In spite of prevalence gaps in several micronutrients supporting immune function, significance of their deficits/supplementation for efficacy of vaccines is underinvestigated. Thus, influence of supplementation combining vitamins C and D, zinc, selenium and manganese, and N-acetyl-cysteine on mouse IgG responses and underlying mechanisms to seasonal quadrivalent influenza vaccine (QIV) was investigated. QIV was given in two doses (28 days apart). The supplementation starting 5 days before the first injection increased the total serum IgG titre, through stimulation of germinal centre (GC) reaction in secondary lymphoid organs (SLOs), as indicated by increase in the frequency of GC B cells and follicular CD4+ T helper (Th) cells, and IL-21-producing Th cells. Additionally, the supplementation “optimized” IgG response following the second QIV injection by supporting more favorable (in respect to virus clearance) IgG2a response through favoring Th1 differentiation as indicating by Th1 (INF-γ) /Th2 (IL-4) signature cytokine level ratio upon QIV restimulation in SLO cell cultures. This most likely reflected partly their antioxidant action (as indicated by redox status analyses) on Th cell differentiation. Thus, the study forms solid base for further research aimed at repurposing use this safe and inexpensive micronutrient combination as an adjuvant for virus influenza vaccine.

We report the case of a 61-year-old woman who was referred to the Oral Surgery and Implantology Unit of the University Hospitals of Geneva to take care edentulous sites after dental avulsions of teeth 11 and 21 following traumatic shock due to endotracheal intubation under general anaesthesia. The dental history revealed that the patient had a history of generalized chronic periodontitis that had been treated several years earlier. Treatment consisted, for the first time to our knowledge, of immediate insertion of implants at sites 11 and 21 with simultaneous bone augmentation in a single surgical procedure and immediate restorations.

Climate change has emerged as a crucial global issue that significantly threatens the survival of plants. In particular, low temperature (LT) is one of the critical environmental factors that influence plant morphological, physiological, and biochemical changes during both the vegetative and reproductive growth stages. LT, including abrupt drops in temperature, as well as winter conditions, can cause detrimental effects on the growth and development of tomato plants, ranging from sowing, transplanting, truss appearance, flowering, fertilization, flowering, fruit ripening, and yields. Therefore, it is imperative to understand the comprehensive mechanisms underlying the adaptation and acclimation of tomato plants to LT at the morphological and the molecular levels. In this review, we discuss the previous and current knowledge of morphological and physiological changes, which contains major factors and traits associated with the LT stress response during the period of the vegetative and reproductive growth and development in tomato plants. Moreover, we highlight recent advances in the understanding of physiological and biochemical responses, and molecular mechanisms, including LT perception, signaling transduction, gene regulation, and fruit ripening and epigenetic regulation. The comprehensive understanding of LT response provides a solid basis to develop the LT-resistant varieties for sustainable tomato production under the ever-changing temperature fluctuations.

Protected and conserved areas are a key area-based strategy to address the biodiversity and climate change crises. Fundamental to understand their performance over time are indicators. The Digital Observatory for Protected Areas (DOPA) was born in 2013 as a set of open access web services and applications to be used to assess, monitor, and report on protected and conserved areas. For over a decade it has delivered over 50 indicators to support policy processes, national and regional governments, and practitioners. DOPA has also developed a versatile and efficient back-end approach that is widely applicable in other area-based conservation contexts. Here, we describe the methods and workflows behind DOPA´s back end and provide examples of policy relevant questions it can answer. We discuss key advantages and limitations of this systematic and replicable approach and explore the use of this back-end architecture to inform progress in area-based conservation targets for the following decades. This approach, embedded in multiple services provided by the Knowledge Centre for Biodiversity of the European Commission (KCBD), can also support the implementation and monitoring of area-based targets of the Kunming Montreal Global Biodiversity Framework at international, regional, and national levels.

Human activities (e.g., exploitation, utilization, and conservation) exert substantial impact on forest ecological functions (FEF). The human influence on FEF significantly varies across developmental stages, which are attributed to the temporal and spatial in nature. This study evaluates some notable FEF indices (FEFI) in the 448 counties within the Yellow River basin (YRB) using panel data from the Seventh to Ninth National Forest Inventory. Data analysis involves employing the residual trends, geographical and temporal weighted regression. Results indicate that, firstly, the overall forest ecological function in the YRB is moderate to inferior, with superior FEF in counties endowed with more natural forest resources. Afforestation demonstrates a short-term improvement, but its effectiveness diminishes over time. Secondly, the positive spatial correlation is stronger among counties, characterized by both high-high and low-low agglomeration effects. Scattered planting, simple stand structure, and concentrated harvesting of forests at the identical stand ages hinder the formation of complex and large-scale FEF agglomerations. Thirdly, significant spatial-temporal differences exist in the impact of human activities on FEF. In the upper reaches of the basin, increased vegetation coverage through agricultural and forestry production benefited FEF, however, some over-exploitation of forests and grasslands is observed there. In the middle reaches, the economic development, expanding population and the greening activities help to improve FEF effectively, but excessive water using in agricultural production brought more difficulties to FEF improvement. In the lower reaches of the basin, improved wastelands and forest protection positively influence FEF. This study recommends that county governments should prioritize forest management with multi-species and multi-layered complex forests. Each county should define its position in regional development and ecological protection, considering the potential impacts on neighboring regions. This holistic approach promotes more effective integrated regional management.

This paper provides the straight proof for the Riemann Hypothesis.The proof has been formulated with the modified version of Riemann Xi function ξ(s) , that shows the relationship with upper incomplete gamma function.

Nollywood, based on the idea of Bollywood from India, is a series of outstanding movies that originate from Nigeria. Unfortunately, while the movies are in English, they are hard to understand for many native speakers due to the dialect of English that is spoken. In this article, we accomplish two goals: (1) create a phonetic sub-title model that is able to translate Nigerian English speech to American English and (2) use the most advanced toxicity detectors to discover how toxic the speech is. Our aim is to highlight the text in these videos which is often times ignored for lack of dialectal understanding due the fact that many people in Nigeria speak a native language like Hausa at home.

For a long-only active equity manager (or investor), the ability to hedge the downside risk before a significant price correction is a valuable skill. The authors proposed constructing a signal that provides timing information for a manager to hedge the downside risk. This systematic signal can help a manager put on a hedge before the price corrections of the dot com bubble in 2000 and the global financial crisis in 2008. The signal is constructed for each GICS sector index in the S&P 500. When a sector’s PE indicates a high valuation and, at the same time, if the high valuation sector’s correlations with some other sectors are out of their historical norm, then these two conditions contribute a timing signal for the significant price swing of the index during the following six months. After observing the timing signal, managers can benefit significantly by hedging the downside risk. The signal can also be interpreted as the beginning of a high volatility regime for a sector.

Proof of the Riemann hypothesis is obtained using the properties of the Gamma function, the Bernoulli function, and limitations imposed by the rational relations of the complex roots of the Riemann zeta function, and the rational relations of the complex Gamma functions.

The cellular model we teach and have theorized assumes that the cell is the basic unit of multicellular living beings. This fundamental element has been the subject of many theories concerning its properties and the exchanges that exist with its environment. In this article, we demonstrate that certain functional aspects, in particular the electrical aspects related to diffusion, have not been correctly assumed or that certain initial conditions have been purely ignored and are in contradiction with physics, chemistry and thermodynamics.

Microbial symbioses exhibit astounding adaptations, yet all symbionts face the problem of how to reliably associate with host offspring every generation. A common strategy is vertical transmission, in which symbionts are directly transmitted from the female to her offspring. The diversity of symbionts and vertical transmission mechanisms is as expansive as the diversity of eukaryotic host taxa that house them. However, there are several common themes among these mechanisms based on the degree to which symbionts associate with the host germline during transmission. In this review, we detail three distinct vertical transmission strategies, starting with associations that are transmitted from host somatic cells to offspring somatic cells, either due to lacking a germline or avoiding it. A second strategy involves somatically-localized symbionts that migrate into the germline during host development. The third strategy we discuss is one in which the symbiont maintains continuous association with the germline throughout development. Unexpectedly, the vast majority of documented vertically inherited symbionts rely on the second strategy: soma-to-germline migration. Given that not all eukaryotes contain a sequestered germline and instead produce offspring from somatic stem cell lineages, this soma-to-germline migration is discussed in the context of multicellular evolution. Lastly, as recent genomics data have revealed an abundance of horizontal gene transfer events from symbiotic and non-symbiotic bacteria to host genomes, we discuss their impact on eukaryotic host evolution.

During their life cycle, plants constantly respond to environmental changes. Abiotic stressors affect the photosynthetic and respiratory processes of plants. Reactive oxygen species (ROS) are produced during aerobic metabolism and play an important role as regulatory mediators in signaling processes, activating the plant's protective response to abiotic stress and restoring "oxidation-reduction homeostasis". Cells develop normally if the rates of ROS production and the ability to neutralize them are balanced. To implement oxidation-reduction signaling, this balance must be disrupted either by an increase in ROS concentration or a decrease in the activity of one or more antioxidant systems. Under abiotic stress, plants accumulate excessive amounts of ROS and if the ROS content exceeds the threshold amount dangerous for living organisms, it can lead to damage to all major cellular components. Adaptive resistance of plants to abiotic stressors depends on a set of mechanisms of adaptation to them. The accumulation of ROS in the cell depends on the type of abiotic stress, the strength of its impact on the plant, the duration of its impact and the recovery period. The aim of this review is to provide a general understanding of the processes occurring during ROS homeostasis in plants, oxidation-reduction processes in cellular compartments in response to abiotic stress and the participation of ROS in signaling processes activating adaptation processes to abiotic stress.

During the extraction of hard coal in Polish conditions, methane is emitted, which is referred to as mine gas. As a result of the desorption of methane, a greenhouse gas is released from coal seams. In order to reduce atmospheric emissions, methane from coal seams is captured by a methane drainage system. On the other hand, methane, which has been separated into underground mining excavations, is discharged into the atmosphere with a stream of ventilation air. For many years, Polish hard coal mines have been capturing methane to ensure the safety of the crew and the continuity of mining operations. As a greenhouse gas, methane has a significant potential, as it is more effective at absorbing and re-emitting radiation than carbon dioxide. The increase in the amount of methane in the atmosphere is a significant factor influencing global warming, however, it is not as strong as the increase in carbon dioxide. Therefore, in Polish mines, the methane-air mixture captured in the methane drainage system is not emitted to the atmosphere, but burned as fuel in systems, including cogeneration systems, to generate electricity, heat and cold. However, in order for such use to be possible, the methane-air mixture must meet appropriate quality and quantity requirements. The article presents an analysis of changes in selected parameters of the captured methane-air mixture from one of the hard coal mines in the Upper Silesian Coal Basin in Poland. The paper analyses the changes in concentration and size of the captured methane stream through the methane capturing system. The gas captured by the methane drainage system, as an energy source, can be used in cogeneration, when the methane concentration is greater than 40%. Considering the variability of CH4 concentration in the captured mixture, it was also indicated which pure methane stream must be added to the gas mixture in order for this gas to be used as a fuel for gas engines. The balance of power of produced electric energy in gas engines is presented. Possible solutions ensuring constant concentration of the captured methane-air mixture are also presented.

Cancers, a large and heterogeneous group of malignancies, are becoming an increasingly important cause of premature mortality worldwide. 2% of these are primary CNS tumors, of which 24% are gliomas. These tumors are diverse, but what they have in common is one of the most unfavorable prognoses among all cancers. A patient's future varies depending on the grade of the diagnosed glioma. To date, however, no standard treatment for grade IV has been established. All glioblastomas eventually undergo progression or recurrence. The current standard of treatment, which includes surgical intervention, radiation therapy and chemotherapy, is therefore far from sufficient. Work is constantly underway to discover a new, effective form of glioma therapy. Photodynamic therapy (PDT) may be one of them. It involves the local or systemic application of a photosensitive compound - a photosensitizer (PS), which accumulates in the affected tissues. Photosensitizer molecules absorb light of the appropriate wavelength, initiating activation processes leading to the formation of reactive oxygen species and selective destruction of inappropriate cells. Currently, this method has been approved for the treatment of several cancers. Research focusing on the effective use of PDT in glioma therapy is already underway, with promising results. In our work, we present molecular insights into PDT of glioma. Based on the available literature, we analyze and systematize the impact of various molecules, proteins, transporters and transmitters on the efficacy of PDT and the effect of PDT on their expression. In addition, we highlight gaps in current knowledge and point out directions for future research that may contribute to the efficacy of PDT glioma.

Antiretroviral therapy has effectively suppressed HIV infection and replication and prolonged the lifespan of HIV-infected individuals. In the meantime, various complications including type 2 diabetes associated with long-term antiviral therapy have shown steady increases. Metformin has been the front-line anti-hyperglycemic drug of choice and the most widely prescribed medication for the treatment of type 2 diabetes. However, little is known about the effects of Metformin on HIV infection and replication. In this study, we showed that Metformin treatment enhanced HIV gene expression and transcription in HIV-transfected 293T and HIV-infected Jurkat and human PBMC. Moreover, we demonstrated that Metformin treatment resulted in increased CREB expression and phosphorylation, and TBP expression. Furthermore, we showed that Metformin treatment increased the recruitment of phosphorylated CREB and TBP to the HIV LTR promoter. Lastly, we showed that inhibition of CREB activation significantly abrogated Metformin-enhanced HIV gene expression. Taken together, these results demonstrated that Metformin treatment increased HIV transcription, gene expression, and production though increased CREB phosphorylation and recruitment to the HIV LTR promoter. These findings may help design the clinical management plan and HIV cure strategy of using metformin to treat type 2 diabetes, a comorbidity with an increasing prevalence, in people living with HIV.

