Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparsity: Optimization Framework for Sparse Matrix Kernels

Sparse matrix–vector multiplication is an important computational kernel that performs poorly on most modern processors due to a low compute-to-memory ratio and irregular memory access patterns. Optimization is difficult because of the complexity of cache-based memory systems and because performance is highly dependent on the non-zero structure of the matrix. The SPARSITY system is designed to address these problems by allowing users to automatically build sparse matrix kernels that are tuned to their matrices and machines. SPARSITY combines traditional techniques such as loop transformations with data structure transformations and optimization heuristics that are specific to sparse matrices. It provides a novel framework for selecting optimization parameters, such as block size, using a combination of performance models and search. In this paper we discuss the optimization of two operations: a sparse matrix times a dense vector and a sparse matrix times a set of dense vectors. Our experience indicates that register level optimizations are effective for matrices arising in certain scientific simulations, in particular finite-element problems. Cache level optimizations are important when the vector used in multiplication is larger than the cache size, especially for matrices in which the non-zero structure is random. For applications involving multiple vectors, reorganizing the computation to perform the entire set of multiplications as a single operation produces significant speedups. We describe the different optimizations and parameter selection techniques and evaluate them on several machines using over 40 matrices taken from a broad set of application domains. Our results demonstrate speedups of up to 4× for the single vector case and up to 10× for the multiple vector case.
Effect of Functionalized MWCNTs with Surfactant and Coupling Agent on Properties of LDPE/POE Blends

The surfactant, sodium dodecylbenzenesulfonate (NaDDBS) and coupling agents, γ-aminopropyltriethoxy sliane (KH550) and isopropyl dioleic(dioctylphosphate) titanate (NDZ101) were used to treat multiwalled carbon nanotubes in this work. The effects of surface modification of multiwalled carbon nanotubes on crystallization behavior, mechanical properties, and electrical properties of low density polyethylene/polyolefin elastomer/multiwalled carbon nanotubes composites were studied. The results showed that NaDDBS, KH550, and NDZ101 had a favorable effect of improving the dispersion of multiwalled carbon nanotubes, but it cannot improve the interfacial interactionbetween multiwalled carbon nanotubes and the matrix. The improvement in dispersion favored the crystallization behavior and mechanical properties. Modified multiwalled carbon nanotubes had a better acceleration nucleation effect than raw multiwalled carbon nanotubes on low density polyethylene/polyolefin elastomer blends at low content (≤1 wt%). The tensile strength of low density polyethylene/polyolefin elastomer/multiwalled carbon nanotubes composites with modified multiwalled carbon nanotubes increased with lower multiwalled carbon nanotubes content (≤1 wt%), and KH550 and NDZ101 led low density polyethylene/polyolefin elastomer/multiwalled carbon nanotubes composites to possess a higher tensile strength than that of NaDDBS with 1 wt% content. NaDDBS, KH550, and NDZ101 had a minor influence on the dielectric properties of the composites and even caused a decrease in the dielectric loss of composites with 10 wt% multiwalled carbon nanotubes content.
Automatic Term Recognition Needs Multiple Evidence

In this paper we argue that the automatic term extraction procedure is an inherently multifactor process and the term extraction models needs to be based on multiple features including a specific type of a terminological resource under development. We proposed to use three types of features for extraction of two-word terms and showed that all these types of features are useful for term extraction. The set of features includes new features such as features extracted from an existing domain-specific thesaurus and features based on Internet search results. We studied the set of features for term extraction in two different domains and showed that the combination of several types of features considerably enhances the quality of the term extraction procedure. We found that for developing term extraction models in a specific domain, it is important to take into account some properties of the domain.
Characterization of Semiconductor Films Epitaxially Grown on Thin Metal Oxide Buffer Layers

