This study aims to systematically review and meta-analyze the nitro-oxidative stress (O&NS)/antioxidant (ANTIOX) ratio in the peripheral blood of people with mild cognitive impairment (MCI). We searched PubMed, Scopus, Google Scholar, and Web of Science for articles published from inception until July 31, 2021. Forty-six studies on 3.798 MCI individuals and 6.063 healthy controls were included. The O&NS/ANTIOX ratio was significantly higher in MCI than in controls with a Standardized Mean Difference (SMD)=0.378 (95% CI: 0.250; 0.506). MCI individuals showed increased lipid peroxidation (SMD=0.774, 95%CI: 4.416; 1.132) and O&NS-associated toxicity (SMD=0.621, CI: 0.377; 0.865) and reduced glutathione (GSH) defenses (SMD=0.725, 95%CI: 0.269; 1.182) as compared with controls. MCI was also accompanied by significantly increased homocysteine (SMD=0.320, CI: 0.059; 0.581), but not protein oxidation, and lowered non-vitamin (SMD=0.347, CI: 0.168; 0.527) and vitamin (SMD=0.564, CI: 0.129; 0.999) antioxidant defenses. The results show that MCI is at least in part due to increased neuro-oxidative toxicity and suggest that treatments targeting lipid peroxidation and the GSH system may be used to treat or prevent MCI.

Terpenoids are toxic compounds produced by plants as a defense strategy against insect herbivores. We tested the effect of Origanum vulgare terpenoids on the generalist herbivore Spodoptera littoralis and the response of the plant to herbivory. Terpenoids were analyzed by GC-FID and GC-MS and quantitative gene expression (qPCR) was evaluated on selected plant genes involved in both terpene biosynthesis. The insect detoxification response to terpenes was evaluated by monitoring antioxidant enzymes activity and expression of insect genes involved in terpene detoxification. O. vulgare terpenoid biosynthesis and gene expression was modulated by S. littoralis feeding. The herbivore-induced increased level of terpenoids (particularly carvacrol and p-cymene) interacted with the herbivore by decreasing larval survival and growth rate. The assimilation by S. littoralis of more than 50% of ingested terpenes correlated with the possible toxic effects of O. vulgare terpenoids. In choice test experiments, carvacrol and γ-terpinene mediated the larval feeding preferences, wherease the prolonged feeding on O. vulgare terpenoids (particularly on γ-terpinene) exerted relevant antinutritional effects on larvae. S. littoralis was found to react to O. vulgare terpenoids by increasing its antioxidant enzymes activities and gene expression, although this was not sufficient to sustain the toxicity of O. vulgare terpenoids.

Background: Hypertension, atherogenicity and insulin resistance are major risk factors of cardiovascular disorder (CVD), which shows a strong comorbidity with major depression (MDD) and bipolar disorder (BD). Activated oxidative and nitrosative stress (O&NS), inflammatory pathways, and increased atherogenicity are shared pathways underpinning CVD and mood disorders. Methods: The current study examined the effects of lipid hydroperoxides (LOOH), superoxide dismutase (SOD), nitric oxide metabolites (NOx), advanced oxidation protein products (AOPP), and malondialdehyde (MDA) on systolic (SBP) and diastolic (DBP) blood pressure in 96 mood disordered patients and 60 healthy controls. Results: A large part of the variance in SBP (31.6%) was explained by the regression on a z unit-weighted composite score (based on LOOH, AOPP, SOD, NOx) reflecting nitro-oxidative stress toxicity (NOSTOX), coupled with highly sensitive C-reactive protein, body weight and use of antihypertensives. Increased DBP was best predicted (23.8%) by body mass index and NOSTOX. The most important O&NS biomarkers predicting an increased SBP were in descending order of significance: LOOH, AOPP and SOD. Higher levels of the atherogenic index of plasma, HOMA2 insulin resistance index and basal thyroid-stimulating hormone also contributed to increased SBP independently from NOSTOX. Although there were no significant changes in SBP/DBP in mood disorders, the associations between NOSTOX and blood pressure were significant in patients with mood disorders but not in healthy controls. Conclusions: Activated O&NS pathways including increased lipid peroxidation and protein oxidation, which indicates hypochlorous stress, are the most important predictors of an increased BP, especially in patients with mood disorders.

Ascending aorta aneurysm (AsAA) is a complex disease, currently defined an inflammatory disease. In the sporadic form, AsAA has, indeed, a complex physiopathology with a strong inflammatory basis, significantly modulated by genetic variants in innate/inflammatory genes, acting as independent risk factors and as largely evidenced in our recent studies performed during the last 10 years. Based on these premises, here, we want to revise the impact of reactive oxygen species (ROS) and oxidative stress on AsAA pathophysiology and consequently on the onset and progression of sporadic AsAA. This might consent to add other important pieces in the intricate puzzle of the pathophysiology of this disease with the translational aim to identify biomarkers and targets to apply in the complex management of AsAA, by facilitating the AsAA diagnosis currently based only on imaging evaluations, and the treatment exclusively founded on surgery approaches.

Intrauterine growth restriction (IUGR) and being born small for gestational age (SGA) are two distinct conditions with different implications for child development. IUGR is associated with greater perinatal morbidity and mortality and can be identified by additional abnormalities (pathological Doppler sonography, oligohydramnios, lack of growth in the interval, estimated weight <3rd percentile). IUGR may also be present in neonates with birth weights above the 10th percentile. Recognizing fetuses being “at risk” of a higher perinatal mortality and morbidity rate in order to monitor them accordingly and deliver them in good time is still challenging. This review article summarizes approaches to increase the diagnostic accuracy of IUGR and presents current concepts of pathophysiology with a focus on oxidative stress and consecutive inflammatory and metabolic changes. Since prenatal influences affect the risk of later diseases, we also discuss the need for interdisciplinary follow-up strategies during childhood and look at future scientific challenges. It should be emphasized that prenatal and postnatal care of IUGR neonates should be regarded as a continuum.

A meta-analysis showed a significant association between activated immune-inflammatory and nitro-oxidative (IO&NS) pathways and suicide attempts (SA). There are no data whether suicidal ideation (SI) is accompanied by activated IO&NS pathways and whether there are differences between SA and SI. The current study searched PubMed, Google Scholar, and Web of Science, for articles published from inception until May 10, 2021, and systematically reviewed and meta-analyzed the association between recent SA/SI (< 3 months) and IO&NS biomarkers. We included studies which compared psychiatric patients with and without SA and SI and controls (either healthy controls or patients without SA or SI) and used meta-analysis (random-effect model with restricted maximum-likelihood) to delineate effect sizes with 95% confidence intervals (CI). Our search included 59 studies comprising 4.034 SA/SI cases and 12.377 controls. Patients with SA/SI showed activated IO&NS pathways (SMD: 0.299; CI: 0.200; 0.397) when compared to controls. The immune profiles were more strongly associated with SA than with SI, particularly when compared to healthy controls, as evidenced by activated IO&NS pathways (SMD: 0.796; CI: 0.503; 1.089), an immune-inflammatory response (SMD: 1.409; CI: 0.637; 1.462), inflammation (SMD: 1.200; CI: 0.584; 1.816), and neurotoxicity (SMD: 0.904; CI: 0.431; 1.378). The effects sizes of the IO&NS, immune-inflammatory response and inflammatory profile were significantly greater in SA than in SI. In conclusion: increased neurotoxicity due to inflammation and nitro-oxidative stress and lowered neuroprotection may explain at least in part why psychiatric patients show increased SA and SI. The IO&NS pathways are more pronounced in recent SA than in SI.

The underlying mechanisms of secondary neuronal damage following intracerebellar hemorrhage are not yet clear. We aimed to study the possible mechanisms in the mediation of secondary neuronal damage following intracerebellar hemorrhage. ICbH was induced by collagenase type VII-S into mice in 2 phases (n=24/phase): 12 in control group, 12 in day 1 group, 12 in day 3 group and another 12 in day 7 group. All mice underwent locomotor assessment and subsequently sacrificed on day 1, day 3 and day 7 respectively. Cerebellum from phase one and phase two were taken to study morphological, immunohistochemistry and oxidative stress respectively. Mice behavior disturbed following ICbH at day 3 and y 7 as compared with control. Besides, NO increased-on day 1 post induction and suppressed on day 3 and 7. Expressions of SOD, CAT, nNOS, GPX1 and COX-2 were significantly raised on day 3. Morphological studies of the perihaematoma region and tissue showed neuronal damage occurred from day 1 onwards, peaked on day 3 and continued day 7. NO and expression of genes be correlating with morphological changes. Briefly, NO and oxidative stress has an important role in the cascade of secondary neuronal damage of the perihematomal region of ICbH.

The design of biomaterial platforms able to release bioactive molecules is mandatory in tissue repair and regenerative medicine. In this context, electrospinning is a user-friendly, versatile and low-cost technique, able to process different kinds of materials in micro- and nano-fibers with a large surface area-to-volume ratio for an optimal release of gaseous signalling molecules. Recently, the antioxidant and anti-inflammatory properties of the endogenous gasotramsmitter hydrogen sulfide (H2S), as well as its ability to stimulate relevant biochemical processes on the growth of mesenchymal stem cells (MSC), have been investigated. Therefore, in this work, new poly(lactic) acid fibrous membranes (PFM), doped and functionalized with H2S slow-releasing donors extracted from garlic, were synthetized. These innovative H2S-releasing mats were characterized for their morphological, thermal, mechanical and biological properties. Their antimicrobial activity and effects on the in vitro human cardiac MSC growth, either in the presence or in the absence of oxidative stress, were here assessed. On the basis of the results here presented, these new H2S-releasing PFM could represent promising and low-cost scaffolds or patches for biomedical applications in tissue repair.

The clinical relationship between diabetes and inflammation is well-established. Various branches of science independently have confirmed that disrupting oxidant-antioxidant equilibrium and elevated lipid peroxidation could be a potential mechanism for chronic kidney disease associated with Type 2 diabetes mellitus (T2DM). Under diabetic condition, hyperglycemia, especially inflammation, and increased reactive oxygen species generation are bidirectionally associated. Inflammation, oxidative stress and tissue damage are believed to have a role in the development of diabetes. Although the exact mechanism underlying the oxidative stress and its impact on diabetes progression remains uncertain, the hyperglycemia-inflammation-oxidative stress interaction clearly plays a significant role in onset and progression of vascular disease, kidney disease, hepatic injury, pancreas damage and, therefore holds promise as a therapeutic target. Evidence strongly indicates that the use of multiple antidiabetic medications therapy fails to achieve the normal range for glycated hemoglobin target, signifying treatment resistant diabetes. Antioxidants with polyphenols are considered useful as adjuvant therapy for their potential anti-inflammatory effect and antioxidant activity. We aimed to analyze the current major points reported in preclinical in vivo and clinical studies of antioxidants in the prevention or treatment of inflammation in T2DM. Then, we will share our speculative vision of the future diabetes clinical trials.

Background: Suicide attempts (SA) frequently occur in patients with mood disorders and schizophrenia, which are both accompanied by activated immune-inflammatory and nitro-oxidative (IO&NS) pathways. Methods: We searched PubMed, Google Scholar, and Web of Science, for articles published from inception until February 1, 2021. We included studies that compared blood biomarkers in psychiatric patients with (SA+) and without SA (SA-) and heathy controls and we combined different IO&NS biomarkers into immune, inflammatory, and neurotoxic profiles and used meta-analysis (random-effect model with restricted maximum-likelihood) to delineate effect sizes with 95% confidence interval (CI).Findings: Our search included 51 studies comprising 4.945 SA+ patients and 24.148 controls. We stratified the control group into healthy controls and SA- patients. SA+ patients showed significantly (p<0.001) increased immune activation (SMD: 1.044; CI: 0.599-1.489), inflammation (SMD: 1.109; CI: 0.505, 1.714), neurotoxicity (SMD: 0.879; CI: 0.465, 1.293), and lowered neuroprotection (SMD: 0.648; CI: 0.354, 0.941) as compared with healthy controls. When compared with SA- patients, those with SA+ showed significant (p<0.001) immune activation (SMD: 0.290; CI: 0.183, 0.397), inflammation (SMD: 0.311; CI: 0.191, 0.432), and neurotoxicity (SMD: 0.315; CI: 0.198, 0.432), and lowered neuroprotection (SMD: 0.341; CI: 0.167, 0.515). Patients with current, but not lifetime, SA showed significant (p<0.001) levels of inflammation and neurotoxicity as compared with controls. Conclusions: Patients with immune activation are at a higher risk of SA which may be explained by increased neurotoxicity due to inflammation and nitro-oxidative stress. This meta-analysis discovered new biomarkers of SA and therapeutic targets to treat individuals with SA.

Abstract: Measures to counteract AMD generation need to start at the mineral surface, inhibiting mineral-oxidizing, acidophilic microbes. Laboratory and long-term field tests with pyrite-containing mining wastes, where Carbonaceous Phosphate Mining Waste (CPMW) was added, resulted in low acidity, and near neutral drainage. The effect was reproducible, nd confirmed by several independent research groups. This was shown to involve an organic coating, likely a biofilm. The biofilm formation was confirmed when CPMW was added to lignite coal waste with an initial pH of 1. Forty five days after the addition, the coal waste was dominated by heterotrophic microorganisms in biofilms. A review of the scientific literature supports that CPMW has physical and chemical characteristics which are capable of inducing a strong inhibitory effect on sulphide oxidation by forming an organic coating over the mineral surface. CPMW characteristics appear to provide the cornerstone of a new technology for the reduction of sulphide oxidation in mine wastes. An hypothesis for testing this technology is presented which could result in an economical and sustainable approach to mine waste and water management.

