Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Scalability of Vehicle-to-Vehicle Communication with Prediction-Based STDMA

Self-organized TDMA (STDMA) has been proposed as a medium access control (MAC) protocol for Vehicle-to-Vehicle (V2V) communication. Although it avoids the unbounded channel access delay faced by other CSMA-based protocols, the reliability in high traffic density is still unsatisfactory for critical road safety applications. This paper introduces an enhanced prediction-based STDMA protocol which utilizes the spatial information available in the messages exchanged for road safety applications. Thus it allocates the radio resources more efficiently and minimizes the mutual interference among different vehicles. The results show that the prediction-based STDMA offers a significant improvement in the scalability and coverage of the V2V communication system for road safety applications with strict reliability requirement. The performance enhancement of the proposed MAC protocol is achieved without adding much complexity to the existing STDMA and it has considerable potential for further improvement.
Target Tracking with Pairwise Uncertainty in Wireless Sensor Networks: Qualitatively and Quantitatively

Ubiquitous uncertainty has great impacts on target tracking accuracy in wireless sensor networks (WSNs). This paper focuses on the uncertainty of pair wise sensor nodes, and analyzes it on unreliable samplings of sensors as well as the uncertain relationship between location points and expected sensing results, qualitatively and quantitatively. The sampling vector, which reflects sensing information, is constructed by multiple grouping samplings, while the tracking area can be divided into patches which are assigned to specific signature vectors. Two target tracking strategies are proposed by matching the two vectors, from the qualitative and quantitative aspect, respectively. Results show that both methods can achieve high tracking reliability and satisfy tracking accuracy and robustness for the uncertainty caused by in-the-field factors.
Semi-dynamic and dynamic flip-flops with embedded logic

Describes a family of semi-dynamic and dynamic edge-triggered flip-flops to be used with static and dynamic circuits, respectively. The flip-flops provide both short latency and the capability of incorporating logic functions with minimum delay penalty, properties which make them very attractive for high-performance microprocessor design. The circuits described are used in the UltraSPARC-III microprocessor.
Effect of hyperoxia, hypercapnia, and hypoxia on cerebral interstitial oxygen tension and cerebral blood flow

The assessment of cerebral interstitial oxygen tension (piO2) can provide valuable information regarding cerebrovascular physiology and brain function. Compartment‐specific cerebral piO2 was measured by 19F NMR following the infusion of an oxygen‐sensitive perfluorocarbon directly into the interstitial and ventricular space of the in vivo rat brain. 19F T1 measurements were made and cerebral piO2 were obtained through in vitro calibrations. The effects of graded hyperoxia, hypercapnia, and hypoxia on piO2 and cerebral blood flow (CBF) were investigated. Under normoxia (arterial pO2 ∼ 120 mm Hg), piO2 was ∼30 mm Hg and jugular venous pO2 was ∼50 mm Hg. During hyperoxia (arterial pO2 = 90–300 mm Hg), piO2 increased linearly with the arterial pO2. Following hypercapnia (arterial pCO2 = 20–60 mm Hg), the piO2 increased sigmoidally with increasing CBF. With hypoxia (arterial pO2 = 30–40 mm Hg), CBF increased ∼56% and piO2 decreased to ∼15 mm Hg. The hypoxia‐induced CBF increase was effective to some extent in compensating for the reduced piO2. This methodology may prove useful for investigating cerebral piO2 under pathologically or functionally altered conditions. Magn Reson Med 45:61–70, 2001. © 2001 Wiley‐Liss, Inc.
An efficient real time rectangle speed limit sign recognition system

This paper present an efficient real time rectangle speed limit sign recognition system. The system design considers computation load and hardware resources for driver assistant system. First multi-scale overlapping LBP features are used to train AdaBoost cascade classifier for speed limit sign object detection. Then a simple linear prediction method is used to do tracking task. At the recognition stage, a novel efficient algorithm is used to correct rotation angle, and then integral image based adaptive threshold algorithm is adopted to segment the speed limit number. The clustering based binary tree of linear support vector machine is adopted for classification task. The system is tested on real road scene video sequences. It achieves 98.3% recognition rate with approximate 16fps frame rate on laptop
Olfactory receptors are displayed on dog mature sperm cells

