Miracle-dz/UniFAR-FTUs huggingface dataset:
Semi-supervised learning based on uncertainty estimation and image segmentation of left ventricle MRI in cardiac clinical diagnosis

Medical image segmentation is closely related to the accuracy of clinical imaging practice and diagnosis. However, the scarcity of labeled data due to rare cases and limited manpower and resources of radiologists in clinical settings has led to a shortage of annotated data. As a result, semi-supervised models have become an attractive approach. In this paper, we use an uncertainty-based estimation model for semi-supervised learning to demonstrate the effectiveness of semisupervised learning in improving the possibilities of medical image diagnosis, specifically in predicting and segmenting the left ventricle in cardiac images. In this paper, We employ the UA-MT framework, which is based on uncertainty modeling, for semi-supervised learning. We analyze and compare the segmented images generated by supervised and semisupervised learning using four labeled and eight unlabeled cardiac MRI datasets from four patients. The segmentation accuracy is evaluated through metrics such as Dice coefficient, Jaccard index, average surface distance (ASD), and Hausdorff distance (HD) to assess the differences in accuracy. Result finds that the semi-supervised learning approach improves the segmentation results by 10.24% in terms of Dice coefficient compared to supervised learning, with a decrease of 4.0 in ASD and a decrease of 8.67 in 95HD. It achieves favorable quantitative evaluation in the assisted segmentation diagnosis of left ventricle MRI in the heart. The conclusion can draw that this method exhibits higher robustness in terms of image segmentation accuracy compared to supervised learning. Its results can provide a basis for the analysis and diagnosis of left ventricular MRI images of the heart.
EXPLORING REGIONAL VARIATION IN SPATIAL LANGUAGE: A CASE STUDY ON SPATIAL ORIENTATION BY USING VOLUNTEERED SPATIAL LANGUAGE DATA

This thesis seeks to answer the question of how spatial language varies regionally within the same language on a geographic scale. Spatial language, such as route directions, is language pertaining to spatial situations and spatial relationships between objects. Spatial language is an important medium through which we study humans’ representation, perception, and communication of spatial information. Existing spatial language studies mostly use data collected via time-consuming experiments, which are therefore limited to a small sample size—thus limiting the detection of how spatial language varies from one region to another. More recently, larger sample sizes have become possible due to the abundance of volunteered spatial language data on the World Wide Web (WWW), such as directions on hotels’ websites. This data is a potential source for scaling up the analysis of spatial language data. Sourcing from the WWW, a spatial language data collection scheme has been developed. Automated webcrawling, spatial language text document classification based on computational linguistic methods, and geo-referencing of text documents are used to build a spatiallystratified corpus. Focusing on route directions on the WWW, the Spatially-strAtified Route Direction Corpus (the SARD Corpus) with more than 10,000 spatially distributed documents covering three countries (the United States, the United Kingdom, and Australia) is built. As a case study on the SARD corpus, a linguistic analysis scheme assisted by computational linguistic tools is designed based on the often raised question of cardinal versus relative direction term usage. Semantic usages of cardinal and relative
Bitcoin Layer Two Scaling Solutions: Lightening Payment Channels Network Comprehensive Review, Mechanisms, Challenges, Open Issues and Future Research Directions

Blockchain technology era is triggered due to current advancement in the decentralized paradigms via facilitating secure collaboration among untrusted entities consequently superseding the necessity for the trusted third parties’ existence. Notwithstanding its potential, blockchain scalability faces severe limitations such as low throughput, high fees, and confirmation time latency. Several scaling solutions have been proposed, including layer one solutions that substantially require fundamentally amending blockchain underlying infrastructure resulted in further scalability complications. Layer two solutions, specifically Lightning Network, is a successful cryptographic layer built atop of the Bitcoin blockchain that aims to alleviate these implications by deporting transaction processing outside blockchain while ensuring security and consensus inherited from blockchain without compromising its infrastructure. Payment channels form the core of the lightning network, facilitating fast and secure transactions between participants. However, the network encounters substantial obstacles associated with transaction amounts that exceed the current channel capacity, leading to payment failures and limiting its effectiveness. Payment Channel Networks (PCN) have been risen as an evolved replacement that solves payment channel’s issues, seeking to enhance transaction throughput and reduce confirmation delays by solving limited capacities shortages. This paper thoroughly examines PCN efficiency impacting factors that hinder its current adoption growth and avoiding its widespread employment. Additionally, existing solutions are reviewed and categorized based on the PCN building architecture. The research concludes by outlining potential research avenues and future directions to improve the efficiency and practicality of the Lightning Network PCN. This research contribution aids the advent of blockchain layer two technology and participates in its integration into real-world applications.
Shear Alfven continua and discrete modes in the presence of a magnetic island