The approach towards myalgic encephalomyelitis / chronic fatigue syndrome (ME/CFS) remains in a permanent state of crisis with fierce competition between the psychosocial school, which attributes ME/CFS to the perception of effort, and the medical approach (Maes and Twisk, BMC Med, 2010,8,35). The aim of this paper is to review how to construct a nomothetic model of ME/CFS using Partial Least Squares (PLS) path analysis and ensembling causome (bacterial translocation as assessed with IgM/IgA responses to LPS), protectome (lowered coenzyme Q10), adverse outcome pathways (AOP) including increased lysozyme, CD38+ T cell activation, cell-mediated immune activation (CMI), and IgM responses to oxidative specific epitopes and NO-adducts (IgM OSENO). Using PLS, we trained, tested and validated this knowledge- and data-driven causal ME/CFS model, which showed adequate convergence, construct and replicability validity. This bottom-up explicit data model of ME/CFS objectivates the descriptive narratives of the ME/CFS phenome, using causome-protectome-AOP data, whereby the abstract concept ME/CFS is translated into pathways, thereby securing the reification of the ME/CFS phenome. We found that 31.6% of the variance in the physiosomatic symptom dimension of ME/CFS was explained by the cumulative effects of CMI and CD38+ activation, IgM OSENO, IgA LPS, lysozyme (all positive) and coenzyme Q10 (inversely). Cluster analysis performed on the PLS-generated latent vector scores of all feature sets exposed three distinct immune groups of ME/CFS, namely one with increased lysozyme, one with increased CMI + CD38 activation + depressive symptoms, and another with increased bacterial translocation + autoimmune responses to OSENO.

This study presents the validation process of the Questionnaire on Academic Stress in Secondary Education –QASSE-, designed to assess the wide variety of school sources and situations related to academic stress in adolescence, and their relationship with students’ physical and psychological well-being. Participants were 860 Spanish high school students (52.9% girls) with an average age of 14.62 years (SD = 1.8). Through a cross-validation process, EFA and CFA supported QASSE multifactorial structure with four first-order factors -academic overload, interaction with classmates, family pressure, and future-oriented perspective- and a second-order factor of academic stress, showing a significant and intense relationship with adolescents’ psychological and physical well-being. Results also highlight the effects of the gender*educational level interaction on the students’ stress, with girls showing higher levels of stress in the transition courses between educational phases (sophomore and junior years). The QASSE demonstrates good validity and reliability, showing potential for both research and educational application. The results show the high impact of the QASSE dimensions on psychological and physical well-being in adolescence, highlighting its special usefulness for designing and adjusting educational prevention and intervention actions in this area to the students’ specific characteristics and needs

MicroRNAs (MiRNAs) are a class of non-coding single-stranded RNA molecules of approximately 20-24 nucleotides in plants that play an important regulatory role in a variety of biological processes such as plant growth and development and response to various abiotic stresses. For example Drought, Salt, Cold, High temperature, Heavy metals and Nutrition. MiRNAs affect gene expression by manipulating the cleavage, translational expression or DNA methylation of target mRNAs. This review describes the current progress made on the way miRNAs are produced and regulated and the way miRNA/target gene is used in plant responses to abiotic stresses. Studying the molecular mechanism of action of miRNAs downstream target genes can optimize the genetic manipulation of crop growth and development conditions that provide a more theoretical basis for improving crop production.

Coronavirus is believed to have originated from a wet market in Wuhan, China, and has spread all over the world, resulting in a large number of hospitalizations and deaths. Social scientists are just beginning to understand its consequences on human behavior. One policy that public health officials put in place to help stop the spread of the virus were stay-at-home/shelter-in-place lockdown-style orders. Schools, Colleges and Universities across the country have now been shut down till now due to Covid-19. Some Governments in India impose lockdown to reduce the crises created by this unknown virus. It is now difficult to make final assessments by school, school leaving examinations and entrance tests for undergraduate and post-graduate courses. This disruption implies for students across the socio-economic spectrum, both in terms of learning outcomes , food and economic security. Here the aim is to discuss the implications of lockdown-induced in schools in both urban and rural areas in India.The whole world implemented a nationwide lockdown to curb the transmission of the virus. A survey was over Five hundred families to complete a questionnaire with questions around symptoms of depression, anxiety, stress, and family affluence. The humans who do not have enough supplies to sustain the lockdown were most affected Families with affluence were found to be negatively correlated with stress, anxiety, and depression. Stress, anxiety, and depression more than others are seen in students and healthcare professionals. The main aim of the paper is to find out how symptoms of depression, anxiety and stress on parents due to COVID-19.

Background: There is a strong comorbidity between mood disorders and metabolic syndrome (MetS). Increased levels of reactive oxygen and nitrogen species (RONS) and nitro-oxidative stress toxicity (NOSTOX) partially underpin this comorbidity.Aims: To examine the associations of RONS/NOSTOX biomarkers with MetS after adjusting for the significant effects of mood disorders (major depression, and bipolar type 1 and 2), generalized anxiety disorder (GAD), tobacco use disorder (TUD), and male sex.Methods: The study included subjects with (n=65) and without (n=107) MetS and measured levels of superoxide dismutase 1 (SOD1), lipid hydroperoxides (LOOH), nitric oxide metabolites (NOx), malondialdehyde (MDA), and advanced oxidation protein products (AOPP) and computed z unit-weighted composite scores which reflect RONS/NOSTOX. The study included 105 patients with mood disorders, 46 with GAD, and 95 with TUD.Results: MetS was associated with increased levels of MDA and AOPP, independently from mood disorders, TUD, sex and GAD. Atherogenicity and insulin resistance (IR) were significantly associated with a NOSTOX composite score. Mood disorders, TUD, GAD, male sex and MetS independently contribute to increased RONS/NOSTOX. The RONS/NOSTOX profile of MetS was different from that of GAD, which showed increased SOD1 and NOx levels. TUD was accompanied by increased SOD1, LOOH and MDA, and male sex by increased LOOH and AOPP.Conclusions: MetS is characterized by increased lipid peroxidation with aldehyde formation and chlorinative stress, and atherogenicity and IR are strongly mediated by RONS/NOSTOX. Partially shared RONS/NOSTOX pathways underpin the comorbidity of MetS with mood disorders, GAD, and TUD.

The COVID-19 pandemic may have increased interpersonal and intimate violence, harmful use of alcohol and other drugs (AOD), and mental health problems. The present study uses a valid path model to describe relationships between these conditions of young Mexicans during the second year of the pandemic. A sample of 7,420 young Mexicans ages 18 to 24—two-thirds of whom were women—completed the Life Events Checklist, the Alcohol, Smoking, and Substance Involvement Screening Test, the Major-Depressive-Episode Checklist, the Generalized Anxiety Scale, and the Posttraumatic Stress Disorder (PTSD) Checklist. Young Mexicans reported higher rates of victimization and perpetration of interpersonal and intimate violence and mental health symptomatology than those noted pre-pandemic and in the first year of the pandemic. Harmful use of AOD rates were like those reported by adolescents before. Findings suggested asymmetric victimization and perpetration of intimate violence by gender (with women being at a higher risk than men, p≤.05). More men than women engaged in the harmful use of AOD (except for sedatives, which more women abuse). In contrast, more women than men were at risk of all mental health conditions. The path model indicates that being a victim of intimate violence predicts harmful use of tobacco, alcohol, cocaine, and sedatives, depression, anxiety, and specific PTSD symptoms (such as re-experimentation and avoidance symptoms). Being a victim of interpersonal violence resulted in severe PTSD symptoms (including avoidance, negative alterations in cognition-mood, and hyperarousal signs). Harmful use of sedatives predicted depressive symptoms. Men´s victimizing intimate violence model contrasted with that of women, which also included being the victim of interpersonal violence and severe PTSD symptoms. The high school youth model had three paths -victimizing-intimate violence, victimizing-interpersonal abuse, and sedative use, which predicted depression. The findings of this study could serve as the basis for future studies exploring mechanisms that predict violence patterns to develop the most cost-effective preventive programs and public policies and to address mental health conditions during community emergencies.

Zero-rate output (ZRO) drift induces deteriorated micro-electromechanical system (MEMS) gy-roscope performances, severely limiting its practical applications. Hence, it is vital to explore an effective method toward ZRO drift reduction. In this work, we conduct an elaborate investigation on the impacts of the internal and packaging stresses on the ZRO drift at the thermal start-up stage, and propose a temperature-induced stress release method to reduce the duration and magnitude of ZRO drift. Self-developed high-Q dual mass tuning fork gyroscopes (TFGs) are adopted to study the correlations between temperature, frequency and ZRO drift. Furthermore, a rigorous finite element simulation model is built based on the actual device and packaging structure, revealing the temperature and stresses distribution inside TFGs. Meanwhile, the relationship between temperature and stresses are deeply explored. Moreover, we introduce a temperature-induced stress release process to generate thermal stresses and reduce the temperature-related device sensitivity. By this way, the ZRO drift duration is drastically reduced from ~2000 s to ~890 s, and the drift magnitude decreases from ~0.4 °/s to ~0.23 °/s. This stress release method achieves a small bias instability (BI) of 7.903 °/h and a low angle random walk (ARW) of 0.792 °/√h, and the long-term bias performance is significantly improved.

The production of plants and crops is influenced by environmental stress, which is a serious scientific issue. Cotton is an essential crop for producing natural fibers that are used to make biofuel and edible oils. Salinity is the main element that influences cotton growth during the beginning of germination. The type of salt and the growth stage affects how sensitive a plant is to salt stress. Developing ways to enhance cotton performance in salty circumstances can be aided by an understanding of the response of cotton to salt, its mechanism of resistance, and its management methods. Osmotic and ionic imbalances originate due to the deposition of soluble salts under salinity stress in the plant's root zone. Soil salinity significantly reduces plant growth due to several factors, such as nutritional ion imbalance, which reduces K+, PO4-, and NO- absorption, excessive salt chloride concentrations, and osmotic stress, which hinders water availability. Research has revealed that compared to subsequent stages, the germination, emergence, and seedling phases are more vulnerable to salinity stress, which ultimately affects the seed cotton yield by delaying blooming, reducing fruiting positions, shedding fewer fruits, and reducing boll weight. The morphology, growth of cotton roots, shoots, yield, and fiber quality are all strongly impacted by salinity stress. It slows down plant feeding, cellular metabolism, and photosynthesis. The soil, water, and climate all affect how the plant responds to salinity stress. During salt stress, excessive exclusion of sodium or its compartmentalization is the key adaptation process in cotton. A major adaptive potential to create cotton types that can withstand salt is provided by the up-regulation of both physicochemical and non-enzymatic antioxidant genes. A successful strategy to increase cotton germination in saline soils is seed priming. Moreover, the transgenic strategy might be a viable choice for improving cotton yield in saline environments. Our review focuses on the impacts of salinity on cotton productivity as well as how plants react to salt stress. It also clarifies recent genetic advancements and molecular breeding for cotton's resistance to soil salt. To create salt-tolerant cultivars, a combination of traditional breeding and novel molecular approaches will be useful.

Global warming has been increasing heat stress threat in animals which can be monitored by Temperature Humidity Index (THI). The present study describes the relationship of THI, calculated using 35 years period weather station data, and production performances of dairy cattle in a se-lected area of Bangladesh. The month January and June were identified as the coolest and hottest, respectively. Based on this outcome, every year in the month of January and June production performances of 10 crossbred cows with homogenous characteristics were monitored for a period of 5 years. The average THIMEAN value was found 17% higher in June as compared to January, and with this increment of THIMEAN average milk production was decreased 24.4% (p<0.05). The milk fat and protein content were also reduced (p<0.05) by 14.5 and 15.2%, respectively suggesting negative correlation as like as milk production. However, ash content was increased 15.3% that indicates a positive correlation. In addition, multiple regression analysis revealed each point increase in THIMEAN and rectal temperature, there was a decrease in milk yield 0.04 and 1.17 kg ECM, respectively. In contrary, each point increase in THIMEAN resulted 0.059 C increase of rectal temperature. Taken together, THIMEAN value calculated using metrological station data has distinct relationship with the production performances of lactating crossbred dairy cows.

Ethylene is an essential plant hormone critical in various physiological processes. These processes include seed germination, leaf senescence, fruit ripening, and the plant's response to environmental stressors. Ethylene biosynthesis is tightly regulated by two key enzymes, namely 1-aminocyclopropane-1-carboxylate synthase (ACS) and 1-aminocyclopropane-1-carboxylate oxidase (ACO). Initially, the prevailing hypothesis suggested that ACS is the limiting factor in the ethylene biosynthesis pathway. Nevertheless, accumulating evidence from various studies has demonstrated that ACO, under specific circumstances, acts as the rate-limiting enzyme in ethylene production. Under normal developmental processes, ACS and ACO collaborate to maintain balanced ethylene production, ensuring proper plant growth and physiology. However, under abiotic stress conditions, such as drought, salinity, extreme temperatures, or pathogen attack, the regulation of ethylene biosynthesis becomes critical for plants’ survival. This review highlights the structural characteristics, examines the transcriptional, post-transcriptional, and post-translational regulation of ACS and ACO, and their role under abiotic stress conditions. Reviews on the role of ethylene signaling in abiotic stress adaptation are available. However, a review that delineates the role of ACS and ACO in abiotic stress acclimation is not available.

