I show how the quantum paradoxes occurring when we adopt a standard realist framework (or a framework in which the collapse implies a physical change of the state of the system) vanish if we abandon the idea that a measurement is related (directly or indirectly) to a physical change of state. In Convivial Solipsism, similarly to Everett’s interpretation, there is no collapse of the wave function. But contrary to Everett’s interpretation, there is only one world. This allows also to get rid of any non-locality and to provide a solution to the Wigner’s friend problem and its more recent versions.

Patients with pT1 high-grade (HG) bladder cancer (BC) and a very high risk of progression might benefit from immediate radical cystectomy (RC), but this option remains controversial. Validation of a standardized method to evaluate the extent of lamina propria (LP) invasion (with recognized prognostic value) in transurethral resections (TURBT) specimens is still needed. The Rete Oncologica Lombarda (ROL) system showed a high predictive value for progression after TURBT in recent retrospective studies. Our aim was to validate ROL system on a large mono-institutional prospective series of primary urothelial carcinomas. From 2016 to 2020, we adopted ROL for all patients with pT1 HG BC on TURBT. We employed a 1.0-mm threshold to stratify tumors in ROL1 and ROL2. A total of 222 pT1HGBC were analyzed. Median age was 74 years, with male predominance (73.8%). ROL was feasible in all cases: 91 cases were ROL1 (41%) and 131 ROL2 (59%). At a median follow up of 26.9 months (IQR 13.8-40.6), we registered 80 recurrences and 40 progressions. ROL was a significant predictor of tumor progression at both univariable (HR 3.53; CI 95% 1.56 – 7.99; p<0.01) and multivariable (HR 2.90; CI 95% 1.25 – 6.75; p=0.01) Cox regression analyses. At Kaplan-Meier estimates, ROL showed correlation with both PFS (p=0.0012) and RFS (p=0.0167). Our results confirmed the strong predictive value of ROL for progression on a large prospective series. We encourage the application of ROL for reporting the extent of LP invasion, substaging T1 HG BC, and improving risk tables for urological decision making.

Theories on life’s origin generally acknowledge the advantage of a semi-permeable vesicle (protocell) for enhancing the chemical reaction-diffusion processes involved in abiogenesis. However, more and more evidence indicates that the origin of life concerned the photo-chemical dissipative structuring of the fundamental molecules under UV-C light. In this paper, we analyze the Mie UV scattering properties of such a vesicle made from long chain fatty acids. We find that the vesicle could have provided early life with a shield from the faint, but dangerous, hard UV-C ionizing light (180-210 nm) that probably bathed Earth’s surface from before the origin of life and until perhaps 1,500 million years after, until the formation of a protective ozone layer as a result of the evolution of oxygenic photosynthesis.

This paper focuses on the so-called proportional intensity-based software reliability models (PI-SRMs), which are extensions of the common non homogeneous Poisson process (NHPP)-based SRMs, and describe the probabilistic behavior of software fault-detection process by incorporating the time-dependent software metrics data observed in the development process. Especially we generalize the seminal PI-SRM in Rinsaka, Shibata and Dohi (2006) by introducing eleven well-known fault-detection time distributions, and investigate their goodness-of-fit and predictive performances. In numerical illustrations with four data sets collected in real software development projects, we utilize the maximum likelihood estimation to estimate model parameters with three time-dependent covariates; test execution time, failure identification work and computer time-failure identification, and examine the performances of our PI SRMs in comparison with the existing NHPP-based SRMs without covariates. It is shown that our PI-STMs could give better goodness-of-fit and predictive performances in many cases.

In this review, we trace the evolution of the quantum spin-wave theory treating non-collinear spin configurations. Non-collinear spin configurations are consequences of the frustration created by competing interactions. They include simple chiral magnets due to competing nearest-neighbor (NN) and next-NN interactions and systems with geometry frustration such as the triangular antiferromagnet and the Kagomé lattice. We review here spin-wave results of such systems and also systems with the Dzyaloshinskii-Moriya interaction. Accent is put on these non-collinear ground states which have to be calculated before applying any spin-wave theory to determine the spectrum of the elementary excitations from the ground states. We mostly show results from a self-consistent Green’function theory to calculate the spin-wave spectrum and the layer magnetizations at finite T in two and three dimensions as well as in thin films with surface effects. Some new unpublished results are also included. Analytical details and the validity of the method are shown and discussed.

: In the last years, materializations of neuromorphic circuits based on nanophotonic arrangements have been proposed, which contain complete optical circuits, laser, photodetectors, photonic crystals, optical fibers, flat waveguides, and other passive optical elements of nanostructured materials, which eliminate the time of simultaneous processing of big groups of data, taking advantage of the quantum perspective and thus highly increasing the potentials of contemporary intelligent computational systems. This article is an effort to record and study the research that has been conducted concerning the methods of development and materialization of neuromorphic circuits of Neural Networks of nanophotonic arrangements. In particular, an investigative study of the methods of developing nanophotonic neuromorphic processors, their originality in neuronic architectural structure, their training methods and their optimization has been realized along with the study of special issues such as optical activation functions and cost functions.

This paper presents an exact solution to the Timoshenko beam theory (TBT) for first-order analysis, second-order analysis, and stability. The TBT covers cases associated with small deflections based on shear deformation considerations, whereas the Euler–Bernoulli beam theory (EBBT) neglects shear deformations. Thus, the Euler–Bernoulli beam is a special case of the Timoshenko beam. The moment-curvature relationship is one of the governing equations of the EBBT, and closed-form expressions of efforts and deformations are available in the literature. However, neither an equivalent to the moment-curvature relationship of EBBT nor closed-form expressions of efforts and deformations can be found in the TBT. In this paper, a moment-shear force-curvature relationship, the equivalent in TBT of the moment-curvature relationship of EBBT, was presented. Based on this relationship, first-order and second-order analyses were conducted, and closed-form expressions of efforts and deformations were derived for various load cases. Furthermore, beam stability was analyzed and buckling loads were calculated. Finally, first-order and second-order element stiffness matrices were determined.

In this paper, a complete tool for real-time detection of atypical energy behaviors of airplanes is presented. The methodology extends in real time an existing offline process using Dubins trajectories as a predictor of the remaining distance to the runway threshold. Two major contributions are presented in this paper. First, a real-time measure of the aircraft energy behaviour is defined, indicating whether the aircraft is in good condition to intercept the extended runway centreline from its current position. Secondly, a 2D trajectory suggestion is given, allowing safe management of the approach path according to atypical criteria of historical data. Finally, this document proposes a comprehensive tool for air traffic controllers, which is a major step forward in understanding, becoming aware of and resolving critical situations that could lead to accidents.

Eating disorder (ED) symptoms often co-occur with nonsuicidal self-injury (NSSI). This comorbidity is consistent with evidence that trait negative urgency increases risk for both of these phenomena. We previously found that impaired late-stage negative emotional response inhibition (i.e., negative emotional action termination or NEAT) might represent a neurocognitive mechanism for heightened negative urgency among people with NSSI history. The current study evaluated whether relations between negative urgency and ED symptoms similarly reflect deficits in this neurocognitive process. One hundred and five community adults completed an assessment of ED symptoms, negative urgency, and an emotional response inhibition task. Results indicated that, contrary to predictions, negative urgency and NEAT contributed independent variance to the prediction of ED symptoms, while controlling for demographic covariates and NSSI history. Worse NEAT was also uniquely associated with restrictive eating, after accounting for negative urgency. Our findings suggest that difficulty inhibiting ongoing motor responses triggered by negative emotional reactions (i.e., NEAT) may be a shared neurocognitive characteristic of ED symptoms and NSSI. However, negative urgency and NEAT dysfunction capture separate variance in the prediction of ED-related cognitions and behaviors, distinct from the pattern of results we previously observed in NSSI.

Background: Recent developments in our understanding of the interactions between long non-coding RNA (lncRNA) and cellular components have improved treatment approaches for various human diseases including cancer, vascular diseases, and neurological diseases. Although investigation of specific lncRNAs revealed their role in the metabolism of cellular RNA, our understanding of their contribution to post-transcriptional regulation is relatively limited. In this study, we explore the role of lncRNAs in modulating alternative splicing and their impact on downstream protein-RNA interaction networks. Results: Analysis of alternative splicing events across 39 lncRNA wildtype and knockout RNA-sequencing datasets from three human cell lines: HeLa (Cervical Cancer), K562 (Myeloid Leukemia), and U87 (Glioblastoma), resulted in high confidence (fdr < 0.01) identification of 4432 skipped exon events and 2474 retained intron events, implicating 759 genes to be impacted at post-transcriptional level due to the loss of lncRNAs. We observed that a majority of the alternatively spliced genes in a lncRNA knockout were specific to the cell type, in agreement with the finding that genes affected by alternative splicing also displayed enriched functions in a cell type specific manner. To understand the mechanism behind this cell-type specific alternative splicing patterns, we analyzed RNA binding protein (RBP)-RNA interaction profiles across the spliced regions. Conclusions: Despite limited RBP binding data across cell lines, alternatively spliced events detected in lncRNA perturbation experiments were associated with RBPs binding in proximal intron-exon junctions, in a cell type specific manner. The cellular functions affected by alternative splicing were also affected in a cell type specific manner. Based on the RBP binding profiles in HeLa and K562 cells, we hypothesize that several lncRNAs are likely to exhibit a sponge effect in disease contexts, resulting in the functional disruption of RBPs due to altered titration of the RBPs from their target loci. We propose that such lncRNA sponges can extensively rewire the post-transcriptional gene regulatory networks by altering the protein-RNA interaction landscape in a cell-type specific manner.

E-commerce businesses employ recommender models to assist in identifying a personalized set of products for each visitor. To accurately assess the recommendations’ influence on customer clicks and buys, three target areas—customer behavior, data collection, user-interface —will be explored for possible sources of erroneous data. Varied customer behavior misrepresents the recommendations’ true influence on a customer due to the presence of B2B interactions and outlier customers. Non-parametric statistical procedures for outlier removal are delineated and other strategies are investigated to account for the effect of a large percentage of new customers or high bounce rates. Subsequently, in data collection we identify probable misleading interactions in the raw data, propose a robust method of tracking unique visitors, and accurately attributing the buy influence for combo products. Lastly, user-interface issues discuss the possible problems caused due to the recommendation widget’s positioning on the e-commerce website and the stringent conditions that should be imposed when utilizing data from the product listing page. This collective methodology results in an exact and valid estimation of the customer’s interactions influenced by the recommendation model in the context of standard industry metrics such as Click-through rates, Buy-through rates, and Conversion revenue.

The most common liver disorder nowadays is non-alcoholic fatty liver disease(NAFLD) and it is a progressive disease that rises in severity from steatosis to nonalcoholic steatohepatitis(NASH), fibrosis and cirrhosis to increase risk of developing hepatocellular carcinoma. It is a cause of great concern as there is an estimated seventy million Americans who are currently affected by NAFLD, and this is expected to only increase because of its association with obesity and diabetes and also a lack of therapies to keep its development and progression in check. In this particular study we performed a gene set enrichment analysis(GSEA) of differentially expressed genes in a green tea against methionine-choline deficient diet in high-fat patients in the development of non-alcoholic fatty liver disease(NAFLD). The downregulated genes were used to perform an enrichment analysis and in the ARCHS4 TFs Coexpression database the most significant gene was found to be KLF5_human_tf_ARCHS4_coexpression. In the ARCHS4 Kinases Coexpression pathway database STYK1_human_kinase_ARCHS4 Coexpression was found to be the most significant gene. And finally for the upregulated genes a similar enrichment analysis was performed and in the humancy database γ-linolenate biosynthesis_Homo sapiens_PWY-6000 gene was discovered to be the most significant one. This study has used bioinformatics tools and the Enrichr software to perform a comparative analysis of differentially expressed gene sets for high-fat patients having a diet consisting of green tea against a methionine-choline deficient diet. Green tea is known to contain several antioxidants and polyphenols which provide protection against many liver diseases such as non-alcoholic fatty liver disease(NAFLD). The present study simply tries to build awareness of this to the general public and allow them to learn more about certain diets which have protective effects against liver diseases. Hopefully by implementing these in their daily lifestyles the public can gain some form of protection against these types of liver disorders.

Meixner's historical remark in 1969 "... it can be shown that the concept of entropy in the absence of equilibrium is in fact not only questionable but that it cannot even be defined...." is investigated from today's insight. Several statements --such as the three laws of phenomenological thermodynamics, the embedding theorem and the adiabatical uniqueness-- are used to get rid of non-equilibrium entropy as a primitive concept. In this framework, Clausius inequality of open systems can be derived by use of the defining inequalities which establish the non-equilibrium quantities contact temperature and non-equilibrium molar entropy which allow to describe the interaction between the Schottky system and its controlling equilibrium environment.

Cyclic peptides have higher stability and better properties as therapeutic agents than their linear peptide analogues. Consequently, intramolecular click chemistry is becoming an increasingly popular method for the synthesis of cyclic peptides from their isomeric linear peptides. However, assessing the purity of these cyclic peptides by mass spectrometry is a significant challenge, as the linear and cyclic peptides have identical masses. In this paper, we have evaluated the analytical capabilities of energy-resolved mass spectrometry (ER MS) and mid-infrared microscopy (IR) to address this challenge. On the one hand, mixtures of both peptides were subjected to Collision Induced Dissociation tandem mass spectrometry (CID MS/MS) experiments in an ion trap mass spectrometer at several excitation energies. Two different calibration models were used: a univariate model (at a single excitation voltage) and a multivariate model (using multiple excitation voltages). The multivariate model demonstrated slightly enhanced analytical performance, which can be attributed to more effective signal averaging when multiple excitation voltages are considered. On the other hand, IR microscopy was used for the quantification of the relative amount of linear peptide. This was achieved through univariate calibration, based on the absorbance of an alkyne band specific to the linear peptide, and through Partial Least Squares (PLS) multivariate calibration. The PLS calibration model demonstrated superior performance in comparison to univariate calibration, indicating that consideration of the full IR spectrum is preferable to focusing on the specific peak of the linear peptide. The advantage of IR microscopy is that it is linear across the entire working interval, from linear peptide molar ratios of 0 (equivalent to pure cyclic peptide) up to 1 (pure linear peptide). In contrast, the ER MS calibration models exhibited linearity only up to 0.3 linear peptide molar ratio. However, ER MS showed better performances in terms of limit of detection, intermediate precision and root-mean-square-error of calibration. Therefore, ER MS is the optimal choice for the detection and quantification of the lowest relative amounts of linear peptide.

