Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of risk factors of pituitary neoplasms invading the sphenoidal sinus

High-resolution computed tomography (HR-CT) can more effectively discern the relationship between pituitary neoplasms (PNs) and neighboring anatomical structures. Moreover, pathological features can facilitate a more accurate determination of the growth pattern of PNs. Consequently, integrating imaging and pathological data might enhance our predictive capability regarding the growth patterns of PNs and aid in the formulation of surgical plans. We compared HR-CT images of 54 patients and 52 volunteers. Using ITK-SNAP software, we segmented and reconstructed the anatomical features of the sphenoidal sinus (SS) and calculated its volume. A comparative analysis of the invasive attributes of the 54 PNs was carried out based on clinical features and pathological data. The average volume of the SS in the volunteer group was 11.05 (8.10) mL, significantly larger than that of the PNs group at 7.45 (4.88) mL (P = .005). The postsellar type was the most common pneumatization type, and a significantly higher proportion in the PNs group exhibited a depressed saddle base (83.3%). A notable male predominance was observed for SS invasion in the PNs group (72.7%), with the Ki-67 antigen and maximum diameter significantly higher (P < .05), showing a positive correlation. The optimal cutoff points for Ki-67 antigen and the maximum diameter of PNs were 3.25% (AUC = 0.754, Sensitivity 54.5%, Specificity 90.6%) and 24.5 mm (AUC = 0.854, Sensitivity 86.4%, Specificity 78.1%), respectively. The type of pneumatization and the morphology of the sellar-floor serve as anatomical foundations for SS invasion. Factors such as the Ki-67 antigen, the maximum diameter of PNs, and high-risk sub-types constitute risk factors for PNs invasion into the SS. These insights are of significant utility for clinicians in crafting treatment strategies for PNs.
Loss of YAP1 C‐terminus expression as an ancillary marker for metaplastic thymoma: a potential pitfall in detecting YAP1::MAML2 gene rearrangement

Metaplastic thymoma is a rare thymic tumour characterized by Yes Associated Protein 1 (YAP1) and Mastermind Like Transcriptional Coactivator 2 (MAML2) gene fusions resulting from an intrachromosomal inversion of chromosome 11. Immunohistochemistry with an antibody directed against the C‐terminus of YAP1 has shown loss of expression in YAP1‐rearranged vascular neoplasms, poromas, and porocarcinomas. This study aimed to validate an anti‐YAP1 C‐terminal antibody as an ancillary immunohistochemical marker for the diagnosis of metaplastic thymoma.
Everyday Pain in Middle and Later Life: Associations with Daily and Momentary Present-Moment Awareness as One Key Facet of Mindfulness

Abstract This study investigated everyday associations between one key facet of mindfulness (allocating attention to the present moment) and pain. In Study 1, 89 community-dwelling adults (33–88 years; M age = 68.6) who had experienced a stroke provided 14 daily end-of-day present-moment awareness and pain ratings. In Study 2, 100 adults (50–85 years; M age = 67.0 years) provided momentary present-moment awareness and pain ratings three times daily for 10 days. Multi-level models showed that higher trait present-moment awareness was linked with lower overall pain (both studies). In Study 1, participants reported less pain on days on which they indicated higher present-moment awareness. In Study 2, only individuals with no post-secondary education reported less pain in moments when they indicated higher present-moment awareness. Findings add to previous research using global retrospective pain measures by showing that present-moment awareness might correlate with reduced pain experiences, assessed close in time to when they occur.
Rare and unexpected ventilation difficulties due to tracheal diverticulum: A case report

