Miracle-dz/UniFAR-FTUs huggingface dataset:
Volumetric Surface Deformation with Auxiliary Voxel Grids

We propose two space deformation methods based on voxels. Our methods, approximately preserving the volume of a mesh object, are simple to implement and have a high performance due to resorting to voxelization. Volumetric deformations are achieved by either dual quaternion skinning or a nonlinear rigidity energy. The mesh surface embedded within the voxel grid is updated by means of interpolation. Three interpolation methods are implemented, targeting speed and smoothness, respectively. Both visual and quantitative evaluations on a variety of large polygon meshes are provided, demonstrating the effectiveness of the methods.
Multitable Methods for Microbiome Data Integration

The simultaneous study of multiple measurement types is a frequently encountered problem in practical data analysis. It is especially common in microbiome research, where several sources of data—for example, 16s-rRNA, metagenomic, metabolomic, or transcriptomic data–can be collected on the same physical samples. There has been a proliferation of proposals for analyzing such multitable microbiome data, as is often the case when new data sources become more readily available, facilitating inquiry into new types of scientific questions. However, stepping back from the rush for new methods for multitable analysis in the microbiome literature, it is worthwhile to recognize the broader landscape of multitable methods, as they have been relevant in problem domains ranging across economics, robotics, genomics, chemometrics, and neuroscience. In different contexts, these techniques are called data integration, multi-omic, and multitask methods, for example. Of course, there is no unique optimal algorithm to use across domains—different instances of the multitable problem possess specific structure or variation that are worth incorporating in methodology. Our purpose here is not to develop new algorithms, but rather to 1) distill relevant themes across different analysis approaches and 2) provide concrete workflows for approaching analysis, as a function of ultimate analysis goals and data characteristics (heterogeneity, dimensionality, sparsity). Towards the second goal, we have made code for all analysis and figures available online at https://github.com/krisrs1128/multitable_review.
Deep sequencing of small RNA facilitates tissue and sex specific microRNA discovery in zebrafish

Role of microRNAs in gene regulation has been well established. Though the number of genes appear to be equal between human and zebrafish, miRNAs detected in zebrafish (∼247) is significantly low compared to human (∼2000; miRBase Release 19). It appears that most of the miRNAs in zebrafish are yet to be discovered. Using next generation sequencing technology, we sequenced small RNAs from brain, gut, liver, ovary, testis, eye, heart and embryo of zebrafish. In few tissues (brain, gut, liver) sequencing was done sex specifically. About 16-62% of the sequenced reads mapped to known miRNAs of zebrafish, with the exceptions of ovary (5.7%) and testis (7.8%). We used miRDeep2, the miRNA predication tool, to discover the novel miRNAs using the un-annotated reads that ranged from 7.6 to 23.0%, with exceptions of ovary (51.4%) and testis (55.2%) that had the largest pool of un-annotated reads. The prediction tool identified a total of 459 novel pre-miRNAs. Comparison of miRNA expression data of the tissues showed the presence of tissue and sex specific miRNAs that could serve as biomarkers. The brain and liver had highest number of tissue specific (36) and sex specific (34) miRNAs, respectively. Taken together, we have made a comprehensive approach to identify tissue and sex specific miRNAs from zebrafish. Further, we have discovered 459 novel pre-miRNAs (∼30% homology to human miRNA) as additional genomic resource for zebrafish. This resource can facilitate further investigations to understand miRNA-mRNA gene regulatory network in zebrafish which will have implications to understand human miRNA function.
Learning Abstract Statistics Concepts Using Simulation

The teaching and learning of statistics has impacted the curriculum in elementary, secondary, and post-secondary education. Because of this growing movement to expand and include statistics into all levels of education, there is also a considerable interest in how to teach statistics. For statistics concepts that tend to be very difficult or abstract, many researchers have recommended using computer simulation methods (CSMs), but there have been very few empirically and theoretically based studies related to student achievement using these methods. The purpose of this study was to determine whether using CSMs enhanced student understanding of abstract statistics concepts for students enrolled in an introductory course. Based on a theoretical framework of how students learn statistics, the preliminary results of this study indicate some evidence that these methods may improve student understanding of
An extensive molecular phylogeny of weaverbirds (Aves: Ploceidae) unveils broad nonmonophyly of traditional genera and new relationships

