bluuebunny/crossref_metadata_2025 huggingface dataset:
Theoretical Prediction of Gastrointestinal Absorption of Phytochemicals
Authors: Vélez Luis A. , Delgado Yamixa , Ferrer-Acosta Yancy , Suárez-Arroyo Ivette J. , Rodríguez Priscilla , Pérez Daraishka
Published: June 2022

The discovery of bioactive compounds for non-invasive therapy has been the goal of research groups focused on pharmacotherapy. Phytonutrients have always been attractive for researchers because they are a significant source of bioactive phytochemicals. Still, it is challenging to determine which components show high biomedical activity and bioavailability after administration. However, based on the chemical structure of these phytochemicals, their physicochemical properties can be calculated to predict the probability of gastrointestinal (GI) absorption after oral administration. Indeed, different researchers have proposed several rules (e.g., Lipinski’s, Veber’s, Ghose’s, and Muegge’s rules) to attain these predictions, but only for synthetic compounds. Most phytochemicals do not fully comply with these rules even though they show high bioactivity and high GI absorption experimentally. Here, we propose a detailed methodology using scientifically validated web-based platforms to determine the physicochemical properties of five phytochemicals found in ginger, echinacea, and tobacco. Furthermore, we analyzed the calculated data and established a protocol based on the integration of these classical rules, plus other extended parameters, that we called the Phytochemical Rule, to obtain a more reliable prediction of the GI absorption of natural compounds. This methodology can help evaluate bioactive phytochemicals as potential drug candidates and predict their oral bioavailability in patients.
Ameliorative Effects of Gut Microbial Metabolite Urolithin A on Pancreatic Diseases
Authors: Li Kailin , Xiao Yao , Bian Ji , Han Lin , He Caian , El-Omar Emad , Gong Lan , Wang Min
Published: June 2022

Urolithin A (Uro A) is a dietary metabolite of the intestinal microbiota following the ingestion of plant-based food ingredients ellagitannins and ellagic acid in mammals. Accumulating studies have reported its multiple potential health benefits in a broad range of diseases, including cardiovascular disease, cancer, cognitive impairment, and diabetes. In particular, Uro A is safe via direct oral administration and is non-genotoxic. The pancreas plays a central role in regulating energy consumption and metabolism by secreting digestive enzymes and hormones. Numerous pathophysiological factors, such as inflammation, deficits of mitophagy, and endoplasmic reticulum stress, can negatively affect the pancreas, leading to pancreatic diseases, including pancreatitis, pancreatic cancer, and diabetes mellitus. Recent studies showed that Uro A activates autophagy and inhibits endoplasmic reticulum stress in the pancreas, thus decreasing oxidative stress, inflammation, and apoptosis. In this review, we summarize the knowledge of Uro A metabolism and biological activity in the gut, as well as the pathological features and mechanisms of common pancreatic diseases. Importantly, we focus on the potential activities of Uro A and the underlying mechanisms in ameliorating various pancreatic diseases via inhibiting inflammatory signaling pathways, activating autophagy, maintaining the mitochondrial function, and improving the immune microenvironment. It might present a novel nutritional strategy for the intervention and prevention of pancreatic diseases.
Powdery Mildew Resistance Genes in Vines: An Opportunity to Achieve a More Sustainable Viticulture
Authors: Sosa-Zuniga Viviana , Vidal Valenzuela Álvaro , Barba Paola , Espinoza Cancino Carmen , Romero-Romero Jesus L. , Arce-Johnson Patricio
Published: June 2022

Grapevine (Vitis vinifera) is one of the main fruit crops worldwide. In 2020, the total surface area planted with vines was estimated at 7.3 million hectares. Diverse pathogens affect grapevine yield, fruit, and wine quality of which powdery mildew is the most important disease prior to harvest. Its causal agent is the biotrophic fungus Erysiphe necator, which generates a decrease in cluster weight, delays fruit ripening, and reduces photosynthetic and transpiration rates. In addition, powdery mildew induces metabolic reprogramming in its host, affecting primary metabolism. Most commercial grapevine cultivars are highly susceptible to powdery mildew; consequently, large quantities of fungicide are applied during the productive season. However, pesticides are associated with health problems, negative environmental impacts, and high costs for farmers. In paralleled, consumers are demanding more sustainable practices during food production. Therefore, new grapevine cultivars with genetic resistance to powdery mildew are needed for sustainable viticulture, while maintaining yield, fruit, and wine quality. Two main gene families confer resistance to powdery mildew in the Vitaceae, Run (Resistance to Uncinula necator) and Ren (Resistance to Erysiphe necator). This article reviews the powdery mildew resistance genes and loci and their use in grapevine breeding programs.
Prevalence, Serotypes, and Antimicrobial Resistance Patterns of Non-Typhoid Salmonella in Food in Northern Taiwan
Authors: Chang Yi-Jung , Chen Chyi-Liang , Yang Hsin-Ping , Chiu Cheng-Hsun
Published: June 2022

