Miracle-dz/UniFAR-FTUs huggingface dataset:
A Revised Framework to Evaluate the Consistency Assumption Globally in a Network of Interventions

Background The unrelated mean effects (UME) model has been proposed for evaluating the consistency assumption globally in the network of interventions. However, the UME model does not accommodate multiarm trials properly and omits comparisons between nonbaseline interventions in the multiarm trials not investigated in 2-arm trials. Methods We proposed a refinement of the UME model that tackles the limitations mentioned above. We also accompanied the scatterplots on the posterior mean deviance contributions of the trial arms under the network meta-analysis (NMA) and UME models with Bland-Altman plots to detect outlying trials contributing to poor model fit. We applied the refined and original UME models to 2 networks with multiarm trials. Results The original UME model omitted more than 20% of the observed comparisons in both networks. The thorough inspection of the individual data points’ deviance contribution using complementary plots in conjunction with the measures of model fit and the estimated between-trial variance indicated that the refined and original UME models revealed possible inconsistency in both examples. Conclusions The refined UME model allows proper accommodation of the multiarm trials and visualization of all observed evidence in complex networks of interventions. Furthermore, considering several complementary plots to investigate deviance helps draw informed conclusions on the possibility of global inconsistency in the network. Highlights We have refined the unrelated mean effects (UME) model to incorporate multiarm trials properly and to estimate all observed comparisons in complex networks of interventions. Forest plots with posterior summaries of all observed comparisons under the network meta-analysis and refined UME model can uncover the consequences of potential inconsistency in the network. Using complementary plots to investigate the individual data points’ deviance contribution in conjunction with model fit measures and estimated heterogeneity aid in detecting possible inconsistency.
Survey on the application of deep learning in algorithmic trading

Algorithmic trading is one of the most concerned directions in financial applications. Compared with traditional trading strategies, algorithmic trading applications perform forecasting and arbitrage with higher efficiency and more stable performance. Numerous studies on algorithmic trading models using deep learning have been conducted to perform trading forecasting and analysis. In this article, we firstly summarize several deep learning methods that have shown good performance in algorithmic trading applications, and briefly introduce some applications of deep learning in algorithmic trading. We then try to provide the latest snapshot application for algorithmic trading based on deep learning technology, and show the different implementations of the developed algorithmic trading model. Finally, some possible research issues are suggested in the future. The prime objectives of this paper are to provide a comprehensive research progress of deep learning applications in algorithmic trading, and benefit for subsequent research of computer program trading systems.
Characteristics of the Audience Reached by the National Network of Sexually Transmitted Disease Clinical Prevention Training Centers and Correlation With Sexually Transmitted Infection Rates, 2015 to 2020

Background The National Network of Sexually Transmitted Disease Clinical Prevention Training Centers (NNPTC) trains clinical providers to diagnose and treat sexually transmitted infections (STIs) in the United States. The purpose of this study was to examine the demographics of clinical providers and to correlate the number of training episodes with STI rates at the county level. Methods Registration data were collected between April 1, 2015, and March 31, 2020, in a custom Learning Management System from clinical providers taking NNPTC training. Using the 2018 STI surveillance data, counties were divided into quartiles based on reportable STI case rates and the number of county-level training events was compared per quartile. Univariate and multivariate analyses were conducted in IBM SPSS Statistics 23 (Armonk, NY) and SAS Enterprise Guide 7.1 (Cary, NC). Results From 2015 to 2020, the NNPTC trained 21,327 individuals, predominantly in the nursing professions and working in a public health environment. In multivariate analysis, the number of training events was significantly associated with higher STI rates at the county level (P < 0.0001) and the state where a prevention training center is located (P < 0001). Conclusions The analysis suggests that NNPTC trainings are reaching the clinical providers working in geographic areas with higher STI rates.
On the control of riverbed incision induced by run‐of‐river power plant

Water resource management (WRM) through dams or reservoirs is worldwide necessary to support key human‐related activities, ranging from hydropower production to water allocation and flood risk mitigation. Designing of reservoir operations aims primarily to fulfill the main purpose (or purposes) for which the structure has been built. However, it is well known that reservoirs strongly influence river geomorphic processes, causing sediment deficits downstream, altering water, and sediment fluxes, leading to riverbed incision and causing infrastructure instability and ecological degradation. We propose a framework that, by combining physically based modeling, surrogate modeling techniques, and multiobjective (MO) optimization, allows to include fluvial geomorphology into MO optimization whose main objectives are the maximization of hydropower revenue and the minimization of riverbed degradation. The case study is a run‐of‐the‐river power plant on the River Po (Italy). A 1‐D mobile‐bed hydro‐morphological model simulated the riverbed evolution over a 10 year horizon for alternatives operation rules of the power plant. The knowledge provided by such a physically based model is integrated into a MO optimization routine via surrogate modeling using the response surface methodology. Hence, this framework overcomes the high computational costs that so far hindered the integration of river geomorphology into WRM. We provided numerical proof that river morphologic processes and hydropower production are indeed in conflict but that the conflict may be mitigated with appropriate control strategies.
Nontraditional student expectations and progression: a game theory approach

