Tryptophan is an essential nutrient required to produce niacin (vitamin B3), which is needed for energy metabolism and DNA production. Alterations in tryptophan metabolism could have significant effects on aging and musculoskeletal health. The kynurenine pathway, the main catabolic route of tryptophan, is modulated by inflammatory factors, which are increased in older persons, a process known as inflammaging. Osteoporosis, sarcopenia, osteosarcopenia and frailty have also been linked with chronic increased levels of inflammatory factors. Due to the disruption of the kynurenine pathway by chronic inflammation and/or changes in the gut microbiota, serum levels of toxic kynurenines are increased and have been associated with osteoporosis, sarcopenia and frailty. In contrast, anabolic end products of this pathway, such as picolinic acid, have demonstrated a beneficial effect on bone and muscle. In addition, recent studies have shown that physical activity can modulate this pathway by promoting the secretion of anabolic kynurenines. According to the evidence collected, kynurenines could have a promising role as biomarkers for osteoporosis sarcopenia, osteosarcopenia and frailty in older persons. In addition, some of these metabolites could become important targets for developing new pharmacological treatments for these conditions.

Daniel Yergin’s “The New Map: Energy, Climate, and the Clash of Nations” is a remarkable and groundbreaking work that addresses the ever-changing global energy landscape and its profound geopolitical implications. In this modest book review, we aim to offer a fresh perspective by re-examining the core issues from the standpoint of political geography. The aim of this article is twofold: to enrich the existing literature on political geography and to provide valuable insights to students of geography to broaden their knowledge in this field.

This work presents the results of a computational study of the chemical reactivity and bioactivity properties of the members of the Theopapuamides A-D family of marine peptides by making use of our own proposed methodology named Computational Peptidology (CP) that has been successfully considered in previous studies of this kind of molecular systems. CP allowed for the determination of the global and local descriptors that come from Conceptual Density Functional Theory (CDFT) that can give an idea of the chemical reactivity properties of the marine natural products under study which are already known to be related to their bioactivity. At the same time, the validity of the procedure based on the adoption of the KID (Koopmans in DFT) technique as well as the MN12SX/Def2TZVP/H2O model chemistry has been successfully verified. Together with several Chemoinformatic tools that can be used for the improvement of process of Virtual Screening, some additional properties of these marine peptides were identified related to their ability to behave as useful drugs. With the further object of analyzing their bioactivity some parameters of usefulness for future QSAR studies, their predicted biological targets and the the ADMET (Absorption, Distribution, Metabolism, Excretion and Toxicity) parameters related to the Theopapuamides A-D pharmacokinetics are also reported.

The storm 'Daniel' has caused the most severe flood phenomenon that Greece has ever experienced, with thousands of hectares of farmland submerged for days. This led to sediment deposition in the inundated areas, which significantly altered the chemical properties of the soil, as revealed by extensive soil sampling and laboratory analysis. Causal relationships between soil chemical properties and sediment deposition were extracted using the DirectLiNGAM algorithm. Results of causality analysis showed that the sediment deposition affected the CaCO3 concentration in the soil. Also, causal relationships were identified between CaCO3 and available phosphorus (P-Olsen), as well as between sediment deposit depth and available manganese. The quantified relationships between the soil variables were then used to generate data using a Multiple Linear Perceptron (MLP) regressor for various levels of deposit depth (0, 5, 10, 15, 20, 25 and 30 cm). Then linear regression equations were fitted across the different levels of deposit depth to determine the effect of deposit depth on CaCO3, P, and Mn. The results show that there is a linear slope of 0.12, -0.16, and 0.13, for CaCO3, P, and Mn with deposit depth, respectively. Statistical analysis indicates that corn growing in soils with sediment over 10 cm requires a 31.8% increase in P rate to prevent yield decline. Additional notifications regarding cropping strategies in the near future are also discussed.

Neural networks require a large quantity of training spectra and detector responses in order to learn to solve the inverse problem of neutron spectrum unfolding. In addition, due to the under-determined nature of unfolding, non-physical spectra which would not be encountered in usage should not be included in the training set. While physically realistic training spectra are commonly determined experimentally or generated through Monte Carlo simulation, this can become prohibitively expensive when considering the quantity of spectra needed to effectively train an unfolding network. In this paper, we present three algorithms for the generation of large quantities of realistic and physically motivated neutron energy spectra. Using an IAEA compendium of 251 spectra, we compare the unfolding performance of neural networks trained on spectra from these algorithms, when unfolding real-world spectra, to two baselines. We also investigate general methods for evaluating the performance of and optimizing feature engineering algorithms.

A methodology based on the concepts that arise from Density Functional Theory named Conceptual Density Functional Theory (CDFT) was chosen for the calculation of some global and local reactivity descriptors of the Discodermins A-H family of marine peptides through the consideration of the KID (Koopmans in DFT) technique that was successfully used in previous studies of this kind of molecular systems. The determination of active sites of the studied molecules for different kind of reactivities was achieved by resorting to some CDFT-based descriptors like the Fukui functions as well as the Parr functions derived from Molecular Electron Density Theory (MEDT). A few properties identified with their ability to behave as a drug and the bioactivity of the peptides considered in this examination were acquired by depending on a homology model by studying the correlation with the known bioactivity of related molecules in their interaction with various biological receptors. With the further object of analyzing their bioactivity some parameters of usefulness for future QSAR studies, their predicted biological targets and the the ADME (Absorption, Distribution, Metabolism, and Excretion) parameters related to the Discodermins A-H pharmacokinetics are also reported.

This paper presents a novel approach for indoor acoustic source localization using microphone arrays and based on a Convolutional Neural Network (CNN). The proposed solution is, to the best of our knowledge, the first published work in which the CNN is designed to directly estimate the three dimensional position of an acoustic source, using the raw audio signal as the input information avoiding the use of hand crafted audio features. Given the limited amount of available localization data, we propose in this paper a training strategy based on two steps. We first train our network using semi-synthetic data, generated from close talk speech recordings, and where we simulate the time delays and distortion suffered in the signal that propagates from the source to the array of microphones. We then fine tune this network using a small amount of real data. Our experimental results show that this strategy is able to produce networks that significantly improve existing localization methods based on SRP-PHAT strategies. In addition, our experiments show that our CNN method exhibits better resistance against varying gender of the speaker and different window sizes compared with the other methods.

The global textile sector, pivotal to economic development, significantly contributes to environmental degradation, prompting a shift towards sustainable raw material sources. Embracing circular economy principles, this industry is exploring the valorization of agricultural by-products. This study introduces an innovative approach to repurposing mango waste into valuable textile fibers, a byproduct of the fruit processing industry, predominantly generated during juice and jam production. The focus is on the lignocellulosic constituents of mango waste, specifically the peel, seed, and fibrous material, traditionally considered as refuse. Previous research has predominantly utilized mango peel in pectin extraction for food applications, whereas the potential of seed and fibrous content remains underexplored. This investigation endeavors to transform these fibrous by-products into high-value materials suitable for textile manufacturing. The process involved washing, drying, and comprehensive physicochemical characterization of mango fibers, emphasizing lignin quantification, revealing a composition of 12.2% lignin. An experimental design was employed to elucidate the impact of variables such as liquid-to-solid ratio, reaction duration, and sodium hydroxide concentration on lignin dissolution through alkaline hydrolysis. Optimal conditions—10% NaOH concentration, 30 mL/g liquid-to-solid ratio over six hours—achieved an 83% reduction in lignin content. The resulting fibers exhibited properties akin to conventional natural fibers, including a favorable aspect ratio indicative of their suitability for textile applications. A subsequent softening process using propylene glycol enhanced the fibers' spinability, producing a durable, textured fabric ideal for eco-conscious fashion applications, including bags, footwear, and accessories. This research demonstrates the feasibility of converting mango waste into a textile-worthy material and underscores the importance of waste revalorization in promoting sustainability within the circular economy framework.

This research elucidates the dynamic expression of expansin genes during the wheat grain (Triticum aestivum L.) development process using comprehensive meta-analysis and experimental validation. We leveraged RNA-seq data from multiple public databases, applying stringent criteria for selection, and identified 60,852 differentially expressed genes across developmental stages. From this pool, 28,558 DEGs were found to exhibit significant temporal regulation in at least two different datasets, and were enriched for processes integral to grain development such as carbohydrate metabolism and cell wall organization. Notably, 30% of the 241 known expansin genes showed differential expression during grain growth. Hierarchical clustering and expression level analysis revealed temporal regulation and distinct contributions of expansin subfamilies during the early stages of grain development. Further analysis using co-expression networks underscored the significance of expansin genes, revealing their substantial co-expression with genes involved in cell wall modification. Finally, qPCR validation and grain morphological analysis under field conditions indicated a significant negative correlation between expression of select expansin genes and grain size and weight. This study illuminates the potential role of expansin genes in wheat grain development and provides new avenues for targeted genetic improvements in wheat.

The anthropogenic deterioration of aquatic ecosystems affects water resources due to agricultural malpractices, pollution from domestic septic tanks, recreational activities, and poor watershed management, among others. This study examines the management of Las Curias Reservoir (176,974 m2), San Juan, Puerto Rico, post the 2016 arrival of the invasive aquatic fern Salvinia molesta. In December 2019, a community-led initiative introduced the Cyrtobagous salviniae weevil, an effective biological control agent for S. molesta, and commenced a mechanical removal campaign using an aquatic harvester. Limnological sampling (September 2019 to March 2022) and drone flights were employed to measure physicochemical and floating plant cover changes, respectively, in the reservoir. Monitoring of weevils in the reservoir demonstrated a rapid establishment and dispersal, which resulted in visible damage including browning of plants and eventually sinking of entire mats. By January 29, 2021, 71% (125,652 m2) of the reservoir surface was covered by salvinia. In 2022, the reservoir recorded an average dissolved oxygen concentration of 2.38 mg/L -1 (± 0.021, n = 144), the highest in the study period and indicative of ecosystem recovery. After three years of control efforts, dissolved oxygen, pH, and specific conductance returned to levels recorded prior to Salvinia molesta introduction. This ecosystem recovery, a first in Puerto Rico, could be attributed to an early use of mechanical control and a long-term impact of biological control.

In recent years, many libraries and archives have started digitizing their collections thus making maps by Indigenous peoples more easily available for scholars to study. While a number of these maps were discussed by G. Malcolm Lewis in the History of Cartography series (volume 2, book 3, Chapter 4: 1984), more have since been found and disseminated. These maps are critical in understanding the historic and current land tenure of Indigenous groups. Further, Indigenous claims to land can be seen in their connections via toponymy. European concepts of territory and political boundaries did not coincide with First Nation/American Indian views resulting in the mistaken view that Natives did not have formal concepts of their territories. Further, Tribes/First Nations with cross-border territory have special jurisdictional problems. This paper will illustrate how many Native residents were very spatially cognizant of their own lands, as well as neighboring nations’ lands, overlaps between groups, hunting territories, populations, and trade networks. Currently, the Sinixt First Nation provides a perfect example of how an Aboriginal people are inputting and using a GIS representation of their territory with proper toponymy and use areas.

In recent years, novel food is becoming an emerging trend increasingly more demanding in developed countries. Food proteins from vegetables (pulses, legumes, cereals), fungi, bacteria and insects are being researched to introduce them in meat alternatives, beverages, baked products and others. One of the most complex challenges for introducing novel foods on the market is to assure food safety. New alimentary scenarios drive the detection of novel allergens that need to be identified and quantified with the aim of appropriate labelling. Allergenic reactions are mostly caused by proteins of great abundance in foods, most frequently of small molecular mass, glycosylated, water-soluble and with high stability to proteolysis. The most relevant plant and animal food allergens such as lipid transfer proteins, profilins, seed storage proteins, lactoglobulins, caseins, tropomyosins and parvalbumins from fruits, vegetables, nuts, milk, eggs, shellfish, and fish have been investigated. New methods for massive screening in the search of potential allergens must be developed particularly concerning protein databases and other online tools. Moreover, several bioinformatic tools based on sequence alignment, motif identification or 3-D structure predictions should be implemented as well. Finally, targeted proteomics will become a powerful technology for the quantification of these hazardous proteins. The ultimate objective is to build an effective and resilient surveillance network with this cutting-edge technology.

