bluuebunny/crossref_metadata_2025 huggingface dataset:
Fault Diagnosis Method Based on Time Series in Autonomous Unmanned System
Authors: Xu Zhuoran , Wang Manyi , Li Qianmu , Qian Linfang
Published: July 2022

There are various types of autonomous unmanned systems, covering different spaces of sea, land, and air, and they are comprehensively going deep into multiple fields of national security and social life. Due to the development of technology, the scale of unmanned systems is getting larger and larger, the number of components in the system is increasing, and the operating environment of the system is also becoming more and more complex. Therefore, the probability of failure of the components of the system will also be significantly increased. In order to eliminate the impact of the fault in time, the fault diagnosis method is significant. Considering the differences of components in autonomous unmanned systems, if a specific fault diagnosis algorithm is designed for each type of component, it will bring difficulties to the coordinated control of the system. Therefore, this paper analyzes the data characteristics of unmanned autonomous system devices (such as sensors) and finds that these data have time series. Therefore, the data of different devices can be converted into time series, and a general fault diagnosis algorithm suitable for most devices can be studied. The fault diagnosis algorithm is based on the clustering algorithm. In order to improve the clustering effect, the time series of different devices are represented by Gaussian mixture clustering to reduce the computational complexity of the clustering calculation. Then, a time series similarity measurement method based on the improved Markov chain is proposed. This method can better distinguish normal samples from abnormal samples so as to classify and identify faults effectively.
Two-Layer Matrix Factorization and Multi-Layer Perceptron for Online Service Recommendation
Authors: Bao Shudi , Wang Tiantian , Zhou Liliang , Dai Guilan , Sun Geng , Shen Jun
Published: July 2022

Service recommendation is key to improving users’ online experience. The development of the Internet has accelerated the creation of many services, and whether users can obtain good experiences among the massive number of services mainly depends on the quality of service recommendation. It is commonly believed that deep learning has excellent nonlinear fitting ability in capturing the complex interactions between users and items. The advantage in learning intricacy relationships enables deep learning to become an important technology for present service recommendation. Recently, it is noticed that linear models can perform almost as well as the state-of-the-art deep learning models, suggesting that capturing linear relationships between users and items is also very important for recommender systems. Therefore, numerous deep learning systems combined with linear models have been proposed. However, existing models are incapable of considering the size of the embedding. When the embedding dimension is too large, it leads to overfitting and thus influences the model’s ability to capture linear relationships. In this paper, a neural network based on two-layer matrix factorization and multi-layer perceptron—Two-layer Matrix factorization and Multi-layer perceptron Neural Network (TMMNN)—is proposed. To solve the problem of overfitting caused by an oversized embedding dimension, multi-size embedding technology has been integrated into the model. Matrix factorization and the multi-layer perceptron are placed in the upper and lower layers respectively, and they both receive embedding vectors dynamically adjusted for dimensions. In the upper layer, the matrix factorization is responsible for receiving the embedding of users and items, capturing linear relationships, and then yielding the generated new vectors as input to the multi-layer perceptron in the lower layer. Compared to other previously proposed models, the experimental results on the standard datasets MovieLens 20M and MovieLens Latest show that the TMMNN model is evidently better in terms of prediction accuracy.
Chemical Composition and Antioxidant Activity of Essential Oil from the Aerial Parts of Teucrium luteum (Mill.) Degen subsp. flavovirens (Batt.) Greuter & Burdet Growing Wild in Tunisia
Authors: Majdoub Siwar , Dall’Acqua Stefano , El Mokni Ridha , Hammami Saoussen , Peron Gregorio
Published: July 2022

Essential oils (EOs), the odorous and volatile products of a plant’s secondary metabolism, have wide applications in folk medicine, in food flavoring and preservation, and in fragrance industries. The aim of this study was to analyze the chemical composition of the EO from the aerial parts (including the inflorescences) of wild Teucrium luteum subsp. flavovirens from Tunisia. The EO obtained by the hydrodistillation of air-dried plant material in a Clevenger-type apparatus was analyzed using gas chromatography coupled with mass spectrometry (GC-MS). Fifty-three components representing 83.9% of the total constituents were identified. The EO of T. luteum subsp. flavovirens is characterized by the presence of β-elemol (7.2%), (+)-α-pinene (6%), β-eudesmol (5.5%), guaiol (4.2%), α-bisabolol (4.2%), and β-caryophyllene (4.1%) as principal chemical components. In vitro (DPPH and β-carotene bleaching assays), it showed significantly higher radical scavenging and antioxidant properties than the reference compound, BHT. To the best of our knowledge, this is the first report describing the composition and antioxidant properties of the EO from Tunisian T. luteum subsp. flavovirens. Our preliminary data will help to valorize this potentially useful plant species from Tunisia and represent a starting point for further studies on its volatile fraction.
A Cascade Model with Prior Knowledge for Bone Age Assessment
Authors: Li Nanxin , Cheng Bochao , Zhang Junran
Published: July 2022

