bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Technique for Controllable Fabrication of Multilayer Copper/Brass Block
Authors: Li Jiansheng , Zhou Zhongchen , Liu Tong , Zhao Yu , Lu Yan , Chen Ming , Wang Xiaozhen , Wang Gang , Mao Qingzhong
Published: November 2021

Fabricating a dissimilar-metal block with micro/nano-multilayered structures is usually used by engineers and scientists because of their excellent mechanical properties. In the current work, multilayered copper/brass blocks were effectively fabricated by a synthetical DWFR technique, which includes the processes of diffusion welding, forging and rolling. Diffusion welding was used as the first operation to metallurgically bond the copper and brass sheets, with a Zn diffusion transition layer (thickness of ~100 μm), which can guarantee the bonding strength of copper/brass interfaces during the subsequent forging and rolling processes. After diffusion welding, the original copper/brass blocks were required to be forged, with its total thickness reduced to ~10 mm. This can further restrain the delamination of copper and brass layers during the final rolling process. Rolling was utilized as the ideal operation that can precisely tune the thickness of copper/brass laminate. This novel DWFR technique can easily tune the multilayered copper/brass blocks with controllable layer thickness (from ~250 to ~800 nm). The copper/brass interfaces were well-bonded, and the utilization efficiency of raw materials was very high (>95%).
Strain Rate and Temperature Effects on Tensile Properties of Polycrystalline Cu6Sn5 by Molecular Dynamic Simulation
Authors: Huang Wei , Pan Kailin , Zhang Jian , Gong Yubing
Published: November 2021

Intermetallic compounds (IMCs) are essential in the soldering of electronic products and are composed mainly of Cu6Sn5 and Cu3Sn. They must maintain reliable mechanical and electrical connections. As they are usually only a few microns thick, and it is difficult to study their mechanical properties by traditional methods. In this study, a 100 Å × 100 Å × 100 Å polycrystal with 10 grains was created by Atomsk through Voronoi tessellation based on a Cu6Sn5 unit cell. The effects of the temperature and strain rate on the tensile properties of the polycrystalline Cu6Sn5 were analyzed based on MEAM potential function using a molecular dynamics (MD) method. The results show that Young’s modulus and ultimate tensile strength (UTS) of the polycrystalline Cu6Sn5 decrease approximately linearly with an increase in temperature. At high strain rates (0.001–100 ps−1), Young’s modulus and UTS of the Cu6Sn5 are logarithmic with respect to the strain rate, and both increase with an increase in strain rate. In addition, at low strain rates (0.00001–0.0005 ps−1), the UTS has a quadratic increase as the strain rate increases.
Synthesis and Characterization of New Guanine Complexes of Pt(IV) and Pd(II) by X-ray Diffraction and Hirshfeld Surface Analysis
Authors: Novikov Anton Petrovich , Volkov Mikhail Alexandrovich , Safonov Alexey Vladimirovich , Grigoriev Mikhail Semenovich , Abkhalimov Evgeny Vladilenovich
Published: November 2021

The aim of the work was to synthesize new perspective compounds of palladium and platinum with nitrogenous bases (guanine), promising for use in biomedicine and catalysis. The article describes the synthesis of new [PdCl2(HGua)2]Cl2·H2O and [PtCl5(HGua)]·2H2O compounds using wet chemistry methods. The structure of the obtained single crystals was established by the method of single crystal X-ray diffraction. The complexes have an M-N bond, and the organic ligand is included in the first coordination sphere. The analysis of Hirshfeld surfaces for the obtained complexes and their analogues for the analysis of intermolecular interactions was carried out. In the palladium complex we obtained, π-halogen and π-stacking interactions were found; in analogues, such interactions were not found. π-halogen and halogen interactions were found in structure of platinum complex and its analogues.
Synthesis, X-ray Structure, Conformational Analysis, and DFT Studies of a Giant s-Triazine bis-Schiff Base
Authors: Almarhoon Zainab M. , Al-Zaben Maha I. , Ben Bacha Abir , Haukka Matti , El-Faham Ayman , Soliman Saied M.
Published: November 2021

The current work involves the synthesis of 2,2′-(6-(piperidin-1-yl)-1,3,5-triazine-2,4-diyl)bis(hydrazin-2-yl-1-ylidene))bis(methanylylidene))diphenol 4, characterization, and the DFT studies of the reported compound. The crystal unit cell parameters of 4 are a = 8.1139(2) Å, b = 11.2637(2) Å, c = 45.7836(8) Å. The unit cell volume is 4184.28(15) Å3 and Z = 4. It crystallized in the orthorhombic crystal system and Pbca space group. The O…H, N…H, C…H, H…H and C…C intermolecular contacts which affect the crystal stability were quantitatively analyzed using Hirshfeld calculations. Their percentages were calculated to be 9.8, 15.8, 23.7, 46.4, and 1.6% from the whole contacts occurred in the crystal, respectively. Conformational analysis was performed using DFT calculations for 17 suggested conformers and the most stable conformer was found to be the one which is stabilized by two intramolecular O-H…N hydrogen bonding interactions. This conclusion was further revealed by natural bond orbital calculations.
Preparation of Flower-like Nickel-Based Bimetallic Organic Framework Electrodes for High-Efficiency Hybrid Supercapacitors
Authors: Jiang Di , Wei Chuanying , Zhu Ziyang , Xu Xiaohui , Lu Min , Wang Guangsheng
Published: November 2021