Decapod crustaceans are a very diverse group and have evolved to suit a wide variety of diets. Alpha-amylases enzymes, responsible for starch and glycogen digestion, have been more thoroughly studies in herbivore and omnivore than in carnivorous species. We used information on the α-amylase of a carnivorous lobster as a connecting thread to provide a more comprehensive view of α-amylases across decapods crustaceans. Omnivorous crustaceans such as shrimps, crabs and crayfish present relatively high amylase activity respect to carnivorous. Yet, contradictory results have been obtained and relatively high activity in some carnivores has been suggested to be a remnant trait from ancestor species. Here we provided information sustaining that high enzyme sequence and overall architecture conservation do not allow high changes in activity, and that differences among species may be more related to number of genes and isoforms, as well as transcriptional and secretion regulation. However, recent evolutionary analyses revealed that positive selection might have also occurred among distant lineages with feeding habits as a selection force. Some biochemical features of decapod α-amylases can be related with habitat or gut conditions, while less clear patterns are observed for other enzyme properties. Likewise, while molt cycle variations in α-amylase activity are rather similar among species, clear relationships between activity and diet shifts through development cannot be always observed. Regarding the adaptation of α-amylase to diet, juveniles seem to exhibit more flexibility than larvae, and it has been described variation in α-amylase activity or number of isoforms due to the source of carbohydrate and its level in diets, especially in omnivore species. In the carnivorous lobster, however, no influence of the type of carbohydrate could be observed. Also, lobsters were not able to fine-regulate α-amylase gene expression in spite of large changes in carbohydrate content of diet, while retaining some capacity to adapt α-amylase activity to very low carbohydrate content in the diets. In this review, we raised arguments for the need of more studies on the α-amylases of less studied decapods groups, including carnivorous species which rely more on dietary protein and lipids, to broad our view of α-amylase in decapods crustaceans.

The aim of this work was to classify the business incubators in Spain according to the four phases of startups incubation. Taking into account that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis have been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors, finally the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3 called activity monitoring and control and was related to phase 3 or basic incubation variables. Clusters analysis facilitates the grouping of incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small Business Incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factor 1 and 2. Factor 3 although positive is susceptible to improvement. They are the largest incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

CYP1B1 loss-of-function (LoF) is the main known genetic alteration present in recessive primary congenital glaucoma (PCG), an infrequent disease characterized by delayed embryonic development of the ocular iridocorneal angle and caused by poorly understood molecular mechanisms. To model CYP1B1 LoF underlying PCG, we developed a cyp1b1 knockout (KO) zebrafish line using CRISPR/Cas9 genome editing. This line carries the c.535_667del frameshift mutation that results in a 72% mRNA reduction with residual mRNA predicted to produce an inactive truncated protein (p.(His179Glyfs*6)). Craniofacial defects and jaw maldevelopment were observed in 23% of somatic mosaic F0 crispant larvae (144 hpf). These early phenotypes were not detected in KO F3 larvae (144 hpf) but 27% of adult fishes (4 months) showed uni or bilateral craniofacial alterations, indicating the existence of incomplete penetrance and variable expressivity. These phenotypes increased to 86% in the adult offspring of inbred progenitors with craniofacial defects. No glaucoma-related phenotypes were observed in the cyp1b1 mutants. Transcriptomic analyses of the offspring (7dpf) of KO cyp1b1 progenitors with adult-onset craniofacial defects revealed that differentially expressed genes were functionally enriched in groups related with extracellular matrix and cell adhesion, cell growth and proliferation, lipid metabolism (retinoids, steroids, and fatty acids, and oxidation-reduction processes which included several cytochrome P450 genes) and inflammation. In summary, this study shows the complexity of phenotypes and molecular pathways associated with cyp1b1 LoF, with species-dependency, and provides evidence for dysregulation of extracellular matrix gene expression as one of the mechanisms underlaying pathogenicity associated with cyp1b1 disruption.

In polymer-based dental composites, wear is a three-body wear system mainly abrasive, because of the food particles and wear products suspended in the oral cavity, which are transferred to the microcavities of the surface of the replacements. Due to this fact, the incorporation of nanodiamond as reinforcement in these polymer matrix composites, which promotes the creation of a solid lubricant tribofilm surface could be advantageous. When nanodiamond is added in contents of 0.8, 1.6 and 3.2 wt %, an increase in microhardness from 95 up to 420 %, compared to the one of neat BisGMA/TEGDMA, is observed. Additionally, the incorporation of a content of 1.6 wt % is enough to cause a diminution of ~78 % in the friction coefficient and a reduction of the specific wear rate and Archard’s coefficient of ~50 %. Nevertheless, the addition of relatively high contents reduces the effectiveness of photoinitiation and UV-curing, which is related to the scattering and absorption of UV radiation by ND.

This work shows the potential of a new way of co-treatment of domestic wastewater (DWW) and a liquid stream coming from the thermal hydrolysis of the organic fraction of municipal solid waste (OFMSW) mediated by a mixed culture of purple phototrophic bacteria (PPB) capable of assimilating carbon and nutrients from the medium. The biological system is an open single-step process operated under microaerophilic conditions at an oxidative reduction potential (ORP) < 0 mV with a photoperiod of 12/24 h and fed during the light Stage only, so the results can be extrapolated to outdoors open ponds operation by monitoring the ORP. The effluent mostly complies with the discharge values of the Spanish legislation in COD and P values (<125mg/L <2 mg/L), respectively, and punctually on values in N (<15mg/L). Applying an HRT of 3 d and a ratio of 100:7 (COD:N), the presence of PPB in the mixed culture surpassed 50% of 16S rRNA gene copies, removing 78% of COD, 53% of N and 66% of P. Furthermore, increasing the HRT to 5 d, removal efficiencies of 83% of COD, 65% of N and 91% of P were achieved. In addition, the reactors were further operated in a membrane bioreactor, thus separating the HRT from the SRT to increase the specific loading rate. Very satisfactory removal efficiencies were achieved by applying HRT and SRT of 2.3 and 3 d, respectively: 84% of COD, 49% of N and 93% of P despite low presence of PPB due to more oxidative conditions, which anyway step-by-step re-colonized the mixed culture until reaching >20% of 16S rRNA gene copies after 49 d of operation. These results open the door to scale up the process in open photobioreactors capable of treating urban wastewater and municipal solid waste in a single stage and under microaerophilic conditions by controlling the ORP of the system. This novel urban biorefinery allows reducing treatment costs of two urban wastes and embed them in the circular bioeconomy through water recycling and valorizing PPB biomass as a source of carbon, nitrogen and phosphorus.

Confined masonry (CM) is a construction system which consists of masonry wall panels enclosed by vertical and horizontal reinforced concrete confining elements. The presence of these confining elements distinguishes CM from unreinforced masonry system and makes this technology suitable for construction of structures in regions subjected to intense seismic or wind actions. CM construction has been used in many countries and regions, and has performed well in past earthquakes. The purpose of the paper is to review past research studies related to the seismic in-plane and out-of-plane behaviour of CM structures. The authors have identified the key design and construction parameters which were considered in past research studies and have performed statistical analyses to establish their influence on the seismic performance of CM buildings. For the purpose of this study the authors have compiled databases of previous experimental studies on CM wall specimens which were used for statistical analyses. Finally, the paper discusses research gaps and needs for future research studies which would contribute to the understanding of seismic behaviour and failure mechanisms of CM walls.

Background Aspergillus spp. is a widely distributed filamentous fungus in the environment due to its high sporulation capacity. Currently, invasive aspergillosis (IA) is the most common invasive fungal infection in patients with hematologic malignancies with high rates of mortality and morbidity. The multifactorial nature of the disease requires appropriate risk stratification to allow the most appropriate preventive measures to be adapted and implemented according to the characteristics of the patient. In this sense, the present research aims to identify recent risk factors and environmental control measures against invasive aspergillosis to establish preventive actions to reduce the incidence of invasive aspergillosis in hospitals; (2) Methods: We conducted a qualitative systematic review of the scientific literature on environmental risk factors and preventive measures for invasive aspergillosis in patients with hematological malignancies. The Medline, Cochrane and Scopus databases were consulted, following the PRISMA and STROBE guidelines; (3) Results Adequate implementation of environmental control measures is presented as the most efficient intervention in terms of prevention to decrease the incidence of invasive aspergillosis in hospitals. We identify neutropenia, fungal contamination, lack of adequate environmental control measures in hospitals and patients´ homes, duration of hospitalization, and anemia as independent risk factors. We show that HEPA, LAF and Plasmair® systems are suitable methods to reduce the concentration of airborne fungal spores. Antifungal prophylaxis did not influence the reduction of IA significantly in our study; (4) Conclusions: Proper professional training and environmental control measures in hospitals are essential for the prevention of invasive aspergillosis. We should optimize risk stratification for patients with hematologic malignancies. Antifungal prophylaxis should be complementary to environmental control measures and should never be substituted for these last ones. Studies should also be done to evaluate the efficiency of environmental control measures against IA at patients' homes.

During the 16th and 17th centuries, Latin American cities adopted earthen construction techniques from European colonizers. As a result, rammed earth (RE) buildings now occupy an important place in Latin America's cultural heritage. However, earthquakes around the world have shown that unreinforced earthen constructions are highly vulnerable. For several years, researchers in northern South America have been proposing a technique that consists of installing confining steel plates (or wooden elements) on both sides of the RE walls forming a grid. This system has shown excellent performance in controlling seismic damage and increasing strength and ductility capacity. Although researchers have tested full-scale one- and two-story earthen walls under pseudo-static loading in the laboratory, and one- and two-story earthen walls at 1:1 and 1:2 scale on uniaxial and biaxial shaking tables, the behavior of a complete reinforced module (one- or two-story) on a shaking table has never been assessed. The present study presents the results of shaking table tests performed on two-story RE modules at 1:4 scale. The experimental data indicate that the retrofit system with confining steel strips was effective in reducing the seismic damage of earthen constructions. In addition, the comparison of the results of the 1:4 scale tests with the 1:2 and 1:1 scale tests previously conducted by the researchers, shows that the acceleration levels of the equivalent prototypes are in the same order of magnitude for the three scales.

Technology has transformed aeroponics, providing numerous advantages over traditional soil-based agriculture. However, there remains a need for comprehensive information on the types of technology employed in aeroponics and their impact on the growing process. This paper presents a literature review of 47 studies published between 2012 and 2023 in peer-reviewed journals and conference proceedings. As a result, it identifies the status and tendencies in the usage of technology in aeroponics as well as the main opportunities and challenges. Furthermore, this paper introduces the Technology Adoption and Integration in Sustainable Agriculture (TAISA) model. TAISA is a model that identifies the degree of technology integration in any sustainable agriculture system to determine how technology affects production and quality. Overall, the systematic review suggests that technology can play a vital role in improving the efficiency and sustainability of aeroponic farming. However, careful consideration must be given to the costs and technical requirements associated with using these technologies. Moreover, the TAISA model reveals that technology has primarily been employed in creating new processes that are not possible to implement without the help of technology. Therefore, we conclude that technology use has taken root in aeroponics and can be promoted to improve sustainable agriculture.

Digital twins are an emerging technology that could be harnessed for the digitalization of the industry. Steel industry systems contain a large number of electro-hydraulic components, as proportional valves. An input-output model for a novel water proportional cartridge valve is derived from physical modelling based on fluid mechanics, dynamics, and electrical principles. The valve is a two-stage valve with two 2/2-way water proportional valves as the pilot stage and a marginally stable poppet-type cartridge valve as the main valve. The orifice equation, which is based on Bernoulli principles, is approximated by a polynomial which makes parameter estimation easier and makes modelling possible without measuring pressure of the varying control volume situated in the pilot stage part of the valve. Data were collected when the valve was operating as a component in a closed-loop system as part of a press-mill machine in a steel manufacturing plant. Parameter estimation was made by convex optimization with physical constraints to overcome problems caused by poor system excitation. For comparison, a simple linear model was derived and the least squares method used for parameter estimation. A thorough estimation of the parameters relative errors is presented. The model contains 5 parameters related to the design parameters of the valve. The modelled position output is in good agreement with experimental data for training and test data. The model can be used for real time monitoring of the valve’s status by the model parameters. One of the model parameters varies linearly with production cycles. Thus, aging of the valve can be monitored.

This article presents a combined route and path planning strategy to guide Skid-Steer Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with complex terrain conditions. The proposed strategy integrates: i) a global planning algorithm based on the Traveling Salesman Problem under the Capacitated Vehicle Routing approach and Optimization Routing (OR-tools from Google) to prioritize harvesting positions by minimum path length, unexplored harvest points, and vehicle payload capacity, and ii) a local planning strategy using Informed Rapidly-exploring Random Tree (IRRT*) to coordinate scheduled harvesting points while avoiding low-traction terrain obstacles. The global approach generates an ordered queue of harvesting locations, maximizing the crop yield in a workspace map. In the second stage, the IRRT* planner avoids potential obstacles, including farm layout and slippery terrain. The path planning scheme incorporates a traversability model and a motion model of SSMRs to meet kinematic constraints. Experimental results in a generic fruit orchard demonstrated the effectiveness of the proposed strategy. In particular, the IRRT* algorithm outperformed RRT and RRT* with 96.1% and 97.6% smoother paths, respectively. The IRRT* also showed improved navigation efficiency, avoiding obstacles and slippage zones, making it suitable for precision agriculture.

In this paper we address one of the most important topics in the field of Social Networks Analysis: the community detection problem with additional information. That additional information is modeled by a fuzzy measure that represents the possibility of polarization. Particularly, we are interested in dealing with the problem of taking into account the Polarization of nodes in the community detection problem. Adding this type of information to the community detection problem makes it more realistic, as a community is more probably to be defined if the corresponding elements are willing to maintain a peaceful dialogue. The polarization capacity is modeled by a fuzzy measure based on the JDJpol measure of polarization related to two poles. We also present an efficient algorithm for finding groups whose elements are no polarized. Hereafter, we work in a real case. It is a network obtained from Twitter, concerning the political position against the Spanish government taken by several influential users. We analyze how the partitions obtained change when some additional information related to how polarized that society is, is added to the problem.

