Miracle-dz/UniFAR-FTUs huggingface dataset:
CS-CNN: Enabling Robust and Efficient Convolutional Neural Networks Inference for Internet-of-Things Applications

Recent advances have shown that convolutional neural networks (CNNs) perform excellent in the tasks of image classification and face recognition when the size of data sets is sufficiently large, i.e., over hundreds of thousands training images. Nevertheless, when public data sets are not suitable for training the model for new application scenarios, it is painful to obtain sufficient training examples, especially when the samples have to be labeled manually. Besides, training and inference using CNNs requires significant resources of energy, computation, and memory usage. Therefore, implanting deep CNN models trained and executed on high performance GPU clusters to resource constrained devices, i.e., Internet of Things (IoT) devices, which have permeated into every aspect of modern life, is not appropriate and impractical. Compression technology is an important and popularly used tool to accelerate the training and inference of the CNN models. In this paper, we aim for a step forward in this area: we propose a new compressed CNN model termed CS-CNN for image classification by incorporating the theory of compressive sensing at the input layer of the CNN models to both reduce the resources consumption (evaluated as computation time in this paper) and a required number of training samples. According to our extensive evaluations on the multiple public data sets for deep learning tasks, e.g., MINST and CIFAR-10, using different metrics, we illustrate that the CS-CNN is able to speed up the process of training and inference by a factor of magnitude. Meanwhile, it achieves higher classification accuracy compared with the traditional large CNN models when the size of training database is small.
Evaluating the efficiency of continuous testing during test-driven development

Continuous testing is a novel feature within modern programming environments, where unit tests constantly run in the background providing early feedback about breaking changes. One of the more challenging aspects of such a continuous testing tool is choosing the heuristic which selects the tests to run based on the changes recently applied. To help tool builders select the most appropriate test selection heuristic, we assess their efficiency in a continuous testing context. We observe on two small but representative cases that a continuous testing tool generates significant reductions in number of tests that need to be executed. Nevertheless, these heuristics sometimes result in false negatives, thus in rare occasions discard pertinent tests.
DTL-RnB: Algorithms and Tools for Summarizing the Space of DTL Reconciliations

Phylogenetic tree reconciliation is an important technique for reconstructing the evolutionary histories of species and genes and other dependent entities. Reconciliation is typically performed in a maximum parsimony framework and the number of optimal reconciliations can grow exponentially with the size of the trees, making it difficult to understand the solution space. This paper demonstrates how a small number of reconciliations can be found that collectively contain the most highly supported events in the solution space. While we show that the formal problem is NP-complete, we give a <inline-formula><tex-math notation="LaTeX">$1-\frac{1}{e}$</tex-math><alternatives> <inline-graphic xlink:href="libeskindhadas-ieq1-2537319.gif"/></alternatives></inline-formula> approximation algorithm, experimental results that indicate its effectiveness, and the new DTL-RnB software tool that uses our algorithms to summarize the space of optimal reconciliations (<monospace><uri>www.cs.hmc.edu/dtlrnb</uri></monospace>).
Recruitment and enrollment of African Americans into health promoting programs: the effects of health promoting programs on cardiovascular disease risk study

ABSTRACT Objectives: Randomized controlled trials (RCT) often employ multiple recruitment methods to attract participants, however, special care must be taken to be inclusive of under-represented populations. We examine how recruiting from an existing observational study affected the recruitment of African Americans into a RCT that included yoga-based interventions. In particular, we report the recruitment success of The Effects of Health Promoting Programs (HPP) on Cardiovascular Disease Risk (NCT02019953), the first yoga-based clinical trial to focus only on African Americans. Design: To recruit participants, a multifaceted recruitment strategy was implemented exclusively in the Jackson Heart Study (JHS) cohort. The HPP recruited from the JHS cohort using direct mailings, signs and flyers placed around JHS study facilities, and through JHS annual follow-up interviews. Results: Enrollment into HPP was open to all active JHS participants that were eligible to return for the third clinic exam (n = 4644). The target sample size was 375 JHS participants over a 24 month recruitment and enrollment period. From the active members of the JHS cohort, 503 were pre-screened for eligibility in HPP. More than 90% of those pre-screened were provisionally eligible for the study. The enrollment goal of 375 was completed after a 16-month enrollment period with over 25% (n = 97) of the required sample size enrolling during the second month of recruitment. Conclusions: The findings show that participants in observational studies can be successfully recruited into RCT. Observational studies provide researchers with a well-defined population that may be of interest when designing clinical trials. This is particularly useful in the recruitment of a high-risk, traditionally underrepresented populations for non-pharmacological clinical trials where traditional recruitment methods may prolong enrollment periods and extend study budgets.
Rapid avatar capture and simulation using commodity depth sensors

