Miracle-dz/UniFAR-FTUs huggingface dataset:
Amyloid β‐Peptide Effects on Synaptosomes from Apolipoprotein E‐Deficient Mice

Abstract: Apolipoprotein E (apoE) is present in the brain and may contribute to neurophysiologic or neuropathologic events, depending on environmental and genetic influences. Recent studies indicate a role for apoE in synaptic plasticity and maintenance of synaptic membrane symmetry, suggesting that apoE may be involved in regulating synaptic homeostasis. In the present study, cerebrocortical synaptosomes were prepared from transgenic mice lacking apoE (apoE KO) to analyze the possible contribution of apoE toward maintaining homeostasis in synaptosomes. Synaptosomal preparations from apoE KO and wild‐type mice exhibited similar basal levels of reactive oxygen species, mitochondrial function, and caspase activity; however, following application of amyloid β‐peptide [Aβ(1‐40)], apoE KO synaptosomes displayed increased levels of oxidative stress, mitochondrial dysfunction, and caspase activation compared with synaptosomes from wild‐type mice. Synaptosomal membranes from apoE KO mice were more fluid than wild‐type synaptosomes and contained higher levels of thiobarbituric acid‐reactive substances, consistent with elevated levels of lipid peroxidation occurring in the synapses of apoE KO mice. Together, these data are consistent with a role for apoE in maintaining homeostasis by attenuating oxidative stress, caspase activation, and mitochondrial homeostasis in synapses.
Natural isolates of Bacillus thuringiensis: worldwide distribution, characterization, and activity against insect pests

Abstract Bacillus thuringiensiswas isolated from natural samples collected from 80 countries. The majority, 45% of the 5303 isolates, originated from stored products, with 25% originating from soil. The materials richest in isolates active in insects were mushroom compost and stored products. The proportion with bipyramidal-shaped crystals was 46%, while among the range of other shapes 14% were spherical and 4% rectangular. The largest proportion of isolates, 45%, was found in the United Kingdom with the majority originating from stored mills, which import produce from all over the world; 22% came from North America. Using single-dose assays, 44% of the isolates killed less than 25% of larvae of all four Lepidoptera tested,Heliothis virescens, Pieris brassicae, Spodoptera littoralis,andAgrotis ypsilon.Among isolates killing more than 25% of the larvae, every combination of activities of the 16 possible against these 4 insects was found, in proportions ranging from 0.6 to 14.5%, suggesting considerable diversity of insect activity. The 44% of strains with little or no activity to Lepidoptera (
Quantitative trait loci conditioning resistance to Fusarium head blight in wheat line F201R

Fusarium head blight (FHB) of wheat (Triticum aestivum L.) is a devastating disease in wheat production worldwide. Identifying resistance genes and understanding the genetic basis of resistance to FHB are prerequisites to developing cultivars that can avoid losses from FHB. This investigation of quantitative trait loci (QTL) was performed in a recombinant inbred (RI) population derived from a cross between the FHB-moderately susceptible cv. Patterson and the FHB-resistant line Fundulea 201R (F201R). Bulk DNAs from the 11 most resistant and 12 most susceptible lines of the phenotypic distribution of the RI population, together with the parental lines, were screened with simple sequence repeat (SSR) markers. Regional QTL mapping identified four interval regions, located on chromosomes 1B, 3A, 3D, and 5A, that conferred resistance to FHB. The QTLs located on chromosomes 1B and 3A, contributed by F201R, had large effects and were consistently expressed in three environments. The four QTLs together accounted for 32.7% of the phenotypic variation, or 43.0% of the genotypic variation. The QTL on chromosome 3A is located in the same region as a QTL that was detected in wild tetraploid wheat T. dicoccoides (Koern. ex Asch. & Graebner) Aarons. The possibility that the FHB resistance QTLs of F201R and that of T. dicoccoides on chromosome 3A have the same origin is discussed.
Iterating Tensor Voting: A Perceptual Grouping Approach for Crack Detection on EL Images

