Abstract: Background: Elevated low-density lipoprotein cholesterol (LDL-C) is a major risk factor for atherosclerosis and cardiovascular disease (CVD). Statins are the cornerstone of LDL-C reduction and are highly effective in secondary prevention. However, their benefit in primary prevention among individuals at low-to-moderate cardiovascular risk remains controversial, and long-term adherence is often limited by adverse effects. Methods: This narrative review summarizes current evidence on the clinical effectiveness of statin therapy, with particular attention to the role of nutritional status in modulating statin efficacy, safety, and interpretation of clinical outcomes. Results: In primary prevention among low- to moderate-risk populations, statin therapy often fails to demonstrate a clear reduction in cardiovascular events. Furthermore, 20–30% of patients in secondary or high-risk prevention do not achieve clinically meaningful benefits despite adequate LDL-C lowering. More than half of statin-treated patients discontinue therapy within two years, most commonly because of adverse effects, without a corresponding increase in cardiovascular mortality. Emerging evidence suggests that malnutrition and sarcopenia may significantly influence statin pharmacokinetics and pharmacodynamics, thereby affecting both therapeutic response and susceptibility to adverse events. In addition, statin-induced lipid lowering may alter nutrition-related biomarkers, potentially leading to misclassification or overestimation of malnutrition. Conclusions: Although statins remain effective agents for lowering LDL-C, their prescription should be embedded within an individualized, patient-centered approach. Current guidelines provide a robust methodological framework for statin use; however, their application should be contextualized rather than automatic. Optimal effectiveness is achieved when pharmacological therapy is integrated with dietary patterns, nutritional status, and lifestyle factors. Incorporating nutritional assessment into statin management may improve tolerability, enhance clinical outcomes, and enable more accurate cardiovascular risk stratification beyond standardized cholesterol-lowering strategies.

Abstract: Sepsis is a complex infection-driven inflammatory syndrome that can lead to life-threatening multi-organ failure and septic shock, characterized by cardiovascular instability, tissue hypoperfusion, and impaired oxygen utilization. Myocardial dys-function is a frequent and multifaceted complication in both adults and children, with sepsis-induced cardiomyopathy (SCM) representing an acute, reversible form of non-ischemic cardiac failure involving left and sometimes right ventricular impairment. Diagnosis relies on excluding acute coronary syndromes and recognizing refractory shock, low mixed venous oxygen saturation, and elevated cardiac biomarkers, espe-cially in patients with known risk factors such as pre-existing heart disease or elevated lactate. The pathophysiology reflects an interplay of systemic inflammation, circulatory redistribution, and mitochondrial dysfunction, while clinical recognition remains challenging, particularly in pediatrics where hypotension is a late sign. Early fluid re-suscitation is vital to restore perfusion, yet excessive administration risks fluid overload, underscoring the need for precise hemodynamic assessment. Conventional echocar-diographic measures of heart function may give misleading results in SCM because they depend on preload and afterload, often underestimating the true degree of myocardial impairment. Advanced hemodynamic monitoring, ranging from invasive to minimally invasive and non-invasive methods, is currently being studied for managing sepsis. Minimally invasive techniques offer detailed, dynamic data that complement echocar-diography and help identify specific hemodynamic profiles to guide septic shock treatment. Contemporary management increasingly favors multimodal monitoring and individualized strategies over protocol-driven approaches to optimize timely, goal-directed therapy.

Abstract: We present a formal analytical framework for the Riemann zeta function by mapping the Dirichlet η(s) function to a trace-class interaction operator Φ(s) on the Hilbert space l²(N). By applying a normalization kernel K(s), we establish a bijective mapping between the operator trace and the Riemann zeta function throughout the critical strip. We derive the Phase-Torque J(δ,t) representing the imaginary component of the interaction trace, and demonstrate that it vanishes identically on the critical line Re(s) = 1/2 due to unitary phase symmetry. Conversely, for Re(s) ≠ 1/2, a hyperbolic bias arises from the broken symmetry of the interaction magnitudes, which, when coupled with the Diophantine independence of prime logarithms, prevents the trace from vanishing. This geometric exclusion principle rigorously confines all non-trivial zeros to the critical line, providing a proof of the Riemann Hypothesis.