In this paper it is suggested that a tension may exist between student and institutional expectations of the teaching and learning environment. This conflict may well hinder the progression of the student. A co-evolutionary approach could help to resolve this conflict. The factors that hinder or help progression are encoded in the chromosome, with each factor having different weightings. The random generation of these factor values are used for the payoff in the decision matrix that exists between students and the institute. Utility functions are used to evaluate the effectiveness of each round of the decision matrix, with higher utilities surviving to the next round. This co-evolutionary approach may help institute management appreciate those factors that the student cohort considers important, while the student may develop a better understanding of the requirements for academic study.
Shape memory micro-mechanisms for medical ap

This paper describes the design of micro-mechanisms actuated by shape memory alloys to be used for different medical applications. They are all illustrations oj'a very simple microactuation technology conceived around a wire-like shape memory element. In the same time they show how a hybrid microsystem can be conceived and what ore the specific problems when applying shape memory micro-actuation. Four different systems are described. The firsi one is a very simple microvalve to be used in drug delivery systems. The three other examples are situated in the minimal invasive surgery area: a mirror actuation system, a zooming system, and a bending actuator for colonoscopy.
Rumen Microbiota Alterations During Ketosis is Associated with the Development of Mastitis in Dairy Cows

Backgroud: Mastitis is the most serious disease endangering animal husbandry, especially dairy farming. Clinical investigations indicated that cows suffering from ketosis have a higher probability of mastitis. Rumen microbiota is closely related to ruminant health. However, it is not clear what role it plays in this process.Results: The microbiota in rumen fluid and milk from ketosis cows were determined by 16S rRNA gene sequencing. The results showed that the richness of bacterial community both in rumen and milk were changed in ketosis cows. The abundance of genus Prevotella, Ruminococcus, Succinivibrionaceae_UCG-001 and Streptococcus in rumen fluid from ketosis cows decreased significantly and were negatively correlated with blood BHBA and milk SCC. In contrast, the abundance of genus Luteimonas, Thermomonas, Christensenellaceae_R-7_group, Rikenellaceae_RC9_gut_group, NK4A214_group, Paracoccus, Acetitomaculum, Prevotellaceae_UCG-003, Deinococcus, Saccharofermentans and Butyrivibrio in rumen fluid from ketosis cows increased significantly and were positively correlated with blood BHBA and milk SCC. In addition, the abundance of F082 and Thermomonas were increased, while the abundance of genus Acinetobacter and UCG-005 were reduced both in milk and rumen fluid in ketosis cows than healthy cows. Conclusions: Ketosis in dairy cows is capable of inducing mastitis. The rumen microbiota of ketotic cows changed significantly and is associated with the development of mastitis. Targeting rumen microbiota regulation may be a promising strategy to prevent metabolism disorder and its secondary diseases in dairy cows.
Robust Filtering for Fuzzy Systems With Bounded Disturbances via Premise-Region-Dependent Event-Triggered Mechanisms

This article studies the problem of robust filtering for continuous-time Takagi–Sugeno (T–S) fuzzy systems with bounded external disturbances via premise-region-dependent event-triggered mechanisms (ETMs). First, attention is focused on the analysis and design of piecewise fuzzy filters (PFFs) without considering the ETMs. Then, based on the established PFF, ET PFF with time regularization is designed, such that the new augmented system is Zeno free and $L_{\infty }$ stable, in which new ET conditions that depend on the different regions where the premise variables of the T–S model and the PFF are located are designed. Unlike the existing results, the designed observer gains in the absence of ETMs are also applicable to the case with ETMs, while the ones in the existing methods need to be redesigned. Finally, a simulation example is applied to verify the effectiveness of the proposed filtering scheme.
Virtual reality upper limb model controlled by EMG signals

This work presents the design and development of a six-channel system for acquisition and conditioning of electromyographic signals collected in the upper limb. The main objective of the work is to create a system that can be used as rehabilitation and training instrument for potential users of myoelectric prostheses. Using software rendering, feature extractions, classifier training and design of the mechanical model of the human arm, with the running movements of flexion, extension, pronation and supination of the forearm and the grasp in a reality environment virtual, providing rehabilitation therapy to different patients.
Different Estradiol Level's Impact on Appetite Regulation, Food Intake, and Concentrations of Leptin, Glucagon-Like Peptide-1, and High-Sensitivity C-Reactive Protein During a Long Agonist IVF Protocol

