Abstract: The increasing penetration of distributed renewable energy resources and electric vehicles has transformed microgrids into complex multi-prosumer systems that require coordinated control. Traditional centralized and local independent control strategies fail to exploit distributed flexibility and often lead to sub-optimal renewable utilization and inefficient energy management. This paper proposes a new method for coordinating these multi-prosumer microgrids using a hybrid coordination framework that utilizes Federated Learning for forecasting, game theory for energy trading, and blockchain for transaction recording through a decentralized network of peer to peer transactions between prosumers. Additionally, using the principles of model predictive control the battery algorithm was trained to make optimal decisions about present and probable future conditions of each microgrid node. By conducting simulations on heterogeneous networks of multi-prosumer microgrids, the system demonstrated a significant increase in renewable energy utilization by up to 91.2% and provided for greater coordination across three (3) microgrids through energy trading, fairness, and energy efficiency while also maintaining adequate levels of voltage regulation and power quality. In comparison, the baseline controller only achieved a lower operational cost. The results revealed essential trade-offs between local optimality and system coordination leading to the design of next generation decentralized microgrids.

Abstract: Climate change and variability pose serious threats to natural and human systems. The Mediterranean region and North Africa (MNA) are among the world’s climate change hotspots. An in-depth understanding of decadal climate variability over this region is critical for climate prediction to support planning and management, as well as adaptation in important sectors such as water resources. Therefore, the observation-based ERA5 precipitation and the outputs of the CORDEX-CORE regional models are used to characterise the decadal precipitation variability over these regions. The influence of a set of large-scale climatic indices (Atlantic Meridional Mode: AMM, Atlantic Multidecadal Oscillation: AMO, Arctic Oscillation: AO, Interdecadal Pacific Oscillation: IPO, North Atlantic Oscillation: NAO, Pacific Decadal Oscillation: PDO, Scandinavia: SCAND, and Western Mediterranean Oscillation: WeMO) on the decadal precipitation is also examined. The results reveal certain discrepancies between ERA5 and the CORDEX-CORE models’ values. Overestimations and underestimations are found between the models and observations, depending on the region and season. However, the capability of multi-model mean (MME) is better in capturing observation patterns over MNA, SMED, and NMED at all time scales; while REMO-Nor and MME perform better than the remaining models over two regions (SAH and WNA) at the annual time scale. As revealed by ERA5, MME confirmed that AMO, NAO, SCAND, and WeMO have more influence on precipitation over the entire region than others. These findings are useful for climate modelling enhancement and predictions in the region that still needs development of multi-annual to decadal time scales, especially in North Africa.

Abstract: Background: Genitourinary (GU) cancers — encompassing prostate, urothelial, and renal cell carcinomas — collectively represent a leading source of oncologic morbidity and mortality worldwide. Tumor heterogeneity and the dynamic evolution of resistance mechanisms limit the clinical utility of static tissue biopsies, creating an urgent need for real-time, non-invasive biomarkers. Circulating tumor DNA (ctDNA), isolated from peripheral blood or urine, captures the somatic mutational landscape of the tumor in a temporally resolved manner and has emerged as a compelling candidate predictive biomarker for treatment selection and resistance monitoring across GU malignancies. Methods: An integrative review was conducted following the Whittemore and Knafl (2005) framework. A systematic literature search was performed across PubMed/MEDLINE, Cochrane Central Register of Controlled Trials, Embase, and Web of Science, covering the period January 2020 to April 2026. Search strategies combined MeSH and free-text terms pertaining to ctDNA, liquid biopsy, and the three principal GU cancer types. After duplicate removal and staged screening, 23 studies met inclusion criteria and formed the basis of the qualitative synthesis. Results: The integrated evidence demonstrates that ctDNA functions as a dynamic predictive biomarker across three GU cancer domains. In castration-resistant prostate cancer (CRPC), ctDNA tumor fraction detected at cycle 3, day 1 of enzalutamide therapy independently predicts radiographic progression-free survival and overall survival (mOS 16.0 vs. 22.1 months for ctDNA-positive vs. ctDNA-negative patients). In muscle-invasive bladder cancer (MIBC), post-cystectomy ctDNA identifies metastatic relapse with 94% sensitivity and 98% specificity and stratifies benefit from adjuvant atezolizumab in IMvigor010. In renal cell carcinoma (RCC), emerging data support ctDNA for VHL and PBRM1 mutation tracking and treatment response assessment, though prospective validation remains limited. ctDNA-guided detection of androgen receptor splice variant 7 (AR-V7) and FGFR3 alterations enables biologically informed treatment sequencing in CRPC and urothelial carcinoma, respectively. Conclusion: ctDNA constitutes a molecularly rigorous, clinically actionable biomarker platform with demonstrated predictive and prognostic value across the GU cancer spectrum. Integration into prospective clinical trials and regulatory frameworks represents the critical next step toward embedding ctDNA-guided decision-making into standard oncologic practice.