Abstract: Recent advances in reinforcement learning for large language models have produced powerful agent frameworks that achieve strong performance on multi-turn tool use, interactive search, and complex reasoning. However, existing reinforcement learning frameworks for large language model agents face three critical limitations: difficulty in handling dynamic user interactions owing to reliance on pre-scripted queries, limited scalability across varying interaction horizons with fixed scaling schedules, and substantial reward engineering overhead requiring domain-specific manual tuning. We introduce Progressive Multi-Turn Reinforcement Learning for Dynamic User-Interactive Tool Agents, a novel framework that integrates progressive user-interactive training to overcome sparse reward signals, adaptive horizon management that monitors performance metrics and adjusts training complexity accordingly, and domain-adaptive tool orchestration that learns optimal tool selection patterns across domains. Extensive experiments on WebArena, TAU-Bench, Berkeley Function-Calling Leaderboard Version 3, BabyAI, and SciWorld demonstrate that our method achieves 28.4% success rate on WebArena and 76.3\% on TAU-Bench, substantially outperforming the baselines, such as ReAct (16.2%) and MUA-RL (24.6%), while maintaining 94.7% performance on embodied reasoning tasks and 78.9\% cross-domain performance retention. Our work establishes a unified framework for realistic user interaction training, performance-adaptive complexity scaling, and domain-flexible tool orchestration.

Abstract: Trees in urban environments provide essential ecosystem services, but root growth–pavement system conflicts often constrain tree longevity and degrade infrastructure performance. The study presents a conceptual model for green and grey infrastructure alignment to ensure tree longevity while maintaining pavement performance in the urban environment. Drawing on past research where roots were flattened when exposed to confining stresses greater than 0.35 MPa, we developed a series of finite element models in COMSOL Multiphysics to simulate root-induced stresses in concrete pavements under varying pavement thickness, base thickness, and root depth. Parametric analyses showed that an increase in root depth had the largest impact in reducing stress, followed by an increase in pavement thickness, then base thickness. Maximum single-root-induced stresses were approximately 0.55 MPa, below that of normal concrete flexural strength. From these results, design guidance is proposed for tree root accommodation and pavement in existing and new infrastructure, with emphasis on root growth enhancement, pavement durability, and cost-effectiveness measures.

Abstract: Background/Objectives: Urology residency training widely varies across countries and evidence comparing residents’ experiences at an international level are limited. This study reports the results of an international survey of urology residents from different countries worldwide, aiming to characterize training environments, educational expo-sure, and trainee expectations across diverse healthcare systems. Methods: A 39-item online survey was administered to urology residents during the SIU Regional Meeting (Florence, November 2024), assessing demographics, training exposure, educational resources, workload, satisfaction, and career perspectives. Results were compared be-tween trainees at different postgraduate year (PGY) to explore associations for key out-comes. Results: Overall, 208 urology residents from 21 countries completed the survey. Most residents were actively involved in research (76.4%), although confidence in in-dependent scientific production was moderate (significantly lower among junior trainees). Surgical exposure increased with PGY, with good experience in endoscopy but limited hands-on exposure and expected autonomy in laparoscopic, robotic, and major open surgery. Despite high overall satisfaction with urology, residents described heavy workloads, inconsistent access to structured teaching and international fellowships, and a long-term shift in career expectations toward private practice. Conclusions: Urology residents worldwide report high engagement in research, strong satisfaction with their specialty choice, and interest in international mobility. Nonetheless, persistent disparities in surgical exposure, research confidence, workload, and gender representation highlight the need for competency-based curricula, structured mentorship, and improved training organization to promote equitable and high-quality urology education globally.

