bluuebunny/crossref_metadata_2025 huggingface dataset:
CALCULATION OF THE GEOMECHANICAL STATE OF MINE WORKING SUPPORT AND SURROUNDING ROCK MASS IN CONDITIONS OF MINING ORE DEPOSITS IN EAST KAZAKHSTAN
Authors: Krasnovsky Andrey A. , Seryakov Viktor M. , Shaposhnik Yuri N. , Shokarev Denisi A.
Published: November 2020

The statement of the problem of determining the stress-strain state of support and rock mass around the mine working in unstable rocks, in case of voids filling with phenol resins is proposed. The initial parameters used in the calculations correspond to the conditions of mining ore deposits in East Kazakhstan. The distribution character of stress fields in the support and their change depending on geometric sizes of the area filled with phenol resins is determined. It is shown that using phenol resins causes formation of a uniform pressure of surrounding rocks on the arch part of the support and facilitates an increase in its stability.
Incidence and outcome of early post stroke seizures in a tertiary care hospital in New Delhi….. a prospective observational study
Authors: Dar Maqsood Ahmad , Saika Vasundhara Aggarwal , Mukherjee Joy Dev , Kumar Mukesh , Goel Khushbu
Published: November 2020

Background: About 11% of all epilepsies and 30% of newly diagnosed seizures in those older than 60 years have been reported to follow cerebrovascular accidents. Acute symptomatic (early) seizures occur in 3-8% of patients, more commonly in those with severe cortical strokes and intra-parenchymal hemorrhages. This study was undertaken to determine the incidence, risk factors and clinical outcome for early seizures after acute stroke.Aims and objectives: To study the incidence, risk factors and clinical outcomes of early seizures in post stroke patients in a tertiary care hospital.Study design: This prospective observational analytical study was conducted from -01-06-2017 to 31-01-2019 in Max Superspeciality Hospital Saket New Delhi. All consecutive patients of acute stroke fulfilling the inclusion and exclusion criteria were included in the study. Inclusion criteria and exclusion criteria: All patients with acute ischemic or hemorrhagic stroke with age above 18 years, either male or female were included in the study. Patients with a history of seizure or epilepsy before admission, patients with SAH, venous infarct and causes other than vascular origin were excluded from the study. Results and observation: Out of two hundred and fifty (n=250) patients of acute stroke included in the study early seizures were diagnosed in 29 patients (11.6%).Conclusions: We concluded that the incidence of post stroke early seizures was 11.6% in our study. We found that Patients with post stroke early seizures had higher NIHSS score, low GCS score and higher modified Rankin score at the time of admission. We recommend that stroke scores like NIHSS, ICH, GCS and mRS should be applied to all the patients of acute stroke to stratify the patients with regard to their risk of developing early seizures and prognosticating the clinical outcome.
SHORT RP TACHYCARDIA, SUCCESFULLY MANAGED WITH RADIO FREQUENCY ABLATION.
Authors: Lone Ajaz Ahmad , Tramboo Nisar Ahmad , Bilal Syed
Published: November 2020

A 35-year female patient presented with recurrent palpitations. Her baseline ECG was normal but during the episode of palpitations, it revealed short RP tachycardia. Intracardiac ECG revealed orthodromic reentrant tachycardia due to concealed left lateral pathway (Figure 1). She was successfully treated by radio-frequency ablation through a trans-septal approach. Figure 2 shows RV pacing getting conducted over the left lateral pathway to atria which disappears after ablation of the pathway.
Case of Van-Wyk Grumbach syndrome
Authors: Vasudevan Vishnu , Viswanath Arun , Misgar Riaz Ahmad
Published: November 2020

Background: Hypothyroidism in childhood typically leads to delayed puberty, rarely can it cause precocious puberty - this latter complex is eponymously known as Van-Wyk Grumbach syndrome.

Case description: We report a case of a seven and a half-year-old girl who was referred with vaginal bleeding after a diagnosis of primary hypothyroidism and starting treatment with levothyroxine. This case report illustrates the typical features of this rare syndrome for primarily educational purposes. Many case reports of Van Wyk Grumbach syndrome have been published in world literature over the past seven decades after the initial description. Though the features of this syndrome are fairly well described previously, the understanding of pathophysiological mechanisms is speculative and still evolving.

Clinical relevance: Further widespread awareness of the complex will encourage primary physicians and pediatricians to counsel the family of a child before starting treatment for hypothyroidism which will help avoid unnecessary worry and more importantly inadvertent procedures or intervention.
High Flow Nasal Cannula Oxygenation
Authors: Shah Tajamul Hussain , Mantoo Suhail , Jan Rafi Ahmad
Published: November 2020

