bluuebunny/crossref_metadata_2025 huggingface dataset:
Behavioral and Synaptic Phenotypes of Female Prdx6−/− Mice
Authors: Pairojana Tanita , Phasuk Sarayut , Suresh Pavithra , Liu Ingrid Y.
Published: June 2022

Peroxiredoxin 6 (PRDX6) is expressed throughout the brain, including the hippocampus, where it plays a potential role in synaptic regulation and forming emotional and spatial memories. PRDX6 is predominantly detected in the female mouse’s hippocampus; thus, we investigate the effect of the Prdx6 gene on behavioral phenotypes and synaptic functions using female Prdx6 knockout (Prdx6−/−) mice. Our results demonstrate that female Prdx6−/− mice exhibited anxiety-like behavior, enhanced contextual fear memory, and impaired spatial memory. We also found increased, paired–pulse facilitation ratios, and decreased long-term potentiation (LTP) in the hippocampal region of these female Prdx6−/− mice. The present study helps to understand better the PRDX6’s role in emotional response and spatial memory formation in female mice.
Dietary Flavonoid Intake and Chronic Sensory Conditions: A Scoping Review
Authors: Tang Diana , Tran Yvonne , Shekhawat Giriraj S. , Gopinath Bamini
Published: June 2022

Dietary flavonoids have antioxidant, anti-inflammatory, and vascular health benefits, which align with the proposed pathophysiology of age-related eye conditions and hearing problems (hearing loss and tinnitus). This scoping review is based on Arksey and O’Malley’s six-stage framework and aims to summarise current evidence on the association between the dietary flavonoid intake and chronic sensory conditions in adults, and to identify the research gaps in this area. Eligible studies were identified by searching MEDLINE, EMBASE PsycINFO via the OVID platform, and Google Scholar, as well as manually searching the reference lists of the eligible articles. The inclusion criteria included: articles with full-text access, written in the English language, and focused on chronic sensory conditions and dietary flavonoid intake in an adult population. Studies focused on flavonoid supplements were excluded. Ten studies were included in this review. The evidence suggests that the flavonoid subclass, flavonols, are protective against eye conditions, including age-related macular degeneration, cataract, and glaucoma. There is insufficient evidence to support an association with hearing loss or tinnitus. Overall, dietary flavonol intake appears to be protective against some chronic eye conditions. However, for most eye and hearing-related conditions, only one study was identified. Thus, there is a need for more recent high-quality research to be conducted to confirm any significant associations.
Effect of Selenium on the Iron Homeostasis and Oxidative Damage in Brain and Liver of Mice
Authors: Staneviciene Inga , Sulinskiene Jurgita , Sadauskiene Ilona , Liekis Arunas , Ruzgaite Ausrine , Naginiene Rima , Baranauskiene Dale , Simakauskiene Vaida , Krusnauskas Raulas , Viezeliene Dale
Published: June 2022

Selenium is an essential trace element that maintains normal brain function, mainly due its antioxidant properties. Although the amount of Se in the body is tightly regulated by the liver, both an excess of and deficiency in Se can modulate the cellular redox status and affect the homeostasis of other essential elements for both humans and animals. The aim of this study was to determine the effect of inorganic selenium excess on oxidative stress and iron homeostasis in brain and liver of laboratory BALB/c mice, which were supplemented with Na2SeO3 solution (0.2 mg and 0.4 mg Se/kg body weight) for 8 weeks. The content of the lipid peroxidation product malondialdehyde and antioxidant enzyme catalase activity/gene expression were used as markers of oxidative damage and were evaluated by spectrophotometric assays. Selenium and iron concentrations were determined by inductively coupled plasma mass spectrometry (ICP-MS). Catalase gene expression was analyzed by qRT-PCR and ΔΔCt methods. Our results showed that doses of 0.2 mg Se and 0.4 mg Se caused a relatively low accumulation of Se in the brain of mice; however, it induced a 10-fold increase in its accumulation in the liver and also increased iron accumulation in both tested organs. Both doses of Se increased the content of malondialdehyde as well as decreased catalase activity in the liver, while the 0.4 mg Se dose has also activated catalase gene expression. Brain of mice exposed to 0.2 mg Se showed reduced lipid peroxidation; however, the exposure to 0.4 mg of Se increased the catalase activity as well as gene expression. One may conclude that exposure to both doses of Se caused the accumulation of this micronutrient in mice brain and liver and have also provided a disrupting effect on the levels of iron. Both doses of Se have triggered oxidative liver damage. In the brain, the effect of Se was dose dependent, where −0.2 mg of Se provided antioxidant activity, which was observed through a decrease in lipid peroxidation. On the contrary, the 0.4 mg dose increased brain catalase activity as well as gene expression, which may have contributed to maintaining brain lipid peroxidation at the control level.
Dim Blue Light at Night Induces Spatial Memory Impairment in Mice by Hippocampal Neuroinflammation and Oxidative Stress
Authors: Liu Qi , Wang Zixu , Cao Jing , Dong Yulan , Chen Yaoxing
Published: June 2022