We demonstrate a method of acquiring a 3D model of a human using commodity scanning hardware and then controlling that 3D figure in a simulated environment in only a few minutes. The model acquisition requires four static poses taken at 90° angles relative to each other. The 3D model is then given a skeleton and smooth binding information necessary for control and simulation. The 3D models that are captured are suitable for use in applications where recognition and distinction among characters by shape, form, or clothing is important, such as small group or crowd simulations or other socially oriented applications. Because of the speed at which a human figure can be captured and the low hardware requirements, this method can be used to capture, track, and model human figures as their appearances change over time. Copyright © 2014 John Wiley & Sons, Ltd.
Cloud-Scale Entity Resolution: Current State and Open Challenges

Entity resolution (ER) is a process to identify records in information systems, which refer to the same real-world entity. Because in the two recent decades the data volume has grown so large, parallel techniques are called upon to satisfy the ER requirements of high performance and scalability. The development of parallel ER has reached a relatively prosperous stage, and has found its way into several applications. In this work, we first comprehensively survey the state of the art of parallel ER approaches. From the comprehensive overview, we then extract the classification criteria of parallel ER, classify and compare these approaches based on these criteria. Finally, we identify open research questions and challenges and discuss potential solutions and further research potentials in this field.
Frustration and Anger in Games

Frustration, anger, and aggression have important consequences for economic and social behavior, concerning for example monopoly pricing, contracting, bargaining, traffic safety, violence, and politics. Drawing on insights from psychology, we develop a formal approach to exploring how frustration and anger, via blame and aggression, shape interaction and outcomes in economic settings.
The Neuroleptic Hypothesis: Study of the Covariation of Extrapyramidal and Therapeutic Drug Effects

Summary A therapeutic trial with chlorpromazine was conducted with a homogeneous (for age and sex) group of recently admitted schizophrenic patients. Extrapyramidal effects were measured through quantitative analysis of digital tremor, after four days of fixed-dose treatment. Assessment of treatment efficacy was based on Brief Psychiatric Rating Scale ratings, done at the end of four weeks' treatment. Those patients whose tremor was least affected by drug were most likely to benefit from the treatment. Implications of this negative correlation for our understanding of the neuroleptic hypothesis and the closely associated dopamine hypothesis of schizophrenia are discussed.
Assessment of plant growth attributes, bioaccumulation, enrichment, and translocation of heavy metals in water lettuce (Pistia stratiotes L.) grown in sugar mill effluent

ABSTRACT This study was conducted to assess the pollutant uptake capability of water lettuce (Pistia stratiotes L.) in terms of bioaccumulation, enrichment, and translocation of heavy metals grown in sugar mill effluent. Results showed that the maximum fresh weight (328.48 ± 2.04 gm kg−1), total chlorophyll content (2.13 ± 2.03 mg g−1 fwt), and relative growth rate, RGR (11.89 gg−1 d−1) of P. stratiotes were observed at 75% concentration of the sugar mill effluent after 60 days of phytoremediation experiment. The bioaccumulation factor (BF) of different heavy metals was greater than 1 with 50% and 75% concentrations of sugar mill effluent and this indicated that P. stratiotes was hyperaccumulator or phytoremediator of these metals. The enrichment factor (EF < 2 for Cu, Fe, Cr, Pb, Zn, and Mn) and (EF > 2 for Cd) indicated that P. stratiotes mineral enrichment deficient and it moderately enriched the different heavy metals. Moreover, translocation factor (TF) was less than 1 which indicated the low mobility of metals in different parts (root and leaves) of P. stratiotes after phytoremediation. Therefore, P. stratiotes can be used for phytotreatment of sugar mill effluent up to 50% to 75% concentrations and considered as hyperaccumulator aquatic plant for different heavy metals and other pollutants from the contaminated effluents.
Effect of Electrostatic Tactile Feedback on Accuracy and Efficiency of Pan Gestures on Touch Screens

