bluuebunny/crossref_metadata_2025 huggingface dataset:
Oxidative Stress Induced by High Salt Diet—Possible Implications for Development and Clinical Manifestation of Cutaneous Inflammation and Endothelial Dysfunction in Psoriasis vulgaris
Authors: Krajina Ivana , Stupin Ana , Šola Marija , Mihalj Martina
Published: June 2022

Although oxidative stress is recognized as an important effector mechanism of the immune system, uncontrolled formation of reactive oxygen and nitrogen species promotes excessive tissue damage and leads to disease development. In view of this, increased dietary salt intake has been found to damage redox systems in the vessel wall, resulting in endothelial dysfunction associated with NO uncoupling, inflammation, vascular wall remodeling and, eventually, atherosclerosis. Several studies have reported increased systemic oxidative stress accompanied by reduced antioxidant capacity following a high salt diet. In addition, vigorous ionic effects on the immune mechanisms, such as (trans)differentiation of T lymphocytes are emerging, which together with the evidence of NaCl accumulation in certain tissues warrants a re-examination of the data derived from in vitro research, in which the ionic influence was excluded. Psoriasis vulgaris (PV), as a primarily Th17-driven inflammatory skin disease with proven inflammation-induced accumulation of sodium chloride in the skin, merits our interest in the role of oxidative stress in the pathogenesis of PV, as well as in the possible beneficial effects that could be achieved through modulation of dietary salt intake and antioxidant supplementation.
The Interaction between Carbon Monoxide and Hydrogen Sulfide during Chronic Joint Pain in Young Female Mice
Authors: Batallé Gerard , Bai Xue , Pol Olga
Published: June 2022

A relationship between carbon monoxide (CO) and hydrogen sulfide (H2S) has been described in different pathological conditions, but their interaction in modulating joint pain has not yet been investigated. In young female mice with monosodium acetate-induced joint degeneration and pain, we assessed: (1) the effects of CORM-2 (tricarbonyldichlororuthenium(II)dimer), a CO-releasing molecule, and CoPP (cobalt protoporphyrin IX), an inducer of heme oxygenase 1 (HO-1), administered alone and combined with low doses of two slow-releasing H2S donors, DADS (diallyl disulfide) and GYY4137 (morpholin-4-ium 4-methoxyphenyl(morpholino) phosphinodithioate dichloromethane complex) on the mechanical allodynia and loss of grip strength provoked by joint degeneration; (2) the role of Nrf2, NAD(P)H: quinone oxidoreductase 1 (NQO1) and HO-1 in the antinociceptive actions of H2S donors; (3) the impact of DADS and GYY4137 treatment on the expression of Nrf2 and several antioxidant proteins in dorsal root ganglia (DRG) and periaqueductal gray matter (PAG). Our data showed that treatment with H2S donors inhibited allodynia and functional deficits, while CORM-2 and CoPP only prevented allodynia. The Nrf2 pathway is implicated in the analgesic actions of DADS and GYY4137 during joint degeneration. Moreover, the co-administration of low doses of CORM-2 or CoPP with DADS or GYY4137 produced higher antiallodynic effects and greater recovery of grip strength deficits than those produced by each of these compounds alone. The activation of the antioxidant system caused by H2S donors in DRG and/or PAG might explain the enhancement of antinociceptive effects. These data reveal a positive interaction between H2S and CO in modulating joint pain in female mice.
The Synergetic Effect of Egyptian Portulaca oleracea L. (Purslane) and Cichorium intybus L. (Chicory) Extracts against Glucocorticoid-Induced Testicular Toxicity in Rats through Attenuation of Oxidative Reactions and Autophagy
Authors: Saleh Samar R. , Manaa Ashraf , Sheta Eman , Ghareeb Doaa A. , Abd-Elmonem Nihad M.
Published: June 2022

Long-term glucocorticoids can alter sperm motility, vitality, or morphology, disrupting male reproductive function. This study scrutinized the synergistic benefits of two Egyptian plants against dexamethasone (Dexa)-induced testicular and autophagy dysfunction in male rats. Phytochemical ingredients and the combination index were estimated for Purslane ethanolic extract (PEE) and Chicory water extract (CWE). Four control groups received saline and 100 mg/kg of each PEE, CWE, and PEE/CWE, daily for 8 weeks. Dexa (1 mg/kg daily for 6 weeks) induced infertility where PEE, CWE, and PEE/CWE were given. Seminal analysis, male hormones, glycemic and oxidative stress markers, endoplasmic reticulum (ER) stress markers (Sigma 1R and GRP78), and autophagy regulators (Phospho-mTOR, LC3I/II, PI3KC3, and Beclin-1, P62, ATG5, and ATG7) were measured. The in vitro study illustrated the synergistic (CI < 1) antioxidant capacity of the PEE/CWE combination. Dexa exerts testicular damage by inducing oxidative reactions, a marked reduction in serum testosterone, TSH and LH levels, insulin resistance, ER stress, and autophagy. In contrast, the PEE and CWE extracts improve fertility hormones, sperm motility, and testicular histological alterations through attenuating oxidative stress and autophagy, with a synergistic effect upon combination. In conclusion, the administration of PEE/CWE has promised ameliorative impacts on male infertility and can delay disease progression.
Circadian and Tidal Changes in Snapping Shrimp (Alpheus brevicristatus) Sound Observed by a Moored Hydrophone in the Coastal Sea of Western Jeju
Authors: Jeong Inyong , Paeng Dong-Guk
Published: June 2022