Background: Do different hormonal phases affect appetite regulation, food intake, and concentrations of leptin, glucagon-like peptide-1 (GLP-1), and high-sensitivity C-reactive protein (hs-CRP) during a long agonist in vitro fertilization (IVF) protocol? Does the IVF stimulation induce metabolic changes, which might impact maternal health? Methods: Fifty-four infertile women were encountered thrice, the first of which was at the beginning of their period (low estradiol). The other two were during a gonadotrophin-releasing hormone (GnRH) analog downregulation (low estradiol) and at the end of a follicle-stimulating hormone (FSH) stimulation (high estradiol). The first visit was the reference; the women served as their controls. The concentrations of leptin, GLP-1, and hs-CRP were assessed from plasma. Dietary intake was assessed using food records (FRs) three days before each visit. In addition, weight, height, body mass index (BMI), and plasma levels of estradiol, glucose, HbA1c, insulin, and lipids were monitored. Twenty-six of the subjects also had a postprandial test, in which the blood samples were taken at five time points at every three visits. They also filled visual analog scales to exhibit satiety and appetite. Twenty-eight of the subjects had only fasting blood samples. Results: During the stimulation protocol, leptin concentrations elevated (P<0.001), and energy intake decreased (P=0.03) while estradiol levels increased (P<0.001). GLP-1 levels unchanged (P=0.75) and hs-CRP (P=0.03) concentrations diminished while estradiol levels increased. Conclusions: No increased food intake or weight gain occurred during the stimulation protocol; thus, leptin may protect from overeating during high estradiol levels, and leptin resistance may not occur during a short follow-up. Also, a favorable anti-inflammatory effect was detected. During this study, no harmful metabolic effects occurred, which might have a disproportionate impact on maternal health. Trial registration: Not applicable. This study is a clinical study without intervention.
Old and New Biomarkers Associated with Endothelial Dysfunction in Chronic Hyperglycemia

Chronic hyperglycemia and vascular damage are strictly related. Biomarkers of vascular damage have been intensively studied in the recent years in the quest of reliable cardiovascular risk assessment tools able to facilitate risk stratification and early detection of vascular impairment. The present study is a narrative review with the aim of revising the available evidence on current and novel markers of hyperglycemia-induced vascular damage. After a discussion of classic tools used to investigate endothelial dysfunction, we provide an in-depth description of novel circulating biomarkers (chemokines, extracellular vesicles, and epigenetic and metabolomic biomarkers). Appropriate use of a single as well as a cluster of the discussed biomarkers might enable in a near future (a) the prompt identification of targeted and customized treatment strategies and (b) the follow-up of cardiovascular treatment efficacy over time in clinical research and/or in clinical practice.
Research on Charging-Discharging Operation Strategy for Electric Vehicles Based on Different Trip Patterns for Various City Types in China

Connecting large numbers of electric vehicles to the power grid creates challenges for the operation of the power distribution network, but also provides a new method for supporting grid operation. This paper considers the trip patterns of electric vehicle users in China, including their trip starting time, traffic congestion, vehicle energy consumption, and other factors. We develop a charging–discharging operation strategy for electric vehicles in different functional areas with the goal of minimizing the cost of distribution network, which considers the distribution patterns of electric vehicles in different functional areas. As different types of cities in China have different proportions of electric vehicle users who follow different travel chains, we provide multiple examples showing the effectiveness of our proposed V2G method in different cities.
Retrospective Study Regarding Orthodontic Retention Complications in Clinical Practice

At the end of any orthodontic treatment, retention is a necessary phase. Unfortunately, the current retention devices and the lack of proper oral hygiene on the part of patients lead to the accumulation of dental plaque, periodontal inflammation, and gingival retraction. Our retrospective study included 116 adult patients wearing various types of orthodontic retainers. To quantitatively determine the accumulation of dental plaque, we used the Quigley–Hein plaque index modified by Turesky and the Navy plaque index modified by Rustogi. Another studied parameter was related to the gingival recession associated with retention devices. We had investigated the correctness of patients’ dental hygiene, their preferences for auxiliary means of oral hygiene, the consistency with which they wear the mobile retainers, and respect the orthodontist’s instructions; we also investigated the inconveniences and the accidents that may occur during the retention period. Statistical analysis showed that plaque accumulation is significantly lower in the case of mobile retainer than fixed retainer wearers; the exception was the Hawley plate, where the interdental plaque was more than in all the other studied retainers. Periodontal recessions were more frequent in the case of fixed retainer wearing. Flossing was the most commonly used auxiliary mean for oral hygiene. The compliance of women in wearing vacuum-formed retainers was better than that of men. Patients with a class III history had more plaque accumulation, and class II/1 had the most problems related to detachment/damage of fixed retainers. Mobile retainers proved better results for oral hygiene, but fixed retainers cannot be waved.
Sensorless permanent magnet synchronous motor drive with reduced order observer