Salmonella is one of the most common bacteria causing food poisoning worldwide. We evaluated the prevalence, the serotypes, and the antimicrobial resistance (AMR) of Salmonella isolates from many kinds of food, particularly pork and chicken in retail, in Taiwan between January 2017 and December 2019. The E-test was used to assess antimicrobial susceptibility and a polymerase chain reaction was performed for serotyping. A total of 459 different foods were investigated, and 117 Salmonella strains were isolated. Retail pork and chicken were the most common Salmonella-contaminated foods (64.1% and 29.1%, respectively). Of the 117 isolates, 23 serotypes were identified. The serotypes Derby (16.2%), Anatum (13.7%), and Agona (8.5%) were the most prevalent. The resistance rates to ciprofloxacin, ceftriaxone, and carbapenem were 41.9%, 11.1%, and 1.7%, respectively. The Derby and Anatum serotypes were prevalent in chicken and pork; the Anatum serotype had significantly higher ciprofloxacin and ceftriaxone resistance rates and was highly prevalent in 2017 and 2018. Multi-locus sequence typing analysis revealed that the 58 randomly chosen Salmonella isolates belonged to 18 sequence types (STs). ST64 (Anatum, 16 out of 58, 27.6%) was the most common, followed by ST321 (Muenster, 6/58, 10.3%), ST831 (Give, 5/58, 8.6%), ST155 (London, 4/58, 6.9%) and ST314 (Kentucky, 4/58, 6.9%). Multidrug-resistant Salmonella strains were remarkably observed in the serotypes Anatum (ST64) and Goldcoast (ST358). This study revealed that retail pork was commonly contaminated with antimicrobial-resistant Salmonella. Thus, periodic investigations of Salmonella serotypes and AMR are needed.
Rossian Intuitionism without Self-Evidence?
Authors: Kaspar David
Published: June 2022

The first phase of the recent intuitionist revival left untouched Ross’s claim that fundamental moral truths are self-evident. In a recent article, Robert Cowan attempts to explain, in a plausible way, how we know moral truths. The result is that, while the broad framework of Ross’s theory appears to remain in place, the self-evidence of moral truths is thrown into doubt. In this paper, I examine Cowan’s Conceptual Intuitionism. I use his own proposal to show how he arrives at a skeptical position on self-evidence. First, he completely ignores the kind of epistemic appraisal intuitionism has always rested on; second, he is committed to the Reasons View of prima facie duty, rather than to Ross’s Properties View; third, he holds that a commitment to self-evidence often comes with a commitment to metaphysically extravagant entities, which he calls Perceptualism; fourth, he scrutinizes only a part of the contemporary theory of self-evidence, overlooking the strengths of the theory when considered as a whole. Revealing these several points supports the conclusion that Cowan has not provided a viable variety of Rossian Intuitionism.
Low Power FPGA Implementation of a Smart Building Free Space Optical Communication System
Authors: Ali Rehab , Eassa Hossameldin , Aly Hesham H. , Abaza Mohamed , Eisa Saleh M.
Published: June 2022

Free Space Optical (FSO) communication systems have extensively invaded the speed of smart city evolution due to the current surge in demand for wireless communication spots that can match recent challenges due to high technical leaps in smart city evolution. As the number of users is vastly increasing throughout all networks in the form of machines, devices, and variously distinct objects, FSO is a hugely recommended robust communication system that mitigates a lot of RF disadvantages on the field with no need for licensing, fast rollout time, and low cost. This paper shows an exploit of a Low Power Field Programmable Gate Array (FPGA) based FSO communication system designed for Line of Sight (LOS) Building to Building Communication over a distance of 12 m using a 650 nm Visible Light (VL) red laser source via On-Off Keying (OOK) and higher-level Intensity Modulation (IM)/Pulse Width Modulation (PWM) schemes. The implemented system reached a doubled data rate than OOK of 230 kbps using the IM technique. Traffic monitoring and building security status can be frequently updated between adherent buildings, each scanning its zone real-time conditions and sharing them with the neighboring links.
Trends and Limits for Quinoa Production and Promotion in Pakistan
Authors: Afzal Irfan , Basra Shahzad Maqsood Ahmed , Rehman Hafeez Ur , Iqbal Shahid , Bazile Didier
Published: June 2022

Quinoa is known as a super food due to its extraordinary nutritional qualities and has the potential to ensure future global food and nutritional security. As a model plant with halophytic behavior, quinoa has potential to meet the challenges of climate change and salinization due to its capabilities for survival in harsh climatic conditions. The quinoa crop has received worldwide attention due to its adoption and production expanded in countries out of the native Andean region. Quinoa was introduced to Pakistan in 2009 and it is still a new crop in Pakistan. The first quinoa variety was registered in 2019, then afterward, its cultivation started on a larger scale. Weed pressure, terminal heat stress, stem lodging, bold grain size, and an unstructured market are the major challenges in the production and promotion of the crop. The potential of superior features of quinoa has not been fully explored and utilized. Hence, there is a need to acquire more diverse quinoa germplasm and to establish a strong breeding program to develop new lines with higher productivity and improved crop features for the Pakistan market. Mechanized production, processing practices, and a structured market are needed for further scaling of quinoa production in Pakistan. To achieve these objectives, there is a dire need to create an enabling environment for quinoa production and promotion through the involvement of policymakers, research institutions, farmers associations, and the private sector.
Lignocellulosic Biomass from Grapevines as Raw Material for Particleboard Production
Authors: Auriga Radosław , Auriga Alicja , Borysiuk Piotr , Wilkowski Jacek , Fornalczyk Olga , Ochmian Ireneusz
Published: June 2022