ABSTRACT The diverse Old World avian family Ploceidae (weaverbirds) presently comprises 117 species in 17 genera. Despite being a well-known bird group, the family has received incomplete attention in terms of molecular systematics; systematists have often focused on subclades, with the most extensive study to date covering <66% of recognized species. As a consequence, weaverbird taxonomy remains outdated, and phylogenetic relationships, particularly of the African Malimbus (previously Ploceus and Malimbus) clade, remains largely unresolved. Here, we sampled 109 weaver species (and numerous nominal subspecies), including 99 of the 103 recognized “typical weaverbird” taxa for an 8-gene dataset. Antique DNA techniques were used to extract DNA from study skins of 27 rare taxa not available in global tissue collections. The study included 32 species and 4 genera of ploceids previously unstudied phylogenetically. Our analyses supported monophyly of the family and identified 8 distinct clades. Our results conflict extensively with current taxonomy. We suggest that plumage traits and morphology exhibit high plasticity, such that phenotype does not always reflect phylogenetic relationships in weaverbirds. We recommend (1) uniting African-Ploceus, Malimbus, Anaplectes, and Notiospiza in Malimbus; (2) retaining the monotypic genus Pachyphantes; and (3) placing Brachycope with Euplectes. This study, the first near-species-level phylogeny for the family, lays a firm foundation for downstream studies of biogeography and character evolution.
Bacterial Communities in Aquatic Sediment from Bukit Duabelas Raintforest and Oil Palm Plantation at Sumatra Indonesia

The diversity of bacterial communities in aquatic sediment of rainforest and oil palm plantation at Sumatra was studied using pyrosequencing of 16S rRNA gene and common biodiversity indices. Phylogenetic approach was used for revealing the community shift of bacterial phyla and genera in both areas. Ecological approach used soil pH, total Carbon (TC), total Nitrogen (TN), available Phosphorus (AP) measurement and bacterial diversity with Shanon and Simpson indices, and bacterial richness with Chao1-ACE indices and OTUs. Bacterial diversity and richness in aquatic sediment of forest area was higher than that ones in oil palm plantation area, although their pH, TC, and TN in both areas were not different significantly. The majority of sequences related to Proteobacteria (34.85%), Acidobacteria (32.67%), Nitrospirae (6.86%), Chloroflexi (4.31%), and Actinobacteria (4.02%) were from forest; whereas those related to Acidobacteria (46.10%), Proteobacteria (25.86%), Nitrospirae (9.20%), Chloroflexi (4.99%), and Actinobacteria (2.34%) invented from oil palm plantation. The genera of Alphaproteobacteria and Betaproteobacteria dominated in genera phylotype of bacterial 16S rRNA phylogenetic revealed both aquatic sediment of forest and oil palm plantation. The most genera in the phylogenetic tree from aquatic sediment of both areas was Burkholderia. The bacterial community shift in aquatic sediment of forest transformation indicated higher bacterial diversity index, richness index, some of phyla and genera in aquatic sediment from forest than from oil palm plantation.
Effect of yeast cell wall supplementation on production performances and blood biochemical indices of dairy cows in different lactation periods

Aim: This experiment was conducted to determine the effect of yeast cell wall (YCW) supplementation on production performances and blood biochemical indices such as liver enzyme activities, energy metabolites, and electrolyte concentrations of dairy cows in different lactation periods (LP). Materials and Methods: Thirty-two lactating Holstein cows were assigned into 2×2 factorial arrangement, in which the factors were the treatment (TM) (control [n=16] vs. YCW [n=16]) and the LP (early lactation [n=14] vs. mid-lactation [n=18]). The cows with day in milk (DIM) <120 (81±7 DIM) were defined as early lactating cows, whereas the cows with DIM >120 (179±5 DIM) were assumed as mid-lactating cows. The YCW (SafMannan; Phileo, Lesaffre Animal Care, France) was used as the dietary supplement (10 g/cow/day) in this experiment. The statistical analysis of the data was performed by the two-way analysis of variance using the general linear model procedure to determine the main effects (TM and LP) and their interaction (TM×LP) on production performances and blood biochemical parameters of experimental cows. Results: No significant effects (p>0.05) of YCW supplementation on production performances and blood biochemical indices of cows in TM groups (control vs. YCW) were observed; however, some obvious effects were detected in LP (early- and mid-lactation). Milk and milk component yield of cows in early lactation were significantly higher (p<0.05) than in mid-lactation, whereas somatic cell count and milk urea nitrogen were not different (p>0.05) with the YCW supplementation. The higher level (p<0.05) of serum albumin was found in mid-lactating cows after YCW supplementation. Before the experiment, the higher (p<0.05) non-esterified fatty acid (NEFA) and NEFA/total cholesterol (T-Cho) ratio, and the lower (p<0.05) calcium (Ca) concentration were observed in early lactating cows comparison with mid-lactating cows; however, there were not different after YCW supplementation. Conclusion: The positive effects of YCW supplementation on milk and milk component yields, energy metabolite, especially NEFA and NEFA/T-Cho ratio and Ca concentration were observed in early lactating cows rather than mid-lactating cows.
QoS Metrics for Cloud Computing Services Evaluation

