Miracle-dz/UniFAR-FTUs huggingface dataset:
Pervasive Floorplan Generation Based on Only Inertial Sensing: Feasibility, Design, and Implementation

Mobile crowdsourcing is deemed as a powerful technique to solve traditional problems. But the crowdsourced data from smartphones are generally low quality, which can induce crucial challenges and hurt the applicability of crowdsourcing applications. This paper presents our study to address such challenges in a concrete application, namely, floorplan generation. Existing proposals mostly rely on infrastructural references or accurate data sources, which are restricted in terms of applicability and pervasiveness. Our proposal called SenseWit is motivated by the observation that people’s behavior offers meaningful clues for location inference. The noise, ambiguity, and behavior diversity contained in the crowdsourced data, however, mean non-trivial challenges in generating high-quality floorplans. We propose: 1) a novel concept called Nail to identify featured locations in indoor space and 2) a heuristic pathlet bundling algorithm to progressively discover the internal layouts of a floorplan. We implement SenseWit and conduct real-world experiments in different spaces to demonstrate its efficacy. This paper offers an efficient technique to obtain high-quality structures (either logical or physical) from low-quality data. We believe it can be generalized to other crowdsourcing applications.
Proving PACELC

Scalable distributed systems face inherent trade-offs arising from the relatively high cost of exchanging information between computing nodes. Brewer's CAP (Consistency, Availability, Partition-Tolerance) principle states that when communication becomes impossible between isolated parts of the system (i.e., the network is partitioned), then the system must give up either safety (i.e., sometimes return an incorrect result) or liveness (i.e., sometimes fail to produce a result). Abadi generalized Brewer's principle by defining the PACELC (if Partition then Availability or Consistency, Else Latency or Consistency) formulation, which captures the ob- servation that the trade-off between safety and liveness is often made in practice even while the network is reliable. Building on Gilbert and Lynch's formal proof of the CAP principle, this paper presents a formal treatment of Abadi's formulation and connects this result to a body of prior work on latency bounds for distributed objects.
Sildenafil (Viagra) evokes retinal arteriolar dilation: dual pathways via NOS activation and phosphodiesterase inhibition.

PURPOSE Sildenafil (Viagra; Pfizer, New York, NY), a selective phosphodiesterase type-5 (PDE5) inhibitor, is widely used to treat impotence by improving penile blood flow via elevation of cGMP. However, its effect on ocular circulation is controversial and whether retinal arterioles are responsive to this drug remains unclear. In this study, the direct reaction of retinal arterioles to sildenafil was examined and the signaling pathway underlying this vasomotor activity was probed. METHODS Retinal arterioles from porcine eyes were isolated, cannulated, and pressurized without flow. Diameter changes in response to sildenafil were recorded using videomicroscopic techniques. RESULTS Retinal arterioles (67 +/- 2 microm) dilated dose dependently to sildenafil (1 ng/mL to 1 microg/mL). This dilation was inhibited by the nitric oxide (NO) synthase inhibitor N(G)-nitro-L-arginine methyl ester (L-NAME), the guanylyl cyclase inhibitor 1H- [1,2,4]oxadiazolo[4,3-a]quinoxalin-1-one (ODQ), the extracellular signal-regulated kinase (ERK) pathway inhibitor PD98059, the nonselective potassium channel blocker tetraethylammonium (TEA), and the selective adenosine triphosphate (ATP)-sensitive potassium (K(ATP)) channel blocker glibenclamide. The vasodilation elicited by the NO donor S-nitroso-N-acetylpenicillamine (SNAP) was inhibited by ODQ and TEA but was insensitive to PD98059. In the presence of L-NAME, the addition of SNAP (1 microM) produced modest vasodilation and the inhibited sildenafil response was subsequently restored. The restored dilation was insensitive to PD98059 but was blocked by TEA. CONCLUSIONS Activation of NO synthase, through ERK signaling, leading to NO production and subsequent guanylyl cyclase activation and K(ATP) channel opening is the major vasodilatory pathway for sildenafil in retinal arterioles. Moreover, the elevated cGMP, from endogenous or exogenous NO, plays a permissive role for sildenafil to exert vasodilation through inhibition of the PDE5 pathway independent of ERK signaling.
Effect of soft-tissue impingement on range of motion during posterior approach Total Hip Arthroplasty: an in vivo measurement study

