Peripheral neuropathy is a broad and clinically diverse group of disorders affecting the peripheral nervous system. Patients may experience pain, numbness, tingling, weakness, impaired balance, and progressive difficulties with daily activities. Diabetes is one of the most common causes, but peripheral neuropathy may also result from inherited disorders, nutritional deficiencies, infections, autoimmune conditions, medications, toxins, and metabolic abnormalities. This diversity makes effective treatment a continuing challenge.

From a pharmaceutical perspective, the management of peripheral neuropathy has traditionally focused on controlling symptoms, particularly neuropathic pain. Drugs such as duloxetine, pregabalin, gabapentin, and tricyclic antidepressants remain widely used therapeutic options. Topical agents, including lidocaine and high-concentration capsaicin, can also be useful for selected patients. Although these treatments can provide meaningful symptom relief, their effectiveness varies between individuals and adverse effects may limit their use.

As technology advances, digital innovation and public health are increasingly collaborating to address global health challenges. Digital health technologies are transforming how we track, predict, and respond to pandemics and chronic diseases. Tools such as artificial intelligence, big data analytics, wearables, and telemedicine enhance monitoring, improve health outcomes, and expand access to care. Effective implementation requires careful consideration of ethics, logistics, and governance. This editorial examines the impact of digital health technologies on public health, highlights their potential, and recommends responsible approaches for their use.

Introduction: In the present turbulent era, security management extends across a broad spectrum of societal life, ranging from the everyday activities of citizens to scientific and technical endeavors in many disciplines. A critical element of every social system is healthcare. Modern technologies are being introduced into this field almost on a daily basis. For accurate disease diagnostics, contemporary healthcare requires high-quality imaging methods. One of the imaging modalities is the discipline of nuclear medicine. Radioactive substances administered into the patient’s body provide an accurate picture of the functional state of the internal environment. Both patients and healthcare personnel are exposed to invisible ionizing radiation, which, in doses exceeding established limits, becomes hazardous. Similar to other disciplines, nuclear medicine is continually advancing. The current standard is represented by SPECT technologies. SPECT CZT is an upgraded system in which analog detection technology has been replaced by semiconductors.
The high incidence of cardiovascular diseases, especially ischemic heart disease, requires early diagnosis and modern treatment.
Methodology: Using nuclear medicine methods, we try to detect these changes in time and thus prevent the occurrence of acute coronary events. In nuclear cardiology, instead of a large-area scintillation detector, a new type of cardio-gamma camera “Discovery CZT 530c” based on the principle of semiconductor detectors began to be used. The abbreviation CZT stands for semiconductor composition (Cadmium-Zinc-Tellur).
The set of respondents consisted of 6280 people examined in the years 2020-2025 by myocardial perfusion scintigraphy. There were 3140 nondiabetic patients and 3140 diabetic patients in the analysed group of the 6280 examined.
Results: In the analysed group of 3140 nondiabetic respondents, 75% had negative findings and 25% had positive findings in terms of the presence of ischemic heart disease. In the group 3140 of diabetic patients, there was a negative finding in 63% of respondents and a positive finding in 37% of the respondents in the sense of positive ischemic heart disease. Using myocardial perfusion scintigraphy in the diagnosis of functional changes, we confirmed a benefit in detecting early changes in coronary heart disease, including in the diagnosis of microvascular angina.
Conclusion: Nuclear medicine methods are of great benefit for the diagnosis of small vessel disease, diabetic cardiomyopathy and cardiac autonomic neuropathy in patients with diabetes mellitus. The new type of cardio gamma camera “Discovery CZT 530c” allows more accurate assessment of myocardial perfusion abnormalities and at the same time the reduction of the radiopharmaceutical dose reduces the patient's radiation load by 50%.
Keywords: Semiconductor Detectors for Ionizing Radiation; Cardiac CZT SPECT gamma camera 530c; SPECT/CT camera Star Guide; Coronary heart disease; Radionuclides

