bluuebunny/crossref_metadata_2025 huggingface dataset:
Natural Resistances to Viruses in Cucurbits
Authors: Martín-Hernández Ana Montserrat , Picó Belén
Published: December 2020

Cucurbit viruses cause considerable economic losses worldwide. The most common viral diseases affecting this crop family are Potyviruses, Cucumoviruses, Criniviruses, Ipomoviruses, Tobamoviruses, and the emerging Begomoviruses. Four main cucurbit crops are grown worldwide, namely melon, cucumber (Cucumis), watermelon (Citrullus), and squash (Cucurbita). Huge natural variation is also available within each genus, providing valuable sources of genetic resistance to these diseases. Intraspecific and intrageneric diversity and crossability are key factors to select the optimum breeding strategies. Melon and cucumber are diverse species for which intraspecific resistance is available. Conversely, in Citrullus and Cucurbita, wild relatives provide the resistance diversity absent in watermelon and in C. pepo. Some of the classical sources used by breeders, many of which are multi-resistant, come from corresponding origin centers in Asia, Africa, and America, as well as from secondary centers of diversity. Genetic studies have identified dominant and recessive and often complex resistance. Many of the genes identified have been mapped and markers for MAS are available, but higher mapping resolutions are required to identify the corresponding genes. Only a few genes could be cloned and functionally characterized. Efforts are underway to use genome mapping and functional genomics to advance toward a genomic-assisted breeding against viral diseases in cucurbits.
Floristic Composition Mediates Change in Forage Nutritive Quality of Atlantic Mountain Grasslands after Experimental Grazing Exclusion
Authors: García-Baquero Gonzalo , Odriozola Iñaki , Aldezabal Arantza
Published: December 2020

Simultaneous reduction of biodiversity and forage nutritive value after grazing abandonment represents a critical agroecological problem observed in temperate mountain grasslands. However, how both processes affect each other after the exclusion of large grazers is not well understood. To address this knowledge gap, we used four Atlantic grassland sites in the Aralar masif (northern Iberian Peninsula) to ask whether floristic composition mediates change in forage nutritive quality after grazing exclusion, and, if so, how much of the effect on forage quality is mediated. To examine the effects of grazing exclusion on forage quality and floristic composition a repeated-measures (2005–10) randomized complete block experiment was used. Then, the direct effects of grazing exclusion on forage quality were disentangled from the indirect effects mediated by concurrent change in floristic composition. Grazing exclusion deteriorated forage mineral content, phosphorus content, neutral detergent fiber and, especially, crude protein and enzymatic digestibility. Concurrent floristic change mediated change in crude protein (80%), enzymatic digestibility (55%) and forage content in calcium (31%). Our study shows that plant diversity and forage quality are intimately linked features of Atlantic mountain grasslands and highlights the importance of preserving leguminous and dicotyledonous species to maintain the nutritive value of these grasslands.
Genotypic Variation in Nutrient Uptake Requirements of Rice Using the QUEFTS Model
Authors: Sun Tao , Yang Xin , Tang Sheng , Han Kefeng , He Ping , Wu Lianghuan
Published: December 2020

Nutrient requirements for single-season rice using the quantitative evaluation of the fertility of tropical soils (QUEFTS) model in China have been estimated in a previous study, which involved all the rice varieties; however, it is unclear whether a similar result can be obtained for different rice varieties. In this study, data were collected from field experiments conducted from 2016 to 2019 in Zhejiang Province, China. The dataset was separated into two parts: japonica/indica hybrid rice and japonica rice. To produce 1000 kg of grain, 13.5 kg N, 3.6 kg P, and 20.4 kg K were required in the above-ground plant dry matter for japonica/indica hybrid rice, and the corresponding internal efficiencies (IEs) were 74.0 kg grain per kg N, 279.1 kg grain per kg P, and 49.1 kg grain per kg K. For japonica rice, 17.6 kg N, 4.1 kg P, and 23.0 kg K were required to produce 1000 kg of grain, and the corresponding IEs were 56.8 kg grain per kg N, 244.6 kg grain per kg P, and 43.5 kg grain per kg K. Field validation experiments indicated that the QUEFTS model could be used to estimate nutrient uptake of different rice varieties. We suggest that variety should be taken into consideration when estimating nutrient uptake for rice using the QUEFTS model, which would improve this model.
Assessing Environmental Control Strategies in Cage-Free Egg Production Systems: Effect on Spatial Occupancy and Natural Behaviors
Authors: Gonzalez-Mora Andrés F. , Larios Araceli D. , Rousseau Alain N. , Godbout Stéphane , Morin Cédric , Palacios Joahnn H. , Grenier Michèle , Fournel Sébastien
Published: December 2020

Animal welfare concerns have been a challenging issue for producers and international marketing. In laying hen production, cage-free systems (CFS) have been identified as an alternative to ensure the laying hens’ well-being. Nevertheless, in CFS, important environmental issues have been reported, decreasing indoor air quality. Environmental control strategies (ECS) have been designed to enhance indoor air quality in CFSs. However, little information exists about the effect of these ECSs on natural animal behaviors. Four strategies and one control were tested in an experimental CFS, previously designed to track behavioral variables using video recordings over seven time-lapses of 1 hour per day. Spatial occupancy (SO) and laying hen behaviors (LHB) were registered. One statistical analysis was applied to evaluate the effect of ECS on SO and LHB using a multinomial response model. Results show lower chances to use litter area within the reduction of litter allowance treatment (T17) (p < 0.05). Neither the four ECSs nor the control implemented in this experiment affected the natural behaviors of the hens. However, stress patterns and high activity were reported in the T17 treatment. This study shows that it is possible to use these ECSs without disrupting laying hens’ natural behaviors.
Beta-Lactamase-Producing Escherichia coli Isolates Recovered from Pig Handlers in Retail Shops and Abattoirs in Selected Localities in Southern Nigeria: Implications for Public Health
Authors: Egbule Olivia Sochi , Iweriebor Benson C. , Odum Edward Ikenna
Published: December 2020

