Miracle-dz/UniFAR-FTUs huggingface dataset:
Declarative Resilience

To protect multicores from soft-error perturbations, research has explored various resiliency schemes that provide high soft-error coverage. However, these schemes incur high performance and energy overheads. We observe that not all soft-error perturbations affect program correctness, and some soft-errors only affect program accuracy, i.e., the program completes with certain acceptable deviations from error free outcome. Thus, it is practical to improve processor efficiency by trading off resiliency overheads with program accuracy. This article proposes the idea of declarative resilience that selectively applies strong resiliency schemes for code regions that are crucial for program correctness (crucial code) and lightweight resiliency for code regions that are susceptible to program accuracy deviations as a result of soft-errors (non-crucial code). At the application level, crucial and non-crucial code is identified based on its impact on the program outcome. A cross-layer architecture enables efficient resilience along with holistic soft-error coverage. Only program accuracy is compromised in the worst-case scenario of a soft-error strike during non-crucial code execution. For a set of machine-learning and graph analytic benchmarks, declarative resilience reduces performance overhead over a state-of-the-art system that applies strong resiliency for all program code regions from ∼ 1.43× to ∼ 1.2×.
Two isoforms of cyclic GMP-dependent kinase-I exhibit distinct expression patterns in the adult mouse dorsal root ganglion

cGMP-dependent kinase-I (cGKI) is known to regulate spinal pain processing. This enzyme consists of two isoforms (cGKIα and cGKIβ) that show distinct substrate specificity and tissue distribution. It has long been believed that the α isoform is exclusively expressed in the adult dorsal root ganglion. The aim of the present study was to reexamine the expression of cGKI isoforms in the adult mouse dorsal root ganglion using isoform-specific cGKI antibodies whose specificities had been validated in the previous studies. Immunoblot and immunohistochemical analyses revealed the presence of both isoforms in the dorsal root ganglion. Moreover, cGKIα was found to be mainly expressed within the cytoplasm of small- to medium-sized peptidergic and nonpeptidegic C-fibers, whereas cGKIβ was located within the nuclei of a wide range of dorsal root ganglion neurons. In addition, glutamine synthetase-positive satellite glial cells expressed both isoforms to varying degrees. Finally, using an experimental model for neuropathic pain produced by L5 spinal nerve transection, we found that cGKIα expression was downregulated in the injured, but not in the uninjured, dorsal root ganglion. In contrast, cGKIβ expression was upregulated in both the injured and uninjured dorsal root ganglions. Also, injury-induced cGKIβ upregulation was found to occur in small-to-medium-diameter dorsal root ganglion neurons. These data thus demonstrate the existence of two differently distributed cGKI isoforms in the dorsal root ganglion, and may provide insight into the cellular and molecular mechanisms of pain.
Association between Carotid Wall Shear Rate and Arterial Stiffness in Patients with Hypertension and Atherosclerosis of Peripheral Arteries

Aim To evaluate carotid wall shear rate (WSR) in association with local and regional vascular stiffness in patients with hypertension (HTN) and atherosclerosis of peripheral arteries and to study the pattern of change of WSR in patients with HTN with increasing severity of peripheral artery atherosclerosis. Materials and Methods Study involved 133 patients with HTN, 65 men and 48 women, aged in average 57.9±10.8 years. All patients were divided into four groups in accordance with ultrasound morphologic classification of vessel wall. Duplex scanning of carotid and lower limb arteries was performed. Carotid-femoral (cfPWV) and carotid-radial (crPWV) pulse wave velocity (PWV) were measured. Local carotid stiffness was evaluated by carotid ultrasound. Results WSR of patients with plaques without and with hemodynamic disturbance was 416±128 s−1 and 405±117 s−1, respectively, which was significantly less than the WSR in patients with intact peripheral arteries – 546±112 s−1. Decreased carotid WSR was associated with increased crPVW, cfPWV, Peterson's elastic modulus, decreased distensibility, and distensibility coefficient. Conclusion In patients with HTN and atherosclerotic lesions of peripheral arteries, it is registered that the carotid WSR decreased with increasing severity of atherosclerosis. Decreased carotid WSR is associated with increased local carotid stiffness, regional vascular stiffness of muscular, and elastic vessels.
HIGH SCHOOL BIOLOGY TOPICS THAT PERCEIVED DIFFICULT BY UNDERGRADUATE STUDENTS

