Abstract: Hybrid use of Terraform for infrastructure andAnsible for configuration is common on Azure, but the two toolsare often joined only by ad hoc scripts and fragile handoffs in CIpipelines. Runbook Mesh proposes a small MCP based controlplane that treats Terraform and Ansible as one coordinatedchange unit rather than two independent stages. Azure DevOpstriggers an MCP server that drives a deployment state machine:it receives Terraform plans and apply results, derives a dynamicAnsible inventory from Terraform outputs, and orchestratesconfiguration playbooks with drain, cordon, and health checksfor VM scale sets, AKS nodes, and virtual machines. TheMCP enforces simple invariants on ordering, handoff safety,and rollback reachability, and packages each deployment intoa witness bundle containing plan digests, state and inventoryhashes, play outcomes, and Azure Resource Graph snapshots.The result is an Azure native pattern where infrastructure andconfiguration share a single timeline, a defined rollback path, anda tamper evident change ledger suited to regulated environments.

Abstract: Background: Hematopoietic stem cell transplantation (HSCT) is a widely utilized subtype of transplantation employed in various malignant and non-malignant diseases, particularly when conventional treatments or therapeutics prove ineffective. Despite the frequent occurrence of post-transplantation lymphoproliferative disease (PTLD) in patients undergoing HSCT, no comprehensive global prevalence rate has been established to date. Methodology: In this study, we selected 39 studies from 941 studies from three databases (i.e., PubMed, ScienceDirect, and Google Scholar) to identify the global prevalence rate of PTLD in HSCT patients. Results: The pooled prevalence was determined as 5.6% (95% CI: 5.0 to 6.3) and increased to 12.4% (95% CI: 10.2 to 14.7) after excluding outlier studies. The quality of the studies was also high. The prevalence of death cases among HSCT patients was determined as 0.6% (95% CI: 0.4 to 0.9). PTLD was most prevalent in allogenic HSCT (i.e., 5.6% (95% CI: 4.9 to 6.3)) and within the European region (i.e., 27.1% (95% CI: 21.4 to 32.8)). Among risk factors, HLA mismatch was reported in most of the studies. Conclusion: This study assessed and discussed the overall global prevalence of PTLD in HSCT patients, continent-based prevalence, and risk factors that can be helpful in finding the possible prevention mechanism of PTLD and implementing individualized treatment approaches based on the treatment availability during HSCT.

Abstract: This study develops a leakage-safe PCA–APT framework that constructs an idiosyncratic market-stress index from cross-sectional residual dispersion and evaluates its usefulness for anticipating equity drawdowns. Using daily adjusted prices for SPY and 11 U.S. sector ETFs from 2020–2025, we compute sector excess returns (sector minus SPY), estimate a low-dimensional common component via principal component analysis (PCA), and define residual stress as the cross-sectional root-mean-square magnitude of PCA reconstruction residuals. To prevent look-ahead bias, the PCA mapping is estimated using information available only through t−1, stress is computed out-of-sample at t, and stress regimes are identified using a rolling train-only quantile threshold that is shifted forward by one trading day. Drawdown-warning performance is assessed using drawdown-onset events and early-warning classification metrics (ROC-AUC, PR-AUC, and horizon-H precision/recall). Empirically, residual stress spikes cluster around drawdown onsets and provides predictive information, although a volatility-based benchmark remains stronger on average across discrimination metrics. Importantly, residual stress exhibits state-dependent complementarity with volatility: conditional on low volatility, high residual stress is associated with a materially higher probability of a drawdown onset within the next H=21 trading days (approximately 17% vs. 8%), and the joint high-stress/high-volatility regime identifies the highest-risk states (approximately 36% onset probability). Event-level overlap diagnostics further indicate that residual stress can flag a subset of drawdown onsets not captured by a volatility-threshold rule, while some onsets are not preceded by either signal. Economic relevance is examined under transaction costs through (i) a residual-ranked sector long–short portfolio and (ii) stress-managed SPY overlays that reduce exposure during detected regimes. In the baseline sample, a volatility-managed overlay improves drawdown control relative to buy-and-hold, whereas the residual-stress overlay does not reduce maximum drawdown and the residual-ranked long–short strategy is not robustly profitable after costs. Overall, the paper contributes a reproducible, leakage-safe evaluation pipeline linking cross-sectional residual dispersion to drawdown risk and clarifies when residual stress serves as a complementary market-structure risk indicator alongside standard volatility-based signals.