A facilitative transport system exists on the blood brain barrier (BBB) that has been tacitly assumed to be a path for glutamate entry to brain. But glutamate is a non-essential amino acid whose brain content is much greater than plasma, and studies in vivo show that glutamate does not enter brain in material quantities except in those small regions with fenestrated capillaries (circumventricular organs). The situation became understandable when luminal (blood facing) and abluminal (brain facing) membranes were isolated and studied separately. Facilitative transport of glutamate and glutamine exist only on the luminal membranes whereas Na+-dependent transport systems for glutamate, glutamine and some other amino acids are present only on the abluminal membrane. The Na+-dependent cotransporters of the abluminal membrane are in a position to actively transport amino acids from the extracellular fluid (ECF) into the endothelial cells of the BBB. These powerful secondary active transporters couple the energy of the Na+-gradient to move glutamate and glutamine into the ECF whereupon glutamate can exit to blood on the luminal facilitative glutamate transporter. Glutamine may also exit brain on a separate facilitative transport system that exists on the luminal membranes or glutamine can be hydrolyzed to glutamate within the BBB thereby releasing ammonia that is freely diffusible. The γ-glutamyl participate cycle participates indirectly by producing oxoproline (pyroglutamate) that stimulates almost all secondary active transporters yet discovered in the abluminal membranes of the BBB.

Thiamethoxam is a neonicotinoid, with systemic and contact action, used in Mexico for the care of different traditional fruit crops, mainly in the cultivation of papaya. International organizations such as the EPA (Environmental Protection Agency) and the EFSA (European Food Safety Authority) establish maximum permissible limits of 0.4 mg/kg and 0.05 mg/kg of thiamethoxam in papaya. The aim of this study was to determine the presence and concentration of thiamethoxam in soil and water in papaya crops associated with watermelon from the central area of Veracruz, Mexico. A diagnosis of thiamethoxam management in different soil types of the region was made; through an experimental plot where soil and water samples were taken in the different stages of papaya cultivation associated with watermelon, using HPLC-UV equipment for its determination. The design was random blocks with six repetitions and the software used for data analysis was the Statistica 2007 program. Thiamethoxam was concentrated in amounts of ≥0.40 mg/L in 79% of the samples in water and ≥0.55 mg/kg in 75% of the samples in soil. The highest values of thiamethoxam in soil were in the stage of watermelon culture with 0.4 mg/kg and in the soil preparation of the papaya crop with concentrations of 0.8 mg/kg. Whereas irrigation water from the watermelon cultivation and the soil preparation for the papaya showed concentrations of 0.5 and 0.7 mg/L respectively. The presence of thiamethoxam was identified in 100% of the samples analyzed in the papaya soil preparation stage. The values of the concentrations in soil and irrigation water exceeded the maximum limits established by international standards.

'Cv 'Doña María' table grape is a high-quality table grape variety included in the Protected Designation of Origin (PDO) of the European Union "The bagged grape of the Vinalopó." The PDO stipulates that grape clusters must be protected with paper bags from inclement weather and insects, which helps enhance the final grape quality. However, 'Doña María' is a variety prone to high shattering in the late stages of ripening on the vine and during postharvest. Inorganic calcium treatments are one of the most commonly used tools to reduce this disorder, but the translocation of this mineral from veraison onward has been questioned. In this study, five applications were performed, from veraison to harvest, using sorbitol-chelated calcium (0.7 % + 1.0 %), Ca(NO3)2 (Ca) at 0.7% and sorbitol at 1%. It was observed that bagged grapes (not wetted with the solutions) only increased the concentration of total and bound calcium when treated with Sorbitol-Ca. This resulted in reduced berry drop during cultivation and postharvest and improved fruit firmness. Additionally, it reduced grape metabolism indicators such as respiration rate, weight loss, malic acid degradation, prevented abscisic acid (ABA) and malondialdehyde (MDA) accumulation, and favored the accumulation of secondary metabolites such as total polyphenols, increased antioxidant activity, and sugar content. The application of sorbitol-chelated calcium is an effective and safe tool that enhances fruit quality and prevents losses due to shattering during postharvest.

Today's city needs more than ever methodological devices that ensure a specific urbanism, in keeping with the complexity of relationships that occur in the urban space. Networks or systems of diverse nature must be activated to achieve a certain success of the city, even more so in its fragile central fabrics. The study is focused on the historic neighborhoods of the city of Jaén (Spain), which have a high vulnerability index. The aim is to establish a strategy to revitalize their urban and social capital and improve their articulation with the rest of the urban and territorial structure. A methodological proposal for the analysis of vulnerability factors and an urban and cartographic analysis of the public space is addressed through an interweaving of a triple network: environmental, social, and urban. For this purpose, the configuration of this overlapping network of analysis and formulation of criteria is presented, which considers the urban multiplicity and promotes new dynamics for the integrated urban regeneration of the area and for the activation of public and collective urban spaces.

The aim of this study was to evaluate patients' knowledge and perception of the use of systemic antibiotics in the treatment of endodontic infections and to determine the possible contribution of patients to the development of bacterial resistance. Five hundred and fifty patients were asked to respond to a survey on the perception of systemic antibiotic use in the treatment of endodontic infections and antibiotic resistance during January 2022 and March 2023. Data were analyzed using descriptive statistics and Pearson's Chi-square test. 514 patients were included in the study, 65.9% of whom were women. While 34.6% of the population studied thought that it was always necessary to take antibiotics prior to endodontics, 49.4% considered that they were necessary after endodontics, regardless of the clinical symptoms (p>0.05). The prevalence of self-medication was 17.3% and women self-medicate more than men, with significant differences (p<0.05), although they have greater knowledge of antibiotic resistance than men (p>0.05). Forty-four percent of the population expect to take antibiotics when faced with dental pain, mainly women (p<0.05). The general population is contributing to the serious problem of bacterial resistance. It is necessary to promote educational strategies focused on the correct use of antibiotics in the community.

In the present work, a predictive modelling and optimization with the adaptive network based fuzzy inference system(ANFIS) modelling of mechanical properties of laser-coated NB/SiC/Ni welds was studied based on Taguchi design by laser cladding. An ANFIS model based on a Sugeno type fuzzy inference system was developed for predicting the hardness properties of SiC/BN/Ni welds by laser cladding with experimental data required for network training and prediction. Based on analysis of variance, three important factors were taken as inputs for the fuzzy logic inferences, while the hardness properties was taken as the output of the ANFIS. The microstructure of welds were analysed using scanning electron microscopy with an energy dispersive X-Ray spectrometer. Highly developed leaf-like dendrites and eutectic crystals were found in some areas of the melting zone for the BN/SiC/Ni weld, which was significantly hardened. The ANFIS model based on Taguchi's design provides a better pattern of response because the predicted and experimental values were highly similar. As a result, a satisfactory result was achieved between the predicted and experimental values of hardness in laser-coated NB/SiC/Ni welds, whereby the success and validity of the method was verified.

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

This review article focuses on the role of Artificial Intelligence (AI) in transforming healthcare in Africa, specifically in combatting infectious diseases, neglected tropical diseases (NTDs), and antimicrobial resistance. We provide a comprehensive overview of the significance of AI in the healthcare industry, highlighting its urgency and importance in addressing these specific health challenges in Africa. We begin by discussing the role of AI in infectious disease surveillance and outbreak detection. We explore how AI technology can be employed for real-time tracking and prediction of outbreaks, providing examples of successful AI applications in infectious disease surveillance within the African context.Next, we examine the potential of AI-enabled diagnosis and treatment for faster and more accurate diagnoses of infectious diseases and NTDs. We highlight specific examples of AI applications in diagnosing and treating these diseases in Africa, showcasing the potential of AI to improve clinical outcomes and save lives.Furthermore, we focus on how AI-driven drug discovery and development can expedite the search for new treatments for infectious diseases and combat antimicrobial resistance. We present examples of AI applications in drug discovery within the African context, illustrating the potential for AI to revolutionize the development of effective therapeutics.In addition, we delve into how AI-powered public health interventions can enhance the design and implementation of targeted interventions. We explore how AI can optimize resource allocation and facilitate data-driven decision-making processes, providing examples of AI applications in public health in Africa.Finally, we address the challenges and limitations of implementing AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. We discuss potential barriers and ethical concerns surrounding AI applications in healthcare, aiming to encourage informed and responsible utilization of AI technologies.Overall, this review emphasizes the importance and potential of AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. It positions AI as a catalyst for revolutionizing healthcare in the region, leading to more effective disease surveillance, diagnosis, treatment, drug discovery, and public health interventions.

This preprint is focused in the presence of plastics and microplastics in food. We will discuss how many we eat, and how they arrive to the food, and why. We will treat many other things, such as the waste treatment in Europe and in Spain, with updated data; how much plastic waste is generated; what are microplastics and how they are analyzed, I will tell about the experience we have at the University of Alicante (UA); how they can be removed and we will estimate how many we eat over the course of a year.

Recurrent pregnancy loss (RPL) affects around 2 % of women of reproductive age. Primary RPL is defined by ≥2 pregnancy losses and no normal birth delivery. In secondary RPL, the losses are after a normal pregnancy and delivery. Most cases have no clear aetiology, although primary cases are the most complex. Several gene polymorphisms have been associated with RPL. Some polymorphisms are increased in women of Asian or Caucasian race. In admixed RPL populations, the information on possible genetic links is scarce and contradictory. The study aimed to assess the frequency of two SNP in different enzymes involved in medical conditions observed during pregnancy. Microsomal epoxy hydrolase (mEPH) is involved in detoxifying xenobiotics. It is present in ovaries, and it is hormonally regulated. The endothelial nitric oxide synthase forms nitric oxide from arginine and is involved in vascular tone. Two SNPs, rs1051740 and rs1799983, were assessed. The study included 26 controls and 63 primary RPL patients. Significant differences were observed in the frequencies of both SNP (p<0.05). The frequency of mutated alleles was higher in patients. Double mutated homozygotes were encountered only in RLP patients (p<0.05). Genetic polymorphisms rs1051740 and rs1799983 may be involved in primary RPL in the Venezuelan admix population. Genetic studies could provide crucial information on the aetiology of primary RPL.

Lead-acid batteries utilised in electrical substations release hydrogen and oxygen when these are charged. These gases could be dangerous and cause a risk of fire if they are not properly ventilated. Therefore, this research seeks to design and implement a network control panel for heating, ventilation, and air-conditioning systems (HVACS). This is done using a specific range of controllers, which have more than thirty loops of proportional, integral and derivative (PID) control to achieve a cost-effective design. It performs the required function of extracting hydrogen, oxygen, and maintaining the desired temperature of the battery storage room within the recommended limits (i.e. 25°C ±1°C tolerance) without compromising quality as set out in the user requirement specification in Appendix-A. The system control panel allows the user to access control parameters such as changing temperature set-points, fan-speed, sensor database amongst others. The hardware is configured to detect extreme hydrogen and oxygen gas content in the battery room and ensure that the HVACS extract the gas content to the outside environment. The results of the system show that the network control panel effectively operates as per the recommended system requirements. Therefore, the effective operation of the HVACS ensures sufficient gas ventilation, thus mitigating the risk of fire in a typical battery storage room. Furthermore, the effective operation of HVACS enhances battery lifespan because of regulated operating temperature, which is conducive to minimise the effect of sulfation in lead acid Batteries (LABs).

A construction for the systems of natural and real numbers is presented in Zermelo-Fraenkel Set Thoery, that allows for simple proofs of the properties of these systems, and practical and mathematical applications. A practical application is discussed, in the form of a Simple and Linear Fast Adder (Patent Pending). Applications to finite group theory and analysis are also presented. A method is illustrated for finding the automorphisms of any finite group $G$, which consists of defining a canonical block form for finite groups. Examples are given, to illustrate the procedure for finding all groups of $n$ elements along with their automorphisms. The canonical block form of the symmetry group $\Delta_4$ is provided along with its automorphisms. The construction of natural numbers is naturally generalized to provide a simple and sound construction of the continuum with order and addition properties, and where a real number is an infinite set of natural numbers. A basic outline of analysis is proposed with a fast derivative algorithm. Under this representation, a countable sequence of real numbers is represented by a single real number. Furthermore, an infinite $\infty\times\infty$ real-valued matrix is represented with a single real number. A real function is represented by a set of real numbers, and a countable sequence of real functions is also represented by a set of real numbers. In general, mathematical objects can be represented using the smallest possible data type and these representations are calculable. In the last section, mathematical objects of all types are well assigned to tree structures in a proposed type hierarchy.