Biology is a science subject which on the one hand becomes a favorite subject for many students, but on the other hand has many topics that are considered difficult by many students. The aims of this study was to map the difficult topics of biology in senior high school based on the opinion of undergraduate students. This present study used survey research design. The participant of this study was the undergraduate student of class of 2017 majoring in Biology in one of the state universities in Malang. The instrument used in this study was a questionnaire of difficulty topics on high school biology subject and descriptive analysis was used as data analysis techniques. The result of this study was Genetics, Metabolism, and Cell Division were the first, second, and third most difficult topics in XII grade. The Immune System, the Coordination System, and the Plant Tissue were the first, second, and third most difficult topic in XI grade. Protista, Monera, and Virus were the first, second, and third most difficult topics in X grade. Genetics, Immune System, and Metabolism also selected into three topics of all grades that were considered most difficult by undergraduate students majoring in Biology. Biologi merupakan mata pelajaran sains yang di satu sisi menjadi mata pelajaran favorit bagi banyak siswa, namun di sisi lain memiliki banyak topik yang dianggap sulit oleh banyak siswa. Tujuan dari studi ini adalah untuk memetakan topik-topik biologi di Sekolah Menengah Atas (SMA) yang dianggap sulit berdasarkan pendapat mahasiswa-mahasiswa S1. Studi ini menggunakan desain penelitian survai. Partisipan pada studi ini adalah mahasiswa S1 angkatan 2017 Jurusan Biologi di salah satu universitas negeri di Malang. Instrumen yang digunakan pada studi ini adalah angket topik-topik sulit pada mata pelajaran Biologi SMA dan analisis deskriptif digunakan sebagai teknik analisis data. Hasil penelitian ini adalah Genetika, Metabolisme, dan Pembelahan Sel merupakan topik tersulit pertama, kedua, dan ketiga di kelas XII. Sistem Imun, Sistem Koordinasi, dan Jaringan Tumbuhan merupakan topik tersulit pertama, kedua dan ketiga dikelas XI. Protista, Monera, dan Virus merupakan topik tersulit pertama, kedua, dan ketiga di kelas X. Genetika, Sistem Imun, dan Metabolisme juga terpilih sebagai tiga topik dari seluruh kelas yang dianggap tersulit bagi mahasiswa Jurusan Biologi.
Global Disruption of α2A Adrenoceptor Barely Affects Bone Tissue but Minimizes the Detrimental Effects of Thyrotoxicosis on Cortical Bone

