Miracle-dz/UniFAR-FTUs huggingface dataset:
A large-scale benchmark study of existing algorithms for taxonomy-independent microbial community analysis

Recent advances in massively parallel sequencing technology have created new opportunities to probe the hidden world of microbes. Taxonomy-independent clustering of the 16S rRNA gene is usually the first step in analyzing microbial communities. Dozens of algorithms have been developed in the last decade, but a comprehensive benchmark study is lacking. Here, we survey algorithms currently used by microbiologists, and compare seven representative methods in a large-scale benchmark study that addresses several issues of concern. A new experimental protocol was developed that allows different algorithms to be compared using the same platform, and several criteria were introduced to facilitate a quantitative evaluation of the clustering performance of each algorithm. We found that existing methods vary widely in their outputs, and that inappropriate use of distance levels for taxonomic assignments likely resulted in substantial overestimates of biodiversity in many studies. The benchmark study identified our recently developed ESPRIT-Tree, a fast implementation of the average linkage-based hierarchical clustering algorithm, as one of the best algorithms available in terms of computational efficiency and clustering accuracy.
Does Blood Pressure Inevitably Rise With Age?: Longitudinal Evidence Among Forager-Horticulturalists

The rise in blood pressure with age is a major risk factor for cardiovascular and renal disease, stroke, and type 2 diabetes mellitus. Age-related increases in blood pressure have been observed in almost every population, except among hunter-gatherers, farmers, and pastoralists. Here we tested for age-related increases in blood pressure among Tsimane forager-farmers. We also test whether lifestyle changes associated with modernization lead to higher blood pressure and a greater rate of age-related increase in blood pressure. We measured blood pressure longitudinally on 2248 adults age ≥20 years (n=6468 observations over 8 years). Prevalence of hypertension was 3.9% for women and 5.2% for men, although diagnosis of persistent hypertension based on multiple observations reduced prevalence to 2.9% for both sexes. Mixed-effects models revealed systolic, diastolic, and pulse blood pressure increases of 2.86 (P<0.001), 0.95 (P<0.001), and 1.95 mmHg (P<0.001) per decade for women and 0.91 (P<0.001), 0.93 (P<0.001), and −0.02 mmHg (P=0.93) for men, substantially lower than rates found elsewhere. Lifestyle factors, such as smoking and Spanish fluency, had minimal effect on mean blood pressure and no effect on age-related increases in blood pressure. Greater town proximity was associated with a lower age-related increase in pulse pressure. Effects of modernization were, therefore, deemed minimal among Tsimane, in light of their lean physique, active lifestyle, and protective diet.
Interfacial Energy Anisotropy and Growth Morphologies in Aluminium-Zinc Alloys

This thesis presents an investigation aimed at the understanding of the effect of interfacial energy anisotropy on growth morphologies in Al-Zn alloys. Most low alloyed metals form dendritic structures that grow along directions that correspond to low index crystal axes, e.g., 〈100〉 directions in fcc aluminum. However, recent findings [Gon06, Gon08] have shown that an increase in the zinc content of Al-Zn continuously changes the dendrite growth direction from 〈100〉 to 〈110〉 in the (100) plane. At intermediate compositions, 〈320〉 dendrites and textured seaweeds were even observed. The reason for this dendrite orientation transition (DOT) is that this system exhibits a large solubility of the element zinc, which forms hexagonal crystals, in the primary fcc aluminum phase, thus modifying its weak solid-liquid interfacial energy anisotropy γsl. Due to the complexity of the phenomenology, there is still no satisfactory theory that predicts all the observed microstructures. The goal of this work was to measure the anisotropy of γsl, to gain further insight in the dendrite growth morphologies and mechanisms in Al-Zn via X-ray tomography and investigate the relationship between dendrite growth directions and the anisotropy of γsl via phase-field modeling. The values of the anisotropy in Al-82 wt. % Zn, obtained by equilibrium shape measurement, suggests a DOT in a regime with very low anisotropy, favoring the formation of seaweed structures. The enhanced experimental procedures and observation methods allowed an unprecedented characterization of such complex morphologies. Observations showed that seaweeds are far from random structures. They grow in a (100) symmetry plane by an alternating growth direction mechanism and are therefore less hierarchically ordered than common dendrites. Phase-field simulations of equiaxed growth of a dilute alloy showed that the DOT is not a continuous transition of growth directions, but rather a competition between the 〈100〉 and the 〈110〉 character of dentrites. However, crystallographic orientation measurements showed that the macroscopic texture evolves as evidenced by Gonzales and Rappaz. This showed that the preferred growth direction is not the same as the final texture of a sample, which is uncommon. Simulations of directional growth showed that seaweeds, which do not appear in equiaxed growth, are in fact produced by the interplay of low or degenerate crystalline anisotropy and the misorientation of the crystal with respect to the thermal gradient.
A batch approach for a survivable virtual network embedding based on Monte-Carlo Tree Search