Drought and salinity are among the most important abiotic stress factors that limit the productivity in economically important plants. Although genes from wild relatives or unadapted germplasm have often been used for stress tolerance breeding, only few studies have examined wild relatives to understand the genetic and molecular basis of stress tolerance. In this study, we monitored the changes in gene expression profiles of leaf and root tissues of two wild barleys (Hordeum spontaneum L.) accessions from Israel after treatment with salt (NaCl) and drought (PEG) stress. We identified a total of 641 differentially expressed genes across 24 conditions (2 accessions, 2 stress conditions, 2 tissues and 3 time points). Our gene expression analyses revealed large numbers of differentially expressed genes in different accessions by different stress treatments. In addition, the number of genes altered in the leaves of stress-exposed plants of both genotypes was higher than those altered in the roots. Interestingly, there was a relatively little overlap between the leaf and the root stress-responsive gene expression patterns, suggesting that different stress-associated processes might be operating in these tissues during stress adaptation. Overall, our results revealed a number of candidate genes and plant processes associated with stress tolerance in wild barley. Wild barley would be a useful source of new genetic variation for drought and salt stress tolerance. Our results could provide new insights into the mechanisms of drought and salt stress tolerance in wild barley and should be useful for genetic improvement of salt-drought tolerance in cultivated barley.

This paper proposes an AI-based approach to overcome the limitations of the SHM system in measuring global stress with limited sensors. Feature elements are selected based on correlation analysis among finite elements and used as stress-measured points. An ANN is used to establish the solution relationship between the feature and correlation elements. The proposed method is applied to the connector structure of an offshore platform, and an optimal ANN is established to optimize accuracy by considering factors like the number of sensors, neural network framework, and convergence criteria. The accuracy of the ANN is verified through a real-scale model test, demonstrating 93.6% accuracy. This technology represents a significant advancement, enhancing the practicality of the structural health monitoring (SHM) system from “point monitoring" to “field monitoring".

Major depression is accompanied by increased IgM-mediated autoimmune responses to oxidative specific epitopes (OSEs). Nevertheless, these responses have not been examined in bipolar disorder type 1 (BP1) and BP2. IgM responses to malondialdehyde (MDA), phosphatidinylinositol, oleic acid, and azelaic acid were determined in 35 healthy controls, and 101 mood disorder patients, namely 47 major depressed (MDD), 29 BP1, and 25 BP2 patients. We also measured serum total peroxides, IgG to oxidized LDL (oxLDL), IgM to nitroso-adducts, and IgM/IgA directed to lipopolysaccharides (LPS). IgM responses to OSEs were significantly higher in MDD and BP1 as compared with controls and higher in MDD than in BP2. Partial Least Squares (PLS) analysis showed that 57.7% of the variance in the clinical phenome of mood disorders was explained by number of episodes, IgM directed to OSEs and nitroso-adducts, IgG to oxLDL, and peroxides. There were significant specific indirect effects of IgA/IgM to LPS on the clinical phenome, which were mediated by peroxides, IgM OSEs, and IgG oxLDL. Using PLS we have constructed a data-driven nomothetic network which ensembled causome (increased plasma LPS load), adverse outcome pathways (namely neuro-affective toxicity), and clinical phenome features of mood disorders in a data-driven model. Based on those feature sets, cluster analysis discovered a new diagnostic class characterized by increased plasma LPS load, peroxides, autoimmune responses to OSEs and nitroso-adducts, and increased phenome scores. Using the new nomothetic network approach, we constructed a mechanistically transdiagnostic diagnostic class indicating neuro-affective toxicity in 74.3% of the mood disorder patients.

Chitosan (CTS) is widely used in agriculture as a soil amendment, plant growth regulator and promoter of cold resistance. However, the effects of CTS on strawberry seedlings under the combined stress of high-temperature and high-light are unclear. In this study, Xuelixiang strawberry was used as a test material, and 100 mg·kg-1 CTS solution was sprayed onto the leaves. We measured the chlorophyll content, membrane peroxidation, reactive oxygen species content, antioxidant enzyme content, AsA-GSH cycle activity and other related indicators of strawberry seedling leaves under the combined stress of high-temperature and high-light and found that CTS can increase the contents of antioxidants, increase the contents of osmotic adjustment substances, increase the activity of antioxidant enzymes activity,; remove reactive oxygen species over time, reduce the damage of reactive oxygen species to photosynthetic organs and cell membranes, and improve the photosynthesis efficiency of leaves of strawberry plants under high-temperature and high-light stress, thereby reducing damage to strawberry seedlings caused by high-temperature and high-light.

An emerging picture in cancer biology is that, paradoxically, chemotherapy can actively induce changes that favor cancer progression. These pro-cancer changes can be either inside (intrinsic) or outside (extrinsic) the cancer cells. In this review, we will discuss the extrinsic pro-cancer effect of chemotherapy; that is, the effect of chemotherapy on the non-cancer host cells to promote cancer progression. We will focus on metastasis, and will first discuss recent data from mouse models of breast cancer. Intriguingly, despite reducing the size of primary tumors, chemotherapy changes the tumor microenvironment, resulting in an increased escape of cancer cells into the blood stream. Furthermore, chemotherapry changes the tissue microenvironment at the distant sites, making it more hospitable to cancer cells upon their arrival. We will then discuss the idea and evidence that these devastating pro-metastatic effects of chemotherapy can be explained in the context of stress response. At the end, we will discuss the potential relevance of these mouse data to human breast cancer and their implication on chemotherapy in the clinic.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

Membrane transporters (MTs) are mainly localized at the plasma membrane (PM), tonoplast and vacuolar membrane (VM) of cells in all plant organs. Their work is to maintain the cellular homeostasis by controlling ionic movements across PM channels from roots to upper plant parts, xylem loading and remobilization of sugar molecules from photosynthesis tissues in the leaf (source) to roots, stem and seeds (sink) via phloem loading. The plant’s whole source-to-sink relationship is regulated by multiple transporting proteins in a highly sophisticated manner and driven based on different stages of plant growth and development (PG&D), and environmental changes. The MTs play a pivotal role in PG&D in terms of increased plant height, branches/tiller numbers, enhanced numbers, length and filled panicles per plant, seed yield and grain quality. Dynamic climatic changes disturbed the ionic balance (salt, drought and heavy metals) and sugar supply (cold and heat stress). Due to poor selectivity, some of the MTs also uptake toxic elements in the roots that negatively impact on PG&D, later on also exported to upper parts and then deteriorate the grain quality. As an adaptive strategy, in response to salt and HMs plants activated PM and VM localized MTs that export toxic elements into vacuole, and also translocate in the root’s tips and shoot. However, in case of drought, cold and heat stresses, MTs increased the water and sugar supply to all organs. In this review, we mainly reviewed recent literature from Arabidopsis, halophytes, and major field crops such as rice, wheat, maize and oilseed rape to argue on the global role of MTs in PG&D and abiotic stress tolerance. We also discussed the gene expression level changes and genomic variations within a species as well as within a family in response to developmental and environmental cues.

The SnRK gene family is a key regulator playing an important role in plant stress response by phosphorylating the target protein to regulate the signalling pathways. The function of SnRK gene family has been reported in many species but is limited to Triticum asetivum. In this study, SnRK gene family in the wheat genome was identified and its structural characteristics were described. One hundred forty-seven SnRK genes distributed across 21 chromosomes were identified in the Triticum aestivum genome and categorised into three subgroups (SnRK1/2/3) based on phylogenetic analyses and domain types. The gene intron-exon structure and protein-motif composition of SnRKs were similar within each subgroup but different amongst the groups. Gene duplication between the wheat, Arabidopsis, rice and barley genomes was also investigated in order to get insight into the evolutionary aspects of the TaSnRK family genes. SnRK genes showed differential expression patterns in leaves, roots, spike, and grains. Redundant stress-related cis-elements were also found in the promoters of 129 SnRK genes and their expression levels varied widely following drought, ABA and light regulated elements. In particular, TaSnRK2.11 had higher and increased expression under the abiotic stresses and can be a candidate gene for the abiotc stress tolerance. The findings will aid in the functional characterization of TaSnRK genes for further research.

Strigolactones (SLs) are a novel emerging plant hormones, which play important roles in regulating plant organ development and environmental stress tolerance. Even though the SL related genes have been identified and well characterized in some plants. The information of SL related genes in soybean is not fully established yet, especially in response to salt stress. In this study, we identified nine SL biosynthesis genes: two D27, two CCD7, two CCD8, and three MAX1, and seven SL signaling genes: two D14, two MAX2 and three D53 in soybean genome. We found that SL biosynthesis and signaling genes are conserved during evolution in different species. Syntenic analysis of these genes revealed their location on nine chromosomes as well as existence of ten pairs of duplication genes. Moreover, plant hormone and stress-responsive elements were identified in the promoter regions of SL biosynthesis and signaling genes. By using quantitative real-time PCR (qRT-PCR), we confirmed that SL genes have different tissue expression in roots, stems and leaves. Further, we also explored the expression profiles of SL biosynthesis and signaling genes under salt stress. These results suggested that SL signaling genes may play important regulatory roles in response to salt stress. In conclusion, we identified and provided valuable information on the soybean SL biosynthesis and signaling genes, and established a foundation for further functional analysis of soybean SL related genes in response to salt stress.

Background: Drought, N deficiency and herbivory are considered the most important stressors caused by climate change in the agro- and eco-systems and varied in space and time shaping a highly dynamic and heterogeneous stressful environments. This study aims to evaluate the to-mato morpho-physiological and metabolic responses to combined abiotic and herbivory at dif-ferent within-plant spatial levels and temporal scales. Methods: Leaf-level morphological, gas exchange traits and VOC profiles were measured in to-mato plants exposed to N deficiency and drought, T. absoluta larvae and their combination. Ad-ditive, synergistic or antagonistic effects of the single stress when combined were also evaluat-ed. Morpho-physiological traits and VOC profile were also measured on leaves located at three different positions along the shoot axes. Results: The combination of the abiotic and biotic stress has been more harmful than single stress with antagonistic and synergistic but non-additive effects for the morpho-physiological and VOC tomato responses, respectively. Combined stress also determined a high within-plant phenotypic plasticity of the morpho-physiological responses. Conclusions: These results suggest that the combined stress in tomato determined a “new stress state” and a higher within-plant phenotypic plasticity which could permit an efficient use of the growth and defence resources in the heterogeneous and multiple stressful environmental condi-tions.

Parental stresses are normal responses to raising children. They are affected by stresses parents and children accumulate and bring to their interrelations. Background factors like economic difficulties or the relations between the parents may affect parental stresses as well as demographic and environmental factors like noise and access to urban parks. Most studies on parental stress are based on a verified psychological questionnaire. We suggest using frequency domain heart rate variability index (HRV) to measure parental stress enabling, by thus, the measurement of physiological aspects of stress and risk to health. Parental stress is measured as the difference between HRV accumulated at home while staying with the children and without the husband and HRV measured in the neighborhood while staying without the children and the husband. We use the index to compare differences among Muslim and Jewish mothers in exposure to maternal stress at their homes and to expose the factors that predict differences in maternal stress. We found that Muslim mothers suffer from home-related maternal stress while Jewish mother do not. Number of children and ethnically related environmental aspects predict differences in maternal stress between Muslim and Jewish mothers. Muslims' lower access to parks stems from lack of home garden and parks in their neighborhoods in the Arab towns but mainly by restrictions on Muslim women's' freedom of movement to parks. Despite differences in levels of noise at home and in the status of the mother in the household, these factors did not predict differences in parental stress. Instead, the study highlights the crucial role of greenery and freedom of movement to parks in moderating home-related maternal stress.

Three different fields intersect in search of an understanding of the point-of-origin of modern-age diseases: 1) D-amino acids and their role under stress conditions; 2) evolutionary origin of the mitochondrion organelle in the eukaryotic cell; and 3) gut microbiota and human healthHere it is first suggested that D-amino acids function as universal signaling agents, after having evolved as prokaryotic communication, part of an organic communication process that governs the basic activities of all the cells and coordinates cell action.Mitochondria (symbiotic prokaryotic organelles), are creative source of D-amino acids as signaling agents in the central nervous system and in the neuroendocrine systems.Amino acids racemases catalyzes the conversion between the L-enantiomers ( protein building blocks) into D-enantiomers (signaling agents).It is suggested that hectic modern life may affect human health by causing stress to the gut microbiota. These affected, gut microbiota then secrete D-amino acids that enter the blood stream, as signaling agents, causing communication errors in the central nervous system, and in the neuroendocrine systems due to excessive quantity of D-amino acids.Treating gut microbiota with inhibitors of amino acids racemases or finding D-amino acid scavengers may be used in developing novel therapeutic strategies for diseases related to the central nervous system and neuroendocrine systems caused by stressed gut microbiota.

