The present study aimed to investigate the effects of a 10-week online high-intensity interval training (HIIT) on body composition and aerobic performance in physically sedentary women. A parallel two-group, longitudinal (pre, post) design was used with physical tests performed before (preintervention) and after (postintervention) the 10-week intervention period. A total of for-ty-eight healthy and physically sedentary women were recruited to participate in this study. Par-ticipants were distributed in two groups: The experimental group (EG) with 24 women (n = 24, age 21.21 ± 2.15 years, weight 61.16 ± 8.94 kg, height 163.96 ± 4.87 cm, body mass index body weight 22.69 ± 2.49 kg/m2), and the control group (CG) with another 24 women (n = 24, age 20.50 ± 1.29 years, weight 62.0 ± 6.65 kg, height 163.92 ± 4 .89 cm, body mass index 23.04 ± 1.74 kg/m2). The EG performed an online HIIT program for 10 weeks, while CG continued with their daily life routines. The repeated measures ANCOVA indicated a significant effect in the within-group analysis for weight (p=0.001; d=-0.96), demonstrating a significant decrease in the Experimental Group (EG) while the Control Group (CG) did not show a significant decrease in body mass in-dex (p=0.15; d=-0.11). Regarding maximal oxygen uptake (VO2 max) values, the EG exhibited a significant improvement (p=0.001; d=-1.07), whereas the CG did not demonstrate a significant improvement (p=0.08; d=-0.37). A new within-group analysis with power output (W) revealed that EG significantly improved (p=0.01; d=-0.96), while CG did not show a significant improve-ment in power output (W/kg) (p=0.20; d=-0.11). Lastly, the within-group analysis with Load re-vealed that EG significantly improved (p=0.001; d=-0.50), while CG did not show a significant improvement in Load (p=0.10.; d=-0.10). The present study showed that 10 weeks of HIIT in an online environment during the Covid-19 lockdown significantly improved maximum oxygen consumption, and caused weight loss and a significant decrease in body mass index in physically sedentary women. These results suggest HIIT may be used as a time-efficient strategy to improve body composition and cardio-respiratory fitness in sedentary women.

The current management of colorectal cancer liver metastasis (CRCLM) patients involves a multidisciplinary approach with surgical resection remaining the primary curative option. The advances in liver surgery have improved outcomes, enabling more patients to undergo surgery successfully. In addition, the development of imaging software has improved the preoperative planning and patient selection for surgery and other interventions. Systemic therapies, such as targeted therapies and immunotherapies have enhanced the chances of complete resection. Targeted agents in combination with chemotherapy, have shown efficacy in downstaging tumors and increasing resectability.

This article explores the relationship between green energy and cryptocurrencies in the sustainable energy finance sector. The research findings contribute to our understanding of the application of green economy practice, enabling investors in financial markets, policymakers, and stakeholders to make informed decisions and develop specific strategies. Adopting the green economy paradigm makes it possible to promote collaboration and innovation by integrating ethical and responsible principles that can improve the overall quality of processes and boost sustainable growth. Cryptocurrencies have been widely used as financial instruments over the last decade. Given the development of the cryptocurrency market and the growing awareness of greener and more energy-efficient tokens, the green economy has become a popular topic for understanding economic and political issues. However, the literature still lacks clear evidence on how cryptocurrencies interact with green energies. Therefore, this study examines the long- and short-term relationships between dirty cryptocurrencies such as Bitcoin (BTC), Ethereum (ETH), clean cryptocurrencies such as Cardano (ADA), Ripple (XRP), Stellar (XLM), and green energies such as ISE Clean Edge Global Wind Energy, S&P Global Clean Energy, S&P TSX Renewable Energy and Clean Technology, Solactive China Clean Energy, in the period from January 2020 to September 2023. The results show that diversification is key, with clean cryptocurrencies such as ADA, XLM and XRP offering diversification opportunities alongside "dirty" cryptocurrencies such as BTC and ETH. Although sustainable energy indices show mixed evidence in the long and short term, they remain relevant for those who focus on clean energy investments. It is also becoming increasingly relevant for investors in sustainable portfolios to assess their environmental impact, especially for energy-intensive cryptocurrencies, and it is advisable to explore sustainable blockchain technologies.

Climate and land-use changes have been contributing to increase the occurrence of extreme wild-fires, shifting fire regimes and driving desertification, particularly in Mediterranean-climate regions. However, few studies have researched the effects of land-use change on fire regimes and carbon storage at the broad national scale. To address this gap, we used spatially explicit data from annual burned areas in mainland Portugal to build a typology of fire regimes based on the accumulated burned area and its temporal concentration (Gini index) between 1984 and 2019, which was combined with 2018 carbon stock data (above- and below-ground), and a landscape typology re-sulting from cluster analysis over land-use composition, diversity and configuration, to explore relationships between landscape types and the two major ecosystem services at stake: wildfire reduction and carbon stock. Cross tabulations, logistic and linear regressions were performed on these data and results revealed a strong relationship between landscapes dominated by maritime pine and eucalypt forest plantations and high-hazardous fire regime but hold the highest carbon stock. Shrubland-mixed landscapes were associated with lower carbon stocks but less hazardous fire regimes. Specialized agricultural landscapes, as well as mixed native forests and mixed agro-forestry landscapes, were the least associated with wildfires. In the case of agricultural landscapes however, this good wildfire performance is achieved at the cost of the poorest carbon stock, de-noting land degradation, whereas native forests and agroforestry landscapes strike the best trade-off between carbon stock and fire regime. Our findings support how nature-based solutions promoting wildfire mitigation and carbon stock ecosystem services may prevent and revert land degradation harming Mediterranean regions.

Chronic obstructive pulmonary disease (COPD) is a multifactorial lung inflammatory disease affecting 174 million people worldwide, with a recently reported increased incidence in female patients. Patients with COPD are especially vulnerable to the detrimental effects of environmental exposures, especially from air particulate and gaseous pollutants. Exposure to air pollution severely influences COPD outcomes, resulting in acute exacerbations, hospitalizations, and death. In the current study, we conducted a review of the literature addressing air pollution induced acute exacerbations of COPD (AECOPD) in order to determine whether air pollution affects COPD patients in a sex-specific manner. We found that while the majority of studies enrolled both male and female patients, only a few reported results disaggregated by sex. Most studies had a higher enrollment of male patients, only four compared AECOPD outcomes between sexes, and only one study identified sex differences in AECOPD, with females displaying higher rates. Overall, our analysis of the literature confirmed that air pollution exposure is a trigger for AECOPD hospitalizations and revealed a significant gap in our knowledge of sex-specific effects of air pollutants on COPD outcomes, highlighting the need for more studies considering sex as a biological variable.

Commercial classification is essential to spatially describe commerce. Although most of the proposed classifications have been classic functional analyses, rooted on qualitative studies, some recent classifications efforts are found to rely heavily on more quantitative methods, due eventually to increasing data availability and technological advancements. In this paper, a classification is proposed, using k-means clustering and a minimal set of variables (density, diversity and clustering) to derive the commercial structure of Lisbon. The classification is implemented for 1995, 2002 and 2010, using a 150m-sided square grid. The cross-sectional analysis of the results shows the rise of shopping-malls against city centre decline and gentrification, along with changes in cluster composition considering 9 different commercial categories (6 categories of retail, and restaurants, cafes and bars). These findings are in line with literature, thus supporting the obtained classification. Since the classification can be used to accurately describe the commercial structure of the city in different time periods, it is implied that it may also be generalized to different cities. Furthermore, the potential use of cluster membership in retail location models, which is an advantage of the proposed classification, could help strengthen the relationship between location modelling and commercial classification, thus reinforcing the role of commercial studies in urban planning and policymaking.

Intrusion Detection Systems play a crucial role in a network. They can detect different network attacks and raise warnings on them. Machine learning-based IDSs are trained on datasets that, due to the context, are inherently large, since they can contain network traffic from different time periods and often include a large number of features. In this paper, we present two contributions: the study of the importance of feature selection when using an IDS dataset, while striking a balance between performance and the number of features; and the study of the feasibility of using a low-capacity device, the Nvidia Jetson Nano, to implement an IDS in a low-capacity network. The results, comparing the GA with other well-known techniques in feature selection and reduction, show that the GA has a higher F1-score of 76%, although the time to find the optimal set of features surpasses other methods; the reduction of the number of features reduces the processing time without a significant impact in f1-score. The Jetson Nano allows the classification of network traffic with an overhead of 10 times in comparison to a traditional server.

Pulmonary hypertension (PH) is a progressive condition that affects pulmonary vessels, but its main prognostic factor is right ventricle (RV) function. Many mice/rat models are used for research in PAH, but results fail to translate in clinical trials. This study reviews studies that test interventions on pulmonary artery banding (PAB), a model of isolated RV disfunction, and PH models. Multiple tested drugs both improved pulmonary vascular hemodynamics in PH models and RV structure and function in PAB animals. PH models and PAB frequently exhibited similar results (73.1% concordance) with drugs other than endothelin receptor antagonists and phosphodiesterase inhibitors. RV systolic pressure accounted for most differences between PH models and PAB. On the other side, all results on RV fibrosis agreed (12 drugs). Macitentan, sildenafil and tadalafil improved most tested pathophysiological parameters in PH models, but almost none in PAB animals. Dapagliflozin was the only drug that improved no parameters. This review shows that many drugs currently under research for PAH have a cardioprotective effect on animals that may translate to humans. To improve the translational potential of drugs in this field, researchers should test them in multiple models, including PAB, while optimizing induction methods for human disease translation.

When a limb suffers a fracture, rupture, or dislocation, it is traditionally immobilized with plaster. This may induce discomfort in the patient, excessive itching and sweating, which creates the growth of bacteria, leading to an unhygienic and difficulty to keep clean from treatment. Furthermore, if the plaster remains for a long period, it may cause lesions in the joints and ligaments. To overcome all these disadvantages, orthoses have emerged as important medical devices to help patients in rehabilitation, as well as for self-care of deficiencies in clinics and daily life. Traditionally, these devices are produced manually, which becomes time-consuming and error prone. From another point-of-view, it is possible to use imageology (X-ray or computed tomography) to scan the human body; a process that may help orthoses manufacturing but induces radiation to the patient. To overcome this great disadvantage, several types of 3D scanners, without any kind of radiation have emerged. This article describes the use of various types of scanners capable of digitizing the human body, to produce custom orthoses. Studies have shown that photogrammetry is the most used and most suitable 3D scanner for the acquisition of the human body in 3D. With this evolution of technology, it is possible to decrease the scanning time and it will be possible to introduce this technology in clinical environment.

The increased demand and use of autonomous vehicles and advanced driver-assistance systems has been constrained by an incidence of accidents involving errors with the perception layer’s functionality. In tandem, recent papers have noted the lack of standardized, independent testing formats and insufficient methods with which to analyze, verify and qualify LiDAR-based data and categorization. While camera-based approaches benefit from an ample amount of research, camera images can be unreliable in situations with impaired visibility such as dim lighting and fog. This paper aims to introduce a novel method based entirely on LiDAR data with the capability to detect anomalous patterns as well as complementing other performance evaluators using a Copula-based approach. With a promising set of preliminary results, this methodology may be used to evaluate an algorithm’s confidence score, the impact conditions may have on LiDAR data and detect cases in which LiDAR data may be insufficient or otherwise unusable.

Tabebuia aurea (Silva Manso) Benth. & Hook. f. The ex S.Moore (yellow ipe), belonging to the Bignoniaceae family, used in the popular for fever, inflammation and healing of skin wounds. The extract was prepared by maceration, using 70% ethanol. Through HPLC analysis, it was possible to identify substances, mainly phenolic, such as lapachol, present in Bignoniaceae. The phenolic content was 21.36 mg / Eag in the antioxidant activity, the effective concentration of 50% was 53.03 ± 1.14 µg / mL. The antimicrobial activity against S.aureus, E. coli and C. albicans was evaluated by microdilution in broth, which verified action against the tested microorganisms. Cell viability has been inhibited for tumor cells, although this has not been observed for normal cells. The LD50 against A.aegypti mosquito larvae was 3504.6 mg / L and there was no mortality in the concentration tested for the snail B.glabrata. Nontoxic or low toxicity for A. salina and T. molitor, respectively, and did not exhibit hemolytic action at concentrations of antibacterial effect. Given the above, it was concluded that the bark extract of the studied species has bioprospecting potential for the future development of antimicrobial products.

The white wine industry generates a large amount of wastes and composting is an alternative for recycling these residues with agronomic and environmental advantages. With this aim, grape marc and grape stalks were composted in static and turned piles, with 3 and 6 turns, to investigate the effects of pile conditions during composting in order to improve final compost quality. Thermophilic temperatures were attained soon after pile construction, and the highest maximum temperatures were achieved in the turned piles (70.5-71.8 ºC). However, pile moisture content decreased bellow recommended values after day 42 in these piles. The extremely high temperatures and low moisture content in turned piles hampered OM mineralization rates and the amount of potentially mineralizable organic matter (OM0) (391-407 g kg-1), whereas the structure of the static pile provided adequate porosity to increase OM decomposition and OM0 (568 g kg-1). This study shows that composting grape marc with stalks, for a period of 140 days, resulted in stabilized and matured compost (NH4+-N / NO3--N <0.5), with good chemical characteristics for application as soil organic amendment in vineyards, without the need for rewetting or turning the piles, thus reducing the agronomic, and environmental cost of the composting process.