Rationale: Tracheal diverticulum is a rare airway-related particular occurrence, and the forcible tube insertion may cause tracheal ruptures during tracheotomy. Therefore, fiberoptic bronchoscopy (FOB) should be used routinely on all patients undergoing tracheal intubation or tracheotomy. Patient concerns: A 60-year-old male with laryngeal neoplasms was scheduled for partial laryngectomy using a suspension laryngoscope in July 2020. All operations were performed under general anesthesia through orotracheal intubation. Orotracheal intubation was a noninvasive procedure that could effectively control breathing. At the end of the surgery, the percutaneous tracheostomy was performed to maintain airway patency, facilitate spontaneous respiration, and remove the secretions. Diagnoses: At this moment, the tracheal diverticulum, located at the right posterolateral region of the trachea, became an unexpected airway-related particular occurrence, which led to tracheal tube placement difficulty, mechanical ventilation difficulty, and high airway pressure. Interventions: Subsequently, the tracheal tube was repositioned, with placement again confirmed by the FOB. Lessons subsections: Tracheal diverticulum is an infrequent cause of tube inserting difficulty for the tracheotomy, and FOB is the first option for patients with catheter placement difficulty and mechanical ventilation difficulty.
Penyusunan norma tes fisik pencak silat remaja kategori tanding

Penelitian ini bertujuan untuk: menyusun norma tes fisik pencak silat remaja kategori tanding. Penelitian ini menggunakan metode survei. Sampel yang digunakan dalam penelitian ini adalah atlet pencak silat remaja kategori tanding DIY yang berjumlah 42 atlet putra dan 46 atlet putri. Penyusunan norma menggunakan rumus norma 5 skala. Teknik analisis data menggunakan pearson correlation. Hasil penelitian berupa norma tes fisik pencak silat remaja kategori tanding yang terdiri dari 8 item tes, yaitu: fleksibilitas ( sit and reach ), kecepatan ( sprint 30 meter), kekuatan lengan ( push up 30 detik), kekuatan tungkai ( wall sit test ), kelincahan ( side step ), power tungkai ( standing broad jump ), daya tahan anaerobik ( sprint 300 meter), dan daya tahan aerobik ( multy fitness test ). Tes dinyatakan valid dan reliabel dengan p < 0,05. Norm drafting of pencak silat physical test for adolescent fighting category Abstract This research aimed to know the norm of pencak silat physical test for adolescent fighting category. This research used survey method. The sample in this research was 42 men and 46 women of Pencak Silat adolescent fighting category. Data analysis used Pearson correlation.The result of the research was the norm of pencak silat physical test for adolescent fighting category, it was consisting of 8 test items: flexibility (sit and reach), speed (30 meters sprint), arm strength (30 seconds push up), leg strength (wall sit test), agility (side step), leg power (standing broad jump), anaerobic endurance (300 meters sprint) and (8) aerobic endurance (multy fitness test). The test was valid and reliable with p < 0,05.
YOLOv5 spore detection algorithm for wheat powdery mildew based on attentional feature fusion

Wheat powdery mildew spore detection is one of the most common scenarios in the field of agricultural pest and disease detection. Since wheat powdery mildew spore images possess the characteristics of small spore targets, easy adhesion, shallow feature dimension, and many background clutter, it leads to the increased difficulty of wheat powdery mildew spore detection. By analyzing the above detection difficulties, a YOLOv5 wheat powdery mildew spore detection algorithm based on attentional feature fusion is proposed in this paper. Improvements are made on the basis of YOLOv5s. Firstly, an attentional mechanism-based feature fusion module AM-FF (Attentional Mechanisms-Feature Fusion) is proposed to strengthen the fusion of features at different scales, which enhances the learning ability of network contextual association by autonomously learning and selecting the optimal features through the attentional mechanism. Secondly, in order to enhance the shallow features and small target detection accuracy, we modify the original network structure to enhance the acquisition of shallow features and add fused reinforced shallow features in the neck network FPN (Feature Pyramid Networks). Finally, the SIoU (SCYLLA-IoU) loss function is introduced in order to increase the consideration of vector angle in the boundary box regression calculation, which effectively improves the detection accuracy. Experiments were conducted on the expert-labeled wheat powdery mildew spore dataset, and the final result of the algorithm experiment AP (Average Precision) was 94.23%, which was a large improvement compared with the original YOLOv5 detection algorithm vertically and also compared with the algorithm made by previous authors horizontally, and the experimental results proved the superiority of the proposed method in this paper.
A deep learning-based adaptive segmentation method for general, national, and provincial trunk roads

