Search results for: forest law and regulation

Authors: Markéta Chmelíková, David Ullrich, Iva Burešová

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The paper maps the possibilities and limits of diagnosing selected personality and performance characteristics of military leadership and psychology students in the context of coping with challenging situations. Individuals vary greatly inter-individually in their ability to effectively manage extreme situations, yet existing diagnostic tools are often criticized mainly for their low predictive power. Nowadays, every modern army focuses primarily on the systematic minimization of potential risks, including the prediction of desirable forms of behavior and the performance of military commanders. The context of military leadership is well known for its life-threatening nature. Therefore, it is crucial to research stress load in the specific context of military leadership for the purpose of possible anticipation of human failure in managing extreme situations of military leadership. The aim of the submitted pilot study, using an experiment of 24 hours duration, is to verify the possibilities of a specific combination of psychodiagnostic to predict people who possess suitable equipment for coping with increased stress load. In our pilot study, we conducted an experiment of 24 hours duration with an experimental group (N=13) in the bomb shelter and a control group (N=11) in a classroom. Both groups were represented by military leadership students (N=11) and psychology students (N=13). Both groups were equalized in terms of study type and gender. Participants were administered the following test battery of personality characteristics: Big Five Inventory 2 (BFI-2), Short Dark Triad (SD-3), Emotion Regulation Questionnaire (ERQ), Fatigue Severity Scale (FSS), and Impulsive Behavior Scale (UPPS-P). This test battery was administered only once at the beginning of the experiment. Along with this, they were administered a test battery consisting of the Test of Attention (d2) and the Bourdon test four times overall with 6 hours ranges. To better simulate an extreme situation – we tried to induce sleep deprivation - participants were required to try not to fall asleep throughout the experiment. Despite the assumption that a stay in an underground bomb shelter will manifest in impaired cognitive performance, this expectation has been significantly confirmed in only one measurement, which can be interpreted as marginal in the context of multiple testing. This finding is a fundamental insight into the issue of stress management in extreme situations, which is crucial for effective military leadership. The results suggest that a 24-hour stay in a shelter, together with sleep deprivation, does not seem to simulate sufficient stress for an individual, which would be reflected in the level of cognitive performance. In the context of these findings, it would be interesting in future to extend the diagnostic battery with physiological indicators of stress, such as: heart rate, stress score, physical stress, mental stress ect.

Keywords: bomb shelter, extreme situation, military leadership, psychodiagnostic

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Authors: W. S. Thulasitha, N. Umasuthan, G. I. Godahewa, Jehee Lee

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In fish, innate immune defense is the first immune response against microbial pathogens which consists of several antimicrobial components. Galectins are one of the carbohydrate binding lectins that have the ability to identify pathogen by recognition of pathogen associated molecular patterns. Galectins play a vital role in the regulation of innate and adaptive immune responses. Rock bream Oplegnathus fasciatus is one of the most important cultured species in Korea and Japan. Considering the losses due to microbial pathogens, present study was carried out to understand the molecular and functional characteristics of a galectin in normal and pathogenic conditions, which could help to establish an understanding about immunological components of rock bream. Complete cDNA of rock bream galectin like protein B (rbGal like B) was identified from the cDNA library, and the in silico analysis was carried out using bioinformatic tools. Genomic structure was derived from the BAC library by sequencing a specific clone and using Spidey. Full length of rbGal like B (contig14775) cDNA containing 517 nucleotides was identified from the cDNA library which comprised of 435 bp in the open reading frame encoding a deduced protein composed of 145 amino acids. The molecular mass of putative protein was predicted as 16.14 kDa with an isoelectric point of 8.55. A characteristic conserved galactose binding domain was located from 12 to 145 amino acids. Genomic structure of rbGal like B consisted of 4 exons and 3 introns. Moreover, pairwise alignment showed that rock bream rbGal like B shares highest similarity (95.9 %) and identity (91 %) with Takifugu rubripes galectin related protein B like and lowest similarity (55.5 %) and identity (32.4 %) with Homo sapiens. Multiple sequence alignment demonstrated that the galectin related protein B was conserved among vertebrates. A phylogenetic analysis revealed that rbGal like B protein clustered together with other fish homologs in fish clade. It showed closer evolutionary link with Takifugu rubripes. Tissue distribution and expression patterns of rbGal like B upon immune challenges were performed using qRT-PCR assays. Among all tested tissues, level of rbGal like B expression was significantly high in gill tissue followed by kidney, intestine, heart and spleen. Upon immune challenges, it showed an up-regulated pattern of expression with Edwardsiella tarda, rock bream irido virus and poly I:C up to 6 h post injection and up to 24 h with LPS. However, In the presence of Streptococcus iniae rbGal like B showed an up and down pattern of expression with the peak at 6 - 12 h. Results from the present study revealed the phylogenetic position and role of rbGal like B in response to microbial infection in rock bream.

Keywords: galectin like protein B, immune response, Oplegnathus fasciatus, molecular characterization

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Authors: Nikolai A. Khlebnikov, Vladimir N. Krasilnikov, Evgenii V. Polyakov, Anastasia A. Maltceva

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Carbon materials with advanced surfaces are widely used both in modern industry and in environmental protection. The physical-chemical nature of these materials is determined by the morphology of primary atomic and molecular carbon structures, which are the basis for synthesizing the following materials: zero-dimensional (fullerenes), one-dimensional (fiber, tubes), two-dimensional (graphene) carbon nanostructures, three-dimensional (multi-layer graphene, graphite, foams) with unique physical-chemical and functional properties. Experience shows that the microscopic morphological level is the basis for the creation of the next mesoscopic morphological level. The dependence of the morphology on the chemical way and process prehistory (crystallization, colloids formation, liquid crystal state and other) is the peculiarity of the last called level. These factors determine the consumer properties of carbon materials, such as specific surface area, porosity, chemical resistance in corrosive environments, catalytic and adsorption activities. Based on the developed ideology of thin precursor synthesis, the authors discuss one of the approaches of the porosity control of carbon-containing materials with a given aggregates morphology. The low-temperature thermolysis of precursors in a gas environment of a given composition is the basis of the above-mentioned idea. The processes of carbothermic precursor synthesis of two different compounds: tungsten carbide WC:nC and zinc oxide ZnO:nC containing an impurity phase in the form of free carbon were selected as subjects of the research. In the first case, the transition metal (tungsten) forming carbides was the object of the synthesis. In the second case, there was selected zinc that does not form carbides. The synthesis of both kinds of transition metals compounds was conducted by the method of precursor carbothermic synthesis from the organic solution. ZnO:nC composites were obtained by thermolysis of succinate Zn(OO(CH2)2OO), formate glycolate Zn(HCOO)(OCH2CH2O)1/2, glycerolate Zn(OCH2CHOCH2OH), and tartrate Zn(OOCCH(OH)CH(OH)COO). WC:nC composite was synthesized from ammonium paratungstate and glycerol. In all cases, carbon structures that are specific for diamond- like carbon forms appeared on the surface of WC and ZnO particles after the heat treatment. Tungsten carbide and zinc oxide were removed from the composites by selective chemical dissolution preserving the amorphous carbon phase. This work presents the results of investigating WC:nC and ZnO:nC composites and carbon nanopowders with tubular, tape, plate and onion morphologies of aggregates that are separated by chemical dissolution of WC and ZnO from the composites by the following methods: SEM, TEM, XPA, Raman spectroscopy, and BET. The connection between the carbon morphology under the conditions of synthesis and chemical nature of the precursor and the possibility of regulation of the morphology with the specific surface area up to 1700-2000 m2/g of carbon-structured materials are discussed.

