Administrative Liability for Artificial Intelligence Damage - An Analytical Study of the Rules of Administrative

تبين هذه الدراسة المسؤولية الإدارية عن أضرار الذكاء الاصطناعي - دراسة تحليلية لقواعد المسؤولية الإدارية، ذلك أن المسؤوليات الإدارية تختلف وفق تطبيقات الذكاء الاصطناعي، إلى جانب قلة المراجع الفقهية وغياب النص التشريعي الناظم لهذه المسألة؛ سواء في دولة قطر أو في غيرها. تناولت الدراسة في فصلها الأول، المفهوم والشخصية القانونية للذكاء الاصطناعي، من خلال تعريف الذكاء الاصطناعي أولا، وتوضيح الشخصية القانونية له ثانيا، وأبان الفصل الثاني مجالات تطبيق الذكاء الاصطناعي واستخداماته في القانون الإداري في حين الصرف الفصل الثالث للبحث في المسؤولية عن تطبيقات الذكاء الاصطناعي في القانونين المدني والإداري، من خلال استعراض موقف القانون المدني من المسؤولية عن الذكاء الاصطناعي، وأحكام المسؤولية الإدارية عن تطبيقات الذكاء الاصطناعي.This study shows administrative responsibility for the harms of artificial intelligence - an analytical study of the rules of administrative responsibility, as administrative responsibilities differ according to the applications of artificial intelligence due to the lack of jurisprudential references and the absence of legislative text, whether in the State of Qatar or comparative laws . The study dealt with the first chapter of the concept and personality of artificial intelligence, through the definition of artificial intelligence, and the legal personality of artificial intelligence, and the second chapter of the areas of application and uses of artificial intelligence in private law, through the areas of use of artificial intelligence in private law, and the areas of use of artificial intelligence in administrative law, and the third chapter of the responsibility for applications of artificial intelligence in civil and administrative law through the position of civil law on responsibility for artificial intelligence and the provisions of administrative responsibility for applications of artificial intelligence

Harnessing Renewable Energy for Smart Healthcare Facilities: Integrating Photovoltaic Systems with IoT for Enhanced Patient Care and Energy Efficiency

Healthcare facilities are among the most energy-intensive infrastructures, necessitating innovative solutions for reducing their environmental impact. This research investigates the integration of photovoltaic (PV) systems with Internet of Things (IoT) technologies to create smart healthcare facilities that optimize energy consumption while enhancing patient care. The study focuses on a case analysis of a mid-sized hospital where a hybrid energy system, combining solar PV panels with an IoT-based energy management platform, was implemented. IoT sensors monitor real-time energy usage, room occupancy, and critical medical equipment operation. This allows for dynamic energy distribution, prioritizing life-saving equipment during peak demand and utilizing excess solar energy for non-critical functions, thus reducing dependence on the grid. Initial findings reveal a 30% reduction in energy costs and a 20% increase in operational efficiency. Additionally, patient care quality improved due to the system’s ability to ensure uninterrupted power supply to critical areas, particularly during emergencies. This research highlights the potential of renewable energy in transforming healthcare facilities into energy-efficient, smart environments. By integrating sustainable energy with advanced technology, this approach addresses the urgent need for greener healthcare facilities and provides a scalable model for energy-efficient hospital management. The study offers significant implications for the future of healthcare infrastructure, presenting a blueprint for nationwide adoption of smart, sustainable energy solutions in medical facilities

Prognostic Models of Mortality Following First-Ever Acute Ischemic Stroke: A Population-Based Retrospective Cohort Study

Background and Aims: There is a lack of population-based studies focusing on guideline-based prognostic models for stroke. This study aimed to develop and validate a prognostic model that predicts mortality following a first-ever acute ischemic stroke. Methods: The study included 899 adult patients (≥ 18 years) with confirmed diagnosis of first-ever acute ischemic stroke enrolled in the Malaysian National Stroke Registry (NSR) from January 2009 to December 2019. The primary outcome was mortality within 90 days post-stroke (266 events [29.6%]). The prognostic model was developed using logistic regression (75%, n = 674) and internally validated (25%, n = 225). Model performance was assessed using discrimination (area under the curve (AUC]) and calibration (Hosmer-Lemeshow test [HL]). Results: The final model includes factors associated with increased risk of mortality, such as age (adjusted odds ratio, aOR 1.06 [95% confidence interval, CI 1.03, 1.10; p < 0.001]), National Institutes of Health Stroke Scale (NIHSS) score aOR 1.08 (95% CI 1.08, 1.13; p = 0.004), and diabetes aOR 2.29 (95% CI 1.20, 4.37; p = 0.012). The protective factors were antiplatelet within 48 h. aOR 0.40 (95% CI 0.19, 0.81; p = 0.01), dysphagia screening aOR 0.30 (95% CI 0.15, 0.61; p = 0.001), antiplatelets upon discharge aOR 0.17 (95% CI 0.08, 0.35; p < 0.001), lipid-lowering therapy aOR 0.37 (95% CI 0.17, 0.82; p = 0.01), stroke education aOR 0.02 (95% CI 0.01, 0.05; p < 0.001) and rehabilitation aOR 0.08 (95% CI 0.04, 0.16; p < 0.001). The model demonstrated excellent performance (discrimination [AUC = 0.94] and calibration [HL, X2 p = 0.63]). Conclusion: The study developed a validated prognostic model that excellently predicts mortality after a first-ever acute ischemic stroke with potential clinical utility in acute stroke care decision-making. The predictors could be valuable for creating risk calculators and aiding healthcare providers and patients in making well-informed clinical decisions during the stroke care process.This work was supported by the Fundamental Research Grant Scheme (FRGS), Ministry of Higher Education, Malaysia, with reference number FRGS/1/2021/SKK06/USM/02/19. Qatar University Open Access publishing facilitated by the Qatar National Library, as part of the Wiley Qatar National Library agreement

