bluuebunny/crossref_metadata_2025 huggingface dataset:
Sorghum-Based Power Generation in Southern Ukraine: Energy and Environmental Assessment
Authors: Havrysh Valerii , Nitsenko Vitalii , Hruban Vasyl
Published: December 2022

An increase in energy demand, fossil fuel reserves depletion, and environmental issues are primary reasons for renewable energy use, including power generation. Bioenergy is the primary alternative to conventional hydrocarbon fuels. Biomass-based power generation is increasing due to some reasons, including a gradual decrease in the levelized cost of electricity and a reduction of carbon dioxide emissions. Sorghum is a promising energy crop for semi-arid climate zones, including southern Ukraine. It can be used for both biofuel production and power generation. However, there is a lack of methodology for energy and environmental assessments of sorghum-based power generation. Some possible technologies were analyzed. The novelty of this study is the accounting of energy consumed and carbon dioxide emissions during crop cultivation. We have determined that sorghum-based power plants can generate from 2 to 12 MWh per hectare. Their operation significantly reduces carbon dioxide emissions (from 613 to 3652 kg of carbon dioxide per hectare of sorghum silage cultivation). Sorghum-based biogas plants have energy and environmental advantages if they use co-generation technologies and utilize digestate as a biofertilizer. The utilization of digestate (obtained from silage production per hectare) substitutes up to 12.8 MWh of indirect energy. The results obtained can be used by farmers and authorities for bioenergy development.
Tomato Disease Monitoring System Using Modular Extendable Mobile Robot for Greenhouses: Automatically Reporting Locations of Diseased Tomatoes
Authors: Ouyang Chen , Hatsugai Emiko , Shimizu Ikuko
Published: December 2022

Based on the appearance of tomatoes, it is possible to determine whether they are diseased. Detecting diseases early can help the yield losses of tomatoes through timely treatment. However, human visual inspection is expensive in terms of the time and labor required. This paper presents an automatic tomato disease monitoring system using modular and extendable mobile robot we developed in a greenhouse. Our system automatically monitors whether tomatoes are diseased and conveys the specific locations of diseased tomatoes to users based on the location information of the image data collected by the robot, such that users can adopt timely treatment. This system consists of two main parts: a modular, extendable mobile robot that we developed and a server that runs a tomato disease detection program. Our robot is designed to be configured and extended according to the actual height of the tomato vines, thus ensuring that the monitoring range covers most tomatoes. It runs autonomously between two rows of tomato plants and collects the image data. In addition to storing the image data of tomatoes, the data server runs a program for detecting diseases. This program contains a two-level disease detection model: a detection network for detecting diseased tomatoes and a validation network for verifying the detection results. The validation network verifies the results of the detection network by classifying the outputs of the detection network, thus reducing the false positive rate of the proposed system. Experimentally, this work focuses on the blossom-end rot of tomatoes. In this paper, YOLOv5, YOLOv7, Faster R-CNN, and RetinaNet are trained and compared on datasets divided by different conditions. YOLOv5l showed the best results on the randomly divided dataset: the mAP@0.5 reached 90.4%, and the recall reached 85.2%. Through the trained YOLOv5l, a dataset was created for training the classification networks: ResNet, MobileNet, and DenseNet. MobileNetv2 achieved the best overall performance with a 96.7% accuracy and a size of 8.8 MB. The final deployment to the system included YOLOv5l and MobileNetv2. When the confidence threshold of YOLOv5l was set to 0.1, the two-level model’s false positive and false negative rates were 13.3% and 15.2%, respectively. Compared to using YOLOv5l alone, the false positive rate decreased by 5.7% and the false negative rate increased by only 2.3%. The results of the actual operation of the proposed system reveal that the system can inform the user of the locations of diseased tomatoes with a low rate of false positives and false negatives, and that it is an effective and promotable approach.
Application of Molybdenum Nanofertilizer on the Nitrogen Use Efficiency, Growth and Yield in Green Beans
Authors: Muñoz-Márquez Ezequiel , Soto-Parra Juan Manuel , Noperi-Mosqueda Linda Citlalli , Sánchez Esteban
Published: December 2022

The increase in the cost of fertilizers and their low efficiency has led, through nanotechnology, to the generation of new innovative products that are sustainable and improve the productivity of crops. Therefore, the objective of the present study was to evaluate the efficacy of a molybdenum nanofertilizer compared to two conventional fertilizers (chelate and sodium molybdate) applied via foliar combined with soil fertilization of NH4NO3 in relation to the Nitrogen Use Efficiency, growth and yield in green bean cv. Strike. Green bean plants cv. Strike were cultivated under controlled conditions in an experimental greenhouse and irrigated with nutrient solution. The treatments consisted of the foliar application of three Mo sources (Nano fertilizer, Mo Chelate and Sodium Molybdate) in four doses 0, 5, 10 and 20 ppm Mo, complemented with the edaphic application of four doses of NH4NO3 (0, 3, 6 and 12 mM of N). The results obtained indicate that the highest accumulation of biomass and yield were obtained with the application of NanoMo, with increases in biomass of 24.31% and 36.47% more in yield with respect to Chelate and Molybdate. Finally, it is concluded that the application of NanoMo improves the assimilation and efficiency of nitrogen use, reducing excessive applications of nitrogenous fertilizers without affecting the yield of the green bean crop.
QPCTL Affects the Daily Weight Gain of the F2 Population and Regulates Myogenic Cell Proliferation and Differentiation in Chickens
Authors: Ren Tuanhui , Lin Wujian , Yang Xiuxian , Zhang Zihao , He Shizi , Li Wangyu , Li Zhuanjian , Zhang Xiquan
Published: December 2022