This paper discovers that current variational principle and Noether theorem for different physics systems with (in)finite freedom systems have missed the double extremum processes of the general extremum functional that both is deduced by variational principle and is necessarily taken in deducing all the physics laws, but these have not been corrected for over a century since Noether's proposing her famous theorem, which result in the crisis deducing relevant mathematical laws and all physics laws. This paper discovers there is the hidden logic cycle that one assumes Euler-Lagrange equations, and then he finally deduces Euler-Lagrange equations via the equivalent relation in the whole processes in all relevant current references. This paper corrects the current key mistakes that when physics systems choose the variational extreme values, the appearing processes of the physics systems are real physics processes, otherwise, are virtual processes in all current articles, reviews and (text)books. The real physics should be after choosing the variational extreme values of physics systems, the general extremum functional of the physics systems needs to further choose the minimum absolute extremum zero of the general extremum functional, otherwise, the appearing processes of physics systems are still virtual processes. Using the double extremum processes of the general extremum functionals, the crisis and the hidden logic cycle in current variational principle and current Noether theorem are solved. Furthermore, the new mathematical and physical double extremum processes and their new mathematical pictures and physics for (in)finite freedom systems are discovered. This paper gives both general variational principle and general Noether theorem as well as their classical and quantum new physics, which would rewrite all relevant current different branches of science, as key tools of studying and processing them.

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance the attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.009°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

Purpose – Extend the Blade Element Momentum Theory (BEMT) such that rotors with pronounced cone and axis angle (tilt or yaw) can be calculated. Derive an equation for the speed ratio (lambda) as a function of Tip Speed Ratio (TSR), radius, blade, cone and axis angle. This converts the BEMT into an Unsteady BEMT or UBEMT. Present the Wagner rotor as one such rotor geometry. --- Methodology – Literature review and calculations. --- Findings – The UBEMT can be used to calculate highly unconventional rotor geometries. --- Research Limitations – Although the aerodynamic coefficients used in the UBEMT are from measurements in steady flow conditions, they can be used with success. --- Practical Implications – Also conventional Horizontal Axis Wind Turbines (HAWT) with noticeable cone and axis angle should be calculated with the UBEMT. The accuracy of power calculations of these HAWTs can be slightly improved. --- Originality – Analytic equations for rotors with cone and axis angle have barely been discussed.

A convenient and efficient strategy for the preparation of 2-sulfonylindoles has been achieved through iodophor/H2O2-mediated 2-sulfonylation of indoles with readily available sulfonyl hydrazides in aqueous phase. Iodophor is commercially available and serves as the green catalyst and aqueous phase. A series of 2-sulfonylated products from indoles and N-methylpyrrole were synthesized in moderate yields in only 10 min. Control experiments were also conducted to reveal the mechanism. This method is environment friendly, easy to operate and suitable for a wide range of substrates.

Background: Nutritional status and oxidative stress have been implicated in the pathogenesis and persistence of long COVID, but data in patients undergoing hemodialysis (HD) are limited. The present study aimed to investigate the association between pre-infection nutritional status, oxidative stress, and one-year long COVID persistence in HD patients. Methods: This prospective observational cohort study enrolled 115 HD patients with confirmed COVID-19. Nutritional status was assessed using the Controlling Nutritional Status (CONUT) score twice: before infection and three months post-infection. Oxidative markers included malondialdehyde (MDAs), ceruloplasmin, transferrin, and sulfhydryl groups. The endpoint was one-year long COVID persistence. Results: Moderate pre-infection CONUT scores were associated with heightened severe undernutrition risk (p < 0.0001), elevated MDAs (p < 0.0001), and reduced ceruloplasmin levels (p = 0.0009) at three months post-COVID-19 compared to light CONUT scores. Pre-infection CONUT score independently predicted post-COVID oxidative damage [OR 2.3 (95%CI 1.2; 4.6), p < 0.0001] and one-year long COVID persistence [HR 4.6 (95%CI 1.4; 9.9), p < 0.0001], even after adjusting for potential confounders. Conclusion: Moderate pre-infection undernutrition in patients undergoing HD associated with increased post-COVID oxidative stress intensity and heightened risk of one-year long COVID persistence.

Sarcopenia is associated with clinical complications, which increase mortality. Effective sarcopenia risk screening in the elderly should be grounded in a comprehensive assessment, encompassing both nutritional status and medication use. Current screening tools, while emphasizing muscular per-formance, exhibit limited sensitivity in identifying elderly individuals at risk of sarcopenia. This cross-sectional study aimed to develop a sarcopenia risk screening tool, named Sarc-Global, with enhanced sensitivity, incorporating factors pertinent to the overall health of the elderly. Utilizing the criteria established by EWGSOP2 for diagnosing sarcopenia, we evaluated 395 communi-ty-dwelling elderly individuals. This evaluation served as a reference for assessing the efficacy of two validated questionnaires, Sarc-F and Sarc-CalF, and our newly developed Sarc-Global. Con-structed through multiple logistic regression, Sarc-Global integrates variables such as sex, age, medication use, body mass index, arm circumference, and handgrip strength – all significantly associated with sarcopenia (p

The introduction of Maritime Autonomous Surface Ship (MASS) through the development of autonomous navigation technologies is expected to bring about new technologies, new vessel types, and new job roles such as remote operation center (ROC) and remote operator (RO). The MASS Code are currently being discussed through Maritime Safety Committee (MSC) of International Maritime Organization (IMO). This code is expected to be adopted in the form of non-mandatory guidelines until 2025, with the goal of establishing mandatory requirements by 2028. Additionally, revisions to the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW) related to crew training and qualifications are planned for adoption by 2027, which will include requirements for MASS operators. This paper aims to examine the fundamental competencies required for safe MASS operation by remote operators using the Analytic Hierarchy Process (AHP) method, considering the emergence of the new profession of RO. Building upon the 66 Knowledge, Understanding & Proficiencies (KUPs) outlined for marine officer in the STCW Convention, the study seeks to identify the additional competencies necessary for RO and contribute to the development of a training model for the future.

Background: Obesity remains a widely debated issue, often criticized for the limitations in its identification and classification. This study aims to compare two distinct systems for classifying obesity: Body Mass Index (BMI) and body fat percentage (BFP) as assessed by bioelectrical impedance analysis (BIA). By examining these measures, the study seeks to clarify how different metrics of body composition influence the identification of obesity-related risk factors. Methods: The study enrolled 1255 adults, comprising 471 males and 784 females, with a mean age of 36 ± 11.90 years. Participants exhibited varying degrees of weight status, including optimal weight, overweight, and obesity. Body composition analysis was conducted using the TANITA Body Composition Analyzer BC-418 MA III device (T5896, Tokyo, Japan), evaluating the following parameters: current weight, basal metabolic rate (BMR), adipose tissue (%), muscle mass (%), and hydration status (%). Results: Age and psychological factors like cravings, fatigue, stress, and compulsive eating were significant predictors of obesity in the BMI model but not in the BFP model. Additionally, having a family history of diabetes was protective in the BMI model (OR: 0.33) but increased risk in the BFP model (OR: 1.66). The BMI model demonstrates exceptional predictive ability (AUC=0.998). In contrast, the BFP model, while still performing well, exhibits a lower AUC (0.975), indicating slightly reduced discriminative power compared to the BMI model. Conclusions:BMI classification demonstrates superior predictive accuracy, specificity, and sensitivity. This suggests that BMI remains a more reliable measure for identifying obesity-related risk factors compared to the BFP model.

Background: Genome-wide association studies have identified the chromosome 9p21 locus as one of the most important genetic risk factors for cardiovascular disease. However, the mechanism by which this locus promotes disease remains unclear due to difficulty identifying the causal genes and lack of a suitable animal model. Methods and Results: A total of 180 coronary artery autopsy specimens were analyzed histopathologically. The genotype of 9p21 (rs1333049) was not associated with any coronary risk factors nor the vulnerable plaque phenotype, but carriers of 9p21 risk allele did demonstrate more lesional calcification. To extend these studies into an animal model, mice with a targeted deletion of the orthologous 70-kb non-coding interval on chromosome 4 (chr4^D70kb/D70kb) were bred onto ApoE^-/- and fed with high fat diet. Targeted deletion of the 9p21 risk interval increased susceptibility to atherosclerotic plaque progression, but did not affect plaque rupture in the tandem stenosis model. Coronary risk factors such as body weight, blood pressure, lipid, and glucose levels did not differ between genotypes. Von Kossa staining revealed that chr4^D70kb/D70kb, ApoE^-/- developed more calcification in the plaque compared with chr4^+/+, ApoE^-/- mice, and that this this change was accompanied by increased aortic mRNA expression of Runx2, a key osteogenic transcription factor. Primarily cultured smooth muscle cells from chr4^D70kb/D70kb were hyperproliferative, and showed a calcification-prone phenotype after exposure to high-phosphate medium. Treatment with Palbociclib, a selective inhibitor of cyclin-dependent kinase 4/6, reduced mRNA expression of osteogenic genes in smooth muscle cells. Conclusion: Results from human and mouse studies indicate that the 9p21 non coding risk interval is associated with larger atherosclerotic plaque burden, but not with plaque rupture. 9p21 may promote lesion expansion by inducing the proliferation of de-differentiated and osteogenic smooth muscle cells.

Recent advancements in artificial intelligence (AI) and deep learning have revolutionized the field of protein engineering, particularly in the area of de novo protein design. This review article explores the impact of AI-driven approaches on protein design, with a specific focus on the role of structure prediction neural networks, such as AlphaFold and RoseTTAFold. The article discusses the paradigm shift brought about by these networks, which have enabled the design of proteins with unique structures and functions that are not found in nature. The review covers various aspects of AI-driven protein design, including the use of protein language models to harness evolutionary information, the development of de novo protein design workflows utilizing deep learning, and the application of generative models like RFdiffusion and RoseTTAFold All-Atom. The article also highlights the successes and applications of AI-driven protein design across diverse domains, such as enzyme engineering, antibody design, and vaccine development. Additionally, the review identifies current challenges and future directions in the field, emphasizing the need to address limitations in modeling conformational dynamics and designing proteins for in vivo functionality. The article concludes by underscoring the potential of AI-driven protein design to transform various aspects of science and technology, while also acknowledging the importance of interdisciplinary collaboration and the development of robust pipelines for the validation and optimization of designed proteins. Overall, this comprehensive review serves as a valuable resource for researchers and practitioners interested in understanding the current state and future prospects of AI-driven protein design.

From the perspective of human cognitive evolution to analyze the origin and sustained development of science, there is a puzzle, because the driving force behind cognitive evolution is natural selection, which favors biological traits improving individual adaptation rather than seeking the truth. Some scholars argue that cultural evolution provides an explanation for the development (or progress) of science, wherein scientific beliefs can be transmitted intergenerationally within the scientific community, thus continually converging toward truth. However, this explanation has ecological validity problem. Research on cultural learning strategies suggests that when choosing beliefs for imitation learning, people tend to consider contextual and content factors rather than the truth value of beliefs. On the other hand, due to the absence of universally accepted criterion for theory selection recognized by all scientists, the best theory choice always fails. I will develop a minimum model for the best theory choice to defend the scientific progress's cultural evolution approach. The criterion for the best theory choice is the mark of a scientific school's establishment and the demarcation line with each other. As a scientific school's member, a scientist could select the best theory as his/her learning model according to the school's criterion. Hence, it is plausible for the approach to explain scientific progress. Finally, my model will show a scientific school is a driver to improve the local scientific progress, and the competition between schools promotes global scientific progress. The school's size and the scientific reasoning diversity decide a result of the competition.

Lipofuscin accumulates with age as intracellular fluorescent granules originating from incomplete lysosomal digestion of phagocytosed and autophagocytosed material. The purpose of this review is to provide an update on the current understanding of the role of oxidative stress and/or lysosomal dysfunction in lipofuscin accumulation and its consequences, particularly for retinal pigment epithelium (RPE). Next, the fluorescence of lipofuscin, spectral changes induced by oxidation, and its contribution to retinal fluorescence are discussed. This is followed by reviewing recent developments in fluorescence imaging of the retina, and the current evidence on the prognostic value of retinal fluorescence for the progression of age-related macular degeneration (AMD), the major blinding disease affecting elderly people in developed countries. The evidence of lipofuscin oxidation in vivo, and the evidence of increased oxidative damage in AMD retina ex vivo lead to the conclusion that imaging of spectral characteristics of lipofuscin fluorescence may serve as a useful biomarker of oxidative damage which can be helpful in assessing the efficacy of potential antioxidant therapies in retinal degenerations associated with accumulation of lipofuscin and increased oxidative stress. Finally, amendments to currently used fluorescence imaging instruments are suggested, to be more sensitive and specific for imaging spectral char-acteristics of lipofuscin fluorescence.

Agricultural workers utilize pesticides extensively on their farms to control weeds and insects, as well as increase crop productivity. Despite these advantages, their excessive use poses a seri-ous threat, particularly to the population living at the nexus of urban and rural areas. Exposure to pesticide drift can be investigated using geospatial tools. Remote sensing technology and Geographic Information Systems (GIS) techniques have been used intensively and constitute trusted tools in different sectors, especially in agriculture. Remote sensing depends on pro-cessing the electromagnetic radiation reflected and emitted from the ground target and can be used to identify the spectral signature of crops exposed to pesticides. GIS has powerful tools for building a spatial geo-database of pesticide exposure drift. Therefore, the major objective of the research was to explore the effectiveness of using remote sensing and GIS techniques to estimate the exposure to pesticides in Macon County (Alabama). To achieve this objective, Maximum Likelihood Classification (MLC) was used to identify accurate cropland areas. The Landsat-8 and Sentinel-2 satellite images. Available agricultural pesticide usage data (seven of the seventeen organophosphates used in Alabama) were obtained through the United States Geological Survey (USGS). The results indicated that 6.6% of Macon County’s residents are considered potentially severely exposed, and the potentially affected population resides primarily in rural areas. While 23 percent of residents of rural edges are considered to have potentially medium to high expo-sure. In addition, 38% of residents living in suburban areas are considered to have potentially low-to-medium exposure. Also, the results indicated that both GIS and remote sensing can play an effective role in estimating pesticide exposure drift.