Recently, a breakdown of paracellular and vascular pathways and activated neuroimmune and oxidative pathways were established in (deficit) schizophrenia. The aim of the current study was to delineate a) the differences in these pathways between stable phase, first (FES) and multiple (MES) episode schizophrenia, and b) the pathways that determine the behavioral-cognitive-physical-psychosocial (BCPS)-worsening in FES/MES. This study included 21 FES and 58 FES patients and 40 healthy controls and measured indicants of serum IgA to C1q, and leaky gut, immune activation, and oxidative stress toxicity (OSTOX) biomarkers. We constructed a BCPS-worsening index by extracting a latent vector from symptomatic, neurocognitive, and quality of life data. FES patients showed significantly higher IgA to C1q, cadherin, catenin, plasmalemma vesicle-associated protein, and IgA/IgM to Gram-negative bacteria than FES patients and controls. In FES patients, the BCPS-worsening score was predicted (48.7%) by IgA to Klebsiella pneumoniae and lowered paraoxonase 1 activity. In MES patients, the BCPS-worsening score was explained (42.7%) by increased tumor necrosis factor-α, OSTOX, and number of episodes. In schizophrenia, 34.0% of the variance in the BCPS-worsening score was explained by IgA to K. pneumoniae, OSTOX, and number of episodes. Increased IgA to K. pneumoniae was the single best predictor of residual psychotic symptoms in FES and MES. This study delineated different mechanistic processes in FES, including breakdown of adherens junctions, bacterial translocation, and C1q circulating immune complexes; and FES, including immune and oxidative stress neurotoxic pathways. FES and MES comprise different staging subtypes, i.e., FES and MES with and without worsening.

Hypoxia can induce pulmonary edema (PE) and inflammation. Furthermore, hypoxia depresses left ventricular (LV) inotropy despite sympathetic activation. Here, we investigated the role of nitrosative stress and cardiovascular dysfunction in hypoxic lung injury. Additionally, we studied effects of adrenergic blockade (AB) on hypoxia-induced pulmonary injury. Eighty-six female rats were exposed for 72 h to normoxia or normobaric hypoxia and received infusions with NaCl, prazosin, propranolol or prazosin-propranolol combination. We evaluated hemodynamic function and performed histological and immunohistochemical analyses of the lung. Hypoxia significantly depressed LV but not right ventricular (RV) inotropic and lusitropic functions. AB significantly decreased LV function both in normoxia and hypoxia. AB effects on RV were weaker. Hypoxic rats showed signs of moderate PE and inflammation. This was accompanied by elevated levels of tumor necrosis factor (TNF)  and nitrotyrosine, a marker of nitrosative stress in the lungs. In hypoxia, all types of AB significantly reduced both TNF and nitrotyrosine to normoxic levels. However, AB did not attenuate PE. Results suggest that hypoxia-induced sympathetic activation contributes to inflammation and nitrosative stress in the lungs but not to PE. We suggest that AB in hypoxia aggravates hypoxia-induced inotropic LV dysfunction and backlog into pulmonary circulation, thus promoting PE.

The Easternmost Mediterranean is a junction zone between the largest Earth's lithospheric segments – Eurasian and African-Arabian, and a transition area from the ocean to the continent. The latest catastrophic earthquakes in eastern Turkey require their geodynamic understanding. The two most decisive events (with magnitude (M) = 7.8 and 7.7) were observed with an interval of 9 hours on February 06, 2023, followed by a whole series of about 10,000 significative aftershocks. These tragic events led to the death of more than 60 thousand people. The above values indicate the colossal tension created in the Earth's crust. The region where these strongest earthquakes occurred is a tectonically very complex junction zone of four tectonic plates: Eurasian, Arabian, African, and Anatolian. The joint movement of these plates (consisting, in turn, of tectonic elements of different ages) occurs at an average rate of 6–15 mm per year. However, after two marked powerful shocks and a series of aftershocks, some sectors of the Anatolian plate shifted to the southwest by more than 11 meters. What happened in eastern Turkey? The interaction of numerous factors complicates the tectonic–geodynamic characteristics of the region. Let us analyze what is the most influencing component. Our recent publications (Eppelbaum et al., 2020, 2021) indicated the presence of a giant, rotating quasi-ring structure below the Easternmost Mediterranean. The GPS vector map coinciding with the gravitational trend displays the counterclockwise rotation of this structure. A review of paleomagnetic data on the projection of the discovered structure into the Earth's surface confirms its mainly counterclockwise rotation. Analysis of the magnetic field ΔZ, geoid anomalies map, and seismic tomography data commonly prove the presence of this deep anomaly. The geodynamic and structural characteristics of the region and paleobiogeographic data are consistent with the proposed physical–geological model. A widespread analysis of tectonic, petrological, and mineralogical data implies a connection between the discovered deep structure and near-surface processes. An examination of numerous publications by different authors confirms the above phenomenon’s existence. A crucial for understanding the nature of the considered seismic stress is its location near the expressed bend of the Mesozoic terrane belt, where the Arabian Plate is deeply intruded into the Alpine-Himalayan belt. Thus, the rotation of this giant deep structure may accumulate the stress effect and be one of the causative reasons for the last catastrophic geodynamic events in Eastern Turkey.

Intensive care nurses are highly prone to occupational stress and burnout, affecting their physical and mental health. The occurrence of the pandemic and related events increased nurses’ workload and exacerbated stress and burnout. We conducted a prospective longitudinal mixed-methods study with a cohort of nurses working in a medical ICU (COVID unit; n = 14) and cardiovascular ICU (non-COVID unit; n = 5). Each participant was followed for six 12-hour shifts. Validated questionnaires measured occupational stress and burnout prevalence. Wrist-worn wearable technologies recorded physiological indices of stress. Participants elaborated on the contributors to stress via post-study questionnaire. Data were analyzed using statistical and qualitative methods. Participants who cared for COVID patients at the COVID unit were 3.71 times more likely to experience stress (p &lt; .001) in comparison to non-COVID unit participants. No differences in stress levels were found when the same participants worked with COVID and non-COVID patients at different shifts at the COVID unit. The cohorts expressed similar contributors to stress including communication tasks, patient acuity, clinical procedures, admission processes, proning, labs, and assisting coworkers. Nurses in COVID units, irrespective of whether they care for a COVID patient, may experience high occupational stress and burnout.

The mangrove plant Acanthus ilicifolius and its relative, A. mollis, have been previously proved to possess diverse pharmacological effects. Therefore, evaluating the differentially expressed proteins of these species under tidal flooding stress is essential to fully exploit and benefit from their medicinal values. The roots of A. ilicifolius and A. mollis were exposed to 6 h of flooding stress per day for 10 days. The dry weight, hydrogen peroxide (H2O2) content, anatomical characteristics, carbon and energy levels, and two-dimensional electrophoresis coupled with MALDI-TOF/TOF MS technology were used to reveal the divergent flooding resistant strategies. A. ilicifolius performed better under tidal flooding stress, which was reflected in the integrity of the morphological structure, more efficient use of carbon and energy, and a higher percentage of up-regulated proteins associated with carbon and energy metabolism. A. mollis could not survive in flooding conditions for a long time, as revealed by incomplete cell structures of the roots, less efficient use of carbon and energy, and a higher percentage of down-regulated proteins associated with carbon and energy metabolism. Energy provision and flux balance played a role in the flooding tolerance of A. ilicifolius and A. mollis.

Hemodialysis (HD) patients experience significant psychological stress related HD. Coping strategies are utilized to help these patients cope with this stress. Prevalence of different types of coping strategies in relation with differential levels of HD-related stress scores and by demographics were assessed. HD patients aged 18 years and above who were seeking regular treatment in a specific HD-unit of a hospital in the upper Midwest, were surveyed between March 2020 and July 2020. Descriptive statistics, correlational analyses, and regression analyses were performed. Females could be expected to have emotional coping scores 8 units greater than males, as B = 8.017 for sex in the model, p =.000. Females could be expected to have coping scores 6.4 points higher than males when adjusted for stress levels, as: B = 6.351, p =.001 for sex in the model. For each 1point increase in Stress Score, the Coping Score could be expected to: increase 6.8 points when adjusted for Sex, where B = 6.751 and p =.000. Increased prevalence of emotional pre-occupation was only observed among female patients which increased with the increase in stress. Psychological interventions in female HD patients should be strongly considered in addressing emotional pre-occupation coping.

Abstract: Kiwifruit, a perennial horticultural crop known for its nutritional value, faces significant challenges due to biotic and abiotic stresses, affecting its yield and quality. Leucine-rich repeat receptor-like proteins (LRR-RLPs), a major group of receptor-like proteins in plants, have diverse functions in plant physiology, including growth, development, signal transduction, and stress responses. Despite their importance, the specific roles of kiwifruit LRR-RLPs in response to biotic and abiotic stresses remain poorly understood. In this study, we investigated the expression patterns of kiwifruit LRR-RLPs under various stress conditions, including pathogen stress, heat stress, waterlogging stress, and copper stress. Through genome and transcriptome analyses, we identified a total of 101, 164, and 105 LRR-RLPs in Actinidia Chinensis 'Hongyang', Actinidia eriantha 'Huate', and Actinidia chinensis 'Red5' kiwifruit, respectively, classified into 9 subgroups based on phylogenetic relationships. Synteny analysis revealed that the expansion of kiwifruit LRR-RLPs was primarily attributed to segmental duplication events. Using RNA-seq data from pathogen-infected kiwifruits, we identified specific LRR-RLP genes potentially involved in different stages of pathogen infection. Additionally, we observed the potential involvement of kiwifruit LRR-RLPs in abiotic stress responses, with upstream transcription factors possibly regulating their expression. Furthermore, protein interaction network analysis unveiled the participation of kiwifruit LRR-RLP genes in the regulatory network of abiotic stress responses. These findings highlight the crucial roles of LRR-RLPs in mediating both biotic and abiotic stress responses in kiwifruit, offering valuable insights for the breeding of stress-resistant kiwifruit varieties.

Background: Clinical trails have revealed that patients with depression generally accompanied with learning and memory impairment, which critically impact on individual’s health and development. Danggui-Shaoyao-San (DSS), a famous Chinese complex prescription, significantly overcame depression and relieved cognitive disorder based on previous research and publication. However, its effectsand potential mechanism against chronic restraint stress (CRS) remained unknown. Methods: CRS animal model was established and mice were divided to six groups while they were oral administrated with Danggui-Shaoyao-San at doses of 1.25, 2.5 and 5 g/kg for 14 days. Emotional and cognitive performances were detected by behavior tests, meanwhile neural plasticity and its molecular mechanism were examined by Dil staining, western blot and immunofluorescence. Results: DSS treatment dose-dependently improved locomotion ability in open filed test, overcame depression behavior in forced swimming test and elevated plus maze test, enhanced learning and memory ability in Morris water maze test. CRS decreased number of total spines and mushroom spines, while DSS treatment dose-dependently restored these by Dil staining. Expression of BDNF and GluR1 were significantly down-regulated in CRS group, which were significantly normalized by DSS. Conclusions: DSS treatment dose-dependently reversed CRS-induced cognitive impairments by inducing structural remodeling of neurons.

The present work deals with the development of finite element methodology for obtaining the stress distributions in thick cylindrical HK40 stainless steel pipe that carry high temperature fluids. The material properties and loading are assumed to be random variables. Thermal stresses that are generated along radial, axial and tangential directions are computed generally using analytical expressions which are very complex. To circumvent such an issue, the probability theory and mathematical statistics have been applied to many engineering problems which allows to determine the safety both quantitatively and objectively based on the concepts of reliability. Monte Carlo simulation methodology is used to study the probabilistic characteristics of thermal stresses which is used for estimating the probabilistic distributions of stresses against the variations arising due to material properties and load. A 2-D Probabilistic finite element code is developed in MATLAB and the deterministic solution is compared with ABAQUS solutions. The values of stresses that are obtained from the variation of elastic modulus are found to be low as compared to the case where the load alone is varying. The probability of failure of the pipe structure is predicted against the variations in internal pressure and thermal gradient. These finite element framework developments are useful for the life estimation of piping structures in high temperature applications and subsequently quantifying the uncertainties in loading and material properties.

The reason for excessive multidecade deflections is still unclear after 70 years of the cantilever method that has been applied in building large-span segmental concrete bridges. The failure of the Koror-Babeldaob bridge gives the author a clue that the reason might be the boundary condition. The asymmetric properties of the bearing and prestress tendon draw the author’s attention. To understand the process of stress redistribution, the virtual stiffness method which is derived from the principle of minimum potential energy was created, and the phenomenon the author suggested named Material Inelasticity and Prestress Loss Coupling Effect is discovered. The unexplainable excessive deflection and prestress loss are found in the new load model. The calculation of excessive deflection is discussed. The new model fits the experience well. The optimization design methods and construction key points are proposed.

Peptides of hydrolysates of food proteins are an easily digestible source of amino acids necessary for the body to adapt to physical stress. Commercially significant hydrolysates include whey protein, casein, and other animal proteins. Hydrolysates of plant proteins are gaining popularity, but they are less common, then animal ones. Soy protein isolate is promising for obtaining the hydrolysates due to its affordable price and balanced amino acid profile. However, there are no direct studies showing an improvement in the result of physical activity when eating soy protein isolate hydrolysate (SPIH). In this work, for the first time, the study was conducted on the safety and efficacy of SPIH during physical load on model animals (rats). It was shown that the hydrolysate did not lead to pathological changes in the viscera, food intake, and weight of animals did not differ from the control group (animals consumed whey protein). Under physical load rats enteral fed SPIH showed a tendency to adapt more quickly to physical stress than the control group and the group of animals that was fed by free amino acids. The metabolites of animal blood serum were studied by NMR spectroscopy. It was shown that by the 95th minute after feeding in the group of rats receiving SPIH, the difference of proteinogenic amino acids concentrations in blood between individuals was significantly less than in the groups receiving whey protein or a mixture of amino acids. In other words, individual biochemical and physiological characteristics of individuals did not affect the assimilation of amino acids of hydrolysate.