Shaping the future of primary healthcare: Factors influencing medical students' preference for family medicine specialty in Qatar

BACKGROUND: As countries strive to strengthen primary healthcare systems, understanding medical students' specialty preferences, particularly for Family Medicine, becomes crucial. Objective of present study was to determine factors that influence medical students' preferences for Family Medicine in Qatar. MATERIALS AND METHODS: A study was conducted among medical students at one public university in Qatar from March 1, 2023, to March 15, 2023. Data collected using a structured, validated questionnaire; students participated in the study by filling an online questionnaire. Information sought included sociodemographic characteristics, medical specialty preferences, and the impact of 31 factors on these choices such as interest in dealing with diverse patient issues, and the influence of physician role models among others. Statistical analysis performed using SPSS version 26.0 Descriptive statistics, including frequencies and percentages, were used to summarize participant demographics and medical specialty preferences. Mann-Whitney U-test tested the difference in preference for family medicine specialty by various students' characteristics. Logistic regression analysis performed to identify factors related to preferring Family Medicine. RESULTS: A total of 262 students completed the survey with age ranging between 17-24 years (Mean=20, SD=1.7 years); majority (68.3%) were females and 54.4% were non-Qatari. About 16% students reported having a first degree relative or a family friend with family medicine specialty. Compared to surgery and internal medicine, a fewer students selected family medicine as their preferred specialty. Surgery was ranked as the top career choice (53.4%) followed by internal medicine (36.5%) and pediatrics (31.7%). Presence of a personal connection to a field seemed to have a significant impact on student preference. Being in the clerkship phase of medical education (adjusted odds ratio [AOR]=2.18, 95% CI: 1.12-4.23, P = 0.022) and possessing a personal connection to Family Medicine (AOR= 3.46, 95% CI: 1.65-7.29, P = 0.001) significantly predicted the selection of Family Medicine between students' top two choices. CONCLUSION: Clinical exposure and personal connections influence students' preference for family medicine specialty. Promoting these elements through targeted educational and mentorship programs may increase students' interest in Family Medicine and help to address the gap between student preferences and the greater need for primary care providers

Drugging dancing protein clouds: A close look at disorder-based drug design

Since it was established in the late 19th century, the traditional “lock-and-key” model of protein functionality has been foundational in biochemistry, particularly with respect to protein structure and function (Fischer, 1894). However, the functionality realm of a protein has evolved, which inevitably rendered the traditional view a rather limited one. Indeed, with the discovery of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs), which do not require a stable structure to function, a paradigm shift was needed more than ever. This is particularly important because IDP and IDR exist as highly dynamic “dancing protein clouds.” Such clouds allow for engagement in diverse interactions that are key to a multitude of biological processes. This dancing cloud concept aptly depicts the notion that proteins are flexible and can change shape over time, akin to a cloud rather than a solid object. As such, our emerging understanding of proteins, particularly the intrinsic disorder thereof, challenges traditional views in biochemistry and the consequent implications for drug design and discovery. It is not surprising then that the roles of IDPs and IDRs in cellular signaling and other regulatory mechanisms are being increasingly appreciated and are fundamentally resha** our comprehension of the long-standing “key and lock” protein functionality. Uversky (2025) provides an extensive and critical look at the ever-growing field of targeting disordered proteins. The author pays close attention to the tractability and druggability of these IDPs (and IDRs). Not only does his paper effectively appraise the uniqueness of these entities as desirable pharmacological targets, but it also provides ample discussion of various modalities for targeting them. The author aptly discusses how in spite of, or in some instances because of, their interesting particularities, IDPs and IDRs are nonetheless druggable (Uversky, 2025). Uversky highlights that IDPs, ubiquitous in eukaryotic cells, have several advantages, including being flexible structures, which lends them multifunctionality. In addition, their binding dynamics/fuzziness, including decoupling specificity and affinity of binding, allow for weak yet specific complexes that are critical for signaling repression or deactivation. Other distinctive features include faster kinetics of interaction and conformational pliability, as well as oneto-many and many-to-one interactions. A rather interesting feature of some IDPs/IDRs is that their functions may be elicited despite, or even originate by virtue of, the lack of a thermodynamically very stable structure in a protein molecule or motif. The paper discusses various potential applications of IDP-based drug delivery systems. These include chimeric polypeptides fuse

