Miracle-dz/UniFAR-FTUs huggingface dataset:
Serum Fibroblast Growth Factor 23 Levels are Associated with Vascular Smooth Muscle Dysfunction in Type 2 Diabetes

Aim: Increased level of serum fibroblast growth factor 23 (FGF23) is a hallmark of abnormal phosphate metabolism in patients with chronic kidney disease (CKD) and is recently shown to be associated with the risk of cardiovascular disease even in those without CKD. This study investigated the association between serum FGF23 levels and vascular function in patients with type 2 diabetes. Methods: This was a cross-sectional study involving 283 Japanese patients with type 2 diabetes. Flow-mediated dilatation (FMD) and nitroglycerin-mediated dilatation (NMD) of the brachial artery were measured via ultrasonography to evaluate vascular endothelial and smooth muscle functions, respectively. Serum intact FGF23 levels were determined via a sandwich enzyme-linked immunosorbent assay. Results: The median values of FMD, NMD, and serum FGF23 were 6.0%, 14.0%, and 27.3 pg/mL, respectively. The serum FGF23 levels were inversely associated with NMD but not with FMD, and the association was independent of atherosclerotic risk factors, estimated glomerular filtration rate (eGFR), and serum phosphate levels. Furthermore, the relationship between serum FGF23 levels and NMD was modified by kidney function, which was pronounced in subjects with normal kidney function (eGFR ≥ 60 mL/min/1.73 m2). Conclusion: Serum FGF23 levels are independently and inversely associated with NMD in patients with type 2 diabetes, particularly in those with normal kidney function. Our results indicate that FGF23 is involved in vascular smooth muscle dysfunction and that increased serum levels of FGF23 may serve as a novel biomarker for vascular smooth muscle dysfunction in patients with type 2 diabetes.
Orchestration of Mitochondrial Function and Remodeling by Post-Translational Modifications Provide Insight into Mechanisms of Viral Infection

The regulation of mitochondria structure and function is at the core of numerous viral infections. Acting in support of the host or of virus replication, mitochondria regulation facilitates control of energy metabolism, apoptosis, and immune signaling. Accumulating studies have pointed to post-translational modification (PTM) of mitochondrial proteins as a critical component of such regulatory mechanisms. Mitochondrial PTMs have been implicated in the pathology of several diseases and emerging evidence is starting to highlight essential roles in the context of viral infections. Here, we provide an overview of the growing arsenal of PTMs decorating mitochondrial proteins and their possible contribution to the infection-induced modulation of bioenergetics, apoptosis, and immune responses. We further consider links between PTM changes and mitochondrial structure remodeling, as well as the enzymatic and non-enzymatic mechanisms underlying mitochondrial PTM regulation. Finally, we highlight some of the methods, including mass spectrometry-based analyses, available for the identification, prioritization, and mechanistic interrogation of PTMs.
Using YouTube's Social Media Analytics for Engineering Educators

Videos are an effective means of knowledge delivery and educators are increasingly using videos as part of their pedagogy. While many universities have digital teaching and learning platforms, most of these platforms are not specifically designed for video-based tuition. Social media platforms, however, have become a popular choice for the uploading of educational content. YouTube is the largest media sharing platform worldwide and provides educators the capacity to share their knowledge with a global audience. In so doing, YouTube provides extensive metrics as part of its social media analytics which are powerful tools that educators can use to improve their educational content and increase their impact on the platform. While there has been some scholarly activity on social media analytics, few, if any, publications are aimed at explaining what YouTube's social media analytics are and how educators can use them to improve their content. This article aims to critically explain and analyse 14 of YouTube's social media analytics to assist educators in increasing their impact. The article reports on the success of numerous engineering tutorial videos published in 2020 and 2021 that have accrued over 1 million views on YouTube. The aim of this article is to provide the reader with practical tools to improve their own offerings on public networks such as YouTube. Since as much as 60% of all YouTube views originate from YouTube's recommendations rather than from direct search queries, YouTube's recommender system is also presented in this article.
Carbon price forecasting based on data decomposition, adaptive boosting algorithm, and Elman neural network

