ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
An Energy-Efficient High CSNR XNOR and Accumulation Scheme For BNN

In this brief, we present an energy-efficient and high compute signal-to-noise ratio (CSNR) XNOR and accumulation (XAC) scheme for binary neural networks (BNNs). Transmission gates achieve a large compute signal margin (CSM) and high CSNR for accurate XAC operation. The 10T1C XNOR SRAM bit-cell performs the in-memory XAC operation without pre-charging the larger bitline capacitances and significantly reducing energy consumption per XAC operation. The validation of the proposed XAC scheme is done through the post-layout simulations in 65nm CMOS technology with V-DD of 1 V. The achieved 1 ns of latency and 2.36 fJ of energy consumption per XAC operation are (7.2 x , 7.2 x ) and (2 x , 1.31 x ) lower than state-of-the-art digital and analog compute in-memory (CIM) XAC schemes respectively. The proposed XAC design achieves 8.6 x improvement in figure-of-merit (FoM), over prior state-of-the-art. Moreover, (sigma/mu) average of 0.2% from Monte Carlo simulations show that proposed XAC scheme is robust against systematic mismatch and process variations.
Sparsity-Driven Despeckling for SAR Images

Speckle noise inherent in synthetic aperture radar (SAR) images seriously affects the result of various SAR image processing tasks such as edge detection and segmentation. Thus, speckle reduction is critical and is used as a preprocessing step for smoothing homogeneous regions while preserving features such as edges and point scatterers. Although state-of-the-art methods provide better despeckling compared with conventional methods, their resource consumption is higher. In this letter, a sparsitydriven total-variation (TV) approach employing l0-norm, fractional norm, or l(1)-norm to smooth homogeneous regions with minimal degradation in edges and point scatterers is proposed. Proposed method, sparsity-driven despeckling (SDD), is capable of using different norms controlled by a single parameter and provides better or similar despeckling compared with the state-of-the-art methods with shorter execution times. Despeckling performance and execution time of the SDD are shown using synthetic and real-world SAR images.
Circuit-Based Approaches to Understanding Corticostriatothalamic Dysfunction Across the Psychosis Continuum

Dopamine is known to play a role in the pathogenesis of psychotic symptoms, but the mechanisms driving dopaminergic dysfunction in psychosis remain unclear. Considerable attention has focused on the role of corticostriatothalamic (CST) circuits, given that they regulate and are modulated by the activity of dopaminergic cells in the midbrain. Preclinical studies have proposed multiple models of CST dysfunction in psychosis, each prioritizing different brain regions and pathophysiological mechanisms. A particular challenge is that CST circuits have undergone considerable evolutionary modification across mammals, complicating comparisons across species. Here, we consider preclinical models of CST dysfunction in psychosis and evaluate the degree to which they are supported by evidence from human resting-state functional magnetic resonance imaging studies conducted across the psychosis continuum, ranging from subclinical schizotypy to established schizophrenia. In partial support of some preclinical models, human studies indicate that dorsal CST and hippocampal-striatal functional dysconnectivity are apparent across the psychosis spectrum and may represent a vulnerability marker for psychosis. In contrast, midbrain dysfunction may emerge when symptoms warrant clinical assistance and may thus be a trigger for illness onset. The major difference between clinical and preclinical findings is the strong involvement of the dorsal CST in the former, consistent with an increasing prominence of this circuitry in the primate brain. We close by underscoring the need for high-resolution characterization of phenotypic heterogeneity in psychosis to develop a refined understanding of how the dysfunction of specific circuit elements gives rise to distinct symptom profiles.
The Effects of Adding Art Therapy to Ongoing Antidepressant Treatment in Moderate-to-Severe Major Depressive Disorder: A Randomized Controlled Study