Antibiotic resistance evolution among pathogenic microorganisms has become a huge burden globally as it has increased the burden of diseases amongst humans and animals. The prevalence of extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-Ec) and metallo beta-lactamase-producing Escherichia coli (MBL-Ec) isolated from pig abattoir and handlers in retail shops was studied. In addition, the relationship between the isolates’ prevalence and the background characteristics of the butchers/retailers was also investigated. Samples from 32 hand swabs of pork sellers at retail shops and 8 butchers at abattoirs, as well as 272 swabs taken from knives, tables, floors, water troughs, and carcasses from both retail shops and abattoirs, were collected. Escherichia coli (E. coli) was isolated from hand swabs, fomites, and carcasses and were identified by standard microbiological procedures. The isolates susceptibility to nitrofurantoin (300 µg), ciprofloxacin (5 µg), ceftazidime (30 µg), cefuroxime (30 µg), gentamicin (10 µg), cefixime (5 µg), ofloxacin (5 µg), amoxicillin/clavulanic acid (30 µg), imipenem (10 µg), and meropenem (10 µg) and their ability to produce ESBL and MBL was determined by phenotypic methods. Demographic information of the handlers was retrieved by means of a structured questionnaire and, in some cases, via face to face interviews. Out of 104 E. coli isolates from both sources, 52 (50.0%) and 8 (7.7%) were ESBL and MBL producers, respectively. ESBL was more prevalent on the hands of the retailers (40.6%) and butchers (75.0%). The isolates were 100% resistant to ceftazidime, cefotaxime, and amoxicillin–clavulanic acid and 4.8% resistant to nitrofurantoin. Diverse resistance patterns were observed among ESBL-Ec and MBL-Ec. It was found that 90% of ESBL-Ec and 100% of MBL-Ec were multidrug-resistant. A possible epidemiological link between the two sources was observed. The prevalence of E. coli ESBL- and MBL-producing isolates was associated with the duty performed by handlers (p = 0.012) and gender (p = 0.012). Our results provide evidence that the handlers’ hands and abattoir environment had a great role to play in the high prevalence and resistance profiles of the microorganisms.
Classification of Chaotic Signals of the Recurrence Matrix Using a Convolutional Neural Network and Verification through the Lyapunov Exponent
Authors: Nam Jaehyeon , Kang Jaeyoung
Published: December 2020

This study classified chaotic time series data, including smooth and nonsmooth problems in a dynamic system, using a convolutional neural network (CNN) and verified it through the Lyapunov exponent. For this, the classical nonlinear differential equation by the Lorenz model was used to analyze a smooth dynamic system. The vibro-impact model was used for the nonsmooth dynamic system. Recurrence is a fundamental property of a dynamic system, and a recurrence plot is a representative method to visualize the recurrence characteristics of reconstructed phase space. Therefore, this study calculated the Lyapunov exponent by parametric analysis and visualized the corresponding recurrence matrix to show the dynamic characteristics as an image. In addition, the dynamic characteristics were classified using the proposed CNN model. The proposed CNN model determined chaos with an accuracy of more than 92%.
Fibrinogen and Fibrin Differentially Regulate the Local Hydrodynamic Environment in Neutrophil–Tumor Cell–Endothelial Cell Adhesion System
Authors: Fu Yi , Li Ang , Wu Jie , Kunz Robert F. , Sun Ren , Ding Zurong , Wu Jianhua , Dong Cheng
Published: December 2020

As cancer is one of the major fatal diseases for human beings worldwide, the metastasis of tumor cells (TCs) from a blood vessel to an adjacent organ has become a focus of research. A tumor metastasis theory named the “two-step theory” pointed out that polymorphnuclear neutrophils (PMNs) could facilitate TC adhesion on an endothelial monolayer under flow, which was regulated by shear flow and promoted by fibrinogen and fibrin. In order to further understand the role of hydrodynamics played in the “two-step theory”, we improved our side-view micro-particle imaging velocimetry (PIV) system and successfully measured the flow velocity profiles around adherent PMNs and TCs on an endothelial monolayer in the presence of soluble fibrinogen or fibrin under shear flow. Combined with a computational fluid dynamics simulation, we found that: (1) soluble fibrinogen and fibrin influenced the variations of relative shear rates above an adhered PMN and an adherent TC at different PMN-to-TC position states; (2) compared with soluble fibrinogen, soluble fibrin made the curves of relative shear rates above an adherent cell flatter. Soluble fibrin might increase the collision frequency and affect the contact time and contact area between PMNs, TCs, and endothelium cells, resulting in the enhancement of TC adhesion and retention on an endothelial monolayer.
Distracted and Drowsy Driving Modeling Using Deep Physiological Representations and Multitask Learning
Authors: Papakostas Michalis , Das Kapotaksha , Abouelenien Mohamed , Mihalcea Rada , Burzo Mihai
Published: December 2020