The study aimed to determine the suitability of agricultural lignocellulosic biomass in the form of vine pruning waste for particleboard production. Two variants of particleboards with densities of 650 kg/m3 and 550 kg/m3 containing a varied amount of vine pruning waste (0, 25, 50 and 100%) were evaluated. The strength (MOR, MOE and IB), thickness swelling and water absorption after immersion in water for 2 and 24 h were tested. The results revealed that vine pruning waste affected the board thickening and reduced strength properties. Boards with a 50% share of waste met the minimum requirements of strength properties specified in the EN 312 standard for boards with a density of 650 kg/m3. However, boards with a density of 550 kg/m3 entirely made with vine pruning waste met the minimum requirements of strength properties of the EN 16368 standard. Moreover, the pruned material reduced axial forces during drilling, swelling and water absorption.
Selective Removal of Iron, Lead, and Copper Metal Ions from Industrial Wastewater by a Novel Cross-Linked Carbazole-Piperazine Copolymer
Authors: Al Anazi Majed , Abdulazeez Ismail , Al Hamouz Othman Charles S.
Published: June 2022

A novel cross-linked Copolymer (MXM) was synthesized by the polycondensation reaction of 3,6-Diaminocarbazole and piperazine with p-formaldehyde as a cross-linker. The Copolymer was fully characterized by solid 13C-NMR and FT-IR. The thermal stability of MXM was investigated by TGA and showed that the Copolymer was stable up to 300 °C. The synthesized polyamine was tested for the removal of iron (Fe2+), lead (Pb2+), and copper (Cu2+) ions from aqueous and industrial wastewater solutions. The effect of pH, concentration and time on the adsorption of iron (Fe2+), lead (Pb2+), and copper (Cu2+) ions was investigated. The adsorption of the studied ions from aqueous solutions onto the MXM polymer occurs following the Freundlich isotherm and pseudo-second-order kinetic models. The intraparticle diffusion model showed that the adsorption mechanism is controlled by film diffusion. The regeneration of MXM showed practical reusability with a loss in capacity of 2–5% in the case of Fe2+ and Cu2+ ions. The molecular simulation investigations revealed similarities between experimental and theoretical calculations. Industrial wastewater treatment revealed the excellent capabilities and design of MXM to be a potential adsorbent for the removal of heavy metal ions.
Fabrication of Rechargeable Photoactive Silk Fibroin/Polyvinyl Alcohol Blend Nanofibrous Membranes for Killing Bacteria
Authors: Yi Shixiong , Wu Jiaxue , Zhou Ying , Wang Xiaomeng , Pu Yunfei , Ran Boli
Published: June 2022

Antibacterial materials that prevent bacterial infections and mitigate bacterial virulence have attracted great scientific interest. In recent decades, bactericidal polymers have been presented as promising candidates to combat bacterial pathogens. However, the preparation of such materials has proven to be extremely challenging. Herein, photoactive silk fibroin/polyvinyl alcohol blended nanofibrous membranes grafted with 3,3’,4,4’-benzophenone tetracarboxylic dianhydride (G-SF/PVA BNM) were fabricated by an electrospinning technique. The premise of this work is that the G-SF/PVA BNM can store photoactive activity under light irradiation and release reactive oxygen species for killing bacteria under dark conditions. The results showed that the resultant G-SF/PVA BNM exhibited the integrated properties of an ultrathin fiber diameter (298 nm), good mechanical properties, robust photoactive activity and photo-store capacity, and great photoinduced antibacterial activity against E. coli and S. aureus (99.999% bacterial reduction with 120 min). The successful construction of blended nanofibrous membranes gives a new possibility to the design of highly efficient antibacterial materials for public health protection.
Effects of Thermochromic Fluorane Microcapsules and Self-Repairing Waterborne Acrylic Microcapsules on the Properties of Water-Based Coatings on Basswood Surface
Authors: Pan Pan , Yan Xiaoxing , Wang Lin
Published: June 2022

The effect of the addition of fluorane microcapsules and urea formaldehyde resin (UF) waterborne acrylic resin microcapsules on the comprehensive properties of the water film on the surface of basswood was studied. Three-factor and two-level orthogonal experiments were carried out with “fluorane microcapsule content”, “aqueous acrylic resin microcapsule content” and the “fluorane microcapsule addition method” to prepare a self-repairing thermochromic coating. The optical, mechanical, microstructure and self-repairing properties of the film were optimized by independent experiments on the maximum influence factors of the fluorane microcapsule content. It was concluded that the topcoat with 15% fluorane microcapsules and primer added with 15% water acrylic resin microcapsules had better comprehensive properties. The temperature range was 30–32 °C, the color difference at 32 °C was 72.6 ± 2.0, the 60° gloss was 3.3%, the adhesion was 0 grade, the hardness was 4 H, the impact resistance was 15.0 ± 0.8 kg∙cm, the elongation at break was 17.2% and the gap width was reduced by 3.5 ± 0.1 μm after the film was repaired. The repair rate reached 62.5%. By using microcapsule embedding technology, the repair agent and discoloration agent are embedded in the matrix. The waterborne acrylic resin microcapsules can effectively inhibit crack formation in the coating, and the fluorane microcapsules can achieve the thermochromic property of the coating. This study provides a new research idea for the self-repairing thermochromic dual function of a water-based coating.
Speciation Distribution and Influencing Factors of Heavy Metals in Rhizosphere Soil of Miscanthus Floridulus in the Tailing Reservoir Area of Dabaoshan Iron Polymetallic Mine in Northern Guangdong
Authors: Qin Jianqiao , Zhao Huarong , Dai Ming , Zhao Peng , Chen Xi , Liu Hao , Lu Baizhou
Published: June 2022

