bluuebunny/crossref_metadata_2025 huggingface dataset:
Hydrolats from Humulus lupulus and Their Potential Activity as an Organic Control for Varroa destructor
Authors: Iglesias Azucena Elizabeth , Fuentes Giselle , Mitton Giulia , Ramos Facundo , Brasesco Constanza , Manzo Rosa , Orallo Dalila , Gende Liesel , Eguaras Martin , Ramirez Cristina , Fanovich Alejandra , Maggi Matias
Published: December 2022

Varroa destructor is a parasitic mite, which is considered a severe pest for honey bees causing serious losses to beekeeping. Residual hydrolats from steam extraction of hop essential oils, generally considered as a waste product, were tested for their potential use as acaricides on V. destructor. Four hop varieties, namely Cascade, Spalt, Victoria, and Mapuche, showed an interesting performance as feasible products to be used in the beekeeping industry. Some volatile oxidized terpenoids were found in the hydrolats, mainly β-caryophyllene oxide, β-linalool, and isogeraniol. These compounds, together with the presence of polyphenols, flavonoids, and saponins, were probably responsible for the promissory LC50 values obtained for mites after hydrolat exposition. Victoria hydrolat was the most toxic for mites (LC50: 16.1 µL/mL), followed by Mapuche (LC50 value equal to 30.1 µL/mL), Spalt (LC50 value equal to 114.3 µL/mL), and finally Cascade (LC50: 117.9 µL/mL). Likewise, Spalt had the highest larval survival, followed by Victoria and Mapuche. Cascade was the variety with the highest larval mortality. In addition, none of the extracts showed mortality higher than 20% in adult bees. The Victoria hydrolat presented the best results, which makes it a good compound with the prospect of an acaricide treatment against V. destructor.
Cannabis sativa Cannabinoids as Functional Ingredients in Snack Foods—Historical and Developmental Aspects
Authors: Krüger Marlize , van Eeden Tertia , Beswa Daniso
Published: December 2022

The published health benefits of Cannabis sativa has caught the attention of health-conscious consumers and the food industry. Historically, seeds have long been utilized as a food source and currently there is an increasing number of edibles on the market that contain cannabis. Cannabinoids include the psychoactive constituent, delta-9-tetrahydrocannabinol (THC), and the non-psychoactive cannabidiol (CBD) that are both compounds of interest in Cannabis sativa. This paper looks at the distribution of nutrients and phytocannabinoids in low-THC Cannabis sativa, the historical uses of hemp, cannabis edibles, and the possible side-effects and concerns related to cannabis edibles. Several authors have pointed out that even though the use of cannabis edibles is considered safe, it is important to mention their possible side-effects and any concerns related to its consumption that negatively influence consumer acceptance of cannabis edibles. Such risks include unintentional overdose by adults and accidental ingestion by children and adolescents resulting in serious adverse effects. Therefore, cannabis edibles should be specifically packaged and labelled to differentiate them from known similar non-cannabis edibles so that, together with tamperproof packaging, these measures reduce the appeal of these products to children.
Effect of Rhizome Fragment Length and Burial Depth on the Emergence of a Tropical Invasive Weed Cyperus aromaticus (Navua Sedge)
Authors: Chadha Aakansha , Florentine Singarayer K. , Dhileepan Kunjithapatham , Turville Christopher
Published: December 2022

Cyperus aromaticus (Navua sedge) is a problematic perennial weed in pastures and crops including sugarcane, banana, rice, and fruits and vegetables in tropical climates. It reproduces both via rhizomes and seeds. As a regenerative and storage organ, these rhizomes play an important part in the invasion, establishment, and persistence of this weed. To eliminate their regenerative ability, it is important to understand the regrowth potential with respect to rhizome fragment size and burial depth. This study evaluated the emergence of C. aromaticus from rhizomes in a controlled condition. Three different sizes of rhizome fragments were buried at seven depths of up to 20 cm in two soil types. The experimental measurements included (i) the time for tillers to emerge, (ii) the cumulative emergence of tillers, recorded weekly, and (iii) the number of underground emerging tillers. The cumulative shoot emergence and the number of underground tillers produced were found to be positively correlated with the initial length of the rhizome fragments and negatively correlated with the burial depth. The time for the emergence of the tillers was negatively correlated with the burial depth, and soil type had no significant effect on any of the parameters recorded. There was no emergence recorded from rhizomes buried at 15 cm depth and deeper, irrespective of their size. Our results indicate that the combination of the fragmentation of rhizomes into small pieces and a deep burial, below 15 cm, is an important aspect to control the regeneration of C. aromaticus from rhizomes, if tillage is carried out, and can therefore form a part of an integrated weed management strategy for this troublesome weed.
Citrus reticulata Leaves Essential Oil as an Antiaging Agent: A Comparative Study between Different Cultivars and Correlation with Their Chemical Compositions
Authors: Fahmy Nouran M. , Elhady Sameh S. , Bannan Douha F. , Malatani Rania T. , Gad Haidy A.
Published: December 2022

