Migrate is a verb representing a process where the intention of providing social services to migrants is to reduce their instability and discomfort. Consequently, social service providers are inclined to view migrants as pitiful, often also those to be feared, with migrants learning to form negative views of themselves, decreasing their mental health. Considering migration as a verb neglects the noun initiating the migration when the migrant is heading to a person, place, thing, event, or idea. In viewing migration as noun-dependent, the migrant is identifiable as self-directed in seeking aid rather than pitiful or inciting fear. This study aims to examine the types of nouns migrants conceptualize for guiding their migration based on a Google Scholar search of “[noun-type] to which [whom] migrants head in their migration” for each noun type regarding the four most highly cited reports published since 2020. The purpose is to determine the social services applicable to migrants in their self-direction regarding theoretical foundations that contrast problem-focused with emotion-focused coping. Viewing such migration nouns as essential migration signifiers encourages migrants’ favorable identification. In recognizing the intended self-direction of the migrant, their mental health is improved and is supportable through relevant and appropriately available social services.

Soil carbon is newly refined as ~32,000 Gt C (gigatonnes) over ten times previous totals. Soil organic carbon (SOC) of ~22,000 Gt C plus plants at ~2,400 Gt C in both above- and below-ground stocks hold 99% of Earth’s biomass. Occupying a topographic surface area of 25 Gha with mean depth 21 m, soil has more organic carbon than all plants, oceans, fossil fuels, or the atmosphere combined. Soils are both the greatest biotic carbon store and the most active CO2 source. Basic inventory is required for proper understanding and utilization of Earth’s natural resources, especially with increasing soil degradation and species loss. Values are raised considerably, the disparity due to lack of full soil depth survey, neglect of terrain and of other omissions. Herein new totals are determined for mineral soils, permafrost, and peats (of all forms and ages), to full depth (easily doubling shallow values) and allowing for terrain that is ignored in all terrestrial models (doubling most values again), plus SOC in recalcitrant glomalins (~30%) and friable saprock (+26%). Additionally, soil inorganic carbon (SIC), aquatic sediments and dissolved fractions are factored in. Soil biota (e.g. fungi, bacteria and earthworms) are similarly upgraded. Primary productivity, also upped for terrain, is confirmed at 220 Gt C/yr on land supported by C/O isotope fluxes. Priority issues of species extinction, humic topsoil loss, and excess atmospheric CO2 are all remedied by SOC restoration and biomass recycling via (vermi-)compost for use in 100% organic husbandry and adoption of wider practices of Permaculture based upon scientific observation of Nature.

The high antigenic variability of the foot-and-mouth disease virus (FMDV) represents a challenge for developing prophylactic strategies, stressing the need of research into vaccines offering broad protection against a range of virus strains. Here, the heterotypic cross-reaction using different vaccine schemes against serotype O strains was studied, evaluating the impact of revaccination, antigen dose, and incorporation of additional FMDV serotypes. Naïve cattle were immunized with seven distinct FMDV vaccines, receiving three doses of the same formulation at 0, 28 and 56 days post-primary vaccination (dpv). Serum samples were collected up to 70 dpv and tested by a virus-neutralizing test against serotype O strains from South American and two strains representative two Asian lineages. Our results showed that vaccines containing the ME-SA topotype O1/Campos strain developed cross-neutralizing responses against the two Asian viruses after the first vaccination. In contrast, significant heterotypic neutralizing antibody titers against the homologous topotype strain were only found after the second immunization, indicating that the phylogenic relationship may differ from the antigenic profiles for these two viruses. The amount of the O1/Campos strain and the revaccination were essential factors for neutralization against the homologous and heterologous type O FMDV viruses. The strain composition of the vaccine was only relevant for cross-neutralization against one of the Asian strains, suggesting potential intra-serotypic divergences for this pattern.

Considerable attention has recently been given to the contribution of greenhouse gas (GHG) emissions of the healthcare sector to climate change, which represents 4-6% of emissions worldwide. GHGs used in medical practice are regularly released into the atmosphere and contribute to elevation in global temperatures that produce detrimental effects on the environment and human health. Consequently, a comprehensive assessment of their global warming potential (GWP) characteristics and clinical uses, many of which have evaded scrutiny from policy makers due to their medical necessity, is needed. Of major interest are volatile anesthetics, analgesics, and inhalers, as well as fluorinated gases used as tamponades in retinal detachment surgery. In this review, we compare estimates of these gases’ GHG emissions in metric tons CO₂ equivalent (MTCO₂e) and their relative GWP. Notably, the anesthetics desflurane and nitrous oxide contribute the most emissions out of the major medical GHGs, equivalent to driving 12 million gasoline-powered cars annually in the US. Retinal tamponade gases have markedly high GWP up to 23,500 times compared to CO₂ and long atmospheric lifetimes up to 10,000 years, thus bearing the potential to contribute to climate change long-term. This review provides the basis for discussions on examining the environmental impacts of medical gases with high GWP, determining whether alternatives may be available, and reducing emissions while maintaining or even improving patient care.

The complex structure of the plant cell wall makes it difficult to use the biomass produced by biosynthesis. For this reason, the search for new strains of microorganisms capable of efficiently degrading fiber is a topic of interest. For these reasons, the present study aimed to evaluate both the microbiological and enzymatic characteristics of the fungus Curvularia kusanoi L7strain. For this, its growth in different culture media was evaluated. Wheat straw mineralization was evaluated by gas chromatography assisted by infrared spectroscopy. The production of endo- and exoglucanase, laccase and peroxidase enzymes in submerged solid fermentation of wheat and sugarcane bagasse were characterized. The strain efficiently mineralized raw wheat straw, showing a significant decrease in signals associated with cellulose, hemicellulose and lignin in the infrared spectra. High enzyme productions were achieved in submerged solid fermentation of both substrates, highlighting the high production of endoglucanases in sugarcane bagasse (2.87 IU/mL) and laccases in wheat (1.64 IU/mL). It is concluded that C. kusanoi L7 is an ascomycete with a versatile enzyme production that allows it to exhaustively degrade complex fibers such as raw wheat straw and sugar cane bagasse, making it a microorganism with great potential in the bioconversion of plant biomass.

Imipramine hydrochloride (IMP), a tricyclic antidepressant used for major depression, enuresis, and neuropathic pain, is limited by gastrointestinal complications, low oral bioavailability (44%), and complex dosing requirements. This study aimed to explore a novel non-invasive nasal delivery system using chitosan nanoparticles (Cs NPs) embedded in an in situ gel to address the limitations of oral IMP administration. Cs NPs loaded with IMP were synthesized via ionic gelation and assessed for precision in drug concentration using a validated HPLC method. The particles were integrated into a thermoresponsive polymer, Pluronic F127, to form an in situ gel suitable for nasal administration. The formulation was characterized for gelation temperature, duration, viscosity, mucoadhesive strength, and overall gel robustness. Drug release kinetics and the controlled release mechanism were studied using ex vivo permeation tests with Franz diffusion cells and nasal sheep mucosa. The optimized nanoparticle formulation (F4-50) exhibited a consistent PS of 141.7±2.2 nm, a ZP of 16.79±2.1 mV, and a high encapsulation efficiency of 67.71±1.9%. The selected in situ gel formulation, F4-50-P1, demonstrated a gelation temperature of 33.6±0.94°C and a rapid gelation time of 48.1±0.7 seconds. Transform-attenuated total reflectance infrared spectroscopy (ATR-IR) confirmed the compatibility and effective encapsulation of IMP within the formulation. The release profile of F4-50 included an initial burst release followed by a sustained release phase, with F4-50-P1 showing improved control over the burst release. The flux rates were 0.50±0.01 mg/cm²/h for F4-50 and 0.33±0.06 mg/cm²/h for F4-50-P1, indicating effective permeation. The developed chitosan nanoparticle-based in situ gel formulation provides a promising approach for the controlled release of IMP, enhancing therapeutic efficacy and patient compliance while mitigating the disadvantages associated with oral delivery.

The natural compounds PSK and PSP have antitumor and immunostimulant properties. These pharmacological benefits have been documented in vitro and in vivo, although there is not information in silico which describes the action mechanisms at molecular level. In this study, the inverse docking method was used to identify the interactions of PSK and PSP with two local databases: BPAT with 66 antitumor proteins, and BPSIC with 138 surfaces and intracellular proteins. This led to the identification interactions and coincidences of PSK and AB680 inhibitor in the active site of CD73. It was also found that PSK bonds to CD59 interacting with amino acids APS22 and PHE23, which coincide with the rlLYd4 internalization inhibitor. With the isoform of K-RAS protein, PSK bonded to the TYR32 amino acid at switch 1, while with BAK it bonded to the region of the α1 helix, while PSP bonded to the activation site and the C-terminal and N-terminal ends of that helix. In Bcl-2, PSK interacted at the binding site of the Venetoclax inhibitor, showing coincidences with amino acids ASP111, VAL133, LEU137, MET115, PHE112, and TYR108; while PSP had coincidences with THR132, VAL133, LEU137, GLN118, MET115, APS111, PHE112, and PHE104.

In this review, recent advances in the combination of CRISPR-Cas systems with graphene-based electrolyte-gated transistors are discussed in detail. In a first part, the functioning of CRISPR-Cas systems is briefly explained, as well as the most common ways to convert their molecular activity into measurable signals. Besides optical means, conventional electrochemical transducers are also developed. However, it seems that the incorporation of CRISPR/Cas systems into transistor devices could be extremely powerful, as the former provides molecular amplification, while the latter provides electrical amplification; combined, the two could help to advance in terms of sensitivity and compete with conventional PCR assays. Today, organic transistors suffer from poor stability in biological media, where graphene materials perform better by being extremely sensitive to their chemical environment while being stable. The need for fast and inexpensive sensors to detect viral RNA arose on the occasion of the COVID-19 crisis, but many other RNA viruses are of interest, such as dengue, hepatitis C, hepatitis E, West Nile fever, Ebola, polio, for which detection means are needed.

Reliable detection of sunflower (Helianthus annuus) in edible and used cooking oil (UCO) is crucial for the sustainable production of food and biodiesel. In this study, a variety of sunflower oils (crude, cold pressed, extra virgin, refined, and UCO) were examined using different methods of DNA extraction and PCR amplification to develop an efficient technology for the identification of sunflower in oils. DNA extraction kits such as NucleoSpin Food, DNeasy mericon Food, and Olive Oil DNA Isolation as well as modified CTAB method were found to be able to isolate amplifiable genomic DNA from highly processed oils. Novel uniplex, double, and nested PCR systems targeting the sunflower-specific helianthinin gene were developed for efficient identification of sunflower. New sunflower DNA markers were revealed by uniplex PCRs. The combination of modified CTAB and nested PCR was demonstrated as a reliable, rapid, and cost-effective technology for detecting traces of sunflower in 700 μl of highly processed oil, including refined and used cooking oil. The study will contribute to both the food industry and the energy sector as developed methods can be used for oil authenticity testing in food and biodiesel production.

Primary hyperparathyroidism represents the third more prevalent endocrine disease in general population consisting of an excessive secretion of parathyroid hormone from one, more frequently, or more of the parathyroid glands, leading to a dysregulation of calcium homeostasis. Schematically, its development occurs primarily by pathophysiological events with genetic mutation, at germline and/or somatic level, that favor the neoplastic transformation of parathyroid cells, and promoting their aberrant proliferation, and mutations determining the shift of PTH "set-point”, thus interfering with the normal pathways of PTH secretion, and leading to a “resetting” of Ca2+-dependent PTH secretion or to a secretion of PTH insensitive to changes in extracellular Ca2+ levels. Familial syndromic and non-syndromic forms of primary hyperparathyroidism are responsible for approximately 2-5%, of primary hyperparathyroidism cases and most of them are inherited forms. The history of the genetic/molecular studies of parathyroid tumorigenesis associated with Multiple Endocrine Neoplasia type 1 Syndrome (MEN1) represents a fascinating topic and model to understand genetic-epigenetic-molecular aspects underlying the pathophysiology of primary hyperparathyroidism, both in relation to the syndromic and non-syndromic forms. This minireview aims to take a quick and simplified look at the MEN1-associated parathyroid tumorigenesis, focusing on the molecular underlying mechanisms. Clinical, epidemiological, and observational studies, as well as specific guidelines, molecular-genetics studies, and reviews, have been considered. Only studies submitted to PubMed in English language were included, without time constraints.

