Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual circularly polarized series‐fed patch antenna array integrated with beam switching network

A reconfigurable patch array antenna exhibiting circular polarization as well as pattern switching capabilities is presented in this work. The proposed 2 × 2 series‐fed structure is capable of generating 11 switched beams at a resonant frequency of 2.44 GHz. The work also hypothesis an unsophisticated method polarization and radiation pattern diversity. An effective reduction from 2N to N for feed ports and from N to N/2 for phase shifters has also been reported. The design is realized on a single‐layered low‐cost FR‐4 epoxy laminate having a thickness of 1.6 mm. The performance evaluation of the fabricated prototype exhibits good agreement between the computationally evaluated and the experimentally obtained results, yielding six circularly polarized and five 45° slant polarized switched beams in two‐dimensional space with appreciably high gain, acceptable side lobe level, and decent impedance matching characteristics for all constituent ports. In this work, a simple four‐port beam switching network has been proposed to synthesize the 11 switched beams at an elevation angle of 0°, ±10° and ±21° in xoz‐plane and yoz‐plane with both circular polarizations and 45° slant polarization. It does not require any additional digital circuit or complex geometry as reported in recent works.
High expression of suppressor of cytokine signaling 1 (SOCS1) associates with favourable responsiveness to neoadjuvant chemoradiotherapy in esophageal squamous cell carcinoma

Background: The responsiveness to preoperative neoadjuvant therapy in esophageal squamous cell carcinoma (ESCC) is significantly related to the surgical effect and long-term prognosis of patients. Biomarkers for predicting the effect of preoperative neoadjuvant therapy of ESCC are urgently needed in clinical practice. M2 macrophage in the tumor microenvironment (TME) has been confirmed to have a definite correlation with neoadjuvant therapy. However, the research on the potential functional genes of M2 macrophage has not been carried out. The purpose of this study is to systematically screen the potential functional genes of M2 macrophages and verify the correlation between the expression of screened genes and responsiveness to neoadjuvant therapy in ESCC.Methods: The Cancer Genome Atlas (TCGA) database was used to screen the potential functional genes of M2 macrophages systematically. The correlation between the screened genes and responsiveness to neoadjuvant therapy in ESCC was analyzed in the training set GSE45670 and the validation set GSE104958. The correlation of the screened genes was confirmed in a cohort of 27 patients using immunohistochemistry (IHC). Results: A total of 11 M2 macrophage potential functional genes were screened out. The suppressor of cytokine signaling 1 (SOCS1) and ORAI calcium release-activated calcium modulator 3 (ORAI3) were selected for subsequent verification. The expression of SOCS1 and ORAI3 in 27 cases of ESCC was evaluated by the H-score system. The result showed that the high expression of SOCS1 was significantly correlated with favourable responsiveness to preoperative neoadjuvant therapy (AUC = 0.830, 95% CI: 0.647-1, P = 0.006). No significant correlation was found between the expression of ORAI3 and neoadjuvant therapy in ESCC (AUC=0.688, 95% CI: 0.478-0.899, P=0.117). Conclusion: The high expression of SOCS1 in the local tumor microenvironment is significantly correlated with favourable responsiveness to neoadjuvant therapy in patients with ESCC, which can be used as a biomarker to predict the responsiveness to neoadjuvant therapy, and has certain clinical value.
An Ensemble Basedheart Disease Predictionusing Gradient Boosting Decision Tree

Heart disease is now one of the deadliest diseases among the world. This crisis is affecting the bulk of people across the globe. Considering the massive death rate and huge amount of people suffering from the disease, the importance of early diagnosis of heart disease has been proven. Known cause for forecasting such a disease exist, but they really do not seem to be adequate. It is critical to develop a standard medical device that can foresee early heart diagnosis and have a more precise diagnosis than existing technologies such as Logistic Regularization, Lasso, Elastic Net, and Lasso Community Regularization.Ensemble classifiers are used in a variety of machine learning models that can increase forecasting ability in healthcare. Four databases are assembled in this paper, and 14 clinical features are fed into Ensemble. Traditional methods like SVM, AdaBoost, Logistic Regularization, and the existing Ensemble Prediction Model are compared to the proposed Ensemble Prediction Model in this paper. Across each experiment, the accuracy rate of the four datasets was 99 percent, outperforming other machine learning techniques and related academic studies. The performance metrics clearly show that the developed ensemble learning approach is superior. The findings show that the suggested ensemble can accurately predict the risk of cardiovascular disease.
A miniaturized quad-band frequency selective surface for C-band applications