In most industrialized countries, screening programs for cervical cancer have shifted from cytology (Pap smear or ThinPrep) alone on clinician-obtained samples to the addition of screening for human papillomavirus (HPV), its main causative agent. For HPV testing, self-sampling instead of clinician-sampling has proven to be equally accurate, in particular for assays that use nucleic acid amplification techniques. In addition, HPV testing of self-collected samples in combination with a follow-up Pap smear in case of a positive result is more effective in detecting precancerous lesions than a Pap smear alone. Self-sampling for HPV testing has already been adopted by some countries, while others have started trials to evaluate its incorporation into national cervical cancer screening programs. Self-sampling may result in more individuals willing to participate in cervical cancer screening, because it removes many of the barriers that prevent women, especially those in low socioeconomic and minority populations, from participating in regular screening programs. Several studies have shown that the majority of women who have been underscreened but who tested HPV-positive in a self-obtained sample, will visit a clinic for follow-up diagnosis and management. Additionally, a self-collected sample can also be used for vaginal microbiome analysis, which can provide additional information about HPV infection persistence as well as vaginal health in general.

Knowledge about the formation energies of compounds is essential to derive phase diagrams of multi-component phases with respect to elemental reservoirs. The determination of formation energies using common (semi-)local exchange-correlation approximations of density functional theory (DFT) exhibits well-known systematic errors if applied to oxide compounds containing transition metal elements. In this work, we generalize, reevaluate and discuss a set of approaches proposed and widely applied in the literature to correct for errors arising from the over-binding of the O2 molecule and from correlation effects of electrons in localized transition-metal orbitals. The DFT+U method is exemplarily applied to iron oxide compounds, and a procedure is presented to obtain U values, which lead to formation energies and electronic band gaps comparable to experimental values. Using such corrected formation energies, we derive the phase diagrams for LaFeO3, Li5FeO4 and NaFeO2, which are promising materials for energy conversion and storage devices. A scheme is presented to transform the variables of the phase diagrams from the chemical potentials of elemental phases to those of precursor compounds of a solid-state reaction, which represents the experimental synthesis process more appropriately. The discussed workflow of methods can directly be applied to other transition metal oxides.

G4v is a four-vector theory of gravitation proposed by Mead (2015, 2023a,b) which reinterprets several major results commonly celebrated for the tensor-based approach of General Relativity (GR). Here, we show that G4v obeys the correspondence principle, an important test of any relativistic theory. We derive the non-relativistic Lagrangian and Energy expressions at the limit of low speeds and potentials, complete with the correct terms for potential energy (something traditional Special Relativity is incapable of achieving). G4v could represent a new interpretation of the gravitational field with essentially the same mathematics as electromagnetism (Mead 2023a). It is also possible to interpret G4v as a very interesting (and useful) approximation of the Einstein field equations (Mead 2023b).

Air quality is a topic of growing relevance on the global agenda. Two key indicators of air quali-ty, nitrogen dioxide (NO2) and carbon monoxide (CO), represent significant hazards to human health and the environment putting the sustainability of natural resources at risk. Therefore, it is imperative to regularly monitor and reduce atmospheric pollutant concentrations to mitigate their harmful consequences. This study presents an analysis of NO2 total and CO emissions in Argentina, utilizing remote sensing data. The research aims to determine the spatiotemporal distribution of NO2 and CO emissions in Argentina from 2019 to 2021. Subsequently, it seeks to establish the influence of land uses and land cover on the emission of NO2 and CO through dif-ferent climatic, anthropic, and natural indicators. The study was carried out in Argentina during the period 2019-2021, where random points were placed for the different land covers with a total of 800 points surveyed. The year with the highest CO concentration (mol/m-2) was 2020. The values were highest for tree covers and herbaceous wetland coverage in the northern part of the country. For total NO2, the highest concentrations were reached during the years 2020 and 2021. Regarding its distribution, throughout the evaluated period, the highest concentrations of total NO2 were found in the built-up and cropland coverages, with the capital of the country and the northern region of the Buenos Aires province being the most affected areas. In addition, the concentration of CO was influenced by climatic variables (atmospheric pressure, wind speed, maximum environment temperature, Palmer index), natural (height, humidity, NDVI), and ur-ban variables (distances to mining extraction, airports, power plants, urban index) for the differ-ent uses and land covers. Finally, the concentrations of total NO2 were influenced by climatic variables (Palmer index and wind speed), natural (height and NDVI), and urban variables (dis-tance to airports, power plants, industries, service stations, and open dumpsites) for the differ-ent uses and land cover. This study contributes to sustainable environmental management, ena-bling the formulation of effective strategies for mitigating emissions and promoting the long-term health and well-being of communities.

Predictive numerical models in the study of ground-borne vibrations generated by railway sys-tems have traditionally relied on the segmented approach of subsystems. In this approach, loads are individually applied, and the cumulative effect of rolling stock is obtained through superposi-tion. While this method serves to mitigate computational costs, it may not fully capture the com-plex interactions involved in ground-borne vibrations. Recent advancements in computational and software tools have enabled the development of more sophisticated vibrational pollution models. These advanced models encompass the entire dynamic system, from the rolling stock to the terrain, allowing for continuous simulations with a defined time step. Furthermore, the incorporation of computational contact tools between various ele-ments not only ensures temporal accuracy but also extends the analysis to the frequency domain. This paper explores the evolution of predictive numerical models in the context of ground-borne vibrations generated by trains on ballasted tracks. It highlights the shift from segmented models to continuous simulations, demonstrating the progressive advancement towards more comprehen-sive and accurate representations of railway-induced and generated vibrations in the track sur-roundings as an additional way of evaluate sustainability of infrastructures. In particular, this development of a numerical model from its inception aimed to expand upon ex-isting emission - prediction models by enriching the data with frequency-domain information. This approach has been driven by the aspiration to bridge the gap between numerical predictions and measured signals, striving for a higher level of accuracy in our obtained results. This model can predict the impact of a high-speed rail (HSR) vehicle passing on its own track. It possesses sufficient information in both the time and frequency domains to precisely characterize vibrations. This initiative marks a pivotal advancement, enabling us to more effectively capture the intricacies of ground-borne vibrations and their impact on the surrounding environment due to a deeper comprehension of the occurrences in the frequency domain, there's a heightened ca-pability to accurately characterize vibrations.

This article is about school evaluation. The objective was to explain critically the mediating relationships between educational evaluation and the production of school knowledge from the perspective of the Dialectical Historical Materialism. With this interest, a documentary analysis was made, obtaining as result four explanatory categories: production, subsumption, distribution and exchange of knowledge, which form a concrete totality with distinctions and antagonistic relationships between them, limited by their opposite. It is concluded that the evaluation as a mediating form lacks antagonistic pair and consequently of control by opposition, emerging from the school daily as autonomous and sovereign entity, oppressive of school subjects.

Forest management aims to preserve ecosystem integrity, maintaining resilience thresholds. For this, conservation and invasion patterns must be determined in managed landscapes. The objective was to identify proxies (landscape and environmental patterns) that allowed the plant species invasion and define thresholds of human impacts to improve management practices. We also want to identify indicator species for the different kinds of impacts and environments. 165 plots were measured in Nothofagus antarctica forests and associated open-lands (dry and wet grasslands) in Tierra del Fuego (Argentina). We found differences in the studied variables across landscape and among different uses and impact types. Human impacts influenced over land types, emphasizing the importance of managing intensities. Indicator plant species allowed to identify potential ecological thresholds related to human impacts and the establishment of species linked to ecological and economic degradation, e.g. Bolax gummifera and Azorella trifurcata were associated with high grazing pressure in grasslands and fire in forested areas, while Rumex acetosella and Achillea millefolium, typically associated with forested areas, were related to high harvesting pressure and fire impacts. These findings contribute to understanding the long-term effects of some impacts, and allow us to define variables of monitoring and indicator species for each impact type.

In response to escalating global concerns regarding climate change, nations worldwide have been undertaking structural adjustments in their energy sectors to promote diversification and decarbonization. This study conducts a comparative analysis of the policies and measures adopted by major economies, including the United States, the United Kingdom, Japan, Germany, and France, focusing on climate change, energy structural adjustments, and carbon emission reduction. By analyzing recent carbon emission and highlighting achievements in renewable energy promotion, green industry development, industrial restructuring, and energy production decarbonization, this study aims to provide valuable insights and formulate strategies for constructing an innovative energy system that ensures economic and social development while facilitating rapid growth and wide applications of low-carbon energy sources.

Near-infrared spectroscopy (NIRS) has become a key modality in medical imaging, finding application in both brain and breast imaging. This paper discusses the current trends in NIRS for brain and breast imaging, exploring advances in multi-modal integration with modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Challenges related to spatial resolution, depth sensitivity, and the impact of extracerebral tissues on signal specificity are examined. In addition, ongoing efforts to enhance hemodynamic measurements’ quantitative accuracy. Challenges, including limited spatial resolution and tissue heterogeneity, are discussed. The discussion extends to diffuse optical tomography and ongoing instrumentation development, clinical trials and studies validating NIRS diagnostic efficacy in breast imaging. The paper emphasizes the need for standardization, integration into routine clinical practice, and motivates for future work.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

It is well established the complex exponential and logarithm are multivalued functions, both failing to maintain most identities originally valid over the positive integers domain. Moreover the general case of complex logarithm, with a complex base, is hardly mentionned in mathematic litterature. We study the exponentiation and logarithm as binary operations where all operands are complex. In a redefined complex number system using an extension of the C field, hereafter named E, we prove both operations always produce single value results and maintain the validity of identities such as log_u (w v) = log_u (w) + log_u (v) where u, v, w in E. There is a cost as some algebraic properties of the addition and subtraction will be diminished, though remaining valid to a certain extent. In order to handle formulas in a C and E dual number system, we introduce the notion of set precision and set truncation. We show complex numbers as defined in C are insufficiently precise to grasp all subtleties of some complex operations, as a result multivaluation, identity failures and, in specific cases, wrong results are obtained when computing exclusively in C. A geometric representation of the new complex number system is proposed, in which the complex plane appears as an orthogonal projection, and where the complex logarithm and exponentiation can be simply represented. Finally we attempt an algebraic formalization of E.

Serendipity favors the prepared mind, but how does the brain make that lucky find? Analyzing the cerebral mechanisms behind an exceptional (albeit trivial) discovery, the author suggests that a combination of ‘concept cells’ and the Global Neuronal Workspace Hypothesis could explain how we make great discoveries.

In recent years, advancements in brain science and neuroscience have significantly influenced the field of computer science, particularly in the domain of reinforcement learning (RL). Drawing insights from neurobiology and neuropsychology, researchers have leveraged these findings to develop novel mechanisms for understanding intelligent decision-making processes in the brain. Concurrently, the emergence of quantum computing has opened new frontiers in artificial intelligence, leading to the development of quantum machine learning (QML). This study introduces a novel model that integrates Quantum Spiking Neural Networks (QSNN) and Quantum Long Short-Term Memory (QLSTM) architectures, inspired by the complex workings of the human brain. Specifically designed for reinforcement learning tasks in energy-efficient environments, our approach progresses through two distinct stages mirroring sensory and memory systems. In the initial stage, analogous to the brain’s hypothalamus, low-level information is extracted to emulate sensory data processing patterns. Subsequently, resembling the hippocampus, this information is processed at a higher level, capturing and memorizing correlated patterns. We conduct a comparative analysis of our model against existing quantum models such as Quantum Neural Networks and their classical counterparts, elucidating its unique contributions. Through empirical results, we aim to underscore the effectiveness of our approach in optimizing energy consumption in practical scenarios.

The pursuit of Artificial Intelligence (AI) that emulates human cognitive processes is a cornerstone of ethical AI development, ensuring that emerging technologies can integrate seamlessly into societal frameworks requiring nuanced understanding and decision-making. Zero-Shot Instance Retrieval (ZSIR) stands at the forefront of this endeavour, potentially providing a robust platform for AI systems, particularly large visual language models, to demonstrate and refine cognition-aligned learning without the need for direct experience. In this paper, we critically evaluate current cognition alignment methodologies within traditional zero-shot learning paradigms, using visual attributes and word embedding generated by large AI models. We propose a unified similarity function that quantifies the cognitive alignment level, bridging the gap between AI processes and human-like understanding. Through extensive experimentation, our findings illustrate that this similarity function can effectively mirror the visual-semantic gap, steering the model towards enhanced performance in zero-shot instance retrieval. This work not only benchmarks the cognition alignment of AI, but also sets a new precedent for the development of visual language models attuned to the complexities of human cognition.}

The existence of the exclusion zone (EZ), a layer of water in which plastic microspheres are repelled from hydrophilic surfaces, has now been independently demonstrated by several groups. A better understanding of the mechanisms which generate EZs would help with understanding the possible importance of EZs in biology and in engineering applications such as filtration and microfluidics. Pollack theorizes that EZ water exists in a new phase which has a layered structure. We note several problems with Pollack's proposed structure, some of which were noted in the 1960's when a similar structure was proposed for ``polywater''. We argue that Schurr's diffusiophoresis based theory presents a compelling alternative explanation for the core EZ phenomena, although there remain other findings from Pollack's lab it does not explain. Among other things, Schurr's theory makes predictions about the growth of the EZ with time which have been confirmed by Florea et al.\ and others. In this work we also introduce and explore a novel hypothesis - that some aspects of EZ phenomena may be attributable to repulsive van der Waals forces. Finally, we touch on several possible confounding factors that make experimentation on EZs difficult, such as charged surface groups, dissolved solutes, and adsorbed nanobubbles.