Work-related thoughts in off-job time have been studied extensively in occupational health psychology and related fields. We provide a focused review of research on overcommitment – a component within the effort-reward imbalance model – and aim to connect this line of research to the most commonly studied aspects of work-related rumination. Drawing on this integrative review, we analyze survey data on ten facets of work-related rumination, namely (1) overcommitment, (2) psychological detachment, (3) affective rumination, (4) problem-solving pondering, (5) positive work reflection, (6) negative work reflection, (7) distraction, (8) cognitive irritation, (9) emotional irritation, and (10) inability to recover. First, we leverage exploratory factor analysis to self-report survey data from 357 employees to calibrate overcommitment items and to position overcommitment within the nomological net of work-related rumination constructs. Second, we leverage confirmatory factor analysis to self-report survey data from 388 employees to provide a more specific test of uniqueness vs. overlap among these constructs. Third, we apply relative weight analysis to quantify the unique criterion-related validity of each work-related rumination facet regarding (1) physical fatigue, (2) cognitive fatigue, (3) emotional fatigue, (4) burnout, (5) psychosomatic complaints, and (6) satisfaction with life. Our results suggest that several measures of work-related rumination (e.g., overcommitment and cognitive irritation) can be used interchangeably. Emotional irritation and affective rumination emerge as the strongest unique predictors of fatigue, burnout, psychosomatic complaints, and satisfaction with life. Our study assists researchers in making informed decisions on selecting scales for their research and paves the way for integrating research on effort-reward imbalance and work-related rumination.

This paper directly addresses a long-standing issue that affects the development of many complex distributed software systems: how to establish quickly, cheaply, and reliably whether they can deliver their intended performance before expending significant time, effort and money on detailed design and implementation. We describe ∆QSD, a novel metrics-based and quality-centric paradigm that uses formalised outcome diagrams to explore the performance consequences of design decisions, as a performance blueprint of the system. The distinctive feature of outcome diagrams is that they capture the essential observational properties of the system, independent of the details of system structure and behaviour. The ∆QSD paradigm derives bounds on performance expressed as probability distributions encompassing all possible executions of the system. The ∆QSD paradigm is both effective and generic: it allows values from various sources to be combined in a rigorous way, so that approximate results can be obtained quickly and subsequently refined. ∆QSD has been successfully used by Predictable Network Solutions for consultancy on large-scale applications in a number of industries, including telecommunications, avionics, and space and defence, resulting in cumulative savings worth billions of US dollars. The paper outlines the ∆QSD paradigm, describes its formal underpinnings, and illustrates its use via a topical real-world example taken from the blockchain/cryptocurrency domain. ∆QSD has enabled challenging throughput targets to be met for a globally distributed blockchain operating on the public internet.

Rates of gestational cannabis use have increased despite limited evidence for its safety in fetal life. Recent animal studies demonstrate that prenatal exposure to 9-tetrahydrocannabinol (9-THC, the psychoactive component of cannabis) promotes intrauterine growth restriction (IUGR), culminating in postnatal metabolic deficits. Given IUGR is associated with impaired hepatic function, we hypothesized that 9-THC offspring would exhibit hepatic dyslipidemia. Pregnant Wistar rat dams received daily injections of vehicular control or 3 mg/kg 9-THC i.p. from embryonic day (E) 6.5 through E22. Exposure to 9-THC decreased the liver to body weight ratio at birth, followed by catch-up growth by three weeks of age. At six months, 9-THC-exposed male offspring exhibited increased visceral adiposity and higher hepatic triglycerides. This was instigated by augmented expression of enzymes involved in triglyceride synthesis (ACC, SCD, FABP1, and DGAT2) at three weeks. Furthermore, the expression of hepatic DGAT1/DGAT2 was sustained at six months, concomitant with mitochondrial dysfunction (i.e., elevated p66shc) and oxidative stress. Interestingly, decreases in miR-203a-3p and miR-29a/b/c, both implicated in dyslipidemia, was also observed in these 9-THC-exposed offspring. Collectively, these findings indicate that prenatal 9-THC exposure results in long-term dyslipidemia associated with enhanced hepatic lipogenesis. This is attributed by mitochondrial dysfunction and epigenetic mechanisms.

The intrusion of seawater in coastal aquifers in Greece is a particularly widespread phenomenon. The coastline of Greece has a length of 15,147 km. Once groundwater resources are contaminated, remediation strategies are difficult, costly and time consuming. In this paper three coastal aquifer systems of Peloponnese are studied. Initially the main ions and cations were calculated for the three aquifers. According to the results from hydrochemical analyzes Na+,Mg2+, Ca2+, SO4-2, Cl- have high values and are affected by the intrusion of seawater into the coastal aquifers. It estimates the vulnerability of groundwater to the intrusion of seawater. Using Geographical Information Systems (GIS) software, maps are prepared for the presentation of each parameter of the GALDIT method. The main factors that affect the seawater intrusion are basically presented in the 6 letters of the acronym GALDIT. The analysis of each parameter is as follows: Groundwater occurrence (aquifer type: unconfined, confined, and leaky confined), Aquifer hydraulic conductivity, depth to groundwater Level above the sea, Distance from the shore (inland distance perpendicular from shoreline), Impact of existing status of sea water intrusion in the area and Thickness of the aquifer. The final map that emerged from the study of the three groundwater systems shows the vulnerability of seawater intrusion in Peloponnese. The maps show that the groundwater system of Larissos presents lower vulnerability to the seawater intrusion compared to the other two groundwater systems. This is because the occurrence of flysch in the northern part of the area acts as a barrier to the penetration of seawater.

Plants have acquired sets of highly regulated and complex signaling pathways to respond to unfavorable environmental conditions during evolution. Calcium signaling, as a vital mechanism, enables plants to respond to external stimuli, including abiotic and biotic stresses, and coordinate the basic processes of the growth and development. In the present study, the calcium sensor families, including CBL and CIPK, were investigated in the halophyte plant, Aeluropus littoralis, with a comprehensive analysis. Here, six AlCBL genes, and twenty AlCIPK genes were presented. The analysis of the gene structure and conserved motifs, as well as physicochemical properties, showed that these genes are highly conserved during evolution. The expression levels of AlCBL genes and AlCIPK genes were evaluated under salt stress in leaf and root tissue. Based on the real-time RT-PCR results, AlCIPK gene family had a higher variation in mRNA abundance compared to the AlCBL gene family. The AlCIPKs were found to have a higher abundance in leaves than in roots. The results suggest that the interaction pattern of AlCBL genes with AlCIPK is tissue-specific, and different interactions can be expected in leaves and roots. Based on these patterns AlCIPK3.1 - AlCBL4.1 and AlCIPK1.2 - AlCBL4.4 can interact in root tissue, while the AlCBL10 has the potential to interact with the AlCIPK5, AlCIPK26 and AlCIPK12.3 in the leaf tissue. These findings provide valuable information on the structure and function of calcium sensor families in Aeluropus littoralis a halophyte plant, for future research on the biological function of CBLs and CIPKs on salt stress resistance.

Studies on human mobility have a long history with increasingly strong connections to multi-disciplines across social science, environmental science, information and technology, computer science, engineering, and health science. However, what is lacking in the current research is a summary of studies on human mobility to identify the evolutional pathway and future research directions. To address this gap, we conduct a systematic review of human mobility-related studies published from 1990 to 2020. Drawing on the selected publications retrieved from the Web of Science, we conduct a bibliometric analysis and network visualisation by CiteSpace and VOSviewer on publication years and numbers, authors and their countries and afflictions, citations, topics, abstracts, keyword, and journals. Our findings show that human mobility-related studies have become increasingly interdisciplinary and multi-dimensional, enhanced by the involvement of multi-source big data, the development of technologies, the innovation of modelling approaches, and the novel applications in various areas. We also summarise four future research directions proposed by top cited authors and mobility studies, in terms of data sources, modelling methods, applications, and technologies. We advocate in-depth research on human mobility to address real-world problems and contribute to social good as promising future orientations through integrating multi-source big data and advanced modelling methods facilitated by artificial intelligence, and machine and deep learning.

Education outside the classroom (EOtC) can be beneficial for students. The relationship between biological stress markers and sedentary behavior (SB) plus physical activity (PA) is insufficiently evaluated in school settings. This exploratory study aims to evaluate the association between students’ cortisol, plus circulating cell-free deoxyribonucleic acid (cfDNA) levels, and their SB, light PA (LPA) and moderate-to-vigorous PA (MVPA) during outdoor and indoor classes in different seasons. We assessed data from an education outside the classroom (EOtC) program (n = 48; intervention group [IG], n = 37; control group [CG], n = 11). We sampled data on 3 school-days in three seasons (fall, spring, and summer) in normal teaching indoors (CG) and outdoor lessons (IG) in the forest. SB and PA were evaluated by accelerometry, and cortisol and cfDNA levels by saliva samples. The compositional data analysis approach analyzed SB and PA. Fitted Bayesian hierarchical linear models evaluated the association between cortisol and cfDNA, and SB/LPA/MVPA. A steady decline of cortisol in the outdoor setting is associated with relatively high levels of LPA. SB and MVPA tended to exhibit a similar effect in the indoor setting. CfDNA is positively associated with a relatively high amount of SB in the IG, the same association is likely for LPA and MVPA in both groups. LPA seems to support a healthy cortisol decrease in children during outdoor lessons. The relevance of SB/PA as a composition in relation to students stress response in school should be emphasized. This study facilitates the formulation of straightforward and directed hypotheses for further research.

Background: Swept-source anterior segment optical coherence tomography (SS-AS- OCT) is a suitable examination for the vitreolenticular interface. Methods: In a prospective study using Anterion (Heidelberg Engineering, Heidelberg, Germany) 102 eyes of 102 patients were examined, in pupil dilation, preoperatively and 6 times over 1-year follow-up. Preoperatively anterior hyaloid membrane (AHM) visibility was determined with Imaging App with high reliability. Postoperatively capsular bag–AHM distance was measured on six points by using Metrics App. Results: The AHM was visible in 18.6% preoperatively and postoperatively as well (Group 1), 49% of the preoperatively adherent AHMs became visible (Group 2A), 32.4% remained attached (Group 2B). Group 1: the average deepest point first day was 782.5 ± 324.1 microns, and it significantly differed from the later follow-up values. Group 2A: the average deepest value was 184.1 ± 220.1 microns, and there was no statistically significant difference between the postoperative visit values. The difference between the groups was statistically significant at every location and at each time points. Conclusions: AS-SS-OCT can be used to check BS both preoperatively(with limitations) and postoperatively.

In this digital era, online learning and teaching is an important platform for college and university learners which required many technical facilities and in depth knowledge to have learning process effectively. Students and teachers in Higher Education Institutions (HEIs) were forced to grapple with the inevitability of shifting to online classes due to the advantages of effective distance learning or for large learning group. In the case of Oman, there have been some efforts to integrate alternative learning mechanisms such as online and mobile education in the past but not followed the scale in the post pandemic world. This study seeks to utilize the principles of Total Quality Management (TQM) through the implementation of Quality Function Deployment (QFD) as a way to better understand the experiences of Omani teachers and students from HEIs. A voice of customer from teachers and students have been collected and recorded. In this regard, 165 staff and 355 students from HEIs of Engineering participated in the survey. After the survey, a house of quality analysis was done to analyze the requirements based on how strongly they are related to the standard learning outcomes expected from HEIs in Oman. The results show that more attention is required in online education in the Sultanate of Oman before it is implemented as a major part in learning and teaching.

The aim was to study alterations of bacterial communities in patients undergoing hip or knee arthroplasty to assess the impact of chlorhexidine gluconate soap decolonisation and systemic antibiotic prophylaxis. A Swedish multicentre, prospective collection of samples obtained from elective arthroplasty patients (n=83) by swabbing anterior nares, skin sites in the groin and the site of planned surgery, before and after arthroplasty surgery, was analysed by 16S rRNA (V3-V4) gene sequencing and a complementary targeted tuf gene sequencing approach to comprehensively characterise alterations in staphylococcal communities. Significant reductions in alpha diversity was detected for both bacterial (p=0.04) and staphylococcal (p=0.03) groin communities after arthroplasty surgery with significant reductions in relative Corynebacterium (p=0.001) abundance and S. hominis (p=0.01) relative staphylococcal abundance. In nares, significant reductions occurred for S. hominis (p=0.02), S. haemolyticus (p=0.02), and S. pasteuri (p=0.003) relative to other staphylococci. S. aureus colonised 35% of anterior nares before and 26% after arthroplasty surgery. S. epidermidis was the most abundant staphylococcal species at all sampling sites. No bacterial genus or staphylococcal species increased significantly after arthroplasty surgery. Application of a targeted tuf gene sequencing approach provided auxiliary staphylococcal community profiles and allowed species-level characterisation directly from low biomass clinical samples.

: For a long time, atherosclerosis has been regarded as a mere lipid deposit in the blood vessels. However, in the recent years a growing body of experimental and clinical evidence have highlighted the role of inflammation and immunity as a central mechanism of disease. Moreover, in the last decade the coming of next-generation sequencing and its application to large human population has broken the barrier between inflammation and cancer. Indeed, acquired mutation in key genes related to the control of hematopoiesis and myeloproliferation have paved the way to establish the new concept of clonal hematopoiesis of indeterminate potential. This phenomenon is being considered not such “indeterminate”, but as an emerging cardiovascular risk factor. Thus, this may explain the mechanisms of myeloproliferation and inflammation in atherosclerosis. And in a bidirectional journey, it has helped to explain the extremely high cardiovascular risk in cancer survivors, in particular in myeloprolfierative neoplasm patients. A deeper understanding of these mechanisms may pave the way for the future early diagnosis and potential preemptive treatments of the leading worldwide cause of death.

