bluuebunny/crossref_metadata_2025 huggingface dataset:
Vegetation Composition of the Halophytic Grass Aeluropus lagopoides Communities within Coastal and Inland Sabkhas of Saudi Arabia
Authors: Dar Basharat A. , Assaeed Abdulaziz M. , Al-Rowaily Saud L. , Al-Doss Abdullah A. , Abd-ElGawad Ahmed M.
Published: March 2022

Sabkhas are unique, highly saline ecosystems, where specially adapted plants can grow. Aeluropus lagopoides (L.) Thwaites is a halophytic forage plant growing in salt marsh habitats of inland and coastal sabkhas of Saudi Arabia. The present study provides an analysis of vegetation composition and distribution of the A. lagopoides community in five different regions within Saudi Arabia, emphasizing the environmental factors that affect species distribution. The floristic survey revealed the presence of 48 species, belonging to 26 families. Poaceae, Chenopodiaceae, Mimosaceae, Zygophyllaceae, and Asteraceae are the largest families (50% of total species). Phanerophyte, followed by chamaephytes, are the most frequent forms, indicating a typical saline desert life-form spectrum. The vegetation analysis revealed the dominance of A. lagopoides in all locations, where it was the most dominant species in Qareenah, Qaseem, and Salwa locations, and the second most dominant species in Jouf and Jizan locations. The flourishment of this halophytic grass within a wide soil range in sabkhas revealed its adaptability to the harsh environment, which could be ascribed to its structural adaptations and modifications, as well as the phenotypic plasticity. The Qareenah and Qaseem locations attained the highest species richness and evenness, while the Jizan location was the least diverse. Within the studied locations, other highly salt-tolerant species were determined with high abundances, such as Suaeda aegyptiaca (Hasselq.) Zohary, Zygophyllum album L.f., Tamarix nilotica (Ehrenb.) Bunge, Cressa cretica L., and Salicornia europaea L. The soil analysis showed a significant variation for all parameters among the studied locations, except for pH, chloride, and clay content. The Qaseem location revealed the highest values of most soil parameters, while the Jizan location showed the lowest. The canonical correspondence analysis (CCA) showed that the community structure and diversity are mainly affected by the soil salinity and moisture. Due to the economic potentialities of A. lagopoides as a forage plant and sand stabilizer, the conservation of its habitats is of vital importance. In addition, this grass could be integrated as a promising forage candidate that can be planted in saline-affected areas, even in the summer dry season.
Bulk Polymerization of PEGDA in Spruce Wood Using a DBD Plasma-Initiated Process to Improve the Flexural Strength of the Wood–Polymer Composite
Authors: Mieles Matthew , Stitt Callie , Ji Hai-Feng
Published: March 2022

The chemical treatment of wood has been shown to increase its mechanical strength by forming composites with a variety of polymers. Polyethylene glycol diacrylate (PEGDA) has commonly been used as a polymer reinforcement to increase the strength and resistance of spruce wood for various applications, such as protection from weathering. In this study, PEGDA was impregnated into wood samples and polymerized by dielectric barrier discharge (DBD) plasma to form wood–polymer composites (WPCs). The kinetic rate order of PEGDA was explored using FT-IR quantitative analysis and the DBD plasma-initiated polymerization was determined to be second order. The strength of the wood samples was then determined by a three-point flexural test. The PEGDA-treated spruce wood samples showed improved flexural strength versus the untreated wood samples. The WPCs were also made using a UV treatment method and were then compared to the DBD plasma-treated samples. The results showed that the DBD plasma-treated samples yielded superior flexural strength relative to the UV-treated samples. We accredited this difference in strength to the plasma process and its ability to penetrate into the various layers of the wood and initiate polymerization, as opposed to UV light that can only penetrate superficially, initiating polymerization in only the first few layers of the wood surface.
Physico-Chemical Properties of Red Pepper (Capsicum annuum L.) as Influenced by Different Drying Methods and Temperatures
Authors: A Anjaneyulu , Sharangi Amit Baran , Upadhyay Tarun Kumar , Alshammari Nawaf , Saeed Mohd , Al-Keridis Lamya Ahmed
Published: March 2022

An experiment was carried out in the laboratories of the Department of Food Engineering, Department of Vegetable Science, and Department of Plantation Spices Medicinal and Aromatic crops, Bidhan Chandra Krishi Viswavidyalaya (BCKV), West Bengal, India. The work was performed during 2018–2019 and 2019–2020 with different drying methods including sun drying, solar drying and oven drying. In oven drying, different temperatures such as 50, 55, 60, 65, and 70 °C were considered. A randomized complete block design (RCBD) was designed with seven treatments and three replications. Experimental results were significantly varied among the treatments as influenced by different drying methods and temperatures. Minimum time taken (480 min) to reach safe moisture content was recorded in T7 (oven drying at 70 °C), whereas maximum values in color components such as L* value (24.55), a* value (32.14), b* value (20.53), and pungency score (7.85) were recorded in T6 (oven drying at 65 °C). However, the highest texture (1180.81) was observed in T1 (sun drying). Biochemical parameters were significantly varied among the treatments. The maximum amounts of ascorbic acid (56.06 mg/100 g) and oleoresin content (10.72) were found in T3 (oven drying at 50 °C), whereas minimum values of biochemical parameters were recorded by T1 (sun drying) and T2 (solar drying) methods, respectively. Mathematical relationships were found in different drying methods and temperatures. Models such as the Lewis, Page, Modified Page, and Henderson and Pabis models were selected to fit the data. Maximum R2 value (0.9835) was found in both the Page and Modified Page models with similar values of drying method and temperature at 65 °C. This value was the highest among all models in all drying temperatures. However, the lowest χ2, and RMSE values (0.000818 and 0.027261, respectively) were recorded with the Page model.
Data-Independent Acquisition Enables Robust Quantification of 400 Proteins in Non-Depleted Canine Plasma
Authors: Ravuri Halley Gora , Noor Zainab , Mills Paul C. , Satake Nana , Sadowski Pawel
Published: March 2022