Introduction: Variants of COVID-19 are responsible for 700 million infections and 7 million deaths worldwide. Vaccinations have high efficiency in preventing infection and secondary benefits of reducing COVID-19 hospital admissions, attenuating disease severity and duration of illness. Conflicting reports were published regarding COVID-19 among PLWH. Objective: The aim of this study was to evaluate COVID-19 morbidity, hospitalization and the magnitude of immunological response to sequential BNT 162b2 mRNA vaccines in PLWH regarding demographic and clinical factors. Results: Our retrospective study included 784 PLWH who had at least one anti- SARS-CoV-2 antibody test between March 2021 and October 2021. Half of our patients (392) had CD4 cells count above 500 cells/µl, 40.2% (315) had 200<CD4<500 cells/µL and only 9.8% (77) had CD4 <200 cells/µL at their last laboratory workup. The mean age was 50.2±12.2 years. About 90% of our patients were given at least two doses of the BNT 1626b2 Pfizer vaccines, about 60% received three doses of the vaccine. About a quarter of our patients (27.3%) had COVID-19 infection. Only 6 patients required hospital admission. All six patients recovered from COVID-19 infection. Titers of COVID-19 antibodies were lower for patients with CD4 cells count of less than 200 cells/ µL in the first, second and third serological tests with statistical significance. In a multinomial logistic regression the influence of other factors such as age, sex, previous COVID-19 infection on first COVID-19 antibodies titers was not significant. Conclusions: PLWH are responsive to COVID-19 vaccines. As was expected, patients with higher CD4 cells count have higher titers of COVID-19 antibodies and less severe illness. Age, sex and previous COVID-19 infection did not significantly affect antibodies titers according to our study. Larger prospective studies with control groups are needed to further characterize immunologic response to COVID-19 vaccination among PLWH.

Nanobubbles, gas-filled entities that possess a size of less than , have notably emerged as critical components within various domains such as environmental science and medicine, primarily due to their remarkable stability and distinctive diffusion characteristics that differentiate them from larger bubbles. This comprehensive study meticulously explores the diffusion rates and stability of hydrogen and oxygen when encapsulated in oxyhydrogen nanobubbles, specifically within aqueous environments, utilizing the Chapman-Enskog theory, which is a well-established framework for understanding gas diffusion processes, alongside a modified Arrhenius equation to effectively evaluate activation volume and stability parameters. The findings from this investigation reveal that the diffusion processes of both gasses experience a significant reduction in rate due to the influence of high internal pressure, as well as the molecular interactions occurring with water, whereby hydrogen is observed to exhibit a marginally accelerated diffusion rate in comparison to oxygen. It is crucial to understand that elements like surface charges, zeta potential, and the idea of activation volume significantly influence the enduring stability of nanobubbles, particularly in specific environmental scenarios that could boost their longevity. These significant findings pose a challenge to classical diffusion models, thereby suggesting a promising potential for the sustained application of nanobubbles in various fields such as water treatment processes and therapeutic medical interventions. Future research endeavors should prioritize the refinement of theoretical models while also aiming to experimentally validate the mechanisms of stability that have been observed across a range of diverse applications to further substantiate these findings.

This paper proposes a design for a platform-based Multi-phase Interleaved Synchronous Buck Converter (MISBC) using Silicon (Si) based Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs). A custom platform was developed to compare the theoretical performance of a MISBC circuit simulated with Multisim and compared it with a prototype that was built at Western Sydney University. The work disclosed in this manuscript describes some steps adopted during the selection of each component and technical considerations taken during the design of the Printed Circuit Board (PCB). The platform designed has a maximum power output of 260 Watts, with a buck reduction of the nominal voltage from 97 Volts to 24 Volts at a maximum switching frequency of 50 kHz. This switching frequency is achieved with an open-loop circuit configuration coupled with synchronized signal generators, used to validate the dead band required between the activation of each MOSFET implemented in a half bridge configuration. A summary of the results based on the duty cycle required to achieve the buck voltage desired highlights the advantages of each operating mode of the MISBC circuit, where the theoretical performance is compared against the data acquired during functional evaluations of the prototype, allowing further interpretations towards the optimal control algorithm required to maximize the performance output of MISBC circuits.

In order to study the thermal deformation behavior of uranium-50wt.%zirconium, used Gleeble 3800 thermal simulation testing machine to carry out compression deformation experiments at different temperatures for this material. The effects of deformation temperature and strain rate on the alloy were studied. The results show that the peak stress of U-50wt.%Zr metallic fuel decreases with the increase of deformation temperature after thermal deformation at 500°C~600°C, especially at 600°C compared with that at 500°C and 550°C. At the same temperature, the peak stress increases with the increase of strain rate, especially the peak stress at strain rate 0.1s-1 and 1s-1 is significantly higher than that at strain rate 0.01s^-1, and then the microstructure and diffraction results of U-50wt.%Zr metal-type fuel after thermal deformation are compared and analyzed, and the Arrhenius-type constitutive equation and thermal proces550℃,έ=1s^-1 diagram of U-50wt.%Zr metal-type fuel are established based on the peak stress.

As Ambeth Ocampo poignantly states, "The past is not dead; it is not even past." In an era where globalization threatens to homogenize distinct cultural identities, the challenge of preserving the rich tapestry of Filipino cultural heritage becomes paramount. This article investigates the dynamic continuum of Filipino cultural identity, shaped by historical influences and contemporary global interactions. It employs theories of cultural hybridity, transnationalism, and identity to examine the interplay between tradition and modernity, revealing how Filipino culture navigates this complex landscape. Through a detailed analysis of traditional practices, modern adaptations, and the impacts of globalization and the COVID-19 pandemic, the study highlights the resilience and adaptability of Filipino cultural expressions. It further explores intergenerational perspectives on cultural preservation, the role of the diaspora in cultural exchange, and the emergence of new cultural forms in urban settings. By evaluating ongoing efforts to celebrate and preserve Filipino heritage, this paper emphasizes the necessity of recognizing both historical roots and contemporary realities. Ultimately, it issues a call to action for a collective commitment to the celebration and preservation of Filipino cultural heritage, underscoring its vital role in fostering identity and community in an increasingly interconnected world.

This study aims to investigate the effectiveness of sustainable urban regeneration projects in mitigating Urban Heat Island (UHI). A place-based approach utilizing Geographic Information Systems (GIS) integrates spatial data and satellite imagery on the urban environment, human ac-tivity, demographics, and climate conditions, facilitating a deeper understanding of UHI dy-namics. Data-driven modelling with Machine Learning algorithms were developed to identify key variables influencing UHI effects, such as building density, greening extent, and surfaces’ albedo. A comparative pre- and post-intervention analysis in Turin (Italy), focusing on the Teksid ex-industrial area, was investigated. This analysis reveals a reduction in surface UHI intensity of -0.94 in summer and -0.54 in winter, highlighting the positive impact of mitigation strategies employed in the regeneration plan. The implications for urban and territorial policies were in-vestigated, focusing on urban planning tools for UHI mitigation. Specifically, the Local Climate Zones method was examined and compared with actual urban morphologies to find more effective and tailored solutions for policy makers and urban planners. The combined approach of geo-graphical and satellite information, Machine Learning models and Local Climate Zones joins quantitative and qualitative data, allowing to find more tailored, effective and alternative solu-tions in critical contexts such as the urban ones.

The immune system’s evolution is crucial for its role in fighting pathogens and involvement in autoimmune and neurodegenerative diseases. The GFI1 gene family controls the function of immune cells, including neutrophils in the innate immune system and CD4+ T cells in the adaptive immune system. GFI1 consists of two members, GFI1A and GFI1B. GFI1A is vital for myeloid and lymphoid differentiation, while GFI1B is crucial for generating red blood cells and platelets. Both genes share a repressor SNAG protein and C2H2 zinc finger domains, though the peptide sequences between these domains remain uncharacterized. Using a comprehensive phylogenetic approach, we traced the evolutionary history of the GFI1 gene family, revealing its early presence in invertebrates. Two rounds of genome duplication led to GFI1A and GFI1B. Despite positive selection, the family retained structural conservation. We identified new motifs in the less-characterized middle regions, such as the SPOP-binding motif in GFI1A, potentially regulating cytokine production, and the FEDFW motif, possibly involved in neutrophil recruitment. These motifs are unique to GFI1A in higher vertebrates. In GFI1B, we discovered a unique EPLRP motif, a Separase cleavage site linked to sister chromatid separation. Our results indicate that GFI1 has evolved new functions to adapt to the complexity of the vertebrate immune system. This highlights the evolutionary significance of GFI1 in immune responses and suggests potential therapeutic applications, especially in diseases related to immune function.

The potential of both plasma and nanotechnology in the production of slow-release fertilizers is immense. These technologies, when combined, may offer green and cheap nitrogen fertilizers, from rich renewable resources available in local areas. Together these technologies may overcome some limitations of conventional synthetic fertilizers which currently are expensive and associated with low nitrogen use efficiency and significant environmental concerns. This review explores how recent advances in plasma and nanotechnology together might be leveraged to formulate new slow-release nitrogen fertilizers. While no attempt has been made so far to produce slow-release nano fertilizers from low-cost liquid nitrate generated by emission-free non-thermal plasma, plasma nitrate has already been reported as effective as a conventional fertilizer for crop production. We propose a more efficient electrocatalytic conversion of plasma nitrate to ammonium salt, followed by coating using plant-based cellulose nanoparticles into a slow-release form. This would synchronize nutrient release with the dynamic N requirements of plants. Formulations using agro-based low-cost cellulose nanomaterials might then replace high-cost carrier hydrogels associated with low mechanical strength. The review also highlights the isolation of nanocellulose from various plant materials and its characterization for use in different formulations of slow-release nano plasma N fertilizer. Additionally, we discuss mechanisms of N loss, slow-release, and retention in the soil. The knowledge from this review has potential to contribute to the production and use of efficient, sustainable fertilizers, to improving food security and, consequently the health of our planet.

In recent years, foodborne biomaterials have been widely used in wound healing, and they have attracted much attention because of their advantages of green, environmental protection and pollution-free. Therefore ，in this study, ginger, a commonly used medicine in traditional Chinese medicine, was used to prepare ginger extract (Ginger E) as wound healing dressing, and its effect was comprehensively compared with curcumin. The results showed that Ginger E and curcumin had excellent biocompatibility and bioactivity. Among them, Ginger E showed better ability to promote cell migration, angiogenesis and intracellular reactive oxygen species (ROS) clearance than curcumin. And Ginger E behaved better anti-inflammatory and antioxidant activity. The results of animal experiments further demonstrate that Ginger E can promote angiogenesis and collagen deposition, promote the expression of anti-inflammatory factors, and refrain from the expression of pro-inflammatory factors, thus showing great potential in wound healing.

This study aims to evaluate the outcomes of neoadjuvant chemotherapy with immunotherapy in patients with non-small cell lung cancer (NSCLC) within a real-world context. We analyzed medical records from January 2022 to August 2023, focusing on individuals aged 18 and older diagnosed with resectable NSCLC who received neoadjuvant chemoimmunotherapy prior to surgical intervention. The cohort comprised 56 patients, predominantly smokers (95%) and male (74%), with 80% presenting at stage III. Of the participants, 44 underwent surgery, with 95% receiving lobar resection. Clinical assessments via PET-CT imaging revealed an 86% rate of response or disease stabilization, while pathological evaluations showed complete and major pathological responses in 61% of cases. This real-world data supports the safety and efficacy of incorporating immune checkpoint inhibitors in the neoadjuvant treatment of NSCLC, followed by surgical resection.

HTA introduced by Annett and Duncan is widely recognized for breaking down complex tasks into manageable subtasks, data, and quantitative analysis confirming its effectiveness are limited. By combining the HTA with the NASA Workload Index (NASA-TLX), a subjective workload assessment tool, this study aims to provide a comprehensive assessment of task performance and workload. The project involved assembling a three-jaw chuck with HTA for process definition and subtasks, while NASA-TLX was used for workload determination. Data were collected through questionnaires and observation forms and analyzed to determine the impact of HTA on task performance and workload distribution. The results show that HTA effectively identifies task complexity and bottlenecks, which facilitates task optimization and improves performance. The NASA-TLX integration provides critical insights into individuals' subjective workload and targets areas where task performance and resource allocation can be improved. This study shows that combining HTA and NASA-TLX provides a holistic approach to understanding and improving task performance, ultimately leading to better user experience and productivity.

A specialized microenvironment in the bone marrow, composed of stromal cells including mesenchymal stem cells (MSCs), support hematopoietic stem cells (HSCs) self-renewal and differentiation but also regulates leukemia development and progression. The reciprocal direct interaction between MSCs and CD34+ HSCs under physiological and pathological conditions has not been well characterized yet. Here, we established a direct co-culture model between MSCs and CD34+ HSCs or MSCs and acute myeloid leukemia cells (THP-1, Molm-13, and primary cells from patients) to study cell-cell communication. Following MSCs-CD34+ HSCs co-culture, the expression of adhesion markers N-cadherin and connexin 43 increased in both cell types, forming gap junction channels. Moreover, the clonogenic potential of CD34+ HSCs was increased. However, direct contact of acute myeloid leukemia cells with MSCs reduced the expression levels of connexin 43 and N-cadherin in MSCs. The impairment in gap junction formation could be ascertained to a defect in the acute myeloid leukemia derived MSCs. Interestingly, CD34+ HSCs and acute myeloid leukemia cell lines restrained MSCs from engaging into osteoblastic differentiation upon prolonged direct cell-cell contact. In conclusion, under physiological conditions, connexin 43 and N-cadherin interaction preserves stemness of both CD34+ HSCs and MSCs, a process that is compromised in acute myeloid leukemia, pointing out to the possible role of gap junctions in modulating stemness.

