Miracle-dz/UniFAR-FTUs huggingface dataset:
The Type III Effectome of the Symbiotic Bradyrhizobium vignae Strain ORS3257

Many Bradyrhizobium strains are able to establish a Nod factor-independent symbiosis with the leguminous plant Aeschynomene indica by the use of a type III secretion system (T3SS). Recently, an important advance in the understanding of the molecular factors supporting this symbiosis has been achieved by the in silico identification and functional characterization of 27 putative T3SS effectors (T3Es) of Bradyrhizobium vignae ORS3257. In the present study, we experimentally extend this catalog of T3Es by using a multi-omics approach. Transcriptome analysis under non-inducing and inducing conditions in the ORS3257 wild-type strain and the ttsI mutant revealed that the expression of 18 out of the 27 putative effectors previously identified, is under the control of TtsI, the global transcriptional regulator of T3SS and T3Es. Quantitative shotgun proteome analysis of culture supernatant in the wild type and T3SS mutant strains confirmed that 15 of the previously determined candidate T3Es are secreted by the T3SS. Moreover, the combined approaches identified nine additional putative T3Es and one of them was experimentally validated as a novel effector. Our study underscores the power of combined proteome and transcriptome analyses to complement in silico predictions and produce nearly complete effector catalogs. The establishment of the ORS3257 effectome will form the basis for a full appraisal of the symbiotic properties of this strain during its interaction with various host legumes via different processes.
The Association between Parathyroid Hormone (PTH) Level and Hemoglobin and Hematocrit Level in Chronic Kidney Disease (CKD) Patients with Regular Hemodialysis

Introduction: Chronic Kidney Disease (CKD) is a pathophysiological process with various etiology that causes a progressive decline in kidney function and ends in kidney failure. [1] CKD is a health problem that occurs in the community and has covered globally. The 2010 Global Burden of Disease stated that CKD was the 27th leading cause of death in the world in 1990. This has increased to 18th in 2010. Parathyroid hormone is a potential factor in the incidence of anemia in CKD patients. In CKD patients, there is an increase in levels of parathyroid hormone which is a uremic toxin that inhibits erythropoietin by increasing fibrosis in the bone marrow (myelofibrosis). The role of PTH in cases of renal anemia has been extensively investigated by various clinical observational studies. This study aimed to determine the association between parathyroid hormone (PTH) levels and hemoglobin and hematocrit levels in chronic kidney disease (CKD) patients with regular hemodialysis in Haji Adam Malik Central General Hospital. Methods: This is an analytical study with a cross-sectional design. A total of 45 study subjects met the inclusion criteria and exclusion criteria, underwent history taking, physical examination, anthropometry, and laboratory examination to measure parathyroid hormone, hemoglobin, hematocrit, and albumin levels. Data analysis was performed using SPSS. Results: The measured PTH level had a minimum value of 113 pg/ml and a maximum of 595 pg/ml with an average of 431.4. The minimum hemoglobin value is 6.3 g/dl and a maximum of 11.5 g/dl with an average of 7.9, while for the hematocrit the minimum value is 19% and the maximum is 35% and the average is 24.7. The Mann-Whitney U test showed that there is a significant relationship between PTH levels and hemoglobin, indicated by a significant p value of 0.001 (p value < 0.05). A significant relationship was also found between PTH levels and hematocrit (p value = 0.039). Conclusion: Parathyroid hormone has a statistically significant relationship with haemoglobin and haematocrit levels in CKD patients with regular hemodialysis. Keywords: Chronic kidney disease; haemoglobin; haematocrit; parathyroid hormone; anemia; hemodialysis.
Dynamic Identification of Industrial Robot Based on Nonlinear Friction Model and LS-SOS Algorithm

