Miracle-dz/UniFAR-FTUs huggingface dataset:
On the function of Ly-5 in the regulation of antigen-driven B cell differentiation. Comparison and contrast with Lyb-2

Generation of anti-sheep erythrocyte plaque-forming cells (PFC) is greatly reduced in the presence of monoclonal Ly-5 alloantibody. Although Ly-5 is expressed in one of its molecular forms on T cells and macrophages (M phi ) involved in this response, the only demonstrated action of Ly-5 antibody was on B cells. Evidence from elimination of Lyt-2+ cells, and from the responses of serial proportions of Ly-5.1 and Ly-5.2 cells and of Ly-5 heterozygous cells, signifies that PFC reduction cannot be ascribed to any known mechanism of suppression or to a direct suppressive action of Ly-5 antibody on B cells. A critical distinction of Ly-5 from Lyb-2 is that Ly-5 antibody reduces PFC generation to trinitrophenylated Ficoll, a thymus-independent type 2 antigen requiring T cells and M phi for maximal PFC generation in vitro. A second distinction is that PFC reduction by Ly-5 antibody is strictly tied to the time of operation of M phi factor, whereas PFC reduction by Lyb-2 antibody relates to the time of B cell triggering by antigen. Accordingly, M phi factor competitively and quantitatively inhibits the action of Ly-5 antibody in reducing PFC generation. It is likely that the Ly-5 system is concerned in the reception or handling of M phi message by B cells.
Semantic Relation Detection based on Multi-task Learning and Cross-Lingual-View Embedding

: Semantic relation extraction automatically is an important task in NLP. Various methods have been developed using either pattern-based approach or distributional approach. However, existing research only focuses on single task modeling without considering the possibility of generalization with other tasks. Besides, the methods that exist only use one view from task language as an input representation that might lack of features. This happens especially in languages that are classified as low resource language. Therefore, in this paper we proposed a framework for semantic relations classification based on multi-task architecture and cross-lingual-view embedding. There are two main stages in this framework, data augmentation based on pseudo parallel corpora and multi-task architecture with cross-lingual-view embedding. Further, extensive experiment of the proposed framework has been conducted. The results show that the use of rich resource language in cross-lingual-view embedding is able to support low-resource languages. This is shown by the results with accuracy and F1-scores of 85.8% and 87.6%, respectively. The comparison result also shows that our proposed model outperforms another state-of-the art.
Active fluorometry improves nutrient-diffusing substrata bioassay

Abstract. Benthic algal nutrient bioassays traditionally have been done by measuring periphytic algal biomass that has grown on fertilized or unfertilized patches of habitat produced by nutrient-diffusing substrata (NDS). This method requires destruction of the accumulated periphyton communities and, thus, does not allow for convenient monitoring through time. Variable fluorescence methods of estimating algal biomass and photosynthetic activity have been used in aquatic environments, but generally not over different nutrient treatments and not for a substantial duration. We evaluated the use of a pulse amplitude modulated (PAM) fluorometer for measuring algal biomass and photosynthetic activity in conjunction with NDS over several weeks in a wetland under several nutrient-addition treatments. We were able to detect a significant fluorometric response as early as 1 wk into the study with addition of both N and P. Wetland periphyton was co-limited by N and P. Dark-acclimated minimal fluorescence was highly correlated with chlorophyll a in different nutrient treatments. Our results suggest that active fluorometry is a useful method for measuring periphytic responses to nutrients and for evaluating the effect of nutrient additions on overall photosynthetic efficiency.
The dispersal of Aceria tulipae and three other grass-infesting Eriophyid mites in Ohio.

