Search Results (708)

Inspired by the growing demand for small and effective optoelectronic devices, this paper presents a simulation-based analysis of InGaN/GaN quantum dot light-emitting diode, focusing on the effects of systematic variation in both anode and cathode contact regions, as well as overall device size. Two-dimensional simulations using APSYS software were used to examine the impact of scaling the device dimensions as well as the individual contact dimensions on significant performance parameters like internal quantum efficiency (IQE), optical output power, and current-voltage (IV) response. We simulated five LED device sizes that is 50 × 50 µm², 100 × 100 µm², 200 × 200 µm², 300 × 300 µm², and 400 × 400 µm². As device size grows, so does the total current at each voltage. The highest current measurement is achieved by the device with dimensions 400 × 400 µm² while the lowest is observed on the device with dimensions 50 × 50 µm². In addition to changing the device dimensions, we ran extensive simulations on the sizes of p-type and n-type contacts. Notable changes were seen in the efficiency, optical power, and emission profile of the p-contact. The behavior of p-side contacts from 0 to 50 µm was the same, while contacts between 60 and 100 µm showed significant differences. The significant performance parameters were unaffected by changes to n-contact dimensions. The results of this study illustrate how the configuration of contacts and dimensions greatly influences the electrical and optical performance of quantum dot light-emitting diode. The results are believed to be helpful to researchers working on the design of next-generation compact and efficient solid-state lighting devices. Full article

Background: Sepsis remains a leading cause of mortality in intensive care units (ICUs) worldwide. Machine learning models for clinical prediction must be accurate, fair, transparent, and reliable to ensure that physicians feel confident in their decision-making processes. Methods: We used the MIMIC-IV (version 3.1) database to evaluate several machine learning architectures, including Logistic Regression, XGBoost, LightGBM, LSTM (Long Short-Term Memory) networks and Transformer models. We predicted three main clinical targets—hospital mortality, length of stay, and septic shock onset—using artificial intelligence algorithms, with respect for responsible AI principles. Model interpretability was assessed using Shapley Additive Explanations (SHAP). Results: The XGBoost model demonstrated superior performance in prediction tasks, particularly for hospital mortality (AUROC 0.874), outperforming traditional LSTM networks, Transformers, and linear baselines. The importance analysis of the variables confirmed the clinical relevance of the model. Conclusions: While XGBoost and ensemble algorithms demonstrate superior predictive power for sepsis prognosis, their clinical adoption necessitates robust explainability mechanisms to gain trust among doctors. Full article

Mini-LED local dimming systems commonly suffer from luminance discontinuity, halo artifacts, and temporal instability in dynamic scenes. Traditional heuristic-based methods and standard convolutional neural networks often fail to capture long-range spatial dependencies and struggle to balance spatial smoothness, content fidelity, and real-time performance under hardware constraints. To address these challenges, this paper proposes SwinLightNet, an efficient adaptive backlight optimization network tailored for Mini-LED displays. Built upon a Swin Transformer framework tailored for Mini-LED backlight optimization, SwinLightNet integrates five hardware-aware design strategies: (i) a lightweight Swin variant (window size = 8, MLP ratio = 2.0) for efficient global context modeling; (ii) CNN encoder–decoder integration for multi-scale feature extraction; (iii) a partition-level alignment module ensuring spatial consistency; (iv) a backlight constraint module enforcing local luminance consistency and contrast preservation; (v) a change-aware temporal decision framework stabilizing dynamic sequences. These components synergistically resolve core limitations: global modeling suppresses halo artifacts while preserving content fidelity; alignment and constraint modules eliminate luminance discontinuity without compromising contrast; and the temporal framework guarantees flicker-free output under motion. Evaluated on DIV2K (static images) and a custom 2K-resolution video dataset (dynamic scenes), SwinLightNet demonstrates robust reconstruction quality while maintaining only 1.18 million parameters and 0.088 GFLOPs (Computational Cost). The results confirm SwinLightNet’s effectiveness in holistically addressing spatial, temporal, and hardware constraints, demonstrating strong potential for practical deployment in resource-constrained Mini-LED backlight control systems. Full article