Recently, many studies examined electrostatic tactile feedback on touch screens to enrich interaction experience. However, it is unclear as to whether added tactile feedback during a sliding process increases the accuracy of pan gestures with velocity constraints. In this study, a custom-designed electrostatic tactile display was considered. Initially, the accuracy and efficiency of pan gestures were compared under two conditions, namely with and without electrostatic tactile feedback. This was followed by exploring the evolution of completion time (CT) with different indices of difficulties (ID). Experimental results with 12 participants indicated that the accuracy and completion time of pan gestures with added tactile feedback significantly exceeded those without tactile feedback. Furthermore, the relationship between CT and ID satisfied Fitts' Law with a correlation coefficient exceeding 0.9. Based on the findings, a “Tactile Fruit Sorting” game was designed, and subjective and objective evaluations were conducted. The results confirmed that the added tactile feedback enhanced both user performance and interest with respect to the game.
Do behavioural defence mechanisms explain different levels of trematode infections in congeneric hosts?

Abstract Susceptibility and tolerance to parasite infection vary greatly between host species. The congeneric isopod species Austridotea annectens and Austridotea lacustris often occur in sympatry and can both serve as intermediate hosts for the trematode Maritrema poulini. However, the intensity and prevalence of infections vary greatly in natural populations, with A. annectens often being heavily infected and A. lacustris rarely being infected. To shed light on the factors that may be involved in infection avoidance in A. lacustris, 100 isopods were collected and experimentally exposed to M. poulini cercariae. To examine for potential behavioural mechanisms, we used carbonated water as a paralysing agent to temporarily stop any movement by the isopods, and exposed paralysed isopods to cercariae. In the experiments, none of the individuals that were exposed to the parasite were found to be infected, although some cercariae seemed to have penetrated isopod hosts. Behavioural defence mechanisms do not seem to explain the different infection levels between A. lacustris and A. annectens, suggesting a physiological, possibly immunological, factor may be present. At the ecosystem level, this suggests a potential dilution effect caused by this low-competency host, and its effects on parasite transmission dynamics should be investigated.
Orthogonal Instruction Processing: An Alternative to Lightweight VLIW Processors

We propose a new processor architecture called Orthogonal Instruction Processing (OIP). Contrary to Very Long Instruction Word (VLIW) decoding, we propose to orthogonally decode the sub-instruction words of each Functional Unit (FU) instead. Hereby, the OIP architecture is able to reduce the overall machine code size of VLIW programs significantly. We willshow analytically as well as experimentally that, compared to a VLIW processor, the savings in instruction memory size easily compensate the overhead of one separate branch unit needed for each FU.For the analytical analysis, a mathematical model of hardware costs of an OIP processor is developed and compared to a conventional VLIW processor. In addition, we compare the code size of selected representative programs of the new processor architecture and show big savings of program memory. Here, the instruction memory requirements can be decreased by a factor of0.465. This decrease in instruction memory, despite the discussed overhead, leads to savings in the overall hardware costs of one processor by a factor of 0.989.
Quality assurance device for four‐dimensional IMRT or SBRT and respiratory gating using patient‐specific intrafraction motion kernels

