Accelerating, exact, explicit and simple solutions of relativistic hydrodynamics allow for a simple and natural description of highly relativistic p+p collisions. These solutions yield a finite rapidity distribution, thus they lead to an advanced estimate of the initial energy density of high energy collisions. We show that such an advanced estimate yields an initial energy density in $\sqrt{s}=7$ and 8 TeV p+p collisions at LHC around or above the critical energy density from lattice QCD, and a corresponding initial temperature above the critical temperature from QCD and the Hagedorn temperature. This suggests that the collision energy of the LHC corresponds to a large enough initial energy density to create a non-hadronic perfect fluid even in pp collisions. %We also show, that several times the %critical energy density may have been reached in high multiplicity events, hinting at a non-hadronic medium created in %high multiplicity $\sqrt{s}=7$ and 8 TeV p+p collisions.

An increase in plant-sourced (PS) nutrient intake is promoted in support of a sustainable diet. PS dietary minerals and proteins have bioactive properties that can affect bone health and the risk of fracture. In a group randomised, cross-over, design, this study evaluated the post-ingestion, temporal pattern of change in arterialised ionised calcium (iCa), parathyroid hormone (PTH), C-terminal crosslinked telopeptide of type I collagen (CTX) and procollagen type 1 amino-terminal propeptide (P1NP) for 4 hours following ingestion of a novel supplement (SUPP) containing a PS marine multi-mineral + PS protein isolate. A diurnally matched intake of mineral water was used as a control (CON). Compared to baseline, the change in iCa concentration was 0.022 (95%CI, 0.006 to 0.038, p = 0.011) mmol/l greater in SUPP than CON, resulting in a -4.214 (95%CI, -8.244 to -.183, p = 0.042) pg/mL mean reduction in PTH, a -0.64 (95%CI, -0.199 to -0.008, p = .029) ng/mL decrease in the biomarker of bone resorption, CTX, and no change in biomarker of bone formation, P1NP. Used as a dietary supplement, or by incorporation into a food matrix, the promotion of PS marine multi-mineral and PS protein isolates may contribute to a more sustainable diet and overall bone health.

Mosquitoes genus Aedes are the most important arthropod disease vector. Dengue Virus (DENV) and Chikungunya Virus (CHIKV) are the main arboviruses distributed in the world. Based on entomo-virological surveillance, appropriating public health strategies can be addressed to contain cases and control outbreaks. This study aims to show the potential performance of two new molecular methods for detecting DENV serotypes and CHIKV in mosquitoes. Mosquitoes were collected in urban areas and sylvatic areas between July to August 2023, DENV and CHIKV were screened using new multiplex RT-PCR and RT-q PCR. A total of 2150 mosquitoes were trapped including 976 Aedes (959 Ae. egypti, 6 Ae. furcifer and 11 Ae. Vittatus) and 1174 Culex from 39 pools of a maximum of 30 mosquitoes each, tested by molecular screening, 7.7% (3/39) were positive for DENV, DENV-1 was detected in one pool (1/3), and DENV-3 in two pools (2/3). All the pools were negative for CHIKV. The overall minimum infection rate (MIR) of DENV in this study was 3.07 (95% CI: 2.24 —19.86). This study shows the usefulness of our new molecular tools in DENV serotypes and CHIKV surveillance.

Abstract Introduction: An important indicator of a hospital's quality of care is the frequency of visits to the emergency department (ED). If a patient returns to the emergency room (ED) shortly after being evaluated or treated, it is generally assumed that their initial evaluation or treatment was inadequate. Objectives: The purpose of this study is to identify the main reasons for patient revisits to the emergency department in Hail. Studies suggest that researchers usually report the reasons for revisiting patients after 72 hours to patients themself. Therefore, alternative hypotheses will attribute the reasons to the system or physician's skill. To test these hypotheses, a methodology was developed. Method: The study analyzed patients discharged from King Khalid Hospital within 72 hours of discharge, involving all adults, regardless of health status or location Results: In February 2019, 17461 ED visits occurred, with 11% returning within 72 hours. In February 2022, 880 of 8749 visits resulted in a 10% return visit, with 30 randomly selected return visits.Conclusion: Increased community awareness post-COVID-19 may explain differences in ED revisit rates between 2022 and 2019, with system errors and patient information re-entry being associated

Coproporphyrins I and III (CP-I and CP-III) are established as substrates of hepatic sinusoidal organic anion transporting polypeptides (Oatps), multidrug resistance-associated protein 3 (Mrp3), and canalicular transporter Mrp2. We aimed to evaluate the potential of plasma CP-I and CP-III concentrations to indicate functional changes in hepatic transporters in nonalcoholic stea-tohepatitis (NASH) rodent models using modeling and simulation approach. Mechanistic copro-porphyrins (CP-I and CP-III) models in rats and mice were constructed based on metabolism, transport, and elimination pathways in rodents. To parameterize the rat mechanistic model, we measured CP concentrations in plasma, liver, bile, and urine in healthy control Sprague Dawley rats. The mouse mechanistic model was parameterized using published data. The rat and mouse CP models described the steady-state levels of CP-I and CP-III in plasma, liver, and bile. The model recapitulated the observed high plasma CP-III / CP-1 ratio (9- and 3-fold in rats and mice, respec-tively) and elimination pathways of CP-I (>90% via biliary secretion) and CP-III (equal via bile and urine). Rat CP model was further validated with the published rat fistula model. The simulated increased plasma CP-I concentrations (4-fold), resulted from decreased Oatp activity (0.6-fold) and increased Mrp3 activity (3-fold) were comparable to those observed in bile-duct ligated NASH model. Sensitivity analysis revealed that 90% inhibition of Oatp and Mrp2 leads to a 4-fold and 2.5-fold increase in plasma CP-I levels, respectively. Additionally, we demonstrated the utility of the mechanistic CP models in testing hypothesis and understanding the mechanisms of the ob-served plasma CPs disposition in the Oatp knockout (KO) mice, bile-duct ligation NASH mice, and Mrp2 deficient TR- rats. Collectively, using a mechanistic model, we conclude that CP-I is a robust and predictable marker for assessing change in the activity of Oatps and Mrps in animal models. Our analysis suggests that efflux transporters (Mrp2 and Mrp3) can play an important role in the disposition of CP-I along with Oatp transporters in rodents.

Purpose: The goal of this article was to introduce a new technique for root coverage (RC), the Mixed-Thickness Tunnel access (MiTT), approaching a full-split design, showing the results obtained in a case series and demonstrating it step-by-step. Methods: Healthy individuals, non-smokers, and non-diabetics, who were diagnosed with gingival recession (GR) type 1 or 2 (RT1 or RT2). After all necessary evaluations, prophylaxis was performed 14 days before the surgical procedure. Then, after the basics clinical conduct and anesthesia, one or two vertical incision(s) on the mucosa (around 1-2 mm apical to the MGJ), lateral to the papilla base, were done. Initial detachment of the mucosa from the muscles (split design); it was permitted (but not mandatory) to do intrasulcular incisions; from the MGJ to coronal, subperiosteal access was done to raise the full-thickness tunnel. It must communicate up to the gingival sulcus area and the papilla’s base, keeping the papilla’s tip intact. A connective tissue graft was harvested, which was inserted through the linear incision or intrasulcularly. Interrupted sutures were done and may be used as adjunctive material. Results: Nine healthy individuals (7 females and 2 males) aged 19 and 43 years were enrolled. They were treated following the MiTT steps. There were four cases with a single GR, 2 patients with 2 teeth involved, and three with 3 or 4 GR. Seven cases were RT1 and two RT2. All RT1 cases achieved 100% RC, while the mean RC obtained for RT2 was around 80%. Conclusion: MiTT can be considered a more straightforward approach for minimally invasive surgical technique, which is a feasible option to treat RC with a high success rate, predictability, and esthetic preservation. There is a technical sensitivity to performing the full-split design procedure.

The Sulfur Dioxide (SO2) compound is a primary environmental pollutant worldwide, whereas elemental Sulfur (S) is a global commodity possessing a variety of industrial as well as commercial functions. The chemical relationship between poisonous SO2 and commercially viable elemental S has motivated this investigation using Density Functional Theory calculation of the relative transition state barriers for the 2-step Dehydro-sulfurization oxidation-reduction reaction. Additionally, doubly-charged nanoscale platelet Molybdenum Disulfide (MoS2), Armchair (6,6) Carbon Nanotube, 28-atom Graphene nanoflake (GR-28), and Fullerene C-60 are utilized as catalysts. The optimal heterogeneous and homogeneous catalysis pathways of the 2-step oxidation-reduction from SO2 to elemental S are further inspired by the biomimicry of the honeybee species multi-step bio-catalysis of pollen conversion to organic honey. Potential applications include environmental depollution, the mining of elemental sulfur, and the functionalization of novel technologies such as the recently patented aerial and amphibious Lynchpin TM drones.

After a 1.5 year screening survey in the lagoons of Western Greece in order to isolate and culture sturdy species of microalgae for aquaculture or other value added uses, as dictated primarily by a satisfactory potential for their mass-culture, five species emerged and their growth was monitored in laboratory conditions. Amphidinium carterae, Nephroselmis sp., Tetraselmis sp. (var. red pappas), Asteromonas gracilis and Dunaliella sp. were batch cultured using low (20 ppt), sea (40 ppt) and high salinity (50 or 60 or 100 ppt) and in combination with a low (2000 lux) and high (8000 lux) intensity of illumination. The results exhibited that all these species can be grown adequately in all salinities and with best growth in terms of maximum cell density, specific growth rate (SGR) and biomass yield (g dry weight/L) at high illumination (8000 lux). The five species examined exhibited different responses in the salinities used, Amphidinium clearly does best in 20 ppt far better than 40 ppt and even more than 50 ppt. Nephroselmis and Tetraselmis grow almost the same in 20 and 40 ppt and less well in 60 ppt. Asteromonas does best in 100 ppt although it can grow quite well in both 40 and 60 ppt. Dunaliella grows equally well in all salinities (20-40-60 ppt). Concerning productivity as maximum biomass yield at the end of the culture period, first rank is occupied by Nephroselmis with ~3.0 g d.w./L, followed by Tetraselmis (2.0 g/L), Dunaliella (1.58 g/L), Amphidinium (1.19 g/L) and Asteromonas (0.7 g/L) with all values recorded at high light (8000 lux).

Despite extensive investigations of the Depression Anxiety Stress Scales-21 (DASS-21) since its development in 1995, its factor structure and other psychometric properties still need to be firmly established, with several calls for revising its item structure. Employing confirmatory factor analysis (CFA), this study examined the factor structure of the DASS-21 and five shortened versions of the DASS-21 among psychiatric patients (N = 168) and the general public (N = 992) during the COVID-19 confinement period in Saudi Arabia. Multigroup CFA, Mann Whitney W test, Spearman’s correlation, and coefficient alpha were used to examine the shortened versions of the DASS-21 (DASS-13, DASS-12, DASS-9 (two versions), and DASS-8) for invariance across age and gender groups, discriminant validity, predictive validity, item coverage, and internal consistency, respectively. Compared with the DASS-21, all three-factor structures of the shortened versions expressed good fit, with the DASS-8 demonstrating the best fit and highest item loadings on the corresponding factors in both samples (χ2(16, 15) = 16.5, 67.0; p = 0.420, 0.000; CFI= 1.000, 0.998; TLI = 0.999, 0.997; RMSEA = 0.013, 0.059, SRMR = 0.0186, 0.0203). It expressed configural, metric, and scalar invariance across age and gender groups. Its internal consistency was comparable to other versions (α = 0.94). Strong positive correlations of the DASS-8 and its subscales with the DASS-21 and its subscales (r = 0.97 to 0.81) suggest adequate item coverage and good predictive validity of this version. The DASS-8 and its subscales distinguished the clinical sample from the general public at the same level of significance expressed by the DASS-21 and other shortened versions, supporting its discriminant validity. Neither the DASS-21 nor the shortened versions distinguished patients diagnosed with depression and anxiety from other conditions. The DASS-8 represents a valid short version of the DASS-21, which may be useful in research and clinical practice for quick identification of individuals with potential psychopathologies. Diagnosing depression/anxiety disorders may be further confirmed in a next step by clinician-facilitated examinations. Brevity of the DASS-21 would save time and effort used for filling the questionnaire and support comprehensive assessments by allowing the inclusion of more measures on test batteries.

In this paper we have defined the effect of bulk viscosity on Quintessence model and scaler field potential as well as on classical field. We have shown the same effect for modified gravity with f(R,T)= R+f(T). In the derivation we have predicted the possibility of time dependent evolution of gravitational constant G and anisotropy.

A bread wheat line (N11) and a disomic 2D(2R) substitution triticale line have been crossed and backrossed four times. At each step electrophoretic selection for the seeds that possessed, simultaneously, the complete set of high molecular weight glutenin subunits of N11 and the two high molecular weight secalins of rye, present in the 2D(2R) line, was carried out. Molecular cytogenetic analyses of the BC4F5 generation have revealed that the selection carried out had produced a disomic addition line (2n=44). The pair of additional chromosomes consisted of the long arm of chromosome 1R (1RL) from rye fused with the satellite body of the wheat chromosome 6B. Rheological analyses revealed that the dough obtained by the new addition line had higher quality characteristics when compared with the two parents. The role of the two additional high molecular weight secalins, present in the disomic addition line, in influencing improved dough characteristics is discussed.

Under one-health perspective and the worldwide antimicrobial resistance concern, we investigate extraintestinal pathogenic Escherichia coli (ExPEC), uropathogenic E. coli (UPEC), and multidrug resistant (MDR) E. coli from 197 isolates recovered from healthy dogs in Spain between 2013 and 2017. Ninety-one (46.2%) isolates were classified as ExPEC and/or UPEC including 50 clones, among which (i) four clones were dominant (B2-CH14-180-ST127, B2-CH52-14-ST141, B2-CH103-9-ST372 and F-CH4-58-ST64815) and (ii) 15 had been shown to be displayed by previously published isolates causing extraintestinal infections in humans. Twenty-eight (14.2%) isolates were classified as MDR, associated with B1, D and E phylogroups and included 24 clones, of which eight had also been identified among human isolates causing infections. We selected 23 ST372 strains, 21 healthy dogs faecal isolates and two human clinical isolates for whole genome sequencing and built a SNP-tree with these 23 genomes and 174 genomes (128 from canine strains and 46 from human strains) obtained from public databases. The analysis of these 197 genomes allowed to identify six clusters. Cluster 1 comprised 74.6% of the strain genomes that were mostly composed of canine strain genomes (P < 0.00001). Clusters 4 and 6 also included canine strain genomes, while clusters 2, 3 and 5 were significantly associated with human strain genomes. All these findings suggest that dogs are reservoirs of ExPEC, UPEC and MDR E. coli isolates with zoonotic potential.

