bluuebunny/crossref_metadata_2025 huggingface dataset:
Unsupervised Clustering of Heartbeat Dynamics Allows for Real Time and Personalized Improvement in Cardiovascular Fitness
Authors: Serantoni Cassandra , Zimatore Giovanna , Bianchetti Giada , Abeltino Alessio , De Spirito Marco , Maulucci Giuseppe
Published: May 2022

VO2max index has a significant impact on overall health. Its estimation through wearables notifies the user of his level of fitness but cannot provide a detailed analysis of the time intervals in which heartbeat dynamics are changed and/or fatigue is emerging. Here, we developed a multiple modality biosignal processing method to investigate running sessions to characterize in real time heartbeat dynamics in response to external energy demand. We isolated dynamic regimes whose fraction increases with the VO2max and with the emergence of neuromuscular fatigue. This analysis can be extremely valuable by providing personalized feedback about the user’s fitness level improvement that can be realized by developing personalized exercise plans aimed to target a contextual increase in the dynamic regime fraction related to VO2max increase, at the expense of the dynamic regime fraction related to the emergence of fatigue. These strategies can ultimately result in the reduction in cardiovascular risk.
Estimation of Elbow Wall Thinning Using Ensemble-Averaged Mel-Spectrogram with ResNet-like Architecture
Authors: Kim Jonghwan , Chung Byunyoung , Park Junhong , Choi Youngchul
Published: May 2022

An elbow wall thinning diagnosis method by highlighting the stationary characteristics of the operating loop is proposed. The accelerations of curved pipe surfaces were measured in a closed test loop operating at a constant pump rpm, combined with curved pipe specimens with artificial wall thinning. The vibration characteristics of wall-thinned elbows were extracted by using a mel-spectrogram in which modal characteristic variation shifting can be expressed. To reduce the deviation of the model’s prediction values, the ensemble mean value of the mel-spectrogram was used to emphasize stationary signals and reduce noise signals. A convolutional neural network (CNN) regression model with residual blocks was proposed and showed improved performance compared to the models without the residual block. The proposed regression model predicted the thinning thickness of the elbow excluded in training dataset.
Distributed-Satellite-Clusters-Based Spectrum Sensing with Two-Stage Phase Alignment
Authors: Wang Yunfeng , Ding Xiaojin , Hong Tao , Zhang Gengxin
Published: May 2022

We investigate a distributed-satellite-clusters (DSC)-system-based spectrum sensing, to enhance the ability for sensing weak signals. However, the spectrum-sensing performance may be significantly decreased by the phase deviations among different satellite clusters, where the deviations may be caused by the movement and the perturbation of satellites. To eliminate such a decrement, we propose a cooperative spectrum-sensing scheme in the presence of phase deviations, where the deviations are alleviated by a special two-stage phase synchronization. Specifically, the phase compensation is first performed relying on broadcasting reference signals and the ephemeris, to address the challenges of the deviations caused by the movement. Then, a two-bit feedback algorithm, having a dynamic disturbance step size, is further adopted for controlling and mitigating the deviations caused by the perturbation. Additionally, we provide the closed-form expression of the correct detection probability of the proposed spectrum-sensing scheme, using the specially derived probability density function of the sum of the shadowed-Rician random variables with independently identical distribution. Simulation results show that the proposed scheme can achieve the best spectrum-sensing performance, comparing with the traditional energy detection, eigenvalue ratio test and the generalized likelihood ratio test.
The Effect of the Back-Pressure Changes in an Exhaust System on Vibration When Attaching a Variable Device during Idling
Authors: Kang Il-Seok , Yang Sung-Mo
Published: May 2022

The vibration of the ignition frequency component of the engine during idling causes driver discomfort. To minimize this, an optimal exhaust system with a variable device that can exert optimal pressure is required. In this study, the geometry of the variable device was designed in orifice and cylinder types. Next, the designed variable devices were implemented in a conventional exhaust system with an X chamber. A comparative analysis was conducted to propose an optimal geometry through back-pressure and vibration measurements. During the experiment, the orifice geometry exhibited higher back pressure than the conventional geometry and a large difference in back pressure before and at the exhaust gas merging position. Furthermore, the orifice geometry showed a 2.56% increase in the vibration of the 1X component in the Y-axis direction. By contrast, the cylinder geometry exhibited slightly higher back pressure than the conventional geometry and the smallest difference in back pressure before and at the exhaust gas merging position. The cylinder geometry showed a 2.45% reduction in the vibration of the 1X component in the Y-axis direction.
Performance Evaluation of Cooperative OMA and NOMA Systems in 6G Deployment Scenarios
Authors: Jain Preksha , Gupta Akhil , Kumar Neeraj , Joshi Gyanendra Prasad , Cho Woong
Published: May 2022