The surface of a multicrystal solar cell shows multiple crystal grains of random shapes and sizes. It creates an inhomogeneous texture in the surface, which brings great difficulty to automatic crack detection of polycrystalline solar surface. As a perceptual grouping approach, tensor voting can extract curvilinear structures such as lines and curves from noisy, binary data in 2-D or 3-D, without invoking specific object or model. However, traditional tensor voting can be susceptible to the gap problem and structural noise. To address the problems mentioned above, a new iterative tensor voting algorithm is presented, which efficacy bases on iterative refinements of the curvilinear structures. By combining the proximity and continuity of Gestalt principles, in each iteration step, a new decay function is redefined according to the difference of angle between the voter and receiver to rebuild the voting field, which makes the points that lie on curvilinear structures vote more information (a bigger tensor) to the ones with the same attribute. The proposed method can solve the gap problem and is robust to structural noises. The experimental results show that the proposed method can detect crack on the inhomogeneous textured surface and achieve an average detection rate of 95.2% on the industrial data set. Note to Practitioners—Automatic vision-based defect detection on the solar cell is difficult due to inhomogeneous texture and low contrast between defects and background in the surface. In order to solve these problems, by combining the proximity and continuity of Gestalt principles, this article proposed a new iterative tensor voting algorithm which can refine the curvilinear structures with iterations. Experiments have shown that the proposed method can detect crack under the interference of inhomogeneous texture and complex background.
Preliminary Evaluation of Somaclonal Variation for the In Vitro Production of New Toxic Proteins from Viscum album L.

SUMMARY In an attempt at preliminary evaluation of the effect of somaclonal variation on the production of white berry mistletoe (Viscum album L.) proteins, one hundred individual callus tissues were assayed for their protein content by means of SDS-PAGE. Somaclonal variation in the qualitative aspect was relatively low (8%). However, variation in quantitative terms was high and in 10% of the calli a protein concentration six times higher than in stems was observed. These results indicate for the first time the possibility of applying tissue culture for the production of mistletoe protein extracts with increased antitumor/immuno-modulatory properties.
A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment

Aligning senses across resources and languages is a challenging task with beneficial applications in the field of natural language processing and electronic lexicography. In this paper, we describe our efforts in manually aligning monolingual dictionaries. The alignment is carried out at sense-level for various resources in 15 languages. Moreover, senses are annotated with possible semantic relationships such as broadness, narrowness, relatedness, and equivalence. In comparison to previous datasets for this task, this dataset covers a wide range of languages and resources and focuses on the more challenging task of linking general-purpose language. We believe that our data will pave the way for further advances in alignment and evaluation of word senses by creating new solutions, particularly those notoriously requiring data such as neural networks. Our resources are publicly available at https://github.com/elexis-eu/MWSA.
Knowledge, awareness and recommendations of cancer among the healthcare professionals in Najran region, Saudi Arabia: A cross-sectional study.

Cancer is a group of diseases considered by uncontrollable growth and spread of abnormal cells. There were an estimated 18.1 million new cases of cancer worldwide in 2018. An inadequate awareness of cancer disease among healthcare professionals (HCPs) may put patient lives at risk. This study aimed to evaluate the knowledge, awareness and beliefs of HCPs towards cancer at Najran Hospitals in Southwest Saudi. A cross- sectional survey among 156 randomly selected HCPs working at Najran hospitals from September-November, 2019. A validated online questionnaire was used to collect the data and descriptive statistics was calculated with p<0.05 being statistically significant. Of the 156 participants 54 (35%) completed the study. More than half of respondents (59%) were male, pharmacists and have 11-15 years of experience. The majority had awareness about cancer disease (78%) and more than 500 cancer cases were reported in Najran in the last five years. Results also showed that breast cancer were the most popular cancer type (42%) followed by liver (22%) and leukemia (17%) among cancer cases in Najran region. The most common barrier for cancer treatment in Najran was lack of resources, staff and equipment. The study also revealed that smoking and changing lifestyle are the most popular cancer risk factors. 78% of respondents strongly agreed that early detection of cancer may greatly increases the chances for successful treatment. The results support that the vast majority of respondents recommended that early detection through regular screening should be mandatory implemented.
Relationship Between Social Support and Psychological Resilience of Patients with Convalescent Stroke: Mediating Effect of Self-Efficacy