The Late Bronze Age on the territory of Southern Transurals is represented by two major archeological cultures: Srubnaya and Andronovskaya (Alakul culture and Fyodorovskaya – type). Their interaction of constitutes a special mix of material cultures which preserves common features of two independent, Srubnaya and Andronovskaya cultures, but also creates novel local material features. These cultural groups are also known to have brought to the region the technology of bronze production. This is evidenced, amongst others, by the proximity of the largest copper mining in the region, Kargaly mines Chernykh (2002). New methods to produce ceramics and to work bones were also developed, combining two traditions, coming from Srubnaya and Andronovskaya cultures respectively. Importantly, the features of these cultures are commonly encountered together in a single cultural horizon across the distribution ares. These diffusion processes took place in a vast area (more than 120,000 km²) andwere reflected in archeological micro-district of the Urshak river basin. We present here the most recent results of the scientific examination of the Late Bronze Age settlements in southern Transurals and attempt to address a peculiar cultural co-habitation of two distinct cultural groups in this region. We also discuss their synchronism based on absolute dates and elaborate on this cultural syncretism in the entire territory of the Volga-Ural region.

Maternal gut and breast milk (BM) are key in vertically transmission bacteria to infants, shaping their gut microbiota in early life. Although the establishment of early gut microbiota is known, the role of the combined influence of maternal factors and newborn characteristics are not explored. In this study we aimed to assess the influence of maternal BMI and total body fat, age, delivery mode, and newborn sex on the diversity and composition of the BM and gut microbiota (GM) in mother- newborn dyads. In this cross-sectional study, of the 986 pregnant women candidates, 53 participated, and finally, 40 mother-newborn dyads exclusively breastfeeding at 20-28 days post-partum were included. Metataxonomic profiling of DNA extracted from BM and fecal samples was conducted using 16S rRNA sequencing. Globally, the findings offer valuable insights that excessive adiposity, age and C-section delivery influence on a lower abundance of specific taxa in the BM, maternal gut, and gut newborns. Also, the simultaneous analysis of maternal factors and newborn characteristics shows that maternal age and newborn sex explain an important variation in the microbiota composition. These results add to understanding of the intricate interplay between maternal factors and the microbial communities that influence early-life gut and BM microbiota.

Background: Heart failure (HF) remains a challenging healthcare issue, necessitating innovative therapies like cardiac resynchronization-defibrillation therapy (CRT-D). However, defining CRT-D responders lacks uniformity, impeding effective clinical evaluation. This study explores diverse CRT-D responder definitions, encompassing functional, echocardiographic, and laboratory criteria. Materials & Methods: A single-center study involving 132 CRT-D patients scrutinized responder criteria, including NYHA stage, LVEF increase, and proBNP decrease. Statistical analyses, such as Kaplan–Meier curves and Cox hazard regression, were employed to evaluate responder characteristics and survival outcomes. Results: Responder rates varied across criteria, revealing nuanced patient profiles. CRT-D responders, defined by NYHA decrease, LVEF increase, or proBNP decrease, exhibit improved survival rates after 2 and 3 years (p < 0.050). Young age, absence of recent myocardial infarction, and normal right ventricular, echocardiographic parameters emerge as predictors for positive response. In part, drug-based HF therapy correlates with increased responder rates. Cox regression identified LVEF ≥ 5% and proBNP decrease ≥ 25% as independent predictors of extended survival. Conclusions: CRT-D responder definitions exhibit considerable variability, emphasizing the need for a nuanced, patient-centered approach. Factors like right ventricular function, drug therapy, atrial fibrillation, and renal function influence responses. The study enriches our understanding of CRT-D response, contributing to the foundation for personalized HF management.

We present a statistical study of the physical properties of Medium Scale Traveling Ionospheric Disturbances (MSTIDs) registered over the Mexican territory during 2018 and 2019 (solar minimum). The analysis is based on Total Electron Content (TEC) approximations using data from the ground-based Global Navigation Satellite System (GNSS) receivers at different locations divided into three regions according to geomagnetic coordinates: North, Center, and South. The MSTIDs were classified into day and night events, and only geomagnetically quiet days were considered to reduce the solar influence. We explored fundamental aspects of the MSTIDs, such as differences between day and night events, occurrence patterns, and geographical differences. Our results show some similarities with the occurrence periods of gravity waves, exhibiting a high activity during summer and winter. For this period, however, most events occurred between 20:00 PM and 04:00 AM UT. Moreover, the disturbances’ energy was stronger (i.e., large amplitudes and power) around the sunset terminator for the three regions. This suggests that the density gradient generated when the sunlight falls benefits MSTIDs formation.

Toxoplasmosis is a zoonosis of warm-blooded animals, affecting also humans, caused by Toxo-plasma gondii, an obligate intracellular parasite with a complex biological cycle. Toxoplasmosis is considered a re-emerging zoonosis and an important public health threat, also for the absence, up to now, of efficient vaccines and preventive measures. Sources of transmission to humans are environmental or food-borne, mainly through the consumption of raw and undercooked meat, predominantly of Sus scrofa, considered highly susceptible to T. gondii. Mainly in the last dec-ades, an effective strategy to counter animal infectious diseases was based on the discovery of resistance immuno-genetic markers, possibly to be used for association studies between geno-typic and phenotypic traits and consequently in Marker Assisted Selection. Until now, this gen-otyping approach has never been adopted for T. gondii infection, so this study aimed, for the first time, to fill this gap. In particular, pigs, reared in different farms of Central Italy, were serologically characterized by an ELISA assay performed on diaphragm meat juice. Out of 179 tested animals, 98 resulted seropositive (54.74%), 57 seronegative (31.84%) and 24 doubtful (10.6%), underlining a possible re-emerging diffusion of this protozoan in the investigated areas. Atten-tion was firstly focused on IL-18 gene, encoding for a pro-inflammatory cytokine that plays a key role starting from the upstream steps of the immunity pathway towards T. gondii. A RT-PCR assay followed by Sanger sequencing of IL-18 cDNA was de novo developed. For this interleukin, at this stage, genetic analysis has not highlighted significant polymorphic variations compared to the reference sequence, except for a seropositive animal. However, the outcomes of this pre-liminary innovative study will be investigated in depth analyzing other relevant genetic re-gions and other target genes.

Background: Breast cancer remains a significant health concern among women globally. Despite advancements in awareness and diagnostic techniques, it persists as a leading cause of death, with profound impacts on affected individuals' quality of life. Primary and secondary prevention, including regular screenings and practices like Breast Self-Examination (BSE), are pivotal in ensuring early diagnosis. The NHS in Italy offers screenings for women aged 50-69 every two years, managed by the Local Health Authority. However, the participation rates, especially among the Chinese female population residing in Italy, are not well-understood. Methods: Using a snowball method, we electronically disseminated a survey to investigate how Chinese women living in Italy engage with available NHS screening programs. The survey also explores their practice of BSE, the use and impact of technological tools on prevention, and aims to understand their depth of knowledge and misconceptions about breast cancer. Results: The data revealed a significant gap in breast cancer screening adherence and knowledge among Chinese women in Italy, with a notable discrepancy between the general population and those who have previously encountered cancer. Conclusions: The results highlight the urgent need for interventions that are culturally sensitive, stressing that these actions are not only desirable but essential.

Binary mixtures of surfactants build a binary mixed micelle in which the ratio of surfactants usually differs from the initial ratio of surfactants in their binary mixture. The thermodynamic stabilization of the binary mixed micellar pseudophase about the hypothetical ideal state (intermolecular interactions between the different particles and the conformational states of the particles are identical to those of monocomponent states) is described by the molar excess Gibbs free energy (gE). The dependence of gE on the molar fraction of surfactant i (xi) from the binary mixed micelle can be described by a symmetric function (symmetry is described to the line parallel to the y-axis and passes through xi = 0.5) or by an asymmetric function. Theoretical analysis (canonical partition function, conformational analysis) examines how the presence of different polar functional groups, some of which are sterically shielded from the steroid skeleton of bile salt (surfactant), affect the symmetry of the function gE of the binary mixed micelle of the cholic acid anion (bile salt) and classical cationic surfactant (hydrophobic tail and polar head). Suppose the steroid skeleton of the bile salt contains non-sterically shielded polar groups (or the temperature is relatively high). In that case, gE is a symmetric function. At the same time, if the steroid skeleton also contains sterically shielded polar groups, then the gE function is asymmetric.

The topic of this paper is the airborne evaluation of ICESat-2 Advanced Topographic Laser Altimeter System (ATLAS) measurement capabilities and surface-height-determination over crevassed glacial terrain, with a focus on the geodetical accuracy of geophysical data collected from a helicopter. To obtain surface heights over crevassed and otherwise complex ice surface, ICESat-2 data are analyzed using the density-dimension algorithm for ice surfaces (DDA-ice), which yields surface heights at the nominal 0.7~m along-track spacing of ATLAS data. As the result of an ongoing surge, Negribreen, Svalbard, provided an ideal situation for the validation objectives in 2018 and 2019, because many different crevasse types and morphologically complex ice surfaces existed in close proximity. Airborne geophysical data, including laser altimeter data (profilometer data at 905~nm frequency), differential Global Positioning System (GPS), Inertial Measurement Unit (IMU) data, on-board-time-lapse imagery and photographs, were collected during two campaigns in summers of 2018 and 2019. Airborne experiment setup, geodetical correction and data processing steps are described here. To date, there is relatively little knowledge of the geodetical accuracy that can be obtained from kinematic data collection from a helicopter. Our study finds that (1)~Kinematic GPS data collection with correction in post-processing yields higher accuracies than Real-Time-Kinematic (RTK) data collection. (2)~Processing of only the rover data using the Natural Resources Canada Spatial Reference System Precise Point Positioning (CSRS-PPP) software is sufficiently accurate for the sub-satellite validation purpose. (3)~Distances between ICESat-2 ground tracks and airborne ground tracks were generally better than 25~m, while distance between predicted and actual ICESat-2 ground track was on the order of 9~m, which allows direct comparison of ice-surface heights and spatial statistical characteristics of crevasses from the satellite and airborne measurements. (4)~The Lasertech Universal Laser System (ULS), operated at up to 300~m above ground level, yields full return frequency (400~Hz) and 0.06-0.08~m on-ice along-track spacing of height measurements. (5)~Cross-over differences of airborne laser altimeter data are 0.1918 $\pm$ 2.385~m along straight paths over generally crevassed terrain, which implies a precision of approximately 2.4~m for ICESat-2 validation experiments. (6)~In summary, the comparatively light-weight experiment setup of a suite of small survey equipment mounted on a Eurocopter (Helicopter AS-350) and kinematic GPS data analyzed in post-processing using CSRS-PPP leads to high accuracy repeats of the ICESat-2 tracks. The technical results (1)-(6) indicate that direct comparison of ice-surface heights and crevasse depths from the ICESat-2 and airborne laser altimeter data is warranted. The final result of the validation is that ICESat-2 ATLAS data, analyzed with the DDA-ice, facilitate surface-height determination over crevassed terrain, in good agreement with airborne data, including spatial characteristics, such as surface roughness, crevasse spacing and depth, which are key informants on the deformation and dynamics of a glacier during surge.

Since December 2019, a rapid increase in the number of SARS-CoV-2 (COVID-19) cases was reported worldwide, despite strict infection control and lock down measures. Current paper investigated the actual facts behind this rapid increase in the number of cases. Study of genomic sequence reveals that domestic and wild animals were likely ancestors and zoonotic source for SARS-CoVs, MERS-CoVs, and SARS-CoV-2. Strong evidence suggest that these viruses already existed and replicated in animals and humans during past several decades, exhibiting diverse mutations, evolutions and self-limiting diseases, except during outbreaks. Serious zoonotic reservoir investigations are required to investigate animal transmission of SARS-CoVs and SARS-CoV-2 to limit current pandemic. This might be the reason of increasing number of cases via animals. SARS-CoV-2 has been retrospectively isolated in different studies in August 2019, several months before Wuhan announced. Hence, there is a possibility that viruses existed, went undetected, infecting subclinically, in past several years, and SARS-CoV-2 antigens and neutralizing antibodies may have been present in humans since long time. This might be another reason of increasing number of cases by screening as mass screening and antigen or antibody testing was not carried out in the past years. Randomized controlled trials are required to investigate human to human transmission by touch, as the current evidence is limited with conflicting results. As all SARS-CoVs are basically respiratory viruses, droplet precautions and infection control measures are essential, especially for hospital staff. Increased number of SARS-CoV-2 asymptomatic, or subclinical cases are detected worldwide. This silent phase of transmission can be beneficial for humans. Lack of symptoms eventually lessen virus transmission and reduce the pathogen's long-term survival and provide humoral herd immunity up to several years. Hence, seropositivity with diverse antibodies develops against mutating SARS-CoVs which will confer strong immunity during epidemics. Strategies such as identification, contact tracing and quarantine are costly and practically difficult. Hence, asymptomatic persons can continue their work with droplet precautions and standard infection control procedures, while symptomatic or sick persons can isolate themselves in their homes without the need for strict quarantine until clinical recovery, with reduced hospital visits and minimizing chances of hospital acquired infections. RT-PCR has low sensitivity and specificity, carries a high risk of handling live virus antigens, and requires difficult protocols. As viral load also sharply declines after few days of onset of infection, this technique might overlook infection. Furthermore, SARS-CoV-2 infection may be present in blood when oropharyngeal swabs are negative by RT-PCR. Additionally, RT-PCR usually gives false negative and false positive results and must be interpreted cautiously. This might be again a reason of increasing number of cases by false positive RT-PCR reporting. Moreover, antibodies against SARS-CoVs develop robustly in serum even by reduced amount of antigens. In contrast to RT-PCR, ELISA for diagnosing antibodies against SARS-CoV-2 demonstrates 100% specificity and 100% sensitivity, even in clinically asymptomatic individuals. These antibodies can be used for serologic surveys, monitoring and screening. However, screening tests for SARS-COV-2 should be avoided in unhygienic public places by nasopharyngeal swabs, which carry a high risk of further transmission, co-infection or superinfection. Such highly infectious virus must be isolated and tested in highly sterilized laboratory. Further strict international laws and policies are required to stop the possible spread of experimental viruses, biological warfare and bioterrorism.

Background: Primary deficit schizophrenia (DS) is characterized by enduring negative symptoms and represents a qualitatively different disease entity with respect to non-deficit schizophrenia (NDS). No studies investigated the association between the enzyme paraoxonase 1 (PON1) and DS and its phenomenology. Methods: In this case-control study, Thai women and men, aged 18-65 years, were divided in DS (n=40) and NDS (n=40) and were compared to controls (n=40). PON1 activities against 4-(chloromethyl)phenyl acetate (CMPA) and phenylacetate were determined. Moreover, subjects were genotyped for their PON1 Q192R polymorphism and IgA levels responses directed to Gram-negative bacteria were measured. Results: DS is significantly associated with the QQ genotype and the Q allele as compared with NDS and controls. PON1 activities are significantly and inversely associated with negative symptoms, formal thought disorders, psychomotor retardation, excitation and DS. The presence of the Q allele is associated with increased IgA responses to Pseudomonas aeruginosa, Morganella morganii, and Pseudomonas putida as compared with RR carriers. Conclusions: The PON1 Q allele and lower PON1 activities especially against CMPA are associated with DS, indicating lowered quorum quenching abilities as well as lowered defenses against lipoperoxidation and immune activation. It is suggested that lowered PON1 activity in DS constitutes an impairment in the innate immune system which together with lowered natural IgM may cause lower immune regulation thereby predisposing towards greater neurotoxic effects of immune-inflammatory, oxidative and nitrosative pathways and Gram-negative microbiota.