Optimization of the energy efficiency, fairness, and rates of the system is a vital part of communication systems. Multiple access techniques have a huge potential to enhance such performance parameters. This paper studies the performance of NOMA and OMA systems in a singular cell environment, where the cellular users are distributed randomly, and cooperative relays are considered for better system reliability. The relay nodes forward the signals to the cell-edge users. This paper considers a practical scenario where all the relay equipment is distributed with non-uniform battery power levels. The performance of OMA and NOMA schemes is compared based on the key performance indicators: sum rate, fairness, and energy efficiency. The fairness factor determines fairness in the allocation of resources to all the system’s users. The performance of the two schemes is assessed in three deployment scenarios: urban, suburban, and rural scenarios. Through numerical results, it is proved that the performance of the NOMA dominates the OMA scheme.
Characteristic Differences of Wind-Blown Sand Flow Field of Expressway Bridge and Subgrade and Their Implications on Expressway Design
Authors: Xie Shengbo , Zhang Xian , Pang Yingjun
Published: May 2022

Bridges and subgrades are the main route forms for expressways. The ideal form for passing through sandy areas remains unclear. This study aims to understand the differences in the influence of expressway bridges and subgrades on the near-surface blown sand environment and movement laws, such as the difference in wind speed and profile around the bridge and subgrade, the difference in wind flow-field characteristics, and the difference in sand transport rate, to provide a scientific basis for the selection of expressway route forms in sandy areas. Therefore, a wind tunnel test was carried out by making models of a highway bridge and subgrade and comparing the environmental effects of wind sand on them. The disturbance in the bridge to near-surface blown sand activities was less than that of the subgrade. The variation ranges of the wind speed of the bridge and its upwind and downwind directions were lower than those of the subgrade. However, the required distance to recover the wind speed downwind of the bridge was greater than that of the subgrade, resulting in the sand transport rate of the bridge being lower than that of the subgrade. The variation in the wind field of the subgrade was more drastic than that of the bridge, but the required distance to recover the wind field downwind of the bridge was greater than that of the subgrade. In the wind speed-weakening area upwind, the wind speed-weakening range and intensity of the bridge were smaller than those of the subgrade. In the wind speed-increasing area on the top of the model, the wind speed-increasing range and intensity of the bridge were smaller than those of the subgrade. In the wind-speed-weakening area downwind, the wind speed weakening range of the bridge was greater than that of the subgrade, and the wind speed-weakening intensity was smaller than that of the subgrade. This investigation has theoretical and practical significance for the selection of expressway route forms in sandy areas.
Accurate Step Count with Generalized and Personalized Deep Learning on Accelerometer Data
Authors: Luu Long , Pillai Arvind , Lea Halsey , Buendia Ruben , Khan Faisal M. , Dennis Glynn
Published: May 2022

Physical activity (PA) is globally recognized as a pillar of general health. Step count, as one measure of PA, is a well known predictor of long-term morbidity and mortality. Despite its popularity in consumer devices, a lack of methodological standards and clinical validation remains a major impediment to step count being accepted as a valid clinical endpoint. Previous works have mainly focused on device-specific step-count algorithms and often employ sensor modalities that may not be widely available. This may limit step-count suitability in clinical scenarios. In this paper, we trained neural network models on publicly available data and tested on an independent cohort using two approaches: generalization and personalization. Specifically, we trained neural networks on accelerometer signals from one device and either directly applied them or adapted them individually to accelerometer data obtained from a separate subject cohort wearing multiple distinct devices. The best models exhibited highly accurate step-count estimates for both the generalization (96–99%) and personalization (98–99%) approaches. The results demonstrate that it is possible to develop device-agnostic, accelerometer-only algorithms that provide highly accurate step counts, positioning step count as a reliable mobility endpoint and a strong candidate for clinical validation.
Uplink NOMA-MIMO Systems with Rayleigh Power Distribution
Authors: Bakulin Mikhail , Ben Rejeb Taoufik , Kreyndelin Vitaly , Pankratov Denis , Smirnov Aleksei
Published: May 2022

The article is devoted to multiple-input multiple-output antenna systems, also called MIMO systems, which are widely used in wireless communication systems. In this article we consider a case when the MIMO system works in overloaded mode. In this mode MIMO systems can be considered as a system with non-orthogonal multiple access NOMA. The main goal of this article is to analyze this interesting case using statistical computer simulation. Based on the analysis of the capacity of a discrete-continuous multiuser MIMO uplink channel, the possibility of such systems functioning in overload mode is proved.
To Assist Oncologists: An Efficient Machine Learning-Based Approach for Anti-Cancer Peptides Classification
Authors: Alsanea Majed , Dukyil Abdulsalam , Afnan  , Riaz Bushra , Alebeisat Farhan , Islam Muhammad , Habib Shabana
Published: May 2022