The presence of Staphylococcus aureus in six dry-cured meat-processing facilities was investigated. S. aureus was detected in 3.8% of surfaces from five facilities. Prevalence was clearly higher during processing (4.8%) than after cleaning and disinfection (1.4%). Thirty eight isolates were typified by PFGE and MLST. Eleven sequence types (STs) were defined by MLST. ST30 (32%) and ST12 (24%), were the most abundant. Enterotoxin genes were detected in 53% of isolates. The enterotoxin A gene (sea) was present in all ST30 isolates, seb in one ST1 isolate and sec in two ST45 isolates. Sixteen isolates harbored the enterotoxin gene cluster (egc) with four variations in the sequence. The toxic shock syndrome toxin gene (tst) was detected in 82% of isolates. Regarding the antimicrobial resistance, twelve strains were susceptible to all the antibiotics tested (31.6%). However, 15.8% were resistant to three or more antimicrobials, and therefore multidrug-resistant. Our results showed that, in general, efficient cleaning and disinfection procedures were applied. Nonetheless, the presence of S. aureus with virulence determinants and resistance to antimicrobials, and particularly multidrug resistant MRSA ST398 strains might represent a potential health hazard for consumers, even though the pathogen was not isolated from final products.

This paper presents a novel micro-segmented genetic algorithm (μsGA) to identify the best solution for the locomotion of a quadruped robot designed on a rectangular ABS plastic platform. We compare our algorithm with three similar algorithms found in the specialized literature: a standard genetic algorithm (GA), a micro-genetic algorithm (μGA), and a micro artificial immune system (μAIS). The quadruped robot prototype guarantees the same conditions for each test. The platform was developed using 3D printing for the structure and can accommodate the mechanisms, sensors, servomechanisms as actuators. It also has an internal battery and a multicore embedded system (mES) to process and control the robot locomotion. This research proposes a μsGA that segments the individual into specific bytes. μGA techniques are applied to each segment to reduce the processing time; the same benefits as the GA are obtained, while the use of a computer and the high computational resources characteristic of the GA are avoided. This is the reason why some research in robot locomotion is limited to simulation. The results show that the performance of μsGA is better than the three other algorithms (GA, μGA and AIS). The processing time was reduced using a mES architecture that enables parallel processing, meaning that the requirements for resources and memory were reduced. This research solves the problem of continuous locomotion of a quadruped robot, and gives a feasible solution with real performance parameters using a μsGA bio-micro algorithm and a mES architecture.

Colorectal cancer is a common disease, both in Chile and worldwide. The most widely used chemotherapy schemes are based on 5-fluorouracil (5FU) as the foundational drug. Genetic polymorphisms have emerged as potential predictive biomarkers of response to chemotherapy, but conclusive evidence is lacking. Additionally, the interplay between hereditary variations and acquired mutations in the EGFR pathway remains unknown. This study aimed to investigate the role of genetic variants associated with 5FU-based chemotherapy on therapeutic effectiveness, considering their interaction with the EGFR pathway mutations. In a retrospective cohort of 63 patients diagnosed with metastatic colorectal cancer, a multivariate analysis revealed that liver metastases, DPYD, ABCB1 and MTHFR polymorphisms are independent indicators of a poor prognostic, irrespective of EGFR pathway mutations. BRAF V600E wild-type status and high-risk drug-metabolism polymorphisms correlated with a poor prognosis in this Chilean cohort. Additionally, findings from the genomics of drug sensitivity (GDSC) project demonstrated that cell lines with wild-type BRAF have higher IC50 values for 5-FU compared to BRAF-mutated cell lines. In conclusion, the genetic polymorphisms DPYD rs1801265, ABCB1 rs1045642 and MTHFR rs180113 may serve as useful biomarkers for predicting a poor prognosis in patients undergoing 5-fluorouracil chemotherapy, regardless of EGFR pathway mutations.

This article focuses on generating an alternative in order to identify traffic officers during driving. This research employed the latest You Only Look Once (YOLO) model, using a six-phase methodology: data collection, data preparation involving resizing and labeling, implementation of various filters to avoid overfitting, model training, prediction evaluation, and result interpretation. The YOLO model was applied across three iterations using a dataset of 1862 images. To enhance training efficiency and detection speed, the graphics processing unit (GPU) acceleration was utilized, further enhancing the experimental process. The results of this study revealed that the YOLOv8x variant produced the most promising results. This proposed model attained a remarkable F1 score of 0.95, bolstered by a confidence score of 0.631, with the potential for an increase to 0.80 in confidence without significantly compromising the F1-score. These findings are poised to make a substantial contribution to the broader research landscape, particularly in advancing the effectiveness of detection models for traffic officers.

The Golgi apparatus (GA) dysfunctions in Parkinson’s Disease (PD), neurodevelopmental disorders (NDDs), cancer, and organelle structural biology (OSB) can provide insights into therapeutic targets, gene therapy, and drug design. Primary defects and fragmentation within the GA are implicated in a wide range of neurodegenerative diseases. GA defects typically result in mislocation of proteins, accumulation of undegraded proteins, and impaired glycosylation of proteins. Inhibition of vesicular trafficking by α-synuclein (aSyn) may affect the dopamine-producing neurons and neuromodulators. GA regulates apoptosis during pathological mechanisms of neurological diseases and could provide new avenues in treatments through translation research. PD patients bearing the hereditary E46K disease mutation manifest the clinical picture of parkinsonism. How do we provide high resolution nanoimages of the GA during disease to capture dysfunction? Could we visualize the aSyn traffic jam between vesicles in the organelles ER and GA? OSB is emerging as a field as more technology advances and is more accessible. Structural studies of the GA will advance the field of neurological disease forward with an in depth understanding of dysfunction, fragmentation, and defects. Discoveries of the GA in PD, NDDs, and cancer would break new ground and provide translational medicine data of these diseases. Future research could be visualizing high angle annular dark field-STEM (HAADF-STEM) tomograms, cryogenic electron tomography (cryo-ET), multiplex correlative light and electron microscopy (cryo-CLEM), nanobody-assisted tissue immunostaining for volumetric EM (NATIVE) and using soft X-ray tomography (SXT) and computational reconstruction of the GA.

Multiple social and environmental justice concerns are linked to urban form such as the distribution of socioeconomic class populations, healthcare spending, air pollution exposure, and human mobility. This study used 1m resolved LIDAR data to characterize land use in Salt Lake County, Utah and associate it with sociodemographic and air quality data at the census block group and zip code levels. We found that increasing tree cover was associated with higher per capita income and lower minority populations while increasing built cover was linked to lower per capita income and higher minority populations. Air quality showed less strong correlations, however, decreased non irrigated cover, increased built cover, and higher amounts of households living under poverty was related to higher long-term PM2.5 exposure. Several policy efforts have been undertaken to improve air quality and reduce negative health outcomes in Utah which are being informed by regulatory and research grade air quality sensors.

Mangroves and salt marshes are among the most productive ecosystems in the global coastal ocean. Mangroves store more carbon (739 Mg CORG ha-1) than salt marshes (334 Mg CORG ha-1), but the latter sequester proportionally more (24%) net primary production (NPP) than mangroves (12%). Mangroves exhibit greater rates of gross primary production (GPP), above-ground net primary production (NPP) and plant respiration (RC) with higher PGPP/RC ratios, but salt marshes exhibit greater rates of below-ground NPP. Mangroves have greater rates of subsurface DIC production and, unlike salt marshes, exhibit significant microbial decomposition to a soil depth of 1 m. Salt marshes release more soil CH4 and export more dissolved CH4 , but mangroves release more CO2 from tidal waters and export greater amounts of POC, DOC and DIC to adjacent waters. Both ecosystems contribute only a small proportion of GPP, RE (ecosystem respiration) and NEP (net ecosystem production) to the global coastal ocean due to their small global area, but contribute 72% of air-sea CO2 exchange from the world’s wetlands and estuaries and contribute 34% of DIC export and 17% of DOC + POC export to the world’s coastal ocean. Thus, both wetland ecosystems contribute disproportionately to carbon flow of the global coastal ocean.

Myocilin is an enigmatic glaucoma-associated glycoprotein whose biological role remains incompletely understood. To gain novel insight into its normal function, we used transposon-mediated transgenesis to generate the first zebrafish line stably overexpressing myocilin [Tg(actb1:myoc-2A-mCherry)]. qPCR showed an approximately four-fold increased myocilin expression in transgenic zebrafish embryos (144 hpf). Adult (13 months old) transgenic animals displayed variable and age-dependent ocular anterior segment alterations. Almost 60% of two-years old male, but not female, transgenic zebrafish developed enlarged eyes with severe asymmetrical and variable abnormalities in the anterior segment, characterized by corneal limbus hypertrophy, and thickening of the cornea, iris, annular ligament and lens capsule. The most severe phenotype presented small or absent ocular anterior chamber and pupils, due to iris overgrowth along with dysplastic retinal growth and optic nerve hypertrophy. Immunohistochemistry revealed increased presence of myocilin in most altered ocular tissues of adult transgenic animals, as well as signs of retinal gliosis, and expanded ganglion cells and nerve fibers. The preliminary results indicate that these cells contributed to retinal dysplasia. Visual impairment was demonstrated in all old male transgenic zebrafish. Transcriptomic analysis of the abnormal transgenic eyes identified disrupted expression of genes involved in lens, muscular and extracellular matrix activities, among other processes. In summary, the developed transgenic zebrafish provides a new tool to investigate this puzzling protein and provides evidence for the role of zebrafish myocilin in ocular anterior segment and retinal biology, through the influence of extracellular matrix organization and cellular proliferation.

The phytoplankton community in 66 reservoirs ubicated at the hydrographic basin of the Ebro River (Spain) was analyzed. Samples were collected in the summer season during the period 2010-2015, with the main purpose of evaluate the Trophic State and Ecological Potential according to the Water Framework Directive of the European Union. In this work we presented a representative overview of several consecutive years of the state of the reservoirs and their associated trophic status; methodology was to obtain statistically significant relationships between the phytoplankton community and main physicochemical water quality variables (water transparency, pH, chlorophyll a, total and soluble phosphorus, anoxic zone depth, nitrite, nitrate and ammonium concentrations). We provide data for retrospective comparative of the state of the reservoirs with previous and current studies in order to improve the management of these reservoirs, and to serve as data reference for future works in a context of global change (climate and pollution).

The acquisition of adverbs in French as L2 (FSL) by learners with different L1s, at various levels of proficiency, has been extensively studied within various SLA projects (ESF, Interfra etc.). In the generativist tradition, it has been noted that “high category adverbs” such as those related to Mood-evaluative, Mood-epistemic and Tense are present early in FSL data. In the functionalist school, the early presence of time adverbs and scope particles in learner varieties has been analysed in relation with the informational and syntactic structures observed in these varieties and in terms of their contribution to temporal reference and other semantic domains in discourse.

With the increasing availability of large digitized fine art collections, automated analysis and classification of paintings is becoming an interesting area of research. However, due to domain specificity, implicit subjectivity, and pervasive nuances that vaguely separate art movements, analyzing art using machine learning techniques poses significant challenges. Residual networks, or variants thereof, are one the most popular tools for image classification tasks, which can extract relevant features for well-defined classes. In this case study, we focus on the classification of a selected painting 'Portrait of the Painter Charles Bruni' by Johann Kupetzky and the analysis of the performance of the proposed classifier. We show that the features extracted during residual network training can be useful for image retrieval within search systems in online art collections.

Ammonium sulfate has been utilized in agriculture; however, there is a dearth of research on its application in maize cultivation subsequent to the implementation of nitrification inhibitors or coating. This study aims to analyze the impacts of various combinations of ammonium sulfate fertilizers on soil nutrients, plant nutrient uptake, yield, and fertilizer utilization efficiency in maize cultivation to ascertain the optimal and stabilized disposal method for ammonium sulfate. A completely randomized design was employed with five treatments (AU, the control using urea; AS, treatment using ammonium sulfate; ASN, treatment using ammonium sulfate with a nitrification inhibitor; ASG, treatment using oil-coated ammonium sulfate; ASD, treatment using oil-humic acid-coated ammonium sulfate). Results showed that: (1) Compared with AU and AS, ASN, ASG and ASD decreased the leaching rates of TN, NH4+-N and NO3-N to the 10-20 cm soil layer, and more residual N was obtained in 0-10 cm soil layer. The first-order kinetic equation Nt=N0(1-e-kt) can better fit the process of nitrogen accumulation and release, and the N release rate constant is AU>CK>AS>ASH>ASN>ASD; (2) Compared with AU and AS treatments, the plant dry weight, grain dry weight, spike width, spike length, and yields of maize increased by 8.85-11.08%, 12.98-14.15%, 2.95-3.52%, 5.50-5.65%, and 43.21-51.10% under ASG treatment respectively. The impact of effective spike number on maize yield was found to be significant, as demonstrated by the path analysis conducted in this study. Furthermore, the accumulation levels of nitrogen, phosphorus, and potassium within above-ground plants significantly increased under the ASG treatment compared to the AU and AS treatments. The partial productivity of nitrogen, phosphorus, and potassium increased by 1.43-1.51-fold under ASG treatment, while grain nitrogen balance, grain phosphorus balance, and grain potassium balance increased by 1.41-1.58-fold, 1.51-1.95-fold, and 1.15-l.96-fold respectively. The oil-coated ammonium sulfate, therefore, exhibited the optimal slow-release effect of nutrients, thereby achieving superior performance in enhancing maize production and efficiency.

