The current Coronavirus Disease 19 (COVID-19) pandemic, caused by the SARS-CoV-2 virus, is unprecedented in recent history and threatens the lives and livelihoods of billions worldwide. The rapid spread and lack of modern parallels have left governments, health agencies, and the public racing to understand how to best mitigate and ultimately suppress the pandemic, but we are still working to understand the strengths and weaknesses of various interventions at our disposal. Few issues have been as contentious as the public use of face masks to control the pandemic’s spread. There is ongoing debate about their effectiveness, but an increasing body of evidence suggests that masks could be a useful in preventing the spread of coronavirus, leading several governments and health agencies to review and revise their policies. Here, we review the theory and evidence behind use of masks. The theory behind masks is that they prevent the spread of viral particles by infected persons, and inhalation of viral particles by uninfected persons. Even assuming masks are not 100% effective in preventing infection, they may reduce severity of infection by reducing viral dosing. Laboratory studies suggest masks may be effective in stopping both exhalation and inhalation of viral particles. However, real-world studies provided limited evidence for the use of masks in controlling influenza transmission and highlight potential problems associated with their misuse, such as poor compliance or improper use. Evidence for efficacy of face masks against the first SARS virus, SARS-CoV-1, implies that they may be effective against the current outbreak of SARS-Cov-2 virus. This is important as mathematical modeling suggests that even small reductions of in transmission rates can make a large difference over time, potentially slowing the pace of viral pandemics and limiting their spread. Perhaps the strongest argument for the use of masks is that countries with early adoption of masks have tended to see flatter pandemic curves, even without strict nationwide lockdowns. There is little evidence that respirators are more effective than surgical masks, but this may be due to misuse or poor compliance. Studies suggest some non-medical masks perform on par with medical masks. Improvised masks are less effective than medical masks, but may provide better protection than nothing at all. While many governments now encourage the use of improvised face coverings, more will need to be known about material, design, and who needs to wear masks, and when, to ensure effectiveness. Proper use of masks will also be important; if masks are used improperly or infrequently they may provide limited protection. It is important that public health policy makers consider the debate and the potential of masks as part of multi-faceted coronavirus control strategies.

Beginning in 2012, our understanding of human papillomavirus (HPV) subcellular trafficking has undergone a drastic paradigm shift. Work from multiple laboratories has revealed that HPV has evolved a unique means to deliver its viral genome (vDNA) to the cell nucleus, relying on a myriad of host cell proteins and processes. The major breakthrough finding from these recent endeavors was the realization of L2-dependent utilization of cellular sorting factors for the retrograde transport of vDNA away from degradative endo/lysosomal compartments to the Golgi, prior to mitosis-dependent nuclear accumulation of L2/vDNA. An overview of current models of HPV entry, subcellular trafficking, and the role of L2 during initial infection is provided below, highlighting unresolved questions and gaps in knowledge.

The disruptive application of ChatGPT (GPT-3.5, GPT-4) to a variety of domains has become a topic of much discussion in the scientific community and society at large. Large Language Models (LLMs), e.g., BERT, Bard, Generative Pre-trained Transformers (GPTs), LLaMA, etc., have the ability to take instructions, or prompts, from users and generate answers and solutions based on very large volumes of text-based training data. This paper assesses the impact and potential impact of ChatGPT on the field of digital forensics, specifically looking at its latest pre-trained LLM, GPT-4. A series of experiments are conducted to assess its capability across several digital forensic use cases including artefact understanding, evidence searching, code generation, anomaly detection, incident response, and education. Across these topics, its strengths and risks are outlined and a number of general conclusions are drawn. Overall this paper concludes that while there are some potential low-risk applications of ChatGPT within digital forensics, many are either unsuitable at present, since the evidence would need to be uploaded to the service, or they require sufficient knowledge of the topic being asked of the tool to identify incorrect assumptions, inaccuracies, and mistakes. However, to an appropriately knowledgeable user, it could act as a useful supporting tool in some circumstances.

In this paper, we present sums and partial sums of Horadam sequences via generating functions which extends a recent result of Prodinger.

For the better part of a century researchers across disciplines have sought to explain the crystallography of the elemental transition metals: hexagonal close packed, body centered cubic, and face centered cubic in a form similar to that used to rationalize the structure of organic molecules and inorganic complexes. Pauling himself tried with limited success to address the origins of transition metal stability. These early investigators were handicapped, however, by incomplete knowledge regarding the structure of metallic charge density. Here we exploit modern approaches to charge analysis to first comprehensively describe transition metal charge density. Then, we use topological partitioning and quantum mechanically rigorous treatments of kinetic energy to account for the structure of the density as arising from the interactions between metallic tetrahedra. We argue that the crystallography of the early transition metals results from charge transfer from the so called “octahedral” to “tetrahedral holes” while the face centered cubic structure of the late transition metals is a consequence of antibonding interactions that increase octahedral hole kinetic energy.

In this paper, closed forms of the sum formulas $\sum_{k=0}^{n}x^{k}W_{k}^{3}$ and $\sum_{k=1}^{n}x^{k}W_{-k}^{3}$ for the cubes of generalized Fibonacci numbers are presented. As special cases, we give sum formulas of Fibonacci, Lucas, Pell, Pell-Lucas, Jacobsthal, Jacobsthal-Lucas numbers.

Ethiopian Airlines is a leading airline in the world. Its supply chain management is one of the most critical aspects in achieving its sustainability objectives. The present study aims to assess the sustainability practices and strategies of Ethiopian Airways in its supply chain, identifying areas for improvement and recommending strategies for enhancing sustainability. The study concentrates on pertinent sustainability concerns within the aviation sector while examining antecedent research on the sustainability of Ethiopian Airlines’ supply chain management strategies. The findings of the study reveal that there are several areas in need of improvement, including the implementation of waste reduction measures, the establishment of a recycling program, and the reduction of single-use plastic usage. It is suggested that promoting responsible tourism embodying sustainable practices is imperative, particularly within the airline context.

The excessive intake of sodium (Na) and insufficient intake of potassium (K) are major concerns to prevent hypertension. Using low-Na/K seasonings (reducing 25% of the NaCl and adding K salt) may improve the dietary Na/K ratio and help prevent hypertension. To devise an intervention study using low-Na/K seasonings at a company cafeteria, we calculated the Na and K contents of the meals served at the cafeteria and estimated changes in the intakes when suitable low-Na/K seasonings were used. We also considered using milk as a good source of K. We used an ingredient list of a company cafeteria and calculated Na and K contents in each dish. The average amounts of NaCl and K per use were 5.04 g and 718 mg, respectively. Seasonings contributed 70.9% of the NaCl. With the use of low-Na/K seasonings, an estimated reduction in NaCl of 0.8 g/day and an estimated increase in K of 308 mg/day was achieved. An additional serving (200 mL) of milk, NaCl was reduced by 0.57 g/day and K was increased by 610 mg/day, with an overall decrease in the dietary Na/K ratio from 3.20 to 2.40. The use of low-Na/K seasonings and dairy may improve the dietary Na/K ratio among cafeteria users and help prevent hypertension.

K-band radar waves have high penetration and low attenuation coefficients. However, the wavelength of this radar wave is relatively short; thus, designing and preparing both broadband and wide-angle radar wave absorbers in this band presents considerable challenges. In this study, a resin-based K-band radar wave absorber with a biomimetic lotus leaf structure was designed and formed by UV curing. Here, microscale lotus leaf papillae and antireflection structures were prepared using a DLP 3D printer, and the contact angle between the material and water droplets was increased from 56° to 130°. In addition, the influence of the geometric parameters of the lotus leaf antireflection structure on the electromagnetic absorption performance and mechanical strength was investigated. After simulation optimization, the maximum electromagnetic loss of the lotus leaf structure 3D printed sample was −32.3 dB, and the electromagnetic loss was below −10 dB in the 20.8–26.5 GHz frequency range. When the radar incidence angle was 60°, the maximum electromagnetic loss was still less than −10 dB. The designed lotus leaf structure has a higher mechanical energy absorption per unit volume (337.22 KJ/m3) and per unit mass (0.55 KJ/Kg) than commonly used honeycomb lightweight structures during the elastic deformation stage, and we expect that the designed structure can be used as an effective lightweight material for K-band radar stealth.

Sexual Violence (SV) can deeply impact victims' physical and psychosocial well-being. Yet many healthcare providers, including registered nurses (RNs), hesitate to screen patients due to a lack of confidence and knowledge. The SATELLITE Sexual Violence Assessment and Care Guide was developed to address this gap; however, the guide’s educational effectiveness remained untested. This pilot study aimed to assess the feasibility, acceptability, and efficacy of an education program based on the SATELLITE guide among RNs in clinical settings, using a pre- and post-test design. Results indicated that the education was not only feasible and acceptable, but also demonstrated the effects as desired with significant increases in RNs' knowledge and confidence in SV screening and care. The program's assessment tool was valid and reliable, and participant recruitment was feasible. Based on these findings, it is recommended that the SATELLITE education program be further tested with a larger RN sample and extended to other healthcare providers. Additionally, exploring different regions, cultural contexts, and healthcare settings would enhance understanding of the program's broader applicability and effectiveness.

Precision agriculture and open-source data repositories provide a plethora of field-specific ecological data about agroecosystems, but few mechanisms have been developed to turn that information into management recommendations for crop production. The On-Farm Precision Experiments (OFPE) framework is an agroecological model-based methodology to improve crop manager’s abilities to make field-scale agronomic input decisions. This work evaluates the use of field-specific experiments that employ open-source data and the data emanating from precision agriculture technologies to gain local knowledge of the spatial and temporal variability in agroeconomic performance at the sub-field scale. Quantification of the temporal variability in crop response to inputs (e.g., crop seeding rates, crop rotations, fertilizers, other soil amendments, pesticides, etc.) allows for estimation of the probability that a future management scenario will outcompete another, in terms of crop yield, crop quality, farmer net return, or environmental quality. The challenge is to integrate OFPE into applied management with minimal disruption of stakeholder practices while drawing on historic knowledge about the field and economic constraints. OFPE is the basis of a decision support system that includes a six-step cyclical process that harnesses precision agriculture technology to apply experiments and gather field-specific data, incorporates modern data management and analytical approaches, and generates management recommendations as probabilities of outcomes. The OFPE framework allows field managers to assess the tradeoffs in agronomic input management between the maximization of crop production, quality and profits from production while considering environmental effects.

Precision cancer medicine primarily aims to identify individual patient genomic variations and exploit vulnerabilities in cancer cells to select suitable patients for specific drugs. These genomic features are commonly determined by gene sequencing prior to therapy, to identify individuals who would be most responsive. This precision approach in cancer therapeutics remains a powerful tool that benefits a smaller pool of patients, sparing others from unnecessary treatments. A limitation of this approach is that proteins, not genes, are the ultimate effectors of biological functions, and therefore the targets of therapeutics. An additional dimension in precision medicine that considers an individual’s cytokine response to cancer therapeutics is proposed. Cytokine responses to therapy are multifactorial and vary among individuals. Thus, precision is dictated by the nature and magnitude of cytokine responses in the tumor microenvironment exposed to therapy. This review highlights cytokine responses as modules for precision medicine in cancer therapy, including potential challenges. For solid tumors, both detectability of cytokines in tissue fluids and their being amenable to routine sensitive analyses could address the difficulty of specimen collection for diagnosis and monitoring. Therefore, in precision cancer medicine, cytokines offer rational targets that can be utilized to enhance the efficacy of cancer therapy.

Human exposure to antimicrobial resistance (AMR) through food is now very imperfectly understood, creating a significant gap in the design of interventions. The interchange of AMR genes and the transfer of AMR bacteria from animals to humans through the food chain necessitate comprehensive methods to risk reduction. With a focus on AMR in bacterial species isolated from food products, foods (of both animal and non-animal origin), and ambient samples, the current meta-analysis gathered up-to-date information on the epidemiology of AMR in animal-source food chain. As a result, the combined prevalence of AMR across the various food sources was calculated. From the 18,784 food samples obtained as a result of selected publications, 7,676 (40.9%) samples were contaminated, including 4343 (56.6%) and 3363 (43.4%) samples from Taiwan and India, respectively. Meat (chicken, pork, and beef), fish and milk all have moderate to medium potential for AMR exposure to both Gram-positive and Gram-negative foodborne pathogens such S. aureus, Clostridium, E. coli, Salmonella, etc. Antibiotic resistance to β-lactam, fluoroquinolone, carbapenem etc, is present in the majority of food samples. The results of this study emphasize the persistent danger of antimicrobial residue in animal-derived foods in Taiwan, India, and other nations with comparable customs.