Light pollution is one of the most serious public problems, especially the night light. However, the effect of dim blue light at night (dLAN-BL) on cognitive function is unclear. In this study, we evaluated the effects of exposure to dLAN-BL in C57BL/6J mice for 4 consecutive weeks. Our results showed dLAN-BL significantly impaired spatial learning and memory and increased plasma corticosterone level in mice. Consistent with these changes, we observed dLAN-BL significantly increased the numbers and activation of microglia and the levels of oxidative stress product MDA in the hippocampus, decreased the levels of antioxidant enzymes Glutathione peroxidase (GSH-Px), Superoxide dismutase (SOD), Gluathione reductase (Gsr), total antioxidants (T-AOC) and the number of neurons in the hippocampus, up-regulated the mRNA expression levels of IL6, TNF-α and the protein expression levels of iNOS, COX2, TLR4, p-p65, Cleaved-Caspase3 and BAX, and down-regulated the mRNA expression levels of IL4, IL10, Psd95, Snap25, Sirt1, Dcx and the protein expression level of BCL2. In vitro results further showed corticosterone (10uM)-induced BV2 cell activation and up-regulated content of IL6, TNF-α in the cell supernatant and the protein expression levels of iNOS, COX2, p-p65 in BV2 cells. Our findings suggested dLAN-BL up-regulated plasma corticosterone level and hippocampal microglia activation, which in turn caused oxidative stress and neuroinflammation, leading to neuronal loss and synaptic dysfunction, ultimately leading to spatial learning and memory dysfunction in mice.
Combination of Pulsed Electric Field and Ultrasound in the Extraction of Polyphenols and Volatile Compounds from Grape Stems
Authors: Ntourtoglou George , Drosou Fotini , Chatzimitakos Theodoros , Athanasiadis Vassilis , Bozinou Eleni , Dourtoglou Vassilis G. , Elhakem Abeer , Sami Rokayya , Ashour Amal Adnan , Shafie Alaa , Lalas Stavros I.
Published: June 2022

Increasing the yield of extraction of bioactive compounds from plants is of high importance. Grape stems are widely discarded during the wine-making process, despite their high content in many valuable compounds. The aim of this work was to examine whether the use of pulsed electric field (PEF) treatment of the stems could increase the yield of polyphenol and volatile compounds in the extracts. For this reason, a relatively low-energy consuming PEF process was employed (low-electric field strength, 1 kV/cm) for a short time (30 min) at the grape stems. In addition, the effect of different solvents during this pretreatment step was examined. With the use of Folin–Ciocalteu assay, the extracts were compared with the respective control samples (not pretreated with PEF). Moreover, extracts were prepared to assess whether changes occur to the volatile profile of the extracts. The results were conclusive that not only PEF can increase the yield of polyphenols (up to 35% increase recorded), but also that the solvent used during PEF pretreatment can affect the process. Furthermore, a 234% increase in the total content of volatile compounds was recorded, when PEF was used as a pretreatment step. Therefore, the combination of PEF and ultrasound-assisted extraction is highly promising to obtain grape stem extracts with a higher content of bioactive compounds.
Nitrate and Dissolved Organic Carbon Release in Sandy Soils at Different Liquid/Solid Ratios Amended with Graphene and Classical Soil Improvers
Authors: Alessandrino Luigi , Colombani Nicolò , Aschonitis Vassilis George , Mastrocicco Micòl
Published: June 2022

This study emphasizes the importance of employing parallel batch tests with different liquid/solid (L/S) ratios to assess their dissolution mechanisms. Changes in physicochemical parameters (electrical conductivity, pH, and oxidation-reduction potential), as well as the sorption/desorption of dissolved organic carbon (DOC) and nitrate (NO3−) due to graphene addition in a calcareous sandy soil (CS) and in a siliciclastic riverine sandy soil (SS) were assessed via batch experiments at different L/S ratios. Graphene’s production is growing at a great pace, so it’s important to test methods to reuse graphene wastes. The results of soil batch experiments mixed with graphene were compared with classical soil improvers (compost, biochar, and zeolites). The batches were performed using the saturation soil extraction method with deionized water as a proxy of rainwater. The contact time was 48 h. At the end of the experiment, water samples were collected to be analyzed for NO3−, DOC, DIC, Ca, and Mg. Graphene did not alter the physiochemical parameters of both soils. Moreover, its addition did not trigger any NO3− increase respect to control and to other improvers. Biochar increased EC and pH beyond recommended limits for most crops’ growth in both soils. As expected, compost addition produced the highest NO3− release.
Developing a Speech Recognition System for Recognizing Tonal Speech Signals Using a Convolutional Neural Network
Authors: Dua Sakshi , Kumar Sethuraman Sambath , Albagory Yasser , Ramalingam Rajakumar , Dumka Ankur , Singh Rajesh , Rashid Mamoon , Gehlot Anita , Alshamrani Sultan S. , AlGhamdi Ahmed Saeed
Published: June 2022