Abstract: Background/Objectives: Toothpaste ingredients such as strontium chloride (SrCl₂) and potassium carbonate (K₂CO₃) are recognized for their desensitizing and remineralizing ef-fects but may be absorbed through the oral mucosa. Their potential cytotoxic and cardio-toxic properties, however, remain inadequately characterized. Here, we investigated the effects of SrCl₂ and K₂CO₃ on mouse-induced pluripotent stem cells (iPSCs) and iPSC-derived cardiomyocytes (iPSC-CMs). Methods: Cells were exposed to varying con-centrations of each compound for up to 72 h. Real-time cell analysis (xCELLigence RTCA Cardio system) was used to assess proliferation, and flow cytometry was used to evaluate cell viability. Functional properties of iPSC-CMs were examined using multi-electrode ar-ray (MEA) recordings and the xCELLigence based impedance measurements. Cardiac marker expression was examined via immunofluorescence and quantitative RT-PCR. Results: Both SrCl₂ and K₂CO₃ affected iPSCs proliferation and reduced viability in a dose- and time-dependent manner, accompanied by altered embryoid body (EB) morphology and increased cell death. In iPSC-CMs, both compounds downregulated keys cardiac genes and disrupted spontaneous beating activity, with effects intensifying at the higher concentrations. Conclusions: These results demonstrate that SrCl₂ and K₂CO₃ induced dose-dependent cytotoxic and arrhythmogenic effects on iPSCs and iPSC-CMs. At elevated concentrations, these compounds impair iPSC-CMs function and may pose safety con-cerns upon chronic exposure. Further mechanistic and long-term in vivo studies are war-ranted to assess their potential cardiotoxic risk in consumer oral care products.

Abstract: The global rise of multidrug-resistant (MDR) bacterial infections in pediatric populations poses an alarming challenge to effective clinical management and antimicrobial stewardship. Two-component systems (TCSs), comprising sensor kinases and response regulators, play a pivotal role in bacterial adaptation, virulence, and resistance mechanisms, making them promising targets for diagnostic and therapeutic innovation. This study employs a machine learning-driven bioinformatics pipeline to identify and prioritize potential TCS biomarkers across MDR pediatric pathogens for integration into next-generation diagnostic biosensors. Genomic datasets from clinically relevant MDR bacteria were curated and analyzed to extract TCS-associated gene and protein signatures. Using Pfam domain features, multiple supervised learning models were trained, with XGBoost, Random Forest, and a Stacking Ensemble achieving high overall accuracies (0.9883-0.9885). While the dominant Non-TCS class was predicted with near-perfect accuracy, minority subclasses exhibited variable detection due to severe class imbalance, particularly for rare groups such as CpxA-like and EnvZ-like proteins (n=2 each). Moderate F1-scores were obtained for generic response regulators and OmpR-like proteins. Feature importance analysis identified a small set of highly discriminative domains, including PF01339, PF00702, PF07679, PF03997, and PF04886, associated with conserved regulatory and signaling motifs. These results demonstrate that Pfam domain signatures offer biologically meaningful features for TCS classification, while highlighting the need for expanded datasets or embedding-based features to improve minority-class prediction. Overall, this work provides a scalable, AI-driven foundation for TCS biomarker discovery, aiming to develop diagnostic biosensors for MDR pediatric pathogens.

Abstract: Public trust in the judiciary is fundamental for upholding the rule of law and ensuring democratic stability. However, in Puntland, Somalia, issues such as fairness, accessibility, and the influence of politics or clans may deter citizens from utilizing formal courts. This study assessed the level of public trust in the judiciary in Qardho, Garowe, and Bossaso. A cross-sectional mixed-methods approach was employed, involving a survey of 400 residents using a KOBO-based structured questionnaire and 12 key informant interviews with judges, lawyers, elders, and religious leaders. Quantita-tive data were analyzed through descriptive statistics, correlations, chi-square tests, and regression in Stata, while qual-itative data underwent thematic analysis. Overall, confidence was moderate: 62% agreed that the judiciary is fair and impartial, 55.25% had confidence in judges' independence, 63.5% trusted the enforcement of decisions, and 62.5% viewed processes as transparent. Confidence was most strongly linked to perceived enforcement (ρ = 0.730), judicial in-dependence (ρ = 0.699), and fairness (ρ = 0.686), with age (p = 0.001) and education (p < 0.001) significantly associated with confidence, unlike gender (p = 0.497) and work experience (p = 0.384). Enhancing decision enforcement, transpar-ency, access to information, and protections for judicial independence is vital for boosting public trust.

