bluuebunny/crossref_metadata_2025 huggingface dataset:
The CCR2+ Monocyte Subsets Increase in Obese Boys but Not Girls with Abnormally High Carotid Intima-Media Thickness: A Pilot Study
Authors: Garcés-Hernández María José , Pedraza-Escudero Karen , Garibay-Nieto Nayely , Hernández-Ruiz Joselin , Prieto-Chávez Jessica Lakshmi , Arriaga-Pizano Lourdes Andrea , Villanueva-Ortega Eréndira , Escobedo Galileo , Manjarrez-Reyna Aaron Noe , López-Alvarenga Juan Carlos , Pérez-Hernández José Luis , Queipo-García Gloria
Published: September 2022

The differential contribution of monocyte subsets expressing the C-C chemokine receptor 2 (CCR2) to subclinical atherosclerosis in girls and boys is unclear. In this pilot study, we compared classical, intermediate, and nonclassical monocyte subsets expressing CCR2 in 33 obese children of both sexes aged 8 to 16 divided by carotid intima-media thickness (IMT), considering values above the 75th percentile (p75) as abnormally high IMT. Obesity was defined as body mass index above the 95th percentile according to age and sex. Flow cytometry analyses revealed that boys but not girls with IMT ≥ p75 displayed increased CCR2+ cell percentage and CCR2 expression in the three monocyte subsets, compared to boys with IMT < p75. The CCR2+ cell percentage and CCR2 expression in the three monocyte subsets significantly correlated with increased IMT and insulin resistance in boys but not girls, where the CCR2+ nonclassical monocyte percentage had the strongest associations (r = 0.73 and r = 0.72, respectively). The role of CCR2+ monocyte subpopulations in identifying an abnormally high IMT shows a marked sexual dimorphism, where boys seem to be at higher subclinical atherosclerosis risk than girls.
Electrochemical Studies of the Corrosion Behavior of Al/SiC/PKSA Hybrid Composites in 3.5% NaCl Solution
Authors: Ikubanni Peter , Oki Makanjuola , Adeleke Adekunle , Adesina Olanrewaju , Omoniyi Peter , Akinlabi Esther
Published: September 2022

The corrosion behavior of metal matrix composites (MMCs) is accelerated by the inclusion of reinforcements. Hence, this study investigates the corrosion behavior of MMCs produced from Al 6063 matrix alloy with reinforcement particulates of silicon carbide (SiC) and palm kernel shell ash (PKSA) inclusion at different mix ratios. The MMCs were synthesized using the double stir casting technique. The corrosion behaviors of the composites in NaCl solutions were studied via gravimetric analysis and electrochemical measurements. The gravimetric analysis showed fluctuating dissolution rate of the samples in NaCl solution to indicate flawed film as well as corrosion product formation over the surface of the specimens. The observed corrosion mechanism of the samples was general and pitting corrosion. The presence of reinforcements within the Al6063 matrix acted as active sites for corrosion initiation. The range of values for Ecorr and Icorr obtained in 3.5% NaCl at 24 h was between −220.62 and −899.46 mV and between 5.45 and 40.87 µA/cm2, respectively, while at 72 h, the Ecorr values ranged from 255.88 to −887.28 mV, and the Icorr ranged from 7.19 to 16.85 µA/cm2. The Nyquist and Bode plots revealed the electrochemical corrosion behavior of the samples under investigation, with predominant reactions on the surface of the samples linked to charge transfer processes. The relative resistance to corrosion of the samples depends on the thin oxide film formed on the surface of the samples.
Strength and Deformation Characteristics of Carbon Fibre Reinforced Composite Wrapped Aluminium Foam Beams
Authors: Zhang Zhizheng , Myler Peter , Zhou Erping , Zhou Ruifeng
Published: September 2022

Sandwich structures fabricated from an aluminium skinned foam enclosed within a carbon fibre reinforced composite structure have the potential application for high-performance on- and off-road automotive vehicles. The deformations and failure of these types of structures are presented, and results indicate that the application of aluminium face sheets with aluminium foam (AF) aids to prevent the delamination of the outer layers of carbon fibre reinforced polymers (CFRP). The load carrying capacity has been increased by utilising a manufacturing method to maintain the adhesion between the core and the skins until the failure stage is reached. The core shear and de-bonded issue associated with this type of sandwich structure can be addressed by this manufacture method. The peak average flexure load capacity of an aluminium foam sandwich structure (AFSS) with a completely wrapped around CFRP skin was 2800 N with a mass of 191 g. This compares favourably with previously used AFSS without the skins, which had a peak average load of 600 N and a mass of 125 g. An initial finite element model for comparison purposes has been developed to represent the structure’s behaviour and predict the associated failure loads. It is proposed that CFRP wrapped around AFSS enhances the structural performance without significant weight gain.
A Fitted Operator Finite Difference Approximation for Singularly Perturbed Volterra–Fredholm Integro-Differential Equations
Authors: Cakir Musa , Gunes Baransel
Published: September 2022

This paper presents a ε-uniform and reliable numerical scheme to solve second-order singularly perturbed Volterra–Fredholm integro-differential equations. Some properties of the analytical solution are given, and the finite difference scheme is established on a non-uniform mesh by using interpolating quadrature rules and the linear basis functions. An error analysis is successfully carried out on the Boglaev–Bakhvalov-type mesh. Some numerical experiments are included to authenticate the theoretical findings. In this regard, the main advantage of the suggested method is to yield stable results on layer-adapted meshes.
Nano-Theranostics Constructed from Terpyridine-Modified Pillar [5]arene-Based Supramolecular Amphiphile and Its Application in Both Cell Imaging and Cancer Therapy
Authors: Zhou Youjun , Yang Lu , Ma Longtao , Han Ying , Yan Chao-Guo , Yao Yong
Published: September 2022