Guiding left-handed students toward a healthy lifestyle during their adaptation to primary school education is a critical pedagogical and psychophysiological issue. This transition involves profound psychological restructuring that demands both mental resilience and significant physical stamina from young learners. School readiness for left-handed children encompasses multifaceted requirements, including overall physical development, foundational knowledge acquisition, self-care skills, behavioral culture, effective speech, fine motor development for handwriting, collaborative abilities, and learning motivation. Contrary to the widespread assumption that school adaptation concludes within the initial 3-5 weeks or the first quarter, empirical evidence shows that for first-grade left-handed students, this adaptation phase often extends through the fourth quarter. This protracted adaptation necessitates sustained health-preserving educational environments, ergonomic adjustments, and systematic healthy lifestyle promotion to prevent premature physical exhaustion and psychological strain. This article explores comprehensive methodologies for educators and parents to support left-handed learners, fostering enduring healthy lifestyle habits, reducing motor stress, and ensuring a seamless, health-oriented integration into primary education.
Keywords: healthy lifestyle; adaptation; rehabilitation; healthy physical education; functional laterality profile; sinistrality; left-handedness; left-handed schoolchildren; left-handed students; school adaptation; healthy lifestyle habits; student well-being; primary education; psychological restructuring; fine motor skills; adaptation period length

Despite favorable outcome of Hodgkin lymphoma approximately 25% of patient’s experience relapse or refractory to initial treatment. Non-Hodgkin Lymphoma is clinically and biologically a diverse group of disease ranging from indolent to aggressive clinical course. Diffuse large B cell variant is clinically aggressive course while follicular, Marginal zone lymphoma are indolent. Response rate to conventional chemotherapy is more than fifty percent however in significant proportion do relapse. Several factors are considered for adopting salvage regimen including autologous bone marrow transplant. Novel emerging treatment are also under current practice. A retrospective clinic -pathological profile and treatment outcome of relapsed lymphoma cases at Vayodha Hospital from January 2022 to February 2026. Retrospective chart review of patients diagnosed as relapsed lymphoma and got treated were enrolled in the study over 50 months’ period. Total of 20 adult patients were enrolled in the study. Biopsy was done in all cases and disease classification was done according to histomorphology and immunohistochemistry. Staging was done by PET CT/CECT. From January 2022 to February 2026, twenty cases were registered with relapsed lymphoma. Mean age of presentation was 42.5 years (range 21-72 years). Male: female ratio was 2.3:1. During this period four patients with Hodgkin lymphoma and sixteen patients with Non-Hodgkin Lymphoma relapsed. Biopsy was done in all and further subtyping was done on the basis of histomorphology and immunohistochemistry. Staging and response evaluation of treatment was done by PET CT in 55% while contrast enhanced CT was done in 45%. All Hodgkin lymphoma were treated with ABVD regimen prior to relapse while Non-Hodgkin lymphoma was treated with Rituximab based regimen in majority 75%. Median time to relapse was 36 months. Majority (80%) was documented as late relapse and nodal disease in 55%. Extra nodal were 45% and sites were Brain & spine (25%), orbit, bone marrow, gastrointestinal tract, nasopharynx and spleen. Diffuse large B cell histology was found in 56%. Mantle cell (19%), T cell rich B cell (12.5%), Follicular and MALT lymphoma each 6% are other histological types. Chemotherapy based salvage regimen was used in 80% and autologous bone marrow transplant after salvage was opted in 10% and remaining 10% was treated with only palliative care. DHAP (Dexamethasone, Ara-C, Cisplatin) regimen was used in 45%. Outcome analysis revealed 70% alive and deaths were recorded in 30% due to progressive and refractory disease. Mean duration of follow up since first diagnosis was 64.5 months (range: 8 - 96 months). Relapse poses significant challenges in resource poor country. Limited diagnostic facilities and poor patient finance poses difficulty in planning treatment strategy. Standard salvage followed by bone marrow transplant is limited due financial constraint and limited facility as well.
Keywords: Lymphoma; Bone marrow transplant; Non-Hodgkin lymphoma and Nepal

Background: There has been a noticeable decline in academic performance globally. This study examined the relationship between physical activity level, sleep quality, and academic performance among undergraduate students in Delta State, Nigeria. Methods: A cross-sectional descriptive survey was conducted using a multi-stage sampling technique and a structured, validated, self-administered questionnaire. Data were analyzed using chi-square tests, Pearson correlation, and multiple linear regression at p < 0.05. Results: 69.0% of the respondents had a moderate physical activity level. Mean sleep duration was 5.96 ± 1.40 hours; 57.2% reported good and 21.3% reported poor overall sleep quality. Mean CGPA was 3.30 ± 0.84. Physical activity level was significantly associated with sleep quality (χ² = 21.38, p = 0.001), and sleep quality was significantly associated with academic performance (χ² = 43.95, p = 0.001). Physical activity, sleep quality, and academic performance were positively correlated (r = 0.291-0.472, p < 0.01). Multiple regression showed that sleep quality (β = 0.418, p = 0.001) and physical activity level (β = 0.208, p = 0.001) jointly predicted academic performance, explaining 28.7% of its variance (R² = 0.287, F = 84.52, p = 0.001). Conclusion: Sleep quality and physical activity are significant, independent predictors of academic performance among undergraduate students in Delta State, with sleep quality exerting the stronger influence.
Keywords: physical activity; sleep quality; academic performance; undergraduate students