Chagas disease, caused by Trypanosoma cruzi, leads to severe complications in 30% of infected individuals, including acute myocarditis and chronic fibrosing cardiomyopathy. Despite the significant burden of the disease, there is currently no licensed vaccine available to prevent it. This study aimed to evaluate the mucosal and systemic immunogenicity as well as the prophylactic efficacy of a mucosal vaccine and its impact on both acute and chronic cardiomyopathy. The results showed that nasal administration of Trans-sialidase (TS) plus c-di-AMP (TS+A). TS+A vaccine elicited NALT expression of IFN-γ, IL-17a, and IL-4 mRNA, and nasal-specific IgA production. Ex vivo challenge with TS also triggered enhanced proliferation of lymphocyte from the NALT, sentinel cervical lymph node and spleen. TS+A immunization increased plasma levels of Th1/Th2/Th17 cytokines and an evident cellular response to judge enhanced delayed-type hypersensitivity responses following TS footpad challenge. After oral infection, TS+A-vaccinated mice showed significantly reduced parasitemia and parasite load in heart, muscle and intestine, while markers of hepatic and muscle damage as well as clinical manifestations of acute infection are strongly diminished. TS+A also attenuated acute myocarditis and heart expression of inflammatory markers. The protection conferred by TS+A extended into the chronic phase, where it resulted in a clear reduction in chronic myocarditis, fibrosis, and functional electrocardiographic abnormalities, associated with decreased expression of the pro-fibrotic TGF-β. These results revealed that it is possible to develop a mucosal vaccine against T. cruzi based on TS and c-di-AMP, capable to reduce the development of Chagas cardiomyopathy, the hallmark of Chagas disease.

Limoncella of Mattinata, a rare and ancient Mediterranean citrus fruit, was investigated by sequence analysis of the ribosomal internal transcribed spacer regions, which assigns it as a variety of Citrus medica L. Morphological, chemical, and biomolecular approaches were used to characterize flavedo and albedo, parts usually rich of bioactive compounds. The morphological findings showed albedo and flavedo cellular structures as “reservoirs” of nutritional components. Both albedo and flavedo hydroalcoholic extracts were rich in polyphenols, but they were different in compounds and quantity. The flavedo is rich in p-coumaric acid and rutin, whereas the albedo contains high levels of hesperidin and quercitrin. Antioxidant, anti-inflammatory, and genoprotective effects for albedo and flavedo were found. The results confirmed the health properties of flavedo and highlighted that albedo is also a rich source of antioxidants. Moreover, this study valorizes Limoncella of Mattinata's nutritional properties, cueing its crops' repopulation.

The growing use of proton-exchange membrane fuel cells (PEMFC) in hybrid propulsion systems, aimed at replacing traditional internal combustion engines and reducing greenhouse gas emis-sions. Effective power distribution between the fuel cell and the energy storage system (ESS) is crucial, which has led to a growing emphasis on developing energy management systems (EMS) to efficiently implement this integration. To address this goal, this study examines the performance of a fuzzy logic rule-based strategy for a hybrid fuel cell propulsion system in a small hydro-gen-powered passenger vessel. The primary objective is to optimize fuel efficiency, with particular attention to reducing hydrogen consumption. The analysis is carried out under typical operating conditions encountered during a river trip. Comparisons between the proposed strategy with other approaches —control-based, optimization-based and deterministic rule-based— are con-ducted to verify the effectiveness of the proposed strategy. Simulation results indicated that EMS based on fuzzy logic mechanisms was the most successful in reducing fuel consumption. The superior performance of this method stems from its ability to adaptively manage power distri-bution between the fuel cell and energy storage systems.

Immunofluorescent methods in vitro have been widely used to characterize the distribution and extent of colocalization of molecules located in various intracellular compartments. These are key processes to better understand the role of those molecules in physiological and pathological conditions.In the brain, interactions of astrocytes with neurons are fundamental for the establishment and proper functioning of neuronal circuits. Among these, the phagocytosis of synapses that need to be removed is a process known as synaptic pruning. When this process is dysregulated, it might lead to the development of several brain disorders. Here, we describe the adaptation of a method to characterize the astrocyte-mediated synaptic phagocytosis and evaluate astrocytic (dys)functions in healthy cells and cells derived from an animal model of major depressive disorder (MDD).

Health management in industrial systems is more critical in maintenance management and it plays an important role in productivity, fault diagnosis, safety, efficiency, and economy in manufacturing industries. Early detection of faults in machinery may increase the effectiveness of maintenance actions and will avoid unwanted consequences in process operations and maintenance. Existing fault diagnosis methods have limitations such as insufficient accuracy, slow detection rate, and handling large and complex data sets. In this digital age, Industry 4.0 techniques have been applied across all fields, including the condition monitoring of machines. This research addresses the gaps in traditional fault diagnosis by using deep learning, a modern AI technique effective for diagnosing faults in various machines. Deep learning algorithms Multilayer Perceptron (MLP), Coevolutionary Neural Network (CNN), and Recurrent Neural Network (RNN) with Long Short-Term Memory (LSTM) are tested for fault diagnosis using vibration datasets collected from Spectra Quest Machinery Fault Simulator (SQMFS). In this research work, NI-DAQ (National Instruments- Data Acquisition) system, accelerometer, and LabVIEW software are used to collect vibration signals. Preprocessing of the signals has been done using a sampling strategy, shuffling, standardization, and reshaping data augmentation. The result shows that MLP accuracy in the prediction of fault is 0.9, CNN reached 0.95, and RNN and LSTM with 0.57 and 0.45 respectively. The high performance of CNN is due to its ability to effectively capture spatial patterns in vibration data which is crucial for fault diagnosis in rotating machinery followed by MLP due to its faster convergence during training. However, when scaling the data, MLP outperformed CNN, demonstrating superior adaptability to increased data complexity and volume. Due to the need for larger datasets and temporal patterns in the vibration data, which RNN and LSTM are designed to handle, they resulted in a lower accuracy. This study shows that CNN has given better results than other deep learning algorithms MLP, RNN, and LSTM in fault diagnosis of rotating machinery. Future research could explore the application of these techniques to different types of machinery and fault conditions.

This study is focus on the petrographic properties and geo-mechanical properties of the Inzari formation rocks at Tar Khel Village, District Swabi, Khyber Pakhtunkhwa, and whether they are suitable for use as building materials for structures like bridges, buildings, and roads. Five fresh and large samples have been taken from various areas of this formation. These rock samples were identified as siliciclastic mudstone through a careful petrographic analysis. The test result of physical properties (water absorption, specific gravity, and porosity) and mechanical properties (unconfined compression strength, unconfined tensile strength, Schmidt hammer test, and shear strength) of these rock samples shows as follows: their unconfined compressive strength with between 23 to 94 MPa, their specific gravity values being very high (≥2.78), and their porosity and water absorption values being very low (<1%), imply that the Inzari formation rock can be used as an excellent building material. The rock sample strength variations may be mainly caused by the presence and abundance of stylolite and fractures. Furthermore, the petrographic property analysis of these rock samples indicates that they have the significant amount of micrite and calcite, which are suitable to be use as both asphalt and concrete aggregate. According to this study, the Inzari formation rock is appropriate for use as fine aggregate in concrete, asphalt, and other building materials.

Turgor pressure – the intracellular hydrostatic pressure exerted by the cell protoplast on the cell wall – is of critical physiological importance for all organisms that have the cell wall. However, in mycology there is increasing evidence that turgor pressure is not the only and not always the main factor influencing, for example, the tension of the plasma membrane, the size and shape of non-apical fungal cells, and is not even always the determining factor of apical growth. This paper characterizes various aspects of the curtain model, previously proposed to describe the regulation of plasma membrane tension in the hyphae of basidiomycetes. The current understanding of the four main components of the curtain model are outlined: the driving actin cytoskeleton, the elastic cell wall, tight adhesion of the plasma membrane to the cell wall and macroinvaginations of the plasma membrane. All four elements, summed in the single curtain model, complement or replace the physiological functions of turgor, and allow imagining how a non-apical fungal cell maintains its integrity and physiological functionality under changing osmotic and other conditions. Further experimental confirmation of the curtain model is not only of fundamental importance for mycology, but also opens up new prospects in the development of drugs that control the growth and pathogenicity of filamentous fungi.

The air attenuation of pure tones as a function of temperature and humidity is well known and described in ISO and ANSI standards. However, room acoustic measurements are performed in octave bands, which is the reason for a complicated, nonlinear behavior of the air attenuation. It is known that room acoustic measurement results depend on air temperature and humidity, and these atmospheric data should always be reported in connection with room acoustic measurements. A calculation model for the air attenuation can make it possible to normalize the room acoustic results. For accurate results it is possible to apply a summation method on each time sample in the impulse response. An approximation to the air attenuation at and above 1 kHz is possible by linearization using the pure-tone attenuation of two different frequencies, one frequency valid for the early part of the impulse response, and another frequency valid for the later part of the impulse response. The purpose of the suggested methods is to make it possible to normalize room acoustic measurements to a standard atmosphere.

Beginning in 2022, the Mpox outbreak, formerly known as monkeypox, has since spread to more than 100 countries and is now a global public health concern. This disease, caused by the Mpox virus, is usually mild, and most infected individuals recover within a few weeks without treatment. However, severe cases have been seen especially in children, pregnant women, or immunocompromised individuals. Antiviral medications such as brincidofovir, tecovirimat, and cidofovir were recently approved for Mpox; but these drugs are expensive and not easily obtainable. Therefore, identifying effective and low-cost drugs against Mpox and testing these through clinical trials remains a priority for global health. Drug repurposing is a well-known strategy for redeploying existing licensed drugs for newer indications, allowing for the shortest possible transition from bench to bedside. Recent in silico studies have determined the efficacy of minocycline, oleanolic acid, ursolic acid, and glycyrrhizinic acid against Mpox virus. Notably, oleanolic acid, ursolic acid, and glycyrrhizinic acid are some of the components of Japanese Kampo medicines, which are low-cost medicines prescribed daily in Japan. Thus, minocycline and Japanese Kampo medicines could potentially be used to treat Mpox.

Thermomechanical, biocompatibility, durability, workability and economic characteristics are the main criteria for development of dental alloys. In an attempt to provide a noble metal dental alloy without the known adverse metallic elements, a novel alloy was produced with the addition of Germanium (Ge), as a more cost-effective alternative to other precious alloying metals. The objective of this investigation was to analyse the thermomechanical and biocompatibility properties of a high noble Au-Pt-Ge porcelain-fused-to-metal (PFM) alloy. These properties were investigated with DSC analysis, hardness, density and coefficient of thermal expansion (CTE) measurements, as well as with metallographic and SEM/EDX microstructure investigations, with the production of a test PFM dental bridge, static immersion testing for metal ion release, and an in vitro primary biocompatibility testing on human gingival cells. The results of the thermomechanical testing showed alloy properties suitable for dental restorations and clinical use, with somewhat lower hardness, making the alloy not suitable for extensive multiunit fixed restorations. The microstructure investigations showed segregations of Ge in a homogeneous alloy matrix, which reduce the alloy’s mechanical properties. The produced PFM dental bridge shows excellent workability of the alloy in a dental laboratory setting, as well as a high standard of the final dental restoration. The ion release was negligible, well below any harmful quantities, while the cell viability examination showed significantly higher viability ratings on polished alloy samples as compared to as-cast samples. The results showed that a dental substructure in direct contact with oral tissue and fluids should be highly polished.

There are currently no effective screening measures to detect early or occult tubo-ovarian cancers resulting in late-stage detection and high mortality. This work explores whether an optical imaging catheter can detect early-stage tubo-ovarian cancers or precursor lesions where they originate in the fallopian tubes. This device collects co-registered optical coherence tomography (OCT) and autofluorescence imaging (AFI). OCT provides three-dimensional assessment of underlying tissue structures; autofluorescence imaging provides functional contrast of endogenous fluorophores. Ex vivo fallopian tubes (n=28; n=7 cancer) are imaged; we present methods for the calculation of and analyze eleven imaging biomarkers related to fluorescence, optical attenuation, and OCT texture for their potential to detect tubo-ovarian cancers and other lesions of interest. We visualize folded plicae, vessel-like structures, tissue layering, hemosiderin deposits, and regions of fibrotic change. High grade serous ovarian carcinoma appears as reduced autofluorescence paired with homogenous OCT and reduced mean optical attenuation. Specimens containing a cancerous lesion demonstrate significant increase in median autofluorescence intensity and decrease in entropy compared specimens with no lesion. Non-cancerous specimens demonstrate an increase in optical attenuation in the fimbriae when compared to the isthmus or ampulla. We conclude that this approach shows promise and merits further investigation of diagnostic potential.

This paper aims to present a robust computational technique utilizing finite difference schemes for accurately solving time fractional reaction-diffusion models, which are prevalent in chemical and biological phenomena. The time-fractional derivative is treated in the Caputo sense, addressing both linear and nonlinear scenarios. The proposed schemes were rigorously evaluated for stability and convergence. Additionally, the effectiveness of the developed schemes was validated through various linear and nonlinear models, including the Allen-Cahn equation, the KPP-Fisher equation, and the Complex Ginzburg-Landau oscillatory problem. These models were tested in one, two, and three-dimensional spaces to investigate the diverse patterns and dynamics that emerge. Comprehensive numerical results were provided, showcasing different cases of the fractional order parameter, highlighting the schemes' versatility and reliability in capturing complex behaviors in fractional reaction-diffusion dynamics.

Reliable access to electricity has become a necessity worldwide, and without it, no country can operate health systems and achieve sustainable development goals (SDGs). However, while developed countries have been successfully electrified for many decades, most developing countries have fallen short, contributing to significant impacts, particularly the health sector. The present study explores the relationship between electrification and health vulnerability in developing countries between 1990 and 2020 using the Feasible Generalized Least Square (FGLS) approach. The varied electrification across countries motivates the use of non-linear associations between electrification and health vulnerability. We demonstrate that electrification and health vulnerability have an inverted U-shaped association. Further analysis indicates that most developing countries have achieved a mature level of an inverted U-shaped curve, showing a reduction in health vulnerability with increasing electrification. There are few developing countries, mainly African countries, struggling to reach maturity. The results of this study indicate the need for increased access to electrification, in combination with a reduction in the use of biomass and fossil fuel feedstocks, to mitigate health vulnerability in developing countries.