Theranostics play an important role in cancer treatment due to its realized real-time tracking of therapeutic efficacy in situ. In this work, we have designed and synthesized a terpyridine-modified pillar [5]arenes (TP5). By the coordination of terpyridine and Zn2+, the complex TP5/Zn was obtained. Then, supramolecular amphiphile can be constructed by using host–guest complexation between a polyethylene glycol contained guest (PM) and TP5/Zn. Combining the fluorescence properties from the terpyridine group and the amphiphilicity from the system, the obtained TP5/Zn/PM can further be self-assembled into fluorescent particles with diameters of about 150 nm in water. The obtained particles can effectively load anti-cancer drugs and realize living cell imaging and a precise release of the drugs.
Extracts of Knoxia roxburghii (Spreng.) M. A. Rau Induce Apoptosis in Human MCF-7 Breast Cancer Cells via Mitochondrial Pathways
Authors: Chen Xiao-Jiao , Pu Xin-Ying , Pu Xue-Mei , Li Xue , Liu Zhi-Bo , Mei Mi-Jia , Wang Xin-Ge , Zhang Fan , Qiu Bin , Yu Jie
Published: September 2022

Knoxia roxburghii (Spreng.) M. A. Rau (KR) is a plant clinically used in traditional Chinese medicine (TCM) for the treatment of cancer. The study objectives were to examine the effects of KR extracts, petroleum ether (PET), ethyl acetate (EtoAc), butanol (n-BuOH), and H2O-soluble fractions (HSF) of the 75% EtOH extraction on A549 (non-small cell lung cancer), HepG2 (liver cancer), HeLa (cervical cancer), MCF-7 (breast cancer), and L02 (normal hepatocyte) cells. It was found that HSF exhibited the strongest cytotoxic activity against MCF-7 cells, and was accompanied by reduced mitochondrial transmembrane potential, increased levels of intra-cellular reactive oxygen species (ROS) and activated caspases, and upregulated pro-apoptotic and downregulated anti-apoptotic proteins. LC-MS analysis further showed that HSF primarily consisted of calycosin, aloe emodin, rein, maackiain, asperuloside, orientin, vicenin-2, and kaempferide, which have been mostly reported for anti-tumor activity in previous studies. In summary, the current study illustrated the effect, mechanism, and the potential major active components of KR against breast cancer.
Mixed Micellar Solubilization of Naphthol Green B Followed by Its Removal from Synthetic Effluent by Micellar-Enhanced Ultrafiltration under Optimized Conditions
Authors: Yusaf Amnah , Usman Muhammad , Siddiq Muhammad , Bakhtiar Manahil , Mansha Asim , Shaukat Saadia , Rehman Hafiza Fatima
Published: September 2022

In this manuscript, the application of cetyltrimethylammonium bromide (CTAB) and cetylpyridinium chloride (CPC) for the removal of Naphthol Green B (NGB) as a synthetic effluent has been studied. The solubilization of NGB by a single and mixed micellar system using Triton X-100 (TX-100) as a nonionic surfactant has been performed to establish both the extent of the partitioning (kx) of NGB and ultimately their respective Gibbs free energies ΔGp as well. An applied methodology, micellar-enhanced ultrafiltration (MEUF), has also been studied in different micellar media of cationic surfactants by variation in some selective parameters, such as the concentration of surfactant, electrolyte, pressure, pH, and RPM to obtain optimum conditions. The results have been analyzed by a UV/visible double beam spectrophotometer. ΔGp was found to be −39.65 kJ/mol and −47.94 kJ/mol by CTAB and CPC, respectively, in the presence of a nonionic surfactant. The maximum value of Gibbs free energy (ΔGp) of the partition was obtained by CPC. The values of the rejection coefficient (R%) and permeate flux (J) are also calculated. A maximum removal of 99.77% and 98.53% by CTAB and CPC, respectively, was obtained. It has been observed that both of the surfactants are strong candidates for NGB removal.
Magnolol as a Potential Anticancer Agent: A Proposed Mechanistic Insight
Authors: Wang Xiaofeng , Liu Qingqing , Fu Yuanfeng , Ding Ren-Bo , Qi Xingzhu , Zhou Xuejun , Sun Zhihua , Bao Jiaolin
Published: September 2022

Cancer is a serious disease with high mortality and morbidity worldwide. Natural products have served as a major source for developing new anticancer drugs during recent decades. Magnolol, a representative natural phenolic lignan isolated from Magnolia officinali, has attracted considerable attention for its anticancer properties in recent years. Accumulating preclinical studies have demonstrated the tremendous therapeutic potential of magnolol via a wide range of pharmacological mechanisms against cancer. In this review, we summarized the latest advances in preclinical studies investigating anticancer properties of magnolol and described the important signaling pathways explaining its underlying mechanisms. Magnolol was capable of inhibiting cancer growth and metastasis against various cancer types. Magnolol exerted anticancer effects through inhibiting proliferation, inducing cell cycle arrest, provoking apoptosis, restraining migration and invasion, and suppressing angiogenesis. Multiple signaling pathways were also involved in the pharmacological actions of magnolol against cancer, such as PI3K/Akt/mTOR signaling, MAPK signaling and NF-κB signaling. Based on this existing evidence summarized in the review, we have conclusively confirmed magnolol had a multi-target anticancer effect against heterogeneous cancer disease. It is promising to develop magnolol as a drug candidate for cancer therapy in the future.
Camellia Seed Cake Extract Supports Hair Growth by Abrogating the Effect of Dihydrotestosterone in Cultured Human Dermal Papilla Cells
Authors: Ma Ling , Shen Huchi , Fang Chengge , Chen Timson , Wang Jing
Published: September 2022

