Miracle-dz/UniFAR-FTUs huggingface dataset:
Features of a Splashing Drop on a Solid Surface and the Temporal Evolution extracted through Image-Sequence Classification using an Interpretable Feedforward Neural Network

This paper reports the features of a splashing drop on a solid surface and the temporal evolution, which are extracted through image-sequence classiﬁcation using a highly interpretable feedforward neural network (FNN) with zero hidden layer. The image sequences used for training-validation and testing of the FNN show the early-stage deformation of milli-sized ethanol drops that impact a hydrophilic glass substrate with the Weber number ranges between 31–474 (splashing threshold about 173). Speciﬁc videographing conditions and digital image processing are performed to ensure the high similarity among the image sequences. As a result, the trained FNNs achieved a test accuracy higher than 96%. Remarkably, the feature extraction shows that the trained FNN identiﬁes the temporal evolution of the ejected secondary droplets around the aerodynamically lifted lamella and the relatively high contour of the main body as the features of a splashing drop, while the relatively short and thick lamella as the feature of a nonsplashing drop. The physical interpretation for these features and their respective temporal evolution have been identiﬁed except for the diﬀerence in contour height of the main body between splashing and nonsplashing drops. The observation reported in this study is important for the development of a data-driven simulation for modeling the deformation of a splashing drop during the impact on a solid surface.
Continuous Switching Control of an Input-Delayed Antagonistic Muscle Pair During Functional Electrical Stimulation

Existing controllers for functional electrical stimulation (FES) of upper limb muscles were initially designed to assist unilateral movements and may not be readily applicable to assist antagonistic muscle movements. Furthermore, it is yet unclear if electromechanical delays (EMDs) are present during the coactivation of muscles. In this article, a robust controller is designed to facilitate the FES of an antagonistic muscle pair during elbow flexion and extension. The controller uses a continuous switching law that maps a joint angle error to control the antagonistic muscle pair. Furthermore, the controller compensates for EMDs in the antagonistic muscle pair. A Lyapunov stability analysis yields uniformly ultimately bounded (UUB) tracking for the human limb joint. The experimental results on four participants without disabilities indicate that the controller is robust and effective in switching between antagonistic muscles. A separate set of experiments also showed that EMDs are indeed present in the coactivated muscle pair. The designed controller compensates for the EMDs and statistically improves root mean square error (RMSE) compared to a traditional linear controller with no EMD compensation. The proposed controller can be generalized to assist FES-elicited tasks that involve a weak antagonistic muscle pair.
Cannabidiol-Treated Ovariectomized Mice Show Improved Glucose, Energy, and Bone Metabolism With a Bloom in Lactobacillus

Loss of ovarian 17β-estradiol (E2) in postmenopause is associated with gut dysbiosis, inflammation, and increased risk of cardiometabolic disease and osteoporosis. The risk-benefit profile of hormone replacement therapy is not favorable in postmenopausal women therefore better treatment options are needed. Cannabidiol (CBD), a non-psychotropic phytocannabinoid extracted from hemp, has shown pharmacological activities suggesting it has therapeutic value for postmenopause, which can be modeled in ovariectomized (OVX) mice. We evaluated the efficacy of cannabidiol (25 mg/kg) administered perorally to OVX and sham surgery mice for 18 weeks. Compared to VEH-treated OVX mice, CBD-treated OVX mice had improved oral glucose tolerance, increased energy expenditure, improved whole body areal bone mineral density (aBMD) and bone mineral content as well as increased femoral bone volume fraction, trabecular thickness, and volumetric bone mineral density. Compared to VEH-treated OVX mice, CBD-treated OVX mice had increased relative abundance of fecal Lactobacillus species and several gene expression changes in the intestine and femur consistent with reduced inflammation and less bone resorption. These data provide preclinical evidence supporting further investigation of CBD as a therapeutic for postmenopause-related disorders.
Physical Simulation Layer for Accurate 3D Modeling