In this study, the occurrence and leachability of rare earth elements and yttrium (REY) in medium-rank coal—meta-bituminous B coal from the southwestern part of the Upper Silesian Coal Basin in Poland—were investigated. The coal samples contained variable amounts of siderite, dolomite, calcite, kaolinite, illite, quartz, apatite, and pyrite in their mineral composition. A five-step sequential chemical leaching procedure was used, including deionized water, 3% HCl, 5% HNO₃, 10% HNO₃ with microwave assistance, and concentrated HCl–HF also with microwave assistance. The highest concentrations of ∑REY were observed in seam 404/1. Light REY (LREY) dominated the REY composition (>75%), while heavy REY (HREY) accounted for less than 10%. The chondrite-normalised REY patterns and total REY content indicate a clastic origin of REY-bearing minerals. The most efficient leaching occurred in stages IV and V. The solutions from stages I–III preferentially mobilised critical REY, while those from stages IV–V reflected the REY distribution in the coal. Based on the C_outl index, both coal and leachates from the later stages are classified as prospective REY resources. However, absolute REY concentrations should be considered when interpreting C_outl values. The positive correlation between apatite and kaolinite contents and ∑REE concentrations suggests their role in REY enrichment. Full article

Background/Objectives: Head and neck squamous cell carcinoma (HNSCC) affects over 600,000 individuals worldwide each year, and its incidence continues to rise. There is a growing need for novel therapeutic strategies that achieve high antitumor efficacy while minimizing functional impairment. We developed a novel approach to enhance intracellular delivery of immunotoxins (ITs) by combining a photosensitizer under illumination. This method, termed intelligent Targeted Anti-body Phototherapy (iTAP), utilizes light as a spatiotemporal trigger to promote the cytoplasmic release of toxins. In the present study, we investigated the in vivo therapeutic efficacy of iTAP using an EGFR-targeted IT composed of cetuximab conjugated to saporin (IT-Cmab), administered in combination with the clinically used photodynamic therapy (PDT) photosensitizer NPe6, in a xenograft mouse model. Methods: Sa3 cells were implanted subcutaneously into the right hind limb of nude mice. Mice were randomized into four groups (n = 5): (i) iTAP (IT-Cmab plus NPe6), (ii) IT-Cmab alone, (iii) NPe6 alone, and (iv) saline control. Treatment was initiated once tumors exceeded 40 mm³. Mice received intraperitoneal IT-Cmab (0.5 mg/kg), followed 72 h later by intravenous NPe6 (5 mg/kg). Tumors were irradiated 3–4 h later using a custom LED device (670 nm, 262 mW/cm², 30 J/cm²). Tumor volume and body weight were monitored over time, and antitumor effects were analyzed using a linear mixed-effects model. Results: iTAP treatment produced the earliest and most pronounced inhibition of tumor growth among the four groups. Significant suppression was observed from day 9 and persisted throughout the study. IT-Cmab alone showed a moderate but sustained antitumor effect with a later onset, whereas NPe6-mediated PDT exhibited only a delayed and weaker response. On the final day, median tumor volumes showed substantial reductions relative to the Control group (601%), with decreases of 41% in PDT (357%), 55% in IT-Cmab (271%), and 70% in iTAP (178%). Overall, iTAP demonstrated the strongest and most durable therapeutic efficacy in vivo. Conclusions: These findings indicate that iTAP represents a promising therapeutic strategy for HNSCC. Full article

The Dakhla Formation in the Western Desert of Egypt comprises a thick Cretaceous–Paleocene, ranging from light gray to dark gray, that represents an underexplored geological resource relevant to sustainable energy and environmental conditions. The present study integrates mineralogical and geochemical data based on samples collected from outcrop at Mut-Manflout and subsurface core samples from Abu Tartur (62–150 m depth) to evaluate depositional environments, paleoclimate, chemical weathering, and organic carbon accumulation. Major and trace element geochemistry, clay mineralogy, total organic carbon (TOC), Rock-Eval pyrolysis, and calorific values are used to assess hydrocarbon potential while minimizing exploration uncertainty. Mineralogical analyses indicate that smectite and kaolinite dominate the Mut-Manflout shales; in contrast, significant relationships among primary oxides and trace elements indicate a source from detrital materials, and elevated Chemical Alteration Index (CIA) values are indicative of intense chemical weathering under humid paleoclimatic conditions. The geochemical results show that Abu Tartur shale core samples contain higher TOC values (0.73–2.08 wt%) and oil-prone kerogen (types I–II to II–III), while Mut-Manflout outcrop samples exhibit lower TOC contents (0.23–1.15 wt%) and gas-prone kerogen (types III–IV). Both successions are thermally immature, with a strong relationship between TOC and S₁ values indicating the presence of indigenous hydrocarbons. By comparing surface and subsurface shales, the present study highlights the importance of site-specific characterization in reducing environmental and economic risks associated with unconventional resource exploration. The results support sustainable resource planning by improving understanding of organic carbon storage, paleoclimate controls, and the responsible evaluation of black shale systems in arid regions such as the Western Desert of Egypt. Full article

