bluuebunny/crossref_metadata_2025 huggingface dataset:
Castanea sativa Mill. Leaf: UHPLC-HR MS/MS Analysis and Effects on In Vitro Rumen Fermentation and Methanogenesis
Authors: Formato Marialuisa , Vastolo Alessandro , Piccolella Simona , Calabrò Serena , Cutrignelli Monica Isabella , Zidorn Christian , Pacifico Severina
Published: December 2022

Castanea sativa Mill. (Fagaceae) is a deciduous tree grown for its wood and edible fruits. Chestnut processing produces residues (burs, shells, and leaves) exploitable for their diversity in bioactive compounds in animal nutrition. In fact, plant-specialized metabolites likely act as rumen modifiers. Thus, the recovery of residual plant parts as feed ingredients is an evaluable strategy. In this context, European chestnut leaves from northern Germany have been investigated, proving to be a good source of flavonoids as well as gallo- and ellagitannins. To this purpose, an alcoholic extract was obtained and an untargeted profiling carried out, mainly by means of ultra-high-performance liquid chromatography/high-resolution tandem mass spectrometry (UHPLC-HR MS/MS) techniques. To better unravel the polyphenol constituents, fractionation strategies were employed to obtain a lipophilic fraction and a polar one. This latter was highly responsive to total phenolic and flavonoid content analyses, as well as to antiradical (DPPH● and ABTS+●) and reducing activity (PFRAP) assays. The effect of the alcoholic extract and its fractions on rumen liquor was also evaluated in vitro in terms of fermentative parameter changes and impact on methanogenesis. The data acquired confirm that chestnut leaf extract and the fractions therefrom promote an increase in total volatile fatty acids, while decreasing acetate/propionate ratio and CH4 production.
The Study of Hypoglycemic Activity of 7-Terpenylcoumarins
Authors: Kuranov Sergey , Marenina Mariya , Ivankin Dmitriy , Blokhin Mikhail , Borisov Sergey , Khomenko Tatyana , Luzina Olga , Khvostov Mikhail , Volcho Konstantin , Tolstikova Tatyana , Salakhutdinov Nariman
Published: December 2022

Natural and synthetic coumarins are often considered privileged scaffolds for obtaining pharmacological agents with hypoglycemic activity. Chemical modification of coumarins often leads to antidiabetic agents with greater efficacy. In the present work, twenty monoterpene-substituted 7-hydroxycoumarins were synthesized. A new approach using the Mitsunobu reaction was shown to be effective for the synthesis of target compounds. All of the synthesized compounds were evaluated in an oral glucose tolerance test, and two of them containing geranyl and (-)-myrtenyl substituents showed in vivo hypoglycemic action. A possible mechanism of action of these compounds may include inhibition of DPP IV, which was proved in an in vitro test.
Convenient Synthesis of N-Heterocycle-Fused Tetrahydro-1,4-diazepinones
Authors: Dzedulionytė Karolina , Veikšaitė Melita , Morávek Vít , Malinauskienė Vida , Račkauskienė Greta , Šačkus Algirdas , Žukauskaitė Asta , Arbačiauskienė Eglė
Published: December 2022

A general approach towards the synthesis of tetrahydro-4H-pyrazolo[1,5-a][1,4]diazepin-4-one, tetrahydro[1,4]diazepino[1,2-a]indol-1-one and tetrahydro-1H-benzo[4,5]imidazo[1,2-a][1,4]diazepin-1-one derivatives was introduced. A regioselective strategy was developed for synthesizing ethyl 1-(oxiran-2-ylmethyl)-1H-pyrazole-5-carboxylates from easily accessible 3(5)-aryl- or methyl-1H-pyrazole-5(3)-carboxylates. Obtained intermediates were further treated with amines resulting in oxirane ring-opening and direct cyclisation—yielding target pyrazolo[1,5-a][1,4]diazepin-4-ones. A straightforward two-step synthetic approach was applied to expand the current study and successfully functionalize ethyl 1H-indole- and ethyl 1H-benzo[d]imidazole-2-carboxylates. The structures of fused heterocyclic compounds were confirmed by 1H, 13C, and 15N-NMR spectroscopy and HRMS investigation.
Surface-Treated Recycling Fibers from Wind Turbine Blades as Reinforcement for Waste Phosphogypsum
Authors: Yang Lilin , Zhao Weilin , Wang Daobei , Liu Yang , Wang Dongzhi , Cui Na
Published: December 2022