We present a new study of Jupiter atmosphere’s dynamics using for the first time the extremely high resolution capabilities of VLT/ESPRESSO to retrieve wind velocities in Jupiter’s troposphere, with a dedicated ground-based Doppler velocimetry method. These results are complemented by a deeper analysis of Cassini data during its flyby of Jupiter in December 2000, performing cloud tracking at visible wavelengths, obtaining a more comprehensive dynamical interpretation. We explore the effectiveness of this new method to measure winds in Jupiter, using high resolution spectroscopy data obtained from ESPRESSO observations performed in July 2019, with a Doppler velocimetry method based on back scattered solar radiation in the visible range. Coupled with our ground based results, we retrieved a latitudinal and longitudinal profile of Jupiter’s winds along select bands of the atmosphere. Comparing the results between cloud tracking methods, based on previous reference observations, and our new Doppler velocimetry approach we found a good agreement between them, demonstrating the eectiveness of this technique. The winds obtained in this exploratory study have a two-fold relevance: they contribute for the temporal and spatial variability study of Jupiter troposphere’s dynamics, and also the results presented here validate this Doppler technique to study the dynamics of Jupiter’s atmosphere and pave the way for further exploration of a broader region of Jupiter’s disk for a more comprehensive retrieval of winds and to evaluate their spatial and temporal variability.

This work exclusively focuses on the assessment of the thermal performance of a multifunctional facade panel incorporating PCM in foam layers, recurring to a hot box heat flux meter method to determine the thermal transmittance (U-value). The experimental setup is based on the steady-state approach using climatic chambers, assuring a stable thermal environment. Even small fractions of PCM achieved a small reduction in thermal amplitude. Numerical simulations using Ansys Fluent were developed to evaluate the performance of PCM use over a wide range of temperature boundary conditions and operating modes. These numerical models were calibrated and validated using the results of experimental tests, achieving a correlation factor of 0.9674, thus accurately representing a real-world scenario. The decrement factor (f) was used to analyse the data. It was identified that the efficiency of the panel and size of the optimum region increased with the PCM fraction growth. The simulated behaviour was optimum when the input mean temperature is of 20 °C for a room temperature of between 18-20 °C. The results show the significant potential of the multi-layered panel and the thermal regulator effect of the PCM incorporated on indoor space temperature to reach good thermal comfort levels.

Biological invasions represent a threat to ecosystems, through competition and habitat destruction, which may result in significant changes of the invaded community. Asparagopsis armata is a red macroalgae (Rodophyta) globally recognized as an invasive species. It is found from the intertidal to shallow subtidal areas, on rock or epiphytic, forming natural vegetation belts on exposed coasts. This study evaluated the variations on native intertidal seaweed and macroinvertebrate assemblages inhabiting rock pools with and without the presence of the invasive macroalgae A. armata. To achieve this, manipulation experiments on Atlantic (Portugal) rock pools were done. Three rock pools were maintained without A. armata by manual removal of macroalgae, and three others were not experimentally manipulated during the study period and A. armata was freely present. In this study the variations between different rock pools were assessed. Results showed different patterns in the macroalgae composition of assemblages but not for the macrobenthic communities. Ellisolandia elongata was the main algal species affected by the invasion of A. armata. Invaded pools tended to show less species richness, showing a more constant and conservative structure, with lower variation of its taxonomic composition than the pools not containing A. armata, where the variability between samples was always higher. Despite the importance of the achieved results, further data based on observation of long-term series are needed, in order to further understand more severe effects of the invader A. armata on native macroalgal assemblage.

This research proposes an algorithm to sign messages using the ElGamal asymmetric cryptosystem, called: Digital signature algorithm based on ElGamal, Diffie-Hellman protocol and the number π (DSAπ). This proposal has a high level of security like the DSA standard, in addition, execution times are reduced in relation to it. The Diffie-Hellman protocol and the number π were used in the construction of the digital signature algorithm in conjunction with the Hash-Sha-512 function. Some experiments are presented to provide evidence that the bits on the right side of the decimal point of π appear randomly, such as: a color image was constructed of a string of consecutive bits chosen at random, of the number π. Subsequently, parameters such as: entropy, correlation, discrete Fourier transform, goodness-of-fit test χ2 were evaluated. It is mentioned that an S-box 8×8 is involved in the signature. The sensitivity of the signature was measured, that is, when small changes are made to the sender’s private key, or small changes to the message. Finally, an image was constructed using the signatures of random texts, and subsequently the randomness of its pixels was obtained, to verify that there is no relationship between the different signatures.

The agronomic characteristics of Cenchrus purpureus were assessed through a randomized block experimental design with seven accessions (Taiwan grass, King grass, Elephant grass, Merkeron, CT-115, Purpule grass and Maralfalfa) as treatments and four replications research was carried out at the Instituto Tecnológico Superior de Tantoyuca, in 2019 and 2020, under rainfed conditions. Sowing density was established at 36 tillers in 25 m2. Green and dry matter yield, daily rates of dry matter accumulation in leaves, leaf/stem ratio, height, leaf area index and cutting frequency were assessed. Rainfall amount, temperature, relative humidity and global radiation levels were recorded to assess their effect on the evaluated variables. One-way ANOVA and multivariate analysis techniques, such as multiple linear regression (MLR), Clustering, and Principal component analysis (PCA) with the Statistica V7 software, were used. The leaf area index was greatest (p < 0.05) on the dry season. Green and dry matter yield were greatest in Maralfalfa (p < 0.05). Variation in the results is attributed to weather phenomena; nonetheless, Elephant grass and Maralfalfa showed the highest yields. Quality parameters must be evaluated to identify those grasses with the best attributes.

Terpenoids, including monoterpenoids (C₁₀), norisoprenoids (C₁₃) and sesquiterpenoids (C₁₅), constitute a large group of plant-derived naturally occurring secondary metabolites which chemical structure is highly diverse. A quantitative structure-activity relationship (QSAR) model to predict the terpenoids toxicity and to evaluate the influences of their chemical structure, was developed in this study, by assessing the toxicity of 27 terpenoid standards using Gram-negative bioluminescent Vibrio fischeri, in real time. Under the test conditions, at concentration of 1 µM, the terpenoids showed a toxicity level lower than five %, with exception of geraniol, citral, (S)-citronellal, geranic acid, (±)-α-terpinyl acetate and geranyl acetone. Moreover, the standards tested displayed a toxicity level higher than 30 % at concentration of 50 to 100 µM, with the exception of (+)-valencene, eucalyptol, (+)-borneol, guaiazulene, β-caryophellene and linalool oxide. Regarding the functional group, the terpenoids toxicity was observed in the following order: alcohol > aldehyde ~ ketone > ester > hydrocarbons. CODESSA software was employed to develop the QSAR models based on the correlation of terpenoids toxicity and a pool of descriptors related to each chemical structure. The QSAR models, based on t-test values, showed that terpenoids toxicity was mainly attributed to geometric (e.g., asphericity) and electronic (e.g., max partial charge for a C atom [Zefirov's PC]) descriptors. Statistically, the most significant overall correlation was the four-parameter equation with training and test coefficient correlation higher than 0.810 and 0.535, respectively, and square coefficient of cross-validation (Q²) higher than 0.689. According to the obtained data, the QSAR models are a suitable and a rapid tool to predict the terpenoids toxicity in a diversity of food products.

Immersive Unit Visualization is an emergent form of visualization that arose from Immersive Analytics where, unlike traditional visualizations, each data point is represented by an individual visual mark in an immersive virtual environment. This practice has focused almost exclusively on virtual reality, excluding augmented reality (AR). This article develops and tests a prototype of an immersive Unit Visualization (Floating Companies II) with two AR devices: head-mounted display (HMD) and hand-held display (HHD). Results from the testing sessions with 20 users were analyzed through qualitative research analysis and thematic coding indicating that, while the HHD enabled a first contact with AR visualization on a familiar device, HMD improved the perception of hybrid space by supporting greater stability of virtual content; wider field of view; improved spatial perception; increased sense of immersion; and more realistic simulation, which impacted on information reading and sense-making. The materialization of abstract quantitative values into concrete reality through its simulation in the real environment and the ludic dimension stand out as important opportunities of this type of visualization. This paper investigates the aspects distinguishing two experiences regarding data visualization in hybrid space; and characterizes ways of seeing information with AR, identifying opportunities to advance information design research.

Peripheral nerve injuries (PNI) can have several etiologies, such as trauma and iatrogenic interventions that can lead to the loss of structure and/or function impairment. These changes can cause a partial or complete loss of motor and sensory functions, physical disability, and neuropathic pain, what in turn can affect the quality of life. For those reasons, PNI is a major public health concern. This review aims to revisit the concepts associated with the PNI. First, the anatomy of the peripheral nerve is detailed to explain the different types of injury. Then, some of the available therapeutic strategies are explained, including surgical methods, pharmacological therapies, and the use of cell-based therapies alone or in combination with biomaterials in the form of tube guides. Nevertheless, even with the various available treatments, it is difficult to achieve a perfect outcome with complete functional recovery. This review aims to explain the urge for new approaches and to understand the methods to evaluate nerve regeneration in a One Health perspective. In vitro models followed by in vivo models are very important to be able to translate the achievements to human medicine.

(1) The purpose of this study was to compare the percentages of quarterly change for each of the variables analysed (height, weight, body fat percentage and muscle mass) as a function of the quarter in a sample of adolescent football players. (2) The sample consisted of young male football players of different categories belonging to a high-performance football academy, (more than 5 years in football and have spent 1 full year at the academy). (3) Two-way repeated measures ANOVA revealed for the anthropometric variable, P_value

The effect of individual and combined supplementation of FA and GPM on physiological variables, productive performance, and carcass characteristics of finishing pigs under heat stress conditions were investigated. Forty Yorkshire x Duroc pigs (80.23 kg) were individually housed and randomly distributed into 4 groups under a 2 x 2 factorial arrangement (n=10): Control (basal diet, BD); FA, BD + 25 mg FA; GPM, BD with 2.5% GPM; and MIX, BD with 25 mg FA and 2.5% GPM. Additives were supplemented for 31 days. The inclusion of FA or GPM did not modify rectal temperature and respiratory rate. An interaction effect (P <0.05) was observed on FI, while average daily gain (ADG) and feed conversion (FC) were not affected by treatments (P >0.05). The inclusion of FA improved hot and cold carcass weight and carcass yields, while the addition of GPM decreased the marbling (P <0.05), and GPM tended to increase loin area (P <0.10). GPM increased liver weight (p <0.05). The addition of GPM and FA can improve some carcass characteristics under heat stress conditions. It is necessary to continue investigating different levels of inclusion of GPM and FA, to demonstrate their potential growth promoting effect in finishing pigs.

Background: This work presents Com@Rehab, a technological patient-centred activity for individuals needing a physical rehabilitation approach and with a specific loss of functionality. Within this scope, this paper focuses on the description of the activity in virtual reality (VR), its components, design and user profile, and its versatility and future adaptability regarding different ages, pathologies and rehabilitation contexts. Methods: The VR activity has been customised according to the patient's clinical needs while replicating an activity of daily living, namely showering. In addition, to validate and get feedback on the developed system, a validation questionnaire was applied to a group of healthy individuals to test the efficiency of the technology that supports the VR activity. Results: Preliminary results show that 94% of the participants recommended the experience, the performance of the various components of the system was successfully implemented, participants quickly adhered to the VR technology, and the UI assistant’s functionality should be improved. Conclusion: This solution creates a more effective, interactive, humanised rehabilitation approach based on a Virtual Reality (VR) activity. The Com@Rehab Communication Module improves human-human and human-machine communication while contributing to health literacy.

Medical and translational scientific research requires the use of animal models as an initial approach to the study of new therapies and treatments, but when the objective is an exploration of translational potentialities, classical models fail to adequately mimic problems in humans. Among the larger animal models that have been explored more intensely in recent decades, small ruminants, namely sheep and goats, have emerged as excellent options. The main advantages associated to the use of these animals in research works are related to their anatomy and dimensions very similar to those of humans in most physiological systems, in addition to their low maintenance and feeding costs, tendency to be docile, long life expectancies and few ethical complications raised in society. The most obvious disadvantages are the significant differences in some systems such as the gastrointestinal, and the reduced amount of data that limits the comparison between works and the validation of the characterization essays. Despite everything, recently these species have been increasingly used as animal models for diseases in different systems, and the results obtained open doors for their more frequent and advantageous use in the future. The purpose of this review is to summarize the general principles related to the use of small ruminants as animal models, with focus on regenerative medicine, to group the most relevant works and results published recently and to highlight the potentials for the near future in medical research.

Objectives: To assess the short-term impact of a single global stretching session on plantar pressures and lumbar range of motion (RoM) over one week in sedentary university students. Design: A randomised controlled trial with two parallel groups. Participants: Sixty-four university students were randomly assigned to a stretching group or control group. The stretching group received a single session of global stretching and the control group remained seated for the same length of time as the stretching session. Main outcome measures: Lumbar RoM and plantar pressures were assessed before, immediately after, 48 hours after, and 7 days after intervention. Results: Group-by-time interaction was significant for lumbar lateral flexion (p = 0.044), right maximal pressure (p = 0.003), left maximal pressure (p = 0.008), right mean pressure (p = 0.025), left mean pressure (p = 0.002), and maximal pressure minus mean pressure in right foot (p = 0.007). The model with plantar pressures showed a significant difference for group-by-time interaction (p = 0.010).Conclusion: Global stretching seems to counteract the ill-effects of prolonged sitting up to seven days with respect to plantar pressure in standing without improving lumbar ROM

. (1) Background: The aim of this study was to verify the differences in body composition, power and lower limb muscle strength in futsal players from three competitive levels. (2) Methods: The study involved 68 players (24.26 ± 4.63 years), divided into three competitive levels: elite, sub-elite and amateur. To assess physical condition, we used the Inbody270, the ChronoJump and the Isokinetic Dynamometer and used the non-parametric Kruskal-Wallis test to compare the three independent variables. (3) Results: There were no differences in body composition between the players at the three competitive levels. With regard to lower limb muscle power and strength, the elite group showed, on average, better performance and capabilities, especially when compared to the amateur group, and all groups showed an H/Q ratio > 60%. (4) Conclusions: We conclude that there are not many differences in physical condition between the three competitive levels of futsal, despite the unequal sporting demands between them. However, the elite group has greater power and muscle strength, and both groups showed a high probability of lower limb muscle injury at this stage of the sporting season, alerting sports training professionals to the importance of individualized analysis of physical condition and performance capacity.