The Leave-One-Out (LOO) Green Fluorescent Protein (GFP) approach to biosensor design com-bines computational protein design with split protein reconstitution. LOO-GFPs reversibly fold and gain fluorescence upon encountering its target peptide, which can be redefined by computa-tional design of the LOO site. Such an approach can be used to create reusable biosensors for the early detection of emerging biological threats. Enlightening biophysical inferences for nine LOO-GFP biosensor libraries are presented, with target sequences from dengue, influenza, or HIV, replacing beta strands 7, 8 or 11. An initially low hit rate was traced to components of the energy function, manifesting in the over-rewarding of over-tight side chain packing. Also, screening by colony picking required a low library complexity, but designing a biosensor against a peptide of at least 12 residues requires a high complexity library. This double-bind was solved using a "piecemeal" iterative design strategy. Also, designed LOO-GFPs fluoresced in the unbound state due to unwanted dimerization, but this was solved by fusing a fully functional prototype LOO-GFP to a fiber-forming protein, Drosophila ultrabithorax, creating a biosensor fiber. One in-fluenza hemagglutinin biosensor is characterized here in detail, showing a shifted excita-tion/emission spectrum, a micromolar affinity for the target peptide, and an unexpected pho-to-switching ability.

Halide perovskite are known by their (1) organic inorganic hybrid and (2) inorganic halide perovskite. Having this in mind, monolithic perovskite/silicon tandem solar cell has already demonstrated extraordinarily high performance in the field of photovoltaic with current efficiency of 29.15%, breaking the efficiency limit for silicon solar cell. Currently, halide perovskites become successful not only in photovoltaic but also in many other related potential optoelectronic applications. Because of this reason, the origin of their multifunctional properties, remarkable energy harvesting and emitting efficiency and the corresponding potential applications in various optoelectronic devices become controversial issues and hot topics of academic research this time. In this review, nano-engineering strategies, microscopic origins and mechanisms are reviewed well to make clarity on what the origin of multifunctional properties such as tunability, ferroelasticity, piezoelectricity, pyroelectricity and thermoelectric properties of halide perovskites. Moreover, the coexistence of multiple properties makes halide provskites possible for synergistic applications and multifunctional perspectives such as emerging energy harvesting, conversion technologies, nano-plasmonic sensing and electromechanical applications, which are now open for the scientific community for further detail investigations. To successfully explore this field, advanced nanometer scale domain characterization tools are highly relevant to understand the microscopic origin of these electrical properties; aid the commercial enterprises and the research institutions. Not only the microscopic origin but also identifying factors and issues affecting the successful understanding and presence or absence of these electrical parameters should be primary task in this review. Finally, the big challenges for operation of halide perovskites owing to temperature, moisture, light, air, etc. induced material degradation and device deteriorations as well as lattice instability, nano scale defects, surface and bulk defects should be considered while dealing with these future research topics.

Conventional approaches in Structural Health Monitoring (SHM) tend to be complex, destructive, and time-intensive. Additionally, they often require a large number of sensors to thoroughly assess structural integrity. In this study, we present a novel, non-destructive SHM framework based on machine learning (ML) for the accurate detection and localization of structural cracks. This approach leverages a minimal number of strain gauge sensors linked via Bluetooth communication. The framework is validated through empirical data collected from 3D carbon fiber-reinforced composites, including three distinct specimens, ranging from crack-free samples to specimens with up to ten cracks of varying lengths and depths. Strain data from five sensors were analyzed using a combination of Shewhart charts, Grubbs Test (GT), and a hierarchical clustering algorithm, specifically designed to evaluate and classify fractures. Our ML-based framework offers a streamlined and efficient alternative to traditional laboratory procedures, delivering precise crack detection with significant potential for applications in the composites industry.

The COVID-19 pandemic has highlighted the critical need for telehealth and remote patient monitoring in healthcare delivery. Despite the growing use of on-body wearable sensors for continuous monitoring and predicting adverse events, such as hospitalizations or falls, their widespread adoption within the healthcare ecosystem remains a significant challenge. While the pandemic has accelerated the acceptance of these technologies, achieving widespread integration requires their sustained incorporation into routine healthcare practices beyond emergency situations. In this study, we extend the application of our previously developed remote patient monitoring system, originally designed for the geriatric frail population, to COVID-19 patients. Our objective is to assess whether the metrics obtained from this system, which includes physical activity and indoor localization sensors, along with vital sign monitoring, can provide additional insights into the recovery trajectory of individuals affected by COVID-19.

Accurate, rapid, and stable prediction of electrical energy consumption is essential for decision-making, energy management, efficient planning, and reliable power system operation. Errors in forecasting can lead to electricity shortages, wasted resources, power supply interruptions, and even grid failures. Accurate forecasting enables timely decisions for secure energy management. However, predicting future consumption is challenging due to the variable behavior of customers, requiring flexible models that capture random and complex patterns. Existing forecasting methods, both traditional and modern, have limitations and do not fully meet accuracy expectations. To address these issues, this research introduces a hybrid models that combine FCRBM based forecaster, and GWDO based optimizer, namely FS-FCRBM-GWDO approach to enhance the model performance in STLF have been developed. While some models excel in accuracy and others in convergence rate, both aspects are crucial. The main objective is to create a forecasting model that provides reliable, consistent, and precise predictions for effective energy management. This led to the development of a novel two-stage hybrid model. The first stage predicts electrical energy usage through four modules using deep learning, support vector machines, and optimization algorithms. The second stage optimizes energy management based on predicted consumption, focusing on reducing costs, managing demand surges, and balancing electricity expenses with customer inconvenience. This approach benefits both consumers and electricity corporations by lowering bills and enhancing power system stability. Simulation results validate the proposed model's efficacy and efficiency compared to benchmark models.

The use of natural chloride in the salt fuel has been sometimes promoted for the chlorine based molten salt fast reactor using for example NaCl-UCl4- UCl3. Most of the chemistry based R&D has been carried out on natural chloride, while in reactor physics most of the calculations are based on enriched chloride-37. In any case, the use of natural chloride (75.77% 35Cl and 24.23% 37Cl) induces specific ecological and neutron economical issues. An ecological issue is the production of 36Cl by neutron activation of 35Cl. Chlorine-36 is a soluble long live nuclide that makes it a ‘first’ nuclide in the safety assessment of the repository. We explore the build-up of 36Cl with burnup for various 37Cl (activation product) enrichment. The neutron economical aspect is gained by achieving reactor criticality with a lower amount of fissile material achieved through the use of enriched chloride-37. The criticality (k) of a core is much larger for enriched chloride than for the natural one. The reactor with 99% 37Cl would have a k99/knat of 1.04346 which would allow to reduce the required uranium enrichment and thus the fuel cost. This reactivity gain is evaluated for various 37Cl enrichment factors to estimate uranium enrichment gain achievable through 37Cl enrichment. However, from economical point of view it could be of interest to use as some kind of compromise solution natural NaCl, which will be analysed, too. Production/enrichment of 37Cl can be performed by physical separation e.g. gas centrifugation of 1H35/37Cl or by chemical separation using anion partitioning and elution of 23Na35/37Cl on solid adsorbent columns or in liquid – liquid extraction systems. These techniques require however extensive investigations including chemical thermodynamics and hydrodynamics. Comparisons are suggested on the basis of the separation factor α. Recommendations are finally given for utilising 37Cl in the fast molten salt reactor. The enrichment work for 37Cl is smaller than the work needed for 235U enrichment.

This study introduces a novel and sustainable method of producing graphene from coconut shells and investigates its application in Graphene, Ni/Graphene, and Zn/Graphene electrodes for advanced energy storage devices. The graphene was synthesized scalably using a pyrolysis and impregnation technique, with its successful synthesis verified by X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), and electrical conductivity measurements characterizations. The study highlights the enhanced performance of Zn/Graphene electrodes, which outperform both pure graphene and Ni/Graphene variants. This superior performance is attributed to the smaller particle size of Zn (mean = 2.356 µm) compared to Ni (mean = 3.09 µm), and Zn’s more favorable electron configuration for electron transfer. These findings demonstrate the potential of bio-derived graphene composites as efficient, high-performance electrodes, paving the way for more sustainable and cost-effective energy storage solutions.

Background: Depression presents with altered energy regulation and neural plasticity. Previous electroencephalography (EEG) studies showed that practice increases power in beta range (13-30 Hz) in healthy subjects but not in those with impaired plasticity. Here, we ascertain whether depression presents with alterations of spectral activity and connectivity before and after practice. Methods: We used publicly available resting state EEG (64 electrodes) of 122 subjects. Based on Beck Depression Inventory (BDI) score, they were assigned to either high BDI (hBDI, BDI&gt;13, N=46) or control (CTL, BDI&lt;7, N=75) group. We analyzed spectral activity, theta-beta and theta-gamma phase-amplitude coupling (PAC) of EEG recorded before and after a learning task. Results: At baseline, compared to CTL, hBDI group exhibited greater beta power over fronto-parietal regions and gamma over right parieto-occipital area. After practice, increases in all frequency ranges were observed only in CTL. Theta-beta and theta-gamma PAC were greater in hBDI before the task but not after the task. Conclusions: The lack of substantial post-task growth of beta power in depressed subjects likely represents power saturation due to greater baseline values. We speculate that inhibitory/excitatory imbalance, altered plasticity mechanisms, and energy dysregulation present in depression may contribute to this phenomenon.

The spin-torsion theory is a gauge theory approach to gravity that expands upon Einstein's general relativity (GR) by incorporating the spin of microparticles. In this study, we further develop the spin-torsion theory to examine spherically symmetric and static gravitational systems that involve free-falling macroscopic particles. We posit that the quantum spin of macroscopic matter becomes noteworthy on cosmic scales. We further assume that the Dirac spinor and Dirac equation adequately capture all essential physical characteristics of the particles and their associated processes. A crucial aspect of our approach involves substituting the constant mass in the Dirac equation with a scale function, allowing us to establish a connection between quantum effects and the scale of gravitational systems. This mechanism ensures that the quantum effect of macroscopic matter is scale-dependent and diminishes locally, a phenomenon not observed in microparticles. For any given matter density distribution, our theory predicts an additional quantum term, the quantum potential energy (QPE), within the mass expression. QPE induces time dilation, distance contraction, and thus mimics a gravitational well. When applied to cosmology, our theory yields a static cosmological model. The QPE serves as a counterpart to the cosmological constant introduced by Einstein to balance gravity in his static cosmological model. The QPE also offers a plausible explanation for the origin of the Hubble redshift (traditionally attributed to the universe's expansion). The predicted luminosity distance-redshift relation aligns remarkably well with SNe Ia data from the cosmological sample of SNe Ia. In the context of galaxies, QPE functions as the equivalent of dark matter. The predicted circular velocities align well with the rotation curve data from the SPARC (Spitzer Photometry and Accurate Rotation Curves database) sample. Importantly, our conclusions in this paper are reached through a conventional approach, with the sole assumption of the quantum effects of macroscopic matter on large scales, without the need for additional modifications or assumptions.

The present research focuses on the endogenous development theory and investigates the relationship between economic growth (dependent variable) and renewable energy consumption, technological innovation, and export diversification (independent variables) in seven emerging economies known as the E-7. Previous studies have examined these factors individually but have not explored their combined impact on the E-7 economies. Therefore, this study contributes to the existing literature on the effects of renewable energy consumption, technological advancement, and export diversification on economic development. The study analyses the dynamic connection among these variables in seven selected emerging countries: Brazil, China, Indonesia, India, Mexico, Russia, and Turkey. Panel data from 1990 to 2022 is utilized, and various methodologies, including panel cointegration, the PMG-ARDL estimator, and robustness tests such as FMOLS and DOLS, are employed. Empirical inferences are drawn using the Dumitrescu-Hurlin Panel Causality (DHC) test, and the long-run relationships among the variables are validated using the Westerlund residual cointegration tests. The results from the PMG-ARDL estimator show that renewable energy consumption, technological advancement, and export diversification have a significant and positive impact on economic expansion, confirming the validity of the endogenous growth model in the E-7 countries. The control variable of the financial sector has a positive but insignificant effect on economic growth, while trade openness has a negative and significant effect. The DHC test results indicate a neutral feedback effect of renewable energy consumption on economic growth. The findings also reveal a unidirectional causal relationship between technological innovation and economic growth. Overall, these findings provide valuable insights for economic policymakers in the E-7 countries. By removing barriers to renewable energy consumption, technological innovation, and export diversification, policymakers can promote sustainable economic development.

The global energy crisis is a significant issue, particularly in developing countries like Ethiopia, where traditional fuels such as wood and charcoal are predominantly used to meet energy demands in urban and rural areas. Despite Ethiopia's substantial charcoal production, the use of inefficient charcoal cookstoves exacerbates fuel consumption, forest degradation, and environmental damage. To address this, various improved charcoal cookstoves (ICS) have been introduced in urban and semi-urban communities in Wereta Town, located in the Amhara Regional State of Ethiopia. This study aims to evaluate household perceptions and identify barriers to the adoption of ICS in the Wereta district. The assessment involved a survey of 308 households using a structured cross-sectional method and analyzed five types of improved cookstoves: clay stoves, insulated clay cylinder stoves, non-insulated rocket stoves, insulated rocket stoves, and non-insulated cylindrical stoves. The study employed various socio-economic variables and utilized both cross-tabulation frequency factors and linear regression statistical analysis through SPSS 20 to identify factors influencing the adoption of ICS. The linear regression results indicated that marital status, income level, family size, and age significantly impact ICS adoption (p-value < 0.05), while the place of cooking, educational level, household decision-making, and the role of societal stakeholders showed no significant impact. This suggests that ICS adoption is primarily influenced by household income levels and family size.

Deploying onshore wind energy as a cornerstone of future global energy systems challenges societies and decision-makers worldwide. Expanding wind energy should contribute to a more sustainable electricity generation without harnessing humans and their environment. Opponents often highlight the negative environmental impacts of wind energy to impede its expansion. This study reviews 152 studies to synthesize, summarize, and discuss critically the current knowledge, research gaps, and mitigation strategies on the environmental impacts of onshore wind energy. The investigated effects comprise impacts on the abiotic and biotic environment, with birds and bats in particular, noise and visual impacts. Effects are discussed in the context of social acceptance, other energy technologies, and wind energy expansion in forests. The review illustrates that many effects are highly case-specific and must be more generalizable. Studies are biased regarding the research focus and areas, needing more standardized research methods and long-term measurements. Most studies focus on the direct mortality of birds and bats at wind farms and are concentrated in Europe and North America. Knowledge gaps persist for many impact categories, and the efficacy of mitigation strategies has yet to be proven. More targeted, unbiased research is required that allows for an objective evaluation of the environmental impacts of wind energy and strategies to mitigate them. Impacts, such as those on biodiversity, need to be addressed in the context of other anthropogenic influences and the benefits of wind energy. This forms the basis for a socially acceptable, efficient, and sustainable expansion of wind energy.