The physiological response to a psychological stressor broadly impacts energy metabolism. In-versely, changes in energy availability affect the physiological response to the stressor in terms of hypothalamus, pituitary adrenal axis (HPA) and sympathetic nervous system activation. Glu-cocorticoids, the endpoint of the HPA axis, are critical checkpoints in endocrine control of ener-gy homeostasis and have been linked to metabolic diseases including obesity, insulin resistance and type 2 diabetes. Glucocorticoids, through the glucocorticoid receptor, activate transcription of genes associated with glucose and lipid regulatory pathways and thereby control both physi-ological and pathophysiological systemic energy homeostasis. Here, we summarize the current knowledge of glucocorticoid functions in energy metabolism and systemic metabolic dysfunc-tion, particularly focusing on glucose and lipid metabolism. There are elements in the external environment that induce lifelong changes in the HPA axis stress response and glucocorticoid levels, the most prominent are early-life adversity, or exposure to traumatic stress. We hypothe-sise that when the HPA axis is so disturbed after early-life adversity, it will fundamentally alter hepatic gluconeogenesis, inducing hyperglycaemia, and hence crystalise the significant lifelong risk of developing either the metabolic syndrome, or type 2 diabetes. This gives a “Jekyll and Hyde” role to gluconeogenesis, providing the necessary energy in situations of acute stress, but driving towards pathophysiological consequences when the HPA axis has been altered.

Abstract: Extensive research shows nurses’ work environment to be particularly stressful. This study develops, explores, and psychometrically tests a new profession specific ques-tionnaire identifying generalized and specific resistance resources, that make it possible to measure resources to manage work-related stress. An exploratory study design was em-ployed. The questionnaire was developed inspired by the MEASURE approach and the salutogenic theory of health. Building on the results from a literature review of nursing re-search and salutogenesis, supplemented by twelve interviews with hospital nurses, an item pool was generated. A first version was pilot tested in a group of nurses who were studying to become specialist nurses. A second version of the questionnaire was psycho-metrically tested on nurses in close patient care (n = 475), analysed using Principal Com-ponent Analysis as the extracting technique to identify the underlying structure of the questionnaire. The Principal Component Analysis revealed a four-component model of 19 items. “Manageability as a resource for handling the workload” was the strongest compo-nent, accounting for 21 % of the explained variance. “Contacts with patients as resources for nurses’ job satisfaction” (17.8 %). “Professional attitudes are labelled as resources to nursing” (15 %). “Colleagues are important resources for remaining in the nursing profes-sion” (11 %). The structure of the questionnaire indicates its usefulness in clinical practice for measuring resistance resources.

The present study evaluates ratcheting response of notched and press-fitted Al 7075-T6 specimens under stress-controlled asymmetric cycles. The degree of interference fit (DIF) directly influenced progressive plastic strain magnitude and rate at notch root region. Local ratcheting at the hole-pin interference region was analyzed by means of two kinematic hardening rules of Ahmadzadeh-Varvani (A-V) and Chaboche coupled with the Neuber rule. Ratcheting strains at notch root of aluminum samples with DIF=0 (non-press-fitting samples) were measured to be highest in magnitude. For the press-fitted samples, however ratcheting strains dropped noticeably as DIF increased from 1% to 2%. Press-fitted samples plastically deformed the perimeter edge of notches and improved materials locally at the notch edge, resulting in a better resistance against ratcheting progress. Local ratcheting at different distances of 0.5, 1.3 and 3.0 mm from the notch root were evaluated for both pinned and unpinned samples through the hardening rules and compared with those of measured values. The predicted ratcheting curves by means of the A-V and Chaboche hardening rules closely agreed with experimental data and respectively positioned above and below the measured data.

Disulfiram (DSF), an anti-alcoholism medicine, exerts treatment effects in patients suffering from persistent Borreliosis and also exhibits anti-cancer effects by its copper chelating derivatives. Since chronic/persistent borreliosis is characterized by increased amounts of proinflammatory macrophages, this study investigated opsonin-independent phagocytosis, migration and surface marker expression of in vivo activated human monocyte-derived macrophages and dendritic cells with and without DSF treatment. Phagocytosis of non-opsonized Dynabeads® M-450 and migration of macrophages and dendritic cells were monitored using live cell analyzer Juli™ Br for 24h by imaging every 3.5 min. Results were analyzed by a newly developed software based on the differential phase contrast images of cells before and after ingestion of Dynabeads bearing an electron dense iron core. As a control, phagocytosis was also monitored by visual counting of ingested beads. DSF decreased the phagocytic capacities exhibited by global macrophages and dendritic cells. DSF also impaired the migration of human monocyte-derived macrophages and dendritic cells (hMDMD) and significantly reduced the expression densities of surface antigens CD45 and CD14. In cells consisting of anti-inflammatory M2 macrophages, DSF led to a remarkable cell death and also increased oxidative stress as determined by MitoSox staining. Mitochondrial oxidative stress was a prominent feature in M2 macrophages which were more sensitive to DSF-induced cytotoxicity.

This paper presents an in-depth study of the stress wave behavior propagating in a Rayleigh–Love rod with a sudden cross-sectional area change. The analytical solutions of stress waves are derived for the reflection and transmission propagation behavior at the interface of the cross-sectional area change in the rod, considering inertia and Poisson’s effects. Examples solved by the finite element method are provided to verify the correctness of the analytical results. In addition to the forward analysis of Rayleigh–Love wave propagation in rods impacted by a striker rod, a nondestructive testing method is proposed to conduct the defect assessment in the rod type of the structure component with a sudden cross-sectional area change within a cover medium by using the measured signals at the measurable zone of the rod to be inspected.

There is a general lack of research involving older lesbian, gay, bisexual, transgender, and queer/questioning (LGBTQ) people. This systematic review aimed to synthesize Japanese and Swedish qualitative research on LGBTQ people aged 60 years or older. PRISMA guidelines were followed. Japanese and Swedish articles, published in English-language journals, were searched across PsychINFO, Medline, CINAHL, and Sociological Abstracts databases. Additional searches were carried out to include studies written in Japanese or Swedish. There were no papers from Japan, and five from Sweden were reviewed. Four articles were included, including 48 participants aged 60–94 years. We summarized the findings using a deductive thematic synthesis. Two major themes emerged: (a) quality of life, minority joy, and resilience (positive aspects), and (b) experiences of discrimination, stigmatization, and minority stress (negative aspects). The participants described a wish to be acknowledged for their own assets and unique life histories, and to be treated as everyone else. They emphasized the importance of knowledge of LGBTQ issues among nursing staff, so that older LGBTQ people are treated in a competent and affirmative way. The study revealed several important topics for understanding older LGBTQ people’s life circumstances and the severe lack of qualitative studies in Japan and Sweden.

Background: According to metacognitive theory, Cognitive–Attentional Syndrome (CAS) is a transdiagnostic factor and main mechanism of psychopathology maintenance. The main goal of this study was to examine whether CAS predicted symptoms of stress and trauma-related symptomatology in the first months of the COVID-19 pandemic and three months later. Methods: Initially 1,792 participants were recruited online via social media; data was collected at two time points. Measures included the Cognitive–Attentional Syndrome Questionnaire, Adjustment Disorder – New Module 20, the International Trauma Questionnaire, and additional measures. Results: Structural equation modeling was conducted in order to determine relations between reported stressors, CAS, and symptomatology. At both time points, CAS was a significant mediator between stressors and symptoms of adjustment disorder. Despite the decrease in the intensity of adjustment disorder symptoms between waves, it was a significant predictor of other psychopathology at both time points, except for traumatic stress. Conclusions: The findings confirm the assumption that CAS is a transdiagnostic factor of psychopathology, and has a mediating role in the relationship between stressors and adjustment disorder and co-occurring symptomatology. The effect was particularly significant in the initial phase of the pandemic, which was highly stressful for many people.

Increased screen time during the COVID-19 pandemic and the accelerated incorporation of technology into daily practices have directly contributed to the increased prevalence of eye disease. The human eye is not built for continual technological use and must adjust to exposure to digital screens. Overexposure to technology can result in eye strain and an increased risk of eye diseases such as myopia with complications later in life, including retinal tears, cataracts, and macular degeneration. As vision and ocular diseases become more prevalent, the study of eye diseases, including their causes and treatments, is especially relevant. There is a need to prevent ocular diseases before they become a burden to individuals, their families, and their communities by better understanding the pathophysiology of ocular diseases. Several ocular diseases are thought to be caused by imbalances in reactive oxygen species (ROS) and autophagy. ROS refers to a class of highly reactive oxygen-containing molecules that can undergo damaging reactions with other molecules in the cell. Autophagy is a cellular process of self-eating whereby damaged, harmful, or dead material in cells is broken down to maintain cellular homeostasis. This paper discusses the role of ROS and autophagy in the pathogenesis of computer vision syndrome (CVS), digital eye strain (DES), myopia, cataracts, glaucoma, diabetic retinopathy (DR), age-related macular degeneration (AMD), optic nerve crush injury (OCN), optic nerve gliomas, and retinoblastoma. Lifestyle changes such as limiting screen time, ensuring adequate exposure to evening sunlight, and using blue light protection measures or protective eyewear are important in the prevention of eye disease. Nutrition also contributes significantly to eye health. A balanced diet rich in vitamins and antioxidants may help to prevent ROS and autophagy imbalance-induced eye disease. Medical and surgical treatments become necessary when preventative measures fail. This paper also addresses how government measures to decrease the onset of eye disease, including targeted programs to increase access to fresh vegetables and fruits in food deserts, are a critical macro-level avenue to reduce eye disease prevalence in the US, which according to the National Eye Institute, costs $139 billion yearly.

This paper presents a theoretical analysis of an International conflict, i.e. East Pakistan Crisis, 1971, and reveals that unequal development creates conflict in society. Natural resource scarcity and environmental degradation can also become a source of conflict, so marginalised and excluded people fight for their rights through non-peaceful means. This essay supports the theoretical approaches of poverty, environment, and conflict nexus and reveals that unequal development and resource scarcity deepens the poverty and creates conflicts in the society, causing harm to the environment. The degraded environment increases the poverty as environment and poverty are interlinked, and the poor have limited choices other than to degrade the environment for their survival. This vicious downward spiral link between poverty and degradation of the environment requires working extensively for poverty alleviation to reverse the environmental decline.

This paper reinterprets, differently from the existing literature, the relationship between law and economics not from the point of view of a lawyer-economist but rather from the point of view of an economist-mathematician, and it raises a methodological issue. To do so, some of the elements of the theory of sets are borrowed to argue that behavioral economics, its application to behavioral law and economics, and behavioral economists have generalized the pioneering work of Judge Calabresi, with reference to the famous books ‘Tragic Choices’ and ‘The Future of Law and Economics – Essays in Reform and Recollection’. Even if the usage of the theory of sets made in this paper is intuitive, some of its basics are reviewed in the appendix.

Ethylene, a gaseous phytohormone, is emerging as a central player in the intricate web of plant developmental processes from germination to senescence under optimal and stressed conditions. It is present in different plant parts, encompassing the stems, leaves, flowers, roots, seeds, and fruits. This review aims to provide a comprehensive overview of ethylene's fascinating roles in shaping various plant growth and adaptation aspects. It intricately examines the multifaceted impact of ethylene on pivotal aspects of plant development, including but not limited to cell division and elongation, senescence, abscission, fruit and flower development, root hair formation, chloroplast maturation, and photosynthesis. This comprehensive assessment encompasses the intricate pathways of ethylene biosynthesis and signaling, providing a snapshot of the regulatory mechanisms governing ethylene production. Understanding ethylene's multifaceted functions has significant implications for agriculture, biotechnology, and our fundamental comprehension of plant biology. This review underscores the need for continued investigation into ethylene's intricate mechanisms and its potential to revolutionize plant development and crop management.

Satisfactory weatherproofing of buildings is vital to maximise their design life and performance which requires the careful design of external sealing technologies. Systems commonly available have served well in conventional construction however with many prefabricated systems emerging in the building industry new and novel means of weatherproofing between panels and modules need to be developed purpose specific to this application. This paper presents a holistic and fundamental methodological approach to Design and Development of waterproof seals and has been applied specific for prefabricated panelised and modular systems. Two purpose specific weatherproof seals are finally presented. Flow charts of the overview of the suggested methodological approach and the processes within which include DfMA that have been incorporated into understanding and developing seals for this practical application. These strategies have enabled a resourceful and holistic set of processes that can be adapted and used for similar forms of product research in new and developing areas of construction such as prefabrication. The design and development process is thoroughly explored and has resulted in an exploration of the technical challenges and potential solutions which take into consideration factors from installation limitations to building tolerances.

We study on the sums of powers of consequtive integers and alternating sums of power of consequtive integers. We derive many identities and correlations including Bernoulli, Euler and Genocchi polynomials and numbers.

