Training Patterns Research Articles

Knowledge Graph-Based Badminton Tactics Mining and Reasoning for Badminton Player Training Pattern Analysis and Optimization

Knowledge Graph-Based Badminton Tactics Mining and Reasoning for Badminton Player Training Pattern Analysis and Optimization

Possible impact of North Atlantic sea surface temperature on decadal variability of dust activity in Gobi Desert

Semiarid to arid regions located in north of China are known as one of the largest sources of dust aerosols in the globe. Previous studies demonstrated direct and indirect effects of atmospheric dust loading on climate. The surface and meteorological properties are known to be affecting dust entrainment process. In this study, we found decadal variations of dust occurrence in Gobi Desert with the period of ∼24 years, utilizing the data acquired at the surface meteorological stations. An analysis of reanalysis datasets shows significant correlations between February North Atlantic Sea Surface Temperature (NASST) and precipitation in Gobi Desert and Mongolia in the following summer, causing a decadal variation of dust event frequency in the subsequent spring over the region. Strong time-lagged correlation is shown to be linked to an atmospheric wave train pattern that initiated from the NASST region, affecting large-scale circulation, ultimately causing surface drought over Gobi Desert.

Refocus the Attention for Parameter-Efficient Thermal Infrared Object Tracking.

Introducing deep trackers to thermal infrared (TIR) tracking is hampered by the scarcity of large training datasets. To alleviate the predicament, a common approach is full fine-tuning (FFT) based on pretrained RGB parameters. Nevertheless, due to its inefficient training pattern and representation collapse risk, some parameter-efficient fine-tuning (PEFT) alternatives have been promoted recently. However, the existing PEFT algorithms typically follow a bottom-up way, where their attention solely relies on the input and lacks the capability of task-guided top-down attention, which provides the task-relevant representation such as the human visual perception system. In this article, we introduce ReFocus, a new PEFT method that adapts the pretrained RGB foundation tracking model to the downstream TIR tracking task through the guidance of high-level task-specific signals in a top-down attention manner. By freezing the entire foundation model and only training query-guided feature selection and top-down blocks, ReFocus achieves state-of-the-art (SOTA) TIR tracking performance while keeping training efficiency. Extensive experiments on five TIR tracking benchmarks demonstrate that ReFocus significantly improves the performance of the foundation tracker. Besides, further ablation studies show the effectiveness and flexible adaptability of the proposed method to lighter foundation models and different tracking frameworks. Compared to FFT and other bottom-up PEFT paradigms, such as head probe, low-rank adaptation (LoRA), and adapter, our method achieves comparable or superior performance with fewer training parameters and reveals the advantage of learning stability.

Comparative Effect of High-Frequency Nasal Cannula and Noninvasive Ventilation on the Work of Breathing and Postoperative Pulmonary Complication after Pediatric Congenital Cardiac Surgery: A Prospective Randomized Controlled Trial.

