This article discusses a transformer-free, high-efficiency DC-DC converter besides renewable energy applications. The traditional buck-boost, classic Zeta, Sepic, and Cuk converter does have the benefits of a simple design, low cost, as well as the capacity to execute voltage step-up and step-down. Conversely, because of the detrimental consequences of the parasitic constraints of the device, the voltage conversion gain of the traditional DC-DC converter is much more restricted and the efficiency is also significantly smaller, whereas this proposed converter does have a higher voltage gain and efficiency because it is used in a single power switch, resulting in reduced switching losses and voltage stress. The said converter's design is very simple, which simplifies the operation control and reduces switching and conduction losses, leading to an efficiency of 97.4 percent. This converter seems to have the same capabilities as the Zeta converter, including continuous desired output current and desired buck-boost operation. Such an article offers the operation principle and steady evaluation, as well as a comparison with other existing high step-up configurations. The proposed converter employs a fuzzy logic controller, which improves the voltage level as well as reduces the time taken to set the voltage output of a conventional PI and ANN controller, especially in comparison to the FLC controller. For deployment, Experimental Result and MATLAB/Simulink has been used, and the modeling results indicate that the proposed controller performance has improved

Wide bandgap (WBG) power semiconductor devices are increasingly replacing silicon IGBTs in high-power and high-voltage power electronics applications. However, there is a significant gap in the literature regarding efficient testing methodologies for high-power and high-voltage converters under constrained laboratory resources. This paper addresses this gap by presenting comprehensive, hardware-focused testing methodologies for high-power and high-voltage WBG power semiconductor based converters, preceding the control evaluation phase. The proposed methods enable thorough evaluation and evaluation of converter hardware, including device switching characteristics, driving circuit functionality, thermal management performance, insulation integrity, and sustained operation at full power. We utilize the double pulse test (DPT) to characterize switching performance in a two-level phase leg configuration, extract circuit parasitics, and validate magnetic components. The DPT is further applied to optimize gate driving circuits, validate overcurrent protection mechanisms, and measure device on-resistance. Additionally, a multicycle test is introduced to rapidly assess steady-state converter performance and estimate efficiency. Recognizing the critical role of thermal management in high-power converters, our methodologies extend to the experimental extraction of key thermal parameters—such as junction-to-ambient thermal resistance and thermal capacitance—via a heat loss injection method. A correlation method between temperature sensor measurements and junction temperature is presented to enhance the accuracy of device temperature monitoring during tests. To ensure reliability and safety, dielectric withstand tests and partial discharge measurements are conducted at both component and converter levels under conventional 60 Hz sinusoidal and high-frequency PWM waveforms. Finally, we highlight the importance of testing converters under full voltage, current, and thermal conditions through power circulating tests with minimal power consumption, applicable to both non-isolated and isolated high-power converters. Practical examples are provided to demonstrate the effectiveness and applicability of these hardware testing methodologies.

Despite the successful introduction of oral cholera vaccines, Zambia continues to experience multiple, sporadic, and protracted cholera outbreaks in various parts of the country. While vaccines have been useful in staying the cholera outbreaks, the ideal window for re-vaccinating individual’s resident in cholera hotspot areas remains unclear. Using a prospective cohort study design, 225 individuals were enrolled, re-vaccinated with two doses of Shanchol™ regardless of previous vaccination and followed-up for 90 days. Bloods collected at baseline before re-vaccination, at day 14 prior to second dosing and subsequently on days 28, 60, and 90. Vibriocidal assay was performed on samples collected at all five time points. Our results showed that anti-LPS and vibriocidal antibody titers increased at day 14 after re-vaccination and decreased gradually at 28, 60 and 90 across all the groups. Seroconversion rates were generally comparable in all treatment arms. We therefore conclude that vibriocidal antibody titers generated in response to re-vaccination still wane quickly irrespective of previous vaccination status. However, despite the observed decline, the levels of vibriocidal antibodies remained elevated over baseline values across all groups, an important aspect for Zambia where there is no empirical evidence as to the ideal time for re-vaccination.

Optimization techniques are pivotal across various scientific domains, typically involving solving problems among feasible alternatives based on specific goals, alternatives, or constraints. In mathematical optimization, traditional methods like Simulated Annealing (SA) do not guarantee finding global minima/optima, especially in cases that contain high dimensions in objective functions. This paper introduces a novel approach where a free-energy driven self-adaptive SA algorithm is designed to handle such cases by incorporating free-energy costs within the Metropolis-Hastings framework. This algorithm not only dynamically adjusts to the changing dimensions of the objective function, but it also enhances a faster optimization process. Furthermore, as examples we demonstrate its capability on a convex unimodal function and the non-convex Rastrigin function, revealing faster convergence to search global minima compared to standard SA algorithm. At last, parameter estimation of noisy exponential data has been executed by our Simulated Annealing driven by the Free-Energy (SAFE) algorithm. Our results suggest that this novel approach may significantly improve optimization speed and accuracy, providing a robust tool for complex multidimensional optimization problems.

Research into the neurobiological and psychosocial mechanisms involved in fibromyalgia (FM) has progressed remarkably in recent years. Despite this, currents accounts of FM fail to capture the complex, dynamic and mutual crosstalk between neurophysiological and psychosocial domains. We conducted a comprehensive review of the existing literature in order to synthesise current knowledge on FM, explore and highlight multi-level links and pathways among different systems and build bridges between existing approaches. An extensive panel of international experts in neurophysiology and psychosocial aspects of FM discussed the collected evidence and progressively refined and conceptualized its interpretation. Fibromyalgia is a complex condition resulting from the dynamic interplay between multiple systems and processes. We provided an updated overview of the most relevant observations in FM to date as well as the potential pathways by which they exert they are related and exert their mutual influence, to produce the manifestations commonly associated with FM. This review constituted the first step towards and supported the development of a much needed model capable of integrating the main factors implicated in FM into a single, unified model that may prove valuable in understanding and managing FM.

To follow the growth and development of each tree (N = 1200) Pinus sylvestris L., var. Negorelskaya starting from the seed and continuing at the juvenile (or even generative) stage is the goal of an ambitious project to create a plant passport if possible. Five datasets of replenished empirical (tab-ular and file) and systematic data reflect the early results of a unique ongoing experiment conducted with families moved along a climatic gradient from the collection area (1731 degree days, 722 mm) to the experimental area (2326 degree days; 786 mm). Datasets of morphometric, VIS-spectrometric, and germination seed data, combined with the first results of biometric data (including the Dickson quality index) of seedlings produced from these seeds, will allow scientists in the future to conduct correlation and other statistical analysis, or train a neural network to determine the presence of connections between a seed and a plant. These data contribute to the early non-destructive diag-nosis and grading of seeds according to VIS-spectrometric properties. This dataset structure can complement the FLR-Library. In the future, by tracing seedlings in their early growth (for example, over three growing seasons at the site being restored), it will be possible to determine the degree of intensification of FRM production depending on the initial properties of the seed.

The molecular structure and vibrational spectra of six 1,2,3-triazoles-containing molecules with possible anticancer activity were investigated. In two of them, the optimized geometry was determined in the monomer, cyclic dimer and staking forms using the B3LYP, M06-2X and MP2 methods. The effect of the para-substitution in the aryl ring was evaluated based on the changes in the molecular structure and atomic charge distribution of the triazole ring. Several relationships were obtained that could facilitate the selection of the substituents on the triazole ring for their further synthesis. The observed IR and Raman bands in the solid state of two of these compounds were accurately assigned according to the functional calculations on the monomer and dimer forms, together with the polynomic scaling equation procedure (PSE).

This work focuses on identifying the most effective machine learning techniques and supervised learning models to precisely estimate power output from Photovoltaic (PV) plants. The performance of various regression models is analyzed by harnessing experimental data, including Random Forest, Support Vector Regression (SVR), Multi-layer Perceptron (MLP), Linear Regressor (LR), Gradient Boosting, and k-Nearest Neighbors (KNN). The methodology applied starts with meticulous data preprocessing steps aimed at ensuring dataset integrity. Following the preprocessing phase, which entails eliminating missing values and outliers using Isolation Feature selection based on a correlation threshold, is performed to identify relevant parameters for accurate prediction in PV systems. Subsequently, Isolation Forest is employed for outlier detection, followed by model training and evaluation using key performance metrics such as Root Mean Squared Error (RMSE), Normalized Root Mean Squared Error (NRMSE), Mean Absolute Error (MAE), and R-squared (R2). Among the array of models evaluated, Random Forest emerges as the top performer, highlighting promising results with an RMSE of 19.413, NRMSE of 0.048% and an R2 score of 0.968. Furthermore, the best-performing model is integrated into a MATLAB application for real-time predictions, thereby enhancing usability and accessibility for a wide range of applications in renewable energy.

In light of the critical and emerging global challenge posed by the increasing frequency and severity of heatwaves in recent decades, this study demonstrates a practical and robust workflow that bridges the gap in understanding how the effective integration of remote sensing data with ground-based observations can facilitate a comprehensive assessment of spatiotemporal heatwave patterns and trends in the central region of Thailand. This research transcends traditional methods, utilizing air temperature (Tair) and satellite-derived land surface temperature (LST) data from 1981 to 2019. Results exhibit that an analysis of Tair indicates increasing daytime heatwaves in peri-urban areas, with significant trends in heatwave number (HWN), heatwave frequency (HWF), and heatwave duration (HWD), heatwave amplitude (HWA) rises in urban settings while nighttime heatwaves significantly intensify in rural locales. Notably, LST trends reveal varied patterns, with peri-urban areas showing marked daytime increases in heatwave magnitude (HWM), HWA, and HWF. Correlation analysis (p=0.05) highlights strong daytime associations between Tair and LST in rural (HWN, HWF, HWD, r>0.90) and peri-urban (HWM, HWA, r>0.65) regions. Overall, this study advances approaches to the adaptable measurement and spatial-temporal pattern of heatwave-related risk areas, providing insights for decision-makers to develop sustainable practices and strategies for climate change adaptation.

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 COLOSS research association has been assessing honey bee colony losses, associated risk factors and management, focusing on Western countries but with a progressive international expansion. Here, we report the first survey on the loss rates of colonies in 2022/23 in Ethiopia using COLOSS monitoring survey tools. A face-to-face interview questionnaire survey was conducted on 64 beekeepers selected from Oromia and Tigray regions. This covered 1,713 honey bee colonies distributed in 68 apiaries. The percentages of colonies lost were significantly different between Oromia (24.1%) and Tigray (66.4%) regions. Colony losses were attributed as unsolvable queen problems (8% in Oromia; 10% in Tigray), natural disaster (32%; 82%), and empty hives or dead colonies (60%; 8%). The loss rate was significantly affected by queen replacement (p

The surface thermodynamic properties of polymers and copolymers modified by supramolecular structures are very used in several industrial processes, such as selective adsorption, paints, coatings, colloids, and adhesion applications. Background: Inverse gas chromatography at infinite dilution was proved to be the best technique to determine the surface properties of solid surfaces by studying the adsorption of some model polar and non-polar organic molecules adsorbed on solid surfaces by varying the temperature. Methods: The retention volume of adsorbed solvents is a precious parameter to obtain the London dispersive and polar free energies and the London dispersive surface energy of styrene–divinylbenzene copolymer modified by supramolecular structure of melamine using the Hamieh thermal model and our new methodology consisting in the separation of the two polar and dispersive free energy of interaction. This led to the determination of the polar acid and base surface energy, and the Lewis’s acid-base constants of the various solid materials. Results: all surface energetic properties of styrene–divinylbenzene copolymer modified by melamine at different percentages were determined as a function of temperature, following our new methodology. Conclusions: It was observed that the styrene–divinylbenzene copolymer exhibited the highest London dispersive surface energy which decreased when the melamine percentage increased. All materials presented higher Lewis’s basicity and this Lewis’s basicity increased with the percentage of melamine.