This article is concerned with the identification of industrial robot dynamics parameters, and an identification method based on a nonlinear friction model and a least squares (LS) with symbiotic organisms search (SOS) algorithm is proposed. First, according to the friction characteristics of robot joints, for the nonlinear Tustin friction model, two parameters are introduced to describe the Stribeck characteristics of Coulomb friction and static friction. Then, the joint velocity trajectory that can offset the nonfriction torque during the forward and reverse rotation is designed, and friction parameters are estimated by using LS. Based on the optimal criterion constructed by Hadamard’s inequality, the excitation trajectory represented by the Fourier series is designed, and the combined inertial parameter set is estimated by using LS. Second, select the minimum inertial parameters and friction parameters (minimum dynamic parameters) as the center points to search the upper and lower bounds; design the fitness function with adjustable weights of each joint and use the SOS algorithm to estimate the minimum dynamic parameter set as a whole. Finally, a variety of parameter identification algorithms are applied to the Stäubli TX-90 robot under the same excitation trajectory. The experiment results show that the root-mean-square (rms) error of the joint torque estimated by the proposed method is the smallest. By executing the verification trajectory, the experiment results show that the rms error of the joint torque is small and the correlation coefficient is close to 1, thereby verifying the effectiveness of the estimated model for different motion trajectories.
Inorganic Elements in Eggs of Two Cavity-Nesting Passerine Species at and around Los Alamos National Laboratory, Los Alamos, New Mexico

Los Alamos National Laboratory (LANL) was established in 1943 as part of the Manhattan Project to build nuclear weapons, and currently operates as a national research laboratory. As part of an ongoing assessment of site-related ecological risk at LANL, western bluebird (Sialia mexicana) and ash-throated flycatcher (Myiarchus cinerascens) eggs were collected from 1997 to 2012 and analyzed for 18 inorganic elements. Concentrations of many inorganic elements in eggs were below reporting limits. Between species comparisons revealed that western bluebird eggs had higher levels of barium while ash-throated flycatcher eggs had higher levels of mercury. No statistically significant differences were observed in concentrations of inorganic elements in western bluebird eggs collected from the study area (which consists of areas within the current and historic LANL boundary) and from a non-industrial reference site; nor were any statistically significant differences observed between two canyons of interest, known to have received effluents and storm water runoff from LANL facilities, and the non-industrial reference site. Inorganic element levels detected in western bluebirds were typically within the range measured in eggs of other passerine in the published literature. These data suggest that concentrations of inorganic elements in passerine eggs collected from the study area appear to be at levels causing negligible risks to local bird populations.
Effects of Multifunctional Margins Implementation on Biodiversity in Annual Crops

The most suitable land for agricultural use has been gradually occupied by crops around the world. Large, uninterrupted croplands have been created, while disproportionate amounts of fertilizers, insecticides, fungicides and herbicides are applied on them. As a result, agricultural activity has a negative impact on biodiversity the ecological intensification of cultivated lands has become necessary. Multifunctional Margins (MFM), the establishment of native flora margins adjacent to croplands, provide a semi-natural habitat for food and wildlife refuge. Three different species mixtures sown in MFM were studied in this paper. The large capacity of six species used in MFM (Borago officinalis, Glebionis coronaria, Coriandrum sativum, Sinapis alba, Trifolium resupinatum and Vicia sativa) was determined. Reductions of up to 65% in the appearance of weeds and increases of 36% in pollinator biodiversity in sown MFM with respect to the MFM of spontaneous flora were observed. The biodiversity of the epigeal fauna increased by 15% in the MFM of spontaneous flora and by 32% in sown MFM, with respect to annual crops.
A review of natural language processing for financial technology

In the past few years, the development of natural language processing has been able to deal with many issues such as emotional analysis, semantic analysis, and so on. This review first introduces the development of natural language processing, and then summarizes their applications in financial technology, which mainly focuses on public opinion analysis, financial prediction and analysis, risk assessment, intelligent question answering, and automatic document generation. The analysis shows that natural language processing can give full play to its advantages in the financial field. Moreover, this paper also discusses the problems and challenges for financial technology that are developed based on natural language processing. Finally, this paper presents two developing trends of natural language processing in financial technology: deep learning and knowledge graph.
A Scalable Bayesian Sampling Method Based on Stochastic Gradient Descent Isotropization