Numerous studies have evaluated the acoustic characteristics of soniferous snapping shrimp, but a few are based on long-term mooring measurements. In this study, underwater ambient noise signals were collected from a hydrophone moored 10 m from the sea bed in the coastal sea of western Jeju, South Korea, from mid-September 2019 for 90 days to analyze the variation in the sound of snapping shrimp. The kernel signal and a threshold value were utilized to identify the snapping shrimp, and the snap rate per minute was computed for quantitative analysis. The results show that the mean and standard deviation of the snap rate in the western sea of Jeju was 2132 ± 432 per minute during the whole measurement period. The surface water temperature and tidal level decreased by 7 °C from 25 °C and 50 cm from 190 cm, respectively, over 90 days. The snap rate decreased from September mainly due to the decrease in water temperature by 71 times per minute for every 1 °C decrease. It showed a circadian cycle, increasing by 17~24% at sunrise and sunset compared to the daytime minimum. The snap rate at night was the highest in late summer but the rate dropped like the one during the day in late fall. The snap rate at high tide was 13% higher on average than at low tide. The circadian and tidal changes of the snapping shrimp sound from long-term mooring measurements may be used as primary data for underwater ambient noise and the ecological behavior of snapping shrimp.
Estimation of the Underlying F0 Range of a Speaker from the Spectral Features of a Brief Speech Input
Authors: Zhang Wei , Xie Yanlu , Lin Binghuai , Wang Liyuan , Zhang Jinsong
Published: June 2022

From a very brief speech, human listeners can estimate the pitch range of the speaker and normalize pitch perception. Spectral features which inherently involve both articulatory and phonatory characteristics were speculated to play roles in this process, but few were reported to directly correlate with speaker’s F0 range. To mimic this human auditory capability and validate the speculation, in a preliminary study we proposed an LSTM-based method to estimate speaker’s F0 range from a 300 ms-long speech input, which turned out to outperform the conventional method. By two more experiments, this study further improved the method and verified its validity in estimating the speaker-specific underlying F0 range. After incorporating a novel measurement of F0 range and a multi-task training approach, Experiment 1 showed that the refined model gave more accurate estimates than the initial model. Based on a Japanese-Chinese bilingual parallel speech corpus, Experiment 2 found that the F0 ranges estimated with the model from the Chinese speech and the model from the Japanese speech produced by the same set of speakers had no significant difference, whereas the conventional method showed significant difference. The results indicate that the proposed spectrum-based method captures the speaker-specific underlying F0 range which is independent of the linguistic content.
Dynamic Modeling of a Flexible-Link Flexible-Joint System with Tip Mass Considering Stiffening Effect
Authors: Tang Lewei , Zhao Dengbiao
Published: June 2022

This paper presents the dynamic model of a flexible-link, flexible-joint manipulator system with a considerable stiffening effect of the flexible link. A gripper, along with tip mass, is attached at one end of the flexible link. By employing the extended Hamilton’s principle, a nonlinear governing equation of motion is derived along with several boundary constraints. Under the assumption of small deformation in free vibration, a simplified motion equation is deduced to determine the natural frequencies of the mechanical system. Four parameters of the system are selected to carry out the sensitivity study on frequency. The results show that the second frequency mainly depends on the mass of tip payload. Moreover, the third frequency is significantly affected by the moment inertia of tip payload. Regarding the constant angular motion, the finite element method is adopted to analyze the dynamic model by considering the stiffening effect. The frequency results are obtained which show a higher stiffness of the Single Flexible-link Flexible-joint (SFF) system with the angular velocity increasing. The influence of three factors (i.e., payload mass, length of the flexible link, and angular velocity) on the fundamental natural frequencies are discussed, which show instinct characteristics of the flexible manipulator system.
Automatic Generation and Evaluation of Chinese Classical Poetry with Attention-Based Deep Neural Network
Authors: Zhao Jianli , Lee Hyo Jong
Published: June 2022

The computer generation of poetry has been studied for more than a decade. Generating poetry on a human level is still a great challenge for the computer-generation process. We present a novel Transformer-XL based on a classical Chinese poetry model that employs a multi-head self-attention mechanism to capture the deeper multiple relationships among Chinese characters. Furthermore, we utilized the segment-level recurrence mechanism to learn longer-term dependency and overcome the context fragmentation problem. To automatically assess the quality of the generated poems, we also built a novel automatic evaluation model that contains a BERT-based module for checking the fluency of sentences and a tone-checker module to evaluate the tone pattern of poems. The poems generated using our model obtained an average score of 9.7 for fluency and 10.0 for tone pattern. Moreover, we visualized the attention mechanism, and it showed that our model learned the tone-pattern rules. All experiment results demonstrate that our poetry generation model can generate high-quality poems.
Network Attack Detection Method of the Cyber-Physical Power System Based on Ensemble Learning
Authors: Cao Jie , Wang Da , Wang Qi-Ming , Yuan Xing-Liang , Wang Kai , Chen Chin-Ling
Published: June 2022