Objectives: To explore the relationship among psychological resilience, social support and self-efficacy of patients with convalescent stroke. Methods: From May 1 to December 31 in 2019, a total of 288 patients with convalescent stroke were investigated with the Social Support Rating Scale(SSRS), Stroke self-efficacy questionnaire (SSEQ), Connor-Davidson resilience scale (CD-RISC) and the general information questionnaire. Correlation analysis and mediating effect analysis were done. Results: The scores of social support, self-efficacy, psychological resilience are (34.25±5.95), (60.28±13.11) and (61.90±13.84), respectively. Psychological resilience is shown to be significantly correlated with social support (r=0.778, P<0.01) and self-efficacy (r=0.750, P<0.01). Self-efficacy had an incomplete mediating effect between social support and psychological resilience, and the mediation ratio was 53.30%. Conclusions: There is a positive correlation between social support, self-efficacy and psychological resilience in patients with convalescent stroke. Self-efficacy plays a part of mediating role between social support and psychological resilience.
The virus and socioeconomic inequality: An agent-based model to simulate and assess the impact of interventions to reduce the spread of COVID-19 in Rio de Janeiro, Brazil

The emergence of COVID-19 in China, in December of 2019 led to a local epidemic that rapidly spread to multiple countries in the world, including Brazil. Nowadays, there is an accelerated search to understand the dynamics of the spread of the disease and evaluate the effectiveness of intervention measures. Given these special socioeconomic conditions surrounding Brazil, using the predictive models developed for other countries can make a very incomplete picture of the epidemic, since these differences could result in different patterns in low income settings. The aim of this work is to simulate interventions and understand the impact to reduce the spread of COVID-19 considering the socioeconomic conditions of Brazil. With this purpose we use an agentbased model (ABM), a subarea of the Artificial Intelligence, as it allows us to treat each individual in a personalized manner, as well as the environment of which they are part. The simulations have heterogeneous populations, considering different age groups, socioeconomic differences and number of members per family, contacts and movements intra and inter the sub-populations (favelas and non-favelas), numbers of Intensive Care Unit (ICU) and study different scenarios to show how the interventions can influence the spread of the virus in the population of simulated environments.
SEATING COMFORT SATISFACTION LEVEL OF OFFICE WORKERS AND THEIR EXPECTATIONS FROM AN OFFICE CHAIR

Oturma konforu; bireyin sandalyesinin ozellikleri, kullanicinin ozellikleri ve sandalyede oturularak gecirilen zamanla iliskilidir. Ofiste calisma saatlerinin artmasi, yanlis isyeri ve is ekipmani tasarimi; cesitli kas-iskelet sistemi rahatsizliklarina yol acmaktadir. Bu calismanin amaci; katilimcilarin bir ofis sandalyesinden beklentilerini belirlemek, ofis sandalyeleri ile ilgili rahatsizliklarini arastirmak ve ofis sandalyesinden genel memnuniyeti etkileyen onemli is ve kullanici ozelliklerini tespit etmektir. Bu calisma, yapisal tasarim ve tekstil tasarimi konusundaki rahatsizlik ve beklentileri goz onunde bulundurarak bir ofis sandalyesi tasarlamayi amaclayan, devam etmekte olan bir projenin parcasidir. Anket sonuclarina gore, katilimcilarin beklentilerini karsilamasi beklenen bir ofis sandalyesi tasarlanacaktir. Rastgele secilmis 382 katilimciya, kendi mevcut ofis sandalyelerinden genel memnuniyetlerini, sandalyelerinin sahip oldugu ozellikleri, sandalyeleri uzerinde kullanilan tekstil malzemelerini ve bir ofis sandalyesinden beklentilerini belirlemek icin bir anket uygulanmistir. Kadinlarin %74,89'unun ve erkeklerin %58,05'inin ofis sandalyelerinden memnun olmadigi tespit edilmistir. Sandalyelerinden memnun olmayan personelin %68,75'i, rahatsizliklarinin ofis sandalyelerinden kaynaklandigini dusunmekteydi. Ayrica, ofis sandalyesinde kullanilan tekstil malzemelerinin sandalyenin rahatligini etkiledigi ve sandalyelere kaplanan tekstil malzemelerinden bazi beklentilerin oldugu tespit edilmistir.
Dynamic MPPT Controller Using Cascade Neural Network for a Wind Power Conversion System with Energy Management