Molecular breeding can accelerate the process of animal breeding and improve the breeding efficiency. To date, many Indel molecular markers have been identified in livestock and poultry, but how Indels affect economic traits is not well understood. For molecular breeding, it is crucial to reveal the mechanism of action of Indels and to provide more accurate information. The purpose of this study was to investigate how the 52/224-bp multiallelic Indels of the chicken QPCTL promoter area affect the daily weight gain of chickens and the potential regulatory mechanism of the QPCTL gene. The analysis was conducted by association analysis, qPCR, dual-fluorescence assay and Western blotting. The results showed that Indels in the QPCTL promoter region were significantly associated with the daily weight gain in chickens and that QPCTL expression showed a decreasing trend in embryonic breast muscle tissues. Furthermore, QPCTL expression was significantly higher in breast muscle tissues of the AC genotype than in those of the AB and BB genotypes. Based on the transcriptional activity results, the pGL3-C vector produced more luciferase activity than pGL3-A and pGL3-B. In addition, overexpression of QPCTL promoted chicken primary myoblast (CPM) proliferation and inhibited differentiation. The results of this study suggest that Indels in the promoter region of the QPCTL gene may regulate the proliferation and differentiation of CPMs by affecting the expression of QPCTL, which ultimately affects the growth rate of chickens. These Indels have important value for the molecular breeding of chickens, and QPCTL can be used as a candidate gene to regulate and improve chicken growth and development.
Antimicrobial Efficacy against Antibiotic-Tolerant Staphylococcus aureus Depends on the Mechanism of Antibiotic Tolerance
Authors: Meredith Emily M. , Harven Lauren T. , Berti Andrew D.
Published: December 2022

Bacteria can adapt to a changing environment by adopting alternate metabolic states favoring small molecule synthesis and resilience over growth. In Staphylococcus aureus, these states are induced by factors present during infection, including nutritional limitations, host responses and competition with other bacteria. Isogenic “tolerant” populations have variable responses to antibiotics and can remain viable. In this study, we compared the capability of antibiotics to reduce the viability of S. aureus made tolerant by different mechanisms. Tolerance was induced with mupirocin, HQNO, peroxynitrite or human serum. Tolerant cultures were exposed to ceftaroline, daptomycin, gentamicin, levofloxacin, oritavancin or vancomycin at physiological concentrations, and the viability was assessed by dilution plating. The minimum duration for 3-log viability reduction and 24 h viability reduction were calculated independently for each of three biological replicates. Each tolerance mechanism rendered at least one antibiotic ineffective, and each antibiotic was rendered ineffective by at least one mechanism of tolerance. Further studies to evaluate additional antibiotics, combination therapy and different tolerance inducers are warranted.
Coastal Flooding Assessment Induced by Barometric Pressure, Wind-Generated Waves and Tidal-Induced Oscillations: Kaštela Bay Real-Time Early Warning System Mobile Application
Authors: Nikolić Željana , Srzić Veljko , Lovrinović Ivan , Perković Toni , Šolić Petar , Kekez Toni
Published: December 2022

Our work presents a reliable procedure to obtain real-time assessment of the sea water elevation at the Kaštela Bay site to ensure the a priori warning in the case of expected coastal flooding along the site area. In its origin, the presented procedure relies on relevant data sets which are site-specific and locally observed. Observed data sets are used within the procedure to assess sea water surface elevation when induced by barometric pressure changes and wind-generated waves. Tidal-induced changes are introduced into the assessment procedure by a pre-learned algorithm which relies on long-term sea level oscillations from the relevant tidal gauge. Wind-generated wave heights are determined in the near shore area, following the features of the depth and reflection of the shoreline subsections. By coupling three mechanisms, this paper offers a unique real-time procedure to determine the sea water elevation and assess the possibility for coastline structure to be flooded by the sea. Given information is visualized in a form of mobile application that implements the algorithm and allows end users to set the notifications based on the given ruleset.
An Explorative Study into the Influence of Different Fibers on the Spalling Resistance and Mechanical Properties of Self-Compacting Concrete after Exposure to Elevated Temperatures
Authors: Ning Xiliang , Li Jianfeng , Li Yuanyuan
Published: December 2022

