Miracle-dz/UniFAR-FTUs huggingface dataset:
Emergence Rate and Initial Growth of Longan (Dimocarpus longan Lour) in Relation to Seeds Sizes

The fruit plant ‘Longan’ is considered as being native to Asia and is at present commercially explored in some regions. The objective of this work was to study the influence of seed size on seed emergence and initial seedling growth. The experiment was carried out using a randomized block design (DBC), with three treatments, namely, the seed sizes at seedling emergence according to their longitudinal diameter: small, medium and large. Each plot was composed of six seeds and five replications per treatment. The following characteristics were evaluated: emergence speed index, average time, percentage and relative frequency of emergence, leaf number, stem diameter, plant height, shoot dry mass and root dry mass. Seeds of medium and large size are those that presented satisfactory results for the characteristics related to seed emergence. The same ones stood out in relation to the small seeds for the variables percentage, average time, average speed and emergence speed index. Small seeds are not recommended for the production of ‘Longan’ seedlings, given the long period of time to emerge and the low probability of the seedlings establishing satisfactorily in the field. The medium and large seeds were the most promising for the variables number of leaves, stem diameter, plant height, dry shoot mass and dry root mass.Therefore, according to the conditions in which the present work was conducted, the use of medium and large seeds for the production of ‘Longan’ seedlings is suggested.
Manifestations and Risk Factors of Atherosclerosis in Chronic Renal Failure

5 CONTENTS 6 ABBREVIATIONS 8 LIST OF ORIGINAL PUBLICATIONS 9 INTRODUCTION 10 REVIEW OF THE LITERATURE 12 1. Cardiovascular disease in chronic renal failure 12 2. Clinical manifestations of atherosclerotic vascular disease in chronic renal failure 15 2.1. Coronary artery disease 15 Diagnosis of coronary artery disease 16 2.2. Cerebrovascular disease 18 Diagnosis of cerebrovascular disease 18 2.3. Peripheral arterial disease 19 Diagnosis of peripheral arterial disease 19 Medial arterial calcification 20 3. Risk factors for atherosclerosis 22 3.1. General population 22 Homocysteine 23 3.2. Risk factors for atherosclerosis in patients with chronic renal failure 25 Hypertension 25 Diabetes 27 Smoking 27 Dyslipidemia 28 Dyslipidemia, outcome and cardiovascular disease in chronic renal failure 28 Oxidation 33 Inflammation 33 Homocysteine 34 4. Arteriosclerosis in patients with chronic renal failure 37 4.1. Definition 37 4.2. Arterial stiffness 37 4.3. Vascular calcification 38 Effect of calcium-phosphate disorders 39 5. Ultrasound examination of arterial vessels 40 5.1. Carotid artery ultrasound examination 40 5.2 Thoracic aortic examination by using transesophageal echocardiography 41
New Insight into Organic Metal Polyaniline Morphology and Structure

Polyaniline is known to be a true metal, though a nanometal. Previous experimental and theoretical evidence is reviewed. Two important structural features are presented, which have not publicly been discussed so far: (a) The formation of complexes between polyaniline and metals (Cu, Fe, Zn, In, etc.) which are crucial for most practical applications of the organic metal, polyaniline; and (b) a model for the polyaniline chain structure within the smallest morphological unit, the roughly 10 nm primary particle.
Pse-Analysis: a python package for DNA/RNA and protein/peptide sequence analysis based on pseudo components and kernel methods

To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned. Based on the benchmark dataset, Pse-Analysis will automatically construct an ideal predictor, followed by yielding the predicted results for the submitted query samples. All the aforementioned tedious jobs can be automatically done by the computer. Moreover, the multiprocessing technique was adopted to enhance computational speed by about 6 folds. The Pse-Analysis Python package is freely accessible to the public at http://bioinformatics.hitsz. edu.cn/Pse-Analysis/, and can be directly run on Windows, Linux, and Unix.
Space and Time Maps of Cone Photoreceptor Signals in Macaque Lateral Geniculate Nucleus