In this paper, we address the survivable batch-embedding virtual network problem within Cloud's backbone. In fact, the batch mapping of virtual networks will enhance the cumulative Cloud provider's revenue thanks to the global view of the incoming requests during a predefined time slot. Hence, the differentiation between requests can be performed and the arrival order of requests is ignored. The embedding of one virtual network is NP-hard. Adding the batch processing of the requests will further increase the complexity of the problem. In order to skirt the exponential complexity, we formulate the problem as building and researching problems within a decision tree. To resolve it, we propose a novel reliable batch-embedding virtual network strategy denoted by BR-VNE. It is based on Monte-Carlo Tree Search optimization method in which the upper confidence bounds can be reached in polynomial time. Based on extensive simulations, the results obtained show that BR-VNE outperforms the related work in terms of i) acceptance rate of virtual network requests, ii) Cloud provider's revenue and iii) rate of requests impacted by physical failures within the Cloud's backbone.
Fitness uniform deletion: a simple way to preserve diversity

A commonly experienced problem with population based optimisation methods is the gradual decline in population diversity that tends to occur over time. This can slow a system's progress or even halt it completely if the population converges on a local optimum from which it cannot escape. In this paper we present the Fitness Uniform Deletion Scheme (FUDS), a simple but somewhat unconventional approach to this problem. Under FUDS the deletion operation is modified to only delete those individuals which are "common" in the sense that there exist many other individuals of similar fitness in the population. This makes it impossible for the population to collapse to a collection of highly related individuals with similar fitness. Our experimental results on a range of optimisation problems confirm this, in particular for deceptive optimisation problems the performance is significantly more robust to variation in the selection intensity.
Robust Feature Selection from Microarray Data Based on Cooperative Game Theory and Qualitative Mutual Information

High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI) for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches.
Subspace gradient domain mesh deformation

In this paper we present a general framework for performing constrained mesh deformation tasks with gradient domain techniques. We present a gradient domain technique that works well with a wide variety of linear and nonlinear constraints. The constraints we introduce include the nonlinear volume constraint for volume preservation, the nonlinear skeleton constraint for maintaining the rigidity of limb segments of articulated figures, and the projection constraint for easy manipulation of the mesh without having to frequently switch between multiple viewpoints. To handle nonlinear constraints, we cast mesh deformation as a nonlinear energy minimization problem and solve the problem using an iterative algorithm. The main challenges in solving this nonlinear problem are the slow convergence and numerical instability of the iterative solver. To address these issues, we develop a subspace technique that builds a coarse control mesh around the original mesh and projects the deformation energy and constraints onto the control mesh vertices using the mean value interpolation. The energy minimization is then carried out in the subspace formed by the control mesh vertices. Running in this subspace, our energy minimization solver is both fast and stable and it provides interactive responses. We demonstrate our deformation constraints and subspace deformation technique with a variety of constrained deformation examples.
P‐128: Solution Processable Polymer OLED Lighting Panels with 25 lm/W Efficiency

Through understanding of the device and photo‐physics we have developed a fluorescent and phosphorescent hybrid materials set and device architecture for stable white Polymer OLED (P‐OLED) lighting devices yielding 25 lm/W efficiency. We show that this technology can be transferred to solution processed ITO‐free lighting panels realizing 32 lm/W efficiency with out‐coupling film.
Fuzzy Logic for Cross-layer Optimization in Cognitive Radio Networks

The search for the ultimate architecture for cross-layer optimization in cognitive radio networks is characterized by challenges such as modularity, interpretability, imprecision, scalability, and complexity constraints. In this article we propose fuzzy logic as an effective means of meeting these challenges, as far as both knowledge representation and control implementation are concerned.
Ongoing and future developments at the Universal Protein Resource

