Miracle-dz/UniFAR-FTUs huggingface dataset:
A Cross-Layer Approach for Cooperative MIMO Multi-hop Wireless Sensor Networks

In this work, we study the problem of determining the minimum scheduling length that can satisfy end-to-end (ETE) traffic demand in scheduling-based multihop WSNs with cooperative multiple-input multiple-output (MIMO) transmission scheme. Specifically, we present a cross-layer formulation for the joint routing, scheduling and stream control problem by incorporating various power and rate adaptation schemes, and taking into account an antenna beam pattern model and the signal-to-interference-and-noise (SINR) constraint at the receiver. In the context, we also propose column generation (CG) solutions to get rid of the complexity requiring the enumeration of all possible sets of scheduling links. Keywords—Wireless Sensor Networks, Cross-Layer Design, Cooperative MIMO System, Column Generation.
Integrating Monocular Vision and Odometry for SLAM

This paper presents an approach to Simultaneous Localization and Mapping (SLAM) based on monocular vision. Standard multiple-view vision techniques are used to estimate robot motion and scene structure, which are then integrated with minimal odometric information and used to build a global environment map. Preliminary experimental results are also presented and discussed. Key-Words:Robot localisation, Mapping, Monocular vision, SLAM
CONTESTED LIVELIHOODS: "PLACING" ONE ANOTHER IN "CEDAR," KENTUCKY

In an east central Kentucky setting many residents combine work for several multinational industries: cash-cropping tobacco, associated with notions of independent production, and work in textile or, now, automobile assembly plants. Theorizing from a local practice of "placing" people (regionally, relationally, occupationally, and ideologically), I discuss the ways in which identity, rurality, livelihood, and the future of a community are negotiated by residents continually "placed" in different development discourses. Through one of these, which I call "tobacco" discourse, single, fixed constructions of identity and livelihood are resisted; through another, which I call "toyota" discourse, engaged in by individuals placed as nonlocal or local, these constructions are promoted. ["placing," Kentucky, farm/factory work, development discourses, negotiating identity]
Device Performance of Graphene Nanoribbon Field-Effect Transistors in the Presence of Line-Edge Roughness

The electrical characteristics of armchair edge graphene nanoribbon field-effect transistors in the presence of line-edge roughness scattering are studied. Self-consistent atomistic simulations based on the nonequilibrium Green's function formalism are employed. A tight binding model incorporating the third nearest neighbor interaction and edge bond relaxation is used to describe the electronic bandstructure. The effect of geometrical and roughness parameters on the on-current, the off -current, subthreshold swing, and the transconductance is investigated.
Quantitative aspects of isoeugenol contact allergy assessed by use and patch tests

The clinical implications of sensitization to the fragrance material isoeugenol were studied in 19 subjects. Patch testing with serial dilutions of isoeugenol and a repeated open application test (ROAT) were performed The minimum effect level under patch test conditions was below 0.01% isoeugenol in 4/19 (20%) of the test subjects. The ROAT was performed with a test solution of 0.2% isoeugenol in ethanol. which is the recommended maximum concentration used in perfumes, ethanol being applied as vehicle control. 4 weeks was the maximum exposure period. The upper arm was used as test site the 1st 14 days and the upper arm as well as the neck for the next 14 days, 12/19 (63%) of test subjects had a positive ROAT. 4 of the responders (33%) reacted beyond day 7, but none alter day 14. Use testing on the neck for 14 days did not add any further ROAT‐positive cases, compared with testing on the upper arm. The sensitivity found on patch testing may be a guidance for the outcome of use tests with the same compound. In this study, all subjects with a positive use test to isoeugenol (0.2%) in ethanol also demonstrated on patch testing a minimum effect level of 0.2% or lower. Data from serial dilution patch and use IC‐N may contribute significant information to assessment of the relationship between patch test responses and clinical contact hypersensitivity, and thus the safety of allergens used in cosmetics.
Relational data pre-processing techniques for improved securities fraud detection