Through field investigation and experimental analysis, the forms, contents and distribution of heavy metals (Zn, Pb, Cu, Cd, Ni, Cr) in rhizosphere and non-rhizosphere soils of Miscanthus floridulus growing everywhere in Tielongwei mine pond (sample plot 1), Caoduikeng tailings pond (sample plot 2), Donghua tailings pond (sample plot 3) and Small tailings pond (sample plot 4) in Dabaoshan, Guangdong Province were studied. The results showed that the main forms and distributions of heavy metals in rhizosphere and non-rhizosphere soils are basically the same, which shows that the mineral content accounts for most of the total amount of heavy metals, while the exchange content is low. Compared with non-rhizosphere soil, the proportion of exchangeable and organic heavy metals in rhizosphere soil increased significantly, in which the proportion of organic-bound Cu increased by 53.25%, the proportion of organic-bound Cd and Pb increased by more than 17%, and the proportion of Zn increased by 5.67%. At the same time, the contents of carbonate-bound and iron manganese oxide-bound decreased. Statistical analyses showed that the morphological distribution of Zn, Pb, Cu, Cd, Ni and Cr in rhizosphere soil was closely related to soil pH value, organic matter content, plant growth and other factors. The results of this study provided a basis for the restoration of heavy metal-contaminated sites by Miscanthus.
Ocean–Atmosphere Variability in the Northwest Atlantic Ocean during Active Marine Heatwave Years
Authors: Sims Lydia D. , Subrahmanyam Bulusu , Trott Corinne B.
Published: June 2022

The Northwest (NW) Atlantic has experienced extreme ecological impacts from Marine Heatwaves (MHWs) within the past decade. This paper focuses on four MHW active years (2012, 2016, 2017, and 2020) and the relationship between Sea Surface Temperature anomalies (SSTA), Sea Surface Salinity anomalies (SSSA), North Atlantic Oscillation (NAO), Geopotential Height anomalies (ZA), and anomalous Jet Stream positions (JSPA). Multichannel singular spectrum analysis (MSSA) reveals the strongest temporal covariances between SSSA and SSTA, and JSPA and SSTA for all years, particularly for 2020 (SSSA–SSTA: 50%, JSPA–SSTA: 51%) indicating that this active MHW year was more atmospherically driven, followed by 2012, which had the second highest temporal covariances (SSSA–SSTA: 47%, JSPA–SSTA: 50%) between these parameters. Spatial correlations for SSSA and SSTA between NAO during MHW active years disrupt the long–term (2010–2020) positive relationship in the NW Atlantic. SSSA and JSPA, and SSSA and SSTA were strongly correlated across the NW Atlantic; 2012 SSSA–JSPA correlations were strong and positive between 56–62°W, and 2016, 2017, and 2020 SSSA–JSPA correlations were mostly strong and negative, with strong positive correlations present near the coastline (70–66°W) or off the NW Atlantic shelf (52–48°W). SSSA–SSTA showed the opposite correlations of similar spatial distributions of SSSA–JSPA for all MHW active years. This indicates strong relationships between JSPA, SSSA, and SSTA during MHWs. Understanding the temporal and spatial interplay between these parameters will aid in better monitoring and prediction of MHWs.
Can Mangrove Silviculture Be Carbon Neutral?
Authors: Wolswijk Giovanna , Barrios Trullols Africa , Hugé Jean , Otero Viviana , Satyanarayana Behara , Lucas Richard , Dahdouh-Guebas Farid
Published: June 2022

Matang Mangrove Forest Reserve (MMFR) in peninsular Malaysia has been managed for pole and charcoal production from Rhizophora stands with a 30-year rotation cycle since 1902. The aim of this study is to estimate the carbon budget of the MMFR by considering the carbon stock of the forest, evaluated from remote sensing data (Landsat TM and ETM+, JERS-1 SAR, ALOS PALSAR, ALOS-2 PALSAR-2, SRTM, TANDEM-X, and WorldView-2) for aboveground carbon and field data for belowground carbon. This was investigated in combination with the emissions from the silvicultural activities in the production chain, plus the distribution and consumer-related activities covering the supply chain, estimated with appropriate emission factors. The aboveground biomass carbon stock of the productive forest was of 1.4 TgC, while for the protective forest (not used for silviculture) it was at least equal to 1.2 TgC. The total soil carbon of ca. 32 TgC shows the potential of the MMFR as a carbon sink. However, the commercial exploitation of mangroves also generates greenhouse gasses with an estimate of nearly 152.80 Mg C ha−1 during charcoal production and up to 0.53 Mg C ha−1 during pole production, for a total emission of 1.8 TgC. Consequently, if the productive forest alone is considered, then the carbon budget is negative, and the ongoing silvicultural management seems to be an unsustainable practice that needs a reduction in the exploited area of at least 20% to achieve carbon neutrality. However, even with the current management, and considering the protective forest together with the productive zones, the MMFR carbon budget is slightly positive, thus showing the importance of mangrove conservation as part of the management for the preservation of the carbon stock.
Impact of Lock-In Time Constant on Remote Monitoring of Trace Gas in the Atmospheric Column Using Laser Heterodyne Radiometer (LHR)
Authors: Shen Fengjiao , Wang Gaoxuan , Xue Zhengyue , Tan Tu , Cao Zhensong , Gao Xiaoming , Chen Weidong
Published: June 2022