Silicon and germanium films epitaxially grown on metal oxide buffer layers on Si(111) substrates are characterized by different X-ray techniques, transmission electron microscopy and Raman spectroscopy. Pr2O3 and Y2O3 or a combination of both is used as buffer material. X-ray pole figure measurements and grazing incident X-ray diffraction prove that epi-semiconductor layers can be grown single crystalline with exactly the same in-plane orientation as the Si(111) substrate. Epi-Ge layers show a small fraction (less than 0.5 vol. %) of so-called type B rotation twin regions located near the oxide-Ge interface. The main structural defects for both epi materials are micro twin lamellas lying in {111} planes 70° inclined to the wafer surface that may reach through the whole layer from the oxide interface to the surface. Furthermore, TEM confirms the existence of stacking faults and threading dislocations. X-ray grazing incident diffraction and Raman measurements show that epi-Ge layers on Pr2O3 buffer are nearly fully relaxed, while epi-Si layers on Y2O3/Pr2O3 double buffer are compressive strained depending on their own thickness and the thickness of the underlying Y2O3 layer. It is demonstrated that the epi-layer quality can be improved by post-deposition annealing procedures.
Developmental plasticity of CNS microglia

Microglia arise from CD45+ bone marrow precursors that colonize the fetal brain and play a key role in central nervous system inflammatory conditions. We report that parenchymal microglia are uncommitted myeloid progenitors of immature dendritic cells and macrophages by several criteria, including surface expression of “empty” class II MHC protein and their cysteine protease (cathepsin) profile. Microglia express receptors for stem cell factor and can be skewed toward more dendritic cell or macrophage-like profiles in response to the lineage growth factors granulocyte/macrophage colony-stimulating factor or macrophage colony-stimulating factor. Thus, in contrast to other organs, where terminally differentiated populations of resident dendritic cells and/or macrophages outnumber colonizing precursors, the majority of microglia within the brain remain in an undifferentiated state.
Strain Localization of Sand Based on a State-Dependent Critical State Model

A state-dependent critical state model is employed to analyze strain localization of sand in this paper. The sand model is developed based on the concept of the state-dependent critical state for sands, and an analysis of strain localization is performed on the drained plane strain tests of Hostun sand. The results show that the state-dependent critical state model is capable of simulating the effect of initial state on strain localization compatibly.
Improved Filter Selection Method for Filter Bank Common Spatial Pattern for EEG-Based BCI Systems

In this paper, we propose an improved filter selection method using Welch's t-test based on discriminative filter bank common spatial pattern (DFBCSP). Existing DFBCSP used the Fisher ratio in order to find out discriminative filters. However, the Fisher ratio can be used to know only comparative value of distinguishability but may not become a meaningful criterion to reject null hypothesis. As a reasonable alternative, we have introduced the Welch's t-test to find out not only contributory but also redundant filters used to classify features efficiently. Experimental results show that the classification accuracy increased by 1.28% on average when using the proposed filter selection method. 
Characterizing discussions in the Spanish Wikipedia

Wikipedia, as the largest online encyclopedia, is edited collaboratively by hundreds of users. The content in some articles can have dispute, giving rise to discussions which are registered in the related talk pages. In this paper, we propose an annotation schema for Spanish Wikipedia talk pages in order to determine the type of opinions expressed in them. We apply the annotation schema to a corpus that includes a collection of discussions about 148 topics drawn from 25 Spanish Wikipedia talk pages. We make the resulting dataset publicly available for download on github1. Furthermore, we train and evaluate supervised machine learning models to automatically identify the annotation labels. Linear Support Vector classifier (LinearSVC) performs better compared to other baseline models, and achieves an accuracy F1 = 0.71 in our experiments.
Role mining based on weights

Role mining from the existing permissions has been widely applied to aid the process of migrating to an RBAC system. While all permissions are treated evenly in previous approaches, none of the work has employed the weights of permissions in role mining to our knowledge, thus providing the motivation for this work. In this paper, we generalize this to the case where permissions are given weights to reflect their importance to the system. The weights can correspond to the property of operations, the sensitive degree of objects, and the attribute of users associated with permissions. To calculate the weight of permissions, we introduce the concept of similarity between both users and permissions, and use a similarity matrix to reinforce the similarity between permissions. Then we create a link between the reinforced similarity and the weight of permissions. We further propose a weighted role mining algorithm to generate roles based on weights. Experiments on performance study prove the superiority of the new algorithm.
Lipopolysaccharide-induced selective priming effects on tumor necrosis factor alpha and nitric oxide production in mouse peritoneal macrophages

