Search results for: Armando Luis Vieira

Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Lívia Pimentel Sant'ana Dourado, Raquel Das Neves Almeida, Luís Henrique Costa Corrêa Neto, Nayara Soares, Kelly Grace Magalhães

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Introduction: Obesity and high-fat diet intake have a crucial impact on immune cells and inflammatory profile, highlighting an emerging realization that obesity is an inflammatory disease. In the present work, we aimed to characterize the role of caspase-1/11 and NLRP3 inflammasome in the establishment of mice obesity and modulation of inflammatory lipid metabolism induced by high fat diet intake. Methods and results: Wild type, caspase-1/11 and NLRP3 knockout mice were fed with standard fat diet (SFD) or high fat diet (HFD) for 90 days. The weight of animals was measured weekly to monitor the weight gain. After 90 days, the blood, peritoneal lavage cells, heart and liver were collected from mice studied here. Cytokines were measured in serum by ELISA and analyzed in spectrophotometry. Lipid antigen presentation molecule CD1d expression, reactive oxygen species (ROS) generation and lipid droplets biogenesis were analyzed in cells from mice peritoneal cavity by flow cytometry. Liver histopathology was performed for morphological evaluation of the organ. The absence of caspase-1/11, but not NLRP3, in mice fed with HFD favored the mice weight gain, increased liver size, induced development of hepatic steatosis and IL-12 secretion in mice compared to mice fed with SFD. In addition, caspase-1/11 knockout mice fed with HFD presented an increased CD1d molecule expression, as well as higher levels of lipid droplets biogenesis and ROS generation compared to wild type mice also fed with HFD. Conclusion: Our data suggest that caspase-1/11 knockout mice have greater susceptibility to obesity as well as increased activation of lipid metabolism and inflammatory markers.

Keywords: caspase 1, caspase 11, inflamassome, obesity, lipids

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Authors: Daniel F. Bohorquez, Luis M. Agudelo, Henry H. León

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Heart rate variability (HRV) is defined as the temporary variation between heartbeats or RR intervals (distance between R waves in an electrocardiographic signal). This distance is currently a recognized biomarker. With the analysis of the distance, it is possible to assess the sympathetic and parasympathetic nervous systems. These systems are responsible for the regulation of the cardiac muscle. The analysis allows health specialists and researchers to diagnose various pathologies based on this variation. For the acquisition and analysis of HRV taken from a cardiac electrical signal, electronic equipment and analysis software that work independently are currently used. This complicates and delays the process of interpretation and diagnosis. With this delay, the health condition of patients can be put at greater risk. This can lead to an untimely treatment. This document presents a single portable device capable of acquiring electrocardiographic signals and calculating a total of 19 HRV metrics. This reduces the time required, resulting in a timelier intervention. The device has an electrocardiographic signal acquisition card attached to a microcontroller capable of transmitting the cardiac signal wirelessly to a mobile device. In addition, a mobile application was designed to analyze the cardiac waveform. The device calculates the RR and different metrics. The application allows a user to visualize in real-time the cardiac signal and the 19 metrics. The information is exported to a cloud database for remote analysis. The study was performed under controlled conditions in the simulated hospital of the Universidad de la Sabana, Colombia. A total of 60 signals were acquired and analyzed. The device was compared against two reference systems. The results show a strong level of correlation (r > 0.95, p < 0.05) between the 19 metrics compared. Therefore, the use of the portable system evaluated in clinical scenarios controlled by medical specialists and researchers is recommended for the evaluation of the condition of the cardiac system.

Keywords: biological signal análisis, heart rate variability (HRV), HRV metrics, mobile app, portable device.

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Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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Authors: Juan José Mesas, Luis Sainz

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The motivation for the development of this paper lies in the need for energy networks to reduce losses, improve performance, optimize their operation and try to benefit from the interconnection capacity with other networks enabled for other energy carriers. These interconnections generate interdependencies between some energy networks and others, which requires suitable models and methods for their analysis. Traditionally, the modeling and study of energy networks have been carried out independently for each energy carrier. Thus, there are well-established models and methods for the steady-state analysis of electrical networks, gas networks, and thermal networks separately. What is intended is to extend and combine them adequately to be able to face in an integrated way the steady-state analysis of networks with multiple energy carriers. Firstly, the added value of multi-energy networks, their operation, and the basic principles that characterize them are explained. In addition, two current aspects of great relevance are exposed: the storage technologies and the coupling elements used to interconnect one energy network with another. Secondly, the characteristic equations of the different energy networks necessary to carry out the steady-state analysis are detailed. The electrical network, the natural gas network, and the thermal network of heat and cold are considered in this paper. After the presentation of the equations, a particular case of the steady-state analysis of a specific multi-energy network is studied. This network is represented graphically, the interconnections between the different energy carriers are described, their technical data are exposed and the equations that have previously been presented theoretically are formulated and developed. Finally, the two iterative numerical resolution methods considered in this paper are presented, as well as the resolution procedure and the results obtained. The pros and cons of the application of both methods are explained. It is verified that the results obtained for the electrical network (voltages in modulus and angle), the natural gas network (pressures), and the thermal network (mass flows and temperatures) are correct since they comply with the distribution, operation, consumption and technical characteristics of the multi-energy network under study.

Keywords: coupling elements, energy carriers, multi-energy networks, steady-state analysis

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Authors: Javier Comes Fayos, Isabel Rodríguez Moreno, Sara Bressanutti, Marisol Lila, Angel Romero Martínez, Luis Moya Albiol

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Empathy is a cognitive-affective capacity whose deterioration is associated with aggressive behaviour. Deficient affective processing is one of the predominant risk factors in men convicted of intimate partner violence (IPV perpetrators), since it makes their capacity to empathize very difficult. The objective of this study is to compare the response of electrodermal activity (EDA), as an indicator of emotionality, to an empathic induction task, between IPV perpetrators and men without a history of violence. The sample was composed of 51 men who attended the CONTEXTO program, with penalties for gender violence under two years, and 47 men with no history of violence. Empathic induction was achieved through the visualization of 4 negative emotional-eliciting videos taken from an emotional induction battery of videos validated for the Spanish population. The participants were asked to actively empathize with the video characters (previously pointed out). The psychophysiological recording of the EDA was accomplished by the "Vrije Universiteit Ambulatory Monitoring System (VU-AMS)." An analysis of repeated measurements was carried out with 10 intra-subject measurements (time) and "group" (IPV perpetrators and non-violent perpetrators) as the inter-subject factor. First, there were no significant differences between groups in the baseline AED levels. Yet, a significant interaction between the “time” and “group” was found with IPV perpetrators exhibiting lower EDA response than controls after the empathic induction task. These findings provide evidence of a subdued EDA response after an empathic induction task in IPV perpetrators with respect to men without a history of violence. Therefore, the lower psychophysiological activation would be indicative of difficulties in the emotional processing and response, functions that are necessary for the empathic function. Consequently, the importance of addressing possible empathic difficulties in IPV perpetrator psycho-educational programs is reinforced, putting special emphasis on the affective dimension that could hinder the empathic function.

