Pregnant women have been considered a high-risk group for SARS-CoV-2 infection; the impact of the disease on the health of a mother and her child is still being studied. The emotional impact of the pandemic on pregnant women has been extensively studied. Emotional distress is proposed as a perspective to explain the emotional manifestations of women during this stage as something common rather than pathological. The objective of this study was to know the emotional experience of women who tested positive for SARS-CoV-2 towards the end of their pregnancy, during the first and second waves of COVID in Mexico. A qualitative study was carried out: 18 pregnant women with COVID were interviewed. A thematic analysis of the data was performed, resulting in three main themes and 14 subthemes. The COVID-infected mothers-to-be experienced mild to moderate emotional distress. It was more intense for those with comorbidities. This distress was aggravated during obstetrical complications and comorbidities, as well as during COVID and postpartum. The emotional distress was appeased by both the perception of medical care and social support. The emotional distress of pregnant women with COVID requires emotional accompaniment to reduce its impact.

Metaheuristic algorithms are widely used as optimization methods, due to their global exploration and exploitation characteristics, which obtain better results than a simple heuristic. The Stochastic Fractal Search (SFS) is a novel method inspired by the process of stochastic growth in nature and the use of the fractal mathematical concept. Considering the chaotic-stochastic diffusion property, an improved Dynamic Stochastic Fractal Search (DSFS) optimization algorithm is presented. The DSFS algorithm was tested with benchmark functions, such as the multimodal, hybrid and composite functions, to evaluate the performance of the algorithm with dynamic parameter adaptation with type-1 and type-2 fuzzy inference models. The main contribution of the article is the utilization of fuzzy logic in the adaptation of the diffusion parameter in a dynamic fashion. This parameter is in charge of creating new fractal particles, and the diversity and iteration are the input information used in the fuzzy system to control the values of diffusion.

Aim: This analytical cross-sectional study aimed to examine whether there is a correlation between tumor differentiation and certain biomarkers in patients with hepatocellular carcinoma (HCC). Methods: Poorly differentiated (n=443), moderately differentiated (n=379), and well-differentiated (n=272) tumors were separated from the research population, along with a control group (n=364). Biopsies were used to establish the presence of HCC, and biomarker levels were analyzed using chemiluminescence immunoassays in both infected and uninfected individuals. Results: The correlation between age and tumor size was shown to be statistically significant (p0.05) across all subgroups using both descriptive and inferential statistics. Patients with hepatitis C virus and non-A, non-B hepatitis had more advanced tumors than those with other types of poorly differentiated liver cancer. Similarly, individuals with HBsAg and moderate differentiation had bigger tumors, although there was no correlation between hepatitis C and non-A, non-B. Patients with HBsAg or hepatitis C had bigger tumors in the well-differentiated group, albeit the hepatitis C connection was not statistically significant. In addition, the study stressed that tumor size increases with age and that farmers were the most commonly diagnosed profession category. Conclusions: It is clear that early detection in infected populations is crucial for improving HCC outcomes and that chemiluminescence immunoassay has the potential to be a helpful platform for biomarker research. However, the study is limited by its small sample size and its emphasis on only three tumor markers, indicating that more biomarker research is required to improve the accuracy of HCC diagnosis and prognosis.

In developed countries, especially the big-sized ones like Australia and the USA, a car is almost an inevitable necessity to carry out daily activities. Due to this, used cars have become a great alternative to brand new cars because of their cost effectiveness. In this work, estimation of prices of used cars based on numerous factors is studied statistically. Data is based on prices of used cars sold across Australia. Statistical methods like correlation and permutation tests using linear regression model, exact tests and non-parametric bootstrapping is implemented to study the relationship of price with mileage and year of manufacture of the car using p-values and null hypothesis. Predictions are also made on the price by calculating a 95% confidence interval (CI) of median prices in small portions of the dataset. The study presents potential ideas for understanding correlation between variables and parameters in business studies.

(1) This study aimed to examine the prevalence of depression and its correlation with acculturative Stress and Social Connectedness among domestic and overseas students in Japan International University. (2) Methods: A Web-based survey was distributed among students of International University, which resulted in 263 responses. On the survey together with socio-demographic data, a nine-item tool from the Patient Health Questionnaire (PHQ-9), was used to measure the prevalence of Depression and its relationship with socio-demographic data, Social Connectedness Scale was used to measure Social Connectedness, and Acculturative Stress Scale for International Students (ASSIS) was used to measured acculturative stress. (3) Results: Depression was significantly high in international and domestic students (37.81% and 29.85% respectively). English language proficiency and students age (20 years old) showed a significant correlation with depression among domestic students (β=-1.63, p=0.038 and β=2.24, p=0.048). Stay length (third year) also displayed a significant correlation with depression among international students (β=1.08, p=0.032). Among international and domestic students statistically significant positive correlation between depression and acculturative stress, negative associations of social connectedness with depression and acculturative stress were also found. Suicidal or self-hurting ideation thoughts are found among around 20% of all students. (4) Conclusions: These findings indicate a relatively high prevalence of depression among students of International University, and overseas students are more affected. Depression, Acculturation stress and Social Connectedness show statistically strong intercorrelation, which highlights the need of host University to recognise the role of Acculturation and Social Connectedness in the development of Depression among students.

An upsurge in global population over the years and rapid urbanization have accelerated huge dependence on petroleum-derived fuels and consequent environment concerns owing to green-house gas emissions in the atmosphere. An integrated biorefinery uses lignocellulosic feedstock as raw material for the production of renewable biofuels, and other fine chemicals. The sustain-able bio-economy and the biorefinery industry would benefit greatly from the effective use of lignocellulosic biomass obtained from agricultural feedstocks to replace petrochemical products. Lignin, cellulose, hemicellulose, and other extractives, which are essential components of ligno-cellulosic biomass, must be separated or upgraded into useful forms in order to fully realize the potential of biorefinery. The development of low-cost and green pretreatment technologies with effective biomass deconstruction potential is imperative for an efficient bioprocess. The abun-dance of microorganisms along with their continuous production of various degradative en-zymes makes them suited for the environmentally friendly bioconversion of agro-industrial wastes into viable bioproducts. The present review highlights the concept of biorefinery, ligno-cellulosic biomass and its valorization by green pretreatment strategies into biofuels and other biochemicals. The major barriers and challenges in bioconversion technologies, environmental sustainability of the bioproducts and promising solutions to alleviate those bottlenecks are also summarized.

People are increasingly encouraged to reduce animal food consumption and shift towards plant-based diets, however the implications for children’s health are unclear. In this narrative review of research in high-income settings, we summarize evidence on the increasing consump-tion of plant-based diets in children, and update an earlier systematic review regarding their associations with children’s health outcomes. The evidence indicates that vegan but not vege-tarian diets can restrict growth relative to omnivorous children, and increase the risk of being stunted and underweight although the percentage affected is relatively small. Bone mineral content is reduced in vegetarian and especially vegan children, compared to omnivores. Both vegetarian and vegan children who do not use vitamin B12 supplements manifest with B12 defi-ciency, however supplementation rectifies this problem. Both vegetarians and vegans have lower concentrations of 25 (OH)D if unsupplemented, and lower body iron stores, but usually have normal iron metabolism markers. Both groups are at risk of iodine deficiency and this might affect thyroid health. Children consuming a vegan diet have more favorable lipid profile than omniv-orous children, however the results for vegetarian diet are inconsistent and vary by outcome. Based on the same scientific evidence, national and international dietary recommendations are heterogeneous, with some countries supporting plant-based diets among infants, children and adolescents, and others discouraging them. We offer a research roadmap, highlighting what is needed to provide adequate evidence to harmonize dietary recommendations for plant-based diets in children. A number of measures should urgently be introduced at international and na-tional levels to improve the safety of their use in children.

Abstract: Congenital cytomegalovirus (cCMV) infection poses significant risks to fetal development, particularly affecting the nervous system. This study reports a fetal autopsy case, examining cCMV infection and focusing on CMV DNA measurements in various fetal organs before formalin fixation, a novel approach for comprehensive CMV DNA evaluations in fetal organs affected by cCMV. A 20-week-old male fetus was diagnosed with cCMV following the detection of CMV DNA in ascites obtained via abdominocentesis in utero. After termination of pregnancy, multiple organs of the fetus, including the cerebrum, thyroid gland, heart, lungs, liver, spleen, kidneys, and adrenal glands, were extracted and examined for CMV DNA loads using real-time polymerase chain reaction. Histopathological examination involved hematoxylin-eosin and CMV-specific immunostaining. A correlation was found between CMV DNA loads and pathology, with higher CMV-infected cell numbers observed in organs positively identified with both staining methods, exhibiting CMV DNA levels of ≥1.0 × 104 copies/mL, compared to those detected solely by CMV-specific immunostaining, where CMV DNA levels ranged from 1.0 x 103 to 1.0 x 104 copies/mL. These results highlight a quantifiable relationship between organ infection extent and CMV DNA concentration, providing insights into cCMV pathogenesis and potentially informing future diagnostic and therapeutic strategies for cCMV infection.

A complex square matrix $A$ is said to be Hermitian if $A= A^{\ast}$, the conjugate transpose of $A$. The topic of the present note is concerned with the characterization of Hermitian matrix. In this note, the we show that each of the two triple matrix product equalities $AA^{\ast}A = A^{\ast}AA^{\ast}$ and $A^3 = AA^{\ast}A$ implies that $A$ is Hermitian by means of decompositions and determinants of matrices, which are named the two-sided removal and cancellation laws associated with Hermitian matrix, respectively. We also present several general removal and cancellation laws as the extensions of the preceding two facts about Hermitian matrix.

Background: Breastfeeding self-efficacy is a critical factor influencing the initiation and continuation of breastfeeding among mothers. Low self-efficacy affects mothers’ ability to sustain breastfeeding. Several studies have investigated the factors influencing breastfeeding self-efficacy, but none have interconnected maternal, infant, and social support factors. Aims: This study aimed to measure the correlation between maternal and infant factors, social support, and breastfeeding self-efficacy. Methods: A cross-sectional approach was employed in Jember, Indonesia, among 200 breastfeeding mothers. The study population consisted of mothers 17-42 years old who were breastfeeding and who met the following inclusion criteria: mothers who have babies aged 1-6 months, term pregnancy history, wanted pregnancy, and baby weight born ≥ 2500 grams. Maternal and infant factors and social support were determined through interviews and questionnaires. Breastfeeding self-efficacy was examined using The Breastfeeding Self-efficacy Scale Short. The multiple logistic analysis was used for multivariate analysis. Results: Of a total of 200 breastfeeding mothers, 63% had low breastfeeding self-efficacy, and 59.5% of mothers did not exclusively breastfeed. The multiple logistic regression indicated that 74.2% of the factors included in the model influenced breastfeeding self-efficacy. Positive correlations were observed between breastfeeding self-efficacy and feeding type (OR=6.603), breastfeeding frequency (OR=6.220), breastfeeding intention (OR=4.993), and family type (OR=4.001). Conclusion: feeding type, breastfeeding frequency, and family support were the important factors that support breastfeeding self-efficacy.

Background: To assess the prevalence of Hypertension (HTN) in Burning Mouth Syndrome (BMS) patients and to investigate its relationship with sociodemographic factors, pain and the psychological profile. Methods: A case-control study was conducted by enrolling 242 BMS patients and 242 controls matched for age and gender. Sociodemographic and clinical characteristics were recorded, and all the participants completed the numeric rating scale (NRS), the short-form of the McGill pain questionnaire (SF-MPQ), the Hamilton rating scale for anxiety and depression (HAM-A, HAM-D), the Pittsburgh sleep quality index (PSQI) and the Epworth sleepiness scale (ESS). Results: The BMS patients presented a statistically significant higher prevalence of HTN compared to the controls (55% versus 33.5%; p-value: <.001**) and higher median scores of the NRS, SF-MPQ, HAM-A, HAM-D, PSQI and ESS (p < .001**). Multivariate regression analysis in the BMS patients indicated positive correlations between HTN and age, systemic diseases, drug consumption and anxiety (p-value: <.001**) and these predictors were responsible for 11.3% of the HTN variance in the BMS patients, when considered together. Conclusions: The prevalence of HTN was significantly higher in the BMS patients, since ageing, the presence of comorbidities, drug consumption and anxiety were potential predictors. Further studies are needed to better investigate the relationship between BMS and HTN.

With the rapid development of Internet and the widely usage of smart devices, massive multimedia data are generated, collected, stored and shared on the Internet. This trend makes cross-modal retrieval problem become a hot issue in this years. Many existing works pay attentions on correlation learning to generate a common subspace for cross-modal correlation measurement, and others uses adversarial learning technique to abate the heterogeneity of multi-modal data. However, very few works combine correlation learning and adversarial learning to bridge the inter-modal semantic gap and diminish cross-modal heterogeneity. This paper propose a novel cross-modal retrieval method, named ALSCOR, which is an end-to-end framework to integrate cross-modal representation learning, correlation learning and adversarial. CCA model, accompanied by two representation model, VisNet and TxtNet is proposed to capture non-linear correlation. Beside, intra-modal classifier and modality classifier are used to learn intra-modal discrimination and minimize the inter-modal heterogeneity. Comprehensive experiments are conducted on three benchmark datasets. The results demonstrate that the proposed ALSCOR has better performance than the state-of-the-arts.