Metal organic frameworks (MOFs) have been rapidly developed in the application of electrode materials due to their controllable morphology and ultra-high porosity. In this research, flower-like layered nickel-based bimetallic MOFs microspheres with different metal central ions were synthesized by solvothermal method. Compared with Ni-MOFs, the optimization of the specific capacitance of NiCo-MOFs and NiMn-MOFs was been confirmed. For example, the specific capacitance of NiCo-MOFs can reach 882 F·g−1 at 0.5 A·g−1 while maintaining satisfactory cycle life (the specific capacity remains 90.1% of the initial value after 3000 charge-discharge cycles at 5 A·g−1). In addition, the NiCo-MOFs//AC HSCs, which are composed of NiCo-MOFs and activated carbon (AC), achieved a maximum energy density of 18.33 Wh·kg−1 at a power density of 400 W·kg−1, and showed satisfactory cycle life (82.4% after 3000 cycles). These outstanding electrochemical properties can be ascribed to the synergistic effect between metal ions, the optimized conductivity, and the unique layered stacked flower structure, which provides a smooth transmission channel for electrons/ions. In addition, this research gives a general method for the application of MOFs in the field of supercapacitors.
Exploring Machine Learning Techniques to Predict the Response to Omalizumab in Chronic Spontaneous Urticaria
Authors: Sardina Davide Stefano , Valenti Giuseppe , Papia Francesco , Uasuf Carina Gabriela
Published: November 2021

Background: Omalizumab is the best treatment for patients with chronic spontaneous urticaria (CSU). Machine learning (ML) approaches can be used to predict response to therapy and the effectiveness of a treatment. No studies are available on the use of ML techniques to predict the response to Omalizumab in CSU. Methods: Data from 132 CSU outpatients were analyzed. Urticaria Activity Score over 7 days (UAS7) and treatment efficacy were assessed. Clinical and demographic characteristics were used for training and validating ML models to predict the response to treatment. Two methodologies were used to label the data based on the response to treatment (UAS7 ≥ 6): (A) at 1, 3 and 5 months; (B) classifying the patients as early responders (ER), late responders (LR) or non-responders (NR) (ER: UAS 7 ≥ 6 at first month, LR: UAS 7 ≥ 6 at third month, NR: if none of the previous conditions occurred). Results: ER were predominantly characterized by hypertension, while LR mainly suffered from asthma and hypothyroidism. A slight positive correlation (R2 = 0.21) was found between total IgE levels and UAS7 at 1 month. Variable Importance Analysis (VIA) reported D-dimer and C-reactive proteins as the key blood tests for the performance of learning techniques. Using methodology (A), SVM (specificity of 0.81) and k-NN (sensitivity of 0.8) are the best models to predict LR at the third month. Conclusion: k-NN plus the SVM model could be used to identify the response to treatment. D-dimer and C-reactive proteins have greater predictive power in training ML models.
Sarcopenia Diagnosis: Reliability of the Ultrasound Assessment of the Tibialis Anterior Muscle as an Alternative Evaluation Tool
Authors: Leigheb Massimiliano , de Sire Alessandro , Colangelo Matteo , Zagaria Domenico , Grassi Federico Alberto , Rena Ottavio , Conte Patrizio , Neri Pierluigi , Carriero Alessandro , Sacchetti Gian Mauro , Penna Fabio , Caretti Giuseppina , Ferraro Elisabetta
Published: November 2021

Sarcopenia is a skeletal muscle disorder characterized by reduced muscle mass, strength, and performance. Muscle ultrasound can be helpful in assessing muscle mass, quality, and architecture, and thus possibly useful for diagnosing or screening sarcopenia. The objective of this study was to evaluate the reliability of ultrasound assessment of tibialis anterior muscle in sarcopenia diagnosis. We included subjects undergoing total or partial hip replacement, comparing measures with a healthy control group. We measured the following parameters: tibialis anterior muscle thickness, echogenicity, architecture, stiffness, skeletal muscle index (SMI), hand grip strength, and sarcopenia related quality of life evaluated through the SarQoL questionnaire. We included 33 participants with a mean age of 54.97 ± 23.91 years. In the study group we found reduced tibialis anterior muscle thickness compared to the healthy control group (19.49 ± 4.92 vs. 28.94 ± 3.63 mm, p < 0.05) with significant correlation with SarQoL values (r = 0.80, p < 0.05), dynamometer hand strength (r = 0.72, p < 0.05) and SMI (r = 0.76, p < 0.05). Moreover, we found reduced stiffness (32.21 ± 12.31 vs. 27.07 ± 8.04 Kpa, p < 0.05). AUC measures of ROC curves were 0.89 predicting reduced muscle strength, and 0.97 predicting reduced SMI for tibialis anterior muscle thickness, while they were 0.73 and 0.85, respectively, for muscle stiffness. Our findings showed that ultrasound assessment of tibialis anterior muscle might be considered a reliable measurement tool to evaluate sarcopenia.
Oral Pemphigoid Recalcitrant Lesion Treated with PRGF Infiltration. Case Report
Authors: Anitua Eduardo , Alkhraisat Mohammad H. , Eguia Asier , Piñas Laura
Published: November 2021