This paper proposed an adaptive road segmentation method based on deep learning for the typical features of variable video scenes and unfixed monitoring perspectives of general national and provincial trunk highways, and constructed an adaptive road segmentation algorithm based on Unet-VGG16 by comparing backbone feature extraction networks to achieve intelligent extraction of variable scenes and perspectives of highway pavement area. The detection accuracy of the algorithm was 95.77% and the recall rate was 96.32%, which achieved good detection performance.
Transfer learning with deep models for small food datasets

Deep Convolutional Neural Networks (DCNNs) have been used in food image classification, segmentation, gradient identification and many other applications. There are many small segments in food industry, and it is very expensive and time-consuming to build a large training dataset for each of them. Transfer learning can play a role in this aspect by reusing knowledge learned from large datasets, like ImageNet, to target tasks where only small datasets are available. In this work, we conduct an empirical study on the transfer learning capability of DCNNs pre-trained with ImageNet on four small food datasets. We find that models perform better on ImageNet dataset also have better transfer performance for small target datasets; In two transfer learning approaches, fine-turning performs better than feature extraction; Data augmentation helps in transfer learning.
Simulation of multi-factor water-floating garbage drift trajectories based on Sa-LSTM

To address the issue of low accuracy in simulating the motion trajectory of water-floating garbage due to multiple factors, a method for simulating the drift trajectory of water-floating garbage based on Sa-LSTM was proposed. The method taking the drift trajectory of water-floating garbage in Lanzhou Section of the Yellow River as the research object, integrated multiple influencing factors through feature derivation and enhanced the memory and generalization ability of LSTM model by using spatial attention module, which further improved the accuracy of water-floating garbage simulation data. The experimental results show that the proposed method can effectively reduce the interference of multiple influencing factors on the simulation of water-floating garbage drifting trajectory, improve the accuracy of drifting trajectory simulation, and provide a method and location information support for the accurate management and management of water-floating garbage.
Metabolic rewiring tunes dermal macrophages in staphylococcal skin infection

The skin needs to balance tolerance of colonizing microflora with rapid detection of potential pathogens. Flexible response mechanisms would seem most suitable to accommodate the dynamic challenges of effective antimicrobial defense and restoration of tissue homeostasis. Here, we dissected macrophage-intrinsic mechanisms and microenvironmental cues that tune macrophage signaling in localized skin infection with the colonizing and opportunistic pathogen Staphylococcus aureus. Early in skin infection, the cytokine granulocyte-macrophage colony-stimulating factor (GM-CSF) produced by γδ T cells and hypoxic conditions within the dermal microenvironment diverted macrophages away from a homeostatic M-CSF– and hypoxia-inducible factor 1α (HIF-1α)–dependent program. This allowed macrophages to be metabolically rewired for maximal inflammatory activity, which requires expression of Irg1 and generation of itaconate, but not HIF-1α. This multifactorial macrophage rewiring program was required for both the timely clearance of bacteria and for the provision of local immune memory. These findings indicate that immunometabolic conditioning allows dermal macrophages to cycle between antimicrobial activity and protection against secondary infections. Description A multifactorial program of metabolic changes is required for dermal macrophages to effectively resolve S. aureus skin infection. Editor’s summary The skin is a highly dynamic setting in which resident microflora are tolerated, but pathogens must be responded to quickly and effectively. Forde et al. analyzed the rapidly evolving role of dermal macrophages during the course of a localized skin infection with Staphylococcus aureus in a mouse model. At early times of infection, γ𝛿 T cells produced the cytokine GM-CSF, and the skin microenvironment became hypoxic, which shifted dermal macrophages away from homeostatic metabolic responses driven by M-CSF and HIF-1α. This shift allowed dermal macrophages to launch inflammatory responses driven by Irg1 expression and itaconate generation, which ultimately promoted bacterial clearance and local immune memory. These results highlight the influence of localized immunometabolomic changes in macrophages on shaping a pivotal host-microbe interface. —Christiana N. Fogg
Fisheye video stream target tracking

