Tashkent Islamic University

Hyperspectral imaging (HSI) enables real-time, non-invasive tissue characterization by capturing biochemical signatures across hundreds of spectral bands simultaneously. However, the computational demands of processing vast hyperspectral datasets create significant bottlenecks for clinical deployment. This chapter examines how edge computing and hardware acceleration technologies—including Field-Programmable Gate Arrays (FPGAs), Graphics Processing Units (GPUs), and specialized neural accelerators—enable real-time HSI processing at the point of care. We analyze architectural trade-offs, implementation strategies, and clinical workflow integration approaches that reduce processing times from minutes to milliseconds. Recent advances in embedded platforms achieve throughput rates exceeding 250 MSamples/s while maintaining power consumption below 15W, making intraoperative HSI guidance practically achievable.

Microgrids offer enhanced resilience and efficiency but require sophisticated energy management systems (EMS) to balance conflicting objectives like cost minimization, renewable energy utilization, and component longevity, especially under uncertainty. Traditional optimization methods often rely on precise forecasts and may struggle with real-time adaptation and complex trade-offs like battery degradation. This research aimed to develop a deep reinforcement learning (DRL) based EMS for optimizing microgrid operation considering operational cost, battery degradation, and renewable generation uncertainty. A deep Q-network (DQN) based reinforcement learning agent was trained to manage energy flows within a simulated microgrid comprising solar PV, battery storage, controllable loads, and a grid connection. The reward function incorporated operational costs, battery degradation, and renewable utilization objectives, with the agent learning control policies through environment interaction. The DRL-based EMS demonstrated effective adaptive control, achieving a 12.01% reduction in overall operational costs compared to the model predictive control benchmark. The DRL agent implicitly learned strategies that reduced battery degradation by 8.19% while increasing renewable energy utilization by 10.39%. Most notably, the approach maintained robust performance under uncertainty, with only 8.9% cost increase under severe forecast errors compared to 21.5% for conventional methods. This study demonstrates the efficacy of DRL for adaptive multi-objective microgrid energy management, successfully balancing economic operation, battery health preservation, and renewable energy integration under uncertainty.

The dysregulation of IL-17/IL-17 receptor A (IL-17RA) signaling axis is a central driver of multiple autoimmune diseases. In contrast to targeting individual IL-17 cytokines, blocking IL-17RA simultaneously inhibits the receptor engagement of multiple IL-17 ligands, thereby effectively suppressing downstream pathway activation. Brodalumab, the only approved IL-17RA-blocking antibody, suggests robust clinical efficacy. However, its inhibition of IL-17RA has been associated with an increase in systemic IL-17C levels, which is related to suicidal ideation and behavior. Consequently, the development of novel strategies capable of broadly blocking IL-17 signaling remains critically important. This study developed a novel therapeutic strategy by engineering cell-membrane vesicles with IL-17RA (IL-17RA-CMVs) as high-avidity decoy receptors for effectively blocking the IL-17/IL-17 receptor A (IL-17RA) signaling axis. Stable 293T cell lines exhibiting high surface expression of mouse or human IL-17RA (m/hIL-17RA), mediated by a platelet-derived growth factor receptor (PDGFR) transmembrane domain, were successfully constructed and applied for the preparation of m/hIL-17RA-CMVs. The mIL-17RA-CMVs were efficiently loaded into hyaluronic acid-based microneedles (mIL-17RA-CMVs-MNs), and the resulting mIL-17RA-CMVs-MNs exhibited sufficient mechanical strength to penetrate the skin and rapidly dissolved within 5min upon insertion. In an imiquimod (IMQ)-induced murine psoriasis model, the topical application of mIL-17RA-CMVs-MNs significantly alleviated disease severity, as evidenced by a remarkable reduction in Psoriasis Area and Severity Index (PASI) scores, suppression of epidermal hyperplasia, and normalization of spleen index. Mechanistic studies revealed that the treatment mIL-17RA-CMVs-MNs markedly downregulated the expression of key IL-17RA pathway-related inflammatory mediators (CXCL1, CXCL2, CCL20) and antimicrobial peptides (S100A7/A8/A9) in skin lesions. Furthermore, in vitro experiments indicated that hIL-17RA-CMVs effectively functioned as decoy receptors, neutralizing IL-17A and consequently inhibiting the upregulation of pro-inflammatory cytokines and hyperproliferation in HaCaT keratinocytes. This study presents a pioneering approach that synergizes the broad-spectrum neutralization capability of engineered decoy receptor vesicles with the localized and minimally invasive delivery advantage of microneedles. These findings position IL-17RA-CMVs (or IL-17RA-CMVs-MNs) as a highly promising and translatable therapeutic modality for the treatment of psoriasis and potentially other IL-17-mediated inflammatory diseases.