Keywords: electrodermal activity, emotional induction, empathy, intimate partner violence

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Diana Karina Baigts Allende, Mariana Gonzalez Diaz, Luis Antonio Chel Guerrero, Mukthar Sandoval Peraza

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Poverty and food insecurity are still incident problems in the developing countries, where population´s diet is based on cereals which are lack in protein content. Nevertheless, during last years the use of native plants has been studied as an alternative source of protein in order to improve the nutritional intake. Chaya crop also called Spinach tree, is a prehispanic plant native from Central America and South of Mexico (Mayan culture), which has been especially valued due to its high nutritional content particularly protein and some medicinal properties. The aim of this work was to study the effect of protein isolation processing from Chaya leaf harvest in Yucatan, Mexico on its structure quality in order: i) to valorize the Chaya crop and ii) to produce low-cost and high-quality protein. Chaya leaf was extruded, clarified and recovered using: a) acid precipitation by decreasing the pH value until reach the isoelectric point (3.5) and b) thermal coagulation, by heating the protein solution at 80 °C during 30 min. Solubilized protein was re-dissolved in water and spray dried. The presence of Fraction I protein, known as RuBisCO (Rubilose-1,5-biphosfate carboxylase/oxygenase) was confirmed by gel electrophoresis (SDS-PAGE) where molecular weight bands of 55 KDa and 12 KDa were observed. The infrared spectrum showed changes in protein structure due to the isolation method. The use of high temperatures (thermal coagulation) highly decreased protein solubility in comparison to isoelectric precipitated protein, the nutritional properties according to amino acid profile was also disturbed, showing minor amounts of overall essential amino acids from 435.9 to 367.8 mg/g. Chaya protein isolate obtained by acid precipitation showed higher protein quality according to essential amino acid score compared to FAO recommendations, which could represent an important sustainable source of protein for human consumption.

Keywords: chaya leaf, nutritional properties, protein isolate, protein structure

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Authors: Jorge Luis Morales Romero, Enrique Murillo Othón

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Business to business (B2B) relationships generally go beyond a purely profit-based result, with firms seeking to maintain a relationship for many years because a breakup or getting a new supplier can be very costly. Therefore, identifying the factors which determine a successful relationship in the long term is of great interest to companies. That is why their reputation and the brand image that customers have of them are among the main factors that can achieve a successful relationship; Because of the positive effect which is driven by the client’s loyalty. Additionally, the perception that a customer may have about a brand is different when it is related to goods or to services. Thereby, they create in their minds their own brand image of it based on the past experiences they have had; Thus, a positive relationship is established between goods-related brand image, service-related brand image, and customer loyalty. The present investigation examines the boundary conditions of said relationship by testing the moderating effects of trust, commitment, and relationship value in a B2B environment. All the variables were tested independently as moderators for service-related brand image/loyalty and for goods-related brand image/loyalty, as they are assumed to be separate variables. Survey data was collected through interviews with customers that have both a product-buying relationship and a service relationship with a global B2B brand of healthcare equipment operating in the Mexican healthcare market. Interviewed respondents were either the user or the purchasing manager and/or the responsible for the equipment maintenance for the customer organization. Hence, they were appropriate informants regarding the B2B relationship with this healthcare brand. The moderation models were estimated using the PROCESS macro for the Statistical Package for the Social Sciences Software (SPSS). Results show statistical evidence that both Relationship Value and Trust are significant moderators for the service-related brand image/loyalty relation but not significant for the goods-related brand/loyalty relation. On the other hand, Commitment results in a significant moderator for the goods-related brand/loyalty relation but is not significant for the service-related brand image/loyalty relation.

Keywords: commitment, trust, relationship value, loyalty, B2B, moderator

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Authors: Tania Vasquez Mata, Luis A. Herrera, Cristian Arriaga Canon

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Background: Locally advanced breast cancer of the luminal B phenotype, poses challenges due to its variable response to neoadjuvant chemotherapy. A predictive biomarker is needed to identify patients who will not respond to treatment, allowing for alternative therapies. This study aims to validate the use of the lncRNA GATA3-AS1, as a predictive biomarker using RNA in situ hybridization. Research aim: The aim of this study is to determine if GATA3-AS1 can serve as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Methodology: The study utilizes RNA in situ hybridization with predesigned probes for GATA3-AS1 on Formalin-Fixed Paraffin-Embedded tissue sections. The samples underwent pretreatment and protease treatment to enable probe penetration. Chromogenic detection and signal evaluation were performed using specific criteria. Findings: Patients who did not respond to neoadjuvant chemotherapy showed a 3+ score for GATA3-AS1, while those who had a complete response had a 1+ score. Theoretical importance: This study demonstrates the potential clinical utility of GATA3-AS1 as a biomarker for resistance to neoadjuvant chemotherapy. Identifying non-responders early on can help avoid unnecessary treatment and explore alternative therapy options. Data collection and analysis procedures: Tissue samples from patients with locally advanced luminal B breast cancer were collected and processed using RNA in situ hybridization. Signal evaluation was conducted under a microscope, and scoring was based on specific criteria. Questions addressed: Can GATA3-AS1 serve as a predictive biomarker for neoadjuvant chemotherapy response in locally advanced luminal B breast cancer? Conclusion: The lncRNA GATA3-AS1 can be used as a biomarker for resistance to neoadjuvant chemotherapy in patients with locally advanced luminal B breast cancer. Its identification through RNA in situ hybridization of tissue obtained from the initial biopsy can aid in treatment decision-making.