Bone age is commonly used to reflect growth and development trends in children, predict adult heights, and diagnose endocrine disorders. Nevertheless, the existing automated bone age assessment (BAA) models do not consider the nonlinearity and continuity of hand bone development simultaneously. In addition, most existing BAA models are based on datasets from European and American children and may not be applicable to the developmental characteristics of Chinese children. Thus, this work proposes a cascade model that fuses prior knowledge. Specifically, a novel bone age representation is defined, which incorporates nonlinear and continuous features of skeletal development and is implemented by a cascade model. Moreover, corresponding regions of interest (RoIs) based on RUS-CHN were extracted by YOLO v5 as prior knowledge inputs to the model. In addition, based on MobileNet v2, an improved feature extractor was proposed by introducing the Convolutional Block Attention Module and increasing the receptive field to improve the accuracy of the evaluation. The experimental results show that the mean absolute error (MAE) is 4.44 months and significant correlations with the reference bone age is (r = 0.994, p < 0.01); accuracy is 94.04% for ground truth within ±1 year. Overall, the model design adequately considers hand bone development features and has high accuracy and consistency, and it also has some applicability on public datasets, showing potential for practical and clinical applications.
Impact of COVID-19 Mobility Changes on Air Quality in Warsaw
Authors: Badyda Artur , Brzeziński Andrzej , Dybicz Tomasz , Jesionkiewicz-Niedzińska Karolina , Olszewski Piotr , Osińska Beata , Szagała Piotr , Mucha Dominika
Published: July 2022

During a pandemic, the mobility of people changes significantly from the normal situation (the number of trips made, the directions of travel and the modes of transport used). Changes in mobility depend on the scale of the pandemic threat and the scale of the restrictions introduced and assessing the impact of these changes is not straightforward. This raises the question of the social cost of changes in mobility and their impact on the environment, including air quality. The article shows that it is possible to determine this impact using big data from mobile operators’-SIM card movements and data from air quality monitoring stations. Data on SIM card movements allows for reconstructing the state of the transport system before and during the different phases of a pandemic. The changes in mobility of people determined in this way can be related to the results of measurements of pollutant concentrations in the air. In this way, it is possible to identify links between mobility changes and air quality. The article presents the extent (in relation to the state without the pandemic) of changes in the mobility of the population during the pandemic and the related impact on air quality using the example of Warsaw.
Effect of COVID-19 on Selected Characteristics of Life Satisfaction Reflected in a Fuzzy Model
Authors: Mikołajewski Dariusz , Prokopowicz Piotr
Published: July 2022

The general goal of the research in this article is to devise an algorithm for assessing overall life satisfaction—a term often referred to as Quality of Life (QoL). It is aggregated to its own proposition, called personal life usual satisfaction (PLUS). An important assumption here is that the model is based on already known and commonly used solutions, such as medical (psychological and physiotherapeutic) questionnaires. Thanks to this, the developed solution allows us to obtain a synergy effect from the existing knowledge, without the need to design new, complicated procedures. Fuzzy multivariate characterization of life satisfaction presents a challenge for a complete analysis of the phenomenon. The complexity of description using multiple scales, including linguistic, requires additional computational solutions, as presented in this paper. The detailed aim of this study is twofold: (1) to develop a fuzzy model reflecting changes in life satisfaction test scores as influenced by the corona virus disease 2019 (COVID-19) pandemic, and (2) to develop guidelines for further research on more advanced models that are clinically useful. Two groups affected by professional burnout to different degrees were analyzed toward life satisfaction twice (pre- and during pandemy): a study group (physiotherapists, n = 25) and a reference group (computer scientists, n = 25). The Perceived Stress Score (PSS10), Maslach Burnout Inventory (MBI), Satisfaction with Life Scale (SWLS), and Nordic Musculoskeletal Questionnaire (NMQ) were used. The resultant model is based on a hierarchical fuzzy system. The novelty of the proposed approach lies in the combination of the use of data from validated clinimetric tests with the collection of data from characteristic time points and the way in which they are analyzed using fuzzy logic through transparent and scalable hierarchical models. To date, this approach is unique and has no equivalent in the literature. Thanks to the hierarchical structure, the evaluation process can be defined as a modular construction, which increases transparency and makes the whole procedure more flexible.
A Lightweight Crop Pest Detection Method Based on Convolutional Neural Networks
Authors: Cheng Zekai , Huang Rongqing , Qian Rong , Dong Wei , Zhu Jingbo , Liu Meifang
Published: July 2022

Existing object detection methods with many parameters and computations are not suitable for deployment on devices with poor performance in agricultural environments. Therefore, this study proposes a lightweight crop pest detection method based on convolutional neural networks, named YOLOLite-CSG. The basic architecture of the method is derived from a simplified version of YOLOv3, namely YOLOLite, and k-means++ is utilized to improve the generation process of the prior boxes. In addition, a lightweight sandglass block and coordinate attention are used to optimize the structure of residual blocks. The method was evaluated on the CP15 crop pest dataset. Its detection precision exceeds that of YOLOv3, at 82.9%, while the number of parameters is 5 million, only 8.1% of the number used by YOLOv3, and the number of computations is 9.8 GFLOPs, only 15% of that used by YOLOv3. Furthermore, the detection precision of the method is superior to all other commonly used object detection methods evaluated in this study, with a maximum improvement of 10.6%, and it still has a significant edge in the number of parameters and computation required. The method has excellent pest detection precision with extremely few parameters and computations. It is well-suited to be deployed on equipment for detecting crop pests in agricultural environments.
Clinical Impact of Balneotherapy and Therapeutic Exercise in Rheumatic Diseases: A Lexical Analysis and Scoping Review
Authors: Tognolo Lucrezia , Coraci Daniele , Fioravanti Antonella , Tenti Sara , Scanu Anna , Magro Giacomo , Maccarone Maria Chiara , Masiero Stefano
Published: July 2022

