NF-B signalling is crucial for cellular responses to inflammation but has also been associated with the hypoxia response. NF-B and HIF transcription factors possess an intense molecular crosstalk. Although it is known that HIF-1beta modulates NF-kappaB transcriptional response, very little is understood regarding how HIF-1beta contributes to NF-kappaB signalling. Here, we demonstrate that HIF-1beta is required for full NF-kappaB activation in cells following canonical and non-canonical stimuli. We found that HIF-1beta specifically controls TRAF6 expression in human cells but also in Drosophila melanogaster. HIF-1beta binds to the TRAF6 gene and controls its expression independently of HIF-1alpha. Furthermore, exogenous TRAF6 expression is able to rescue all of the cellular phenotypes observed in the absence of HIF-1beta. These results indicate that HIF-1beta is an important regulator of NF-kappaB with consequences for homeostasis and human disease.

In recent decades, power consumption has become an essential factor in attracting the attention of integrated circuit (IC) designers. Multiple-valued logic (MVL) and approximate computing are some techniques that could be applied to integrated circuits to make power-efficient systems. By utilizing MVL-based circuits instead of binary logic, the information conveyed by digital signals increases, and this reduces the required interconnections and power consumption. On the other hand, approximate computing is a class of arithmetic computing used in systems where the accuracy of the computation can be traded-off for lower energy consumption. In this paper, we propose novel designs for exact and inexact ternary multipliers based on carbon-nanotube field-effect transistors (CNFETs). The unique characteristics of CNFETs make them a desirable alternative to MOSFETs. The simulations are conducted using Synopsys HSPICE. The proposed design is compared against existing ternary multipliers. The results show that the proposed exact multiplier reduces energy consumption by up to 6X. At the same time, the best inexact design improves energy efficiency by up to 35X compared to the latest state-of-the-art methods. Using the imprecise multipliers for image processing provides evidence that these proposed designs are a low-power system with an acceptable error.

Hematopoietic stem cells (HSCs) are responsible for the production of blood cells throughout the human life span. Single HSCs can give rise to at least eight distinct blood cell lineages. Together, hematopoiesis, erythropoiesis and angiogenesis coordinate several biological processes, such as cellular interactions in development and proliferation, guided migration, lineage programming and reprogramming by transcription factors. Any dysregulation of these processes may result in hematological disorders and/or malignancies. Several studies of the molecular mechanisms governing HSC maintenance have demonstrated that protein regulation by the ubiquitin proteasomal pathway is crucial for normal HSC function. Recent studies have shown that the reversal of ubiquitination by deubiquitinating enzymes (DUBs) plays an equally important role in hematopoiesis; however, there is only limited additional information regarding the biological function of DUBs. In this review, we focus on recent discoveries that have led to a better understanding of the physiological roles of DUBs in hematopoiesis, erythropoiesis and angiogenesis. In addition, we discuss the DUBs associated with common hematological disorders and malignancies, which may potentially be therapeutic drug targets.

We demonstrate a concept and fabrication of lithography-free layered metal-\ce{SiO2} thin-film structures which have reduced reflectivity (black appearance), to as low as 0.9~\%, with 4.9~\% broadband reflectance (8.9~\% for soda lime) in the 500 - 1400~nm range. The multi-layered (four layers) thin-film metamaterial is designed so that optical impedance matching produces minimal reflectance and transmittance within the visible and infra-red (IR) spectral region for a range of incident angles. The structure has enhanced absorbance and is easily tuned for reduced minimal transmission and reflection.

The underground injection and geological sequestration of carbon dioxide (CO₂) is a promising approach for reducing the levels of CO₂ in the atmosphere. To mitigate the leakage of CO₂ resulting from natural fracture networks in rock masses, the sequestration process is commonly accompanied by the injection of reactive Portland cement representing a coupled hydro-chemo-mechanical process. In this work, a numerical approach based on the unified pipe network method (UPM) is presented that considers the coupled permeation and diffusion processes with chemical precipitation. Most input parameters are derived from the published literature. The proposed approach is validated through a comparison with analytical solutions, which are applied to simulate the CO₂ sequestration process in a fractured rock mass. The results indicate that the long-term sequestration effect, which is highly influenced by the fracture distribution, can be captured effectively by the model. Consequently, the presented approach can assist engineers in properly designing the arrangement of boreholes and determining the concentration of the grouting material.

Human NAD(P)H:quinone oxidoreductase 1 (NQO1) is a multi-functional protein whose alteration is associated with cancer, Parkinson´s and Alzheimer´s diseases. NQO1 displays a remarkable functional chemistry, capable of binding different functional ligands that modulate its activity, stability and interaction with proteins and nucleic acids. Our understanding on this functional chemistry is limited by the difficulty of obtaining structural and dynamic information on many of these states. Herein, we have used hydrogen/deuterium exchange monitored by mass-spectrometry (HDXMS) to investigate the structural dynamics of NQO1 in three ligation states: without ligands (NQO1apo), with FAD (NQO1holo) and with FAD and the inhibitor dicoumarol (NQO1dic). We show that NQO1apo has a minimally stable folded core holding the protein dimer and with FAD and dicoumarol ligand binding sites populating binding non-competent conformations. Binding of FAD significantly decreases protein dynamics and stabilizes the FAD and dicoumarol binding sites as well as the monomer:monomer interface. Dicoumarol binding further stabilizes all three functional sites, a result not previously anticipated by available crystallographic models. Our work provides an experimental perspective into the communication of stability effects through the NQO1 dimer, valuable to understand at the molecular level the effects of disease-associated variants, post-translation modifications and ligand binding cooperativity in NQO1.

Precipitation processes are technologies commonly used in hydrometallurgical plants to recover metals or to treat wastewaters. Moreover, solid-liquid separation technologies, such as thickening or filtering, are relevant unit operations, included in the precipitation technologies. These methods are strongly dependent on the characteristics of the solid precipitates formed during the specific precipitation reaction. One of these characteristics is the particle size distribution (PSD) of the solid precipitates which are fed into a solid-liquid separation process. Therefore, PSD determination is a typical practice for the characterization of the slurries generated in a precipitation plant. Furthermore, the precipitates generated in these processes have a colloidal or aggregation behavior, depending on the operational conditions. Nevertheless, the conventional methods used to estimate PSD (e.g., laser diffraction and/or ciclosizer) have not been designed to measure particles that tend to aggregate or disaggregate, since they include external forces (e.g., centrifugal, agitation, pumping and sonication). These forces affect the true size of the aggregates formed in a unit operation, thereby losing representativity in terms of aggregates particle size. This study presents an alternative method of measuring the size distribution of particles with aggregation behavior, particularly, by using non-invasive microscopy and image processing and analysis. The samples used have been obtained from an experimental precipitation process by applying sulfidization to treat the cyanide-copper complexes contained in a cyanidation solution. This method has been validated with statistical tools and compared with a conventional analysis based on laser diffraction. Our results show significant differences between the methods analyzed, demonstrating that image processing and analysis by microscopy is an excellent and non-invasive alternative to obtaining size distribution of aggregates in precipitation processes.

This study analyses uncertainties associated with the annual cycle of West African rainfall characteristics in 15 simulations of the Coupled Model Intercomparison Project phase 5 (CMIP5) over the Sahel and Guinean regions. Indices based on daily rainfall such as the frequency and the ntensity of wet days, the consecutive dry days (CDD) and wet days (CWD), the 95th percentile of daily rainfall (R95) and its contribution to the umulative monsoon rainfall (R95PTOT) have been assessed. Over both regions, TRMM, GPCP and CHIRPS observational datasets provide very consistent results on the annual cycle of precipitation but less so on the frequency of wet days. Conversely, higher uncertainties are noted on the intensity of wet days over both study areas, particularly over the Guinean region. Overall, CMIP5 simulations present much higher uncertainties in the representation of the mean precipitation climatology, often provide too early (late) onset dates over the Sahel (the Guinean region) and overestimate rainfall during the early and late monsoon phases. These errors do not compensate at the annual scale nor when considering West Africa as a hole. Results also reveal that over the Guinean region, the difficulty of models to represent the annual structure of the mean precipitation strongly involves biases in the representation of the annual cycle of the frequency of wet days. We found strong uncertainties in the simulation of the CWD and he CDD over both areas. Conversely for R95 and R95PTOT, the ncertainties in CMIP5 models appear somewhat weaker, but the magnitude of R95 is largely underestimated in most models.

The foreign trade sustainable development index system of Shenzhen City, including the three subsystems of environment, economy, and society, was constructed based on the theory of emergy analysis.The sustainable development of foreign trade in Shenzhen City from 2009 to 2016 was evaluated, and a detailed analysis of changes in the emergy of light and heavy industries was performed. The results showed that the scale of economy has been expanding, and the total volume of imports and exports has turned from a rise to a decline in 2013. The status of sustainable development is not optimistic. The transaction volume of energy is reduced, and the quality of people's living environment is declining. The sustainable development of Shenzhen City is not perfect, but it is in a phase of gradual optimization. Moreover, the proportion of heavy industry in import and export trade is significantly higher than that of light industry, which has caused the outflow of energy to a certain extent. Therefore, to improve the level of foreign trade sustainable development, we must improve the efficiency of resource utilization, increase the import of energy products, strengthen the ability to cope with external interference and adjust the foreign trade industrial structure.

Bauxite residue is the voluminous by-product of alumina production after Bayer process. Its high alkalinity causes disposal problems and harmful environmental impacts. However, the residue contains significant amounts of valuable elements such as rare earth elements including scandium. Greek bauxite residue contains a high amount of scandium close to its main resources. Taking into account scandium limited availability coupled with its high demand in modern technology, bauxite residue could be considered as a potential resource for scandium recovery. In this study, the optimization of scandium extraction from bauxite residue with sulfuric acid is investigated using Taguchi methodology. Based on previous studies acid molarity, leaching time, solid/liquid ratio and reaction temperature were selected as control parameters for the selective Sc recovery. Method optimization targeted the highest concentration of scandium combined with the lowest concentration of iron without taking into account applications constraints. The predicted values resulted by Taguchi methodology were affirmed by a confirmation experiment conducted at optimal conditions. Regression analysis provided the respective equations to be applied on several conditions depending on different applications.

Fibromyalgia (FM) and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) are diseases of unknown etiology presenting complex and often overlapping symptomatology. Despite promising advances on the study of miRNomes of these diseases, no validated molecular diagnostic biomarker yet exists. Since FM and ME/CFS patient treatments commonly include polypharmacy it is of concern that biomarker miRNAs are masked by drug interactions. Aiming at discriminating between drug-effects and true disease-associated differential miRNA expression, we evaluated the potential impact of commonly prescribed drugs on disease miRNomes, as reported by the literature. By using the web search tools SM2miR, Pharmaco-miR and repoDB, we found a list of commonly prescribed drugs that impact on FM and ME/CFS miRNomes and therefore could be interfering in the process of biomarker discovery. On another end, disease-associated miRNomes may incline patient´s response to treatment and toxicity. Here, we explored treatments for diseases in general that could be affected by FM and ME/CFS miRNomes finding a long list of them, including treatments for lymphoma, a type of cancer affecting ME/CFS patients at a higher rate than healthy population. We conclude that FM and ME/CFS miRNomes could help refine pharmacogenomic/pharmacoepigenomic analysis to elevate future personalized medicine and precision medicine programs in the clinic.