Abstract: The treatment of chronic lymphocytic leukemia (CLL) has significantly shifted from chemoimmunotherapy to targeted therapies like Bruton’s tyrosine kinase and BCL2 inhibitors. Despite these advancements, CLL remains an incurable disease characterized by immune dysregulation, therapeutic resistance, and cumulative toxicities. To overcome these challenges, novel immunotherapeutic strategies are emerging as fundamentally different approaches that target the immune-tumor interactions. These innovations include novel monoclonal antibodies, bispecific antibodies that redirect T-cell cytotoxicity, chimeric antigen receptor (CAR)-T cell therapies, and natural killer (NK) cell-based platforms. By actively engaging cellular cytotoxicity, these approaches show promise in high-risk and treatment-resistant scenarios where standard pathway inhibition is inadequate. Establishing the optimal use, toxicity management, and combination strategies of these cellularly engaged immunotherapies is now a critical priority in contemporary CLL research.

Abstract: The article explores the question how the new developments in the EU copyright law influence the Slovenian legislation. Presently, the Slovenian system of collective management of copyright and related rights is under scrutiny of European Commission, which recently opened infringement proceedings for failing to correctly apply the InfoSoc Directive and Collective Right Management Directive. The future Streamz decision of the Court of Justice of European Union, initiated by the Belgian Constitutional Court, could also significantly influence the Slovenian copyright rules, since the Slovenian legislator implemented the Digital Single Market Directive by similar means as Belgian legislator. One of the pressing issues in Slovenian copyright law, which was recently considered by the Higher Court of Ljubljana, is also the collection, management, and distribution of private copying levy as one of the permittable exceptions and limitations of exclusive authors rights under InfoSoc Directive. The thorough analysis of these pressing issues reveals complex intertwining of the EU and national law regarding collective management of exclusive author’s rights and of various remuneration rights. The article, focusing on legal-dogmatic approach and the analysis of legal sources using grammatical, purposeful, systematical and comparative legal methods, offers overview of Slovenia's system of copyright protection, draws attention to its possible incompatibilities with EU law, and provides possible legislative solutions.

Abstract: This paper examines the relationship between decentralisation, human resource development (HRD), and operational efficiency in water utilities managed by state and local governments across Madhya Pradesh, Chhattisgarh, and Jharkhand, India. Drawing on a random sample of 200 towns and villages, the study quantifies how decentralisation influences HRD investment and how both variables jointly shape service delivery outcomes. The findings challenge the widely held assumption — promoted by international donors and development institutions — that devolving authority to lower tiers of government inherently improves public service performance. Results indicate that decentralisation, as practised in India's drinking water sector, does not enhance operational efficiency. Instead, vocational training — the primary measure of HRD employed here — emerges as the principal driver of improved performance. Since decentralisation is negatively correlated with HRD investment, transferring authority without commensurate workforce development commitments risks compounding existing inefficiencies rather than resolving them.

Abstract: Artificial intelligence (AI) is significantly changing the landscape of banking and financial markets, improving predictive precision, operational productivity, and decision-making speed. However, underlying these improvements is an underexplored structural vulnerability: the risk of systemic AI convergence. As financial institutions become more dependent on similar foundational models, cloud infrastructure, data suppliers, and AI middleware platforms, diverse firms may begin to interpret and respond to market signals in similar ways. This paper presents the notion of model monoculture risk—a systemic fragility that arises when model similarities, market synchronisation, and infrastructure concentration align. Rather than focusing solely on traditional firm-level model risk management, this paper introduces the M³ Framework (Model–Market–Middleware) to clarify how shared AI architectures can transform localised optimisations into widespread amplification. The Model layer encapsulates the convergence of foundational architectures and training interdependencies; the Market layer reflects synchronised adjustments in portfolios, credit, and liquidity; and the Middleware layer emphasises the concentration of cloud services and vendors that quickens the spread. Collectively, these layers create multiplied exposure to correlated failures. To put this concept into practice, the paper proposes a qualitative Model Monoculture Risk Index (MMRI) to evaluate cross-layer alignment and the erosion of diversity within AI-driven financial systems. By redefining AI governance as a challenge of structural diversification rather than just a validation task, this contribution highlights cognitive diversity as an essential element of financial stability in the era of AI.