In this paper, we investigated various physiological indicators on their ability to identify distracted and drowsy driving. In particular, four physiological signals are being tested: blood volume pulse (BVP), respiration, skin conductance and skin temperature. Data were collected from 45 participants, under a simulated driving scenario, through different times of the day and during their engagement on a variety of physical and cognitive distractors. We explore several statistical features extracted from those signals and their efficiency to discriminate between the presence or not of each of the two conditions. To that end, we evaluate three traditional classifiers (Random Forests, KNN and SVM), which have been extensively applied by the related literature and we compare their performance against a deep CNN-LSTM network that learns spatio-temporal physiological representations. In addition, we explore the potential of learning multiple conditions in parallel using a single machine learning model, and we discuss how such a problem could be formulated and what are the benefits and disadvantages of the different approaches. Overall, our findings indicate that information related to the BVP data, especially features that describe patterns with respect to the inter-beat-intervals (IBI), are highly associates with both targeted conditions. In addition, features related to the respiratory behavior of the driver can be indicative of drowsiness, while being less associated with distractions. Moreover, spatio-temporal deep methods seem to have a clear advantage against traditional classifiers on detecting both driver conditions. Our experiments show, that even though learning both conditions jointly can not compete directly to individual, task-specific CNN-LSTM models, deep multitask learning approaches have a great potential towards that end as they offer the second best performance on both tasks against all other evaluated alternatives in terms of sensitivity, specificity and the area under the receiver operating characteristic curve (AUC).
Comparative Polyphenol Composition, Antioxidant and Anticorrosion Properties in Various Parts of Panax ginseng Extracted in Different Solvents
Authors: Malathy Ramalingam , Prabakaran Mayakrishnan , Kalaiselvi Kathirvel , Chung Ill-Min , Kim Seung-Hyun
Published: December 2020

Panax ginseng C.A. (P. ginseng) Meyer has been in use since ancient times for its therapeutic activities. Although several studies have investigated the roles of phytoconstituents in human and animal health, no comparative studies have been conducted to test the efficacy of P.ginseng leaf, fruit and root. Therefore, this study aimed to identify the antioxidant and anticorrosion activities of ginseng prepared using five different solvents. The methanolic fruit extract showed comparatively good activity in all assays. The total phenolic content (TPC) was higher in fruit (95.21 mg/g), followed by leaf (39.21 mg/g) extracted in methanol solvent compared other solvents. The total flavonoid content (TFC) of fruit methanolic extract was 50.21 mg/g, which was followed by fruit extracted in ethanol (41.33 mg/g). The same phenomenon was observed in all antioxidant studies. Through Ultrahigh Performance Liquid Chromatography (UHPLC), the presence of 23 phenolic components categorized as hydroxycinnamic acids, hydroxybenzoic acids and a few other groups that play a vital role in antioxidation was identified. Phenols such as chlorogenic acid (1002.2 μg/g), gentisic acid (854.21 μg/g) and rutin (165.32 μg/g) were found in higher amounts in fruit whereas leaf showed significant amounts of m-coumaric acid (185.32 μg/g) and p-coumaric acid (125.24 μg/g). The anti-corrosive property of the fruit extract of the ginseng with methanol as a solvent was analyzed for a copper specimen exposed to 1 M HCl medium and found to have 96% corrosion inhibition efficiency at a 1000-ppm concentration. The smooth surface of the specimen exposed to corrosive media shown in a field emission scanning electron microscope (FESEM) image confirms that the specimen was protected from corrosion, and energy-dispersive X-ray spectroscopy (EDX) spectra show that the loss of Cu is reduced in inhibited metal surface. Atomic force microscopy (AFM) images and surface roughness factor also validate the corrosion inhibition characteristic of ginseng plant extract.
The Effect of BDS-3 Time Group Delay and Differential Code Bias Corrections on Positioning
Authors: Dai Peipei , Xing Jianping , Ge Yulong , Yang Xuhai , Qin Weijin , Dong Yanchen , Zhang Zhe
Published: December 2020

The timing group delay parameter (TGD) or differential code bias parameter (DCB) is an important factor that affects the performance of GNSS basic services; therefore, TGD and DCB must be taken seriously. Moreover, the TGD parameter is modulated in the navigation message, taking into account the impact of TGD on the performance of the basic service. International GNSS Monitoring and Assessment System (iGMAS) provides the broadcast ephemeris with TGD parameter and the Chinese Academy of Science (CAS) provides DCB products. In this paper, the current available BDS-3 TGD and DCB parameters are firstly described in detail, and the relationship of TGD and DCB for BDS-3 is figured out. Then, correction models of BDS-3 TGD and DCB in standard point positioning (SPP) or precise point positioning (PPP) are given, which can be applied in various situations. For the effects of TGD and DCB in the SPP and PPP solution processes, all the signals from BDS-3 were researched, and the validity of TGD and DCB has been further verified. The experimental results show that the accuracy of B1I, B1C and B2a single-frequency SPP with TGD or DCB correction was improved by approximately 12–60%. TGD will not be considered for B3I single-frequency, because the broadcast satellite clock offset is based on the B3I as the reference signal. The positioning accuracy of B1I/B3I and B1C/B2a dual-frequency SPP showed that the improvement range for horizontal components is 60.2% to 74.4%, and the vertical components improved by about 50% after the modification of TGD and DCB. In addition, most of the uncorrected code biases are mostly absorbed into the receiver clock bias and other parameters for PPP, resulting in longer convergence time. The convergence time can be max increased by up to 50% when the DCB parameters are corrected. Consequently, the positioning accuracy can reach the centimeter level after convergence, but it is critical for PPP convergence time and receiver clock bias that the TGD and DCB correction be considered seriously.
Improving Soil Nitrogen Availability and Rice Growth Performance on a Tropical Acid Soil via Mixture of Rice Husk and Rice Straw Biochars
Authors: Selvarajh Gunavathy , Ch’ng Huck Ywih , Md Zain Norhafizah , Sannasi Palsan , Mohammad Azmin Siti Nuurul Huda
Published: December 2020

