Miracle-dz/UniFAR-FTUs huggingface dataset:
Change in obesity‐related metabolic abnormalities associated with body mass index improvement through life‐style intervention: A meta‐regression

The reduction in body mass index standard deviation score (BMI‐SDS) associated with improvement in biomarkers relating to metabolic health in obese children is unknown. We aimed to establish the change in BMI‐SDS associated with improved inflammation, liver function, and insulin resistance to inform clinical guidelines for pediatric weight management interventions and to assess the efficacy of future trials. A large‐scale systematic review was conducted to identify relevant studies. Studies of children with a diagnosis of obesity according to defined BMI thresholds, participating in lifestyle interventions to reduce obesity, were included. Studies must have reported baseline (pre‐) and postintervention (or change of) BMI‐SDS and either fasting glucose, homeostatic model of insulin resistance (HOMA‐IR), alanine aminotransferase (ALT), C‐reactive protein (CRP), or interleukin‐6 (IL‐6). A series of meta‐regressions were conducted to establish links between BMI‐SDS change scores and change in metabolic markers of health. Sixty‐eight articles were identified. From the meta‐regression analyses, across all study subsets, greater mean falls in all four parameters, (HOMA‐IR, Glucose, ALT, and CRP) were observed with greater mean loss of BMI‐SDS, but the trends were only statistically significant for HOMA‐IR and CRP (P = .003; P = .021). However, we could not find minimum changes in BMI‐SDS that would ensure a fall in these outcomes. At this time, we are unable to recommend a definitive value of BMI‐SDS reduction needed to improve the markers of metabolic health. Future trials should aim to report additional indices of derived BMI values, which may better reflect changes in actual adiposity.
Temporal instability of salience network activity in migraine with aura.

This study aims to investigate whether intra-network dynamic functional connectivity and causal interactions of the salience network is altered in the interictal term of migraine. 32 healthy controls, 37 migraineurs without aura and 20 migraineurs with aura were recruited. Participants underwent a T1-weighted scan and resting-state fMRI protocol inside a 1.5T MR scanner. We obtained average spatial maps of resting-state networks using group independent component analysis, which yielded subject-specific time series via a dual regression approach. Salience network ROIs (bilateral insulae and prefrontal cortices, dorsal anterior cingulate cortex) were obtained from the group average map via cluster-based thresholding. To describe intra-network connectivity, average and dynamic conditional correlation was calculated. Causal interactions between the default-mode, dorsal attention and salience network were characterised by spectral Granger's causality. Time-averaged correlation was lower between the right insula and prefrontal cortex in migraine without aura vs. with aura and healthy controls (p<0.038, p<0.037). Variance of dynamic conditional correlation was higher in migraine with aura vs. healthy controls and migraine with aura vs. without aura between the right insula and dorsal anterior cingulate cortex (p<0.011, p<0.026), and in migraine with aura vs. healthy controls between the dorsal anterior cingulate and left prefrontal cortex (p<0.021). Causality was weaker in the <0.05 Hz frequency range between the salience and dorsal attention networks in migraine with aura (p<0.032). Overall, migraineurs with aura exhibit more fluctuating connections in the salience network, which also affect network interactions, and could be connected to altered cortical excitability and increased sensory gain.
Anti-Angiogenic Activity Of Bevacizumab-Bearing Dexamethasone-Loaded PLGA Nanoparticles For Potential Intravitreal Applications

Purpose Age-related macular degeneration is a multifactorial disease involving inflammation and choroidal neovascularization. Vascular endothelial growth factor (VEGF) has been regarded as a potential therapeutic target to treat choroidal neovascularization. Dexamethasone can interfere with the expression or action of VEGF while bevacizumab targets and combines with VEGF. We propose electrostatically-conjugated bevacizumab-bearing dexamethasone-loaded poly (D,L-lactide-co-glycolide)/polyethylenimine nanoparticles (eBev-DPPNs) for angiogenic combination treatment of ocular diseases. Methods We prepared a novel nanoparticle composed of poly (D, L-lactide-co-glycolide) and polyethylenimine and loaded the nanoparticles with dexamethasone. Bevacizumab was adsorbed onto the surfaces of the nanoparticles by electrostatic interactions. The eBev-DPPNs were evaluated according to their size, polydispersity index, zeta potential, morphology, drug loading, release behavior, and stability. The structural stability of bevacizumab on the surface of the nanoparticles was also analyzed. Subsequently, angiogenesis was investigated in the presence of the eBev-DPPNs using cell apoptosis, wound healing, Transwell invasion, and tube formation assays on the human umbilical vein endothelial cells (HUVECs) in vitro and chick embryo chorioallantoic membrane assay in vivo. The eBev-DPPNs intravitreal injection was applied in the laser-induced rabbit choroidal neovascularization (CNV) model to confirm the role for potential intravitreal applications. Results The eBev-DPPNs was about 200 nm in diameter, with a narrow diameter distribution, and the surface charge was neutral (0.85 ± 0.37mV), which made the eBev-DPPNs stable under physiological conditions. The apoptosis, migration, invasion, and tube formation assays showed that the eBev-DPPNs had a good anti-angiogenic effect on HUVECs. The eBev-DPPNs also provided a strong inhibitory effect on VEGF secretion from HUVECs. Moreover, in vivo chick embryo chorioallantoic membrane assay showed eBev-DPPNs greatly reduced the amount of blood vessels. The leakage area of CNV decreased in the eBev-DPPNs group on rabbit CNV model. Conclusion The eBev-DPPNs are a promising novel anti-angiogenesis therapeutic for potential intravitreal applications such as age-related macular degeneration.
OPTIMIZATION OF PCL-PEG-PCL TRIBLOCK COPOLYMER MICELLES AS HYDROPHOBIC DRUG CARRIER WITH A 22 FULL FACTORIAL DESIGN