Preculture of thioglycollate-elicited C3HeB/FeJ mouse peritoneal macrophages in vitro with subthreshold stimulatory concentrations of lipopolysaccharide (LPS) can induce hyporesponsiveness (desensitization) to both tumor necrosis factor alpha (TNF-alpha) and nitric oxide (NO) production when these cells are subsequently stimulated with 100 ng/ml of LPS. We have established, however, that the primary dose of LPS required for inducing downregulation of NO production is significantly lower than that required for inducing downregulation of TNF-alpha production. Further, when LPS-pretreated macrophages become refractory to subsequent LPS stimulation for NO production, the secondary LPS-stimulated TNF-alpha production is markedly enhanced, and vice versa. These results indicate that LPS- induced TNF-alpha and NO production by macrophages are differentially regulated, and that the observed desensitization process may not reflect a state in which macrophages are totally refractory to subsequent LPS stimulation. Rather, our data suggest that LPS- pretreated macrophages become selectively primed for differential responses to LPS. The LPS-induced selective priming effects are not restricted to LPS stimulation, but extend as well to stimuli such as zymosan, Staphylococcus aureus, and heat-killed Listeria monocytogenes.
Presence of platelet‐activating factor in rhesus (Macaca mulatta) spermatozoa

Abstract: Platelet‐activating factor [1‐O‐alkyl‐2‐acetyl‐sn‐glycero‐phosphocholine; PAF] is a unique signaling phospholipid which has been implicated in a number of biological activities (e.g., reproduction). PAF has been detected in the spermatozoa from a number of laboratory and domestic species, including, but not limited to, rabbit, bovine, and the mouse. The concentration of PAF is inversely related to human (Homo sapien) spermatozoal quality. Additionally, PAF levels are significantly higher in Bolivian squirrel monkey (Saimiri sciureus) spermatozoa obtained during the breeding season than spermatozoa obtained during the nonbreeding season. There are no reports on the presence of PAF in rhesus (Macaca mulatta) spermatozoa. Therefore, the primary objective of this study was to detect the presence of PAF in rhesus spermatozoa. A second objective was to determine if PAF spermatozoa levels differ between animals housed individually (single‐caged) versus free‐ranging (open corrals). Semen were collected from mature rhesus via electro‐ejaculation. Spermatozoa were washed free of ejaculatory plug and quick frozen in PBS. Endogenous lipids were extracted from thawed spermatozoa and ejaculatory plugs then assayed for the presence of PAF by [125I]‐radioimmunoassay. PAF was not detected in any ejaculatory plugs. PAF levels were significantly higher (P < 0.01) in spermatozoa obtained from free‐ranging males (mean: 1.16 pmol/106 spermatozoa) than males housed individually in single cage units (mean: 0.53 pmol/106 spermatozoa). PAF was present in rhesus spermatozoa. Additionally, PAF levels were higher in spermatozoa obtained from corral‐housed animals. Additional studies are warranted to elucidate the role of PAF in spermatozoa function.
A Linear Algebra Approach to Fast DNA Mixture Analysis Using GPUs

Analysis of DNA samples is an important tool in forensics, and the speed of analysis can impact investigations. Comparison of DNA sequences is based on the analysis of short tandem repeats (STRs), which are short DNA sequences of 2-5 base pairs. Current forensics approaches use 20 STR loci for analysis. The use of single nucleotide polymorphisms (SNPs) has utility for analysis of complex DNA mixtures. The use of tens of thousands of SNPs loci for analysis poses significant computational challenges because the forensic analysis scales by the product of the loci count and number of DNA samples to be analyzed. In this paper, we discuss the implementation of a DNA sequence comparison algorithm by re-casting the algorithm in terms of linear algebra primitives. By developing an overloaded matrix multiplication approach to DNA comparisons, we can leverage advances in GPU hardware and algoithms for dense matrix multiplication (DGEMM) to speed up DNA sample comparisons. We show that it is possible to compare 2048 unknown DNA samples with 20 million known samples in under 6 seconds using a NVIDIA K80 GPU.
Safety of subcutaneous adrenaline as prophylaxis against acute adverse reactions to anti-venom serum in snakebite.

