Miracle-dz/UniFAR-FTUs huggingface dataset:
PCB Defect Detection via Local Detail and Global Dependency Information

Due to the impact of the production environment, there may be quality issues on the surface of printed circuit boards (PCBs), which could result in significant economic losses during the application process. As a result, PCB surface defect detection has become an essential step for managing PCB production quality. With the continuous advancement of PCB production technology, defects on PCBs now exhibit characteristics such as small areas and diverse styles. Utilizing global information plays a crucial role in detecting these small and variable defects. To address this challenge, we propose a novel defect detection framework named Defect Detection TRansformer (DDTR), which combines convolutional neural networks (CNNs) and transformer architectures. In the backbone, we employ the Residual Swin Transformer (ResSwinT) to extract both local detail information using ResNet and global dependency information through the Swin Transformer. This approach allows us to capture multi-scale features and enhance feature expression capabilities.In the neck of the network, we introduce spatial and channel multi-head self-attention (SCSA), enabling the network to focus on advantageous features in different dimensions. Moving to the head, we employ multiple cascaded detectors and classifiers to further improve defect detection accuracy. We conducted extensive experiments on the PKU-Market-PCB and DeepPCB datasets. Comparing our proposed DDTR framework with existing common methods, we achieved the highest F1-score and produced the most informative visualization results. Lastly, ablation experiments were performed to demonstrate the feasibility of individual modules within the DDTR framework. These experiments confirmed the effectiveness and contributions of our approach.
Amazon River and floodplain hydrodynamics

iv explicit exclusion of the floodplain, indicating that the storage volume of the floodplain has a minimal affect on the passage of the Amazon flood wave for this reach. The spatial analysis of Landsat TM images shows a total of 1,762 floodplain channels in the study area with a mean width of 47 m. Shuttle radar topography mission data has difficulty in resolving many of these floodplain channels due to 96% of the channels having a width less than the SRTM spatial resolution of 90 m. Comparing floodplain channel widths with their frequency reveals a power law relationship, showing patterns of structure that are self-similar over many orders of magnitude. Analysis of the floodplain channel network connectivity showed that the complex floodplain can be divided into floodplain hydrologic units (FHU) and that each unit type has different geomorphic characteristics resulting from a different mixture of water inputs, with each unit isolated from other units for much of the flood cycle by sediment barriers. A field survey of the floodplain channels was conducted in order to measure and characterise their morphology. The findings of this survey together with numerical connectivity experiments, demonstrate that floodplain channels could be playing a much more significant role in the floodplain hydrodynamics then previously acknowledged. Floodplain channels were grouped into three types by depth: (i) for channels carrying only river flood water, depth was strongly correlated with the flood wave’s mean annual range of 11.4 m; (ii) for channels which carried river flood water and local runoff, the mean depth was substantially deeper at 15.9 m; and, (iii) main river island channels were deeper again, with a mean depth of 17.7 m. Finally, a coherent, evidence based, conceptual floodplain hydrodynamics framework was developed to inform a broad range of future Amazon wetland research. The framework represents an extension to the macro level understanding available in the scientific literature and provides an important link between the macro and detailed level study scale.
Teachers' Perspectives on Teacher Self-Efficacy and Principal Leadership Characteristics

The purpose of this study was to investigate how elementary teachers rate their level of self-efficacy and to examine the characteristics of school leaders influencing teacher self-efficacy, including when teachers worked from home during the COVID-19 school shutdown. On the Teachers’ Sense of Efficacy Scale (TSES), all 287 participating teachers rated their self-efficacy in the high or moderate range. On the Principal Rating and Ranking Scale (PRRS), teachers reported that Communication, Inspiring Group Purpose, Consideration, and Empowering Staff were the most important characteristics of leaders related to teacher self-efficacy. The teachers interviewed reported that Communication and Flexibility were their principals’ most supportive leadership characteristics during the COVID-19 school shutdown, and that areas for improvement were more Communication, Situational Awareness, and Modelling Instructional Expectations. This work gives district leaders a clearer understanding of practices, strategies, and behaviours they can implement to improve teacher self-efficacy, teacher practice, and student achievement.
Non-contiguous Rare Presentation of Spinal Tuberculosis: A Case Report

Spinal tuberculosis (TB), also known as Pott's disease, is a severe form of extrapulmonary TB that affects the vertebral bodies and intervertebral discs. While the typical presentation involves the contiguous involvement of multiple vertebrae, atypical forms, such as non-contiguous multilevel spinal TB (NMLST), can occur. However, diagnosing spinal TB poses challenges due to its gradual onset, nonspecific symptoms, and varying imaging results. The timely diagnosis and treatment of spinal TB are critical to prevent serious consequences, including vertebral damage, irreversible neurological impairment, or even death. In this report, we present the case of a 58-year-old South Asian female who presented with several months of back pain, fatigue, and weight loss. Despite initially negative TB test results, spinal magnetic resonance imaging (MRI) raised suspicion of NMLST, which was later confirmed by bone biopsy. This case highlights the complexities of diagnosing and managing atypical spinal TB presentations while discussing the case findings and reviewing relevant research.
Variability of response spectra of single-path ground-motion record pairs