Mass spectrometry-based plasma proteomics offers a major advance for biomarker discovery in the veterinary field, which has traditionally been limited to quantification of a small number of proteins using biochemical assays. The development of foundational data and tools related to sequential window acquisition of all theoretical mass spectra (SWATH)-mass spectrometry has allowed for quantitative profiling of a significant number of plasma proteins in humans and several animal species. Enabling SWATH in dogs enhances human biomedical research as a model species, and significantly improves diagnostic and disease monitoring capability. In this study, a comprehensive peptide spectral library specific to canine plasma proteome was developed and evaluated using SWATH for protein quantification in non-depleted dog plasma. Specifically, plasma samples were subjected to various orthogonal fractionation and digestion techniques, and peptide fragmentation data corresponding to over 420 proteins was collected. Subsequently, a SWATH-based assay was introduced that leveraged the developed resource and that enabled reproducible quantification of 400 proteins in non-depleted plasma samples corresponding to various disease conditions. The ability to profile the abundance of such a significant number of plasma proteins using a single method in dogs has the potential to accelerate biomarker discovery studies in this species.
Proposal to Extend Access to Loans for Serious Illnesses Using Open Data
Authors: Planchet Frédéric , Debonneuil Édouard , Péju Marie
Published: March 2022

In France, access to a loan requires one to obtain loan insurance and the presence of a pathology in the applicant may be a reason for refusal. Improving knowledge of health risks and pooling risks are two methods of broadening access to loans. We attempt to analyse these possibilities using open data and risk pooling scenarios. We find that the removal of medical selection can be ensured if the current framework is adjusted. We also demonstrate how to use open data to estimate loan insurance premiums for a variety of diseases. We take two examples: breast cancer and type 1 diabetes. Broadening access to borrowing would be beneficial for patients and for the development of the economy associated with these projects.
Winter–Spring Phytoplankton Phenology Associated with the Kuroshio Extension Instability
Authors: Siswanto Eko , Sasai Yoshikazu , Matsumoto Kazuhiko , Honda Makio C.
Published: March 2022

We used ocean color data of chlorophyll-a (CHL) from the period 1998 to 2017 to investigate phytoplankton phenology during winter–spring in association with the Kuroshio Extension (KE) instability. In the areas south of the KE, CHLs tended to be higher in winter during periods of unstable KEs (compared to stable KEs) which were attributed to the increases in nutrient and light availability. Nutrients were supplied from the deep layer due to physical processes indicated by negative sea surface height anomalies (SSHAs) and shallow mixed layer depths (MLDs). The increase in light availability could be attributed to greater exposure of phytoplankton to light in the shallower MLD. The same physical processes also explained higher CHLs in spring during unstable KEs. We also found that CHLs could possibly be lower during unstable KEs in spring which might be related to warmer SSTs in winter–spring. On average, the onset of the phytoplankton spring bloom south of the KE tended to be 1–3 weeks earlier during the period of unstable KEs than during the period of stable KEs. Whether this difference of 1–3 weeks impacts high-trophic-level organisms should be investigated in future studies.
What Can We Learn from Nighttime Lights for Small Geographies? Measurement Errors and Heterogeneous Elasticities
Authors: Bluhm Richard , McCord Gordon C.
Published: March 2022

Nighttime lights are routinely used as a proxy for economic activity when official statistics are unavailable and are increasingly applied to study the effects of shocks or policy interventions at small geographic scales. The implicit assumption is that the ability of nighttime lights to pick up changes in GDP does not depend on local characteristics of the region under investigation or the scale of aggregation. This study uses panel data on regional GDP growth from six countries, and nighttime lights from the Defense Meteorological Satellite Program (DMSP) to investigate potential nonlinearities and measurement errors in the light production function. Our results for high statistical capacity countries (the United States and Germany) show that nightlights are significantly less responsive to changes in GDP at higher baseline level of GDP, higher population densities, and for agricultural GDP. We provide evidence that these nonlinearities are too large to be caused by differences in measurement errors across regions. We find similar but noisier relationships in other high-income countries (Italy and Spain) and emerging economies (Brazil and China). We also present results for different aggregation schemes and find that the overall relationship, including the nonlinearity, is stable across regions of different shapes and sizes but becomes noisier when regions become few and large. These findings have important implications for studies using nighttime lights to evaluate the economic effects of shocks or policy interventions. On average, nighttime lights pick up changes in GDP across many different levels of aggregation, down to relatively small geographies. However, the nonlinearity we document in this paper implies that some studies may fail to detect policy-relevant effects in places where lights react little to changes in economic activity or they may mistakenly attribute this heterogeneity to the treatment effect of their independent variable of interest.
Incorporation of Net Radiation Model Considering Complex Terrain in Evapotranspiration Determination with Sentinel-2 Data
Authors: Wang Linjiang , Wu Bingfang , Elnashar Abdelrazek , Zhu Weiwei , Yan Nana , Ma Zonghan , Liu Shirong , Niu Xiaodong
Published: March 2022

