bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Injury Patterns between Electric Bicycle, Bicycle and Motorcycle Accidents
Authors: Spörri Emilian , Halvachizadeh Sascha , Gamble Jamison G. , Berk Till , Allemann Florin , Pape Hans-Christoph , Rauer Thomas
Published: July 2021

Background: Electric bicycles (E-bikes) are an increasingly popular means of transport, and have been designed for a higher speed comparable to that of small motorcycles. Accident statistics show that E-bikes are increasingly involved in traffic accidents. To test the hypothesis of whether accidents involving E-bikes bear more resemblance to motorcycle accidents than conventional bicyclists, this study evaluates the injury pattern and severity of E-bike injuries in direct comparison to injuries involving motorcycle and bicycle accidents. Methods: In this retrospective cohort study, the data of 1796 patients who were treated at a Level I Trauma Center between 2009 and 2018 due to traffic accident, involving bicycles, E-bikes or motorcycles, were evaluated and compared with regard to injury patterns and injury severity. Accident victims treated as inpatients at least 16 years of age or older were included in this study. Pillion passengers and outpatients were excluded. Results: The following distribution was found in the individual groups: 67 E-bike, 1141 bicycle and 588 motorcycle accidents. The injury pattern of E-bikers resembled that of bicyclists much more than that of motorcyclists. The patients with E-bike accidents were almost 14 years older and had a higher incidence of moderate traumatic brain injuries than patients with bicycle accidents, in spite of the fact that E-bike riders were nearly twice as likely to wear a helmet as compared to bicycle riders. The rate of pelvic injuries in E-bike accidents was twice as high compared with bicycle accidents, whereas the rate of upper extremity injuries was higher following bicycle accidents. Conclusion: The overall E-bike injury pattern is similar to that of cyclists. The differences in the injury pattern to motorcycle accidents could be due to the higher speeds at the time of the accident, the different protection and vehicle architecture. What is striking, however, is the higher age and the increased craniocerebral trauma of the E-bikers involved in accidents compared to the cyclists. We speculate that older and untrained people who have a slower reaction time and less control over the E-bike could benefit from head protection or practical courses similar to motorcyclists.
Correlation between the Level of Social Distancing and Activity of Influenza Epidemic or COVID-19 Pandemic: A Subway Use-Based Assessment
Authors: Seong Hye , Hong Jin-Wook , Hyun Hak-Jun , Yoon Jin-Gu , Noh Ji-Yun , Cheong Hee-Jin , Kim Woo-Joo , Jung Jae-Hun , Song Joon-Young
Published: July 2021

Social distancing is an effective measure to mitigate the spread of novel viral infections in the absence of antiviral agents and insufficient vaccine supplies. Subway utilization density may reflect social activity and the degree of social distancing in the general population.; This study aimed to evaluate the correlations between subway use density and the activity of the influenza epidemic or coronavirus disease 2019 (COVID-19) pandemic using a time-series regression method. The subway use-based social distancing score (S-SDS) was calculated using the weekly ridership of 11 major subway stations. The temporal association of S-SDS with influenza-like illness (ILI) rates or the COVID-19 pandemic activity was analyzed using structural vector autoregressive modeling and the Granger causality (GC) test. During three influenza seasons (2017–2020), the time-series regression presented a significant causality from S-SDS to ILI (p = 0.0484). During the COVID-19 pandemic in January 2020, S-SDS had been suppressed at a level similar to or below the average of the previous four years. In contrast to the ILI rate, there was a negative correlation between COVID-19 activity and S-SDS. GC analysis revealed a negative causal relationship between COVID-19 and S-SDS (p = 0.0098).; S-SDS showed a significant time-series association with the ILI rate but not with COVID-19 activity. When public transportation use is sufficiently suppressed, additional social mobility restrictions are unlikely to significantly affect COVID-19 pandemic activity. It would be more important to strengthen universal mask-wearing and detailed public health measures focused on risk activities, particularly in enclosed spaces.
Functional Translation of Exercise Responses from Exercise Testing to Exercise Training: The Test of a Model
Authors: Tyrrell Tristan , Pavlock Jessica , Bramwell Susan , Cortis Cristina , Doberstein Scott T. , Fusco Andrea , Porcari John P. , Foster Carl
Published: July 2021

Exercise prescription based on exercise test results is complicated by the need to downregulate the absolute training intensity to account for cardiovascular drift in order to achieve a desired internal training load. We tested a recently developed generalized model to perform this downregulation using metabolic equivalents (METs) during exercise testing and training. A total of 20 healthy volunteers performed an exercise test to define the METs at 60, 70, and 80% of the heart rate (HR) reserve and then performed randomly ordered 30 min training bouts at absolute intensities predicted by the model to achieve these levels of training intensity. The training HR at 60 and 70% HR reserve, but not 80%, was significantly less than predicted from the exercise test, although the differences were small. None of the ratings of perceived exertion (RPE) values during training were significantly different than predicted. There was a strong overall correlation between predicted and observed HR (r = 0.88) and RPE (r = 0.52), with 92% of HR values within ±10 bpm and 74% of RPE values within ±1 au. We conclude that the generalized functional translation model is generally adequate to allow the generation of early absolute training loads that lead to desired internal training loads.
A Robust Document Identification Framework through f-BP Fingerprint
Authors: Guarnera Francesco , Giudice Oliver , Allegra Dario , Stanco Filippo , Battiato Sebastiano , Livatino Salvatore , Matranga Vito , Salici Angelo
Published: July 2021