This comprehensive review explores the multifaceted landscape of supercapacitors, highlighting their pivotal role in meeting the global demand for efficient energy storage solutions. Supercapacitors, with their high power density, rapid charge-discharge cycles, and extended cycle life, offer a compelling alternative to conventional batteries and capacitors. The review delves into the fundamental mechanisms of energy storage in supercapacitors, categorizing them into Electrochemical Double-Layer Capacitors (EDLCs), pseudocapacitors, and hybrid capacitors. It discusses significant advancements in supercapacitor technology, including nanostructured materials, flexible and wearable supercapacitors, solid-state supercapacitors, and hybrid supercapacitors, highlighting their potential applications across industries such as transportation, renewable energy, consumer electronics, and industrial power management. Through continued research and development, supercapacitors are poised to play a pivotal role in driving the transition towards a greener and more efficient future.

In response to the escalating global waste production rate, sustainable waste management be-comes indispensable. In parallel, the transformation of energy system is vital in order to ensure affordable, decentralized, and sustainable energy for the global community, based on economic, environmental, and social criteria. Waste-to-Energy (WtE) is an effective option in order to put a stepping stone to address both issues provided that multiple views and criteria are considered. This paper puts forward a generic methodological framework to holistically assess WtE technologies based on the PROMETHEE approach. In addition to environmental, economic, and social aspects, demonstration of applicability of the proposed methodology is realized at national level the case of Greece. Anaerobic Digestion seems to be the most preferable choice, recognized for its cost-effectiveness and lower environmental burden to other WtE technologies (i.e. gasification, pyrolysis, incineration). Insightful expert opinions and public preference are of paramount importance to the adopted approach, revealing technology-specific concerns and preferences. In addition, the material presented underscores a crucial gap in Life Cycle Assessment studies for large-scale WtE, emphasizing the need for future scientific attention and exploration. Public consensus indicates a positive overall attitude towards waste valorization in the context of energy production.

Harnessing Quantum Energy States for Unprecedented Computing Capabilities In this proposal, we advocate for the use of energy states as fundamental units of quantum computer programming. Each unit of programming is conceptualized as an energy state, manifested as an essence-unit. An essence-unit, defined as the minimal form encapsulating complete uniqueness or specificity, serves as the cornerstone of this paradigm. This approach enables the recording of various forms of matter on quantum computers in essence-units, portraying their energy states. The recording of energy states is achieved through the creation of four distinct coherent potentials, facilitated by quantum dots or crystals. Crucially, these energy states embodied in essence-units resist subdivision. The study explores the intricate relationship among similarity, fractals, and uniqueness in quantum dot operations, revealing their profound implications for information transfer efficiency. Normalized entropy characterizes charge localized in quantum dot impurities in systems that have distortions. Through the utilization of N-level recording and entropy-fractal dimension equivalence, the paper elucidates the potential of quantum dots in reducing transmission time and modeling complex systems. The proposed methodology signifies a paradigm shift in quantum computing, presenting unparalleled possibilities for tackling hitherto insurmountable challenges.

To support the integration of renewable energy sources and preserve grid stability, this study examines several approaches for controlling the temperature of Battery Energy Storage Systems (BESS) in modern energy settings. Specifically, the usage of BESS in Virtual Power Plants (VPPs) is the focus of this study. The effectiveness, safety features, dependability, affordability, and suitability for VPP applications of these systems are examined. Among the various hybrid cooling alternatives, two particularly promising combinations emerge. Firstly, the integration of heat pipes and phase change materials leverages their ability to conduct heat efficiently away from heat sources with minimal temperature differences, making them excellent for rapid heat transfer. Secondly, an approach employing heat pipes and liquid passive cooling a combination that capitalizes on the efficient heat transfer capabilities of heat pipes and the consistent cooling offered by liquid passive systems. The study underscores the importance of improving BESS performance and sustainability within VPPs by providing useful recommendations for choosing the best thermal management system depending on climate conditions and geographic location.

The manuscript presents the use of three novel technologies for the implementation of wireless green battery-less sensors that can be used in agriculture. The three technologies, namely additive manufacturing, energy harvesting, and wireless power transfer from airborne transmitters carried from UAVs, are considered for smart agriculture applications. Additive manufacturing is exploited for the implementation of both RFID based sensors and passive sensors based on humidity sensitive materials. A number of energy-harvesting systems at UHF and ISM frequencies are presented which are in position to power platforms of wireless sensors, including humidity and temperature IC sensors used as agriculture sensors. Finally, in order to provide the wireless energy to the soil-based sensors with energy harvesting features, wireless power transfer (WPT) from UAV carried transmitters is utilized. The use of these novel technologies can facilitate the extensive use and exploitation of battery-less wireless sensors which are environmentally friendly and thus “green”. Additionally, it can potentially drive precision agriculture in the next era, through the implementation of a vast network of wireless green sensors which can collect and communicate data, to airborne readers so as to support with data the Artificial Intelligence and Machine Learning based, decision making platforms.

The future index prices are viewed as a critical issue for any trader and investor. For this craving, various models have shown up in the literature. The Geometric Brownian motion (GBM) is one of the popular models. This work examines four types of GBM as per the presence of memory or kind of volatility. These models include classical GBM with memoryless and constant volatility assumptions, SVGBM with memoryless and stochastic volatility assumption, GFBM with memory and constant volatility assumption, and SVGFBM with memory and stochastic volatility assumption. These models are utilized in an empirical study to forecast the future index price of Energy Sector in the Saudi Stock Exchange Market. The assessment was led by utilizing two error standards, mean square error (MSE) and mean absolute percentage error (MAPE). The outcomes showed that the SVGFBM occupies the highest level of accuracy according to smallest values of MSE and MAPE. While the accuracy of GBM come in the tail of the list models under study. These results have affirmed the positive affection of combining memory and stochastic volatility assumption into the GBM model, which agreed findings of numerous earlier works. Furthermore, the findings showed the GFBM models are more accurate than GBM models regardless of the type of volatility. While, under the same type of memory, the models with stochastic volatility assumption are more accurate than the corresponding models of constant volatility assumption. In general, all models considered in this work uncovered high accuracy through the value of MAPE ≤ 10%. This indicates of the ability of applying these models in a real financial environment. Through this empirical study, we can say that the Energy Sector in Saudi Arabia is predictable and stable and afterward we urge financial investors and stockholder to trade and invest in this sector.

C-terminal Src kinase (CSK) is the major inhibitory kinase for Src family kinases (SFKs) through phosphorylation of their C-tail tyrosine site, and regulates various cellular activities in association with SFKs functions. As a cytoplasmic protein, CSK need be recruited to the plasma membrane to regulate SFKs activities. The regulatory mechanism for CSK activity and its subcellular localization remains largely unclear. In this work, we developed a genetically encoded biosensor based on fluorescence resonance energy transfer (FRET) to visualize CSK activity in live cells. The biosensor with optimized substrate peptide confirmed crucial Arg107 site in CSK SH2 domain, and displayed sensitivity and specificity to CSK activity while little responses to co-transfected Src and Fyn. FRET measurements showed CSK having relatively mild level of kinase activity in comparison to Src and Fyn ones in rat airway smooth muscle cells. The biosensor tagged with different submembrane-targeting signals detected CSK activity at both non-lipid raft and lipid raft microregions, while showed higher FRET level at non-lipid ones. Co-transfected receptor-type protein tyrosine phosphatase alpha (PTPα) had inhibitory effect on the CSK FRET response. The biosensor didn’t detect obvious changes of CSK activity between metastatic cancer cells and normal ones. In conclusion, a novel FRET biosensor was generated to monitor CSK activity, and demonstrated CSK activity existing in both non-lipid and lipid raft membrane microregions while more present at non-lipid ones.

We delve into the intricate dynamics governing anisotropic fluids within the cosmological paradigm, elucidating the nuanced influence of conformal anomalies upon the stress-energy tensor. Through the presentation of a sophisticated theoretical framework, we seamlessly intertwine unconventional fluidic properties with profound cosmological considerations, thereby augmenting and refining our comprehension of the primordial universe.

This case study focuses on exploring the potential of biogas as a direct substitute for conventional fossil fuels in industrial applications. Instead of being limited to its common uses as a vehicle fuel or for power generation, this research aims to investigate how biogas can be integrated into industrial processes as an advanced and sustainable energy solution. By conducting a detailed analysis of the financial implications associated with the utilization of landfill gas and gas derived from biomass, a comprehensive understanding of their practical applications in the industrial sector can be obtained. This research goes beyond a superficial examination and delves into the intricate aspects of incorporating biogas as a viable alternative fuel source. When we say that utilizing biogas is technically feasible, it means that the necessary infrastructure and technologies are available to support its integration into industrial processes. This implies that there are existing methods and systems in place that can efficiently harness and utilize biogas for various industrial applications. These technologies ensure a seamless transition from conventional fossil fuels to renewable energy sources, leading to a more sustainable and environmentally friendly industrial landscape. Moreover, the statement that utilizing biogas is economically feasible emphasizes that the financial viability of employing biogas in industrial processes is advantageous. This research explores the potential cost savings and benefits associated with substituting conventional fuels with biogas. By carefully examining the economic aspects, such as initial investments, operational costs, and potential revenue streams, a comprehensive understanding of the financial impact of adopting biogas solutions in the industrial sector can be gained. By expanding and broadening the understanding of the technical and economic feasibility of biogas integration, this research aims to provide valuable insights into the potential of advanced biogas solutions for industrial applications. Indeed, to make biogas a viable and sustainable option as a raw material, it is necessary to establish farming subsidies and financial support specifically tailored for biogas production, similar to the existing support provided for food production. These subsidies and financial incentives play a crucial role in promoting and encouraging the growth of the biogas industry. By establishing such support systems, farmers and other stakeholders in the agricultural sector can be incentivized to participate in the production of biogas. This can involve the utilization of agricultural waste, organic residues, or dedicated energy crops for biogas generation. The financial assistance can help offset the initial investment costs, provide incentives for production, and ensure the economic viability of biogas projects. Moreover, when considering large-scale landfills or situations where industrial demands for energy are relatively low, landfill gas becomes a viable and practical option. Landfill gas, which is generated by the decomposition of organic waste in landfills, can be harnessed and utilized for various industrial purposes. This not only helps in managing waste but also provides a valuable source of renewable energy. In summary, while farming subsidies and financial support are crucial for promoting biogas production, landfill gas remains a viable option for large landfills or situations with minor industrial demands. The combination of these two approaches offers a comprehensive outlook on utilizing biogas as a renewable energy source for industrial applications.

We present a modified version of the Szilard Engine, demonstrating that an explicit measurement procedure is entirely unnecessary for its operation. By considering our modified engine, we are able to provide a new interpretation of Landauer’s original argument for the cost of erasure. From this view, we demonstrate that a reset operation is strictly impossible in a dynamical system with only conservative forces. Then, we prove that to approach a reset yields an unavoidable instability at the reset point. Finally, we present an original proof of Landauer’s principle that is completely independent from the Second Law of Thermodynamics.

The EU’s energy targets are to achieve at least 32% renewables in the energy mix by 2030. Part of the solution is strengthening consumer rights by empowering individuals to generate their own electricity. The study aimed to identify the most suitable energy system for electricity generation of up to 50 kW in the EU residential sector. The Multi-Criteria Decision Analysis was used to compare four systems: proton exchange membrane fuel cell with photovoltaic panels, photovoltaic panels, biomass powered Stirling engine, and solar powered Stirling engine. Based on the results, the most beneficial system for household electricity generation is the Biomass-fueled Stirling engine system due to its affordability, reliability, and low environmental impact. Governments and businesses can use these findings to improve information for the residential sector and enable the transition to renewable energy.

The paper proposes an innovative solution for managing and ensuring high energy efficiency of power supply systems at high non-linear loads. This is realized by maintaining optimal value of reliability indicators and high quality of power supply. The validation is carried out using analyzes and tests of quality of electromagnetic compatibility (EMC) for increased number of powered frequency converters. It has been proven that the effective use and reduction of energy consumption can be achieved thanks to the unique technological features of the employed electrical devices. This enables a normal operation of the system with decreased power and adequate control of energy processes. The problem of predicting power losses under changing conditions in a decentralized electrical network has been solved based on the theory of electromagnetic compatibility. The influence of the mains mode parameters and the indices of instantaneous distortion of current and voltage waveforms caused by the operation of converters on the resonance phenomena in power supply systems were investigated. Recommendations were developed for the selection of proper parameters of compensators for 6-10 kV and 0.4-0.66 kV circuits based on the analysis of the optimization problem when minimizing active power losses. Results of our findings may aid parties involved in designing and maintaining power networks in various applications, such as mines, etc.

In this paper, we investigate the structural, microstructural, dielectric, and energy storage properties of Nd and Mn co-doped Ba0.7Sr0.3TiO3 [(Ba0.7Sr0.3)1-xNdxTi1-yMnyO3 (BSNTM) ceramics (x = 0, 0.005, and y = 0, 0.0025, 0.005, and 0.01)] via a defect dipole engineering method. The complex defect dipoles (MnTi"-VO∙∙)∙ and (MnTi"-VO∙∙) between acceptor ions and oxygen vacancies capture electrons, enhancing the breakdown electric field and energy storage performances. XRD, Raman spectroscopy, and microscopic investigations of BSNTM ceramics revealed the formation of a tetragonal phase, increased oxygen vacancies, and reduced grain size with Mn dopant, respectively. The BSNTM ceramics with x=0.005 and y=0 exhibit a high dielectric constant of 2058 and a dielectric loss of 0.026 at 1 kHz. These values gradually decreased to 1876 and 0.019 for x=0.005 and y=0.01 due to the Mn2+ ions at Ti4+-site, which facilitates the formation of oxygen vacancies, and prevents the decrease of Ti4+. In addition, the defect dipoles act as a driving force for depolarization to tailor the domain formation energy and domain wall energy, which provides a high difference between the maximum polarization of Pmax and remnant polarization of Pr (ΔP=10.39 µC/cm2). Moreover, the complex defect dipoles with optimum oxygen vacancies in BSNTM ceramics can provide not only a high ΔP but also reduce grain size, which together improve the breakdown strength from 60.4 to 110.6 kV/cm, giving rise to a high energy storage density of 0.41 J/cm3 and high efficiency of 84.6% for x=0.005 and y=0.01. These findings demonstrate that defect dipoles engineering is an effective method to enhance the energy storage performance of dielectrics for capacitor applications.

The paper considers the issues of structural stability, electronic properties, and phonon dispersion of the cubic, tetragonal, and monoclinic phases of ZrO2. It was found that the monoclinic phase of zirconium dioxide is the most stable among the other two phases in terms of total energy, lowest enthalpy, highest entropy, and other thermodynamic values. The smallest negative modes were found for m-ZrO2. An analysis of the electronic properties showed that during the m–t phase transformation of ZrO2, the Fermi level first shifts by 0.125 eV towards higher energies, and then decreases by 0.08 eV in the t–c cross section. The band gap for c-ZrO2, t-ZrO2, and m-ZrO2 is 5.140 eV, 5.898 eV, and 5.288 eV, respectively. Calculations based on the analysis of the influence of doping 3.23, 6.67, 10.35 and 16.15 mol. %Y2O3 on the m-ZrO2 structure showed that the enthalpy of m-YSZ decreases linearly, which accompanies further stabilization of monoclinic ZrO2 and an increase in their defectiveness. In this case, the position of the Fermi level changes abruptly, and the energy gap decreases. It has been established that not only for pure systems, including those doped with Y2O3, the main contribution to the formation of the conduction band is made by the p-states of electrons. An analysis of the mechanism of water adsorption on the surface of t-ZrO2 (101) and t-YSZ (101) showed that H2O on unstabilized t-ZrO2 (101) is adsorbed dissociatively with an energy of -1.22 eV, as well as by the method of molecular chemisorption with an energy of -0.69 eV and the formation of a hydrogen bond with a bond length of 1.01 Å. In the case of t-YSZ (101), water is molecularly adsorbed onto the surface with an energy of -1.84 eV. Dissociative adsorption of water occurs at an energy of -1.23 eV, near the yttrium atom.