High Flow Nasal Cannula Oxygenation

The current pandemic of COVID-19 caused by novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tested the healthcare infrastructure throughout the globe at all possible levels. Early reports suggest about 20% of patients infected with SARS-CoV-2 require hospitalization and 5-8% require admission to intensive care unit (ICU) due to severe disease.Supplementation of oxygen provided by various conventional oxygen therapy (COT) devices (like nasal prongs, face mask, venture mask or non-rebreather mask) may not be sufficient in cases of worsening respiratory failure. One form of escalating respiratory support in such patients is a high flow nasal oxygenation device. High flow nasal cannula oxygenation (HFNC) is a form of non invasive respiratory support. It acts as a bridge between low flow devices and non invasive ventilation and may reduce the need for intubation.
Selection of Lactic Acid Bacteria from Alfalfa Silage and Its Effects as Inoculant on Silage Fermentation
Authors: Silva Vanessa P. , Pereira Odilon G. , Leandro Eliana S. , Paula Rosinea A. , Agarussi Mariele C. N. , Ribeiro Karina G.
Published: November 2020

The first part of the study aimed to isolate, characterize, and identify wild lactic acid bacteria (LAB) strains from alfalfa silage produced in a tropical area. LAB strains were isolated from alfalfa silage ensiled for 1, 3, 7, 14, 28, and 56 days (d) and were identified by sequencing the 16S rRNA gene. The second part aimed to investigate the effects of wild LAB strains on the nutritive and fermentative characteristics of alfalfa silage. This trial was conducted according to a completely randomized design in a 4 × 2 factorial scheme [four inoculants (I) × two harvests (H)], (n = 4). The inoculants were: (1) no inoculant (CTRL), (2) Lactobacillus pentosus (AV 14.17); (3) L. pentosus + Lactobacillus brevis + Pediococcus acidilactici (Combo); and (4) commercial inoculant (CI). Alfalfa forage (7 kg) was ensiled in 10 L buckets and opened after 90 d. Seventy-seven strains were isolated. Pediococcus, Lactobacillus, and Weissella represented 52.0, 24.7, and 20.8% of the isolates, respectively. For the first harvest, Combo, CI, and all inoculated silages showed lower acid detergent fiber ADF, neutral detergent fiber (NDF), and ammonia nitrogen (NH3-N), respectively. Silage fermented with AV14.17 presented greater residual water-soluble carbohydrate (WSC) in the second harvest and showed the lowest pH in both harvests. AV14.17 strain has potential as an inoculant for alfalfa silage production.
Effects of Polyacrylamide-Based Super Absorbent Polymer and Corn Straw Biochar on the Arid and Semi-Arid Salinized Soil
Authors: Feng Weiying , Gao Jiayue , Cen Rui , Yang Fang , He Zhongqi , Wu Jin , Miao Qingfeng , Liao Haiqing
Published: November 2020

Green approaches are much more appreciable during the present scenario. Soil amendments are frequently applied for improving water use efficiency, reducing soil salinity in arid and semi-arid areas, controlling the secondary salinization of cultivated soils, and increasing the carbon sequestration capacity of soils. Thus, lab soil column simulation experiments and field experiments were carried out to evaluate these functions of two separate amendments, polyacrylamide-based super absorbent polymer (SAP) and corn straw biochar at different application rates. The simulation experiments showed that both SAP and biochar inhibited the accumulation of soil salinity, with a reduced rate of 9.7–26.3% and 13.5–37.2%, respectively, dependent on the amendment application rates. The field experiments found different salt inhibition effects of the two amendments with growth stages of maize. Soil salinization was inhibited in the pre-germination and early jointing stages by SAP, but throughout the whole growth period by biochar. Both soil amendments reduced soil electrical conductivity, and biochar increased the soil contents of Ca2+, Mg2+, and K+. Our observations demonstrated that application of biochar and SAP played important roles in increasing soil fertility and inhibiting soil salt accumulation. It provided an effective method to potentially mitigate the environmental crisis and promote sustainable development in agriculture.
Morphological and Physiological Responses of Cucumber Seedlings to Supplemental LED Light under Extremely Low Irradiance
Authors: Zhang Yiting , Dong Hao , Song Shiwei , Su Wei , Liu Houcheng
Published: November 2020

In order to inhibit spindling growth and improve quality of cucumber seedlings under low irradiance, effects of supplemental light-emitting diodes (LED) light (SL) on morphological and physiological characteristics of cucumber seedlings at different growth stages under extremely low irradiance (ELI) were investigated. Supplementary monochromatic, dichromatic and trichromatic LED light on cucumber seedlings were conducted in experiment one, and supplements of combination ratios and intensity of blue and red LED light (RB) were conducted in experiment two. The morphological and physiological parameters of cucumber seedlings were promoted effectively by supplemental monochromatic red light or dichromatic containing red light (RB and RG) under ELI as early as one-leaf seedling stage, as demonstrated by suppressed length of hypocotyl and first internode, increased stem diameter and biomass, higher net photosynthetic rate (Pn) and soluble sugar content. Monochromatic or additional green light was not beneficial to cucumber seedlings under the ELI. The length of shoot and hypocotyl decreased, while stem diameter and leaf area increased as early as one-leaf seedling stage by RB SL. Root activities, root–shoot ratio, activities of catalase (CAT) and peroxidase (POD), as well as palisade–spongy ratio in the leaf of cucumber seedlings were promoted effectively by increasing blue light proportion (1R1B/1R2B). Increasing light intensity (50/75) enhanced soluble sugar accumulation in leaves. There were synergistic effects of RB ratio and light intensity on increasing stem diameter, leaf area, seedling index and decreasing hypocotyl cell area of the vertical section. In conclusion, 1R2B-75 may be the optimal SL to inhibit spindling growth of cucumber seedlings under ELI condition.
Impact of Climate Change on Population Dynamics and Herbicide Resistance in Kochia (Bassia scoparia (L.) A. J. Scott)
Authors: Chen Jinyi , Burns Erin , Fleming Margaret , Patterson Eric
Published: November 2020

