bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Ions Contained in Concrete Pore Solutions on Natural Zeolites
Authors: Czapik Przemysław
Published: February 2023

This article investigates the relationships between different chemical compositions of simulated cement concrete pore solutions and changes on the surface of zeolite rock with potassium clinoptilolite as its main component. The changes were studied using X-ray diffraction (XRD), thermal analysis (DTA-TG) and scanning electron microscopy (SEM). Zeolite powder samples and a ground section of 16–64 mm grain were tested. The simulated pore solutions were based on Ca, Na, K hydroxides and K2SO4. It was found that 100% of Ca(OH)2 in the systems could react between 7 and 180 days of hydration due to pozzolanic and side reactions. As the degree of clinoptilolite conversion increased, it became more difficult to detect it in X-ray patterns. At the same time, various microstructural changes could be observed. As a result of the reactions that occurred, hydrated calcium silicates, sulfate and carbonate compounds were formed. Potassium hydroxide had a more substantial effect on clinoptilolite reactivity than sodium hydroxide. This effect can be enhanced by the presence of SO23− ions in the solution.
Co-Pyrolysis of Unsaturated C4 and Saturated C6+ Hydrocarbons—An Experimental Study to Evaluate Steam-Cracking Performance
Authors: Petrů Jiří , Herink Tomáš , Patera Jan , Zámostný Petr
Published: February 2023

Unsaturated C4 hydrocarbons are abundant in various petrochemical streams. They can be considered as a potential feedstock for the steam-cracking process, where they must be co-processed with C6 and higher (C6+) hydrocarbons of primary naphtha fractions. Co-pyrolysis experiments aiming at the comparison of different C4 hydrocarbon performances were carried out in a laboratory micro-pyrolysis reactor under standardized conditions: 820 °C, 400 kPa, and 0.2 s residence time in the reaction zone. C4 hydrocarbons were co-pyrolyzed with different co-pyrolysis partners containing longer hydrocarbon chain to study the influence of the co-pyrolysis partner structure on the behavior of C4 hydrocarbons. The yields of the pyrolysis products and the conversion of C4 hydrocarbons were used as the performance factors. A regression model was developed and used as a valuable tool for quantifying the inhibition or acceleration effect of co-pyrolysis on the conversion of co-pyrolyzed hydrocarbons. It was found that the performance of different C4 hydrocarbons in co-pyrolysis is substantially different from the separate pyrolysis of the individual components.
Dynamic Diagnostic Tests and Numerical Analysis of the Foundations for Turbine Sets
Authors: Szolomicki Jerzy , Dmochowski Grzegorz , Roskosz Maciej
Published: February 2023

This paper shows current trends in testing and numerical analysis of dynamic loading in relation to a real frame foundation for a turbogenerator set. The analysis of the machine’s foundations, which are subjected to static and dynamic loads, is a complex problem combining the issues of geotechnics, structural engineering, and vibration theory. The authors present a case study of the assessment of the foundation’s technical condition. The main objective of this study is to perform and compare experimental and numerical dynamic analysis which includes the measurement of the acceleration, speed, and amplitude of the natural vibrations of the foundation during the operational speed of the turbogenerator. In addition, auxiliary material tests were carried out to fully diagnose the foundation and obtain the material properties required for the numerical analysis. They included both destructive and non-destructive of concrete strength, the evaluation of the degree of its carbonation, and the scanning of the reinforcement distribution. The research presented in the paper is intended to facilitate the preparation of appropriate data for the design of the foundation renovation and strengthening.
Early Wildfire Smoke Detection Using Different YOLO Models
Authors: Al-Smadi Yazan , Alauthman Mohammad , Al-Qerem Ahmad , Aldweesh Amjad , Quaddoura Ruzayn , Aburub Faisal , Mansour Khalid , Alhmiedat Tareq
Published: February 2023

Forest fires are a serious ecological concern, and smoke is an early warning indicator. Early smoke images barely capture a tiny portion of the total smoke. Because of the irregular nature of smoke’s dispersion and the dynamic nature of the surrounding environment, smoke identification is complicated by minor pixel-based traits. This study presents a new framework that decreases the sensitivity of various YOLO detection models. Additionally, we compare the detection performance and speed of different YOLO models such as YOLOv3, YOLOv5, and YOLOv7 with prior ones such as Fast R-CNN and Faster R-CNN. Moreover, we follow the use of a collected dataset that describes three distinct detection areas, namely close, medium, and far distance, to identify the detection model’s ability to recognize smoke targets correctly. Our model outperforms the gold-standard detection method on a multi-oriented dataset for detecting forest smoke by an mAP accuracy of 96.8% at an IoU of 0.5 using YOLOv5x. Additionally, the findings of the study show an extensive improvement in detection accuracy using several data-augmentation techniques. Moreover, YOLOv7 outperforms YOLOv3 with an mAP accuracy of 95%, compared to 94.8% using an SGD optimizer. Extensive research shows that the suggested method achieves significantly better results than the most advanced object-detection algorithms when used on smoke datasets from wildfires, while maintaining a satisfactory performance level in challenging environmental conditions.
An Autonomous Maze-Solving Robotic System Based on an Enhanced Wall-Follower Approach
Authors: Alamri Shatha , Alamri Hadeel , Alshehri Wejdan , Alshehri Shuruq , Alaklabi Ahad , Alhmiedat Tareq
Published: February 2023