Stochastic gradient sg-based algorithms for Markov chain Monte Carlo sampling (sgmcmc) tackle large-scale Bayesian modeling problems by operating on mini-batches and injecting noise on sgsteps. The sampling properties of these algorithms are determined by user choices, such as the covariance of the injected noise and the learning rate, and by problem-specific factors, such as assumptions on the loss landscape and the covariance of sg noise. However, current sgmcmc algorithms applied to popular complex models such as Deep Nets cannot simultaneously satisfy the assumptions on loss landscapes and on the behavior of the covariance of the sg noise, while operating with the practical requirement of non-vanishing learning rates. In this work we propose a novel practical method, which makes the sg noise isotropic, using a fixed learning rate that we determine analytically. Extensive experimental validations indicate that our proposal is competitive with the state of the art on sgmcmc.
The dynamics of attitudes toward immigrants: Cohort analyses for Western EU member states

Public opinion climates on immigrants are subject to certain dynamics. This study examines two mechanisms for such dynamics in Western EU member states for the 2002–2018 period. First, the impact of cohort replacement and, second, the impact of periodic threat perceptions, namely, changing macroeconomic conditions and shifts in immigration rates. To date, empirical research on anti-immigrant sentiments rarely combines these two concepts simultaneously to disentangle the interplay of period and cohort effects and determine the factors for long- and short-term attitude changes in societies. Motivated by this gap in the literature, I conduct multiple linear regression analyses of pooled data from all waves of the European Social Survey to show that the process of cohort replacement has led to a substantially more positive opinion climate toward immigrants since the 2000s. However, results indicate that in the future, this positive development is likely to come to a halt since younger cohorts no longer hold significantly more immigrant-friendly attitudes than their immediate predecessors. Furthermore, we observe different period effects to impact cohorts’ attitudes. Fixed-effects panel analyses show that the effect of changing macroeconomic conditions on cohorts’ attitudes is low. Changes in immigration rates, however, lead to significantly more dismissive attitudes when immigrants originate from the Global South as opposed to when they enter from EU countries. These insights suggest that it is less economic or cultural threat perceptions, but ethnic prejudice that plays a key role for natives to oppose immigration. Overall, findings suggest that it is not either cohort or period effects driving large-scale attitude changes, but rather we observe an interplay of both.
First Comparative Analysis of the Simultaneous Horizontal Wind Observations by Collocated Meteor Radar and FPI at Low Latitude through 892.0-nm Airglow Emission

The Fabry–Pérot interferometer (FPI) and meteor radar are two important techniques for measuring the horizontal wind field in mesopause region, the observations of which still lack comprehensive comparison. Kunming Observatory (25.6°N,103.8°E) has deployed both instruments in recent years and provides collocated meteor radar and FPI observations. The meteor radar measures the horizontal wind fields over 24 hours every day continuously, whereas the FPI can only work during the night with clear air condition. FPI horizontal wind data from the 892.0-nm airglow emission (with a peak height at ~87 km) from 26 January to 8 February 2019 were comparatively analyzed with simultaneous meteor radar observations, which cover the range between 80 and 90 km with a vertical resolution of 1.8 km. It was found that the temporal variations in the horizontal wind fields observed by the FPI and meteor radar were generally consistent with one another, with the highest 2-D correlation coefficients of 0.91 (0.88) at 88 (87) km for the meridional (zonal) wind, which agreed with the peak height of OH airglow emission observed by the TIMED/SABER instrument. In addition, the correlation coefficient for the weighted meteor radar horizontal wind by OH concentration between 86 and 88 km and 85 and 89 km increased slightly from 0.91 (0.89) to 0.92 (0.89) for the meridional (zonal) wind, which indicated the contribution of OH concentration beyond the peak height to the FPI wind observations. We also found that the absolute horizontal wind values detected by two instruments were linearly correlated with a slope of ~1.3 for both wind components, and meteor radar wind observations were usually larger than the FPI observations.
Doses de nitrogênio e de fósforo recomendadas para produção econômica de milho verde em Mossoró-RN