An attempt at the treatment of the waste fiber (WF) from the wind turbine blade (WTB) was made through the modifier of dopamine hydrochloride and the compound modifier of dopamine hydrochloride and 2,5-dihydroxy terephthalic acid or 3,4-dihydroxy cinnamic acid or 3,4-dihydroxy benzonitrile, corresponding to obtain four modified waste fibers (MWF1, MWF2, MWF3, and MWF4). The MWFs samples’ microstructure properties were characterized using SEM, EDS, XPS, FTIR analyses, and water contact angle tests. The results revealed that all the MWF surfaces were wrapped by a distinct coating layer and had different elemental compositions and chemical groups, demonstrating the significant effect of the four modifications on the WF surfaces. The hydroxyl, amino, or nitrile groups were grafted onto the WF surfaces causing improvement of the hydrophilicity and reactivity. Furthermore, all the MWFs as the reinforced materials were incorporated into the industrial waste phosphogypsum (PG) to manufacture the phosphorous-building gypsum composites (PBGC). The effects on the micro-morphology and mechanical properties of the PBGC were evaluated. The results also show the improvement in flexural and compressive strength with the addition of MWFs into the PBGC, due to the enhancement of the compactness between the MWF and phosphogypsum matrix. In particular, the effects of three compound modifiers on the flexural and compressive strength are more significant. The highest flexural and compressive strength was contributed by the PBGC-MWF4 with 2% dosage using a compound modifier of dopamine hydrochloride and 3,4-dihydroxy benzonitrile, which were enhanced 61.04% and 25.97% compared with the PBG.
Properties of Polyunsaturated Fatty Acids in Primary and Secondary Prevention of Cardiovascular Diseases in the View of Patients (Silesia, Poland)
Authors: Krupa-Kotara Karolina , Grajek Mateusz , Wypych-Ślusarska Agata , Martynus-Depta Sandra , Oleksiuk Klaudia , Głogowska-Ligus Joanna , Szczepańska Elżbieta , Słowiński Jerzy
Published: December 2022

Background: Cardiovascular diseases are a major cause of morbidity and mortality in Europe. Lifestyle plays an important role in the primary and secondary prevention of cardiovascular diseases, apart from pharmacotherapy and diagnostics. Numerous studies confirm that the type and quality of fat consumed in the diet have a huge impact on the risk of cardiovascular diseases. Reducing the risk of cardiovascular disease can be helped by minimizing the proportion of saturated fatty acids in the diet and replacing them with polyunsaturated fatty acids. These acids and, above all, their long-chain forms have a positive effect on health. Aim: This study aims to assess the awareness of the properties of polyunsaturated fatty acids in the primary and secondary prevention of cardiovascular diseases in the opinions of patients of the Cardiology Department of the Racibórz Medical Center. Material and Methods: The analysis included 302 patients (113 women and 189 men) hospitalized in the Cardiology Department. The research method was the authors’ questionnaire consisting of the patients’ record and thirty closed questions. To answer the research questions posed and test the hypotheses, statistical analyses were carried out using the IBM SPSS Statistics version 25 package. Results: Among the respondents, the least frequently used healthy eating habit was the infrequent eating of fried foods. A total of 18.2% of respondents had such a habit. The most commonly used healthy eating habit was checking the fat content in products, which was performed by 67.2% of respondents. Among the respondents, 58.3% said that butter and margarine increase serum cholesterol. Conclusions: The analysis of the data shows that the place of residence, education, sex, and reason for hospitalization of the respondents did not affect the frequency of healthy eating habits. In addition, the subjects had a low amount of healthy eating habits.
Dicarbocyanine Dye-Based Organic Photodiodes
Authors: Md Sabri Amirul Ashraf , Natashah Fadlan Arif , Hisamuddin Syaza Nafisah , Roslan Nur Adilah , Bawazeer Tahani M. , Alsoufi Mohammad S. , Supangat Azzuliani
Published: December 2022

We report on the utilization of 1′-1′-diethyl-4,4′-dicarbocyanine iodide (DDCI-4) as a photoactive material for organic photodiodes (OPDs). A device was fabricated using a ternary blended ratio in the conventional stack order of ITO/PEDOT:PSS/P3HT:DDCI-4:OXCBA/Al to improve stability and enhance light absorption. An investigation was carried out into the optical and morphological characteristics of the device along with its electrical performance using different concentrations of DDCI-4 in a blended ratio of P3HT:DDCI-4:OXCBA in the photoactive layer. The mechanism of the OPD device and its performance with a gradual increase in DDCI-4 concentration is explained throughout this work, in which the increase in DDCI-4 concentration caused the dislocation defect and a decrease in charge carriers. The appropriate concentration of DDCl-4 resulted in improved light broadening, especially in near-infrared (NIR) regions.
Phytoprofiling of Sorbus L. Inflorescences: A Valuable and Promising Resource for Phenolics
Authors: Zymone Kristina , Raudone Lina , Žvikas Vaidotas , Jakštas Valdas , Janulis Valdimaras
Published: December 2022

The leaves and fruits of various Sorbus L. genotypes have long ethnopharmacological and food-usage histories, but inflorescences are still underutilized and neglected materials with scarce phytochemical scientific evidence. The aim of this study was to determine the phenolic profiles of inflorescence extracts of 26 Sorbus species, genotypes, and cultivars. HPLC and UPLS with MS detection were applied, and coupled data revealed unique phytochemical phenolic profiles. Neochlorogenic and chlorogenic acids were the key compounds, reaching up to 5.8 mg/g of dw. Rutin, isoquercitrin, quercetin 3-O-malonylglucoside, isorhamnetin 3-O-rutinoside, sexangularetin derivative, and kaempferol acetyl hexoside were detected in all Sorbus inflorescence samples. Overall, high quantitative heterogeneity across the various Sorbus genotypes was found by profiling. Phenolic fingerprint profiles and sexangularetin derivatives could serve as markers in authenticity studies and quality control schemes. The species S. amurensis, S. arranensis, S. commixta, and S. discolor and the cultivars ‘Chamsis Louing’, ‘Coral Beauty’, and ‘Edulis’ could be used as target genotypes for production of smart and innovative inflorescence matrix-based ingredients.
Predicting the Recovery and Nonrecoverable Compliance Behaviour of Asphalt Binders Using Artificial Neural Networks
Authors: Hamid Abdulrahman , Baaj Hassan , El-Hakim Mohab
Published: December 2022