In the context of freshwater ecosystems, turbidity and suspended solids play crucial roles, with their levels significantly influenced by anthropogenic activities. This study focuses on assessing and monitoring these parameters in Albufera de Valencia using Sentinel-2 imagery. The primary aim is to establish reliable estimation algorithms that can contribute to effective ecosystem management. The study calibrated and validated algorithms for estimating turbidity and suspended solids. The R783×R705/R490 model proved to have the best performance for estimating turbidity and total solids in the Albufera. However, R783/R490 obtained a higher coefficient of de-termination for the organic part, while the R705 band was selected for the inorganic part. However, to achieve better estimates of turbidity and inorganic matter, more research is needed in the future. The implications of excessive suspended solids are underscored, including the depletion of dissolved oxygen, and reduced primary productivity due to limited light penetration and habitat availability. Collaboration between disciplines such as limnology, optics and water chemistry are crucial to advance water quality estimation models in lakes and lagoons such as Albufera. By integrating expertise and approaches from these diverse fields, new knowledge can be gained and the basis for more effective management and conservation strategies can be laid.

Noise in requirements has been known to be a defect in software requirements specifications (SRS). Detecting defects at an early stage is crucial in the process of software development. Noise can be in the form of irrelevant requirements that are included within a SRS. A previous study had attempted to detect noise in SRS, in which noise was considered as an outlier. However, the resulting method only demonstrated a moderate reliability due to the overshadowing of unique actor words by unique action words in the topic-word distribution. In this study, we propose a framework to identify irrelevant requirements based on the MultiPhiLDA method. The proposed framework distinguishes the topic-word distribution of actor words and action words as two separate topic-word distributions with two multinomial probability functions. Weights are used to maintain a proportional contribution of actor and action words. We also explore the use of two outlier detection methods, namely Percentile-based Outlier Detection (PBOD) and Angle-based Outlier Detection (ABOD), to distinguish irrelevant requirements from relevant requirements. The experimental results show that the proposed framework was able to exhibit better performance than previous methods. Furthermore, the use of the combination of ABOD as the outlier detection method and topic coherence as the estimation approach to determine the optimal number of topics and iterations in the proposed framework outperformed the other combinations and obtained sensitivity, specificity, F1-score, and G-mean values of 0.59, 0.65, 0.62, and 0.62, respectively.

Large ruminant production is associated with high greenhouse gas emissions (GHGe) intensity, with the highest in southeast Asia being Laos at 102.9 CO2eq/kg meat produced, compared with average global meat emissions intensity of 33 CO2eq/kg. As recent studies in Laos identified emissions control molasses blocks (ECBs) achieved abatement of 470kg CO2eq/20kg block consumed, a study was conducted with a supplement mix with reported methane reducing properties, containing plant tannins and citral extract, salt, molasses and water. Groups of housed dairy buffalo (n=7) and pasture-fed grazing beef cows (n=11) were randomly selected, body condition scores estimated (BCS:1-5) and baseline nasa-oral methane eructation measured daily for 2 weeks. All animals were offered 300-400g/day of the mix for a month, with buffalo accessing abundant fresh cut forages whereas the grazing cows accessing rice straw and pasture declining in quality and quantity due to severe drought. The buffalo consumed all of the mix and retained their BCS of 3, whereas the cattle consumed between 200-300g/day of the mix and their BCS declined from 1.5 to 1.0 during the trial. Analysis of data points (buffalo n=309; cattle n=378) found average methane concentration (AMP) per animal of both cohorts increased over the 2 week baseline period, then declined during the supplementation period by 36% in the buffalo and 18% in cattle cohorts.

The pharmacological effects of the fruiting body of Ophiocordyceps sinensis (Os) exerted antioxidant, anti-virus, and immunomodulatory, whereas the anti-inflammatory effects and active components of Os mycelial submerged culture (OMSC) are not known. This study aimed to investigate the active compounds in the fermented liquid (FLOS), hot water (WEOS), and 50-95% (EEOS-50, EEOS-95) ethanol extracts of OMSC and their anti-inflammatory effects and potential mechanisms in LPS-stimulated microglial BV2 cells. The results demonstrated that all of the OMSC extracts could inhibit NO production in BV2 cells. EEOS-95 exhibited the strongest inhibitory effects (41 % inhibitory ability at 500 µg/mL), and its ergosterol, GABA, total phenolic, and total flavonoid contents were significantly higher than those of the other extracts (18.60, 18.60, 2.28, and 2.14 mg/g, p &lt; 0.05, respectively). EEOS-95 also has a strong inhibitory ability against IL-6, IL-1β and TNF-α with IC50 of 617, 277 and 507 µg/mL, respectively, which is higher than that of 1 mM melatonin. The anti-inflammatory mechanism of EEOS-95 seems to be associated with up-regulation of PPAR-γ/Nrf-2/HO-1 antioxidant-related expression and down-regulation of NF-κB/COX-2/iNOS pro-inflammatory expression signaling. Therefore, we hypothesized that EEOS-95 can prevent neurodegenerative diseases, but the effect on the application in vivo should be further investigated.

At 12:28 UTC (8:28 PM, local time) on 15 January 2023, a shallow, moderate earthquake with a magnitude (Mw) of 4.7 and a depth of one (1) kilometer shook the northern part of Leyte Island in the central part of the Philippines. The ground shaking was felt at PHIVOLCS Earthquake Intensity Scale (PEIS) VI, (very strong) equivalent to Modified Mercalli Intensity (MMI) VI in areas along the strike of the Leyte segment of the Philippine Fault. Even though this earthquake is classified as moderate in size, significant geologic, structural, and socio-economic impacts were documented. Most of the earthquake impacts that include surface rupture, liquefaction, and mass movements are limited near the epicentral area. The earthquake produced an 8-km-long surface rupture, the first documented rupture generated by a magnitude &lt;6 along the Philippine Fault, and is unusual in other surface rupturing earthquakes worldwide. It injured 18 persons and damaged 434 residential buildings and 26 public infrastructures which amounts to about 500 thousand US dollars. Structural damages were caused by surface rupture and/or poor engineering construction practices. Analysis of the seismic waveform and recorded peak ground acceleration (PGA) suggests that the subsurface geology influenced the ground motion amplification in an area near the epicenter. Based on the hypocenter, focal mechanism solution, aftershock distribution, and actual field observation, the causative fault for this event is the northern end of the Philippine Fault – Leyte segment. Moderate in size, this earthquake emphasizes the need and importance of documenting moderate-sized earthquakes as a tool and guide for medium and long-term earthquake risk assessment and resiliency.

According to official sources, the numbers of children-to-parent violence (CPV) in the most advanced countries have been on an increasing trend for more than a decade, which generates great social concern. This phenomenon has also aroused enormous interest among researchers, who have identified risk and protective factors related to adolescent CPV in numerous studies. To contribute to a better explanation of CPV, the aim of the present study was to analyze the relationship between family communication problems and CPV, through psychosocial adjustment variables -psychological distress and positive attitude toward the transgression of social norms- in schooled adolescents. The sample consisted of 8115 adolescents enrolled in schools in the State of Nuevo León (Mexico) (51.5% boys, 49.5% girls), whose ages ranged from 11 to 16 years (M = 13.34, SD = 1.04). Structural equation modeling was performed using Structural Equation Modeling Software (EQS). The results showed that family communication problems have a direct and signif-icant relationship with CPV. It was also observed that there is an indirect relationship between both variables, through the relationships of psychological distress and positive attitude towards the transgression of social norms. The multigroup analysis performed showed gender differences in some of these relationships. Finally, the results and their implications in the field of family intervention are discussed.

Bacteria’s ability to withstand the detrimental effects of antimicrobials may take the form of resistance or tolerance with the minimum inhibitory concentration (MIC), the mutant prevention concentration (MPC), and the mutant selection window as salient concepts. Isolates exposed for 30 days to different concentrations of selected antibiotics, biocides, and heavy metals, singly and in combination, were additionally exposed to very high (15 × MIC) concentrations of ampicillin., and their tolerance was calculated the time to kill 99.9% of the isolate population (MDK99.9). These values were increased by 30 to 50% in test isolates compared to the untreated control. BAC 10-exposed isolates had the highest tolerance increase, and the tolerance appeared to originate from two sources, i.e., stochastic persistence and genetic-induced persistence, involving multiple genes using diverse mechanisms. The mutant selection window of the isolates to ampicillin, amoxicillin, and oxytetracycline also slightly increased compared to the control, indicating the amplification of persister cells during the 30-day exposure. These findings indicate that bacterial exposure to sub-inhibitory concentrations of environmental chemical stressors may not always result in the development of antimicrobial resistance but could initiate this process by selecting for persisters that could evolve into resistant isolates.

The purpose of this longitudinal study was to determine the effects of a rowing training program on physical fitness and body composition in female breast cancer survivors (56.78 ± 6.38 years). Over six months, the participants (n=40) performed two training sessions per week for an average of 75 minutes, combining resistance and muscle strength exercises with rowing. To evaluate the impact of the program, physical fitness tests and anthropometric measurements were carried out before and after the training protocol. The results show statistically significant improvements in measures such as weight (-1.84 kg), BMI (-0.7 kg/m2), hip (-3.24 cm) and waist circumference (-2.45 cm). In addition, variables associated with physical fitness also improved including leg strength (3.04 cm), dominant handgrip strength (4.24 kgf), non-dominant handgrip strength (3.49 kgf), aerobic endurance (78.35 m) and muscle flexibility (3.96 cm). We can therefore conclude that a rowing-based exercise program is an effective strategy to improve physical fitness in this type of population, yielding improvements in both anthropometric measurements and basic physical capacity variables, essential factors for better health and quality of life.

Edible insects can diversify diets, improve livelihoods, contribute to food and nutrition security, and have a smaller ecological impact. European Union has categorized insects as novel food, and recently, in 2021 and 2022, two species: Tenebrio molitor and Acheta domesticus have been authorized for commercialization. Acceptance and perception of food risk derived from insect consumption vary depending on factors impacting insect consumption acceptability, including neophobic tendencies, gender differences, familiarity, and gastronomic perceptions. The aim of this work was to evaluate the perception and acceptance of edible insects by exploring those factors. The study was carried out on higher education students from Universities from Valencia (Spain). Students recognize insects for their high nutritional value, particularly protein content, and have varying knowledge levels about specific nutritional components. In terms of labeling and marketing, removing health and sustainability benefits from packaging can improve consumer responses. Most respondents prefer clear labeling of insect derivatives, quality certification seals, and complete information about insect content. Students consider marketing and knowledge as significant influencers of insect consumption. In summary, the text highlights the multifaceted nature of insect consumption acceptability. These insights offer valuable perspectives on insect consumption dynamics.

This work aims to investigate the expression levels of four preselected miRNAs previously linked to Cancer and/or Obesity, with the purpose of finding potential biomarkers in the clinical management of Colorectal Cancer (CRC) developed by obese and non-obese patients. We analyzed samples from a total of 65 subjects, 43 affected by CRC and 22 without cancer. Serum and both subcutaneous and omental adipose tissues (SAT and OAT) were analyzed, as well as tumor and non-tumor colorectal tissues in the case of the CRC patients. The relative expression (2-∆∆Ct) levels of 4 miRNAs (miR-181a-5p, miR-143-3p, miR-132-3p and miR-23a-3p) were measured by RT-qPCR. Serum, SAT and OAT expression levels of these miRNAs showed significant differences between subjects with and without CRC, especially in the group of overweight/obese subjects. In CRC serum levels of miR-181a-5p, miR-143-3p and miR-23a-3p correlated with their levels in both SAT and OAT. Moreover, in the case of miR-181a-5p, these correlations were significantly influenced by the body mass index (BMI). From these data, we can conclude that both adiposity and CRC induce changes in the expression of the miRNAs investigated, demonstrating the potential utility of this panel of miRNAs in the diagnosis and prognosis of CRC patients.