Keywords: carbon morphology, composite materials, precursor synthesis, tungsten carbide, zinc oxide

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Daniela Manila Bianchi, Samantha Lupi, Elisa Barcucci, Sandra Fragassi, Clara Tramuta, Lucia Decastelli

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Introduction: The undeclared allergens detection in food products plays a fundamental role in the safety of the allergic consumer. The protection of allergic consumers is guaranteed, in Europe, by Regulation (EU) No 1169/2011 of the European Parliament, which governs the consumer's right to information and identifies 14 food allergens to be mandatorily indicated on food labels: among these, an egg is included. An egg can be present as an ingredient or as contamination in raw and cooked products. The main allergen egg proteins are ovomucoid, ovalbumin, lysozyme, and ovotransferrin. This study presents the results of a survey conducted in Northern Italy aimed at detecting the presence of undeclared egg proteins in food matrices in the latest ten years (2011-2021). Method: In the period January 2011 - October 2021, a total of 1205 different types of food matrices (ready-to-eat, meats, and meat products, bakery and pastry products, baby foods, food supplements, pasta, fish and fish products, preparations for soups and broths) were delivered to Food Control Laboratory of Istituto Zooprofilattico Sperimentale of Piemonte Liguria and Valle d’Aosta to be analyzed as official samples in the frame of Regional Monitoring Plan of Food Safety or in the contest of food poisoning. The laboratory is ISO 17025 accredited, and since 2019, it has represented the National Reference Centre for the detection in foods of substances causing food allergies or intolerances (CreNaRiA). All samples were stored in the laboratory according to food business operator instructions and analyzed within the expiry date for the detection of undeclared egg proteins. Analyses were performed with RIDASCREEN®FAST Ei/Egg (R-Biopharm ® Italia srl) kit: the method was internally validated and accredited with a Limit of Detection (LOD) equal to 2 ppm (mg/Kg). It is a sandwich enzyme immunoassay for the quantitative analysis of whole egg powder in foods. Results: The results obtained through this study showed that egg proteins were found in 2% (n. 28) of food matrices, including meats and meat products (n. 16), fish and fish products (n. 4), bakery and pastry products (n. 4), pasta (n. 2), preparations for soups and broths (n.1) and ready-to-eat (n. 1). In particular, in 2011 egg proteins were detected in 5% of samples, in 2012 in 4%, in 2013, 2016 and 2018 in 2%, in 2014, 2015 and 2019 in 3%. No egg protein traces were detected in 2017, 2020, and 2021. Discussion: Food allergies occur in the Western World in 2% of adults and up to 8% of children. Allergy to eggs is one of the most common food allergies in the pediatrics context. The percentage of positivity obtained from this study is, however, low. The trend over the ten years has been slightly variable, with comparable data.

Keywords: allergens, food, egg proteins, immunoassay

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Authors: Igor V. Grigoriev

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Understanding of biological processes encoded in fungi is instrumental in addressing future food, feed, and energy demands of the growing human population. Genomics is a powerful and quickly evolving tool to understand these processes. The Fungal Genomics Program of the US Department of Energy Joint Genome Institute (JGI) partners with researchers around the world to explore fungi in several large scale genomics projects, changing the fungal genomics landscape. The key trends of these changes include: (i) rapidly increasing scale of sequencing and analysis, (ii) developing approaches to go beyond culturable fungi and explore fungal ‘dark matter,’ or unculturables, and (iii) functional genomics and multi-omics data integration. Power of comparative genomics has been recently demonstrated in several JGI projects targeting mycorrhizae, plant pathogens, wood decay fungi, and sugar fermenting yeasts. The largest JGI project ‘1000 Fungal Genomes’ aims at exploring the diversity across the Fungal Tree of Life in order to better understand fungal evolution and to build a catalogue of genes, enzymes, and pathways for biotechnological applications. At this point, at least 65% of over 700 known families have one or more reference genomes sequenced, enabling metagenomics studies of microbial communities and their interactions with plants. For many of the remaining families no representative species are available from culture collections. To sequence genomes of unculturable fungi two approaches have been developed: (a) sequencing DNA from fruiting bodies of ‘macro’ and (b) single cell genomics using fungal spores. The latter has been tested using zoospores from the early diverging fungi and resulted in several near-complete genomes from underexplored branches of the Fungal Tree, including the first genomes of Zoopagomycotina. Genome sequence serves as a reference for transcriptomics studies, the first step towards functional genomics. In the JGI fungal mini-ENCODE project transcriptomes of the model fungus Neurospora crassa grown on a spectrum of carbon sources have been collected to build regulatory gene networks. Epigenomics is another tool to understand gene regulation and recently introduced single molecule sequencing platforms not only provide better genome assemblies but can also detect DNA modifications. For example, 6mC methylome was surveyed across many diverse fungi and the highest among Eukaryota levels of 6mC methylation has been reported. Finally, data production at such scale requires data integration to enable efficient data analysis. Over 700 fungal genomes and other -omes have been integrated in JGI MycoCosm portal and equipped with comparative genomics tools to enable researchers addressing a broad spectrum of biological questions and applications for bioenergy and biotechnology.

Keywords: fungal genomics, single cell genomics, DNA methylation, comparative genomics

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Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

Procedia PDF Downloads 149

Authors: Chang-Hui Shen, Paulina Konarzewska

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Cell homeostasis is regulated by vacuolar activity and it has been shown that lipid composition of the vacuole plays an important role in vacuolar function. The major phosphoinositide species present in the vacuolar membrane include phosphatidylinositol 3,5-biphosphate (PI(3,5)P₂) which is generated from PI(3)P controlled by Fab1p. Deletion of FAB1 gene reduce the synthesis of PI(3,5)P₂ and thus result in enlarged or fragmented vacuoles, with neutral vacuolar pH due to reduced vacuolar H⁺-ATPase activity. These mutants also exhibited poor growth at high extracellular pH and in the presence of CaCl₂. Conversely, VPS34 regulates the synthesis of PI(3)P from phosphatidylinositol (PI), and the lack of Vps34p results in the reduction of vacuolar activity. Although the cellular observations are clear, it is still unknown about the molecular mechanism between the phospholipid biosynthesis pathway and vacuolar activity. Since both VPS34 and FAB1 are important in vacuolar activity, we hypothesize that the molecular mechanism of vacuolar function might be regulated by the transcriptional regulators of phospholipid biosynthesis. In this study, we study the role of the major phospholipid biosynthesis transcription factor, INO2, in the regulation of vacuolar activity. We first performed qRT-PCR to examine the effect of Ino2p on the expression of VPS34 and FAB1. Our results showed that VPS34 was upregulated in the presence of inositol for both WT and ino2Δ cells. However, FAB1 was only upregulated significantly in ino2Δ cells. This indicated that Ino2p might be the negative regulator for FAB1 expression. Next, growth sensitivity experiment showed that WT, vma3Δ, and ino2Δ grew well in growth medium buffered to pH 5.5 containing 10 mM CaCl₂. As cells were switched to growth medium buffered to pH 7 containing CaCl₂ WT, ino2Δ and opi1Δ showed growth reduction, whereas vma3Δ was completely nonviable. As the concentration of CaCl₂ was increased to 60 mM, ino2Δ cells showed moderate growth reduction compared to WT. This result suggests that ino2Δ cells have better vacuolar activity. Microscopic analysis and vacuolar acidification were employed to further elucidate the importance of INO2 in vacuolar homeostasis. Analysis of vacuolar morphology indicated that WT and vma3Δ cells displayed vacuoles that occupied a small area of the cell when grown in media buffered to pH 5.5. Whereas, ino2Δ displayed fragmented vacuoles. On the other hand, all strains grown in media buffered to pH 7, exhibited enlarged vacuoles that occupied most of the cell’s surface. This indicated that the presence of INO2 may play negative effect in vacuolar morphology when cells are grown in media buffered to pH 5.5. Furthermore, vacuolar acidification assay showed that only vma3Δ cells displayed notably less acidic vacuoles as cells were grown in media buffered to pH 5.5 and pH 7. Whereas, ino2Δ cells displayed more acidic pH compared to WT at pH7. Taken together, our results demonstrated the molecular mechanism of the vacuolar activity regulated by the phospholipid biosynthesis transcription factors Ino2p. Ino2p negatively regulates vacuolar activity through the expression of FAB1.