The number of SIEM introduction is increasing in order to detect threat patterns in a short period of time with a large amount of structured/unstructured data, to precisely diagnose crisis to threats, and to provide an accurate alarm to an administrator by correlating collected information. However, it is difficult to quickly recognize and handle with various attack situations using a solution equipped with complicated functions during security monitoring. In order to overcome this situation, new detection analysis process has been required, and there is an effort to increase response speed during security monitoring and to expand accurate linkage analysis technology. In this paper, reflecting these requirements, we design and propose profiling auto-generation model that can improve the efficiency and speed of attack detection for potential threats requirements. we design and propose profiling auto-generation model that can improve the efficiency and speed of attack detection for potential threats.

We propose a universal approach for modeling complex integrated photonic resonators based on the scattering matrix method. By dividing devices into basic elements including directional couplers and connecting waveguides, our approach can be used to model integrated photonic resonators with both unidirectional and bidirectional light propagation, with the simulated spectral response showing good agreement with experimental results. A simplified form of our approach, which divides devices into several independent submodules such as microring resonators and Sagnac interferometers, is also introduced to streamline the calculation of spectral transfer functions. Finally, we discuss the deviations introduced by approximations in our modeling, along with strategies for improving modeling accuracy. Our approach is universal across different integrated platforms, providing a useful tool for designing and optimizing integrated photonic devices with complex configurations.

Dual quaternions have wide applications in automatic differentiation, computer graphics, mechanics and others. Due to its application in control theory, the matrix equation AXB=C has been extensively studied. However, there is currently limited information on matrix equation AXB=C over the dual quaternion algebra. In this paper, we provide the necessary and sufficient conditions for the solvability of the dual quaternion matrix equation AXB=C, and present the expression for the general solution when it is solvable. As an application, we derive the ϕ-Hermitian solutions for the dual quaternion matrix equation AXAϕ=C, where the ϕ-Hermitian extends the concepts of Hermiticity and η-Hermiticity. Lastly, we present a numerical example to verify the main research results of this paper.

In this paper, we introduce ResNetMF, a groundbreaking approach that harnesses the power of residual network matrix factorization to revolutionize recommendation systems. ResNetMF integrates residual networks, renowned for their ability to capture intricate patterns and features, with matrix factorization techniques that excel in modelling user-item interactions. This fusion presents a novel solution that surpasses the limitations of traditional recommendation systems. Through comprehensive experimentation and evaluation of diverse datasets, ResNetMF demonstrates remarkable enhancements in recommendation accuracy and efficiency. By effectively capturing both linear and nonlinear relationships in user-item interactions, ResNetMF provides superior recommendation quality. The outcomes from experiments unequivocally highlight the superiority of ResNetMF over existing state-of-the-art recommendation approaches, thereby validating its innovative nature and underscoring its potential to shape the future of recommendation systems. Through the integration of the deep residual network, ResNetMF approach facilitates the training of neural networks, enabling them to explore the underlying data layers more comprehensively. Extensive experimentation and evaluation across various datasets provide compelling evidence for the superiority of ResNetMF. Moreover, the proposed method utilized natural language processing (NLP) techniques for targeted information dissemination in recommendation systems, emphasizing the importance of personalized and relevant recommendations for user satisfaction and engagement.

There is need to address the challenges of organ shortage, through development of tissues and organs with alternatives to those of the allograft-kind. This illustrates the quest behind novel biofabrication strategies such as 3D bio-printing, which is necessary to create artificial multi-cellular tissues/organs. Several findings have been reported in this review. First, the role of ECM components in tissue regenerative medicine is presented. Different ECM components such as collagen, gelatin, elastin, fibronectin, laminins and glycosaminoglycans are concisely examined for their tissue regenerative medicine applications. Next, current state of research on extrusion-based 3D bio-printing techniques and their limitations are reviewed. For example, we show that cell viability is still a challenge with extrusion, while the use of natural polymers such as collagen in improving composites’ mechanical properties is limited. Lastly, we examine unresolved research questions necessary to advance the present state of research in the field.

This study's main target was to analyze and design rectangular edges supported two ways solid slabs by using ES EN 1992-1-1:2015. Slab design is often carried out either manually or with the use of design and analytic software. The researcher sees that some software cannot accept some countries' standard codes. For example, currently in Ethiopia analysis and design of two-way solid slab is done using readily available Excel sheet template. But working with this might have many problems, firstly the structure that is already analyzed by SAP or SAFE or any other international software application that uses international codes but which cannot design structure using ES EN 1992; for instant euro codes and designed by excel sheet can create failure and uneconomical analysis and design result. In this paper, the slab is designed and analyzed based on the chosen concrete grade, chosen reinforcement bar diameter, chosen steel grade for design and analysis of slabs calculations like load, moment, shear, and deflection checking using the moment coefficient method for analysis and design and Microsoft Visual Basic 2010 for coding. All input values are given by the International Standard units and are also used to represent output values. Using manual calculations delays time and mostly the result is not correct. But using this Computer program can increase computation accuracy and save time. The procedure the researcher followed is, first the manual calculation has been done and then SADSE2021 has been done. The result is that both are 99.9% identical, and the disadvantage of this method is that it cannot be used to determine the detailed drawing.

Herbicides are widely used in agriculture to control weeds and enhance crop productivity. However, their application can have significant impacts on soil health and nutrient dynamics. This paper reviews the effects of herbicides on soil properties, microbial communities, and nutrient availability, with a particular focus on calcium deficiency. The review synthesizes findings from peer-reviewed journals and reports, including research conducted in Australia. The correlation between herbicide application and calcium deficiency is explored, highlighting both positive and negative impacts. The paper concludes with recommendations for sustainable herbicide use and alternative weed management strategies.

The purpose of the investigation was to determine the relationship between rotary kiln liner loss and steel structure ovality. As measurement apparatus, a terrestrial laser scanner was used. The interior and exterior of the rotary kiln were measured. The primary focus object was inner-lining loss and the geometric characteristics of cylindrical shells. The research uncovered significant disparities in inner lining loss between sections. A correlation was found between ovality and elimination of inner lining. Due to the hypothesis of constant inner linig loss from the middle of the rotary kiln, the investigation found that the loss of brick lining was less than the value reported from the boreholes. The study offers significant information on maintenance and repair strategies for rotary kilns, which have the potential to increase their efficiency and useful life.

Cosmic strings can arise from spontaneous phase transitions during the inflationary period and are describable as disclination topological defects in spacetime. Analytical integration of the geodesic equations for a particle around a cosmic string reveals distinct orbit patterns dependent on the disclination intensity $\beta_{0}$. After its interaction with the cosmic string, the particle's behavior becomes random. To categorize these patterns, we describe the geodesic motion as iterated maps of a discrete parameter. Through the stabilization values of these functions, we correlate the scattering angle and the number of loops for the particle with $\beta_{0}$. Therefore, we interpret the gravitational field mathematically as an instructor of a particle's next position, given its previous one. We find that the radial function in the small displacement limit is similar to the logistic map. This leads us to conjecture the potential of the discrete parameter being a multiple of Planck's time, suggesting a method for the geometric discretization of spacetime around a cosmic string.

This study investigates the frequency dependence of the correlation or anticorrelation of ozone and temperature in the middle atmosphere. The anticorrelation of ozone and temperature plays a role for the expected recovery or superrecovery of upper stratospheric ozone in presence of manmade cooling of the middle atmosphere due to increasing carbon dioxide emissions. The correlation between lower stratospheric ozone and temperature indicates the dependence of lower stratospheric temperature trends on the ozone evolution in addition to greenhouse gas emissions. Ozone and temperature measurements of the microwave limb sounder (MLS) on the satellite Aura from 2004 to 2021 are utilized for Bern (46.95∘N, 7.44∘E) at middle latitudes and for the equator region. The time series are bandpass filtered for periods from 2 days to 5 years. The correlation coefficient depends on the period of the oscillation in temperature and ozone. The strongest correlation and anticorrelation are found for the annual oscillation. The anticorrelation between ozone and temperature in the upper stratosphere is about −0.7 at a period of 2 days and −0.99 at a period of one year. Thus, the temperature dependence of the ozone reaction rates also leads to an anticorrelation of ozone and temperature at short periods so that ozone can be considered as a tracer of planetary waves. At the equator, a dominant semiannual oscillation and an 11 year solar cycle are found for nighttime ozone in the upper mesosphere. The SAO in ozone and temperature show a strong correlation indicating a dynamical control of the ozone SAO in the upper mesosphere. The SAO in the equatorial nighttime values of ozone and temperature is due to a semiannual modulation of vertical advection by the diurnal tide.

To explore the spatial network structure characteristics and driving effects of carbon emission intensity in China's construction industry, the investigation combined the modified gravity model and social network analysis method to deeply analyze the spatially associated network structure characteristics and driving effects of carbon emission intensity in China's construction industry, based on the measurement of carbon emission data of China's construction industry from 2006 to 2017. The results show that the regional differences of carbon emission of construction industry are significant, and the carbon emission intensity of construction industry show a fluctuation trend. The overall network of carbon emission intensity shows an obvious “core-edge” state, the hierarchical network structure is gradually broken. Economically developed provinces generally play a leading role in the network, and play an intermediary role to guide other provinces to develop together with them. Among the network blocks, most of the blocks play the role of “brokers”. The block with the leading economic development has a strong influence on the other blocks. The increase of network density, the decrease of network hierarchy and network efficiency will reduce the construction carbon emission intensity.

Background: Essential hypertension is a major public health associated with increase pressure on the vascular walls and red blood cells (RBCs). In the present work, osmotic fragility (OF) of RBCs was reexamined in the means of its correlation with two risk factor; iron status and lipid profile. Experimental: OF, iron status parameters, and lipid profile components were measured in 60 patients and compared with the results of 30 controls. Results: The results showed a significant increase in all iron indices of hypertensive patients in comparing with healthy control group except TIBC, UIBC, and transferrin concentrations, which decrease in these patients in comparing with control group. Serum TGs, total cholesterol, VLDLc, and LDLc were increased while there is no significant in serum HDLc in patients to comparing with control group. There is no significant change in OF between patients and controls where p=0.173. The iron status parameters and lipid profile components were dependent on sex and smoking state. Hemoglobin and PCV were correlated significantly with total cholesterol and LDLc. Transferrin saturation showed a positive correlation with cholesterol, LDLc, and TGs, but negatively correlated with HDL_c. No significant correlation between all the measured parameters and OF in HT patients. There is a significant correlation between serum ferritin and systolic BP and between Hb and systolic BP. Conclusion: No significant effect on the OF in HT patients. HT patients have elevated level of iron parameters in comparing with controls. OD has no correlation with iron status parameters or with lipid profile components.

Currently the rapid growth of global economy has the competition among high-tech industries develop from regional to global, and the competition becomes fierce. In face of such fierce competition in global high-tech industry, it is realized that tangible assets could no longer be the differentiation basis, but intangible assets are regarded as the differentiation capital. An enterprise with sustainable innovation would dominate the world market and enhance the international competitiveness of domestic economy. When internal entrepreneurial culture is prevalent, an enterprise would naturally promote the innovation capability. Such a point of view also explains more popular of the innovative products or services of some enterprises than those with larger scales. Aiming at employees in high-tech industry in Guanxi Province, total 500 copies of questionnaire are randomly distributed, and 337 valid copies are retrieved, with the retrieval rate 67%. The research results reveal significantly positive correlations between 1.entrepreneurial culture and sustainable innovation capability, 2.sustainable innovation capability and patent, and 3.entrepreneurial culture and patent. According to the results, suggestions are proposed, expecting to explain how a high-tech business outperforms in the changeable digital era and acquires the sustainable innovation capability and patent to grasp the opportunity.

This article shows how to establish expansion formulas for calculating the mixed operations $(A^{\dag})^{\#}$, $(A^{\#})^{\dag}$, $((A^{\dag})^{\#})^{\dag}$, $((A^{\#})^{\dag})^{\#}$, $\ldots$ of generalized inverses, where $(\cdot)^{\dag}$ denotes the Moore--Penrose inverse of a matrix and $(\cdot)^{\#}$ denotes the group inverse of a square matrix. As applications of the formulas obtained, the author constructs and classifies some groups of matrix equalities involving the above mixed operations, and derives necessary and sufficient conditions for them to hold.

In order to meet the diversified rehabilitation needs of people, it is necessary to design a product for active rehabilitation of patients. Existing rehabilitation chairs use intelligent massage, which can cause problems such as large massage area, inability to local massage, large chair size, and inability to meet the continuous use of the damaged parts. In this paper, modular design method and multi-layer evaluation method are used to solve the problems related to rehabilitation chairs. The authors use the questionnaire survey method and the functional technology matrix method to determine the functional requirements of the rehabilitation chair, and then use the multilevel evaluation methods, including the AHP method, entropy weight method main and grey correlation analysis, to optimize the functional solutions of the rehabilitation chair, and finally obtain a chair for the rehabilitation of patients with upper and lower limb disorders. Problems such as generalisation of rehabilitation scope and non-durable use of components were solved, and the purpose of active exercise was achieved. This study verifies that the use of multilevel decision evaluation method can effectively improve the efficiency of programme decision-making, and provides theoretical and practical basis for the design of similar products.