This randomized controlled study aimed to investigate the effects of art psychotherapy on moderate-to-severe major depressive disorder (MDD). Forty-two MDD patients were recruited from a psychiatric outpatient clinic in Seoul, the Republic of Korea. Participants were allocated on a randomized, open-label basis to either an experimental group, wherein they were treated with art psychotherapy added to pharmacotherapy, or a control group, wherein they were treated with pharmacotherapy alone. Pre- and post-test measures of the Hamilton Depression Rating Scale, Beck Depression Inventory-II, and remission rates were measured. The results indicate that patients treated with art psychotherapy and ongoing pharmacotherapy showed slightly greater improvement when compared with pharmacotherapy alone in moderate-to-severe MDD. These results suggest that art psychotherapy could be an effective add-on strategy for the treatment of moderate-to-severe MDD. However, a rigorous test would facilitate a better understanding of art psychotherapy as an add-on strategy for MDD treatment.
Fast 3-D Image Reconstruction on Nonregular UWB Sparse MIMO Planar Array Using Scaling Techniques

This article proposes a novel multistatic scaling algorithm for fast 3-D imaging with an ultrawideband (UWB) multiple-input-multiple-output (MIMO) planar array architecture. The proposed imaging method well addresses the weaknesses of the state-of-the-art imaging techniques, such as heavy computation burden and requirement of regular MIMO topologies. The key range cell migration in MIMO data set is corrected by a multistatic scaling operation. Only the fast Fourier transform and multiplications are employed during the entire imaging procedure that is easy to implement. For an arbitrary MIMO planar array, the computation complexity of the algorithm is O(N(5)log(2)N), which is lower than the optimum backpropagation and omega-K techniques. We have designed a 16 x 16 UWB sparse MIMO planar array with nonregular topology in our experiments. Results with both synthetic and practical data demonstrate the accuracy and efficiency of the algorithm, i.e., it obtains images of the same quality with much less time compared with the state-of-the-art other imaging algorithms.
Cyberchondria, Anxiety Sensitivity, Hypochondria, and Internet Addiction: Implications for Mental Health Professionals

Repetitive online searches for health information increase anxieties and result in Internet addiction. Internet addiction, cyberchondria, anxiety sensitivity, and hypochondria have been studied separately, but how these concepts are reciprocally linked has not been investigated. This study aimed to determine the levels, correlations, and predictors of Internet addiction, cyberchondria, anxiety sensitivity, and hypochondria among students based on the sample's characteristics. A sample of 143 university students participated in this cross-sectional online survey. A self-reported questionnaire was employed to collect data from students. The studied concepts had moderate to high correlations with each other and with the students' characteristics. Not getting infected with the coronavirus was among the demographic factors inserted into the regression model that only predicted cyberchondria. The model of cyberchondria was significant and explained 11.5% of the variance in the score of concepts. The results of the standard regression analysis indicated that the model predicting Internet addiction accounted for 41.2% of the variability. Our unique findings indicate that cyberchondria can contribute to developing Internet addiction compared to earlier studies. The findings suggest the importance of empowering students to overcome their anxieties by managing cyberchondria and Internet addiction. Mental health professionals, namely psychiatric nurses, are at the forefront of taking preventive mental health measures on campus, such as screening and referring students who exhibit these problems to psychological support and counseling to cope with their anxieties.
MOANA: An Online Learned Adaptive Appearance Model for Robust Multiple Object Tracking in 3D

Multiple object tracking has been a challenging field, mainly due to noisy detection sets an identity switch caused by occlusion and similar appearance among nearby targets. Previous works rely on appearance models that are built on an individual or several selected frames for the comparison of features, but they cannot encode the long-term appearance changes caused by pose, viewing angle, and lighting conditions. In this paper, we propose an adaptive model that learns online a relatively long-term appearance change of each target. The proposed model is compatible with any feature of fixed dimension or their combination, whose learning rates are dynamically controlled by the adaptive update and spatial weighting schemes. To handle occlusion and nearby objects that are sharing a similar appearance, we also design the cross-matching and re-identification schemes based on the application of the proposed adaptive appearance models. In addition, the 3D geometry information is effectively incorporated in our formulation for data association. The proposed method outperforms all the state of the art on the MOTChallenge 3D benchmark and achieves real-time computation with only a standard desktop CPU. It has also shown superior performance over the state of the art on the 2D benchmark of MOTChallenge.
Spatially Consistent Supervoxel Correspondences of Cone-Beam Computed Tomography Images

