In recent years, change in behaviour towards the environment has gained prominence as a policy tool to influence positive environmental value. Simultaneously, the role played by social identity in promoting pro-environmental action is gaining recognition. Within this work, the intersection between collective group identity and environmental behaviour has received very little attention. Group norms are considered a strong predictor of pro-environmental behaviour, yet the influence of social identity and collective action on environmental action has not been adequately investigated in a multi-ethnic setting. Within this context, this study examines the affective component of social identity influence on pro-environmental action. More succinctly, this study demonstrates how outgroups and in-groups’ relations and broader socio-cultural structures, values, interest, and norms impact environmental and sustainability transitions behaviours. Through interviews with participants across the four dominant social groups in South Africa, this study provides compelling evidence that country wide expressions of social identity and in-group dynamics shapes the individual behaviour regarding environmental and sustainability concerns and further strengthen the individual’s perspective for social environmental transformation. This study advances the need for a social-identity centred approach to foster pro-environmental and sustainability outcomes.

Developing new antibiotics poses a significant challenge in the fight against antimicrobial resistance (AMR), a critical global health threat responsible for approximately 5 million deaths annually. Finding new classes of antibiotics that are safe, have acceptable pharmacokinetic properties, and are appropriately active against pathogens is a lengthy and expensive process. Therefore, high-throughput platforms are needed to screen large libraries of synthetic and natural compounds. In this review, we present bacterial cytological profiling (BCP) as a rapid, scalable, and cost-effective method for identifying the mechanisms of action of antibiotics, offering a promising tool for combating AMR and drug discovery. We present the application of BCP for different bacterial organisms and different classes of antibiotics and discuss BCP's advantages, limitations, and potential improvements. Furthermore, we highlight the studies that have utilized BCP to investigate pathogens listed in the Bacterial Priority Pathogens List 2024 and we identify the pathogens whose cytological profiles are missing. Lastly, we explore the most recent artificial intelligence and deep learning techniques that could enhance the analysis of data generated by BCP, potentially advancing our understanding of antibiotic resistance mechanisms and the discovery of novel druggable pathways.

The universal Debye – Mayer – Kelly hybrid model was proposed for the description of the heat capacity from 0 K to the melting points of substance within the experimental uncertainty for the first time. To describe the heat capacity, the in-house software on the base of commercial one DELPHI-7 was used with a 95% confidence level. To demonstrate the perfect suitability of this model, a thermodynamic analysis of the heat capacities of the fourth group elements, and some compounds of the A^IIIB^V and A^IIB^VI phases was carried out. It produced good agreement within the experimental uncertainty. There is no a similar model description in literature.The Similarity Method is a convenient and effective tool for critical analysis of the heat capacities of isostructural phases, which was used as an example for diamond-like compounds. Phases with the same sum of the atomic numbers of elements (Z), such as diamond and B_0.5 N_{0.5 (cub)} (Z = 6); pure silicon (Si) and Al_0.5 P_0.5 (Z=14); pure germanium (Ge) and Ga_0.5 As_0.5 (Z = 32)); pure grey tin (alpha-Sn) and In_0.5 Sb_0.5, and Cd_0.5 Te_0.5 (Z = 50) have the same heat capacity experimental values in the solid state. The proposed models can be used to both different binary and multicomponent phases. It helps to standardize the physicochemical constants.

Recent advancements in vascular organoid (VO) and vessel-on-chip (VoC) technologies have revolutionized our approach to studying cardiovascular diseases (CVDs), offering unprecedented insights through more physiologically relevant models. VOs generated from human pluripotent stem cells exhibit remarkable self-organization capabilities, forming complex three-dimensional structures that closely mimic human blood vessel architecture and function, while VoCs engineered with groundbreaking microfluidic systems that meticulously recreate the physical and functional attributes of blood vessels. These innovative constructs serve as powerful tools for investigating vascular development, disease progression, and therapeutic efficacy. By enabling the creation of patient-specific VOs and VoCs, they pave the way for personalized medicine approaches, allowing researchers to delve into genetic variations, intricate cellular interactions, and dynamic processes with exceptional resolution. The synergy between VOs and VoCs with cutting-edge technologies such as single-cell sequencing and high-resolution imaging has further amplified their potential, unveiling novel mechanisms underlying CVDs and identifying promising therapeutic targets. Herein, we summarize different types of VOs and VoCs and present an extensive overview on the generation and applications of VOs and VoCs in CVDs. We will also highlight clinical and translational challenges and future perspectives around VOs and VoCs.

Artificial Intelligence (AI) is revolutionizing head and neck cancer (HNC) care by providing innovative tools that enhance diagnostic accuracy and personalize treatment strategies. This review highlights the advancements in AI technologies, including deep learning and natural language processing, and their applications in HNC. The integration of AI with imaging techniques, genomics, and electronic health records is explored, emphasizing its role in early detection, biomarker discovery, and treatment planning. Despite noticeable progress, challenges such as data quality, algorithmic bias, and the need for interdisciplinary collaboration remain. Emerging innovations like explainable AI, AI-powered robotics, and real-time monitoring systems are poised to further advance the field. Addressing these challenges and fostering collaboration among AI experts, clinicians, and researchers is crucial for developing equitable and effective AI applications. The future of AI in HNC holds significant promise, offering potential breakthroughs in diagnostics, personalized therapies, and improved patient outcomes.

Extremophilic bacteria are important groups of extremophilic organisms that have been studied during the last years. They are considered as a source of enzymes due to great diversity and can survive under extreme conditions. Many enzymes produced by these microorganisms are of great importance and have found applications in several industries. Due to their activity and stability under extreme conditions, these enzymes offer new alternatives for current biotechnological and industrial applications. They have a wide range of potential uses and have been a nuclear subject of many different investigations. To date, some of the enzymes produced by extremophilic bacteria are currently being assessed thier industrials applications. Despite, benefits that present these enzymes, their potentials remain largely unexplored. These enzymes pose new opportunities for new line of research, and biotechnological applications. This review provides a summary on diversity and biotechnological and industrial applications of some enzymes produced by extremophilic bacteria.

Astronauts at are risk of losing 1.0 – 1.5% of their bone mass for every month they spend in space despite their adherence to high impact exercise training programs designed to preserve the musculoskeletal system. This article reviews the basics of bone formation and resorption and details how exposure to microgravity or simulated microgravity affects the structure and function of osteoblasts, osteocytes, osteoclasts, and their mesenchymal and hematologic stem cell precursors. It details the critical roles that insulin-like growth facor-1 and its receptor IGFR1 play in maintaining bone homeostasis and how exposure of bone cells to microgravity affects the function of these growth factors. Lastly, it discusses the potential of tumor necrosis factor-related apoptosis-inducing ligand, syncytin-A, and sclerostin inhibitors and recombinant IGF-1 as a bone-saving treatment for astronauts in space and during their colonization of the Moon.

Sickle cell disease is characterized by stiff, “sickled” red blood cells that have difficulty moving through the bloodstream and do not efficiently carry oxygen. It is an inherited disease with severely limited treatment options, and is caused by a point mutation. Its prevalence in black and brown communities makes the already limited treatment options even less accessible. Base editing and prime editing are two relatively recent discoveries in the field of genome editing and were developed after the groundbreaking discovery of the CRISPR Cas9 system. While not fully tested, they hold a lot of promise in providing alternative treatment options for sickle cell disease. Both editing systems are able to install individual point mutations in the beta globin gene, which is where the sickle cell mutation occurs, and can thus cure sickle cell disease (in theory). In this paper we outline the mechanisms of CRISPR-Cas9 systems and base and prime editing, and provide insight into how to apply them to treat SCD. Further investigation should be done on specific editing systems and designs to use to ensure optimal treatment of SCD.

(S)-1-Methyl-2-oxoimidazolidine-4-carboxylic acid 1 is an analog of (S)-pyroglutamic acid, a key component of naturally occurring peptide hormones and synthetic pharmaceutical candidates. Reaction of (S)-2-amino-3-(methylamino)propionic acid with COCl2 and aqueous NaHCO3 followed by ion exchange afforded 1, which was recrystallized from acetonitrile and then characterized by IR, 1H NMR, 13C NMR, polarimetry, elemental microanalysis, high resolution mass spectrometry and single crystal X-ray diffraction. The acid 1 crystallized in the orthorhombic chiral space group P212121 with cell constants a = 6.2275(4) Å, b = 8.3963(5) Å, c = 24.9490(14) Å. The X-ray crystal structure reveals that two distinct conformers of 1 occur at alternating positions within helices which are supported by hydrogen-bonding. Each molecule of 1 is linked to its two neighbors in the helix by a total of three hydrogen bonds and four molecules of 1 are contained within each turn of the helix. The pattern of hydrogen bonds illustrates a preference for the carboxylic acid group to act as a hydrogen bond donor and for the urea unit to be a hydrogen bond acceptor.

Business school curriculums are designed to improve business skills and a student’s eventual workplace performance. In addition to these business skill sets the emerging business environment demands softer skills associated with ethical decision-making and sustainable business practices. Understanding the key influencers of ethical orientation and attitudes towards the environment is the first critical step for curriculum planning designed to develop both ethical decision-making and environmental sensibilities of students in business schools. Using a bivariate regression analysis (OLS) that compared the established New Ecological Paradigm (NEP) scale and the newly introduced Ethical Orientation Scale (EOS), this study assesses environmental eco-consciousness and ethical orientation over time and across varying socio-demographic variables. The study shows first, that in addition to socio-cultural variables, situational factors influence ethical decision-making. Secondly, it illuminates that ethical orientations as measured by the EOS predicts beliefs about the environment as measured by the NEP scale. It further provides evidence of the ethical underpinnings of the New Ecological Paradigm as well as provides initial validation for the new EOS. These outcomes provide additional levers to assist business educators in the creation of high impact teaching strategies to measure and encourage ethical decision-making and sustainable business practices that protect the environment.

Solid tumors universally possess the ability to evade contact inhibition of proliferation (CIP), a mechanism halting cell proliferation when cell-cell contacts occur. Merlin, an ERM-like protein, crucially regulates CIP and is frequently deactivated in various cancers, indicating its signifi-cance as a tumor suppressor in cancer biology. Despite extensive investigations into Merlin's role in cancer, its lack of intrinsic catalytic activity and frequent conformation changes has made it notoriously challenging to study. To address this challenge, we harnessed innovative luciferase technologies to create and validate a split-luciferase biosensor system. This system enables precise quantification of Merlin's conformation and activity both in vitro and within living cells. This biosensor significantly enhances the study of Merlin's molecular functions, serving as a potent tool to explore its contributions to CIP and tumorigenesis.

The existence of insecurity in a state necessitates immediate government attention and action as it poses a risk to human life and property and impedes socio-economic development. The study aims to evaluate insecurity and its impact on socio-economic development in Oyo state. It will also determine the major causes of insecurity problems and offer data that can help develop effective security strategies and policies. The study population consisted of residents who were randomly selected from the Ibarapa North Local Government Area of Oyo State, Nigeria. The descriptive survey method was adopted and analyzed with the Chi-square technique. According to this research, there is a negative correlation between insecurity and the state's socio-economic development. The study recommends good governance and inclusive government policies to curb insecurity and ensure the state's socio-economic development.

“Minas Frescal” cheese is a high moisture product, subject to the proliferation of several microorganisms. Essential oils are natural antimicrobial alternatives that can increase the quality of dairy products. This study aimed to analyze the antimicrobial action of oregano (Origanum vulgare) and rosemary (Rosmarinus officinalis) essential oils against Escherichia coli and Staphylococcus aureus. An antimicrobial test by diffusion and microdilution was performed to calculate the MIC (Minimum Inhibitory Concentration) and MBC (Minimum Bactericidal Concentration). The behavior of E. coli in “Minas Frescal” cheese added with oregano oil was evaluated. The MIC of oregano oil was 0.25% against E. coli and 1% against S. aureus. For rosemary essential oil, the MIC was 8% of against E. coli. There was no activity of rosemary oil against S. aureus. The MBC observed for oregano essential oil was 1% and 0.25% respectively for S. aureus and E. coli. Bacterial analysis during cheese storage with E. coli indicated inhibition of microorganisms by oregano essential oil at a concentration of 0.25%. No alterations were observed regards to physical-chemical attributes. The use of essential oil as an antimicrobial agent has potential for industrial use, and type of microorganism, oil and sensory reflexes in the product must be observed.

Data on the seasonally dry tropical forests of Mexico have been examined in the light of statistical mechanics. The results suggest a division into two classes of species. There are drifting populations of a cosmopolitan class capable of existing in most dry forest sites; these have a statistical distribution previously only observed (globally) for populations of alien species. A high proportion of species found only at a single site are endemic and these prefer sites comparatively low in species richness.