Autocrine and paracrine factors play key roles in the process of Androgenetic alopecia (AGA), which are secreted by balding dermal papilla cells (DPCs) after dihydrotestosterone (DHT) induction. Camellia seed cake is an oriental oil extraction byproduct, and its extract has been traditionally used to wash hair in China. This study elucidated the hair growth-promoting effects of Camellia seed cake extract (CSCE) in DHT-treated cultured DPCs and its underlying mechanisms. The effect of CSCE on cell viability and release of inflammatory factors IL-6 and IL-1α was performed on human dermal papilla cells (DPCs) incubated with DHT. Relative expression of bax, bcl-2, p53, androgen receptor (AR) and 5α- reductase type II (SRD5A2) was determined by PCR. Senescence-associated was examined by β-galactosidase (SA-β-Gal) assays. CSCE restored DHT-induced cell damage in a dose-dependent manner, and effectively reduced the production of IL-6 and IL-1α in DHT-treated DPCs. CSCE exhibited an anti-apoptotic effect, which increased the expression of bcl-2, and decreased the expressions of bax and p53 in DHT-incubated DPCs. CSCE also showed an anti-androgenic effect reversing the increase in AR and SRD5A2 expressions in DPCs driven by DHT incubation. In addition, CSCE inhibited the β-galactosidase enzyme activity and slowed down the cell senescence of DPCs which is crucial for AGA progression. In this study, we found that CSCE may have the potential to prevent and alleviate AGA by abrogating the effect of DHT in cultured DPCs.
Paradoxes of Emotional Life: Second-Order Emotions
Authors: Caeiro Antonio de Castro
Published: September 2022

Heidegger tries to explain our emotional life applying three schemes: causal explanation, mental internalisation of emotions and metaphorical expression. None of the three schemes explains emotion though. Either because the causal nexus does not always occur or because objects and people in the external world are carriers of emotional agents or because language is already on a metaphorical level. Moreover, how is it possible that there are presently emotions constituting our life without our being aware of their existence? From the analysis of boredom in its three varieties (“bored by X”, “get oneself bored”, and “it is boring”) we will get to the depth where emotions lie, trying to rouse them and to keep them awake. Although it surfaces with the force and energy of the present, every emotion has its past and future constitution. How can we understand the future of a present emotion along with its past?
FLNet: A Near-shore Ship Detection Method Based on Image Enhancement Technology
Authors: Tang Gang , Zhao Hongren , Claramunt Christophe , Men Shaoyang
Published: September 2022

In the past few years, Synthetic Aperture Radar (SAR) has been widely used to detect marine ships due to its ability to work in various weather conditions. However, due to the imaging mechanism of SAR, there is a lot of background information and noise information similar to ships in the images, which seriously affects the performance of ship detection models. To solve the above problems, this paper proposes a new ship detection model called Feature enhancement and Land burial Net (FLNet), which blends traditional image processing methods with object detection approaches based on deep learning. We first design a SAR image threshold segmentation method, Salient Otsu (S-Otsu), according to the difference between the object and the noise background. To better eliminate noise in SAR images, we further combine image processing methods such as Lee filtering. These constitute a Feature Enhancement Module (FEM) that mitigates the impact of noise data on the overall performance of a ship detection model. To alleviate the influence of land information on ship detection, we design a Land Burial Module (LBM) according to the morphological differences between ships and land areas. Finally, these two modules are added to You Only Look Once V5 (YOLO V5) to form our FLNet. Experimental results on the SAR Ship Detection Dataset (SSDD) dataset show that FLNet comparison with YOLO V5 accuracy when performing object detection is improved by 7% and recall rate by 6.5%.
Comparing Machine and Deep Learning Methods for the Phenology-Based Classification of Land Cover Types in the Amazon Biome Using Sentinel-1 Time Series
Authors: Magalhães Ivo Augusto Lopes , de Carvalho Júnior Osmar Abílio , de Carvalho Osmar Luiz Ferreira , de Albuquerque Anesmar Olino , Hermuche Potira Meirelles , Merino Éder Renato , Gomes Roberto Arnaldo Trancoso , Guimarães Renato Fontes
Published: September 2022