In the past decades, regenerative medicine applied on skin lesions has been a field of constant improvement for both human and veterinary medicine. The process of healing cutaneous wound injuries implicates a well-organized cascade of molecular and biological processes. However, sometimes the normal process fails and can result in a chronic lesion. In addition, wounds are considered an increasing clinical impairment, due to the progressive ageing of the population, as well as the prevalence of concomitant diseases, such as diabetes and obesity, that represent risk aggravating factors for the development of chronic skin lesions. Stem cells regenerative potential has been recognized worldwide, including towards skin lesion repair, Tissue engineering techniques have long been successfully associated with stem cell therapies, namely the application of 3D bioprinted scaffolds. With this review we intend to explore several stem cell sources with promising aptitude towards skin regeneration, as well as different techniques used to deliver those cells and provide a supporting extracellular matrix environment, with effective outcomes. Furthermore, different studies are discussed, both in vitro and in vivo, towards their relevance in the skin regeneration field.

This paper presents a review on numerical and experimental methods to predict fracture of ad-vanced high strength steels (AHSS). AHSS are widely processed through sheet metal forming processes. Although being an excellent choice when lightweight, high strength and ductility are critical factors, their multi-phase microstructure accentuates forming challenges. To accurately model forming behavior, necking based failure criteria as well as direct fracture models require improvements. As a necking based failure model, the conventional forming limit diagram/curve (FLD/FLC) presents limitations such as in estimating direct fracture (surface cracks, edge cracks, shear cracks), as well as deformation histories under nonlinear strain paths. Thus, significant re-search efforts are being made towards the needs of advanced fracture constitutive models capa-ble of predicting fracture scenarios without necking, more frequently observed in the realm of AHSS. Scientific community research is divided into several directions aiming at improving the forming and fracture behavior accuracy of parts subjected to sheet metal forming operations. In this review paper, a comprehensive overview on ductile fracture modeling is presented. Firstly, the FLD/FLC limitations modeling fracture behavior in sheet metal forming operations are stud-ied. Followed by the recent trends in constitutive material modeling. Afterwards, material char-acterization methods advancements to cover a broad range of stress states are comprised. Final-ly, damage and fracture models predicting failure in AHSS are investigated. This review paper supplies relevant information on the current issues the sheet metal forming community is chal-lenged with due to the trend towards AHSS employment in the automotive industry.

Two polyurethanes (PUs) were similarly synthesized by reacting a cycloaliphatic isocyanate with 1,4 butanediol and two polyols of different nature (polyester, polycarbonate diol) with molecular weights of 1000 Da. The PU made with polycarbonate diol polyol (YCD) was the only showing intrinsic self-healing at 20 °C. For assessing the mechanism of intrinsic self-healing of YCD, a structural characterization by molecular weights determination, infrared and X-ray photoelectronic spectroscopies, differential scanning calorimetry, X-ray diffraction, thermal gravimetric analysis and dynamic mechanical thermal analysis was carried out. It was concluded that the self-healing at 20 °C of YCD was due to non-covalent dynamic exchange interactions among the carbonate groups of the soft segments. Therefore, the chemical nature of the polyol played a key role in developing PUs with intrinsic self-healing at 20 °C.

The major histocompatibility complex (MHC) genes are the most polymorphic genes in vertebrates, and their proteins play a critical role in adaptive immunity for defense against a variety of pathogens. MHC diversity was lost in many species after experiencing a decline in size. To understand the variation and evolution of MHC genes in the Siberian ibex, Capra sibirica, which has undergone a population decline, we analyzed the variation of the second exon of MHC class II DRB genes in samples collected from five geographic localities in Xinjiang, China, that belong to three diverged mitochondrial clades. Consequently, we identified a total of 26 putative functional alleles (PFAs) with 260 bp in length from 43 individuals, and found one (for 27 individuals) to three (for 5 individuals) PFAs per individual, indicating the presence of one or two DRB loci per haploid genome. The Casi-DRB1*16 was the most frequently occurring PFA, Casi-DRB1*22 came after found in only seven individuals, 14 PFAs occurred once (7 PFAs twice), implying high frequency of rare PFAs. Interestingly, more than half of the (15) PFAs were specific to clade I, only one and three PFAs were specific to clades II and III, respectively. So, we assume that the polygamy and sextual segregation nature of this species likely contributed to the allelic diversity of DRB genes. Genetic diversity indices showed that PFAs of clade II were lower in nucleotide, amino acid, and supertype diversity compared to those of the other two clades. The way of allele sharing and FST values between three clades were to some extent in agreement with pattern observed in mitochondrial DNA divergence. In addition, recombination analyses revealed no evidence for significant signatures of recombination events. Alleles shared by clades III and the other two clades diverged 6 million years ago, and systematic neighbor grids showed cross-species polymorphisms. Together with the PAML and MEME analyses, the results indicated that the DRB gene in C. sibirica evolved under balancing and positive selection. However, by comparison, it can be clearly seen that different populations were under different selective pressures. Our results are valuable in understanding the diversity and evolution of the DRB gene in a mountain living C. sibirica and in making decisions on future long-term protection strategies.

The present study aimed to develop a mathematical model to estimate the performance of an indoor rowing event of 6000m through an 500 m all out test in junior athletes. We selected141 subjects from the Brazilian rowing confederation database (15.9 ± 1.0 years), subsequently randomised the sample to the development (~70%) and cross-validation (~30%) groups of the mathematical model. Performance data for 500m and 6000m were collected (there was a 48h washout between one test and anoth-er).Subsequently, the mathematical model: Time(min) 6000m = { [( Time(s) 500-m * 6) * 2] / 60} + 1.3, was developed by arithmetic modeling using machine learning and Regression analysis, being tested by intraclass correlation coefficient (ICC), Concordance correlation coefficient (CCC), Validity (Cb ), preci-sion (ρ) and bland-Altman plotting. The prediction of the result of 6000m through the mathematical model utilizando apenas o desempenho de 500m “all-out” test showed a significant reliability in de-velopment group (r2 = 0.730, ICC = 0.753; CCC = 0.895, Cb = 0.879, ρ: 0.957, pure error: 0.2 secounds (1.0% estimative error)); and in cross-validation group (r2 = 0.710, ICC = 0.747; CCC = 0.888, Cb = 0.875, ρ: 0.903, pure error: 0.3 secounds (1.4% estimative error)). When comparing the estimated re-sults of the 6000m performance by the mathematical model with the real performance of 6000m per-formed in indoor rowing, no statistical differences were observed. In addition, the mathematical model did not present a significant proportion bias in relation to the 6000 m performance in both groups. The mathematical model for predicting 6000m performance through a 500m fast test was significant for national level junior rowing athletes.

Open-vocabulary learning has recently gained prominence as a means to enable image segmentation for arbitrary categories based on textual descriptions. This advancement has extended the applicability of segmentation systems to a broader range of generally purpose scenarios. However, current methods often revolve around specialized architectures and parameters tailored to specific segmentation tasks, resulting in a fragmented landscape of segmentation models. In response to these challenges, we introduce OVAMTSeg, a versatile framework designed for Open-Vocabulary and Multitask Image Segmentation. OVAMTSeg harnesses adaptive prompt learning to empower the model to capture category-sensitive concepts, enhancing its robustness across diverse multi-task and scenario contexts. Text prompts are employed to effectively capture semantic and contextual features of the text, while cross-attention and cross-modal interactions enable the fusion of image and text features. Furthermore, a transformer-based decoder is incorporated for dense prediction. Extensive experimental results underscore the effectiveness of OVAMTSeg, showcasing its state-of-the-art performance and superior generalization capabilities across three segmentation tasks. Notable achievements include a 47.5 mIoU in referring expression segmentation, 51.6 mIoU on Pascal-VOC with four unseen classes, 46.6 mIoU on Pascal-Context in zero-shot segmentation, 65.9 mIoU on Pascal-5i, and 35.7 mIoU on COCO-20i datasets for one-shot segmentation.

We constrain two dynamical dark energy models that are parametrized by the logarithm form of $w(z)=w_{0}+w_{1}\left(\frac{\ln (2+z)}{1+z}-\ln 2\right)$ and the oscillating form of $w(z)=w_{0}+w_{1}\left(\frac{\sin(1+z)}{1+z}-\sin(1)\right)$. Comparing with the Chevallier-Polarski-Linder (CPL) model, the two parametrizations for dark energy can explore the whole evolution history of the universe properly. Using the current mainstream observational data including the cosmic microwave background data and the baryon acoustic oscillation data as well as the type Ia supernovae data, we perform the $\chi^2$ statistic analysis to global fit these models, finding that the logarithm parametrization and the oscillating parametrization are almost as well as the CPL scenario in fitting these data. We make a comparison for the impacts of the dynamical dark energy on the cosmological constraints on the total mass of active neutrinos. We find that the dark energy properties could significantly change the fitting results of neutrino mass. Looser constraints on $\sum m_{\nu}$ are obtained in the logarithm and oscillating models than those derived in the CPL model. Consideration of the possible mass ordering of neutrinos reveals that the most stringent constraint on $\sum m_{\nu}$ appears in the degenerate hierarchy case.

Different studies corroborate a role for ceramide synthases and their downstream products, ceramides, in modulation of apoptosis and autophagy in the context of cancer. These mechanisms of regulation, however, appear to be context dependent in terms of ceramides’ fatty acid chain length, subcellular localization, and the presence or absence of their downstream targets. Our current understanding of the role of ceramide synthases and ceramides in regulation of apoptosis and autophagy could be harnessed to pioneer the development of new treatments to activate or inhibit a single type of ceramide synthase, thereby regulating the apoptosis induction or cross talk of apoptosis and autophagy in cancer cells. Moreover, the apoptotic function of ceramide suggests that ceramide analogues can pave the way for the development of novel cancer treatments. Therefore, in the current review paper we discuss the impact of ceramide synthases and ceramides in regulation of apoptosis and autophagy in context of different types of cancers. We also briefly introduce the latest methods to analyze the lipids in biological samples. Finally, we discuss the drug development strategies focusing on the ceramide synthases and ceramides as future therapeutic approaches in cancer therapy.

Flood events are becoming more severe, causing significant problems to human communities, including physical, psychological, and material damage. For both flood forecasting in emergency response situations and flood mapping, georeferencing and data curation are paramount in the context of prevention or preparedness. Hence, data display, data management, and articulation with numerical simulation results must occur on GIS platforms. Our research is motivated by recent advances in Web and GIS technologies, social sensing and high-performance computing, and an envisaged wider availability of remote sensing data. This paper presents and discusses an innovative Web GIS platform named "RiverCure Portal" or "RCP" for short. This platform combines observations and hydrodynamic modelling tools to support various stages of the flood risk management cycle, including operational response, emergency preparedness, and risk assessment. RCP is a multi-organisation, multi-context digital platform with flexible configuration features to define and support multiple sensor types and modelling options, satisfying the various needs of different organisations and stakeholders. In addition, this paper discusses the RiverCure Approach, which encompasses the following tasks directly supported by the RCP platform: defining the context and involved geometries, associating sensors to the context, pre-processing and generating the context mesh, defining the simulation event, running the simulation event, and analysing the results from the simulation event. Thus, the RCP streamlines and simplifies data analysis and simulation procedures to meet decision-makers' needs. The novelties discussed in this paper include the design and discussion of a Web GIS platform that allows (i) to manage flood data and results of simulations at several contextual levels by different stakeholders such as domain experts, decision-makers, researchers, or students; (ii) to process and curate sensed data obtained from physical and social sensors; and (iii) update the state and values of the parameters of simulation tools through continuous data assimilation techniques for forecasting purposes. Finally, this paper supports the explanation and discussion with a running example, "Águeda 2016 flood" event, which dataset is publicly available for further study and experimentation.

Weight loss solutions are on the rise, and there is growing interest in natural alternatives to the pharmaceuticals in the market, which are not devoid of relevant side effects. To this end, the objective of the current study is to assess the effects of a botanical-based blend comprised of lemon verbena and hibiscus extracts in weight management, body fat, appetite, lipid, and glucose profiles, in an overweight population, for 90 days. As a result, the volunteers presented significant weight loss in absence of diet, which coincided with decreased body fat. Body fat was assessed by anthropometry, electrical bioimpedance and DEXA scan. Cholesterol levels were also significantly decreased. Satiety assessment revealed that the product contributed to increased feeling of fullness and satisfaction after a meal, compared to the placebo group, which could contribute to the weight loss observed. Blood glucose and blood pressure levels remained unchanged, which was expected as the volunteers were normoglycemic and their blood pressure was in the healthy range. In conclusion, daily supplementation of a botanical-based blend contributes to weight loss in overweight individuals, in absence of diet, while not affecting other parameters that are in the healthy range. This product could be a candidate alternative or add-on to other weight loss products, as part of a healthy lifestyle.