Climate change has greatly impacted agronomy. Climate forecasts for the coming years predict increases in global temperature, carbon dioxide concentration, and extreme weather events. These changes will continue to influence agricultural production by altering abiotic stress on plants, including crops and weeds. Kochia, one of the most common weeds in North America, is a C4 plant exceptional for its drought tolerance. Kochia has also demonstrated rapid adaption and evolution to the abiotic stress of herbicide application, particularly glyphosate. Abiotic stresses from both climate change and herbicides impact the distribution and expansion of kochia. Being aware of the features and properties of kochia, especially those resulting from herbicide resistance, will help anticipate how kochia responds or migrates under future climate change, and help create proper strategies for kochia weed management.
Simulation-Based Capacity Planning of a Biofuel Refinery
Authors: Kim Sojung , Ofekeze Evi , Kiniry James R. , Kim Sumin
Published: November 2020

The reduction in the operational cost of a biofuel refinery is vitally important to make biofuel competitive with fossil fuels. The aim of this paper is to find a cost-efficient and sustainable refinery capacity for grain-based ethanol (i.e., corn-based ethanol) production, which will play an important role in promoting the widespread adoption and sustainable use of ethanol, by improving the productivity of the overall refining process. Continuous-event simulation was utilized in this study to model complex operations of a refinery such as the loading, unloading and treatment of feedstock over nine major phases (e.g., feedstock storage and handling, pretreatment and conditioning, fermentation and hydrolysis, and enzyme production) to produce ethanol. To improve the model prediction, the real data of corn yield produced in Tazewell County, Illinois, U.S. were used. The proposed simulation model is implemented in AnyLogic® University 8.6.0 simulation software, Chicago, IL, USA, and the (near) optimal number of reactors for the hydrolysis and fermentation is found via optimization software known as OptQuest®, Boulder, CO, USA, As a result, the proposed approach found that six reactors showed the optimal daily profit from USD 67,500 to 82,217. This information will help engineers and policy makers to modify the capacity of a biofuel refinery for enhancement of the system efficiency and ethanol production.
Transcriptomic Analysis Reveals Salt Tolerance Mechanisms Present in Date-Plum Persimmon Rootstock (Diospyros lotus L.)
Authors: Gil-Muñoz Francisco , Delhomme Nicolas , Quiñones Ana , Naval Maria del Mar , Badenes Maria Luisa , García-Gil M. Rosario
Published: November 2020

Agriculture needs solutions for adapting crops to increasing salinity globally. Research on physiological and molecular responses activated by salinity is needed to elucidate mechanisms of salinity tolerance. Transcriptome profiling (RNA-Seq) is a powerful tool to study the transcriptomic profile of genotypes under stress conditions. Persimmon species have different levels of tolerance to salinity, this variability may provide knowledge on persimmon species and development of salt--tolerant rootstocks. In this study, we conducted a physiological and transcriptomic profiling of roots and leaves in tolerant and sensitive plants of persimmon rootstock grown under saline and control conditions. Characterization of physiological responses along with gene expression changes in roots and leaves allowed the identification of several salt tolerance mechanisms related to ion transport and thermospermine synthesis. Differences were observed in putative H+/ATPases that allow transmembrane ionic transport and chloride channel protein-like genes. Furthermore, an overexpression of thermospermine synthase found in the roots of tolerant plants may indicate that alterations in root architecture could act as an additional mechanism of response to salt stress. These results indicate that Diospyros lotus L. exhibits genetically-controlled variability for salt tolerance traits which opens potential opportunities for breeding salt-tolerant persimmon rootstocks in a Mediterranean environment challenged by drought and salinity.
Antioxidant Therapy against Oxidative Damage of the Inner Ear: Protection and Preconditioning
Authors: Pak Jhang Ho , Kim Yehree , Yi Junyeong , Chung Jong Woo
Published: November 2020

Oxidative stress is an important mechanism underlying cellular damage of the inner ear, resulting in hearing loss. In order to prevent hearing loss, several types of antioxidants have been investigated; several experiments have shown their ability to effectively prevent noise-induced hearing loss, age-related hearing loss, and ototoxicity in animal models. Exogenous antioxidants has been used as single therapeutic agents or in combination. Antioxidant therapy is generally administered before the production of reactive oxygen species. However, post-exposure treatment could also be effective. Preconditioning refers to the phenomenon of pre-inducing a preventative pathway by subtle stimuli that do not cause permanent damage in the inner ear. This renders the inner ear more resistant to actual stimuli that cause permanent hearing damage. The preconditioning mechanism is also related to the induction of antioxidant enzymes. In this review, we discuss the mechanisms underlying antioxidant-associated therapeutic effects and preconditioning in the inner ear.
Detection of Ki67 Hot-Spots of Invasive Breast Cancer Based on Convolutional Neural Networks Applied to Mutual Information of H&E and Ki67 Whole Slide Images
Authors: Swiderska-Chadaj Zaneta , Gallego Jaime , Gonzalez-Lopez Lucia , Bueno Gloria
Published: November 2020