The pharmaceutical industry is one of the largest pollutants and generator of toxic solvent resi-dues for the environment and human beings. In the last decade, there has been a huge evolution in the design and development of new environmentally friendly products and processes, in re-sponse to the global environmental concern and the growing demand for products with quality ingredients and manufacturing processes aimed at achieving sustainability. Consumers are looking for products with the benefits of natural products, with sustainable and environmentally friendly formulations with few synthetic molecules as possible. Thus, based on the origins of the pharmaceutical industry, it is important to return to Nature and enjoy the benefits that natural products bring to us. Deep eutectic solvents appear as an alternative to toxic solvents commonly used to extract bioactive compounds. These solvents are considered green solvents because they are made up of natural compounds such as sugars, amino acids, and carboxylic acids. In addition, they are simple to prepare, with an atomic economy of 100%, with attractive physicochemical properties. This paper is a comprehensive review in which is described the main properties, characteristics, and production methods of deep eutectic solvents as well as its application to extract from natural sources bioactive compounds with pharmaceutical interest.

The paper presents the numerical and experimental results of research aimed at determining the influence of hardness in the range of 50-90 Shore A of layered tools made of elastomeric materials on the possibility of forming Inconel 625 nickel-based alloy sheets. A stamping die made of 90MnCrV8 steel (hardness 60HRC) was designed for forming embosses in drawpieces, ensuring various stress states on the cross-section of the formed element. The principle of operating the stamping die was based on the Guerin method. Finite element-based numerical modelling of the forming process for various configurations of polyurethane inserts was also carried out. The drawpieces obtained by sheet forming were subjected to geometry tests using optical 3D scanning. The results confirm that in the case of forming difficult-to-deform Inconel 625 Ni-based alloy sheets, the hardness of the polyurethane inserts significantly affects the geometric quality of the obtained drawpieces. The assumptions made in numerical simulations were verified in experimental studies. Based on the test results, it was concluded that the selection of polyurethane hardness should be determined by the shape of the formed element. Significant non-uniform sheet metal deformation was also found, which may pose a problem in the process of designing forming tools and technology of plastic forming of Inconel 625 Ni-based alloy sheets.

The boreal Hemisphere has been experiencing increasing extreme hot and dry conditions over the past few decades, consistent with anthropogenic climate change expectations. The continental extension of the phenomenon calls for tools and techniques capable of monitoring the global to regional scales. In this context, the satellite is the only system that can satisfy the need for global coverage. The main objective we have addressed in the present paper is the capability of infrared satellite observations helping to monitor the vegetation stress due to increasing drought and heatwaves in summer. We have designed and implemented a new water deficit index (wdi) that exploits satellite observations in the infrared to retrieve humidity, air temperature, and surface temperature simultaneously. These three parameters are combined to provide the water deficit index. The index has been developed based on the Infrared Atmospheric Sounder Interferometer or IASI, which covers the infrared spectral range 645 to 2760 cm-1 with a sampling of 0.25 cm-1. The index has been used to study the 2017 heatwave, which hit Continental Europe from May to October. In particular, we have examined Southern Italy, where Mediterranean forests suffer from climate change. We have computed the index's time series and show that it can be used to indicate the atmospheric background conditions associated with meteorological drought. We have also found a good agreement with soil moisture, which suggests that the persistence of anomalously high water deficit index was an essential driver of the rapid development and evolution of the exceptionally severe 2017 droughts.

Cotton (Gossypium spp.) is the most important fibre crop worldwide. Black root rot and Fusarium wilt are two major diseases of cotton caused by soil-borne Berkeleyomyces rouxiae and Fusarium oxysporum f. sp. vasinfectum (Fov), respectively. Phenotyping plant symptoms caused by soil-borne pathogens has always been a challenge. To increase the uniformity of infection, we adapted a seedling screening method that directly uses liquid cultures to inoculate the plant roots and the soil. Four isolates each of B. rouxiae and Fov were collected from cotton fields in Australia and were characterised for virulence on cotton under controlled plant growth conditions. While the identity of all four B. rouxiae isolates were confirmed by multi-loci sequencing, only two of them were found to be pathogenic on cotton, suggesting variability in the ability of isolates of this species to cause disease. The four Fov isolates were phylogenetically clustered together with the other Australian Fov isolates and displayed both external and internal symptoms characteristic of Fusarium wilt on cotton plants. Furthermore, the isolates appeared to induce varied levels of plant disease severity indicating differences in their virulence on cotton. To contrast the virulence of the Fov isolates, four putatively non-pathogenic Fusarium oxysporum (Fo) isolates collected from cotton seedlings exhibiting atypical wilt symptoms were assessed for their ability to colonise cotton host. Despite the absence of Secreted In Xylem genes (SIX6, SIX11, SIX13 and SIX14) characteristic of Fov, all four Fo isolates retained the ability to colonise cotton and induce wilt symptoms. This suggests that slightly virulent strains of Fo may contribute to the overall occurrence of Fusarium wilt in cotton fields. Findings from this study will allow better distinction to be made between plant pathogens and endophytes and allow fungal effectors underpinning pathogenicity to be explored.

Outliers seriously affect the accuracy in geometric model fitting. Previous works in coping with outliers involve threshold selection and scale estimation. However most scale estimators suppose the inlier distribution as a Gaussian model, which usually poorly meets the cases in geometric model fitting. Outliers, considered as the points with big residuals to all the true models, share common items with big values in quantized residual preferences, thus making the outliers gather away from the inliers in quantized residual preference space. In this paper we make use of this outlier consensus in quantized residual preference space by extending the usage of energy minimization to combine the model error and the spatial smoothness in quantized residual preference space for outlier detection. The energy minimization based outlier detection process follows an alternate sampling and labeling framework. After the outlier detection, an ordinary energy minimization method is employed to optimize the inlier labels, which also follows the framework of alternate sampling and labeling. The experimental results in this study show that the energy minimization based outlier detection method can detect most of the outliers in the data. Furthermore, the proposed energy minimization based inlier segmentation process segments the inliers into different models quite accurately. Overall, the performance of the proposed method is better than most of the state-of-the-art methods.

Coronavirus Disease-2019 (COVID-19) is an infectious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). There is sufficient experimental evidence to confirm that SARS-CoV-2 infection produces states of ciliary and flagellar dysfunction. However, these studies are unable to explain the observed effects molecularly, because they lack a sufficient understanding of the interaction between human proteins and virus proteins. Using the physical-chemical study of the human interactome in interaction with the SARS-CoV-2 proteome, we found evidence of interactions to explain the experimental effects from a molecular perspective. We found that ten viral proteins interact with key components in the maintenance of the molecular structure of axoneme. Additionally, we evaluated the pulmonary and extrapulmonary pathogenesis of COVID-19 from the point of view of ciliary dysfunction, and warned about other possible complications such as episodes of transient infertility that, due to the limitations of our work, would need verification.

Viroids are smallest pathogen that consist of non-capsidated, single-stranded non-coding RNA replicons and exploits host factors for their replication and propagation. The severe stunting disease caused by Citrus bark cracking viroid (CBCVd) is a serious threat, which spread rapidly within hop gardens. In this study, we employed comprehensive transcriptome analyses to dissect host-viroid interactions and identify gene expression changes associated with disease development in hop. Our analysis revealed that CBCVd-infection resulted in the massive modulation of activity of over 2000 genes. Expression of genes associated with plant immune responses (protein kinase and mitogen-activated protein kinase), hypersensitive responses, phytohormone signaling pathways, photosynthesis, pigment metabolism, protein metabolism, sugar metabolism and modification and others were altered, which could be attributed to systemic symptom development upon CBCVd-infection in hop. In addition, genes encoding RNA-dependent RNA polymerase, pathogenesis-related protein, chitinase as well as those related to basal defense responses were up-regulated. The expression levels of several genes identified from RNA sequencing analysis were confirmed by qRT-PCR. Our systematic comprehensive CBCVd-responsive transcriptome analysis provides a better understanding and insights into complex viroid-hop plant interaction. This information will assist further in the development of future measures for the prevention of CBCVd spread in hop fields.

Recently, polyacetylene (PA) is receiving a renewed scientific attention due to its electrical properties potentially useful for energy applications (e.g., fabrication of electrodes for batteries and supercapacitors) and unique functional characteristics (e.g., flame retardant, oxygen scavenger, EMI-shielding, etc.). This chemical compound can be obtained in form of a polyacetylene-PVOH copolymers simply by chemical dehydration of poly(vinyl alcohol) (PVOH), which is a very common type of polymer, widely used in packaging and other technological areas. This very inexpensive chemical reaction for the large-scale synthesis of PA/polyvinylenes has been investigated by reacting PVOH with fuming sulfuric acid at room temperature. In this process, PVOH, shaped in form of film, is dipped in fuming sulfuric acid (i.e., H₂SO₄ at 95-97%) and, after complete chemical-dehydration, it has been mechanically removed from the liquid phase by using a nylon sieve. The reduction process leads to a substantial PVOH film conversion to PA as it has been proved by infrared spectroscopy (ATR-mode). Indeed, the ATR spectrum of the reaction product included all characteristic absorption bands of PA. The reaction product has been also characterized by UV-Vis spectroscopy in order to evidence the presence in the structure of conjugated carbon-carbon double bonds of various lengths. Differential scanning calorimetry (DSC) and thermogravimetric analysis have been used respectively to investigate the PA solid-state cis-trans isomerization and thermal stability in air and nitrogen, respectively.

Prostate cancer is the second leading cause of death in males in America, with advanced prostate cancers exhibiting a 5-year survival rate of only 32%. Castration-resistance is often developed during the course of treatment, though its influences require further understanding. This study explores the human microbiome for its implications in castration-resistance and metastasis in prostate cancer. RNA sequencing data was downloaded for bone and soft tissue biopsies of patients with metastatic castration-resistant prostate cancer. These sequences were mapped to bacterial sequences to yield species-level abundance approximations. Numerous species were found to correlate to the expression of known markers of castration-resistance, including AR, PI3K, and AKT. Castration-resistance-associated signaling pathways were also enriched with these species, including PI3K-AKT signaling and endocrine resistance. For their implications in cancer aggression and metastasis, cancer stem cell markers were further explored for relation to these species. EGFR and SLC3A2 were widely downregulated with greater abundance of most species. Our results suggest that the microbiome is heavily associated with castration-resistance and stemness in prostate cancer. By considering the microbiome’s importance in these factors, we may better understand the highly aggressive and highly invasive nature of prostate cancer, allowing for needed improvement in the treatment of this disease.

We construct a Bayesian estimator for the dilution of a wastewater sample. When wastewater is diluted by rainwater an estimate of the level of dilution is required if we are to normalise sample measurements of disease markers such as SARS-CoV-2 RNA. We consider the situation where flow measurements are available, but will regularly be unreliable because of the action of combined sewer outflows (CSOs) and wastewater storage tanks, which divert wastewater away from treatment plants when the flow is excessive. However, we also have proxies for the flow from various chemical markers (e.g.\ phosphate, ammonium, electrical conductivity), whose level per unit of population is fixed. The new flow estimator has multiple advantages compared to existing procedures: credible intervals for the estimates; optimal weighting of the chemical markers; systematic handling of missing and censored values; and model based smoothing without lags.

This paper seeks to model the crack propagation in of AAs (aluminum-alloys) 2524-T3 and 7050-T7452 subjected to fatigue loading at low temperature. Fatigue crack growth tests were performed on AAs 2524-T3 and 7050-T7452 subjected to constant-amplitude and actual random-spectra loading histories at room temperature of about 25 °C and at cryogenic temperature of -70 °C, respectively, to determine their crack growth properties and residual lives. The interaction mechanisms between cryogenic temperature and the fatigue load were deduced on the basis of the results of fractographic analysis. Temperature-dependent residual lives under actual random-spectrum load history were modeled based on a modified accumulation damage rule by accounting for the load interaction. Good correlation was achieved between the predictions and actual experiments, demonstrating the practical and effective use of the proposed method.

Bio-molecular reagents like antibodies required in experimental biology are expensive and their effectiveness, among other things, is critical to the success of the experiment. Although such resources are sometimes donated by one investigator to another through personal communication between the two, there is no previous study to our knowledge on the extent of such donations, nor a central platform that directs resource seekers to donors. In this paper, we describe, to our knowledge, a first attempt at building a web-portal titled Bio-Resource Exchange that attempts to bridge this gap between resource seekers and donors in the domain of experimental biology. Users on this portal can request for or donate antibodies, cell-lines and DNA Constructs. This resource could also serve as a crowd-sourced database of resources for experimental biology. Further, in order to index donations outside of our portal, we mined scientific articles to find instances of donations of antibodies and attempted to extract information about these donations at the finest granularity. Specifically, we extracted the name of the donor, his/her affiliation and the name of the antibody for every donation by parsing the acknowledgements sections of articles. To extract annotations at this level, we propose two approaches – a rule based algorithm and a bootstrapped relation learning algorithm. The algorithms extracted donor names, affiliations and antibody names with average accuracies of 57% and 62% respectively. We also created a dataset of 50 expert-annotated acknowledgements sections that will serve as a gold standard dataset to evaluate extraction algorithms in the future. Contact: madhavi@pitt.edu, madhavi@cs.cmu.edu Database URL: http://tonks.dbmi.pitt.edu/brx Supplementary information: Supplementary data are available at Database online.

We present a very computationally light and fast approximation algorithm and then verify it with genetic algorithm and simulated annealing. We show that our algorithm is on par with GA and SA in terms of output produced while having a tightly bounded time complexity. Our algorithm works best when there is a strong positive correlation between the reliability of a component and its cost. We present two algorithms with the same essence. One of them is system cost bounded and the other is target reliability bounded. Our proposed algorithm works on a subsystem level redundancy instead of component level redundancy.