In this paper, a low-profile quad-band frequency selective surface (FSS), designed as a sub-reflector for satellite communication is presented. This single layered FSS employs non-concentric open loops with controlled field coupling to provide four closely spaced transmission zeroes within the C-band. The proposed design approach occupies lesser metallized area which gives an additional benefit of frequency tuning while retaining the miniaturized cell dimension. The four band-stop center frequencies are 4.6, 5.5, 6.3 and 7.3 GHz with an average bandwidth of 240 MHz. The unit cell has a miniaturized dimension of 0.138 0.138 0.012 , where stands for free space wavelength at the lowest resonating frequency. The FSS provides angularly stable frequency response up to for TE as well as TM polarization. Additionally, the FSS can be mechanically tuned to allow either TE or TM polarized wave. This study also reports the outcomes based on parametric variations and verifies the frequency behaviour of the structure using a circuit model. The simulated results are validated by testing a design prototype of the proposed FSS. Good concordance is observed between the simulated and measured results.
Detection and Difference Analysis of the Enzyme Activity of Colloidal Gold Nanoparticles With Negatively Charged Surfaces Prepared by Different Reducing Agents

Nanozymes are particles with diameters in the range of 1–100 nm, which has been widely studied due to their biological enzyme-like properties and stability that natural enzymes do not have. In this study, several reducing agents with different structures (catechol (Cc), hydroquinone (Hq), resorcinol (Rs), vitamin C (Vc), pyrogallic acid (Ga), sodium citrate (Sc), sodium malate (Sm), and sodium tartrate (St)) were used to prepare colloidal gold with a negative charge and similar particle size by controlling the temperature and pH. The affinity analysis of the substrate H2O2 and TMB showed that the order of activities of colloidal gold Nanozymes prepared by different reducing agents was Cc, Hq, Rs, Vc, Ga, Sc, Sm, St. It was also found that the enzyme activity of colloidal gold reduced by benzene rings is higher than that of the colloidal gold enzyme reduced by linear chains. Finally, we discussed the activity of the colloidal gold peroxidase based on the number and position of isomers and functional groups; and demonstrated that the nanozymes activity is affected by the surface activity of colloidal gold, the elimination of hydroxyl radicals and the TMB binding efficiency.
Floral morphology and pollen viability of an endangered and endemic Bromeliaceae species from the Atlantic Forest

Abstract The present study describes the floral morphology and evaluates pollen viability for the bromeliad Nidularium minutum Mez. during the flowering period 2018‒2019 through histochemistry and pollen germination tests. The inflorescences are nidular, capituliform with short branches bearing two to three odourless, bisexual and greenish-white flowers and with an androecium shorter than the gynoecium, consisting of six stamens with anthers featuring rimose dehiscence. The ovules are anatropous, displaying a small appendage in the chalazal region. The first flower opened in late November 2018 and flowering peak was in January 2019. Anthesis started at 6:55 a.m. and lasted until 8:49 a.m. Pollen/ovule ratio indicates facultative autogamy. The pollen grains are monads, medium to large, 2-(3)-porate, reticulate heterobrochate with abundant pollenkitt. A high frequency of unviable pollen grains with discrepant sizes was observed. The mature pollen grain is considered recalcitrant and therefore sensitive to desiccation. In vitro pollen germination after 48 hours was higher in BKM medium (64.77%) compared to SM (38.51%). Pollen viability was overestimated in all histochemistry tests, with Alexander (72.46%) being the closest to the in vitro germination rate. The results obtained for N. minutum bring new information about its floral biology as a subsidy to the cultivation of ornamental bromeliads that are at risk of extinction.
Metrics and methods for evaluating model‐driven reality capture plans