To improve the accuracy of seismic hazard analysis, understanding the uncertainty of the prediction of the ground-motion amplitude for a specific site owing to a specific source is important. In this study, the variability of the acceleration response spectra of single-path ground motion was evaluated using record pairs obtained from two earthquakes at the same site with the same magnitude, location, and focal mechanism, recorded by high-density strong-motion observation networks in Japan. The natural log standard deviations of the single-path ground motions varied with the period and were distributed in the range of approximately 0.3–0.5. Even if an empirical ground-motion prediction model that accurately models the characteristics of single-path ground motions could be developed, avoiding this variability in the prediction is difficult. The standard deviation of the within-event residuals was smaller at larger distances, and the period of the maximum standard deviation tended to increase as the earthquake magnitude increased. These features may be attributed to differences in the source characteristics of each earthquake. These findings will be useful for the development of advanced empirical ground-motion models and for improving the accuracy of seismic hazard analysis.
A See-ability Metric to Improve Mini Unmanned Aerial Vehicle Operator Awareness Using Video Georegistered to Terrain Models

A SEE-ABILITY METRIC TO IMPROVE MINI UNMANNED AERIAL VEHICLE OPERATOR AWARENESS USING VIDEO GEOREGISTERED TO TERRAIN MODELS Cameron H. Engh Department of Computer Science Master of Science Search and rescue operations conducted in wilderness environments can be greatly aided by the use of video filmed from mini-UAVs. While lightweight, inexpensive and easily transportable, these small aircraft suffer from wind buffeting and may produce video that is difficult to search. To aid in the video search process, we have created a system to project video frames into a 3D representation of the search region. This projection allows us to tie each frame of video to a real-world location, enabling a myriad of novel views, mosaics and metrics that can be used to guide the search including a new metric dubbed “see-ability. ” The “see-ability” metric is the primary contribution of this research as it indicates what portion of the search area has been viewed and provides an estimate of the quality of that viewing. The research includes a validation of the “see-ability” metric as it correlates to objective performance in the search task by real people.
A mixed-methods evaluation of capacity strengthening within an international conservation agriculture research consortium

Background: The Strengthening Capacity in Environmental Physics, Hydrogeology and Statistics for conservation agriculture research (CEPHaS) consortium sought to to strengthen research capacity among a network of African and UK researchers, and their respective institutions, to fill knowledge gaps on the impacts of conservation agriculture practices on the water cycle in cultivated soils. We examined experiences of consortium membership and, drawing on this information, determined key recommendations for future programmes with similar objectives. Methods: A mixed methods study encompassing an online survey (N=40) and semi-structured interviews (N=19) completed between June 2021 and February 2022 with CEPHaS consortium members from Malawi, UK, Zambia and Zimbabwe. Survey and interview data were analysed separately, using univariate statistics and framework synthesis respectively Results: Survey and interview findings were generally aligned, with both revealing a wide range of reported capacity strengthening gains resulting from CEPHaS engagement at both an individual and institutional level. Participants consistently expressed their CEPHaS involvement in positive terms with praise for the applied ‘learn by doing’ approach underpinning many of the activities as well as the engaging and highly inclusive leadership. There was evidence that the various trainings and resources provided through CEPHaS were valued, frequently utilised, and often transferred beyond the immediate CEPHaS membership for wider benefit. Resource provision and staff training were seen as foundational for long-term institutional benefits. Some challenges and suggested areas for improvement were reported by participants as were potential opportunities to facilitate greater impact. Conclusion: Our findings suggest that the basic ‘template’ of the CEPHaS consortium provided a strong basis for research capacity strengthening in Conservation Agriculture, especially at the level of individual researchers, and that this template could be further enhanced in any future iteration of the same or similar programme. Recommendations for replicating and enhancing CEPHaS programme strengths are presented.
Pre-service teachers and conceptions of intelligence in the Scottish context: challenging a unidimensional view