Background and Objectives Neurofibromatosis 1 (NF1 MIM # 162200), also known as von Recklinghausen disease, is among the most common autosomal dominantly transmitted disorders characterized mainly by neurocutaneous manifestations such as café au lait spots, intertriginous freckling, various types of neurofibromas (cutaneous neurofibromas or plexiform tumors), neurological manifestations, and bone abnormalities. It occurs with an incidence of 1:3000–1:4000 cases. Cone-rod dystrophies belong to the large group of retinal dystrophies, a highly heterogeneous group of disorders clinically manifested mainly by damage to cone and rod cells and have a broad spectrum of clinical manifestations. Many genes are involved in their etiology, with more than 100 currently identified, including the CRX gene responsible for the autosomal dominant form of cone-rod dystrophy (ad CORD). Materials and Methods: The authors present an intriguing case of a patient diagnosed with Neurofibromatosis type 1 (NF1) as an infant and ocular involvement (myopia and astigmatism onset at age 15), which yielded a surprising molecular testing result. Results: Molecular DNA analysis identified a rare occurrence of two mutational variants, including a pathogenic variant in the NF1 gene, c.3871-2A, and a likely pathogenic variant in the CRX gene c.119G>A. Conclusions: The authors present this case to highlight the surprises offered by molecular testing in a condition where the diagnosis is usually based on clinical criteria, thus providing patients with competent genetic advice.

To mitigate the COVID-19 infection, many world governments endorsed the cessation of non-essential activities, such as the school attendance. Thereby, forcing the evolution of the teaching model to the virtual classroom. In the present work we show the application of a modified version of the adapted COVID-19 stress scales (ACSS) which also included teaching anxiety and preparedness, and resilience for academic professionals in Mexico, during the unprecedented transformation of the education system undergone in the COVID-19 quarantine. Most of the studied variables: gender, age, academic degree, household occupants, having a disease, teaching level, teaching mode, work hours, resilience, teaching anxiety and preparedness, and fear of being an asymptomatic patient (FOBAP), showed significant statistical correlation between each other (p<0.050) and to the 6 areas of the ACSS (danger, contamination, social economical, xenophobia, traumatic stress and compulsive checking). Our results further showed that the perceived stress and anxiety, fell into the category of absent to mild with only the danger section of the ACSS falling into the moderate category. Finally, resilience generated throughout the quarantine, seems to be a predictor of the adaptation the academic professional has undergone to cope with stress.

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.

Gestational diabetes mellitus (GDM) triggers alterations in the maternal gut microbiome. Alongside metabolic shifts, microbial products may impact clinical factors and influence pregnancy outcomes. Here, we performed two separate analyses to integrate the maternal microbiome-metabolomic differences from a subset of the “Choosing Healthy Options in Carbohydrate Energy” (CHOICE) study. Women diagnosed with GDM were randomized to a diet higher in complex carbohydrates (CHOICE, n=18, 60% complex carbohydrate/25% fat/15% protein) or a conventional GDM diet (CONV, n=16, 40% carbohydrate/45% fat/15% protein). All meals were provided, diets were eucaloric, and fiber content was similar. CHOICE diet was associated with increases in TMAO, lysophosphotidylcholines, indoxyl sulfate, and several triglyceride (TG) species, while CONV diet was associated with higher plasma hippuric acid, aspartic acid, betaine, glutamic acid, indole propionic acid, and indoleacetic acid, suggesting that differences in lipid metabolism and tryptophan utilization pathways are linked to specific maternal diets. We also identified two latent metabolic groups not associated with either diet treatment: one metabolome associated with higher fasting glucose, and the other associated with higher fasting TGs after 7 weeks on either diet. Our study underscores the importance of utilizing dietary approaches to optimize maternal-fetal health outcomes in GDM treatment.

During March and April 2020, the European Union (EU) was the center of the COVID-19 pandemic. Many National Governments imposed severe lockdown policies to mitigate the health crisis. The European Parliament commissioned a survey to analyse the citizens’ attitudes over a number of issues related to the COVID-19 pandemic. 21804 European citizens in 21 EU countries responded the survey between 23 April and 1 May 2020. The paper analyses empirically the individual satisfaction that European citizens have experienced over the measures taken by the respective National Governments to control the COVID-19 pandemic. The analysis is based on a micro-econometric model (ordered probit) that explains the citizens’ satisfaction by a number of attitudes and sociodemographic factors. Our results reveal that Spaniards are the least satisfied citizens in comparison with Danes, Irelanders, Greeks and Croats who are the most satisfied nationals. The years of education and the social class also play a determinant role. We also find that the most important determinant is the political support to the Government, and that those who are more worried by the economy and the protection of individual rights are usually more critic with the measures than those who are more worried by the health consequences.

In this study, we present a federated learning approach that combines a multi-branch network and the Oort client selection algorithm to improve the performance of federated learning systems. This method successfully addresses the significant issue of non-iid data, a challenge not adequately tackled by the commonly used MFedAvg method. Additionally, one of the key innovations of this research is the introduction of uniformity, a metric that quantifies the disparity in training time amongst participants in a federated learning setup. This novel concept not only aids in identifying stragglers but also provides valuable insights into assessing the fairness and efficiency of the system. Experimental results underscore the merits of the integrated multi-branch network with the Oort client selection algorithm and highlight the crucial role of uniformity in designing and evaluating federated learning systems.

There are currently worldwide efforts to reduce sugar intake due to the various adverse health effects linked with the overconsumption of sugars. Artificial sweeteners have been used as an alternative to nutritive sugars in numerous applications; however, their long-term effects on human health remain controversial. This led to a shift in consumer preference towards non-caloric sweeteners from natural sources. Thaumatins are a class of intensely sweet proteins found in arils of the fruits of the West-African plant Thaumatococcus danielli. Thaumatins’ current production method through aqueous extraction from this plant and uncertainty of the harvest from tropical rainforests limits its supply while the demand is increasing. Despite successful recombinant expression of the protein in several organisms, no large-scale bioproduction facilities exist. We present preliminary process design, process simulation, and economic analysis for a large-scale (50 metric tons/year) production of thaumatin II variant by several different molecular farming platforms.

Europium is one of the most reactive lanthanides and humans use it in many different applica-tions, but we still know little about its potential toxicity and cellular response to its exposure. Two strains of the eukaryotic microorganism model Tetrahymena thermophila adapted to high concentrations of two Eu(III) compounds (EuCl3 or Eu2O3) were obtained and compared to a control strain and cultures treated with both compounds. In this ciliate, EuCl3 is more toxic than Eu2O3. LC50 values show that this microorganism is more resistant to these Eu(III) compounds than other microorganisms. Oxidative stress originated mainly by Eu2O3 is minimized by overexpression of genes encoding important antioxidant enzymes. The overexpression of metallothionein genes under treatment with Eu(III) compounds supports the possibility that this lanthanide may interact with the -SH groups of the cysteine residues from metallothi-oneins and/or displace essential cations of these proteins during their homeostasis function. Both lipid metabolism (lipid droplets that fuse with europium-containing vacuoles) and au-tophagy are involved in the cellular response to europium stress. Bioaccumulation, together with a possible biomineralization to europium phosphate, seems to be the main mechanism of Eu(III) detoxification in these cells.

Solar and wind resources available for power generation are subject to variability due to meteorological factors. Here, we use a new global climate reanalysis product, Version 2 of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), to quantify interannual variability of monthly-mean solar and wind resource from 1980 to 2016 at a resolution of about 0.5 degrees. We find an average coefficient of variation (CV) of 11% for monthly-mean solar radiation and 8% for windspeed. Mean CVs were about 25% greater over ocean than over land, and, for land areas, were greatest at high latitude. The correlation between solar and wind anomalies was near zero in the global mean, but markedly positive or negative in some regions. Both wind and solar variability were correlated with values of climate modes such as the Southern Oscillation Index and Arctic Oscillation, with correlations in the Northern Hemisphere generally stronger during winter. We conclude that reanalysis solar and wind fields could be helpful in assessing variability in power generation due to interannual fluctuations in the wind and solar resource. Skillful prediction of these fluctuations seems to be possible, particularly for certain regions and seasons, given persistence or predictability of climate modes with which these fluctuations are associated.

Given a quasi-definite linear functional u in the linear space of polynomials with complex coefficients let us consider the corresponding sequence of monic orthogonal polynomials (SMOP in short) (Pn)n≥0. For the Christoffel transformation u˜=(x−c)u with SMOP (P˜n)n≥0, we are interested to study the relation between u˜ and u(1)˜, where u(1) is the linear functional for the associated orthogonal polynomials of the first kind (Pn(1))n≥0 and u(1)˜=(x−c)u(1) is its Christoffel transformation. This problem is also studied for the Geronimus transformations.

City marathons have evolved and grown exponentially in type and popularity, managerial complexity, for their financial impact on their host cities and for the attraction of corporate sponsors. Much research has focused on evaluating the broad economic, urban, tourist, social, sporting, and symbolic effects of city marathons on host cities. Research have not examined the importance of the contribution of sponsors to the financial stability and its implications to the overall management and further success of marathons. This article focuses on the cases of the Bank of America Chicago Marathon and the Marathon Valencia Trinidad Alfonso and examines how effective has been the contribution of their sponsors to the financial stability and its implications for the management and success of both races over time. Results show that the international success of both events –in terms of sporting participation, performance and economic impact– is closely related to the design and management of the event; the synergies between the political, business and sporting spheres that the organizational leadership of the event has made it possible to implement and, as a consequence, the support received from sponsors, which has not only provided both races with financial stability, but also has contributed to improve the management of the race.

After brings about a brief review of the theoretical explanations and researches on the reasons for being a victim, this article is organized into two sections. The first presents a comparative analysis of the data for 1999 and 2016 in terms of perceptions, profiles and most significant sociodemographic and socioeconomic variables. The second one shows an explanatory analysis based on a multivariate logistical regression model using as an independent variable lifestyle of the population and socioeconomic variables, and as dependent variables individual’s susceptibility to becoming a victim of certain crimes. The results points towards an explanatory model of victimization in which sociodemographic variables play an increasingly less important role while variables related to lifestyle and subjective perceptions make a significant contribution to greater understanding of the nature of being the victim of a crime.

This work addresses the challenge of EEG visual multiclass classification into 40 classes for Brain-Computer interface applications, by using deep learning architectures. The visual multiclass classification approach offers BCI applications a significant advantage, since it allows the supervision of more than one BCI interaction, considering that each class label supervises a BCI task. However, because of the nonlinearity and nonstationarity of EEG signals, performing multiclassifiers based on EEG features remains a significant challenge for BCI systems. In the present work, mutual information-based discriminant channel selection and Minimum-Norm Estimate algorithms are implemented to select discriminant channels and enhance EEG data. Hence, deep EEGNet and Convolutional-recurrent neural networks are implemented separately to classify EEG data of image visualization into 40 labels. By using the k-fold cross-validation approach, average classification accuracies of 94.8% and 89.8% were obtained by implementing the aforementioned network architectures, respectively. Satisfactory results obtained with this method offer a new implementation opportunity for multi-task BCI applications by utilizing a reduced number of channels (&lt;50%), compared to those presented in the related literature where the whole set of channels is used.

The main purpose of the study was to study the effects of a specific rowing ergometer training program on the athletic performance of young adolescents (n=56; 11.73 ± 1.4 years old) com-pared to a workout based on general strength training. Eight-week training program was im-plemented, with four sessions per week and two-hours per session. Sample was divided in two groups: a control group (CG) that performed circuit training with exercises aimed at building general strength and an experimental group (EG) who focused on specifically training on a rowing ergometer (rowing machine). The data obtained in a rowing meter test over the compe-tition distance were analyzed to obtain the average power attained (W) at the beginning of the training, at the middle (4 weeks), at the end of the training (8 weeks) and one year after the ex-perimentation. The results show that, although both forms of training improve the average W obtained in both categories, the EG subjects (+29.94W) obtained better averages in all phases of the study compared to the CG (+5.88W). Furthermore, this increase was greater in male rowers (+ 34.06W) than in female rowers (+24.54W). These results reveal that a specific rower rowing ergometer training program has a significant effect than a general strength program and these effects can even be observed a year after the intervention.

Industry 4.0 is in continuous technological growth that benefits all sectors of industry and society in general. This article reviews the concept of Digital Twin (DT) and the interest of its application in photovoltaic installations. A comparison is made on how other authors use the DT approach in photovoltaic installations to improve the efficiency of the renewable energy generated and consumed, the energy prediction and the reduction of the operation and maintenance costs of the photovoltaic installation. It is reviewed how, by providing real-time data and analysis, DTs enable more informed decisions in the solar energy sector. The objectives of the review are to study the digital twin technology and to analyze its application and implementation in photovoltaic systems.

We describe the design and fabrication of an industrial injection moulding system which can be mounted and used on the NCD-SWEET Small-angle X-Ray Scattering Beamline at ALBA. We show how highly useful time-resolved data can be obtained using this system. We are able to evaluate the fraction of material in the mould cavity and identify the first material to solidify and how this varies with the injection tem-perature. The design follows current industrial practice and provides opportunities to collect time-resolved data at several points within the mould cavity so we can build up a 4D perspective of the morphology and its temporal development. The quantitative data obtained will prove invaluable for the optimisation of the next generation of in-jection moulding techniques. This preliminary work used results from the injection moulding of a general purpose isotactic polypropylene.