Deep learning-based machine learning models have shown significant results in speech recognition and numerous vision-related tasks. The performance of the present speech-to-text model relies upon the hyperparameters used in this research work. In this research work, it is shown that convolutional neural networks (CNNs) can model raw and tonal speech signals. Their performance is on par with existing recognition systems. This study extends the role of the CNN-based approach to robust and uncommon speech signals (tonal) using its own designed database for target research. The main objective of this research work was to develop a speech-to-text recognition system to recognize the tonal speech signals of Gurbani hymns using a CNN. Further, the CNN model, with six layers of 2DConv, 2DMax Pooling, and 256 dense layer units (Google’s TensorFlow service) was also used in this work, as well as Praat for speech segmentation. Feature extraction was enforced using the MFCC feature extraction technique, which extracts standard speech features and features of background music as well. Our study reveals that the CNN-based method for identifying tonal speech sentences and adding instrumental knowledge performs better than the existing and conventional approaches. The experimental results demonstrate the significant performance of the present CNN architecture by providing an 89.15% accuracy rate and a 10.56% WER for continuous and extensive vocabulary sentences of speech signals with different tones.
A Multi-Source Separation Approach Based on DOA Cue and DNN
Authors: Zhang Yu , Jia Maoshen , Jia Xinyu , Pai Tun-Wen
Published: June 2022

Multiple sound source separation in a reverberant environment has become popular in recent years. To improve the quality of the separated signal in a reverberant environment, a separation method based on a DOA cue and a deep neural network (DNN) is proposed in this paper. Firstly, a pre-processing model based on non-negative matrix factorization (NMF) is utilized for recorded signal dereverberation, which makes source separation more efficient. Then, we propose a multi-source separation algorithm combining sparse and non-sparse component points recovery to obtain each sound source signal from the dereverberated signal. For sparse component points, the dominant sound source for each sparse component point is determined by a DOA cue. For non-sparse component points, a DNN is used to recover each sound source signal. Finally, the signals separated from the sparse and non-sparse component points are well matched by temporal correlation to obtain each sound source signal. Both objective and subjective evaluation results indicate that compared with the existing method, the proposed separation approach shows a better performance in the case of a high-reverberation environment.
Comparative Assessment of Perception about Angle Inclination of Mandibular and Maxillary Incisors on the Cephalometric Analysis between Skeletal Class 3 and Orthognathic Cases
Authors: Hija Ahmad , Allon Dror Michael
Published: June 2022

Before orthognathic surgery, a thorough diagnosis of the maxillofacial structure is performed for combined orthodontic–surgical treatment planning. One of the tools that are used for this collaboration is the cephalometric radiograph. Cephalometric analysis is a method for measuring the location of specific anatomical landmarks upon a cephalogram. Some of these parameters are more difficult to define accurately in cases of dentofacial deformities. Therefore, the data obtained from different examiners are characterized by high variability. The present study aimed to examine whether there is a significant variation in the physicians’ measurements between orthognathic Class I (normal) cases and the cases of skeletal deformity Class III. The study involved ten physicians with a mean age of 27. All physicians underwent appropriate instruction for reading and analyzing cephalometric radiographs, and all physicians were instructed about their role in the study. Each participant received 100 cephalometric radiographs, consisting of 50 radiographs of patients with a regular facial structure (Class-I = orthognathic) and 50 photographs of patients with a specific skeletal deformity (Class-III = prognathic). According to the Frankfort Horizontal plane, each physician marked the upper incisor (U1) longitudinal axis on the radiograph and the lower incisor (L1) longitudinal axis according to the mandibular plane. Then, we measured the angle degree with the Cephninja® application. Afterward, we performed a statistical analysis of the t-test with Bonferroni correction to check whether there is a significantly large standard deviation between the indices in the orthognathic cases compared to the prognathic cases. In the group of physicians who participated in this sample of these cephalometric radiographs, we found that in prognathic patients, the upper incisor angle measurements showed significantly more t variance relative to those physicians’ corresponding measurements radiographs of orthognathic patients. Variability increases as skeletal deformity become more severe (p = 0.026) in U1 TO FH and (p = 0.014) L1 TO MP. Cephalometric measurements, which are essential for the correct diagnosis and planning of combined orthodontic treatment, suffer from a significant examiner-based bias that is greater as deformity becomes more severe. This conclusion has implications for the accuracy of the model on which the entire plan process of the combined treatment of facial and jaw deformities is based. The surgeon should use CBCT (cone-beam computed tomography) for its three-dimensional superiority over cephalometric imaging, which will result in a more accurate evaluation of surgery planning and performance.
Joint Entity and Relation Extraction Network with Enhanced Explicit and Implicit Semantic Information
Authors: Wu Huiyan , Huang Jun
Published: June 2022

The main purpose of the joint entity and relation extraction is to extract entities from unstructured texts and extract the relation between labeled entities at the same time. At present, most existing joint entity and relation extraction networks ignore the utilization of explicit semantic information and explore implicit semantic information insufficiently. In this paper, we propose Joint Entity and Relation Extraction Network with Enhanced Explicit and Implicit Semantic Information (EINET). First, on the premise of using the pre-trained model, we introduce explicit semantics from Semantic Role Labeling (SRL), which contains rich semantic features about the entity types and relation of entities. Then, to enhance the implicit semantic information and extract richer features of the entity and local context, we adopt different Bi-directional Long Short-Term Memory (Bi-LSTM) networks to encode entities and local contexts, respectively. In addition, we propose to integrate global semantic information and local context length representation in relation extraction to further improve the model performance. Our model achieves competitive results on three publicly available datasets. Compared with the baseline model on Conll04, EINET obtains improvements by 2.37% in F1 for named entity recognition and 3.43% in F1 for relation extraction.
Accurate Sinusoidal Frequency Estimation Algorithm for Internet of Things Based on Phase Angle Interpolation Using Frequency Shift
Authors: Cheng Minglong , Jia Guoqing , Fang Weidong , Yi Huiyue , Zhang Wuxiong
Published: June 2022

