Abstract: Insulin resistance (IR) is a hallmark of type 2 diabetes, characterized by disrupted metabolic regulation, oxidative stress, and altered cell signaling. This study employed Data-Independent Acquisition (DIA) quantitative proteomics to profile the proteomic landscape in a cellular model of insulin resistance (MOD) and to evaluate the therapeutic effects of camel milk derived peptide TYYPPQ. Principal Component Analysis (PCA) confirmed distinct proteomic profiles between healthy control (C), MOD, and P2-treated cells, indicating that TYYPPQ induced a partial but significant reprogramming of the insulin-resistant proteome. Enrichment analyses (GO and KEGG) revealed that insulin resistance was characterized by widespread dysregulation, including increased endoplasmic reticulum (ER) stress, oxidative stress, inflammatory pathways, and disruptions in sphingolipid and fructose metabolism. In contrast, TYYPPQ treatment promoted a recovery signature, significantly enriching pathways related to improved insulin signaling (PI3K-Akt, AMPK), regulation of lipolysis, amino acid metabolism, actin cytoskeleton organization, and a marked reduction in ER stress markers. Crucially, these pathway predictions were validated at the molecular level, as qPCR and Western blot analysis confirmed that TYYPPQ effectively restored the expression and phosphorylation of AMPK. Further domain and subcellular localization analyses indicated that insulin resistance disrupted mitochondrial, redox, and protein homeostasis, while P2 treatment counteracted these effects by modulating domains related to mitochondrial function (proline dehydrogenase, cytochrome c oxidase) and restoring protein distribution, notably reducing ER-localized proteins. Collectively, these multi-faceted proteomic findings demonstrate that the peptide TYYPPQ mitigates insulin resistance by coordinately restoring key metabolic and signaling pathways, reducing cellular stress, and improving mitochondrial and cytoskeletal function, highlighting its potential as a therapeutic agent.

Abstract: Human non-polio enteroviruses (NPEV) cause a plethora of infections in humans, ranging from mild to severe neurological diseases including aseptic meningitis. NPEV are the leading cause of aseptic meningitis in both children and adults worldwide. In Russia, reports of NPEV infections have surged, especially in the post-COVID era starting in 2022, with elevated infection rates into 2023. A comprehensive examination of the complete genome is crucial for understanding the evolution of NPEV genes and for predicting potential outbreaks. The study focused on to identify the circulating NPEV strains in the Ural Federal District and Western Siberia, using Sanger sequencing and next-generation sequencing (NGS) methodologies. Biological samples were collected from (n = 225) patients diagnosed with aseptic. Bioinformatics analysis targeted the nucleotide sequences of the VP1 gene fragment, and the assembly of complete NPEV genomes. 159 NPEV were characterized, representing 70.7% of the collected samples. The main capsid variants forming the predominant genotypic profile included E30 (n = 39, 24.3%), E6 (n = 31, 19.3%), and CVA9 (n = 25, 15.6%). Using NGS sequencing, we successfully assembled 13 complete genomes for E6, E30, EV-B80, CVA9, CVB5, E11 and EV-A71. This molecular-genetic analysis provides contemporary insights into the genotypic composition, circulation patterns, and evolutionary dynamics of the dominant NPEV associated with aseptic meningitis in the Ural Federal District and Western Siberia. The laboratory-based monitoring and epidemiological surveillance for genetic changes and evolutionary studies are important for improving prevention and healthcare.

Abstract: Geopolymer mortars were produced from recycled concrete powder (RCP) and recycled brick powder (RBP) at a 30/70 wt% ratio, activated with a hybrid alkaline solution (NaOH/Na₂SiO₃/KOH) and reinforced with sisal (Agave) fibers at 0–2 wt%. Mechanical performance (compression and flexural) and microstructure–phase evolution were as-sessed by XRD, FTIR, and SEM-EDS after low-temperature curing. Sisal addition de-livered a strength–toughness balance, with an intermediate dosage (~1–1.5 wt%) providing the best overall performance; higher dosages induced packing loss and fiber clustering. Microstructural evidence indicates the coexistence and co-crosslinking of N-A-S-H and C-(A)-S-H gels promoted by the RCP, which densifies the matrix and enhances fiber–matrix anchorage. Fractographic features support a crack-bridging/pull-out mechanism responsible for the improvement without penaliz-ing early-age strength. The study identifies a practical advantage of sisal reinforcement in RCP/RBP geopolymer mortars and links it to gel chemistry and interfacial phenom-ena, providing a reproducible pathway toward fiber-reinforced, low-embodied-carbon geopolymers derived from construction and demolition waste and suitable for durable construction applications.