In the modern technological era, Anti-cancer peptides (ACPs) have been considered a promising cancer treatment. It’s critical to find new ACPs to ensure a better knowledge of their functioning processes and vaccine development. Thus, timely and efficient ACPs using a computational technique are highly needed because of the enormous peptide sequences generated in the post-genomic era. Recently, numerous adaptive statistical algorithms have been developed for separating ACPs and NACPs. Despite great advancements, existing approaches still have insufficient feature descriptors and learning methods, limiting predictive performance. To address this, a trustworthy framework is developed for the precise identification of ACPs. Particularly, the presented approach incorporates four hypothetical feature encoding mechanisms namely: amino acid, dipeptide, tripeptide, and an improved version of pseudo amino acid composition are applied to indicate the motif of the target class. Moreover, principal component analysis (PCA) is employed for feature pruning, while selecting optimal, deep, and highly variated features. Due to the diverse nature of learning, experiments are performed over numerous algorithms to select the optimum operating method. After investigating the empirical outcomes, the support vector machine with hybrid feature space shows better performance. The proposed framework achieved an accuracy of 97.09% and 98.25% over the benchmark and independent datasets, respectively. The comparative analysis demonstrates that our proposed model outperforms as compared to the existing methods and is beneficial in drug development, and oncology.
An Effective Skin Cancer Classification Mechanism via Medical Vision Transformer
Authors: Aladhadh Suliman , Alsanea Majed , Aloraini Mohammed , Khan Taimoor , Habib Shabana , Islam Muhammad
Published: May 2022

Skin Cancer (SC) is considered the deadliest disease in the world, killing thousands of people every year. Early SC detection can increase the survival rate for patients up to 70%, hence it is highly recommended that regular head-to-toe skin examinations are conducted to determine whether there are any signs or symptoms of SC. The use of Machine Learning (ML)-based methods is having a significant impact on the classification and detection of SC diseases. However, there are certain challenges associated with the accurate classification of these diseases such as a lower detection accuracy, poor generalization of the models, and an insufficient amount of labeled data for training. To address these challenges, in this work we developed a two-tier framework for the accurate classification of SC. During the first stage of the framework, we applied different methods for data augmentation to increase the number of image samples for effective training. As part of the second tier of the framework, taking into consideration the promising performance of the Medical Vision Transformer (MVT) in the analysis of medical images, we developed an MVT-based classification model for SC. This MVT splits the input image into image patches and then feeds these patches to the transformer in a sequence structure, like word embedding. Finally, Multi-Layer Perceptron (MLP) is used to classify the input image into the corresponding class. Based on the experimental results achieved on the Human Against Machine (HAM10000) datasets, we concluded that the proposed MVT-based model achieves better results than current state-of-the-art techniques for SC classification.
Optimal Compact Network for Micro-Expression Analysis System
Authors: Sie-Min Koo , Zulkifley Mohd Asyraf , Kamari Nor Azwan Mohamed
Published: May 2022

Micro-expression analysis is the study of subtle and fleeting facial expressions that convey genuine human emotions. Since such expressions cannot be controlled, many believe that it is an excellent way to reveal a human’s inner thoughts. Analyzing micro-expressions manually is a very time-consuming and complicated task, hence many researchers have incorporated deep learning techniques to produce a more efficient analysis system. However, the insufficient amount of micro-expression data has limited the network’s ability to be fully optimized, as overfitting is likely to occur if a deeper network is utilized. In this paper, a complete deep learning-based micro-expression analysis system is introduced that covers the two main components of a general automated system: spotting and recognition, with also an additional element of synthetic data augmentation. For the spotting part, an optimized continuous labeling scheme is introduced to spot the apex frame in a video. Once the apex frames have been recognized, they are passed to the generative adversarial network to produce an additional set of augmented apex frames. Meanwhile, for the recognition part, a novel convolutional neural network, coined as Optimal Compact Network (OC-Net), is introduced for the purpose of emotion recognition. The proposed system achieved the best F1-score of 0.69 in categorizing the emotions with the highest accuracy of 79.14%. In addition, the generated synthetic data used in the training phase also contributed to performance improvement of at least 0.61% for all tested networks. Therefore, the proposed optimized and compact deep learning system is suitable for mobile-based micro-expression analysis to detect the genuine human emotions.
Simultaneous Determination of Fenchone and Trans-Anethole in Essential Oils and Methanolic Extracts of Foeniculum vulgare Mill. Fruits Obtained from Different Geographical Regions Using GC-MS Approach
Authors: Ahmad Wasim , Amir Mohd , Ahamad Syed Rizwan , Alam Prawez , Alshehri Sultan , Ghoneim Mohammed M. , Wahab Shadma , Shakeel Faiyaz
Published: May 2022

The gas chromatography–mass spectrometry (GC-MS) approach is established for the simultaneous determination of fenchone (FCO) and trans-anethole (TOH) in the essential oils and methanolic extracts of fennel (Foeniculum vulgare Mill.) fruits obtained from India (IND), Pakistan (PAK), and Saudi Arabia (SA). The simultaneous determination of FCO and TOH was performed via Agilent 190914S HP–5MS fused-silica capillary column (30 m × 250 µm ID, 0.25 µm film thickness). The proposed GC-MS approach was linear in the range of 0.10–50 µg/g for FCO and TOH. FCO’s detection (LOD) and quantification (LOQ) limits were calculated to be 0.04 and 0.12 µg/g, respectively. The LOD and LOQ values for TOH, on the other hand, were calculated to be 0.05 and 0.15 µg/g, respectively. In addition, the proposed GC-MS approach was accurate and precise for the simultaneous determination of FCO and TOH. The amount of FCO in essential oils of F. vulgare was computed as 0.021, 0.034, and 0.029 mg/g in the samples obtained from IND, PAK, and SA, respectively. The amount of TOH in the essential oils of F. vulgare was computed as 7.40, 14.8, and 10.2 mg/g in the samples obtained from IND, PAK, and SA, respectively. However, the amount of FCO in the methanolic extract of F. vulgare was estimated as 0.031, 0.021, and 0.057 mg/g in the samples obtained from IND, PAK, and SA, respectively. On the other hand, the amount of TOH in the methanolic extract of F. vulgare was estimated as 0.440, 0.498, and 1.74 mg/g in the samples obtained from IND, PAK, and SA, respectively. These findings suggested that the proposed GC-MS approach might be used to simultaneously determine the FCO and TOH in a variety of essential oils and plant extracts.
Methodological Approaches to Talent Identification in Team Sports: A Narrative Review
Authors: Barraclough Sam , Till Kevin , Kerr Adam , Emmonds Stacey
Published: May 2022