Introduction: Since its discovery in late 2019, the novel coronavirus (SARSCOVID-2) that causes COVID-19 has spread fast, prompting the World Health Organization (WHO) to designate the disease a worldwide pandemic on March 11, 2020.The epidemic has profoundly altered the preexisting global sexual and reproductive health landscape .The virus’s load has put ordinary services in jeopardy and harmed other health priorities. This encompasses both the provision and the supply of contraceptives, sexual health, new born and maternal health services. This Scoping review therefore mapped the availability evidence on the impact and effects of the COVID-19 disease outbreak on sexual and reproductive health. Methods: The methodological framework by Arksey and O’Malley guided this scoping review. A literature search was conducted from the following databases: Embase, PubMed, CINAHL, Scopus, WOS, and AJOL. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram and the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) checklist were used to document the review process. The Strobe critical review checklist was used to determine the quality of the included studies. Results:19 studies were reviewed, out of which 4 were cross sectional studies, 1 was an observational study, 1 was a descriptive analytical study and the rest were qualitative studies .Majority of the studies showed evidence on the impact of COVID-19 and family planning service, maternal and child services, and three studies reported on COVID-19 and sexual behaviour. Five of the nineteen included studies reported on the impact of COVID-19 and family planning service. Conclusion: This scoping review has granted the assessment of the impact of novel SARS-CoV-2 on Sexual and reproductive health services with regards to sexual behaviour, family planning and maternal, neonatal and child health. From the 18 articles identified and reviewed, the overall responses stipulated a significant reduction in client’s utilization of services due to challenges experiences in service implementation such as stock outs. In addition, low demand for reproductive health services by clients due to restrictions imposed on the movements of people to curb the spread of the virus. It is therefore important that Governments and relevant stakeholders in Maternal and Sexual Reproductive Health prioritize development of policies and practices that protect women from the impacts of the pandemic. Furthermore, regular audits to detect trends in MSRH are necessary to inform on going mitigation efforts.

This paper analyzes the political and economic changes in the world after the drastic changes in eastern Europe, starting with Chinese President Xi Jinping's viewpoint "the biggest change in a century". Also, the new international situation and new development in the post-epidemic as well as the development path and direction of China in the post-epidemicera are expected.

The objective of this study is to determine the impact of COVID-19 on the performance of Pakistani Stock Market. This study uses the data of COVID-19 related positive cases, fatalities, recovers and the closing prices of PSX 100 index of the first half of 2020. The findings of the study suggest that only COVID-19 recoveries are influencing the performance of the index and the daily positive cases and fatalities are insignificantly related to the performance. Further studies can be performed by incorporating other variables such as economic growth, interest rate and inflation rate along with the COVID-19 related variables at a cross-country level.

Biomolecular structure drives function, and computational capabilities have progressed such that the prediction and computational design of biomolecular structures is increasingly feasible. Because computational biophysics attracts students from many different backgrounds and with different levels of resources, teaching the subject can be challenging. One strategy to teach diverse learners is with interactive multimedia material that promotes self-paced, active learning. We have created a hands-on education strategy with a set of fifteen modules that teach topics in biomolecular structure and design, from fundamentals of conformational sampling and energy evaluation to applications like protein docking, antibody design, and RNA structure prediction. Our modules are based on PyRosetta, a Python library that encapsulates all computational modules and methods in the Rosetta software package. The workshop-style modules are implemented as Jupyter Notebooks that can be executed in the Google Colaboratory, allowing learners access with just a web browser. The digital format of Jupyter Notebooks allows us to embed images, molecular visualization movies, and interactive coding exercises. This multimodal approach may better reach students from different disciplines and experience levels as well as attract more researchers from smaller labs and cognate backgrounds to leverage PyRosetta in their science and engineering research. All materials are freely available at https://github.com/RosettaCommons/PyRosetta.notebooks.

To better understand how immunity develops against SARS-CoV-2 during the pandemic period of 2020 to 2022, we analyzed the immune response of a small group of university staff and students who were either infected or vaccinated. We investigated the levels of receptor-binding domain (RBD)-specific and nucleocapsid (N)-specific IgG and IgA antibodies in serum and saliva samples taken early (around 10 days after infection or vaccination) and later (around 1 month later), as well as N-specific T-cell responses. One patient who had been infected in 2020 developed serum RBD and N-specific IgG antibodies, but declined 8 months later, then mRNA vaccination in 2021 produced a higher level of anti-RBD IgG than natural infection. In the vaccination of naïve individuals, vaccines induced anti-RBD IgG, but it declined after 6 months. A third vaccination boosted the IgG level again, albeit to a lower level than after the second. In 2022, when the Omicron variant became dominant, familial transmission occurred even among vaccinated people. In infected individuals, the levels of serum anti-RBD IgG antibodies increased later, while anti-N IgG peaked earlier. The N-specific activated T cells expressing IFN- or CD107a were detected early. In saliva, SARS-CoV-2-specific IgG but not IgA was detected. Interestingly, two individuals showed a temporary peak in RBD- and N-specific IgA antibodies in their saliva on the second day after infection. Thus, SARS-CoV-2 infection triggers typical immune responses in humans against acute viral infections, but mucosal immune responses, which are temporarily induced early during infection, may be more important for protection than current intramuscular vaccines.

The determinants of enterprises providing ICT training in Europe are analyzed in this article. Data are collected from the European Innovation Scoreboard-EIS of the European Commission for 36 European countries in the period 2000-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, Dynamic Panel, WLS and Pooled OLS. Results show that the number of enterprises providing ICT training in Europe is positively associate with “Innovation Index”, “Innovators”, “New Doctorate Graduates”, “Tertiary Education” and negatively associated with “Government Procurement of Advanced Technology Products”, “Human Resources”, and “Marketing or Organisational Innovators”. In adjunct a cluster analysis is performed by using k-Means algorithm optimized with the Silhouette Coefficient and we find the presence of four clusters. Finally, we use eight different machine learning algorithms to predict the value of the enterprises providing ICT training in Europe. We found that the Simple Tree Regression is the best predictor and that the number of enterprises providing ICT training in Europe is expected to growth of the 5,02%.

Prefabricated forms of construction have led to the rapid onsite assembly of buildings however there are still on-site tasks and processes which can be reevaluated and redone specifically in keeping with the principles of prefabrication instead being adapted to fit its purpose. One such process is that of waterproofing between prefabricated panels and modules which come from the factory fully complete façade and all. Conventional means of waterproofing can be used however it results in more work done on site, potential delays and generally requires access from the external face of the building. This paper presents the Modelling, Implementation and Evaluation of purpose developed weatherproof seals specific for Prefabricated Construction. An overview is provided of the entire development process and specific focus is given to the modeling using FEA computer simulations, manufacturing and testing which then resulted in the implementation in a prefabricated panelised building which is used as a case study and the means of further evaluation. These strategies have enabled an efficient and robust prefabricated waterproofing solution specific for this form of construction to be understood and implemented. The resulting case study has successfully verified the time and cost savings when compared to conventional techniques whilst still providing a durable and effective weatherproof seal for prefabricated panelised and modular systems.

Coating of suitable materials having thickness of few atoms to several microns on a substrate is of great interest to the scientific community. Hard coatings develop under the significant composition of suitable-natured atoms where their force-energy behaviors when in certain transition state favour binding. In the binding mechanism of suitable atoms, electron belonging to outer ring filled state of gas-atom undertakes another clamp of energy knot belonging to outer ring unfilled state of solid-atom. Set process conditions develop the binding of different-natured atoms when processing their suitable composition in a system. Atoms of different nature develop structure in the form of hard coating by locating their ground points between the original ones. Here, gas-natured atoms increase the potential energy under decreasing levitational force of electrons, whereas, solid-natured atoms decrease the potential energy under decreasing gravitational force of electrons. In TiN coating, Ti–Ti atoms bind under the difference of expansion of their lattices, called nets of energy knots, where one atom just lands on the already landed atom. An adhered N-atom to a Ti-atom forms its position among four Ti-atoms where N-atom occupies the interstitial site of Ti-atoms. Two oppositely working force-energy behavior atoms deposit in the form of coating at substrate surface as per set conditions of the process. The rate of ejecting (or dissociating) solid-natured atoms depend on the nature of their source (target), process parameters and processing technique. In random arc-based vapor deposition system, depositing differently natured atoms at substrate surface depends on the input power. In addition to intrinsic nature of atoms, different properties and characteristics of coatings emerge as per engaged forces under their involved energy. The present study sets new trends in the field of coatings involving the diversified class of materials and their counterparts.

Employing data supplied by the Oxford-based UK Childhood Cancer Research Group in 2003 it is shown that after the Chernobyl accident, childhood leukemia by single age and year of birth in the 0-4y cohort increased significantly in Wales and Scotland combined in the period 1986-1990 compared with controls born 1970-1985 and 1991-1994. Relative risk RR = 1.41; 95% CI 1.20<RR<1.65; p = 0.00004. These exposure periods were chosen because whole body Caesium-137 monitoring had demonstrated that internal exposures persisted for more than 4 years. The dose-response exhibits saturation and reversal, interpreted as biological censoring effects in the developing individual.

This paper presents a two-way factor design incorporating both spatial and temporal variation in the prediction of COVID 19 in Africa. In line with this, the impact of COVID-19on the GDP in Africa is well scrutinized. In contrast to the existing works [1–3], this work also extends the two-factor design into the one-way factor design through incorporating covariates into spatial effects. The data rely on the spatial and temporal obtained from WHO datasets [4, 5]. The one-factor design with more covariates is taken into consideration to identify the major potential predictor variables responsible for the deaths and confirmed cases due to COVID 19 in Africa. The MANCOVA considered population density, temperature, humidity; perception, and wind are all considered as co-variates. Simulations show that the two-way analysis of variance has shown that there is a statistically significant difference between the spatial (Fcal= 8.2704, Pvalue= 3.099∗10−6)and temporal (Fcal= 48.7964, Pvalue= 9.147∗10−16) effects. South Africa and Nigeria are highly influencing due to the pandemic where their GDP also relatively mostly declined. A significant economic change is observed before the pandemic and after the outbreak of the pandemic(tcal= 2.9548, Pvalue= 0.01805). COVID 19 negatively influenced the economy of1 most of the African countries. The population density, temperature, and wind are found to be statistically significantly associated with COVID 19 cases and deaths.

Textile and clothing is one of the most important industrial sectors, not only due to the significant number of jobs generated, but also because it addresses one of the people’s fundamental needs (clothing). It is, however, a sector with a huge environmental impact, all over the world, and also an important social impact, especially in developing countries. Sustainability in the Textile &amp; Clothing value chain is a known issue, concerning both environmental, and economical-social facets of sustainability. One way to improve sustainability in this sector is by measuring the environmental, economic and social impacts of value chain activities and, ultimately, computing an Environmental and Circular score for each batch of textile and clothing product, and an Economical and Social score for each involved firm, reflected in their products. The consumer will then have the opportunity and responsibility for selecting products with the least negative environmental, economical and social impact. This article presents the results of STVgoDigital project - PPS1, developed in Portugal with the aim of implementing the traceability of textile and clothing products, boosting sustainability in this sector, and preparing the ground for the implementation of the circular economy. More exactly, a blockchain-based textile and clothing value-chain traceability platform is presented, for tracing textile product lots and activities, along the value chain, classifying them with a score, which measures their environmental and social impact. The environmental, economic and social impact scores are based on a set of proposed indicators. The results are assessed through the presentation of a case study of a face towel (home textile) and a case study of a T-shirt (clothing).

Identification of Dengue drivers is crucial for pro-active prevention strategies. In semi-arid regions, the relationship between meteorological variables, particularly rainfall, and the dengue vector is complex. This study analyzes associations between the number of dengue cases and rainfall categories in six semi-arid locations in India. Focusing on official website data, we find significant correlations only with heavy rainfall (R>10 mm/day). The findings underscore the importance of heavy rainfall in Dengue incidence and offer insights for pro-active prevention. The study methodology involves rainfall and dengue occurrence over Indian region. This research contributes to the growing body of knowledge on Dengue prevention, emphasizing the need for targeted interventions during periods of heavy rainfall.

Political and legal debate about freedom of religion and belief (FoRB) in Australia has intensified since the Same-sex marriage postal survey in 2017. Central to this debate has been children, their parents and institutions (Schools). This paper outlines the place of children in the Australian FoRB since 2017, focusing on the Same-sex marriage postal survey debate and subsequent reviews into freedom of religion. In particular it highlights the links drawn between same-sex marriage or marriage equality and the Safe School Coalition Australia campaign, the emphasis on parental rights in relation to education about marriage in schools and the ongoing debate about potential reform to Australia’s suit of anti-discrimination laws

Orthogonal operators can successfully be used to calculate eigenvalues and eigenvector compositions in complex spectra. Orthogonality ensures least correlation between the operators and thereby more stability in the fit, even for small interactions. The resulting eigenvectors are used to transform the pure transition matrix into realistic intermediate coupling transition probabilities. Calculated transition probabilities for close lying levels illustrate the power of the complete orthogonal operator approach.

Epistemological naturalism dismisses the notion that epistemology is a basis for the empirical sciences. In particular, it rejects the demand for a general justification of induction. Making inductive generalisations is a basic habit among humans. There is no such thing as a logic of inductive inference. The role of induction in science is heuristic; it is our way of inventing new theoretical predicates and developing theories. We discover new laws by applying inductive thinking; but this is not any kind of inference which can be evaluated as more or less rational.