The time constant selected for lock-in amplification (LIA) has a crucial impact on observed line shapes in laser heterodyne spectroscopy, in particular in the case of ground-based remote monitoring of trace gas in the atmospheric column using laser heterodyne radiometer (LHR). Conventional simulation could not allow validation of LHR spectra measured in a real and complex atmospheric environment exhibiting large temporal and spatial variability (humidity, temperature, pressure, etc) that impact significantly the measured LHR spectra profiles. High-precision spectral measurement is thus crucial to avoid any spectral distortion resulting from the measurement. In this paper, the impact of LIA time constant on spectral line shape is investigated for LHR operating in continuous laser tuning mode, based on analysis of laboratory heterodyne spectra, in terms of signal-to-noise ratio (SNR), line width broadening, absorption depth and line shift. With respect to the given frequency scanning speed in continuous mode and to the halfwidth of the absorption feature to scan, a reasonable scanning time ΔTscan, the time needed for scanning laser frequency through the halfwidth ΔνHWHM of the absorption line, equal to or longer than 14 times of the LIA time constant τ is concluded in order to efficiently reduce the noise while without significant shift and distortion of the line shape. Experimental validation was carried out using a laser heterodyne absorption spectroscopy approach in the laboratory. Four different combinations of time constants τ and scanning time ΔTscan were used to record heterodyne spectra of a CH4 absorption line near 1242.00 cm−1 in continuous laser tuning mode. An optimal combination of a scanning time of 137 ms with a time constant of 1 ms was obtained. This optimal combination was used for ground-based measurements of CH4 and N2O in the atmospheric column by LHR. The extracted LHR spectrum is in good agreement with a referenced TCCON (Total Carbon Column Observing Network) FT-IR (Fourier-transform infrared) spectrum.
An Extended Usability and UX Evaluation of a Mobile Application for the Navigation of Individuals with Blindness and Visual Impairments Outdoors—An Evaluation Framework Based on Training
Authors: Theodorou Paraskevi , Tsiligkos Kleomenis , Meliones Apostolos , Filios Costas
Published: June 2022

Navigation assistive technologies have been designed to support the mobility of people who are blind and visually impaired during independent navigation by providing sensory augmentation, spatial information and general awareness of their environment. This paper focuses on the extended Usability and User Experience (UX) evaluation of BlindRouteVision, an outdoor navigation smartphone application that tries to efficiently solve problems related to the pedestrian navigation of visually impaired people without the aid of guides. The proposed system consists of an Android application that interacts with an external high-accuracy GPS sensor tracking pedestrian mobility in real-time, a second external device specifically designed to be mounted on traffic lights for identifying traffic light status and an ultrasonic sensor for detecting near-field obstacles along the route of the blind. Moreover, during outdoor navigation, it can optionally incorporate the use of Public Means of Transport, as well as provide multiple other uses such as dialing a call and notifying the current location in case of an emergency. We present findings from a Usability and UX standpoint of our proposed system conducted in the context of a pilot study, with 30 people having varying degrees of blindness. We also received feedback for improving both the available functionality of our application and the process by which the blind users learn the features of the application. The method of the study involved using standardized questionnaires and semi-structured interviews. The evaluation took place after the participants were exposed to the system’s functionality via specialized user-centered training sessions organized around a training version of the application that involves route simulation. The results indicate an overall positive attitude from the users.
Multi-Mobile Agent Trust Framework for Mitigating Internal Attacks and Augmenting RPL Security
Authors: Farooq Umer , Asim Muhammad , Tariq Noshina , Baker Thar , Awad Ali Ismail
Published: June 2022

Recently, the Internet of Things (IoT) has emerged as an important way to connect diverse physical devices to the internet. The IoT paves the way for a slew of new cutting-edge applications. Despite the prospective benefits and many security solutions offered in the literature, the security of IoT networks remains a critical concern, considering the massive amount of data generated and transmitted. The resource-constrained, mobile, and heterogeneous nature of the IoT makes it increasingly challenging to preserve security in routing protocols, such as the routing protocol for low-power and lossy networks (RPL). RPL does not offer good protection against routing attacks, such as rank, Sybil, and sinkhole attacks. Therefore, to augment the security of RPL, this article proposes the energy-efficient multi-mobile agent-based trust framework for RPL (MMTM-RPL). The goal of MMTM-RPL is to mitigate internal attacks in IoT-based wireless sensor networks using fog layer capabilities. MMTM-RPL mitigates rank, Sybil, and sinkhole attacks while minimizing energy and message overheads by 25–30% due to the use of mobile agents and dynamic itineraries. MMTM-RPL enhances the security of RPL and improves network lifetime (by 25–30% or more) and the detection rate (by 10% or more) compared to state-of-the-art approaches, namely, DCTM-RPL, RBAM-IoT, RPL-MRC, and DSH-RPL.
Stretchy Electrochemical Harvesters for Binarized Self-Powered Strain Gauge-Based Static Motion Sensors
Authors: Sim Hyeon Jun , Kim Jeeeun , Choi Jin Hyeong , Oh Myoungeun , Choi Changsoon
Published: June 2022