Bio-economy is a major area of the strategy that must enable the European Union to achieve growth: smart, through the development of knowledge and innovation; and sustainable, based on a greener, more efficient economy in resource management. We believe that the progress of bio-economy cannot be achieved without the harnessing of intellectual capital. Our research aimed to emphasize the benefits of the dynamics of the intellectual capital growth on the evolution of the bio-economy. The aim of this analysis was to study the established link between the Energy Intensity of the Economy (EIE) and a number of factors that can measure the intellectual capital, such as: Market Capitalization of Bitcoin, Patent applications listed by European Patent Office and the Turnover from Innovation as a proportion of the total Turnover. The ultimate goal was represented by the generation of a regression model to see what factor influences mostly the progress of the bio-economy at European and Romanian level.

The accuracy of sales prediction models based on the big data of online word-of-mouth (eWOM) is still not satisfied. We argue that eWOM contains heat and sentiments of different product dimensions, which can improve the accuracy of these models. In this paper, we propose a dynamic topic analysis (DTA) framework in order to extract heat and sentiments of product dimensions from the big data of eWOM. Finally, we propose an autoregressive-heat-sentiment (ARHS) model, which integrates heat and sentiments of dimensions into the baseline predictive model. The empirical study in movie industry confirms that heat and sentiments of dimensions can improve the accuracy of sales prediction model. ARHS model is better for movie box-office revenue prediction than other models.

Polystyrene as a thin film on arbitrary substrates or pellets form defective graphene films or powders that can be dispersed in water and organic solvents. The materials were characterized by visible absorption, Raman and X-ray photoelectron spectroscopy, electron and atomic force microscopy and electrochemistry. Raman spectra of these materials show the presence of the expected 2D, G and D peaks at 2750, 1590 and 1350 cm^-1, respectively. The relative intensity of the G vs. the D peak is taken as a quantitative indicator of the density of defects in the G layer.

Fatty Acid Amide Hydrolase (FAAH) is one of the enzymes responsible of endocannabinoids metabolism. The inhibition of FAAH is a useful and indirect strategy to raise endogenous cannabinoid concentrations, which would be useful for the treatment of various pathological processes in which cannabinoid concentrations are lowered. In the present work, we present an extensive 3D-QSAR/CoMSIA study on a series of 90 irreversible inhibitors of FAAH of pyrimidinyl-piperazine-carboxamide structure. The final model obtained was extensively validated (q2 = 0.734; r2test = 0.966; r2m = 0.723), and based on the information derived from the contour maps we reported a series of 10 new compounds designed as powerful FAAH inhibitors (pIC50 of the best-proposed compounds = 12.196; 12.416).

We report the effects of surface passivation by depositing a hydrogenated amorphous silicon (a-Si:H) layer on the electrical characteristics of low temperature polycrystalline silicon thin film transistors (LTPS TFTs). The a-Si:H layer was optimized by hydrogen dilution and its structural and electrical characteristics were investigated. The a-Si:H layer in the transition region between a-Si:H and µc-Si:H resulted in superior device characteristics. Using an a-Si:H passivation layer, the field-effect mobility of the LTPS TFT was increased by 78.4% compared with a conventional LTPS TFT. Moreover, the leakage current measured at a V_GS of 5 V was suppressed because the defect sites at the poly-Si grain boundaries were well passivated. Our passivation layer, which allows thorough control of the crystallinity and passivation-quality, should be considered a candidate for high performance LTPS TFTs.

This paper presents a method to detect and classify the high impedance fault that occur in the medium voltage distribution network using discrete wavelet transform (DWT) and adaptive neuro-fuzzy inference system (ANFIS). The network is designed using Matlab software and various faults such as high impedance, symmetrical and unsymmetrical fault have been applied to study the effectiveness of the proposed ANFIS classifier method. This is achieved by training the ANFIS classifier using the features (standard deviation values) extracted from the three phase fault current signal by DWT technique for various cases of fault with different values of fault resistance in the system. The success and discrimination rate obtained for identifying and classifying the high impedance fault from the proffered method is 100% whereas the values are 66.7% and 85% respectively for conventional fuzzy based approach. The results indicate that the proposed method is more efficient to identify and discriminate the high impedance fault accurately from other power system faults in the system.

Hippophae is a tree species with ecological, economic and social benefits. In this study, we assembled and annotated chloroplast genomes of sympatric Hippophae gyantsensis and H. rhamnoides subsp. yunnanensis. Their full-length are 155260 and 156415 bp, respectively. Each of them has 131 genes, comprising 85 protein-coding genes, 8 ribosomal RNA genes and 38 transfer RNA genes. After comparing the chloroplast genomes, we found 1302 base difference loci, and 63.29% are located in the intergenic region or intron sequences and 36.71% are located in the coding sequences. The SSC region has the highest mutation rate, followed by the LSC region; the IR regions have the lowest mutation rate. Among the protein-coding genes, three had a ratio of nonsynonymous to synonymous substitutions (Ka/Ks) >1 (but P values were non-significant) and 66 had Ka/Ks <1 (46 were significant). In general, the chloroplast protein-coding genes may be subject to purification selection. Among H. gyantsensis and H. rhamnoides subsp. yunnanensis chloroplast protein-coding genes, there are 20 and 16 optimal codons, respectively. Most of the optimal codons were ending with A or U, which indicates significant AT preference. It is an important reference for studies on the general characteristics and evolution of the Hippophae chloroplast genome.

Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this mini-review, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions and, on other hand, highly simplified structure-based Elastic Network Models of protein flexibility. In contrast to classical Molecular Dynamics the modeling strategies discussed here allow quite accurate modeling of much larger systems and longer time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.

Cone snails (genus Conus) are venomous marine snails that inject prey with a lethal cocktail of conotoxins, small, secreted, cysteine-rich peptides. Given the diversity and often high affinity for their molecular targets, consisting of ion channels, receptors or transporters, many conotoxins have become invaluable pharmacological probes, drug leads and therapeutics. Transcriptome sequencing of Conus venom glands followed by de novo assembly and homology-based toxin identification and annotation is currently the state-of-the-art for discovery of new conotoxins. However, homology-based search techniques, by definition, can only detect novel toxins that are homologous to previously reported conotoxins. To overcome these obstacles for discovery we have created ConusPipe, a machine learning tool that utilizes prominent chemical characters of conotoxins to predict whether a certain transcript in a Conus transcriptome, which has no otherwise detectable homologs in current reference databases, is a putative conotoxin. By using ConusPipe on RNASeq data of 10 species, we report 5,230 new putative conotoxin transcripts that have no homologues in current reference databases. 893 of these were identified by at least 3 out of 4 models used. These data significantly expand current publicly available conotoxin datasets and our approach provides a new computational avenue for the discovery of novel toxin families.

Glutamine is the most abundant and versatile amino acid in the body. In health and disease, the rate of glutamine consumption by immune cells is similar or greater than glucose. For instance, in vitro and in vivo studies have determined that glutamine is an essential nutrient for lymphocyte proliferation and cytokine production, macrophage phagocytic plus secretory activities and neutrophil bacterial killing. Glutamine release to the circulation and availability is mainly controlled by key metabolic organs, such as the gut, liver and skeletal muscles. During catabolic/hypercatabolic situations glutamine can become essential for metabolic function, but its availability may be compromised due to impairment of homeostasis in the inter-tissue metabolism of amino acids. For this reason, glutamine is currently part of clinical nutrition supplementation protocols and/or recommended for immune suppressed individuals. However, in a wide range of catabolic/hypercatabolic situations (e.g. ill/critically ill, post-trauma, sepsis, exhausted athletes) it is currently difficult to determine whether glutamine parenteral or enteral supplementation should be recommended based on the amino acid plasma concentration (glutaminemia). Although the beneficial immune based effects of glutamine supplementation is already established, many questions and evidence for positive in vivo outcomes still remain to be presented. Therefore, this paper provides an integrated review on how glutamine metabolism in key organs is important to cells of the immune system. We also discuss glutamine metabolism, action and important issues related to the effects of glutamine supplementation in catabolic situations.

The effect of filling velocity on positive macrosegregations in large size steel ingots was studied. Macrosegregation and macro-/micro-structure were characterized on the hot-tops and a portion of the upper section of two ingots. The measurements revealed that segregation features in the two ingots varied as a function of the alloying elements, and that the severity of positive macrosegregation in the casting body was reduced when the filling rate was increased. It was also found that at the higher filling rate, grain morphologies in the first solidified zones of the ingot changed from columnar to equiaxe, and secondary dendrite arm spacing (SDAS) became slightly smaller in the intermediate and final solidified zones. The experimental findings were analyzed in the framework of diffusion and convection controlled solidification, as well as liquid metal flow theories. The solute dependence of segregation features was related to the difference in solid-liquid partition coefficient and diffusion capability of each element in the liquid iron. Calculation of Reynolds numbers (Re) during the filling process, for both ingots, showed that higher filling velocity caused more instable movement of the liquid metal in the initial solidification stage, resulting in the modification of grain morphology, as well as accelerated solidification rate.

Premature ovarian insufficiency (POI) is a highly prevalent disorder, characterized by the development of menopause before age of 40. Most cases are idiopathic; however, in some women the cause of this condition (e.g. anticancer treatment, genetic disorders, and enzymatic defects) may be identified. Although hormone replacement therapy, the principal therapeutic approach for POI, helps to alleviate the related symptoms, this does not effectively solve the issue of fertility. Assisted reproductive techniques also lack efficacy in these women. Thus, the effective approach to manage the patients with POI is highly warranted. Several mechanisms, associated with POI, have been identified, including lack of FSH receptor functioning, alterations in the apoptosis control, mutations in Sal-like 4 genes, thymulin or basonuclin-1 deficiency etc. The above-mentioned may be good targets for gene therapy in order to correct defects, leading to POI. The goal of this review is to summarize the current experience on the POI studies, that employed gene therapy, and to discuss the possible future directions in this field.

The multidrug resistance transporter NorM is an important drug resistance pump and plays a critical role in multidrug resistance in bacteria and mammals. In this study we carried out molecular dynamics simulation to study the mechanism of Na+ binding and dynamical structures of two long loops in the substrate-releasing process in substrate binding NorM. Our simulation study identified several key residues (D41, E261 D377) along the Na+ binding pathway and a multi-state ion-binding mechanism is proposed based on the simulation study. In this proposed model, the transport of Na+ is a multi-stage process with D41 being the first station for binding to Na+, followed by Na+ binding to the second station E262 and finally to the cation-binding site of E262 and D377. During the transport of Na+, the transmembrane components TM1, TM7 and TM2 are rearranged to facilitate the ion transport as well conformational changes of NorM to a closed state. Further, substrate-bound simulation revealed that Loop3-4 and Loop9-10 control the substrate-releasing process.

The surface planarity and asperity removal behaviors of atomic scale under the ultrathin water environment was studied for the nanoscale process by molecular dynamics simulation. The monolayer atomic removal was achieved under the noncontact and monoatomic layer contact conditions with different water film thickness, and the newly formed surface is relatively smooth and no deformed layer and plastic defects exist. The nanoscale processing is governed by the interatomic adhering action during which the water film transmits the loading forces to Cu surface and thereby result in the migration and removal of surface atoms. With scratching depth ≥ 0.5 nm, the abrasive particle squeezed out the water film from scratching region and scratched Cu surface directly, leading to the surface quality deterioration mainly governed by the plowing action. This study brings the goals of “0 nm planarity, 0 residual defects and 0 polishing pressure” closer to us in the nanoscale process for the development of ultra-precision manufacture technology.

