Miracle-dz/UniFAR-FTUs huggingface dataset:
Belongingness and Satisfaction Recognition from Physiological Synchrony with A Group-Modulated Attentive BLSTM under Small-group Conversation

Physiological synchrony is a particular phenomenon of physiological responses during a face-face conversation. However, while many previous studies proposed various physiological synchrony measures between interlocutors in dyadic conversations, very few works on computing physiological synchrony in small groups (three or more people). Besides, belongingness and satisfaction are two critical factors for humans to decide where group they want to stay. Therefore, we want to investigate and reveal the relationship between physiological synchrony and belongingness/satisfaction under group conversation in this preliminary work. We feed the physiology of group members into a designed learnable graph structure with the group-level physiological synchrony and heart-related features computed from Photoplethysmography (PPG) signals. We then devise a Group-modulated Attentive Bi-directional Long Short-Term Memory (GGA-BLSTM) model to recognize groups’ three levels of belongingness and satisfaction (low, middle, and high). Finally, we evaluate the proposed method on our recently collected multimodal group interaction corpus (never published before), NTUBA. The results show that (1) the models trained jointly with the group-level physiological synchrony and the conventional heart-related features consistently outperforms the model only trained with the conventional features, and (2) the proposed model with a Graph-structure Group-modulated Attention mechanism (GGA), GGA-BLSTM, performs better than the robust baseline model, the attentive BLSTM. Finally, the GGA-BLSTM achieves a good unweighted average recall (UAR) of 73.3% and 82.1% on group satisfaction and belongingness classification tasks, respectively. In further analyses, we reveal the relationships between physiological synchrony and group satisfaction/belongingness.
Study on Health Behavior Pattern of Community Residents in Public Health Emergency

The psychological reaction and behavior mechanism of people in public health emergency is complex and difficult to observe. Combined with the stimulation of different supervision mechanisms of blockchain and different levels of human needs, this study constructs an influencing factors analysis model of residents' health behavior, analyzes the impact of different supervision environment stimuli on residents' health behavior, and excavates the mechanism of residents' health behavior, so as to provide reference for epidemic prevention and control departments. The empirical analysis shows that residents' risk perception and sense of belonging are significantly affected by three supervisory stimuli: health certification, behavioral civilization points and subjective norm. In addition, risk perception and sense of belonging also have effect on residents' compulsory health behavior and self-conscious health behavior, thus clarifying the mechanism of residents' health behavior patterns under the blockchain environment.
A Web-Based Longitudinal Mental Health Monitoring System

Current clinical assessments of depression disorder are heavily relied on the questionnaire tables on patients’ daily behavior, sleeping, and mood status of the past two weeks. However, the information obtained through the patient’s review of the past two weeks’ experience is neither timely nor objective. Moreover, while patients have medicine at home, doctors lose the way of monitoring and intervening them on time. In this paper, we propose and implement a web-based longitudinal mental health monitoring system. On the user end, the patients can report their daily information through ecological momentary assessment (EMA), share their emotions in speech or face video, test their depression severity through the PHQ-9 questionnaire table or face videos recorded while going through a semi-structured interview, and check their recent history of activity, sleeping, emotion log, and depression severity etc. The server end implements emotion recognition and depression estimation on the pre-trained deep learning models. On the doctor end, the doctor can manage the information of all the patients under his(her) supervision, monitor their recent status, and edit their depression severity after clinical diagnosis.
Personalized Dynamic Pricing with RFM Modeling

Dynamic pricing primitives from the airline and hotel industry have lately shifted to the wider electronic retail industry, however there is still a lack of ready to use frameworks for applying or testing dynamic pricing policies in online e-commerce stores. This has practically generated limitations in the way dynamic pricing can be applied in real-life. This paper introduces a new dynamic pricing model that uses an extended version of the RFM model to calculate a personal price for each product sold online. Moreover, our work introduces an open-source simulation framework that allows testing and validation or different dynamic pricing policies. According to our evaluation, the proposed methodology achieved 54.33% increase in net profits when compared with nine other merchants following a fixed pricing policy and 16.13% increase when compared with the derivative-following pricing strategy.
A Multimodal Dynamic Neural Network for Call for Help Recognition in Elevators