This paper presents new metrics and methods for evaluating the quality of reality capture plans—commonly used to operate camera‐mounted unmanned aerial vehicles (UAVs) or ground rovers—for construction progress monitoring and inspection of as‐is conditions. Using 4D building information model (BIM) or 3D reality model as a priori, these metrics provide feedback on the quality of a plan (within a few minutes), accounting for resolution, visibility, accuracy, completeness of the capture, and satisfying battery capacity and line‐of‐sight requirements. A cloud‐based system is introduced to create and optimize UAV/rover missions in the context of prior model. Results from real‐world construction data sets demonstrate that the proposed metrics offer actionable insights into the accuracy and completeness of reality capture plans. Additionally, a capture plan—with a combination of canonical and noncanonical camera views—that satisfies the introduced metrics is statistically correlated with the quality of reconstructed reality. These metrics can improve computer‐vision progress monitoring and inspection methods that rely on the construction site's appearance and geometry.
Fish Avoid Visually Noisy Environments Where Prey Targeting Is Reduced

The environment contains different forms of ecological noise that can reduce the ability of animals to detect information. Here, we ask whether animals adapt their behavior to either exploit or avoid areas of their environment with increased dynamic visual noise. Three-spined sticklebacks (Gasterosteus aculeatus) were immersed in environments with a simulated form of naturally occurring visual noise—moving light bands that form on underwater substrates caused by the refraction of light through surface waves. We tested whether this form of visual noise affected fish’s habitat selection, movements, and prey-targeting behavior. Fish avoided areas of the environment with increased visual noise and achieved this by increasing their activity as a function of the locally perceived noise level. Fish were less likely to respond to virtual prey in environments with increased visual noise, highlighting a potential impact that visual noise has on their perceptual abilities. Fish did not increase or decrease their refuge use in environments with increased visual noise, providing no evidence that visual noise increased either exploratory or risk-aversive behavior. Our results indicate that animals can use simple behavioral strategies to avoid visually noisy environments, thereby mitigating the impacts that these environments appear to have on their perceptual abilities.
Biomarkers in ROS and Role of Isoprostanes in Oxidative Stress

Biomarkers of reactive oxygen species serve as indicators of oxidative stress in the pathology of cardiovascular diseases. This chapter presents an overview of the various biomarkers available to quantify oxidative stress to advance the understanding of the pathophysiology of cardiovascular diseases as well as to serve as an adjunct in their diagnosis and prognosis. The plasma levels of reactive oxygen species themselves are unstable and unreliable markers of oxidative stress. The commonly used stable biomarkers are derivatives of oxygen radicals such as products of lipid peroxidation and protein oxidation, with isoprostanes and malondialdehyde (MDA) being the most widely used biomarkers due to higher specificity and ease of measurement. Recently, micro‐RNA is emerging as stable and specific biomarkers for detection of heart failure. Other biomarkers have a role in certain conditions; for example, advanced oxidation protein products indicate acute inflammation, whereas advanced glycation end products serve as indicators of chronic disease.
Tuning ANN Hyperparameters for Forecasting Drinking Water Demand

The evolution of smart water grids leads to new Big Data challenges boosting the development and application of Machine Learning techniques to support efficient and sustainable drinking water management. These powerful techniques rely on hyperparameters making the models’ tuning a tricky and crucial task. We hence propose an insightful analysis of the tuning of Artificial Neural Networks for drinking water demand forecasting. This study focuses on layers and nodes’ hyperparameters fitting of different Neural Network architectures through a grid search method by varying dataset, prediction horizon and set of inputs. In particular, the architectures involved are the Feed Forward Neural Network, the Long Short Term Memory, the Simple Recurrent Neural Network and the Gated Recurrent Unit, while the prediction interval ranges from 1 h to 1 week. To avoid the problem of the Neural Networks tuning stochasticity, we propose the selection of the median model among several repetitions for each hyperparameter’s configurations. The proposed iterative tuning procedure highlights the change of the required number of layers and nodes depending on Neural Network architectures, prediction horizon and dataset. Significant trends and considerations are pointed out to support Neural Network application in drinking water prediction.
3D Printing Individualized Assisted Repair and Reconstruction of Irregular Bone Neoplastic Bone Defects: Exploration and Practice in Scapular Aneurysmal Cystic Bone Defects

