An overview of the link between nonequilibrium thermodynamics and complexity theory is offered. It is shown how the rate of entropy production can be quantified through the spectrum of the Lyapunov exponents. It was shown how the entropy production per unit of time meets the necessary and sufficient conditions to be a Lyapunov function and constitutes per se an extremal principle. The entropy production fractal dimension conjecture was established. It is shown how the rate of entropy production as a non-extremal criterion represents an alternative way of sensitivity analysis of differential equations. Finally, an extension to biophysical-chemical systems, on the one hand, the use of the dissipation function is shown, as a thermodynamic potential out of equilibrium, in the characterization of biological phase transitions. On the other hand, it was evidenced how the rate of entropy production represents a physical quantity to evaluate the complexity and robustness of cancer.

Purpose: This study builds upon an established effective training method to investigate the advantages of high variability phonetic identification training for enhancing lexical tone perception and production in Mandarin-speaking pediatric cochlear implant (CI) recipients, who typically face ongoing challenges in these areas. Method: Thirty two Mandarin-speaking children with CIs were quasi-randomly assigned into the training group (TG) and the control group (CG). The sixteen TG participants received five sessions of high variability phonetic training (HVPT) within a period of three weeks. The CG participants did not receive the training. Perception and production of Mandarin tones were administered before (pretest) and immediately after (posttest) the completion of HVPT via lexical tone recognition task and picture naming task. Both groups participated in the identical pretest and posttest with the same time frame between the two test sessions. Results: TG showed significant improvement from pretest to posttest in identifying Mandarin tones for both trained and untrained speech stimuli. Moreover, perceptual learning of HVPT facilitated trainees’ lexical tone production as rated by a cohort of 10 Mandarin-speaking adults with normal hearing. In contrast, CG did not exhibit significant changes in either perception or production. Conclusion: The results represent initial evidence of HVPT-induced transfer of perceptual learning to lexical tone production in CI users, which supports the application of this speech training protocol to aural rehabilitation practice.

Udder health of dairy cows is related to their productivity and welfare. The period from dry-off to calving and early lactation is crucial. Ultrasonography is a useful and practical tool for the examination of the mammary parenchyma and blood flow. This observational study investigated the relationship between udder echotexture features, blood flow volume (BFVol) in the milk vein, milk somatic cell count (SCC) and daily milk yield (DMY) from late lactation, throughout dry period and consecutive early lactation. Seventeen repeated measurements were performed on 21 Holstein cows. The udder parenchyma was examined with B-mode ultrasonography. Udder echotexture was studied using 15 features: Numerical Pixel Value (NPV), Pixel Standard Deviation (PSD), Skewness, Excess, Contrast, Homogeneity, Correlation, Entropy, Run Percentage, Long Run Emphasis, Grey Value Distribution, Runlength Distribution, Gradient Mean Value, Gradient Variance and Percentage of Non-zero Gradients. Blood flow in the milk vein was examined with spectral Doppler. Linear mixed effects models were employed to investigate relationships between BFVol, udder echotexture features, SCC and DMY, throughout the study period. Our models showed that a 1-kg increase in DMY was associated with a significant increase of 0.25 L/min in the expected BFVol, and that a 1,000,000-cells/mL increase in SCC was associated with a significant BFVol decrease of 0.49 L/min, keeping all other variables constant. Multivariable models showed significant associations between DMY and NPV, PSD and Long Run Emphasis, and between SCC and NPV, PSD, Gradient Mean Value, Homogeneity, Gradient Variance and Entropy. In conclusion, udder echotexture and BFVol in the milk vein are related to SCC and milk yield. Ultrasonography can be used for the comprehensive assessment of udder health in the direction of precision dairy farming.

Heavy metals and metalloids (HMs) are environmental pollutants, most notably cadmium, lead, arsenic, mercury, and chromium. When HMs accumulate to toxic levels in agricultural soils, these non-biodegradable elements adversely affect crop health and productivity. The toxicity of HMs on crops depends upon factors including crop type, growth condition, and developmental stage; nature of toxicity of the specific elements involved; soil physical and chemical properties; occurrence and bioavailability of HM ions in the soil solution; and soil rhizosphere chemistry. HMs can disrupt normal structure and function of cellular components and impede various metabolic and developmental processes. This review evaluates: (1) HM contamination in arable lands through agricultural practices, particularly due to chemical fertilizers, pesticides, livestock manures and compost, sewage-sludge based biosolids, and irrigation; (2) factors affecting the bioavailability of HM elements in the soil solution, and their absorption, translocation, and bioaccumulation in crop plants; (3) mechanisms by which HM elements directly interfere with the physiological, biochemical, and molecular processes in plants with particular emphasis on the generation of oxidative stress, inhibition of photosynthetic phosphorylation, enzyme/protein inactivation, genetic modifications, and hormonal deregulation, and indirectly through inhibition of soil microbial growth, proliferation, and diversity; and (4) visual symptoms of highly toxic non-essential HM elements in plants with an emphasis on crop plants. Finally, suggestions and recommendations are made to minimize crop losses from suspected HM contamination in agricultural soils.

Nutrient release from marine sediments in Osaka Bay has a significant impact on nutrient concentrations in seawater. A tsunami induced by the Nankai Trough earthquake may disturb marine sediments in the inner part of Osaka Bay. An incubation experiment to estimate the release rates of NH4-N and PO4-P was conducted to understand the present conditions and to quantify the changes caused by tsunamis. Two types of cores were created: a "control core" representing the current sediment, and a "redeposition core" representing the redeposition after the tsunami. The release rates have been decreasing since the year 2000 and have remained low. The experimental results suggest that the release rate after exposure to an aerobic environment by a tsunami may decrease to approximately 70% for NH4-N and 60% for PO4-P of the current level. In the past, the release rates were values experienced in the inner part of Osaka Bay. However, the reduction in the release rate by tsunamis may be more limiting for primary production under the current situation where the contribution of release for nutrients in seawater is significant.

The sustainable metabolic engineering (SME) concept was defined by Stalidzans and Dace as an approach for the selection of most sustainable metabolic engineering designs taking the economic, environmental and social components of sustainability into account. In the centre of sustainability calculations is a genome scale metabolic model that provides full balance of all incoming and outgoing metabolic fluxes at steady state. Therefore, sustainability indicators are assigned for each exchange reaction enabling calculation of sustainability features of consumption or production of each metabolite. The further development of the SME concept depends on its implementation at the computational level to acquire applicable results – sustainable production strain designs. This study proposes for the first time a workflow and tools of SME implementation using constraint based stoichiometric modelling, genome scale metabolic models and growth coupled product synthesis approach. For SME application demonstration purposes, a relatively simple engineering task has been carried out. The most sustainable designs have been identified using Escherichia coli as chassis organism, glucose as a substrate and gene deletions as metabolic engineering tool. A growth coupled production design tool has been used to reduce the variability of sustainability. The 10 000 most sustainable designs were producing succinate as the main product with the number of deleted genes ranging from two to ten. A big number of similar designs has been identified due to the combinatorial explosion of different alternative combinations of gene deletion sets that result in interruption of the same metabolic pathways with the same impact on the metabolism.

Riverine particulates dominate the transport of vital nutrients like Si, Fe or P to the ocean mar-gins, where they may increase primary production by acting as slow release fertilizer. Further-more, the supply of particulate surface area to the ocean is considered to be a major control or-ganic carbon burial. Taken together, these observations suggest a close link between the supply of riverine particulate material and the organic carbon cycle. To explore this link, we conducted microcosm experiments to measure the growth of the marine diatom Thalassiosira weissflogii in the presence and absence of different types and concentrations of riverine particulate material. Results demonstrate a strong positive effect of riverine particulate material on diatom growth with increased total diatom concentrations and slowed post-exponential death rates with in-creasing particulate concentration. Moreover, SEM and optical microscope investigations con-firm that riverine particulates facilitates organic carbon burial through their role in the aggrega-tion and sedimentation of phytoplankton. The supply of riverine particulate material has been shown to be markedly climate sensitive with their fluxes increasing dramatically with increas-ing global temperature and runoff. This pronounced climate sensitivity implies that riverine particulates contribute substantially in regulating atmospheric CO2 concentrations through their role in the organic carbon cycle.

Renewable active sludge is a smart material for wastewater treatment and the protection of surface water bodies. The generated pellets (dried and pelletised dehydrated anaerobically stabilised excess sludge) are produced in a quantity of 31.4 g ± 5.6 g dry matter (DM) per one Population equivalent (PE) calculated to COD (PE_COD) in one day. As pellets are combustible material, their energy utilisation must reach sustainable development goals (SDGs) - a bridge must be created between »treated sewage sludge as the tool to remove pollutants and nutrients from wastewater« and »preparation of the valuable material as a solid recovered fuel (SRF) that meets customer-specific requirements«. Technical Report CEN/TR 15508 and Technical Standard EN ISO 21640 set up methods for specifying and classifying pellets as an SRF. In the last eleven years (2010 – 2021), pellets' net calorific value (NCV) is 13.0 ± 0.7 MJ kg^-1 as received (ar). In 2021, the 80^th percentile of the Hg/NCV ratio was 0.079 mg Hg MJ^-1. In 2010 – 2021, the annual amount of Hg transferred to stakeholders reduced by 64.3 % m/m - from 10.1 kg to 3.67 kg. The halogen contents of the pellets do not threaten corrosion to the incineration facility. Stable pellets' energy potential and perspective ash composition for critical raw materials recovery qualify pellets as a specific waste stream and a renewable material for SRF production.

In the article, the fireball formed in the collision of relativistic nuclei is considered as a quantum object. Based on this, an attempt is made to explain the difference in the measurements of hyperon yields in the two experiments - NA49 and NA57. Using the basic principles of quantum mechanics, it was shown that a fireball can have two quantum states - with and without ignited Quark-Gluon Plasma (QGP). With an increase of the collision energy of heavy ions, the probability of QGP ignition increases. At the same time, the probability of the formation of fireball without QGP ignition also remains nonzero even at nuclear collision energies that are much higher than the threshold QGP formation energy, which may be erroneously considered to be fixed and which is intensively sought in modern heavy ion accelerators. Thus, at SPS energy of heavy ion collisions \sqrt{s_{NN}} = 17.3 GeV, which is much higher than the assumed threshold energy of QGP formation in the region around or slightly above of \sqrt{s_{NN}} = 3 GeV, only half of the central collisions of heavy ions bring to the formation of a fireball consisted of deconfined matter (quarks and gluons), the remaining half of the collisions lead to the formation of a fireball from only hadronic matter (mesons, nucleons, hyperons etc.).

Background. Diesel exhaust particles (DEPs) have a great impact on general increase of atopic diseases worldwide. However, it is still unknown whether DEPs induce systemic B-cell IgE class switching in secondary lymphoid organs or locally in lungs, in inducible bronchial-associated lymphoid tissue (iBALT). The aim of this work was to identify the exact site of DEPs mediated B-cell IgE class switching and pro-allergic antibodies production. Methods. We immunized BALB/c mice with different OVA doses (0.3 and 30 µg) intranasally in the presence and absence of two types of DEPs, SRM1650B and SRM2786. We used low (30 µg) and high (150 µg) DEPs doses in our study. Results. Only high DEP dose induced IgE production regardless of particle type. Local IgE class switching was stimulated upon treatment with both types of particles with both low and high antigen doses. Despite the similar ability of two standard DEP samples to stimulate IgE production, their ability to induce iBALT formation and growing, was markedly different upon co-administration together with low antigen doses. Conclusion. DEPs induced local IgE class switching takes place in pre-existing iBALTs, independently of de novo iBALT formation, at least in the case of SRM1650B co-administrated with low antigen doses.

Internet of Things (IoT) technologies can greatly benefit from machine learning techniques and Artificial Neural Networks for data mining and vice versa. In the agricultural field, this convergence could result in the development of smart farming systems suitable for use as decision support systems by peasant farmers. This work presents the design of a smart farming system for crop production, which is based on low-cost IoT sensors and popular data storage services and data analytics services on the Cloud. Moreover, a new data mining method exploiting climate data along with crop production data is proposed for the prediction of production volume from heterogeneous data sources. This method was initially validated using traditional machine learning techniques and open historical data of the northeast region of the state of Puebla, Mexico, which were collected from data sources from the National Water Commission and the Agri-food Information Service of the Mexican Government.

Nutrient depletion in Tanzanian sisal production has led to yield decreases over time. We use nutrient mass balances embedded within a life cycle assessment to quantify the extent of nutrient depletion for different production systems, then used circular economy principles to identify potential cosubstrates from within the Tanzanian economy to anaerobically digest with sisal wastes. The biogas produced is then used to generate bioelectricity and the digestate residual can be used as a fertilizer to address the nutrient depletion. If no current beneficial use of the cosubstrate was assumed, then beef manure and marine fish processing waste were the best cosubstrates. If agricultural wastes were assumed to have a current beneficial use as fertilizer, then marine fish processing waste and human urine were the best cosubstrates. The largest reduction in environmental impacts resulted from bioelectricity replacing electricity from fossil fuels in the national electricity grid and improved onsite waste management practices. There is significant potential to revitalize Tanzanian sisal production by applying circular economy principles to sisal waste management and bioenergy production.

This work aims to investigate systematically the influence of process temperature, bio-mass-to-water ratio, and production scales (laboratory and pilot) on the chemical composition of aqueous and gaseous phases and mass production of chemical by hydrothermal processing of Açaí (Euterpe Oleraceae, Mart.) seeds. The hydrothermal carbonization carried out at 175, 200, 225, and 250 °C, 2 °C/min, biomass-to-water ratio of 1:10, and at 250 °C, 2 °C/min, and biomass-to-water ratios of 1:10, 1:15, and 1:20, in technical scale, as well as at 200, 225, and 250 °C, 2 °C/min, bio-mass-to-water ratio of 1:10, in laboratory scale. The elemental composition (C, H, N, S) of solid phase determined to compute the HHV. The chemical composition of aqueous phase determined by GC and HPLC and the volumetric composition of gaseous phase by using an infrared gas an-alyzer. For the experiments in pilot scale with constant biomass-to-water ratio of 1:10, the yields of solid, liquid, and gaseous phases varied between 53.39 and 37.01% (wt.), 46.61 and 59.19% (wt.), and 0.00 and 3.80% (wt.), respectively. The yield of solids shows a smooth exponential de-cay with temperature, while that of liquid and gaseous phases a smooth growth. By varying the biomass-to-water ratios, the yields of solid, liquid, and gaseous reaction products varied be-tween 53.39 and 32.09% (wt.), 46.61 and 67.28% (wt.), and 0.00 and 0.634% (wt.), respectively. The yield of solids decreases exponentially with increasing water-to-biomass ratio and that of liquid phase increases in a sigmoid fashion. For constant biomass-to-water ratio, the concentrations of Furfural and HMF decrease drastically with increasing temperature, reaching a minimum at 250 °C, while that of phenols increases. In addition, the concentrations of CH3COOH and total car-boxylic acids increase, reaching a maximum at 250 °C. For constant process temperature, the concentrations of aromatics vary smoothly with the temperature. The concentrations of furfural, HMF, and cathecol decrease with temperature, while that of phenols increases. The concentra-tions of CH3COOH and total carboxylic acids decrease exponentially with temperature. Finally, for the experiments with varying water-to-biomass ratios, the productions of chemicals (furfu-ral, HMF, phenols, cathecol, and acetic acid) in the aqueous phase is highly dependent on the biomass-to-water ratio. For the experiments in laboratory scale with constant biomass-to-water ratio of 1:10, the yields of solid ranged between 55.9 and 51.1% (wt.), showing not only a linear decay with tem-perature, but also a lower degradation grade. The chemical composition of main organic compounds (furfu-ral, HMF, phenols, cathecol, and acetic acid) dissolved in the aqueous phase in laboratory scale shows the same behavior of those in obtained in pilot scale.