The benefits of event-driven architecture (EDA) derive from how systems and components are loosely coupled, which can facilitate independent development and deployment of systems, improved scaling and fault tolerance, and integration with external systems, especially in comparison to monolithic architectures. With the advent of new technologies such as containers, and microservices, a new generation of distributed event streaming platforms are commonly used in event-driven architecture for efficient event-driven communication. However, the asynchronous and distributed nature of EDA poses several problems that include handling failures, the dependence of an end-to-end transaction on individual component stability, etc. In this paper, we describe a new approach to designing self-regulating distributed applications with autopoietic and cognitive workflow management. This approach is based on the new science of information processing structures derived from the General Theory of Information. Just as a genome enables self-organizing and self-regulating biological structures, a digital genome enables a specific software application with several components, the ability to use distributed resources and self-regulate the evolution of the system based on functional and non-functional requirements, and best-practice policies that maintain the stability, safety, and survival under non-deterministic fluctuations in the demand for resources. In addition, cognitive workflow management assures end-to-end transaction delivery.

In the dynamic realm of agribusiness construction, firms are striving to bolster their operational efficiency and profitability amidst the global shift from traditional farming to commercial agriculture. This transition has intensified the demand for sophisticated infrastructure development, presenting new challenges for commercial managers. A critical hurdle is the accurate estimation of profitability for prospective contracts, a task often reliant on intuition rather than data-driven methods. To address this, we propose the development of a mathematical model utilising machine learning techniques to predict contract profitability and identify influential factors. This model aims to aid in bid decision-making, financial forecasting, and enhancing competitiveness in the marketplace. Furthermore, it would provide valuable insights into how altering specific contract attributes might affect predicted profitability. The implementation of such a system necessitates close collaboration between IT professionals and construction executives. This study delineates the development of this predictive model, outlining the data analysis process and the application of machine learning algorithms to tackle this complex commercial challenge. The ultimate goal is to bridge the gap between intuitive estimation and data-driven prediction, thereby enhancing the financial performance and strategic decision-making capabilities of firms in the agribusiness construction sector.

Unmanned aerial vehicles (UAVs) equipped with multispectral sensors present an opportunity to monitor vegetation with on-demand high spatial and temporal resolution. In this study, we use multispectral imagery from quadcopter UAVs to monitor the progression of a water manipulation experiment on a common shrub, Baccharis pilularis (coyote brush), at the Blue Oak Ranch Reserve (BORR) near San Jose, California. We recorded multispectral data from the plants at several altitudes with nearly hourly intervals to explore the relationship between two common spectral indices, NDVI and NDRE, and plant water content and water potential, as physiological metrics of plant water status, across a gradient of water deficit. An examination of the spatial and temporal thresholds at which water limitations were most detectable revealed that the best separation between levels of water deficit were at higher resolution (lower flying height), and in the morning (NDVI) and early morning (NDRE). We found that both measures were able to identify moisture deficit in plants and distinguish them from control and watered plants; however, NDVI was better able to distinguish between treatments than NDRE and was more positively correlated with field measurements of plant water content than NDRE. Finally, we explored how relationships between spectral indices and water status changed when the imagery was scaled to courser resolutions provided by satellite-based imagery (PlanetScope) and found that PlanetScope data was able to capture the overall trend in treatments but was not able to capture subtle changes in water content. These kinds of experiments that evaluate the relationship between direct field measurements and UAV camera sensitivity are needed to enable translation of field-based physiology measurements to landscape or regional scales.

This paper provides an alternative Slope-Deflection equation for performing the static analysis of the indeterminate structures. While the conventional Slope-Deflection method introduced in undergraduate structural analysis course involves the use of fixed end moments in the Slope-Deflection equations, the proposed method employs the slope of a simply supported beam to obtain the unknown moments at the joints. Three numerical examples of continuous beams with different load configurations are chosen and the efficacy of the proposed equations is demonstrated. From the perspective of undergraduate structural analysis course in Civil Engineering education, the approach proposed in this paper offers two advantages: (1) prior knowledge of fixed beams is not required and (2) the concepts gained from determinate structural analysis are directly applicable.

We propose a pricing formula for a defaultable zero-coupon bond with imperfect information under a regime-switching model using a structural form of credit risk modelling. While the value of the firm’s equity is observed continuously, we assume that the total value of the firm is only observed at discrete times, such as the dates of the release of the firm’s annual reports, or quarterly reports. This uncertainty about the true value of the firm results in credit spreads that do not approach zero as the debt approaches maturity, which is a problem with many structural models. The firm’s value is typically defined as its equity and debt; however, we consider the asset-to-equity ratio, an accounting ratio used to examine a firm’s financial well-being. A dependent regime-switching process models the components of this ratio, and the Markov chain represents the states of the economy. The main contribution is to study this problem when the dynamics of a firm’s assets have different parameters with regime changes.

The acoustic environment in learning spaces significantly influences learning effectiveness and occupant well-being. Recent studies have shown that a series of architectural factors within physical learning environments can impact students' educational experiences. This research delves into the relationship between architectural characteristics and the perceived acoustic environment among 467 primary students in 19 learning spaces across 9 schools in Chile. The survey comprises a student questionnaire, a checklist evaluating space characteristics, and acoustic measurements of indoor noise levels during occupied conditions. Examined topics include Indoor Environmental Quality (IEQ) comfort perception, noise annoyance, hearing ability, and acoustic preference. Architectural characteristics considered encompass flexible and acoustic space design parameters. The results indicated that noise discomfort was a common issue, especially in traditional learning spaces without acoustic treatment. The type of learning space (traditional or flexible settings) has a greater impact on acoustic perception particularly concerning noise discomfort and acoustic preference. However, poorly acoustic spaces lacking absorbing materials or exhibiting lower spatial density (m2 per student) contribute to increased indoor noise levels affecting noise annoyance caused by children's talking inside. The study emphasizes the importance of considering both architectural design and acoustic conditioning for optimizing the acoustic experience in educational spaces.

Two desirable functions of healthy soil are nutrient cycling and pest suppression. We review recent literature on the contributions of soil microarthropods to soil health through their intersecting roles in decomposition and nutrient cycling and direct and indirect suppression of plant pests. Microarthropods can impact soil and plant health directly by feeding on pest organisms or serving as alternate prey for larger predatory arthropods, and indirectly, by mediating the ability of crop plants to resist or tolerate insect pests and diseases through interactions with the decomposition food web in support of plant nutrition. Soil fauna, including microarthropods, are key regulators of decomposition at local scales but their role at larger scales is unresolved. Future research priorities include the incorporation of multi-channel omnivory into food web modeling and understanding the vulnerability of our soil carbon to increased global temperatures.

The Gestalt psychologists’ theory of insight problem-solving was based on a direct parallelism between perceptual experience and higher-order forms of cognition (e.g., problem-solving). Simi-larly to the sudden recognition of an ambiguous figure, they contended that problem-solving in-volves a restructuring of one's initial representation of the problem’s elements, leading to a sud-den leap of understanding phenomenologically indexed by the "Aha!" feeling. Over the last centu-ry, different scholars discussed the validity of the Gestalt psychologists’ perspective foremost us-ing the behavioral measures available at the time. However, in the last 2 decades, scientists gained a deeper understanding of insight problem-solving due to the advancements in cognitive neuroscience. This review aims to provide a retrospective reading of Gestalt theory based on the knowledge accrued by adopting novel paradigms and investigating their neurophysiological correlates. Among several key points that the Gestalt psychologists underscored, we focus specif-ically on the role of the visual system in marking a discrete switch of knowledge into awareness, as well as the perceptual experience and the holistic standpoints. While the main goal of this paper is to read the previous theory in light of new evidence, we also hope to initiate an academic dis-cussion and encourage further research about the points we raise.

The microbiome gut brain (MGB) axis involves bidirectional routes of communication and has emerged as a potential therapeutic target for multiple medical specialities including psychiatry. Significant numbers of preclinical trials have taken place with some transitioning to clinical studies in more recent years. Some positive results have been reported secondary to probiotic administration in both healthy populations and specific patient groups. This review aims to summarise the current understanding of the MGB axis and the preclinical and clinical findings relevant to psychiatry. The link between the gut microbiome and irritable bowel syndrome (IBS) is well established. Significant differences have been identified between the microbiome of patients with a diagnosis of depressive disorder and healthy controls. Similar findings have occurred in patients diagnosed with bipolar affective disorder. A probiotic containing Lactobacillus acidophilus, Lactobacillus casei, and Bifidobacterium bifidum produced clinically measurable symptom improvement in patients with depressive disorder. To date some promising results have suggested that probiotics could play a role in the treatment of stress-related psychiatric disease. However, more well-controlled clinical trials are required to determine which clinical conditions are likely to benefit most significantly from this novel approach.

This research presents a maximum power point tracking of traditional single-ended primary converter (SEPIC) with the aid of fuzzy logic controller (FLC) for regulating the voltage and perturbation and observation(P&O) algorithms for regulating the reference voltage and reaching the maximum power point tracking. This is a promising technique for the conventional SEPIC converter to achieve maximum power point tracking with much less error. Moreover, the method is simple, reliable, and understandable for photovoltaic systems.

In 2023, the Bureau of Land Management (BLM) estimated that there were 68,928 mustangs living on United States public lands in 10 western states. The agency uses Appropriate Management Levels to determine the number of mustangs who need to be removed from the land. Once removed and processed, mustangs are sent to adoptions or sales events or retained in short-or long-term holding facilities. Adoptions and sales are the leading avenues for rehoming mustangs; however, the number of horses the BLM can place fluctuates annually and never approaches the greater number removed from the range. To explore opportunities for increasing the number of mustang adoptions, we conducted in-depth interviews with 23 horse trainers located on the U.S. East Coast, asking about participants’ training programs, relationships with horses, perceptions of mustangs, and challenges that mustangs face in the dressage and eventing industries. Participants had varying experiences with mustangs; however, all were willing to work with a mustang in some capacity. Participants voiced the need for more satellite adoption locations on the East Coast to decrease barriers to acquiring a mustang, notably cost and time, and for expanding existing training programs to include eventing and dressage.

A recent paper demonstrates the importance of the linker region joining the two SNARE motifs of the neuronal t-SNARE SNAP25 for maintaining rates of secretion with roles for distinct segments in speeding fusion pore expansion (Shaaban et al., 2019, Elife. 8). Remarkably, lipid perturbing agents rescue a palmitoylation-deficient phenotype that includes slow fusion pore expansion, suggesting that protein-protein interactions have a role not only in bringing together the granule or vesicle membrane with the plasma membrane but also in orchestrating protein-lipid interactions leading to the fusion reaction. Furthermore, biochemical investigations demonstrate the importance of the C-terminal domain of the linker in the formation of the plasma membrane t-SNARE acceptor complex for synaptobrevin2 (Jiang, et al., 2019, FASEB J. 33:7985-7994;Shaaban et al., 2019, Elife. 8). This insight, together with biophysical and optical studies from other laboratories (Wang, et al., 2008, Molecular Biology of the Cell. 19:3944-3955; Zhao, et al., 2013, Proc Natl Acad Sci U S A. 110:14249-14254) suggests that the plasma membrane SNARE acceptor complex between SNAP25 and syntaxin and the resulting trans SNARE complex with the v-SNARE synaptobrevin form just milliseconds before fusion.