The identification of printed materials is a critical and challenging issue for security purposes, especially when it comes to documents such as banknotes, tickets, or rare collectable cards: eligible targets for ad hoc forgery. State-of-the-art methods require expensive and specific industrial equipment, while a low-cost, fast, and reliable solution for document identification is increasingly needed in many contexts. This paper presents a method to generate a robust fingerprint, by the extraction of translucent patterns from paper sheets, and exploiting the peculiarities of binary pattern descriptors. A final descriptor is generated by employing a block-based solution followed by principal component analysis (PCA), to reduce the overall data to be processed. To validate the robustness of the proposed method, a novel dataset was created and recognition tests were performed under both ideal and noisy conditions.
Understanding the Role of Trichoderma reesei Vib1 in Gene Expression during Cellulose Degradation
Authors: Chen Xiuzhen , Song Bingran , Liu Minglu , Qin Lina , Dong Zhiyang
Published: July 2021

Vib1, a member of the Ndt80/PhoG-like transcription factor family, has been shown to be essential for cellulase production of Trichoderma reesei. Here, we combined transcriptomic and genetic analyses to gain mechanistic insights into the roles of Vib1 during cellulose degradation. Our transcriptome analysis showed that the vib1 deletion caused 586 genes with decreased expression and 431 genes with increased expression on cellulose. The downregulated genes were enriched for Gene Ontology terms associated with carbohydrate metabolism, transmembrane transport, oxidoreductase activity, and transcription factor activity. Of the 258 genes induced by cellulose, 229 showed no or decreased expression in Δvib1 on cellulose, including almost all (hemi)cellulase genes, crucial sugar transporter genes (IDs:69957, 3405), and the genes encoding main transcriptional activators Xyr1 and Ace3. Additionally, Vib1 also regulated the expression of genes involved in secondary metabolism. Further comparison of the transcriptomes of Δvib1 and Δxyr1 in cellulose revealed that the genes regulated by Vib1 had much overlap with Xyr1 targets especially for the gene set induced by cellulose, presumably whose expression requires the cooperativity between Vib1 and Xyr1. Genetic evidence indicated that Vib1 regulates cellulase gene expression partially via Xyr1. Our results will provide new clues for strain improvement.
Connecting the Dots: Interplay of Pathogenic Mechanisms between COVID-19 Disease and Mucormycosis
Authors: Prakash Hariprasath , Skiada Anna , Paul Raees Ahmad , Chakrabarti Arunaloke , Rudramurthy Shivaprakash Mandya
Published: July 2021

Coronavirus disease (COVID-19)-associated mucormycosis (CAM) is an emerging threat globally, especially in India. More than 40,000 CAM cases have been reported in India. The emergence of CAM cases in India has been attributed to environmental, host, and iatrogenic factors. Mucorales spore burden has been reported globally; however, their presence is higher in tropical countries such as India, contributing to the emergence of CAM. Before the COVID-19 pandemic, patients with diabetes mellitus, haematological malignancies, solid organ transplants, corticosteroid therapy and neutropenia were more prone to mucormycosis, whereas in COVID-19 patients, virus-induced endothelial dysfunction, hyperglycaemia, and immune dysfunction following corticosteroid use increase the risk of acquiring mucormycosis. The interaction of Mucorales spores with the epithelial cells, followed by endothelial invasion, is a crucial step in the pathogenesis of mucormycosis. Endothelial damage and increased endothelial receptor expression induced by COVID-19 infection may predispose patients to CAM. COVID-19 infection may directly induce hyperglycaemia by damaging beta cells of the pancreas or by corticosteroid therapy, which may contribute to CAM pathogenesis. Iron acquisition from the host, especially in diabetic ketoacidosis (DKA) or deferoxamine therapy, is an important virulence trait of Mucorales. Similarly, the hyperferritinaemia caused by COVID-19 may act as a source of iron for Mucorales growth and invasion. In addition, corticosteroid treatment reduces or abolishes the innate immune functions of phagocytic cells contributing to the pathogenesis of CAM. This review aims to discuss primarily the host and iatrogenic factors shared between COVID-19 and mucormycosis that could explain the emergence of CAM.
Tourism, Water Pollution, and Waterway Landscape Changes in a Traditional Village in the Huizhou Region, China
Authors: Chen Pinyu , Zhao Yizheng , Zuo Di , Kong Xiang
Published: July 2021

Based on archival research, non-participatory observation, and semi-structured interviews, this paper examined waterway landscape changes mainly caused by tourism development in Hongcun, a traditional village in the Huizhou region, China, and how the locals have responded to water pollution in order to achieve landscape sustainability. It is found that the physical structure of the waterways of Hongcun Village has been well preserved, but the water pollution caused by tourism, with a combination of changes of land use and demographic structure, has changed the functions and cultural meanings of waterways. Although there remains quite a daunting task towards sustainability in terms of technology, heritage protection, and desire for development, we claim the waterways environmental governance in which local governments play a crucial role in resilience strategies by controlling the sewage from homestays, restaurants, and pigment sewage from sketches. However, the ways in which landscape animates, including the daily lives, processual daily practices, and mundane activities of different social actors related to waterways, deserve further implementation to build the resilience of cultural landscape from the perspective of non-representational theory. This paper adds to a new narrative to the waterway landscape research by presenting a water utilization pattern that could profitably coexist with a specific environment in the Huizhou region in the agricultural society of ancient China and discussing how the non-representational theory contributes to analyzing and managing waterway landscapes in modern times. It also sheds light on the connection between cultural landscape and resilience.
Psycho-Social Constraints on Naturalistic Adult Second Language Acquisition
Authors: Al-Kendi Azza , Khattab Ghada
Published: July 2021