We introduce a novel approach for generative 3D modeling that explicitly encourages the physical and thus functional consistency of the generated shapes. To this end, we advocate the use of online physical simulation as part of learning a generative model. Unlike previous related methods, our approach is trained end-to-end with a fully differentiable physical simulator in the training loop. We accomplish this by leveraging recent advances in differentiable programming, and introducing a fully differentiable point-based physical simulation layer, which accurately evaluates the shape's stability when subjected to gravity. We then incorporate this layer in a signed distance function (SDF) shape decoder. By augmenting a conventional SDF decoder with our simulation layer, we demonstrate through extensive experiments that online physical simulation improves the accuracy, visual plausibility and physical validity of the resulting shapes, while requiring no additional data or annotation effort.
Deep Learning for Demand Forecasting in the Fashion and Apparel Retail Industry

Compared to other industries, fashion apparel retail faces many challenges in predicting future demand for its products with a high degree of precision. Fashion products’ short life cycle, insufficient historical information, highly uncertain market demand, and periodic seasonal trends necessitate the use of models that can contribute to the efficient forecasting of products’ sales and demand. Many researchers have tried to address this problem using conventional forecasting models that predict future demands using historical sales information. While these models predict product demand with fair to moderate accuracy based on previously sold stock, they cannot fully be used for predicting future demands due to the transient behaviour of the fashion industry. This paper proposes an intelligent forecasting system that combines image feature attributes of clothes along with its sales data to predict future demands. The data used for this empirical study is from a European fashion retailer, and it mainly contains sales information on apparel items and their images. The proposed forecast model is built using machine learning and deep learning techniques, which extract essential features of the product images. The model predicts weekly sales of new fashion apparel by finding its best match in the clusters of products that we created using machine learning clustering based on products’ sales profiles and image similarity. The results demonstrated that the performance of our proposed forecast model on the tested or test items is promising, and this model could be effectively used to solve forecasting problems.
Decision-Making Method of Autonomous Vehicles in Urban Environments Considering Traffic Laws

In order to improve the efficiency and safety of autonomous vehicles’ decision-making process in complex urban scenarios, a decision-making method for hierarchical processing of static traffic law information and dynamic traffic participant information is proposed in this paper. In the decision-making method, the candidate behavior set is constructed by extracting the element of traffic laws and fully considering the traffic laws constraints to ensure the legality and effectiveness of the decision-making algorithm. Besides, four evaluation indicators and two-level entry threshold are designed to select the optimal driving behavior with the consideration of driving efficiency, ride safety and macro path requirement. The advantage of proposed method is that it avoids the problem of poor adaptability to traffic laws and regulations as the existing methods usually make decisions under the condition of mixed traffic laws and traffic participant information. A complete driving task simulation and analysis, including six typical urban traffic scenarios, is given under Matlab environment. The results show that the proposed decision-making method is able to make reasonable and feasible decisions and highly consistent with the actual driver’s decision-making behavior in complex urban scenarios, which verifies the effectiveness of the proposed method.
Functional and Process Model on Big Data, Machine Learning, and Digital Phenotyping in Clinical Psychiatry

implications for psychiatrists dealing with the patients directly. BD in MH has been predominantly discussed from a computational and engineering perspective.12 There are no reviews that broaden the knowledge landscape in clinical psychiatry that underpin the basic science of artificial intelligence (AI) for MH, psychiatry epidemiology, and MH policymaking. This article aims to create an easy-tounderstand functional and process model for psychiatrists with little to no knowledge about BD, ML, and AI. The best way to realize this aim is to synthesize knowledge from the existing literature and personal experiences in dealing with clinical data. Therefore, this article was written to provide familiarity with upcoming concepts and trends in BD, AI, and their potential applications for psychiatrists, without delving into the technical jargon. This viewpoint article will also help psychiatrists collaborate with technology counterparts to translate these ideas and concepts for effective clinical applications. Discussion on complex techniques and technology has been
COL8A1 Predicts the Clinical Prognosis of Gastric Cancer and Is Related to Epithelial-Mesenchymal Transition

