Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration of ATAC-Seq and RNA-Seq Analysis to Identify Key Genes in the Longissimus Dorsi Muscle Development of the Tianzhu White Yak

During the postnatal stages, skeletal muscle development undergoes a series of meticulously regulated alterations in gene expression. However, limited studies have employed chromatin accessibility to unravel the underlying molecular mechanisms governing muscle development in yak species. Therefore, we conducted an analysis of both gene expression levels and chromatin accessibility to comprehensively characterize the dynamic genome-wide chromatin accessibility during muscle growth and development in the Tianzhu white yak, thereby elucidating the features of accessible chromatin regions throughout this process. Initially, we compared the differences in chromatin accessibility between two groups and observed that calves exhibited higher levels of chromatin accessibility compared to adult cattle, particularly within ±2 kb of the transcription start site (TSS). In order to investigate the correlation between alterations in chromatin accessible regions and variations in gene expression levels, we employed a combination of ATAC-seq and RNA-seq techniques, leading to the identification of 18 central transcriptional factors (TFs) and 110 key genes with significant effects. Through further analysis, we successfully identified several TFs, including Sp1, YY1, MyoG, MEF2A and MEF2C, as well as a number of candidate genes (ANKRD2, ANKRD1, BTG2 and LMOD3) which may be closely associated with muscle growth and development. Moreover, we constructed an interactive network program encompassing hub TFs and key genes related to muscle growth and development. This innovative approach provided valuable insights into the molecular mechanism underlying skeletal muscle development in the postnatal stages of Tianzhu white yaks while also establishing a solid theoretical foundation for future research on yak muscle development.
Impact of Starting Knee Flexion Angle on Muscle Activity and Performance during Plyometrics without Jumping

Most of the existing research has focused on jump plyometrics, where landing reaction forces must be dissipated among lower limb articulations. In contrast, the investigation of resisted plyometrics without jumping, devoid of such landing forces, remains relatively limited. This study aimed to (i) investigate the impact of resisted plyometrics without jumping at two knee flexion angles (60 and 90 degrees) on vastus muscle activity relative to limb dominance and (ii) assess strength, power, and work during the concentric–eccentric phases of these exercises. Thirty-one healthy participants underwent quantification of lower limb muscle amplitude, strength, power, and work during resisted plyometrics without jumping from both 60° and 90° knee flexion positions. After anthropometric evaluations, participants used a dynamometer with a load equal to 80% of body weight while wireless surface electromyography electrodes recorded data. Statistical analyses utilized paired t-tests or nonparametric equivalents and set significance at p ≤ 0.05. Results showed significantly higher muscle activity in the vastus medialis (VM) (dominant: 47.4%, p = 0.0008, rs = 0.90; nondominant: 54.8%, p = 0.047, rs = 0.88) and vastus lateralis (VL) (dominant: 46.9%, p = 0.0004, rs = 0.86; nondominant: 48.1%, p = 0.021, rs = 0.67) muscles when exercises started at 90° knee flexion, regardless of limb dominance. Substantial intermuscle differences occurred at both 60° (50.4%, p = 0.003, rs = 0.56) and 90° (54.8%, p = 0.005, rs = 0.62) knee flexion, favoring VM in the nondominant leg. Concentric and eccentric strength, power, and work metrics significantly increased when initiating exercises from a 90° position. In conclusion, commencing resisted plyometrics without jumping at a 90° knee flexion position increases VM and VL muscle activity, regardless of limb dominance. Furthermore, it enhances strength, power, and work, emphasizing the importance of knee flexion position customization for optimizing muscle engagement and functional performance.
PAS-based analysis of natural gas samples

Photoacoustic spectroscopy (PAS) is well known for the detection of short-chain hydrocarbons, such as methane, ethane and propane, in the ppm (parts per million) or ppb (parts per billion) range. However, in the production process of natural gas and its combustion in gas-fired devices the composition, especially the concentrations of the main alkanes, plays a decisive role. Gas chromatography (GC) is considered the gold standard for natural gas analysis. We present a method to analyze natural gas samples by PAS. Furthermore, we describe a method to prepare storage gas samples, which are usually under atmospheric pressure, for PAS analysis. All measurements are validated by means of GC. The investigation allows conclusions to be drawn to what extent PAS is suitable for the investigation of natural gas samples.
Enhanced Dexterity Maps (EDM): A New Map for Manipulator Capability Analysis