Uterine fibroid (UF) is a tumour in some parts of the uterus, which introduces health challenges or death due to failed surgery among women globally. This study was designed to ascertain the involvement of micro-nutrients, inflammation, and antioxidant enzymes in the UF development to gain further insights and provide a strategy for managing the disease. One hundred ninety reproductive-aged women were recruited and classified equally into case and control subjects. The supernatant obtained from excised tissues from the fibroid and the normal samples from the adjacent myometrium were assessed for the selected biochemical parameters with standard methods. The levels of vitamin A and sodium between 26-35 years; vitamins D, E, zinc, and selenium between 46-55 years; and vitamin E at 56 years and above significantly decreased (p<0.05). Interleukin-2 (IL-2) level significantly increased (P < 0.05) among the case between 36-45 years. An increase in the activity of glutathione-s-transferase and the reduction in glutathione peroxidase activity and vitamin A level in the uterus between 26-45 years were the most pronounced significant findings (p<0.05) recorded. Prolonged vitamin A deficiency coupled with excess sodium salts facilitating inflammation induced by IL-2 are critical factors for UF development.

Computation of Discrete Fourier Transform (DFT) is a challenging task. Especially, on computational machines/embedded systems where resources are limited. The importance of Fourier Transform (FT) cannot be denied in the field of signal processing. This paper proposes a technique that can compute Discrete Fourier Transforms for a matrice or vector with the help of matrix multiplication. Moreover, this paper discusses the trivial methods used for computation of DFT along with methods based on matrix multiplication used to compute discrete Fourier Transform in addition to the shortcomings. The proposed method can help in the calculation of a Discrete Fourier Transformation matrix by truncation of values from the proposed generic method which can help in computing DFT of varying lengths of vectors. On legacy computing machines and programming environments, having support for matrix multiplication, the proposed methodology can be implemented.

Tenascin C (TNC) is an element of the extracellular matrix (ECM) of various tissues, including the skin, and is involved in modulating ECM integrity and cell physiology. Although skin aging is apparently associated with changes in the ECM, little is known about the role of TNC in skin aging. Here we found that Tnc mRNA level was significantly reduced in the skin tissues of aged mice compared with young mice, consistent with reduced TNC protein expression in aged human skin. TNC-large (TNC-L; 330-kDa) and -small (TNC-S; 240-kDa) polypeptides were observed in conditional media from primary dermal fibroblasts. Both recombinant TNC polypeptides, corresponding to TNC-L and TNC-S, increased the expression of type I collagen and reduced the expression of matrix metalloproteinase-1 in fibroblasts. Treatment of fibroblasts with a recombinant TNC polypeptide, corresponding to TNC-L, induced phosphorylation of SMAD2 and SMAD3. TNC increased the level of TGF-β1 mRNA and upregulated the expression of type I collagen by activating the TGF-β signaling pathway. In addition, TNC also promoted the expression of type I collagen in fibroblasts embedded in a three-dimensional collagen matrix. Our findings suggest that TNC contributes to the integrity of ECM in young skin and to prevention of skin aging.

The use of biodegradable materials has a growing field of application due to environmental concerns, however, scientific research on incremental forming using biomaterials is scarce. Thus, this study focuses on the single point incremental forming (SPIF) process applied to a composite sheet that combines a biodegradable thermoplastic matrix (Solanyl) reinforced with natural fibres (flax). The influence of the process parameters on the final geometry is determined, evaluating the effect of the following factors: step depth, wall angle and temperature reached during the process. Additionally, a heated aqueous medium is incorporated which facilitates the formability of the composite sheets. This method is especially useful for materials that have poor formability at room temperature. The benefits of using controlled heat include the reduction of formation forces applied to the plate, improved accuracy due to the reduction of elastic recovery, and the manipulation of the samples remarkably close to the glass transition temperatures. Through this experimental study with the variables analysed, a maximum shaping depth of 310 mm is obtained. These results confirm that the single point shaping used with bioplastic materials is possible and has positive outcomes for incremental forming.

One of the main challenges for autonomous learning in virtual environments is finding the right material that fits students’ needs and supports their learning process. Personalized recommender systems partially solve this problem by suggesting online educational resources to students based on their preferences. However, in educational environments (which need a proper characterization of both users and educational resources), most existing recommendation algorithms either fail to include all the available information or use hybrid processes that do not exploit possible relationships between users and item features. This article presents a personalized recommender system for educational resources aimed at combining user and item information into a single mathematical model based on matrix factorization. As a result, estimated latent factors can provide insight into possible interactions between users and item features, improving the quality of the information retrieval process. We validated the proposed model on a real dataset that contains the ratings assigned by students from Universidad Nacional de Colombia and Universidade Feevale to educational resources in the Colombian Federation of Learning Object Repositories (FROAC in Spanish). User characterization included learning style and educational level, whereas item characterization (obtained from the objects’ metadata), included interactivity level, aggregation level and type, and resource format. These results, compared to those obtained when not all the available information is included, show that our method can improve the recommendation process.

Heparanase (HPSE) has been defined as a multitasking protein that exhibits a peculiar enzymatic activity towards HS chains but which simultaneously performs other non-enzymatic functions. Through its enzymatic activity, HPSE catalyzes the cutting of the side chains of heparan sulfate (HS) proteoglycans, thus contributing to the remodeling of the extracellular matrix and of the basal membranes. Furthermore, thanks to this activity, HPSE also promotes the release and diffusion of various HS-linked molecules as growth factors, cytokines and enzymes. In addition to being an enzyme HPSE has been shown to possess the ability to trigger different signaling pathways by interacting with transmembrane proteins. In normal tissue and in physiological conditions, HPSE exhibits only low levels of expression restricted only to keratinocytes, trophoblast, platelets and mast cells and leukocytes. On the contrary, in pathological conditions, such as in tumor progression and metastasis, inflammation and fibrosis, it is overexpressed. With this brief review, we intend to provide an update on current knowledge about the different role of HPSE protein exerted by its enzymatic and not-enzymatic activity.

Heparanase (HPSE) has been defined as a multitasking protein that exhibits a peculiar enzymatic activity towards HS chains but which simultaneously performs other non-enzymatic functions. Through its enzymatic activity, HPSE catalyzes the cutting of the side chains of heparan sulfate (HS) proteoglycans, thus contributing to the remodeling of the extracellular matrix and of the basal membranes. Furthermore, thanks to this activity, HPSE also promotes the release and diffusion of various HS-linked molecules as growth factors, cytokines and enzymes. In addition to being an enzyme HPSE has been shown to possess the ability to trigger different signaling pathways by interacting with transmembrane proteins. In normal tissue and in physiological conditions, HPSE exhibits only low levels of expression restricted only to keratinocytes, trophoblast, platelets and mast cells and leukocytes. On the contrary, in pathological conditions, such as in tumor progression and metastasis, inflammation and fibrosis, it is overexpressed. With this brief review, we intend to provide an update on current knowledge about the different role of HPSE protein exerted by its enzymatic and not-enzymatic activity.

The dynamic landscape of AI adoption and its impact on employment in Malaysia demands a multifaceted approach to navigate the challenges and harness the opportunities presented. While the government's commitment to fostering AI adoption through initiatives like the National AI Framework and the Malaysia Digital Economy Blueprint is commendable, it is imperative to address concerns regarding job displacement and ensure inclusive growth. This study identifies the pressing research problem of workforce readiness for the AI-driven future, emphasizing the need to explore strategies for reskilling and upskilling affected workers. By employing critical lenses such as Marxist, feminist, and postcolonial perspectives, scholars highlight the power dynamics and societal implications inherent in AI deployment, guiding the development of policies and interventions that prioritize workers' interests and address social inequalities. Moving forward, a comprehensive approach combining policy interventions, educational reforms, and inclusive strategies is essential to maximize the benefits of AI adoption while mitigating its potential risks. Longitudinal studies, interdisciplinary research, and comparative analyses will further advance our understanding and inform evidence-based policymaking in this evolving field. Ultimately, by prioritizing workforce preparedness, social equity, and sustainable development, Malaysia can position itself as a leader in the AI-driven global economy, fostering a resilient, inclusive, and prosperous society for all.

Background: Many clinical conditions are affected by meteorological factors and climate changes. Psychiatric disorders are large contributors to the global disease burden, but the literature on the impact of climate changes on mental health is limited. The aim of this study is to investigate the correlation between rising temperatures and admissions for acute exacerbations of psychiatric disorders. Methods: Data were collected for summer months of years 2013 to 2022. Mean monthly tempera-tures were obtained from the meteorological station of the Department of Physics of the Universi-ty of Turin. Data on patients admitted to the acute psychiatric unit of San Luigi Gonzaga Univer-sity Hospital (Turin, Italy) were extracted from the hospital registry. Linear regression analyses were used to investigate the correlation between temperature and number of admissions. Results: A total of 1600 admissions to our psychiatric ward were recorded. Mean monthly temper-ature and monthly number of admissions were directly correlated (P = 0.0020). The correlation between temperature and admissions was significant for the subgroup of admissions due to Bipo-lar Disorders (BD) (P=0.0011), but not for Schizophrenia (P=0.6070) (SCZ) or Major Depressive Disorder (MDD) (P=0.0588). Conclusions: These results confirm the impact of meteorological factors on mental disorders, and in particular on the course of BD. This provides new insights into etiopathological mechanisms and can contribute to improved follow up and relapse prevention.

The outbreak of the COVID-19 pandemic has raised concerns about potential environmental factors that could influence the spread and severity of the SARS-CoV-2 virus. Atmospheric pollution, particularly particulate matter (PM), has been suggested as a contributing factor to viral infections and respiratory complications. This two-year observational study aimed to investigate the relation between air pollution and the spread of COVID-19, focusing on PM2.5. Unlike previous studies limited to specific cities or countries, inevitable to use temporal data. Our research analyzed data from various states across the United States, considering both spatial and temporal correlation. The analysis considered the number and geographic distribution of COVID-19 cases along with daily PM2.5 exposure levels, accounting for monthly average PM2.5 exposure, from March 2020 to December 2021. The observed conflicting results of the temporal and spatial correlation present challenges for researchers in understanding the true nature of the relationship between PM2.5 air pollution and COVID-19 cases. The correlation between various factors, such as population density, PM2.5, temperature, and wind speed, and COVID-19 refers to an association or statistical relationship, not causation. Moreover, the intricate interplay of these variables makes it difficult to establish a clear cause-and-effect relationship.

The heat and matter transfer during glucose catabolism in living systems and their relation with entropy production are a challenging subject of the classical thermodynamics applied to biology. In this respect, an analogy between mechanics and thermodynamics has been performed via the definition of the entropy density acceleration expressed by the time derivative of the rate of entropy density and related to heat and matter transfer in minimum living systems. Cells are regarded as open thermodynamic systems that exchange heat and matter resulting from irreversible processes with the intercellular environment. Prigogine’s minimum energy dissipation principle is reformulated using the notion of entropy density acceleration applied to glucose catabolism. It is shown that, for out-of-equilibrium states, the calculated entropy density acceleration is finite and negative and approaches as a function of time a zero value at global thermodynamic equilibrium for heat and matter transfer independently of the cell type and the metabolic pathway. These results could be important for a deeper understanding of entropy generation and its correlation with heat transfer in cell biology with special regard to glucose catabolism representing the prototype of irreversible reactions and a crucial metabolic pathway in stem cells and cancer stem cells.

Magnetic resonance elastography (MRE) has revealed sexual dimorphism in brain stiffness in healthy individuals and multiple sclerosis (MS) patients. In the animal model of MS, experimental autoimmune encephalomyelitis (EAE), we showed previously that inflammation-induced brain softening was associated with alterations of the extracellular matrix (ECM). However, it remained unclear whether the brain ECM presents sex-specific properties that can be visualized by MRE. Therefore, we aimed here at quantifying sexual dimorphism in brain viscoelasticity in association with ECM changes in healthy and inflamed brains. Multifrequency MRE was applied to the midbrain of healthy and EAE mice of both sexes to quantitatively map regional stiffness. To define differences in brain ECM composition, gene expression of the key basement membrane components laminin (Lama4, Lama5), collagen (Col4a1, Col1a1) and fibronectin (Fn1) was investigated by RT-qPCR. We showed that the healthy male cortex expressed less Lama4, Lama5, Col4a1 but more Fn1 (all p < 0.05) than the healthy female cortex, which was associated with 9% softer properties (p = 0.044) in that region. At peak EAE, cortical softening was similar in both sexes compared to healthy tissue, with an 8% difference remaining between males and females during EAE (p < 0.001). Cortical Lama4, Lama5 and Col4a1 expression increased 2 to 3-fold in EAE in both sexes while Fn1 decreased only in males (all p < 0.05). No significant sex differences in stiffness were detected in other brain regions. In conclusion, sexual dimorphism in the ECM composition of cortical tissue in the mouse brain is reflected by in vivo stiffness measured with MRE and should be considered in future studies by sex-specific reference values.

In this paper we perform numerous numerical studies for the problem of low-rank matrix completion. We compare the Bayesian approaches and a recently introduced de-biased estimator which provides a useful way to build confidence intervals of interest. From a theoretical viewpoint, the de-biased estimator comes with a sharp minimax-optimal rate of estimation error whereas the Bayesian approach reaches this rate with an additional logarithmic factor. Our simulation studies show originally interesting results that the de-biased estimator is just as good as the Bayesian estimators. Moreover, Bayesian approaches are much more stable and can outperform the de-biased estimator in the case of small samples. However, we also find that the length of the confidence intervals revealed by the de-biased estimator for an entry is absolutely shorter than the length of the considered credible interval. These suggest further theoretical studies on the estimation error and the concentration for Bayesian methods as they are being quite limited up to present.