A groundbreaking integrated predictive model, termed Cyber Forensics Behavioral Analysis (CFBA), has been developed in an environment characterized by rapidly evolving and increasingly sophisticated cyber threats. This model merges Cyber Behavioral Sciences with Digital Forensics to enhance the prediction accuracy and effectiveness of cyber threats originating from specific Autonomous System Numbers (ASNs). It has been observed that traditional cybersecurity strategies, predominantly focused on technical aspects, must be improved in addressing the complex landscape of cyber threats. Consequently, a novel approach has been proposed in this research, combining technical expertise with insights into the behavior of cybercriminals, thereby addressing a significant gap in existing methodologies. A mixed-methods approach has been employed in the study, integrating quantitative and qualitative research methods. This approach has created a comprehensive framework incorporating digital forensics, cybersecurity, computer science, forensic psychology, and the cyber behavioral sciences which incorporates disciplines scuch as cyberpsychology and forensic cyberpsychology. The study is anchored around four key concepts: (1) Forensic Cyberpsychology, which focuses on understanding psychological aspects of cybercriminal behavior; (2) Digital Forensics, involving the collection and analysis of digital evidence from cyber incidents; (3) Predictive Modeling, which utilizes historical data and patterns to anticipate potential cyber threats; and (4) the Cyber Behavioral Analysis Metric (CBAM) and Cyber Behavioral Score (CBS), tools designed for evaluating and scoring ASNs based on their behavior in terms of cybersecurity threat risks. Challenges encountered in the development of this integration have been significant. Initial setbacks included the misalignment of traditional cyber defense methods with the evolving nature of cyber threats and the absence of a holistic approach in pre-existing models. Through the narrative of these challenges and the subsequent development of the CFBA model, the research highlights the necessity for an interdisciplinary approach to cybersecurity. The outcomes of this study are not merely theoretical but provide practical, actionable tools and frameworks that markedly improve the precision of predicting cyber threats, especially from ASNs. The CFBA model represents a significant shift in cybersecurity strategies, highlighting the importance of integrating behavioral insights with technical knowledge. The study emphasizes the need for ongoing research and collaboration in cybersecurity, advocating for an approach that is as comprehensive and multifaceted as the cyber threats it seeks to mitigate. This research has been conducted to contribute significantly to cybersecurity, offering new perspectives and methodologies in a rapidly changing domain.

innate and adaptive immune responses lead to wound healing by regulating a complex series of events promoting cellular cross-talk. An inflammatory response is presented with its characteristic clinical symptoms: heat, pain, redness, and swelling. Some smart thermo-responsive polymers like chitosan can be used to create biocompatible and biodegradable scaffolds with 3D architectures similar to human structures, allowing their efficient and safe use as tissue engineering and drug delivery systems in chronic wounds. Locally heated tumors above polymer lower critical solution temperature can induce its conversion into a hydrophobic form, enhancing drug release until the thermal stimulus is gone, where a lower release is due to the swelling of the material. This paper integrates the relevant reported contributions of bioengineered scaffolds for thermo-responsive drug delivery in wound healing. Therefore, we present a comprehensive review that aims to demonstrate the capacity of these systems to provide spatially and temporally controlled release strategies for one or more drugs used in wound healing. In this sense, the novel manufacturing techniques of 3D-printing and electrospinning are explored for the tuning of their physicochemical properties to adjust therapies according to the patient’s convenience, as well as reduce drug toxicity and side effects.

While persons with schizophrenia find steady employment difficult to sustain, many of the women take on the most difficult task of all – motherhood. The aim of this paper is to review the challenges of motherhood in this population and the treatment strategies needed to keep mothers and children safe, protecting health and fostering growth. This is a narrative review reflecting the author’s life experience and a non-systematic search of the recent literature. Topics added are the stigma against motherhood in the context of schizophrenia, mothers’ painful choices, issues of contraception, abortion, and child custody, fostering and kin placement of children, the effects of antipsychotics, specific perinatal delusional syndromes, and parental supports. Recommendations are to work collaboratively with mothers who struggle with serious mental illness, take note of their strengths as well as their failings, offer a wide array of family services, monitor closely for safety, and appreciate the challenges these women daily face.

Severe mental illness such as schizophrenia is associated with factors such as unemployment, meagre per capita income, and residence in disadvantaged, poorly resourced neighbourhoods. This means difficult access to healthy food and is particularly problematic for pregnant women and mothers with children to feed. Eating problems are also linked to the necessity of taking antipsychotic drugs that often lead to serious cognitive, psychological, and behavioural sequelae. Psychosis makes it extremely difficult to maintain a healthy diet; nutritional deficiencies result, as do medical complications. The results of present literature review confirm the gravity of the problem and suggest a number of potentially useful interventions.

The purpose of this paper is to elucidate the roles that microbes may be playing in the rootzone of the medicinal plant Datura inoxia. We hypothesized that rhizospheric and endophytic microbes would be found that were capable of performing the same secondary metabolic functions of the plant rootzone they inhabited. We also hypothesized that the microbial functions would be co-operative with and supportive to plant secondary metabolite production, for example, by providing precursors to important plant bioactive molecules. The methods employed were mi-crobial barcoding, tests of essential oils against antibiotic resistant bacteria and other soil bacterial isolates, 16S Next Generation Sequencing (NGS) metabarcoding, and Whole Genome Shotgun (WGS) taxonomic and functional. A few of the main bacterial genera of interest that were dis-covered in the Datura root microbiome were Flavobacterium, Chitinophaga, Pseudomonas, Strepto-myces, Rhizobium, and Bacillus. In the context of known interactions, and current results, plants and microbes influence the flavonoid biosynthetic pathways of one other, in terms of the regulation of the phenylpropanoid pathway. This is important because these compounds are phyto-protective antioxidants and are precursors to many aromatic bioactive compounds that are relevant to human health. There was strong evidence to support the notion that synergistic production of plant de-rived secondary metabolites by microbes occurred, as well as the ability for the compounds to enter plant cells. There are possible biopharmaceutical and agricultural applications of the natural interplay that was discovered during this study of the Datura inoxia rhizosphere.

Background: Process mining (PM) exploits event logs to obtain meaningful information about the processes that produced them. As the number of applications developed on cloud infrastructures is increasing, it becomes important to study and discover their underlying processes. However, many current PM technologies face challenges in dealing with complex and large event logs from cloud applications, especially when they have little structure (e.g., clickstreams). Methods: Using Design Science Research, this paper introduces a new method, called Cloud Pattern API – Process Mining (CPA-PM), that enables discovering and analyzing cloud-based application processes using PM in a way that addresses many of these challenges. CPA-PM exploits a new application programming interface (API), with an R implementation, for creating repeatable scripts that preprocess event logs collected from such applications. Results: Applying CPA-PM to a case with real and evolving event logs related to the trial process of a Software-as-a-Service cloud application led to useful analyses and insights, with reusable scripts. Conclusion: CPA-PM helps producing executable scripts for filtering event logs from clickstream and cloud-based applications, where the scripts can be used in pipelines while minimizing the need for error-prone and time-consuming manual filtering.

Childhood obesity has become a global epidemic, with significant increases in prevalence over recent decades. While excessive calorie consumption and physical inactivity are known factors, emerging research highlights the role of Endocrine-Disrupting Chemicals (EDCs), particularly obesogens, in obesity's pathogenesis. This review explores the historical context of the environmental obesogens hypothesis, their sources, mechanism of action, impact on prenatal and postnatal development and epigenetics. Additionally, it discusses the long-term consequences of childhood obesity and proposes prevention strategies that will mitigate the negative health effects. Obesogens were found to disrupt hormonal balance and metabolic processes through various mechanisms such as altering gene expression, hormonal interference, and inflammation. Especially significant, was exposure during critical windows of development which correlates with increased risk of obesity in childhood or adolescence. Long-term effects of childhood obesity include chronic health conditions and psychosocial issues. A comprehensive approach is necessary to address childhood obesity, encompassing genetic, environmental, and lifestyle factors. Prevention strategies should focus on reducing obesogens exposure, promoting healthy lifestyles, and implementing regulatory policies. Future research should investigate obesogens-diet interactions, microbiome impacts, and combined obesogens effects. Long-term human studies are also crucial for validating findings from animal models and allow for inform decision-making to combat the obesity pandemic.

In the rapidly evolving landscape of wireless communication, each successive generation of networks has achieved significant technological leaps, profoundly transforming the way we connect and interact. From the analog simplicity of 1G to the digital prowess of 5G, the journey of mobile networks has been marked by constant innovation and escalating demands for faster, more reliable, and more efficient communication systems. As 5G becomes a global reality, laying the foundation for an interconnected world, the quest for even more advanced networks leads us to the threshold of the sixth-generation (6G) era. This paper presents a hierarchical exploration of 6G networks, poised at the forefront of the next revolution in mobile wireless technology. This study delves into the technological advancements that underpin the need for 6G, examining its key features, benefits, and the key enabling technologies. We dissect the intricacies of cutting-edge innovations like terahertz communication, ultra-massive MIMO, artificial intelligence (AI), machine learning, quantum communication, and re-configurable intelligent surfaces. Through a meticulous analysis, we evaluate the strengths, weaknesses, and state-of-the-art research in these areas, offering a wider view of the current progress and potential applications of 6G networks. Central to our discussion is the transformative role of AI in shaping the future of 6G networks. By integrating AI and machine learning, 6G networks are expected to offer unprecedented capabilities, from enhanced mobile broadband to groundbreaking applications in areas like smart cities and autonomous systems. This integration heralds a new era of intelligent, self-optimizing networks that promise to redefine the parameters of connectivity and digital interaction. This paper also addresses critical challenges in the deployment of 6G, from technological hurdles to regulatory concerns, providing a holistic assessment of potential barriers. By highlighting the interplay between 6G and AI technologies, this study not only maps out the current landscape but also lights the path forward in this rapidly evolving domain. This paper aims to be a cornerstone resource, providing essential insights, addressing unresolved research questions, and stimulating further investigation into the multifaceted realm of 6G networks. By highlighting the synergy between 6G and AI(Artificial Intelligence) technologies, we aim to illuminate the path forward in this rapidly evolving field.

This study explores the potential of yoga in developing crucial executive competencies within the context of transitional economies in Eastern Europe. As public sector enterprises face increasing competition, both domestically and internationally, there is a growing need for executives to acquire new skills. Through the lens of mindfulness, this research investigates the impact of yoga on the helping behavior and cultural intelligence of business leaders in a transitional economy. The findings reveal that yoga practices significantly enhanced participants' helping behavior and cultural intelligence. The study demonstrates that approximately two-thirds of the impact on helping behavior can be attributed to increased mindfulness, with the remaining one-third stemming directly from yoga practice. In terms of cultural intelligence, the results indicate that 88% of the improvement is due to heightened mindfulness, while 12% is directly attributable to yoga practices.

Digital machine intelligence has evolved from its inception in the form of computation of numbers to AI, which is centered around performing cognitive tasks that humans can perform, such as predictive reasoning or complex calculations. The state of the art includes tasks that are easily described by a list of formal, mathematical rules or a sequence of event-driven actions such as modeling, simulation, business workflows, interaction with devices, etc., and also tasks that are easy to do “intuitively”, but are hard to describe formally or as a sequence of event-driven actions such as recognizing spoken words or faces. While these tasks are impressive, they fall short in applying common sense reasoning to new situations, filling in information gaps, or understanding and applying unspoken rules or norms. Human intelligence uses both associative memory and event-driven transaction history to make sense of what they are observing fast enough to do something about it while they are still observing it. In addition to this cognitive ability, all bio-logical systems exhibit autopoiesis and self-regulation. In this paper, we demonstrate how machine intelligence can be enhanced to include both associative memory and event-driven transaction history to create a new class of knowledge-based assistants to augment human intelligence. The digital assistants use global knowledge derived from the Large Language Models to bridge the knowledge gap between various participants interacting with each other. We use the general theory of information and schema-based knowledge representation to create the memory and history of various transactions involved in the interactions.

Senescence is a stable cell cycle arrest that is either tumor suppressive or tumor promoting depending on context. Epigenetic changes such as histone methylation are known to affect both induction and suppression of senescence by altering expression of genes that regulate the cell cycle and the senescence-associated secretory phenotype. A conserved group of proteins containing a Jumonji C (JmjC) domain alter chromatin state, and therefore gene expression, by demethylating histones. Here, we will discuss what is currently known about JmjC demethylases in induction of senescence and how these enzymes suppress senescence to contribute to tumorigenesis.

Many species of plants are found in regions to which they are alien. Their global distributions are characterised by a family of exponential functions of the kind that arise in elementary statistical mechanics (an example in ecology is MacArthur's broken stick). We show here that all these functions are quantitatively reproduced by a model containing a single parameter – some global resource partitioned at random on the two axes of species number and site number. A dynamical model generating this equilibrium is a two fold stochastic process and suggests a curious and interesting biological interpretation in terms of niche structures fluctuating with time and productivity; with sites and species highly idiosyncratic. Idiosyncrasy implies that attempts to identify a priori those species likely to become naturalized are unlikely to be successful. Although this paper is primarily concerned with a particular problem in population biology, the two fold stochastic process may be of more general interest.

Chronic inflammation may have a detrimental impact on human health as it tends to result in cancer. In addition, it is often linked to different steps that participate in tumorigenesis, including cellular transformation, survival, promotion, invasion, proliferation, angiogenesis, and metastasis. Hence, inflammation predisposes cancer development and plays a vital role in promoting all tumorigenesis stages. Inflammation is caused by many factors, such as bacterial and viral infections, tobacco smoking, autoimmune diseases, obesity, asbestos exposure, and many others, increasing cancer risk. Moreover, cancer can be enhanced by mutations that proceed to cancer progression. Consequently, it leads to immunosuppression and provides a favorable background for tumor development. Although many studies address the question of relationships between inflammation and cancer development, little attention is paid to the link between inflammation and blood cancer. Therefore, the current study reviews the role of inflammation in cancer development, particularly in blood cancer. A meta-analysis research approach meets the research objective and answers the research question. The review results indicate that chronic inflammation directly relates to the development of many cancer types, blood cancer in particular.