Nitrogen deficiency frequently occurs at agricultural soil because of NH3 volatilization to the environment which results in low urea-N use efficiency by rice plants. A pot experiment was conducted to assess the synergistic effects of a mixture of rice straw and rice husk biochars (RSRH) on (1) total N, soil exchangeable NH4+, and available NO3−, and (2) uptake of N, P, and K in rice plant. RSRH biochar at 5 and 10 t ha−1 had significantly minimized ammonia volatilization by 33.5% and 40.7%. Further, RSRH biochars also had significantly increased available NH4+, NO3−, available P, and available K in the soil over T1. In line to increase in soil nutrient availability, the rice plant height, tiller number, greenness, and panicle number were increased. This resulted in an increase of nutrient uptake, use efficiency, and dry matter production of the rice plant. RSRH biochar altered the soil environment by minimizing NH3 loss and increasing soil nutrients for efficient plant uptake.
Effect of Vinylene Carbonate Electrolyte Additive on the Surface Chemistry and Pseudocapacitive Sodium-Ion Storage of TiO2 Nanosheet Anodes
Authors: Maça Rudi Ruben , Etacheri Vinodkumar
Published: December 2020

Although titanium dioxide has gained much attention as a sodium-ion battery anode material, obtaining high specific capacity and cycling stability remains a challenge. Herein, we report significantly improved surface chemistry and pseudocapacitive Na-ion storage performance of TiO2 nanosheet anode in vinylene carbonate (VC)-containing electrolyte solution. In addition to the excellent pseudocapacitance (~87%), the TiO2 anodes also exhibited increased high-specific capacity (219 mAh/g), rate performance (40 mAh/g @ 1 A/g), coulombic efficiency (~100%), and cycling stability (~90% after 750 cycles). Spectroscopic and microscopic studies confirmed polycarbonate based solid electrolyte interface (SEI) formation in VC-containing electrolyte solution. The superior electrochemical performance of the TiO2 nanosheet anode in VC-containing electrolyte solution is credited to the improved pseudocapacitive Na-ion diffusion through the polycarbonate based SEI (coefficients of 1.65 × 10−14 for PC-VC vs. 6.42 × 10−16 for PC). This study emphasizes the crucial role of the electrolyte solution and electrode–electrolyte interfaces in the improved pseudocapacitive Na-ion storage performance of TiO2 anodes.
Effect of Weed Management on the Parasitoid Community in Mediterranean Vineyards
Authors: Möller Gabriella , Keasar Tamar , Shapira Idan , Möller Daniella , Ferrante Marco , Segoli Michal
Published: December 2020

Enriching agroecosystems with non-crop vegetation is a popular strategy for conservation biocontrol. In vineyards, the effects of specific seeded or planted cover crops on natural enemies are well-studied, whereas conserving spontaneously developing weeds received less attention. We compared parasitoid communities between matched pairs of vineyard plots in northern Israel, differing in weed management practices: “herbicide”, repeated herbicide applications vs. “ground cover”, maintaining resident weeds and trimming them when needed. Using suction sampling, we assessed the parasitoids’ abundance, richness, and composition during three grape-growing seasons. Ground cover plots had greater parasitoid abundances and cumulative species richness than herbicide-treated plots, possibly because of their higher vegetation cover and richness. Dominant parasitoid species varied in their magnitude and direction of response to weed management. Their responses seem to combine tracking of host distributions with attraction to additional vegetation-provided resources. Parasitoid community composition was mildly yet significantly influenced by weed management, while season, year, and habitat (weeds vs. vine) had stronger effects. Vineyard weeds thus support local biocontrol agents and provide additional previously demonstrated benefits (e.g., soil conservation, lower agrochemical exposure) but might also attract some crop pests. When the benefits outweigh this risk, weed conservation seems a promising step towards more sustainable agricultural management.
Using Artificial Neural Network to Discriminate Parkinson’s Disease from Other Parkinsonisms by Focusing on Putamen of Dopamine Transporter SPECT Images
Authors: Chien Chung-Yao , Hsu Szu-Wei , Lee Tsung-Lin , Sung Pi-Shan , Lin Chou-Ching
Published: December 2020

