Search Results (2,452)

Today’s rapidly increasing number and performance of Remotely Piloted Aircraft Systems (RPASs) and sensors allows for an innovative approach in monitoring, mitigating, and responding to natural disasters and risks. At present, there are 100s of different RPAS platforms and smaller and more affordable payload sensors. As natural disasters pose ever increasing risks to society and the environment, it is imperative that these RPASs are utilized effectively. In order to exploit these advances, this study presents the development and validation of a Natural Disaster Information System (NDIS), a geospatial decision-support framework for RPAS-based natural hazard missions. The system integrates a global geohazard database with specifications of geophysical sensors and RPAS platforms to automate mission planning in a generalized form. NDIS v1.0 uses decision tree algorithms to select suitable sensors and platforms based on hazard type, distance to infrastructure, and survey feasibility. NDIS v2.0 introduces a Random Forest method and a Critical Path Method (CPM) to further optimize task sequencing and mission timing. The latest version, NDIS v3.8.3, implements a staggered decision workflow that sequentially maps hazard type and disaster stage to appropriate survey methods, sensor payloads, and compatible RPAS using rule-based and threshold-based filtering. RPAS selection considers payload capacity and range thresholds, adjusted dynamically by proximity, and ranks candidate platforms using hazard- and sensor-specific endurance criteria. The system is implemented using ArcGIS Pro 3.4.0, ArcGIS Experience Builder (2025 cloud release), and Azure Web App Services (Python 3.10 runtime). NDIS supports both batch processing and interactive real-time queries through a web-based user interface. Additional features include a statistical overview dashboard to help users interpret dataset distribution, and a crowdsourced input module that enables community-contributed hazard data via ArcGIS Survey123. NDIS is presented and validated in, for example, applications related to volcanic hazards in Indonesia. These capabilities make NDIS a scalable, adaptable, and operationally meaningful tool for multi-hazard monitoring and remote sensing mission planning. Full article

Laboratories are complex and dynamic environments where diverse hazards—including toxic gas leakage, volatile solvent combustion, and unexpected fire ignition—pose serious threats to personnel safety and property. Traditional monitoring systems relying on single-type sensors or manual inspections often fail to provide timely warnings or comprehensive hazard perception, resulting in delayed response and potential escalation of incidents. To address these limitations, this study proposes a multi-node laboratory safety monitoring and early warning system integrating multi-source sensing, heterogeneous communication, and cloud–edge collaboration. The system employs a LoRa-based star-topology network to connect distributed sensing and actuation nodes, ensuring long-range, low-power communication. A Raspberry Pi-based module performs real-time facial recognition for intelligent access control, while an OpenMV module conducts lightweight flame detection using color-space blob analysis for early fire identification. These edge-intelligent components are optimized for embedded operation under resource constraints. The cloud–edge–app collaborative architecture supports real-time data visualization, remote control, and adaptive threshold configuration, forming a closed-loop safety management cycle from perception to decision and execution. Experimental results show that the facial recognition module achieves 95.2% accuracy at the optimal threshold, and the flame detection algorithm attains the best balance of precision, recall, and F1-score at an area threshold of around 60. The LoRa network maintains stable communication up to 0.8 km, and the system’s emergency actuation latency ranges from 0.3 s to 5.5 s, meeting real-time safety requirements. Overall, the proposed system significantly enhances early fire warning, multi-source environmental monitoring, and rapid hazard response, demonstrating strong applicability and scalability in modern laboratory safety management. Full article

Background: Plant-based diets are associated with reduced risk of chronic diseases and improved health outcomes. However, sustaining dietary changes remains challenging. Digital interventions—including virtual culinary medicine programs, web-based nutrition coaching, SMS and email reminders, mobile application–based self-management, and hybrid community programs—offer promising strategies to support behavior change, enhance cooking skills, and improve dietary adherence. These approaches are relevant for both healthy individuals and those living with chronic conditions. Methods: We conducted a narrative review of studies published between 2000 and 2025 in PubMed/MEDLINE, Scopus, and Web of Science, supplemented with manual searches. Included studies comprised randomized controlled trials, quasi-experimental designs, feasibility studies, and qualitative research. Interventions were categorized by modality (SMS, email, web platforms, mobile apps, virtual culinary programs, and hybrid formats) and population (healthy adults, patients with chronic diseases). Outcomes examined included dietary quality, self-efficacy, psychosocial well-being, and program engagement. Results: Most studies reported improvements in dietary quality, cooking skills, nutrition knowledge, and psychosocial outcomes. Virtual cooking programs enhanced dietary adherence and engagement, particularly among individuals at cardiovascular risk. Digital nutrition education supported behavior change in chronic disease populations, including patients with multiple sclerosis. SMS and email reminders improved self-monitoring and participation rates, while mobile applications facilitated real-time feedback and goal tracking. Hybrid programs combining online and in-person components increased motivation, social support, and long-term adherence. Reported barriers included limited technological access or skills, lack of personalization, and privacy concerns. Conclusions: Virtual culinary medicine programs and other digital microinterventions—including SMS, email, web, mobile, and hybrid formats—are effective tools to promote plant-based diets. Future interventions should focus on personalized, accessible, and hybrid strategies, with attention to underserved populations, to maximize engagement and sustain long-term dietary change. Full article