Olfactory receptors constitute a huge family of structurally related G protein-coupled receptors, with up to a thousand members expected. We have shown previously that genes belonging to this family were expressed in the male germ line from both dog and human. The functional significance of this unexpected site of expression was further investigated in the present study. We demonstrate that a few dog genes representative of various subfamilies of olfactory receptors are expressed essentially in testis, with little or no expression in olfactory mucosa. Other randomly selected members of the family show the expected site of expression, restricted to the olfactory system. Antibodies were generated against the deduced amino acid sequence of the most abundantly expressed olfactory receptor gene in dog testis. The purified serum was able to detect the gene product (DTMT receptor) in late round and elongated spermatids, as well as in the cytoplasmic droplet that characterizes the maturation of dog sperm cells, and on the tail midpiece of mature spermatozoa. Western blotting further confirmed the presence of a 40-kD immunoreactive protein in the membrane of mature sperm cells. Altogether , these results demonstrate that the main expression site of a subset of the large olfactory receptor gene family is not olfactory mucosa but testis. This expression correlates with the presence of the corresponding protein during sperm cell maturation, and on mature sperm cells. The pattern of expression is consistent with a role as sensor for unidentified chemicals possibly involved in the control of mammalian sperm maturation, migration, and/or fertilization.
Navigating the relationship between policy and practice: competing discourses of fear and care in teachers’ sense-making about the FAIR Education Act

Abstract In this article, I examine the relationship between large-scale social discourses and local, school discourses as it plays out in conversations about gender and sexuality with and among teachers, specifically in the context of the passage of the Fair, Accurate, Inclusive, and Respectful (FAIR) Education Act in California. Grounded in feminist poststructural theories of discourse, I discuss qualitative data from a year-long study at one public middle school in Southern California where I provided professional development. I examine what happens when teachers are given opportunities to make sense of their roles in attending to topics of gender and sexual diversity, through conversations and dialogue. The following research questions guided my analyses: What themes arise in teachers’ conversations about their roles and responsibilities in the implementation of the FAIR Education Act? (How) are these themes produced in relationship with large-scale social discourses about gender and sexual diversity in schools? I argue that examining this relationship provides key insights into the ways teachers make sense of equity-focused policies that are meant to shift sociopolitical paradigms, and their roles and responsibilities in the implementation of such policies.
2 3 Ja n 20 04 An interest rates cluster analysis

An empirical analysis of interest rates in money and capital markets is performed. We investigate a set of 34 different weekly interest rate time series during a time period of 16 years between 1982 and 1997. Our study is focused on the collective behavior of the stochastic fluctuations of these time-series which is investigated by using a clustering linkage procedure. Without any a priori assumption, we individu-ate a meaningful separation in 6 main clusters organized in a hierarchical structure.
Perspectives on: Molecular dynamics and computational methods: On the functional significance of soft modes predicted by coarse-grained models for membrane proteins

Recent years have seen an explosion in the number of studies that explore the collective dynamics of biomolecular systems using coarse-grained (CG) models along with methods based on principal component analysis (PCA). Among them, elastic network models (ENMs) and normal mode analyses (NMAs) have found wide use in several applications. Recent studies are now providing evidence for the usefulness of these methods in exploring the dynamics of membrane proteins. The type of motions explored by the ENMs represents a different regime compared with the highly specific chemical events and electrostatic interactions that are usually explored by molecular dynamics (MD) simulations. These are collective motions that cooperatively involve all subunits, usually exploit the symmetry of the quaternary structure, and facilitate mechanical functions such as pore opening and allosteric communication. Understanding the mechanisms of function of membrane proteins using computational methods may necessitate adopting multi-scale approaches that integrate ENM-based methods with full atomic simulations.
Performance of likelihood-based estimation methods for multilevel binary regression models

By means of a fractional factorial simulation experiment, we compare the performance of penalised quasi-likelihood (PQL), non-adaptive Gaussian quadrature and adaptive Gaussian quadrature in estimating parameters for multilevel logistic regression models. The comparison is done in terms of bias, mean-squared error (MSE), numerical convergence and computational efficiency. It turns out that in terms of MSE, standard versions of the quadrature methods perform relatively poorly in comparison with PQL.
Energy effective 3D stacked hybrid NEMFET-CMOS caches

In this paper we propose to utilise 3D-stacked hybrid memories as alternative to traditional CMOS SRAMs in L1 and L2 cache implementations and analyse the potential implications of this approach on the processor performance, measured in terms of Instructions-per-Cycle (IPC) and energy consumption. The 3D hybrid memory cell relies on: (i) a Short Circuit Current Free Nano-Electro-Mechanical Field Effect Transistor (SCCF NEMFET) based inverter for data storage; and (ii) adjacent CMOS-based logic for read/write operations and data preservation. We compare 3D Stacked Hybrid NEMFET-CMOS Caches (3DS-HNCC) of various capacities against state of the art 45 nm low power CMOS SRAM counterparts (2D-CC). All the proposed implementations provide two orders of magnitude static energy reduction (due to NEMFET's extremely low OFF current), a slightly increased dynamic energy consumption, while requiring an approximately 55% larger footprint. The read access time is equivalent, while for write operations it is with about 3 ns higher, as it is dominated by the mechanical movement of the NEMFET's suspended gate. In order to determine if the write latency overhead inflicts any performance penalty, we consider as evaluation vehicle a state of the art mobile out-of-order processor core equipped with 32-kB instruction and data L1 caches, and a unified 2-MB L2 cache. We evaluate different scenarios, utilizing both 3DS-HNCC and 2D-CC at different hierarchy levels, on a set of SPEC 2000 benchmarks. Our simulations indicate that for the considered applications, despite of their increased write access time, 3DS-HNCC L2 caches inflict insignificant IPC penalty while providing, on average, 38% energy savings, when compared with 2D-CC. For L1 instruction caches the IPC penalty is also almost insignificant, while for L1 data caches IPC decreases between 1% to 12% were measured.
A Generalized Quadratic Loss for Support Vector Machines