Ammonia-oxidizing microorganism communities are abundant and functionally efficacious in nitrification. However, ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) groups complicate this process in subtropical streams. This study investigates the abundance of ammonia-oxidizing communities south of the Dabie Mountains, China, using quantitative polymerase chain reaction (qPCR). Clone libraries were utilized to analyze the abundance and microbial structures of AOA and AOB in sediments. Such analysis may provide strong evidence reflecting the links within the environment. The results show that AOB had a lower abundance of copies of the ammonia-oxidizing gene (amoA) than AOA. Interestingly, the AOA and AOB community compositions were correlated with ecological characteristics. The dissolved oxygen (DO) and oxidation-reduction potential (ORP) had significant positive correlations, whereas the phosphorus within the structure had a negative correlation with the abundance of both groups. Our study shows that it might adopt some species related to Nitrosotalea clusters that can resist comparably higher pH (toward pH 6.5). Together, these results imply that the physiological adaptation of microbial guilds to environmental pressures in ammonia-oxidizing archaea might allow them to have a more substantial function of ammonia-oxidizing communities in natural habitats.

The level of development of the innovation factor plays a crucial role in supporting the high-quality development of China's economy. To advance the development of regional innovation factor allocation efficiency along the Belt and Road. This article introduces the super-efficiency SBM-DEA-Malmquist model for the static and dynamic analysis of innovation factor allocation efficiency in 17 provinces along the Belt and Road from 2012 to 2021. The Moran index model analyzes the spatial correlation. The results show that: (1) The overall innovation factor allocation efficiency along the Belt and Road is not high, and there are obvious differences among different regions. The eastern region is the highest compared to other regions. (2) According to the efficiency decomposition results, pure technical efficiency is the main reason for the low innovation factor allocation efficiency. (3) Through the Malmquist index and decomposition index, it is found that pure technical efficiency and scale efficiency are key factors in improving technical efficiency. (4) The analysis of spatial correlation reveals a strong spatial agglomeration feature among the provinces along the Belt and Road. The innovation factor allocation efficiency is mainly manifested in the L-L type. Finally, according to the analysis results, suggestions and policies are put forward to improve the innovation factor allocation efficiency in the regions along the Belt and Road.

Beginning in December 2019, a novel coronavirus known as SARS-CoV-2 has caused an international outbreak of respiratory illness termed COVID-19. This disease may cause mild to moderate respiratory illness. However, older individuals and those with underlying medical conditions like diabetes, cancer, and cardiovascular disease are more likely to develop serious illnesses (progressive pneumonia, multi-organ failure, and even death) (1). The main target for antiviral therapy for COVID-19 is the 3CL protease (3CLpro, Main protease, Mpro, Nsp5). The 3CL protease plays an integral role in viral replication and is often known as the “Achilles heel” of the SARS-CoV-2 virus (2). Thus, NLC Pharma utilized a unique and novel technology termed Quantum Core Technology (QCT) to design a mechanism-based potent inhibitor against the SARS-Cov-2 3CL protease. 3CL Pharma has designed an oral anti-viral for COVID-19 called Tollovir. Biochemical assays have revealed that 40uM of Tollovir in PBS can achieve 90% maximum inhibition of 3CL protease. Furthermore, the oral anti-viral has completed clinical trial phase 2b/3. Tollovir has proven to be safe and significantly decreases mortality rates of hospitalized patients with COVID-19 infection.

Abstract Introduction PCa is one of the cancers that exhibits the widest disparity gaps. Geographical place of residence has been shown to be associated with healthcare access/utilization and PCa outcomes. Geographical Information Systems (GIS) are widely being utilized for PCa disparities research, however, inconsistencies in their application exist. This systematic review will summarize GIS application within PCa disparities research, highlight gaps in the literature and propose alternative approaches. Methods This paper followed the methods of the Cochrane Collaboration and the criteria set of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Articles published in peer-reviewed journals were searched through the PubMed, Embase, and Web of Science databases till December 2022. The main inclusion criteria were employing a GIS approach and examining a relationship between geographical components and PCa disparities. The main exclusion criteria were studies conducted outside the US and those that were not published in English. Results A total of 25 articles were included, 23 focused on PCa measures as outcomes: incidence, survival, and mortality while only two examined PCa management. GIS application in PCa disparities research was grouped into three main categories: mapping, processing, and analysis. GIS mapping allowed for the visualization of quantitative, qualitative, and temporal trends of PCa factors. GIS processing was mainly used for geocoding and smoothing of PCa rates. GIS analysis mainly served to evaluate global spatial autocorrelation and distribution of PCa cases, while local cluster identification techniques were mainly employed to identify locations with poorer PCa outcomes, soliciting public health interventions. Discussion Varied GIS applications and methodologies have been used in researching PCa disparities. Multiple geographical scales were adopted leading to variation in associations and outcomes. Geocoding quality varied considerably leading to less robust findings. Limitations in cluster-detection approaches were identified especially when variations were captured using the Spatial Scan Statistic. GIS approaches utilized in other diseases might be applied within PCa disparities research for more accurate inferences. A novel approach for GIS research in PCa disparities could be focusing more on geospatial disparities in procedure utilization especially when it comes to PCa screening techniques. Conclusion This systematic review summarized and described the current state and trend of GIS application in PCa disparities research. Although GIS is of crucial importance when it comes to PCa disparities research, future studies should rely on more robust GIS techniques, carefully select the geographical scale studied, and partner with GIS scientists for more accurate inferences. Such interdisciplinary approaches have the potential to bridge the gaps between GIS and cancer prevention and control to further advance cancer equity.

A rare genetic disorder caused by col18.a1 mutations, inherited mostly in autosomal recessive and rarely in autosomal dominant pattern, giving rise to ocular abnormalities and other associated disorders, the condition is referred to as Knobloch syndrome. This paper overviews the anterior and posterior ocular symptoms in Knobloch patients, thus demonstrating the major findings in Knobloch cases including the mutational analysis which discusses the proteins involved and exon number on which mutations are detected. Animal modeling done by knocking out col18.a1 has also been discussed to determine the functions of this gene which have been identified based on anomalies found in knock-out mice.

The effects of post-treatment temperature-based methods on 1D single PLA filaments after FFF have been studied. This lets to decouple the variables related to the 3D structure (layer height, raster angle, infill density, and others) from the variables solely related to the material (molecular weight, molecular orientation, crystallinity, and others). PLA 1D filaments have been aged at 20, 39, 42, 51, 65, 75 and 80 ºC in a water-bath-inspired process in which the hydrolytic degradation of the PLA has been minimised for the ageing temperatures of interest. The evolution of the thermal and mechanical properties of the PLA filaments at different temperatures was recorded. Differential scanning calorimetry (DSC) was used to evaluate thermal and physical properties, in which the glass transition, enthalpic relaxation, crystallisation and melting reactions were analysed. Tensile tests were performed to evaluate the tensile strength and elastic modulus. The flow-induced molecular orientation, the degradation, the logistic fitting and the so-called summer effect –stabilisation of properties at higher temperatures– are discussed for assessing the safeness of accelerating ageing.

Fungal infections impact the lives of at least 12 million people every year, killing over 1.5 million. Wide-spread use of fungicides and prophylactic antifungal therapy have driven resistance in many serious fungal pathogens, and there is an urgent need to expand the current antifungal ar-senal. Recent research has focused on improving azoles, our most successful class of antifungals, by looking for synergistic interactions with secondary compounds. Synergists can co-operate with azoles by targeting steps in related pathways, or they may act on mechanisms related to re-sistance like active efflux or on totally disparate pathways or processes. A variety of sources of potential synergists have been explored, including pre-existing antimicrobials, pharmaceuticals approved for other uses, bioactive natural compounds and phytochemicals, and novel synthetic compounds. Synergy can successfully widen the antifungal spectrum, decrease inhibitory dosag-es, reduce toxicity, and prevent the development of resistance. This review highlights the diversity of mechanisms that have been exploited for the purposes of azole synergy and demonstrates that synergy remains a promising approach for meeting the urgent need for novel antifungal strate-gies.

Abstract:Global ship demolition is mostly concentrated in south Asian countries, namely Bangladesh, India, Pakistan and China, since 1990’s, having competitive advantage for their high natural tide, and low environmental and social costs. Due to high social and environmental externalities, stakeholders increase monitoring of the externalities and continue to prescribe improvement towards sustainability, which put pressures on profitability and competitiveness. As a consequence, also seen in the past, a leakage effect may emerge, leading to shift of this activity to a region, with relatively less monitored and less stricter on social and environmental impacts. Unfortunately, the leakage effect is never predicted in shipbreaking in order to understand the level of push compatible in the given socio-economic contexts. In this study, we have attempted to predict the future ship demolition landscape, applying machine learning technique to 34,531 in-service vessels worldwide, larger than 500 gross tonnage (GT), which is run against a learning model based on 3500 demolished vessels from 2014. This study shows that redistribution may occur among the top recycling nations: India may emerge out to be a dominant player in shipbreaking, surpassing Bangladesh by a margin of two-fold, while Pakistan and China are in decreasing trend. In addition, the leakage effect is observed, in that Vietnam is predicted to be the fourth largest ship demolition country, while China and Pakistan recede from the third and fourth place to 6th and 8th. Turkey is predicted to advance from fifth position to third position by vessel count but stays same in term of total GT dismantled. Although it is not clear if any leakage is to be observed in the near future, this study may be a model for future predictive analytics and help stakeholders take evidence-based business decisions.

In this study, a novel absorbable hemostatic agent was developed using carrageenan (CRG) as a natural polymer and cerium oxide nanoparticles (CeO2 NPs).  CRG-CeO2-0.5 and CRG-CeO2-1 composites were prepared by compositing CRG and CeO2 at a weight ratio of 200:1 and 100:1, respectively. Physio-chemical and structural properties of these compounds were studied and compared with pristine CRG. Upon incorporation of CeO2 nanoparticles into the CRG matrix, significant reductions in hydrogel degradation were observed. In addition, it was noted that CRG-CeO2 exhibited better antibacterial and hemostatic properties than CRG hydrogel without CeO2.The biocompatibility of the materials was tested using the NIH 3T3 cell line and all samples were found to be nontoxic. Particularly, CRG-CeO2-1 demonstrated superior hemostatic effects, biocompatibility, and a lower degradation rate since more CeO2 Nps were present in the CRG matrix. Therefore, CRG-CeO2-1 has the potential to be used as a hemostatic agent and wound dressing.

Abstract: The study focuses on how socio-economic and demographic indicators affect fertilization sustainability (excessive amount of fertilization). Principally we aim to examine the significance magnitude of the effects of three socio-demographic variables such as traditional way of fertilization, rental land farming, and farmers’ younger age on over-fertilization in Bangladesh and other developing countries. In 1960s, Bangladesh state authority launched a campaign ‘Grow more Food’ to feed huge numbers of population and thus the farmers are provided chemical fertilizers and pesticides at a subsidized low price. Farmers began to use huge amount of fertilizers for gaining high yields and continued it to present causing environmental woes a lot. We interview (face-to-face, focus group discussion, and phone interview) 210 Bangladesh farmers in 2016 by semi-structured questionnaire. Data has been analyzed using General Linear Model (GLM) in Univariate Analysis of Variance. The study found the effect of traditional way of fertilization on excessive amount of fertilization is strongly significant at 1% level. Apart from, rental land farming and farmers’ younger age have a significant influence on over- fertilization; though their significance level (5% and 10% respectively) is quasi-strong. Policy makers can be able to formulate fertilizer policy on the basis of these findings.

This study investigates the effect of altitude on the fatty acid composition of grass, yak milk, and yak ghee on the Qinghai-Tibet Plateau, aiming to understand how environmental factors influence the nutritional quality of these products. Samples were collected from four different altitudes and analyzed for fatty acid profiles using gas chromatography. The findings reveal significant differences in fatty acid profiles, with notably higher concentrations of lauric acid (C12:0) and myristic acid (C14:0) at altitude A2 compared to others (p＜ 0.001). Furthermore, the fatty acid composition in yak milk and ghee is influenced by the grass consumed and the metabolism of rumen microorganisms. The results indicate that yaks adapt their lipid biosynthesis to high-altitude conditions, as evidenced by a significant increase in stearic acid (C18:0) levels at higher altitudes, which subsequently affects the nutritional value of their milk and ghee. These insights are crucial for improving yak breeding and dairy production practices, ultimately enhancing food security and nutritional health for local communities residing in high-altitude areas. The study underscores the necessity for further research on optimizing these natural resources for better health outcomes.

The Castelo Intrusive Complex (CIC), located in the southern state of Espírito Santo, southeast-ern Brazil, is a pluton inserted in the context of post-collisional magmatism of the Araçuaí Orogeny, known as Supersuite G5, related to the extensional collapse during the Brasili-ano/Pan-African Orogeny. This work presents an integration of field, petrographic, lithogeo-chemical, and isotopic data, in addition to bringing new U-Pb ages for the CIC and a new geo-logical map. The CIC presents a great compositional variety, presenting rocks of monzogranitic, granodioritic, quartz-monzodioritic, and dioritic compositions that are inserted in the context of mixed magmas. The magma mixing process is generalized in the CIC through field, petro-graphic, lithogeochemical, and isotopic data, in addition to U-Pb data in the different units that attest to the cogeneticity between them. The delamination process promoted the fusion of the asthenospheric mantle. It promoted the anatexis of different portions of the crust, evident through the values of εHf and TDM ages, where later magmatic mechanisms of physical disper-sion (mingling) and chemical diffusion (mixing) favored hybridization and promoted the com-positional diversity of the CIC.