Infections are a common post-operative ailment for patients who have received a dental implant or device and can be attributed to biofilm formation in tissue or on the implant. Many current solutions for oral hygiene have side effects and affect the natural oral microbiome. 2-heptylcyclopropane-1-carboxylic acid (2CP) is a medium-chain fatty acid and synthetic diffusible signaling factor that can prevent and disperse biofilm. The purpose of this work was to evaluate an immersion strategy for coating hydroxyapatite (HAp) with 2CP to prevent biofilm attachment on and around natural teeth and dental implants. The release profile of 2CP-loaded and 2CP+oral rinse-loaded HAp coupons (n=6) was assessed by a 3-day exposure to phosphate buffered saline (PBS). Antimicrobial properties against Porphyromonas gingivalis and cytocompatibility of 2CP-loaded HAp coupons (n=4) were also assessed alone and in combination with 0.12% chlorhexidine gluconate oral rinse. The majority of 2CP is released by 12 hours. 2CP, oral rinse, and 2CP+oral rinse significantly reduced P. gingivalis viability, though direct contact assay demonstrates a significant reduction in Saos-2 viability for oral rinse and 2CP+oral rinse coupons. Immersion or rinsing hydroxyapatite with 2CP could inhibit biofilm-associated dental infections and prevent further complications including caries, gingivitis, and peri-implantitis.

p-type Ag-N dual acceptor doped ZnO thin films with long electrical stability were deposited by DC magnetron reactive co-sputtering technique. After deposition, the films were annealed at 400 °C for one hour in a nitrogen-controlled atmosphere. The deposited films were amorphous. However, after annealing they crystallize in the typical hexagonal wurtzite structure of ZnO. The Ag-N dual acceptors were incorporated substitutionally in the structure of zinc oxide and achieving that the three samples presented the p-type conductivity in the ZnO. Initial electrical properties showed a low resistivity of from 1 to10^{−3} Ω.cm, Hall mobility of tens cm2/V.s and a hole concentration from 10^{17} to 10^{19} cm^{−3}. The electrical stability analysis reveals that the p-type conductivity of the ZnO:Ag,N films is very stable and does not revert to n-type, even after 36 months of aging. These results reveal the feasibility of using these films for applications in short-wavelength or transparent optoelectronic devices.

To achieve n-type doping in diamond, extensive investigations employing first principles have been conducted on various models of phosphorus doping and boron-phosphorus co-doping. The primary focus of this study is to comprehensively analyze the formation energy, band structure, density of states, and ionization energy of these structures. It is observed that within a diamond structure solely composed of phosphorus atoms, the formation energy of an individual carbon atom is excessively high. However, the substitution of two carbon atoms leads to the conversion of diamond into a p-type semiconductor. Upon examining the P-B co-doping structure, it is revealed that the doped impurities exhibit a tendency to form more stable cluster configurations. As the separation between the freely doped atoms and the cluster impurity structure increases, the overall stability of the structure diminishes, consequently resulting in an elevation of the ionization energy. Analysis of the electronic density of states demonstrates that the electron orbit of the B atom makes negligible contributions to the impurity levels during P-B doping.

Nanoindentation load-depth (P-h) plots is the basis for determination of mechanical properties of the samples and is especially vital for thin coatings deposited on substrates of various mechanical makeup from amorphous-brittle (borosilicate glass) to Silicon (having different crystallographic texture) to ductile substrates like stainless steel as well other aspects like indenter tip shape. The elastic-plastic response by simulated P-h plots as per modified empirical relations have been presented. The outcomes of this computational studies enlighten the database on the P-h plots for various coating/substrate systems and shall aid in the analysis of experimental P-h plots obtained,

The seismic damage in reinforced concrete bridges is identified in this study using the "M and P" hybrid technique initially developed for planar frames. The proposed methodology involves a series of pushover and instantaneous modal analyses with a progressively increasing target deck displacement along the longitudinal direction of the bridge. From the results of these analyses, the diagram of the instantaneous eigenfrequency of the bridge, ranging from the health state to near collapse, is plotted against the inelastic seismic deck displacement. By pre-determining the eigen-frequency of an existing bridge along its longitudinal direction through "monitoring and frequency identification", the target deck displacement corresponding to the damage state can directly be found from this diagram. Subsequently, the damage can be identified by examining the results of the pushover analysis at the step where the target deck displacement is indicated. The effectiveness of this proposed technique is evaluated in the context of multiple span bridges with unequal pier heights, illustrated through an example of a four-span bridge. The findings demonstrate that the damage potential in bridge piers can be successfully identified by combining the results of a monitoring process and pushover analysis.

In tropical areas, simultaneous transmission of several vector-borne diseases is common due to ecological factors that are shared by arthropod vectors. Malaria and dengue virus, transmitted by Anopheles and Aedes mosquitoes, respectively, are among the top vector-borne diseases that cause significant morbidity and mortality in endemic areas. Notably, tropical areas often have suitable conditions for the co-existence of these mosquito species, highlighting the importance of identifying markers that accurately indicate the risk of acquiring each specific disease entity. Aedes are daytime-biting mosquitoes, while Anopheles preferentially bite during the night. These biting patterns raises the possibility of concurrent exposure to bites from both species. This pattern is important since mosquito saliva, deposited in the skin during blood feeding, induces immune responses that modulate pathogen establishment and infection. Previous studies have focused on characterizing such effects on the vector-pathogen interface for an individual pathogen and its mosquito vector. In this study, we evaluated associations between immune responses to salivary proteins from non-dengue and non-malaria vector mosquito species with clinical characteristics of malaria and dengue, respectively. Surprisingly, antibody responses against Anopheles antigens in dengue patients correlated with red blood cell count and hematocrit, while antibody responses against Aedes proteins were associated with platelet count in malaria patients. Our data indicate that concurrent exposure to multiple disease-carrying mosquito vectors and their salivary proteins with differing immunomodulatory properties could influence the transmission, pathogenesis, and clinical presentation of malaria, dengue fever, and other vector-borne illnesses.

In this paper we study a special kind of finite mixture model. The sample drawn from the model consisits of three parts. The first two parts are drawn from specified distributions f1 and f2, while the third one is drawn from the mixture. A problem of interest is whether the two distributions f1 and f2 are the same. To test this hypothesis, we first define the regular location and scale family of distributions and assume that f1 and f2 are regular denisty functions. Then the hypothesis transforms to the equalities of the location and scale parameters, respectively. To utilize the information in the sample, we use Bayes’ theorem to obtain the posterior distribution and give the sampling method. Then we propose the posterior p-value to test the hypothesis. The simulation studies show that our posterior p-value largely improves the power in both normal and logistic cases while nicely controls the Type-I error. A real halibut dataset is used to illustrate the validity of our method.

Properties of coherent states for the Heisenberg group over a field of $p$-adic numbers are investigated. It turns out that coherent states form an orthonormal basis. The family of all such bases is parametrized by a set of self-dual lattices in the phase space. The Wehrl entropy $S_W$ is considered and its properties are investigated. In particular, it is proved that $S_W\geq 0$ and vanishes only on coherent states. For a pair of different bases of coherent states, an entropic uncertainty relation is obtained. It is shown that the lower bound for the sum of the corresponding Wehrl entropies is given by the distance between the lattices. The proof uses the fact that the bases of coherent states corresponding to a pair of lattices are mutually unbiased.

In this paper, various Ni-P composite coatings containing toner, MoS2, and nano-SiO2 particles were deposited on steel substrates by the electroless method. Then, the electrochemical properties of these coatings after a heat treatment process were compared. The microstructural evaluations were also done by using the optical and electron microscopy methods. Both Tafel polarization and electrochemical impedance spectroscopy techniques were utilized to survey the electrochemical behavior of such coatings. The surface morphology of all coatings contained cauliflower-like nodules. The X-ray diffraction patterns showed the crystalline phases of Ni and Ni3P for all coatings after the heat-treatment step. Obtained results showed that all composite coatings exhibited lower corrosion rates with respect to Ni-P coatings. Such a reduction was about 21.6-92.2%. This behavior was attributed to the presence of reinforcement as barriers for corrosive ion diffusion through the coating plus the changes in detected phases and thickness. Electrochemical impedance spectroscopy test results also demonstrated that the increase in the polarization resistance for composites coatings was about 18.4-85.3% after 1 h immersion in a 0.6M NaCl solution; however, when the immersion time increased to 24 h, such increased resistance changed to 18.1 to 73.1%. Totally, despite the lower deposition rate, the presence of MoS2 and nano-SiO2 particles were more effective than toner particles to raise the corrosion rate of the Ni-P coating.

Hypothesis: Anti-diabetic drugs modulate p-21 activated kinase (PAK) signaling Introduction: Type 2 diabetes mellitus (T2DM) is a chronic inflammatory disease associated with increased cancer risk. PAK signaling is implicated in cellular homeostasis when regulated, and cancer when unrestrained. Recent reports provided a role for PAK signaling in glucose homeostasis, but the role of PAKs in the pathogenesis of T2DM is unknown. Here we performed a mini-meta analysis to explore if anti-diabetic drugs modify PAK signaling pathways, and provide insight regarding modulation of these pathways to potentially reduce diabetes-associated cancer risk. Methods: PAK interacting partners in T2DM were identified using online STRING database. Correlation studies were performed via systematic literature review to understand the effect of anti-diabetic drugs on PAK signaling. Mini meta analysis correlated multiple clinical studies and revealed the overall clinical response rate and percentage of adverse events in piogliazone (n=53) and metformin (n=91) treated patients with PAK-associated diseases. Results: A total of 30 PAK interacting partners were identified (10: reduced beta-cell mass; 10: beta-cell dysfunction; 10: obesity-insulin resistance) which were highly associated with Wnt, and G-protein signaling. Anti-diabetic drug metformin activated signaling pathways upstream; whereas pioglitazone inhibited pathways downstream of PAK. Overall clinical response upon pioglitazone treatment was 53%. 79% of pioglitazone and 75% of metformin treated patients had adverse events. Pioglitazone reduced molecular-PAK biomarkers of proliferation (Ki67 and CyclinD1), and metformin had the opposite effect. Conclusions: PAK signaling in T2DM likely involves Wnt and G-protein signaling which may be altered by anti-diabetic drugs metformin and pioglitazone. Apart from the therapeutic limitations of adverse events, pioglitazone may be promising in chemoprevention, however long-term multi-centered studies, which initiate pioglitazone treatment early will be required to fully assess the full potential of these drugs.

Hypothesis: Anti-diabetic drugs modulate p-21 activated kinase (PAK) signaling Introduction: Type 2 diabetes mellitus (T2DM) is a chronic inflammatory disease associated with increased cancer risk. PAK signaling is implicated in cellular homeostasis when regulated, and cancer when unrestrained. Recent reports provided a role for PAK signaling in glucose homeostasis, but the role of PAKs in the pathogenesis of T2DM is unknown. Here we explored whether PAK signaling should be targeted via chemoprevention to reduce diabetes-associated cancer risk. Methods: PAK interacting partners in T2DM were identified using online STRING database. Systematic literature review provided the effect of anti-diabetic drugs on PAK signaling. Review of clinical studies revealed the overall clinical response rate and percentage of adverse events in piogliazone (n=53) and metformin (n=91) treated patients with PAK-dependent diseases. Results: A total of 30 PAK interacting partners were identified (10: reduced beta-cell mass; 10: beta-cell dysfunction; 10: obesity-insulin resistance) which were highly associated with Wnt, and G-protein signaling. Anti-diabetic drug metformin activated signaling pathways upstream; whereas pioglitazone inhibited pathways downstream of PAK. Overall clinical response upon pioglitazone treatment was 53%. 79% of pioglitazone and 75% of metformin treated patients had adverse events. Pioglitazone reduced molecular-PAK biomarkers of proliferation (Ki67 and CyclinD1), and metformin had the opposite effect. Conclusions: PAK signaling in T2DM involves Wnt and G-protein signaling which is altered by anti-diabetic drugs metformin and pioglitazone. Apart from the therapeutic limitations of adverse events, pioglitazone is promising in chemoprevention, however long-term multi-centered studies, which initiate pioglitazone treatment early will be required to fully assess the full potential of these drugs.

In this paper, we define a (p,v)-extension of Hurwitz-Lerch Zeta function by considering an extension of beta function defined by Parmar et al. [J. Classical Anal. 11 (2017) 81–106]. We obtain its basic properties which include integral representations, Mellin transformation, derivative formulas and certain generating relations. Also, we establish the special cases of the main results.

