Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating Electric Vehicles’ Response Time to Regulation Signals in Smart Grids

Electric vehicles (EVs) are considered as a flexible load in smart grids. This flexibility promotes the EVs to be good candidates for providing the grid with ancillary services, such as regulation services. A group of EVs controlled by an aggregator can collectively work as a regulation reserve in the electric grid. However, a fast response to the regulation commands is crucial to providing reliable regulation service. Typically, the response time to the regulation command requires to be less than four seconds. In this paper, we precisely evaluate the expected time delay from the instant when an aggregator server sends a regulation command to $n$ EVs to the instant when all the EVs’ responses are received successfully by the server. To achieve this goal, first, a realistic communication structure between the aggregator server and the EVs is considered. Second, the wireless link between the access point (AP) and the EVs is accurately modeled in order to estimate the average delay. The model is based on Markov chain representation for the wireless IEEE 802.11 MAC protocol. Two important factors are considered in this model. First, the packet loss probability due to the lossy wireless environment has been incorporated into the model. Second, the transition stages for the contention window size of 802.11 MAC protocol to reach the saturation stage is taken into account. The model has been validated by means of extensive simulation using the well-known Network Simulator 2 (NS2) tool. Our analysis shows that one AP is capable of handling up to 1000 EVs without violating the 4-s latency limit when the probability of packet loss is 0.01. However, this number decreases significantly, less than 500 EVs, when the wireless link is experiencing a significant packet loss probability of 0.2. Further, we show that by commanding a subgroup of the charging EVs, it is possible to achieve the same regulation service but with a lesser response time, compared to commanding all charging EVs every time.
Vehicle Pose and Shape Estimation Through Multiple Monocular Vision

In this paper, we present a method to estimate a vehicle's pose and shape from off-board multi-view images. These images are taken from monocular cameras with small overlaps. We utilize state-of-the-art Convolutional Neural Networks (CNNs) to extract vehicles' semantic keypoints and introduce a Cross Projection Optimization (CPO) method to estimate the 3D pose. During the iterative CPO process, an adaptive shape adjustment method named Hierarchical Wireframe Constraint (HWC) is implemented to estimate the shape. Our approach is evaluated under both simulated and real-world scenes for performance verification. It's shown that our algorithm outperforms other existing monocular and stereo methods for vehicles' pose and shape estimation. This approach provides a new and robust solution for off-board visual vehicle localization and tracking, which can be applied to massive surveillance camera networks for intelligent transportation.
3 D Medical Image Synthesis using Generative Adversarial Networks

In this work we propose an architecture for 3D medical image synthesis based on Generative Adversarial Networks. ACM Reference format: Irina Sánchez and Verónica Vilaplana. 2017. 3D Medical Image Synthesis using Generative Adversarial Networks. In Proceedings of womENcourage 2017, Barcelona, Spain, September 2017, 1 pages.
Convex Optimization of Distributed Cooperative Detection in Multi-Receiver Molecular Communication

In this paper, the error performance achieved by cooperative detection among <inline-formula> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> distributed receivers in a diffusion-based molecular communication system is analyzed and optimized. In this system, the receivers first make local hard decisions on the transmitted symbol and then report these decisions to a fusion center (FC). The FC combines the local hard decisions to make a global decision using an <inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula>-out-of-<inline-formula> <tex-math notation="LaTeX">${K}$ </tex-math></inline-formula> fusion rule. Two reporting scenarios, namely, perfect reporting and noisy reporting, are considered. Closed-form expressions are derived for the expected global error probability of the system for both reporting scenarios. New approximated expressions are also derived for the expected error probability. Convex constraints are then found to make the approximated expressions jointly convex with respect to the decision thresholds at the receivers and the FC. Based on such constraints, suboptimal convex optimization problems are formulated and solved to determine the optimal decision thresholds which minimize the expected error probability of the system. Numerical and simulation results reveal that the system error performance is greatly improved by combining the detection information of distributed receivers. They also reveal that the solutions to the formulated suboptimal convex optimization problems achieve near-optimal global error performance.
Lost in translation: reproductive health care experiences of Somali Bantu women in Hartford, Connecticut.