The mass-based metabolomic approach was implemented using GC-MS coupled with chemometric analysis to discriminate between the essential oil compositions of six cultivars of Citrus reticulata. The antiaging capability of the essential oils were investigated through measurement of their ability to inhibit the major enzymes hyaluronidase, collagenase, and amylase involved in aging. GC-MS analysis resulted in the identification of thirty-nine compounds including β-pinene, d-limonene, γ-terpinene, linalool, and dimethyl anthranilate as the main components. Multivariate analysis using principal component analysis (PCA) and hierarchal cluster analysis (HCA) successfully discriminated the cultivars into five main groups. In vitro antiaging activity showed that Kishu mandarin (Km) (2.19 ± 0.10, 465.9 ± 23.7, 0.31 ± 0.01 µg/mL), Cara mandarin (Cm) (3.22 ± 0.14, 592.1 ± 30.1, 0.66 ± 0.03 µg/mL), and Wm (8.43 ± 0.38, 695.2 ± 35.4, 0.79 ± 0.04%) had the highest inhibitory activity against hyaluronidase, collagenase, and amylase, respectively. Molecular docking studies on the major compounds validated the activities of the essential oils and suggested their possible mechanisms of action. Based on our result, certain cultivars of Citrus reticulata can be proposed as a promising candidate in antiaging skin care products.
Growth, Biomass Partitioning, and Photosynthetic Performance of Chrysanthemum Cuttings in Response to Different Light Spectra
Authors: Moosavi-Nezhad Moein , Alibeigi Boshra , Estaji Ahmad , Gruda Nazim S. , Aliniaeifard Sasan
Published: December 2022

Chrysanthemum (Chrysanthemum morifolium) is among the most popular ornamental plants, propagated mainly through stem cuttings. There is a lack of information regarding the impact of the lighting environment on the successful production of cuttings and underlying mechanisms. The light spectrum affects plant morphology, growth, and photosynthesis. In the present study, chrysanthemum, cv. ‘Katinka’ cuttings, were exposed to five lighting spectra, including monochromatic red (R), blue (B) lights, and multichromatic lights, including a combination of R and B (R:B), a combination of R, B, and far red (R:B:FR) and white (W), for 30 days. B light enhanced areal growth, as indicated by a higher shoot mass ratio, while R light directed the biomass towards the underground parts of the cuttings. Monochromatic R and B lights promoted the emergence of new leaves. In contrast, individual leaf area was largest under multichromatic lights. Exposing the cuttings to R light led to the accumulation of carbohydrates in the leaves. Cuttings exposed to multichromatic lights showed higher chlorophyll content than monochromatic R- and B-exposed cuttings. Conversely, carotenoid and anthocyanin contents were the highest in monochromatic R- and B-exposed plants. B-exposed cuttings showed higher photosynthetic performance, exhibited by the highest performance index on the basis of light absorption, and maximal quantum yield of PSII efficiency. Although R light increased biomass toward roots, B light improved above-ground growth, photosynthetic functionality, and the visual performance of Chrysanthemum cuttings.
Biochar Stimulated Actual Evapotranspiration and Wheat Productivity under Water Deficit Conditions in Sandy Soil Based on Non-Weighing Lysimeter
Authors: Ghanem Kholoud Z. , Hasham Mostafa M. A. , El-Sheshtawy Abdel-Nasser A. , El-Serafy Rasha S. , Sheta Mohamed H.
Published: December 2022

The major climate-related hazard to worldwide agricultural productivity is drought, which is becoming more common because of ongoing climate change, especially in the arid and semi-arid regions. Herein, we investigated the influence of biochar soil application at 0, (B1), 7.5 ha−1 (B2), and 15 t ha−1 (B3) on the productivity and drought-tolerance indices of wheat (Triticum aestivum L., cv. Sakha 93) grown in sandy soil under irrigation levels of 100 (I1), 80 (I2), and 60% (I3) of crop evapotranspiration (ETc), as well as soil properties based on non-weighing lysimeter units. Increasing water deficiency significantly decreased the actual evapotranspiration (ETa) values. A growing biochar rate caused a significant increase in ETa values, water use efficiency, and wheat productivity compared to the untreated control. Additionally, biochar supplementation revealed an improvement in soil quality as measured by the reduction in the bulk density and hydraulic conductivity with an increase in the total porosity and void ratio of the experimental soil. The correlation analysis exhibited a highly significant and positive correlation (0.98 **) between biological yield and grain yield traits. Therefore, it may be stated that these traits are the most significant components of the evaluated grain yield in wheat plants. The productivity of I1 plants was not significantly different and slightly higher than that of I2 plants. Therefore, it can be recommended that exposed wheat plants cultivated in sandy soil with I2 × B3 treatment significantly provide the highest yield while saving 20% of the irrigation water.
Impact of Crosslinking on the Characteristics of Pectin Monolith Cryogels
Authors: Nesic Aleksandra , Meseldzija Sladjana , Onjia Antonije , Cabrera-Barjas Gustavo
Published: December 2022