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In this study, in particular. I analyse social protection in some poor Countries. The Study shows how some Countries have for example more inefficiency that are promoted from Fiscal Policy in general and from many weaknesses of institutions, politics and government. In general the government actions normally yours fail Contributed to accelerate the Stagnation and make high fail of social system, the Poverty in these Countries have your source from these inefficiency that not converge to development and not converge to Created the Wealth. In some Countries, the Wealth generated not are satisfied to make good contributions in majors societies, these evidences are relatively about the missing the high Transformation, first, second because not exist some important purpose that normally guarantee high and good Wealth Share for many vulnerable People. The Stagnation, os the main reason that the government are responsable, it's that relatively about missing the good and high discipline that are responsible for good and important ways that normally can give to this good Budgetary Policy. The approach shows that, Countries can have high levels of social Protection, when these Countries establish good ways that your's government spend Public money generated from Fiscal Policy, that need be more relevance and more efficiency, that Will be enough efficiency and convergence to accelerate social development in general.

Abstract:

We derive an operationally defined lower bound on the physical time \( \Delta t \)required to execute any information-processing task, based on the total entropy produced \( \Delta\Sigma \). The central result, \( \Delta t \geq \tau_{\Sigma} \Delta\Sigma \), introduces the Process-Dependent Dissipation Timescale \( \tau_{\Sigma} \equiv 1/\langle \dot{\Sigma} \rangle_{\text{max}} \), which quantifies the maximum achievable entropy production rate for a given physical platform. We derive \( \tau_{\Sigma} \) from microscopic system-bath models and validate our framework against experimental data from superconducting qubit platforms. Crucially, we obtain a Measurement Entropic Time Bound:\( \Delta t_{\text{meas}} \geq \tau_{\Sigma} k_{\text{B}}[H(P) - S(\rho)] \), relating measurement time to information gained. Comparison with IBM and Google quantum processors shows agreement within experimental uncertainties. This framework provides a thermodynamic interpretation of quantum advantage as reduced entropy production per logical inference and suggests concrete optimization strategies for quantum hardware design.

Abstract: This study analyzes the evolution and spatial distribution of cervical cancer mortality. Furthermore, it develops a dynamic simulation model for estimating the evolution of the disease up to 2040. This manuscript details an ecological and retrospective study that an-alyzed official mortality, morbidity, and population data from the 58 municipalities that constitute the state of San Luis Potosi. We used Moran's index, linear correlation, structur-al equation modeling, Excel predictions, and Vensim simulation software to conduct this study. The evolution of deaths from cervical cancer shows a downward trend; mortality follows a clustered distribution pattern, and it is not random. The struc-tural model showed a correlation coefficient of 0.68 between syphilis cases and cervical cancer cases, with a coefficient of 0.35 for deaths. Candidiasis correlated with cervical cancer at a coeffi-cient of 0.25 and with deaths from the same disease at a coefficient of 0.46. The coefficients of determination for cervical cancer cases and deaths were 0.74 and 0.91, respectively. This shows that these co-infections—syphilis and candidiasis—are a risk factor for cervi-cal cancer mortality. The estimated mortality rates per 100,000 inhab-itants for 2025, 2030, 2035, and 2040 were 5.5, 5.1, 4.8, and 4.4, respectively. The prediction indicates an in-crease in the number of CC cases and deaths from this cause.