Frequency estimation of a sinusoidal signal is a fundamental problem in signal processing for the Internet of Things. The frequency interpolation estimation algorithm based on the fast Fourier transform is susceptible to being disturbed by noise, which leads to estimation error. In order to improve the accuracy of frequency estimation, an improved Rife frequency estimation algorithm based on phase angle interpolation is proposed in this paper, namely the PAI–Rife algorithm. We changed the existing frequency deviation factor of the Rife algorithm using phase angle interpolation. Then, by setting the frequency shift threshold, the frequency that is not within the threshold range is shifted to the optimal estimation space. The simulation results show that the proposed algorithm has a wider valid estimation range, and the estimated standard deviation is closer to the Cramer–Rao lower bound. Compared with the Rife algorithm and some recently proposed advanced algorithms, the proposed algorithm has less computational complexity, lower misjudgment rate, and more stable performance.
AFM/XPS Analysis of the Growth and Architecture of Oriented Molecular Monolayer by Spin Cast Process and Its Cross-Linking Induced by Hyperthermal Hydrogen
Authors: Liu Jinkun , Xu Run , Zhu Yan , Yang De-Quan , Nie Heng-Yong , Lau Woon Ming
Published: June 2022

We used atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS) to comprehensively study the growth and the cross-linking of dotriacontane (C32H66) nanofilms that were deposited on a silicon wafer by the spin-coating process. It was found that the molecular structure of the nanofilms changed with C32H66 concentration at the given spin speed, of which a monolayer of oriented C32H66 molecules, formed at lower deposition concentrations, was composed of a perpendicular orientation state with the molecular long-chain axis perpendicular to the substrate surface and a parallel orientation state, while the perpendicular state was essentially dominant when the nanofilm was formed at higher deposition concentrations. The shortening of the first perpendicular layer in AFM topography could be attributed to the mixing of both parallel and perpendicular lamellas in the first layer. XPS analysis indicated that the average thickness of the layer almost linearly increased with the C32H66 concentration. The monolayer of C32H66 film could be cross-linked by a hyperthermal hydrogen-induced cross-linking (HHIC) at a few eV via kinetic collision to cleave C-H bonds. The water contact angle measurement of extensive HHIC on C32H66 nanofilms disclosed that the static contact angle decreased with the treatment time (or fluence) and saturated after full cross-linking of the film.
Interoperability of Infrastructure and Transportation Information Models: A Public Transport Case Study
Authors: Čuš-Babič Nenad , Guerra De Oliveira Sara Filipa , Tibaut Andrej
Published: June 2022

The duplication of semantic data modelled in different disciplines poses interoperability challenges. Information models that benefit from the application of standards that enable data reusability and prevent redundancy and misuse should be compatible, particularly when different systems are used in the same domain-specific area, as in the case of public transportation. Transportation information models, leading and providing reliable and robust public transport services, can nowadays be enriched with information found in building information models devoted to transportation infrastructure. Therefore, in the present paper, a mapping between the standards and technical specifications that support each modelling approach is explored, analysed, and aligned to maximise the best out of the current common practices used. The information from the Industry Foundation Classes IFC specification-based models complements the conceptual and physical transportation models, where Transmodel and NeTEx are well-established, with accurate (as-built) detailed characteristics of the transportation infrastructure (stop places, quays, entrances, access spaces and equipment as ramps, staircases, and escalators). The extraction of topological information stored in IFC models allows for navigation-network extraction, information about spaces, and passages between spaces. A specific public transport case study focused on a train station is detailed to better corroborate and illustrate the advantages and uses of compatible and complementing modelling approaches. As building-information-modelling awareness and use is growing, the validated mapping approach can benefit from the future application of automation procedures.
Design of an Intelligent Tutoring System to Create a Personalized Study Plan Using Expert Systems
Authors: Bradáč Vladimír , Smolka Pavel , Kotyrba Martin , Průdek Tomáš
Published: June 2022

The article is devoted to the issue of the construction of an intelligent tutoring system which was created by our university for implementing distance learning and combined forms of studies. Significantly higher demand for such tools occurred during the COVID-19 pandemic when distance learning was used by students in their full-time studies. Current Learning Management Systems (LMS) do not address students’ individuality regarding their various levels of input knowledge and skills or their different learning styles, which, in our case, are based on sensory preferences. Therefore, this article proposes a model of an intelligent tutoring system to control learning by accentuating the individual needs of a student. The foundation stones of this system are an expert system and adaptation mechanisms. The expert system acts as a tool for the identification of students’ needs from the point of view of input knowledge and sensory preferences. Sensory preferences influence the student’s learning style. The implemented adaptation mechanisms control the progress of the student through a study unit. The model was implemented in the LMS Moodle environment. Regarding the focus of the research content, our model is oriented on the study of the English language, where each student receives a unique study plan, which is continuously adapted based on achieved results. We consider the focus on the individuality of the student to be an innovative approach that can be achieved automatically on a mass scale.
Object Detection in Remote Sensing Images by Combining Feature Enhancement and Hybrid Attention
Authors: Zheng Jin , Wang Tong , Zhang Zhi , Wang Hongwei
Published: June 2022