Mucous membrane pemphigoid (MMP) is a heterogeneous group of chronic autoimmune subepithelial blistering diseases. Oral involvement is present in almost all patients, may represent the onset of the disease, and causes different degrees of pain, dysphagia, soreness, and bleeding. Treatment is based on systemic and/or oral corticoids, or other immunosuppressants. Occasionally, oral lesions can show a poor response to standard treatments. We present the case of a 61-year-old female patient with a painful extensive MMP oral ulcerative lesion recalcitrant to previous systemic azathioprine and local triamcinolone treatment, which was successfully treated in a novel way using PRGF infiltrations as adjuvant. After four weekly infiltrations, pain was reduced from 10 to 0 in a VAS and the lesion was completely healed. The patient continued with a low dose maintenance immunosuppressive treatment (prednisone 5 mg/day PO), and after 13 months of follow-up, there was no relapse of the lesion and no side effects. Although future research is necessary to confirm these observations, PRGF could be a useful adjuvant for the management of extensive mucous membrane pemphigoid oral lesions.
Winsorization for Robust Bayesian Neural Networks
Authors: Sharma Somya , Chatterjee Snigdhansu
Published: November 2021

With the advent of big data and the popularity of black-box deep learning methods, it is imperative to address the robustness of neural networks to noise and outliers. We propose the use of Winsorization to recover model performances when the data may have outliers and other aberrant observations. We provide a comparative analysis of several probabilistic artificial intelligence and machine learning techniques for supervised learning case studies. Broadly, Winsorization is a versatile technique for accounting for outliers in data. However, different probabilistic machine learning techniques have different levels of efficiency when used on outlier-prone data, with or without Winsorization. We notice that Gaussian processes are extremely vulnerable to outliers, while deep learning techniques in general are more robust.
Performances of Transcritical Power Cycles with CO2-Based Mixtures for the Waste Heat Recovery of ICE
Authors: Liu Jinghang , Yu Aofang , Lin Xinxing , Su Wen , Ou Shaoduan
Published: November 2021

In the waste heat recovery of the internal combustion engine (ICE), the transcritical CO2 power cycle still faces the high operation pressure and difficulty in condensation. To overcome these challenges, CO2 is mixed with organic fluids to form zeotropic mixtures. Thus, in this work, five organic fluids, namely R290, R600a, R600, R601a, and R601, are mixed with CO2. Mixture performance in the waste heat recovery of ICE is evaluated, based on two transcritical power cycles, namely the recuperative cycle and split cycle. The results show that the split cycle always has better performance than the recuperative cycle. Under design conditions, CO2/R290(0.3/0.7) has the best performance in the split cycle. The corresponding net work and cycle efficiency are respectively 21.05 kW and 20.44%. Furthermore, effects of key parameters such as turbine inlet temperature, turbine inlet pressure, and split ratio on the cycle performance are studied. With the increase of turbine inlet temperature, the net works of the recuperative cycle and split cycle firstly increase and then decrease. There exist peak values of net work in both cycles. Meanwhile, the net work of the split cycle firstly increases and then decreases with the increase of the split ratio. Thereafter, with the target of maximizing net work, these key parameters are optimized at different mass fractions of CO2. The optimization results show that CO2/R600 obtains the highest net work of 27.43 kW at the CO2 mass fraction 0.9 in the split cycle.
Analysis of Expected Climate Extreme Variability with Regional Climate Simulations over Napoli Capodichino Airport: A Contribution to a Climate Risk Assessment Framework
Authors: Bucchignani Edoardo , Zollo Alessandra Lucia , Montesarchio Myriam
Published: November 2021

In recent years, the scientific community has paid particular attention to the analysis of extreme events, such as heat waves, droughts, and intense rain events that have caused loss of human life and significant economic damage. Climate-related extremes generally produce large impact on infrastructures, especially on those with insufficient design, while some infrastructures may become inadequate under the effects of severe extremes. In the particular case of airports, the increase in frequency and severity of extreme weather events will worsen their deterioration rate. This work presents an analysis of the expected climate variability over Napoli Capodichino Airport, using climate projections generated by the Regional Climate Model COSMO-CLM. Simulations were performed over Italy, employing a spatial resolution of approximately 8 km. The time period simulated was 1979–2100, and, in particular, the CMIP5 historical experiment (based on historical greenhouse gas concentrations) was used for the period 1979–2005, while, for the period 2006–2100, two different simulations were performed, employing the Representative Concentration Pathways IPCC RCP4.5 and RCP8.5 greenhouse gas concentrations. The meteorological situations over the airport have been analyzed, along with the identification of conditions that could cause relevant impact on airport environment. In particular, extreme summer temperatures may exceed design standards, leading to heat damage to surfaces, while runways or aprons may have trouble due to the surface melting during peak heat periods. Long term changes in the directions of wind can adversely affect the usability of runways, while changes in wind shear could modify strength and frequency of clear-air turbulence. Analyses have been performed considering suitable Extreme Events Indicators (EWI), both on past trends and on numerical projections over future periods, with the aim of contributing to the definition of a risk assessment methodology based on the combination of the frequency and of the severity of meteorological hazards.
Useful Teaching Strategies in STEMM (Science, Technology, Engineering, Mathematics, and Medicine) Education during the COVID-19 Pandemic
Authors: Church Frank C. , Cooper Scott T. , Fortenberry Yolanda M. , Glasscock Laura N. , Hite Rebecca
Published: November 2021