Biological systems have a unique ability inherited through their genome. It allows them to build, operate, and manage a society of cells with complex organizational structures where autonomous components execute specific tasks and collaborate in groups to fulfill systemic goals with shared knowledge. The system receives information from various senses, makes sense of what is being observed, and acts using its experience, while the observations are still in progress. We use the General Theory of Information (GTI) to implement a digital genome, specifying the operational processes that design, deploy, operate, and manage a cloud-agnostic distributed application that is independent of IaaS and PaaS infrastructure, which provides the resources required to execute the software components. The digital genome specifies the functional and non-functional requirements that define the goals and best-practice policies to evolve the system using associative memory and event-driven interaction history to maintain stability and safety while achieving the system’s objectives. We demonstrate a structural machine, cognizing oracles, and knowledge structures derived from GTI used for designing, deploying, operating, and managing a distributed video streaming application with autopoietic self-regulation that maintains structural stability and communication among distributed components with shared knowledge while maintaining expected behaviors dictated by functional requirements.

Succinate is proposed to be a mediator of muscle exercise-induced adaptations. We studied metabolic health and changes of muscle mass in 6-month-old male mice after 12 weeks of feeding regular diet (RD, 13.4 kcal% fat, 66.8 kcal% carbohydrate, 29.8 kcal% protein), high fat diet (HFD, 60 kcal% fat, 20 kcal% carbohydrates, 20 kcal% protein) and ketogenic diet (KD, 80 kcal% fat, <1 kcal% carbohydrates, 20 kcal% protein) with or without 2% succinate supplements (SUS) in drinking water (n=8-12 per group). Functional overloading of the plantaris muscle (PL) was induced in a group of mice by denervation of the gastrocnemius and soleus muscles at week 6 of feeding different diets. HFD induced the greatest (p < 0.001) increase in body and fat mass. HFD and KD lead to significant (p < 0.01) impairment in glucose tolerance compared to RD. SUS blunted (p < 0.01) initial surge in energy intake when mice were switched from RD to HFD, but did not influence any measures of metabolic health after 12 weeks of the study. Functional overloading lead to ~25% increase in PL mass which was not affected by diet or SUS. In conclusion, SUS does not have a long-term effect on metabolic health or muscle mass.

Objective: To investigate fundamental movement skills (FMS) and physical activity differences among Hispanic and non-Hispanic White elementary school children. Materials and Methods: This study included 194 children aged between 4 and 11 in kindergarten, 2nd, and 5th grades. For evaluable participants, t-tests were used to test potential differences in fitness or movement skills. The characteristics of Hispanic and non-Hispanic White were compared using the p-value to detect statistical differences in anthropometric, FMS, and fitness characteristics. To identify any noticeable differences, the means and standard deviations of each group were compared. Results: There were significant group differences across the participants in age, height, Body Mass Index (BMI), BMI percentile, arm circumference, and waist circumference. In addition, there were significant differences between Hispanic and Non-Hispanic White in catch, run, dodge, punt, and two-hand strike (all p’s <0.05). Lastly, there were significant differences between Hispanic and Non-Hispanic White in pull-up, push-up, and sit-up (all p’s <0.05). Conclusion: Future studies should focus on decreasing obesity, increasing fitness, and FMS in elementary school children. Particularly, with Hispanic children whose FMS is negatively affected at such a young age, leading to eventual implications for their physical fitness and health in the future.

In a world filled with uncertainties, Ebb&Flow emerged as a story of convergence, intertwining dementia research, caregiving, and artistic exploration into a tripartite creative knowledge exchange. This study delves into the complexities of uncertainty in dementia care and research through a collaborative project involving artists, researchers, carers, and individuals with lived experience of dementia. Initiated by the Trellis:Arbor program, Ebb&Flow sought to co-created a human space addressing the multifaceted nature of uncertainty. The sea, with its unpredictable nature, served as a guiding metaphor for the project, reflecting the unpredictability of dementia and life. Over three months, through paintings, writings, and digital mediums, participants documented the changing emotions, challenges, and discoveries they encountered daily. The project fostered an environment where uncertainties were openly discussed, building supportive and resilient communities through participatory co-creation and methodological exchange. Key activities included a digital logbook, allowing participants to document and share their experiences of uncertainty, and the creation of the Ebb&Flow card deck—a compilation of personal stories and insights that serve as a legacy of shared experiences. Each card facilitated dialogue, understanding, and connection, bridging gaps between those affected by dementia and the broader community. The project culminated in a final exhibition and sharing event, where participants, researchers, and the public celebrated the journey's outcomes through stories and artworks. Throughout this journey, we observed that embracing uncertainty and fostering empathy through creative collaboration profoundly impacted participants, enhancing empathy and resilience. This project underscores the transformative potential of integrating artistic practices with scientific research to address the emotional and psychological burdens of dementia and research environments. Ebb&Flow demonstrates that even in the face of the unknown, a united community can find strength, solace, and understanding, highlighting the power and beauty of unity in exploring and expressing the multifaceted experiences of dementia and life.

Volatile compounds, abundant in breath, can be used to accurately diagnose and monitor a range of medical conditions. This offers a non-invasive, low-cost approach with screening applications; however, uptake of this diagnostic approach has been limited by conflicting published outcomes. Most published reports rely on large scale screening of the public, at single time points and without reference to ambient air. Here, we present a novel approach to volatile sampling from cellular headspace and mouse breath that incorporates multi-time point analysis and ambient air subtraction revealing compound flux as an effective proxy of active metabolism. This approach to investigating breath volatiles offers a new avenue for disease biomarker discovery and diagnosis. Using gas chromatography mass spectrometry (GC/MS), we focus on low molecular weight, metabolic substrate/by-product compounds and demonstrate that this non-invasive technique is sensitive (reproducible at ~1 µg cellular protein, or ~500,000 cells) and capable of precisely determining cell type, status and treatment. Isolated cellular models represent components of larger mammalian systems and we show that stress- and pathology-indicative compounds are detectable in mice, supporting further investigation using this methodology as a tool to identify volatile targets in human patients.

Although fragility fractures, osteoporosis, sarcopenia and frailty are becoming more prevalent in our aging society the treatment options are limited and preventative strategies are needed. Despite magnesium being integral bone and muscle physiology the relationship between dietary magnesium and skeletal muscle and bone health has not been investigated concurrently before. We analysed cross-sectional associations between dietary magnesium and skeletal muscle mass (as fat free mass – FFM), grip strength and bone density (BMD) in 156,575 men and women aged 39-72 years from the UK Biobank cohort. FFM was measured with bioelectrical impedance and expressed as the percentage of body weight (FFM%) or divided by body mass index (FFM_BMI). Adjusted mean grip strength, FFM%, FFM_BMI, and BMD were calculated according quintiles of dietary magnesium, correcting for covariates. Significant inter-quintile differences across intakes of magnesium existed in men and women respectively of 1.1% and 2.4% for grip strength, 3.0% and 3.6% for FFM%, 5.1% and 5.5% for FFM_BMI, and 2.9% and 0.9% for BMD. These associations are as great or greater than annual measured losses of these musculoskeletal outcomes indicating potential clinical significance. Our study suggests that dietary magnesium may play a role in musculoskeletal health and have relevance for population prevention strategies for sarcopenia, osteoporosis and fractures.

Background: The uptake of COVID-19 booster vaccines has been significantly low. Therefore, it is questionable whether combining the COVID-19 booster vaccines with Influenza vaccines can increase the population's interest in taking such vaccines and manage the health pandemic effectively. Methodology: In this systematic review and meta-analysis, a synthesis of the findings and summary of a total of 30 research articles based on the topic, ‘combining influenza and COVID-19 booster vaccination strategy’ was undertaken. The research articles were identified from three databases, namely, PubMed, Cochran Library, and Google Scholar using specific keywords and inclusion criteria. However, research articles that were not peer-reviewed and not published in English were excluded from the systematic review and meta-analysis. The average risk ratio of the included articles was 0.78% based on a 95% CI. On the other hand, the heterogeneity between such studies was I² = 35%, while the statistical significance of their findings occurred at p < 0.05. The average p-value of the included research studies was p = 0.62, implying that the null hypothesis was not rejected in almost all the studies. Results: A synthesis of the chosen research articles revealed that when influenza and COVID-19 booster vaccines are combined, there is potential for an increase in the uptake of the latter, mainly because many populations have already been accustomed to taking influenza vaccines on an annual basis. Conclusions: In this way, through such findings, medical health experts can make informed decisions to increase the population's willingness to receive the COVID-19 booster vaccines.

Introduction: Established predictors for COVID-19 related mortalities are diverse, with cytokine release syndrome (CRS), a key intermediator to the case fatalities being dominant and multi-faceted. The impact of these several risk factors on coronavirus mortality have been previously reported in several meta‐analyses limited by small sample sizes and premature data, and CRS not fully being accounted for. The objective of this systematic review and meta-analysis was to evaluate the evidence on the risk of COVID-19 related CRS and mortality with HIV serostatus using published data, and a meta-regression to account for possible covariates. Method: Electronic databases including Google Scholar, Cochrane Library, Web of Sciences (WOS), EMBASE, Medline/PubMed, COVID-19 Research Database, and Scopus, were systematically searched till 30th February, 2022. All human studies were included irrespective of publication date or region. Twenty-two studies with a total of 19,783,097 patients detailing COVID-related mortality and eleven with a total of 2,005,274 were included. To pool the estimate, a random-effects model with risk ration as the effect measure was used. Moreover, publication bias and sensitivity analysis were evaluated followed by meta-regression. The trial was registered (CRD42021264761) on the PROSPERO register. Results: The findings were consistent in stating the contribution of HIV infection for COVID-19 related CRS and mortality. The cumulative COVID-19 related mortality and CRS was 110270 (0.6%) and 48863 (2.4%) with total events of 2010 (3.6%), 108260 (0.5%) and 837(4.6%), 48026 (2.4%) among HIV-positive and negative persons respectively. HIV infection showed an increased risk of COVID-19 related CRS and mortality [RR= 1.48, 95% CI (1.16, 1.88) (P=0.002)] and [RR =1.19, 95% CI (1.02 -1.39) (P=0.00001)] respectively, both with substantial heterogeneity (I² > 80%). The true effects size in 95% of all the comparable populations fell between 0.64 to 2.22 and 0.67 to 3.29 for mortality and CRS respectively. MC studies and COVID-19 mortality with HIV infection showed a significant association [RR = 1.305, 95% CI (1.092 -1.559) (P = 0.003)], similar to studies conducted in America (RR = 1.422, 95% CI 1.233–1.639) and South Africa (RR = 1.123, 95% CI 1.052–1.198). HIV infection showed a risk for ICU admission [(P=0.00001) (I² = 0%)] and mechanical ventilation [(P=0.04) (I² = 0%)] as parameters of CRS. Furthermore, risk of COVID-19 related CRS is influenced by the year a study was conducted (R² = 0.55) and the region (R² = 0.11) same for mortality (R² = 0.60). The variance proportion explained by covariates was significant for CRS (I² = 86.5%, Q = 73.99, df = 10, P = 0.0000) (R² = 0.78) and mortality (I² = 87.5%, Q = 168.02, df = 21, p = 0.0000) (R² = 0.67). Conclusion: Our updated meta-analysis indicated that HIV infection was significantly associated with an increased risk for both COVID-19 – CRS and mortality, which might be modulated by regions, study setting and year. Risk for ICU admission and mechanical ventilation are the key indicators of CRS. We believe the updated data further anchoring CRS will contribute to more substantiation of the findings reported by similar earlier studies (Dong et al., 2021; K. W. Lee et al., 2021; Massarvva, 2021; Mellor et al., 2021; Ssentongo et al., 2021)

(1) Background: The definition of value addition is based on the process or processes which are used to transform physically the initial raw material in the final food or non-food article. Diversification can enhance the possibility of increased gains. The aim of this work is to give a reliable description of value addition when speaking of coconut-based beverages among all possible derivatives; (2) Methods: a systematic review of main papers on the argument has been critically examined and discussed; (3) Results: Processing degree is a consequence of consumers’ requests. Three different drivers for value addition have been considered: packaging, durability, and size options; sensorial features; and sustainability. Results of this investigation have highlighted the added value of several products because of recyclable packaging materials, intermediate or long durability expectations, different available sizes, and good or excellent sensorial performances; (4) Conclusions: There are different value-added coconut-based beverages with interesting perspectives. On the other side, sustainability and eco-friendly policies may be a problem for those products which are produced similarly to non-coconut based beverages. The opportunity of certified organic and/or fair-trade products could help the industry of coconuts in the next future. More research is still needed in this ambit.