Fungi critically impact the health and function of global ecosystems and economies. In Canada, fungal researchers often work within silos defined by sub-discipline and institutional type, complicating the collaborations necessary to understand the impacts fungi have on the environment, economy, and plant and animal health. Here, we announce the establishment of the Canadian Fungal Research Network (CanFunNet, https://fungalresearch.ca) whose mission is to strengthen and promote fungal research in Canada by facilitating dialogue among scientists. We summarize the challenges and opportunities for Canadian fungal research that were discussed at CanFunNet’s inaugural meeting in 2019, and identify four priorities for our community: 1) increasing collaboration among scientists; 2) studying diversity in the context of ecological disturbance; 3) preserving culture collections in the absence of sustained funding; and 4) leveraging diverse expertise to attract trainees. We have gathered additional information to support our recommendations, including a survey identifying underrepresentation of fungal-related courses at Canadian universities, a list of Canadian fungaria and culture collections, and a case study of a human fungal pathogen outbreak. We anticipate that these discussions will help prioritize fungal research in Canada, and we welcome all researchers to join this nationwide effort to enhance knowledge dissemination and funding advocacy.

Background: Xenogenous bone has been proposed as an alternative to overcome the disadvantages of autogenous grafting. The aim of the present study was to study bone dynamics at inlay and onlay xenografts used for bone augmentation applying a ring technique. Methods: The bone at the lateral surface of the mandibular angle of 12 adult male New Zealand White rabbits was exposed bilaterally. The cortical layer received multiple perforations at one side of the mandible and a xenograft block of collagenated cancellous equine bone, 7 mm in diameter and 3 mm in width, was fixed on the prepared surface using an implant (onlay group). On the opposite side, a defect 7 mm in diameter and 3 mm in depth was prepared, the xenograft block was adapted to the defect and fixed with an implant (inlay group). Results: After ten weeks of healing, in the onlay grafts, new bone was mainly formed on the trabeculae surface, reaching in some specimens the most coronal regions of the block. In the inlay grafts, new bone was found arranged on the trabecular surfaces but also occupying the spaces among the trabeculae. The entrance of the defect was often found close at the top of the block by newly formed bone. A higher percentage of new bone was found in the inlay (19.0 ±9.3%) compared to the onlay (10.4 ±7.4%) groups (p=0.031). The mean gain in osseointegration at the implant in relation to the base of the original 3 mm deep defect was 0.95 ±1.05% at the onlay group and 0.78 ±0.71% at the inlay group (p=0.603). Conclusion: The inlay grafts exhibited a higher new bone percentage than the onlay grafts possibly due to the defect conformation that presented more sources for bone formation. The trabecular conformation and the composition of the grafts made possible the expression of the osteoconductive properties of the material used. This resulted, in several specimens, in growth of bone on the graft trabeculae toward the most superior regions in both groups, and in the closure of the coronal entrance of the defects in the inlay group.

Ewing sarcoma (EWS) is an aggressive pediatric malignancy of the bone and soft tissues in need of novel therapeutic options. To identify potential therapeutic targets, we focused on essential biological pathways that are upregulated by EWS-FLI1, the primary oncogenic driver of EWS, including mitotic proteins such as Aurora Kinase A (AURKA), Kinesin Family Member 15 (KIF15) and its binding partner, targeting protein for Xklp2 (TPX2). KIF15/TPX2 cooperates with KIF11, a key mitotic kinesin essential for mitotic spindle orientation. Given the lack of clinical grade KIF15/TPX2 inhibitors, we chose to target KIF11 (using SB-743921) in combination with AURKA (using VIC-1911), given phosphorylation of KIF15S1169 by Aurora A is required for its targeting to the spindle. In vitro, the drug combination demonstrated strong synergy (Bliss score ≥10) at nanomolar doses. Colony formation assay revealed significant reduction in plating efficiency (1-3%) and increased percent accumulation of cells in G2/M phase with the combination treatment (45-52%) upon cell-cycle analysis indicating mitotic arrest. In vivo studies in EWS xenograft mouse models showed significant tumor reduction and overall effectiveness: drug combination vs vehicle control (p≤0.01), SB-743921 (p≤0.01) and VIC-1911 (p≤0.05). Kaplan-Meier curves demonstrated superior overall survival with the combination compared to vehicle or monotherapy arms (p≤0.0001).

Non-Vitamin K Oral Anticoagulants (NOACs) have revolutionized anticoagulant therapy, offering improved safety and efficacy over traditional agents like warfarin. This review comprehensively examines the dual roles of NOACs—Apixaban, Rivaroxaban, Edoxaban, and Dabigatran—not only as anticoagulants but also as modulators of inflammation via Protease-Activated Receptor (PAR) signaling. We highlight the unique pharmacotherapeutic properties of each NOAC, supported by key clinical trials demonstrating their effectiveness in preventing thromboembolic events. Beyond their established anticoagulant roles, emerging research suggests that NOACs influence inflammation through PAR signaling pathways, implicating factors such as FXa and Thrombin in the modulation of inflammatory responses. This review synthesizes current evidence on the anti-inflammatory potential of NOACs, exploring their impact on inflammatory markers and conditions like atherosclerosis and diabetes. By delineating the mechanisms by which NOACs mediate anti-inflammatory effects, this work aims to expand their therapeutic utility, offering new perspectives for managing inflammatory diseases. Our findings underscore the broader clinical implications of NOACs, advocating for their consideration in therapeutic strategies aimed at addressing inflammation-related pathologies. This comprehensive synthesis not only enhances understanding of NOACs' multifaceted roles but also paves the way for future research and clinical applications in inflammation and cardiovascular health

In the paper, the authors generalize the notion "k-Mittag-Leffler function'', establish some integral transforms of the generalized k-Mittag-Leffler function, and derive several special and known conclusions in terms of the generalized Wright function and the generalized k-Wright function.

Probiotics are becoming more and more popular in the growing of fin and shellfish because these species are consumed worldwide and because different techniques are employed to maximize the productivity and efficiency of fin and shellfish. Probiotic Bacillus is one of the many types of probiotics that are used, but it stands out due to its superior qualities. For instance, because of its ability to sporulate, it can survive in harsh environments, produce antimicrobial substances, and is safe to feed to fish. The different species of Bacillus used in the farming of fin and shell fish were discussed in this review, along with the benefits of using Bacillus spp. as a good substitute in sustainable aquaculture to improve feed utilization, immune system response, stress adaptation, resistance to infectious diseases, tissue preservation integrity, and water quality. Additionally, we discussed the possible risks to safety that Bacillus poses when raising these significant species. For the purpose of future research and development regarding Bacillus application in aquaculture, a summary of the findings of recent studies about the advantages of applying Bacillus to enhance fin and shellfish aquatic animal culture has been provided.

Guided by the Conceptual Model of Implementation Research, we explored the acceptability, appropriateness, and feasibility of: 1) automated screening approaches utilizing existing health data to identify those who require subsequent diagnostic evaluation for familial hypercholesterolemia (FH) and 2) family communication methods including chatbots and direct contact to communicate information about inherited risk for FH. Focus groups were conducted with 22 individuals with FH (2 groups) and 20 clinicians (3 groups). These were recorded, transcribed, and analyzed using deductive (coded to implementation outcomes) and inductive (themes based on focus group discussions) methods. All stakeholders described these initiatives as: 1) acceptable and appropriate to identify individuals with FH and communicate risk with at-risk relatives; and 2) feasible to implement in current practice. Stakeholders cited current initiatives, outside of FH (e.g., pneumonia protocols, colon cancer and breast cancer screenings), that gave them confidence for successful implementation. Stakeholders described perceived obstacles, such as nonfamiliarity with FH, that could hinder implementation and potential solutions to improve systematic uptake of these initiatives. Automated health data screening, chatbots, and direct contact approaches may be useful for patients and clinicians to improve FH diagnosis and cascade screening.

This paper will explore analogs of groups formed by the transformations of two ropes as presented by Minh-Tam Quang Trinh.1 The two operations acting on these ropes are T and S, defined as twists and clockwise turns, respectively. These actions intertwine the ropes, creating tangles. T and S also have the ability to untangle the rope when used in certain combinations. In the two-rope case, these actions expressed as a group presentation were shown to be isomorphic to SL₂(Z). We explored the analog of these opera- tions, T and S, and conjectured the corresponding group to which they are isomorphic. Partial proofs for this conjecture are included and future work would include proving our conjecture as well as generalizing results to k ropes.

60\% of the global population is expected to be in cities by 2050. At the same time the climate is changing at an accelerated rate. In this short paper we discuss the conflation of these two phenomena and how it may change the cities of the future. We formulate this as an optimization problem that could help answer important questions such as where are they likely to be located? How are they to be powered? What would be their demand for mobility and how might this be met? How over or under ground might these cities be? This paper first looks at a historical paradigm of cities in the absence of the climate crisis and then proposes the new paradigm to look at cities of the future faced by the challenge of the climate change crisis.

The KcsA is a prokaryotic potassium-oriented channel, which is sourced from the Streptomyces lividans soil bacteria. From extensive studies that have been carried over the KcsA potassium channel, it has been proved that various factors enable the gating and shuttling of the potassium ions into and out of the cells. Some of the factors include the different concentration of protons in the inside and outside membrane. The other factor is the existence of the selectivity filter equipped in the exit of channel pore, which enables the movement of the K⁺ ions. Not only are potassium ions present in the channel but also sodium ions. Potassium and sodium ions are the ions that are essential in the conductivity of a cell because of their charge. An intuitive idea about why K⁺ ions are at least 10,000 times more permeant than Na⁺ ions is presented in various entities. The hypothesis is that the selectivity ratio is probably related to the successive entry of Na⁺ ions, based on the premise that the ratio seems to be relevant to unpredictable quantities caused by Brownian corrosion of ions.

Motivated by Autonomous vehicle idea and driving safety issues, driver assistance system such as Active braking, Cruise Control, Lane departure warning lane keeping and etc. has become a very active research area. However, this paper presents the performance and robustness analysis of a model predictive control and proportional integral derivative control for lane keeping maneuvers of an autonomous vehicle using computer vision simulation studies. A simulation study was carried out where a vehicle model based on single tracked bicycle model was developed in MATLAB/SIMULINK environment together with a vision dynamic system. Both PID controller and MPC were simulated to maintain the desired reference trajectory of the vehicle by controlling steering angle. Further performance and robustness analysis were carried out and the simulation results show that the proposed control system for the PID control achieved its objective even though it was less robust in maintaining its performance under various conditions like vehicle load change, different longitudinal speed and different cornering stiffness. While in the case of MPC the optimizer made sure that the predicted future trajectory of the vehicle output tracks the desired reference trajectory and was more robust in maintaining its performance under same conditions as in PID.

Clothing consumers mostly purchase, use, and dispose of clothing products in a linear business model. This approach pollutes the environment and causes economic and social crises in the ecosystems. This study evaluates the amount of generated postconsumer clothing waste (PCCW) and proposes recycling as a sustainable waste management approach. Data were collected to understand disposal behavior of consumers with 474 respondents selected from households in Bahir Dar city. The findings show that all the determinant factors on the PCCW generation level except religion were significant. The most frequently disposed type of clothing waste is jeans-trouser (51%). The CEBM was used to develop alternative products from a jeans-based clothing waste. The jean's fiber and fabric-reinforced composite materials were developed using unsaturated polyester resin as a sustainable way of PCCW management strategy. The shredded form fiber-reinforced composite was found to have a smoother surface than that of the chopped or cut fabric-reinforced composite. The product was characterized by physical and mechanical properties. The study can be further extended to the scope of the entire consumers in Ethiopia and alternative recyclable products can be studied.

Abstract The aim of the present review is to discuss the roles of vitamin K and vitamin K-dependent proteins, and the combined action of the vitamins K and D, for maintenance of bone health. The most relevant vitamin K-dependent proteins in this respect are osteocalcin and matrix Gla-protein (MGP). When carboxylated these proteins appear to have the ability to chelate and import calcium from the blood to the bone, thereby reducing the risk of osteoporosis. Carboxylated osteocalcin appears to contribute directly to bone quality and strength. Adequate vitamin K status is required for carboxylation of MGP and osteocalcin. In addition, vitamin K acts on bone metabolism by other mechanism, such as a ligand for the nuclear steroid and xenobiotic receptor (SXR). In this narrative review, we examine the evidence for increased bone mineralization through dietary adequacy of vitamin K (phylloquinone or menaquinone). Summarizing the evidence for a synergistic effect of vitamin K and vitamin D3 we find that an adequate supply of vitamin K on top of an optimal vitamin D status seems to add to the benefit for maintaining bone health. More research related to synergism and possible mechanisms of vitamins D3 and K interaction in bone health is needed.