The objects in remote sensing images have large-scale variations, arbitrary directions, and are usually densely arranged, and small objects are easily submerged by background noises. They all hinder accurate object detection. To address the above problems, this paper proposes an object detection method combining feature enhancement and hybrid attention. Firstly, a feature enhancement fusion network (FEFN) is designed, which carries out dilated convolution with different dilation rates acting on the multi-layer features, and thus fuses multi-scale, multi-receptive field feature maps to enhance the original features. FEFN obtains more robust and discriminative features, which adapt to various objects with different scales. Then, a hybrid attention mechanism (HAM) module composed of pixel attention and channel attention is proposed. Through context dependence and channel correlation, introduced by pixel attention and channel attention respectively, HAM can make the network focus on object features and suppress background noises. Finally, this paper uses box boundary-aware vectors to determine the locations of objects and detect the arbitrary direction objects accurately, even if they are densely arranged. Experiments on public dataset DOTA show that the proposed method achieves 75.02% mAP, showing an improvement of 2.7% mAP compared with BBAVectors.
A Practical App for Quickly Calculating the Number of People Using Machine Learning and Convolutional Neural Networks
Authors: Lu Ching-Ta , Ou Chun-Jen , Lu Yen-Yu
Published: June 2022

Calculating the number of people is often necessary and repeated in real life. As the number of people increases, the calculation is time-consuming. Efficiently calculating the number of people is helpful to human life. In this article, we propose a valuable app to quickly calculate the number of people in a photo by a convolutional neural network (CNN). Initially, suspected face areas are segmented into micro-blocks. The segmented blocks are then confirmed through the CNN by rejecting the segmented micro-blocks without the human face to ensure the detection accuracy of the face area. The experimental results reveal that the proposed app can efficiently calculate the number of people. The world is now seriously threatened by the COVID-19 epidemic. The proposed app can help quickly calculate the number of people, avoid crowd gathering, and cause the risk of group infections.
An Enhanced Artificial Electric Field Algorithm with Sine Cosine Mechanism for Logistics Distribution Vehicle Routing
Authors: Zheng Hongyu , Gao Juan , Xiong Juxia , Yao Guanglei , Cui Hongjiang , Zhang Lirong
Published: June 2022

Aiming at the scheduling problem of logistics distribution vehicles, an enhanced artificial electric field algorithm (SC-AEFA) based on the sine cosine mechanism is proposed. The development of the SC-AEFA was as follows. First, a map grid model for enterprise logistics distribution vehicle path planning was established. Then, an enhanced artificial electric field algorithm with the sine cosine mechanism was developed to simulate the logistics distribution vehicle scheduling, establish the logistics distribution vehicle movement law model, and plan the logistics distribution vehicle scheduling path. Finally, a distribution business named fresh enterprise A in the Fuzhou Strait Agricultural and Sideline Products Trading Market was selected to test the effectiveness of the method proposed. The theoretical proof and simulation test results show that the SC-AEFA has a good optimization ability and a strong path planning ability for enterprise logistics vehicle scheduling, which can improve the scheduling ability and efficiency of logistics distribution vehicles and save transportation costs.
Product Model Derivation from Feature Model and Formal Specification
Authors: Wang Xi , Wang Weiwei , Liu Hongbo
Published: June 2022

Product derivation is the process of building a specific product from a software product line. Effective product derivation can improve software reuse productivity. Existing methods can only obtain abstract feature models, lacking detailed specifications of individual features. They are more about deriving code assets or class diagram templates without precise model descriptions for specific products. This article proposes a product derivation approach to obtain a formal specification of a specific product based on the feature model and formal specification. We use the integration ordering and behavior preserving integration techniques to integrate the formal specification for each feature pair. The method is divided into two steps. First, it determines the feature formal specification integration ordering based on the feature model. Then, the behavior-preserving integration will be conducted for pairs, including declaration integration, functional scenario path generation, and function integration based on path matching. Behavior preserving integration guarantees consistent behavior to ensure the quality of the formal specification after integration. Finally, we developed a support tool to conduct a case study. The tool first guides the user to perform feature functional scenario path matching, then performs functional integration based on the matching results and repeats the above steps to generate a product model. The result indicates that our method facilitates the derivation process and improves the quality of the generated models.
Aerodynamic Characteristics When Trains Pass Each Other in High-Speed Railway Shield Tunnel
Authors: Li Feilong , Luo Jianjun , Wang Dengke , Wang Lei
Published: June 2022

