Search Results (1,805)

Coral reef ecosystems are declining rapidly due to climate change, disease, and anthropogenic stressors, driving the expansion of land-based coral propagation for reef restoration. A major bottleneck in these efforts is the manual measurement of coral recruit tissue area from microscopy images, which requires 2–7 min per image and limits scalability. We present a hierarchical deep learning pipeline that automates this measurement by integrating YOLO-based detection with Segment Anything Model (SAM) segmentation. YOLO localizes recruits and classifies them by developmental stage; stage-specific fine-tuned SAM models then segment live tissue using bounding box and background point prompts to suppress segmentation leakage and improve boundary precision. Surface area is computed directly from the segmented masks using pixel size extracted from image metadata. The pipeline reduces processing time to approximately 3–5 s per image—a 24–140× speedup over manual tracing. Evaluated on 3668 microscopy images from two national coral research facilities, the system achieves a mean IoU exceeding 95% and an auto-acceptance rate (AAR) of 71.51%, where predicted-to-ground-truth area ratios fall within a ±5% tolerance of expert annotation, substantially reducing manual workload while maintaining measurement reliability across species, developmental stages, and imaging conditions. This workflow addresses a critical bottleneck in restoration research and demonstrates the broader applicability of AI-based image analysis in marine ecology. Full article

Background: Almost all correlation measures currently available are unable to directly handle missing values. Typically, missing values are either ignored completely by removing them or are imputed and used in the calculation of the correlation coefficient. In either case, the correlation value will be impacted based on the perspective that the missing data represents no useful information. However, missing values occur in real datasets for a variety of reasons. In metabolomics datasets a major reason for missing values is that a specific measurable phenomenon falls below the detection limits of the analytical instrumentation (left-censored values). These missing data are not missing at random, but represent potentially useful information by virtue of their “missingness” at one end of the data distribution. Methods: To include this information due to left-censored missingness, we propose the information-content-informed Kendall-tau (ICI-Kt) methodology. We develop a statistical test and then show that most missing values in metabolomics datasets are the result of left-censorship. Next, we show how left-censored missing values can be included within the definition of the Kendall-tau correlation coefficient, and how that inclusion leads to an interpretation of information being added to the correlation. We also implement calculations for additional measures of theoretical maxima and pairwise completeness that add further layers of information interpretation in the methodology. Results: Using both simulated and over 700 experimental data sets from the Metabolomics Workbench, we demonstrate that the ICI-Kt methodology allows for the inclusion of left-censored missing data values as interpretable information, enabling both improved determination of outlier samples and improved feature–feature network construction. Conclusions: We provide explicitly parallel implementations in both R and Python that allow fast calculations of all the variables used when applying the ICI-Kt methodology on large numbers of samples. The ICI-Kt methods are available as an R package and Python module on GitHub. Full article

Aspergillosis is a group of different invasive and non-invasive diseases affecting the lung and other organs, caused by species of the genus Aspergillus. Additionally, complications associated with treatment and the increasing emergence of antifungal-resistant strains of Aspergillus spp. are high-impact problems. For these reasons, a combined approach of diagnostic tests is necessary to reach an accurate and timely diagnosis. This review aims to describe some biomarkers and their usefulness for the diagnosis of aspergillosis. Among the findings obtained in different studies, the nature, analytical performance and usefulness for diagnosis in different clinical forms of this disease are described. Currently, the main biomarkers used in the diagnosis of Aspergillus disease fall into three categories: membrane components, specific DNA sequences and metabolic products. The detection of biomarkers is one of the most important innovations of recent decades in the field of medical mycology, as it is a diagnostic aid that allows the timely detection of infections and decreases the time of administration of antifungal therapy. Full article