The risk of inhalation exposure to elevated concentrations of hydrogen sulfide (H₂S) and ammonia (NH₃) during the agitation of stored swine manure is high. Once or twice a year, farmers agitate manure before pump-out and application to fields. Agitation of the swine manure causes the short-term releases of highly toxic levels of H₂S and NH₃. In our previous pilot-scale studies, the biochar powder had shown significant mitigation of H₂S and NH₃ emissions when surficially applied to manure immediately before agitation. However, fine biochar powder application poses hazards by itself and may not be practical to apply on a farm scale, especially when livestock and workers are present. We hypothesized that applying pelletized biochar to manure surface is just as effective as applying powder to protect farmers and animals from excessive exposure to H₂S and NH₃. This work reports on the lab-scale proof-of-the-concept trials with biochar pellets on the lab-scale. The objective was to compare the biochar pellets and biochar powder on their effectiveness of mitigation on H₂S and NH₃ gases during 3-hour long swine manure agitation. Three scenarios were compared in (n=3) trials (i) control, (ii) 12.5 mm thick surficial application to manure surface of biochar powder, and (iii) an equivalent (by mass) dose of pelletized biochar applied to manure surface. The biochar powder was bound with 35% (wt) water into ~5 × 10 mm (dia × length) pellets. Biochar powder was significantly (p<0.05) more effective than the biochar pellets. Still, pellets reduced total H₂S and NH₃ emissions by ~72% and ~68%, respectively (p=0.001), compared with ~99% by powder (p=0.001). The maximum H₂S & NH₃ concentrations were reduced from 48.1±4.8 ppm & 1,810±850 ppm to 20.8±2.95 ppm & 775±182 ppm by pellets, and to 22.1±16.9 ppm & 40.3±57 ppm by powder, respectively. These reductions are equivalent to reducing the maximum concentrations of H₂S and NH₃ during the 3-h manure agitation by 57% and 57% (pellets) and 54% and 98% (powder), respectively. Treated manure properties hinted at improved nitrogen retention, yet not significant due to high variability. We recommend scaling-up and trials on the farm-scales using biochar pellets to assess the feasibility of application to large manure surfaces and techno-economic evaluation.

This work aims to investigate systematically the influence of process temperature and biomass-to-water ration on the chemical composition of aqueous and gaseous phases and mass production of chemical by hydrothermal processing of Açaí (Euterpe Oleraceae, Mart.) seeds. The hydrothermal carbonization carried out at 175, 200, 225, and 250 °C, 2 °C/min, biomass-to-water ratio of 1:10, and at 250 °C, 2 °C/min, and biomass-to-water ratios of 1:10, 1:15, and 1:20, in technical scale. The chemical composition of aqueous phase determined by GC and HPLC and the volumetric composition of gaseous phase by using an infrared gas analyzer. For constant biomass-to-water ratio of 1:10, the yields of solid, liquid, and gaseous phases varied between 53.39 and 37.01% (wt.), 46.61 and 59.19% (wt.), and 0.00 and 3.80% (wt.), respectively. The yield of solids shows a smooth exponential decay with temperature, while that of liquid and gaseous phases a smooth growth. By variation of biomass-to-water ratios, the yields of solid, liquid, and gaseous reaction products varied between 53.39 and 32.09% (wt.), 46.61 and 67.28% (wt.), and 0.00 and 0.634% (wt.), respectively. The yield of solids decreases exponentially with increasing water-to-biomass ratio and that of liquid phase increases in a sigmoid fashion. For constant biomass-to-water ratio, the concentrations of Furfural and HMF decrease drastically with temperature, reaching a minimum at 250 °C, while that of phenols increases. In addition, the concentrations of CH3COOH and total carboxylic acids increase, reaching a maximum at 250 °C. For constant process temperature, the concentrations of aromatics vary smoothly with the temperature. The concentrations of furfural, HMF, and cathecol decrease with temperature, while that of phenols increases. The concentrations of CH3COOH and total carboxylic acids decrease exponentially with temperature. Finally, for the experiments with varying water-to-biomass ratios, the productions of chemicals (furfural, HMF, phenols, cathecol, and acetic acid) in the aqueous phase is highly dependent on the biomass-to-water ratio.

The article deals with aspects of identifying industrial products in motion based on their color. An automated robotic workplace with conveyor belt, robot and industry color sensor is created for this purpose. Measured data are processed in a database and then statistically evaluated in form of standard uncertainties of type A and B, in order to obtain combined standard uncertainties results. Based on the acquired data, control charts of RGB color components for identified products are created. Influence of product speed on the measuring process identification and process stability is monitored. In case of identification uncertainty i.e. measured values are outside the limits of control charts, the K-nearest neighbor machine learning algorithm is used. This algorithm, based on the Euclidean distances to the classified value, estimates its most accurate iteration. This results into the comprehensive system for identification of product moving on conveyor belt, where based on the data collection and statistical analysis using machine learning, industry usage reliability is demonstrated.

With the COVID-19 pandemic now ongoing for close to a year, people all over the world are still waiting for a vaccine to become available. The initial focus of accelerated global research and development efforts to bring a vaccine to market as soon as possible was on novel platform technologies that promised speed but had limited history in the clinic. In contrast, recombinant protein vaccines, with numerous examples in the clinic for many years, missed out on the early wave of investments from government and industry. Emerging data are now surfacing suggesting that recombinant protein vaccines indeed might offer an advantage or complement to the nucleic acid or viral vector vaccines that will likely reach the clinic faster. Here, we summarize the current public information on the nature and on the development status of recombinant subunit antigens and adjuvants targeting SARS-CoV-2 infections.

Environmental darkness signal is transferred from the retina to the pineal gland triggering melatonin secretion. Melatonin influences the synthesis and release of the hypothalamic GnRH and the adenohypophyseal gonadotropin hormones and therefore, regulates testicular function in photoperiodic species. Besides the brain, direct actions of melatonin at the testicular level have also been described. Melatonin released from the pineal gland to the circulation is taken up by peripheral tissues including testes. Testicular synthesis of melatonin has also been reported. The two key somatic cell types in the testis, Leydig and Sertoli cells, express melatonergic receptors. Melatonin acts as a local modulator of the endocrine activity in Leydig cells. In Sertoli cells, melatonin influences the oxidation state and the energy metabolism, and consequently may regulate spermatogenesis. Melatonergic receptors were also described in testicular macrophages and mast cells of infertile patients. Whereas melatonin exerts anti-proliferative and anti-inflammatory effects on testicular macrophages, it provides protective effects against oxidative stress in testicular mast cells. These data pinpoints melatonin as a key player in the regulation of testicular physiology (i.e. steroidogenesis, spermatogenesis) mostly in seasonal breeders. More importantly, melatonin is also involved in the modulation of testicular inflammatory and oxidant/anti-oxidant states in patients with idiopathic infertility.

This work presents the results of optimizing the physicochemical properties of composite briquettes based on microsilica for metallurgical-grade silicon production. Microsilica, a waste product of silicon production, contains a sufficiently high amount of silicon dioxide (96-97%). This fact makes microsilica a promising composite material for metallurgical processing. However, its granulometric composition limits its direct use. The method of briquetting on an industrial briquetting press was used. The influence of the granulometric composition of the composite mixture on the heat tolerance and strength of the finished briquettes was studied. The methods of obtaining and testing the briquettes, their composition, and the briquetting and drying process are described. The obtained briquettes were tested for the smelting of metallurgical silicon. The silicon recovery rate in the metal with the standard charge was 71%, while the recovery rate with the briquetted monocharge was 85%. The results of silicon smelting from the briquettes demonstrated the high quality of the obtained metal, corresponding to the standards of metallurgical-grade silicon. The implementation of these technologies not only improves the quality of the final product but also addresses environmental issues related to the disposal of microsilica, reducing its accumulation and minimizing its impact on the environment.

Graphene was synthesized through a two-step pyrolysis method using waste candlenut (Aleurites moluccanus) shells as the precursor. Cerium (Ce)/graphene composites were prepared via an impregnation technique. The resulting graphene and Ce/graphene were characterized using various analytical methods, including Scanning Electron Microscopy with Energy-Dispersive Spectroscopy (SEM-EDS), X-ray Diffraction (XRD), X-ray Photoelectron Spectroscopy (XPS), Transmission Electron Microscopy (TEM), Thermo Gravimetric Analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy, Cyclic Voltammetry (CV), and Linear Sweep Voltammetry (LSV). The bio-carbon produced predominantly exhibited a graphene structure with flat carbon morphology and an interlayer distance of 0.33 nm. This structural information is supported by XRD data, which shows a broad and weak peak at 2θ = 26° corresponding to the C (002) plane, indicative of graphene presence. FTIR, XPS, and Raman spectroscopy further confirmed the presence of graphene through the detection of Csp2 aromatic bonds and the characteristic D, G, and 2D peaks. Notably, the performance of cerium can be enhanced by the incorporation of graphene, attributed to the large surface area and chemical interactions between Ce and graphene. Consequently, candlenut-derived graphene shows potential as a supportive material for modifying the properties of cerium, thereby opening avenues for various advanced applications, such as sustainable and high-performance energy storage systems.

In a constantly changing environment brought about by the climate crisis and escalated anthropogenic perturbations driven by the growing population, harmful algal bloom dynamics and their impacts are expected to shift, necessitating adaptive management strategies and comprehensive research efforts. Similar to primary productivity, HABs have been thought to be driven primarily by major nutrients such as N, P, and Si. However, recent investigations on the role and importance of micronutrients as limiting factors in aquatic environments have been highlighted. This paper provides a review of metal and phytoplankton interactions, with a specific emphasis on pertinent information on the influence of trace nutrients on growth, toxin production, and other underlying mechanisms related to the dynamics of HABs. Low to near-depleted levels of essential nutrients including Fe, Cu, Zn, Se, Mn, Co, and Mo, negatively impact cell growth and proliferation of various marine and freshwater HAB species. However, evidence shows that at elevated levels, these trace elements along with other non-essential ones, could still cause toxic effects to certain HAB species manifested by decreased photosynthetic activities, oxidative stress, ultrastructure damage, and cyst formation. Interestingly, while elevated levels of these metals mostly result in increased toxin production, Co (i.e., yessotoxins, gymnodimine, and palytoxins) and Mn (i.e., isodomoic acid, okadaic and diol esters) enrichments revealed otherwise. In addition to toxin production, releasing dissolved organic matter (DOM) including dissolved organic carbon (DOC) and humic substances was observed as an adaptation strategy, since these organic compounds have been proven to chelate metals in the water column, thereby reducing metal-induced toxicity. Whilst current research center on free metal toxicity of specific essential elements such as in Cu and Zn, a comprehensive account of how trace metals contribute to the growth, toxin production, and other metabolic processes under conditions reflective of in-situ scenarios of HAB-prone areas, would yield new perspectives on the roles of trace metals in HABs. With the growing demands of the global population for food security and sustainability, substantial pressure is exerted on the agriculture and aquaculture sector, highlighting the need for effective communication of information regarding the interactions of macro- and micronutrients with HABs to improve existing policies and practices.

Aquifer Thermal Energy Storage (ATES) systems are garnering attention as high-efficiency air conditioning technologies that contribute to the realization of a carbon-neutral society. This study focuses on an ATES system constructed in Japan, characterized by its complex geological conditions and thin aquifer layers. Through performance analysis using four years of operational data, we achieved a Coefficient of Performance (COP) of 5 on the building load side. This paper confirms the equivalence of the dimensionless production temperature and heat recovery rate, observing nearly identical changes in the dimensionless production temperature over four cycles (eight seasons). Furthermore, we propose an operational method for the following fiscal year that maintains the balance between accumulated storage quantity and pumping volume, based on predictions from this plant's operational pattern.

Nitric oxide (NO) is synthesized and is involved in various physiological and developmental process regulation in all kingdoms of life. Fungi have been less explored in terms of endogenous NO biology than mammals, plants, and bacteria. In this review, we summarize and discuss the studies to date on intracellular NO biosynthesis and function in fungi. Two mechanisms for NO biosynthesis, NO synthase (NOS)-mediated arginine oxidation, and nitrate and nitrite reductase-mediated nitrite reduction, are most frequently reported. Furthermore, we summarize the multifaceted functions of NO in fungi, as well as its role as a signaling molecule in fungal growth regulation, development, abiotic stress, virulence regulation, and metabolism. Finally, we present potential directions for future research on fungal NO biology.

To ensure sustainable production and consumption in the agricultural sector, it is necessary to assess the contribution of each element of the nexus in the agricultural production chain. The aim of this study is to make a quantitative and qualitative analysis of the contributions of each element of the energy, water, waste and land nexus to agricultural products. A composite method approach combining aspects based on input-output model, Location Quotient (LQ) as well as competitive position is adopted. A database of nexus elements over a period from 2009 to 2018 is used for Cameroon, with ten regions considered. The results show proportions of around 0.42% energy, 67.88% water withdrawal, 11.91% harvested area, 97.81% waste for agricultural products. The geolocation of harvested areas shows that the largest portion is in the far north (1,373,829 ha) and the smallest in Adamawa (224,038 ha). Maximum production is in the central region (4,334,095 tons) and minimum in the Adamawa region (915,841 tons). The central, littoral and west regions are more representative of agricultural products. The analysis of the competitive position of agricultural products contributes to a better orientation of national strategies for agricultural sustainability according to existing potentials.