Polarimetric Synthetic Aperture Radar (PolSAR) images encompass valuable information that can facilitate extensive land cover interpretation and generate diverse output products. Extracting meaningful features from PolSAR data poses challenges distinct from those encountered in optical imagery. Deep Learning (DL) methods offer effective solutions for overcoming these challenges in PolSAR feature extraction. Convolutional Neural Networks (CNNs) play a crucial role in capturing PolSAR image characteristics by leveraging kernel capabilities to consider local information and the complex-valued nature of PolSAR data. In this study, a novel three-branch fusion of complex-valued CNN named Shallow to Deep Feature Fusion Network (SDF2Net) is proposed for PolSAR image classification. To validate the performance of the proposed method, classification results are compared against multiple state-of-the-art approaches using the Airborne Synthetic Aperture Radar (AIRSAR) datasets of Flevoland, San Francisco, and ESAR Oberpfaffenhofen dataset. The results indicate that the proposed approach demonstrates improvements in OA, with 1.3% and 0.8% enhancement for the AIRSAR datasets and 0.5% improvement for the ESAR dataset. The analyses conducted on the Flevoland data underscore the effectiveness of the SDF2Net model, revealing a promising OA of 96.01% even with only 1% sampling ratio.

Background: The global pandemic of coronavirus disease 2019 (COVID-19) resulted to many deaths from fulminant respiratory failure. Chronic obstructive pulmonary disease (COPD) is the leading cause of morbidity and mortality worldwide. There has been great concern regarding the impact of COPD on COVID-19 illness. Methods: Data from the Philippine CORONA Study were analyzed to determine the association of COPD and COVID-19 in terms of mortality, disease severity, respiratory failure, mechanical ventilation, and lengths of stay in the intensive care unit (ICU) and hospital. The influence of smoking on COVID-19 disease severity and mortality were also reviewed. Results: A total of 10,881 patients were included in the study and 156 (1.4%) patients had been diagnosed with COPD. Majority of COVID-19 patients with COPD had other existing comorbidities: hypertension, diabetes mellitus, chronic cardiac disease, and chronic kidney disease. COPD patients more commonly present with severe or critical COVID-19. COPD patients with COVID-19 were at higher risk to experience in-hospital mortality, respiratory failure, and to be admitted in the ICU. Smokers were more likely to present with higher COVID-19 severity and experience in-hospital mortality. Conclusion: Our study supports that the growing evidence that COPD among COVID-19 patients is a risk for higher mortality, more severe form of COVID-19, higher ICU admission, and higher respiratory failure needing ventilatory support. Smoking increases risk for developing severe COVID-19 and mortality.

This study examines the historiography of early Islam by assessing the reliability of Qurʾānic exegeses as sources documenting the early history of Islam and the biography of the Prophet Muḥammad in Mecca. Focusing on Qurʾānic exegetical practices from late antiquity to the medieval period, this article argues that there is a significant discontinuity in how Qurʾānic exegeses align with the historical context of the Qur'an, especially in relation to Meccan sūras such as Q 107. Significantly, this challenges the continuity of tradition, the fundamental concept upon which the “Islamic sciences” are based. This discontinuity is herein revealed through a historical-critical analysis of the exegesis of Q 107:4 that demonstrates how Qurʾānic exegetical practices have reinterpreted and reshaped early Islamic history in response to the pressures of new identity formation and made Qurʾānic exegeses more reflective of the social and political contexts of the exegetes than of the historical milieu of the Qurʾān itself. This analysis contributes to the ongoing discussion of the role exegesis played in reshaping the history of Islam. Indeed, it emphasises the importance of critically evaluating these sources in order to uncover a more nuanced historical narrative of early Islam.

It was the aim of this study to examine whether the usage of the vaccine COXEVAC® (Ceva Santé Animale) could reduce the consumption of antibiotics in Q-fever-positive dairy farms. Additionally, the effects of other herd-level factors on the consumption of antibiotics were investigated. In this longitudinal cohort study, 36 farms with vaccination and 13 farms without vaccination participated. In all herds, Coxiella burnetii had been directly or indirectly diagnosed. To compare the treatment frequency of antibiotics between the vaccinated group and the non-vaccinated group, the consumption of antibiotics for each farm was collected using the veterinary documents about the application and delivery of antibiotics. To gather detailed information about herd data, nutrition, milking management, housing, and animal health, the farmers were interviewed with the help of a questionnaire. The results suggest that there might be an association between the vaccination against Q fever and a reduced consumption of antibiotics. Neither herd size nor milk yield level influenced the consumption of antibiotics in the study herds. Type of flooring and udder cluster disinfection while milking were associated with a lower and higher therapy frequency, respectively. Further studies are necessary to elucidate the cause-effect relationship between vaccination and the consumption of antibiotics.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

Firstly, we present a more explicit formulation of the complete system $D(N)$ of representatives of Manin's symbols over $\mathbb{Q}$, which was initially given by Shimura. Then we establish a bijection between $D(M)\times D(N)$ and $D(MN)$ for $(M,N)=1$, which reveals a recursive structure between Manin's symbols of different levels. Based on Manin's complete system $\Pi (N)$ of representatives of cusps on $X_0(N)$ and Cremona's characterization of the equivalence between cusps, we establish a bijection between a subset $C(N)$ of $D(N)$ and $\Pi (N)$, and then establish a bijection between $C(M)\times C(N)$ and $C(MN)$ for $(M,N)=1$. We also provide a recursive structure for elliptical points on $X_0(N)$. Based on these recursive structures, we obtain recursive algorithms for constructing Manin symbols over $\mathbb{Q}$, cusps and elliptical points on $X_0(N)$. This gives rise to a more efficient algorithms for modular elliptic curve. As direct corollaries of these recursive structures, we present a recursive version of the genus formula and an elementary proof of formulas of the numbers of $D(N)$, cusps and elliptical points on $X_0(N)$.

Tuning fork gyroscopes (TFGs) are promising for potential high-precision applications. This work proposes and experimentally demonstrates a novel high-Q dual mass tuning fork microelectro-mechanical system (MEMS) gyroscope utilizing three-dimensional (3D) packaging techniques. Except for two symmetrically-decoupled proof masses (PM) with synchronization structures, a symmetrically-decoupled lever structure is designed to force the antiparallel, antiphase drive-mode motion and basically eliminate the low-frequency spurious modes. The thermoelastic damping (TED) and anchor loss are greatly reduced by the linearly-coupled, momentum- and torque-balanced antiphase sense mode. Besides, a novel 3D packaging technique is used to realize high Q-factors. A composite substrate encapsulation cap, fabricated by through-silicon-via (TSV) and glass-in-silicon (GIS) reflow processes, is anodically bonded to the sensing structures at wafer scales. A self-developed control circuit is adopted to realize loop control and characterize gyro-scope performances. It is shown that a high-reliability electrical connection together with a high-air-impermeability package can be fulfilled with this 3D packaging technique. Furthermore, the Q-factors of the drive and sense modes reach up to 51947 and 49249, respectively. This TFG realizes a wide measurement range of ±1800° /s and a high resolution of 0.1° /s with a scale-factor nonlinearity 720 ppm after automatic mode-matching. Besides, the long-term zero-rate output (ZRO) drift can be effectively suppressed by temperature compensation, inducing a small angle random walk (ARW) of 0.923°/√h and a low bias instability (BI) of 9.270°/h.

In this paper we present experimental results concerning Acoustic Emission (AE) recorded during cyclic compression tests on two different kinds of brittle building materials, namely concrete and basalt. The AE inter-event times were investigated through a non-extensive statistical mechanics analysis which shows that their decumulative probability distributions follow q-exponential laws. The entropic index q and the relaxation parameter q  1=Tq, obtained by fitting the experimental data, exhibit systematic changes during the various stages of the failure process, namely (q; Tq) linearly align. The Tq = 0 point corresponds to the macroscopic breakdown of the material. The slope, including its sign, of the linear alignment appears to depend on the chemical and mechanical properties of the sample. These results provide an insight on the warning signs of the incipient failure of building materials and could therefore be used in monitoring the health of existing structures such as buildings and bridges.

Explainable AI (XAI) has emerged as a pivotal tool in healthcare diagnostics, offering much-needed transparency and interpretability in complex AI models. XAI techniques, such as SHAP, Grad-CAM, and LIME, enable clinicians to understand AI-driven decisions, fostering greater trust and collaboration between human and machine in clinical settings. This review explores the key benefits of XAI in enhancing diagnostic accuracy, personalizing patient care, and ensuring compliance with regulatory standards. However, despite its advantages, XAI faces significant challenges, including balancing model accuracy with interpretability, scaling for real-time clinical use, and mitigating biases inherent in medical data. Ethical concerns, particularly surrounding fairness and accountability, are also discussed in relation to AI's growing role in healthcare. The review emphasizes the importance of developing hybrid models that combine high accuracy with improved interpretability and suggests that future research should focus on explainable-by-design systems, reducing computational costs, and addressing ethical issues. As AI continues to integrate into healthcare, XAI will play an essential role in ensuring that AI systems are transparent, accountable, and aligned with the ethical standards required in clinical practice.

Toxoplasma gondii is a protozoan and the etiologic agent of toxoplasmosis causes high mortality in immunocompromised individuals and newborns. Despite the medical importance of toxoplasmosis, few drugs are available for its treatment, which are associated with side events and parasite resistance. Here, we show a screening of molecules present in Covid-Box as a way of discovering new hits with anti-T. gondii activity. Covid-Box contains 160 molecules with known or predicted activity against SARS-CoV-2. Our analysis selected 23 Covid-Box molecules that can inhibit the tachyzoite forms of the RH strain of T. gondii in vitro by more than 70% at 1 µM after seven days of treatment. The inhibitory curves showed that most of these molecules inhibited the proliferation of tachyzoites with IC50 values below 0.80 µM; Cycloheximide and (-)-Anisomycin were the most active drugs, with IC50 values of 0.02 μM. Cell viability assays showed that the compounds are not toxic at active concentrations, and most are highly selective for parasites. Overall, all 23 compounds were selective, and for three of them (Apilimod, Midostaurin, and Salinomycin), this is the first report of activity against T. gondii. To better understand the effect of the drugs, we analyzed the effect of six of them on the ultrastructure of T. gondii using transmission electron microscopy. The main changes observed in parasite morphology after treatment with the selected drugs were changes in cell division and parasite organelles.

We developed a novel machine learning (ML) algorithm with the goal of producing transparent models (i.e. understandable-by-humans) while also flexibly accounting for nonlinearity and interactions. Our method is based on ranked sparsity, and allows for flexibility and user-control in varying the shade of the opacity of black-box machine learning methods. The main tenet of ranked sparsity is that an algorithm should be more skeptical of higher-order polynomials and interactions \textit{a~priori} compared to main effects, and hence the inclusion of these more complex terms should require a higher level of evidence. In this work, we put our new ranked sparsity algorithm (as implemented in the open-source R package, `sparseR`) to the test in a predictive model "bakeoff" (i.e. a benchmarking study of ML algorithms applied "out-of-the-box," that is, with no special tuning). Algorithms were trained on a diverse set of simulated and real-world data sets from the Penn Machine Learning Benchmarks database, addressing both regression and binary classification problems. We evaluate the extent to which our human-centered algorithm can attain predictive accuracy that rivals popular black-box approaches such as neural networks, random forests, and support vector machines, while also producing more interpretable models. Using out-of-bag error as a meta-outcome, we describe the properties of data sets in which human-centered approaches can perform as well as or better than black-box approaches. We find that interpretable approaches predicted optimally or within 5% of the optimal method in most real-world data sets. We provide a more in-depth comparison of the performances of random forests to interpretable methods for several case studies, including exemplars in which algorithms performed similarly, and several cases when interpretable methods underperformed. This work provides a strong rationale for including human-centered transparent algorithms such as ours in predictive modeling applications.

Artificial Intelligence (AI) and Machine Learning (ML) approaches that could learn from large data sources have been identified as useful tools to support clinicians in their decisional process; AI and ML implementations have had a rapid acceleration during the recent COVID-19 pandemic. However, many ML classifiers are “black box” to the final user, since their underlying reasoning process is often obscure. Additionally, the performance of such models suffer from poor generalization ability in presence of dataset shift. Here, we present a comparison between an explainable-by-design (“white box”) model (Bayesian Network (BN)) versus a black-box model (Random Forest), both studied with the aim to support clinicians of Policlinico San Matteo University Hospital in Pavia (Italy) during the triage of COVID-19 patients. Our aim is to evaluate whether the BN predictive performances are comparable with those of a widely used but less explainable ML model such as Random Forest and to test the generalization ability of the ML models across different waves of the pandemic.