In this research, the pectin monoliths were prepared via the sol-gel process through different routes of crosslinking and additional freeze-drying. The crosslinking reaction was induced by the use of calcium ions in aqueous solutions and in alcohol/water solutions. The resulting pectin monoliths obtained by freeze-drying were macroporous with open cells, limited specific surface area, moderate mechanical stability and moderate biodegradation rate. The presence of alcohol in crosslinking solution significantly changed the morphology of final pectin monoliths, which was evidenced by the reduction of their pore size for one order. The specific surface area of pectin monoliths obtained through the calcium-water-alcohol route was 25.7 m2/g, the Young compressive modulus was 0.52 MPa, and the biodegradation rate was 45% after 30 days of immersion in compost media. Considering that pectin can be obtained from food waste, and its physical properties could be tailored by different crosslinking routes, the pectin monoliths could find wide application in the pharmaceutical, agricultural, medical and food industries, providing sustainable development concepts.
Use of Polystyrene Nanoparticles as Collectors in the Flotation of Chalcopyrite
Authors: Murga Romina , Rodriguez Camila , Amalraj John , Vega-Garcia Dennis , Gutierrez Leopoldo , Uribe Lina
Published: December 2022

This study proposes the use of polymeric nanoparticles (NPs) as collectors for copper sulfide flotation. The experimental phase included the preparation of two types of polystyrene-based NPs: St-CTAB and St-CTAB-VI. These NPs were characterized by Fourier-Transform Infrared (FTIR) spectroscopy and dynamic light scattering (DLS). Then, microflotation tests with chalcopyrite under different pH conditions and nanoparticle dosages were carried out to verify their capabilities as chalcopyrite collectors. In addition, the zeta potential (ZP) measurements of chalcopyrite in the presence and absence of NPs were carried out to study their interaction. Lastly, some Atomic Force Micrographs (AFM) of NPs and Scanning Electronic Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) analysis of NPs on the chalcopyrite surface were conducted to analyze the size, the morphology and their interaction. The results obtained at pH 6 and pH 8 show that the NPs under study can achieve a chalcopyrite recovery near or higher than that obtained with the conventional collector. In this study, it was possible to observe that the NPs functionalized by the imidazole group (St-CTAB-VI) achieved better performance due to the presence of this group in its composition, allowing to achieve a greater affinity with the surface of the mineral.
Synthesis and Study of Properties of Waterborne Polyurethanes Based on β-Cyclodextrin Partial Nitrate as Potential Systems for Delivery of Bioactive Compounds
Authors: Karpov Sergei V. , Dzhalmukhanova Aigul S. , Kurbatov Vladimir G. , Perepelitsina Eugenia O. , Tarasov Alexander E. , Badamshina Elmira R.
Published: December 2022

Eco-friendly waterborne polyurethanes (WPU) find wide application in agriculture as pesticide carriers, which enhances their efficiency. To provide better control of the retention time and capacity of pesticides, WPU can be modified by cyclodextrin derivatives able to form supramolecular assemblies with bioactive substances. Synthesis of WPU containing up to 15 wt.% of covalently bound β-cyclodextrin partial nitrate (CDPN) is reported in this work. Covalent bonding of CDPN to a polyurethane matrix has been proved by IR spectroscopy and size exclusion chromatography. The particle size and viscosity of the WPU dispersion have been determined. The introduction of CDPN affects molecular weight and thermal properties of WPU films. The presence of CDPN in WPU is shown to provide higher average molecular weight, wider molecular weight distribution, and larger average size of dispersed particles, compared with WPU reference samples containing 1,4-butanediol. The analysis of the rheological behavior of the obtained WPU dispersions shows that they can be classified as pseudoplastic liquids. The analysis of the thermal parameters of WPU films indicates that the introduction of 15.0 wt.% CDPN shifts the value of the glass transition temperature from −63 °C to −48 °C compared with reference samples. We believe that the results of the present study are sufficiently encouraging in terms of using CDPN-modified eco-friendly WPU as potential systems for developing the delivering agents of bioactive compounds. The application of such systems will allow the long-term contact of pesticides with the plant surface and minimize the possibility of their release into the environment.
Fixed-Time Tracking Control for Nonlinear Cascade Systems with Unknown High Powers
Authors: Ding Jiling , Zhang Weihai , Zhao Junsheng , Ma Limin
Published: December 2022

This paper investigates the global fixed-time tracking control problem of nonlinear cascade systems with unknown high powers. In the process of control design, a upper bound and a lower bound of high powers are introduced to compensate the unknown system powers, and a state feedback controller is designed under any initial system conditions. Based on the Lyapunov stability analysis method and the fixed-time stability theory, it is verified that the proposed method can regulate the output tracking error to a disc region of the origin within a fixed-time and all the closed-loop signals are bounded. At last, the effectiveness of the proposed scheme is verified by some simulation results.
A New Approach for Increasing Speed, Loading Capacity, Resolution, and Scalability of Preparative Size-Exclusion Chromatography of Proteins
Authors: Xu Yating , Pan Si , Ghosh Raja
Published: December 2022