We studied neurons in the central visual field representation of the lateral geniculate nucleus (LGN) in macaque monkeys by mapping their receptive fields in space and time. The mapping was performed by reverse correlation of a spike train of a neuron with pseudorandom, binary level stimuli (m-sequence grids). Black and white m-sequence grids were used to map the receptive field for luminance. The locations of receptive field center and surround were determined from this luminance map. To map the contribution of each cone class to the receptive field, we designed red–green or blue–yellow m-sequence grids to isolate the influence of that cone (long, middle, or short wavelength-sensitive: L, M, or S). Magnocellular neurons generally received synergistic input from L and M cones in both the center and the surround. A minority had cone-antagonistic (M–L) input to the surround. Red–green opponent parvocellular neurons received opponent cone input (L+M− or M+L−) that overlapped in space, as sampled by our stimulus grid, but that had somewhat different extents. For example, an L+ center parvocellular neuron would be L+/M− in both center and surround, but the L+ signal would be stronger in the center and the M− signal stronger in the surround. Accordingly, the luminance receptive field would be spatially antagonistic: on-center/off-surround. The space–time maps also characterized LGN dynamics. For example, magnocellular responses were transient, red–green parvocellular responses were more sustained, and blue-on responses were the most sustained for both luminance and cone-isolating stimuli. For all cell types the surround response peaked 8–10 msec later than the center response.
Loss-of-function tolerance of enhancers in the human genome

Previous studies have surveyed the potential impact of loss-of-function (LoF) variants and identified LoF-tolerant protein-coding genes. However, the tolerance of human genomes to losing enhancers has not yet been evaluated. Here we present the catalog of LoF-tolerant enhancers using structural variants from whole-genome sequences. Using a conservative approach, we estimate that each individual human genome possesses at least 28 LoF-tolerant enhancers on average. We assessed the properties of LoF-tolerant enhancers in a unified regulatory network constructed by integrating tissue-specific enhancers and gene-gene interactions. We find that LoF-tolerant enhancers are more tissue-specific and regulate fewer and more dispensable genes. They are enriched in immune-related cells while LoF-intolerant enhancers are enriched in kidney and brain/neuronal stem cells. We developed a supervised learning approach to predict the LoF-tolerance of enhancers, which achieved an AUROC of 96%. We predict 5,677 more enhancers would be likely tolerant to LoF and 75 enhancers that would be highly LoF-intolerant. Our predictions are supported by known set of disease enhancers and novel deletions from PacBio sequencing. The LoF-tolerance scores provided here will serve as an important reference for disease studies.
Economic development and the role of agricultural technology

In earlier debates on economic development, the agricultural sector's role was somewhat controversial. While dualistic models highlighted the importance of agriculture, the mainstream literature placed a greater emphasis on the creation of a modern industrial sector. Soon agriculture disappeared from the mainstream development literature to re-emerge recently with a variety of multiple-sector growth models emphasizing the key role of agriculture and specifically technology in agriculture. This article is an empirical cross-country analysis of agricultural technology's role in economic development. Specifically, the hypothesis being tested is whether improvements in agricultural technology have a significant impact on long-run economic growth. The results indicate that agricultural modernization has a positive effect on both measures of economic growth and human development. Copyright 2007 International Association of Agricultural Economists.
Executive functions and school readiness intervention: Impact, moderation, and mediation in the Head Start REDI program

Abstract Despite their potentially central role in fostering school readiness, executive function (EF) skills have received little explicit attention in the design and evaluation of school readiness interventions for socioeconomically disadvantaged children. The present study examined a set of five EF measures in the context of a randomized-controlled trial of a research-based intervention integrated into Head Start programs (Head Start REDI). Three hundred fifty-six 4-year-old children (17% Hispanic, 25% African American; 54% girls) were followed over the course of the prekindergarten year. Initial EF predicted gains in cognitive and social–emotional skills and moderated the impact of the Head Start REDI intervention on some outcomes. The REDI intervention promoted gains on two EF measures, which partially mediated intervention effects on school readiness. We discuss the importance of further study of the neurobiological bases of school readiness, the implications for intervention design, and the value of incorporating markers of neurobiological processes into school readiness interventions.
Participation in Online Courses and Interaction With a Virtual Agent

Online learning environments could be well understood as a multifaceted phenomenon affected by different aspects of learner participation including synchronous/asynchronous interactions. The aim of this study was to investigate learners’ participation in online courses, synchronous interaction with a conversational virtual agent, their relationships with learner performance, and the participation/interaction factor identification. To examine learner participation, we collected learning management system (LMS) log data that included the frequency and length of course access, discussion board postings, and final grades. To examine synchronous learner interaction, we collected learners’ conversation logs from the conversational agent. We calculated the quantity and quality of discussion postings and conversations with the agent. The results showed that the frequency and length of course access, the quantity and quality of discussion postings, and the quality of conversation with the agent were significantly associated with the learner achievement. This study also identified two factors that comprise online learning participation and interaction: interaction quality and LMS-oriented interaction.
Administration of intracoronary bone marrow mononuclear cells on chronic myocardial infarction improves diastolic function