This study examined how different photoperiods affect net energy partitioning and explored the mechanisms via blood biochemistry, gut microbiota, and fecal metabolites. Twelve healthy crossbred pigs (47.7 ± 7.5 kg) were randomly allocated to two groups and subjected to a self-controlled crossover design. Following an 8-day baseline under a normal photoperiod (12L:12D, 12 h light:12 h dark), pigs were assigned to two photoperiod treatment groups: prolonged photoperiod (18L:6D, 18 h light:6 h dark; P group) and shortened photoperiod (6L:18D, 6 h light:18 h dark; S group). Measurements during the baseline (12L:12D) and treatment phases are designated as N1/P (for the P group) and N2/S (for the S group), respectively. The treatment periods were interspersed with the baseline 12L:12D photoperiod and repeated six times. It was observed that, compared to N2, shortened photoperiod (S) had significantly higher net energy deposition, net energy for protein deposition, and net energy for fat deposition (p < 0.05). Compared with N2, plasma low-density lipoprotein in short photoperiod decreased (p < 0.05), and gastric inhibitory peptides increased (p < 0.05). Compared to the prolonged photoperiod, the levels of ghrelin and apolipoprotein A-IV were higher in the shortened photoperiod (p < 0.05). A shortened photoperiod decreased fecal acetic acid compared to N2 (p < 0.05) and decreased propionic acids compared to P (p < 0.05). The significance test of differences between microbial groups showed that there were different microorganisms among the different groups. The results indicated that shortening the photoperiod significantly altered the energy allocation in growing pigs. Full article

Homeodomain-Leucine Zipper (HD-Zip) constitutes a distinct class of plant-specific transcription factors (TFs) that serves an essential function in mediating plant responses to environmental cues, with the HD-Zip II subfamily recognized as a major regulator of light-intensity adaptation and other environmental responses. However, the involvement of HD-Zip genes in regulating the light response of Juglans mandshurica Maxim. is largely unexplored. In this study, a genome-wide identification, classification, and expression analysis of the HD-Zip gene family in J. mandshurica was conducted. Furthermore, transcriptomic profiling under varying light-intensity conditions was performed to investigate the transcriptional regulation and potential functional networks of differentially expressed HD-Zip genes. The results showed that a total of 57 HD-Zip family genes were identified in J. mandshurica (named as JmHD-Zip) and classified into four subfamilies (HD-Zip I, HD-Zip II, HD-Zip III and HD-Zip IV). Gene structure and phylogenetic analyses indicated that members within the same subfamily exhibited analogous structural characteristics and shared strong homology with closely related species such as Juglans sigillata Dode and Populus trichocarpa. Torr. & A.Gray ex Hook. Promoter cis-acting element analysis revealed that the promoter regions of JmHD-Zip genes were enriched with multiple regulatory motifs associated with light responsiveness, hormone signaling, and stress regulation. Protein–protein interaction network analysis identified JmHDZ57 and JmHDZ43 as the central genes of the differentially expressed HD-Zip genes. Through validation of gene functions, JmHDZ43 promotes plant growth by coordinating shade-responsive morphogenesis via integration of light and hormone signaling pathways. This study offers a theoretical foundation and candidate gene resources for breeding initiatives and molecular investigations of light adaptation in J. mandshurica and potentially other woody species. Full article