This academic paper explores the synergistic potential of Agroforestry systems and Climate-Smart Agriculture (CSA) in enhancing climate change adaptation strategies. Focusing on Australia and Pacific Island Countries, the study delves into the pivotal role of these approaches in mitigating the impacts of changing climate variables on agricultural production. By analysing important climate variables, their potential alterations, and their subsequent effects on crop production, the paper advocates for a holistic and forward-thinking approach to sustainable agriculture in the face of climate change.

Since a large amount of sewage sludge (WSS) has been generated daily, it is necessary to explore effective methods for utilizing WSS. Although a photo-fermentation system sometimes alters the characteristics of microbial functions, there are no attempts to perform the photo-fermentation using WSS which is regularly treated under a dark-fermentation style. In this study, the effect of photo-fermentation (photo-irradiation) on anaerobic digestion using WSS was revealed. Photo-irradiation during the anaerobic digestion of WSS significantly reduced the amount of organic acids and hydrogen sulfide and methane production was also suppressed. However, it was shown that the activity of sulfate-reducing bacteria in WSS under the light treatment increased. Photo-irradiation also stimulated the growth of green-sulfur bacteria and induced anoxygenic photosynthesis, by which the fermented samples turned green linking with the consumption of hydrogen sulfide. Finally, a dark/light switching fermentation was able to reduce only hydrogen sulfide while methane production remained the same.

Upper mesophilic temperature acclimation of halophilic, hydrogen-producing bacteria from salt fields was investigated in this study, along with the changes in microbial abundance during an-aerobic digestion (AD) process. Genomic approaches such as PCR-denaturing gradient gel elec-trophoresis (DGGE) and next-generation sequencing (NGS) were performed to profile the mi-crobial communities. During AD, there was a significant abundance of Halanaerobacter lacunarum at 48°C followed by the increase in hydrogen yield, signifying potential contribution from the halophile in the hydrogen production. A decrease in the dominance of H. lacunarum and Halan-aerobium fermentans at 42°C, likely due to an increase in other bacterial species, was noted but their dominance significantly increased at temperatures of 45°C and 48°C. This investigation provides valuable insights in highlighting the potential of Halanaerobium sp. and the other halo-philic bacteria to adapt under upper mesophilic temperature conditions and synthesizing hy-drogen. The findings in the present study also underscore the importance of optimizing temper-ature and pH conditions to maximize hydrogen yield during high-salt anaerobic digestion.

The objective of this study was to investigate the effects of body weight gain during the cashmere non-growing period on cashmere production performance and secondary hair follicle activity, to provide a theoretical basis for appropriate supplementary feeding of cashmere goats. Fifty Inner Mongolian cashmere goats aged 2-4 years old were randomly selected and weighed in May and September 2019, respectively. Based on body weight gain between the two weights, the experi-mental ewe goats were divided into two groups: 0-5.0 kg group (n = 30) and 5.0-10.0 kg group (n = 20). Skin samples and cashmere samples were collected. Results of Pearson correlation analysis showed that body weight gain during the cashmere non-growing period had a moderate and strong positive correlation with cashmere yield (P = 0.021) and cashmere staple length (P = 0.002) respectively, but did not correlate with cashmere diameter (P = 0.254). Compared with cashmere goats with a body weight gain of 0-5.0 kg, cashmere goats with a body weight gain of 5.0-10.0 kg had a 17.10% increment in cashmere yield (P = 0.037), 8.09% increase in cashmere staple length (P=0.045) and had no significant difference in cashmere diameter (P = 0.324). Results of Pearson correlation analysis showed that there was a strong positive correlation between body weight gain and the population of active secondary hair follicles in the skin of cashmere goats (P < 0.01). Compared with cashmere goats with a body weight gain of 0-5.0 kg, cashmere goats with a body weight gain of 5.0-10.0 kg had an increase in the population of active secondary hair follicles (P < 0.05). In conclusion, the body weight gain during the cashmere non-growing period had a sig-nificant effect on secondary hair follicle activity and cashmere production performance in cash-mere goats. Since body weight gain reflects nutritional level to a certain extent, this study suggests that nutritional manipulations such as supplementary feeding during cashmere non-growing periods can increase cashmere production performance. However, specific nutritional manipula-tions during the cashmere non-growing period need further research to increase cashmere pro-duction performance.

The fishmeal production industry is essential for providing protein for animal feed in the aquaculture sector. However, the industry faces challenges related to energy consumption and environmental sustainability. This study evaluates the energy efficiency and environmental benefits of waste heat recovery (WHR) technologies in a fishmeal production plant in Vietnam. Data were collected from the plant between 2016 and 2022, and a specific energy consumption (SEC) indicator and a comprehensive methodology were utilized. Implementing an economizer as a WHR technology resulted in a 55.5% decrease in SEC compared to the state before installation. The enhanced energy efficiency also translated to reduced energy consumption per output unit. Moreover, the economizer contributed to annual energy savings of 4,537.57 GJ/year and cost savings of $26,474.49. Additionally, carbon dioxide (CO2) emissions associated with producing one ton of fishmeal decreased by 58.37%. These findings highlight the potential for WHR technologies to improve energy efficiency and reduce the environmental footprint of fishmeal production. The study's results provide valuable insights for practitioners and policymakers in promoting energy efficiency practices and reducing environmental impact in the industry.

Ventricina del Vastese is a traditional dry fermented sausage from Central Italy not yet charac-terized for occurrence, identity and safety of coagulase negative staphylococci (CNS), a bacterial group technologically important for this kind of products. Therefore, in this study, 98 CNS isolates from four manufacturers were differentiated by Repetitive element palindromic PCR (Rep-PCR) and identified by 16S rRNA gene sequencing. These were examined for genes encoding biogenic amine (BA) production, resistance to aminoglycosides, β-lactams and tetracyclines and staphylococcal enterotoxins (SEs). Staphylococcus succinus (55%) predominated, followed by S. xylosus (30%), S. epidermidis (7.4%), S. equorum (3.1%), S. saprophyticus (3.1%) and S. warneri (1%). One S. succinus subsp. casei isolate was slightly β-hemolytic. SEs and the histidine decarboxylase gene hdcA were not detected, while the tyrosine decarboxylase gene tdcA was detected in four S. xylosus isolates. A blaZ beta-lactamase gene and tetracycline resistance genes tetK (six isolates) and tetA (one isolate also bearing tetK) were found, respectively. However, fewer hazardous and AR traits compared to CNS examined in other studies were found, as a probable consequence of using meat from animals reared in conditions that allow to minimize pathogen circulation and antibiotic use. Therefore, appropriate production conditions can reduce these threats.

An in-depth study of the failure of granular materials, which is known as a mechanism to generate defects, can reveal the facts about the origin of the imperfections such as cracks in the carbon anodes. The initiation and propagation of the cracks in the carbon anode, especially the horizontal cracks below the stub-holes, reduce the anode efficiency during the electrolysis process. In order to avoid the formation of cracks in the carbon anodes, the failure analysis of coke aggregates can be employed to determine the appropriate recipe and operating conditions. In this paper, it will be shown that a particular failure mode can be responsible for the crack generation in the carbon anodes. The second-order work criterion is employed to analyze the failure of the coke aggregate specimens and the relationships between the second-order work, the kinetic energy, and the instability of the granular material are investigated. In addition, the coke aggregates are modeled by exploiting the discrete element method (DEM) to reveal the micro-mechanical behavior of the dry coke aggregates during the compaction process. The optimal number of particles required for the failure analysis in the DEM simulations is determined. The effects of the confining pressure and the strain rate as two important compaction process parameters on the failure are studied. The results reveal that increasing the confining pressure enhances the probability of the diffusing mode of the failure in the specimen. On the other hand, the increase of strain rate augments the chance of the strain localization mode of the failure in the specimen.

The use of swine manure as a source of plant nutrients is one alternative to synthetic fertilizers. However, conventional manure application with >90% water and a low C:N ratio results in soil C loss to the atmosphere. Our hypothesis was to use biochar as a manure nutrient stabilizer that would slowly release nutrients to plants upon biochar-swine manure mixture application to soil. The objectives were to evaluate the impact of biochar-treated swine manure on soil total C, N, and plant-available macro and micronutrients in greenhouse-cultivated corn (Zea mays L.) and soybean (Glycine max (L.) Merr.). Neutral pH red oak (RO), highly alkaline autothermal corn stover (HAP), and mild acidic Fe-treated autothermal corn stover (HAPE) biomass were pyrolyzed to prepare biochars. Each biochar was surface-applied to swine manure at a 1:4 (biochar wt/manure wt) ratio to generate mixtures of manure and respective biochars (MRO, MHAP, and MHAPE). Conventional manure (M) control and manure-biochar mixtures were then applied to the soil at a recommended rate. Corn and soybean were grown under these controls and treatments (S, M, MRO, MHAP, and MHAPE) to evaluate the manure-biochar impact on soil quality, plant biomass yield, and nutrient uptake. Soil OM significantly (<0.05) increased in all manure-biochar treatments; however, no change in soil pH or N was observed under any treatment. No difference in soil ammonium between treatments was identified. There was a significant decrease in soil M3-P and soil NO₃^- for all manure-biochar treatments compared to the conventional M. However, the plant biomass nutrient concentrations were not significantly different from control manure. Moreover, an increasing trend of N and decreasing trend of P in the plant under all biochar-manure treatments than the controls were noted. This observation suggests that the presence of biochar is capable of influencing the soil N and P in such a way as not to lose those nutrients at the early growth stages of the plant. In general, no statistical difference in corn or soybean biomass yield and plant nutrient uptake for N, P, and K was observed. Interestingly, manure-biochar application to soil significantly diluted the M3-extractable soil Cu and Zn concentrations. The results attribute that manure-biochar has the potential to be a better soil amendment than conventional manure application to the soil.

The premise regarding COVID-19 disease is that it is a spectrum which begins with infection with viral SARS-CoV-2 exposure via airborne or oral virus particles. The individual response to it depends on many factors including co-morbid conditions. An important aspect of SARS-CoV-2 virus infection is the cytokine storm that develops after the infection. The immuno-chemical chaos created in this cytokine storm is to the benefit of the virus. In this meta analysis the authors explore ways to let the cytokine storm die down by looking into the role of histamine. Histamine is a metabolic product of the essential aminoacid histidine. Histamine has 4 known receptors: H1, H2, H3 and H4. The immunoglobulines IgE and IgM are indicative for a COVID-19 infection. This immune response is related to inflammation. Inflammation, in turn, runs mainly via histamine after e.g. virus inoculation. The goal of the meta-study is to gather evidence to primarily block the H4 receptor (H4R) in gastrointestinal cells to diminish the cytokine overproduction in the $\approx$ 30\% of the patients suffering from gastrointestinal problems caused by SARS-CoV-2. Our concept is as follows. If we can strike a careful balance between hampering the gastrointestinal spreading of the virus and histamine antagonists to tackle the cytokine storm, then the natural immunity can later on come on line again and attack the virus without being led astray by cytokine chaos. We will concentrate on H4R but also look at H1R and H2R related effects. The proposed substances in our systemic approach can be balanced for an effective early treatment. The nature of our work is by its method and results theoretical. In that respect we also may note the structural chemistry indol skeleton resemblance among a number of different drugs.

As the EU is moving towards a low carbon economy and seeks to further develop its renewable energy policy, this paper quantitatively investigates the impact of plausible energy market reforms from the perspective of bio-renewables. Employing a state-of-the-art biobased variant of a computable general equilibrium model, this study assesses the perceived medium-term benefits, risks and trade-offs which arise from an advanced biofuels plan, two exploratory scenarios of a more 'sustainable' conventional biofuels plan and a 'no-mandate' scenario. Consistent with more recent studies, none of the scenarios considered present significant challenges to EU food-security or agricultural land usage. An illustrative advanced biofuels plan simulation requires non-trivial public support to implement whilst a degree of competition for biomass with (high-value) advanced biomass material industries is observed. On the other hand, it significantly alleviates land use pressures, whilst lignocellulose biomass prices are not expected to increase to unsustainable levels. Clearly, these observations are subject to assumptions on technological change, sustainable biomass limits, expected trends in fossil fuel prices and EU access to third-country trade. With these same caveats in mind, the switch to increased bioethanol production does not result in significant market tensions in biomass markets.

Foam rolling is widespread and deeply rooted in exercise practice. Optimal duration and role of this treatment still lack scientific consensus. Relatively novel foam rolling treatment that combines vibration during application targets different muscle characteristics that are not well understood. Studies exploring this combined treatment are scarce therefore the aim of this study was to investigate the acute effects of different duration vibration (15-s, 30-s and 60-s) foam rolling treatment on muscle skin temperature and surface muscle electromyography during Maximal Voluntary Isometric Contraction. Eighteen male subjects attended the research laboratory for three experimental sessions and performed four sets of three trials of maximal isometric heel rises. Repeated measures ANOVA determined that muscle skin temperature significant difference was only found for the 30-s treatment (p = 0.013 - 0.000). For surface muscle electromyography a 30-s treatment out of all three yielded the most significant results, between pretreatment set and post treatment set1 (p=0.01) small effect size (Cohen’s d= -0.33) and pretreatment set to post treatment set3 (p=0.01) small effect size (Cohen’s d= -0.30). All treatments did not produce significant difference during Maximal Voluntary Isometric Contraction heel rises. Future studies should investigate accute effects of longer duration treatment on changes in surface muscle temperature. Muscle activity could suggest that efficiency was improved taken into account of unchanged muscle strength, also downward trend of muscle activity caused by other two treatment durations could be of significance during rehabilitation process or during activites where this is a desired and indicated goal.

Lidar and camera sensors are widely utilized in autonomous vehicles (AVs) and robotics due to their complementary sensing capabilities—lidar provides accurate depth information, while cameras capture rich visual data. However, effective fusion of these sensors requires precise calibration, which is often challenging due to the differences in sensing modalities. This paper presents a self-calibration algorithm based on Singular Value Decomposition (SVD) to address this problem. Singular Value Decomposition is a powerful matrix factorization technique that helps identify key calibration parameters by decomposing matrices into singular vectors and values, representing essential calibration data. Our method not only automates the calibration process but also provides a reliable mechanism for detecting calibration errors, ensuring long-term accuracy and robustness in sensor fusion. The algorithm simplifies deployment in real-world applications by eliminating the need for manual calibration or external targets. Experimental results show that our approach improves sensor alignment and fusion accuracy, making it particularly useful for AV and robotic systems where maintaining precise calibration is critical.