Shear Alfvén instabilities are of considerable interest to plasma confinement and will become even more important in ITER and future devices containing strong energetic particle drive. In this dissertation, we investigate the effects of a magnetic island on the shear Alfvén continuum both analytically and numerically. Using an island coordinate system and a WKB approximation of the linearized ideal MHD equations, a shear Alfvén dispersion relation for the continuum is found globally in the presence of an island; the first time this has been obtained analytically. The island is shown to cause an upshift in the continuum accumulation point frequency. The minimum of the frequency spectrum is shifted from the rational surface to the island separatrix. This analytic result confirms previous numerical work. The new theory also identifies additional parity constraints for the continuum not captured by the previous numerical work in the field. The structure of the continuum modes is also presented. The theory is used to explain some previously uncategorized Alfvénic activity observed on the Madison Symmetric Torus (MST) reversed-field pinch during neutral beam injection. A sizable n = 5 island exists in the plasma core that has not been included in past simulations of the Alfvén spectrum in MST. The theoretical Alfvén continua in the core of the island provide a gap in which the observed n = 4 Alfvénic bursts reside, suggesting that these modes may arise from a coupling due to the island. A novel code for computing Alfvén eigenmodes called SIESTAlfvén is described. SIESTAlfvén utilizes 3D MHD equilibria with an island obtained using the SIESTA code. The Alfvén modes are computed by solving the generalized eigenvalue problem obtained from the Hessian matrix of the potential energy along with the inertia matrix of the SIESTA equilibrium. Numerical simulations using the STELLGAP/AE3D codes, as well as SIESTAlfvén, are used to identify the Alfvén bursts on MST as the first observation of an Island-induced Alfvén
Secure Beamforming for MISO Visible Light Communications With ISI and NLoS Components

For simplicity, most works on visible light communications (VLC) neglect the non-line-of-sight (NLoS) channel gain and the inter-symbol interference (ISI). This letter investigates the optimal and robust secure beamforming problems for multiple-input single-output VLC systems, where both the NLoS channel gain and ISI are considered. Under perfect channel state information (CSI), we formulate an optimal beamforming problem to maximize the secrecy rate under amplitude constraints on beamformers. The problem is shown to be nonconvex. We transform it into multiple tractable quasiconvex subproblems, and propose an iterative algorithm to solve it. To be more practical, we then consider the imperfect CSI and design the robust secure beamformers. Numerical results verify the efficiency of the proposed beamforming schemes. Moreover, it is also shown that the NLoS channel gain can improve the secrecy rate and well-designed beamformers can reverse the effect of ISI.
A method for assessing green value chain readiness

Sustainable industrialization is the 9th goal of the 17 Sustainable Development Goals (SDGs) agreed by the United Nations. Green business practice is a fundamental concept that is important for the realization of sustainable industrialization. In a business practice, there is a value chain involved. The value chain is a series of activities to increase the added value of products/services so that the business practice has a competitive advantage. The first initiative towards green business is to conduct a descriptive and diagnostic analysis of the readiness of each activity in the value chain to become green. A suitable method is needed to perform accurate descriptive and diagnostic research. This article proposes a technique for measuring the readiness of the green value chain. The measure green value chain readiness method will use STEER (Sociocultural, Technological, Economic, Ecological, and Regulatory) as the measurement dimension. STEER has been widely used for macro analysis in business investment. The proposed method captures the existing condition of a business through the green readiness of each activity in the value chain. This measurement method is built through a literature review and uses a questionnaire as a data collection tool. Simple mathematical equations will be involved in indicating the level of readiness. The measurement results with the proposed method can map the green readiness of each activity in the value chain so that the company can start an initiative for a green strategy to become a sustainable industry.
Adaptação transcultural e validade de conteúdo da Postpartum Specific Anxiety Scale (PSAS) para o português brasileiro