Talent identification (TID) and talent development (TD) continue to receive significant investment from team sports organisations, highlighting their importance in attempting to identify potential elite athletes. Accompanying this continual pursuit to unearth future talent is an ever-increasing body of research aiming to provide solutions and strategies to optimise TID and TD processes. Therefore, the aim of this review is to provide a summary and critical synthesis of the methodological approaches applied to TID in team sports and present considerations for future TID research. Specifically, this review highlights three key areas for consideration: (1) the timespan of the research design; (2) the use of monodisciplinary or multidisciplinary variables; and (3) the fidelity of the methodological approaches to the assessment of talent. The review highlights the benefits of longitudinal, multidisciplinary, and ecologically valid research designs for TID within team sports.
Informal Environment Regulation, Green Technology Innovation and Air Pollution: Quasi-Natural Experiments from Prefectural Cities in China
Authors: Wang Xinghua , Wu Shunchen , Qin Xiaojuan , La Meixiang , Zuo Haixia
Published: May 2022

Facing informal environment regulation carried out by the environmental protection organizations, we study and judge its inhibitory effect on air pollution and the acting path. Based on panel data of 285 cities in China from 1998 to 2018, a time-varying difference-in-difference model is used to estimate the effect of informal environment regulation on air pollution. The estimation results show that informal environment regulation can inhibit air pollution significantly under different scenarios. Green technology innovation is introduced into the research and a mediating effect model is used to investigate the influencing mechanism. Informal environment regulation strengthens pressure on pollutant emissions. This forces enterprises to enhance the investment and application of green technology innovation during production. Mechanism analysis shows that informal environment regulation inhibits air pollution by encouraging the application of green technology innovation. The above conclusions are still valid after a series of robustness tests, including parallel trend, placebo test and instrumental variables. The research conclusions provide empirical evidence for the construction of a diversified air-pollution control system and demonstrate the practical significance of informal environment regulation to improve air quality.
General Defense Response under Biotic Stress and Its Genetics at Pepper (Capsicum annuum L.)
Authors: Szarka János , Timár Zoltán , Hári Regina , Palotás Gábor , Péterfi Balázs
Published: May 2022

Since the beginning of resistance breeding, protection of plants against pathogens has relied on specific resistance genes encoding rapid tissue death. Our work has demonstrated in different host–pathogen relationships that plants can defend themselves against pathogens by cell growth and cell division. We first demonstrated this general defence response (GDR) in plants by identifying the gds gene in pepper. Subsequently, the existence of a genetic system for tissue defence became apparent and we set the goal to analyse it. The gdr 1 + 2 genes, which operate the complete GDR system, protect plant tissues from pathogens in a direcessive homozygous state in both host and non-host relationships. The inheritance pattern of the two genes follows a 12:3:1 cleavage of the dominant epistasis. With the knowledge of the gds and gdr 1 + 2 genes, the role of tissue-preserving (GDR) and tissue-destructive (HR) pathways in disease development and their relationship was determined. The genes encoding the general defence response have a low stimulus threshold and are not tissue-destructive and pathogen-specific. They are able to fulfil the role of the plant immune system by providing a general response to various specific stresses. This broad-spectrum general defence system is the most effective in the plant kingdom.
Establishment of Repeated In Vitro Exposure System for Evaluating Pulmonary Toxicity of Representative Criteria Air Pollutants Using Advanced Bronchial Mucosa Models
Authors: Upadhyay Swapna , Chakraborty Ashesh , Thimraj Tania A. , Baldi Marialuisa , Steneholm Anna , Ganguly Koustav , Gerde Per , Ernstgård Lena , Palmberg Lena
Published: May 2022