Background Gastric cancer (GC) is the fifth most common malignant tumor and the third leading cause of cancer-related deaths. Because GC has the characteristics of high heterogeneity, unclear mechanism, limited treatment methods, and low five-year survival rate, it is necessary to find the prognostic biomarkers of GC and explore the mechanism of GC. Methods We first identified differentially expressed genes (DEGs) between gastric cancer and normal gastric cells through expression analysis. A protein-protein interaction (PPI) network was constructed to find tightly connected modules. We performed survival analysis on the DEGs in the modules to identify genes with prognostic significance. Gene set enrichment analysis (GSEA) was used to identify gene enrichment pathways. Finally, we used our own collected clinical samples of 119 gastric adenocarcinoma (STAD) tissues and 40 normal gastric tissues to perform immunohistochemical (IHC) staining to verify the differential expression of COL8A1 in STAD tissues and normal gastric tissues and its correlation with epithelial-mesenchymal transition- (EMT-) related factors. Results We identified 356 DEGs through differential expression analysis. Through PPI analysis and survival analysis, we determined that the collagen type VII alpha-1 chain (COL8A1) gene has prognostic significance. GSEA analysis showed that COL8A1 was significantly enriched in the EMT. IHC results showed that COL8A1 was upregulated in STAD tissues and could be used as an independent prognostic factor and was related to EMT. Conclusion This study shows that COL8A1 is related to the prognosis of GC patients and might affect the progress of GC through the EMT pathway. Therefore, COL8A1 may be a biomarker for predicting the prognosis of GC.
Making sense of gambling. Swedish youth navigating between risk and responsibility

ABSTRACT Youth gambling is commonly described in policy and research as a high-risk behavior. To design relevant measures to prevent gambling problems among youth, it is important to understand how youth themselves relate to gambling. To explore how youth navigate their position on gambling in the context of their everyday lives, we conducted qualitative interviews with 35 participants aged 17–21 years in Sweden; 15 had gambled and 20 had experience of others’ gambling. The thematic analysis showed that both gamblers and non-gamblers overall had negative attitudes toward gambling and emphasized repeatedly discourses of personal responsibility in it. The participants used various neutralization techniques to navigate the economic and addictive risks of gambling. Youth who gambled distanced themselves from the risks of gambling by drawing a line between themselves and excessive gamblers, between safe and unsafe gambling, or highlighted how their skills and strategic thinking made gambling less problematic. Also, gambling in liminal circumstances abroad or in alcohol-serving venues offered a safe time and place for gambling by separating it from everyday life practices. The findings provide important cues to how young people locate gambling in their everyday life, which is useful knowledge for policy and prevention.
Effects of a Smoke-Free Policy in Xi'an, China: Impact on Hospital Admissions for Acute Ischemic Heart Disease and Stroke

Background Smoking and secondhand smoke (SHS) exposure rates are much higher in China than in other countries. A smoke-free policy was implemented in Xi'an, a city in Shaanxi Province, China, on November 1, 2018. This study aimed to evaluate the effect of the smoke-free policy on changes in hospital admissions for acute ischemic heart disease (AIHD) and stroke in Xi'an. Methods All subjects had been hospitalized for AIHD or stroke from February 9, 2017 to December 25, 2019 (study period: 150 weeks) in six randomly selected public hospitals out of 36 tertiary hospitals in Xi'an. A generalized additive model developed using an interrupted time series design was used to compare immediate and annual percent changes in hospital admissions before and after policy implementation. Results The study included 31,400 cases (16,656 cases of AIHD and 14,744 cases of stroke) from 6 hospitals in Xi'an. Immediately after implementation of the smoke-free policy, AIHD admissions were reduced significantly (−31.66%, 95% CI: – 39.45 to −22.86%), but stroke admissions were not (−4.94%, 95% CI: −13.26 to 4.17%). The annual reduction in stroke-related admissions (−14.54%, 95% CI: −23.53 to −4.49%) and the annual increase in AIHD-related admissions (40.58%, 95% CI: 22.08 to 61.87%) were significant. Although there was no significant reduction in AIHD admissions, stroke admissions were significantly reduced by −15.73% (from 7,350 to 6,194) after implementation of the smoke-free policy in Xi'an. Conclusion The smoke-free policy had different effects on hospital admissions for AIHD and stroke in Xi'an. Xi'an should improve its smoke-free legislation and expand the measures to maintain or achieve additional significant health benefits. These findings can guide the formulation and implementation of regional and national smoke-free policies.
Shared Perception Is Different From Individual Perception: A New Look on Context Dependency

