Miracle-dz/UniFAR-FTUs huggingface dataset:
The possibilities of embroidered passive UHF RFID textile tags as wearable moisture sensors

Moisture measurements of the body can be used for healthcare purposes as well as for helping in exercising. In this paper, the suitability of passive UHF RFID technology for moisture sensing is investigated. The technology has a great potential in wearable, comfortable, and wireless moisture sensing systems, although it is not originally used for sensing purposes. In our study, the tag antenna outlines are embroidered on a fabric substrate, the tag ICs are attached by embroidery or with conductive glue, and the tag performance as a moisture sensor is evaluated by wireless measurements. All tags attained peak read ranges of about 7–8 meters, which is well enough for wireless moisture sensors. The effects of moisture on the tag response were noticeable through a frequency range of 900–980 MHz and the tag performance was excellent also when wet. Thus, the achieved results indicate high potential of passive UHF RFID textile tags in moisture sensing and embroidery as a textile tag antenna and antenna-IC interconnection fabrication method.
Hybrid wireless network on chip: A new paradigm in multi-core design

The performance benefits of conventional network-on-chip (NoC) architectures are limited by the high latency and energy dissipation in long distance multihop communication between embedded cores. This limitation of conventional NoC architectures can be addressed by introducing long-range, high bandwidth and low power wireless links between the distant cores. Using miniaturized on-chip antennas as an enabling technology, wireless NoCs (WiNoCs) can be designed. In this paper, we elaborate the design principles of a hybrid WiNoC. It is demonstrated that a WiNoC outperforms its wireline counterpart and the performance gain is more significant for larger system size.
Twelve polymorphic microsatellites in Oriental river prawn, Macrobrachium nipponense

Oriental river prawn, Macrobrachium nipponense, is a commercially important freshwater prawn species in China, Japan, Korea and Vietnam. Due to overfishing for food, the wild stocks M. nipponense are endangered. Twenty microsatellite loci were isolated from the M. nipponense. Twelve of these loci were polymorphic (seven to 16 alleles per locus), with expected heterozygosity ranging from 0.68 to 0.86 (n = 48). These polymorphic loci provide a valuable tool for assessing genetic diversity of wild and cultured populations.
Energy-Efficient Channel-Dependent Cooperative Relaying for the Multiuser SC-FDMA Uplink

In this paper, we exploit the benefits of combining the diversity gains that arise from cooperation, multiple propagation paths, and opportunistic relaying (OR) of multiple users. Our goal is to improve the energy efficiency of the amplify-and forward (AF) single-relay-assisted single-carrier frequency-division multiple-access (SC-FDMA) uplink, where the single relay considered may support a single user or may be shared by multiple users who communicate over dispersive channels subject to large-scale fading. Based on the proposed amalgam of single-tap frequency-domain equalization (FDE) and a diversity-combining-aided receiver that relies on the minimum mean-square error (MMSE) criterion, three different relay selection schemes designed for either single-user or multiuser relaying scenarios are investigated, when combined with source/relay power sharing, which employ imperfect power control. Our results demonstrate that, at a bit error ratio (BER) of 10-4, the proposed receiver can save 2 dB power by achieving a higher cooperative diversity gain than the conventional receiver. Moreover, a beneficial energy efficiency improvement may be achieved when the cooperative regime operates at Eb/N0<; 0. Most importantly, when the shadowing variance is increased from 4 dB to 8 dB, the energy consumption gain gleaned from our multiuser and multiaccess relay selection schemes may increase to 4~9, compared with the direct transmission in the absence of shadowing at Eb|N0 = -10 dB.
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks

Recently, Convolutional Neural Networks (ConvNets) have shown promising performances in many computer vision tasks, especially image-based recognition. How to effectively use ConvNets for video-based recognition is still an open problem. In this paper, we propose a compact, effective yet simple method to encode spatio-temporal information carried in 3D skeleton sequences into multiple 2D images, referred to as Joint Trajectory Maps (JTM), and ConvNets are adopted to exploit the discriminative features for real-time human action recognition. The proposed method has been evaluated on three public benchmarks, i.e., MSRC-12 Kinect gesture dataset (MSRC-12), G3D dataset and UTD multimodal human action dataset (UTD-MHAD) and achieved the state-of-the-art results.
Supplementary Text: Capturing Heterogeneity in Gene Expression Studies Nested Ks-tests: a Procedure to Test Whether a Procedure Is Valid

