Miracle-dz/UniFAR-FTUs huggingface dataset:
Increased Serum Adipsin Correlates with MAFLD and Metabolic Risk Abnormalities

Purpose A panel of international experts proposed a new definition of fatty liver in 2020, namely metabolic dysfunction-associated fatty liver disease (MAFLD). As an adipokine, adipsin is closely related to metabolic-related diseases. In this study, we aimed to evaluate the relationship among MAFLD, serum adipsin, and metabolic risk abnormalities. Methods Our study was a cross-sectional study based on the first follow-up of the Guangzhou Nutrition and Health Study (GNHS). A total of 908 patients with hepatic steatosis were involved in our study. Detailed data of patients were collected based upon questionnaire information, physical examination, and blood biochemical test. Results Among the 908 patients, 789 patients were diagnosed with MAFLD. The levels of serum adipsin in the MAFLD group and non-MAFLD group were (3543.00 (3187.94–3972.50) ng/mL) and (3095.33 (2778.71–3354.77) ng/mL) (P < 0.001), respectively. After adjusting for potential confounders, adipsin levels were found to be associated with MAFLD. The OR was 3.46 (95% CI: 1.57–7.64) for adipsin when comparing subjects in the highest tertile with those in the lowest tertile. With the increase in the number of metabolic risk abnormalities, both the levels of serum adipsin and the proportion of moderate to severe fatty liver increased (all p-trend < 0.001). Conclusion Increased serum adipsin correlates with MAFLD. Both adipsin levels as well as fatty liver severity increase with higher numbers of metabolic risk abnormalities.
Theory of Diamagnetism of Graphite

The conduction-electron diamagnetism was calculated for the three- dimensional band structure of graphite. The magnetic energy levels are found and the susceptibility calculated by analytically carrying out the free energy sum. Agreement with experiment is found for values of the band parameters nearly equal to those which give agreement with the de Haas-van Alphen effect and other phenomena. The value of gamma /sub 0/ is found to be 2.8 plus or minus 0.1 ev. The results indicate the gamma /sub 1/ is about 0.27 ev and DELTA is about 0.025. The other band parameters do not have an important influence upon the value of the susceptibility. The relation to the general treatments of conduction-electron diamagnetism is also discussed. (auth)
Nonperiodic Multirate Sampled-Data Fuzzy Control of Singularly Perturbed Nonlinear Systems

Choosing adequate sampling frequencies in sensors has a considerably positive impact on the two time scale fuzzy logic controller design. Motivated by this concept, this article addresses the fuzzy-parallel distribution compensation (PDC)-based control synthesis for a singularly perturbed nonlinear systems (SPNS) under a nonperiodic multirate sampling mechanism, which also provides guidance on the reasonable choice of maximum allowable sampling time intervals (MASTIs) for multirate sensors. First, the sampled SPNS is converted into a continuous-time Takagi-Sugeno fuzzy singularly perturbed model (TSFSPM) with slow and fast time-varying delays. Then, an <inline-formula><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula>-dependent Lyapunov-Krasovskii functional of order <inline-formula><tex-math notation="LaTeX">$n$</tex-math></inline-formula> is proposed to derive the sufficient conditions for stabilizing a multirate sampled TSFSPM under a two time scale PDC control. Given the slow MASTI, an efficient linear-matrix-inequality-based design is proposed to recast the <inline-formula><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula>-dependent stabilization conditions as a set of <inline-formula><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula>-independent linear matrix inequalities that are easily solved. On this basis, the upper bound of singular perturbation parameter <inline-formula><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula>, i.e., <inline-formula><tex-math notation="LaTeX">$\epsilon ^*$</tex-math></inline-formula>, should be determined to compute the fast MASTI for the possibly slow sampling of fast states. The optimal match of <inline-formula><tex-math notation="LaTeX">$(\epsilon ^*,n)$</tex-math></inline-formula> is detected for a tradeoff among the closed-loop stability, the controller performance, and the sensor cost. The superiority of the obtained results is shown in an example of a flexible joint inverted pendulum system.
A growth model to estimate economic values for food intake capacity in pigs