This article compares the predictive capabilities of six models namely the Linear Discriminant Analysis (LDA), Logistic Regression (LR), Support Vector Machine (SVM), XGBoost, Random Forest (RF) and Deep Neural Network (DNN) to predict the default behaviour of credit card holders in Taiwan using data from the UCI machine learning database. Python programming language was used for data analysis. Statistical methods were compared with machine learning algorithms using the confusion matrix measured in metric terms of prediction accuracy, sensitivity, specificity, precision, G-mean, F1 score, ROC and AUC. The dataset contains 30,000 credit card user’s information with 6636 default observations and 23,364 non-default cases. The study results found that modern machine learning methods outperformed traditional statistical methods in terms of predictive performance measured by F1 score, G-mean and AUC. Traditional methods like logistic regression were marginally better than linear discriminant analysis and support vector machines in terms of predictive performance measured by area under the receiver operating characteristic curve. In the modern machine learning methods, deep neural networks were better in most of the predictive performance metrics than XGBoost and Random Forest methods.

This study investigates the impact of single prolonged stress (SPS), a model of post-traumatic stress disorder (PTSD), on cardiovascular responses, hypothalamic paraventricular nucleus (PVN) activity, and vascular function to elucidate the mechanisms linking traumatic stress to hypertension. Although SPS did not directly cause chronic hypertension in male Sprague Dawley (SD) rats, it induced acute but transient increases in blood pressure and heart rate and significantly altered the expression of hypertension-associated genes, such as vasopressin, angiotensin II type 1 receptor (AT1R), and FOSL1 in the PVN. Notably, mitochondrial reactive oxygen species (mtROS) were predominantly elevated in the pre-autonomic regions of the PVN, colocalizing with AT1R- and FOSL1-expressing cells, suggesting that oxidative stress amplifies sympathetic activation and stress responses. SPS also triggered vascular inflammation, evidenced by increased mRNA levels of pro-inflammatory cytokines (TNFα and IL1β) and inducible nitric oxide synthase (iNOS) in the aorta, and impaired vascular reactivity to vasoconstrictor and vasodilator stimuli, reflecting compromised vascular function. These findings suggest that SPS sensitizes neuroendocrine, autonomic, and vascular pathways, creating a state of cardiovascular vulnerability that could pre-dispose individuals to hypertension when exposed to additional stressors. Understanding these mechanisms provides critical insights into the pathophysiology of stress-related cardiovascular disorders and underscores the need for targeted therapeutic interventions that address oxidative stress and modulate altered PVN pathways to mitigate the cardiovascular impact of PTSD and related conditions.

Modeling dense nonaqueous phase liquids (DNAPLs) contamination in groundwater is challenging because of its multiphase distribution. To understand the research trends of DNAPL modeling in groundwater, a bibliometric analysis was conducted using CiteSpace based on 614 publications from the WoS Core Collection database (1993-2023). The publications were statistically analyzed, and the research hotspots and trends were summarized. The statistical analysis of the publications indicates that: the United States is leading the international research on DNAPL models, followed by China and Canada; collaboration between countries and disciplines in this field needs to be strengthened. The summary of keyword clustering and burst detection reveals that: the current research hotspots focus on multiphase flow models, mass transfer models, back diffusion, and practical applications of the models; the research trends are centered on back diffusion mechanisms, characterization of contamination source zones and prediction of contaminant distribution in real-world sites, as well as the optimization of remediation strategies.

Integrated Fixed Film Activated Sludge (IFAS) technology greatly enhances nitrogen removal effectiveness and treatment capacity in municipal wastewater treatment plants, addressing the issue of limited land availability. Hence, this method is appropriate for treating household wastewater from office buildings. The research was conducted at the wastewater treatment plant in an office building in Ho Chi Minh City, Vietnam. Experiments were conducted to ascertain the most favorable working conditions, including Hydraulic Retention Time (HRT), alkalinity dosage, and Dissolved Oxygen (DO). According to the study, the IFAS system had the highest nitrogen removal effectiveness when operated at a hydraulic retention time (HRT) of 7 hours, an alkalinity dose of 7.14 mgCaCO3/mgN-NH4+, and a dissolved oxygen (DO) value of 6 mg/L. The nitrification efficiency ranges from 89.2% to 98.8%. The nitrate concentration post-treatment is within the range of 27 – 45 mg/L, which is lower than the allowable discharge limit of 60 mg/L as per Vietnam's wastewater discharge requirements. The research findings have enhanced the efficiency of the office building management process, thereby promoting the sustainable growth of society.

This paper proposes an innovative postulate based on experimental observations, namely, that the speed of light can vary between two inertial reference systems. This postulate is defined as the principle of relative change in the speed of light, which refreshes the concept of absolute speed of light in traditional physics. By integrating the principle of the invariance of the speed of light with the principle of relativity in relativity theory, several important conclusions are derived: space and time must be capable of and proportionally expand and contract. Between two inertial reference systems with different relative speeds of light, objects have an energy difference of k^2 times, which induces a natural tendency for objects to move towards a state of lower energy. The acceleration is only related to the relative change rate of the speed of light in vacuum space and is independent of the mass of the object. The kinetic energy obtained by the object comes from the reduction of internal energy of the object, emphasizing the key role of energy conversion in this process. The paper provides a new theoretical perspective for explaining the physical mechanisms of universal gravitation and dark energy.

This research explores the feasibility of a data-driven optimization algorithm for placing sparse arrays of artificial hair-cell airflow velocity sensors to enable agile and robust flight-by-feel control of unmanned aircraft. The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm exploits the information-rich features of large flow datasets to find a near-optimal set of locations for flow sensors on a wing. The flow information from these sensors can be used to predict flight state parameters such as the angle of attack, mimicking the fly-by-feel control systems observed in nature. We evaluate the effectiveness of this approach for a blunt-edged 45∘ swept delta wing. Exploiting the information in the complex airflow patterns over this wing, the SSPOP algorithm selects a sensor location design point (DP) which reliably ranks within the top 1% of all possible DPs by root mean square error in angle of attack prediction. This performance was consistent across models of various artificial hair lengths, and one model with variable hair lengths. This bioinspired dimension-reducing method for sensor placement optimization exhibits reliability and flexibility benefits when compared with a conventional greedy search algorithm and gradient-based optimization using auto-differentiation. The successful application of SSPOP in complex 3D flows paves the way for experimental evaluation of data-driven sparse sensor placement optimization for artificial hair-cell airflow sensors and is a major step toward biomimetic flight-by-feel.

This study examines the impact of natural resource exploitation, renewable energy consumption, economic growth, biocapacity, and information and communication technologies (ICT) on the ecological footprint of BRICS+ nations using panel data from 1991 to 2019. Advanced econometric techniques, including FMOLS, DOLS, CCR, and GMM, reveal significant findings relevant to sustainability-focused policymakers. The results show that natural resource exploitation significantly contributes to environmental degradation, while renewable energy consumption mitigates these effects to varying degrees across the studied countries. Although economic growth is crucial, it worsens ecological footprints unless accompanied by sustainable practices. ICT and biocapacity emerge as key factors in promoting environmental sustainability, with ICT enhancing innovation and efficiency to reduce ecological impacts. The study emphasizes the need for tailored policy frameworks that align economic growth with environmental sustainability, advocating for the adoption of renewable energy, eco-innovations, and green finance initiatives suited to the unique conditions of BRICS+ nations. The findings aim to guide policymakers in advancing sustainable development and mitigating the adverse environmental impacts of rapid industrialization and urbanization, while contributing to the global discourse on achieving a balance between economic growth and ecological well-being in developing countries.

Bipolar disorder (BD) is a complex mental health condition characterized by alternating periods of mania and depression. This review provides a comprehensive overview of BD, focusing on its genetics, causal hypotheses, clinical signs and evolution, potential biomarkers with an emphasis on electroencephalography (EEG), and treatment options. Genetic studies have identified several susceptibility genes and polygenic risk scores, highlighting the heritable nature of BD. Various causal hypotheses, including monoamine dysregulation, kindling, circadian rhythm disruptions, and neuroinflammation, have been proposed to explain its pathophysiology. The clinical course of BD is characterized by recurrent episodes of mania/hypomania and depression, with significant heterogeneity among individuals. EEG and other biomarkers hold promise for improving diagnosis, predicting treatment response, and elucidating the neurobiological underpinnings of BD. Current treatment options include pharmacotherapy, psychotherapy, and neuromodulation techniques, which can be tailored to individual needs based on clinical presentation and response to treatment. Future research should focus on identifying more specific biomarkers, developing novel treatments, and optimizing existing therapies to improve outcomes for individuals with BD.

Chronic noncommunicable diseases (NCDs) are responsible for approximately 74% of deaths globally. Medicinal plants have traditionally been used to treat NCDs, including diabetes, cancer, and rheumatic diseases, and are a source of anti-inflammatory compounds. This study aimed to evaluate the anti-inflammatory effects of Rhus trilobata (Rt) extracts and fractions in lipopolysaccharide (LPS)-induced inflammation models in vitro and in vivo. The aqueous extract (RtAE) and five fractions (F2 to F6) were obtained via C18 solid-phase separation and tested in murine LPS-induced J774.1 macrophages. Key inflammatory markers such as IL-1β, IL-6, TNF-α, and COX-2 gene expression were measured using RT-qPCR, and PGE2 production was assessed via HPLC-DAD. The in vivo effects were tested in an LPS-induced paw edema model in Wistar rats. Results showed that RtAE at 15 μg/mL significantly decreased IL-1β and IL-6 gene expression in vitro. Fraction F6 further reduced IL-1β, TNF-α, and IL-6 gene expression, COX-2 expression, and PGE2 production. In vivo, F6 significantly reduced LPS-induced paw edema, inflammatory infiltration, and IL-1β and COX-2 protein expression. These findings support the anti-inflammatory potential of RtAE and F6, reinforcing the medicinal use of Rt.

Tefluthrin (Tef) is categorized as a type-I pyrethroid insecticide, telmisartan (Tel) functions as an angiotensin II receptor blocker, and KB-R7943 was identified as an inhibitor of Na+-Ca2+ exchange process. However, the influence of these compounds on the amplitude and gating properties of voltage-gated Na+ current (INa) in neurons associated with pain signaling remains unclear. In cultured dorsal root ganglion (DRG) neurons, whole-cell current recordings revealed that Tef or Tel increased the peak amplitude of INa, concomitant with an elevation in the time constant of INa inactivation, particularly in the slow component. Conversely, exposure to KB-R7943 resulted in a depression in INa, coupled with a decrease in the slow component of the inactivation time constant of INa. Theoretical simulations and bifurcation analyses were performed on a modeled interneuron in the spinal dorsal horn. The occurrence of INa inactivation accentuated the subthreshold oscillations (SO) in the membrane potential. With an increase in applied current, SO became more pronounced, accompanied by the emergence of high-frequency spiking (HF) with a frequency of approximately 150 Hz. Moreover, an elevation in INa conductance further intensified both SO and HF. Consequently, through experimental and in silico studies, this work reflects that Tef, Tel, or KB-R7943 significantly impacts the magnitude and gating properties of INa in neurons associated with pain signaling. The alterations in INa magnitude and gating in these neurons suggest a close relationship with pain transmission.

Modern advances in technology have increased the demand for traditional accounting systems to be upgraded for real-time data processing, security, and standardized reports. Thus, this paper proposes a new accounting information system that integrates IoT, blockchain, and XBRL. The proposed system aims to automate the accounting process by using IoT to collect data and send it automatically to a blockchain, which acts as a database that will generate journal entries automatically through smart contracts. XBRL will then be used as an output method for standardized financial reports based on the data transferred from the blockchain. This paper uses a qualitative research design based on semi-structured interviews with 13 industry experts from IT engineering, academia, and financial systems analysis. NVivo software was used to conduct a thematic analysis of interview transcripts. The findings revealed the technical feasibility, challenges, and benefits of the proposed integration and identified the most efficient mechanism for data transmission across the three technologies. The paper concluded that while integration complexity and user adoption are challenging, this integrated system can revolutionize accounting by enabling real-time data capture, automation of essential operations, data security, and integrity improvements. To our knowledge, this is the first paper to develop a comprehensive accounting information system framework using IoT, blockchain, and XBRL to automate data collection, improve data security, and streamline financial reporting. The study's potential to impact accounting systems and financial reporting research and practice emphasizes its importance.

An approach to estimate the dynamic characteristic of multilayered three-dimensional cubic quasicrystal cylindrical shells, annular plates, and truncated conical shells with different boundary conditions is presented. These investigated structures can be in a vacuum, totally filled with quiescent fluid, and subjected to internal flowing fluid, in which the fluid is incompressible and inviscid. The velocity potential, Bernoulli’s equation, and impermeability condition have been applied to the shell-fluid interface to obtain an explicit expression, from which the fluid pressure can be converted into the coupled differential equations in terms of displacement functions. The state-space method is formulated to quasicrystal linear elastic theory to derive the state equations for three structures along the radial direction. The mixed supported boundary conditions are represented by means of the differential quadrature technique and Fourier series expansions, respectively. A global propagator matrix, which connects the field variables at the internal interface to those at the external interface for the whole structure, is further completed by joint coupling matrices to overcome the numerical instabilities. Numerical examples show the correctness of the proposed method and the influence of the semi-vertical angle, different boundary conditions, and the fluid debit on the natural frequencies and mode shapes for various geometries and boundary conditions.

The finite volume method (FVM) is a kind of numerical analysis method that can take into account topography and apply local subdivision cells as the finite element method (FEM). The adjoint state method (ASM) can easily calculate the gradient vector of the objective function for the inversion. The author developed a program that applied these methods to 3-D Magnetotelluric (MT) inversion and verified it using test models. As a result, it was confirmed that the program can perform analysis properly and efficiently considering topography and subsurface resistivity heterogeneity.

Background: The CoBaTrICE initiative standardized intensive care training throughout Europe. Pericardiocentesis, an important yet infrequent operation, poses unique training challenges often unmet by conventional methods. This study evaluates the efficacy of virtual reality (VR) simulations and 3D-printed mannequins in pericardiocentesis training, both crafted from scratch using highly affordable materials and free software. Methods: Thirty-five final-year medical students participated in this prospective, quasi-experimental study. Initially, students underwent VR simulation training, followed by training using 3D-printed self-made mannequins. Learning outcomes were assessed using the Objective and Structured Clinical Examination (OSCE) questionnaire. Heart rate variability (HRV) analysis was employed to monitor stress responses, while the NASA Task Load Index (NASA-TLX) was used to gauge self-perceived difficulty. Results: Although the mannequin model induced more stress reactions, it excelled in tasks requiring fine motor skills, such as correct placement and asepsis maintenance. In contrast, lower NASA-TLX scores indicated that the VR model imposed less mental demand and effort, reflecting a reduced cognitive load. Conclusion: Both VR simulations and 3D-printed mannequins effectively taught pericardiocentesis skills, each offering distinct advantages. Mannequins enhanced fine motor skills, whereas VR reduced cognitive load and increased engagement. The combination of both approaches could maximize training outcomes, particularly in resource-constrained environments, thus broadening access to advanced simulation education.