Cyanobacteria, microorganisms performing oxygenic photosynthesis, must adapt their metabolic processes to environmental challenges such as day and night changes. PipX, a unique regulatory protein from cyanobacteria provides a mechanistic link between signalling protein PII, a widely conserved (in bacteria and plants) transducer of carbon/nitrogen/energy richness, and the transcriptional regulator NtcA, which controls a large regulon involved in nitrogen assimilation. PipX is also involved in translational regulation by interaction with the ribosome-assembly GTPase EngA. However, increases of the PipX/PII ratio are toxic, presumably by abnormally increased binding of PipX to other partner(s). Here we present mutational and structural analyses of reported PipX-PII and PipX-NtcA complexes, leading to identification of single amino acid changes that decrease or abolish PipX toxicity. Four out of 11 mutations decreasing toxicity did not decrease PipX levels, suggesting that the targeted residues (F12, D23, L36, R54) provide toxicity determinants. In addition, one of those four mutations (D23A) argued against the over-activation of NtcA as the cause of PipX toxicity. Since most mutations at residues contacting PII decreased PipX levels, PipX stability would depend on its ability to bind to PII, a conclusion supported by the light-induced decrease in PipX levels observed in Synechococcus elongatus PCC7942.

In the framework of mean field approximation, we consider a spin system consisting of two interacting sub-ensembles: spins interactions with in each sub-ensemble are ferromagnetic, while the inter-ensemble interactions are antiferromagnetic. We define the effective number of the nearest neighbors, and show that if the two sub-ensembles have the same effective number of the nearest neighbors, the classical form of critical exponents (, , , ) gives way to the non-classical form (, , , ), and the scaling function changes simultaneously. We demonstrate that this system allows for two second-order phase transitions and two first-order phase transitions. We observe that an external magnetic field does not destroy the phase transitions, but only shifts their critical points, allowing for control of the system’s parameters. We discuss the regime when the magnetization as a function of the magnetic field develops a low-magnetization plateau, and show that the height of this plateau abruptly rises to the value of one when the magnetic field reaches a critical value. Our analytical results are supported by a Monte Carlo simulation of a three-dimensional layered model.

The Mine Internet of Things (MIoT), as a key technology for reconstructing post-disaster communication networks, enables to realize the safety monitoring and controlling of the affected roadway. However, due to the challenging underground mine environment, the MIoT suffers from severe signal attenuation, vulnerable nodes, and limited energy, which result in low network reliability of the post-disaster MIoT. To improve the transmission reliability as well as to reduce energy consumption, a directional-area-forwarding-based energy-efficient opportunistic routing (DEOR) for the post-disaster MIoT is proposed. DEOR defines a forwarding zone (FZ) for each node to route packets toward the sink. The candidate forwarding set (CFS) is constructed by the nodes within the FZ that satisfy the energy constraint and the neighboring node degree constraint. The nodes in CFS are prioritized based on the routing quality evaluation by taking the local attributes of nodes into consideration, such as the directional angle, transmission distance, and residual energy. DEOR adopts a recovery mechanism to address the issue of void nodes. The simulation results validate that the proposed DEOR outperforms ORR, OBRN and ECSOR in terms of energy consumption, average hop count, packet delivery rate, and network lifetime.

Strong convective storms can be a serious threat to modern society, influencing both the economy and human life. Thunderstorms can bring much-needed rain after a dry spell, but the nature of thunderstorm mostly causes damage due to high wind associated with it and heavy intensity rain that mostly causes quick overlandflow and flashfloods. The paper focused on the 2011 Pukkelpop event in Belgium where due to heavy thunderstorm a lot of financial damage occurred, and five casualties. In this paper we look into the basic elements that enforces the creation of a thunderstorm like CAPE and windshear. A representative grid has been taken from the Alaro-0 model of 12.5 km resolution for the analysis of the thunderstorm over Belgium which is detailed out in the methodology. The model runs of Alaro-0 from Royal Meteorological Institute of Belgium (RMI) is used for historical and future years for CAPE and Shear. We look into STEnv which is a composite number that can provide some insight on occurrence of thunderstorm, and STEnv is when CAPE*Shear exceeds certain threshold. In this study the threshold has been chosen as 97%. Only summer months have been taken into account into this study as summer(s) has the most thunderstorm in Belgium. The analysis of CAPE and STEnv over historical period (1977-2005), near future (2041-2069) and far future (2071-2099) shows significant increase in occurrence of thunderstorm in the 2071-2099s, specially in extreme cases such as 97% and 99% quantile. CAPE (J/Kg) increases in all future scenarios compared to the historical period. In 2071-2099s, CAPE increases from 2100 J/Kg to 2300 J/Kg (90% quantile) and from 3500 J/Kg to 3900 J/Kg (99% quantile) compared to the historical period. The number of STEnv increases from 300 to 378 in top 10% storm case (90% quantile), 158 to 218 in top 5% storm (95% quantile), 97 to 153 in top 3% storm (97% quantile) and 33 to 66 in top 1% storm (99% quantile) with a 90% confidence interval overall. Shear mostly remains unchanged. The study also shows spatial variation of CAPE, shear and STEnv over Belgium for present and future scenarios in different extremities (90%, 95%, 97% and 99% quantiles). There is a good indication that increase in CAPE translates to increase in STEnv, which is an accepted measure to predict occurrence of thunderstorm. Future climate change also amplifies the occurrence of thunderstorm, which is coherent with relevant studies. The uncertainty related to the study can be reduced with more detailed dataset and involvement of numerical weather prediction models beyond data statistics.

The concept of ecosystem services (ESs) provides a valuable approach to communicate societies' dependence on natural ecosystems, assisting in the evaluation of measures to protect vegetation in watersheds that promote water-related ESs. Vegetation cover and land use are important factors related to the capacity of ecosystems to provide soil loss regulation and sediment retention services, which are highly relevant for sediment management in watersheds draining into reservoirs with multiple water uses. This study aims to assess the relationship between potential changes in land use and land cover and the sediment retention service provided by riparian vegetation in a watershed draining into a hydroelectric reservoir in the Brazilian Cerrado. Sediment load was selected as a physical variable that affects different water uses in reservoirs, with these uses being dependent on the quality or quantity of stored water. Scenarios were analyzed to represent landscape reconfigurations from a baseline condition in order to account for the recovery of riparian vegetation by the agricultural sector, as foreseen in the Brazilian Forest Code. To map and quantify variations in annual sediment retention, the InVEST model was used, which allows estimating an integrated response of the drainage basin to large-scale land use changes over time and space. The results show that for the drainage basin of the Corumbá IV Hydroelectric Power Plant (HPP), the recovery of riparian areas occupied by annual crops has the potential to generate greater benefits to water use in the reservoir. In the studied catchment area, 14% of the total vegetation deficit in riparian areas is occupied by crops, while 86% is occupied by pastures. This highlights the buffering role of riparian vegetation as an effective practice for managing sediment flows originating from sheet erosion in agricultural landscapes. The methodology employed in this study allows for the quantification and mapping of the effects of soil and water conservation measures in river basins. This enables the prioritization of sectoral efforts for the restoration of native vegetation, considering the highest returns in benefits perceived by water users affected by sediment input in reservoirs. The study's results reinforce the importance of conserving vegetation in riparian areas and their surroundings for sediment retention, highlighting the role of these areas as assets in providing water-related ecosystem services.

Accurately predicting the power of solar power generation can greatly reduce the impact of the randomness and volatility of power generation on the stability of the power grid system, which is beneficial for the balanced operation and optimized dispatch of the power grid system, and reduces operating costs. Solar PV power generation depends on weather conditions, which are prone to large fluctuations under different weather conditions. Its power generation is characterized by randomness, volatility and intermittency. Recently, the demand for further investigation and effective use on the uncertainty of short-term solar PV power generation prediction has been getting increasing attention in many application of renewable energy sources. In order to improve the predictive accuracy of output power of solar PV power generation and develop a precise predictive model, the authors worked predictive algorithms for the output power of a solar PV power generation system. Moreover, since short-term solar PV power forecasting is one of the important aspects for optimizing the operation and control of renewable energy systems and electricity markets, this review focuses on the predictive models of solar PV power generation, which can be verified in the daily planning and operation of a smart grid system. In addition, the predictive methods in the reviewed literature are classified according to the input data source used for accurate predictive models, and the case studies and examples proposed are analyzed in detail. The contributions, advantages and disadvantages of the predictive probabilistic methods are compared. Finally, the future studies of short-term solar PV power forecasting is proposed.

The growing integration of renewable energy sources (RES) into the power system causes congestion to occur more frequently. In order to reduce congestion in the short term and to make the utilization of the power system more efficient in the long term, power flow control (PFC) in the transmission system has been proposed. However, exemplary studies show that congestion will increase also in the distribution system if the transmission system is expanded. For this reason, the potential of PFC to reduce congestion in a model of a real 110 kV distribution system is investigated. Several Unified Power Flow Controller (UPFC) devices are optimized in terms of their number and placement in the power system, their size, control parameters, and costs, by using a Parallel Tempering approach as well as a greedy algorithm. Two optimization variants are considered, one reducing the number of degrees of freedom by integrating system knowledge while the other is not. We find that near a critical grid state and disregarding costs, PFC can reduce congestion significantly (99.13 %). When costs of the UPFCs are taken into account, PFC can reduce congestion by 73.2 %. A basic economic analysis of the costs reveals that the usage of UPFCs is profitable. Furthermore, it is found that the reduction of the solution space of the optimization problem leads to better results faster and that, contrary to expectations, the optimization problem is simple to solve. The developed methods allow not only for the determination of the optimal use of UPFCs to minimize congestion, but also to estimate their profitability.

In various domains such as energy, manufacturing, and maritime, cyber-physical systems (CPS) have seen increased interest. Both academia and industry have focused on the cybersecurity aspects of such systems. The assessment of cyber risks in CPS is a popular research area with many existing approaches that aim to suggest relevant methods and practices. However, few works have addressed the extensive and objective evaluation of the proposed approaches. In this paper, a standard-aligned evaluation methodology is presented and empirically conducted to evaluate a newly proposed cyber risk assessment approach for CPS. The approach, which is called FMECA-ATT&CK is based on Failure Mode, Effects & Criticality Analysis (FMECA) risk assessment process and enriched with the semantics and encoded knowledge in the Adversarial Tactics, Techniques, and Common Knowledge framework (ATT&CK). Several experts were involved in conducting two risk assessment processes, FMECA-ATT\&CK and Bow-Tie, against two use cases in different application domains, particularly an autonomous passenger ship (APS) as a maritime use case and a digital substation as an energy use case. This allows for the evaluation of the approach based on a group of characteristics, namely, applicability, feasibility, accuracy, comprehensiveness, adaptability, scalability, and usability. The results highlight the positive utility of FMECA-ATT&CK in model-based, design-level, and component-level cyber risk assessment of CPS with several identified directions for improvements. Moreover, the standard-aligned evaluation method and the evaluation characteristics have been demonstrated as enablers for the thorough evaluation of cyber risk assessment methods.

Herpes simplex virus type 1 (HSV-1) is among the most widely spread viruses on the planet. However, the rate of binding to the receptor is not among the greatest ones. Gibbs energy of binding, which represents the driving force for antigen-receptor binding, of HSV-1 is less negative than can be expected. Furthermore, the Gibbs energy of biosynthesis of HSV-1 is among the most negative in nature. This implies high rate of multiplication of HSV-1. Obviously, HSV-1 uses specific strategy in virus-host interaction. While most other viruses increase infectivity through a high rate of antigen-receptor binding and cell entry/ highly negative Gibbs energy of binding, HSV-1 uses another strategy. It is related to a relatively slow reaction of antigen-receptor binding, which is followed by a higher rate of multiplication, which is a consequence of a highly negative Gibbs energy of biosynthesis. We can conclude empirically that both strategies are successful.

The product is a centrifugal air extractor, whose objective is to extract the stale air of SARS-CoV-2 or Covid-19 (Coronavirus); designed for civil and commercial use, it works with a single-phase alternating current (AC) motor of 220 (V) and 50 (Hz), with high energy efficiency (EE). Developed under the Design Thinking methodology, by electromechanical simulation using NI Multisim 14.0 software, case design using Cfturbo 2020 R2.0 CAD software, and rapid 3D prototyping with the OverLord Pro printer; with a prototype of the conventional stator winding of a synchronous motor with a two-pole PMSM/IPM single-phase alternating current (AC) field winding and a 4000 (Gauss) ferromagnetic ceramic magnet rotor. Innovating online nº 15 of invention patent nº 381968 by Nikola Tesla, 5/1/1888.One of the objectives is to link the middle level or Technical Schools with the University system (and careers with a Technological profile) through Project B374 located in the Secretariat of Science and Technology (SCyT) of the National University of La Plata ( UNLP), whose title is: “Integrated Management of Design and Innovation. Contributions for a theoretical-conceptual and methodological review” by the Director: Mg. Federico del Giorgio Solfa. Just as links were sought with the Research and Development Laboratory of the Department of Industrial Design (LIDDI-FBA-UNLP) through its Director D.I. Pablo Ungaro and D.I. Ana Bocos. In 2021, the project participated in the INNOVAR National Contest of the Ministry of Science, Technology and Productive Innovation of the Nation (MINCYT), Argentine Republic; in the "Covid-19 Projects" category, having been selected in the catalog of innovative products, won the 1st. "Covid-19 Projects" position of the National Agency for Research and Technological Development and local innovation (R+D+i) dependent on MINCYT.The results showed, according to the analysis of the test bench, that the PMSM/IPM type synchronous motor used in the centrifugal fan, with the innovation of the reactance-inductive control in series plus the capacitor in parallel, reduces the power by 67% (Watts) and active energy consumption (kWh), performing 56% more mechanical work (Joules) on the fluid air (with a 50% reduction in carbon footprint). Which leads us to the following conclusion: it is possible to develop centrifugal fans that save electricity (kWh) without the need to resort to (1) the "Fan Affinity Law", nor (2) the use of variable speed drives (VDF) or frequency (which are devices with complex and expensive electronics). Which would bring an enormous saving of the cost of electrical energy.