Evidence shows that sympathetic nervous system (SNS) activation inhibits bone formation and activates bone resorption leading to bone loss. Because thyroid hormone (TH) interacts with the SNS to control several physiological processes, we raised the hypothesis that this interaction also controls bone remodeling. We have previously shown that mice with double-gene inactivation of α2A- and -adrenoceptors (α2A/2C-AR−/−) present high bone mass (HBM) phenotype and resistance to thyrotoxicosis-induced osteopenia, which supports a TH-SNS interaction to control bone mass and suggests that it involves α2-AR signaling. Accordingly, we detected expression of α2A-AR, α2B-AR and α2C-AR in the skeleton, and that triiodothyronine (T3) modulates α2C-AR mRNA expression in the bone. Later, we found that mice with single-gene inactivation of α2C-AR (α2C-AR−/−) present low bone mass in the femur and HBM in the vertebra, but that both skeletal sites are resistant to TH-induce osteopenia, showing that the SNS actions occur in a skeletal site-dependent manner, and that thyrotoxicosis depends on α2C-AR signaling to promote bone loss. To further dissect the specific roles of α2-AR subtypes, in this study, we evaluated the skeletal phenotype of mice with single-gene inactivation of α2A-AR (α2A-AR−/−), and the effect of daily treatment with a supraphysiological dose of T3, for 4 or 12 weeks, on bone microarchitecture and bone resistance to fracture. Micro-computed tomographic (μCT) analysis revealed normal trabecular and cortical bone structure in the femur and vertebra of euthyroid α2A-AR−/− mice. Thyrotoxicosis was more detrimental to femoral trabecular bone in α2A-AR−/− than in WT mice, whereas this bone compartment had been previously shown to present resistance to thyrotoxicosis in α2C-AR−/− mice. Altogether these findings reveal that TH excess depends on α2C-AR signaling to negatively affect femoral trabecular bone. In contrast, thyrotoxicosis was more deleterious to femoral and vertebral cortical bone in WT than in α2A-AR−/− mice, suggesting that α2A-AR signaling contributes to TH actions on cortical bone. These findings further support a TH-SNS interaction to control bone physiology, and suggest that α2A-AR and α2C-AR signaling pathways have key roles in the mechanisms through which thyrotoxicosis promotes its detrimental effects on bone remodeling, structure and resistance to fracture.
Beyond Halo and Wedge: visualizing out-of-view objects on head-mounted virtual and augmented reality devices

Head-mounted devices (HMDs) for Virtual and Augmented Reality (VR/AR) enable us to alter our visual perception of the world. However, current devices suffer from a limited field of view (FOV), which becomes problematic when users need to locate out of view objects (e.g., locating points-of-interest during sightseeing). To address this, we developed and evaluated in two studies HaloVR, WedgeVR, HaloAR and WedgeAR, which are inspired by usable 2D off-screen object visualization techniques (Halo, Wedge). While our techniques resulted in overall high usability, we found the choice of AR or VR impacts mean search time (VR: 2.25s, AR: 3.92s) and mean direction estimation error (VR: 21.85°, AR: 32.91°). Moreover, while adding more out-of-view objects significantly affects search time across VR and AR, direction estimation performance remains unaffected. We provide implications and discuss the challenges of designing for VR and AR HMDs.
Improving text relatedness by incorporating phrase relatedness with word relatedness

Text is composed of words and phrases. In the bag‐of‐words model, phrases in text are split into words. This may discard the semantics of phrases, which, in turn, may give an inconsistent relatedness score between 2 texts. Our objective is to apply phrase relatedness in conjunction with word relatedness on the text relatedness task to improve text relatedness performance. We adopt 2 existing word relatedness measures based on Google n‐gram and Global Vectors for Word Representation, respectively, and incorporate them differently with an existing Google n‐gram–based phrase relatedness method to compute text relatedness. The combination of Google n‐gram–based word and phrase relatedness performs better than Google n‐gram–based word relatedness alone, by achieving the higher weighted mean of Pearson's r, ie, 0.639 and 0.619, respectively, on the 14 data sets from the series of Semantic Evaluation workshops SemEval‐2012, SemEval‐2013, and SemEval‐2015. Similarly, the combination of GloVe‐based word relatedness and Google n‐gram–based phrase relatedness performs better than GloVe‐based word relatedness alone, by achieving the higher weighted mean of Pearson's r, ie, 0.619 and 0.605, respectively, on the same 14 data sets. On the SemEval‐2012, SemEval‐2013, and SemEval‐2015 data sets, the text relatedness results obtained from the combination of Google n‐gram–based word and phrase relatedness ranked 24, 3, and 31 out of 89, 90, and 73 text relatedness systems, respectively.
PENGARUH MODEL PEMBELAJARAN BERBASIS MASALAH (PBM) DALAM SETTING PEMBELAJARAN KOOPERATIF TIPE TGT DAN GI TERHADAP KETERAMPILAN BERPIKIR KRITIS DAN HASIL BELAJAR KIMIA PESERTA DIDIK SMAN 1 AIKMEL