Background: The challenge of differentiating, at an early stage, Parkinson’s disease from parkinsonism caused by other disorders remains unsolved. We proposed using an artificial neural network (ANN) to process images of dopamine transporter single-photon emission computed tomography (DAT-SPECT). Methods: Abnormal DAT-SPECT images of subjects with Parkinson’s disease and parkinsonism caused by other disorders were divided into training and test sets. Striatal regions of the images were segmented by using an active contour model and were used as the data to perform transfer learning on a pre-trained ANN to discriminate Parkinson’s disease from parkinsonism caused by other disorders. A support vector machine trained using parameters of semi-quantitative measurements including specific binding ratio and asymmetry index was used for comparison. Results: The predictive accuracy of the ANN classifier (86%) was higher than that of the support vector machine classifier (68%). The sensitivity and specificity of the ANN classifier in predicting Parkinson’s disease were 81.8% and 88.6%, respectively. Conclusions: The ANN classifier outperformed classical biomarkers in differentiating Parkinson’s disease from parkinsonism caused by other disorders. This classifier can be readily included into standalone computer software for clinical application.
Label-Free Amperometric Immunosensor Based on Versatile Carbon Nanofibers Network Coupled with Au Nanoparticles for Aflatoxin B1 Detection
Authors: Huang Yunhong , Zhu Fei , Guan Jinhua , Wei Wei , Zou Long
Published: December 2020

Facile detection methods for mycotoxins with high sensitivity are of great significance to prevent potential harm to humans. Herein, a label-free amperometric immunosensor based on a 3-D interconnected carbon nanofibers (CNFs) network coupled with well-dispersed Au nanoparticles (AuNPs) is proposed for the quantitative determination of aflatoxin B1 (AFB1) in wheat samples. In comparison to common carbon nanotubes (CNTs), the CNFs network derived from bacterial cellulose biomass possesses a unique hierarchically porous structure for fast electrolyte diffusion and a larger electrochemical active area, which increases the peak current of differential pulse voltammetry curves for an immunosensor. Combined with AuNPs that are incorporated into CNFs by using linear polyethyleneimine (PEI) as a soft template, the developed Au@PEI@CNFs-based immunosensor showed a good linear response to AFB1 concentrations in a wide range from 0.05 to 25 ng mL−1. The limit of detection was 0.027 ng mL−1 (S/N = 3), more than three-fold lower than that of an Au@PEI@CNTs-based sensor. The reproducibility, storage stability and selectivity of the immunosensor were proved to be satisfactory. The developed immunosensor with appropriate sensitivity and reliable accuracy can be used for the analysis of wheat samples.
Development of Fluorescence In Situ Hybridization as a Rapid, Accurate Method for Detecting Coliforms in Water Samples
Authors: Kuo Jong-Tar , Chang Li-Li , Yen Chia-Yuan , Tsai Teh-Hua , Chang Yu-Chi , Huang Yu-Tang , Chung Ying-Chien
Published: December 2020

Coliform bacteria are indicators of water quality; however, most detection methods for coliform bacteria are time-consuming and nonspecific. Here, we developed a fluorescence in situ hybridization (FISH) approach to detect four types of coliform bacteria, including Escherichia coli, Klebsiella pneumoniae, Enterobacter aerogenes, and Citrobacter freundii, simultaneously in water samples using specific probes for 16S rRNA. This FISH method was applied to detect coliform bacteria in simulated water and domestic wastewater samples and compared with traditional detection methods (e.g., plate counting, multiple-tube fermentation (MTF) technique, and membrane filter (MF) technique). Optimal FISH conditions for detecting the four types of coliforms were found to be fixation in 3% paraformaldehyde at 4 °C for 2 h and hybridization at 50 °C for 1.5 h. By comparing FISH with plate counting, MTF, MF, and a commercial detection kit, we found that FISH had the shortest detection time and highest accuracy for the identification of coliform bacteria in simulated water and domestic wastewater samples. Moreover, the developed method could simultaneously detect individual species and concentrations of coliform bacteria. Overall, our findings indicated that FISH could be used as a rapid, accurate biosensor system for simultaneously detecting four types of coliform bacteria to ensure water safety.
Motor Cortical Activity during Observing a Video of Real Hand Movements versus Computer Graphic Hand Movements: An MEG Study
Authors: Hsieh Yu-Wei , Lee Meng-Ta , Lin Yu-Hsuan , Chuang Li-Ling , Chen Chih-Chi , Cheng Chia-Hsiung
Published: December 2020

Both action observation (AO) and virtual reality (VR) provide visual stimuli to trigger brain activations during the observation of actions. However, the mechanism of observing video movements performed by a person’s real hand versus that performed by a computer graphic hand remains uncertain. We aimed to investigate the differences in observing the video of real versus computer graphic hand movements on primary motor cortex (M1) activation by magnetoencephalography. Twenty healthy adults completed 3 experimental conditions: the resting state, the video of real hand movements (VRH), and the video of computer graphic hand movements (CGH) conditions with the intermittent electrical stimuli simultaneously applied to the median nerve by an electrical stimulator. The beta oscillatory activity (~20 Hz) in the M1 was collected, lower values indicating greater activations. To compare the beta oscillatory activities among the 3 conditions, the Friedman test with Bonferroni correction (p-value < 0.017 indicating statistical significance) were used. The beta oscillatory activities of the VRH and CGH conditions were significantly lower than that of the resting state condition. No significant difference in the beta oscillatory activity was found between the VRH and CGH conditions. Observing hand movements in a video performed by a real hand and those by a computer graphic hand evoked comparable M1 activations in healthy adults. This study provides some neuroimaging support for the use of AO and VR in rehabilitation, but no differential activations were found.
Enhanced Neural Empathic Responses in Patients with Spino-Bulbar Muscular Atrophy: An Electrophysiological Study
Authors: Palmieri Arianna , Meconi Federica , Vallesi Antonino , Capizzi Mariagrazia , Pick Emanuele , Marcato Sonia , Kleinbub Johann R. , Sorarù Gianni , Sessa Paola
Published: December 2020