The most aggressive primary malignant brain tumor in adults is glioblastoma (GBM), which has poor overall survival (OS). There is a high relapse rate among patients with GBM despite maxi-mally safe surgery, radiation therapy, temozolomide (TMZ), and aggressive treatment. Hence, there is an urgent and unmet clinical need for new approaches to managing GBM. The current study identified modules (MYC, EGFR, PIK3CA, SUZ12, and SPRK2) involved in GBM disease through the NeDRex plugin. Furthermore, hub genes were identified in a comprehensive interaction network containing 7,560 proteins related to GBM disease and 3,860 proteins associated with signaling pathways involved in GBM. By integrating the results of the aforementioned analyses and performing centrality analysis again, eleven key genes involved in GBM disease were identi-fied. ProteomicsDB or Gliovis databases were used for determining the gene expression in normal or tumor brain tissue. The NetworkAnalyst and the mGWAS-Explorer tools identified miRNAs, SNPs, and metabolites associated with these 11 genes. Moreover, a literature review of recent studies revealed other lists of metabolites related to GBM disease. The enrichment analysis of iden-tified genes, miRNAs, and metabolites associated with GBM disease was done using ExpressAna-lyst, miEAA, and MetaboAnalyst tools. Further investigation of metabolite roles in GBM was done through the pathway, joint pathway, and network analyses. The results of this study identified 11 genes (UBC, HDAC1, CTNNB1, TRIM28, CSNK2A1, RBBP4, TP53, APP, DAB1, PINK1, and RELN), five miRNAs (hsa-mir-221-3p, hsa-mir-30a-5p, hsa-mir-15a-5p, hsa-mir-130a-3p, hsa-let-7b-5p), six metabolites (HDL, N6-acetyl-L-lysine, cholesterol, formate, N, N-dimethylglycine/xylose and X2. piperidinone) and 15 distinct signaling pathways that play an indispensable role in the GBM disease development. To establish early diagnostic methods and plan personalized GBM treatment strategies, the identified top genes-miRNAs and metabolite signatures can be targeted.

In pattern recognition domain, deep architectures are widely used nowadays and they have achieved fine grades. However, these deep architectures need special demands, especially big datasets and GPU. Aiming to gain better grades without deep networks, we propose a simplified algorithm framework using fusion features extracted from the salient areas of faces. Furthermore, the proposed algorithm has achieved a better result than some deep architectures. For extracting more effective features, this paper firstly defines the salient areas on the faces. This paper normalizes the salient areas of the same location in the faces to the same size, therefore it can gain more similar features from different subjects. LBP and HOG features are extracted from the salient areas, fusion features’ dimensions are reduced by Principal Component Analysis( PCA) and we apply softmax to classify the six basic expressions at once. This paper proposes a salient areas definitude method which uses peak expressions frames to compare with their neutral faces. This paper also proposes and applies the idea of normalizing the salient areas to align the specific areas which express the different expressions. This makes the salient areas found from different subjects have the same size. Besides, gamma correction method is firstly applied on LBP features in our algorithm framework which improves our recognition rates significantly. By applying this algorithm framework, our research has gained state-of-the-art performances on CK+ database and JAFFE database.

Soil amendments with composted organic materials are recommended to increase soil organic matter (SOM), promote soil fertility, and the Circular Economy. Growing areas of hedged olive groves in southern Iberia peninsula generate huge amounts of olive leaves whose potential as soil organic amendment is not fully studied. An experimental field trial in a hedged olive grove (cv. “Cobrançosa”) was set up near Portalegre, Portugal, to test a compost of olive leaves plus sheep manure (2:1) applied in the row, at soil surface. Three nominal rates (0 or control, 2.5 and 5.0 kg m-2) were used, in a complete randomized block setup (3 treatments, 3 replicas, 9 plots) and soil chemical properties of layers 0-5, 5-15, and 15-30 cm deep were annually monitored. Results (mainly in layer 0-5 cm) showed increases in total N, carbon of the particulate organic matter (POM-C), permanganate oxidizable carbon (POX-C), extractable phosphorus, and zinc, after one year, and increases in soil organic carbon (SOC), C-stock, pHKCl, extractable phosphorus, and zinc, after two years. POX-C was the most sensitive SOM-related indicator, showing increases up to 30 cm deep after one year. This compost improved soil fertility, but should be monitored over longer periods of time, namely for SOC and extractable zinc content.

Laser marking on polymer composite surfaces can be difficult to contrast and cause readability problems for electronic decoding equipment on production lines due to poor interaction between the laser and the fibres used to reinforce these materials. This problem can be solved with the right choice of marking parameters, resulting in savings for companies by avoiding production problems such as rejection, scrap and customer complaints. The present work uses the PBT/glass fibre composite used in the manufacture of instrument panels for motorcycles. The tests were carried out with different laser marking parameters using a Nd: YAG laser. Subsequently, the laser-marked DMC codes were analysed using a Verifier to evaluate the quality according to the ISO/IEC 29158:2020 standard. A detailed analysis of these surfaces was also carried out to observe some physical and chemical changes using SEM microscopy and EDS spectroscopy. The optical analysis showed that the lower the radiation power and pulse frequency and the higher the marking speed, the weaker the laser marking and therefore the poorer the DMC code quality, which was confirmed by the SEM. EDS spectroscopy showed that the laser marking process did not affect the chemical changes on the sample surface.

Power semiconductor devices are essential from the operation point of view, size, efficiency and cost, these components are used in a myriad of applications, providing features that make them an important part of the system in which they are operating. This document analyzes and compares the basic structure, properties, design aspects, as well as temperature performance, stability and switching losses, present in devices on silicon (Si), silicon carbide (SiC) and new generation devices fabricated in gallium nitride (GaN) applied in renewable energy systems. The main objective is determinate the viability of the new generation components, which present a superior performance in view of an increase in efficiency, conductivity, decreases in switching losses, lower resistances and parasitic capacitances as well as higher operating frequency range. Therefore demonstrating the GaN components are a strong and viable candidate to solve some of the problems present in renewable energy systems.

This study addresses the implementation of the International Financial Reporting Standard 9 (IFRS 9) in the European Union as of January 1, 2018, replacing the International Accounting Standard 39 (IAS 39) to introduce a new model for recognizing Loan Loss Provisions (LLP) based on Expected Credit Loss (ECL). This model responds to criticisms of the former Incurred Credit Loss (ICL) system for its inability to reflect credit losses in a timely manner, potentially exacerbating the effects of financial crises (Bushman & Williams, 2015; Gebhardt & Novotny-Farkas, 2011). The study focuses on the effects of adopting the ECL model on the level of Loan Loss Allowances (LLA) in loans, own equity, and the Common Equity Tier 1 (CET1) ratio across 13 Portuguese commercial banks. A mean comparison test is used to evaluate scenarios before and after the application of the ECL model, highlighting the importance of regulator actions and the adequacy of loss recognition policies, including the effects of Regulation (EU) 2017/2395 of December 12. The results obtained demonstrate significant negative impacts on the net values of loans, own equity, and the CET1 ratio upon adopting the IFRS 9 ECL model, due to the widespread increase in LLAs.

Brushless Synchronous Machines (BSM) are replacing conventional synchronous machines with static excitation in generation facilities due to the absence of sparking and lower maintenance. However, this excitation system makes challenging measuring electric parameters in the rotor. This fact highly difficult the detection of ground faults, which are the most common type of electrical fault in electric machines. In this paper, a ground fault detection method for BSM is proposed. It is based on an inductive AC/DC rotating current sensor installed in the shaft. In case of a ground fault in the rotating parts of the BSM, a fault current will flow through the rotor’s sensor, inducing voltage in its stator. Analyzing the frequency components of the induced voltage the detection of a ground fault in the rotating elements is possible. The ground faults detection method proposed covers the whole rotor and discern between DC and AC sides. To corroborate the detection method, experimental tests have been performed using a prototype of this sensor connected to laboratory synchronous machines achieving satisfactory results.

Fucoidan is a brown algae-derived polysaccharide having several biomedical applications. This study simultaneously compares the anticancer activities of crude fucoidans from Fucus vesiculosus and Sargassum filipendula, and effects of low (LMW, 10-50kDa), medium (MMW, 50-100kDa) and high (HMW, >100kDa) molecular weight fractions of S. filipendula fucoidan against osteosarcoma cells. Glucose, fucose and acid levels were lower and sulphation was higher in F. vesiculosus crude fucoidan compared to S. filipendula crude fucoidan. MMW had highest the levels of sugars, acids and sulphation among molecular weight fractions. There was a dose dependent drop in focal adhesion formation and proliferation of cells for all fucoidan-types, but F. vesiculosus fucoidan and HMW had the strongest effects. G1-phase arrest was induced by F. vesiculosus fucoidan, MMW and HMW, however F. vesiculosus fucoidan treatment also caused accumulation in sub G1-phase. Mitochondrial damage occurred for all fucoidan-types, however F. vesiculosus fucoidan led to mitochondrial fragmentation. Annexin V/PI, TUNEL and cytochrome c staining confirmed stress induced apoptosis-like cell death for F. vesiculosus fucoidan but features of stress-induced necrosis-like cell death for S. filipendula fucoidans. There was also variation in penetrability of different fucoidans inside the cell. These differences in anti-cancer activity of fucoidans are applicable for osteosarcoma treatment.

In recent years, video anomaly detection technology , which can intelligently analyze massive video and quickly find abnormal phenomena, has attracted extensive attention with the wide application of video surveillance technology . To address the complex and diverse problem of abnormal human behavior detection in surveillance videos, a surveillance video abnormal behavior detection and localization supervised method based on the deep network model and the traditional method is proposed. Specifically, we combined AGMM and YOLACT methods to obtain more accurate foreground information by fusing the foreground maps extracted by each technique. To further improve the accuracy , we use the PWC-Net technique to extract features of the foreground images and input them into an anomaly classification model for classification. The proposed method effectively detects and locates the abnormal behavior in the monitoring scene. In addition to the aforementioned methods, this paper also employs YOLOV5 and DeepSORT networks for object detection and tracking in the video, which allows us to track the detected objects for better understanding of the scene in the video. Experiments on the UCSD benchmark dataset and the comparison with state-of-the-art schemes prove the advantages of our method.

Caudal autotomy is a dramatic adaptation used by many lizard species to evade predators. Most studies to date indicate that caudal autotomy impairs lizard locomotor performance. Surprisingly, some species bearing the longest tails show negligible impacts of caudal autotomy on sprint speed. Part of this variation has been attributed to lineage effects. For the first time, we model the effects of caudal autotomy on the locomotor performance of a gymnophthalmid lizard, Micrablepharus atticolus, characterized by a long and bright blue tail. To improve model accuracy, we incorporated the effects of several covariates. We found that body temperature, pregnancy, mass, collection site, and the length of the regenerated portion of the tail were the most important predictors of locomotor performance in Micrablepharus atticolus. However, sprint speed was unaffected by tail loss. Apparently, the long tail of M. atticolus is more useful when using undulation amidst the leaf litter and not when using quadrupedal locomotion on a flat surface. Our findings highlight the intricate relationships among physiological, morphological, and behavioral traits. We suggest that future studies about the impacts of caudal autotomy among long-tailed lizards should consider the role of different microhabitats/substrates on locomotor performance, using laboratory conditions that closely mimic their natural environments.

By using the particle swarm optimization algorithm for crystal structure prediction, we reveal a newly orthorhombic Cmcm structure of HfB4, which is more energetically superior to the previously proposed YB4-, ReP4-, FeB4-, CrB4-, and MnB4-type structures in the considered pressure range. The phonon dispersion and elastic constants calculations confirm that the new phase is dynamically and mechanically stable. The calculated large shear modulus (240 GPa) and high hardness (45.7 GPa) imply that the predicted Cmcm-HfB4 is a potential superhard material. Meanwhile, the directional dependences of the Young's modulus, bulk modulus, and shear modulus for HfB4 are systematically investigated. Further analyses of the density of states and electronic localization function indicate that the strong B-B and B-Hf covalent bonds greatly contribute to its high hardness and stability.

In recent years, researchers have paid increasing attention on hyperspectral image (HSI) classification using deep learning methods. To improve the accuracy and reduce the training samples, we propose a double-branch dual-attention mechanism network (DBDA) for HSI classification in this paper. Two branches are designed in DBDA to capture plenty of spectral and spatial features contained in HSI. Furthermore, a channel attention block and a spatial attention block are applied to these two branches respectively, which enables DBDA to refine and optimize the extracted feature maps. A series of experiments on four hyperspectral datasets show that the proposed framework has superior performance to the state-of-the-art algorithm, especially when the training samples are signally lacking.

Most research on colostrum quality and colostrum management focuses on maternal IgG transfer to the newborn calf. However, in addition to being a source of antibodies, colostrum has other components that influence passive immune transfer, nutrition, gut maturation, and thermoregulation. In this review, the constituents in the bovine colostrum, as well as their variation, are explored and it is discussed the biological role of colostrum on the newborn calf. Protein is the nutrient in higher concentration and fat is the nutrient with the most variation. There is a pronounced amplitude in the total solids content of colostrum, but the average concentration does not vary much between studies (24.7%). Bovine colostrum major components can vary with several factors, such as the region, season, breed, dry period length, and nutritional aspects of the dam. Bioactive components, cells, and microbiome variability are less understood, besides IgG. Regardless, they play crucial distinct roles in the physiological development of the newborn. However, a multi-interactive effect between these components, cells, and microorganisms is more likely to occur. Recently researched components in colostrum like miRNA, nucleo(t)sides, the milk fat globule membrane, oligosaccharides, minor proteins, and the microbiome are examples of promising interest areas of study.

In this article we present the design and development of T-Shirt prototypes that embed novel textile sensors for the capture of cardio and respiratory signals. The sensors are connected through textile interconnects to either an embedded custom designed data acquisition and transmission unit or to snap fastener terminals for connection to external monitoring devices. Prototypes with diverse approaches of integration are presented. The performance of the wearable systems is addressed in terms of signal-to-noise ratio amplitude and signal interference caused by baseline wander and motion artifacts, through laboratorial tests with subjects in standing and walking conditions. Performance tests were also conducted in Hospital environment using a T-Shirt prototype connected to a commercial 3-channel Holter monitoring device. The textile sensors and interconnects were realized with the assistance of an industrial 6-needle digital embroidery tool and their resistance to wear addressed with normalized tests of laundering and abrasion. The main aspects of the system´s design leading to major improvements and failure factors are discussed. Pathways and methods for the overall system´s optimization are highlighted.

