bluuebunny/crossref_metadata_2025 huggingface dataset:
The Mediterranean Athlete’s Nutrition: Are Protein Supplements Necessary?
Authors: Passariello Catherine L. , Marchionni Silvia , Carcuro Mariateresa , Casali Giorgia , della Pasqua Alberto , Hrelia Silvana , Malaguti Marco , Lorenzini Antonello
Published: November 2020

(1) Background: It is recommended that an athlete, in order to ensure correct nutrition and performance, should consume between 1.2 and 2.0 g/kg/day of protein, while the daily recommended protein intake for a non-athlete is 0.8and 0.9 mg/kg/day. It is unclear if athletes living in Mediterranean countries are able to meet protein requirements without supplementation, since Mediterranean diet de-emphasizes meat and meat products. (2) Methods: 166 athletes (125 males) enrolled between 2017 and 2019 were required to keep a dietary journal for three consecutive days (2 workdays and 1 weekend day). Athletes had to be >18 years old, train in a particular sport activity more than 3 h a week and compete at least at an amateur level. Journal data were collected and then translated into macro-nutrient content (grams of protein, carbohydrates, and lipids) by a nutritionist. (3) Results: The protein intake reported by this specific population vary slightly from the Academy of Nutrition and Dietetics (AND), Dietitians of Canada (DC), and the American College of Sports Medicine (ACSM) joint statement recommendation level. Average protein levels without protein supplementation fell within the protein guidelines. Counterintuitively, the intake among those who supplemented their diet with protein was higher compared with those who did not, even when excluding the contribution of supplements. Although the majority of subjects participating in the study were able to meet protein intake recommended for athletes without protein supplementation, 27% of athletes were below the guideline range. (4) Conclusions: these data suggest that athletes’ nutrition should be more often evaluated by a nutritionist and that they will benefit from increasing their nutritional knowledge in order to make better food choices, resorting to protein supplementation only when effectively needed.
Association between Body Mass Index and Sensory Processing in Childhood: InProS Study
Authors: Navarrete-Muñoz Eva-María , Fernández-Pires Paula , Mubarak-García Carmela , Espinosa-Sempere Cristina , Peral-Gómez Paula , Juárez-Leal Iris , Sánchez-Pérez Alicia , Pérez-Vázquez María-Teresa , Hurtado-Pomares Miriam , Valera-Gran Desirée
Published: November 2020

We assessed the association between body mass index (BMI) and sensory processing in 445 Spanish children aged 3–7 from the InProS project. Child sensory processing was measured using the short sensory profile (SSP); an atypical sensory performance was defined as an SSP total score <155 and scores of tactile sensitivity <30; taste/smell sensitivity <15; movement sensitivity <13; under-responsive/seeks sensation <27; auditory filtering <23; low energy/weak <26; and visual/auditory sensitivity <19. The BMI was calculated according to the cutoffs by the World Health Organization for children aged 0–5 and 5–19 years. We used multiple Poisson regression models with robust variance to obtain prevalence ratios (PR). No associations between children’s overweight and obesity and the prevalence of atypical sensory outcomes were observed. A one-point increase in BMI was significantly associated with a higher prevalence of atypical tactile sensitivity (PR = 1.07, 95% CI: 1.02; 1.12). A statistically marginal association was also observed for atypical total SSP (PR = 1.03, 95% CI: 1.00; 1.07) and atypical movement sensitivity (PR = 1.05, 95% CI: 1.00; 1.10). To our knowledge, this is the first time the association between children’s BMI and sensory processing has been reported. Our findings suggest that sensory processing issues may play a part in the complex context of childhood obesity. Further research is required to confirm these findings.
Effects of Cocoa Polyphenols and Dark Chocolate on Obese Adults: A Scoping Review
Authors: Halib Hasmiza , Ismail Amin , Mohd Yusof Barakatun-Nisak , Osakabe Naomi , Mat Daud Zulfitri Azuan
Published: November 2020

Obesity remains a major public health problem due to its increasing prevalence. Natural products have become common as adjunct therapeutic agents for treating obesity and preventing metabolic diseases. Cocoa and its products are commonly consumed worldwide. Dark chocolate, a rich source of polyphenols, has received attention lately for its beneficial role in the management of obesity; however, conflicting results are still being reported. This scoping review aims to provide a comprehensive understanding of the existing literature on the relationship and effects of cocoa and dark chocolate intake among obese adults. We searched multiple databases for research investigating the consumption of cocoa and/or dark chocolate in managing obesity among adults. This review includes epidemiological and human studies that were published in English over the last 10 years. Our review of the current literature indicates that epidemiological and human trials with obese adults have shown inconsistent results, which may be due to the different populations of subjects, and different types of cocoa products and doses used for intervention. Studies among obese adults are mainly focusing on obese individuals with comorbidities, as such more studies are needed to elucidate the role of cocoa polyphenols in weight control and preventing the risk of chronic diseases among obese individuals without comorbidities as well as healthy individuals. Careful adjustment of confounding factors would be required. The effects of cocoa and dark chocolate intake on obese adults were discussed, and further research is warranted to identify the gaps.
Short-Term Medical Cannabis Treatment Regimens Produced Beneficial Effects among Palliative Cancer Patients
Authors: Aviram Joshua , Lewitus Gil , Vysotski Yelena , Uribayev Anton , Procaccia Shiri , Cohen Idan , Leibovici Anca , Abo-Amna Mahmud , Akria Luiza , Goncharov Dmitry , Mativ Neomi , Kauffman Avia , Shai Ayelet , Hazan Or , Bar-Sela Gil , Meiri David
Published: November 2020