The impacts of the COVID-19 pandemic throughout the world continue. These impacts influence many aspects of life, work, healthcare, and education in the U.S., which are drastically affected by the COVID-19 pandemic. Thus, a considerable challenge to tertiary-level education has been how to adapt our teaching styles and modalities to keep all stakeholders (students, faculty, teaching assistants, and staff) safe in lectures and labs. This viewpoint presents 15 teaching lessons and tips for undergraduate and graduate STEMM (Science, Technology, Engineering, Mathematics, and Medicine) education for face-to-face, hybrid, and distance learning. The goal was to describe teaching strategies that could be adaptable to most STEMM courses, independent of the classroom size, which is valuable for those educational settings capable of migrating from a classroom to either a hybrid or strictly online teaching environment. Although some of these teaching tips were straightforward, we believe collectively that they (1) provide safety and stability to the students and the instructors; (2) help to improve communications between faculty and students that the pandemic had strained; (3) strengthen student attention; (4) facilitate the transition from the classroom to online teaching; (5) enable the use of new technologies; and (6) offer teaching practices we imagined for educational scenarios post-SARS-CoV-2. Finally, we hope these teaching strategies offer valuable insight as we continue to navigate STEMM education during the ongoing COVID-19 pandemic.
Application of Lean Manufacturing Concepts to Evolving a Policy for Engineering Education
Authors: Céspedes-Mota Armando , Shenoy Dinesh , Cárdenas-Barrón Leopoldo Eduardo
Published: November 2021

This work analyzes the current situation of engineering education in India, especially technical universities characterized by low-quality infrastructure, inflexible curricula, and poor teaching resources including faculty, usually resulting in low student learning and very low graduate placement rates, and identifies the root causes of these problems, summarizes the methodologies adapted by previous researchers in the lean area, and applies the lean manufacturing philosophy to engineering education. This paper applies a value stream map to analyze the current state of engineering education. This technique identifies eight wastes and is given in form of a current state diagram. A future state diagram is presented that recommends solutions to eliminate these wastes. These recommendations make learning processes responsive to needs and provide long-lasting value to students. Overall, it is beneficial in developing a policy for engineering education.
Real-Time Application of Computer Graphics Improvement Techniques Using Hyperspectral Textures in a Virtual Reality System
Authors: Díaz-Barrancas Francisco , Cwierz Halina , Pardo Pedro J.
Published: November 2021

In virtual reality technology, it is necessary to develop improvements and apply new techniques that allow rapid progress and innovative development. Nowadays, virtual reality devices have not yet demonstrated the great potential they could develop in the future. One main reason for this is the lack of precision to represent three-dimensional scenarios with a similar solvency to what our visual system obtains from the real world. One of the main problems is the representation of images using the RGB color system. This digital colorimetry system has many limitations when it comes to representing faithful images. In this work we propose to develop a virtual reality environment incorporating hyperspectral textures into a virtual reality system. Based on these hyperspectral textures, the aim of our scientific contribution is to improve the fidelity of the chromatic representation, especially when the lighting conditions of the scenes and its precision are relevant. Therefore, we will present the steps followed to render three-dimensional objects with hyperspectral textures within a virtual reality scenario. Additionally, we will check the results obtained by applying such hyperspectral textures by calculating the chromaticity coordinates of known samples.
Cross-Modal Guidance Assisted Hierarchical Learning Based Siamese Network for MR Image Denoising
Authors: Naseem Rabia , Alaya Cheikh Faouzi , Beghdadi Azeddine , Muhammad Khan , Sajjad Muhammad
Published: November 2021

Cross-modal medical imaging techniques are predominantly being used in the clinical suite. The ensemble learning methods using cross-modal medical imaging adds reliability to several medical image analysis tasks. Motivated by the performance of deep learning in several medical imaging tasks, a deep learning-based denoising method Cross-Modality Guided Denoising Network CMGDNet for removing Rician noise in T1-weighted (T1-w) Magnetic Resonance Images (MRI) is proposed in this paper. CMGDNet uses a guidance image, which is a cross-modal (T2-w) image of better perceptual quality to guide the model in denoising its noisy T1-w counterpart. This cross-modal combination allows the network to exploit complementary information existing in both images and therefore improve the learning capability of the model. The proposed framework consists of two components: Paired Hierarchical Learning (PHL) module and Cross-Modal Assisted Reconstruction (CMAR) module. PHL module uses Siamese network to extract hierarchical features from dual images, which are then combined in a densely connected manner in the CMAR module to finally reconstruct the image. The impact of using registered guidance data is investigated in removing noise as well as retaining structural similarity with the original image. Several experiments were conducted on two publicly available brain imaging datasets available on the IXI database. The quantitative assessment using Peak Signal to noise ratio (PSNR), Structural Similarity Index (SSIM), and Feature Similarity Index (FSIM) demonstrates that the proposed method exhibits 4.7% and 2.3% gain (average), respectively, in SSIM and FSIM values compared to other state-of-the-art denoising methods that do not integrate cross-modal image information in removing various levels of noise.
Multi-Method Analysis of Medical Records and MRI Images for Early Diagnosis of Dementia and Alzheimer’s Disease Based on Deep Learning and Hybrid Methods
Authors: Mohammed Badiea Abdulkarem , Senan Ebrahim Mohammed , Rassem Taha H. , Makbol Nasrin M. , Alanazi Adwan Alownie , Al-Mekhlafi Zeyad Ghaleb , Almurayziq Tariq S. , Ghaleb Fuad A.
Published: November 2021