Ultraviolet radiation, particularly in the UVC sub-band 200–280 nm, is a non-thermal disinfection technology capable of inactivating a broad spectrum of microorganisms primarily through nucleic acid damage and protein oxidation. Its effectiveness depends on wavelength, irradiance, exposure time, environmental conditions, and microbial characteristics, such as species and repair capacity. In food processing environments, where equipment surfaces and packaging materials are critical control points for microbial contamination, UVC offers several advantages, including the absence of chemical residues, and compatibility with sustainable sanitization strategies. However, efficacy is strongly influenced by surface properties. Smooth, non-porous, reflective materials (stainless steel, glass), and photocatalytic metal coatings, enhance UVC performance, whereas rough, porous, or fibrous surfaces reduce penetration and create shadowing effects that limit microbial inactivation. This review synthesizes current evidence on UV-based decontamination in the food industry, highlighting both its potential and limitations. The findings emphasize that, although UVC radiation is effective in microbial control, its implementation must consider the complex interactions between surface properties, microorganisms and irradiation parameters, requiring optimization for each environment and application. Further research is therefore needed into: (i) wavelength-tuned systems, (ii) hybrid technologies (UV–plasma or UV-photocatalysis), (iii) material integrity and durability of materials under repeated exposure, and (iv) emerging alternative light sources. Full article

Candidozyma auris is an emerging multidrug-resistant yeast that readily contaminates healthcare environments, persisting on dry surfaces and enabling transmission and difficult-to-control outbreaks. A systematic review of environmental hygiene interventions targeting C. auris was conducted, focusing on efficacy against planktonic cells and surface-associated biofilms (including dry-surface biofilms, DSB where available). PubMed and Scopus were searched for English-language records published from 1 January 2017 to 30 September 2025, and study selection followed PRISMA 2020. Thirty-six studies from nine countries met the inclusion criteria. These were predominantly laboratory efficacy evaluations using carrier/suspension or quantitative surface methods reporting log₁₀ Colony Forming Unit (CFU) reductions; only seven studies assessed biofilm-associated C. auris. Across clades I–IV, chlorine-based disinfectants and oxidizing chemistries (hydrogen peroxide/peracetic acid formulations) most consistently achieved high-level reductions (often ≥ 5 log₁₀ CFU) under label-relevant conditions. In contrast, products containing only quaternary ammonium compounds (QACs) frequently underperformed and demonstrated greater variability. No-touch methods, particularly 254 nm ultraviolet-C light (UV-C), provided meaningful adjunctive reductions, but were highly dependent on dose delivery and geometry, and evidence for ozone-based approaches was mixed. Limited data on C. auris DSBs suggest planktonic testing may overestimate real-world conditions and underscore the importance of endpoints, such as transfer prevention and regrowth suppression. Full article

Background/Objectives: Combined chronotherapy (CCT), which combines repeated sleep deprivation and light therapy, is used in the clinical treatment of severe depression. Despite its potential to rapidly reduce depressive symptoms, CCT is infrequently used in clinical practice. We explored whether actigraphy-derived within-patient changes in physical activity, sleep parameters, and sleep–wake patterns prior to CCT can help identify those most likely to benefit from this treatment, supporting personalized mental health care. Methods: Actigraphy data from nine severely depressed patients were collected before, during, and after CCT. Data were assessed with a questionnaire on depressive symptoms (Inventory of Depressive Symptomatology—Self Report, IDS-SR) and actigraphy measures for sleep–wake patterns and physical activity: daily mean activity level, rhythm (intradaily variability (IV), interdaily stability (IS)), Midpoint of Sleep (MSF), time in bed, sleep efficiency (SE), and the fragmentation index (FI). Variables were compared before and after CCT by systematic visual inspection due to the small sample size. A prior set Minimal Clinically Important Difference (MCID) of a 30% change in IDS scores from before and the week after CCT was used to categorize patients as responders (n = 3) or nonresponders (n = 6) to CCT. Results: After CCT, for both responders and nonresponders, there was a notable decrease in IDS, IV and FI. Prior to CCT, responders, compared to nonresponders, were characterized with higher IDS, more time in bed and higher FI, while having lower SE. Conclusions: We concluded that actigraphy assessments during regular CCT are feasible and found preliminary evidence that patients with the most disrupted sleep–wake patterns prior to treatment may benefit most from CCT. Full article