ABSTRACT This paper proposes a dynamic maximum power point tracking (MPPT) controller for a permanent magnet synchronous generator (PMSG)-based variable speed autonomous wind power conversion system (WPCS) with an energy storage system (ESS). The dynamic controller extracts the maximum power from the WPCS under variable speed conditions using a cascade neural network (CNN)-based MPPT algorithm. Also, the efficient power management between an ESS, load and WPCS is obtained using a conventional PI controller. The CNN is trained and tested using simulation and experimental data, respectively. The performance of CNN-based MPPT is also compared with feed-forward-based MPPT in terms of accuracy and complexity. This paper also discusses FPGA implementation aspects of CNN-based MPPT and hardware resources management for desired accuracy. The proposed method is first implemented on a simulation model 900-watt PMSG-based WECS and results are validated. Further, the enthusiastic results were finally evaluated in a hardware setup of 1 HP PMSG-based WECS. The proposed method is shown to extract maximum power with a simple structure and provide a better response to variable wind speed.
A multi-spectral fluorescence induction and relaxation (FIRe) technique for physiological and taxonomic analysis of phytoplankton communities

Phytoplankton are extraordinarily di verse, comprising 13 phylogenetic groups, with dia toms, dinoflagellates, and haptophytes among the most prominent eukaryotes in the ocean. Development of sensor technologies for rapid taxonomic and physiological analysis of phytoplankton communities is crucial for ecological monitoring programs in the global ocean. We describe a novel, ultra-sensitive, multi-spectral fluorescence induction and relaxation instrument (a mini-FIRe) and examine its analytical capability of rapidly determining phytoplankton taxonomic groups, as well as physiological characteristics and photosynthetic rates. We collected and analyzed the database of spectral and photosynthetic properties of major taxonomic groups of phytoplankton. We revealed that the spectral shape of the functional absorption cross-section of Photosystem II (PSII), σPSII(λex), is remarkably constrained within each ma jor phylogenetic group of eukaryotic phytoplankton, including diatoms, haptophytes, dinoflagellates, and chlorophytes. Variability in σPSII(λex) within each group was significantly smaller than the difference between groups. We also examined the classical ex citation spectra of chl a fluorescence yields, Fm(λex). Our comparative analysis revealed that σPSII(λex) is a better and more specific proxy for taxonomic analysis. For instance, our developed σPSII-based algorithm correctly identified 90% of experimental data, compared to 77% identified by the Fm-based algorithm. Our results suggest that the multi-color variable fluorescence analysis offers a tool for combined physiological and taxonomic analysis, including identification of major phyla within the ‘red’ lineage of eukaryotic phytoplankton. OPEN ACCESS Phytoplankton cells emit red fluorescence from chlorophyll with the fluorescence quantum yield reflecting physiological status and the spectral properties (graph of σPSII, r.u. against wavelength, nm) reflecting taxonomic identity.
AUV-Aided Localization for Internet of Underwater Things: A Reinforcement-Learning-Based Method

Localization is a critical issue for many location-based applications in the Internet of Underwater Things (IoUT). Nevertheless, the asynchronous time clock, stratification effect, and mobility properties of the underwater environment make it much more challenging to solve the localization issue. This article is concerned with an autonomous underwater vehicle (AUV)-aided localization issue for IoUT. We first provide a hybrid network architecture that includes surface buoys, AUVs, and active and passive sensor nodes. On the basis of this architecture, an asynchronous localization protocol is designed, through which the localization problem is provided to minimize the sum of all measurement errors. In order to make this problem tractable, a reinforcement-learning (RL)-based localization algorithm is developed to estimate the locations of AUVs, and active and passive sensor nodes, where an online value iteration procedure is performed to seek the optimization locations. It is worth mentioning that the proposed localization algorithm adopts two neural networks to approximate the increment policy and value function, and more importantly, it is much preferable for the nonsmooth and nonconvex underwater localization problem due to its insensitivity to the local optimal. Performance analyses for the RL-based localization algorithm are also provided. Finally, simulation and experimental results reveal that the localization performance in this article can be significantly improved as compared with the other works.
The Role of Credit Obtained from Input Suppliers in Farm Investment in Afghanistan