Global wind observations are fundamental for studying weather and climate dynamics. Most wind measurements come from atmospheric motion vectors (AMVs) by tracking the displacement of cloud or water vapor features. These AMVs generally rely on thermal infrared (IR) techniques for their height assignments, which are subject to large uncertainties in the presence of weak or reversed vertical temperature gradients around the planetary boundary layer (PBL) and with tropopause folding. Stereo imaging can overcome the height assignment problem using geometric parallax for feature height determination. In this study we develop a stereo 3D-Wind algorithm to simultaneously retrieve AMV and height from geostationary (GEO) and low Earth orbit (LEO) satellite imagery and apply it to collocated Geostationary Operational Environmental Satellite (GOES) and Multi-angle Imaging SpectroRadiometer (MISR) imagery. The new algorithm improves AMV and height relative to products from GOES or MISR alone, with an estimated accuracy of <0.5 m/s in AMV and <200 m in height with 2.2 km sampling. The algorithm can be generalized to other LEO-GEO or GEO-GEO combinations for greater spatiotemporal coverage. The technique demonstrated with MISR and GOES has important implications for future high-quality AMV observations, for which a low-cost constellation of CubeSats can play a vital role.

During the COVID-19 pandemic, the term “behavioural fatigue” became the centre of policy debates in Great Britain. These debates involved deciding when to go into lockdown and whether behavioural interventions could be effective. Behavioural interventions can only succeed where people’s capabilities, opportunities, and motivations to perform target behaviours are supported. Our retrospective data analyses examine the relationships between people’s capabilities, opportunities, motivations, and behaviours, i.e., adherence to lockdown guidelines. Our cross-sectional analyses include 17,962 unique participants in Great Britain who completed a survey over the initial 30 days of the first lockdown (April 2020). We examine trends in responses to each scale and then the relationships between the scales using Granger’s causality test with tests for stationarity and cointegration. A mixture of increasing and decreasing trends were identified for capabilities and opportunities. Decreasing trends were identified for motivation and behaviour. Granger’s causality tests found that capability forecasts opportunity and behaviour and that motivation forecasts opportunity. The discussion reiterates that to realize and maintain behaviour changes, policies surrounding people's capabilities, opportunities, and motivations must continue to support target behaviours.

Background of the Study: We investigated the link between hypertension and cancer since it has been suggested that hypertension may raise the long-term risk of cancer. Previous large observational cohort studies found that greater blood pressure (BP) was related to a higher risk of cancer. Mendelian randomization (MR) was utilized to produce less confounded blood pressure estimates (BP) on overall and site-specific malignancies. The study aims to draw conclusions on the relationship between high blood pressure and cancer. Methods: Studies on high blood pressure and various malignancies are inconclusive, except for renal cell carcinoma. However, given that most meta-analyses only contained a limited number of trials, some relative risks had small to moderate magnitudes, and several may have been impacted by residual confounding, careful interpretation is necessary. The study was conducted using the meta-analysis technique. Cochran's Q test and I2 test were used to assess statistical heterogeneity between studies in the current investigation for research involving two or more cause and outcome combinations. Results: Positive correlations were also reported between high blood pressure and esophageal adenocarcinoma, squamous cell carcinoma, liver, and squamous cell carcinoma. However, most studies lacked multivariable adjustments. Physical and numerical risk of cardiovascular disease is linked to bowel cancer but no other cancers. According to a meta-analysis, hypertensive persons could also be at increased danger of gastrointestinal and breast cancer. Most meta-analyses comprised several trials with moderate or mild hazard ratios.ConclusionDifferent types of cancers have been noted to be directly caused by hypertension. In addition, some treatments have also been associated with the side effects of cancer treatments to cause hypertension. Women facing hypertension have an increased risk of getting breast cancer. Although some cancers showed a real relationship with hypertension, others had no connection at all.

A significant number of research studies have focused on determining whether BMI influences various types of cancer. The findings of these studies showed that people have to manage their BMIs to decrease their risk of developing various types of cancer, one of which is ovarian cancer. A PRISMA guideline for systematic review and meta-analysis was used to identify 20 research studies related to the topic to establish the truth or falsity of the findings. Later, their findings were synthesized. The synthesis of the findings of such research articles suggests that overweight and obesity increase an individual’s risk of developing ovarian cancer and experiencing severe symptoms of the disease. In such a manner, the current research study can conclude that effective management of BMI is necessary for decreasing the prevalence and mortality rates associated with ovarian cancer.

Covid-19 restrictions impacted many people’s daily lives through infection, fear of infection and the implementation of restrictions on movement. Restrictions and fear of contamination impacted physical activity patterns activity and increased mental health issues globally across a variety of ages. This re-issue of a questionnaire sought to examine the impact of Covid-19 restrictions on frequency of physical activity, participation in sports, wellbeing and symptoms of anxiety and depression in Irish adolescents. 3,021 adolescents from 61 post-primary schools in the Republic of Ireland completed questionnaires. Consistent with a previous issue of the questionnaire, a minority of adolescents were found to meet the WHO’s physical activity guidelines (11.6% of males and 5.2% of females) although there were large decreases in 1^st year males and females. Adolescents reporting elevated symptoms of depression increased from 39% to 46% with almost 3 in 5 females reporting symptoms of depression ranging from mild to extreme. Highest levels of wellbeing were found in adolescents who participated in 3 or more sports, although there was an 8% reduction in the amount of adolescents who participated in 3 or more sports. There were no changes in physical activity levels overall, despite changes within sub-groups and patterns of physical activity. There was a clear increase in symptoms of depression, with females impacted more than males. Previously active individuals were more likely to increase activity and therefore report higher levels of mental health while those who were less active were more likely to decrease activity and report lower mental health.

Background: Several kinds of research say that adjuvant blood glucose and blood pressure are usual, but an efficient solution for medical application count remains. This review analyzes the pandemic blood pressure and blood glucose to identify the publications which tell about the clinical practices and research gaps in systematic research.Methods: A study guides to identify the research of Blood Pressure (BP) and Blood Glucose. In order to analyze the recent innovations and research on BP and Blood glucose, the relevant publications and literature from journals were identified.Results: Co-morbidity of BP and Blood glucose is reported as very high. The commonness of blood pressure is thrice as high in type I diabetes patients and almost two times higher in type II diabetes patients when compared to others without Diabetes. The pervasiveness of getting depression is more in the female when compared with men. A detailed study about the linkage of BP and blood glucose tells that the relationship between them is not exactly clear.Limitations: Nearly all reviews providing the linkage of BP and blood glucose are with some limitations and they are not providing any clear conclusion.Conclusions: Present research tells that people having high blood glucose will have a greater chance of getting high blood pressure. More research is needed to state the linkage between BP, blood glucose, and the growth of diabetes mellitus issues and to provide support for managing Diabetes.

Significant problems have arisen in the last years, such as climate change, global warming, and hunger. These complications are correlated with the depletion and exploitation of natural resources and environmental contamination. Due to overcrowding, the list of challenges for the next few years is growing. A comprehensive approach was made to the agro-industrial production of Avocado (Persea americana) and the management of all its biomass waste. So, bioprocesses and biorefinery can be used to produce high added-value products. A large number of residues are composed of lignin and cellulose. They have many potentials to be exploited sustainably for chemical and biological conversion; physical, chemical, and natural treatments improve the following operations. There are some applications to many fields such as pharmaceutical, medical, material engineering, and environmental remediation. Possible pathways are mentioned to take advantage of Avocado as biofuels, drugs, bioplastics, and even in the environmental part and emerging technologies such as nanotechnology using bioprocesses and biotech. In conclusion, Avocado and its waste could be transformed into high value-added products in industries above to mitigate global warming and save non-renewable energy.

This paper presents an innovative data-centric paradigm for designing computational systems by introducing a new informatics domain model. The proposed model moves away from the conventional node-centric framework and focuses on data-centric categorization, using a multimodal approach that incorporates objects, events, concepts, and actions. By drawing on interdisciplinary research and establishing a foundational ontology based on these core elements, the model promotes semantic consistency and secure data handling across distributed ecosystems. We also explore the implementation of this model as an OWL 2 ontology, discuss its potential applications, and outline its scalability and future directions for research. This work aims to serve as a foundational guide for system designers and data architects in developing more secure, interoperable, and scalable data systems.

Despite the known benefits of precision agriculture, the adoption is challenging due to the cost of investment and the farm sizes. Therefore, profitability is an important aspect to consider. This study aimed to evaluate the net returns, profitability, and investment efficiencies of PA by different economic farm sizes. The study was based on data retrieved from FADN and Eurostat. The study examined four countries (Poland, Germany, France, and Romania) under field crop farming using an investment cost of €35 941 - €71 883, and a 20% and 15% reduction in the cost of crop protection and fertilizer usage respectively without compromising productivity. There is a positive relationship between the adoption of PA and farm returns for larger-scale farms. The result of the profitability and analysis of investment efficiency using NPV showed a positive value for economic farm sizes of €100 000 and above. Hence, it is not economically advisable that all farmers use PA technologies with the hope that they will be profitable but with public support (subsidies) more farms will be able to use PA and be profitable. Also, an opportunity to meet the goal of the European Union Green Deal of minimizing emissions that cause climate change.

This paper investigates the energy dissipation level of a nonlinear vehicle suspension system. The suspension system is modelled as a mass-spring-damper system, which is designed using the output frequency response function (OFRF) method. This method enables the derivation of an explicit relationship, between the system output spectrum (or Performance metric) and the system nonlinear parameters of interest. The OFRF polynomial, of the energy dissipation level, was derived in terms of the nonlinear parameters of interest. The results obtained show that the OFRF model, of the energy dissipation level, could be used to estimate the amount of heat dissipated, for a set of design parameters. This has potentials of providing some insights, in the design of vibration-based energy harvesters, as some of the wasted heat energy could be converted to electrical energy.

Starfish are keystone species as predators in benthic ecosystems, but when population outbreaks occur this can have devastating consequences ecologically. Furthermore, starfish outbreaks and invasions can have adverse impact economically by impacting shellfish aquaculture. Addressing the imperative need to proactively mitigate starfish invasions requires comprehensive research on their behavior and the underlying mechanisms of outbreaks. This review scrutinizes the historical patterns of outbreaks among diverse starfish species across various regions, delineates the factors contributing to the proliferation of Asterias amurensis in Chinese waters, articulates preventive and remedial strategies, and outlines the potential for sustainable utilization of starfish.

This study explored differences in student-athletes’ symptoms of depression, anxiety, and stress pre- to post-COVID-19 pandemic. The WHO reported a 25% increase in depression and anxiety rates worldwide with young people disproportionately affected. Student-athletes face many stressors related to their sporting and academic feats but what is not known is how the COVID-19 pandemic affected their experiences of mental illness. A multiple cohort cross-sectional study design was employed, and data collected using physical and online surveys. Participants (M age = 19.98 years, SD = 1.50) were recruited from UK universities (N = 807; 427 pre-pandemic cohort, 380 post-pandemic cohort). Results revealed statistically significant differences in mean depression, anxiety, and stress scores between cohorts. Scores for the post-pandemic cohort were significantly higher than pre-pandemic, suggesting a worsening of symptom severity. Distributions of student-athletes across categories of symptom severity also worsened for depressive and anxiety symptoms post-pandemic and were skewed towards more severe categories. Symptoms of de-pression, anxiety, and stress were a concern pre-pandemic. Rates are higher in the post-pandemic cohort, suggesting a worsening of symptoms. This data adds to evidence on student-athletes’ symptoms of mental illness by exploring a UK sample and comparing scores pre- and post-pandemic.

Local Authorities have significant tourism planning responsibilities and can benefit from evidence-based approaches. Qualitative interviews with 29 Local Authorities identified impediments to adopting indicators. Key barriers included more knowledge of indicator systems, training in using systems and understanding sustainability value and governance issues. However, transitioning to sustainable tourism through monitoring requires efficient resourcing of Local Authorities. Statutory adoption of indicators may be needed to enable evidence-based planning and policymaking. More informed planning approaches can help destinations respond to tourism issues and sustainability threats. Findings have implications for facilitating indicator implementation and evidence-based planning in other tourism destinations internationally.

InSAR and associated analytic methods enable relative surface deformation measurements from low Earth orbit with a potential accuracy of centimeters to millimeters. However, assessing the actual accuracy can be quite difficult. The analytic methods are complicated enough that naive analytic error propagation is infeasible, and, in many settings, InSAR practitioners lack sufficient ground truth to assess results. Phase noise due to partial decorrelation from changes in the scattering properties of the ground is a prominent source of accuracy loss. In this paper we present a method to assess the loss of precision due to this component of phase noise. The proposed method consists of generating synthetic data stacks whose statistical properties match those of the actual input SAR data stacks, and then using the synthetic data for an ensemble calculation. The spread of the results of the ensemble calculation indicates the loss of precision. We show examples of the ensemble analysis at a mining operation in South Africa, and demonstrate the ability to estimate the precision of two InSAR deformation retrieval methods on a point-by-point and epoch-by-epoch basis.

