Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Region Growing Algorithm using Wavelet Coefficient Feature Combination of Image Dynamics

—Moving object detection has versatile and potential applications in video surveillance, traffic monitoring, human motion capture etc., where detecting object(s) in a complex scene is vital. In the existing background subtraction method based on frame differencing, the false positive and misclassification rate increases as the background becomes more complex and also with the presence of multiple moving objects in the scene. In this piece of work, an approach has been made to enhance the detection performance of the background subtraction method by exploiting the dynamism available in the scene. The resultant differencing frame so obtained by the spatial background subtraction method is subjected to wavelet transformation. By extracting and combining wavelet features from the dynamics of the scene, a novel method of region growing technique has been further utilized to detect the moving object(s) in the scene. Simulation of various video sequences from CDnet, SBMnet, AGVS, I2R and Urban Tracker database has been applied and the method provides satisfactory detection of the moving object in a complex scene. The quantitative measure like Recall, Precision, F1-measure, and specificity computed for the algorithms, have indicated the algorithms can be a suitable candidate for surveillance applications.
On the Practical Robustness of the Nesterov's Accelerated Quasi-Newton Method

This study focuses on the Nesterov's accelerated quasi-Newton (NAQ) method in the context of deep neural networks (DNN) and its applications. The thesis objective is to confirm the robustness and efficiency of Nesterov's acceleration to quasi-Netwon (QN) methods by developing practical algorithms for different fields of optimization problems.
Mapping prosody and meaning by Cantonese-speaking children with and without autism spectrum disorder

Effective usage of prosody enables speakers to stress new and important information while deemphasizing old and less important information. The current study investigates how children with and without Autism Spectrum Disorder (ASD) perceive focus-marking in Cantonese. We presented matched and mismatched conversation pairs regarding broad and narrow focus conditions to participants aged six to ten and test their ability by using a naturalness judgmental task. Compared to the performance of adults, the results showed that children have difficulties in integrating prosodic cues and information structure marking regardless of their IQ, language ability or autistic condition in general.
How Many Representatives Do We Need? The Optimal Size of a Congress Voting on Binary Issues

Aggregating opinions of a collection of agents is a question of interest to a broad array of researchers, ranging from ensemble-learning theorists to political scientists designing democratic institutions. This work investigates the optimal number of agents needed to decide on a binary issue under majority rule. We take an epistemic view where the issue at hand has a ground truth ``correct'' outcome and each one of n voters votes correctly with a fixed probability, known as their competence level or competence. These competencies come from a fixed distribution D. Observing the competencies, we must choose a specific group that will represent the population. Finally, voters sample a decision (either correct or not), and the group is correct as long as more than half the chosen representatives voted correctly. Assuming that we can identify the best experts, i.e., those with the highest competence, to form an epistemic congress we find that the optimal congress size should be linear in the population size. This result is striking because it holds even when allowing the top representatives to become arbitrarily accurate, choosing the correct outcome with probabilities approaching 1. We then analyze real-world data, observing that the actual sizes of representative bodies are much smaller than the optimal ones our theoretical results suggest. We conclude by examining under what conditions congresses of sub-optimal sizes would still outperform direct democracy, in which all voters vote. We find that a small congress would beat direct democracy if the rate at which the societal bias towards the ground truth decreases with the population size fast enough, and we quantify the speed needed for constant and polynomial congress sizes.
A Generalized Nonlinear Model of 1-bit PIN-diode Based Transmitarray Unit Cell

This paper presents the results of an analysis of the nonlinear distortions in the transmitarray unit cell caused by the control element. The model of a unit cell with a one-bit PIN diode phase shifter was developed, to evaluate the loss and third-order intermodulation products dependencies on an applied voltage. The unit cell was manufactured and measured to prove the model simulation results. Measurements results of the transmission coefficient modules and third-order intermodulation products level as function of input power for different bias voltages are in a good agreement with the simulated results. It allows using this model for the estimation of the linear and nonlinear performance of the transmitarray.
DC and Analog/RF Performance Comparison of Renovated GAA JLFET Structures