This study aims to explore the impact of different fibers on the explosive spalling resistance, residual compressive strength, residual flexural tensile strength, and mass loss of self-compacting concrete (SCC) after heating to elevated temperatures. The fiber types, fiber contents, and target temperatures are selected as the tested variables. Steel fibers (SF), polypropylene fibers (PF), and their combination are used to improve the fire resistance of SCC. Then, the specimens are tested after exposure to different target temperatures varying from 200 °C to 1000 °C and cooling down to room temperature naturally. The obtained results reveal that PF can effectively prevent explosive spalling in the SCC. Moreover, it was found that the temperature of 400 °C is a critical temperature for the residual compressive strength of fiber-reinforced SCC. Regarding the flexural tensile strength, the temperature of 200 °C was found to be a changing point of the SCC after heating to elevated temperatures. A sharp decrease in the compressive strength is observed when the target temperature exceeds 400 °C. For temperatures below 400 °C, the compressive strength is enhanced slightly with the increase of the target temperature. Moreover, incorporating a fiber cocktail is an effective way to improve the explosive spalling resistance and residual mechanical properties in the case of fire. Finally, the regression analysis was performed and the proposed correlations between the residual strengths and elevated temperatures are compared with equations in the literature. Good accuracy of the proposed correlation is achieved for fiber-reinforced SCC.
Study on the Deformation Induced by Vertical Two-Layer Large Diameter Pipe-Jacking in the Soil-Rock Composite Stratum
Authors: Shao Guangbiao , Yang Nan , Han Jianyong
Published: December 2022

Aiming at the features of deformation caused by large diameter vertical two-layer pipe jacking in the soil-rock composite stratum, on-site monitoring and numerical analysis has been done based on an electric power tunnel project constructed with the pipe jacking method, in which the upper tunnel is located in the soil layer and the lower tunnel is partially located in the rock layer. The research shows that: (1) During upper pipe jacking construction, the maximum transverse and longitudinal ground settlements are about three times those of the lower pipe jacking construction, and the maximum horizontal lateral displacement is about 3.3 times the lower pipe jacking construction. (2) Total ground settlement increases rapidly with the reduction of vertical clear spacing of the upper and lower pipe, and the superimposed effect should be taken into consideration during the vertical arranged pipe-jacking construction. (3) The Peck formula, which is used to estimate lateral surface subsidence distribution, is modified to make it more applicable in the soil–rock composite stratum to calculate the ground settlement induced by the construction of pipe-jacking.
Testing Clean-Up Methods for the Quantification of Monosaccharides and Uronic Acids
Authors: Bargagli Irene , Sabatini Francesca , Modugno Francesca , Łucejko Jeannette Jacqueline
Published: December 2022

The determination of carbohydrate composition is extremely important for quality control in food and beverages, in material science, in pharmaceutics, and in the field of cultural heritage. Considering the complexity and the heterogeneity of the matrices, the optimization of extraction and purification steps aiming at maximizing the saccharide recovery from the matrix and effectively removing interferences is mandatory. The presence of inorganic components, besides being detrimental to the analytical instrumentation, can catalyze the isomerization of some sugars causing an alteration to their quantitative and qualitative profiles. In the present paper, protocols for suppressing the interference of inorganic ions in the quantification of monosaccharides and uronic acids by Gas Chromatography–Mass Spectrometry (GC-MS) are proposed. Two clean-up methods based on ion exchange resins (Amberlite MB-6113 and Amberlite IRN-150) and one making use of solid-phase extraction with a polypropylene Solid-Phase Extraction (SPE) column were tested on a standard carbohydrate solution, and the elution conditions optimized. The best purification conditions, in terms of higher recovery yield values for seven monosaccharides and two uronic acids, were obtained using SPE. Furthermore, the optimized SPE method was validated on a sample of mural painting rich in saccharides and inorganic material.
Verification of Convolutional Neural Network Cephalometric Landmark Identification
Authors: Davidovitch Moshe , Sella-Tunis Tatiana , Abramovicz Liat , Reiter Shoshana , Matalon Shlomo , Shpack Nir
Published: December 2022

Introduction: The mass-harvesting of digitized medical data has prompted their use as a clinical and research tool. The purpose of this study was to compare the accuracy and reliability of artificial intelligence derived cephalometric landmark identification with that of human observers. Methods: Ten pre-treatment digital lateral cephalometric radiographs were randomly selected from a university post-graduate clinic. The x- and y-coordinates of 21 (i.e., 42 points) hard and soft tissue landmarks were identified by 6 specialists, 19 residents, 4 imaging technicians, and a commercially available convolutional neural network artificial intelligence platform (CephX, Orca Dental, Hertzylia, Israel). Wilcoxon, Spearman and Bartlett tests were performed to compare agreement of human and AI landmark identification. Results: Six x- or y-coordinates (14.28%) were found to be statistically different, with only one being outside the 2 mm range of acceptable error, and with 97.6% of coordinates found to be within this range. Conclusions: The use of convolutional neural network artificial intelligence as a tool for cephalometric landmark identification was found to be highly accurate and can serve as an aid in orthodontic diagnosis.
An Unsupervised Learning Approach for Analyzing Unsafe Pilot Operations Based on Flight Data
Authors: Li Xiuyi , Qian Yu , Chen Hongnian , Zheng Linjiang , Wang Qixing , Shang Jiaxing
Published: December 2022