Abstract Sickle cell anaemia (SCD) is a life-threatening haematological disorder which is predominant in sub-Saharan Africa and is triggered by a genetic mutation of the β-chain haemoglobin gene resulting in the substitution of glutamic acid with valine. This mutation leads to the production of an abnormal haemoglobin molecule called haemoglobin S (HbS). When deoxygenated, haemoglobin S (HbS) polymerizes and results in a sickle-shaped red blood cell which is rigid and has a significantly shortened life span. Various reports have shown a strong link between oxidative stress, inflammation, the immune response, and the pathogenesis of sickle cell disease. The consequence of these processes lead to the development of vasculopathy (disease of the blood vessels) and several other complications. The role of the immune system, particularly the innate immune system, in the pathogenesis of SCD has become increasingly clear in recent years of research, However, little is known about the roles of the adaptive immune system in this disease. This review examines the interaction between the immune system, inflammation, oxidative stress, blood transfusion, and their effects on the pathogenesis of sickle cell anaemia

This paper reports aligned activities to promote energy and resource-efficient construction practice in Vietnam. First, the governance framework is introduced, including government decrees and technical standards. Then, a laboratory with building physics measurement technology is designed and partly set up at the local partner Vietnam Institute for Building Materials (VIBM), which can be used to determine the essential characteristic values required for the implementation of energy standards. The basis for the prioritization of the characteristic values are the requirements of the National technical regulation on energy efficient buildings of Vietnam – QCVN09:2017/BXD. Furthermore, basic characteristic values from international standards are described, which can also be used for calculations to optimize the energy consumption of buildings. In order to be able to carry out transient hygrothermal computer simulations, special characteristic values were also included. These are particularly useful for the research and development of new building materials and the evaluation of entire buildings in terms of thermal and moisture protection In order to communicate the material properties to the market and enable informed decision making by the stakeholders, a labeling system has been developed. Thereby, the practical means for implementing governance instruments are provided, and the related technical applications are supported.

This study analyzed eye examination data from the 5th Korea National Health and Nutrition Examination Survey to investigate the relationship between cataract prevalence and sunlight exposure among Koreans. Out of 952 individuals from 192 districts surveyed from January to December, statistical analyses using SPSS version 26, including chi-square tests and logistic regression, were conducted. Results: Results showed that the incidence of cataracts was higher in people exposed to sunlight for more than 5 hours. Regarding gender, the incidence of cataracts was higher in female in the 2-5 hours of sunlight exposure group, and in male in the group exposed to sunlight for more than 5 hours. Age significantly increased cataracts after age 45 in both groups. Additionally, the prevalence was higher among college graduates in the 2 to 5 groups, and among elementary school graduates in the more than 5 hours usage group. In urban areas, the cataract prevalence rate was higher in the 2-5-hour usage group, and in rural areas, the cataract prevalence was higher in the more than 5-hour usage group. In conclusion, prolonged sunlight exposure, particularly over 5 hours, correlated with higher cataract prevalence among Koreans, with various demographic factors influencing incidence rates.

The study of angular correlations of heavy-flavor particles in hadronic collisions can provide crucial insight into the heavy-quark production, showering and hadronization processes. The comparison with model predictions allows us to discriminate among different approaches for heavy-quark production and hadronization, as well as different treatments of the underlying event employed by the models to reproduce correlation observables. In ultra-relativistic heavy-ion collisions, where a deconfined state of matter, the quark-gluon plasma (QGP), is created, heavy-flavor correlations can shed light on the modification of the heavy-quark fragmentation due to interaction of charm and beauty quarks with the QGP constituents, as well as characterize their energy loss processes while traversing the medium. Insight into possible emergence of collective-like mechanisms in smaller systems, resembling those observed in heavy-ion collisions, can also be obtained by performing correlation studies in high-multiplicity proton-proton and proton-nucleus collisions. In this review, the most recent and relevant measurements of heavy-flavor correlations performed in all collision systems at the LHC and RHIC will be presented, and the new understandings that they provide will be discussed.

IgA vasculitis is a hypersensitivity vasculitis, which is usually self-limiting. Renal involvement is the most damaging long-term complication of IgA vasculitis, happening in 20% - 100% of cases. Some factors have been reported to be associated with renal involvement in IgA vasculitis; however, no biomarker has been proved as a risk factor for renal involvement and its severity yet. We followed 48 patients with a confirmed diagnosis of IgA vasculitis for six months. We checked these patients for renal involvement by microscopic urine examination. We checked aPL antibodies in all patients on admission and 12 weeks later. Urinalysis showed renal involvement in 14 of 48 patients with IgA vasculitis (29.16%). Antiphospholipid antibodies were positive in 9 patients with IgA vasculitis and renal involvement (9 out of 14, 64.28%), while they were positive in only six patients with IgA vasculitis without renal involvement (6 out of 34, 17.64%), showing a moderate correlation between positive aLP and renal involvement in patients with IgA vasculitis, with a kappa index of 0.457. Serum aPL antibodies, as a tool to predict renal involvement in IgA vasculitis, show a sensitivity of 64.3%, a specificity of 82.4%, PPV of 60.0%, and NPV of 84.8%, demonstrating that a positive serum aPL antibody can be used to positively predict the renal involvement, while a negative result is not strong enough to rule out future renal involvement.

Optical properties of the cornea are responsible for correct vision, ultrastructure allows optical transparency and biomechanical properties governs the shape, elasticity or stiffness of the cor-nea affecting ocular integrity and intraocular pressure. Therefore, optical aberrations, corneal transparency, structure and biomechanics play a fundamental role in the optical quality of hu-man vision, ocular health and refractive surgery outcomes. However, the convergence of those properties is not yet reported at macroscopic scale within the hierarchical structure of the cornea. This work explores the relationships between biomechanics, structure and optical properties (corneal aberrations and optical density) at macrostructural level of the cornea through dual Placido-Scheimpflug imaging and air-puff tonometry systems in a healthy young adult popula-tion. Results showed convergence between optical transparency, corneal macrostructure and biomechanics.

Brain-Computer Interfaces (BCIs) are essential in advancing medical diagnosis and treatment by providing non-invasive tools to assess neurological states. Among these, Motor Imagery (MI), where patients mentally simulate motor tasks without physical movement, has proven to be an effective paradigm for diagnosing and monitoring neurological conditions. Electroencephalography (EEG) is widely used for MI data collection due to its high temporal resolution, cost-effectiveness, and portability. However, EEG signals can be noisy from a number of sources, including physiological artifacts and electromagnetic interference. They can also vary from person to person, which makes it harder to extract features and understand the signals. Additionally, this variability, influenced by genetic and cognitive factors, presents challenges for developing subject-independent solutions. To address these limitations, this paper presents a Multimodal and Explainable Deep Learning (MEDL) approach for MI-EEG classification and physiological interpretability. Our approach involves: i) evaluating different deep learning (DL) models for subject-dependent MI-EEG discrimination; ii) employing Class Activation Mapping (CAM) to visualize relevant MI-EEG features; and iii) utilizing a Questionnaire-MI Performance Canonical Correlation Analysis (QMIP-CCA) to provide multidomain interpretability. On the GIGAScience MI dataset, experiments show that shallow neural networks are good at classifying MI-EEG data, while the CAM-based method finds spatio-frequency patterns. Moreover, the QMIP-CCA framework successfully correlates physiological data with MI-EEG performance, offering an enhanced, interpretable solution for BCIs.

Introduction: intraocular pressure (IOP) measurement is an essential part glaucoma’s diagnosis and follow-up. Goldmann applanation tonometry (GAT) is the gold standard for IOP measurement but it’s affected by many factors like central corneal thickness (CCT). Racial differences in CCT are reported but the Syrian population was never studied. Research design and methods: 57 subjects with 114 eyes visiting Damascus hospital were examined and 100 eyes were included. IOP was measured using GAT and CCT was measured using OCULUS Pentacam AXL Corneal Topography, demographic data and history of ocular surgery, systemic co-morbidities and history of medications were collected. IOP values were corrected for CCT. Results: 56% were males, the mean age was 48.1. 24% of subjects had hypertension. Males had higher CCT with 557.23± 25.33 compared with 531.34 ± 41.88 for females. There was a moderately positive correlation between CCT and IOP (r=0.232, p-0.02), CCT and IOP values were linearly correlated (ANOVA, p=0.02). Conclusions: This study showed that the correlation between CCT and IOP is present in the Syrian population. Males had a slightly thicker corneas than females and CCT didn’t significantly change with age.

To accurately and non-destructively monitor the growth of spring wheat in the Hetao Irrigation Area, UAV remote sensing was employed during various fertility stages. Digital image indices from diverse fertilization treatments were calculated and compared with physiological indices to identify the most sensitive digital image indices corresponding to these indices. The study underscored the critical importance of the flowering stage in the growth of spring wheat, thus highlighting the necessity of focusing on this stage. This finding reiterated that the flowering stage was pivotal for spring wheat development in the Hetao Irrigation Area. Several digital image indices, such as GLA, R, G, INT, g, GRVI, MGRVI, RGBVI, EXG, and GRRI, exhibited a high frequency of significant correlations with physiological indices during the four primary reproductive stages of wheat. Consequently, these sensitive digital image indices during the flowering stage can more effectively characterize the physiological indices of spring wheat.

The Spearman rank correlation coefficient is a non-parametric (distribution-free) rank statistic proposed by Charles Spearman as a measure of the strength of the relationship between two variables. It is a measure of a monotonic relationship that is used when the distribution of the data makes Pearson's correlation coefficient undesirable or misleading. The Spearman coefficient is not a measure of the linear relationship between two variables. It assesses how well an arbitrary monotonic function can describe the relationship between two variables, without making any assumptions about the frequency distribution of the variables. Unlike Pearson's product-moment (linear) correlation coefficient, it does not require the assumption that the relationship between variables is linear, nor does it require that the variables be measured on interval scales; it can be applied to variables measured at the ordinal level. The purpose of this study is to compare the values of Pearson's product-moment correlation coefficient (treating the data in a quantitative way) and Spearman's rank correlation coefficient (treating the same data in a somewhat "qualitative" way) and their statistical significance for six Pinus sylvestris L. traits (original – for Pearson's coefficient and ranked – for Spearman's coefficient) estimated from all observations, object means (for trees) and medians. The results show that the linear and rank correlation coefficients are consistent (as to direction and strength). In cases of divergence in the direction of correlation, the correlation coefficients were not statistically significant, which does not imply consistency in decision-making. Estimation of correlation coefficients based on medians is robust to outlier observations and factors that linear correlation is then very similar to rank correlation.

In our previous work, we demonstrated the potential of the amphiphilic cyclic peptide [W4R4] as a promising antimicrobial agent. The extensive data accumulated on the antimicrobial activity of this peptide and its homologs presented an opportunity to unravel the molecular mechanisms governing their action and establish crucial structure-activity relationships (SAR). To achieve this, we employed a comprehensive approach involving peptide synthesis, in vitro biological testing, and molecular modeling to systematically analyze the SAR of a series of cyclic peptides derived from the [W4R4] scaffold. Minimal modifications were introduced to the original peptide by incorporating either one aromatic hydrophobic residue (W) or one polar positively charged residue (R) while maintaining the sequential W/R arrangement. Additionally, we introduced an "intermediate" substitution by incorporating 2,5-diketopiperazine (DKP), possessing both aromatic and polar properties, into the macrocycle [W4R4] between the W and R residues. Notably, this study marked the first synthesis and evaluation of the [W4R4(DKP)] peptide. Structural, dynamic, hydrophobic, and membrane-binding properties of four cyclic peptides ([W4R4], [W5R4], [W4R5], [W4R4(DKP)]) were explored using molecular dynamics simulations within a DOPC/DOPG lipid bilayer that mimics the bacterial membrane. The results obtained revealed distinct SAR profiles for all peptides, enabling the establishment of correlations between their antimicrobial activity and structural/dynamic parameters. These parameters included the degree of conformational plasticity, the depth of immersion into the bi-layer, and the population of the membrane binding mode characterized by the embedding of the hydrophobic peptide pattern into the acyl chain region of lipids. In particular, the peptide [W4R5] exhibited an optimal "activity/binding to the bacterial membrane" pattern. This work highlights the significance of our multidisciplinary approach in efficiently deciphering finely regulated SAR profiles for a series of homologous peptides with diverse activities. Furthermore, this research provides a solid foundation for the rational design of novel antimicrobial peptides.

To improve the accuracy of short-term multi-energy load prediction models for integrated energy systems, the historical development law of the multi-energy loads must be considered. Moreover, understanding the complex coupling correlation of the different loads in the multi-energy systems and accounting for other load-influencing factors, such as weather, may further improve the forecasting performance of such models. In this study, a two-stage fuzzy optimization method is proposed for the feature selection and identification of the multi-energy loads. To enrich the information content of the prediction input feature, we introduced a copula correlation feature analysis in the proposed framework, which extracts the complex dynamic coupling correlation of multi-energy loads and applies Akaike information criterion (AIC) to evaluate the adaptability of the different copula models presented. Furthermore, we combined a NARX neural network with Bayesian optimization and an extreme learning machine model optimized using a genetic algorithm to effectively improve the feature fusion performances of the proposed multi-energy load prediction model. The effectiveness of the proposed short-term prediction model was confirmed by the experimental results obtained using the multi-energy load time-series data of an actual integrated energy system.