There is mounting evidence that shows the association between chronic exposure to air pollutants (particulate matter and gaseous) and onset of various respiratory impairments. However, the corresponding toxicological mechanisms of mixed exposure are poorly understood. Therefore, in this study, we aimed to establish a repeated exposure setting for evaluating the pulmonary toxicological effects of diesel exhaust particles (DEP), nitrogen dioxide (NO2), and sulfur dioxide (SO2) as representative criterial air pollutants. Single, combined (DEP with NO2 and SO2), and repeated exposures were performed using physiologically relevant human bronchial mucosa models developed at the air–liquid interface (bro-ALI). The bro-ALI models were generated using human primary bronchial epithelial cells (3–4 donors; 2 replicates per donor). The exposure regime included the following: 1. DEP (12.5 µg/cm2; 3 min/day, 3 days); 2. low gaseous (NO2: 0.1 ppm + SO2: 0.2 ppm); (30 min/day, 3 days); 3. high gaseous (NO2: 0.2 ppm + SO2: 0.4 ppm) (30 min/day, 3 days); and 4. single combined (DEP + low gaseous for 1 day). The markers for pro-inflammatory (IL8, IL6, NFKB, TNF), oxidative stress (HMOX1, GSTA1, SOD3,) and tissue injury/repair (MMP9, TIMP1) responses were assessed at transcriptional and/ or secreted protein levels following exposure. The corresponding sham-exposed samples under identical conditions served as the control. A non-parametric statistical analysis was performed and p < 0.05 was considered as significant. Repeated exposure to DEP and single combined (DEP + low gaseous) exposure showed significant alteration in the pro-inflammatory, oxidative stress and tissue injury responses compared to repeated exposures to gaseous air pollutants. The study demonstrates that it is feasible to predict the long-term effects of air pollutants using the above explained exposure system.
Therapeutic Approach to Botulinum Injections for Hemifacial Spasm, Synkinesis and Blepharospasm
Authors: Yahalom Gilad , Janah Amir , Rajz Gustavo , Eichel Roni
Published: May 2022

The aim of this study was to show our therapeutic outcome of botulinum injection to the facial muscles and thereby to find the best therapeutic concept which should be embraced. The decision to treat the lower eyelid with 1-point or 2-points injection was randomly taken as there is no consensus regarding this debate. Injections of the lateral end of the upper eyelid were performed more laterally to the conventional injection point, just lateral to the conjunction of the upper and lower eyelids. Twenty-three patients (12 hemifacial spasm, 6 blepharospasm, 5 post facial palsy synkinesis) were enrolled. Data were retrieved from 112 visits between 2019 and 2022. Overall, 84.9% of the treatments had moderate or marked improvement. The most common side effect was facial weakness (11.8%). Neither ptosis nor diplopia were noted. Two-points regimen in the lower eyelid was associated with a lower risk of facial weakness (p = 0.01), compared to 1-point regimen, with a better therapeutic outcome as reflected by more favorable PGI-C scores (p = 0.04). Injection of the pretarsal segment of the upper eyelid, just onto or even lateral to the conjunction of the upper and lower eyelids, lowers the risk of ptosis.
Effect of Fluid Composition on a Jet Breaking out of a Cocoon in Gamma-Ray Bursts: A Relativistic de Laval Nozzle Treatment
Authors: Vyas Mukesh K.
Published: May 2022

In this paper we carry out a semi-analytic general relativistic study of a Gamma-Ray Bursts (GRB) jet that is breaking out of a cocoon or stellar envelope. We solve hydrodynamic equations with the relativistic equation of state that takes care of fluid composition. In short GRBs, a general relativistic approach is required to account for curved spacetime in strong gravity. The piercing of the jet through the cocoon resembles a de Laval nozzle and the jet may go through recollimation shock transitions. We show that the possibility of shock transition and the shock properties are sensitive to the matter composition and the cocoon strength. Obtained Lorentz factors in thermally driven jets comfortably reach few ×10.
Quantum Fluctuations in Vacuum Energy: Cosmic Inflation as a Dynamical Phase Transition
Authors: Morikawa Masahiro
Published: May 2022

A variety of models of inflation in the early Universe have been proposed and applied to describe successfully the origin of all possible structures in the Universe. On the other hand, inflation theory is still phenomenological and needs systematic physical foundations, including the relation to dark matter and dark energy. The essence of cosmic inflation would be a dynamical phase transition and the spontaneous symmetry breaking process, which are common in ordinary physics in the laboratory. At the beginning of the phase transition, the system is often in an adiabatic ground state and produces a squeezed state. This is widely interpreted as the generation of classical structures; however, it is not. The common notion of decoherence is not sufficient to describe the inflationary phase transition: a particular trajectory must be singled out in the dynamics. When an interaction turns on, dissipation or the energy flow/cascade is possible, and the c-number random field appears. The separation of these classical statistical fluctuations from the deterministic time evolution is indicated by the secular divergence or the infrared divergence of the system. We describe this phase transition based on the closed-time-path method and derive a quantum Langevin equation with classical noise, which sources the development of a coherent state. Introducing the effective action method to describe the evolution of the coherent state, we describe the order parameter that characterizes the phase transition and the associated spontaneous symmetry breaking. Since this phase transition process is common in physics, we discuss further applications of this formalism in other physical systems.
Preclinical Efficacy of a Capsid Virus-like Particle-Based Vaccine Targeting IL-1β for Treatment of Allergic Contact Dermatitis
Authors: Goksøyr Louise , Funch Anders B. , Okholm Anna K. , Theander Thor G. , de Jongh Willem Adriaan , Bonefeld Charlotte M. , Sander Adam F.
Published: May 2022