Evapotranspiration (ET) is the primary mechanism of water transformation between the land surface and atmosphere. Accurate ET estimation given complex terrain conditions is essential to guide water resource management in mountainous areas. This study is based on the ETWatch model driven by Sentinel-2 remote sensing data at a spatial resolution of 10 m incorporating a net radiation model considering the impact of a complex terrain. We tested our model with two years of data in two regions with a high relief near the Huairou (2020) and Baotianman (2019) weather stations. Regarding the validation results of the ET model, the coefficient of determination (R2) reached 0.84 in Huairou and 0.86 in Baotianman, while the root mean square error (RMSE) value reached 0.59 mm in Baotianman and 0.82 mm in Huairou. The validation results indicated that the model is applicable in regions with a complex terrain, and the ET results can capture topographic textures. In terms of the slope aspect, the ET value on south-facing slopes is higher than that on north-facing slopes in both study areas. Accurate ET monitoring in mountainous regions with a high relief yields a profound meaning in obtaining a better understanding of the characteristics of heat and water fluxes at different vegetation growth stages and underlying surface types, which can provide constructive suggestions for water management in mountainous areas.
Spatial Potential Energy Weighted Maximum Simplex Algorithm for Hyperspectral Endmember Extraction
Authors: Song Meiping , Li Ying , Yang Tingting , Xu Dayong
Published: March 2022

Most traditional endmember extraction algorithms focus on spectral information, which limits the effectiveness of endmembers. This paper develops a spatial potential energy weighted maximum simplex algorithm (SPEW) for hyperspectral endmember extraction, combining the relevance of hyperspectral spatial context with spectral information to effectively extract endmembers. Specifically, for pixels in a uniform spatial area, SPEW assigns a high weight to pixels with higher spatial potential energy. For pixels scattered in a spatial area, the high weights are assigned to the representative pixels with a smaller spectral angle distance. Then, the optimal endmember collection is determined by the simplex with maximum volume in the space of representative pixels. SPEW not only reduces the complexity of searching for the maximum simplex volume but also improves the performance of endmember extraction. In particular, compared with other newly proposed spatial-spectral hyperspectral endmember extraction methods, SPEW can effectively extract the hidden endmembers in a spatial area without adjusting any parameters. Experiments on synthetic and real data show that the SPEW algorithm has also provides better results than the traditional algorithms.
Modern Dryland Source-to-Sink System Segments and Coupling Relationships from Digital Elevation Model Analysis: A Case Study from the Mongolian Altai
Authors: Zeng Zhiwei , Zhu Hongtao
Published: March 2022

Source-to-sink (S2S) systems have represented a major area of research in recent years; however, few modern S2S system analyses have been applied to typical dryland uplifts/mountains. A modern lacustrine sedimentary system is widely developed in the Great Lakes Basin of western Mongolia, and the Jargalant Nuruu in the Mongolian Altai is a suitable natural laboratory for modern dryland S2S system analysis. In this study, the multi-order S2S system of the Jargalant Nuruu was applied based on a digital elevation model (DEM) and Google Earth database analysis. The Jargalant Nuruu system is subdivided into three second-order sub-S2S systems of the eastern, western, and southern parts (S2S-E, S2S-W, and S2S-S, respectively) and 35 third-order sub-S2S systems (E1–E18, W1–W9, and S1–S8) according to the slope gradients, altitude, and hydrographic net of the Jargalant Nuruu recognized by DEM data, integrated with the quantitative recognition of the topographic drainage divide and structural patterns of the uplift margin. The three second-order S2S systems correspond to three various S2S system coupling models. The S2S-E is characterized by a steep slope gradient system (average 15.61°) with small-scale dominantly alluvial fan deposits (average 4.56 km2). S2S-W is represented by a gentle slope gradient system (average 10.24°) with large-scale dominated fan-shaped lobes (average 30.04 km2). S2S-S, in contrast, is a transformation zone system with transitional features between the two former types. Four major potential controlling factors for the difference in sub-S2S systems are summarized here, including tectonic activity, bedrock properties in the source area, morphology from source to sink, and climatic conditions. The landforms, sedimentary characteristics, and their differences in these sub-S2S systems are the result of the comprehensive influence and control of these multiple factors. This case study could serve as a useful reference for characterizing the sedimentary features of a modern or even ancient S2S system in other regions.
PSPS: A Step toward Tamper Resistance against Physical Computer Intrusion
Authors: Lu Ming-Chang , Huang Qi-Xian , Chiu Min-Yi , Tsai Yuan-Chia , Sun Hung-Min
Published: March 2022