The state of Amapá within the Amazon biome has a high complexity of ecosystems formed by forests, savannas, seasonally flooded vegetation, mangroves, and different land uses. The present research aimed to map the vegetation from the phenological behavior of the Sentinel-1 time series, which has the advantage of not having atmospheric interference and cloud cover. Furthermore, the study compared three different sets of images (vertical–vertical co-polarization (VV) only, vertical–horizontal cross-polarization (VH) only, and both VV and VH) and different classifiers based on deep learning (long short-term memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent Units (GRU), Bidirectional GRU (Bi-GRU)) and machine learning (Random Forest, Extreme Gradient Boosting (XGBoost), k-Nearest Neighbors, Support Vector Machines (SVMs), and Multilayer Perceptron). The time series englobed four years (2017–2020) with a 12-day revisit, totaling 122 images for each VV and VH polarization. The methodology presented the following steps: image pre-processing, temporal filtering using the Savitsky–Golay smoothing method, collection of samples considering 17 classes, classification using different methods and polarization datasets, and accuracy analysis. The combinations of the VV and VH pooled dataset with the Bidirectional Recurrent Neuron Networks methods led to the greatest F1 scores, Bi-GRU (93.53) and Bi-LSTM (93.29), followed by the other deep learning methods, GRU (93.30) and LSTM (93.15). Among machine learning, the two methods with the highest F1-score values were SVM (92.18) and XGBoost (91.98). Therefore, phenological variations based on long Synthetic Aperture Radar (SAR) time series allow the detailed representation of land cover/land use and water dynamics.
Statistical Analysis of the Spatiotemporal Distribution of Lower Atmospheric Ducts over the Seas Adjacent to China, Based on the ECMWF Reanalysis Dataset
Authors: Zhou Yong , Liu Yi , Qiao Jiandong , Li Jinze , Zhou Chen
Published: September 2022

On the basis of 12 years of the European Centre for Mesoscale Weather Forecasts (ECMWF) reanalysis dataset, we statistically analyzed the spatiotemporal distribution of lower atmospheric ducts over the seas around China, and we investigated the possible generation mechanisms. The results show that the ducts’ occurrence had obvious seasonal and regional variations. Ducting events were more likely to occur in spring and summer, and the maximum occurrence rate reached 45.6%, which was closely related to the East Asian monsoon. The ducts’ altitude in continental coastal areas was lower than that far from the coast due to the dominance of surface ducts. The ducts’ thickness varied between 50 m and 450 m, and the thicker ducts were mainly concentrated in the South China Sea and the Pacific Ocean on the east side of the East China Sea near the Philippines and Taiwan. Except for a few areas, the ducts’ intensity was less than 10 M-units (an M-unit is the unit of atmospheric modified refractivity) and the diurnal variations were less pronounced. The duct formation in the lower atmosphere was related to factors such as monsoons, tropical cyclones, ocean currents, radiative cooling, and sea–land breezes.
Seasonal and Microphysical Characteristics of Fog at a Northern Airport in Alberta, Canada
Authors: Boudala Faisal S. , Wu Di , Isaac George A. , Gultepe Ismail
Published: September 2022

Reduction in visibility (Vis) due to fog is one of the deadliest severe weather hazards affecting aviation and public transportation. Nowcasting/forecasting of Vis reduction due to fog using current models is still problematic, with most using some type of empirical parameterization. To improve the models, further observational studies to better understand fog microphysics and seasonal variability are required. To help achieve these goals, the seasonal and microphysical characteristics of different fog types at Cold Lake airport (CYOD), Alberta, Canada were analyzed using hourly and sub-hourly METAR data. Microphysical and meteorological measurements obtained using the DMT Fog Monitor FM-120 and the Vaisala PWD22 were examined. The results showed that radiation fog (RF) dominates at CYOD in summer while precipitation, advection and cloud-base-lowering fogs mostly occur in fall and winter. All fog types usually form at night or early morning and dissipate after sunrise. The observed dense fog events (Vis < 400 m) were mainly caused by RF. The observed mean fog particle spectra (n(D)) for different fog types and temperatures showed bimodal n(D) (with two modes near 4 μm and 17–25 μm; the maximum total number concentration (Nd) was 100 cm−3 and 20 cm−3, respectively, corresponding to each mode). Parameterizations of Vis as a function of liquid water content (LWC) and Nd were developed using both the observed Vis and calculated Vis based on  n(D). It was found that the observed Vis was higher than the calculated Vis for warm fog with LWC > 0.1 gm−3 and most of the mass was contributed by the large drops. Based on the observed Vis, the relative error of the visibility parameterization as a function of both LWC and Nd (32%) was slightly lower than that (34%) using LWC alone for warm fogs.
Integration of Hyperspectral and Magnetic Data for Geological Characterization of the Niaqornarssuit Ultramafic Complex in West-Greenland
Authors: Kuras Agnieszka , Heincke Björn H. , Salehi Sara , Mielke Christian , Köllner Nicole , Rogass Christian , Altenberger Uwe , Burud Ingunn
Published: September 2022

The integration of imaging spectroscopy and aeromagnetics provides a cost-effective and promising way to extend the initial analysis of a mineral deposit. While imaging spectroscopy retrieves surface spectral information, magnetic responses are used to determine magnetization at both shallower and greater depths using 2D and 3D modeling. Integration of imaging spectroscopy and magnetics improves upon knowledge concerning lithology with magnetic properties, enhances understanding of the geological origin of magnetic anomalies, and is a promising approach for analyzing a prospective area for minerals having a high iron-bearing content. To combine iron diagnostic information from airborne hyperspectral and magnetic data, we (a) used an iron absorption feature ratio to model pseudo-magnetic responses and compare them with the measured magnetic data and (b) estimated the apparent susceptibility along the surface by some equivalent source modeling, and compared them with iron ratios along the surface. For this analysis, a Modified Iron Feature Depth index was developed and compared to the surface geochemistry of the rock samples in order to validate the spectral information of iron. The comparison revealed a linear increase in iron absorption feature depths with iron content. The analysis was performed by empirically modeling the statistical relationship between the diagnostic absorption features of hyperspectral (HS) image spectra of selected rock samples and their corresponding geochemistry. Our results clearly show a link between the spectral absorption features and the magnetic response from iron-bearing ultra/-mafic rocks. The iron absorption feature ratio of Fe3+/Fe2+ integrated with aeromagnetic data (residual magnetic anomaly) allowed us to distinguish main rock types based on physical properties. This separation matches the lithology of the Niaqornarssuit complex, our study area in West Greenland.
A Review of MEMS Vibrating Gyroscopes and Their Reliability Issues in Harsh Environments
Authors: Gill Waqas Amin , Howard Ian , Mazhar Ilyas , McKee Kristoffer
Published: September 2022