Various forms of commonly used noninvasive respiratory support strategies have considerable effect on diaphragmatic contractile function which can be evaluated using sonographic diaphragm activity parameters. To compare the magnitude of respiratory workload decreased as assessed by thickening fraction of the diaphragm and longitudinal diaphragmatic strain while using high-flow nasal cannula (HFNC) and noninvasive ventilation (NIV) modes [nasal intermittent positive pressure ventilation (NIPPV) and bilevel positive airway pressure (BiPAP)] in pediatric patients after cardiothoracic surgery. This prospective randomized controlled trial was performed at a tertiary care surgical intensive care unit in postcardiac surgery patients aged between 1 and 48 months, who were randomly allocated into three groups: 1) HFNC (with flows at 2 L/kg/min), 2) NIPPV via RAMS cannula in PSV mode (pressure support 8 cmH2O, PEEP 5 cmH2O), and 3) BiPAP in nCPAP mode (CPAP of 5 cmH2O). Measurements were recorded at baseline after extubation (R0) and subsequently every 12 hourly (R1, R2, R3, R4, R5) at 12, 24, 36, 48, and 60 hours respectively until therapy was discontinued. Sixty patients were included, with 20 patients each in the NIPPV group, HFNC group, and BiPAP group. Longitudinal strain at crura of diaphragm was lower in the BiPAP group as compared to HFNC group at R2-R4 [R2 (-4.27± -2.73 vs - 8.40± -6.40, P = 0.031), R3 (-5.32± -2.28 vs -8.44± -5.6, P = 0.015), and R4 (-3.8± -3.42 vs -12.4± -7.12, P = 0.040)]. PFR was higher in HFNC than NIPPV group at baseline and R1-R3[R0 (323 ± 114 vs 264 ± 80, P = 0.008), R1 (311 ± 114 vs 233 ± 66, P = 0.022), R2 (328 ± 116 vs 237 ± 4, P = 0.002), R3 (346 ± 112 vs 238 ± 54, P = 0.001)]. DTF and clinical parameters of increased work of breathing remain comparable between three groups. The rate of reintubation (within 48 hours of extubation or at ICU discharge) was 0.06% (1 in NIPPV, 1 in BiPAP, 2 in HFNC) and remain comparable between groups (P = 1.0). BiPAP may provide better decrease in work of breathing compared to HFNC as reflected by lower crural diaphragmatic strain pattern. HFNC may provide better oxygenation compared to NIPPV group, as reflected by higher PFR ratio. Failure rate and safety profile are similar among different methods used.

Distributed and multimodal strain sensing performance of flexible hydrogel functional optical fibers

Flexible fiber enables large-scale, multi-mode, and distributed strain sensing and provides a versatile solution for wearable and implantable strain sensors.

Effect of Ultrasonic Vibration on Tensile Mechanical Properties of Mg-Zn-Y Alloy

Ultrasonic vibration assisted (UVA) plastic forming technology has proven to be a highly effective processing method, particularly for materials that are challenging to deform. In this research, UVA tensile tests were carried out on Mg98.5Zn0.5Y1 alloy at different vibration frequencies and amplitudes. The experimental results indicate that, compared with conventional tensile tests, the yield strength and tensile strength of Mg98.5Zn0.5Y1 alloy exhibit a decrease. Furthermore, the application of ultrasonic vibration demonstrates an ability to enhance the material’s elongation and plasticity. In order to further predict the stress-strain relationship in the metal tensile process, a hybrid constitutive model coupling the frequency and amplitude of ultrasonic vibration was developed based on the modified Johnson Cook model. The calculated results of the constitutive equation are in good agreement with the experimental results, indicating that the established constitutive equation can accurately predict the trend of alloy stress change at different amplitudes and frequencies. It establishes a theoretical foundation for scrutinizing the deformation mechanisms of the alloy under ultrasonic vibration. Furthermore, Abaqus finite element analysis software was employed to simulate and analyze the UVA tensile process, elucidating the impact of ultrasonic vibration on stress distribution, strain patterns, and material flow in the tensile behavior of Mg98.5Zn0.5Y1 alloys.

Social Interaction in Basic Training for Prospective Civil Servants Using the Blended Learning Method

The movement in the style of Basic Training for Civil Servant Candidates (CPNS) from traditional or face-to-face methods to blended learning has been prompted by advancements in information technology and the COVID-19 pandemic outbreak. Changes in training patterns result in alterations to the social interaction processes conducted among organizers, teachers, and participants. In the classical method, direct social contact is abundant, whereas in blended learning, digital-based communication media predominantly facilitate the engagement process. This study employs a literature review methodology to offer a comprehensive picture of social interactions during the CPNS Basic Training process, utilizing the blended learning approach.