Objetivo: Descrever o processo de adaptação transcultural e validação de conteúdo da Postpartum Specific Anxiety Scale para o português brasileiro. Métodos: Trata-se de um estudo metodológico desenvolvido em cinco etapas: tradução, síntese, retrotradução, avaliação por especialistas e pré-teste. O comitê de especialistas, composto por 6 doutores, avaliou a equivalência semântica, idiomática, experiencial, cultural e a relevância de cada item através do Índice de Validade de Conteúdo. O pré-teste foi realizado com 30 mulheres nos primeiros 6 meses após o parto. Resultados: Após avaliação dos especialistas, seis itens não alcançaram a concordância de 80% em alguma das equivalências. Entretanto, todos os itens obtiveram concordância superior a 80% em relação à relevância. As participantes do pré-teste sugeriram alteração em um item para facilitar a compreensão. Conclusão: A Postpartum Specific Anxiety Scale foi adaptada para o português brasileiro. Contudo, é necessária a realização de estudos que avaliem suas propriedades psicométricas para que seja realizada a validação da mesma.
Multi-Scale-Denoising Residual Convolutional Network for Retinal Disease Classification Using OCT

Macular pathologies can cause significant vision loss. Optical coherence tomography (OCT) images of the retina can assist ophthalmologists in diagnosing macular diseases. Traditional deep learning networks for retinal disease classification cannot extract discriminative features under strong noise conditions in OCT images. To address this issue, we propose a multi-scale-denoising residual convolutional network (MS-DRCN) for classifying retinal diseases. Specifically, the MS-DRCN includes a soft-denoising block (SDB), a multi-scale context block (MCB), and a feature fusion block (FFB). The SDB can determine the threshold for soft thresholding automatically, which removes speckle noise features efficiently. The MCB is designed to capture multi-scale context information and strengthen extracted features. The FFB is dedicated to integrating high-resolution and low-resolution features to precisely identify variable lesion areas. Our approach achieved classification accuracies of 96.4% and 96.5% on the OCT2017 and OCT-C4 public datasets, respectively, outperforming other classification methods. To evaluate the robustness of our method, we introduced Gaussian noise and speckle noise with varying PSNRs into the test set of the OCT2017 dataset. The results of our anti-noise experiments demonstrate that our approach exhibits superior robustness compared with other methods, yielding accuracy improvements ranging from 0.6% to 2.9% when compared with ResNet under various PSNR noise conditions.
Performance Consistency Metric Considering Two-Dimensional Performance Characterization for IGBTs

IGBT is a class of power semiconductor device. Due to the limitations of the manufacturing process, the performance of IGBTs is bound to be inconsistent. Further, inconsistent performance will lead to load imbalance when IGBTs are operated in parallel, reducing their reliability. However, the complexity of performance characterization makes it difficult to measure performance consistency for IGBTs. In this paper, the performance of IGBTs is considered comprehensively and the concept of IGBT characteristic function is proposed. On this basis, the performance consistency metric for IGBTs is established. In the application case, performance tests and performance consistency evaluations are carried out on two types of IGBT products.
Cervical Dermal Sinus Tract: A Case Report and Comprehensive Literature Review