Abstract: 3,4-Methylenedioxyamphetamine (MDMA) has been shown in multiple clinical trials to greatly reduce Post-Traumatic Stress Disorder (PTSD) symptoms, with many patients experiencing lasting improvement. However, recent regulatory rejection based on problems with blinding highlights a contradiction, with regulatory agencies demanding placebo-controlled trials, yet the strong psychoactive effects of MDMA-assisted therapy (MDMA-AT) make true blinding impossible. This paper moves the focus from bureaucracy to science. First, it introduces the Trauma-Affective Memory Loop (TAML), a simple model of how traumatic memories are stored, reactivated, and reinforced through key brain regions. Second, it explains how MDMA works on a neurofunctional level, by reducing fear signals it creates a temporary “therapeutic window”. In this state, patients can revisit trauma safely, without being overwhelmed, and reprocess the memory in a healthier way. Third, the paper proposes that different types of trauma exposures respond differently to MDMA-AT. Acute, one-time traumas may often be resolved within one to three MDMA sessions, while complex or developmental trauma, formed over years, may need repeated and carefully structured treatment. Finally, a new clinical trial design, the Brinzei MDMA-PTSD Protocol (BMPP), is presented, a role-separated, quadruple-masked approach that limits bias and expectation effects while still allowing therapists to deliver effective care. The aim is to move beyond debates about flawed blinding methods and instead design trials that clarify why MDMA works, for whom it works best, and how to deliver it safely and effectively.

Abstract: This work synthesizes a complete paradigm developed across multiple interconnected publications, and we propose a paradigm where space itself is the fundamental, elastic medium. This framework rehabilitates an absolute reference frame while fully preserving the mathematical formalism of Special Relativity as an effective observational theory. The model replaces the postulate of a featureless vacuum with three physical principles: space elasticity, wave-matter identity, and energy-conserving In/Out wave circulation. From these we derive a self-consistent field theory where particles emerge as localized standing waves and photons as self-propelled dipoles. The paradigm provides mechanistic explanations for core principles: velocity and kinetic energy are geometric deformation states of matter waves, and the equivalence of inertial and gravitational mass follows from their common origin in total deformation energy. Crucially, it yields testable predictions that distinguish it from standard physics, including an asymmetric outcome for the symmetric Twin Paradox scenario and measurable asymmetries in high-energy ion collisions. This work offers a realist, wave-based foundation for reconciling quantum non-locality, relativistic effects, and gravitational interaction.

Abstract:

Climate change poses increasing risks to global food security, with maize production in vulnerable regions such as Nakuru County, Kenya, and Northwest China expected to be significantly affected. This study assessed the impacts of future climate conditions on maize growth and yield in the 2030s (2021–2040) and 2050s (2041–2060) under RCP 4.5 and RCP 8.5, relative to a 1986–2005 baseline. The CERES-Maize model was used to simulate the effects of projected changes in temperature, precipitation, and solar radiation, and to evaluate the effectiveness of key adaptation strategies. Results showed that climate change is likely to shorten maize growing durations by up to 34 days in Nakuru County and 38 days in Northwest China, leading to yield reductions of 2.7–26.5% and 4.6–22.4%, respectively, with stronger impacts in the 2050s and under RCP 8.5. Simulations further demonstrated that adaptation measures—including adjusting planting dates, applying appropriate irrigation, and adopting improved cultivars—could increase maize yields by 20.7–38.6% in Nakuru and 17.6–28.6% in Northwest China, depending on the scenario. These findings indicate that integrating multiple adaptation strategies can substantially reduce climate-induced yield losses, emphasizing the need for investment in irrigation infrastructure, climate services, and cultivar improvement to safeguard future maize production.

Abstract: Despite substantial growth in eco-innovation (EI) research, most studies rely on cross-sectional data, limiting understanding of the temporal dynamics of EI and its determinants under varying macroeconomic conditions. This study addresses this gap by analysing panel data from Spanish manufacturing firms across three phases of the business cycle: pre-crisis expansion (2004–2007), the global financial crisis (2008–2013), and recovery (2014–2016). We investigate the drivers of two distinct types of eco-innovation: efficiency EI (energy and material savings) and environmental EI (reducing environmental harm), focusing on the role of regulation, institutional interventions, and firm-level innovation capacities. Using a random-effects panel probit model that accounts for unobserved firm heterogeneity, we examine how these drivers operate across different macroeconomic contexts. Our findings reveal that regulation consistently fosters EI, while the influence of subsidies, R&D capacity, and collaborative networks is more context-dependent, particularly during economic downturns. The results highlight the cumulative, path-dependent, and cyclical nature of eco-innovation, providing novel insights into the conditions that enable firms to sustain green innovation over time.