Background: This research examines how market knowledge and artificial intelligence (AI) interact in different market designs such as business-to-business (B2B) settings while taking emerging technologies and the changing digitalization landscape into account. Objective: The main goal is to understand how AI affects market knowledge in different market designs such as business-to-business (B2B) contexts, taking into account language barriers, practical difficulties, and the revolutionary effects on decision-making and customer interactions. Result: They underscore the transformative potential of artificial intelligence (AI) by highlighting how it shapes market knowledge, encourages customized approaches, and improves marketing efficacy in the business-to-business (B2B) space. Conclusion: In order to create a path for responsible AI integration in B2B marketing, the study concludes with recommendations for standardized terminology related to AI, practical insights into implementation challenges, and ethical issues.

The concept of {\it quantum ratio} emerged in the recent efforts to understand how Newton's equations appear for the center of mass (CM) of an isolated macroscopic body at finite body-temperatures, as the first approximation to quantum-mechanical equations. It is defined as $Q\equiv R_q/L_0$, where the quantum fluctuation range $R_q$ is the spatial extension of the pure-state CM wave function, whereas $L_0$ stands for the body's linear size (the space support of the internal, bound-state wave function). The two cases $R_q /L_0 \lesssim 1$ or $R_q/ L_0 \gg 1$, roughly correspond to the body's CM behaving classically or quantum mechanically, respectively. In the present note we elaborate more on this concept, illustrating it in several examples. An important notion following from introduction of the quantum ratio is that the elementary particles (thus the electron and the photon) are quantum mechanical, even when the environment-induced decoherence turns them into a mixed state. Decoherence and classical state should not be identified. This simple observation, further illustrationed by the consideration of a few atomic or molecular processes, may have significant implications on the way quantum mechanics works in biological systems.

The use of artificial intelligence (AI) is becoming more prevalent across industries as diverse as healthcare, finance, and transportation. Artificial intelligence is based on the analysis of large data sets and requires a continuous supply of high-quality data. However, using data for AI is not without its challenges. This paper comprehensively reviews and critically examine the challenges of using data for AI, including data quality, data volume, privacy and security, bias and fairness, interpretability and explainability, ethical concern, and technical expertise and skills. This paper examines e these challenges in details and offers advices on how companies can address them. By understanding and addressing these challenges, organizations can harness the power of AI to make smarter decisions and gain a competitive advantage in the digital age.

NACA 0015 and NACA 4415 aerofoil are most common four digits and broadly used aerodynamic shape. Both of the shapes are extensively used for various kind of applications including turbine blade, aircraft wing and so on. NACA 0015 is symmetrical and NACA 4415 is unsymmetrical in shape. Consequently, they have big one-of-a-kind in aerodynamic traits at the side of widespread differences of their utility and performance. Both of them undergo the same fluid principle while applied in any fluid medium giving dissimilar outcomes in aerodynamics behavior. On this work, experimental and numerical investigation of each NACA 0015 and NACA 4415 is done to decide their performance. For this purpose, aerofoil section is tested for a prevalence range attack of angle (AOA). The study addresses the performance of NACA 0015 and NACA 4415 and evaluates the dynamics of flow separation, lift, drag, pressure and velocity contour and so on. This additionally enables to layout new optimistic aerofoil, which is critical to enhance the efficiency and performance of an aircraft in terms of lift enhancement and drag reduction.

We investigate the innovational determinants of “Patent Applications” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS and Dynamic Panel. We found that the variables that have a deeper positive association with “Patent Applications” are “Human Resources” and “Intellectual Assets”, while the variables that show a more intense negative relation with Patent Applications are “Employment Share in Manufacturing” and “Total Entrepreneurial Activity”. A cluster analysis with the k-Means algorithm optimized with the Silhouette Coefficient has been realized. The results show the presence of two clusters. A network analysis with the distance of Manhattan has been performed and we find three different complex network structures. Finally, a comparison is made among eight machine learning algorithms for the prediction of the future value of the “Patent Applications”. We found that PNN-Probabilistic Neural Network is the best performing algorithm. Using PNN the results show that the mean future value of “Patent Applications” in the estimated countries is expected to decrease of -0.1%.

In this article we have estimated the value of “Opportunity Driven Entrepreneurship” in Europe. We use data from European Innovation Scoreboard-EIS of the European Commission for 36 countries in the period 2010-2019. We use Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, Pooled OLS, and Dynamic Panel. Our results show that “Opportunity Driven Entrepreneurship” is positively associated, among others, to “Innovation Friendly Environment” and “Turnover Share Large Enterprises”, while it is negatively associated, among others, to “Sales Impacts” and “R&D Expenditure Business Sectors”.

In this article we estimate the value of “Non-R&D Innovation Expenditures” in Europe. We use data from the European Innovation Scoreboard-EIS of the European Commission from the period 2010-2019. We test data with the following econometric models i.e.: Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. We found that “Non-R&D Innovation Expenditures” is positively associated among others to “Innovation Index” and “Firm Investments” and negatively associated among others to “Human Resources” and “Government Procurement of Advanced Technology Products”. We use the k-Means algorithm with either the Silhouette Coefficient and the Elbow Method in a confrontation with the network analysis optimized with the Distance of Manhattan and we find that the optimal number of clusters is four. Furthermore, we propose a confrontation among eight machine learning algorithms to predict the level of “Non-R&D Innovation Expenditures” either with Original Data-OD either with Augmented Data-AD. We found that Gradient Boost Trees Regression is the best predictor for OD while Tree Ensemble Regression is the best Predictor for AD. Finally, we verify that the prediction with AD is more efficient of that with OD with a reduction in the average value of statistical errors equal to 40,50%.

In this article we investigate the determinants of “New Doctorate Graduates” in Europe. We use data from the EIS-European Innovation Scoreboard of the European Commission for 36 countries in the period 2010-2019 with Pooled OLS, Dynamic Panel, WLS, Panel Data with Fixed Effects and Panel Data with Random Effects. We found that “New Doctorate Graduates” is positively associated, among others, with “Human Resources” and “Government Procurement of Advanced Technology Products” and negatively, associated among others, with “Total Entrepreneurial Activity” and “Innovation Index”. We apply a clusterization with k-Means algorithm either with the Silhouette Coefficient either with the Elbow Method and we found that in both cases the optimal number of clusters is three. Furthermore, we use the Network Analysis with the Distance of Manhattan, and we find the presence of seven network structures. Finally, we propose a confrontation among ten machine learning algorithms to predict the value of “New Doctorate Graduates” either with Original Data-OD either with Augmented Data-AD. Results show that SGD-Stochastic Gradient Descendent is the best predictor for OD while Linear Regression performs better for AD.

In this article we investigate the determinants of the European “Most Cited Publications”. We use data from the European Innovation Scoreboard-EIS of the European Commission for the period 2010-2019. Data are analyzed with Panel Data with Fixed Effects, Panel Data with Random Effects, WLS, and Pooled OLS. Results show that the level of “Most Cited Publications” is positively associated, among others, to “Innovation Index” and “Enterprise Birth” and negatively associated, among others, to “Government Procurement of Advanced Technology Products” and “Human Resources”. Furthermore, we perform a cluster analysis with the k-Means algorithm either with the Silhouette Coefficient and the Elbow Method. We find that the Elbow Method shows better results than the Silhouette Coefficient with a number of clusters equal to 3. In adjunct we perform a network analysis with the Manhattan distance, and we find the presence of 4 complex and 2 simplified network structures. Finally, we present a confrontation among 10 machine learning algorithms to predict the level of “Most Cited Publication” either with Original Data-OD either with Augmented Data-AD. Results show that the best machine learning algorithm to predict the level of “Most Cited Publication” with Original Data-OD is SGD, while Linear Regression is the best machine learning algorithm for the prediction of “Most Cited Publications” with Augmented Data-AD.

In this article we analyze the determinants and the export trend of European countries of medium and high technology products. The data were analyzed using various econometric models, namely WLS, Pooled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects. The results show that exports of medium and high-tech products are positively associated, among other variables, with the value of “Average Annual GDP Growth”, “Total Entrepreneurial Activity” and “Sales Impacts”, and negatively associated with, among other variables, “Human Resources”, “Government and Procurement of Advanced Technology Products” and “Buyer Sophistication”. A cluster analysis was realized with the k-Means algorithm optimized with the Silhouette coefficient. The result showed the presence of only two clusters. Since this result was considered poorly representative of the industrial complexity of the European Union countries, a further analysis was carried out with the Elbow method. The result showed the presence of 6 clusters with the dominance of Germany and the economies connected to the German economy. In addition, a network analysis was carried out using the distance to Manhattan. Four complex network structures and two simplified network structures were detected. A comparison was then made between 10 machine learning algorithms for predicting the value of exports of medium and high-tech products. The result shows that the best performing algorithm is the SGD. An analysis with Augmented Data-AD was implemented with a comparison between 10 machine learning algorithms for prediction and the result shows that the Linear Regression algorithm is the best predictor. The prediction with the Augmented Data-AD allows to reduce the MAE by about 0.0022131 compared to the prediction with the Original Data-OD.

The article affords the question of lifelong learning in Europe using data from the European Innovation Scoreboard-EIS in the period 2010-2019 for 36 countries. The econometric analysis is realized using WLS, Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects and Random Effects. The results show that lifelong learning is, among other variables, positively associated to “Human Resources” and “Government procurement of advanced technology products” and is negatively associated, among others, to “Average annual GDP growth” and “Innovation Index”. A clusterization is realized using the k-Means algorithm with a confrontation between the Elbow Method and the Silhouette Coefficient. Subsequently, a Network Analysis was applied with the distance of Manhattan. The results show the presence of 4 complex and 2 simplified network structures. Finally, a comparison was made among eight machine learning algorithms for the prediction of the value of lifelong learning. The results show that the linear regression is the best predictor algorithm and that the level of lifelong learning is expected to growth on average by 1.12%.

In this article we investigate the determinants of marketing or organizational innovators in Europe for 36 countries in the period 2010-2019. We have used data from the European Innovation Scoreboard-EIS of the European Commission. We perform different econometric models i.e. Dynamic Panel, Pooled OLS, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. Results show that the level of marketing or organizational innovators in positively associated, among others variables to “Innovation Index”, “Innovators” and “Knowledge Intensive Service Exports”, while is negatively associated with “Sales Impacts”, “Foreign Controlled Enterprises Share of Value Added” and “Government procurement of advanced technology products”.

In the following article, the value of the "Knowledge Intensive Services Exports in Europe" in 36 European countries is estimated. The data were analyzed through a set of econometric models or: Poled OLS, Dynamic Panel, Panel Data with Fixed Effects, Panel Data with Random Effects, WLS. The results show that “Knowledge Intensive Services Exports” is negatively associated, among others, with "Buyer Sophistication", "Government Procurement of Advanced Technology Products", and positively associated with the following variables i.e. "Innovation Index", "Sales Impacts" and "Total Entrepreneurial Activity". Then a clusterization with k-Means algorithm was made with the Elbow method. The results show the presence of 3 clusters. A network analysis was later built and 4 complex network structures and three structures with simplified networks were detected. To predict the future trend of the variable, a comparison was made with eight different machine learning algorithms. The results show that prediction with Augmented Data-AD is more efficient than prediction with Original Data-AD with a reduction of the mean of statistical errors equal to 55,94%.

The following article indicates the determinants of “Internet User Skills” among European countries based on the application of the database deriving from the DESI-Index. The data were analyzed using the following econometric models, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, Pooled OLS, WLS, WLS corrected for heteroskedasticity. The Elbow method and the Silouette coefficient method were compared for the optimization of the number of clusters obtained by the k-Means algorithm. The result shows the presence of 5 clusters. A network analysis was carried out using the Euclidean distance with the result of identifying two network structures between some analyzed countries. subsequently a comparison was made between six different machine learning algorithms for the prediction of the future value of the variable of interest. The result shows that the best predictor algorithm is Gradient Boosted Tree Regression with an expected value of the predicted variable increasing by a value of 1.75%. Later a further comparison was made by comparing 6 algorithms with the increased data. The result shows that the best predictor is Simple Regression Tree. The interest variable is predicted to decrease by an amount equal to -6.099%. Statistical errors improve on average by 32.43% in the transition between the original data and the increased data.

The following article analyzes the determinants of the innovation index in Europe. The data refer to the European Innovation Scoreboard-EIS of the European Commission for the period between 2010 and 2019 for 36 countries. The data are analyzed using the following econometric techniques: Panel Data with Random Effects, Panel Data with Fixed Effects, Dynamic Panel Data, Pooled OLS, WLS. The results show that the Innovation Index is negatively connected to some variables, among which the most significant are "GDP per capita", "R&D expenditure public sector", "Venture capital", "Tertiary education", and positively connected to some variables among which the most relevant are: "Government procurement of advanced technology products", "Average annual population growth", "Finance and support", "Human resources", "Marketing or organisational innovators", "Linkages". A clustering was then carried out using the unsupervised k-Means algorithm optimized with the Silhouette coefficient which shows the presence of 2 clusters per value of the Innovation Index. Eight machine learning algorithms has been used for prediction with real data. The Tree Ensemble Regression algorithm has been chosen as best performer. A further prediction has been made with the augmented data. The result shows that the best performing algorithm is Linear Regression with an innovation index value predicted to grow by approximately 3.38%.