Cloud systems are transforming the Information Technology trade by facultative the companies to provide admission to their structure and also software products to the membership foundation. Because of the vast range within the delivered Cloud solutions, from the customer's perspective of an aspect, it's emerged as troublesome to decide whose providers they need to utilize and then what's the thought of his or her option. Especially, employing suitable metrics is vital in assessing practices. Nevertheless, to the most popular of our knowledge, there's no methodical explanation relating to metrics for estimating Cloud products and services. QoS (Quality of Service) metrics playing an important role in selecting Cloud providers and also optimizing resource utilization efficiency. While many reports have got to devote to exploitation QoS metrics, relatively not much equipment supports the remark and investigation of QoS metrics of Cloud programs. To guarantee a specialized product is published, describing metrics for assessing the QoS might be an essential necessity. So, this text suggests various QoS metrics for service vendors, especially thinking about the consumer's worry. This article provides the metrics list may stand to help the future study and also assessment within the field of Cloud service's evaluation.
Shiny-SoSV: A web app for interactive evaluation of somatic structural variant calls

Somatic structural variants play a significant role in cancer development and evolution. Accurate detection of these complex variants from whole genome sequencing data is influenced by many variables, the effects of which are not always linear. With increasing demand for the application of whole genome sequencing in clinical settings, there is an unmet need for clinician scientists to easily make technical decisions for every unique patient and sample. To address this, we have developed Shiny-SoSV, an interactive web application for evaluating the effects of five common variables on the sensitivity and precision of somatic structural variant calls, thereby enabling users to quickly make informed sequencing and bioinformatics decisions early on in their study design. Availability: Shiny-SoSV is freely available at https://hcpcg.shinyapps. io/Shiny-SoSV and source code available at https://github.com/tgong1/Shiny-SoSV
An Efficient Semantic Ranked Keyword Search of Big Data Using Map Reduce

Information retrieval is fast becoming the prevailing form of information access, surpassing traditional database style searching. Ontologies have become the tool of choice employed in many information retrieval systems and more prominently in semantic information retrieval. In order to overcome the disadvantages in key word based information retrieval systems, which transfer irrelevant information, ontology has been designed. A system with ontology mimics the real world, where every task is laced with certain meaning as this is basic idea behind knowledge processing. Hadoop, which is an open source frame work for storing and processing large datasets, is used for preprocessing the text documents. First, a set of text documents are considered. Preprocessing is performed on a large domain of data using Hadoop MapReduce. This includes the removal of the stop words along with stemming and excluding less frequency words. Despite this pre-processing, owing to the colossal number of index terms still floating in the considered domain data, the problem of high dimensionality is encountered. Therefore the dimensionality of such a group of terms is reduced by identifying it as a concept and those concepts can be viewed as a single dimension in a ontology based information retrieval system. Now ontology is constructed by assigning synonym set to each concept in this structure using tools like word net. Thus constructed ontology can be mapped on to the processed query which gives us the relevant information from the data pool considered.
A process model for building social capital in virtual learning communities

Social capital adds significant value to learning in virtual learning environments. Social capital is created when learners interact with each other, by exchanging rich and thoughtful experiences among themselves through storytelling. Little research has focused on how this stock of capital is valued in virtual environments. The goal of this paper is to describe how social capital is created, through storytelling. Trust is essential for building social capital in virtual learning environments. This paper presents a process model for creating and maintaining social capital in virtual communities based on trust.
Investigating Genotype 1a HCV Drug Resistance in NS5A Region via Bayesian Inference

Hepatitis C virus(HCV) treatment is on the cutting edge of medicine. Due to the high rate of mutations and low fidelity of HCV replication, resistant strains quickly become dominant in a viral population under the selection pressure of a drug. In this paper, we examined the drug resistance mechanism in the NS5 A region of genotype1 a HCV virus by comparing the sequence data from interferon-ribavirin treated and untreated patients. To find the drug resistance difference, we used innovative Bayesian probability models to detect mutation combinations and inferred detailed interaction structures of these mutations. We aim to provide reference to drug design and mutation mechanism understanding through our work.
Exploration of bacterial endophytes in cucumber (Cucumis sativus L.)

In an attempt to explore the potentials of the endophytic bacterial population in cucumber plants, thirty different isolates have been made and tested for its efficacy against damping off the pathogen, Pythium aphanidermatum (Edson) using dual culture technique. The result revealed the potentials of Pseudomonas aeurginosa (MPP EB 4 and MPP EB 3) and Achromobacter denitrificans (MPP EB 8). The isolates MPP EB 3, MPP EB 4 and MPP EB 8 showed the maximum inhibition of 36.7, 40.0 and 32.2 per cent over control, respectively. The convoction of animicrobial compound isolated from selected isolates of MPP EB 3, MPP EB 4 and MPP EB 8 were tested against the pathogen by using agar well diffusion technique, which showed inhibition of 25.2, 43.2 and13.7 per cent over control, respectively. GCMS analysis for the secondary metabolites of P.aeurginosa deciphered an array of compounds, which are known to have antifungal property. Achromobacter denitrificans (MPP EB 8) could not inhibit the pathogen, but enhanced the plant growth up to 57.9 per cent, when compared to control. In addition to suppressing the pathogen, isolate MPP EB4 and MPP EB 3 could increase the growth of cucumber seedlings up to 31.6 and 17.0 per cent over control, respectively. Hence, MPP EB 4 (P.aeuriginosa) could be exploited as endophytic bioinoculant with adequate biosafety measures.
A proposal of grading system for fallen rice using neural network