Cyberattacks are increasing in both number and severity for private, corporate, and governmental bodies. To prevent these attacks, many intrusion detection systems and intrusion prevention systems provide computer security by monitoring network packets and auditing system records. However, most of these systems only monitor network packets rather than the computer itself, so physical intrusion is also an important security issue. Furthermore, with the rapid progress of the Internet of Things (IoT) technology, security problems of IoT devices are also increasing. Many IoT devices can be disassembled for decompilation, resulting in the theft of sensitive data. To prevent this, physical intrusion detection systems of the IoT should be considered. We here propose a physical security system that can protect data from unauthorized access when the computer chassis is opened or tampered with. Sensor switches monitor the chassis status at all times and upload event logs to a cloud server for remote monitoring. If the system finds that the computer has an abnormal condition, it takes protective measures and notifies the administrator. This system can be extended to IoT devices to protect their data from theft.
Acute Effects of Self-Correction on Spine Deviation and Balance in Adolescent Girls with Idiopathic Scoliosis
Authors: Marin Luca , Lovecchio Nicola , Pedrotti Luisella , Manzoni Federica , Febbi Massimiliano , Albanese Ilaria , Patanè Pamela , Carnevale Pellino Vittoria , Vandoni Matteo
Published: March 2022

Background: Adolescent idiopathic scoliosis (AIS) is a three-dimensional deformity of spine and trunk with a higher incidence in girls. AIS alters and reduces postural control and balance. Self-correction movement (SCM) is a well-known non-invasive approach to ameliorate spine curve in AIS subjects. We aimed to evaluate the effects of SCM on the spine and on the balance of adolescents with AIS with a new non-invasive instrumentation. Methods: A total of 38 girls with AIS were recruited. To evaluate the acute effects of SCM and the oscillations of center of pressure (COP), we used LiDAR technology combined with a stabilometric platform to evaluate both changes in spinal curves and balance at the same time. Two tests were carried out simultaneously using the two instruments: before the execution of SCM, in the spontaneously assumed position of each subject (SP) and after the execution of SCM, during the achieved position (SC). Sway area, COP medio-lateral and antero-posterior directions, eccentricity of the ellipse and vertebral lateral deviation were recorded. The two conditions were compared with a Wilcoxon signed-rank test. Results: In general, all measures showed lower values in SC condition (p < 0.05), except the variation along the Y axis. Conclusions: Thanks to objective measured data, the therapists observed real-time changes during the performance of SCM, appreciating its efficacy on curve correction.
Transmission Line Vibration Damper Detection Using Multi-Granularity Conditional Generative Adversarial Nets Based on UAV Inspection Images
Authors: Chen Wenxiang , Li Yingna , Zhao Zhengang
Published: March 2022

The vibration dampers can eliminate the galloping phenomenon of transmission lines caused by the wind. The detection of vibration dampers based on visual technology is an important issue. Current CNN-based methods struggle to meet the requirements of real-time detection. Therefore, the current vibration damper detection work has mainly been carried out manually. In view of the above situation, we propose a vibration damper detection-image generation model called DamperGAN based on multi-granularity Conditional Generative Adversarial Nets. DamperGAN first generates a low-resolution detection result image based on a coarse-grained module, then uses Monte Carlo search to mine the latent information in the low-resolution image, and finally injects this information into a fine-grained module through an attention mechanism to output high-resolution images and penalize poor intermediate information. At the same time, we propose a multi-level discriminator based on the multi-task learning mechanism to improve the discriminator’s discriminative ability and promote the generator to output better images. Finally, experiments on the self-built DamperGenSet dataset show that the images generated by our model are superior to the current mainstream baselines in both resolution and quality.
Towards On-Device Dehydration Monitoring Using Machine Learning from Wearable Device’s Data
Authors: Sabry Farida , Eltaras Tamer , Labda Wadha , Hamza Fatima , Alzoubi Khawla , Malluhi Qutaibah
Published: March 2022

With the ongoing advances in sensor technology and miniaturization of electronic chips, more applications are researched and developed for wearable devices. Hydration monitoring is among the problems that have been recently researched. Athletes, battlefield soldiers, workers in extreme weather conditions, people with adipsia who have no sensation of thirst, and elderly people who lost their ability to talk are among the main target users for this application. In this paper, we address the use of machine learning for hydration monitoring using data from wearable sensors: accelerometer, magnetometer, gyroscope, galvanic skin response sensor, photoplethysmography sensor, temperature, and barometric pressure sensor. These data, together with new features constructed to reflect the activity level, were integrated with personal features to predict the last drinking time of a person and alert the user when it exceeds a certain threshold. The results of applying different models are compared for model selection for on-device deployment optimization. The extra trees model achieved the least error for predicting unseen data; random forest came next with less training time, then the deep neural network with a small model size, which is preferred for wearable devices with limited memory. Embedded on-device testing is still needed to emphasize the results and test for power consumption.
Inter-Unit Consistency and Validity of 10-Hz GNSS Units in Straight-Line Sprint Running
Authors: Chahal Amandeep Kaur , Lim Jolene Ziyuan , Pan Jing-Wen , Kong Pui Wah
Published: March 2022