Objective: To review the evidence regarding the clinical effect of spa therapy for rheumatic diseases, with particular attention given to association protocols between balneotherapy and rehabilitation interventions, and to support the literature research and studies’ selection with lexical analysis. Methods: A lexical analysis was performed considering a list of words representing diseases and outcome measures linked to the theme studied in our review. Then, two independent researchers conducted a literature search on PubMed using the string employed for lexical analysis, including Randomized Controlled Trials regarding spa therapy’s clinical effects on patients affected by rheumatic diseases published in the last 30 years. After the exclusion of works that did not meet the eligibility criteria, 14 studies were included in the final scoping review. Results: Spa therapy has shown a favourable effect on pain, function and quality of life in patients with Osteoarthritis, Fibromyalgia and Rheumatoid Arthritis. Different treatment modalities and types of water have demonstrated beneficial long-term clinical improvement. Furthermore, the association between thermal therapy and rehabilitation treatments has shown better clinical outcomes, probably due to the synergistic effect between the peculiar properties of the thermal waters and the therapeutic exercise program, if conducted in the same context. Conclusions: The combination of balneotherapy and rehabilitative interventions seems to be effective in ameliorating several outcomes in patients with rheumatic diseases. However, due to the wide variety of methodologies and interventions employed, these findings need to be further investigated. The lexical analysis should represent an auxiliary support for an extensive evaluation of scientific literature.
Numerical Simulation of Non-Isothermal Mixing Flow Characteristics with ELES Method
Authors: Sun Chengbin , Wang Hexu , Jiang Yanlong , Zou Zhixin , Zhu Faxing
Published: July 2022

Thermal fatigue caused by turbulent thermal mixing in tee pipes is always one of the failure factors of industrial pipes. At present, computational fluid dynamics (CFD) is still the main research method to study the thermal fatigue mechanism. Due to the limitations of the large eddy simulation (LES) model and the classical Reynolds Averaged Navier–Stokes (RANS) model in simulating thermal mixing, an advanced Embedded LES (ELES) model was developed. By comparing the model with data in the open literature, the validity of the ELES model to iso-thermal mixing was evaluated and proven. After that, the flow characteristics of the backflow upstream with different momentum ratios (MR) were studied using the ELES method, as well as the temperature characteristics near the wall where the backflow appears. It was found that the characteristics of the backflow and the temperature distribution upstream in the tee were different with different MR values and some regions under specified MR values are found to be more prone to thermal fatigue at the intersection of the tee upstream. Moreover, the frequency analysis at specified points near the wall under three different MR values was estimated to evaluate thermal fatigue and the results showed that long-period fluctuations of lower frequencies than 6 Hz upstream were observed. This work helps form a comprehensive understanding of the backflow in thermal mixing and the relationship between fatigue and backflow in the tee.
Groundwater Contaminant Transport Solved by Monte Carlo Methods Accelerated by Deep Learning Meta-Model
Authors: Špetlík Martin , Březina Jan
Published: July 2022

Groundwater contaminant transport modeling is a vitally important topic. Since modeled processes include uncertainties, Monte Carlo methods are adopted to obtain some statistics. However, accurate models have a substantial computational cost. This drawback can be overcome by employing the multilevel Monte Carlo method (MLMC) or approximating the original model using a meta-model. We combined both of these approaches. A stochastic model is substituted with a deep learning meta-model that consists of a graph convolutional neural network and a feed-forward neural network. This meta-model can approximate models solved on unstructured meshes. The meta-model within the standard Monte Carlo method can bring significant computational cost savings. Nevertheless, the meta-model must be highly accurate to obtain similar errors as when using the original model. Proposed MLMC with the new lowest-accurate level of meta-models can reduce total computational costs, and the accuracy of the meta-model does not have to be so high. The size of the computational cost savings depends on the cost distribution across MLMC levels. Our approach is especially efficacious when the dominant computational cost is on the lowest-accuracy MLMC level. Depending on the number of estimated moments, we can reduce computational costs by up to ca. 25% while maintaining the accuracy of estimates.
Infill Microstructures for Additive Manufacturing
Authors: Ntintakis Ioannis , Stavroulakis Georgios E.
Published: July 2022