Background: Regeneration of the myocardium and improved ventricular function have been demonstrated in patients with acute myocardial infarction (MI) treated by intracoronary delivery of autologous bone marrow mononuclear cells (BMC) a few days after successful myocardial reperfusion by percutaneous coronary intervention (PCI); however, the effects of intracoronary cell infusion in chronic MI patients are still unknown. Aims: To investigate whether intracoronary infusion of BMC into the infarct-related artery in patients with healed MI could lead to improvement in left ventricular (LV) function. Methods: Among 47 patients with stable ischaemic heart disease due to a previous MI (13 (SD 8) months previously), 24 were randomised to intracoronary infusion of BMC (BMC group) and 23 to a saline infusion (control group) into the target vessel after successful PCI within 12 hours after chest pain occurred. LV systolic and diastolic function, infarct size and myocardial perfusion defect were assessed with the use of echocardiography, magnetic resonance imaging (MRI) or 201Tl single-photon-emission computed tomography (SPECT) at baseline and repeated at the 6-month follow-up examination. Results: BMC treatment did not result in a significant increase in LV ejection fraction in any of the groups by any of the methods used, and the apparent tendency of an improvement was not statistically different between the two groups. The two groups also did not differ significantly in changes of LV end-diastolic and systolic volume, infarct size or myocardial perfusion. However, there was an overall effect of BMC transfer compared with the control group with respect to early/late (E/A) (p<0.001), early diastolic velocity/late diastolic (Aa) velocity (Ea/Aa) ratio (p = 0.002) and isovolumetric relaxation time (p = 0.038) after 6 months, as evaluated by tissue Doppler echocardiography. We noted no complications associated with BMS transfer. Conclusion: Intracoronary transfer of autologous BMC in patients with healed MI did not lead to significant improvement of cardiac systolic function, infarct size or myocardial perfusion, but did lead to improvement in diastolic function.
Stable Encoding of Finite-State Machines in Discrete-Time Recurrent Neural Nets with Sigmoid Units

There has been a lot of interest in the use of discrete-time recurrent neural nets (DTRNN) to learn finite-state tasks, with interesting results regarding the induction of simple finite-state machines from inputoutput strings. Parallel work has studied the computational power of DTRNN in connection with finite-state computation. This article describes a simple strategy to devise stable encodings of finite-state machines in computationally capable discrete-time recurrent neural architectures with sigmoid units and gives a detailed presentation on how this strategy may be applied to encode a general class of finite-state machines in a variety of commonly used first- and second-order recurrent neural networks. Unlike previous work that either imposed some restrictions to state values or used a detailed analysis based on fixed-point attractors, our approach applies to any positive, bounded, strictly growing, continuous activation function and uses simple bounding criteria based on a study of the conditions under which a proposed encoding scheme guarantees that the DTRNN is actually behaving as a finite-state machine.
A Quantitative Image Cytometry Technique for Time Series or Population Analyses of Signaling Networks

Background Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. Methodology/Principal Findings We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. Conclusions/Significance The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.
Micro Modelling of User Perception and Generation Processes for Macro Level Predictions in Online Communities

The way information is presented to users in online community platforms has an influence on the way the users create new information. This is the case, for instance, in question-answering fora, crowdsourcing platforms or other social computation settings. To better understand the effects of presentation policies on user activity, we introduce a generative model of user behaviour in this paper. Running simulations based on this user behaviour we demonstrate the ability of the model to evoke macro phenomena comparable to the ones observed on real world data.
Sparse Representation in Classification

Sparse representation with learning-based overcomplete dictionaries has recently achieved impressive results in signal representation and outperforms traditional methods in tasks such as signal denosing and image inpainting. Inference algorithms also benefit from sparse representation because of its effectiveness in removing data corruption such as dense noise and partial occlusion and the ability to model the high-level factors underlying the data. The representation, also known as feature extraction has contributed to machine learning algorithms with good performance. In this thesis, the problem of combining sparse representation-based methods and discrimination-based methods in inference tasks to gain benefit from both types of approaches has been studied. Specifically, three algorithms were developed to address problems in three different applications. Sparse representation was firstly employed as an interpretable method to model pathological human gait in order to help diagnosis. The used sparse representation algorithms simultaneously train linear classifiers during the representation process. Then the problem of inter-class coherence in multi-class data is addressed to encourage classes to be sparsely represented in a more discriminative way. A framework was proposed to separate the representative and discriminative components though sparse representation to enlarge the disparity of learned class models. Finally, support vector machine and a special form of sparse representation, the archetype analysis, is combined in a latent model with temporal constraints to extract ordinal key poses from 3D skeleton videos for action recognition. Experiments using well-known datasets were designed to evaluate the proposed algorithms and demonstrate their effectiveness.
Determinants and prediction of transmural myocardial perfusion.