The ability of a manipulator to compute a geometry-aware quality index for general tasks with different joint configurations is essential. Such workspace assessment is a well-known and studied field in existing robotics literature, often deployed through embodied structures such as voxelized maps. Notwithstanding, existing literature solely focuses on the assessment of a single pose (end-effector), neglecting the whole-body structure and its dexterity, which allows for secondary task optimization, nullspace motion, body placement, and improved manipulability. The proposed enhanced dexterity maps (EDM) aims to close these gaps using an augmented data structure. It offers a systematic analysis of disjoint flip solutions and accommodates additional performance metrics. Further analysis of EDMs through case studies highlight the limitations of existing methods and supports the need for a whole-body analysis.
Analyzing public perception toward COVID-19 vaccines in Indonesia

The research is prompted by the dearth of studies addressing public perceptions of various COVID-19 vaccines in Indonesia using extensive datasets spanning and a wide timeframe. This study examined public perception toward COVID-19 vaccines in Indonesia using a dataset of tweets. We further detect whether there are any changes in sentiment toward each type of vaccine. The five most commonly used vaccines in Indonesia (AstraZeneca, Moderna, Pfizer, Sinopharm, and Sinovac) were analyzed for sentiment using a lexicon-based method: Valence Aware Dictionary and Sentiment Reasoner (VADER), with changes in sentiment detected using Pruned Exact Linear Time (PELT). The 280,826 tweets collected between 2021 and 2022, 39% were positive, 18% were negative, and 43% were neutral. While Indonesian citizens generally responded positively and neutrally to each vaccine, with Sinopharm and Pfizer receiving the highest sentiment scores and AstraZeneca receiving the lowest, some change points in sentiment were associated with real-world events. Jakarta had the highest number of tweets (22%), while Maluku had the highest sentiment score (0.498). A significant positive correlation was also found between the total number of tweets and two variables: new cases of COVID-19 (r=0.9, p=0.001) and total new deaths caused by COVID-19 (r=0.8, p=0.008). Overall, the discussion of COVID-19 vaccines is still ongoing, and Indonesian citizens tend to respond neutrally and positively regardless of location or time.
Temporal Electroencephalography Traits Dissociating Tactile Information and Cross-Modal Congruence Effects

To explore whether temporal electroencephalography (EEG) traits can dissociate the physical properties of touching objects and the congruence effects of cross-modal stimuli, we applied a machine learning approach to two major temporal domain EEG traits, event-related potential (ERP) and somatosensory evoked potential (SEP), for each anatomical brain region. During a task in which participants had to identify one of two material surfaces as a tactile stimulus, a photo image that matched (‘congruent’) or mismatched (‘incongruent’) the material they were touching was given as a visual stimulus. Electrical stimulation was applied to the median nerve of the right wrist to evoke SEP while the participants touched the material. The classification accuracies using ERP extracted in reference to the tactile/visual stimulus onsets were significantly higher than chance levels in several regions in both congruent and incongruent conditions, whereas SEP extracted in reference to the electrical stimulus onsets resulted in no significant classification accuracies. Further analysis based on current source signals estimated using EEG revealed brain regions showing significant accuracy across conditions, suggesting that tactile-based object recognition information is encoded in the temporal domain EEG trait and broader brain regions, including the premotor, parietal, and somatosensory areas.
“They made space for me”

Drawing on 16 months of ethnographic fieldwork with young, Anglican social justice activists in Aotearoa New Zealand, this article engages with Romand Coles’s theory of receptive generosity, and the theme of the western church as marginal, to explore why a particular Anglican Diocese was attracting new, millennial aged members, most of whom did not grow up Anglican. I consider how spaces of generous reciprocity were formed and enabled through living in intentional communities (ICs) and being able to engage with pluralistic ‘broad table’ spaces of discussion and dissent. These factors were part of what drew the research participants to this Diocese and to Anglicanism in general, as well as enhancing their social justice activism. My research shows the importance of intentionally making spaces of belonging for millennials and Gen Z aged people in a faith community, rather that hoping the status quo of the past will suffice.
Acoustic characterization of pedestrian areas

Many of the actions that have been proposed to revitalize tourism projects have not taken into account the environmental context and urban heritage in which they have to be developed, threatening the viability of it. One element often overlooked is related to acoustics and how it affects the city and citizens. Our experience allows us to show that these areas with many different noise sources are being subjected to high noise levels. This could lead to social and structural deterioration of these surroundings often characterized as pedestrian areas. Moreover, European Directive 2002/49/EC notes Strategic Noise Maps as a tool for designing action plans against noise pollution, collecting information from road traffic, railway, aircraft and industrial noise. However, pedestrian areas are not taken into account for this study, and, judging by the number of complaints we should consider them as a major source of noise pollution. We propose the development of a project focused on the study of noise impact in an urban pedestrian area like the one in Leon (Spain). This will let us set out the foundation of sources found in pedestrian areas, which will help to establish a proper methodology for its analysis as part of noise maps.
Skin Cancer Detection Using Semi-Unsupervised Deep Learning in Generative Adversarial Networks: A Study on Melanoma Detection