Is there a qualitative difference between apes’ and human Theory-of-Mind (or ability to estimate others’ mental states)? After opting for the idea that expectations are empty profiles that recognize a particular content when it arrives, I apply the same description to ‘vicarious expectations’ –very probably present in apes. Thus, (empty) vicarious expectations and one’s own (full) contents are distinguished without need of meta-representation. Then, three proposals are made. First, vicarious expectations are enough to support apes’ Theory-of-Mind (including ‘spontaneous altruism’). Second, since vicarious expectations require a profile previously built in the subject that activates them, this subject cannot activate any vicarious expectation of mental states that are intrinsically impossible for him. Third, your mental states that think of me as a distal individual are intrinsically impossible states for me, and therefore, to estimate them, I must estimate your mental contents. This ability (the original nucleus of human Theory-of-Mind) is essential in human lifestyle. It is involved in unpleasant and pleasant self-conscious emotions, which respectively contribute to ‘social order’ and to cultural innovations. More basically, it makes possible the human (prelinguistic or linguistic) communication, since it originally made possible the understanding of others’ mental states as states that are addressed to me, and that are therefore impossible for me.

Background and Objectives: Fifty percent of individuals with borderline personality disorder (BPD) experience Non-Suicidal Self-Injury (NSSI). One of the crucial factors related to NSSI is the feeling of emptiness. Although some inner strengths, such as five precepts, meditation, and equanimity, have been identified as potential buffers against negative mental health outcomes in BPD, their role in mediating the relationship between emptiness and NSSI is not well-documented. This study aimed to explore how these inner strengths mediate the relationship between feelings of emptiness and NSSI in individuals with BPD symptoms. Materials and Methods: A total of 302 participants with BPD symptoms completed several assessments: the SCID-II Personality Disorder (Borderline PD) to assess feelings of emptiness and NSSI, the Inner-Strength-Based Inventory (i-SBI) to evaluate five precepts, meditation, and equanimity, and the Outcome Inventory Depression (OI-Dep) to assess depression. Mediation analysis was performed using IBM SPSS and AMOS, with NSSI as the outcome variable, feelings of emptiness as the predictor, and the inner strengths as mediators. Results: The participants had a mean age of 36.56, with 65.4% being female. The analysis showed that five precepts, meditation, and equanimity significantly mediated the relationship between feelings of emptiness and NSSI, with a standardized coefficient of β = 0.534 (95% CI = 0.417 to 0.647, p &lt; 0.001). The indirect effect of emptiness through these inner strengths was significant (β = 0.034, 95% CI = 0.009 to 0.075, p = 0.005). The mediation model explained 38% of the variance in NSSI with a 3% increase, albeit small but significant. Conclusions: The study highlights a negative mediating role of inner strengths in the relationship between feelings of emptiness and NSSI meaning that as these inner strengths increase, the direct impact of feelings of emptiness on NSSI decreases. This suggests that these inner strengths act as protective factors, reducing the likelihood that someone with feelings of emptiness will resort to NSSI as a coping mechanism. These findings suggest that targeting these inner strengths could be a valuable strategy in developing interventions aimed at reducing NSSI by addressing the underlying emotional challenges associated with BPD.

Since the beginning of the internet era, there has been an explosion of growth in structured data (such as numbers, symbols, and labels) as well as unstructured data (including images, videos, and text). Efficient and accurate mixed query of these two types of data is a key technology to achieve high-quality information retrieval, and it is also a major challenge that needs to be solved urgently in the industry. In this study, we employ an advanced Transformer model that combines strategies and fine-tuning techniques for multi-task learning. Specifically, the model is first pre-trained on a large-scale, general-purpose dataset to learn different types of data representations and basic language comprehension skills. After that, we fine-tuned the parameters of the model to better suit these specific data processing tasks for specific application scenarios, such as image annotation, video content analysis, and structured data query. At the heart of the model is the self-attention mechanism, which allows the model to automatically emphasize the important parts and ignore irrelevant information when processing the input data. In addition, we have introduced task-specific adaptation layers that are designed to add additional processing power to the original Transformer architecture, such as a semantic analysis layer for unstructured text data and a relational extraction layer for structured data. This combination of general pre-training and task-specific fine-tuning allows the model to flexibly process and integrate information from different data sources, improving processing efficiency and accuracy. Experimental results show that the model performs well in a variety of data processing tasks, significantly improves the accuracy and efficiency of information retrieval, and verifies the strong potential and adaptability of large language models in processing mixed data types.

Background: Atopic dermatitis is a chronic condition that significantly affects the daily life of those who suffer from it, requiring complex and personalized management with active participation of the patient in the management of their disease. Objective: to describe the design and development process of a mobile application, using the Design Thinking method, for the follow-up of patients with atopic dermatitis. Methods: User-centered design and prototype creation method, differentiating the phases of the empathize, define, idea, prototype, and test. A purposive snowball sampling was used to recruit patients with atopic dermatitis, family members, and health professionals. Three two-hour workshops were held, attended by 25 people. Results: the parameters to be monitored will include objective data (physical, behavioral, treatments, environmental, integration of daily routines) and subjective data (user experience). On the other hand, it will figure out behavior patterns, set up rewards, foster a feeling of community, and use notifications and a chatbot. Conclusion: The active integration of all stakeholders at each stage of the design and development of the digital solution has improved its relevance and acceptance, resulting in a tool that is expected to significantly improve the management of atopic dermatitis.

The study is based on information as the property of matter and its evolution from chemical to digital information. Consequences of these forms of information include molecular, modular, cel-lular, non-human, and human individual interactions, as well as human-machine interaction, and the formation of corresponding modules through self-organizing selective processes. The function of modular structures is decision-making and is analogous to the behavior of an intelligent agent. The evolutionary modular model is proposed based on the interaction of evolutionary factors (matter, energy, information, self-organization, natural selection, and heritability) among themselves and with the arrow of time. In conclusion, we realize that the essence of the evolution of living organ-isms is modular evolution. Modules through which the survival and reproduction of living organ-isms is ensured, are formed by two basic molecular processes, which are molecular recognition or information and modular self-organization.

Numerous investigations have suggested that seismic source parameters and properties of the surrounding medium harbor valuable information regarding alterations in stress fields and medium properties at the focal depth. Monitoring the spatial and temporal evolution of these parameters can yield insights into variations in stress fields or medium properties within the seismogenic zone, offering a critical avenue to overcome the Earth's inaccessible nature. In recent years, modern seismic parameters such as seismic moment, focal mechanism solution, source stress drop, corner frequency, radiated seismic energy, rupture radius, and apparent stress have been increasingly used to characterize source characteristics. The Sichuan region is situated on the southeastern edge of the Qinghai-Tibet Plateau and is known for its strong eastward extrusion and structural deformation. The main fault zones in the area include the Xianshuihe Fault, Anninghe Zemuhe Fault, and Longmenshan Fault. This paper estimates source parameters of small to medium-sized earthquakes (ML 1.5-5.2) in the main fault zones and adjacent areas in Sichuan. A total of 4,310 earthquake stress drop measurements from 2019 to 2023 were analyzed to create a stress distribution image along the fault. This earthquake parameters training catalog provides insight into how coseismic stresses change and their relationship with other geophysical factors, as well as their spatial and temporal evolution.

School bullying represents a widespread expression of violence in the peer context. Guided by the social-ecological model, this study investigated the longitudinal and transactional pathways linking domestic and neighborhood/community violence exposure (through direct victimization and witnessing), self-serving cognitive distortions (CDS), and school bullying perpetration. Furthermore, the cognitive desensitization hypothesis that the literature has supposed to develop in response to chronically violent contexts was examined. Two four‐wave cross-lagged panel mediation models were tested in a sample of 778 high school students (28.1% males; Mage [Time 1; T1] = 14.20, SD = 0.58). The results showed that both domestic and neighborhood/community violence exposure, as a victim and as a witness, respectively, were associated to self-serving CDs and bullying perpetration over time. Moreover, significant associations between CDs and bullying perpetration over time were found, with bidirectional effects for each of these longitudinal patterns. Finally, self-serving CDs were found to significantly mediate the relationships between both domestic violence victimization and community violence witnessing and school bullying perpetration. These findings highlight the need to consider school bullying as a social phenomenon stemming from a complex and bidirectional interplay between the individuals and the environments they inhabit confirming a basic postulate that “violence breeds violence”.

The aim of this investigation is focused on the effects of hooked-end steel fibers on both fresh and hardened properties of modified self-compacting concretes (SCC). For this purpose, the steel fibers are associated with other residues contents (i.e. marble, granite and rubber). This concatenated materials contents constitutes a novelty since no investigations are reported. It is found that the increase of rubber content, a better ability to absorb energy is observed. This indicates that a good alternative of structural material is provided. Fresh properties are evaluated by using flow, T500 time, V-funnel, J-ring methods. The mechanical behavior is evaluated in terms of compressive strength, tensile strength, static and dynamic modulus of elasticity, and damping ratio. Experimental results of the water absorption, porosity and density are also attained. It is also found that a SCC mixture containing steel fiber, marble/granite residue and rubber content is a potential mixture to be considered when in SCC designing associated with improved damping ratio. Although the rubber content decreases the mechanical behavior and slump flow, the concatenated utilization of MGR and steel fiber contents provide a slight improve in the damping result. An environmental benefit can also be associated since the cement consumption is decreased with marble additions.

This study investigates how customers’ technological readiness affects service quality and the adoption of self-service banking by developing an empirical model. The model was proposed to explore the relationships between technology readiness, self-service quality, and customer satisfaction. The hypotheses and stability of the model were tested using structural equation modeling. The findings revealed that technology readiness, including the optimism, innovation, and insecurity dimensions, had a significant positive impact on self-service quality. In addition, service quality fully mediated the relationship between technological readiness and customer satisfaction. These results suggest that when customers are ready to embrace and use new technology, their evaluation of service quality is high. Thus, bank managers should drive customer perceptions of the quality of self-service banking by improving their technological readiness through various measures. Furthermore, based on the mediating effect of self-service quality, banks must be aware that improving service quality can enhance customer satisfaction and maintain a competitive advantage.

This study explores how the covid-19 pandemic affected some psychological factors in people who got tattoos during or after the lockdown, the psychological factors assessed were self-esteem, risk taking behaviour, body image and locus of control. The study used a quantitative, between-subjects design to investigate the experiences of participants who acquired tattoos during the pandemic compared to those who did not. The results showed that participants who got a tattoo during the pandemic reported higher levels of self-esteem and body image satisfaction compared to those who did not get a tattoo. Furthermore, the findings suggest that individuals with tattoos may have a more external locus of control. Participants with tattoos exhibited higher levels of risk-taking behaviour compared to those without tattoos, furthermore sex affected risk-taking behaviour in tattooed individuals, and females with tattoos displayed a higher risk taking tendency than their tattooed male counterparts. Further research needs to be done while acknowledging the limitations of this study. Overall, this study is pivotal in establishing how the pandemic may have affected the aforementioned psychological factors in people with tattoos. It also adds to the growing body of literature in body modification and psychology.

Spiritual security should be a priority in our modern globalized society. Therefore, the study provides convincing evidence that it is important to develop a theoretical understanding of spiritual security. Several theoretical concerns regarding the establishment and maintenance of spiritual security are addressed in the article. He explores many ideas that are interrelated, including spiritual security, worldview, and spirituality. To ensure spiritual security, a practical analysis is carried out of the need to carry out various measures that strengthen the spiritual health of society.The article explains the methodology used in spiritual Security Investigations. According to the author, different levels of spiritual security can be analyzed using a structural-logical model and a dialectical method of cognition. Comparative analysis is also seen as a valuable tool. Spiritual intelligence is essential to overcome barriers, manage change, and ensure personal security and its impact on relationships. The process begins with introspection and evaluation, concluding with the ability to assess and understand the environment. By analyzing and understanding natural phenomena, it is possible to develop a sense of reality and a deeper appreciation of the nature of human existence. A person can feel spiritually safe if he adheres to his moral and spiritual beliefs and complies with the norms of society. It contains such things as worldview, social behavior, culture, research and social development. By expanding the spiritual point of view, the danger to the spiritual security of a person can be reduced.

This article delves into the complex tension between national self-rule and international involvement, in the context of global politics, examining the inherent challenges of upholding both principles when confronted with human rights abuses and the pursuit of global peace. The introduction presents the fundamental dilemma: self-governance versus moral obligations. The problem statement calls for a nuanced approach to address the intricate complexities of sovereignty and intervention, acknowledging the potential misuse by oppressive regimes and the ongoing challenges of determining when and how intervention is warranted. The article advocates for a more responsible and effective approach to global conflicts and human rights violations, balancing national sovereignty with judicious intervention when required. The methodology employs both literature review and case analysis to construct a framework for objectively assessing when international intervention is justified in instances of human rights abuses. The conclusion stresses the criticality of objective intervention criteria, transcending cultural, political, and economic biases, and advocates for a globally accepted approach that celebrates diversity while promoting global stability.

"Enhancing the Efficiency of Natural Gas Liquid (NGL) Extraction and Fractionation Trains: An Integrated Approach of Simulation Analysis, Advanced Modifications, and Technological Advancements. Through comprehensive research, innovative solutions such as the heat pump aided distillation (HPAD) system and self-heat recuperation technology (SHRT) have been developed to significantly reduce the energy consumption associated with conventional distillation systems. To identify a practical system for NGL fractionation trains, this study extensively examined and compared various HPAD and SHRT options to retrofit a single column. The objective was to find the most suitable and efficient solution for the fractionation process of natural gas liquids (NGLs). The retrofit options analyzed in this study encompassed a range of techniques, including vapor compression (VC), mechanical vapor re-compression (MVR), thermal vapor re-compression (TVR), bottom flashing (BF), side heat exchanger (SHE), intermediate heating and cooling (IHC), self-heat recuperative (SHR), and modified self-heat recuperative (MSHR) distillation. These methods were carefully examined to determine their suitability and effectiveness in improving the performance of NGL fractionation trains In this study, a depropanizer column, typically employed in conventional NGL plants, was selected as a case study. The simulation software Aspen HYSYS V7.3 was employed to model and analyze eight retrofit designs based on predefined criteria. The simulation data was carefully evaluated to identify the most efficient design for minimizing energy consumption. Among the retrofit options, the mechanical vapor re-compression (MVR) technique demonstrated the most significant energy cost reduction, with a remarkable 68.11 percent improvement compared to the base case conventional column. These findings highlight the potential of MVR as an effective solution for lowering energy costs in NGL fractionation trainsFollowing the MVR retrofit option, the study found that vapor compression (VC) achieved a considerable energy cost reduction of 66.65 percent, closely followed by modified self-heat recuperative (MSHR) at 64.02 percent, bottom flashing (BF) at 62.88 percent, self-heat recuperative (SHR) at 55.85 percent, side heat exchanger (SHE) at 54.23 percent, intermediate heating and cooling (IHC) at 39.54 percent, and thermal vapor re-compression (TVR) also at 39.54 percent. These findings highlight the significant potential for energy savings offered by these retrofit options, with VC being the most popular choice, closely followed by MSHR, BF, SHR, SHE, IHC, and TVR.

