bluuebunny/crossref_metadata_2025 huggingface dataset:
Strategies to detect and manage latent tuberculosis infection among household contacts of pulmonary TB patients in high TB burden countries ‐ a systematic review and meta‐analysis
Authors: Sagili Karuna Devi , Muniyandi Malaisamy , Shringarpure Kalpita , Singh Kavita , Kirubakaran Richard , Rao Raghuram , Tonsing Jamhoih , Sachdeva Kuldeep Singh , Tharyan Prathap
Published: August 2022

Objective

To summarise latent tuberculosis infection (LTBI) management strategies among household contacts of bacteriologically confirmed pulmonary tuberculosis (TB) patients in high‐TB burden countries.

Methods

PubMed/MEDLINE (NCBI) and Scopus were searched (January 2006 to December 2021) for studies reporting primary data on LTBI management. Study selection, data management and data synthesis were protocol‐driven (PROSPERO‐CRD42021208715). Primary outcomes were the proportions of LTBI, initiating and completing tuberculosis preventive treatment (TPT). Reported factors influencing the LTBI care cascade were qualitatively synthesised.

Results

From 3694 unique records retrieved, 58 studies from 23 countries were included. Most identified contacts were screened (median 99%, interquartile range [IQR] 82%–100%; 46 studies). Random‐effects meta‐analysis yielded pooled proportions for: LTBI 41% (95% confidence interval [CI] 33%–49%; 21,566 tested contacts); TPT initiation 91% (95% CI 79%–97%; 129,573 eligible contacts, 34 studies); TPT completion 65% (95% CI 54%–74%; 108,679 TPT‐initiated contacts, 28 studies). Heterogeneity was significant (I2 ≥ 95%–100%) and could not be explained in subgroup analyses. Median proportions (IQR) were: LTBI 44% (28%–59%); TPT initiation 86% (60%–100%); TPT completion 68% (44%–82%). Nine broad themes related to diagnostic testing, health system structure and functions, risk perception, documentation and adherence were considered likely to influence the LTBI care cascade.

Conclusion

The proportions of household contacts screened, detected with LTBI and initiated on TPT, though variable was high, but the proportions completing TPT were lower indicating current strategies used for LTBI management in high TB burden countries are not sufficient.
Mechanical evaluation of canine sacroiliac joint stabilization using two short screws
Authors: Hanlon John , Hudson Caleb C. , Litsky Alan S. , Jones Stephen C.
Published: August 2022

Objective

To assess the feasibility and mechanical stability of sacroiliac (SI) joint stabilization using 2 short 3.5 mm cortical screws, each spanning an average of 23% of the width of the sacral body.

Study design

Cadaveric experimental study.

Sample population

Twenty‐four canine pelvis specimens.

Methods

Pelvis specimens were prepared by disarticulation of the left SI joint and osteotomy of the left pubis and left ischium, and stabilized using a single long lag screw (LLS), 2 short lag screws (SLS) or 2 short positional screws (SPS). Computed tomography (CT) imaging was used to determine standardized screw lengths for each group and was repeated following implant insertion. Specimens were secured within a servohydraulic test frame and loaded through the acetabulum to simulate weight bearing under displacement control at 4 mm/min for 20 mm total displacement. Group mechanical testing data were compared.

Results

Peak load, yield load, and stiffness were more than 2 times greater in both the SLS and SPS groups when compared with the LLS group. No mechanical difference was identified between the short‐screw groups.

Conclusion

Sacroiliac luxation fixation using 2 short screws created a stronger, stiffer construct when compared with fixation using a single lag screw spanning 60% of the width of the sacral body. No mechanical advantage was observed between short screws inserted in positional vs. lag fashion.

Clinical significance

Sacroiliac luxation fixation using 2 short screws creates a mechanically superior construct with a larger region of acceptable implant positioning and potentially reduced risk of iatrogenic injury compared with conventional fixation.
Mechanical Behaviour of Cancellous bone: Compression and Three-Point Bending Test
Authors: Mohd Ghazali Farah Amira , Syahrom Ardiyansyah
Published: August 2022

The mechanical properties of cancellous bone are fundamental in providing structural support and flexibility during physical activities. Characterization of cancellous bone properties and its mechanical behaviour were found crucial as information of the elastic and failure properties of the tissue may potentially be used to study the effects of drug treatments, aging and disease at the tissue level. This study aims to present the difference of mechanical properties of cancellous bone between compressive and three-point bending loads. Cancellous bone specimens from the femoral and tibial condyles of bovines were mechanically tested using three-point bending test and compression test and correlated with morphological parameters such as bone volume fraction and porosity. From the results, significant difference of mechanical properties was found between cancellous bone specimens tested with compressive and three-point bending load. From compressive load, the maximum stress reached 4.2 MPa, whereas in three-point bending, maximum flexural stress reached 17.0 MPa. Cancellous bone strength was found to be much higher when tested with three-point bending load, although correlations with morphological parameters such as bone volume fraction (BV/TV) and porosity were found lower compared to that in compressive load. In conclusion, there are no correlation between compression and three-point bending with morphology indices (BV/TV and porosity).
The Feasibility of Using Human Primary Chondrocytes Derived from Osteoarthritic Patients Overexpressed with SOX9 Seeded on PLGA-Fibrin Hybrid Scaffolds for Cartilage Engineering
Authors: Mohamad Sukri Norhamiza , Sha'ban Munirah , Ahmad Radzi Muhammad Aa’zamuddin , Abdul Rahman Rozlin , Zulkifly Ahmad Hafiz
Published: August 2022