Low speed, low capacity, and poor scalability make size-exclusion chromatography (SEC) unattractive for use in the preparative separation of proteins. We discuss a novel z2 cuboid SEC device that addresses these challenges. A z2 cuboid SEC device (~24 mL volume) was systematically compared with a conventional SEC column having the same volume and packed with the same resin. The primary objective of this study was to use the same volume of SEC medium in a much more efficient way by using the novel device. At any given flow rate, the pressure drop across the z2 cuboid SEC device was lower by a factor of 6 to 8 due to its shorter bed height and greater cross-sectional area. Under overloaded conditions, the peaks obtained during protein separation with the conventional column were poorly resolved and showed significant fronting, while those obtained with the z2 cuboid SEC device were much better resolved and showed no fronting. At any given flow rate, better resolution was obtained with the z2 cuboid SEC device, while for obtaining a comparable resolution, the flow rate that could be used with the z2 cuboid SEC device was higher by a factor of 2 to 3. Hence, productivity in SEC could easily be increased by 200 to 300% using the z2 cuboid SEC device. The scalability of the z2 cuboid SEC device was also demonstrated based on a device with a 200 mL bed volume.
Over-Generalizing, Under-Promising, and Over-Promising: Singing Sadness and Joy in the Church
Authors: Jesse Daniel
Published: December 2022

In this article, I examine the emotional content of songs sung in Christian churches. An analysis of the lyrical content of the songs that have been tracked by Christian Copyright Licensing International (CCLI) from 1988 to 2018, shows there is a definition of the Christian life that is set before the church and in turn sung by it. The word “joy” appears 37 times and the word “praise” is used 152 times in the 133 songs that comprise the contemporary praise and worship hymnody in the defined time period. In the same time frame, the word sad or any of its derivatives (sadly, sadness, etc.) never occurs in the group of songs that are being discussed. Nor is the word “sorrow” ever used. There are two conclusions that can be drawn from the lack of the use of the word sad. The first is that sadness is undervalued. The second conclusion is that the word “sad” is not a good song word, meaning that it is awkward to sing and fit in the rhythm or meter of a song. The first conclusion relates to the lexical value of a word and the second to the semantic value. To understand the emotional content of music, the texts which provide a lexical meaning need to be examined. Secondly, the semantic meaning, which is composed of the cultural connotations, needs to be considered. The first part, the lexical, is considered by looking at only the text. The second, the semantic, involves looking at how the words and music (both apart and together) conceal and reveal meanings that surpass the lexical level. Thus, the first part of the present work will look at the lyric’s words devoid of context while the second part of the essay will examine the fullness of the songs. As the semantic levels are explored, they will be brought together with the lyrics and the previous level and the question of whether there is an overpromising of joy in the songs will be answered.
A Narrative Review on Wearable Inertial Sensors for Human Motion Tracking in Industrial Scenarios
Authors: Digo Elisa , Pastorelli Stefano , Gastaldi Laura
Published: December 2022

Industry 4.0 has promoted the concept of automation, supporting workers with robots while maintaining their central role in the factory. To guarantee the safety of operators and improve the effectiveness of the human-robot interaction, it is important to detect the movements of the workers. Wearable inertial sensors represent a suitable technology to pursue this goal because of their portability, low cost, and minimal invasiveness. The aim of this narrative review was to analyze the state-of-the-art literature exploiting inertial sensors to track the human motion in different industrial scenarios. The Scopus database was queried, and 54 articles were selected. Some important aspects were identified: (i) number of publications per year; (ii) aim of the studies; (iii) body district involved in the motion tracking; (iv) number of adopted inertial sensors; (v) presence/absence of a technology combined to the inertial sensors; (vi) a real-time analysis; (vii) the inclusion/exclusion of the magnetometer in the sensor fusion process. Moreover, an analysis and a discussion of these aspects was also developed.
Multi-Channel SAR Imaging on Cruising Ships with Sub-Orbital Spaceplane
Authors: Su Li-Yang , Kiang Jean-Fu
Published: December 2022

A multi-channel synthetic aperture radar (SAR) on board a spaceplane orbiting near the top of the atmosphere is proposed to acquire images of cruising ships. Low pulse repetition frequency (PRF) is required for high-resolution wide-swath (HRWS) imaging, leading to inevitable problems of azimuth spectrum aliasing (ASA) and azimuth Doppler ambiguity (ADA). In this work, we propose a phase matching technique to solve the ASA problem in restoring the azimuth spectrum. A multi-stage compressive-sensing (CS) technique is also proposed to solve both ADA and ASA problems. Five similar types of cruising ship are simulated to verify the efficacy of the proposed approach, at different levels of signal-to-noise ratio. Indices of geometry match, intensity match, and structural similarity are used to identify different ships from the acquired SAR images.
Impacts of Extreme Temperature and Precipitation on Crops during the Growing Season in South Asia
Authors: Fan Xinyi , Zhu Duoping , Sun Xiaofang , Wang Junbang , Wang Meng , Wang Shaoqiang , Watson Alan E.
Published: December 2022

South Asia, one of the most important food producing regions in the world, is facing a significant threat to food grain production under the influence of extreme high temperatures. Furthermore, the probability of simultaneous trends in extreme precipitation patterns and extreme heat conditions, which can have compounding effects on crops, is a likelihood in South Asia. In this study, we found complex relationships between extreme heat and precipitation patterns, as well as compound effects on major crops (rice and wheat) in South Asia. We also employed event coincidence analysis (ECA) to quantify the likelihood of simultaneous temperature and crop extremes. We used the Enhanced Vegetation Index (EVI) as the primary data to evaluate the distinct responses of major crops to weather extremes. Our results suggest that while the probability of simultaneous extreme events is small, most regions of South Asia (more than half) have experienced extreme events. The regulatory effect of precipitation on heat stress is very unevenly distributed in South Asia. The harm caused by a wet year at high temperature is far greater than that during a dry year, although the probability of a dry year is greater than that of a wet year. For the growing seasons, the highest significant event coincidence rates at a low EVI were found for both high- and low-temperature extremes. The regions that responded positively to EVI at extreme temperatures were mainly concentrated in irrigated farmland, and the regions that responded negatively to EVI at extreme temperatures were mostly in the mountains and other high-altitude regions. Implications can guide crop adaptation interventions in response to these climate influences.
Parcel-Level Flood and Drought Detection for Insurance Using Sentinel-2A, Sentinel-1 SAR GRD and Mobile Images
Authors: Thapa Aakash , Horanont Teerayut , Neupane Bipul
Published: December 2022