Autonomous robots are designed to discover and interpret their surroundings and orient themselves around obstacles to reach the destination point from an initial point. Robot autonomous navigation is a requirement for maze-solving systems, where the solver robot is required to navigate the maze area to get its desire destination location using the fastest route possible. In this paper, a new, modified wall-follower system for a maze-solving robot was proposed that overcame the infinite loop-back issue in the traditional wall-follower approaches. We also investigated and analyzed the performance of three different maze-solving algorithms and compared them with the proposed, modified wall-follower robotic system by conducting several real experiments to validate the efficiency of the developed wall-follower robotic system.
Anisotropy-Based Adaptive Polynomial Chaos Method for Hybrid Uncertainty Quantification and Reliability-Based Design Optimization of Structural-Acoustic System
Authors: Yin Shengwen , Gao Yuan , Zhu Xiaohan , Wang Zhonggang
Published: February 2023

The evaluation of objective functions and component reliability in the optimisation of structural-acoustic systems with random and interval variables is computationally expensive, especially when strong nonlinearity exhibits between the response and input variables. To reduce the computational cost and improve the computational efficiency, a novel anisotropy-based adaptive polynomial chaos (ABAPC) expansion method was developed in this study. In ABAPC, the anisotropy-based polynomial chaos expansion, namely the retained order of polynomial chaos expansion (PCE) differs from each variable, is used to construct the initial surrogate model instead of first-order polynomial chaos expansion in conventional methods. Then, an anisotropy-based adaptive basis growth strategy was developed to reduce the estimation of the coefficients of the polynomial chaos expansion method and increase its computational efficiency. Finally, to solve problems with probabilistic and interval parameters, an adaptive basis truncation strategy was introduced and implemented. Using the ABAPC method, the computational cost of reliability-based design optimisation for structural-acoustic systems can be efficiently reduced. The effectiveness of the proposed method were demonstrated by solving two numerical examples and optimisation problems of a structural-acoustic system.
Variational Bayesian Network with Information Interpretability Filtering for Air Quality Forecasting
Authors: Jin Xue-Bo , Wang Zhong-Yao , Gong Wen-Tao , Kong Jian-Lei , Bai Yu-Ting , Su Ting-Li , Ma Hui-Jun , Chakrabarti Prasun
Published: February 2023

Air quality plays a vital role in people’s health, and air quality forecasting can assist in decision making for government planning and sustainable development. In contrast, it is challenging to multi-step forecast accurately due to its complex and nonlinear caused by both temporal and spatial dimensions. Deep models, with their ability to model strong nonlinearities, have become the primary methods for air quality forecasting. However, because of the lack of mechanism-based analysis, uninterpretability forecasting makes decisions risky, especially when the government makes decisions. This paper proposes an interpretable variational Bayesian deep learning model with information self-screening for PM2.5 forecasting. Firstly, based on factors related to PM2.5 concentration, e.g., temperature, humidity, wind speed, spatial distribution, etc., an interpretable multivariate data screening structure for PM2.5 forecasting was established to catch as much helpful information as possible. Secondly, the self-screening layer was implanted in the deep learning network to optimize the selection of input variables. Further, following implantation of the screening layer, a variational Bayesian gated recurrent unit (GRU) network was constructed to overcome the complex distribution of PM2.5 and achieve accurate multi-step forecasting. The high accuracy of the proposed method is verified by PM2.5 data in Beijing, China, which provides an effective way, with multiple factors for PM2.5 forecasting determined using deep learning technology.
Rockburst Intensity Classification Prediction Based on Multi-Model Ensemble Learning Algorithms
Authors: Wang Jiachuang , Ma Haoji , Yan Xianhang
Published: February 2023

Rockburst is a common and huge hazard in underground engineering, and the scientific prediction of rockburst disasters can reduce the risks caused by rockburst. At present, developing an accurate and reliable rockburst risk prediction model remains a great challenge due to the difficulty of integrating fusion algorithms to complement each other’s strengths. In order to effectively predict rockburst risk, firstly, 410 sets of valid rockburst data were collected as the original data set in this paper, which was used to process these rockburst cases by the SMOTE oversampling method. Then, four integrated algorithms and eight basic algorithms were selected, which were optimized by hyperparameters and five-fold cross-validation and combined with the random search grid method, thus improving the classification performance of these algorithms. Third, the stacking integration algorithm, which was combined with the principles of various machine learning algorithms and the characteristics of the rockburst cases, integrated the optimization of rockburst algorithms with reference to four combinatorial strategies. Further, we adopted the voting integration algorithm, chose multiple combination schemes, and referred to the weighted fusion of accuracy, F1 score, recall, precision, and cv-mean as the weight values, and the optimal model for rockburst risk prediction was obtained. Finally, using the 35 generated stacking integration algorithms and 18 voting integration algorithms, the optimal model in the fusion strategy was selected and the traditional integration algorithm model was analyzed on the basis of different sample combinations of the models. The results showed that the prediction performance of stacking and voting integration algorithms was mostly better than the ordinary machine-learning performance, and the selection of appropriate fusion strategies could effectively improve the performance of rockburst prediction for ensemble learning algorithms.
Train Delay Predictions Using Markov Chains Based on Process Time Deviations and Elastic State Boundaries
Authors: Spanninger Thomas , Büchel Beda , Corman Francesco
Published: February 2023