Abstract: We propose a geometrically motivated framework in which the large-scale evolution of the Universe is described by a coherent multidimensional wavefunction possessing a preferred direction of propagation. Within this formulation, the scalar envelope of the wavefunction defines a critical hypersurface whose temporal evolution provides an effective geometric description of cosmic expansion. The resulting picture naturally incorporates an arrow of time, large-scale homogeneity, and a nonsingular expansion history, without invoking an inflationary phase, a cosmological constant, or an initial singularity. The critical hypersurface takes the form of a three-dimensional sphere whose radius plays the role of a cosmological scale factor. Its evolution leads to a time-dependent expansion rate with a positive but gradually decreasing acceleration. The associated density evolution follows a well-defined scaling law that is consistent with the standard stress–energy continuity equation and corresponds to an effective equation-of-state parameter w = -1/3. As a consequence, the total mass–energy contained within the expanding hypersurface increases with time in a manner that remains fully compatible with the continuity relation. Analytical estimates derived from the model yield values for the present expansion rate and mean density that are in close agreement with current observational constraints. Within this geometric interpretation, the gravitational constant emerges as an invariant global potential associated with the critical hypersurface, linking the conserved properties of the wavefunction to observable gravitational coupling. The framework therefore provides a self-consistent, effective description in which cosmic expansion and gravitational dynamics arise from the geometry of a universal wavefunction, suggesting a deep connection between quantum structure, spacetime geometry, and cosmological evolution.

Abstract: Astronaut training has undergone significant transformation since the early days of human spaceflight, evolving in response to technological advances, changing mission objectives, and the increasing complexity of international cooperation. This paper provides a historical overview of astronaut training, tracing its development from the early Space Race era to the present day. It examines how initial training programs, largely focused on military pilots and short-duration missions, have expanded to encompass a broader range of skills, disciplines, and professional backgrounds. The paper compares astronaut training approaches across six major spacefaring entities: NASA (United States), Roscosmos (Russia), ESA (Europe), CNSA (China), JAXA (Japan), and CSA (Canada), highlighting both commonalities and differences shaped by national priorities, organizational culture, and mission requirements. In addition, the paper discusses the emergence of commercial human spaceflight and its impact on training philosophies, regulatory frameworks, and safety considerations. By outlining historical trends and current practices, this paper provides a comprehensive overview of astronaut training in the new era of spaceflight and identifies key factors influencing its continued evolution.

Abstract: This work presents a time-domain analog-to-digital conversion method in which the amplitude of a sensor signal is encoded through its crossing instants with a periodic ramp. The proposed architecture departs from conventional ADC and PWM demodulation approaches by shifting quantization entirely to the time domain, enabling waveform reconstruction using only a ramp generator, an analog comparator, and a timer capture module. A theoretical framework is developed to formalize the voltage-to-time mapping, derive expressions for resolution and error, and identify conditions that ensure monotonicity and single-crossing behavior. Simulation results demonstrate high-fidelity reconstruction for both periodic and non-periodic signals, including real photoplethysmographic (PPG) waveforms, with errors approaching the theoretical quantization limit. A hardware implementation on a PSoC 5LP microcontroller confirms the practicality of the method under realistic operating conditions. Despite ramp nonlinearity, comparator delay, and sensor noise, the system achieves effective resolutions above 12 bits using only native mixed-signal peripherals and no conventional ADC. These results show that accurate waveform reconstruction can be obtained from purely temporal information, positioning time-encoded sensing as a viable alternative to traditional amplitude-based conversion. The minimal analog front end, low power consumption, and scalability of timer-based processing highlight the potential of the proposed approach for embedded instrumentation, distributed sensor nodes, and biomedical monitoring applications.