Establishingdense correspondencesof conebeam computed tomography (CBCT) images is a crucial step for the attribute transfer and morphological variation assessment in clinical orthodontics. In this paper, a novel method, unsupervised spatially consistent clustering forest, is proposed to tackle the challenges for automatic supervoxel-wise correspondences of CBCT images. A complexity analysis of the proposed method with respect to the clustering hypotheses is provided with a data-dependent learning guarantee. The learning bound considers both the sequential tree traversals determined by questions stored in branch nodes and the clustering compactness of leaf nodes. A novel tree- pruning algorithm, guided by the learning bound, is also proposed to remove locally inconsistent leaf nodes. The resulting forest yields spatially consistent affinity estimations, thanks to the pruning penalizing trees with inconsistent leaf assignments and the combinational contextual feature channels used to learn the forest. A forest- based metric is utilized to derive the pairwise affinities and dense correspondences of CBCT images. The proposedmethod has been applied to the label propagation of clinically captured CBCT images. In the experiments, the method outperforms variants of both supervised and unsupervised forest- based methods and state-of-the- art label-propagation methods, achieving the mean dice similarity coefficients of 0.92, 0.89, 0.94, and 0.93 for the mandible, the maxilla, the zygoma arch, and the teeth data, respectively.
Simple production of resilin-like protein hydrogels using the Brevibacillus secretory expression system and column-free purification

Resilin, an insect structural protein, has excellent flexibility, photocrosslinking properties, and temperature responsiveness. Recombinant resilin-like proteins (RLPs) can be fabricated into three-dimensional (3D) structures for use as cell culture substrates and highly elastic materials. A simplified, high-yielding production process for RLPs is required for their widespread application. This study proposes a simple production process combining extracellular expression using Brevibacillus choshinensis (B. choshinensis) and rapid column-free purification. Extracellular production was tested using four representative signal peptides; B. choshinensis was found to efficiently secrete Rec1, an RLP derived from Drosophila melanogaster, regardless of the type of signal peptide. However, it was suggested that Rec1 is altered by an increase in the pH of the culture medium associated with prolonged incubation. Production in a jar fermentor with controllable pH yielded 530 mg Rec1 per liter of culture medium, which is superior to productivity using other hosts. The secreted Rec1 was purified from the culture supernatant via (NH4 )2 SO4 and ethanol precipitations, and the purified Rec1 was applied to ring-shaped 3D hydrogels. These results indicate that the combination of secretory production using B. choshinensis and column-free purification can accelerate the further application of RLPs.
Development and validation of a potential biomarker to improve the assessment of liver fibrosis progression in patients with chronic hepatitis B

We aimed to develop and validate a novel combined score to improve the assessment of liver fibrosis progression in patients with chronic hepatitis B (CHB). In this study, a total of 331 CHB patients from three cohorts who underwent liver biopsy were enrolled, and the Scheuer system was used for liver fibrosis classification. The combined score was derived by principal component analysis of key differentially expressed genes. For significant liver fibrosis (≥S2), the areas under the receiver operating characteristics curves (AUROCs) of the combined score were 0.838, 0.842, and 0.881 in the three cohorts, respectively. And for advanced liver fibrosis (≥S3), the AUROCs were 0.794, 0.801, and 0.901, respectively. Compared with the results of AUROCs for aspartate aminotransferase≥to≥platelet ratio (APRI) and fibrosis index based on four factors (FIB-4) in the validation cohorts, better clinical diagnostic value for assessing the progression of liver fibrosis was found in the combined score. Additionally, univariate ordered logistic regression analysis indicated that the combined score could serve as a more superior and stable risk factor than APRI and FIB-4 in the assessment of liver fibrosis. For CHB patients with normal alanine aminotransferase (ALT), our results further emphasized the diagnostic value of the combined score for significant fibrosis (≥S2) and advanced fibrosis (≥S3). Moreover, it was found that patients with the high combined score, who were associated with the advanced fibrosis stage, had higher levels of drug sensitivity and immune checkpoint expression. In conclusion, the novel combined score could serve as a potential biomarker and contribute to improving the assessment of fibrosis stage in CHB patients.
A large-scale study of the Trichinella genus in the golden jackal (Canis aureus) population in Serbia

