Miracle-dz/UniFAR-FTUs huggingface dataset:
Beta Pictoris Debris Disk is a Proto-planetary Disk

The debris disk around the star Beta Pictoris is a proto-planetary disk which was caused by a collision of two or more aging stars. Beta Pictoris is shown to possess a large debris disk which glows in the infared. [1] It has been hypothesized that this debris disk is not evidence for the formation of new stars/exoplanets [2] but of the destruction of older stars colliding with each other, thus taking up new orbits around the proto-star Beta Pictoris, which is a very young planet, and leaving a very large debris field similar to our own asteroid belt. [3] The larger stars that collided will stabilize after losing incredible amounts of material and forming rings (like Saturn, Jupiter, Uranus, Neptune). The smaller much more traveled stars will stabilize and take up orbit around the younger stars and form round, undifferentiated objects similar to the moon Callisto [4] , or the many other arrangements of moons around Saturn or Jupiter and smaller objects such as Ceres. This could also explain why they do not possess iron cores but are mostly volatiles such as water, ammonia, methane and sulfur dioxide which have a relatively low equilibrium condensation as opposed to refractory elements and molecules which have a much higher boiling point, and play a large part in the differentiation process. [5] It should also be understood by the reader that the establishment is very confused as to the nature of the cosmos. They have proto-planetary disk, debris disk and circumstellar disk all different objects, when via Ockham’s razor they are the exact same objects caused by the exact same mechanisms, world collisions. [6] The idea that an older star similar to Earth could enter the solar system at random at any time from somewhere else in the galaxy and smack into the Earth is frightening to the God/Big Bang creationists. As a matter of fact it would not even require a collision the influence from another star entering the solar system would disrupt the orbital parameters of the Earth and cause an extinction level event without even touching the Earth.
Precoded MIMO Systems With Nonbinary LDPC Codes and Many-to-One Mapping

A precoding design is proposed for multiple-input multiple-output (MIMO) systems utilizing nonbinary low-density parity check (NB-LDPC) codes and many-to-one mapping. When a high-order modulation scheme is used, many-to-one mapping converts a group of low-order Galois field (GF) coded symbols into one modulated MIMO symbol vector. In contrast, one-to-one mapping maps a high-order modulation symbol directly from one high-order GF coded symbol. With the help of an interleaver between the NB-LDPC encoder and the GF to MIMO symbol mapper, the many-to-one mapping enables turbo receiver and reduces the computational complexity by more than 95%. The proposed MIMO precoders enhance the error-rate performance of the many-to-one NB-LDPC MIMO system, especially in terms of reducing the error floor and improving the waterfall region. The proposed precoder design modifies the approach that suboptimally maximizes the minimal Euclidean distance between the received MIMO symbols. Simulation results show that the proposed precoders enhance the robustness of the precoder design and reduce the inner and outer iterations of the turbo receiver.
Multicategory Nets of Single-Layer Perceptrons: Complexity and Sample-Size Issues

The standard cost function of multicategory single-layer perceptrons (SLPs) does not minimize the classification error rate. In order to reduce classification error, it is necessary to: 1) refuse the traditional cost function, 2) obtain near to optimal pairwise linear classifiers by specially organized SLP training and optimal stopping, and 3) fuse their decisions properly. To obtain better classification in unbalanced training set situations, we introduce the unbalance correcting term. It was found that fusion based on the Kulback-Leibler (K-L) distance and the Wu-Lin-Weng (WLW) method result in approximately the same performance in situations where sample sizes are relatively small. The explanation for this observation is by theoretically known verity that an excessive minimization of inexact criteria becomes harmful at times. Comprehensive comparative investigations of six real-world pattern recognition (PR) problems demonstrated that employment of SLP-based pairwise classifiers is comparable and as often as not outperforming the linear support vector (SV) classifiers in moderate dimensional situations. The colored noise injection used to design pseudovalidation sets proves to be a powerful tool for facilitating finite sample problems in moderate-dimensional PR tasks.
Robotic wheelchair commanded by SSVEP, motor imagery and word generation

This work presents a robotic wheelchair that can be commanded by a Brain Computer Interface (BCI) through Steady-State Visual Evoked Potential (SSVEP), Motor Imagery and Word Generation. When using SSVEP, a statistical test is used to extract the evoked response and a decision tree is used to discriminate the stimulus frequency, allowing volunteers to online operate the BCI, with hit rates varying from 60% to 100%, and guide a robotic wheelchair through an indoor environment. When using motor imagery and word generation, three mental task are used: imagination of left or right hand, and imagination of generation of words starting with the same random letter. Linear Discriminant Analysis is used to recognize the mental tasks, and the feature extraction uses Power Spectral Density. The choice of EEG channel and frequency uses the Kullback-Leibler symmetric divergence and a reclassification model is proposed to stabilize the classifier.
Role of Lactobacillus reuteri in Human Health and Diseases