This study aims to describe the differences in critical thinking skills and chemistry learning achievement between learners who follow the model of problem-based learning (PBL) in cooperative learning settings TGT and GI at the rate of material reaction. The research is a quasi-experimental research design with pretest-posttest non equivalent control group designe with sample XI IPA 1 and XI IPA 2 are determined by random selection technique based on similarity mean value of daily tests I. Experiential learning and learner response is estimated to affect more significant learning achievement in the classroom PBM setting GI as evidenced by the average N-Gain learning outcomes in the classroom PBM setting GI of 0.43 and the average N-Gain learning achievement in the classroom PBM setting TGT of 0.32. The differences are also evidenced by the results of the hypothesis test showed a significance value of 0.002 (p <0.05). While based on the calculation of the average critical thinking skills in mind that PBM setting TGT has a more significant effect than the PBM GI settings as evidenced by the difference in the value of critical thinking skills after learning process (posttest) and prior to the learning process (pretest) on PBM classroom setting TGT and PBM GI settings are respectively 19.93 and 14.42. While the test is based on differences in critical thinking skills, it is known that there are differences between classes of critical thinking skills PBM settings TGT and PBM settings GI as evidenced by the significant value of 0.018 (p <0.05). Keywords: PBM setting TGT, PBM setting GI, critical thinking skills, learning achievement of chemistry.
Molecular Characterization of Newcastle Disease Virus from Backyard Poultry Farms and Live Bird Markets in Kenya

Newcastle disease (ND) is a serious disease of poultry that causes significant economic losses. Despite rampant ND outbreaks that occur annually in Kenya, the information about the NDV circulating in Kenya is still scarce. We report the first countrywide study of NDV in Kenya. Our study is aimed at evaluating the genetic characteristics of Newcastle disease viruses obtained from backyard poultry in farms and live bird markets in different regions of Kenya. We sequenced and analyzed fusion (F) protein gene, including the cleavage site, of the obtained viruses. We aligned and compared study sequences with representative NDV of different genotypes from GenBank. The fusion protein cleavage site of all the study sequences had the motif 112RRQKRFV118 indicating their velogenic nature. Phylogenetic analysis revealed that the NDV from various sites in Kenya was highly similar genetically and that it clustered together with NDV of genotype V. The study samples were 96% similar to previous Ugandan and Kenyan viruses grouped in subgenotype Vd This study points to possible circulation of NDV of similar genetic characteristics between backyard poultry farms and live bird markets in Kenya. The study also suggests the possible spread of velogenic NDV between Kenya and Uganda possibly through cross-border live bird trade. Our study provides baseline information on the genetic characteristics of NDV circulating in the Kenyan poultry population. This highlights the need for the ND control programmes to place more stringent measures on cross-border trade of live bird markets and poultry products to prevent the introduction of new strains of NDV that would otherwise be more difficult to control.
Wide Activation for Efficient and Accurate Image Super-Resolution

In this report we demonstrate that with same parameters and computational budgets, models with wider features before ReLU activation have significantly better performance for single image super-resolution (SISR). The resulted SR residual network has a slim identity mapping pathway with wider (\(2\times\) to \(4\times\)) channels before activation in each residual block. To further widen activation (\(6\times\) to \(9\times\)) without computational overhead, we introduce linear low-rank convolution into SR networks and achieve even better accuracy-efficiency tradeoffs. In addition, compared with batch normalization or no normalization, we find training with weight normalization leads to better accuracy for deep super-resolution networks. Our proposed SR network \textit{WDSR} achieves better results on large-scale DIV2K image super-resolution benchmark in terms of PSNR with same or lower computational complexity. Based on WDSR, our method also won 1st places in NTIRE 2018 Challenge on Single Image Super-Resolution in all three realistic tracks. Experiments and ablation studies support the importance of wide activation for image super-resolution. Code is released at: this https URL
Comparative mitochondrial genomic analyses of three chemosynthetic vesicomyid clams from deep‐sea habitats