The article examines the historical development, transformation, and current state of Islamic education in Uzbekistan, tracing its roots from the medieval “Higher Madrasahs” of Mawaraunnahr to contemporary institutions under the Muslim Board of Uzbekistan. It highlights the continuity of religious and secular knowledge despite the challenges posed by the Soviet atheistic regime, the role of SADUM and influential figures such as the Babakhan muftis in preserving educational traditions, and the restructuring of religious education after independence. The study analyzes the curricula, textbooks, organizational structure, and achievements of institutions such as the Mir Arab Madrasah, Barak Khan Madrasah, Tashkent Islamic Institute, and new specialized centers established under the initiatives of President Shavkat Mirziyoyev. The research emphasizes the integration of secular and religious sciences, the training of highly qualified specialists, and the role of modern Islamic educational institutions in fostering national identity, tolerance, and universal values. The findings provide insights into the continuity, reform, and modernization of Islamic education in Uzbekistan, offering a framework for understanding its prospects and challenges in the 21st century.

ABSTRACT In this paper, initial‐boundary value problems for a nonlocal analogue of a degenerate parabolic equation are considered. The authors study the inverse problems where it is necessary to determine not only a solution to the equation, but also a function in its right‐hand side. In the framework of this research theorems on the existence and uniqueness of solutions to these problems are proved.

Autoimmune thyroiditis is a multifactorial endocrine disorder characterized by chronic immune-mediated inflammation, oxidative imbalance, and disruption of gut microbiota homeostasis. These pathological processes lead to thyroid hormone deficiency, metabolic dysfunction, and systemic immune polarization. The present study aimed to evaluate the immunological, antioxidant, and microbiota-corrective effects of three plant-derived flavonoids - quercetin, dihydroquercetin (taxifolin), and luteolin - in an experimental rat model of autoimmune thyroiditis. Thyroid hormone concentrations (T3, T4, and fT3), antioxidant enzyme activity (GPX1), macro- and microelement balance (Ca²⁺, Mg²⁺, Fe, K⁺ and P), and intestinal bacterial composition were analyzed to assess the extent of restoration. Autoimmune thyroiditis caused a pronounced decrease in thyroid hormone levels (T3 −66.5%, T4 −66.7% and fT3 −39.5%) and GPX1 activity (−59.1%), along with disturbances in essential macro- and microelements and microbiota composition. Flavonoid treatment markedly ameliorated these impairments: luteolin restored T3 and T4 levels to near-physiological values and normalized GPX1 activity by 93.6% of the control. Quercetin and dihydroquercetin showed moderate but significant improvements in antioxidant and endocrine parameters. Additionally, flavonoid supplementation rebalanced the gut microbiota, increasing beneficial taxa (Lactobacillus, Bifidobacterium and Faecalibacterium prausnitzii) while reducing pathogenic species (Escherichia coli, Streptococcus and Fusobacterium). Collectively, the findings demonstrate that natural flavonoids exert a potent corrective influence on immune, redox, and microbiota disturbances in autoimmune thyroiditis. Among them, luteolin exhibited the strongest integrative effect, suggesting its potential as a promising adjunctive therapy to conventional treatment in thyroid autoimmune diseases. HIGHLIGHTS Autoimmune thyroiditis induced severe endocrine, oxidative, and microbiota disturbances in rats. Dietary flavonoids significantly restored thyroid hormone homeostasis and antioxidant defense. Luteolin exhibited the strongest integrative effects on GPX1 activity and immune modulation. Flavonoid treatment rebalanced gut microbiota by increasing beneficial and reducing pathogenic taxa. Natural flavonoids represent promising functional agents for correcting immune-redox-microbiota dysregulation in AIT. GRAPHICAL ABSTRACT

Buildings are shifting from static, environment centric control schemes toward dynamic systems that adaptively respond to individual occupants. To clarify how this transition affects building operation, this paper reviews recent advances in occupant centric control from three dimensions: physical control systems, data and network infrastructure, and occupant interaction mechanisms. The review draws from research in building science and computing and organizes key developments using the trinity of transformation, resilience, and sustainability. The results show that the shift to occupant centric requires high-density sensing, distributed data processing, interoperable protocols, and feedback models that integrate occupant behavior. The paper also discusses how concepts introduced from Web3 can support decentralized data management and long-term trust in occupant participation. This work provides a technical and conceptual basis for researchers and practitioners involved in the digital transformation of smart building operation.