The majority of Candida species are known as non-pathogenic yeasts and rarely involved in human diseases. However, recently case reports of human infections caused by non-albicans Candida species have increased, mostly in immunocompromised hosts. Our study aimed to describe and caracterise as thoroughly as possible, a new species of the Candida genus, named here Candida massiliensis (PMML0037), isolated from a clinical sample of human sputum. We compared genetic data based on the sequences of four genetic regions: "Internal Transcribed Spacers" of rRNA, D1/D2 domains (28S large subunit rRNA) and part of the genes encoding Translation Elongation Factor 1-α and β-tubulin2, to morphological characters, from scanning electron microscopy (TM 4000 Plus, SU5000), physiological, including the results of oxidation and assimilation tests of different carbon sources by the Biolog system, and chemical mapping by Energy-Dispersive X-ray Spectroscopy. Lastly, the in vitro antifungal susceptibility profile was performed using the E-testTM exponential gradient method. The multilocus analysis supported the genetic position of Candida massiliensis (PMML0037) as a new species of the genus Candida, and the phenotypic analysis highlighted its unique morphological and chemical profile when compared to other Candida species included in the study.

Three isoenergetic diets differing on their fishmeal/ soy protein concentrate (SPC) ratio were assessed on tissue growth and energy budget of juvenile crabs Scylla serrata in postmolt stages (PMolt) and in intermolt stages (IMolt). The average growth rate on dry matter basis, were 2.064 ± 0.324% and 0.492 ± 0.08% initial BW.day-1 during PMolt and IMolt stages respectively. The efficiency in feed conversion (FCE, %), protein retention (PRE, %) and energy retention (ERE, %) were similar for the 3 experimental diets. However, FCE, PRE and ERE in PMolt stages were 4 to 5 times higher than in IMolt stages. Feed intake, energy and protein required for growth in PMolt stages were obviously higher than in IMolt stages. The energy budgets (%total energy intake) were marginally affected by diet but were significantly affected by the molt stage. Maintenance energy was lower in PMolt stages (49.84 ± 4.9%) than in IMolt stages (83.33 ± 2.45%). The excess of maintenance energy in IMolt stages represents the portion set aside for next molt: shell energy content (4.97 ± 0.31%) and energy for ecdysis (± 28%). Conversely, recovery energy was significantly higher in PMolt stages (34.39 ± 0.99%) than in IMolt stages (8.33 ± 1.7%). In conclusion SPC sustained good tissue growth and good feed utilization and can be used as a main source of dietary protein for crab juveniles in captivity.

Principal component analysis (PCA) is used to reduce the dimensionalities of high dimensional datasets in a variety of research areas. For example, biological macromolecules, such as proteins, exhibit many degrees of freedom, allowing them to adopt intricate structures and exhibit complex functions by undergoing large conformational changes. Therefore, molecular simulations of and experiments on proteins generate a large number of structure variations in high dimensional space. PCA and many PCA-related methods have been developed to extract key features from such structural data, and these approaches have been widely applied for over 30 years to elucidate macromolecular dynamics. This review mainly focuses on the methodological aspects of PCA and related methods, and their applications for investigating protein dynamics.

By 2020, over 100 countries expanded electric and plug-in hybrid electric vehicle (EV/PHEV) technologies, with global sales surpassing 7 million units. Governments are adopting cleaner vehicle technologies due to proven environmental and health implications of internal combustion engine vehicles (ICEVs), evidenced by the recent COP26 meeting. This article proposes an agent-based model of vehicle activity as a tool for quantifying energy consumption by simulating a fleet of EV/PHEVs within an urban street network at various spatio-temporal resolutions. Driver behaviour plays a significant role in fuel consumption, thus, simulating various levels of individual behaviour enhancing heterogeneity should provide more accurate results of potential energy demand in cities. The study found that 1) energy consumption is lowest when speed limit adherence increases (low variance in behaviour) and is highest when acceleration/deceleration patterns vary (high variance in behaviour) and 2) on average, for tested vehicles, EV/PHEVs were £116.33 cheaper to run than ICEVs across all experiment conditions. The difference in the average fuel costs (electricity and petrol) shrinks at the vehicle level as driver behaviour is less varied (more homogeneous). This research should allow policymakers to quantify the demand for energy and subsequent fuel costs in cities.

Integrating large-scale wind energy in modern power systems is demanding more efficient mathematical models to properly address classical assumptions in power system problems. In particular, there are two main assumptions in power system problems with wind integration that have not been adequately studied yet; First, non-linear AC power flow equations have been linearized in most of the literature. Such simplifications can lead to inaccurate power flow calculations that may result in other technical issues. Second, wind power uncertainties are inevitable and have been mostly modelled using the traditional uncertainty modelling approaches, that may not be suitable for large-scale wind power integration. In this paper, we address both challenges: we present a tight second-order conic relaxation (SOCR) for optimal power flow (OPF) problem, and simultaneously, implement the new effective budget of uncertainty approach for uncertainty modelling that determines the maximum wind power admissibility first and then addresses the uncertainty in the model. To the best of our knowledge, this is the first study that proposes an effective robust second-order conic programming (ERSOCP) model that simultaneously addresses the issues of power flow linearization and wind power uncertainty with the new paradigm on the budget of uncertainty approach. Our numerical results show the merit of the proposed model against traditional linearized power flow equations as well as traditional uncertainty modelling approaches.

HU is the Hypergeometrical Universe Theory (HU)[1-8], proposed in 2006, where the Universe is a Lightspeed Expanding Hyperspherical Hypersurface and Gravitation is an absolute-velocity-dependent, epoch-dependent force. Here we introduce the Big Pop Cosmogenesis and show our calculations associated with the Equation of State of the Universe. This article is the first in a series of articles[9-22] supporting the paradigm shift.

The paper deals with the Compound Inverse Rayleigh distribution, shown to constitute a proper model for the characterization of the probability distribution of extreme values of wind-speed, a topic which is gaining growing interest in the field of renewable generation assessment, both in view of wind power production evaluation and the wind-tower mechanical reliability and safety. The first part of the paper illustrates such model starting from its origin as a generalization of the Inverse Rayleigh model - already proven to be a valid model for extreme wind-speeds - by means of a continuous mixture generated by a Gamma distribution on the scale parameter, which gives rise to its name. Moreover, its validity to interpret different field data is illustrated, also by means of numerous numerical examples based upon real wind speed measurements. Then, a novel Bayes approach for the estimation of such extreme wind-speed model is proposed. The method relies upon the assessment of prior information in a practical way, that should be easily available to system engineers. In practice, the method allows to express one’s prior beliefs both in terms of parameters, as customary, and/or in terms of probabilities. The results of a large set of numerical simulations – using typical values of wind-speed parameters - are reported to illustrate the efficiency and the accuracy of the proposed method. The validity of the approach is also verified in terms of its robustness with respect to significant differences compared to the assumed prior information.

An analysis of the consistency of the Abraham and Minkowski momenta in the determination of the photon trajectory was carried out considering a new principle of conservation of the photon's mechanical energy, in which the photon conserves translational energy in orbital angular momentum when transiting between two media, introducing the relativistic energy wave (REW). The confrontation between REW and the recent theory of space-time waves (ST) was considered, pondering your differences. Throughout this study it was possible to verify that the Abraham momentum appears a relativistic photon ignition device in the transition between two media, acting as the hidden momentum of the Minkowski’s relativistic momentum. The wavy behavior in the matter is relativistic, and the relativistic trajectory appears with delays and advances, with points of synchronization between source-observer. The classical or relativistic trajectories are determined as a function of the angle of incidence and the relative refractive index, by one of two distinct non-additive torques, the classic by Abraham or the relativistic by Minkowski. It was found that the same analysis conducted under the principle of conservation of the mechanical energy of the photon can be treated by an new Doppler, Relativistic Apparent, that can be confused with other Dopplers in the treatment of redshift from distant sources. It was found that the conservation of energy in Orbital Angular Momentum (OAM), in the interaction with matter, explains that the synchronization instants are found in the inversion of the OAM, where the advances and delays of REW occur under negligible variations of the OAM, however, opposites.

The motivations for the move to electrified vehicles are discussed with reference to their improved energy efficiency, their potential for lower CO2 emissions (if the electricity system is decarbonized), their lower (or zero) NOx/particulate matter (PM) tailpipe emissions, and the lower overall costs for owners. Some of the assumptions made in life-cycle CO2 emissions calculations are discussed and the effect of these assumptions on the CO2 benefits of electric vehicles are made clear. A number of new tribological challenges have emerged, particularly for hybrid vehicles that have both a conventional internal combustion engine and a battery, such as the need to protect against the much greater number of stop-starts that the engine will have during its lifetime. In addition, new lubricants are required for electric vehicle transmissions systems. Although full battery electric vehicles (BEVs) will not require engine oils (as there is no engine) they will require a system to cool the batteries – alternative cooling systems are discussed, and where these are fluid based, the specific fluid requirements are outlined.

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating degree-day (HDD), the cooling degree-day (CDD) and the HDD+CDD were computed from an ensemble of 7 high-resolution bias-corrected simulations attained from EURO-CORDEX under RCP4.5 and RCP8.5. These three indicators were analyzed for 1971-2000 (from E-OBS) and 2011-2040 and 2041-2070, under both RCPs. Results show that the overall spatial distribution of HDD trends for the 3 time-periods points out an increase of energy demand to heat internal environments in Portugal's northern-eastern regions, most significant under RCP8.5. It is projected an increase of CDD values for both scenarios; however, statistically significant linear trends were only found for 2041-2070 under RCP4.5. The need for cooling is almost negligible for the remaining periods, though linear trend values are still considerably higher for 2041-2070 under RCP8.5. By the end of 2070, higher amplitudes for all indicators are depicted for southern Algarve and Alentejo regions, mainly under RCP8.5. For 2041-2070 the Centre and Alentejo (North and Centre) regions present major positive differences for HDD(CDD) under RCP4.5(RCP8.5), within the 5 NUTS II regions predicting higher heating(cooling) requirements for some locations.

Abstract: Wireless body area networks (WBANs) have strong potential in the field of health monitoring. However, the energy consumption required for accurate monitoring limits the time between battery charges of the wearable sensors, which is a key performance factor (and can be critical in the case of implantable devices). In this paper, we study the inherent trade-off between the power consumption of the sensors and the probability of misclassifying a patient’s health state. We formulate this trade-off as a dynamic problem, in which at each step we can choose to activate a subset of sensors that provide noisy measurements of the patient’s health state. We assume that the (unknown) health state follows a Markov chain, so our problem is formulated as a partially observable Markov decision problem (POMDP). We show that all the past measurements can be summarized as a belief state on the true health state of the patient, which allows tackling the POMDP problem as an MDP on the belief state. We then empirically study the performance of a greedy one-step look-ahead policy compared to the optimal policy obtained by solving the dynamic program. For that purpose, we use an open-source Continuous Glucose Monitoring (CGM) data set of 232 patients over six months and extract the transition matrix and sensor accuracies from the data. We find that the greedy policy saves ~50% of the energy costs while reducing the misclassification costs by less than 2% compared to the most accurate policy possible that always activates all sensors. Our sensitivity analysis reveals that the greedy policy remains nearly optimal across different cost parameters and a varying number of sensors. The results also have practical importance, because while the optimal policy is too complicated, a greedy one-step look-ahead policy can be easily implemented in WBAN systems.

This paper discusses domestic problem of waiting hot water for the shower use till it reaches satisfactory temperature, which result a lot of wastage in fresh water. The outcome from research survey shows that there is no satisfactory solution till now as all solutions were either expensive or with no effective results. Local small inline electric heater equipped with fuzzy logic controller is proposed in this paper to be installed just before the showerhead to measure the water temperature and flow before the showerhead, as control input-variables, and decide the operating voltage of the heater, as control output-variable (MISO). MATLAB Simulink is used to model the proposed system. Different test cases are simulated to prove the performance and the safe operation of the system. Techno-economic study is carried out to determine the “Direct Benefits” and “Indirect Benefits” that can be achieved if such system is implemented in wide range. Azerbaijan data is taken as an example to calculate the economic benefits. The results show important benefits not only for economy but also for climate and the reduction of CO₂ gas emission. Different economic indices are provided to be an easy reference for decision makers and project managers.

Adequate energy intake is critical for the healthy longevity of older adults, and the estimated energy requirement is determined by total energy expenditure (TEE). We aimed to identify the relationship between measured aerobic capacity and TEE, activity energy expenditure (AEE) or physical activity level (PAL) with the doubly labeled water (DLW) methods in the advanced older adults. A total of 12 physically independent older adults (10 males and 2 females) aged between 81 to 94 years participated in this study. Aerobic capacity was evaluated according to the lactate threshold (LT). TEE under free-living conditions was assessed using the DLW method, and self-reported physical activity was obtained through the Japanese version of the International Physical Activity Questionnaire (IPAQ). LT was significantly positively correlated with TEE, AEE, and PAL after adjustment for age and sex (ρ= 0.77 (P<0.01), 0.86 (p<0.01), and 0.86 (p<0.01), respectively). We found the LT as an aerobic capacity is positively and independently correlated with TEE, AEE or PAL. The present results suggest that maintaining aerobic capacity is an important factor for preventing frailty, although further research is needed to multisite studies and many samples.

A simplified nonlinear dispersive system of BBM-type, initially derived by D. Mitsotakis, is employed here in order to model the generation and propagation of surface water waves over variable bottom. The simplification consists in applying the so-called Boussinesq approximation. Using the finite element method and the FreeFem++ software, we solve numerically this system for three different complexities for the bathymetry function: a flat bottom case, a variable bottom in space, and a variable bottom both in space and in time. The last case is illustrated with the Java 2006 tsunami event. This article is designed rather as a tutorial paper even if it contains the description of completely new adaptation techniques.

IoT system becomes hot topic nowadays for smart home, IoT helps devices to communicate together without human intervention inside home, so it is offering many challenges. A new smart home IoT platform powered using electromagnetic energy harvesting is proposed in this paper. It contains a high gain transmitted antenna array and efficient circular polarized array rectenna system to harvest enough power from any direction to increase life time of the batteries used in IoT system. Optimized energy consumption, the software with adopting the Zigbee protocol of the sensor node and low power microcontroller are used to operate in lower power modes. The proposed system has an 84.6 days lifetime which is approximately 10 times the lifetime for similar system. On the other hand, the proposed power management circuit operated at 0.3 V DC to boost the voltage to ~3.7V from radio frequency energy harvesting and manage battery level to increase the batteries lifetime. A predictive indoor environment monitoring system is designed based on a novel hybrid system to provide a non-static plan, approve energy consumption and avoiding failure of sensor nodes in smart home.