Over the last decades the golden jackal (Canis aureus) has significantly expanded its range throughout Southeast and Central Europe, and the Balkan Peninsula is considered to be a core area of the species distribution in this part of the range. Due to its increasing number, ability of long distance movement through a wide range of landscapes and opportunistic feeding habits, the golden jackal may represent an important reservoir and transmitter of a variety of zoonotic agents, including parasites. The Balkans, Serbia included, remain an endemic area for various zoonotic parasites including Trichinella spp. Trichinella has recently been recorded in jackals in Serbia, which prompted us to carry out a large-scale survey of its prevalence, distribution and species identification in this host. In cooperation with local hunters, carcasses of a total of 738 legally hunted golden jackals were collected at 24 localities over an 11-year period (2003-2013). Analysis of tongue base tissue revealed Trichinella larvae in 122, indicating a prevalence of infection of 16.5%. No difference in the prevalence of infection was found between genders [16.2% in males and 16.9% in females (χ(2)=0.05, p=0.821)], or among the study years (G=7.22, p=0.705). Trichinella larvae were found in 13 out of the 24 examined localities. Molecular identification was performed for 90 isolates, and 64 (71.1%) larvae were identified as Trichinella spiralis and 25 (27.9%) as Trichinella britovi. Mixed infection (T. spiralis and T. britovi) was recorded in a single case. Although T. spiralis was more prevalent, T. britovi had a wider distribution, and was the only recorded species in jackal populations from the mountainous region of eastern Serbia. On the other hand, T. spiralis was dominant in jackals in the lowlands of central and northern Serbia, where domestic pigs are mostly reared. These results show that the golden jackal is involved in both the domestic and sylvatic cycle, and that it has emerged as a major host species in the sylvatic cycle of the Trichinella genus. Therefore, continued monitoring of Trichinella infection in golden jackals in Serbia and the whole of the Balkans is recommended in order to control transmission of this parasite to humans and domestic animals.
The Expected Job Satisfaction Affecting Entrepreneurial Intention as Career Choice in the Cultural and Artistic Industry

Artists have chosen a career between employment and self-employment. We studied the factors that influence career choices. We examined the effects of work conditions and employability on job satisfaction, and examined the effect of job satisfaction, outcome expectations and self-efficacy on entrepreneurial intentions. In addition, this study examined whether heuristic factors influence entrepreneurial intentions. Our findings suggest that perceived employability positively affected job satisfaction, while expectation gaps in working conditions negatively affected job satisfaction. Secondly, job satisfaction had a negative effect on entrepreneurial intention. In addition, self-efficacy and outcome expectations mediated between job satisfaction and entrepreneurial intention. Finally, overconfidence was positively influenced by job satisfaction and positively affected self-efficacy. This study contributed the study of the entrepreneurial intent to the field of culture and arts. It confirmed the effect of career choice and heuristic factors on entrepreneurial intention.
Morphological instability and roughening of growing 3D bacterial colonies