Melanoma is widely recognized as the most life-threatening type of skin cancer, and early detection plays a critical role in improving a patient's chances of survival. While various deep learning techniques, including object detection and supervised learning utilizing frameworks such as Visual Geometry Group Neural Network (VGGNet) and Residual Neural Network (ResNet), have been employed for skin cancer detection, this study proposes the use of Deep Learning with Deep Convolutional Generative Adversarial Networks (DCGANs) to address the challenge of melanoma detection. The presented experiment achieved an accuracy of 88.33% using a model with only 9 layers and less than 700 thousand parameters, resulting in a parameter size of 2.55 MB and an estimated total size of 29.16 MB. The approach resulted in a substantial increase in both the accuracy and speed of the model, demonstrating the effectiveness of the proposed method. This methodology aligns with practical scenarios where labeling all melanoma objects by humans may not be feasible.
A Review on Human Pose Estimation Using Mediapipe

Human Posture Estimation is one of the foremost essential errands within the field of computer vision that empowers the localization and the discovery of key body points and can advantage the areas like gaming, excitement, sports investigation and numerous more. Capturing human developments, analysing them and giving feedback on execution can profoundly advantage from the Human Posture Estimation and it's dependable location. The later progressions within the field of profound learning have presently made it conceivable to create real-time frameworks that contain the capability to precisely recognize and analyse human postures in realtime.
Accessing genetic variability in Spanish barleys through high-throughput sequencing

193 Pags. - Tabls. - Grafcs. Research memory presented by Carlos Perez Cantalapiedra to obtain the title of Doctor in Plant Biology and Biotechnology from Universidad Autonoma de Barcelona (UAB). This work has been done at Estacion Experimental de Aula Dei (EEAD), belonging to Consejo Superior de Investigaciones Cientificas (CSIC), in Zaragoza
Recalibrating single-study effect sizes using hierarchical Bayesian models

Introduction There are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance. Methods We estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method. Results The results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = −0.27, p < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments. Discussion Our findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.
Alterations in cognitive function and blood biomarkers following transcranial direct current stimulation in patients with amyloid positron emission tomography-positive Alzheimer’s disease: a preliminary study

Introduction Alzheimer’s disease (AD), the most common form of dementia, is characterized by progressive cognitive decline. To address this, we conducted a randomized, double-blinded, sham-controlled study to investigate the therapeutic potential of transcranial direct current stimulation (tDCS) on patients with amyloid positron emission tomography (PET)- positive AD. Methods Participants already undergoing pharmacological treatment and testing positive for amyloid PET were divided into Active-tDCS (n = 8) and Sham-tDCS (n = 8) groups. For 12 weeks, participants or their caregivers administered daily bi-frontal tDCS (YMS-201B+, Ybrain Inc., Seongnam, Korea) at home (2 mA, 30 min). Pre- and post-intervention assessments included neuropsychological tests and blood sample measurements for oligomerized beta-amyloid. Results The Active-tDCS group demonstrated significant improvements in cognitive domains such as language abilities, verbal memory, and attention span and in frontal lobe functions compared to the Sham-tDCS group. Furthermore, the Active-tDCS group showed a marked reduction in post-intervention plasma Aβ oligomerization tendency level, suggesting changes in pivotal AD-associated biomarkers. Discussion Our results emphasize the potential therapeutic benefits of tDCS for mild AD patients with amyloid PET positivity and stress the urgency for broader research, considering the global challenges of dementia and the need to pursue innovative therapeutic strategies.
Stochastic estimation of hydraulic transmissivity fields using flow connectivity indicator data

Most methods for hydraulic test interpretation rely on a number of simplified assumptions regarding the homogeneity and isotropy of the underlying porous media. This way, the actual heterogeneity of any natural parameter, such as transmissivity ( T ), is transferred to the corresponding estimates in a way heavily dependent on the interpretation method used. An example is a long‐term pumping test interpreted by means of the Cooper‐Jacob method, which implicitly assumes a homogeneous isotropic confined aquifer. The estimates obtained from this method are not local values, but still have a clear physical meaning; the estimated T represents a regional‐scale effective value, while the log‐ratio of the normalized estimated storage coefficient, indicated by ω′ , is an indicator of flow connectivity, representative of the scale given by the distance between the pumping and the observation wells. In this work we propose a methodology to use ω′ , together with sampled local measurements of transmissivity at selected points, to map the expected value of local T values using a technique based on cokriging. Since the interpolation involves two variables measured at different support scales, a critical point is the estimation of the covariance and crosscovariance matrices. The method is applied to a synthetic field displaying statistical anisotropy, showing that the inclusion of connectivity indicators in the estimation method provide maps that effectively display preferential flow pathways, with direct consequences in solute transport.
A Dual-Agent Approach for Coordinated Task Offloading and Resource Allocation in MEC