In the last decade the use of medical cannabis (MC) for palliative cancer treatment has risen. However, the choice between products is arbitrary and most patients are using Tetrahydrocannabinol (THC)-dominant cannabis products. In this study, we aimed to assess the short-term outcomes of MC treatment prescribed by oncologists in relation to the type of cannabis they receive. A comparative analysis was used to assess the differences in treatment effectiveness and safety between THC-dominant (n = 56, 52%), cannabidiol (CBD)-dominant (n = 19, 18%), and mixed (n = 33, 30%) MC treatments. Oncology patients (n = 108) reported on multiple symptoms in baseline questionnaires, initiated MC treatment, and completed a one-month follow-up. Most parameters improved significantly from baseline, including pain intensity, affective and sensory pain, sleep quality and duration, cancer distress, and both physical and psychological symptom burden. There was no significant difference between the three MC treatments in the MC-related safety profile. Generally, there were no differences between the three MC treatments in pain intensity and in most secondary outcomes. Unexpectedly, CBD-dominant oil treatments were similar to THC-dominant treatments in their beneficial effects for most secondary outcomes. THC-dominant treatments showed significant superiority in their beneficial effect only in sleep duration compared to CBD-dominant treatments. This work provides evidence that, though patients usually consume THC-dominant products, caregivers should also consider CBD-dominant products as a useful treatment for cancer-related symptoms.
From Zn(II) to Cu(II) Detection by MRI Using Metal-Based Probes: Current Progress and Challenges
Authors: Malikidogo Kyangwi P. , Martin Harlei , Bonnet Célia S.
Published: November 2020

Zinc and copper are essential cations involved in numerous biological processes, and variations in their concentrations can cause diseases such as neurodegenerative diseases, diabetes and cancers. Hence, detection and quantification of these cations are of utmost importance for the early diagnosis of disease. Magnetic resonance imaging (MRI) responsive contrast agents (mainly Lanthanide(+III) complexes), relying on a change in the state of the MRI active part upon interaction with the cation of interest, e.g., switch ON/OFF or vice versa, have been successfully utilized to detect Zn2+ and are now being developed to detect Cu2+. These paramagnetic probes mainly exploit the relaxation-based properties (T1-based contrast agents), but also the paramagnetic induced hyperfine shift properties (paraCEST and parashift probes) of the contrast agents. The challenges encountered going from Zn2+ to Cu2+ detection will be stressed and discussed herein, mainly involving the selectivity of the probes for the cation to detect and their responsivity at physiologically relevant concentrations. Depending on the response mechanism, the use of fast-field cycling MRI seems promising to increase the detection field while keeping a good response. In vivo applications of cation responsive MRI probes are only in their infancy and the recent developments will be described, along with the associated quantification problems. In the case of relaxation agents, the presence of another method of local quantification, e.g., synchrotron X-Ray fluorescence, single-photon emission computed tomography (SPECT) or positron emission tomography (PET) techniques, or 19F MRI is required, each of which has its own advantages and disadvantages.
Effect of Sulfur Variation on the Vulcanizate Structure of Silica-Filled Styrene-Butadiene Rubber Compounds with a Sulfide–Silane Coupling Agent
Authors: Han Sangwook , Gu Bonyoung , Kim Sungwoo , Kim Seongrae , Mun Dalyong , Morita Koichi , Kim Donghyuk , Kim Wonho
Published: November 2020

The vulcanizate structure of filled compounds is affected by filler–rubber interactions (FRI) and the chemical crosslink density (CCD) of the matrix rubber. In particular, in filled compounds using a silica–silane system, FRIs due to silica–rubber coupling are a major influencing factor for the vulcanizate structure and physical properties. In this study, the effect of sulfur variation on the vulcanizate structure of silica-filled solution styrene–butadiene rubber compounds using a sulfide–silane coupling agent was studied. The vulcanizate structure according to sulfur variation was quantitatively analyzed using the swelling test and Flory–Rehner and Kraus equations. As the sulfur content increased, both FRI and the CCD increased, and it was confirmed that sulfur variation influenced the silica–rubber coupling efficiency through increased FRI. In addition, field emission scanning electron microscope images showed that increased FRI contributed to improvements in silica dispersion, abrasion resistance, and energy loss characteristics.
Research on Non-Uniform Wear of Liner in SAG Mill
Authors: Wu Wanrong , Che Haoran , Hao Qianhua
Published: November 2020

The numerical calculation method is used to analyze the wear of the liner of the general structure of a semi-autogenous mill in the axial direction, and the non-uniform wear of each area of the liner is studied to explore the reasons for said wear. The liner is divided into areas along the axial direction, and the discrete element method (DEM) is used to analyze the relationship between the wear volume of each area and the total mass of particles. The composition ratio of the rocks and steel balls in each area, and its relationship with time, are also studied. The results show that the total mass of the particles in the area has a significant effect on the wear of the liner. When the particles are affected by the conical end cover on both sides during the operation of the mill, they will be stratified along the axial direction. The particles with large masses will accumulate on both sides of the mill, and the particles with small masses will be concentrated in the middle of the mill. As a result, the difference between the density and impact energy of rocks and steel balls in each area is caused, and eventually, the mill liner appears to have non-uniform wear.
Methanogenic Microorganisms in Industrial Wastewater Anaerobic Treatment
Authors: Vítězová Monika , Kohoutová Anna , Vítěz Tomáš , Hanišáková Nikola , Kushkevych Ivan
Published: November 2020