The following study investigated a rare case of adult immersion in a second language context without prior exposure to the language. It aimed to investigate whether Length of Residence (LoR) acts as a strong index of L2 speech performance when coupled with daily exposure and interaction with first language speakers. Twenty-two females from Africa and Asia who worked as Foreign Domestic Helpers (FDH) in Omani homes and with varying LoRs performed an AX discrimination and a production task which tapped into Omani consonants and clusters that are absent from their L1s; their accent was also rated by L1 Omani listeners. Results showed a surprising lack of significance of LoR on all the production and perception measures examined. Discrimination results showed a low sensitivity to Arabic consonantal contrasts that are lacking in the L1 across all participants, and a small positive effect of L1 literacy. Production results exhibited low accuracy on all Arabic consonants and a marked foreign accent as judged by L1 listeners, with a small positive effect of L2 literacy. We argue that the nature of the interactions between FDH and employers, along with uneven power relations and social distance, counteract any advantage of LoR and the immersion setting examined here.
Assessment of the Impact of Clothing Structures for Premature Babies on Biophysical Properties
Authors: Skrzetuska Ewa , Puszkarz Adam K. , Pycio Zofia , Krucińska Izabella
Published: July 2021

This article presents research on ergonomics and physiological comfort of protective clothing. Biophysical properties of selected three-layer textile assemblies that differ in geometry and raw material composition for the production of types of mummy sleeping bags for premature babies were investigated. The tests included measurements of air permeability, thermal resistance and water vapor resistance (both by means of human skin model), thermal insulation, and water vapor resistance (both using newborn manikin). Experimental research was supplemented by modeling the thermal insulation of the assemblies by designing their 3D models using selected CAD software and applying the finite volume method. The obtained results allowed the evaluation of the influence of different geometry and the raw material composition of the proposed assemblies on the performance parameters of protective clothing.
First Screen-Printed Sensor (Electrochemically Activated Screen-Printed Boron-Doped Diamond Electrode) for Quantitative Determination of Rifampicin by Adsorptive Stripping Voltammetry
Authors: Kozak Jędrzej , Tyszczuk-Rotko Katarzyna , Wójciak Magdalena , Sowa Ireneusz , Rotko Marek
Published: July 2021

In this paper, a screen-printed boron-doped electrode (aSPBDDE) was subjected to electrochemical activation by cyclic voltammetry (CV) in 0.1 M NaOH and the response to rifampicin (RIF) oxidation was used as a testing probe. Changes in surface morphology and electrochemical behaviour of RIF before and after the electrochemical activation of SPBDDE were studied by scanning electron microscopy (SEM), CV and electrochemical impedance spectroscopy (EIS). The increase in number and size of pores in the modifier layer and reduction of charge transfer residence were likely responsible for electrochemical improvement of the analytical signal from RIF at the SPBDDE. Quantitative analysis of RIF by using differential pulse adsorptive stripping voltammetry in 0.1 mol L−1 solution of PBS of pH 3.0 ± 0.1 at the aSPBDDE was carried out. Using optimized conditions (Eacc of −0.45 V, tacc of 120 s, ΔEA of 150 mV, ν of 100 mV s−1 and tm of 5 ms), the RIF peak current increased linearly with the concentration in the four ranges: 0.002–0.02, 0.02–0.2, 0.2–2.0, and 2.0–20.0 nM. The limits of detection and quantification were calculated at 0.22 and 0.73 pM. The aSPBDDE showed satisfactory repeatability, reproducibility, and selectivity towards potential interferences. The applicability of the aSPBDDE for control analysis of RIF was demonstrated using river water samples and certified reference material of bovine urine.
Influence of Ground Calcium Carbonate Waste on the Properties of Green Self-Consolidating Concrete Prepared by Low-Quality Bagasse Ash and Rice Husk Ash
Authors: Lertwattanaruk Pusit , Makul Natt
Published: July 2021

Bagasse ash (BA) and rice husk ash (RHA) are by-products from electricity power plants. Ground calcium carbonate waste (GCW) is the by-product of the mining of calcium carbonate (CaCO3) in the color pigment manufacturing industry. Both BA and RHA are classified as low-quality pozzolanic materials, differing from GCW, which contains a high calcium oxide (CaO) content that leads to products equivalent to the hydration reaction. Therefore, GCW is likely able to improve the properties of self-consolidating concrete (SCC) incorporating BA and RHA. This paper discusses the production of green self-consolidating concrete (gSCC) and identifies the benefit of using GCW in gSCC prepared by triple combined GCW (10 and 20 wt%), BA (10, 20, and 30 wt%), and RHA (20 wt%). The results indicate that the majority of the gSCC retain acceptable flowability. The differences in the levels of gSCC substitution and the V-funnel flow results show general correlations with the increase in GCW. The gSCC prepared by 10 wt% GCW associated with 10 wt% BA and 20 wt% RHA was improved significantly. The filling and passing abilities of the gSCC were improved by using GCW. In addition, gSCC achieved mechanical property development and was able to minimize the consumption of OPC by up to 40%.
Interfacial Crystallization and Supramolecular Self-Assembly of Spider Silk Inspired Protein at the Water-Air Interface
Authors: Mohammadi Pezhman , Zemke Fabian , Wagermaier Wolfgang , Linder Markus B.
Published: July 2021