The host range, populations, and dispersal of 4 grassinfesting eriophyid species (Acarina: Eriophyidae) of Ohio were studied. High populations of wheat curl mite, Aceria tulipae (Keifer), were found on wheat in the spring and early summer and on corn in the late summer and early fall in Ohio. Quackgrass was the most important host for the grain rust mite, Abacarns hystrix Nalepa), and Aculodes mckenziei (Keifer) and timothy was the sole host for Aculodes dubius (Nalepa) (often referred to as Phytocoptes dubius). A. tulipae colonized secluded areas under leaf ligules and sheaths, under the glumes on wheat heads, and under husks on the corn ear, while the other 3 species readily colonized exposed leaf blades of their hosts. Eriophyids trapped on silicone grease-coated slides, were separated by structural characters after the mites were prepared for study by special procedures. Results of trapping showed that A. hystrix, A. mckensiei, and A. dubius dispersed continuously in spring and early summer while their hosts were growing vigorously. Few of these mites were trapped after July when there was a scarcity of green host tissue and low mite populations. Large numbers of A. tulipae were trapped in July when the wheat crop was nearly mature and again in the fall when corn ears were dry. Of the nearly 10,000 mites of several species trapped during 1968, all appeared tobe adults, suggesting that eriophyid dispersal is actively initiated by adult behavior. Wind, temperature, and light all affect eriophyid dispersal. In the field, an interaction between temperatures 18°C and wind >15 mph accounted for more than 80% of the variability in numbers of A. dubius trapped on greased slides. Both temperature and light affected the dispersal of A. tulipae under controlled environmental conditions. An increase in temperature from 12 to 24°C resulted in an 8-fold increase in the number of mites trapped. More mites were trapped during periods of light than darkness. However, the photopositive effect decreased in magnitude with an increase in temperature. The relation of eriophyid behavior to dispersal is discussed.
Examining Spatial Heterogeneity Effects of Landscape and Environment on the Residential Location Choice of the Highly Educated Population in Guangzhou, China

The residential location choice of the highly educated population is an important consideration to construct a livable city. While landscape and environment are important factors, few studies have deeply analyzed the spatial heterogeneity effects of landscape and environment on the residential location choices of a highly educated population. Taking Guangzhou as the sample, we built a livability-oriented conceptual framework of landscape and environment, and constructed datasets for highly educated population proportion, landscape, and environment factors, and other influencing factors for Guangzhou’s 1364 communities. Global regression and geographically weighted regression (GWR) models are used for analysis. The GWR model is more effective than the global regression model. We found spatial heterogeneity in the strength and direction of the relationship between the highly educated population proportion and landscape and environment. We find that landscape and environment exert spatial heterogeneity effects on the residential location choice of the highly educated population in Guangzhou. The conclusions will be of reference value to further understand how the spatial limitations of landscape and environment affect residential location choices. This study will help city managers formulate spatially differentiated environment improvement policies, thereby increasing the city’s sustainable development capabilities.
INTRODUCTION OF A PREDACIOUS RED WOOD ANT, FORMICA LUGUBRIS (HYMENOPTERA: FORMICIDAE), FROM ITALY TO EASTERN CANADA

Abstract A brief history of the importance attributed to red wood ants in Europe and the outstanding qualities of three species, Formica lugubris Zett. , F. polyctena (Foerst.), and F. aquilonia Yarr. , are presented. The reasons for choosing F. lugubris as a suitable species for introduction to Canada are given. The collecting in Italy, shipping by air to Canada, and eventual release in Quebec is discussed. In conclusion it is stated that the establishment and acclimatization of this species in Quebec was successful, and that increased reproduction and spread is anticipated. Résumé On présente un bref rappel historique de l’importance des fourmis des bois d’Europe et les qualités remarquables de trois espèces particulières, Formica lugubris Zett. , F. polyctena (Foerst,) et F. aquilonia Yarr. On explique le choix de F. lugubris pour son introduction au Canada. Sa récolte en Italie, son transport aérien jusqu’au Canada et son relâchement au Québec sont décrits. En conclusion, on affirme le succès de l’établissement et de l’acclimatation de cette espèce au Québec, de même qu’on anticipe une reproduction et une dispersion accrue.
LSA & LDA topic modeling classification: comparison study on e-books