This study aimed to find an optimal formulation to form 3D hyaline-like cartilage substitutes using the tissue engineering triads. The primary cells taken from osteoarthritic patients were overexpressed with transcriptional factor SRY (Sex Determining Region Y)-Box 9 (SOX9) using Lipofectamine 2000™ through a non-viral transfection method. The transfected and non-transfected cells were seeded on poly(lactic-co-glycolic acid) (PLGA) based scaffolds with and without fibrin. The arrangement resulted in four experimental groups. The 3D ‘cells-scaffolds’ tissue constructs were cultured for three weeks and implanted ectopically in nude mice for four weeks. The evaluations include macroscopic and microscopic study, gene expression analyses, and sulfated glycosaminoglycan (sGAG) assay, focusing on the cartilage properties. A biomechanical evaluation was performed only on post-implanted constructs. All in vitro, two- and four-week post-implanted constructs exhibited firm and smooth hyaline-like cartilage appearance. In vitro constructs showed sparse cells distribution with minimal cartilaginous tissue formation. However, a high density, lacunae-encapsulated chondrocytes embedded within the basophilic ground substances was observed in all post-implanted constructs. It is supported by positive-brownish precipitation immunolocalisation against collagen type II. Besides, molecular analysis showed that COL2A1 and other cartilaginous markers were also expressed. Increased sGAG content and compressive strain could be observed in vitro and in vivo. Although quantitatively, no significant statistical differences were found between the four groups, the qualitative results indicated that SOX9-overexpressed cells, PLGA, and fibrin combination guides hyaline-like cartilage formation better than other groups. Hence, the combination may be studied in a big animal model to develop its potential for future clinical application.
Modeling of Traffic Flow on Roundabouts
Authors: Cheah Yuat Hoong , Yeak Su Hoe
Published: August 2022

The aim of this research is to create the modeling of roundabouts. First of all, the three-arm roundabout is created for validation with the existing model. Then, the model is expanded to the four-arm roundabout. In the development of a modern intelligent transportation system, the effectiveness of dealing with the non-linear, time-varying and congested traffic flow is imperative in achieving traffic control and accuracy. In this paper, the roundabout is modelled as a circuit of 2×2 junction comprising a main lane and a secondary lane. The rotation of the roundabout is in the clockwise direction, as in the case of Malaysia. In mathematical modelling, the traffic flow is created, based on one-dimensional hyperbolic conservation laws which are represented by non-linear partial differential equations where the unknown variable is a conserved quantity. As a scheme used in the computation and analysis, the Godunov method computes the fluxes at the interfaces of each cell in order to advance the solution of a Riemann Problem. In addition, the Courant-Friedrichs-Levy (CFL) condition is proposed and used to ensure the stability and accuracy of the numerical algorithm where the time step is not a constant. The optimization on the roundabout for Total Travel Time and Total Waiting Time with several parameters is applied to generate numerous results which will assist in assessing the reasonableness of the roundabout. The comparison data of the three-arm roundabout with our model and the existing model are discussed. In comparison, our results show similar properties with higher readings than in other published papers because our calculations involved all arms and roads. In addition, the comparison data between three-arm and four-arm roundabouts are reasonable and logical. Lastly, our model is more flexible and realistic, as compared to the existing model.
Electrodeposition Technique to Fabrication CIGS using Pure Selenium and SeO2 as Selenium Source
Authors: Rahmawati Hilda , Abadi M. Tommy Hasan , Zulaikah Siti , Mufti Nandang
Published: August 2022

Energy demands are increasing day by day because almost all equipment that supports human activities uses electrical energy. CIGS solar cells are an energy source that is environmentally friendly, renewable, and has high efficiency. Selenium is one of the materials used in making solar cell CIGS. However, researchers often find the problems of this material hard to dissolve compared to other materials (copper, indium, and gallium). Therefore, in this study, pure selenium will be synthesized to produce selenium dioxide (SeO2) as a material for making solar cell CIGS with electrodeposition. The XRF  showed the resulting selenium dioxide of 99.077%, SEM-EDX showed At% selenium from SeO2 greater than pure selenium, XRD showed CIGS orientation on (211) and (105).
Optimal Repair Rate for a Repairable Machine with Nonlinear State Equation
Authors: Al-Matar Najeeb , Tadj Lotfi
Published: August 2022