Abstract Purpose: While implant impingement and bony impingement have been recognized as causes of poor outcomes in total hip arthroplasty (THA), reports of soft-tissue impingement are rare. To clarify the issue, the effect of anterior capsule resection on hip range of motion (ROM) was quantitatively measured in vivo during posterior approach THA using a CT-based hip navigation system. Materials and methods: For 47 patients (51 hips), hip ROM was measured intraoperatively before and after resection of the anterior hip capsule, and the difference was compared. Results: Resection of the anterior hip capsule brought about an average 6° increase of ROM in the direction of flexion with internal rotation and did not markedly change ROM in other directions. Conclusions: During THA through a posterior approach, soft-tissue impingement by the anterior hip capsule can occur. Clinically, we expect that resection of the anterior hip capsule can reduce the risk of posterior instability without increasing the risk of anterior instability.
Four Heat Shock Protein Genes of the Endoparasitoid Wasp, Cotesia vestalis, and Their Transcriptional Profiles in Relation to Developmental Stages and Temperature

Heat shock proteins (Hsps) play important roles in the environmental adaptation of various organisms. To explore the functions of Hsps in relation to heat stress and development in Cotesia vestalis, a solitary larval endoparasitoid of Plutella xylostella, four heat shock protein genes, CvHsp40, CvHsc70, CvHsp70 and CvHsp90, were cloned and sequenced from C. vestalis by real-time quantitative PCR and RACE. The cDNA sequence of CvHsp40, CvHsc70, CvHsp70 and CvHsp90 were 1473 bp, 2316 bp, 2279 bp and 2663 bp long, which encode proteins with calculated molecular weights (MW) of 39.1 kDa, 71.2 kDa, 70.1 kDa and 83.3 kDa, respectively. Furthermore, the analysis of genomic DNA confirmed that no introns existed in CvHsp40, CvHsp70 and CvHsp90 while two introns were present in CvHsc70. The amino acid sequence analysis of CvHsps indicated that CvHsp40 is a Type II Hsp40 homolog, CvHsp70 and CvHsc70 are the eukaryotic cytoplasmic Hsp70s, and CvHsp90 is the β-isoform of Hsp90. The divergent transcriptional patterns of CvHsp40, CvHsp70 and CvHsp90 in the different developmental stages suggested that CvHsp transcripts were under different mechanisms of regulation during the development of parasitoid larvae. The dramatic increase of transcripts of CvHsp70 at the third-instar larva coincided with its developmental change in this stage, that is, from inside host to outside host. CvHsp40, CvHsc70 and CvHsp70 showed a trend of sex-specific differences of transcript abundance in the adult stage. All CvHsp transcripts in different developmental stages were significantly induced by heat stress, and the lowest transcript abundances appeared around the temperature 27°C, which probably suggest that this is the most favorable temperature for the development of C. vestalis. Our results suggest that the expression of heat shock proteins reflects to some extent the developmental changes and environmental requirements of insects.
Video Scene Change Detection Using Convolution Neural Network

There are various contents such as music, image, and image on digital. There are many kinds of dual image contents such as movies, drama, entertainment, and anime. In the case of image contents, a frame or a shot unit, which is one image unit, a scene where consecutive frames are gathered, and a plurality of scenes are connected to form a single image. In this paper, we propose an algorithm to distinguish scenes from image contents. We distinguished the scene using a convolution neural network for video scene discrimination. The video was classified by frame, and the data of the frame portion in which the scene such as the frame data of the portion where the scene changes was held was labeled and trained. By using the trained network, it is possible to extract images in frame units from movie contents such as movies and drama, and to identify the scene changing parts and to divide the images into scene units. It is possible to distinguish scenes with higher accuracy even in areas that change very quickly, such as actions, compared to conventional methods.
Alcohol and remembering a hypothetical sexual assault: Can people who were under the influence of alcohol during the event provide accurate testimony?