Hypersensitivity to a contact allergen is one of the most abundant forms of inflammatory skin disease. Today, more than 20% of the general population are sensitized to one or more contact allergens, making this disease an important healthcare issue, as re-exposure to the allergen can initiate the clinical disease termed allergic contact dermatitis (ACD). The current standard treatment using corticosteroids is effective, but it has side effects when used for longer periods. Therefore, there is a need for new alternative therapies for severe ACD. In this study, we used the versatile Tag/Catcher AP205 capsid virus-like particle (cVLP) vaccine platform to develop an IL-1β-targeted vaccine and to assess the immunogenicity and in vivo efficacy of the vaccine in a translational mouse model of ACD. We show that vaccination with cVLPs displaying full-length murine IL-1β elicits high titers of neutralizing antibodies, leading to a significant reduction in local IL-1β levels as well as clinical symptoms induced by treatment with 1-Fluoro-2,4-dinitrobenzene (DNFB). Moreover, we show that a single amino acid mutation in muIL-1β reduces the biological activity while maintaining the ability to induce neutralizing antibodies. Collectively, the data suggest that a cVLP-based vaccine displaying full-length IL-1β represents a promising vaccine candidate for use as an alternative treatment modality against severe ACD.
Nucleic Acid Vaccine Platform for DENGUE and ZIKA Flaviviruses
Authors: Taslem Mourosi Jarin , Awe Ayobami , Jain Swati , Batra Himanshu
Published: May 2022

Dengue virus and Zika virus are mosquito-borne, single-stranded, positive-sense RNA viruses that belong to the Flaviviridae family. Both the viruses are closely related and have similarities with other flaviviruses. Dengue virus (DENV) causes a severe febrile illness with fever, joint pain, and rash leading to a life-threatening condition in severe cases. While Zika virus (ZIKV) primarily causes mild fever, it can be passed from a pregnant mother to her fetus, resulting in severe birth defect microcephaly and even causing a rare autoimmune disease—Guillain–Barre syndrome. To date, there are no approved DENV and ZIKA vaccines available, except a Dengue vaccine (Dengvaxia, Sanofi Pasteur Inc., Lyon, France) recently approved to be used only for 9–16 years of age groups living in endemic areas and having a previous record of confirmed dengue infection. There are several potential vaccine candidates in the clinical trials based on multiple vaccine platforms, such as live attenuated, subunit, nucleic acid, and viral vector-based vaccines. In the current review, we have focused exclusively on the nucleic acid vaccine platform and discussed the progress of all the DNA/RNA vaccine candidates under preclinical and clinical studies for DENV and ZIKA viruses. Additionally, we have described a brief history of the emergence of these flaviviruses, major structural similarities between them, prominent vaccine targets, and the mechanism of virus entry and infection.
mRNA COVID-19 Vaccine Reactogenicity among Healthcare Workers: Results from an Active Survey in a Pediatric Hospital from Bucharest, January–February 2021
Authors: Crăciun Maria-Dorina , Nițescu Gabriela Viorela , Golumbeanu Mihaela , Tănase Alina-Andreea , Pițigoi Daniela , Săndulescu Oana , Crăciun Petru , Enciu Bianca Georgiana , Bălănescu Radu Ninel , Ulici Alexandru
Published: May 2022

In Romania, health and social workers were prioritized for COVID-19 vaccination. We aimed to describe the vaccine adverse events identified through an active survey (using an electronic questionnaire) conducted among the staff of a pediatric hospital from Bucharest, vaccinated with the mRNA Pfizer-BioNTech vaccine. Data on the frequency and duration of adverse events were collected and analyzed using Microsoft Excel, Epi Info, and MedCalc. The questionnaire was sent to 426 persons. The participation rate was 81.2% after 1st dose and 63.8% after the 2nd dose. Overall, 81.9% were women, median age 42 (IQR 32–50 years). A total of 48 respondents (14.8%) reported no adverse event after the 1st dose and 35 (14.1) after the 2nd dose. No anaphylaxis was reported. The most frequent adverse event was pain at injection site, being reported by 261 responders (80.3%) after 1st dose and 187 (75.1%) after 2nd dose. Fatigue and headache were reported significantly less frequently in our study compared with data provided by the vaccine manufacturer. The current study has shown higher local reactogenicity after the first dose of the vaccine and higher systemic reactogenicity after the second dose. This real-world knowledge of the reactogenicity and safety profile may increase the vaccine’s acceptance rate among healthcare workers.
Modeling Combined Operation of Engine and Torque Converter for Improved Vehicle Powertrain’s Complex Control
Authors: Diachuk Maksym , Easa Said M.
Published: May 2022

