Miracle-dz/UniFAR-FTUs huggingface dataset:
iMSCGnet: Iterative Multi-Scale Context-Guided Segmentation of Skin Lesion in Dermoscopic Images

Despite much effort has been devoted to skin lesion segmentation, the performance of existing methods is still not satisfactory enough for practical applications. The challenges may include fuzzy lesion boundary, uneven and low contrast, and variation of colors across space, which often lead to fragmentary segmentation and inaccurate boundary. To alleviate this problem, we propose a multi-scale context-guided network named as MSCGnet to segment the skin lesions accurately. In MSCGnet, the context information is utilized to guide the feature encoding procedure. Moreover, because of the information loss in spatial down-sampling, a context-based attention structure (CAs) is designed to select effective context features in the decoding path. Furthermore, we boost the performance of MSCGnet with iterations and term this upgraded version as iterative MSCGnet, denoted as iMSCGnet. To supervise the training of iMSCGnet in an end-to-end fashion, a novel objective function of deep supervision, which consists of the terms of each encoding layers and the terms from each MSCGnet output of iMSCGnet, is employed. Our method is evaluated extensively on the four publicly available datasets, including ISBI2016 <xref ref-type="bibr" rid="ref1">[1]</xref>, ISBI2017 <xref ref-type="bibr" rid="ref2">[2]</xref>, ISIC2018 <xref ref-type="bibr" rid="ref3">[3]</xref> and PH2 <xref ref-type="bibr" rid="ref4">[4]</xref> datasets. The experimental results prove the effectiveness of proposed components and show that our method generally outperforms the state-of-the-art methods.
Improved Automatic Correction for Digital VLSI Circuits

The exploitation of Computer Aided Design (CAD) solutions has allowed for the development of many advances toward debugging of very-large-scale integration (VLSI) digital circuits. However, many of the established verification and debugging methods are limited to producing lists of error locations without automatic identification of design corrections. Here, we introduce an automatic correction algorithm (ACM) using an improved in-circuit mutation technique as well as improved parallel distribution of test patterns through the debugging circuit in order to generate unit clauses (UCs) using the NVidia Compute Unified Device Architecture (CUDA). Comparative analysis demonstrates that our proposed algorithm efficiently targets single design bugs of type - gate replacements in several VLSI digital circuits from ISCAS’85 and ISCAS’89 benchmarks with high performance and 100% accuracy. The proposed auto-correction algorithm with serial distribution of test patterns has achieved 5.92x speed-up using ISCAS’85 benchmark and ISCAS’89 benchmark in comparison to previously published mechanism. In addition, the combination of improved in-circuit mutation mechanism and parallelization of distributing test patterns delivers about 11.66x speed-up using ISCAS’85 and ISCAS'89 benchmarks compared to the latest existing correcting methods.
Overhang Effect Analysis of a Homopolar HTS Synchronous Generator Using 3D Finite Element Method

In this paper, the overhang effect of a homopolar synchronous generator with high-temperature superconducting (HTS) field winding is analyzed. Homopolar topology can be used to implement stationary field winding, which is advantageous for superconducting electrical rotating machine applications that rotate at a relatively high speed. The homopolar machine has an axial-winding radial-flux structure, unlike general heteropolar machines that have a radial-winding radial-flux structure. Therefore, in order to analyze the characteristics of the homopolar machine more accurately, use of 3D finite element method (FEM) should be considered. The overhang of rotor poles in electrical rotating machines can be used to enhance the flux linkage in armature windings and to improve the output power. Therefore, applying the overhang structure in the development of an electrical rotating machine is a method that can further improve the performance of the machines. In this paper, we use 3D FEM to analyze the overhang effect of a homopolar HTS synchronous generator and present the overhang length required to improve the performance of the machine.
Effect of Relative Humidity on Expenditure of Body Fluids and Blood Pressure When Exercise