INTRODUCTION Reproductive health problems are the leading cause of women's morbidity and mortality worldwide. In the United States, officially sponsored refugee women continue to face challenges in accessing reproductive health programs despite having access to health insurance. METHODS The objective of this study was to explore the reproductive health experiences of 1 such population--Somali Bantu women in Connecticut--to identify potential barriers to care experienced by marginalized populations. The study was qualitative, consisting of key informant interviews, a focus group session, and a semistructured survey. RESULTS Although all the women in the study reported having access to reproductive health care services, they also reported having unmet health needs resulting from barriers to care that included ethnic distinction/language barriers, passive acceptance of incorrect care, cultural discordance in family planning services, patient-provider sex discordance, and desire but limited scope for ownership in health care outcomes. The root cause of the various types of patient-provider discordance was the lack of recognition that the Somali Bantu are distinct in culture, language, and solidarity from ethnic Somalis, resulting in Language Line translation services being conducted in a Somali language that the Somali Bantu women did not understand. DISCUSSION The results of the study primarily highlight the larger issue of information asymmetry within the health care system that, if left unaddressed, will persist as new vulnerable populations of refugees arrive in the United States.
The Mediterranean Sea system: a review and an introduction to the special issue

Abstract. The Mediterranean Sea is a semi-enclosed sea characterized by high salinities, temperatures and densities. The net evaporation exceeds the precipitation, driving an anti-estuarine circulation through the Strait of Gibraltar, contributing to very low nutrient concentrations. The Mediterranean Sea has an active overturning circulation, one shallow cell that communicates directly with the Atlantic Ocean, and two deep overturning cells, one in each of the two main basins. It is surrounded by populated areas and is thus sensitive to anthropogenic forcing. Several dramatic changes in the oceanographic and biogeochemical conditions have been observed during the past several decades, emphasizing the need to better monitor and understand the changing conditions and their drivers. During 2011 three oceanographic cruises were conducted in a coordinated fashion in order to produce baseline data of important physical and biogeochemical parameters that can be compared to historic data and be used as reference for future observational campaigns. In this article we provide information on the Mediterranean Sea oceanographic situation, and present a short review that will serve as background information for the special issue in Ocean Science on "Physical, chemical and biological oceanography of the Mediterranean Sea". An important contribution of this article is the set of figures showing the large-scale distributions of physical and chemical properties along the full length of the Mediterranean Sea.
The relevance of technological autonomy in the customer acceptance of IoT services in retail

The Internet of Things (IoT) represents a shift towards a digitally enriched environment connecting smart objects and users that promises to provide retailers with innovative ways to approach their customers. IoT technologies differ from previous innovations as they are ubiquitous, intelligent and autonomous. Research into the customer acceptance of IoT services in retailing is scarce and the relevance of technological autonomy has been neglected. Hence, the aim of this research was to assess the relevance of technological autonomy in the IoT service acceptance and to investigate factors influencing the willingness to accept. Based on the technology acceptance model (TAM) this research proposed a new model that consists of seven perceptional factors and degree of autonomy. In a between-subject experimental design, data from 167 supermarket customers was analysed using multiple (moderated) regression. First, degree of autonomy statistically significantly influences intention to accept IoT retail services. The results emphasize that the customer acceptance intention of IoT services decreases when technological autonomy grows. Further, support for the positive direct effects of perceived usefulness, compatibility, enjoyment, and technology trust in intention to accept was found. Ease of use, behavioural control and credibility did not play a significant role. Remarkably, support was found that enjoyment and technology trust gained relevance in situations when technological autonomy was high. These findings highlight that perceptions of relative advantage in enjoyment and trust are important, especially when technologies are highly autonomous. Finally, the insignificance of ease of use challenges the robustness and applicability of TAM in latest technologies. The findings encourage future research to consider degree of autonomy in other contexts of IoT technology acceptance.
A new stereo formulation not using pixel and disparity models

We introduce a new stereo formulation which does not use pixel and disparity models. Many problems in vision are treated as assigning each pixel a label. Disparities are labels for stereo. Such pixel-labeling problems are naturally represented in terms of energy minimization, where the energy function has two terms: one term penalizes solutions that inconsistent with the observed data, the other term enforces spatial smoothness. Graph cuts are one of the effi- cient methods for solving energy minimization. However, exact minimization of multi labeling problems can be performed by graph cuts only for the case with convex smoothness terms. In pixel-disparity formulation, convex smoothness terms do not generate well reconstructed 3D results. Thus, truncated linear or quadratic smoothness terms, etc. are used, where approximate energy minimization is necessary. In this paper, we introduce a new site-labeling formulation, where the sites are not pixels but lines in 3D space, labels are not disparities but depth numbers. For this formulation, visibility reasoning is naturally included in the energy function. In addition, this formulation allows us to use a small smoothness term, which does not affect the 3D results much. This makes the optimization step very simple, so we could develop an approximation method for graph cut itself (not for energy minimization) and a high performance GPU graph cut program. For Tsukuba stereo pair in Middlebury data set, we got the result in 5ms using GTX1080GPU, 19ms using GTX660GPU.
ERP benefits capability framework: orchestration theory perspective