The prediction of carbon price can contribute to the reduction of carbon emissions. A carbon price forecasting model based on the data decomposition method, adaptive boosting (AdaBoost) algorithm, and Elman neural network (ENN) is proposed in this paper, which firstly decomposes original data into subsequences by the variational mode decomposition algorithm, and then combines the ENN models by the AdaBoost.RT algorithm to forecast each subsequence, and finally the predicted results of each subsequence are combined into the final prediction results. Using the carbon price in Beijing, China as the experimental data, the evaluation errors certify that the proposed ensemble model can achieve a better forecasting effect than the single models including the ENN, extreme learning machine, and long short-term memory network and the ensemble model AdaBoost.RT-ENN, which proves the effectiveness of the data decomposition and adaptive boosting algorithm.
Exact Analytical Solutions of Damped Periodic Structures

An analytical procedure for the dynamic analysis of damped periodic systems is presented. An equivalent system with cyclic periodicity is first formed to replace the original periodic system. The U transformation method is then used to uncouple the dynamic equations and the continuity conditions of the equivalent system. Consequently the exact analytical solutions can be easily obtained.
Three-dimensional transport of neutral particles in the CHS edge region

We used Monte Carlo simulation code DEGAS and studied the neutral particle behavior in the Compact Helical System (CHS) three-dimensionally. In contrast to other helical devices, the CHS plasma in the standard configuration has contact with the inner vacuum vessel wall like the material limiter used in many Tokamaks and the neutral recycling becomes dominant there. As the intensity of neutral recycling changes also along toroidal direction, we extended our previous simulation model geometry three-dimensionally and compared the results of these models. We found the variation of the gap between the vacuum wall and main plasma enhanced toroidal transport of hydrogen molecules and atoms. As the formation of the edge transport barrier (EBT) discovered recently in CHS is characterized by a clear drop in Hα emissions, it is interesting to study the relationship with the profile of atomic/molecular hydrogen and the Hα emission profile. We estimated emission not only from excited hydrogen atoms but also from dissociated molecules with a collisional radiation model. We found that our Hα detector signal in CHS mostly came from excited atoms and that the emission profile largely changed with the ETB formation.
A PRINTED LOG-PERIODIC TREE-DIPOLE ANTENNA (PLPTDA)

A miniaturized printed log-periodic fractal dipole antenna is proposed. Tree fractal structure is introduced in an antenna design and evolves the traditional Euclidean log-periodic dipole array into the log-periodic second-iteration tree-dipole array (LPT 2 DA) for the flrst time. Main parameters and characteristics of the proposed antenna are discussed. A fabricated proof-of-concept prototype of the proposed antenna is etched on a FR4 substrate with a relative permittivity of 4.4 and volume of 490mm £ 245mm £ 1:5mm. The impedance bandwidth (measured VSWR < 2) of the fabricated antenna with approximate 40% reduction of traditional log-periodic dipole antenna is from 0.37 to 3.55GHz with a ratio of about 9.59 : 1. Both numerical and experimental results show that the proposed antenna has stable directional radiation patterns and apparently miniaturized efiect, which are suitable for various ultra-wideband applications.
Effects on hematology and blood biochemistry profile of intramuscular meloxicam injection in Brahminy kite and Barn owl