Commercial datasets are often large, relational, and dynamic. They contain many records of people, places, things, events and their interactions over time. Such datasets are rarely structured appropriately for knowledge discovery, and they often contain variables whose meanings change across different subsets of the data. We describe how these challenges were addressed in a collaborative analysis project undertaken by the University of Massachusetts Amherst and the National Association of Securities Dealers(NASD). We describe several methods for data pre-processing that we applied to transform a large, dynamic, and relational dataset describing nearly the entirety of the U.S. securities industry, and we show how these methods made the dataset suitable for learning statistical relational models. To better utilize social structure, we first applied known consolidation and link formation techniques to associate individuals with branch office locations. In addition, we developed an innovative technique to infer professional associations by exploiting dynamic employment histories. Finally, we applied normalization techniques to create a suitable class label that adjusts for spatial, temporal, and other heterogeneity within the data. We show how these pre-processing techniques combine to provide the necessary foundation for learning high-performing statistical models of fraudulent activity.
Machine Learning for Social Multiparty Human--Robot Interaction

We describe a variety of machine-learning techniques that are being applied to social multiuser human--robot interaction using a robot bartender in our scenario. We first present a data-driven approach to social state recognition based on supervised learning. We then describe an approach to social skills execution—that is, action selection for generating socially appropriate robot behavior—which is based on reinforcement learning, using a data-driven simulation of multiple users to train execution policies for social skills. Next, we describe how these components for social state recognition and skills execution have been integrated into an end-to-end robot bartender system, and we discuss the results of a user evaluation. Finally, we present an alternative unsupervised learning framework that combines social state recognition and social skills execution based on hierarchical Dirichlet processes and an infinite POMDP interaction manager. The models make use of data from both human--human interactions collected in a number of German bars and human--robot interactions recorded in the evaluation of an initial version of the system.
Economic performance evaluation and classification using hybrid manifold learning and support vector machine model

Economic performance evaluation and classification is an important and challenging issue and has been gaining attention the last three decades of academic research, monetary institutions groups and business development. The purpose of this paper is to propose a hybrid model which combines support vector machine with isometric feature mapping (ISOMAP), Principal Component Analysis (PCA) and Locally Linear Embedding (LLE) utilized as a preprocessor in order to improve countries economic performance evaluation and classification capability by support vector machine. The results show that our hybrid approach SMV+ISOMAP only not has the best classification rate, but also produces the lowest incidence of Type II errors and have the excellent Receiver Operating Characteristic (ROC) curve. In addition it's capable to provide on time the economic performance classification for better investment and government decisions.
LEMAR: A novel length matching routing algorithm for analog and mixed signal circuits

Enabled by the heterogeneous integration in modern System-On-Chips (SOCs), the design automation for analog and mixed signal circuit components in SOCs is attracting increasing interests. Matching constraints for specific analog signals are critical for correct functionalities. This paper presents a novel single-layer detailed routing algorithm with the length matching constraint, called LEMAR. LEMAR features an innovative routing model for partitioning the routing layout for wire detouring, effective detouring patterns according to the geometric shapes of the partitioned tiles, an enhanced A*-search algorithm along with the backtrack technique for finding the routing path, and an iterative rip-up and reroute procedure for finding the feasible routing solution with the matching constraint. Experimental results are promising and show that LEMAR is both effective and efficient.
Genomic Analysis of 15 Human Coronaviruses OC43 (HCoV-OC43s) Circulating in France from 2001 to 2013 Reveals a High Intra-Specific Diversity with New Recombinant Genotypes