Rice sorting in high-speed is needed for the mass shipment. However, the recognition performance of the conventional sorter is not fast enough for the transaction volume concerned. In a conventional rice sorter, if the rice flow rate exceeds a few thousands [kg/h], the recognition percentage is below 90% and recognition ability is not guaranteed. Thus we propose a new system for the rice grading using the neural network. We show the effectiveness of the proposed method by simulation with real rice data, such as the normal rice and damaged rice. Furthermore, we also propose an extraction algorithm, which can sample a single grain or rice among a large quantity of rice in a single image frame. Moreover, we develop a prototype system for rice grading, and show its performance and effectiveness.
Uncovering the underlying mechanisms and whole-brain dynamics of therapeutic deep brain stimulation for Parkinson’s disease

Deep brain stimulation (DBS) for Parkinson’s disease is a highly effective treatment in controlling otherwise debilitating symptoms yet the underlying brain mechanisms are currently not well understood. We used whole-brain computational modeling to disclose the effects of DBS ON and OFF during collection of resting state fMRI in ten Parkinson’s Disease patients. Specifically, we explored the local and global impact of DBS in creating asynchronous, stable or critical oscillatory conditions using a supercritical bifurcation model. We found that DBS shifts the global brain dynamics of patients nearer to that of healthy people by significantly changing the bifurcation parameters in brain regions implicated in Parkinson’s Disease. We also found higher communicability and coherence brain measures during DBS ON compared to DBS OFF. Finally, by modeling stimulation we identified possible novel DBS targets. These results offer important insights into the underlying effects of DBS, which may in time offer a route to more efficacious treatments.
Effect of Manipulation of Notch Signaling Pathway on Neural Stem Cell Proliferation in the Hippocampus Following Traumatic Brain Injury

9 Chapter 1 – Introduction and Background.12 Epidemiology.12 Mechanism and Biomechanics of TBI.13 Pathology of TBI.14 Adult Neurogenesis.16 TBI-induced Neurogenesis in TBI Animal Models.21 Notch Signaling Pathway.28 Chapter 2 – Materials and Methods.39 Experimental Animals.39 Experimental Setup.39 Surgical Procedures.40 Lateral Fluid Percussion Injury.42 Intraventricular Osmotic Mini-pump Infusion.44 BrdU Injections.44 Sacrifice and Tissue Processing.45 BrdU Immunostaining.45 DCX, Ki67 Immunostaining.47 Stereological Cell Quantification.47 Statistical Analysis.48
TIME-EFFICIENT pH-BASED METHOD TO QUANTIFY THE ACTIVITY OF ALKALINE AND HALO-ALKALINE PROTEASES

Proteases from haloalkaliphilic microorganisms are biocatalyst with a great interest to be studied in biotechnological implications. Nevertheless, available methods for assay haloalkaliphilic proteases on protein substrates are few, are carry out to end point and implies the use of complicated steps. A new high throughput screening assay is described involving pH indicators at haloalkaline conditions. Rapid Enzymatic Determination method use casein as natural substrate and salts: NaCl and KCl to measure the activity of halophilic proteases. When a peptide bond is cleaved by a protease a proton is released changing the color of the indicator, proteolysis is followed by monitoring the decrease in absorbance. This is the easiest, quickest, and cheapest kinetic assay. Moreover, amounts of about 40 ng×mL-1 of proteolytic enzyme could be detected by this method in a pH range from 7.5 to 10.9 and salt concentrations from 0 to 4 M.
A prototype report filter to reduce information overload in combat simulations

This research resulted in a successful design and demonstration of the Simulation Information Filtering Tool (SIFT). SIFT is an information technology that can assist decision-makers in reducing their information flows when participating in combat training simulations. SIFT converts the commander's critical information requirements (CCIR) into filtering criteria. The CCIR standard filters all but critical information from a commander's message stream. Critical information is, by definition, information with the highest value. The message stream becomes smaller, yet packed with high value information. In demonstration, SIFT reduced the volume of reports by 86% and retained those that were critical. Using a cognitive model to estimate human report processing capacity, the SIFT prototype shows great potential in helping commanders avoid information overload.