Additives are widely used to enhance the rheological and performance properties of asphalt binder to satisfy the demands of extreme loading and climatic conditions. Meanwhile, adding to the complexity of asphalt binder behaviour that requires more time, effort, and material resources during laboratory work. The purpose of this research was to use Artificial Neural Networks (ANNs) to predict the recovery (R) and nonrecoverable compliance (Jnr) behaviour of asphalt binder based on mechanical test parameters and rheological properties of asphalt binder. A comprehensive experimental database consisting of the results of the frequency sweep and Multiple Stress Creep Recovery (MSCR) test using a dynamic shear rheometer (DSR) at five test temperatures (46 ∘C, 52 ∘C, 58 ∘C, 64 ∘C, and 70 ∘C). Prediction models for R and Jnr of asphalt binder modified with different contents of fly ash, fly ash-based geopolymer, glass powder/fly ash-based geopolymer, and styrene–butadiene styrene (SBS) were developed. The ANNs model was developed using five input parameters (temperature, frequency, storage modulus, loss modulus, and viscosity) and one hidden layer with five neurons. The results pointed out that the hybrid and 4%SBS binders achieved the highest ability to resist extremely heavy traffic and to recover the deformation with 60.1% and 85.5% at 46 ∘C, respectively, compared with the other modified asphalt binders. Excellent R-values for the total data set of 0.937, 0.997, 0.985, and 0.987 for Jnr3.2 of unaged binder, Jnr3.2 of aged binder, R3.2 of unaged binder, and R3.2 of aged binder, respectively. Therefore, the ANNs model is appropriate tool to predict the R3.2 and Jnr3.2 using unaged or aged binders at different temperatures.
Analyzing Energy Transfer Mechanism during Coal and Gas Protrusion in Deep Mines
Authors: Sun Haitao , Dai Linchao , Lu Jun , Cao Jie , Li Minghui
Published: December 2022

Coal is the mainstay of China’s energy supply. With the gradual progress in China’s policy of phasing out backward coal production capacity, the intensive and deep mining of coal has gradually become the new norm. The current mining depth is increasing at a rate of 10~15 m/year. The high crust stress, high gas pressure, high ground temperature, and engineering disturbance stress in deep coal mines can lead to the occurrence of coal–rock–gas dynamic disasters that are complex and show the characteristics of compound dynamic disasters. It is important to understand the evolution and mechanism of deep coal and rock dynamic disasters accurately for the safe development of deep resources. To study the mechanism of occurrence and the evolution of impact–protrusion compound dynamic disasters, we herein analyzed the apparent characteristics of coal–rock–gas compound dynamic disasters in deep mines and obtained the mechanical and acoustic emission characteristics of coal–rock composites through indoor experiments. Then, we conducted in-depth analysis on the non-uniform deformation behaviors and non-uniform stress field of the coal–rock composite and clarified the generation mechanism of local tensile cracks at the coal–rock interface. Subsequently, we established the energy transfer model of the rock–rock–gas composite specimen in the process of dynamic destabilization in the engineering scale mining field and revealed the mechanism of nonlinear energy evolution and release of the coal–rock–gas composite, which has been less reported in previous studies. In this paper, we further clarified the occurrence and development mechanism of coal–rock–gas compound dynamic disasters in the engineering scale mining environment to guide the prevention and control of coal–rock–gas dynamic disasters in deep mines.
Optimization of Red Pigment Anthocyanin Recovery from Hibiscus sabdariffa by Subcritical Water Extraction
Authors: Rizkiyah Dwila Nur , Putra Nicky Rahmana , Idham Zuhaili , Che Yunus Mohd Azizi , Veza Ibham , Harny Irianto , Syahlani Nurfadlih , Abdul Aziz Ahmad Hazim
Published: December 2022

The optimization of red pigment anthocyanin from roselle (Hibiscus sabdariffa) by subcritical water extraction (SWE) has not been the topic of a scientific investigation. Therefore, the objective of this paper was to establish the optimal parameters for obtaining the maximum yield, total anthocyanin compounds (TAC), total phenolic compounds (TPC), and total flavonoid compounds (TFC) by SWE utilizing a response surface methodology. The optimal conditions were 8.75 MPa, 393.54 K, and 4.89 mL/min, with a yield of 0.69 g/g, TAC of 927.74 mg/100 g, TPC of 39.54 mg/100 g, and TFC of 614.57 mg/100 g. High temperatures and flow rates are favorable for achieving a maximum yield. In contrast, a high temperature is suitable for obtaining high concentrations of anthocyanin, flavonoid, and phenolic compounds. This technique (SWE) recovers anthocyanin at a greater extraction rate than traditional methods; hence, SWE may be substituted for conventional methods for extracting anthocyanin.
Highly Sensitive and Selective Graphene Nanoribbon Based Enzymatic Glucose Screen-Printed Electrochemical Sensor
Authors: Gričar Ema , Radić Josip , Genorio Boštjan , Kolar Mitja
Published: December 2022