The interaction between spinors and gravity is the most complicated and subtle interaction in the universe, which involves the basic problem to unified quantum theory and general relativity. By means of Clifford Algebra, a unified language and tool to describe the rules of nature, this paper systematically discusses the dynamics and properties of spinor fields in curved space-time, such as the decomposition of the spinor connection, the classical approximation of Dirac equation, the energy momentum tensor of spinors and so on. To split spinor connection into Keller connection $\Upsilon_\mu\in\Lambda^1$ and pseudo-vector potential $\Omega_\mu\in\Lambda^3$ by Clifford algebra not only makes the calculation simpler, but also highlights their different physical meanings. The representation of the new spinor connection is dependent only on the metric, but not on the Dirac matrix. Keller connection only corresponds to geometric calculations, but the potential $\Omega_\mu$ has dynamical effects, which couples with the spin of a spinor and may be the origin of the celestial magnetic field. Only in the new form of connection can we clearly define the classical concepts for the spinor field and then derive its complete classical dynamics, that is, Newton's second law of particles. To study the interaction between space-time and fermion, we need an explicit form of the energy-momentum tensor of spinor fields. However, the energy-momentum tensor is closely related to the tetrad, and the tetrad cannot be uniquely determined by the metric. This uncertainty increases the difficulty of deriving rigorous expression. In this paper, through a specific representation of tetrad, we derive the concrete energy-momentum tensor and its classical approximation. In the derivation of energy-momentum tensor, we obtain a spinor coefficient table $S^{\mu\nu}_{ab}$, which plays an important role in the interaction between spinor and gravity. From this paper we find that, Clifford algebra has irreplaceable advantages in the study of geometry and physics.

An adequate number of waste management facilities is the key element to meet circular economy goals. Using empirical data taken from official sources the research framework bases on an econometric model to compare the elasticity of cost on quantity of different alternatives such as waste-to-energy facilities, mechanical biological facilities and landfills impact on waste management cost. Results suggest that both waste-to-energy facilities (-0.278%) and landfills (-0.38%) concur to lower the cost while the higher the percentage of waste sent to mechanical biological treatment facilities, the higher the cost (0.788%). This figure deserves to be examined in more details as such facilities represent an intermediary step in the chain which efficiency depends on the industrial organization of the chain.

Recent astronomical observations with respect to measurements in distant supernovas, cosmic microwave background and weak gravitational lensing confirm that the Universe is undergoing a phase of accelerated expansion and it has been proposed that this cosmological behavior is caused by a hypothetical dark energy which has a strong negative pressure that allows explain the expanding universe. Several theoretical ideas and models related dark the energy includes the cosmological constant, quintessence, Chaplygin gas, braneworld and tachyonic scalar fields. In this paper, we have obtained new relativistic stellar configurations considering an anisotropic fluid distribution with a charge distribution which could represents a potential model of a dark energy star. In order to investigate the effect of a quadratic equation of state in this anisotropic model we specify particular forms for the gravitational potential that allow solving the Einstein-Maxwell field equations. For these new solutions we checked that the radial pressure, metric coefficients, energy density, anisotropy factor, charge density , mass function are well defined and are regular in the interior of the star. The solutions found can be used in the development of dark energy stars models satisfying all physical acceptability conditions but the causality condition and strong energy condition are violated. We expect that these models have multiple applications in astrophysics and cosmology.

This study deals with computational analysis of dominant fatty acid ethyl esters characterized from the biodiesel produced from waste beef tallow by means of KOH catalyzed ethanol based transesterification. Ethyl palmitate, Ethyl Oleate, Ethyl Stearate and Ethyl Myristate were identified as dominant fatty acid esters and were computed for molecular analysis in Gaussian 09 software using Density Functional Theory (B3LYP method) with 6-31G* as basis set. Geometric parameters were in accordance with existing experimental values and population analysis exhibited negative charge for oxygen atoms, both positive & negative charge for carbon atoms in all ester molecules. The molecular dipole moment was higher for unsaturated ester molecule and quadruple moment proposed electronic dislocation in X+Y direction. Also, energy gap decreased slightly with increasing carbon chain but reduced drastically with increase in unsaturation. Electrostatic potential mapping displayed negative electrostatic potential for oxygen atoms in ester linkage of all ester molecules.

Strip-mined land (SML) disturbed by coal-mining is the non-crop land resource that can be utilized to cultivate high-yielding energy crops such as miscanthus for bioenergy applications. However, the biomass yield potential, annual availability and environmental impacts on growing energy crops in SML are less understood. In this study, we estimated the yield potential of miscanthus (Miscanthus sinensis) in SML and its environmental impacts on local streams using the Soil and Water Assessment Tool (SWAT). After calibration and validation of the SWAT model, the results demonstrated that miscanthus yield potentials were 2.6 (0.8−5.53), 10.0 (1.3−16.0) and 16.0 (1.34−26.0) Mg ha^-1 with the fertilizer application rate of 0, 100, and 200 kg-N ha^-1 respectively. Furthermore, cultivation of miscanthus in the SML has the potential to reduce sediment (~20%) and nitrate (2.5%−10.0 %) loads reaching to water streams with a marginal increase in phosphorus load. The available SML in the United States could produce about 10 to 16 dry Tg of biomass per year without negatively impacting the water quality. In conclusion, SML can provide a unique opportunity to produce biomass for bioenergy applications, while improving stream water quality in highly dense mining area (the Appalachian region) in the United States.

TThe number of supermarkets offering a grocery delivery has been increasing during the last years. Many studies deduce CO₂ emission savings using this concept. Since the delivery of groceries also consumes energy and produces emissions, break-even points can be calculated, from where the delivery has environmental advantages compared to the customer pickup. In this paper, influences of differing vehicle use on break-even points for savings of energy and CO₂ emissions are analyzed for the case of Haidhausen Süd, a city district of Munich in Germany. Internal combustion engine and electric vehicles are investigated to depict current as well as future trends. After an introduction to the used methodology, the potential to save energy and CO₂ emissions related to the delivery of groceries in the chosen district of Munich is evaluated. Afterwards, influences on the break even points are presented and discussed. As the results show, a delivery of groceries leads to energy and carbon dioxide savings in a wide range of private vehicle use for grocery shopping trips. Nevertheless, if the complete customer vehicle fleet is electrified, the use of delivery vehicles with an internal combustion engine can cause an additional environmental impact at the current modal split for shopping trips in Germany.

The cosmological relevance of emptiness—that is, space without bodies—is not yet sufficiently appreciated in natural philosophy. This paper addresses two aspects of cosmic emptiness from the perspective of natural philosophy: the distances to the stars in the closer cosmic environment and the expansion of space as a result of the accelerated expansion of the universe. Both aspects will be discussed from both a historical and a systematic perspective. Emptiness can be interpreted as “coming” in a two-fold sense: Whereas in the past knowledge of emptiness as it were came to human beings, in the future it is coming insofar as its relevance in the cosmos will increase.The longer and more closely emptiness was studied since the beginning of modernity, the larger became the spaces over which it was found to extend. From a systematic perspective, I will show with regard to the closer cosmic environment that the earth may be separated from the perhaps habitable planets of other stars by an emptiness that is inimical to life and cannot be traversed by humans. This assumption is a result of the discussion of the constraints and possibilities of interstellar space travel as defined by the known natural laws and technical means. With the accelerated expansion of the universe, the distances to other galaxies (outside of the so-called local group) are increasing. According to the current standard model of cosmology and assuming that the acceleration will remain constant, in the distant future this expansion will lead first to a substantial change in the epistemic conditions of cosmological knowledge and finally to the completion of the cosmic emptiness and of its relevance, respectively. Imagining the postulated completely empty last state leads human thought to the very limits of what is conceivable.

The operation of electricity and natural gas transmission networks in the U.S. are increasingly interdependent, due to the growing number of installations of gas fired generators and the penetration of renewable energy sources. This development suggests the need for closer communication and coordination between gas and power transmission system operators in order to improve the efficiency and reliability of the combined energy system. In this paper, we present a co-simulation platform for examining the interdependence between natural gas and electricity transmission networks based on a direct current unit-commitment and economic dispatch model for the power system and a transient hydraulic gas model for the gas system. We analyze the value of day-ahead coordination of power and natural gas network operations and show the importance of considering gas system constraints when analyzing power systems operation with high penetration of gas generators and renewable energy sources. Results show that day-ahead coordination contributes to a reduction in curtailed gas during high stress periods (e.g., large gas offtake ramps) and a reduction in energy consumption of gas compressor stations.

The water cushion depth of stilling basin with shallow-water cushion is a key factor that affects the flow regime of hydraulic jump in the basin. However, the specific depth at which the water cushion is considered as “shallow” has not be stated clearly for now, and only conceptual description is provided. This paper attempts to specify the best water cushion depth based on the flow regime of hydraulic jump and underflow speed; namely, in case of critical hydraulic jump in the basin, the best water cushion depth is located where the minimum distance to the bottom plate of the stilling basin is 1/5~1/4 of the water cushion depth. The theoretical analysis indicates, at different inclinations of discharge chute (θ) and depth ratios of inlet (m), instead of monotonic change, the Froude number (Fr) at inlet of the stilling basin with shallow-water cushion firstly reduces and then increases as the flow velocity at discharge chute inlet (V) increases; the parameters of inflection point (critical flow velocity and critical Fr) increase as the inclinations of discharge chute (θ) and depth ratios of inlet (m) increase. Such regularity is the theoretical basis for selecting representative study cases. The reliability of the large eddy simulation calculation results are verified by a model test; in the paper, 30 cases including five different Froude numbers and six shallow-water cushion depths are selected, for calculating the hydraulic factors such as flow profile, flow regime and flow velocity in the stilling basin with shallow-water cushion; and the varying pattern between the best depth of stilling basin with shallow-water cushion (depth-to-length ratio) and the inflow Froude number is obtained which indicates that the best depth of stilling basin with shallow-water cushion varies little as the change of the Froude number before reaching the critical Froude number; however, the best depth-to-length ratio of stilling basin with shallow-water cushion increases as the Froude number increases after the critical Froude number is reached. The study results in this paper are of reference significance to design and calculation of the stilling basin with shallow-water cushion.

We have studied the relative positions of the frontier levels determine the main electronic properties and reaction ability, there is important necessity to compare the MO of the purine and рyrimidine bases: adenine (A), guanine (G), cytosine (C), thymine (T) and uracil (U). The donor and acceptor properties are the fundamental characteristic of the conjugated molecules and can be quantitatively estimated by relative positions of the frontier molecular orbitals. The MO’s energies can be estimated experimentally or quantum-chemically. Analysis of the relative position of the frontier levels (calibrated by the energy gap) enables the investigation of the donor/acceptor properties of the RNA/DNA bases more detailed. The index φ0 is proposed for the quantitative quantum-chemical estimation of the donor ability of the conjugated molecules: it points on the shifting of the energy gap relative to the reference electron balanced system. The RNA/DNA bases divided strictly by two groups: predominantly donors (φ0 > 0.5) and predominantly acceptors (φ0 > 0.5). Each representative base of the first group forms the stable base pair the representative base of the second group the difference of indices Δφ0 should be optimal to enables the DNA replication.

Motivated by diffraction experiments on the $\left(2\sqrt{3}\times \sqrt{3}\right)\mathrm{R}{30}^{\circ }$ reconstructed Si(111) due to deposition of rare earth elements (Dy, Tb) and silicide formation we analyse the splitting and non-splitting of superstructure spots. For this purpose, we model diffraction patterns for one dimensional structures generated by the binary surface technique and use supercell models to keep the analysis simple. Diffraction pattern are calculated in the framework of the kinematical diffraction theory and they are analyzed as a function of the domains and domain boundaries. Basic properties of the diffraction pattern are analyzed for model systems of a two-fold and a three-fold periodicity. The rules derived from these calculations are applied to the "real-world" system of Si(111)-($\left(2\sqrt{3}\times \sqrt{3}\right)\mathrm{R}{30}^{\circ }$)-RESi$2_{}$ (RE = Dy or Tb). Depending on the combination of domains and domain boundaries of different types a plethora of different features are observed in the diffraction patterns. These are analyzed to determine the sizes of both domain boundaries and domains from experimentally observed splitting of specific superstructure spots.

Non-melanoma skin cancers (NMSCs), including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), are highly prevalent and a significant cause of morbidity. Image-guided su-perficial radiation therapy (IGSRT) uses integrated high-resolution dermal ultrasound to improve lesion visualization, but it is unknown whether efficacy varies by histology. This large retro-spective cohort study was conducted to determine the effect of tumor histology on freedom from recurrence in 20,069 biopsy-proven NMSC lesions treated with IGSRT, including 9,928 BCC (49.5%), 5,294 SCC (26.4%), 4,648 SCCIS (23.2%), and 199 lesions with ≥2 NMSCs (1.0%). Freedom from recurrence at 2, 4, and 6 years was 99.60%, 99.45%, and 99.45% in BCC; 99.58%, 99.49%, and 99.49% in SCC; and 99.96%, 99.80%, and 99.80% in SCCIS. Freedom from recurrence at 2, 4, and 6 years following IGSRT did not differ significantly comparing BCC vs. non-BCC or SCC vs. non-SCC but were slightly lower among SCCIS vs. non-SCCIS (p = 0.002). There were no significant differences in freedom from recurrence when stratifying lesions by histologic subtype. This study demonstrates that there is no significant effect of histology on freedom from recurrence in IGSRT-treated NMSC except in SSCIS. These findings support IGSRT as a first-line therapeutic option for NMSC regardless of histology.

Previous research has indicated that ultra-high pressure (UHP) technology is useful in speeding up the extraction process of cold brew (CB) coffee. However, the impact of different degrees of roasting on UHP CB coffee is still unclear. Therefore, this study aimed to investigate the effects of three different degrees of roasting (light, medium, and dark) on the physicochemical and flavor characteristics of UHP CB coffee. The results of this study showed that most physicochemical characteristics of UHP coffee were similar to those of conventional CB coffee, regardless of the degree of roasting. However, the majority of physicochemical characteristics, non-volatile components, and sensory evaluation significantly increased with an increase in roasting degree. The HS-SPME-GC/MS analysis showed that most volatile components, such as pyrazines, furans (except furfural), esters, pyrrole, pyridine, and most aldehydes, increased from light to dark roasting, and this was significantly evident in CB coffee compared with UHP. The content of volatile components in UHP coffee was significantly (P<0.05) higher than that in CB coffee at the same degree of roasting, especially with dark roasting. The combination of orthogonal partial least squares-discriminant analysis (OPLS-DA) and principal component analysis (PCA) indicated that the distance between coffee samples at different degrees of roasting under CB coffee was greater than that under UHP coffee. However, the distance between these two extraction methods at medium roasting was evidently closer than that at light and dark roasting. Moreover, 15 representative differential compounds, such as were Hazelnut pyrazine, linalool, butane-2,3-dione, 3- methylbutanal found by the calculation of odor-active values (OAVs) indicating the main contributing compounds to odor. Overall, the effect of roasting degrees on UHP coffee was less than that on CB coffee, which was consistent with the results of physicochemical characteristics, volatile components, and sensory evaluation.