This study investigated the adaptability of Dunaliella salina to different salinity levels, with emphasis on growth, pigment concentration, and desalination potential. It was found that among the 21 salinity levels, salinity 75 produced consistently favorable results in cell count (13.08 x 10³ ± 1.41 x 10³ cells/mL), dry biomass (2.46 ± 0.06 g/L), pigment content (chlorophyll a = 97.5 ± 0.1 µg/L, chlorophyll b = 123.6 ± 0.3 µg/L), and desalination (9.32 ± 0.47 reduction). Therefore, salinity 75 was selected for the final trial (scale-up), which revealed unanticipatedly high cell counts (58.96 x 10³ ± 535.22 cells/mL), with dry biomass weight being statistically different (higher) than the expected (4.21 ± 0.02 g/L) (p<0.0001), most likely due to high cell count and energy reserve storage for high salinity adaption in the form of bio-compounds. Pigment growth continued (chlorophyll a = 95.4 ± 2.2 µg/L, chlorophyll b = 128.1 ± 5.1 µg/L), indicating pigment production under salt stress. Notably, desalination did not occur in this stage, possibly due to the necessity for a bigger initial inoculate, prolonged exposure or bioaccumulation becoming the prevailing mechanism over desalination. Nevertheless, the trial highlights D. salina's strong adaptation to various salinity levels. This suggests a promising future in halophyte research, particularly in understanding the mechanisms that prevent salt accumulation in cells and how to overcome this barrier. Additionally, these results suggest that microalgae could be a viable resource in saline-rich environments unsuitable for conventional agriculture, promoting industrial adaptation to adverse conditions.

A macro network loading Model for multi-flow lines, time-varying and pedestrian congestion is proposed. The station hub is abstracted as a network of different types of nodes, and the flow of passengers at each node is calculated in real time for the purpose of simulating the hub's collection and distribution process. For correct transmission of passenger flow on heterogeneous networks, three types of indexes are proposed to distinguish the nodes, and then match the corresponding fundamental diagrams. This paper divides the update process of the dynamic network loading model into multiple processes by flow lines, and improves computational speed of DNL model. The proposed model is applied to the simulation of passenger flow collection and distribution in an actual hub station with multi-flow lines. The analysis results illustrate that the model can accurately reflect the realistic congestion facilities and explain the formation process of high-density areas. A rolling passenger flow control model based on optimal control theory is proposed. The effectiveness of the control model is verified based on simulation data.

To solve the problem of smooth switching between car-following model and lane-changing model, the Intelligent Driver Model (IDM) for a single lane was used to study the driver's behavior switching mechanism of normally following, generating intentions to change lanes, creating space and speed gains, and performing lane change. In the case of sufficient lane-changing space and speed gains, the ego vehicle's intention to change lane was considered to solve the switching boundary between car-following behavior and lane-changing behavior, which is also the IDM failure point. In the event that there is no lane-changing gains, the IDM was optimized by incorporating the constraint components of the target lane vehicles in conjunction with the actual motion state of the ego vehicle, and the Stepless Switching Intelligent Driver Model (SSIDM) was constructed. Drivers' natural driving information was collected and scenario mining was performed on structured roads. On the basis of the collected data, an elliptic equation was used to fit the behavior switching boundary, and the two component balance coefficients of the front and rear vehicles on the target lane were identified. According to the test set verification results, the Mean Square Error (MSE) of the SSIDM is 2.172, which is 57.98% less than that of the conventional single-lane IDM. The SSIDM can accomplish stepless switching comparable to driver's behavior between the car-following behavior and the lane-changing behavior, with greater precision than IDM.

Purpose: The treatment of renal fibrosis caused by long-term obstructive nephropathy is limited. The purpose of this study was to establish a mouse model of renal fibrosis with unilateral ureteral obstruction (UUO) and to treat it with exosomes derived from SIRT6 transfected urine-derived stem cells (USCs), which will determine whether exosomes have the effect of anti-fibrosis Methods: The renal fibrosis model of UUO mice was established by ligating unilateral ureter. USCs were extracted from human urine and transfected with SIRT6 lentivirus plasmid. The SIRT6-USCs-exosomes(SIRT6-USCs-exos) were collected and identified by transmission electron microscope, nanoparticle tracking analysis and western blot. SIRT6-USCs-exos were injected into the tail vein of mice and the renal tissue of mice was stained with HE. The relative gene expressions of α-SMA, E-cadherin and TGF-β1 were analyzed by RT-qPCR. Results: In this study, we successfully constructed the renal fibrosis model of UUO mice and hUSCs with overexpression of SIRT6. The SIRT6-USCs-exos significantly improved the renal fibrosis in UUO mice. The relative mRNA expressions of fibrosis-related genes α-SMA, E-cadherin and TGF-β1 in renal tissue were significantly down-regulated after SIRT6-USCs-exos treatment. Conclusion: Our results indicate that SIRT6-USCs-exos can effectively alleviate renal fibrosis caused by long-term obstructive nephropathy. The findings may be promising for dealing with renal fibrosis.

Objective: To evaluate the direct costs of treating patients with neuromyelitis optica spectrum disorders (NMOSD) in outpatient care, from a hospital and Unified Health System (SUS) perspective. Methods: Observational study with data collection by microfunding, carried out with patients diagnosed with neuromyelitis optics, treated at a university hospital, in the city of Rio de Janeiro. Mann-Whitney tests were performed to measure cost differences between patient groups by disease severity and analysis perspective. Results: Nine individuals with a median age of 48 years (IQR 30 - 59 years) were included. The median total costs for patients with greater severity from the perspective of the SUS and the hospital were R$ 21,638.22 (IIQ: R$ 15,614.63; R$ 25,985.32) and R$ 32,094.11 (IIQ: R$ 25,610 .60; R$ 38,617.25) respectively. For patients with moderate severity the median was R$ 7,339.85 (IIQ: R$ 6,235.45; R$ 11,912.05) from the SUS perspective and R$ 11,505.80 (IIQ: R$ 7,339.85; R$ 22,424.76) from the perspective of the hospital, where the use of medications had a major impact. Conclusion: The main cost drivers were medicines, especially those used off-label, and procedures.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

OBJECTIVE: Analyzing the effects of different physical exercise programs on the anthropometric, cardiovascular, metabolic, and strength variables of the elderly participating in health care programs. METHODS: Controlled clinical trial, with 60 elderly participants from health care groups, allocated into four groups: Group of resistance exercises in open-air gyms – GT1 (n = 17); Group of aerobic and localized exercises - GT2 (n = 11); Group of resistance exercises at GT3 gym (n = 17); Control group: non-exercise practitioners - CG (n = 15). Anthropometric (BMI, % body fat, and waist circumference), cardiovascular (SBP, DBP, HR, and DP), metabolic (total cholesterol, triglycerides, and glycemia), and strength variables were evaluated before and after 16 weeks of intervention. Descriptive statistics, Shapiro-Wilk and Kolmogorov-Smirnov normality test, equal variance test, T-Student test, non-parametric Mann-Witney test, ANOVA One Way, multivariate data analysis using data mining and machine learning techniques, Pearson and Spearman correlation tests, Classical Clustering (Agglomerative Hierarchical Method); Principal Component Analysis (PCA), Z score, Fruchterman-Reingold algorithm, Euclidian Similarity Index and, Cohen’s equations were applied. RESULTS: To observe effect size, morphofunctional variables for the GT1 group show a small effect for fat percentage, WHR, and ULS and a medium effect for LLS. For the GT2 group, there was a small effect for fat percentage, WHR, and ULS and a large effect for LLS. For the GT3 group, there was a small effect for the percentage of fat and HC, a medium effect for ULS, and a large effect for LLS. A small effect for glycemia in GT1, a medium effect for glycemia and triglycerides for GT2, a small effect for total cholesterol for GT3, and a large effect for glycemia in CG, with this effect being an increase in this analyte. For the cardiovascular variables, there is a small effect for SBP and HR in GT1, a small effect for DBP, HR, and DP, and a large effect for SBP in GT2, a small effect for SBP, DBP, and HR in GT3 and small effects for SBP and HR in CG. The correlation between BMI (P = 0.0007) and Body Fat% (P = 0.007) with ULS. The variables TG, LLS, and ULS were the ones that differed most in each type of stimulus chosen as an intervention in the present study. CONCLUSIONS: The results of this study indicate that GT2 caused more significant percentage reductions in body mass and BMI. However, GT3 caused greater fat percentage reduction. The GT2 caused the greatest decrease in waist circumference, while the GT3 caused the largest decline in hip circumference. The three groups induced an increase in strength (ULS and LLS). However, in ascending order, GT1 caused the smallest increase, GT2 an intermediate increase, and GT3 the greatest increase in strength, with considerable effects in GT2 and GT3. Finally, GT2 caused a greater percentage reduction in systolic blood pressure (large effect) and double product (small effect) than the other groups. The three methods proved to be efficient, but with particularities that may reflect the choice of one over another due to health conditions, objectives to be achieved, or characteristics of the patient at the time of their choice by the prescriber.

As consequence of COVID-19, millions of households suffered mobility restrictions and changes in their lifestyle during several months. The aim of this study was to evaluate the effects of COVID-19 home confinement in food habits, lifestyle and emotional balance of the Spanish population. This cross-sectional study used data collected via an anonymous online questionnaire during the last month before lockdown finished in Spain in a total of 675 participants. 38.8% of the respondents experienced weight gain while 31.1% lost weight during confinement. The increase in body weight was positively correlated with the age (Rs = 0.14, p &lt;0.05) and BMI (Rs = 0.20, p &lt;0.05). We also identified that 39.7% reported poorer quality sleep, it was positively correlated with BMI (Rs = -0.18, p &lt;0.05) and with age (Rs = -0.21, p &lt;0.05). 44.7% of the participants had not performed physical exercise during confinement with differences by sex (p &lt;0.05), by age (p &lt;0.05), by BMI (p &lt;0.05) and sleep quality (p &lt;0.05). According to emotional-eater questionnaire, 21.8% and 11% were classified as emotional eater and very emotional eater, respectively. We emphasize the importance of adopting a healthy lifestyle, as the COVID-19 pandemic nowadays is ongoing.

The essence of cross-modal generation and retrieval modeling for image-text interactions lies in semantic consistency. Among these, cross-modal representation alignment serves as the foundational requirement for achieving cross-modal semantic consistency. The crux of our proposed method entails the collaborative training of an image captioning model(referred to as the ’captioner’) and a pair of contrastive encoders for image-text matching(referred to as the ’concoder’). This synergistic approach yields concurrent enhancements in concoder’s performance, captioner’s proficiency, and cross-modal semantic coherence. We coin the proposed method as ‘ReCap’. To begin, we initialize the concoder through knowledge distillation from a pre-trained model. During the training process, we use the output of the initialized concoder as input to a residual attention network, jointly training it with the captioner to achieve semantic consistency. Subsequently, we iteratively update the concoder during the image-text momentum encoding phase using the residual attention network, creating a closed-loop for semantic consistency resolution. Upon completion of training, the concoder and captioner modules can be used independently to perform tasks related to cross-modal retrieval and cross-modal generation of text and images. In order to substantiate the efficacy of our proposed method, we initially conducted empirical experiments encompassing image-text retrieval and image captioning tasks, employing a widely recognized benchmark dataset, MSCOCO. Subsequently, we assessed the fine-grained cross-modal alignment performance of the concoder through an image classification task on the iNaturalist 2018 dataset. The achieved performance metrics notably surpassed those achieved by several incumbent state-of-the-art models, thus validating the proficiency of our method. Finally, motivated by the practical requirements of handling the nature conservation image data, we performed caption annotation for the iNaturalist 2018 dataset. Subsequently, we trained the ReCap on this annotated data. Experimental results demonstrate that our proposed method can maintain semantic consistency between cross-modal retrieval and image caption generation for species with similar visual features but distinct semantics. This achievement signifies a meaningful exploration in the field of cross-modal semantic consistency representation, holding significant practical value in the domain of biological research.

As a medical student (Granada University Medical School, Spain), interested in Pediatrics, expended countless hours at the hospital pediatric facilities and got to know many of the children and their medical problems. A particular case, still vivid on my mind, awaken my scientific curiosity. One day, walking and talking with a seven years old child he unexpectedly felt down unconscious with multiple, incontrollable and erratic muscular contractions involving face, body and extremities and salivating. I was overwhelmed thinking it was the child’ last hour. At the time, my knowledge of epilepsy was nil. Following the seizures, the child was up, talking and walking with me as if nothing has happened and without any knowledge of the event. What could have caused the brain motor cortex to suddenly discharge that amount of altered activity causing generalized and erratic muscular contractions remains inexplicable. I migrated to USA, become a Pediatric (Developmental) Pathologist and Director of the Pediatrics Autopsy Service (1962-1999) at the Dartmouth-Hitchcock Medical Center, New Hampshire. I carried out countless postmortem studied of children brains, normal (unaltered) as well as those altered by hemorrhagic, hypoxic-ischemic and/or traumatic damage. With an NIH Fellowship, I spend one year (1967-68) at the Cajal Institute (Madrid, Spain) studying Cajal’ old Golgi preparations and learning about the method. Some of my Golgi studies of children’ brains have been published: The Human Brain. Prenatal Development and Structure, Springer, Heidelberg, Germany, 2012. The present monograph explores the developmental neuropathology of selected perinatal cortical injuries through their acute, subacute and chronic stages. Including: a) how an altered neuronal activity evolves in a damaged cortical region; b) how it moves through the cortex (epileptic auras); and c) how it reaches the motor cortex to be discharged as erratic and incontrollable muscular contractions. Understanding these processes should provide insights into the pathogenesis of epilepsy secondary to perinatal brain damage.