Resumo: O nitrogenio (N) e o fosforo (P) geralmente sao os dois nutrientes que ocorrem em menores teores no solo em relacao a necessidade da planta e sao os nutrientes mais exigidos pela cultura do milho. Objetivou-se definir a melhor combinacao das doses de N e P associadas a maxima producao economica do milho verde, assim como definir os niveis criticos desses nutrientes no solo e na planta, em um Argissolo Vermelho-Amarelo do municipio de Mossoro-RN. Foram aplicados 17 tratamentos, sendo 16 tratamentos resultantes da combinacao entre quatro doses de N (30, 60, 90 e 120 kg ha -1 ) e de quatro doses de P 2 O 5 (30, 60, 90 e 120 kg ha -1 ) e um tratamento controle (sem N e sem P). O delineamento experimental foi o de blocos ao acaso com quatro repeticoes. As caracteristicas avaliadas foram: numero e peso total de espigas, numero e peso de espigas empalhadas comercializaveis e numero e peso de espigas despalhadas comercializaveis. A melhor combinacao das doses de N e de P 2 O 5 recomendadas para a producao de espigas verdes empalhadas comercializaveis e que proporcionam o maior retorno economico e de 120 kg ha -1 de N combinado com 120 kg ha -1 de P 2 O 5 . Para producao de espigas verdes empalhadas comercializaveis, nas condicoes deste experimento, o nivel critico de N no solo e de 0,43 g kg -1 , o nivel critico de P no solo e de 8,21 mg dm -3 e os niveis criticos de N e de P na folha sao, respectivamente, de 17,17 g kg -1 e 1,54 g kg -1 . Palavras chave: Zea mays L. , Adubacao nitrogenada, Niveis criticos.
Mind Mapping: Learning Strategy for Novice Learners of Anatomy for Physical Education Undergraduate Program

There is an important demand for faculty in undergraduate program to deliver lecture through student-centered learning environment. The purpose of this study is to determine the effects of a mind –mapping learning strategy on novice learner’s basic knowledge of anatomy. The subject of this study were new entrants of physical education undergraduate program of Universitas Muhammadiyah Surakarta. A paper-based mindmap learning strategy was introduced to the students in the experimental group to improve their basic knowledge of anatomy. This study applied the experimental method using control group design. Through one-way ANOVA analysis, it was found that paperbased mind-map learning strategy had no significant contribution enhancing basic understanding of anatomy in the experimental group. In addition, the results of simple paired t-test analysis indicated that mind-map performed as similar to standard note taking technique as an effective method to facilitate students learning new subject.
A review of separation anxiety disorder with a focus on research based intervention strategies

The purpose of this paper is to discuss what Separation Anxiety Disorder is, what causes SAD symptoms in some children, successful assessment methods, and finally treatment and intervention options available and the efficacy of each one. The focus of this paper is on research based interventions with the intention of finding the most successful and empirically based intervention available. The most widely used and empirically based intervention available at this time is Cognitive Behavioral Therapy (CBT). Alternative methods of treatment include psycho-education for mild cases and CBT plus medication for severe cases. Many areas need further research and future studies need more comparisons to active control groups, not just wait-list control groups. Some of the areas needing future research include: medications and their safety; CBT and variations of it; and the affects of the family on recovery. Lastly, the most effective and time efficient therapy should be found that includes both group and family components. This open access graduate research paper is available at UNI ScholarWorks: https://scholarworks.uni. edu/grp/997 A Review of Separation Anxiety Disorder with a Focus on Research Based Intervention Strategies A Research Paper Submitted in Partial Fulfillment of the Requirements of the Degree Masters of Arts in Education Lauryn C. Kittleson University of Northern Iowa August, 2003 I
Uranium thermochemical cycle: hydrogen production demonstration