The Advanced Very High-Resolution Radiometer (AVHRR) onboard NOAA-7 through NOAA-19 satellites has been the primary data source for two Climate Data Records (CDRs) that were developed specifically for Arctic and Antarctic studies: the AVHRR Polar Pathfinder (APP) and Extended AVHRR Polar Pathfinder (APP-x). With the decommissioning of these satellites and the loss of the AVHRR, a method for extending the CDRs with the Visible Infrared Imaging Radiometer Suite (VIIRS) on NOAA’s recent satellites is presented. The goal is to produce long-term, continuous, consistent, and traceable CDRs for polar climate research. As a result, APP and APP-x can now be continued as the VIIRS Polar Pathfinder (VPP) and Extended VIIRS Polar Pathfinder (VPP-x) CDRs. To ensure consistency, a VIIRS Global Area Coverage (VGAC) dataset that is comparable to AVHRR GAC data was used to develop an analogous VIIRS Polar Pathfinder suite. Five VIIRS bands (I1, I2, M12, M15, and M16) were selected to correspond to AVHRR Channels 1, 2, 3b, 4, and 5, respectively. A multivariate regression approach was used to intercalibrate these VIIRS bands to AVHRR channels based on data from overlapping AVHRR and VIIRS observations from 2013 to 2018. The data from 2012 and 2019 were reserved for independent validation. For the Arctic region north of 60°N at 14:00/04:00 Local Solar Time (LST) during 2012–2019, mean biases between APP and VPP composites at a spatial resolution of 5 km are −0.85%/3.03% (Channel 1), −1.22%/3.65% (Channel 2), −0.18 K/0.81 K (Channel 3b), 0.01 K/0.24 K (Channel 4), and 0.07 K/0.19 K (Channel 5). Mean biases between APP-x and VPP-x at a spatial resolution of 25 km for the same region and period are −1.52%/−1.48% for surface broadband albedo, 0.69 K/0.61 K for surface skin temperature, and −0.011 m/−0.017 m for sea ice thickness. Similar results were observed for the Antarctic region south of 60°S at 14:00/02:00 LST, indicating strong agreement between APP and VPP, and between APP-x and VPP-x. Full article

Recent protest movement studies have focused almost exclusively on the impact of social media platforms in the organization of protests movements. These inquiries contend that mainstream media platforms are stale and ineffective. They claim that the diffusion of social media technologies has rendered mainstream media platforms insignificant in influencing protest movements. However, these inquiries fail to unbundle these media platforms for a more succinct evaluation. These anecdotal illustrations are lacking in evidence which tests the validity of these claims. This study is commissioned to bridge that gap. This study examines the influence of different media platforms in contentious politics and solidarity building by evaluating how protesters learned about and planned the 2019 #Ikokwu4 protests in Port Harcourt, Rivers State of Nigeria. The study utilizes explanatory mixed methods research, comprising a survey of protesters (N = 384) in Port Harcourt and semi-structured interviews with participants who participated in the protests. Analyses of survey data indicate that protesters who used radio, Facebook, and WhatsApp to learn about and plan the 2019 #Ikokwu4 protests in Nigeria and who reported to have had previous protest experience were more likely to report joining on the first day of the protest. The study demonstrates the emancipatory aspects of radio as an instrument of protests. The study highlights the need to unbundle media platforms when studying how such media platforms influence protest movements. Full article