Keywords: vacuole, phospholipid, homeostasis, Ino2p, FAB1

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

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Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, a new set of metrics and measurement system is needed to better quantify the environmental, social and economic impacts of circular zero-waste design. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. Lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. In particular, the forestry-based plants which have been an invaluable outlet for woody biomass surplus, forest health improvement, timber production enhancement, and especially reduction of wildfire risk. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. It proposes not only models for integration of forestry, aquaculture, and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. Typically, life cycle analyses measure environmental impacts of different industrial production stages and are not integrated with indicators of material use circularity. This concept paper proposes the further development of a new set of metrics that would illustrate not only the typical life-cycle analysis (LCA), which shows the reduction in greenhouse gas (GHG) emissions, but also the zero-waste circularity measures of mass balance of the full value chain of the raw material and energy content/caloric value. These new measures quantify key impacts in making hyper-efficient use of natural resources and eliminating waste to landfills. The project utilized traditional LCA using the GREET model where the standalone biomass energy plant case was contrasted with the integration of a jet-fuel biorefinery. The methodology was then expanded to include combinations of co-hosts that optimize the life cycle of woody biomass from tree to energy, CO₂, heat and wood ash both from an energy/caloric value and for mass balance to include reuse of waste streams which are typically landfilled. The major findings of both a formal LCA study resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. If proven as a model, the expedited roll-out of these innovative scenarios can set a new standard for circular zero-waste projects that advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable bio-economy paradigm where waste streams become valuable inputs, supporting local and rural communities in simple, sustainable ways.

Keywords: bio-economy, biomass energy, financing, metrics

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Authors: Fabrizio Ascione, Martina Borrelli, Rosa Francesca De Masi, Silvia Ruggiero, Giuseppe Peter Vanoli

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The refurbishment of public buildings is one of the key factors of energy efficiency policy of European States. Educational buildings account for the largest share of the oldest edifice with interesting potentialities for demonstrating best practice with regards to high performance and low and zero-carbon design and for becoming exemplar cases within the community. In this context, this paper discusses the critical issue of dealing the energy refurbishment of a university building in heating dominated climate of South Italy. More in detail, the importance of using validated models will be examined exhaustively by proposing an analysis on uncertainties due to modelling assumptions mainly referring to the adoption of stochastic schedules for occupant behavior and equipment or lighting usage. Indeed, today, the great part of commercial tools provides to designers a library of possible schedules with which thermal zones can be described. Very often, the users do not pay close attention to diversify thermal zones and to modify or to adapt predefined profiles, and results of designing are affected positively or negatively without any alarm about it. Data such as occupancy schedules, internal loads and the interaction between people and windows or plant systems, represent some of the largest variables during the energy modelling and to understand calibration results. This is mainly due to the adoption of discrete standardized and conventional schedules with important consequences on the prevision of the energy consumptions. The problem is surely difficult to examine and to solve. In this paper, a sensitivity analysis is presented, to understand what is the order of magnitude of error that is committed by varying the deterministic schedules used for occupation, internal load, and lighting system. This could be a typical uncertainty for a case study as the presented one where there is not a regulation system for the HVAC system thus the occupant cannot interact with it. More in detail, starting from adopted schedules, created according to questioner’ s responses and that has allowed a good calibration of energy simulation model, several different scenarios are tested. Two type of analysis are presented: the reference building is compared with these scenarios in term of percentage difference on the projected total electric energy need and natural gas request. Then the different entries of consumption are analyzed and for more interesting cases also the comparison between calibration indexes. Moreover, for the optimal refurbishment solution, the same simulations are done. The variation on the provision of energy saving and global cost reduction is evidenced. This parametric study wants to underline the effect on performance indexes evaluation of the modelling assumptions during the description of thermal zones.

Keywords: energy simulation, modelling calibration, occupant behavior, university building

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Authors: Pinzhe Zhao

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This study focuses on predicting university students' cheating tendencies using psychological traits and machine learning techniques. Academic dishonesty is a significant issue that compromises the integrity and fairness of educational institutions. While much research has been dedicated to detecting cheating behaviors after they have occurred, there is limited work on predicting such tendencies before they manifest. The aim of this research is to develop a model that can identify students who are at higher risk of engaging in academic misconduct, allowing for earlier interventions to prevent such behavior. Psychological factors are known to influence students' likelihood of cheating. Research shows that traits such as test anxiety, moral reasoning, self-efficacy, and achievement motivation are strongly linked to academic dishonesty. High levels of anxiety may lead students to cheat as a way to cope with pressure. Those with lower self-efficacy are less confident in their academic abilities, which can push them toward dishonest behaviors to secure better outcomes. Students with weaker moral judgment may also justify cheating more easily, believing it to be less wrong under certain conditions. Achievement motivation also plays a role, as students driven primarily by external rewards, such as grades, are more likely to cheat compared to those motivated by intrinsic learning goals. In this study, data on students’ psychological traits is collected through validated assessments, including scales for anxiety, moral reasoning, self-efficacy, and motivation. Additional data on academic performance, attendance, and engagement in class are also gathered to create a more comprehensive profile. Using machine learning algorithms such as Random Forest, Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks, the research builds models that can predict students’ cheating tendencies. These models are trained and evaluated using metrics like accuracy, precision, recall, and F1 scores to ensure they provide reliable predictions. The findings demonstrate that combining psychological traits with machine learning provides a powerful method for identifying students at risk of cheating. This approach allows for early detection and intervention, enabling educational institutions to take proactive steps in promoting academic integrity. The predictive model can be used to inform targeted interventions, such as counseling for students with high test anxiety or workshops aimed at strengthening moral reasoning. By addressing the underlying factors that contribute to cheating behavior, educational institutions can reduce the occurrence of academic dishonesty and foster a culture of integrity. In conclusion, this research contributes to the growing body of literature on predictive analytics in education. It offers a approach by integrating psychological assessments with machine learning to predict cheating tendencies. This method has the potential to significantly improve how academic institutions address academic dishonesty, shifting the focus from punishment after the fact to prevention before it occurs. By identifying high-risk students and providing them with the necessary support, educators can help maintain the fairness and integrity of the academic environment.

Keywords: academic dishonesty, cheating prediction, intervention strategies, machine learning, psychological traits, academic integrity

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Authors: Yasmine Salehy, Yann Leroy, Francois Cluzel, Hong-Minh Hoang, Laurence Fournaison, Anthony Delahaye, Bernard Yannou

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Taking into consideration all the life cycle of a product is now an important step in the eco-design of a product or a technology. Life cycle assessment (LCA) is a standard tool to evaluate the environmental impacts of a system or a process. Despite the improvement in refrigerant regulation through protocols, the environmental damage of refrigeration systems remains important and needs to be improved. In this paper, the environmental impacts of refrigeration systems in a typical supermarket are compared using the LCA methodology under different conditions. The system is used to provide cold at two levels of temperature: medium and low temperature during a life period of 15 years. The most commonly used architectures of supermarket cold production systems are investigated: centralized direct expansion systems and indirect systems using a secondary loop to transport the cold. The variation of power needed during seasonal changes and during the daily opening/closure periods of the supermarket are considered. R134a as the primary refrigerant fluid and two types of secondary fluids are considered. The composition of each system and the leakage rate of the refrigerant through its life cycle are taken from the literature and industrial data. Twelve scenarios are examined. They are based on the variation of three parameters, 1. location: France (Paris), Spain (Toledo) and Sweden (Stockholm), 2. different sources of electric consumption: photovoltaic panels and low voltage electric network and 3. architecture: direct and indirect refrigeration systems. OpenLCA, SimaPro softwares, and different impact assessment methods were compared; CML method is used to evaluate the midpoint environmental indicators. This study highlights the significant contribution of electric consumption in environmental damages compared to the impacts of refrigerant leakage. The secondary loop allows lowering the refrigerant amount in the primary loop which results in a decrease in the climate change indicators compared to the centralized direct systems. However, an exhaustive cost evaluation (CAPEX and OPEX) of both systems shows more important costs related to the indirect systems. A significant difference between the countries has been noticed, mostly due to the difference in electric production. In Spain, using photovoltaic panels helps to reduce efficiently the environmental impacts and the related costs. This scenario is the best alternative compared to the other scenarios. Sweden is a country with less environmental impacts. For both France and Sweden, the use of photovoltaic panels does not bring a significant difference, due to a less sunlight exposition than in Spain. Alternative solutions exist to reduce the impact of refrigerating systems, and a brief introduction is presented.