Floods and droughts cause catastrophic damage in paddy fields, and farmers need to be compensated for their loss. Mobile applications have allowed farmers to claim losses by providing mobile photos and polygons of their land plots drawn on satellite base maps. This paper studies diverse methods to verify those claims at a parcel level by employing (i) Normalized Difference Vegetation Index (NDVI) and (ii) Normalized Difference Water Index (NDWI) on Sentinel-2A images, (iii) Classification and Regression Tree (CART) on Sentinel-1 SAR GRD images, and (iv) a convolutional neural network (CNN) on mobile photos. To address the disturbance from clouds, we study the combination of multi-modal methods—NDVI+CNN and NDWI+CNN—that allow 86.21% and 83.79% accuracy in flood detection and 73.40% and 81.91% in drought detection, respectively. The SAR-based method outperforms the other methods in terms of accuracy in flood (98.77%) and drought (99.44%) detection, data acquisition, parcel coverage, cloud disturbance, and observing the area proportion of disasters in the field. The experiments conclude that the method of CART on SAR images is the most reliable to verify farmers’ claims for compensation. In addition, the CNN-based method’s performance on mobile photos is adequate, providing an alternative for the CART method in the case of data unavailability while using SAR images.
Few-Shot Radar Emitter Signal Recognition Based on Attention-Balanced Prototypical Network
Authors: Huang Jing , Li Xiao , Wu Bin , Wu Xinyu , Li Peng
Published: December 2022

In recent years, radar emitter signal identification has been greatly developed via the utilization of deep learning and has achieved significant improvements in identification accuracy. However, with the continuous emergence of complex regime radars and the increasing complexity of the electromagnetic environment, some new kinds of radar emitter signals collected are not in sufficient quantities to satisfy the demand of deep learning. As a result, in this paper, we adopted the prototypical network (PN) belonging to metric-based meta-learning to realize few-shot radar emitter signal recognition with the aim of meeting the needs of modern electronic warfare. Additionally, considering the problems that may arise in the field of few-shot radar emitter signal recognition, such as discriminative location bias caused by a small number of base classes or the large difference between base classes and novel classes, we proposed an attention-balanced strategy to improve meta-learning. Specifically, each channel in the feature map is forced to make the same contribution in the distinguishment of different classes. In addition, for PN, taking into account that the feature vectors of each support sample in the class are different, we set a network to exploit the relation between each support sample in the same classes, and weighted each feature vector of the support samples according to the relation. Large quantities of experiments indicate that our algorithm possesses more advantages than other algorithms.
Dynamic Order Picking Method for Multi-UAV System in Intelligent Warehouse
Authors: Han Changwan , Jeon Hyeongjun , Oh Junghyun , Lee Heungjae
Published: December 2022

For the logistics environment, multi-UAV algorithms have been studied for the purpose of order picking in warehouses. However, modern order picking adopts static order picking methods that struggle to cope with increasing volumes of goods because the algorithms receive orders for a certain period of time and pick only those orders. In this paper, by using the modified interventionist method and dynamic path planning, we aim to assign orders received in real-time to multi-UAVs in the warehouse, and to determine the order picking sequence and path of each UAV. The halting and correcting strategy is proposed to assign orders to UAVs in consideration of the similarity between the UAV’s picking list and the orders. A UAV starts picking orders by using the ant colony optimization algorithm for the orders initially assigned. For additional orders, the UAV modifies the picking sequence and UAV’s path in real time by using the k-opt-based algorithm. We evaluated the proposed method by changing the parameters in a simulation of a general warehouse layout. The results show that the proposed method not only reduces completion time compared to the previous algorithm but also reduces UAV’s travel distance and the collapsed time.
Effect of a Novel Variant with Let-7c MicroRNA Gene on Litter Size in Markhoz Goats
Authors: Zergani Emel , Rashidi Amir , Rostamzadeh Jalal , Tetens Jens , Razmkabir Mohammad
Published: December 2022