The vulnerability of subendocardial muscle to ischemic damage is due primarily to the greater risk of underperfusion. Recent studies of coronary autoregulation have shown that as myocardial oxygen needs increase beyond the ability of coronary blood flow to supply oxygen, maximal vasodilatation occurs earliest in subendocardial vessels; any further imbalance then causes subendocardial ischemia, since no further compensatory vasodilatation is possible. In animal experiments relative subendocardial perfusion (the ratio of flow per gram in subendocardial to subepicardial muscle) can be predicted from the DPTI: SPTI ratio of two pressure-time areas, where DPTI = the area between coronary and left ventricular pressures in diastole and SPTI = the area beneath the left ventricular systolic pressure. Early studies demonstrated subendocardial underperfusion when DPTI: SPTI was below 0.7, but more recent studies show that this critical ratio is about 0.4. Applying the results of these animal studies to man must be done very cautiously. Peak ventricular systolic pressure is better than SPTI in predicting myocardial oxygen needs, but neither measure allows for changes in wall tension
The interference of Newcastle, avian influenza and infectious bursal disease vaccines with the efficiency of IB vaccine in broiler chicks by using quantitative RT-PCR test

This study was conducted to investigate the effects the interference of ND, AI, IBD vaccines on efficacy of the IBV vaccination program (H120 and Ma5). Three hundred broiler chicks (Ross308) from Al-Haddi hatchery / Babel province were divided randomly into three equal groups, each group contain 100 chicks and treated as follows: the 1 group; IB vaccine (H120) was given at one day old by intranasal and ocular drop methods, IB vaccine Ma5 strain vaccine was given at age 14 days by spray method. The 2 group at one day old IB H120 + ND LaSota alive vaccines strain was given by intranasal and ocular drop method, also given mixed killed vaccine contain ND with AI by S/C injection. At 10 days old alive ND vaccine LaSota strain gives by drinking water. At 12 in day old attenuated IBD vaccine gives by drinking water. At day old IB Ma5 strain vaccine was given using spray method. The 3 group: control group without vaccine. Blood samples were collected from jugular vein at 1, 7, 14, 21, 28, 35 and 40 day old to determine the antibody titer against IBV by ELISA test and samples were taken from trachea and kidney for Realtime quantitative -PCR (viral load) at 21 and 35 days old. All groups were challenged with local virulent IBV isolate (IBV CH Babylon F2 2013) 100×10 ELD50/ml at 28 days old by ocular and intranasal drop method. Morbidity and mortality were recorded in all the challenged birds. The result show that the significant differences between all groups in different parameters at P<0.05.
Impact of VEGF polymorphisms on the severity of peripheral artery disease in diabetic patients

Objective. To determine the potential genotype vascular endothelial growth factor (VEGF) gene differences in diabetic patients with peripheral arterial disease (PAD), which might be associated with different stages of the vascular disease. Methods. A study was conducted with type 2 diabetic patients with PAD [n = 70; 32 intermittent claudication and 38 critical limb ischaemia (CLI)]. Genotyping of the VEGF gene insertion/deletion − 2549, − 2578 C/A and +405 G/C polymorphisms was done in both groups and correlated them with the severity of PAD. We compared serum VEGF levels in both groups. Results. There was a higher frequency of +405 CC and − 2578 CC genotypes in claudication group [(31.3% vs. 5.4%, p = 0.01) and (37.5% vs. 15.8%, p = 0.05), respectively]. The presence of +405 GG and − 2578 AA genotypes was more common among CLI patients [(57.8% vs. 37.5%, p = 0.01) and (42.1% vs. 18.8%, p = 0.05), respectively]. There were higher serum VEGF levels in patients with CLI (p = 0.029). Conclusions. We found preliminary evidence regarding the association between VEGF polymorphisms and different stages of PAD in diabetic patients.