Lactobacillus reuteri (L. reuteri) is a well-studied probiotic bacterium that can colonize a large number of mammals. In humans, L. reuteri is found in different body sites, including the gastrointestinal tract, urinary tract, skin, and breast milk. The abundance of L. reuteri varies among different individuals. Several beneficial effects of L. reuteri have been noted. First, L. reuteri can produce antimicrobial molecules, such as organic acids, ethanol, and reuterin. Due to its antimicrobial activity, L. reuteri is able to inhibit the colonization of pathogenic microbes and remodel the commensal microbiota composition in the host. Second, L. reuteri can benefit the host immune system. For instance, some L. reuteri strains can reduce the production of pro-inflammatory cytokines while promoting regulatory T cell development and function. Third, bearing the ability to strengthen the intestinal barrier, the colonization of L. reuteri may decrease the microbial translocation from the gut lumen to the tissues. Microbial translocation across the intestinal epithelium has been hypothesized as an initiator of inflammation. Therefore, inflammatory diseases, including those located in the gut as well as in remote tissues, may be ameliorated by increasing the colonization of L. reuteri. Notably, the decrease in the abundance of L. reuteri in humans in the past decades is correlated with an increase in the incidences of inflammatory diseases over the same period of time. Direct supplementation or prebiotic modulation of L. reuteri may be an attractive preventive and/or therapeutic avenue against inflammatory diseases.
Preparation and Properties of a Novel High-Strength Foam

A novel high-strength foam (PSA foam) was prepared by adding foaming agent in silicon-containing arylacetylene (PSA) via free heat foaming. The dispersion of foaming agent was observed by Scanning Electron Microscopy-Energy Disperse Spectroscopy (SEM-EDS) and the result indicated that the foaming agent was dispersed uniformly in PSA. The microstructure of the PSA foams prepared with different foam temperatures were characterized by SEM and the results showed the PSA foam had uniform pores when the foaming temperature was 165°C. Compressive strength of the PSA foam could reach 10.3 MPa. Furthermore, PSA foam possessed excellent thermal stability, dimensional stability and heat insulation performance: char residue reached 92.3% at 800°C under nitrogen atmosphere; the highest coefficient of thermal expansion was 83*10-6/K; the thermal conductivity was 0.0724 W/(m•K).
Low-Level Environmental Lead Exposure and Children’s Intellectual Function: An International Pooled Analysis

Lead is a confirmed neurotoxin, but questions remain about lead-associated intellectual deficits at blood lead levels < 10 μg/dL and whether lower exposures are, for a given change in exposure, associated with greater deficits. The objective of this study was to examine the association of intelligence test scores and blood lead concentration, especially for children who had maximal measured blood lead levels < 10 μg/dL. We examined data collected from 1,333 children who participated in seven international population-based longitudinal cohort studies, followed from birth or infancy until 5–10 years of age. The full-scale IQ score was the primary outcome measure. The geometric mean blood lead concentration of the children peaked at 17.8 μg/dL and declined to 9.4 μg/dL by 5–7 years of age; 244 (18%) children had a maximal blood lead concentration < 10 μg/dL, and 103 (8%) had a maximal blood lead concentration < 7.5 μg/dL. After adjustment for covariates, we found an inverse relationship between blood lead concentration and IQ score. Using a log-linear model, we found a 6.9 IQ point decrement [95% confidence interval (CI), 4.2–9.4] associated with an increase in concurrent blood lead levels from 2.4 to 30 μg/dL. The estimated IQ point decrements associated with an increase in blood lead from 2.4 to 10 μg/dL, 10 to 20 μg/dL, and 20 to 30 μg/dL were 3.9 (95% CI, 2.4–5.3), 1.9 (95% CI, 1.2–2.6), and 1.1 (95% CI, 0.7–1.5), respectively. For a given increase in blood lead, the lead-associated intellectual decrement for children with a maximal blood lead level < 7.5 μg/dL was significantly greater than that observed for those with a maximal blood lead level ≥7.5 μg/dL (p = 0.015). We conclude that environmental lead exposure in children who have maximal blood lead levels < 7.5 μg/dL is associated with intellectual deficits.
Assumptions made when preparing drug exposure data for analysis have an impact on results: An unreported step in pharmacoepidemiology studies

Real‐world data for observational research commonly require formatting and cleaning prior to analysis. Data preparation steps are rarely reported adequately and are likely to vary between research groups. Variation in methodology could potentially affect study outcomes. This study aimed to develop a framework to define and document drug data preparation and to examine the impact of different assumptions on results.
CWLP: coordinated warp scheduling and locality-protected cache allocation on GPUs