Background : Physical exercise is prolonged at high relative humidity can lead to an increase in expenditure of body fluids (EBF) through perspiration. Excessive discharge can cause changes in body functions such as blood pressure changes in practice. Objective : This study aimed to prove that the relative humidity (RH) 40% inhibiting EBF and does not inhibit the increase in systolic blood pressure (SBP) and diastolic blood pressure (DBP) after physical exercise during 2X30 minutes. In addition, it also to prove physical exercise can improve exercise SBP and DBP. Methods : The study was conducted on 51 male students Faculty of Physical Education and Health , IKIP PGRI Bali. The samples were divided into three groups, and each group was given a different treatment. Group-1 exercise on the RH of 40%, Group-2 at the 50% RH, and the Group-3 at the RH of 60%. Data EBF, SBP, and DBP is measured before and after treatment. Results : The mean difference EBF, SBP, and DBP between before with after treatment in all groups increased significantly (p 0.05). Conclusion : Thus, physical exercise can improve the EBF, SBP, and DBP. RH of 40% can inhibit the EBF and can’t inhibit an increase in SBP and DBP. Thus, if practiced in a long time expected to be made on the RH of 40% because it can inhibit the EBF.
Phase-field modeling of geologic shear fracture

Geologic shear fractures such as faults and slip surfaces involve marked friction along the discontinuities as they are subjected to significant confining pressures. This friction plays a critical role in the growth of these shear fractures, as revealed by the fracture mechanics theory of Palmer and Rice decades ago. In this paper, we develop a novel phase-field model of shear fracture in pressure-sensitive geomaterials, honoring the role of friction in the fracture propagation mechanism. Building on a recently proposed phase-field method for frictional interfaces, we formulate a set of governing equations for different contact conditions (or lack thereof) in which frictional energy dissipation emerges in the crack driving force during slip. We then derive the degradation function and the threshold fracture energy of the phase-field model such that the stress-strain behavior is insensitive to the length parameter for phase-field regularization. This derivation procedure extends a methodology used in recent phase-field models of cohesive tensile fracture to shear fracture in frictional materials in which peak and residual strengths coexist and evolve by confining pressure. The resulting phase-field formulation is demonstrably consistent with the theory of Palmer and Rice. Numerical examples showcase that the proposed phase-field model is a physically sound and numerically efficient method for simulating shear fracture processes in geomaterials, such as faulting and slip surface growth.
GAMESPECT: Aspect Oriented Programming for a Video Game Engine using Meta-languages

Video game programming is an area where code duplication is extremely prevalent. Similar types of tasks are performed in multiple places throughout a game engine codebase. For example: game balance, logging, and memory allocation are just a few of the areas which are located across disparate locations of the codebase. Meanwhile, aspect oriented programming (AOP) was created to make use of common themes in a codebase and allow for advice to be given during compilation or runtime. GAMESPECT is a Domain Specific language (DSL) which resides in a higher level language space, above the typical languages used by game engines such as Unreal Engine 4. The language is written with the popular XText language toolset and contains advices in the spirit of aspect oriented programming: point cuts and join points. These advices can be executed at runtime when the programmer wants to finetune values or perform debugging. The advising is made possible through the Clang toolchain. Unique to this approach, GAMESPECT takes a source language and converts into multiple target languages. Depending on the context, GAMESPECT can generate C++, LUA, Blueprints or Skookum Script. This type of source to source translation is made possible through GAMESPECT’s “composition specifications”. With GAMESPECT, video game designers can increase their productivity and reduce the required lines of code for certain tasks by a 9–40% reduction. In addition, it provides for an AOP platform which is agnostic to the underlying game code. The applicability of this approach extends beyond game programming into software engineering as a whole.
Speech Prosody and Eye Movements in Processing Discourse Information: A Preliminary Study in Mandarin Chinese