Keywords: biomarkers, breast neoplasms, genetics, neoadjuvant therapy, tumor

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Authors: Lise Alonso, Audrey Dubost, Patricia Luis, Thomas Pommier, Yvan Moënne-Loccoz

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The Lascaux Cave in South-Est France is an archeological landmark renowned for its Paleolithic paintings dating back c.18.000 years. Extensive touristic frequenting and repeated chemical treatments have resulted in the development of microbial stains on cave walls, which is a major issue in terms of art conservation. Therefore, it is of prime importance to better understand the microbiology specific to the Lascaux Cave, in comparison to regional situations. To this end, we compared the microbial community (i.e. both prokaryotic and eukaryotic microbial populations) of Lascaux Cave with three other anthropized Périgord caves as well as three pristine caves from the same area. We used state-of-the-art metagenomic analyses of cave wall samples to obtain a global view of the composition of the microbial community colonizing cave walls. We measured the relative abundance and diversity of four DNA markers targeting different fractions of the ribosomal genes of bacteria (i.e. eubacteria), archaea (i.e. archeobacteria), fungi and other micro-eukaryotes. All groups were highly abundant and diverse in all Périgord caves, as several hundred genera of microorganisms were identified in each. However, Lascaux Cave displayed a specify microbial community, which differed from those of both pristine and anthropized caves. Comparison of stains versus non-stained samples from the Passage area of the Lascaux Cave indicated that a few taxa (e.g. the Sordiaromycetes amongst fungi) were more prevalent within than outside stains, yet the main difference was in the relative proportion of the different microbial taxonomic groups and genera, which supposedly supports the biological origin of the stains. Overall, metagenomic sequencing of cave wall samples was effective to evidence the large colonization of caves by a diversified range of microorganisms. It also showed that Lascaux Cave represented a very particular situation in comparison with neighboring caves, probably in relation to the extent of disturbance it had undergone. Our results provide key baseline information to guide conservation efforts in anthropized caves such as Lascaux and pave the way to modern monitoring of ornamented caves.

Keywords: cave conservation, Lascaux cave, microbes, paleolithic paintings

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Authors: Soledad Carinelli, Iñigo Fernández, José Luis González-Mora, Pedro A. Salazar-Carballo

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Mastitis is the most relevant inflammatory disease in cattle, affecting the animal health and causing important economic losses on dairy farms. This disease takes place in the mammary gland or udder when some opportunistic microorganisms, such as Staphylococcus aureus, Streptococcus agalactiae, Corynebacterium bovis, etc., invade the teat canal. According to the severity of the inflammation, mastitis can be classified as sub-clinical, clinical and chronic. Standard methods for mastitis detection include counts of somatic cells, cell culture, electrical conductivity of the milk, and California test (evaluation of “gel-like” matrix consistency after cell lysed with detergents). However, these assays present some limitations for accurate detection of subclinical mastitis. Currently, haptoglobin, an acute phase protein, has been proposed as novel and effective biomarker for mastitis detection. In this work, an electrochemical biosensor based on polydopamine-modified magnetic nanoparticles (MNPs@pDA) for haptoglobin detection is reported. Thus, MNPs@pDA has been synthesized by our group and functionalized with hemoglobin due to its high affinity to haptoglobin protein. The protein was labeled with specific antibodies modified with alkaline phosphatase enzyme for its electrochemical detection using an electroactive substrate (1-naphthyl phosphate) by differential pulse voltammetry. After the optimization of assay parameters, the haptoglobin determination was evaluated in milk. The strategy presented in this work shows a wide range of detection, achieving a limit of detection of 43 ng/mL. The accuracy of the strategy was determined by recovery assays, being of 84 and 94.5% for two Hp levels around the cut off value. Milk real samples were tested and the prediction capacity of the electrochemical biosensor was compared with a Haptoglobin commercial ELISA kit. The performance of the assay has demonstrated this strategy is an excellent and real alternative as screen method for sub-clinical bovine mastitis detection.

Keywords: bovine mastitis, haptoglobin, electrochemistry, magnetic nanoparticles, polydopamine

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Authors: Luis Alvarado, Victor Poblete, Isaac Gonzalez, Yetzabeth Gonzalez

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In MIREX 2016 (http://www.music-ir.org/mirex), the deep neural network (DNN)-Deep Chroma Extractor, proposed by Korzeniowski and Wiedmer, reached the highest score in an audio chord recognition task. In the present paper, this tool is assessed under acoustic reverberant environments and distinct source-microphone distances. The evaluation dataset comprises The Beatles and Queen datasets. These datasets are sequentially re-recorded with a single microphone in a real reverberant chamber at four reverberation times (0 -anechoic-, 1, 2, and 3 s, approximately), as well as four source-microphone distances (32, 64, 128, and 256 cm). It is expected that the performance of the trained DNN will dramatically decrease under these acoustic conditions with signals degraded by room reverberation and distance to the source. Recently, the effect of the bio-inspired Locally-Normalized Cepstral Coefficients (LNCC), has been assessed in a text independent speaker verification task using speech signals degraded by additive noise at different signal-to-noise ratios with variations of recording distance, and it has also been assessed under reverberant conditions with variations of recording distance. LNCC showed a performance so high as the state-of-the-art Mel Frequency Cepstral Coefficient filters. Based on these results, this paper proposes a variation of locally-normalized triangular filters called Locally-Normalized Quarter Tone (LNQT) filters. By using the LNQT spectrogram, robustness improvements of the trained Deep Chroma Extractor are expected, compared with classical triangular filters, and thus compensating the music signal degradation improving the accuracy of the chord recognition system.

Keywords: chord recognition, deep neural networks, feature extraction, music information retrieval

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Authors: Mariana Durana Pinto, Thierry Aubry, Eduarda Vieira

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The Côa River is one of the tributaries of the Douro River, which in turn connects two Portuguese regions: Beira-Alta (Serra das Mesas, Sabugal) and Trás-os-Montes (Douro River, Vila Nova de Foz Côa). The river, which is approximately 140 kilometres in length, is surrounded by characteristic Northern-Estearn Portugal landscape. The dominant flora in the region includes olive and almond trees and vines, which provide habitat for a diverse range of native species. These include mammals such as the lynx and Iberian wolf, as well as birds of prey such as the Egyptian vulture and the griffon vulture. Additionally, herbivorous species such as red deer and roe deer also inhabit the region. However, the Vale Côa is inextricably linked with the rocky outcrops bearing the emblematic open-air Upper Palaeolithic rock art, indeed, it houses the world's largest collection of prehistoric open-air rock art, inscribed on the World Heritage list by UNESCO in 1998. From the initial discovery of the first engravings in 1991 to the present day, approximally 1,500 panels with rock art, mostly engravings and carving, but also some paintings, have been discovered, inventoried and recorded spanning from earlu Upper Paleolithic to the 20th century. The study and interpretation of the engravings and its geoarchaeological context, allow the construction of a chronological timeline of the human occupation and graphical production in this region. The area has been inhabited since the Early Palaeolithic, with human communities exploiting the diversity of the natural resources of the environment and adapting it to their needs. This led to the creation of an archaeological and historical cultural landscape.The region is currently inhabited by rural communities whose primary source of income is derived from agricultural activities, with a particular focus on olive oil and wine production, including the emblematic Vinho do Porto. Additionally, the region is distinguished by activities such as stone exploration and extraction (e.g. schist and granite quarries) and tourism. The latter has progressively assumed a role in the promotion and development of the region, primarily due to the engravings of the Côa Valley itself, as well as the Alto Douro Wine Region. Furthermore, this cultural landscape has been inscribed in the UNESCO World Heritage Site in 2001. The aforementioned factors give rise to a series of challenges and issues pertaining to the management and safeguarding of rock art on a daily basis. These include: I) the management of conflicts between cultural heritage and economic activity (between Rock art and vineyards, both classified as World Heritage Sites); II) the management of land-use planning in areas where the engravings are located (since the areas with engravings are larger than those identified as buffer zones by UNESCO); III) the absence of the legal figure of an 'archaeological park' and the need to solve this issue; IV) the management of tourist pressure and unauthorised visits; and V) the management of vandalism (as a consequence of misinformation and denial).