This study was focused on identifying the effects of single nucleotide polymorphisms (SNPs) located on an entire region of the let-7c miRNA gene with consideration of its ability to promote litter size in Markhoz goats. The Markhoz goat, the native breed in Iran, is important for its reproductive traits, such as litter size. DNA polymorphism of let-7c miRNA gene was revealed and considered for further studies for its effect on litter size in Markhoz goats. PCR-SSCP analysis investigated different band patterns for this miRNA; however, sequencing results have detected only an A to T substitution located five nucleotides downstream of the let-7c miRNA gene. The chi-squared test showed that the let-7c miRNA gene locus was out of the Hardy–Weinberg equilibrium (HWE) and has significant effect (p < 0.05). Furthermore, the least-square analysis indicated that the let-7c miRNA gene does not affect prolificacy in the Markhoz goat (p > 0.05). In sum, all loci failed to have a significant effect on the litter size trait (p > 0.05). Moreover, years of kidding and parity had no significant impact on let-7c_S (p > 0.05); however, the let-7c_B affected the litter size trait significantly (p < 0.05). Additionally, binary logistic regression and chi-square analysis revealed that allele A of the detected SNP within 3′ UTR region of the let-7c gene had a non-significant effect on litter size in the studied goats (p > 0.05).
Multi-Target Tracking Algorithm Combined with High-Precision Map
Authors: An Qingru , Cai Yawen , Zhu Juan , Wang Sijia , Han Fengxia
Published: December 2022

On high-speed roads, there are certain blind areas within the radar coverage, especially when the blind zone is in curved road sections; because the radar does not have the measurement point information in multiple frames, it is easy to have a large deviation between the real trajectory and the filtered trajectory. In this paper, we propose a track prediction method combined with a high-precision map to solve the problem of scattered tracks when the targets are in the blind area. First, the lane centerline is fitted to the upstream and downstream lane edges obtained from the high-precision map in certain steps, and the off-north angle at each fitted point is obtained. Secondly, the normal trajectory is predicted according to the conventional method; for the extrapolated trajectory, the northerly angle of the lane centerline at the current position of the trajectory is obtained, the current coordinate system is converted from the north-east-up (ENU) coordinate system to the vehicle coordinate system, and the lateral velocity of the target is set to zero in the vehicle coordinate system to reduce the error caused by the lateral velocity drag of the target. Finally, the normal trajectory is updated and corrected, and the normal and extrapolated trajectories are managed and reported. The experimental results show that the accuracy and convergence effect of the proposed methods are much better than the traditional methods.
Robust Pulse Rate Measurements from Facial Videos in Diverse Environments
Authors: Park Jinsoo , Hong Kwangseok
Published: December 2022

Pulse wave and pulse rate are important indicators of cardiovascular health. Technologies that can check the pulse by contacting the skin with optical sensors built into smart devices have been developed. However, this may cause inconvenience, such as foreign body sensation. Accordingly, studies have been conducted on non-contact pulse rate measurements using facial videos focused on the indoors. Moreover, since the majority of studies are conducted indoors, the error in the pulse rate measurement in outdoor environments, such as an outdoor bench, car and drone, is high. In this paper, to deal with this issue, we focus on developing a robust pulse measurement method based on facial videos taken in diverse environments. The proposed method stably detects faces by removing high-frequency components of face coordinate signals derived from fine body tremors and illumination conditions. It optimizes for extracting skin color changes by reducing illumination-caused noise using the Cg color difference component. The robust pulse wave is extracted from the Cg signal using FFT–iFFT with zero-padding. It can eliminate signal-filtering distortion effectively. We demonstrate that the proposed method relieves pulse rate measurement problems, producing 3.36, 5.81, and 6.09 bpm RMSE for an outdoor bench, driving car, and flying drone, respectively.
Effect of Face Blurring on Human Pose Estimation: Ensuring Subject Privacy for Medical and Occupational Health Applications
Authors: Jiang Jindong , Skalli Wafa , Siadat Ali , Gajny Laurent
Published: December 2022

The face blurring of images plays a key role in protecting privacy. However, in computer vision, especially for the human pose estimation task, machine-learning models are currently trained, validated, and tested on original datasets without face blurring. Additionally, the accuracy of human pose estimation is of great importance for kinematic analysis. This analysis is relevant in areas such as occupational safety and clinical gait analysis where privacy is crucial. Therefore, in this study, we explore the impact of face blurring on human pose estimation and the subsequent kinematic analysis. Firstly, we blurred the subjects’ heads in the image dataset. Then we trained our neural networks using the face-blurred and the original unblurred dataset. Subsequently, the performances of the different models, in terms of landmark localization and joint angles, were estimated on blurred and unblurred testing data. Finally, we examined the statistical significance of the effect of face blurring on the kinematic analysis along with the strength of the effect. Our results reveal that the strength of the effect of face blurring was low and within acceptable limits (<1°). We have thus shown that for human pose estimation, face blurring guarantees subject privacy while not degrading the prediction performance of a deep learning model.
Feasibility of Tracking Human Kinematics with Simultaneous Localization and Mapping (SLAM)
Authors: Laal Sepehr , Vasilyev Paul , Pearson Sean , Aboy Mateo , McNames James
Published: December 2022

We evaluated a new wearable technology that fuses inertial sensors and cameras for tracking human kinematics. These devices use on-board simultaneous localization and mapping (SLAM) algorithms to localize the camera within the environment. Significance of this technology is in its potential to overcome many of the limitations of the other dominant technologies. Our results demonstrate this system often attains an estimated orientation error of less than 1° and a position error of less than 4 cm as compared to a robotic arm. This demonstrates that SLAM’s accuracy is adequate for many practical applications for tracking human kinematics.
Synthesis of High-Input Impedance Electronically Tunable Voltage-Mode Second-Order Low-Pass, Band-Pass, and High-Pass Filters Based on LT1228 Integrated Circuits
Authors: Chen Hua-Pin , Chen Shih-Jun , Chang Chih-Yang
Published: December 2022