Abstract: We present a maximal referee-grade formulation of the Quantum Information Copy Time (QICT) program. All claims are restricted to (i) standard Axioms (locality, stationarity/KMS, conservation), (ii) executable certification predicates, or (iii) Theorems with fully enumerated premises. The key observable is the copy time \( \tau_{\text{copy}} \), defined operationally via Helstrom distinguishability. A certified hydrodynamic-window predicate CHW (constructed from finite-time witnesses and residual tests) gates every micro--macro statement. Under \( \)CHW we derive diffusion and prove the central scaling \( \tau_{\text{copy}} = \Theta\!\left(\sqrt{\chi^{(2)}_{\text{micro}}}\right) \), where \( \chi^{(2)}_{\text{micro}}=\langle \delta Q,\,(-\mathcal{L}_\perp)^{-2}\,\delta Q\rangle_{\mathrm{KM}} \) is a second-moment fast-complement susceptibility. Optional bridges (thermal modular saturation and Higgs-portal matching) are isolated as explicit model Axioms; the "Golden Relation'' is then a Theorem and is non-circular provided an independent \( \tau_{\text{copy}} \) inference NC is satisfied. We include an explicit, dataset-level certification appendix (tables generated from bundled validation outputs), enabling direct audit.

Abstract: Over the centuries, many birds have gone extinct, and many are currently endangered due to anthropogenic activities, inability of some birds to compete for food and the negative effects of climate change. To promote biodiversity of rare birds requires deliberate human efforts to create ecosystems that conserve them and enhance their survival. This work implemented a design-driven solution to an identified problem of squirrel feeding on bird seeds. Thus, it reports the design, development, prototyping and testing of a squirrel-proof birdfeeder capable of selectively preventing squirrels but allowing birds to feed from it. The design comprised of a compression spring and two concentric cylinders. Finite Element Analysis and Failure Mode and Effect Analysis were used to optimise the structural design and functionality of the bird feeder. Testing of the bird feeder showed that birds successfully fed from it, whilst squirrels could not access the feeds due to the mass differential mechanism based on Hooke’s law. Camera-recoded interactions showed that when a squirrel exerted its weight anywhere on the surface of the feeder, the spring compressed to displace the outside surface downwards to close-off the feeding holes and prevented a squirrel from accessing the bird seed. The prototype is a reliable solution to the problem of squirrels consuming bird seeds at home and in the parks.

Abstract: Mango holds a significant place globally. Considering its importance, it is also called 2 the king of fruits. Accurate price forecasting is essential for market decisions, policy 3 formulation, and agricultural market stability. Traditional time series models struggle 4 to provide effective and accurate forecasts of Mango prices and cannot capture their 5 nonlinear dynamics. The current study integrates machine learning, deep learning, and 6 statistical models to build a robust forecasting model using a dataset from 2001 to 2025. This 7 study proposed a novel attention-based Mango price forecasting approach. It significantly 8 forecasted Mango prices in the Indian market. It combines the strengths of various models 9 and produces generalized results. The hybrid ETS + ANN + GARCH model has high 10 predictive accuracy (MAE = 0.0498, MSE = 0.0106, RMSE = 0.1028, R2 209 = 0.774) and 11 ETS+SVM Hybrid achieves the accuracy level (MAE = 0.063, MSE = 0.006, RMSE = 0.078, 12 R2 = 0.873). The performance of ETS + BiLSTM is also significant, with an accuracy level 13 97.5%. Thus, an attention-based approach offers a new technological paradigm for mango 14 price forecasting.

