Miracle-dz/UniFAR-FTUs huggingface dataset:
Interconnected vector pairs image conditions: New possibilities for visualization of acoustical media

Reflection or scattering of acoustical wave on an obstacle at any moment may be considered as interaction of two interconnected vectors: the particle velocity vector of the incident wave and the generated vector of the reflected or scattered wave. In this paper an accurate statistical analysis of the amplitudes and phases of the interconnected vectors for the whole ensemble of the time samples and sources is proposed. We have developed interconnected vector pairs image conditions that give a new look on visualization of acoustical media.
Older Adults’ Perspectives of Smart Technologies to Support Aging at Home: Insights from Five World Café Forums

Globally, there is an urgent need for solutions that can support our aging populations to live well and reduce the associated economic, social and health burdens. Implementing smart technologies within homes and communities may assist people to live well and ‘age in place’. To date, there has been little consultation with older Australians addressing either the perceived benefits, or the potential social and ethical challenges associated with smart technology use. To address this, we conducted five World Cafés in two Australian states, aiming to capture citizen knowledge about the possibilities and challenges of smart technologies. The participants (n = 84) were aged 55 years and over, English-speaking, and living independently. Grounding our analysis in values-based social science and biomedical ethical principles, we identified the themes reflecting the participants’ understanding, resistance, and acceptance of smart technologies, and the ethical principles, including beneficence, non-maleficence, autonomy, privacy, confidentiality, and justice. Similar to other studies, many of the participants demonstrated cautious and conditional acceptance of smart technologies, while identifying concerns about social isolation, breaches of privacy and confidentiality, surveillance, and stigmatization. Attention to understanding and incorporating the values of older citizens will be important for the acceptance and effectiveness of smart technologies for supporting independent and full lives for older citizens.
Derivation and Characterization of Endothelial Cells from Porcine Induced Pluripotent Stem Cells

Although the study on the regulatory mechanism of endothelial differentiation from the perspective of development provides references for endothelial cell (EC) derivation from pluripotent stem cells, incomplete reprogramming and donor-specific epigenetic memory are still thought to be the obstacles of iPSCs for clinical application. Thus, it is necessary to establish a stable iPSC-EC induction system and investigate the regulatory mechanism of endothelial differentiation. Based on a single-layer culture system, we successfully obtained ECs from porcine iPSCs (piPSCs). In vitro, the derived piPSC-ECs formed microvessel-like structures along 3D gelatin scaffolds. Under pathological conditions, the piPSC-ECs functioned on hindlimb ischemia repair by promoting blood vessel formation. To elucidate the molecular events essential for endothelial differentiation in our model, genome-wide transcriptional profile analysis was conducted, and we found that during piPSC-EC derivation, the synthesis and secretion level of TGF-β as well as the phosphorylation level of Smad2/3 changed dynamically. TGF-β-Smad2/3 signaling activation promoted mesoderm formation and prevented endothelial differentiation. Understanding the regulatory mechanism of iPSC-EC derivation not only paves the way for further optimization, but also provides reference for establishing a cardiovascular drug screening platform and revealing the molecular mechanism of endothelial dysfunction.
Microbial Communities in Peruvian Acid Mine Drainages: Low-Abundance Sulfate-Reducing Bacteria With High Metabolic Activity

Abstract We investigated the microbial community composition in three different mine tunnels from Hualgayoc (Cajamarca, Peru) and the metabolic activity of acidophilic sulfate-reducing bacteria (aSRB) enriched from acidic sediments of the mining tunnels. Microbial community composition in environmental samples was analyzed by 16S rRNA amplicon sequencing. Metallibacterium and Acidiphilium were found as the most abundant bacteria in PM1 and PM2 sites, respectively, while Cyanobacteria was abundant in PM3 site. Isosphaera and Pseudomonas thrived in the acidic water of PM2 site as well. Sulfate reduction at low pH was then evaluated in microcosm experiments showing activity even at pH 3.4. Hydrogen was the most favorable electron donor in terms of sulfate reducing rates (0.5 mM day−1 at pH 5.1) and sulfide production (4.9 mM at the end of the experiment). Sequences affiliated to Desulfosporosinus and Desulfovibrio were abundant in the hydrogen microcosms (60.3 and 17.8%, respectively). These sequences were not detected in sediments, but their occurrence in the microcosms suggests their low abundance in the studied AMD systems. Our results expand the phyla detected in AMD environments and contribute to the understanding of aSRB for the possibility of applying these microorganisms in bioremediation.
A study of the correlation between chalazion and intestinal ora in chinese children