A simple, sensitive, cost effective, and reliable enzymatic glucose biosensor was developed and tested. Nitrogen-doped heat-treated graphene oxide nanoribbons (N-htGONR) were used for modification of commercially available screen-printed carbon electrodes (SPCEs), together with MnO2 and glucose oxidase. The resulting sensors were optimized and used to detect glucose in a wide linear range (0.05–5.0 mM) by a simple amperometric method, where the limit of detection was determined to be 0.008 mM. (lifetime), and reproducibility studies were also carried out and yielded favorable results. The sensor was then tested against potential interfering species present in food and beverage samples before its application to real matrix. Spiked beer samples were analyzed (with glucose recovery between 93.5 and 103.5%) to demonstrate the suitability of the developed sensor towards real food and beverage sample applications.
Federated Deep Reinforcement Learning Based Task Offloading with Power Control in Vehicular Edge Computing
Authors: Moon Sungwon , Lim Yujin
Published: December 2022

Vehicular edge computing (VEC) is a promising technology for supporting computation-intensive vehicular applications with low latency at the network edges. Vehicles offload their tasks to VEC servers (VECSs) to improve the quality of service (QoS) of the applications. However, the high density of vehicles and VECSs and the mobility of vehicles increase channel interference and deteriorate the channel condition, resulting in increased power consumption and latency. Therefore, we proposed a task offloading method with the power control considering dynamic channel interference and conditions in a vehicular environment. The objective is to maximize the throughput of a VEC system under the power constraints of a vehicle. We leverage deep reinforcement learning (DRL) to achieve superior performance in complex environments and high-dimensional inputs. However, most conventional methods adopted the multi-agent DRL approach that makes decisions using only local information, which can result in poor performance, while single-agent DRL approaches require excessive data exchanges because data needs to be concentrated in an agent. To address these challenges, we adopt a federated deep reinforcement learning (FL) method that combines centralized and distributed approaches to the deep deterministic policy gradient (DDPG) framework. The experimental results demonstrated the effectiveness and performance of the proposed method in terms of the throughput and queueing delay of vehicles in dynamic vehicular networks.
A Dual Distribution Control Method for Multi-Power Components Energy Output of 4WD Electric Vehicles
Authors: Guo Zhiqi , Chu Liang , Hou Zhuoran , Wang Yinhang , Hu Jincheng , Sun Wen
Published: December 2022

Energy management strategies are vitally important to give full play to the energy-saving of the four-wheel drive electric vehicle (4WD EV). The cooperative output of multi-power components is involved in the process of driving and braking energy recovery of 4WD EV. This paper proposes a novel energy management strategy of dual equivalent consumption minimization strategy (D-ECMS) to improve the economy of the vehicle. According to the different driving and braking states of the vehicle, D-ECMS can realize the proportional control of the energy cooperative output among the multi-power components. Under the premise of satisfying the dynamic performance of the vehicle, the operating points of the power components are distributed more in the high-efficiency range, and the economy and driving range of the vehicle are optimized. In order to achieve the effectiveness of D-ECMS, MATLAB/Simulink is used to realize the simulation of the vehicle. Compared with the rule-based strategy, the economy of D-ECMS increased by 4.35%.
RustOnt: An Ontology to Explain Weather Favorable Conditions of the Coffee Rust
Authors: Suarez Carlos , Griol David , Figueroa Cristhian , Corrales Juan Carlos , Corrales David Camilo
Published: December 2022

Crop disease management in smart agriculture involves applying and using new technologies to reduce the impact of diseases on the quality of products. Coffee rust is a disease that factors such as poor agronomic management activities and climate conditions may favor. Therefore, it is crucial to identify the relationships between these factors and this disease to learn how to face its consequences and build intelligent systems to provide appropriate management or help farmers and experts make decisions accordingly. Nevertheless, there are no studies in the literature that propose ontologies to model these factors and coffee rust. This paper presents a new ontology called RustOnt to help experts more accurately model data, expressions, and samples related to coffee rust and apply it whilst taking into account the geographical location where the ontology is adopted. Consequently, this ontology is crucial for coffee rust monitoring and management by means of smart agriculture systems. RustOnt was successfully evaluated considering quality criteria such as clarity, consistency, modularity, and competence against a set of initial requirements for which it was built.
IGWO-IVNet3: DL-Based Automatic Diagnosis of Lung Nodules Using an Improved Gray Wolf Optimization and InceptionNet-V3
Authors: Bilal Anas , Shafiq Muhammad , Fang Fang , Waqar Muhammad , Ullah Inam , Ghadi Yazeed Yasin , Long Haixia , Zeng Rao
Published: December 2022