How do growing bacterial colonies get their shapes? While colony morphogenesis is well studied in two dimensions, many bacteria grow as large colonies in three-dimensional (3D) environments, such as gels and tissues in the body or subsurface soils and sediments. Here, we describe the morphodynamics of large colonies of bacteria growing in three dimensions. Using experiments in transparent 3D granular hydrogel matrices, we show that dense colonies of four different species of bacteria generically become morphologically unstable and roughen as they consume nutrients and grow beyond a critical size-eventually adopting a characteristic branched, broccoli-like morphology independent of variations in the cell type and environmental conditions. This behavior reflects a key difference between two-dimensional (2D) and 3D colonies; while a 2D colony may access the nutrients needed for growth from the third dimension, a 3D colony inevitably becomes nutrient limited in its interior, driving a transition to unstable growth at its surface. We elucidate the onset of the instability using linear stability analysis and numerical simulations of a continuum model that treats the colony as an "active fluid" whose dynamics are driven by nutrient-dependent cellular growth. We find that when all dimensions of the colony substantially exceed the nutrient penetration length, nutrient-limited growth drives a 3D morphological instability that recapitulates essential features of the experimental observations. Our work thus provides a framework to predict and control the organization of growing colonies-as well as other forms of growing active matter, such as tumors and engineered living materials-in 3D environments.
A blast fungus zinc-finger fold effector binds to a hydrophobic pocket in host Exo70 proteins to modulate immune recognition in rice

Exocytosis plays an important role in plant-microbe interactions, in both pathogenesis and symbiosis. Exo70 proteins are integral components of the exocyst, an octameric complex that mediates tethering of vesicles to membranes in eukaryotes. Although plant Exo70s are known to be targeted by pathogen effectors, the underpinning molecular mechanisms and the impact of this interaction on infection are poorly understood. Here, we show the molecular basis of the association between the effector AVR-Pii of the blast fungus Maganaporthe oryzae and rice Exo70 alleles OsExo70F2 and OsExo70F3, which is sensed by the immune receptor pair Pii via an integrated RIN4/NOI domain. The crystal structure of AVR-Pii in complex with OsExo70F2 reveals that the effector binds to a conserved hydrophobic pocket in Exo70, defining an effector/target binding interface. Structure-guided and random mutagenesis validates the importance of AVR-Pii residues at the Exo70 binding interface to sustain protein association and disease resistance in rice when challenged with fungal strains expressing effector mutants. Furthermore, the structure of AVR-Pii defines a zinc-finger effector fold (ZiF) distinct from the MAX (Magnaporthe Avrs and ToxB-like) fold previously described for a majority of characterized M. oryzae effectors. Our data suggest that blast fungus ZiF effectors bind a conserved Exo70 interface to manipulate plant exocytosis and that these effectors are also baited by plant immune receptors, pointing to new opportunities for engineering disease resistance.
Accelerated 3D bSSFP Using a Modified Wave-CAIPI Technique With Truncated Wave Gradients

The Wave Controlled Aliasing In Parallel Imaging (Wave-CAIPI) technique manifests great potential to highly accelerate three-dimensional (3D) balanced steady- state free precession (bSSFP) through substantially reducing the geometric factor (g-factor) and aliasing artifacts of image reconstruction. However, severe banding artifacts appear in bSSFP imaging due to unbalanced gradients with nonzero 0th moment applied by the conventional Wave-CAIPI technique. In this study, we propose a 3DWave-bSSFP scheme that adopts truncated wave gradients with zero 0th moment to avoid introducing additional banding artifacts and to maintain the advantages of wave encoding. The simulation results indicate that the number of wave cycles that are truncated and different options of applying wave gradients affect both the g-factor reduction and image quality, but the influence is limited. In phantom experiments, the proposed technique shows similar acceleration performance as the conventional Wave-CAIPI technique and effectively eliminates its introduced banding artifacts. Additionally, Wave-bSSFP obtains up to 12x retrospective acceleration at 0.8 mm isotropic resolution in in vivo 3D brain experiments and is superior to the state-of-the-art Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration ( CAIPIRINHA) technique, according to both visual validation and quantitative analysis. Moreover, in vivo 3D spine and abdomen imaging demonstrate the potential clinical applications of Wave-bSSFP with fast acquisition speed, improved isotropic resolution and fine image quality.