Abstract: The rapid proliferation of healthcare data from electronic health records (EHRs), medical imaging systems, laboratory devices, and IoT-enabled patient monitoring devices has created unprecedented challenges for healthcare data management. Traditional Extract, Transform, Load (ETL) tools have long been employed to collect, integrate, and load data into centralized repositories such as data warehouses and data lakes. However, conventional ETL processes are often limited by rigid rule-based transformations, inefficiencies in handling unstructured or semi-structured data, and lack of automation in data quality assurance. This study investigates the integration of Artificial Intelligence (AI) techniques into ETL pipelines to enhance healthcare data management. AI methods—including machine learning, deep learning, and natural language processing (NLP) are incorporated to automate anomaly detection, optimize transformation rules, and extract insights from unstructured clinical text. A conceptual framework is proposed for an AI-augmented ETL system that ingests heterogeneous healthcare data, applies intelligent transformations, and loads high-quality, enriched datasets into a secure data warehouse. The system architecture enables real-time and batch processing, anomaly detection, and adaptive learning to improve ETL efficiency over time. Evaluation metrics include data quality improvement, processing speed, anomaly detection accuracy, and scalability. The findings demonstrate that AI-enhanced ETL significantly reduces data errors, accelerates processing, and provides enriched datasets suitable for downstream analytics, predictive modeling, and decision-making in healthcare operations. By integrating AI into ETL workflows, healthcare organizations can achieve more reliable, timely, and actionable data management, supporting clinical decision-making, operational efficiency, and regulatory compliance. This study contributes to the literature on intelligent data engineering in healthcare, presenting a scalable framework for future research and practical implementation in complex healthcare IT ecosystems.

Abstract: In blockchain ecosystems, maintaining transparency and privacy has become an ethical dilemma. This is because, while certain specific information of the user is shared to ensure transparency of transactions across networks, such information could be detrimental to the user, as there is a possibility of it being tampered with. For instance, in the Catalyst voting process in Cardano, users can still see the amount of ADA tokens being held by other users, which can influence their voting options, especially when large ADA holders vote in support of certain ideas or proposals. To discourage such challenges as voter manipulation and vote buying, this study proposed the implementation of zero-knowledge proof (ZKP) in blockchain ecosystems to enhance the transparency of the catalyst voting process and enhance efficiency and speed of result release. Using survey questionnaire and a multivocal literature review, this study was able to proof that ZKP cannot only be applied in the catalyst voting process to enhance its transparency, but also addressed potential challenges to its applications such as scalability, encourage trust and fairness of the voting system, and improve voter participation due to its user-friendliness. Mathematical models emphasize scaled voting as optimal for balancing inclusion and plutocratic control.

Abstract: High gain and low sidelobe level remain challenges for 5G millimeter-wave antenna systems. This paper presents a low-sidelobe, high-gain microstrip array antenna based on non-uniformly slotted identical-sized radiating patch, designed to simultaneously enhance gain and suppress sidelobe levels for 5G millimeter-wave (mmWave) communication systems. The key innovation lies in the use of an intermediate-deep, edge-shallow non-uniform slotting technique to precisely control the surface current distribution of the radiating elements. thereby achieving significant sidelobe level (SLL) suppression and antenna isolation enhancement without increasing the physical footprint of each element. The final design operates at a center frequency of 78.5 GHz, achieving a maximum gain of 15 dB and suppressing the first sidelobe below −20 dB, outperforming conventional linear arrays. Notably, the patch width is reduced to only 1 mm—compared to Chebyshev-distributed arrays—resulting in a compact array layout with over 40% unit width size reduction while simultaneously improving inter-element isolation by more than 18 dB. This current-distribution engineering approach offers a novel, structure-efficient pathway for designing high-performance, densely packed mmWave antenna arrays, circumventing the need for additional decoupling structures or enlarg the antenna spacing，simulation results show that the average isolation has increased by more than 5 dB from 76 GHz to 79 GHz.