Approaches to identification of metabolites have progressed from early biochemical pathway evaluation to modern high dimensional metabolomics which is a powerful tool to identify and characterize biomarkers of health and disease. While traditionally considered relevant in the context of classic metabolic diseases, immunometabolism has emerged as an important area of study as leukocytes generate key metabolites important to innate and adaptive immunity. Herein we discuss the metabolomic signatures and pathways perturbed during infection as well as vaccination. For example, changes in lipid and amino acid pathways (e.g., tryptophan, serine, and threonine) have been noted during infection while carbohydrate and bile acid pathways have shift upon vaccination. Metabolomics holds substantial promise to provide fresh insight into the molecular mechanisms underlying host response to infection and vaccination, and its integration with other systems biology platforms will add further impact to our studies of health and disease.

Precipitates are the primary source of strength for the Al-Mg-Si alloy. Aluminum alloy in the peak-aged state mainly contain β'' and β' precipitates. In the past, most of the literature only considered the strengthening effect of β''. Here we develop a single crystal intensity model including both precipitate enhancement effects for the first time. This model was subsequently implemented into a crystal plastic finite element method to model the uniaxial tensile process of a polycrystalline aggregate model of Al-Mg-Si alloy. The simulation results for uniaxial stretching are in good agreement with the experimental results, confirming that the constitutive parameters used for the single crystal strength model with two precipitates are based on realistic physical implications. Furthermore, by comparing the uniaxial tensile simulation results of a peak-aged alloy considering the actual precipitated phase composition of the alloy with those assuming that the precipitated phase is only the β'' phase, the predicted tensile strength of the former is around 5.65% lower than that of the latter, suggesting that the two kinds of precipitation should be considered separately when simulating the mechanical response of Al-Mg-Si alloy. It is highly expected that the present simulation strategy is not limited to the Al-Mg-Si alloys, and it can be equally applied to the other age-enhanced alloys.

As global economic integration and rapid technological advancements transform international business, international engineering contracting has become essential for achieving sustainable development goals (SDGs). This paper investigates the significant impact of China’s strategic initiatives, notably the "Going Global" strategy and the Belt and Road Initiative (BRI), on the operational practices of Chinese enterprises involved in overseas investments. Central to this transformation is the Engineering, Procurement, and Construction (EPC) model, which emphasizes the integration of supply chain management and stakeholder collaboration to enhance performance in international EPC projects and underscores the crucial role of these elements in promoting sustainability. Incorporating insights from social network data analysis, this study reveals that contractors collaborating with various stakeholders—such as owners/consulting engineers, domestic and foreign customs departments, and group headquarters/design parties—exhibit a high degree of similarity in personnel profiles. This suggests that the internal organizational structure and personnel allocation of contractors could be optimized to enhance operational efficiency, aligning with the collaborative patterns identified. This study addresses a critical research gap by exploring how effective supply chain management and collaborative stakeholder engagement within multinational EPC projects contribute to sustainable outcomes. Employing advanced social network analysis software, the research examines the complex interactions among stakeholders and their influence on procurement dynamics. Findings indicate that strong relational networks and strategic collaborations significantly enhance procurement efficiency and project success, underscoring the importance of supply chain integration. Ultimately, integrating supply chain management principles into the EPC model not only offers innovative perspectives for advancing sustainability in international projects but also provides actionable insights for improving project outcomes within the BRI framework. This research underscores the pivotal role of supply chain organization and stakeholder cooperation in achieving sustainability objectives, thereby enriching the discourse on sustainable enterprise operation and supply chain management in the context of global initiatives.

Genetic engineering has revolutionized our ability to modify microorganisms for various applications in agriculture, medicine, and industry. This review examines recent advances in genetic engineering techniques for bacteria, fungi, and oomycetes, with a focus on CRISPR-Cas systems. In bacteria, CRISPR-Cas9 has enabled precise genome editing, enhancing applications in antibiotic production and metabolic engineering. For fungi, despite challenges associated with their complex cell structures, CRISPR/Cas9 has advanced the production of enzymes and secondary metabolites. In oomycetes, significant plant pathogens, modified Agrobacterium-mediated transformation and CRISPR/Cas12a have contributed to developing disease-resistant crops. The review provides a comparative analysis of genetic engineering efficiencies across these microorganisms and addresses ethical and regulatory considerations. Future research directions include refining genetic tools to improve efficiency and expand applicability in non-model organisms. This comprehensive overview highlights the transformative potential of genetic engineering in microbiology and its implications for addressing global challenges in agriculture, medicine, and biotechnology.

As hen body weight (BW) impacts egg weight (EW) and feed efficiency, egg producers prefer pullets of a specific size to enter the egg-laying cycle. Lighting and feeding programs were tested to achieve target pullet BW. Three feeding programs: Ad libitum (Ad lib); feeding to achieve breed standard weight for age (BSW); feeding to achieve 88% BSW (managed) were used with either control lighting, (CL: 10h light/d from 7 weeks of age (WOA)) or reduced lighting (RL: 9h light/d from 4 WOA). At 16 WOA pullets moved to cages and ad libitum feeding under a step-up photoperiod reaching 16h at 33 WOA. The age and weight of first egg, BW, feed intake (FI), egg production (EP) and EW were measured until 36 WOA. At 16 WOA, pullets reared with Ad lib feeding under CL had higher BW and cumulative FI (CFI) compared to Ad lib feeding under RL. The latter were the earliest and managed pullets under CL the latest, to lay. Control lighting and BSW independently generated the heaviest first eggs. At 36 WOA, BW, EW, CFI and CEP were highest following Ad lib feeding during rearing while CL generated higher BW and EW but lower CEP than RL. Hence lighting and feeding programs throughout rearing can regulate pullet growth and, hen performance throughout early lay.

Preventive Maintenance (PM) is a periodic maintenance strategy, which has great results for devices in extending their life, increasing productivity, and most importantly, help avoid unexpected breakdowns and their costly consequence. A preventive maintenance scheduling (PMS) is determining the time for carrying out PM, and it represents a sensitive issue in terms of impact on production if the time for the PM process is not optimally distributed. In this study, hybrid heuristic methods were used to solve the PMS problem, as genetic algorithm and Tabu research were adopted. The optimal solution was reached in a short time compared to previous studies in which optimal methods were used, integer programming and nonlinear integer programming. Also, sensitivity analysis was applied to measure the robustness and strength of the method used, where an optimal solution was obtained for all experiments and in record time. This method can be used for power plants in privet or public sectors, to generate an optimal PMS, to save money, and to avoid water or electricity cuts.

This work presents a novel approach for the study of the movement of droplets on inclined surfaces under the influence of gravity and chemical heterogeneities. The developed numerical methodology uses data-driven modeling to extend the applicability limits of an analytically derived reduced-order model for the contact line velocity. More specifically, while the reduced-order model is able to capture the effects of the chemical heterogeneities to a satisfactory degree, it does not account for gravity. To alleviate this shortcoming, datasets generated from direct numerical simulations are used to train a data-driven model for the contact line velocity, which is based on the Fourier neural operator and corrects the reduced-order model predictions to match the reference solutions. This hybrid surrogate model, which comprises of both analytical and data-driven components, is then integrated in time to simulate the droplet movement, offering a speedup of five orders of magnitude compared to direct numerical simulations. The performance of this hybrid model is quantified and assessed in different wetting scenarios, by considering various inclination angles and values for the Bond number, demonstrating the accuracy of the predictions as long as the adopted parameters lie within the ranges considered in the training dataset.

Introduction: Despite great advances in the treatment of oncological diseases, the development of medical technologies to prevent or reduce complications of therapy, in particular, those associated with surgery and the introduction of antibiotics remains relevant. The aim of the study: to evaluate the effectiveness of the use of autoprobiotics based on indigenous non-pathogenic strains of Enterococcus faecium and Enterococcus hirae in the complex therapy of colorectal cancer (CRC) in the early postoperative period. Materials and methods: A total of 36 patients diagnosed with CRC were enrolled in the study. The study group (Group A) comprised 24 CRC patients who received autoprobiotic therapy in the early postoperative period, while the control group (Group C) included 12 CRC patients without autoprobiotic therapy.Prior to surgery and between days 14-16 post-surgery, comprehensive evaluations were conducted on all patients, encompassing the following: stool and gastroenterological complains analysis. examination of the gut microbiota (bacteriological study, quantitative polymerase chain reaction, metagenome analysis), analysis of interleukins in serum. Results: The use of autoprobiotics led to decrease dyspeptic complaints after surgery, was associated with absence of postoperative complications, did not cause side effects, led to a decrease in the level of pro-inflammatory cytokines (IL-6 and IL-18) in the blood serum. The use of autoprobiotics led to positive changes in the structure of escherichia and enterococci populations, the elimination of Parvomonas micra, Fusobacterium nucleatum, decrease in the quantitative content of Clostridium perfringens, Akkermansia muciniphila. Metagenomic analysis (16S rRNA) revealed an increase in alpha diversity. Conclusion: The administration of autoprobiotics in the postoperative period is highly effective and safe in the comprehensive treatment of colorectal cancer patients. Future studies will allow the discovery of additional fine mechanisms of autoprobiotic therapy and its impact on the digestive, immune, endocrine and neural systems.

This study evaluated the neuroprotective potential of peptain-1 conjugated to a cell-penetrating peptide (CPP-P1) in an ocular hypertension model of glaucoma. Brown Norway (BN) rats were subjected to intraocular pressure (IOP) elevation via intracameral injection of silicone oil (SO), with concurrent intravitreal injections of either CPP-P1 or a vehicle. Retinal cross-sections were analyzed for markers of neuroprotection, including cAMP Response Element-Binding Protein (CREB), phosphorylated CREB (p-CREB), growth-associated protein-43 (GAP43), synapsin-1 (SYN1), and superoxide dismutase 2 (SOD2). Hematoxylin and eosin staining was used to assess retinal layer thickness. SO-treated rats exhibited significant reductions in the thickness of the inner nuclear layer (INL, 41%, p=0.016), inner plexiform layer (IPL, 52%, p=0.0002), and ganglion cell layer (GCL, 57%, p=0.001). CPP-P1 treatment mitigated these reductions, preserving INL thickness by 32% (p=0.059), IPL by 19% (p=0.119), and GCL by 31% (p=0.057). Increased levels of CREB and p-CREB were observed in IOP-elevated, CPP-P1-treated retinas compared to IOP-elevated vehicle-treated retinas. Although overall GAP43 levels were low, there was a modest increase in expression within the IPL and GCL in SO- and CPP-P1-treated retinas (p=0.15 and p=0.09, respectively) compared to SO- and vehicle-treated retinas. SO injection reduced SYN1 expression in both IPL and GCL (p=0.01), whereas CPP-P1 treatment significantly increased SYN1 levels in the IPL (p=0.03) and GCL (p=0.002). While SOD2 expression in the GCL was minimal across all groups, a trend toward increased expression was observed in CPP-P1-treated animals (p=0.16). The SO model was replicated with SO removal after 7 days and monitored for 21 days followed by retinal flat-mount preparation to assess retinal ganglion cell (RGC) survival. A 42% loss in RGCs (p=0.009) was observed in SO-injected eyes, which was reduced by approximately 37% (p=0.03) with CPP-P1 treatment. These findings suggest that CPP-P1 is a promising neuroprotective agent that promotes retinal ganglion cell survival and the preservation of other retinal neurons, potentially through enhanced CREB signaling in a rat model of SO-induced ocular hypertension.

The human mandible's cancellous bone, which is characterized by its unique porosity and directional sensitivity to external forces, is crucial for sustaining biting stress. Traditional CAD models fail to fully represent bone's anisotropic structure and thus depend on simple isotropic assumptions. For our research, we use the latest versions of nTopology and Creo Parametric software to make biomimetic Voronoi lattice models that accurately reflect the complex geometry and mechanical properties of trabecular bone. The porosity of human cancellous bone is accurately modeled in this work using biomimetic Voronoi lattice models. The porosities range from 70% to 95%, which can be achieved by changing the pore sizes to 1.0 mm, 1.5 mm, 2.0 mm, and 2.5 mm. Finite element analysis (FEA) was used to examine the displacements, stresses, and strains acting on dental implants with a buttress thread, abutment, retaining screw, and biting load surface. The results show that the Voronoi model accurately depicts the complex anatomy of the trabecular bone in the human jaw, compared to standard solid block models. The ideal pore size for biomimetic Voronoi lattice trabecular bone models is 2 mm, taking into account both the von Mises stress distribution over the dental implant, screw retention, cortical bone, cancellous bone, and micromotions. This pore size displayed balanced performance by successfully matching natural bone's mechanical characteristics. Advanced finite element analysis (FEA) improves biomechanical understanding of how bones and implants interact by creating more accurate models of biological problems and dynamic loading situations. This makes biomechanical engineering better.

Northern Nigeria has had historically low antenatal care (ANC) utilization rates with poor health outcomes. Group antenatal care (gANC) improves ANC behavior and pregnancy outcomes. The gANC has been adopted in Kaduna and Kano states, Nigeria. This paper presents baseline findings from the evaluation of the implementation of the gANC program to support scaling in real-world setting. Baseline data were collected from a cohort of 1,269 and 1,200 pregnant women enrolled in gANC at health facilities in Kaduna and Kano states respectively from March to April 2024. Analyses of socio-demographic and pregnancy behavior data were done. Participants were mostly between ages 19-31 years, married or living with a partner, with over 50% having their own businesses. Over 62% and 34% had completed secondary or higher-level education with 60% and 80% living in urban areas in Kaduna and Kano States, respectively. In Kano State, >60% of the women had their last delivery at home with 41.6% not assisted by a skilled birth attendant. In Kaduna, >63% delivered in the hospital and >50% had skilled attendance during labor. Almost half had not used contraceptives previously. Subsequent longitudinal data will examine the impact of gANC utilization on perinatal outcomes.