Exploring global natural product databases for NLRP3 inhibition: Unveiling novel combinatorial therapeutic strategy for hidradenitis suppurativa

BackgroundHidradenitis suppurativa (HS) is a chronic inflammatory skin condition of the terminal hair follicle, which can present in sporadic, familial, or syndromic forms. The exact pathogenesis of HS remains elusive, posing a challenge for the development of effective treatments. Among the various immunological mechanisms, the NLRP3 inflammasome is thought to contribute to the pathogenesis of HS, releasing cytokines such as IL-1β and IL-18 which initiates and exacerbates inflammation. Consequently, targeting NLRP3 offers a potential strategy for mitigating inflammation in HS-affected skin. MethodsIn this study we used the docking, molecular dynamics simulation and binding free energy approaches to identify the potent inhibitor of NLRP3 by screening the African phytocompounds and traditional Chinese medicine databases. ResultsOur virtual drug screening analysis identified two lead compounds from each database, characterized by high docking scores such as SA-21676268 (-8.135 kcal/mol), SA-167673 (-10.251 kcal/mol), EA-45360194 (-10.376 kcal/mol), EA-46881231 (-10.011 kcal/mol), NEA-44258150 (-9.856 kcal/mol), NEA-135926572 (-7.662 kcal/mol), NA-163089376 (-9.237 kcal/mol), NA-440735 (-8.826 kcal/mol), TCM-392442 (-10.438 kcal/mol), and TCM-10043097 (-9.046 kcal/mol) which highlighted the strong binding affinity as compared to the control NP3–146 drug (-5.09 kcal/mol). Moreover, the values of dissociation constant further validated the strong binding affinity between the identified lead compounds and NLRP3. The dynamic stability and strong bonding energies of the lead compounds-NLRP3 complexes were confirmed by the molecular dynamic simulation and binding free energy calculation. The analysis of ADMET properties for all compounds indicated high intestinal absorption, water solubility, absence of hepatotoxicity, and skin sensitivity. ConclusionIn conclusion, our molecular simulations and binding free energy calculations confirmed the strong affinity of these lead compounds for NLRP3 as compared to the control drug, highlighting their potential as part of a combinatorial therapeutic strategy for HS to effectively reduce disease-related inflammation.This work was supported by Qatar University grant No. QUPD CAS-23-24491. This research was partially supported by Italian Ministry of Health (Ricerca Corrente) of Fondazione IRCCS Ca\u2019 Granda Ospedale Maggiore Policlinico, Milan (Italy)

Self-reported outcomes in adults with hypospadias: A meta-analysis of patient satisfaction and quality-of-life metrics

IntroductionHypospadias reconstruction seeks to correct structural problems associated with this congenital condition to improve patient quality-of-life (QoL) and overall well-being. While corrective surgery can lead to major functional and psychosocial improvements, some patients experience continuing problems that require additional procedures. This study evaluates patient-reported outcomes (PROs) in hypospadias care, particularly penile satisfaction and QoL after surgery, to fill this essential gap in the literature. MethodsComputerized bibliographic searches were performed in PubMed, ScienceDirect, Cochrane Library, and ClinicalTrials. Up to July 30th, 2024. Funnel plots and ROBINS-I questioners were used to assess publication and overall risk of bias. The random effect model was applied to determine the pooled parameters when I2 was more than 50 %. The fixed effect model was applied to the contrary. Confidence intervals (CIs) of 95 % were calculated. ResultEight studies were selected which included a total of 726 patients who self-evaluated satisfaction levels following hypospadias repair procedures the earliest of which was published on 2008. Three studies involving 144 people also examined QoL metrics among patients underwent hypospadias repair, with low publication bias and low-to-moderate overall risk of bias across the included studies. The pooled results indicated that subjects without hypospadias (control group) reported significantly higher satisfaction with penile appearance in 4 studies with continuous data (mean difference −1.43, 95 % CI -2.79–0.07, p < 0.05, high heterogeneity I2 = 90 %, p<0.05) and 4 studies with dichotomous data (odds ratio 0.1, 95 % CI 0.07–0.15, p < 0.05, low heterogeneity I2 = 0 %, p = 0.48). There is no significant difference of QoL between two groups (mean difference 0.62, 95 % CI -2.05–3.28, p < 0.65, moderate level of heterogeneity I2 = 69 %, p < 0.05). ConclusionOur research shows that post-hypospadias repair surgery patient satisfaction is inadequate, but their quality of life is equivalent to those without hypospadias. This study enhances understanding of hypospadias patients' key issues and suggests ways to improve quality of life after corrective surgery.This research is funded by Directorate of Research and Development, Universitas Indonesia under Hibah PUTI 2024 (Grant No NKB-635/UN2.RST/HKP.05.00/2024)