Abstract:

Multi-component polymer hydrogels present complex physiochemical interactions that make accurate compositional analysis challenging. This study evaluates three analytical techniques: Nuclear Magnetic Resonance (NMR), Advanced Polymer Chromatography (APC), and Thermogravimetric Analysis (TGA) to quantify polyvinyl alcohol (PVA) and polyethylene glycol (PEG) content in hybrid freeze-thaw derived PVA/PEG/PVP hydrogels. Hydrogels were synthesized using an adapted freeze–thaw method across a wide range of PVA:PEG ratios, with PVP included at 1 wt% to assess potential intermolecular effects. NMR and APC reliably quantified polymer content with low average errors of 2.77% and 2.01%, respectively, and were unaffected by phase separation or hydrogen bonding within the composite matrix. TGA enabled accurate quantification at PVA contents ≤62.5%, where PEG and PVA maintained distinct thermal decomposition behaviors. At higher PVA concentrations, increased hydrogen bonding and crystalline restructuring, confirmed by FTIR through shifts near 1140 cm⁻¹ and significant changes in the –OH region, altered thermal profiles and reduced TGA accuracy. Together, these findings establish APC as a high-throughput alternative to NMR for multi-component polymer analysis and outline critical thermal and structural thresholds that influence TGA-based quantification. This work provides a framework for characterizing complex polymer networks in biomedical hydrogel systems.

Abstract: Systems favoring cross-pollination such as male sterility and female flowering type are of great importance in the development of new hybrid cultivars and their seed production. The advantages of male sterility are expressed in production of cheaper and competitive seeds. The presence of this characteristic in watermelon is not common, and in some cases, it is accompanied by negative manifestations. A collection of 150 watermelon genotypes was tested at the Maritsa Vegetable Crops Research Institute, Bulgaria, over the past nine years to search for a genetic source of male sterility. The results revealed that two mutations were found. The first mutation was in a plant of the Asar variety, which formed completely degenerated structures in the place of male and female flowers that were completely sterile. The other mutation affected male flowers, female flowers and leaf shape. Male flowers produced a small amount of pollen. Female flowers were formed but they were sterile and aborted at an early stage. The genotype can be propagated by pollination of the normal plants, which in the next generation segregate into mutant - 25%, and normal - 75%. The gene source is phenotyped according to the main characteristics of the fruits and the vegetation period. The mutation found cannot be directly used in a breeding program, but it is of interest for studying this important trait. The success of detecting flowers that are sterile depends on the number of watermelon plants, which for the conditions of the experiment amounted to a minimum of 4492 plants at a probability level of P3 – 0.95.

Abstract: In this paper, a wireless network architecture is considered that combines double Intelligent Reflecting Surfaces (IRSs), Energy Harvesting (EH), and Non-Orthogonal Multiple Access (NOMA) with cooperative relaying (C-NOMA), to leverage the performance of Non-Line-of-Sight (NLoS) communication and incorporate energy efficiency in next-generation networks. To optimize the phase shifts of both IRSs, we employ a machine learning model that offers a low-complexity alternative to traditional optimization methods. This lightweight learning-based approach is introduced to predict effective IRS phase configurations without relying on solver-generated labels or repeated iterations. The model learns from channel behaviour and system observations, which allows it to react rapidly under dynamic channel conditions. Numerical analysis demonstrates the validity of the proposed architecture in providing considerable improvements in terms of spectral efficiency and service reliability through the integration of energy harvesting and relay-based communication, compared to conventional systems, thereby facilitating green communication systems.

Abstract: The clinical management of Pancreatic Neuroendocrine Neoplasms (Pan-NENs) is complicated by the disease's intrinsic variability, which creates significant hurdles for accurate risk profiling and the standardization of treatment protocols. Recently, Artificial Intelligence (AI) has offered a promising avenue to address these challenges. By integrating and processing high-dimensional multimodal datasets (encompassing clinical history, radiomics, and pathology), these computational tools can refine survival forecasts and support the development of personalized medicine. However, the transition from experimental success to routine clinical use is currently obstructed by reliance on limited, retrospective cohorts that lack external validation, alongside unresolved concerns regarding algorithmic transparency and ethical governance. This review evaluates the current landscape of AI-driven prognostic modeling for Pan-NENs and critically examines the pathway towards their reliable integration into clinical practice.