Keywords: eco-design, industrial engineering, LCA, refrigeration system

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Authors: Monika Trzaskowska, Dorota Zielinska, Anna Lepecka, Katarzyna Neffe-Skocinska, Beata Bilska, Marzena Tomaszewska, Danuta Kolozyn-Krajewska

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Microbiological quality and food safety are important food characteristics. Regulation (EU) No 1169/2011 of the European Parliament and of the Council on the provision of food information to consumers introduces the obligation to provide information on the 'use-by' date or the date of minimum durability (DMD). The second term is the date until which the properly stored or transported foodstuff retains its physical, chemical, microbiological and organoleptic properties. The date should be preceded by 'best before'. It is used for durable products, e.g., pasta. In relation to reducing food losses, the question may be asked whether products with the date of minimum durability currently declared retain quality and safety beyond this. The aim of the study was to assess the sensory quality and microbiological safety of selected cereal products, i.e., pasta and millet after DMD. The scope of the study was to determine the markers of microbiological quality, i.e., the total viable count (TVC), the number of bacteria from the Enterobacteriaceae family and the number of yeast and mold (TYMC) on the last day of DMD and after 1 and 3 months of storage. In addition, the presence of Salmonella and Listeria monocytogenes was examined on the last day of DMD. The sensory quality of products was assessed by quantitative descriptive analysis (QDA), the intensity of 14 differentiators and overall quality were defined and determined. In the tested samples of millet and pasta, no pathogenic bacteria Salmonella and Listeria monocytogenes were found. The value of the distinguishing features of selected quality and microbiological safety indicators on the last DMD day was in the range of about 3-1 log cfu/g. This demonstrates the good microbiological quality of the tested food. Comparing the products, a higher number of microorganisms was found in the samples of millet. After 3 months of storage, TVC decreased in millet, while in pasta, it was found to increase in value. In both products, the number of bacteria from the Enterobacretiaceae family decreased. In contrast, the number of TYMCs increased in samples of millet, and in pasta decreased. The intensity of sensory characteristic in the studied period varied. It remained at a similar level or increased. Millet was found to increase the intensity and flavor of 'cooked porridge' 3 months after DMD. Similarly, in the pasta, the smell and taste of 'cooked pasta' was more intense. To sum up, the researched products on the last day of the minimum durability date were characterized by very good microbiological and sensory quality, which was maintained for 3 months after this date. Based on these results, the date of minimum durability of tested products could be extended. The publication was financed on the basis of an agreement with the National Center for Research and Development No. Gospostrateg 1/385753/1/NCBR/2018 for the implementation and financing of the project under the strategic research and development program 'social and economic development of Poland in the conditions of globalizing markets – GOSPOSTRATEG - acronym PROM'.

Keywords: date of minimum durability, food losses, food quality and safety, millet, pasta

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Authors: Ilana Singer, Anastasia Lučić, Julie Leclerc

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Introduction: Tics, characterized by repetitive, sudden, non-voluntary motor movements or vocalizations, are prevalent in chronic tic disorder (CT) and Tourette Syndrome (TS). These neurodevelopmental disorders often coexist with various psychiatric conditions, leading to challenges and reduced quality of life. While medication in conjunction with behavioral interventions, such as Habit Reversal Training (HRT), Exposure Response Prevention (ERP), and Comprehensive Behavioral Intervention for Tics (CBIT), has shown efficacy, a significant proportion of patients experience persistent tics. Thus, innovative treatment approaches are necessary to improve therapeutic outcomes, such as mindfulness-based approaches. Nonetheless, the effectiveness of mindfulness-based interventions in the context of CT and TS remains understudied. Objective: The objective of this scoping review is to provide an overview of the current state of research on mindfulness-based interventions for CT and TS, identify knowledge and evidence gaps, discuss the effectiveness of mindfulness-based interventions with other treatment options, and discuss implications for clinical practice and policy development. Method: Using guidelines from Peters (2020) and the PRISMA-ScR, a scoping review was conducted. Multiple electronic databases were searched from inception until June 2023, including MEDLINE, EMBASE, PsychInfo, Global Health, PubMed, Web of Science, and Érudit. Inclusion criteria were applied to select relevant studies, and data extraction was independently performed by two reviewers. Results: Five papers were included in the study. Firstly, we found that mindfulness interventions were found to be effective in reducing anxiety and depression while enhancing overall well-being in individuals with tics. Furthermore, the review highlighted the potential role of mindfulness in enhancing functional connectivity within the Default Mode Network (DMN) as a compensatory function in TS patients. This suggests that mindfulness interventions may complement and support traditional therapeutic approaches, particularly HRT, by positively influencing brain networks associated with tic regulation and control. Conclusion: This scoping review contributes to the understanding of the effectiveness of mindfulness-based interventions in managing CT and TS. By identifying research gaps, this review can guide future investigations and interventions to improve outcomes for individuals with CT or TS. Overall, these findings emphasize the potential benefits of incorporating mindfulness-based interventions as a smaller subset within comprehensive treatment strategies. However, it is essential to acknowledge the limitations of this scoping review, such as the exclusion of a pre-established protocol and the limited number of studies available for inclusion. Further research and clinical exploration are necessary to better understand the specific mechanisms and optimal integration of mindfulness-based interventions with existing behavioral interventions for this population.

Keywords: scoping reviews, Tourette Syndrome, tics, mindfulness-based, therapy, intervention

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Suikinai Nobre Santos, Ranko Gacesa, Paul F. Long, Itamar Soares de Melo

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Extremophilic microorganism are adapted to biotopes combining several stress factors (temperature, pressure, radiation, salinity and pH), which indicate the richness valuable resource for the exploitation of novel biotechnological processes and constitute unique models for investigations their biomolecules (1, 2). The above information encourages us investigate bioprospecting synthesized compounds by a noval actinomycete, designated thermotolerant Streptomyces caatingaensis CMAA 1322, isolated from sample soil tropical dry forest (Caatinga) in the Brazilian semiarid region (3-17°S and 35-45°W). This set of constrating physical and climatic factores provide the unique conditions and a diversity of well adapted species, interesting site for biotechnological purposes. Preliminary studies have shown the great potential in the production of cytotoxic, pesticidal and antimicrobial molecules (3). Thus, to extend knowledge of the genes clusters responsible for producing biosynthetic pathways of natural products in strain CMAA1322, whole-genome shotgun (WGS) DNA sequencing was performed using paired-end long sequencing with PacBio RS (Pacific Biosciences). Genomic DNA was extracted from a pure culture grown overnight on LB medium using the PureLink genomic DNA kit (Life Technologies). An approximately 3- to 20-kb-insert PacBio library was constructed and sequenced on an 8 single-molecule real-time (SMRT) cell, yielding 116,269 reads (average length, 7,446 bp), which were allocated into 18 contigs, with 142.11x coverage and N50 value of 20.548 bp (BioProject number PRJNA288757). The assembled data were analyzed by Rapid Annotations using Subsystems Technology (RAST) (4) the genome size was found to be 7.055.077 bp, comprising 6167 open reading frames (ORFs) and 413 subsystems. The G+C content was estimated to be 72 mol%. The closest-neighbors tool, available in RAST through functional comparison of the genome, revealed that strain CMAA1322 is more closely related to Streptomyces hygroscopicus ATCC 53653 (similarity score value, 537), S. violaceusniger Tu 4113 (score value, 483), S. avermitilis MA-4680 (score value, 475), S. albus J1074 (score value, 447). The Streptomyces sp. CMAA1322 genome contains 98 tRNA genes and 135 genes copies related to stress response, mainly osmotic stress (14), heat shock (16), oxidative stress (49). Functional annotation by antiSMASH version 3.0 (5) identified 41 clusters for secondary metabolites (including two clusters for lanthipeptides, ten clusters for nonribosomal peptide synthetases [NRPS], three clusters for siderophores, fourteen for polyketide synthetase [PKS], six clusters encoding a terpene, two clusters encoding a bacteriocin, and one cluster encoding a phenazine). Our work provide in comparative analyse of genome and extract produced (data no published) by lineage CMAA1322, revealing the potential of microorganisms accessed from extreme environments as Caatinga” to produce a wide range of biotechnological relevant compounds.