As elevator accidents do great damage to people’s lives and property, taking immediate responses to emergent calls for help is necessary. In most emergency cases, passengers must use the “SOS” button to contact the remote safety guard. However, this method is unreliable when passengers lose the ability of body movement. To address this problem, we define a novel task of identifying real and fake calls for help in elevator scenes. Given that the limited call for help dataset collected in elevators contains multimodal data of real and fake categories, we collected and constructed an audiovisual dataset dedicated to the proposed task. Moreover, we present a novel instance-modality-wise dynamic framework to efficiently use the information from each modality and make inferences. Experimental results show that our multimodal network improves the performance on the call for help multimodal dataset by 2.66% (accuracy) and 1.25% (F1 Score) with respect to the pure audio model. Besides, our method outperforms other methods on our dataset.
New methodology to evaluate the rolling contact fatigue performance of bearing steels with surface dents : Application to 32CrMoV13 (nitrided) and M50 steels

A new methodology is proposed to evaluate the rolling contact fatigue (RCF) performances of bearing steels in presence of surface dents. The experimental procedure consists in denting the raceway of the test specimen with a hardness machine using spherical diamond tips of different radius, i.e. 200, 400 and 600 μm, and normal loads ranging from 5 to 50 daN. Analysis of various dent geometries yields to an analytical law with five parameters useful to fit experimental profiles for contact simulation. Besides local residual stresses and plastic strains around the dent have been obtained by finite element simulations of the indentation process. RCF tests performed on a two-disk machine have shown better performances of nitrided 32CrMoV13 steel compared to M50 reference steel. The dominating role of sliding has been highlighted and two areas where damage initiates were identified, while the effects of the normal load and hoop stresses are less marked.Copyright © 2003 by ASME
Energy harvesting from human motion: exploiting swing and shock excitations

Modern compact and low power sensors and systems are leading towards increasingly integrated wearable systems. One key bottleneck of this technology is the power supply. The use of energy harvesting techniques offers a way of supplying sensor systems without the need for batteries and maintenance. In this work we present the development and characterization of two inductive energy harvesters which exploit different characteristics of the human gait. A multi-coil topology harvester is presented which uses the swing motion of the foot. The second device is a shock-type harvester which is excited into resonance upon heel strike. Both devices were modeled and designed with the key constraint of device height in mind, in order to facilitate the integration into the shoe sole. The devices were characterized under different motion speeds and with two test subjects on a treadmill. An average power output of up to 0.84 mW is achieved with the swing harvester. With a total device volume including the housing of 21 cm3 a power density of 40 μW cm−3 results. The shock harvester generates an average power output of up to 4.13 mW. The power density amounts to 86 μW cm−3 for the total device volume of 48 cm3. Difficulties and potential improvements are discussed briefly.
Role of p16INK4A/Ki-67 dual immunostaining on cell blocks in detecting high-grade cervical intraepithelial lesions