Abstract Vesicomyid clams of the subfamily Pliocardinae are among the dominant chemosymbiotic bivalves found in sulfide‐rich deep‐sea habitats. Plastic morphologies and present molecular data could not resolve taxonomic uncertainties. The complete mitochondrial (mt) genomes will provide more data for comparative studies on molecular phylogeny and systematics of this taxonomically uncertain group, and help to clarify generic classifications. In this study, we analyze the features and evolutionary dynamics of mt genomes from three Archivesica species (Archivesica sp., Ar. gigas and Ar. pacifica) pertaining to subfamily Pliocardinae. Sequence coverage is nearly complete for the three newly sequenced mt genomes, with only the control region and some tRNA genes missing. Gene content, base composition, and codon usage are highly conserved in these pliocardiin species. Comparative analysis revealed the vesicomyid have a relatively lower ratio of Ka/Ks, and all 13 protein‐coding genes (PGCs) are under strong purifying selection with a ratio of Ka/Ks far lower than one. Minimal changes in gene arrangement among vesicomyid species are due to the translocation trnaG in Isorropodon fossajaponicum. Additional tRNA genes were detected between trnaG and nad2 in Abyssogena mariana (trnaL3), Ab. phaseoliformis (trnaS3), and Phreagena okutanii (trnaM2), and display high similarity to other pliocardiin sequences at the same location. Single base insertion in multiple sites of this location could result in new tRNA genes, suggesting a possible tRNA arising from nongeneic sequence. Phylogenetic analysis based on 12 PCGs (excluding atp8) supports the monophyly of Pliocardiinae. These nearly complete mitogenomes provide relevant data for further comparative studies on molecular phylogeny and systematics of this taxonomically uncertain group of chemosymbiotic bivalves.
ERS-TOOL: hybrid model for software requirements elicitation in Spanish language

The nature of the software requirements is subjective and varied. For this reason the level of complexity increases according to the volume, especially when the requirements are made in a natural language. Therefore obtain quality software requirements that are understandable and unambiguous in the Spanish language becomes a necessity. First, a controlled syntax was proposed to express software requirements taking into account the static and dynamic behavior among the different actors of the system, where the expressions are elaborated based on the Backus-Naur form (BNF). Then a set of writing rules were adapted to the Spanish language, creating four additional rules. Finally, the results of the case study had high accuracy in understandability; also the ambiguity of requirements elicitation was reduced. In addition to improving the development of software engineering activities, since there are no tools available for the elicitation of software requirements with language Spanish.
Deep learning: Computational aspects

In this article, we review computational aspects of deep learning (DL). DL uses network architectures consisting of hierarchical layers of latent variables to construct predictors for high‐dimensional input–output models. Training a DL architecture is computationally intensive, and efficient linear algebra library is the key for training and inference. Stochastic gradient descent (SGD) optimization and batch sampling are used to learn from massive datasets.
Deep Stochastic Attraction and Repulsion Embedding for Image Based Localization

This paper tackles the problem of large-scale image-based localization where the geographical location at which a query image was taken is estimated by retrieving geo-tagged reference images depicting the same place from a large database. For this problem, an important and yet under-researched issue is how to learn discriminative image representations that are best tailored to the task of geo-localization. Aiming to find a novel image representation having higher location-discriminating power, this paper presents the following contributions: 1) we represent a place (location) as a set of exemplar images depicting the same landmarks, instead of some pre-defined geographic locations by partitioning the world; 2) we advocate the use of competitive learning among places, directly via feature embeddings, aiming to maximize similarities among intra-class images while minimizing similarities among inter-class images. This represents a significant departure from the state-of-the-art IBL methods using triplet ranking loss, which only enforces intra-place visual similarities are bigger than inter-place ones; 3) we propose a new Stochastic Attraction and Repulsion Embedding (SARE) loss function to facilitate the competitive learning. Our SARE loss is easy to implement and pluggable to any Convolutional Neural Network. Experiments show that the method improves localization performance on standard benchmarks by a large margin.