Abstract: The South Africa national programme aims to enhance energy in informal settlements by maximising access to energy, alleviating poverty, and promoting urban inclusion. Nevertheless, a high rate of unlawful connections and old distribution systems has been identified in municipalities already experiencing financial poverty. This article assesses the suitability of electrifying informal settlements, mainly by funding capital programmes with grants. These programmes have beneficial effects on municipal revenue, non-technical electricity losses (NTLs), network destruction, and sustainability in the long run. Based on recent studies, city reports, and case studies in large cities, this paper concludes that electrification without commensurate investment in revenue protection systems, reinforced infrastructure, and institutional changes drives losses in revenues and leads to additional maintenance burdens. This article ends with policy guidelines, which aim to unify the process of electrification with sustainable municipal revenue recovery.

Abstract:

The increasing demand for sustainable energy production necessitates the development of innovative technologies for converting municipal waste into valuable energy offering a viable alternative to fossil fuels. This study presents a flexible, portable, and expandable waste-to-energy concept that integrates gasification and pyrolysis processes production of combustible gases and liquid fuels. Particular emphasis is placed on the use of transparent and interpretable modeling approaches to support system optimization and future scalability. The proposed methodology is demonstrated on two experimental systems currently operated at CEET Explorer, VSB – Technical University of Ostrava, Czech Republic: (i) a primary gasification facility equipped with a plasma torch, reactor, hydrogen separator and tank, fuel cells, and renewable grid connections; and (ii) a secondary pyrolysis unit designed to maximize pyrolysis oil production. Both systems are modeled and simulated using in-house software developed in Python, employing stoichiometric balances, symbolic regression, and polynomial regression to represent chemical reactions and energy flows. The findings demonstrate that transparent models—such as stoichiometric modeling combined with interpretable machine learning—can accurately reproduce the operational behavior of waste-to-energy processes. Gasification is optimized for hydrogen generation and electricity production via fuel cells, whereas pyrolysis favors liquid fuel yield with syngas as a by-product. Molar mass relations are applied to ensure consistent conversion between mass and volume across gasification, pyrolysis, and combustion pathways, maintaining the conservation of mass. Overall, the integration of stoichiometric balance models with symbolic and polynomial regression provides a reliable and interpretable framework for simulating real waste-to-energy systems. The current results, based on bio-wood waste from the Czech Republic, validate the proposed methodology, which is made openly available to promote transparency, reproducibility, and further advancement of sustainable waste-to-energy technologies.

Abstract: Diatoms are key primary producers and sensitive indicators in polar freshwater ecosystems, responding rapidly to environmental change. This study investigates diatom species richness and the influence of environmental variables in fourteen coastal lakes on King George and Horseshoe Islands in the maritime Antarctic. Water and surface sediment samples collected in 2017, 2019, and 2020 were analyzed using light and scanning electron microscopy, revealing 86 diatom species and genera across all lakes except Lake 5. King George Island exhibited higher species richness, with frequent occurrences of Planothidium lanceolatum, Achnanthidium dolomiticum, Fragilaria capucina and Nitzschia homburgiensis. On Horseshoe Island, common taxa included Achnanthes, Achnanthidium, Fragilaria, Nitzschia, Navicula, and Gomphonema. Among the previously measured water chemistry variables, HCO3- (ρ = 0.78, p = 0.005) and K+ (ρ = 0.69, p = 0.019) showed the strongest positive correlations with diatom species richness. Major ions and nutrients exhibited moderate relationships with DO, salinity, and pH. In contrast, temperature and trace metals displayed weak or negligible correlations, suggesting indirect influences on diatom diversity. These findings demonstrate that diatom communities in the Maritime Antarctic lakes are highly diverse and are strongly shaped by variations in water chemistry, underscoring the ecological sensitivity of these freshwater ecosystems.