Micro-electromechanical systems (MEMS) vibrating gyroscopes have gained a lot of attention over the last two decades because of their low power consumption, easy integration, and low fabrication cost. The usage of the gyroscope equipped with an inertial measurement unit has increased tremendously, with applications ranging from household devices to smart electronics to military equipment. However, reliability issues are still a concern when operating this inertial sensor in harsh environments, such as to control the movement and alignment of mini-satellites in space, tracking firefighters at an elevated temperature, and assisting aircraft navigation in gusty turbulent air. This review paper focuses on the key fundamentals of the MEMS vibrating gyroscopes, first discussing popular designs including the tuning fork, gimbal, vibrating ring, and multi-axis gyroscopes. It further investigates how bias stability, angle random walk, scale factor, and other performance parameters are affected in harsh environments and then discusses the reliability issues of the gyroscopes.
Data Fusion-Based Musculoskeletal Synergies in the Grasping Hand
Authors: Olikkal Parthan , Pei Dingyi , Adali Tülay , Banerjee Nilanjan , Vinjamuri Ramana
Published: September 2022

The hypothesis that the central nervous system (CNS) makes use of synergies or movement primitives in achieving simple to complex movements has inspired the investigation of different types of synergies. Kinematic and muscle synergies have been extensively studied in the literature, but only a few studies have compared and combined both types of synergies during the control and coordination of the human hand. In this paper, synergies were extracted first independently (called kinematic and muscle synergies) and then combined through data fusion (called musculoskeletal synergies) from 26 activities of daily living in 22 individuals using principal component analysis (PCA) and independent component analysis (ICA). By a weighted linear combination of musculoskeletal synergies, the recorded kinematics and the recorded muscle activities were reconstructed. The performances of musculoskeletal synergies in reconstructing the movements were compared to the synergies reported previously in the literature by us and others. The results indicate that the musculoskeletal synergies performed better than the synergies extracted without fusion. We attribute this improvement in performance to the musculoskeletal synergies that were generated on the basis of the cross-information between muscle and kinematic activities. Moreover, the synergies extracted using ICA performed better than the synergies extracted using PCA. These musculoskeletal synergies can possibly improve the capabilities of the current methodologies used to control high dimensional prosthetics and exoskeletons.
Artificial Intelligence-Based Detection of Human Embryo Components for Assisted Reproduction by In Vitro Fertilization
Authors: Mushtaq Abeer , Mumtaz Maria , Raza Ali , Salem Nema , Yasir Muhammad Naveed
Published: September 2022

Assisted reproductive technology is helping humans by addressing infertility using different medical procedures that help in a successful pregnancy. In vitro fertilization (IVF) is one of those assisted reproduction methods in which the sperm and eggs are combined outside the human body in a specialized environment and kept for growth. Assisted reproductive technology is helping humans by addressing infertility using different medical procedures that help in a successful pregnancy. The morphology of the embryological components is highly related to the success of the assisted reproduction procedure. In approximately 3–5 days, the embryo transforms into the blastocyst. To prevent the multiple-birth risk and to increase the chance of pregnancy the embryologist manually analyzes the blastocyst components and selects valuable embryos to transfer to the women’s uterus. The manual microscopic analysis of blastocyst components, such as trophectoderm, zona pellucida, blastocoel, and inner cell mass, is time-consuming and requires keen expertise to select a viable embryo. Artificial intelligence is easing medical procedures by the successful implementation of deep learning algorithms that mimic the medical doctor’s knowledge to provide a better diagnostic procedure that helps in reducing the diagnostic burden. The deep learning-based automatic detection of these blastocyst components can help to analyze the morphological properties to select viable embryos. This research presents a deep learning-based embryo component segmentation network (ECS-Net) that accurately detects trophectoderm, zona pellucida, blastocoel, and inner cell mass for embryological analysis. The proposed method (ECS-Net) is based on a shallow deep segmentation network that uses two separate streams produced by a base convolutional block and a depth-wise separable convolutional block. Both streams are densely concatenated in combination with two dense skip paths to produce powerful features before and after upsampling. The proposed ECS-Net is evaluated on a publicly available microscopic blastocyst image dataset, the experimental segmentation results confirm the efficacy of the proposed method. The proposed ECS-Net is providing a mean Jaccard Index (Mean JI) of 85.93% for embryological analysis.
Hint-Based Image Colorization Based on Hierarchical Vision Transformer
Authors: Lee Subin , Jung Yong Ju
Published: September 2022