This work deals with two models of a single machine subject to breakdowns. The first model is a binary-state model while the second one is a multi-state model. Breakdowns are followed by repairs. The systems under study are of the tracking type. We use nonlinear model predictive control to determine the optimal repair rates that keep the variables as close as possible to their target. Numerical illustrations with sensitivity analysis are used to assess the effect of the system parameters on the optimal solution.
Autoencoding Conditional GAN for Portfolio Allocation Diversification
Authors: Lu Jun , Yi Shao
Published: August 2022

Over the decades, the Markowitz framework has been used extensively in portfolio analysis though it puts too much emphasis on the analysis of the market uncertainty rather than on the trend prediction. While generative adversarial network (GAN) and conditional GAN (CGAN) have been explored to generate financial time series and extract features that can help portfolio analysis. The limitation of the CGAN framework stands in putting too much emphasis on generating series rather than keeping features that can help this generator. In this paper, we introduce an autoencoding CGAN (ACGAN) based on deep generative models that learns the internal trend of historical data while modeling market uncertainty and future trends. We evaluate the model on several real-world datasets from both the US and Europe markets, and show that the proposed ACGAN model leads to better portfolio allocation and generates series that are closer to true data compared to the existing Markowitz and CGAN approaches.
Melanin‐concentrating hormone regulates the hypercapnic chemoreflex by acting in the lateral hypothalamic area
Authors: Rodrigues Laísa T. C. , Patrone Luis Gustavo A. , Gargaglioni Luciane H. , Dias Mirela B.
Published: August 2022

New Findings

What is the central question of this study?

Melanin‐concentrating hormone (MCH) suppresses the hypercapnic chemoreflex: what is the mechanism by which this effect is produced?

What is the main finding and its importance?

MCH acting in the lateral hypothalamic area but not in the locus coeruleus in rats, in the light period, attenuates the hypercapnic chemoreflex. The data provide new insight into the role of MCH in the modulation of the hypercapnic ventilatory response.

Melanin‐concentrating hormone (MCH) is a hypothalamic neuropeptide involved in a broad range of homeostatic functions including regulation of the hypercapnic chemoreflex. We evaluated whether MCH modulates the hypercapnic ventilatory response by acting in the lateral hypothalamic area (LHA) and/or in the locus coeruleus (LC). Here, we measured pulmonary ventilation (), body temperature, electroencephalogram (EEG) and electromyogram (EMG) of unanaesthetized adult male Wistar rats before and after microinjection of MCH (0.4 mM) or MCH receptor 1 (MCH1‐R) antagonist (SNAP‐94847; 63 mM) into the LHA and LC, in room air and 7% CO2 conditions during wakefulness and sleep in the dark and light periods. MCH intra‐LHA caused a decreased CO2 ventilatory response during wakefulness and sleep in the light period, while SNAP‐94847 intra‐LHA increased this response, during wakefulness in the light period. In the LC, MCH or the MCH1‐R antagonist caused no change in the hypercapnic ventilatory response. Our results suggest that MCH, in the LHA, exerts an inhibitory modulation of the hypercapnic ventilatory response during the light‐inactive period in rats.
A change of heart: Mechanisms of cardiac adaptation to acute and chronic hypoxia
Authors: Williams Alexandra M. , Levine Benjamin D. , Stembridge Mike
Published: August 2022

Over the last 100 years, high‐altitude researchers have amassed a comprehensive understanding of the global cardiac responses to acute, prolonged and lifelong hypoxia. When lowlanders are exposed to hypoxia, the drop in arterial oxygen content demands an increase in cardiac output, which is facilitated by an elevated heart rate at the same time as ventricular volumes are maintained. As exposure is prolonged, haemoconcentration restores arterial oxygen content, whereas left ventricular filling and stroke volume are lowered as a result of a combination of reduced blood volume and hypoxic pulmonary vasoconstriction. Populations native to high‐altitude, such as the Sherpa in Asia, exhibit unique lifelong or generational adaptations to hypoxia. For example, they have smaller left ventricular volumes compared to lowlanders despite having larger total blood volume. More recent investigations have begun to explore the mechanisms underlying such adaptive responses by combining novel imaging techniques with interventions that manipulate cardiac preload, afterload, and/or contractility. This work has revealed the contributions and interactions of (i) plasma volume constriction; (ii) sympathoexcitation; and (iii) hypoxic pulmonary vasoconstriction with respect to altering cardiac loading, or otherwise preserving or enhancing biventricular systolic and diastolic function even amongst high altitude natives with excessive erythrocytosis. Despite these advances, various areas of investigation remain understudied, including potential sex‐related differences in response to high altitude. Collectively, the available evidence supports the conclusion that the human heart successfully adapts to hypoxia over the short‐ and long‐term, without signs of myocardial dysfunction in healthy humans, except in very rare cases of maladaptation.

image
Interpolated Moduli Adjustment Technique for Limit Loads
Authors: Mangalaramanan Sathya Prasad
Published: August 2022

A method to determine lower and upper bound limit loads called interpolated moduli adjustment technique (IMAT) is proposed in this article. This method is based on iterative linear elastic analyses and is applied to several test cases of practical interest. IMAT fully conforms to the classical lower and upper bound theorems. In all the cases, the upper and lower bound limit loads converge, thereby establishing the robustness of the technique. The results from IMAT correlate with nonlinear finite element analysis consistently within 3%.
Use of the Alvarado Score for Assessment of Abdominal Pain in a Women’s Soccer Player
Authors: Gray Courtney
Published: August 2022