Keywords: Douro and Côa Valleys, archaeological cultural landscapes, rock art, Douro wine, conservation challenges

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Authors: D. Castillo T., Luis F. Jimenez

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The compressed earth blocks (CEBs) constitute an alternative as a constructive element for building homes in regions with high levels of poverty and marginalization. Such is the case of Southeastern Mexico, where the population, predominantly indigene, build their houses with feeble materials like wood and palm, vulnerable to extreme weather in the area, because they do not have the financial resources to acquire concrete blocks. There are several advantages that can provide BTCs compared to traditional vibro-compressed concrete blocks, such as the availability of materials, low manufacturing cost and reduced CO2 emissions to the atmosphere for not be subjected to a burning process. However, to improve its mechanical properties and resistance to adverse weather conditions in terms of humidity and temperature of the sub-humid climate zones, it requires the use of a chemical stabilizer; in this case we chose Ca(OH)2. The stabilization method Eades-Grim was employed, according to ASTM C977-03. This method measures the optimum amount of lime required to stabilize the soil, increasing the pH to 12.4 or higher. The minimum amount of lime required in this experiment was 1% and the maximum was 10%. The employed material was clay unconsolidated low to medium plasticity (CL type according to the Unified Soil Classification System). Based on these results, the CEBs manufacturing process was determined. The obtained blocks were from 10x15x30 cm using a mixture of soil, water and lime in different proportions. Later these blocks were put to dry outdoors and subjected to several physical and mechanical tests, such as compressive strength, absorption and drying shrinkage. The results were compared with the limits established by the Mexican Standard NMX-C-404-ONNCCE-2005 for the construction of housing walls. In this manner an alternative and sustainable material was obtained for the construction of rural households in the region, with better security conditions, comfort and cost.

Keywords: calcium hydroxide, chemical stabilization, compressed earth blocks, sub-humid warm weather

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Authors: Andrea Parisi, Samantha Vilkins, Luis Furuya-Kanamori, John A. Crump, Benjamin P. Howden, Darren Gray, Kathryn Glass, Martyn Kirk

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Objectives: Salmonella is a leading cause of foodborne enterocolitis worldwide. Nontyphoidal Salmonella (NTS) infections that are Multi-Drug Resistant (MDR) (non-susceptible to ≥1 agent in ≥3 antimicrobial categories) may result in more severe outcomes, although these effects have not been systematically examined. We conducted a systematic review and meta-analysis to examine impacts of MDR NTS on health in high-income settings. Methods: We systematically reviewed the literature from scientific databases, including PubMed, Scopus and grey literature sources, using PRISMA guidelines. We searched for data from case-control studies, cohorts, outbreaks, reports and theses, imposing no language restriction. We included only publications from January 1990 to September 2016 from high income countries as classified by World Bank. We extracted data from papers on duration of illness, hospitalisation rates, morbidity and mortality for MDR and non-MDR NTS strains. Results: After removing duplicates, the initial search revealed 4258 articles. After further screening, we identified 16 eligible studies for the systematic review, and 9 of these were included in meta-analysis. NTS serotypes differed among the reported studies but serotype Typhimurium, Enteritidis, Newport and Heidelberg were among the most often reported as MDR pathogens. Salmonella infections that were MDR were associated with excess bloodstream infections (OR 1.63; 95%CI 1.18-2.26), excess hospitalisations (OR 2.77; 95%CI 1.47-5.21) and higher mortality (OR 3.54; 95%CI 1.10-11.40). Conclusions: MDR NTS infections are a serious public health concern. With the emergence of MDR Salmonella strains in the high-income countries, it is crucial to restrict the use of antimicrobials both in animals and humans, and intervene to prevent foodborne infections.

Keywords: Antimicrobial Resistance, Bloodstream Infection, Health Outcomes, Hospitalisation, Invasive Disease, Multi-Drug Resistance (MDR), Mortality, Nontyphoidal Salmonella

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Authors: Leixuri Aguirre, Iñaki Milton-Laskibar, Elizabeth Hijona, Luis Bujanda, Agnes M. Rimando, Maria P. Portillo

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Introduction: In recent years great attention has been paid by scientific community to phenolic compounds as active biomolecules naturally present in foodstuffs due to their beneficial effects on health. Pterostilbene is a resveratrol dimethylether derivative which shows higher biodisponibility. Objective. To analyze the effects of two doses of pterostilbene on several markers of thermogenic capacity in a model of genetic obesity, which shows reduced thermogenesis. Methods: The experiment was conducted with thirty Zucker (fa/fa) rats that were distributed in 3 experimental groups, the control group and two groups orally administered with pterostilbene at 15 and 30 mg/kg body weight/day for 6 weeks. Gene expression of Ucp1, Pgc-1α, Cpt1b, Pparα, Nfr1, Tfam and Cox-2 were assessed by RT-PCR, protein expression of UCP1 and GLUT4 by western blot and enzyme activity of carnitine palmitoyl transferase 1b and citrate synthase by spectrophotometry in interscapular brown adipose tissue (iBAT). Statistical analysis was performed by using one way ANOVA and Newman-Keuls as post-hoc test. Results: Pterostilbene did not change gene expression of Pgc-1α. However, significant increases were found in the expression of Ucp1, Pparα, Nfr-1 and Cox-2. Protein expression of UCP1 and GLUT4 was increased in animals treated with pterostilbene, as well as the activities of CPT-1b and CS. These effects were observed with both doses of pterostilbene, without differences between them. Conclusions: These results show that pterostilbene increases thermogenic and oxidative capacity of brown adipose tissue in obese rats. Whether these effects effectively contribute to the anti-obesity properties of these compound needs further research. Acknowledgments: MINECO-FEDER (AGL2015-65719-R), Basque Government (IT-572-13), University of the Basque Country (ELDUNANOTEK UFI11/32), Institut of Health Carlos III (CIBERobn). Iñaki Milton is a fellowship from the Basque Government.