Macromolecular assembly into complex morphologies and architectural shapes is an area of fundamental research and technological innovation. In this work, we investigate the self-assembly process of recombinantly produced protein inspired by spider silk (spidroin). To elucidate the first steps of the assembly process, we examined highly concentrated and viscous pendant droplets of this protein in air. We show how the protein self-assembles and crystallizes at the water–air interface into a relatively thick and highly elastic skin. Using time-resolved in situ synchrotron x-ray scattering measurements during the drying process, we showed that the skin evolved to contain a high β-sheet amount over time. We also found that β-sheet formation strongly depended on protein concentration and relative humidity. These had a strong influence not only on the amount, but also on the ordering of these structures during the β-sheet formation process. We also showed how the skin around pendant droplets can serve as a reservoir for attaining liquid–liquid phase separation and coacervation from the dilute protein solution. Essentially, this study shows a new assembly route which could be optimized for the synthesis of new materials from a dilute protein solution and determine the properties of the final products.
Target Search Algorithm for AUV Based on Real-Time Perception Maps in Unknown Environment
Authors: Li Juan , Zhai Xiaoliang , Xu Jian , Li Chengyue
Published: July 2021

For the problem of AUV target searches in unknown underwater environments, a target search algorithm for AUVs based on a real-time perception map is proposed. Real-time perception maps, including target existence probability maps, uncertainty maps, and pheromone maps and their updating rules, are established. Attraction source maps and search status maps based on the environmental information detected by the AUV are established. The maps are used for the AUV to search for corner areas that are unknown to a high degree and areas with low coverage around the current location. At the same time, a release mechanism for attraction and revisiting pheromones is established by combining a neural excitation network algorithm to make the gradient spread in the pheromone grid map. By setting up a search revenue function based on real-time perception maps, an AUV search decision-making method is established. When the AUV finds a suspected target, the AUV approaches the suspected target. The path planning of the AUV is carried out through an improved artificial potential field method. The short-distance confirmation of the target and obstacle avoidance in the search process are realized. The simulation results show that the algorithm has high search efficiency. Additionally, when the target exists in a corner area, the probability of the AUV to quickly search for the target is fast and feasible.
Adomian Decomposition Method with Orthogonal Polynomials: Laguerre Polynomials and the Second Kind of Chebyshev Polynomials
Authors: Xie Yingying , Li Lingfei , Wang Mancang
Published: July 2021

In this paper, a new efficient and practical modification of the Adomian decomposition method is proposed with Laguerre polynomials and the second kind of Chebyshev polynomials which has not been introduced in other articles to the best of our knowledge. This approach can be utilized to approximately solve linear and nonlinear differential equations. The proposed formulations are examined by a representative example and the numerical results confirm their efficiency and accuracy.
Expression and Characterization of a Novel Cold-Adapted and Stable β-Agarase Gene agaW1540 from the Deep-Sea Bacterium Shewanella sp. WPAGA9
Authors: Wang Wenxin , Wang Jianxin , Yan Ruihua , Zeng Runying , Zuo Yaqiang , Wang Dingquan , Qu Wu
Published: July 2021

The neoagaro-oligosaccharides, degraded from agarose by agarases, are important natural substances with many bioactivities. In this study, a novel agarase gene, agaW1540, from the genome of a deep-sea bacterium Shewanella sp. WPAGA9, was expressed, and the recombinant AgaW1540 (rAgaW1540) displayed the maximum activity under the optimal pH and temperature of 7.0 and 35 °C, respectively. rAgaW1540 retained 85.4% of its maximum activity at 0 °C and retained more than 92% of its maximum activity at the temperature range of 20–40 °C and the pH range of 4.0–9.0, respectively, indicating its extensive working temperature and pH values. The activity of rAgaW1540 was dramatically suppressed by Cu2+ and Zn2+, whereas Fe2+ displayed an intensification of enzymatic activity. The Km and Vmax of rAgaW1540 for agarose degradation were 15.7 mg/mL and 23.4 U/mg, respectively. rAgaW1540 retained 94.7%, 97.9%, and 42.4% of its maximum activity after incubation at 20 °C, 25 °C, and 30 °C for 60 min, respectively. Thin-layer chromatography and ion chromatography analyses verified that rAgaW1540 is an endo-acting β-agarase that degrades agarose into neoagarotetraose and neoagarohexaose as the main products. The wide variety of working conditions and stable activity at room temperatures make rAgaW1540an appropriate bio-tool for further industrial production of neoagaro-oligosaccharides.
Melatonin and Indole-3-Propionic Acid Reduce Oxidative Damage to Membrane Lipids Induced by High Iron Concentrations in Porcine Skin
Authors: Rynkowska Aleksandra , Stępniak Jan , Karbownik-Lewińska Małgorzata
Published: July 2021