Antimicrobial resistance (AMR) is a growing public health concern worldwide, and it poses a significant threat to human, animal, and environmental health. The overuse and misuse of antibiotics have contributed significantly to the emergence and spread of antimicrobial resistance, which may lead to significant economic consequences like reduced productivity and increased healthcare costs. Nanotechnology offers a promising platform for addressing this challenge. Nanoparticles have unique properties that make them highly effective in combating bacterial infections by inhibiting the growth and survival of multidrug-resistant bacteria in three areas of health: human, animal, and environmental. To conduct an economic evaluation of surveillance in this context, it is crucial to have a comprehension of the connections to be addressed by several nations by implementing national action policies based on the One Health strategy. This review provides an overview of the progress made thus far and presents potential future directions to optimize the impact of nanobiotics on AMR.

Recent pollinator declines have focused efforts on their conservation which require clear estimates of pollination value to agriculture. Our socio-economic producer surveys and agronomic field research data were used to present a new way of estimating ecosystem service value of native pollinators. Using two regionally important U.S.A. crops, Maine wild blueberry and Massachusetts cranberry as models, we present perceived values of native bee pollinators from both consumer and producers. Wild blueberry’s Replacement Cost (RC) was greater than Attributable Net Income (ANI), since greater rented honey bee stocking densities are required. Attributable Net Income for native bees were similar for wild blueberry ($613/ha) and cranberry ($689/ha). Marginal Net Farm Income (MNFI) from incrementally adding more hives per ha was greater from stocking a third/fourth hive per ha for cranberry ($6,206) than stocking a ninth/tenth hive per ha for wild blueberry ($556), given greater responsiveness of yield, revenue, and profit to using rented honey bee hives in cranberry compared to wild blueberry. Both crops’ producers were only willing to annually invest $140–188/ha in native pollination enhancements on their farms, justifying government support. Consumers are willing to pay ~6.7 times more to support native bees than producers, supporting market-based support for invertebrate conservation.

As sustainability gains significance within Higher Education Institutions (HEIs) worldwide, the University of British Columbia (UBC) stands as one of the global champions of sustainability. In 2019, Times Higher Education ranked UBC as number one in the world for taking urgent action to combat climate change and its impacts and ranked one in Canada for making cities inclusive, safe, resilient, and sustainable. Over the years, UBC students have been instrumental to sustainability on the UBC campus by advocating for divestment, climate justice, and other sustainability commitments and projects in the university. Hence, this qualitative study examines students’ engagement with or their perception of the university’s sustainability programs and image. The study found that students acknowledged and commended the university’s sustainability efforts in teaching, research, providing sustainability-related opportunities for students, and in sustainability operations. However, students also addressed hesitation on the part of university administration in championing climate justice and bolder climate action. The conclusion is that continued support and engagement with students are critical for UBC to achieve its climate action plans and sustainability goals in general. The study contributes to the ongoing discourse on the influential role of young people and the youth climate movement in catalyzing ambitious global climate action at all levels.

:Peat substrate is made from peat from drained peatlands, which is a limited resource. A realistic estimate is that 50% of the world’s wetlands have been lost. Peat is used in horticulture, especially for the cultivation of vegetables in greenhouses. The consequences of peatland exploitation are an in-crease in the greenhouse effect and a decrease in carbon stocks. Wood fiber can be used as an al-ternative to peat. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the growing container. This study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) variety “Dirigent H” developed in the Netherlands, were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) con-ventional fertilization (CF); (2) N13; (3) N23; (4) N30. The experiment was carried out in three repli-cations. As the amount of wood fiber increased, the humidity and pH of the growing medium in-creased. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in 50/50 and 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat sub-strate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

: Greenhouse plants are usually grown in containers filled with growing media. Peat is the main component of the growing media used in greenhouses. However, peat substrate is made from peat from drained peatlands, which is a limited resource. Wood fiber can be an alternative to use as a growing media for controlled-climate crops. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the vegetative container. Therefore, this study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) conventional fertilization (CF); (2) N13; (3) N23; (4) N30. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in WF/PS 50/50 and WF/PS 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat substrate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

The $k$-means problem is to compute a set of $k$ centers (points) that minimizes the sum of squared distances to a given set of $n$ points in a metric space. Arguably, the most common algorithm to solve it is $k$-means++ which is easy to implement, and provides a provably small approximation factor in time that is linear in $n$. We generalize $k$-means++ to support: (i) non-metric spaces and any pseudo-distance function. In particular, it supports M-estimators functions that handle outliers, e.g. where the distance $\mathrm{dist}(p,x)$ between a pair of points is replaced by $\min {\mathrm{dist}(p,x),1}$. (ii) $k$-means clustering with $m\geq 1$ outliers, i.e., where the $m$ farthest points from the $k$ centers are excluded from the total sum of distances. This is the first algorithm whose running time is linear in $n$ and polynomial in $k$ and $m$.

Background: The conformation of the recipient site for an inlay graft presents an increased contact with the parent bone compared to the onlay graft. This might favor bone growth within the inlay compared to the onlay grafts. Hence, the objective of this study was to compare bone incorporation and remodeling process of xenogeneic en bloc grafts, placed using two bone grafting techniques, i.e., onlay vs. inlay. Methods: In this prospective, randomized, split-mouth study (test and control sides in the same animal), two bone grafting techniques were comparatively evaluated on the lateral aspect of the rabbit mandibles. One side was prepared with perforations (onlay site), whereas the other side was prepared with trephines and drills to obtain a wide (7 mm) standardized recipient site (inlay site). A xenogeneic bone block was fixed in the center with a titanium screw in both sides of the mandible and covered with a collagen membrane. Two healing periods were applied in the study: 2 and 10 weeks of healing. Results: after 2 weeks of healing, the mean percentage of new bone was 10.4% and 23.3% at the onlay and inlay grafts, respectively (p=0.022). After 10 weeks of healing, new bone increased to 13.2% and 25.4%, respectively (p=0.080). In this period of healing, the inlay grafts presented new bone percentage >20% in all regions examined while the onlay graft presented a lower percentage in the most external regions of the graft. Conclusion: The percentage of new bone increased faster and was higher in the inlay compared to the onlay grafts. The composition of the grafts allowed new bone to reach the most peripheral regions in both graft groups, even though it was higher in the inlay group. A marginal closure of the defects by newly formed bone was observed in the inlay group.

In the year in which the world "stopped" due to the pandemic, many people didn't have that option and had to keep moving as the only alternative to survive. One of the main destinations in South America, during the quarantine measures established around the world, was Brazil, especially because of the crisis Venezuela went through in the second half of the 2010s. Throughout the research, we observed measures that were applied by the Brazilian government on the grounds of public health issues or cases of health risks related to COVID-19. An analysis of the first measures published by the Brazilian government reveals an effort to securitize borders, which at the same time restricted the government's responsibility to fulfil its role of protecting migrants in need.

Biochemical compositions of black carpenter ants (Camponotus pennsylvanicus) were analyzed using standard methods. The proximate composition (%) were as follows: crude protein (22.50), crude fibre (1.46), carbohydrate by difference (30.86) and energy (35.4Kcal). The predominant mineral was potassium and nickel was the least. The antinutritional properties (mgkg^-1) ranged as follows: Oxalate (1.35), phytate (62.79), and tannins (0.72). The results suggested that the ant may be a good source of nutrition.

In the quest to develop a more effective and representative electoral system that offers a higher global satisfaction while also resisting strategic voting, this paper introduces the Bipartisan/Range method. This electoral system operates in two separate rounds: a first round where voters rank candidates, and if no Condorcet winner emerges, a second round where voters score candidates within a small head set known as the bipartisan set. The proposed method takes inspiration from randomized Condorcet voting system, probably the most strategy-resistant Condorcet methods, but eliminates the non-determinism while improving efficiency in the case of paradoxes. By introducing an unpredictable second round spaced in time and prohibiting predictive surveys, voters face difficulties in anticipating paradoxes, and insincere votes carry inherent risks. Furthermore, the Bipartisan set's limited size mitigates the range voting problem of exaggerated votes. Thus, the method has the potential to be both efficient in reflecting voters' preferences and resistant to strategic voting, exceeding expectations from Arrow's theorem. The method's versatility allows for extensions to multiple candidates, enhancing its applicability across various electoral contexts. Additionally, we have developed BipartiVox, an online platform specifically designed to conduct elections using the Bipartisan/Range method, making it accessible to a wider audience. In conclusion, the Bipartisan/Range method represents a substantial contribution to the field of voting systems, providing a practical, strategy-resistant, and efficient alternative that aligns closely with genuine voter preferences.

Poultry eggs are a critical source of protein, vitamins, and minerals for people worldwide; facing the current global egg shortage is a significant concern. The shortage results from various factors, including avian flu outbreaks, changes in consumer demand, and supply chain disruptions caused by the COVID-19 pandemic. The economic crisis caused by the pandemic has also impacted the availability and affordability of eggs, particularly in low-income countries. The global egg shortage has implications for public health, particularly for vulnerable populations who rely on eggs for essential nutrients. One Health, an approach that recognizes the interconnectedness of human, animal, and environmental health, provides a useful framework for understanding and addressing the egg shortage. One Health approaches to the egg shortage involve collaboration between agriculture and environmental sectors to address the root causes of the lack and ensure the sustainable production and distribution of eggs. Addressing the global egg shortage requires a multifaceted approach considering the complex social, economic, and environmental factors. One Health perspectives offer a way to understand and address the interconnected factors contributing to the shortage to ensure access to affordable, nutritious eggs for all in a healthy way

Sudden cardiac arrest (SAC) is a leading cause of mortality. In recent years, though, many lives have been saved through the use of defibrillators by random bystanders. As a result, defibrillators have been popping up in various locations. In this work we propose a state mandate demanding the presence of a defibrillator at every pharmacy store and argue that it could greatly enhance and augment the impact of the defibrillator network. We support our claim via detailed calculations of the immediate (a defibrillator readily available) and partial (a defibrillator available at a reasonable distance) population coverage achievable by the implementation of our proposal, taking the Argolis area in Peloponnese Greece as a case study. Our findings indicate that, in addition to other benefits, the use of pharmacies to establish a defibrillator network could bring an eight-fold increase in the immediate population coverage of defibrillators and would provide immediate / partial access to a defibrillator to 18 / 24 incidents of SCA per year that would otherwise lead to death, potentially leading to the saving of numerous lives. Alternative scenaria are also discussed.

Recent data suggest that K-Ras4B (hereafter K-Ras) can drive cancer cell stemness via calmodulin (CaM)-dependent, non-canonical Wnt-signalling. Here we examined whether another Ca2+-binding protein, the CaM-related centrin1, binds to K-Ras and could mediate some K-Ras functions that were previously ascribed to CaM. While CaM and centrin1 appear to distinguish between peptides that were derived from their classical targets, they both bind to K-Ras in cells. Cellular BRET-data suggest that CaM engages more with K-Ras than centrin1 and that the interaction with the C-terminal membrane anchor of K-Ras is sufficient for this. Surprisingly, binding of neither K-Ras nor its membrane anchor alone to CaM or centrin1 is sensitive to inhibition of prenylation. In support of an involvement of the G-domain of K-Ras in cellular complexes with these Ca2+-binding proteins, we find that oncogenic K-RasG12V displays increased engagement with both CaM and centrin1. This is abrogated by addition of the D38A effector-site mutation, suggesting that K-RasG12V is held together with CaM or centrin1 in complexes with effectors. When treated with CaM-inhibitors the BRET-interaction of K-RasG12V with centrin1 was also disrupted in the low micromolar range, comparable to that with CaM. While CaM predominates in regulating functional membrane anchorage of K-Ras, it has a very similar co-distribution with centrin1 on mitotic organelles. Given these results, a significant overlap of the CaM- and centrin1-dependent functions of K-Ras is suggested.