This research work deals with the modeling and control of hybrid photovoltaic (PV) - Wind micro-grid using Quasi Z-Source inverter. This inverter provides better buck/boost characteristics, able to regulate the phase angle output, less harmonic content, no requirement of the filter and has high power performance characteristics over conventional inverter as major benefits. A SEPIC converter as dc-dc switched power apparatus is employed for maximum power point tracking (MPPT) functions which provides high voltage gain throughout the process. Moreover, a modified power ratio variable step (MPRVS) based perturb & observe (P&O) method has been proposed in the PV MPPT action which forces the operating point close to maximum power point (MPP). Practical responses justify the performance of hybrid PV-Wind micro-grid with Quasi Z-Source inverter structure.

Today, due to recent developments in technology, children devote plenty of time for screen viewing. However, its harmful effects are not yet clear. The purpose of present study was to examine the associations among screen viewing and sleep duration, and body mass index (BMI) in under-five years old children. This cross-sectional study was conducted with 322 under-five healthy children that were selected using multistage stratified cluster sampling method in 2017. The data that were gathered by time-use diary method were analyzed using Kolmogorov-Smirnov test, Spearman correlation tests, multiple linear regression analysis, one-way ANCOVA, two-way ANCOVA. There was a negative correlation between screen time and sleep duration (rs = -0.42, p = 0.00), positive correlation between screen time and BMI (rs = 0.38, p = 0.00) and sleep duration negatively correlated with BMI (rs = -0.22, p = 0.00). screen viewing was a predictive factor for both sleep duration (β = -0.26, p = 0.00) and BMI (β = -0.26, p = 0.00). screen viewing had a significant impact on sleep duration (4, 314) = 5.02, P = 0.001) and BMI (F (4, 314) = 1.16, P=0.298). Results of this study indicated that screen viewing is related to sleep duration and BMI in under-five children. furthermore, screen time has an impact on sleep duration and BMI scores of children. findings of our study suggest that sleep duration negatively is associated with BMI in under-five-year-old children.

Catalytic upgrading of bio-based platform molecules is one of promising approaches for biomass valorization. However, most solid catalysts are thermally and/or chemically unstable and difficult to prepare. In this study, a stable organic phosphonate-hafnium solid catalyst (PPOA-Hf) was synthesized, and acid-base bifunctional sites were found to play a cooperative role in the cascade transfer hydrogenation and cyclization of ethyl levulinate (EL) to γ-valerolactone (GVL). Under relatively mild reaction conditions of 160 ºC for 6 h, EL was completely converted to GVL in a good yield of 85%. The apparent activation energy was calculated to be 53 kJ/mol, which was lower than other solid catalysts for the same reaction. In addition, the PPOA-Hf solid catalyst did not significantly decrease its activity after five recycles, and no evident leaching of Hf was observed, indicating its high stability and potential practical application.

Our previous in vitro reports showed that crude extract prepared with 50% ethanol (ethanol crude extract, ECE) from Mongolian oak cups possessed excellent antioxidant capacities as well as inhibitory activities against α-glucosidase, α-amylase and protein glycation caused by its enrichment in phenolics, including mainly ellagic acid, kaempferol and their derivatives. Nevertheless, few in vivo studies on antidiabetic activities of these phenolics were conducted. The present study investigated hypoglycemic effects with normal and diabetic rats being administrated orally without or with ECE at 200 and 800 mg/kg for 15 days. In normal rats, no significant differences were exhibited after ECE administration in body weight, fasting blood glucose level, levels of chelesterol, triglyceride, LDL and AST in serum, organ indexes, and levels of GSH and MDA in organs. In diabetic rats, the fasting blood glucose level, indexes of heart and liver, and levels of chelesterol and triglyceride in serum and MDA in heart tissue were significantly decreased. Moreover, HDL levels in serum and SOD activities in the four organs of diabetic rats were significantly improved after ECE administration at 800 mg/kg. Thus, in addition to inhibiting α-glucosidase, α-amylase and protein glycation reported previously, oak cups might contain novel dietary phytonutrients in preventing abnormal changes in blood glucose and lipid profile and attenuating oxidant stress in vivo. The results also implied that it is ellagic acid, kaempferol and their derivatives enriched in ECE that might play vital roles in managing type 1 as well as type 2 diabetes.

Irisin, a skeletal muscle-secreted myokine, produced in response to physical exercise, has protective functions in both the central and the peripheral nervous systems, including the regulation of brain-derived neurotrophic factors and modification of telomere length. Such beneficial effects may inhibit or delay the emergence of neurodegenerative diseases, including Alzheimer’s disease (AD). This review is based on the hypothesis that irisin produced by physical exercise helps control AD progression. Herein, we describe the physiology of irisin and its potential role in delaying or preventing AD. Although current and ongoing studies on irisin show promising results, further research is required to clarify its potential as a meaningful therapeutic target for treating human diseases.

Rice grassy stunt virus (RGSV) a member of Tenuivirus family, is very potent and destructive which effects rice crop in many countries, particularly China. Non coding RNAs have important functions in development and epigenetic regulation of gene expression in numerous organsisms. There is three type of small non coding RNAs have been found in eukaryotes, which are small interferring RNAs (siRNAs), microRNAs (miRNAs) and piwi interacting RNAs (piRNAs). Small RNAs (sRNAs) origination is from the infecting virus which is known as virus-derived small interfering RNAs (vsiRNAs), has responsibility for RNA silencing in plants. Virus-induced gene silencing (VIGS) is mainly dependent on RNA silencing (RNAi). Interestingly, RNA silencing happens in plants during viral infections. RNAi technique showed significant results in Nephotettix cincticeps. RNAi technique demonstrated the gene silencing of planthopper Nilaparvata lugens. The proteins P5, pcf4, Dnj, psn5, and pn6 act as potential movement proteins and serve as silencing suppressors for RGSV. VsiRNAs originate from dsRNA molecules which require Dicer-like (DCL) proteins, RNA dependent RNA polymerase (RdRP) proteins, and Argonaute (AGO) proteins. RdRP uses ssRNA for perfect RNA amplification process and can also be used for DCL dependent secondary vsiRNA formation. VSRs interfere with the movement of signals during silencing mechanism. Moreover, intercellular movement of viruses is facilitated by virus-encoded movement protein. RNAi is found in many eukaryotes which are related to transcriptional or post-transcriptional regulation by gene suppression. Transcription is bidirectional in ssDNA viruses which are originated from dsRNA molecules. In this review, we highlighted the biology of Rice grassy stunt virus and its insect vector and its silencing suppressors. This work will be helpful for plant virologists to understand the whole biogenesis mechanism for rice viruses especially RGSV.

The theoretical limit of link prediction is a fundamental problem in this field. Taking the network structure as object to research this problem is the mainstream method. This paper proposes a new viewpoint that link prediction methods can be divided into single or combination methods, based on the way they derive the similarity matrix, and investigates whether there a theoretical limit exists for combination methods. We propose and prove necessary and sufficient conditions for the combination method to reach the theoretical limit. The limit theorem reveals the essence of combination method that is to estimate probability density functions of existing links and nonexistent links. Based on limit theorem, a new combination method, theoretical limit fusion (TLF) method, is proposed. Simulations and experiments on real networks demonstrated that TLF method can achieve higher prediction accuracy.

The pennate diatom Phaeodactylum tricornutum is a model organism able to synthesize industrially-relevant molecules. Commercial-scale cultivation currently requires large monocultures, prone to bio-contamination. However, little is known about the identity of the invading organisms. To reduce the complexity of natural systems, we systematically investigated the microbiome of non-axenic P. tricornutum cultures from a culture collection in reproducible experiments. The results revealed a dynamic bacterial community that developed differently in “complete” and “minimal” media conditions. In complete media, we observed an accelerated “culture crash”, indicating a more stable culture in minimal media. The identification of only four bacterial families as major players within the microbiome suggests specific roles depending on environmental conditions. From our results we propose a network of putative interactions between P. tricornutum and these main bacterial factions. We demonstrate that, even with rather sparse data, a mathematical model can be reconstructed that qualitatively reproduces the observed population dynamics, thus indicating that our hypotheses regarding the molecular interactions are in agreement with experimental data. Whereas the model in its current state is only qualitative, we argue that it serves as a starting point to develop quantitative and predictive mathematical models, which may guide experimental efforts to synthetically construct and monitor stable communities required for robust upscaling strategies.

Copper mine tailings are the residual products after the purification of precious copper from copper ores, and their storage can create numerous environmental problems. Many researchers have used copper mine tailings for preparation of geopolymer. This paper studies the enhancement of the cementitious activity of copper mine tailings in geopolymer system. First, copper mine tailings are activated through a mechanical grinding activation. Afterward, the mechanically activated copper mine tailings are further processed through thermal activation and alkaline roasting activating. The cementitious activity index of copper mine tailings is characterized through the degree of concentration of alkali leaching silicon and aluminum. It was observed that the Si and Al alkali leaching concentration of mechanical activated tailings was increased by 26.03% and 93.33%, respectively. The concentration of Si and Al was increased by 54.19% and 119.92%, respectively. For alkaline roasting activating, roasting time, temperature and (C/N ratio) were evaluated through the orthogonal test, and the best condition was activation for 120 min at 600℃ with C/N ratio is 5:1. In this study, the SEM, XRD and IR analysis show that mechanically activation, thermal activation and alkaline roasting activating can improve the cementitious activity index of copper mine tailings.

Europium (Eu)-doped fluorapatite (FA) nanorods has a similar biocompatibility with hydroxyapatite (HA) in terms, attracted much attention as cell imaging biomaterials due to their luminescent property. Here, we will discuss the new feature of europium doped fluorapatite (Eu-FA) nanorods as anticancer drug carrier. Eu-FA nanorods was prepared using a hydrothermal method. The morphology, crystal structure, fluorescence and composition are investigated. The specific crystal structure, enabling an effective loading of drug molecules. Doxorubicin (DOX), used as an anticancer model drug, was shown to be effectively loaded onto the surface of the nanorods. The DOX release was fairly pH-dependent, occurring more rapidly at pH 5.5 than pH 7.4 was observed. The intracellular penetration of the DOX-loaded Eu-FA nanorods (Eu-FA/DOX) can be imaged in situ due to the self-fluorescence property. Treatment of melanoma A375 cells with Eu-FA/DOX elicited a more effective apoptosis rate than direct DOX treatment. Overall, Eu-FA show great promise for tracking and treating tumor, may potentially useful as a multifunctional carrier system to effectively load and sustainably deliver drugs.

The performance of modified electrode of nanocomposite film consisting of polypyrrole-chitosan-titanium dioxide (Ppy-CS-TiO2) has been explored as non-enzymatic glucose biosensors. The synergy effect of TiO2 nanoparticles and conducting polymer on the current response of electrode resulted in higher sensitivity for nanocomposite modified electrode. The incorporation of TiO2 nanoparticles in the nanocomposite films were confirmed by XPS spectra. The FESEM and HR-TEM provided more evidences for the presence of TiO2 in Ppy-CS structure. Glucose biosensing properties were determined by amperommetry and cyclic voltammetry (CV) methods. The interfacial properties of nanocomposite electrodes were studied by electrochemical impedance spectroscopy (EIS). The developed biosensors showed a good sensitivity over the liner range of 1-14 mM with a detection limit of 614 μM for glucose. It also exhibited good selectivity and long term stability with no interference effect. The Ppy-CS-TiO2 nanocomposites film presented high electron transfer kinetics.