High-frequency circuit performance is significantly impacted by impedance variations, particularly within the low-resistance regime. Traditional Ohm’s Law based modeling approaches often fail to accurately predict circuit behavior in these conditions, leading to design inaccuracies and potential system failures. The Standard Ohm’s Law based model’s prediction of infinite current as resistance approaches zero is physically unrealistic and hinders its application in practical scenarios. Despite the recognition of these limitations, existing models have not comprehensively addressed the complex impedance behavior observed in high-frequency circuits. To overcome these challenges, this paper introduces a modified version of the Ohm’s Law incorporating an exponential correction term. The Modified Ohm’s Law’s accuracy was evaluated through simulated experiments across a wide frequency range (1kHz to 1GHz) using various electronic components. The findings demonstrate the superior performance of the modified model in predicting currents under low-resistance and high-current conditions compared to the Standard Ohm’s Law model. By providing finite and accurate current values, the proposed model effectively mitigates the unrealistic infinite current predictions of the standard approach. The enhanced predictive capabilities of the Modified Ohm’s Law hold significant implications for high-frequency circuit design and analysis. Its application can lead to improved performance and reliability in power electronics, telecommunications, and other high-frequency systems. By incorporating non-linear impedance behavior, the model offers a more accurate representation of real-world circuit conditions. Future research should focus on refining the exponential term’s parameters to optimize the model's accuracy across a broader range of applications. Additionally, real-time implementation and hardware validation are essential to assess the model's practical utility in complex circuit environments.

Several cities are experiencing an increase in flood hazard and exposure, and consequentially in flood risk, attributable to the coupled effect of climate change and urbanization. Non-structural protection strategies demonstrate significant potential in the short term for mitigating hydraulic risk in urban areas, particularly where the implementation of structural measures is impeded by a complex urban environment. This work proposes an Early Warning System (EWS) for fluvial floods developed for the city of Palermo (Italy). It is based on the preliminary definition of po-tential Flood Event Scenarios (FESs) as a function of typical potential precursors. Each FES pre-dicts first points of flooding, flood areas and water depths, also providing specific hazard maps for people, vehicles, and buildings. The EWS uses rainfall depth-duration thresholds to assess the expected hydrograph as a function of rainfall forecasts and the water stage observed in real time at an upstream section of the river crossing the city. This last also allows for estimating the ante-cedent wetness conditions. Based on this information, the EWS retrieves an expected FES from a pre-built library with a preannouncement time up to 36 h. The EWS is here successfully tested on a historical flood event.

In our study, we investigated the prognostic significance of hematological markers—NLR (Neutrophil-to-Lymphocyte Ratio), PLR (Platelet-to-Lymphocyte Ratio), and RDW-CV (Red Blood Cell Distribution Width - Coefficient of Variation)—in 117 glioblastoma patients. Data collected from January 2016 to December 2018 included demographics, clinical scores, and treatment regimens. Unlike previous research, which often examined these markers solely before surgery, our unique approach analyzed them at multiple stages: preoperative, postoperative, and before adjuvant therapies. We correlated these markers with overall survival (OS) and progression-free survival (PFS) using statistical tools, including ANOVA, Cox regression, and Kaplan-Meier survival analyses, employing SPSS version 29.0. Our findings revealed notable variations in NLR, PLR, and RDW-CV across different treatment stages. NLR and PLR decreased after surgery, with some stabilization post-STUPP phase (NLR: p=0.007, η2p=0.06; PLR: p=0.001, η2p=0.23), while RDW-CV increased post-surgery and during subsequent treatments (RDW-CV: p &lt; 0.001, η2p=0.67). Importantly, we observed significant differences between the preoperative phase and other treatment phases. Additionally, higher NLR and RDW-CV at the second-line treatment and disease progression were associated with an increased risk of death (NLR at 2nd line: HR=1.03, p=0.029; RDW-CV at progression: HR=1.14, p=0.004). We proposed specific marker cutoffs that demonstrated significant associations with survival outcomes when applied to Kaplan-Meier survival curves (NLR at 2nd line &lt; 5: p&lt;0.017; RDW-CV at progression &lt; 15: p=0.007). Elevated NLR and RDW-CV at later treatment stages correlated with poorer OS and PFS. No significant preoperative differences were detected. These biomarkers may serve as non-invasive tools for glioblastoma management.

: Image guided superficial radiation therapy (IGSRT) combines superficial radiation therapy (SRT) with full dermal visualization (FDV) via high resolution dermal ultrasound (HRDUS) for the treatment of non-melanoma skin cancer (NMSC). The gold standard for IGSRT delivery includes a comprehensive cancer care model with support for the dermatologists by a multidisciplinary team. When delivered in this model, IGSRT can achieve cure rates of 99% for treatment of NMSC. This paper focuses on the benefits of IGSRT during therapy. Medical records from 7 dermatology clinics of 883 patients with 1,507 cases of NMSC treated with IGSRT be-tween 2017 and 2018 were retrospectively reviewed. 92% of the NMSC lesions showed daily depth fluctuations, 60.32% of lesions did not require changes during therapy, and nearly 40% of lesions required at least one compensatory change during therapy. 83% of NMSC lesions were labeled high-risk based on the 2024 NCCN guidelines. Increasing and decreasing tumor depth measurements during IGSRT inform dermatologists when adaptive changes in energy (kV), TDF and dose will result in more efficacy and less toxicity, respectively.

Diagnosis and treatment of Attention-Deficit/Hyperactivity Disorder (ADHD) in women remain insufficient. Fluctuations of reproductive hormones during the premenstrual period, postpartum period and (peri)menopause are neglected, even though they impact ADHD symptoms and as-sociated mood disorders [1]. Therefore, we created a female-specific treatment group for women with ADHD and premenstrual worsening of ADHD and/or mood symptoms. We describe the group programme and underlying rationale, offering a qualitative analysis of the participants’ evaluation. The 7 two-weekly sessions foreground the menstrual cycle and address several ADHD-specific topics in relation to this cyclical pattern: emotional regulation; impulsivity; setting boundaries, and triggers. Concurrently, women track their menstrual cycle and (fluctuating) ADHD and mood symptoms with an adjusted premenstrual calendar. In total, 18 women (25-47yrs) participated in three consecutive groups. We analysed the evaluation of the last group. Participants experienced the group as a safe and welcoming space. Recognition was valued by all. The topics discussed were deemed valuable and the structure suited them well. Completing the premenstrual calendar augmented awareness and recognition of individual cyclical symptoms. Discussing ADHD throughout the lifespan increased self-understanding. Participants took their menstrual cycle more seriously, prioritising self-acceptance and self-care in the luteal phase of the cycle. Exploring a cyclical approach in a group setting seems to be a positive addition to treatment for female ADHD.

Background: The scaffold protein tyrosine kinase substrate 4 (TKS4) undergoes tyrosine phos-phorylation by the epidermal growth factor receptor (EGFR) pathway via Src kinase. The TKS4 deficiency in humans is responsible for the manifestation of a genetic disorder known as Frank-Ter Haar syndrome (FTHS). Based on our earlier investigation, the absence of TKS4 triggers migration, invasion, and epithelial-mesenchymal transition (EMT)-like phenomena while concurrently suppressing cell proliferation in HCT116 colorectal carcinoma cells. This indicates that TKS4 may play a unique role in the progression of cancer. In this study, we demonstrated that the enhancer of zeste homolog 2 (EZH2) and the histone methyltransferase of polycomb repressive complex 2 (PRC2) are involved in the migration, invasion, and EMT-like changes in TKS4-deficient cells (KO). EZH2 is responsible for the maintenance of the trimethylated lysine 27 on histone H3 (H3K27me3). Methods: We performed the transcriptome sequencing, chromatin immunoprecipitation, protein and RNA quantitative studies, cell mobility, invasion, and proliferation studies combined with/without EZH2 activity inhibitor 3-deazanoplanocine (DZNep) Results: We detected an elevation of global H3K27me3 levels in the TKS4 KO cells, which could be reduced with treatment with DZNep, an EZH2 inhibitor. Inhibition of EZH2 activity reversed the phenotypic effects of the knockout of TKS4, reducing the migration speed and wound healing capacity of the cells as well as decreasing the invasion capacity, while the decrease in cell prolif-eration became stronger. In addition, inhibition of EZH2 activity also reversed most epithelial and mesenchymal markers. We investigated the wider impact of TKS4 deletion on the gene expression profile of colorectal cancer cells using transcriptome sequencing of wild-type and TKS4 knockout cells, particularly before and after treatment with DZNep. Additionally, we observed changes in the expression of several protein-coding genes and long non-coding RNAs that showed a recovery in expression levels following EZH2 inhibition. Conclusions: Our results indicate that the removal of TKS4 causes a notable disruption in the gene expression pattern, leading to the disruption of several signal transduction pathways. Inhibiting the activity of EZH2 can restore most of these transcriptomics and phenotypic effects.

The exploration of three-dimensional (3D) DNA structures marks a pivotal shift in genomics, offering unprecedented insights into the intricacies of cellular regulation, disease genesis, and the potential for novel diagnostic and therapeutic strategies. This study delves into the dynamic nature of 3D genome organization, investigating how these structures influence cellular functions in response to environmental changes and over time. Through a combination of real-time imaging and advanced computational models, we aim to unravel the complex interplay between 3D DNA structures, non-coding RNAs, and chromatin organization, and their collective impact on gene expression and cellular differentiation. A significant focus is placed on understanding the role of 3D DNA structures in the development and progression of genetic disorders. By employing comprehensive genomic and epigenomic profiling, this research seeks to identify structural aberrations linked to diseases, paving the way for the development of targeted diagnostics and therapies. Additionally, the study explores the potential of genome editing technologies, such as CRISPR-Cas systems, in correcting these structural abnormalities, while also addressing the ethical, legal, and social implications (ELSI) of such interventions. Integrating data from various genomic analyses, we propose the development of advanced computational models to predict the effects of 3D DNA structures on gene expression and cellular function. This integrative approach not only promises to enhance our understanding of genomic regulation but also sets the stage for groundbreaking advances in genomics-based diagnostics and therapeutics. The findings of this study have the potential to revolutionize our approach to treating genetic disorders, offering a new frontier in personalized medicine.

This article discusses how, in today’s world of disruptive and dramatic social change (DSC), non-sports related coaching, which includes a wide range of services such as life coaching, career coaching, executive coaching, and team coaching, can inadvertently fuel undesirable social dynamics. There is little or no awareness of this risk among coaches and coachees. The global, fast-growing, multi-billion-dollar industry aimed at supporting people and organisations to perform better and increase wellbeing while managing and adapting to change has been developed with limited sociological input. The article is based on 15 years of social constructionist-informed reflective practice by a sociologist-turned-coach, and uses a multi-layered autoethnographic account to argue for a sociologically informed paradigm shift in coaching, as well as relevant sociological knowledge and social and human sciences research methodology in coaches’ education. It presents the rationale and key features of a new coaching approach that places DSC-relevant sociological concepts at the heart of the coaching process, helps people develop psycho-sociological awareness, and uses a learning-to-develop through research design. A new definition of coaching to address DSC is derived. Coaching practitioners will find DSC-relevant sociological concepts, critical reflections, coaching questions, and procedures to expand coaching effectiveness. Interdisciplinary research topics combining coaching sociology and coaching psychology are suggested.

This study investigates the emergence of ertapenem-resistant, meropenem-susceptible (ErMs) among non-carbapenemase producing (NCP) and carbapenemase producing (CP) Escherichia coli and Klebsiella pneumoniae. As mutations for ertapenem resistance establish the genetic background for non-carbapenemase meropenem resistance, there is a great need for antibiotic stewards and researchers to understand the determinants of a strain’s propensity to become resistant. Whole genome sequencing was conducted on clinical carbapenem-resistant E. coli (CREC) and K. pneumoniae (CRKP) across 5 hospitals in San Antonio, U.S. from 2012-2018. The majority of carbapenem resistant Enterobacterales (CRE) were NCP (54%; 41/76). The blaCTX-M was found to be most prevalent among NCP isolates (p = 0.02). LC-MS/MS analysis of carbapenem hydrolysis revealed that blaCTX-M-mediated carbapenem hydrolysis, indicating the need to reappraise the term, “non-carbapenemase (NCP)” for quantitatively uncharacterized CRE strains harboring blaCTX-M. Antimicrobial susceptibility results showed that 56% of all NCPE isolates had an ErMs phenotype (NCPE vs. CPE, p &lt; 0.001), with E. coli driving the phenotype (E. coli vs. K. pneumoniae, p &lt; 0.001). ErMs strains carrying blaCTX-M, had approximately 4-fold more copies of blaCTX-M than ceftriaxone-resistant but ertapenem and meropenem susceptible (EsMs) isolates (3.7 v. 0.9, p &lt; 0.001). ErMs also carried more mobile genetic elements (MGEs), particularly IS26 composite transposons, than EsMs (37 vs. 0.2, p &lt; 0.0001). Immunoblot analysis demonstrated the absence of OmpC expression in NCP-ErMs E. coli, with 92% of strains lacking full contig coverage of ompC. Overall, this work provides evidence of a collaborative effort between blaCTX-M and OmpC in NCP strains that confer resistance to ertapenem but not meropenem. To thwart potential mismanagement of CRE infected patients, future efforts should focus on understanding the mechanism(s) underlying OmpC loss, developing rapid methods to detect blaCTX-M copy number variants, and targeted antimicrobials for NCPE and ErMs strains.

In the evolving landscape of Portfolio Management (PM), the fusion of advanced machine 1 learning techniques with traditional financial methodologies has opened new avenues for innovation. 2 Our study introduces a cutting-edge model combining Deep Reinforcement Learning (DRL) with 3 a Non-stationary Transformer architecture. This model is specifically designed to decode complex 4 patterns in financial time series data, enhancing portfolio management strategies with deeper insights 5 and robustness. It effectively tackles the challenges of data heterogeneity and market uncertainty, 6 key obstacles in PM. Our approach integrates key macroeconomic indicators and targeted news 7 sentiment analysis into its framework, capturing a comprehensive picture of market dynamics. This 8 amalgamation of varied data types addresses the multifaceted nature of financial markets, enhancing 9 the model’s ability to navigate through the complexities of asset management. Rigorous testing 10 demonstrates the model’s efficacy, highlighting the benefits of blending diverse data sources and 11 sophisticated algorithmic approaches in mastering the nuances of PM.12

The goal of this study was to evaluate the feasibility of methods based on the Worldwide Harmonized Light-Duty Vehicles Test Procedure Brake Cycle to measure brake wear particle emissions for currently used electrified vehicles. Our results indicated that reducing brake friction work reduced brake wear particle emissions. Commercially available, plug-in hybrid electric vehicles reduced emissions by 85% for PM₁₀, 78% for PM_2.5, and 87% for particle numbers (PNs) compared to vehicles with internal combustion engines. Brake friction work showed a linear relationship with PM₁₀ and PM_2.5. Nanoparticle PM emissions tended to increase slightly with regenerative braking, but did not contribute significantly to the overall PM percentage. the emission events of high number concentrations of nuclei mode particles (<20 nm in diameter) in electric vehicle brake assemblies designed for regenerative braking use under high-temperature, high-load braking conditions with full-friction brakes. The nuclei mode particles amplified the PN emissions and led to a high variability. In strict regulatory certification tests, where measurement reproducibility and stability are required, it is appropriate to measure PNs under brake conditions appropriate for the actual use of electric vehicles rather than under full-friction brake conditions or to remove particle measurements smaller than 20 nm.