Pregnancy is associated with significant physiological changes, including alterations in lipid metabolism, which can have implications for both maternal and fetal health. This study aimed to evaluate serum lipid profile variations among healthy Sudanese women during the second and third trimesters of pregnancy. A total of 60 pregnant women, divided equally between the second and third trimesters, were compared with 30 non-pregnant, age-matched controls. Serum levels of total cholesterol, triglycerides, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) were measured using a BTS-Biosystem analyzer. The results revealed a statistically significant increase in total cholesterol, triglycerides, LDL, and HDL levels among pregnant women compared to the control group (p < 0.01). Additionally, lipid levels were significantly higher in the third trimester than in the second trimester. A weak positive correlation was found between parity and serum levels of total cholesterol, triglycerides, and LDL, while no significant correlation was observed for HDL. These findings suggest that pregnancy, particularly in the third trimester, is associated with substantial increases in serum lipid levels, highlighting the need for monitoring lipid profiles during pregnancy to manage potential risks of hyperlipidemia and its associated complications.

One of the efficient data mining tools is density-based clustering, including the density grid-based clustering. However, a common drawback always existing in clusters made by the density grid-based method is the existence of weakly connected grids deriving mainly from noise. Appearing such an unwanted connection with a high frequency reduces the accuracy of the obtained cluster data space (CDS) and its application efficiency. Here, we present an essential improvement to overcome this problem. First, we describe a concept of the weak-connected grid cell (WCG) and present a fuzzy-type approximation to depict the density-based distribution of data points at grid nodes. Then, we propose a strategy of searching WCG for density grid-based clustering (SWCG-DGB) to set up a CDS, filter noise, and tune the created CDS. A buffer is deployed during this phase to collect border points and filter noise, which improves the computational time significantly, especially for noisy datasets. Results from numerical surveys reflected the compared efficiency of this method in clustering validity, including the accuracy of the number of clusters.

As the smallest member of the fullerene family, C20 is yet to be discovered in planetary nebulae. In this work, we present a quantum chemical study via density functional theory (DFT) on the ionization tolerance of this molecule in the space environment. Considering that the ionization and excitation phenomena play key roles in alerting the lifetime of a molecule, we examined both ground and excited electronic states potential energy surfaces (PES) of C20 and its cations C20q+. Our theoretical results indicate that the C20 cage tolerates a positive charge as high as 13+ via characterizing local minimum geometries on both mentioned electronic states. We also explored theoretically and systematically, scenarios in which the electronic structure of neutral C20 is excited to very high spin multiplicity (beyond triplet state) and local minimum molecular geometries with cage structure are well characterized. We anticipate that such structural resistance to excitation and ionization deliver a prolonged lifetime necessary for the spectroscopic detection of this interesting molecule and its cations in space and potentially in planetary nebulea (PN).

Floods in various regions cause irreparable damage to infrastructure, agricultural lands, and industrial centers. In recent years, due to the effects of climate change and, in particular, the increased activity of the monsoon system in the Balochistan region located in southern Sistan and Baluchestan province, local rivers have overflowed, causing widespread flooding and significant damage. Accurate flood routing not only provides decision-makers with precise information about flood volume and flow behavior but also facilitates planning for effective preventive measures. In this study, the Muskingum-Cunge model was used to simulate floods in eight major rivers of Balochistan, including Kajou, Sarbaz, Nik Shahr, Kehir, Bahu, Sia Jangal, Rapch, and Kamb. The model parameters (K and X) were optimized using two machine learning algorithms: Particle Swarm Optimization (PSO) and Harmony Search (HS). The results showed that in most stations, the PSO algorithm outperformed HS. The algorithms were evaluated using the coefficient of residual mass (CRM), normalized root mean square error (NRMSE), efficiency (EF), and agreement index (d). For instance, at the Kajou station, PSO improved CRM by 0.017, Ef by 0.921, d by 0.982, and NRMSE by 0.099 compared to HS. At the Kamb station, both algorithms yielded comparable results. Considering the overall better performance of the PSO algorithm in most evaluation indices, it can be concluded that this algorithm is a more suitable option for optimizing the parameters of the Muskingum-Cunge model and simulating flood hydrographs with higher accuracy at most of the studied stations.

Accurate, rapid, and stable prediction of electrical energy consumption is essential for decision-making, energy management, efficient planning, and reliable power system operation. Errors in forecasting can lead to electricity shortages, wasted resources, power supply interruptions, and even grid failures. Accurate forecasting enables timely decisions for secure energy management. However, predicting future consumption is challenging due to the variable behavior of customers, requiring flexible models that capture random and complex patterns. Existing forecasting methods, both traditional and modern, have limitations and do not fully meet accuracy expectations. To address these issues, this research introduces a hybrid models that combine FCRBM based forecaster, and GWDO based optimizer, namely FS-FCRBM-GWDO approach to enhance the model performance in STLF have been developed. While some models excel in accuracy and others in convergence rate, both aspects are crucial. The main objective is to create a forecasting model that provides reliable, consistent, and precise predictions for effective energy management. This led to the development of a novel two-stage hybrid model. The first stage predicts electrical energy usage through four modules using deep learning, support vector machines, and optimization algorithms. The second stage optimizes energy management based on predicted consumption, focusing on reducing costs, managing demand surges, and balancing electricity expenses with customer inconvenience. This approach benefits both consumers and electricity corporations by lowering bills and enhancing power system stability. Simulation results validate the proposed model's efficacy and efficiency compared to benchmark models.

The sustainability concept has acquired a variety of meanings according to different currents of thought and the context in which it is used. The aim of this research was to characterize the perception of producers, extension agents and officials regarding sustainable cattle ranching (SCR) in an area where tropical cattle ranching is practiced. A survey was applied to producers chosen through stratified random sampling, and to extension agents and officials selected using the snowball technique. The perception of SCR was determined under two contexts: 1) the idea or interpretation of the individual and 2) the assessment (positive or negative) of this type of cattle ranching (net perception index, NPI). The extension agents oriented their perception of SCR mainly in economic (52.2%) and environmental (47.8%) aspects, similar to the producers (48.4% and 21.3% respectively), while the officials related it more to an environmental dimension (71.4%). It is concluded that the perception of SCR in general is positive, but its conceptualization is differentiated, according to the role the individuals play in the activity, their academic training and their expectations.

1) Background: Overweight children usually have lower levels of physical activity (PA) than their normal-weight peers. Low PA predisposes to increase fat mass in the body. The aim of this study was to evaluate the effectiveness of school-based PA intervention on anthropometric indicators and body composition of overweight and obese children during a two-year observation period, from the age of 10 to 12. (2) Materials and methods: The research included 148 children with overweight or obesity who were born in 2007. There were two groups of children of standard and elevated PA at school (SPA and EPA, 4 and 10 hours of physical education lessons a week, respectively). An anthropometric and body composition measurements were done. Body mass index (BMI), fat mass (FM), fat-free mass (FFM), skeletal muscle mass (SMM) and total body water (TBW) were determined. Totally, 5 measurements were done at intervals of 5–6 months. (3) Results: In EPA, the percentage of obese children decreased from 46% to 35.25%, and in SPA increased from 42.75% to 46%. In EPA, FM decreased from 28.65% to 26.41%, and in SPA increased from 30.31% to 31.75%. The highest increase in FFM was in EPA boys, while SPA boys recorded the highest decrease. In SPA, SMM increased by 0.43% from 38.85% to 39.28%, and in EPA by 2.51% from 40.27% to 42.78%. TBW In EPA slightly increased from 53.26% to 53.59%, and in SPA decreased from 50.70% to 49.93%. (4) Conclusions: The elevated PA at school has a positive effect on the BMI and body composition of children who are overweight or obese. Increasing the mandatory number of physical education lessons in school curricula is an efficient strategy for reducing obesity in school-aged children.

The advancement of computational drug discovery and design necessitates continuous innovation to enhance the accuracy and scope of predictive models for early-stage drug research and development. This article introduces a novel workflow for in silico generation of structural and intermolecular binding affinity data with reasonable accuracy, combining two computational tools: Modeller and Prodigy. By leveraging synthetic structural and biophysical data, this approach addresses the limitations of existing experimental datasets, generating extensive, high-quantity binding affinity data with reasonable accuracy for biomolecular binding pairs, which broadens the horizon of computational biomolecule design and discovery by enabling extensive exploration of the sequence space of biomolecular binding pairs, and narrows the gap between experimental binding affinity data and its unexplored territories. Overall, this article presents a methodological advance to enhance the accuracy and scope of computational biomolecule discovery and design, paves the way for the development of preclinical candidates with improved efficacy and specificity, and holds transformative potential for further advancements in artificial intelligence-enabled biomolecule discovery and design in the future.

Decidualization of the uterine endometrium is a critical process for embryo implantation in mammals, primarily occurring on gestational day 8 in pregnant mice. However, the interplay between the maternal gut microbiome, metabolism, and the uterus at this specific time point remains poorly understood. This study employed a multi-omics approach to investigate the metabolic, gut microbiome, and transcriptomic changes associated with early pregnancy (gestational day 8 (E8)) in mice. Serum metabolomics revealed a distinct metabolic profile in E8 compared to controls, with differential metabolites primarily enriched in amino acid metabolism pathways. Gut microbial composition showed that E8 mice exhibited higher alpha-diversity and a significant shift of beta-diversity. Specifically, the E8 group displayed a decrease in pathogenic Proteobacteria and an increase in beneficial Bacteroidetes and S24-7 taxa. Transcriptomics identified myriads of distinct gene between E8 and control mice. The differentially expressed genes were enriched in pathways involved in Alanine, Aspartate and Glutamate metabolism, PI3K-Akt signaling, and PPAR signaling pathway. Integrative analysis of the multi-omics data uncovered potential mechanistic relationships among the differential metabolites, gut microbiota, and uterine gene expression changes. Notably, the gene Asns showed strong correlations with specific gut S24-7 and metabolite L-Aspartatic acid, suggesting its potential role in mediating the crosstalk between the maternal environment and embryo development during early pregnancy. These findings provide valuable insights into the complex interplay between the maternal metabolome, gut microbiome, and uterine transcriptome in the context of early pregnancy, which may contribute to our understanding of the underlying mechanisms of embryo implantation and development.

With the increasing awareness of environmental protection, the rotary hearth furnace system has emerged as a key technology that facilitates a win-win situation for both environmental protection and enterprise economic benefits. This is attributed to its high flexibility in raw material utilization, capability of directly supplying blast furnaces, low energy consumption, and high zinc removal rate. However, the complexity of the raw material proportioning process, coupled with its reliance on manual labor, results in a time-consuming and inefficient process. This paper innovatively introduces an intelligent formula method for raw materials based on online clustering algorithms and develops an intelligent batching system for rotary hearth furnaces. Firstly, the ingredients of raw materials undergo data preprocessing, which involves using the Local Outlier Factor (LOF) method to detect any abnormal values, Kalman filtering to smooth the data, and performing one-hot encoding to represent the different kinds of raw materials. Afterwards, the affinity propagation (AP) clustering method is used to evaluate past data on the ingredients of raw materials and their ratios. This analysis aims to extract information based on human experience with ratios and create a library of machine learning formulas. The incremental AP clustering algorithm is utilized to learn new ratio data and continuously update the machine learning formula library. To ensure that the formula meets the actual production performance requirements of the rotary hearth furnace, the machine learning formula is fine-tuned based on expert experience. The integration of machine learning and expert experience has demonstrated good flexibility and satisfactory performance in the practical application of intelligent formulas for rotary hearth furnaces. An intelligent batching system is developed and executed at a steel plant in China. It shows an excellent user interface and has significantly enhanced batching efficiency and product quality.

We used numerical methods to define the normative structure of the different stages of sleep and wake (W) in a pilot study of 19 subjects without pathology (18–64 years old) using a double-banana bipolar montage. Artefact-free 120–240 s epoch lengths were visually identified and divided into 1 s windows with a 10% overlap. Differential channels were grouped into frontal, parieto-occipital, and temporal lobes. For every channel, the power spectrum (PS) was calculated via fast Fourier transform and used to compute the areas for the delta (0–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) bands, which were log-transformed. Furthermore, Pearson’s correlation coefficient and coherence by bands were computed. Differences in logPS and synchronization from the whole scalp were observed between the sexes for specific stages. However, these differences vanished when specific lobes were considered. Considering the location and stages, the logPS and synchronization vary highly and specifically in a complex manner. Furthermore, the average spectra for every channel and stage were very well defined, with phase-specific features (e.g., the sigma band during N2 and N3, or the occipital alpha component during wakefulness), although the slow alpha component (8.0–8.5 Hz) persisted during NREM and REM sleep. The average spectra were symmetric between hemispheres. The properties of K-complexes and the sigma band (mainly due to sleep spindles – SSs) were deeply analysed during the NREM N2 stage. The properties of the sigma band are directly related to the density of SSs. The average frequency of SSs in the frontal lobe was lower than that in the occipital lobe. In approximately 30% of patients, SSs showed bimodal components in anterior regions. qEEG can be easily and reliably used to study sleep in healthy subjects and patients.

With the rapid development of electric vehicles, the infrastructure for charging stations is also expanding quickly, and the failure rate of charging piles is increasing. To address the effective operation and maintenance of charging stations, a method based on the XGBoost algorithm for electric vehicle DC charging stations is proposed. An operation and maintenance system is con-structed based on state analysis, considering the operation status of the charging station and users' charging habits. Factors such as driving and charging habits, road traffic, and charging station equipment are taken into account. The training sample data is established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. Based on the condition assessment results, a risk assessment model is established in combination with fault parameters. Risk tracking of the charging station is conducted using the lack of power supply (ENC), evaluating the risk level of each station, and determining the operation and maintenance order. The optimal opera-tion and maintenance model for DC charging stations, aimed at achieving both economic and reliable goals, is constructed to determine the operation and maintenance schedule for each sta-tion. The results of the case study demonstrate that the state evaluation and operation and maintenance strategy can significantly improve the reliability of the system and the overall ben-efits of operation and maintenance while meeting the required standards.