Over the past decades, anaerobic biotechnology is commonly used for treating high-strength wastewaters from different industries. This biotechnology depends on interactions and co-operation between microorganisms in the anaerobic environment where many pollutants’ transformation to energy-rich biogas occurs. Properties of wastewater vary across industries and significantly affect microbiome composition in the anaerobic reactor. Methanogenic archaea play a crucial role during anaerobic wastewater treatment. The most abundant acetoclastic methanogens in the anaerobic reactors for industrial wastewater treatment are Methanosarcina sp. and Methanotrix sp. Hydrogenotrophic representatives of methanogens presented in the anaerobic reactors are characterized by a wide species diversity. Methanoculleus sp., Methanobacterium sp. and Methanospirillum sp. prevailed in this group. This work summarizes the relation of industrial wastewater composition and methanogen microbial communities present in different reactors treating these wastewaters.
Optimization of an Inter-Plant Hydrogen Network: A Simultaneous Approach to Solving Multi-Period Optimization Problems
Authors: Han Rusong , Kang Lixia , Jiang Yinghua , Wang Jing , Liu Yongzhong
Published: November 2020

Inter-plant hydrogen integration can reduce the consumption of hydrogen utility in petrochemical parks. However, the fluctuation of operating conditions will lead to complex multi-period problems of hydrogen network integration. This work develops a simultaneous optimization approach to solving multi-period optimization problems for the inter-plant hydrogen network. To do this, we consider the inter-plant hydrogen integration and the fluctuation of operating conditions in each plant at the same time, and aim to minimize the total annualized cost of the entire hydrogen system of all plants involved. An industrial case study of a three-plant hydrogen network with seven subperiods was adopted to verify the effectiveness of the proposed method. Results show that the optimal structure and the corresponding scheduling scheme can be obtained when the lowest cost of the system is targeted. Compared with the stepwise methods, the proposed approach features taking the characteristics of all subperiods into account simultaneously and making the structure of the hydrogen network much more effective and economical. For the scheduling schemes, the utilization efficiency of the internal hydrogen sources is increased by hydrogen exchange among the plants.
Carrier Phase-Based Ionospheric Gradient Monitor Under the Mixed Gaussian Distribution
Authors: Cheng Jianhua , Li Jiaxiang , Li Liang , Jiang Chao , Qi Bing
Published: November 2020

Anomalous ionospheric gradient is a critical risk to be monitored by ground-based augmentation systems (GBASs) utilized for safety-of-life navigation applications. A dual-frequency carrier phase-based ionospheric gradient monitoring method is proposed under the mixed Gaussian distribution. The minimum detection error of the proposed method can be greatly reduced by allowing acceptable ambiguity resolution failure modes, given the required averaging length. The real BeiDou navigation satellite system data were utilized to test the proposed method. The experimental results showed that the minimum detection error (MDE) of the proposed dual-frequency ionospheric gradient monitoring method can be reduced by at least 30% in comparison with the maximum acceptable anomalous ionospheric gradient of category III GBAS. This study demonstrated that the proposed method can be used to protect against the ionospheric gradient for a ground-based augmentation system.
Soil Moisture Mapping Based on Multi-Source Fusion of Optical, Near-Infrared, Thermal Infrared, and Digital Elevation Model Data via the Bayesian Maximum Entropy Framework
Authors: Han Leran , Wang Chunmei , Liu Qiyue , Wang Gengke , Yu Tao , Gu Xingfa , Zhang Yunzhou
Published: November 2020

This paper proposes a combined approach wherein the optical, near-infrared, and thermal infrared data from the Landsat 8 satellite and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM) data are fused for soil moisture mapping under sparse sampling conditions, based on the Bayesian maximum entropy (BME) framework. The study was conducted in three stages. First, based on the maximum entropy principle of the information theory, a Lagrange multiplier was introduced to construct general knowledge, representing prior knowledge. Second, a principal component analysis (PCA) was conducted to extract three principal components from the multi-source data mentioned above, and an innovative and operable discrete probability method based on a fuzzy probability matrix was used to approximate the probability relationship. Thereafter, soft data were generated on the basis of the weight coefficients and coordinates of the soft data points. Finally, by combining the general knowledge with the prior information, hard data (HD), and soft data (SD), we completed the soil moisture mapping based on the Bayesian conditioning rule. To verify the feasibility of the combined approach, the ordinary kriging (OK) method was taken as a comparison. The results confirmed the superiority of the soil moisture map obtained using the BME framework. The map revealed more detailed information, and the accuracies of the quantitative indicators were higher compared with that for the OK method (the root mean squared error (RMSE) = 0.0423 cm3/cm3, mean absolute error (MAE) = 0.0399 cm3/cm3, and Pearson correlation coefficient (PCC) = 0.7846), while largely overcoming the overestimation issue in the range of low values and the underestimation issue in the range of high values. The proposed approach effectively fused inexpensive and easily available multi-source data with uncertainties and obtained a satisfactory mapping accuracy, thus demonstrating the potential of the BME framework for soil moisture mapping using multi-source data.
Novel Techniques for Void Filling in Glacier Elevation Change Data Sets
Authors: Seehaus Thorsten , Morgenshtern Veniamin , Hübner Fabian , Bänsch Eberhard , Braun Matthias
Published: November 2020