Background: Frailty assessment allows the identification of patients at risk of death, and it is a challenge in both emergency departments and support wards. The aim here was to study the ability of the Frail-VIG Index (FI-VIG) in order to discriminate frailty groups of older adults and garner its correlation with mortality in an emergency department short-stay unit (2) Methods: Our observational, single-center, prospective study consecutively included patients over 65-years-old admitted to the unit between March 1, 2021, and April 30, 2021. (3) Results: A total of 302 patients were included (56% women), with a mean age of 83 ± 8 years, and 39.1% of them had a functional disability whilst 16.5% of them had dementia. A total of 174 patients (58%) met the frailty criteria (FI-VIG ≥0.2): 111 (63.8%) had mild frailty (FI-VIG 0.2 - 0.36), 52 (29.9%) had moderate frailty (FI-VIG 0.36 - 0.55), and 11 (6.3%) had advanced frailty (FI-VIG >0.55). Mortality at 30 days, 6 months, and 1 year was analyzed: no frailty was 6.3%, 10.8%, and 12.5%, respectively; mild frailty was 10.8%, 22.5%, and 22.5%, respectively; moderate frailty was 25%, 34.6%, and 42.3%, respectively; and advanced frailty was 36.4%, 54.5%, and 3.6%, respectively. This shows the significant differences between the groups (1-year mortality p<0.001). Mild frailty vs. non-frail HR was 2.47 (95%CI 1.12 - 5.46), moderate frailty vs. non-frail HR was 6.93 (95%CI 3.16 - 15.23), and advanced frailty vs. non-frail HR was 11.29 (95%CI 3.54 - 36.03). The mean test time was 7 minutes. (4) Conclusions: There was a strong correlation between frailty degree and mortality at 1, 6, and 12 months. FI-VIG Index is a fast and easy-to-use tool in this setting, and its routine implementation in SSUs could enable early risk stratification in order to detect vulnerable patients with specific needs.

Understanding the effect of staking sequences and identifying the damage occurring within a structure using a structural health monitoring system are the keys to an efficient design of composite-based parts. In this research, a combination of digital image correlation (DIC) and acoustic emission (AE) is used to locate and classify the type of damage depending on the stacking sequence of the laminate during flexural loading. A comparison of the strain field results for unidirectional, cross-ply, and quasi-isotropic laminates was made in a first attempt to discuss their global behavior and to correlate the different damage patterns with the possible failure mechanisms. The damage was then addressed using a comprehensive interpretation of the acoustic emission signatures using the K-means classification of the acoustic events. The development of each damage mechanism was correlated to the applied load and expressed as a function of the loading rate to highlight the effect of the stacking sequence. Finally, the results of DIC and AE were combined to improve the reliability of the damage investigation without limiting the failure mechanism to matrix cracking, interfacial failure, and fiber breakage, as expected by the unsupervised event clustering.

(1) Background: Recent studies provide some evidence for the contribution of antibody-mediated autoimmune mechanisms to the nature of fibromyalgia (FM) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Much attention was paid to the autoantibodies (AAb) targeting G protein-coupled receptors as natural components of the immune system. However, natural AAb network is much more extensive, and has not been previously investigated in these disorders; (2) Methods: The enzyme immunoassays ELI-Viscero-Test and ELI-Neuro-Test were used to determine changes in serum content of a 33 natural AAb to neural, organ-specific and non-tissue-specific autoantigens a) in 11 FM patients with comorbid ME/CFS; b) in 11 ME/CFS patients without FM; c) in 11 healthy controls. Individual autoantibody profiles and their correlation with some clinical symptoms were analyzed. (3) Results: both patients with ME/CFS and ME/CFS+FM were characterized by more frequent and pronounced deviations in the immunoreactivity to GABA-receptors than healthy controls. Although the level of other natural AAb did not differ between study groups, AAb correlation signatures were changing in patients compared to healthy controls. Both in patients and healthy controls the level of natural AAb to various neural and tissue-specific antigens correlated with the severity of fatigue, bodily pain, depression, anxiety, physical and mental-health related quality of life. Notably, that widely different correlation patterns were observed between study groups. (4) Conclusions: Findings from this pilot study provide some evidence that the homeostasis of autoimmune relationships, which are possibly a physiological part of our immune system, may break down in FM and ME/CFS. The correlation of disease-induced perturbations in individual AAb profiles with some clinical symptoms may arise from the immune system's ability to reflect qualitative and quantitative changes in antigenic composition of the body.

In this paper, industrial structure distortion, two-way FDI and carbon emission intensity are brought into a unified research framework, and based on China's panel data from 2011 to 2020, empirical tests are conducted employing Exploratory Spatial Data Analysis (ESDA), spatial econometric model and intermediary effect test. The results show the following. Firstly, China's industrial structure distortion index shows a downward trend. The industrial structure distortion index is the highest in the west, followed by the middle, and the lowest in the East. Secondly, the relationship between carbon emission intensity and economic development shows a "decoupling" effect and keeps decreasing year by year. The spatial disparity is remarkable, showing the pattern of "the east leading, the middle catching up and the west lagging ". At the provincial level, except in Xinjiang province, the carbon emission intensity of other provinces showed different degrees of decline. In terms of spatial distribution, the polarization characteristics of carbon emission intensity are significant, and the traditional spatial distribution pattern has been broken. Thirdly, there is a positive spatial correlation between China's industrial structure distortion, two-way FDI and carbon emission intensity. The distortion of industrial structure will not only lead to the increase of local carbon emission intensity but also produce reverse spillover to adjacent areas. IFDI and OFDI provide a strong driving force for the decline of carbon emission intensity. IFDI promotes the decline of carbon emission intensity in adjacent areas, while OFDI will increase the carbon emission intensity in surrounding areas. The interaction of IFDI and OFDI can significantly reduce the carbon emission intensity of local and adjacent areas. Fourthly, the results of intermediary effect analysis show that two-way FDI is the two channels of industrial structure distortion affecting carbon emission intensity. Industrial structure distortion can affect the transmission mechanism of carbon emission intensity by affecting two-way FDI.

Background: Takayasu Arteritis (TAK) increases vascular stiffness and arterial resistance. Hypertension and atherosclerosis lead to similar changes. We investigated possible differences in cardiovascular remodeling between these diseases and whether the differences are correlated with immune cell expression. Methods: Patients with active TAK arteritis were compared with age- and sex-matched hypertensive and atherosclerotic patients. In a subpopulation of TAK patients, Treg/Th17 cells were measured before (T0) and after 18 months (T18) of infliximab treatment. Echocardiogram, supraaortic Doppler ultrasound, and lymphocytogram were performed in all patients. Histological and immunohistochemical evaluation of the vessel wall was performed to compare the in vivo results. Results: TAK patients have increased aortic valve dysfunction and diastolic dysfunction. These data have been associated with uric acid levels. A significant increase in aortic stiffness was also noted and associated with peripheral T lymphocyte levels. CD3+CD4+ cell infiltrates were detected in the vessel wall samples of these patients. They had a lower mean percentage of Tregs at T0 than controls, but levels increased significantly at T18. Opposite results were found in Th17 cells. Finally, TAK patients were found to have an increased risk of atherosclerotic cardiovascular disease (ASCVD). Conclusion: Our data suggest that different pathogenic mechanisms of vessel damage, including atherosclerosis, underlie TAK patients compared with control subjects. The increased risk of ASCVD in TAK patients correlates directly with the degree of inflammatory cell infiltration in the vessel wall. Infliximab restores the normal frequency of Tregs/Th17 in TAK patients and allows a possible reduction of steroids and immunosuppressants.

The study of the brain networks using analysis of electroencephalography (EEG) data based on statistical dependencies (functional connectivity) and mathematical graph theory concepts is common in neuroscience and cognitive sciences for examinations of patient and healthy individuals. The Consciousness Fields according to Taheri theory and applications in the optimization of system under study have been investigated in various studies. In this study, we examine the results of working with Faradarmani Consciousness Field (FCF) in the brain of Faradarmangars. Faradarmangars are one of the necessary components in mind mediation of the function of Faradarmani Consciousness Fields according to Taheri. For this purpose, the functional and effective connectivity and the corresponding brain graphs of EEG from the brain of Faradarmangars is compared with that of non Faradarmangar groups during FCF connection. According to the results of the present study, the brain of the Faradarmangars shows significant decreased activity in delta (BA8), beta2 (BA4/6/8/9/10/11/32/44/47) and beta3 (in 34 of 52 BA) frequency bands mainly in frontal lobe and after that in parietal and temporal lobes in the comparison with the non Faradarmangars. Moreover, the functional and effective connectivity analysis in the frontal network shows dominant multiple decreased connectivity mainly in the case of beta3 frequency band in all parts of the frontal network. On the other hand, the graph theory analysis of the Faradarmangar brain shows an increase in the activity of the O2-T5-F4-F3-FP2-F8 areas and significant decrease in the characteristic path length and increases in global efficiency, clustering coefficient and transitivity. In conclusion, the unique higher graph function efficiency and the reduction in the brain activity and connectivity during the Faradarmani Consciousness Field mind mediation, shown the passive and detector like function of the human brain in this task.

Globally, the COVID-19 pandemic has brought the world to a standstill with the infected cases surpassing millions. The causative agent of COVID-19, the SARS-CoV-2 is a novel coronavirus that emerged from the wet animal market in Wuhan, China in early December 2019. Soon after, human-to-human transmission increased the rate of infection making the disease widespread with new hotspots emerging around the world.The epidemiological reports based on clinical characteristics including age, gender, symptoms (both severe and non-severe), and the conditions requiring intensive medical care, along with case fatality revealed that people with co-existing health conditions like diabetes, hypertension, cigarette smoking, and others with cardiovascular and kidney diseases were more susceptible to COVID-19 infection with poor prognosis in cases related to the severity of symptoms and requiring ICU, medical ventilators with a high fatality rate. Even people with immunosuppressed conditions like HIV and cancer, alongwith old age and pregnant women are vulnerable to COVID-19 infection and can cause severe health complications.It is extremely important to have a comprehensive idea of the underlying pathophysiology related to these health conditions which makes them more susceptible to contract SARS-CoV-2 infection in correlation with the development of severe symptoms. This review will provide an extensive viewpoint related to COVID-19 patients having coexisting health conditions together with the association between the prognosis of the disease and the pathogenesis of the SARS-CoV-2 infection, based on the current information available.

The semi-nonparametric (SNP) modeling of the return distribution has been proved to be a flexible and accurate methodology for portfolio risk management that allows two-step estimation of the dynamic conditional correlation (DCC) matrix. For this SNP-DCC model, we propose a stepwise procedure to compute pairwise conditional correlations under bivariate marginal SNP distributions, overcoming the curse of dimensionality. The procedure is compared to the assumption of Dynamic Equicorrelation (DECO), which is a parsimonious model when correlations among the assets are not significantly different but requires joint estimation of the multivariate SNP model. The risk assessment of both methodologies is tested for a portfolio on cryptocurrencies by implementing backtesting techniques and for different risk measures: Value-at-Risk, Expected Shortfall and Median Shortfall. The results support our proposal showing that the SNP-DCC model has better performance for a smaller confidence level than the SNP-DECO model, although both models perform similarly for higher confidence levels.

The present work shows a novel physical-mathematical model to estimate the average corrosion resistance index from the crystallographic texture in API 5L steels. The crystallographic texture of the studied steels was measured by means of the X-ray diffraction technique. The model, based on the symmetric spherical surface harmonics for a BCC structure, is capable of describing the anisotropy surface of anodic dissolution resistance of the crystal and establishing a straightforward relationship between crystallographic texture, surface roughness, and metal corrosion behavior. The predictions of the average corrosion resistance index made from the crystallographic texture were in good agreement with those obtained from potentiodynamic polarization curves for the investigated steels. This agreement validates the capacity of this model and opens the possibility of applying it as a novel criterion for the material selection and design stages in order to combat metal corrosion problems.

Thermoplastic fiberglass has been compression molded in the shape of thick panels with the nominal thickness of 10 mm and the size of 300x300 mm2. A simplified procedure has been adopted to speed up the lamination procedure, and making it adapt to the aim of recycling waste glass fiber fabrics and thermoplastics films. Low density polyethylene has been used as matrix to simplify the laboratory activities, but the same procedure can be extended to any other thermoplastic film, such as polyamide. The final thermoplastic composite shows unique properties in terms of repairability and improves its performances by increasing the number of repairing steps. For this aim, a repairability test has been designed in the bending configuration, and 3 consecutive cycles of bending/repairing/bending have been carried out. Static mechanical properties were, instead, low in comparison with traditional fiberglass, because of the choice of a polyethylene matrix. Bending tests have shown that the maximum strength is lower than 10 MPa and the elastic modulus less than 1 GPa. Nevertheless, the toughness of the thermoplastic composite was very high, and the samples continued to deform under bending for any displacement.

The extracellular matrix (ECM) provides structural support for tissues and regulatory signals for resident cells. ECM requires a careful balance between protein accumulation and degradation for homeostasis. Disruption of this balance can lead to pathological processes such as fibrosis in organs across the body. Post-translational crosslinking modifications to ECM proteins such as collagens alter ECM structure and function. Dysregulation of crosslinking enzymes as well as changes in crosslinking composition are prevalent in fibrosis. Because of the crucial roles that ECM crosslinking pathways play in disease, the enzymes that govern crosslinking events are being explored as therapeutic targets for fibrosis. Here we review in-depth the molecular mechanisms underlying ECM crosslinking, how ECM crosslinking contributes to fibrosis, and therapeutic strategies being explored to target ECM crosslinking in fibrosis to restore normal tissue structure and function.