The National Breast and Cervical Cancer Early Detection Program (NBCCEDP) of Minnesota, “Sage”, provides breast cancer screening to uninsured women. We introduce a novel mapping technique, spatially adaptive filters (SAFs), to estimate utilization of Sage screening in Minnesota. Sage screenings (N = 74,712) were geocoded. The eligible population was modeled with the RTI synthetic population dataset. Between 2011 and 2015, 36,979 women a year were Sage eligible. Utilization was highly variable across Minnesota (M = 37.2%, range 0% - 131%, SD = 18.7%). This replicable approach modeled utilization rates to the neighborhood-level, allowing Sage to prioritize locations and engage communities.

On 25 May 2018, the General Data Protection Regulation (GDPR)Article 17, the Right to Erasure (‘Right to be Forgotten’) came into force making it vital for organisations to identify, locate and delete all Personally Identifiable Information (PII) where a valid request is received from a data subject to erase their PII and the contractual period has expired. This must be done without undue delay and the organisation must be able to demonstrate reasonable measures were taken. Failure to comply may incur significant fines, not to mention impact to reputation. Many organisations do not understand their data, and the complexity of a hybrid cloud infrastructure means they do not have the resources to undertake this task. The variety of available tools are quite often unsuitable as they involve restructuring so there is one centralised data repository. This research aims to demonstrate compliance with GDPR’s Article 17 Right to Erasure (‘Right to be Forgotten’) is achievable in a Hybrid cloud environment by following a list of recommendations. However, 100% retrieval, 100% of time will not be possible, but we show that small organisations running an ad-hoc Hybrid cloud environment can demonstrate that reasonable measures were taken to be Right to Erasure (‘Right to be Forgotten’) compliant.

Eye movements support memory encoding by binding distinct elements of the visual world into coherent representations. However, the role of eye movements in memory retrieval is less clear. We propose that eye movements play a functional role in retrieval by reinstating the encoding context. By overtly shifting attention in a manner that broadly recapitulates the spatial locations and temporal order of encoded content, eye movements facilitate access to, and reactivation of, associated details. Such mnemonic gaze reinstatement may be obligatorily recruited when task demands exceed cognitive resources, as is often observed in older adults. We review research linking gaze reinstatement to retrieval, describe the neural integration between the oculomotor and memory systems, and discuss implications for models of oculomotor control, memory, and aging.

(R)-2-Amino-1-hydroxyethylphosphonic acid 2 was prepared by hydrolytic kinetic resolution of rac-diethyl oxiran-2-ylphosphonate followed by reaction with benzylamine, acid hydrolysis, catalytic hydrogenolysis and anion exchange chromatography. Recrystallization from water-ethanol gave 2, which was characterized by IR, 1H NMR, 13C NMR, 31P NMR, polarimetry, elemental microanalysis, high-resolution mass spectrometry and single-crystal X-ray diffraction. The acid 2 crystallized in the orthorhombic chiral space group P212121 with cell constants a = 6.303(2) Å, b = 7.104(2) Å, c = 11.627(3) Å. The X-ray crystal structure confirmed the (R)-configuration of 2 and revealed that 2 is zwitterionic in the solid state, with extensive intermolecular hydrogen bonding between the hydroxyl, ammonium cation and phosphonate anion groups.

Mid-tropospheric cut-off low (COL) pressure systems are linked to severe weather, heavy rainfall and extreme cold conditions over South Africa. They often result in floods and snowfalls in winter disrupting economic activities. This paper examines the evolution and circulation patterns associated with severe COLs over South Africa. We evaluate the performance of the 4.4 km Unified Model (UM) which is currently used operationally by the South African Weather Service to simulate daily rainfall. Circulation variables and precipitation simulated by the UM were compared against ECMWF’s ERA Interim reanalyses and GPM precipitation at 24-hour timesteps. We present five recent (2016-2019) severe COLs that had high impact and found higher model skill when simulating heavy precipitation during the initial stages than the dissipating stages of the systems. A key finding was that the UM underestimated precipitation mainly due to inaccurate placing of COL centers and areas of heavy rainfall by up to 5° of latitude away from the actual location, due to the poor formulating of cumulus and microphysics schemes in the model. Understanding the performance and limitations of the UM model in simulating COL characteristics can benefit severe weather forecasting and contribute to disaster risk reduction in South Africa.

Online education allows learners to develop knowledge and skills flexibly and conveniently—such observation among students whose characteristics involve student engagement, self-regulation, and self-efficacy. However, studies to characterize Filipino online learners seem lacking. Thus, this study aimed to characterize science education tertiary students in the Philippines concerning their online student engagement (OSE), self-regulated learning (SRL), and online learning self-efficacy (OLSE). The unprecedented events brought by COVID-19 pandemic also urged the implementation of online modalities while there is no available information on students’ online learning profiles. Hence, researchers used a survey research employed through ex post facto approach to determine the effects of the demographic profile on OSE, SRL, and OLSE. The survey was participated by N=373 respondents who answered the questionnaire with informed consent administered via Google Forms. Results revealed that OSE indicators moderately characterized students, while SRL and OLSE indicators are true of them, substantiated by the overall mean M=3.85(SD=0.90), M=3.86(SD=0.92), and M=3.14(SD=0.73), respectively. Also, multivariate tests showed no significant effect among the independent groups (p&gt;0.05), except for gender and OLSE interaction (p&lt;0.05) so, only in OLSE was a significant difference found in gender. In conclusion, Filipino online learners are moderate across aspects of student engagement, self-regulation, and self-efficacy.

Using a randomized, double-blinded, placebo-controlled, parallel group design, this investigation determined if the combination of 2-weeks flavonoid supplementation (329 mg/day, quercetin, anthocyanins, flavan-3-ols mixture) and a 45-minute walking bout (62.2±0.9% VO_2max) enhanced the translocation of gut-derived phenolics into circulation in a group of walkers (N = 77). The walkers (flavonoid, placebo groups) were randomized to either sit or walk briskly on treadmills for 45 minutes (thus four groups: placebo-sit, placebo-walk, flavonoid-sit, flavonoid-walk). A comparator group of runners (N = 19) ingested a double flavonoid dose for 2 weeks (658 mg/day) and ran for 2.5 h (69.2±1.2% VO_2max). Four blood samples were collected (pre- and post-supplementation, immediately-post- and 24-h post-exercise/rest). Of the 76 metabolites detected in this targeted analysis, 15 increased after the 2.5-h run, and when grouped were also elevated post-exercise (versus placebo-sit) for the placebo- and flavonoid-walking groups (P < 0.05). A secondary analysis showed that pre-study plasma concentrations of gut-derived phenolics in the runners were 40% higher compared to walkers (P = 0.031). These data indicate that acute exercise bouts (brisk walking, intensive running) are linked to an increased translocation of gut-derived phenolics into circulation, an effect that is amplified when combined with a 2-week period of increased flavonoid intake or chronic training as a runner.

We report the first correction by Prime editing of a mutation in the RYR1 gene, paving the way to gene therapies for RYR1-related myopathies. The RYR1 gene codes for a calcium channel named Ryanodine receptor 1, which is expressed in skeletal muscle fibers. The failure of this channel causes muscle weakness in patients, which degenerates into motor disabilities. Currently, there are no effective treatments for these diseases, which are mainly caused by point mutations. Prime editing allows the modification of precise nucleotides in the DNA. Our results showed a 59% correction rate of the T4709M mutation in the RYR1 gene in human myoblasts by RNA delivery of the Prime editing components. It is to be noted that the T4709M is recessive, and thus, persons having a heterozygous mutation are healthy. These results are the first demonstration that it is possible to correct mutations in the RYR1 gene.

The biophysical consequences of nanoscale curvature have been challenging to resolve due to size-dependent membrane behavior and the experimental resolution limits imposed by optical diffraction. Recent advances in nanoengineering and super-resolution techniques have enabled new capabilities for creating and observing curvature. In particular, draping supported lipid bilayers over lithographically patterned substrates provides a model system for endocytic pits. The experiments and simulations presented below describe the possible detection of membrane curvature through fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS), single particle tracking (SPT), and polarized localization microscopy (PLM). FRAP and FCS depend on diffraction-limited illumination and detection. In particular, a simulation of FRAP shows no effects on lipids diffusion due to a 50 nm diameter membrane bud at any stage in the budding process. Simulated FCS demonstrated small effects due to a 50 nm radius membrane bud that was amplified with curvature-dependent lipid mobility changes. However, PLM and SPT achieve sub-diffraction-limited resolution of membrane budding and lipid mobility through the identification of the single-lipid positions with ≤15 nm spatial and ≤20 ms temporal resolution. By mapping the single-lipid step lengths to locations on the membrane, the effects of curvature on lipid behavior have been resolved.

Stress has been identified as one of the major causes of automobile crashes which then lead to high rates of fatalities and injuries each year. Stress can be measured via physiological measurements and in this study the focus will be based on the features that can be extracted by common wearable devices. Hence the study will be mainly focusing on the heart rate variability (HRV). This study is aimed to develop a good predictive model that can accurately classify stress levels from ECG-derived HRV features, obtained from automobile drivers, testing different machine learning methodologies such as K-Nearest Neighbor (KNN), Support Vector Machines (SVM), Multilayer Perceptron (MLP), Random Forest (RF) and Gradient Boosting (GB). Moreover, the models obtained with highest predictive power will be used as reference for the development of a machine learning model that would be used to classify stress from HRV features derived from HRV measurements obtained from wearable devices. We demonstrate that MLP was the ideal stress classifier by achieving a Recall of 80%. The proposed method can be also used on all applications in which is important to monitor the stress level e. g. in physical rehabilitation, anxiety relief or mental wellbeing.

Muscle mass, strength and physical function are known to decline with age. This is associated with the development of geriatric syndromes including sarcopenia and frailty. These conditions are associated with disability, falls, longer hospital stay, higher readmission rates, institutionalisation, osteoporosis, and death. Moreover, they are associated with reduced quality of life, as well as substantial costs to health services around the world. Dietary protein is essential for skeletal muscle function. Older adults have shown evidence of anabolic resistance, where greater amounts of protein are required to stimulate muscle protein synthesis and therefore require higher daily amounts of dietary protein. Research shows that resistance exercise has the most beneficial effect on preserving skeletal muscle. A synergistic effect has been noted when this is combined with dietary protein, yet studies in this area lack consistency. This is due, in part, to the variation that exists within dietary protein, in terms of dose, quality, source, amino acid composition and timing. Research has targeted participants that are replete in dietary protein with negative results. Inconsistent measures of muscle mass, muscle function, physical activity and diet are used. This review attempts to summarise these issues, as well as introduce the possible role of the gut microbiome and its metabolome in this area.

Lifelong learning has been integral to advancement of the nutrition and dietetics profession and its practitioners. Both the Commission on Dietetic Registration (CDR) and the Academy of Nutrition and Dietetics (Academy) advocate for continuous skill development and professional growth. Responding to evolving environmental trends and diverse practice perspectives, CDR joined the Joint Accreditation for Interprofessional Continuing Education organization in 2020 and CDR is transforming its own continuing professional education (CPE) requirements and prior approval program. This paper, a historical perspective and current state review, chronicles past and recent developments in nutrition and dietetics CPE, including opportunities for reflective learning and interprofessional continuing education (IPCE). Also explored are the establishment and expansion of the Joint Accreditation organization and its standards, as well as applicable case examples. Additionally, the paper outlines CDR’s and the Academy's strategies to advance inclusion, diversity, equity, and access (IDEA) within the profession and identifies how CPE advancements may facilitate accessible and equitable CPE for an increasingly diverse membership of practitioners. Nutrition and dietetics professionals stand to benefit from a more comprehensive understanding of CPE changes and the opportunities they may bring to the future of the profession.

Chronic pain is a serious health concern and potentially debilitating condition, leading to anxiety, depression, reduced productivity and functionality, and poor quality of life. This condition can be even more detrimental and incapacitating in the pediatric patient population. In low and middle income countries (LMICs), pain services are inadequate or unavailable, leaving most of the world's pediatric population with chronic pain untreated. Many of these children in LMICs are suffering without treatment, and often die in pain. Awareness and advocacy for this population must be prioritized. We reviewed the available literature on the chronic pediatric pain burden in LMICs, barriers to treatments, and current efforts to treat these patients.

InSAR and associated analytic methods can measure surface deformation from low earth orbit with a claimed accuracy of centimeters to millimeters. The realized accuracy depends on the area being measured and on the choice of analytic method, suggesting one choose a method in response to the area being measured. Here we consider a specific fixed analytic method and compare the results it produces to measurements gathered from other means in a variety of settings. In particular we compare Sentinel-1 InSAR with GPS at the Kilauea volcano around the 2018 eruption, with GPS in the city of Arica, Chile, and with public survey data at a decommissioned tailings mine. In addition, we compare two independent Sentinel-1 InSAR analyses for a railway station in Oslo, Norway. Our goal is estimate the accuracy of a fully automated Sentinel-1 InSAR pipeline in various settings. Our conclusions are that centimeter level accuracy is a reasonable claim in many, but not all settings, and that accuracy is typically not lost by using an automated pipeline, instead of hand-selecting and tuning parameters.