The increasing availability of digital elevation models (DEMs) facilitates the monitoring of glacier mass balances on local and regional scales. Geodetic glacier mass balances are obtained by differentiating DEMs. However, these computations are usually affected by voids in the derived elevation change data sets. Different approaches, using spatial statistics or interpolation techniques, were developed to account for these voids in glacier mass balance estimations. In this study, we apply novel void filling techniques, which are typically used for the reconstruction and retouche of images and photos, for the first time on elevation change maps. We selected 6210 km2 of glacier area in southeast Alaska, USA, covered by two void-free DEMs as the study site to test different inpainting methods. Different artificially voided setups were generated using manually defined voids and a correlation mask based on stereoscopic processing of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) acquisition. Three “novel” (Telea, Navier–Stokes and shearlet) as well as three “classical” (bilinear interpolation, local and global hypsometric methods) void filling approaches for glacier elevation data sets were implemented and evaluated. The hypsometric approaches showed, in general, the worst performance, leading to high average and local offsets. Telea and Navier–Stokes void filling showed an overall stable and reasonable quality. The best results are obtained for shearlet and bilinear void filling, if certain criteria are met. Considering also computational costs and feasibility, we recommend using the bilinear void filling method in glacier volume change analyses. Moreover, we propose and validate a formula to estimate the uncertainties caused by void filling in glacier volume change computations. The formula is transferable to other study sites, where no ground truth data on the void areas exist, and leads to higher accuracy of the error estimates on void-filled areas. In the spirit of reproducible research, we publish a software repository with the implementation of the novel void filling algorithms and the code reproducing the statistical analysis of the data, along with the data sets themselves.
Tree Species Classification in Mixed Deciduous Forests Using Very High Spatial Resolution Satellite Imagery and Machine Learning Methods
Authors: Deur Martina , Gašparović Mateo , Balenović Ivan
Published: November 2020

Spatially explicit information on tree species composition is important for both the forest management and conservation sectors. In combination with machine learning algorithms, very high-resolution satellite imagery may provide an effective solution to reduce the need for labor-intensive and time-consuming field-based surveys. In this study, we evaluated the possibility of using multispectral WorldView-3 (WV-3) satellite imagery for the classification of three main tree species (Quercus robur L., Carpinus betulus L., and Alnus glutinosa (L.) Geartn.) in a lowland, mixed deciduous forest in central Croatia. The pixel-based supervised classification was performed using two machine learning algorithms: random forest (RF) and support vector machine (SVM). Additionally, the contribution of gray level cooccurrence matrix (GLCM) texture features from WV-3 imagery in tree species classification was evaluated. Principal component analysis confirmed GLCM variance to be the most significant texture feature. Of the 373 visually interpreted reference polygons, 237 were used as training polygons and 136 were used as validation polygons. The validation results show relatively high overall accuracy (85%) for tree species classification based solely on WV-3 spectral characteristics and the RF classification approach. As expected, an improvement in classification accuracy was achieved by a combination of spectral and textural features. With the additional use of GLCM variance, the overall accuracy improved by 10% and 7% for RF and SVM classification approaches, respectively.
Development of a Wireless Telemetry Sensor Device to Measure Load and Deformation in Orthopaedic Applications
Authors: Anderson William D. , Wilson Sydney L. M. , Holdsworth David W.
Published: November 2020

Due to sensor size and supporting circuitry, in-vivo load and deformation measurements are currently restricted to applications within larger orthopaedic implants. The objective of this study is to repurpose a commercially available low-power, miniature, wireless, telemetric, tire-pressure sensor (FXTH87) to measure load and deformation for future use in orthopaedic and biomedical applications. The capacitive transducer membrane was modified, and compressive deformation was applied to the transducer to determine the sensor signal value and the internal resistive force. The sensor package was embedded within a deformable enclosure to illustrate potential applications of the sensor for monitoring load. To reach the maximum output signal value, sensors required compressive deformation of 350 ± 24 µm. The output signal value of the sensor was an effective predictor of the applied load on a calibrated plastic strain member, over a range of 35 N. The FXTH87 sensor can effectively sense and transmit load-induced deformations. The sensor does not have a limit on loads it can measure, as long as deformation resulting from the applied load does not exceed 350 µm. The proposed device presents a sensitive and precise means to monitor deformation and load within small-scale, deformable enclosures.
A Machine Learning Approach for the Automatic Estimation of Fixation-Time Data Signals’ Quality
Authors: Gabrieli Giulio , Balagtas Jan Paolo Macapinlac , Esposito Gianluca , Setoh Peipei
Published: November 2020