The false discovery rate (FDR) has been discussed extensively and it has been pointed out that the distribution of the null p-values must be " correct " or conservative for FDR estimation or any other standard statistical significance measure to behave properly. What is meant for distribution of the null p-values to be correct is that they are Uniformly distributed in the interval (0,1). The null p-values are have a conservative distribution or they are pushed towards 1 relative to the Uniform(0,1). P-values are constructed to have the Uniform distribution property under the null hypothesis, and if this cannot be done exactly the conservative version is calculated [1]. In a simulation study where the right answer is known, there is no off-the-shelf approach to test whether the null p-values have a proper distribution. In this study, we use a Kolmogorov-Smirnov (KS) test on the set of null p-values for deviation from the Uniform. However, we want to test whether this is true over many repeated simulations to avoid " getting lucky " on one particular simulated data set. If the set of null p-values are Uniform, then the p-value resulting from the KS test should also follow the Uniform distribution. Therefore, by examining the KS test p-values over all simulations, we can again apply a KS test to verify that these are Uniformly distributed. Here we have employed this nested KS test to compare the relative behavior of each multiple testing procedure discussed. If the quantiles of the KS test p-values follow the diagonal line in a quantile-quantile plot against the quantiles of the Uniform distribution, then this is very strong evidence that the p-values resulting from the procedure are " correct. " 1
Techniques for Power-Aware Hardware Synthesis from Concurrent Action Oriented Specifications

Specification of a concurrent system using CAOS (Concurrent Action Oriented Specifications) (CAOS) as illustrated by Bluespec Inc.’s Bluespec System Verilog provides a high abstraction level, effective concurrency management through atomicity, and powerful compilation to efficient RTL hardware. In this paper, we present two algorithms that make CAOS to RTL synthesis power-aware and produce RTL that can be synthesized into hardware competitive in terms of power/area/slack trade-off against the well-known industrial-strength power optimization RTL to gate-level synthesis tools. Our algorithms are simple and intuitive because the higher abstraction level allows one to easily analyze certain exploits that exist in the model. Discovering these opportunities at the RTL and lower levels require a much more involved circuit or gate structure analysis. We show through extensive experimental results that when a CAOS specification is compiled using our algorithms, the resulting hardware (without any additional gate-level power optimizations) has power/area/latency numbers comparable to those obtained by using existing tools for applying gate-level power minimization techniques. Also, the experiments show that in the absence of gate-level power optimizers such as Magma Blast Power or Synopsys Power Compiler, these algorithms show significant power reduction over standard Bluespec Compiler (BSC) for CAOS to RTL generation. And most importantly, our algorithms allow analyzing the affects of various power saving techniques in the early phases of the design cycle, thus avoiding the need to perform logic synthesis for such an analysis.
Absorption Distribution Metabolism Excretion and Toxicity Property Prediction Utilizing a Pre-Trained Natural Language Processing Model and Its Applications in Early-Stage Drug Development

Machine learning techniques are extensively employed in drug discovery, with a significant focus on developing QSAR models that interpret the structural information of potential drugs. In this study, the pre-trained natural language processing (NLP) model, ChemBERTa, was utilized in the drug discovery process. We proposed and evaluated four core model architectures as follows: deep neural network (DNN), encoder, concatenation (concat), and pipe. The DNN model processes physicochemical properties as input, while the encoder model leverages the simplified molecular input line entry system (SMILES) along with NLP techniques. The latter two models, concat and pipe, incorporate both SMILES and physicochemical properties, operating in parallel and with sequential manners, respectively. We collected 5238 entries from DrugBank, including their physicochemical properties and absorption, distribution, metabolism, excretion, and toxicity (ADMET) features. The models’ performance was assessed by the area under the receiver operating characteristic curve (AUROC), with the DNN, encoder, concat, and pipe models achieved 62.4%, 76.0%, 74.9%, and 68.2%, respectively. In a separate test with 84 experimental microsomal stability datasets, the AUROC scores for external data were 78% for DNN, 44% for the encoder, and 50% for concat, indicating that the DNN model had superior predictive capabilities for new data. This suggests that models based on structural information may require further optimization or alternative tokenization strategies. The application of natural language processing techniques to pharmaceutical challenges has demonstrated promising results, highlighting the need for more extensive data to enhance model generalization.
Pitch extraction in Human-Robot interaction

