared threat awareness, space system resilience, response strategies, and responsible behaviour in outer space, the article provides insights for stakeholders to harness EU space capabilities. The article concludes by assessing implications for the domestic realm. EU Space Strategy for Security and Defence addresses space intricacies with political, operational and other fields of action. By focusing on vital components such as threat understanding, system protection, responsive measures, and cooperative behaviour, the article sheds light on EU Space Strategy’s strategic importance in the defence and security realms.

Utility of the Interferon-Gamma Enzyme-Linked Immunosorbent Spot Assay to Predict Risk of Cytomegalovirus Infection in Kidney Transplant Recipients.

Non-specific interferon-gamma (IFN-γ) enzyme-linked immunosorbent (ELISpot) responses after solid organ transplant (SOT) and their relationship with cytomegalovirus (CMV) reactivation have hardly been investigated. Adult kidney transplant (KT) recipients underwent measurement of IFN-γ-producing T cells using the ELISpot assay before and 1 month after transplantation. Data for CMV infection episodes were collected. Risk factors for post-transplant CMV infection, based on IFN-γ responses, were analyzed using a Cox proportional hazards model. A total of 93 KT recipients were enrolled in the study and 84 evaluable participants remained at 1 month post KT. Thirty-three (39%) recipients developed subsequent CMV infection within 6 months post-transplant. At 1-month post-transplant, IFN-γ-producing T cells with <250 spot-forming units (SFUs)/2.5 × 105 peripheral blood mononuclear cells (PBMCs) were significantly associated with CMV infection (HR 3.1, 95% CI 1.4-7.1, p = 0.007). On multivariable analysis, posttransplant IFN-γ-producing T cells with <250 SFUs/2.5 × 105 PBMCs remained independently associated with CMV infection (HR 3.1, 95% CI 1.2-7.8, p = 0.019). Conclusions: KT recipients with low IFN-γ-producing T cells measured by the ELISpot assay are more likely to develop CMV infection after transplantation. Therefore, measurement of nonspecific cell-mediated immunity ELISpot responses could potentially stratify recipients at risk of CMV infection (Thai Clinical Trials Registry, TCTR20210216004).

A social media analysis of quarantined passengers’ social-supported coping and resilience-building experiences

Cruise lines are adopting onboard quarantine as part of emergency response measures to the global pandemic. However, little is known about the social support embedded in the social-mediated communication process to assist passengers in coping and building resilience. Guided by the conservation of resource theory, this study adopted the netnography approach to analyze the online interactions between quarantined passengers on Diamond Princess and netizens. A qualitative approach was employed to analyze the content of a relational dataset consisting of 14 research subjects, 3,368 posts, and 67,964 comments. The results not merely showed the changing foci of the comments over time but also revealed the supporting role played by social media. The constant engagement with netizens provided passengers with information and social support, which contributed to their coping and resilience-building. These findings offer a new theoretical perspective on incorporating social media in tourism crisis management, as well as practical implications for cruise lines and tourism organizations to optimize their resource utilization for marketing recovery.

Seismic response and capacity of inelastic acceleration‐sensitive nonstructural elements subjected to building floor motions

AbstractThe paper investigates the seismic response of nonstructural elements (NEs), focusing on acceleration‐sensitive components housed in buildings, modelled as inelastic Ibarra–Medina–Krawinkler (SDOF) systems. Incremental dynamic analysis (IDA) is carried out considering (a) representative suites of building floor motions (real loading histories recorded within reinforced concrete (RC) buildings and table testing protocol inputs) and (b) a wide range of NE models (with elastic frequencies ranging within 1–9 Hz). The Ibarra‐Medina‐Krawinkler (IMK) model was implemented in OpenSees, defining the key modeling parameters according to the formulations provided by Lignos and Krawinkler. Both IDA curves and component (acceleration) amplification factor (CAF) are characterized, also considering statistical measures. The seismic capacity of the investigated NEs is estimated through fragility curves, accounting for five incremental damage states (DSs). The fragility parameters are correlated with the frequency of the NE models, and (statistical‐based) closed‐form capacity criteria are provided. The study provides a robust technical and scientific methodological framework for assessing the seismic capacity of NEs that can be modeled by inelastic SDOF systems. The findings have a potential major impact on both research and practice, enriching scientific knowledge and providing useful applicative tools. In particular, quantitative response and capacity measures are supplied, and the developed capacity criteria can be particularly useful for expeditious but reliable design and assessment, as well as for comparison purposes.

Lower limb muscle MRI fat fraction is a responsive outcome measure in CMT X1, 1B and 2A.

With potential therapies for many forms of Charcot-Marie-Tooth disease (CMT), responsive outcome measures are urgently needed for clinical trials. Quantitative lower limb MRI demonstrated progressive calf intramuscular fat accumulation in the commonest form, CMT1A with large responsiveness. In this study, we evaluated the responsiveness and validity in the three other common forms, due to variants in GJB1 (CMTX1), MPZ (CMT1B) and MFN2 (CMT2A). 22 CMTX1, 21 CMT1B and 21 CMT2A patients and matched controls were assessed at a 1-year interval. Intramuscular fat fraction (FF) was evaluated using three-point Dixon MRI at thigh and calf level along with clinical measures including CMT examination score, clinical strength assessment, CMT-HI and plasma neurofilament light chain. All patient groups had elevated muscle fat fraction at thigh and calf levels, with highest thigh FF and atrophy in CMT2A. There was moderate correlation between calf muscle FF and clinical measures (CMTESv2 rho = 0.405; p = 0.001, ankle MRC strength rho = -0.481; p < 0.001). Significant annualised progression in calf muscle FF was seen in all patient groups (CMTX1 2.0 ± 2.0%, p < 0.001, CMT1B 1.6 ± 2.1% p = 0.004 and CMT2A 1.6 ± 2.1% p = 0.002). Greatest increase was seen in patients with 10-70% FF at baseline (calf 2.7 ± 2.3%, p < 0.0001 and thigh 1.7 ± 2.1%, p = 0.01). Our results confirm that calf muscle FF is highly responsive over 12 months in three additional common forms of CMT which together with CMT1A account for 90% of genetically confirmed cases. Calf muscle MRI FF should be a valuable outcome measure in upcoming CMT clinical trials.

Constructing semi-arid ecological barriers to prevent desertification

&lt;p&gt;Semi-arid regions worldwide face escalating challenges, including water resource shortages, ecological fragility, and relentless expansion of desertification. Here, we propose the establishment of a worldwide Semi-arid Ecological Barrier (SAEB) as a proactive measure in response to these challenges to curtail desertification and alleviate extreme events. Beyond its immediate benefits, the SAEB holds significant promise for future global carbon control efforts. This perspective offers a case study exemplifying the principles of ecological civilization, focusing on preventing desertification in the Yellow River Basin. Policy of ecological recover, such as the ��Grain for Green�� project in China, has shown to be effective in strengthening the SAEB. It contributes valuable insights into innovative strategies for addressing water scarcity, ecological fragility, and desertification expansion.&lt;/p&gt;