Abstract: Background: Whooping cough (pertussis), caused by Bordetella pertussis, remains a major public health concern worldwide despite high vaccination coverage. Resurgent outbreaks underscore the need for continued epidemiological and immunological monitoring to evaluate population immunity. To assess the humoral immune protection in children aged 1–14 years vaccinated with DTP/Hib/HB between January and December 2022 in Duque de Caxias, Rio de Janeiro, Brazil. Methods: A total of 220 serum samples were analyzed using commercial ELISA kits to detect circulating IgG antibodies against pertussis toxin (PTx) and B. pertussis antigens. Antibody levels were compared across age groups using the Kruskal–Wallis test followed by Dunn’s multiple comparisons. Results: Anti-PTx antibody levels were low across all age groups, with only 2.17% of children showing seropositive levels (>40 IU/mL). Broader reactivity to B. pertussis antigens (PTx + FHA) was detected in 36.7% of samples, but antibody titers declined significantly with increasing age (p < 0.05). These findings indicate waning vaccine-induced immunity and potential susceptibility to reinfection. Conclusions: The study reveals low levels of circulating IgG antibodies against pertussis among vaccinated children, emphasizing the need to reassess the current immunization schedule. Introduction of adolescent booster doses and expanded access to acellular pertussis vaccines are recommended to enhance long-term protection.

Abstract: Cardiovascular diseases remain the leading cause of mortality worldwide despite significant advances in diagnostic and therapeutic technologies. A substantial body of evidence indicates that myocardial metabolic remodeling and bioenergetic impairment develop long before the onset of overt cardiovascular disease. Conventional electrocardiography, although widely accessible and inexpensive, is traditionally limited to identifying manifest electrical abnormalities and lacks sensitivity for detecting early metabolic stress. Recent advances in artificial intelligence, particularly deep learning models trained on raw electrocardiographic waveforms, have demonstrated the ability to extract latent physiological information embedded within cardiac electrical signals.This study proposes a comprehensive framework for AI-powered electrocardiography aimed at detecting hidden myocardial metabolic stress prior to clinically apparent cardiovascular disease. By integrating multimodal cardiometabolic biomarkers with high-dimensional ECG analysis, this approach seeks to identify early electrophysiological signatures of energetic dysfunction.

Abstract: Glucose and ascorbate transport and their opposite effects on the physiological processes, explain the pathophysiology of the Ebola virus. The virus impairs intracellularly the interferon (IFN) signalling. The present article will focus on the viral factors (VP24, VP35, VP40 proteins, nucleoprotein NP) that operate in the inner of the cell, subsequently to the viral entry. The haemorrhagic fever syndrome could be understood as a state of oxidative stress, driven by hyperglycaemia and the activation of NF-kB pathway and inflammatory cytokines. High glucose levels in plasma contributes to oxidative stress. It has also an inhibitory effect on Interferon (IFN) signalling. Conversely, ascorbate can counteract the IFN blocking exerted by the virus and interfere virus budding. A treatment strategy would focus on the administration of ascorbate and glutathione, glucose or insulin at convenience, in order to maintain constant and normal levels of glucose in plasma, to combat the oxidative and inflammatory stress.

Abstract: Excess sodium intake is a growing public health concern in Malaysia. Reformulation using potassium chloride (KCl) and monosodium glutamate (MSG) offers a potential strategy to reduce sodium while maintaining palatability, although consumer responses to these ingredients remain mixed. This study examined young adults’ preferences for sodium-reduced canned soup and evaluated how flavour, sodium information, price, and additive-related cues influence stated choice, alongside sensory evaluation of sodium-reduced formulations. A cross-sectional mixed-method study was conducted among 211 Malaysian young adults. Participants completed a choice-based conjoint (CBC) experiment comprising six hypothetical purchase tasks that varied across seven product attributes. Multinomial logit models estimated part worth utilities and attribute importance. Sensory evaluation was conducted in a controlled environment using the generalised Labelled Magnitude Scale (gLMS) and Labelled Affective Magnitude (LAM) scale to assess saltiness intensity and pleasantness across soup formulations. Sodium-related attributes accounted for approximately 36% of stated decision weight, with sodium reduction percentage and flavour emerging as the strongest drivers of stated choice. Moderately sodium-reduced formulations incorporating KCl and MSG achieved favourable sensory ratings. Young adults’ acceptance of sodium-reduced soup is shaped primarily by flavour, sodium cues, and affordability. Sensory findings support the feasibility of sodium reduction using KCl and MSG without compromising palatability.