Fixation time measures have been widely adopted in studies with infants and young children because they can successfully tap on their meaningful nonverbal behaviors. While recording preverbal children’s behavior is relatively simple, analysis of collected signals requires extensive manual preprocessing. In this paper, we investigate the possibility of using different Machine Learning (ML)—a Linear SVC, a Non-Linear SVC, and K-Neighbors—classifiers to automatically discriminate between Usable and Unusable eye fixation recordings. Results of our models show an accuracy of up to the 80%, suggesting that ML tools can help human researchers during the preprocessing and labelling phase of collected data.
New Service Virtualisation Approach to Generate the Categorical Fields in the Service Response
Authors: Farahmandpour Zeinab , Seyedmahmoudian Mehdi , Stojcevski Alex
Published: November 2020

Software services communicate with different requisite services over the computer network to accomplish their tasks. The requisite services may not be readily available to test a specific service. Thus, service virtualisation has been proposed as an industry solution to ensure availability of the interactive behaviour of the requisite services. However, the existing techniques of virtualisation cannot satisfy the required accuracy or time constraints to keep up with the competitive business world. These constraints sacrifices quality and testing coverage, thereby delaying the delivery of software. We proposed a novel technique to improve the accuracy of the existing service virtualisation solutions without sacrificing time. This method generates the service response and predicts categorical fields in virtualised responses, extending existing research with lower complexity and higher accuracy. The proposed service virtualisation approach uses conditional entropy to identify the fields that can be used to drive the value of each categorical field based on the historical messages. Then, it uses joint probability distribution to find the best values for the categorical fields. The experimental evaluation illustrates that the proposed approach can generate responses with the required fields and accurate values for categorical fields over four data sets with stateful nature.
Design of a Scalable and Fast YOLO for Edge-Computing Devices
Authors: Han Byung-Gil , Lee Joon-Goo , Lim Kil-Taek , Choi Doo-Hyun
Published: November 2020

With the increase in research cases of the application of a convolutional neural network (CNN)-based object detection technology, studies on the light-weight CNN models that can be performed in real time on the edge-computing devices are also increasing. This paper proposed scalable convolutional blocks that can be easily designed CNN networks of You Only Look Once (YOLO) detector which have the balanced processing speed and accuracy of the target edge-computing devices considering different performances by exchanging the proposed blocks simply. The maximum number of kernels of the convolutional layer was determined through simple but intuitive speed comparison tests for three edge-computing devices to be considered. The scalable convolutional blocks were designed in consideration of the limited maximum number of kernels to detect objects in real time on these edge-computing devices. Three scalable and fast YOLO detectors (SF-YOLO) which designed using the proposed scalable convolutional blocks compared the processing speed and accuracy with several conventional light-weight YOLO detectors on the edge-computing devices. When compared with YOLOv3-tiny, SF-YOLO was seen to be 2 times faster than the previous processing speed but with the same accuracy as YOLOv3-tiny, and also, a 48% improved processing speed than the YOLOv3-tiny-PRN which is the processing speed improvement model. Also, even in the large SF-YOLO model that focuses on the accuracy performance, it achieved a 10% faster processing speed with better accuracy of 40.4% mAP@0.5 in the MS COCO dataset than YOLOv4-tiny model.
Copper Content Inversion of Copper Ore Based on Reflectance Spectra and the VTELM Algorithm
Authors: Fu Yanhua , Xie Hongfei , Mao Yachun , Ren Tao , Xiao Dong
Published: November 2020

Copper is an important national resource, which is widely used in various sectors of the national economy. The traditional detection of copper content in copper ore has the disadvantages of being time-consuming and high cost. Due to the many drawbacks of traditional detection methods, this paper proposes a new method for detecting copper content in copper ore, that is, through the spectral information of copper ore content detection method. First of all, we use chemical methods to analyze the copper content in a batch of copper ores, and accurately obtain the copper content in those ores. Then we do spectrometric tests on this batch of copper ore, and get accurate spectral data of copper ore. Based on the data obtained, we propose a new two hidden layer extreme learning machine algorithm with variable hidden layer nodes and use the regularization standard to constrain the extreme learning machine. Finally, the prediction model of copper content in copper ore is established by using the algorithm. Experiments show that this method of detecting copper ore content using spectral information is completely feasible, and the algorithm proposed in this paper can detect the copper content in copper ores faster and more accurately.
Visual Sorting of Express Parcels Based on Multi-Task Deep Learning
Authors: Han Song , Liu Xiaoping , Han Xing , Wang Gang , Wu Shaobo
Published: November 2020

Visual sorting of express parcels in complex scenes has always been a key issue in intelligent logistics sorting systems. With existing methods, it is still difficult to achieve fast and accurate sorting of disorderly stacked parcels. In order to achieve accurate detection and efficient sorting of disorderly stacked express parcels, we propose a robot sorting method based on multi-task deep learning. Firstly, a lightweight object detection network model is proposed to improve the real-time performance of the system. A scale variable and the joint weights of the network are used to sparsify the model and automatically identify unimportant channels. Pruning strategies are used to reduce the model size and increase the speed of detection without losing accuracy. Then, an optimal sorting position and pose estimation network model based on multi-task deep learning is proposed. Using an end-to-end network structure, the optimal sorting positions and poses of express parcels are estimated in real time by combining pose and position information for joint training. It is proved that this model can further improve the sorting accuracy. Finally, the accuracy and real-time performance of this method are verified by robotic sorting experiments.
140 GHz Ultra-Long Bessel–Like Beam with Near-Wavelength Beamwidth
Authors: Ok Gyeongsik , Park Kee Jai
Published: November 2020