Human perception is based on unconscious inference, where sensory input integrates with prior information. This phenomenon, known as context dependency, helps in facing the uncertainty of the external world with predictions built upon previous experience. On the other hand, human perceptual processes are inherently shaped by social interactions. However, how the mechanisms of context dependency are affected is to date unknown. If using previous experience—priors—is beneficial in individual settings, it could represent a problem in social scenarios, where other agents might not have the same priors, causing a perceptual misalignment on the shared environment. The present study addresses this question. We studied context dependency in an interactive setting with a humanoid robot iCub that acted as a stimuli demonstrator. Participants reproduced the lengths shown by the robot in two conditions: one with iCub behaving socially and another with iCub acting as a mechanical arm. The different behavior of the robot significantly affected the use of prior in perception. Moreover, the social robot positively impacted perceptual performances by enhancing accuracy and reducing participants’ overall perceptual errors. Finally, the observed phenomenon has been modeled following a Bayesian approach to deepen and explore a new concept of shared perception.
Short-Term, Voluntary Exercise Affects Morpho-Functional Maturation of Adult-Generated Neurons in Rat Hippocampus

Physical exercise is a well-proven neurogenic stimulus, promoting neuronal progenitor proliferation and affecting newborn cell survival. Besides, it has beneficial effects on brain health and cognition. Previously, we found that three days of physical activity in a very precocious period of adult-generated granule cell life is able to antedate the appearance of the first GABAergic synaptic contacts and increase T-type Ca2+ channel expression. Considering the role of GABA and Ca2+ in fostering neuronal maturation, in this study, we used short-term, voluntary exercise on a running wheel to investigate if it is able to induce long-term morphological and synaptic changes in newborn neurons. Using adult male rats, we found that: (i) three days of voluntary physical exercise can definitively influence the morpho-functional maturation process of newborn granule neurons when applied very early during their development; (ii) a significant percentage of new neurons show more mature morphological characteristics far from the end of exercise protocol; (iii) the long-term morphological effects result in enhanced synaptic plasticity. Present findings demonstrate that the morpho-functional changes induced by exercise on very immature adult-generated neurons are permanent, affecting the neuron maturation and integration in hippocampal circuitry. Our data contribute to underpinning the beneficial potential of physical activity on brain health, also performed for short times.
Tunable liquid crystal metasurface with polarization selection characteristic

In this paper, a systematic design method for tunable metasurface based on liquid crystal (LC) is proposed, which exhibits the property of polarization selection. A compact LC-based meta-atom with a dimension of 0.12 λ × 0.12 λ is designed. The metasurface element consists of a pair of planar metallic structures, between which the LC is sandwiched. The equivalent circuit, electric field distribution, and current distribution elaborate on the design method and operating principle of the LC-based metasurface in detail. Full wave simulations show that the tunable metasurface provides bandpass and bandstop characteristics for TE and TM polarization, respectively. The center frequencies of the passband and stopband are tuned from 10.88 GHz to 10.3 GHz and 10.90 GHz to 10.18 GHz, and the tuning range reaches up to 5.5% and 6.8%, respectively. Compared with the existing work, tunability is introduced while maintaining the polarization selection characteristics. Moreover, frequency responses of the LC-based metasurface under various incident angles from 0° to 70° are kept to be stable for arbitrary LC states. In addition, a prototype sample is designed, fabricated, and measured to verify the proposed design method.
Low-Power Design of Digital LDO With Nonlinear Symmetric Frequency Generation