With the rapid growth of information technology, the amount of unstructured text data in digital libraries is rapidly increased and has become a big challenge in analyzing, organizing and how to classify text automatically in E-research repository to get the benefit from them is the cornerstone. The manual categorization of text documents requires a lot of financial, human resources for management. In order to get so, topic modeling are used to classify documents. This paper addresses a comparison study on scientific unstructured text document classification (e-books) based on the full text where applying the most popular topic modeling approach (LDA, LSA) to cluster the words into a set of topics as important keywords for classification. Our dataset consists of (300) books contain about 23 million words based on full text. In the used topic models (LSA, LDA) each word in the corpus of vocabulary is connected with one or more topics with a probability, as estimated by the model. Many (LDA, LSA) models were built with different values of coherence and pick the one that produces the highest coherence value. The result of this paper showed that LDA has better results than LSA and the best results obtained from the LDA method was ( 0.592179 ) of coherence value when the number of topics was 20 while the LSA coherence value was (0.5773026) when the number of topics was 10.
FPGA-Based System for Electromagnetic Interference Evaluation in Random Modulated DC/DC Converters

Field-Programmable Gate Array (FPGA) provides the possibility to design new “electromagnetic compatibility (EMC) friendly” control techniques for power electronic converters. Such control techniques use pseudo-random modulators (RanM) to control the converter switches. However, some issues connected with the FPGA-based design of RanM, such as matching the range of fixed-point numbers, might be challenging. The modern programming tools, such as LabVIEW, may facilitate the design process, but there are still fixed-point operations and limitations in arithmetic operations. This paper presents the design insights on the FPGA-based EMC friendly control system for DC/DC converter. Probability density functions (PDF) are used to analyse and improve pseudo-random algorithms. The theoretical algorithms, hardware details and experimental results are presented and discussed in terms of conducted electromagnetic interference emission.
Cosine K-Nearest Neighbor in Milkfish Eye Classification

: K-Nearest Neighbors (K-NN) classification method gains refined version proposed by the researcher. The refinement aims to solve noise sensitive when using small K, and irrelevant class as classification result when using large K. The problem in the previous version of method was that the weights were calculated individually, so the result was not optimal. We propose recent weighting scheme where the weights were no longer gained from the nearest neighbor individually, but by involving all pair of the nearest neighbor, called Cosine K-NN (CosKNN). We also introduce a trigonometric map to describe the Cosine weight. CosKNN is soft value to represent ownership of each class to the testing data. Empirically, CosKNN is tested and compared with other K-NN refinement using milkfish eye, UCI, and KEEL dataset. The result shows that CosKNN hold superior performance compared to the other methods although K number is higher of which accuracy is 96.79%.
A NOVEL RISK EVALUATION APPROACH FOR FREQUENTLY ENCOUNTERED RISKS IN SHIP ENGINE ROOMS

The purpose of this study is to evaluate risks which are frequently encountered in the engine room on-board. In this context, twenty common risks are assessed using the neutrosophic analytic hierarchy process (N-AHP) and trapezoidal fuzzy technique for order preference by similarity to ideal solution (TrF-TOPSIS). In maritime risk evaluation, since it is frequently required the linguistic assessment of decision-makers to achieve a robust risk assessment tool, neutrosophic sets and fuzzy sets are used together in this study. Neutrosophic sets represent real-world problems effectively by considering all aspects of decision-making situations, (i.e. truthiness, indeterminacy, and falsity). Therefore, AHP is integrated with neutrosophic sets to assign weights of risk parameters initially. Then, the encountered risks are prioritized by TrF-TOPSIS. Finally, preventative actions for the risks have been discussed. In conclusion of the study, it is shown that skin exposure to the fuels/oils, exposure to chemicals and exposure to high pressure and temperature liquids are the most important risks through the engine room on-board. This study both emphasizes the importance of preventing damage to crew in the risk assessment of ship engine rooms and aims to increase the level of safety control and minimize the potential environmental impacts of a ship's damage.
The surface ciliation of anuran amphibian embryos and early larvae: Patterns, timing differences and functions