The Bessel–Gauss beam has outstanding features, such as long depth of focus (DOF) and super resolution for nondestructive imaging inspection. However, most approaches for generating a nondiffractive beam have mainly focused on extending the DOF. In this study, the ultra-long high-resolution Bessel–like beam was first demonstrated in a sub-THz wave range (140 GHz). An axicon lens having an apex angle of 110° was used to generate the highly focused Bessel–like beam. To extend the depth of focus, we varied the incident beam angle on the axicon by moving the first lens distance. With the newly developed beam profiler, 3D beam profiles were acquired for characterizing in detail the beam propagation. As a result, even if the depth of focus was 72 times (154 mm) the source wavelength (2.143 mm), the focusing beamwidth was simultaneously maintained at 1.4 times (3.0 mm) the wavelength (i.e., the near-wavelength beamwidth). An ultra-long needle beam of near-wavelength size can promote the applicability of the sub-THz imaging technique in noninvasive sensing applications, such as computer tomography, materials inspection, and through-the-wall-imaging.
Autonomous Corrosion Assessment of Reinforced Concrete Structures: Feasibility Study
Authors: Taffese Woubishet Zewdu , Nigussie Ethiopia
Published: November 2020

In this work, technological feasibility of autonomous corrosion assessment of reinforced concrete structures is studied. Corrosion of reinforcement bars (rebar), induced by carbonation or chloride penetration, is one of the leading causes for deterioration of concrete structures throughout the globe. Continuous nondestructive in-service monitoring of carbonation through pH and chloride ion (Cl−) concentration in concrete is indispensable for early detection of corrosion and making appropriate decisions, which ultimately make the lifecycle management of RC structures optimal from resources and safety perspectives. Critical state-of-the-art review of pH and Cl− sensors revealed that the majority of the sensors have high sensitivity, reliability, and stability in concrete environment, though the experiments were carried out for relatively short periods. Among the reviewed works, only three attempted to monitor Cl− wirelessly, albeit over a very short range. As part of the feasibility study, this work recommends the use of internet of things (IoT) and machine learning for autonomous corrosion condition assessment of RC structures.
Mechanical Energy before Chemical Energy at the Origins of Life?
Authors: Hansma Helen Greenwood
Published: November 2020

Mechanical forces and mechanical energy are prevalent in living cells. This may be because mechanical forces and mechanical energy preceded chemical energy at life’s origins. Mechanical energy is more readily available in nonliving systems than the various forms of chemical energy used by living systems. Two possible prebiotic environments that might have provided mechanical energy are hot pools that experience wet/dry cycles and mica sheets as they move, open and shut, as heat pumps or in response to water movements.
Bioethanol Production from Date Seed Cellulosic Fraction Using Saccharomyces cerevisiae
Authors: Bouaziz Fatma , Abdeddayem Amal Ben , Koubaa Mohamed , Barba Francisco J. , Jeddou Khawla Ben , Kacem Imen , Ghorbel Raoudha Ellouz , Chaabouni Semia Ellouz
Published: November 2020

This study investigates the feasibility of producing ethanol from date palm seeds. The chemical compositions of three varieties of date seeds were first studied, showing mainly the presence of cellulose and hemicellulose. Ethanol was produced after a pre-treatment of date seeds using acid hydrolysis to extract the cellulosic fraction and to remove the lignin. Producing ethanol by fermentation was performed using the yeast Saccharomyces cerevisiae for 24 h, during which ethanol yield, biomass concentration, and total reducing sugars were recorded. The results obtained showed that the sugar content decreased over time, while ethanol production increased. Indeed, date seeds gave the highest ethanol concentration of 21.57 g/L after 6 h of alcoholic fermentation. These findings proved the feasibility of producing ethanol from date seeds.
Efficacy and Safety of Lopinavir/Ritonavir for Treatment of COVID-19: A Systematic Review and Meta-Analysis
Authors: Alhumaid Saad , Al Mutair Abbas , Al Alawi Zainab , Alhmeed Naif , Zaidi Abdul Rehman Zia , Tobaiqy Mansour
Published: November 2020

(Background) Lopinavir-ritonavir (LPV/RTV) is a human immunodeficiency virus (HIV) antiviral combination that has been considered for the treatment of COVID-19 disease. (Aim) This systematic review aimed to assess the efficacy and safety of LPV/RTV in COVID-19 patients in the published research. (Methods) A protocol was developed based on the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) statement. Articles were selected for review from 8 electronic databases. This review evaluated the effects of LPV/RTV alone or in combination with standard care ± interferons/antiviral treatments compared to other therapies, regarding duration of hospital stay, risk of progressing to invasive mechanical, time to virological cure and body temperature normalization, cough relief, radiological progression, mortality and safety. (Results) A consensus was reached to select 32 articles for full-text screening; only 14 articles comprising 9036 patients were included in this study; and eight of these were included for meta-analysis. Most of these studies did not report positive clinical outcomes with LPV/RTV treatment. In terms of virological cure, three studies reported less time in days to achieve a virological cure for LPV/RTV arm relative to no antiviral treatment (−0.81 day; 95% confidence interval (CI), −4.44 to 2.81; p = 0.007, I2 = 80%). However, the overall effect was not significant (p = 0.66). When comparing the LPV/RTV arm to umifenovir arm, a favorable affect was observed for umifenovir arm, but not statically significant (p = 0.09). In terms of time to body normalization and cough relief, no favorable effects of LPV/RTV versus umifenovir were observed. The largest trials (RECOVERY and SOLIDARITY) have shown that LPV/RTV failed to reduce mortality, initiation of invasive mechanical ventilation or hospitalization duration. Adverse events were reported most frequently for LPV/RTV (n = 84) relative to other antivirals and no antiviral treatments. (Conclusions) This review did not reveal any significant advantage in efficacy of LPV/RTV for the treatment of COVID-19 over standard care, no antivirals or other antiviral treatments. This result might not reflect the actual evidence.
A Glimmer of Hope: Recent Updates and Future Challenges in Zika Vaccine Development
Authors: Castanha Priscila M. S. , Marques Ernesto T. A.
Published: November 2020