The Alvarado score is used in emergency rooms to determine probability of appendicitis and provide a recommendation for care. A women’s soccer player presented to the athletic training clinic with right lower quadrant pain. She was evaluated and due to a differential diagnosis of appendicitis, the Alvarado score was used for screening. Based on her score, she was referred to the emergency room and, after diagnostic testing, was found to have a ruptured ovarian cyst. The Alvarado score was helpful in determining the need for referral when used in the clinical setting.
A modern pulse of ultrafast exhumation and diachronous crustal melting in the Nanga Parbat Massif
Authors: Guevara Victor E. , Smye Andrew J. , Caddick Mark J. , Searle Michael P. , Olsen Telemak , Whalen Lisa , Kylander-Clark Andrew R. C. , Jercinovic Michael J. , Waters David J.
Published: August 2022

We combine monazite petrochronology with thermal modeling to evaluate the relative roles of crustal melting, surface denudation, and tectonics in facilitating ultrafast exhumation of the Nanga Parbat Massif in the western Himalayan syntaxis. Our results reveal diachronous melting histories between samples and a pulse of ultrafast exhumation (9 to 13 mm/year) that began ~1 Ma and was preceded by several million years of slower, but still rapid, exhumation (2 to 5 mm/year). Recent studies show that an exhumation pulse of similar timing and magnitude occurred in the eastern Himalayan syntaxis. A synchronous exhumation pulse in both Himalayan syntaxes suggests that neither erosion by rivers and/or glaciers nor a pulse of crustal melting was a primary trigger for accelerated exhumation. Rather, our results, combined with those of recent studies in the eastern syntaxis, imply that larger-scale tectonic processes impose the dominant control on the current tempo of rapid exhumation in the Himalayan syntaxes.
The membrane-actin linker ezrin acts as a sliding anchor
Authors: Korkmazhan Elgin , Dunn Alexander R.
Published: August 2022

Protein linkages to filamentous (F)–actin provide the cell membrane with mechanical stability and support intricate membrane architectures. However, the actin cytoskeleton is highly dynamic and undergoes rapid changes in shape during cell motility and other processes. The molecular mechanisms that generate a mechanically robust yet fluid connection between the membrane and actin cytoskeleton remain poorly understood. Here, we adapted a single-molecule optical trap assay to examine how the prototypical membrane-actin linker ezrin acts to anchor F-actin to the cell membrane. We find that ezrin forms a complex that slides along F-actin over micrometer distances while resisting detachment by forces oriented perpendicular to the filament axis. The ubiquity of ezrin and analogous proteins suggests that sliding anchors such as ezrin may constitute an important but overlooked element in the construction of the actin cytoskeleton.
Decoding moms’ rules of engagement with cytomegalovirus
Authors: Martinez David R.
Published: August 2022

Cytomegalovirus-infected moms with antibodies that can engage the immune system via FcγR are less likely to congenitally transmit the virus.
Supplemental Material: Spatiotemporally heterogeneous deformation, indirect tectonomagmatic links, and lithospheric evolution during orogenic activity coeval with an arc flare-up
Authors: Attia S. , al. et
Published: August 2022

File S1: Geochronology analytical methods for LA-ICPMS analyses and geochronology compilation data sources. File S2: Data source information. File S3: Concordia plots and weighted mean age interpretations for new geochronology samples. File S4: Comprehensive details of the nature and age of central Sierra Nevada mid-Cretaceous structural features.
Quality Enhancement of Compressed 360-Degree Videos Using Viewport-based Deep Neural Networks
Authors: Qin Qipu , Jung Cheolkon
Published: August 2022

360-degree video provides omnidirectional views by a bounding sphere, thus also called omnidirectional video. For omnidirectional video, people can only see specific content in the viewport through head movement, i.e., only a small portion of the 360-degree content is exposed at a given time. Therefore, the viewport quality is of particular importance for 360-degree videos. In this article, we propose a quality enhancement of compressed 360-degree videos using viewport-based deep neural networks, named V-DNN. V-DNN is mainly composed of two modules: viewport prediction network (VPN) and viewport quality enhancement network (VQEN). VPN based on spherical convolution and 2D convolution generates potential viewports for omnidirectional video. VQEN takes the current viewport and its reference viewports as the input and enhances residual for the current viewport based on bidirectional offset prediction and Spatio-temporal deformable convolutions. Compared with HM16.16 baseline at QP = 37 under the Low Delay P (LDP) configuration, experimental results show that V-DNN achieves an average 0.605 dB and 0.0139 gains in viewport-based ΔPSNR and ΔMS-SSIM, respectively, and is 0.379 dB (59.63%) and 0.0073 (110.61%) higher than the multi-frame quality enhancement (MFQE-2.0) scheme at QP = 37, respectively. Moreover, V-DNN consistently outperforms MFQE-1.0, MFQE-2.0, and HM16.16 baseline at the other QPs in terms of ΔPSNR, ΔWS-PSNR, and ΔMS-SSIM.
Anomaly Detection Using Explainable Random Forest for the Prediction of Undesirable Events in Oil Wells
Authors: Aslam Nida , Khan Irfan Ullah , Alansari Aisha , Alrammah Marah , Alghwairy Atheer , Alqahtani Rahaf , Alqahtani Razan , Almushikes Maryam , Hashim Mohammed AL
Published: August 2022