The human monitoring system has motivated the search for new technology, leading to the development of a self-powered strain sensor. We report on the stretchable and soft stretchy electrochemical harvester (SECH) bilayer for a binarized self-powered strain gauge in dynamic and static motion. The active surface area participating in the electrochemical reaction was enhanced after stretching the SECH in the electrolyte, leading to an increase in the electrochemical double-layer capacitance. A change in the capacitance induced a change in the electrical potential of the bilayer, generating electrical energy. The SECH overcomes several challenges of the previous mechano-electrochemical harvester: The harvester had high elasticity (50%), which satisfied the required strain during human motion. The harvester was highly soft (modulus of 5.8 MPa), 103 times lower than that of the previous harvester. The SECH can be applied to a self-powered strain gauge, capable of measuring stationary deformation and low-speed motion. The SECH created a system to examine the configuration of the human body, as demonstrated by the human monitoring sensor from five independent SECH assembled on the hand. Furthermore, the sensing information was simplified through the binarized signal. It can be used to assess the hand configuration for hand signals and sign language.
Objective Measurement of Walking Activity Using Wearable Technologies in People with Parkinson Disease: A Systematic Review
Authors: Correno Mathias Baptiste , Hansen Clint , Carlin Thomas , Vuillerme Nicolas
Published: June 2022

Parkinson’s disease (PD) is a complex neurodegenerative disease with a multitude of disease variations including motor and non-motor symptoms. Quality of life and symptom management may be improved with physical activity. Due to technological advancement, development of small new wearable devices recently emerged and allowed objective measurement of walking activity in daily life. This review was specifically designed to synthesize literature on objective walking activity measurements using wearable devices of patients with PD. Inclusion criteria included patients with a diagnosis of PD and exclusion criteria included studies using animal models or mixed syndromes. Participants were not required to undergo any type of intervention and the studies must have reported at least one output that quantifies daily walking activity. Three databases were systematically searched with no limitation on publication date. Twenty-six studies were eligible and included in the systematic review. The most frequently used device was the ActiGraph GT3X which was used in 10 studies. Duration of monitoring presented a range from 8 h to one year. Nevertheless, 11 studies measured walking activity during a 7-day period. On-body sensor wearing location differed throughout the included studies showing eight positions, with the waist, ankle, and wrist being the most frequently used locations. The main procedures consisted of measurement of walking hours during a 2-day period or more, equipped with a triaxial accelerometer at the dominant hip or ankle. It is also important for further research to take care of different factors such as the population, their pathology, the period, and the environment.
A Review of Image Processing Techniques for Deepfakes
Authors: Shahzad Hina Fatima , Rustam Furqan , Flores Emmanuel Soriano , Luís Vidal Mazón Juan , de la Torre Diez Isabel , Ashraf Imran
Published: June 2022

Deep learning is used to address a wide range of challenging issues including large data analysis, image processing, object detection, and autonomous control. In the same way, deep learning techniques are also used to develop software and techniques that pose a danger to privacy, democracy, and national security. Fake content in the form of images and videos using digital manipulation with artificial intelligence (AI) approaches has become widespread during the past few years. Deepfakes, in the form of audio, images, and videos, have become a major concern during the past few years. Complemented by artificial intelligence, deepfakes swap the face of one person with the other and generate hyper-realistic videos. Accompanying the speed of social media, deepfakes can immediately reach millions of people and can be very dangerous to make fake news, hoaxes, and fraud. Besides the well-known movie stars, politicians have been victims of deepfakes in the past, especially US presidents Barak Obama and Donald Trump, however, the public at large can be the target of deepfakes. To overcome the challenge of deepfake identification and mitigate its impact, large efforts have been carried out to devise novel methods to detect face manipulation. This study also discusses how to counter the threats from deepfake technology and alleviate its impact. The outcomes recommend that despite a serious threat to society, business, and political institutions, they can be combated through appropriate policies, regulation, individual actions, training, and education. In addition, the evolution of technology is desired for deepfake identification, content authentication, and deepfake prevention. Different studies have performed deepfake detection using machine learning and deep learning techniques such as support vector machine, random forest, multilayer perceptron, k-nearest neighbors, convolutional neural networks with and without long short-term memory, and other similar models. This study aims to highlight the recent research in deepfake images and video detection, such as deepfake creation, various detection algorithms on self-made datasets, and existing benchmark datasets.
Toward a Structural Health Monitoring Methodology for Concrete Structures under Dynamic Loads Using Embedded FBG Sensors and Strain Mapping Techniques
Authors: Amaya Alejandra , Sierra-Pérez Julián
Published: June 2022

A data-driven-based methodology for SHM in reinforced concrete structures using embedded fiber optic sensors and pattern recognition techniques is presented. A prototype of a reinforced concrete structure was built and instrumented in a novel fashion with FBGs bonded directly to the reinforcing steel bars, which, in turn, were embedded into the concrete structure. The structure was dynamically loaded using a shaker. Superficial positive damages were induced using bonded thin steel plates. Data for pristine and damaged states were acquired. Classifiers based on Mahalanobis’ distance of the covariance data matrix were developed for both supervised and unsupervised pattern recognition with an accuracy of up to 98%. It was demonstrated that the proposed sensing scheme in conjunction with the developed supervised and unsupervised pattern recognition techniques allows the detection of slight stiffness changes promoted by damages, even when strains are very small and the changes of these associated with the damage occurrence may seem negligible.
Amniotic Fluid Classification and Artificial Intelligence: Challenges and Opportunities
Authors: Khan Irfan Ullah , Aslam Nida , Anis Fatima M. , Mirza Samiha , AlOwayed Alanoud , Aljuaid Reef M. , Bakr Razan M.
Published: June 2022