Hint-based image colorization is an image-to-image translation task that aims at creating a full-color image from an input luminance image when a small set of color values for some pixels are given as hints. Though traditional deep-learning-based methods have been proposed in the literature, they are based on convolution neural networks (CNNs) that have strong spatial locality due to the convolution operations. This often causes non-trivial visual artifacts in the colorization results, such as false color and color bleeding artifacts. To overcome this limitation, this study proposes a vision transformer-based colorization network. The proposed hint-based colorization network has a hierarchical vision transformer architecture in the form of an encoder-decoder structure based on transformer blocks. As the proposed method uses the transformer blocks that can learn rich long-range dependency, it can achieve visually plausible colorization results, even with a small number of color hints. Through the verification experiments, the results reveal that the proposed transformer model outperforms the conventional CNN-based models. In addition, we qualitatively analyze the effect of the long-range dependency of the transformer model on hint-based image colorization.
Ship Fire Detection Based on an Improved YOLO Algorithm with a Lightweight Convolutional Neural Network Model
Authors: Wu Huafeng , Hu Yanglin , Wang Weijun , Mei Xiaojun , Xian Jiangfeng
Published: September 2022

Ship fire is one of the greatest dangers to ship navigation safety. Nevertheless, typical detection methods have limited detection effectiveness and accuracy due to distance restrictions and ship motion. Although the issue can be addressed by image recognition algorithms based on deep learning, the computational complexity and efficiency for ship detection are tough. This paper proposes a lightweight target identification technique based on the modified YOLOv4-tiny algorithm for the precise and efficient detection of ship fires, taking into account the distinctive characteristics of ship fires and the marine environment. Initially, a multi-scale detection technique is applied to broaden the detection range and integrate deep semantic information, thereby enhancing the feature information of small targets and obscured objects and improving the detection precision. Then, the proposed algorithm employs the SE attention mechanism for inter-channel feature fusion to improve the capability of feature extraction and the precision of ship fire detection. Last but not least, picture transformation and migration learning are added to the small ship fire dataset to accelerate the convergence pace, improve the convergence effect, and reduce dataset dependence. The simulation experiments reveal that the proposed I-YOLOv4-tiny + SE model outperforms the benchmark algorithm in terms of ship fire detection accuracy and detection efficiency and that it satisfies the real-time ship fire warning criteria in demanding maritime environments.
Verification of the System for Ship Position Keeping Equipped with a Set of Anchors in Unity3d
Authors: Wnorowski Jakub , Łebkowski Andrzej
Published: September 2022

Modern computers with specialised software are able to simulate oceans with waves and sea currents, and the action of wind, gravity, ships and other vehicles. The high-level programming languages that are used in this type of software can read information from navigation devices connected to the computer (e.g., via serial ports), and proceed to use the raw data in control algorithms. More and more desktop software and simulators can use data from additional electronic devices such as pressure sensors, temperature sensors, etc. Thus, it is possible to conduct real-time communication with a PLC (programmable logic controller) and use it in simulators. In this article, a user interface designed in Unity3d is presented. The user interface was able to read data from navigation devices, which were used in a ship positioning control algorithm. Verification of the algorithm occurred during research on a real ship, which used an anchor-based positioning system. Using data obtained on the real ship, a mathematical model of anchor winches was developed. Next, the mathematical model was implemented in the simulator developed in Unity3d. The simulator contained the same environmental conditions as during the research on the real ship. The mathematical model of anchor winches and implementation developed in the simulator will allow for future research on anchor-based positioning systems (e.g., in different environmental conditions). The research resulted in a shift of the ship’s position by 26.3 m under 280 degrees. The difference in arrival time to the target point between the real ship and the virtual ship was 19%, and the difference in position deviation was 330%.
Growth Promotion of Guava “Pear” (Psidium guajava cv.) by Sinorhizobium mexicanum in Southern Mexican Agricultural Fields
Authors: Rincón-Molina Clara Ivette , Martínez-Romero Esperanza , Manzano-Gómez Luis Alberto , Rincón-Rosales Reiner
Published: September 2022

Biofertilizers formulated with nitrogen-fixing bacteria represent an alternative to chemical fertilizers because they increase soil fertility and protect the environment. Therefore, the objective of this study was to analyze the effects on the growth of guava “pear” (Psidium guajava cv.) after inoculation with a nitrogen fixing bacterium Sinorhizobium mexicanum ITTG-R7T. The study was carried out in an agricultural rural area of Chiapas, Mexico, where farmers do not have programs of regenerative agriculture. First, the agricultural soil was subjected to physicochemical and metagenomic analysis in order to determine the soil quality and its bacterial community composition. Likewise, multifunctional biochemical tests and plant inoculation assays were evaluated to determine the potential of S. mexicanum ITTG-R7T as plant-growth-promoting bacteria (PGPB). The site was rain fed and had silty clay loam soil with abundant Bacillaceae. S. mexicanum ITTG-R7T showed different properties as PGPB such as the production of indole compounds, synthesis of extracellular enzymes, phosphate solubilization, synthesis of siderophores, ACC (1-aminocyclopropane-1-carboxylate) deaminase, and nitrogenase activity (ARA). When the strain ITTG-R7 T was combined with chemical nutrients, it had the highest positive effect on the growth and development of guava plants. Guava biofertilization with ITTG-R7T had a significant influence (p < 0.05) mainly on the total plant height (368.83 cm), number of flowers (36.0) and the amount of chlorophyll (2.81 mg mL−1) in comparison with the other treatments evaluated. ITTG-R7T is a promising strain for improving the guava crop yield.
An Empirical Analysis of the Relationships among Participatory Decision Making and Employees’ Task Performance and Personal Growth
Authors: Kim Jeong Sik
Published: September 2022