The present study aimed to investigate the inter-unit consistency and validity of multiple 10-Hz Catapult Global Navigation Satellite System (GNSS) units in measuring straight-line sprint distances and speeds. A total of 13 participants performed one 45.72-m linear sprint at maximum effort while wearing all eight GNSS units at once. Total run distance and peak speed recorded using GNSS units during the sprint duration were extracted for analysis. Sprint time and peak speed were also obtained from video recordings as reference values. Inter-unit consistency was assessed using intraclass correlation coefficients (ICC) and standard errors of measurements (SEM). For a validity test, one-sample t-tests were performed to compare each GNSS unit’s distance with the known distance. Additionally, Wilcoxon signed-rank tests were performed to compare each unit’s peak speed with the reference peak speed measured using video analysis. Results showed poor inter-unit consistency for both distance (ICC = 0.131; SEM = 8.8 m) and speed (ICC = 0.323; SEM 1.3 m/s) measurements. For validity, most units recorded a total distance (44.50 m to 52.69 m) greater than the known distance of 45.72 m and a lower peak speed (7.25 (0.51) m/s) than the video-based reference values (7.78 (0.90) m/s). The present findings demonstrate that there exist variations in distance and speed measurements among different units of the same GNSS system during straight-line sprint running. Practitioners should be aware of the window of errors associated with GNSS measurements and interpret the results with caution. When making comparisons over a season, players should wear the same unit every time if logistically possible.
Dual-Wavelength Polarization-Dependent Bifocal Metalens for Achromatic Optical Imaging Based on Holographic Principle
Authors: Qu Jiaqi , Luo Huaijian , Yu Changyuan
Published: March 2022

Recently, ultrathin metalenses have attracted dramatically growing interest in optical imaging systems due to the flexible control of light at the nanoscale. In this paper, we propose a dual-wavelength achromatic metalens that will generate one or two foci according to the polarization of the incident. Based on geometric phase modulation, two unit cells are attentively selected for efficient operation at distinct wavelengths. By patterning them to two divided sections of the metalens structure plane, the dual-wavelength achromatic focusing effect with the same focal length is realized. In addition, the holographic concept is adopted for polarization-dependent bifocal generation, in which the objective wave is originated from two foci that are respectively formed by two orthogonal polarization states of circularly polarized light, namely Left-handed circularly polarized (LCP) light and Right-handed circularly polarized (RCP) light. The incident light is considered as the reference light. The achromatic focusing and polarization-dependent bifocusing are numerically verified through simulations. The proposed design opens the path for the combination of multi-wavelength imaging and chiral imaging, which may find potential applications, such as achromatic optical devices and polarization-controlled biomedical molecular imaging systems.
A Deep Learning-Based Chinese Semantic Parser for the Almond Virtual Assistant
Authors: Liao Shih-wei , Hsu Cheng-Han , Lin Jeng-Wei , Wu Yi-Ting , Leu Fang-Yie
Published: March 2022

Almond is an extendible open-source virtual assistant designed to help people access Internet services and IoT (Internet of Things) devices. Both are referred to as skills here. Service providers can easily enable their devices for Almond by defining proper APIs (Application Programming Interfaces) for ThingTalk in Thingpedia. ThingTalk is a virtual assistant programming language, and Thingpedia is an application encyclopedia. Almond uses a large neural network to translate user commands in natural language into ThingTalk programs. To obtain enough data for the training of the neural network, Genie was developed to synthesize pairs of user commands and corresponding ThingTalk programs based on a natural language template approach. In this work, we extended Genie to support Chinese. For 107 devices and 261 functions registered in Thingpedia, 649 Chinese primitive templates and 292 Chinese construct templates were analyzed and developed. Two models, seq2seq (sequence-to-sequence) and MQAN (multiple question answer network), were trained to translate user commands in Chinese into ThingTalk programs. Both models were evaluated, and the experiment results showed that MQAN outperformed seq2seq. The exact match, BLEU, and F1 token accuracy of MQAN were 0.7, 0.82, and 0.88, respectively. As a result, users could use Chinese in Almond to access Internet services and IoT devices registered in Thingpedia.
Swarm Optimization for Energy-Based Acoustic Source Localization: A Comprehensive Study
Authors: Fé João , Correia Sérgio D. , Tomic Slavisa , Beko Marko
Published: March 2022

In the last decades, several swarm-based optimization algorithms have emerged in the scientific literature, followed by a massive increase in terms of their fields of application. Most of the studies and comparisons are restricted to high-level languages (such as MATLAB®) and testing methods on classical benchmark mathematical functions. Specifically, the employment of swarm-based methods for solving energy-based acoustic localization problems is still in its inception and has not yet been extensively studied. As such, the present work marks the first comprehensive study of swarm-based optimization algorithms applied to the energy-based acoustic localization problem. To this end, a total of 10 different algorithms were subjected to an extensive set of simulations with the following aims: (1) to compare the algorithms’ convergence performance and recognize novel, promising methods for solving the problem of interest; (2) to validate the importance (in convergence speed) of an intelligent swarm initialization for any swarm-based algorithm; (3) to analyze the methods’ time efficiency when implemented in low-level languages and when executed on embedded processors. The obtained results disclose the high potential of some of the considered swarm-based optimization algorithms for the problem under study, showing that these methods can accurately locate acoustic sources with low latency and bandwidth requirements, making them highly attractive for edge computing paradigms.
Low-Area Four-Channel Controlled Dielectric Breakdown System Design for Point-of-Care Applications
Authors: Hong Jonggi , Oh Yeonji , Choi Hojong , Kim Jungsuk
Published: March 2022