The microscopic origin of the de Sitter entropy remains a central puzzle in quantum gravity that is related to the cosmological constant problem. Within the paradigm of $\mathcal{H}$olographic $\mathcal{N}$aturalness, we propose that this entropy is carried by a vast number of light, coherent degrees of freedom—called “hairons”—which emerge as the moduli of gravitational instantons on orbifolds. Starting from the Euclidean de Sitter instanton ($S^4$), we construct a new class of orbifold gravitational instantons, $S^4/{\mathbb{Z}}_N$, where N corresponds to the de Sitter entropy. We demonstrate that the dimension of the moduli space of these instantons scales linearly with N, and we identify these moduli with the hairon fields. A ${\mathbb{Z}}_N$ symmetry, derived from Wilson loops in the instanton background, ensures the distinguishability of these modes, leading to the correct entropy count. The hairons acquire a mass of the order of the Hubble scale and exhibit negligible mutual interactions, suggesting that the de Sitter vacuum is a coherent state, or Bose–Einstein condensate, of these fundamental excitations. Then, we present a novel framework which unifies neutrino mass generation with the cosmological constant through gravitational topology and holography. The small neutrino mass scale emerges naturally from first principles, without requiring new physics beyond the Standard Model and Gravity. The gravitational Chern–Simons structure and its anomaly with neutrinos force a topological Higgs mechanism, leading to neutrino condensation via $S^4/{\mathbb{Z}}_N$ gravitational instantons. The number of topological degrees of freedom $N\sim M_{\mathrm{P}}^2/\mathrm{\Lambda }\sim {10}^{120}$ provides both the holographic counting of the de Sitter entropy and a $1/N$information see-saw mechanism for neutrino masses. Our framework makes the following predictions: (i) a neutrino superfluid condensation forming Cooper pairs below meV energies, as a viable candidate for cold dark matter; (ii) a possible resolution of the strong CP problem through a QCD composite axion state; (iii) time-varying neutrino masses which track the evolution of dark energy; and (iv) several distinctive signatures in astroparticle physics, ultra-high-energy cosmic rays and high magnetic field experiments. Full article

Estimating grape yields in viticulture is hindered by persistent challenges, including strong occlusion between grapes, irregular cluster morphologies, and fluctuating illumination throughout the growing season. This study introduces YOLOv11-IMP, an improved multiscale anchor-free detection framework extending YOLOv11, tailored to vineyard environments. Its architecture comprises five specialized components: (i) a viticulture-oriented backbone employing cross-stage partial fusion with depthwise convolutions for enriched feature extraction, (ii) a bifurcated neck enhanced by large-kernel attention to expand the receptive field coverage, (iii) a scale-adaptive anchor-free detection head for robust multiscale localization, (iv) a cross-modal processing module integrating visual features with auxiliary textual descriptors to enable fine-grained cluster-level yield estimation, and (v) aross multiple scales. This work evaluated YOLOv11-IMP on five grape varieties collecten augmented spatial pyramid pooling module that aggregates contextual information acd under diverse environmental conditions. The framework achieved 94.3% precision and 93.5% recall for cluster detection, with a mean absolute error (MAE) of 0.46 kg per vine. The robustness tests found less than 3.4% variation in accuracy across lighting and weather conditions. These results demonstrate that YOLOv11-IMP can deliver high-fidelity, real-time yield data, supporting decision-making for precision viticulture and sustainable agricultural management. Full article