The perovskite solar cells (PSCs) have been significantly improved by utilizing inorganic hole transporting layer (HTL), such as nickel oxide. Despite the promising properties, there are still limitations due to defects. Recently, research on self-assembled monolayers (SAM) is being actively conducted, which show promise in reducing defects and enhancing device performance. In this study, we successfully engineered a p-i-n perovskite solar cell structure utilizing HC-A1 and HC-A4 molecules. These SAM molecules were found to enhance the grain morphology and uniformity of the perovskite film, which are critical factors in determining optical properties and device performance. Notably, HC-A4 demonstrated superior performance due to its distinct hydrophilic properties with a contact angle of 50.3°, attributable to its unique functional groups. Overall, the HC-A4 applied film exhibited efficient carrier extraction properties, attaining a carrier lifetime of 117.33 ns. Furthermore, HC-A4 contributed the superior device performance with its favorable band alignment, achieving the highest device efficiency of 20%.

Introduction: In an era of increasing public awareness regarding the pivotal role of nutrition in the onset and progression of chronic degenerative diseases, there is a growing demand for information and assistance pertaining to the intricate relationship between diet and disease. Nutritional practices, therefore, emerge as a fundamental element in the prevention and management of these maladies, necessitating a proactive response from healthcare professionals (HCP). This study sought to evaluate the impact of participation in a Culinary Medicine (CM) program on Mediterranean diet adherence, food management skills, culinary proficiency, and counseling confidence among HCP. Methods: A mixed-methods pilot implementation program (PIP) was meticulously designed and executed, engaging a cohort of 20 HCP recruited from Hospital Clinic Barcelona. The program unfolded at the Alícia Foundation kitchen-lab and encompassed a series of interactive, hands-on sessions that delved into the realms of gastronomy, food management, culinary skills, and culinary diet therapy, with a specific focus on prevalent diseases and their prevention, treatment, and care. Tailored questionnaires were administered to all participants both before and after the PIP. Results: Of the 20 participants, 14 successfully completed the study, comprising 86% women, 86% aged above 40, 71% nurses, and 7% medical doctors. Interestingly, 86% of the participants had previously received nutrition training, whereas only 14% had received culinary training. Following the completion of the program, there was a remarkable improvement in adherence to the Mediterranean diet (p < 0.01). However, no statistically significant improvements were observed in food management and culinary skills or counseling confidence (p > 0.5). Despite the absence of statistical significance, there was a noteworthy trend towards greater advocacy for dietary changes before resorting to medication, along with enhanced confidence in providing nutritional and culinary guidance to patients. Conclusion: The findings from this study underscore the potential of hands-on CM training as a vital component of nutrition education for HCP. While statistically significant improvements in certain domains were not observed, the program did demonstrate its ability to influence attitudes, knowledge, and behaviors related to healthy cooking and eating for both HCP themselves and their patients. Given these promising trends, future studies with a larger sample size must be performed to further elucidate the impact of CM training on HCP and its potential benefits for public health.

Gastric outlet obstruction (GOO) poses a common and challenging clinical scenario, characterized by mechanical blockage in the pylorus, distal stomach, or duodenum, resulting in symptoms such as nausea, vomiting, abdominal pain, and early satiety. Its diverse etiology encompasses both benign and malignant disorders. The spectrum of current treatment modalities extends from conservative approaches to more invasive interventions, incorporating procedures like surgical gastroenterostomy (SGE), self-expandable metallic stents (SEMS) placement, and the advanced technique of endoscopic ultrasound-guided gastroenterostomy (EUS-GE). While surgery is favored for longer life expectancy, stents are preferred in malignant gastric outlet stenosis. The novel EUS-GE technique, employing a lumen-apposing self-expandable metal stent (LAMS), combines the immediate efficacy of stents with the enduring benefits of gastroenterostomy. Despite its promising outcomes, EUS-GE is a technically demanding procedure requiring specialized expertise and facilities.

Estimating the Remaining Useful Life (RUL) of aircraft engines holds a pivotal role in enhancing safety, optimizing operations, and promoting sustainability, thus being a crucial component of modern aviation management. Precise RUL predictions offer valuable insights into an engine’s condition, enabling informed decisions regarding maintenance and crew scheduling. In this context, we propose a novel RUL prediction approach in this paper, harnessing the power of Bi-directional LSTM and Transformer architectures, known for their success in sequence modeling, such as natural languages. We adopt the encoder part of the full Transformer as the backbone of our framework, integrating it with a self-supervised denoising autoencoder that utilizes Bidirectional LSTM for improved feature extraction. Within our framework, a sequence of multivariate time series sensor measurements serves as the input, initially processed by the Bidirectional LSTM autoencoder to extract essential features. Subsequently, these feature values are fed into our Transformer encoder backbone for RUL prediction. Notably, our approach simultaneously trains the autoencoder and Transformer encoder, different from the naive sequential training method. Through a series of numerical experiments carried out on the C-MAPSS datasets, we demonstrate that the efficacy of our proposed models either surpasses or stands on par with that of other existing methods.

Self-supervised learning is a method that learns general representation from unlabeled data. Masked image modeling (MIM), one of the generative self-supervised learning methods, has drawn attention showing state-of-the-art performance on various downstream tasks, though showing poor linear separability resulting from the token-level approach. In this paper, we propose a contrastive learning-based multi-view masked autoencoder for MIM, exploiting an image-level approach by learning common features from two different augmented views. We strengthen MIM by learning long-range global patterns from contrastive loss. Our framework adopts simple encoder-decoder architecture, learning rich and general representation by following a simple process: 1) two different views are generated from an input image with random masking and by contrastive loss, we can learn semantic distance of the representations generated by an encoder. By applying a high mask ratio, 80%, it works as strong augmentation and alleviates the representation collapse problem. 2) With reconstruction loss, decoder learns to reconstruct an original image from the masked image. We assess our framework by several experiments on benchmark datasets of image classification, object detection, and semantic segmentation. We achieve 84.3% fine-tuning accuracy on ImageNet-1K classification and 76.7% in linear probing, exceeding previous studies and show promising results on other downstream tasks. Experimental results demonstrate that our work can learn rich and general image representation by applying contrastive loss to masked image modeling.

This study proposes self-calibration of capacitor mismatch errors for high-resolution pipeline analog-to-digital converters (ADCs). The proposed calibration circuit recursively amplifies the capacitor mismatch error by re-utilizing a multiplying digital-to-analog converter in a pipeline stage without increasing the circuit complexity, and the amplified error voltage is converted into digital code by utilizing the remaining pipeline stages. Error correction is performed by subtracting the digital code from the ADC output during normal operation. A prototype of a 12-bit pipeline ADC is fabricated in a 0.18 µm standard CMOS process. The ADC comprises eight 1.5-bit stages, followed by a 4-bit flash ADC as the final stage; the capacitor mismatch errors in the first two pipeline stages are corrected by utilizing the proposed self-calibration technique. At a sampling rate of 30 MS/s, the measured differential and integral nonlinearities improve from +0.82/-0.75 and +1.12/-1.79 to +0.45/-0.41 and +0.47/-0.91 after calibration, respectively. Further, the measured dynamic performances improve significantly with calibration. For an input frequency of 2.09 MHz, the ADC achieves a spurious-free dynamic range (SFDR) and signal-to-noise and distortion ratios (SNDR) of 69.3dB and 63.9dB before calibration, respectively. After calibration, the SFDR and SNDR increase to 84.1dB and 68.9dB, respectively, and the effective number of bits is approximately 11.1bit. The power consumption of the ADC is 35mW under 1.8V supply, and the resulting figure of merit is 514fJ/conversion step.

Living organisms are active open systems far from thermodynamic equilibrium. The ability to behave actively corresponds to dynamical metastability: minor but supercritical internal or external effects may trigger major substantial actions such as gross mechanical motion, dissipating internally accumulated energy reserves. Gaining selective advantage from beneficial use of activity requires a consistent combination of sensual perception, memorised experience, statistical or causal prediction models, and resulting favourable decisions on actions. This information processing chain originated from mere physical interaction processes prior to life, here denoted as structural information exchange. From there, the self-organised transition to symbolic information processing marks the beginning of life, evolving by novel purposivity of trial-and-error feedback and accumulation of symbolic information. The emergence of symbols and prediction models can be described as a ritualisation transition, a symmetry-breaking kinetic phase transition of the 2^nd kind previously known from behavioural biology. The related new symmetry is the neutrally stable arbitrariness, conventionality or code invariance of symbols with respect to their meaning. The meaning of such symbols is given by the structural effect they ultimately unleash, directly or indirectly, by deciding on which actions to take. The early genetic code represents the first symbols. The genetically inherited symbolic information is the first prediction model for activities sufficient for survival under the condition of environmental continuity, sometimes understood as a “final causality” property of the model.

In the realm of mathematics education, self-explanation stands as a crucial learning mechanism, allowing learners to articulate their comprehension of intricate mathematical concepts and strategies. As digital learning platforms grow in prominence, there are mounting opportunities to collect and utilize mathematical self-explanations. However, these opportunities are met with challenges in automated evaluation. Automatic scoring of mathematical self-explanations is crucial for preprocessing tasks, including the categorization of learner responses, identification of common misconceptions, and the creation of tailored feedback and model solutions. Nevertheless, this task is hindered by the dearth of ample sample sets. Our research introduces a semi-supervised technique using the Language Learning Model (LLM), specifically its Japanese variant, to enrich datasets for the automated scoring of mathematical self-explanations. We rigorously evaluated the quality of self-explanations across five datasets, ranging from human-evaluated originals to ones devoid of original content. Our results show that combining LLM-based explanations with mathematical material significantly improves the model's accuracy. Interestingly, there's an optimal limit to how much synthetic self-explanation data can bene-fit the system. Exceeding this limit doesn't further improve outcomes. This study thus highlights the need for careful consideration when integrating synthetic data into solutions, especially within the mathematics discipline.

Acute myocardial infarction (AMI) is a leading cause of morbidity and mortality worldwide. This study aimed to test the efficacy of a newly-developed symptom self-management program on health outcomes among inpatients post-AMI. A pilot randomised, controlled trial was utilised. A convenience sample of 90 was recruited from a tertiary hospital in Singapore. Adult inpatients with post-AMI were randomly assigned to the three groups: IManage-HSet, IManage-FF or control group. Sample size was computed using power analysis. Data were collected through self-reported questionnaires and physiological instruments. Data analyses included univariate statistics, analysis of variance and repeated measure analysis of variance. Ninety participants were recruited with 30 in each group. Participants in the IManage-HSet and IManage-FF group had significantly greater relaxation (ηp2 = 0.11), lower objective stress (ηp2 =0.14), and greater knowledge (ηp2 = 0.62) than those of the control group. The two intervention groups had lower subjective stress (ηp2 = 0.04), depression (ηp2 = 0.01), and anxiety (ηp2 = 0.03) than the control but such differences did not achieve statistical significance. Furthermore, most participants reported that they were satisfied with the programs and they provided positive comments on the contents, educational materials and relaxation practice. This pilot study supports the potential benefits and feasibility of the IManage-VR and IManage-FF interventions on stress, perceived relaxation, knowledge and patient satisfaction. Contents of the symptom management interventions could be added into current cardiac rehabilitation programs. Future RCTs with multi-centered sites and larger sample size are required to further test the intervention. This study was prospectively registered with the International Standard Randomised Controlled Trial on the 5th August 2014 with registration number ISRCTN61027816.

Many researches have identified that adverse childhood experiences (ACEs) are associated with non-suicidal self-injury (NSSI) and suicidality. However, most studies have been restricted to a few types of ACEs. This study aims to investigate associations of 13 common types of ACEs with NSSI, suicidal ideation (SI) and suicide attempt (SA), as well as the mediation of depressive and anxiety symptoms therein. A total of 1771 students aged 11-16 years who participated in the baseline survey of the Chinese Adolescent Health Growth Cohort study were included for the analysis. ACEs, SI, SA, depressive and anxiety symptoms were recorded by standard questionnaire. Of included participants, 92.0% reported one or more category of ACEs. Smoking, parent-child separation, emotional abuse, physical abuse and being bullied were positively associated with NSSI, with the adjusted odds ratio (aOR) of 2.41(95%CI, 1.01-5.75), 1.80(1.28-2.54), 1.69(1.21-2.37), 2.08(1.44-3.01) and 1.87(1.35-2.59), respectively; smoking (4.03, 1.66-9.81), parent-child separation (1.42, 1.07-1.90), emotional abuse (1.91, 1.41-2.59), physical abuse (1.80, 1.27-2.57), emotional neglect (1.78, 1.28-2.49) and being bullied (2.08, 1.54-2.81) were positively associated with SI; smoking(4.30, 1.67-11.10), emotional abuse (2.42, 1.58-3.72) and being bullied (1.75, 1.17-2.60) were positively associated with SA. The associations of ACEs with NSSI, SI and SA were each partially or completely mediated through depressive and anxiety symptoms. Children and adolescents who had experiences of smoking, physical abuse and being bullied during childhood are consistently and independently associated with NSSI and suicidality, and these associations may be largely mediated through depressive and anxiety symptoms.

The self-organization properties of C70 fullerene molecules in a xylene/tetrahydrofuran binary mixture were studied for the first time by optical absorption, refractometry, and dynamic light scattering. A correlation has been established between the change in the refractive index of the C70/xylene/tetrahydrofuran solution and the degree of self-organization of C70 molecules in the medium at various concentrations and storage periods of the solution. It is shown that the features of the optical absorption spectrum of C70/xylene/tetrahydrofuran at a fixed low concentration of the fullerene are sensitive to its storage time. It was determined that the beginning time of the formation of C70 nanoclusters and their final size depend on the concentration of fullerene and the time of keeping the solution. The observed nature of the C70 fullerene solution in a binary mixture may help to elucidate the mechanism of self-organization in the future.