Yuanyue Cui Shanghai Children's Medical Center Lei Song Shanghai Children's Medical Center Xie Li Shanghai Children's Medical Center Ting Qiu Shanghai Children's Medical Center Jing Jin Shanghai Children's Medical Center Keke Zhao Shanghai Children's Medical Center Xiaowei Zhu Shanghai Children's Medical Center Jifang Qu (  13801722163@163.com ) Shanghai Children's Medical Center Qing Cao Shanghai Children's Medical Center Bo Jiang Sichuan Academy of Medical Sciences and Sichuan People's Hospital https://orcid.org/0000-00028296-3622
Profile of Bacterial Community and Antibiotic Resistance Genes in Typical Vegetable Greenhouse Soil

The use of vegetable greenhouse production systems has increased rapidly because of the increasing demand for food materials. The vegetable greenhouse production industry is confronted with serious environmental problems, due to their high agrochemical inputs and intensive utilization. Besides this, antibiotic-resistant bacteria, carrying antibiotic-resistance genes (ARGs), may enter into a vegetable greenhouse with the application of animal manure. Bacterial communities and ARGs were investigated in two typical vegetable-greenhouse-using counties with long histories of vegetable cultivation. The results showed that Proteobacteria, Firmicutes, Acidobacteria, Chloroflexi, and Gemmatimonadetes were the dominant phyla, while aadA, tetL, sul1, and sul2 were the most common ARGs in greenhouse vegetable soil. Heatmap and principal coordinate analysis (PCoA) demonstrated that the differences between two counties were more significant than those among soils with different cultivation histories in the same county, suggesting that more effects on bacterial communities and ARGs were caused by soil type and manure type than by the accumulation of cultivation years. The positive correlation between the abundance of the intI gene with specific ARGs highlights the horizontal transfer potential of these ARGs. A total of 11 phyla were identified as the potential hosts of specific ARGs. Based on redundancy analysis (RDA), Ni and pH were the most potent factors determining the bacterial communities, and Cr was the top factor affecting the relative abundance of the ARGs. These results might be helpful in drawing more attention to the risk of manure recycling in the vegetable greenhouse, and further developing a strategy for practical manure application and sustainable production of vegetable greenhouses.
Socio-Demographic Composition and Potential Occupational Exposure to SARS-CoV2 under Routine Working Conditions among Key Workers in France

This study aims to describe the socio-demographic profile of so-called “key workers” during the first lockdown in France and to assess their potential occupational exposure to SARS-CoV-2 under routine, pre-pandemic working conditions. We used the French list of essential jobs that was issued during the first lockdown to identify three subgroups of key workers (hospital healthcare, non-hospital healthcare, non-healthcare). Based on the population-based “Conditions de travail-2019” survey, we described the socio-demographic composition of key workers and their potential work-related exposures (to “infectious agents,” “face-to-face contact with the public,” and “working with colleagues”) using modified Poisson regression. In general, women, clerical and manual workers, workers on temporary contracts, those with lower education and income, and non-European immigrants were more likely to be key workers, who accounted for 22% of the active population. Non-healthcare essential workers (57%) were the most socially disadvantaged, while non-hospital healthcare workers (19%) were polarized at both extremes of the social scale; hospital healthcare workers (24%) were intermediate. Compared to non-key workers, all subgroups had greater exposure to infectious agents and more physical contact with the public. This study provides evidence of accumulated disadvantages among key workers concerning their social background, geographical origin, and potential SARS-CoV-2 exposure.
From dynamical lung ventilation data to plugs distribution in asthma – A numerical diagnosis tool