Human coronavirus OC43 (HCoV-OC43) is one of five currently circulating human coronaviruses responsible for respiratory infections. Like all coronaviruses, it is characterized by its genome’s high plasticity. The objectives of the current study were to detect genetically distinct genotypes and eventually recombinant genotypes in samples collected in Lower Normandy between 2001 and 2013. To this end, we sequenced complete nsp12, S, and N genes of 15 molecular isolates of HCoV-OC43 from clinical samples and compared them to available data from the USA, Belgium, and Hong-Kong. A new cluster E was invariably detected from nsp12, S, and N data while the analysis of nsp12 and N genes revealed the existence of new F and G clusters respectively. The association of these different clusters of genes in our specimens led to the description of thirteen genetically distinct genotypes, among which eight recombinant viruses were discovered. Identification of these recombinant viruses, together with temporal analysis and tMRCA estimation, provides important information for understanding the dynamics of the evolution of these epidemic coronaviruses.
Herpes Simplex Virus 1 Suppresses the Function of Lung Dendritic Cells via Caveolin-1

ABSTRACT Caveolin-1 (Cav-1), the principal structural protein of caveolae, has been implicated as a regulator of virus-host interactions. Several viruses exploit caveolae to facilitate viral infections. However, the roles of Cav-1 in herpes simplex virus 1 (HSV-1) infection have not fully been elucidated. Here, we report that Cav-1 downregulates the expression of inducible nitric oxide synthase (iNOS) and the production of nitric oxide (NO) in dendritic cells (DCs) during HSV-1 infection. As a result, Cav-1 deficiency led to an accelerated elimination of virus and less lung pathological change following HSV-1 infection. This protection was dependent on iNOS and NO production in DCs. Adoptive transfer of DCs with Cav-1 knockdown was sufficient to confer the protection to wild-type (WT) mice. In addition, Cav-1 knockout (KO) (Cav-1−/−) mice treated with an iNOS inhibitor exhibited significantly reduced survival compared to that of the nontreated controls. We found that Cav-1 colocalized with iNOS and HSV-1 in caveolae in HSV-1-infected DCs, suggesting their interaction. Taken together, our results identified Cav-1 as a novel regulator utilized by HSV-1 to evade the host antiviral response mediated by NO production. Therefore, Cav-1 might be a valuable target for therapeutic approaches against herpesvirus infections.
Failure of routine susceptibility tests to detect imipenem resistance among strains of methicillin-resistant Staphylococcus aureus

We tested 75 methicillin-resistant Staphylococcus aureus strains for susceptibility to imipenem by using disk diffusion tests and broth microdilution tests with standard and heavy inocula. Population analysis was performed on isolates that appeared to be susceptible by these methods. All of the strains contained subpopulations of cells that are phenotypically resistant to imipenem.
Short-Term Hypoxic Exposure and Training Improve Maximal Anaerobic Running Test Performance

Abstract Oriishi, M, Matsubayashi, T, Kawahara, T, and Suzuki, Y. Short-term hypoxic exposure and training improve maximal anaerobic running test performance. J Strength Cond Res 32(1): 181–188, 2018—The purpose of this study was to examine the effectiveness of short-term hypoxic exposure and training in the performance of competitive 400- or 800-m runners. Fifteen female competitive 400- and 800-m runners volunteered to participate and were assigned to either the hypoxic (n = 7) or normoxic (n = 8) group. The subjects completed 6 days of training. The hypoxic group trained and slept in normobaric hypoxia, with oxygen concentrations of 14.4 and 16.5% for training and sleep, respectively. The normoxic group trained and slept at sea level. The subjects completed 4 sprint and 5 endurance training sessions during the camp. The subjects underwent a maximal anaerobic running test before and 8 days after the training camp. The maximal power determined by the anaerobic running test improved significantly in the hypoxic group (p ⩽ 0.05). Blood lactate concentration at submaximal running speed (275, 300, and 375 m·min−1) in the hypoxic group decreased significantly (p ⩽ 0.05) after the training period. No significant changes in these values were found in the normoxic group. These results suggest that 6 days of hypoxic exposure and training enhanced performance and improved lactate metabolism in 400- and 800-m runners.
Electromagnetic Performance Estimation of UHF RFID Tags in Harsh Contexts