Expression of Krüppel–like factor 15 (KLF15), a stress induced transcription factor, is induced during bovine herpesvirus 1 (BoHV-1) reactivation from latency, and KLF15 stimulates BoHV-1 replication. Transient transfection studies revealed KLF15 and glucocorticoid receptor (GR) cooperatively transactivate the BoHV-1 immediate early transcription unit 1 (IEtu1), herpes sim-plex virus type 1 (HSV-1) infected cell protein 0 (ICP0), and ICP4 promoter. The IEtu1 promoter drives expression of bICP0 and bICP4, two key BoHV-1 transcriptional regulatory proteins. Based on these studies, we hypothesized infection is a stressful stimulus that increases KLF15 ex-pression and enhances productive infection. New studies demonstrated that silencing KLF15 impaired HSV-1 productive infection and KLF15 steady state protein levels were increased at late stages of productive infection. KLF15 was primarily localized to the nucleus following in-fection of cultured cells with HSV-1, but not BoHV-1. When cells were transfected with a KLF15 promoter construct and then infected with HSV-1, promoter activity was significantly increased. The ICP0 gene and to a lesser extent bICP0 transactivated the KLF15 promoter in the absence of other viral proteins. In contrast, BoHV-1 or HSV-1 encoded VP16 had no effect on KLF15 pro-moter activity. Collectively, these studies revealed HSV-1 and BoHV-1 productive infection in-creased KLF15 steady state protein levels, which correlated with increased virus production.

Inflammation is an underlying problem for many disease states and has been implicated in iron deficiency (ID). This study aimed to determine whether iron status is improved by epigallocate-chin-3-gallate (EGCG) through reducing inflammation. Thirty-two male Sprague-Dawley rats were randomly divided into four groups (n = 8 each): positive controls, negative controls, lipo-polysaccharide (LPS, 0.5 mg/kg body weight), and LPS + EGCG (LPS plus 600 mg EGCG/kg diet). Iron status, hepcidin, C - reactive protein (CRP), serum amyloid A (SAA), and interleukin-6 (IL-6) were measured. There were no differences in treatment groups compared with control in CRP, hepcidin, and liver iron concentrations. Serum iron concentrations were significantly lower in the LPS (p=0.02) and the LPS+EGCG (p=0.01) than in the positive control group. Compared to the positive control group, spleen iron concentrations were significantly lower in the negative con-trol (p<0.001) but not with both LPS groups. SAA concentrations were significantly lower in LPS + EGCG group compared to LPS alone group. IL-6 concentrations were significantly higher in LPS+EGCG (p= 0.004) than in any of the three groups. EGCG reduced SAA concentrations but did not affect hepcidin or improve serum iron concentration or other iron markers.

Aims: The aims of this meta-analysis were to assess: the prevalence of Post-Acute COVID-19 sequalae in HIV positive patients; average time of diagnosis; and meta-regress for possible moderators of PACS.Methods: A standard search strategy was used in PubMed, and then later modified according to each specific database to get the best relevant results. These included Medline indexed journals; PubMed Central; NCBI Bookshelf and publishers' Web sites in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis statement. Search terms included “long COVID-19 or post-acute COVID-19 syndrome/sequalae”, “persons living with HIV or HIV. The criteria for inclusion were published clinical articles reporting HIV in association with long COVID-19, further, the average time to an event of post-acute COVID-19 sequelae among primary infected patients with COVID-19. Random-effects model was used. Rank Correlation and Egger's tests were used to ascertain publication bias. Sub-group, sensitivity and meta-regression analysis were conducted. A 95% confidence intervals were presented and a p-value < 0.05 was considered statistically significant. Review Manager 5.4 and comprehensive meta-analysis version 4 (CMA V4) were used for the analysis. The review/trial was PROSPERO registered (CRD42022328509).Results: A total of 43 studies reported post-acute COVID-19 syndrome. Of those, five reported post-acute COVID-19 sequalae in PLHIV. Prevalence of post-acute COVID-19 sequalae was 43.1% (95% CI 20.5% to 68.9%) in persons living with HIV (PLWH). The average time to PACS diagnosis was 4 months at 64% [0.64 (95% CI 0.230, 0.913) (P < 0.0000), I²= 93%] and at one year to PACS diagnosis was at 70 %, however with non-significant correlation (P > 0.05). On comorbidities, asthenia was associated with PACS at 17.6 % [0.176 (95% CI 0.067, 0.385) (P = 0.008), I²= 86%] while fatigue at 82%, however not related with PACS event incidence (P < 0.05). Americas, Asian and European regions showed PACS events rates of 82%, 43% and 19 % respectively (P<0.05) relative to HIV infection. Conclusion: PACS prevalence in PLWH was 43% occurring at an average time of 4 months at 64% and 70 % at 12 months however non-significant with PACS. Asthenia was significantly associated with PACS at 17.6 % while fatigue at 82%, however not related with PACS event incidence. Americas recorded the highest PACS event rates in PLWH.

(1) Background: Youths with multiple risks and severe disadvantages experience poorer health and educational outcomes than less disadvantaged peers. To address problems with coping and self-regulation in this group, mental skills training (MST) approaches more commonly used in sport are an emerging intervention approach. (2) Methods and Results: This narrative review synthesizes literature to explain the need for MST, how it works, and evidence to support it works by focusing on two well evaluated programmes: LifeMatters and My Strengths Training for Life™. (3) Conclusions: To support positive youth development, MST is a strengths-based, flexible and adaptable approach to help fill the shortage of available evidence-based programs for those youths facing multiple disadvantages. The findings of this review may facilitate policy makers, commissioners, program planners, and researchers in the uptake of MST or similar psychoeducational approaches in future.

Introduction People are presenting with chronic musculoskeletal pain at a younger age, and many fulfil criteria for fibromyalgia. We have recently shown a strong association between fibromyalgia symptoms and autistic traits in a self-selected community population, with the relationship mediated in part by the presence of hypermobility. Many respondents also described food sensitivities and intolerances. This study explores relationships between food issues and fibromyalgia symptoms in this population Methods The study used a nonexperimental, correlational design with data collected from a volunteer sample of 442 adults (aged 18-60) who completed online self-report questionnaires assessing each of fibromyalgia symptoms (ACR criteria), autistic traits (RAADS score) and hypermobility (Beighton’s test). Subjects were also asked to record any food sensitivities, allergies, or intolerances, along with their consequences. Correlation analyses and linear regressions were used to test the relationships between these features and each of fibromyalgia, autistic traits and hypermobility. Data was analysed using parametric and non-parametric techniques to assess the strength and significance of relationships, causes of variance and the potential mediating effect of food-related symptoms in the correlation between fibromyalgia features and autistic traits Results Our self-selected community population had a mean age of 24 years and was 77% female. The prevalence of fibromyalgia, autistic traits and hypermobility was 40%, 65% and 44% respectively. Half of all subjects reported food sensitivity and 31% reported food intolerance. The incidence of food-related symptoms was higher among subjects who met criteria for fibromyalgia than those who reported autistic traits or hypermobility. Food sensitivity and food intolerance were both more significantly associated with fibromyalgia (r=0.24, p>0.001 and r=0.38, p>0.001) than with autistic traits (r=0.15, p>0.01 and r=0.17, p>0.01). Discussion This is the first community study to provide evidence for a direct association between features of fibromyalgia and reported food intolerance and sensitivity. Although self-selected, the findings in our predominantly young population suggest that gluten and lactose consumption may be associated with higher levels of musculoskeletal pain. Avoidance of these foodstuffs was commonly reported to reduce symptoms. Dietary adjustment may merit further investigation as a therapeutic modality for some patients with fibromyalgia.

The review aims to assess fifteen (15) academic literature sources, highlighting the application of machine learning algorithms in the maintenance operations of optical fiber networks. It exhibits the collection of data using PRISMA methodology—Preferred Reporting Item for Systems Review and Meta-Analyses. The application, results, and performance metrics are discussed based on the collected observations, computations, and statistics in the studies, which revealed records of high accuracy degrees ranging from 86% to 98% on average and quality ML models including Neural Networks (NNs), Support Vector Machines (SVMs), and LSTM, as well as deep learning models that disclosed effective results of determining challenges and problems within the optical fiber lines. The review mainly centralized on superior machine learning technologies that surpass traditional techniques in fault detection and localization for improved optical fiber networks’ operations while providing insights into the limitations and challenges encountered in real-world applications of these models, offering a comprehensive perspective on the optical fiber network’s domain.

In 2015, the World Health Organization substantially revised its guidance for vaccination coverage cluster surveys (revisions were finalized in 2018) and has since developed a set of accompanying resources, including definitions for standardized coverage indicators and software (named the Vaccination Coverage Quality Indicators - VCQI) to calculate them. The current WHO vaccination coverage survey manual was used to design and conduct two nationally representative vaccination coverage surveys in Nigeria – one to assess routine immunization and one to measure post-measles campaign coverage. The primary analysis for both surveys was conducted using VCQI. In this paper, we describe those surveys and highlight some of the analyses that are facilitated by the new resources. In addition to calculating coverage of each vaccine-dose by age group, VCQI analyses provide insight into several indicators of program quality such as crude coverage versus valid doses, vaccination timeliness, missed opportunities for simultaneous vaccination, and, where relevant, vaccination campaign coverage stratified by several parameters, including the number of previous doses received. The VCQI software furnishes several helpful ways to visualize survey results. We show that routine coverage of all vaccines is far below targets in Nigeria and especially low in northeast and northwest zones, which also have highest rates of dropout and missed opportunities for vaccination. Coverage in the 2017 measles campaign was higher and showed less geospatial variation than routine coverage. Nonetheless, substantial improvement in both routine program performance and campaign implementation will be needed to achieve disease control goals.

Ethiopia is one of the countries with the highest level of malnourishment of lactating mothers in sub-Saharan Africa. However, different communities produced different foods solely for lactating mothers. "Shameta" is one of the cereal-based fermented cultural foods exclusively produced for lactating mothers with the perception that it would support the health, strength, and recovery of mothers. This study investigated the effects of fermentation time and blending ratio on the nutritional quality of "Shameta." Three levels of blending ratio of ingredients (Maize-Barley-Fava bean) and three levels of fermentation times were laid down in a completely randomized design (CRD). The study showed that lactic acid bacteria were the dominant group, followed by yeasts. Notably, the ingredient formulation ratio of Maize-Barley-Fava bean (81:5:5) in all fermentation times (8, 10, and 12 days) results in the highest LAB dominance with the highest crude fat (13.23 g/100g) content. However, the highest crude protein (16.56 g/100g) and mineral contents were observed in a ratio mix of 66:10:15 fermented for 12 days. The nutritional quality of culturally prepared Shameta can be improved by optimizing fermentation time and ingredient compositions for better recovery, strength, and health of lactating mothers.

Providing healthcare workers with cost information about the medications they prescribe can influence their decisions, particularly when that information is provided at the very moment they are faced with a prescribing decision. The current study aimed to analyse the impact of nudges that presented cost information to prescribers through their organisation's electronic prescribing system. The nudges were co-created by the research team (composed of behavioural scientists) and the lead hospital pharmacist. One nudge provided simple cost information (percentage difference between two brands of Mesalazine – Asacol and Octasa). The second nudge provided the potential annual cost-saving that could result if the cheaper medication was selected across the organisation. While the statistical analyses revealed that these nudges were not effective, several administrative barriers were overcome, which may inform future research. For example, presenting aggregated cost information to the prescribers is possible even when the actual cost of medicine is confidential and can not be displaced. In addition, future research could reveal more behavioural factors that facilitate medication optimisation.

Growing evidence suggests sleep plays an important role in the development of healthy adolescents, with increased interest in the associations between sleep and mental health. Higher duration and quality of sleep has been suggested as a mechanism for increased wellbeing in adolescents. Cross sectional data was collected from 5,661 Irish adolescents. 55% of Irish adolescents reported meeting the guidelines for adolescents of 8-10 hours per night. This was found to decrease with age. Higher duration and quality of sleep was positively associated with wellbeing and negatively associated with symptoms of anxiety and depression. A higher frequency of physical activity was associated with longer duration and higher quality of sleep. 9-10 hours of sleep was associated with the highest levels of wellbeing and lowest symptoms of anxiety and depression. The relationship between physical activity and increased wellbeing may be impacted by physical activity leading to higher durations and quality of sleep.