Invasive species represent an important agent of change and threat to native biological diversity due to their high ability to enter and establish themselves in natural or semi-natural ecosystems. Urban and peri-urban areas are an easy entrance door for invasive vegetal species firstly used as ornamental that can become naturalized. In this study, it was analysed the presence, frequency and distribution of invasive alien plant species in the urban, peri-urban and natural area surrounding the city of Córdoba, Southern Spain. Our research reveals the presence of 17 invasive plant species from 10 different families. It supposes the 35% of the invasive plant species detected in the Andalusia region, and 27% of Spain. The highest number was located in ruderal areas, following by abandoned crop fields, being phanerophytes the most abundant life-form. Regarding the native source area, the highest percentage come from the America continent. Data indicates that the use of non-native species as ornamental can enhance invader establishment, spread, and ecological impact, which can facilitate subsequent alien species success aided by global change conditions. Additionally, our results are a strong knowledge base for effective management strategies in the area and will help to addressing data gaps related to the distribution of alien species on a regional scale in the Mediterranean area.

The purpose of this study was to examine how factors that contribute to the service quality (responsiveness, product diversity, price fairness, and tangibles) offered by a sporting goods store on an online shopping mail affect shopping value. We also explore the moderating effects of positive emotions on the relationship between service quality and shopping value. A total of 654 respondents participated in the survey. The SPSS statistical package and smartPLS 4.0 were used to test the research hypotheses as well as to confirm the moderating effect. The study finds that the abovementioned factors that contribute to the quality of service provided by the online sportswear store had a significant effect on shopping value. Shopping value was in turn found to have a significant effect on customer satisfaction. Customer satisfaction was in turn found to have a significant effect on shopping mall loyalty. The study finds that positive emotions do not have a moderating effect when responsiveness and tangibles affect shopping value. When product diversity and price fairness affect shopping value, however, the moderating effect of positive emotions was found. The results provide implications for practitioners who are concerned about improving the quality of service on online shopping malls. The results of this study contribute valuable guidance to marketers seeking to establish delivery-platform service-marketing strategies.

This article describes a new application of the global optimization method HQF ASA to the investigation of the Riemann hypothesis, in the sense of searching for zeros of the Riemann zeta function ζ outside the critical line but inside the (open) subset of the critical strip ((0,1/2)∪(1/2,1))×(−∞,∞). The underlying idea is very simple: a complex root r of a given complex function f : C → C must satisfy the condition ||f(r)|| = 0, that is, f(r) must have 2-dimensional Eu- clidean norm equal to 0, considering r as a point of R2. In the opposite direction, for any r ∈ C, ||f(r)|| = 0 implies f(r) = 0 and r is a root of f. Focusing again on the Riemann zeta function ζ, the open and simply connected region Rc = (1/2,1)×(0,∞) is used along the text, taking into account the symmetries of zeros of ζ in the critical strip. In this fashion, finding a global optimizer for ||ζ|| is equivalent to finding a root of ζ. Therefore, and taking into account the well-known efficacy of HQF ASA, a good sign of the trueness of RH would be not finding global minima in several optimization sessions with expanding subsets of Rc. In practical terms, several optimization sessions are executed using QMF ASA with increasing subsets of Rc, searching for global minima of ||ζ||. After presenting numerical results and figures, the adequacy of the proposed approach as a tool for preliminary empirical analysis for this type of problem is discussed.

Assessing the suitability of older adults with acute myeloid leukemia (AML) to intensive chemotherapy or stem cell transplantation remains a long-standing challenge. Geriatric assessment, which evaluates multiple dimensions of health, may influence a patient's ability to tolerate intensive or mild intensity approach, including treatment related mortality. Prospective studies are needed to validate different fitness criteria as well as to compare the effectiveness of geriatric assessment–based fitness against other criteria, in order to identify which aspects of the geriatric assessment are linked to treatment tolerance. Hopefully, validation studies should include different group of patients receiving either intensive or lower-intensity chemotherapy. At a minimum, the geriatric assessment should measure comorbidity burden, cognition, physical function, and emotional health—factors previously associated with mortality in AML. These assessments should be conducted before starting chemotherapy in order to minimize the treatment's impact on the results. While treatment tolerance has traditionally been evaluated through toxicity rates in solid tumor patients, AML treatment often results in high toxicity rates regardless of intensity. Therefore, early mortality should be the primary endpoint for assessing treatment tolerance, given its significant and clear implications. Other important endpoints might include declines in functional status, quality of life, and treatment adjustments or discontinuation due to toxicities. Validating these fitness criteria is essential for guiding treatment choices, improving supportive care, determining trial eligibility, interpreting study outcomes, and informing drug labeling.

Technological advancements and evolving government regulations are driving the adoption of construction equipment powered by renewable energy sources, aiming to significantly reduce emissions. Electrifying non-road mobile machinery (NRMM), particularly self-propelled Rough-Terrain Variable Reach Trucks (RTVRT) with telescopic booms, presents stability challenges. Replacing diesel engines with electric motors and battery packs shifts the centre of gravity, necessitating precise load capacity determinations via load charts to ensure safe operation. This paper introduces a virtual model developed using multi-physic modelling with Bond Graph methodology. The model encompasses crucial components, including the chassis, rear axle, telescopic boom, attachment fork, and wheels, requiring three-dimensional treatment for spatial dynamics resolution. An illustrative example, supported by experimental data, demonstrates the model's capabilities. Special focus is placed on calculating ground wheel reaction forces and hydraulic self-leveling of the attachment fork. Numerical results validate the BG-3D simulation model of the telehandler with 20-Sim as a promising tool for estimating stability limits with satisfactory precision and predicting dynamic behavior across various operating conditions. Moreover, the paper explores potential extensions of the model, such as integrating the virtual vehicle model with a platform of variable inclination in subsequent phases which aims to evaluate telehandler longitudinal and lateral stability, aligning with the ISO 22915 standard and operator safety.

Electronic sports (esports) and research on this emerging field are interdisciplinary in nature. By extension, it is essential to understand how to standardize and structure training with the help of existing tools developed by years of research in sports sciences and informatics. Our goal in this article was to verify if the current body of research contains substantial evidence of the training systems applied to training esports players. To verify the existing sources, we have applied a framework of scoping review to address the search from multiple scientific databases with further local processing. We conclude that the current research on esports dealt mainly with describing and modeling performance metrics spanned over multiple fragmented research areas (psychology, nutrition, informatics), and yet these building blocks were not assembled into an existing well-functioning theory of performance in esports by providing exercise regimes, and ways of periodization for esports.

This research answers the knowledge gap regarding the explanation of the quantum jump of the electron. This scientific paper aims to complete Einstein’s research regarding general relativity and attempt to link general relativity to quantum laws.

Epilepsy is a brain disease characterized by a persistent predisposition to epileptic seizures. The current issue is the development of new methods of epilepsy therapy, In particular, using gene therapy methods. Promising areas of research in this field are the modulation of the expression of a number of neuropeptides, ion channels, transcription factors, neurotrophic factors, etc., as well as the use of antisense oligonucleotides. One of the optimal vectors for the delivery of therapeutic transgenes is the adenoassociated virus (AAV), which is most often used in the gene therapy of neurological disorders due to the high transduction ability of neuronal tissues and low immunogenicity/cytotoxicity. In this study, we analyze the existing achievements in the use of AAV vectors in the treatment of epilepsy of various etiologies.

Conventionally, antibiotics have been regularly practiced as a cure of specific infections caused by specific bacteria. The rational use of antibiotics has always been challenging. Antibiotic residual time period is different for different antibiotics. The overuse and under-use of antimicrobials provokes the development of resistance, through which MDR strains have emerged. In this research, we intend to use Non-Antibiotic Antibacterial Agents (NAAB) that have no side effect and no residual time, in order to treat these MDR strains. Microorganisms do not develop resistance against NAAB. This study revolves around the use of Lactic Acid (LA) and Acetic Acid (AA) as NAAB against MDR strains of Staphylococcus aureus, E. coli and Klebsiella. Through broth dilution method, we identified the Minimum Inhibitory Concentration (MIC). For LA, MIC for Staphylococcus aureus, E. coli and Klebsiella is 0.78µl, 0.39µl and 0.39µl respectively and OD600 values at MIC is 0.041 for all microorganisms. Similarly, for AA the MIC was recorded at 0.78µl for Staphylococcus aureus, E. coli and Klebsiella, with OD600 value 0.041.Through Disc Diffusion Method, we got zone of inhibition (ZOI) 25mm ±1 to 18mm±1 at NAAB concentrations above MIC, indicating concentrations sufficient enough to kill bacteria while we got ZOI below 10mm at concentrations below MIC indicating that bacteria are resistant at these concentrations. We concluded that NAAB agents possess strong potential as disinfectants and antiseptics and can be ployed for the treatment of mastitis as their MIC concentrations are totally harmless for living tissue even if we inject directly into it.

This study presents the Bayesian-Optimized Attentive Neural Network (BOANN), a novel approach enhancing image classification performance by integrating Bayesian optimization with channel and spatial attention mechanisms. Traditional image classification struggles with the extensive data in today's big data era. Bayesian optimization has been integrated into neural networks in recent years to enhance model generalization, while channel and spatial attention mechanisms improve feature extraction capabilities. This paper introduces a model combining Bayesian optimization with these attention mechanisms to boost image classification performance. Bayesian optimization optimizes hyperparameter selection, accelerating model convergence and accuracy; the attention mechanisms augment feature extraction. Compared to traditional deep learning models, our model utilizes attention mechanisms for initial feature extraction, followed by a Bayesian-optimized neural network. On the CIFAR-100 dataset, our model outperforms classical models in metrics such as accuracy, loss, precision, recall, and F1 score, achieving an accuracy of 77.6%. These technologies have potential for broader application in image classification and other computer vision domains.

(1) Background: Eosinophils importance as T2 inflammation markers is known to be fundamental in asthma, chronic sinusitis, vasculitis. In cancer, despite their potential antiproliferative effect, their role remains unclear. Our purpose was to describe the relation between baseline blood eosinophil count (EOS) and overall survival in pancreatic ductal adenocarcinoma (PDAC) patients. (2) Methods: We have analyzed retrospectively the data of 137 adult patients, who underwent surgical treatment of PDAC between years 2012-2019 with no history of systemic steroid use directly before surgical treatment and no metastases found intraoperatively. (3) Results: EOS&lt;0,1 G/l (vs. ≥0,1 G/l) was an independent prognostic factor for OS both the uni- and multivariate Cox regression (respectively: HR=1,48, p=0,035 and HR=1,57, p=0,021). According to EOS and PDAC stage, median OS were: in stage I-III, EOS ≥0,1 G/l group: 14,5 months, in stage I-III, EOS &lt;0,1 G/l group: 8,0 months, in stage IV, EOS ≥0,1 G/l group: 7,0 months, in stage IV, EOS &lt;0,1 G/l group: 5,0 months. (4) Conclusions: Peripheral eosinophilia seems to be a potential independent prognostic factor. Further studies are necessary to confirm this hypothesis, since our findings suggest that T2 inflammation may be the factor directly or indirectly lengthening survival of PDAC patients.

Probability is initially defined on a Boolean algebra or a lattice of projectors. We propose here to start from a Heyting algebra.

This study, which investigates the impact of foreign bank entry on the efficiency and sustainability of domestic banks in developing countries using a Meta-Frontier analysis to estimate efficiency scores, presents findings of significant importance to banking and finance. By incorporating financial, social, and environmental sustainability proxies—such as efficiency, loan portfolio composition, and macroeconomic conditions—this study assesses whether foreign competition enhances or undermines the long-term stability of domestic banking sectors. The results show that while foreign banks can improve financial efficiency, they may destabilize domestic banks, notably smaller or less capitalized institutions. Additionally, the findings suggest that banks with higher investments in SME lending and green projects demonstrate better social and environmental sustainability. Policymakers and financial institutions must consider these dual effects when promoting foreign bank entry.

Obviously, the discussion of different factors that could have contributed to the origin of life and evolution represents a clear speculation, since there is no way to check the validity of the most of the related hypotheses on practice, as the corresponding events are not only already happened, but took place in a very distant past. However, there are a few undisputable facts obviously present at the moment, such as the existence of a broad variety of living forms and the abundant presence of intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains and intrinsically disordered regions (IDRs) in all those living forms. Since it seems that the currently existing living forms have originated from a common ancestor, their variety represents a result of evolution. Therefore, one could ask a logical question of what role(s) those structure-less and highly dynamic but vastly abundant and multifunctional IDPs/IDRs might have in evolution. This study represents an attempt to consider various ideas pertaining to the potential roles of protein intrinsic disorder in origin of life and evolution.