Moving object tracking plays a very important role in computer vision. With the advancement of science and technology, effective tracking of targets in various scenarios is a hot research direction in many fields. The emergence of fisheye cameras provides a new research direction for target tracking of video streams. With a fisheye lens, a fisheye camera can capture a wider range of images at once and obtain more information. In this paper, the inter frame difference method (IFD-method) and optical-flow method (OF-method) commonly used in the target tracking algorithm are mainly studied to realize the tracking of moving targets in fisheye video streams. Experiments show that the IFD-method, especially the three-frame IFD-method, can effectively extract the target area, while the OF-method can realize the real-time tracking of the feature points on the moving target in the array-to-array video stream.
A new deep learning-based intelligent production support system that can be used in ordinary factories

With the advancement of industry and the advent of Industry 4.0, the original traditional factories also need information and intelligent changes to adapt to the times. Our new system demonstrates a support system for mid/low-volume production, designed to help employees assemble different products with visual or tactile feedback in a traditional factory. The system records the entire workflow using multiple sensors (mainly image, motion, and electrical contact sensors) and learns to analyze each production stage through deep learning networks to set optimal values. The system compares the current state of the job with the learned target state and provides information to the employee when deviations occur so that corrections can be made on-site. After testing, the system has improved the product quality and production efficiency of the factory, meeting the standards of modern factories.
‘Without technology we’d be very stuck’: Ageing migrants’ differential (im)mobile practices during a lockdown

Ubiquitous mobile communication technologies have played an integral role in the way people navigated forced physical immobilities produced through restrictive measures during a pandemic. This paper critically investigates how 15 ageing people from Culturally and Linguistically Diverse (CALD) backgrounds in Victoria, Australia used a range of digital communication technologies and online platforms to cope during the 2020 lockdown. The study deploys the mobilities lens (Urry, 2007) in analysing a data set based on conducting remote and in-depth interviewing. It foregrounds how everyday and multi-scalar digital behaviours afford cultural and social connectedness, reflecting diverse forms of care practices. However, forced immobile practices emerged as shaped by disproportionate network capital. In sum, this study puts forward a nuanced perspective in understanding the scales and textures of (im)mobile practices of ageing migrants during a lockdown in Australia.
Synchronization of Resilient Complex Networks Under Attacks

One fundamental yet challenging issue in security control for resilient complex networks is to construct distributed control laws for the networks to perform various cooperative tasks in the presence of failures and attacks, where resilient indicates that the complex networks are exposed to the environment with cyber uncertainties and malicious adversaries. This is particularly important in today’s critical infrastructure networks since most of them are vulnerable to attacks in the era of the Internet. Inspired by this observation, this paper focuses on synchronization control for resilient complex networks subject to cyber and physical attacks, where the states of nodes being attacked may change abruptly (i.e., the synchronization error may suffer impulsive disturbances), and some nodes as well as their corresponding connections may not work in some instances. Suppose that a smart control center is equipped in the considered network to detect the attacks in real time. Furthermore, the nodes and communication channels are assumed to be recovered through some repair work after detecting the attacks. On the theoretical side, by using the ${M}$ -matrix theory, we get a few sufficient criteria to guarantee the achievement of secure synchronization against attacks on both nodes and communication links. On the algorithmic side, security control algorithm and architecture are proposed to select the coupling strength and the feedback gain matrix to realize synchronization. Finally, we perform two simulation examples to validate our theoretical results.
Observation True State Estimated State Place of Better Fitness PSfrag

We explore the use of information models as a guide for the development of single objective optimization algorithms, giving particular attention to the use of Bayesian models in a PSO context. The use of an explicit information model as the basis for particle motion provides tools for designing successful algorithms. One such algorithm is developed and shown empirically to be effective. Its relationship to other popular PSO algorithms is explored and arguments are presented that those algorithms may be developed from the same model, potentially providing new tools for their analysis and tuning.
Cardiac rehabilitation for heart failure and atrial fibrillation: a propensity- matched study