The intricate relationship between genomic mutations and proteomic network topology represents a frontier in understanding cellular resilience and disease mechanisms. This study presents a novel approach to analyzing how proteomic topological structures evolve and potentially break down in response to accumulating genomic mutations, offering insights into the complex interplay between genetic alterations and protein interaction networks. We developed a computational model simulating a network of ten key proteins (A-J) over 20 discrete time points, each representing a state of increasing genomic mutation load. Our model incorporates dynamic protein interaction strengths that fluctuate in response to simulated genomic alterations and a topological representation of the protein network, allowing for visualization of structural changes. Not forgetting a quantitative measure of network integrity, correlating with the system's ability to maintain function under mutational stress. Our Key findings include: visualization of proteomic network evolution through a series of topological graphs, revealing how genomic mutations progressively alter protein interaction patterns and identification of a critical "breakage point" in the network topology, signifying a threshold where genomic mutations overwhelm the protein network's ability to maintain its functional structure. And also quantification of network properties, including interaction strengths and overall network density, demonstrating the non-linear relationship between genomic mutations and proteomic topological integrity.The observed breakage point may represent a critical threshold in disease progression, where the accumulation of genomic mutations leads to a collapse in the proteomic interaction network, potentially triggering pathological states. This methodology offers a new perspective on the genotype-phenotype relationship, viewing it through the lens of protein network topology. Our approach provides a framework for future studies to analyze how specific genomic mutations might impact proteomic structures, potentially leading to new insights in cancer research, neurodegenerative disorders, and other mutation-driven diseases. It also suggests that maintaining proteomic topological integrity could be a key factor in cellular resilience against genomic instability.

Student attrition poses significant societal and economic challenges, leading to unemployment, lower earnings, and other adverse outcomes for individuals and communities. To address this, predictive systems leveraging machine learning and Big Data aim to identify at-risk students early and intervene effectively. This project focuses on extracting key parameters from past dropout data to construct a predictive model and alert authorities to intervene promptly. Two preliminary trials refine machine learning models, establish evaluation standards, and optimize hyperparameters. These trials facilitate systematic exploration of model performance and data quality assessment. Achieving 100% accuracy in dropout prediction, the study identifies academic performance as the primary influencer, with early-year subjects like Mechanics and Materials, Design of Machine Elements, and Instrumentation and Control having significant impact. The longitudinal effect of these subjects on attrition underscores the importance of early intervention. Proposed solutions include early engagement and support or restructuring courses to better accommodate novice learners, aiming to reduce attrition rates.

Histamine (HA), a biogenic monoamine, exerts its pleiotropic effects through four H1R–H4R histamine receptors, which are also expressed in brain tissue. Together with the projections of HA-producing neurons located within the tuberomammillary nucleus (TMN), which innervate most areas of the brain, they constitute the histaminergic system. Thus, while remaining a mediator of the inflammatory reaction and immune system function, HA also acts as a neurotransmitter and a modulator of other neurotransmitter systems in the central nervous system (CNS). Although the detailed causes are still not fully understood, neuroinflammation seems to play a crucial role in the etiopathogenesis of both neurodevelopmental and neurodegenerative (neuropsychiatric) diseases, such as autism spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD), Alzheimer's disease (AD) and Parkinson's disease (PD). Given the increasing prevalence/diagnosis of these disorders and their socioeconomic impact, the need to develop effective forms of therapy has focused researchers' attention on the brain's histaminergic activity and other related signaling pathways. This review presents the current state of knowledge concerning the involvement of HA and the histaminergic system within the CNS in the development of neurodevelopmental and neurodegenerative disorders.

The emergence of superhydrophobicity-based antibacterial materials represents a promising approach to upholding surface cleanliness and hygiene, effectively preventing bacterial adhesion. This research describes the synthesis of a superhydrophobic coating with antibacterial and bacteriostatic properties using silica nanoparticles (SiO2 NPs) modified with 1H,1H,2H,2H-Perfluorodecyltriethoxysilane (PFDTES). TEM, XRD, EDS, SEM, and FTIR analyses were conducted to study its morphology and surface characterization. Additionally, the coating was applied on glass substrates using the spray coating method, varying the number of layers to evaluate antibacterial and bacteriostatic properties through turbidimetry and inhibition halo measurement techniques. The durability of the coatings was also assessed by exposing them to outdoor conditions for 35 days. This study aimed to evaluate the antibacterial capacity of the superhydrophobic coating and its weather resistance. The results demonstrate that a superhydrophobic coating with a contact angle ≥150° and a sliding angle ≤10° was successfully synthesized using SiO2 NPs smaller than 10 nm modified with PFDTES. The coating exhibited the ability to inhibit bacterial growth by preventing the adhesion of bacteria such as Escherichia coli and Staphylococcus aureus; moreover, the number of layers correlated with enhanced antibacterial properties. The coating also showed good durability under outdoor conditions. These results support the potential application of superhydrophobic coatings to prevent these bacteria from adhering and growing in areas where they can be harmful.

This article explores the relationship between Wang Yangming's philosophy and the new quality productivity, revealing how the new quality productivity, while inheriting the core ideas of Yangming's philosophy, achieves a higher level through innovation and development. The new quality productivity emphasizes the integration and innovation of knowledge, technology, and information, characterized by knowledge-driven innovation, information technology support, sustainable green development, and global collaborative development. The fusion of Yangming's philosophy and the new quality productivity holds significant theoretical and practical implications.

The study surveyed the use of academic libraries and information seeking behaviour of students at Lusaka Apex Medical University. The objectives of the study were to determine how often LAMU students used the libraries, to ascertain the purpose for which students used the library and to determine the challenges faced in accessing library services. Using a survey research design, 230 students selected using simple random sampling participated. Findings revealed that there were more male (51.1%) students who participated. The study also found that the majority of students (54.7%) were occasionally using the library. Results on the purpose for using the library showed that the majority (39.6%) were using it to read in order to improve personal competence. In relation to the challenges, majority students (42.6%) stressed the inadequacy of relevant materials. The need for librarians to make themselves available to aid students that seek information for different purposes was recommended. This was seen as a way through which many would have access to the available information in their field. There is a need for proper orientation and sensitization to students on how to access both physical and online materials. This would increase the library use as well as improve the performance of students. Lastly, it was recommended that a study on the digital literacy of students be done in order to ascertain their competence and search skills in sourcing for information.

S6K1 (ribosomal protein S6 kinase beta-1) is a critical serine/threonine kinase involved in the regulation of various cellular processes, including protein synthesis, gene expression, and metabolic homeostasis. The structural complexity of S6K1, with its multiple isoforms and unique kinase domain, allows for diverse functionality across different cellular contexts. In this review, we report the intricate structure of S6K1, highlighting the significance of its kinase domain. Additionally, we explored the tissue-specific expression and subcellular localization of S6K1 isoforms, emphasizing their distinct roles in cellular processes. The regulation of S6K1 extends beyond transcriptional control, with post-translational modifications such as phosphorylation and acetylation playing crucial roles in its activity and stability. The physiological implications of S6K1 are vast, influencing processes from cell growth and protein synthesis to immune responses and muscle hypertrophy. However, dysregulation of S6K1 is implicated in numerous pathological conditions, including cancer Studies reveal that altered S6K1 activity, particularly in its phosphorylation state, can lead to reduced neuronal viability, contributing to the progression of diseases such as Parkinson's. This manuscript synthesizes current knowledge on S6K1, offering insights into its multifaceted roles and highlighting its potential as a therapeutic target in various disease contexts.

Objective: In this study, we investigated vitamin D, inflammatory hematologic ratios such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), MHR and plasma atherogenic index (PAI) and possible relationships with insulin resistance in children. Methods: A total of 210 individuals, including 96 children with insulin resistance and 114 children without insulin resistance, aged 6-18 years, who were admitted to the Pediatric Endocrinology Outpatient Clinic at Medicine Hospital, Istanbul Atlas University were included in our study. Result: NLR, PLR, SII and MHR were significantly higher in patients with insulin resistance compared to those without. Fasting insulin, PAI, HOMA-IR, HOMA- were significantly higher and QUICKI was significantly lower in patients with insulin resistance compared to those without insulin resistance. NLR, SII and MHR were lower in normal vitamin D groups than the others were (p

Colorectal cancer (CRC) ranks as the third most prevalent cancer globally, with 25% of patients presenting with metastases; of these, 8% have synchronous liver and peritoneal metastases. Although the concurrent presence of liver and peritoneal metastases was previously considered an absolute contraindication, the feasibility of combined surgery is now being re-evaluated. This study assesses 41 patients who underwent liver surgery for CRC metastases at our center between October 2021 and February 2024. Among these patients, 7 underwent concomitant cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) due to the presence of synchronous liver and peritoneal metastases. We employed simple linear regression to identify parameters that influenced the development of postoperative complications, classified by the Clavien-Dindo (CD) system. The statistical analysis showed only the operative time, the CRS+HIPEC procedure and the length of hospital stay as significative variables on CD outcome, while the different types of liver surgery were not significant. This study suggests that combining liver surgery with CRS+HIPEC may be beneficial for selected patients, potentially improving overall survival without a significant increase in postoperative complications. A multidisciplinary approach is essential to achieve a survival advantage without elevating morbidity rates.

The Gulf of Mannar, a UNESCO World Biosphere Reserve, faces severe overfishing and habitat degradation threats. In this study, we investigate the pivotal role of ecosystem services in sustaining local livelihoods and overall well-being. By conducting a comprehensive survey of 480 respondents across two districts, we gathered extensive data on demographics, livelihoods, fishing practices, reliance on ecosystem services, and community management participation. The analysis reveals a critical dependence on the Gulf's resources (income, food security, traditions) with gender disparities (men fish, women in pre/post-harvest), but fishing is only allowed in the 10km buffer zone (not the core zone). The findings emphasize the promise of community-based strategies, such as Marine Protected Areas and reviving co-management committees, for achieving sustainable fisheries management. However, we also identify gaps, including the need for more nuanced well-being indicators and improved models for community management participation. To address these challenges, we advocate for sustainable fishing practices, tackling social inequities, especially gender disparities in resource access and decision-making, and investing in healthcare, education, and social safety nets for fishing communities. Promoting alternative livelihoods can alleviate pressure on fish stocks, and empowering local communities through capacity building and community-based management initiatives is crucial for ensuring the long-term sustainability of both the Gulf of Mannar ecosystem and the well-being of its dependent communities. This multifaceted approach holds significant promise for balancing ecological health with human prosperity.

As the aging of the world accelerates, clarifying the relationship between cultural differences and ageism is an urgent issue. Therefore, in this study, we conducted a correlation analysis between the six cultural scales of Hofstede et al. [1] and the 10 ageism scales calculated from data on 35,232 people from 31 countries included in the World Values Survey Wave 6 by Inglehart et al. [2]. The results of a partial correlation analysis controlling for economic and demographic factors showed that the cultural scales were correlated with ageism. This is the first study to show that diverse cultural scales are related to multiple dimensions of ageism.

This work focused on the solubility of ethane in three promising ionic liquids {1-Hexyl-3-methylimidazolium bis(trifluormethylsulfonyl) imide [HMIM][Tf2N], 1-Butyl-3-methyl-imidazolium dimethyl-phosphate [BMIM][DMP] and 1-Propyl-3- methylimidazolium bis(trifluoromethyl-sulfonyl)-imide [PMIM][Tf2N]}. The solubilities were measured at 303.15 K to 343.15 K and pressures up to 1.4 MPa using a gravimetric microbalance. The overall ranking of ethane solubility in the ionic liquids from highest to lowest is the following: [HMIM][Tf2N] > [PMIM][Tf2N] > [BMIM][DMP]. The Peng- Robinson equation of state was used to model the experimental data using three different mixing rules: van der Waals one, van der Waals two and Wong-Sandler mixing rules combined with the Non-Random Two-Liquid model. The average absolute deviations for the three mixing rules for the ionic liquids at the three temperatures were (4.39, 2.45 and 2.45) %, respectively. Henry’s Law constants for ethane in [BMIM] [DMP] were the highest (lowest solubility) amongst other ionic liquids studied in this work. The selectivity of CO2 over C2H6 was estimated at the three temperatures and the overall ranking of the selectivity was in the following order: [PMIM][Tf2N] > [BMIM][DMP] > [HMIM][Tf2N]> Selexol. Selexol, a widely used physical solvent in gas sweetening has better selectivity than the three ionic liquids studied. [PMIM][Tf2N], a promising solvent, has the highest selectivity among the three ILs studied, and would therefore be the best choice if in addition to carbon dioxide capture, ethane co-absorption was to be avoided. The enthalpy and entropy of solvation at infinite dilution were also estimated.

Context: Business Process Automation (BPA) is adopted by organizations to improve efficiency, reduce costs, and increase overall business performance. Traditional Business Process Automation (TBPA) is one of the three approaches employed to develop a BPA. TBPA entails developing BPA in a programming language for integrating the relevant applications in the digital ecosystem to execute a given process. Process variability and practitioner unavailability encumber the requirements specification for TBPA software. Objective: This work proposes a log-based approach for TBPA software to make software more adaptable to process changes and reduce reliance on practitioners, by providing a higher alignment among business process requirements and software architecture, and employing process mining to semi-automatically discover the business process during requirements elicitation. Method: The research conducted a case study in a technology institute to assess the approach and report its results in practice. Results: The results revealed significant improvements in adaptability to business process changes and decreased the time spent with practitioners, and, efficiency in development. The approach also presented limitations, including human intervention to accurately obtain the business process, complexity to trace the process into the architecture, data privacy concerns, and risk of network traffic overload. Conclusion: This research demonstrated the effectiveness of traceability between process requirements and software architecture, as well as the use of logs and process mining. These methods made TBPA software enhanced the software adaptability to changes and minimized the reliance on practitioners during requirements elicitation respectively.

In response to the increasing importance of knowledge as a key competitive advantage, the role of knowledge management in value creation cannot be overstated. The International Standards Organization (ISO) has recognized this and announced a Management Standard for Knowledge Management Systems (KMS). This initiative is significant because, by viewing knowledge strategically, organizations are seeking ways to enhance their processes and align them to address their challenges. A synergistic effect can be achieved when another management system highly relevant to KMS is joined and later integrated. This new system is Artificial Intelligence Management (AIMS). The paper is structured as follows: Firstly, we explore knowledge and knowledge management (KM), along with the challenges companies face in implementing and operating KM. Next, we examine the ISO 30401:2018 standard as a guide for KM implementation. Finally, we discuss how ISO 30401:2018 and ISO/IEC 42001:2023 can help solve key organizational problems and support machine learning and knowledge extraction through AI. In conclusion, we summarize the key outcomes of the paper. The main purpose of the paper is to determine how these standards contribute to solving practical problems in the creation and development of a knowledge management system supported by artificial intelligence and to demonstrate their synergistic effect when used together.

Three neutral Pt(II) complexes with diphenylamino-modified 2-phenylpyridine derivatives as cy- clometalating ligands and acetylacetone as the ancillary ligand exhibit aggregation-induced phosphorescent emission (AIPE) properties in THF/H2O. The crystal structures of the complexes highlight the contributions of non-covalent Pt···Pt interactions and hydrogen bonds to the AIPE properties. These AIPE-active Pt(II) complexes 1-3 have been successfully applied to detect picric acid (PA) in aqueous media, affording the lowest limit of detection at 70 nM. Furthermore, three Pt(II) complexes are able to detect PA in common water samples. The quenching of luminescence in the detection can be attributed to photo-induced electron transfer.