Beta-lactam resistant bacteria, commonly resident in tertiary hospitals, have emerged as a worldwide health problem because of ready-to-eat vegetable intake. We aimed to characterize the genes providing resistance to beta-lactam antibiotics in Enterobacteriaceae, isolated from five commercial salad brands for human consumption in Mexico City. 25 samples were collected, grow in blood agar plates, the bacteria were biochemistry identified and antimicrobial susceptibility testing was done, the carried family genes were identified by endpoint PCR and the specific genes were confirmed with WGS by NGS. 12 positive cultures were identified and their microbiological distribution was as follows, 8.3% for Enterobacter aerogene (n=1), 8.3% for Serratia fonricola (n=1), 16.7% for Serratia marcesens (n=2), 16.7% for Klebsiella pneumoniae (n=2), and 50% (n=6) for Enterobacter cloacae. The endpoint PCR results showed 11 colonies positive for blaBIL (91.7%), 11 for blaSHV (91.7%), 11 for blaCTX (97.7%), 12 for blaDHA (100%),4 for blaVIM (33.3%), 2 for blaOXA (16.7%), 2 for blaIMP (16.7%), 1 for blaKPC (8.3%) and 1 for blaTEM (8.3%) gene, all samples were negative blaROB, blaCMY, blaP, blaCFX and blaLAP gene. The sequencing analysis revels a specific genotypes for Enterobacter cloacae (blaSHV-12, blaCTX-M-15, blaDHA-1, blaKPC-2); Serratia marcescens (blaSHV-1, blaCTX-M-3, blaDHA-1, blaVIM-2); Klebsiella pneumoniae (blaSHV-12, blaCTX-M-15, blaDHA-1); Serratia fonticola (blaSHV-12, blaVIM-1, blaDHA-1) and Enterobacter aerogene (blaSHV-1, blaCTX-M-1, blaDHA-1, blaVIM-2, blaOXA-9). Our results indicate that beta-lactam resistant bacteria have acquired integrons with a different number of genes that providing panresistance to beta-lactam antibiotics, including penicillins, oxacillins, cefalosporins, monobactams, carbapenems and imipenems.

Ras is the most frequently mutated oncogene and recent drug development efforts have spurred significant new research interest. Here we will review progress toward understanding how Ras functions in nanoscale, proteo-lipid signaling complexes on the plasma membrane, called nanocluster. We will discuss how G-domain reorientation is plausibly linked to Ras-nanoclustering and -dimerization. We will then look at how these mechanistic features could cooperate in the engagement and activation of RAF by Ras. Moreover, we will show how this structural information can be integrated with microscopy data that provide nanoscale resolution in cell biological experiments. Synthesizing the available data, we propose to distinguish between two types of Ras nanoclusters, an active, immobile RAF-dependent type and an inactive/ neutral membrane anchor-dependent. We conclude that it is possible that Ras reorientation enables dynamic Ras dimerization, while the whole Ras/ RAF complex transits into an active state. These transient di/oligomer interfaces of Ras may be amenable to pharmacological intervention. We close by highlighting a number of open questions including, whether all effectors form active nanoclusters and whether there is an isoform specific composition of Ras nanocluster.

The emerging whitefly-transmitted crinivirus Tomato chlorosis virus (ToCV) causes substantial economic losses by inducing yellow leaf disorder in tomato crops. This study explores potential resistance mechanisms by examining early-stage molecular responses to ToCV. A time-course transcriptome analysis compared naïve, mock and ToCV-infected plants at 2, 7, and 14 days post-infection (dpi). Gene expression changes were most notable at 2 and 14 dpi, likely corresponding to whitefly feeding and viral infection. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed key genes and pathways associated with ToCV infection, including those related to plant immunity, flavonoids and steroids biosynthesis, photosynthesis, and hormone signalling. Additionally, virus-derived small interfering RNAs (vsRNAs) originating from ToCV predominantly came from RNA2 and were 22 nucleotides in lengt. To confirm these findings, two genes involved in plant immunity, Hsp90 (heat shock protein 90) and its co-chaperone Sgt1 (suppressor of the G2 allele of Skp1) were targeted through viral-induced gene silencing (VIGS), showing potential contribution to basal resistance against viral infections since their reduction correlated with increased ToCV accumulation. This study provides insights into tomato plants responses to ToCV, with potential implications for developing effective disease control strategies.

Introduction: Osteosarcomas of the jaw (OSJ) are rare tumors with a different behavior from osteosarcomas of other bones. This study aims to analyze the clinical, pathological, and therapeutic characteristics of this type of sarcoma. Methods: a retrospective observational study of cases diagnosed with OSJ registered at the “La Paz” University Hospital (Madrid). Results: Eight cases with a diagnosis of OSJ were obtained in a study period of 22 years (2000-2022). The mean age was 41 years. The distribution was 1:1 between the maxilla and mandible. Painful inflammation was the most frequent clinical manifestation. Conventional osteoblastic osteosarcoma was the most common. Survival at 5 years was 50%, while at 10 years, it decreased to 25%. Conclusions: OSJ differs from conventional osteosarcomas of long tubular bones. Surgery continues to be the mainstay of treatment; more studies are needed in which more standardized protocols can be proposed for adjuvant therapeutic management.

The medium-voltage DC (MVDC) technology has gained increasing interests in recent years. Power electronics devices dominate those grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system level control model of such a modern MVDC distribution grid. Aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/- 10 kV MVDC grid case study, including Solid State Transformer (SST) and Modular Multilevel Converter (MMC) based Active Front End (AFE). Additional aim of this paper is to supply an educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented.

The problem addressed in this article consists of the motion control of a quadrotor, comprising model disturbances and uncertainties. In order to tackle model uncertainty, adaptive control based on reinforcement learning is used. The distinctive feature of this article, in comparison with other works on quadrotor control using reinforcement learning is the exploration of the underlying optimal control problem in which a quadratic cost and a linear dynamics allow an algorithm that runs in real time. Instead of identifying a plant model, adaptation is obtained by approximating the performance index given by the Q-function using directional forgetting recursive least squares that rely on a linear regressor build from quadratic functions of input/output data. The adaptive algorithm proposed is tested in simulation in a cascade control structure that drives a quadrotor. Simulations show the improvement in performance that results when the proposed algorithm is turned on.

Thermodynamics of protein-ligand interactions seems to be associated to a narrow range of Gibbs Free Energy. As a consequence, a linear enthalpy-entropy relationship showing an apparent Enthalpy-Entropy compensation (EEC) is frequently observed associated to the study of protein-ligand interactions. This EEC affects negatively the design and discovery of new and more efficient drugs capable of binding protein-targets with a higher affinity. Originally attributed to experimental errors, compensation between H and TS values is a real observable fact, although its molecular origin has remained obscure and controversial. Herein we show the results of a data search of G values of 2558 protein-ligand interactions and 3025 “in vivo” ligand concentrations from the Protein Data Bank bind Database and the Metabolome Data Base (2020). These results, together with the mechano-statistical interpretation of the thermodynamic properties leads to the conclusion that the EEC has no basis in statistical thermodynamics. It can be plausibly explained as a consequence of the narrow range of G associated to protein-ligand interactions. The Gaussian distribution of the G values matches very well with that of ligands. These results suggest the hypothesis that the set of G values for the protein-ligand interactions is the result of the evolution of proteins. The conformation versatility of present proteins and the exchange of thousands (even millions) of minute amounts of energy with the environment may have functioned as a homeostatic mechanism to make G of proteins adaptive to changes in availability of ligands, and therefore achieve the maximum regulatory capacity of the protein function. Finally, a plausible strategy to avoid the EEC is suggested.

A key goal of modern neuroscience involves understanding how connections in the brain form and function. Such a knowledge is essential to better inform how defects in the exquisitely complex steps of nervous system growth underlie neuropsychiatric and neurodevelopmental disorders. In the last 40 years, studies of the nervous system in the fruit fly Drosophila melanogaster enabled the discovery of a wealth of molecular and genetic mechanisms that drive the development of these synaptic connections – specialized cell-to-cell connections that are the essential substrate for information flow and processing in the nervous system. The major driver of knowledge focused on studies at the neuromuscular junction due to its ease of examination. Analogous studies in the central nervous system lagged behind due to a lack of genetic accessibility of specific central neuron classes, appropriate synaptic labels compatible with cell-type specific access, and high resolution, quantitative imaging strategies. However, understanding how synapses in central circuits form remains a prerequisite to understanding brain development. In the last decade, a host of new tools and techniques made possible the extension of genetic studies of synapse organization into central circuits and greatly enhanced our understanding of central synapse formation, organization, and maturation. In this review, we consider the current state-of-the-field, focusing on two major elements. We first discuss the tools, technologies, and strategies developed to visualize and quantify synapses in vivo in genetically identifiable neurons of the Drosophila CNS. Second, we explore in depth how these tools enabled a clearer understanding of synaptic development and organization in different circuits of the fly brain and discovered novel molecular mechanisms that underlie synapse formation. These studies establish multiple brain regions in the fly as powerful in vivo genetic models that offer novel insights into synaptogenic regulators and mechanisms of neural development.

Although RNA modifications were discovered decades ago, the identification of enzymes that write, read, and erase RNA modifications enabled their functional study and spawned the field of epitranscriptomics. Coupling that knowledge to new methods has enabled the precise pinpointing of epitranscriptomic modifications across the transcriptome plus the elucidation of their functional consequences. PCIF1 (Phosphorylated CTD Interacting Factor 1) was shown to add N6, 2’-O-dimethyladenosine (m⁶Am) marks at the first nucleotide after the 5’ N7-methylguanosine (m⁷G) cap. In this review, we discuss the epitranscriptomic regulation of mRNA in general, and focus on m⁷G cap-adjacent m⁶Am in particular. m⁶Am positions can now be distinguished from N6-methyladenosine (m⁶A) using new techniques leveraging PCIF1-knockout cells. Although m⁶Am modification sites can be detected precisely, conflicting data have been published regarding how cap-adjacent m⁶Am marks affect their host mRNA. Discrepancies in the data mean that the effects of cap-adjacent m⁶Am on mRNA stability, decapping, and translation continue to be debated. Finally, while PCIF1 is predominantly nuclear, a subset of results suggest a possible cytoplasmic role as well. Taken together, these contradictory results which employed different methodologies and cell lines means that further experiments are required to determine the ultimate biological function(s) of m⁷G cap-adjacent m⁶Am.

This study is centred on Insecurity and Electoral Administration in Nigeria. Elections are the leading mechanism for selecting governments and a cardinal feature of democratisation. The quest for fair representation, development, good governance, inclusiveness and a true sense of belonging has been the driving force for election. The conduct of credible elections remains one of the thorny and fundamental issues in a democracy. The trajectory of electoral administration in Nigeria is long and tortuous; it precedes independence and is punctuated by the elite's scheming and cunning, electoral fraud, gimmicks and violence. Nigeria has had its fair share of insecurity from diverse sources such as banditry, insurgency, recurring violent religious crises, ethnic, resource and poverty-induced militancy, and crises occasioned by the clamour for self-determination. This has left the electoral management body in a quandary and has undoubtedly imperilled the administration of elections in Nigeria and equally accentuated the temerity for a holistic approach in reversing the trend and engendering the right atmosphere for the administration of elections. This study depends mainly on secondary sources and uses qualitative means in data analysis. It is revealed in this study that violence and various degrees of interruptions have taken the front burner in the democratisation process and are one of the dangerous dimensions in electoral administration; electoral politics remains one of the remarkable principal bases of clashes, political failure and social dislocation, Elections and their administration are some of the most complicated, time-sensitive activities undertaken by any country which will be exacerbated by insecurity. Democratic elections are successful when the electorate can make informed decisions; when faith in the process is sustained; when fraud is disincentivised, detected and punished. When insecurity is whittled down, mitigated or eradicated. The need for electoral security can never be overemphasised.

We present the real number system as a natural generalization of the natural numbers. First, we prove the co-finite topology, $Cof(\mathbb N)$, is isomorphic to the natural numbers. Then, we generalize these results to describe the continuum $[0,1]$. Then we prove the power set $2^{\mathbb Z}$ contains a subset isomorphic to the non-negative real numbers, with all its defining structure of operations and order. Finally, we provide two different constructions of the entire real number line. We see that the power set $2^{\mathbb N}$ can be given the defining structure of $\mathbb R$. The constructions here provided give simple rules for calculating addition, multiplication, subtraction, division, powers and rational powers of real numbers, and logarithms. The supremum and infimum are explicitly constructed by means of a well defined algorithm that ends in denumerable steps. In section 5 we give evidence our construction of $\mathbb N$ and $\mathbb R$ are canonical; these constructions are as natural as possible. In the same section, we propose a new axiomatic basis for analysis. In the last section we provide a series of graphic representations and physical models that can be used to represent the real number system. We conclude that the system of real numbers is completely defined by the order structure of $\mathbb N$.}