Background: Atrial fibrillation (AF) is common among intensive care unit (ICU) patients and is associated with increased mortality, prolonged length of stay (LOS), and greater resource utilization. Widely used AF risk scores were developed for stable outpatient populations and have limited applicability in critically ill patients. This study aimed to (1) characterize ICU patients with AF, (2) develop and temporally externally validate machine learning models to predict ICU mortality and ICU LOS, and (3) identify early clinical factors associated with these outcomes using interpretable methods. Methods: Adult ICU patients with AF from MIMIC-IV (n = 20,058) were used for model development with grouped cross-validation, and MIMIC-III (n = 11,475) served as a temporal external validation cohort. Predictors included demographics, admission characteristics, vital signs, laboratory values, vasoactive support, and AF-related medications available within the first 24 h of ICU admission. Eight classification algorithms were evaluated for ICU mortality, and six regression algorithms were evaluated for ICU LOS. Discrimination was primarily assessed using the area under the receiver operating characteristic curve (AUC) and average precision (AP), with additional threshold-dependent metrics reported to characterize operating-point behavior under low event prevalence. Probability-threshold optimization using out-of-fold predictions was applied to the primary mortality model. LOS performance was evaluated using mean absolute error (MAE), root mean squared error (RMSE), and the coefficient of determination (R²). Model interpretability was assessed using SHapley Additive exPlanations (SHAP). Results: The median age was 75 years, and ICU mortality was 8.9%. For mortality prediction, the XGBoost model demonstrated preserved discrimination on temporal external validation (MIMIC-III) (AUC = 0.743; AP = 0.226). At the default probability threshold (0.50), recall and F1 scores were low due to low event prevalence; applying a prespecified F1-optimized threshold derived from the development cohort improved sensitivity while maintaining overall discrimination. For ICU LOS, models explained little variance on temporal validation; LightGBM performed best, but the explained variance was low (MAE = 88.9 h; RMSE = 163.9 h; R² = 0.038), indicating that the first 24-h structured data provide an insufficient signal to accurately predict ICU LOS, likely due to downstream clinical and operational factors. SHAP analysis identified clinically plausible predictors of mortality and prolonged ICU stay, including reduced urine output, renal dysfunction, metabolic derangement, hypoxemia, early vasopressor use, advanced age, and admission pathways. Full article

Melatonin, an indolic neuromodulator with putative oncostatic and proposed anti-inflammatory properties, primarily demonstrated in preclinical models, is produced at extrapineal sites—most notably in the gut. Its canonical actions are mediated by high-affinity GPCRs (MT1/MT2) and by NQO2, a cytosolic enzyme with a melatonin-binding site (historically termed “MT3”). A growing body of work highlights a bidirectional interaction between the gut microbiota and host melatonin. We integrated two lines of work: (i) three clinical cohorts—cardiac arrhythmias (n = 111; 46–75 y), epilepsy (n = 77; 20–59 y), and stage III–IV solid cancers (25–79 y)—profiled with stool 16S rRNA sequencing, SCFA measurements, and circulating melatonin/urinary 6-sulfatoxymelatonin and (ii) an age-spanning cognitive cohort with melatonin phenotyping, microbiome analyses, and exploratory immune/metabolite readouts, including a novel observation of melatonin binding on bacterial membranes. Across all three disease cohorts, we observed moderate-to-severe dysbiosis, with reduced alpha-diversity and shifted beta-structure. The core dysbiosis implicated tryptophan-active taxa (Bacteroides/Clostridiales proteolysis and indolic conversions) and depletion of SCFA-forward commensals (e.g., Faecalibacterium, Blautia, Akkermansia, and several Lactobacillus/Bifidobacterium spp.). Synthesised literature indicates that typical human gut commensals rarely secrete measurable melatonin in vitro; rather, their metabolites (SCFAs, lactate, and tryptophan derivatives) regulate host enterochromaffin serotonin/melatonin production. In arrhythmia models, dysbiosis, bile-acid remodelling, and autonomic/inflammatory tone align with melatonin-sensitive antiarrhythmic effects. Epilepsy exhibits circadian seizure patterns and tryptophan–metabolite signatures, with modest and heterogeneous responses to add-on melatonin. Cancer cohorts show broader dysbiosis consistent with melatonin’s oncostatic actions. In the cognitive cohort, the absence of dysbiosis tracked with preserved learning across ages, and exploratory immunohistochemistry suggested melatonin-binding sites on bacterial membranes in ~15–17% of samples. A unifying microbiota–tryptophan–melatonin axis plausibly integrates circadian, electrophysiologic, and immune–oncologic phenotypes. Practical levers include fiber-rich diets (to drive SCFAs), light hygiene, and time-aware therapy, with indication-specific use of melatonin. Our conclusions regarding microbiota–melatonin crosstalk rely primarily on local paracrine effects within the gut mucosa (where melatonin concentrations are 10–400× plasma levels), whereas systemic chronotherapy conclusions depend on circulating melatonin amplitude and phase. This original research article presents primary data from four prospectively enrolled clinical cohorts (total n = 577). Full article