The advanced industrial systems are characterized by complex event-driven processes. The specification and computer analysis are illustrated by the common problem of a servo drive with the PWM controller. A mathematical model from the class of Cauchy problems with non-liner control logic is presented to resolve the task discussed. The designed model is performed in two stages: the mathematical model specification (modeling) and implementation (simulation). Two approaches to make a model specification are considered, the first one is the traditional structural technique, and the advanced method is based on the finite state machine paradigm. Structural and finite state software models are built in progressive simulation tools. Computer implementation of the software models of hybrid systems is performed using platform built-in libraries with numerical methods and algorithms for correct event detection. The results of computational experiments for transient processes of phase variables are qualitatively identical, that proves the adequacy of the developed models. The algorithm for asymptotic event detection is considered in detail. This technique demonstrated the best results by the one-sidedness criterion, which is explained by using the author’s algorithm for the integration step determining and the event function dynamics monitoring in the vicinity of the event limits.

Is it possible to develop a meaningful measure for the complexity of a simulation model? Algorithmic information theory provides concepts that have been applied in other areas of research for the practical measurement of object complexity. This article offers an overview of complexity from a variety of perspectives and provides a body of knowledge with respect to the complexity of simulation models. Key terms of model detail, resolution, and scope are defined. An important concept from algorithmic information theory, Kolmogorov complexity, and an application of this concept, normalized compression distance, are used to indicate the possibility of measuring changes in model detail. Additional research in this area can advance the modeling and simulation body of knowledge toward the practical application of measuring simulation model complexity. Examples show that KC and NCD measurements of simulation models can detect changes in scope and detail.

Summary: Studying biological systems generally relies on computational modeling and simulation, e.g., for model-driven discovery and hypothesis testing. Progress in standardization efforts led to the development of interrelated file formats to exchange and reuse models in systems biology, such as SBML, the Simulation Experiment Description Markup Language (SED-ML), or the Open Modeling EXchange format (OMEX). Conducting simulation experiments based on these formats requires efficient and reusable implementations to make them accessible to the broader scientific community and to ensure the reproducibility of the results. The Systems Biology Simulation Core Library (SBSCL) provides interpreters and solvers for these standards as a versatile open-source API in Java™. The library simulates even complex bio-models and supports deterministic Ordinary Differential Equations (ODEs); Stochastic Differential Equations (SDEs); constraint-based analyses; recent SBML and SED-ML versions; exchange of results, and visualization of in silico experiments; open modeling exchange formats (COMBINE archives); hierarchically structured models; and compatibility with standard testing systems, including the Systems Biology Test Suite and published models from the BioModels and BiGG databases. Availability and implementation: SBSCL is freely available at https://draeger-lab.github.io/SBSCL/.

This article is devoted to Feller's diffusion equation which arises naturally in probabilities and physics (e.g. wave turbulence theory). If discretized naively, this equation may represent serious numerical difficulties since the diffusion coefficient is practically unbounded and most of its solutions are weakly divergent at the origin. In order to overcome these difficulties we reformulate this equation using some ideas from the Lagrangian fluid mechanics. This allows us to obtain a numerical scheme with a rather generous stability condition. Finally, the algorithm admits an elegant implementation and the corresponding Matlab code is provided with this article under an open source license.

A simple and sensitive liquid chromatography-tandem mass spectrometry (LC– MS/MS) method has been developed for the simultaneous determination of atorvastatin (ATOR), ezetimibe (EZM) and their three metabolites including o-hydroxyl atorvastatin (o-OH ATOR), p-hydroxyl atorvastatin (p-OH ATOR), and ezetimibe-glucuronide (EZM-G) in human plasma using benzyl paraben (BP) as internal standard (IS). The analytes and IS were ionized using ESI positive ion mode (ATOR, o-OH ATOR, and p-OH ATOR), ESI negative ion mode (EZM, EZM-G, and BP), and operated in multiple reaction monitoring (MRM) mode. They were next extracted by salting-out assisted liquid–liquid extraction with acetonitrile, and then analyzed by liquid chromatography on a reversed-phase chromatographic column (50 mm × 4.6 mm; 3.5 µm), using a mixture of ac-etonitrile and an acetic acid solution (0.5%) as the mobile phase, showing high extraction effi-ciency (>70%), and a minimized matrix effect. The method was satisfactorily validated, and showed excellent linearity over wide concentration ranges of 0.06–15 ng/mL, 0.6–150 ng/mL, 0.4–100 ng/mL, 0.12–30 ng/mL, and 0.05–3 ng/mL for EZM, EZM-G, ATOR, o-OH ATOR, and p-OH ATOR, respectively.

Counter-current spontaneous imbibition of water is a critical oil-recovery mechanism. In the laboratory, the Amott test is a widely used technique to assess efficacy of brine imbibition into oil-saturated core plugs. The classic Amott-cell methodology was designed to estimate ultimate oil recovery, but not the recovery dynamics that provides essential information about the imbibition mechanisms. Retention of oil droplets at the external core surface and delayed onset of oil production are the two key artifacts of the classic Amott experiment. This retention, referred to here as the ``external-surface oil holdup effect'', often results in stepwise recovery curves that obscure true dynamics of spontaneous imbibition. To address these holdup drawbacks of the classic Amott method, we modified the Amott cell and experimental procedure. For the first time, using water-wet Indiana limestone cores saturated with brine and mineral oil, we showed that our improvements of the Amott method enabled accurate and reproducible measurements of oil-recovery dynamics. We used the Generalized Extreme Value (GEV) statistics to describe oil-production histories from water-wet heterogeneous limestone cores with finite initial water saturations, for the first time. We demonstrated that our four-parameter GEV model accurately described the recovery dynamics, and that optimal GEV parameter values systematically reflected the key characteristics of the oil-rock system, such as oil viscosity and rock permeability. These findings gave us a more fundamental understanding of spontaneous, counter-current imbibition mechanisms and insights into what constitutes a predictive model of counter-current water imbibition into oil-saturated rocks with finite initial water saturation.

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. The focus of this study was to estimate and thematically map on a pixel-by-pixel basis, the actual evapotranspiration (ET_a) of the Wonji Shoa Sugarcane Estate using the Surface Energy Balance Algorithm for Land (SEBAL), Simplified Surface Energy Balance (SSEB) and Operational Simplified Surface Energy Balance (SSEBop) algorithms. The results obtained revealed that the ranges of the daily ETa estimated on January 25, February 26, September 06 and October 08, 2002 using SEBAL were 0.0 - 6.85, 0.0 – 9.36, 0.0 – 3.61, 0.0 – 6.83 mm/day; using SSEB 0.0 - 6.78, 0.0 – 7.81, 0.0 – 3.65, 0.0 – 6.46 mm/day, and SSEBop were 0.05 - 8.25, 0.0 – 8.82, 0.2 – 4.0, 0.0 – 7.40 mm/day, respectively. The Root Mean Square Error (RMSE) values between SSEB and SEBAL, SSEBop and SEBAL, and SSEB and SSEBop were 0.548, 0.548, and 0.99 for January 25, 2002; 0.739, 0.753, and 0.994 for February 26, 2002;0.847, 0.846, and 0.999 for September 06, 2002; 0.573, 0.573, and 1.00 for October 08, 2002, respectively. The standard deviation of ET_a over the sugarcane estate showed high spatio-temporal variability perhaps due to soil moisture variability and surface cover. The three algorithm results showed that well watered sugarcane fields in the mid-season growing stage of the crop had higher ET_a values compared with the other dry agricultural fields confirming that they consumptively use more water. Generally during the dry season, ET_a is limited to water surplus areas only and in wet season, ET_a was high throughout the entire sugarcane estate. The evaporation fraction (ETrF) results also followed the same pattern as the daily ET_a over the sugarcane estate. The total crop and irrigation water requirement and effective rainfall estimated using the Cropwat model were 2468.8, 2061.6 and 423.8 mm/yr for January 2001 planted and 2281.9, 1851.0 and 437.8 mm/yr for March 2001 planted sugarcanes, respectively. The mean annual ET_a estimated for the whole estate were 107 Mm³, 140 Mm³, and 178 Mm³ using SEBAL, SSEB, and SSEBop, respectively. Even though the algorithms should be validated through field observation, they have potential to be used for effective estimation of ET in the sugarcane estate.

It is challenging to apply heat flow through a thermal bridge, which requires the analysis of 2D or 3D heat transfer to building energy simulation(BES). Research on the dynamic analysis of thermal bridges has been underway for many years, but their utilization remains low in BESs. This paper proposes a thermal bridge modeling and a dynamic analysis method that can be easily applied to BESs. The main idea begins with an analogy of the steady-state analysis of thermal bridges. As with steady-state analysis, the proposed method first divides the thermal bridge into a clear wall, where the heat flow is uniform, and the sections that are not the clear wall (the thermal bridge part). For the clear wall part, the method used in existing BESs is applied and analyzed. The thermal bridge part (TB part) is modeled with the linear time-invariant system (LTI system) and the system identification process is performed to find the transfer function. Then, the heat flow is obtained via a linear combination of the two parts. This method is validated by comparing the step, sinusoidal and annual outdoor temperature response of the finite differential method(FDM) simulation. When the thermal bridge was modeled as a third-order model, the root mean square error(RMSE) of annual heat flow with the FDM solution of heat flow through the entire wall was about 0.1W.

Population-based data on hematologic malignancies (HM) are rare in Greece regarding adults (≥18 years old). The aim of this study was the assessment of the burden of these malignant neoplasms (MN) for adults in Crete. The study assessed temporal trends of incidence and mortality, depicted their spatial distribution and extracted net-survival curves of patients. Population-data on these MN were obtained from the database of the Cancer Registry of Crete, for a 22 year time period (1/1/1992-31/12/2013). All HM were classified into four main groups of diseases: (1) Hodgkin’s lymphoma (HL); (2) Non-Hodgkin’s lymphomas (NHLs); (3) Multiple myeloma (MM); and (4) All chronic and acute leukemias. Annual, gender-specific, age standardized incidence and mortality rates were estimated (ASIR/100.000/year; ASMR/100.000/year). A total of 3,380 newly diagnosed cases were included in the final analyses; All ASIRs/100,000 increased significantly throughout the study period presenting differences in their geographical distribution of rates among municipalities of Crete. ASIRs for NHLs, HL, MM, leukemias and for all 4 MN were 13.1, 2.6, 4.7, 11.7 and 32.1, respectively, in 2013. Five-year net-survival for patients diagnosed with NHLs, HL, MM and leukemias were: 82%, 85%, 52% and 56%, respectively. This first research article studying a long period of time for adults in Greece generates hypotheses on the existence of risk factors that may partly explain this variation of rates.

The development of electric aircrafts is becoming an important technology for achieving the goals set by the European Commission for the reduction of gases emissions by 2050 in the aeronautical transportation system. However, there is a gap between the values of specific power in commercial electric machines and the ones required for aeronautical applications. Therefore, the search for alternative materials and non-conventional designs is mandatory. One emergent solution is using superconducting machines and systems to overcome the current limits of conventional electrical machines. This work reviews the new hybrid and all-electric aircraft tendencies, complementing it with recent research on the design and development of high specific power superconducting machines. This includes the main topologies for hybrid and all-electric aircraft, with an overview of the ongoing worldwide projects of these types of aircrafts, systematizing the main characteristics of their propulsion systems. It also includes the research on superconducting machines for the purpose of high specific power, considering the impact on the redesign of aircraft systems in the electrical, cooling, and fuel source sense.