Ki67 hot-spot detection and its evaluation in invasive breast cancer regions play a significant role in routine medical practice. The quantification of cellular proliferation assessed by Ki67 immunohistochemistry is an established prognostic and predictive biomarker that determines the choice of therapeutic protocols. In this paper, we present three deep learning-based approaches to automatically detect and quantify Ki67 hot-spot areas by means of the Ki67 labeling index. To this end, a dataset composed of 100 whole slide images (WSIs) belonging to 50 breast cancer cases (Ki67 and H&E WSI pairs) was used. Three methods based on CNN classification were proposed and compared to create the tumor proliferation map. The best results were obtained by applying the CNN to the mutual information acquired from the color deconvolution of both the Ki67 marker and the H&E WSIs. The overall accuracy of this approach was 95%. The agreement between the automatic Ki67 scoring and the manual analysis is promising with a Spearman’s ρ correlation of 0.92. The results illustrate the suitability of this CNN-based approach for detecting hot-spots areas of invasive breast cancer in WSI.
The Accuracy of Three Intraoral Scanners in the Oral Environment with and without Saliva: A Comparative Study
Authors: Rapone Biagio , Palmisano Cosimo , Ferrara Elisabetta , Di Venere Daniela , Albanese Giovanni , Corsalini Massimo
Published: November 2020

Background: with the emergence of technological innovations in the dental industry, one emerging trend has been the intraoral digitizing of patients by using intraoral scanning systems. Compared to taking conventional impressions, the use of intraoral scanners (IOS) is suitable for capturing direct optical impressions, helping to improve diagnostic efficacy, save time, reduce patient discomfort, and simplify clinical procedures. Intraoral scanning systems appear to have a high potential for providing guidance on proper standards of care. However, one main disadvantage is breathing and saliva secretion, which causes deviations, interfering with the applicability and accuracy of the optical impression. The aim of this study was to compare the validity and accuracy of three commercially available intraoral scanners, performing an analysis exploiting a wet model. Methods: an in vitro experimental study of four permanent teeth (two molars and two premolars) on the accuracy of copings obtained by subgingival preparations was performed, using an oral wet environment model. Two hundred and forty digital impressions were produced from three digital scanners using four samples. Descriptive analysis was performed using mean, standard deviation, and median. ANOVA and F-tests were performed to assess the amount of variability between the groups. For statistical analysis a 95% significance level was chosen. Results: all differences between groups were statistically significant. Conclusions: the present data implicate a huge impact of the oral biological fluids on the accuracy of digital impression to corresponding images, implying a failure of accurate impression under wetness conditions.
Artificial Intelligence Prediction of Rutting and Fatigue Parameters in Modified Asphalt Binders
Authors: Uwanuakwa Ikenna D. , Ali Shaban Ismael Albrka , Hasan Mohd Rosli Mohd , Akpinar Pinar , Sani Ashiru , Shariff Khairul Anuar
Published: November 2020

The complex shear modulus (G*) and phase angle (δ) are fundamental viscoelastic rheological properties used in the estimation of rutting and fatigue pavement distress in asphalt binder. In the tropical regions, rutting and fatigue cracking are major pavement distress affecting the serviceability of road infrastructure. Laboratory testing of the complex shear modulus and phase angle requires expensive and advanced equipment that is not obtainable in major laboratories within the developing countries of the region, giving rise to the need for an accurate predictive model to support quality pavement design. This research aims at developing a predictive model for the estimation of rutting and fatigue susceptive of asphalt binder at intermediate and high pavement temperatures. Asphalt rheological and ageing test was conducted on eight mixes of modified binders used to build the study database containing 1976 and 1668 data points for rutting and fatigue parameters respectively. The database was divided into training and simulation dataset. The Gaussian process regression (GPR) algorithm was used to predict the rutting and fatigue parameters using unaged and aged conditioned inputs. The proposed GPR was compared with the support vector machine (SVM), recurrent neural networks (RNN) and artificial neural network (ANN) models. Results show that the model performed better in the estimation of rutting parameter than the fatigue parameter. Further, unaged input variables show better reliability in the prediction of fatigue parameter.
Transfer Learning-Based Fault Diagnosis under Data Deficiency
Authors: Cho Seong Hee , Kim Seokgoo , Choi Joo-Ho
Published: November 2020