The present study aimed to analyze novel mechanisms underlying Nrf2-mediated anti-apoptosis in periodontal ligament stem cells (PDLSCs) in the periodontitis oxidative microenvironment. We created an oxidative stress model with H2O2-treated PDLSCs. Herein, we used real-time PCR, western blotting, TUNEL staining, fluorogenic assay and transfer genetics to confirm the degree of oxidative stress and apoptosis as well as the Nrf2 function. Surprisingly, we demonstrated that with up-regulated ROS and MDA levels, the effect of oxidative stress was obvious under H2O2 treatment. Anti-oxidative molecules were changed after the H2O2 exposure, whereby the anti-oxidative signaling of Nrf2 was activated with the increase of its downstream effectors, HO-1, NQO1 and γ-GCS. Additionally, the apoptosis levels gradually increased with oxidative stress and changes in the caspase-9, caspase-3, Bax and c-Fos levels, but not with caspase-8 and down-regulated Bcl-2. The enhanced antioxidant effect could not resist the occurrence of apoptosis. Furthermore, Nrf2 overexpression effectively improved the anti-oxidative levels and increased cell proliferation. At the same time, overexpression effectively restrained TUNEL staining and decreased the molecular levels of caspase-9, caspase-3, et al, but not that of caspase-8. By contrast, silencing the expression Nrf2 levels had the opposite effect. Collectively, Nrf2 alleviates PDLSCs via its effects on anti-oxidative and anti-intrinsic apoptosis by the activation of anti-oxidative enzymes.

In 2013, the CMA at the İstanbul Stock Exchange increased the weight assigned to the Board of Directors component of its Corporate Governance Index to 35% from the previous 25%. Interpreting this as a recognition of the increasing vital role of the board, this study seeks to enhance the work of Abdıoğlu and Kılıç (2015) by putting more focus on the role of women in the boards and the effect of the busy chairman as well as the presence of outside directors on the effectivity of the Board. (The general business structure is associated with family owned groups and holdings which results into a network of intertwined board membership and cases of multiple directorship where, one board chairman can hold the same position or any directorship in as many as ten firmshence the busy chairman). I employ a different method of evaluating performance (EVA) together with the accounting measures of ROE and ROA (as opposed to the overused Tobin’s Q), which I regress against the Board Index to be created. The focus is on firms on the BIST 100 index (excluding financial) between 2009 and 2013. The results reveal that the BINDEX has a significant and positive relationship with firm performance as measured by EVA. A second model reveals no relationship between the BINDEX and firm ROA, similar to the results of Kiliç and Abdioğlu (2015). ROA however has a positive relationship with the proportion of female directors in the board, as earlier reported by LückerathRovers (2013). Another model using ROE as the proxy for performance registers a significant negative relationship with the index. The contradiction obtained in the results from these three models underscore the importance choosing the right methods when estimating the performance of a firm.

The article describes the use of deep neural networks to detect small floating objects located in the own vessel’s path. The research aimed to evaluate the performance of deep neural networks by classifying sea surface images and assigning the level of threat resulting from the detection of objects floating on the water, such as fishing nets, plastic debris or buoys. Such a solution could function as a decision support system capable of detecting and informing the watch officer or helmsman about possible threats and reducing the risk of overlooking them at a critical moment. Several neural network structures were compared to find the most efficient solution, taking into account the speed and efficiency of network training and its performance during testing. Additional time measurements have been made to test real-time capabilities of the system. The research results confirm that it is possible to create a practical lightweight detection system with Convolutional Neural Networks that calculates safety level in real time.

The rapid advancements in the Fourth Industrial Revolution and artificial intelligence (AI) necessitate a transformative approach to leadership in higher education. This paper investigates the current state of leadership in Iraqi universities and proposes strategies to enhance leadership capabilities aligned with technological advancements. Through a comprehensive review of existing literature, qualitative analysis, and quantitative data collection, the study identifies key challenges and opportunities for developing effective university leadership. The findings underscore the importance of strategic human resource management, high-performance work systems, and technological integration in fostering leadership excellence. Practical recommendations for policymakers and educational leaders in Iraq are provided, highlighting the need for strategic investments in leadership development to meet the demands of the evolving educational landscape.

The Integrated Territorial Program (ITP) for the development of camelid livestock faces key challenges, such as low productivity and lack of infrastructure in the region. This program is aligned with the Territorial Agenda for Agricultural Innovation (FIA) and the Sustainable Development Goals of the 2030 Agenda, prioritizing camelid livestock farming in Chile's highlands as a strategic productive resource. The methodology used is based on co-creation with stakeholders in the territory and comparative analysis to improve competitiveness. This document highlights the relevance of the ITP in a volatile and constantly changing global environment, and its contribution to the innovation and competitiveness of camelid livestock in the Arica and Parinacota region.

In this work, we present a real-time heart rate estimation method from a video using face detection, color-based signal extraction, and signal processing tech- niques. The proposed approach computes the heart rate by analyzing the color fluctuations in the facial region of interest (ROI). This report outlines the math- ematical formulation and results of the implementation.

A novel approach to enhance Additive Friction Stir Deposition (AFSD) is presented through the integration of Multimodal Retrieval Augmented Generation (RAG). AFSD which is a solid-state metal additive manufacturing process characterized by its complexity, necessitating advanced analytical tools. A multimodal RAG system is implemented, integrating textual, and visual data. The methodology involves text extraction using LangChain's PyPDFLoader, followed by chunking and embedding generation via Google's Generative AI model. ChromaDB is utilized for vector storage and efficient information retrieval. The system, powered by Google's Gemini large language model, demonstrates proficiency in generating detailed explanations of friction-based deposition processes, identifying manufacturing techniques from visual data, and evaluating material microstructures. Information from multiple sources is synthesized to produce context-aware responses. Process control, quality assurance, and decision-making in AFSD are significantly enhanced by this approach. The system's capabilities are illustrated through the analysis of various friction-based deposition techniques and microstructure evaluation.

We present a novel derivation of fundamental physical laws by solving a maximization problem on the Shannon entropy of all possible measurements relative to a system's initial state, subject to specific linear constraints. By introducing appropriate linear constraints, we create probability measures that adhere to particular underlying mathematical structures, enabling us to recover various physical theories within a unified framework. Specifically, imposing a U(1) group constraint leads to the emergence of quantum mechanics by incorporating complex probability amplitudes and interference effects. Extending this approach, we apply a Spinc(3,1) group constraint to derive a relativistic quantum theory that naturally includes Lorentz symmetry. Remarkably, in 3+1 dimensions, this method uniquely results in the metric tensor of general relativity through a double-copy mechanism applied to the Dirac current. Furthermore, it inherently incorporates the SU(3)xSU(2)xU(1) gauge symmetries of the Standard Model, providing a unified description of fundamental interactions. These findings highlight the power of entropy maximization under linear constraints to reveal the deep connections between probability theory and the mathematical structures underlying fundamental physics, offering new insights into the emergence of spacetime dimensions and symmetry structures in our universe.

Graph neural networks and graph convolutional networks are effective at representing complex relationships. We attempt to apply them to sports analytics by reviewing existing applications in sports. These methodologies leverage the inherent graph structure of sports data, capturing interactions among players, teams, and game events. By systematically examining various studies, we highlight how GNNs and GCNs can enhance performance prediction, player evaluation, and tactical analysis in sports. Our review emphasizes the unique advantages these models offer over traditional analytical approaches, particularly in their ability to account for the dynamic and interconnected nature of sports activities. We conclude by identifying potential areas for future research and application, suggesting that the integration of advanced graph-based techniques could significantly advance the field of sports analytics.

Over the last few years there has been much effort put into the development and validation of stochastic models of the trajectories of swarming insects. These models typically assume that the positions and velocities of swarming insects can be represented by continuous jointly Markovian processes. These models are first-order autoregressive processes. In more sophisticated models, second-order autoregressive processes the positions, velocities and accelerations of swarming insects are collectively Markovian. Although it is mathematically conceivable that this hierarchy of stochastic models could be extended to higher orders, here I show that such a procedure would not be well-based biologically because some terms in these models represent processes that have the potential destabilize insect flight dynamics. This prediction is supported by an analysis of pre-existing data for laboratory swarms of the non-biting midge Chironomus riparius. I suggest that the Reynolds number is a finely tuned property of swarming, as swarms may disintegrate at both sufficiently low and sufficiently high Reynolds numbers.

Biomimicry, though still emerging within the social sciences, offers promising insights for improving food security by drawing analogies from natural ecosystems and re-exploring traditional ecological knowledge. This paper argues that adopting nature-inspired strategies in urban agriculture can significantly enhance resilience against geoeconomic pressures, logistical disruptions, and disasters. As geopolitical tensions intensify, exacerbated by climate change, pandemics, and urbanization, the strategic use of food power is likely to become increasingly relevant, particularly impacting urban areas due to their high dependence on external food supplies. Urban agroecology, which inherently embodies biomimetic principles, is presented as a viable pillar for building more resilient and self-sustaining food systems. The paper explores how an urban agriculture approach grounded in biomimicry can serve as a critical mechanism for food security, especially in urbanized regions vulnerable to potential food power dynamics. Additionally, it examines current methods by which states and cities prepare for food supply challenges and highlights the untapped potential of urban food production as a strategic response to these vulnerabilities.

In this paper, we focus on the influence of Riemann space-time curvature on the laws of electromagnetism, such as Gauss’s law, Maxwell-Amp´ere’s law, and Faraday’s law. Furthermore, we also introduce the work done on the unification of the gravitation and electromagnetic fields.

Migrate is a verb representing a process where the intention of providing social services to migrants is to reduce their instability and discomfort. Consequently, social service providers are inclined to view migrants as pitiful, often also those to be feared, with migrants learning to form negative views of themselves, decreasing their mental health. Considering migration as a verb neglects the noun initiating the migration when the migrant is heading to a person, place, thing, event, or idea. In viewing migration as noun-dependent, the migrant is identifiable as self-directed in seeking aid rather than pitiful or inciting fear. This study aims to examine the types of nouns migrants conceptualize for guiding their migration based on a Google Scholar search of “[noun-type] to which [whom] migrants head in their migration” for each noun type regarding the four most highly cited reports published since 2020. The purpose is to determine the social services applicable to migrants in their self-direction regarding theoretical foundations that contrast problem-focused with emotion-focused coping. Viewing such migration nouns as essential migration signifiers encourages migrants’ favorable identification. In recognizing the intended self-direction of the migrant, their mental health is improved and is supportable through relevant and appropriately available social services.

Probability is initially defined on a Boolean algebra or a lattice of projectors. We propose here to start from a Heyting algebra.

In this paper, we explore the theoretical foundation of Graph Neural Network (GNN) model and apply it to various traditional supply chain logistics problem. In particular, we study the Route Optimization Problem, Demand Forecasting Problem, Risk Assessment and Anomaly Detection, Supplier Section and Procurement Optimization, Inventory Optimization Problem, and Green Supply Chain Problem. The study helps us the expand the use the GNN and gives daily supply chain management a boost.