Background and objectives: Chronic Kidney Disease and Mineral Bone Disorders (CKD-MBD) are frequently associated with an increased risk of both Vascular Calcifications (VCs) and bone fractures (BFs). The complex pathogenesis of VCs and BFs involves various factors such as calcium overload, phosphate imbalance, and secondary hyperparathyroidism. Key players, such as the vitamin K-dependent proteins (VKDPs) matrix Gla protein (MGP) and osteocalcin (BGP), have pivotal roles both for VCs and BFs. The Vitamin K Italian (VIKI) dialysis study, highlighted that hemodialysis patients treated with calcimimetics had higher levels of total BGP and MGP as compared to those untreated, suggesting a potential protective effect of these drugs on BFs and VCs, beyond the beneficial effect to reduce PTH levels. Methods: ETERNITY-ITA is a multi-center, comparative effectiveness, observational, longitudinal study that will enroll 160 hemodialysis patients (80 patients treated with Etelcalcetide and 80 age and sex-matched patients treated with Calcitriol or vitamin D analogs). Nephrologists will tailor the target dose of Etelcalcetide on individual level to achieve the KDIGO PTH target. In the Etelcalcetide-treated group, the addition of calcitriol will be allowed when required by clinical practice (for correction of hypocalcemia). Conclusion: The study will evaluate the real-world effect of Etelcalcetide on VKDP levels, such as BGP and MGP, at 3, 9, and 18 months from baseline. The resulting preservation of vascular and bone health will be assessed for the first time by examining aortic and iliac artery calcifications and vertebral fractures, respectively. Keywords: bone fractures; etecalcetide; hemodialysis; vascular calcification; vitamin K

Nearest-neighbour clustering is a simple yet powerful machine learning algorithm that finds natural application in the decoding of signals in classical optical-fibre communication systems. Quantum k-means clustering promises a speed-up over the classical k-means algorithm; however, it has been shown to currently not provide this speed-up for decoding optical-fibre signals due to the embedding of classical data, which introduces inaccuracies and slowdowns. Although still not achieving an exponential speed-up for NISQ implementations, this work proposes the generalised inverse stereographic projection as an improved embedding into the Bloch sphere for quantum distance estimation in k-nearest-neighbour clustering, which allows us to get closer to the classical performance. We also use the generalised inverse stereographic projection to develop an analogous classical clustering algorithm and benchmark its accuracy, runtime and convergence for decoding real-world experimental optical-fibre communication data. This proposed `quantum-inspired' algorithm provides an improvement in both the accuracy and convergence rate with respect to the k-means algorithm. Hence, this work presents two main contributions. Firstly, we propose the general inverse stereographic projection into the Bloch sphere as a better embedding for quantum machine learning algorithms; here, we use the problem of clustering quadrature amplitude modulated optical-fibre signals as an example. Secondly, as a purely classical contribution inspired by the first contribution, we propose and benchmark the use of the general inverse stereographic projection and spherical centroid for clustering optical-fibre signals, showing that optimizing the radius yields a consistent improvement in accuracy and convergence rate.

Vitamin K occupies a unique and often obscured place among its fellow fat-soluble vitamins. Evidence is mounting however, that vitamin K (VK) may play an important role in the visual system apart from the hepatic carboxylation of hemostatic related proteins. However, to our knowledge, no review covering the topic has appeared in the medical literature. Recent studies have confirmed that matrix Gla protein (MGP), a vitamin K-dependent protein (VKDP), is essential for the regulation of intraocular pressure in the mouse. The PREDIMED (Prevención con Dieta Mediterránea) study, a randomized trial involving 5860 adults at risk for cardiovascular disease, demonstrated a 29% reduction in the risk of cataract surgery in participants with the highest tertile of dietary vitamin K1 (PK) intake compared with the lowest tertile. However, the specific requirements of the eye and visual system (EVS) for VK, and what might constitute an optimized VK status, is currently unknown and largely unexplored. It is the intention therefore of this narrative review to provide an introduction concerning VK and the visual system, review ocular VK biology, and to provide some historical context to recent discoveries. Potential opportunities and gaps in current research efforts will be touched upon, in the hope of raising awareness, and encouraging continued VK related investigations in this important and highly specialized sensory system.

Clustering, or otherwise known as cluster analysis, is a learning problem that takes place without any human supervision. This technique has often been utilized, much efficiently, in data analysis, and serves for observing and identifying interesting, useful, or desired patterns in the said data. The clustering technique functions by performing a structured division of the data involved, in similar objects based on the characteristics that it identifies. This process results in the formation of groups, and each group that is formed, is called a cluster. A single said cluster consists of objects from the data, that have similarities among other objects found in the same cluster, and resemble differences when compared to objects identified from the data that now exist in other clusters. The process of clustering is very significant in various aspects of data analysis, as it determines and presents the intrinsic grouping of objects present in the data, based on their attributes, in a batch of unlabeled raw data. A textbook or otherwise said, good criteria, does not exist in this method of cluster analysis. That is because this process is so different and so customizable for every user, that needs it in his/her various and different needs. There is no outright best clustering algorithm, as it massively depends on the user’s scenario and needs. This paper is intended to compare and study two different clustering algorithms. The algorithms under investigation are k-mean and mean shift. These algorithms are compared according to the following factors: time complexity, training, prediction performance and accuracy of the clustering algorithms.

Sugarcane (Saccharum spp.) is a crop of great industrial and alimentary importance, essential for the production of numerous products. Given its significance, genetic improvement programs exist that involve a rigorous study process, from material selection to the development of new varieties, requiring at least seven selection phases. This study modeled the growth curve of the sucrose percentage (SP) in 33 hybrids and six control varieties (MEX 69-290, ITV 92-1424, CP 72-2086, COLMEX 94-8, COLMEX 95-27, RB 85-5113) during the plant and ratoon periods in the experimental fields of the Melchor Ocampo Sugar Mill, Jalisco, Mexico. For clustering the materials, k-means, k-medoids, and Density-based spatial clustering of applications with noise (DBSCAN) algorithms were used, considering four maturity types among the control varieties. The DBSCAN algorithm proved to be the most effective, as the means between groups were not statistically equal. The hybrids identified as candidates for subsequent phases due to their high SP were COSTA JAL, ATEMEX 99-48, ATEMEX 99-1, ATEMEX 99-61, MEX 70-486, MEX 80-1521, ITSAMEX 07-44814, ITSAMEX 06-6395, and ITSAMEX 07-1903. These results are crucial for improving the productivity and sustainability of the crop, with significant implications for the sugar industry.

This study explores the intricacies of supplier relationships and inventory optimization within high-technology industries, offering a comprehensive analysis of the strategic imperatives and operational challenges faced by firms in these sectors. By adopting a qualitative research methodology involving semi-structured interviews with supply chain professionals and documentary analysis, the study provides in-depth insights into the evolving dynamics of supply chain management. Findings reveal a marked shift towards collaborative and strategic supplier relationships, characterized by trust, transparency, and joint innovation initiatives. These partnerships are essential for enhancing operational efficiency, driving product development, and navigating market uncertainties. Additionally, the research underscores the critical role of advanced technologies, such as artificial intelligence and the Internet of Things, in optimizing inventory levels and improving supply chain visibility. The integration of these technologies facilitates precise demand forecasting and proactive inventory management, thereby reducing costs and enhancing service levels. However, the study also highlights significant challenges, including geopolitical uncertainties, supply chain disruptions, and cultural barriers, which necessitate robust risk management strategies and adaptive supply chain practices. Strategic implications for organizational leaders and policymakers include the need to invest in supplier development, embrace digital transformation, and enhance risk management frameworks to build resilient and agile supply chains. This study contributes valuable insights into the complex interplay between supplier relationships, inventory optimization, and technological integration in high-technology industries, offering actionable recommendations for practitioners and researchers seeking to drive innovation and maintain competitiveness in a dynamic global marketplace.

This qualitative research explores the intricate relationship between cultural influences on supply chain practices and their implications for marketing strategies. Cultural dimensions such as individualism versus collectivism, uncertainty avoidance, and contextuality significantly shape decision-making processes, risk management strategies, and relationship dynamics within global supply chains. Through semi-structured interviews with supply chain managers, marketing executives, and cultural experts across diverse industries and regions, this study investigates how cultural values impact supply chain operations and consumer engagement strategies. Key findings highlight that collectivist cultures prioritize consensus-building and long-term relationships, fostering trust and collaboration among supply chain partners. In contrast, individualist cultures emphasize efficiency and accountability but may face challenges in relationship building. Risk management practices vary with cultural orientations towards uncertainty, influencing the adoption of structured versus flexible approaches to mitigate disruptions. In terms of marketing implications, the study underscores the importance of cultural sensitivity in crafting effective strategies. High-context cultures require marketing messages that resonate emotionally through implicit communication and cultural symbolism, while low-context cultures prefer clear, direct messaging focusing on product benefits. The study concludes by advocating for cultural competence as a strategic imperative for global businesses, enabling them to leverage cultural diversity for innovation and competitive advantage. It emphasizes the need for continuous adaptation to cultural nuances and market dynamics to foster inclusive collaboration and achieve sustainable growth in a globalized economy.

In the particular configuration of the scalar field K-essence in the Wheeler-DeWitt quantum equation, for some age in the Bianchi type I anisotropic cosmological model, a fractional differential equation for the scalar field arises naturally. The order of the fractional differential equation is $\beta=\frac{2\alpha}{2\alpha - 1}$. This fractional equation belongs to different intervals, depending on the value of the barotropic parameter; when $\omega_{X} \in [0,1]$, the order belongs to the interval $1\leq \beta \leq 2$, and when $\omega_{X}\in[-1,0)$, the order belongs to the interval $0<\beta \leq 1$. In the quantum scheme, we introduce the factor ordering problem in the variables $(\Omega,\phi)$ and its corresponding momenta $(\Pi_\Omega, \Pi_\phi)$, obtaining a linear fractional differential equation with variable coefficients in the scalar field equation, then the solution is found using a fractional power series expansion. The corresponding quantum solutions are also given. We found the classical solution in the usual gauge N obtained in the Hamiltonian formalism and without a gauge. In the last case, the general solution is presented in a transformed time $T(\tau)$, however in the dust era we found a closed solution in the gauge time $\tau$.

The main objective of this paper is to introduce k-fractional derivative operator by using the definition of k-beta function. We establish some results related to the newly defined fractional operator such as Mellin transform and relations to k-hypergeometric and k-Appell's functions. Also, we investigate the k-fractional derivative of k-Mittag-Leffler and Wright hypergeometric functions.

The paper is dedicated to studying the influence of annealing temperature on the chemical, structural and electrophysical properties of low-k films made from porous organosilicate glasses containing terminal methyl groups. The films were deposited using centrifugation, followed by drying at 200 °C and annealing at temperatures ranging from 350 °C to 900 °C. Changes in refractive index, porosity, pore size, chemical composition, and electrical properties as a function of annealing temperature are evaluated. The results of JV measurements indicate that the methyl-modified film, which was annealed at 450 °С, demonstrates minimal leakage currents. This phenomenon can be explained by the almost complete removal of surfactant residues and non-condensed silanols, as well as the minimal thermal degradation of methyl groups. The results of the study on leakage current models in methyl-modified films, obtained at various annealing temperatures, lead us to conclude that the predominant mechanism of charge carrier transfer is Poole–Frenkel emission.

Along with the Coronavirus pandemic, another crisis has manifested itself in the form of mass fear and panic phenomena, fuelled by incomplete and often inaccurate information. There is therefore a tremendous need to address and better understand COVID-19's informational crisis and gauge public sentiment, so that appropriate messaging and policy decisions can be implemented. In this research article, we identify public sentiment associated with the pandemic using Coronavirus specific Tweets and R statistical software, along with its sentiment analysis packages. We demonstrate insights into the progress of fear-sentiment over time as COVID-19 approached peak levels in the United States, using descriptive textual analytics supported by necessary textual data visualizations. Furthermore, we provide a methodological overview of two essential machine learning classification methods, in the context of textual analytics, and compare their effectiveness in classifying Coronavirus Tweets of varying lengths. We observe a strong classification accuracy of 91% for short Tweets, with the Naive Bayes method. We also observe that the logistic regression classification method provides a reasonable accuracy of 74% with shorter Tweets, and both methods showed relatively weaker performance for longer Tweets. This research provides insights into Coronavirus fear sentiment progression, and outlines associated methods, implications, limitations and opportunities.

The integration of supply chain analytics and Customer Relationship Management (CRM) systems represents a critical strategy for organizations seeking to enhance operational efficiency and customer-centricity in today's competitive business environment. This qualitative study investigates the motivations, strategies, challenges, and outcomes associated with integrating supply chain analytics with CRM systems across diverse industries. Motivations for integration include gaining a unified view of customer data, improving decision-making capabilities, enhancing operational efficiency, and ensuring strategic alignment across organizational functions. Strategies employed by organizations include cross-functional collaboration, investment in scalable technology platforms, and leadership commitment to drive successful integration initiatives. Despite the potential benefits, the integration process presents challenges such as data integration complexities, technical interoperability issues, and organizational resistance to change. Addressing these challenges requires robust technological solutions, effective change management strategies, and a proactive approach to data governance and security. The study identifies significant outcomes from integration efforts, including improved operational efficiency through streamlined processes and optimized resource allocation, enhanced customer insights leading to personalized experiences, and strengthened strategic decision-making supported by real-time analytics.