With the rapid development of power grid informatization, the power system has evolved into a multi-dimensional heterogeneous complex system with high cyber-physical integration, denoting the Cyber-Physical Power System (CPPS). Network attack, in addition to faults, becomes an important factor restricting the stable operation of the power system. Under the influence of network attacks, to improve the operational stability of CPPSs, this paper proposes a CPPS network attack detection method based on ensemble learning. First, to solve the shortcomings of a low detection precision caused by insufficient network attack samples, a power data balancing processing method was proposed. Then, the LightGBM ensemble was constructed to detect network attack events and lock the fault points caused by the attack. At the same time, in the process of gradient boost, the focal loss was introduced to optimize the attention weight of the classifier to the misclassified samples, thus improving the network attack detection precision. Finally, we propose an effective evaluation method of the network attack detection model based on cyber-physical comprehensive consideration. In addition, the cyber-physical power system stability under the action of the network attack detection model is quantitatively analyzed. The experimental results show that the F1 score of network attack detection increases by 16.73%, and the precision increases by 15.67%.
Intelligent Manufacturing Planning System Using Dispatch Rules: A Case Study in Roofing Manufacturing Industry
Authors: Ren Samuel Ching Xin , Chaw Jun Kit , Lim Yee Mei , Lee Wah Pheng , Ting Tin Tin , Fong Cheng Weng
Published: June 2022

This paper aims to investigate the optimal sorting of orders reflecting on the material changing lead time over the machines in the roofing manufacturing industry. Specifically, a number of jobs were sorted together based on the material used and then consolidated for subsequent processes, i.e., assigned to the corresponding machines. To achieve the optimal sorting for the received orders, a combinatorial dispatch rule was proposed, which were Earliest Due Date (EDD), First In First Out (FIFO), and Shortest Processing Time (SPT). The sequence of orders organized by the scheduling algorithm was able to minimize the changing material lead time and also maximize the number of orders to be scheduled in the production. Consequently, on-time delivery could be achieved. Tests based on real data have been set up to evaluate the performance of the proposed algorithm in sorting the received orders. As a result, the proposed algorithm has successfully reduced the material changing lead time by 47.3% and 40% in the first and second tests, respectively.
How Much Does the Variety of Scenery and the Different Percentages of Audience Occupancy Affect the Indoor Acoustics at the National Theater of Zagreb?
Authors: Tronchin Lamberto , Bevilacqua Antonella
Published: June 2022

The performance of opera and the post-pandemic slow recovery of the public, who have been hesitant to return to frequent attendance of cultural venues, has inspired the authors to analyze the acoustic behavior of the National Theater of Zagreb, by reflecting five specific scenarios. Starting from acoustic measurements undertaken inside the National Theater of Zagreb without any scenery in place, this research study compares the main acoustic parameters simulated with the scenery of Tosca in three different acts. A numerical model was realized by reproducing the geometry and the architectural features of this historic performance arts space. Before the simulations, the absorption coefficients applied to the digital entities were calibrated with the values gathered from the recorded impulse responses. After the calibration process, the acoustic simulations were also carried out with the presence of an audience at two percentages of occupancy.
The Development Progress of Surface Structure Diffraction Gratings: From Manufacturing Technology to Spectroscopic Applications
Authors: Wang Ye , Fu Xiuhua , Chen Yongyi , Qin Li , Ning Yongqiang , Wang Lijun
Published: June 2022

The high-precision diffraction grating is an important chromatic dispersion component that has been widely used in many fields, including laser beam combining, chirped pulse compression, spectroscopy, among others. In this paper, we review the development status of reflection and transmission gratings with high diffraction efficiency and high laser-induced damage thresholds, such as metal-film and multilayer-dielectric-film gratings. Then, we review the basic principles and most recent stages in the development of manufacturing techniques, such as mechanical scribing, holographic exposure, electron-beam lithography, and nanoimprinting.
Special Issue on Wastewater Treatment Technologies
Authors: Yu Jaecheul
Published: June 2022

Wastewater treatment technology has a history spanning thousands of years, while the activated sludge process is only 100 years old [...]
A Practical Multiclass Classification Network for the Diagnosis of Alzheimer’s Disease
Authors: Khan Rizwan , Qaisar Zahid Hussain , Mehmood Atif , Ali Ghulam , Alkhalifah Tamim , Alturise Fahad , Wang Lingna
Published: June 2022