In a time of ecological and social crises, designing new institutions is crucial for meeting future challenges. Institutions emerge from the imaginations of individuals, moving into social movements and crystallizing in legal structures. As present movements seek to develop tomorrow’s governances, they turn to decentralized structures: distributed networks with little hierarchy, characterized by a diversity of actors and dynamics. While movements and technologies may seek to utilize decentralized ideas, they lack design principles: only recently has it been possible to decentralize at the national stage. Designs may come from biology and ecological networks; fungi, plants, and slime molds in soil to the neurons, glia, and blood vessels within our own bodies. This article blends these biological analogies with present technologies like blockchain and Web3 to posit future decentralized institutions, movements and legalities that give greater consideration to the more-than-human world.

BackgroundThe clean energy transition required for decarbonisation of our societies make policymakers targets for broad business and non-business advocacy to ensure one’s often conflicting interests are protected or taken into consideration in public policies. The concept of policy entrepreneurs foregrounds the role of agency in understanding such acts of advocacy. This paper compares strategies used by policy entrepreneurs from different social spheres, advocating policy change or status quo, in four longitudinal cases related to European Union energy and climate policy 2011–2023. ResultsPolicy entrepreneurship was mainly of a cultural-institutional nature, aiming at altering or diffusing people’s perceptions, beliefs, norms and cognitive frameworks, worldviews, or institutional logics. But the actions of the European Commission did also include structural entrepreneurship, aiming at overcoming structural barriers to enhance governance influence by altering the distribution of formal authority and factual and scientific information. Motifs of policy entrepreneurs in the four cases differ, but strategies do not differ significantly between the public, private and civic spheres of society. Results indicate that civil society policy entrepreneurs focus on building broader coalitions than public and private sector entrepreneurs. There is no indication that policy entrepreneurs from a certain sector would be more successful than others in setting the agenda, changing perceptions of policy actors, or influencing actual policy change. However, policy entrepreneurs advocating policy change are more active and use more elaborated strategies than policy entrepreneurs advocating status quo. ConclusionsIt is concluded that policy entrepreneurs advocating policy change are more active and use more elaborated strategies than policy entrepreneurs advocating status quo. Thus, they are more successful in influencing policy outcomes. The European Commission was the only policy entrepreneurs to use structural entrepreneurship. the Commission acts to expand its reach into areas where the European Union does not hold much legal competence according to the constitution of the European Union. This comes with democratic deficits related to accountability and legitimacy and should be combated to reinstate and reinforce the position and powers of both the national and European legislators in taking the important decisions that impact the lives of European citizens.

Background: The COVID infection became the source of serious disagreements between scientists, doctors, politicians and private citizens, directly after it’s detection in the population in January 2020. The pandemic had some very unusual properties as well as the people’s reaction to it. It was feared, that the virus might be used, intentionally or accidentally, to interfere with the usual, democratic way of the upcoming election. Objective: Re-search the original COVID statistic and metadata to obtain better understanding of the pandemic including the biological (viral) as well as the social (human) aspects of it. Provide a professional, independent, non-biased view of the pandemic, that is not polluted by political and media suggestions. Methods: Publicly available data – covering the first 5 months of the COVID pandemic, 2020 Jan-May - were collected and analyzed with the usual, common statistical methods, like student’s t-test and regression analyses.The political attitude of the states were characterized by a ratio (D/R) of the number of left, democrat (D) and right, republican (R) oriented citizens in the respective states, as determined by opinion research. Results: De novo statistical analyzes of publicly available data (covering the initial five months of the pandemic) suggests that the negative medical consequences of COVID pandemic were significantly more expressed in “democrat-dominated” (D) states than in “republican-dominated”, (R) states. The proportion of COVID test positive persons was higher in D-states (6.831 +/- 1605, n=14 and 1,165 +/- 323, n=13 respectively, p<0.001). The difference in mortality was even more striking, 8-times more person/million population died in COVID related conditions in solid D states than in solid R states (438 +/- 128, and 59 +/- 13; p<0.001, respectively). The COVID associated mortality increased two fold from right to left on the political scale of the states (2.7% +/- 0.3 vs. 5.3% +/- 0.5, p<0.001). The correlation between COVID deaths (mortality) and the age/pre-existing medical condition(s) of the diseased is very strong (R2= 0.98) and the overwhelming majority of COVID “victims” are persons who were close to death even independently of the epidemic. Conclusions: Alarming signals regarding the dangerousness of COVID infection seems to have originated in a few states with predominantly left oriented citizens (high D/R ratio). The COVID mortality statistic seems to be seen and analyzed with little or no respect for the context of mortality caused by other well-known diseases or even by the natural, age related deaths. We conclude that it is absolutely necessary to pay serious attention to the correct analyses and interpretation of the epidemic data to avoid being misled or manipulated by false circumstances.

This study investigates the pricing of exotic options, specifically Barrier and Asian options, through the application of Monte Carlo simulation. The research commences by establishing the theoretical foundations and closed-form solutions within the Black-Scholes framework. Subsequently, three distinct random walk models are introduced to generate underlying asset paths for simulation purposes. The antithetic variate technique is demonstrated to significantly reduce standard error and accelerate convergence in the pricing of both options, thereby enhancing the precision of Monte Carlo estimates. Notably, the selection of underlying random walk models is found to have a minimal impact on accuracy, suggesting avenues for further research in advanced variance reduction techniques. This study provides valuable insights into the pricing of exotic options, offering implications for finance professionals and researchers, and driving innovation in option pricing methodologies for dynamic financial markets. The research underscores the efficacy of Monte Carlo simulation and variance reduction techniques in pricing complex options, contributing to the advancement of financial modelling and derivatives pricing.

Phase errors in magnetic resonance (MR) techniques, including Nuclear Magnetic Resonance (NMR) spectroscopy and Magnetic Resonance Imaging (MRI), pose significant challenges to data accuracy and interpretation. As MR technologies advance, the demand for more sophisticated phase correction methods continues to grow, enhancing diagnostic precision and analytical outcomes. This review explores the evolution of phase correction models, beginning with simple global phase shifts, progressing through traditional linear statistical models, and culminating in modern machine learning techniques—specifically, neural networks. We also examine a range of optimization functions and optimizers, including both MR data-specific and common statistical approaches, applied in phase error correction. Despite notable progress, challenges remain in developing fully automatic phase error correction methods, particularly given the absence of ground truth in real-world MR data. This review highlights key methods, discusses their limitations, and proposes future pathways, including ensemble learning, that could guide further innovation in phase error correction.

Companies operating in the PayTech and online e-commerce sectors play a crucial role in critical infrastructure, functioning within the dynamic digital landscape. This study focuses on the recovery process after cyber-attacks and examines the contrasting perspectives of internal and external professionals. The research reveals notable differences in the perceptions of recovery strategies between internal stakeholders such as investor relations, reputation management, and Chief Information Security Officers, representing companies belonging to critical infrastructure and external auditors, who provide just and emergency support and perform specific tasks. Importantly, the study underscores the current attitudes towards future information security strategies and their influence on the financial recovery and reputation of reliable companies following cyber incidents. This research contributes to the existing knowledge by shedding light on the perspectives of both a company's internal and external specialists involved in the recovery process and cyber resilience strategies in critical infrastructure sectors.

BackgroundContextualising the narrative on energy efficiency as the first fuel in the clean energy transition, the energy efficiency first principle (EE1) was introduced in EU energy and climate policy with the Energy Union communication in 2015 and made nonbinding with the EU Governance Regulation in 2018. In 2023, the EU legislators made EE1 legally binding to apply in policy, planning and investment decisions exceeding 100 million euros each and 175 million euros in the transport sector across all sectors that affect the energy system. Understanding the process through which new legislation is developed and adopted is important for understanding the policy itself, why it was designed in the way it was. Understanding the contextualisation of EE1 is particularly important since it introduced a paradigm shift in EU energy and climate policy. Better knowledge of the process of transformative policy change is important for policy and governance towards a clean energy transition for climate neutrality.ResultsApplying the multiple streams framework as a theoretical lens for analysing policy processes, this paper determines the policy process and the agency of policy entrepreneurs to make EE1 legally binding, from problem formulation to final adoption. Based on qualitative text analysis of policy documents, position papers and reports from EU negotiations, combined with interviews of key actors, the study shows how non-profit and non-governmental organisations such as the Regulatory Assistance Project (RAP), the European Climate Foundation (ECF) and the Energy Efficiency Financial Institutions Group (EEFIG), as well as the European Commission and the rotating Council Presidency, were critical policy entrepreneurs for coupling the problem, policy and politics streams. RAP together with ECF and EEFIG considered the unequal treatment of energy supply and energy demand in energy policy to hamper efficient use of the energy system and suggested the EE1 principle to overcome this problem. Using a broad set of strategies related to cultural-institutional entrepreneurship, such as attention- and support seeking strategies, linking strategies, relational management strategies, and arena strategies, they persuaded the European Commission to propose legislation on EE1. But the initial framing was too technical. for decision-makers to understand. The coupling of the problem–policy package to politics was performed once a policy window was opened by external and internal events such as the Paris Agreement on climate change, the entering office of the Ursula von der Leyen European Commission in late 2019, and the energy crisis in Europe following Russia’s second war on Ukraine. Climate change and security of supply were problems that decision-makers could understand. ConclusionsIt is concluded that coalition-building is important for policy entrepreneurs to gain broad acceptance for their policy proposals. In addition, timing is of great importance for policy entrepreneurs being able to couple a package of problems and policy solutions to the political stream. Political decision-makers must be receptive to the problem and its policy solution. This happens when a policy window of opportunity is opened. In this case, the policy entrepreneurs proposed a solution to what they perceived of as a problem almost seven years before the politics stream was mature and receptive. This led policy entrepreneurs to use ‘salami tactics’ to sequentially introduce policy change whit bits and pieces of the proposed policy instrument being implemented over a long period. It also highlights the need for endurance of policy entrepreneurs.But the study also raises ethical issues that policy entrepreneurship may not only be positive to democratic governance for the clean and just energy transition. The agency of policy entrepreneurs is often technocratic and non-transparent, and they take the role of political decision-makers but with no formal decision-making power, reducing possibilities to claim accountability, legitimacy and justice.

This study examines the current functioning of Health Care Bioethics Committees (HBCs) in Chile, with the objective of providing recommendations for improving public health care management. Through a comprehensive literature review and a case analysis of the ‘Hospital Clínico de la Universidad de Chile’, the structure, functions and challenges of the CEA are explored. The research reveals the importance of the multidisciplinary composition of the committees, the need for continuing education in bioethics, and the relevance of the consultative role in ethical decision making. The results suggest that the effectiveness of CABs does not necessarily depend on the number of members or the length of their terms of office, but on the quality of their training and experience. It is concluded that for adequate health care management, it is essential to strengthen the role of the CEA in the ethical education of health care personnel and in the development of institutional regulations, as well as to improve their visibility and accessibility within the Chilean health care system.

The current developments in the theory of quantum static triplet correlations and their associated structures (real r-space and Fourier k-space) in monatomic fluids are reviewed. The main framework utilized is Feynman’s path integral formalism (PI) and the issues addressed cover quantum diffraction effects and zero-spin bosonic exchange. The structures are associated with the external weak fields that reveal their nature, and due attention is paid to the underlying pair level structures. Without the pair level one cannot fully grasp the triplet extensions in the hierarchical ladder of structures, as both the pair and the triplet structures are essential ingredients in the triplet response functions. Three general classes of PI structures do arise: centroid, total continuous linear response, and instantaneous. Use of functional differentiation techniques is widely made and, as a bonus, this leads to identify an exact extension of the “classical isomorphism” when the centroid structures are considered. In this connection, the direct correlation functions, as borrowed from classical statistical mechanics, play a key role (either exact or approximate) in the corresponding quantum applications. Additionally, as an auxiliary framework, the traditional closure schemes for triplets are also discussed, owing to their potential usefulness for rationalizing PI triplet results. To illustrate some basic concepts, new numerical calculations (path integral Monte Carlo PIMC and closures) are reported. They are focused on the purely diffraction regime and deal with supercritical helium-3 and the quantum hard-sphere fluid.