Digital transformation is revolutionizing supply chain management, profoundly influencing marketing effectiveness across industries. This qualitative study explores the impact of digital transformation on supply chains and its implications for marketing strategies. Through in-depth interviews, case studies, and document analysis, the research elucidates how digital technologies such as IoT, blockchain, AI, and advanced analytics are reshaping supply chain dynamics. Key findings highlight enhanced supply chain visibility, improved decision-making capabilities, and strengthened collaboration among supply chain partners. These technological advancements empower organizations to optimize inventory management, anticipate market trends, and deliver personalized customer experiences, thereby enhancing operational efficiency and customer satisfaction. Furthermore, the study underscores the role of digital transformation in promoting sustainability and ethical practices within supply chains. Technologies like blockchain facilitate transparent and traceable supply chains, supporting initiatives for responsible sourcing and environmental stewardship. Despite the transformative benefits, the study identifies challenges including significant investment requirements, integration complexities, and data security concerns. Strategic approaches to technology adoption, robust cybersecurity measures, and employee training are essential for overcoming these challenges and maximizing the benefits of digital transformation. Overall, this study contributes to understanding how digital transformation drives innovation in supply chain management and enhances marketing effectiveness. By embracing digital technologies and aligning supply chain strategies with marketing objectives, organizations can navigate competitive landscapes, meet evolving consumer expectations, and achieve sustainable growth in the digital era.

This qualitative study explores consumer responses to sustainable supply chains and green marketing strategies, aiming to uncover insights into consumer behavior, perceptions, and attitudes towards sustainability in the marketplace. Through semi-structured interviews and focus group discussions with 30 participants, the study examines key factors influencing consumer trust in green marketing claims, barriers to adopting sustainable products, generational differences in attitudes towards sustainability, and the impact of social media on consumer perceptions. Findings reveal that consumers value transparency and credibility in green claims, preferring products certified by trusted third parties and companies that demonstrate transparent supply chain practices. Higher pricing, concerns about product effectiveness, and limited availability emerged as significant barriers to consumer adoption of sustainable products, highlighting the need for cost competitiveness and increased market accessibility. Generational cohorts, particularly Millennials and Generation Z, exhibit strong inclinations towards sustainability-driven behaviors, shaping market trends towards ethical consumption practices. Social media plays a pivotal role in influencing consumer perceptions, disseminating information about sustainability, and fostering engagement with environmental issues. The study underscores the importance of clear communication, consumer education, and supportive regulatory frameworks in promoting sustainable consumption behaviors. Practical implications include recommendations for businesses to enhance transparency, innovate sustainable products, align with consumer values, leverage social media platforms, and advocate for regulatory measures that uphold environmental standards. By addressing these insights, businesses and policymakers can effectively meet consumer expectations and contribute to sustainable development goals in the global marketplace.

This qualitative study explores consumer perceptions of supply chain sustainability and its impact on buying decisions. Through in-depth interviews and focus groups, the research investigates the multifaceted factors influencing consumer behaviors towards sustainable products. Findings reveal that environmental impact, social responsibility, transparency, economic considerations, and cultural influences are pivotal in shaping consumer attitudes. While consumers express strong motivations to support sustainability, practical barriers such as higher costs and limited availability often hinder consistent adoption of sustainable practices. Effective communication strategies, including transparency reports and sustainability certifications, emerge as crucial in bridging the gap between consumer intentions and actions. The study underscores the importance of aligning corporate sustainability initiatives with consumer expectations to build trust and foster sustainable consumption patterns. Insights suggest a need for targeted interventions and policy measures to address barriers and promote broader adoption of sustainable behaviors. By understanding and responding to consumer concerns, businesses can enhance their sustainability strategies and contribute to a more environmentally and socially responsible marketplace.

This study explores the dynamic interplay between supply chain integration and marketing strategies in achieving customer satisfaction. Through a qualitative approach involving semi-structured interviews with supply chain and marketing professionals, the research delves into how these traditionally distinct functions can be aligned to enhance operational efficiency and deliver superior customer experiences. Findings reveal that strategic alignment between supply chain management (SCM) and marketing fosters better coordination of product availability and service delivery, thereby meeting customer expectations consistently and enhancing brand loyalty. Information sharing and technological integration emerge as critical enablers, facilitating real-time data exchange and collaborative decision-making. The study also identifies challenges such as organizational silos, cultural resistance, and technological constraints that impede seamless integration, highlighting the need for proactive strategies to foster cross-functional collaboration. Additionally, the evolving roles of sustainability and customer-centricity are emphasized as key drivers for differentiating brands and achieving competitive advantage. By integrating sustainable practices and adopting a customer-centric approach, organizations can build stronger customer relationships and enhance their market position. The research underscores the importance of leadership support, investment in technology, and a collaborative organizational culture in overcoming integration barriers. The study’s findings provide actionable insights for organizations aiming to optimize their SCM and marketing strategies, drive innovation, and sustain growth in an increasingly complex and competitive business environment. This research contributes to the growing body of knowledge on supply chain and marketing integration, offering practical recommendations for achieving customer satisfaction and long-term success.

Consumer trust in supply chain certifications plays a pivotal role in shaping contemporary consumer behavior and marketing effectiveness. This qualitative research investigates consumer perceptions of supply chain certifications and their impact on purchasing decisions and brand loyalty. Through semi-structured interviews and focus group discussions with 30 participants, the study explores themes such as credibility, transparency, perceived value, and the influence of certifications on consumer trust. Findings reveal that consumers value certifications that signal ethical sourcing practices and sustainability commitments, viewing them as assurances of product quality and social responsibility. Credibility and transparency in certification processes emerged as critical factors influencing consumer trust, while perceived benefits such as environmental sustainability and fair labor practices positively influenced purchase intentions. Moreover, certifications were found to enhance brand loyalty by aligning with consumers' ethical values and beliefs. However, the study identifies challenges including high certification costs, complexity in compliance, and consumer skepticism, which hinder broader adoption and effectiveness of certifications. The implications of these findings suggest that businesses can enhance consumer trust and market competitiveness by investing in rigorous certification standards, clear communication strategies, and sustainable practices. Addressing barriers through improved transparency and consumer education is crucial for maximizing the impact of certifications on ethical consumption. Future research directions include longitudinal studies on certification impacts and comparative analyses across industries and global markets to further enrich understanding of consumer behavior and certification influences.

People counting applications have been used in diverse applications. The ability and accuracy of thermal imaging over conventional image cameras has led to the implementation of thermal cameras in people counting applications. This paper present a thermal people counting smart glass windows. The people counting application would be remotely monitored from a single centralized PC station as it’s connected to a multiplex of mass monitoring of 20 thermal camera, all embedded into different glass windows. The thermal cameras would then be able to detect body temperatures of all individuals who pass through any of the camera range and also count the numbers of people who passed through the camera range. The data gotten can then be further utilized in various ways, example is in the control of air conditioning and lightening.

We review time expansion wave theory and refine our model showing it to accurately match observed cosmological luminosity data. The theory augments general relativity to create a container within which quantum effects can be explained by treating time as an artefact of a fourth spatial dimension that we observe as the expansion of the universe. This leads us to explain mass creation, the speed of light limit, gravity, black holes without singularities and other macroscopic effects. Our model leads to an expansion velocity of 6.87 0.36 × 106 ms-1, which results in a Hubble expansion rate constant of 71.3 3.7 km/s/Mpc. Because of the finite window of time in which we exist, an extra a degree of freedom is available leading to interesting interpretations at the subatomic level. At this size range, then a spin is allowed within the time dimension explaining why wave particle duality occurs and explains the electromagnetic force and other quantum mechanical properties. It provides a solution to the double slit conundrum and can explain how quantum entangled partners can behave in a quantum way and pass seemingly time-defying information. The potential quantitative origin of the fine structure constant which governs the size of the electromagnetic force is also strongly indicated by this theory.

Aligning supply chain and marketing functions is crucial for high-tech startups aiming to successfully launch new products in competitive markets. This qualitative research explores the strategies, challenges, benefits, and best practices associated with supply chain and marketing alignment in high-tech startups. Through a detailed analysis of case studies and semi-structured interviews with industry professionals, the study identifies key insights into how startups can effectively integrate these functions to enhance operational efficiency, market responsiveness, customer satisfaction, and risk management. The findings reveal that successful alignment requires the formation of cross-functional teams, leveraging integrated technologies like CRM and ERP systems, establishing regular inter-departmental communication, and developing joint performance metrics. These strategies foster collaboration and ensure that supply chain and marketing efforts are coordinated towards shared goals. However, startups face challenges such as differing departmental objectives, resource constraints, communication barriers, and technological limitations, which hinder effective alignment. Benefits observed from effective alignment include improved operational efficiency through streamlined processes, enhanced market responsiveness to adapt quickly to changing demands, increased customer satisfaction by delivering products that meet market expectations, and better risk management through proactive identification and mitigation of supply chain and market risks. Best practices identified include fostering a culture of collaboration, investing in technology for data integration and transparency, aligning strategic objectives across functions, and continuously monitoring and adjusting alignment strategies. Integration of broader elements such as sustainability, entrepreneurship, emotional intelligence, marketing, and supplier relationship management further enriches the alignment framework. This study contributes to a deeper understanding of how high-tech startups can strategically align their supply chain and marketing functions to achieve competitive advantage and sustainable growth in dynamic market environments.

This qualitative research explores the influence of supply chain disruption management on brand resilience and consumer perception. Amidst increasingly complex global dynamics, effective strategies are crucial for organizations to mitigate risks, maintain operational continuity, and preserve consumer trust. The study employs semi-structured interviews with stakeholders across diverse industries, focusing on strategies employed, outcomes observed, and challenges faced in managing disruptions. Key findings underscore the significance of proactive measures such as risk assessment, contingency planning, diversification, technology integration, and collaboration in enhancing organizational resilience. These strategies not only enable businesses to navigate disruptions effectively but also contribute to sustaining competitive advantage and stakeholder confidence. Consumer perception during disruptions emerges as pivotal, shaped by brands' transparency, responsiveness, and ethical considerations in managing supply chain challenges. Transparent communication and reliable service delivery during disruptions enhance brand reputation and foster consumer loyalty. However, challenges including information gaps, resource constraints, coordination issues, and regulatory compliance complexities highlight the need for adaptive strategies and robust partnerships across the supply chain. Overall, the study provides insights into the interconnectedness of disruption management, brand resilience, and consumer perception, offering practical implications for organizations seeking to strengthen their resilience strategies and consumer relationships in dynamic market environments.

This qualitative study explores the transformative role of digital technologies in enhancing supply chain efficiency and marketing effectiveness across diverse industries. The integration of Internet of Things (IoT), artificial intelligence (AI), blockchain, and advanced analytics has reshaped organizational practices, enabling real-time data collection, analysis, and decision-making in supply chain management (SCM) and marketing. Through semi-structured interviews with 25 professionals, including supply chain managers, marketing executives, and IT specialists, insights were gathered into the adoption, integration, and impact of digital technologies within organizational contexts. Key findings highlight IoT's contribution to enhancing supply chain visibility, predictive maintenance, and operational efficiency through continuous monitoring and data-driven insights. AI technologies support demand forecasting, inventory optimization, and personalized marketing strategies, improving customer engagement and satisfaction. Blockchain enhances supply chain transparency, traceability, and security, reducing risks associated with fraud and ensuring compliance with regulatory standards. Advanced analytics provide organizations with actionable insights into consumer behavior and market trends, guiding strategic decision-making and optimizing marketing campaigns. Despite these benefits, organizations face challenges such as technological complexity, integration issues, data privacy concerns, and organizational resistance to change. Strategic planning, leadership support, and investment in digital infrastructure are essential for overcoming these challenges and maximizing the potential of digital technologies. Future research directions include exploring sustainability initiatives in digital SCM, advancing AI-driven analytics, and understanding digital transformation in emerging markets.

This qualitative study explores the relationship between supply chain responsiveness (SCR) and customer loyalty within the e-commerce sector. E-commerce has revolutionized global commerce, driven by technological advancements and shifting consumer behaviors. Central to e-commerce success is the ability to meet customer expectations swiftly and reliably, necessitating agile supply chain management (SCM) practices. SCR in e-commerce encompasses the capacity to adapt to dynamic market demands, minimize disruptions, and enhance customer satisfaction through efficient logistics, inventory management, and last-mile delivery. Through in-depth interviews with customers, e-commerce platform managers, and supply chain practitioners, this study investigates key themes, challenges, strategies, and impacts associated with SCR and customer loyalty. Findings reveal that customers prioritize fast order fulfillment, reliable service quality, personalized experiences, and trustworthy interactions, all of which significantly influence their loyalty and advocacy behaviors. Challenges identified include inventory management complexities, logistical hurdles in last-mile delivery, and the need for effective supplier communication. Strategic approaches to enhance SCR include leveraging data analytics for demand forecasting, adopting agile SCM practices, integrating customer feedback into service improvements, and fostering collaborative relationships with suppliers. These strategies not only optimize operational efficiency but also cultivate enduring customer relationships based on satisfaction, trust, and loyalty. The study concludes that improved SCR practices lead to increased customer satisfaction, repeat purchases, and positive word-of-mouth, thereby strengthening competitive advantage and sustainability in the e-commerce marketplace.