Optimization Method for Conductance Modulation in Ferroelectric Transistor for Neuromorphic Computing

AbstractThe learning accuracy of neuromorphic computing that mimics the biological brain, is affected by the conductance‐modulation characteristics of an artificial synapse. In ferroelectric‐based devices, these characteristics are implemented using a distribution of polarization values. Therefore, the distribution in a ferroelectric thin film with various external voltage signals is investigate. As polarization switching proceeds with voltage pulse, the domains of the switched polarization become larger. In ferroelectric‐gate field effect transistors, the channel layer assumed to lie beneath the ferroelectrics experiences a local conductance change, according to the polarization distribution of the ferroelectric layer. It is found that small clusters with high conductivity become large clusters in the channel layer as the polarization switching proceeds. When the additional pulses are applied, the high conductive regions eventually connect (i.e., percolate) in the channel layer and the conductance of the layer is greatly increased. Adjusting the height of the applied voltage can slow down or speed up this phenomenon. Also, the nanosecond voltage pulses are employed and the width of the conductive pathway is adjusted. It enables to fine‐tune the conductance of the channel layer. It demonstrates that conductance modulation is optimized with an appropriate voltage pulse train pattern.

Construction Of Drug Abuses (Case Study at Class 11-A Kupang Penitentiary)

Completers reported higher alcohol use than counterparts. Explores the model's subcategories: “life choices” (substance use, criminal and sexual behavior), static (background and disposition), and dynamic situational influences (occupation, psychological state, recent and past encounters).This research aims to determine the development of drug abuse in the Kupang Class II A Correctional Institution. The method used is an analytical descriptive approach . The data collection method is data from interviews and observations, the data analysis used is qualitative data analysis . The results of the research show that drug abuse guidance in Class IIA Kupang Prison has been achieved implemented in accordance with the Decree of the Minister of Justice of the Republic of Indonesia regarding the pattern of training prisoners/detainees of the Minister of Justice of the Republic of Indonesia, however, its implementation is still not perfect due to various obstacles. The training for narcotics prisoners has so far remained the same as the training for general prisoners . Drug abuse is a special case and should receive special guidance.

Accurate and Efficient Sitting Posture Recognition and Human‐Machine Interaction Device Based on Fabric Pressure Sensor Array and Neural Network

AbstractThis article presents a novel approach to interact with users through posture recognition, leveraging its advantages of convenience and real‐time feedback to enhance user engagement and personalized experiences. In contrast to traditional methods that rely on camera‐based posture detection, this study proposes a deep learning‐based framework for posture recognition by classifying the distribution of body pressure under different sitting positions. The system integrates a large‐area, highly flexible fabric pressure sensor array into the chair, which collects data on posture‐specific pressure patterns for training and identification purposes. A deep learning algorithm, specifically the LeNet architecture, is employed to classify 49 different sitting positions based on angular variations, including body tilt to the left or right, standard posture, and forward or backward leaning. The proposed approach achieves an impressive accuracy rate of 99.86%. Furthermore, the application of this posture recognition system in VR devices enables intelligent chair control for VR games. This research provides strong support for future advancements in chair design and human‐computer interaction technologies, enhancing ergonomic designs in various domains such as automotive seats, office chairs, and medical seating, while simultaneously improving user comfort and well‐being.

Characterization of genotypes and antimicrobial resistance profiles of clinical isolates of Shigella from patients in the southern region of Iran