In recent years, numerous approaches have been developed to comprehend the molecular altera-tions underlying thyroid cancer (TC) oncogenesis and explore novel therapeutic strategies for TC. It is now well established that the neurokinin-1 receptor (NK-1R) is overexpressed in cancer cells and that NK-1R is essential for viability of cancer cells. The binding of substance P (SP) to NK-1R in neoplastic cells plays a pivotal role in cancer progression by promoting neoplastic cell growth, protecting tumour cells from apoptosis, triggering invasion and metastasis through enhanced migration of cancer cells, and stimulating endothelial cell proliferation for tumour angiogenesis. Remarkably, all types of human TC (papillary, follicular, medullary, anaplastic), as well as met-astatic lesions, exhibit overexpression of SP and NK-1R compared to the normal thyroid gland. TC cells synthesize and release SP, which exerts its multiple functions through autocrine, para-crine, intracrine, and neuroendocrine processes, including the regulation of tumour burden. Con-sequently, the secretion of SP from TC results in increased SP levels in plasma, which are signifi-cantly higher in TC patients compared to controls. Additionally, NK-1R antagonists have demonstrated a dose-dependent antitumour action. They impair cancer cell proliferation on one side and induce apoptosis of tumour cells on the other side. Furthermore, it has been demonstrat-ed that NK-1R antagonists inhibit neoplastic cell migration, thereby impairing both invasiveness and metastatic abilities, as well as angiogenesis. Given the consistent overexpression of NK-1R in all types of TC, targeting this receptor represents a promising therapeutic approach for TC. Therefore, NK-1R antagonists, such as the drug aprepitant, may represent novel drugs for TC treatment.

This study investigates the intricate relationship between Venezuelan migration and urban growth in Colombia from 2018 to 2021. The study employs remote sensing data and social network metrics to uncover migration patterns and their impact on urban expansion. The methodology consists of three stages. Firstly, nighttime satellite imagery is used to analyze year-over-year urban growth in Colombia. Secondly, social network data estimates Venezuelan migration, overcoming challenges of underreporting and informal border crossings. Lastly, an econometric analysis explores the quantitative link between Venezuelan migration and urban growth, integrating socioeconomic variables to address endogeneity. The findings reveal the complex interplay of Venezuelan migration, socioeconomic factors, and urban growth. The study outlines remote sensing analysis, introducing the Anthropogenic Footprint Expansion Index (AFEI) to quantify urban growth. Facebook API data estimates migration trends and explores socioeconomic impacts on urban expansion. The analysis uncovers migration, poverty, aging, and urban population proportion as key factors affecting Colombia's urban landscape. Furthermore, the research underscores how Venezuelan migration affected short-term urban expansion pre- and post-COVID-19. Migration had a notable effect before the pandemic, but this influence waned afterward. The study highlights migration's short-term nature and emphasizes age demographics' role in medium-term dynamics.

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

Obesity is related to the establishment of chronic inflammation and metabolic diseases, but it can be positively influenced by the regular practice of physical activity. The study aimed to compare the anthropometric, metabolic, and inflammatory parameters of physically active Military Police Officers (MPOs) with those who are less physically active. Sixty male MPOs, low activity (n=28) and physically active (n=32) participated. The following parameters were measured: plasma cytokine levels, C-reactive protein (CRP) levels, circulating glucose triglyceride (TAG) and high-density lipoprotein cholesterol (HDL-C) levels, and plasma glutamic oxalacetate transaminase (GOT), glutamic-pyruvate transaminase (GPT), and gamma-glutamyl transferase (GGT) activities. The physically active group presented lower body fat and reduced TAG and IL-8 levels compared to the low activity group. Moreover, a negative correlation between SPE and SBP, DBP, BPM was detected for the physically active group (p<0.05) but not in the low activity group. Furthermore, the physically active group's work time (WT) values were not correlated with the important metabolic markers SBP, DBP, BPM, GLU, TAG (p>0.05) but could be in the low activity group (p<0.05). These findings highlight the fundamental protective role of physical activity in controlling body composition, subclinical inflammation, and cardiovascular risk in MPOs.

Background: Evidences on the effects of chemotherapy treatment cycles on measures of muscle, mental state, social and cognitive performance are scarce. Objective: To analyze the effects of chemotherapy cycles on muscle strength and activation, functional capacity, quality of life, fatigue and anxiety of women with breast cancer. Methods: Twenty-two women divided into a treatment group (n = 10; 46.6 ± 9.6 years) and control group (n = 12; 51.6 ± 7.0 years) participated in the study. Analysis of muscle performance, quality of life, fatigue and anxiety after the 2nd and 4th cycle of chemotherapy with anthracyclines and cyclophosphamide were performed in women with breast cancer (TRA) and compared to healthy women (CTR). Two-way ANOVA was used to compare the variance of the means and the significance level was set as p≤0.05. Results: Differences were found in the muscular activation of the vastus medialis between the groups at post time (p = 0.038), as well as in the sit and stand test in the baseline (p<0.001) and post moment (p<0.001). Functional capacity performance was different between baseline (p<0.001) and post-time (p<0.001) groups. Additionally, the TRA group worsened the quality of life in the domains of functional capacity (p<0.001) and limitation of physical aspects (p=0.002), besides presenting negative changes in fatigue. Conclusion: Anthracycline and cyclophosphamide chemotherapy cycles reduce muscular performance and affect biopsychosocial variables in women with breast cancer.

Construction and demolition waste (CDW) represents 1/3 of the weight of all-waste produced. Increasing their recycling and reutilization with recycled aggregates (RA) means closing the life cycle of construction materials. Research has been carried out on artificial aggregates from the exclusive crushing of structural concrete waste in selective demolitions (CDWRConc). This study analyses the use of recycled concrete as graded aggregate (GARConc) and in cement soil (CSRConc). The material complies with the requirements as a road base, although due to the low values of resistance to fragmentation these materials are adequate for use in sensitive road systems and other places such as urban roads and car parks. The sensitive road systems are infrastructures in places of great natural wealth and low traffic intensity, with an annual average of heavy vehicle traffic (AADTh) below 50 vhp/d. As soluble salt contents have been detected, additional waterproofing or drainage measures must be adopted to prevent water infiltration into the layers made up of CDWRHorm. Finally, the high initial values of UCS allow the temporary passage of light vehicles over CSRConc after 3 days.

While adequate for English-speaking users in the United States, as well as many Commonwealth countries and other English-speaking jurisdictions (e.g., Canada, Australia, New Zealand or South Africa among others), typing in Romance Languages (Spanish, French, Portuguese and Italian) by using a standard US-QWERTY Keyboard is not easy since it is not adapted to special characters such as accented vowels, tildes and cedillas or ligatures, used in Romance Languages. With regard to the International Layout, intended to enable access to the most common diacritics used in Western European Languages, the problem comes from the fact that accented vowels are spread throughout the Keyboard layout, and their uppercase versions need chord combinations which can require good manual dexterity. This paper will analyze how the Spanish or Portuguese Keyboards are the best options for these users since they are QWERTY-based and the most compatible ones for the different character sets in Spanish, French, Portuguese and Italian Languages.

Unpaid family caregivers might suffer losses in income as a result of care provision. Here we used data from the baseline survey of the China Health and Retirement Longitudinal Study to assess the relationship between hours of weekly caregiving provided to grandchildren/parents/parents-in-law and individual’s monthly employment income. Our study sample comprised 3,718 middle-aged Chinese adults who were of working age (45-60 years). For women and men separately, we used a likelihood-based method to determine a caregiving threshold in a two-stage Heckman selection procedure. Instrumental variables were used to rule out the endogeneity of caregiving hours. Our analysis revealed a negative association between caregiving and income for women that depended on a caregiving threshold of 63-hours per week. There was an absence of caregiving-income relationship among men. These results offer new insights into the opportunity costs of unpaid caregiving and support tailored policies to protect the financial well-being of female caregivers.

Lignin fibers typically influence the mixture performance of stone matrix asphalt (SMA), such as strength, stability, durability, noise level, rutting resistance, fatigue life, and water sensitivity. However, limited studies were conducted to analyze the influence of fibers on the percent voids in mineral aggregate in bituminous mixture (VMA) during the mixture design. This study analyzed the effect of different fibers and fiber contents on the VMA in SMA mixture design. A surface-dry condition method test and Marshall Stability test were applied on the SMA mixture with four different fibers (i.e., flocculent lignin fiber, mineral fiber, polyester fiber, blended fiber). The test results indicated that the bulk specific gravity of SMA mixtures and asphalt saturation decreased with the increasing fiber content, whilst the percent air voids in bituminous mixtures (VV), Marshall Stability and VMA increased. Mineral fiber had the most obvious impact on the bulk specific gravity of bituminous mixtures, while flocculent lignin fiber had a minimal impact. The mixture with mineral fiber and polyester fiber had significant effects on the volumetric properties, and, consequently, exhibited better VMA over the conventional SMA mixture with lignin fiber. Modified fiber content range was also provided, which will widen the utilization of mineral fiber and polyester fiber in the applications of SMA mixtures. The mixture evaluation suggested no statistically significant difference between lignin fiber and polyester fiber on the stability. The mineral fiber required a much larger fiber content to improve the mixture performance than other fibers. Overall, the results can be a reference to guide SMA mixture design.

Robotic systems have been widely used in various industries, so the security of communication between robots and their components has become an issue that needs to be focused on. As a framework for developing robotic systems, the security of ROS2 can directly affect the security of the upper-level robotic systems. Therefore, it is a worthwhile research topic to detect and analyze the security of ROS2. In this paper, we adopt a formal approach to analyze the security of the communication mechanism of ROS2. First, we use a state transition system to model the potential vulnerabilities of ROS2 based on the ROS2 communication mechanism and the basic process of penetration testing. Secondly, we introduce the CIA model on the basis of the established vulnerability model and use LTL to define its security properties. Then, we design and implement a vulnerability detection tool for ROS2 applications based on the vulnerability model and security properties. Finally, we experimentally test some ROS2-based applications, and the results show that ROS2 has vulnerabilities without additional protection safeguards.

Nowadays, hydropower is the principal renewable; however, climate change increases extreme events such as floods, droughts, erosion, and sedimentation of rivers that produce uncertainty in hydroelectric generation. Thus, this document aims to analyze the climate change projections in the hydropower systems of Ecuador based on data from 14 projects studying the scenarios ac-cording to the Shared Socioeconomic Pathways from the Intergovernmental Panel on Climate Change. The study period starts from 2010 to 2020 with historical data, collects the tendency, defines a database year, and then projects the scenarios to 2050. The quantitative methodology uses a statistic on Ecuador's hydropower obtained inflow time series to calculate the deviation over the last years and develop a model to simulate future generation. The results show that the hydropower in Ecuador is expected to decrease considerably through 2050 due to meteorological changes. In this calculation of the Shared Socioeconomic Pathways, the selected scenarios show a reduction in SSP5 of 11.5%, SP2 of 16.2%, and SSP4 of 18.2% to 2050, concluding that the oppor-tunities for hydroelectric production facing climate change are variable, but the challenges are broad. In Ecuador, the projections of hydropower plants represent a sensitive issue of their re-ductions, especially knowing that the country had an energy grid in 2020 that depended on 87% of hydroelectric production.

Functional articular cartilage regeneration remains an unmet medical challenge, increasing the interest for innovative biomaterial-based tissue engineering (TE) strategies. Hydrogels, 3D macromolecular networks with hydrophilic groups, present articular cartilage-like features such as high water content and load-bearing capacity. In this study, 3D porous polyethylene glycol diacrylate (PEGDA) hydrogels were fabricated combining the gas foaming technique and an UV-based crosslinking strategy. The 3D porous PEGDA hydrogels were characterized in terms of their physical, structural and mechanical properties. Our results showed that the size of the hydrogels pores can be modulated by varying the initiator concentration. In vitro cytotoxicity tests showed that 3D porous PEGDA hydrogels presented high biocompatibility both with human chondrocytes and osteoblast-like cells. Importantly, the 3D porous PEGDA hydrogels supported the viability and chondrogenic differentiation of human bone marrow-derived mesenchymal stem/stromal cells (hBM-MSCs)-based spheroids as demonstrated by the positive staining of typical cartilage extracellular matrix (ECM) (glycosaminoglycans (GAGs)) and upregulation of chondrogenesis marker genes. Overall, the produced 3D porous PEGDA hydrogels presented cartilage-like mechanical properties and supported MSC-spheroid chondrogenesis, highlighting their potential as suitable scaffolds for cartilage TE or disease modelling strategies.

Currently, the textile industry is a poorly automated sector, due in part to problems in the handling of deformable leather and textile parts during production operations. In this work, several problems in the handling process of leather and textile parts are addressed, introducing methods to increase the automation of the process. A pneumatic actuator designed to pick up textile or leather parts avoiding their deformation during transport has been developed. This actuator maximizes the number of gripping points to improve handling, making it more stable and efficient. Additionally, a vision system has been implemented in the part picking task which, in conjunction with the CAD information of the part, sends the modified gripping position of the part to the robot. This allows customized handling of each textile or leather part. Finally, validation tests have been carried out on this development, both in simulations and in laboratory conditions, demonstrating its viability and direct applicability in the production line.