Additive Manufacturing (AM) is a well-known and rapidly advancing method, especially in the manufacturing of high-strength and lightweight microstructures. Utilizing AM, it is possible to fabricate any structure as complicated as it is. For an efficient and cost-effective printing, a critical parameter is the infill, which can be characterized from an easy 2D shape to high complexity. At the same time, Topology Optimization (TO) is an appropriate method to create high-strength and mass optimized microstructure lattices. In the current study, TO starts from a solid cubic volume of 15 × 15 mm, and different boundary conditions of two new cellular microstructures designed with 0.4 and 0.1 relative density are applied, respectively. The adopted TO method was Solid Isotropic Material with Penalization (SIMP), which predicts an optimal material distribution within a given design domain. TO methods do not check other characteristics of the structure, such as anisotropy. To evaluate and characterize the optimized microstructure, a general purpose homogenization method is utilized to calculate the Zener ratio and the elastic modulus. Using Fused Filament Fabrication (FFF), which is a material extrusion 3D printing method, lattice structure samples are fabricated and then tested in compression and tensile strength tests. The comparative results from the homogenization study showed that both microstructures have anisotropic behavior and an accepted response in the stress test similar to the homogenized material. The experimental results show that the mechanical behavior of the lattice structure changes significantly when the cell mapping angle differs.
Reducing the Number of Sensors in the Data Glove for Recognition of Static Hand Gestures
Authors: Piskozub Jakub , Strumillo Pawel
Published: July 2022

Data glove devices, apart from being widely used in industry and entertainment, can also serve as a means for communication with the environment. This is possible thanks to the advancement in electronic technology and machine learning algorithms. In this paper, the results of the study using a designed data glove equipped with 10 piezoelectric sensors are reported, and the designed glove is validated on a recognition task of hand gestures based on 16 static signs of the Polish Sign Language (PSL) alphabet. The main result of the study is that recognition of 16 PSL static gestures is possible with a reduced number of piezoelectric sensors. This result has been achieved by applying the decision tree classifier that can rank the importance of the sensors for the recognition performance. Other machine learning algorithms were also tested, and it was showed that for the Support Vector Machines, k-NN and Bagged Trees classifiers, a recognition rate of the signs exceeding 90% can be achieved just for three preselected sensors. Such a result is important for a reduction in design complexity and costs of such a data glove with sustained reliability of the device.
Infants Hospitalized with Lower Respiratory Tract Infections Were More Likely to Develop Asthma
Authors: Zaitsu Masafumi , Morita Shun
Published: July 2022

Introduction: Lower respiratory tract infections (LRTIs) have been reported to possibly initiate the development of asthma in children. However, the role of LRTIs in infantile asthma remains controversial. The goal of this study is to investigate whether LRTIs in hospitalized infants are involved in the development of asthma. Materials and Methods: The subjects were 251 infants under 2 years of age who were admitted to our hospital with an RTI (59 cases of upper RTI (URTIs) with upper respiratory tract inflammation and pharyngeal tonsillitis; 192 cases of LRTIs with bronchitis, pneumonia, and bronchiolitis). Pathogens of viral infections were examined at admission using viral antigen test kits that could be used in ordinary clinical practice in Japan. When the children reached the age of 3 years, a survey was conducted by mailing a questionnaire to determine the symptoms, diagnosis, and treatment of asthma. Results: The mailed questionnaires were returned by 116 of the 251 subjects. On the questionnaire, the diagnosis of asthma and treatment for asthma were significantly higher in hospitalized infants with LRTIs than in those with URTIs. By diagnosis of LRTIs, infants with pneumonia and bronchiolitis were significantly more likely to develop asthma. However, on pathogen-specific examination, there was no difference in the development of asthma among infants with LRTIs. Conclusion: LRTI in infancy may be involved in the development of asthma. The severity of LRTI in hospitalized infants, but not the particular viral pathogen causing infection, may be associated with later asthma onset.
Quantitative Assessment of Climate Change Impact and Anthropogenic Influence on Crop Production and Food Security in Shandong, Eastern China
Authors: Cheng Junqi , Yin Shuyan
Published: July 2022

Food security plays an important role in maintaining national stability and sustainable development of human society, and its research has become a hot issue at present. Shandong is the main grain producing area in China, and its grain production plays an important role in national food security. Accordingly, this paper is based on the county climate change, grain yield, sown area, fertilizer use, total power of rural machinery, and total population data in Shandong Province from 1995 to 2020. The evolution process of the food security pattern was studied by the methods of spatial analysis and comprehensive evaluation, the influencing factors of food security were quantitatively analyzed, and the adaptive countermeasures to alleviate the food security risks in this region were discussed. The results show that: Grain production increased by 30.62% from 1995 to 2020. The total population and per capita food availability also increased. Since 2000, more than a quarter of counties have experienced a high risk of food insecurity. The spatial agglomeration of grain production was enhanced, and the local agglomeration characteristics were significantly different. The average temperature in the growing season, the sown area, and the total power of agricultural machinery had a significant positive impact on grain production, while the annual average temperature had a significant negative impact on grain production. Improving the food supply system, strengthening the protection of cultivated land, improving the efficiency of fertilizer utilization, and increasing investment in agricultural science and technology can effectively alleviate food security risks.
Spatiotemporal Variation of Snow Cover and Its Response to Climate Change in the Source Region of the Yangtze River, China
Authors: Shi Mengqi , Yuan Zhe , Hong Xiaofeng , Liu Simin
Published: July 2022