Iron excess in tissues results in increased oxidative damage. Among different tissues, the skin can particularly be severely damaged by oxidative stress, as it is exposed not only to endogenous but also directly to exogenous pro-oxidants. The skin is especially vulnerable to harmful oxidative stress. Melatonin and indole-3-propionic acid (IPA), two indole substances, are efficient antioxidants. This study aims to evaluate the potential protective effects of melatonin and IPA against oxidative damage to membrane lipids (lipid peroxidation (LPO)), induced in porcine skin homogenates by the Fenton reaction (Fe2+ + H2O2 → Fe3+ + •OH + OH−) when iron is used in extremely high concentrations. Skin homogenates were incubated in the presence of FeSO4 (2400, 1200, 600, 300, 150 and 75 µM) + H2O2 (5 mM) with/without melatonin or IPA. LPO level (MDA + 4-HDA/mg protein) was measured spectrophotometrically. Melatonin, in its highest used concentration (5.0 mM), prevented FeSO4 (1200 mM)-induced LPO, whereas it was effective in concentrations as low as 2.5 mM against all lower iron concentrations. IPA was protective in concentrations as low as 2.5 mM independently of FeSO4 concentration. In conclusion, melatonin and IPA effectively protect against oxidative damage to membrane lipids induced by high concentrations of iron in porcine skin; therefore, both can be considered pharmacological agents in the case of disorders associated with excessive iron accumulation in the skin.
Research on Trimming Frequency-Increasing Technology for Quartz Crystal Resonator Using Laser Etching
Authors: Zhang Jun-Lin , Liao Shuang , Chen Cheng , Yang Xiu-Tao , Lin Sheng-Ao , Tan Feng , Li Bing , Wang Wen-Wu , Zhong Zheng-Xiang , Zeng Guang-Gen
Published: July 2021

A quartz crystal resonator (QCR) is an indispensable electronic component in the field of the modern electronics industry. By designing and depositing electrodes of different shapes and thicknesses on a quartz wafer with a certain fundamental frequency, the desired target frequency can be obtained. Affected by factors such as the deposition equipment, mask, wafer size and placement position, it is difficult to accurately obtain the target frequency at a given time, especially for mass-produced QCRs. In this work, a laser with a wavelength of 532 nm was used to thin the electrodes of a QCR with a fundamental frequency of 10 MHz. The electrode surface was etched through a preset processing pattern to form a processing method of local thinning of the electrode surface. At the same time, the effect of laser etching on silicon dioxide and resonator performance was analyzed. Satisfactory trimming frequency-increasing results were achieved, such as a frequency modulation accuracy of 1 ppm, frequency distribution with good consistency and equivalent parameters with small changes, by the laser partial etching of the resonator electrode. However, when the surface electrode was etched into using through-holes, the attenuation amplitude of the equivalent parameter became larger, especially in terms of the quality factor (Q), which decreased from 63 K to 1 K, and some resonators which had a serious frequency drift of >40%. In this case, a certain number of QCRs were no longer excited to vibrate, which was due to the disappearance of the piezoelectric effect caused by the local thermal phase change in the quartz wafer.
Laser Processing of Hard and Ultra-Hard Materials for Micro-Machining and Surface Engineering Applications
Authors: Hazzan Kafayat Eniola , Pacella Manuela , See Tian Long
Published: July 2021

Polycrystalline diamonds, polycrystalline cubic boron nitrides and tungsten carbides are considered difficult to process due to their superior mechanical (hardness, toughness) and wear properties. This paper aims to review the recent progress in the use of lasers to texture hard and ultra-hard materials to a high and reproducible quality. The effect of wavelength, beam type, pulse duration, fluence, and scanning speed is extensively reviewed, and the resulting laser mechanisms, induced damage, surface integrity, and existing challenges discussed. The cutting performance of different textures in real applications is examined, and the key influence of texture size, texture geometry, area ratio, area density, orientation, and solid lubricants is highlighted. Pulsed laser ablation (PLA) is an established method for surface texturing. Defects include melt debris, unwanted allotropic phase transitions, recast layer, porosity, and cracking, leading to non-uniform mechanical properties and surface roughness in fabricated textures. An evaluation of the main laser parameters indicates that shorter pulse durations (ns—fs), fluences greater than the ablation threshold, and optimised multi-pass scanning speeds can deliver sufficient energy to create textures to the required depth and profile with minimal defects. Surface texturing improves the tribological performance of cutting tools in dry conditions, reducing coefficient of friction (COF), cutting forces, wear, machining temperature, and adhesion. It is evident that cutting conditions (feed speed, workpiece material) have a primary role in the performance of textured tools. The identified gaps in laser surface texturing and texture performance are detailed to provide future trends and research directions in the field.
Synthesis, Characterization, In Vitro Anticancer Potentiality, and Antimicrobial Activities of Novel Peptide–Glycyrrhetinic-Acid-Based Derivatives
Authors: Moustafa Gaber O. , Shalaby Ahmed , Naglah Ahmed M. , Mounier Marwa M. , El-Sayed Heba , Anwar Manal M. , Nossier Eman S.
Published: July 2021