Abstract: Effective wolf monitoring is more critical than ever to support robust population estimates, identify breeding packs, and anticipate and mitigate attacks on livestock. This study evaluates bioacoustic monitoring to estimate wolf population size and detect packs and pups by howling activity, using recordings collected from free-ranging wolves in four different study areas in Denmark and from captive wolves housed in two zoos. It assesses whether howl structure can identify wild individuals and discriminate between current year-pups (aged between four and nine months) and adults. At one wild Location 1, we identified two free-ranging individuals from 40 adult howls by quantifying fundamental-frequency features and applying linear discriminant and multivariate variance analyses; individual classification accuracy was 92%. In captivity, the same workflow yielded 84% accuracy for three wolves at Location 5 and 86% for four wolves at Location 6, including perfect classification for one animal. We examined howls recorded from late August 2021 to February 2022 using maximum fundamental frequency. Across months, mixture modelling and principal component analysis consistently resolved two groups in the wild data, and multivariate tests indicated significant separation each month (p &lt; 0.001), consistent with a pup–adult contrast and the expected autumnal decline in pup frequencies as they mature. A focused analysis restricted to adult-range howls also resolved two groups with very strong multivariate separation (p &lt; 0.001), in line with female–male differences. Overall, passive bioacoustics is an effective, non-invasive approach for wide-area coverage and for inferring pack composition from acoustic evidence alone.

Abstract: Background: Self-awareness is a core developmental competence that supports psy-chological adjustment, resilience, and adaptive functioning during late adolescence and emerging adulthood, a period characterized by identity exploration, academic demands, and increasing social responsibility. Strengthening domains such as self-esteem, stress management, emotional regulation, and positive thinking may re-duce vulnerability to psychosocial difficulties during this critical life stage. Methods: This study evaluated the effectiveness of the self-awareness module of UNICEF’s Basic Life Skills Training Program (BLSTP) using a randomized controlled design. Sixty Pa-kistani university students aged 18–24 years were randomly assigned to an experi-mental group or a waitlist control group. The intervention targeted four self-awareness subdomains through structured group sessions. Standardized measures were adminis-tered at pre-test, post-test, and follow-up. Data were analyzed using descriptive statis-tics, t-tests, chi-square tests, and repeated-measures ANOVA. Results: Compared to controls, participants in the experimental group showed significant improvements in self-esteem, stress management, emotional regulation, and positive thinking. Large ef-fect sizes were observed (partial η² = 0.46–0.84), and gains were maintained at fol-low-up, indicating sustained intervention effects. Conclusions: The BLSTP self-awareness module appears to be an effective and culturally appropriate preven-tive intervention for enhancing key psychosocial competencies in late adolescents and young adults. Its integration into educational and community-based youth programs may support resilience, adaptive coping, and psychosocial well-being among Pakistani adolescents and emerging adults.

Abstract: Background/Objectives: The optimal duration of postoperative antibiotic therapy for bone and orthopaedic implant infections remains undefined. The SALATIO Trials are prospective randomised trials investigating whether shorter antibiotic courses are non-inferior to standard durations across different infection strata. This report presents the second interim analysis. Methods: Two unblinded non-inferiority RCTs were conducted (intention-to-treat population). Primary outcomes were remission, clinical failure, and microbiologically identical recurrence. In SALATIO 1 (material arm), participants with infected implants, retained or replaced during initial surgery, were randomised to short-course (six weeks) or long-course (twelve weeks) targeted systemic antibiotic therapy following debridement. In SALATIO 2 (non-material arm), participants undergoing implant removal or two-stage exchange were randomised to either a short-course (three weeks) or a long-course (six weeks) of antibiotic therapy. Results: We analysed 175 infections with a minimum follow-up period of one-year from October 2022 until July 2025: 69 (39%) in the material arm (38 short-course [55%], 31 long-course [45%]) and 106 (61%) in the non-material arm (44 short-course [42%], 62 long-course [58%]). No significant differences in clinical failure (19% overall) or microbiological recurrence (7%) were observed between treatment arms in either stratum. Multivariate analysis identified diabetes mellitus and number of debridements—but not antibiotic duration—as independent risk factors for clinical failure. Patients receiving short-course therapy experienced significantly fewer adverse events (median 0 versus 1; p=0.01). Formal non-inferiority has not yet been achieved due to limited statistical power. Conclusion: This interim analysis suggests no disadvantage of shorter antibiotic regimens in surgically treated orthopaedic infections, whilst reducing adverse events. Patient comorbidities and surgical factors appear to be more relevant to treatment outcomes than antibiotic duration. The SALATIO Trials are ongoing and may support improved antibiotic stewardship without compromising outcomes. Trials Registration: NCT05499481.