Inconel 718 is a widely popular aerospace superalloy known for its high-temperature performance and resistance to oxidation, creep, and corrosion. Traditional manufacturing methods, like casting and powder metallurgy, face challenges with intricate shapes that can result in porosity and uniformity issues. On the other hand, Additive Manufacturing (AM) techniques such as Powder Bed Fusion (PBF) and Direct Energy Deposition (DED) can allow the creation of intricate single-part components to reduce weight and maintain structural integrity. However, AM- parts often exhibit directional solidification, leading to anisotropic properties and potential crack propagation sites. To address this, post-processing treatments like HIP and heat treatment are necessary. This study explores the effects of the raster and stochastic spot melt scanning strategies on the microstructural and mechanical properties of IN718 parts fabricated using Electron Beam Powder Bed Fusion (EB-PBF). The research demonstrates that raster scanning produces columnar grains with higher aspect ratios. In contrast, stochastic spot melt scanning promotes the formation of equiaxed grains, enhancing microstructural refinement and reducing anisotropy. Microhardness values also show variation in strength in build direction, denoting changes in mechanical performance due to scanning strategies. These findings emphasize the critical role of scanning strategies in optimizing the EB-PBF process for improved material properties.

Mortality rates are fundamental to understanding the overall health of a population. However, statistics are usually reported using the primary underlying cause of death, overlooking potentially relevant contributing causes listed on death certificates. This paper presents indicators for multiple cause-related mortality in Canada from 2000 – 2022. Deaths from the Canadian Vital Statistics Database (2000 – 2022) were merged with multiple cause files and classified into 136 cause of death groupings. Summary statistics for multiple causes were calculated, including the Standardized Ratio of Multiple to Underlying (SRMU), which is also calculated by neighbourhood income quintile. Age-Standardized Mortality Rates (ASMR) were calculated for the underlying cause of death (ASMRUC) and compared to rates including any mention of each respective cause (ASMRAM). These were then compared to ASMRs based on a contributing-cause weighting scheme (ASMRW). The average number of causes reported on death certificates has increased from 2.79 in 2002 to 3.19 in 2021. Those in the lowest income quintiles have a higher average number of causes (3.31 in 2021) compared to those in the highest income quintile (3.09 in 2021). When employing multiple cause weighting strategies, the rank order of age-standardized mortality rates is significantly elevated for conditions including renal failure, hypertension, pneumonia, septicemia, arterial fibrillation, and artery diseases. Multiple cause-of-death approaches provide further insight into the patterns of mortality and highlight conditions that become leading causes using weighted approaches. This provides evidence to support efforts to address these conditions. There are also differences in multiple causes of death reporting by income quintile which warrants further investigation.

This work aimed to determine the effect of PBZ concentrations and application protocols on the ornamental quality and global preference of customers. PBZ was applied in five concentrations by three protocols (drench at transplanting, drench at 30 days after transplanting and immersion). At commercial maturity, the plants were evaluated for plant growth parameters related to height and canopy characteristics, fruits and leaves, in addition to sensory analysis. PBZ produced plants with darker green leaves and the drench method was more effective in modulating plant growth pa-rameters compared to immersion. Conversely, the sensory analysis showed a greater preference among evaluators for plants treated with PBZ at 2.5 and 5 mg L-1 via drench at 30 DAT or through immersion (IM), even though IM was not associated with any of the ornamental quality parameters evaluated. Likewise, the application of PBZ by drench during transplanting is not recommended as the plants showed a reduced number and size of fruits, which affected the ornamental value of the plants and global preference. Therefore, PBZ applied by drench 30DAT at concentrations of 2.5 and 5 mg L-1 produced ‘Biquinho Vermelha’ pepper plants with attractive ornamental characteristics being an alternative method for producers of potted ornamental plants.

This article provides a comprehensive historical analysis of Brazil's industrialization, tracing its evolution from the 19th century to the present day. It examines key periods and policies that have shaped the nation's economic landscape, beginning with early industrial efforts during the Imperial era and the Old Republic. The analysis delves into the Vargas regime's Import Substitution Industrialization policies, post-war industrial expansion under developmentalism, the military regime's economic strategies during the "Economic Miracle," and the challenges posed by the 1980s debt crisis. The discussion highlights contemporary issues faced in the 21st century, including premature deindustrialization and the complexities during the administrations of Presidents Lula da Silva and Dilma Rousseff. It explores the impact of Operation Lava Jato on industrial development and assesses the ramifications of President Jair Bolsonaro's policies during the COVID-19 pandemic. Central to this exploration is the critical examination of regional disparities, social inclusion efforts, and environmental sustainability initiatives. The article emphasizes that Brazil's most significant challenges lie in persistent inequality and structural racism, which serve as fundamental barriers to economic progress and industrial advancement. It argues that addressing these issues through comprehensive policies focused on education reform, economic inclusion, healthcare access, legal and institutional changes, community development, and cultural recognition is essential. By integrating social justice into economic strategies, Brazil can achieve sustainable and inclusive industrial development, fostering a more equitable and prosperous society.

This paper proposes a methodology for multi-criteria calibration of a thermo-mechanical model for numerical simulation of welding in vacuum. A finite element model of a steel plate is created. Experimental and computational data are obtained. An inverse problem is formulated for the vector identification of five calibration parameters from the heat flow model. They are evaluated for adequacy with controlled accuracy according to four criteria. An optimization problem is solved using a two-step interactive procedure. The parameter space studying method (PSI) has been applied to the study of multidimensional regions by means of quasi-uniform sounding. A Pareto-optimal set is defined. It is used to determine reduced ranked Pareto subsets by -selection. Salukvadze optimum is also determined.

Background: Narcolepsy is characterized by excessive daytime sleepiness (EDS) and episodes of cataplexy, frequently triggered by psychological stress, significant disturbances in sleep-wake cycles, pregnancy, or trauma. Modafinil is widely used as the preferred treatment due to its effectiveness in alleviating EDS, improving disease outcomes, and enhancing overall quality of life. Nonetheless, long-term safety and efficacy data are still lacking, underscoring the importance of future research to advance treatment options for narcolepsy. Aim: In our systematic review and meta-analysis, we aim to assess the effectiveness of Modafinil in the treatment of Narcolepsy. Methods: We searched in electronic databases (PubMed, Embase, Google Scholar, Scopus, Science Direct, Web of Science) was performed to identify cohort studies and randomized controlled trials (RCTs) up to 8th July 2024. Data extraction focused on baseline characteristics of the included studies and efficacy outcomes, including scores on the Maintenance of Wakefulness Test (MWT) and Epworth Sleepiness Scale (ESS) . We performed the meta-analysis utilizing the Review Manager software, version 5.4. To assess the outcomes, we compared the Modafinil-treated group with the placebo group, employing the mean difference (MD) and a 95% confidence interval (CI) for statistical analysis. Result: In total, 3833 articles were identified for screening, with nine studies included in the systematic review and five in the meta-analysis. These studies involved 997 adult patients with Narcolepsy treated with Modafinil. MWT revealed a significant increase in total scores (MD= 3.56, 95% CI [2.25 to 4.86], p < 0.00001) and ESS revealed a significant decrease in scores (MD= -3.34, 95% CI [-4.13 to -2.56], p < 0.00001). Conclusion: The research emphasizes the potential of Modafinil in alleviating EDS associated with Narcolepsy. While the results are promising, they are based on short term scale studies. It is crucial to undertake larger-scale, extended-duration, placebo-controlled studies that include a broad range of demographic populations. These trials are essential to confirm the efficacy, verify the safety profile, and fine-tune dosing strategies to maximize the long-term therapeutic benefits.

Background: Nonsurgical treatment in uncomplicated appendicitis is in many cases a reasonable option, despite the sparsity of robust, easy access, externally validated and multimodally informed clinical decision support systems (CDSS). Developed by OpenAI, the Generative Pre trained Transformer 3.5 model (GPT 3), may provide enhanced decision support for surgeons in less certain appendicitis cases or those posing a higher risk for (relative) operative contra indications. Our objective was to determine whether GPT 3.5, when provided high throughput clinical, laboratory and radiological text based information will come to similar clinical decisions as a machine learning model and a board certified surgeon (reference standard) in decision making for appendectomy versus conservative treatment. Methods: In this cohort study we randomly collected patients presenting at the Emergency Department (ED) of two German hospitals (GFO, Troisdorf and University Hospital Cologne) with right abdominal pain between October 2022 and October 2023. Statistical analysis was performed using R, version 3.6.2, on RStudio, version 2023.03.0+386. Overall agreement between GPT 3.5 output and the reference standard was assessed by means of inter observer kappa values as well as accuracy, sensitivity, specificity, positive and negative predictive value with the “Caret” and “irr” package. Statistical significance was defined as p < 0.05. Results: There was agreement between surgeon decision and GPT 3.5 in 102 of 113 cases and all cases where the surgeon decided upon conservative treatment were correctly classified by GPT 3.5. The estimated model training accuracy was 83.3 % (95% CI: 74.0, 90.4), while the validation accuracy for the model was 87.0 % (95% CI: 66.4, 97.2). This in comparison to the GPT 3.5 accuracy of 90.3% (95% CI: 83.2, 95.0), which did not perform significantly better in comparison to the machine learning model (P = 0.21). Conclusions: This to our knowledge first “intended use” for surgical treatment GPT 3.5 study comparing surgical decision making versus algorithm found a high degree of agreement between board certified surgeons and GPT 3.5 for surgical decision making in patients presenting to the emergency department with lower abdominal pain.

This paper explores the use of GNN architectures, including Graph Convolutional Networks (GCNs), Graph Attention Networks (GATs), and GraphSAGE, in modeling blockchain data. A specific focus is given to their applications in cryptocurrency transaction networks, where GNNs can detect fraudulent activities and track illicit fund flows by learning from transaction patterns and network structure. Additionally, future directions for GNN research in blockchain are discussed, including scalability challenges, privacy-preserving models, and multi-chain graph analysis. Through these advancements, GNNs offer significant potential for enhancing the security, transparency, and efficiency of blockchain and cryptocurrency ecosystems. This paper also shows an example of fraud detection for Ethereum cryptocurrencies.

The 14-3-3 protein in dimorphic fungi from the Ajellomycetaceae family, including Blastomyces spp., Histoplasma spp., Paracoccidioides spp., Emergomyces spp., and Emmonsia spp., play a crucial role in host-pathogen interactions. Thus, we performed a comparative genomic analysis across 21 fungal species which revealed the presence of two 14-3-3 gene copies in most fungi, with exceptions in Histoplasma ohiense and Emergomyces africanus which revealed one and three gene copies, respectively. Moreover, in this study it was found a high degree of similarity (over 70%) between fungal 14-3-3 proteins and the human 14-3-3ɛ isoform, particularly in conserved Ser/Thr phosphorylation sites. However, distinct differences were noted in the C- and N-terminal regions, where fungal 14-3-3 proteins have additional amino acids. Though not directly linked to pathogenicity, these structural differences may offer insights into new therapeutic strategies. The conserved regions and 3D similarities identified could serve as potential targets for broad-spectrum antifungal drug development and vaccine production. Further research is necessary to validate these in silico findings and explore the functional roles of these phosphorylation sites, which could contribute to understanding fungal pathogenicity and developing specific antifungal interventions.

Background: Post-operative pancreatic fistula (POPF) is a common complication associated with pancreatic resections. Early identification of this adverse event could avoid otherwise prolonged hospital stay due to clinical management and treatment of symptoms created by POPF. This retrospective study investigated the prevalence of pancreatic fistula among patients who underwent oncological pancreatic resection between August 2018 and December 2023 at Bnai-Zion Medical Center. Elevated C-reactive protein levels have been utilized as an early postoperative marker indicating the presence of inflammation due to tissue injury complication. Objective: The aim of the current study was to evaluate the prediction potential of elevated C-reactive protein levels in detecting the risk for infection created by pancreatic fistula. Methods: Demographic and clinical data was collected from medical records files of ninety-four pancreatic cancer patients’ cohort who were subjected to resection. Results: A significant increase in C-reactive protein levels was found on day three following surgery at the group of forty-six patients having developed pancreatic fistula compared to patients without pancreatic fistula (p=0.002). There was no statistical difference among the groups in any demographic characteristics (such as age, gender, BMI, smoking status, etc.) and any other clinical features (e.g. serum albumin levels, chemotherapy protocol, surgical technique, hospitalization time, lymph node involvement). Conclusions: The results of the study suggest that C-reactive protein could serve as an early biomarker for pancreatic fistula formation in patients undergoing pancreatic resection for cancer.

Additive Manufacturing (AM) methods are increasingly beign abopted in the industry as an alternative for mass production. In particular, Fused Deposition Modeling (FDM) technology is leading the way in this field. However, the adhesion of layers in products produced using FDM technology is an important issue. These products are particularly vulnerable to forces acting parallel to the layers and specially to impact strength. This study aims to optimize the impact strength against loads acting parallel to the layers (ZX orientation) of PA6, one of the most widely used materials in the industry. This orientation is critical in term of mechanical properties, and the mechanical characteristics are significantly lower compared to other orientation. In this study, filaments containing pure PA6 with 15% short carbon fiber and 30% glass fiber were utilized. Additionally, printing temperature, layer thickness and heat treatment duration were used as independent variables. An L9 orthogonal array was employed in this study, and each experiment was repeated three times to conduct impact strength tests. Characterization, Taguchi optimization, a factor analyses were performed, followed by fracture surface characterization by SEM. As a result, the highest impact strength was achieved with pure PA6 at 8.9 kJ/m2, followed by PA6 GF30 at 8.1 kJ/m2 and the lowest impact strength was obtained with PA6 CF15 at 6.258 kJ/m2. When compared to the literature and manufacturer datasheets, it was concluded that the impact strength values have significantly increased, and the chosen experimental factors and their levels, particularly nozzle temperature, were effective.