Abstract: Abstract Background: Parenting stress is typically elevated in families of children with intellectual disability, yet less is known about how everyday family routines may buffer this stress in early childhood across different developmental groups. This study examined parenting stress and family routines in families of children with and without intellectual disability. Methods: In this cross-sectional study, 125 parents of children aged 0–9 years (n = 75 typi-cally developing; n = 50 with intellectual disability) completed the Family Time and Rou-tines Index and the Parental Stress Scale, along with a sociodemographic questionnaire. Group differences in parenting stress and routine-related indices were examined using in-dependent samples t-tests, and associations between parenting stress and the perceived importance of weekday/leisure and disciplinary routines were analyzed with Pearson cor-relation coefficients. Results: Parents of children with intellectual disability reported significantly higher par-enting stress than parents of typically developing children and less prevalent family disci-plinary routines. Across the total sample, lower levels of parenting stress were moderately associated with greater perceived importance of weekday and leisure routines and paren-tal disciplinary routines. Conclusions: Family routines, particularly weekday, leisure, and disciplinary routines, represent a promising target for personalized, family-centered support in early childhood. Tailoring interventions to families’ routine profiles and stress levels may help strengthen family resilience and everyday functioning in families raising children with and without intellectual disability. Keywords: parenting stress; family routines; intellectual disability; early childhood; fami-ly-centered interventions; parental self-efficacy

Abstract: Low‑level jets (LLJs) play an important role in the transport of heat, water vapor, and pollutants. Based on one year of tropospheric wind profiler radar (RWP) observations, this study systematically analyzes the wind field structure in the middle and lower troposphere over the Chengdu region, as well as the vertical distribution and evolution characteristics of LLJs. The results show that the effective detection height of the wind profiler radar reaches 7.4 km throughout the year, demonstrating good consistency with radiosonde data. Horizontal wind speed accelerates significantly above 3 km, with the highest vertical gradient of wind speed occurring in winter. The prevailing wind direction in the lower layer is mainly influenced by mountain‑valley breezes; with increasing altitude, the westerly belt gradually becomes the dominant wind system. Within the atmospheric boundary layer (below 1 km), the wind field exhibits a distinct diurnal variation: easterly winds dominate in the afternoon, shifting to northerly winds at night. The peak surface wind speed occurs in the afternoon, while the peak upper‑level wind speed occurs at night. The occurrence frequency of LLJs is highest in July, followed by April. The prevailing wind directions of LLJs are north‑northeasterly and northeasterly, and the jet core heights are mainly distributed between 0.7 and 1.9 km. Both the occurrence frequency and intensity of LLJs are higher at night than during the day. These findings deepen our understanding of the boundary layer structure over complex basin terrain.

Abstract: The fast growth of wireless communication systems and the growing need for very high data rates have been the driving force behind the creation of sixth-generation (6G) technologies that operate in the terahertz (THz) frequency region. This research represents the design and analysis of a small compact microstrip patch antenna that works in the terahertz (THz) frequency range for 6G cellular connectivity. The Rogers RT5880 substrate and annealed copper are used in the design of the suggested antenna, which aims for a 593 GHz resonance frequency. A progressive design technique that incorporates slotting and geometric optimization has been used to develop a castle shaped antenna which improve impedance matching and bandwidth to overcome the inherent constraints of traditional microstrip antennas. Excellent impedance matching is shown by the final design's near-ideal voltage standing wave ratio (VSWR) and return loss (S11) of –48.76 dB. It achieves a broad impedance bandwidth of 154.88 GHz, which far outperforms many current systems. The antenna exhibits consistent radiation characteristics in the broadside direction, a gain of 8.005 dBi, a directivity of 8.727 dBi, and an efficiency of around 91.73%. The proposed design performs very well in terms of bandwidth and efficiency, while also preserving compact dimensions and structural simplicity, as shown by a comparative comparison with most current literature. These results validate the suitability of the proposed antenna for high-speed, short-range THz communication systems in future 6G networks.