We present a summary of our protocol for employment of small-molecule circadian rhythm modulators. The abilities of compounds to affect oscillations have received significant attention. We outline assessments of circadian changes using indirubin-3’-oxime (IO), 5-iodo-indirubin-3’-oxime (5I-IO), and 5-sulfonic acid-indirubin-3’-oxime (5SA-IO), analyzing effects on Bmal1 and Per2 oscillations and oncogenic features.

Waterford Blaa is one of only seven Irish Protected Geographical Indication (PGI) products and the only Irish PGI bread. Currently, there are few published data characterising these products. This study aimed to determine whether any compositional or sensory markers could be used to differentiate between the three authorised producers of Waterford Blaa. Compositional testing was completed using AOAC standard methods; colour of top crust, bottom crust and crumb were identified with the Minolta Hunter lab colorimeter and texture profile analysis (TPA) was completed with an 80% compression test using the Instron 5544 to establish hardness, gumminess, and springiness. The fatty acid and aroma profiles were established in triplicate testing for the three authorised Blaa products using gas chromatography-flame ionisation detection and headspace-solid phase micro extraction-gas chromatography-mass spectrometry, respectively. As expected, results showed little variation in the overall composition of Waterford Blaa products. However, this study identified a unique fatty acid profile/volatile aroma profile for each Blaa. Specifically, the volatile profile showed potential differentiation between Blaa’s in terms of pentanal, furfural, 2-furanmethanol, 2-ethyl-1-hexanol and 2-pentyl furan. In addition, levels of hexanal and ethyl acetate were significantly different (p&lt;0.05) in the crumb section of all three Blaa’s. This unique fingerprint has the potential to be used to identify fraudulent products claiming to be Waterford Blaa.

(1) Background: Loss of weight is one of the practices which have been identified as key in reducing the risk of various forms of cancer. Therefore, this study is a systematic review and meta-analysis of studies related to the topic of loss of weight and risk of cancer and addresses the question, ‘does losing weight reduce the risk of cancer?’ Its purpose is to identify current high-quality evidence on such a question and synthesize such evidence before summarizing it given specific data attributes to improve decision-making processes on cancer management. (2) Methods: Research studies were identified from four main databases: PubMed, Science Direct, Google scholar, and Medline. A systematic review and meta-analysis of such studies were then conducted to reveal the most current evidence on the research topic. (3) Results: The studies showed that losing weight reduces cancer risk. Nonetheless, such intervention is not necessarily effective, especially in cases where patients may be at risk of developing cancer due to other risk factors. (4) Conclusions: The current study concludes that there is a need to implement effective interventions such as physical exercise, dietary restrictions, or both that can be effective in reducing weight to reduce the risk of cancer.

Fresh water springs are unique natural resources in Florida, currently under threat from increasing groundwater pumping and pollution resulting from a variety of sources. This paper estimates current recreation benefits from visiting springs using the travel cost method and elicits residents’ willingness to contribute for springs restoration using the contingent valuation method. It further compares the performance of count data models correcting for endogenous stratification and truncation, and finds that the annual consumer surplus per person per trip is between $20 and $43. Furthermore, visitors are willing to contribute $12 to $14 per person per trip for springs restoration without reducing trip demand.

This study developed gelatin-based films with incorporation of microcrystalline cellulose as reinforcement material. Clove (Syzygium aromaticum), nutmeg (Myristica fragrans), and black pepper (Piper nigrum) oleoresins containing antimicrobial compounds of natural origin were incorporated into films. The mechanical, thermal, optical, and structural properties, as well as color, resistance to sealing and permeability to water vapor, light, and oil of the films were determined. Adding oleoresins to the gelatin matrix increased elongation of the material and significantly diminished its permeability to water vapor and oil. Evaluation of the potential use of films containing different oleoresins as bread packaging material was influenced by the film properties. The biocomposite film containing oleoresin from black pepper was the most effective packaging material for maintaining the bread’s quality characteristics.

Underpinned by the new world Kirkpatrick model and in the context of a community-based, sport psychology program (My Strengths Training for Life™) for young people experiencing homelessness, this process evaluation investigated: (1) young peoples’ reactions (program and facilitator evaluation, enjoyment, attendance, and engagement) to and learning (mental skills and transfer intention), (2) the relationship between reaction and learning variables, and (3) the mediators underpinning this relationship. 301 young people living in a West Midlands housing service completed questionnaires on demographics, reaction and learning variables. Higher levels of program engagement were positively associated with more favorable reactions to the program. Enjoyment positively predicted learning outcomes, which was mediated by transfer intention. Recommendations are made for: (1) a balance between rigor and flexibility for evaluation methods with disadvantaged youth, (2) including engagement as well as attendance for indicators of meaningful program participation, (3) measuring program experiences (e.g., enjoyment) to understand program effectiveness, and (4) providing opportunities for skill transfer during and after program participation. Findings have implications for researchers, program commissioners, and policy makers working designing and evaluating programs in community-based settings.

In the United States, obesity is prevalent, and it could be described as a pandemic. Obesity is excessive fat accumulation, leading to a BMI ≥ 30 (Fruh, 2017). Surveys conducted by the CDC show that the obesity prevalence in the US is on the rise, as several obese people rose from 30.5% to 41.9% between 1999 and 2020 (Bryan et al., 2021). During the same time, several people suffering from severe obesity rose from 4.7% to 9.2% (Bryan et al., 2021). Additionally, childhood obesity is on the rise. Statistics indicate that between 2017-2020 over 19.7% of children and adolescents aged 2-19 years had obesity. During the same period, obesity prevalence in children aged 2-5 years, 6-11 years, and 12-19 years olds was 12.7%, 20.7%, and 22.2%, respectively (Bryan et al., 2021). With so many people suffering from obesity, the WHO declared it a public health crisis (WHO, 2020). The COVID-19 pandemic further exacerbated the prevalence of obesity in the US. According to the surveys, there was a 4.4% increase in obesity between 2019 to March 2020 due to lifestyle changes that were put on people during the COVID-19 pandemic (Akter et al., 2022). Many comorbidities are associated with obesity. Without adequate health interventions, millions of people could suffer severe health disorders like respiratory problems, type II diabetes, psychological issues, gastrointestinal disorders, and cardiovascular diseases. It is also essential to develop health interventions to mitigate obesity due to its strain on the healthcare system. Research shows that people suffering from obesity spend $2,505 more than people with average weight on healthcare (Cawley et al., 2021). Obesity has financial ramifications in every healthcare category: inpatient, outpatient, and prescription drugs (Cawley et al., 2021). One essential action toward the efforts to mitigate the soaring obesity rates is understanding the demographic inequities across populations and how they can be resolved.

Oncological patients need the proper doses of medications to facilitate their recovery. The two basic approaches used in dosing Monoclonal Antibodies (mAbs) are fixed-dose combination and variable dosing. In Fixed-Dose Combination Drugs (FDCs), two or more active components are combined in a single formulation at a predetermined dose. Variable dosage, which has long been the industry standard, is the polar opposite of this approach. The body changes over time; the Body Surface Area (BSA) in square meters is often used as a Measure (m2). This study uses a systematic review. Most mAbs used in oncology are predominantly given as cytotoxic anticancer drugs using body-size-based (variable) regimens. Despite the benefits of fixed-dose, variable dosing has become the industry standard, despite being criticized for ineffectiveness. While variable dosing has some advantages, the prevalent view is that continuous dosing has significant advantages based on the balance of probabilities. After assessing each alternative, including its benefits and drawbacks, history of use, and suitability in the current context, fixed dosing emerges as a viable option.

Many pilot-based initiatives have been developed to promote awareness and use of climate information services among vulnerable smallholder farmers in Africa through million-dollar investments. However, despite their experimental nature, these pilot projects have been successful in raising participating farmers’ awareness and use of climate information services and they can inform transferrable good practices. Through a systematic literature review approach, this review sought to understand ways in which these past pilot projects have contributed to climate risk management in the context of smallholder farming and the factors that led to their success. Results showed that climate information services main contribution to climate risk management has been through facilitating farm level decision making. Factors that led to success of the pilots include: use of downscaled information; building institutional partnerships to add value to climate information; involving farmers through the co-designing and co-developing process; face-to-face way of communication; embedding pre-seasonal workshops in the activities of local institutions for sustainability; using diversity of communication channels to enhance reach among others. These factors can be borrowed as good practices to inform future efforts focused on increasing adoption of climate information services among a wider population beyond pilot project reach.

Road-embedded inductive power transfer (IPT) systems have the potential to accelerate the electrification of the transportation sector. For these systems to be economically viable however, they need to have a similar durability and lifespan compared to that of asphalt roads. One area that has lacked investigation is thermally induced stresses in a primary IPT pad, which is caused by the increase in temperature of the pad when it is energized and the differing thermal expansion of the materials within. This paper presents an experimental and a finite-element based methodology for investigating the thermal-mechanical behaviour of a ¼-scale double-D pad, which was energized while suspended in air, as well as energized when embedded in pavement. A focus was placed on the measurement and prediction of strains in the magnetic ferrite cores because of their brittleness. Ferrite strains were measured using a combination of resistive strain gauges and non-metallic Fibre Bragg Grating (FBG) sensors. Coupled electromagnetic-thermal-structural simulations were conducted to predict temperature and strains in the system, with temperature-dependent properties obtained through physical testing. At an ambient temperature of 50°C, the temperature in the middle of the copper litz wire coil was predicted to be 100°C in both the suspended and embedded case. There was excellent correlation to experimental results, with a difference of less than 10% for most temperature measurements. When energized, the pad was predicted to experience an upward bow due to its temperature rise, resulting bending strains in the ferrite cores. At an ambient temperature of 50°C, maximum tensile strain in the ferrites of the embedded pad was measured to be 62 microstrain (με), with a root-mean square error that was 18 με across three sensors. The experimental and validated numerical methodology can be applied to full-scale operational IPT pads to analyse and improve their thermal-mechanical performance.

Ghana spends over $4000 (US dollars) annually managing municipal solid waste (MSW) with little improvement in regional sanitation. Energy demand in the country is also on the rise. Therefore, addressing waste problems via the waste-to-energy valorization approach is necessary for dual benefits. This paper thus seeks to comprehensively review Ghana's MSW's proximate and ultimate compositions for biological and thermochemical conversions. Studies between 2011 and 2024 were analyzed. The findings revealed that the organic fraction of Ghana’s MSW is currently about 10.47Kt per day. The proximate analysis reveals a moisture content from 13.55 – 61.9 %, volatile matter ranges from 6.24 - 80.25%, and the calorific value ranges from 14.96-21.46MJ/Kg. The ultimate analysis revealed that the carbon-to-nitrogen ratios range from 24.3-32.2, and the hydrogen content ranges from 5.53-22.8%. The sulphur and nitrogen contents were below 0.6 and 1.7% respectively. Approximately 2,534.65 GWh of electricity is estimated from the organic fraction. Ghana’s MSW is more suited for biochemical conversions.

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

Abstract: Fertility tracking of menstrual cycles during perimenopause with a quantitative hormone monitor is a novel undertaking. Women in regular menstrual cycles have been tracking their fertility using different biomarkers since the 1960’s [1]. Presently, there are newer electronic hormonal devices used to track fertility that provide more exact and objective data to help delineate the fertile time frame of a woman’s cycle. These devices measure quantitative levels of estrogen, luteinizing hormone, progesterone, and follicle stimulating hormone, all of which occur at varying levels during the menstrual cycle. As women advance toward menopause, their cycles vary in length and their hormones fluctuate [2]. In this retrospective analysis, forty-two women aged 40 to 50 tracked their cycles over time and eight of the forty-two women used the quantitative hormonal device. With the use of this device, the perimenopausal period has revealed distinct hormonal cycle characteristics unique to this group of women. It is the purpose of this paper to discuss those cycle characteristics during perimenopause that were found with the use of the quantitative hormonal device.

Data centres, though a necessary part of modern society, are being stigmatised for consuming vast amounts of electricity for their operational and cooling needs. Due to Ireland’s reliance on fossil fuels to meet the increased energy demand of data centres, the data centres are contributing significantly to Ireland’s total carbon emissions. As much of this energy is expelled from data centres as waste heat energy, the potential for recycling some of this wasted heat energy was explored using environmentally friendly systems from recent publications. The recovered waste heat energy was applied in a vertical farming system, and the benefits of this waste heat to the vertical farm were analysed and quantified in two scenarios. Using conservative estimates, it was predicted that each vertical farm could be between 5-23% the size of the data centre and produce enough food to feed between 14-61 adults their daily calorie needs, and between 13-58 people their daily fresh produce requirements, depending on the scenario applied. For a more accurate prediction, each vertical farm would have to be assessed on a case-by-case basis. However, there was not enough data available on Irish data centres to perform these calculations.