This study investigates variations in speech prosody and eye movements and their potential correlations in processing discourse information of map direction in Mandarin Chinese. A production experiment was conducted to collect mean duration, F0, intensity of target words in speech prosody and fixation counts and fixation duration of target areas of interest in eye movements for statistical analyses. The results show fixation counts, fixation duration, and syllable duration of the target words decreased, syllable intensity increased, but syllable pitch remained intact as the information became old to the speaker in the discourse. Prosodic reduction of duration, F0, and intensity was found in speech repetition and in the processing of old information.
Multiple Linear Discriminant Models for Extracting Salient Characteristic Patterns in Capsule Endoscopy Images for Multi-Disease Detection

Background: Computer-aided disease detection schemes from wireless capsule endoscopy (WCE) videos have received great attention by the researchers for reducing physicians’ burden due to the time-consuming and risky manual review process. While single disease classification schemes are greatly dealt by the researchers in the past, developing a unified scheme which is capable of detecting multiple gastrointestinal (GI) diseases is very challenging due to the highly irregular behavior of diseased images in terms of color patterns. Method: In this paper, a computer-aided method is developed to detect multiple GI diseases from WCE videos utilizing linear discriminant analysis (LDA) based region of interest (ROI) separation scheme followed by a probabilistic model fitting approach. Commonly in training phase, as pixel-labeled images are available in small number, only the image-level annotations are used for detecting diseases in WCE images, whereas pixel-level knowledge, although a major source for learning the disease characteristics, is left unused. In view of learning the characteristic disease patterns from pixel-labeled images, a set of LDA models are trained which are later used to extract the salient ROI from WCE images both in training and testing stages. The intensity patterns of ROI are then modeled by a suitable probability distribution and the fitted parameters of the distribution are utilized as features in a supervised cascaded classification scheme. Results: For the purpose of validation of the proposed multi-disease detection scheme, a set of pixel-labeled images of bleeding, ulcer and tumor are used to extract the LDA models and then, a large WCE dataset is used for training and testing. A high level of accuracy is achieved even with a small number of pixel-labeled images. Conclusion: Therefore, the proposed scheme is expected to help physicians in reviewing a large number of WCE images to diagnose different GI diseases.
Design of Miniaturized Antenna Using Corrugated Microstrip

We present a new method to design miniaturized antennas using a corrugated microstrip (CM) line, which shows good slow wave characteristic in the required frequency band. To achieve good radiating behavior and low profile simultaneously, CM is employed as the resonating part of the antenna. The impact of the CM propagation constant on the antenna is discussed in detail. The miniaturized antenna is designed and measured to verify the feasibility of the design method. The measured results show that the proposed antenna can achieve a beamwidth of 70° in E-plane and 75° in H-plane with a gain tolerance of 3 dB, and the realized peak gain level at the central frequency is 5.15 dBi, which have good agreements to the expected designs. Such results indicate that the proposed antenna exhibits excellent radiation characteristics at the resonant mode. The effective size of the proposed miniaturized antenna is <inline-formula> <tex-math notation="LaTeX">$0.16\lambda _{0}\times 0.16 \lambda _{0}\times 0.04 \lambda _{0}$ </tex-math></inline-formula> at 9 GHz, in which <inline-formula> <tex-math notation="LaTeX">$\lambda _{0}$ </tex-math></inline-formula> is the wavelength of the central frequency.
Periodic Fast Radio Bursts as a Probe of Extragalactic Asteroid Belts

The periodic activity of the repeating fast radio burst (FRB) 180916.J0158+65 was recently reported by the CHIME/FRB Collaboration team. From this source 28 bursts not only show a ∼16 day period with an active phase of ∼4.0 days, but they also exhibit a broken power law in differential energy distribution. In this Letter, we suggest that FRB 180916.J0158+65-like periodic FRBs could provide a unique probe of extragalactic asteroid belts (EABs), based on our previously proposed pulsar-EAB impact model, in which repeating FRBs arise from an old-aged, slowly spinning, moderately magnetized pulsar traveling through an EAB around another stellar-mass object. These two objects form a binary, and thus the observed period is in fact the orbital period. We show that this model can be used to well interpret all of the observed data of FRB 180916.J0158+65. Furthermore, we constrain the EAB’s physical properties and find that (1) the outer radius of the EAB is at least an order of magnitude smaller than that of its analog in the solar system, (2) the differential size distribution of the EAB’s asteroids at small diameters (large diameters) is shallower (steeper) than that of solar system small objects, and (3) the two belts have a comparable mass.
FOAL: Fast Online Adaptive Learning for Cardiac Motion Estimation