Since the emergence of convolutional neural networks (CNNs), and later vision transformers (ViTs), the standard paradigm for model development has been using a set of identical block types with varying parameters/hyper-parameters. To leverage the benefits of different architectural designs (e.g., CNNs and ViTs), we propose alternating structurally different types of blocks to generate a new architecture, mimicking how Lego blocks can be assembled. Using two CNN-based and one SwinViT-based blocks, we investigate three variations to the so-called LegoNet that apply the new block alternation concept for the segmentation task in medical imaging. We also study a new clinical problem that has not been investigated before – the right internal mammary artery (RIMA) and perivascular space segmentation from computed tomography angiography (CTA). It was proven to demonstrate a prognostic value to primary cardiovascular outcomes. We compare the model performance against popular CNN and ViT architectures using two large datasets (achieving 0.749 dice similarity coefficient (DSC) on the larger dataset). We also evaluate the model’s performance on three external testing cohorts, where an expert clinician corrected model-segmented results (DSC>0.90 for the three cohorts). To assess our proposed model for suitability in clinical use, we perform intra- and inter-observer variability analysis. Finally, we investigate a joint self-supervised learning approach to determine its impact on model performance.

The poor conductivity and instability of layered dihydroxides (LDHs) limit their widespread application in oxygen evolution reaction (OER). In this study, the composite electrode of NiMn-LDHs, reduced graphene oxide (rGO) and nickel foam (NF), i.e., NiMn-LDHs/rGO/NF, was prepared by a hydrothermal method. When subjected to oxygen evolution reaction (OER) catalytic performance in a solution of 1 M KOH, the NiMn-LDHs/rGO/NF composite catalyst exhibited an overpotential of only 140 mV at a current density of 10 mA cm-2 and a Tafel slope of 49 mV dec-1, which is not only better than the comparing RuO2/NF catalyst, but also better than most of the Mn-based and the Ni–Fe containing bimetallic OER catalysts reported in the literature. The excellent electrocatalytic performance is ascribed to the efficient integration of ultrathin NiMn-LDHs sheets, thin-layered rGO and NF, contributing a lot to the decrease in charge transfer resistance and the increase in electrochemically active surface area. Moreover, NF plays a role of current collector and a role of rigid support for the NiMn-LDHs/rGO composite, contributing extra conductivity and stability to the NiMn-LDHs/rGO/NF composite electrode.

This study analyses key aspects of the professional life of primary school teachers in a southern European context. In the social changes of last two decades profoundly impacted the well-being of teachers putting a strain on their ability to adapt to sometimes unfair working conditions. For this purpose twenty teachers (M = 38.85; DS = 9.17) were interviewed from different areas of Italy, data were analyzed using the Grounded Theory Method. Through data analysis were summa-rize and emphasize eight core themes. The results show the effects of a gradual impoverishment of the recognition of the role of teacher, highlighting the difficulty for teachers of renegotiating more flexible workload assessments and of reinforcing psycho-emotional skills for the development of a teaching methodology attentive to the psycho-emotional needs of pupils. Schools emerge as a rigid working context, in which a competent organizational function is often absent. Practical psychological implications are discussed.

The transition from undergraduate dental student to the actual practicing dentist is a crucial phase and ensuring the preparedness of graduates for the complexity and demands of contempo-rary dental practice is a challenging task. This study aimed to evaluate the self-perceived prepar-edness of undergraduate dental students and house officers in the dental colleges of Pakistan. Cross-sectional national study was planned to collect the information from dental students and new graduates in Pakistan. The pre-validated Dental Undergraduates Preparedness Assessment Scale (DU-PAS) was used. Purposive sampling technique was utilized to recruit house officers and undergraduate dental students from 27 dental schools in Pakistan. The data analysis was car-ried out using the R statistical environment for Windows (R Core Team, 2015). The total of 862 responses with 642 females and 219 males were analyzed in the study. Overall, clinical skills score was 30.56+9.08 and score for soft skills was 30.54+10.6. The mean age of the participants was 23.42+1.28. Deficiencies were reported in various soft skills and clinical skills attributes.The results highlighted the strengths and weaknesses of dental students and new graduates in Pakistani den-tal institutions. The findings may be used to further develop and strengthen teaching and training of dental students in Pakistan.

For any molecule, network, or process of interest, to keep up with new publications on these, is becoming increasingly difficult. For many cellular processes, molecules and their interactions that need to be considered can be very large. Automated mining of publications can support large scale molecular interaction maps and database curation. Text mining and Natural Language Processing (NLP)-based techniques are finding their applications in mining the biological literature, handling problems such as Named Entity Recognition (NER) and Relationship Extraction (RE). Both rule-based and machine learning (ML)-based NLP approaches have been popular in this context, with multiple research and review articles examining the scope of such models in Biological Literature Mining (BLM). In this review article, we explore self-attention based models, a special type of neural network (NN)-based architectures that have recently revitalized the field of NLP, applied to biological texts. We cover self-attention models operating either at a sentence level or an abstract level, in the context of molecular interaction extraction, published from 2019 onwards. We conduct a comparative study of the models in terms of their architecture. Moreover, we also discuss some limitations in the field of BLM that identifies opportunities for the extraction of molecular interactions from biological text.

The Amoebic Self Theory is a concept of the social psychology, which postulates that humans have a psychological boundary. As the authors of the concept propose [1], the function of the boundary is to allow psychological separation of one from the others. In this study, we examined how sen-sitivity to violation of the boundary, measured by an amoebic self scale, is connected with differ-ent types of procrastination sensu lato, measured by seven procrastination subscales. Only two of the seven procrastination aspects, i.e. the preference for pressure and outcome satisfaction, were negatively and significantly related to the spatial-symbolic domain of the amoebic self scale. The other purpose of this research was to examine the connection between the students’ grade point average (GPA) and scores obtained in the procrastination subscales. Only the non-adaptive aspect of procrastination predicted significantly the GPA. That is an important detail, because pointing out the gap between one’s self-opinion and the real, non dependent of the opinion, academic achievement. All these findings were considered in the academic context and consequences of these results were discussed.

Background: Adolescence is a developmental stage when there is a high risk of engaging in non-suicidal self-injury (NSSI). There is recent interest in the study of thwarted belongingness and perceived burdensome as variables associated with the frequency of NSSI in adolescents. Meaning in life (MIL) could be negatively associated with thwarted belongingness and perceived burdensome. To date, no studies have analyzed whether thwarted belongingness and perceived burdensomeness could be associated with the frequency of NSSI in adolescents. On the other hand, no studies have analyzed the buffering role of MIL in the association between thwarted belongingness and perceived burdensomeness and the frequency of NSSI. Aims: a) to test whether thwarted belongingness and perceived burdensomeness are associated with NSSI frequency; b) to test whether MIL moderates the association between thwarted belongingness and NSSI frequency; and c) to test whether MIL moderates the association between perceived burdensomeness and NSSI frequency. Method: The sample consisted of N = 1531 participants between 12 and 18 years old from Spain. The participants filled out the Inventory of Statements about Self-Injury, Purpose-In-Life Test-Adolescents Version, and Interpersonal Needs Questionnaire. Moderation analysis were performed. Results: Thwarted belongingness and perceived burdensomeness were positively associated with the frequency of NSSI in Spanish adolescents. MIL was a moderating variable between thwarted belongingness and the frequency of NSSI, and between perceived burdensomeness and the frequency of NSSI. Conclusion: Thwarted belongingness and perceived burdensomeness could be a risk factor for NSSI and MIL could be a protective factor against NSSI, and adding these variables to current descriptive theories of NSSI in adolescents would allow us to improve the assessment and treatment protocols for adolescents with NSSI.

Not only does this paper present a novel type-2 fuzzy system for identification and behavior prognostication of an experimental solar cell set and a wind turbine, but also it brings forward an exquisite technique to acquire an optimal number of membership functions and the corresponding rules. It proposes a seven-layered NCPRT2FS. For fuzzification in the first two layers, Gaussian type-2 fuzzy membership functions with uncertainty in the mean, are exploited. The third layer comprises rule definition and the forth one embeds fulfillment of type reduction. The three last remained layers are the ones in which resultant left–right firing points, two end-points and output all get assessed correspondingly. It should not be neglected off the nutshell that recurrent feedback at the fifth layer exerts delayed outputs ameliorating efficiency of the suggested NCPRT2FS. Later in the paper, a modern structural learning, established on type-2 fuzzy clustering, is held forth. An adaptively rated learning back-propagation algorithm is extended to adjust the parameters ensuring the convergence as well. Eventually, solar cell photo-voltaic and wind turbine are deemed as case studies. The experimental data are exploited and the consequent yields emerge so persuasive.

Due to the fact that negative energies have no existence in physical reality, the advanced mechanics of purely positive energies should describe gravitational interactions and collisions in monistic terms of extended kinetic energies and their local stresses. Such non-Newtonian mechanics of continuous inertial densities reinforces the Cartesian concept of matter-extension in the metric formalism of Einstein-Grossmann with a supplemental (dark, aether) fraction of bi-vertex mass-energy distributions. Local accelerations or decelerations of mono-vertex material densities in a multi-vertex distribution of complete kinetic energy arise under its constant integral due to nonlocal organization of continuous densities. Such integral conservation of the distributed mass-energy occurs instantaneously throughout the whole continuum of correlated densities and metric stresses despite the time-varying contributions of complementary mono-vertex and bi-vertex fractions. Under the nonlocal organization of purely kinetic (positive) mass-energy, geodesic self-heating and self-cooling of the pulsating space-matter conserve the integral energy in the two-fraction virial theorem for the averaged motion of visible mono-vertexes in the presence of invisible bi-vertex (interference, dark) mass-energy. Metric stresses of such material space are subordinate to nonlocal self-government of continuously distributed kinetic energy, including the relativistic rest-energy of General Relativity. These mutually consistent or correlated stresses in inertial space-time-energy create timelessly coordinated self-accelerations, observed for dense material volumes as distant gravitational pulls. In order to falsify/verify the nonlocal self-organization of adaptive kinetic energy, the monistic mechanics of self-consistent inertial densities and metric stresses can suggest moderate field changes in the temporal redshift, cycles of geodetic falls and takeoffs in pulsating kinetic organizations, and the calculated acceleration of the expanding Metagalaxy in its current phase of geodesic self-cooling.

Drought severity still remains a serious concern across sub-Saharan Africa (SSA) due to the destructive impact on multiple sectors of our society The interannual variability and trends in the changes of self-calibrated Palmer Drought Severity Index based on Penman–Monteith (scPDSIPM) and Thornthwaite (scPDSITH) methods for potential evapotranspiration (PET), precipitation (P) and normalized difference vegetation index (NDVI) anomalies, and sea surface temperature (SST) anomaly were investigated through statistical analysis of modelled and remote sensing data. It is shown that scPDSIPM and scPDSITH differed in the representation of drought characteristics over SSA. The scPDSI and remotely-sensed-based anomalies of P and NDVI showed wetting and drying trends over the period 1980-2012. The trend analysis showed increased drought events in the semi-arid and arid regions of SSA over the same period. A correlation analysis reveals a strong relationship between scPDSI variability and P, and NDVI anomalies for monsoon and pre-monsoon seasons. The correlation analysis of scPDSI variability with SST anomalies indicates significant positive and negative relationships, respectively. This study has demonstrated the applicability of multiple data sources for drought assessment and provides useful information for regional drought predictability and mitigation strategies.

The purpose of this study was to assess the extent to which self-esteem and depression mediated the influence of internalized stigma on life satisfaction among Korean out-of-school youths. Cross-sectional data on 318 youths provided information on perceived stigma, self-esteem, depression, life satisfaction, and personal characteristics. A multinomial logistic regression analysis was followed by structured path analysis to investigate the mediation effects. Internalized stigma was negatively associated with life satisfaction. Self-esteem significantly mediated the influence of stigma on depression and the influence of depression on life satisfaction. Further, stigma directly and significantly influenced depression. This study demonstrated that self-esteem and depression were important to the relationship between internalized stigma and life satisfaction. Implications for possible policies and programs with the aim of helping out-of-school youths to integrate and lead successful satisfying lives are discussed.

The use of cow bones for biomaterial is still limited; accordingly, the cow bones waste has low economic value. Basically, a human’s and a cow’s bones are the same in terms of their forming compound. Aluminum (Al) has the potential to combine with hydroxyapatite (HAp) to make metal matrix composites (MMC) that have the potential for biomaterials. Compatible elements to be combined with Al and HAp are magnesium (Mg), titanium (Ti), and Copper (Cu), used self-high propagating temperatures synthesis (SHS). MMC can be processed to be a useful, solid product. Applying pressure to the SHS reaction and heating process may result in biomaterial composite product consisting of some matrix materials such as Al come from cans materials used in the experiment was HAp that was processed from cow bones calcination, added by can that contained aluminum and wetting agent, namely magnesium. The exothermic temperature was 800-900°C. The compaction process was done to allow materials to be bound. Based on the ASTM F138 standard for element of biomaterials, the porosity value was below 30% and hardness level above 40 HV. Cow bones and can-based composite sample with the composition of HAp-Al-Mg: 85%-10%-5% met the standard since the hardness value was: 73.3 HV with a porosity value of 29.88%.

COVID-19 thromboembolic disease has brought all of us back to the drawing board. In COVID-19, pre-existing activated endothelium with increased Von Willebrand factor (VWF), low density lipoprotein (LDL) promoting “self-association” and “sticking” of long VWF strings to the vascular endothelial wall, suppressed ADAMTS13 cleavage of VWF, hypoxia induced upregulation and activation of VWF, fibrous network from neutrophil extracellular traps (NETs) with free DNA and histone, all appear to be initiating the thrombogenesis. Worsening complement activation, cytokine storm and resulting endothelial destruction, unregulated thrombogenesis leads to vascular occlusions and hypoxia. At this stage, the presence of abundant extracellular DNA, histone and -defensins appears worse than the SARS-CoV-2 itself. Previously observed in vitro mechanisms like histone “auto-activating” prothrombin, histone activated platelets generating thrombin without FXII, thrombin and plasmin cleaving complement C5 appears highly likely in COVID-19. Megakaryocytes are actively producing platelets in the lungs and appear to play a major role in thrombogenesis of COVID-19 raising suspicion of emperipolesis. This focused review is a compilation of my observations in relation to the pathophysiology of the intravascular environment, mainly in COVID-19 lungs. Pathophysiology based clinical trials are paramount in reducing morbidity and mortality in COVID-19.