The worldwide demand for oil has been rising rapidly for many decades, being the first indicator of economic development. Oil is extracted from underneath reservoirs found below land or ocean using oil wells. An offshore oil well is an oil well type where a wellbore is drilled underneath the ocean bed to obtain oil to the surface that demands more stability than other oil wells. The sensors of oil wells generate massive amounts of multivariate time-series data for surveillance engineers to analyze manually and have continuous insight into drilling operations. The manual analysis of data is challenging and time-consuming. Additionally, it can lead to several faulty events that could increase costs and production losses since the engineers tend to focus on the analysis rather than detecting the faulty events. Recently, machine learning (ML) techniques have significantly solved enormous real-time data anomaly problems by decreasing the data engineers’ interaction processes. Accordingly, this study aimed to utilize ML techniques to reduce the time spent manually to establish rules that detect abnormalities in oil wells, leading to rapid and more precise detection. Four ML algorithms were utilized, including random forest (RF), logistic regression (LR), k-nearest neighbor (K-NN), and decision tree (DT). The dataset used in this study suffers from the class imbalance issue; therefore, experiments were conducted using the original and sampled datasets. The empirical results demonstrated promising outcomes, where RF achieved the highest accuracy, recall, precision, F1-score, and AUC of 99.60%, 99.64%, 99.91%, 99.77%, and 1.00, respectively, using the sampled data, and 99.84%, 99.91%, 99.91%, 99.91%, and 1.00, respectively, using the original data. Besides, the study employed Explainable Artificial Intelligence (XAI) to enable surveillance engineers to interpret black box models to understand the causes of abnormalities. The proposed models can be used to successfully identify anomalous events in the oil wells.
Topological Indices of Drugs Used in Rheumatoid Arthritis Treatment and Its QSPR Modeling
Authors: Parveen Saima , Farooq Fozia Bashir , Awan Nadeem Ul Hassan , Fanja Rakotondrajao , Choudhary Muhammad Farooq
Published: August 2022

A topological index is a molecular descriptor derived from the molecular structure of a chemical substance. These indices can be used to analyze mathematical values and predict various physical properties of drugs. This article discusses tofacitinib, leflunomide, upadacinib, baricitinib, filgotinib, methotrexate, and other drugs used to treat rheumatoid arthritis, and the goal of the QSPR study is to calculate the relationship between the properties under investigation (e.g., boiling point, polarity, and molar volume) and molecular descriptors. Topological indices (TIs) were imposed on said drugs to calculate the correlation with physicochemical properties in this course.
Effects of Feeding an All-Plant Diet on Rainbow Trout Performance and Solid Waste Characteristics
Authors: Schumann Mark , Holm Jørgen , Brinker Alexander
Published: August 2022

Plant-based ingredients have become a main component of modern salmonid feeds, substituting for a significant proportion of fish-based ingredients while maintaining a high nutritional quality. But besides the nutritional value of a feed, there are other important aspects to be considered when altering formulations, foremost amongst which is the impact on water quality. A 100-day trial was conducted to evaluate the impact of different feed mixtures on fish performance, faecal stability, and particle size distribution. In a two-factorial experiment, three feed treatments (a fish-based reference, a diet with 10% hemoglobin meal, and a plant-based alternative) were trialled with and without inclusion of 0.3% dietary binder and were fed to triplicate groups of rainbow trout. While fish performance was not affected by dietary treatment, rheological measurements showed that the stability of faeces from fish consuming plant-based diets was distinctly reduced. Strong binder effects were observed for all dietary treatments, but faeces resulting from the pure plant-based diet produced more small particles and resulted in lower removal efficiencies by drum filter and sedimentation than those resulting from other dietary treatments. The implications of these findings for sustainable and effective aquaculture are discussed.
Emotion Recognition and Classification of Film Reviews Based on Deep Learning and Multimodal Fusion
Authors: Na Risu , Sun Ning
Published: August 2022