The standard SVM formulation for binary classification is based on the Hinge loss function, where errors are considered not correlated. Due to this, local information in the feature space which can be useful to improve the prediction model is disregarded. In this paper we address this problem by defining a generalized quadratic loss where the co-occurrence of errors is weighted according to a kernel similarity measure in the feature space. In particular the proposed approach weights pairs of errors according to the distribution of the related patterns in the feature space. The generalized quadratic loss includes also target information in order to penalize errors on pairs of patterns that are similar and of the same class. We show that the resulting dual problem can be expressed as a hard margin SVM in a different feature space when the co-occurrence error matrix is invertible. We compare our approach against a standard SVM on some binary classification tasks. Experimental results obtained for different instances of the co-occurrence error matrix on these problems, seems to show an improvement in the performance.
PubMed search filters for the study of putative outdoor air pollution determinants of disease

Objectives Several PubMed search filters have been developed in contexts other than environmental. We aimed at identifying efficient PubMed search filters for the study of environmental determinants of diseases related to outdoor air pollution. Methods We compiled a list of Medical Subject Headings (MeSH) and non-MeSH terms seeming pertinent to outdoor air pollutants exposure as determinants of diseases in the general population. We estimated proportions of potentially pertinent articles to formulate two filters (one ‘more specific’, one ‘more sensitive’). Their overall performance was evaluated as compared with our gold standard derived from systematic reviews on diseases potentially related to outdoor air pollution. We tested these filters in the study of three diseases potentially associated with outdoor air pollution and calculated the number of needed to read (NNR) abstracts to identify one potentially pertinent article in the context of these diseases. Last searches were run in January 2016. Results The ‘more specific’ filter was based on the combination of terms that yielded a threshold of potentially pertinent articles ≥40%. The ‘more sensitive’ filter was based on the combination of all search terms under study. When compared with the gold standard, the ‘more specific’ filter reported the highest specificity (67.4%; with a sensitivity of 82.5%), while the ‘more sensitive’ one reported the highest sensitivity (98.5%; with a specificity of 47.9%). The NNR to find one potentially pertinent article was 1.9 for the ‘more specific’ filter and 3.3 for the ‘more sensitive’ one. Conclusions The proposed search filters could help healthcare professionals investigate environmental determinants of medical conditions that could be potentially related to outdoor air pollution.
Neural Correlates of the Clock Drawing Test Performance in Alzheimer’s Disease: A FDG-PET Study

Background/Aim: This study aimed to identify the functional neuroanatomical correlates of impaired clock drawing test (CDT) performance in patients with Alzheimer’s disease (AD). Method: The CDT was administered to 71 patients with AD, and regional cerebral glucose metabolism (rCMglc) was measured by positron emission tomography (PET). Correlations between CDT scores and rCMglc were examined on a voxel-by-voxel basis. Results: Significant positive correlations were found between CDT performance and rCMglc in the right inferior parietal lobule and right posterior cingulate cortex. Conclusion: These results provide the first PET evidence that poor CDT performance in patients with AD is closely related to the functional decline in the right hemisphere, especially the right parietal cortex.
Classification Fusion in Wireless Sensor Networks

In wireless sensor networks, target classification differs from that in centralized sensing systems because of the distributed detection, wireless communication and limited resources. We study the classification problem of moving vehicles in wireless sensor networks using acoustic signals emitted from vehicles. Three algorithms including wavelet decomposition, weighted k-nearest-neighbor and Dempster-Shafer theory are combined in this paper. Finally, we use real world experimental data to validate the classification methods. The result shows that wavelet based feature extraction method can extract stable features from acoustic signals. By fusion with Dempster's rule, the classification performance is improved.
The Impact of Posture on Wrist Tendinosis Among Blue-Collar Workers