ABSTRACT In hydrogen production industry, thermochemical cycle technology for converting thermal energy into chemical storage energy of hydrogen owns absolute advantages. Compared with other thermochemical cycles, thermochemical cycle technology based on uranium (UTC) is safer and more efficient. This technology consists of three steps, where only the hydrogen production step is unique. In this paper, the verification has been done for this step. Solid products were characterized by XRD and Raman spectroscopy, which were confirmed to be α-Na2U2O7. Gas chromatographic analyses were performed for gas samples, in which hydrogen output was obtained using an internal standard method.
A prediction method for population density in key areas

Predicting the population density in certain key areas of the city is of great importance. It helps us rationally deploy urban resources, initiate regional emergency plans, reduce the spread risk of infectious diseases such as Covid-19, predict travel needs of individuals, and build intelligent cities. Although current researches focus on using the data of point-of-interest (POI) and clustering belonged to unsupervised learning to predict the population density of certain neighboring cities to define metropolitan areas, there is almost no discussion about using spatial-temporal models to predict the population density in certain key areas of a city without using actual regional images. We abstract 997 key areas in Beijing and their regional connections into a graph structure and propose a model called Word Embedded Spatial-temporal Graph Convolutional Network (WE-STGCN). WE-STGCN is mainly composed of three parts, which are the Spatial Convolution Layer, the Temporal Convolution Layer, and the Feature Component. Based on the data set provided by the Data Fountain platform, we evaluate the model and compare it with some typical models. Experimental results show that the Spatial Convolution Layer can merge features of the nodes and edges to reflect the spatial correlation, the Temporal Convolution Layer can extract the temporal dependence, and the Feature Component can enhance the importance of other attributes that affect the population density of the area. In general, the WE-STGCN is better than baselines and can complete the work of predicting population density in key areas.
Effects of additives on the rheological and textural properties of surimi

Surimi is a concentrated myofibrillar protein added with several additives. It has been used by seafood industries as an intermediate product to produce various seafood analogues. Due to the current increase in health awareness, consumer demands healthier and less sweeter surimi. The objective of this study is to investigate the rheological and textural properties of surimi added with different types of additives which is sugar, salt and sago starch. This study is also done to determine the possibility of reducing the amounts of additives added to surimi. Sago starch as an additive to improve the rheological and textural property of surimi is studied. Another concern in the surimi industry is the washing process. The 3 washing cycle procedure produces large amount of water waste. Thus, this study is done to understand the effects of reducing the washing cycle and using nanobubble water on surimi. Results obtained from this research shows that mannitol yields the best results when compared to sucrose and sorbitol. Surimi with 4% (w/w) salt concentration yields the highest gel strength. However, surimi with 1% (w/w) salt concentration which possesses a lower gel strength showed frozen stability up to 6 months. Sago starch was found to increase gel strength up to 11 0%. Washing using medium concentrated nanobubble water ( 11.15 x 1 08 bubbles/ml) was found to display a high gelling strength with only 2 washing cycle compared to using distilled water.
Stacking BERT based Models for Arabic Sentiment Analysis

: Recently, transformer-based models showed great success in sentiment analysis and were considered as the state-of-the-art model for various languages. However, the accuracy of Arabic sentiment analysis still needs improvements. In this work, we proposed a stacking architecture of Arabic sentiment analysis by combing different BERT models. We also create a large-scale dataset of Arabic sentiment analysis by merging small publicly available datasets. The experimental study proves the efﬁciency of the proposed approach in terms of classiﬁcation accuracy compared to single model architecture.