Background/Objectives: Breast cancer is one of the most prevalent cancers among women, with notable increases among women younger than 50 years. Knowledge about breast cancer and preventive measures (e.g., early detection) are key to reducing breast cancer morbidity and mortality. Many graduate students fall within an age range when breast cancer risk starts to rise. However, research focused specifically on graduate students’ breast cancer knowledge and practices of preventive measures are sparse. Methods: This scoping review aims to synthesize the literature on breast cancer knowledge and practice of preventive measures among graduate students in a global context. Four databases (PubMed, CINAHL, APA PsycINFO, Embase) were searched for articles published between 2014 and 2024, and the following inclusion criteria were applied: full-text peer-reviewed articles available online; target population includes graduate students aged 20 to 50 years; English language; and, cross-sectional, cohort, case–control, ecological, and experimental/intervention studies. Two reviewers independently conducted article screening and data extraction using Covidence. Results: Sixteen studies met the selection criteria. Knowledge of breast cancer was examined in 94% (15/16) of the included studies and 75% (12/16) of the studies assessed practice of prevention measures (e.g., breast self-examination) among graduate students. Overall, most studies reported poor knowledge and limited uptake of prevention practices. Educational background (e.g., years of education, academic discipline and GPA), access to healthcare services, and other socioeconomic characteristics were commonly reported factors significantly associated with breast cancer knowledge and practice of preventive measures in graduate students. Conclusions: These findings may inform targeted educational interventions to increase knowledge and promote the early detection and prevention of breast cancer among graduate students. Full article

Background/Objectives: Sarcopenia is a progressive decline in skeletal muscle strength and mass, leading to decreased functionality, metabolic disorders, morbidity, and mortality. There are a number of sarcopenia screening tools, such as the SARC-F questionnaire (that includes noting strength, assistance with walking, ability to raise from the chair, climb stairs, and falls), with its augmented forms that have added calf circumference (SARC-CalF), BMI and age (SARC-F + EBM), and the Ishii score, which show variable performance across populations. However, these were developed and validated mostly in Asian cohorts. To evaluate the diagnostic accuracy of these tools for the European Working Group on Sarcopenia in Older People (EWGSOP2), as well as define sarcopenia in hospitalized East European older adults, with sex and obesity stratification. Methods: Sarcopenia was diagnosed using the EWGSOP2. ROC analyses with DeLong tests assessed SARC-F, SARC-CalF, SARC-F + EBM, and the Ishii score in 278 Romanian inpatients (probable sarcopenia n = 201/278, 72.3%; confirmed n = 77/278, 27.7%). Results: Probable sarcopenia was noted as good-excellent discrimination against across all tools (AUCs 0.764–0.812); confirmed sarcopenia was noted as SARC-CalF superior (AUC = 0.743), followed by SARC-F + EBM (0.697), the Ishii score as moderate (0.667), and SARC-F was limited (0.591; p < 0.001 vs. augmented). SARC-CalF optimal cut-offs varied significantly: 4–6 (probable) vs. ≥11 (confirmed). Sex-stratified outcomes had excellent probable detection in both sexes, and this was confirmed to be superior in men. The Ishii score thresholds were 152/244 vs. Asian ≥ 105/120. Obesity required higher cut-offs with high NPVs (77–100%), confirming rule-out utility and SARC-F + EBM performing the best, both in the obesity and sarcopenic obesity subgroups (AUCs 0.742, 0.964). Conclusions: Augmented SARC-F scores outperformed the original SARC-F for confirmed sarcopenia in multimorbid Europeans, with SARC-F CalF having the best performance overall. Population-specific (sex/obesity) data-driven thresholds are essential, especially for the Ishii score, as this first Romanian validation reveals limitations of Asian norms in European cohorts, thus advocating for European recalibration. Full article

This paper presents an ARMv8/NEON-oriented implementation of NCC-Sign targeting the NTT-friendly trinomial parameter sets (NCC-Sign-1/3/5), whose dominant cost arises from mixed-radix NTT computations with $n=2^a·3^b$. We design lane-local SIMD kernels—including a four-lane Montgomery multiply–reduce, a centered modular reduction pass, a fused stage-0 butterfly, and streamlined radix-2/radix-3 pipelines—and extend them with three further optimizations: (i) radix-2 multi-stage butterfly merging to halve intermediate load/store traffic, (ii) a stride-3 vectorization technique exploiting NEON structure load/store instructions (vld3q/vst3q) to fully vectorize small-len radix-3 stages that would otherwise fall back to scalar execution, and (iii) NEON-parallel pointwise Montgomery multiplication. Using cycle-accurate PMU measurements under identical toolchains for baseline and optimized builds on Apple M1 Pro, we observe geometric-mean speedups of 1.40× for key generation, 2.24× for signing, and 2.01× for verification across NCC-Sign-1/3/5, with per-kernel gains of up to 5–6× for NTT/INTT and 7.5× for pointwise multiplication. To contextualize these results, we provide a direct comparison with the NEON-optimized ML-DSA (Dilithium) implementation of Becker et al. on the same platform, a cross-platform evaluation on Arm Cortex-A72 (Raspberry Pi 4), a Montgomery-versus-Barrett microbenchmark supporting our design choice, and an empirical constant-time assessment via dudect confirming that no timing leakage is detected in any NEON kernel under 30 million measurements. Full article