In asthma and COPD, some airways of the tracheo-bronchial tree can be constricted, from moderate narrowing up to closure. Those pathological patterns affect the lung ventilation distribution. While some imaging techniques enable visualization and quantification of constrictions in proximal generations, no non-invasive technique provides precise insights on what happens in more distal areas. In this work, we propose a process that exploits lung ventilation measures to access positions of airways closures in the tree. This identification approach combines the lung ventilation model in which a tree is strongly coupled to a parenchyma description along with a machine learning approach. Based on synthetic data generated with typical temporal and spatial resolutions as well as reconstruction errors, we obtain very encouraging results with a detection rate higher than 90%.
Economic valuation and its determinates of improved irrigation water use; evidence based on South Gondar Zone, Ethiopia

Abstract The main aim of the research was to analyze economic evaluation and determinants of willingness to pay decisions for efficient irrigation water use improvement. Use for this purpose total of 300 HHs was selected using the Multi-stage sampling technique. The collected data was analyzed using econometrics model. In the econometric part, a seemingly unrelated bivariate probit model was applied to estimate households’ mean willingness to pay and its determinant’s for efficient irrigation water use. Leads by a double bounded dichotomous choice method. From seemingly unrelated bivariate probit model regression results, the mean and aggregate willingness to pay off the households 950.7 ETB (€25.7) per month per household per hectare was 1087159.09 ETB (€29382.7) per month and (12*1087159.09 = 13045909.08 ETB per year) respectively. The Mean and aggregate willingness to pay from the open-ended questions to be 926.059 ETB (€25.03) per month per household per hectare was 1072990.52 ETB (€28,999.74) per month respectively also, The bivariate probit model result revealed that bid values, sex of the household head, irrigation farm size, extension service significantly affected households’ WTP in both initial and followed up bid values So, policymakers should be households have a high willingness to pay for improved irrigation water use systems and the government should implement irrigation water management practices to supply reliable irrigation water to the farmers and should set up proper irrigation water pricing at an amount close to the mean WTP that households were willing and able to pay.
A Depression Diagnosis Method Based on the Hybrid Neural Network and Attention Mechanism

Depression is a common but easily misdiagnosed disease when using a self-assessment scale. Electroencephalograms (EEGs) provide an important reference and objective basis for the identification and diagnosis of depression. In order to improve the accuracy of the diagnosis of depression by using mainstream algorithms, a high-performance hybrid neural network depression detection method is proposed in this paper combined with deep learning technology. Firstly, a concatenating one-dimensional convolutional neural network (1D-CNN) and gated recurrent unit (GRU) are employed to extract the local features and to determine the global features of the EEG signal. Secondly, the attention mechanism is introduced to form the hybrid neural network. The attention mechanism assigns different weights to the multi-dimensional features extracted by the network, so as to screen out more representative features, which can reduce the computational complexity of the network and save the training time of the model while ensuring high precision. Moreover, dropout is applied to accelerate network training and address the over-fitting problem. Experiments reveal that the 1D-CNN-GRU-ATTN model has more effectiveness and a better generalization ability compared with traditional algorithms. The accuracy of the proposed method in this paper reaches 99.33% in a public dataset and 97.98% in a private dataset, respectively.
High-Temporal-Resolution Forest Growth Monitoring Based on Segmented 3D Canopy Surface from UAV Aerial Photogrammetry