This study examines the evolution of the tourism industry in Chile during the period 2013-2019, focusing on its contribution to the country's Gross Domestic Product (GDP). Using data from the National Tourism Service (SERNATUR) and the Undersecretariat of Tourism, it analyzes the approximation of tourism GDP and its share in the Chilean economy. The results indicate a sustained growth of the tourism sector, with a contribution to GDP that reached 3.3% in 2019. The main Tourism Characteristic Activities (TCAs) contributing to this growth are identified, highlighting administrative and support activities, food services and accommodation. The study reveals growth patterns, fluctuations in the contribution of different TCAs, and the impact of external factors on the sector's performance. This research provides valuable insights for the formulation of tourism development policies and strategies in Chile.

Curcumin, extracted from the Curcuma longa rhizome, has gained substantial attention for its anti-inflammatory, antioxidant, and neuroprotective properties. Despite these potential benefits, its low bioavailability limits its usage and potential in clinical settings. To overcome these limitations, novel formulations have been developed using liposomal, nanoparticular and micellization technologies to improve bioavailability. The current randomized, double-blind, crossover, pharmacokinetic study compared AQUATURM^®, a novel, patented water-soluble formulation, to another commercially available and widely used curcumin supplement in 12 human subjects over a 12-hour period separated by a 7-day washout period. Plasma samples were analyzed by tandem mass spectrometry detection (UPLC-MS/MS). The area under the plasma concentration-time curve indicated that the bioavailability of AQUATURM^® was over 7-fold greater than that of the other curcumin supplement, reaching concentrations up to 20 ng/mL for up to 12-hours. This study demonstrates AQUATURM^®’s superior bioavailability to that of another, conventional, widely used curcumin supplement.

In this paper, we will describe the general theory of relativity. The special theory of relativity is based on the ideal inertial frames. These ideal inertial frames are assumed to exist in every event in space-time. In contrast, in the general theory of relativity, we do not have to make that assumption. Additionally, the space-time is considered to be part of the solution to the motion. Moreover, interpretation of geometrical quantities is introduced.

This study presents an application of fractal mathematics to financial markets through the utilization of the Multifractal Model of Asset Returns (MMAR). The model is employed to analyse a 30-year dataset encompassing three distinct financial markets: the USD/NOK currency pair, the OMXS30 stock index, and the 12-month LIBOR rate. The MMAR model successfully captures essential stylized facts about financial markets, including high kurtosis, non-independent price movements, and clustered volatile days. Simulations generated by the model demonstrate realistic behaviour and multifractal characteristics. However, the model lacks a statistical method for assessing its accuracy and may underestimate kurtosis in high-kurtosis markets. Notably, the model is capable of producing simulations across a wide range of kurtosis values and can be instrumental in stress-testing portfolios. Despite its potential, the model is subject to limitations, such as the need for human judgment, ambiguous predictions, and interpretability issues. Furthermore, the model may become unreliable following a high-kurtosis event.

With the ever-growing geopolitical tensions across borders arising, ultimately from the eternal energy needs, it is the peak time for humanity to put its reliance on a more quasi-perpetuity source of energy, such as the Sun. Even though current photovoltaics are the frontier of solar power harvesting, their efficiencies are reaching a state of stasis sooner or later. The efficiencies of single-junction solar cells are capped by the Shockley-Quiesser limit of 33.7%. Researchers are racing toward a way to beat this limit while keeping the Levelized Cost of Energy (LCE) to its minimum. Amongst all contenders, rectenna (or rectifying antenna), which was invented only a decade after the first practical PV cell by the Bells lab [1], is the most promising technology to take the forefront in quenching the energy needs, not only because of the absence of any such theoretical limit but also a lower cost of production. This report will review three state-of-the-art architectures for optical rectification developed by the leading groups worldwide. The review will compile a concise discussion on Metal-Double-Insulator-Metal diodes, CNT-Insulator-Metal diodes, and Point-contact-Metal-Insulator-Metal diodes, with an elaborative focus on their fabrication methods and results obtained.

The article investigates the impact of the Environmental, Social, and Governance (ESG) criteria on the current tax systems worldwide. The ESG principles, although yet to be codified in hard law in most countries, are gaining increasing prominence in shaping business practices and policies. The article explores how these principles might influence the interpretation and application of existing tax rules, even without explicit legal mandates. It delves into four key areas where ESG considerations could play a significant role: the calculation of business income, transfer pricing regulations, the application of anti-avoidance rules, and the interpretation of the "business purpose" test. It argues that ESG principles, by redefining the purpose of a business beyond mere profit maximisation, could lead to a broader understanding of deductible costs, influence transfer pricing decisions, and impact the application of anti-avoidance measures. It concludes by emphasising the potential of ESG principles to shape the future of taxation, promoting a more sustainable and equitable approach to economic growth.

The enormous diversity of hair fibers found in human population is striking, while the basic structure of human fibers is often the same! But why do some fibers curl? Curling is related to the machinery and processes that produce different keratin filament orientation in relation to the axis of hair growth, influenced by developmental and molecular control. It is established that a curly hair shaft is produced by a curved hair follicle that have an angulated dermal implantation, with a bulb bent in the shape of golf club, while the outer root sheath is dissymmetrical; have an outer side that is convex bulging and thin and a concave side in which the cells express alpha-smooth muscle protein reflecting internal mechanical force. Yet, the exact cause of hair curling is not known. All the previous studies were short of impacting curly hair treatment. My hypothesis is that the curling mechanical force is generated by a hypersensitive contracted Arrector Pili muscle (APM) of the hair follicle. In curly hair, each APM fiber is shortened; pulling its attachment spot upward towards the epidermis and obliquely or laterally; curling the outer root sheath to produce the curved follicle described above. This contraction has the influence at a time when the young hair root is being formed and keratin microfibrils are being oriented and packed. APM is a multi-unit muscle wherein each fiber contracts independently to create the enormous diversity of curly hair types. APM contraction can be modulated by oral administration of selective smooth muscle relaxing treatment that relax the curved follicle from within. Further studies are needed to confirm the role of APM in shaping curly hair follicle including AI studies, i.e., computer-aided target identification to demonstrate APM active site that can interact with herbal small molecules.

This paper introduces the novel concept of Time-Traveling Turing Machines (TTTMs) — Turing Machines with the ability to read symbols that have been explicitly sent from their future computational state. We delve into their properties and behavior, particularly emphasizing the importance of maintaining a self-consistent computational timeline. We present theorems demonstrating the universality of these machines and the challenges in achieving faster computations than traditional Turing Machines.

Fine-needle aspiration cytology (FNAC) is a pivotal diagnostic tool in oncology, utilized for evaluating suspicious lesions and stratifying tumors. The incorporation of machine learning (ML) into FNAC has revolutionized accuracy, efficiency, and diagnostic precision. This comprehensive review explores recent advances in FNAC, emphasizing the transformative role of ML in image-guided sample collection and tumor stratification. Leveraging deep learning and other ML algorithms, researchers have improved diagnostic accuracy, minimized unnecessary biopsies, and optimized treatment selection. This article highlights the transformative applications of machine learning in FNAC while addressing its current limitations and future potential.

This study describes the energy-momentum density tensor of matter. The main focus is on discussing the conservation laws of the general theory of relativity.

This paper explores Augmented Reality (AR) as an innovative active methodology for student assessment in the Higher Education Authority of Arcoverde, proposing an alternative to the traditional assessment model. It investigates how AR can transform the educational process, making assessments more interactive, engaging and effective. The study focuses on three main issues: the impact of AR on student motivation and engagement, its effectiveness in improving content comprehension and retention, and the challenges and limitations of its implementation as an assessment method. Employing dialectical methods, action research and literature reviews, this research documents a 34% increase in students’ content comprehension and a 47% increase in their participation in practical activities. These findings suggest that, despite the technical and curricular integration challenges, AR not only improves assessment methodologies, but also enhances learning, promoting a more dynamic and interactive environment. The overall objective is to demonstrate the ability of AR to replace conventional approaches with a more innovative and efficient practice, highlighting the importance of this technology in advancing pedagogical practices and improving student performance. This study sheds light on the relevance of AR in the educational field, encouraging its adoption to enrich the learning and assessment experience.

The present studies are specifically aimed at investigating the sensitivity of different dynamic stall models when exposed to various excitation frequencies targeted at the blade edgewise vibrations. The work is done on a modified version of the IEA 15 MW reference wind turbine employing a wind turbine design tool Bladed. The state-of-the-art dynamic stall models for wind turbine applications such as the ye model, Beddoes-Leishman (BL) model and the newly developed IAG model are evaluated. The beginning of the research work starts by evaluating different dynamic stall model effects on rigid blade section forces against known airfoil datasets. Then, the blade flexibility is considered to enable systematic evaluations of the blade flexibility influences in comparison to the rigid blade cases. It is observed that the range of the angle of attack grows depending on the excitation frequency and the adopted dynamic stall model. The critical excitation frequency range and the effects of twist distribution are then identified from the studies, which can be useful as a rough guidance when designing wind turbine blades.

Afghanistan is located on the Eurasian tectonic plate's edge, a highly seismically active region. It is bordered by the northern boundary of the Indian plate and influenced by the collisional Arabian plate to the south. The Hindu Kush and Pamir Mountains in Afghanistan are part of the western extension of the Himalayan orogeny and have been uplifted and sheared by the convergence of the Indian and Eurasian plates. These tectonic activities have generated numerous active deep faults across the Hindu Kush-Himalayan region, many of which intersect Afghanistan, resulting in frequent high-magnitude earthquakes. This tectonic interaction produces ground shaking of varying intensity, from high to moderate and low, with the epicenters often located in the northeast and extending southwest across the country. The reoccurrence and severity of earthquakes have been increasing since 1900. This study maps Afghanistan's tectonic structures, identifying the most active geological faults and regions with heightened seismicity. The increasing trend in recurrence and intensity of the earthquakes are drawn. Historical earthquake data were reviewed, and recent destructive events were incorporated into the national earthquake dataset to improve disaster management strategies. Additionally, the study addresses earthquake hazards related to building and infrastructure design, offering potential solutions and directions to mitigate risks to life and property.

This study aims to explore methods for automating the replication of correlated portfolios across shares using various algorithms. The goal is to select one algorithm for implementation in a visualization tool that will facilitate portfolio building. The dynamics of the stock market provide a comprehensive view of the global economy, acting as a catalyst for stakeholders to participate and benefit various sectors financially, primarily through investments in companies that yield returns and contribute to the economy. The evaluation and comparison of these algorithms are crucial for making well-informed decisions regarding the core objectives of the study. Ultimately, a determination will be made as to whether the program can effectively analyse data from Yahoo finance to provide a quick overview of the financial market state of companies in the S&P 500 US stock prices.