A fetal ultrasound (US) is a technique to examine a baby’s maturity and development. US examinations have varying purposes throughout pregnancy. Consequently, in the second and third trimester, US tests are performed for the assessment of Amniotic Fluid Volume (AFV), a key indicator of fetal health. Disorders resulting from abnormal AFV levels, commonly referred to as oligohydramnios or polyhydramnios, may pose a serious threat to a mother’s or child’s health. This paper attempts to accumulate and compare the most recent advancements in Artificial Intelligence (AI)-based techniques for the diagnosis and classification of AFV levels. Additionally, we provide a thorough and highly inclusive breakdown of other relevant factors that may cause abnormal AFV levels, including, but not limited to, abnormalities in the placenta, kidneys, or central nervous system, as well as other contributors, such as preterm birth or twin-to-twin transfusion syndrome. Furthermore, we bring forth a concise overview of all the Machine Learning (ML) and Deep Learning (DL) techniques, along with the datasets supplied by various researchers. This study also provides a brief rundown of the challenges and opportunities encountered in this field, along with prospective research directions and promising angles to further explore.
Assessment of the Effect of Soil Sample Preparation, Water Content and Excitation Time on Proximal X-ray Fluorescence Sensing
Authors: Li Shuo , Shen Jiali , Bishop Thomas F. A. , Viscarra Rossel Raphael A.
Published: June 2022

X-ray fluorescence (XRF) spectroscopy offers a fast and efficient method for analysing soil elemental composition, both in the laboratory and the field. However, the technique is sensitive to spectral interference as well as physical and chemical matrix effects, which can reduce the precision of the measurements. We systematically assessed the XRF technique under different sample preparations, water contents, and excitation times. Four different soil samples were used as blocks in a three-way factorial experiment, with three sample preparations (natural aggregates, ground to ≤2 mm and ≤1 mm), three gravimetric water contents (air-dry, 10% and 20%), and three excitation times (15, 30 and 60 s). The XRF spectra were recorded and gave 540 spectra in all. Elemental peaks for Si, K, Ca, Ti, Fe and Cu were identified for analysis. We used analysis of variance (anova) with post hoc tests to identify significant differences between our factors and used the intensity and area of the elemental peaks as the response. Our results indicate that all of these factors significantly affect the XRF spectrum, but longer excitation times appear to be more defined. In most cases, no significant difference was found between air-dry and 10% water content. Moisture has no apparent effect on coarse samples unless ground to 1 mm. We suggested that the XRF measurements that take 60 s from dry samples or only slightly moist ones might be an optimum option under field conditions.
A Smarter Health through the Internet of Surgical Things
Authors: Mulita Francesk , Verras Georgios-Ioannis , Anagnostopoulos Christos-Nikolaos , Kotis Konstantinos
Published: June 2022

(1) Background: In the last few years, technological developments in the surgical field have been rapid and are continuously evolving. One of the most revolutionizing breakthroughs was the introduction of the IoT concept within surgical practice. Our systematic review aims to summarize the most important studies evaluating the IoT concept within surgical practice, focusing on Telesurgery and surgical Telementoring. (2) Methods: We conducted a systematic review of the current literature, focusing on the Internet of Surgical Things in Telesurgery and Telementoring. Forty-eight (48) studies were included in this review. As secondary research questions, we also included brief overviews of the use of IoT in image-guided surgery, and patient Telemonitoring, by systematically analyzing fourteen (14) and nineteen (19) studies, respectively. (3) Results: Data from 219 patients and 757 healthcare professionals were quantitively analyzed. Study designs were primarily observational or based on model development. Palpable advantages from the IoT incorporation mainly include less surgical hours, accessibility to high quality treatment, and safer and more effective surgical education. Despite the described technological advances, and proposed benefits of the systems presented, there are still identifiable gaps in the literature that need to be further explored in a systematic manner. (4) Conclusions: The use of the IoT concept within the surgery domain is a widely incorporated but less investigated concept. Advantages have become palpable over the past decade, yet further research is warranted.
Multi-Agent Decision-Making Modes in Uncertain Interactive Traffic Scenarios via Graph Convolution-Based Deep Reinforcement Learning
Authors: Gao Xin , Li Xueyuan , Liu Qi , Li Zirui , Yang Fan , Luan Tian
Published: June 2022

As one of the main elements of reinforcement learning, the design of the reward function is often not given enough attention when reinforcement learning is used in concrete applications, which leads to unsatisfactory performances. In this study, a reward function matrix is proposed for training various decision-making modes with emphasis on decision-making styles and further emphasis on incentives and punishments. Additionally, we model a traffic scene via graph model to better represent the interaction between vehicles, and adopt the graph convolutional network (GCN) to extract the features of the graph structure to help the connected autonomous vehicles perform decision-making directly. Furthermore, we combine GCN with deep Q-learning and multi-step double deep Q-learning to train four decision-making modes, which are named the graph convolutional deep Q-network (GQN) and the multi-step double graph convolutional deep Q-network (MDGQN). In the simulation, the superiority of the reward function matrix is proved by comparing it with the baseline, and evaluation metrics are proposed to verify the performance differences among decision-making modes. Results show that the trained decision-making modes can satisfy various driving requirements, including task completion rate, safety requirements, comfort level, and completion efficiency, by adjusting the weight values in the reward function matrix. Finally, the decision-making modes trained by MDGQN had better performance in an uncertain highway exit scene than those trained by GQN.
Interturn Short Fault Diagnosis Using Magnitude and Phase of Currents in Permanent Magnet Synchronous Machines
Authors: Jeong Hyeyun , Lee Hojin , Kim Seongyun , Kim Sang Woo
Published: June 2022