In terms of cross-cultural exchanges, the film is not only an important embodiment of a country’s cultural soft power but also the most direct and favorable way of communication. The advent of the all-around well-off era has propelled people’s demand for spiritual, cultural, and entertainment which promotes the vigorous development of the film culture industry. The expansion and development of China’s film market, domestic films, are a reflection and extension of China’s culture and ideas. It plays an extremely important role in enhancing cultural self-confidence and cultural output. In order to better grasp the emotional tendency of the audience, understand the viewing needs, and put forward suggestions on domestic film production, it is very necessary to analyze the emotion of film reviews and dig deep into semantics. Since the evaluation of film works considers many factors that are complex and changeable, the choice of model plays a significant role in the process of emotion analysis. The deep learning model represented by a deep neural network has high tolerance to sentence noise, has strong information discrimination, and features self-learning ability. It also has great advantages in emotion classification tasks. This study conducts an in-depth study and research on the traditional emotion analysis methods and finally puts forward an effective emotion analysis framework that combines the traditional emotion analysis method and deep learning network. This framework enhances the text vectorization representation and emotion classification model by performing emotion analysis. The effectiveness is verified by corresponding experiments which justify the superiority of the approach.
Zigbee Wireless Sensor Networks: Performance Study in an Apartment-Based Indoor Environment
Authors: Dash Biswajit Kumar , Peng Jun
Published: August 2022

Zigbee is a very popular technology for Internet of things (IoT) networks mainly because of its low power consumption and low-cost features. It shares the unlicensed 2.4 GHz Industrial, Scientific, and Medical (ISM) radio band with other wireless networks such as Wi-Fi. Usually, Zigbee and Wi-Fi networks coexist in indoor environments for their respective applications. Hence, the coexistence introduces interference for both types of networks lowering the performance of the networks, but Zigbee suffers more significant performance losses because of its lower transmission power than Wi-Fi. Since the number of IoT devices is increasing at an unprecedented rate due to numerous emerging applications and thus making the indoor environments very populous, the peaceful coexistence between Zigbee and Wi-Fi networks in proximity becomes an important research study. For this purpose, this paper presents a comprehensive performance study of a Zigbee network in the presence of a Wi-Fi interference network in a real-life apartment-based indoor environment where Wi-Fi access points of dense neighbors exist. The experiments were done in a XBee module-based Zigbee network for measuring the received signal strength indicator (RSSI), packet drop rate (PDR), and loopback throughput with and without nearby Wi-Fi traffic introduced on purpose. Various networking parameters such as the operating channels, the distances between Zigbee devices and Wi-Fi devices, the transmit timeout of Zigbee packets, and the transmission power of the Zigbee transmitter have been used in the experiments to study the network performance. Our results show that in the deployment of IoT networks in a smart home, radio interference from neighboring homes would not be an important factor, but serious considerations may need to be taken inside the same home. The experimental observations of this paper can serve as a good reference study for Zigbee network deployments in real indoor environments, particularly when interference sources are present in proximity.
Embedded Real-Time Detection of Vehicles and Pedestrians Based on Minimal Networks
Authors: Tian Zhenghao
Published: August 2022

The safety and security of vehicles and pedestrians have always been a topic of high social concern. Since the safety awareness of vehicles and pedestrians is generally low nowadays, there is no relatively perfect and systematic method to guarantee that they can share information among themselves efficiently. As the number of vehicles and pedestrians continues to increase, ensuring their safe operation has become an important and real issue in today’s society. To ensure traffic order in unsupervised areas, it is necessary not only to be intelligent in management but also to have a comprehensive safety system to ensure that pedestrians and vehicles can share information and ensure traffic order. At present, the road management department has taken relatively effective measures to deal with these accidents, first of all, it is necessary to strengthen the construction of road safety facilities and also to improve the road transport vehicle detection capacity, to be able to timely detect the existence of safety hazards between vehicles and pedestrians, then reduce the possibility of accidents through technical means. Second, improve the ability to detect road safety facilities so that when accidents occur, it can detect the accident in time and take effective measures. Finally, improve the safety measures between vehicles and pedestrians in the road enforcement department, to effectively ensure that information can be shared between pedestrians and vehicles, thus reducing the possibility of traffic accidents.
Reversible Data Hiding Based on Multichannel Difference Value Ordering for Color Images
Authors: Kong Yongjun , Ke Yan , Zhang MinQing , Su TingTing , Ge Yu , Yang Sha
Published: August 2022

Considering the correlation existing among different color channels of the image, we propose a novel reversible data hiding (RDH) scheme based on multichannel difference value ordering. By applying the technique of pixel value ordering (PVO), we establish a certain relationship by sorting the differences among adjacent pixels of different color channels. Combined with the optimized pairwise prediction-error expansion by analyzing the distribution of pixel difference, our scheme can adaptively select pixel channel to achieve reversible embedding of information. Through simulation experiments, the feasibility of this RDH scheme in image distortion and computational complexity is verified. When the threshold T is set to 3, the average PSNR of the test images embedded with 5000 bits of additional information in each color channel can reach 63.41, 64.38, and 63.96, respectively. When the embedding capacity is 20000 bits, the PSNR of the color image can reach 58.90 dB. Considering the embedding capacity and image distortion comprehensively from the simulation data, our proposed scheme has a better performance than the previous PVO-RDH schemes which only consider a single channel.
Impact of COVID-19 Outbreak on Stoma Surgery and Stoma Clinic Service: A Retrospective Study at a Single Japanese Referral Hospital
Authors: Nozawa Hiroaki , Kawasaki Akiko , Hayashi Chieko , Kawai Kazushige , Sasaki Kazuhito , Murono Koji , Emoto Shigenobu , Ishihara Soichiro
Published: August 2022