OBJECTIVES To study the safety of low dose subcutaneous adrenaline given as prophylaxis against acute adverse reactions to anti-venom serum (AVS) in patients bitten by snakes. METHODS Patients admitted with snakebite envenoming who satisfied inclusion criteria were given 0.25 ml of 1:1000 adrenaline subcutaneously immediately before administration of AVS. They were observed for adverse effects, and pulse and blood pressure (BP) were monitored. RESULTS 51 patients [35 males, mean age 34.8 years (SD 14)] were included in the study. Adverse reactions to AVS occurred in 15 (29.4%) patients. There was one death from suspected cerebral haemorrhage, and 3 (5.9%) patients developed small haematomas at the subcutaneous injection site. There were no significant changes in mean pulse or BP following administration of subcutaneous adrenaline. CONCLUSIONS Low dose subcutaneous adrenaline did not cause significant changes in pulse rate or BP. Although the death was unlikely to be directly related to subcutaneous adrenaline, we suggest further studies on the safety of this prophylactic treatment before its routine use.
Is it difficult to concentrate during the 3rd trimester and postpartum?

OBJECTIVE The purpose of this study was to examine changes in women's directed attention, the ability to focus or concentrate, during the last trimester of pregnancy and during 1st week postpartum. DESIGN Pregnant women were tested at enrollment (during the 3rd trimester), at 37 weeks gestation, and during the 1st postpartum week for this descriptive, repeated measures study. SETTING Women were recruited from childbirth education classes in southwestern Michigan. PARTICIPANTS Fifty-seven women in their 3rd trimester of pregnancy. MAIN OUTCOME MEASURES Directed attention was measured objectively by the Digits Span Forward and Backward, Trailmaking A and B, and Category Matching tests. Subjective measures were the Attentional Function Index and Mental Effort in Tasks tests. RESULTS Participant means on the objective measures were within the normal range at all three time points. Some individuals, however, showed limitations in the capacity to direct their attention. Ability to use directed attention was lowest at enrollment and improved during the study, with statistically significant changes from Times 1 to 2 on several measures. Subjectively, the participants felt that they had moderately low competence on tasks that required directed attention throughout the study. CONCLUSIONS Women had the greatest difficulty focusing during the 3rd trimester. Some individuals had problems with tasks requiring directed attention at all three time points. Many participants perceived that their ability to pay attention was lower than normal. Some women may benefit from nursing interventions to reduce attentional demands during the 3rd trimester and early postpartum period.
ODOR: a microresonator-based high-performance low-cost router for optical networks-on-Chip

The performance of system-on-chip is determined not only by the performance of its functional units, but also by how efficiently they cooperate with one another. It is the on-chip communication architecture which determines the cooperation efficiency. Network-on-Chip (NoC) is introduced to improve communication bandwidth and power efficiency. However, traditional metallic interconnects consume significant amount of power to deliver large communication bandwidths. Optical NoCs are based on silicon optical interconnects with significant bandwidth and power advantages. Optical routers are the key enabling components of optical NoCs. This paper proposed a novel optical router architecture, ODOR, for optical NoCs based on XY routing algorithm. We compared ODOR with four other router architectures, and analyzed three aspects in details, including power consumption, optical power insertion loss, and the number of microresonators. The results show that ODOR has the lowest power consumption and losses and requires the least microresonators. ODOR has 40% less power consumption, 40% less loss, and 52% less microresonator than the full-connected crossbar. Furthermore, ODOR has a special feature which guarantees the maximum power to route a packet through a network to be a small constant number, regardless of the network size. The maximum power consumption is 0.96fJ/bit under current technology. We simulated a 6x6 2D mesh NoC based on ODOR, and showed the end-to-end delay and network throughput under different offered loads and packet sizes.
Robust Reconstruction of Interior Building Structures with Multiple Rooms under Clutter and Occlusions