Background: P16/Ki-67 dual immunostaining has been confirmed as a sensitive and specific test for human papillomavirus positive women. In the present study, we evaluated cell blocks (CBs) with p16INK4A/Ki-67 biomarkers to detect high-grade cervical intraepithelial neoplasia (CIN). Materials and Methods: Samples for CB preparation were taken from females with abnormal Pap smears, who also underwent colposcopic guided biopsies, P16INK4A and Ki-67 staining were performed on CBs and tissue biopsies, histopathology with p16INK4A expression was considered the gold standard. Sixty-five specimens were included in the study. Results: The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy (AC) of CB + p16INK4A/Ki-67 in detecting CIN2 when considering only cytology specimens with the low-grade squamous intraepithelial lesion (LSIL) were 86.67%, 100%, 66.67%, 89.66%, and 82.93%, respectively. The sensitivity, specificity, PPV, NPV, and AC of CB + p16INK4A/Ki-67 in detecting CIN2 when considering only cytology specimens with atypical squamous cells of uncertain significance/LSIL were 75%, 85%, 60%, 91.89%, 82.69%, respectively. Rates of positive staining for p16 INK4A/ki-67 were enhanced according to increased pathologic grade and differed statistically between CIN1 and CIN2 as well as squamous cell carcinoma. Conclusion: CB preparation technique with p16INK4A and Ki-67 immunostainings have improved the diagnostic AC of Pap smear in detecting high-grade CIN.
Novel inhibitors designing against the potential drug target of Plasmodium falciparum M17 Leucyl Aminopeptidase – PfM17LAP

Malaria is one of the major disease of concern worldwide especially in the African regions. According to the recent WHO reports, African regions share 95% of the total deaths worldwide that occurs due to malaria. Plasmodium falciparum M17 Leucyl Aminopeptidase (PfM17LAP) plays an important role in the regulation of amino acids release and for the survival of the parasite. We performed molecular docking and simulation studies to find the potential inhibitors against PfM17LAP using ChEMBL antimalarial library. Molecular docking studies and post-docking analysis revealed that molecules CHEMBL369831 and CHEMBL176888 showed better binding than the reference molecule BESTATIN. LibDock and X-SCORES of molecules BES, CHEMBL369831 and CHEMBL176888 are 130.071, 230.38, 223.56 and -8.75 Kcal/mol, -10.90 Kcal/mol, -11.05 Kcal/mol respectively. ADMET profiling of the top ten ranked molecules was done by using the Discovery Studio. Molecular dynamic studies revealed that the complex PfM17LAP-CHEMBL369831 is stable throughout the simulation. Finally, we have reported novel inhibitors which possess more binding affinity towards PfM17LAP.
The Effect of Fermented Palm Kernel Cake Layer Quail Rations on Production Performance and Eggshell Thickness

The purpose of the study was to evaluate how palm kernel cake fermented by Sclerotium rolfsii and supplemented with humic acid affected production performance and egg quality of quails. The animals used in this study were 200-layer quail (Coturnix coturnix japonica) at 14 weeks of age. Fermented palm kernel cake (FPKC) with rationed compositions of 0, 5, 10, 15 and 20% were utilized in the research treatment, which lasted for eight weeks. Also, this study used a randomized design with four replicates in each group. The results showed that feed intake, egg production, feed conversion, egg weight, and eggshell thickness of layer quail were not statistically significant (P>0.05). Conclusively, palm kernel cake fermented with S. rolfsii may be utilized in laying quail feed at a concentration of up to 20%.
Design and analysis of missing miner searching robot

A new type of mobile robot that is used to search and locate missing miners after mine disasters is designed according to the complex environment underground mine. The general structure and main parameters of the Missing Miner Searching Robot (MMSR) are presented. Four tracked units drive MMSR under independent control and cooperative driving mode. Each tracked unit is a leg-tracked function moving mechanism. The moving and legged rotating of a unit are respectively controlled by two motors. Surmounting obstacles capability, steering performance, toppling stability and kinematical reconfigurability of the MMSR are analyzed. The results show that MMSR adapted itself to terrains and topographic environment underground mine. It could directly surmount a raceway with width or an obstacle with height less than one tracked unit length. It had recovery ability of moving function.
Food Shelf Life and Safety: Challenge Tests, Prediction and Mathematical Tools