As we approach the exascale era in supercomputing, designing a balanced computer system with a powerful computing ability and low power requirements has becoming increasingly important. The graphics processing unit (GPU) is an accelerator used widely in most of recent supercomputers. It adopts a large number of threads to hide a long latency with a high energy efficiency. In contrast to their powerful computing ability, GPUs have only a few megabytes of fast on-chip memory storage per streaming multiprocessor (SM). The GPU cache is inefficient due to a mismatch between the throughput-oriented execution model and cache hierarchy design. At the same time, current GPUs fail to handle burst-mode long-access latency due to GPU’s poor warp scheduling method. Thus, benefits of GPU’s high computing ability are reduced dramatically by the poor cache management and warp scheduling methods, which limit the system performance and energy efficiency. In this paper, we put forward a coordinated warp scheduling and locality-protected (CWLP) cache allocation scheme to make full use of data locality and hide latency. We first present a locality-protected cache allocation method based on the instruction program counter (LPC) to promote cache performance. Specifically, we use a PC-based locality detector to collect the reuse information of each cache line and employ a prioritised cache allocation unit (PCAU) which coordinates the data reuse information with the time-stamp information to evict the lines with the least reuse possibility. Moreover, the locality information is used by the warp scheduler to create an intelligent warp reordering scheme to capture locality and hide latency. Simulation results show that CWLP provides a speedup up to 19.8% and an average improvement of 8.8% over the baseline methods.
Sparse representation via ℓ1-minimization for underdetermined systems in classification of tumors with gene expression data

The development of cancer diagnosis models and cancer discovery from DNA microarray data are of great interest in bioinformatics and medicine. In pattern recognition and machine learning, a classification problem refers to finding an algorithm for assigning a given input data into one of several categories. Many natural signals are sparse or compressible in the sense that they have short representations when expressed in a suitable basis. Motivated by the recent successful algorithm developments for sparse signal recovery, we apply the selective nature of sparse representation to perform the above mentioned classification. In order to find such sparse representation we implement an ℓ1-minimization algorithm. This methodology overcomes the lack of robustness with respect to outliers. In contrast to other classification algorithms, no model selection dependency is involved. The minimization algorithm is a convex relaxation-like that has been proven to efficiently recover sparse signals. To study its performance, the proposed method is applied to six tumor gene expression datasets and numerically compared with various support vector machine methods (SVM). The numerical results show that the ℓ1-minimization algorithm proposed performs at least comparably and often better than SVMs.
Actively controlling the topological transition of dispersion based on electrically controllable metamaterials

Topological transition of the iso-frequency contour (IFC) from a closed ellipsoid to an open hyperboloid, will provide unique capabilities for controlling the propagation of light. However, the ability to actively tune these effects remains elusive and the related experimental observations are highly desirable. Here, tunable electric IFC in periodic structure which is composed of graphene/dielectric multilayers is investigated by tuning the chemical potential of graphene layer. Specially, we present the actively controlled transportation in two kinds of anisotropic zero-index media containing PEC/PMC impurities. At last, by adding variable capacitance diodes into two-dimensional transmission-line system, we present the experimental demonstration of the actively controlled magnetic topological transition of dispersion based on electrically controllable metamaterials. With the increase of voltage, we measure the different emission patterns from a point source inside the structure and observe the phase-transition process of IFCs. The realization of actively tuned topological transition will opens up a new avenue in the dynamical control of metamaterials.
Change-of-state determination to recognize mobility activities using a BlackBerry smartphone

A Wearable Mobility Monitoring System (WMMS) can be a useful tool for rehabilitation decision-making. This paper presents preliminary design and evaluation of a WMMS proof-of-concept system. Software was developed for the BlackBerry 9550, using the integrated three axes accelerometer, GPS, video camera, and timer to identify mobility changes-of-state (CoS) between static activities, walking-related activities, taking an elevator, bathroom activities, working in the kitchen, and meal preparation (five able-bodied subjects). This pilot project provides insight into new algorithms and features that recognize CoS and activities in real-time. Following features extraction from the sensor data, two decision trees were used to distinguish the CoS and activities. Real-time CoS identification triggered BlackBerry video recording for improved mobility context analysis during post-processing.
Classification of Alzheimer's Disease from structural MRI using sparse logistic regression with optional spatial regularization