Patients who have Alzheimer’s disease (AD) pass through several irreversible stages, which ultimately result in the patient’s death. It is crucial to understand and detect AD at an early stage to slow down its progression due to the non-curable nature of the disease. Diagnostic techniques are primarily based on magnetic resonance imaging (MRI) and expensive high-dimensional 3D imaging data. Classic methods can hardly discriminate among the almost similar pixels of the brain patterns of various age groups. The recent deep learning-based methods can contribute to the detection of the various stages of AD but require large-scale datasets and face several challenges while using the 3D volumes directly. The extant deep learning-based work is mainly focused on binary classification, but it is challenging to detect multiple stages with these methods. In this work, we propose a deep learning-based multiclass classification method to distinguish amongst various stages for the early diagnosis of Alzheimer’s. The proposed method significantly handles data shortage challenges by augmentation and manages to classify the 2D images obtained after the efficient pre-processing of the publicly available Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. Our method achieves an accuracy of 98.9% with an F1 score of 96.3. Extensive experiments are performed, and overall results demonstrate that the proposed method outperforms the state-of-the-art methods in terms of overall performance.
Exploring Space Syntax Integration at Public Transport Hubs and Public Squares Using Drone Footage
Authors: Johnsson Carl , Camporeale Rosalia
Published: June 2022

Space Syntax theory is a methodological framework for describing and analysing the relationships between spaces and buildings. The fundamental building blocks of Space Syntax are called axial lines, which represent lines of sight from a specific point in space. These lines can then be used to quantitatively analyse the integration (or attractiveness) of an area. However, many public squares and transport hubs are crossed by roads which prove a hinderance when walking although not impairing the sightlines of pedestrians. The aim of this paper is to test how this limitation affects the concept and whether Space Syntax is still useful to understand how people move in such areas. Seven public squares and transport hubs in Malmö (Sweden) were selected and their Space Syntax integration was calculated. These values were compared with pedestrian detections from the same areas based on video recordings from a drone. When aggregating the areas into several levels based on their integration value, the result shows a clear link between Space Syntax integration and the number of pedestrian detections made at each location, demonstrating how this measure could be useful for understanding micromobility usage on a small scale.
Grammatically Derived Factual Relation Augmented Neural Machine Translation
Authors: Li Fuxue , Zhu Jingbo , Yan Hong , Zhang Zhen
Published: June 2022

Transformer-based neural machine translation (NMT) has achieved state-of-the-art performance in the NMT paradigm. This method assumes that the model can automatically learn linguistic knowledge (e.g., grammar and syntax) from the parallel corpus via an attention network. However, the attention network cannot capture the deep internal structure of a sentence. Therefore, it is natural to introduce some prior knowledge to guide the model. In this paper, factual relation information is introduced into NMT as prior knowledge, and a novel approach named Factual Relation Augmented (FRA) is proposed to guide the decoder in Transformer-based NMT. In the encoding procedure, a factual relation mask matrix is constructed to generate the factual relation representation for the source sentence, while in the decoding procedure an effective method is proposed to incorporate the factual relation representation and the original representation of the source sentence into the decoder. Positive results obtained in several different translation tasks indicate the effectiveness of the proposed approach.
Design of Platforms for Experimentation in Industrial Cybersecurity
Authors: Domínguez Manuel , Fuertes Juan J. , Prada Miguel A. , Alonso Serafín , Morán Antonio , Pérez Daniel
Published: June 2022

The connectivity advances in industrial control systems have also increased the possibility of cyberattacks in industry. Thus, security becomes crucial in critical infrastructures, whose services are considered essential in fields such as manufacturing, energy or public health. Although theoretical and formal approaches are often proposed to advance in the field of industrial cybersecurity, more experimental efforts in realistic scenarios are needed to understand the impact of incidents, assess security technologies or provide training. In this paper, an approach for cybersecurity experimentation is proposed for several industrial areas. Aiming at a high degree of flexibility, the Critical Infrastructure Cybersecurity Laboratory (CICLab) is designed to integrate both real physical equipment with computing and networking infrastructure. It provides a platform for performing security experiments in control systems of diverse sectors such as industry, energy and building management. They allow researchers to perform security experimentation in realistic environments using a wide variety of technologies that are common in these control systems, as well as in the protection or security analysis of industrial networks. Furthermore, educational developments can be made to meet the growing demand of security-related professionals.
A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube
Authors: Al-amri Redhwan , Murugesan Raja Kumar , Almutairi Mubarak , Munir Kashif , Alkawsi Gamal , Baashar Yahia
Published: June 2022

As applications generate massive amounts of data streams, the requirement for ways to analyze and cluster this data has become a critical field of research for knowledge discovery. Data stream clustering’s primary objective and goal are to acquire insights into incoming data. Recognizing all possible patterns in data streams that enter at variable rates and structures and evolve over time is critical for acquiring insights. Analyzing the data stream has been one of the vital research areas due to the inevitable evolving aspect of the data stream and its vast application domains. Existing algorithms for handling data stream clustering consider adding various data summarization structures starting from grid projection and ending with buffers of Core-Micro and Macro clusters. However, it is found that the static assumption of the data summarization impacts the quality of clustering. To fill this gap, an online clustering algorithm for handling evolving data streams using a tempo-spatial hyper cube called BOCEDS TSHC has been developed in this research. The role of the tempo-spatial hyper cube (TSHC) is to add more dimensions to the data summarization for more degree of freedom. TSHC when added to Buffer-based Online Clustering for Evolving Data Stream (BOCEDS) results in a superior evolving data stream clustering algorithm. Evaluation based on both the real world and synthetic datasets has proven the superiority of the developed BOCEDS TSHC clustering algorithm over the baseline algorithms with respect to most of the clustering metrics.
Effect of Buildings on the Radiation Characteristics of MF Broadcast Antennas
Authors: Liodakis George S. , Ioannidou Melina P. , Petrakis Nikolaos S. , Baklezos Anargyros T. , Kapetanakis Theodoros N. , Nikolopoulos Christos D. , Vardiambasis Ioannis O.
Published: June 2022