Train delays are inconvenient for passengers and major problems in railway operations. When delays occur, it is vital to provide timely information to passengers regarding delays at their departing, interchanging, and final stations. Furthermore, real-time traffic control requires information on how delays propagate throughout the network. Among a multitude of applied models to predict train delays, Markov chains have proven to be stochastic benchmark approaches due to their simplicity, interpretability, and solid performances. In this study, we introduce an advanced Markov chain setting to predict train delays using historical train operation data. Therefore, we applied Markov chains based on process time deviations instead of absolute delays and we relaxed commonly used stationarity assumptions for transition probabilities in terms of direction, train line, and location. Additionally, we defined the state space elastically and analyzed the benefit of an increasing state space dimension. We show (via a test case in the Swiss railway network) that our proposed advanced Markov chain model achieves a prediction accuracy gain of 56% in terms of mean absolute error (MAE) compared to state-of-the-art Markov chain models based on absolute delays. We also illustrate the prediction performance advantages of our proposed model in the case of training data sparsity.
Compression Reconstruction Network with Coordinated Self-Attention and Adaptive Gaussian Filtering Module
Authors: Wei Zhen , Yan Qiurong , Lu Xiaoqiang , Zheng Yongjian , Sun Shida , Lin Jian
Published: February 2023

Although compressed sensing theory has many advantages in image reconstruction, its reconstruction and sampling time is very long. Fast reconstruction of high-quality images at low measurement rates is the direction of the effort. Compressed sensing based on deep learning provides an effective solution for this. In this study, we propose an attention-based compression reconstruction mechanism (ACRM). The coordinated self-attention module (CSAM) is designed to be embedded in the main network consisting of convolutional blocks and utilizes the global space and channels to focus on key information and ignore irrelevant information. An adaptive Gaussian filter is proposed to solve the loss of multi-frequency components caused by global average pooling in the CSAM, effectively supplementing the network with different frequency information at different measurement rates. Finally, inspired by the basic idea of the attention mechanism, an improved loss function with attention mechanism (AMLoss) is proposed. Extensive experiments show that the ACRM outperforms most compression reconstruction algorithms at low measurement rates.
EJS: Multi-Strategy Enhanced Jellyfish Search Algorithm for Engineering Applications
Authors: Hu Gang , Wang Jiao , Li Min , Hussien Abdelazim G. , Abbas Muhammad
Published: February 2023

The jellyfish search (JS) algorithm impersonates the foraging behavior of jellyfish in the ocean. It is a newly developed metaheuristic algorithm that solves complex and real-world optimization problems. The global exploration capability and robustness of the JS algorithm are strong, but the JS algorithm still has significant development space for solving complex optimization problems with high dimensions and multiple local optima. Therefore, in this study, an enhanced jellyfish search (EJS) algorithm is developed, and three improvements are made: (i) By adding a sine and cosine learning factors strategy, the jellyfish can learn from both random individuals and the best individual during Type B motion in the swarm to enhance optimization capability and accelerate convergence speed. (ii) By adding a local escape operator, the algorithm can skip the trap of local optimization, and thereby, can enhance the exploitation ability of the JS algorithm. (iii) By applying an opposition-based learning and quasi-opposition learning strategy, the population distribution is increased, strengthened, and more diversified, and better individuals are selected from the present and the new opposition solution to participate in the next iteration, which can enhance the solution’s quality, meanwhile, convergence speed is faster and the algorithm’s precision is increased. In addition, the performance of the developed EJS algorithm was compared with those of the incomplete improved algorithms, and some previously outstanding and advanced methods were evaluated on the CEC2019 test set as well as six examples of real engineering cases. The results demonstrate that the EJS algorithm can skip the trap of local optimization, can enhance the solution’s quality, and can increase the calculation speed. In addition, the practical engineering applications of the EJS algorithm also verify its superiority and effectiveness in solving both constrained and unconstrained optimization problems, and therefore, suggests future possible applications for solving such optimization problems.
Quantile Regression in Space-Time Varying Coefficient Model of Upper Respiratory Tract Infections Data
Authors: Tantular Bertho , Ruchjana Budi Nurani , Andriyana Yudhie , Verhasselt Anneleen
Published: February 2023

Space-time varying coefficient models, which are used to identify the effects of covariates that change over time and spatial location, have been widely studied in recent years. One such model, called the quantile regression model, is particularly useful when dealing with outliers or non-standard conditional distributions in the data. However, when the functions of the covariates are not easily specified in a parametric manner, a nonparametric regression technique is often employed. One such technique is the use of B-splines, a nonparametric approach used to estimate the parameters of the unspecified functions in the model. B-splines smoothing has potential to overfit when the number of knots is increased, and thus, a penalty is added to the quantile objective function known as P-splines. The estimation procedure involves minimizing the quantile loss function using an LP-Problem technique. This method was applied to upper respiratory tract infection data in the city of Bandung, Indonesia, which were measured monthly across 30 districts. The results of the study indicate that there are differences in the effect of covariates between quantile levels for both space and time coefficients. The quantile curve estimates also demonstrate robustness with respect to outliers. However, the simultaneous estimation of the quantile curves produced estimates that were relatively close to one another, meaning that some quantile curves did not depict the actual data pattern as precisely. This suggests that each district in Bandung City not only has different categories of incidence rates but also has a heterogeneous incidence rate based on three quantile levels, due to the difference in the effects of covariates over time and space.
A Comprehensive Study of the Complex mKdV Equation through the Singular Manifold Method
Authors: Albares Paz , Estévez Pilar G.
Published: February 2023