In this study, we propose a low-area multi-channel controlled dielectric breakdown (CDB) system that simultaneously produces several nanopore sensors. Conventionally, solid-state nanopores are prepared by etching or drilling openings in a silicon nitride (SiNx) substrate, which is expensive and requires a long processing time. To address these challenges, a CDB technique was introduced and used to fabricate nanopore channels in SiNx membranes. However, the nanopore sensors produced by the CDB result in a severe pore-to-pore diameter variation as a result of different fabrication conditions and processing times. Accordingly, it is indispensable to simultaneously fabricate nanopore sensors in the same environment to reduce the deleterious effects of pore-to-pore variation. In this study, we propose a four-channel CDB system that comprises an amplifier that boosts the command voltage, a 1-to-4 multiplexer, a level shifter, a low-noise transimpedance amplifier and a data acquisition device. To prove our design concept, we used the CDB system to fabricate four nanopore sensors with diameters of <10 nm, and its in vitro performance was verified using λ-DNA samples.
An Efficient Dynamic Solution for the Detection and Prevention of Black Hole Attack in VANETs
Authors: Malik Abdul , Khan Muhammad Zahid , Faisal Mohammad , Khan Faheem , Seo Jung-Taek
Published: March 2022

Rapid and tremendous advances in wireless technology, miniaturization, and Internet of things (IoT) technology have brought significant development to vehicular ad hoc networks (VANETs). VANETs and IoT together play a vital role in the current intelligent transport system (ITS). However, a VANET is highly vulnerable to various security attacks due to its highly dynamic, decentralized, open-access medium, and protocol-design-related concerns. Regarding security concerns, a black hole attack (BHA) is one such threat in which the control or data packets are dropped by the malicious vehicle, converting a safe path/link into a compromised one. Dropping data packets has a severe impact on a VANET’s performance and security and may cause road fatalities, accidents, and traffic jams. In this study, a novel solution called detection and prevention of a BHA (DPBHA) is proposed to secure and improve the overall security and performance of the VANETs by detecting BHA at an early stage of the route discovery process. The proposed solution is based on calculating a dynamic threshold value and generating a forged route request (RREQ) packet. The solution is implemented and evaluated in the NS-2 simulator and its performance and efficacy are compared with the benchmark schemes. The results showed that the proposed DPBHA outperformed the benchmark schemes in terms of increasing the packet delivery ratio (PDR) by 3.0%, increasing throughput by 6.15%, reducing the routing overhead by 3.69%, decreasing the end-to-end delay by 6.13%, and achieving a maximum detection rate of 94.66%.
Signal Quality Investigation of a New Wearable Frontal Lobe EEG Device
Authors: Gao Zhilin , Cui Xingran , Wan Wang , Qin Zeguang , Gu Zhongze
Published: March 2022

The demand for non-laboratory and long-term EEG acquisition in scientific and clinical applications has put forward new requirements for wearable EEG devices. In this paper, a new wearable frontal EEG device called Mindeep was proposed. A signal quality study was then conducted, which included simulated signal tests and signal quality comparison experiments. Simulated signals with different frequencies and amplitudes were used to test the stability of Mindeep’s circuit, and the high correlation coefficients (>0.9) proved that Mindeep has a stable and reliable hardware circuit. The signal quality comparison experiment, between Mindeep and the gold standard device, Neuroscan, included three tasks: (1) resting; (2) auditory oddball; and (3) attention. In the resting state, the average normalized cross-correlation coefficients between EEG signals recorded by the two devices was around 0.72 ± 0.02, Berger effect was observed (p < 0.01), and the comparison results in the time and frequency domain illustrated the ability of Mindeep to record high-quality EEG signals. The significant differences between high tone and low tone in auditory event-related potential collected by Mindeep was observed in N2 and P2. The attention recognition accuracy of Mindeep achieved 71.12% and 74.76% based on EEG features and the XGBoost model in the two attention tasks, respectively, which were higher than that of Neuroscan (70.19% and 72.80%). The results validated the performance of Mindeep as a prefrontal EEG recording device, which has a wide range of potential applications in audiology, cognitive neuroscience, and daily requirements.
Proposed Fatigue Index for the Objective Detection of Muscle Fatigue Using Surface Electromyography and a Double-Step Binary Classifier
Authors: Qassim Hassan M. , Hasan Wan Zuha Wan , Ramli Hafiz R. , Harith Hazreen Haizi , Mat Liyana Najwa Inche , Ismail Luthffi Idzhar
Published: March 2022