Keywords: brown adipose tissue, pterostilbene, thermogenesis, uncoupling protein 1

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Authors: Sergio Alejandro Cuevas, Catherine Etchebest, Fernando Luis Barroso Da Silva

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The flavivirus genus has several organisms responsible for generating various diseases in humans. Special in Brazil, Zika (ZIKV), Dengue (DENV) and Yellow Fever (YFV) viruses have raised great health concerns due to the high number of cases affecting the area during the last years. Diagnostic is still a difficult issue since the clinical symptoms are highly similar. The understanding of their common structural/dynamical and biomolecular interactions features and differences might suggest alternative strategies towards differential serological diagnostics and therapeutic intervention. Due to their immunogenicity, the primary focus of this study was on the ZIKV, DENV and YFV non-structural proteins 1 (NS1) protein. By means of computational studies, we calculated the main physical chemical properties of this protein from different strains that are directly responsible for the biomolecular interactions and, therefore, can be related to the differential infectivity of the strains. We also mapped the electrostatic differences at both the sequence and structural levels for the strains from Uganda to Brazil that could suggest possible molecular mechanisms for the increase of the virulence of ZIKV. It is interesting to note that despite the small changes in the protein sequence due to the high sequence identity among the studied strains, the electrostatic properties are strongly impacted by the pH which also impact on their biomolecular interactions with partners and, consequently, the molecular viral biology. African and Asian strains are distinguishable. Exploring the interfaces used by NS1 to self-associate in different oligomeric states, and to interact with membranes and the antibody, we could map the strategy used by the ZIKV during its evolutionary process. This indicates possible molecular mechanisms that can explain the different immunological response. By the comparison with the known antibody structure available for the West Nile virus, we demonstrated that the antibody would have difficulties to neutralize the NS1 from the Brazilian strain. The present study also opens up perspectives to computationally design high specificity antibodies.

Keywords: zika, biomolecular interactions, electrostatic interactions, molecular mechanisms

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Authors: Constâncio Augusto Machanguana, Luís Miguel Estevão Cristóvão

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In Mozambique, over 80% of the rural population relies on agriculture, livestock, and silviculture for their livelihoods. Unfortunately, these communities face persistent food shortages, which are exacerbated by natural disasters and post-harvest losses due to inadequate storage facilities. Addressing post-harvest loss is critical not only for ensuring food security but also for preventing financial hardships faced by farmers. The study delves into the perceptions of beneficiary communities regarding the construction of three food dryer models made from metal, wood, and clay brick. These solar dryers are part of the project titled ‘Solar Dryer Integrated with Natural Rocks as Energy Storage for Drying Fruits and Vegetables in Mozambique.’ The overarching goal is to enhance food availability beyond the typical growing season, particularly for fruits and vegetables, while simultaneously combating hunger. Given the context of climate change impacts on agriculture, this project becomes even more relevant. Structured interviews conducted with 45 members of beneficiary associations in Manica Province—primarily female heads of households—revealed that rural communities are aware of various food drying alternatives. However, reliance on traditional methods often comes at a cost: compromised product quality and reduced shelf life. To address these challenges, the project implemented energy storage solutions like rock-based thermal energy storage for food drying. This result underscores the urgent need to foster innovation and extend these sustainable practices —such as solar dryers integrated with thermal energy-storage systems made of locally abundant and affordable materials— to more local communities, especially those with significant agricultural potential within the country. By taking these actions, we can improve food security and alleviate hunger.

Keywords: solar dryer, food security, rural community, small technology

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Authors: Nilesh Bandekar, Sumita Dasgupta, Luis Alberto Allcahuaman Huaya, Souvik Manna

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Cryptobiosis is a dormant state where all measurable metabolic activities are at a halt, allowing an organism to survive in extreme conditions like low temperature (cryobiosis), extreme drought (anhydrobiosis), etc. This phenomenon is observed especially in tardigrades that can retain this state for decades depending on the abiotic environmental conditions. On returning to favorable conditions, tardigrades re-attain a metabolically active state. In this study, cyanobacteria as a model organism are being chosen to induce cryptobiosis for its effective preservation over a long period of time. Preserving cyanobacteria using this strategy will have multiple space applications because of its ability to produce oxygen. In addition, research has shown the survivability of this organism in space for a certain period of time. Few species of cyanobacterial residents of the soil such as Microcoleus, are able to survive in extreme drought as well. This work specifically focuses on Synechococcus elongatus, an endolith cyanobacteria with multiple benefits. It has the capability to produce 25% oxygen in water bodies. It utilizes carbon dioxide to produce oxygen via photosynthesis and also uses carbon dioxide as an energy source to form glucose via the Calvin cycle. There is a fair possibility of initiating cryptobiosis in such an organism by inducing certain proteins extracted from tardigrades such as Heat Shock Proteins (Hsp27 and Hsp30c) and/or hydrophilic Late Embryogenesis Abundant proteins (LEA). Existing methods like cryopreservation are difficult to execute in space keeping in mind their cost and heavy instrumentation. Also, extensive freezing may cause cellular damage. Therefore, cryptobiosis-induced cyanobacteria for its transportation from Earth to Mars as a part of future terraforming missions on Mars will save resources and increase the effectiveness of preservation. Finally, Cyanobacteria species like Synechococcus elongatus can also produce oxygen and glucose on Mars in favorable conditions and holds the key to terraforming Mars.

Keywords: cryptobiosis, cyanobacteria, glucose, mars, Synechococcus elongatus, tardigrades

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Authors: Laura Bravo-García, Gotzone Barandika, Begoña Bazán, M. Karmele Urtiaga, Luis M. Lezama, María I. Arriortua

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Solid coordination networks (SCNs) are materials consisting of metal ions or clusters that are linked by polyfunctional organic ligands and can be designed to form tridimensional frameworks. Their structural features, as for example high surface areas, thermal stability, and in other cases large cavities, have opened a wide range of applications in fields like drug delivery, host-guest chemistry, biomedical imaging, chemical sensing, heterogeneous catalysis and others referred to greenhouse gases storage or even separation. In this sense, the use of polycarboxylate anions and dipyridyl ligands is an effective strategy to produce extended structures with the needed characteristics for these applications. In this context, a novel compound, [Cu4(m-BDC)4(bpa)2DMF]•DMF has been obtained by microwave synthesis, where m-BDC is 1,3-benzenedicarboxylate and bpa 1,2-bis(4-pyridyl)ethane. The crystal structure can be described as a three dimensional framework formed by two equal, interpenetrated networks. Each network consists of two different CuII dimers. Dimer 1 have two coppers with a square pyramidal coordination, and dimer 2 have one with a square pyramidal coordination and other with octahedral one, the last dimer is unique in literature. Therefore, the combination of both type of dimers is unprecedented. Thus, benzenedicarboxylate ligands form sinusoidal chains between the same type of dimers, and also connect both chains forming these layers in the (100) plane. These layers are connected along the [100] direction through the bpa ligand, giving rise to a 3D network with 10 Å2 voids in average. However, the fact that there are two interpenetrated networks results in a significant reduction of the available volume. Structural analysis was carried out by means of single crystal X-ray diffraction and IR spectroscopy. Thermal and magnetic properties have been measured by means of thermogravimetry (TG), X-ray thermodiffractometry (TDX), and electron paramagnetic resonance (EPR). Additionally, CO2 and CH4 high pressure adsorption measurements have been carried out for this compound.