Traditional forest monitoring has been mainly performed with images or orthoimages from aircraft or satellites. In recent years, the availability of high-resolution 3D data has made it possible to obtain accurate information on canopy size, which has made the topic of canopy 3D growth monitoring timely. In this paper, forest growth pattern was studied based on a canopy point cloud (PC) reconstructed from UAV aerial photogrammetry at a daily interval for a year. Growth curves were acquired based on the canopy 3D area (3DA) calculated from a triangulated 3D mesh. Methods for canopy coverage area (CA), forest coverage rate, and leaf area index (LAI) were proposed and tested. Three spectral vegetation indices, excess green index (ExG), a combination of green indices (COM), and an excess red union excess green index (ExGUExR) were used for the segmentation of trees. The results showed that (1) vegetation areas extracted by ExGUExR were more complete than those extracted by the other two indices; (2) logistic fitting of 3DA and CA yielded S-shaped growth curves, all with correlation R2 > 0.92; (3) 3DA curves represented the growth pattern more accurately than CA curves. Measurement errors and applicability are discussed. In summary, the UAV aerial photogrammetry method was successfully used for daily monitoring and annual growth trend description.
Assessing the product quality of mango slices treated with osmotic and microwave drying by means of image, microstructural, and multivariate analyses

Abstract Osmotic dehydration (OD) and microwave drying (MD) have been applied to fruits to preserve their functional and quality attributes. The aim of this study was to determine the correlation between different parameters (shrinkage, color, image texture, microstructure) on the quality of three different types of cuts (oval, longitudinal, transversal) of mango slices when sequentially dried by OD, MD, and microwave oven-processing (MOP). After each processing, the samples showed different changes in geometrical parameters, shrinkage, color, image texture, and microstructure from inside the cell structure to the macroscopic level. Principal components analysis (PCA) was used to select the most suitable cut type with the least separation distance between fresh and processed samples. The most suitable cut after the processing was the longitudinal cut which was associated with higher quality mango slices. This contribution provides an insight into how the cut types affect the drying, shrinkage, color parameters, and microstructure when studying the quality of dried fruits by means of multivariate analysis.
Identification of the Mechanical Failure Factors with Potential Influencing Road Accidents in Ecuador

Road traffic accidents result in injury or even death of passengers. One potential cause of these accidents is mechanical failures due to a lack of vehicle maintenance. In the quest to identify these mechanical failures, this paper aims to set up the procedure to identify the mechanical failures that contribute to traffic accidents in cities located in developing countries, including the city of Cuenca-Ecuador. For present research, a database provided by the entity responsible for the Vehicle Technical Inspection, the Empresa Pública Municipal de Movilidad, Tránsito y Transporte and for the ones responsible of managing traffic accident data, Oficina de Investigación de Accidentes de Tránsito and Sección de Investigación de Accidentes de Tránsito was used. The vehicle subcategories M1 and M3 (bus type) and N1, so named according to Ecuadorian technical standards, were considered the most relevant regarding accident rates. The database was analysed with descriptive statistics, a Pareto chart and time series with the quadratic trend. From this analysis, the most significant failures found in the VTI in all three subcategories were the alignment of the driver headlight, both horizontal and vertical, braking imbalance on the 2nd axle, insufficient tire tread and parking brake effectiveness. All these failures showed a decreasing trend over time and in the forecast at a maximum of two to three years. The most relevant causes of road accidents recorded during the period 2009–2018 related to mechanical failures were the braking system (65.5%) and the steering system (17.2%) for subcategory M1.
Resistance Switching Memory Devices based on Zinc Oxide Nanoparticles on Paper Substrates

Júri Presidente: Doutor Rodrigo Ferrão de Paiva Martins, Professor Catedrático, Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa Arguente: Doutora Joana Maria Dória Vaz Pinto, Professora Auxiliar, Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa Vogal: Doutor Luís Miguel Nunes Pereira, Professor Auxiliar, Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa
Associations between Lifestyle Changes and Adherence to COVID-19 Restrictions in Older Adults with Hypertension