Background: Spino-bulbar muscular atrophy is a rare genetic X-linked disease caused by testosterone insensitivity. An inverse correlation has been described between testosterone levels and empathic responses. The present study explored the profile of neural empathic responding in spino-bulbar muscular atrophy patients. Methods: Eighteen patients with spino-bulbar muscular atrophy and eighteen healthy male controls were enrolled in the study. Their event-related potentials were recorded during an “Empathy Task” designed to distinguish neural responses linked with experience-sharing (early response) and mentalizing (late response) components of empathy. The task involved the presentation of contextual information (painful vs. neutral sentences) and facial expressions (painful vs. neutral). An explicit dispositional empathy-related questionnaire was also administered to all participants, who were screened via neuropsychological battery tests that did not reveal potential cognitive deficits. Due to electrophysiological artefacts, data from 12 patients and 17 controls were finally included in the analyses. Results: Although patients and controls did not differ in terms of dispositional, explicit empathic self-ratings, notably conservative event-related potentials analyses (i.e., spatio-temporal permutation cluster analyses) showed a significantly greater experience-sharing neural response in patients compared to healthy controls in the Empathy-task when both contextual information and facial expressions were painful. Conclusion: The present study contributes to the characterization of the psychological profile of patients with spino-bulbar muscular atrophy, highlighting the peculiarities in enhanced neural responses underlying empathic reactions.
Life Cycle GHG Emissions of Residential Buildings in Humid Subtropical and Tropical Climates: Systematic Review and Analysis
Authors: Satola Daniel , Röck Martin , Houlihan-Wiberg Aoife , Gustavsen Arild
Published: December 2020

Improving the environmental life cycle performance of buildings by focusing on the reduction of greenhouse gas (GHG) emissions along the building life cycle is considered a crucial step in achieving global climate targets. This paper provides a systematic review and analysis of 75 residential case studies in humid subtropical and tropical climates. The study investigates GHG emissions across the building life cycle, i.e., it analyses both embodied and operational GHG emissions. Furthermore, the influence of various parameters, such as building location, typology, construction materials and energy performance, as well as methodological aspects are investigated. Through comparative analysis, the study identifies promising design strategies for reducing life cycle-related GHG emissions of buildings operating in subtropical and tropical climate zones. The results show that life cycle GHG emissions in the analysed studies are mostly dominated by operational emissions and are the highest for energy-intensive multi-family buildings. Buildings following low or net-zero energy performance targets show potential reductions of 50–80% for total life cycle GHG emissions, compared to buildings with conventional energy performance. Implementation of on-site photovoltaic (PV) systems provides the highest reduction potential for both operational and total life cycle GHG emissions, with potential reductions of 92% to 100% and 48% to 66%, respectively. Strategies related to increased use of timber and other bio-based materials present the highest potential for reduction of embodied GHG emissions, with reductions of 9% to 73%.
Magnetite, Hematite and Zero-Valent Iron as Co-Catalysts in Advanced Oxidation Processes Application for Cosmetic Wastewater Treatment
Authors: Bogacki Jan , Marcinowski Piotr , Bury Dominika , Krupa Monika , Ścieżyńska Dominika , Prabhu Prasanth
Published: December 2020

Background: There is a need for more effective methods of industrial wastewater treatment. Methods: Cosmetic wastewater was collected and subjected to H2O2/Fe3O4/Fe2O3/Fe0 and UV/H2O2/Fe3O4/Fe2O3/Fe0 process treatment. Results: Total organic carbon (TOC) was decreased from an initial 306.3 to 134.1 mg/L, 56.2% TOC removal, after 120 min of treatment for 1:1 H2O2/COD mass ratio and 500/500/1000 mg/L Fe3O4/Fe2O3/Fe0 catalyst doses. The application chromatographic analysis allowed for the detection and identification of pollutants present in the wastewater. Identified pollutants were removed during the treatment processes. Processes carried out at a pH greater than 3.0 were ineffective. The UV process was more effective than the lightless process. Conclusions: The applied processes are effective methods for wastewater treatment. Chromatographic results confirmed the effectiveness of the treatment method. The kinetics of the process were described by the modified second-order model. On the basis of ANOVA results, the hypothesis regarding the accuracy and reproducibility of the research was confirmed.
Photocatalytic Properties of Core-Shell Structured Wool-TiO2 Hybrid Composite Powders
Authors: Gu Haoshuai , Zhang Hui , Zhang Xinyue , Guo Yani , Yang Limeng , Wu Hailiang , Mao Ningtao
Published: December 2020

In this study, a special core–shell structured wool-TiO2 (WT) hybrid composite powder also having TiO2 nanoparticles incorporated inside cortical cells was reported. The wool pallets were pulverized from wool fibers using vibration-assisted ball milling technique and the WT powders having mesopores and macropores were produced in hydrothermal process. Experimental results indicated that the infiltrated TiO2 nanoparticles were amorphous structure, while the coated TiO2 nanoparticles were anatase phase structure. The crystallized TiO2 nanoparticles were grafted with wool pallets by the N−Ti4+/S−Ti4+/O−Ti4+ bonds. The BET surface area was measured as 153.5 m2/g and the particle sizes were in the 600–3600 nm and 4000–6500 nm ranges. The main reactive radical species of the WT powders were holes, and •O2−, 1O2, and •OH were also involved in the photodegradation of MB dye under visible light irradiation. The experimental parameters for photodegradation of MB dye solution were optimized as follows: 0.25 g/L of WT powders was added in 40 mL of 3 mg/L MB dye solution containing 50 mL/L H2O2, which resulted in the increases of COD value of degraded MB dye solution up to 916.9 mg/L at 120 min. The WT powders could be used for repeatedly photodegradation of both anionic and cationic dyes.
Monocyte Recruitment, Specification, and Function in Atherosclerosis
Authors: Kim Ki-Wook , Ivanov Stoyan , Williams Jesse W.
Published: December 2020