Decision sciences (DSC) involve studying complex dynamic systems and processes to aid informed choices subject to constraints in uncertain conditions. It integrates multidisciplinary methods, techniques, and strategies to evaluate decision engineering processes, identifying alternatives and providing insights towards enhancing prudent decision-making. This study analyzes the evolutionary trends and innovation in DSC education and research to uncover the transformations over the years. We employ the science mapping method, text analytics, and metadata from bibliographic databases to evaluate thematic and social structures. The results highlight data science methods, including data mining and business/learning analytics as essential components. The evolutionary trends in DSC education and research mirror the development in practice, including technological transformation, computer science advances, and engineering processes. Sustainable education through virtual/online learning also constitutes a significant component of scientific production. The evolutionary trends in DSC education and research highlight innovative pedagogical approaches and strategies, including computer simulation and games ('play and learn'). The current era witnessed generative artificial intelligence (GenAI) adoption (e.g., ChatGPT) in teaching, learning, and scholarly activities amidst challenges (academic integrity, plagiarism, intellectual property violations, and other ethical and legal issues). Future research will implement and integrate AI automatic detection systems to address some GenAI adoption challenges.

This paper aims to explore the relationship between airfoil deformation and airfoil aerial-aquatic adaptation. The form of “flexible skin and rigid drive structura” holds immense potential for various applications. In this study, we utilize the B-spline method to parametrically describe the airfoil shape. An airfoil deformation parameterization method is proposed based on the isogeometric method. This method allows us to depict airfoil deformation as the position and displacement of the driving point, enabling an expression of the flexible skin's deformation driven by the internal structure. We utilize the Xfoil application and Gaussian regression method to elucidate the relationship between driving point position and displacement and the airfoil's dynamic performance. Additionally, we employ the Sobol method to assess the sensitivity of the driving point variables to the airfoil's dynamic performance. Our findings indicate that the attack angle of the airfoil exhibits the highest sensitivity index to the airfoil's dynamic performance. Furthermore, variables of the driving point situated at the leading and trailing edges of the lower surface significantly impact the airfoil lift coefficient, those located at the mid-section of the upper surface have a considerable effect on the airfoil drag coefficient.

Bio-inspired gyroid triply periodic minimum surface (TPMS) lattice structures have been the focus of research in automotive engineering because they can absorb a lot of energy and have wider plateau ranges. The main challenge is determining the optimal energy absorption capacity and accurately capturing plastic plateau areas using finite element analysis (FEA). Using nTop's Boolean subtraction method, this study combined walled TPMS gyroid structures with normal TPMS gyroid lattice. This made a composite TPMS-gyroid lattice with relative densities ranging from 14% to 54%. Using the ideaMaker software and the fused deposition modeling (FDM) Raise3D Pro 2 3D printer to print polylactic acid (PLA) bioplastics in 1.75 mm filament made it possible to slice computer aided design (CAD) models and fabricate 36 lattices samples precisely layer by layer technique. Shimadzu 100kN testing equipment was utilized for the mechanical compression experiments. And the validation using finite element analysis (FEA). Further, CTG was examined using a field emission scanning electron microscope (FE-SEM) before and after compression testing. The composite TPMS gyroid lattice showed potential as shock absorbers for vehicles with relative densities of 33%, 38%, and 54%. The Gibson-Ashby model showed that the composite TPMS gyroid lattice deformed mainly by bending, and the size effect was seen when the relative densities were less than 15%. The lattice's relative density had a significant impact on its ability to absorb energy. The research also explored the use of these innovative foam-like composite TPMS-gyroid lattices in high-speed crash box scenarios, potentially enhancing vehicle safety and performance.

There is a need to develop tools for mastitis management in goats and to measure the effects of milking machines on teats. Infrared thermography (IRT), as shown in cows, was a good candidate for early detection of mastitis and focusing on milking equipment and settings implicated in potential problems. The aim of this study was to test IRT to detect udder inflammation and the effects of mechanical milking on teats in relation to inflammation status, udder balance and teat shape in Alpine goats. IRT spectra were compared before and after milking in 551 goats from three commercial herds compared to their individual SCC (somatic cell count). We found no regression or trend between logSCC and IRT measurement or response to milking, even in highly inflamed goat udders. The effect of milking was significant (P

In recent years, the economics of emotions (EoE) field, which aims to create models of the human mind, has grown quickly. EoE models work well with simulation theory (ST), which is one of the main theories of mind. EoE models show how people's behavior and emotions change based on their knowledge and perception of others. It is hoped that by developing this model, it will be possible to quantitatively analyze not only the mental states of real others, but also the subtleties of the minds of characters in novels in the future. Until now, the decision-making or the factual-reasoning mechanisms have been a black box in ST. This study analyzes how EoE models add to the understanding of ST.

The aim of this paper is to apply all the existing pyranometric method, to estimate the sunshine duration from the global solar irradiation, in order to find in their original form the most suitable method for a tropical site. Then, in a second step, one of these methods will be optimized to well fit tropical sites. Five methods in the literature (Step Algorithm, Carpentras Algorithm, Slob & Monna Algorithm, Slob & Monna 2 Algorithm, and Linear Algorithm) were applied with eleven years of global and diffuse solar radiation data. As a result, in their original form, the Step Algorithm is on the first rank. But in the second step, after improving its main coefficients, the Carpentras Algorithm was found to be the best algorithm for tropical site in the southern hemisphere.

Meningitis is a severe disease associated with death in children under five with highest rates of infections under age of one. Vaccines for Neisseria meningitides and Haemophilus influenza are used to prevent the main causative agents of meningitis. Administration of H. influenzae type b (Hib) vaccine is recommended at 2, 4 and 6 months with a booster dose at 18 months. N. meningitidis has two commercially available vaccines, the pure polysaccharide is recommended at 24 months meanwhile the protein-conjugated vaccines at 12 months. We sought in this study to examine if coadministering the vaccines for the two main meningitis causing bacteria might be synergistic as a preliminary step towards the possibility of shuffling immunization schedule. So, we coadministered Hib vaccine with commercially available vaccines either quadrate (ACWY) polysaccharide meningococcal (Men) or conjugated meningococcal (Nim) vaccines in Balb/C mice (n = 6/group) and compared to each vaccine administered separately and controls. Thirty-five days post immunization, we measured specific antibodies titers. Hib vaccine increased Men antibody titers significantly for serotypes Y and W. When Hib vaccine was coadministrated with Nim, antibody titer for Y, W and A significantly increased. For serotype C, there was no significant difference in antibody titers among immunized groups. As for effect of meningococcal vaccines on Hib, Men significantly increased Hib antibody titers while Nim had no effect. Collectively, our data suggested that coadministration of Hib and Men or Nim vaccines was safe and had synergistic effect on immune responses elicited to both vaccines. Further studies are needed before immunization schedule modifications. Such immunization schedule recommendation should provide better protection against this life-threatening disease in young children.

This study presents an innovative method for producing thermosensitive bio-ink from chitosan hydrogels saturated with carbon dioxide and agarose. It focuses on a detailed characterization of their physicochemical properties and potential applications in biomedicine and tissue engineering. The ORO test approved rapid regeneration of the three-dimensional structure of chitosan-agarose composites in the unidirectional bench press simulation test. The diffusion of dyes through chitosan-agarose hydrogel membranes strongly depended on the share of both polymers in the composite and the molecular weight of the dyes. Glucose, as a nutrient marker, also diffused through all membranes regardless of composition. Biocompatibility assessment using MTT tests on 46BR.1N fibroblasts and HaCaT keratinocytes confirmed the safety of the bioink. The regenerative potential of the bioink was confirmed by efficient cell migration, especially HaCaT. Long-term viability studies showed that chitosan-agarose scaffolds, unlike the agarose ones, support cell proliferation and survival, especially 14 days after bioink extrusion. Experiments in a skin wound model in mice confirmed the biocompatibility of tested dressing and the beneficial action of chitosan on healing. Studies on vessel formation in chicken embryos highlight the potential of the chitosan-agarose composition for enhancing proangiogenic effects. This composition meets all entry criteria and possesses excellent biological properties.

Temporomandibular disorders (TMDs) refer to a group of conditions that affect the temporomandibular joint, causing pain and dysfunction in the jaw joint and related muscles. The diagnosis of TMDs typically involved clinical assessment through operator-based physical examination, self-reported questionnaire and imaging studies. To objectivize the measurement of TMD, this study aims at investigating on the feasibility to use machine-learning algorithms fed with data gathered from low-cost and portable instruments to discriminate the presence of TMD in adult subjects. Through this aim, the experimental protocol involved fifty participants, equally distributed between TMD and healthy subjects, acting as control group. The diagnosis of TMD has been performed by a skilled operator through the typical clinical scale. Participants underwent to a baropodometric analysis by using a pressure matrix and the evaluation of the cervical mobility through inertial sensors. Nine machine-learning algorithms belonging to support vector machine, k-nearest neighbours and decision tree were compared. The k-nearest neighbours based on cosine distance was found as the best performing, achieving performance of 0.94, 0.94 and 0.08 for the accuracy, F1-score and G-index, respectively. These findings open the possibility to use such methodology to support the diagnosis of TMDs in clinical environments.

Background: Tumor mutational burden (TMB) is increasingly recognized as a vital biomarker for predicting the efficacy of immune checkpoint inhibitors (ICIs) in cancer treatment. Despite its growing importance, the effectiveness of TMB as a predictive marker are well established in lung cancer and melanoma but remain ambiguous for breast and prostate cancers. Objective: This study aims to evaluate the role of TMB in predicting response to ICIs across four major cancer types—lung, melanoma, breast, and prostate—and to address the variability in TMB's predictive value in different cancers. Methods: A comprehensive review of the current literature was performed, analysing studies that investigated TMB and its association with ICI therapy outcomes in the specified cancer types. Results: The analysis reveals a strong consensus on the predictive value of TMB in lung cancer and melanoma, where high TMB levels are associated with improved clinical outcomes and better responses to ICIs. In contrast, the evidence for breast and prostate cancers is less conclusive, with variability in results highlighting the need for further research. Specifically, high TMB in these cancers does not consistently predict better responses to ICIs, suggesting that additional biomarkers or refined criteria might be necessary. Conclusion: TMB is a promising biomarker for predicting responses to ICI therapy, particularly in lung cancer and melanoma. However, its predictive value in breast and prostate cancers remains uncertain, underscoring the need for more extensive studies. Future research should focus on standardizing TMB evaluation methods and exploring additional biomarkers to improve treatment personalization and outcomes in these cancer types.

Plantar flexors (PF) spasticity is known to poorly correlate with active dorsiflexion (DF) impairment throughout the swing phase of hemiparetic gait. Spastic Cocontraction, instead, stemming from descending pathways, potentially misdirect antagonist PF activity opposing DF during swing. Electromyographic (EMG) recordings, while unable to differentiate between reflex-based and descending origins, may offer valuable insights into this distinction by exploring PF EMG activity after tibial nerve neurotomy (which eliminates PF spasticity). Eleven subjects with hemiparesis walking at comfortable velocity and 11 controls walking at comfortable and slow velocity, underwent kinematic and PF/DF EMG analysis. Five of the hemiparetic subjects underwent tibial neurotomy >1 year prior. We evaluated spasticity at rest (Tardieu scale), maximal ankle dorsiflexion, tibialis anterior agonist recruitment and gastrocnemius medialis and soleus cocontraction coefficients during swing. At slow velocity, controls (0.80±0.12 m/s) moved at a similar pace as hemiparetic subjects (0.73±0.37 m/s, NS). Hemiparetic subjects showed: (i) reduced ankle DF across swing (ii) increased PF cocontraction, including before any DF (iii) higher cocontraction despite absent spasticity in tibial neurotomy subjects (iv) higher tibialis anterior recruitment. Increased PF cocontraction occurs in the absence of spasticity or ankle DF despite higher agonist recruitment. Spastic cocontraction is a major factor limiting active DF at swing, unlike spasticity.

This article explores the efficiency of various clustering methods for image segmentation under different luminosity conditions. Image segmentation plays a crucial role in computer vision appli-cations, and clustering algorithms are commonly used for this purpose. The search for an adaptive clustering mechanism aims to ensure maximum symmetry of real objects with objects/segments in their digital representations. However, clustering methods performance can fluctuate with varying lighting conditions during image capture. Therefore, we assess the performance of several clustering algorithms — including k-means, K-Medoids, fuzzy c-means, Possibilistic C-Means, Gus-tafson-Kessel, Entropy-based Fuzzy, Riddler-Calvard, Kohonen Self-Organizing Maps, and Meanshift — across images captured under different illumination conditions. Additionally, we develop an adaptive image segmentation system utilizing empirical data. Conducted experiments highlight varied performance among clustering methods under different luminosity conditions. This research enhance better understanding of luminosity's impact on image segmentation and aiding in method selection for diverse lighting scenarios.

A rheological modifier was used to prepare solutions with viscosities of 1, 4, 6 and 8 cp, which exhibited Newtonian behavior. These solutions were later used to prepare suspensions of monosize quartz (53, 45 and 38 microns) at 60 % in solids. Monosize grinding tests in a laboratory ball mill were performed to determine breakage parameters, with different ball diameters. A model was developed to determine the specific rate of breakage in terms of the system rheology. With this model, it was demonstrated that an increase in suspending fluid viscosity until 6 cp, leads to an increased fracture rate and consequently affects the grinding degree. The above test is considered as an alternative for improving and optimizing such operations with excellent quality products with low energy and steel consumption, thereby minimizing environmental impact.