A biological growth model was developed to study economic values for average ad libitum food intake capacity (FIC) in growing pigs. The model was based on the linear/plateau relationship between protein deposition and food intake. Input variables were: minimum fat to protein deposition ratio (R), maximum protein deposition rate (Pdmax)and food intake (FI). Output variables were production traits and production costs. Economic values (under commercial conditions with ad libitum feeding) were derived with the growth model for each of the traits FIC, R, and Pdmax keeping the other two traits constant, for three alternative levels of FIC. If FIC was too low to realize Pdmax, FIC had a positive economic value, R had a negative economic value and the value of Pd max was zero. If FIC was higher than necessary to realize Pd max , economic values were negative, zero and positive for FIC, R, and Pd max respectively. If FIC was just sufficient to realise Pdmax, the lowest production costs occurred. Now, R had a negative economic value and Pdmax had a positive economic value. With a restricted feeding regimen under commercial conditions a daily food supply just sufficient to realize Pd max should be pursued. It was concluded that use of a biological growth model to estimate economic values for FIC would give more insight into correct selection strategies than would the use of an economic model.
Prediction of Functional Outcome in Stroke Patients with Proximal Middle Cerebral Artery Occlusions Using Machine Learning Models

At present, clinicians are expected to manage a large volume of complex clinical, laboratory, and imaging data, necessitating sophisticated analytic approaches. Machine learning-based models can use this vast amount of data to create forecasting models. We aimed to predict short- and medium-term functional outcomes in acute ischemic stroke (AIS) patients with proximal middle cerebral artery (MCA) occlusions using machine learning models with clinical, laboratory, and quantitative imaging data as inputs. Included were consecutive AIS patients with MCA M1 and proximal M2 occlusions. The XGBoost, LightGBM, CatBoost, and Random Forest were used to predict the outcome. Minimum redundancy maximum relevancy was used for selecting features. The primary outcomes were the National Institutes of Health Stroke Scale (NIHSS) shift and the modified Rankin Score (mRS) at 90 days. The algorithm with the highest area under the receiver operating characteristic curve (AUROC) for predicting the favorable and unfavorable outcome groups at 90 days was LightGBM. Random Forest had the highest AUROC when predicting the favorable and unfavorable groups based on the NIHSS shift. Using clinical, laboratory, and imaging parameters in conjunction with machine learning, we accurately predicted the functional outcome of AIS patients with proximal MCA occlusions.
ALIEN: Assisted Learning Invasive Encroachment Neutralization for Secured Drone Transportation System

Priority-based logistics and the polarization of drones in civil aviation will cause an extraordinary disturbance in the ecosystem of future airborne intelligent transportation networks. A dynamic invention needs dynamic sophistication for sustainability and security to prevent abusive use. Trustworthy and dependable designs can provide accurate risk assessment of autonomous aerial vehicles. Using deep neural networks and related technologies, this study proposes an artificial intelligence (AI) collaborative surveillance strategy for identifying, verifying, validating, and responding to malicious use of drones in a drone transportation network. The dataset for simulation consists of 3600 samples of 9 distinct conveyed objects and 7200 samples of the visioDECT dataset obtained from 6 different drone types flown under 3 different climatic circumstances (evening, cloudy, and sunny) at different locations, altitudes, and distance. The ALIEN model clearly demonstrates high rationality across all metrics, with an F1-score of 99.8%, efficiency with the lowest noise/error value of 0.037, throughput of 16.4 Gbps, latency of 0.021, and reliability of 99.9% better than other SOTA models, making it a suitable, proactive, and real-time avionic vehicular technology enabler for sustainable and secured DTS.
A representation of multivariate normal probability integrals by integral transforms

SUMMARY By using the integral representation of the Hermite polynomial, the tetrachoric series for arbitrary dimension K is transformed into a finite sum of multivariate Fourier transforms over (- oo, oo) each involving the normal characteristic function divided by the product of the variables of integration. These integral transforms are evaluated numerically by Gaussian quadrature and provide rapidly convergent formulae for the multivariate normal probability integral.
Generation of micro gas bubbles of uniform diameter in an ultrasonic field