Background Atrial fibrillation (AF) is common in individuals with heart failure (HF). Individuals with HF and AF may have a reduced functional capacity and quality of life (QoL) which leads to hospital admission and burden on clinical services. Evidence supported the effect of exercise training in individuals with HF. However, there is no existing data on the effectiveness of comprehensive cardiac rehabilitation (CR) in individuals with coexisting HF and AF. Aim To explore the effect of CR in individuals with HF and AF compared with those with HF and no-coexisting AF. Methods Using CR database, individuals with HF and AF were identified and propensity matched to those with no coexisting AF. The change in incremental shuttle walking test, Heart Disease Quality of Life questionnaire, Hospital Anxiety and Depression Scores were compared between groups pre-CR and post-CR. Results 149 individuals were propensity matched from each group. The mean±SD age of the matched sample was 73.4±8 years, body mass index 29±5.5 kg/m2, left ventricular ejection fraction 35.2±9.8% and 56% were male. A statistically significant improvements in exercise capacity, heart disease QoL, anxiety and depression scores were observed within each group. There were no significant differences between groups for any of these outcome measures. Conclusions Individuals with HF and AF gain a similar improvement in exercise capacity and health related QoL outcomes as individuals with no coexisting AF following CR. The presence of AF did not compromise the effectiveness of CR.
ANATOMICAL LANDMARK BASED REGISTRATION of CONTRAST ENHANCED-T1 WEIGHTED MAGNETIC RESONANCE IMAGES

In many problems involving multiple image analysis, an image registration step is required. One such problem appears in brain tumor imaging, where baseline and follow-up image volumes from a tumor patient are often to-be compared. Nature of the registration for a change detection problem in brain tumor growth analysis is mainly rigid. Contrast enhanced T1-weighted MR images (CE-T1 MRI) are widely used in clinical practice for monitoring brain tumors. Over this modality, contours of the active tumor cells and whole tumor borders and margins are visually enhanced. In this thesis, a new technique to register serial CE-T1 MRI is presented. The proposed fully-automated method is based on five anatomical landmarks: eye balls, nose, confluence of sagittal sinus, and apex of superior sagittal sinus. After extraction of anatomical landmarks from fixed and moving volumes, a rigid transformation is estimated by minimizing the sum of squared distances between the landmark coordinates. Final result is refined with a surface registration, which is based on head masks confined to the surface of the scalp, as well as to a plane constructed from three of the extracted features. The overall registration is not intensity based, and it depends only on the inherent anatomical structures. Validation studies using both synthetically transformed MRI data, and real MRI scans, which included several markers over the head of the patient were performed. In addition, comparison studies against manual landmarks marked by a radiologist, as well as against the results obtained from ITK mean squares and cross correlation based methods were carried out to demonstrate the effectiveness of the proposed method.
Distributed autonomous coordinated control strategy for AC-DC hybrid multi-microgrid system

The interconnected operation of multiple microgrids can effectively deal with the power fluctuation caused by largescale distributed power supply access, and enhance the anti-interference ability of the system. A distributed autonomous coordinated control strategy is proposed for AC-DC hybrid multi-microgrid system. This strategy can reduce the dependence on communication system, realize power exchange among subgrids, and reduce the voltage or frequency offset of each subgrid effectively. Firstly, the reference voltage or frequency of each subgrid is established by the energy storage unit. Then, the bidirectional DC-DC converter (BDDC) or bidirectional AC-DC converter (BADC) of each subgrid adjusts the power output to ensure the reasonable power distribution of the system. Finally, the AC-DC hybrid multi-microgrid system simulation model was established in PSCAD/EMTDC, and different working conditions were simulated and verified. The simulation results show that the control strategy can realize the coordinated operation of multiple microgrids.