Artificial intelligence plays an essential role in diagnosing lung cancer. Lung cancer is notoriously difficult to diagnose until it has progressed to a late stage, making it a leading cause of cancer-related mortality. Lung cancer is fatal if not treated early, making this a significant issue. Initial diagnosis of malignant nodules is often made using chest radiography (X-ray) and computed tomography (CT) scans; nevertheless, the possibility of benign nodules leads to wrong choices. In their first phases, benign and malignant nodules seem very similar. Additionally, radiologists have a hard time viewing and categorizing lung abnormalities. Lung cancer screenings performed by radiologists are often performed with the use of computer-aided diagnostic technologies. Computer scientists have presented many methods for identifying lung cancer in recent years. Low-quality images compromise the segmentation process, rendering traditional lung cancer prediction algorithms inaccurate. This article suggests a highly effective strategy for identifying and categorizing lung cancer. Noise in the pictures was reduced using a weighted filter, and the improved Gray Wolf Optimization method was performed before segmentation with watershed modification and dilation operations. We used InceptionNet-V3 to classify lung cancer into three groups, and it performed well compared to prior studies: 98.96% accuracy, 94.74% specificity, as well as 100% sensitivity.
Widely-Linear Digital Self-Interference Cancellation in Full-Duplex USRP Transceiver
Authors: Despina-Stoian Cristina , Youssef Roua , Digulescu Angela , Radoi Emanuel , Gautier Roland , Serbanescu Alexandru
Published: December 2022

Full-duplex (FD) communication systems allow for increased spectral efficiency but require effective self-interference cancellation (SIC) techniques to enable the proper reception of the signal of interest. The underlying idea of digital SIC is to estimate the self-interference (SI) channel based on the received signal and the known transmitted waveform. This is a challenging task since the SI channel involves, especially for mass-market FD transceivers, many nonlinear distortions produced by the impairments of the analog components from the receiving and transmitting chains. Hence, this paper first analyzes the power of the SI components under practical conditions and focuses on the most significant one, which is proven to be produced by the I/Q mixer imbalance. Then, a widely-linear digital SIC approach is adopted, which simultaneously deals with the direct SI and its image component caused by the I/Q imbalance. Finally, the performances achieved by linear and widely-linear SIC approaches are evaluated and compared using an experimental FD platform relying on software-defined radio technology and GNU Radio. Moreover, the considered experimental framework allows us to set different image rejection ratios for the transmission path I/Q mixer and to study its influence on the SIC capability of the discussed approaches.
Object Pose Estimation Using Edge Images Synthesized from Shape Information
Authors: Moteki Atsunori , Saito Hideo
Published: December 2022

This paper presents a method for estimating the six Degrees of Freedom (6DoF) pose of texture-less objects from a monocular image by using edge information. The deep learning-based pose estimation method needs a large dataset containing pairs of an image and ground truth pose of objects. To alleviate the cost of collecting a dataset, we focus on the method using a dataset made by computer graphics (CG). This simulation-based method prepares a thousand images by rendering the computer-aided design (CAD) data of the object and trains a deep-learning model. As an inference stage, a monocular RGB image is entered into the model, and the object’s pose is estimated. The representative simulation-based method, Pose Interpreter Networks, uses silhouette images as the input, thereby enabling common feature (contour) extraction from RGB and CG images. However, estimating rotation parameters is less accurate. To overcome this problem, we propose a method to use edge information extracted from the object’s ridgelines for training the deep learning model. Since edge distribution changes largely according to the pose, the estimation of rotation parameters becomes more robust. Through an experiment with simulation data, we quantitatively proved the accuracy improvement compared to the previous method (error rate decreases at a certain condition are translation 22.9% and rotation: 43.4%). Moreover, through an experiment with physical data, we clarified the issues of this method and proposed an effective solution by fine-tuning (error rate decrease at a certain condition are translation 20.1% and rotation 57.7%).
Hand Gesture Recognition Using EMG-IMU Signals and Deep Q-Networks
Authors: Vásconez Juan Pablo , Barona López Lorena Isabel , Valdivieso Caraguay Ángel Leonardo , Benalcázar Marco E.
Published: December 2022

Hand gesture recognition systems (HGR) based on electromyography signals (EMGs) and inertial measurement unit signals (IMUs) have been studied for different applications in recent years. Most commonly, cutting-edge HGR methods are based on supervised machine learning methods. However, the potential benefits of reinforcement learning (RL) techniques have shown that these techniques could be a viable option for classifying EMGs. Methods based on RL have several advantages such as promising classification performance and online learning from experience. In this work, we developed an HGR system made up of the following stages: pre-processing, feature extraction, classification, and post-processing. For the classification stage, we built an RL-based agent capable of learning to classify and recognize eleven hand gestures—five static and six dynamic—using a deep Q-network (DQN) algorithm based on EMG and IMU information. The proposed system uses a feed-forward artificial neural network (ANN) for the representation of the agent policy. We carried out the same experiments with two different types of sensors to compare their performance, which are the Myo armband sensor and the G-force sensor. We performed experiments using training, validation, and test set distributions, and the results were evaluated for user-specific HGR models. The final accuracy results demonstrated that the best model was able to reach up to 97.50%±1.13% and 88.15%±2.84% for the classification and recognition, respectively, with regard to static gestures, and 98.95%±0.62% and 90.47%±4.57% for the classification and recognition, respectively, with regard to dynamic gestures with the Myo armband sensor. The results obtained in this work demonstrated that RL methods such as the DQN are capable of learning a policy from online experience to classify and recognize static and dynamic gestures using EMG and IMU signals.
A High-Sensitivity Dual-Axis Accelerometer with Two FP Cavities Assembled on Single Optical Fiber
Authors: Zheng Bolun , Liu Hanjie , Pan Zhen , Chen Xi , Wang Lixiong , Fan Dian
Published: December 2022