Objective: This study aims to optimize PCL-PEG-PCL (PCEC) triblock copolymer micelles as a hydrophobic drug carrier, simvastatin (SV). Methods: PCEC triblock copolymer was prepared by the ring-opening polymerization method (ROP) with different ɛCL/PEG ratio (2 and 5). SV was incorporated into the PCEC triblock copolymer micelles with a concentration of 2.5 and 10 % w/w by the solvent evaporation method (film formation). The influence of the ɛCL/PEG ratio and concentration of SV effect on the responses particle size (PS), polydispersity index (PI) and entrapment efficiency (EE) was assessed using 22 full factorial design method. The test results were analyzed using Design-Expert software to obtain the optimum formula. Result: The selection of the optimum formula is based on the desirability value, the formula with the largest desirability value is chosen as the optimum formula. The results showed the optimum formula chosen had a desirability value of 0.860 consisting of a ɛCL/PEG ratio of 5 and SV concentration of 10 % w/w, with the PS, PI dan EE value was 322.1±3.51 nm, 0.471±0.09 and 87.08±1.17 %, respectively. Conclusion: The 22 full factorial design has been proven to be used as an optimization method to determine the optimum formula of SV-loaded PCEC triblock copolymer micelles with a good result of the PS, PI and EE responses.
Design of optical waveguides considering thermo-mechanical aspects

Optical waveguides are used as components in integrated optical circuits and as the transmission medium in optical communication systems. In recent age, optical fiber communication is the most promising contribution in communication systems due to its numerous advantages. Fabrication of optical waveguide is a very complex process. Stress is generated after fabrication of the waveguide because of thermomechanical effects of the materials used in the waveguide and thus, polarization occurs in the waveguide which causes the anisotropic distribution of the refractive index. The distribution of stress can be analyzed by a numerical investigation by finite element modeling. To achieve the accuracy of optical waveguide design, distribution of thermomechanical effects must be considered. In this paper, the thermomechanical effects of different waveguides are analyzed. It is observed that more efficient polarization-insensitive optical waveguide can be designed achieving better birefringence stability. Finite Element modeling of thermomechanical problems in optical waveguides and the stress distribution of various types of optical waveguides are analyzed.
Which kinds of online reviews predict the online purchase behavior?

As the continuous growth of online shopping, the massive data behind this are valuable sources for website to study and adjust marketing strategies. Therefore, it is of great significance to scrutinize the consumers ' purchase behaviours and the related factors that have major effects on purchase intention or behaviour. This study analysed the data from laboratory setting first, then the online sales data from Taobao.com to explore how the influential factors, such as online reviews (positive vs. negative mainly), risk perception (higher vs. lower) and product types (experiencing vs. searching), interacted on the online purchase intention or online purchase behaviour. The results showed that: (1) in the laboratory setting, the online purchase intention was greatly affected by the online reviews and the interaction between the reviews and the product types. In particular, the purchase intention was higher presented with positive reviews than negative ones, especially for experiencing products. Furthermore, stronger purchase intention was found for experiencing goods with lower risk perception and positive reviews. (2) For the real online transaction data, interestingly, the positive reviews had no effects on purchase, but the neural/negative reviews may negatively affect the purchase behaviour for products with higher risk perception. In addition, these findings were discussed from theories and practice perspectives respectively.
A Modular Simulation Platform for Training Robots via Deep Reinforcement Learning and Multibody Dynamics