Embryonic and early larval surface ciliation patterns are described stage by stage, using scanning electron microscopy and live specimen observations, in 20 species of anuran amphibians from six families including the first detailed description of surface ciliation in a direct‐developing eleutherodactylid: four species are from temperate regions and 16 are tropical. The study asks whether differences in pattern relate to ciliation functions, or show any phylogenetic features, or demonstrate heterochrony. It also asks whether the timing of ciliated cell regression is fixed or can vary with the environment. Respiration appears to be the main function of surface ciliation, both pre‐ and post‐hatching, regressing when internal gills become functional. Substratum gliding after hatching may also be a valuable role. Late stage persistence of ciliation around the external nares suggests a sensory function. Localized early regression of ciliated cells is linked to lateral line development. Dramatic changes in ciliated cell shape are described, though functions are unclear. Ciliation patterns, density and duration vary considerably between species, with no obvious phylogenetic or environmental correlates, nor is there a clear relationship with egg size or hatching stage. Ciliation patterns also vary with body region, with density and duration consistently highest round the nostrils and adhesive glands (when present) compared to other body regions.
Fabric Defect Detection Using the Sensitive Plant Segmentation Algorithm

Fabric quality control and defect detection are playing a crucial role in the textile industry with the development of high customer demand in the fashion market. This work presents fabric defect detection using a sensitive plant segmentation algorithm (SPSA) which, is developed with the sensitive behaviour of the sensitive plant biologically named “mimosa pudica”. This method consists of two stages: The first stage enhances the contrast of the defective fabric image and the second stage segments the fabric defects with the aid of the SPSA. The SPSA proposed was developed for defective pixel identification in non-uniform patterns of fabrics. In this paper, the SPSA was built through checking with devised conditions, correlation and error probability. Every pixel was checked with the algorithm developed to be marked either a defective or non-defective pixel. The SPSA proposed was tested on different types of fabric defect databases, showing a much improved performance over existing methods.
Elatostema scaposum sp. nov. (Urticaceae) from Guizhou, China

Elatostema scaposum Q. Lin & L. D. Duan (Urticaceae: Elatostema sect. Pellionioides W. T. Wang), a new species from Libo County, Guizhou Province, China, is described and illustrated. This species was found growing at the base of a large limestone chamber at an altitude of ca 800 m a.s. l. , and differs from all other species in Elatostema sect. Pellionioides W. T. Wang by scapiform male inflorescences (axillary in other species of Elatostema sect. Pellionioides).
Using Satellite Imagery to Evaluate Bark Beetle-Caused Tree Mortality Reported in Aerial Surveys in a Mixed Conifer Forest in Northern Idaho, USA

Bark beetles cause significant tree mortality in western North America. The United States Forest Service coordinates annual insect and disease surveys (IDS) by observers in airplanes to map and quantify the tree mortality caused by beetles. The subjective nature of these surveys means that accuracy evaluation is important for characterizing uncertainty. Furthermore, the metric reported for quantifying tree mortality recently changed (2012–2018 depending in region) from killed trees per acre to percent tree mortality within damage polygons, posing challenges for linking older and newer records. Here we evaluated IDS severity estimates in a beetle-affected forest in northern Idaho, USA using fine-resolution satellite imagery, which permitted greater areal coverage than field data. We first used well-established methods to map beetle-caused tree mortality in two WorldView-2 (WV2) images with a high accuracy relative to field observations. Trees-per-acre measurements within collocated IDS polygons were then converted to percent mortality using three methods and evaluated with the WV2 maps. The overall accuracies for the three methods ranged from 35–38% (for methods that used five percent-mortality classes) and 49–56% (three classes). When IDS and WV2 estimates of mortality severity that were within ±15% of each other were considered accurate, overall accuracies were 71–78%. Within the aerial survey damage polygons, the total mortality area tended to be overestimated relative to WV2. WV2 imagery identified ~50% more mortality across the study region compared with the IDS methods, with most of the difference occurring where damage was low severity or in wilderness areas. Severity of Douglas-fir beetle-caused tree mortality was estimated the most accurately, whereas severity of mountain pine beetle-caused tree mortality was estimated the least accurately. Future studies that control for temporal ambiguity between IDS and satellite imagery, as well as IDS spatial error, might provide better assessments of IDS severity accuracy. Our study increases the usefulness of the rich aerial survey database by providing estimates of uncertainty in the IDS database of tree mortality severity.
pLoc_Deep-mGneg: Predict Subcellular Localization of Gram Negative Bacterial Proteins by Deep Learning