In the context of global warming, snow cover changes have an extremely important impact on the hydrological cycle and the redistribution of water resources in arid and semi-arid regions. In this paper, based on the daily cloud-free snow area remote sensing product data in the source region of Yangtze River (SRYR) from 2000 to 2019, the snow phenology variables such as the snow cover day (SCD), snow onset date (SOD), snow end date (SED), and snow duration day (SDD) were extracted separately for each hydrological year, and the vertical distribution of snow cover area (SCA) in the SRYR was analyzed by combining with the digital elevation model (DEM). In addition, we also combined climate factors and land cover types to further explore the spatiotemporal variation characteristics of snow phenology in response to different influencing factors, in order to reveal the spatiotemporal variation patterns of snow cover in the SRYR. The results showed that: (1) The SCA in the SRYR has a more obvious vertical distribution, with the maximum SCA reaching 61.58% at high elevation, while at low elevation, the SCA is mostly below 20%. The distribution of SCD in the study area showed a significant exponential correlation with DEM (R2 = 0.87). (2) The area of SOD in the SRYR showed an advanced trend of about 63.37%, while the area of SED showed a delayed trend of about 69.59%, and the area which showed significant trends is 4.29% and 4.36%, respectively. Therefore, the trends of both SOD and SED showed insignificant changes. (3) Temperature change is the main factor affecting the change of snow cover in the SRYR. Among them, 90.9% of the regions showed a significant positive correlation between temperature and SCD, while precipitation showed a significant negative correlation with SCD in about 75.3% of the total area of SRYR. Under the stable snow area (SCD > 60), the land cover type is glacial or permanent snow about 1.5 × 103 km2, which covers almost the entire glacial or permanent snow of the SRYR.
Analysis of Synergistic Effects of Cold Source and East Asian Winter Wind on Air Pollution in Typical Regions of China in Winter
Authors: Li Yanjun , An Xingqin , Wang Baozhen , Li Jiangtao , Wang Chao
Published: July 2022

This paper collects and analyzes the 1954–2017 monthly average reanalysis data from the U.S. National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), the 1954–2017 haze days observation data from the National Meteorological Information Center/China Meteorological Administration (NMIC/CMA) and the PM2.5 daily average mass concentration data in 2013–2017 from the China Air Quality Online Monitoring Platform. The atmospheric apparent heat source Q1 (negative Q1 means cold source in winter) over the Tibetan Plateau in December of 1954–2017 is estimated based on thermodynamic equations, and the East Asian winter monsoon index (EAWMI) is calculated. In addition, the discrepancies of the air quality among China’s five typical regions (Beijing–Tianjin–Hebei, Fen-Wei Plain, Yangtze River Delta, Pearl River Delta and Sichuan-Chongqing regions) under the joint influence of the Q1 and EAWMI are studied. Results show that when it is a strong cold source year, abnormal downdrafts and “temperature inversion covers” occur in areas far from the high terrain, resulting in increased pollution, while the opposite is true in weak cold source years. In strong EAWMI years, there is an abnormal northerly sinking cold flow in the lower layers of mid-high latitudes, which increases the pollution in the area south of 30° N, and the opposite is true in weak EAWMI years. Affected by the combined activities of the Q1 and the EAWMI, the meteorological conditions of the five typical regions are different, and thus present different air pollution characteristics.
A Coherent Approach to Evaluating Precipitation Forecasts over Complex Terrain
Authors: Gofa Flora , Flocas Helena , Louka Petroula , Samos Ioannis
Published: July 2022

Precipitation forecasts provided by high-resolution NWP models have a degree of realism that is very appealing to most users of meteorological data. However, it is a challenge to demonstrate whether or not such forecasts contain more skillful information than their lower resolution counterparts. A verification procedure must be based on equally detailed observations that are also realistic in areas where ground observations are not available and remote sensing data can only increase the accuracy of the location of rain events at the cost of decreased accuracy in estimating the amount of rain that has actually reached the ground. Traditional verification methods based on station or grid point comparison yield poor results for high-resolution fields due to the double penalty error that is attributed to finite space and time displacement that such methods do not account for. A complete approach to evaluating precipitation forecasts over complex terrain is suggested. The method is based on realistic gridded precipitation observations generated by an interpolation method that uses long climate data series to determine the geographical characteristics that this parameter is best correlated with as well as remote sensing estimates as background information to cover the areas where observations are insufficient. Spatial verification methodologies are subsequently applied to a convective event that accentuate the relative skill of high-resolution COSMOGR forecasts in revealing characteristics in the precipitation patterns such as structure and intensity.
Control of Disabling Vertigo in Ménière’s Disease Following Cochlear Implantation without Labyrinthectomy
Authors: Canale Andrea , Dalmasso Giulia , Albera Roberto , Lucisano Sergio , Dumas George , Perottino Flavio , Albera Andrea
Published: July 2022