BackgroundShigella spp., which are facultative anaerobic bacilli within the Enterobacteriaceae family, present a significant public health burden due to their role as prominent contributors to diarrheal diseases worldwide. A molecular analysis can facilitate the identification and assessment of outbreaks involving this bacterium. So, we aimed to investigate the antibiotic susceptibility pattern and clonal relatedness of clinical Shigella spp. isolates obtained from patients with diarrhea in Hormozgan province, South of Iran.MethodsFrom 2019 to 2021, a cross-sectional investigation was conducted on 448 stool samples obtained from patients who were experiencing diarrhea, in the southern region of Iran. Shigella spp. isolates were identified based on biochemical and serological tests. All Shigella species were verified using species-specific polymerase chain reaction (PCR), followed by susceptibility testing to antimicrobial agents. Subsequently, genotyping of all Shigella species was conducted using ERIC-PCR.ResultsOut of a total of 448 stool samples, the presence of Shigella was detected in 62 cases, accounting for a prevalence rate of 13.84%. Among the identified isolates, the majority were attributed to S. flexneri, representing 53.23% of the cases. This was followed by S. sonnei at 24.19% and S. boydii at 22.58%. Notably, no instances of S. dysenteriae were found. The highest prevalence of Shigella isolates was observed in infants and children under the age of five. A significant proportion of the identified isolates demonstrated resistance to various antibiotics. Specifically, high resistance rates were noted for ampicillin (90.78%), piperacillin–tazobactam (87.1%), cefixime (83.87%), trimethoprim–sulfamethoxazole (83.87%), cefotaxime (82.26%), and ceftriaxone (80.65%). In addition, a substantial number (87.1%) of the isolates exhibited a multidrug-resistant (MDR) phenotype. Using the ERIC-PCR method, a total of 11 clusters and 6 distinct single types were identified among all the Shigella isolates.ConclusionA notable occurrence of antibiotic-resistant Shigella species has been noted, with multi-drug resistant (MDR) strains presenting an increasing challenge for treating shigellosis worldwide, and this includes Iran. Techniques such as ERIC-PCR are useful for assessing the genetic variation and connections between Shigella strains, which indirectly contributes to understanding antimicrobial resistance patterns. Further research is needed to explore the specific correlation between resistance genes and ERIC genotyping patterns in Shigella strains.

Match-play, training workloads and sensorimotor and neuromuscular performance of elite young soccer players

Purpose: The purpose of this study was to assess sensorimotor and neuromuscular performance capabilities over an in-season microcycle in early-career professional soccer players and to examine the relationship with training and match-play workload. Methods: Sensorimotor and neuromuscular performance capabilities (isometric knee extensor: force replication error, peak force, electromechanical delay, rate of force development) of 12 professional soccer players were assessed over a 7-day period. Training and match-play workload was also recorded over the same period for each player (high-intensity running distance). Fluctuations in sensorimotor and neuromuscular performance and workload variables were analysed. Results: There was evidence of fluctuations in sensorimotor and neuromuscular performance capability over the microcycle that reached statistical (p < .005) and practical (18.1% [baseline-to-peak]) significance alongside heterogeneity in training and match workload (264% [coefficient of variation], p < .0005). Some temporal congruence among fluctuating patterns of intra-microcycle training and match-play load and concomitant electromechanical delay performance was noted (p < .005). Asynchronous responses were observed for peak force, but rate of force development and force replication error capabilities were unchanged during the microcycle. Conclusion: While some neuromuscular performance capabilities fluctuate over an in-season microcycle and are influenced partially by high-intensity running workload, sensorimotor performance capabilities were unchanged during the microcycle.

Prevalence and Antimicrobial Resistance Pattern of Bacterial Strains Isolated from Patients with Urinary Tract Infection in Al-Wahda Hospital in Derna City/Libya

Background: Urinary tract infection (UTI) is One of the most prevalent infectious diseases in human, where the study aimed to identify the most uropathogen that caused UTIs ,and its the antimicrobial resistance pattern. Methods: the samples were collected from January and December 2021 using a standard data collection form, where the patient outcome records were mined for information on the patients' gender, age, isolated organisms, and susceptibility test results, then statistical analysis was done. Results: 266 from 463 samples were identified as S. aureus 14.3% , in addition, the antibacterial resistance rats showed that the highest resistance was against ampicillin/Sulbactam, ceftazidine, and meropenem 79%, while, the lowest was against ciprofloxacin 40%. Conclusion: The study showed that S. aureus is the primary cause of UTIs in Derna city, as a result of consuming antibiotics randomly, which resulted in an increase in spread and resistance of S. aureus.