This study aims to investigate the impact of the presence of buildings on the radiation characteristics of MF broadcast antennas. Two different antennas are considered: a monopole operating at 1494 kHz and a two-element linear array radiating at 1008 kHz. The buildings were modeled as wire-grids and the total electric field intensity was calculated as the sum of the scattered field by the wire-grid and the field radiated from the antenna in free space. The radiation pattern of the antennas, when one or two buildings were situated in their vicinity, were the end result of the analysis, and they were compared to the corresponding patterns in free space. The results demonstrate that the radiation characteristics of antennas are mostly affected by the heights of buildings. If these heights are less than a critical value, the buildings do not significantly obstruct the operation of the antenna, despite the value of other parameters, such as the length and the width of the buildings, as well as their distance from the antenna.
Fault Detection in Offshore Structures: Influence of Sensor Number, Placement and Quality
Authors: Tockner Andreas , Lei Jixiang , Ellermann Katrin
Published: June 2022

Within the Space@Sea project floating offshore islands, designed as an assembly of platforms, are used to create space in offshore environments. Offshore structures are exposed to harsh environment conditions. High wind speeds, heavy rainfall, ice and wave forces lead to highly stressed structures. The platforms at the Space@Sea project are connected by ropes and fenders. There exists the risk of a rope failing which is therefore investigated subsequently. To ensure the safety of the structure, the rope parameters are monitored by the Extended Kalman Filter (EKF). For platform arrangements, a large number of sensors is required for accurate fault diagnosis of these ropes, leading to high investment costs. This paper presents a strategy to optimize the number and placement of acceleration sensors attached to the floating platforms. There are also high demands on the sensors due to the harsh offshore conditions. Material deterioration and overloading may lead to decayed sensor performance or sensor defects. Maintenance of offshore sensors is difficult, expensive and often not feasible within a short time. Therefore, sensor measurement deviations must not affect reliable structure fault detection. The influence of defect sensors on the rope fault detection is examined in this study: Types, intensities, number, place of occurrence of defect sensors and the distance between defect sensors and rope faults are varied.
Landscape Projection and Its Technological Use in Conceptualising Places and Architecture
Authors: Jóźwik Renata , Jóźwik Anna
Published: June 2022

The manipulation of landscape and the technological use of its views can be a strategy for place-making and a way of creating architecture and making it original. The methods used for this can be different, for example, by mechanically revealing and obscuring views, optical or film projection, directing the viewer to specific frames, using mirrors, etc. This approach is alternative and somewhat in opposition to the natural incorporation of the object into the landscape. In modernism, different architectural views of the surroundings were tested and used differently. These experiences are now transposed to contemporary architectural objects thanks to technological developments and the scenographic shaping of space. The article refers to the sources of transferring landscape views in popular dioramas and the effects of the development of photography, cinematography, and IT media. It describes the possible consequences of perceiving such a created landscape and more general—the world. An example of such a means of expression being fully and consciously taken is the now-defunct Charles de Beistegui Paris apartment. It was designed by Le Corbusier and Pierre Jeanneret in 1929–1931. The apartment was selected for analysing as a case study and confronted with contemporary realisations that use various creative techniques involving the landscape.
Spatiotemporal Variations of Chinese Terrestrial Ecosystems in Response to Land Use and Future Climate Change
Authors: Li Shuaishuai , Zhang Jiahua , Henchiri Malak , Cao Dan , Zhang Sha , Bai Yun , Yang Shanshan
Published: June 2022

Terrestrial ecosystems in China are threatened by land use and future climate change. Understanding the effects of these changes on vegetation and the climate-vegetation interactions is critical for vegetation preservation and mitigation. However, land-use impacts on vegetation are neglected in terrestrial ecosystems exploration, and a deep understanding of land-use impacts on vegetation dynamics is lacking. Additionally, few studies have examined the contribution of vegetation succession to changes in vegetation dynamics. To fill the above gaps in the field, the spatiotemporal distribution of terrestrial ecosystems under the current land use and climate baseline (1970–2000) was examined in this study using the Comprehensive Sequential Classification System (CSCS) model. Moreover, the spatiotemporal variations of ecosystems and their succession under future climate scenarios (the 2030s–2080s) were quantitatively projected and compared. The results demonstrated that under the current situation, vegetation without human disturbance was mainly distributed in high elevation regions and less than 10% of the national area. For future vegetation dynamics, more than 58% of tundra and alpine steppe would shrink. Semidesert would respond to climate change with an expansion of 39.49 × 104 km2, including the succession of the steppe to semidesert. Although some advancement of the temperate forest at the expense of substantial dieback of tundra and alpine steppe is expected to occur, this century would witness a considerable shrinkage of them, especially in RCP8.5, at approximately 55.06 × 104 km2. Overall, a warmer and wetter climate would be conducive to the occurrence and development of the CSCS ecosystems. These results offer new insights on the potential ecosystem response to land use and climate change over the Chinese domain, and on creating targeted policies for effective adaptation to these changes and implementation of ecosystem protection measures.
DeepWings©: Automatic Wing Geometric Morphometrics Classification of Honey Bee (Apis mellifera) Subspecies Using Deep Learning for Detecting Landmarks
Authors: Rodrigues Pedro João , Gomes Walter , Pinto Maria Alice
Published: June 2022