The characteristics of the aerodynamic effects of high-speed trains passing in a shield tunnel were studied using the three-dimensional, compressible, unsteady Reynolds-averaged Navier-Stokes (RANS) equations for the simulation analysis. Numerical calculations were compared with dynamic model tests to verify the reliability of the numerical simulations. The results showed that the compression wave characteristics of high-speed trains in shield tunnels were consistent with those in molded concrete tunnels. When high-speed trains met in the middle of the shield tunnel, the positive and negative peak attenuation rates of shield tunnels were higher than the positive and negative peak attenuation rates of molded lining tunnels, and the maximum pressure attenuation rate could reach 57.8%. At the same time, the micro-pressure wave of the former was reduced by 10.78%, compared with those of the latter. When meeting cars at different locations, the maximum pressure at the intersection in the center of the tunnel was significantly higher than those at other intersection points in the tunnel. Different intersection positions and different tunnel lining structures had relatively little influence on the aerodynamic drag and lateral force, while train speed had a significant influence.
Unfair and Risky? Profit Allocation in Closed-Loop Supply Chains by Cooperative Game Approaches
Authors: Zeng Ting , Yang Tianjian
Published: June 2022

Behavioral factors (i.e., risk aversion and fairness concern) are considered for profit allocation in a closed-loop supply chain. This paper studies a two-echelon closed-loop supply chain (CLSC) consisting of a risk-neutral manufacturer, a risk-averse fairness-neutral retailer, and a risk-neutral retailer having fairness concerns. Cooperative game analysis is used to characterize equilibriums under five scenarios: a centralized, a decentralized and three partially allied models. Analytical results confirm that even when factoring in retailers’ risk aversion and fairness concern, the centralized model still outperforms decentralized. This paper makes a numerical study on the effects of risk aversion and fairness concern on profit distribution under these five models. It reveals that the impact of the risk aversion parameter and fairness concern parameter is dynamic, not always positive or negative. These research results provide helpful insights for CLSC managers to find out available choices and feasible ways to achieve fair profit allocations.
Construction and Evaluation of Prediction Model of Main Soil Nutrients Based on Spectral Information
Authors: Yu Siyao , Bu Haoran , Dong Wancheng , Jiang Zhen , Zhang Lixin , Xia Yuanqing
Published: June 2022

The rapid and accurate detection of soil nutrient content through spectral technology is one of the requisite technologies for precision fertilization, which, however, is an unsolved issue. In order to achieve this purpose, a more robust and accurate model is established in this study. The regression algorithm is integrated with effective wavelength selection to construct the prediction model for total nitrogen, available phosphorus, and available potassium (N, P, and K), which removes the need for complex pretreatment and algorithm constraints. According to the research results, with regard to the prediction of soil nitrogen, phosphorus, and potassium contents, the joint interval support vector regression (Si-SVR) model performed best in modeling, with the root mean square error of prediction (RMSEP) limited to 0.0231%, 1.0554%, and 3.4225%, respectively. In addition, the relative percentage deviation (RPD) values were restricted to 2.68, 2.12, and 2.37, respectively. As indicated by the prediction results obtained for the above three nutrient contents, the RPD values of the Si-SVR model prediction accuracy evaluation indicators exceeded 2.0, which evidences a high level of prediction accuracy. This method makes it possible for spectral data to be applied in practical production, and these results provide a valuable reference for the effective detection of major soil nutrients.
Microencapsulation of Bacteriophages for the Delivery to and Modulation of the Human Gut Microbiota through Milk and Cereal Products
Authors: Schubert Christina , Fischer Sabina , Dorsch Kathrin , Teßmer Lutz , Hinrichs Jörg , Atamer Zeynep
Published: June 2022

There is a bidirectional interaction between the gut microbiota and human health status. Disturbance of the microbiota increases the risk of pathogen infections and other diseases. The use of bacteriophages as antibacterial therapy or prophylaxis is intended to counteract intestinal disorders. To deliver bacteriophages unharmed into the gut, they must be protected from acidic conditions in the stomach. Therefore, an encapsulation method based on in situ complexation of alginate (2%), calcium ions (0.5%), and milk proteins (1%) by spray drying was investigated. Powdered capsules with particle sizes of ~10 µm and bacteriophage K5 titers of ~107 plaque-forming units (pfu) g−1 were obtained. They protected the bacteriophages from acid (pH 2.5) in the stomach for 2 h and released them within 30 min under intestinal conditions (in vitro). There was no loss of viability during storage over two months (4 °C). Instead of consuming bacteriophage capsules in pure form (i.e., as powder/tablets), they could be inserted into food matrices, as exemplary shown in this study using cereal cookies as a semi-solid food matrix. By consuming bacteriophages in combination with probiotic organisms (e.g., via yoghurt with cereal cookies), probiotics could directly repopulate the niches generated by bacteriophages and, thus, contribute to a healthier life.
Simulation Oriented Layer of Embedded Software Architecture for Rapid Development of Custom Embedded Systems Virtual Simulators Used in Didactics
Authors: Radecki Andrzej , Rybicki Tomasz
Published: June 2022