Keywords: gas adsorption, interpenetrated networks, magnetic measurements, solid coordination network (SCN), thermal stability

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Authors: Fernanda Piculo, Giovana Vesentini, Gabriela Marini, Debora Cristina Damasceno, Angelica Mercia Pascon Barbosa, Marilza Vieira Cunha Rudge

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Introduction: Women with previous gestational diabetes mellitus (GDM) were significantly more likely to have urinary incontinence (UI) and pelvic floor muscle dysfunction compared to non-diabetic women two years after a cesarean section. Additional results demonstrated that induced diabetes causes detrimental effects on pregnant rat urethral muscle. These results indicate the need for exploration of the mechanistic role of a recovery factor in female UI. Chemokine ligand 7 (CCL7) was significantly over expressed in rat serum, urethral and vaginal tissues immediately following induction of stress UI in a rat model simulating birth trauma. CCL7 over expression has shown potency for stimulating targeted stem cell migration and provide a translational link (clinical measurement) which further provide opportunities for treatment. The aim of this study was to investigate the CCL7 levels profile in diabetic pregnant women with urinary incontinence during pregnancy over the first year postpartum. Methods: This study was conducted in the Perinatal Diabetes Research Center of the Botucatu Medical School/UNESP, and was approved by the Research Ethics Committee of the Institution (CAAE: 20639813.0.0000.5411). The diagnosis of GDM was established between 24th and 28th gestational weeks, by the 75 g-OGTT test according to ADA’s criteria. Urinary incontinence was defined according to the International Continence Society and the CCL7 levels was measured by ELISA (R&D Systems, Catalog Number DCC700). Two hundred twelve women were classified into four study groups: normoglycemic continent (NC), normoglycemic incontinent (NI), diabetic continent (DC) and diabetic incontinent (DI). They were evaluated at six-time-points: 12-18, 24-28 and 34-38 gestational weeks, 24-48 hours, 6 weeks and 6-12 months postpartum. Results: At 12-18 weeks, it was possible to consider only two groups, continent and incontinent, because at this early gestational period has not yet been the diagnosis of GDM. The group with GDM and UI (DI group) showed lower levels of CCL7 in all time points during pregnancy and postpartum, compared to normoglycemic groups (NC and NI), indicating that these women have not recovered from child birth induced UI during the 6-12 months postpartum compared to their controls, and that the progression of UI and/or lack of recovery throughout the first postpartum year can be related with lower levels of CCL7. Instead, serum CCL7 was significantly increased in the NC group. Taken together, these findings of overexpression of CCL7 in the NC group and decreased levels in the DI group, could confirm that diabetes delays the recovery from child birth induced UI, and that CCL7 could potentially be used as a serum marker of injury. Conclusion: This study demonstrates lower levels of CCL7 in the DI group during pregnancy and postpartum and suggests that the progression of UI in diabetic women and/or lack of recovery throughout the first postpartum year can be related with low levels of CCL7. This provides a translational potential where CCL7 measurement could be used as a surrogate for injury after delivery. Successful controlled CCL7 mediated stem cell homing to the lower urinary tract could one day introduce the potential for non-operative treatment or prevention of stress urinary incontinence.

Keywords: CCL7, gestational diabetes, pregnancy, urinary incontinence

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Authors: Marisol Rodriguez-Duarte, Aide Saenz-Galindo, Carolina Flores-Gallegos, Raul Rodriguez-Herrera, Juan Ascacio-Valdes

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The plant known as tarbush (Fluorensia cernua) is a plant originating in northern Mexico, mainly in the states of Coahuila, Durango, San Luis Potosí, Zacatecas and Chihuahua. It is a branched shrub that belongs to the family Asteraceae, has oval leaves of 6 to 11 cm in length and also has small yellow flowers. In Mexico, the tarbush is a very appreciated plant because it has been used as a traditional medicinal agent, for the treatment of gastrointestinal diseases, skin infections and as a healing agent. This plant has been used mainly as an infusion. Due to its traditional use, the content and type of phytochemicals present in the plant are currently unknown and are responsible for its biological properties, so its recovery and identification is very important because the compounds that it contains have relevant applications in the field of food, pharmaceuticals and medicine. The objective of this work was to determine the best extraction condition of phytochemical compounds (mainly polyphenolic compounds) from the leaf using ultrasound/microwave assisted extraction (U/M-AE). To reach the objective, U/M-AE extractions were performed evaluating three mass/volume ratios (1:8, 1:12, 1:16), three ethanol/water solvent concentrations (0%, 30% and 70%), ultrasound extraction time of 20 min and 5 min at 70°C of microwave treatment. All experiments were performed using a fractional factorial experimental design. Once the best extraction condition was defined, the compounds were recovered by liquid column chromatography using Amberlite XAD-16, the polyphenolic fraction was recovered with ethanol and then evaporated. The recovered polyphenolic compounds were quantified by spectrophotometric techniques and identified by HPLC/ESI/MS. The results obtained showed that the best extraction condition of the compounds was using a mass/volume ratio of 1:8 and solvent ethanol/water concentration of 70%. The concentration obtained from polyphenolic compounds using this condition was 22.74 mg/g and finally, 16 compounds of polyphenolic origin were identified. The results obtained in this work allow us to postulate the Mexican plant known as tarbush as a relevant source of bioactive polyphenolic compounds of food, pharmaceutical and medicinal interest.