We present a system for real-time fundamental frequency, i. e. pitch, extraction on a humanoid robot. The system extracts pitch using an 8 channel microphone array mounted on the Honda humanoid robot in a realistic Human-Robot interaction scenario. The main building blocks of the system are a multi-channel signal enhancement followed by robust pitch extraction and tracking. The signal enhancement is based on 8 channel Geometric Source Separation. For the pitch extraction the signal is first transformed with a Gammatone filter bank into the frequency domain. Next a histogram of zero crossing distances is calculated from all filter bank signals. During the calculation of the histogram spurious side peaks resulting from harmonics and sub-harmonics of the true fundamental frequency are inhibited. The resulting histogram then serves as input to a grid based Bayesian tracker which deploys Bayesian filtering in a forward step and Bayesian smoothing in a backward step on a 100ms time window. We demonstrate the performance of the system in a scenario where male and female speakers utter different phrases while standing at a normal interaction distance to the robot. For the evaluation we compare the pitch tracking results once obtained from a clean headset signal and once from the signals obtained from the robot. The results show that the tracking performance only degrades to a small extent in the realistic interaction scenario compared to the headset recordings.
Perceptual interaction of local motion signals

Motion signals are a rich source of information used in many everyday tasks, such as segregation of objects from background and navigation. Motion analysis by biological systems is generally considered to consist of two stages: extraction of local motion signals followed by spatial integration. Studies using synthetic stimuli show that there are many kinds and subtypes of local motion signals. When presented in isolation, these stimuli elicit behavioral and neurophysiological responses in a wide range of species, from insects to mammals. However, these mathematically-distinct varieties of local motion signals typically co-exist in natural scenes. This study focuses on interactions between two kinds of local motion signals: Fourier and glider. Fourier signals are typically associated with translation, while glider signals occur when an object approaches or recedes. Here, using a novel class of synthetic stimuli, we ask how distinct kinds of local motion signals interact and whether context influences sensitivity to Fourier motion. We report that local motion signals of different types interact at the perceptual level, and that this interaction can include subthreshold summation and, in some subjects, subtle context-dependent changes in sensitivity. We discuss the implications of these observations, and the factors that may underlie them.
Genomic prediction of coronary heart disease

Background Genetics plays an important role in coronary heart disease (CHD) but the clinical utility of a genomic risk score (GRS) relative to clinical risk scores, such as the Framingham Risk Score (FRS), is unclear. Methods We generated a GRS of 49,310 SNPs based on a CARDIoGRAMplusC4D Consortium meta-analysis of CHD, then independently tested this using five prospective population cohorts (three FINRISK cohorts, combined n=12,676, 757 incident CHD events; two Framingham Heart Study cohorts (FHS), combined n=3,406, 587 incident CHD events). Results The GRS was strongly associated with time to CHD event (FINRISK HR=1.74, 95% CI 1.61-1.86 per S.D. of GRS; Framingham HR=1.28, 95% CI 1.18-1.38), and was largely unchanged by adjustment for clinical risk scores or individual risk factors, including family history. Integration of the GRS with clinical risk scores (FRS and ACC/AHA13 score) improved prediction of CHD events within 10 years (meta-analysis C-index: +1.5-1.6%, P<0.001), particularly for individuals ≥60 years old (meta-analysis C-index: +4.6-5.1%, P<0.001). Men in the top 20% of the GRS had 3-fold higher risk of CHD by age 75 in FINRISK and 2-fold in FHS, and attaining 10% cumulative CHD risk 18y earlier in FINRISK and 12y earlier in FHS than those in the bottom 20%. Furthermore, high genomic risk was partially compensated for by low systolic blood pressure, low cholesterol level, and non-smoking. Conclusions A GRS based on a large number of SNPs substantially improves CHD risk prediction and encodes decades of variation in CHD risk not captured by traditional clinical risk scores.
High-pressure freezing provides insights into Weibel-Palade body biogenesis