In this paper, a dual-axis Fabry–Pérot (FP) accelerometer assembled on single optical fiber is proposed. The sensor is equipped with a special beam-splitting prism to split the light into two perpendicular directions (the X- and Y-axes); the prism surface coated with semi-permeable film and the reflective sheet on the corresponding Be-Cu vibration-sensitive spring form two sets of FP cavities of different sizes. When the Be-Cu spring with a proof mass (PM) is subjected to the vibration signal, the cavity length of the corresponding FP cavity is changed and the interference signal returns to the collimator through the original path of the prism. After bandpass filtering and demodulation, the two cavity lengths are obtained, and the acceleration measurement in dual-axis directions is completed. The resonant frequency of the proposed dual-axis fiber optic accelerometer is around 280 Hz. The results of the spectral measurements show 3.93 μm/g (g = 9.8 m/s2: gravity constant) and 4.19 μm/g for the applied acceleration along the X- and Y-axes, respectively, and the cross-axis sensitivity is below 5.1%. Within the angle range of 180°, the maximum error of measured acceleration is less than 3.77%. The proposed fiber optic dual-axis FP accelerometer has high sensitivity and strong immunity to electromagnetic interference. The size of the sensor mainly depends on the size of the prism, which is easy to reduce and mass produce. Moreover, this FP construction method has high flexibility and development potential.
Comprehensive Controller for Super Sonic Molecular Beam Gas Chromatograph Mass Spectrometer
Authors: Flaxer Eli
Published: December 2022

This paper presents a new, comprehensive digital circuit used for the control of a novel gas chromatograph mass spectrometer (GC-MS) interface that is based on supersonic molecular beam (SMB). The circuit includes a Texas Instruments 150 MHz digital signal controller (DSC), high voltage amplifiers for 8 independent channels and 4 independent channels of high resolution pulse width modulation (PWM). The circuit, along with a sophisticated embedded program and a custom made personal computer (PC) application, control all aspects of the interface: smart filament emission-current stabilization, static and scanning mass-dependent ion-source voltages, transfer-line heater proportional integral differential (PID) controls with thermocouple feedbacks, on/off valves, relays and several peripheral device controls that enable the full operation of a turbo-molecular vacuum pump, and of gas flow and pressure controllers. All aspects of this comprehensive controller were successfully tested. The signal for the 450 Th ion (C32H66) for example increased by 123% which is a significant increase. It is obvious that correctly tuned dynamic voltages can guarantee the optimal signal for each mass.
Towards Whole Health Toxicology: In-Silico Prediction of Diseases Sensitive to Multi-Chemical Exposures
Authors: Arowolo Olatunbosun , Salemme Victoria , Suvorov Alexander
Published: December 2022

Chemical exposures from diverse sources merge on a limited number of molecular pathways described as toxicity pathways. Changes in the same set of molecular pathways in different cell and tissue types may generate seemingly unrelated health conditions. Today, no approaches are available to predict in an unbiased way sensitivities of different disease states and their combinations to multi-chemical exposures across the exposome. We propose an inductive in-silico workflow where sensitivities of genes to chemical exposures are identified based on the overlap of existing genomic datasets, and data on sensitivities of individual genes is further used to sequentially derive predictions on sensitivities of molecular pathways, disease states, and groups of disease states (syndromes). Our analysis predicts that conditions representing the most significant public health problems are among the most sensitive to cumulative chemical exposures. These conditions include six leading types of cancer in the world (prostatic, breast, stomach, lung, colorectal neoplasms, and hepatocellular carcinoma), obesity, type 2 diabetes, non-alcoholic fatty liver disease, autistic disorder, Alzheimer’s disease, hypertension, heart failure, brain and myocardial ischemia, and myocardial infarction. Overall, our predictions suggest that environmental risk factors may be underestimated for the most significant public health problems.
Bulk Viscous Flat FLRW Model with Observational Constraints in f(T, B) Gravity
Authors: Dixit Archana , Pradhan Anirudh
Published: December 2022

This paper investigates the impact of bulk viscosity within the framework of f(T,B) gravity. We consider a time-dependent viscosity model with a particular Hubble parameter expression. Here, we looked into the viability of well-motivated f(T,B) gravity model, which takes the form f=αlog(B)+βT, and has free parameters α and β. The 46 observational Hubble data (OHD) in the range 0≤z≤2.36 were used to constrain the model parameters to achieve the solution. We have used the Markov Chain Monte Carlo (MCMC) method to estimate model parameters and observe that the model appears to be in good agreement with the observations. In addition, we evaluate the effective viscous equation of state parameter for the f(T,B) model. We have examined the characteristics of different energy conditions for the stability analysis. The model is valid based on the positive behavior of null energy conditions (NEC), weak energy conditions (WEC), and dominant energy conditions (DEC); however, strong energy conditions (SEC) are in violation, suggesting that the universe is expanding faster. Our model was found in the quintom region. We also discussed how the tachyon scalar field corresponds to f(T,B) gravity.
Multiverse Predictions for Habitability: Element Abundances
Authors: Sandora McCullen , Airapetian Vladimir , Barnes Luke , Lewis Geraint F. , Pérez-Rodríguez Ileana
Published: December 2022