In this paper, a comparative analysis is conducted among Dual Metal Gate-All-Around Junctionless Silicon FET (DMG GAA JLFET), a high-k spacer induced symmetrically underlapped GAA JLFET (SPACER GAA JLFET) and a stacked oxide-based GAA JLFET (SO GAA JLFET) architectures to find out the suitable structure for appropriate applications. The DC and Analog/R.F. performances of proposed devices are analyzed in terms of drain current, threshold voltage, electric field, surface potential, Subthreshold swing, intrinsic capacitances, transconductances, and cut-off frequency. A detailed simulation study of the proposed structures is performed with the SILVACO ATLAS 3-D device simulator. It has been observed that SPACER-induced GAA JLFET gives the best static performances, whereas DMG and SO GAA JLFET show some significant Analog/R.F. performance improvement than their counterpart.
The P2X7R-NLRP3 and AIM2 Inflammasome Platforms Mark the Complexity/Severity of Viral or Metabolic Liver Damage

P2X7R-NLRP3 and AIM2 inflammasomes activate caspase-1 and the release of cytokines involved in viral-related liver disease. Little is known about their role in non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steato-hepatitis (NASH). We characterized the role of inflammasomes in NAFLD, NASH, and HCV. Gene expression and subcellular localization of P2X7R/P2X4R-NLRP3 and AIM2 inflammasome components were examined in histopathological preparations of 46 patients with biopsy-proven viral and metabolic liver disease using real-time PCR and immunofluorescence. P2X7R, P2X4R, and Caspase-1 are two- to five-fold more expressed in patients with NAFLD/NASH associated with chronic HCV infection than those with metabolic damage only (p ≤ 0.01 for all comparisons). The AIM2 inflammasome is 4.4 times more expressed in patients with chronic HCV infection, regardless of coexistent metabolic abnormalities (p = 0.0006). IL-2, a cytokine playing a pivotal role during chronic HCV infection, showed a similar expression in HCV and NASH patients (p = 0.77) but was virtually absent in NAFLD. The P2X7R-NLRP3 complex prevailed in infiltrating macrophages, while AIM2 was localized in Kupffer cells. Caspase-1 expression correlated with elastography-based liver fibrosis (r = 0.35, p = 0.02), whereas P2X7R, P2X4R, NRLP3, Caspase-1, and IL-2 expression correlated with circulating markers of disease severity. P2X7R and P2X4R play a major role in liver inflammation accompanying chronic HCV infection, especially when combined with metabolic damage, while AIM2 is specifically expressed in chronic viral hepatitis. We describe for the first time the hepatic expression of IL-2 in NASH, so far considered a peculiarity of HCV-related liver damage.
Skeletal Muscle Pathogenesis in Polyglutamine Diseases

Polyglutamine diseases are characterized by selective dysfunction and degeneration of specific types of neurons in the central nervous system. In addition, nonneuronal cells can also be affected as a consequence of primary degeneration or due to neuronal dysfunction. Skeletal muscle is a primary site of toxicity of polyglutamine-expanded androgen receptor, but it is also affected in other polyglutamine diseases, more likely due to neuronal dysfunction and death. Nonetheless, pathological processes occurring in skeletal muscle atrophy impact the entire body metabolism, thus actively contributing to the inexorable progression towards the late and final stages of disease. Skeletal muscle atrophy is well recapitulated in animal models of polyglutamine disease. In this review, we discuss the impact and relevance of skeletal muscle in patients affected by polyglutamine diseases and we review evidence obtained in animal models and patient-derived cells modeling skeletal muscle.
Safe Storage? An Assessment of Polyethylene for the Storage of Heritage Objects