The following article estimates the value of ICT Specialists in Europe between 2016 and 2021 for 28 European countries. The data were analyzed using the following econometric techniques, namely: Panel Data with Fixed Effects, Panel Data with Random Effects, WLS and Pooled OLS. The results show that the value of ICT Specialists in Europe is positively associated with the following variables: "Desi Index", "SMEs with at least a basic level of digital intensity", "At least 100 Mbps fixed BB take-up" and negatively associated with the following variables: "4G Coverage","5G Coverage", "5G Readiness", "Fixed broadband coverage", "e-Government", "At least Basic Digital Skills", "Fixed broadband take-up", "Broadband price index", "Integration of Digital Technology". Subsequently, two European clusters were found by value of "ICTG Specialists" using the k-Means clustering algorithm optimized by using the Silhouette coefficient. Finally, eight different machine learning algorithms were compared to predict the value of "ICT Specialists" in Europe. The results show that the best prediction algorithm is ANN-Artificial Neural Network with an estimated growth value of 12.53%. Finally, "augmented data" were obtained through the use of the ANN-Artificial Neural Network, through which a new prediction was made which estimated a growing value of the estimated variable equal to 3.18%.

The following article analyzes the determinants of e-government in 28 European countries between 2016 and 2021. The DESI-Digital Economy and Society Index database was used. The econometric analysis involved the use of the Panel Data with Fixed Effects and Panel Data with Variable Effects methods. The results show that the value of “e-Government” is negatively associated with “Fast BB (NGA) coverage”, “Female ICT specialists”, “e-Invoices”, “Big data” and positively associated with “Open Data”, “e-Government Users”, “ICT for environmental sustainability”, “Artificial intelligence”, “Cloud”, “SMEs with at least a basic level of digital intensity”, “ICT Specialists”, “At least 1 Gbps take-up”, “At least 100 Mbps fixed BB take-up”, “Fixed Very High Capacity Network (VHCN) coverage”. A cluster analysis was carried out below using the unsupervised k-Means algorithm optimized with the Silhouette coefficient with the identification of 4 clusters. Finally, a comparison was made between eight different machine learning algorithms using "augmented data". The most efficient algorithm in predicting the value of e-government both in the historical series and with augmented data is the ANN-Artificial Neural Network.

This article analyzes the determinants of the "Broadband Price Index" in Europe. The data used refer to 28 European countries between 2016 and 2021. The database used is the Digital, Economy and Society Index-DESI of the European Commission. The data were analyzed using the following econometric techniques, namely Panel Data with Random Effects, Panel Data with Fixed Effects, Pooled OLS, WLS and Dynamic Panel. The value of the "Broadband Price Index" is positively associated with the DESI Index, and "Connectivity" while it is negatively associated with "Fixed Broadband Take Up", "Fixed Broadband Coverage", "Mobile Broadband", "e-Government", "Advanced Skills and Development", "Integration of Digital Technology", "At Least Basic Digital Skills ", "Above Basic Digital Skills "," At Least Basic Software Skills ". A cluster analysis was carried out below using the k-Means algorithm optimized with the Silhouette coefficient. The analysis revealed the existence of three clusters. Finally, an analysis of the machine learning algorithms was carried out to predict the future value of the "Broadband Price Index". The result shows that the most useful algorithm for prediction is the Artificial Neural Network-ANN with an estimated value equal to an amount of 9.21%.

The determinants of the presence of “Foreign Doctorate Students” among 36 European Countries for the period 2010-2019 are analyzed in this article. Panel Data with Fixed Effects, Random Effects, WLS, Pooled OLS, and Dynamic Panel are used to investigate the data. We found that the presence of Foreign Doctorate Students is positively associated to “Attractive Research Systems”, “Finance and Support”, “Rule of Law”, “Sales Impacts”, “New Doctorate Graduates”, “Basic School Entrepreneurial Education and Training”, “Tertiary Education” and negatively associated to “Innovative Sales Share”, “Innovation Friendly Environment”, “Linkages”, “Trademark Applications”, “Government Procurement of Advanced Technology Products”, “R&D Expenditure Public Sectors”. A cluster analysis was then carried out through the application of the unsupervised k-Means algorithm optimized using the Silhouette coefficient with the identification of 5 clusters. Finally, eight different machine learning algorithms were used to predict the value of the "Foreign Doctorate Students" variable. The results show that the best predictor algorithm is the "Tree Ensemble Regression" with a predicted value growing at a rate of 114.03%.

Research into professionalization in health and safety has recently gained in interest. Graduate training is one of the factors that determines or conditions the role of the safety professional, thus intervene in the professionalization process. This article is the result of a workshop and the discussions of nine academic directors of safety education programs about quality evaluation. This article introduces the issue with a historic overview of safety education, presents a synthesis of nine selected education programs, discusses quality evaluation of health and safety education programs, propose a quality evaluation frame and finally, proposes a process for designing a quality safety education program with an associated model of the learning objectives. The outcomes are interesting for everyone who is interested in health and safety education and quality evaluation and will give insights into how safety professionals are educated.

In Low and Lower-Middle-Income countries, the prevalence of anemia in infancy remains high. In early childhood anemia cause irreversible cognitive deficits and represents a higher risk of child mortality. The consequences of anemia in infancy are a major barrier to overcome poverty traps. The aim of this study was to analyze based on a multi-level approach, different factors associated with anemia in children 6–23 m old based on recent available Standard Demographic Health Surveys (S-DHS). We identified 52 S-DHS that had complete information in all covariates of interest in our analysis between 2005 and 2015. We performed traditional logistic regressions and multilevel logistic regression analyses to study the association between hemoglobin concentrations and household, child, maternal, socio-demographic variables. In our sample, 70 % of the 6–23 m old children were anemic. Child anemia was strongly associated with maternal anemia, household wealth, maternal education and low birth weight. Children fed with fortified foods, potatoes and other tubers had significantly lower rates of anemia. Improving overall household living conditions, increasing maternal education, delaying childbearing and introducing iron rich foods at six months of age may reduce the likelihood of anemia at in toddlerhood.

In the past two decades the world experienced an exceptional number of unprecedented extreme weather events, some causing major human suffering and economic damage, such as the March 2012 heat event, which was called “Meteorological March Madness.” From the beginning of space era a correlation of solar flares with pressure changes in atmosphere within 2–3 days or even less was reported. In this study we wanted to test the possible relation of highly warm weather events in North-East America with Solar Energetic Particle (SEP) events. For this reason we compared ground temperatures T_M in Madison, Wisconsin, with energetic particle fluxes P measured by the EPAM instrument onboard the ACE spacecraft. In particular, we elaborated case events and the results of a statistical study of the SEP events related with the largest (Dst ≤ −150nT) Coronal Mass Ejection (CME)-induced geomagnetic storms, between with the years 1997–2015. The most striking result of our statistical analysis is a very significant positive correlation between the highest temperature increase_. ΔT_M and the time duration of the temperature increase ΔT_M (r = 0.8, p <0.001) at “winter times” ( r = 0.5, p , 0.01 for the whole sample of 26 SEP examined events). The time response of T_M to P was found to be in general short (a few days), but in the case of March 2015, during a gradual P8 increase, a cross-correlation test indicated highest c.c. within 1 day (p < 0.05). The March 2012 “meteorological anomaly” was elaborated in the case of South-East Europe, where, beside a period of strong winds and rainfall (6-13.3.2012), intense precipitation in North-East Greece (Alexandroupoli) were found to be correlated with distinct high energy flux enhancements. A rough theoretical interpretation is discussed for the space—atmospheric extreme weather relationship we found. However, much work should be done to achieve early warning of space weather dependent extreme meteorological events. Such future advances in understanding the relationships between space weather and extreme atmospheric events would improve atmospheric models and help people’s safety, health and life.

In today's digital landscape, cybersecurity has become a priority, with attacks becoming increasingly sophisticated. Traditional security approaches are no longer enough, requiring a more dynamic and advanced response. In this context, integrating Artificial Intelligence (AI) and Machine Learning (ML) appears key to addressing this growing threat. However, despite their high effectiveness, there is a developed problem: the integration of various data sources and technologies for comprehensive protection. This article presents an in-depth review of integrating Artificial Intelligence and Machine Learning in cybersecurity, focusing particularly on Open Extended Detection and Response (Open XDR) technology. The literature review in this article was meticulously conducted with specific criteria in mind. It focused on sourcing peer-reviewed journals, authoritative cybersecurity publications, and recent conferences that primarily concentrate on the advancements in AI and ML within the cybersecurity domain, particularly from 2018 to 2023. This timeframe was chosen to ensure the inclusion of the most current and relevant developments in Open XDR technology, Intrusion Detection Systems, Endpoint Detection and Response, and Security Information and Event Management systems. Additionally, the review gave special attention to studies and reports highlighting practical implementations and real-world applications of these technologies, thereby ensuring a comprehensive understanding of their impact and effectiveness in enhancing cybersecurity resilience. The methodology used is a detailed literature review, examining how various cybersecurity components interact and function. These components include Intrusion Detection Systems (IDS), which monitor networks for malicious activities; Endpoint Detection and Response (EDR), which focuses on detecting and investigating security incidents on endpoints; and Security Information and Event Management (SIEM), systems that provide real-time analysis of security alerts. The review also considers the role of Active Directory, a directory service for Windows domain networks, and the process of log forwarding, where log files are transmitted to a central server for analysis, in the context of AI and ML. The paper delves into the development of AI and ML, underscoring their roles in cybersecurity for advanced data processing, pattern recognition, and predicting threats. It explores both supervised (where the model is trained on labeled data) and unsupervised learning (where the model learns from unlabeled data) in ML, and how these techniques bolster cybersecurity measures. The article highlights the significance of Open XDR as a critical innovation that integrates data from multiple sources for comprehensive security analysis. Further, the review discusses how the integration of AI and ML into various cybersecurity tools, such as IDS, EDR, and SIEM, augments capabilities in threat detection and response. It addresses the challenges and opportunities that AI and ML present in the cybersecurity domain, focusing on ethical issues, data privacy concerns, and the necessity for ongoing professional development in this rapidly advancing field. The paper concludes by affirming the effectiveness of merging AI and ML with these cybersecurity tools within the Open XDR framework.

Recreational and leisure areas play a special role. These areas mitigate or eliminate the disadvantages of living in large cities, and they enhance the quality of life in small towns. The aim of this study was to analyze the share of recreational and leisure areas in Polish counties in 2022. In Poland, recreational and leisure areas constitute a separate land-use category in cadastral registers. Annual cadastral data from the Land and Building Register at county level (in tabular form) were the main source of data for the study. The analysis revealed that the share of recreational and leisure areas was higher in counties situated in western and south-western Poland, as well as in cities. The spatially varied influence of socioeconomic factors on the share of recreational and leisure areas in Polish counties in 2002 was determined with the use of local Moran's I statistic and geographically weighted regression (GWR). The study confirmed that population density was significantly related to the share of recreational and leisure areas in Polish counties. The impact of the remaining socioeconomic factors associated with spatial and economic development varied across regions. The study also revealed that in addition to the current socioeconomic determinants, the share of recreational and leisure areas in Polish counties was also influenced by historical factors and the counties' development since their establishment.

In this work, the nearest neighbor distances and Voronoi cell features of the Cu-Ag deposits were analyzed and fitted with Lognormal, Weibull, and Gamma distributions. The nearest neighbor distance distributions of the samples were compared with those of complete spatially random points, showing spatial inhomogenity due to the nucleation exclusion effect. The radial distribution function was calculated, showing both influences from the grain size and the nucleation exclusion effect. Voronoi cells were generated based on the shape of the grains. The size, occupancy, and coordination of the Voronoi cells were examined and fitted. The results show that despite the Cu-Ag deposits seem to be governed by instantaneous nucleation mode, the spatial distribution of the nuclei is more impacted by the nucleation exclusion effect than the Cu-only samples. This behavior is also justified by the grain size distribution generated with Voronoi cell size and occupancy distributions.

A clinical case of atypical endophthalmitis in an 82-year-old patient who underwent complicated cataract phacoemulsification. Clinical manifestations showed signs of a bacterial process, however, the treatment was not effective. Antifungal therapy had yielded positive results, despite the low probability of a fungal etiology of the process.

When sellers set the price for ex-ante unobservable and ex-post unenforceable quality, price signals credence quality. Hedge funds resemble incomplete long-term contracts for credence goods under buyer-determined auctions. I show that hedge funds' ability to solicit investments at higher management fees signals their capacity to generate higher net returns. This result is more pronounced during bust cycles and closer to financial hubs, i.e., when signaling quality is more valuable. The findings are relevant to understanding price and effort in the provision of credence goods like medical procedures and legal advice.

The aim of the study is to assess the loads that are transferred from the main rotor and the tail rotor to the helicopter fuselage. These loads change in the various phases of the transient flight as a result of the variable control of the maneuver and as a result of the variable flow around the blades. The knowledge of the loads allows for the proper selection of the level of excitations that should load the fuselage structure during fatigue and strength tests. The simulation model describing the helicopter flight is discussed. This model takes into account the motion of each blade relative to its hinges. Results are shown for two maneuvers - pullup/pushover and diving. The values of extreme loads transferred to the fuselage were obtained.