Mass transfer restrictions of scaffolds are currently hindering the development of three-dimensional (3D), clinically viable, and tissue engineered constructs. For this situation, a 3D poly(lactide-co-glycolide)/hydroxyapatite porous scaffold, which was much favorable for transfer of nutrients to and waste products from the cells in the pores, was developed in this study. The 3D scaffold had an innovative structure, including macropores with diameters of 300−450 μm for cell ingrowth and microchannels with diameters of 2−4 μm for nutrition and waste exchange. The mechanical strength in wet state was strong enough to offer the structural support. The typical structure was more beneficial for the attachment, proliferation, and differentiation of rabbit bone marrow mesenchymal stem cells (rBMSCs). The alkaline phosphatase (ALP) activity and calcium (Ca) deposition were evaluated on the differentiation of rBMSCs, and the results indicated that the microchannel structure was very favorable for differentiating rBMSCs into maturing osteoblasts. For repairing rabbit radius defects in vivo, there was rapid healing in the defects treated with the 3D porous scaffold with microchannels, where the bridging by a large bony callus was observed at 12 weeks post-surgery. Based on the results, the 3D porous scaffold with microchannels was a promising candidate for bone defect repair.

Malaria parasites increase their host erythrocyte’s permeability to obtain essential nutrients from plasma and facilitate intracellular growth. In the human P. falciparum pathogen, this increase is mediated by the plasmodial surface anion channel (PSAC) and has been linked to CLAG3, as encoded by one member of the conserved clag multigene family. Whether paralogs encoded by other clag genes also contribute to PSAC formation or serve unrelated roles remains unknown. Here, we generated transfectant lines carrying epitope-tagged versions of each CLAG. Each paralog colocalized with CLAG3, with concordant trafficking via merozoite rhoptries to the host erythrocyte membrane of newly-invaded erythrocytes. Each also exists within infected cells in at least two forms: an alkaline-extractable soluble form and a form integral to the host membrane. Like CLAG3, CLAG2 has a variant region cleaved by extracellular protease but CLAG8 and CLAG9 are protease-resistant. Paralog knockout lines, generated through CRISPR/Cas9 transfection, exhibited uncompromised growth in PGIM, a modified medium with more physiological nutrient levels; this finding is in marked contrast to a recently reported CLAG3 knockout parasite. CLAG2 and CLAG8 knockout lines exhibited compensatory increases in transcription of remaining clags and associated rhoph genes, yielding increased PSAC-mediated uptake to specific solutes. We also report distinct transport properties of these knockout lines, suggesting partially overlapping roles of CLAG paralogs in PSAC activity. We propose that the nutrient channel pore is formed by a higher order assembly of CLAG proteins at the host membrane.

In this paper, we prove the existence of three solutions for a $p$-Kirchhoff problem with $\psi$-Hilfer fractional derivative. To be more precise, we use the variational method and we prove that the associated functional energy admits a critical point in each of the three constructed sets, these critical points are weak solutions for a studied problem. Moreover, by definition of these sets, one of these solutions is positive, the second is negative, and the third one change sign. At the end of this work, we present an example to validate our main results.

This research employs a spatial optimization approach customized for addressing equitable emergency medical facility location problems, through the p-dispersed-median problem (p-DIME). The p-DIME integrates two conflicting classes of spatial optimization problems, dispersion, and median problems, aiming to identify the optimal locations for emergency medical facilities to achieve a balanced spatial distribution of emergency medical services (EMS) while effectively serving demands. To demonstrate the utility of the p-DIME model, we selected Gyeongsangbuk-do in South Korea, recognized as one of the most challenging areas for providing EMS to the elderly population (aged 65 and over). This challenge arises from the significant spatial disparity in the distribution of emergency medical facilities. The results of the model assessment gauge the spatial disparity of EMS, provide significantly enhanced solutions for a more equitable EMS distribution in terms of service coverage, and offer policy implications for future EMS location planning. In addition, to address the computational challenges posed by p-DIME's inherent complexity, involving mixed-integer programming, this study introduces a solution technique through constraint formulations aimed at tightening the lower bounds of the problem's solution space. The computational results confirm the effectiveness of this approach in ensuring reliable computational performance, with significant reductions in solution times, while still producing optimal solutions.

The global malaria community has picked up the theme of malaria elimination in greater than 90 % of the world’s population in the next decade. The recent reports of P. vivax in all sub-Saharan Africa, including Duffy negative individuals, threaten the efforts to achieve elimination. This is not only in view of strategies that are tailored only to P. falciparum elimination, but also due to currently revealed biological characteristics of P. vivax concerning the relapse patterns of hypnozoites and conservation of a large biomass at cryptic sites in the bone marrow and spleen. A typical scenario has been observed in Botswana from the period between 2008 to 2018, which palpably projects how P. vivax could endanger efforts at malaria elimination where the two parasites co-exist. The need for the global malaria community, NMPs, funding agencies and relevant stakeholders to engage in a forum to discuss and recommend clear pathways for sub-Saharan Africa regarding malaria elimination including P. vivax, is warranted.

The communication link between the base station and the mobile sensor networks, such as multi-agent systems for collaborative tasks which include ground mobile robots and drones, is crucial for localization and success of tasks in indoor environments. The Power-domain Non-Orthogonal Multiple Access (P-NOMA) is an emerging multiplexing technique that enables the base station to accumulate signals for different agents using the same time-frequency channel. The environment information such as distance from the base station is required at the base station to calculate communication channel gains and allocate suitable signal power to each agent. The accurate estimate of the position for power allocation of P-NOMA in a dynamic environment is challenging due to changing location of the end-agent and shadowing. In this paper, we take advantage of the two-way Visible Light Communication (VLC) link to: (1) estimate the position of the end-agent in a real-time indoor environment based on the signal power received at the base station and (2) allocate resources using the Simplified Gain Ratio Power Allocation (S-GRPA) scheme with the look-up table method. In addition, we use the Euclidean Distance Matrix (EDM) to estimate the location of the end-agent whose signal was lost due to shadowing.

A renewable cyclic monoterpene obtained from citrus peel, limonene is widely used as a fra-grance, nutraceutical ingredient, antibacterial, biopesticide, and green extraction solvent. Indus-trial demand largely exceeds supply. After reviewing recent advances in the recovery of limonene from citrus peel and residues with a particular attention to benign-by-design extractive processes, we focus on the latest results in its dehydrogenation to p-cymene via heterogeneous catalysis.

Bacteria develop various defense mechanisms against stresses, including the bacteriophage infection. The giant phiKZ phage infection induced the appearance of a pseudo-nucleus inside the bacterial cytoplasm. Here, we used FISH, electron tomography and analytical electron microscopy to study the morphology of this unique nucleus-like shell and to demonstrate the distribution of phiKZ and bacterial DNA in infected P. aeruginosa cells. The maturation of the pseudo-nucleus was traced in short intervals for 40 min after infection. This study was accompanied by the identification of phiKZ and bacterial DNA by real-time RCR. We demonstrated that phage DNA that isolated from the cytoplasm during all infection stages were compacted within the pseudo-nucleus in a specific structure. Bacterial DNA was diminished in the course of infection, but did not completely degrade until at least 40 min after phage application. The content of the total phage DNA, on the other hand, increased. EDX analysis confirmed these results and revealed that, during the infection, Sulfur content in the bacterial cytoplasm increased, which suggests the increase of DNA-binding Met-reach proteins synthesis, which could protect bacterial DNA from stress.

Box tree moth, Cydalima perspectalis is native to East Asia where it occurs on Buxus trees. Its natu-ral distribution includes China, Japan, Korea and India, and it was accidentally introduced into Europe, Middle East, North America and north Africa through the trade in Buxus spp., where it can cause considerable damage. In the native range of C. perspectalis, three tachinids (Diptera, Tachinidae) are known to parasitize larvae of C. perspectalis, including Exorista sp., Pseudoperichaeta nigrolineata (Walker 1853) and Compsilura concinnata (Meigen 1824). Data on tachinid parasitoids parasitizing C. perspectalis on the European continent include only P. nigrolineata. Field collection of mature larvae and pupae of C. perspectalis during July 2020 in four locations in Split – Dalmatia County in Croatia resulted in collection of live tachinid larvae that were reared to adults. The tachinid specimens were identified at the Natural History Museum, London, UK, as Nemorilla flo-ralis (Fallén, 1810) (Diptera, Tachinidae). Conservatively, 1.2 – 2.4 % parasitism rate was achieved. This is the first world record of N. floralis parasitism on C. perspectalis larvae, which can be added as a potential tool for C. perspectalis biological control.

RAD51 is a recombinase that plays a pivotal role in homologous recombination. Although the role of RAD51 in homologous recombination has been extensively studied, it is unclear whether RAD51 can be involved in gene regulation as a co-factor. In this study, we found in silico evidence that RAD51 may contribute to the regulation of genes involved in the autophagy pathway through interaction with E-box proteins such as USF1, USF2, and/or MITF in GM12878, HepG2, K562, and MCF-7 cell lines. The canonical USF binding motif (CACGTG) was significantly identified at RAD51 binding sites in all four cell lines. In addition, genome-wide USF1, USF2, and/or MITF-binding regions significantly coincided with the RAD51-binding sites in the same cell line. Interestingly, the promoters of genes associated with the autophagy pathway were significantly occupied by RAD51 in all four cell lines. Taken together, these results predicted a novel role of RAD51 that had not been addressed previously, and provided evidence that RAD51 could possibly be involved in regulating genes associated with the autophagy pathway, through interaction with E-box binding proteins.

Ucuùba fat is fat obtained from a plant found in South America, mainly in Amazonian Brazil. Due to its biocompatibility and bioactivity, the Ucuùba fat was used for production of ketoconazole-loaded nanostructured lipid carriers (NLC) in view of an application for the treatment of onychomycosis and other persistent fungal infections. The development and optimization of the Ucuùba fat based NLC were performed using a Box-Behnken design of experiment. The independent variables were surfactant concentration (% w/v), liquid lipids concentration (% w/v), solid lipids concentration (% w/v), while the outputs of interest were particle size, polydispersity index (PDI) and drug encapsulation efficiency (EE). The Ucuùba fat based NLC were produced and the process optimized determining a predictive mathematical model. Applying the model, two formulations with the pre-required particle size, i.e., 30 and 85 nm, were produced for further evaluation. The optimized formulations were characterized and showed a particle size in agreement to the predicted value, i.e. 33.6 nm and 74.6 nm, respectively. The optimized formulations were also characterized using multiple techniques in order to investigate the solid state of drug and excipients (DSC and XRD), particle morphology (TEM) and interactions between the formulation components (FTIR). Furthermore, particle size and surface charge of the formulations was studied during a one-month stability study and did not evidence any significative modification during storage.

Background/Objectives: This literature review, on occasion of the reported case report, explores the complex interplay between gabapentin (GBP), a gamma-aminobutyric acid (GABA) analog, and the hypothalamic-pituitary-adrenal (HPA) axis in patients undergoing major surgical procedures. It specifically investigates the potential impact of GBP on cortisol levels, stress responses, and infection risk, illustrated by a detailed clinical case. Methods: This review combines a comprehensive literature search with a case report of a 17-year-old male with osteosarcoma who experienced transient adrenal insufficiency and infections while receiving GBP. The case is analyzed in the context of existing literature on GBP and the HPA axis. Results: The findings highlight the intricate relationship between GBP use, adrenal insufficiency, and infection susceptibility. It underscores the need for further research and clinical vigilance when prescribing GBP to patients with underlying medical conditions, particularly in the context of major surgical procedures. The review underscores the need for further research and clinical vigilance when prescribing GBP, particularly in perioperative settings. Conclusions: GBP’s effects on the HPA axis and immune responses are complex and multifaceted. Clinicians should exercise caution when prescribing GBP, especially for patients with underlying conditions undergoing major surgery. Further research is needed to elucidate the mechanisms of GBP's influence on cortisol levels and stress responses.

The effect of sonication on the molecular characteristics of poliacrylic acid (Carbopol® Ultrez 10) and its rheological behavior in aqueous dispersions and microgels containing 0.25 wt. % of the polymer was analyzed in this work by rheometry, weight-average molecular weight (Mw) measurements via static light scattering (SLS), Fourier transform infrared (FTIR) spectroscopy and confocal microscopy. For this, the precursor dispersion and the microgels were sonicated in a commercial ultrasound bath at constant power and different times. We observed a softening of the microgel microstructure consisting of a systematic decrease in its shear modulus, yield stress and viscosity with increasing sonication time, while their overall Herschel-Bulkley (H-B) behavior was preserved. SLS measurements evidenced a reduction of Mw of polyacrylic acid with sonication time. Separately, FTIR measurements indicate that sonication produces scission in the C-C links of the Carbopol® backbone, which results in chains with the same chemistry but lower molecular weight. Finally, confocal microscopy measurements revealed a concomitant diminution of the size of the microsponge domains with sonication time, which is reflected in a softer microstructure resulting from reduction of the molecular weight of polyacrylic acid. The present results indicate that both the microstructure and the rheological behavior of Carbopol® microgels, in particular, and complex fluids in general, may be manipulated or tailored by high-power ultrasonication.