In this paper, we introduce a modification of the Singular Manifold Method in order to derive the associated spectral problem for a generalization of the complex version of the modified Korteweg–de Vries equation. This modification yields the right Lax pair and allows us to implement binary Darboux transformations, which can be used to construct an iterative method to obtain exact solutions.
How Tourists’ Perceived Risk Affects Behavioral Intention through Crisis Communication in the Post-COVID-19 Era
Authors: Chen Shui-Lien , Hsu Hsiang-Ting , Chinomona Richard
Published: February 2023

In the post-COVID-19 era, with tourism activity beginning to revitalize, the behavioral intention of tourists has emerged as the focus of much research interest. While previous studies have suggested that tourists’ perceived risk affects behavioral intention, it has not been found that perceived risk is influenced by other factors that affect behavioral intention in the post-COVID-19 era. This study constructs a research model to understand how tourists’ perceived risk influences emotional attachment to destinations and tourists’ behavioral intention through crisis communication and NPI. Through face-to-face interviews, this study conducted a survey and collected data from 1047 tourists who visited Dadaocheng’s renowned Chinese herbal street in Taiwan and examined the causal relationships through structural equation modeling. The results indicated that an increase in perceived risk had a positive effect on crisis communication and NPI and affected tourists’ behavioral intentions through emotional attachment to the destination. This study provides an opportunity to establish an essential contribution to post-disaster crisis management, which may serve as a marketing reference for tourism operators in the post-COVID-19 era, as well as to address future pandemic challenges.
Identifying Combination of Dark–Bright Binary–Soliton and Binary–Periodic Waves for a New Two-Mode Model Derived from the (2 + 1)-Dimensional Nizhnik–Novikov–Veselov Equation
Authors: Alquran Marwan , Jaradat Imad
Published: February 2023

In this paper, we construct a new two-mode model derived from the (2+1)-dimensional Nizhnik–Novikov–Veselov (TMNNV) equation. We generalize the concept of Korsunsky to accommodate the derivation of higher-dimensional two-mode equations. Since the TMNNV is presented here, for the first time, we identify some of its solutions by means of two recent and effective schemes. As a result, the Kudryashov-expansion method exports a combination of bright–dark binary solitons, which simulate many applications in optics, photons, and plasma. The modified rational sine and cosine functions export binary–periodic waves that arise in the field of surface water waves. Moreover, by using 2D and 3D graphs, some physical properties of the TMNNV were investigated by means of studying the effect of the following parameters of the model: nonlinearity, dispersion, and phase–velocity. Finally, we checked the validity of the obtained solutions by verifying the correctness of the original governing model.
A Placebo-Controlled Trial to Evaluate Two Locally Delivered Antibiotic Gels (Piperacillin Plus Tazobactam vs. Doxycycline) in Stage III–IV Periodontitis Patients
Authors: Ilyes Ioana , Rusu Darian , Rădulescu Viorelia , Vela Octavia , Boariu Marius Ion , Roman Alexandra , Surlin Petra , Kardaras Giorgios , Boia Simina , Chinnici Salvatore , Jentsch Holger Friedrich Rudolf , Stratul Stefan-Ioan
Published: February 2023

Background and objectives: this study aims to evaluate the clinical and microbiological effects of a single subgingival administration of a locally delivered antibiotic gel containing piperacillin plus tazobactam and compare it with a slow-release doxycycline (14%) gel and a placebo gel, following subgingival instrumentation (SI) in patients with severe periodontitis. Materials and methods: sixty-four patients diagnosed with stage III–IV periodontitis were enrolled, were randomly assigned into three groups, and were treated additionally with a single subgingival administration of piperacillin plus tazobactam gel (group A); doxycycline gel (group B); and placebo gel (group C). The primary outcome variable was the change in mean probing pocket depth (PPD) 6 months after the intervention. Secondary outcome variables were changes in mean full-mouth bleeding score (FMBS); full-mouth plaque score (FMPS); overall bleeding index (BOP); pocket closure; and clinical attachment level (CAL), along with changes in the numbers of five keystone bacteria: Aggregatibacter actinomycetemcomitans (A.a.), Porphyromonas gingivalis (P.g.), Prevotella intermedia (P.i.), Tannerella forsythia (T.f.), and Treponema denticola (T.d.). Intergroup and intragroup differences were evaluated at 3 and 6 months. Results: at baseline, the three groups were comparable. An improvement in clinical parameters such as PPD, CAL, and BOP between groups was observed at 3 and 6 months, but without statistical significance (p > 0.05). At 6 months, the intragroup analysis showed a significant reduction in clinical parameters. Even though the piperacillin plus tazobactam group showed slightly higher PPD reduction, this was not statistically significant when compared to both control groups. Conclusions: The groups had similar results, and subgingival instrumentation can be executed without adjunctive antimicrobials, reducing the costs for the patient and the working time/load of the professional.
Surgical Treatment for Advanced Oropharyngeal Cancer: A Narrative Review
Authors: Maniaci Antonino , Hao Sheng-Po , Cancemi Francesco , Giardini Damiano , Checcoli Emanuele , Soprani Francesco , Iannella Giannicola , Vicini Claudio , Cocuzza Salvatore , La Mantia Ignazio , Fakhry Nicolas , De Vito Andrea
Published: February 2023