Background Meloxicam is used widely for exotic animal analgesia, but its toxicity in common raptor species in Thailand is unclear. Objectives This study evaluated the single-dose effect of intramuscular meloxicam in common raptor species in Thailand for short-term and long-term periods. Methods Twenty-two raptors were administered a single 1 mg/kg dose of meloxicam individually via intramuscular injection. The following were evaluated: clinical appearance, body weight, body condition score, body temperature, fecal appearance, complete blood cell count, and biochemistry panel before (day 0) and after the injection (1, 7, and 30 days). The collected samples were categorized into three groups: Brahminy kite (Haliastur indus) (n = 10), adult Barn owl (Tyto javanica) (n = 4), and juvenile Barn owl (n = 8). Results None of the raptors in the study groups showed any abnormalities. The hematological profiles were significantly different in the short-term period (day 1 and day 7). The creatinine, aspartate aminotransferase, and creatinine kinase increased in several groups. On the other hand, the packed cell volume decreased in the Brahminy kite and juvenile Barn owl groups. According to the findings, an intramuscular injection of 1 mg/kg meloxicam affected the blood biochemistry panel of the muscle, but the affected raptors recovered within one week. Conclusions An intramuscular injection of meloxicam at a single 1 mg/kg dose in Brahminy kites and Barn owls was not associated with the morbidity, hepatotoxicity, gastrointestinal toxicity, and nephrotoxicity in the short- and long-term periods.
Score Statistic and Its Local Influence Analysis in Weighted Nonlinear Regression

The assumption of homoscedasticity is a commonly concerned problem in regression analysis. Cook and Weisherg (1983) provided a diagnostic test for heteroscedasticity based on the score statistic in linear regression. In this paper, we extend their result to nonlinear regression . We also obtain a modified score statistic based on the method of Cox and Reid (1987) in which the orthogonality between parameters of interest and nuisance parameters is used. Furthermore,we study the local influence of small perturbations on the score statistic and corresponding diagnostic measures are presented. A numerical example is given to illustrate our results.
The Potential Applications of Reinforced Bioplastics in Various Industries: A Review

The introduction of bioplastics has been an evolution for plastic industry since conventional plastics have been claimed to cause several environmental issues. Apart from its biodegradability, one of the advantages can be identified of using bioplastic is that they are produced by renewal resources as the raw materials for synthesis. Nevertheless, bioplastics can be classified into two types, which are biodegradable and non-biodegradable, depending on the type of plastic that is produced. Although some of the bioplastics are non-biodegradable, the usage of biomass in synthesising the bioplastics helps in preserving non-renewable resources, which are petrochemical, in producing conventional plastics. However, the mechanical strength of bioplastic still has room for improvement as compared to conventional plastics, which is believed to limit its application. Ideally, bioplastics need to be reinforced for improving their performance and properties to serve their application. Before 21st century, synthetic reinforcement has been used to reinforce conventional plastic to achieve its desire properties to serve its application, such as glass fiber. Owing to several issues, the trend has been diversified to utilise natural resources as reinforcements. There are several industries that have started to use reinforced bioplastic, and this article focuses on the advantages of using reinforced bioplastic in various industries and its limitations. Therefore, this article aims to study the trend of reinforced bioplastic applications and the potential applications of reinforced bioplastics in various industries.
Aspect ratio- and size-controlled patterned triangulations of parametric surfaces

A method to produce patterned, controlled size triangulation of Boundary Representations is presented. Although the produced patterned triangulations are not immediately suited for fast visualization, they were used in Fixed Grid Finite Element Analysis, and do provide a control on the aspect ratio or shape factor of the triangles produced. The method presented first calculates a triangulation in the parameter space of the faces in which the B-Rep is partitioned and then maps it to 3D space. Special emphasis is set in ensuring that the triangulations of neighboring faces meet in a seamless manner, therefore ensuring that a borderless C2 2-manifold would have as triangulation a C0 borderless 2-manifold. The method works properly under the conditions (i) the parametric form of the face is a 1--1 function, (ii) the parametric pre-image of a parametric face is a connected region, and (iii) the user-requested sampling frequency (samples per length unit) is higher than twice the spatial frequency of the features in the B-Rep (thus respecting the Nyquist principle). As the conditions (i) and (ii) are possible under face reparameterization or sub-division and the condition (iii) is the minimum that a triangulation should comply with, the method is deemed as generally applicable.
Differential object marking in Latgalian