In this work we focus on the role of Multibody Simulation in creating Reinforcement Learning virtual environments for robotic manipulation, showing a versatile, efficient and open source toolchain to create directly from CAD models. Using the Chrono::Solidworks plugin we are able to create robotic environments in the 3D CAD software Solidworks® and later convert them into PyChrono models (PyChrono is an open source Python module for multibody simulation). In addition, we demonstrate how collision detection can be made more efficient by introducing a limited number of contact primitives instead of performing collision detection and evaluation on complex 3D meshes, still reaching a policy able to avoid unwanted collisions. We tested this approach on a 6DOF robot Comau Racer3: the robot, together with a 2 fingers gripper (Hand-E by Robotiq) was modelled using Solidworks®, imported as a PyChrono model and then a NN was trained in simulation to control its motor torques to reach a target position. To demonstrate the versatility of this toolchain we also repeated the same procedure to model and then train the ABB IRB 120 robotic arm.
Tag Information Recognition Approaches and Algorithms for Cross-Border Products Checking

The images with fixed layouts, such as images from ID cards, driving licenses, and invoices can be recognized from prior knowledge[1]-[7]. However, The non-immobilized images, such as product labels at ports, is very difficult to be extracted structured data information from tag images because the formats and contents of tags in different countries and different product vary widely[8]. The process is complex and the error rate is high. This paper combines the characteristics of the Cross-Border Products label, overall format complex and simple local structure (top-to-down and left-to-right), and proposes a method for identifying and structuring port commodity label information. The method mainly establishes a template library of keyword and data unit information of commodity labels according to the port commodity classification and then separates the keyword and the data information from the multi-line text with accurate location information recognized by the OCR engine. Finally, the keyword and data are structured according to the local layout pattern between the keyword and the data, and the structured Cross-Border product information is obtained.
Videl: A Vision-based AI Diagnoser for Early Leukemia

Leukemia is one of TOP 10 cancers in China, especially to young children and elderly. Treating Leukemia at the early stage can significantly increase the cure rate. However, detecting early stage Leukemia, i.e, finding a small amount of blood cells among massive normal cells, is both technically challenge and labor intensive. Therefore, we designed an AI-powered diagnoser for precise identification of white blood cells. The precise identification has two steps, blood image collecting and cell classification. First, with the help of doctors in Ruijing Hospital, we have been collecting about 1,000 high-quality labeled blood cell samples each week and accumulated more than 200,000 samples in total. This is the largest blood cell image dataset for leukemia in China. Second, based on these blood cell samples, we adopted the ResNet-variant classification method and achieved above 95% accuracy in 17 subtypes of white blood cells. The classification accuracy is comparable to experienced doctors in Ruijing Hospital. Third, models are trained on the latest Intel Knights Landing 7210 Platform with Intel Omni-Path interconnections. Applying MKL-optimized matrix operatiors and RDMA-enable comunication library (PSM) shortens the training time from more than 6 hours to less than an hour. Our AI-powered diagnoser can reduce the time and the cost of early Leukemia diagnosis from one week to one day, and 1,000 USD to 100 USD, respectively.
Measurement of cognitive load for writing tasks using galvanic skin response

The term cognitive load refers to the used amount of working memory resources whenever we are performing any cognitive work. Though various physiological signals had used already to measure this, researchers' attention presently has turned to galvanic skin response a prospective physiological indicator to measure cognitive load and emotions. In our research, we have observed changing in cognitive load for writing tasks with different task difficulty level. We have captured galvanic skin response data including fifteen writing tasks with three difficulty levels, which provides us multiple cognitive load level. Then we have calculated time and frequency domain features of this data. For statistical evaluation of this data, we have done analysis of variance test. Finally we got result which is lot more significant to clarify that cognitive load is increasing with the increase of task difficulty level. This observation has extensive applications in efficient learning for students. Because taking proper class note is one of the vital way of learning, hence this study can reveal the best possible way of delivering lecture to the students so that the cognitive load remains low. In return, it will increase students' ability to process new information.
Low Cost Lower Limb Exoskeleton for Assisting Gait Rehabilitation: Design and Evaluation

This paper presents the design and implementation of a low cost, yet robust, three degrees of freedom (DoF) lower limb exoskeleton intended to assist patients in gait rehabilitation. The majority of patients with incomplete spinal cord injuries (SCI) are able to walk after a rehabilitation process. Among the broad options of physical rehabilitation therapies, there is a relatively recent interest in those assisted by robotic exoskeletons, due to features as high precision movements and automated repetitions. In this context, the subsystems of the exoskeleton prototype described throughout this paper are the following: i) a controlled area network (CAN) communications bus with SDO protocol; and, ii) a hierarchical control system consisting of two levels: a trajectory generator of the walk biomechanics implemented in a centralized controller (CC), and distributed controllers (DC) installed at each joint of the exoskeleton. The multiplication mechanical system uses reduction speed boxes based on cycloidal and planetary gears. Experimental results of the prototype operating, with and without carrying weight, show effectiveness of the whole control system for tracking a non-pathological gait biomechanics trajectory.
Gestures as Intrinsic Creativity Support