We investigate the dependence of elemental abundances on physical constants, and the implications this has for the distribution of complex life for various proposed habitability criteria. We consider three main sources of abundance variation: differing supernova rates, alpha burning in massive stars, and isotopic stability, and how each affects the metal-to-rock ratio and the abundances of carbon, oxygen, nitrogen, phosphorus, sulfur, silicon, magnesium, and iron. Our analysis leads to several predictions for which habitability criteria are correct by determining which ones make our observations of the physical constants, as well as a few other observed features of our universe, most likely. Our results indicate that carbon-rich or carbon-poor planets are uninhabitable, slightly magnesium-rich planets are habitable, and life does not depend on nitrogen abundance too sensitively. We also find suggestive but inconclusive evidence that metal-rich planets and phosphorus-poor planets are habitable. These predictions can then be checked by probing regions of our universe that closely resemble normal environments in other universes. If any of these predictions are found to be wrong, the multiverse scenario would predict that the majority of observers are born in universes differing substantially from ours, and so can be ruled out, to varying degrees of statistical significance.
PossibleExistence of Dark-Matter-Admixed Pulsar in the Disk Region of the Milky Way Galaxy
Authors: Rahman Nilofar , Murshid Masum , Molla Sajahan , Kalam Mehedi
Published: December 2022

In our previous study, (Eur Phys J Plus 135:362, 2020 & Eur Phys J Plus 135:637, 2020), we have discussed the possible existence of the dark-matter-admixed pulsars, located in dwarf as well as in massive spiral galaxies (based on Singular Isothermal Sphere dark-matter density profile) and in the Milky Way galaxy (based on Universal Rotational Curve dark-matter density profile). In this article, we use the Navarro–Frenk–White (NFW) dark-matter density profile to get analogous results for the pulsars in the disk region of the Milky Way galaxy. These findings may be treated as valuable complements to the previous findings. We conclude from our findings that there is a unique possibility of the presence of dark-matter-admixed pulsars in all the regions of the galaxies.
An IgY Effectively Prevents Goslings from Virulent GAstV Infection
Authors: Zhang Mengran , Zhang Lijiao , Yang Jing , Zhao Dongmin , Han Kaikai , Huang Xinmei , Liu Qingtao , Xiao Yichen , Gu Youfang , Li Yin
Published: December 2022

Goose astrovirus (GAstV) leads to viscera and joints urate deposition in 1- to 20-day-old goslings, with a mortality rate of up to 50%, posing a severe threat to entire colonies; however, there is no efficient prevention and control method for GAstV infection. This study describes a prophylactic anti-GAstV strategy based on the specific immunoglobulin Y (IgY) from egg yolk. The specific IgY was produced by 22-week-old laying hens intramuscularly immunized with the inactivated GAstV three consecutive times, with 2-week intervals. The egg yolk was collected weekly after the immunization and the anti-GAstV IgY titer was monitored using an agar gel immune diffusion assay (AGID). The results revealed that the AGID titer began to increase on day 7, reached a peak on day 49, and remained at a high level until day 77 after the first immunization. The specific IgY was prepared from the combinations of egg yolk from day 49 to day 77 through PEG-6000 precipitation. Animal experiments were conducted to evaluate the effects of prevention and treatment. The result of the minimum prophylactic dose of the IgY showed that the protection rate was 90.9% when 2.5 mg was administrated. Results of the prevention and the treatment experiments showed prevention and cure rates of over 80% when yolk antibody was administered in the early stages of the GAstV infection. These results suggested that the specific IgY obtained from immunized hens with the inactivated GAstV could be a novel strategy for preventing and treating GAstV infection.
Impact of COVID-19 Vaccination on Heart Rate Variability: A Systematic Review
Authors: Kwon Chan-Young , Lee Boram
Published: December 2022

Establishing and disseminating evidence-based safety information could potentially facilitate beneficial choices in coronavirus disease (COVID-19) vaccinations. This systematic review investigated the potential impact of COVID-19 vaccinations on human heart rate variability (HRV) parameters through comprehensive searches of four electronic medical databases. Five observational studies reporting HRV parameters of individuals vaccinated against COVID-19 and published up to 29 July 2022 were included in this review. Among them, four studies reported the square root of the mean squared differences of successive NN intervals (RMSSD) as their outcome, and the remaining study reported an HRV-based stress indicator. These studies reported short-term changes and rapid recovery in HRV parameters within up to 3 days after COVID-19 vaccination. Some studies showed that the impact of COVID-19 vaccinations on RMSSD was greater in women than men, and in the younger group than in the older group. The methodological quality of the included studies was not optimal; the review revealed short-term changes in HRV parameters, particularly RMSSD, following COVID-19 vaccination. However, as the included studies did not report important parameters besides RMSSD, the limitation exists that the postvaccination long-term HRV stability was not reported.
A Descriptive Analysis of the Relationship between Social Media Use and Vaccine Hesitancy among a Sample of Unvaccinated Adults in Canada
Authors: Chen Thomas , Piltch-Loeb Rachael , Harriman Nigel , Testa Marcia , Savoia Elena
Published: December 2022