Consecutive images of the fragmentation of capillary waves in an ultrasonic field were obtained using a high-speed video camera through a microscope at a frame rate of 500000 frames per second. The images showed that micro bubbles of uniform diameter from 4 to 15$\,\mu$m were generated at a constant periodic rate when a small amount of gas was introduced (via a needle) into a highly viscous liquid whose kinematic viscosity was between 5 and 100 mm$^{2}\,{\rm s}^{-1}$. Conditions for stable generation of micro bubbles of uniform diameter were also studied by changing the inner diameter of the needle between 0.08 and 0.34 mm, excitation frequency of around 18.77 and 42.15 kHz, kinematic viscosity of liquid between 5 and 100 mm$^{2}\,{\rm s}^{-1}$, surface tension between 20 and 34 mN m$^{-1}$, and viscosity of gas between 9.0 and 31.7$\,\mu$Pa s. Results revealed that (i) a projection is formed on the oscillatory gas–liquid interface and micro bubbles are released from the tip of the projection; (ii) gas viscosity critically affects the formation of the projection and should be around 20.0$\,\mu $Pa s for stable mother bubble oscillation; (iii) conditions for stable generation of micro bubbles are also affected by excitation frequency, surface tension and viscosity of the liquid, and dimensions of the needle; (iv) two controlling parameters for stable generation are the Weber number (${\it We}\,{=}\,\rho {f}^{2}d_{\hbox{\scriptsize{\it in}}}^{3}/\sigma $, where $\rho $ is the density of the liquid, $f$ is the excitation frequency, $d_{\hbox{\scriptsize{\it in}}}$ is the inner diameter of the needle, and $\sigma $ is the surface tension) and the Womersley number (${\it Wo}\,{=}\,d_{\hbox{\scriptsize{\it in}}}(f/{\nu })^{1 / 2}$, where $\nu $ is the kinematic viscosity of liquid); and (v) uniform-diameter micro bubbles are generated stably when ${\it We}<300$ and $2<$ ${\it Wo}<5$. Under the conditions where micro bubbles of uniform diameter were stably generated, the bubble diameter increased almost linearly with increasing gas pressure inside the needle. The gradient of this linear function can be expressed as a function of Wo We, and the normalized outer diameter of the needle, and decreases either with decreasing inner diameter of the needle or with increasing excitation frequency, surface tension and viscosity of the liquid, and outer diameter of the needle.
NEGL: Lightweight and Efficient Neighborhood Encoding-Based Global Localization for Unmanned Ground Vehicles

This paper proposes a lightweight and efficient Neighborhood Encoding-based Global Localization (NEGL) approach for unmanned ground vehicles (UGVs). To realize the reliable feature description and overcome the restriction of limited Field of View (FOV), neighborhood encoding (NE) scheme is firstly proposed to describe the feature via constructing the structural relationship among neighborhood features. Following that, the reliability of NE scheme is analyzed through the NE-similarity measurement between the priori feature and the detected feature. In addition, the probability model of NEGL is proposed, which is a novel idea based on the priori feature map and simplified through the hierarchical clustering and distance-triggered multiple hypothesis tracking (DT-MHT). Finally, the correct global pose of the vehicle under ambiguous environments is gradually recovered. Comparative experiments using the publicly available datasets and our self-recorded datasets are conducted, and evaluation results show the superior performance of NEGL on success ratio, efficiency, running time and localization accuracy over the adaptive Monte Carlo localization (AMCL), NE+AMCL and Cartographer. Additionally, the experimental results of different FOVs demonstrate NEGL is independent on the range and the direction of the FOV.
Nanoimprint lithography process chains for the fabrication of micro- and nanodevices