Atherosclerotic lesions progress through the continued recruitment of circulating blood monocytes that differentiate into macrophages within plaque. Lesion-associated macrophages are the primary immune cells present in plaque, where they take up cholesterol and store lipids in the form of small droplets resulting in a unique morphology termed foam cell. Recent scientific advances have used single-cell gene expression profiling, live-cell imaging, and fate mapping approaches to describe macrophage and monocyte contributions to pro- or anti-inflammatory mechanisms, in addition to functions of motility and proliferation within lesions. Yet, many questions regarding tissue-specific regulation of monocyte-to-macrophage differentiation and the contribution of recruited monocytes at stages of atherosclerotic disease progression remain unknown. In this review, we highlight recent advances regarding the role of monocyte and macrophage dynamics in atherosclerotic disease and identify gaps in knowledge that we hope will allow for advancing therapeutic treatment or prevention strategies for cardiovascular disease.
NeuroHeal Improves Muscle Regeneration after Injury
Authors: Marmolejo-Martínez-Artesero Sara , Romeo-Guitart David , Venegas Vanesa , Marotta Mario , Casas Caty
Published: December 2020

Musculoskeletal injuries represent a challenging medical problem. Although the skeletal muscle is able to regenerate and recover after injury, the process engaged with conservative therapy can be inefficient, leading to a high re-injury rate. In addition, the formation of scar tissue implies an alteration of mechanical properties in muscle. There is still a need for new treatments of the injured muscle. NeuroHeal may be one option. Published studies demonstrated that it reduces muscle atrophy due to denervation and disuse. The main objective of the present work was to assess the potential of NeuroHeal to improve muscle regeneration after traumatic injury. Secondary objectives included characterizing the effect of NeuroHeal treatment on satellite cell biology. We used a rat model of sport-induced injury in the gastrocnemius and analyzed the effects of NeuroHeal on functional recovery by means of electrophysiology and tetanic force analysis. These studies were accompanied by immunohistochemistry of the injured muscle to analyze fibrosis, satellite cell state, and fiber type. In addition, we used an in vitro model to determine the effect of NeuroHeal on myoblast biology and partially decipher its mechanism of action. The results showed that NeuroHeal treatment advanced muscle fiber recovery after injury in a preclinical model of muscle injury, and significantly reduced the formation of scar tissue. In vitro, we observed that NeuroHeal accelerated the formation of myotubes. The results pave the way for novel therapeutic avenues for muscle/tendinous disorders.
Galvanic Corrosion Performance of an Al–BN Abradable Seal Coating System in Chloride Solution
Authors: Lei Bing , Peng Mingxiao , Liu Ling , Hu Shengnan , Zhang Wei , Meng Guozhe
Published: December 2020

In this study, we investigated the galvanic corrosion performance of an Aluminum–Boron Nitride (Al–BN) abradable seal coating system (with a Ni5Al bond layer and a 0Cr17Ni4Cu4Nb substrate) in chloride solution by electrochemical methods. The results indicated a three-stage process occurred during the anodic dissolution of the coupled coating system, consisting of a spontaneous pitting stage I under charge transfer control with a decreasing rate, a corrosion developing stage II under mass transfer control with an increasing rate, and a final steady stage III. Precipitation of Al(OH)3 restricts the oxygen transport process to the cathode and induces localized acidification of the occluded pores of the Al–BN layer, which was the mechanism that could explain the changes of corrosion performance during the three immersion stages of Al–BN coating system. The study suggests that galvanic corrosion of the porous multi-layer Al–BN abradable coating system is mostly influenced by its corrosion product deposition.
RNA-Based Multiplexing Assay for Routine Testing of Fusion and Splicing Variants in Cytological Samples of NSCLC Patients
Authors: Aguado Cristina , Giménez-Capitán Ana , Román Ruth , Rodríguez Sonia , Jordana-Ariza Núria , Aguilar Andrés , Cabrera-Gálvez Carlos , Rivas-Corredor Carlos , Lianes Pilar , Viteri Santiago , Moya Irene , Molina-Vila Miguel A.
Published: December 2020

The detection of ALK receptor tyrosine kinase (ALK), ROS proto-oncogen1, receptor tyrosine kinase (ROS1), ret proto-oncogen (RET), and MET proto-oncogen exon 14 skipping (METΔex14) allows for the selection of specific kinase inhibitor treatment in patients with non-small cell lung cancer (NSCLC). Multiplex technologies are recommended in this setting. We used nCounter, a multiplexed technology based on RNA hybridization, to detect ALK, ROS1, RET, and METΔex14 in RNA purified from cytological specimens (n = 16) and biopsies (n = 132). Twelve of the 16 cytological samples (75.0%) were evaluable by nCounter compared to 120 out of 132 (90.9%) biopsies. The geometrical mean (geomean) of the housekeeping genes of the nCounter panel, but not the total amount of RNA purified, was significantly higher in biopsies vs. cytological samples. Among cytological samples, we detected ALK (n = 3), METΔex14 (n = 1) and very high MET expression (n = 1) positive cases. The patient with METΔex14 had a partial response to tepotinib, one of the patients with ALK fusions was treated with crizotinib with a complete response. Cell blocks and cytological extensions can be successfully used for the detection of fusions and splicing variants using RNA-based methods such as nCounter.
The Role of Artificial Intelligence in Endoscopic Ultrasound for Pancreatic Disorders
Authors: Tonozuka Ryosuke , Mukai Shuntaro , Itoi Takao
Published: December 2020