Abstract: The rapid expansion of digital technology in English language teaching has created new opportunities for learning while raising concerns about the marginalization of local cultural values. This study investigated the integration of cultural and local wisdom in technology based English language teaching in Indonesia, focusing on the extent of implementation, the challenges encountered by teachers, and possible strategies for effective integration. A qualitative approach was employed, involving semi structured interviews, classroom observations, and document analysis with English teachers across secondary and tertiary levels. The findings indicated that although teachers acknowledged the importance of incorporating local wisdom, its integration remained partial and largely dependent on individual initiative. Cultural elements were often used as supplementary content rather than being systematically embedded in digital instructional design. Several challenges were identified, including the dominance of globally oriented digital materials, limited access to culturally relevant resources, varying levels of digital competence, and institutional constraints. Despite these limitations, some teachers demonstrated innovative practices by integrating local narratives and project based activities into digital platforms, which enhanced student engagement and contextual understanding. The study concluded that meaningful integration of local wisdom in technology based ELT required more structured pedagogical models, institutional support, and professional development. These findings contributed to the growing discourse on culturally responsive digital pedagogy and highlighted the importance of aligning technological innovation with local cultural contexts in language education.

Abstract: This study presents a comprehensive PRISMA 2020-compliant systematic review of satellite remote sensing approaches used to monitor vegetation responses to climate change over the period 2000–2025. A total of 757 peer-reviewed studies were analysed to evaluate trends in sensor usage, spectral indices, machine learning (ML) and deep learning (DL) applications, geographic distribution, and methodological practices. Results indicate a rapid growth in research output, particularly after 2019, driven by the availability of high-resolution satellite data (e.g., Sentinel-2), cloud computing platforms, and advances in artificial intelligence. MODIS, Landsat, and Sentinel-2 emerged as dominant sensors, while NDVI remains the most widely used vegetation index despite known limitations. Random Forest and regression models continue to dominate analytical approaches, although DL methods such as CNNs and LSTMs are increasingly adopted. The review identifies significant geographic inequities, with over 80% of studies originating from Global North institutions, and highlights underrepresentation of critical ecosystems such as drylands, peatlands, and shrublands. Furthermore, inconsistent reporting of model performance metrics and limited adoption of open science practices constrain reproducibility and cross-study comparison. The study concludes by outlining key research gaps and providing strategic recommendations to advance the integration of multi-sensor data, improve methodological standardisation, and promote equitable and reproducible research in vegetation–climate remote sensing.

Abstract: Polymerase chain reaction (PCR) is a widely used molecular biology technique; however, it remains highly susceptible to non-specific primer binding, particularly in genomic regions with extensive sequence similarity. Such off-target amplification can generate false amplicons that are difficult to detect using conventional quality control methods and may lead to erroneous downstream interpretation. Here, we present FalseAmpHunter, a pipeline designed to detect, assemble, and characterize false amplicons from paired-end next-generation sequencing (NGS) data generated from PCR amplification. FalseAmpHunter reconstructs candidate amplicons, maps them genome-wide, evaluates primer-binding orientation, and distinguishes true target amplification from paralog-driven off-target products and sequencing artifacts. We validated FalseAmpHunter using a synthetic dataset derived from in silico PCR of paralogous olfactory receptor (OR) genes. The pipeline successfully identified both the intended target amplicon and false amplicons originating from paralogous loci, while excluding a random decoy control. FalseAmpHunter provides a systematic and transparent solution for investigating false PCR amplification events and is applicable to assay development, primer validation, and troubleshooting of targeted sequencing experiments. By transforming raw sequencing data into interpretable genomic evidence, it enhances confidence in PCR-based analyses, particularly in paralog-rich genomic contexts. The pipeline is accessible online at: https://github.com/xoaib4/FalseAmpHunter.