Beyond the Injury: How Does Smoking Impair Stem Cell-Mediated Repair Mechanisms? A Dual Review of Smoking-Induced Stem Cell Damage and Stem Cell-Based Therapeutic Applications.

While the literature on molecular and clinical effects of smoking on the lungs and other organs has been expansively reviewed, there is no comprehensive compilation of the effects of smoking on stem cell (SC) populations. Recent research has shown that tobacco exposure severely compromises the function of SC populations, particularly those involved in tissue regeneration: mesenchymal SCs (MSCs), neural progenitors, and hematopoietic SCs. SC-based therapies have emerged as a promising approach to counteract smoking-related damage. In particular, MSCs have been extensively studied for their immunomodulatory properties, demonstrating the ability to repair damaged tissues, reduce inflammation, and slow disease progression in conditions such as chronic obstructive pulmonary disease. Combination therapies, which integrate pharmaceuticals with SC treatments, have shown potential in enhancing regenerative outcomes. This review examines the impact of smoking on SC biology, describes the processes impairing SC-mediated repair mechanisms and highlights recent advancements in SC-based therapies in the treatment of smoking-induced diseases. This review has two prongs: (1) it attempts to explain potential smoking-related disease etiology, and (2) it addresses a gap in the literature on SC-mediated repair mechanisms in chronic smokers.This work was supported by a grant from the University of Balamand, Lebanon (RGA/FHS/2223/002) and from Qatar University (QU collaborative grant QUCG-BRC- 23/24–125) and from Stem Cell Reserve (Texas, USA)

Hybrid Deep Learning Model for Accurate Short-Term Electricity Price Forecasting

Accurate short-term electricity price forecasting (STEPF) is critical for efficient energy market operations, guiding investment strategies, resource allocation, and consumer behavior. This study introduces a hybrid deep learning approach specifically designed to improve STEPF accuracy by leveraging historical Hourly Ontario Energy Price (HOEP) data from 2017 to 2019. The model integrates advanced techniques, including data preprocessing and denoising through a Stacked Denoising Autoencoder (SDAE), along with enhanced temporal modeling via Bidirectional Long Short-Term Memory (BiLSTM) and Gated Recurrent Unit (GRU) networks. By capturing the complex dynamics inherent in electricity pricing data, the proposed hybrid model significantly enhances forecasting accuracy. Trained on data from 2017 and 2018, with 2019 used for testing, the model achieves a strong correlation coefficient (R = 99.86%) and substantially lowers forecasting errors. Comparative evaluations against established forecasting methods highlight the model's superior performance. This work demonstrates the practical value of deep learning techniques in the energy sector, particularly in responding to the volatility of demand and supply in real-time electricity markets

FINE-GRAINED TAINT TRACING IN CRYPTOCURRENCIES: A SUB-RANGE-BASED UTXO MODEL WITH VERKLE TREE PROOFS

Cryptocurrency taint analysis is critical for tracking illicit funds, but existing methods either over-taint legitimate coins or struggle with scalability. This thesis proposes a finegrained taint tracing model for UTXOs that treats each coin as a collection of indivisible sub-units (satoshis) with unique IDs. We design a sub-range-based UTXO model with the support of Verkle tree commitments to efficiently encode and prove ownership of these sub-units and to validate the correct computation. Our approach allows a user to spend arbitrary portions of a UTXO while providing succinct cryptographic proofs: a membership proof to showeach spent sub-unit existed in theUTXO, a delta proof to prove the UTXO's commitment updates correctly after removing spent parts, and a combined Vroot proof to verify multiple inputs merge consistently into newUTXO.We validate the model's correctness using Kate-Zaverucha-Goldberg (KZG) polynomial commitments ensuring that the sum of spent and remaining parts matches the original commitment with minimal verification overhead. In our design, no on-chain enumeration of sub-units is required , only short commitments and proofs. Key findings demonstrate that finegrained taint can be traced through complex transactions (including coin mixes) without false positives: taint remains tied to the exact units of illicit origin. This work bridges the gap between regulatory needs and technical feasibility by delivering a provably correct, efficient mechanism for tracking tainted cryptocurrency funds at a granular level