Honey bee classification by wing geometric morphometrics entails the first step of manual annotation of 19 landmarks in the forewing vein junctions. This is a time-consuming and error-prone endeavor, with implications for classification accuracy. Herein, we developed a software called DeepWings© that overcomes this constraint in wing geometric morphometrics classification by automatically detecting the 19 landmarks on digital images of the right forewing. We used a database containing 7634 forewing images, including 1864 analyzed by F. Ruttner in the original delineation of 26 honey bee subspecies, to tune a convolutional neural network as a wing detector, a deep learning U-Net as a landmarks segmenter, and a support vector machine as a subspecies classifier. The implemented MobileNet wing detector was able to achieve a mAP of 0.975 and the landmarks segmenter was able to detect the 19 landmarks with 91.8% accuracy, with an average positional precision of 0.943 resemblance to manually annotated landmarks. The subspecies classifier, in turn, presented an average accuracy of 86.6% for 26 subspecies and 95.8% for a subset of five important subspecies. The final implementation of the system showed good speed performance, requiring only 14 s to process 10 images. DeepWings© is very user-friendly and is the first fully automated software, offered as a free Web service, for honey bee classification from wing geometric morphometrics. DeepWings© can be used for honey bee breeding, conservation, and even scientific purposes as it provides the coordinates of the landmarks in excel format, facilitating the work of research teams using classical identification approaches and alternative analytical tools.
A Comprehensive Spark-Based Layer for Converting Relational Databases to NoSQL
Authors: Abdel-Fattah Manal A. , Mohamed Wael , Abdelgaber Sayed
Published: June 2022

Currently, the continuous massive growth in the size, variety, and velocity of data is defined as big data. Relational databases have a limited ability to work with big data. Consequently, not only structured query language (NoSQL) databases were utilized to handle big data because NoSQL represents data in diverse models and uses a variety of query languages, unlike traditional relational databases. Therefore, using NoSQL has become essential, and many studies have attempted to propose different layers to convert relational databases to NoSQL; however, most of them targeted only one or two models of NoSQL, and evaluated their layers on a single node, not in a distributed environment. This study proposes a Spark-based layer for mapping relational databases to NoSQL models, focusing on the document, column, and key–value databases of NoSQL models. The proposed Spark-based layer comprises of two parts. The first part is concerned with converting relational databases to document, column, and key–value databases, and encompasses two phases: a metadata analyzer of relational databases and Spark-based transformation and migration. The second part focuses on executing a structured query language (SQL) on the NoSQL. The suggested layer was applied and compared with Unity, as it has similar components and features and supports sub-queries and join operations in a single-node environment. The experimental results show that the proposed layer outperformed Unity in terms of the query execution time by a factor of three. In addition, the proposed layer was applied to multi-node clusters using different scenarios, and the results show that the integration between the Spark cluster and NoSQL databases on multi-node clusters provided better performance in reading and writing while increasing the dataset size than using a single node.
Facial Pain: RCT between Conventional Treatment and Fascial Manipulation® for Temporomandibular Disorders
Authors: Sekito Florence , Pintucci Marco , Pirri Carmelo , Ribeiro de Moraes Rego Mariana , Cardoso Mayra , Soares Paixão Kenia , Ribeiro da Silva Valquiria , Stecco Antonio
Published: June 2022

Background: To investigate the effectiveness of a specific manual therapy, Fascial Manipulation® (FM), in comparison with conventional treatments in temporomandibular disorders (TMD) patients using a two-arm randomized controlled trial. Methods: The study consisted of 28 patients that were divided in two groups (Group 1: Fascial Manipulation® vs. Group 2: conventional TMD treatment). The Verbal Rating Scale (VRS), RDC/TMD, electromyography (EMG) and Pression/Pain Evaluation on Masseter and Temporalis Muscle were assessed with different times. Results: In both groups, the improvement in pain was evident on the VRS scale (p < 0.0001) and pain-free opening (p < 0.001). In Group 1, the recovery of the function was faster; maximum unassisted opening T0 vs. T1 (p = 0.001). Conclusions: FM® can be used as an effective method for facial pain, being a rapid, safe and cost-effective approach to reduce pain, gain function and mouth opening that can be used prior to occlusion stabilization appliances.
Comparison Study of Nontreated and Fermented Wheat Varieties ‘Ada’, ‘Sarta’, and New Breed Blue and Purple Wheat Lines Wholemeal Flour
Authors: Bartkiene Elena , Starkute Vytaute , Zokaityte Egle , Klupsaite Dovile , Mockus Ernestas , Bartkevics Vadims , Borisova Anastasija , Gruzauskas Romas , Liatukas Žilvinas , Ruzgas Vytautas
Published: June 2022