Issues related to the duration of university studies, have attracted the interest of many researchers from different scientific fields, as far back as the middle of the 20th century. In this study, a Survival Analysis methodology, and more specifically a Cox Proportional hazards model, has been pro-posed to evaluate a theoretical framework/model that relates the risk a student either graduating on time or having a late graduation, with a number of observed and latent factors that have been proposed in the literature as the main determinants of degree completion. The major findings of the analysis suggest that the factors contributing to the shortening of the duration of studies in-clude high academic achievements at early stages, positive motivation, expectations, attitudes, and beliefs about studies. On the contrary, external situations, negative academic experiences and some individual characteristics of the students contribute to an extended duration of studies.

Lignin is a complex organic polymer. It has a crucial role in providing structural support, rigidity, and defense against disintegration. Following cellulose, it ranks as the second most abundant natural polymer discovered on Earth. Lignin is composed of several phenolic compounds that form a complex, three-dimensional framework. Lignin, unlike cellulose, is a non-carbohydrate polymer rather than a polysaccharide. Lignin's characteristics pose both difficulties and prospects in several sectors, spanning from agriculture to renewable energy. The investigation of the composition of Lignin and its manipulation through engineering are closely intertwined. Disruptions of genes implicated in the lignin biosynthesis pathway can result in substantial alterations in the composition and architecture of Lignin. These modifications can offer novel approaches for altering Lignin and deliberately engineering the polymer to enhance its worth or simplify its extraction from cell wall polysaccharides. As a result, the definition of Lignin is constantly expanding and being adjusted to accommodate its diversity and adaptability. This review examines explicitly the versatility of the lignin molecule.

Achieving complete remission (CR) is crucial for acute myeloid leukemia (AML) patients undergoing curative therapy, but relapse often occurs within months, highlighting the need for strategies to prolong leukemia-free survival (DFS). Our phase III study compared the efficacy and safety of azacitidine (AZA) versus best supportive care (BSC) in elderly AML patients who achieved CR after intensive induction and consolidation therapy. This ancillary study (QOL-ONE Trans-2) evaluated biological changes in bone marrow using Next Generation Sequencing (NGS). We analyzed baseline, randomization, and 6-month post-remission samples from 24 patients (median age 71, 12 males). High-throughput NGS targeted 350 myeloid malignancy-related genes, considering variants with a Variant Allele Frequency (VAF) ≥ 4%. At diagnosis, all patients had 5 to 17 (median 10) mutations, with DNMT3A (42%), NPM1 (33%), and TET2 (33%) being most frequent. FANCA mutations in 4 patients were linked to a higher relapse risk (HR 4.96, p=0.02) for DFS at both 2 and 5 years. Further HLA-specific NGS analyses are ongoing to confirm these results and their therapeutic implications.

The basic helix loop helix (bHLH) transcription factors play crucial roles in plant growth, development, and stress responses. However, their identification and insight understanding in rubber trees remain largely uncovered. In this study, the bHLH gene family was explored and characterized in rubber trees using systematic bioinformatics approaches. In total, 180 bHLH genes were identified in the rubber tree genome, distributed unevenly across 18 chromosomes, and phylogenetic analysis classified these genes into 23 distinct subfamilies. Promoter regions revealed a high density of cis-elements responsive to light and hormones. Enrichment analysis indicated involvement in numerous biological processes, including growth, development, hormone responses, abiotic stress resistance, and secondary metabolite biosynthesis. Protein interaction network analysis identified extensive interactions between HbbHLH genes and other functional genes, forming key clusters related to iron homeostasis, plant growth, and stomatal development. Expression profiling of HbbHLH genes have demonstrated varied responses to endogenous and environmental changes. RT-qPCR of eleven HbbHLH genes in different tissues and under ethylene, jasmonic acid, and cold treatments revealed tissue-specific expression patterns and significant responses to these stimuli, highlighting the roles of these genes in hormone and cold stress responses. These findings establish a framework for exploring the molecular functions of bHLH transcription factors in rubber trees.

Images are widely used in educational materials due to their ability to effectively convey complex concepts. However, unauthorized image use often leads to legal issues related to copyright infringement. To address this issue, we introduce a dual-module system designed specifically for educators. The first module, a copyright infringement detection system, leverages deep learning techniques to verify the copyright status of images. It employs a Convolutional Variational Autoencoder (CVAE) model to extract meaningful features from copyrighted images and compares them against user-provided images. If infringement is suspected, the second module, an image retrieval system, recommends alternative copyright-free images using a Vision Transformer (ViT)-based hashing model. Evaluation on benchmark datasets demonstrates the system's effectiveness, achieving a mean Average Precision (mAP) of 0.812 on the Flickr25k dataset. Furthermore, a user study with 65 teachers indicates high satisfaction levels, particularly in addressing copyright concerns and ease of use. Our system significantly aids educators in creating educational materials compliant with copyright regulations.

Background and Objectives: Total rehabilitation of atrophic maxillae with zygomatic implants (ZI) has become a more common practice nowadays. However, the need for training and expertise of surgeons to correctly perform the technique in order to minimize possible complications has been described. The objective of this article is to describe an atypical case of tearing for 24 hours after the installation of a zygomatic implant. Materials and Methods: A 58-year-old male patient, with dark skin, without systemic alterations, who during the installation of one of the ZIs suffered a greenstick fracture of the zygomatic body, thus, a second, deeper milling was performed in the zygomatic body. Results: After the uneventful surgical procedure, the molding was performed, and the patient complained of excessive tearing in his right eye with regression 24 hours after surgery. The implant-supported prosthesis was installed one week after surgery and the patient continues to rehabilitate without functional or aesthetic complaints.Conclusions:Therefore, since the literature on the subject of postoperative complications of ZIs is still scarce, we believe that since the milling and installation of IZs are always close to the foramen of the zygomaticofacial nerve, this type of complication may become more frequent due to the increase in indications for rehabilitation using ZIs.

When assessing potential mates is costly, there will be selection for copying others. Mate-choice copying, which is the increased chance of mating with another individual after observing them mating with someone else (i.e., individual-based copying), has been documented in several species, including humans. It is touted as an example of the influence of culture on animal and human mating, but alone it is unlikely to lead the cultural evolution of mating. Rather, it requires mate-choice copying with generalisation (i.e., trait-based copying), which is the effect of immediate observations on future mating. This sort of mate-choice copying has been documented in six species, including humans. Here, I extend an existing game-theory model of mate-choice copying to include generalization (Extension 1), a cost to immediate copying (Extension 2), and both previous extensions (Extension 3). The results show that Extensions 1 and 2 decrease the adaptive value of mate-choice copying when compared to the original model. Extension 3 suggests that adding generalisation to mate-choice copying with a cost to immediate copying is a more likely evolutionary trajectory than adding it to mate-choice copying without this cost These results have implications for illuminating the emergence of the cultural evolution of mating preferences.

Background/Objectives: The approval of direct acting antiviral (DAA) therapy for hepatitis C (HCV) resulted in a highly effective oral treatment for patients. The primary objective of this study was to compare patients who were not treated to patients who were treated. Identifying potential reasons for the failure to treat can provide a pathway to interventions using evidence-based data. Methods: The electronic medical records in an urban predominately African American (AA) population were searched for all patients with HCV seen at least once in a GI or ID clinic 2019. Data collected included demographics, treatment visits, laboratory, insurance, and ZIP codes for median income. Results: Of the 441 patients who were not yet treated at the first 2019 visit, only 43% were treated by July 2020. Insurance and median income were not factors in failure to treat. Patients with an average of 4 visits were more likely to be treated than those with 2 or less thus confirming that failure to follow up was a significant factor for patient treatment (42% vs 8% p

In this paper, we explore the theoretical foundation of Graph Neural Network (GNN) model and apply it to various traditional supply chain logistics problem. In particular, we study the Route Optimization Problem, Demand Forecasting Problem, Risk Assessment and Anomaly Detection, Supplier Section and Procurement Optimization, Inventory Optimization Problem, and Green Supply Chain Problem. The study helps us the expand the use the GNN and gives daily supply chain management a boost.

Thurstonian scaling, i.e., Thurstonian discriminal distance δ or d' can be used as a sensory measurement index to measure and monitor food sensory difference/similarity between test and control samples due to potential food contamination. It can be obtained from any one of the sensory discrimination methods. Thurstonian scaling is theoretically independent of methods or scales used for its estimation. This paper discusses statistical inference including estimations and tests of hypothesis for d'. Ten basic sensory discrimination methods including 6 forced-choice methods and 4 methods with response bias are used in this paper to estimate d' values and their variances. Statistical tests are conducted based on the estimated d' values and their variances. The statistical tests include difference testing and equivalence/similarity testing for individual d' values for test and control samples and for two or multiple d' values for test samples. Application and significance of Thurstonian scaling for sensory discrimination methods is discussed generally. R codes for estimations and tests for d' values are provided in the paper.

The present paper discusses an elliptic equation with Steklov boundary conditions and $(p(x),q(x))$-Laplacian. Using mountain pass theorem together with Ekeland's variational principle, we prove, under appropriate conditions on the functions involved, that the problem admits at least two solutions.

This study aims to evaluate the potential of machine learning algorithms (Random Forest and Support Vector Machine) in predicting the open porosity of a general-use industrial mortar applied to different substrates based on the characteristics of both the mortar and substrates. For this purpose, an experimental database comprising 1592 samples of industrial mortar applied to five different substrates (hollowed ceramic brick, solid ceramic brick, concrete block, concrete slab, and lightweight concrete block) was generated by an experimental program. The samples were characterized by bulk density, open porosity, capillary water absorption coefficient, drying index, and compressive strength. This database was then used to train and test the machine learning algorithms to predict the open porosity of the mortar. The results indicate that it is possible to predict the open porosity of the mortar with good prediction accuracy and that both Random Forest (RF) and Support Vector Machine (SVM) algorithms (RF =0.880; SVM = 0.896) are suitable for this task. Regarding the main characteristics that influence the open porosity of the mortar, bulk density and the open porosity of the substrate are significant factors. Furthermore, the study employs a straightforward methodology with a machine learning no-code platform, enhancing the replicability of its findings for future research and practical implementations.

Grilling has become a widespread method of thermal food processing. However, food prepared this way may be a source of carcinogenic organic compounds, such as polycyclic aromatic hydrocarbons (PAHs). The present study aimed to evaluate the impact of different marinades and grilling tools on PAH contamination of chicken breast tenderloins. Together with the determination of PAHs carried out using the QuEChERS–HPLC–FLD/DAD method, the amount of meat weight loss after the thermal process and the color of raw and grilled samples were analyzed. Statistically, the highest levels of PAH contamination were stated in samples prepared on a charcoal grill without a tray, whereas the lowest using the ceramic contact grill. Meat marination showed that universal and chicken marinades can be barriers against PAHs. Following requirements set in Commission Regulation (EU) No. 915/2023, none of the analyzed samples exceeded the maximum allowable level for B[a]P (5.0 µg/kg), and the sum of 4 marker–heavy PAHs (30.0 µg/kg). Thus, preparing meat before the thermal process, including marinades rich in phenolic compounds, and selecting a grilling method with appropriate grilling tools can ensure food safety and effectively reduce PAH contamination in grilled poultry meat.

Placental cadherin (cadherin-P, CDH3) is a cell-to-cell adhesion molecule expressed at a high level in many malignant tumors. Associations of serum CDH3 with atherosclerosis have not been investigated previously. The present clinical cohort study with 3-year follow up measured atherosclerosis of the coronary, brachiocephalic, and femoral circulation and fasting levels of CDH3 in the serum in 218 patients in a hospital setting. Coronary lesions were assessed as Gensini score calculated according to the data of coronary angiography. The volumes of the brachiocephalic and femoral circulation plaques were quantified by ultrasound imaging. Serum proteomic profiling was performed in selected samples using antibody microarrays. The content of CDH3 in the serum was measured using an indirect ELISA. Odds ratio (OR), ROC-analysis, and logistic regressions were used to evaluate the associations between CDH3 content, atherosclerotic lesions, and various serum biomarkers. CDH3 serum content was associated with severity of atherosclerosis and diastolic blood pressure. The levels of СDH3 were able to discriminate patients with total subclinical and hemodynamically significant atherosclerotic lesions in all circulation pools (coronary, brachiocephalic, and femoral). Elevated serum СDH3 appeared to be a risk factor for cardiovascular outcomes after 3-year follow up with OR=1.81 (95%CI: 1.07-3.72; P=0.022). Endothelin-1 and NOx were associated with the content of СDH3 in the serum, suggesting the involvement of certain signal transduction pathways that may participate in plaque formation. CDH3 was associated with cardiovascular outcomes adjusted for coronary plaque presence, indicating a role of CDH3 in plaque biology.