In the fault diagnosis study, data deficiency, meaning that the fault data for the training are scarce, is often encountered, and it may deteriorate the performance of the fault diagnosis greatly. To solve this issue, the transfer learning (TL) approach is employed to exploit the neural network (NN) trained in another (source) domain where enough fault data are available in order to improve the NN performance of the real (target) domain. While there have been similar attempts of TL in the literature to solve the imbalance issue, they were about the sample imbalance between the source and target domain, whereas the present study considers the imbalance between the normal and fault data. To illustrate this, normal and fault datasets are acquired from the linear motion guide, in which the data at high and low speeds represent the real operation (target) and maintenance inspection (source), respectively. The effect of data deficiency is studied by reducing the number of fault data in the target domain, and comparing the performance of TL, which exploits the knowledge of the source domain and the ordinary machine learning (ML) approach without it. By examining the accuracy of the fault diagnosis as a function of imbalance ratio, it is found that the lower bound and interquartile range (IQR) of the accuracy are improved greatly by employing the TL approach. Therefore, it can be concluded that TL is truly more effective than the ordinary ML when there is a large imbalance between the fault and normal data, such as smaller than 0.1.
Determination of Initial-Shear-Stress Impact on Ramsar-Sand Liquefaction Susceptibility through Monotonic Triaxial Testing
Authors: Nategh Mehrdad , Ekinci Abdullah , Iravanian Anoosheh , Salamatpoor Siavash
Published: November 2020

Liquefaction risk assessment is critical for the safety and economics of structures. As the soil strata of Ramsar area in north Iran is mostly composed of poorly graded clean sand and the ground water table is found at shallow depths, it is highly susceptible to liquefaction. In this study, a series of isotropic and anisotropic consolidated undrained triaxial tests were performed on reconstituted specimens of Ramsar sand to identify the liquefaction potential of the area. The specimens are consolidated isotropically to simulate the level ground condition, and anisotropically to simulate the soil condition on a slope and/or under a structure. The various states of soil behavior are studied by preparing specimens at different initial relative densities and applying different levels of effective stress. The critical state soil mechanics approach for identifying the liquefaction susceptibility is adopted and the observed phenomena are further explained in relation to the micro-mechanical behavior. As only four among the 27 conducted tests did not exhibit liquefactive behavior, Ramsar sand can be qualified as strongly susceptible to liquefaction. Furthermore, it is observed that the pore pressure ratio is a good indication of the liquefaction susceptibility.
Investigation of Open Air Stability of CsPbBr3 Thin-Film Growth on Different Substrates
Authors: Calisi Nicola , Caporali Stefano
Published: November 2020

Originally developed out of scientific curiosity, lead halide perovskites are rapidly gaining success due to their broad tenability and ease of fabrication. Despite these advantages and the considerable progress made in the efficiency of perovskite-based devices, the stability of such materials remains a challenge. In this research paper, the role of substrate materials on which thin films of perovskites were deposited was examined, highlighting their critical importance for atmosphere-induced degradation. Indeed, CsPbBr3 thin films sputtered on glass (soda lime and quartz) and indium tin oxide (ITO) resulted more stable, while those deposited on polycrystalline gold-coated glass were much more prone to degradation in a temperature- and moisture-controlled (43% relative humidity (RH)) atmosphere.
Effect of Severe Plastic Deformation, through Equal-Channel Angular Press Processing, on the Electrochemical Behavior of Al5083 Alloy
Authors: Seikh Asiful H. , Baig Muneer , Ur Rehman Ateekh
Published: November 2020

In this study, Al5083 alloy was deformed through equal-channel angular pressing (ECAP) up to three passes. The ECAP was conducted at room temperature in a mold using route C. The microstructure evolution was investigated under optical microscopic observations. The grain size was measured using ImageJ software. Grain refinement from 145 µM (as received) to 37 µM (after third pass) was observed due to ECAP. The potentiodynamic polarization of the Al5083 alloy was obtained from a 3.5% sodium chloride solution. Electrochemical impedance spectroscopy was performed in the sodium chloride solution to study the alloy’s surface properties. Scanning electron microscopy and Raman spectroscopy were conducted after obtaining the corrosion performance. As a result, we found that ECAP processing leads to the grain refinement of the alloy, which causes a detrimental effect on the corrosion resistance property.
Determination of Leg Alignment in Hip Osteoarthritis Patients with the EOS® System and the Effect on External Joint Moments during Gait
Authors: van Drongelen Stefan , Kaldowski Hanna , Fey Benjamin , Tarhan Timur , Assi Ayman , Stief Felix , Meurer Andrea
Published: November 2020

The present study considered the entire leg alignment and links static parameters to the external joint moments during gait in patients with hip osteoarthritis. Eighteen patients with unilateral hip osteoarthritis were measured using the EOS® system. Clinical leg alignment and femoral parameters were extracted from the 3D reconstruction of the EOS images. A 3D gait analysis was performed and external knee and hip adduction moments were computed and compared to 18 healthy controls in the same age group. The knee adduction moments of the involved leg were strongly correlated to the femoral offset and the varus/valgus alignment. These parameters alone explained over 50% of the variance in the knee adduction moments. Adding the pelvic drop of the contralateral side increased the model of femoral offset and varus/valgus alignment and explained 78% of the knee adduction moment during the first half of the stance phase. The hip adduction moments were best associated with the hip kinematics and not the leg alignment.
Hyperspectral Imaging for Minced Meat Classification Using Nonlinear Deep Features
Authors: Ayaz Hamail , Ahmad Muhammad , Mazzara Manuel , Sohaib Ahmed
Published: November 2020