Flight safety is a hot topic in the aviation industry. Statistics show that safety incidents during landing are closely related to the flare phase because this critical period requires extensive pilot operations. Many airlines require that pilots should avoid performing any forward stick inputs during the flare. However, our statistical results from about 86,504 flights show that this unsafe pilot operation occasionally happens. Although several case studies were conducted previously, systematic research, especially based on a large volume of flight data, is still missing. This paper aims to fill this gap and provide more insights into the issue of pilots’ unsafe stick operations during the flare phase. Specifically, our work is based on the Quick Access Recorder (QAR) data, which consist of multivariate time-series data from various flight parameters. The raw data were carefully preprocessed, then key features were extracted based on flight expert experience, and a K-means clustering algorithm was utilized to divide the unsafe pilot operations into four categories. Based on the clustering results, we conducted an in-depth analysis to uncover the reasons for different types of unsafe pilot stick operations. In addition, extensive experiments were conducted to further investigate how these unsafe operations are correlated with different factors, including airlines, airports, and pilots. To the best of our knowledge, this is the first systematic study analyzing pilots’ unsafe forward stick operations based on a large volume of flight data. The findings can be used by airlines to design more targeted pilot training programs in the future.
Geographically Weighted Flow Cross K-Function for Network-Constrained Flow Data
Authors: Zhang Weijie , Zhao Jun , Liu Wenkai , Tan Zhangzhi , Xing Hanfa
Published: December 2022

Network-constrained spatial flows are usually used to describe movements between two spatial places on a road network. The analysis of the spatial associations between different types of network-constrained spatial flows plays a key role in understanding the spatial relationships among different movements. However, existing studies usually do not consider the effect of distance decay, which may reduce the effectiveness of the detected bivariate spatial flow patterns. Moreover, most existing studies are based on the planar space assumption, which is not suitable for network-constrained spatial flows. To overcome these problems, this study proposed a new statistical method, the Geographically Weighted Network Flow Cross K-function, which improves the Flow Cross K-Function method by taking the distance decay effect and the constraints of road networks into account. Both global and local versions are extended in this study: the global version measures the overall spatial association and the local version identifies the exact locations where a spatial association occurs. The experiments on simulated datasets show that the proposed method can identify predefined bivariate flow patterns. In a case study, the proposed method is also applied to flow data comprising Xiamen taxi and ride-hailing datasets. The results demonstrate that the proposed method effectively identifies the competitive relationships between taxi and ride-hailing services.
Applying Convolutional Neural Network in Automatic Assessment of Bone Age Using Multi-Stage and Cross-Category Strategy
Authors: Peng Ching-Tung , Chan Yung-Kuan , Yuh Yeong-Seng , Yu Shyr-Shen
Published: December 2022

Bone age is a common indicator of children’s growth. However, traditional bone age assessment methods usually take a long time and are jeopardized by human error. To address the aforementioned problem, we propose an automatic bone age assessment system based on the convolutional neural network (CNN) framework. Generally, bone age assessment is utilized amongst 0–18-year-old children. In order to reduce its variation in terms of regression model building, our system consists of two steps. First, we build a maturity stage classifier to identify the maturity stage, and then build regression models for each maturity stage. In this way, assessing bone age through the use of several independent regression models will reduce the variation and make the assessment of bone age more accurate. Some bone sections are particularly useful for distinguishing certain maturity stages, but may not be effective for other stages, and thus we first perform a rough classification to generally distinguish the maturity stage, and then undertake fine classification. Because the skeleton is constantly growing during bone development, it is not easy to obtain a clear decision boundary between the various stages of maturation. Therefore, we propose a cross-stage class strategy for this problem. In addition, because fewer children undergo X-rays in the early and late stages, this causes an imbalance in the data. Under the cross-stage class strategy, this problem can also be alleviated. In our proposed framework, we utilize an MSCS-CNN (Multi-Step and Cross-Stage CNN). We experiment on our dataset, and the accuracy of the MSCS-CNN in identifying both female and male maturity stages is above 0.96. After determining maturity stage during bone age assessment, we obtain a 0.532 and 0.56 MAE (mean absolute error) for females and males, respectively.
Properties of Emulsion Paints with Binders Based on Natural Latex Grafting Styrene and Methyl Methacrylate
Authors: Ibrahim Bahruddin , Helwani Zuchra , Wiranata Arya , Fadhillah Ivan , Miharyono Joni , - Nasruddin
Published: December 2022