Emerging technologies such as four‐dimensional computed tomography (4D CT) and implanted beacons are expected to allow clinicians to accurately model intrafraction motion and to quantitatively estimate internal target volumes (ITVs) for radiation therapy involving moving targets. In the case of intensity‐modulated (IMRT) and stereotactic body radiation therapy (SBRT) delivery, clinicians must consider the interplay between the temporal nature of the modulation and the target motion within the ITV. A need exists for a 4D IMRT/SBRT quality assurance (QA) device that can incorporate and analyze customized intrafraction motion as it relates to dose delivery and respiratory gating. We built a 4D IMRT/SBRT prototype device and entered (X, Y, Z)(T) coordinates representing a motion kernel into a software application that transformed the kernel into beam‐specific two‐dimensional (2D) motion “projections,” previewed the motion in real time, and drove a precision X–Y motorized device that had, atop it, a mounted planar IMRT QA measurement device. The detectors that intersected the target in the beam's‐eye‐view of any single phase of the breathing cycle (a small subset of all the detectors) were defined as “target detectors” to be analyzed for dose uniformity between multiple fractions. Data regarding the use of this device to quantify dose variation fraction‐to‐fraction resulting from target motion (for several delivery modalities and with and without gating) have been recently published. A combined software and hardware solution for patient‐customized 4D IMRT/ SBRT QA is an effective tool for assessing IMRT delivery under conditions of intrafraction motion. The 4D IMRT QA device accurately reproduced the projected motion kernels for all beam's‐eye‐view motion kernels. This device has been proved to • effectively quantify the degradation in dose uniformity resulting from a moving target within a static planning target volume, and • integrate with a commercial respiratory gating system to ensure that the system is working effectively. Such a device is discussed as a potential tool to optimize the gating duty cycle to maximize delivery efficiency while minimizing dose variability. PACS numbers: 87.50. Gi, 87.53. Dq, 87.53. Kn, 87.53. Mr, 87.53. Tf, 87.56. Fc, 87.58. Sp
Accuracy of relocation, evaluation of geometric uncertainties and clinical target volume (CTV) to planning target volume (PTV) margin in fractionated stereotactic radiotherapy for intracranial tumors using relocatable Gill‐Thomas‐Cosman (GTC) frame

The present study is aimed at determination of accuracy of relocation of Gill‐Thomas‐Cosman frame during fractionated stereotactic radiotherapy. The study aims to quantitatively determine the magnitudes of error in anteroposterior, mediolateral and craniocaudal directions, and determine the margin between clinical target volume to planning target volume based on systematic and random errors. Daily relocation error was measured using depth helmet and measuring probe. Based on the measurements, translational displacements in anteroposterior (z), mediolateral (x), and craniocaudal (y) directions were calculated. Based on the displacements in x, y and z directions, systematic and random error were calculated and three‐dimensional radial displacement vector was determined. Systematic and random errors were used to derive CTV to PTV margin. The errors were within ± 2 mm in 99.2% cases in anteroposterior direction (AP), in 99.6% cases in mediolateral direction (ML), and in 97.6% cases in craniocaudal direction (CC). In AP, ML and CC directions, systematic errors were 0.56, 0.38, 0.42 mm and random errors were 1.86, 1.36 and 0.73 mm, respectively. Mean radial displacement was 1.03 mm ± 0.34. CTV to PTV margins calculated by ICRU formula were 1.86, 1.45 and 0.93 mm; by Stroom's formula they were 2.42, 1.74 and 1.35 mm; by van Herk's formula they were 2.7, 1.93 and 1.56 mm (AP, ML and CC directions). Depth helmet with measuring probe provides a clinically viable way for assessing the relocation accuracy of GTC frame. The errors were within ± 2 mm in all directions. Systematic and random errors were more along the anteroposterior axes. According to the ICRU formula, a margin of 2 mm around the tumor seems to be adequate. PACS number: 87.55. ‐x
Capturing the multifactorial nature of ARDS – “Two‐hit” approach to model murine acute lung injury