ABSTRACT Sealable polyethylene bags are widely used to protect and store heritage items. While polyethylene is regarded as a stable material, consideration should be given to potential chemical interactions between the polymer and stored objects. The presence of additives used in manufactured polyethylene storage materials should also be considered when they are used in contact with objects. For this study, infrared spectroscopy has been successfully used to identify storage materials and associated additives, as well as to characterise the chemical changes that they undergo. Three case studies are presented that demonstrate that polyethylene bags can undergo chemical changes when exposed to the typical storage conditions used for heritage objects. The storage of degrading cellulose nitrate items shows that polyethylene undergoes oxidation when exposed to the cellulose nitrate degradation products and is identified as detrimental to long term storage viability of the polyethylene. An investigation of the yellow discolouration of polyethylene bags suggests that the oxidation of antioxidant additives, rather than the polyethylene, is responsible for the colour change. It is also demonstrated that polyethylene bags used in a procedure for the consolidation of archaeological ceramics show an interaction between the adhesive solvent employed and the bag additives.
Sparse Feature Aware Noise Removal Technique for Brain Multiple Sclerosis Lesions using Magnetic Resonance Imaging

Medical Resonance Imaging (MRI) is nonradioactive-based medical imaging that provides a superresolution of tissues. However, because of its complex nature using existing Deep Learning-based noise removal (i.e., Denoising) techniques, the reconstruction quality is poor and time-consuming. An extensive study shows very limited work has been done on Brain Multiple Sclerosis (MS) Lesions MRI. Designing an efficient noise removal technique will aid in improving MRI quality; thereby will aid in achieving better segmentation classification performance. In reducing computing time and enhancing image quality (i.e. reduce noise) this paper presents the Sparse Feature Aware Noise Removal (SFANR) technique for Brain MRI using Convolution Neural Network (CNN) architecture. A sparse-aware feature is incorporated into the patch-wise morphology learning model for removing noise in large-scale MRI MS lesion datasets. Experimental results demonstrated that our model SFANR outperforms all other state-of-art noise removal techniques in terms of Peak-SignalNoise-Ratio (PSNR), Structural Similarity Index Metric (SSIM) with less running time. Keywords—Convolution neural networks; deep learning; denoising; magnetic resonance imaging; morphology learning; multiple sclerosis; sparse features
A 23-pW NMOS-Only Voltage Reference With Optimum Body Selection for Process Compensation

This brief presents an NMOS-only voltage reference with small process variations for ultra-low-power applications. All MOSFETs work in the subthreshold region and are biased by the leakage current of the NMOS transistor manufactured in Deep-N-Well (DNW). By fitting the variations of threshold voltage (<inline-formula> <tex-math notation="LaTeX">$\text{V}_{\mathrm{ TH}}$ </tex-math></inline-formula>) from slow/fast corners to typical corners linearly, an optimum body selection (OBS) is proposed to reduce the impact of the process variations from <inline-formula> <tex-math notation="LaTeX">$\text{V}_{\mathrm{ TH}}$ </tex-math></inline-formula> or <inline-formula> <tex-math notation="LaTeX">$\Delta \text{V}_{\mathrm{ TH}}$ </tex-math></inline-formula> with the aid of the body effect. The proposed design was fabricated in a 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process, together with a baseline design without using the OBS. Based on the 25-chip measurement results, the output voltage variation of the proposed design is <inline-formula> <tex-math notation="LaTeX">$0.0035 \sigma /\mu $ </tex-math></inline-formula>, which is 61% smaller than that of the baseline design. Besides, for the proposed design with the OBS, the power consumption is 23pW (27°C), while the die area is 0.003mm2. The temperature coefficient is 52ppm/°C in a temperature range from 0°C to 85°C without trimming. The line sensitivity is 0.03%/V, and the power supply rejection ratio is 47dB at 100Hz.
Compressive optic neuropathy caused by a flow-diverter-occluded-but-still-growing supraclinoid internal carotid aneurysm: illustrative case