Glycyrrhetinic acid (GA) is one of many interesting pentacyclic triterpenoids showing significant anticancer activity by triggering apoptosis in tumor cell lines. This study deals with the design and synthesis of new glycyrrhetinic acid (GA)–amino acid peptides and peptide ester derivatives. The structures of the new derivatives were established through various spectral and microanalytical data. The novel compounds were screened for their in vitro cytotoxic activity. The evaluation results showed that the new peptides produced promising cytotoxic activity against the human breast MCF-7 cancer cell line while comparing to doxorubicin. On the other hand, only compounds 3, 5, and 7 produced potent activity against human colon HCT-116 cancer cell line. The human liver cancer (HepG-2) cell line represented a higher sensitivity to peptide 7 (IC50; 3.30 μg/mL), while it appeared insensitive to the rest of the tested peptides. Furthermore, compounds 1, 3, and 5 exhibited a promising safety profile against human normal skin fibroblasts cell line BJ-1. In order to investigate the mode of action, compound 5 was selected as a representative example to study its in vitro effect against the apoptotic parameters and Bax/BCL-2/p53/caspase-7/caspase-3/tubulin, and DNA fragmentation to investigate beta (TUBb). Additionally, all the new analogues were subjected to antimicrobial assay against a panel of Gram-positive and Gram-negative bacteria and the yeast candida Albicans. All the tested GA analogues 1–8 exhibited more antibacterial effect against Micrococcus Luteus than gentamicin, but they exhibited moderate antimicrobial activity against the tested bacterial and yeast strains. Molecular docking studies were also simulated for compound 5 to give better rationalization and put insight to the features of its structure.
Effects of Enzymatic Pretreatment of Seeds on the Physicochemical Properties, Bioactive Compounds, and Antioxidant Activity of Pomegranate Seed Oil
Authors: Kaseke Tafadzwa , Opara Umezuruike Linus , Fawole Olaniyi Amos
Published: July 2021

Enzymatic pretreatment of seeds is a novel approach that enhances the health benefits of the extracted oil. The study investigated the influence of the enzymatic pretreatment of seeds on the quality of oil from different pomegranate cultivars. The quality of the ultrasound-assisted (and ethanol-extracted) oil was studied, with respect to the refractive index (RI), yellowness index (YI), conjugated dienes (K232), peroxide value (PV) ρ-anisidine value (AV), total oxidation value (TOTOX), total carotenoid content (TCC), total phenolic compounds (TPC), fatty acid composition, phytosterol composition, ferric reducing antioxidant power (FRAP), and 2.2-diphenyl-1-picryl hydrazyl (DPPH) radical scavenging capacity. The seeds of three different pomegranate cultivars (‘Wonderful’, ‘Herskawitz’, and ‘Acco’) were digested with an equal mixture of Pectinex Ultra SPL, Flavourzyme 100 L, and cellulase crude enzymes, at a concentration, pH, temperature, and time of 1.7%, 4.5, 40 °C, and 5 h, respectively. Enzymatic pretreatment of PS increased oil yield, PV, TPC, TCC, and DPPH radical scavenging capacity, but decreased the YI. The levels of K232, AV and TOTOX, fatty acids, phytosterols, RI, and FRAP, were not significantly affected by enzymatic pretreatment of PS. Principal component analysis (PCA) established that oil extracted from the ‘Acco’ seed after enzymatic pretreatment had higher yield, TPC, TCC, and DPPH radical scavenging capacity. Therefore, enzyme-pretreated ‘Acco’ pomegranate fruit seed is a source of quality seed oil with excellent antioxidant properties.
Determining the Effect of Pre-Treatment in Rice Noodle Quality Subjected to Dehydration through Hierarchical Scoring
Authors: Ismail Muhammad Heikal , Lik Hii Ching , Routray Winny , Woo Meng Wai
Published: July 2021

Fresh rice noodle was usually coated in a large amount of oil to avoid stickiness and extend the shelf life. Pre-treatment has been applied to reduce the quantity of oil in rice noodle. In this research, the pre-treatment and temperature effect on the rice noodle quality subjected to hot air drying, heat pump drying, and freeze drying was investigated. Texture, color, oil content, and starch gelatinization of the dried noodle was further evaluated. Results revealed that there were significant differences (p < 0.05%) in texture, color, oil content, and starch gelatinization in rice noodle subjected to pre-treatment. Furthermore, the texture, color, oil content, and starch gelatinization demonstrated a significant difference (p < 0.05%) in freeze drying rather than hot air drying and heat pump drying. The findings indicate that the qualitative features of the dehydrated noodle are synergistic to pretreatment and drying temperature. Despite superior quality shown by freeze drying, the hierarchical scoring has proven that rice noodle undergoing hot air drying at 30 °C to produce comparable quality attributes. The hierarchical scoring can be a useful tool in quality determination for the food industry.
Cistercian Monasteries in Medieval Sweden—Foundations and Recruitments, 1143–1420
Authors: Andersson Catharina
Published: July 2021