Dementia and Alzheimer’s disease are caused by neurodegeneration and poor communication between neurons in the brain. So far, no effective medications have been discovered for dementia and Alzheimer’s disease. Thus, early diagnosis is necessary to avoid the development of these diseases. In this study, efficient machine learning algorithms were assessed to evaluate the Open Access Series of Imaging Studies (OASIS) dataset for dementia diagnosis. Two CNN models (AlexNet and ResNet-50) and hybrid techniques between deep learning and machine learning (AlexNet+SVM and ResNet-50+SVM) were also evaluated for the diagnosis of Alzheimer’s disease. For the OASIS dataset, we balanced the dataset, replaced the missing values, and applied the t-Distributed Stochastic Neighbour Embedding algorithm (t-SNE) to represent the high-dimensional data in the low-dimensional space. All of the machine learning algorithms, namely, Support Vector Machine (SVM), Decision Tree, Random Forest and K Nearest Neighbours (KNN), achieved high performance for diagnosing dementia. The random forest algorithm achieved an overall accuracy of 94% and precision, recall and F1 scores of 93%, 98% and 96%, respectively. The second dataset, the MRI image dataset, was evaluated by AlexNet and ResNet-50 models and AlexNet+SVM and ResNet-50+SVM hybrid techniques. All models achieved high performance, but the performance of the hybrid methods between deep learning and machine learning was better than that of the deep learning models. The AlexNet+SVM hybrid model achieved accuracy, sensitivity, specificity and AUC scores of 94.8%, 93%, 97.75% and 99.70%, respectively.
Random Forest Similarity Maps: A Scalable Visual Representation for Global and Local Interpretation
Authors: Mazumdar Dipankar , Neto Mário Popolin , Paulovich Fernando V.
Published: November 2021

Machine Learning prediction algorithms have made significant contributions in today’s world, leading to increased usage in various domains. However, as ML algorithms surge, the need for transparent and interpretable models becomes essential. Visual representations have shown to be instrumental in addressing such an issue, allowing users to grasp models’ inner workings. Despite their popularity, visualization techniques still present visual scalability limitations, mainly when applied to analyze popular and complex models, such as Random Forests (RF). In this work, we propose Random Forest Similarity Map (RFMap), a scalable interactive visual analytics tool designed to analyze RF ensemble models. RFMap focuses on explaining the inner working mechanism of models through different views describing individual data instance predictions, providing an overview of the entire forest of trees, and highlighting instance input feature values. The interactive nature of RFMap allows users to visually interpret model errors and decisions, establishing the necessary confidence and user trust in RF models and improving performance.
A Hybrid Methodology Based on Smart Management Energy Consumption in Irrigation Systems
Authors: Scarlatache Florina , Grigoras Gheorghe , Scarlatache Vlad-Andrei , Neagu Bogdan-Constantin , Ivanov Ovidiu
Published: November 2021

Innovative practices in irrigation systems can bring improvements in terms of economic efficiency and, at the same time, can reduce environmental impacts. Investment in high-tech technologies frequently involves additional costs, but an efficient water management system can increase the lifetime of the equipment. The most utilized electronic device for a smart management, used to pump units from irrigation systems, is the frequency converter. This device can regulate the speed of the motors that control the pumps according to the consumption of water, ensuring that it does not pump more water than is needed. This paper develops a new operating algorithm that ensures the operation of the pumping group at safe operating intervals and identifies the equivalent pump operating points for the entire flow range and pumping height of the pumping group in order to bring smart management to irrigation systems. The parameters monitored and collected for each vertical pump refers to the voltage, current, frequency (speeds) and flow of each hydraulic operating mode. The methodology used is based on the principle of creating an expert system to optimize energy consumption in the pumping groups. The proposed methodology was tested on an irrigation system that includes a pumping group with five pumps, showing its effectiveness in obtaining the optimal solution with a relatively low computational burden and without the violation of any system constraints under any operating conditions.
Comparing Three Countries’ Higher Education Students’ Cyber Related Perceptions and Behaviours during COVID-19
Authors: Tick Andrea , Cranfield Desireé J. , Venter Isabella M. , Renaud Karen V. , Blignaut Rénette J.
Published: November 2021

In 2020, a global pandemic led to lockdowns, and subsequent social and business restrictions. These required overnight implementation of emergency measures to permit continued functioning of vital industries. Digital technologies and platforms made this switch feasible, but it also introduced several cyber related vulnerabilities, which students might not have known how to mitigate. For this study, the Global Cyber Security Index and the Cyber Risk literacy and education index were used to provide a cyber security context for each country. This research project—an international, cross-university, comparative, quantitative project—aimed to explore the risk attitudes and concerns, as well as protective behaviours adopted by, students at a South African, a Welsh and a Hungarian University, during the pandemic. This study’s findings align with the relative rankings of the Oliver Wyman Risk Literacy and Education Index for the countries in which the universities reside. This study revealed significant differences between the student behaviours of students within these universities. The most important differences were identified between students’ risk attitudes and concerns. It was also discovered that South African students reported having changed their protective online behaviours to the greatest extent, since the pandemic commenced. Recommendations are made suggesting that cyber security training and education, as well as improving the digital trust and confidence in digital platforms, are critical.
Imbalanced Mach-Zehnder Modulator for Fading Suppression in Dispersion-Uncompensated Direct Detection System
Authors: Zhu Yixiao , Miao Xin , Wu Qi , Yin Longjie , Hu Weisheng
Published: November 2021