The Weibel-Palade bodies (WPBs) of endothelial cells play an important role in haemostasis and the initiation of inflammation, yet their biogenesis is poorly understood. Tubulation of their major content protein, von Willebrand factor (VWF), is crucial to WPB function, and so we investigated further the relationship between VWF tubule formation and WPB formation in human umbilical vein endothelial cells (HUVECs). By using high-pressure freezing and freeze substitution before electron microscopy, we visualised VWF tubules in the trans-Golgi network (TGN), as well as VWF subunits in vesicular structures. Tubules were also seen in WPBs that were connected to the TGN by membranous stalks. Tubules are disorganised in the immature WPBs but during maturation we found a dramatic increase in the spatial organisation of the tubules and in organelle electron density. We also found coated budding profiles suggestive of the removal of missorted material after initial formation of these granules. Finally, we discovered that these large, seemingly rigid, organelles flex at hinge points and that the VWF tubules are interrupted at these hinges, facilitating organelle movement around the cell. The use of high-pressure freezing was vital in this study and it suggests that this technique might prove essential to any detailed characterisation of organelle biogenesis.
Hydrocarbon Vertical Continuity Evaluation in the Cretaceous Reservoirs of Azadegan Oilfield, Southwest of Iran: Implications for Reservoir Geochemistry

A collection of data obtained from analytical methods in geochemistry along with the reservoir engineering and geologic data were used to investigate the reservoir continuity in the Cretaceous Fahliyan, Gadavan, Kazhdumi and Sarvak reservoirs of the super‐giant Azadegan oilfield, SW Iran. The geochemical data indicate that the oil samples, with medium to high level of thermal maturity, have been generated from the anoxic marine marl/carbonate source rock(s). The Sargelu (Jurassic) and Garau (Cretaceous) formations are introduced as the main source rocks for the studied oils. The dendrogram obtained from the cluster analysis of high‐resolution gas chromatography data introduces two main oil groups including Fahliyan reservoir, and Kazhdumi along with Sarvak/Gadvan reservoirs. This is confirmed by C7 Halpern star diagram, indicating that, the light oil fraction from Fahliyan reservoir is distinct from the others. Also, different pressure gradient of the Fahliyan Formation (over‐pressured) relative to other reservoirs (normally‐pressured) show the presence of compartments. The relation between toluene/n‐heptane and n‐heptane/methylcyclohexane represents the compartmentalization due to maturation/evaporative fractionation for Fahliyan and water washing for other studied reservoirs. Also, the impermeable upper part of the Fahliyan Formation and thin interbedded shaly layers in the Kazhdumi, Sarvak and Gadvan formations have controlled reservoir compartmentalization.
Effects of Dietary l-Glutamine Supplementation on the Intestinal Function and Muscle Growth of Piglets