Adult mesenchymal stem cells (MSCs) are a promising cell source for tissue regeneration. However, ex vivo expansion results in cell senescence; cells lose their proliferation and differentiation capacity. Fetal MSCs can be an alternative due to their robust proliferation and differentiation capacities as well as immune privilege properties. Given the rejuvenation effect of decellularized extracellular matrix (dECM) on adult MSCs, it remains unknown whether dECM influences the regenerative potential of fetal stem cells. In this study, passage five fetal nucleus pulposus cells (fNPCs) and fetal synovium-derived stem cells (fSDSCs) were expanded on dECMs deposited by fNPCs (NECM) and fSDSCs (SECM) for one passage with expansion on tissue culture plastic (Plastic) as a control. We found that dECM expanded fNPCs and fSDSCs exhibited both similarities and differences in expression of stemness genes and surface markers. Expanded fNPCs yielded more differentiated pellets after chondrogenic induction but no adipogenic differentiation following adipogenic induction in both Plastic and dECM groups than the corresponding fSDSC group. Despite a significant increase in fNPCs, dECM expanded fSDSCs exhibited no increase in chondrogenic potential; however, compared to the Plastic group, dECM expanded fSDSCs exhibited a small increase in osteogenic potential and a great increase in adipogenic potential. These results suggest that fNPCs are more sensitive to NECM rejuvenation for cartilage tissue engineering and regeneration; in contrast, dECMs exhibited limited effects on fSDSC rejuvenation in chondrogenic capacity except for enhanced adipogenic capacity following expansion on SECM.

Due to the great threat of torpedo against surface warships, an efficient hydroacoustic countermeasure system must output realtime strategies that can accommodate varied antagonizing scenarios. Aiming at the decision-making problem in the anti-torpedo hydroacoustic countermeasure cases, this paper proposes an intelligent adversarial strategy based on the game theory. By discretizing the strategy space of both sides, a matrix game model is established with the payoff characterized by the capture probability of attacking torpedo. An improved simplex algorithm is then developed to get the mixed-strategy Nash equilibrium of the game model, with which preferred avoiding strategies can be obtained to minimize the risk of being captured by the attacking torpedo. Based on the probabilistic view of preferred adversarial strategy, the launching strategy of floating acoustic decoy can be achieved, and the evasion trajectory of warship can be confirmed simultaneously. Numerical simulation demonstrates that the proposed method can generate realtime intelligent antagonizing strategy, and consequently, can improve the survival rate of surface warships in the of anti-torpedo countermeasure scenarios.

Nonnegative matrix factorization (NMF) has been shown to be a strong data representation technique, with applications in text mining, pattern recognition, image processing, clustering and other fields. In this paper, we propose a hypergraph regularized Lp smooth nonnegative matrix factorization (HGSNMF), by incorporating hypergraph regularization and Lp smoothing constraint terms into the standard NMF. The hypergraph regularization term can capture the intrinsic geometry structure of the high dimension space data more comprehensively than simple graph, the Lp smoothing constraint may yield a smooth and more accurate solution to the optimization problem. The updating rules are given using multiplicative update techniques, and the convergence of HGSNMF is theoretically investigated. The experimental results on four different data sets show that the proposed method has better clustering effect than the related state-of-the-art methods in the vast majority of cases.

In the era of big data with increasingly complex data structures and ever-larger data scales, matrix-type data are becoming highly valued and their applications in the fields of medicine, industry, education, geography, and astronomy are growing in extent. In recent years, significant progress has been made in the practical use of matrix variable t-distribution finite mixture models for handling data in order to address the issues of multi-subgroup structures and long data tails. In this paper, the expectation-maximization (EM) algorithm with penalized maximum likelihood is proposed to resolve the problem of the unbounded nature of the likelihood function applied to the model by considering the degeneracy of the variance-covariance matrix of this model. Our data were analyzed through simulations and real data, and the results demonstrate that our model is effective in both preventing the likelihood function from being unbounded and in ensuring the accuracy of the estimated parameters of the EM algorithm.

Work from the last years indicate that the extracellular matrix (ECM) plays a direct role in vari-ous cellular processes including proliferation, migration and differentiation. Besides homeostat-ic processes, its regulatory function in inflammation becomes more and more evident. In in-flammation like inflammatory bowel disease, the ECM composition is constantly remodeled which can result in a structuring of fistulizing disease course. Thus, tracking early ECM changes might bear the potential to predict the disease course. In this review, we will provide an over-view of relevant diagnostic methods focusing on ECM changes.

The new barrier mode in Apache Spark allows embedding distributed deep learning training as a Spark stage to simplify the distributed training workflow. In Spark, a task in a stage doesn’t depend on any other tasks in the same stage, and hence it can be scheduled independently. However, several algorithms require more sophisticated inter-task communications, similar to the MPI paradigm. By combining distributed message passing (using asynchronous network IO), OpenJDK’s new auto-vectorization and Spark’s barrier execution mode, we can add non-map/reduce based algorithms, such as Cannon’s distributed matrix multiplication to Spark. We document an efficient distributed matrix multiplication using Cannon’s algorithm, which improves significantly on the performance of the existing MLlib implementation. Used within a barrier task, the algorithm described herein results in an up to 24% performance increase on a 10,000x10,000 square matrix with a significantly lower memory footprint. Applications of efficient matrix multiplication include, among others, accelerating the training and implementation of deep convolutional neural network based workloads, and thus such efficient algorithms can play a ground-breaking role in faster, more efficient execution of even the most complicated machine learning tasks

The aim of this paper is to show how the mathematical basis is used for a precise treatment of double-entry bookkeeping, which was firstly developed in the nineteenth century by Sir William Rowan Hamilton. This is done by using basic notions of matrix algebra with the roots to the idea of using ordered pairs. We also reveal how the complex numbers and the rationals (fractions) developed in a mainstream of accounting science and became a leading platform for the ongoing processes within the Industry 4.0. The paper concludes with the examples on how accounting operations can be represented by matrix equations with a result of the essential report generating. The author represents a mathematical model of accounting which is independent of the specific existential forms but is capable to undertake the form of any of them and thus has the prospect of being understood and accepted by specialists globally.

Background: To compare the clinical efficacy of Japas osteotomy of the middle foot and first metatarsal sequence osteotomy in treating children with cavovarus foot deformity. Methods: A retrospective analysis was performed on the clinical effect of cavovarus foot surgery from January 2012 to January 2019. Thirty light and medium cavovarus foot cases underwent osteotomy based on soft tissue release. Among them, 16 cases of 22 feet underwent first metatarsal sequence osteotomy, and 14 cases of 21 feet underwent middle foot Japas osteotomy. Ankle-posterior foot (Wicart) scoring system was used to evaluate the good and good rates of the two surgical methods. X-ray films were taken before and after the last follow-up in a standing weight-bearing position, and Meary Angle, Hibb Angle, and Pitch Angle were measured to compare the clinical efficacy of the two surgical methods in correcting the light and medium-cavovarus foot deformity.Results: (1) All patients were followed up for an average of 30 months. There was no significant difference in Meary, Hibb, and Pitch Angle between first metatarsal osteotomy and middle foot Japas osteotomy before surgery, indicating that the severity of malformation was similar between the two groups. (2) The Meary, Hibb, and Pitch Angle of the last follow-up were compared between the two groups (P>0.05), which showed no statistical significance, indicating that the two surgical methods had similar effects on cavovarus deformity correction. (3) At the most recent follow-up, there was no statistically significant difference between the two groups regarding the percentage of patients who achieved an excellent or good Wicart score; for the first metatarsal osteotomy group, the rate was 87%, and for the Japas osteotomy group was 90%; the Fisher test p>0.05 indicates that the postoperative excellent and good rates of the two treatments are comparable.II (4) Comparison of operation time and intraoperative blood loss between the two groups, P<0.05, showed statistically significant differences, indicating that the first metatarsal osteotomy had obvious advantages over Japas osteotomy operation time and intraoperative blood loss. Conclusions: There is no significant difference in postoperative efficacy between first metatarsal osteotomy and Japas osteotomy for light and medium-cavovarus with the apex of the deformity located at the medial cuneus or navicular cuneiform joint. However, the intraoperative blood loss and operative time of first metatarsal osteotomy are superior to Japas osteotomy of the middle foot, and the trauma to children is less. Therefore, the first metatarsal osteotomy can be considered a surgical procedure.

The main purpose of the work was to determine the powder composition and properties of iron-based sinters used as a matrix in metallic diamond tools. The FeCuSnNi sinters obtained from a mixture of commercial powders were used for research. The material was subjected to milling in a ball mill and sinter have been performed with the hot-pressing technique in a graphite mold. The physical and mechanical properties of the sinters were tested. The investigations of obtained sinters concerned density, porosity, hardness, oxygen content, static tensile test and analysis of microstructure. The static tensile test was carried out with the use of a universal testing machine UTS-100. The study of the microstructure of sinters was performed using the JSM-7100F scanning electron microscope. The sinters are characterized by a high coefficient of thermal expansion and good mechanical properties. The FeCuSnNi sinter revealed a complex phase structure. Spot chemical analysis revealed the presence of Fe solution, Cu solution and the presence of iron oxides oxides. Nickel atoms were present throughout the sinter volume. The obtained results indicate that the presented material can be used as a matrix of a diamond-metal composite in diamond tools for the processing of natural stones and building materials.

Collagen, the most abundant structural protein found in mammals, plays a vital role as a constituent of the extracellular matrix (ECM) that surrounds cells. Collagen fibrils are strengthened through the formation of covalent cross-links, which involve complex enzymatic and non-enzymatic reactions. Lysyl oxidase (LOX) is responsible for catalyzing the oxidative deamination of lysine and hydroxylysine residues, resulting in the production of aldehydes, allysine, and hydroxyallysine. These intermediates undergo spontaneous condensation reactions, leading to the formation of immature cross-links, which are the initial step in the development of mature covalent cross-links. Additionally, non-enzymatic glycation contributes to the formation of abnormal cross-linking in collagen fibrils. During glycation, specific lysine and arginine residues in collagen are modified by reducing sugars, leading to the creation of Advanced Glycation End-products (AGEs). These AGEs have been associated with changes in the mechanical properties of collagen fibers. Interestingly, various studies have reported that plant polyphenols possess amine oxidase-like activity and can act as potent inhibitors of protein glycation. This review article focuses on compiling literature describing polyphenols with amine oxidase-like activity and antiglycation properties. Specifically, we explore the molecular mechanisms by which specific flavonoids impact or protect the normal collagen cross-linking process. Furthermore, we discuss how these dual activities can be harnessed to generate properly cross-linked collagen molecules, thereby promoting the stabilization of highly organized collagen fibrils.

As the coproduct of steelmaking, steelmaking slag, volumetrically expansive-prone without treatment, has been satisfactorily used as an aggregate base course material in highway construction. Although numerous technical reports and papers have revealed that steel slag aggreged using in rigid matrixes, the end product, paving block, non-structural concrete, for example, possesses superb strength and durability properties, the application of steel slag aggregate as a concrete aggregate is currently prohibited in highway construction. Naturally, researchers explore the practicality of use of steel slag, how to connect the laboratory experiment results to the end-product behavior, and further convert the research results into real construction? For all nontraditional or secondary materials utilization, the procedure of laboratory material examination, lab and field trial test are critical. To generalize the utilization, usability criteria establishment is necessary. This paper tries to use step-by-step method and plain language to explain how the volumetrically expansion can be simulated in lab testing apparatus, and based on the model, the mathematical deduction can result in a numerical usability criterion for steel slag use as a coarse aggregate in concrete (a rigid material). Therefore the paper is composed four main parts, laboratory test methods to examine the expansion force resulted from steel slag; converting the measured expansion force in a given volume of mass aggregate to the expansion (body) force of a single particle; modeling of slag and end material disruption; and a usability criterion from numerical deduction for the use of expansive-prone coarse slag in concrete or other rigid matrices. The paper provides the solutions to answer the above questions. Through the mathematical and mechanical modeling, provides the potential criteria that could result in specifications and guidance establishment for broad volumetric expansive-prone slags.

Atomic structure of N-electron atoms is often determined using the Hartree-Fock method, which is an integro-differential equation. The exchange term of the Hartree-Fock equations is usually treated as an inhomogeneous term of a differential equation, or with a local density approximation. This work uses matrix methods to solve for the Hartree-Fock equations, rather than the more commonly-used shooting method to integrate an inhomogeneous differential equation. It is well known that a derivative operator can be expressed as a matrix made of finite-difference coefficients; energy eigenvalues and eigenvectors can be obtained by using computer linear-algebra packages. We extend the same technique to integro-differential equations, where a discretized integral can be written as a sum in matrix form. This method is compared against experiment and standard atomic structure calculations. We also can use this method for free-electron wavefunctions. This technique is important for spectral line broadening in two ways: improving the atomic structure calculations, and improving the motion of the plasma electrons that collide with the atom.

Psychiatric disorders, characterized by complex and fluctuating patterns of thoughts, emotions, and behaviors, can be effectively modeled and visualized using mathematical wave equations. This study explores the representation of three major psychiatric conditions— Psychosis, Bipolar Disorder and Obsessive Compulsive Disorder (OCD)—through the application of differential equations, damping factors, and noise perturbations. Psychosis is modeled using Lissajous figures with high-frequency components, damping, and noise, symbolizing the irregular and erratic thought patterns characteristic of this condition. The inclusion of random perturbations and varying frequencies illustrates the chaotic and unpredictable nature of psychotic episodes, while damping effects reflect the temporary reductions in symptom intensity. For bipolar disorder, a system of partial differential equations simulates the cyclical nature of manic and depressive episodes. The model captures high-energy manic phases with periodic disturbances and the subsequent transition to lower-energy depressive states through damping effects. This representation highlights the oscillatory behavior and recurring episodes inherent to bipolar disorder. OCD is represented with Circumferential Complex Equations in Mult directions. The resulting graphical representations provide intuitive visual insights into the dynamics of these psychiatric disorders. By leveraging wave equations and mathematical modeling, this approach offers a novel perspective on understanding and analyzing the complex behaviors associated with OCD, bipolar disorder and psychosis. This method not only aids in the conceptualization of psychiatric phenomena but also underscores the potential of mathematical tools in the study of mental health conditions.