The objective detection of muscle fatigue reports the moment at which a muscle fails to sustain the required force. Such a detection prevents any further injury to the muscle following fatigue. However, the objective detection of muscle fatigue still requires further investigation. This paper presents an algorithm that employs a new fatigue index for the objective detection of muscle fatigue using a double-step binary classifier. The proposed algorithm involves analyzing the acquired sEMG signals in both the time and frequency domains in a double-step investigation. The first step involves calculating the value of the integrated EMG (IEMG) to determine the continuous contraction of the muscle being investigated. It was found that the IEMG value continued to increase with prolonged muscle contraction and progressive fatigue. The second step involves differentiating between the high-frequency components (HFC) and low-frequency components (LFC) of the EMG, and calculating the fatigue index. Basically, the segmented EMG signal was filtered by two band-pass filters separately to produce two sub-signals, namely, a high-frequency sub-signal (HFSS) and a low-frequency sub-signal (LFSS). Then, the instantaneous mean amplitude (IMA) was calculated for the two sub-signals. The proposed algorithm indicates that the IMA of the HFSS tends to decrease during muscle fatigue, while the IMA of the LFSS tends to increase. The fatigue index represents the difference between the IMA values of the LFSS and HFSS, respectively. Muscle fatigue was found to be present and was objectively detected when the value of the proposed fatigue index was equal to or greater than zero. The proposed algorithm was tested on 75 EMG signals that were extracted from 75 middle deltoid muscles. The results show that the proposed algorithm had an accuracy of 94.66% in distinguishing between conditions of muscle fatigue and non-fatigue.
Effect of Strength Training Protocol on Bone Mineral Density for Postmenopausal Women with Osteopenia/Osteoporosis Assessed by Dual-Energy X-ray Absorptiometry (DEXA)
Authors: Holubiac Iulian Ștefan , Leuciuc Florin Valentin , Crăciun Daniela Maria , Dobrescu Tatiana
Published: March 2022

This study aims to introduce a resistance training protocol (6 repetitions × 70% of 1 maximum repetition (1RM), followed by 6 repetitions × 50% of 1RM within the same set) specifically designed for postmenopausal women with osteopenia/osteoporosis and monitor the effect of the protocol on bone mineral density (BMD) in the lumbar spine, assessed by dual-energy X-ray absorptiometry (DEXA). The subjects included in the study were 29 postmenopausal women (56.5 ± 2.8 years) with osteopenia or osteoporosis; they were separated into two groups: the experimental group (n = 15), in which the subjects participated in the strength training protocol for a period of 6 months; and the control group (n = 14), in which the subjects did not take part in any physical activity. BMD in the lumbar spine was measured by DEXA. The measurements were performed at the beginning and end of the study. A statistically significant increase (Δ% = 1.82%) in BMD was observed at the end of the study for the exercise group (0.778 ± 0.042 at baseline vs. 0.792 ± 0.046 after 6 months, p = 0.018, 95% CI [−0.025, −0.003]); while an increase was observed for the control group (Δ% = 0.14%), the difference was not statistically significant (0.762 ± 0.057 at baseline vs. 0.763 ± 0.059, p = 0.85, 95% CI [−0.013, 0.011]). In conclusion, our strength training protocol seems to be effective in increasing BMD among women with osteopenia/osteoporosis and represents an affordable strategy for preventing future bone loss.
Evaluation of Liposome-Loaded Microbubbles as a Theranostic Tool in a Murine Collagen-Induced Arthritis Model
Authors: Deprez Joke , Roovers Silke , Lajoinie Guillaume , Dewitte Heleen , Decruy Tine , Coudenys Julie , Descamps Benedicte , Vanhove Christian , Versluis Michel , Elewaut Dirk , Jacques Peggy , De Smedt Stefaan C. , Lentacker Ine
Published: March 2022

Rheumatoid arthritis (RA) is an autoimmune disease characterized by severe inflammation of the synovial tissue. Here, we assess the feasibility of liposome-loaded microbubbles as theranostic agents in a murine arthritis model. First, contrast-enhanced ultrasound (CEUS) was used to quantify neovascularization in this model since CEUS is well-established for RA diagnosis in humans. Next, the potential of liposome-loaded microbubbles and ultrasound (US) to selectively enhance liposome delivery to the synovium was evaluated with in vivo fluorescence imaging. This procedure is made very challenging by the presence of hard joints and by the limited lifetime of the microbubbles. The inflamed knee joints were exposed to therapeutic US after intravenous injection of liposome-loaded microbubbles. Loaded microbubbles were found to be quickly captured by the liver. This resulted in fast clearance of attached liposomes while free and long-circulating liposomes were able to accumulate over time in the inflamed joints. Our observations show that murine arthritis models are not well-suited for evaluating the potential of microbubble-mediated drug delivery in joints given: (i) restricted microbubble passage in murine synovial vasculature and (ii) limited control over the exact ultrasound conditions in situ given the much shorter length scale of the murine joints as compared to the therapeutic wavelength.
Comparative Evaluation of Membrane Filtration on the Tertiary Treatment of Synthetic Secondary Effluent
Authors: Mortula Md Maruf , Abdelrahman Malak , Tatan Bushra
Published: March 2022