This article discusses variation in object marking in Latgalian, based on sources where this phenomenon is most pronounced. Differential object marking in Latgalian consists in the choice of the genitive instead of the accusative for objects of transitive verbs. Genitive marking regularly appears in negated clauses and in constructions with the supine. It is optionally used in clauses that portray a situation as unreal, unlikely, or undesired from the point of view of the speaker. Apart from these clause-related factors, genitive marking is common though less regular with mass nouns and count nouns in the plural in descriptions of single events, while for habitually occurring events the accusative is used. The use of the partitive genitive is increasingly coupled with prefixing of the verb. A further type is the use of the genitive with cumulative verbs. There is also a small group of non-derived verbs that select the genitive. Those that have a nominative subject tend to become transitive verbs in modern written Latgalian.
Guamara and Cocuixtle: Source of Proteases for the Transformation of Shrimp By-Products into Hydrolysates with Potential Application

Simple Summary Guamara and cocuixtle fruits are underutilized and the need arises to use them because they can favor the production of hydrolyzates, in addition to the fact that white shrimp is the crustacean that is produced in the greatest quantity in Mexico, of which approximately 50% of the total weight of shrimp is wasted. The objective of this research was to determine the optimum conditions for obtaining protein hydrolyzates from cooked shrimp waste, since it has been mentioned that cooking the shells improves their digestibility. This study is of vital importance for the utilization of resources, in addition to opening the possibility of using a new drug with antioxidant capacity or, failing that, to be used as a food additive to produce functional foods. Abstract Since the fruits of Bromelia pinguin and Bromelia karatas are rich in proteases, the aim of this research was to optimize the hydrolysis process of cooked white shrimp by-products due to the effect of these proteases. A robust Taguchi L16’ design was used to optimize the hydrolysis process. Similarly, the amino acid profile by GC-MS and antioxidant capacity (ABTS and FRAP) were determined. The optimal conditions for hydrolysis of cooked shrimp by-products were pH 8.0, 30 °C, 0.5 h, 1 g of substrate and 100 µg/mL of B. karatas, pH 7.5, 40 °C, 0.5 h, 0.5 g substrate and 100 µg/mL enzyme extract from B. pinguin and pH 7.0, 37 °C, 1 h, 1.5 g substrate and 100 µg/mL enzyme bromelain. The optimized hydrolyzates of B. karatas B. pinguin and bromelain had 8 essential amino acids in their composition. The evaluation of the antioxidant capacity of the hydrolyzates under optimal conditions showed more than 80% inhibition of in ABTS radical, B. karatas hydrolyzates had better higher ferric ion reduction capacity with 10.09 ± 0.02 mM TE/mL. Finally, the use of proteolytic extracts from B. pinguin and B. karatas to optimize hydrolysis process allowed obtaining hydrolyzates of cooked shrimp by-products with potential antioxidant capacity.
Direct numerical simulation of the turbulent boundary layer over a cube-roughened wall

Direct numerical simulation (DNS) of a spatially developing turbulent boundary layer (TBL) over a wall roughened with regularly arrayed cubes was performed to investigate the effects of three-dimensional (3-D) surface elements on the properties of the TBL. The cubes were staggered in the downstream direction and periodically arranged in the streamwise and spanwise directions with pitches of px/k = 8 and pz/k = 2, where px and pz are the streamwise and spanwise spacings of the cubes and k is the roughness height. The Reynolds number based on the momentum thickness was varied in the range Reθ = 300−1300, and the roughness height was k = 1. 5θin, where θin is the momentum thickness at the inlet, which corresponds to k/δ = 0.052–0.174 from the inlet to the outlet; δ is the boundary layer thickness. The characteristics of the TBL over the 3-D cube-roughened wall were compared with the results from a DNS of the TBL over a two-dimensional (2-D) rod-roughened wall. The introduction of cube roughness affected the turbulent Reynolds stresses not only in the roughness sublayer but also in the outer layer. The present instantaneous flow field and linear stochastic estimations of the conditional averaging showed that the streaky structures in the near-wall region and the low-momentum regions and hairpin packets in the outer layer are dominant features in the TBLs over the 2-D and 3-D rough walls and that these features are significantly affected by the surface roughness throughout the entire boundary layer. In the outer layer, however, it was shown that the large-scale structures over the 2-D and 3-D roughened walls have similar characteristics, which indicates that the dimensional difference between the surfaces with 2-D and 3-D roughness has a negligible effect on the turbulence statistics and coherent structures of the TBLs.
CNN-LSTM Model Optimized by Bayesian Optimization for Predicting Single-Well Production in Water Flooding Reservoir