The recently discovered Gaia BH1 binary system, a Sun-like star and a dark object (presumably a black hole), may significantly change our understanding of the population of low-q binaries. The paper presents the components mass ratio distributions of binary systems of different observational classes. They all demonstrate a significant shortage of low-q systems. It is shown that this shortage can be filled with the help of search and study of objects like Gaia BH1.

A second order rational difference equation $$x_{n+1}=px_{n}+\frac{q}{x_{n-1}^2}$$ with the parameters $p$ and $q$ which lies in $(0,1)$, is studied. The dynamics of the equilibrium is characterized through the trichotomy of the parameter $p<\frac{1}{2}$, $p=\frac{1}{2}$ and $p>\frac{1}{2}$. It is found that there is no periodic solution of period $2$ and $3$ but there exists periodic solutions with only periodic solution $5$ and $10$ are achieved computationally.

The proliferation of mobile and IoT devices, coupled with the advances in the wireless communication capabilities of these devices, have urged the need for novel communication paradigms for such heterogeneous hybrid networks. Researchers have proposed opportunistic routing as a means to leverage the potentials offered by such heterogeneous networks. While several proposals for multiple opportunistic routing protocols exist, only a few have explored fuzzy logic to evaluate wireless links status in the network to construct stable and faster paths towards the destinations. We propose FQ-AGO, a novel Fuzzy Logic Q-learning Based Asymmetric Link Aware and Geographic Opportunistic Routing scheme that leverages the presence of long-range transmission links to assign forwarding candidates towards a given destination. The proposed routing scheme utilizes fuzzy logic to evaluate whether a wireless link is useful or not by capturing multiple network metrics, the available bandwidth, link quality, node transmission power, and distance progress. Based on the fuzzy logic evaluation, the proposed routing scheme employs a Q-learning algorithm to select the best candidate set toward the destination. We implement FQ-AGO on the NS-3 simulator and compare the performance of the proposed routing scheme with three other relevant protocols: AODV, DSDV, and GOR. For precise analysis, we consider various network metrics to compare the performance of the routing protocols. Our simulation result validates our analysis and demonstrates remarkable performance improvements in terms of total network throughput, packet delivery ration, and end-to-end delay.

Soft-Core architecture for Analogue to Digital Converter (ADC) sampling is useful for mixed signal applications. Soft-core architecture for cutting edge odd or even ADC sampling with interface to block RAM memory has not been found. Soft-core architecture as a concept has become popular due to the advantage of customization for different applications as compared to general-core architecture suited for single application. The latest generation of piece wise sampling is odd sampling and was introduced in the second decade of the 20th century. Odd and even order sampling techniques are analogue in nature driven by a tuned (tuned for odd or even) mixer. This paper proposes a third-generation piece wise sampling with soft-core architecture that enables an option to select both odd and even while interfacing to memory mapping. The proposed odd/even has superior SNR performance of 6 dB as compared to existing architecture such as Mod-∆ which recorded worst performance of 18 dB. Advances in soft-core technology have allowed a niche odd/even switching field to be identified and studied, the study has also been extended to include memory architecture.

A prominent class of reactions, reductive aminations are used extensively in research labs and industry to synthesize amines; which are applied in a variety of medicines, agrochemicals, and biomolecules. Amine compounds are essential in many aspects of life; amino groups exist in many natural and agricultural products. New 4-(benzylamino)benzoic acid derivatives with general formula of C14H12NO2R, where [R= (H), (4-Cl), (4-NMe), (4-Br), (3-NO2), (4-NO2), (2-OMe), (3-OMe), (4-OMe), (2,3-OMe), (3,4-OMe), (2-OH, 3-OMe), (3-OMe, 4-OH), (3,5-OMe, 4-OH), (2-OH, 5-Br), (3-OH), (4-SMe), (2,3-OH), (3-CF3)] (compounds 1-19) were obtained by reductive amination reaction via reacting p-amino benzoic acid with benzaldehyde derivatives and sodium borohydride. All prepared compounds has been characterized by a variety of spectroscopic techniques (HRMS, FT-IR, 1H, and 13C{1H} NMR) and elemental analysis. Furthermore, the structure of some of the synthesized derivatives were confirmed by single crystal X-ray diffraction (R = 4-Cl, 4-Br, 2-OMe, 3-OMe, 4-OMe, 2,3-OMe), compounds 2, 4, 7-9 and 11, respectively. Moreover, some of these new compounds have shown somehow moderate antibacterial activities against different strains of bacteria (gram-positive and gram-negative) with MIC values ranging from 64-256 µg/ mL. The anticancer activities of all compounds (IC50 values, µM) were evaluated against different cell lines, HGF (Fibroblasts; normal cell line), A549 (Non-Small Cell Lung Cancer cell line) and H69 (Small Cell Lung Cancer cell line). Compound 18 showed a considerable IC50 value of 90.69 against A549 and an excellent value of 32.22 and H69, respectively.

To reveal the relationship between metallodrugs and cancer malignancy, molecular networks of anti-cancer drugs were analyzed. Molecular networks in several types of cancers were analyzed in Ingenuity Pathway Analysis (IPA). Analysis of carboplatin revealed the causal network in diffuse large B-cell lymphoma. Analysis of 12 analyses of cisplatin treatment identified causal networks including camptothecin and NUPR1. The causal network of camptothecin, which includes PTEN, FAS, and IRF1, was inactivated in diffuse-type GC and activated in intestinal-type GC. Upstream regulator analysis of cisplatin revealed an increase in FAS, BTG2, SESN1 and CDKN1A, and the involvement of the tumor microenvironment pathway. Upstream regulators of cisplatin-treated lung adenocarcinoma included a histone deacetylase inhibitor, trichostatin A (TSA). Causal network of arsenic was inactivated in diffuse-type GC and activated in intestinal-type GC, and included ERK, EGFR, SRC, IKK and TP53. Prediction of RNA-RNA interactions with the causal network of arsenic identified 10 microRNAs including mir-101, mir-103, and mir-22. The results revealed the involvement of EMT in arsenic treatment. Analysis of oxaliplatin, a platinum drug, revealed that the SPINK1 pancreatic cancer pathway is inactivated in ischemic cardiomyopathy. The study showed the importance of the relationship between platinum drugs or arsenic trioxide and the tumor microenvironment in the treatment of resistant cancer in humans.

Certain Trichoderma isolates provide biofertilizer, biocontrol, and other plant-beneficial activities while inhabiting the soil or internal plant issues; and their use in agricultural systems could contribute to sustainable food production. It is thought that this colonization of soil and internal plant tissues is fundamental for biocontrol and biofertilizer applications. Our collective analyses of prior surveys, where the tef1 sequence was almost exclusively used to identify Trichoderma species, showed that isolates from the Harzianum Complex Clade, the T. asperellum/T. asperelloides group, T. virens, T. hamatum, and T. atroviride were prevalent in soil and/or as endophytes. Population structure and genetic diversity of these species were investigated, and new lineages with geo-graphic significance within T. atroviride, T. asperellum, T. hamatum, and T. virens populations were found. The nearest relatives of some species were also revealed. Choosing isolates from among more than 500 known Trichoderma species for use in non-targeted evaluation screens for biocontrol or biofertilizer applications is time-consuming and expensive. Preferentially selecting species from T. atroviride, T. asperellum/T. asperelloides, T. hamatum, species from the T. harzianum Complex Clade, T. virens, and possibly nearest relatives, may speed the identification of candidates for commercialization due to the demonstrated ability of these species to successfully inhabit the soil and endorhizosphere. To our knowledge, this is the first report where dominant soil- and en-dophyte-inhabiting Trichoderma species were identified from past survey data and population structure and genetic diversity analyses conducted.

Volumetric modification of transparent materials by femtosecond laser pulses is successfully used in a wide range of practical applications. The level of modification is determined by the locally absorbed energy density, which depends on numerous factors. In this work, it is shown experimentally and theoretically that, in a certain range of laser pulse energies, the peak of absorption of laser radiation for doughnut-shaped (DS) pulses is several times higher than for Gaussian ones. This makes the DS pulses very attractive for material modification and direct laser writing applications. Details of the interaction of laser pulses of Gaussian and doughnut shapes with fused silica obtained by numerical simulations are presented for different pulse energies and compared with the experimentally obtained data. The effect of absorbed energy delocalization with increasing laser pulse energy is demonstrated for both beam shapes while, at relatively low pulse energies, the DS beam geometry provides a stronger local absorption compared to Gaussian one. Implications of a DS pulse action on post-irradiation material evolution are discussed based on thermoelastoplastic modeling.

Since the onset of coronavirus disease 2019 (COVID-19) pandemic, the virus kept developing and mutating into different variants over time that also gained increased transmissibility and spread in populations at a higher pace, culminating in successive waves of COVID-19 cases. The scientific community has developed vaccines and antiviral agents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease. Realizing that growing SARS-CoV-2 variations significantly impact the efficacy of antiviral therapies and vaccines, we have summarized the appearance and attributes of SARS-CoV-2 variants for future perspectives in drug design, bringing up-to-date hints for developing therapeutic agents targeting the variants. The Omicron variant is among the most mutated form; its strong transmissibility and immune resistance capacity have prompted international worry. Most mutation sites currently being studied are located in the BCOV_S1_CTD of the S protein. Despite this, several hurdles remain, such as developing vaccination and pharmacological treatment efficacies for emerging mutants of SARS-CoV-2 strains. In this review, we present an updated viewpoint on the current issues faced by the emergence of various SARS-CoV-2 variants. Furthermore, we discuss the clinical studies conducted to assist the development and dissemination of vaccines, small molecule therapeutics, and therapeutic antibodies having broad-spectrum action against SARS-CoV-2 strains.

Food insecurity remains a significant developmental challenge, particularly in rural areas, despite ongoing efforts to mitigate it. To better understand the persistence of this issue, this study investigates the causes of household food insecurity and the coping strategies employed by households in Zorkor Goo, Zorkor Kanga, and Zorkor Kadaare communities within the Bongo District of Ghana’s Upper East Region. A descriptive cross-sectional survey was conducted, sampling 196 households systematically from these communities. Data were collected through a structured questionnaire covering socio-demographic factors, causes of food insecurity, household coping strategies, and dietary intake. The analysis was performed using SPSS (Version 21.0), with food security status and dietary intake assessed via the FANTA Household Food Insecurity Access Scale (HFIAS) and Food Consumption Score, respectively. The study identified key factors contributing to food insecurity, including soil infertility, poor rainfall patterns, food spoilage, extravagant funerals, large family size, high unemployment, and lack of education. Major coping strategies among households included meal skipping, reducing meal size and frequency, migration, asset sales, and basket weaving. The findings revealed that 96.4% of households were severely food insecure, and over two-thirds (67.3%) exhibited poor dietary consumption. Notably, household employment levels, education, and food consumption scores were significantly associated with food insecurity (P&lt;0.001). These findings underscore the need for targeted interventions addressing the root causes of food insecurity and enhancing household resilience in these communities.

The stock beta coefficient literature extensively discusses the proper methods for the estimation of beta as well as its use in asset valuation. However, there are relatively few references with respect to the appropriate time horizon that investors should utilize when evaluating the risk-return relationship of a stock. We examine the appropriate time horizon for beta estimation differentiating our results by sector according to the Industry Classification Benchmark. We employ data from the NYSE and we estimate varying lengths of beta employing data from 30 to 250 trading days. The constructed beta series is then examined for the presence of breaks using the endogenous structural break literature. Results show evidence against the use of betas that employ more than 90 trading days of data provisional to the sector under study.