The aim of this study was to analyze and compare the acidity, microbiological, and chromaticity parameters; fatty acid (FA) and volatile compound (VC) profiles; and biogenic amine (BA), macro- and microelement, and mycotoxin concentrations in nontreated ‘Ada’, ‘Sarta’, and new breed blue (DS8472-5) and purple (DS8526-2) wheat lines wholemeal (WW) with those fermented with lactic acid bacteria (LAB) possessing antimicrobial/antifungal properties, isolated from spontaneous sourdough: Pediococcus acidilactici-LUHS29, Liquorilactobacillus uvarum-LUHS245, Lactiplantibacillus plantarum-LUHS122). All the fermented WW showed >8.0 log10 CFU/g of LAB count, and the type of LAB was a significant factor in the WW acidity parameters. Phenylethylamine was the predominant BA in WW, and the wheat variety (WV), the type of LAB, and their interaction were significant factors on the BA formation. Despite the fact that some differences in trace element concentrations in WW were obtained, in most of the cases fermentation was not a significant factor in their content. The main FAs in WW were palmitic acid, all-cis,trans-octadecenoic acid, and linoleic acid. Fermented WW showed a more diverse VC profile; however, the influence of fermentation on deoxynivalenol in WW was varied. Finally, further studies are needed to indicate the technological parameters that would be the most effective for each WV, including the lowest BA formation and mycotoxin degradation.
Detecting Drug–Target Interactions with Feature Similarity Fusion and Molecular Graphs
Authors: Lin Xiaoli , Xu Shuai , Liu Xuan , Zhang Xiaolong , Hu Jing
Published: June 2022

The key to drug discovery is the identification of a target and a corresponding drug compound. Effective identification of drug–target interactions facilitates the development of drug discovery. In this paper, drug similarity and target similarity are considered, and graphical representations are used to extract internal structural information and intermolecular interaction information about drugs and targets. First, drug similarity and target similarity are fused using the similarity network fusion (SNF) method. Then, the graph isomorphic network (GIN) is used to extract the features with information about the internal structure of drug molecules. For target proteins, feature extraction is carried out using TextCNN to efficiently capture the features of target protein sequences. Three different divisions (CVD, CVP, CVT) are used on the standard dataset, and experiments are carried out separately to validate the performance of the model for drug–target interaction prediction. The experimental results show that our method achieves better results on AUC and AUPR. The docking results also show the superiority of the proposed model in predicting drug–target interactions.
Biochemistry of the Endocrine Heart
Authors: Goetze Jens P. , Bartels Emil D. , Shalmi Theodor W. , Andraud-Dang Lilian , Rehfeld Jens F.
Published: June 2022

Production and release of natriuretic peptides and other vasoactive peptides are tightly regulated in mammalian physiology and involved in cardiovascular homeostasis. As endocrine cells, the cardiac myocytes seem to possess almost all known chemical necessities for translation, post-translational modifications, and complex peptide proteolysis. In several ways, intracellular granules in the cells contain not only peptides destined for secretion but also important granin molecules involved in maintaining a regulated secretory pathway. In this review, we will highlight the biochemical phenotype of the endocrine heart recapitulating that the cardiac myocytes are capable endocrine cells. Understanding the basal biochemistry of the endocrine heart in producing and secreting peptides to circulation could lead to new discoveries concerning known peptide products as well as hitherto unidentified cardiac peptide products. In perspective, studies on natriuretic peptides in the heart have shown that the post-translational phase of gene expression is not only relevant for human physiology but may prove implicated also in the development and, perhaps one day, cure of human cardiovascular disease.
Molecular Mechanisms and Key Processes in Interstitial, Hemorrhagic and Radiation Cystitis
Authors: Brossard Clément , Lefranc Anne-Charlotte , Pouliet Anne-Laure , Simon Jean-Marc , Benderitter Marc , Milliat Fabien , Chapel Alain
Published: June 2022

Cystitis is a bladder disease with a high rate of prevalence in the world population. This report focuses on Interstitial Cystitis (IC), Hemorrhagic Cystitis (HC) and Chronic Radiation Cystitis. These pathologies have different etiologies, but they share common symptoms, for instance, pain, bleeding, and a contracted bladder. Overall, treatments are quite similar for abacterial cystitis, and include bladder epithelium protective or anti-inflammatory agents, alleviating pain and reducing bleeding. This review summarizes the mechanisms that the pathologies have in common, for instance, bladder dysfunction and inflammation. Conversely, some mechanisms have been described as present in only one pathology, such as neural regulation. Based on these specificities, we propose identifying a mechanism that could be common to all the above-mentioned pathologies.
Silencing VDAC1 to Treat Mesothelioma Cancer: Tumor Reprograming and Altering Tumor Hallmarks
Authors: Pandey Swaroop Kumar , Machlof-Cohen Renen , Santhanam Manikandan , Shteinfer-Kuzmine Anna , Shoshan-Barmatz Varda
Published: June 2022