Multiaccess edge computing (MEC) is a novel distributed computing paradigm. In this paper, we investigate the challenges of task offloading scheduling, communication bandwidth, and edge server computing resource allocation for multiple user equipments (UEs) in MEC. Our primary objective is to minimize system latency and local energy consumption. We explore the binary offloading and partial offloading methods and introduce the dual agent-TD3 (DA-TD3) algorithm based on the deep reinforcement learning (DRL) TD3 algorithm. The proposed algorithm coordinates task offloading scheduling and resource allocation for two intelligent agents. Specifically, agent 1 overcomes the action space explosion problem caused by the increasing number of UEs, by utilizing both binary and partial offloading. Agent 2 dynamically allocates communication bandwidth and computing resources to adapt to different task scenarios and network environments. Our simulation experiments demonstrate that the binary and partial offloading schemes of the DA-TD3 algorithm significantly reduce system latency and local energy consumption compared with deep deterministic policy gradient (DDPG) and other offloading schemes. Furthermore, the partial offloading optimization scheme performs the best.
First Safety and Efficacy Data with the Radiohybrid 177Lu-rhPSMA-10.1 for the Treatment of Metastatic Prostate Cancer.

We recently published the first dosimetry data, to our knowledge, for the radioligand therapy agent 177Lu-rhPSMA-10.1, providing an intrapatient comparison with 177Lu-PSMA-I&T in patients with metastatic prostate cancer. Here, we report efficacy and safety findings from these patients. Methods: Four consecutive patients with prostate-specific membrane antigen (PSMA)-positive metastatic prostate cancer received up to 6 cycles of 177Lu-rhPSMA-10.1 (7.4-7.7 GBq per cycle). Efficacy (prostate-specific antigen response according to Prostate Cancer Working Group 3 criteria and the Response Evaluation Criteria in PSMA PET/CT), progression-free survival, and overall survival were evaluated. Adverse events were recorded from the first dose until 16-24 mo after treatment. Results: The patients received a total activity of 29.6-59.4 GBq (4-6 cycles). Prostate-specific antigen was reduced by 100%, 99%, 88%, and 35%. Progression-free survival was not reached for 2 patients at 24 and 18 mo of follow-up and was 15 and 12 mo for the other 2 patients. One patient had a sustained complete response with 2 y of follow up. All patients were alive at the last time point of data collection. No serious adverse events were reported. Conclusion: 177Lu-rhPSMA-10.1 demonstrated encouraging preliminary efficacy and was well tolerated. Formal clinical trials are now under way to evaluate its potential prospectively (NCT05413850).
Using Piezosurgery in Anterior Cervical Discectomy and Fusion to Treat Complex Cervical Spondylotic Myelopathy Is Safe and Effective

Objective To investigate the safety and efficacy of piezosurgery in anterior cervical discectomy and fusion (ACDF) for cervical spondylotic myelopathy (CSM). Methods 47 patients with complex CSM (cCSM) underwent ACDF surgery from 2014 to 2017. Among these patients, 26 underwent ACDF using piezosurgery (group A) and 21 underwent ACDF by using traditional tools such as high-speed air drill, bone curette, and Kerrison bone punch (group B). Average surgical time, intraoperative blood loss, surgical complications, preoperative and postoperative Japanese Orthopaedic Association (JOA) scores, and improvement rate were measured. Results Average surgical time and intraoperative blood loss were significantly lower in group A than those in group B (P < 0.01). The incidences of surgical complications were 3.8% and 23.8% in the A and B groups (P < 0.05), respectively. There were no significant differences in JOA scores and improvement rates between data collection periods at preoperative, 3-day postoperative, and 1-year postoperative follow-ups (P > 0.05). Conclusion For treating cCSM, both the piezosurgery and traditional tools led to significant neurological improvement. However, the piezosurgery was superior to the traditional tools in terms of surgical time, blood loss, and complication rate. Hence, piezosurgery was a safe and effective adjunct for ACDF treating cCSM.