Time evolution of the quantum correlation of the hybrid qubit-qutrit system in multilocal and global dephasing under the effect of a classical noises environment is presented. We considered the qutrit in z direction and the qubit x direction. In addition, our system presents two configurations: the different and the common environment and our discussion involves three types of noises: A Static Noise (SN), Random Telegraph Noise (RTN) and Ornstein- Uhlenbeck noise (OU). By using the density matrix approach to determine the evolution of the state of the system, the found that the static noise is fatal for the quantum entanglement, the quantum correlation and for RTN and OU noises the quantum entanglement, the quantum correlation decreases monotonically with a sufficiently long time. Therefore, we can say that, entanglement and the quantum correlation are more robust to the noise precisely those Random telegraph noise and Ornstein-Uhlenbeck noise.

Even if the field of medicine has made great strides in recent years, infectious diseases caused by novel viruses that damage the respiratory system continue to plague people all over the world. This type of virus is very dangerous, especially for people who deal with serious long-term breathing problems, like triggering asthma, pneumonia, or bronchitis infections. Thus, this paper demonstrates a new Secure Machine Learning Monitoring System for a model for virus detection. Our proposed model makes use of 4 basic emerging technologies, Internet of Things (IoT), Wireless Sensor Networks (WSN), Cloud Computing (CC), and Machine Learning (ML), to detect dangerous types of viruses that infect people or animals causing panic worldwide and deregulating human daily life. The proposed system is a robust system that could be established in various buildings, like hospitals, entertainment halls, universities, etc., and will provide accuracy, speed, and privacy for data collected in the detection of viruses.

Globally, there is massive uptake and explosion of data and challenge is to address issues like scale, pace, velocity, variety, volume and complexity of this big data. Considering the recent epidemic in China, modeling of COVID-19 epidemic for cumulative number of infected cases using data available in early phase was big challenge. Being COVID-19 pandemic during very short time span, it is very important to analyze the trend of these spread and infected cases. This chapter presents medical perspective of COVID-19 towards epidemiological triad and the study of state-of-the-art. The main aim this chapter is to present different predictive analytics techniques available for trend analysis, different models and algorithms and their comparison. Finally, this chapter concludes with the prediction of COVID-19 using Prophet algorithm indicating more faster spread in short term. These predictions will be useful to government and healthcare communities to initiate appropriate measures to control this outbreak in time.

In-plane electro-optical switching (IPS) is a natural feature of a conventional planar aligned display cell based on deformed helix ferroelectric liquid crystal effect (DHFLC-effect) with sub-wavelength helix pitch if the tilt angle close to 40 degrees.

Japanese encephalitis virus is a mosquito-borne member of the Flaviviridae family. JEV is the leading cause of viral encephalitis in Asia and is characterized by encephalitis, high lethality and neurological sequelae in survivors. The virus also causes severe disease in swine, which are an amplifying host in the transmission cycle, and in horses. US agricultural authorities have recently recognized the threat to the swine industry and initiated preparedness activities. Other mosquito-borne viruses exotic to the Western Hemisphere have been introduced and established in in recent years, including West Nile, Zika, and chikungunya viruses, and JEV has recently invaded continental Australia for the first time. These events amply illustrate the potential threat of JEV to US health security. Susceptible indigenous mosquito vectors, birds, feral and domestic pigs, and possibly bats, constitute the receptive ecological ingredients for spread of JEV in the US. Fortunately, unlike the other virus invaders mentioned above, an inactivated whole virus JE vaccine (IXIARO®) has been approved by the US Food & Drug Administration for human use in advance of a public health emergency, but there is no veterinary vaccine. This paper describes the risks and potential consequences of introduction of JEV in the US, the need to integrate planning for such an event in public health policy and the requirement for additional countermeasures, including antiviral drugs and an improved single dose vaccine that elicits durable immunity in both humans and livestock.

Based upon 30-years of research by the author a new approach to hospital bed planning and international benchmarking is proposed. The number of hospital beds per 1000 population is commonly used to compare international bed numbers. This method is flawed because it does not consider population age structure or the effect of nearness-to-death on hospital utilization. Deaths are also serving as a proxy for wider bed demand arising from undetected outbreaks of 3000 species of human pathogens. To remedy this problem a new approach to bed modelling has been developed which plots beds per 1000 deaths against deaths per 1000 population. Lines of equivalence can be drawn on the plot to delineate countries with higher or lower bed supply. This method is extended to attempt to define the optimum region for bed supply in an effective health care system. England is used as an example of a health system descending into operational chaos due to too few beds and manpower. The former Soviet bloc countries represent a health system overly dependent on hospital beds. Several countries also show evidence for over-utilization of hospital beds. The new method is used to define a potential range for bed supply and manpower where the current most effective health systems currently reside. The method is applied to total curative beds, medical beds, psychiatric beds, critical care, geriatric care, etc., and can also be used to compare different types of healthcare staff, i.e., nurses, physicians, surgeons. Issues surrounding the optimum hospital size and the optimum average occupancy will also be discussed. The role of poor policy in the English NHS is used to show how the NHS has been led into a bed crisis. The method is also extended beyond international benchmarking to illustrate how it can be applied at a local or regional level in the process of long-term bed planning. Issues regarding the volatility in hospital admissions are also addressed to explain the need for surge capacity and why an adequate average bed occupancy margin is required for an optimally functioning hospital.

In estimating the maximum and minimum index void ratios for mixtures of sand and silt, the values of several empirical constants must be determined based on the type of sand and silt involved. These empirical constants are the filling coefficient, a, and embedment coefficient, b, both of which can be determined either through lab testing or correlations. These constants are then used in equations to predict the maximum and minimum index void ratios of the sand-silt mixtures. The study reported here developed simple correlations for estimating the filling and embedment coefficients using readily obtained laboratory data. These models were found to be excellent in developing filling and embedment coefficients that accurately (R2 values typically of 0.94 or greater.) predicted values of the index void ratios for sand and silt mixtures.

There are four commercial pathways to make grill charcoal from wood. These have been modelled to calculate a carbon intensity (CI) for each. Results are presented along with discussion of the sensitivities: biogenic carbon; quality of the charcoal; classification of products, wastes and residues; and division of burden. Grill charcoal’s CI ranges greatly, depending on the pathway by which it is produced. Wood distillation, a commercial process that once was common but now is rare, has a CI 50+% lower than that of the next-lowest commercial process, Kilns. Earth mounds/pits and external-fuelled Retorts have CIs considerably higher still. The carbon efficiency (CE) of Wood distillation is more than twice that of the next-best, again Kilns. CE is defined as normalised, total carbon emitted. This is not the same as CI, it is not usually considered in studies such as this, yet it is important for climate impact. CE could be a useful measure in assessments (such as this) where biogenic carbon is significant.

While investigating the outcomes of balloon dilatation procedures in patients with congenital obstructive lesions of the heart, several parallel observations have been made. The purpose of this review is to present these observations/phenomena/innovations related to balloon dilatation of pulmonary stenosis (PS), aortic stenosis (AS), and aortic coarctation (AC). In subjects who had balloon pulmonary valvuloplasty (BPV), development of infundibular obstruction, electrocardiographic (ECG) changes, changes in right ventricular filling, role of balloon/annulus ratios on the results of BPV, and double balloon vs. single balloon BPV will be reviewed. In patients who had balloon aortic valvuloplasty (BAV), causes of aortic insufficiency and trans-umbilical venous approach for BAV will be tackled. In children who had balloon angioplasty (BA) of AC, aortic remodeling and biophysical response after BA of AC will be discussed.

There must exist a reformulation of quantum field theory, even at low energies, which does not depend on classical time. The octonionic theory proposes such a reformulation, leading to a pre-quantum pre-spacetime theory. The ingredients for constructing such a theory, which is also a unification of the standard model with gravitation, are : (i) the pre-quantum theory of trace dynamics – a matrix-valued Lagrangian dynamics, (ii) the spectral action principle of non-commutative geometry, (iii) the number system known as the octonions, for constructing a non-commutative manifold and for defining elementary particles via Clifford algebras, (iv) a Lagrangian with $E_8 \times E_8$ symmetry. The split bioctonions define a sixteen dimensional space (with left-right symmetry) whose geometry (evolving in Connes time) relates to the four known fundamental forces, while predicting two new forces, $SU(3)_{grav}$ and $U(1)_{grav}$. This latter interaction is possibly the theoretical origin of MOND. Coupling constants of the standard model result from left-right symmetry breaking, and their values are theoretically determined by the characteristic equation of the exceptional Jordan algebra of the octonions. The quantum-to-classical transition, precipitated by the entanglement of a critical number of fermions, is responsible for the emergence of classical spacetime, and also for the familiar formulation of quantum theory on a spacetime background.

Estimates by the World Health Authority suggest that 1 billion people do not have access to the assistive technologies they require. Over the past decade, the design of products that empower people with a disability has shifted from specialised and dedicated products designed only for those with a disability to features and functions integrated into cost-effective consumer technologies for the benefit of all. The opportunity for expansion of the availability of such technologies is at risk of being ignored as a result of models of delivery that are founded in medical devices and which have failed to reflect trends in our understanding of technology and the choices and preferences expressed by persons with a disability. This research undertaken suggests that the opportunities of such expansion offer significant benefits to people with a disability and better both economic and social return on investment for authorities.

When gravity is quantum, the point structure of space-time should be replaced by a non-commutative geometry. This is true even for quantum gravity in the infra-red. Using the octonions as space-time coordinates, we construct a pre-spacetime, pre-quantum Lagrangian dynamics. We show that the symmetries of this non-commutative space unify the standard model of particle physics with $SU(2)_R$ chiral gravity. The algebra of the octonionic space yields spinor states which can be identified with three generations of quarks and leptons. The geometry of the space implies quantisation of electric charge, and leads to a theoretical derivation of the mysterious mass ratios of quarks and the charged leptons. Quantum gravity is quantisation not only of the gravitational field, but also of the point structure of space-time.

Financial capacity instruments are psychometric tools designed to evaluate individual decisional capacity based on financial decisions. As tests are complex and need special conditions for administration and evaluation, it is difficult to use them in daily geriatric clinics. Our scoping review objective was to evaluate existing financial capacity instruments from the perspective of simplicity and portability. We evaluated one English speaking knowledge database (Medline) using a dedicated MeSH terminology. The review yielded one independent instrument, The Semi-Structured Clinical Interview for Financial Capacity, that can be easy adapted for every-day clinical use. It is simple to understand and perform and do not need trained personnel for administration. It can be finalized in 15 minutes. Initially validated on 261 subjects (with different forms of cognitive impairment), it showed good accuracy and precision mainly in subjects with cognitive impairment. The test is less apt to detect early or fluctuating cognitive impairment. Simplicity, the main advantage of the test, allows gamification fact that increases portability. Familiar images (coins, money) that are used for performing simple tasks does not need complex translation and adaptation. In form of a game, the test is suitable for serial administration, increasing the chance for early capacity reduction detection. Results reflect a physician judgement related to the subjects’ capacity to understand and execute simple financial instructions and not financial proficiency scores. The main limitation of our review is that we investigated only one, English speaking, knowledge database. The scoping strategy generated a financial capacity instrument that can be used in geriatric clinics for early diagnostic of decisional capacity reduction. Further studies are needed to evaluate the reliability and validity of the test in conditions of serial administration and in populations having various financial experience.

The effect of capitalization premium in forest estate markets on forest management and climate change mitigation economics is investigated. It is shown that proportional goodwill in capitalization induces linear scaling of the financial return, without any contribution to sound management practices. However, there is a financial discontinuity as harvesting deteriorates goodwill. On the contrary, capitalization premium set on bare land as a tangible asset would increase timber storage and carbon sequestration. Observations indicate that the proportional goodwill is closer to reality within the Nordic Region, resulting in continuity problems but a reduced capital expense for carbon storage.

Flowers have always accompanied people thanks to their manifold aesthetic properties. Some species have also become a component of human diet. Recent years have seen an increased interest in edible flowers and, consequently, research has been undertaken to determine their chemical composition. Dyes abundantly contained in flowers, whose role is to attract pollinating animals, are recognized substances with health promoting properties. Anthocyanins are a group of dyes that is very common in petals and other parts of flowers. Studies carried out in the twentieth and twenty-first century have found very strong antioxidant and anti-inflammatory properties of anthocyanins. Therefore, flowers used by humans for centuries to decorate their surroundings may become an easily available source of nutrients and health-promoting substances. This paper discusses the health-promoting properties of anthocyanins and collects literature on anthocyanin content in edible flowers commonly grown on balconies, terraces and roofs.