The main characteristic of polycystic kidney disease is the development of multiple fluid filled renal cysts. The discovery of mislocated Na,K-ATPase in the apical membrane of cyst lining epithelia alluded to a reversal of polarity as a possible explanation to the fluid secretion. The topic of apical Na,K-ATPase in cysts remains controversial. We investigated the localization of the Na,K-ATPase and assessed the apical-basolateral polarization of cyst lining epithelia by means of immunohistochemistry in kidney tissue from six polycystic kidney disease patients undergoing nephrectomy. The Na,K-ATPase α1 subunit was conventionally situated in the basolateral membrane of all immunoreactive cysts. Proteins of the Crumbs and partitioning defective (Par) complexes were localized to the apical membrane domain in cyst epithelial cells. The apical t-SNARE protein Syntaxin-3 also immunolocalized to the apical domain of cyst lining epithelial cells. Proteins of the basolateral Scribble complex immunolocalized to the basolateral domain of cysts. Furthermore, we confirmed that cysts can originate from virtually any tubular segment with preserved polarity. In conclusion, we find no evidence of a reversal in apical-basolateral polarity in cyst lining epithelia in polycystic kidney disease.

Introduction: Over decades, much have been said and done regarding under-five mortality in Ethiopia. The country has been following the lead of sustainable development goals and UNICEF with its transformation plan targets. However, unless the efforts supported by status assessing studies, it might be difficult for the country to progress. Thus, the current study was directed to identify the prevalence and associated factors of under-five mortality in 2019. Methods: According to the study criteria, we extract and cleaned data in STATA v. 15.0. The data then weighted as per the sampling weight, primary sampling unit, and strata before analyzing in STATA 15.0. Data management consisted of descriptive (mean, standard deviation, and proportion or percent) and association statistics. We deliberated binary logistic regression for this analysis and we checked each variable at 0.25 p-values to include in the model. The final p-value to declare association was p <0.05 and AOR with 95% CI was also applied to describe the results. The data source was the Ethiopian Mini Demographic Health Survey (EMDHS) 2019. EMDHS collected the data from 8,885 in a face-to-face manner with a 99% response rate. Results: From 5,527 numbers of weighted women with under-five analysed in this study, the proportion of under-five mortality was 277.23(5.02%). Factors like 2nd birth order 0.52(0.35, 0.79), 3rd-4th 0.49(0.28, 0.84), 1-2 ANC visits 0.24(0.12, 0.49, ANC visit three’ 0.14(0.07, 0.28), ANC visit four and above 0.22(0.14, 0.36), in marriage mother 0.43(0.19, 0.96), ‘1-2 under-five children 0.02(0.011, 0.03), and greater than three under-five children 0.007(0.0007, 0.004) were all negatively associated with under-five mortality rate. Conclusion: To obtain the exalted outcome out of this study, the government might need to increase antenatal care, women education, institutional delivery, and the modern contraceptive methods use through enhanced community mobilization, health education using community health workers, increasing access to essential cares of mothers and children, and the policy commitment for the issues related to family size, birth order, and birth interval.

This qualitative research investigates the role of collaborative planning in synchronizing supply chain and marketing activities among multinational companies (MNCs). Collaborative planning integrates traditionally separate functions to enhance operational efficiency, customer responsiveness, and strategic alignment. The study employs semi-structured interviews with key informants from diverse MNCs across industries and geographies to explore practices, challenges, and outcomes associated with collaborative planning initiatives. Findings highlight the pivotal role of cross-functional collaboration and advanced technologies, such as artificial intelligence and big data analytics, in improving demand forecasting accuracy, optimizing inventory management, and enabling personalized marketing strategies. Challenges include organizational resistance, cultural barriers, and the complexity of aligning global strategies. Strategic outcomes encompass improved operational efficiency, cost savings, enhanced customer satisfaction, and strengthened competitive advantage. Moreover, the integration of sustainability goals underscores the importance of environmental responsibility and regulatory compliance in collaborative planning frameworks. The study also identifies emerging trends in digital transformation and agile supply chains shaping future practices. Overall, collaborative planning emerges as a strategic imperative for MNCs to navigate complexities, capitalize on opportunities, and sustain growth in a globalized marketplace.

This qualitative research explores consumer perceptions of supply chain responsiveness and its impact on brand loyalty within the apparel industry. The study investigates how consumers perceive supply chain practices such as reliability, agility, and sustainability, and examines their influence on brand loyalty decisions. Thirty participants, representing diverse demographics and purchasing behaviors, were interviewed to gather insights into their awareness, expectations, and experiences related to supply chain responsiveness. Findings reveal that consumers prioritize supply chain reliability, expecting brands to consistently deliver high-quality products, accurate sizing, and timely responses to market trends. Sustainability practices also emerged as a significant factor, with consumers favoring brands that demonstrate ethical sourcing and environmental responsibility. Technology plays a crucial role in enhancing supply chain responsiveness, as consumers value real-time updates, personalized experiences, and seamless transactions. Moreover, the study underscores the impact of supply chain disruptions on brand trust and loyalty, highlighting the importance of resilience and contingency planning in supply chain management. Brands that effectively navigate disruptions through agile strategies can enhance consumer trust and loyalty, even in challenging circumstances. Overall, this research contributes to understanding the intricate relationship between supply chain dynamics, consumer perceptions, and brand loyalty in the apparel industry. It offers practical implications for apparel brands seeking to enhance consumer satisfaction, differentiate themselves in a competitive market, and foster sustainable growth through strategic supply chain management.

Brand communication and supply chain management are critical components of value co-creation in B2B markets, yet their interplay and implications remain underexplored in current literature. This qualitative study investigates how these elements synergistically contribute to mutual value creation among businesses. Through semi-structured interviews with senior executives and managers from diverse industries, key insights were gleaned regarding the strategic alignment of brand communication strategies with supply chain practices. Findings underscore the importance of authenticity, transparency, and consistency in brand messaging to build credibility and foster stakeholder trust. Supply chain management emerged as pivotal in supporting effective brand communication, facilitated by advancements in AI, blockchain, IoT, and cloud computing, enhancing operational efficiency and responsiveness across global networks. Entrepreneurship and emotional intelligence were identified as crucial drivers of innovation and collaboration within B2B contexts, augmenting organizational agility and resilience. Furthermore, the integration of sustainable practices within supply chain operations was found to enhance brand reputation and mitigate risks associated with environmental and ethical considerations. The study highlights actionable insights for practitioners, emphasizing the strategic integration of brand communication and SCM capabilities to navigate complexities, capitalize on emerging opportunities, and foster sustainable growth. This research contributes to a deeper understanding of the multifaceted dynamics shaping B2B interactions and provides a foundation for future research endeavors. By aligning brand communication strategies with SCM practices and leveraging technological advancements, businesses can enhance competitive advantage, cultivate enduring relationships with stakeholders, and achieve sustainable success in a dynamic global marketplace.

In today's volatile and competitive business landscape, achieving synergy between supply chain agility and marketing flexibility is imperative for organizations striving to enhance resilience and maintain competitiveness. This qualitative study explores the integration of these strategic elements and their impact on organizational performance in turbulent markets. Semi-structured interviews were conducted with key stakeholders from diverse industries to capture insights into adaptation strategies, challenges, and outcomes associated with aligning supply chain agility and marketing flexibility. Findings reveal that supply chain agility, characterized by rapid response capabilities to disruptions and fluctuating demands, is essential for optimizing operational efficiency and maintaining continuity in uncertain environments. Meanwhile, marketing flexibility enables organizations to adjust strategies swiftly based on real-time market insights, enhancing customer engagement and market responsiveness. The study identifies organizational silos, resistance to change, and technological limitations as primary barriers to achieving seamless integration. Benefits of synergy include improved customer satisfaction, accelerated time-to-market for new products, and enhanced competitive advantage through personalized marketing strategies and optimized resource allocation. Moreover, organizations that effectively integrate supply chain agility with marketing flexibility reported greater innovation, employee satisfaction, and sustainable growth.

Interest in organic foods is increasing at a moment when humanity is facing a range of health challenges including the concern that some conventionally produced foods may pose possible adverse effects on human and livestock health. With the increasing human population, intensive production is increasingly trending towards high-input systems that aim to close yield gaps, increase crop yields, and develop new crop varieties with higher yield potential and tolerance to biotic and abiotic stresses, all within the context of incorporating specific traits to satisfy consumer demand. Potato (Solanum tuberosum L.) is one of the most consumed foods under different cultural diets, however its production faces some challenges related to soilborne diseases, marketable yield and quality, sugars and dry matter content of the produced tubers, tuber content in terms of nitrate, minerals, vitamins, bioactive compounds and antioxidants, and consumer appreciation regarding the sensory characteristics of tubers and processed products. Different studies have been investigating some of these challenges, with sometimes straightforward and sometimes connflicting results. This variability in research results indicates the general non-transferability of the results from one location to another under the same management practices in addition to differences in plant material. This review compares some characteristics of raw or boiled potato and processed products from potato tubers grown organically and conventionally. Ideally, such information may be of benefit in decision making by consumers in their dietary choices, by potato growers in their selection of crop management practices, and by scientists looking at potential areas for future research on potatoes.

Nanoporous membranes promise energy-efficient water desalination. Hexagonal boron nitride (h-BN), like graphene, exhibits outstanding physical and chemical properties, making it a promising candidate for water treatment. We employed Car–Parrinello molecular dynamics simulations to establish accurate modeling of Na+ and Cl- permeation through hydrogen passivated nanopores in graphene and h-BN membranes. In these complex systems the classical potentials cannot properly account for the physics at play. We demonstrate that ion separation works well for the h-BN by imposing a barrier of 0.13 eV and 0.24 eV for Na+ and Cl- permeation respectively, compared to the graphene where the Cl- ion faces a negative barrier of 0.68 eV and is prone toward blockade and Na+ permeation is associated with a slightly negative barrier of 0.03 eV. From the change in the solvation shell, we get the following trend: Na/h-BN > Na/G > Cl/G > Cl/h-BN. We argue that the trend in the permeation barrier changes to Cl-h-BN > Na-h-BN > Na-G > Cl-G due to a combination of several interactions, including the distortion of the water network induced by the ions, the ion-water interaction, and the ion-nanopore interaction. Overall, the desalination performance of h-BN surpasses that of their graphene counterparts.

The visualization of hyperspectral images in display devices, having RGB colour composition channels is quite difficult due to the high dimensionality of these images. Thus, principal component analysis has been used as a dimensionality reduction algorithm to reduce information loss, by creating uncorrelated features. To classify regions in the hyperspectral images, K-means clustering has been used to form clusters/regions. These two algorithms have been implemented on the three datasets imaged by AVIRIS and ROSIS sensors.

Concept Knowledge (C-K) theory has been used in engineering and science-based research for more than a decade. Design of an Information Technology (IT) artefact is mostly pragmatic in nature. Design Science Research (DSR) methodology applied and studied in many Information Systems (IS) research. Many sub design decisions involved through the design of an IT artefact from a concept (idea) to a working prototype. A DSR artefact is based on a combination of decisions made during several sub-design stages. Artefacts are built based on the selection of elements in each sub-design space. Recording the design decisions on each sub-design space would be beneficial for future researchers. By knowing the design decisions on each sub-design space, researchers would be able to try different combinations of the design. C-K theory provides the ability to capture the design processes’ several sub-design spaces. In this paper, we discuss the DSR research methodology by looking at the stages proposed in the literature, and the application of C-K theory in an IT-based DSR. This paper also proposed a C-K theory-based protocol called Concept Tree for tracking and reporting artefact design steps. The application of C-K theory in DSR is exhibited using the implementation of the Concept Tree for a prototype design IT artefact.

In this paper, some convexity properties and some inequalities for the (p,k)-analogue of the Gamma function, Г_p,k(x) are given. In particular, a (p,k)-analogue of the celebrated Bohr-Mollerup theorem is given. Furthermore, a (p,k)-analogue of the Riemann zeta function, ζ_p,k(x) is introduced and some associated inequalities are derived. The established results provide the (p,k)-generalizations of some known results concerning the classical Gamma function.

Transcription factors are diverse intracellular proteins facilitating cellular responses to inducing factors via gene expression. Regulatory signalling cascades from the membrane proteins (sensors) to transcription factors (effectors) are paramount to accurate phenotypic display against external factors. This review examines several transcription factors germane to Cryptococcus (C.) neoformans adaptation and survival for human infection. These opportunistic pathogenic single-cell yeasts (fungi) possess several gene duplications and peculiar membrane proteins due to adaptive phenotypes and morphological plasticity. Consequently, hundreds of responsible pleiotropic genes have been studied to understand how these genes are induced, regulated, and coordinated. However, these findings are sparsely converged and interlinked, making it cumbersome to relate one gene to the other or group them by their functions. We reviewed several wide-ranging transcriptional analysis works associated with C. neoformans into comparable phenotypic traits that necessitate adaptation, survival, and human infection. We present a robust work that addresses several transcription factors and their inducing factors. Lastly, we converge, link, and group several of these factors according to their multifunctional expression pattern. We also provide adequate information on certain genes critical to this fungus, which could be explored pharmaceutically in drug targeting for more effective antifungal management.