The cervical and thoracic dermal sinuses are rare entities, conforming epithelium-lined tracts that extend from an opening in the skin through a corridor to the layers of the spinal cord. They are commonly detected in early childhood; however, adult reports are singularly rare, especially in cervical regions. We report a very unusual case of a 45-year-old Mexican female who developed progressive left-side weakness and dexterity suffered from childhood, getting worse in the last year. Physical examination revealed a soft, congenital round cystic lesion in the dorsal-midline skin at the level of C4-C5 vertebrae with no previous treatment received. MRI showed a dermal sinus tract at the C4 level from the skin tethering to the spinal cord and syringomyelia. CT scan showed a dysraphism corresponding to spina bifida at the C4 level and an incomplete closure at the C3 and C5 vertebrae. We surgically managed the lesion by microscopic resection with C3-C5 laminectomy preserving strength and sensitivity. Follow-up MRI showed no residual lesion and contained fistula with no further complications. Cervical dermal sinus lesions are unusual entities, even less prevalent in adulthood. It represents a possible delay in diagnosis and an increased rate of complications. Early suspicion of the condition is required to make an accurate diagnosis since it is a potentially treatable lesion with a high risk of sequelae without surgical treatment.
Assessing the contribution of mild high-altitude exposure to obstructive sleep apnea-hypopnea syndrome comorbidities

Background Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a common sleep disorder. The lower atmospheric pressure and decreased oxygen levels of high-altitude areas can exacerbate the severity of OSAHS, but research into OSAHS in high-altitude areas remains limited. This study, from June 2015 to January 2020, involved 4,667 patients with suspected OSAHS and 38 healthy volunteers. The non-OSAHS group (AHI <5/h) had 395 patients, while the larger OSAHS group (AHI ≥5/h) comprised 4,272 patients. The significant size difference between the groups emphasized the study’s focus on OSAHS, using the non-OSAHS mainly for comparison. Methods Sleep technicians monitored the OSAHS patient group overnight by polysomnography (PSG), the apnea-hypopnea index (AHI), the mean oxygen saturation (MSpO2), lowest oxygen saturation (LSpO2), the oxygen desaturation index (ODI) and the total sleep time with oxygen saturation less than 90% (TST-SpO2 <90%). Healthy volunteers self-monitored sleep patterns at home, using the CONTEC RS01 respiration sleep monitor with a wristwatch sleep apnea screen meter. The RSO1 wristwatch-style device has already been studied for consistency and sensitivity with the Alice-6 standard multi-lead sleep monitor and can be used for OSAHS screening in this region. Results LSpO2 recordings from healthy volunteers (86.36 ± 3.57%) and non-OSAHS (AHI <5/h) cohort (78.59 ± 11.99%) were much lower than previously reported normal values. Regression analysis identified no correlations between AHI levels and MSpO2 or TST-SpO2 <90%, weak correlations between AHI levels and LSpO2 or MSpO2, and a strongly significant correlation between AHI levels and the ODI (r = 0.76, p < 0.05). The data also indicated that the appropriate clinical thresholds for OSAHS patients living at mild high altitude are classified as mild, moderate, or severe based on LSpO2 saturation criteria of 0.85–0.90, 0.65–0.84, or <0.65, respectively. Conclusion The study findings suggest that individuals with an AHI score below 5 in OSAHS, who reside in high-altitude areas, also require closer monitoring due to the elevated risk of nocturnal hypoxia. Furthermore, the significant correlation between ODI values and the severity of OSAHS emphasizes the importance of considering treatment options. Additionally, the assessment of hypoxemia severity thresholds in OSAHS patients living in high-altitude regions provides valuable insights for refining diagnostic guidelines.
Eutrophication issues attacked by a numerical model of the North Sea/Skagerrak

Several issues of eutrophication in the North Sea and Skagerrak have been attacked using a three dimensional ecological model, NORWECOM. The focus have been on two different years, 2000 and 2001, their characteristics and the differences between them. The results show that the annual depth integrated primary production in the whole North Sea is higher in 2001 than in 2000, but with large spatial differences. In the North Sea an extreme oxygen minimum were found in 2000 south of Dogger Bank that were not seen in 2001. Both the Atlantic inflow to the northern North Sea and the inflow through the English Channel were lower in 2001 than in 2000. Estimates from a long term modeling experiment, rank the Atlantic inflow in 2001 among the lowest since 1955, and the English Channel net flow in 2000 as the highest. The cross boundary flow of inorganic nitrogen from the German Bight to the Skagerrak was 50% higher in 2000 than in 2001. An eutrophication assessment from the modeled N/P ratio gives significant higher levels in 2000. The effect on this level is also documented from a reduced input of inorganic nitrogen in the river waters.
Host-directed therapy against mycobacterium tuberculosis infections with diabetes mellitus