This paper introduces two new high-input impedance electronically tunable voltage-mode (VM) multifunction second-order architectures with band-pass (BP), low-pass (LP), and high-pass (HP) filters. Both proposed architectures have one input and five outputs, implemented employing three commercial LT1228 integrated circuits (ICs), two grounded capacitors, and five resistors. Both proposed architectures also feature one high-impedance input port and three low-impedance output ports for easy connection to other VM configurations without the need for VM buffers. The two proposed VM LT1228-based second-order multifunction filters simultaneously provide BP, LP, and HP filter transfer functions at Vo1, Vo2, and Vo3 output terminals. The pole angular frequencies and the quality factors of the two proposed VM LT1228-based second-order multifunction filters can be electronically and orthogonally adjusted by the bias currents from their corresponding commercial LT1228 ICs, and can be independently adjusted in special cases. In addition, both proposed VM LT1228-based second-order multifunction filters have two independent gain-controlled BP and LP filter transfer functions at Vo4 and Vo5 output terminals, respectively. Based on the three commercial LT1228 ICs and several passive components, simulations and experimental measurements are provided to verify the theoretical predictions and demonstrate the performance of the two proposed high-input impedance electronically tunable VM LT1228-based second-order multifunction filters. The measured input 1-dB power gain compression point (P1dB), third-order IMD (IMD3), third-order intercept (TOI) point, and spurious-free dynamic range (SFDR) of the first proposed filter were −7.1 dBm, −48.84 dBc, 4.133 dBm, and 45.02 dBc, respectively. The measured input P1dB, IMD3, TOI, and SFDR of the second proposed filter were −7 dBm, −49.65 dBc, 4.316 dBm, and 45.88 dBc, respectively. Both proposed filters use a topology synthesis method based on the VM second-order non-inverting/inverting HP filter transfer functions to generate the BP, LP and HP filter transfer functions simultaneously, making them suitable for applications in three-way crossover networks.
Deep Multi-Scale Features Fusion for Effective Violence Detection and Control Charts Visualization
Authors: Mumtaz Nadia , Ejaz Naveed , Aladhadh Suliman , Habib Shabana , Lee Mi Young
Published: December 2022

The study of automated video surveillance systems study using computer vision techniques is a hot research topic and has been deployed in many real-world CCTV environments. The main focus of the current systems is higher accuracy, while the assistance of surveillance experts in effective data analysis and instant decision making using efficient computer vision algorithms need researchers’ attentions. In this research, to the best of our knowledge, we are the first to introduce a process control technique: control charts for surveillance video data analysis. The control charts concept is merged with a novel deep learning-based violence detection framework. Different from the existing methods, the proposed technique considers the importance of spatial information, as well as temporal representations of the input video data, to detect human violence. The spatial information are fused with the temporal dimension of the deep learning model using a multi-scale strategy to ensure that the temporal information are properly assisted by the spatial representations at multi-levels. The proposed frameworks’ results are kept in the history-maintaining module of the control charts to validate the level of risks involved in the live input surveillance video. The detailed experimental results over the existing datasets and the real-world video data demonstrate that the proposed approach is a prominent solution towards automated surveillance with the pre- and post-analyses of violent events.
A Wildfire Smoke Detection System Using Unmanned Aerial Vehicle Images Based on the Optimized YOLOv5
Authors: Mukhiddinov Mukhriddin , Abdusalomov Akmalbek Bobomirzaevich , Cho Jinsoo
Published: December 2022

Wildfire is one of the most significant dangers and the most serious natural catastrophe, endangering forest resources, animal life, and the human economy. Recent years have witnessed a rise in wildfire incidents. The two main factors are persistent human interference with the natural environment and global warming. Early detection of fire ignition from initial smoke can help firefighters react to such blazes before they become difficult to handle. Previous deep-learning approaches for wildfire smoke detection have been hampered by small or untrustworthy datasets, making it challenging to extrapolate the performances to real-world scenarios. In this study, we propose an early wildfire smoke detection system using unmanned aerial vehicle (UAV) images based on an improved YOLOv5. First, we curated a 6000-wildfire image dataset using existing UAV images. Second, we optimized the anchor box clustering using the K-mean++ technique to reduce classification errors. Then, we improved the network’s backbone using a spatial pyramid pooling fast-plus layer to concentrate small-sized wildfire smoke regions. Third, a bidirectional feature pyramid network was applied to obtain a more accessible and faster multi-scale feature fusion. Finally, network pruning and transfer learning approaches were implemented to refine the network architecture and detection speed, and correctly identify small-scale wildfire smoke areas. The experimental results proved that the proposed method achieved an average precision of 73.6% and outperformed other one- and two-stage object detectors on a custom image dataset.
HomeMonitor: An Enhanced Device Event Detection Method for Smart Home Environment
Authors: Zhao Meng , Chen Jie , Yang Zhikai , Liu Yaping , Zhang Shuo
Published: December 2022