Infrastructure developments in recent decades have led to increasing demand for high-performance paints for construction and decorative purposes. Emulsion paint is water-based paint that is commonly used for coating the internal and external surfaces of a building. The quality and performance of this emulsion paint are highly dependent on its constituent components, such as binders, pigment, solvents, and additives. Emulsion paints initially used conventional formaldehyde-based binders and were, for some reason, prohibited from being used in paints due to health and environmental issues. The development of bio-based paints with natural rubber latex (NRL) has the potential to be developed as an emulsion paint binder. The results showed that NRL grafting of styrene monomer or MMA showed much better resistance to wet scrub and abrasion than PVAc at a monomer concentration of 20%, for styrene, and 30%, for MMA, with washability values reaching each of 11 and 12 cycles at 4% binder concentration. The NgSt20-4 and NgMMA30-4 binders’ abilities to overcome wet scrub and abrasion increased with increasing paint binder concentrations, reaching 22 and 23 cycles at 10% binder concentration. Overall, the combination of NRL grafted with MMA monomer and 30% PVAc showed better performance and could compete with commercial binders such as PVAc. Adding methyl methacrylate monomer increases the adhesion and cohesion properties of the binder and increases the binder’s resistance to scrubbing and wet abrasion. However, the combination of NRL grafted MMA and 30% PVAc showed the same effectiveness as NRL grafted MMA without PVAc, with more economical production costs.
Spatial Data-Based Automatic and Quantitative Approach in Analyzing Maintenance Reachability
Authors: Geng Jie , Li Ying , Guo Hailong , Zhang Huan , Lv Chuan
Published: December 2022

Reachability, as a vital parameter in product maintainability design, exerts a tremendous influence in practical maintenance, especially in the usage stage. To decrease subjectivity in maintenance reachability analysis, this study proposes an automatic and quantitative approach based on the spatial data of the human arm to implement maintenance reachability analysis. The approach focused on two aspects, namely, accuracy and efficiency. In terms of accuracy, the presented methodology starts from the maintenance spot where the human hand is attached. An original global data sequence set was generated, including the wrist, elbow, and shoulder joints, under the constraints of kinematics, in which a data sequence represents an arm motion. Moreover, the surrounding objects are represented by their geometric data, in which each data sequence is analyzed to judge whether collision occurs between arm segments and surrounding objects. In this filtering process, the data sequence is retained if the aforementioned collision does not occur. In terms of efficiency, owing to the large number of global data sequences, the efficiency of the interval selection in collision calculation is also taken into consideration in this methodology. Unlike the traditional methods in the virtual environment, the starting point is the maintenance spot, rather than the human body. Hence, nearly all possibilities of arm postures are considered in a global perspective with little subjective involvement, which enhances the automation and objectivity in maintenance reachability analysis to a certain extent. The case study shows the usability and feasibility by a practical maintenance scene.
MSFL: Explainable Multitask-Based Shared Feature Learning for Multilingual Speech Emotion Recognition
Authors: Ma Yiping , Wang Wei
Published: December 2022

Speech emotion recognition (SER), a rapidly evolving task that aims to recognize the emotion of speakers, has become a key research area in affective computing. However, various languages in multilingual natural scenarios extremely challenge the generalization ability of SER, causing the model performance to decrease quickly, and driving researchers to ask how to improve the performance of multilingual SER. Recent studies mainly use feature fusion and language-controlled models to address this challenge, but key points such as the intrinsic association of languages or deep analysis of multilingual shared features (MSFs) are still neglected. To solve this problem, an explainable Multitask-based Shared Feature Learning (MSFL) model is proposed for multilingual SER. The introduction of multi-task learning (MTL) can provide related task information of language recognition for MSFL, improve its generalization in multilingual situations, and further lay the foundation for learning MSFs. Specifically, considering the generalization capability and interpretability of the model, the powerful MTL module was combined with the long short-term memory and attention mechanism, aiming to maintain the generalization in multilingual situations. Then, the feature weights acquired from the attention mechanism were ranked in descending order, and the top-ranked MSFs were compared with top-ranked monolingual features, enhancing the model interpretability based on the feature comparison. Various experiments were conducted on Emo-DB, CASIA, and SAVEE corpora from the model generalization and interpretability aspects. Experimental results indicate that MSFL performs better than most state-of-the-art models, with an average improvement of 3.37–4.49%. Besides, the top 10 features in MSFs almost contain the top-ranked features in three monolingual features, which effectively demonstrates the interpretability of MSFL.
The Impact of Nonlinear Mobility Models on Straight Line Conflict Detection Algorithm for UAVs
Authors: Alajlan Maram , Belghith Abdelfettah
Published: December 2022

Conflict detection is an essential issue in flying ad hoc networks (FANETs) to ensure the safety of unmanned aerial vehicles (UAVs) during flights. This paper assesses the applicability and utilization of a conflict detection algorithm that sees immediate trajectory as a straight line for short periods with nonlinear mobility models such as Gauss–Markov (GM). First, we use a straight line conflict detection algorithm with two nonlinear mobility models. Then, we perform an extensive simulation study to evaluate the performance. Additionally, we present a comprehensive discussion to tune the collision detection parameters efficiently. Simulation results indicate that an algorithm considering the immediate trajectory as a straight line to predict conflicts between UAVs can be applied with nonlinear mobilities and can provide an acceptable performance measured in false and missed alarms.
Differentiation of the Wright Functions with Respect to Parameters and Other Results
Authors: Apelblat Alexander , Mainardi Francesco
Published: December 2022