This article presents an overview of the Cistercian monasteries that were founded in Sweden in the 12th and 13th centuries. The first were Alvastra and Nydala, founded in 1143, both male monasteries. However, eventually the nunneries came to outnumber the male monasteries (7/5). The purpose of the article is also to discuss the social background of the monks and nuns who inhabited these monasteries. As for the nuns, previous studies have shown that they initially came from the society’s elite, the royal families, but also other magnates. Gradually, social recruitment broadened, and an increasing number of women from the aristocratic lower levels came to dominate the recruitment. It is also suggested that from the end of the 14th century, the women increasingly came from the burghers. The male monasteries, on the other hand, were not even from the beginning populated by men from the nobles. Their family backgrounds seem rather to be linked to the aristocratic lower layers. This difference between the sexes can most probably be explained by the fact that ideals of monastic life—obedience, equality, poverty and ban on weapons—in a decisive way broke with what in secular life was constructed as an aristocratic masculinity.
Self-Disclosure to a Robot: Only for Those Who Suffer the Most
Authors: Duan Yunfei (Euphie) , Yoon Myung (Ji) , Liang Zhixuan (Edison) , Hoorn Johan Ferdinand
Published: July 2021

Social robots may become an innovative means to improve the well-being of individuals. Earlier research has shown that people easily self-disclose to a social robot, even in cases where it was unintended by the designers. We report on an experiment considering self-disclosing in a diary journal or to a social robot after negative mood induction. An off-the-shelf robot was complemented with our in-house developed AI chatbot, which could talk about ‘hot topics’ after training it with thousands of entries on a complaint website. We found that people who felt strongly negative after being exposed to shocking video footage benefited the most from talking to our robot, rather than writing down their feelings. For people less affected by the treatment, a confidential robot chat or writing a journal page did not differ significantly. We discuss emotion theory in relation to robotics and possibilities for an application in design (the emoji-enriched ‘talking stress ball’). We also underline the importance of otherwise disregarded outliers in a data set of therapeutic nature.
Remote Sensing Image Super-Resolution Based on Dense Channel Attention Network
Authors: Ma Yunchuan , Lv Pengyuan , Liu Hao , Sun Xuehong , Zhong Yanfei
Published: July 2021

In the recent years, convolutional neural networks (CNN)-based super resolution (SR) methods are widely used in the field of remote sensing. However, complicated remote sensing images contain abundant high-frequency details, which are difficult to capture and reconstruct effectively. To address this problem, we propose a dense channel attention network (DCAN) to reconstruct high-resolution (HR) remote sensing images. The proposed method learns multi-level feature information and pays more attention to the important and useful regions in order to better reconstruct the final image. Specifically, we construct a dense channel attention mechanism (DCAM), which densely uses the feature maps from the channel attention block via skip connection. This mechanism makes better use of multi-level feature maps which contain abundant high-frequency information. Further, we add a spatial attention block, which makes the network have more flexible discriminative ability. Experimental results demonstrate that the proposed DCAN method outperforms several state-of-the-art methods in both quantitative evaluation and visual quality.
Estimating Primary Forest Attributes and Rare Community Characteristics Using Unmanned Aerial Systems (UAS): An Enrichment of Conventional Forest Inventories
Authors: Fraser Benjamin T. , Congalton Russell G.
Published: July 2021

The techniques for conducting forest inventories have been established over centuries of land management and conservation. In recent decades, however, compelling new tools and methodologies in remote sensing, computer vision, and data science have offered innovative pathways for enhancing the effectiveness and comprehension of these sampling designs. Now with the aid of Unmanned Aerial Systems (UAS) and advanced image processing techniques, we have never been closer to mapping forests at field-based inventory scales. Our research, conducted in New Hampshire on complex mixed-species forests, used natural color UAS imagery for estimating individual tree diameters (diameter at breast height (dbh)) as well as stand level estimates of Basal Area per Hectare (BA/ha), Quadratic Mean Diameter (QMD), Trees per Hectare (TPH), and a Stand Density Index (SDI) using digital photogrammetry. To strengthen our understanding of these forests, we also assessed the proficiency of the UAS to map the presence of large trees (i.e., >40 cm in diameter). We assessed the proficiency of UAS digital photogrammetry for identifying large trees in two ways: (1) using the UAS estimated dbh and the 40 cm size threshold and (2) using a random forest supervised classification and a combination of spectral, textural, and geometric features. Our UAS-based estimates of tree diameter reported an average error of 19.7% to 33.7%. At the stand level, BA/ha and QMD were overestimated by 42.18% and 62.09%, respectively, while TPH and SDI were underestimated by 45.58% and 3.34%. When considering only stands larger than 9 ha however, the overestimation of BA/ha at the stand level dropped to 14.629%. The overall classification of large trees, using the random forest supervised classification achieved an overall accuracy of 85%. The efficiency and effectiveness of these methods offer local land managers the opportunity to better understand their forested ecosystems. Future research into individual tree crown detection and delineation, especially for co-dominant or suppressed trees, will further support these efforts.
Modeling and Performance Evaluation of Precise Positioning and Time-Frequency Transfer with Galileo Five-Frequency Observations
Authors: Xu Wei , Shen Wen-Bin , Cai Cheng-Hui , Li Li-Hong , Wang Lei , Shen Zi-Yu
Published: July 2021