Abstract: Mediastinal staging remains a critical step in the management of non-small-cell lung cancer (NSCLC), as it directly impacts treatment planning, surgical decision-making, and overall prognosis. For many years, mediastinoscopy was considered the standard approach; however, in routine practice, less invasive techniques have largely taken its place. Endobronchial Ultrasound (EBUS) and Endoscopic Ultrasound (EUS) have become widely adopted because they allow real-time sampling of lymph nodes with good accuracy and a low complication rate. In clinical seĴings, these techniques are often used together rather than separately, as each provides access to different nodal stations. This combined approach improves diagnostic yield and reduces the number of patients who require surgical staging. At the same time, recent updates in the IASLC TNM classification, including the proposed 9th edition, have introduced more detailed nodal categories, making accurate tissue confirmation even more important in daily practice. In this review, we summarize the current use of combined EBUS and EUS in mediastinal staging, focusing on their practical advantages, limitations, and roles across different clinical scenarios. We also discuss their relevance in the context of molecular testing and evolving treatment strategies. Despite their strengths, there are situations in which negative results should be interpreted with caution and confirmed surgically. Overall, these techniques have reshaped the approach to mediastinal staging and are now central to modern lung cancer care.

Abstract: Background: Recent work has revealed that protein-coding sequences encode regulatory information influencing mRNA stability and translation through a nascent peptide code. However, the evolutionary origin of this regulatory layer remains unclear. This study aims to determine when peptide-mediated translational control emerged during the evolution of the proteome and genetic code. Methods: Dipeptide-specific effects on mRNA stability and translation were integrated with a phylogenetic timeline of dipeptide emergence derived from dipeptide sequences across proteomes. Each of the 400 canonical dipeptides was assigned an evolutionary age, and experimentally derived regulatory effects were mapped onto this timeline, with associations assessed using rank-based correlation and regression analyses. Results: A weak but statistically significant negative association was observed between dipeptide age and mRNA stability, indicating that more recently evolved dipeptides tend to destabilize transcripts. This trend was stronger at the amino acid level, where later-emerging residues showed greater contributions to reduced mRNA levels. Destabilizing effects were associated with physicochemical properties such as positive charge, side-chain bulkiness, and β-strand propensity. Mapping these effects onto codon space revealed a non-random distribution aligned with the evolutionary and structural organization of the genetic code. Destabilizing effects were also enriched within specific codon exchange groups, indicating that regulatory signals are structured within the degeneracy and mutational neighborhoods of the code. Conclusions: These findings indicate that the nascent peptide code is a late evolutionary innovation linked to amino acid expansion and proteomic complexity, with regulation embedded within both peptide sequences and the degeneracy structure of the standard genetic code.

Abstract: Protein conformational inheritance is documented across bacteria, fungi, and neurons, and while several authors have argued for its conceptual inclusion in molecular inheritance frameworks, a concise, widely adopted formal vocabulary that unifies these literatures remains lacking. Naming by pathological outcome rather than mechanism has partitioned prion disease research, adaptive conformational biology, and protein engineering into separate silos despite a shared mechanistic basis. This review formalises the shared mechanism with three terms. Alt-F protein (alternatively folded protein) names the mechanistic class irrespective of outcome. Conformoreplication names the protein-to-protein templated propagation of fold geometry — a third conceptual extension of the Central Dogma. The conformotype is the third molecular inheritance tier, transmitted through cell division independently of DNA sequence or epigenetic marks, initiated by post-translational modifications acting as environmental transducers, and regulated by the chaperone network. The framework identifies blind spots in three research fields that the current sequence-centric paradigm structurally excludes: AMR surveillance that cannot detect conformationally-encoded resistance in genotypically susceptible isolates; industrial biotechnology that screens enzyme variants by sequence but not conformational state; and neurodegeneration therapeutics that targets downstream aggregates rather than the upstream chaperone regulatory failure. To move beyond conceptual identification of these blind spots, the review operationalises each through a concrete analytical pipeline — integrating conformational proteomics, MSA-subsampled AlphaFold screening, and chaperone modulation assays — demonstrating that the conformotype framework is not merely taxonomic but immediately actionable across all three fields.