Background and Objectives: to describe current scientific knowledge regarding the treatment options in advanced oropharyngeal cancer. The standard care for advanced oropharyngeal cancer (OPSCC) has been chemoradiotherapy, although surgical approaches followed by adjuvant treatment have been proposed. The best therapy for each patient should be decided by an interdisciplinary tumour-board. Different strategies should be considered for the specific patient’s treatment: surgery, chemotherapy and radiation therapy or combinations of them. The treatment choice is influenced by tumour variability and prognostic factors, but it also depends on cancer extension, extranodal extension, nervous invasion, human papilloma virus (HPV) presence, making the decisional algorithm not always clear. HPV-related OPSCC is strongly associated with a favourable overall survival (OS) and disease-free survival rate (DSS); by contrast, HPV-negative OPSCC often flags a worse prognosis. Consequently, the American Joint Committee on Cancer (AJCC) differentiates OPSCC treatment and prognosis based on HPV status. Methods: we carried out a review of current scientific literature to analyze the different indications and limitations of surgical treatment options in OPSCC stage III and IV. Conclusion: robotic surgery or open approaches with reconstructive flaps can be considered in advanced stages, resulting in the de-intensification of subsequent systemic therapy and fewer related side effects. Furthermore, in the event of the primary failure of systemic therapy or disease recurrence, the surgical approach constitutes an additional therapeutic option which lengthens patient survival functions.
Morphopathogenesis of Adult Acquired Cholesteatoma
Authors: Dambergs Kristaps , Sumeraga Gunta , Pilmane Māra
Published: February 2023

Background and Objectives. The aim of this study was to compare the distribution of proliferation markers (Ki-67, NF-κβ), tissue-remodeling factors (MMP-2, MMP-9, TIMP-2, TIMP-4), vascular endothelial growth factor (VEGF), interleukins (IL-1 and IL-10), human beta defensins (HβD-2 and HβD-4) and Sonic hedgehog gene protein in cholesteatoma and control skin. Methods. Nineteen patient cholesteatoma tissues and seven control skin materials from cadavers were included in the study and stained immunohistochemically. Results. Statistically discernible differences were found between the following: the Ki-67 in the matrix and the Ki-67 in the skin epithelium (p = 0.000); the Ki-67 in the perimatrix and the Ki-67 in the connective tissue (p = 0.010); the NF-κβ in the cholesteatoma matrix and the NF-κβ in the epithelium (p = 0.001); the MMP-9 in the matrix and the MMP-9 in the epithelium (p = 0.008); the HβD-2 in the perimatrix and the HβD-2 in the connective tissue (p = 0.004); and the Shh in the cholesteatoma’s perimatrix and the Shh in the skin’s connective tissue (p = 0.000). Conclusion. The elevation of Ki-67 and NF-κβ suggests the induction of cellular proliferation in the cholesteatoma. Intercorrelations between VEGF, NF-κβ and TIMP-2 induce neo-angiogenesis in adult cholesteatoma. The similarity in the expression of IL-1 and IL-10 suggests the dysregulation of the local immune status in cholesteatoma. The overexpression of the Sonic hedgehog gene protein in the cholesteatoma proves the selective local stimulation of perimatrix development.
Distributions of Platelet-Derived Growth Factor Receptor-α Positive Cells and Interstitial Cells of Cajal in the Colon of Rats with Diabetes Mellitus Type 2
Authors: Veličkov Aleksandra Ivana , Djordjević Branka , Lazarević Milica , Veličkov Asen Veselin , Petrović Vladimir , Jović Marko , Denčić Tijana , Radenković Goran
Published: February 2023

Background and Objectives: Diabetic gastroenteropathy (DG) is a common complication of diabetes mellitus type 2. Interstitial cells are non-neural cells of mesenchymal origin inserted between nerve elements and smooth muscle cells, necessary for normal function and peristaltic contractions in the gastrointestinal (GI) tract. There are at least two types of interstitial cells within the GI muscle layer—interstitial cells of Cajal (ICC) and interstitial platelet-derived growth factor receptor α-positive cells (IPC). The mechanism of diabetic gastroenteropathy is unclear, and interstitial cells disorders caused by metabolic changes in diabetes mellitus (DM) could explain the symptoms of DG (slow intestinal transit, constipation, fecal incontinence). The aim of this study was to identify PDGFRα and c-kit immunoreactive cells in the colon of rats with streptozotocin–nicotinamide-induced diabetes mellitus type 2, as well as to determine their distribution in relation to smooth muscle cells and enteric nerve structures. Materials and Methods: Male Wistar rats were used, and diabetes type 2 was induced by an intraperitoneal injection of streptozotocin, immediately after intraperitoneal application of nicotinamide. The colon specimens were exposed to PDGFRα and anti-c-kit antibodies to investigate interstitial cells; enteric neurons and smooth muscle cells were immunohistochemically labeled with NF-M and desmin antibodies. Results: Significant loss of the intramuscular ICC, myenteric ICC, and loss of their connection in intramuscular linear arrays and around the ganglion of the myenteric plexus were observed with no changes in nerve fiber distribution in the colon of rats with diabetes mellitus type 2. IPC were rarely present within the colon muscle layer with densely distributed PDGFRα+ cells in the colon mucosa and submucosa of both experimental groups. In summary, a decrease in intramuscular ICC, discontinuities and breakdown of contacts between myenteric ICC without changes in IPC and nerve fibers distribution were observed in the colon of streptozotocin/nicotinamide-induced diabetes type 2 rats.
Diaphragmatic Activation Correlated with Lumbar Multifidus Muscles and Thoracolumbar Fascia by B-Mode and M-Mode Ultrasonography in Subjects with and without Non-Specific Low Back Pain: A Pilot Study
Authors: Perez Alicia Martin , Fernández-Carnero Samuel , Sicilia-Gomez-de-Parada Cristina , Cuenca-Zaldívar Nicolas , Naranjo-Cinto Fermin , Pecos-Martín Daniel , Gallego-Izquierdo Tomás , Nuñez-Nagy Susana
Published: February 2023