The present Global Navigation Satellite System (GNSS) can provide at least double-frequency observations, and especially the Galileo Navigation Satellite System (Galileo) can provide five-frequency observations for all constellation satellites. In this contribution, precision point positioning (PPP) models with Galileo E1, E5a, E5b, E5 and E6 frequency observations are established, including a dual-frequency (DF) ionospheric-free (IF) combination model, triple-frequency (TF) IF combination model, quad-frequency (QF) IF combination model, four five-frequency (FF) IF com-bination models and an FF uncombined (UC) model. The observation data of five stations for seven days are selected from the multi-GNSS experiment (MGEX) network, forming four time-frequency links ranging from 454.6 km to 5991.2 km. The positioning and time-frequency transfer performances of Galileo multi-frequency PPP are compared and evaluated using GBM (which denotes precise satellite orbit and clock bias products provided by Geo Forschung Zentrum (GFZ)), WUM (which denotes precise satellite orbit and clock bias products provided by Wuhan University (WHU)) and GRG (which denotes precise satellite orbit and clock bias products provided by the Centre National d’Etudes Spatiales (CNES)) precise products. The results show that the performances of the DF, TF, QF and FF PPP models are basically the same, the frequency stabilities of most links can reach sub10−16 level at 120,000 s, and the average three-dimensional (3D) root mean square (RMS) of position and average frequency stability (120,000 s) can reach 1.82 cm and 1.18 × 10−15, respectively. The differences of 3D RMS among all models are within 0.17 cm, and the differences in frequency stabilities (in 120,000 s) among all models are within 0.08 × 10−15. Using the GRG precise product, the solution performance is slightly better than that of the GBM or WUM precise product, the average 3D RMS values obtained using the WUM and GRG precise products are 1.85 cm and 1.77 cm, respectively, and the average frequency stabilities at 120,000 s can reach 1.13 × 10−15 and 1.06 × 10−15, respectively.
A Deep Neural Network-Based Multi-Frequency Path Loss Prediction Model from 0.8 GHz to 70 GHz
Authors: Nguyen Chi , Cheema Adnan Ahmad
Published: July 2021

Large-scale fading models play an important role in estimating radio coverage, optimizing base station deployments and characterizing the radio environment to quantify the performance of wireless networks. In recent times, multi-frequency path loss models are attracting much interest due to their expected support for both sub-6 GHz and higher frequency bands in future wireless networks. Traditionally, linear multi-frequency path loss models like the ABG model have been considered, however such models lack accuracy. The path loss model based on a deep learning approach is an alternative method to traditional linear path loss models to overcome the time-consuming path loss parameters predictions based on the large dataset at new frequencies and new scenarios. In this paper, we proposed a feed-forward deep neural network (DNN) model to predict path loss of 13 different frequencies from 0.8 GHz to 70 GHz simultaneously in an urban and suburban environment in a non-line-of-sight (NLOS) scenario. We investigated a broad range of possible values for hyperparameters to search for the best set of ones to obtain the optimal architecture of the proposed DNN model. The results show that the proposed DNN-based path loss model improved mean square error (MSE) by about 6 dB and achieved higher prediction accuracy R2 compared to the multi-frequency ABG path loss model. The paper applies the XGBoost algorithm to evaluate the importance of the features for the proposed model and the related impact on the path loss prediction. In addition, the effect of hyperparameters, including activation function, number of hidden neurons in each layer, optimization algorithm, regularization factor, batch size, learning rate, and momentum, on the performance of the proposed model in terms of prediction error and prediction accuracy are also investigated.
Low-Cost Eye Tracking Calibration: A Knowledge-Based Study
Authors: Garde Gonzalo , Larumbe-Bergera Andoni , Bossavit Benoît , Porta Sonia , Cabeza Rafael , Villanueva Arantxa
Published: July 2021

Subject calibration has been demonstrated to improve the accuracy in high-performance eye trackers. However, the true weight of calibration in off-the-shelf eye tracking solutions is still not addressed. In this work, a theoretical framework to measure the effects of calibration in deep learning-based gaze estimation is proposed for low-resolution systems. To this end, features extracted from the synthetic U2Eyes dataset are used in a fully connected network in order to isolate the effect of specific user’s features, such as kappa angles. Then, the impact of system calibration in a real setup employing I2Head dataset images is studied. The obtained results show accuracy improvements over 50%, probing that calibration is a key process also in low-resolution gaze estimation scenarios. Furthermore, we show that after calibration accuracy values close to those obtained by high-resolution systems, in the range of 0.7°, could be theoretically obtained if a careful selection of image features was performed, demonstrating significant room for improvement for off-the-shelf eye tracking systems.
A Frequency Modulation-Based Taxel Array: A Bio-Inspired Architecture for Large-Scale Artificial Skin
Authors: Assaf Tareq
Published: July 2021

This work introduces an array prototype based on a Frequency Modulation (FM) encoding architecture to transfer multiple sensor signals on a single wire. The use case presented adopts Hall-effect sensors as an example to represent a much larger range of sensor types (e.g., proximity and temperature). This work aims to contribute to large area artificial skin systems which are a key element to enhance robotic platforms. Artificial skin will allow robotic platforms to have spatial awareness which will make interaction with objects and users safe. The FM-based architecture has been developed to address limitations in large-scale artificial skin scalability. Scalability issues include power requirements; number of wires needed; as well as frequency, density, and sensitivity bottlenecks. In this work, eight sensor signals are simultaneously acquired, transferred on a single wire and decoded in real-time. The overall taxel array current consumption is 36 mA. The work experimentally validates and demonstrates that different input signals can be effectively transferred using this approach minimizing wiring and power consumption of the taxel array. Four different tests using single as well as multiple stimuli are presented. Observations on performances, noise, and taxel array behaviour are reported. The results show that the taxel array is reliable and effective in detecting the applied stimuli.