The interrelatedness of social-structural aspects and psychological features with the vaccination intention provides the context to explore personal psychological fea-tures related to general decision-making and vaccine-related dispositions, and their contribution to the intention to vaccinate, within post-pandemic circumstances, after the imposed possibility of choosing a vaccine brand. The aim of our study was to map the function (promotive, protective, risk, vulnerability) of a set of psychological aspects in the intention to vaccinate, in people with different social roles regarding the vaccination. We surveyed three samples of people: healthcare providers (HPs), parents, and lay people, within the context of the after-pandemic. Negative vaccine attitudes lower intention to vaccinate in all regression models (all βs ranging from -.128 to -.983, all ps < .01). The main results indicate that, regardless of the sam-ple/social role, there is a shared attitudinal core for positive vaccination intention. This core consists of [high] trust in large corporations, government, and healthcare systems, as well as perceived consensus on vaccine safety/efficacy and experience of freedom (protective factors), and [low] vaccination conspiracy beliefs, trust in social media, and choice overload (risk and vulnerability factors, respectively). There are no common promotive factors of intention to vaccinate; for parents, perceived consensus on vaccines, and trust in corporations and the healthcare system play such roles, for HPs experience of freedom is obtained as a unique promotive factor. In contrast, for laypeople, no unique promotive factors were found. These results and guidelines for the promotion of positive vaccination behavior are further discussed.

Background: Magnetic Resonance Imaging (MRI) is essential in pediatric diagnostics; however, the need for effective sedation due to children’s inability to remain still presents a challenge. Oral Chloral Hydrate (OCH) is commonly used for its efficacy and safety, but there is a lack of detailed exploration of the median induction time, the period from administration to effective sedation. This study aimed to evaluate the efficacy of OCH and identify the determinants of the median induction time for pediatric MRI procedural sedation.Methods: This retrospective study evaluated oral chloral hydrate (50-100 mg/kg) for pediatric MRI sedation using records from the Imam Abdulrahman Bin Faisal Hospital (2018-2022). Pediatric patients (1–8 years) were assessed for sedation efficacy, with exclusion criteria for allergies or incomplete data. Time-to-event analysis (Kaplan–Meier and Cox regression) was used to identify factors influencing sedation induction time. The data included age, weight, dose, and outcomes. The analysis highlighted the key predictors of sedation success and optimized procedural sedation protocols.Results: The study included 183 pediatric patients with a median age of 30 months and a median chloral hydrate dose of 66 mg. Sedation success was 85.79%, with younger age and shorter induction times being significantly associated with success (p<0.001). Kaplan-Meier analysis showed no significant difference in induction times between the neurological and non-neurological groups (p=0.64). Cox regression identified longer MRI duration and multiple doses as significant factors influencing the timing of sedation (p=0.050, p=0.008). Bootstrap analysis confirmed a robust median induction time of 30 minutes.Conclusions: Oral chloral hydrate achieved 85.79% success in pediatric MRI sedation, with younger and lighter patients having better outcomes. The median sleep induction time was 30 minutes, and extending sedation to 60 minutes further improved the success rate.

This work introduces the mathematical framework of the novel “First-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (1st-CASAM-NODE)” which yields exact expressions for the first-order sensitivities of NODE decoder-responses to the NODE parameters, including encoder initial conditions, while enabling the most efficient computation of these sensitivities. The application of the 1st-CASAM-NODE is illustrated by using the Nordheim-Fuchs reactor dynamics/safety phenomenological model, which is representative of physical systems that would be modeled by NODE while admitting exact analytical solutions for all quantities of interest (hidden states, decoder outputs, sensitivities with respect to all parameters and initial conditions, etc.). This work also lays the foundation for the ongoing work on conceiving the “Second-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-CASAM-NODE)” which aims at yielding exact expressions for the second-order sensitivities of NODE decoder-responses to the NODE parameters and initial conditions while enabling the most efficient computation of these sensitivities.

Attackers are perpetually modifying their tactics to avoid detection and frequently leverage legitimate credentials with trusted tools already deployed in a network environment, making it difficult for organizations to proactively identify critical security risks. Network traffic analysis products have emerged in response to attackers’ relentless innovation, offering organizations a realistic path forward for combatting creative attackers. Additionally, thanks to the widespread adoption of cloud computing, Device Operators (DevOps) processes, and the Internet of Things (IoT), maintaining effective network visibility has become a highly complex and overwhelming process. What makes network traffic analysis technology particularly meaningful is its ability to combine its core capabilities to deliver malicious intent detection. In this paper, we propose a novel darknet traffic analysis and network management framework to real-time automating the malicious intent detection process, using a weight agnostic neural networks architecture. It is an effective and accurate computational intelligent forensics tool for network traffic analysis, the demystification of malware traffic, and encrypted traffic identification in real-time. Based on Weight Agnostic Neural Networks (WANNs) methodology, we propose an automated searching neural net architectures strategy that can perform various tasks such as identify zero-day attacks. By automating the malicious intent detection process from the darknet, the advanced proposed solution is reducing the skills and effort barrier that prevents many organizations from effectively protecting their most critical assets.

The effects of photon inertia on the determination of its trajectory were verified and the representation of a displacement mass characterized by the flow of the number of wavefronts and the decomposition of photon inertia into parts associated with translation and rotation motions was considered. It was found that with the relativistic increase of the photon's resistance to change its directional properties, it inhibits the relativistic trajectory of the second torque, of Minkowski, in an angular range of incidence. After synchronizations, in the OAM inversions, there are reductions of the inertia associated to the translational part that assumes classical predominance, where the relativistic trajectory is allowed while the photon offers less resistance to changes in its directional properties. The classical-relativistic variability of the photon inertia characterizes the classical or relativistic profile of the energy distribution in forms of motion, where adjustments of the rotational and translational parts can be performed as a function of the refractive index rate, temperature and angle of incidence. It was found that with increasing temperature of the refringent medium, the synchronizations displacement in the sense of the normal incidence. A specific vacuum temperature for the refringent medium was characterized, where the photon exhibits a classical-relativistic synchronization under all angles of incidence, characteristic of its immaterial state in vacuum.

The present study examined music-induced dopamine release, as measured by a proxy measure of spontaneous eye blinks. Specifically, we explored the effects of uplifting and sombre tones in different sections of Vivaldi's Four Seasons to investigate the affective content of musical pieces within one composition. Seventeen participants listened to four concertos (Major modes: Spring, Autumn, Minor modes: Summer and Winter) and a silence condition while completing the 3-Stimulus Odd-ball attention task. Electrooculograms were recorded from electrodes placed above and under the left eye. Self-reported arousal and music preference measures were also gathered during the testing session. In addition, the P3a Event-Related Potential (ERP) component was analysed as another potential index of dopamine function. Results revealed significant differences in the blink rates during music listening and silence, with the largest effect observed for the sad, melancholic Winter concerto. However, no significant correlation was found between blink rate and music preference or arousal. Furthermore, no reliable association was found between blink rate and the P3a ERP component, suggesting that these measures tap into different aspects of dopamine function. These findings contribute to understanding the link between dopamine and blink rate, particularly in response to classical music. Crucially, the study's discovery that the Winter concerto, with its sorrowful tone, significantly increased the blink rate highlights the significance of sad music and perhaps the programmatic qualities of this concerto to induce a strong emotional response.

Based on its large surface area and covering the whole human body, the skin body’s largest organ and its main function is protection. Injuries and wound healing involving the skin offer valuable lessons shared with and of relevance to other organ systems and the diseases that impact them. Arguably the most complex human body process, wound healing is a multifaceted process that involves multiple cells and the extracellular matrix (ECM), with each component playing a specific role in the different stages of the healing process. Importantly, studies indicate that cells with stem cell-like properties are present within many of the human tissues and play key roles in case of tissue and cellular injury. Cell-to-cell and cell-to-ECM interactions are salient in wound healing subsequent to an injury. Microenvironment related factors and the variations therein including hypoxia or the abundance of oxygen, the presence/absence of growth factors and cytokines add to the complexity of the wound healing process and impact cell function and result in compromised or enhanced wound healing. This expert review critically examines the advances in biochemical and analytical tools that are enable the analysis of numerous cells and molecules within the wound microenvironment, revealing great cellular heterogeneity as well as novel molecular targets of importance to enhance wound healing. In a broader angle, we emphasize the ways in which wound healing is significant in the search for perfect skin after injury and in many common complex human diseases including cancer. In all, wound healing is a centrepiece of integrative biology research and applications in medicine as well as dermatology as discussed in this review.

Reconstructing ancestral species is a challenging endeavour: fossils are often scarce or enigmatic, and inferring ancestral characters based on novel molecular approaches (e.g. comparative genomics or developmental genetics) has long been controversial. A key philosophical challenge pertinent at present is the lack of a theoretical framework capable of evaluating inferences of homology made through integration of multiple kinds of evidence (e.g. molecular, developmental, or morphological). Here, I present just such a framework. I start with a brief history and critical assessment of attempts at inferring morphological homology through developmental genetics. I then bring attention to a recent model of homology, namely Character Identity Mechanisms (DiFrisco, Love, & Wagner, 2020), intended partly to elucidate the relationships between morphological characters, developmental genetics, and homology. I utilise and build on this model to construct the evaluative framework mentioned above, which judges the epistemic value of evidence of each kind in each particular case based on three proposed criteria: effectiveness, admissibility, and informativity, as well as providing a generalised guideline on how it can be scientifically operationalised. I then point out the evolution of the eumetazoan body plan as a case in point where the application of this framework can yield satisfactory results, both empirically and conceptually. I will conclude with a discussion on some potential implications for more general philosophy of biology and philosophy of science, especially surrounding evidential integration, models and explanation, and reductionism.

For over a century, viruses have left a long trail of evidence implicating them as frequent suspects in the development of type 1 diabetes. Through vigorous interrogation of viral infections in individuals with islet autoimmunity and type 1 diabetes using serological and molecular virus detection methods, and mechanistic studies of virus infected human pancreatic β-cells, the prime suspects have been narrowed down to predominantly human enteroviruses. Here we provide a comprehensive overview of evidence supporting the hypothesised role of enteroviruses in the development of islet autoimmunity and type 1 diabetes. We also discuss concerns over the historical focus and investigation bias toward enteroviruses, and summarise current unbiased efforts aimed at characterising the complete population of viruses (the “virome”) contributing early in life to the development of islet autoimmunity and type 1 diabetes. Finally, we review the range of vaccine and antiviral drug candidates currently being evaluated in clinical trials for the prevention and potential treatment of type 1 diabetes.

Abstract We aim to describe the diagnosis and surgical management of urinary tract endometriosis (UTE). We detail current diagnostic tools including advanced transvaginal ultrasound, magnetic resonance imaging, and surgical diagnostic tools such as cystourethroscopy. While discussing surgical treatment options, we emphasize the importance of an interdisciplinary team, for complex cases that involve the urinary tract. While bladder DE is more straightforward in its surgical treatment, ureteral DE requires a high level of surgical skill. Specialists should be aware of the important entity of UTE due to the serious health implications for women. When UTE exists, it is important to work within a interdisciplinary radiological and surgical team.

Athletes are exposed to high-intensity loads to promote athletic performance, however without appropriate evaluation for its effects. This study investigates the effects of four types of exhaustion exercises on Heart Rate Variability (HRV) and Poincaré features as markers of central fatigue; Creatine Kinase (CK) and blood lactate concentrations ([LA-]b) as biomarkers of peripheral fatigue. To achieve this purpose, ten healthy volunteers were exposed to exhaustive exercise using isotonic-, isometric-, aerobic-, and anaerobic-fatigue protocols. HRV Poincaré features, standard deviation of instantaneous beat-to-beat R-R interval variability (SD1) and standard deviation of continuous long-term R-R interval variability (SD2) variables were collected. Central fatigue was tested through the sympathetic stress index (SS) and the sympathetic and parasympathetic index (SS/SD1). Blood samples were collected at the beginning and at the end of the exercises to determine CK and [LA-]b. The SD1 decreased in each exercise protocol, while the SS and SS/SD1 increased. [LA-]b and CK increased at the end of each protocol and correlated with SD1 and SS/SD1. HRV, CK, and [LA^-]_b are acute markers to detect, both central and peripheral fatigue; sensitive to the type, duration, and intensity of exercise, being HRV a novel noninvasive marker, simple and useful for sports coaches and athletes.

We describe the effect of the expansion of space on the wavelength of the light beam in a Fabry-Pérot interferometer. For an instrument such as the Laser Interferometer Gravitational-Wave Observatory (LIGO), which has high sensitivity and a long period of light storage, the wavelength ${\lambda }_L$ of laser photons are redshifted due to the expansion of space in each cavity by an amount $\delta \lambda$ given by $\delta \lambda /{\lambda }_L=H_0{\tau }_s\approx 8.8\times {10}^{-21}$ , where $H_0\approx 2.2\times {10}^{-18}{\mathrm{s}}^{-1}$ is the Hubble constant and ${\tau }_s\approx 4\mathrm{ms}$ is the light storage time for the cavity. Since ${\tau }_s$ is based on the cavity finesse $\mathcal{F}$ which depends on the laser beam full width at half maximum (FWHM) $\delta \omega$ of each cavity, we show that a difference in finesses between the LIGO arm cavities produces a signal $h_H\left(t\right)$ at the anti-symmetric output port given by $h_H\left(t\right)=2a_1{H}_0\left(\frac{1}{\delta {\omega }_X\left(t\right)}-\frac{1}{\delta {\omega }_Y\left(t\right)}\right),$ where $\delta {\omega }_X\left(t\right)$ and $\delta {\omega }_Y\left(t\right)$ are the beam FWHM at time t, respectively, for the X and Y arm cavities and $a_1$ is a beam proportionality constant to be determined expermentally. Assuming $a_1\approx 1$ , then for cavity beams FWHM of $\delta \omega \left(t\right)\approx (523.2\pm 31)\mathrm{rad}.{\mathrm{s}}^{-1}$ the output signal has the range $\mid h_H\left(t\right)\mid \le 1\times {10}^{-21}$ , which is detectable by advanced LIGO.

This paper builds on previous work introducing the Secure Remote Update Protocol (SRUP)—a secure communications protocol for Command & Control applications in the Internet of Things, built on top of MQTT. This paper builds on the original protocol, and introduces a number of additional message types: adding additional capabilities to the protocol. We also discuss the difficulty of proving that a physical device has an identity corresponding with a logical device on the network, and propose a mechanism to overcome this within the protocol.