The recent worldwide spreading of pneumonia-causing virus, such as Coronavirus, COVID-19, and H1N1, has been endangering the life of human beings all around the world. In order to really understand the biological process within a cell level and provide useful clues to develop antiviral drugs, information of Gram negative bacterial protein subcellular localization is vitally important. In view of this, a CNN based protein subcellular localization predictor called “pLoc_Deep-mGnet” was developed. The predictor is particularly useful in dealing with the multi-sites systems in which some proteins may simultaneously occur in two or more different organelles that are the current focus of pharmaceutical industry. The global absolute true rate achieved by the new predictor is over 98% and its local accuracy is around 94% - 100%. Both are transcending other existing state-of-the-art predictors significantly. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_Deep-mGneg/, which will become a very useful tool for fighting pandemic coronavirus and save the mankind of this planet.
Variation in Sugar Content in Fruit of Four Strawberry Cultivars Grown in the Field and under Forced Culture, Harvest Years, and Maturation Stages

The soluble sugar content and composition in four strawberry cultivars grown in the open field and under forcing culture and sampled at various maturation stages in different harvest seasons were compared. 1. Sucrose, fructose, and glucose are the major sugars, and inositol and sorbitol are the minor ones in the sugar compostion of strawberry fruit. Content and compostiion of souluble sugars differed among cultivars, fructose and glucose being higher in 'Toyonoka' and 'Hokowase' than in 'Nyoho' and 'Reiko' fruits. 2. The percentage of fructose or glucose to total sugar content was large in 'Toyonoka' and 'Hokowase' as compared to 'Reiko' and 'Nyoho' during the early maturation stages ; the percentage decreased in 'Reiko' and 'Nyoho', while it increased in 'Toyonoka' and 'Hokowase' as the fruits ripened. 3. In 'Reiko' and 'Toyonoka', the variation of total sugar content in the fruits grown by open culture was larger than that of fruits grown under forcing culture. 'Toyonoka' fruit had large amounts of sugars with small variations during the harvest as compared to 'Reiko'. 4. The amount of sugars in strawberry fruit varied among cultivars, harvest years, cropping types and developmental stages of fruit, but the ratio of each sugars to total sugar content was nearly constant. The sugar composition of each cultivars seems to be a heritable characteristic, unaffected by the environment.
Integrated soil management in eroded land augments the crop yield and water-use efficiency

Abstract Cultivated lands in erosion prone agro-ecologies incessantly experience a substantial loss of productive soil and organic matter. Currently, the fertility-management and rainwater-conservation practices are given emphasis separately. This study appraised collectively both the water-conservation and fertility-management practices for the restoration of soil productivity in eroded farmlands. Field experiments were carried out on wheat (Triticum aestivum L.) and maize (Zea mays L.) in eight farmer fields. Four fields of Missa soil series (Typic Ustochrept) and four of Rajar soil series (Typic Ustorthent) were selected. Treatments in each field were: farmers' practice as control without soil-water conservation, and with farmers' rate of fertilizer (per hectare 40 kg N + 30 kg P2O5); improved fertilization (per hectare 100 kg N, 60 kg P2O5, 2 kg Zn, and 1 kg B) without soil-water-conservation practices; soil-water-conservation practices (deep plowing, bund improvement, ploughing across the contour) + farmers' rate of fertilizers; and soil-water conservation + improved fertilization. Crop grain yields were at the highest with soil-water conservation + improved fertilization (per hectare wheat 3.31 Mg and 1.65 Mg in 2004–2005 and 2005–2006; and maize 4.55 Mg and 4.19 Mg in 2005 and 2006, respectively). The lowest yields were recorded under farmers' practice for both crops. Similar was the response for water-use efficiency and plant uptake of nitrogen, phosphorus, zinc, and boron. Missa soil series was more responsive than was Rajar to integrated soil-management practices. Synergistic application of soil-water conservation and improved fertilization practices significantly improved the crop yields, nutrient uptake, and water-use efficiency.