ABSTRACT This exploratory study aimed to investigate the implicit (personal theories) of student teachers through consideration of their beliefs about the nature of ability (intelligence). By drawing on ideas of personhood and identity to investigate constructions of intelligence, the authors also hoped to begin to explore the legitimacy of a multifaceted notion of individual accounts of ability. A questionnaire was administered to student teachers undertaking a one-year intensive postgraduate diploma in order to become high school teachers (n = 46) (12–18 years) or primary teachers (n = 41) (3 up to 12 years). Findings highlight the ways in which these student teachers held contrasting views of intelligence depending on their positioning and the implications for teaching decisions and children’s learning experiences.
GastroNet: Gastrointestinal Polyp and Abnormal Feature Detection and Classification With Deep Learning Approach

The early detection of digestive problems is essential for lowering the chance of acquiring any form of gastrointestinal cancer, including esophageal cancer. Endoscopy is the method that is used the majority of the time for the purpose of examining and taking photos of this sort of illness. The application of artificial intelligence is now proving to be very efficient in enhancing the identification of gastrointestinal polyps and other abnormal features located inside the gastrointestinal system. As a direct consequence of this development, the use of AI within this sector has seen substantial growth. In the framework of artificial intelligence, this research investigates how well various types of algorithms perform in terms of polyp and abnormal feature recognition accuracy, efficiency, and detection. And introduced a model in this work that is GastroNet. It is developed by doing hyperparameter fine-tuning on YOLOv5 in order to find specific polyps and abnormal characteristics, particularly esophagitis. In this method, a single neural network is used to do an analysis on the whole picture before it is disassembled into its component parts and the bounding boxes and probabilities for each one are calculated independently. The goal of the hyperparameter fine-tuning is to further enhance the overall optimization of the model. Two different methods of annotation were used on a collection of data that consisted of one thousand separate images that needed to be labelled. In addition to implementing the fine-tuned SSD model, this study used three distinct backbone networks: MobileNet v2, MobileNet v2 FPN Lite, and Resnet50 v1 FPN. Additionally, this study has used CSPdarknet53 to create the improved YOLOv4 model. The results of the studies demonstrate that the proposed model, GastroNet was effective in correctly recognizing polyps and aberrant characteristics, reaching a high mAP (mean Average Precision), F1 score, and precision with a value of 0.99 and recall with a value of 1.00. The findings of this research will be a great help to physicians in the proper identification and diagnosis of abnormal features and gastrointestinal polyps.
Allopurinol-Induced Uncommon Dermatological Emergency of Toxic Epidermal Necrolysis (TEN)

Toxic epidermal necrolysis (TEN) is a life-threatening, blistering dermatitis. It is characterized by fever and the development of mucocutaneous lesions, which lead to necrosis and sloughing of the epidermis. It is commonly triggered by medications and infections. We present the case of a 75-year-old male who presented to the hospital with a fever and widespread exfoliating skin rash involving 41% of his body surface area (BSA). He has a past medical history of gout, hypertension, asthma, and depression. He was recently started on allopurinol by his general practitioner (GP) for hyperuricemia. The condition also involved oral, eye, and pharynx mucosae. He was diagnosed with toxic epidermal necrolysis and was managed with intravenous (IV) hydrocortisone, steroid and antibiotic eye drops, and steroid and antibiotic topical creams. Due to the weak available evidence supporting the use of ciclosporin and intravenous immunoglobulins, this patient was managed with steroid use only. His rash initially worsened, but ultimately, he made a full recovery without any sequelae. The patient was reviewed in the dermatology clinic four weeks post-discharge, and he did not have any residual disease.
Governance and Development

The contemporary focus on good governance reforms in developing countries is based on developing market-enhancing governance capabilities of states. If successful, this type of governance should make markets more efficient. However, the evidence in support of these reforms is poor. Cross-sectional evidence can be used to extract some support for the importance of market-enhancing governance, but the data is weak and can support a number of different results. Some of this evidence is presented in this paper, and we argue that it actually supports the view that ‘good governance’ reforms are difficult to implement in any developing country. Rapidly growing countries in general did not enjoy better marketenhancing governance conditions compared to the others. If some developing countries nevertheless succeeded in achieving sustained convergence, they must have had other governance capabilities that allowed them to achieve this.
Expression of the ether-a-gò-gò-related gene 1 channel during B and T lymphocyte development: role in BCR and TCR signaling