Inpatient falls often occur at the bedside during unsupervised bed egress or bed exit attempts. Many artificial intelligence methods predict fall risk, but clinical value depends on workflow-ready decision support. This scoping review, reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR), mapped AI-driven inpatient fall prevention systems using continuous monitoring data that generate explicit action triggers. We searched PubMed, Scopus, and Web of Science Core Collection for English-language studies published between 2016 and 2026 on 15 February 2026. Of 200 records identified, 32 duplicates were removed, and 168 records were screened. Eighty-three full-text reports were assessed for eligibility. Thirty-eight studies were included in the Tier 1 synthesis as action-trigger decision support systems, and 20 were classified as Tier 2 prediction or detection only to characterize evidence gaps. Tier 1 systems clustered into room-based monitoring with direct nurse alerting, wearable or batteryless sensing for bed egress and bed or chair exit alarms, and bed-centered early warning. Reporting was often incomplete for implementation-critical metrics such as alert burden, false alarms, response times, alert routing, and downstream actions. We propose a minimum operational reporting set to support clearer evaluation and comparison of AI-enabled inpatient fall-prevention systems in real-world ward settings. Full article

The coronavirus disease 19 pandemic disrupted pediatric respiratory infections through non-pharmaceutical interventions and altered contact patterns. Long-term comparisons across the pandemic timeline in children remain limited. In this study, we analyzed 15,657 respiratory specimens from patients ≤ 18 years at Dankook University Hospital (2007–2023) using multiplex polymerase chain reaction assays targeting 15 viruses. Age-stratified positivity rates were compared across pandemic phases. Children ≤ 6 years comprised 88.61% of the study population. Human rhinovirus showed the highest detection rate (24.06%), followed by adenovirus (12.33%), respiratory syncytial virus-subtypes A and B (RSV-A: 11.13%; RSV-B: 8.65%), human parainfluenza virus-type 3 (HPIV-3; 6.21%), human metapneumovirus (HMPV; 5.33%), and enterovirus (2018–2023; EV; 10.96%). Monthly distributions differed (p < 0.001). RSV peaked in late autumn and winter; influenza and seasonal coronaviruses in winter and spring; HMPV, HPIV-3, EV, and human bocavirus in summer and fall. Positivity declined during the pandemic, rebounding in 2023, most prominently among children aged 1–6 years (84.91%). HPIV-3 and EV increased (p < 0.001). RSV-A predominated pre-pandemic, whereas RSV-B showed a non-significant relative increase post-pandemic; no subtype differences occurred during the pandemic. Findings demonstrate pathogen-specific shifts in predominance and seasonality and support ongoing surveillance and pediatric care planning. Full article

Background: Traditional functional mobility assessments often fail to detect subclinical postural decline in active aging populations. This study introduces the Head–Sternum Dissociation Index as a novel digital biomarker to identify latent sensorimotor deficits before macroscopic balance failure occurs. Methods: Ninety-four participants (Young, Middle-Aged Civil, Middle-Aged Dancers, and Older Adults) performed instrumented limits of stability tasks, specifically functional and lateral reach tests, utilizing a three-sensor inertial measurement unit configuration. Postural strategies were quantified via the Head–Sternum Dissociation Index and the peak ratio of corrective micro-movements, validating the sensor output against a gold-standard force platform. Results: A significant kinematic breakpoint in postural control was identified at age 55 (p < 0.001). However, Middle-Aged Civilians exhibited early kinematic divergence despite maintaining normal Timed Up and Go test performance. Receiver operating characteristic analysis revealed distinct, sex-specific physiological limits: aging males predominantly adopted a rigid “Stiffness” strategy (peak ratio ≤ 1.15, head–sternum dissociation threshold > 0.63°), while females utilized a broader, more permissive “Continuous” strategy (head–sternum dissociation threshold > 0.31°). Notably, recreational rhythmic training (dance) completely neutralized this age-related decay, with middle-aged dancers maintaining highly efficient, youthful stabilization profiles (Cohen’s d = 2.20). Conclusions: The Head–Sternum Dissociation Index, combined with relative corrective frequency, successfully phenotypes early sensorimotor erosion. These findings advocate for the integration of sex-specific kinematic screening into primary care, allowing clinicians to prescribe targeted interventions well before clinical fall risk manifests. Full article