Due to rapid changes in technology and the resulting increase in uncertainty, the organization is becoming more horizontal, and participatory decision making as an effective method of decision making has attracted more attention. This study empirically explored and verified the path through which participatory decision-making leads to employees’ task performance and personal growth. The author focused on the sequential mediating role of perceived job meaningfulness and job involvement. Hypotheses were tested using survey data from 453 supervisor–subordinate dyads within organizations, across multiple industrial sectors. The results confirmed the direct and indirect relationships between participatory decision making and employees’ task performance and personal growth. Additionally, perceived job meaningfulness and job involvement were found to sequentially mediate the relationship between participatory decision making and task performance, and that between participatory decision making and personal growth. This study empirically demonstrates the necessity and importance of participatory decision making and suggests a specific mechanism. Furthermore, it presents implications for using participatory decision making in organizations effectively.
Machine-Learning-Based Suitability Prediction for Mobile Applications for Kids
Authors: Meng Xianjun , Li Shaomei , Malik Muhammad Mohsin , Umer Qasim
Published: September 2022

Digital media has a massive presence in the modern world, and it significantly impacts kids’ intellectual, cognitive, ethical, and social development. It is nearly impossible to isolate kids from digital media. Therefore, adult content on mobile applications should be avoided by children. Although mobile operating systems provide parental controls, handling such rules is impossible for illiterate people. Consequently, kids may download and use adults’ mobile applications. Mobile applications for adults often publish age group information to distinguish user segments that can be used to automate the downloading process. Sustainable Development Goal (SDG) #4 emphasizes inclusivity and equitability in terms of quality of education and the facilitation of conditions for the promotion of lifelong learning for everyone. The current study can be counted as being in line with SDG#4, as it proposes a machine-learning-based approach to the prediction of the suitability of mobile applications for kids. The approach first leverages natural language processing (NLP) techniques to preprocess user reviews of mobile applications. Second, it performs feature engineering based on the given bag of words (BOW), e.g., abusive words, and constructs a feature vector for each mobile app. Finally, it trains and tests a machine learning algorithm on the given feature vectors. To evaluate the proposed approach, we leverage the 10-fold cross-validation technique. The results of the 10-fold cross-validation indicate that the proposed solution is significant. The average results of the exploited metrics (precision, recall, and F1-score) are 92.76%, 99.33%, and 95.93%, respectively.
Review of the Organizational Structures of the Trail Running, Skyrunning and Mountain Running Modalities in Spain
Authors: López-García Sergio , Muriel-Isidro Jaime , Ruibal-Lista Brais , Maneiro Rubén , Amatria-Jiménez Mario
Published: September 2022

The purpose of this research was to analyze the organizational structures of the different federations and entities representing the modalities of trail-running, skyrunning, and mountain running and how they have settled in the current sports landscape. The main task of these entities is to act as hosts of the legally established modalities, both internationally and nationally, applying their respective regulations and statutes unilaterally. Through an in-depth review of the different regulations, statutes, and current articles of all the organizations that represent the different disciplines, we can observe how a sport modality that seems to be the same is nevertheless distant in its execution (regulations, championships, classifications, systems of points, etc.), which has led to the international level being established in different sport modalities (trail running and skyrunning). At the level of the Spanish territory, it has led to an administrative dispute to know who has the powers to approve sports competitions.
Petrotympanic Fissure Architecture and Malleus Location in Temporomandibular Joint Disorders
Authors: Almășan Oana , Leucuța Daniel-Corneliu , Dinu Cristian , Buduru Smaranda , Băciuț Mihaela , Hedeșiu Mihaela
Published: September 2022

The aim of this research was to assess possible relationships between petrotympanic fissure (PTF) characteristics, malleus position, and temporomandibular joint disorders (TMD). A retrospective study was performed, including patients with TMD. Magnetic resonance imaging (MRI) and cone-beam computed tomography (CBCT) examination were used to evaluate temporomandibular joint (TMJ) disc position and condylar bone changes. Fifty-eight TMJs from twenty-nine patients (23:6 females: males) were assessed. Erosive changes (DDR-disc displacement with a reduction of 6 (24%), DDwR-disc displacement without a reduction of 8 (61.5%) vs. normal disc position 3 (15%), p = 0.012) and condyle osteophytes production (DDR 6 (24%), DDwR 9 (69.2%) vs. normal condyle 7 (35%), p = 0.012) were more frequent in subjects with disc displacement compared to normal disc position; malleus was closer to PTF in cases with erosive changes (median 2.15 interquartile range: (1.85–2.75) vs. 2.75 (2.25–3.15), p = 0.029) as well as those with condylar osteophytosis (2.25 (1.91–2.75) vs. 2.75 (2.33–3.32), p = 0.015); the PTF length was higher in cases with condylar osteophytosis compared to those without (4.45 (3.50–4.77) vs. 3.67 (3.34–4.28), p = 0.039). The disc position and disc shape were not related to PTF or malleus position. Malleus position and PTF dimensions were not associated with the PTF type. In cases with erosive changes and condylar osteophytosis, malleus was closer to PTF.
Toxicological Aspects of Methotrexate Intoxication: Concentrations in Postmortem Biological Samples and Autopsy Findings
Authors: Szpot Paweł , Wachełko Olga , Zawadzki Marcin
Published: September 2022