Radio-Frequency Identification (RFID) technology is a consolidated example of electromagnetic system in which passive labels equipped with flexible antennas, called tags, are able to use a portion of the electromagnetic energy from the reader antennas, power-up their internal circuitry and provide the automatic identification of objects. Being fully-passive, the performance of RFID tags is strongly dependent on the context, so that the selection of the most suitable tag for the specific application becomes a key point. In this work, a cost-effective but accurate system for the over-the-air electromagnetic characterization of assembled UHF RFID tags is firstly presented and then validated through comparison with a consolidated and diffused measurement systems. Moreover, challenging use-cases demonstrating the usefulness of the proposed systems in analyzing the electromagnetic performance of label-type tags also when applied on materials on different shape or embedded into concrete blocks have been carried out.
Electronic Markets and Electronic Hierarchies: effects of Information Technology on Market Structur Corporate Strategies

This paper analyzes the fundamental changes in market structures that may result from the increasing use of information technology. First, an analytic framework is presented and its usefulness is demonstrated in explaining several major historical changes in American business structures. Then, the framework is used to help explain how electronic markets and electronic hierarchies will allow closer integration of adjacent steps in the value added chains of our economy. The most surprising prediction is that information technology will lead to an overall shift toward proportionately more coordination by markets rather than by internal decisions within firms. Finally, several examples of companies where these changes are already occurring are used to illustrate the likely paths by which new market structures will evolve and the ways in which individual companies can take advantage of these changes. ___1 _^ 1 ___ 1 _1 1 _
Content accessibility in optical cloud networks under targeted link cuts

One of the key enablers of the digital society is a highly reliable information infrastructure that can ensure resiliency to a wide range of failures and attacks. In cloud networks, replicas of various content are located at geographically distributed data centers, thus inherently enhancing cloud network reliability through diversification and redundancy of user accessibility to the content. However, cloud networks rely on optical network infrastructure which can be a target of deliberate link cuts that may cause service disruption on a massive scale. This paper investigates the dependency between the extent of damage caused by link cuts and a particular replica placement solution, as a fundamental prerequisite of resilient cloud network design that lacks systematic theoretical quantification and understanding. To quantify the vulnerability of optical cloud networks based on anycast communication to targeted link cuts, we propose a new metric called Average Content Accessibility (ACA). Using this metric, we analyze the impact of the number and the placement of content replicas on cloud network resiliency and identify the best and the worst case scenarios for networks of different sizes and connectivity. We evaluate the efficiency of simultaneous and sequential targeted link cuts, the latter reassessing link criticality between subsequent cuts to maximize disruption. Comparison with Average Two-Terminal Reliability (A2TR), an existing robustness measure for unicast networks, shows great discrepancy in the vulnerability results, indicating the need for new measures tailored to anycast-based networks.
Measurement of the electrical properties of ungelled ECG electrodes

This paper reports the measurement of the properties of dry or pasteless conductive electrodes to be used for long-term recording of the human electrocardiogram (ECG). Knowledge of these properties is essential for the correct design of the input stage of associated recording amplifiers. Measurements were made on seven commercially available conductive carbon based electrodes at pressures of 5 mmHg (0.67 kPa) and 20 mmHg (2.7 kPa), located on the lower abdomen and chest of the body on seven subjects having different skin types. Parameter values were fitted to a two-time- constant based model of the electrode using data measured over a period of 10 s. Values of resistance, ranging from 23 kΩ to 1850 kΩ and of capacitance ranging from 0.01 μF to 65 μF were obtained for the components, while the values of the time-constants varied from 0.02 s to 7.2 s.
Distortionary company car taxation: deadweight losses through increased car ownership