Covid-19 is a disease caused by SARS-CoV-2, which has spread worldwide since the beginning of 2020. Several pharmaceutical and non-pharmaceutical strategies were proposed to contain the virus dissemination, including vaccination and lockdowns. One of the consequences of the pandemic was the denial or delay of access to convenient health care services, but also potentially the increase of adverse events within those services, like the number of hospital infections. Therefore, the main question here is: What happened to the performance and sustainability of hospitals? The main goal of this work was to test if the Portuguese public hospitals' performance has been affected by the SARS-CoV-2 pandemic. We used the Benefit-of-Doubt method integrated with the Malmquist Index to analyze the performance evolution over time. Then, we employed a multiple regression model to test whether some pandemic-related variables could explain the performance results. We considered a database of 40 Portuguese public hospitals evaluated from January 2017 to May 2022. The period 2017 to 2019 corresponds to the baseline (pre-pandemic), against which the remaining period will be compared (during the pandemic). We also considered fourteen variables characterizing hospital quality, divided into three main performance definitions (efficiency and productivity; access; safety and care appropriateness). As potential explanatory variables, we consider seven dimensions, including vaccination rate and the need for intensive care for Covid-19 infected people. Results suggest that Covid-19 pandemic features help explain the drop on access after 2020, but not the evolution of safety and appropriateness of care, which surpris-ingly increased the whole time.

This article aims to understand the domains and conceptual uses of contagion, its modalities and its effects, in its different historical contexts and meanings, as an expression of the process of interdependence between the positions and the different points of view of different actors involved in multiple scientific, moral, social and political challenges. Another objective focuses on understanding the process of collective management of contagion, disease and health, where prevention is an essential element of its objectives and justifications, its discursive order, as well as its practical activities.

In the present work we revise and extend the Characteristic Crystallographic Element (CCE) norm, an algorithm used to simultaneously detect radial and orientational similarity of computer-generated structures with respect to specific reference crystals and local symmetries. Based on the identification of point group symmetry elements, the CCE descriptor is able to gauge local structure with high precision and finely distinguish between competing morphologies. As test cases we use computer-generated monomeric and polymer systems of spherical particles interacting with the hard-sphere and square-well attractive potentials. We demonstrate that the CCE norm is able to detect and differentiate, between others, among: hexagonal close packed (HCP), face centered cubic (FCC), hexagonal (HEX) and body centered cubic (BCC) crystals as well as non-crystallographic fivefold (FIV) local symmetry in bulk 3-D systems; triangular (TRI), square (SQU) and honeycomb (HON) crystals, as well as pentagonal (PEN) local symmetry in thin films of one-layer thickness (2-D systems). The descriptor is general and can be applied to identify the symmetry elements of any point group for arbitrary atomic or particulate system in two or three dimensions, in the bulk or under confinement.

Genomic surveillance represents an important strategy for understanding evolutionary mechanisms, transmission profile, and infectivity of different SARS-CoV-2 variants. We assessed the epidemiological profile of 366 individuals who tested positive for SARS-CoV-2 from 29 municipalities in Rondônia between December 2021 to March 2022. Samples were collected, RNA was ex-tracted and screened using RT-qPCR for Alpha, Beta, Gamma, Delta and Omicron VOCs and viral quantification was performed. Sequences were analyzed for phylogeny, mutations and lineages. Of the samples analyzed, 93.71% were positive for the Omicron variant and 6.28% were positive for the Delta variant. The symptoms observed were cough, sore throat, and fever, with a mean duration of 5 days; no hospitalizations or deaths were reported. We noted that among the positive individuals, 51% had been immunized with two doses, 22% received three doses, 13% received one dose, and 13% were not immunized. Just 242 samples were amenable to analysis for alignment and phylogenetic characterization; corresponding to variants BA.1 and BA.1.1; a total of 120 mutations were identified, 36% of which were found in the S gene. In conclusion, there was a high frequency of mutations in the SARS-CoV-2 genome, but no record of clinical severity, demonstrating the positive effect of vaccination.

Because most of the recognized causes of superior gluteal nerve (SGN) injury are iatrogenic, detailed knowledge of the anatomy of the SGN is crucial to prevent its injury associated with surgical procedures. This study aims to describe the precise location of SGN or its branches at the greater sciatic foramen, measure the distances of these nervous structures to palpable bony landmarks, and evaluate the possible correlation between these parameters and pelvis size. Twenty human cadaveric hemipelvises were studied. After dissection to expose the SGN or its branches at the greater sciatic foramen, the distances from these nervous structures to the greater trochanter (GT), to the anterior superior iliac spine (ASIS), to the posterior superior iliac spine (PSIS), to the ischial tuberosity (IT), and to the greater sciatic notch were measured. We found that at the greater sciatic foramen the SGN emerges as a common trunk in 75% of hemipelvises, and already divided in its superior and inferior branches in 25% of hemipelvises. When the SGN exits the pelvis as a common trunk, it does so, in most cases, in contact with the bone at the apex of the greater sciatic notch or superior to it. The median distance from the SGN at the greater sciatic notch to the PSIS, ASIS, GT and IT is 7.6 cm, 10.9 cm, 7.5 cm and 10.8 cm, respectively. We found a positive correlation between some of the analyzed parameters and the size of the pelvis. The anatomical data of this study may serve as pivotal guides during orthopedic pelvic surgery, contributing to minimize SNG iatrogenic lesions with significant implications in the patient's quality of life.

Sociology and History as consolidated scientific and academic projects have maintained a peculiar and paradoxical relationship. The growing disciplinary and subdisciplinary specialization of these two sciences poses relevant epistemological and methodological challenges to face potential situations of isolation, fragmentation and enable the apology of an interdisciplinary perspective characterized by the historicity of social structures, actions and senses.Several types of reasons shape this diffuse process of approach/distinction between Sociology and History, namely, epistemological and methodological, disciplinary closure, academic, professional, configuring what can be called contained dialogues. This paper, starting from the sociological perspective of the authors, seeks to contribute to the reflection on the relevance of a scientific project aimed at affirming an interdisciplinary perspective that may foster the heuristic potentialities of both Sociology and History in the analysis of the complexity of social reality and human action.

Atrial fibrillation (AF) is a cardiac arrhythmia caused by electrophysiological anomalies in the atrial tissue, tissue degradation, structural abnormalities, and comorbidities. A direct relation exists between AF and altered mitochondrial activity resulting from membrane potential loss, contractile dysfunction, or decreased ATP levels. This review aimed to elucidate the role of mitochondrial oxidative mechanisms in AF pathophysiology, the impact of mitochondrial oxidative stress on AF initiation and perpetuation, and current therapies. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews. PubMed, Excerpta Medica Database, and Scopus were explored until June 2023 using "MESH terms." Bibliographic references from relevant papers were also included. Oxidative stress is an imbalance that causes cellular damage from excessive oxidation, resulting in conditions such as AF. An imbalance in reactive oxygen species production and elimination can cause mitochondrial damage, cellular apoptosis, and cardiovascular diseases. Oxidative stress and inflammation are intrinsically linked, and inflammatory pathways are highly correlated with the occurrence of AF. AF is an intricate cardiac condition that requires innovative therapeutic approaches. The involvement of mitochondrial oxidative stress in the pathophysiology of AF introduces novel strategies for clinical treatment.

A (2,6)-fullerene F is a 2-connected cubic planar graph whose faces are only 2-length and 6-length. Furthermore, it consists of exactly three 2-length faces by Euler's formula. The (2,6)-fullerene comes from Do\v{s}li\'{c}'s (k,6)-fullerene, a 2-connected 3-regular plane graph with only k-length faces and hexagons. Do\v{s}li\'{c} showed that the (k,6)-fullerenes only exist for k = 2, 3, 4 or 5, and some of the structural properties of (k,6)-fullerene for k = 3, 4 or 5 are studied. In this paper, we study the properties of (2,6)-fullerene. We obtain that the edge-connectivity of (2,6)-fullerenes is 2. Every (2,6)-fullerene is 1-extendable, but not 2-extendable. F is said to be k- resonant (k>0) if the deleting of any i (0=< i<= k) disjoint even faces of F results in a graph with at least one perfect matching. We have that every (2,6)-fullerene is 1-resonant. An edge set S of F is called an anti-Kekule set if F-S is connected and has no perfect matchings, where F-S denotes the subgraph obtained by deleting all edges in S from F. The anti-Kekule number of F, denoted by ak(F), is the cardinality of a smallest anti-Kekule set of F. We have that every (2,6)-fullerene F with |V(F)|>6 has anti-Kekule number 4. Further we mainly prove that there exists a (2,6)-fullerene F having f_{F} hexagonal faces, where f_{F} is related to the two parameters n, m.

Unpaid family caregivers must consider the economic trade-off between caregiving and paid employment. Prior literature has suggested labour force participation (LFP) to decline with caregiving intensity, but no study has evaluated this relationship by accounting for the presence of both kinks and discontinuities. Here we used respondents of the China Health and Retirement Longitudinal Study baseline survey who were non-farming, of working-age (aged 45-60) and had a young grandchild and/or a parent/parent-in-law. For women and men separately, a caregiving threshold-adjusted probit model was used to assess the association between LFP and weekly unpaid caregiving hours. Instrumental variables were used to rule out the endogeneity of caregiving hours. Of the 3,718 respondents in the analysis, for men, LFP was significantly and inversely associated with caregiving that involved neither discontinuities nor kinks. For women, a kink was identified at the caregiving threshold of 8 hours per week such that before 8 hours, each caregiving hour was associated with an increase of 0.0257 in the marginal probability of LFP, but each hour thereafter was associated with a reduction of 0.0014 in the marginal probability of LFP. These results have implications for interventions that simultaneously advance policies of health, social care and labour force.

Inside hippocampal circuits, neuroplasticity events that individual cells may undergo during synaptic transmissions occur in the form of Long Term Potentiation (LTP) and Long Term Depression (LTD). The high density of NMDA receptors expressed on the surface of the dendritic CA1 spines confers to hippocampal CA3-CA1 synapses, the ability to easily undergo NMDA-mediated LTP and LTD, that is essential for some forms of explicit learning in mammals. Providing a comprehensive kinetic model that can be used for running computer simulations of the synaptic transmission process is currently a major challenge. Here, we propose a compartmentalized kinetic model for CA3-CA1 synaptic transmission. Our major goal was to tune our model in order to predict the functional impact caused by disease associated variants of NMDA receptors related to severe cognitive impairment. Indeed, for variants Glu413Gly and Cys461Phe, our model predicts negative shifts in the glutamate affinity and changes in the kinetic behavior, consistent with experimental data. These results pinpoint to the predictive power of this multiscale viewpoint, which aims to integrate the quantitative kinetic description of large interaction networks typical of system biology approaches with a focus on the quality of few, key, molecular interactions typical of structural biology ones.

In recent years, the Chinese government pays more and more attention to agricultural development and ecological protection. While improving the cultivated land green use efficiency(CLGUE) is the key to promote the sustainable development of agriculture. This study aims to study the current situation and influencing factors of agricultural production from the perspective of green utilization efficiency of cultivated land. It takes 39 cities in the upper, middle and lower reaches of the Yangtze River basin in China as an example. The CLGUE values in those 39 cities from 2011 to 2020 were specifically measured, using the Super-SBM model, kernel density estimation and geographic detector method. Their temporal and spatial heterogeneity was described, and the influencing factors were detected at both single and interactive levels. The results showed that: （1）From 2011 to 2020, the green utilization efficiency value of cultivated land in the Yangtze River Basin showed an upward trend on the whole; （2）There is a clear spatial heterogeneity the CLGUE values in the Yangtze River Basin cities, as shown by: downstream region > midstream region > upstream region; (3) Cultivated land resource endowment, socioeconomic development, and agricultural production technology are important factors affecting the variability of CLGUE values. However, there are some differences in the degree and direction of influence of different influencing factors on different sample subgroups.

3,4-methylenedioxypyrovalerone (MDPV) is a new psychoactive substance (NPS) and the most widespread and life-threatening synthetic cathinone of the “bath salts”. Preclinical research has proven the cocaine-like psychostimulant effects of MDPV and its potential for abuse. Cannabidiol (CBD) is a non-psychotropic phytocannabinoid that has emerged as a new potential treatment for drug addiction. Here, we tested the effects of CBD (20 mg/kg) on MDPV (2 mg/kg)-induced conditioned place preference and MDPV (0.05 and 0.075 mg/kg/infusion) self-administration paradigm. We also assessed the effects of the combination of CBD, and MDPV (3 and 4 mg/kg) on anxiety-like behaviour using the elevated plus maze (EPM). CBD mitigated the MDPV-induced conditioned place preference. On the contrary, CBD administration throughout the MDPV (0.075 mg/kg/infusion) self-administration increased drug-seeking and taking behaviours, but only in the high-responders group of mice. Additionally, CBD exerted anxiolytic-like effects, but only in MDPV-treated mice. Taken together, our results indicate that CBD modulation of MDPV-induced motivational responses in mice vary depending on the requirements of the learning task, resulting in a complex response. More research attempting to decipher the behavioural and molecular interactions between CBD and MDPV is needed.

In this study, we discuss the thermospheric density response to the solar activity and QBO. By using the wavelet power spectrum method, the thermospheric density from 1967 to 2013 shows ~11-year period, semiannual and annual variations, while the seasonal variation is usually more significant under high solar activity conditions. Importantly, we investigate the possible link between the density and the QBO, with the aid of GAMDM model and different density residual method. As a result, the difference between the measured density and empirical model seemingly has QBO signal, but the ratio of them revels that the QBO signal does not exist in the thermospheric density. Comprehensively, we thought the stratospheric QBO cannot impact on the thermosphere, and more data and numerical modeling are needed for further validation.