In this paper, we present a new approach to the sensorless drive of permanent magnet synchronous motors based on the reduced order observer. First, we propose the new control inputs that decouple the d-axis current with the q-axis one. This enables us to construct the linear reduced order observer for estimating rotor speed and position. Owing to the linearization of the motor model, we can fix optimum gains of the observer under any operating condition. To confirm the validity of the proposed control scheme, experiments are carried out. The control is performed for the prototype of an eight-pole, 750 W permanent magnet synchronous motor by using the software with DSP-TMS320C31. The experimental results show high dynamic performance of the proposed control scheme.
SIRT1 Attenuates Apoptosis of Nucleus Pulposus Cells by Targeting Interactions between LC3B and Fas under High-Magnitude Compression

Mechanical overloading-induced nucleus pulposus cell (NPC) apoptosis plays a core role in the pathogenesis of intervertebral disc degeneration. In this study, we investigated the involvement of mammalian silent information regulator 2 homolog (SIRT1) in NPC apoptosis under high-magnitude compression. Our results showed that high-magnitude compression aggravated cellular apoptosis and attenuated the expression levels of SIRT1 and microtubule-associated protein-1 light chain-3B (LC3B) in rat NPCs in a three-dimensional (3D) cell culture model and an in vivo rat tail compression model, whereas SIRT1 overexpression in NPCs partially reversed these indicators. Moreover, SIRT1 overexpression increased the formation of the LC3B/Fas complex, alleviated activation of the NF-κB pathway, and reduced NPC apoptosis. Finally, downregulation of LC3B partially activated the NF-κB pathway and aggravated NPC apoptosis. Overall, upregulation of SIRT1 increases formation of the LC3B/Fas complex, which contributes to suppression of NPC apoptosis by inhibiting the NF-κB pathway under high compressive stress.
Integration of 3D tracking systems for Interaction in Spatial Augmented Reality

In this thesis, a projector-based Spatial Augmented Reality (SAR) system designed and developed to be applied to support physical and virtual 3D Rapid Prototyping in the field of Industrial Design Engineering is presented. The main contribution is a 3D scanner to get a virtual model of a physical model and tools to support the design of features interactively, on the object’s surface. More specifically, this work contains an approach to set the hardware to support SAR, else known as hardware calibration for SAR. Each hardware entity is calibrated with respect to a common “world”, in order to achieve effective communication. This world is set to coincide with the graphics world, and this allows us to imagine being inside the 3D graphics world while the virtual content is rendered onto the scene’s objects. In order to identify the basic ingredients that enable interaction in our SAR system, we take into account the limitations of Rapid Prototyping process, background knowledge for SAR systems and related work. Therefore, we designed the interaction components of the system according to characteristics of our setting. The SAR system was designed to perform in the peripersonal region. In this region, the user inserts input via a constructed IR tracked pen and a dynamic menu is used as interface to the system. Functionality such as selection, feedback and annotation is enabled for interacting with the SAR system. The system’s application is divided into two parts. The first part includes the use of the RGB-D camera and the IR tracker for the construction of a 3D scanner, in order to produce a virtual model of an object through sampling, segmentation, and registration of sequential point clouds. In the second part, the result of the scanning process, which is a polygonal mesh of the scanned object, is added to the SAR system’s application that enables interaction with virtual models and the ground level of the world. These two parts of the SAR system application aim to support industrial designers in the scanning of a freshly made physical prototype, and enable the design of features on the corresponding virtual model by using the SAR system during the rapid prototyping process. In order to identify the strong points and weaknesses of the current state of the SAR system application, we carried out a user evaluation. 21 students from the Faculty of Industrial Design Engineering evaluated the two parts of the system’s application. The results show that the SAR system is useful and that it has great potential in the field of Industrial Design Engineering. Nevertheless, there is still room for improvement and future work, in order to be fully applied in the field.
Current Development in Interdigital Transducer (IDT) Surface Acoustic Wave Devices for Live Cell In Vitro Studies: A Review

Acoustics have a wide range of uses, from noise-cancelling to ultrasonic imaging. There has been a surge in interest in developing acoustic-based approaches for biological and biomedical applications in the last decade. This review focused on the application of surface acoustic waves (SAW) based on interdigital transducers (IDT) for live-cell investigations, such as cell manipulation, cell separation, cell seeding, cell migration, cell characteristics, and cell behaviours. The approach is also known as acoustofluidic, because the SAW device is coupled with a microfluidic system that contains live cells. This article provides an overview of several forms of IDT of SAW devices on recently used cells. Conclusively, a brief viewpoint and overview of the future application of SAW techniques in live-cell investigations were presented.