Background and Objectives: The diaphragm, the lumbar multifidus muscles, and the thoracolumbar fascia (TLF) execute an important role in the stability of the lumbar spine and their morphology has been modified in subjects with non-specific low back pain (NS-LBP). While it is true that three structures correlate anatomically, the possible functional correlation between them has not been investigated previously in healthy subjects nor in subjects with NS-LBP. The aim of the present study was to examine this functional nexus by means of a comparison based on ultrasonographic parameters of the diaphragm, the lumbar multifidus muscles, and the TLF in subjects with and without NS-LBP. Materials and Methods: A sample of 54 (23 NS-LBP and 31 healthy) subjects were included in the study. The thickness and diaphragmatic excursion at tidal volume (TV) and force volume (FV), the lumbar multifidus muscles thickness at contraction and at rest, and the TLF thickness were evaluated using rehabilitative ultrasound imaging (RUSI) by B-mode and M-mode ultrasonography. The diaphragm thickening capacity was also calculated by thickening fraction (TF) at tidal volume and force volume. Results: There were no significant differences recorded between the activation of the diaphragm and the activation of the lumbar multifidus muscles and TLF for each variable, within both groups. However, there were significant differences recorded between both groups in diaphragm thickness and diaphragm thickening capacity at tidal volume and force volume. Conclusions: Diaphragmatic activation had no functional correlation with the activation of lumbar multifidus muscles and TLF for both groups. Nevertheless, subjects with NS-LBP showed a reduced diaphragm thickness and a lower diaphragm thickening capacity at tidal volume and force volume, compared to healthy subjects.
Broadband Flexible Microstrip Antenna Array with Conformal Load-Bearing Structure
Authors: Tang Can , Zheng Hongxing , Li Ziwei , Zhang Kanglong , Wang Mengjun , Fan Chao , Li Erping
Published: February 2023

To enhance the load-bearing mechanical properties and broadband electromagnetic characteristics of the conformal antenna, a broadband microstrip antenna array with a conformal load-bearing structure is proposed in this paper, which consists of three flexible substrate layers and two honeycomb core layers stacked on each other. By combining the antenna and honeycomb core layer in a structural perspective, the antenna array is implemented in the composition function of surface conformability and load-bearing. Additionally, the sidelobe level of the antenna is suppressed based on the reflection surface loaded. Meanwhile, an equivalent model of a honeycomb core layer has been established and applied in the design of a conformal antenna with a load-bearing structure. The presented model increases the accuracy of simulated results and reduces the memory consumption and time of the simulation. The overall size of the proposed antenna array is 32.84 × 36.65 × 4.9 mm (1.36 λ0 × 1.52 λ0 × 0.2 λ0, λ0 is the wavelength at 12.5 GHz). The proposed antenna element and array have been fabricated and measured in the flat state and under other various bending states. Experiment results show the operating relative bandwidth of the antenna array is 20.68% (11.67–13.76 GHz and 14.33–14,83 GHz) in the flat state. Under different bending conditions, the proposed antenna array covers 24.16% (11.08–14.1 GHz), 23.82% (10.63–13.5 GHz), and 23.12% with 30°, 60°, and 90° in the xoz plane (11.55–14.33 GHz). In terms of mechanical load bearing, the structure has better performance than the traditional single-layer honeycomb core load-bearing structure antenna.
The Conjusome—A Transient Organelle Linking Genome Rearrangements in the Parental and Developing Macronuclei
Authors: Janetopoulos Christopher , Aufderheide Karl J.
Published: February 2023