Tuberculosis (TB) is caused by the bacterial pathogen Mycobacterium tuberculosis (MTB) and is one of the principal reasons for mortality and morbidity worldwide. Currently, recommended anti-tuberculosis drugs include isoniazid, rifampicin, ethambutol, and pyrazinamide. TB treatment is lengthy and inflicted with severe side-effects, including reduced patient compliance with treatment and promotion of drug-resistant strains. TB is also prone to other concomitant diseases such as diabetes and HIV. These drug-resistant and complex co-morbid characteristics increase the complexity of treating MTB. Host-directed therapy (HDT), which effectively eliminates MTB and minimizes inflammatory tissue damage, primarily by targeting the immune system, is currently an attractive complementary approach. The drugs used for HDT are repositioned drugs in actual clinical practice with relative safety and efficacy assurance. HDT is a potentially effective therapeutic intervention for the treatment of MTB and diabetic MTB, and can compensate for the shortcomings of current TB therapies, including the reduction of drug resistance and modulation of immune response. Here, we summarize the state-of-the-art roles and mechanisms of HDT in immune modulation and treatment of MTB, with a special focus on the role of HDT in diabetic MTB, to emphasize the potential of HDT in controlling MTB infection.
Optimal Reconfiguration of Network with Variant Transmission Times on Arcs

Contraflow means lane reversals on networks. In lane reversal reconfiguration, the capacity of the arc increases by reorienting arcs towards demand nodes, which maximizes the flow value and reduces the travel time. In this work, we survey the existing pieces of literature on single and multi-commodity contraflow problems with symmetric and asymmetric travel times on parallel but oppositely oriented edges. Many illustrations are included to support the main results.
The role of purinergic receptor A1 in neurogenesis modulation from subventricular zone

La neurogenesis continua en la edad adulta en regiones especificas del cerebro como la zona subgranular del hipocampo y la zona subventricular (SVZ) de los ventriculos laterales. Resultados previos de nuestro laboratorio demostraron que el ATP liberado tras la deprivacion de oxigeno y glucosa inhibe la neurogenesis adulta. Por lo tanto, nuestro objetivo es determinar el papel de la adenosina, uno de los productos de la hidrolisis del ATP, en la modulacion de la neurogenesis. Los resultados obtenidos demuestran que altas concentraciones de adenosina (100? M) inhiben la diferenciacion neuronal en cultivos de neuroesferas de la SVZ. Las celulas multipotentes de la SVZ expresan todos los receptores de adenosina (A1, A2a, A2b y A3); sin embargo el receptor A1 es el involucrado en la inhibicion de la diferenciacion neuronal como demostramos por PCR cuantitativa, Western Blot y en un ensayo de silenciamiento genico del receptor A1. Ademas, la activacion del receptor A1 indujo una disminucion de la expresion de genes relacionados con la neurogenesis como observamos en un analisis de expresion genica. El efecto inhibitorio de la activacion del receptor A1 fue tambien confirmado en un modelo in vivo; de manera que observamos una reduccion de la neurogenesis y un aumento de la astrogliogenesis en el bulbo olfatorio de ratas adultas tras la infusion intracerebroventricular del agonista del receptor A1 CPA. A su vez, el estudio de los mecanismos por los que la adenosina inhibe la neurogenesis y sostiene la astrogliogenesis demostraron la implicacion de la IL10 y la activacion de la ruta STAT3/Bmp2/Smad. Ademas, dado que la adenosina es liberada de forma masiva durante la isquemia cerebral, estudiamos el efecto del bloqueo del receptor A1 en un modelo de isquemia cerebral (oclusion transitoria de la arteria cerebral media). El antagonismo del receptor A1 produjo un aumento del numero de nuevas neuronas (celulas positivas para DCX/BrdU o NeuN/BrdU) asi como una reduccion de nuevos astrocitos (celulas positivas para Thbs4/GFAP/BrdU) en la zona de penumbra isquemica. En definitiva, estos resultados sugieren que la activacion del receptor A1 en isquemia puede ser un modulador de neurogenesis y astrogliogenesis.