BACKGROUND Flow diverter stenting is an effective treatment for large proximal internal carotid artery (ICA) aneurysms. Cranial neuropathy caused by the mass effect of the aneurysm usually subsides over time. However, a new onset of compressive optic neuropathy after successful flow diverter stenting of a large proximal ICA aneurysm is seldom reported. OBSERVATIONS A 57-year-old woman had a right supraclinoid ICA aneurysm (approximately 17 mm) on magnetic resonance angiography (MRA) in a health checkup. She received intervention with the Pipeline embolization device. Six months later, she started to experience progressive hemianopia in the left half of the visual field. Nine months after stenting, MRA showed that the aneurysm was growing and causing mass effect, but digital subtraction angiography confirmed that the aneurysm was completely excluded from the circulation. She received a craniotomy for microsurgical decompression of the optic nerve and coagulation shrinkage of the aneurysm. Clipping and thrombectomy were not attempted. Her visual fields recovered gradually. Follow-up MRA showed that the aneurysm also diminished in size. LESSONS Whether the coagulation technique of the flow-diverter-occluded aneurysm alone is enough to cause satisfactory shrinkage and interaction between the flow diverter and the aneurysmal vasa vasorum/neointima formation should be further examined.
In Vitro Antifungal Susceptibility Profile of Miltefosine against a Collection of Azole and Echinocandins Resistant Fusarium Strains

Fusarium species are filamentous fungi that cause a variety of infections in humans. Because they are commonly resistant to many antifungal drugs currently available in clinical settings, research into alternative targets in fungal cells and therapeutic approaches is required. The antifungal activity of miltefosine and four comparators, amphotericin B, voriconazole, itraconazole, and caspofungin, were tested in vitro against a collection of susceptible and resistant clinical (n = 68) and environmental (n = 42) Fusarium isolates. Amphotericin B (0.8 μg/mL) had the lowest geometric mean (GM) MICs/MECs values followed by miltefosine (1.44 μg/mL), voriconazole (2.15 μg/mL), caspofungin (7.23 μg/mL), and itraconazole (14.19 μg/mL). Miltefosine was the most effective agent against Fusarium isolates after amphotericin B indicating that miltefosine has the potential to be studied as a novel treatment for Fusarium infections.
AlphaHoldem: High-Performance Artificial Intelligence for Heads-Up No-Limit Poker via End-to-End Reinforcement Learning

Heads-up no-limit Texas hold’em (HUNL) is the quintessential game with imperfect information. Representative priorworks like DeepStack and Libratus heavily rely on counter-factual regret minimization (CFR) and its variants to tackleHUNL. However, the prohibitive computation cost of CFRiteration makes it difficult for subsequent researchers to learnthe CFR model in HUNL and apply it in other practical applications. In this work, we present AlphaHoldem, a high-performance and lightweight HUNL AI obtained with an end-to-end self-play reinforcement learning framework. The proposed framework adopts a pseudo-siamese architecture to directly learn from the input state information to the output actions by competing the learned model with its different historical versions. The main technical contributions include anovel state representation of card and betting information, amultitask self-play training loss function, and a new modelevaluation and selection metric to generate the final model.In a study involving 100,000 hands of poker, AlphaHoldemdefeats Slumbot and DeepStack using only one PC with threedays training. At the same time, AlphaHoldem only takes 2.9milliseconds for each decision-making using only a singleGPU, more than 1,000 times faster than DeepStack. We release the history data among among AlphaHoldem, Slumbot,and top human professionals in the author’s GitHub repository to facilitate further studies in this direction.
Signals of Potential Species Associations Offer Clues about Community Organisation of Stream Fish across Seasons