The primary mission of Universal Protein Resource (UniProt) is to support biological research by maintaining a stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces freely accessible to the scientific community. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is updated and distributed every 4 weeks and can be accessed online for searches or download at http://www.uniprot. org.
Vector Autoregressive Model-Order Selection From Finite Samples Using Kullback's Symmetric Divergence

In this paper, a new small-sample model selection criterion for vector autoregressive (VAR) models is developed. The proposed criterion is named Kullback information criterion (KICvc), where the notation vc stands for vector correction, and it can be considered as an extension of the KIC, for VAR models. KICvc adjusts KIC to be an unbiased estimator for the variant of the Kullback symmetric divergence, assuming that the true model is correctly specified or overfitted. Furthermore, KICvc provides better VAR model-order choices than KIC in small samples. Simulation results show that the proposed criterion selects the model order more accurately than other asymptotically efficient methods when applied to VAR model selection in small samples. As a result, KICvc serves as an effective tool for selecting a VAR model of appropriate order. A theoretical justification of the proposed criterion is presented
A Decision Support System for Real-Time Stress Detection During Virtual Reality Exposure

Virtual Reality (VR) is increasingly being used in combination with psycho-physiological measures to improve assessment of distress in mental health research and therapy. However, the analysis and interpretation of multiple physiological measures is time consuming and requires specific skills, which are not available to most clinicians. To address this issue, we designed and developed a Decision Support System (DSS) for automatic classification of stress levels during exposure to VR environments. The DSS integrates different biosensor data (ECG, breathing rate, EEG) and behavioral data (body gestures correlated with stress), following a training process in which self-rated and clinical-rated stress levels are used as ground truth. Detected stress events for each VR session are reported to the therapist as an aggregated value (ranging from 0 to 1) and graphically displayed on a diagram accessible by the therapist through a web-based interface.
Mitochondrial Encephalomyopathies: Therapeutic Approach

Abstract: Therapy for mitochondrial diseases is woefully inadequate. How‐ever, lack of cure does not equate with lack of treatment. In this review, we consider sequentially several different therapeutic approaches. Palliative therapy is dictated by good medical practice and includes anticonvulsant medication, control of endocrine dysfunction, and surgical procedures. Removal of noxious metabolites is centered on combating lactic acidosis, but it extends to other metabolites, such as thymidine in patients with the mitochondrial neurogastrointestinal encephalomyopathy syndrome. Attempts to bypass blocks in the respiratory chain by administration of artificial electron acceptors have not been successful, but this concept may be amenable to genetic engineering. Administration of metabolites and cofactors is the mainstay of real‐life therapy and includes both components of the respiratory chain and other natural compounds. There is increasing interest in the administration of reactive oxygen species scavengers both in primary mitochondrial diseases and in neurodegenerative diseases directly or indirectly related to mitochondrial dysfunction. Aerobic exercise and physical therapy prevent or correct deconditioning and improve exercise tolerance in patients with mitochondrial myopathies due to mtDNA mutations. Gene therapy is a challenge because of polyplasmy and heteroplasmy, but interesting experimental approaches are being pursued and include, for example, decreasing the ratio of mutant to wild‐type mitochondrial genomes (gene shifting), converting mutated mtDNA genes into normal nDNA genes (allotropic expression), importing cognate genes from other species, or correcting mtDNA mutations with specific restriction endonucleases. Germline therapy raises ethical problems but is being seriously considered to prevent maternal transmission of mtDNA mutations. Preventive therapy through genetic counseling and prenatal diagnosis is still limited for mtDNA‐related disorders but is becoming increasingly important for nDNA‐related disorders.
Spacing between core recognition motifs determines relative orientation of AraR monomers on bipartite operators

Transcription factors modulate expression primarily through specific recognition of cognate sequences resident in the promoter region of target genes. AraR (Bacillus subtilis) is a repressor of genes involved in l-arabinose metabolism. It binds to eight different operators present in five different promoters with distinct affinities through a DNA binding domain at the N-terminus. The structures of AraR-NTD in complex with two distinct operators (ORA1 and ORR3) reveal that two monomers bind to one recognition motif (T/ANG) each in the bipartite operators. The structures show that the two recognition motifs are spaced apart by six bases in cases of ORA1 and eight bases in case of ORR3. This increase in the spacing in the operators by two base pairs results in a drastic change in the position and orientation of the second monomer on DNA in the case of ORR3 when compared with ORA1. Because AraR binds to the two operators with distinct affinities to achieve different levels of repression, this observation suggests that the variation in the spacing between core recognition motifs could be a strategy used by this transcription modulator to differentially influence gene expression.
Design and implement of high resolution still image compression and storage system