Aim. The impact of the COVID-19 pandemic on medical practice has been frequently reported from Western countries, but there have been few studies in other areas, especially regarding stoma surgery and stoma care. Methods. We investigated the numbers of all operations and stoma-related surgeries at our hospital in 2019 and 2020. The cumulative numbers of consultations at our ostomy clinic and patient population stratified by the period of having a stoma were compared between these calendar years. The frequency of ostomy clinic visit by individual patients within the first year after stoma creation and stoma-related complications per consultation were also analyzed. Results. The number of elective surgeries decreased by approximately 10% from 2019 to 2020, but the numbers of stoma creation and closure procedures did not differ. The total numbers of consultations at our ostomy clinic were also similar between these years. However, the percentage of patients with a stoma for less than a year who visited our ostomy clinic increased from 49.7% in 2019 to 53.5% in 2020, whereas the visitation rate for other patients decreased. Moreover, patients with a stoma for less than a year visited the ostomy clinic more frequently in 2020 (0.42/month) than in 2019 (0.30/month,

p
=
0.032

). There were fewer grade 2 or more severe peristomal complications in 2020 (11% vs 17% in 2019,

p
<
0.001

) at our ostomy clinic. Conclusion. The COVID-19 outbreak led to a shift in the patient population at ostomy clinics of new stoma patients, which may have resulted in fewer peristomal complications.
Protection of Intangible Cultural Heritage Based on VR: Taking Xiuyan Jade Carving Craft as an Example
Authors: Du Yanyan
Published: August 2022

Innovative exploration of the inheritance and dissemination of intangible cultural heritage can make it play an important role in national development and international social exchange. By taking the inheritance and development of Xiuyan jade carving craft as the background, in this study, the design principle, technology platform, process flow, and technology integration of virtual display technology applied to jade carving technology are elaborated, and the realization of adopting virtual reality technology to assist inheritance of Xiuyan jade carving technology is summarized, so as to form the inheritance system mode, which is suitable for the modern lifestyle. Finally, VR technology is used to explore the development of visualization platform for Xiuyan craft, which further explores the way of intangible cultural heritage protection of traditional manual technology.
Hypertrophic Osteoarthropathy Associated with Probable Smear-Negative Pulmonary Tuberculosis
Authors: Ahmed Ghassem Mohamed , Biyi Abdelhamid , Djossou Julien H , Hamza Toufik , Majjad Abderrahim , Achemlal Lahsen
Published: August 2022

Association of hypertrophic osteoarthropathy (HOA) with pulmonary tuberculosis is rarely reported, especially with smear-negative pulmonary tuberculosis (SNPT), in which its diagnosis is a challenge. We used a systematic approach to analyze all relevant literature reviews, and we identified only two cases of HOA associated with pulmonary tuberculosis in the last 10 years. We report the case of a 36-year-old man who presented with bilateral symmetric polyarthralgia and digital clubbing. Laboratory exams associated elevated acute phase reactants with negative immunological examinations. Two series of three acid-fast Bacillus (AFB) smear microscopy in sputum, separated by 15 days of broad-spectrum antibiotic therapy, were negative. A sputum culture was negative for Mycobacterium tuberculosis. A chest X-ray and computed tomography (CT) showed an apical pulmonary cavity. Plain X-ray and bone scintigraphy revealed periostosis of the tubular bones. Therefore, the diagnosis of HOA associated with probable SNPT was made. HOA symptoms had remitted after 3 months of antitubercular therapy. After 7 months of treatment, chest CT and bone scintigraphy showed a regression of the pulmonary cavity and disappearance of periostosis. The search for tuberculosis in front of any HOA seems to be justified in our epidemiological context.
Improved Performance Analysis of PV Array Model Using Flower Pollination Algorithm and Gray Wolf Optimization Algorithm
Authors: Jayaudhaya J. , Ramash Kumar K. , Tamil Selvi V. , Padmavathi N.
Published: August 2022

The efficiency of a photovoltaic (PV) system under partial shading conditions (PSCs) is primarily determined by how the PV panels are connected to the load. Various PV system architectures have been developed to improve power processing capability and thus power conversion efficiency. In this article, a central and string architecture are considered, and the performance characteristics are obtained using optimization techniques such as gray wolf optimization (GWO) and flower pollination algorithm (FPA) in MATLAB/Simulink. The simulation results show that the performance characteristics of string architecture obtained using the GWO algorithm outperform central architecture with both GWO and FPA.
Application of Image Processing Technology in the Diagnosis of Football Injury
Authors: Xu Liyun , Xu Zhubo
Published: August 2022