The frequent incidents of oil spills and other forms of pollution arising from crude oil exploration and exploitation (OEE) in the Niger Delta have caused several investigations on Polycyclic Aromatic Hydrocarbons (PAHs) pollution. This study aimed at developing a comprehensive report on PAH pollution and its human health risks recorded in the Niger Delta. Studies were extracted from Google Scholar, PubMed, and ResearchGate using a defined selection criterion. The quality of each study was assessed using the Newcastle – Ottawa Scale. Thirty-eight studies were selected with the majority reporting on PAH pollution in aquatic environments. Across all the selected studies, the total number of PAHs recorded ranged from 7 to 28 PAH congeners. Also, PAH potential sources reported in the studies were of pyrogenic and petrogenic sources. PAH concentrations recorded in water, sediment, aquatic organisms (fish and shrimp), soil, dust, and crop samples ranged from below detection limit (BDL) to 450 ± 117.9 mg/L, BDL to 1821.5 mg/kg, 0.005 to 1.098 mg/kg, ND to 4154 ± 3461 mg/kg, 165.1 to 1012 mg/kg, and 0.020 to 3.37 mg/kg, respectively. Majority of the selected studies reported PAH levels which were higher than the permissible limits. Incremental Lifetime Cancer Risk (ILCR) assessment of PAHs in samples ranged from low to high via ingestion and dermal routes of exposure to humans. It is recommended that the Federal Government of Nigeria promotes environmentally friendly operations of OEE. Future studies should focus on PAH pollution in farmlands, ambient air and the associated human and ecological health risks.

Despite the existence of pasteurization and its advocacy worldwide, most marketed milk in a developing country like Nigeria are sold raw by the locals. It costs hundreds of millions of Naira to set up a conventional pasteurizing plant in Nigeria. Boiled milk ends up curdling which results in to a loss of nutrients, so it is not beneficial to treat milk by this method. This paper hence presents the re-designing and fabrication of the contact area of a solar milk pasteurizer

Research topics surrounding the giraffe have been subject to recent disagreement, with work focusing on taxonomy over ecological phenomena such as behavioural thermoregulation. Much interest in taxonomy arises around the existence of distinct local populations of giraffes, often enclosed in small, fenced reserves, preventing natural gene flow. Targeted management of reserves may act as a buffer for declining populations, providing landscape that minimises requirements for thermoregulatory behaviours. Notable behaviours include shade-usage via trees and other giraffes, and positioning of the body towards the sun, employing an individual’s own neck as a shade source. Breeding programmes and translocation of individuals away from large communities on fenced reserves may increase giraffe population numbers across their range; however, the genetic diversity of large populations in enclosed spaces may be called into question. 55 of the 57 giraffes from the population on the Mogalakwena River Reserve (MRR) were observed over eight months, recording thermoregulatory behaviours such as body positioning in response to sun exposure, and shade usage; behaviours both noted in secondary works. These behaviours were compared across identities, such as sex and age, to assess how thermoregulation varies per individual. The population on the MRR spent more time facing the sun during high temperature days, with adults, sub-adults, males, and dark-coated individuals prioritising the behaviour beyond other individuals. Body positioning behaviours of individuals were also found to be more important in thermoregulation than shade-seeking, with shade usage decreasing on hotter days. Positional behaviour, disregarding identity, was also observed across wet and dry seasons, with a clear contrast; giraffes face the sun significantly more during the hotter wet season. The behaviours observed in this work provide an insight into the direction conservational strategies may take on closed reserves. However, further work is required on other reserves with varied population structures, to determine whether one strategy may be implemented across the giraffe's range, or whether specialised strategies are required in individual locations.

In this research a neccessary and sufficient condition for the proof of the Binary Goldbach conjecture is established. It is established that the square of all natural numbers greater or equal to 2 have an additive partition equal to the sum of the square of a natural number greater or equal to zero and a Goldbach partition semiprime. All Goldbach partition semiprimes are odd except 4. This finding is in itself proof all composite even numbers have at least Goldbach partition. The result of the proof of the Binary Goldbach conjecture is used to prove the Andrica and Legendre conjectures. The Riemann hypothesis is examined and sources of non trivial zeroes outside the critical strip are discussed. An example example of a non-trivial zero outside the critical strip is given

Social Anxiety Disorder (SAD) is a common mental health condition characterized by an intense fear of social situations, leading to significant impairments in daily functioning. Traditional exposure therapies, including Cognitive-Behavioral Therapy (CBT), have shown efficacy in treating SAD but are often limited by logistical challenges and patient reluctance. Virtual Reality Exposure Therapy (VRET) has emerged as a promising alternative, providing a controlled and immersive environment for exposure to anxiety-provoking scenarios. This paper explores the integration of Generative Adversarial Networks (GANs) into VRET to enhance the personalization, realism, and adaptability of therapeutic scenarios. GANs, which consist of a generator and a discriminator network, allow for the creation of highly realistic virtual environments tailored to the specific fears and triggers of individual patients. By offering real-time adjustments and personalized exposure scenarios, GAN-enhanced VRET addresses key limitations of traditional therapies, increasing patient engagement and treatment adherence. This review synthesizes findings from key studies on GAN-enhanced VRET, evaluating its efficacy in reducing anxiety symptoms and discussing the potential for broader application across various anxiety disorders. The results indicate that GAN-enhanced VRET offers a significant advancement in the treatment of SAD, providing a more accessible, engaging, and effective approach to exposure therapy. Future directions include expanding accessibility through cost reduction, integrating additional AI techniques, and exploring applications beyond SAD to improve mental health outcomes across diverse patient populations.

In this paper we aim to help topical probiotics research and development achieve its potential as an incredible future solution for skin problems by investigating whether the current products on the market satisfy criteria for safe and effective use on the skin microbiome. As previously defined, this includes whether they use microbes known to be part of a healthy skin microbiome and in healthy amounts. In addition, we evaluate whether they contain live microbes, and therefore can be classified as probiotics according to the WHO’s definition. Using recent market analysis at least 84% of products do not contain live microbes. Of the products that appeared to use live microbes, they contained those used in research and development of probiotics for the gut. Due to the varying composition of each person’s microbiome, there is not a one size fits all probiotic solution. Personalisation of probiotics products is essential to satisfy the criteria for safe and effective use, but none of the products on the market, understandably, offer this. Upsetting the delicate ecosystem balance of the skin microbiome could have damaging effects and regulation could help to stop a loss of trust between consumers and cosmetics industry. Future work will perform an in-depth evaluation of the topical probiotics on the market in the EU, USA, and Canada. We will also investigate how to move the topic closer to achieving its potential by updating the criteria, including by discussing how to measure the success of a probiotic solution.

The current study aims to produce a material that has a dual effect of healing and anti-inflammatory. For this target k-carrageenan/polyacrylamide hydrogel film loaded with cetrimide (k-CAR/PAAm/CI) was performed by manual casting technique. Definite concentrations of k-CAR and AAm was heated at 80°C for 2 hours, CI and glycerol were added. The solution was cast without using initiator and cross-linker. The reaction of the sulfonic acid group -SO3H of k-CAR with -CONH2 group of PAAm lead to the formation of a sulfonamide (-SO2NH-) linkage. The characteristics of the produced films were investigated by FTIR, TGA, contact angle, and mechanical properties. Improvement in the thermal stability was performed in k-CAR/PAAm/CI2 film containing 1.5% CI compared to the film has 0.5% CI (k-CAR/PAAm/CI1). The contact angle measurement proved the films are hydrophobic that enhanced by increasing CI content. The tensile strength and elongation percent values are considered adequate for materials used in wound care. k-CAR/PAAm/CI2 (1.5% CI) film showed superior antimicrobial activity against P. aeruginosa, moderate activity against S. aureus, and low activity against E. coli. The film k-CAR/PAAm/CI2 was effectively inhibiting the heat-induced hemolysis and may offer a promising approach for the development of effective wound dressings.

This paper presents a new semi-explicit algorithm for parameters estimation in a time-fractional generalization of dual-phase-lag heat conduction model with the Caputo fractional derivatives. It is shown that this model can be derived from a general linear constitutive relation for the heat transfer by conduction when the heat conduction relaxation kernel contains the Mittag-Leffler function. The model can be used to describe heat conduction phenomena in a material with power-law memory. The proposed algorithm of parameters estimation is based on the time integral characteristics method. The explicit representations of the thermal diffusivity and the fractional analogues of the thermal relaxation time and the thermal retardation are obtained via a Laplace transform of the temperature field and utilized in the algorithm. An implicit relation is derived for the order of fractional differentiation. In the algorithm, this relation is resolved numerically. An example illustrates the proposed technique.

The electron of spin −1/2 is a Dirac fermion of a complex four-component spinor field. Though it is effectively addressed by relativistic quantum field theory, an intuitive form of the fermion still remains lacking and it is often described by the so-called Dirac belt trick. In this novel undertaking, the electron is examined within the boundary posed by a recently proposed MP model of a hydrogen atom into 4D space-time. Its transformation to Dirac fermion appears consistent with Dirac belt trick, quantum mechanics and Lie group with gravity considered to be a classical force for an irreducible spinor field. These outcomes are compatible with Dirac field theory and its associated features like wave function collapse, quantized Hamiltonian, non-relativistic wave function, Weyl spinor, Lorentz transformation and Feynman diagrams. The model though speculative, it could become important towards defining the fundamental state of matter subject to further examinations.

This interdisciplinary work presents a novel patent pending method of inertial electrostatic confinement (IEC) fusion called the Nuclear Electromagnetic Shaping Accelerator Reactor (NESAR) that addresses all of the major failure problems with currently known methods of IEC fusion. A brief background of previous IEC methods that generate a negative potential well to accelerate ions for fusion will be reviewed and compared to the NESAR method of magnetic confinement. In addition, a direct comparison will be presented between the NESAR and the tokamak method of fusion. The NESAR method of fusion obtains the plasma oscillation and compression capabilities of a tokamak without producing the catastrophic magnetic reconnection disruptions that currently plague tokamaks. Since the NESAR can oscillate charged particles comparable to the tokamak, this work will briefly review the history of the tokamak, how sawtooth magnetic reconnection occurs, and how the NESAR precludes the occurrence of magnetic reconnection. This work will also review the beginnings of a novel unified field theory that has obtained interest from the Defense Advanced Research Projects Agency (DARPA). This unified field theory is based upon the trajectory of charged particle movements within the NESAR, which is the only concept of magnetic confinement in the world that may allow charge particles to collectively interact relatively to a solitary location. Due to this possible capability, the confined charged particles have the potential to experience curved trajectories; allowing for the effects of curvature deviation to be placed upon the charged particle within the magnetic confines of the NESAR. If charged particles can experience curvature deviation then deviated acceleration is generated; allowing the electromagnet field to be propelled to a higher spatial dimension that could influence spacetime. Finally, this work will review another theory that explains how magnetic pole reversals are observed by the National Aeronautics and Space Administration’s (NASA) coiled magnetic field detectors. This theory requires little to no postulations to be framed and it is purely based upon the trajectory of charged particles within the NESAR, Michael Faraday’s law of induction, and experimental observations of rotating plasmas.

This short communication reports on the initial results of a much larger, ongoing project, the aim of which is to investigate the question: could the skin microbiome, just like the gut microbiome, play a role in sports recovery and performance – and if so, could this role be as significant a one as that played by the gut microbiome? 17 high performance college athletes addressed their skin microbiome by minimizing contact with synthetic chemicals and by using topical skin supplements, shown previously to significantly increase skin microbiome biodiversity, for two weeks after training. 76% said their skin softness improved, 35% said their muscle stiffness and recovery after sport improved, 12% said their sleep quality improved, and 100% said they would be likely to use skin supplements again. Future work will use hundreds of athletes.

Recent years have seen a massive increase in research on mindfulness as both a therapeutic practice as well as a protective health factor. While many associations have been made between mindfulness and clinical outcomes, understanding of the underlying mechanistic processes is still in its infancy. In this review, associations between mindfulness and other established frameworks in cognitive control are explored—in particular the dual modes of control framework in cognitive control theory. Studies in mindfulness providing evidence towards a dual-mode mindfulness model are reviewed and compared with the proactive and reactive modes of cognitive control to identify common underlying principles. Studies involving cognitive testing, advanced neuroimaging, and neurotransmitter levels and their associations with proactive and reactive control are reviewed in the context of the dual modes of mindfulness. While evidence supporting relationships between proactive and reactive modes of mindfulness and cognitive control are preliminary, existing literature on mindfulness already supports the notion of two components of mindfulness and is in line with the hypothesis that cognitive control and mindfulness are closely related. Since preliminary evidence suggests that proactive forms of mindfulness are more associated with improvement in clinical outcomes, mindfulness programs could be modified to target proactive mindfulness practices to maximize outcomes. The implications of proactive and reactive mindfulness on therapy, limitations of the framework, and necessity of studies providing direct evidence are further discussed.