High resolution still image compression and storage plays a very important role in the application field of aero military reconnaissance, topography mapping and satellite remote sensing exploration. An embedded high resolution still image compression and storage system based on POWER PC, FPGA and ADV212 is presented in the paper in order to implement 4008×5366×12bit lossy and lossless compression of high resolution aero image. Image compression storage system structure and the software and hardware design method of the system are shown here. The design object is to save one image each two seconds and to send one image each eight seconds on the condition of 1.44Mbps transmission rate. The experimental results show that the system could implement expected real-time compression and storage of high resolution aero image.
Positional Fuzzy Relations in Robot Control

We define a new representation of the object in the known area. We can assign a name to the object and express uncertainty about its position using a fuzzy relation. This kind of representation about physical object can be used in the knowledge-based systems using rules and fuzzy inference system. We show an application in multi-robot coordination and control in the pursuit-evasion task.
Real-time classification of ground from lidar data for helicopter navigation

Helicopter pilots often have to deal with bad weather conditions and degraded views. Such situations may decrease the pilots' situational awareness significantly. The worst-case scenario would be a complete loss of visual reference during an off-field landing due to brownout or white out. In order to increase the pilots' situational awareness, helicopters nowadays are equipped with different sensors that are used to gather information about the terrain ahead of the helicopter. Synthetic vision systems are used to capture and classify sensor data and to visualize them on multifunctional displays or pilot's head up displays. This requires the input data to be a reliably classified into obstacles and ground. In this paper, we present a regularization-based terrain classifier. Regularization is a popular segmentation method in computer vision and used in active contours. For a real-time application scenario with LIDAR data, we developed an optimization that uses different levels of detail depending on the accuracy of the sensor. After a preprocessing step where points are removed that cannot be ground, the method fits a shape underneath the recorded point cloud. Once this shape is calculated, the points below this shape can be distinguished from elevated objects and are classified as ground. Finally, we demonstrate the quality of our segmentation approach by its application on operational flight recordings. This method builds a part of an entire synthetic vision processing chain, where the classified points are used to support the generation of a real-time synthetic view of the terrain as an assistance tool for the helicopter pilot.
Fluoride Intensifies Hypercaloric Diet-Induced ER Oxidative Stress and Alters Lipid Metabolism

The role of fluoride (F) in oxidative stress is well reported, but its effects on the lipid metabolism has not been completely explored Background Here, we evaluated the relationship of diet and F-induced oxidative stress to lipid metabolism in the liver of rats eating normocaloric or hypercaloric diets for two time periods (20 or 60 days). Methods Seventy-two 21-day-old Wistar rats were divided into 2 groups (n = 36) based on the type of diet they were eating; each of these groups was then further divided into another two groups (n = 18) based on the time periods of either 20 or 60 days, for a total of four groups. Each of these was divided into 3 subgroups (n = 6 animals/subgroup), dependent on the dose of F administered in the drinking water (0 mg/L(control), 15 mg/L or 50 mg/L). After the experimental period, blood samples and the liver were collected. Plasma samples were analyzed for HDL, cholesterol and triglycerides. Western blots were performed to probe for GRP78, Erp29, SOD2, Apo-E and SREBP in hepatic tissues. Results As expected,the expression of target proteins involved in oxidative stress increased in the F-treated groups, especially in liver tissue obtained from animals eating a hypercaloric diet. Most changes in the lipid levels and pathological conditions were seen earlier in the time period, at day 20. The morphometric analyses showed a reduction in steatosis in groups on ahypercaloric diet and treated with 50 mg F/L compared to the control, while no changes were obtained in normocaloric-fed rats. Accordingly, plasma TG was reduced in the F-treated group. The reduced expression of Apo-E in a time- and diet-dependent pattern may account for the particular decrease in steatosis in hypercaloric-fed F-treated rats. Conclusions These results suggest that F changes liver lipid homeostasis, possibly because of the induction of oxidative stress, which seems to be higher in animals fed hypercaloric diets.