Background: Digital transformation is reshaping public organizations worldwide, yet in low-resource contexts, its success is constrained by weak infrastructure and governance. In India, programs such as the Ayushman Bharat Digital Mission and the Aspirational Districts Programme rely on meso-level officers who act as key managerial intermediaries, but their organizational challenges remain understudied. Aim: This study examines sub-district health and nutrition officers’ experiences, organizational barriers, and adaptive strategies in implementing digital reforms. Methods: Eight in-depth interviews were conducted with Medical Officers in Charge (MOICs) and Child Development Project Officers (CDPOs) across urban, semi-urban, rural, and flood-prone blocks of Muzaffarpur, Bihar. Data were transcribed, translated, and thematically analyzed using Braun and Clarke’s approach, informed by organizational and technology adoption theories. Results: Officers valued digital tools for transparency and real-time monitoring but faced systemic barriers, including hardware decay, poor connectivity, fragmented platforms, and limited fiscal autonomy. Despite these, they displayed managerial agency through informal infrastructures such as WhatsApp, peer mentoring, and parallel records. COVID-19 accelerated digital use while widening inequities. Conclusions: Meso-level officers are critical enablers of organizational resilience. Their experiences highlight how leadership, governance, and adaptive management shape digital transformation in resource-constrained settings. Full article

Throughout the 2019 coronavirus disease pandemic, various vaccine regimens were implemented. Real-world data comparing their effectiveness during the BA.1/BA.2 Omicron wave remain limited. We prospectively enrolled healthcare workers who had completed two doses of mRNA or ChAdOx1 (A) vaccine and received an mRNA vaccine booster (BNT162b2 (P) or mRNA-1273 (M)). Neutralizing antibody levels were measured 6 months after the primary vaccinations and 1 month post-booster vaccination using a surrogate virus neutralization assay. Breakthrough infections were identified through institutional surveillance and the national reporting system. Among 318 participants (P-P-P: 71; A-A-P: 205; A-P-P: 19; M-M-M: 23), pre-booster neutralizing activity was lowest in the ChAdOx1-primed groups. One month post-booster vaccination, the neutralizing activity exceeded 97% across all regimens. The cumulative incidence of breakthrough infection varied significantly from 43.7% (P-P-P) to 84.2% (A-P-P). In adjusted Cox models, A-P-P showed the highest infection risk (HR 2.99, 95% CI 1.65–5.42). In summary, mRNA boosters restored neutralizing activity, but during the early BA.1/BA.2 Omicron wave they were less effective in preventing infections regardless of disease severity. Therefore, antibody titers alone are insufficient for evaluating protection, underscoring the need for continuous monitoring to support timely policy decisions during epidemic surges. Full article

Biometric authentication, such as facial recognition and fingerprint scanning, is now standard on mobile devices, offering secure and convenient access. However, the processing of biometric data is tightly regulated under the European Union’s General Data Protection Regulation (GDPR), where such data qualifies as “special category” personal data when used for uniquely identifying individuals. Compliance requires meeting strict conditions, including explicit consent and data protection by design. Passkeys, the modern name for FIDO2-based authentication credentials developed by the FIDO Alliance, enable passwordless login using public key cryptography. Its “match-on-device” architecture stores biometric data locally in secure hardware (e.g., Android’s Trusted Execution Environment, Apple’s Secure Enclave), potentially reducing the regulatory obligations associated with cloud-based biometric processing. This paper examines how Passkeys are implemented on Android and iOS platforms and their differences in architecture, API access, and hardware design, and how those differences affect compliance with the GDPR. Through a comparative analysis, we evaluate the extent to which each platform supports local processing, data minimization, and user control—key principles under GDPR. We find that while both platforms implement strong local protections, differences in developer access, trust models, and biometric isolation can influence the effectiveness and regulatory exposure of Passkeys deployment. These differences have direct implications for privacy risk, legal compliance, and implementation choices by app developers and service providers. Our findings highlight the need for platform-aware design and regulatory interpretation in the deployment of biometric authentication technologies. This work can help inform stakeholders, policymakers, and legal experts in drafting robust privacy and ethical policies—not only in the realm of biometrics but across AI technologies more broadly. By understanding platform-level implications, future frameworks can better align technical design with regulatory compliance and ethical standards. Full article