The continuously increasing global demand for energy, driven by population growth, rapid urbanization, and ongoing digital transformation, necessitates the adoption of sustainable, clean, and universally accessible energy sources. In this context, solar energy, as an abundant and renewable resource, stands out as one of the most promising solutions to address these challenges. The Earth receives an immense amount of solar radiation, yet only a small fraction is currently harnessed. Indeed, the solar irradiance reaching the Earth’s surface has the theoretical potential to meet global energy demands.

Traditional pollution source attribution relies on expensive chemical speciation and handcrafted statistical models that cannot leverage the rich semantic information embedded in environmental monitoring metadata. We present EnhancedPollutionAttributorWithLLMs, a novel multimodal framework that integrates Large Language Models with advanced neural architectures for automated pollution source attribution. Our approach extracts semantic features from EPA Air Quality System site descriptions and combines them with spatiotemporal environmental data using rigorous geographic holdout validation. Experimental evaluation on 3,899 EPA monitoring records demonstrates that Vision Transformer with LLM-enhanced features achieves exceptional performance (R² = 0.9969, RMSE = 0.3116), significantly outperforming traditional approaches. Ablation studies reveal that LLM-derived semantic features contribute 1.2% improvement in R², while comprehensive interpretability analysis using SHAP provides actionable insights for environmental policy. This work establishes the first reproducible benchmark for LLM-enhanced environmental monitoring and demonstrates the potential for automated, large-scale pollution source attribution.

Keywords: pollution attribution; large language models; environmental monitoring; EPA AQS; semantic feature extraction; vision transformer; interpretable ML; neural networks

AI and AI-based technologies like ChatGPT are beginning to redefine how firms can create value, make decisions, engage with customers, operate their business, and even build new business models. However, evidence relating to the organizational characteristics required for the successful implementation of AI is limited, especially within the Hong Kong business environment. This study looks at the adoption, implementation, and business implications of AI and ChatGPT within the context of Hong Kong firms and sectors. The objective is to determine the various capabilities and success factors that determine the successful implementation of AI, which includes strategic alignment, support from the leadership, technological capabilities, data availability, employee competencies, organizational culture, ethical management, and change management capability. These findings will serve as the basis for developing a context-based theoretical framework that connects the use of AI technology to organizational capability, implementation factors, and business performance. Another aspect that is considered is the role of business leadership in the use of AI to transform businesses, as well as the issues of privacy, security, ethics, cost of implementation, technical skill, and readiness of employees. This research will not only benefit the academic field of AI readiness and digital transformation but will also give practical advice to Hong Kong businesses.

In this paper we are considering linear elasticity theory to model the maximum horizontal force on a building that can only carry compression stresses from the gravity load, such as masonry and unreinforced concrete buildings. To solve this problem, we define two simple dimensionless geometrical quantities and define a corresponding plot between the two quantities that we denote the Bella Curve. This curve can be used to provide an estimate of the moment arm of the normal force to withstand the above mentioned maximum horizontal force so that we still have compression stress in all load bearing walls. We illustrate the principle on classical beam sections and then also demonstrate how the principle can be applied to provide an estimate of safety towards wind for the Danish high rise building from Bellahøj and for the 670-year-old Giotto Bell Tower in Italy.

Off-grid solar energy systems are increasingly adopted for residential use as a sustainable alternative to fossil fuel–based electricity. Accurate design of these systems is essential to ensure reliability, efficiency, and cost-effectiveness. This study compares manual sizing calculations with PVsyst simulation outputs for residential off-grid systems. The manual approach focuses on determining the required number of PV modules, inverter capacity, and battery storage while accounting for surge loads. PVsyst simulations are then used to model the same system under environmental and operational conditions. Results reveal that while PVsyst provides valuable long-term performance insights, it tends to underestimate inverter requirements and battery usability in off-grid applications. Manual design, in contrast, ensures reliable surge load handling and more realistic storage capacity estimates. The study concludes that a hybrid approach—integrating manual engineering methods with PVsyst simulations—offers a more reliable pathway for residential off-grid solar system design.

Keywords: Solar Energy; System Manual Design; Residential Solar Design; PVsyst Simulation; Battery Sizing; Surge Load