This study investigated co-constructed research poetry as a way to understand the lived experiences of people affected by rarer dementia and as a means to use poetry to convey those experiences to healthcare professionals. Using mixed-methods, 71 people living with rarer dementia and care-partners (stakeholders) contributed to co-constructing 27 poems with professional poets; stakeholders’ verbatim words were analysed with descriptive qualitative analysis. Stakeholders were also surveyed and interviewed about their participation. Healthcare professionals (n = 93) were surveyed to elicit their responses to learning through poetry and its acceptability as a learning tool. Poems conveyed a shared narrative of different aspects of lived experience, often owing to atypical symptoms, misunderstandings by professionals, lack of support pathways, and a continuous struggle to adapt. Stakeholder surveys indicated it was a valuable experience to both co-create and respond to the poems, whilst group interviews revealed people’s experiences of the research poetry were characterised by reflection on lived experience, curiosity and exploration. Healthcare professionals’ responses reinforced the poetry’s capacity to stimulate cognitive and affective learning specific to rare dementia support and prompt both empathy and critical thinking in practice. As the largest poetry-based study that we are aware of, this novel accessible approach of creating group poems yielded substantial information about the experiences and needs of those affected by rarer dementia and how poetry can contribute to healthcare education and training.

The complexity of modern power grids, exacerbated by integrating diverse energy sources, espe-cially inverter-based resources (IBRs), presents a significant challenge to grid operation and plan-ning since linear models fail to capture the intricate IBR dynamics. This study employs the Sparse Identification of Nonlinear Dynamics (SINDy) method to bridge the gap between theoretical un-derstanding and practical implementation in power system analysis. It introduces the novel Volterra-based Nonlinearity Index (VNI) to examine system-level nonlinearity comprehensively. The distinction of dynamics into first-order linearizable terms, second-order nonlinear dynamics, and third-order noise elucidates the intricacy of power systems. The findings demonstrate a fundamental shift in system dynamics as power sources transit to IBRs, revealing system-level nonlinearity compared to module-level nonlinearity in conventional syn-chronous generators. The VNI quantifies nonlinear-to-linear relationships, enriching our comprehension of power system behavior and offering a versatile tool for distinguishing between different nonlinearities and visualizing their distinct patterns through the proposed VIN profile.

In the past decade, targeted therapies for solid tumors, including non-small cell lung cancer (NSCLC), have advanced significantly, offering tailored treatment options for patients. However, individuals without targetable mutations pose a clinical challenge, as they may not respond to standard treatments like immune-checkpoint inhibitors (ICIs) and novel targeted therapies. While the mechanism of action of ICIs seems promising, the lack of a robust response limits their widespread use. Although the expression levels of programmed death ligand 1 (PD-L1) on tumor cells are used to predict ICI response, identifying new biomarkers, particularly those associated with the tumor microenvironment (TME), is crucial to address this unmet need. Recently, inflammatory cytokines such as interleukin-1 beta (IL-1β) have emerged as a key area of focus and hold significant potential implications for future clinical practice. Combinatorial approaches of IL-1β inhibitors and ICIs may provide a potential therapeutic modality for NSCLC patients without targetable mutations. In this review, we discuss the role of IL-1β in NSCLC, its involvement in inflammatory pathways, and explore its potential role in the treatment of NSCLC.

People must have particular personality traits and social resources, also known as health literacy, in order to access, comprehend, and use information to make decisions about their health. Patients' ability to engage in complex disease management and self-care is strongly related to their level of health literacy. It can help us stay healthy by preventing illness and effectively managing existing illnesses. People with low health literacy (LHL) may find it difficult to manage their condition and prevent illness, which may lead to increased use of healthcare services. Furthermore, LHL is associated with increased hospitalizations, increased use of emergency care, decreased use of preventative services, and a worsened ability to understand labels and health messages, a worsened state of health, higher mortality, and more expensive medical care.

: Seasonal influenza (a.k.a flu) is responsible for considerable morbidity and mortality across the globe. The three recognized pathogens that cause epidemics during the winter season are influenza A, B and C. The influenza virus is particularly dangerous due to its mutability. Vaccines are an effective tool in preventing seasonal influenza, and their formulas are updated yearly according to WHO recommendations. However, in order to facilitate decision-making in the planning of the intervention, policymakers need information on the projected costs and quantities related to introducing the influenza vaccine, in order to help governments obtain an optimal allocation of the vaccine each year. In this paper, an approach based on a Controlled Elitism Non-Dominated Sorting Genetic Algorithm (CENSGA) model is introduced to optimize the allocation of influenza vaccination. A bi-objective model is formulated to control the infection volume, and reduce the unit cost of the vaccination campaign. An SIR (Susceptible–Infected–Recovered) model is employed for representing a potential epidemic. The model constraints are based on the epidemiological model, time management, and vaccine quantity. A two-phase optimization process is proposed: guardian control followed by contingent controls. The proposed approach is an evolutionary metaheuristic multi-objective optimization algorithm with a local search procedure based on a hash table. Moreover, in order to optimize the scheduling of a set of policies over a predetermined time to form a complete campaign, an extended CENSGA is introduced with a variable-length chromosome (VLC) along with mutation and crossover operations. To validate the applicability of the proposed CENSGA, it is compared with the classical Non-Dominated Sorting Genetic Algorithm (NSGA-II). The results are analyzed using graphical and statistical comparisons in terms of cardinality, convergence, distribution and spread quality metrics, illustrating that the proposed CENSGA is effective and useful for determining the optimal vaccination allocation campaigns.

Pericentromeric regions of chromosomes enriched in tandemly repeated satellite DNA although representing a significant part of eukaryotic genomes are still understudied mainly due to interdisciplinary knowledge gaps. Recent studies suggest their important role in genome regulation, karyotype stability and evolution. Thus, the idea of satellite DNA as a junk part of the genome was refuted. Integration of data about molecular composition, chromosome behaviour and details of in situ organization of pericentromeric regions is of great interest. The objective of this work was a cytogenetic analysis of the interactions of pericentromeric regions non-homologous chromosomes in mouse spermatocytes using immuno-FISH. We analysed two events: the associations between cerntomeric regions of X chromosome and autosomes, and associations between centromeric regions of autosomal bivalents forming chromocenters. We conclude that X chromosome form temporary synaptic associations with different autosomes in early meiotic prophase I which normally can be found at pachytene-diplotene without signs of pachytene arrest. These associations are formed between the satellite DNA-enriched centomeric regions of X chromosome and different autosomes but not involve the satellite-poor centromeric region of Y-chromosome. We suggest the mechanism of X chromosome competitive replacement from such associations during synaptic correction. We showed that centromeric region of the X chromosome remains free of γH2Ax-dependent chromatin inactivation, while Y chromosome is completely inactivated. This findings highlights the predominant role of associations between satellite DNA-enriched regions of different chromosomes including X. We assume that X-autosome temporary associations is a manifestation of an additional synaptic disorders checkpoint. These associations are normally corrected before the late diplotene. We revealed that the intense spreading conditions applied to the spermatocytes I nuclei did not lead to destruction of stretched chromatin fibers i.e. elongated chromocenters enriched in satellite DNA. Revealed by us tight associations between pericentromeric regions of different autosomal bivalents and X chromosome may represent the basis for repeat stability maintenance in autosomes an X chromosome. The consequences of our findings are discussed. We obtained the preparations of mouse spermatocytes nuclei in the meiotic prophase I using two approaches: standard and extremely intense surface spread techniques. Using immuno-FISH we visualized tandemly repeated mouse Major and Minor satellite DNA located in the pericentromeric regions of chromosomes and performed a morphological comparison of the standard- and intensely spreaded meiotic nuclei. Based on our results, we assume the remarkable strength of the chromocenter-mediated associations, “chromatin “bridges”, between different bivalents at the pachytene and diplotene stages. We have demonstrated that the chromocenter “bridges” between the centromeric ends of meiotic bivalents are enriched in both tandemly repeated Major and Minor satellite DNA. Association of centromeric regions of autosomal bivalents and X-chromosome but not with Y-chromosome correlates with the absence of Major and Minor satellites on Y-chromosome. We suggest that revealed tight associations between pericentromeric regions of bivalents may represent the network-like system providing dynamic stability of chromosomal territories, as well as add new data for the hypothesis of ectopic recombination in these regions which supports sequence homogeneity between non-homologous chromosomes and does not contradict the meiotic restrictions imposed by the crossing-over interference near centromeres. We conclude that nuclear architecture in meio-sis may play an essential role in contacts between the non-homologous chromosomes providing the specific characteristics of pericentromeric DNA.

In humans, age-associated degrading changes are observed in molecular and cellular processes underly the time-dependent decline in spatial navigation, time perception, cognitive and psy-chological abilities, and memory. Cross talk of biological, cognitive, and psychological clocks provides an integrative contribution to healthy and advanced aging. At the molecular level, ge-nome, proteome, and lipidome instability are widely recognized as the primary causal factors in aging. We narrow attention to the roles of protein aging linked to prevalent amino acids chirali-ty, enzymatic and spontaneous (non-enzymatic) post-translational modifications (PTMs SP), and non-equilibrium phase transitions. The homochirality of protein synthesis, resulting in the steady-state non-equilibrium condition of protein structure, makes them prone to multiple types of enzymatic and spontaneous PTMs, including racemization and isomerization. Spontaneous racemization leads to the loss of the balanced prevalent chirality. Advanced biological aging re-lated to irreversible PTMs SP has been associated with the nontrivial interplay between poor so-matic and mental health conditions. Through stress response systems (SRS), the environmental and psychological stressors contribute to the age-associated “collapse” of protein homochirality. The role of prevalent protein chirality and entropy of protein folding in biological aging is mainly overlooked. In a more generalized context, the time-dependent shift from enzymatic to the non-enzymatic transformation of biochirality might represent an important and yet un-der-appreciated hallmark of aging.

Insufficient mixing in large-scale bioreactors, provokes gradient zones of substrate, dissolved oxygen, pH and other parameters. E. coli responds to a high glucose, low oxygen feeding zone with the accumulation of mixed acid fermentation products, especially formate, but also with the synthesis of non-canonical amino acids, such as norvaline, norleucine and -methyl-norleucine. These amino acids can be mis-incorporated into recombinant products, which causes a problem for pharmaceutical production whose solution is not trivial. While these effects can also be observed in scale down bioreactor systems, these are challenging to operate. Especially the high-throughput screening of clone libraries is not easy, as fed-batch cultivations would need to be controlled via repeated glucose pulses with simultaneous oxygen limitation, as has been demonstrated in well controlled robotic systems. Here we show that not only glucose pulses in combination with oxygen limitation can provoke the synthesis of these non-canonical branched-chain amino acids, but also that pyruvate pulses produce the same effect. Therefore we combined the enzyme based glucose delivery method Enbase® in a PALL24 mini-bioreactor system and combined repeated pyruvate pulses with simultaneous reduction of the aeration rate. These cultivation conditions, produced an increase in the non-canonical branched chain amino acids norvaline and norleucine in both the intracellular soluble protein and inclusion body fractions with mini-proinsulin as an example product, and this effect was verified in a 15 L stirred tank bioreactor. To our opinion this cultivation strategy is easy to apply for the screening of strain libraries under standard laboratory conditions if no complex robotic and well controlled parallel cultivation devices are available.

Vitamin C is an essential nutrient that must be obtained through the diet in adequate amounts to prevent hypovitaminosis C and the potentially fatal deficiency disease scurvy. Global vitamin C status and prevalence of deficiency has not previously been reported, despite vitamin C’s pleiotropic roles in both non-communicable and communicable disease. This review highlights the global literature on vitamin C status and the prevalence of hypovitaminosis C and deficiency. Related dietary intake is reported if assessed in the studies. We also explore if global vitamin C status has changed over time. Overall, the review illustrates the shortage of high quality epidemiological studies of vitamin C status in many countries, particularly low- and middle-income countries. The available evidence indicates that vitamin C deficiency is common in low- and middle-income countries and not uncommon in high income settings. Further high quality studies are required to confirm these findings, including in the countries not yet represented, and to fully understand associations with a range of disease processes. Our findings suggest a need for interventions to prevent deficiency in a range of at risk groups and regions of the world.

Liquid manipulation by photoisomerization attracts recent attentions as a new active droplet control method for micro-chemical analysis. Such a non-inverse manipulation can be realized by a use of solution liquid of surfactant that exhibits the \emph{cis}-\emph{trans} isomerization triggered by light irradiation with a specific wavelength such as ultraviolet light. Since the isomerization is accompanied by changes in fluid properties, a light irradiation on one of liquid-air interfaces of a liquid column in a tube would generate differences in the wettability accompanied between the both sides of the finite liquid column. Although this technique has been demonstrated experimentally by Muto et al. (\emph{Euro.~Phys.~J.~Special Topics}, {\bf 226}, 2016, 1199--1205), its dynamics and developments of each isomer distribution are not understood. In order to reveal the liquid-column migration phenomenon, we have performed numerical simulations of air-liquid two-phase flows and its scalar transport of the isomer, using the Volume-of-Fluid method in conjunction with the Continuum-Surface-Force model and Continuous-Species-Transfer method. We validated present results by comparison with experimental result in terms of the migration distance of the liquid column. We confirmed a termination of the liquid-column migration occurs when the \emph{cis} isomer distribution reaches the non-irradiated region. The migration speed was less dependent on the liquid-column length and was proportional to the tube diameter.

Maintenance of integrity and function of the gastric mucosa (GM) requires a high regeneration rate of epithelial cells during the whole life span. The health of the gastric epithelium highly depends on redox homeostasis, antioxidant defense and activity of detoxifying systems within the cells as well as robustness of blood supply. Bioactive products of lipid peroxidation, in particular second messengers of free radicals, the bellwether of which is 4-hydroxynonenal (HNE), are important mediators in physiological adaptive reactions and signaling but they are also thought to be implicated in the pathogenesis of numerous gastric diseases. Molecular mechanisms and consequences of increased production of HNE and its protein adducts in response to stressors during acute and chronic gastric injury are well studied. However, several important issues related to the role of HNE in gastric carcinogenesis, tumor growth and progression, the condition of GM after eradication of Helicobacter pylori, or the relevance of antioxidants for HNE-related redox homeostasis in GM still need more studies and new comprehensive approaches. In this regard, preclinical studies and clinical intervention trials are required, which should also include the use of state-of-the-art analytical techniques such as HNE determination by immunohistochemistry and ELISA as well as modern mass-spectroscopy methods.