The aim of this study was the establishment of a UHPLC-QqQ-MS/MS method to determine methotrexate in postmortem biological samples and quantify the postmortem distribution of methotrexate in a case of fatal intoxication of this drug. A volume of 100 μL or 100 mg of postmortem specimens was precipitated with 400 μL of cold methanol and then analyzed using UHPLC-QqQ-MS/MS. The validation parameters of the method were as follows: limit of quantification: 0.1–1.0 ng/mL or ng/g, coefficient of determination: >0.998 (R2), matrix effect, intra- and inter-day accuracies and precisions: not greater than 13.6%, 14.8% and 17.4%, respectively. The recoveries were: 89.0–113.6%. The postmortem distribution studies revealed methotrexate concentrations as follows: blood—7.2 ng/mL, vitreous humor—0.8 ng/mL, liver—43.7 ng/g, kidney—20.6 ng/g, bone marrow—29.9 ng/g, lumbar vertebra—20.0 ng/g. The highest concentrations of methotrexate after poisoning were found in the tissues with the most rapidly dividing cells. The method described is simple, precise and selective. Methotrexate concentrations can be routinely determined in postmortem specimens. Determination of methotrexate in the postmortem biological material is possible after a few days of intensive treatment.
Long-Standing International Cooperation in Parasitology Research: A Summary of 35 Years of Activities in the Bolivian Chaco
Authors: Gabrielli Simona , Macchioni Fabio , Spinicci Michele , Strohmeyer Marianne , Roselli Mimmo , Nicoletti Alessandra , Cicero Calogero Edoardo , Poma Veronica , Rojo David , Lara Yunni , Gómez Elizabeth Blanca Crespo , Rojas Patricia , Gamboa Herlan , Villagran Ana Liz , Cosmi Francesco , Monasterio Joaquín , Cancrini Gabriella , Bartoloni Alessandro
Published: September 2022

The Bolivian Chaco is a semiarid region with a low population density, situated in the southeast part of the Plurinational State of Bolivia. Here, despite the improvements of the last 15 years, poverty remains high in rural areas, where social vulnerability is widespread. The Guaraní ethnic group often lives in isolated communities with a low standard of hygiene and sanitation. This epidemiological scenario favors the spread of transmissible diseases, including several parasitic infections belonging to the neglected tropical diseases (NTDs) group. In this area, a long-standing research activity, built upon the synergism between local and foreign institutions, has been established since the late 1980s and helps to fill in the knowledge gap about the epidemiology dynamics of soil-transmitted helminths, vector-borne parasites, and other parasitic diseases. A 35-year history of cooperation programs in parasitology research has contributed to informing local health authorities of the NTD burden in the Bolivian Chaco and, ultimately, supports local healthcare providers in the management of parasitic diseases.
Studi Perbandingan Kemampuan Pemecahan Masalah Siswa Menggunakan Model Pembelajaran Problem Based Learning Dan Problem Solving
Authors: Sabora Ririn S. , Lukum Astin , Paputungan Mardjan , Iyabu Hendri , Aman La Ode , Alio La
Published: September 2022

Tujuan penelitian adalah untuk Adapun tujuan dari penelitian ini adalah untuk: Mengetahui perbedaan signifikan antara kemampuan pemecahan masalah siswa yang menerapkan model pembelajaran Problem Based Learning dan Problem Solving di SMAT Wira Bhakti. Desain penelitian yang digunakan adalah Quasi Eksperimental dengan rancangan pretest-posttest control group design. Sampel pada penelitian ini berjumlah 40 siswa yaitu sebanyak 20 siswa pada kelas eksperimen I dan 20 siswa pada kelas eksperimen II. Berdasarkan hasil yang diperoleh dari uji t, nilai thitung sebesar 4,9774 dan nilai ttabel pada taraf α = 0,05; dk = 38 diperoleh sebesar 1,68595. Dengan demikian thitung dilihat lebih besar dari ttabel (thitung = 4,9774 ˃ ttabel =1,68595) sehingga H0 ditolak dengan arti lain bahwa H1 diterima. artinya terdapat adanya perbedaan signifikan antara kemampuan pemecahan masalah siswa pada pokok bahasan hukum-hukum dasar kimia antara kelas yang menerapkan model pembelajaran problem based learning dan kelas yang menerapkan model pembelajaran problem solving di SMA Terpadu Wira Bhakti.
Nilai Tukar Petani Komoditas Tanaman Pangan Dan Faktor-Faktor Yang Mempengaruhinya Di Provinsi Jawa Barat Tahun 2008 – 2020
Authors: Gunawan Indra , Nataliningsih Nataliningsih , Sukmawati Dety , Dahtiar Agi
Published: September 2022

This study aims to analyze the exchange rate of farmers and the factors that influence it in West Java province in 2008 – 2020. The variables studied were land area, rice productivity, fertilizer cost and seed cost. The research method used is the study of literature by examining secondary data published nationally and regionally from various valid and credible sources derived from the Central Statistics Agency, the Department of food crops and Horticulture of West Java Province, the Ministry of Agriculture and others. The study was conducted in the period between November 2021 and March 2022. Data processing is done using Least Squares analysis with the help of E-Views 9 Software. The results showed that the exchange rate of farmers of food crops in West Java Province in the period from 2008 to 2020 was influenced simultaneously by land area, rice productivity, fertilizer cost and seed cost. But partially, the variable land area does not significantly affect the exchange rate of food crop farmers. Variable rice productivity, fertilizer costs and seed costs partially significantly affect the exchange rate of farmers of food crops in West Java.