Keywords: caatinga, streptomyces, environmental stresses, biosynthetic pathways

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Authors: Swati Srivastava, Mattia Lauriola, Yuval Gilad, Adi Kimchi, Yosef Yarden

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The glucocorticoid receptor (GR) has been proposed to play important, but incompletely understood roles in cancer. Glucocorticoids (GCs) are widely used as co-medication of various carcinomas, due to their ability to reduce the toxicity of chemotherapy. Furthermore, GR antagonism has proven to be a strategy to treat triple negative breast cancer and castration-resistant prostate cancer. These observations suggest differential GR involvement in cancer subtypes. The goal of our study has been to elaborate the current understanding of GR signaling in tumor progression and metastasis. Our study involves two cellular models, non-tumorigenic breast epithelial cells (MCF10A) and Ewing sarcoma cells (CHLA9). In our breast cell model, the results indicated that the GR agonist dexamethasone inhibits EGF-induced mammary cell migration, and this effect was blocked when cells were stimulated with a GR antagonist, namely RU486. Microarray analysis for gene expression revealed that the mechanism underlying inhibition involves dexamenthasone-mediated repression of well-known activators of EGFR signaling, alongside with enhancement of several EGFR’s negative feedback loops. Because GR mainly acts primarily through composite response elements (GREs), or via a tethering mechanism, our next aim has been to find the transcription factors (TFs) which can interact with GR in MCF10A cells.The TF-binding motif overrepresented at the promoter of dexamethasone-regulated genes was predicted by using bioinformatics. To validate the prediction, we performed high-throughput Protein Complementation Assays (PCA). For this, we utilized the Gaussia Luciferase PCA strategy, which enabled analysis of protein-protein interactions between GR and predicted TFs of mammary cells. A library comprising both nuclear receptors (estrogen receptor, mineralocorticoid receptor, GR) and TFs was fused to fragments of GLuc, namely GLuc(1)-X, X-GLuc(1), and X-GLuc(2), where GLuc(1) and GLuc(2) correspond to the N-terminal and C-terminal fragments of the luciferase gene.The resulting library was screened, in human embryonic kidney 293T (HEK293T) cells, for all possible interactions between nuclear receptors and TFs. By screening all of the combinations between TFs and nuclear receptors, we identified several positive interactions, which were strengthened in response to dexamethasone and abolished in response to RU486. Furthermore, the interactions between GR and the candidate TFs were validated by co-immunoprecipitation in MCF10A and in CHLA9 cells. Currently, the roles played by the uncovered interactions are being evaluated in various cellular processes, such as cellular proliferation, migration, and invasion. In conclusion, our assay provides an unbiased network analysis between nuclear receptors and other TFs, which can lead to important insights into transcriptional regulation by nuclear receptors in various diseases, in this case of cancer.

Keywords: epidermal growth factor, glucocorticoid receptor, protein complementation assay, transcription factor

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Authors: John G. Skelly, Peter K. Dearden, Thomas W. R. Harrop, Sarah N. Inwood, Joseph Guhlin

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The Argentine stem weevil (ASW; L. bonariensis) is an economically important pasture pest in New Zealand, which causes about $200 million of damage per annum. Microctonus hyperodae (Mh), a parasite of the ASW in its natural range in South America, was introduced into New Zealand to curb the pasture damage caused by the ASW. Mh is an endoparasitic wasp that lays its eggs in the ASW halting its reproduction. Mh was initially successful at preventing ASW proliferation and reducing pasture damage. The effectiveness of Mh has since declined due to decreased parasitism rates and has resulted in increased pasture damage. Although the mechanism through which ASW has developed resistance to Mh has not been discovered, it has been proposed to be due to the different reproductive modes used by Mh and the ASW in New Zealand. The ASW reproduces sexually, whereas Mh reproduces asexually, which has been hypothesised to have allowed the ASW to ‘out evolve’ Mh. Other species within the Microctonus genus reproduce both sexually and asexually. Strains of Microctonus aethiopoides (Ma), a species closely related to Mh, reproduce either by sexual or asexual reproduction. Comparing the genomes of sexual and asexual Microctonus may allow for the identification of the mechanism of asexual reproduction and other characteristics that may improve Mh as a biocontrol agent. The genomes of Mh and three strains of Ma, two of which reproduce sexually and one reproduces asexually, have been sequenced and annotated. The French (MaFR) and Moroccan (MaMO) reproduce sexually, whereas the Irish strain (MaIR) reproduces asexually. Like Mh, The Ma strains are also used as biocontrol agents, but for different weevil species. The genomes of Mh and MaIR were subsequently upgraded using Hi-C, resulting in a set of high quality, highly contiguous genomes. A subset of the genes involved in mitosis and meiosis, which have been identified though the use of Hidden Markov Models generated from genes involved in these processes in other Hymenoptera, have been catalogued in Mh and the strains of Ma. Meiosis and mitosis genes were broadly conserved in both sexual and asexual Microctonus species. This implies that either the asexual species have retained a subset of the molecular components required for sexual reproduction or that the molecular mechanisms of mitosis and meiosis are different or differently regulated in Microctonus to other insect species in which these mechanisms are more broadly characterised. Bioinformatic analysis of the chemoreceptor compliment in Microctonus has revealed some variation in the number of olfactory receptors, which may be related to host preference. Phylogenetic analysis of olfactory receptors highlights variation, which may be able to explain different host range preferences in the Microctonus. Hi-C clustering implies that Mh has 12 chromosomes, and MaIR has 8. Hence there may be variation in gene regulation between species. Genome alignment of Mh and MaIR implies that there may be large scale genome structural variation. Greater insight into the genetics of these agriculturally important group of parasitic wasps may be beneficial in restoring or maintaining their biocontrol efficacy.

Keywords: argentine stem weevil, asexual, genomics, Microctonus hyperodae

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Authors: Yusuf Ahmad Sani, Adamu Alhaji Yakubu, Alhaji Abdullahi Jamilu, Joel Omeke, Ibrahim Jumare Sambo

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With the rising global threat of food security, cancer, and related diseases (carcinogenic) because of increased usage of inorganic substances in agricultural food production, the Ministry of Food Agriculture and Livestock of the Republic of Turkey organized an International Workshop on Organic Agriculture between 8 – 12th December 2014 at the International Agricultural Research and Training Center, Izmir. About 21 countries, including Nigeria, were invited to attend the training workshop. Several topics on organic agriculture were presented by renowned scholars, ranging from regulation, certification, crop, animal, seed production, pest and disease management, soil composting, and marketing of organic agricultural products, among others. This paper purposely selected two countries (Macedonia and Iran) out of the 21 countries to assess their level of development in terms of organic agriculture as compared to Nigeria. Macedonia, with a population of only 2.1 million people as of 2014, started organic agriculture in 2005 with only 266ha of land and has grown significantly to over 5,000ha in 2010, covering such crops as cereals (62%), forage (20%) fruit orchard (7%), vineyards (5%), vegetables (4%), oil seed and industrial crops (1%) each. Others are organic beekeeping from 110 hives to over 15,000 certified colonies. As part of government commitment, the level of government subsidy for organic products was 30% compared to the direct support for conventional agricultural products. About 19 by-laws were introduced on organic agricultural production that was fully consistent with European Union regulations. The republic of Iran, on the other hand, embarked on organic agriculture for the fact, that the country recorded the highest rate of cancer disease in the world, with over 30,000 people dying every year and 297 people diagnosed every day. However, the host country, Turkey, is well advanced in organic agricultural production and now being the largest exporter of organic products to Europe and other parts of the globe. A technical trip to one of the villages that are under the government scheme on organic agriculture reveals that organic agriculture was based on market-demand-driven and the support of the government was very visible, linking the farmers with private companies that provide inputs to them while the companies purchase the products at harvest with high premium price. However, in Nigeria, research on organic agriculture was very recent, and there was very scanty information on organic agriculture due to poor documentation and very low awareness, even among the elites. The paper, therefore, recommends that the government should provide funds to NARIs to conduct research on organic agriculture and to establish clear government policy and good pre-conditions for sustainable organic agricultural production in the country.