In this work, we discuss the derivatives of the Wright functions (of the first and the second kinds) with respect to parameters. The differentiation of these functions leads to infinite power series with the coefficients being the quotients of the digamma (psi) and gamma functions. Only in few cases is it possible to obtain the sums of these series in a closed form. The functional form of the power series resembles those derived for the Mittag-Leffler functions. If the Wright functions are treated as generalized Bessel functions, differentiation operations can be expressed in terms of the Bessel functions and their derivatives with respect to the order. In many cases, it is possible to derive the explicit form of the Mittag-Leffler functions by performing simple operations with the Laplacian transforms of the Wright functions. The Laplacian transform pairs of both kinds of Wright functions are discussed for particular values of the parameters. Some transform pairs serve to obtain functional limits by applying the shifted Dirac delta function. We expect that the present analysis would find several applications in physics and more generally in applied sciences. These special functions of the Mittag-Leffler and Wright types have already found application in rheology and in stochastic processes where fractional calculus is relevant. Careful readers can benefit from the new results presented in this paper for novel applications.
Composite Based on Multi-Walled Carbon Nanotubes and Manganese Oxide with Rhenium Additive for Supercapacitors: Structural and Electrochemical Studies
Authors: Korusenko Petr M. , Nesov Sergey N.
Published: December 2022

The structure and electrochemical characteristics of composites based on multi-walled carbon nanotubes (MWCNTs) and manganese oxide with the addition of rhenium oxide has been studied. It has shown that the decorating of the MWCNT surface with layers or nanoparticles of manganese oxide (Mn(III) + Mn(IV)) provides more than a twofold increase in the value of the specific capacitance at low potential scan rates. However, composites based only on manganese oxide exhibit poor electrochemical behavior and the value of the specific capacitance decreases rapidly with increasing potential scan rate due to the limitation of diffusion processes. The addition of rhenium oxide to composites significantly increases their electrochemical properties due to changes in the chemical composition and morphology of composites. Studies of the structure and chemical state have shown that an improvement in the specific capacitance is provided by increasing in the proportion of Mn(IV) oxide in such composites, which has the ability to rapidly and completely reverse redox reactions and has lower electrical resistance values, compared to Mn(III) oxide. A detailed analysis of the voltammetric data showed that an increase in the rate capability in composites with the addition of rhenium oxide can also be provided by increasing the availability of the electrode surface for electrolyte ions and increasing the amount of charge stored due to the formation of a double electric layer.
A Statistical Analysis of Sporadic-E Characteristics Associated with GNSS Radio Occultation Phase and Amplitude Scintillations
Authors: Emmons Daniel J. , Wu Dong L. , Swarnalingam Nimalan
Published: December 2022

Statistical GNSS-RO measurements of phase and amplitude scintillation are analyzed at the mid-latitudes in the local summer for a 100 km altitude. These conditions are known to contain frequent sporadic-E, and the S4-σϕ trends provide insight into the statistical distributions of the sporadic-E parameters. Joint two-dimensional S4-σϕ histograms are presented, showing roughly linear trends until the S4 saturates near 0.8. To interpret the measurements and understand the sporadic-E contributions, 10,000 simulations of RO signals perturbed by sporadic-E layers are performed using length, intensity, and vertical thickness distributions from previous studies, with the assumption that the sporadic-E layer acts as a Gaussian lens. Many of the key trends observed in the measurement histograms are present in the simulations, providing a key for understanding the complex mapping between layer characteristics and impacts on the GNSS-RO signals. Additionally, the inclusion of Kolmogorov turbulence and a diffusion-limited threshold on the lens strength/(vertical thickness)2 ratio helps to make the layers more physically realistic and improves agreement with the observations.
Solution to Integral Equation in an O-Complete Branciari b-Metric Spaces
Authors: Dhanraj Menaha , Gnanaprakasam Arul Joseph , Mani Gunaseelan , Ege Ozgur , De la Sen Manuel
Published: December 2022

In this paper, we prove fixed point theorem via orthogonal Geraghty type α-admissible contraction map in an orthogonal complete Branciari b-metric spaces context. An example is presented to strengthen our main result. We provided an application to find the existence and uniqueness of a solution to the Volterra integral equation. We have compared the approximate solution and exact solution numerically.
The Effect of Cultivation Conditions on Antifungal and Maize Seed Germination Activity of Bacillus-Based Biocontrol Agent
Authors: Vlajkov Vanja , Pajčin Ivana , Loc Marta , Budakov Dragana , Dodić Jelena , Grahovac Mila , Grahovac Jovana
Published: December 2022