We examined the influence of alcohol on remembering an interactive hypothetical sexual assault scenario in the laboratory using a balanced placebo design. Female participants completed a memory test 24 hours and 4 months later. Participants reported less information (i.e., responded “don't know” more often to questions) if they were under the influence of alcohol during scenario encoding. The accuracy of the information intoxicated participants reported did not differ compared to sober participants, however, suggesting intoxicated participants were effectively monitoring the accuracy of their memory at test. Additionally, peripheral details were remembered less accurately than central details, regardless of the intoxication level; and memory accuracy for peripheral details decreased by a larger amount compared to central details across the retention interval. Finally, participants were more accurate if they were told they were drinking alcohol rather than a placebo. We discuss theoretical implications for alcohol myopia and memory regulation, together with applied implications for interviewing intoxicated witnesses.
Conjoint Treatment: A Novel Approach to Target the Syndemic Conditions of Trauma, Substance Abuse, and HIV in Women Living with HIV

Impact of HIV Among Women in the United States The Centers for Disease Control and Prevention estimates that in the United States, 1.2 million adults and adolescents are living with human immunodeficiency virus (HIV). In a span of 15 years, from 1985 to 2000, the proportion of women living with HIV more than tripled. The Centers for Disease Control and Prevention estimated that by the end of 2013, 232,511 women were living with HIV in the United States. Today, of all of the individuals living with HIV in the United States, 25% are women, a figure that is even higher in some states. There are many converging factors that make women especially vulnerable to HIV. These include but are not limited to increased disparities and needs they face because of socioeconomic and structural barriers, competing needs of taking care of family and children, an unequal role and power within a relationship, and biological differences that make them more susceptible to HIV. Many women combat cooccurring substance abuse and psychiatric symptoms that are largely the result of complex trauma from intimate partner violence or physical, sexual, and psychological violence by an intimate partner, The syndemics or confluence of these factors creates a synergy between coexisting health and social problems and factors that exacerbate and perpetuate health risks and poor health outcomes. These syndemic conditions also undermine
Human Mobility Enhances Global Positioning Accuracy for Mobile Phone Localization

Global positioning system (GPS) has enabled a number of geographical applications over many years. Quite a lot of location-based services, however, still suffer from considerable positioning errors of GPS (usually 1 to 20 m in practice). In this study, we design and implement a high-accuracy global positioning solution based on GPS and human mobility captured by mobile phones. Our key observation is that smartphone-enabled dead reckoning supports accurate but local coordinates of users' trajectories, while GPS provides global but inconsistent coordinates. Considering them simultaneously, we devise techniques to refine the global positioning results by fitting the global positions to the structure of locally measured ones, so the refined positioning results are more likely to elicit the ground truth. We develop a prototype system, named GloCal, and conduct comprehensive experiments in both crowded urban and spacious suburban areas. The evaluation results show that GloCal can achieve 30 percent improvement on average error with respect to GPS. GloCal uses merely mobile phones and requires no infrastructure or additional reference information. As an effective and light-weight augmentation to global positioning, GloCal holds promise in real-world feasibility.
Optimizing Information Freshness in Wireless Networks Under General Interference Constraints

Age of information (AoI) is a recently proposed metric for measuring information freshness. AoI measures the time that elapsed since the last received update was generated. We consider the problem of minimizing average and peak AoI in a wireless networks, consisting of a set of source-destination links, under general interference constraints. When fresh information is always available for transmission, we show that a stationary scheduling policy is peak age optimal. We also prove that this policy achieves average age that is within a factor of two of the optimal average age. In the case where fresh information is not always available, and packet/information generation rate has to be controlled along with scheduling links for transmission, we prove an important separation principle: the optimal scheduling policy can be designed assuming fresh information, and independently, the packet generation rate control can be done by ignoring interference. Peak and average AoI for discrete time G/Ber/1 queue is analyzed for the first time, which may be of independent interest.
A high‐level library for multidimensional arrays programming in computational science