Keywords: U/M-AE, tarbush, polyphenols, identification

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Authors: Daniel Alfonso Reséndiz-García, Luis Antonio García-Villanueva

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As a result of the high industrial activity, which arises from the search to satisfy the needs of products and services for society, several chemical accidents have occurred, causing serious damage to different sectors: human, economic, infrastructure and environmental losses. Historically, with the study of this chemical accidents, it has been determined that the causes are mainly due to human errors (inexperienced personnel, negligence, lack of maintenance and deficient risk analysis). The industries have the aim to increase production and reduce costs. However, it should be kept in mind that the costs involved in risk studies, implementation of barriers and safety systems is much cheaper than paying for the possible damages that could occur in the event of an accident, without forgetting that there are things that cannot be replaced, such as human lives.Therefore, it is of utmost importance to implement risk studies in all industries, which provide information for prevention and planning. The aim of this study is to compare risk methodologies by identifying the consequences of accidents related to the storage of flammable, dangerous goods for decision making and emergency response.The methodologies considered in this study are qualitative and quantitative risk analysis and consequence analysis. The latter, by means of modeling software, which provides radius of affectation and the possible scope and magnitude of damages.By using risk analysis, possible scenarios of occurrence of chemical accidents in the storage of flammable substances are identified. Once the possible risk scenarios have been identified, the characteristics of the substances, their storage and atmospheric conditions are entered into the software.The results provide information that allows the implementation of prevention, detection, control, and combat elements for emergency response, thus having the necessary tools to avoid the occurrence of accidents and, if they do occur, to significantly reduce the magnitude of the damage.This study highlights the importance of risk studies applying tools that best suited to each case study. It also proves the importance of knowing the risk exposure of industrial activities for a better prevention, planning and emergency response.

Keywords: chemical accidents, emergency response, flammable substances, risk analysis, modeling

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Authors: Cesar Augusto Hoil Rosas, José Luis Vázquez Burgos, José Juan Carbajal Hernandez

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White fish (Chirostoma estor estor) is an endemic species that habits in the Patzcuaro Lake, located in Michoacan, Mexico; being an important source of gastronomic and cultural wealth of the area. Actually, it have undergone an immense depopulation of individuals, due to the high fishing, contamination and eutrophication of the lake water, resulting in the possible extinction of this important species. This work proposes a new computational model for monitoring and assessment of critical environmental parameters of the white fish ecosystem. According to an Analytical Hierarchy Process, a mathematical model is built assigning weights to each environmental parameter depending on their water quality importance on the ecosystem. Then, a development of an advanced system for the monitoring, analysis and control of water quality is built using the virtual environment of LabVIEW. As results, we have obtained a global score that indicates the condition level of the water quality in the Chirostoma estor ecosystem (excellent, good, regular and poor), allowing to provide an effective decision making about the environmental parameters that affect the proper culture of the white fish such as temperature, pH and dissolved oxygen. In situ evaluations show regular conditions for a success reproduction and growth rates of this species where the water quality tends to have regular levels. This system emerges as a suitable tool for the water management, where future laws for white fish fishery regulations will result in the reduction of the mortality rate in the early stages of development of the species, which represent the most critical phase. This can guarantees better population sizes than those currently obtained in the aquiculture crop. The main benefit will be seen as a contribution to maintain the cultural and gastronomic wealth of the area and for its inhabitants, since white fish is an important food and economical income of the region, but the species is endangered.

Keywords: Chirostoma estor estor, computational system, lab view, white fish

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Authors: Luís F. da Silva, Ariadne C. Catto, Osmando F. Lopes, Khalifa Aguir, Valmor R. Mastelaro, Caue Ribeiro, Elson Longo

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Gas detection is important for controlling industrial, and vehicle emissions, agricultural residues, and environmental control. In last decades, several semiconducting oxides have been used to detect dangerous or toxic gases. The excellent gas-sensing performance of these devices have been observed at high temperatures (~250 °C), which forbids the use for the detection of flammable and explosive gases. In this way, ultraviolet light activated gas sensors have been a simple and promising alternative to achieve room temperature sensitivity. Among the semiconductor oxides which exhibit a good performance as gas sensor, the zinc oxide (ZnO) and tin oxide (SnO2) have been highlighted. Nevertheless, their poor selectivity is the main disadvantage for application as gas sensor devices. Recently, heterostructures combining these two semiconductors (ZnO-SnO2) have been studied as an alternative way to enhance the gas sensor performance (sensitivity, selectivity, and stability). In this work, we investigated the influence of mass ratio Zn:Sn on the properties of ZnO-SnO2 nanocomposites prepared by hydrothermal treatment for 4 hours at 200 °C. The crystalline phase, surface, and morphological features were characterized by X-ray diffraction (XRD), high-resolution transmission electron (HR-TEM), and X-ray photoelectron spectroscopy (XPS) measurements. The gas sensor measurements were carried out at room-temperature under ultraviolet (UV) light irradiation using different ozone levels (0.06 to 0.61 ppm). The XRD measurements indicate the presence of ZnO and SnO2 crystalline phases, without the evidence of solid solution formation. HR-TEM analysis revealed that a good contact between the SnO2 nanoparticles and the ZnO nanorods, which are very important since interface characteristics between nanostructures are considered as challenge to development new and efficient heterostructures. Electrical measurements proved that the best ozone gas-sensing performance is obtained for ZnO:SnO2 (50:50) nanocomposite under UV light irradiation. Its sensitivity was around 6 times higher when compared to SnO2 pure, a traditional ozone gas sensor. These results demonstrate the potential of ZnO-SnO2 heterojunctions for the detection of ozone gas at room-temperature when irradiated with UV light irradiation.

Keywords: hydrothermal, zno-sno2, ozone sensor, uv-activation, room-temperature

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Authors: José Luis Gallizo, Pilar Gargallo, Ramon Saladrigues, Manuel Salvador

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This study offers an exploratory statistical analysis of the persistence of annual profits across a sample of firms from different European Union (EU) countries. To this end, a hierarchical Bayesian dynamic model has been used which enables the annual behaviour of those profits to be broken down into a permanent structural and a transitory component, while also distinguishing between general effects affecting the industry as a whole to which each firm belongs and specific effects affecting each firm in particular. This breakdown enables the relative importance of those fundamental components to be more accurately evaluated by country and sector. Furthermore, Bayesian approach allows for testing different hypotheses about the homogeneity of the behaviour of the above components with respect to the sector and the country where the firm develops its activity. The data analysed come from a sample of 23,293 firms in EU countries selected from the AMADEUS data-base. The period analysed ran from 1999 to 2007 and 21 sectors were analysed, chosen in such a way that there was a sufficiently large number of firms in each country sector combination for the industry effects to be estimated accurately enough for meaningful comparisons to be made by sector and country. The analysis has been conducted by sector and by country from a Bayesian perspective, thus making the study more flexible and realistic since the estimates obtained do not depend on asymptotic results. In general terms, the study finds that, although the industry effects are significant, more important are the firm specific effects. That importance varies depending on the sector or the country in which the firm carries out its activity. The influence of firm effects accounts for around 81% of total variation and display a significantly lower degree of persistence, with adjustment speeds oscillating around 34%. However, this pattern is not homogeneous but depends on the sector and country analysed. Industry effects depends also on sector and country analysed have a more marginal importance, being significantly more persistent, with adjustment speeds oscillating around 7-8% with this degree of persistence being very similar for most of sectors and countries analysed.