In this work, we systematically analyze the impact of three kinds of Mach-Zehnder modulator (MZM) imbalances, including bias deviation, amplitude mismatch, and differential time skew in intensity-modulation direct-detection (IM-DD) links. It is shown that, for power fading limited transmission, the imbalances can be utilized as advantages rather than impairments. Specifically, the bias deviation with single-arm driven mode and amplitude mismatch with differential driven mode can increase the available bandwidth by shifting the frequency of fading notches. Meanwhile, time skew provides another way to avoid fading by shaping the double sideband (DSB) signal into a vestigial sideband (VSB) with an asymmetrical transfer function. In the transmission experiment, 34 Gbaud Nyquist 6/8-ary pulse amplitude modulation (PAM-6/8) signals are used for investigation in a 20 km dispersion-uncompensated standard single-mode fiber (SSMF) link. With the help of a Volterra nonlinear equalizer, all three kinds of imbalances can achieve bit-error rates (BERs) below the 7% and 20% hard-decision forward error correction (HD-FEC) thresholds for PAM-6 and PAM-8 signals, respectively. The received power sensitivity is also compared at the back-to-back (BTB) case and after fiber transmission. Both numerical simulation and experimental demonstration confirm that the dispersion-induced power fading can be effectively suppressed with bias, amplitude, or skew imbalance, providing a feasible solution for transmission distance extension of C-band DD links.
Energy, Environmental, and Economic Analyses of a District Heating (DH) Network from Both Thermal Plant and End-Users’ Prospective: An Italian Case Study
Authors: Corradi Erica , Rossi Mosè , Mugnini Alice , Nadeem Anam , Comodi Gabriele , Arteconi Alessia , Salvi Danilo
Published: November 2021

District heating (DH) is an alternative technology to Individual Heating (IH) for satisfying end-user’s needs. This paper assesses the competitiveness of a DH network in the center of Italy from energy, environmental, and economic points of view considering both thermal power plant and end-users’ sides. On the thermal power plant side, the energy analysis considers the Primary Energy Saving (PES) and the specific energy (Esp) of the fuel actually exploited in the thermal power plant compared to its Low Heating Value (LHV), while the environmental analysis considers the avoided CO2 and the economic analysis considers the Energy Efficiency Certificates (EECs). Results showed that the current thermal power plant configuration with two boilers and a Combined Heat and Power (CHP) unit reaches a yearly PES of 21.3% as well as 1099 tCO2 avoided. From the economic analysis of the thermal power plant side, 829 EECs with an economic return of 207,222€ are obtained, while from the end-users’ side the DH network is cheaper than IH in 84.7% of the cases. Further technologies are also studied to enhance the CHP unit flexibility.
Automatic Detection of Subsidence Troughs in SAR Interferograms Using Mathematical Morphology
Authors: Dwornik Maciej , Porzycka-Strzelczyk Stanisława , Strzelczyk Jacek , Malik Hubert , Murdzek Radosław , Franczyk Anna , Bała Justyna
Published: November 2021

In this paper, an automatic algorithm for the detection of subsidence areas in SAR interferograms is proposed. It is based on the analysis of spatial distribution of the interferogram phase, and its coherence and entropy. The developed method was tested for differential interferograms generated on the basis of Sentinel-1 SAR images covering mining areas in South Poland. The obtained results were compared with those achieved using a method based on circular Gabor filters. Performed analysis revealed that the detection rate for the proposed method varied from 34% to 83%. It is an improved method based on Gabor filters that achieved a detection rate from 30% to 53%.
Heat Flux Based Optimization of Combined Heat and Power Thermoelectric Heat Exchanger
Authors: Yazawa Kazuaki , Shakouri Ali
Published: November 2021

We analyzed the potential of thermoelectrics for electricity generation in a combined heat and power (CHP) waste heat recovery system. The state-of-the-art organic Rankine cycle CHP system provides hot water and space heating while electricity is also generated with an efficiency of up to 12% at the MW scale. Thermoelectrics, in contrast, will serve smaller and distributed systems. Considering the limited heat flux from the waste heat source, we investigated a counterflow heat exchanger with an integrated thermoelectric module for maximum power, high efficiency, or low cost. Irreversible thermal resistances connected to the thermoelectric legs determine the energy conversion performance. The exit temperatures of fluids through the heat exchanger are important for the system efficiency to match the applications. Based on the analytic model for the thermoelectric integrated subsystem, the design for maximum power output with a given heat flux requires thermoelectric legs 40–70% longer than the case of fixed temperature reservoir boundary conditions. With existing thermoelectric materials, 300–400 W/m2 electrical energy can be generated at a material cost of $3–4 per watt. The prospects of improvements in thermoelectric materials were also studied. While the combined system efficiency is nearly 100%, the balance between the hot and cold flow rates needs to be adjusted for the heat recovery applications.
Single-Track Bike Trails in the Moravian Karst as Part of Forest Recreation
Authors: Hrůza Petr , Pelikán Petr , Olišarová Lucie
Published: November 2021