ERP benefits can be classified as automation, planning and innovation benefits. This research aims to answer two research questions: (1) what are the ERP resources and organizational complementary resources (OCRs) required to achieve each group of benefits? and (2) on the basis of its resources, when should an organization invest more in ERP resources and/or OCRs so that the potential value of its ERP is realised? Evidence from studying 12 organizations in different countries and validating the results with 8 consultants has been drawn upon to develop the ERP Benefits Realisation Capability Framework, showing (1) that each group of benefits requires ERP resources (classified into features, attached technologies and IT department competences) and OCRs (classified into practices, attitudes, culture, skills and organizational characteristics) and (2) that leaping ahead to gain innovation benefits before being mature enough in realising a firm’s planning and automation capabilities could be a waste of time and effort. This research can be used as a benchmark for designing the various blueprints required to achieve different groups of benefits from ERP investments.
A countermeasure against relay attack in NFC payment

Near Field Communication (NFC) is a convenient short range contactless communication method that is receiving more and more attentions for its simplicity to support mobile payment. Influential industry players, such as Apple, Google and Samsung have integrated NFC technology in their mobile payment applications, i.e. Apple Pay, Android Pay and Samsung Pay, respectively. To deploy NFC for mobile payment, one of the most significant concern is its security. In this article, we proposed a countermeasure to fight against Replay attacks. While some existing work has proposed to set a time bound to prevent relay attack based on the assumption that a relay attack will take much longer time to complete than a normal NFC transaction. Existing approaches however did not address the situation when cloud-based authentication is involved and may confuse it as a relay attack. We extended the time-bound approach in this work and presents a comprehensive estimate of normal transactions versus relayed transactions. A prototype Android application was also built to prove the correctness of the proposed approach.
Fast skewed object matching with adaptive rotation step based on affine transformation

Using affine transformation, object picture can be rotated to the same direction with template picture but it is required to rotate from step by step. This method is very inefficient and time-consuming. To solve this problem, an improved fast skewed object matching algorithm is proposed in this paper. At the beginning, the picture rotate several steps at a given step size to one direction and match a template picture at the same time. The final direction of rotation is determined by the first moment of the similarity. Once the direction is settled, the rotation step size is determined by similarity. If the similarity is lower than threshold then step size increases to approaching the correct angle faster. If the similarity is higher than threshold then step size decreases to achieve the purpose of precise matching the correct angle. It provides a feasible way for the skewed object matching. For example, the skewed Chinese character matching is used to demonstrate this algorithm.
Assembly of alginate microfibers to form a helical structure using micromanipulation with a magnetic field

Helical structures assembled using alginate microfibers have a promising spatial architecture mimicking in vivo vessels for culturing vascular cells. However, the helical structure can only be assembled at the macroscale, since a microassembly-based approach has not yet been developed. In this paper, we propose a magnetic-field-based micromanipulation method to fabricate a helical microstructure. By microfluidic spinning, alginate microfibers encapsulating magnetic nanoparticles are synthesized to enable the control of an electromagnetic needle (EMN). We developed a microrobotic system to actuate a micropipette to fix a free end of the microfiber, and then move the EMN to reel the microfiber around a micropillar. The motion of the EMN is guided using an upright microscope and a side-view camera. Because of the limitation of operation space, a spacer sleeve was designed to keep the tip of the EMN attracted to the microfiber, and simultaneously to keep the other part of the EMN isolated from the microfiber. To ensure the availability of the microfiber for continuously coiling, we enable the EMN tip to slide on the surface of the microfiber without changing the tensioning of the microfiber for positioning control. Furthermore, stable and repeatable micromanipulation was achieved to form multi-turn microfiber coils based on the motion planning of the EMN. Finally, we successfully fabricated a helical microstructure that can be applied in vascular tissue engineering in the future.
Dual antimicrobial and blood repellent finishes for cotton hospital fabrics

Antimicrobial and blood repellant finish has been applied to cotton fabrics used for surgical gowns, bed linens and drapes to reduce the surgical site infections. The extract of neem was applied to the fabric for imparting antimicrobial activity by pad-dry-cure method. The neem treated fabric was then imparted blood repellency through two different techniques, namely by treatment with fluoropolymer (3%, 4% and 5% owf) using pad-dry-cure method and by ‘sputter deposition of teflon’ technique using argon plasma. The antimicrobial activity is found to be higher for teflon deposited fabric than for the fluoropolymer finished fabric. Blood repellency increases with the higher concentration of fluoropolymer and the highest repellency for the teflon deposited fabric is observed at 80W power and 20 min exposure in the plasma chamber.
Neuroplasticity of language in left-hemisphere stroke: evidence linking subsecond electrophysiology and structural connections