Retailers of digital goods often use discount pricing to attract consumers. To make an effective promotion, they naturally want to understand consumers’ valuation. Nonetheless, rigorous research is lacking on how to use consumer ratings on the retailer side. Our study aims to fill this research gap by investigating how retailers can determine optimal discount size in response to consumer ratings. We use both an analytical model and an empirical analysis. Our analytical results showed that discount size decreases with consumer ratings for non-supreme ratings. Nevertheless, there is no significant impact for supreme ratings. In addition, we find that consumers’ confidence and the regular price of digital goods are critical moderators. Using a unique dataset of 419 online audiobooks, we empirically test the proposed hypotheses. The predictions of our model are consistent with empirical evidence. Our study demonstrates that retailers can provide smaller discounts when consumers give higher ratings of digital goods. In addition, consumers’ confidence enlarges the consumer rating effect, while the regular price reduces such effect. Our findings can be applied to other digital goods such as digital movies, software/APP and online newspapers. Full article

Damage control surgery (DCS) is a staged surgical strategy for rapid control of life-threatening bleeding, followed by physiological stabilization and delayed definitive repair. Abdomino-pelvic packing (APP)—placing compressive material within the pelvis and/or abdomen to tamponade bleeding—is a cornerstone of DCS as a temporizing measure to achieve hemostasis and stabilization in critically unstable patients. This narrative review synthesizes current evidence on DCS with a focus on APP—a technique historically developed in trauma and orthopedic surgery for exsanguinating pelvic bleeding but adaptable to gynecologic and obstetric emergencies. We outline the historical evolution, physiological basis, and stepwise protocol of DCS, adapted to specialty-specific conditions such as postpartum hemorrhage, placenta accreta spectrum, uterine rupture, and hepatic rupture in HELLP syndrome, as well as oncologic surgeries (debulking, exenteration, lymphadenectomy) and benign procedures (trocar-entry injuries in laparoscopy, presacral bleeding in sacrocolpopexy, and retroperitoneal hemorrhage in deep-infiltrating endometriosis). Modern adjuncts—including early tranexamic acid, topical hemostatic agents, and multidisciplinary coordination—have transformed packing from a last-resort maneuver into an integrated component of staged hemorrhage control. In OB/GYN, APP allows for successful hemostasis in 75–90% of cases, with significantly lower mortality rates than trauma surgery. In conclusion, APP as a potentially life-saving maneuver within DCS requires integration into standardized, institution-wide hemorrhage protocols in OB/GYN. Training, simulation, and guideline adoption are critical, particularly in resource-limited settings where advanced interventions for catastrophic bleeding are inaccessible. Full article

Aim: The study developed and validated AppER, an mHealth tool for informal caregivers of children with Duchenne Muscular Dystrophy, and examined differences between app users and non-users. Methods: Four phases were followed: (1) focus groups with experts and caregivers to identify care-related domains; (2) prototype development and validity testing (CVR, I-CVI, I-FVI) using the MARS scale; (3) implementation of the final app; and (4) psychosocial profiling of 88 caregivers (42 users and 46 non-users) measuring quality of life, dependency, somatic symptoms, and coping strategies. Results: AppER showed high content and face validity, surpassing reference thresholds. In the psychosocial analysis, users reported lower perceived quality of life than non-users, despite no significant differences in dependency, somatic symptoms, or coping strategies. Conclusions: Employment patterns differed: more users were dedicated to household tasks, while more non-users were self-employed, suggesting economic factors may affect app uptake and quality of life perceptions. Findings indicate AppER is a valid, well-rated support tool, and that caregivers with lower perceived quality of life may be more inclined to adopt digital health solutions, potentially to address complex care demands. Designing targeted digital interventions may be particularly valuable for those in less favorable socioeconomic contexts. Because of the small sample and between-group imbalances, results are exploratory and warrant confirmation in larger, balanced samples. Full article

Background/Objectives: Peer support offers a promising approach for improving psychosocial outcomes among adults with type 1 diabetes (T1D). However, research has focused largely on the recipients of peer support rather than the individuals who provide support. This pilot study investigates the impact of delivering support on diabetes distress and other secondary mental health outcomes (e.g., depressive symptoms, resilience, and perceived social support). Methods: This pre–post single-cohort study recruited 44 adults with T1D who underwent a six-hour Zoom-based peer supporter training program designed to equip them with support-related skills (asking open-ended questions, making reflections, expressing empathy). Of this group, 36 served as peer supporters for REACHOUT, a six-month mental health support intervention delivered via mobile app. Assessments were conducted at baseline and after six months and measured diabetes distress (Type 1 Diabetes Distress Scale), depressive symptomatology (Patient Health Questionnaire-8), resilience (Diabetes Strengths and Resilience Measure), and perceived social support. Unadjusted and adjusted linear mixed models were performed for each outcome measure of interest. Results: Peer supporters had a mean age of 41 ± 16 years, with a majority identifying as female (75%). At baseline, peer supporters had little to no diabetes distress (50%) and no to mild depressive symptomatology (72%). Mean scores at baseline for diabetes distress, depressive symptoms, resilience, and perceived social support were sustained at 6 months post-intervention. Conclusions: Among peer supporters whose diabetes distress scores start around the target range, ongoing maintenance of these levels may reflect a favorable outcome associated with delivering mental health support. Full article