Mesothelioma, an aggressive cancer with a poor prognosis, is linked to asbestos exposure. However, carbon nanotubes found in materials we are exposed to daily can cause mesothelioma cancer. Cancer cells reprogram their metabolism to support increased biosynthetic and energy demands required for their growth and motility. Here, we examined the effects of silencing the expression of the voltage-dependent anion channel 1 (VDAC1), controlling the metabolic and energetic crosstalk between mitochondria and the rest of the cell. We demonstrate that VDAC1 is overexpressed in mesothelioma patients; its levels increase with disease stage and are associated with low survival rates. Silencing VDAC1 expression using a specific siRNA identifying both mouse and human VDAC1 (si-m/hVDAC1-B) inhibits cell proliferation of mesothelioma cancer cells. Treatment of xenografts of human-derived H226 cells or mouse-derived AB1 cells with si-m/hVDAC1-B inhibited tumor growth and caused metabolism reprogramming, as reflected in the decreased expression of metabolism-related proteins, including glycolytic and tricarboxylic acid (-)cycle enzymes and the ATP-synthesizing enzyme. In addition, tumors depleted of VDAC1 showed altered microenvironments and inflammation, both associated with cancer progression. Finally, tumor VDAC1 silencing also eliminated cancer stem cells and induced cell differentiation to normal-like cells. The results show that silencing VDAC1 expression leads to reprogrammed metabolism and to multiple effects from tumor growth inhibition to modulation of the tumor microenvironment and inflammation, inducing differentiation of malignant cells. Thus, silencing VDAC1 is a potential therapeutic approach to treating mesothelioma.
The Multifaceted Role of Aquaporin-9 in Health and Its Potential as a Clinical Biomarker
Authors: da Silva Inês V. , Garra Sabino , Calamita Giuseppe , Soveral Graça
Published: June 2022

Aquaporins (AQPs) are transmembrane channels essential for water, energy, and redox homeostasis, with proven involvement in a variety of pathophysiological conditions such as edema, glaucoma, nephrogenic diabetes insipidus, oxidative stress, sepsis, cancer, and metabolic dysfunctions. The 13 AQPs present in humans are widely distributed in all body districts, drawing cell lineage-specific expression patterns closely related to cell native functions. Compelling evidence indicates that AQPs are proteins with great potential as biomarkers and targets for therapeutic intervention. Aquaporin-9 (AQP9) is the most expressed in the liver, with implications in general metabolic and redox balance due to its aquaglyceroporin and peroxiporin activities, facilitating glycerol and hydrogen peroxide (H2O2) diffusion across membranes. AQP9 is also expressed in other tissues, and their altered expression is described in several human diseases, such as liver injury, inflammation, cancer, infertility, and immune disorders. The present review compiles the current knowledge of AQP9 implication in diseases and highlights its potential as a new biomarker for diagnosis and prognosis in clinical medicine.
The Impact of Zinc and Zinc Homeostasis on the Intestinal Mucosal Barrier and Intestinal Diseases
Authors: Wan Yan , Zhang Bingkun
Published: June 2022

Zinc is an essential trace element for living organisms, and zinc homeostasis is essential for the maintenance of the normal physiological functions of cells and organisms. The intestine is the main location for zinc absorption and excretion, while zinc and zinc homeostasis is also of great significance to the structure and function of the intestinal mucosal barrier. Zinc excess or deficiency and zinc homeostatic imbalance are all associated with many intestinal diseases, such as IBD (inflammatory bowel disease), IBS (irritable bowel syndrome), and CRC (colorectal cancer). In this review, we describe the role of zinc and zinc homeostasis in the intestinal mucosal barrier and the relevance of zinc homeostasis to gastrointestinal diseases.
Genetic Changes in Thyroid Cancers and the Importance of Their Preoperative Detection in Relation to the General Treatment and Determination of the Extent of Surgical Intervention—A Review
Authors: Hlozek Jiri , Pekova Barbora , Rotnágl Jan , Holý Richard , Astl Jaromir
Published: June 2022

Carcinomas of the thyroid gland are some of the most common malignancies of the endocrine system. The causes of tumor transformation are genetic changes in genes encoding cell signaling pathways that lead to an imbalance between cell proliferation and apoptosis. Some mutations have been associated with increased tumor aggressiveness, metastatic lymph node spread, tendency to dedifferentiate, and/or reduced efficiency of radioiodine therapy. The main known genetic causes of thyroid cancer include point mutations in the BRAF, RAS, TERT, RET, and TP53 genes and the fusion genes RET/PTC, PAX8/PPAR-γ, and NTRK. Molecular genetic testing of the fine needle aspiration cytology of the thyroid tissue in the preoperative period or of the removed thyroid tissue in the postoperative period is becoming more and more common in selected institutions. Positive detection of genetic changes, thus, becomes a diagnostic and prognostic factor and a factor that determines the extent of the surgical and nonsurgical treatment. The findings of genetic research on thyroid cancer are now beginning to be applied to clinical practice. In preoperative molecular diagnostics, the aggressiveness of cancers with the most frequently occurring mutations is correlated with the extent of the planned surgical treatment (radicality of surgery, neck dissection, etc.). However, clear algorithms are not established for the majority of genetic alterations. This review aims to provide a basic overview of the findings of the most commonly occurring gene mutations in thyroid cancer and to discuss the current recommendations on the extent of surgical and biological treatment concerning preoperatively detected genetic changes.