Objective: The objective was to evaluate the effect of wrist posture on incidence of wrist tendinosis in a prospective cohort of blue-collar workers. Background: Previous studies have identified awkward wrist posture as a risk factor for wrist tendinosis, though the magnitude of the relationship is unclear. Method: Workers (N = 413) at four industries were followed for up to 28 months with questionnaires and physical examinations every 4 months. Individualized exposure assessments of wrist posture were based on video analysis to determine the wrist extension/flexion angle for up to four tasks. Posture measures were calculated while in “heavy pinch” (> 1 kg force), “heavy power grip” (> 4 kg force), and across “all grips. ” A proportional hazards model estimated the relationship between time-weighted average posture measures and incidence of dominant-side wrist tendinosis. Results: In a model based on tertiles of exposure, adjusted for age, gender, hand force, and repetition of exertions, risk of tendinosis more than doubled in the highest category (HR = 2.69, 95% CI = 1.01–7.21) across all grips. The relative risk was highest during heavy pinch (HR = 5.03, 95% CI = 0.74–34.05), though not statistically significant. Increased median wrist extension while in heavy power grip was protective (HR = 0.24, 95% CI = 0.06–0.94). Conclusion: In this study of production workers, median wrist flexion of more than 7°, across all grips, was associated with an increased risk of tendinosis. The protective findings on median wrist extension during power grip deserve further investigation. Work tasks and tools should be designed to prevent sustained wrist flexion, especially during tasks involving forceful pinch.
Running title : Tenascin-C-deficiency accelerates sarcopenia

Tenascin-C (TNC) is a mechano-regulated, morphogenic, extracellular matrix protein which is associated with tissue remodeling. The physiological role of TNC remains unclear because transgenic mice engineered for a TNC-deficiency via a defect in TNC secretion show no major pathologies. We hypothesized that TNC-deficient mice would demonstrate defects in the repair of damaged leg muscles, which would be of functional significance because this tissue is subjected to frequent cycles of mechanical damage and regeneration. TNC-deficient mice demonstrated a blunted expression of the large TNC isoform, and a selective atrophy of fast muscle fibers, associated with a defective fast myogenic expression response to a damaging mechanical challenge. Transcript profiling mapped a set of de-adhesion, angiogenesis, and wound healing regulators as TNC expression targets in striated muscle. Expression of these regulators correlated with the residual expression of a damage-related 200-kDa protein, which resembled the small TNC isoform. Somatic Knock-in of TNC in fast muscle fibers confirmed the activation of a complex expression program of interstitial and slow myofiber repair by myofiber-derived TNC. The results presented here show for the first time that a TNC-orchestrated molecular pathway integrates muscle repair into the load-dependent control of the striated muscle phenotype.
Lightweight Public Key Infrastructure and Service Relation Model for Designing a Trustworthy ONS

With the rapidly development and large scale applications of Electronic Product Code (EPC) networks, researchers and customers have turned their attention to the security problems. In this paper, we discuss the design methodology of trustworthy ONS, an Object Naming System of EPC network, and propose an adjusted Public Key Infrastructure (PKI), called LPKI, for trustworthy ONS. It enhances the security of ONS using a new encryption encode/decode strategy of EPC, and improves reliability of the Certificate Authority by a new multiple customer relation model. Our preliminary experiments show that the proposed method does provide the needed security with reasonable performance, and hence is feasible for building trustworthy ONS.
IP network for emergency service

Internet has become the primary means for worldwide communications. In terms of recreation, business, and various imaginative reasons for information distribution it is the most used communication method today. In recent times, it is a big issue of how we can make the best use of Internet in an emergency period. The goal of this paper is to ensure Internet's best effort services to help during emergencies without any major changes in existing technology. Here, we present a system architecture that reflects a general overview of how it can work parallel to the authorized Emergency Telecommunications Services (ETS). To detect location information in a loosely coupled network environment is the most challenging aspect using IP's flat address model. Our conceptual view of the system architecture shows how the service can be provided extending DHCP, XML with existing core technology. In succession, a simulation of the system is shown to realize call setup delay and end to end VoIP packet delay over the IP network.
Footprint-based Scheduling

As we move into the multicore era, fine-grain multithreading will be among the primary tools used by software developers to enhance the parallel performance of their applications. However, more so than in prior, coarsegrain multithreading systems, intelligent locality-aware scheduling of fine-grain threads is paramount for good performance. Fortunately, in fine-grain multithreaded applications there is an abundance of threads eligible for execution at any given time, suggesting opportunities to develop efficient, locality-aware thread scheduling algorithms that can improve overall performance. In this paper, we develop techniques for footprint-based thread scheduling – a previously uncharted area of research. We experimentally evaluate two sets of synthetic workloads to demonstrate the importance of localityaware scheduling. For array-based workloads, we show a worst-case 5X performance difference between localityaware and locality-indifferent executions. Similarly, for tree-based workloads, we show in excess of a 2X performance difference across best-case and worst-case executions. We also discuss and present architectural enhancements to expose thread footprint information to software for efficient footprint-based thread scheduling. Finally, we describe a footprint-based thread scheduling algorithm to be evaluated in future work.