As more and more smart devices are deployed in homes, the communication between these smart home devices and elastic computing services may face some risks of privacy disclosure. Different device events (such as the camera on, video on, etc.) will generate different data traffic during communication. However, the current smart home system lacks monitoring of these device events, which may cause the disclosure of private data collected by these devices. In this paper, we present our device event monitor system, HomeMonitor. HomeMonitor runs in the OpenWRT system and supports complete event monitoring for smart home devices. HomeMoitor solves the problem that machine learning models for detecting device events do not scale flexibly. It uses the network packet size and the direction of the device event for unique identification during training. When detecting, it only needs to get the packet size and timestamp and then query the policy table for signature matching to control the device events. We evaluated the effectiveness of HomeMonitor, and the experiments show that the match rate of our method is 98.8%, the false positive rate is 1.8%, and the detection time is only 16.67% for PINBALL. The results mean that our method achieves the balance of applicable protocol scope, detection performance, and detection accuracy.
Customized Textile Capacitive Insole Sensor for Center of Pressure Analysis
Authors: Ho Jong-Gab , Kim Young , Min Se-Dong
Published: December 2022

Center of pressure refers to the centroid of the ground reaction force vector detected underneath the walking foot, which is a summary measure representing body segment movements during human locomotion. In this study, we developed a cost-effective, lightweight insole-type textile capacitive sensor (I-TCPs) to analyze plantar pressure (PP) distribution and center of pressure (COP) trajectory. To test the accuracy of I-TCPs, the measured pressure data was compared with that of F-scan. The sensor performance test was divided into a static baseline test and a dynamic gait experiment, both at two different gait speeds self-selected by the subjects. Static gait results showed that I-TCPs were capable of recognizing PP segments at different gait speeds. Dynamic gait results showed an average RMSE of 1.29 ± 0.47 mm in COPx (mediolateral shift) and 12.55 ± 5.08 mm in COPy (anteroposterior shift) at a comfortable gait speed. The COP correlation between I-TCPs and F-scan was 0.54 ± 0.09 in COPx and 0.92 ± 0.04 in COPy in comfortable gait speed conditions, in which COPy values presented a stronger correlation. RMSE and correlation in fast gait speed conditions also showed similar results. The findings of this study can be the basis for future research, including rehabilitation engineering, developing ICT devices, and creating smart wearable sensors to improve quality of life for patients and healthy individuals.
Investigation of the Suitability of a Commercial Radiation Sensor for Pretherapy Dosimetry of Radioiodine Treatment Patients
Authors: O’Callaghan Janet , Cody Dervil , Cooke Jennie
Published: December 2022

Radioiodine (I-131) therapy is routinely used to treat conditions of the thyroid. Dosimetry planning in advance of I-131 therapy has been shown to improve patient treatment outcomes. However, this pretherapy dosimetry step requires multiple outpatient appointments and is not feasible for patients living at greater distances. Here, the feasibility of a commercially available smartphone-operated radiation sensor (Smart Geiger Pro, Technonia) for at-home patient pretherapy dosimetry has been investigated. The influence of both treatment-specific parameters (radioisotope activity, gamma photon energy, patient size) and external factors (sensor placement and motion) on the ability of the radiation sensor to accurately quantify radiation dose rates has been studied. The performance limits of the radiation sensor have been identified. A preliminary trial of the sensor on four I-131 patients prior to their therapy, conducted at the Nuclear Medicine/Endocrinology departments of St James’s Hospital Dublin, is also presented. A comparable performance between the low-cost radiation sensor and that of a hospital-grade thyroid uptake probe is reported. This work demonstrates the potential of low-cost commercially available radiation sensors as a solution for at-home pretherapy dosimetry for long distance patients, or indeed for hospitals who wish to implement dosimetry at reduced cost. Recommended conditions for optimum sensor performance use are presented.
Smartphone Pedometer Sensor Application for Evaluating Disease Activity and Predicting Comorbidities in Patients with Rheumatoid Arthritis: A Validation Study
Authors: Wagner Stefan R. , Gregersen Rasmus R. , Henriksen Line , Hauge Ellen-Margrethe , Keller Kresten K.
Published: December 2022

Smartphone-based pedometer sensor telemedicine applications could be useful for measuring disease activity and predicting the risk of developing comorbidities, such as pulmonary or cardiovascular disease, in patients with rheumatoid arthritis (RA), but the sensors have not been validated in this patient population. The aim of this study was to validate step counting with an activity-tracking application running the inbuilt Android smartphone pedometer virtual sensor in patients with RA. Two Android-based smartphones were tested in a treadmill test-bed setup at six walking speeds and compared to manual step counting as the gold standard. Guided by a facilitator, the participants walked 100 steps at each test speed, from 2.5 km/h to 5 km/h, wearing both devices simultaneously in a stomach pouch. A computer automatically recorded both the manually observed and the sensor step count. The overall difference in device step counts versus the observed was 5.9% mean absolute percentage error. Highest mean error was at the 2.5 km/h speed tests, where the mean error of the two devices was 18.5%. Both speed and cadence were negatively correlated to the absolute percentage error, which indicates that the greater the speed and cadence, the lower the resulting step counting error rate. There was no correlation between clinical parameters and absolute percentage error. In conclusion, the activity-tracking application using the inbuilt Android smartphone pedometer virtual sensor is valid for step counting in patients with RA. However, walking at very low speed and cadence may represent a challenge.