The application of the proposed Simulation Oriented Layer in the embedded-software architecture is shown in this paper. The SOL’s purpose is to deliver only limited and highly desirable microprocessor-system functionality to the Application Layer, which would be implemented in a virtual simulator without requiring its complex development. It was used in two virtual simulators of embedded systems, as presented in the article. Each virtual simulator covers one customized embedded system (RPILAB and TMSLAB) used for didactical purposes. On each embedded platform, a different method of system-functionality simulation was shown. Presented virtual simulators can run recompiled (for the virtual-simulator platform) programs in a seamless process, giving real-like experiences for programmers, who can verify and test their high-level solutions. Being accurately chosen, taken for the simulation because of essential and limited functionality, and used in the Application Layer allowed for the rapid design of the virtual simulators. Unit- and functional-test results using RPILAB- and TMSLAB-embedded systems and their virtual simulators are shown in this paper. Both simulators of real RPILAB and TMSLAB platforms are used with success in the didactical process, at the Institute of Automatic Control in Lodz University of Technology, since the COVID-19 pandemic.
Precipitable Water Content Climatology over Poland
Authors: Ojrzyńska Hanna , Błaś Marek , Kryza Maciej
Published: June 2022

In this work, the high-resolution spatial and temporal variability of precipitable water (PW) over Poland is presented. PW is one of the key parameters of the atmosphere taken into account in thermodynamic and radiation models. The daily PW values from years 2001–2010, calculated with the use of the WRF model, were compared with PW from soundings. The WRF modeled PW is in close agreement with measurements for the whole column of the troposphere and for individual levels: below 1.5 km, 1.5–3 km, 3–6 km and 6–10 km. The best agreement is observed in the lower part of the troposphere, especially for winter months. At the levels of 1.5 km to 10 km, the WRF model overestimates the PW values throughout the year, whereas up to 1.5 km PW is underestimated. The study shows an increasing trend of PW annual values between 1983 and 2010, but the trend is statistically insignificant. A significant positive trend with a high Sen’s slope is observed for the summer season up to 3 km in the troposphere, along with a significant negative tendency for spring. The trends in PW over Poland and Central Europe identified in this study contribute to the ongoing discussion on the observed climate changes.
Comparison of East Asian Summer Monsoon Simulation between an Atmospheric Model and a Coupled Model: An Example from CAS-ESM
Authors: Zhang Wen , Xue Feng , Jin Jiangbo , Dong Xiao , Zhang He , Lin Renping
Published: June 2022

In this study, the Chinese Academy of Sciences’ Earth System Model Version 2 (CAS-ESM2) and its atmospheric component were evaluated for the ability to simulate the East Asian summer monsoon (EASM), in terms of climatology and composites in El Niño decaying years (EN) and La Niña years (LN). The results show that the model can realistically simulate the El Niño Southern Oscillation (ENSO) annual cycle, the interannual variation, the evolution process, and the prerequisites of ENSO, but the trend of developing and decaying is faster than that of the observations. With regard to the climatological mean state in the EASM, the coupled model run can largely improve the precipitation and 850 hPa wind simulated in the atmospheric model. Moreover, the coupled run can also reduce the mid-latitude bias in the atmospheric model simulation. Composite methods were then adopted to examine performance in different phases of the ENSO, from a mature winter to a decaying summer. The atmospheric model can well reproduce the Western North Pacific Anomalous Anticyclone (WNPAC)/Western North Pacific Anomalous Cyclone (WNPC) during EN/LN well, but the westerly/easterly anomalies and the associated precipitation anomalies over the equatorial Central Eastern Pacific are somewhat overestimated. Compared with the atmospheric model, these anomalies are all underestimated in the coupled model, which may be related to the ENSO-related SST bias appearing in the Eastern Indian Ocean. Due to the ENSO and ITCZ bias in the historical simulations, the simulated ENSO-related SST and the precipitation anomaly are too equator-trapped in comparison with the observations, and the cold tongue overly extends westward. This limits the ability of the model to simulate ENSO-related EASM variability. For the subseasonal simulations, though atmospheric model simulations can reproduce the westward extension of the Western Pacific subtropic high (WPSH) in EN decaying summers, the eastward retreat of the WPSH in LN is weak. The historical simulations show limited improvement, indicating that the subseasonal variation in the EASM is still a considerable challenge for current generation models.
Smooth Versions of the Mann–Whitney–Wilcoxon Statistics
Authors: Herawati Netti , Ahmad Ibrahim A.
Published: June 2022

The well-known Mann–Whitney–Wilcoxon (MWW) statistic is based on empirical distribution estimates. However, the data are often drawn from smooth populations. Therefore, the smoothness characteristic is not preserved. In addition, several authors have pointed out that empirical distribution is often an inadmissible estimate. Thus, in this work, we develop smooth versions of the MWW statistic based on smooth distribution function estimates. This approach preserves the data characteristics and allows the efficiency of the procedure to improve. In addition, our procedure is shown to be robust against a large class of dependent observations. Hence, by choosing a rectangular array of known distribution functions, our procedure allows the test to be a lot more reflective of the real data.
Biomechanical Analysis of the Use of Stems in Revision Total Knee Arthroplasty
Authors: Innocenti Bernardo , Bori Edoardo , Pianigiani Silvia
Published: June 2022