Minced meat substitution is one of the most common forms of food fraud in the meat industry. Recently, Hyperspectral Imaging (HSI) has been used for the classification and identification of minced meat types. However, conventional methods are based only on spectral information and ignore the spatial variability of the data. Moreover, these methods first tend to reduce the size of the data, which to some extent ignores the abstract level information and does not preserve the spatial information. Therefore, this work proposes a novel Isos-bestic wavelength reduction method for the different minced meat types, by retaining only Myoglobin pigments (Mb) in the meat spectra. A total of 60 HSI cubes are acquired using Fx 10 Hyperspectral sensor. For each HSI cube, a set of preprocessing schemes is applied to extract the Region of Interest (ROI) and spectral preprocessing, i.e., Golay filtering. Later, these preprocessed HSI cubes are fed into a 3D-Convolutional Neural Network (3D-CNN) model for nonlinear feature extraction and classification. The proposed pipeline outperformed several state-of-the-art methods, with an overall accuracy of 94.0%.
Assessment of Human-Related Driving Forces for Reduced Carbon Uptake Using Neighborhood Analysis and Geographically Weighted Regression: A Case Study in the Grassland of Inner Mongolia, China
Authors: Sha Zongyao , Li Ruren
Published: November 2020

The ever-rising concentration of atmospheric carbon is viewed as the primary cause for global warming. To discontinue this trend, it is of urgent importance to either cut down human carbon emissions or remove more carbon from the atmosphere. Grassland ecosystems occupy the largest part of the global land area but maintain a relatively low carbon sequestration flux. While numerous studies have confirmed the impacts on grassland vegetation growth from climate changes and human activities, little work has been done to understand the driving forces for a reduced carbon uptake (RCU)—a loss in vegetation carbon sequestration because of inappropriate grassland management. This work focused on assessing RCU in the grassland of Inner Mongolia and understanding the influential patterns of the selected variables (including grazing intensity, road network, population, and vegetation productivity) related to RCU. Neighborhood analysis was proposed to locate optimized grassland management practices from historical data and to map RCU. Ordinary least squares (OLS) and geographically weighted regression (GWR) models were applied to explore the driving forces for RCU. The results indicated that the human-related factors, including stock grazing intensity, population density, and road network were likely to present a spatially varied impact on RCU, which accounted for more than 1/4 of the total carbon sequestration.
Practical Security Bounds against Trojan Horse Attacks in Continuous-Variable Quantum Key Distribution
Authors: Pan Yaxi , Zhang Ling , Huang Duan
Published: November 2020

As the existence of non-zero reflection coefficients in the real component of continuous-variable quantum key distribution (CV-QKD) systems, Eve can probe the system by sending the bright light pulses into Alice’s set-up. With the analysis of back-reflections, Eve only takes a few back-reflected photons to intercept information and obtain the raw key bit. In this paper, the attack problems are converted into the information leakage problems. First, we analyzed the Trojan horse attacks with different wavelengths and confirmed its side effects, such as crosstalk and anti-Stokes Raman scattering, by a numerical simulation. Then, based on the wavelength-dependent property of beam splitter, we presented a practical way to estimate the deviation of shot noise and therefore correct the excess noise by inserting different wavelength pulses under joint attacks. Finally, we specified the security bounds of the system through quantifying the excess noise bounds caused by the Trojan horse attacks and provided a theoretical reference for the secret key transmission of system. As a consequence, the transmission errors within the security bounds can be negligible and the legitimate users will not perceive the presence of Eve.
Detection for Frying Times of Various Edible Oils Based on Near-Infrared Spectroscopy
Authors: Liu Yi , Sun Laijun , Bai Hongyi , Ran Zhiyong
Published: November 2020

Taking a variety of edible oils as the research object, including soybean oil, peanut oil, rapeseed oil, a method based on Near-Infrared Spectroscopy (NIRS) to identify the frying times is proposed to evaluate the quality of frying oil. Ten rounds of frying experiments are carried out for each of the three oils. The spectra of the first eight rounds are used to build the model, and the last two are used for model testing. First, all the original spectra are preprocessed using the first derivative (1D). Then, the correlation coefficient between the sequence of frying times and absorbance is calculated, and the characteristic wavelengths with a high correlation coefficient are extracted. Finally, a differential prediction model is established based on the characteristic wavelengths. The results show that the differential prediction model accurately predicts the frying times of various edible oils and provides a new method for quality inspection of frying oil, and the predicted accuracy of the frying times of three frying oils is 100% within the allowable range of error.
Multi-Task Learning for Small Brain Tumor Segmentation from MRI
Authors: Ngo Duc-Ky , Tran Minh-Trieu , Kim Soo-Hyung , Yang Hyung-Jeong , Lee Guee-Sang
Published: November 2020