Recently, cycling has become a popular recreation activity, and mountain biking provides an experience that is sought by an increasing number of people. Bike trails constructed for mountain bikers in access areas lead mostly through the forest and provide not only an extraordinary riding experience but the opportunity to admire the surrounding nature. The reason for constructing such trails from a landowner’s point of view is to help keep bikers’ movements within a defined access area and to ensure adjacent areas are left free for other forest functions. It also helps distribute groups of visitors with other interests to other parts of the forest. This is what we call “controlled recreation”. In this example, it means that if cyclists come to the locality to use the bike trails, they should ride only along the designated trails; however, they may leave these trails and ride on the surrounding land. This article studied the movements of bikers in an accessible area of the Moravian Karst and the regulation of their movements by controlled recreation. Attendance in the area was measured using automatic counters. These were placed at the entry points to the accessible area and just behind the routes where the trails branch off. The results showed that bikers mostly stayed on the formal routes and that the trails were effective, i.e., there was no uncontrolled movement of bikers into the surrounding forest stands. We also noted the time of day that cyclists were active. These results can be used to better plan work in the forest, for example, harvesting and logging. To further the suitable development of accessible areas of the forest, we also compared the usual size of trail areas in two other European countries and the increasing width of bike trails due to the transverse slope of the terrain.
Evaluation of Fermented Extracts of Aloe vera Processing Byproducts as Potential Functional Ingredients
Authors: Lee Seong-Hun , Eun Chang-Ho , Kwon Yong-Seong , Baek Jin-Hong , Kim In-Jung
Published: November 2021

Aloe is widely used as a cosmetic and medicinal plant. Numerous studies have reported that aloe gel extract has antioxidant, anticancer, antidiabetic, immunity, and skin antiaging properties. However, few studies have investigated the properties of fermentation products of aloe processing byproducts. Aloe stalks and leaves remain as byproducts after the aloe beverage manufacturing process. This study evaluated whether fermentation products of blender and press extracts of aloe processing byproducts (BF and PF, respectively) that remain after beverage manufacturing were useful as functional biomaterial by investigating their effects on adipocyte differentiation, hyaluronic acid (HA) production, tyrosinase activity, and antioxidant activity. Co-fermentation of G. xylinus and S. cerevisiae was conducted for fermentation of aloe processing byproducts. The BF and PF products did not induce observable cytotoxicity effects. However, BF and PF products did inhibit a 3T3-L1 adipocyte differentiation compared with control, with the BF product displaying greater inhibition of 3T3-L1 adipocyte differentiation than the PF product. HA production increased in HaCaT cell cultures as the concentration of the MF product increased, as compared with the untreated control. The levels of tyrosinase inhibition, 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, and superoxide dismutase (SOD)-like activity also depended on the MF product concentration. This study indicates that the fermented products of aloe processing byproducts have biological potential for applications in the manufacturing of cosmetics, pharmaceuticals, and beverages. These laboratory bench results provide the foundation for future studies of scaling and practical applications at the industrial level.
Bioleaching of Sorghum Straw in Bioreactors for Biomass Cleaning
Authors: Zhang Ning , Walker Terry , Jenkins Bryan , Anderson Stanley , Zheng Yi
Published: November 2021

Pretreatments are often needed for lignocellulosic biomass feedstocks before either thermochemical or biochemical conversion processes. Our previous research has demonstrated the potential of bioleaching, with its superior capability of removing certain inorganic compounds compared to water leaching, to improve biomass quality for thermochemical conversion in biofuel production. In this study, the bioleaching process was scaled up from 250 mL beakers to be carried out in custom-designed 2.5 L bioreactors. The fungus Aspergillus niger was used in the bioreactors for leaching sorghum straw biomass with an initial ash content of 6.0%. The effects of three operating parameters on leaching efficiency (i.e., residual ash content) were extensively studied, including the fungal mass added to each reactor, leaching time, and glucose concentration in the starting liquid phase. Response surface methodology (RSM) was used for the experiment design. The results showed that the average residual ash content of the sorghum feedstock after bioleaching was significantly lower (3.63 ± 0.19%) than that of the ash content (4.72 ± 0.13%) after water leaching (p < 0.00001). Among the three parameters, glucose concentration in the starting liquid phase had the most significant effect on leaching effectiveness (p = 0.0079). Based on this outcome, subsequent bioleaching experiments yielded reductions in residual ash content to as low as 2.73%.
Selection of Bacteriocinogenic Bacillus spp. from Traditional Fermented Korean Food Products with Additional Beneficial Properties
Authors: Choi Gee Hyeun , Fugaban Joanna Ivy Irorita , Dioso Clarizza May , Vazquez Bucheli Jorge Enrique , Holzapfel Wilhelm Heinrich , Todorov Svetoslav Dimitrov
Published: November 2021

Two Bacillus spp. isolated from kimchi, Bacillus tequilensis ST816CD and Bacillus subtilis ST830CD, were characterized for their antimicrobial properties and safety. The proteinaceous nature of their inhibitory metabolites was confirmed after exposure to proteolytic enzymes, resulting in partial loss of the antimicrobial effect. This indicated that different non-proteinaceous antimicrobial substances may also be produced by these strains. This hypothesis was later confirmed when genes associated with the production of surfactants were detected in their DNA. The expressed antimicrobial metabolites were not affected by treatment at different temperatures and pH levels, including exposure to selected chemicals. Their strong adherence to susceptible pathogens was not significantly affected by different temperatures, chemicals, or pH values. Both Bacillus strains showed inhibitory activity against clinical and food-associated pathogens, including Listeria monocytogenes ATCC 15313, and some Staphylococcus species. Several genes associated with the production of antimicrobial metabolites were detected, but key virulence and beneficial genes were not present in these strains. Even though only B. tequilensis ST816CD displayed γ-hemolysin production, both selected strains were found to produce gelatinase and biogenic amines, which are considered as either potential virulence- or health-related factors. Moreover, the strains were susceptible to a variety of antibiotics except for the penicillin G [1 IU/disc] resistance of B. tequilensis ST816CD. Both strains showed proteolytic activity. Additionally, both strains showed low hydrophobicity based on bacterial adherence measured by hydrocarbons (n-hexadecane).
Detection of Hidden Communities in Twitter Discussions of Varying Volumes
Authors: Blekanov Ivan , Bodrunova Svetlana S. , Akhmetov Askar
Published: November 2021