Abstract: Background. Small and medium enterprises (SMEs) dominate East African commerce yet incur persistent time, cost, and liquidity frictions when settling cross-border transactions. Digital payment technologies promise to ease these constraints, but rigorous evidence connecting adoption to measurable trade-process efficiency is sparse. Purpose. This study evaluates whether, and under what institutional conditions, SME digital-payment adoption improves cross-border trade efficiency in Kenya, Uganda, Rwanda, and Tanzania. Methods. A harmonised dataset pools 2023–2025 World Bank Enterprise Surveys microdata with country-level indicators of payment-system interoperability and Trade Facilitation Agreement (TFA) progress. Adoption is captured through the shares of sales and purchases conducted electronically, while efficiency is proxied by customs-clearance days, compliance costs, and perceived predictability. Ordinary least squares models with survey-design inference estimate adoption–efficiency associations; interaction terms test moderation by interoperability and regulatory alignment. Results. Controlling for firm and country heterogeneity, electronic-payment adoption is associated with 1.5 fewer customs-clearance days (p = 0.019), a 2.1-percentage-point fall in compliance costs (p = 0.006), and a significant decline in perceived unpredictability (p = 0.009). Marginal-effects analysis shows that these gains intensify where remittance-corridor costs are low and TFA implementation exceeds 70 percent, underscoring the complementary roles of systemic interoperability and regulatory alignment. Conclusions. Digital-payment adoption yields tangible efficiency dividends for trading SMEs, but only when embedded in supportive payment and trade-governance ecosystems. Policymakers should therefore pair interoperability and regulatory reforms with targeted SME onboarding to translate Africa’s extensive mobile-money infrastructure into sustained trade competitiveness.

Abstract: Background: Intestinal acute radiation syndrome (IARS) represents a life-threatening component of acute radiation syndrome with limited effective countermeasures. Under-standing molecular determinants governing intestinal epithelial resilience to ionizing ra-diation is critical for developing radiation toxicity mitigation strategies. Objectives: This study investigates the role of PIKfyve, a phosphoinositide kinase essential for endolysosomal homeostasis, in modulating radiation-induced intestinal toxicity. Methods: We utilized an inducible intestinal epithelial-specific PIKfyve-knockout mouse model (PIKfyve cKO) subjected to 10 Gy abdominal irradiation. Intestinal toxicity was as-sessed through histopathology, barrier permeability (FD4 assay), apoptosis markers, and transcriptomic profiling. Small intestinal organoids were employed for mechanistic vali-dation. Results: PIKfyve deletion alone did not perturb normal gut architecture but precipitated severe post-irradiation toxicity, including villous atrophy, crypt hypoplasia, and massive crypt-cell apoptosis. Barrier dysfunction was evidenced by elevated serum FD4 and heightened systemic pro-inflammatory cytokines, culminating in markedly increased mortality. Transcriptomic analysis revealed potentiated DNA-damage signaling and am-plified inflammatory cascades in PIKfyve-deficient intestines. Conclusions: These findings identify PIKfyve as a critical guardian of intestinal epithelial integrity against radiation toxicity. Given emerging PIKfyve inhibitors in cancer therapy, our results raise important safety considerations for clinical radiotherapy and position PIKfyve as a potential target for radiation toxicity mitigation.

Abstract: Background: Response to neoadjuvant therapy in locally advanced rectal cancer (LARC) is heterogeneous and early identification of non-responders may help optimize treatment strategies and reduce unnecessary toxicity. This study aimed to develop and internally validate a machine learning model based on radiomic features extracted from baseline magnetic resonance imaging (MRI) to predict treatment response assessed at restaging MRI. Methods: In this retrospective single-center study 86 patients with histologically confirmed LARC who underwent baseline and restaging MRI, neoadjuvant therapy, and surgery, were included. Primary tumors were manually segmented on oblique axial T2-weighted images. A total of 107 radiomic features were extracted using PyRadiomics, with and without N4 bias field correction. Feature selection was performed using LASSO, followed by elasticnet–regularized logistic regression. Model performance was assessed using repeated stratified 5-fold cross-validation. Response was defined according to MRI tumor regression grade (mrTRG) at restaging, dichotomized into responders (mrTRG ≤ 2) and non-responders (mrTRG ≥ 3). Results: The model achieved a mean area under the receiver operating characteristic curve (AUC-ROC) of 0.73, accuracy of 72.5%, sensitivity of 79.2%, and specificity of 50%. Conclusions: Baseline MRI-based radiomics demonstrated to potentially identify patients at higher risk of non-response to neoadjuvant therapy in LARC.