This brief proposes a digital LDO (Low DropOut regulator) with a built-in non-linear VCO (Voltage Controlled Oscillator) to achieve both the fast transient response and low power operation. This on-chip VCO generates a clock signal whose frequency is a non-linear symmetric function of the output voltage error. Here, we propose a design technique to realize the symmetric frequency generation with low power consumption. We demonstrate a design example of LDO using our proposed technique in a commercial 65 nm low-power CMOS process. We evaluate the LDO using transistor-level simulation using HSPICE. It achieves 0.03-<inline-formula> <tex-math notation="LaTeX">$11 ~\mu \text{A}$ </tex-math></inline-formula> of quiescent current with an input voltage range of 0.6-1.2 V and an average current efficiency of 99.68% across <inline-formula> <tex-math notation="LaTeX">$50\times $ </tex-math></inline-formula> load range.
Recent Advances of Fluorescence Probes for Imaging of Ferroptosis Process

Ferroptosis is an iron−dependent form of regulated cell death. It has attracted more and more research interests since it was found because of its potential physiological and pathological roles. In recent years, many efforts have been made for the developments and applications of selective fluorescence probes for real−time and in situ tracking of bioactive species during ferroptosis process, which is necessary and significant to further study the modulation mechanisms and pathological functions of ferroptosis. In this review, we will focus on summarizing the newly developed fluorescence probes that have been applied for ferroptosis imaging in the recent years, and comprehensively discussing their design strategies, including the probes for iron, reactive oxygen species, biothiols and intracellular microenvironmental factors.
Systematic Design of Loop Circuit Topologies Using C/IDS Methodology

Herein, a systematic approach for designing loop topology circuits, such as ring oscillators (ROs), latches, and frequency dividers, is proposed. The design flow is devised to implement the target circuits with minimum power dissipation at the desired operating frequency. Using a modified <inline-formula> <tex-math notation="LaTeX">$C/I_{\text {DS}}$ </tex-math></inline-formula> methodology, several design examples in different technology nodes are provided showing less than ±5% error in the estimated circuit performance, confirmed by experimental data in 0.18 <inline-formula> <tex-math notation="LaTeX">${\mu }\text{m}$ </tex-math></inline-formula> technology. A standardized procedure has been developed to extract fundamental device characteristics for different technology nodes, which are subsequently fed into an optimizer script. Examples for implementing current-steering ROs and frequency dividers will be provided. The proposed approach can be employed to custom design high-speed sequential logic circuits, as well as voltage-controlled oscillators (VCOs), digitally controlled oscillators (DCOs), and frequency dividers for applications such as clock generators, sequential circuits, and serial data transceivers in modern integrated systems.
Accuracy of the Axillary Temperature Screening Compared to Core Rectal Temperature in Infants

Purpose. To compare the sensitivity of axillary and rectal temperature in infants who presents to the emergency department with a recent history of fever. Methods. A single-center cross-sectional comparative study of 201 patients who presents with a recent history of fever. Infants Up to 12 months of age were included. Demographic characteristics such as age and gender, weight, mean axillary and rectal temperatures were documented. Fever is defined as rectal temperature >38°C as opposed to >37.4 in the axillary method. Results. The mean age was 6.1 ± 3.5 months. The mean (SD) rectal-axillary temperature difference was 0.8°C ± 0.7°C which was statistically significant (P < .001). The sensitivity, specificity, positive predictive and negative predictive values of the axillary method for fever >37.4 were 79.34% (95% CI [73-84.9]), 14.3% (95% CI [0.36-57.9]), 96.2% (95% CI [95-97.2]), and 2.4% (95% CI [0.4-13.5]), respectively. Conclusion. The rectal method remains highly important for accurate and prompt diagnosis in infants.