The conjusome plays an important role in the conjugation events that occur in Tetrahymena thermophila. The conjusome appears in the anterior of conjugant pairs during the early stages of new macronuclei (anlagen) development. It lacks a membrane, and is composed of a network of fibrous, electron dense material, containing background cytoplasm and ribosomes. Several proteins localize to this organelle, including Pdd1p, a chromodomain protein that participates in the formation of chromatin-containing structures in developing macronuclear anlagen, and is associated with the elimination of specific germ-line sequences from developing macronuclei. Conjugants lacking the PDD1 allele in the parental macronucleus do not show Pdd1p antibody staining in conjusomes. Investigations were performed using mutant cell lines, uniparental cytogamy and drug treatment, and show that the conjusome appears to be dependent on parental macronuclei condensation, and is a transitory organelle that traffics nuclear determinants from the parental macronucleus to the developing anlagen. These data, taken together with Pdd1p knockout experiments, suggest the conjusome is involved in the epigenetic phenomena that occur during conjugation and sexual reorganization. This is likely a conserved organelle. Conjusome-like structures were also observed in another Ciliate, Stylonichia. In general, conjusomes have features that resemble germ line P-granules.
The Impact of Earthquakes on Public Health: A Narrative Review of Infectious Diseases in the Post-Disaster Period Aiming to Disaster Risk Reduction
Authors: Mavrouli Maria , Mavroulis Spyridon , Lekkas Efthymios , Tsakris Athanassios
Published: February 2023

Earthquakes are among the most impressive natural phenomena with very high potential to set off a chain of effects that significantly affects public health through casualties and injuries. Related disasters are attributed not only to the strong ground motion and coseismic phenomena but also to secondary effects, comprising mainly landslides and tsunamis, among others. All these can create harsh conditions favorable for the emergence of infectious diseases that are capable of causing additional human and economic losses and disruption of the emergency and recovery process. The present study comprises an extensive narrative review of the existing literature on the earthquake-triggered infectious diseases recorded worldwide, along with their symptoms, causative pathogens, associated risk factors, most vulnerable population groups, and prevention strategies. Respiratory, gastrointestinal, and vector-borne diseases, as well as wound and skin infections, are mainly recorded among the earthquake-affected population. Measures for effectively preventing earthquake-triggered infectious diseases are also proposed. One of the widely proposed measures is the establishment of a proper disease surveillance system in order to immediately and effectively identify the pre- and post-disaster occurrence of infectious diseases. This approach significantly contributes to disease trends monitoring, validation of early warning, and support of the emergency response and recovery actions.
Microbial Dynamics in Mixed-Culture Biofilms of Salmonella Typhimurium and Escherichia coli O157:H7 and Bacteria Surviving Sanitation of Conveyor Belts of Meat Processing Plants
Authors: Yang Xianqin , Wang Hui , Hrycauk Scott , Holman Devin B. , Ells Tim C.
Published: February 2023

Biofilm formation can lead to the persistence of Salmonella Typhimurium (ST) and E. coli O157:H7 (O157). This study investigated the impact of meat processing surface bacteria (MPB) on biofilm formation by O157 (non-biofilm former; NF) and ST (strong biofilm former; BF). MPB were recovered from the contacting surfaces (CS), non-contacting surfaces (NCS), and roller surfaces (RS) of a beef plant conveyor belt after sanitation. O157 and ST were co-inoculated with MPB (CO), or after a delay of 48 h (IS), into biofilm reactors containing stainless steel coupons and incubated at 15 °C for up to 144 h. Coupons were withdrawn at various intervals and analyzed by conventional plating and 16S rRNA gene amplicon sequencing. The total bacterial counts in biofilms reached approximately 6.5 log CFU/cm2, regardless of MPB type or development mode. The mean counts for O157 and ST under equivalent conditions mostly did not differ (p > 0.05), except for the IS set at 50 h, where no O157 was recovered. O157 and ST were 1.6 ± 2.1% and 4.7 ± 5.0% (CO) and 1.1 ± 2.2% and 2.0 ± 2.8% (IS) of the final population. Pseudomonas dominated the MPB inocula and biofilms, regardless of MPB type or development mode. Whether or not a pathogen is deemed BF or NF in monoculture, its successful integration into complex multi-species biofilms ultimately depends on the presence of certain other residents within the biofilm.
Implementation of Biopolymeric Nanomaterials to Reduce the Negative Impacts of Salinity on Tomato Quantity and Quality
Authors: Ahmed Shreen S. , Khan Thana K. , Abd El-Aziz Gehan H. , Shoala Tahsin , El-Garhy Hoda A. S. , Fahmy Ashraf H.
Published: February 2023

Sustainable waste reduction strategies and innovative waste reduction concepts, as well as their application in the creation of compounds and products with added value, can benefit the economy while reducing environmental pressures. This research aimed to use biopolymeric nanomaterials to reduce the negative effects of salinity on tomato yield and quality. Three types of biopolymers (cellulose, pectin, and starch) were synthesized and characterized using natural materials such as rice straw, orange peel, and potato peel. The polymer’s ability to retain sodium ions was investigated. A greenhouse experiment was conducted to assess the potential of natural polymers (cellulose, starch, and pectin individually or in combination) to reduce the salinity side effects on tomato plants (Solanum Lycopersicon L.) cultivar (Super Strain B). Tomato seeds were germinated on soil bits for 20 days before planting five seedlings in each pot (20 cm diameter) with three replicates and filling each pot with sandy loam soil, with or without natural polymers at a rate of 2 g/Kg. The results revealed that all the polymers utilized had a superlative capability to hold sodium ions for both soluble and exchanged sodium. The use of various natural polymer hydrogels increased the number and fresh weight of tomato fruits. Data showed that using biopolymers hydrogels reduced salinity stress by rising the content of phenol, flavonoid, and antioxidant enzymes such as catalase and peroxidase. The use of natural biopolymers significantly improved total soluble solids, pH, and juice substance. Implementing biopolymeric materials could reduce environmental pressures while increasing farm income. Innovative waste reduction strategies, such as the creation of value-added products, will benefit the economy, and this work is a good start in that direction.
Qualitative Analysis of Visible Foreign Solids in Armillarisin A Injection Formulations Using Ultra-High Performance Liquid Chromatography–Tandem Mass Spectrometry
Authors: Wang Ruiqi , Zhou Haichang , Liao Shiyu , Tian Qi , Lv Zhengbing , Bao Kangde , Liu Lili
Published: February 2023