Adequate fixation is fundamental in revision total knee arthroplasty; consequently, surgeons must determine the correct set-up for each patient, choosing from numerous stem solutions. Several designs are currently available on the market, but there are no evidence-based quantitative biomechanical guideline yet. Therefore, several stems were designed and analyzed using a previously-validated finite-element model. The following parameters were studied: stem design characteristics (length and shape), added features (straight/bowed stem), fixation technique, and effect of slots/flutes. Bone stress and Risk of Fracture (RF) were analyzed in different regions of interest during a squat (up to 120°). For the femoral stem, the results indicated that all parameters influenced the bone stress distribution. The maximum von Mises stress and RF were always located near the tip of the stem. The long stems generated stress-shielding in the distal bone. Regarding the tibial stem, cemented stems showed lower micromotions at the bone-tibial tray interface and at the stem tip compared to press-fit stems, reducing the risk of implant loosening. The results demonstrated that anatomical shapes and slots reduce bone stress and risk of fracture, whereas flutes have the opposite effect; no relevant differences were found in this regard when alternating cemented and press-fit stem configurations. Cemented tibial stems reduce antero-posterior micromotions, preventing implant loosening.
Effectiveness of the REvision System and Sonic Irrigation in the Removal of Root Canal Filling Material from Oval Canals: An In Vitro Study
Authors: Kaloustian Marc Krikor , Hachem Claire El , Zogheib Carla , Nehme Walid , Hardan Louis , Rached Pamela , Kharouf Naji , Haikel Youssef , Mancino Davide
Published: June 2022

This study aimed to evaluate the effectiveness of the Endostar REvision system (Poldent, Warsaw, Poland) in the removal of filling materials from oval root canals using sonic irrigation as an additional cleaning method. Thirty human-extracted mandibular premolars with oval canals were prepared using the ProTaper Universal system (Dentsply Maillefer, Ballaigues, Switzerland) up to instrument F1 (20/.07), and then filled by the continuous wave vertical compaction technique using pulp canal sealer EWT (Sybron Dental Specialties, Orange, CA, USA). The teeth were randomly divided into two groups (n = 15) according to the instrumentation system and the additional cleaning method, as follows: REvision (30/.08, 25/.06) with EQ-S sonic activation (Meta Biomed, Chungcheongbuk-do, Korea), REvision (30/.08, 25/.06) without additional activation. All specimens were sectioned longitudinally at 3 and 7 mm from the apex, and analyzed using digital microscopy (KEYENCE, Osaka, Japan) to measure the total area of the residual obturation materials, followed by SEM analysis. The data on the percentage of remaining filling material were analyzed by Kruskal–Wallis one-way Analysis of Variance on ranks. None of the retreatment protocols completely removed the filling material from the root canals (p > 0.05); the retreatment technique using sonic activation showed statistically less residual filling materials than the retreatment technique using irrigants without activation at the coronal third (p < 0.05), whilst no significant difference was found between both tested groups at the apical and middle thirds (p > 0.05). The REvision system showed promising results in the removal of filling materials from oval canals.
Proof of Concept of Biopolymer Based Hydrogels as Biomimetic Oviposition Substrate to Develop Tiger Mosquitoes (Aedes albopictus) Cost-Effective Lure and Kill Ovitraps
Authors: Friuli Marco , Cafarchia Claudia , Cataldo Andrea , Lia Riccardo Paolo , Otranto Domenico , Pombi Marco , Demitri Christian
Published: June 2022

Pest management is looking for green and cost-effective innovative solutions to control tiger mosquitoes and other pests. By using biomimetic principles and biocompatible/biodegradable biopolymers, it could be possible to develop a new approach based on substrates that selectively attract insects by reproducing specific natural environmental conditions and then kill them by hosting and delivering a natural biopesticide or through mechanical action (biomimetic lure and kill approach, BL&K). Such an approach can be theoretically specialized against tiger mosquitoes (BL&K-TM) by designing hydrogels to imitate the natural oviposition site’s conditions to employ them inside a lure and kill ovitraps as a biomimetic oviposition substrate. In this work, the hydrogels have been prepared to prove the concept. The study compares lab/on-field oviposition between standard substrates (absorbing paper/masonite) and a physical and chemically crosslinked hydrogel composition panel. Then the best performing is characterized to evaluate a correlation between the hydrogel’s properties and oviposition. Tests identify a 2-Hydroxyethylcellulose (HEC)-based physical hydrogel preparation as five times more attractive than the control in a lab oviposition assay. When employed on the field in a low-cost cardboard trap, the same substrate is seven times more capturing than a standard masonite ovitrap, with a duration four times longer.
Role of mTOR Signaling Cascade in Epidermal Morphogenesis and Skin Barrier Formation
Authors: Wang Juan , Eming Sabine A. , Ding Xiaolei
Published: June 2022

The skin epidermis, with its capacity for lifelong self-renewal and rapid repairing response upon injury, must maintain an active status in metabolism. Mechanistic target of rapamycin (mTOR) signaling is a central controller of cellular growth and metabolism that coordinates diverse physiological and pathological processes in a variety of tissues and organs. Recent evidence with genetic mouse models highlights an essential role of the mTOR signaling network in epidermal morphogenesis and barrier formation. In this review, we focus on the recent advances in understanding how mTOR signaling networks, including upstream inputs, kinases and downstream effectors, regulate epidermal morphogenesis and skin barrier formation. Understanding the details of the metabolic signaling will be critical for the development of novel pharmacological approaches to promote skin barrier regeneration and to treat epidermal barrier defect-associated diseases.