We analyse the effects of distortionary company car taxation through increased household car consumption for the Netherlands. We use several identification strategies and demonstrate that for about 20 % of households company car possession increases car ownership. The annual welfare loss of distortionary company taxation through increased car ownership is generally rather small, maximally €120 per company car, and much less than the welfare loss through increased expenditure on the company car. However, for policies that exempt households from paying tax on their company car, the annual deadweight loss is likely higher. Our first-best tax policy recommendation is to increase company car tax rates. However, our current results suggest that a second-best policy, which keeps average company car taxation constant but which reduces the marginal tax on cheaper cars and increases the marginal tax on expensive cars, would be welfare improving as overconsumption of company cars will be reduced.
PESC: A parallel system for clustering ECG streams based on MapReduce

Nowadays, cardiovascular disease (CVD) has become a disease of the majority. As an important instrument for diagnosing CVD, electrocardiography (ECG) is used to extract useful information about the functioning status of the heart. In the domain of ECG analysis, cluster analysis is a commonly applied approach to gain an overview of the data, detect outliers or pre-process before further analysis. In recent years, to provide better medical care for CVD patients, the cardiac telehealth system has been widely used. However, the extremely large volume and high update rate of data in the telehealth system has made cluster analysis challenging work. In this paper, we design and implement a novel parallel system for clustering massive ECG stream data based on the MapReduce framework. In our approach, a global optimum of clustering is achieved by merging and splitting clusters dynamically. Meanwhile, a good performance is gained by distributing computation over multiple computing nodes. According to the evaluation, our system not only provides good clustering results but also has an excellent performance on multiple computing nodes.
Mixed-Methods Research in a Complex Multisite VA Health Services Study: Variations in the Implementation and Characteristics of Chiropractic Services in VA

Maximizing the quality and benefits of newly established chiropractic services represents an important policy and practice goal for the US Department of Veterans Affairs' healthcare system. Understanding the implementation process and characteristics of new chiropractic clinics and the determinants and consequences of these processes and characteristics is a critical first step in guiding quality improvement. This paper reports insights and lessons learned regarding the successful application of mixed methods research approaches—insights derived from a study of chiropractic clinic implementation and characteristics, Variations in the Implementation and Characteristics of Chiropractic Services in VA (VICCS). Challenges and solutions are presented in areas ranging from selection and recruitment of sites and participants to the collection and analysis of varied data sources. The VICCS study illustrates the importance of several factors in successful mixed-methods approaches, including (1) the importance of a formal, fully developed logic model to identify and link data sources, variables, and outcomes of interest to the study's analysis plan and its data collection instruments and codebook and (2) ensuring that data collection methods, including mixed-methods, match study aims. Overall, successful application of a mixed-methods approach requires careful planning, frequent trade-offs, and complex coding and analysis.
Newly assembled cyclin B‐cdc2 kinase is required to suppress DNA replication between meiosis I and meiosis II in starfish oocytes.

Micro‐injection of catalytically inactive GST‐cdc2‐K33R or GST‐cdk2‐K33R fusion proteins, each of which efficiently titrates cyclin B in oocytes and prevents assembly of cyclin B‐cdc2 complexes, readily induces premature DNA replication in starfish oocytes after emission of the first polar body. Moreover, partial ablation of cyclin B mRNA by micro‐injection of antisense oligonucleotides facilitates premature DNA replication induced by the dominant‐negative cdc2 and cdk2 mutant proteins. We thus propose that enhanced translation of cyclin B after GVBD, a universal feature of oocyte maturation in the animal kingdom, and subsequent assembly of cyclin B‐cdc2 complexes, are part of the checkpoint that prevents DNA replication in the oocyte after emission of the first polar body. MAPK inactivation is neither required for premature DNA replication after the first meiotic cell cycle nor for DNA replication after completion of meiotic maturation. However, micro‐injection of a N‐terminally truncated form of the budding yeast STE11 protein, that constitutively maintains MAPK active after the second meiotic cleavage, prevents fertilized eggs from proceeding into embryogenesis, and arrests them at G2, as is the case in unfertilized eggs that cannot inactivate MAPK after the second meiotic cleavage. We thus propose that MAPK functions in meiotic maturation by preventing unfertilized eggs from proceeding into parthenogenetic development.