This paper describes ExaShark, a hybrid n‐dimensional array toolkit offered as a high‐level library for scientists to compute large‐scale simulations. It offers a global‐array–like interface while its runtime can be configured to use shared memory threading techniques, inter‐node distribution techniques, or combinations of both. ExaShark takes advantage of the latest HPC technologies, helping to scale to future generation systems. It has been used to develop several scientific applications including stencil codes, solvers, and matrix factorization algorithms. These applications are used to demonstrate that it improves on the state of the art by providing a user‐friendly, generic API without sacrificing performance.
Projective Unsupervised Flexible Embedding with Optimal Graph

Graph based dimensionality reduction techniques have been successfully applied to clustering and classification tasks. The fundamental basis of these algorithms is the constructed graph which dominates their performance. Usually, the graph is defined by the input affinity matrix. However, the affinity matrix is sub-optimal for dimension reduction as there is much noise in the data. To address this issue, we propose the projective unsupervised flexible embedding with optimal graph (PUFE-OG) model. We build an optimal graph by adjusting the affinity matrix. To tackle the out-of-sample problem, we employ a linear regression term to learn a projection matrix. The optimal graph and projection matrix are jointly learned by integrating the manifold regularizer and regression residual into a unified model. An efficient algorithm is derived to solve the challenging model. The experimental results on several public benchmark datasets demonstrate that the presented PUFE-OG outperforms other state-of-the-art methods.
Symmetric Pseudo-Random Matrices

We consider the problem of generating symmetric pseudo-random sign (±1) matrices based on the similarity of their spectra to Wigner’s semicircular law. Using binary <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>-sequences (Golomb sequences) of lengths <inline-formula> <tex-math notation="LaTeX">$n=2^{m}-1$ </tex-math></inline-formula>, we give a simple explicit construction of circulant <inline-formula> <tex-math notation="LaTeX">$n \times n$ </tex-math></inline-formula> sign matrices and show that their spectra converge to the semicircular law when <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> grows. The Kolmogorov complexity of the proposed matrices equals to that of Golomb sequences and is at most <inline-formula> <tex-math notation="LaTeX">$2 {\mathrm{log}}_{2}(n)$ </tex-math></inline-formula> bits.
Perils of using CQIC in LTE network and a quick fix with delayed ACK

In this poster, we revisit the CQIC congestion control and adapt the implementation from 3G/QUIC semantic to LTE/TCP. We identify the reason for performance degradation of End-to-End (E2E) high data rate connection-oriented download in LTE Acknowledgement Mode (AM, which is turned on by default) and further recommend to turn on the Delayed Acknowledgement (DelAck) feature for TCP-CQIC, or more generally, for all the high speed E2E connections in LTE-AM mode. Finally, an NS3 simulation of TCP-CQIC and TCP-CQIC-DelAck with TCP Cubic and Westwood as a bench mark is made.
Power Allocation for OFDM Over Multi-scale Multi-lag Channels