Motion estimation of cardiac MRI videos is crucial for the evaluation of human heart anatomy and function. Recent researches show promising results with deep learning-based methods. In clinical deployment, however, they suffer dramatic performance drops due to mismatched distributions between training and testing datasets, commonly encountered in the clinical environment. On the other hand, it is arguably impossible to collect all representative datasets and to train a universal tracker before deployment. In this context, we proposed a novel fast online adaptive learning (FOAL) framework: an online gradient descent based optimizer that is optimized by a meta-learner. The meta-learner enables the online optimizer to perform a fast and robust adaptation. We evaluated our method through extensive experiments on two public clinical datasets. The results showed the superior performance of FOAL in accuracy compared to the offline-trained tracking method. On average, the FOAL took only $0.4$ second per video for online optimization.
Multiple Private Key Generation for Continuous Memoryless Sources With a Helper

We propose a method to study the secrecy constraints in key generation problems where side information might be present at untrusted users. Our method is inspired by a recent work of Hayashi and Tan who used the Rényi divergence as the secrecy measure to study the output statistics of applying hash functions to a random sequence. By generalizing the achievability result of Hayashi and Tan to the multi-terminal case, we obtain the output statistics of applying hash functions to multiple random sequences, which turn out to be an important tool in the achievability proof of strong secrecy capacity regions of key generation problems with side information at untrusted users. To illustrate the power of our method, we derive the capacity region of the multiple private key generation problem with an untrusted helper for continuous memoryless sources under Markov conditions. The converse proof of our result follows by generalizing a result of Nitinawarat and Narayan to the case with side information at untrusted users.
Artificial intelligence in glioma imaging: challenges and advances

Primary brain tumors including gliomas continue to pose significant management challenges to clinicians. While the presentation, the pathology, and the clinical course of these lesions are variable, the initial investigations are usually similar. Patients who are suspected to have a brain tumor will be assessed with computed tomography (CT) and magnetic resonance imaging (MRI). The imaging findings are used by neurosurgeons to determine the feasibility of surgical resection and plan such an undertaking. Imaging studies are also an indispensable tool in tracking tumor progression or its response to treatment. As these imaging studies are non-invasive, relatively cheap and accessible to patients, there have been many efforts over the past two decades to increase the amount of clinically-relevant information that can be extracted from brain imaging. Most recently, artificial intelligence (AI) techniques have been employed to segment and characterize brain tumors, as well as to detect progression or treatment-response. However, the clinical utility of such endeavours remains limited due to challenges in data collection and annotation, model training, and the reliability of AI-generated information. We provide a review of recent advances in addressing the above challenges. First, to overcome the challenge of data paucity, different image imputation and synthesis techniques along with annotation collection efforts are summarized. Next, various training strategies are presented to meet multiple desiderata, such as model performance, generalization ability, data privacy protection, and learning with sparse annotations. Finally, standardized performance evaluation and model interpretability methods have been reviewed. We believe that these technical approaches will facilitate the development of a fully-functional AI tool in the clinical care of patients with gliomas.
SAM: a Similarity Measure for Link Prediction in Social Network