Interpersonal communication is essential to group creativity tasks, such as group brainstorming. However, what's easily overlooked in supporting group creativity is the potential use of nonverbal behavior in communication. When people communicate verbally (e.g., discussing a topic through conversation), they may also co-produce hand movements along with verbal contents as part of the communication process. Going beyond using external interventions for creativity gain, we examine the potential to facilitate worker's in-conversation gesture use as an intrinsic mechanism for bolstering group creativity. In this paper, we aim to gain a deeper understanding of the usage and function of hand gestures in computer-mediated group brainstorming. Through a laboratory study, we verified that metaphoric gestures, or producing spatial cues with hands to convey intended concepts, can best influence self's and partner's idea generation. Also, the positive effect of metaphoric gesture is independent of media richness of communication medium (e.g., whether there's visibility or not). The results help to fill in the knowledge gap regarding how gesture use may relate to group creativity, and reveal the potential viability of shaping metaphoric gesture use as an intrinsic creativity support.
Functions and physical functioning after total knee arthroplasty surgery

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Into Scandinavia

Denmark is a generous welfare state which provides resources and legal means for fathers to take their parental role seriously and engage with their children. In this paper, we explore the relation between Danish fathers' interaction online and the societal, legal, and economic infrastructures in which they are situated. By focusing on how fathers living in Denmark make use of the Internet and social media sites to facilitate their role as parents, we are able to explore how online engagement is shaped by the different societal 'norms' of parenting. Our research outlines the ways in which societal infrastructures influence how fathers perceive, and subsequently make use of social media in relation to child-caring. We find that fathers discuss their experiences of legal inequities and stereotypical discrimination on social network sites like Facebook. We also study fathers' online reviews of a Danish parenting App, FAR, designed specifically to support fathers. By analyzing social media discussions around fatherhood in Denmark, we found connections to the ways in which the current political climate shapes and influences fatherhood in Denmark, as they reflect the societal infrastructures which situate fathers in contemporary Denmark. Further, we found a strong political interest for collective action to transform the societal infrastructures to support legal equality for child caretaking across genders. This strong political motivation is distinct from existing studies exploring how fatherhood is displayed on social media in other countries such as the USA. On this basis, we argue that research exploring social media use in institutions which are strongly shaped by societal norms, must explicitly consider the role which society takes in shaping such institutions, and include these aspects into the analysis. Our data show that fathers use social media sites as platforms to produce a fatherhood more in line with their lived experience of parenting, and that they advocate for collective political action to strengthen fathers' legal rights.
Part-Time Ride-Sharing

Ride-sharing companies have been reshaping the structure and practice of ride-hailing work. At the same time, studies have been showing mixed driver experiences on the platform while many of the drivers are working part-time. In this research, we seek to understand why drivers on this platform are working part-time, how this impacts their view of the platform, and what this means for more accurately evaluating the design of these platforms. To investigate this question, we focused on situating ride-sharing in the lives and constellation of gigs that drivers maintain. We collected 53 survey responses and conducted 10 semi-structured interviews with drivers to probe these questions. We found that the extent that drivers categorize themselves as part-time is less about the number of hours worked and more about how dependent they are on ride-sharing income. The level of this dependency seemed to heavily influence how they interacted with the platform and their attitudes towards difficulties faced. It seemed to us that in some ways that the design or functioning of the platform almost pushed users towards working part-time. We discuss the importance of taking these different types of workers and their situations into consideration when evaluating the design and usability of these platforms.
On the Determinants of the Business Model of Online Ride-Hailing Market

In this paper, we focus on the business model of online ride-hailing platform and analyze the fundamental factors that determines the economic performance of online ride-hailing business model. We define the business model of platform economy in the perspective of organizational economics, and based on this definition, two types business model of online ride-hailing market are conceptually constructed. Then, we analyze the economic determinants that influence the adoption of the business model of the online ride-hailing platform. We find that, when the network effects is weak and the passengers' heterogeneity degree in service quality is low, the marketplace model dominates the online ride-hailing market and the market competition level is relatively low; when the network effects and passengers' heterogeneity degree are moderate, the marketplace model remains dominant, while the integration model will emerge in the market, and the proportion of two models depend on the level of network effects and passengers' heterogeneity degree; when the network effects and passengers' heterogeneity degree are all high, the marketplace model and the integration model will coexist, and the market competition is relatively high.