This paper proposes an alternative model for describing the hydro-mechanical drive operation of the automatic transmissions. The study is aimed at preparing a reliable model that meets the requirements of sufficient informativeness and rapidity to, basically, be used as a model for optimized control. The study relevance is stipulated by the need for simple and precise models ensuring minimal computational costs in model predictive control (MPC) procedures. The paper proposes a method for coordinating the engine’s control and operating modes, with the torque converter (TC) operating mode, based on the criteria of angular acceleration derivative (jerk), which fosters including the angular acceleration in the state vector for using the optimal control. The latter provides stronger prediction quality than using only the crankshaft angular speed criterion. This moment comprises a study novelty. Additionally, the proposed approach can be helpful in tasks of powertrain automation, autonomous vehicles’ integrated control, elaboration of control algorithms, co-simulations, and real-time applications. The paper material is structured by the modeling stages, including mathematics and simulations, data preparation, testing and validation, virtual experiments, analysis of results, and conclusions. The essence of the problem, goals, and objectives are first presented, followed by the overview of main approaches in modeling the automatic transmission elements. The internal combustion engine (ICE), torque converter, drivetrain, tires, and translational dynamics mathematical models are determined and discussed in detail. The proposed approach convergence on decomposing the indicators of powertrain aggregates by derivatives is demonstrated. The considered method was simulated by using the data of the Audi A4 Quattro. The gear shifting control algorithm was described in detail, and a series of virtual tests for the composed model were carried out. The comparative analysis of the results for the conventional and advanced models of the automatic transmission’s hydro-mechanical drive were performed. The differences of the model outputs were discussed. The approach advantages were noted, as well as the options for extending the proposed technique.
Strategies for Hypothermia Compensation in Altricial and Precocial Newborn Mammals and Their Monitoring by Infrared Thermography
Authors: Lezama-García Karina , Mota-Rojas Daniel , Martínez-Burnes Julio , Villanueva-García Dina , Domínguez-Oliva Adriana , Gómez-Prado Jocelyn , Mora-Medina Patricia , Casas-Alvarado Alejandro , Olmos-Hernández Adriana , Soto Paola , Muns Ramon
Published: May 2022

Thermoregulation in newborn mammals is an essential species-specific mechanism of the nervous system that contributes to their survival during the first hours and days of their life. When exposed to cold weather, which is a risk factor associated with mortality in neonates, pathways such as the hypothalamic–pituitary–adrenal axis (HPA) are activated to achieve temperature control, increasing the circulating levels of catecholamine and cortisol. Consequently, alterations in blood circulation and mechanisms to produce or to retain heat (e.g., vasoconstriction, piloerection, shivering, brown adipocyte tissue activation, and huddling) begin to prevent hypothermia. This study aimed to discuss the mechanisms of thermoregulation in newborn domestic mammals, highlighting the differences between altricial and precocial species. The processes that employ brown adipocyte tissue, shivering, thermoregulatory behaviors, and dermal vasomotor control will be analyzed to understand the physiology and the importance of implementing techniques to promote thermoregulation and survival in the critical post-birth period of mammals. Also, infrared thermography as a helpful method to perform thermal measurements without animal interactions does not affect these parameters.
Photoperiodic Modulation in Immune and Reproductive Systems in Japanese Quails (Coturnix japonica): A Morphometric Perspective
Authors: Hayat Khizar , Raza Ali , Anas Aitzaz , Qureshi Anas Sarwar , Rehan Sarmad , Rabbani Ameer Hamza , Rehman Hafiz Faseeh ur , Qamar Abdul Ghaffar , Rehman Tayyab , Deeba Farah , Salman Amber
Published: May 2022

The present study was designed to elucidate a relationship between lymphoid organs and reproductive activity in male Japanese quails (Coturnix japonica) bred in a temperate region of Pakistan (30.3753° N, 69.3451° E) in response to photoperiodic changes. The research focused primarily on the relative morphological changes in primary (thymus and bursa of Fabricius) and secondary (spleen) lymphoid organs with respect to seasonal variations in the histomorphometry of testicular tissue. For this purpose, a comparable number of clinically healthy Japanese quails were exsanguinated during active (April–May), regressive (September–October) and inactive (January–February) reproductive phases. Following an extensive gross measurement of lymphoid and reproductive organs, a histomorphometric analysis was performed on sampled tissues by employing ImageJ® software. Blood was collected for hormonal and leukocytic analysis. One-way ANOVA was used for statistical comparison. Testes had the highest parenchymal development in the active phase (80.66 ± 21.22 µm) and the lowest in the inactive phase (27.80 ± 7.22 µm). Conversely, a percentage change was evident in the sizes of primary (bursa: 61.5%, thymus: 46.9%) and secondary (spleen: 23.9%) lymphoid organs during inactive and active reproductive phases. This study demonstrated that a physiological trade-off is imperative between immune and reproductive systems for optimum survivability and reproductive performance.
An Efficient Numerical Model to Predict the Mechanical Response of a Railway Track in the Low-Frequency Range
Authors: El Moueddeb Maryam , Louf François , Boucard Pierre-Alain , Dadié Franck , Saussine Gilles , Sorrentino Danilo
Published: May 2022