Underwater acoustic (UWA) signal is wideband in nature and suffers doubly selective fading in time and frequency. In the presence of relative motion, a typical UWA channel can be described by a multiscale multilag (MSML) model. To compensate the scaling effect of UWA channels, many UWA communication systems employ a signal-resampling operation by a single scale at the front end of the receiver. For orthogonal frequency division multiplexing systems, since the path scales are different from each other, the resampling can alleviate but not clean out the intercarrier interference (ICI) resulting from the MSML channel. In this paper, we first describe the resampled signal by an equivalent MSML model with residual time scales, which are much smaller than that of the original MSML channel. With the given statistical parameters of the equivalent MSML channel, the closed-form expressions of the average subchannel gains and ICI coefficients are derived. Based on the ICI coefficients, we derive the analytical expression of a lower bound on the average achievable rate of the system as a function of the power allocation. We then investigate the power allocation to improve the lower bound on the achievable rate. Our key idea is that, on subcarriers whose ICIs dominate the additive noise, nothing is transmitted to avoid low energy efficiency. After proving that the ICI coefficient increases monotonically as the subcarrier frequency rises, we propose an ON–OFF uniform power allocation method, in which subcarriers with odd indices keep inactive starting from a certain index to avoid ICI. The performance of the proposed power allocation is evaluated via numerical simulations, whose results show that the proposed method outperforms the existing methods when the residual time scales cannot be neglected.
Distributed Averaging of Exponential-Class Densities With Discrete-Time Event-Triggered Consensus

The paper addresses discrete-time event-driven consensus on exponential-class probability densities (including Gaussian, binomial, Poisson, Rayleigh, Wishart, Inverse Wishart, and many other distributions of interest) completely specified by a finite-dimensional vector of so-called natural parameters. First, it is proved how such exponential classes are closed under Kullback-Leibler fusion (average), and how the latter is equivalent to a weighted arithmetic average over the natural parameters. Then, a novel event-driven transmission strategy is proposed in order to trade off the data-communication rate and, hence, energy consumption, versus consensus speed and accuracy. A theoretical analysis of the convergence properties of the proposed algorithm is provided by exploiting the Fisher metric as a local approximation of the Kullback-Leibler divergence. Some numerical examples are presented in order to demonstrate the effectiveness of the proposed event-driven consensus. It is expected that the latter can be successfully exploited for energy- and/or bandwidth-efficient networked state estimation.
A machine learning pipeline for multiple sclerosis course detection from clinical scales and patient reported outcomes

In this work we present a machine learning pipeline for the detection of multiple sclerosis course from a collection of inexpensive and non-invasive measures such as clinical scales and patient-reported outcomes. The proposed analysis is conducted on a dataset coming from a clinical study comprising 457 patients affected by multiple sclerosis. The 91 collected variables describe patients mobility, fatigue, cognitive performance, emotional status, bladder continence and quality of life. A preliminary data exploration phase suggests that the group of patients diagnosed as Relapsing-Remitting can be isolated from other clinical courses. Supervised learning algorithms are then applied to perform feature selection and course classification. Our results confirm that clinical scales and patient-reported outcomes can be used to classify Relapsing-Remitting patients.
Ready, set, verify! applying hs-to-coq to real-world Haskell code (experience report)

Good tools can bring mechanical verification to programs written in mainstream functional languages. We use hs-to-coq to translate significant portions of Haskell’s containers library into Coq, and verify it against specifications that we derive from a variety of sources including type class laws, the library’s test suite, and interfaces from Coq’s standard library. Our work shows that it is feasible to verify mature, widely-used, highly optimized, and unmodified Haskell code. We also learn more about the theory of weight-balanced trees, extend hs-to-coq to handle partiality, and – since we found no bugs – attest to the superb quality of well-tested functional code.
Power Grid Reduction by Sparse Convex Optimization

With the dramatic increase in the complexity of modern integrated circuits (ICs), direct analysis and verification of IC power distribution networks (PDNs) have become extremely computationally expensive. Various power grid reduction methods are proposed to reduce the grid size for fast verification and simulation but usually suffer from poor scalability. In this paper, we present a convex optimization-based framework for power grid reduction. Edge sparsification is formulated as a weighted convex optimization problem with sparsity-inducing penalties, which provides an accurate control over the final error. A greedy coordinate descent (GCD) method with optimality guarantee is proposed along with a novel coordinate selection strategy to improve the efficiency and accuracy of edge sparsification. Experimental results demonstrate that the proposed approach achieves better performance compared with traditional gradient descent methods, and 98% accuracy and good sparsity for industrial benchmarks.