COVID-19 has changed people’s routines and imposed new ways of living. This study investigated variations in lifestyles (namely, physical activity, diet, alcohol consumption, and cigarette smoking) between the prepandemic and the pandemic period in a sample of older adults with hypertension. Moreover, it investigated predictors of adherence to government restrictions during the first lockdown period, evidencing the role of relevant sociodemographic indicators and lifestyle changes. A sample of 105 older Italian adults (M_age = 70 years; SD = 5.83) with hypertension was enrolled from a previous longitudinal study and interviewed on the phone between May and August 2020. Updated information about sociodemographic indicators and lifestyle changes was collected. Adherence to restrictions was explored through several questions regarding compliance with home confinement, facemask use, and the observance of social distancing. Results evidenced that only 33% of the respondents abided by all the national restrictions. During the first pandemic peak, considerable changes in lifestyles occurred, particularly regarding physical activity, which diminished in 70% of the sample. Women, unemployed/retired people, and individuals who decreased their amount of physical activity reported higher adherence to rules. Maintaining a healthy lifestyle over time is essential for disease prevention. Therefore, it is essential to continue to inform the population about the importance of a healthy lifestyle, and it is necessary to provide guidelines to maintain and promote it even during housebound periods.
Optimization of Relocation Processes for Shared E-vehicles

This study describes a system with one-way trips and relocations of e-vehicles between sectors by service personnel according to a dynamically compiled list of service trips. The model includes an algorithm that uses model parameter values to optionalize expected income, depending on the dynamically selected e-vehicle transfer. The implementation of the MIP (Mixed-Integer Programming) type algorithm proposed in the study pays particular attention to its performance, as optimization should be performed dynamically with a few hours' interval. The developed optimization algorithm has been validated for its practical application in Riga, Latvia.
The Psychology of Rivalry by Gavin James Kilduff A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Business Administration in the Graduate Division

1 TABLE OF CONTENTS . i ACKNOWLEDGEMENTS . ii PREFACE . 1 CHAPTER 1: Theoretical background and literature review . 3 CHAPTER 2: The effects of rivalry on motivation and performance . 9 CHAPTER 3: The effects of rivalry on unethical behavior . 22 CHAPTER 4: The effects of interorganizational rivalry on work performance and attitudes . 33 CHAPTER 5: Conclusions and future directions . 38 REFERENCES. 42 FOOTNOTES . 48 TABLES . 49 FIGURES . 53
Characterization and Functional Analysis of a New Calcium/Calmodulin-Dependent Protein Kinase (CaMK1) in the Citrus Pathogenic Fungus Penicillium italicum

Calcium (Ca2+)/calmodulin-dependent protein kinases (CaMKs) act as a class of crucial elements in Ca2+-signal transduction pathways that regulate fungal growth, sporulation, virulence, and environmental stress tolerance. However, little is known about the function of such protein kinase in phytopathogenic Penicillium species. In the present study, a new CaMK gene from the citrus pathogenic fungus P. italicum, designated PiCaMK1, was cloned and functionally characterized by gene knockout and transcriptome analysis. The open reading frame of PiCaMK1 is 1209 bp in full length, which encodes 402 amino acid residues (putative molecular weight ~45.2 KD) with the highest homologous (~96.3%) to the P. expansum CaMK. The knockout mutant ΔPiCaMK1 showed a significant reduction in vegetative growth, conidiation, and virulence (i.e., to induce blue mold decay on citrus fruit). ΔPiCaMK1 was less sensitive to NaCl- or KCl-induced salinity stress and less resistant to mannitol-induced osmotic stress, indicating the functional involvement of PiCaMK1 in such environmental stress tolerance. In contrast, the PiCaMK1-complemented strain ΔPiCaMK1COM can restore all the defective phenotypes. Transcriptome analysis revealed that knockout of PiCaMK1 down-regulated expression of the genes involved in DNA replication and repair, cell cycle, meiosis, pyrimidine and purine metabolisms, and MAPK signaling pathway. Our results suggested the critical role of PiCaMK1 in regulating multiple physical and cellular processes of citrus postharvest pathogen P. italicum, including growth, conidiation, virulence, and environmental stress tolerance.