A Multi-Point Geostatistical Modeling Method Based on 2D Training Image Partition Simulation

In this paper, a multi-point geostatistical (MPS) method based on variational function partition simulation is proposed to solve the key problem of MPS 3D modeling using 2D training images. The new method uses the FILTERSIM algorithm framework, and the variational function is used to construct simulation partitions and training image sequences, and only a small number of training images close to the unknown nodes are used in the partition simulation to participate in the MPS simulation. To enhance the reliability, a new covariance filter is also designed to capture the diverse features of the training patterns and allow the filter to downsize the training patterns from any direction; in addition, an information entropy method is used to reconstruct the whole 3D space by selecting the global optimal solution from several locally similar training patterns. The stability and applicability of the new method in complex geological modeling are demonstrated by analyzing the parameter sensitivity and algorithm performance. A geological model of a uranium deposit is simulated to test the pumping of five reserved drill holes, and the results show that the accuracy of the simulation results of the new method is improved by 11.36% compared with the traditional MPS method.

Probing the Intrinsic Strain in Suspended Graphene Films Using Electron and Optical Microscopy.

Quantifying the intrinsic properties of 2D materials is of paramount importance for advancing their applications. Large-scale production of 2D materials merits the need for approaches that provide direct information about the role of growth substrate on 2D material properties. Transferring the 2D material from its growth substrates can modify the intrinsic properties of the asgrown 2D material. In this study, suspended chemical vapor deposition (CVD) graphene films are prepared directly on their growth substrates in a high-density grid array. The approach facilitates the quantification of intrinsic strain and doping in suspended CVD graphene films. To achieve this, transmission electron microscopy and large-area Raman mapping are employed. Remarkably, the analysis reveals consistent patterns of compressive strain (≈-0.2%) both in the diffraction patterns and Raman maps obtained from these suspended graphene films. By conducting investigations directly on the growth substrates, the potential influences introduced during the transfer process are circumvented effectively. Consequently, the methodology offers a robust and reliable means of studying the intrinsic properties of 2D materials in their authentic form, uninfluenced by the transfer-induced alterations that may skew the interpretation of their properties.

Pangeo-Enabled ESM Pattern Scaling (PEEPS): A customizable dataset of emulated Earth System Model output

Emulation through pattern scaling is a well-established method of rapidly producing climate fields (like temperature or precipitation) from existing Earth System Model (ESM) output that, while inaccurate, is often useful for a variety of downstream purposes. Conducting pattern scaling has historically been a laborious process, in large part due to the increasing volume of ESM output data that has often required downloading and storing locally to train on. Here we describe the Pangeo-Enabled ESM Pattern Scaling (PEEPS) dataset, a repository of trained annual and monthly patterns from CMIP6 outputs. This manuscript describes and validates these updated patterns so that users can save effort calculating and reporting error statistics in manuscripts focused on the use of patterns. The trained patterns are available as NetCDF files on Zenodo for ease of use in the impact community, and are reproducible with the code provided via GitHub in both Jupyter notebook and Python script formats. Because all training data for the PEEPS data set is cloud-based, users do not need to download and house the ESM output data to reproduce the patterns in the zenodo archive, should that be more efficient. Validating the PEEPS data set on the CMIP6 archive for annual and monthly temperature, precipitation, and near-surface relative humidity, pattern scaling performs well over a variety of future scenarios except for regions in which there are strong, potentially nonlinear climate feedbacks. Although pattern scaling is normally conducted on annual mean ESM output data, it works equally well on monthly mean ESM output data. We identify several downstream applications of the PEEPS data set, including impacts assessment and evaluating certain types of Earth system uncertainties.

Towards Garment Sewing Pattern Reconstruction from a Single Image

Garment sewing pattern represents the intrinsic rest shape of a garment, and is the core for many applications like fashion design, virtual try-on, and digital avatars. In this work, we explore the challenging problem of recovering garment sewing patterns from daily photos for augmenting these applications. To solve the problem, we first synthesize a versatile dataset, named SewFactory, which consists of around 1M images and ground-truth sewing patterns for model training and quantitative evaluation. SewFactory covers a wide range of human poses, body shapes, and sewing patterns, and possesses realistic appearances thanks to the proposed human texture synthesis network. Then, we propose a two-level Transformer network called Sewformer, which significantly improves the sewing pattern prediction performance. Extensive experiments demonstrate that the proposed framework is effective in recovering sewing patterns and well generalizes to casually-taken human photos. Code, dataset, and pre-trained models will be released.