Access to improved technologies largely depends on the availability of credit. Access to formal credit is shallow in Afghanistan, and the farmers mostly rely on the informal credit. Input supplier credit is one of the informal sources of credit available to the farmers. Using qualitative data from the interviews of 23 farmers and 10 input suppliers from three cities of Afghanistan, this study aims to analyze the role of the credit obtained from input suppliers in farm investment, the reasons for obtaining and giving credit, and the problems faced. The study also analyzes the advantages the input suppliers have over financial institutions. The credit was provided in-kind, which is acceptable to the farmers as it complies with Islamic doctrines of finance. The credit reduced the risk of underinvesting in production. However, it did not help in acquiring capital goods and long-term investment. The credit was mainly based on good rapport. The short repayment period and the lack of transparency were the challenges faced by the farmers. Input suppliers gave credit mainly to expand their businesses. Default and currency risk were the main problems they faced. In lending to farmers, input suppliers had advantages over financial institutions in acquiring information, controlling borrowers, and in the social acceptance of the credit they disbursed. The study also suggests suitable policies to increase access to formal credit for farm investment in Afghanistan.
Water use characteristics and impact factors in the Yellow River basin, China

ABSTRACT This study focuses on the water use characteristics and impact factors in the Yellow River basin. Water use increased from 1980 to 2000 and then stabilized. Water use in the eight regions of the basin varies significantly in both time and space. Water use in different sectors is sensitive to variations in the irrigation area, industrial added value, efficiency, population and urbanization. Change trends are the results of the joint effects of supply-and-demand relationship and water policy. Water use is insensitive to precipitation, because irrigation mainly relies on river water and groundwater.
The influence of nocturnal CO2 advection on CO2 flux measurements

Abstract Eddy covariance (EC) measurements of CO2 are widely used to assess the CO2 budget of ecosystems. However, important uncertainties exist about how to obtain flux values that are representative for the regional scale from local-scale EC measurements. This paper addresses the issues of nocturnal CO2 advection in non-flat topography, and the representativeness of the local clover-rich grass surface for the larger region, at the end of the growing season. Local EC measurements were compared with the fluxes obtained from a boundary-layer budget method (BLB) which employed tethered balloon measured vertical profiles of CO2 concentration in the lowest few hundred meters of the atmosphere. It was found that the diurnal change in CO2 concentration was restricted to the lowest ≈450 m of the atmosphere.
Optimal Sizing of Battery Energy Storage for Grid-Connected and Isolated Wind-Penetrated Microgrid

Renewable energy (RE) sources, particularly wind and solar are gaining more popularity due to their inherent benefits, consequently, nations have set ambitious goals to enhance the penetration of RE into their energy-mix. However, the RE sources especially wind and photovoltaic sources are intermittent, uncertain, and unpredictable. Therefore, there is a need to optimize their usage when they are available. Moreover, energy storage system like battery energy storage has much potential to support the RE integration with the power grid. This study, therefore, investigates the sizes of battery energy storage required to support a grid-connected microgrid and a stand-alone microgrid for 12 months considering hourly wind power potential. In this study, we have considered three Scenarios of operations and have determined the BESS sizes and recommend the best based on the cost of operation. Scenarios 1 and 2 are grid-connected configuration while Scenario 3 is a standalone microgrid supported with diesel generators. In each Scenario, the optimization problem is formulated based on the optimal operation cost of the microgrids. The powers consumed from the main grid are reported in Scenarios 1 & 2 and the extra cost spent on the maintenance of diesel generators is reported in Scenario 3. The study evaluates and analyzes the operational environmental effects and costs between the three Scenarios. The formulated problems are solved using the nonlinear optimization method. Simulations results proved the effectiveness of the study.