Aflatoxin contamination is a global risk and a concerning problem threatening food safety. The biotechnological answer lies in the production of biocontrol agents that are effective against aflatoxins producers. In addition to their biocontrol effect, microbial-based products are recognized as efficient biosolutions for plant nutrition and growth promotion. The present study addresses the characterization of the representative of Phaseolus vulgaris rhizosphere microbiome, Bacillus sp. BioSol021, regarding plant growth promotion traits, including the activity of protease, cellulase, xylanase, and pectinase with the enzymatic activity index values 1.06, 2.04, 2.41, and 3.51, respectively. The potential for the wider commercialization of this kind of product is determined by the possibility of developing a scalable bioprocess solution suitable for technology transfer to an industrial scale. Therefore, the study addresses one of the most challenging steps in bioprocess development, including the production scale-up from the Erlenmeyer flask to the laboratory bioreactor. The results indicated the influence of the key bioprocess parameters on the dual mechanism of action of biocontrol effects against the aflatoxigenic Aspergillus flavus, as well on maize seed germination activity, pointing out the positive impact of high aeration intensity and agitation rate, resulting in inhibition zone diameters of 60 mm, a root length 96 mm, and a shoot length 27 mm.
Effect of Hypoxia on Branching Characteristics and Cell Subpopulations during Kidney Organ Culture
Authors: Hamon Morgan , Cheng Hsiao-Min , Johnson Ming , Yanagawa Norimoto , Hauser Peter V.
Published: December 2022

During early developmental stages, embryonic kidneys are not fully vascularized and are potentially exposed to hypoxic conditions, which is known to influence cell proliferation and survival, ureteric bud branching, and vascularization of the developing kidney. To optimize the culture conditions of in vitro cultured kidneys and gain further insight into the effect of hypoxia on kidney development, we exposed mouse embryonic kidneys isolated at E11.5, E12.5, and E13.5 to hypoxic and normal culture conditions and compared ureteric bud branching patterns, the growth of the progenitor subpopulation hoxb7+, and the expression patterns of progenitor and differentiation markers. Branching patterns were quantified using whole organ confocal imaging and gradient-vector-based analysis. In our model, hypoxia causes an earlier expression of UB tip cell markers, and a delay in stalk cell marker gene expression. The metanephric mesenchyme (MM) exhibited a later expression of differentiation marker FGF8, marking a delay in nephron formation. Hypoxia further delayed the expression of stroma cell progenitor markers, a delay in cortical differentiation markers, as well as an earlier expression of medullary and ureteral differentiation markers. We conclude that standard conditions do not apply universally and that tissue engineering strategies need to optimize suitable culture conditions for each application. We also conclude that adapting culture conditions to specific aspects of organ development in tissue engineering can help to improve individual stages of tissue generation.
Chronic Bedridden Condition Is Reflected by Substantial Changes in Plasma Inflammatory Profile
Authors: Magliozzi Roberta , Pedrinolla Anna , Rossi Stefania , Stabile Anna Maria , Danese Elisa , Lippi Giuseppe , Schena Federico , Calabrese Massimiliano , Venturelli Massimo Venturelli
Published: December 2022

Absent or reduced physical activity and spontaneous movement over days, weeks, or even years may lead to problems in almost every major organ/system in the human body. In this study, we investigated whether the dysregulation and alteration of plasma protein inflammatory profiling can stratify chronic bedridden conditions observed in 22 elderly chronic bedridden (CBR) individuals with respect to 11 age-matched active (OLD) controls. By using a combination of immune-assay multiplex techniques, a complex of 27 inflammatory mediators was assessed in the plasma collected from the two groups. A specific plasma protein signature is indeed able to distinguish IPO individuals from age-matched OLD controls; while significantly (p < 0.001) higher protein levels of IL-2, IL-7, and IL-12p70 were measured in the plasma of CBR with respect to OLD individuals, significantly (p < 0.01) higher levels of seven inflammatory mediators, including IL-9, PDGF-b, CCL4 (MIP-1b), CCL5 (RANTES), IL-1Ra, CXCL10 (IP10), and CCL2 (MCP-1), were identified in OLD individuals with respect to CBR individuals. These data suggest that the chronic absence of physical activity may contribute to the dysregulation of a complex molecular pattern occurring with ageing and that specific plasma protein signatures may represent potential biomarkers as well as new potential therapeutic targets for new treatments aimed at improving health expectancy.
Concentrations of N6-Carboxymethyllysine (CML), N6-Carboxyethyllysine (CEL), and Soluble Receptor for Advanced Glycation End-Products (sRAGE) Are Increased in Psoriatic Patients
Authors: Damasiewicz-Bodzek Aleksandra , Nowak Agnieszka
Published: December 2022

Psoriasis is a chronic, recurrent, and often severe skin disease which is frequently associated with metabolic disorders and increased risk of cardiovascular complications. One of the postulated links is an intensified process of advanced protein glycation and/or glycoxidation. Therefore, the aim of the study was to assess concentrations of N6-carboxymethyllysine (CML), N6-carboxyethyllysine (CEL), and soluble form of receptor for advanced glycation end-products (sRAGE) in psoriasis patients at different phases of the disease activity, in comparison to healthy individuals. The study material consisted of sera from psoriasis patients in active phase, in the remission phase, and healthy controls. Concentrations of CML, CEL, and sRAGE were determined using ELISA technique. In the patients with psoriasis (in both phases of the disease), concentrations of CML, CEL and sRAGE were significantly higher than in healthy individuals but they did not correlate with psoriasis area severity index (PASI) values. The remission of the disease was followed by a significant decrease in CML, CEL, and sRAGE concentrations when compared to active patients; however, these concentrations were still significantly higher than in the controls. Our data suggest that psoriasis is accompanied by an intense glycoxidation process and that high sRAGE levels seem to reflect permanent RAGE overstimulation.
Plant-Derived Bioactive Compounds and Potential Health Benefits: Involvement of the Gut Microbiota and Its Metabolic Activity
Authors: Chen Xinyu , Pan Shifeng , Li Fei , Xu Xinyu , Xing Hua
Published: December 2022