During the trial production of Armillarisin A for injection (AA-I), unidentified needle-like yellow-brown crystals were occasionally observed. Here, we report an ultra-high performance liquid chromatography–tandem mass spectrometry (UPLC-MS) method for determining the source of the visible foreign bodies in the formulations of Armillarisin A active pharmaceutical ingredient (AA-API). AA-API, photolyzed samples, the intermediate polymer, and the excipient analyzed determined after the separation on a Waters Symmetry C18 (3.5 μm, 4.6 × 75 mm) column with a mobile phase consisting of a methanol/acetic acid (0.1 mol/L) aqueous solution (50:50). Furthermore, the crystal type of the visible foreign bodies, the intermediate polymer and AA-API were investigated by X-ray powder diffraction (XRD). The results revealed that the characteristics of the visible foreign solids were the same as those of AA-API as regards UPLC peak position (368 nm) and MS spectrum in negative ion detection mode. The visible foreign solids were thus identified as unpolymerized crystals of AA-API and were attributed to AA-API itself. The results showed that the production process could be improved by changing the stirring method and frequency as well as by optimizing the polymerization temperature to ensure the safety, stability, and control of the product quality in the stage of batch production.
Beer and Microbiota: Pathways for a Positive and Healthy Interaction
Authors: Zugravu Corina-Aurelia , Medar Cosmin , Manolescu Loredana , Constantin Ciprian
Published: February 2023

Beer is one of the most consumed drinks worldwide. It contains numerous categories of antioxidants, phenolic products, traces of group B vitamins, minerals (selenium, silicon, potassium), soluble fibers and microorganisms. Low or moderate beer consumption, with or without alcohol, showed positive effects on health by stimulating the development of a healthy microbiota. In the present review we focused on four components responsible with interaction with gut microbiota: microorganisms, polyphenols, fiber and melanoidins, their presence in usual beers and on perspectives of development of fortified beers with enhanced effects on gut microbiota. Though microorganisms rarely escape pasteurization of beer, there are new unpasteurized types that might bring strains with probiotic effects. The polyphenols from beer are active on the gut microbiota stimulating its development, with consequent local anti-inflammatory and antioxidant effects. Their degradation products have prebiotic action and may combat intestinal dysbiosis. Beer contains dietary fiber such as non-starchy, non-digestible carbohydrates (β-glucans, arabinoxylans, mannose, fructose polymers, etc.) that relate with gut microbiota through fermentation, serving as a nutrient substrate. Another type of substances that are often considered close to fiber because they have an extremely low digestibility, melanoidins (melanosaccharides), give beer antioxidant and antibacterial properties. Though there are not many research studies in this area, the conclusion of this review is that beer seems a good candidate for a future functional food and that there are many pathways by which its ingredients can influence in a positive manner the human gut microbiota. Of course, there are many technological hinderances to overcome. However, designing functional beers fortified with fiber, antioxidants and probiotics, with a very low or no alcoholic content, will counteract the negative perception of beer consumption, will nullify the negative effects of alcohol, while simultaneously exerting a positive action on the gut microbiota.
Determining Dietary Patterns to Recommend for Type 2 Diabetes: An Umbrella Review
Authors: Whiteley Cathryn , Benton Fiona , Matwiejczyk Louisa , Luscombe-Marsh Natalie
Published: February 2023

Some specific dietary patterns improve glycaemic levels and cardiovascular risk factors better than others. We aimed to identify the most effective dietary patterns using a food-focused approach to improve blood glucose management (primary outcome) and cardiovascular risk factors (secondary outcome) in people with type 2 diabetes. An umbrella review was conducted comparing dietary patterns for the management of these outcomes. Studies published between 2012 and 2022 were identified using PubMed Central, ProQuest, Web of Science, and the Cochrane Database of Systematic Reviews. Thirty systematic reviews met the inclusion criteria. Twenty-two of thirty reviews quantitated (via meta-analyses of over 212 randomised control trials) the effect size of different dietary patterns. Twelve reviews found Low-carbohydrate (LC), Mediterranean (M), Plant-based (PB), and/or Low-glycaemic Index (LGI) diets reduced HbA1c moderately more than control diets (typically a high-carbohydrate, low-fat diet) (i.e., LC: −0.1 to −0.5%; M: −0.3 to −0.5%; PB: −0.2 to −0.4%; LGI −0.2 to −0.5%; all p-value < 0.01). We conclude that Low-carbohydrate, Mediterranean, Plant-based, and Low-glycaemic Index dietary patterns are all clinically effective for people with type 2 diabetes as alternatives to high-carbohydrate, low-fat diets typically used for managing glycaemic levels and CVD risk. However, quality evidence about the sustainability of effects and safety remains limited, warranting future research.