Our understanding of neuroplasticity following stroke is predominantly based on neuroimaging measures that cannot address the subsecond neurodynamics of impaired language processing. We combined behavioral and electrophysiological measures and structural-connectivity estimates to characterize neuroplasticity underlying successful compensation of language abilities after left-hemispheric stroke. We recorded the electroencephalogram from patients with stroke lesions to the left temporal lobe and matched controls during context-driven word retrieval. Participants heard lead-in sentences that either constrained the final word (“He locked the door with the”) or not (“She walked in here with the”). The last word was shown as a picture to be named. We conducted individual-participant analyses and focused on oscillatory power as a subsecond indicator of a brain region's functional neurophysiological computations. All participants named pictures faster following constrained than unconstrained sentences, except for two patients, who had extensive damage to the left temporal lobe. Left-lateralized alpha-beta oscillatory power decreased in controls pre-picture presentation for constrained relative to unconstrained contexts. In patients, the alpha-beta power decreases were observed with the same time course as in controls but were lateralized to the intact right hemisphere. The right lateralization depended on the probability of white-matter connections between the bilateral temporal lobes. The two patients who performed poorly behaviorally showed no alpha-beta power decreases. Our findings suggest that incorporating direct measures of neural activity into investigations of neuroplasticity can provide important neural markers to help predict language recovery, assess the progress of neurorehabilitation, and delineate targets for therapeutic neuromodulation.
B Cell–Extrinsic Myd88 and Fcer1g Negatively Regulate Autoreactive and Normal B Cell Immune Responses

MyD88 and FcR common γ-chain (Fcer1g, FcRγ) elicit proinflammatory responses to exogenous Ags. Deletion of these receptors in autoimmune models has generally led to reduced overall disease. In B cells, Myd88 is required for anti-DNA and anti-RNA autoantibody responses, whereas Fcer1g is not expressed in these cells. The roles of these receptors in myeloid cells during B cell autoimmune activation remain less clear. To investigate the roles of Myd88 and Fcer1g in non-B cells, we transferred anti–self-IgG (rheumatoid factor) B cells and their physiologic target Ag, anti-chromatin Ab, into mice lacking Fcer1g, Myd88, or both and studied the extrafollicular plasmablast response. Surprisingly, we found a markedly higher and more prolonged response in the absence of either molecule; this effect was accentuated in doubly deficient recipients, with a 40-fold increase compared with wild-type recipients at day 10. This enhancement was dependent on CD40L, indicating that Myd88 and FcRγ, presumably on myeloid APCs, were required to downregulate T cell help for the extrafollicular response. To extend the generality, we then investigated a classic T cell–dependent response to (4-hydroxy-3-nitrophenyl)acetyl conjugated to chicken γ globulin and found a similar effect. Thus, these results reveal novel regulatory roles in the B cell response for receptors that are typically proinflammatory.
Availability Modeling and Analysis for Software Defined Networks

Software Defined Network (SDN) is an emerging paradigm for flexible network design and implementation. Availability metric of SDNs is critically demanding further studies. This paper aims to propose hierarchical models to assess the availability of SDNs. We incorporate various failure modes and recovery behaviors in the SDN including (i) link failures at network level, and (ii) software and hardware failures at network device level. We use hierarchical models in which a Reliability Graph (RG) is used to represent the reachability of hosts (and switches) in the SDN at the upper level and Stochastic Reward Net (SRN)s are used to represent the detailed failure and recovery of network devices at the lower level, respectively. We incorporate the programmable capability of the SDN at the upper level (i.e., the RG). We perform numerical analysis to assess the availability of the SDN in terms of steady state availability and downtime in minutes per year, and we also show the sensitivity analysis.
Pay for Performance in Medicaid: Evidence from Three Natural Experiments.

OBJECTIVE To examine the impact of pay for performance in Medicaid on the quality and utilization of care. DATA SOURCES Medicaid claims and encounter data in three intervention states (Pennsylvania, Minnesota, and Alabama) and three comparison states. STUDY DESIGN Difference-in-difference analysis with propensity score-matched comparison group. Primary outcomes of interest were Healthcare Effectiveness Data and Information Set (HEDIS)-like process measures of quality, utilization by service category, and ambulatory care-sensitive admissions and emergency department visits. PRINCIPAL FINDINGS In Pennsylvania, there was a statistically significant reduction of 88 ambulatory visits per 1,000 enrollee months compared with Florida. In Minnesota, there was a significant decrease of 7.2 hospital admissions per thousand enrollee months compared with Wisconsin. In Alabama, where incentives were not paid out until the end of a 2-year waiver period, there was a decline of 1.6 hospital admissions per thousand member months, and an increase of 59 ambulatory visits per 1,000 enrollees compared with Georgia. No significant quality improvements in intervention relative to control states. CONCLUSIONS Our findings are mixed, with no measurable quality improvements across the three states, but reductions in hospital admissions in two programs. As states move to value-based payment for patient-centered medical homes and Accountable Care Organizations, lessons learned from these pioneering states should inform program design.