Simple Summary Species interactions are one of the main factors affecting community assembly, yet the role of such interactions remains mostly unknown. Here, we investigated roles of potential species associations in fish community assembly in the Qiupu River, China. Our results suggested that potential species associations might have been underestimated in stream fish community assembly. The contribution of potential species associations to fish community assembly can be reflected by interaction network structures. Omnivorous species play an important role in maintaining network structure as they may have more associations with other species. This study highlights the importance of capturing species associations in river ecosystems across different geographical and environmental settings. Abstract Environmental filtering, spatial factors and species interactions are fundamental ecological mechanisms for community organisation, yet the role of such interactions across different environmental and spatial settings remains mostly unknown. In this study, we investigated fish community organisation scenarios and seasonal species-to-species associations potentially reflecting biotic associations along the Qiupu River (China). Based on a latent variable approach and a tree-based method, we compared the relative contribution of the abiotic environment, spatial covariates and potential species associations for variation in the community structure, and assessed whether different assembly scenarios were modulated by concomitant changes in the interaction network structure of fish communities across seasons. We found that potential species associations might have been underestimated in community-based assessments of stream fish. Omnivore species, since they have more associations with other species, were found to be key components sustaining fish interaction networks across different stream orders. Hence, we suggest that species interactions, such as predation and competition, likely played a key role in community structure. For instance, indices accounting for network structure, such as connectance and nestedness, were strongly correlated with the unexplained residuals from our latent variable approach, thereby re-emphasising that biotic signals, potentially reflecting species interactions, may be of primary importance in determining stream fish communities across seasons. Overall, our findings indicate that interaction network structures are a powerful tool to reflect the contribution of potential species associations to community assembly. From an applied perspective, this study should encourage freshwater ecologists to empirically capture and manage biotic constraints in stream ecosystems across different geographical and environmental settings, especially in the context of the ever-increasing impacts of human-induced local extinction debts and species invasions.
Encoding of contextual tonal alternations in word production in Teochew

Context-dependent tonal alternations occur abundantly in many Chinese dialects, but how they are encoded in speech production is still unclear. Previous research on Mandarin third-tone sandhi production has suggested that the encoding of sandhi tonal variant may involve an online computation process in the phonological encoding before articulation, but it is unknown whether this also applies to the tone sandhi in other Chinese dialects. In the current study, we employed an odd-one-out implicit priming task to investigate the encoding process of a similar tonal alternation phenomenon in Teochew (a Min Chinese dialect), whereby Tone 2 (T2) and Tone 3 (T3) exhibit different sandhi tonal variants in the non-phrasal-final positions depending on the following tones. Our two experiments showed that compared to the tonal unrelated condition, the word production latencies were significantly facilitated by a similar magnitude when the underlying tonal category was shared, regardless of the surface sandhi tonal values. These results indicate that different contextual-dependent sandhi tonal variants in Teochew are probably represented as the same underlying representation in the lexicon, but their realization is more likely to occur in the course of articulation in anticipation of the subsequent tonal context. This stands in contrast to the findings from Mandarin third-tone sandhi, suggesting different processing mechanisms could be engaged for different types of tonal alternations.
Review on primary headache among college students

Introduction: The most common sort of headache problem on the planet is primary headache disorders yet underappreciated, misunderstood, and inadequately treated, and they seem to be the third leading cause of disability in the world, because of the unpredictability of headache attacks and the existence of associated symptoms including dizziness, vomiting, nausea, and visual and/or hearing problems, persistent primary headaches can even have a massive effect on peoples’ health. Migraine, the most common cause of headache in the world, is characterized by headache bouts that last anywhere from 4 to 72 hours if left untreated. Students are more likely to experience exhaustion, stress, and worry, being the most prevalent triggers of TTH as well as migraine. Cluster Headache is amongst the most debilitating headache conditions, with a significant level of severity. CH has a lesser incidence than migraines. It hits about one out of every thousand people. Methodology: Database searches including PubMed Central, Google Scholar and Cochrane library were performed. Studies that investigated Impact of primary headache, prevalence of primary headache among students, health related quality of life in students with primary headache disorders were included and reviewed. Articles that evaluate any form of secondary headache were excluded.