Machine learning algorithms have made significant strides, achieving high accuracy in many applications. However, traditional models often need large datasets, as they typically peel sub-stantial portions of the data in each iteration, complicating classifier development without suffi-cient data. In critical fields like healthcare, there is a growing need to identify and analyze small yet significant subgroups within data. To address these challenges, we introduce a novel classifier based on the Patient Rule Induction Method (PRIM), a subgroup discovery algorithm. PRIM finds rules by peeling minimal data at each iteration, enabling the discovery of highly relevant regions. Unlike traditional classifiers, PRIM requires experts to select input spaces manually. Our inno-vation transforms PRIM into an interpretable classifier by starting with random input space se-lections for each class, then pruning rules using Metarules, and finally selecting definitive rules for the classifier. Tested against popular algorithms such as Random Forest, Logistic Regression, and XGBoost, our Random PRIM-based Classifier (R-PRIM-Cl) demonstrates comparable robustness, superior interpretability, and the ability to handle categorical and numeric variables. It discovers more rules in certain datasets, making it valuable especially in fields where understanding the model's decision-making process is as important as its predictive accuracy.

The quality of education in Bangladeshi universities has long been a topic of concern, yet comprehensive studies on its statistical impact remain limited. This research aims to assess the current state of education quality in Bangladeshi higher education institutions using secondary data from national surveys, academic reports, and global rankings. A variety of statistical methods are employed to identify key factors influencing educational outcomes, including faculty-to-student ratios, infrastructure, research output, and employability of graduates. The findings reveal significant disparities in academic standards across public and private universities, highlighting challenges such as inadequate funding, lack of modern teaching practices, and low research productivity. This study provides data-driven insights and recommendations for policymakers and educators to enhance the quality of university education in Bangladesh, with the ultimate goal of aligning it with global standards.

This study examines the rationale and perceptions surrounding AI in military technologies, focusing on its application in autonomous weapons systems (AWS), intelligence, surveillance, and reconnaissance (ISR), and decision-support systems (DSS). AI models, such as unmanned aerial and ground platforms, showed high mission success rates, with 92% mission accomplishment, 95% true positive threat identification, and low false alarms. AI's effectiveness surpassed human operators, particularly in response time and threat detection. A global survey revealed mixed opinions: two-thirds believed AI enhances national security, yet 70% opposed autonomous weapons due to ethical concerns, particularly civilian casualties. The study highlights AI's advantages in improving decision-making speed and accuracy but acknowledges challenges such as ethical considerations and public trust in autonomous systems. Future research should address ethical AI models, international humanitarian law (IHL) standards in military operations, human-AI interaction in hazardous environments, and policies related to military robotics and accountability. Understanding and enhancing public awareness of AI in military contexts is also essential.

Background: The healthcare professional who performs sedation for digestive endoscopy procedures is usually the nurse. Therefore, knowledge and training on the part of the nurse is an important factor for the correct sedation of the patient and may affect, among other factors, the quality of health care and the recovery and well-being of the patient. Objective: To determine the training opportunities and resources available to the specialists involved indigestive endoscopy services in hospitals in Spain in which sedation is performed by the nursing staff.Methods: This was a descriptive cross-sectional study performed in the Digestive Endoscopy Service at Toledo University Hospital and nearby hospitals in central Spain. The sample consisted of 75 nurses who administer sedation in digestive endoscopic procedures. Results: Regarding the training of nurses, the vast majority were generalist nurses, and only a small percentage obtained specialized training through ongoing training. Most had been working in the service for more than two years, and very few had previous experience in sedation, although the vast majority currently applied sedation. Life support training was also critical. There were significant differences in the availability of resources between different hospitals. Conclusions: The training of nurses who perform sedation in digestive endoscopy services could be improved since there is a high proportion of personnel without specific training in sedation before starting to work in the service. It is crucial to implement targeted and ongoing training programs to improve competencies in this area, as they are essential to ensure the safety and effectiveness of the procedure. Given the variability in resources and personnel training that exists between different hospitals, it seems important to establish standards at the institutional level.

Rural areas are not only faced with the problems of rural depopulation but also with the problem of water supply and water quality which is a basic necessity of life. In light of this, this paper assesses the rural water supply situation and the bacteriological quality of different water sources in the Obokun Local Government Area of Osun State, Nigeria. The safety of the water sources for human consumption and possible occurrence of the water borne diseases in the study area were determined. The study employed descriptive and analytical methods of data analysis to achieve the objectives of the inquiry. Findings showed that the study area suffered from inadequate water supply and poor locations of the sources of water: The study also revealed that the microbiological quality of the water sources used was unsafe, poor and not acceptable for human consumption. In addition, many man- days-hours were wasted in search of water. It is therefore recommended that the government should make the rural water supply and the maintenance of water quality a priority in its policy formulation.

The consistent recognition of both explicit short term and implicit long term elements of post-retirement contracts between employees and the firm can have a significant implication for estimating a firms long term sustainable cost of capital. In this paper, we show that the significant levels of investment in company own stock by pension and post-retirement plans can effectively dilute the interest of pre-existing shareholders in the enterprise value of corporations in ways which are not revealed by a classic entity theory perspective on equity. We test the empirical implications of adopting a pre-existing shareholder model of the reporting entity to re-examine the relationship between a firm’s sustainable cost of capital and various sources of idiosyncratic risk. We find that the estimated cost of capital is sensitive to: (a) alternative explicit versus implicit definitions of pension liability; (b) the nature and scope of long-term deferred compensation arrangements; and (c) the scope and nature of investment-related risks through investment in sponsoring company stock that are associated with these pension arrangements.

A sublingual vaccine comprising Poly(I:C) adjuvant and influenza HA antigen was evaluated for safety in both mice and macaque monkeys relative to its intranasal counterpart. Safety was assessed with harmful effects corresponding to upregulation of the inflammation-associated genes: Saa3, Tnf, IL6, IL1b, Ccl2, Timp1, C2, Ifi4, Aif1, Omp, Nos2, and/or Gzmb in mice and SAA2, TNF, IL6, IL1B, CCL2, TIMP, C2, AIF1, and GZMB in macaques. Quantitative gene expression analyses were performed using RT-qPCR with RNA samples from four tissues: olfactory bulb, pons, lung, tongue, and (submandibular) lymph node from both mice and macaques. In mice, the intranasally delivered vaccine markedly upregulated the inflammation-related genes in the olfactory bulb 1 day and 7 days after vaccination. The adverse effects of intranasal vaccination were also observed in macaques, however to a lesser extent than in mice. The intranasal vaccination also upregulated these genes in the pons of both mice and macaques. In contrast, the sublingual vaccine did not adversely affect the olfactory bulb or pons in either mice or macaques. The intranasally administered vaccine significantly upregulated these genes in the lungs only 1 day after vaccination, but not 7 days later, in both mice and macaques. We conclude that intranasal vaccination results in unfavorable side effects corresponding to upregulated inflammatory genes in the brain (olfactory bulb and pons). Sublingual vaccination, however, did not induce these side effects in either mice or macaque and was hence evaluated as safe.

Situational awareness detection and characterization of mental states have a vital role in medicine and many other fields. An electroencephalogram (EEG) is one of the most effective tools for identifying and analyzing cognitive stress. Yet, the measurement, interpretation, and classification of EEG sensors is a challenging task. This study introduces a novel machine learning-based approach to assist in evaluating situational awareness detection using EEG signals and spiking neural networks (SNNs) based on a unique spike-continuous-time-neuron (SCTN). The implemented biologically inspired SNN architecture is used for effective EEG feature extraction by applying time-frequency analysis techniques and allows adept detection and analysis of the various frequency components embedded in the different EEG sub-bands. The EEG signal undergoes encoding into spikes and is then fed into an SNN model which is well-suited to the serial sequence order of the EEG data. We utilize the SCTN-based resonator for EEG feature extraction in the frequency domain which demonstrates a high correlation with the classical FFT features. A new SCTN-based 2-D neural network is introduced for efficient EEG feature mapping aiming to achieve a spatial representation of each EEG sub-band. To validate and evaluate the performance of the proposed approach a common publicly available EEG dataset is used. Experimental results show that by using the extracted EEG frequencies features and the SCTN-based SNN classifier the mental state can be accurately classified with an average accuracy of 96.8% for the common EEG dataset. Our proposed method outperforms existing machine learning-based methods and demonstrates the advantages of using SNN for situational awareness detection and mental state classifications.

During recent archeological excavations in the Roman city of Carnuntum three spots with residues of streets, houses and side buildings from the time span between 1st and 4th century have been investigated. 40 soil samples taken from different layers gave the possibility to investigate the local soil bacterial communities by Next Generation Sequencing (NGS) of 16S rRNA. The background of this study was to check similarities and differences in the composition of microbial communities and to check of special types of proved bacteria or groups of them could be related to the archaeological findings. In result, the 16S rRNA data shows similarities between some samples, but also important differences in the compositions of soil bacterial communities of single samples. On the one hand, some samples are distinguished by the dominance of single major components from other samples. On the other hand, specific differences between soil samples are reflected by the patterns of mediate and less abundant bacterial groups. This supports the hypothesis, that differences in soil bacteria composition are strongly influenced by differences of the deposed soil material and, therefore, dependent on ancient human activities which created the deposits and local ancient environmental conditions many hundred years ago. This “echo” of ancient human impact on local soil bacteria composition is reflected, for example, by manure- and oil-related OTUs originating from two different street surfaces as well as by contaminated and mixed soil fills and ancient hearths and fire places. The findings support the concept of “ecological memory of soil” meaning that early impacts impress traces in the composition of soil bacterial communities which are detectable up to the present.

Digital transformation, powered by technologies like AI, IoT, and big data, is reshaping industries and societies at an unprecedented pace. While these innovations promise smarter energy management, precision agriculture, and efficient resource utilization, they also introduce serious environmental challenges. This paper examines the dual impact of digital technologies, highlighting key threats such as rising energy consumption, growing e-waste, and increased extraction of raw materials. For instance, global e-waste reached 62 million metric tons in 2022, and data centers alone accounted for nearly 1% of the world's electricity demand in 2019. The review synthesizes findings from studies on topics like the energy use of blockchain technologies and the environmental costs of raw material extraction in the smartphone industry. Moreover, it identifies critical research gaps, particularly in understanding the environmental impact of digital usage at individual and household levels. Practical strategies such as integrating circular economy principles, promoting renewable energy, and green computing are proposed to balance technological advancement with sustainability goals. This study highlights the need for a holistic approach, suggesting future research directions to minimize digital transformation’s environmental footprint while maximizing its sustainability benefits.

Recent advancements highlight the utilization of vegetable oils as additives in polymeric materials, particularly for replacing conventional plasticizers. Buriti oil (BO), extracted from the Amazon's Mauritia flexuosa palm tree fruit, boasts an impressive profile of vitamins, minerals, proteins, carotenoids, and tocopherol. This study investigates the impact of incorporating buriti oil as a plasticizer in linear low-density polyethylene (LLDPE) matrices. The aim of this research was to evaluate how buriti oil, a bioactive compound, influences the thermal and rheological properties of LLDPE. Compositions of buriti oil\LLDPE were prepared via melt intercalation techniques, and the resulting materials were characterized through Thermogravimetric Analysis (TGA), differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), mechanical property testing, and contact angle measurement. The addition of buriti oil was found to act as a processing aid and plasticizer, enhancing the fluidity of LLDPE polymer chains. TGA revealed distinct thermal stabilities for buriti oil/LLDPE under different degradation conditions Notably, buriti oil exhibited an initial weight loss temperature at 402°C, whereas LLDPE at 466.4°C. This indicated a minor reduction in the thermal stability of buriti oil/LLDPE compositions. The thermal stability, as observed through DSC displayed a nuanced response to the oil's incorporation, suggesting a complex interaction between the oil and polymer matrix. Detailed mechanical testing indicated a marked increase in tensile strength and elongation at break, especially at optimal concentrations of buriti oil. SEM analysis showcased a more uniform and less brittle microstructure, correlating with the enhanced mechanical properties. Contact angle measurements revealed a notable shift in surface hydrophobicity, indicating a change in the surface chemistry. This study demonstrates that buriti oil can positively influence the processability and thermal properties of LLDPE contributing to expand its potential applications as an effective plasticizer.

Azolla is a substitute compost that has the potential to enhance nutrient cycling in agricultural systems for sustainable development. In this study, four experiments were conducted to compare the Department of Agriculture (DOA, Thailand)'s methodology for determining the suitable type and rate of animal manure and the optimal light intensity for the growth and yield of Azolla (Azolla microphylla). The results revealed that applying 100% pig manure gave the highest yield of Azolla compared to the other manure. However, there was no discernible difference in yield across the various doses (20.16, 30.16, and 40.16 gN m-2) of pig manure treatments, for which the minimal pig manure dosage of 20.16 gN m-2 was chosen. For further experimentation in the optimal light in-tensity, the 40% shading gave the highest yield of Azolla compared to no shading or 20 and 60% shading. When compared with the DOA Thailand methodology (1.27 kg m-2 of cow manure and covered with a size 32 mesh net), the findings indicated that the modified method (20.16 gN m-2 of pig manure + 40% shading) gave a 16% greater Azolla yield than that under the DOA Thailand methodology.