Keywords: organic agriculture, food security, food safety, food nutrition

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Authors: Ekatereine Abashidze, Nino Nazarashvili, Dali Gaganidze, Oleg Gorgadze, Mariam Aznarashvili, Eter Gvritishvili

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Potato is one of the leading agricultural crops in Georgia. Georgia produces early and late potato varieties in almost all regions. Potato production is equal to 25,000 ha and its average yield is 20-25 t/ha. Among the plant pests that limit potato production and quality, the potato cyst nematodes (Globodera pallida (Stone) Behrens and Globodera rostochiensis (Wollenveber) Behrens) are harmful around the world. PCN is among the most difficult plant pests to control. Cysts protected by a durable wall can survive for over 30 years . Control of PCN (G. pallida and G. rostochiensis) is regulated by Council Directive 2007/33/EE C. There was no legislative regulation of these pests in Georgia before 2016. By Resolution #302 from July 1, 2016, developed within the action plan of the DCFTA (Deep and Comprehensive Free Trade Area) the Government of Georgia established control over potato cyst nematodes. The Agreement about the legal acts approximation to EU legislation concerns the approval of rules of PCN control and research of these pests. Taking into consideration the above mentioned, it is necessary to study PCN (G. pallida and G. rostochiensis) in the potato-growing areas of Georgia. The aim of this research is to conduct survey of potato cyst nematodes (Globodera rostochiensis and G. pallida) in two geographically distinct regions of Georgia - Samtskhe - Javakheti and Svanetii and to identify the species G. Rostochiensis and G. Pallida by the morphological - morphometric and molecular methods. Soil samples were taken in each village, in a zig-zag pattern on the potato fields of the private sector, using the Metlitsky method. Samples were taken also from infested potato plant roots. To extract nematode cysts from soil samples Fanwick can be used according to standard methods by EPPO. Cysts were measured under a stereoscopic microscope (Leica M50). Identification of the nematod species was carried out according to morphological and morphometric characteristics of the cysts and larvae using appropriate protocols EPPO. For molecular identification, a multiplex PCR test was performed by the universal ITS5 and cyst nematodes’ (G. pallida, G. rostochiensis) specific primers. To identify the species of potato cyst nematodes (PCN) in two regions (Samtskhe-Javakheti and Svaneti) were taken 200 samples, among them: 80 samples in Samtskhe-Javakheti region and 120 in Svaneti region. Cysts of Globiodera spp. were revealed in 50 samples obtained from Samtskhe-Javakheti and 80 samples from Svaneti regions. Morphological, morphometric and molecular analysis of two forms of PCN found in investigated regions of Georgia shows that one form of PCN belongs to G. rostoshiensi; the second form is the different species of Globodera sp.t is the subject of future research. Despite the different geographic locations, larvae and cysts of G. rostoshiensi were found in both regions. But cysts and larvae of G. pallida were not reported. Acknowledgement: The research has been supported by the Shota Rustaveli National Scientific Foundation of Georgia: Project # FR17_235.

Keywords: cyst nematode, globodera rostochiensis, globodera pallida, morphologic-morphometric measurement

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Authors: Antònio Inês, Davide Silva, Filipa Carvalho, Luís Filipe-Riberiro, Fernando M. Nunes, Luís Abrunhosa, Fernanda Cosme

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The presence of mycotoxins in foodstuff is a matter of concern for food safety. Mycotoxins are toxic secondary metabolites produced by certain molds, being ochratoxin A (OTA) one of the most relevant. Wines can also be contaminated with these toxicants. Several authors have demonstrated the presence of mycotoxins in wine, especially ochratoxin A. Its chemical structure is a dihydro-isocoumarin connected at the 7-carboxy group to a molecule of L-β-phenylalanine via an amide bond. As these toxicants can never be completely removed from the food chain, many countries have defined levels in food in order to attend health concerns. OTA contamination of wines might be a risk to consumer health, thus requiring treatments to achieve acceptable standards for human consumption. The maximum acceptable level of OTA in wines is 2.0 μg/kg according to the Commission regulation No. 1881/2006. Therefore, the aim of this work was to reduce OTA to safer levels using different fining agents, as well as their impact on white wine physicochemical characteristics. To evaluate their efficiency, 11 commercial fining agents (mineral, synthetic, animal and vegetable proteins) were used to get new approaches on OTA removal from white wine. Trials (including a control without addition of a fining agent) were performed in white wine artificially supplemented with OTA (10 µg/L). OTA analyses were performed after wine fining. Wine was centrifuged at 4000 rpm for 10 min and 1 mL of the supernatant was collected and added of an equal volume of acetonitrile/methanol/acetic acid (78:20:2 v/v/v). Also, the solid fractions obtained after fining, were centrifuged (4000 rpm, 15 min), the resulting supernatant discarded, and the pellet extracted with 1 mL of the above solution and 1 mL of H2O. OTA analysis was performed by HPLC with fluorescence detection. The most effective fining agent in removing OTA (80%) from white wine was a commercial formulation that contains gelatin, bentonite and activated carbon. Removals between 10-30% were obtained with potassium caseinate, yeast cell walls and pea protein. With bentonites, carboxymethylcellulose, polyvinylpolypyrrolidone and chitosan no considerable OTA removal was verified. Following, the effectiveness of seven commercial activated carbons was also evaluated and compared with the commercial formulation that contains gelatin, bentonite and activated carbon. The different activated carbons were applied at the concentration recommended by the manufacturer in order to evaluate their efficiency in reducing OTA levels. Trial and OTA analysis were performed as explained previously. The results showed that in white wine all activated carbons except one reduced 100% of OTA. The commercial formulation that contains gelatin, bentonite and activated carbon reduced only 73% of OTA concentration. These results may provide useful information for winemakers, namely for the selection of the most appropriate oenological product for OTA removal, reducing wine toxicity and simultaneously enhancing food safety and wine quality.

Keywords: wine, ota removal, food safety, fining

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Authors: Hantian Wu, Bo Huang, Yuan Zeng

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Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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Authors: Soraia V. M. de Sá, Miguel A. Faria, José O. Fernandes, Sara C. Cunha

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Cereals play a vital role in fulfilling the nutritional needs of children, supplying essential nutrients crucial for their growth and development. However, concerns arise due to children's heightened vulnerability due to their unique physiology, specific dietary requirements, and relatively higher intake in relation to their body weight. This vulnerability exposes them to harmful food contaminants, particularly mycotoxins, prevalent in cereals. Because of the thermal stability of mycotoxins, conventional industrial food processing often falls short of eliminating them. Children, especially those aged 4 months to 12 years, frequently encounter mycotoxins through the consumption of specialized food products, such as instant foods, breakfast cereals, bars, cookie snacks, fruit puree, and various dairy items. A close monitoring of this demographic group's exposure to mycotoxins is essential, as toxins ingestion may weaken children’s immune systems, reduce their resistance to infectious diseases, and potentially lead to cognitive impairments. The severe toxicity of mycotoxins, some of which are classified as carcinogenic, has spurred the establishment and ongoing revision of legislative limits on mycotoxin levels in food and feed globally. While EU Commission Regulation 1881/2006 addresses well-known mycotoxins in processed cereal-based foods and infant foods, the absence of regulations specifically addressing emerging mycotoxins underscores a glaring gap in the regulatory framework, necessitating immediate attention. Emerging mycotoxins have gained mounting scrutiny in recent years due to their pervasive presence in various foodstuffs, notably cereals and cereal-based products. Alarmingly, exposure to multiple mycotoxins is hypothesized to exhibit higher toxicity than isolated effects, raising particular concerns for products primarily aimed at children. This study scrutinizes the presence of 22 mycotoxins of the diverse range of chemical classes in 148 processed cereal-based foods, including 39 breakfast cereals, 25 infant formulas, 27 snacks, 25 cereal bars, and 32 cookies commercially available in Portugal. The analytical approach employed a modified QuEChERS procedure followed by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis. Given the paucity of information on the risk assessment of children to multiple mycotoxins in cereal and cereal-based products consumed by children of Portugal pioneers the evaluation of this critical aspect. Overall, aflatoxin B1 (AFB1) and aflatoxin G2 (AFG2) emerged as the most prevalent regulated mycotoxins, while enniatin B (ENNB) and sterigmatocystin (STG) were the most frequently detected emerging mycotoxins.