In this paper I dig deep down along the slope of what touches me deeply – a democratic decline in climate politics. I follow the course of critical researchers in management and organisation studies, striving to move away from traditional, horizontal norms of academic writing that focus on counting rather than content and elision the author from the text, towards a more vertical writing acknowledging the value of incorporating the voice of the author. Embodying and resonating with my own emotional experiences of hate and threat campaigns, not locking my own vulnerabilities in, I analyse qualitatively the use, reasons, contents, senders and targets of such nasty rhetoric in Swedish climate politics, and the implications thereof for democracy. At the moment, a far-right populist nativist party holds tangible powers dictating the content and process of Swedish climate politics. In less than two years, Swedish climate politics have turned into an antidemocratic divisive politics portraying climate science as “a point of view”, female journalists writing about climate change and climate policy as “crypto environmentalists”, “motherfuckers” and “moron hags” that should be “fired” and “raped”, and the climate justice movement as “terrorists” and “a threat to Swedish democracy” that should be “sent to prison” and “executed”. Such nasty rhetoric is used not only by anonymous trolls in social media, but by the prime minister, cabinet ministers and parliamentarians, even in debates in the Swedish parliament. It has inspired the far-right extremist movement to use physical violence. Use of nasty politics aims to silence the opponents to the government’s climate policy, the political opposition, climate scientists, the climate justice movement and journalists, breaching liberal and deliberative democratic norms such as legitimacy, accountability and justice. It is a powerful tactic that leaves its targets with an anxious fear of losing control and often a need for disappearance. Many targets resign or stay silent. I chose to break the silence and write differently about the issue.

The use of digital twin and shadow concepts for industrial material processes have promoted new notions to bridge the gap between physical and cyber manufacturing processes. Hence, many multi-disciplinary areas like advanced sensor technologies, material science, data analytics, and machine learning algorithms are employed to create such hybrid systems. On the other hand, new additive manufacturing (AM) processes for metals and polymers based on novel emerging technologies have already shown a promising horizon for manufacturing of sophisticated parts with complex geometries. These processes are going through a major transformation with the emergence of digital technology, hybrid physical-data driven modelling and fast reduced models. This paper presents a fresh look at the hybrid physical-data driven and reduced order modelling (ROM) techniques for digitalization of AM processes within a digital-twin concept. The main contribution is to show the benefits of ROM and machine learning (ML) technology for process data handling, optimization\controlling and their integration into the real-time assessment of AM processes. Hence, a novel combination of efficient data solver technology and architecturally designed neural network (NN) module has been developed for the transient manufacturing processes with high heating\cooling rates. Furthermore, a real-world case study has been presented where the combination of hybrid modelling along with ROM and ML schemes are used for an industrial wire arc AM (WAAM) process.

Ramsey approach to the vectors fields is introduced. Set of vectors defined on R^3, taken as the generators of the bi-colored complete graph, is introduced. Vectors are considered as the vertices of the graph. Following coloring procedure is suggested: vertices numbered i and j are linked with the red edge if their scalar product is non-negative; and they are linked with the green edge if their scalar product is negative. This procedure gives rise to the complete, bi-color graph. Graph generated by six vectors inevitably contains the monochromatic triangle: the Ramsey number Ring-like systems of generating vectors are addressed. Applications of the graphs emerging from the vector fields are discussed.

Software quantum simulators are the most accessible tools for designing and testing quantum algorithms. This paper presents a comprehensive approach to building a software-based quantum simulator based on classical computing architectures. We explore fundamental quantum computing concepts, including state vector representations, quantum gates, and memory management techniques. The simulator prototype implements various memory optimization strategies, such as full-state representation, dynamic state pruning, and shared memory parallelization with OpenMP and distributed memory models using MPI. Additionally, data compression techniques, like ZFP, are explored to enhance simulation performance by reducing memory footprint. The results are validated through performance comparisons with leading open-source quantum simulators, such as Intel-QS, QuEST, and qsim. Our findings highlight the trade-offs between computational overhead and memory efficiency. This demonstrates that a hybrid approach using distributed memory and compression offers the best scalability for simulating large quantum systems. This work provides a foundation for developing efficient quantum simulators supporting more complex quantum algorithms on classical hardware.

This paper is intended to correlate the impact of leadership skills on organizations' performance, all organizations grow differently, and their growth depends mostly on positive performance from one year to another which has direct correlations to the leadership dreams, visions, foresight and aspirations for the organization. There is one thing for the leader to have vision, but the leader needs to have followership to assist in implementing their vision to make it goals which translate to performance in the organization and growth. The leadership style or management skills greatly influence how they command and motivate followership to actualize their dreams or the organizational visions and mission which results in the organization's performance. A positive leadership influence produces or actualizes a positive organisational performance that will move the organization towards the vision of the organization. Knowing the difference between a manager and a leader is pertinent in explaining the correlation between leadership and organizational performance. The understanding of these two roles provides credence to the correlation between effective leadership and organisational performance, and the understanding of the term, the use and the importance of strategic management to leadership and organizational performance. There is a wide difference between managers and leaders, which is based on personality and their approach to the resolution of challenges they are confronted with.

The article examines the evolution and resilience of the Spanish desalination industry in response to changing market conditions and technological challenges. Initially focused on domestic projects, Spanish companies leveraged the A.G.U.A. Program to gain expertise, which later facilitated their successful international expansion as local demand diminished. The industry has adapted to varying international regulations and local conditions, demonstrating flexibility and competitiveness. In recent years, there has been a growing emphasis on integrating renewable energy into desalination processes to address rising energy costs and environmental concerns. This shift not only reduces CO2 emissions but also stabilizes operational costs, highlighting the sector’s ongoing innovation and adaptability.

Plastic surgery is a diverse speciality, relevant to non-plastic doctors, as plastic surgeons frequently collaborate with other specialities and its’ basic principles are transferable across multiple specialities. Foundation year (FY) doctors are the most junior doctors in the workforce and may need to apply plastic surgery knowledge and principles during their clinical duties. Despite this, formal plastic surgery education for junior doctors is limited, resulting in an educational gap. This study gains insight into the perceived confidence, knowledge gaps, skills, educational activities and needs related to plastic surgery. This qualitative study uses phenomenology through semi-structured individual interviews with 8 FY doctors. Data was analysed using reflexive thematic analysis. This study revealed that plastic surgery features diversely in the work life of FYs, who often manage patients with a lack of knowledge and confidence, influencing patient care and FY wellbeing. FYs primarily acquire knowledge and confidence through experiential learning and individual initiative. A need for curriculum improvements was expressed. FYs are an essential part of the workforce who exhibited educational gaps and a lack of confidence in plastic surgery knowledge. We suggest improved integration of plastic surgery into the FY curriculum for improved FY knowledge and patient care.

In this note we prove that the Riemann hypothesis is false. The proof is by contradiction based on a criterion of Hu.

This paper investigates the secular decline in real interest rates and the potential influence of central bank monetary policy on long-term government bond yields, focusing particularly on the US Federal Reserve (Fed). While various demand-side and supply-side explanations, such as ageing populations, lack of investment opportunities, and reduced productivity growth, have been proposed for this decline. A recent study highlighted the significant role of 3-day time windows around Federal Open Market Committee (FOMC) meetings in capturing yield changes in 10-year Treasuries. To explore if similar patterns exist in other advanced economies, this study constructs 3-day monetary policy decision windows around the 10-year government bond yields for selected countries, using both domestic central bank decision dates and those of the Fed. The findings suggest that, despite heterogeneity among advanced economies and factors like unconventional monetary policy tools and exchange rate interventions, there is substantial evidence supporting a stronger influence of the Fed's decisions on global bond yields compared to national monetary policies. By employing a simple Ordinary Least Squared (OLS) method to analyze the covariance between bond yields and policy decisions, this study establishes a connection between the literature on the global financial cycle and secular stagnation. The results imply that the Fed's influence extends beyond US borders, potentially contributing to a global monetary policy dynamic.

An analogy between magneto-fluid dynamics (MFD/MHD) and geostrophic flow in a rotating frame of reference including the existence of electromagnetic columns identical to Taylor-Proudman columns is identified and demonstrated theoretically. The latter occurs in the limit of large values of a dimensionless group representing the magnetic field number. Such conditions are shown to be easily satisfied in reality. Consequently, the electromagnetic fluid flow subject to these conditions is two dimensional and the streamlines are being shown to be identical to the pressure lines in complete analogy to rotating geostrophic flows. An experimental setup is suggested to confirm the theoretical results experimentally.

Late-life diseases result from the poorly understood process of senescence (aging), that is largely genetically determined. According to a recently proposed evolutionary physiology-based account, the multifactorial model, senescence is largely caused by evolved but non-adaptive programmatic mechanisms specified by the wild-type (i.e. normal) genome. These act together with disruptions to wild-type function (due e.g. to infectious pathogens, mechanical injury and malnutrition) in a variety of combinations to generate diverse late-life diseases. Here the utility of this model is explored by testing its capacity to provide an account of one complex, late-life disease, osteoarthritis (OA), and a framework for understanding OA etiology suggested. In this framework, the core OA disease mechanism is a futile endochondral ossification quasi-program (non-adaptive developmental program), in which hypertrophic articular chondrocytes alter joint architecture. Programmatic changes prime chondrocytes for quasi-program activation, which can be triggered by secondary causes of OA (e.g. joint mechanical injury). A suggested evolutionary cause of this priming, involving antagonistic pleiotropy, is selection to maximize early life tissue repair benefits at the expense of late-life programmatic costs.

Background: The Covid-19 pandemic was in reality a syndemic there the balance between a multitude of biological (Nature-made) and socio-political (men-made) factors determined individually the outcome of every single infection, on a scale of nothing-to-fatal. Blaming the virus for everything bad that happened to us after January 2020 is incorrect. Now, in ~ 2 years distance from the syndemic, it may be timely and possible to uncover the human contribution to this historical event and learn of it. Objective: To identify and use some qualitative approach to estimate the objective, statistical / epidemiological ‘value’ of the virus-selected individuals (in age-normalized groups) for the rest of the society. This non-political, non-religious approach may be the only way to understand the benefit / cost ratio of actions and emergency orders we had to survive in addition to the virus itself. Methods: Statistical data were obtained from publicly available official databases, including the relevant actuarial tables and evaluated by widely used statistical methods. The estimation of statistical/epidemiological ‘value of life’ was based, strictly and exclusively, on the real age and the statistically calculated Residual Life Expectancy (RLE, i.e. remaining years alive at a given age). The American healthcare expenses were compared to the corresponding healthcare costs/capita in other similarly well-developed west-European countries. This was the only available method to get some ideas about the magnitude of the well-established (rational) healthcare spending and compare it to the American standards. Results 1) Life expectancy uninterruptedly increased in USA since 1933, due to continuous reduction of Mortality Rate of the youngest and oldest citizens. COVID didn’t stop the population growth (+8.2 M /2020-2023). 2) The total count of Excess COVID associated Deaths (XCD) is ~ 2-times as much as the official statistic was able to explain by virus infection. It is speculated that these Complementary Covid Deaths (CCD) are probably the unexpected side-effects of the pandemic related emergency orders. 3) The worldwide ‘longevity’ trend exponentially increased the healthcare expenses, especially the care of elderly. However the USA is unique in this aspect and the healthcare costs are irrationally much higher than in any other country. 4) We can see a large economic incentive in the development of excesses under COVID syndemic. Conclusions The harm of the COVID virus - as well as the benefits of the mandatory, emergency actions during the pandemic - were grossly over-estimated. Professional, unbiased (non-religious, non-political) and independent reviews are strongly recommended.