Segmenting brain tumors accurately and reliably is an essential part of cancer diagnosis and treatment planning. Brain tumor segmentation of glioma patients is a challenging task because of the wide variety of tumor sizes, shapes, positions, scanning modalities, and scanner’s acquisition protocols. Many convolutional neural network (CNN) based methods have been proposed to solve the problem of brain tumor segmentation and achieved great success. However, most previous studies do not fully take into account multiscale tumors and often fail to segment small tumors, which may have a significant impact on finding early-stage cancers. This paper deals with the brain tumor segmentation of any sizes, but specially focuses on accurately identifying small tumors, thereby increasing the performance of the brain tumor segmentation of overall sizes. Instead of using heavyweight networks with multi-resolution or multiple kernel sizes, we propose a novel approach for better segmentation of small tumors by dilated convolution and multi-task learning. Dilated convolution is used for multiscale feature extraction, however it does not work well with very small tumor segmentation. For dealing with small-sized tumors, we try multi-task learning, where an auxiliary task of feature reconstruction is used to retain the features of small tumors. The experiment shows the effectiveness of segmenting small tumors with the proposed method. This paper contributes to the detection and segmentation of small tumors, which have seldom been considered before and the new development of hierarchical analysis using multi-task learning.
Non-Linear Spectral Unmixing for the Estimation of the Distribution of Graphene Oxide Deposition on 3D Printed Composites
Authors: Licciardi Giorgio , Del Gaudio Costantino , Chanussot Jocelyn
Published: November 2020

Hyperspectral analysis is a well-established technique that can be suitably implemented in several application fields, including materials science. This approach allows us to deal with data samples containing spatial and spectral information at very high resolution, thus enabling us to evaluate materials properties at a nanoscale level. As a proof of concept, hyperspectral imaging was here considered to investigate 3D printed polymer matrix composites, considering graphene oxide (GO) as a nanofiller. Commercial polycaprolactone and polylactic acid filaments were firstly treated with GO to be then printed into testing specimens. Raman analysis was performed to assess the GO distribution on samples surface by mapping different regions of interest and the collected data were the input of a custom-made algorithm for hyperspectral image analysis, tailored to detect the GO signature. Findings showed a valuable matching to Raman maps and were also characterized by the positive feature of avoiding to set specific conditions to perform the investigation as GO Raman distribution was carried out by fixing the wavenumber at 1580 cm−1, which is representative of the G band of the nanofiller. This occurrence might lead to an uneven intensity representation related to possible peak shifts which can bias the acquired results. Differently, hyperspectral imaging needs a minimal set of data input, i.e., the spectral signatures of neat materials, to directly identify the searched nanomaterial. More in-depth investigations need to be performed to fully validate the proposed approach, but the here presented results already show the potential and versatility of hyperspectral analysis in the materials science field.
Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation
Authors: Bouteraa Yassine , Ben Abdallah Ismail , Ibrahim Atef , Ahanger Tariq Ahamed
Published: November 2020

The last few years have seen significant advances in neuromotor rehabilitation technologies, such as robotics and virtual reality. Rehabilitation robotics primarily focuses on devices, control strategies, scenarios and protocols aimed at recovering sensory, motor and cognitive impairments often experienced by stroke victims. Remote rehabilitation can be adopted to relieve stress in healthcare facilities by limiting the movement of patients to clinics, mainly in the current COVID-19 pandemic. In this context, we have developed a remote controlled intelligent robot for elbow rehabilitation. The proposed system offers real-time monitoring and ultimately provides an electronic health record (EHR). Rehabilitation is an area of medical practice that treats patients with pain. However, this pain can prevent a person from positively interacting with therapy. To cope with this matter, the proposed solution incorporates a cascading fuzzy decision system to estimate patient pain. Indeed, as a safety measure, when the pain exceeds a certain threshold, the robot must stop the action even if the desired angle has not yet been reached. A fusion of sensors incorporating an electromyography (EMG) signal, feedback from the current sensor and feedback from the position encoder provides the fuzzy controller with the data needed to estimate pain. This measured pain is fed back into the control loop and processed to generate safe robot actions. The main contribution was to integrate vision-based gesture control, a cascade fuzzy logic-based decision system and IoT (Internet of Things) to help therapists remotely take care of patients efficiently and reliably. Tests carried out on three different subjects showed encouraging results.
Laser Induced Aggregation of Light Absorbing Particles by Marangoni Convection
Authors: Li Bo-Wei , Zhong Min-Cheng , Ji Feng
Published: November 2020

Laser induced Marangoni convection can be used to accumulate micro-particles. In this paper, a method is developed to control and accumulate the light absorbing particles dispersed in a thin solution layer. The particles are irradiated by a focused laser beam. Due to the photothermal effect of the particles, the laser heating generates a thermal gradient and induces a convective flow around the laser’s heating center. The convective flow drives the particles to accumulate and form a particle aggregate close to the laser’s heating center. The motion of particles is dominated by the Marangoni convection. When the laser power is high, the vapor bubbles generated by laser heating on particles strengthen the convection, which accelerates the particles’ aggregation.
Multi-Scale Demodulation for Fault Diagnosis Based on a Weighted-EMD De-Noising Technique and Time–Frequency Envelope Analysis
Authors: Du Wei-tao , Zeng Qiang , Shao Yi-min , Wang Li-ming , Ding Xiao-xi
Published: November 2020