Metal additive manufacturing (AM), commonly referred to as 3D printing with metals, is an innovative technology with significant potential to transform industries such as aerospace, automotive, and healthcare. Despite its promise, the field faces several challenges that impact both its technical feasibility and economic viability. This paper explores the primary technical challenges, including material properties and processing complexities, such as the need for precise control of thermal gradients and the mitigation of defects like porosity and residual stresses. Additionally, it addresses the economic barriers, including high initial equipment costs, the need for specialized knowledge, and the relatively slow build speeds compared to traditional manufacturing methods. By examining these challenges, this paper aims to provide a comprehensive overview of the current state of metal additive manufacturing and suggest potential pathways for overcoming these obstacles to facilitate wider adoption and technological advancement in the field.

This study investigates the use of geopolymer technology as an alternative for the management of mine tailings, which is a serious environmental problem in mining environments including that of Arequipa region of Peru. In this study, the mixture of stabilized mine tailings with different percentages of binders (metakaolin and pumice) and their impact on the mechanical, microstructural, and toxicological properties of the synthesized geopolymers were analyzed. The ratios of mine tailings to binder material varied between 100/0 and 0/100. The activation was carried out with an alkaline solution of sodium hydroxide (10M) and sodium silicate (modulus 2.5). 50 mm cubic specimens were fabricated, and 7 mixtures with 3 replicates each were evaluated. The evaluations included compressive strength at 7, 14, 28, and 56 days of curing, chemical analysis by X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR), microstructural characterization by Scanning Electron Microscopy (SEM/EDS), thermal behavior by thermogravimetry and differential thermal analysis (TGA/DTA) between 40°C and 1000°C, and toxicological tests by the Toxicity Characteristic Leaching Procedure (TCLP, EPA 1311) to determine the efficiency of immobilization of toxic metals. The results showed good mechanical strength, reaching 25 MPa at 7 days of curing, high microstructural stability with an average pore size of 7.21 μm, and good efficiency in the immobilization of heavy metals in geopolymers composed of 60% - 40% and 70% - 30% of the mine tailings - binders ratio, as the concentrations of As, Cd, Pb, Hg were below the established thresholds, acquiring the classification of non-hazardous materials. Geopolymers with 30 to 50% binder showed good mechanical behavior, microstructural stability, and high efficiency in the immobilization of heavy metals, complying with current regulations. Therefore, these geopolymers are suitable for various applications and in different environmental conditions.

Metal corrosion poses a significant challenge for industries by decreasing the lifespan of materials and escalat-ing maintenance and replacement costs. This study is critically important as it assesses the corrosion resistance properties of annealed steel wire electrodes coated with manganese, employing chronoamperometry and linear voltammetry techniques. The electrodes were immersed in an electrolyte solution and subjected to chronoam-perometry at various voltages (-0.55 V, -0.60 V, and -0.70 V) and durations (60 seconds and 1800 seconds). Sub-sequently, linear voltammetry was performed over a potential range from -0.8 V to 0.8 V to generate Tafel plots. The Butler-Volmer equation was applied to the data obtained to determine the corrosion current density. The re-sults indicate that the optimal conditions for forming a highly effective protective manganese layer occur at a potential of -0.70 V for 1800 seconds. Under these conditions, the electrodes exhibited superior corrosion re-sistance. The study also revealed that shorter durations and less negative potentials led to less effective manga-nese coatings, with higher corrosion rates and reduced stability. These findings are significant for developing ef-ficient corrosion protection methods in industrial and research applications, providing clear parameters for op-timizing the manganese electrodeposition process on annealed steel.

Achieving the best aesthetic result is a key objective of implant-prosthetic therapy. To maximize the aesthetic outcome, ensuring that implant-supported restorations are in harmony with the peri-implant soft tissues and bone is essential. A comparative analysis of zirconia and titanium dental implants revealed that both materials offer high success rates; however, they present distinct advantages and limitations in clinical practice. Titanium implants, with surface modifications but without chemical composition changes, boast remarkable long-term survival. In contrast, zirconia implants, while presenting high aesthetic and biocompatibility qualities, have a relatively high incidence of material-specific failure, ranging from 4% to 2% after 5-10 years. While titanium implants generally show superior long-term performance, zirconia implants benefit from ongoing advancements aimed at improving their osseointegration and longevity. This study emphasizes the need for short-term and long-term studies, complemented by randomized controlled trials (RCTs), which are essential for optimizing implant materials and ensuring patient satisfaction. Continued innovation and research are crucial for advancing dental implant technology and enhancing the quality of life for patients requiring dental restorations. Finally, it is important to understand that all materials have both advantages and disadvantages, so the choice of the optimal material should be based on the specific purpose.

Several technologies have been introduced into neurorehabilitation programs to en-hance traditional treatment of individuals with Spinal Cord Injury (SCI). Their effec-tiveness has been widely investigated but their adoption has not been properly quanti-fied. The aim of this study is to assess the distribution of conventional (Treatment As Usual – TAU) and technology-aided (Treatment With Technologies – TWT) treatments, conveniently grouped based on different therapeutic goals, in a selected SCI unit. Data from 104 individuals collected in 29 months were collected in a custom database and categorized according to both the conventional American Impairment Scale classifica-tion and a newly developed multifactor (MF) clustering approach, that considers addi-tional sources of information (the lesion level, the level of independence in the activi-ties of daily living and the hospitalization duration). Results indicated an average technology adoption of about 30%. Moreover, the MF clusters were less overlapped and the differences in TWT adoption were more pronounced than in AIS-based clus-tering. MF clustering was capable of grouping individuals based both on neurological features and functional abilities. In particular, individuals with motor complete inju-ries were grouped together, whereas individuals with sensorimotor incomplete SCI were collected separately based on the lesion level. Analyzing TWT adoption, we found that in case of motor complete SCI, TWT for muscle tone control and modulation were mainly selected while the other types of TWT were seldom adopted. Even for in-dividuals with incomplete SCI the most frequent rehabilitation goal was muscle tone modulation, regardless of the AIS level, and technologies to improve walking ability and balance control were mainly used for individuals with thoracic or lumbar lesions. Analyzing TAU distribution, we found that the highest adoption of muscle tone mod-ulation strategies was reported in case of individuals with motor complete SCI, i.e. in cases when almost no gait training was pursued. In case of cervical motor incomplete SCI, compared to thoracic and lumbar incomplete SCI, there was a greater focus on muscle tone control and force recruitment in addition to walking, than on balance training.

Understanding the interaction between pharmaceuticals and serum proteins is crucial for optimizing therapeutic strategies, especially in patients with coexisting chronic diseases. The primary goal of this study was to assess the potential changes in binding affinity and competition between glipizide (GLP, a second-generation sulfonylurea hypoglycemic drug) and losartan (LOS, a medication commonly prescribed for hypertension, particularly for patients with concurrent diabetes) with non-glycated (HSA) and glycated (gHSAGLC, gHSAFRC) human serum albumin using multiple spectroscopic techniques (fluorescence, UV-visible absorption, and circular dichroism spectroscopy). The results indicate that FRC is a more effective glycation agent for HSA than GLC, significantly altering the albumin structure and affecting the microenvironment around critical amino acid residues, Trp-214 and Tyr. These modifications reduce the binding affinity of LOS and GLP to gHSAGLC and gHSAFRC, compared to HSA, resulting in less stable drug-protein complexes. The study reveals that LOS and GLP interact nonspecifically with the hydrophobic regions of the albumin surface in both binary (ligand-albumin) and ternary systems (ligand-albumin-ligandconst) and specifically saturate the binding sites within the protein molecule. Furthermore, the presence of an additional drug (GLP in the LOS-albumin complex or LOS in the GLP-albumin complex) complicates the interactions, likely leading to competitive binding or displacement of the initially bound drug in both non-glycated and glycated albumins. Analysis of the CD spectra suggests mutual interactions between GLP and LOS, underscoring the importance of closely monitoring patients co-administered these drugs to ensure optimal therapeutic efficacy and safety. Początek formularzaDół formularza

Arthrospira platensis (Ap) and Bacillus coagulans (Bc) have been successfully used to develop functional foods, but not a combination of both regarding functional implications in nutritional value and antioxidant capacity. This work aimed to develop an artisanal wheat flour pasta with egg using 5% A. platensis and 1% B. coagulans GBI 6068 (Bc+Ap). Uncooked pasta was characterized regarding nutritional value; furthermore, total phenolic content, antioxidant capacity (by ABTS and FRAP), pigment content (chlorophyll a + b, and total carotenoids), colorimetry assay, textural profile analysis, buffering capacity and probiotic viability were carried out on uncooked and cooked pasta to assess the changes induced by cooking. The Bc+Ap pasta showed enhanced nutritional value with a significant increase in protein content (30.61%). After cooking, the pasta increased phenolic content (14.22% mg GAE/g), antioxidant capacity (55.59% µmol Trolox Equivalents/g and 10.88% µmol Fe+2/g) for ABTS and FRAP respectively, pigment content (6.72 and 1.17 mg/100g), for chlorophyll a+b and total carotenoids respectively, but relative positive impacts on colorimetric parameters in contrast to control (wheat flour pasta). Furthermore, Bc+Ap showed improved firmness (59%, measured in g), buffer capacity (87.80% μmol H+(g × ΔpH)−1), and good probiotic viability (7.2 ± 0.17 log CFU/g) after the cooking process.

In manufacturing chatter is an unwanted phenomenon that can lead to product quality reduction and tool wear. Real time chatter detection is key to preventing these issues and improving overall machining efficiency. In this paper we propose an unsupervised chatter detection method using autoencoders (AE) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm that uses internal signals of Computer Numerical Control (CNC) machines. The proposed method starts by using an AE to extract features from raw internal signals collected from CNC machines. This step reduces the dimensionality of the data and captures the underlying patterns of chatter. Then the extracted features are fed into DBSCAN clustering algorithm which is a density based algorithm that groups similar data points and identifies outliers. We tested the proposed method with real world data collected from various CNC machines. The results show that our unsupervised chatter detection method has high accuracy, precision and recall, can detect chatter and distinguish it from normal machining. Also the method is robust to noise and can adapt to dynamic machining conditions. In summary our work presents an unsupervised chatter detection method using AE and DBSCAN clustering that uses internal signals of CNC machines. This method is a reliable and efficient solution for real time chatter detection so manufacturers can improve product quality, optimize machining process and reduce tool wear during machining.

Exosomes, nanoscale extracellular vesicles, are a hot area of investigation in the biomedical field, as they have been shown to play a crucial role in the physiology of numerous tissues, including bone. This study explores the landscape of exosome-based bone regeneration research using infometric techniques. By relying on BERTopic, an advanced topic modeling algorithm, we analyzed a comprehensive corpus of scientific literature to identify key themes and trends in exosome research in the bone regeneration field. We then extracted significant concepts from the abstracts of the corpus and we used them to create knowledge graphs using GPT 3.5 turbo Large Language Model, to map the distribution of information within this domain. The resulting ide-oscape highlights the key ideas that aggregate most of the recent research in the area, from mesenchymal stem cell-derived exosomes to engineered exosome-integrated biomaterials. This exploration provides a holistic view of the field and uncovers its emerging trends, providing useful insight to guide future research directions.

The article considers the issues of ensuring operational performance and environmental sustainability of marine diesel engines by using biodiesel fuel. The research was conducted on 5S60ME-C8 MAN-B&W Diesel Group and 6DL-16 Daihatsu Diesel marine diesel engines, which were operated using RMG380 petroleum fuel and B10 and B30 biodiesel fuels. The efficiency of biofuel usage was assessed based on environmental (reduced nitrogen oxide concentration in exhaust gases) and economic (increased specific effective fuel consumption) criteria. It was found out that the use of B10 and B30 biofuels provides reduction of nitrogen oxides concentration in exhaust gases by 14.71–25.13 %, but at the same time increases specific effective fuel consumption by 1.55–6.01 %. Optimum fuel injection advance angles were determined that ensure the best thermal energy, economic and environmental performance of diesel engines. The optimum angle of biofuel supply advance is determined experimentally and should correspond to the limits recommended by the diesel engine operating instructions. It has been proven experimentally that the use of biofuel increases the environmental sustainability of marine diesel engines by 13.75–29.42 %. It increases the diesel engines environmental safety in case of emergency situations, as well as accidental and short-term emissions of exhaust gases with an increased content of nitrogen oxides into the atmosphere - phenomena that are possible in starting modes of diesel engine operation, as well as in modes of sudden load changes. It is the increase in the environmental friendliness of marine diesel engines in the case of using biofuel that is the most positive criterion and contributes to the intensity of biofuel use in power plants of sea vessels.

Brazil is the world leader in pesticide consumption, and its indiscriminate use puts farmers’ health at risk. The CYP2C9 gene stands out for encoding the CYP2C9 enzyme, which metabolizes several endogenous substrates and specific xenobiotics, especially pesticides. Our goal is to study the risk of pesticide use, espe-cially the herbicide glyphosate, in the development of diseases and the association with two CYP2C9 poly-morphisms, in farmers living in the southern region of Espírito Santo state, Brazil. The allelic frequency of CYP2C9*1, CYP2C9*2 and CYP2C9*3 was determined in blood samples from individuals exposed or not to pesticides using real-time PCR. 304 blood samples were analyzed, dividing CYP2C9 genotypes into three metabolization classes: normal, intermediate, and slow. Our results show that normal metabolizers are more vulnerable to diseases such as blood pressure changes and cardiovascular and kidney problems, while in-termediate metabolizers show an association with attention deficit disorder and miscarriages, suggesting that farmers in the studied region developed symptoms correlated to the CYP2C9 genotype they have. This work is pioneering in associating specific genetic variations and health risks with pesticide exposure, em-phasizing the importance of personalized medicine and stricter regulation of pesticide use for public health and occupational safety.

Cardiac arrest may cause significant hypoxic-ischemic injury leading to coma, seizures, myoclonic jerks, or status epilepticus. Mortality is high but accurate prognostication is challenging. A multimodal approach is employed, in which electroencephalograph (EEG) forms a key part with several recognised patterns of prognostic significance. In this retrospective study, clinical and qualitative features of the EEG of patients admitted to the Intensive Care Unit (ICU) at Kingston General Hospital following cardiac arrest from 2017-2020 were reviewed. The study included 81 adult patients (>18 years). Outcome was assessed using the Cerebral Performance Category as 1-2 (favourable) or 3-5 (unfavourable). EEG patterns were divided into groups within the highly malignant, malignant, and benign patterns described in the literature. There were a wide range of causes and 22% had a favourable outcome. Highly malignant, malignant, and benign patterns were associated with survival in 0%, 78% and 100% respectively and favourable outcomes in 0%, 44% and 100%. All patients with seizures died and 94% with myoclonus had unfavourable outcomes. In contrast, EEG reactivity and improvement on follow-up EEG was associated with a favourable outcome. In conclusion, highly malignant EEG, seizures and myoclonus were associated with unfavourable outcome, while patient with malignant EEG had better outcome.