Geared toward the problems of predicting the unsteadily changing single oil well production in water flooding reservoir, a machine learning model based on CNN (convolutional neural network) and LSTM (long short-term memory) is established which realizes precise predictions of monthly single-well production. This study is considering more than 60 dynamic and static factors that affect the changes of oil well production, introduce water injection parameters into data set, select 11 main control factors, and then, build a CNN-LSTM model optimized by Bayesian optimization. The effectiveness of the proposed model is verified in a realistic reservoir. The experiment results show that the prediction accuracy of the proposed model is over 90%, which suggests a penitential application in an extensive range of applications. Production forecasting by the developed model is simple, efficient, and accurate, which can provide a guidance for the dynamic analysis of a water flooding reservoir, and work as a good reference of the development and production of other types of reservoirs.
Wind Speed Forecasting for Wind Power Production Based on Frequency-Enhanced Transformer

Wind power plays a more and more important part in today’s electricity market with the increasing need of clean energy. How to make better use of wind power is attracting great attention due to the inherent uncertainty caused by extreme complexity of weather systems. In order to address difficulty, we introduced a time-series prediction method called FEDformer to the field of wind power forecasting, and made some adjustment so that the FEDformer could perform better in this field. We tested this novel model on a real-world wind farm dataset, and compared it with other traditional machine learning methods. Results show that the proposed method for wind power prediction has better accuracy and greater potential for engineering applications. It is effective to apply transformer-based model to the field of wind power prediction.
A machine learning framework for process optimization in aerosol jet 3D printing

As a burgeoning three-dimensional (3D) printing technology, aerosol jet printing (AJP) technique has the characteristics of direct writing and customizing microelectronic components with flexible substrates. Therefore, it has been widely applied to manufacture different electronic devices. Although AJP has unique advantages over traditional methods, the electrical performance of printed electronic devices is significantly reduced because of the inferior printing qualities, such as high overspray, low level of line thickness and high level of edge roughness. Therefore, producing lines with high-controllability and high-aspect ratio is urgent for AJP technology. In this research, a machine learning scheme is developed for process optimization in AJP. In the proposed scheme, a support vector machine is combined with Latin hyper sampling to determine an optimal operating window of AJP, producing conductive lines with better edge definition and reduced overspray. Then, based on the identified 3D operating window, the conflicting relationship between the deposited line width and thickness was revealed based on the developed Gaussian process regression models. Following that, via a non-dominated sorting genetic algorithm, the conflicting printed line morphology was further optimized under dual conflicting targets for maximizing line thickness and customizing line width, which helps to produce high-controllability and high-aspect ratio lines for AJP. The optimization results demonstrated the validity of the proposed approach, which is beneficial to the systemic optimization of the entire printing process.
Security risk assessment for distribution Internet of Things

Aiming at the characteristics of complex business scenarios and sensitive data of distribution IoT, this project proposes a security risk assessment method for distribution IoT based on the analysis hierarchy process, which assesses the security of distribution IoT in terms of hardware, system, application and data. First, according to the characteristics and business scenarios of distribution IoT, the security status is divided into two parts: self-security and security control to ensure the integrity of the analysis. Based on the analysis results, typical security threats of different types of devices are extracted; secondly, based on the security threat analysis results, a security index system is designed and proposed from the perspective of defense and response of distribution IoT, and the index system is classified and quantified to form numerical information that can support the security assessment; thirdly, based on the analysis hierarchy process and fuzzy comprehensive analysis technology, the security risk assessment method of distribution IoT is formed Finally, the effectiveness of the proposed security assessment method is demonstrated by selecting the actual application scenarios of the distribution IoT.