The accurate prediction of heat load profiles with a daily resolution is required for a broad range of applications such as potential studies, design, or predictive operation of heating systems. If the heat demand of a consumer is mainly caused by (production) processes independent of the ambient temperature, existing load profile prediction methods fail. To close this gap, this study develops two ex post machine learning models for the prediction of the heat demand with a daily resolution. The selected input features are commonly available to each consumer connected to public natural gas and electricity grids or operating an energy monitoring system: Ambient temperature, weekday, electricity consumption, and heat consumption of the last seven days directly before the predicted day. The study’s database covers electricity and natural gas consumption load profiles from 82 German consumers over a period of two years. Electricity and heat consumption correlate strongly with individual patterns for many consumers. Both, shallow and deep learning algorithms are evaluated. The highest accuracy is achieved by a Long Short Term Memory (LSTM) model with a median of R² of 0.94. The ex post model architecture makes the model suitable for automated anomaly detection in energy monitoring systems.

The energy transition is a challenge that affects all sectors, from transport to civil structures and industry. In the industrial sector, the greatest need is the decarbonisation of energy-intensive in-dustries, such as producers of iron and steel, aluminum, cement, petrochemicals, paper, and more. The steel industry, in particular, is a hard-to-abate high-emissivity industry that, due to chemical processes and high thermal demands (often above 500 °C), contributed to 7.4% of global CO2 emissions in 2021. This paper explores the potential applications of hydrogen in these hard-to-abate sectors, highlighting its versatility and significance in decarbonization efforts, especially as a me-dium to facilitate the transition to green electric energy uses. It provides an overview of hydrogen production methods, emphasizing the importance of sustainable and green hydrogen production. It reviews hydrogen production methods, storage, and potential in blended combustion. In the final part of the article, some considerations are introduced on the possible role of hydrogen in the steel sector (both as a supplementary fuel and as a reducing agent in innovative processes), showing that while there is potential for its inclusion as an element for decarbonization, it is necessary to carefully evaluate the energy balances of the various processes and the methods of hydrogen production, in order to avoid achieving only marginal effects.

Background: Chronic non-specific low back pain (CNSLBP) is defined as back pain that lasts longer than 12 weeks. Objectives: To investigate the efficacy of manual therapy (MT) program combined with Capacitive and Resistive Electric Transfer (TECAR) therapy in individuals with CNSLBP. Method: Sixty adults with CNSLBP were randomly equally divided into three groups. The first group followed an MT protocol in the lumbar region (MT group), the second group followed the same MT protocol combined with TECAR therapy (MT + TECAR group) using a conventional capacitive electrode as well as a special resistive electrode bracelet and the third group (Control group) received no treatment. Both intervention programs included six treatments over two weeks. Pain in the last 24 hours with the Numeric Pain Rating Scale (NPRS), functional ability with the Roland-Morris Disability Questionnaire (RMDQ), Pressure Pain Threshold (PPT) in the lumbar region with pressure algometry, and mobility of the lumbo-pelvic region through fingertip-to-floor distance (FFD) test were evaluated before and after the intervention period with a one-month follow-up. Analysis of variance with repeated measures was applied. Results: In the NPRS score, both intervention groups showed statistically significant differences compared to the control group both in the second week as well as in the one-month follow-up (p < .001). Between-groups differences were also noticed between the two intervention groups in the second week (p < .05). Differences in the RMDQ score in the second week and on the one-month follow-up were detected between the intervention groups and the control group (p < .001), while differences between the two intervention groups were only detected in the one-month follow-up (p < .001). Regarding the PPT values, differences were found mainly between the MT + TECAR and the control group and between the MT + TECAR and the MT group (p < .05), with the MT + TECAR group in most cases showing the greatest improvement compared to the other two groups, which remained statistically significant in the one-month follow-up (p < .05). Finally, both intervention groups improved the mobility of the lumbo-pelvic region in both time points compared to the control group without, however, statistically significant differences between them (p> .05). Conclusion: The application of an MT protocol with TECAR therapy appeared more effective than conventional MT as well as compared to the control group in reducing pain and disability and improving PPT in individuals with CNSLBP. No further improvement was noted in mobility of the lumbo-pelvic region by adding TECAR to the MT intervention.

Abstract: The contribution of breakfast to diet quality (DQ) can inform future dietary guidelines. This study examined breakfasts that were associated with highest-quality diets. Dietary data came from the first reported day of the National Health and Examination Survey (NHANES) 2011-2014 (n=14,488). DQ measures were the Nutrient Rich Foods Index (NRF9.3) and the USDA Healthy Eating Index 2015 (HEI 2015). Analyses of breakfast intakes were conducted by NRF9.3 tertiles and by age and socioeconomic groups. Four out of 5 NHANES participants ate breakfast. Breakfast provided 19-22% of dietary energy depending on age. Breakfast intakes of complex carbohydrates and total sugars were higher and intakes of protein and fats were lower relative to energy intakes. Breakfast provided more that 20% of daily intakes of B vitamins, vitamins A and D, folate, calcium, iron, potassium and magnesium. Eating breakfast was associated with higher NRF9.3d scores. Breakfasts associated with top tertile of NRF9.3d had more carbohydrates and less added sugars and fats. Such breakfasts had more fruit and juices, more whole grains, more milk and yogurt and less meat and eggs. Breakfast patterns that favored fruit, whole grains, and dairy were associated with healthiest diets.

In this paper, the notion of θ∗-weak contraction is introduced, which is utilized to prove some fixed point results. These results are helpful to give a positive response to certain open question raised by Kannan [Amer. Math. Monthly 76:1969] and Rhoades [Contemp. Math. 72:1988] on the existence of contractive definition which does not force the mapping to be continuous at the fixed point. Some illustrative examples are also given to support our results. As applications of our result, we investigate the existence and uniqueness of a solution of non-linear matrix equations and integral equations of Volterra type as well.

Aim: To study the relationship between the location of chest pain (topography) and site of coronary artery involvement in patients of Acute coronary syndrome (ACS) undergoing percutaneous transluminal coronary angioplasty (PTCA). Materials and Method: This observational study analyzed 589 angina topographic sites in 411 consecutive patients hospitalized for Acute Coronary syndrome (ACS) who underwent PTCA at a tertiary care center between January 2017 and December 2019. All parameters including the characteristics and site of the anginal pain, Electrocardiogram (ECG), and Coronary angiography (CAG) findings were recorded and analyzed for their topographical correlation with site of culprit vessel involvement. Result: Out of 411 patients, 337 were Males (82.0%) and 74 (18.0%) were females with 589 topographic sites of angina. The mean age of the study subject was 57.03± 11.28 years. In both ST elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI), the Left anterior descending (LAD) was the most affected vessel in 201(63.4%) and 49(53.3%) respectively. The correlation coefficient for LAD occlusion was 0.298 (p=0.001) for the Retrosternal site. The Left Circumflex (LCX) artery showed a positive correlation of 0.647 (p= 0.001) for Jaw with Neck pain and of 0.585 (p=0.001) for Backache with Shoulder pain. The Right Coronary Artery (RCA) showed a positive correlation of 0.713 (p=0.001) for Retrosternal plus Jaw and Neck pain and of 0.719 (p=0.001) for Retrosternal plus Backache. Conclusion: The study reveals a significant correlation between chest pain topography and site of coronary artery involvement. It provides a basis for future research to develop tools that help healthcare professionals quickly identify culprit artery in ACS.

Gastric inflammation-related disorders are commonly observed digestive system illnesses char-acterized by the activation of proinflammatory cytokines, particularly tumor necrosis factor-α (TNF-α). This results in the induction of cyclooxygenase-2 (COX-2)/prostaglandin E2 (PEG2) and matrix metallopeptidase-9 (MMP-9). These factors contribute to the pathogenesis of gastric in-flammation disorders. We examined the preventive effects of Lonicera japonica Thunb. ethanol ex-tract (Lj-EtOH) on gastric inflammation induced by TNF-α in normal GES-1 cells. The GES-1 cell line was used to establish a model that simulated the overexpression of COX-2/PGE2 and MMP-9 proteins induced by TNF-α, to examine the anti-inflammatory properties of Lj extracts. The re-sults indicated that Lj-EtOH exhibits significant inhibitory effects on COX-2/PEG2 and MMP-9 ac-tivity, attenuates cell migration, and provides protection against TNF-α-induced gastric inflam-mation. The protective effects of Lj-EtOH are associated with the modulation of COX-2/PEG2 and MMP-9 through activation of TNFR–ERK 1/2 signaling pathways as well as the involvement of c-Fos and nuclear factor kappa B (NF-κB) signaling pathways. Based on our findings, Lj-EtOH ex-hibits a preventive effect on human gastric epithelial cells. Consequently, it may represent a novel treatment for the management of gastric inflammation.

As the aging of the world accelerates, clarifying the relationship between cultural differences and ageism is an urgent issue. Therefore, in this study, we conducted a correlation analysis between the six cultural scales of Hofstede et al. [1] and the 10 ageism scales calculated from data on 35,232 people from 31 countries included in the World Values Survey Wave 6 by Inglehart et al. [2]. The results of a partial correlation analysis controlling for economic and demographic factors showed that the cultural scales were correlated with ageism. This is the first study to show that diverse cultural scales are related to multiple dimensions of ageism.

Bicycle transport stands at the forefront of sustainable mobility initiatives, a cornerstone of European Union policy. While support for cycling is crucial, its advancement hinges upon the presence of high-quality, secure infrastructure for cyclists. Safety emerges as a paramount concern, influencing the viability of cycling as a mode of transportation, yet its perception varies among user demographics. In light of this, this article endeavors to examine and contrast cycling infrastructure across various European nations, alongside analyzing statistics pertaining to fatal traffic accidents involving cyclists. The findings underscore a substantial correlation between the quality of cycling infrastructure and the incidence of accidents. This correlation underscores the pressing need for robust infrastructure development and safety measures to bolster cycling as a safe and viable transportation option. By understanding the intricate interplay between infrastructure quality and safety outcomes, policymakers can better prioritize resources and enact measures to foster safer cycling environments, thus furthering the objectives of sustainable mobility on a continental scale.

This retrospective study examines 248 test-bolus examinations preceding contrast-enhanced magnetic resonance angiography (CE-MRA) to extract clinically relevant data for critical limb ischemia (CLI) management. Methods involved a retrospective review of test-bolus exams, analysing 60 graphs for time-to-peak (TTP), full-width half-maximum (FWHM) time, and time to continual rise in signal intensity. These values were correlated with heart function parameters (ejection fraction, ASA-Classification, Lee-Index, and MET-Score). Results indicate a mean TTP of 31.2 ± 7.3s, showing a correlation between ejection fraction and ASA classification. Patients with atrial fibrillation exhibited prolonged TTP compared to those without. Despite population heterogeneity, findings facilitate risk stratification for limb-saving interventions in CLI. TTP emerges as a potential clinical cardiovascular parameter and a risk factor for vascular interventions. Given the variation in injection protocols across centres, this study underscores the importance of precise bolus arrival time documentation for future multicentre studies.

Upon the outbreak of the COVID-19, countries worldwide developed policies with the goal to introduce restrictive measures geared towards mitigating the spread of the virus. Although these health initiatives were put in place through top-down public directives, they relied heavily on the cooperation of citizens who had to be willing to carry them out. As a consequence, we could observe differences in compliance with governmental restrictions within and between countries. Increasing policy stringency was the method adopted overall to promote people’s compliance. This article used survey data from 10308 participants in Brazil to examine whether there was a positive correlation between policy stringency and compliance with restrictive measures to reduce the spread of COVID-19. The results revealed, however, that there was no direct influence of policy stringency on people’s health behaviors. Accordingly, I hypothesized that individual differences in personality traits were one of the drivers behind policy compliance, as they would support self-interests such as the duty to support authorities as well as the perceived health risks of certain behaviors and ultimately motivate compliance. The findings’ implications for both compliance research and for authorities wanting to nurture voluntary compliance with public health orders are discussed and suggestions are provided.

Aircraft heat exchangers play a crucial role in maintaining thermal balance and ensuring that essential components operate efficiently and safely. In this context, it is highly relevant to gain knowledge about the deterioration and the predominant damage mechanisms of these components. In this study, two different non-destructive methods are employed to analyze the damage initiation of a heat exchanger part during fatigue test. On the one hand, Acoustic Emission technique is employed using membrane-free microphones capable of capturing a broad bandwidth. The acoustic events were classified by a machine learning algorithm to determine their source and damage mechanisms. On the other side, Digital Image Correlation (DIC) allowed the measurement of the strain evolution along the test and more precisely, redistributions were considered as damage indicators. As a result, it was identified that AE served as early damage indicator as the cumulative number of events was in good agreement with the severity of the damage. With respect to classification two clear clusters ascribed to different type of events were identified. In the case of DIC, strain redistributions gave clear indications of damage or deterioration but at a later stage compared to AE