Keywords: cereal-based products, children´s nutrition, food safety, UPLC-MS/MS analysis

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Authors: Maria Jose Granero Paris, Ana Isabel Jimenez Zarco, Agustin Pablo Alvarez Herranz

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In the industrial sector collaboration with suppliers is key to the development of innovations in the field of processes. Access to resources and expertise that are not available in the business, obtaining a cost advantage, or the reduction of the time needed to carry out innovation are some of the benefits associated with the process. However, the success of this collaborative process is compromised, when from the beginning not clearly rules have been established that govern the relationship. Abundant studies developed in the field of innovation emphasize the strategic importance of the concept of “Governance”. Despite this, there have been few papers that have analyzed how the governance process of the relationship must be designed and managed to ensure the success of the collaboration process. The lack of literature in this area responds to the wide diversity of contexts where collaborative processes to innovate take place. Thus, in sectors such as the car industry there is a strong collaborative tradition between manufacturers and suppliers being part of the value chain. In this case, it is common to establish mechanisms and procedures that fix formal and clear objectives to regulate the relationship, and establishes the rights and obligations of each of the parties involved. By contrast, in other sectors, collaborative relationships to innovate are not a common way of working, particularly when their aim is the development of process improvements. It is in this case, it is when the lack of mechanisms to establish and regulate the behavior of those involved, can give rise to conflicts, and the failure of the cooperative relationship. Because of this the present paper analyzes the similarities and differences in the processes of governance in collaboration with suppliers in the European aerospace industry With these ideas in mind, we present research is twofold: Understand the importance of governance as a key element of the success of the collaboration in the development of product and process innovations, Establish the mechanisms and procedures to ensure the proper management of the processes of collaboration. Following the methodology of the case study, we analyze the way in which manufacturers and suppliers cooperate in the development of new products and processes in two industries with different levels of technological intensity and collaborative tradition: the automotive and aerospace. The identification of those elements playing a key role to establish a successful governance and relationship management and the compression of the mechanisms of regulation and control in place at the automotive sector can be use to propose solutions to some of the conflicts that currently arise in aerospace industry. The paper concludes by analyzing the strategic implications for the aerospace industry entails the adoption of some of the practices traditionally used in other industrial sectors. Finally, it is important to highlight that in this paper are presented the first results of a research project currently in progress describing a model of governance that explains the way to manage outsourced services to suppliers in the European aerospace industry, through the analysis of companies in the sector located in Germany, France and Spain.

Keywords: supplier collaboration, supplier relationship governance, innovation management, product innovation, process innovation

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Authors: P. Asiabi, M. Shahhoseini, R. Favaedi, F. Hassani, N. Nassiri, B. Movaghar, L. Karimian, P. Eftekhariyazdi

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Introduction: Polycystic Ovary Syndrome is a common gynecologic disorder. Many factors including environment, metabolism, hormones and genetics are involved in etiopathogenesis of PCOS. Of genes that have altered expression in human reproductive system disorders are HOX family genes which act as transcription factors in regulation of cell proliferation, differentiation, adhesion and migration. Since recent evidences consider epigenetic factors as causative mechanisms of PCOS, evaluation of association between known epigenetic marks of acetylation/methylation of histone 3 (H3K9ac/me) with regulatory regions of these genes can represent better insight about PCOS. In the current study, cumulus cells (CCs) which have critical roles during folliculogenesis, oocyte maturation, ovulation and fertilization were aimed to monitor epigenetic alterations of HOX genes. Material and methods: CCs were collected from 20 PCOS patients and 20 fertile women (18-36 year) with male infertility problems referred to the Royan Institute to have ICSI under GnRH antagonist protocol. Informed consents were obtained from the participants. Thirty six hours after hCG injection, ovaries were punctured and cumulus oocyte complexes were dissected. Soluble chromatin were extracted from CCs and Chromatin Immune precipitation (ChIP) coupled with Real Time PCR was performed to quantify the epigenetic marks of histone H3K9 acetylation/methylation (H3K9ac/me) on regulatory regions of 15 members of HOX genes from A-D subfamily. Results: Obtained data showed significant increase of H3K9ac epigenetic mark on regulatory regions of HOXA1, HOXB2, HOXC4, HOXD1, HOXD3 and HOXD4 (P < 0.01) and HOXC5 (P < 0.05) and also significant decrease of H3K9ac into regulatory regions of HOXA2, HOXA4, HOXA5, HOXB1 and HOXB5 (P < 0.01) and HOXB3 (P<0.05) in PCOS patients vs. control group. On the other side, there was a significant decrease in incorporation of H3K9me level on regulatory region of HOXA2, HOXA3, HOXA4, HOXA5, HOXB3 and HOXC4 (P≤0.01) and HOXB5 (P < 0.05) in PCOS patients vs. control group. This epigenetic mark (H3K9me2) has significant increase on regulatory region of HOXB1, HOXB2, HOXC5, HOXD1, HOXD3 and HOXD4 (P ≤ 0.01) and HOXB4 (P < 0.05) in patients vs. control group. There were no significant changes in acetylation/methylation levels of H3K9 on regulatory regions of the other studied genes. Conclusion: Current study suggests that epigenetic alterations of HOX genes can be correlated with PCOS and consequently female infertility. This finding might offer additional definitions of PCOS, and eventually provides insight for novel treatments with epidrugs for this disease.

Keywords: epigenetic, HOX genes, PCOS, female infertility

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Authors: Danny Barash

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Riboswitches are RNA genetic control elements that were originally discovered in bacteria and provide a unique mechanism of gene regulation. They work without the participation of proteins and are believed to represent ancient regulatory systems in the evolutionary timescale. One of the biggest challenges in riboswitch research is that many are found in prokaryotes but only a small percentage of known riboswitches have been found in certain eukaryotic organisms. The few examples of eukaryotic riboswitches were identified using sequence-based bioinformatics search methods that include some slight structural considerations. These pattern-matching methods were the first ones to be applied for the purpose of riboswitch detection and they can also be programmed very efficiently using a data structure called affix arrays, making them suitable for genome-wide searches of riboswitch patterns. However, they are limited by their ability to detect harder to find riboswitches that deviate from the known patterns. Several methods have been developed since then to tackle this problem. The most commonly used by practitioners is Infernal that relies on Hidden Markov Models (HMMs) and Covariance Models (CMs). Profile Hidden Markov Models were also carried out in the pHMM Riboswitch Scanner web application, independently from Infernal. Other computational approaches that have been developed include RMDetect by the use of 3D structural modules and RNAbor that utilizes Boltzmann probability of structural neighbors. We have tried to incorporate more sophisticated secondary structure considerations based on RNA folding prediction using several strategies. The first idea was to utilize window-based methods in conjunction with folding predictions by energy minimization. The moving window approach is heavily geared towards secondary structure consideration relative to sequence that is treated as a constraint. However, the method cannot be used genome-wide due to its high cost because each folding prediction by energy minimization in the moving window is computationally expensive, enabling to scan only at the vicinity of genes of interest. The second idea was to remedy the inefficiency of the previous approach by constructing a pipeline that consists of inverse RNA folding considering RNA secondary structure, followed by a BLAST search that is sequence-based and highly efficient. This approach, which relies on inverse RNA folding in general and our own in-house fragment-based inverse RNA folding program called RNAfbinv in particular, shows capability to find attractive candidates that are missed by Infernal and other standard methods being used for riboswitch detection. We demonstrate attractive candidates found by both the moving-window approach and the inverse RNA folding approach performed together with BLAST. We conclude that structure-based methods like the two strategies outlined above hold considerable promise in detecting riboswitches and other conserved RNAs of functional importance in a variety of organisms.