With the hot development of football, sports injuries caused by football have also received special attention. In football games, although there are medical staff on and off the field always on call to protect the safety of players, because of the complexity of diagnosis work, medical staff can easily lead to diagnostic errors due to factors such as fatigue, which seriously affects the condition of athletes. Image processing is a technology that uses computer to process images, which can greatly overcome the uncertain factors brought by manual diagnosis. Based on this, this paper uses image processing technology and pattern recognition as technical means to explore the specific application of image processing in football injury diagnosis. This paper firstly takes football clubs as the main research object and analyzes and explores the specific utility of image segmentation and feature recognition in sports injury image processing. Then, starting from the relevant image features, the paper analyzes and compares the sensitivity of support vector machine pattern recognition and neural network pattern recognition in football injury diagnosis. This article comprehensively summarizes the application of image processing technology in the diagnosis of football injuries and puts forward constructive suggestions for its subsequent development. Experiments show that the effect of pattern recognition is often different for different injury parts of football. Among them, the sensitivity of pattern recognition based on image processing can reach 68.9%, and the detection rate of football injuries can also be maintained at about 81.2%. This fully shows that image processing technology can play an active role in the actual football injury diagnosis, and provide very valuable information for clinical diagnosis.
High-Precision Target Detection of Remote Sensing Image Based on Feature Enhancement with 6G Technology
Authors: Chen Haiyan
Published: August 2022

We provide remote sensing image enhancement technology based on 6G nursing urine technology to solve the main problems and current challenges of target detection in remote sensing imaging. High-resolution images: to get a good image, first look at the remote control image, and objective findings on the remote control image play an important role in this process. Military and civilian use: at present, many advanced object detection algorithms have achieved success in natural imaging, but their development is limited by two factors: large variation in object size and low detection accuracy, the scale, rotation direction, and distribution density of remote sensing images. On the other hand, the first remote sensing image is usually a high-resolution, large-scale image, which requires more time than blank image detection. The model is fine-tuned on the ICDAR2015 training package for 60,000 repetitions. The same model experimentally reduced the image to 1280 × 768 and displayed the results in one dimension. Therefore, in order to solve the problem of low detection due to changes in azimuth, rotation direction, and velocity distribution, it is necessary to further study methods for detecting large-capacity remote sensing objects using abundant high-precision remote sensing technologies, sensing imaging service on remote sensing maps.
Multitarget Tracking Algorithm in Intelligent Analysis of Football Movement Training Stance
Authors: Li Changrui , Peng Qiuping
Published: August 2022

In recent years, with the continuous development of computer technology, deep learning has been widely applied to computer vision tasks and has achieved great success in areas such as visual detection and tracking. On this basis, making deep learning techniques truly accessible to people becomes the next objective. Target detection and tracking in football gesture training is a quite challenging task with great practical and commercial value. In traditional football training methods, target trajectories are often extracted by means of a recording chip carried by the player. However, the cost of this method is high and it is difficult to replicate in amateur stadiums. Some studies have also used only cameras to process targets in football videos. However, due to the similarity in appearance and frequent occlusion of targets in football videos, these methods often only segment targets such as players and balls in the image but do not allow them to be tracked. Target tracking techniques are of great importance in football training and are the basis for tasks such as player training analysis and match strategy development. In recent years, many excellent algorithms have emerged in the field of target tracking, mainly in the categories of correlation filtering and deep learning, but none of them are able to achieve high accuracy in player tracking for football training videos. After all, the problem of locating clips of interest to athletes from a full-length video is a pressing one. Traditional machine learning-based approaches to sports event detection have poor accuracy and are limited in the types of events they can detect. These traditional methods often rely on auxiliary information such as audio commentary and relevant text, which are less stable than video. In recent years, deep learning-based methods have made great progress in the detection of single-player video events and actions, but less so in the detection of sports video events. As a result, there are few sports video datasets that can be used for deep learning training. Based on research in computer vision and deep learning, this paper designs a multitarget tracking system for football training. To be specific, this algorithm uses multiple cameras for image acquisition in the stadium in order to accurately track multiple targets in the stadium over time. Furthermore, the framework for a single camera multitarget tracking approach has been designed based on deep learning-based visual detection methods and correlation filter-based tracking methods. This framework focuses on using data correlation algorithms to fuse the results of detectors and trackers so that multiple targets can be tracked accurately in a single camera. To sum up, this research allows for robust and real-time long-term accurate tracking of targets in football training videos through multitarget tracking algorithms and the intercorrection of multiple camera systems.
Study on Cold Chain Logistics Operation and Risk Control of Fresh e-Commerce Products
Authors: Wang Shenxiang
Published: August 2022

With the rapid development of the Internet, my country’s e-commerce market has been very active in recent years, and the number of e-commerce platforms and the volume of product transactions have achieved rapid development. However, through the investigation of the main circulation products of e-commerce brands, it can be found that the output value of my country’s e-commerce industry as a whole in the fresh food field is very low. Many fresh products are prone to various risks during the circulation process, resulting in large losses on the platform and online agricultural products e-commerce. There is a shortage of fresh cold chain equipment and cold chain technicians, which directly affects the stable and healthy development of fresh cold chain logistics in China. This paper analyzes the existing operation mode of e-commerce, analyzes the main bottleneck of the operation of the fresh cold chain, and puts forward corresponding suggestions to enhance the awareness of risk control, so as to better promote the benign operation of agricultural products cold logistics and provide some reference for the optimization of e-commerce fresh cold chain logistics.