Abstract. The nanoimprint lithography (NIL) process with its key elements molding and thin film pattern transfer refers to the established process chain of resist-based patterning of hard substrates. Typical processes for mass fabrication are either wafer-scale imprint or continuous roll-to-roll processes. In contrast to this, similar process chains were established for polymeric microelements fabricated by injection molding, particularly when surface topographies need to be integrated into monolithic polymer elements. NIL needs to be embedded into the framework of general replication technologies, with sizes ranging from nanoscopic details to macroscopic entities. This contribution presents elements of a generalized replication process chain involving NIL and demonstrates its wide application by presenting nontypical NIL products, such as an injection-molded microcantilever. Additionally, a hybrid approach combining NIL and injection molding in a single tool is presented. Its aim is to introduce a toolbox approach for nanoreplication into NIL-based processing and to facilitate the choice of suitable processes for micro- and nanodevices. By proposing a standardized process flow as described in the NaPANIL library of processes, the use of establish process sequences for new applications is facilitated.
Social Capital—Can It Weaken the Influence of Abusive Supervision on Employee Behavior?

The travel industry has been severely affected by the COVID-19 outbreak. The operating pressure on enterprises has sharply increased, leading to the prominent phenomenon of abusive supervision. Managers employ this management method so that employees perceive work pressure as motivation to work harder and improve their performance. Employees may adopt the behavior of defensive silence to protect themselves from abusive supervision, which can subsequently affect employee behavior. However, social capital and relationships may lessen this effect. This study analyzed survey data on 475 workers from the Chinese tourism service industry to examine the mediating role of workers’ defensive silence under abusive supervision, employee behavior, and the moderating role of social capital. The results showed that abusive supervision does not promote employee performance but hinders employee growth. Employees’ defensive silence also affects employee behavior and has a partially mediating role in the relationship between abusive supervision and employee behavior. Social capital can mitigate the negative impact of abusive supervision on employee behavior. This study theoretically expands the applicable scope of employee silence as a mediating variable and social capital as a moderating variable. It is helpful for managers to change their negative leadership style, follow the suggestions of employees, pay attention to the organizational atmosphere, and enhance their team cohesion.
Numerical analysis of fractional-order tumor model

In this paper, the tumor-immune dynamics are simulated by solving a nonlinear system of differential equations. The fractional-order mathematical model incorporated with three Michaelis–Menten terms to indicate the saturated effect of immune response, the limited immune response to the tumor and to account the self-limiting production of cytokine interleukin-2. Two types of treatments were considered in the mathematical model to demonstrate the importance of immunotherapy. The limiting values of these treatments were considered, satisfying the stability criteria for fractional differential system. A graphical analysis is made to highlight the effects of antigenicity of the tumor and the fractional-order derivative on the tumor mass.
The Vascular Flora of Autauga County, Alabama

ABSTRACT The vascular flora of Autauga County, Alabama, was surveyed from 2016 to 2020. A total of 168 families, 617 genera, 1,393 species, and eight named hybrids are reported. Of the 1,393 species, 1,097 were collected during this study and 296 are from the search of online databases. Thirty of the species are listed on The Inventory List of Rare, Threatened, and Endangered Plants and Animals of Alabama. Approximately 21.4% of the flora (298 species), are considered non-native. Families with the largest number of species and named hybrids were Asteraceae (162), Poaceae (147), Fabaceae (100), Cyperaceae (96), Rosaceae (42), and Lamiaceae (33).
An improved integrated coherent receiver optical-electronic testing system

We present an improved 400G chip/device level Integrated Coherent Receiver (ICR) optical-electronic testing system based on the system last year [1]. It shows high repeatability and high accuracy compared with commercial system. This new system can greatly promote the efficiency, and it is also compatible for 100G/400G chip level test and device level test. What’s more, the system can get most of important parameters of ICR automatically.
Unsupervised Curve Clustering using B‐Splines