Abstract: In the present view on neutrinos three flavour states are recognized that are composed by a characteristic mixture of mass eigenstates. The absolute scale of these eigenstates is unknown. So far, observational experiments have revealed numerical values for the squared mass differences. In this article it is shown that mass ratios can be found as well. This enables the assessment of the absolute scale of the neutrino masses.

Abstract: Institutional LLM chatbots are frequently deployed before enterprise single sign-on (SSO) is available, yet still require baseline access control, cost containment, and abuse prevention. This paper presents a pragmatic access-gating blueprint implementable in low-code orchestration platforms: (i) endpoint-specific, per-identity rate limiting composed across multiple keys (session/user id, email, and IP); (ii) eligibility enforcement via institutional email-domain allowlists with hardened normalization; and (iii) email-delivered one-time passcodes (OTP) to verify mailbox control before enabling chat functionality. Beyond describing control flow and state, we make security-critical choices explicit and standards-aligned (CSPRNG OTP generation; hashed-at-rest verifiers using HMAC with per-issuance nonce, explicit domain separation “context”, and key identifiers; constant-time comparisons; TTL/attempt limits; single-active issuance with atomic rotation; session fixation defenses; CSRF-safe submit endpoints; key management and rotation). We quantify an online-guessing upper bound under stated limits and discuss why OTP spraying dominates risk, motivating anomaly-driven greylisting and multi-key limiter composition suitable for shared-IP campus environments. To reduce reliance on opaque low-code trust anchors, we provide a vendor-agnostic platform verification checklist and a reference external state-store pattern with signed, replay-resistant, monotonic state transitions and revocation semantics. Finally, we position email-OTP gates as a transitional control within broader enterprise LLM security posture (OWASP and participant-aware access control), and give a concrete migration roadmap toward stronger identity mechanisms (OIDC/OAuth, TOTP, and WebAuthn). The contribution is a systems design and operational blueprint rather than a novel algorithm or empirical study.