Background: Exclusive enteral nutrition (EEN) is the recommended first-line induction therapy for pediatric patients with active luminal Crohn’s disease (CD). The primary aim of this retrospective study was to ascertain the efficacy of EEN used as induction therapy for children with newly diagnosed CD resident in the South Island of NZ over a ten-year period (2010 – 2021). Secondary aims were to assess the clinical impact of EEN therapy on anthropometry, biochemistry, the progression to medical therapies over three time periods, and to identify positive predictors of response to EEN therapy. Methods: This retrospective clinical case review collected data from children diagnosed with CD at Christchurch Hospital, Christchurch, New Zealand, and prescribed EEN as induction therapy between the years January 1^st, 2010 – December 31^st, 2021. Descriptive statistics, Spearman’s correlation coefficient, multivariate logistic regression test and standard t-tests were used for analyses. Results: Data were collected for total of 161 children, 128 (80%) children were offered EEN as induction therapy and were included in this analysis. One hundred and twenty-one (94.5%) children successfully completed an eight-week course of EEN, and a decrease in PCDAI scores ≥ 15 points from baseline to the end of week 8 of EEN treatment was seen in 119 (98.3%). L1 and L4 disease location were positive predictors of response (p<0.05). One hundred and two (89.3%) children achieved disease remission defined as PCDAI <10 at the eight-week time-point. Conclusions: These children with newly diagnosed CD from the South Island of NZ achieved high rates of clinical remission using EEN as induction therapy. Moreover, these children also experienced significantly improved growth parameters and biochemical markers of disease consequent to their course of EEN.

Within the European Union (EU), new plant varieties, to be included at the Common catalog of a member state, has to be registered at the national list, after plant variety testing processes to establish whether the candidate variety is distinguishable, uniform and stable (DUS) and meets the requirement of the cultivation or use value requirement (VCU). Technical development, climate change and changing consumer needs, including the detection of GMOs, necessitate the innovation of plant variety testing methods. Within the EU-funded "InnoVar" project, it has been sent out questionnaires to several countries, which were aimed at analyzing strengths, weaknesses, opportunities and threats (SWOT) of the current methods and with their help it is possible to have look for a new direction, opportunity and strategy, which can incorporate together with the innovation results into the development of the new methods. Our study confirmed that the SWOT analysis could be used to achieve the set goals; according to the answers to the questionnaires, it became necessary to introduce new characters (e.g. cold tolerance) and new test methods (molecular markers, precision techniques, organic farming) into the variety testing procedures. The development of high-yielding, disease and/or pest-resistant plant varieties with good adaptability and the accurate evaluation of genotypes play a crucial role in ensuring that farmers can access high-performing plant varieties and contribute to sustainable food production.

Breast cancer (BC) is the most common invasive neoplasm and affects many women of working age. The return to work (RTW) of female survivors (BCSs) is associated with a better quality of life and longer survival. A tailored intervention to promote RTW was launched in 2022. A year later, the women were contacted to find out if RTW had occurred regularly and what their health conditions were compared to baseline. BCSs reported excessive fatigue, poor sleep quality, anxiety, depression and reduced work ability; these parameters had not improved significantly compared to baseline. Thematic analysis of the interviews confirmed the presence of personal, company and societal factors that could hinder or favor RTW. The interviews demonstrated that, even in an economically developed country that has provided numerous benefits for BCSs, protection is not always effective. Personalized intervention seems necessary to complete the process of reintegrating BCSs into their future working careers.

Implementing machine learning technologies in manufacturing environment relies heavily on human expertise in terms of domain and machine learning knowledge. Yet, the required machine learning knowledge is often not available in manufacturing companies. A possible solution to overcome this competence gap and let domain experts with limited machine learning programming skills build viable applications are digital assistance systems that support the implementation. At the present, there is no comprehensive overview over corresponding assistance systems. Thus, within this study a systematic literature review was conducted. Twenty-nine papers were identified and analyzed in depth regarding machine learning use case, required resources and research outlook. Six key findings as well as requirements for future developments are derived from the investigation. As such, the existing assistance systems basically focus on technical aspects whereas the integration of the users as well as validation in industrial environments lack behind. Future assistance systems should put more emphasis on the users and integrate them both in development and validation.

Wastewater genomic surveillance is an efficient and economic approach to track infectious diseases and can help detect unusual epidemiological events. The current study uses this approach for the first time in Morocco to monitor the epidemiology of SARS-CoV-2 and Influenza A, B and RSV virus infections during the third wave of COVID-19 caused by the Omicron variant. The virome was concentrated from wastewater collected from two sewer sheds of two cities, Agadir and Inezgane, using the PEG/NaCl method. The viral copy number was determined using qRT-PCR. All 26 samples in both cities were tested positive for SARS-CoV-2 at various viral loads. For Influenza A virus, two samples were tested positive in Inezgane. The estimated SARS-CoV-2 viral RNA copy numbers observed were then used to estimate the number of infected individuals using the SEIR model. The number of viral copies of SARS-CoV-2 for Agadir and Inezgane varied from 82932 ± 15479 to 507865 ± 58759 copies/L and 61244 ± 8552 to 497506 ± 18061 copies/L, respectively. The estimated number of cases correlates positively with the number of reported cases. Next Generation Sequencing showed that samples contain the following two variants: BA.1 and BA.2 that have been detected in clinical samples. This study demonstrates the effectiveness and feasibility of wastewater genomic surveillance in monitoring pathogens such as SARS-CoV-2 in Morocco.

Aim: To analysis the relationship between healthy adults right ventricular diameter (RVD) and geographical factors. Location: China’s 22 provinces, municipalities and autonomous regions. Methods: Using correlation analysis the relationship between RVD and nine geographic factors, build predictive models by factor analysis. Results: There is significant correlation between RVD and geographical factors, and the annual average temperature is most relevant geographical factors, a predictive model was built by factor analysis: Ŷ = 19.46 + 0.0007072X1 + 0.001034X2 -0.05412X3 -0.001405X4 -0.0006351X5 + 0.02903X6 + 0.01243X7 -0.01033X8 + 0.03816X9 ± 0.63. Then using Kriging interpolation interpolate the geographical distribution of Chinese healthy adult right ventricular diameter reference value in ArcGIS software. Main Conclusion: If geographic factors can be derived in anywhere of China, RVD can be calculated by the model, you can also get RVD from geographical distribution.

Extreme heat is a climate hazard that has been linked with high morbidity and mortality. The way extreme heat events are felt in the population varies depending on a variety of factors, such as age, employment status, living conditions, air-conditioning, housing conditions, habits, behaviors, and other socio-demographic parameters. To quantify and locate vulnerabilities of populations to extreme heat, we analyze socio-economic data at the NUTS3 level for the national case study of Greece and at the census tract level for the local case study of the city of Athens. The target variable for this study is defined as the average daily mortality during heatwaves per 100,000 individuals and a methodology is developed for constructing this variable, based on socio-economic data available in public databases. Independent variables were selected based on their contribution to socioeconomic vulnerability; they include the percentage of elderly, retired, unemployed, renting, living alone, residing in smaller houses, living in older houses, and immigrants from developing countries. An ensemble gradient boosted tree model was employed for this study to obtain feature importance metrics that was used to construct a composite index of socioeconomic heat vulnerability. The socioeconomic heat vulnerability index (SHVI) was calculated for each prefecture in Greece and for each census tract in the city of Athens, Greece. The unique feature of this SHVI is that it can be applied to any geographical resolution using the same methodology and produces a result that is not only quantifiable, but also allows comparison between vulnerability scores of different regions. This application aimed to map the SHVI of both prefecture and city, to examine the significance of scale, to identify vulnerability hotspots, and rank the most vulnerable areas, which are prioritized by authorities for interventions that protect public health.

Global dust events have become more frequent due to climate change and increased human activity, significantly impacting air quality and human health. Previous studies have often focused on simulating cross-regional dust transport based on atmospheric parameters; however, comprehensive monitoring of dust events remains challenging. Therefore, this study utilized Fengyun-4A (FY-4A) satellite Advanced Geostationary Radiation Imager (AGRI) imagery, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar, and other auxiliary data to conduct three-dimensional spatiotemporal monitoring and cross-regional transport analysis of two typical dust events in the Beijing–Tianjin–Hebei (BTH) region of China using four dust intensity indices (Icsd, Dust Detection Index (DDI), Dust value (DV), and Dust Strength Index (DSI)) and the HYSPLIT model. We found that among the four indices, DDI was the most suitable for studying dust in the BTH region, with a detection accuracy (POCD) of > 88% at all times and reaching a maximum of 96.14%. Both the 2021 and 2023 dust events originated from large-scale deforestation in southern Mongolia and the border area of Inner Mongolia, with dust plumes distributed between 2 and 12 km being transported across regions to the BTH area. Further, when dust aerosols are primarily concentrated below 4 km and PM10 concentrations consistently exceed 600 µg/m³, large dust storms are more likely to occur in the BTH region. The findings of this study provide valuable insights into the sources, transport pathways, and environmental impacts of dust aerosols.

In previous research, 1,2,3-triazolium salts showed significant biological activity as potential in-hibitors of the enzymes cholinesterases (ChEs), crucial for neurotransmission. In this research, pairs of uncharged thienobenzo-triazoles and their charged salts were prepared in order to ex-amine further the role of the positive charge on the nitrogen of the triazole ring on the interac-tions in the active site of the enzymes and to compare the selectivity of 1,2,3-triazolium salts in relation to their uncharged analogs obtained by photochemical cyclization. Neutral thienoben-zo-triazoles showed very good selective activity toward butyrylcholinesterase (BChE), while their salts showed excellent non-selective inhibition toward both BChE (the most active 23: IC50 0.47 mikroM) and acetylcholinesterase (AChE) enzymes (the most active 23: IC50 4.4 mikroM). These new structures with incorporated 1,2,3-triazolium salts present the new scaffold for drug development as it is known that the current therapy in Alzheimer's disease (AD) are selective AChE inhibitors, while in Parkinson's and all stages of AD, non-selective inhibitors of ChEs are preferred. Molecular docking of the selected compounds and their corresponding salts into the active sites of ChEs was conducted to identify the interactions responsible for the stability of the non-covalent cholinesterase-ligand complexes. As genotoxicity studies are crucial when devel-oping new active substances and finished drug forms, in silico studies for all the synthesized compounds have shown that compound 18 is the most promising candidate for genotoxic safety.

The focus of this article is the evaluation of the quality and the degree of community engagement in an expert-based, public-health communicative intervention for Alcohol Use Disorder (AUD). In 2023 the Canadian Alcohol Use Disorder Society collaborated with a grass-roots community health group, a regional health authority, and an academic participatory researcher to organize a working group to mount a social-marketing campaign to increase community support for AUD medical treatment in family-practice settings in a rural community in British Columbia. The partnership working group conducted a series of activities in the school system, the town council, and the community. This article covers the formative evaluation and the summative evaluation of the working group's effectiveness. The formative evaluation ("lessons learned" and "recommendations") consists of consensus evaluations of the quality of each activity using a variety of data sources. The formative evaluation followed improvement science methods and used consensus meetings to provide and reflect on formal and informal feedback. Formative results reflect the consensus of the participants in the working group and they record the reactions in the community. The summative evaluation measures evidence of community engagement found in transcribed text from meeting minutes. The summative evaluation used theory-based frameworks and text data visualization to assess the engagement dynamics of the working group. The summative evaluation helps to put the formative evaluation into perspective as communicative action. The summative evaluation validates the formative evaluation by revealing the communicative dynamics of engagement which resulted in the community’s increased capacity to understand and support Alcohol Use Disorder Treatment options. The working group and the entire intervention was seen by the participants and the public as a success and capable of replication. In a small community, it instilled new understandings and attitudes, bringing an emerging awareness of medication as an optional health mitigation strategy for Alcohol Use Disorder. Our study furthers this overall assessment by using theoretical constructs and analysis of communicative records to trace engagement characteristics of interest to researchers, societies, and community groups contemplating similar interventions in the future. The study also validates the effectiveness of communicative analysis as a measure of social-marketing for expert-based public health interventions.

There is a significant risk of injury in sports and intense competition due to the demanding physical and psychological requirements. Hamstring strain injuries (HSI) are the most prevalent type of injury among professional soccer players and are the leading cause of missed days in the sport. These injuries stem from a combination of factors, making it challenging to pinpoint the most crucial risk factors and their interactions, let alone find effective prevention strategies. Recently, there has been a growing recognition of the potential of tools provided by artificial intelligence (AI). However, current studies primarily concentrate on enhancing the performance of complex machine learning models, often overlooking their explanatory capabilities. Consequently, medical teams encounter difficulty interpreting these models and are hesitant to trust them fully. In light of this, there is an increasing need for advanced injury detection and prediction models that can aid doctors in diagnosing or detecting injuries earlier and with greater accuracy. Accordingly, this study aims to identify biomarkers of muscle injuries in professional soccer players through a biomechanical analysis, employing several ML algorithms, such as Decision tree (DT) methods, Discriminant methods, Logistic regression, Naive Bayes, Support vector machine (SVM), K-nearest neighbor (KNN), Ensemble methods, Boosted and bagged trees, Artificial Neural Networks (ANN), and XGBoost. In particular, XGBoost was also used to obtain the most important features. The findings highlight that the variables that most effectively differentiate the groups and could serve as reliable predictors for injury prevention are the maximum muscle strength of the hamstrings and the stiffness of the same muscle. With regards to the 35 techniques employed, a precision of up to 78% was achieved with XGBoost, indicating that by considering scientific evidence, suggestions based on various data sources, and expert opinions, it is possible to attain good precision, thus enhancing the reliability of the results for doctors and trainers. Furthermore, the obtained results strongly align with the existing literature, although further specific studies about this sport are necessary to draw a definitive conclusion.