Abstract: Background/Objectives: Pediatric tracheotomy has evolved from an emergency procedure for acute infections to a planned intervention for chronic conditions requiring prolonged airway support. This study aims to describe the clinical characteristics, indications, and outcomes of pediatric tracheotomy over a 21-year period at a tertiary care center. Methods: A retrospective observational case series was conducted including 246 pediatric patients (0–18 years) who underwent tracheotomy between 2004 and 2024. Data were collected from medical records and included demographics, indications, procedural details, complications, decannulation, and mortality. Patients were categorized into airway obstruction (AO) and respiratory support (RS) groups. Statistical analyses were performed using the Mann–Whitney U test, Chi-square and Fisher’s exact test. Results: A significant increase in tracheotomy procedures was observed over time. Respiratory support was the predominant indication (75.2%), mainly due to neurological disorders, while airway obstruction accounted for 24.8%. Patients in the AO group were significantly younger and more likely to undergo urgent procedures (p < 0.001). Complication rates were comparable between groups (AO 16.4% vs. RS 21.1%; p = 0.295). Decannulation was significantly more successful in the AO group (16.4% vs. 5.4%; p = 0.012). Mortality did not differ significantly between groups and was associated with underlying comorbidities. Conclusions: Pediatric tracheotomy is increasingly performed for chronic respiratory support. While procedural safety is high, outcomes vary by indication, with better decannulation rates in airway obstruction cases. Multidisciplinary, individualized management is essential for optimizing patient outcomes.

Abstract: In recent years, the rapid expansion of low-temperature facilities—such as cold storage and indoor ice and snow venues—has underscored their pronounced vulnerability to fire, as evidenced by multiple severe incidents. Due to their distinct environmental conditions, existing theoretical frameworks, technical approaches, and standards exhibit limited applicability. Consequently, the fire risk characteristics of such facilities remain insufficiently defined, and systematic methods for hazard identification and assessment are lacking. This study conducts a detailed analysis of fire incident data from representative low-temperature facilities to identify the fire risks characteristics across all lifecycle stages, including construction, renovation and expansion, operation, maintenance, and demolition. An integrated framework combining the WBS/RBS matrix and CN methods is then proposed to establish a structured methodology for full lifecycle fire hazard identification and classification. The results address critical gaps, including the absence of clearly defined lifecycle fire risk profiles and a robust scientific basis for hazard identification, and provide a technical foundation for lifecycle fire risk management in low-temperature facilities.

Abstract: This study supports the use of human skin explants as a versatile and translational model for evaluating pharmacologic skin responses and topical bioactivity. The approach allows mechanistic insight beyond single biomarkers and may serve as a scalable pharmacologic platform for efficacy testing, particularly when expanded to include multiple donors and broader readouts.

Abstract: Purpose: With the growing interest in multimodal large language models (MLLMs) for medical image analysis, expanding the application scope of the unimodal TAIDE large-scale language model has emerged as a prominent and significant research direction. Methods: This study employed the SkinCAP multimodal dataset, which consists 4,000 images of skin lesions along with their associated textual descriptions. Two approaches for model training and evaluation are proposed: (1) A visual retrieval-augmented generation (RAG) method, which leverages transfer learning for image feature extraction and cosine similarity for image retrieval. Retrieved results are used to generate prompts that guide the TAIDE model to produce diagnostic descriptions in traditional Chinese. (2) A fine-tuning-based method that integrates the MiniGPT-V2 framework with the TAIDE model to develop a multimodal system capable of automatically generating diagnostic descriptions. Results: Model performance was evaluated using BLEU, ROUGE-L, METEOR, CIDEr, and SPICE metrics. The results demonstrate that the fine-tuning-based approach—integrating MiniGPT-V2 with the TAIDE model—achieves superior performance compared to the visual RAG-based method, which combines transfer learning-based retrieval with the TAIDE model for description generation. Conclusion: This study presents an empirical comparison of two methodologies for extending unimodal large language models into multimodal applications for the automatic generation of diagnostic descriptions of skin lesions. The findings provide valuable technical insights and serve as a reference for the development of future AI-based medical systems.

Abstract: Environmental noise exposure has become an increasingly prevalent public health con-cern, with effects extending beyond the auditory system. Accumulating evidence indicates that chronic noise exposure induces both structural and functional alterations in the cen-tral nervous system, ultimately affecting cognitive and emotional processes. This review summarizes the impact of noise on key brain regions, including the hippocampus, pre-frontal cortex, and auditory cortex. Structurally, noise exposure is associated with reduced neurogenesis, dendritic remodeling, synaptic loss, alterations in white matter and changes in glial activity. Functionally, it disrupts synaptic plasticity mechanisms—such as long-term potentiation and long-term depression—as well as neuronal connectivity, lead-ing to impairments in higher-order cognitive and behavioral functions. These effects are mediated by interconnected mechanisms, including activation of the hypothalamic–pituitary–adrenal axis, neuroinflammation, oxidative stress, and alterations in neu-rotrophic signaling.