Melanoma, a deadly form of skin cancer, has seen improved survival rates due to advances in diagnosis and treatment, yet the need for further improvement remains critical. Tumor-associated antigens, such as PRAME (Preferentially Expressed Antigen in Melanoma), offer promising avenues for enhanced diagnostic precision, prognostic assessment, and targeted immunotherapy. PRAME, a cancer-testis antigen, is selectively expressed in various cancers, including melanoma, and plays a key role in promoting tumorigenesis through inhibition of retinoic acid signaling, epithelial-to-mesenchymal transition, and immune evasion. This review explores the diagnostic utility of PRAME in distinguishing melanoma from benign nevi, its prognostic value in aggressive melanoma subtypes, and its potential as a therapeutic target in cancer vaccines and adoptive T-cell therapies. While PRAME-targeted therapies face challenges such as tumor heterogeneity and immune suppression, ongoing research aims to overcome these barriers, offering hope for more effective melanoma treatments.

The arrest of Pavel Durov, the CEO of Telegram, represents a critical moment in the ongoing discourse surrounding free speech and content moderation. This event exemplifies the tension between upholding individual liberties and addressing the potential societal harms caused by unregulated digital communication. This paper explores the implications of Durov’s arrest and Telegram’s stance on free speech through the lens of John Stuart Mill’s Harm Principle. The Harm Principle, as articulated in Mill’s seminal work On Liberty (1859), provides a valuable theoretical framework for examining the balance between individual freedom and societal protection. This paper argues that the application of the Harm Principle can offer a nuanced perspective on the ethical responsibilities of digital platforms like Telegram in the age of global communication.

The optimization of the energy grid is a critical task for ensuring a sustainable and efficient energy future. Deep machine learning techniques have the potential to improve energy grid optimization by predicting energy demands and supplies, optimizing energy production and distribution, and detecting and preventing fraud. However, there are also several challenges associated with the use of deep machine learning in energy grid optimization. These include the lack of standardized datasets and data quality issues, interpretability and explain-ability of machine learning models, ethical and social implications of using machine learning, and integration with existing energy infrastructure and regulatory frameworks. Having a clear understanding that continued research and developments in deep learning applications to energy field are crucial for achieving a sustainable and efficient energy future. This paper therefore reviewed existing literature for challenges and opportunities associated with deep machine learning in energy grid optimization; and highlights the importance of continued research and development in the field. The paper found out that opportunities for future research in deep machine learning for energy grid optimization include advancements in machine learning algorithms and techniques, development of new datasets and data collection methods, integration of machine learning with other emerging technologies. It also established needs for collaborative research and public-private partnerships.

In this review, we present several extracellular proteases, enzymes, membrane permeases, and transporters as essential accessories proteins for nutrient assimilation, conservation, and transportation as determined by nutrient repletion or depletion. As an obligate aerobic pathogen, it is crucial for invading Cryptococcus (C.) neoformans to negotiate its adaptation to human internal organs like the brain and spinal cord, where the oxygen level is low compared to peripheral organs. Besides, essential metals like copper and iron are important cofactors to functional proteins; however, these metals are not usually freely available to invading human pathogens. Again, the phagolysosome low pH with glucose paucity, internal temperature, immune response, and complex extracellular matrixes are challenging environments that must be circumvented by C. neoformans in the systemic tissues for survival, adaptation, and infection in humans. We review extensive works on several extracellular proteases, enzymes, membrane permeases and transporters orchestrated by different transcription factors and present these proteins as weapons needed to outwit systemic resistance to invading pathogens. Lastly, we examine the extracellular secretory vesicles of C. neoformans as “an exosomal virulence bag” that harbours urease, laccase, phosphatase, and capsular components as additional secretory weapons for tissue invasion and persistence.

While lidar-based forest inventory methods have been widely demonstrated, prediction of tree diameters with lidar is not well understood. The performance metrics typically used in studies for prediction of diameters can be difficult to interpret and may not support comparative inferences between sampling designs or study areas. We evaluate a variety of lidar and k nearest neighbor (k-NN) strategies for prediction of tree diameter distributions using two indices which are easier to interpret and compare. The indices are based on the coefficient of determination (R²), and root mean square deviation (RMSD). These indices facilitate comparisons with alternative (non-lidar) inventory strategies, and with other project areas. We evaluate k nearest neighbors (k-NN) dbh density (relative frequency by dbh class) prediction strategies with lidar for 190 training plots distribute across the 800 km² Savannah River Site in South Carolina, USA. We evaluate the performance of k-NN with respect to distance metrics, number of neighbors, predictor sets, and response sets. Amongst the examined strategies we found Mahalanobis distance with k = 3 neighbors performed best according to a number of criteria.

We present an open-source Star Tracker (ST) for Attitude Determination. Our implementation makes use of open source software of common usage in astronomy running on a Raspberry Pi 2 platform. The developed platform is open and available for parties interested in further development. Evaluation of the system showed that the ST is suitable for Cubesats of 2U or larger. The ST platform is capable of solving the Lost-In-Space (LIS) problem. Currently, the average accuracy reached of the algorithm is close to 5 seconds of arc with an average processing time of 75 seconds. However, a average accuracy of about 3 minutes of arc can be reached with 35 seconds in average processing time. We also describe the evaluation procedure, the found conclusions of this procedure, in particular the section of the algorithm where most of the processing time is spent and other possible source of errors not included in this study.

Legal research is an indispensable skill for lawyers. Therefore, it is always necessary for lawyers to engage in legal research in due course of trying to alleviate various legal problems. Although the purpose and methodology of the research may vary from lawyer to lawyer, doing research is a common activity. As a result, the quest to assess the impacts of artificial intelligence (hereinafter ‘AI’) on legal research allows one to measure the influence of AI on the legal profession in general. Moreover, with the advent of Legal AI, it is now evident that the legal profession is not immune from disruption. According to the above, this article discusses the impacts of AI on research in the legal profession in general in accomplishing various lawyerly tasks by different legal professionals.

Tremendous progress has been witnessed in artificial intelligence within the domain of neural network backed deep learning systems and its applications. As we approach the post Moore’s Law era, the limit of semiconductor fabrication technology along with a rapid increase in data generation rates have lead to an impending growing challenge of tackling newer and more modern machine learning problems. In parallel, quantum computing has exhibited rapid development in recent years. Due to the potential of a quantum speedup, quantum based learning applications have become an area of significant interest, in hopes that we can leverage quantum systems to solve classical problems. In this work, we propose a quantum deep learning architecture; we demonstrate our quantum neural network architecture on tasks ranging from binary and multi-class classification to generative modelling. Powered by a modified quantum differentiation function along with a hybrid quantum-classic design, our architecture encodes the data with a reduced number of qubits and generates a quantum circuit, loading it onto a quantum platform where the model learns the optimal states iteratively. We conduct intensive experiments on both the local computing environment and IBM-Q quantum platform. The evaluation results demonstrate that our architecture is able to outperform Tensorflow-Quantum by up to 12.51% and 11.71% for a comparable classic deep neural network on the task of classification trained with the same network settings. Furthermore, our GAN architecture runs the discriminator and the generator purely on quantum hardware and utilizes the swap test on qubits to calculate the values of loss functions. In comparing our quantum GAN, we note our architecture is able to achieve similar performance with 98.5% reduction on the parameter set when compared to classical GANs. With the same number of parameters, additionally, QuGAN outperforms other quantum based GANs in the literature for up to 125.0% in terms of similarity between generated distributions and original data sets.

An article's tone and framing not only influence an audience's perception of a story but may also reveal attributes of author identity and bias. Building upon prior media, psychological, and machine learning research, this neural network-based system detects those writing characteristics in ten news agencies' reporting, discovering patterns that, intentional or not, may reveal an agency's topical perspectives or common contextualization patterns. Specifically, learning linguistic markers of different organizations through a newly released open database, this probabilistic classifier predicts an article's publishing agency with 74% hidden test set accuracy given only a short snippet of text. The resulting model demonstrates how unintentional 'filter bubbles' can emerge in machine learning systems and, by comparing agencies' patterns and highlighting outlets' prototypical articles through an open source exemplar search engine, this paper offers new insight into news media bias.

This case represents the association between the presence of large fibroid tumor and pulmonary embolism in 47-year-old women. We highlight the diagnostic investigations and treatment methods for PE, followed by further evaluation of the underlying explanation of this pathology and eliminating other related risk factors.

Sterile alpha motif domain-containing protein 9 (SAMD9) is a regulatory protein centrally involved in cell proliferation and apoptosis. Mapped to 7p21.1, variants in SAMD9 have been reported in &lt;50 pediatric cases worldwide, typically with early lethality. Germline gain-of-function SAMD9 variants are associated with MIRAGE Syndrome (myelodysplasia, infection, restricted growth, adrenal hypoplasia, genital anomalies, and enteropathy). Spalt like transcription factor 1 (SALL1) is a zinc finger transcriptional repressor located at 16q12.1 where only two transcript variants in SALL1 are known. RUNX2 (6p21.1) encodes a nuclear protein with a Runt DNA-binding domain critical for osteoblastic differentiation, skeletal morphogenesis, and serves as a scaffold for nucleic acids and regulatory factors involved in skeletal gene expression. RUNX2 and SALL1 are thus both ‘master regulators’ of tissue organization and embryo development. Here, we describe exome sequencing and copy number variants in two previously unknown mutations—R824Q in SAMD9, and Q253H in SALL1. A new multiexon 3’ terminal duplication in RUNX2 is also reported. This is the first known phenotype characterization for the intersection of all three variants in a healthy 46,XX adult. Focusing on developmental progress, ultrastructural renal anatomy, and selected reproductive aspects, we describe this unique genotype diagnosed incidentally during Covid-19 illness. Individual disruption in SAMD9, RUNX2, or SALL1 would be expected to give a bleak prognosis. However, the convergence discovered here appears to dampen severe pathology, perhaps by cross-gene silencing of effects normally deleterious when such changes occur alone.

The first published description of intraovarian platelet-rich plasma (PRP) appeared in mid-2016, when a new experimental technique was successfully used in adult human ovaries to correct the reduced fertility potential accompanying advanced maternal age. Considering the potential therapeutic scope of intraovarian activated PRP and/or condensed platelet cytokines would likely cover both menopause treatment and infertility, the mainstream response has ranged from skeptical disbelief to welcome astonishment. Indeed, reports of restored menses in menopause (as an alternative to conventional hormone replacement therapy) and healthy term livebirths for infertility patients (either with IVF or as unassisted conceptions) after intraovarian PRP injection continue to draw notice. Yet any proper criticism of ovarian PRP applications will be difficult to rebut given the heterogenous patient screening, varied sample preparations, wide differences in platelet incubation and activation protocols, surgical/anesthesia techniques, and delivery methods. Notwithstanding these features, no adverse events have been reported thus far and ovarian PRP appears well tolerated by patients. Here, early research guiding the transition of ‘ovarian rejuvenation’ from experimental to clinical is outlined. Likely mechanisms are presented to explain results observed in both veterinary and human ovarian PRP research. Current and future challenges for intraovarian cytokine treatment are also discussed.

This study delves into the impact of artificial intelligence on students’ learning.The paper pioneers the use of kmeans classification to reduce the dimensionality of features before the classification process, which minimizes redundant information and computational overhead. This step is not commonly found in prior research.Firstly, a random forest model is established with “whether AI assistance was used to complete the paper” as the output, and various features as inputs. The analysis of the predictive accuracy when changing input features reveals the degree of influence of each feature on using AI to complete the paper. After feature selection, the remaining 6 features can still effectively predict the use of AI to complete the paper, indicating the representativeness of the extracted indicators. Subsequently, the PCA-K-means algorithm is employed to classify the use of artificial intelligence. PCA algorithm is used for dimensionality reduction of the extracted features to better characterize students’ use of AI. Three representative variables are selected, and the contribution of each feature is computed based on the factor loading matrix. Finally, the K-means algorithm is used to classify students based on the three dimensional features, showing that students can be effectively classified into 2 categories. The results indicate that the majority of students support the use of AI technology to enhance their abilities, although some students may only intend to use AI to cope with exams and similar tasks.

The primary purpose of this research article is to study the famous K$\ddot{o}$the's Conjecture for the special cases - when a ring $\mathfrak{R}$ is commutative, and when $\mathfrak{R}$ is an Algebra over a field. Furthermore, some open problems involving tensor product of Algebras over a field has also been discussed extensively along with their proofs. Subsequently, an equivelent statement of K$\ddot{o}$the's problem in terms of algebra of matrices has been established.