Background: The placement of a cochlear implant (CI) can restore auditory function in the case of profound cochlear deafness, which may be due to Ménière’s disease (MD) or be associated with symptoms related to endolymphatic hydrops. The usual treatment of disabling vertigo in MD is based on vestibular deafferentation by labyrinth ablation. The aim of the present study was to retrospectively evaluate the efficacy of the CI in the control of disabling vestibular manifestations in the case of MD unresponsive to medical treatments. Methods: A case series of five MD patients with disabling vestibular manifestations associated with profound hearing loss was included. A complete audio-vestibular evaluation was performed after CI positioning. Results: All patients reported clinical benefits after implant positioning: no vestibular crisis was reported after the surgery. The vHIT and the caloric test showed a normal function or a mild vestibular hypofunction. The auditory performances were comparable to those in the general implanted population. All patients reported subjective tinnitus reduction. Conclusions: To date, very few studies have reported vestibular outcomes in hydropic pathology on the implanted side; our results are encouraging. We can therefore confirm the efficacy and safety of the CI as a unique treatment for hearing loss, dizziness, and tinnitus in case of disabling cochlear hydrops, especially in those patients where the history of the disease requires preservation of the vestibular function.
Nutrient Homeostasis of Aegilops Accessions Differing in B Tolerance Level under Boron Toxic Growth Conditions
Authors: Khan Mohd. Kamran , Pandey Anamika , Hamurcu Mehmet , Germ Mateja , Yilmaz Fatma Gokmen , Ozbek Merve , Avsaroglu Zuhal Zeynep , Topal Ali , Gezgin Sait
Published: July 2022

Boron (B) is a crucial microelement for several biological processes in plants; however, it becomes hazardous when present in excess in the soil. B toxicity adversely affects the wheat yield all around the world, particularly in the arid and semiarid regions. Aegilops, the nearest wild wheat relatives, could be an efficient source to develop B toxicity tolerance in modern cultivars. However, to potentially utilize these species, it is necessary to understand the underlying mechanisms that are involved in providing them tolerance. Other than hampering cellular and physiological activities, high B inhibits the uptake of nutrients in wheat plants that lead to nutrients deficiency causing a hindered growth. Thus, it is crucial to determine the effect of B toxicity on nutrient uptake and finally, to understand the role of nutrient homeostasis in developing the adaptive mechanism in tolerant species. Unfortunately, none of the studies to date has explored the effect of high B supply on the nutrient uptake in B toxicity tolerant wild wheat species. In this study, we explored the effect of 1 mM B (toxic B), and 10 mM B (very toxic B) B on the nutrient uptake in 19 Aegilops genotypes differing in B tolerance in contrast to Bolal 2973, the familiar B tolerant genotype. The obtained outcomes suggested a significant association between the B toxicity tolerance and the level of nutrient uptake in different genotypes. The B toxicity tolerant genotypes, Ab2 (TGB 026219, A. biuncialis genotype) and Ac4 (TGB 000107, A. columnaris genotype) were clustered together in the nutrient homeostasis-based heat map. Though B toxicity mostly had an inhibitory effect on the uptake of nutrients in root-shoot tissues, the tolerant genotypes revealed an increase in nutrient uptake under B toxicity in contrast with Control. The study directs towards future research where the role of external supply of few nutrients in enhancing the B toxicity tolerance of susceptible genotypes can be studied. Moreover, the genotype-dependent variation in the nutrient profile of the studied Aegilops genotypes under high B suggested that increasing number of Aegilops germplasm should be screened for B toxicity tolerance for their successful inclusion in the pre-breeding programs focusing on this issue.
The Role of ApoE Serum Levels and ApoE Gene Polymorphisms in Patients with Laryngeal Squamous Cell Carcinoma
Authors: Liutkeviciene Rasa , Auzelyte Justina , Liutkevicius Vykintas , Vilkeviciute Alvita , Gedvilaite Greta , Vaiciulis Paulius , Uloza Virgilijus
Published: July 2022

Recent studies have revealed that the inflammatory ApoE effect may play a significant role in various cancer development. However, this effect has still not been analyzed in patients with laryngeal squamous cell carcinoma (LSCC). In the present study, we evaluated two single nucleotide polymorphisms (SNPs) of ApoE (rs7412 and rs429358) and determined their associations with LSCC development and the LSCC patients’ five-year survival rate. Additionally, we analyzed serum ApoE levels using an enzyme-linked immunosorbent assay. A total of 602 subjects (291 histologically verified LSCC patients and 311 healthy controls) were involved in this study. The genotyping was carried out using the real-time PCR. We revealed that ApoE ε3/ε3 was associated with a 1.7-fold higher probability of developing LSCC (p = 0.001), with 1.7-fold increased odds of developing LSCC without metastasis to the lymph nodes (p = 0.002) and with a 2.0-fold increased odds of developing well-differentiated LSCC (p = 0.008), as well as 1.6-fold increased odds of developing poorly differentiated LSCC development (p = 0.012). The ApoE ε2/ε4 and ε3/ε4 genotypes were associated with a 2.9-fold and 1.5-fold decrease in the likelihood of developing LSCC (p = 0.042; p = 0.037, respectively). ApoE ε3/ε4 was found associated with a 2.4-fold decreased likelihood of developing well-differentiated LSCC (p = 0.013). Conclusion: ApoE ε2/ε4 and ε3/ε4 were found to play a protective role in LSCC development, while ApoE ε3/ε3 may have a risk position in LSCC development.
Folding and Binding Mechanisms of the SH2 Domain from Crkl
Authors: Nardella Caterina , Toto Angelo , Santorelli Daniele , Pagano Livia , Diop Awa , Pennacchietti Valeria , Pietrangeli Paola , Marcocci Lucia , Malagrinò Francesca , Gianni Stefano
Published: July 2022