Abstract: We propose an observationally motivated effective framework for the gravitationally relevant vacuum sector, in which only a spectrally bounded subset of quantum fluctuations contributes to the vacuum energy density. The construction is defined by two physically motivated scales: a short-wavelength ultraviolet bound associated with confinement-scale physics, and a long-wavelength infrared scale arising from thermodynamic and entropic structuring in the late-time universe. Within this bounded spectral domain, the vacuum energy density is governed by a characteristic geometric scale defined by the ultraviolet and infrared bounds, leading to a robust inverse fourth-power scaling that is largely insensitive to the detailed form of the spectral kernel.This effective description provides a structured interpretation of the observed smallness of vacuum energy in terms of spectral selection rather than ultraviolet cancellation. The model yields testable predictions at low redshift, including percent-level deviations in the equation of state and in the growth of structure, offering a falsifiable alternative to a purely phenomenological cosmological constant.

Abstract: The human spinal cord is increasingly recognized as an active and adaptable compo-nent of sensorimotor function, contributing to motor control, pain modulation, and recovery after neurological injury. Within this framework, the Hoffmann reflex (H-reflex) has evolved from a classical electrophysiological phenomenon into a useful probe of spinal circuit function. Rather than reflecting motoneuron excitability alone, H-reflex amplitude and modulation arise from the interaction of Ia afferent transmis-sion, presynaptic inhibition, homosynaptic depression, and interneuronal networks that regulate sensorimotor gain in a state-dependent manner. This review synthesizes classical and contemporary evidence to position the H-reflex as an indirect measure of spinal inhibitory function in humans. We integrate physiological mechanisms with findings from studies in chronic pain syndromes, spasticity, Parkinson's disease, and recovery after central nervous system injury, where alterations in spinal inhibitory processes have been described. We further discuss methodological and conceptual challenges that limit clinical translation, including state dependence, protocol hetero-geneity, and the lack of normative reference frameworks. Finally, we outline directions for integrating H-reflex paradigms with complementary approaches to improve the interpretation of spinal circuit function and its relation to clinical phenomena. Framed in this context, the H-reflex can be considered a valuable experimental and transla-tional tool, whose utility depends on careful methodological implementation and physiologically informed interpretation.

Abstract: Background: Variation in suspected adverse drug reactions (SARs) linked to different batches of COVID-19 vaccines has been reported in several countries, including the Czech Republic, Denmark, Sweden, and the USA. However, SAR data from spontaneous reporting systems are subject to under-reporting and other biases. To investigate the potential association between vaccine batches and adverse reactions using an unequivocal endpoint, we examined the temporal relationship between all-cause mortality (ACM) and COVID-19 vaccine type and batch up to three months after vaccination.Methods: We analysed nationwide data from the Czech Republic on vaccine type and batch, together with corresponding three-month ACM data. Cluster analysis was used to assess age- and sex-specific differences in ACM within and across vaccine batches and types. We also investigated the relationship between ACM and SAR rates for the same batches.Results: During a 21-month period (December 2020 to September 2022), vaccine batches clustered according to their three-month age- and sex-adjusted ACM rates for the four products administered (Comirnaty, Spikevax, Vaxzevria, and Jcovden). For Comirnaty, Spikevax, and Vaxzevria, a clear temporal pattern was observed, with earlier batches showing significantly higher ACM rates. A strong correlation was found between batches that clustered by ACM and those previously identified as clustering by SARs, across all vaccine products except Jcovden.Conclusions: Data from the Czech Republic show a clear association between administered COVID-19 vaccine batches and 3-month ACM rates for Comirnaty, Spikevax, and Vaxzevria, with earlier batches linked to notably higher ACM. A strong correlation between batch-associated ACM and SAR rates for Comirnaty and Spikevax supports the validity of these batch-related safety signals and warrants further investigation using individual-level patient data.