Keywords: dynamic models, Bayesian inference, MCMC, abnormal returns, persistence of profits, return on assets

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Authors: Luís R. Silva, Catarina Bento, Ana C. Gonçalves, Fábio Jesus, Branca M. Silva

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Nowadays, the general population is more and more concerned about nutrition and the health implications of an unbalanced diet. Current knowledge regarding the health benefits and antioxidant properties of certain foods such as fruits and vegetables has gained the interest of both the general public and scientific community. Peach (Prunus persica (L.) Batsch) is one of the most consumed fruits worldwide, with low sugar contents and a broad range of nutrients essential to the normal functioning of the body. Six different peach cultivars from the Fundão region in Portugal were evaluated regarding their phenolic composition by LC-DAD and biological activity. The prepared extracts’ capacity to scavenge free-radicals was tested through the stable free radical DPPH• and nitric oxide (•NO). Additionally, antidiabetic potential and protective effects against peroxyl radical (ROO•) induced damage to erythrocytes were also tested. LC-DAD analysis allowed the identification of 17 phenolic compounds, among which 5-O-caffeoylquinic acids and 3-O-caffeoylquinic acids are pointed out as the most abundant. Regarding the antioxidant activity, all cultivars displayed concentration-dependent free-radical scavenging activity against both nitrogen species and DPPH•. In respect to α-glucosidase inhibitory activity, Royal Magister and Royal Glory presented the highest inhibitory activity (IC50 = 11.7 ± 1.4 and 17.1 ± 1.7 μg/mL, respectively), nevertheless all six cultivars presented higher activity than the control acarbose. As for the protective effect of Royal Lu extract on the oxidative damage induced in erythrocytes by ROO•, the results were quite promising showing inhibition IC50 values of 110.0 ± 4.5 μg/mL and 83.8 ± 6.5 μg/mL for hemolysis and hemoglobin oxidation, respectively. The demonstrated activity is of course associated to the peaches’ phenolic profile, rich in phenolic acids and flavonoids with high hydrogen donating capacity. These compounds have great industrial interest for the manufacturing of natural products. The following step would naturally be the extraction and isolation from the plant tissues and large-scale production through biotechnology techniques.

Keywords: antioxidants, functional food, phenolic compounds, peach

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Authors: Manuela Caciula, Luis Torres, Simion Tomoiaga

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Introduction: The SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), more commonly referred to as COVID-19, has wreaked havoc on all facets of higher education since its inception in late 2019. College students, in particular, significantly reduced their daily energy expenditure and increased the time spent sitting to listen to online classes and complete their studies from home. This change, in combination with the associated COVID-19 lockdown, presumably decreased physical activity levels, increased mental health symptoms, and led to the promotion of unhealthy eating habits. Objectives: The main objective of this study was to determine the current self-reported physical activity levels, mental health symptoms, and body composition of college students after the COVID-19 lockdown in order to develop future interventions for the overall improvement of health. Methods: All participants completed pre-existing, well-validated surveys for both physical activity (International Physical Activity Questionnaire - long form) and mental health (Hospital Anxiety and Depression Scale). Body composition was assessed in person with the use of an Inbody 570 device. Results: Of the 90 American college students (M age = 22.52 ± 4.54, 50 females) who participated in this study, depressive and anxious symptom scores consistent with 58% (N = 52) heightened symptomatology, 17% (N = 15) moderate borderline symptomatology, and 25% (N = 23) asymptomatology were reported. In regard to physical activity, 79% (N = 71) of the students were highly physically active, 18% (N = 16) were moderately active, and 3% (N = 3) reported low levels of physical activity. Additionally, 46% (N = 41) of the students maintained an unhealthy body fat percentage based on World Health Organization recommendations. Strong, significant relationships were found between anxiety and depression symptomatology and body fat percentage (P = .003) and skeletal muscle mass (P = .015), with said symptomatology increasing with added body fat and decreasing with added skeletal muscle mass. Conclusions: Future health interventions for American college students should be focused on strategies to reduce stress, anxiety, and depressive characteristics, as well as nutritional information on healthy eating, regardless of self-reported physical activity levels.

Keywords: physical activity, mental health, body composition, COVID-19

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Authors: Natalia M. Acevedo, Luis M. Jimenez, Erick Lambis

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Imperfections in the capital market are used to argue the relevance of the corporate risk management function. With corporate hedge, the value of the company is increased by reducing the volatility of the expected cash flow and making it possible to face a lower bankruptcy costs and financial difficulties, without sacrificing tax advantages for debt financing. With the propose to avoid exchange rate troubles over cash flows of Colombian exporting firms, this dissertation uses financial options, over exchange rate between Peso and Dollar, for realizing a financial hedge. In this study, a strategy of hedge is designed for an exporting company in Colombia with the objective of preventing fluctuations because, if the exchange rate down, the number of Colombian pesos that obtains the company by exports, is less than agreed. The exchange rate of Colombia is measured by the TRM (Representative Market Rate), representing the number of Colombian pesos for an American dollar. First, the TMR is modelled through the Geometric Brownian Motion, with this, the project price is simulated using Montecarlo simulations and finding the mean of TRM for three, six and twelve months. For financial hedging, currency options were used. The 6-month projection was covered with financial options on European-type currency with a strike price of $ 2,780.47 for each month; this value corresponds to the last value of the historical TRM. In the compensation of the options in each month, the price paid for the premium, calculated with the Black-Scholes method for currency options, was considered. Finally, with the modeling of prices and the Monte Carlo simulation, the effect of the exchange hedging with options on the exporting company was determined, this by means of the unit price estimate to which the dollars in the scenario without coverage were changed and scenario with coverage. After using the scenarios: is determinate that the TRM will have a bull trend and the exporting firm will be affected positively because they will get more pesos for each dollar. The results show that the financial options manage to reduce the exchange risk. The expected value with coverage is approximate to the expected value without coverage, but the 5% percentile with coverage is greater than without coverage. The foregoing indicates that in the worst scenarios the exporting companies will obtain better prices for the sale of the currencies if they cover.

Keywords: currency hedging, futures, geometric Brownian motion, options

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