Butylparaben (BP), a widely used preservative, was implicated in cognitive impairment, though its neurotoxic mechanisms remain elusive. Basal forebrain cholinergic neurons (BFCN) are selectively lost in dementias, contributing to cognitive decline. To explore different mechanisms related with BFCN loss, we employed BF SN56 cholinergic wild-type or silenced cells for Tau, amyloid-beta precursor protein (βApp), acetylcholinesterase (AChE), or glycogen synthase kinase-3 beta (GSK3β) genes, exposing them to BP (0.1–80 µM) for 1 or 14 days alongside triiodothyronine (T3; 15 nM), N-acetylcysteine (NAC; 1 mM), or recombinant heat shock protein 70 (rHSP70; 30 µM). BP disrupted cholinergic transmission by AChE inhibition and provoked cell death through thyroid hormones (THs) pathway disruption, Aβ/p-Tau protein accumulation, AChE-S overexpression, and oxidative stress (OS). Aβ/p-Tau accumulation was correlated with HSP70 downregulation, OS exacerbation, and GSK3β hyperactivation (for p-Tau). BP-induced OS was mediated by reactive oxygen species (ROS) overproduction and nuclear factor erythroid 2-related factor 2 (NRF2) pathway disruption. All observed effects were contingent upon TH signaling impairment. These findings uncover novel mechanistic links between BP exposure and BFCN neurodegeneration, providing a framework for therapeutic strategies. Full article

Digital transformation in higher education necessitates a central role for university faculty, yet there is a lack of comprehensive tools to measure their actual pedagogical use of technology. This study aims to refine the definition of a composite indicator to evaluate mobile technology adoption among social science university teachers. Using the results of the validated MOBILE-APP questionnaire, administered to a sample of N = 295 teachers from various social science degree programs, we employed multilevel structural equation modeling (SEM) to develop and implement a synthetic indicator for assessing mobile technology adoption levels among educators. The analysis of the considered factors (motivation, training, tools, and use) revealed differences in mobile technology adoption based on degree program, age, and previous experience. High motivation, training, use of institutional tools, and propensity for use promote the adoption of mobile technologies. Three levels of mobile technology adoption are identified and characterized. This synthetic indicator can be used both technically and socially to track the evolution of mobile technology adoption, enabling comparative analyses and longitudinal assessments that inform strategic decisions in training, infrastructure, and curriculum development. This research represents a step forward in the development of quantitative indicators and the assessment of research practices. Full article

Honey bee health and productivity are strongly linked to management practices and biosecurity measures. We collected and analyzed 744 practice records from 191 peer-reviewed field studies published since 1995, each documenting the impact of a specific hive intervention on colony health or productivity parameters. Practices were categorized into good beekeeping practices (n = 128, 17.2%) and biosecurity measures (n = 616, 82.8%) and grouped by management or pathogen theme, geographic region, and season. Most research originated from Europe (34.6%) and North America (33.4%), with nearly all focused on Apis mellifera (99.9%). Varroa control dominated (57.0%), followed by general apiary management (17.2%) and american foulbrood (9.7%). For varroosis, “soft” acaricides such as oxalic and formic acid accounted for 58.5% of records, while “hard” synthetic products represented 21.0%. Within general apiary management, colony management was most frequent (46.9%). For american foulbrood, antibiotics (41.7%) and biotechnical methods (22.2%) were prominent. Tropilaelaps app. treatments relied mainly on “soft” acaricides (81.5%), while small hive beetle control focused on in-hive traps (55.9%). Seasonally, most interventions occurred from August to October, with AFB measures peaking in spring and early summer. The dataset highlights regional research gaps and offers a structured, expandable framework to guide future research and support evidence-based decision-making in beekeeping and advisory services. Full article