The community-based structure of communication on social networking sites has long been a focus of scholarly attention. However, the problem of discovery and description of hidden communities, including defining the proper level of user aggregation, remains an important problem not yet resolved. Studies of online communities have clear social implications, as they allow for assessment of preference-based user grouping and the detection of socially hazardous groups. The aim of this study is to comparatively assess the algorithms that effectively analyze large user networks and extract hidden user communities from them. The results we have obtained show the most suitable algorithms for Twitter datasets of different volumes (dozen thousands, hundred thousands, and millions of tweets). We show that the Infomap and Leiden algorithms provide for the best results overall, and we advise testing a combination of these algorithms for detecting discursive communities based on user traits or views. We also show that the generalized K-means algorithm does not apply to big datasets, while a range of other algorithms tend to prioritize the detection of just one big community instead of many that would mirror the reality better. For isolating overlapping communities, the GANXiS algorithm should be used, while OSLOM is not advised.
Bitter Gourd Honey Ameliorates Hepatic and Renal Diabetic Complications on Type 2 Diabetes Rat Models by Antioxidant, Anti-Inflammatory, and Anti-Apoptotic Mechanisms
Authors: Arigela Chandra Sekhar , Nelli Giribabu , Gan Siew Hua , Sirajudeen Kuttulebbai Nainamohamed Salam , Krishnan Kumarathevan , Abdul Rahman Nurhanan , Pasupuleti Visweswara Rao
Published: November 2021

Honey has several pharmacological effects, including anti-diabetic activity. However, the effectiveness of bitter gourd honey (BGH) in the treatment of diabetes mellitus (DM) is unknown. The aim of this study was to determine the antioxidant, anti-inflammatory, and anti-apoptotic properties of BGH on the kidney and liver of a streptozotocin-induced diabetes rat model. Methods: A single dose (nicotinamide 110 mg/kg, streptozotocin (STZ) 55 mg/kg, intraperitoneal (i.p.)) was used to induce DM in male rats. For 28 days, normal or diabetic rats were administered 1 g/kg/day and 2 g/kg/day of BGH orally. After the treatment, blood, liver, and kidney samples were collected and analysed for biochemical, histological, and molecular parameters. In addition, liquid chromatography–mass spectrometry (LC-MS) was used to identify the major bioactive components in BGH. Results: The administration of BGH to diabetic rats resulted in significant reductions in alanine transaminase (ALT),aspartate aminotransferase (AST), creatinine, and urea levels. Diabetic rats treated with BGH showed lesser pathophysiological alterations in the liver and kidney as compared to non-treated control rats. BGH-treated diabetic rats exhibited reduced levels of oxidative stress (MDA levels), inflammatory (MYD88, NFKB, p-NFKB, IKKβ), and apoptotic (caspase-3) markers, as well as higher levels of antioxidant enzymes (SOD, CAT, and GPx) in the liver and kidney. BGH contains many bioactive compounds that may have antioxidative stress, anti-inflammatory, and anti-apoptotic effects. Conclusion: BGH protected the liver and kidney in diabetic rats by reducing oxidative stress, inflammation, and apoptosis-induced damage. As a result, BGH can be used as a potential therapy to ameliorate diabetic complications.
Consumer Preferences and Willingness to Pay for Mud Crabs in Southeast Asian Countries: A Discrete Choice Experiment
Authors: Sayeed Zubayer , Sugino Hiroaki , Sakai Yutaro , Yagi Nobuyuki
Published: November 2021

The mud crab (Scylla serrata) is an economically important species found in the mangroves and estuaries of tropical countries and is a popular seafood product in the coastal areas of Southeast Asian markets. The aim of this study is to identify factors affecting consumer preference of mud crabs, and to understand consumers’ willingness to pay (WTP) for these factors in a Singapore market where imported mud crabs from other Asian countries are sold. The results showed that the country of origin matters to participants, affecting purchasing decisions, and consumers were willing to pay approximately 16.48 SGD (11.49 USD, the average price of four shops: 35.55 USD/kg for one mud crab) more if the mud crabs were from Sri Lanka if compared with Indonesian or Cambodian mud crabs. Moreover, consumers were willing to pay 25.08 SGD (17.48 USD) more if the mud crabs were alive and 13.40 SGD (9.34 USD) less if the mud crabs were frozen compared with fresh, but not alive, mud crabs. Furthermore, consumers’ preference in mud crab was associated with the consumers’ religion. Some groups of consumers preferred female mud crabs with eggs over male mud crabs, while other groups preferred male crabs. The results identified diverse consumer preference of mud crabs and, therefore, could provide new insights that are useful for sustainable consumption of mud crabs in the region.