Predictive microbiology (PM) is an interesting tool to predict the survival/growth of pathogens and spoiling microorganisms in foods, as well as a powerful mean for the evaluation of the shelf life and the effects of some hurdles in food industry. This chapter offers an overview of the most important primary models to fit growth (Baranyi, Gompertz and lag-exponential equations) or survival kinetics (the function of Bigelow, along with the equations included in the Add-in-Excel component GInaFiT). Then, the chapter describes some secondary models used in food microbiology (square root, cardinal, Arrhenius and polynomial equations), as well as a brief synopsis of a new approach, the S/P model, based on the simultaneous evaluation of the microflora growth and the production of an end-product or the consumption of a substrate. Another interesting tool proposed by the chapter is a summary of the approaches used for the evaluation of the lag phase of a microbial population, along with an appendix reporting some key-concepts of the Design of Experiments and a description of the indices for the evaluation of the goodness of fitting of a function.
Reinforcement Learning for Vision-based Object Manipulation with Non-parametric Policy and Action Primitives

The object manipulation is a crucial ability for a service robot, but it is hard to solve with reinforcement learning due to some reasons such as sample efficiency. In this paper, to tackle this object manipulation, we propose a novel framework, AP-NPQL (Non-Parametric Q Learning with Action Primitives), that can efficiently solve the object manipulation with visual input and sparse reward, by utilizing a nonparametric policy for reinforcement learning and appropriate behavior prior for the object manipulation. We evaluate the efficiency and the performance of the proposed AP-NPQL for four object manipulation tasks on simulation (pushing plate, stacking box, flipping cup, and picking and placing plate), and it turns out that our AP-NPQL outperforms the state-of-the-art algorithms based on parametric policy and behavior prior in terms of learning time and task success rate. We also successfully transfer and validate the learned policy of the plate pick-and-place task to the real robot in a sim-to-real manner.
Quadruped Robot Hopping on Two Legs

This paper presents a control strategy for quadruped robots to hop on their rear legs in three-dimensional space. The proposed approach generates nominal center of mass (CoM) trajectories based on a template spring-loaded inverted pendulum (SLIP) model. Tracking this reference remains a challenge due to the underactauted nature of balance with point feet. To address this challenge, a control-Lyapunov function based quadratic programming (CLF-QP) controller is proposed, which modulates nominal ground reaction forces (GRFs) to balance the torso while considering friction limits. The CLF construction is guided by a variational-based linearization (VBL) applied to a reduced-order single-rigid-body (SRB) model, and treats underactuation via solving a Riccati equation to obtain the CLF. A new balance control approach is presented that effectively decouples sagittal plane control (via re-planning) with lateral and rotational control (via the CLF and VBL). The proposed approach shows more robust balancing performance than the conventional CLF-QP approach. Simulations of the Mini Cheetah demonstrate in-place hopping with up to a 0.71m apex height.
Lactobacillus plantarum MA2 Ameliorates Methionine and Choline-Deficient Diet Induced Non-Alcoholic Fatty Liver Disease in Rats by Improving the Intestinal Microecology and Mucosal Barrier

Non-alcoholic fatty liver disease (NAFLD) has become a highly concerned health issue in modern society. Due to the attentions of probiotics in the prevention of NAFLD, it is necessary to further clarify their roles. In this study, the methionine and choline-deficient (MCD) diet induced NAFLD rats model were constructed and treated with strain L. plantarum MA2 by intragastric administration once a day at a dose of 1 × 108 cfu/g.bw. After 56 days of the therapeutic intervention, the lipid metabolism and the liver pathological damage of the NAFLD rats were significantly improved. The content of total cholesterol (TC) and total triglyceride (TG) in serum were significantly lower than that in the NAFLD group (p < 0.05). Meanwhile, the intestinal mucosal barrier and the structure of intestinal microbiota were also improved. The villi length and the expression of claudin-1 was significantly higher than that in the NAFLD group (p < 0.05). Then, by detecting the content of LPS in the serum and the LPS-TLR4 pathway in the liver, we can conclude that Lactobacillus plantarum MA2 could reduce the LPS by regulating the gut microecology, thereby inhibit the activation of LPS-TLR4 and it downstream inflammatory signaling pathways. Therefore, our studies on rats showed that L. plantarum MA2 has the potential application in the alleviation of NAFLD. Moreover, based on the application of the strain in food industry, this study is of great significance to the development of new therapeutic strategy for NAFLD.
An image dataset of cleared, x-rayed, and fossil leaves vetted to plant family for human and machine learning