With railway interoperability, new trains are allowed to move on the French railway network. These trains may present different designs from standard trains. This work aims to complete the current approach for vehicle admission on the railway network, which is defined in technical baselines. Historically, computation rules for traffic conditions are based on simplified analytical works, which are considerably qualitative. They have evolved through feedback and experimental campaigns to comply with the track structure evolution. An efficient methodology based on numerical simulation is needed to evaluate railway vehicle admission to answer this issue. A perspective to update these computation rules is to evaluate the structural fatigue in the rail. That is to say, fatigue is caused by bending and shear stresses. The complexity of the railway system has led to an investigation at first of the vertical response of the railway track and quantifying its contribution to the rail’s stress response. In that sense, this paper investigates the vertical track response to a moving railway vehicle at low frequencies. For this purpose, a lightweight numerical model for the track, a multi-body model for the vehicle, and a random vertical track irregularity are proposed. More explicitly, the track model consists of a two-layer discrete support model in which the rail is considered as a beam and sleepers are point masses. The rail pads and ballast layer are modelled as spring/damper couples. Numerical results show a negligible effect of track inertia forces due to high track stiffness and damping. Nevertheless, this assumption is valid for normal rail stresses but not for ballast loading, especially in the case of sleeper voids or unsupported sleepers. Hence, the prediction of the mechanical stress state in the rail for fatigue issues is achieved through a static track model where the equivalent loading is obtained from a dynamic study of a simplified vehicle model. A statistical analysis shows that the variability of the vertical track irregularity does not influence the output variabilities like the maximum in time and space of the normal and shear stress.
Ways to improve the provision of measures of state support for the development of small and medium-sized businesses in the Russian Federation
Authors:   Russian University of Cooperation, Pyastolov O.A. , Stoynova A.F. ,   Russian University of Cooperation
Published: May 2022

The article is devoted to the analysis of the current state and problems of the development of small and medium-sized businesses in the Russian Federation; the correction of the mission and the goals of the development of small and medium-sized businesses in the Russian Federation is proposed. In addition, the factors that hinder the development of entrepreneurial activity are identified, and systemic measures, methods and mechanisms of support for small and medium-sized businesses are proposed. The paper considers and analyzes the existing measures to support small and medium-sized businesses in the Russian Federation. A retrospective analysis of the current regulatory framework has been carried out. Also, the aspect of the application of promising directions of the development of scientific and technological progress and the demand for its results in the general theory of business management have been studied. The authors proposed adjustments and additions to the small and medium-sized business management model, taking into account the increasing possibilities of scientific and technological progress, the development and improvement of the general management theory and the prospects for working in foreign markets. The conducted study helps to supplement the theoretical picture of the effectiveness of the application of the regulatory framework by small and medium-sized businesses and ensures the sustainable progressive development of the theory of business management in the current epidemiological situation in the country.
Nanostructured dry extract of dandelion: properties and applications in the production of functional food
Authors:   Laboratory of Synthesis of Micro- and Nanostructures, Regional Open Social Institute, Krolevets A.A. , Myachikova N.I. ,   Belgorod State National Research University, Glotova S.G. ,   Regional Open Social Institute, Staneva A.I. ,   Belgorod State National Research University, Androsova A.A. ,   Belgorod State National Research University, Ivanov A.S. ,   Kursk State Agricultural Academy
Published: May 2022

The paper presents the properties of nanostructured dry dandelion extract and its application for the production of yoghurt, ice cream and marmalade. The data on self-organization and the size of nanostructured dry extract of dandelion using the NTA method are presented.
Contemporary Russian-Chinese relations and the US position
Authors:   Moscow University for the Humanities, Alekseenko Dara
Published: May 2022

Russia's relations with China occupy one of the most important places in Russian politics. This is due to geographic proximity, the place of the People's Republic of China in the world economy and its potential, and its influence on the international situation. At the current stage, relations with China are becoming increasingly important for the Russian Federation. The Russian Federation and the People's Republic of China are building their strategic partnership on the basis of common national interests, as well as on the basis of historical experience. The article discusses the relationship between Russia and China, describes the nature of the interaction between the two countries at the present stage, and considers the challenges and problems that arise in the future in the economic and political sphere of international relations between Russia and China. Since the United States of America, the People's Republic of China and the Russian Federation, today's main geopolitical players and leading military powers, are in a complex triangle of relationships, the position of the United States is considered.
Methodological approaches to the formation of income and expense accounting registers for tax purposes
Authors:   Federal State Budgetary Educational Institution of Higher Education “RGAU — MSHA named after K. A. Timiryazev”, Moscow, Khoruzhy L. I. , Katkov Yu. N. ,   Federal State Budgetary Educational Institution of Higher Education “RGAU — MSHA named after K. A. Timiryazev”, Moscow, Kostina R. V. ,   Federal State Budgetary Educational Institution of Higher Education “RGAU — MSHA named after K. A. Timiryazev”, Moscow, Romanova A. A. ,   Federal State Budgetary Educational Institution of Higher Education “RGAU — MSHA named after K. A. Timiryazev”, Moscow, Myrksina Yu. A. ,   Federal State Budgetary Educational Institution of Higher Education “RGAU — MSHA named after K. A. Timiryazev”, Moscow
Published: May 2022

The article analyzes the main aspects of the problem and promising approaches to accounting for income and expenses when determining the object of taxation for agricultural producers under a special tax regime; the main differences in the accounting of income and expenses in determining the object of taxation for agricultural producers and for accounting purposes are studied and the main correspondence of accounting accounts on the reflection of income and expenses in the conditions of the domestic agro-industrial complex, in particular for agricultural producers using a special tax regime, is proposed.