SH2 domains are structural modules specialized in the recognition and binding of target sequences containing a phosphorylated tyrosine residue. They are mostly incorporated in the 3D structure of scaffolding proteins that represent fundamental regulators of several signaling pathways. Among those, Crkl plays key roles in cell physiology by mediating signals from a wide range of stimuli, and its overexpression is associated with several types of cancers. In myeloid cells expressing the oncogene BCR/ABL, one interactor of Crkl-SH2 is the focal adhesion protein Paxillin, and this interaction is crucial in leukemic transformation. In this work, we analyze both the folding pathway of Crkl-SH2 and its binding reaction with a peptide mimicking Paxillin, under different ionic strength and pH conditions, by using means of fluorescence spectroscopy. From a folding perspective, we demonstrate the presence of an intermediate along the reaction. Moreover, we underline the importance of the electrostatic interactions in the early event of recognition, occurring between the phosphorylated tyrosine of the Paxillin peptide and the charge residues of Crkl-SH2. Finally, we highlight a pivotal role of a highly conserved histidine residue in the stabilization of the binding complex. The experimental results are discussed in light of previous works on other SH2 domains.
Comparative Analysis of Enzyme Production Patterns of Lignocellulose Degradation of Two White Rot Fungi: Obba rivulosa and Gelatoporia subvermispora
Authors: Marinovíc Mila , Di Falco Marcos , Aguilar Pontes Maria Victoria , Gorzsás András , Tsang Adrian , de Vries Ronald P. , Mäkelä Miia R. , Hildén Kristiina
Published: July 2022

The unique ability of basidiomycete white rot fungi to degrade all components of plant cell walls makes them indispensable organisms in the global carbon cycle. In this study, we analyzed the proteomes of two closely related white rot fungi, Obba rivulosa and Gelatoporia subvermispora, during eight-week cultivation on solid spruce wood. Plant cell wall degrading carbohydrate-active enzymes (CAZymes) represented approximately 5% of the total proteins in both species. A core set of orthologous plant cell wall degrading CAZymes was shared between these species on spruce suggesting a conserved plant biomass degradation approach in this clade of basidiomycete fungi. However, differences in time-dependent production of plant cell wall degrading enzymes may be due to differences among initial growth rates of these species on solid spruce wood. The obtained results provide insight into specific enzymes and enzyme sets that are produced during the degradation of solid spruce wood in these fungi. These findings expand the knowledge on enzyme production in nature-mimicking conditions and may contribute to the exploitation of white rot fungi and their enzymes for biotechnological applications.
ESWT Diminishes Axonal Regeneration following Repair of the Rat Median Nerve with Muscle-In-Vein Conduits but Not after Autologous Nerve Grafting
Authors: Heinzel Johannes C. , Oberhauser Viola , Keibl Claudia , Schädl Barbara , Swiadek Nicole V. , Längle Gregor , Frick Helen , Slezak Cyrill , Prahm Cosima , Grillari Johannes , Kolbenschlag Jonas , Hercher David
Published: July 2022

Investigations reporting positive effects of extracorporeal shockwave therapy (ESWT) on nerve regeneration are limited to the rat sciatic nerve model. The effects of ESWT on muscle-in-vein conduits (MVCs) have also not been investigated yet. This study aimed to evaluate the effects of ESWT after repair of the rat median nerve with either autografts (ANGs) or MVCs. In male Lewis rats, a 7 mm segment of the right median nerve was reconstructed either with an ANG or an MVC. For each reconstructive technique, one group of animals received one application of ESWT while the other rats served as controls. The animals were observed for 12 weeks, and nerve regeneration was assessed using computerized gait analysis, the grasping test, electrophysiological evaluations and histological quantification of axons, blood vessels and lymphatic vasculature. Here, we provide for the first time a comprehensive analysis of ESWT effects on nerve regeneration in a rat model of median nerve injury. Furthermore, this study is among the first reporting the quantification of lymphatic vessels following peripheral nerve injury and reconstruction in vivo. While we found no significant direct positive effects of ESWT on peripheral nerve regeneration, results following nerve repair with MVCs were significantly inferior to those after ANG repair.
Novel Motion Sequences in Plant-Inspired Robotics: Combining Inspirations from Snap-Trapping in Two Plant Species into an Artificial Venus Flytrap Demonstrator
Authors: Tauber Falk J. , Auth Philipp , Teichmann Joscha , Scherag Frank D. , Speck Thomas
Published: July 2022