Data in many different fields come to practitioners through a process naturally described as functional. Although data are gathered as finite vector and may contain measurement errors, the functional form have to be taken into account. We propose a clustering procedure of such data emphasizing the functional nature of the objects. The new clustering method consists of two stages: fitting the functional data by B‐splines and partitioning the estimated model coefficients using a k‐means algorithm. Strong consistency of the clustering method is proved and a real‐world example from food industry is given.
Multi-Scale Thermal Modeling of RRAM-based 3D Monolithic-Integrated Computing-in-Memory Chips

Calculation of chip-scale temperature distribution with considering the device behaviors and integration structure is a challenging modeling task. In this paper, we demonstrated the first multi-scale thermal simulation for RRAM-based computing-in-memory chips. To achieve this, we developed a thermal modeling framework, from RRAM device to two level of circuits, 3D integration architecture, and chip package. We assess the temperature distributions under different technology nodes, different cooling methods, and different operation conditions. Furthermore, with the embedded compact model of RRAM, the thermal effects on the computing accuracy of deep neural network computing is evaluated. Some useful design guidelines are provided based on the simulation results.
Two-Dimensional Transition Metal Dichalcogenide Based Biosensors: From Fundamentals to Healthcare Applications

There has been an exponential surge in reports on two-dimensional (2D) materials ever since the discovery of graphene in 2004. Transition metal dichalcogenides (TMDs) are a class of 2D materials where weak van der Waals force binds individual covalently bonded X–M–X layers (where M is the transition metal and X is the chalcogen), making layer-controlled synthesis possible. These individual building blocks (single-layer TMDs) transition from indirect to direct band gaps and have fascinating optical and electronic properties. Layer-dependent opto-electrical properties, along with the existence of finite band gaps, make single-layer TMDs superior to the well-known graphene that paves the way for their applications in many areas. Ultra-fast response, high on/off ratio, planar structure, low operational voltage, wafer scale synthesis capabilities, high surface-to-volume ratio, and compatibility with standard fabrication processes makes TMDs ideal candidates to replace conventional semiconductors, such as silicon, etc., in the new-age electrical, electronic, and opto-electronic devices. Besides, TMDs can be potentially utilized in single molecular sensing for early detection of different biomarkers, gas sensors, photodetector, and catalytic applications. The impact of COVID-19 has given rise to an upsurge in demand for biosensors with real-time detection capabilities. TMDs as active or supporting biosensing elements exhibit potential for real-time detection of single biomarkers and, hence, show promise in the development of point-of-care healthcare devices. In this review, we provide a historical survey of 2D TMD-based biosensors for the detection of bio analytes ranging from bacteria, viruses, and whole cells to molecular biomarkers via optical, electronic, and electrochemical sensing mechanisms. Current approaches and the latest developments in the study of healthcare devices using 2D TMDs are discussed. Additionally, this review presents an overview of the challenges in the area and discusses the future perspective of 2D TMDs in the field of biosensing for healthcare devices.
Forksheet FETs with Bottom Dielectric Isolation, Self-Aligned Gate Cut, and Isolation between Adjacent Source-Drain Structures

We report on forksheet field-effect transistors that are isolated from the substrate by bottom dielectric isolation (BDI) formed by replacing a SiGe epitaxial layer with a dielectric film while the devices are anchored to the substrate by forksheet walls. Functional unipolar forksheet devices with BDI are demonstrated for both N- and PMOS, for wall widths down to 10 nm. In addition, we describe a scheme to isolate adjacent source-drain structures by the forksheet dielectric wall. This scheme relies on increasing wall height, by means of active area patterning hard mask engineering, to compensate for wall losses in downstream process modules. Finally, self-alignment of gate cut to active is demonstrated morphologically.
Oxytocin level among heroin users and its correlation with personality traits and perceived childhood neglect

Introduction: The oxytocin (OXT) levels and personality traits of heroin addicts and control participants are significantly different, which may be a sign of a general propensity to substance use disorders. The aberration of OXT secretion was also linked to unfavorable early experiences, such as neglect as a youngster. Aim of the study: To determine whether there were any baseline variations in oxytocin levels between individuals with heroin use disorder and healthy controls, as well as the relationship between oxytocin levels and patients' assessments of childhood neglect. Subjects and methods