The functional relevance of K+ and Ca2+ ion channels in the “Store Operated Calcium Entry” (SOCE) during B and T lymphocyte activation is well proven. However, their role in the process of T- and B- cell development and selection is still poorly defined. In this scenario, our aim was to characterize the expression of the ether à-go-go-related gene 1 (ERG1) and KV1.3 K+ channels during the early stages of mouse lymphopoiesis and analyze how they affect Ca2+signaling, or other signaling pathways, known to mediate selection and differentiation processes of lymphoid clones. We provide here evidence that the mouse (m)ERG1 is expressed in primary lymphoid organs, bone marrow (BM), and thymus of C57BL/6 and SV129 mice. This expression is particularly evident in the BM during the developmental stages of B cells, before the positive selection (large and small PreB). mERG1 is also expressed in all thymic subsets of both strains, when lymphocyte positive and negative selection occurs. Partially overlapping results were obtained for KV1.3 expression. mERG1 and KV1.3 were expressed at significantly higher levels in B-cell precursors of mice developing an experimental autoimmune encephalomyelitis (EAE). The pharmacological blockage of ERG1 channels with E4031 produced a significant reduction in intracellular Ca2+ after lymphocyte stimulation in the CD4+ and double-positive T-cell precursors’ subsets. This suggests that ERG1 might contribute to maintaining the electrochemical gradient responsible for driving Ca2+ entry, during T-cell receptor signaling which sustains lymphocyte selection checkpoints. Such role mirrors that performed by the shaker-type KV1.3 potassium channel during the activation process of mature lymphocytes. No effects on Ca2+ signaling were observed either in B-cell precursors after blocking KV1.3 with PSORA-4. In the BM, the pharmacological blockage of ERG1 channels produced an increase in ERK phosphorylation, suggesting an effect of ERG1 in regulating B-lymphocyte precursor clones’ proliferation and checkpoint escape. Overall, our results suggest a novel physiological function of ERG1 in the processes of differentiation and selection of lymphoid precursors, paving the way to further studies aimed at defining the expression and role of ERG1 channels in immune-based pathologies in addition to that during lymphocyte neoplastic transformation.
Breast Cancer Screening Using a Modified Inertial Projective Algorithms for Split Feasibility Problems

To detect breast cancer in mammography screening practice, we modify the inertial relaxed CQ algorithm with Mann's iteration for solving split feasibility problems in real Hilbert spaces to apply in an extreme learning machine as an optimizer. Weak convergence of the proposed algorithm is proved under certain mild conditions. Moreover, we present the advantage of our algorithm by comparing it with existing machine learning methods. The highest performance value of 85.03% accuracy, 82.56% precision, 87.65% recall, and 85.03% F1-score show that our algorithm performs better than the other machine learning models.
A methodology for velocity field measurement in multiphase high‐pressure flow of CO2 and water in micromodels

This paper presents a novel methodology for capturing instantaneous, temporally and spatially resolved velocity fields in an immiscible multiphase flow of liquid/supercritical CO2 and water through a porous micromodel. Of interest is quantifying pore‐scale flow processes relevant to geological CO2 sequestration and enhanced oil recovery, and in particular, at thermodynamic conditions relevant to geological reservoirs. A previously developed two‐color microscopic particle image velocimetry approach is combined with a high‐pressure apparatus, facilitating flow quantification of water interacting with supercritical CO2. This technique simultaneously resolves (in space and time) the aqueous phase velocity field as well as the dynamics of the menisci. The method and the experimental apparatus are detailed, and the results are presented to demonstrate its unique capabilities for studying pore‐scale dynamics of CO2‐water interactions. Simultaneous identification of the boundary between the two fluid phases and quantification of the instantaneous velocity field in the aqueous phase provides a step change in capability for investigating multiphase flow physics at the pore scale at reservoir‐relevant conditions.
Geographies of football: why do men play football in the Bega Valley, NSW

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Higher Order Sliding Mode Control-Based Finite-Time Constrained Stabilization

This brief addresses the problem of finite-time constrained stabilization of nonlinear systems with matched uncertainties. The constrained stabilization refers to designing of higher order finite-time control law such that the output <inline-formula> <tex-math notation="LaTeX">$ {\sigma }$ </tex-math></inline-formula> of the system remains in some prescribed range, i.e., <inline-formula> <tex-math notation="LaTeX">$ {\sigma \in (- c, c)}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${c}$ </tex-math></inline-formula> is chosen as constant while all the higher derivative of the output <inline-formula> <tex-math notation="LaTeX">$ {\sigma }$ </tex-math></inline-formula> satisfy, <inline-formula> <tex-math notation="LaTeX">${\sigma }=\ddot {\sigma }= \cdots =\dot {\sigma }^{n}=0$ </tex-math></inline-formula> in some finite interval of time. The above problem of relative degree <inline-formula> <tex-math notation="LaTeX">${n}$ </tex-math></inline-formula> with respect to output <inline-formula> <tex-math notation="LaTeX">$ {\sigma }$ </tex-math></inline-formula> cannot be directly solved by using higher order sliding mode control. Therefore, a new coordinate transformation has been proposed in this brief to reduce the relative degree of such systems by one in some pre-specified range of space. However, in the remaining space, the problem of stabilization can be solved by higher order sliding mode controller having the same relative degree. The segway application is considered as an example to demonstrate the efficacy of the proposed theory.