Two sets of initial conditions are used in the investigation of capital return rate and carbon storage in boreal forests. Firstly, a growth model is applied in young stands as early as the inventory-based model is applicable. Secondly, the growth model is applied to observed wooded stands. Four sets of thinning schedules are investigated in either case. First, the capital return rate is aspired without any restriction. Second, the number of thinnings is restricted to at most one. Third, thinnings are restricted to the removal of only trees thicker than 237 mm. Fourth, commercial thinnings are omitted. The two sets of initial conditions yield similar results. The capital return rate is a weak function of rotation age, which results in variability in the optimal number of thinnings. Reducing the number of thinnings to one increases timber stock but induces a capital return rate deficiency. The deficiency per excess volume unit is smaller if the severity of any thinning is restricted by the removal of large trees only. Omission of thinnings best applies to spruce-dominated stands with stem count less than 2000/ha. Restricted thinning intensity applies to deciduous stands and dense pine stands. The albedo effect increases the benefits of restricted thinnings and increased clearcuttings instead of contradicting the carbon storage.

There must exist a reformulation of quantum field theory which does not refer to classical time. We propose a pre-quantum, pre-spacetime theory, which is a matrix-valued Lagrangian dynamics for gravity, Yang-Mills fields, and fermions. The definition of spin in this theory leads us to an eight dimensional octonionic space-time. The algebra of the octonions reveals the standard model; model parameters are determined by roots of the cubic characteristic equation of the exceptional Jordan algebra. We derive the asymptotic low energy value 1/137 of the fine structure constant, and predict the existence of universally interacting spin one Lorentz bosons, which replace the hypothesised graviton. Gravity is not to be quantized, but is an emergent four-dimensional classical phenomenon, precipitated by the spontaneous localisation of highly entangled fermions.

The impact that new technologies have on all aspects of our lives, work, and businesses is significant and growing over time. Blockchain and artificial intelligence, among other innovative technologies, are having a profound effect on practically all business functions, including most human resources (HR) tasks. The HR sector is currently facing a variety of challenges as HR departments invest many hours in vetting candidates' applications and authenticating records to decrease the chances of imperfect recruiting. Nowadays, more technologically based processes are utilised for talent search, selection and management, as well as for accumulating, retaining, and integrating new talents into a company. These HR practices are far more effective compared to traditional methods but can also be more expensive if the transactional costs are considered. This paper consists of two parts. Following an introduction, the first part discusses the trust and confidentiality that can be attained, while the second part examines security, fraud prevention and the productivity gained from using blockchain technology in HR activities. Finally, there is a concluding section, discussing the implications of blockchain technology for firms who choose to employ it.

Growth and yield of boreal tree species are discussed. A growth model is applied, along with verified yield models of sawlogs and veneer logs. Using the normal forest-principle, thinning schedules and rotation ages maximizing the estate-level capital return rate are clarified. Regeneration expenses are amortized at the end of any rotation. Consequently, capitalizations are greater and rotations longer than in recent studies. The capital return rate is a weak function of initial stem count but differs by tree species. The initial stem count strongly contributes to biomass stored in trees. The most promising way of increasing the capital return rate is the reduction of regeneration expenses. Thinnings are triggered by stand volumes of at least 200 m3/ha. The average commercial trunk volume of trees removed in thinnings always exceeds 200 liters. Risk aversion theory proposes short rotations and low stem count in seedling planting unless carbon storage compensation exists.

Clearly policy makers should consider the impacts of any decisions they might make before making them. Science can provide estimates of various economic, ecologic, environmental, and even social impacts of alternative policies, impacts that determine how effective any particular policy will be. These impact estimates can be used to compare and evaluate alternative policies in the search for identifying the best one to implement. Among all scientists providing inputs to policy making processes are analysts who develop and apply models that provide these estimated impacts and, possibly, their probabilities of occurrence. But just producing them is not a guarantee that they will be considered by policy makers. This paper discusses ways scientists, including systems analysts, can effectively contribute to and inform those involved in making water management decisions. Brief descriptions of a variety of past and on-going water management policy making processes illustrate both some successes and failures of science informing policy.

(1) Background: To investigate the dynamic issues behind international variation in EWM. (2) A rolling EWM calculation is used to reveal seasonal changes in the EWM calculation and is especially relevant nearer to the equator. (3) Results: In addition to latitude country specific factors determine EWM. Females generally show higher EWM mainly due to respiratory conditions. The EWM for respiratory conditions in England and Wales ranges from 44% to 83% which is about double the all-cause mortality equivalent. Age has a profound effect on EWM with a peak in puberty and then increasing EWM at old age. The gap between male and female EWM seems to act as a diagnostic tool reflecting the infectious/metrological mix in each winter. Additional difference due to ethnicity are also observed. An EWM equivalent calculation for sickness absence demonstrates how additional health-related variables can be linked to EWM. (4) Conclusions: EWM does not reach a peak at the same time each year, especially so in the tropics. Countries midway between the equator and the poles show highest EWM. Differences between the genders are highly significant and seem to vary according to the mix of variables active each winter. Pandemic influenza does not elevate EWM, although seasonal influenza plays a part each winter.

An empirical model for log yield from trees is established and applied in microeconomics of carbon storage in a boreal spruce estate. The transition from pulpwood to sawlogs is a smoother function of stem diameter in the empirical data, in comparison to literature values. Correspondingly, the value transition of trees along with increasing size is gentler. Due to price premium of sawlogs from clearcuttings, all economically feasible treatment schedules terminate in clearcutting. Best capital return rates are gained with two heavy thinnings from above before clearcutting. Present carbon emission prices allow moderate carbon storage increment if the increment is compensated by proportional carbon rent. Doubling the present carbon prices would allow strong carbon storage increments if compensated by carbon rent. Application of nonproportional carbon rent is proposed.

Imagination is more important than knowledge, but if intellect does not provide the needed logical structures, capacities for envisioning new possibilities are overly constrained. The sustainability problems we face today cannot be solved with the same kind of thinking that created them, but clarity on what counts as a new kind of thinking is sorely lacking. This article proposes methodical, model-based ways of heeding Bateson's warning about the negative consequences for the ecology of mind that follow from ignoring the contexts of relationships. Informed by S. L. Star's sense of boundary objects, a sequence of increasingly complex logical types distinguishes and interconnects qualitatively different kinds of thinking in ways that liberate imaginative new possibilities for life. The economy of thought instantiated at each level of complexity is only as meaningful, useful, beautiful, ethical, and efficient as the standards informing local adaptive improvisations. Standards mediating the general and specific, global and local, universally transcendent and embodied particulars enable meaningful negotiations, agreements, and communications. Attending to the differences between levels of discourse sets up new possibilities for creative and imaginative entrepreneurial approaches to viable, feasible, and desirable goals for measuring and managing sustainable development.

We review and assess the classic SIR and SEIR epidemiological models regarding possible applications to the COVID-19 pandemic. In spite of numerous more complicated models, we show how the qualitative features of the solution to the SIR and SEIR models continue to provide valuable public health insights in some scenarios. Using estimated COVID-19 data as of this date, the SEIR model shows that if it were possible to reduce R₀ from 2.5 to 1.25 through social distancing and other measures, the maximum fraction of the population that would become infected at any particular time would drop from 17% to 4%, provided that all of the model assumptions are satisfied. Finally, we compare the classic SIR model with a recent stochastic model with favorable results. Since this comparison underscores the importance of underlying connectivity assumptions, we conclude with Monte-Carlo simulations with specific connectivity that reproduce the classical SIR model with standard incidence.

The expense of carbon sequestration in terms of capital return deficiency is investigated at estate level, in the case of a fertile boreal estate dominated by spruce forest. Thinnings from below result as a high expense of increased rotation age, thinnings from above as a small expense. The expense of increased timber stock is greater than any proportional carbon rent based on present carbon prices. Application of non-proportional carbon rent is proposed.

We have used the varying physical constant approach to resolve the flatness problem in cosmology. Friedmann equations are modified to include variability of speed of light, gravitational constant, cosmological constant and the curvature constant. The continuity equation obtained with such modifications includes scale factor dependent cosmological term as well as the curvature term along with the standard energy-momentum term. The result is that as the scale factor tends to zero (i.e. as the big-bang is approached) the universe becomes strongly curved rather than flatter and flatter in the standard cosmology. We have used the supernovae 1a redshift versus distance modulus data to determine the curvature variation parameter of the new model, which yields a better fit to the data than the standard ΛCDM model. The universe is found to be open type with radius of curvature R_c = 1.64 (1+z)^-3.3 c₀/H₀, where z is the redshift, c₀ is the current speed of light and H₀ is the Hubble constant.

We have shown that three astrometric solar-system anomalies can be explained satisfactorily by using evolutionary gravitational constant G and speed of light c in the Einstein’s field equation. These are: a) the Pioneer acceleration anomaly; b) the anomalous secular increase of Moon-orbit eccentricity; and c) the anomalous secular change in the astronomical unit AU. The gravitational constant G and the speed of light c both increase as dG/dt = 5.4GH₀ and dc/dt = 1.8cH₀ with H₀ as the Hubble constant. We also show that the Planck’s constant ħ increases as dħ/dt = 1.8ħH₀. Additionally, the new approach fits the supernovae Ia redshift vs distance modulus data as well as the standard ΛCDM model with just one adjustable parameter H₀.

We have shown that the use of evolutionary gravitational constants G, the speed of light c, and cosmological constant Λ in the Einstein’s field equations leads to a very simple model that fits the supernovae Ia data with a single parameter as well as the standard ΛCDM model with two parameters, and has the predictive capability superior to the latter. We have shown that at the current time G and c both increase as dG/dt = 5.4GH₀ and dc/dt = 1.8cH₀ with H₀ as the Hubble constant, and Λ decreases as dΛ/dt = −1.2ΛH₀. Negative finding on the variation of G with time derived from the analysis of lunar laser ranging data in several studies has been attributed to the fact that these studies did not consider the variation of c simultaneously with G.

Many models have been proposed to explain the intergalactic redshift using different observational data and different criteria for the goodness-of-fit of a model to the data. The purpose of this paper is to examine several suggested models using the same supernovae Ia data and gamma-ray burst (GRB) data with the same goodness-of-fit criterion and weigh them against the standard $\text{Λ}$ CDM model. We have used the redshift – distance modulus ( $z-\mu$ ) data for 580 supernovae Ia with $0.015\le z\le 1.414$ to determine the parameters for each model, and then use these model parameter to see how each model fits the sole SNe Ia data at $z=1.914$ and the GRB data up to $z=8.1$ . For the goodness-of-fit criterion, we have used the chi-square probability determined from the weighted least square sum through non-linear regression fit to the data relative to the values predicted by each model. We find that the standard ΛCDM model gives the highest chi-square probability in all cases albeit with a rather small margin over the next best model - the recently introduced nonadiabatic Einstein de Sitter model. We have made ( $z-\mu$ ) projections up to $z=1096$ for the best four models. The best two models differ in $\mu$ only by 0.328 at $z=1096$ , a tiny fraction of the measurement errors that are in the high redshift datasets.

We have developed a cosmological model by allowing the speed of light c, gravitational constant G and cosmological constant Λ in the Einstein filed equation to vary in time, and solved them for Robertson-Walker metric. Assuming the universe is flat and matter dominant at present, we obtain a simple model that can fit the supernovae 1a data with a single parameter almost as well as the standard ΛCDM model with two parameters, and has the predictive capability superior to the latter. The model, together with the null results for the variation of G from the analysis of lunar laser ranging data determines that at the current time G and c both increase as dG/dt = 5.4GH0 and dc/dt = 1.8cH0 with H0 as the Hubble constant, and Λ decreases as dΛ/dt = -1.2ΛH0. This variation of G and c is all what is needed to account for the Pioneer anomaly, the anomalous secular increase of the Moon eccentricity, and the anomalous secular increase of the astronomical unit. We also show that the Planck’s constant ħ increases as dħ/dt = 1.8ħH0 and the ratio D of any Hubble unit to the corresponding Planck units increases as dD/dt = 1.5DH0. We have shown that it is essential to consider the variation of all the physical constants that may be involved directly or indirectly in a measurement rather than only the one whose variation is being considered.