﻿Abstract Leaves are the most abundant and visible plant organ, both in the modern world and the fossil record. Identifying foliage to the correct plant family based on leaf architecture is a fundamental botanical skill that is also critical for isolated fossil leaves, which often, especially in the Cenozoic, represent extinct genera and species from extant families. Resources focused on leaf identification are remarkably scarce; however, the situation has improved due to the recent proliferation of digitized herbarium material, live-plant identification applications, and online collections of cleared and fossil leaf images. Nevertheless, the need remains for a specialized image dataset for comparative leaf architecture. We address this gap by assembling an open-access database of 30,252 images of vouchered leaf specimens vetted to family level, primarily of angiosperms, including 26,176 images of cleared and x-rayed leaves representing 354 families and 4,076 of fossil leaves from 48 families. The images maintain original resolution, have user-friendly filenames, and are vetted using APG and modern paleobotanical standards. The cleared and x-rayed leaves include the Jack A. Wolfe and Leo J. Hickey contributions to the National Cleared Leaf Collection and a collection of high-resolution scanned x-ray negatives, housed in the Division of Paleobotany, Department of Paleobiology, Smithsonian National Museum of Natural History, Washington D.C.; and the Daniel I. Axelrod Cleared Leaf Collection, housed at the University of California Museum of Paleontology, Berkeley. The fossil images include a sampling of Late Cretaceous to Eocene paleobotanical sites from the Western Hemisphere held at numerous institutions, especially from Florissant Fossil Beds National Monument (late Eocene, Colorado), as well as several other localities from the Late Cretaceous to Eocene of the Western USA and the early Paleogene of Colombia and southern Argentina. The dataset facilitates new research and education opportunities in paleobotany, comparative leaf architecture, systematics, and machine learning.
Velocity, Potential, and Temperature Distributions in Molten Metals During Electromagnetic Stirring: Part I — Experimental Measurements

An experimental technique has been developed to measure the local velocity in molten metals. Couette flow of liquid aluminum, lead, tin and low melting alloy in cylindrical container was chosen for calibration of the experimental technique and the magnetic probe. Velocity and temperature profiles for liquid aluminum rotating in cylindrical container at different angular velocities are obtained for two different values of the depth. We determined that the velocity values increase with magnetic induction, and the relationship between the normalized azimuthal velocity and the magnetic induction can be expressed by quadratic function.
A multi-scale E-jet 3D printing regulated by structured multi-physics field

Micro/nano scale structure as important functional part have been widely used in wearable flexible sensors, gas sensors, biological tissue engineering, microfluidic chips super capacitors and so on. Here a multi-scale electrohydrodynamic jet (E-jet) 3D printing approach regulated by structured multi-physics fields was demonstrated to generate 800 nm scale 2D geometries and high aspect ratio 3D structures. The simulation model of jetting process under resultant effect of top fluid field, middle electric field and bottom thermal field was established. And the physical mechanism and scale law of jet formation were studied. The effects of thermal field temperature, applied voltage and flow rate on the jet behaviors were studied; and the range of process parameters of stable jet was obtained. The regulation of printing parameters was used to manufacture the high resolution gradient graphics and the high aspect ratio structure with tight interlayer bonding. The structural features could be flexibly adjusted by reasonably matching the process parameters. Finally, polycaprolactone/polyvinylpyrrolidone (PCL/PVP) composite scaffolds with cell-scale fiber and ordered fiber spacing were printed. The proposed E-jet printing method provides an alternative approach for the application of biopolymer materials in tissue engineering.