The use of artificial intelligence (AI) in various medical imaging applications has expanded remarkably, and several reports have focused on endoscopic ultrasound (EUS) images of the pancreas. This review briefly summarizes each report in order to help endoscopists better understand and utilize the potential of this rapidly developing AI, after a description of the fundamentals of the AI involved, as is necessary for understanding each study. At first, conventional computer-aided diagnosis (CAD) was used, which extracts and selects features from imaging data using various methods and introduces them into machine learning algorithms as inputs. Deep learning-based CAD utilizing convolutional neural networks has been used; in these approaches, the images themselves are used as inputs, and more information can be analyzed in less time and with higher accuracy. In the field of EUS imaging, although AI is still in its infancy, further research and development of AI applications is expected to contribute to the role of optical biopsy as an alternative to EUS-guided tissue sampling while also improving diagnostic accuracy through double reading with humans and contributing to EUS education.
Automatic Fetal Middle Sagittal Plane Detection in Ultrasound Using Generative Adversarial Network
Authors: Tsai Pei-Yin , Hung Ching-Hui , Chen Chi-Yeh , Sun Yung-Nien
Published: December 2020

Background and Objective: In the first trimester of pregnancy, fetal growth, and abnormalities can be assessed using the exact middle sagittal plane (MSP) of the fetus. However, the ultrasound (US) image quality and operator experience affect the accuracy. We present an automatic system that enables precise fetal MSP detection from three-dimensional (3D) US and provides an evaluation of its performance using a generative adversarial network (GAN) framework. Method: The neural network is designed as a filter and generates masks to obtain the MSP, learning the features and MSP location in 3D space. Using the proposed image analysis system, a seed point was obtained from 218 first-trimester fetal 3D US volumes using deep learning and the MSP was automatically extracted. Results: The experimental results reveal the feasibility and excellent performance of the proposed approach between the automatically and manually detected MSPs. There was no significant difference between the semi-automatic and automatic systems. Further, the inference time in the automatic system was up to two times faster than the semi-automatic approach. Conclusion: The proposed system offers precise fetal MSP measurements. Therefore, this automatic fetal MSP detection and measurement approach is anticipated to be useful clinically. The proposed system can also be applied to other relevant clinical fields in the future.
The End of a Classical Ontology for Quantum Mechanics?
Authors: Evans Peter W.
Published: December 2020

In this paper, I argue that the Shrapnel–Costa no-go theorem undermines the last remaining viability of the view that the fundamental ontology of quantum mechanics is essentially classical: that is, the view that physical reality is underpinned by objectively real, counterfactually definite, uniquely spatiotemporally defined, local, dynamical entities with determinate valued properties, and where typically ‘quantum’ behaviour emerges as a function of our own in-principle ignorance of such entities. Call this view Einstein–Bell realism. One can show that the causally symmetric local hidden variable approach to interpreting quantum theory is the most natural interpretation that follows from Einstein–Bell realism, where causal symmetry plays a significant role in circumventing the nonclassical consequences of the traditional no-go theorems. However, Shrapnel and Costa argue that exotic causal structures, such as causal symmetry, are incapable of explaining quantum behaviour as arising as a result of noncontextual ontological properties of the world. This is particularly worrying for Einstein–Bell realism and classical ontology. In the first instance, the obvious consequence of the theorem is a straightforward rejection of Einstein–Bell realism. However, more than this, I argue that, even where there looks to be a possibility of accounting for contextual ontic variables within a causally symmetric framework, the cost of such an account undermines a key advantage of causal symmetry: that accepting causal symmetry is more economical than rejecting a classical ontology. Either way, it looks like we should give up on classical ontology.
The Relationship between Spatial Ability and the Conservation of Matter in Middle School
Authors: Cole Merryn , Wilhelm Jennifer , Vaught Briana Marie-McKnight , Fish Corinne , Fish Hailey
Published: December 2020

Research has shown that spatial ability plays a key role in understanding STEM (Science, Technology, Engineering, and Mathematics) content, including chemistry. Conservation of Matter (CoM) is an essential but challenging topic for chemistry students of all ages to grasp; it is often taught in a way where students memorize it but do not learn what it means conceptually. This research explored the relationship between understanding spatial ability and conceptual understanding of CoM in middle school students. CoM was examined in two ways using the Conservation of Matter Assessment (CoMA): through questions on conservation of atoms and the conservation of mass. Spatial ability was measured using the Purdue Spatial Visual Test: Rotations (PSVT). Significant, moderate correlations were found between spatial ability and understanding of CoM prior to and after a chemistry unit including instruction on CoM; the correlation was stronger after instruction. Scores on the PSVT and CoMA significantly increased pre to post instruction. The data show spatial ability may impact students’ understanding of CoM, which contributes to the literature on factors that impact students’ understanding of chemistry. Additionally, it provides evidence that teachers should consider including spatially rich experiences in their chemistry classroom, such as making explicit connections between the areas of Johnstone’s Triad.