Guochen Luo A liated Zhongshan Hospital of Dalian University yao Zhang (  zhangyour@126.com ) Dalian University of Technology https://orcid.org/0000-0002-4725-111X Xiahua Wang A liated Zhongshan Hospital of Dalian University Shuaishuai Chen A liated Zhongshan Hospital of Dalian University Dongyi Li A liated Zhongshan Hospital of Dalian University Mingyang Yu A liated Zhongshan Hospital of Dalian University
Evaluation of immunomodulatory activity of Immusante® in zebrafish

Immusante® (IM-133N) a proven polyherbal immunomodulator was evaluated for its immunomodulatory activity in zebrafish models. In the present study, Aeromonas hydrophila (A. hydrophila) is used to develop the experimental model for studying immunomodulatory activity in zebrafish. To determine the A. hydrophila dose for the study, either sex of 30 zebrafish were taken and divided into 5 groups followed by intra-peritoneal injected with 10 µl of 6.0 × 106 , 6.0 × 205 , 6.0 × 105, 6.0 × 104 , and 6.0 × 103 cells/ml of live A. hydrophila suspension, respectively and continuously cultured. Acute toxicity study of Immusante® was done as per the procedures described in OECD 203 guideline. To examine the protective role of Immusante® and to check the survival rate, two zebrafish survival assays were performed. Immusante® was evaluated on A. hydrophila infection in zebrafish to study the effect and differential WBC count was also measured in the zebrafish infected with A. hydrophila. Gene expression analysis was done to check the expression levels of pro-inflammation cytokines. Immusante® at a dose of 200 and 400 mg/L enhanced the survival rate of infected zebrafish and at 400 mg/L, decreased the number of colony forming units (CFUs) of A. hydrophila in the blood and kidney of infected fishes. A significant increase in lymphocyte and decrease in neutrophils was observed in the treatment groups, which are the signs of improvement in non-specific immune response. Immusante® at a dose of 400 mg/L suppressed the pro-inflammatory cytokine’s expression such as IL-1β, IFN-γ, and TNF-α in the kidney of infected zebrafish and prevented the detrimental effects on zebrafish caused due to excessive inflammatory response.
Carcass Traits of Growing Meat Goats Fed Different Levels of Hempseed Meal

Simple Summary Industrial hemp is currently being investigated as a potential new crop in the U.S. after the passage and approval of the 2014 and 2018 Farm Bills. Hemp plants grow efficiently, and its seeds are used in the production of hemp oil, leaving hempseed meal (HSM) as a byproduct, which is reported to be rich in crude protein (CP) around 30–38% on a dry matter basis and fiber, making it a possible feedstuff and a protein source for ruminants. However, limited work has been carried out to evaluate the effects of utilizing HSM as feedstuffs for goats on their carcass characteristics. This study aims to investigate the effects of feeding various levels of HSM on the carcass traits of the crossbred Boer goats. Results suggest that including up to 30% of HSM in the diet of growing meat goats has no adverse effects on their carcass traits and meat quality. These results might be encouraging for the hemp industry as HSM could potentially be marketed and used as an alternative protein source for livestock. Abstract Hempseed meal (HSM) is the byproduct of hemp seeds and is rich in crude protein and fiber, making it an ideal candidate as a feedstuff for ruminants. The objective of the present study is to evaluate the effects of feeding different levels of HSM on the carcass traits of crossbred Boer goats. Forty castrated goat kids (approximately six months, 25.63 ± 0.33 kg) were assigned to one of four treatments (n = 10) in a completely randomized design. Goats were fed pelleted diets (50% forage and 50% concentrate) with additional supplementation of HSM: control with 0%, 10%, 20%, and 30% of the total diets. Goats were harvested and processed after a 60-day feeding trial. There were no significant differences (p > 0.05) in the mean values of dressing percentages, carcass weights, body wall thickness, and ribeye area among treatments. Marbling scores and percentages of moisture, fats, proteins, and collagen in the muscles showed no significant differences (p > 0.05) among the treatments. Results suggest that including up to 30% of HSM in the diet of growing meat goats does not affect their carcass traits.
Investigation of Cloud Computing Based Big Data on Machine Learning Algorithms.