We report the enhancement of organic photodetector (OPD) performance through the incorporation of CsPbBr₃ perovskite nanocrystals (PNCs) into P3HT:PCBM devices. The optimized device (HPD_01) exhibits a maximum responsivity of 0.083 A/W and a specific detectivity of ~4.7 × 10¹⁰ Jones, and a minimum NEP of 5.2 × 10⁻¹² W·Hz^−1/2 at the self-powered operating point (V ≈ 0 V), outperforming the nanoparticle-free reference. Frequency- and distance-dependent measurements under visible light communication conditions demonstrate that the optimized device maintains strong signal detection up to 1 MHz and at distances exceeding 15 cm. Notably, the external quantum efficiency spectra reveal an additional contribution in the 450–575 nm range, which is absent in the reference device. This enhancement is consistent with a radiative absorption–reemission energy-transfer mechanism, supported by quantitative spectral overlap analysis showing that 99.5% of the PNC photoluminescence falls within the 450–575 nm EQE enhancement window and that the maximum differential EQE gain occurs at 519 nm—only 2 nm from the PNC emission peak. Our results suggest that controlled PNC incorporation enables efficient optical energy coupling, leading to high-sensitivity, fast-response OPDs suitable for optical communication applications. Full article

We develop Cs_xFA_1−xPbI₃ perovskite photodetectors with varying Cs content in the x = 0.05–0.25 range to identify the most stable cubic-lattice perovskite composition for visible-light photodetection. The perovskite layers were deposited by the spin-coating technique on a nickel oxide p-type contact and then were covered with C₆₀/Ag electron contact to obtain a vertical pin diode structure. X-ray diffraction (XRD) and scanning electron microscopy (SEM) measurements show that x = 0.1–0.2 provides the most stable lattice and pinhole-free perovskite layers. The photocurrents are linear in an extremely wide 1 nW–10 mW excitation power range, providing photoresponsivity of 0.28 A/W at 532 nm (green light), similar to that of Si photodiodes. The testing of the photodetectors using picosecond pulses provided their rise times and fall times. The x = 0.2 composition provided the shortest rise time values of 27.5 ns, leading to a detector modulation bandwidth of 12.7 MHz. This indicates that this perovskite composition is suitable for replacing silicon photodetectors in cost-efficient light detection systems for imaging and light communication applications such as Li-Fi. Full article

We examine whether speculative bubbles in shadow banking institutions contribute to the buildup and materialization of systemic risk. Using the Phillips–Shi–Yu (BSADF) bubble detection methodology and market-based systemic risk measures (ΔCoVaR and Marginal Expected Shortfall), we analyze daily data for 17 publicly listed U.S. shadow banking firms over the period 2010–2026. We document a pronounced pro-cyclical measurement puzzle. During bubble periods, firms exhibit higher market exposure and greater tail risk—Beta increases by 4.9% and Expected Shortfall by 7.9%—yet widely used systemic risk measures decline, with ΔCoVaR falling by 6.6%. This pattern suggests that conventional systemic risk metrics may underestimate vulnerabilities during speculative expansions. However, when bubbles burst, systemic risk materializes rapidly. During burst windows, ΔCoVaR increases by 7.9% and MES by 8.6%, indicating that vulnerabilities accumulated during bubble phases translate into significant systemic spillovers once speculative dynamics collapse. Our findings highlight a pro-cyclical bias in commonly used systemic risk indicators: these measures capture realized financial stress but fail to detect the buildup of fragility during expansion phases. Monitoring bubble dynamics in shadow banking may therefore provide valuable complementary signals for macroprudential surveillance. Full article