General derivation of the well-known Ren-Otsuka relation, 1/α (dTo)/dx=-α/β (where To, x, α and β(>0) are the transformation temperature, the composition, as well as the composition and temperature coefficient of the critical shear constant, c’, respectively) for shape memory alloys, SMAs, is provided based on the similarity of interatomic potentials in the framework of dimensional analysis. A new dimensionless variable, to(x)=(To (x))/(Tm (x) ), describing the phonon softening (where Tm is the melting point) is introduced. The dimensionless values of the heat of transformation, H, and entropy, S as well as the elastic constants c’, c44, A=c44/c' are universal functions of to(x) and have the same constant values at to(0) within sub-classes of host SMAs having the same type of crystal symmetry change during martensitic transformation. The ratio of (dto)/dx and α has the same constant value for all members of a given sub-class and relative increase of c’ with increasing composition should be compensated by the same decrease of to. In the generalized Ren-Otsuka relation the anisotropy factor, A appears instead of c’ and α as well as β are the differences of the corresponding coefficients for the c44 and c’ elastic constants. The obtained linear relation between h and to rationalizes the observed empirical linear relations between the heat of transformation measured by DSC (QAM) and the martensite start temperature, Ms.

Understanding and addressing dehumanization in healthcare is crucial due to its pro-found impact on patient care, ethical implications on patient dignity and autonomy, and its potential to affect the psychological well-being of healthcare professionals. The primary aim of this study was to establish reliable and valid instruments measuring two different types of dehumanization, namely animalistic dehumanization (i.e., stripping one of their uniquely human characteristics) and mechanistic dehumanization (i.e., stripping one of their human nature characteristics) among healthcare professionals. In a cross-sectional validation study among healthcare professionals, we tested measures of both animalistic and mechanistic dehumanization, focusing on dehumanization of patients (hetero-dehumanization) and oneself (self-dehumanization), respectively. All measures were developed and validated based on a concept analysis, a literature review, and an appraisal of pre-existing scales. The research was conducted among 400 nurses and medical doctors employed in Greek public hospitals. Coefficient Validity Ratio re-sults showed that 100% of items were acceptable for both measures. The newly estab-lished and validated hetero-dehumanization scale encompassed two-factors (factor 1: animalistic dehumanization, factor 2: mechanistic dehumanization, Cronbach’s alpha was equal to 0.86 for each measure). The self-dehumanization scale was a mono-factorial measure mechanistic dehumanization (Cronbach’s alpha = 0.97). Two validated measures of (self and hetero-) animalistic and mechanistic dehumanization measures were developed for the assessment of dehumanization among health profes-sionals, which will form the basis for future research in this important scientific field.

Pharmacist-prescribed hormonal contraception (HC) is supported by a majority of pharmacists and pharmacy students; however, few studies have evaluated perceptions of non-community pharmacists, or differences in geographic areas. The primary objective of this study is assess differences between community and non-community pharmacists in perceptions of pharmacist HC prescribing. Secondary objectives include assessment of community pharmacist interest in prescribing HC, and differences in perceptions between pharmacists in metropolitan and nonmetropolitan areas. A survey was emailed in early 2022 to 2592 Georgia pharmacists, with Likert questions assessing interest, perceptions, comfort, and perceived barriers regarding pharmacist prescribed HC. Completed survey response rate was 11.8%. Regardless of practice site, a majority agreed pharmacists are well-trained to prescribe HC (Community 61.8% vs. Non-community 68.1%, p=0.25) and provision of HC services is within the pharmacist’s scope (Community 73.6% vs. Non-community 74.2%, p=0.90). Overall metropolitan and non-metropolitan community pharmacists' perceptions were similar, however more metropolitan pharmacists believed pharmacists are well trained to prescribe HC (66.7% vs 48.7%, p=0.049) and that it is within their scope of practice (78.1% vs. 61.5%, p=0.045). In summary, the majority of pharmacists, regardless of practice type, believe that pharmacists are prepared to prescribe HC and it is a part of pharmacist’s professional scope of practice.

Photodynamic therapy has emerged as a non-invasive treatment modality for various diseases, leveraging photosensitizing compounds to induce localized cytotoxicity upon light activation. This review explores the isolation and characterization of photosensitizing compounds sourced from microalgae, focusing on their potential applications in photodynamic therapy. Microalgae represent a rich source of bioactive molecules, including chlorophylls, phycobiliproteins, and carotenoids, which exhibit inherent photosensitizing properties. Methodologies for the extraction and purification of these compounds from different microalgal species are discussed, emphasizing the importance of optimizing extraction techniques to enhance yield and purity. Characterization techniques such as UV-Vis absorption spectroscopy, fluorescence spectroscopy, and mass spectrometry are highlighted for elucidating the chemical structures and photophysical properties of isolated compounds. Furthermore, the review examines the photodynamic efficacy of microalgae-derived photosensitizers through in vitro and in vivo studies, assessing their cytotoxic effects on cancer cells and antimicrobial activity against pathogens. The integration of microalgae-derived photosensitizers into PDT protocols represents a promising avenue for developing sustainable and effective therapeutic strategies, underscoring the potential of these natural compounds in advancing biomedical applications.

The Fading Affect Bias (FAB) occurs in autobiographical memory when unpleasant emotions fade faster than pleasant emotions and the phenomenon appears to be a form of emotion regulation. As emotion regulation is positively related to problem-solving, the current study examined FAB in the context of problem-solving. In-person and online studies asked participants to provide basic demographics, describe their problem-solving abilities, and rate various healthy and unhealthy variables including emotional intelligence and positive problem-solving attitudes. Participants also completed an autobiographical event memory form for which they recalled and described 2 pleasant and 2 unpleasant problem-solving and non-problem-solving events and rated the initial and current affect and rehearsals for those events. We found a robust FAB effect that was larger for problem-solving events than for non-problem-solving events in Study 1 but not in Study 2. We also found that FAB was positively related to healthy variables, such as grit, and negatively related to unhealthy variables, such as depression. Moreover, many of these negative relations were inverted at high levels of positive problem-solving attitudes, and these complex interactions were partially mediated by talking rehearsals and thinking rehearsals.

The whimsical Las Vegas/Monte Carlo cubic dice are generalized to construct the combinatorial problem of enumerating all n-dimensional hypercube dice, and dice of other shapes that exhibit cubic, icosahedral and higher symmetries. By utilizing powerful generating function techniques for various irreducible representations, we derive the combinatorial enumerations of all possible dice in n-dimensional space with hyperoctahedral symmetries. Likewise a number of shapes that exhibit icosahedral symmetries such as a truncated dodecahedron and a truncated icosahedron are considered for the combinatorial problem of dice enumerations with the corresponding shapes. We consider several dice with cubic symmetries such as truncated octahedron, dodecahedron and Rubik’s cube shapes. It is shown that all enumerated dice are chiral and we provide the counts of chiral pairs of dice in the n-dimension space. During the combinatorial enumeration, it was discovered that two different shapes of dice exist with the same chiral pair count culminating into the novel concept of isochiral polyhedra. The combinatorial problem of dice enumeration is generalized to multi-coloring partitions. Applications to chirality in n-dimension, molecular clusters, zeolites, mesoporous materials, cryptography and biology are also pointed out. Applications to nonlinear n-dimensional hypercube and other dicey encryptions are exemplified with romantic, clandestine messages; “I love U” and “V Elope at 2”.

Background: Diagnosis of acute kidney injury (AKI) relies on serum creatinine (SCr) changes. This study investigated if urinary aminopeptidases are early and predictive biomarkers of cardiac surgery associated-AKI (CSA-AKI). Methods: Glutamyl aminopeptidase (GluAp), alanyl aminopeptidase (AlaAp), dipeptidyl peptidase-4 (DPP4), proteinuria, albuminuria, N-acetyl-β-D-glucosaminidase (NAG) and neutrophile gelatinase-associated lipocalin (NGAL) were measured in urine samples from 44 patients at arrival in Intensity Care Unit (ICU) after cardiac surgery. Sensitivity, specificity, positive and negative predictive value for diagnosis of stages 1, 2 and 3 of AKI were analyzed for the highest quartile of each marker. We also studied the relationship with SCr after surgery, 6- and 12-months glomerular filtration rate (GFR) and other long-term events over the next 5 years. Results: GluAp diagnosed the maximal number of patients that developed stage 2 or 3 of AKI, increasing diagnostic sensitivity from 0 to 75 %. Besides, GluAp and DPP4 was related to the decrease in GFR at 6- or 12-months after surgery. Conclusions: Urinary aminopeptidases are a potential tool for the early diagnosis of CSA-AKI, being GluAp the most effective marker for diagnosing stages 2 or 3 of AKI at ICU admission. GluAp and DPP4 serve as predictive biomarkers for the decrease in GFR.

This study investigates the dynamic relationship between leverage and dividend policy in Nigerian manufacturing enterprises. Utilizing panel data from 26 firms between 2016 and 2020, our findings reveal that while dividend payments boost firm value, leverage typically diminishes it. Intriguingly, when leverage interacts with dividend policy, the combined effect on firm value becomes significantly positive. This observation, despite Nigeria's institutional differences from advanced economies, supports modern capital structure theories such as the pecking order and static trade-off theories. Our results suggest that for mature Nigerian companies with limited growth opportunities, high leverage and dividends effectively mitigate the "free cash flow" problem, curbing managerial tendencies to overinvest or underinvest. Thus, leverage and dividends serve as complementary mechanisms for monitoring and controlling managerial discretion. Consequently, firms with high leverage ratios can leverage dividend policies as disciplinary tools, and vice versa. This underscores the necessity for Nigerian manufacturing firms to carefully balance debt and equity to sustain market confidence and investment potential.

This paper investigates, experimentally and numerically, the buckling behavior of innovative sustainable Low-Cost Bamboo Composite (LCBC) structural columns under compressive loading. The LCBC columns are manufactured from bamboo culms in combination with bio-based resins to form composite structural columns. Different LCBC cross-sectional configurations are investigated in this study including the Russian doll (RD), Big Russian doll (BRD), Hawser (HAW), and Scrimber (SCR). Extra-large, large, medium, and small sizes of bamboo are employed to form the proposed configurations. Two bio-based resins including one bio-epoxy and one furan-based resin, in addition to a soft bio-based filler and a synthetic epoxy resin are applied. The bamboo species used as the cast-in-place giant bamboo for all configurations include Moso, Guadua, and Tali. In addition to experimental testing of the slender LCBC short columns, finite element analysis (FEA) software ABAQUS is applied to model the composite columns and predict their behavior. A buckling analysis using static Riks method is carried out to determine the LBCB’s response to axial compressive loading. A model is calibrated using test results with various imperfections, accounting for the variable behavior of each bamboo specimen, to accurately predict the behavior of LCBC columns with different resin contents. Slender LCBC columns showed maximum stress at buckling up to 60 MPa, highlighting the potential of bio-based resins for structural applications. The study found that the samples with bio-epoxy resin (BE2) exhibited enhanced material stiffness when compared to with synthetic epoxy (EPX) and furan-based resin (PF1), while PF1 specimens demonstrated increased ductility. The BE2 samples showed strain hardening in their stress-strain behavior, and the PF1 samples exhibited a long plateau phase before reaching the maximum load. Among the specimens with Moso bamboo and BE2 resin, those with SCR and HAW configurations achieved the highest compressive strengths.

This study explores the integration of computer vision with topology optimization for additive manufacturing, with a focus on maximizing eigenfrequency in a design domain. Utilizing cus-tom-developed photogrammetry software, high-resolution images are processed to generate de-tailed 3D models, subsequently converted to STL files with precision. Adaptive meshing in COMSOL Multiphysics, controlled through a MATLAB API, ensures optimal mesh resolution. Prioritizing resource conservation in extraterrestrial environments, the original volume is reduced by 50% while preserving structural integrity. The design domain undergoes rigorous topology optimization in MATLAB, supported by COMSOL's advanced FEM simulation. The optimized design exhibits a 57% performance improvement and a 50% weight reduction, maintaining desired vibration characteristics, validating the efficacy of the modifications. Moreover, the case with an eccentric mass shows a significant 64% increase in eigenfrequency.

Livestock production in the Cajamarca, La Libertad and Amazonas basins is based on pasture-based feeding with "Cajamarquino ecotype" ryegrass under monoculture or in association with white clover. The objective of this research work was the morphological characterization and evaluation of the productive yield and cutting time of annual ryegrass - Lolium multiflorum L. Six local genotypes of Lolium multiflorum in six locations were characterised, using the multiplicative interaction effect model and additive main effects for the analysis of interaction and variability of the genotypes and locations. Ryegrass “Cajamarquino ecotype” is semi-erect with intermediate growth, with a dark green colouring, 0.8 cm broadleaf, and can reach an average stem length of 46 cm, up to 1.6 cm.day, achieving the growth of the fourth leaf after 28 days under adequate management conditions. Despite the differentiated characteristics, according to the BLASTn evaluation, the ITS1 sequences showed an identification greater than 99.9% similar to Lolium multiflorum L. It was determined that the Cajamarquino ecotype produces from 3.52 to 4.98 Mg.ha.biomass cutting. Likewise, the pasture's quality is better when used at 30 days with 14.84% protein and at 45 days, it achieves 12.75% protein with a biomass of 4.05 Mg.ha.cut. With these morphological and yield characteristics, the "Cajamarca ecotype" ryegrass is a well-adapted species for local livestock farming. These species are adapted to the Sierra Norte area of Peru.

The increasing variability of precipitation, higher temperatures and recurring droughts in the semi-arid regions due to climate change are leading to increased aridity, resulting in scarcer water resources for crops. The present study aimed to analyse the spatial distribution of climate variables related to water resources in the olive-growing areas throughout Extremadura, southwestern Spain. To perform this task, three climate variables were used: potential evapotranspiration of the crop, the FAO aridity index and the annual water requirement. Considering data from 58 weather stations located throughout Extremadura and 17 along boundaries with at least 30-year length (within the 1991-2021 period), each variable was computed at each station. After calculating some descriptive statistics, a multivariate geostatistical (regression-kriging) algorithm, incorporating secondary information on elevation and latitude, was used to accurately map each climate variable. Later, temporal trends and their magnitude were analysed using the Mann-Kendall test and the Sen’s estimator, respectively. The highest evapotranspiration and water requirements are located in the southern part of the region, which has large areas dedicated to olive cultivation. In the northern part of the region, there is greater spatial variability in evapotranspiration and, consequently, in water requirements for olive groves due to the more rugged topography. Similarly, the olive-growing areas with the highest aridity are also in the south of Extremadura. In most areas of Extremadura, olive cultivation requires appropriate irrigation for optimal productivity. According to evapotranspiration trends, the water requirements will become greater in the future. However, it is not guaranteed that the water supply will be sufficient in olive-growing areas where aridity is higher and water resources are scarce. The results of this study are very important for evaluating water deficit and water resources in vulnerable olive-growing areas throughout Extremadura.