Cloud computing technology is a model that allows access to a common pool of configurable computing resources whenever and wherever. With the developing technology, the use of this model is increasing day by day. There are many benefits of cloud computing to its users. The data that users keep in their data sets is the simplest example of this. With the cloud technology, the size of the data stored in databases is also increasing. For this reason, cloud technology and big data concepts are intertwined due to the large amount of data stored in databases. It is of great importance that the obtained data is evaluated by machine learning methods and produces results that can be used for technical and commercial purposes. In this study, first of all, cloud technology, the big data brought by this technology and the classification of these data with machine learning methods and algorithms have been examined. Then the studies in the literature were evaluated.
Analysis of the Effects of the Location of Passive Control Devices on the Platform of a Floating Wind Turbine

Floating offshore wind turbines (FOWT) are subjected to strong loads, mainly due to wind and waves. These disturbances cause undesirable vibrations that affect the structure of these devices, increasing the fatigue and reducing its energy efficiency. Among others, a possible way to enhance the performance of these wind energy devices installed in deep waters is to combine them with other marine energy systems, which may, in addition, improve its stability. The purpose of this work is to analyze the effects that installing some devices on the platform of a barge-type wind turbine have on the vibrations of the structure. To do so, two passive control devices, TMD (Tuned Mass Damper), have been installed on the platform of the floating device, with different positions and orientations. TMDs are usually installed in the nacelle or in the tower, which imposes space, weight, and size hard constraints. An analysis has been carried out, using the FAST software model of the NREL-5MW FOWT. The results of the suppression rate of the tower top displacement and the platform pitch have been obtained for different locations of the structural control devices. They have been compared with the system without TMD. As a conclusion, it is possible to say that these passive devices can improve the stability of the FOWT and reduce the vibrations of the marine turbine. However, it is indispensable to carry out a previous analysis to find the optimal orientation and position of the TMDs on the platform.
Integrated analysis of tRNA-derived small RNAs in proliferative human aortic smooth muscle cells

Background Abnormal proliferation of vascular smooth muscle cells (VSMCs) contributes to vascular remodeling diseases. Recently, it has been discovered that tRNA-derived small RNAs (tsRNAs), a new type of noncoding RNAs, are related to the proliferation and migration of VSMCs. tsRNAs regulate target gene expression through miRNA-like functions. This study aims to explore the potential of tsRNAs in human aortic smooth muscle cell (HASMC) proliferation. Methods High-throughput sequencing was performed to analyze the tsRNA expression profile of proliferative and quiescent HASMCs. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to validate the sequence results and subcellular distribution of AS-tDR-001370, AS-tDR-000067, AS-tDR-009512, and AS-tDR-000076. Based on the microRNA-like functions of tsRNAs, we predicted target promoters and mRNAs and constructed tsRNA–promoter and tsRNA–mRNA interaction networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to reveal the function of target genes. EdU incorporation assay, Western blot, and dual-luciferase reporter gene assay were utilized to detect the effects of tsRNAs on HASMC proliferation. Results Compared with quiescent HASMCs, there were 1838 differentially expressed tsRNAs in proliferative HASMCs, including 887 with increased expression (fold change > 2, p < 0.05) and 951 with decreased expression (fold change < ½, p < 0.05). AS-tDR-001370, AS-tDR-000067, AS-tDR-009512, and AS-tDR-000076 were increased in proliferative HASMCs and were mainly located in the nucleus. Bioinformatics analysis suggested that the four tsRNAs involved a variety of GO terms and pathways related to VSMC proliferation. AS-tDR-000067 promoted HASMC proliferation by suppressing p53 transcription in a promoter-targeted manner. AS-tDR-000076 accelerated HASMC proliferation by attenuating mitofusin 2 (MFN2) levels in a 3′-untranslated region (UTR)-targeted manner. Conclusions During HASMC proliferation, the expression levels of many tsRNAs are altered. AS-tDR-000067 and AS-tDR-000076 act as new factors promoting VSMC proliferation.