Demodulation is one of the most useful techniques for the fault diagnosis of rotating machinery. The commonly used demodulation methods try to select one sensitive sub-band signal that contains the most fault-related components for further analysis. However, a large number of the fault-related components that exist in other sub-bands are ignored in the commonly used envelope demodulation methods. Based on a weighted-empirical mode decomposition (EMD) de-noising technique and time–frequency (TF) impulse envelope analysis, a multi-scale demodulation method is proposed for fault diagnosis. In the proposed method, EMD is first employed to divide the signal into some IMFs (intrinsic mode functions). Then, a new weighted-EMD de-noising technique is presented, and different weights are assigned to IMFs for construction according to their fault-related degrees; thus, the fault-unrelated components are suppressed to improve the signal-to-noise ratio (SNR). After that, continuous wavelet transformation (CWT) is adopted to obtain the time–frequency representation (TFR) of the de-noised signal. Subsequently, the fault-related components in the entire frequency range scale are calculated together, referring to the TF impulse envelope signal. Finally, a fault diagnosis result can be obtained after the fast Fourier transformation of the TF impulse envelope signal. The proposed method and three commonly used methods are applied to the fault diagnosis of a planetary gearbox with a sun gear spalling fault and a fixed shaft gearbox with a crack fault. The results show that the proposed method can effectively detect gear faults and yields better performance than other methods.
Anti-SARS-Cov-2 IgA Response in Tears of COVID-19 Patients
Authors: Caselli Elisabetta , Soffritti Irene , Lamberti Giuseppe , D’Accolti Maria , Franco Filippo , Demaria Davide , Contoli Marco , Passaro Angela , Contini Carlo , Perri Paolo
Published: November 2020

The pandemic virus SARS-CoV-2 has been reported to be able to enter the body via the eye conjunctiva, but the presence of antiviral response in the eye remains poorly known. Our study was thus aimed to analyze the presence of secretory mucosal anti-SARS-CoV-2 type A immunoglobulins (IgA) in the conjunctival fluid of COVID-19 patients. The tears of 28 COVID-19 patients and 20 uninfected controls were collected by the Schirmer test and analyzed by a specific ELISA assay detecting anti-spike (S1) virus protein IgA. The results showed that 35.7% of COVID-19 subjects have specific antiviral IgA at the ocular level, persisting till 48 days post disease onset. Most of the IgA positive subjects presented mild symptoms. The collected data indicate a prolonged persistence of anti-SARS-CoV-2 IgA at the eye level and suggest that IgA detection may be extremely helpful in clarifying virus pathology and epidemiology.
Proteasome Inhibitor MG132 is Toxic and Inhibits the Proliferation of Rat Neural Stem Cells but Increases BDNF Expression to Protect Neurons
Authors: Kim Young Min , Kim Hyun-Jung
Published: November 2020

Regulation of protein expression is essential for maintaining normal cell function. Proteasomes play important roles in protein degradation and dysregulation of proteasomes is implicated in neurodegenerative disorders. In this study, using a proteasome inhibitor MG132, we showed that proteasome inhibition reduces neural stem cell (NSC) proliferation and is toxic to NSCs. Interestingly, MG132 treatment increased the percentage of neurons in both proliferation and differentiation culture conditions of NSCs. Proteasome inhibition reduced B-cell lymphoma 2 (Bcl-2)/Bcl-2 associated X protein ratio. In addition, MG132 treatment induced cAMP response element-binding protein phosphorylation and increased the expression of brain-derived neurotrophic factor transcripts and proteins. These data suggest that proteasome function is important for NSC survival and differentiation. Moreover, although MG132 is toxic to NSCs, it may increase neurogenesis. Therefore, by modifying MG132 chemical structure and developing none toxic proteasome inhibitors, neurogenic chemicals can be developed to control NSC cell fate.
Modular and Integrated Systems for Nanoparticle and Microparticle Synthesis—A Review
Authors: Lu Hongda , Tang Shi-Yang , Yun Guolin , Li Haiyue , Zhang Yuxin , Qiao Ruirui , Li Weihua
Published: November 2020

Nanoparticles (NPs) and microparticles (MPs) have been widely used in different areas of research such as materials science, energy, and biotechnology. On-demand synthesis of NPs and MPs with desired chemical and physical properties is essential for different applications. However, most of the conventional methods for producing NPs/MPs require bulky and expensive equipment, which occupies large space and generally need complex operation with dedicated expertise and labour. These limitations hinder inexperienced researchers to harness the advantages of NPs and MPs in their fields of research. When problems individual researchers accumulate, the overall interdisciplinary innovations for unleashing a wider range of directions are undermined. In recent years, modular and integrated systems are developed for resolving the ongoing dilemma. In this review, we focus on the development of modular and integrated systems that assist the production of NPs and MPs. We categorise these systems into two major groups: systems for the synthesis of (1) NPs and (2) MPs; systems for producing NPs are further divided into two sections based on top-down and bottom-up approaches. The mechanisms of each synthesis method are explained, and the properties of produced NPs/MPs are compared. Finally, we discuss existing challenges and outline the potentials for the development of modular and integrated systems.