The misuse and abuse of antibiotics in livestock and poultry seriously endanger both human health and the continuously healthy development of the livestock and poultry breeding industry. Plant-derived bioactive compounds (curcumin, capsaicin, quercetin, resveratrol, catechin, lignans, etc.) have been widely studied in recent years, due to their extensive pharmacological functions and biological activities, such as anti-inflammatory, antioxidant, antistress, antitumor, antiviral, lowering blood glucose and lipids, and improving insulin sensitivity. Numerous studies have demonstrated that plant-derived bioactive compounds are able to enhance the host’s ability to resist or diminish diseases by regulating the abundance of its gut microbiota, achieving great potential as a substitute for antibiotics. Recent developments in both humans and animals have also highlighted the major contribution of gut microbiota to the host’s nutrition, metabolism, immunity, and neurological functions. Changes in gut microbiota composition are closely related to the development of obesity and can lead to numerous metabolic diseases. Mounting evidence has also demonstrated that plant-derived bioactive compounds, especially curcumin, can improve intestinal barrier function by regulating intestinal flora. Furthermore, bioactive constituents can be also directly metabolized by intestinal flora and further produce bioactive metabolites by the interaction between the host and intestinal flora. This largely enhances the protective effect of bioactive compounds on the host intestinal and whole body health, indicating that the bidirectional regulation between bioactive compounds and intestinal flora has great application potential in maintaining the host’s intestinal health and preventing or treating various diseases. This review mainly summarizes the latest research progress in the bioregulation between gut microbiota and plant-derived bioactive compounds, together with its application potential in humans and animals, so as to provide theoretical support for the application of plant-derived bioactive compounds as new feed additives and potential substitutes for antibiotics in the livestock and poultry breeding industry. Overall, based on this review, it can be concluded that plant-derived bioactive compounds, by modulating gut microbiota, hold great promise toward the healthy development of both humans and animal husbandry.
Melanogenesis and the Targeted Therapy of Melanoma
Authors: Li Cang , Kuai Le , Cui Rutao , Miao Xiao
Published: December 2022

Pigment production is a unique character of melanocytes. Numerous factors are linked with melanin production, including genetics, ultraviolet radiation (UVR) and inflammation. Understanding the mechanism of melanogenesis is crucial to identify new preventive and therapeutic strategies in the treatment of melanoma. Here, we reviewed the current available literatures on the mechanisms of melanogenesis, including the signaling pathways of UVR-induced pigment production, MC1R’s central determinant roles and MITF as a master transcriptional regulator in melanogenesis. Moreover, we further highlighted the role of targeting BRAF, NRAS and MC1R in melanoma prevention and treatment. The combination therapeutics of immunotherapy and targeted kinase inhibitors are becoming the newest therapeutic option in advanced melanoma.
TGF-β Pathways Stratify Colorectal Cancer into Two Subtypes with Distinct Cartilage Oligomeric Matrix Protein (COMP) Expression-Related Characteristics
Authors: Ding Jia-Tong , Zhou Hao-Nan , Huang Ying-Feng , Peng Jie , Huang Hao-Yu , Yi Hao , Zong Zhen , Ning Zhi-Kun
Published: December 2022

Background: Colorectal cancers (CRCs) continue to be the leading cause of cancer-related deaths worldwide. The exact landscape of the molecular features of TGF-β pathway-inducing CRCs remains uncharacterized. Methods: Unsupervised hierarchical clustering was performed to stratify samples into two clusters based on the differences in TGF-β pathways. Weighted gene co-expression network analysis was applied to identify the key gene modules mediating the different characteristics between two subtypes. An algorithm integrating the least absolute shrinkage and selection operator (LASSO), XGBoost, and random forest regression was performed to narrow down the candidate genes. Further bioinformatic analyses were performed focusing on COMP-related immune infiltration and functions. Results: The integrated machine learning algorithm identified COMP as the hub gene, which exhibited a significant predictive value for two subtypes with an area under the curve (AUC) value equaling 0.91. Further bioinformatic analysis revealed that COMP was significantly upregulated in various cancers, especially in advanced CRCs, and regulated the immune infiltration, especially M2 macrophages and cancer-associated fibroblasts in CRCs. Conclusions: Comprehensive immune analysis and experimental validation demonstrate that COMP is a reliable signature for subtype prediction. Our results could provide a new point for TGFβ-targeted anticancer drugs and contribute to guiding clinical decision making for CRC patients.