Worldwide cervical cancer ranks the fourth most common cancer in women. In Tanzania, cervical cancer is the leading female malignancy, and a major cause of cancer related mortality and morbidity in women. More than 80% of women with cervical cancer, are diagnosed with late stage, in which curative treatment options are not available. To explore the knowledge, perceptions and behaviors among women with late-stage cervical cancer who attended Bugando Medical Centre (BMC) from November to December 2021. Explorative qualitative study was conducted from November to December 2021 at BMC, involving 11 participants who had late-stage cervical cancer. Purposive sampling was used to recruit information-rich participants. Data collection was done by using open ended In-depth interview guide. The guide contained information on social demographic characteristics, knowledge on cervical disease, perceptions towards cervical cancer symptoms, health care seeking behaviors. Data was transcribed and analysed manually by using thematic approach. The coded texts generated three themes and nine subthemes. The results showed that Participants had poor knowledge about cervical cancer disease, causes, risk factors, prevention measures and treatment options which had impact on the perceptions and health care seeking behaviors. Participants misinterpreted the symptoms with other urogenital conditions like fungus and urinary tract infection. Misconception about the symptoms and disease, long distance to health facilities and financial challenges hindered involvement in seeking biomedical intervention and witch doctors were given a priority. Findings from this study suggest a strong need of intensive health promotion efforts and education through mass media and outreaches to improve adequate and correct knowledge and awareness about cervical cancer disease, causes, symptoms, risk factors, prevention and treatment options. Health care providers and policy makers should include cervical cancer disease as a topic of everyday health education in the health facilities.

The growing emphasis on sustainability and environmental stewardship in the pharmaceutical industry necessitates innovative solutions to manage pharmaceutical waste, particularly medication bottles. This research paper explores the potential of integrating Radio Frequency Identification (RFID) and blockchain technology to enhance the traceability, accountability, and efficiency of recycling empty medication bottles. By utilizing RFID for real-time tracking and blockchain for secure, immutable data storage, this proposed system improves transparency across the supply chain and incentivizes consumer participation in recycling programs. The solution provides benefits to pharmaceutical manufacturers, regulators, and consumers, contributing to sustainability, regulatory compliance, and environmental protection.

In this paper, the distribution of prime numbers is expressed based on proving the Riemann hypothesis. The relationship between three numbers, three, six, and nine, and the modality to the distribution of prime numbers, is one of the results of Riemann's zeta function. Prime numbers are classified into six groups of single-digit numbers. There are no prime numbers in groups of three, six, and nine. The groups are made based on the sum of the internal digits. And for each set, there is an angle in the complex plane. The distance between the prime numbers in each group has a regular pattern. This pattern is a multiple of the numbers three, six, and nine. According to Euler's number, for an angle of 60 degrees, the real part of the cosine is 1/2. Accordingly, all prime numbers are related to angles greater than 60 degrees to 90 degrees. As a result, based on the relationship between the golden spiral and the complex conjugate of the zeta function, the function in The 1/2 point becomes zero based on the prime numbers.

Maria Valtorta (MV) (1897–1961) – an Italian mystic who claimed to have visions of Jesus’s life – describes Jesus’ crucifixion with many details from which significant data can be retrieved. My investigation based on these data and the topography of northwest Jerusalem in the I century AD, shows that Jesus’ crucifixion place, Golgotha (the “skull”), is neither at the Holy Sepulchre nor in the Garden Tomb area. The paved road to Golgotha she accurately describes arrives at its top with the minimum mean route gradient; its half way defines two distinct tracts with same height and same walking time but different mean route gradient; at half way Jesus is allowed to walk to the top in a spiral country road less steep than the second tract. The paved road leads to a place where few years after Jesus’ crucifixion the Psephinus Tower, described by Flavius Josephus, was erected, in the area known today as the Russian Compound. In conclusion, the Golgotha reveiled by MV’s writings was located at the same site of the Psephinus Tower.

A thorough understanding of nuclear reaction rates at low energies is essential for improving our understanding of energy generation in stars and primordial and stellar nucleosynthesis. At low energies, fusion reactions between charged particles are strongly suppressed by the presence of the Coulomb barrier which classically inhibits the penetration of one nucleus into another. The barrier penetration causes the cross section to have a steep energy dependence at low energies, making cross section measurements very challenging. Furthermore, little is known about the impact of surrounding electrons in stellar plasmas that are currently beyond the reach of experiments. As a result, measuring the bare cross sections as accurately as possible is essential. Reaction rate measurements at very low energies have been made possible in recent years by the development of high-current low-energy accelerators as well as enhanced target and detection methods. Nevertheless, the presence of atomic electrons, which alter the Coulomb barrier by screening the nuclear charge and increase the cross section at low energies compared to the case of bare nuclei, complicates these observations. A review of the experimental and corresponding theoretical work on laboratory electron screening performed so far will be presented.

Theories about consciousness—what it is/is not; who does/does not possess it; included/excluded functional modes; how/when it appears to be operational—are regularly published in books and articles. This essay opines that while many, if not most, of those speculations contain elements properly subsumed within a comprehensive doctrine, none satisfactorily fulfills its subject’s immense scope. Consciousness = Metaphysics + Physics + Biology is intended to rectify the situation by providing omitted components. As the title states, this is a wide-ranging approach neglecting many relevant details found in cited references, but also including ideas not found elsewhere in the easily accessible literature.

The electrochemical investigation of 1,2- and 1,4-dihydroxybenzenes was carried out with platinum macro- and microelectrode by using the square wave and cyclic voltammetry techniques. On the other hand the effect of the two solvents acetic acid and ethyl acetate were compared. By using square wave voltammetry signals showed up only at lower frequencies and in excess of supporting electrolyte as it was expected due to the relatively low permittivities of the used solvents. The behaviour of hydroquinone and catechol did not differ significantly from that of their derivatives (dihydroxybenzaldehydes, dihydroxybenzoic acids and 2’,5’-dihydroxyacetophenone). When the cyclic voltammetric examinations with microelectrode were extended to higher anodic potentials the electrode fouling was very significant in ethyl acetate after the potential region of steady-state oxidation to the corresponding quinone. The substituent effect was not significant also here rather the position of the two hydroxyl groups in the benzene ring. Contrarily, the positions had dramatic influence on the susceptibility to electropolymerization as 1,2-dihydroxybenzenes independently on the nature of substituent in the benzene ring deactivated the electrode while 1,4-dihydroxybenzenes did not possibly due to the different solubilities of polymers formed from the primary oxidation product quinones.

The global prevalence of cancer is on the rise, and while targeted therapies, early diagnosis, im-munotherapies, and conventional personalized chemotherapy have significantly upgraded out-comes for cancer patients, there is still a significant likelihood that cancer cannot be fully eradi-cated. Cancer stem-like cells (CSCs) and Epithelial-mesenchymal transition (EMT) exhibit pivotal roles in cancer cell metastasis, tumor recurrence, chemotherapy resistance, and cancer cell death, among other processes. This review aims to elucidate the molecular mechanisms underlying EMT and CSCs, their interplay, associated signaling pathways, and regulation of the EMT process and the initiation of CSCs. EMT induction confers mesenchymal properties and the potential of cancer cells to adopt the CSC state. These processes are intricately associated with the regulation of Notch and Wnt signaling pathways, transforming growth factor-β (TGF-β), as well as the expres-sion of miRNAs. Further exploring the relationship between EMT and CSCs is essential for the development of new chemotherapeutic strategies and the identification of novel therapeutic tar-gets, and hence, the development of therapeutic strategies targeting EMT, or CSCs holds promise for improving cancer therapy.

The fundamental divergence in foundation of modern physics lies in the incompatibility between quantum theory and relativity. This study created a relative continuum, found a mathematical tool for the cosmic continuum; proposed dark particle hypothesis, filled gap on minimum existence quantity particle; discovered new equivalence principle, bridged differences in foundation of physics; and established an ideal model, revealed deep essence of cosmic and material structure. In this model, any cosmic system is a continuum composed of existence continuum relative to the wavelength of bosons energy waves and its dimension continuum. This model provides new perspectives on the fundamental problems of physics and cosmology. Firstly, it elucidated the physical mechanism of bosons in fundamental interactions. Secondly, it reconstructed the understanding of the basic unit of the cosmic and material structure. Thirdly, it updated the inherent concepts about the existence form and existence dimension. Fourthly, it restored the causality truth of wave function collapse in quantum mechanics.

Recent advancements in semantic communication (SC) have shown the potential to surpass the limitations of the Shannon theorem, by leveraging an understanding of the meaning of data instead of the data itself. In networks, data-aided sensing (DAS) presents a powerful tool that can significantly reduce communication overhead, aligning perfectly with the goals of SC by providing more powerful semantic messages. This survey explores the synergy between DAS and SC and investigates how their convergence can lead to more efficient and effective communication.

Theoretical physics addresses the fundamental principles of nature and the mysteries of the universe. In the last century, the theory of relativity challenged people's understanding of time and space, while quantum mechanics revealed various forms of energy. However, the concept of gravity remains elusive. All matter in the universe is composed of energy that can be converted into other forms, yet it is always conserved. However, achieving a state of equilibrium, represented by the equal sign, can be challenging to achieve on both macro and quantum scales. A phenomenon that can transition from one state to infinity is called collision and is essential for understanding natural phenomena and physical processes throughout the universe. In the study of general relativity cannot be three-dimensional problems to gain mathematical inspiration, understand the application of new dimensions. Here, we elucidate the nature of gravity, which inspires the solution of the Riemann hypothesis. Our results show that the conduction mode of dimensional energy is defined by Euler's formula. And a special mode of collision is derived which translates into vibration.

The increasing global demand for efficient and sustainable energy storage solutions has driven the exploration of sulfur-based battery technologies. Sulfur’s abundance, low cost, and high theoretical energy density make it a promising candidate for next-generation energy storage, particularly in electric vehicles (EVs) and renewable energy systems. This paper reviews the development of sulfur-based batteries, including lithium-sulfur (Li-S), sodium-sulfur (Na-S), magnesium-sulfur (Mg-S), solid-state sulfur, sulfur-carbon nanocomposites, and hybrid sulfur flow batteries. Each technology is analyzed based on its advantages, challenges, and potential applications. Key research areas such as advanced electrolytes, nanomaterial integration, and sustainable manufacturing are highlighted, along with the current technological barriers to large-scale adoption. This review underscores the importance of continued research and innovation in sulfur-based battery technology to meet future energy storage demands.

Urban logistics is a critical component of smart city initiatives, aiming to enhance the efficiency and sustainability of goods delivery in densely populated areas. This paper explores the integration of artificial intelligence (AI), autonomous vehicles, and Internet of Things (IoT) technologies to optimize urban logistics. By leveraging real-time data from IoT-enabled infrastructure and AI-driven analytics, we propose a framework for dynamic route planning, traffic signal control, and predictive demand management for delivery services.

The aim of this article is to shed some light on ‘black open access’ model, that still remains poorly understood and largely neglected in the literature, despite being widely adopted in practice. I give an overview of the historical development of black OA and its most important projects: Sci-Hub and Library Genesis. Arguments are provided for why the term ‘black OA’ is misleading and the term ‘RGB OA’ (red, green and blue) would better describe a diverse landscape of open access projects that emerged after 2001. While practical approaches towards OA evolved dramatically in the past 20 years, theoretical discussion is still operating the same two-color scheme of ‘green’ and ‘gold’ open access from BOAI declaration of 2001: novel approaches are either not recognized as OA at all or are neglected as ‘black’. A new and more inclusive OA declaration might be needed to account for greater diversity of approaches.