The aim of this study was to investigate the effects of dietary l-glutamine (Gln) supplementation on the morphology and function of the intestine and the growth of muscle in piglets. In this study, sixteen 21-day-old piglets were randomly divided into two groups: the Control group (fed a basal diet) and the Gln group (fed a basal diet supplemented with 0.81% Gln). Blood, gut, and muscle samples were collected from all piglets on Day 20 of the trial. Compared with the Control group, the supplementation of Gln increased (p < 0.05) the villus height, villus width, villus surface area, and villus height/crypt depth ratio of the small intestine. Furthermore, the supplementation of Gln increased (p < 0.05) total protein, total protein/DNA, and RNA/DNA in both the jejunum and ileum. It also increased (p < 0.05) the concentrations of carnosine and citrulline in the jejunal mucosa, as well as citrulline and cysteine concentrations in the ileum. Conversely, Gln supplementation decreased (p < 0.05) Gln concentrations in both the jejunum and ileum, along with β-aminoisobutyric acid and 1-Methylhistidine concentrations, specifically in the ileum. Subsequent research revealed that Gln supplementation increased (p < 0.05) the mRNA levels for glutathione-S-transferase omega 2 and interferon-β in the duodenum. In addition, Gln supplementation led to an increase (p < 0.05) in the number of Lactobacillus genus in the colon, but a decrease (p < 0.05) in the level of HSP70 in the jejunum and the activity of diamine oxidase in plasma. Also, Gln supplementation reduced (p < 0.05) the mRNA levels of glutathione-S-transferase omega 2 and interferon stimulated genes, such as MX1, OAS1, IFIT1, IFIT2, IFIT3, and IFIT5 in both the jejunum and ileum, and the numbers of Clostridium coccoides, Enterococcus genus, and Enterobacterium family in the colon. Moreover, Gln supplementation enhanced (p < 0.05) the concentrations of total protein, RNA/DNA, and total protein/DNA ratio in the longissimus dorsi muscle, the concentrations of citrulline, ornithine, arginine, and hydroxyproline, and the mRNA level of peptide transporter 1, while reducing the contents of hydrogen peroxide and malondialdehyde and the mRNA level of glutathione-S-transferase omega 2 in the longissimus dorsi muscle. In conclusion, dietary Gln supplementation can improve the intestinal function of piglets and promote the growth of the longissimus dorsi muscle.
Contrast-enhanced transcranial color-coded duplex sonography in ischemic cerebrovascular disease.

BACKGROUND AND PURPOSE Echo contrast agents have been shown to provide conclusive examinations in most patients with insufficient ultrasound penetration through the temporal bone. We investigated the diagnostic value of contrast-enhanced (CE) transcranial color-coded duplex sonography (TCCD) in patients with ischemic cerebrovascular disease and insufficient temporal windows and evaluated TCCD criteria that predict whether CE-TCCD studies may become conclusive. METHODS Thirty-three patients presenting with ischemic strokes (n = 21) and transient ischemic attacks (n = 12) were investigated. Extracranial color duplex imaging showed normal findings in 24 patients, eight > or = 70% stenoses and one occlusion of the carotid arteries in 8 patients, and severe occlusive disease of both vertebral arteries in 1 patient. Seven carotid stenoses and vertebral artery obstructions were confirmed by angiography. The galactose/palmitic acid-based echo contrast agent was injected intravenously as bolus of 200, 300, or 400 mg/mL in a dosage of 10, 5, and 5 mL, respectively. RESULTS Thirty-two of the 33 patients were completely examined because 1 patient who felt pain at the injection site declined further investigations. Twenty-one (66%) of 32 CE studies were conclusive and showed cross-flow through three anterior and two posterior communicating arteries, but no stenoses and occlusions. Precontrast identification of any cerebral artery provided an overall accuracy of 97% in predicting a conclusive CE investigation. Precontrast TCCD identified no arterial Doppler signals in patients with inconclusive CE studies. CONCLUSIONS CE-TCCD provided conclusive examinations in two thirds of patients with ischemic cerebrovascular disease and ultrasound-refractory temporal windows. Precontrast detection of any cerebral artery reliably predicted a conclusive CE investigation.
Towards automatic detection of antisocial behavior from texts

The automatic analysis of emotional content of text has become pervasive and has been applied in many fields of research. The work reported in this paper is in particular interested in modeling antisocial behavior and the emotional states that define it. We introduce the antisocial behavior detection (ASBD) model for portraying the emotions pertaining to antisocial behavior. In addition to describing negative affective states, our model uses the concepts of action tendencies and evidences in order to predict possible acts of antisocial behavior based on input texts. We outline a design for an antisocial behavior detection system based on the ASBD model.