In this paper, we apply Sparse Logistic Regression Classifiers to the classification of 69 Alzheimer's Disease and 60 normal control subjects based on voxel-wise grey matter volumes derived from structural MRI. Methods such as standard logistic regression cannot be used in such problems because of the large number of voxels in comparison to the number of training subjects. Sparse Logistic Regression (SLR) addresses this issue by incorporating a sparsity penalty into the log-likelihood, which effects an automatic feature selection within the classification framework. We apply two different formulations of sparse logistic regression and compare their classification accuracy with that of Penalized Logistic Regression (PLR) and Maximum uncertainty Linear Discriminant Analysis (MLDA). In the first approach, we use the original formulation of SLR in which correlated voxels are forced to have similar weights. In the second approach we use a spatially regularized formulation, SRSLR, to force the discriminating vector to be spatially smooth when viewed as an image. Evaluation of the methods using cross-validation shows similar classification accuracies for SLR and SRSLR, with both performing better than PLR and MLDA. In addition, SRSLR produced classifiers that were spatially smoother than those produced by SLR, which may better reflect the regional effects of Alzheimer's Disease.
Identification and genetic characterization of porcine circovirus type 3 in China

Summary A novel circovirus called porcine circovirus type 3 (PCV3) was recently reported to exist in the USA. This circovirus is associated with porcine dermatitis, nephropathy syndrome and reproductive failure. This study reports on the first identification, widely epidemic, different phylogenetic clusters, potential role in sow reproductive failure and possible origins of PCV3 in China.
Productivity in Agile Software Development: A Systematic Mapping Study

Many organizations dedicated to software development have adopted agile principles with the aim of increasing their productivity. Agile Software Development (ASD) encourages the delivery of working software frequently; however, there are many factors that affect productivity in that context. The objective of this paper is to analyze the research works about productivity in ASD to identify: the factors that affect productivity, the most used research methods, the most studied productivity levels, the concepts related to productivity, the most studied agile methodologies, and the use of productivity metrics in ASD. To perform such analysis, we conducted a Systematic Mapping Study (SMS) in which we included 25 primary studies. As result of the SMS, we identified the main factors that affect productivity in ASD and the context in which the included primary studies were performed. We found that Case Study was the most used research method, and interviews and questionnaires are widely used as data collection methods. We found that most of the reported factors affecting productivity in ASD are related to agile teams, and although quality should be related to productivity, it was not considered in all studies.
The potential distribution of the Russian wheat aphid (Diuraphis noxia): an updated distribution model including irrigation improves model fit for predicting potential spread

Abstract Diuraphis noxia (Kurdjumov), Russian wheat aphid, is one of the world's most invasive and economically important agricultural pests of wheat and barley. In May 2016, it was found for the first time in Australia, with further sampling confirming it was widespread throughout south-eastern regions. Russian wheat aphid is not yet present in New Zealand. The impacts of this pest if it establishes in New Zealand, could result in serious control problems in wheat- and barley-growing regions. To evaluate whether D. noxia could establish populations in New Zealand we used the climate modelling software CLIMEX to locate where potential viable populations might occur. We re-parameterised the existing CLIMEX model by Hughes and Maywald (1990) by improving the model fit using currently known distribution records of D. noxia, and we also considered the role of irrigation into the potential spread of this invasive insect. The updated model now fits the current known distribution better than the previous Hughes and Maywald CLIMEX model, particularly in temperate and Mediterranean areas in Australia and Europe; and in more semi-arid areas in north-western China and Middle Eastern countries. Our model also highlights new climatically suitable areas for the establishment of D. noxia, not previously reported, including parts of France, the UK and New Zealand. Our results suggest that, when suitable host plants are present, Russian wheat aphid could establish in these regions. The new CLIMEX projections in the present study are useful tools to inform risk assessments and target surveillance and monitoring efforts for identifying susceptible areas to invasion by Russian wheat aphid.
Architectural Decisions in Commercial Aircraft from the DC-3 to the 787

The volume of passenger air travel has increased rapidly since the first commercially viable passenger aircraft, the DC-3. Over this period, commercial aircraft increasingly appear to have consolidated around a dominant architecture. That is to say, aircraft designers have increasingly made the same architectural decisions (categorical choices such as high wing or low wing), while realizing performance gains in component technologies rather than from major architectural innovations. To quantify the assertion that a dominant architecture has emerged, in this paper, architectural decisions over time are analyzed, finding a decrease in variation of these decisions in a data set of 157 historical aircraft architectures. An architectural performance metric is defined based on passenger-carrying efficiency, technical performance, and market value, observing that, in parallel with architectural consolidation, there has been a twofold increase in average performance since the inception of the DC-3. However, the p.
Functionally graded bio-ceramic reinforced PVA hydrogel composites for knee joint artificial cartilages

Research progress in materials science for bio-based materials for cartilage repair or supportive to host tissue has become a fashionable, worldwide. Few efforts in biomedical engineering has attempted in the development of newer biomaterials successfully. Bio ceramics, a class of materials been used in particulate form as a reinforcement with polymers those ensure its biocompatibility. Every artificial biomedical system has to meet the minimum in Vitro requirements for successful application. Equally the biological behavior of normal and diseased tissues is also essential to understand the artificial systems to human body.