Wastewater reuse is essential for sustainable water management. However, it requires tertiary treatment within the plant to ensure suitable water quality. This project aims to investigate the comparative performance of conventional tertiary treatment (sand filtration) against membrane filtration technology to demonstrate the viability of membrane treatment for wastewater reuse. Sand filtration along with two membrane filtrations, Nano Filtration (NF) and Reverse Osmosis (RO), were tested for their efficiency in removing the target pollutants: chromium, phosphate, and UV-254 from secondary effluent. Standard medium-sized laboratory setups were used. Synthetic secondary effluent was used for comparison among the different treatment processes. The synthetic effluent was compared to the real wastewater to demonstrate the reliability of using synthetic effluent. Evaluation of the role of time and pressure on the treatment efficiency was also examined. Based on the experimental results, RO had the highest removal efficiency for all pollutants with more than 90% removal. The experimental results also showed that synthetic wastewater was reliable in representing the treatability of real wastewater. Time did not seem to have an impact on the quality of filtration. Moreover, as pressure increased there was a slight increase in the efficiency. This trend was observed in all pollutants except UV-254. ANOVA showed different results of the effect of pressure on the removal efficiency in both RO and NF as well as time in NF.
n-Octyltrichlorosilane Modified SAPO-34/PDMS Mixed Matrix Membranes for Propane/Nitrogen Mixture Separation
Authors: Cai Weibin , Xie Jiangyu , Luo Jingyu , Chen Xiaohan , Wang Mingqian , Wang Yujun , Li Jiding
Published: March 2022

In this study, zeolite molecular sieve SAPO-34/polydimethylsiloxane (PDMS) mixed matrix membranes (MMMs) were prepared to recover propane. n-Octyltrichlorosilane (OTCS) was introduced to improve compatibility between SAPO-34 and PDMS, and enhance the separation performance of the MMMs. Physicochemical properties of the MMMs were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD) and water contact angle (WCA). Results showed that, after modification, alkyl chains were successfully grafted onto SAPO-34 without changing its crystal structure, particles in the MMMs were evenly distributed in the base film, and the hydrophobicity of the MMMs was enhanced. Moreover, the effects of SAPO-34 filling content, operating pressure, and feed gas concentration on the separation performance was explored. This indicated that the modification with OTCS effectively enhanced the separation performance of SAPO-34/PDMS MMMs. When the filling content of modified SAPO-34 was 15%, the maximal separation factor of 22.1 was achieved, and the corresponding propane permeation rate was 101 GPU.
Signal Detection in Nearly Continuous Spectra and ℤ2-Symmetry Breaking
Authors: Lahoche Vincent , Ousmane Samary Dine , Tamaazousti Mohamed
Published: March 2022

The large scale behavior of systems having a large number of interacting degrees of freedom is suitably described using the renormalization group from non-Gaussian distributions. Renormalization group techniques used in physics are then expected to provide a complementary point of view on standard methods used in data science, especially for open issues. Signal detection and recognition for covariance matrices having nearly continuous spectra is currently an open issue in data science and machine learning. Using the field theoretical embedding introduced in Entropy, 23(9), 1132 to reproduce experimental correlations, we show in this paper that the presence of a signal may be characterized by a phase transition with Z2-symmetry breaking. For our investigations, we use the nonperturbative renormalization group formalism, using a local potential approximation to construct an approximate solution of the flow. Moreover, we focus on the nearly continuous signal build as a perturbation of the Marchenko-Pastur law with many discrete spikes.
Hadamard-Type Inequalities for Generalized Integral Operators Containing Special Functions
Authors: Jung Chahnyong , Farid Ghulam , Yussouf Muhammad , Nonlaopon Kamsing
Published: March 2022

Convex functions are studied very frequently by means of the Hadamard inequality. A symmetric function leads to the generalization of the Hadamard inequality; the Fejér–Hadamard inequality is one of the generalizations of the Hadamard inequality that holds for convex functions defined on a finite interval along with functions which have symmetry about the midpoint of that finite interval. Lately, integral inequalities for convex functions have been extensively generalized by fractional integral operators. In this paper, inequalities of Hadamard type are generalized by using exponentially (α, h-m)-p-convex functions and an operator containing an extended generalized Mittag-Leffler function. The obtained results are also connected with several well-known Hadamard-type inequalities.
CREDO-Maze Cosmic Ray Mini-Array for Educational Purposes
Authors: Wibig Tadeusz , Karbowiak Michał
Published: March 2022

In this paper, we present the concept of local networks of small extensive air shower arrays installed mainly in secondary schools. As part of the CREDO-Maze Project, we plan to equip as many schools as possible with sets of detectors capable of detecting extensive air showers and transmitting their data to the central CREDO Project server. The synergy of such a network will make it possible to create a CREDO "global detector" and carry out physical research sensu stricto, e.g., the search for the Gerasimova–Zatsepin effect or the Cosmic Ray Ensemble. The discovery of one or the other would have extremely important consequences for our understanding of the nature of very-high-energy cosmic rays. In this paper, we describe a prototype local mini-array built at our university and some of the results of the exemplary tests performed. The design of the station’s electronics and the small size of the detectors allow it to be used to perform, with the simple addition of software, also other tasks within physics circles and student projects. The mini-array consists of four small detectors, with a simple system for triggering, recording, and online communication with the world. The station is designed for autonomous and continuous operation.