With the increased demand for permanent magnet synchronous machines (PMSMs) in various industrial fields, interturn short fault (ITSF) diagnosis of PMSMs is under the limelight. In particular, to prevent accidents caused by PMSM malfunctions, it is difficult and greatly necessary to diagnose slight ITSF, which is a stage before the ITSF becomes severe. In this paper, we propose a novel fault indicator based on the magnitude and phase of the current. The proposed fault indicator was developed using analysis of positive-sequence current (PSC) and negative-sequence current (NSC), which means the degree of the asymmetry of the three-phase currents by ITSF. According to the analysis, as ITSF increases, the phase difference between PSC and NSC decreases and the magnitude of NSC increases. Therefore, the novel fault indicator is suggested as a product of the cosine value of the phase indicator and the magnitude indicator. The magnitude indicator is the magnitude of NSC, and the phase indicator means the phase difference between the PSC and the NSC. The suggested fault indicator diagnoses the degree of ITSF as well as slight ITSFs under various conditions by only measured three-phase currents. Experimental results demonstrate the effectiveness of our proposed method under various torque and speeds.
Synchrotron Radiation Study of Gain, Noise, and Collection Efficiency of GaAs SAM-APDs with Staircase Structure
Authors: Colja Matija , Cautero Marco , Menk Ralf Hendrik , Palestri Pierpaolo , Gianoncelli Alessandra , Antonelli Matias , Biasiol Giorgio , Dal Zilio Simone , Steinhartova Tereza , Nichetti Camilla , Arfelli Fulvia , De Angelis Dario , Driussi Francesco , Bonanni Valentina , Pilotto Alessandro , Gariani Gianluca , Carrato Sergio , Cautero Giuseppe
Published: June 2022

In hard X-ray applications that require high detection efficiency and short response times, such as synchrotron radiation-based Mössbauer absorption spectroscopy and time-resolved fluorescence or photon beam position monitoring, III–V-compound semiconductors, and dedicated alloys offer some advantages over the Si-based technologies traditionally used in solid-state photodetectors. Amongst them, gallium arsenide (GaAs) is one of the most valuable materials thanks to its unique characteristics. At the same time, implementing charge-multiplication mechanisms within the sensor may become of critical importance in cases where the photogenerated signal needs an intrinsic amplification before being acquired by the front-end electronics, such as in the case of a very weak photon flux or when single-photon detection is required. Some GaAs-based avalanche photodiodes (APDs) were grown by a molecular beam epitaxy to fulfill these needs; by means of band gap engineering, we realised devices with separate absorption and multiplication region(s) (SAM), the latter featuring a so-called staircase structure to reduce the multiplication noise. This work reports on the experimental characterisations of gain, noise, and charge collection efficiencies of three series of GaAs APDs featuring different thicknesses of the absorption regions. These devices have been developed to investigate the role of such thicknesses and the presence of traps or defects at the metal–semiconductor interfaces responsible for charge loss, in order to lay the groundwork for the future development of very thick GaAs devices (thicker than 100 μm) for hard X-rays. Several measurements were carried out on such devices with both lasers and synchrotron light sources, inducing photon absorption with X-ray microbeams at variable and controlled depths. In this way, we verified both the role of the thickness of the absorption region in the collection efficiency and the possibility of using the APDs without reaching the punch-through voltage, thus preventing the noise induced by charge multiplication in the absorption region. These devices, with thicknesses suitable for soft X-ray detection, have also shown good characteristics in terms of internal amplification and reduction of multiplication noise, in line with numerical simulations.
A High Time-Efficient Missing Tag Detection Scheme for Integrated RFID Systems
Authors: Guo Kaimin , Xie Xin , Qi Heng , Li Keqiu
Published: June 2022

Missing tag incidents are common in RFID-enabled supply-chain and warehousing scenarios due to cargo theft and employee error operations, which may lead to serious economic losses or potential safety hazards. On the premise of ensuring the accuracy of missing tag detection, this paper aims to improve the time efficiency in an integrated RFID system. Unlike prior work focusing on detecting missing items from a large number of homogeneous tags that are monitored by a single reader, one integrated RFID system possesses multiple readers to communicate with the heterogeneous tags, which have different categorical attributes. In addition, the prior work required repeating the execution several times to capture the missing tags in assorted categories, which is of low time efficiency. Thus, a protocol called Multi-reader Missing Tag Detection (MMTD) is proposed to capture the missing tag quickly and reliably, which can detect missing tags from different categories in a parallel manner and is much more time-efficient than previous work. MMTD has two major advantages compared to prior work: (i) It leverages the knowledge of the spatial distribution of tags to divide up a difficult detection task into several lightweight tasks, which are shared by multiple readers. (ii) It personalizes the time frame of the reader based on the tag population to optimize the utilization of the communication channel. The final simulation results reveal that MMTD is the best in time-efficiency among the comparison protocols, and MMTD outperforms the other missing tag detection protocols by at least 1.5× in the Integrated RFID scenarios.