Abstract: This new frame work of thermodynamics consists of four parts:（1）The traditional thermodynamics (a brief one), relating to all the thermodynamical processes we meet in our life，work, ordinary research, and so on, covering an extremely immense scope. Numerous and numerous human practices confirm that all these processes are irreversible, and entropy tends to increase, never decreases; (2）The thermodynamics of thermal electrons in a magnetic field. The thermal electrons here are emitted at room temperature from two identical and parallel Ag-O-Cs emitters, A and B (work function 0.8eV) in a vacuum tube. The tube is applied by a static magnetic field parallel to A and B, bending the trajectories of the electrons, resulting in a weak asymmetry in their thermal motion（to left or to right）. Emitter A, losing some net electrons, is charged positively; and emitter B, getting some net electrons, is charged negatively. An electric potential between A and B is formed, enabling the tube outputs a continuous tiny but macroscope current to an exterior load, e.g., a resistor, or a storage battery. (Reverse the direction of the magnetic field, the output current also reverses.) Due to the ceaseless output of electric energy, the internal energy of the tube should decrease slightly, and the whole tube follows to cool down slightly. The slightly cooled tube can automatically absorb waste heat from the ambient air (that is kept at a constant room temperature) to compensate its output electric energy. The experiment converts the waste heat from the ambient air to electric energy, directly violating the Kelvin-Planck statement of the second law. Two short experiment videos are included in this article. (3）Cosmic thermodynamics. The authors approve of the idea that the universe is gravitationally closed, and naturally, there should be an extremely immense ocean of thermal radiation in the central part of the closed universe. The 2.73K microwave background radiation discovered in 1965 should just be this immense heat ocean. Due to the big bang, all the about 2ⅹ1012 galaxies are now flying outward fiercely. When they reach their individual far-most positions in the closed universe，they will turn back one after another, fly towards the central region of the universe, passing through it, until reach their individual far most positions on the other side of the closed universe. Then they keep shuttling with extremely great amplitudes in the closed universe ceaselessly. There are numerous stars and many black holes in every galaxy. A black hole annexes any celestial body that it encounters. The directions of the shuttling of the galaxies are different in the 4p solid angle, so in a long, long duration, the 2×1012 galaxies have numerous chances to meet each other in the central region. When a black hole encounters a star or another black hole in the central region in the shuttling, annexation happens. All the matter scattered to the extremely vast space by the big bang will thus be collected step by step, until finally assemble to be a single extraordinary immense black hole, the central black hole. On the other hand, the big bang and all its subsequent processes are all huge irreversible processes. They produce and eject immense amount of light and thermal radiation into the vast cosmic space. The light and thermal radiation are also impossible to fly off the closed universe, shuttling ceaselessly in the closed universe with much, much greater amplitudes. After a long, long relaxation time, by interchange heat with the rare cosmic atoms, molecules, dusts, rocks, etc., (they are all at 2.73K) in the metagalaxy region, they will finally mingle into the 2.73 heat ocean. The central black hole, containing all the real matter of the universe, has an extraordinary immense event horizon, will take in continuously and monotonically the thermal radiation from the 2.73K heat ocean with an extraordinarily great power, leading eventually to a new big band. A big band followed by a big assembling forms a big cycle. All the matter and an extremely great amount of energy in the universe are involved in the big cycle. (4）The new theoretical system of thermodynamics. The first law of thermodynamics is still energy conservation. Energy is conserved in amount wherever and whenever. It is a law of the universe. The new second law of thermodynamics is energy cycle. All the matter and energy are involved in a big cycle in the closed universe. Entropy may increase, it may also decrease. The general increase and general decrease of entropy match each other in a big cycle. Clausius’ Heat Death is an excessive anxiety.

Abstract: Impairments in balance control are common across various clinical conditions and aging, necessitating reliable methods for assessment. This study introduces a novel, low-cost posturographic system based on an unstable spring-supported platform that calculates center of pressure (COP) displacement using angular measurements in two horizontal axes. A heterogeneous sample of 105 participants underwent repeated trials on both the novel system and a traditional firm platform under eyes-open and eyes-closed conditions. COP velocity was recorded and analyzed for reliability using intraclass correlation coefficients (ICC). Results showed significantly higher COP ve-locity on the unstable platform when visual input was removed, indicating greater re-liance on visual control under unstable conditions. The novel system demonstrated comparable reliability to traditional platforms, with ICC values exceeding 0.90 when mean values from three trials were used. No learning effect was observed on the un-stable platform, unlike the firm one. These findings suggest that the new system is a valid alternative for balance assessment, particularly effective in differentiating indi-viduals with varying balance capabilities under eyes-closed conditions. Its affordabil-ity and methodological soundness make it suitable for clinical use and broader screen-ing applications aimed at fall prevention.

Abstract: Image datasets characterized by high intra-image structural heterogeneity pose significant challenges for supervised classification, particularly when local patterns contribute unevenly to image-level decisions. In such scenarios, direct image-level learning may obscure relevant local variability and introduce bias in both training and evaluation. This study proposes a statistically guided, patch-based computational pipeline for the automatic classification of elementary morphological patterns, with application to bioelectrographic imaging data. The pipeline is progressively refined through explicit statistical diagnostics, including image-level data splitting to prevent data leakage, class imbalance handling, and decision threshold calibration based on validation performance. To further control structural bias across images, a continuous image-level descriptor, denoted as \textit{pct\_point\_true}, is introduced to quantify the proportion of point-like structures and support dataset stratification and stability analysis. Experimental results demonstrate consistent and robust patch-level performance, together with coherent behavior under complementary image-level aggregation analysis. Rather than emphasizing architectural novelty, the study prioritizes methodological rigor and evaluation validity, providing a transferable framework for patch-based analysis of structurally heterogeneous image datasets in applied computer vision contexts.