Both traditional and social media information sources have disseminated information on the COVID-19 pandemic. The content shared may influence public opinion on different mitigation strategies, including vaccination. Misinformation can alter risk perception and increase vaccine hesitancy. This study aimed to explore the impact of using social media as the primary information source about the COVID-19 vaccine on COVID-19 vaccine hesitancy among people living in Canada. Secondary objectives identified other predictors of vaccine hesitancy and distinguished the effects of using traditional and social media sources. We used quota sampling of adults in Canada [N = 985] to conduct an online survey on the Pollfish survey platform between 21st and 28th May 2021. We then used bivariate chi-squared tests and multivariable logistic regression modeling to explore the associations between using social media as one’s primary source of information about the COVID-19 vaccine and vaccine hesitancy. We further analyzed the association between specific types of channels of information and vaccine hesitancy. After controlling for covariates such as age, sex, race, and ethnicity, individuals reporting social media as their primary source of COVID-19 vaccine information versus those who had not used social media as their primary source of COVID-19 vaccine information had 50% higher odds of vaccine hesitancy. Among different channels of information, we found that information from television was associated with a 40% lower odds ratio for vaccine hesitancy. Since social media platforms play an essential role in influencing hesitancy in taking the COVID-19 vaccination, it is necessary to improve the quality of social media information sources and raise people’s trust in information. Meanwhile, traditional media channels, such as television, are still crucial for promoting vaccination programs.
Knowledge and Attitude Regarding Monkeypox Virus among Physicians in Saudi Arabia: A Cross-Sectional Study
Authors: Alshahrani Najim Z. , Algethami Mohammed R. , Alarifi Abdullah M. , Alzahrani Faris , Alshehri Eman A. , Alshehri Aishah M. , Sheerah Haytham Abdulwhab , Abdelaal Abdelaziz , Sah Ranjit , Rodriguez-Morales Alfonso J.
Published: December 2022

The growing incidence of human monkeypox cases emphasizes the significance of prevention, early detection, and prompt responses for healthcare providers. The aim of this study was to assess the knowledge and attitudes toward monkeypox infection among physicians, a frontline healthcare worker group, in Saudi Arabia. A cross-sectional survey assessing knowledge and attitudes towards monkeypox infection on multiple-item scales was sent to physicians in Saudi Arabia. The associations between independent factors and either knowledge or attitude were assessed. The final analysis included 398 participants. Approximately 55% of the surveyed participants had a “good knowledge” score about human monkeypox. The adjusted logistic regression analysis showed that being a female physician, working in the private sector, and having information on human monkeypox during medical school or residency years were the only factors associated with a good level of knowledge about human monkeypox. However, physicians’ knowledge and attitudes regarding monkeypox infection are inadequate and influenced by various factors. There is a significant knowledge gap between the therapeutic management of monkeypox and its vaccination. Training and knowledge assessments are important, especially when studies show significant improvement in related and specific knowledge.
Effect of Breeding Season on Haemosporidian Infections in Domestic Chickens
Authors: Che-Ajuyo Nuela Manka’a , Rao Xiaodong , Liu Boye , Deng Zhuqing , Dong Lu , Liang Wei
Published: December 2022

Reproduction is believed to contribute to the frequently observed seasonal cycles in parasite loads in many organisms, as an investment in reproduction by the host could result in a higher susceptibility to parasites. In this study, we examined the impact of breeding season on haemosporidian infection in free-range chickens (Gallus gallus domesticus). We sampled a total of 122 chickens (66 chickens during the breeding season of April 2017 and 56 chickens during the non-breeding season of January 2017) to test for haemosporidian infections. The result showed that 56 out of 66 chickens examined during the breeding season tested positive for parasites (84.8% parasite prevalence), whereas 39 out of 56 chickens tested positive for parasites during the non-breeding season (69.6% parasite prevalence). Moreover, among the 11 Leucocytozoon lineages and 2 Plasmodium lineages identified, the parasite lineages that infected chickens during the breeding season were more diversified than those that affected chickens during the non-breeding season. This study indicated that chickens have a higher incidence of haemosporidian infection and a greater diversity of haemosporidian parasite lineages during the breeding season relative to the non-breeding season.
Plasma Chymase Activity Reflects the Change in Hemodynamics Observed after the Surgical Treatment of Patent Ductus Arteriosus in Dogs
Authors: Shimada Kazumi , Hamabe Lina , Hirose Miki , Watanabe Momoko , Yokoi Aimi , Takeuchi Aki , Ozai Yusuke , Yoshida Tomohiko , Takai Shinji , Jin Denan , Kocaturk Meric , Uehara Katsumi , Tanaka Ryou
Published: December 2022

Chymase is a protease stored in mast cell granules that produces angiotensin II (ANG II) from angiotensin I (ANG I) and is associated with tissue injury, inflammation, and remodeling, especially involving the cardiovascular system. As cardiovascular events occur, chymase is activated by degranulation to the extracellular matrix. Although chymase has been suggested to be associated with cardiovascular disease progression, there are not enough reports in veterinary medicine. Patent ductus arteriosus (PDA) is a common congenital cardiac disease in veterinary medicine. Almost all cases of PDA can be treated surgically to prevent the development of congestive heart disease and/or pulmonary hypertension. The aims of the present study were to measure chymase activity before and after PDA occlusions, and to investigate the relationships between the congestive and hemodynamic states of PDA and chymase activity. In the present study, 17 puppies diagnosed with PDA were included and all puppies completely recovered to the level of healthy dogs. Chymase activity significantly decreased at 2 months after the operation, along with the echocardiography parameters of congestion. Therefore, plasma chymase activity may be useful as a novel predictor for understanding the hemodynamics of PDA in veterinary medicine.