The field of plant-inspired robotics is based on principles underlying the movements and attachment and adaptability strategies of plants, which together with their materials systems serve as concept generators. The transference of the functions and underlying structural principles of plants thus enables the development of novel life-like technical materials systems. For example, principles involved in the hinge-less movements of carnivorous snap-trap plants and climbing plants can be used in technical applications. A combination of the snap-trap motion of two plant species (Aldrovanda vesiculosa and Dionaea muscipula) has led to the creation of a novel motion sequence for plant-inspired robotics in an artificial Venus flytrap system, the Venus Flyflap. The novel motion pattern of Venus Flyflap lobes has been characterized by using four state-of-the-art actuation systems. A kinematic analysis of the individual phases of the new motion cycle has been performed by utilizing precise pneumatic actuation. Contactless magnetic actuation augments lobe motion into energy-efficient resonance-like oscillatory motion. The use of environmentally driven actuator materials has allowed autonomous motion generation via changes in environmental conditions. Measurement of the energy required for the differently actuated movements has shown that the Venus Flyflap is not only faster than the biological models in its closing movement, but also requires less energy in certain cases for the execution of this movement.
Effect of Menin Deletion in Early Osteoblast Lineage on the Mineralization of an In Vitro 3D Osteoid-like Dense Collagen Gel Matrix
Authors: Troka Ildi , Griffanti Gabriele , Canaff Lucie , Hendy Geoffrey , Goltzman David , Nazhat Showan
Published: July 2022

Bone has a complex microenvironment formed by an extracellular matrix (ECM) composed mainly of mineralized type I collagen fibres. Bone ECM regulates signaling pathways important in the differentiation of osteoblast-lineage cells, necessary for bone mineralization and in preserving tissue architecture. Compared to conventional 2D cell cultures, 3D in vitro models may better mimic bone ECM and provide an environment to support osteoblastic differentiation. In this study, a biomimetic 3D osteoid-like dense collagen gel model was used to investigate the role of the nuclear protein menin plays in osteoblastic differentiation and matrix mineralization. Previous in vitro and in vivo studies have shown that when expressed at later stages of osteoblastic differentiation, menin modulates osteoblastogenesis and regulates bone mass in adult mice. To investigate the role of menin when expressed at earlier stages of the osteoblastic lineage, conditional knockout mice in which the Men1 gene is specifically deleted early (i.e., at the level of the pluripotent mesenchymal stem cell lineage), where generated and primary calvarial osteoblasts were cultured in plastically compressed dense collagen gels for 21 days. The proliferation, morphology and differentiation of isolated seeded primary calvarial osteoblasts from knockout (Prx1-Cre; Men1f/f) mice were compared to those isolated from wild-type (Men1f/f) mice. Primary calvarial osteoblasts from knockout and wild-type mice did not show differences in terms of proliferation. However, in comparison to wild-type cells, primary osteoblast cells derived from knockout mice demonstrated deficient mineralization capabilities and an altered gene expression profile when cultured in 3D dense collagen gels. In summary, these findings indicate that when expressed at earlier stages of osteoblast differentiation, menin is important in maintaining matrix mineralization in 3D dense collagen gel matrices, in vitro.
Direct and Sensitive Electrochemical Evaluation of Pramipexole Using Graphitic Carbon Nitride (gCN) Sensor
Authors: Shanbhag Yogesh M. , Shanbhag Mahesh M. , Malode Shweta J. , Dhanalakshmi S. , Mondal Kunal , Shetti Nagaraj P.
Published: July 2022

Pramipexole (PMXL) belongs to the benzothiazole class of aromatic compounds and is used in treating Parkinson’s disease; however, overdosage leads to some abnormal effects that could trigger severe side effects. Therefore, it demands a sensitive analytical tool for trace level detection. In this work, we successfully developed an electrochemical sensor for the trace level detection of PMXL, using the voltammetric method. For the analysis, graphitic carbon nitride (gCN) was opted and synthesized by using a high-temperature thermal condensation method. The synthesized nanoparticles were employed for surface characterization, using transmission electron microscopy (TEM), X-ray diffraction (XRD), and atomic force microscopy (AFM) techniques. The electrochemical characterization of the material was evaluated by using the electrochemical impedance spectroscopy (EIS) technique to evaluate the solution–electrode interface property. The cyclic voltammetry (CV) behavior of PMXL displayed an anodic peak in the forward scan, indicating that PMXL underwent electrooxidation, and an enhanced detection peak with lower detection potential was achieved for gCN-modified carbon paste electrode (gCN·CPE). The influence of different parameters on the electrochemical behavior was analyzed, revealing the diffusion governing the electrode process with an equal number of hydronium ions and electron involvement. For the fabricated gCN·CPE, good linearity range was noticed from 0.05 to 500 µM, and a lower detection limit (LD) of 0.012 µM was achieved for the selected concentration range (0.5 to 30 µM). Selectivity of the electrode in PMXL detection was investigated by conducting an interference study, while the tablet sample analysis demonstrates the sensitive and real-time application of the electrode. The good recovery values for the analysis illustrate the efficiency of the electrode for PMXL analysis.