Optimism and self-efficacy have been associated with psychological health. Empathy has also been found to promote positive functioning and to have a unique role in community health volunteering. This study investigated whether self-efficacy and optimism were associated with psychological and subjective well-being in a group of healthcare volunteers and whether empathy added incrementally to these associations. A sample of 160 Italian clown doctors volunteering in various hospitals completed self-report measures of self-efficacy, optimism, empathy, psychological well-being, and subjective well-being. Results indicated that self-efficacy and optimism were associated with both outcomes and that aspects of empathy, such as others’ perspective-taking and personal distress for others’ difficulties, incrementally added to these associations, although with opposite effects. The present study adds to previous research on the role of self-efficacy, optimism, and empathy for community health volunteers’ psychological health and offers suggestions regarding the training of this type of volunteer.

Owing to the time-varying characteristics and nonlinearities of industrial processes, control has higher difficulties and results in challenges for advanced technology. In this paper, a self-tuning controller that includes a nonlinear proportional-integral-derivative (NPID) control function as well as a self-tuning function is proposed for first-order plus time delay (FOPTD) process control. The NPID control function is implemented using the nonlinear PID controller whose optimum parameters are adapted by a neural network (NN). The self-tuning function is able to identify the process dynamics using a short period of process behavior and tune NPID parameters based on the identified parameters. The advantage of the proposed method is validated with a set of simulation works on three processes and the comparison results are presented.

Accurate prediction of the self-propulsion performance is one of the most important factors for energy-efficient design of a ship. In general, the hydrodynamic performance of a full-scale ship could be achieved by model-scale simulation or towing tank test with extrapolations. With the development of CFD methods and computing power, directly predict ship performance with full-scale CFD is an important approach. In this article, a numerical study on the full-scale self-propulsion performance with propeller operating behind ship at model- and full-scale is presented. The study includes numerical simulations using RANS method with double-model and VOF model respectively and scale effect analysis based on overall performance, local flow fields and detailed vortex identification. Verification study on grid convergence is also performed for full-scale simulation with global and local mesh refinements. And a series of sea trail tests were performed to collect reliable data for the validation of CFD predictions. The analysis of scale effect on hull-propeller interaction shows that the difference on hull boundary layer and flow separation is the main source of scale effect on ship wake. And the results of the fluctuations of propeller thrust and torque along with circulation distribution and local flow field show that propeller’s loading is significantly higher for model-scale ship. It is suggested that the difference on vortex evolution and interaction is more pronounced and have larger effects on ship’s powering performance at model-scale than full-scale according to the simulation results. From the study on self-propulsion prediction, it could be concluded that the simplification on free surface treatment does not only affect the wave-making resistance for bare hull but also the propeller performance and propeller induced ship resistance which can produced up to 5% uncertainty to the power prediction. Roughness is another important factor in full-scale simulation because it has up to approximately 7% effect on the delivery power. As a result of validation study, the numerical simulations of full-scale ship self-propulsion shows good agreement with the sea trail data especially for cases that have considered both roughness and free surface effects. This result will largely enhance our confidence to apply full-scale simulation in the prediction of ship’s self-propulsion performance in the future ship designs.

Opioids are highly addictive substances with a relapse rate of over 90%. While preclinical models of chronic opioid exposure exist for studying opioid dependence, none recapitulate the relapses observed in human opioid addiction. The mechanisms associated with opioid dependence, the accompanying withdrawal symptoms and the relapses that are often observed months or years after opioid dependence are poorly understood. Therefore, we developed a novel model of chronic opioid exposure whereby the level of administration is self-directed with periods of behavior acquisition, maintenance and then extinction alternating with reinstatement. This profile arguably mirrors that seen in humans, with initial opioid use followed by alternating periods of abstinence and relapse. Recent evidence suggests that dietary interventions that reduce inflammation, including omega-3 fatty acids such as docosahexaenoic acid (DHA), may reduce substance misuse liability. Using the self-directed intake model, we characterize the observed profile of opioid use and demonstrate that a diet enriched in polyunsaturated fat acids (PUFAs) ameliorates oxycodone-seeking behaviors in the absence of drug availability and reduces anxiety. Guided by the major role gut microbiota have on brain function, neuropathology, and anxiety, we profile the microbiome composition and the effects of chronic opioid exposure and DHA supplementation. We demonstrate that withdrawal of opioids led to a significant depletion in specific microbiota genera whereas DHA supplementation increased microbial richness, phylogenetic diversity, and evenness. Lastly, we examined the activation state of microglia in the striatum and found that DHA supplementation reduced the basal activation state of microglia. These preclinical data suggest that a diet enriched in PUFAs could be used as a treatment to alleviate anxiety induced opioid-seeking behavior and relapse in human opioid addiction.

The quantization error (QE) from Self-Organizing Map (SOM) output after learning is exploited in this studies. SOM learning is applied on time series of spatial contrast images with variable relative amount of white and dark pixel contents, as in monochromatic medical images or satellite images. It is proven that the QE from the SOM output after learning provides a reliable indicator of potentially critical changes in images across time. The QE increases linearly with the variability in spatial contrast contents of images across time when contrast intensity is kept constant. The hitherto unsuspected capacity of this metric to capture even the smallest changes in large bodies of image time series after using ultra-fast SOM learning is illustrated on examples from SOM learning studies on computer generated images, MRI image time series, and satellite image time series. Linear trend analysis of the changes in QE as a function of the time an image of a given series was taken gives proof of the statistical reliability of this metric as an indicator of local change. It is shown that the QE is correlated with significant clinical, demographic, and environmental data from the same reference time period during which test image series were recorded. The findings show that the QE from SOM, which is easily implemented and requires computation times no longer than a few minutes for a given image series of 20 to 25, is useful for a fast analysis of whole series of image data when the goal is to provide an instant statistical decision relative to change/no change between images.

Owing to the nondiffracting, self-accelerating, and self-healing properties, Airy beams of different nature have become a subject of immense interest in the past decade. Their interesting properties have opened doors to many diverse applications. Consequently, the questions of how to properly design spatial manipulation of Airy beams or how to implement them in different setups have become important and timely in the development of various optical devices. Here, based on our previous work, we present a short review on the spatial control of Airy beams, including the interactions of Airy beams in nonlinear media, beam propagation in harmonic potential, and the dynamics of abruptly autofocusing Airy beams in the presence of a dynamic linear potential. We demonstrate that under the guidance of nonlinearity and external potential, the trajectory, acceleration, structure, and even the basic properties of Airy beams can be adjusted to suit specific needs. We describe other fascinating phenomena observed with Airy beams, such as self-Fourier transformation, periodic inversion of Airy beams, and the appearance of spatial solitons in the presence of nonlinearity. These results have promoted the development of Airy beams, and have been utilized in various applications, including particle manipulation, self-trapping, and electronic matter waves.

In wireless sensor networks (WSNs), each sensor node can estimate the global parameter from the local data in distributed manner. This paper proposed a robust diffusion estimation algorithm based on minimum error entropy criterion with self-adjusting step-size, which are referred to as diffusion MEE-SAS (DMEE-SAS) algorithm. The DMEE-SAS algorithm has fast speed of convergence and is robust against non-Gaussian noise in the measurements. The detailed performance analysis of the DMEE-SAS algorithm is performed. By combining the DMEE-SAS with diffusion minimum error entropy (DMEE) algorithms, an Improving DMEE-SAS algorithm is proposed, in non-stationary environment where tracking is very important. The Improving DMEE-SAS algorithm can avoid insensitivity of the DMEE-SAS algorithm due to the small effective step-size near the optimal estimator, and obtain a fast convergence speed. Numerical simulations are given to verify the effectiveness and advantages of these proposed algorithms.

This numerical study investigates the impact of reaction temperature, molar ratio of CH4:CO2, and catalyst porosity (p) on H2 yield and H2 selectivity during biogas dry reforming over a Ni/Cr catalyst. Using COMSOL Multiphysics, we conducted detailed simulations to elucidate the underlying reaction characteristics. Our findings reveal that increasing p significantly enhances H2 production and H2 selectivity, while simultaneously reducing CO selectivity. This effect is attributed to the improved mass transfer within the catalyst bed, leading to more efficient reactant conversion and product formation. Additionally, we observed a strong correlation between higher reaction temperatures and increased H2 yield and H2 selectivity, confirming the endothermic nature of the reforming process. By optimizing these operational parameters, our results suggest that Ni/Cr catalysts can be effectively employed for the sustainable production of H2 from biogas.

Plastic pollution is a pressing environmental challenge, necessitating the development of biodegradable alternatives like polyhydroxybutyrate (PHB). This study focuses on optimizing PHB production by Neobacillus niacinii GS1, a bacterium isolated from a municipal dumping site. By utilizing agricultural residues such as corn flour, wheat bran, and peptone as substrates, we aimed to establish an eco-friendly method for biopolymer production, contributing to sustainable waste management and bioplastic innovation. The bacterium was identified using morphological, biochemical, and molecular techniques. The optimization process involved adjusting variables such as inoculum age, inoculum size, incubation time, agitation rate, incubation temperature, pH of the medium, carbon sources and nitrogen sources. Response surface methodology (RSM) was employed to identify optimal conditions, with the highest PHB yield of 61.1% achieved under specific conditions: 37°C, pH 7, and an agitation rate of 150 rpm. These findings underscore the potential of Neobacillus niacinii GS1 in converting agro-industrial residues into valuable biopolymers, promoting sustainable bioplastic production, and advancing waste valorization efforts through the use of eco-friendly materials.

Photocatalytic processes offer promising solutions for environmental remediation and clean energy production, yet their efficiency under visible light remains a significant challenge. Here, we report a novel silver-graphene (Ag-G) modified TiO2 (Ag-G-TiO2) nanocomposite photocatalyst that demonstrates remarkably enhanced photocatalytic activity for both dye wastewater degradation and hydrogen production under visible and UV light irradiation. Through comprehensive characterization and performance analysis, we reveal that the Ag-G modification narrows the TiO2 bandgap from 3.12 eV to 1.79 eV, enabling efficient visible light absorption. The nanocomposite achieves a peak hydrogen production rate of 191 μmolesg-1h-1 in deionized water dye solution under visible light, significantly outperforming unmodified TiO2. Intriguingly, we observe an inverse relationship between dye degradation efficiency and hydrogen production rates in dye solutions with tap water versus deionized water, highlighting the critical role of water composition in photocatalytic processes. Our findings demonstrate sustained hydrogen production under visible light and rapid initial rates under UV irradiation, underscoring the versatility of Ag-G-TiO2 catalyst. This work not only advances our understanding of fundamental photocatalytic mechanisms but also presents a promising material for solar-driven environmental and energy applications, potentially contributing to the global transition towards sustainable technologies.

The MAPK signaling pathway with BRAF mutations has been shown to drive the pathogenesis of 40-60% of melanomas. Inhibitors of this pathway's BRAF and MEK components are currently used to treat these malignancies. However, responses to these treatments are not always successful. Therefore, identifying noninvasive biomarkers to predict treatment responses is essential for personalized medicine of melanoma patients. Using noninvasive 1H magnetic resonance spectroscopy (1H MRS), we previously showed that BRAF inhibition reduces lactate and alanine tumor levels at early stages of effective therapy and could be construed as metabolic imaging biomarkers for drug response. The present work aimed to demonstrate if these metabolic changes and those assessed by 31P MRS are also found in preclinical human melanoma models treated with MEK inhibitors. Apart from 1H and 31P MRS, additional supporting in vitro biochemical analyses are described. Our results indicate significant early metabolic correlations with response levels to MEK inhibition in the melanoma models and are consistent with our previous study of BRAF inhibition. Given these results, our study supports the potential clinical utility of noninvasive MRS to objectively image metabolic biomarkers for early predicting melanoma response to MEK inhibition.

The study examines the integration of postbiotics in food products through the use of attenuated probiotics, specifically lactic acid bacteria (LAB) in bread. Postbiotics, non-viable microorganisms or their metabolites, offer health benefits similar to probiotics without the risks associated with live bacteria. This research evaluates the regulatory aspects and safety of LAB in sourdough bread production, highlighting their historical and significant use in Europe before 1997. The study includes microbial quantification and Next-Generation Sequencing (NGS) to identify LAB in traditional sourdough, comparing them with historical and current EFSA Qualified Presumption of Safety (QPS) lists. Findings show that the LAB present in sourdough have been extensively and safely used in bread making, supporting their classification as non-novel foods under EU regulations. The stability and consistency of LAB metabolites in sourdough bread are also confirmed, ensuring quality and safety in each batch. The study concludes that LAB in sourdough, when inactivated through bread-making processes, are not considered novel foods, aligning with historical, scientific, and regulatory evidence.

Seed potato treatment is vital for plant protection, yield enhancement, and product quality. In the conducted research, the plant biostimulator Supporter was applied to evaluate its impact on potato yields. Field studies were conducted in Northeastern, Northwestern, Western, and Southwest Poland from 2015 to 2017, using a randomized complete block design with a split-plot arrangement. The use of seed treatment technology with the Supporter product resulted in increased overall and commercial potato yields and improved yield tuber structure compared to traditional cultivation methods without tuber treatment before planting. Conclusion: The application of the plant biostimulator Supporter in seed potato treatment technology brings significant benefits, including, increased potato yield and improved yield structure. The cultivation location significantly influences potato yield and tuber structure. Understanding these differences can aid in better adapting cultivation practices and selecting varieties to specific local conditions, potentially leading to increased potato crop productivity. In terms of efficiency and yield quality, further research into its application in agricultural practice is recommended, which may contribute to further increasing potato production efficiency and quality. Developing more ecological and efficient farming practices can help meet society's growing food needs.

Access to urban green and blue spaces (UGBS) has been associated with positive effects on health and wellbeing; however, the past decades have seen a decline in quality and user satisfaction with UGBS. This reflects the mounting challenges that many UK cities face in providing appropriate public facilities alongside issues such as health inequalities, an ageing population, climate change, and loss of biodiversity. At present, little is known about the preferences of different population subgroups and, specifically, the UGBS they visit and the spaces they avoid. Using a public participatory geographic information system (PPGIS), the overall aim of the research presented here was to investigate the preferences of different population subgroups in urban areas, and the UGBS they visit, using Edinburgh, Scotland as a case study. We created a baseline visitor demographic profile for UGBS use, and highlighted how visitors perceive, physically access, use, and engage with UGBS. The results revealed considerable variation in UGBS preference: one person’s favourite UGBS may be one that someone else dislikes and avoids. It is clear that adapting UGBS to suit local communities should not be a ‘one-size-fits-all’ approach. The conflicting views and preferences of different groups of respondents point to the importance of developing policies and park management plans that can accommodate a variety of uses and experiential qualities within individual parks. PPGIS offers an ideal tool for achieving this

Resveratrol is currently considered an option for chemoprevention and treatment of oral cancer, but the instability and unfavorable pharmacokinetics hinder its use in clinical practice. The present study deals with the preparation of resveratrol liposomes by a method that preserves stability and provides payload high enough for chemoprevention and/or treatment of oral cancer. Different temperatures, RSV concentrations and molar fractions, as well as the presence or absence of vitamin C in the hydration media were assayed. Liposome hydrodynamic diameter, polydispersity and zeta potential were evaluated by dynamic light scattering. In vitro biocompatibility, antioxidant activity and permeability were evaluated using TR146 cells and PermeaPad® membranes. Liposomes were included in hydrogels and films, and their suitability for buccal application was evaluated. According to the results, a temperature of 37ºC was optima to efficiently produce the resveratrol liposomes. Vitamin C was found to influence the liposome size, while resveratrol concentration significantly influenced the entrapment efficiency. High cell biocompatibility and potent intracellular antioxidant activity were observed and the inclusion of vitamin C reinforced the antioxidant effects. High permeation across PermeaPad® membranes and efficient uptake by TR146 cells was proved for resveratrol loaded liposomes. Liposomal hydrogels and films appropriated for buccal application were obtained and the payload of the formulations was high enough to produce mucosa concentrations above resveratrol IC50 values reported for cancer cells.