Federated unlearning represents a sophisticated evolution in the domain of machine learning, particularly within federated learning frameworks. In financial applications, where data privacy and security are paramount, federated unlearning allows institutions to selectively remove or “unlearn” specific data from trained models without compromising their overall performance and accuracy. This capability is essential for ensuring that models remain adaptable, secure, and compliant with regulatory requirements, while minimizing the need for expensive retraining. In this paper, we explore various financial applications where federated unlearning can have a significant impact, including fraud detection, portfolio management, and credit risk modeling. By allowing targeted removal of outdated, erroneous, or sensitive data, federated unlearning enhances the agility of financial models, enabling institutions to keep pace with the dynamic financial landscape. Using practical numerical examples, we demonstrate how unlearning improves model accuracy and decision-making while maintaining data privacy across distributed systems. This paper underscores the critical role of federated unlearning in addressing the challenges of modern financial institutions, offering insights into its practical applications and future potential.

A novel approach for designing acceptance sampling plans is presented. It is based on the Bayesian conformity assessment framework from JCGM 106. In particular, the concept of conformance probability plays a central role in the new approach. The new approach takes into account both the producer's and the consumer's perspective by allowing each to have their own prior. In parallel, the JCGM 106 framework allows the definition of Bayesian consumer's and producer's risks which complement the "classical" risks defined in the ISO 2859 and ISO 3951 series. The new approach also casts a new light on the plans from the ISO standards.

Objectives: The aim of this study was to determinate the validity and the reliability of the self-administered Timed Up and Go (TUG) test, a gold standard test for fall risk screening, when compared to the traditional face-to-face assessment carried out by a physiotherapist. Methods: A total of 37 community-dwelling adults, mean age 61.78±6.88, 73% female, who took part in fall risk screening actions in the central region of Portugal, were assessed. The protocol included sociodemographic and history of falls questions, the Self-Efficacy for Exercise questionnaire, the Activities and Participation Profile Related to Mobility (PAPM) and three functional tests, namely the 10-Meter Walking Speed (10-MWS), TUG and 30 Seconds Sit to Stand (30s STS) tests. Within an interval of 18-24 hours after the face-to-face moment, the participants were instructed to self-administer the TUG test at home. The validity and reliability of self-administered TUG test were examined using the limits of agreement, clinically acceptable limit, intra-class correlation coefficients (ICC), paired t-tests and Pearson´s coefficient correlation (r). Results: The limits of agreement for self-administered assessment were within the clinically acceptable limits. The average result of the face-to-face TUG test and self-administered TUG test was 7.47 ± 2.45 and 7.57 ± 3.10 seconds, respectively. When comparing the two evaluations, they were strongly associated (r=0.716, p<0.001), with an excellent ICC of 0.82 (0.65-0.91), for a 95% confidence interval. Conclusion: The use of the self-administered TUG test for the screening of risk of fall, using low-cost technology, appears to be valid and reliable in community-dwelling adults aged 50 and over.

The paper presents two novel mathematical approaches to prove Goldbach's conjecture. The conjecture states that every even number greater than or equal to 6 can be expressed as the sum of two odd prime numbers. We propose that the conjecture has only four genetic codes, and as long as one of them remains valid, the conjecture continues to hold. Through these new mathematical ideas, we aim to prove the validity of Goldbach's conjecture comprehensively.

In a time of ecological and social crises, designing new institutions is crucial for meeting future challenges. Institutions emerge from the imaginations of individuals, moving into social movements and crystallizing in legal structures. As present movements seek to develop tomorrow’s governances, they turn to decentralized structures: distributed networks with little hierarchy, characterized by a diversity of actors and dynamics. While movements and technologies may seek to utilize decentralized ideas, they lack design principles: only recently has it been possible to decentralize at the national stage. Designs may come from biology and ecological networks; fungi, plants, and slime molds in soil to the neurons, glia, and blood vessels within our own bodies. This article blends these biological analogies with present technologies like blockchain and Web3 to posit future decentralized institutions, movements and legalities that give greater consideration to the more-than-human world.

The California Genetic Disease Screening Program (GDSP) employs a fixed immunoreactive trypsinogen (IRT) cutoff followed by molecular testing to screen newborns for Cystic Fibrosis (CF). The cutoffs approximate a 1.6% yearly IRT screen positive rate, however seasonal variation in IRT population means led us to develop a model to establish fixed IRT cutoffs that anticipate seasonal variation and minimize missed cases below cutoff. We utilized an ARIMA model to fit monthly IRT screen-positive percentiles and estimated regular seasonal expectations. We established a retrospective cohort followed for at least 1.5 years to capture missed false negative CF cases. We compared missed CF cases identified by seasonal cutoffs vs floating cutoffs. GDSP screened 7,410,016 newborns, from July 2007 to Dec. 2022, and missed 36 CF cases below the fixed cutoff; five of the 36 were within 3 ng/mL below the cutoff. There was a regular, seasonal cycle that varied from 1.4% in summer to 1.8% in winter. We would have missed 59 CF cases using a 1.6% daily floating cutoff. California would need to use a 4% daily floating cutoff to improve our current detection rate which would double the number of specimens sent for costly molecular analysis.

Non-compliance with iron supplementation consumption contributes to the high rate of anemia among adolescent girls in Indonesia. This study explores the barriers and enablers perceived by adolescent girls regarding regular iron supplement consumption. Using a qualitative design, eight focus group discussions (FGD) were conducted in Makassar and Padang involving 32 girls grade 8 and 9 from four junior high schools. Data on perceived barriers and enablers were collected using a social cognitive theory framework and analyzed thematically. The average age of the informants was 13,65±0,60 years. Although all participants received supplement at school, most did not consume them regularly. Key barriers include dislike of the taste and smell, parental prohibition negative experience consuming iron supplement, and the belief that iron supplements increase menstrual blood flow and volume. Enablers include self-awareness of the supplement’s benefits, trust in school-provided supplements, and positive support from parents and peers. Behavior change strategies are needed to address these barriers and strengthen supporting factors to improve iron supplementation consumption.

Understanding visual engagement in marketing is crucial for optimizing user experience and enhancing campaign effectiveness. This study introduces the Visual Interaction Analysis (VIA) methodology, utilizing advanced eye-tracking technology within immersive virtual reality (VR) environments to examine generational and gender differences in visual engagement after exposure to advertising materials. Using the Cognitive 3D platform for precise data capture, this research analyzed fixation patterns—total fixations, duration of fixations, and average duration per fixation—across Millennial and Generation Z cohorts. The analysis involved 44 participants, who were exposed to three posters in controlled VR settings. Results revealed significant generational differences: Generation Z demonstrated more focused attention, with higher fixation counts and longer total fixation durations compared to Millennials, suggesting that differences in media consumption and technological adaptation influence engagement strategies. However, both generations showed a similar depth of engagement, as indicated by the average duration per fixation. Gender analysis within Generation Z further revealed that female participants engaged for longer periods per fixation, indicating deeper processing of visual information. This methodology offers a robust framework for quantifying visual engagement, providing actionable insights that can help marketers tailor strategies and optimize campaign designs before launch.

Aims: The aim of our work was to demonstrate the possibility, in carefully selected cases, to perform operations under local anesthesia with a benefit to the patient and savings for national health care. Method: 123 patients with breast cancer underwent quadrantectomy or wide tumorectomy and sentinel lymph node removal under local anesthesia in out-patient surgery. Results: Of the 123 patients, 9 had micro-metastases and 4 had macro-metastases and only three of this had metastasis in other lymph nodes. Conclusions: Our results demonstrate that it is possible in selected cases to operate on breast cancer in out-patient surgery, with an advantage for the patient and savings for national health care.

Central composite design (CCD) is a methodology that utilizes experimental conditions based on the combination of variable points to be studied. This study aimed to select a hydrogel from the combinations provided by CCD for 3D bioprinting applications. Three biopolymers were chosen: sodium alginate (SA), gelatin (GEL), and carboxymethylcellulose (CMC), and their maximum and minimum concentrations were defined. After CCD provided the suggested combinations, the hydrogels were mixed and analyzed for their swelling degree (SD) in phosphate buffer saline (PBS) and Dulbecco's modified Eagle medium (DMEM), and printability was assessed in 2D and 3D assays. The hydrogel with the concentrations of 7.5%, 7.5%, and 2.5% for SA, GEL, and CMC, respectively, was chosen for presenting the highest SD in both fluids and good printability parameters in manual and 3D printer-based extrusion. This study demonstrated the potential utilization of Design of Experiments (DoE) methodologies to assist the development of hydrogels for 3D bioprinting purposes.

Outbreaks of avian pathogens such as Newcastle disease virus, avian influenza virus and Salmonella have a major impact on economies and food security worldwide. Some pathogens also pose a significant zoonotic potential, especially avian influenza viruses. Vaccination plays a key role in controlling many poultry diseases and there are many vaccines licenced in the United Kingdom for diseases of poultry caused by viruses, bacteria, and parasites. However, these vaccines often do not provide complete protection and can cause unwanted side effects. Several factors affect the potency of poultry vaccines including the type of vaccination used, the mechanism of delivery and the use of adjuvants. Advancements in technology have led to the study and development of novel vaccines and vaccine adjuvants for use in poultry. These induce stronger immune responses compared to current vaccine technology and have the potential to protect against multiple poultry diseases. This review aims to discuss existing poultry vaccine technology, the effect of delivery mechanisms of vaccine efficacy, the use of current and novel adjuvants, the ability to target antigen to antigen presenting cells, the use of probiotics, multivalent vaccines, and nanotechnology to enhance the potency of poultry vaccines.

Telomerase and telomeres are crucial in cancer cell immortalization, making them key targets for anticancer therapies. Currently, 6-thio-dG combined with the anti-PD1 inhibitor Cemiplimab is under Phase 2 clinical investigation (NCT05208944) in NSCLC patients resistant to prior immunotherapies. This study presents the design, synthesis, and evaluation of novel bimodular conjugate molecules combining telomere-targeting nucleoside analogs and phosphatidyl diglyceride groups. Among them, dihexanoyl-phosphatidyl-THIO (diC6-THIO) showed high anticancer activity with sub-µM EC50 values in vitro across various cancer cell lines. In mouse colorectal cancer models, diC6-THIO demonstrated strong anticancer effects alone and in combination with PD1/PD-L1 inhibitors. Administration of this compound resulted in the efficient formation of Telomere dysfunction Induced Foci (TIFs) in vitro, indicating an on-target, telomerase-mediated telomere-modifying mechanism of action for the molecule. Systemic treatment also activated CD4+ and CD8+ T cells while reducing regulatory T cells, indicating immune system enhancement. These findings highlight diC6-THIO as a promising telomere-targeting prodrug with dual effects on telomere modification and immune activation.

Cellulose-based materials are now commonly used, including in the field of acoustic comfort. Often presented as a less environmentally impactful alternative to traditional acoustic absorbents (such as melamine, glass wool, etc.), these cellulose-based materials are more frequently derived from recycling, thus undergoing in most cases the technical process allowing these cellulose fibers to be obtained, thus inheriting the acoustic properties of the latter, with limited or even non-existent control. This paper proposes a manufacturing process that allows for the production of cellulose foam with precise control over its porosity, pore size, and interconnections. In addition to exhibiting remarkable sound absorption properties, this process also enables the fabrication of gradient porous structures and other hybrid materials that can result in remarkable sound absorption properties.

Statement of problem: The stereo-optical method can be used for assessment of strains and deformations of different fixed or removable prosthodontic constructions. Material and methods: The study used two master casts of a lower jaw with bilateral terminal edentulous seats. Their topography was identical, with missing lower molars, the left lower second premolar, and the right canine and incisors, indicating a partially edentulous lower jaw according to Eichner's B3 (and C2) classification (i.e. Kennedy class 1). The control cast had conventional oval copings for overdenture. The experimental cast was almost the same as the control, with the exception of the surfaces simulating three specific milled copings covering the remaining tooth substance. Controlled loading was measured using a gnathodynamometer. Loading stages were at 400, 800, and 1000 N. Measurements of strain and displacement were provided by the Digital Image Correlation Method and the associated software. ‘Wilcoxon Lambda’ two sample tests based on the simple linear rank statistics were used in the analysis of differences in the displacement and deformation between the control rounded and experimental milled copings under loading numerical values. Results: It was found that smaller values of deformations are measured on milled copings when compared to the controls. There were statistically significant differences in displacement between the control rounded and experimental milled copings (Pr > |Z| = 0.001) as well as in deformations (Pr > |Z| = 0.0298). Conclusions: Experimental milled copings are less susceptible to deformation compared to the control conventional oval copings. These findings may have clinical significance in improvements of primary and secondary retention of overdentures on milled copings.