Onchocerca flexuosa is a vector-borne filarial nematode infecting red deer (Cervus elaphus) throughout Europe. Despite numerous reports from Central, Northern, and Southern Europe, its occurrence in South-Eastern Europe has remained largely undocumented. This study provides the first molecularly confirmed report and the first systematic epidemiological assessment of O. flexuosa in red deer in Croatia. During the 2024–2025 hunting season, 110 legally harvested red deer from central Croatia were examined for subcutaneous nodules. Nodules were evaluated morphologically, and adult nematodes were identified and confirmed by sequencing of a fragment of the mitochondrial cytochrome c oxidase subunit I (COI) gene. Subcutaneous nodules were detected in 53.6% (59/110) of examined animals. O. flexuosa was confirmed in 52 deer, corresponding to an overall prevalence of 47.3%. Co-infection with Hypoderma diana occurred in 21.2% of infected animals. Sequence similarity ranged from 96.37% to 99.85% compared to published European O. flexuosa isolates. Phylogenetic analysis placed Croatian sequences within the established European lineage, without evidence of regional genetic divergence. The observed prevalence falls within the intermediate range reported across Europe and indicates stable local transmission. These findings close an important geographical knowledge gap and demonstrate that nodular onchocercosis is established in red deer populations in South-Eastern Europe. Full article

This paper presents the synthesis, physicochemical characterisation, and analytical applications of chemiluminescent (CL) labels based on acridinium salts (ALs) for biomedical diagnostics. These compounds emit light as a result of oxidative reactions and represent an established class of reagents widely employed in chemiluminescence immunochemical assays (CLIAs) today. A series of structurally differentiated acridinium labels (AL1–AL5) was synthesised applying mostly original synthetic routes and purified to chromatographic purity (>90%, RP-HPLC). The compounds, including a commercial product treated as a reference, were successfully conjugated to anti-human IgG, yielding stable immunochemical reagents suitable for immunoassays with CL detection. The chemiluminescence properties of the obtained labels and their protein conjugates were investigated in aqueous buffers and in the presence of surfactants. The emission profiles exhibited characteristic flash-type kinetics with emission maxima occurring within 0.15–0.25 s after reaction initiation. The presence of surfactants more or less significantly enhanced the emission intensity, with signal increases of up to approx. 2-fold compared to surfactant-free systems. Analytical calibration demonstrated a linear response of signal derived from native labels over at least one order of magnitude of concentration, with detection limits falling in the range of 10⁻⁹–10⁻¹⁰ M, confirming the high sensitivity of the developed compounds. The experimental results were supported by theoretical studies using density functional theory (DFT), which confirmed the energetic feasibility of the CL reaction pathway and identified structural factors influencing activation barriers. Additional semiempirical calculations (PM7) indicated that the dielectric environment and proximity of ionic species can influence the reaction energetics, providing mechanistic support for the experimentally observed effects of surfactants. The results demonstrate that both molecular structure and microenvironment influence CL efficiency and kinetics of the investigated systems. The developed acridinium labels exhibit analytical performance better or comparable to commercial reagents and are fully compatible with standard immunodiagnostic conjugation protocols, confirming their suitability for use in modern chemiluminescent immunoassays. Full article

Falls pose severe risks to vulnerable populations, particularly the elderly and individuals with adverse neurological conditions, necessitating reliable and non-obstructive detection systems. While previous multi-modal approaches utilizing video and audio have demonstrated strong performance, they face significant limitations regarding sensitivity to environmental noise. This paper presents a robust, video-only fall detection framework that eliminates reliance on acoustic data to enhance universality. We conduct a comprehensive comparative analysis of five optical flow (OF) algorithms—Horn–Schunck, Lucas–Kanade (LK), LK-Derivative of Gaussian, Farneback, and the spectral method SOFIA—to determine the range of applicability of each technique for capturing fall dynamics. Beyond detection accuracy, we investigate the computational efficiency of each configuration. This optimized, privacy-centric pipeline offers a scalable solution for continuous monitoring in home and clinical settings, addressing the critical need for immediate intervention following high-impact falls. Full article