The emergence and rapid spread of Zika virus (ZIKV) on a global scale as well as the establishment of a causal link between Zika infection and congenital syndrome and neurological disorders triggered unprecedented efforts towards the development of a safe and effective Zika vaccine. Multiple vaccine platforms, including purified inactivated virus, nucleic acid vaccines, live-attenuated vaccines, and viral-vectored vaccines, have advanced to human clinical trials. In this review, we discuss the recent advances in the field of Zika vaccine development and the challenges for future clinical efficacy trials. We provide a brief overview on Zika vaccine platforms in the pipeline before summarizing the vaccine candidates in clinical trials, with a focus on recent, promising results from vaccine candidates that completed phase I trials. Despite low levels of transmission during recent years, ZIKV has become endemic in the Americas and the potential of large Zika outbreaks remains real. It is important for vaccine developers to continue developing their Zika vaccines, so that a potential vaccine is ready for deployment and clinical efficacy trials when the next ZIKV outbreak occurs.
Estimation of Nitrite—Nitric Oxide Derivative—In Horses with Intestinal Colic by ESR Spectroscopy
Authors: Borunova Seid-Fatima , Tkachev Nikolay , Iolchiev Baylar , Artyushina Zinaida , Abramov Pavel , Nikitina Marina , Silanteva Anastasia , Khusnetdinova Neilia , Serezhenkov Vladimir
Published: November 2020

Diseases of the gastrointestinal tract of horses are caused by many factors and have a complex pathogenesis. Developing effective methods of differential diagnostics is of high fundamental and applied importance. The pathogenesis of diseases of the digestive tract of horses accompanied by the development of inflammation and oxidative stress, can be associated with a lack of the nitrogen monoxide which controls many signaling pathways in the body. The level of the nitric oxide (NO) is involved in the regulation of the immune and nervous systems, the tone of all the blood vessels, and the courses of many pathological processes. The nitric oxide activates guanylate cyclase (sGC) and leads to vascular relaxation. The aim of this investigation was to study the metabolites of nitric oxide in horses suffered from intestinal diseases. The levels of nitric oxide in the blood serum of horses depending on their age and health state was studied. The concentration of nitrites in the blood serum of horses aged 6–25 years was 3.4 ± 4.2 μM, and in the young horses (1–5 years) the level of this indicator was 8.2 ± 5.4 μM. A sharp decrease in nitrite was observed in all the horses with intestinal diseases of 2 ± 0.9 μM, especially with tympanitic caecun of 0.6 ± 0.4 μM and with spasmodic colic of 1.8 ± 0.5 μM. The level of nitrosylhemoglobin HbNO in the blood of the diseased animals was higher than that in clinically healthy horses, regardless of age.
Analysis of Water Droplet Distribution in Wind for the Fluidic Sprinkler
Authors: Dwomoh Frank Agyen , Yuan Shouqi , Li Hong , Zhu Xingye , Liu Junping , Mensah Richard , Fordjour Alexander
Published: November 2020

The fluidic sprinkler, a relatively new type of rotating sprinkler, has been the subject of quite a lot of research about its structural parameters, hydraulic characteristics, and water distribution profile, albeit under indoor conditions. The fluidic sprinkler’s performance in terms of water distribution profile and droplet size distribution pattern in wind has seen little investigation. To obtain information about its droplet size distribution in wind, the Thiess Clima Laser Precipitation Monitor was employed. Drop diameter, drop velocity, and the number of drops at varying distances from the fluidic sprinkler were measured in both wind and no wind at three operating pressures of 250, 300, and 350 kPa. The logistic model was adopted to fit a relationship between the drop diameter and the cumulative numeric frequency (CNF) and the cumulative volumetric frequency (CVF) values resulting in very high correlation coefficient (R2) values of above 0.99 for all conditions. At 250, 300, and 350 kPa, drops traveled 0.6, 1.0, and 1.3 m, respectively, farther in wind than in no wind along the direction of throw. Drops exhibited a spectrum of velocities and diameters at a given radial distance from the sprinkler. Up to two-thirds of the radius of throw, the proportion of drops with diameters ranging from 0.125 mm to 1.00 mm were above 80% at 300 and 350 kPa.
Radon as a Natural Tracer for Monitoring NAPL Groundwater Contamination
Authors: Mattia Martina , Tuccimei Paola , Soligo Michele , Carusi Claudio
Published: November 2020