Severe acute respiratory distress syndrome (ARDS) presents typically with an initializing event, followed by the need for mechanical ventilation. Most animal models of ALI are limited by the fact that they focus on a singular cause of acute lung injury (ALI) and therefore fail to mimic the complex, multifactorial pathobiology of ARDS. To better capture this scenario, we provide a comprehensive characterization of models of ALI combining two injuries: intra tracheal (i.t.) instillation of LPS or hypochloric acid (HCl) followed by ventilator‐induced lung injury (VILI). We hypothesized, that mice pretreated with LPS or HCl prior to VILI and thus receiving a (“two‐hit injury”) will sustain a superadditive lung injury when compared to VILI. Mice were allocated to following treatment groups: control with i.t. NaCl, ventilation with low peak inspiratory pressure (PIP), i.t. HCl, i.t. LPS, VILI (high PIP), HCl i.t. followed by VILI and LPS i.t. followed by VILI. Severity of injury was determined by protein content and MPO activity in bronchoalveolar lavage (BAL), the expression of inflammatory cytokines and histopathology. Mice subjected to VILI after HCl or LPS instillation displayed augmented lung injury, compared to singular lung injury. However, mice that received i.t. LPS prior to VILI showed significantly increased inflammatory lung injury compared to animals that underwent i.t. HCl followed by VILI. The two‐hit lung injury models described, resulting in additive but differential acute lung injury recaptures the clinical relevant multifactorial etiology of ALI and could be a valuable tool in translational research.
Neuromorphic synapses with reconfigurable voltage-gated dynamics for biohybrid neural circuits

Chemical synapses are the main link between neurons in biological neural networks, giving neural cells their special ability to communicate action potentials with great temporal precision. As such, neuromorphic synapses could serve as critical units for implementing biohydrid circuits interfacing biological and silicon neurons. Here we describe a biophysical model of a chemical synapse with reconfigurable pre-synaptic and post-synaptic voltage-gated dynamics implemented on a neuromorphic VLSI chip, and evaluate its versatility with measurements from the chip reproducing response characteristics from ionotropic inhibitory GABAa and excitatory NMDA synapses. We also discuss applications of the reconfigurable dynamic clamp capabilities of the neuromorphic synapse for interacting neuronal populations and biological neurons to establish biohybrid circuits ranging from the single-cell to the population level with intra- and extra-cellular interfaces, respectively.
Outage probability of energy harvesting relay systems under unreliable backhaul connections

In this paper, the performance of energy harvesting systems in the presence of unreliable backhaul links is investigated over independent but not necessarily identically distributed (i.n.i.d.) Nakagami-m fading channels. In particular, the energy-constrained relay uses the amount of harvested energy from the best small-cell transmitter based on time switching-based relaying (TRS) protocol to process for the next hop transmission. We derived the closed-form expression of the outage probability and the asymptotic expression in high signal-to-noise ratio (SNR) regime. Our results show that under the unreliable backhaul links the outage probability yields the error-floor in the high SNR regime which demonstrates the significant impact of the backhaul unreliability.
Numerical solution of the infinite-dimensional LQR problem and the associated Riccati differential equations

Abstract The numerical analysis of linear quadratic regulator design problems for parabolic partial differential equations requires solving Riccati equations. In the finite time horizon case, the Riccati differential equation (RDE) arises. The coefficient matrices of the resulting RDE often have a given structure, e.g., sparse, or low-rank. The associated RDE usually is quite stiff, so that implicit schemes should be used in this situation. In this paper, we derive efficient numerical methods for solving RDEs capable of exploiting this structure, which are based on a matrix-valued implementation of the BDF and Rosenbrock methods. We show that these methods are suitable for large-scale problems by working only on approximate low-rank factors of the solutions. We also incorporate step size and order control in our numerical algorithms for solving RDEs. In addition, we show that within a Galerkin projection framework the solutions of the finite-dimensional RDEs converge in the strong operator topology to the solutions of the infinite-dimensional RDEs. Numerical experiments show the performance of the proposed methods.