Keywords: riboswitches, RNA folding prediction, RNA structure, structure-based methods

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Authors: Rayanne Branco Dos Santos Lima, Lorena Pinheiro Barbosa, Kamila Ferreira Lima, Victor Manuel Tegoma Ruiz, Monyka Brito Lima Dos Santos, Maria Wendiane Gueiros Gaspar, Luzia Camila Coelho Ferreira, Leandro Cardozo Dos Santos Brito, Deyse Maria Alves Rocha

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Introduction: The lack of regulation of the baby's sleep-wake pattern in the first years of life affects the health of thousands of women. Maternal sleep deprivation can trigger or aggravate psychosomatic problems such as depression, anxiety and stress that can directly influence maternal safety, with consequences for the baby's and mother's sleep. Such conditions can affect the family's quality of life and child development. Objective: To correlate maternal security with maternal state anxiety scores and the mother's and baby's total sleep time. Method: Cross-sectional study carried out with 96 mothers of babies aged 10 to 24 months, accompanied by nursing professionals linked to a Federal University in Northeast Brazil. Study variables were maternal security, maternal state anxiety scores, infant latency and sleep time, and total nocturnal sleep time of mother and infant. Maternal safety was calculated using a four-point Likert scale (1=not at all safe, 2=somewhat safe, 3=very safe, 4=completely safe). Maternal anxiety was measured by State-Trait Anxiety Inventory, state-anxiety subscale whose scores vary from 20 to 80 points, and the higher the score, the higher the anxiety levels. Scores below 33 are considered mild; from 33 to 49, moderate and above 49, high. As for the total nocturnal sleep time, values between 7-9 hours of sleep were considered adequate for mothers, and values between 9-12 hours for the baby, according to the guidelines of the National Sleep Foundation. For the sleep latency time, a time equal to or less than 20 min was considered adequate. It is noteworthy that the latency time and the time of night sleep of the mother and the baby were obtained by the mother's subjective report. To correlate the data, Spearman's correlation was used in the statistical package R version 3.6.3. Results: 96 women and babies participated, aged 22 to 38 years (mean 30.8) and 10 to 24 months (mean 14.7), respectively. The average of maternal security was 2.89 (unsafe); Mean maternal state anxiety scores were 43.75 (moderate anxiety). The babies' average sleep latency time was 39.6 min (>20 min). The mean sleep times of the mother and baby were, respectively, 6h and 42min and 8h and 19min, both less than the recommended nocturnal sleep time. Maternal security was positively correlated with maternal state anxiety scores (rh=266, p=0.009) and negatively correlated with infant sleep latency (rh= -0.30. P=0.003). Baby sleep time was positively correlated with maternal sleep time. (rh 0.46, p<0.001). Conclusion: The more secure the mothers considered themselves, the higher the anxiety scores and the shorter the baby's sleep latency. Also, the longer the baby sleeps, the longer the mother sleeps. Thus, interventions are needed to promote the quality and efficiency of sleep for both mother and baby.

Keywords: sleep, anxiety, infant, mother-child relations

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Authors: Yana Posmitnaya, Galina Rudnitskaya, Tatyana Lukashenko, Anton Bukatin, Anatoly Evstrapov

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An important area of biological and medical research is the study of genetic mutations and polymorphisms that can alter gene function and cause inherited diseases and other diseases. The following methods to analyse DNA fragments are used: capillary electrophoresis and electrophoresis on microfluidic chip (MFC), mass spectrometry with electrophoresis on MFC, hybridization assay on microarray. Electrophoresis on MFC allows to analyse small volumes of samples with high speed and throughput. A soft lithography in polydimethylsiloxane (PDMS) was chosen for operative fabrication of MFCs. A master-form from silicon and photoresist SU-8 2025 (MicroChem Corp.) was created for the formation of micro-sized structures in PDMS. A universal topology which combines T-injector and simple cross was selected for the electrophoretic separation of the sample. Glass K8 and PDMS Sylgard® 184 (Dow Corning Corp.) were used for fabrication of MFCs. Electroosmotic flow (EOF) plays an important role in the electrophoretic separation of the sample. Therefore, the estimate of the quantity of EOF and the ways of its regulation are of interest for the development of the new methods of the electrophoretic separation of biomolecules. The following methods of surface modification were chosen to change EOF: high-frequency (13.56 MHz) plasma treatment in oxygen and argon at low pressure (1 mbar); 1% aqueous solution of polyvinyl alcohol; 3% aqueous solution of Kolliphor® P 188 (Sigma-Aldrich Corp.). The electroosmotic mobility was evaluated by the method of Huang X. et al., wherein the borate buffer was used. The influence of physical and chemical methods of treatment on the wetting properties of the PDMS surface was controlled by the sessile drop method. The most effective way of surface modification of MFCs, from the standpoint of obtaining the smallest value of the contact angle and the smallest value of the EOF, was the processing with aqueous solution of Kolliphor® P 188. This method of modification has been selected for the treatment of channels of MFCs, which are used for the separation of mixture of oligonucleotides fluorescently labeled with the length of chain with 10, 20, 30, 40 and 50 nucleotides. Electrophoresis was performed on the device MFAS-01 (IAI RAS, Russia) at the separation voltage of 1500 V. 6% solution of polydimethylacrylamide with the addition of 7M carbamide was used as the separation medium. The separation time of components of the mixture was determined from electropherograms. The time for untreated MFC was ~275 s, and for the ones treated with solution of Kolliphor® P 188 – ~ 220 s. Research of physical-chemical methods of surface modification of MFCs allowed to choose the most effective way for reducing EOF – the modification with aqueous solution of Kolliphor® P 188. In this case, the separation time of the mixture of oligonucleotides decreased about 20%. The further optimization of method of modification of channels of MFCs will allow decreasing the separation time of sample and increasing the throughput of analysis.

Keywords: electrophoresis, microfluidic chip, modification, nucleic acid, polydimethylsiloxane, soft lithography

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Authors: B. Ratchaneepun, N.S. Bardell

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It is recognized that people are the main drivers in almost all the processes that affect airworthiness assurance. This is especially true in the area of aircraft maintenance, which is an essential part of continuing airworthiness. This work investigates what impact English language proficiency, the intersection of the military and Thai cultures, and the lack of initial and continuing human factors training have on the work performance of maintenance personnel in the Royal Thai Air Force (RTAF). A quantitative research method based on a cross-sectional survey was used to gather data about these three key aspects of “people” in a military airworthiness environment. 30 questions were developed addressing the crucial topics of English language proficiency, impact of culture, and human factors training. The officers and the non-commissioned officers (NCOs) who work for the Aeronautical Engineering Divisions in the RTAF comprised the survey participants. The survey data were analysed to support various hypotheses by using a t-test method. English competency in the RTAF is very important since all of the service manuals for Thai military aircraft are written in English. Without such competency, it is difficult for maintenance staff to perform tasks and correctly interpret the relevant maintenance manual instructions; any misunderstandings could lead to potential accidents. The survey results showed that the officers appreciated the importance of this more than the NCOs, who are the people actually doing the hands-on maintenance work. Military culture focuses on the success of a given mission, and leverages the power distance between the lower and higher ranks. In Thai society, a power distance also exists between younger and older citizens. In the RTAF, such a combination tends to inhibit a just reporting culture and hence hinders safety. The survey results confirmed this, showing that the older people and higher ranks involved with RTAF aircraft maintenance believe that the workplace has a positive safety culture and climate, whereas the younger people and lower ranks think the opposite. The final area of consideration concerned human factors training and non-technical skills training. The survey revealed that those participants who had previously attended such courses appreciated its value and were aware of its benefits in daily life. However, currently there is no regulation in the RTAF to mandate recurrent training to maintain such knowledge and skills. The findings from this work suggest that the people involved in assuring the continuing airworthiness of the RTAF would benefit from: (i) more rigorous requirements and standards in the recruitment, initial training and continuation training regarding English competence; (ii) the development of a strong safety culture that exploits the uniqueness of both the military culture and the Thai culture; and (iii) providing more initial and recurrent training in human factors and non-technical skills.

Keywords: aircraft maintenance, continuing airworthiness, military culture, people, Royal Thai Air Force

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