We present a robust approach for reconstructing the architectural structure of complex indoor environments given a set of cluttered input scans. Our method first uses an efficient occlusion-aware process to extract planar patches as candidate walls, separating them from clutter and coping with missing data. Using a diffusion process to further increase its robustness, our algorithm is able to reconstruct a clean architectural model from the candidate walls. To our knowledge, this is the first indoor reconstruction method which goes beyond a binary classification and automatically recognizes different rooms as separate components. We demonstrate the validity of our approach by testing it on both synthetic models and real-world 3D scans of indoor environments.
NetLord: a scalable multi-tenant network architecture for virtualized datacenters

Providers of "Infrastructure-as-a-Service" need datacenter networks that support multi-tenancy, scale, and ease of operation, at low cost. Most existing network architectures cannot meet all of these needs simultaneously. In this paper we present NetLord, a novel multi-tenant network architecture. NetLord provides tenants with simple and flexible network abstractions, by fully and efficiently virtualizing the address space at both L2 and L3. NetLord can exploit inexpensive commodity equipment to scale the network to several thousands of tenants and millions of virtual machines. NetLord requires only a small amount of offline, one-time configuration. We implemented NetLord on a testbed, and demonstrated its scalability, while achieving order-of-magnitude goodput improvements over previous approaches.
Distributed Network Management with Secured Mobile Agent Support

Network computing is changing rapidly these days. The mobile agent technology invented to overcome the complexity resulting due to the increasing size of network components rises new network management schemes. Many prototype applications providing mobile agent capability have been proposed for being used in network management. E-commerce and information retrieval are some of them. The motive behind the agent mobility is that, it addresses some limitations faced by traditional centralized client-server architecture, which are mainly, minimizing bandwidth consumption, supporting network load balancing, enhancing scalability as well as flexibility, increase fault tolerance and solve problems caused by unreliable network connections. However, despite its benefits, mobile agent systems still pose security threats. In this paper we propose a mobile agent architecture that supports flexible and reliable interaction of autonomous components in a distributive network environment. We present a management scheme in a hierarchical level that provides to a user with a reliable and flexible global access to Internet/network information services. We further describe a protection mechanism to both agents and their hosting sites of execution called agent servers
Microbial diversity of Loki's Castle black smokers at the Arctic Mid‐Ocean Ridge

Hydrothermal vent systems harbor rich microbial communities ranging from aerobic mesophiles to anaerobic hyperthermophiles. Among these, members of the archaeal domain are prevalent in microbial communities in the most extreme environments, partly because of their temperature‐resistant and robust membrane lipids. In this study, we use geochemical and molecular microbiological methods to investigate the microbial diversity in black smoker chimneys from the newly discovered Loki's Castle hydrothermal vent field on the Arctic Mid‐Ocean Ridge (AMOR) with vent fluid temperatures of 310–320 °C and pH of 5.5. Archaeal glycerol dialkyl glycerol tetraether lipids (GDGTs) and H‐shaped GDGTs with 0–4 cyclopentane moieties were dominant in all sulfide samples and are most likely derived from both (hyper)thermophilic Euryarchaeota and Crenarchaeota. Crenarchaeol has been detected in low abundances in samples derived from the chimney exterior indicating the presence of Thaumarchaeota at lower ambient temperatures. Aquificales and members of the Epsilonproteobacteria were the dominant bacterial groups detected. Our observations based on the analysis of 16S rRNA genes and biomarker lipid analysis provide insight into microbial communities thriving within the porous sulfide structures of active and inactive deep‐sea hydrothermal vents. Microbial cycling of sulfur, hydrogen, and methane by archaea in the chimney interior and bacteria in the chimney exterior may be the prevailing biogeochemical processes in this system.