The properties of carbon powder filled nitrile rubber (NBR) were investigated. The effect of carbon powder content on the mechanical strength, vulcanization properties, mechanical properties, electrical conductivity, and thermal conductivity of NBR was explored. The purpose of the research is to pursue the optimal filling ratio and conditions of carbon powder to optimize the performance of rubber products.The reasonable filling range of carbon powder has been compared with N660 carbon black filled NBR and determined to evaluate the advantages and disadvantages of carbon powder. The suitable application scenarios of carbon powder is clarified .The research results indicate that carbon powder can delay the sulfurization of NBR in the sulfurization system. The research results indicate that carbon powder can delay the sulfurization of NBR. In terms of filling system, the tensile strength, tear strength, and elongation at break of NBR gradually enhance as the amount of carbon powder increases. Carbon powder can replace carbon black in the application of NBR to improve the comprehensive performance of NBR, which provides a new kind of reinforcing material for NBR.

This paper reexamines climate justice through the framework of environmental sociology, offering fresh perspectives on the intersection of social and ecological systems in the face of escalating global climate crises. It emphasizes that inequality lies at the heart of global climate politics, often obstructing pathways toward achieving true climate justice. Drawing from established traditions within environmental sociology—such as the new ecological paradigm, the post-growth society, and the environmental justice paradigm—the paper advocates for profound systemic and structural reforms in political and economic systems to tackle entrenched inequalities. By integrating these frameworks, the paper proposes a comprehensive model of climate justice, encompassing material, procedural, compensatory, and transformative justice. This holistic approach not only addresses environmental sustainability but also prioritizes social equity, ensuring that marginalized communities are included in the global response to climate change. The paper thus positions climate justice as a critical component of broader environmental and social transformation.

This study outlines the development and optimization of a Long Short-Term Memory (LSTM) network designed to analyze and classify time-series data from tribological experiments, with a particular emphasis on identifying stationary phases. The process of fine-tuning key hyperparameters was systematically optimized through Bayesian optimization, coupled with K-fold cross-validation, to minimize the inherent randomness associated with training neural networks. The refined LSTM network achieved a weighted average accuracy of 84%, demonstrating a high level of agreement between the network's identified stationary phases and those manually determined by researchers. This result suggests that LSTM networks can reliably mimic manual identification processes in tribological data, providing a promising avenue for automating data analysis. The study underscores the potential of neural networks to transcend their traditional role in predictive modeling within tribology, opening up new possibilities for their application across a broader spectrum of tasks within the field.

Parametric decay instabilities frequently occur in wave interactions. These instabilities typically have thresholds for wave amplitudes. They arise when nonlinearity, such as a spatial pressure inhomogenety, couples different waves. For these instabilities to arise, the waves must satisfy frequency and wavenumber matching conditions, which follow from the laws of energy and momentum conservation. However, parametric instabilities are not limited to wave interactions; the simples form of parametric instability is parametrically coupled oscillators. Magnetized plasma represents a unique wave medium in which numerous waves of various polarizations and spatial-temporal scales are easily excited and weakly damped. The greater the number of wave types, the easier it is to satisfy resonance conditions like the frequency and wavenumber matching conditions, and thus parametrically excite, or "drive" new waves from the initial wave. Therefore, in magnetoactive plasma, all known types of parametric instabilities can arise.

Magnetic nanoparticles coated with gold nanoparticles are hybrid nanostructures combining the magnetic properties of iron oxide with the optical and chemical versatility of gold. The iron oxide core gives the nanoparticles magnetic functionality, which is useful in magnetic resonance imaging (MRI), targeted drug delivery, and hyperthermia treatment. The gold coating enhances biocompatibility, provides resistance to oxidation, and allows for surface functionalisation with biomolecules for targeted applications. This combination makes these nanoparticles ideal for a range of biomedical applications, including diagnostics, therapeutics, and imaging, due to their magnetic, optical, and chemical properties. Transmission electron microscopy, dynamic light scattering, zeta potential and magnetisation of nanoparticles are key techniques that provide a comprehensive understanding of the nanoparticles’ size, structure, optical properties and magnetic behaviour, which are important factors for determining their potential use in various applications.

In the present study, we investigated to what extent the soybean has been used in in-dustrial and homemade sausage produced in Kosovo, as well as its potential impact on the fatty acid profile. In total, 63 samples, 42 industrial and 21 traditional sausages, were collected either from the market or the production site. All samples were tested by means of real-time PCR for the detection and quantification of soy content, as well as the GC-FID to determine the potential re-flection in the fatty acid profile. The presence of soy DNA was detected in 54 out of 63 samples. 41 out of 42 industrial sausage samples were positive for soy DNA, with an average ct value of 22.60 and a standard deviation (SD) of 4.28, whereas 13 out of 21 traditional sausage samples were positive for soy DNA, with a mean ct value of 23.36 and a standard deviation (SD) of 4.56. There was a statistically significant difference in means between industrial sausage and traditional sausage, p≤0.001 based on CT values (ANOVA test). We investigated the correlation between ct values in real-time PCR for soy DNA with each fatty acid content. There is a moderate correlation of soy DNA ct values with C16:0 palmitin (decrease), C18:0 stearic acid (decrease), C18:1 oleic acid (in-crease), and overall saturated fatty acids (decrease). With the exception of C14:0 Myristin, C18:1 Oleic, and C20:0 Arachin acids and monosaturated fats, the ANOVA test reveals a significant dif-ference in means between groups for the majority of the fatty acids between industrial sausages and traditional sausages. The current study demonstrates that the fatty acid composition of sau-sages is influenced by the amount of soy present in them. The extent to which other components affect the fatty acid profile is unknown. However, an increase in oleic acid and a decrease in stearic and overall saturated fatty acids are expected.

This study explores the use of Generative Artificial Intelligence (GAI) in assessing pilot fatigue risk by integrating facial recognition and physiological signals with Inertial Measurement Units (IMUs). By leveraging IMU technology's precise, real-time data on movement and combining it with GAI's advanced data analysis capabilities, the study aims to enhance the accuracy of fatigue prediction models. The analysis reveals that while traditional classifiers like Extreme Random Trees and Random Forests offer modest performance, advanced models such as Support Vector Machines and Naive Bayes demonstrate superior recall rates, highlighting their potential to identify true positives. This integration of AI and IMUs offers a promising approach to developing comprehensive, real-time fatigue monitoring systems, improving safety and efficiency in aviation by providing actionable insights and facilitating more effective fatigue management.

As is known, the Maxwell stress-energy tensor typically used in electromagnetism is not a canonical tensor in the sense of Noether, since its four-divergence is not zero in the presence of sources, in other words, outside of free space. Indeed, the result provided by the calculation of the four-divergence of this tensor is the opposite of the four-vector generalizing the Lorentz force density. The idea is to associate with it a tensor constructed from potentials and sources, such that its four-divergence is the opposite of that of the Maxwell tensor. The distribution of sources will also be analyzed in light of fluid mechanics, allowing us to account for its influence in terms of generated pressure.

Terpenoids are crucial secondary metabolites found in plants, essential for numerous physiological functions such as defense strategies, signal communication, and adaptation to environmental stresses. The enzymes referred to as Terpene Synthases (TPS) play crucial roles in the production of these compounds, fulfilling an essential role throughout the entire biosynthetic pathway.Despite their importance, systematic studies on the TPS genome in Physcomitrium patens (P. patens) remain inadequate. This research offers an extensive bioinformatics evaluation of the TPS genes in P. patens, aiming to clarify their possible functions in plant development, growth, and responses to stress. Preliminary examinations were conducted on the physicochemical characteristics, secondary protein structures, subcellular distribution, and genetic configurations of the TPS genes in P. patens. Initial analyses were performed on the physicochemical properties, protein secondary structures, subcellular localization, and gene structures of the TPS genes in P. patens. The findings demonstrate that TPS family members are dispersed across six chromosomes, with ten TPS family members identified. Analysis of conserved motifs revealed that the PpTPS members exhibit high sequence conservation, suggesting that these enzymes maintain stable structural characteristics during terpene synthesis. Further examination of evolutionary pressures indicated that TPS family members are predominantly subjected to purifying selection, which helps preserve the structural stability of TPS enzymes. Furthermore, an analysis of cis-acting elements indicated that TPS genes might respond to various factors, including light, plant hormones, tissue development, and environmental stressors. This suggests that TPS genes could be vital in managing how plants adapt to changes in their environment. Tissue expression profiling revealed that TPS family members have significant functions across various developmental stages and tissues. This is demonstrated by qRT-PCR analyses, indicating that the expression of the PpTPS gene is influenced by abscisic acid (ABA), methyl jasmonate (MeJA), sodium chloride (NaCl), and polyethylene glycol (PEG). The findings suggest that the PpTPS genes could play an essential role in the functional development of plant leaves and in their responses to abiotic stress.In summary, this research presents a comprehensive examination of the TPS family members in P. patens, yielding important perspectives on the functions of the PpTPS7 and PpTPS8 genes in the development of leaves and responses to abiotic stress.The findings contribute to a deeper understanding of the functions and regulatory mechanisms of TPS genes and present new perspectives and strategies for the enhancement and application of P. patens.

The dawn of quasispecies theory revolutionized our understanding of viral evolution and pathogenesis. This theory conceptualises viruses as dynamic populations of closely related but genetically diverse variants that constantly mutate and adapt to environmental pressures. Quasispecies dynamics govern key aspects of virus-host interactions, such as adaptive evolution, immune evasion, drug resistance, and host tropism. In this article, we discuss the fundamental role of quasispecies theory in elucidating viral fitness landscapes, shaping antiviral strategies, and predicting viral emergence and evolution. We provide a concise overview of the original quasispecies model and its latest advancements, which enable the study of the connection between viral dynamics and the significant genetic diversity exhibited by viruses. We then point out some key features of virus dynamics that need to be incorporated into quasispecies theory. We continue with examples of convergence between theory and real viruses by discussing theoretical results supported by RNA virus data and vice versa. Next, we discuss the need to extend the concept of sequence space beyond the classical hypercube towards more complex, multidimensional connected sequence spaces that we have called ultracubes. Finally, we highlight the necessity of developing multi-scale models to understand how viral evolutionary dynamics within a host can affect epidemiological patterns. We also examine the limitations of quasispecies theory in predicting virus evolution and emergence.

The increasing demands on global resources due to technological development driven by consumer expectations and demands have resulted in significant problems with ecological sustainability and material availability. The creation of biocomposites has resulted in notable advancements in the green industry within the materials science area this century, owing to concerns regarding sustainability and the environment. Globally, there is a surge in the creation of highly efficient materials derived from natural resources. In aviation applications, plant-fiber-supported polymer composite materials are becoming increasingly popular. Aerospace materials are typically used in aircraft construction as structural materials to support loads throughout different flight phases. There are many diverse mechanical qualities of natural fibres; therefore, selecting one for the interior parts of an aircraft cabin based only on its attributes leads to a multiple-attribute decision-support issue. In this paper, the effective natural fibre and polymer choice for use as reinforcing materials in composite materials is represented for the composite materials’ improvement to aircraft cabin luggage for aerospace implementations. This study can guide material designers in investigating different hybrid materials with the most effective natural fiber and polymer obtained by hierarchical strategy by elucidating the effective material choice to meet the criteria determined for the aircraft cabin luggage. For this purpose, the definitive rankings of the twelve polymers and sixteen natural fibers in terms of performance score were assessed using hierarchical strategy methodology.

This study investigates the impact of stakeholder participation on the efficiency of irrigation projects by the implementation of Farmers Water User Committees (FWUCs). Utilising a difference-in-difference methodology, the research analyses data from 79 irrigation projects over a 13-year period. The findings reveal a statistically significant positive correlation between FWUC establishment and improved project effectiveness, even when controlling for variables such as project size, age, and socio-economic factors. Smaller, newer projects exhibited higher effectiveness, whilst remote locations faced greater challenges. The temporal analysis indicates that the benefits of participation accrue gradually, underscoring the importance of sustained implementation. These results carry significant implications for public enterprise reform, particularly in irrigation management. The study contributes to the growing body of evidence supporting the efficacy of stakeholder participation in public enterprise management, offering valuable insights for policymakers seeking to enhance the efficiency and sustainability of irrigation systems.

In the fields of partnership research and social innovation, there have been an increasing number of calls for evidence regarding the kind of collaborative multi-level governance structures that might support large scale transformation processes, specially towards climate-neutral cities. This paper conceptualizes a new type of intermediary actor; the Systemic Collaborative Platform (SCP). Using the example of a multi-stakeholder arrangement set up to design and implement Madrid’s Climate Neutrality Roadmap, the key features of an SCP include a focus on multi-stakeholder and cross-sectoral collaboration for public policy development, in this case operating at both a systemic level and a city scale, and a strong link to a key actor within this regime (a city council). Our study reveals how a SCP can contribute to articulation of a shared mandate among city actors and enhance the efficiency and effectiveness of a targeted transition by attracting, aligning and managing a wide and diverse organizational ecosystem through distributed facilitation, collaborative leadership and continuous learning.