In this research, the radioactive noble gas radon was used as a tracer for Non-Aqueous Phase Liquids (NAPLs) contamination, since it is much more soluble in these substances than in air or water. Soil radon remains trapped within the NAPLs, resulting in a local reduction in the radon concentration within close proximity to the contaminated area. This technique was applied to a contaminated site in Roma (Italy). The main residual NAPLs are total hydrocarbons and methyl-tertiary-butyl ether (MTBE), a water-soluble additive. The monitoring activities included two sampling campaigns of groundwater from 18 wells in February and May 2020. Concentration maps were produced using radon data. The results show that the radon deficit traces the location of NAPLs in the fuelling station very well, with a residual source zone extending in a NNW-SSE direction. A good correspondence between a low amount of radon and a higher concentration of NAPLs was found. A reduction in the average amount of radon in the May 2020 survey indicated a stronger remobilization of NAPLs compared to that of the February 2020 monitoring campaign. The peaks of Volatile Organic Compounds (VOCs) detected between 8–9 and 11–12 m depths indicate the presence of residual blobs of NAPLs in the vadose zone of the aquifer.
CAMUFLAGEM ORTODÔNTICA DA MÁ OCLUSÃO DE CLASSE III COM ENVOLVIMENTO ESQUELÉTICO ASSOCIADO À MORDIDA ABERTA ANTERIOR COM PRESCRIÇÃO BIOFUNCIONAL
Authors: Barbosa José Felipe Claudino , Valarelli Danilo Pinelli , Cotrin Paula , Freitas Karina Maria Salvatore , Valarelli Fabricio Pinelli
Published: November 2020

Introdução: A escolha pelo melhor protocolo de tratamento para a Classe III estará na interdependência dos fatores etiológicos envolvidos. Uma das opções para o tratamento compensatório desta má-oclusão é o uso da prescrição Biofuncional, cuja principal característica é o torque lingual nos incisivos superiores e vestibular nos incisivos inferiores, que funcionaria como uma resistência ao movimento indesejado da maioria das mecânicas convencionais com elásticos de Classe III. Objetivo: O presente caso clínico relata o tratamento de uma paciente com má oclusão de Classe III associada à mordida aberta anterior. Método: Foi utilizado a técnica Biofuncional e elásticos intermaxilares para a correção da má oclusão, concomitante ao uso da grade palatina fixa. Resultados: Houve a correção das discrepâncias sagitais e transversais, sem prejuízo a estética do sorriso e facial da paciente. Conclusão: A prescrição Biofuncional pode ser utilizada no tratamento compensatório da má-oclusão de Classe III
TRATAMENTO DE QUEIMADURAS: ANÁLISE DE VÍDEOS DO YOUTUBE®
Authors: Freitas Noélle De Oliveira , Da Silva Bruna Carolayne Neves , Almeida Maria das Dores Dos Santos , Pereira Nathalia Aparecida Martins , De Oliveira Alfredo Almeida Pina , Pan Raquel
Published: November 2020

Introdução: Recursos disponíveis na internet, como vídeos, passaram a ser utilizados como meios de informação da população sobre tratamento de queimaduras por se tratar de uma informação mais acessível e direta. Objetivos: Analisar as informações de vídeos do Youtube® sobre o tratamento de queimaduras. Método: Estudo descritivo com abordagem quantitativa, realizadopor meio de levantamento de vídeos disponíveis no Youtube® sobre tratamentos para queimaduras produzidos entre janeiro de 2013 a julho de 2019.Resultados: Foram incluídos 70 vídeos sobre tratamento de queimaduras, sendo identificados 30 (42,9%) sobre terapias complementares, seguidos de nove (12,9%) sobre tratamentos caseiros, nove (12,9%) sobre notícias ou entrevistas com profissionais, oito (11,4%) sobre tratamento tópico, sete (10,0%) educativos, cinco (7,1%) sobre tratamento cirúrgico e dois (2,9%) sobre reabilitação. Conclusões: Este estudo proporcionou conhecimento sobre os tratamentos abordados nos vídeos do Youtube®, destacando a importância em avaliar os conteúdos disponibilizados na internet para orientação da população.
Molecular detection and phylogenetic analysis of Theileria equi and Babesia caballi in wild horses in Konya province of Turkey
Authors: DERİNBAY EKİCİ Özlem , CEYLAN Onur , SÖNMEZ Gonca , DİK Bilal , CEYLAN Ceylan , SEMASSEL Asma
Published: November 2020

The aim of this study was to investigate equine piroplasms of wild horses (Equus ferus caballus) in Konya province of Turkey in November-December 2017. For this aim, blood samples were collected from 36 wild horses and examined for equine piroplasms by microscopy and multiplex PCR. Some of the PCR products from positive samples were also sequenced. Five (13.89%) out of the 36 horses were infected with either Theileria equi, Babesia caballi or both in the microscopical examination. Single infections with T. equi and B. caballi were detected in three (8.33%) and one horses (2.78%), respectively. Prevalence of T. equi, B. caballi and mix infections was determined as 50%, 38.8% and 38.8% by multiplex PCR, respectively. Multiplex PCR was found more sensitive than microscopical examination to detect the piroplasms of horses. The results of sequence analysis showed 99.25-100% and 98.23-99.59% nucleotide sequence identity to the previously reported T. equi and B. caballi 18S rRNA gene sequences, respectively. Consequently, the existence of equine piroplasmosis in wild horses was reported for the first time in Turkey, and high molecular prevalences of T. equi and B. caballi were reported with this study.