Background: The purpose of this review is to clarify the natural course of Benign Paroxysmal Torticollis (BPT) and to update the relationship of this disorder with migraine. BPT belongs to a group of “episodic syndromes that may be associated with migraine” and is diagnosed when according to diagnostic criteria of the International Classification of Headache Disorders, 3rd edition. It is present in infants and young children and it is an underdiagnosed manifestation, because it is not well recognized and in most cases with a benign evolution, but requires careful differential diagnosis. It was first described by Snyder in 1969 as a movement disorder, a cervical dystonia consequent to labyrinthic disorder.Materials and methods: The PubMed and Web of Science databases were consulted from 1968 to 2024, according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines ,2020.( PRISMA)Results: 113 articles were identified, 86 selected and 20 considered for the purpose of this review. The clinical studies were considered in relation to evolution, cognitive and motor development, to genetic and not genetic etiology, to the relationship with migraine with and without aura, vestibular migraine, hemiplegic migraine, and paroxysmal vertigo.

Autonomous driving systems are increasingly becoming a necessary trend towards building smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional end-to-end system, such as object detection, tracking, path planning, sentiment or intent detection. Nevertheless, few efforts have been made to systematically compile all of these systems into a single proposal that effectively considers the real challenges these systems will have on the road, such as real-time computation, hardware capabilities, etc. This paper has reviewed various techniques towards proposing our own end-to-end autonomous vehicle system, considering the latest state on the art on computer vision, DSs, path planning, and parallelization.

Camelina (Camelina sativa L.) is an oilseed with potential for use as a raw material in second-generation biofuels. Camelina has a seed yield of up to 2380 kg ha^-1 and contains around 45% fatty acids. Selection of a suitable site is critical for production optimization. The objective of this study was to determine Chilean agro-climatic suitability for establishing camelina as a productive alternative. Climate and soil requirements and geographical restraints were evaluated for the species, considering the climatological characteristics of its regions of origin, as well as regions where camelina is successfully grown in the rest of the world. The variables considered include factors (maximum temperatures of the warmest month, water deficits, and degree days) and limitations (altitude, geomorphology, and current land use), which permitted the evaluation of the national territory for a certain level of suitability. It was determined that 1.3% of the national territory (960,664 ha) has some degree of suitability for camelina adoption. Between the Biobío and Los Lagos regions, 49.0% of land (471,203 ha) is in the category of without thermic restrictions, with mild water restrictions, and mild soil restrictions or without information, which can be used for camelina production. The Los Ríos region had 21.4% surface area (321,176 ha) with some level of suitability for camelina, the most suitable region to establish this crop in Chile.

This research provides a computationally efficient numerical tool for predicting 3-D turbulent flows over hydrofoils. It addresses a gap in existing numerical methods by extending the capabilities of the laminar VIScous Vorticity Equation (VISVE) solver to handle 3-D turbulent flow scenarios. The implementation integrates the k − ω SST model into the 3-D VISVE solver using the Finite Volume Method (FVM), extending its capability to handle turbulent flows. The turbulence model is also parallelized to improve computational efficiency. The application of the newly developed model to 3-D hydrofoil cases expands its scope and serves as preparatory work for future rotational propeller applications. Rigorous testing includes a convergence analysis concerning grid numbers and time step sizes, and validation against a Reynolds-Averaged Navier-Stokes (RANS) solver ensures the reliability and accuracy of the enhanced VISVE solver for turbulent flow simulations. The turbulent VISVE solver offers advantages such as reduced computational domain and costs through a vorticity-based approach. Turbulence concentration within boundary layers and free shear flows does not compromise the advantages of the small computational domain. The simplified meshing process, automatically generated by denoting the number of panels on the hydrofoil, makes the solver accessible for researchers and engineers.

The ZX Spectrum was a popular 8-bit home computer by Sinclair Research in the 80s. Even though some of these computers may still work, the audio tapes, the TV with an analog tuner and the micro-switch joystick, used with the original ZX Spectrum, nowadays are outdated and hard to find in good working order or replicate. Since many other old closed systems are also very difficult to update to support modern peripherals, there is a necessity to provide a methodology to adapt such systems to support new peripherals while being compatible with existing software. The work proposed in this paper is focused on recreating a ZX Spectrum+/48k computer and interface it with modern peripherals on an FPGA. This is accomplished by adding a co-processor to assist with the control of the new peripherals which would either require to complex architectural changes to the original system and in the end it would perform poorly due to the low performance of the Z80 CPU. This work distances from previous ones on emulating a ZX Spectrum since it focuses on the use of different upgraded peripherals and the use of a NIOS II soft-processor as a co-processor to manage the SD Card accesses. A demonstration of the proposed modernized architecture was made by successfully running a diagnostics ROM and playing original ZX Spectrum games from an SD card for game with a PS/2 keyboard and a pair of joysticks.

As a stimulus signal, coded electrical signals can control the motion behavior of animals, which has been widely used in the field of animal robots. In current research, most of the stimulus signals used by researchers are traditional waveform, such as square waves. To enrich the stimulus waveform, a wireless animal robot stimulation system based on neuronal electrical signal characteristics is presented in this paper. The stimulator uses the CC1101 wireless module to control animal behavior through brain stimulation. The LabVIEW-based graphical user interface(GUI) can manipulate brain stimulation remotely while the stimulator powered by battery. Additionally, the spikes of animals have been simulated by this system through Direct Digital Synthesizer(DDS) algorithm. The GUI enable users to customize the combination of these analog spike signals. The recombined signals are sent to the stimulator through CC1101 as stimulus signals. In vivo experiments conducted on five pigeons verified the efficacy of the stimulation mechanism. The analog spike signal with an amplitude of 3-5V successfully caused the pigeon’s turning behavior. The feasibility of the analog spike signals as stimulus signals was successfully verified. Increased the diversity of stimulus waveform in the field of animal robots.

The utilization of primary school buildings is multifaceted, primarily due to the high occupancy density, varying thermal preferences among occupants, diverse indoor activities (such as walking, sports, and conversation), and a constant flow of individuals entering and exiting the building. This results in frequent opening and closing of external windows and doors and fluctuations in internal heat gain. Consequently, frequent interactions between the indoor and outdoor microenvironments lead to energy losses. This study conducts a comprehensive literature review on building energy loss stemming from occupant behavior and the interactions between indoor and outdoor microenvironments. Furthermore, it proposes a dynamic real-time monitoring system based on a computer data capture and visualization platform foundation for building energy loss. The research methods include data crawling, data association rule mining, and data association analysis. The research findings yield a universally applicable and informative building energy-saving design theory based on extensive data analysis. Additionally, the system presents information on occupants' behavior and the microclimate data of indoor and outdoor environments on a computer screen, facilitating human-machine communication and enabling timely adjustments to design strategies for new buildings and operation and maintenance strategies for existing buildings.

Drowning remains a prominent global pediatric health concern, necessitating preventive measures such as educational initiatives for children and caregivers. This study aimed to assess the feasibility and educational effectiveness of an interactive puppet show centered on water safety for children and parents. A 30-minute original theater performance, featuring two actors and three puppets (a girl, a crab, and a lifeguard), was conducted. Subsequently, 185 children (aged 4 to 8) and their 160 parents (134 mothers and 26 fathers) participated in this quasi-experimental study. Pre- and post-show tests were administered to evaluate knowledge and behaviors in aquatic environments. Prior to the puppet show, 78% of children exhibited basic aquatic competency. Only 33% considered swimming alone risky. Following the intervention, 81.6% of children changed their perception of the risks of solo beach activities, showing improved knowledge of emergency number activation (from 63.2% to 98.9%, p&lt;0.001). The intervention increased parents' intention to visit lifeguard-patrolled beaches and improved their CPR knowledge for drowning victims by 58.8%. In conclusion, a drowning prevention puppet show positively impacts children and parents, potentially enhancing safety behaviors during water-related leisure activities, warranting consideration as part of comprehensive drowning prevention strategies.

This paper presents high-resolution digital measurements at low cost, combining oversample and averaging. Experiments of processing data between samples and between multiple temperature sensors in the same environment are conducted. They provide results with effective increase in the analog to digital converter bits, in correspondence with the minimization on the effects of noise. It is shown that averaging a set of small, low-cost sensors at a small microcontroller can give flexible access to improved measurement accuracy.

The European mink (Mustela lutreola) is one of Europe's most endangered species, and it is on the brink of extinction in the Iberian Peninsula. The species' precarious situation requires the application of new ex-situ conservation methodologies that complement the existing ex-situ and in-situ conservation measures. Here, we report for the first time the establishment of a biobank of European mink mesenchymal stem cells (emMSC) and oocytes from specimens found dead in the Iberian Peninsula, either free or in captivity. New emMSC lines were isolated from different tissues: bone marrow (emBM-MSC), oral mucosa (emOM-MSc), dermal skin (emDS-MSC), oviduct (emO-MSc), endometrium (emE-MSC), testicular (emT-MSC), and adipose tissue from two different adipose depots: subcutaneous (emSCA-MSC) and ovarian (emOA-MSC). All the eight emMSC lines showed plastic adhesion, detectable expression of characteristic markers of MSCs and, when cultured under osteogenic and adipogenic conditions, differentiation capacity to these lineages. Additionally, we were able to keep 227 Cumulus-oocyte complexes (COCs) in the biobank, 97 of which are grade I or II. The European mink MSC and oocyte biobank will allow for the conservation of the species' genetic variability, the application of assisted reproduction techniques, and the development of in vitro models for studying the molecular mechanisms of infectious diseases that threaten the species' precarious situation.

Mannosylerythritol lipids (MELs), one of the most promising biosurfactants (BS), are glycolipids produced by yeasts or fungi, with great environmental performance and a high compatibility with the human body. MELs besides working as typical surfactants, can form diverse structures when in the critical aggregation concentration (CAC), reducing the surface tension of water and other solutions, and being stable over a wide range of conditions. Among others, MELs present anti-microbial, antitumor, antioxidant and anti-inflammatory activity, skin and hair repair capacity, which opens possibilities for their use in applications from cosmetics and pharmaceutics to bio-remediation and agriculture. However, their market share is still low when compared to other glycolipids, due to their less developed production process and higher production cost. This re-view gathers information on the potential applications of MELs mentioned on the literature since 1993. Furthermore, it is also explored the current strategies being developed to enhance the market presence of MELs, in parallel with the ones developed for rhamnolipids and sophorolipids.

The Textile and Clothing (T\&C) value chain is one of the most polluting in the world and one that produces the most waste. It is, therefore, important to encourage the Circular Economy (CE) model in this sector, to reduce pollution and mitigate the effects of waste production, and consequently increase environmental sustainability. For that, the involvement of the final consumer is essential. And, the final consumer's use of an Eco-gamified application for registering and promoting Consumer-to-Consumer (C2C) and Consumer-to-Business (C2B) activities, which extends the life time of textile products, is of utmost importance. In this article, we survey gamification frameworks for analyzing system design level techniques that enable engaging the final consumer in the CE process. Then, we select and use one of such frameworks, Gameful Design Heuristics (GDH), for defining the gamification structure needed to implement on a Business-to-Consumer-to-Consumer (B2C2C) context of a circular economy. As result, we present a B2C2C circular business process model for the T\&C value chain, and propose the design model of a gamified platform for the final consumers, which allows them to register the C2B and C2C activities, from the circular value chain's business process, and benefit from a game-like experience. All model features have been mapped to GDH framework heuristics, validating that it is possible to support a set of defined heuristics of applied gamification for promoting CE in the T\&C value chain.

Glucose is a simple sugar molecule. The sugar molecule is chemically symbolised as C6H12O6. This means that the glucose molecule contains 6 carbon atoms (C), 12 hydrogen atoms (H) and 6 oxygen atoms (O). In human blood, the molecule glucose circulates as blood sugar. Normally after eating or drinking, our body breaks down the sugars in food and uses them to obtain energy for our cells. To do this, our pancreas produces insulin. Insulin "pulls" sugar from the blood and puts it into the cells for use. If someone has diabetes, their pancreas can't produce enough insulin. As a result, the level of glucose in the blood rises. This can lead one to many potential complications, including blindness, disease, nerve damage, amputation, stroke, heart attack and damage to blood vessels etc. In this study, a non-invasive method for monitoring blood glucose has been developed and is therefore easily usable. The device developed can measure the glucose level continuously and eliminates the disadvantages of the invasive system. Near-IR sensors (optical sensors) were used to estimate the concentration of glucose in the blood; these sensors have a wavelength of 940 nm. The sensor is placed on the tip of the finger and the output of the optical sensor is then connected to the microcontroller at the analogue input. Another sensor used, but only to provide more medical information was the heartbeat sensor. After processing and regression analysis, the glucose level is predicted, and data is sent via the Bluetooth network to a developed APP. The results of the implemented device were compared with available invasive methods. The study consists of a hardware platform inserted into an armband and then a small black parallelepiped-shaped box in which the optical sensors are inserted. The hardware consists of a microcontroller, a Near-IR optical sensor, a heartbeat sensor and a Bluetooth module.

Iapetus, a Saturn moon, shows the most differentiated albedo dichotomy of the Solar System. The dark leading side has a lower albedo than the bright trailing side. Spectral data on the visible light reveal the existence of two types of materials on the surface. The darkening in the leading side is thought to be originated by the presence of organic material and carbonaceous compounds on surface, while the trailing side is covered by water ice due to migration processes from the dark side. On airless bodies like Iapetus, the surface escape speed is greater than the speed of water molecules, resulting in the retention of a H2O atmosphere that allows some species to get diffused through it. Here, there were performed simulations of the evolution of the surface temperature for each of the two hemispheres of Iapetus. The results showed a slow yet steady increment of temperatures for both sides, with a steeper slope for the dark hemisphere. It was also simulated how much energy budget can be accumulated in both sides and its consequences. Finally, we calculated the diffusion coefficients for ammonia, methane, and water ice. The results let us infer how these compounds could evolve over time.