Abstract: Post-endometrial ablation persistent uterine bleeding indicates that no method of endometrial ablation (EA) eliminates the entire endometrium and hysteroscopy shows distorted and scarred uterine cavity in the majority of women. These observations raise concerns regarding presentation, assessment and stage of potential post-ablation endometrial cancer (PAEC) developing in residual endometrium. To address these concerns, we conducted a systematic search for reports of endometrial cancer (EC) associated with or after EA using multiple data bases imputing keywords of EC after EA and possible combinations of first- and second-generation EA techniques associated with EC from its inception in the 1980s through 2025. After excluding irrelevant publications, we identified 86 ECs associated with EA described in 20 case reports (N=20), four case series (N=18), eleven cohort studies (N=21), one registry (N=27) and five reviews. Based on 12 relevant studies, at follow up of 1.9-25 years, 43 ECs were identified in 39,795 women with a history of EA; summary incidence of 0.11% (range 0.0 - 1.59%). Based on the remaining 43 evaluable cases of PAEC, the mode and time to presentation, investigation, diagnosis, and stage of PAEC were not altered by EA. We conclude that EA has a protective effect reducing the risk EC significantly, likely due to quantitative reduction in endometrium that can potentially become malignant and the EA process eliminating occult pre- or malignant endometrial tissues which are vulnerable to ablation techniques. The mode and time to presentation, the diagnostic work-up, including endometrial biopsy and hysteroscopy, and stage of PAEC are not altered by EA.

Abstract: The use of Traditional Chinese Medicine (TCM) is expanding worldwide. In the UK, TCM has developed rapidly since the 1990s, but limited scientific evidence supports its safety, quality, or efficacy. This creates challenges for regulatory governance and public health protection.Objective:To review the development of TCM regulations in the UK and examine how existing regulations address safety, quality, and efficacy through different regulatory instruments, objectives, targets, and enforcement mechanisms. A narrative literature review was conducted, which is supplemented by grey literature searches of government reports and legislative documents published between 1970 and 2020. Thematic and chronological analyses were applied to map regulatory transitions and classify instruments and objectives. Ten key regulations and policy documents were identified, forming a hierarchical and fragmented framework dominated by product-focused oversight. While the system ensures basic safety and quality standards, it lacks consistent mechanisms for enforcement, practitioner regulation, and efficacy assessment. UK-TCM regulation has evolved through a mix of EU and domestic legislation, but gaps in enforcement and practitioner oversight persist. Policymakers should develop proportionate efficacy evaluation methods, enhance enforcement, and establish clearer practitioner standards to ensure safe, evidence-informed practice in post-Brexit UK health policy.

Abstract: Contemporary enterprise IT operations are implemented largely atop Shannon–Turing computing: programs execute read–compute–write cycles over data structures, while governance (fault handling, configuration control, auditability, and continuity) is applied externally through infrastructure platforms, observability stacks, and human processes. This separation scales analytic throughput but accumulates coherence debt: locally expedient commitments whose provenance and revisability degrade until exposed by shocks (failures, security incidents, regulatory demands, or architectural transitions). We synthesize a model evolution that integrates computation with regulation at two distinct levels: (i) Distributed Intelligent Managed Elements (DIME), which modifies the Turing cycle to read–check-with-oracle–compute–write by infusing a signaling overlay and FCAPS (Fault, Configuration, Accountability, Performance, Security) supervision into computation in progress; and (ii) AMOS, which fully decouples the process executor from governance by treating any Turing-equivalent engine as a replaceable execution substrate while elevating knowledge structures—encoded as local and global Digital Genomes—to first-class operational state in a governed Knowledge Network. We further present implementation evidence via a microservice transaction testbed that operationalizes dynamic topology as data, a capability-oriented control plane, decoupled application-layer FCAPS from IaaS/PaaS FCAPS, and policy-selectable consistency/availability semantics. We argue that the principal benefit of AMOS is not “circumventing” impossibility results such as CAP, but governing their trade-offs as explicit commitments with auditable lineage and controlled convergence back to coherent state.