PELATIHAN PEMBUATAN BAHAN AJAR KURIKULUM MERDEKA BERBASIS KEARIFAN LOKAL UNTUK MGMP IPA TINGKAT MTs KABUPATEN PADANG LAWAS

This activity is a training and mentoring program for the creation of teaching materials based on local wisdom for Middle School Science Teachers (MTs) in Padang Lawas Regency. This is based on the following facts: (1) teachers have a low understanding of creating teaching materials for the Merdeka Curriculum based on local wisdom, (2) there hasn't been any training for creating teaching materials for science subjects in the Merdeka Curriculum based on local wisdom in Padang Lawas District, (3) teachers are not using relevant, creative, and student-appropriate teaching materials. The target of this activity is the members of the Middle School Science Teacher Working Group (MGMP IPA) in Padang Lawas Regency, totaling 15 people. The implementation of the activity begins with a preparation phase, followed by the implementation phase using the in-on-in training pattern, and completed by the evaluation phase. This activity results in 15 teaching materials for the Merdeka Curriculum based on local wisdom created by the training participants. Survey results show that 93% of participants strongly agree that this training improves their understanding of creating teaching materials for the Merdeka Curriculum based on local wisdom. Post-test results show that 80% of participants scored highly in the range of 70-100. The average score of participants in the pre-test was 61, while the post-test results increased to 90. This indicates that the training is effective in enhancing teachers' understanding and ability to create teaching materials for the Merdeka Curriculum based on local wisdom.

Investigation of the transport and metabolic patterns of oil-displacing bacterium FY-07-G in the microcosm model using X-CT technology.

Microbially Enhanced Oil Recovery (MEOR) is dedicated to enhancing oil recovery by harnessing microbial metabolic activities and their byproducts within reservoir rocks and fluids. Therefore, the investigation of microbial mobility and their extensive distribution within crude oil is of paramount importance in MEOR. While microscale models have been valuable for studying bacterial strain behavior in reservoirs, they are typically limited to 2D representations of porous media, making them inadequate for simulating actual reservoir conditions. Consequently, there is a critical need for 3D models and dependable visualization methods to observe bacterial transport and metabolism within these complex reservoir environments. Bacterial cellulose (bc) is a water-insoluble polysaccharide produced by bacteria that exhibits biocompatibility and biodegradability. It holds significant potential for applications in the field of MEOR as an effective means for selective plugging and spill prevention during oil displacement processes. Conditionally cellulose-producing strain, FY-07-G, with green fluorescent labeling, was engineered for enhanced oil recovery. 3D micro-visualization model was constructed to directly observe the metabolic activities of the target bacterial strain within porous media and to assess the plugging interactions between cellulose and the medium. Additionally, X-ray computed tomography (X-CT) technology was employed for a comprehensive analysis of the transport patterns of the target strain in oil reservoirs with varying permeabilities. The results indicated that FY-07-G, as a microorganism employing biopolymer-based plugging principles to enhance oil recovery, selectively targets and seals regions characterized by lower permeability and smaller pore spaces. This work provided valuable insights into the transport and metabolic behavior of MEOR strains and tackled the limitation of 2D models in faithfully replicating oil reservoir conditions, offering essential theoretical guidance and insights for the further application of oil-displacing bacterial strains in MEOR processes.

3D strain pattern in additively manufactured AlSi10Mg from digital volume correlation

Although much research has focused on AlSi10Mg processed via laser-based powder bed fusion, the material deformation mechanisms at the microscale are still unclear. To improve the current understanding, 3D measurements of the strain field at the microstructural scale are needed to complement surface-based SEM observations. This work demonstrates that X-ray tomography combined with digital volume correlation can be used to measure the strain in the bulk of AlSi10Mg using the Si-rich particles contained in the heat-treated microstructure as markers. The method allows for measuring strains larger than 0.5 % with a spatial resolution of 35 μm and it can thus be used to study the impact of factors like porosity distribution or crystallographic texture on the material deformation and damage mechanisms.