Research in the field of social network analysis attracting majority of the researchers nowadays. Out of many social network analysis problems, link prediction gaining high attention due to a growing number of social network users. Link prediction is a task to predict which new interaction is going to be occurring in the future. Traditional link prediction techniques considered pair of node as one unit and make decisions based on the commonality between them. We argued that both nodes in a pair have their own similarity to each other. It may be that one person is 100% similar to another, but the other person is not the same as the first. Moreover, we have proposed a similarity measure SAM for link prediction in the social network. We have compared SAM similarity with four other state-of-the-art link prediction techniques (i.e., Jaccard, Salton Index, Salton Cosine and Resource Allocation). The experiments in this paper are performed on five different datasets (i.e., Astro, CondMat, GrQc, HepPh and HepTh). Our results show that SAM performs better than rest of the link prediction techniques on all datasets.
Measurement of an Uneven Terrain Model for Potential Applications in Caves

Despite the fact that cave communication has an abundant history, when an accident happened, some of the major problems are seemed to be left untreated yet. A year ago, thousands of people from around the world gathered in Thailand to help rescue one Thai soccer team who was trapped inside a cave. Tragedy could be avoided or better resolved with wireless communication inside cave. In this work, we have built an uneven terrain model for potential applications in cave environment since the ground in cave is oftentimes not flat but uneven. We performed field measurement on this uneven terrain model at 2.4 GHz. Subsequently, the measured result is compared with two ray-tracing results – one original one and another one with a scattering factor incorporated. The comparison shows that the latter ray-tracing simulation matches the measured result better, with an improved standard deviation value.
Relationship Between Vitamin D Deficiency and Metabolic Syndrome in Renal Transplant Patients in Mashhad, Iran

Background: Vitamin D is a lipophilic hormone that affects homeostasis of calcium and phosphorus. Recent studies have shown that vitamin D deficiency may be a risk factor for metabolic syndrome (MS). Also, metabolic syndrome is highly prevalent in renal transplant patients and it can be associated with graft survival reduction. Objectives: This study aimed at investigating the relationship between vitamin D deficiency and MS in renal transplant patients. Methods: This cross-sectional study was performed on 86 stable renal transplant patients in warm seasons of 2014. Metabolic syndrome was diagnosed using the modified Asian adult treatment panel III (ATP III) criteria. Patients were classified based on their serum 25-hydroxy vitamin D levels: normal (> 30 ng/mL), insufficiency (16 30 ng/mL), and deficiency (< 16 ng/mL). Patients with a history of the malabsorption syndrome, alcoholism, taking vitamin D supplementations in the last 2 months, pretransplant diabetes mellitus, and pregnancy were excluded from the study. Results: Fifty percent of the patients had MS, consisting of 48 males (55.8%) and 38 females (44.2%). The mean age of the MS group was significantly higher than the non-MS group. The body mass index in the MS group was significantly higher than the non-MS group (P = 0.001). The mean serum vitamin D level in the MS group was lower, but this difference was not significant (P = 0.914). Conclusions: Although the serum vitamin D level was lower in MS patients, it was not significant. Also, due to the high prevalence of both MS and vitamin D deficiency among renal transplant patients, we did not find any significant relation between vitamin D deficiency and MS.
Histone Signatures Predict Therapeutic Efficacy in Breast Cancer

Objective: Regulatory abnormalities caused by chromatin modifications are being increasingly recognized as contributors to cancer. While many molecularly targeted drugs have the potential to revert these modifications, their precise mechanism of action in cellular reprogramming is not known. Methods: To address this, we introduce an integrated phosphoprotein-histone-drug network (iPhDNet) approach to generate “global chromatin fingerprints of histone signatures. ” The method integrates proteomic/phosphoproteomic, transcriptomic and regulatory genomic data to provide a causal mechanistic network and histone signatures of drug response. Results: We demonstrate the utility of iPhDNet in identifying H3K27me3K36me3 histone mark as a key fingerprint of response, mediated by chromatin remodelers BRD4, NSD3, EZH2, and a proto-oncogene MYC when treated with CDK inhibitors. Conclusions: We construct a regulatory network of breast cancer response to treatment and show that histone H3K27me3K36me3 status changes, driven by the BRD4/MYC pathway, upon treatment with drugs are hallmarks of response to treatment.