: Sulfate presence is of great importance for anaerobic digestion as its addition can control the anaerobic microbial community. In this study, the effect of sulfuric acid addition on the perfor-mance of an UASB reactor fed with hydrolyzed starch was investigated. TOC, Fe and SO4-2 re-moval as well as the methane production were monitored under various COD/ SO4-2 ratios, HRTs and OLRs. When HRT was 16 hours and OLR equal to 2 g COD/LUASB-d the methane production was 0.24 L CH4/LUASB-day. After the sulfuric acid addition, TOC removal reached 95%. At HRT, OLR, and COD/ SO4-2 ratio equal to 16 hours, 2 g COD/ LUASB-d and 3.72 respectively, the methane production was 0.267 L CH4/LUASB-d. When the OLR was increased to 5.94 g COD/LUASB-d and COD/SO4-2 ratio was equal to 12.5, the methane production was 3 times higher (0.84 L CH4/LUASB-d) with a methane content in the produced biogas greater than 70%. 16s rRNA gene analysis demonstrated that after the sulfate addition, SRB were enriched and methane was mainly produced by Methanosaeta sp. This study indicates that appropriate sulfate concentrations in the feed in combination with the presence of iron in the UASB reactor lead to enhanced me-thane yields.

Novel approaches under the extreme conditions of ultra-high gravity of a super massive black hole allow us to assume that the spacetime degrades into the single dimension of time. A unique interpretation of the non-relativistic Schrödinger equation together with the relativistic Klein-Gordon and Dirac equations is presented by swapping the three dimensional space derivatives with the singular time derivative in the D’Alembertian operator. This apparatus reveals a unique time dependent wave equation that results in some implications such as possible time quantization with the intervals of around 3.36 × 10−21 ? which is in the order of uncertainty in time, ∆? = 1.3 × 10−21 ?, calculated from the energy-time version of the Heisenberg uncertainty principle for electrons. As a result of this, an antisymmetric wave function around the edge of the event-horizon zone appears and indicates that the virtual particle-antiparticle pairs of the electron field split into two real components with the spin-up and down states, reconfirming the Hawking radiation. Energy eigenvalues calculated from the application of the Dirac equation satisfies the preservation of energy and charge. The wave equation invoked in this study reduces into the time dependent Dirac equation within the neighborhood of zero-point, ? = 0, insuring the relevance of the evaluations.

Previous research on the relative benefits of Augmentative and Alternative Communication Systems (AACs) has indicated controversial results regarding the effectiveness, the ease of use, and the preference for the different systems. The study aims to observe the comparative effectiveness of two different Augmentative and Alternative Communication (AAC) tools, the Picture Exchange Communication System (PECS) and a speech-generating device (SGD), as communication aids for children with autism. Three children with severe autism and minimally verbally or with no functional language participated. The results showed an increase of communicative behavior with both AAC intervention strategies and a speed acquisition time slightly shorter for the SGD training. Two of the three participants showed a preference for the use of the SGD. Reduction in problem behaviors and improvement in vocal production was observed for one of the participants. Results suggest that PECS and SGD are similarly appropriate for the development of initial request skills and that they can encourage vocal production in students with specific prerequisites.

The owners of forests with water protection functions in Bulgaria do not receive compensation for their limited right to use wood and non-wood forest products from the forest areas they own. At the same time, the contribution derived from forests with water protection functions is received by water users and water consumers, whereas the costs of managing the forests are borne by their owners. The problem thus defined is not a forestry one, but an economic one, and the purpose of this paper ensues therefrom, namely to propose and test a methodology for valuating the produc-tion function of forest areas with water protection function in Bulgaria, allowing a fair distribu-tion of income between the forest owner and the user of forest ecosystem services. The methodol-ogy is based on the form of forest management and the analytical expression of the economic rela-tionship between a forest owner and a user of forest ecosystem services, constructed using Schen-rock’s formula. It has been tested with actual data on forest areas with water protection functions falling within the administrative and territorial scope of Velingrad municipality and based on the obtained results proposals have been made for the distribution of the contributions generated by forest ecosystems between the forest owner and the user of the forest ecosystem services.

This article purposed to examine the impact of integration between Lean accounting (LA) tools & Just in Time (JIT) technique on Cost Reduction (CR) in modern manufacturing environment in Saudi establishments, these two variable moderated by Ethical Standards (ESs). A quantitative methodology was used for realizing the study objectives and answering study questions, the main tool exercised for producing the incipient data was a fully-structured questionnaire with closed ended questions, which was designed and passed around online among a selected sample of (109) managers and accountants in Saudi manufacturing firms. Descriptive and deductive statistics adopted to derive the findings, wherefore the compiled responses analyzed by SPSS & AMOS and the results showed that there is direct and indirect effect of LA tools & JIT technique on CR in Saudi industrial companies, especially when using ESs. These findings could provide decision makers in Saudi manufacturing companies with the acuity of adopting both methods in a combined way to maximize the profits of these firms. The results of this study also suggest that the application of LA tools & JIT technique has a positive effect on the promotion of sustainable manufacture and consequent achievement of high sustainable performance.

Infection with the porcine reproductive and respiratory syndrome virus type 1 (PRRSV-1) has serious economic consequences for the pig industry. Swine practitioners and other agricultural advisors often describe an increase in antibiotic use when PRRSV-1 is circulating. Our objective was to assess the impact of PRRSV-1 stabilization programmes on reducing antibiotic use. The study was carried out on 19 French farrow-to-finish farms that successfully implemented a PRRSV-1 stabilization protocol between 2007 and 2019. For each farm, antibiotic consumption (expressed in mg/PCU and ALEA) were compared one year before (P1) and one year after (P2) the implementation of such a protocol and the change between P1 and P2 were calculated in percentages. Data were then analysed by level of consumption. Antibiotic use decreased significantly between P1 and P2 if expressed in mg/PCU and showed a decreased tendency in terms of exposure (ALEA). Concerning the change from P1 to P2, our results showed that the higher consumption levels in P1, the greater antibiotic reduction in P2. This study highlights the ability of a stabilization protocol against PRRSV-1 to reduce antibiotic use, especially on farms that have high consumption. These hopeful results show that further investigations about the relationship between PRRSV-1 and antibiotic usage could be beneficial.

Through a modern derivation of Planck's formula for the entropy of an arbitrary beam of photons we derive a general expression for the entropy production due to the irreversible process of the absorption of an arbitrary incident photon spectrum in material and its dissipation into an infrared-shifted grey-body emitted spectrum, the rest being reflected or transmitted. Employing the framework of Classical Irreversible Thermodynamic theory, we define the generalized thermodynamic flow as the flow of photons from the incident beam into the material and the generalized thermodynamic force is then just the entropy production divided by the photon flow which is the entropy production per unit photon at a given wavelength. We compare the entropy production under sunlight of different inorganic and organic materials (water, desert, leaves and forests) and show that organic materials are the greater entropy producing materials. Intriguingly, plant and phytoplankton pigments (including chlorophyll) have peak absorption exactly where entropy production through photon dissipation is maximal for our solar spectrum $430<\lambda<550$ nm, while photosynthetic efficiency is maximal between 600 and 700 nm. These results suggest that the evolution of pigments, plants and ecosystems has been towards optimizing entropy production rather than photosynthesis. We propose using the wavelength dependence of global entropy production as a biosignature for discovering life on planets of other stars.

The objective was to analyze the effects of adding anthocyanin delphinidin-3-O-sambubioside and cyanidin-3-O-sambubioside of Hibiscus sabdariffa L. in animal diets. Scientific articles published before 2021 in clinics, pharmacology, nutrition, and animal production were included. The grains/concentrate, metabolic exigency, and caloric stress contribute to increasing the reactive oxygen species (ROS); the excess of ROS unbalance the oxidants and antioxidants. Cyanidin-3-O-sambubioside and delphinidin-3-O-sambubioside have antioxidant, antibacterial, antiviral, and anthelmintic activities. In the rumen, anthocyanin might show interactions and/or synergisms with substrates, microorganisms, and enzymes which could reduce the fiber degradability, but increase the potential methane (CH4) emissions; since anthocyanin interferes in the biohydrogenation of fats, they increase the fat milk and meat quality. Anthocyanins reduce plasma oxidation and deposit in tissues, increasing the milk and meat antioxidant activities. Cyanidin-3-O-sambubioside and delphinidin-3-O-sambubioside act as inhibitors of the angiotensin-converting enzyme (ACEi) and rennin expression which may improve milk yield (there is not enough evidence in ruminants, though). Polyphenols affect the reproductive potential. Sub products of HS contain as many amounts of polyphenols as calyces, and their inclusion in diets would positively affect the average daily gain and fat meat quality. Including HS in ruminant diets can improve the meat and milk quality.

To safeguard against meat supply shortages during pandemics or other catastrophes, this study analyzed the potential to provide the average household’s entire protein consumption using either soybean production or distributed meat production at the household level in the U.S. with: 1) pasture-fed rabbits, 2) pellet and hay-fed rabbits, or 3) pellet-fed chickens. Only using the average backyard resources, soybean cultivation can provide 80%-160% of household protein and 0%-50% of a household’s protein needs can be provided by pasture-fed rabbits using only the yard grass as feed. If external supplementation of feed is available, raising 52 chickens while also harvesting the concomitant eggs or alternately 107 grain-fed rabbits can meet 100% of an average household’s protein requirements. These results show that resilience to future pandemics and challenges associated with growing meat demands can be incrementally addressed through backyard distributed protein production. Backyard production of chicken meat, eggs, and rabbit meat reduces environmental costs of protein due to savings in production, transportation, and refrigeration of meat products and even more so with soybeans. Generally, distributed production of protein was found to be economically competitive with centralized production of meat if distributed labor costs were ignored.

Low-cost miniature hyperspectral and thermal cameras onboard lightweight unmanned aerial vehicles (UAV) bring new opportunities for monitoring land surface variables at unprecedented fine spatial resolution with acceptable accuracy. This research applies hyperspectral and thermal imagery from a drone to quantify upland rice growth and water use efficiency (WUE) after biochar application in a Costa Rican dry region. The field flights were conducted over two experimental groups with bamboo biochar and sugarcane biochar amendments and one control group without biochar application. Rice canopy biophysical variables were estimated by inversion of a canopy radiative transfer model on hyperspectral reflectance. Variations in gross primary production (GPP) and WUE across treatments were estimated from the normalized difference vegetation index (NDVI), canopy chlorophyll content (CCC), and evapotranspiration. We found that GPP was increased by 41.9±3.4 % when using bamboo biochar and 17.5±3.4 % when using sugarcane biochar, which was probably due to higher soil moisture in the biochar-amended plots and led to significantly higher WUE by 40.8±3.5 % in bamboo biochar and 13.4±3.5 % in sugarcane biochar. This study demonstrated the use of hyperspectral and thermal imagery from drone to provide indicators for quantifying biochar effects on tropical dry cropland by integrating with ground point samples and physical models.

Proper treatment of infectious air could potentially mitigate the spread of airborne viruses such as porcine reproductive and respiratory syndrome virus (PRRSV). The objective of this research is to test the effectiveness of ultraviolet (UV) in inactivating aerosolized PRRSV, specifically, four UV lamps, UV-A (365 nm, both fluorescent and LED-based), "excimer" UV-C (222 nm), and germicidal UV-C (254 nm), were tested. The two UV-C lamps effectively irradiated fast-moving PRRSV aerosols with short treatment times (<2 s). One-stage and two-stage UV inactivation models estimated the UV doses needed for target percentage (%) reductions on PRRSV titer. UV-C (254 nm) dose needed for 3-log (99.9%) reduction was 0.521 and 0.0943 mJ/cm2, respectively, based on one-stage and two-stage models. An order of magnitude lower UV-C (222 nm) doses were needed for a 3-log reduction, i.e., 0.0882 and 0.048 mJ/cm2, based on one-stage and two-stage models, respectively. However, the cost of 222-nm excimer lamps is still economically prohibitive for scaling-up trials. The UV-A (365 nm) lamps could not reduce PRRSV titers for tested doses up to 4.11 mJ/cm2. Pilot-scale or farm-scale testing of UV-C on PRRSV aerosols simulating barn ventilation rates are recommended based on its effectiveness and reasonable costs comparable to HEPA filtration.

Porcine reproductive and respiratory syndrome virus (PRRSV) infections cause significant economic losses to swine producers every year. Aerosols containing infectious PRRSV are an important route of transmission, and proper treatment of air could mitigate the airborne spread of the virus within and between barns. Previous bioaerosol studies focused on the microbiology of PRRSV aerosols; thus, the current study addressed the engineering aspects of virus aerosolization and collection. Specific objectives were to (1) build and test a virus aerosolization system, (2) achieve a uniform and repeatable aerosol generation and collection throughout all replicates, (3) identify and minimize sources of variation, (4) verify that the collection system (impingers) performed similarly. The system for virus aerosolization was built and tested (Obj. 1). The uniform airflow distribution was confirmed using a physical tracer (<12% relative standard deviation) for all treatments and sound engineering control of flow rates (Obj. 2). Theoretical uncertainty analyses and mass balance calculations showed <3% loss of air mass flow rate between the inlet and outlet (Obj. 3). A comparison of TCID₅₀ values among impinger fluids showed no statistical difference between any two of the three trials (p-value = 0.148, 0.357, 0.846) (Obj. 4). These results showed that the readiness of the system for research on virus aerosolization and treatment (e.g., by ultraviolet light), as well as its potential use for research on other types of airborne pathogens and their mitigation on a laboratory scale.