ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
View-based 3D object retrieval via multi-modal graph learning

Content-based 3D object retrieval has wide applications in various domains, ranging from virtual reality to computer aided design and entertainment With the rapid development of digitizing technologies, different views of 3D objects are captured, which requires for effective and efficient view-based 3D object retrieval (V3DOR) techniques. As each object is represented by a set of multiple views, V3DOR becomes a group matching problem. Most of state-of-the-art V3DOR methods use one single feature to describe a 3D object, which is often insufficient. In this paper, we propose a feature fusion method via multi-modal graph learning for view-based 3D object retrieval. Firstly, different visual features, including 2D Zernike moments, 2D Fourier descriptor and 2D Krawtchouk moments, are extracted to describe each view of a 3D object Then the Hausdorff distance is computed to measure the similarity between two 3D objects with multiple views. Finally we construct multiple graphs based on different features and learn the optimized weights of each graph automatically for feature fusion task. Extensive experiments are conducted on the ETH-80 dataset and the National Taiwan University 3D model dataset. The results demonstrate the superior performance of the proposed method, as compared to the state-of-the-art approaches. (C) 2014 Elsevier B.V. All rights reserved.
Emission Characteristics and Formation Mechanism of Carbonyl Compounds from Residential Solid Fuel Combustion Based on Real-World Measurements and Tube-Furnace Experiments

This study updated carbonyl compound (CC) emission factors (EFs) and composition for residential solid fuel combustion based on real-world measurements of 124 fuel/stove combinations in China and explored the CC formation mechanism using tube-furnace experiments with 19 fuels and low/high temperatures to explain the impact of fuel and stove on CC emission characteristics. The average EFCC values for straw, wood, and coal were 1.94 ± 1.57, 1.50 ± 0.88, and 0.40 ± 0.54 g/kg, respectively. Formaldehyde and acetaldehyde were the most abundant species, accounting for 40-60% of CCs, followed by acetone (∼20%), aromatic aldehydes (∼10%), and unsaturated aldehydes (∼5%). Different from formaldehyde and acetaldehyde, other species showed significant variation among fuel types. All these characteristics could be explained by the difference in the volatile content and chemical structure of fuel, such as aromatic in coal versus lignin in biomass. The improvement in stove technology reduced CC emissions by 30.4-69.7% (mainly formaldehyde and acetaldehyde) among fuels but increased the proportion of aromatic aldehydes by 24.3-89.4%. Various CC species showed different formation mechanisms related to fuel property and burning temperature. The volatile matter derived from thermal pyrolysis of fuel polymers determined CC composition, while higher temperature preferentially degraded formaldehyde and acetaldehyde but promoted the formation of acetone and aromatic aldehydes. This study not only revealed emission characteristic of CCs from RSFC but also contributed to the improvement of clean combustion technology.
A new approach to clustering data with arbitrary shapes

In this paper we propose a clustering algorithm to cluster data with arbitrary shapes without knowing the number of clusters in advance. The proposed algorithm is a two-stage algorithm. In the first stage, a neural network incorporated with an ART-like training algorithm is used to cluster data into a set of multi-dimensional hyperellipsoids. At the second stage, a dendrogram is built to complement the neural network. We then use dendrograms and so-called tables of relative frequency counts to help analysts to pick some trustable clustering results from a lot of different clustering results. Several data sets were tested to demonstrate the performance of the proposed algorithm. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Monkeypox in Pregnancy: Susceptibility, Maternal and Fetal Outcomes, and One Health Concept

An overlooked endemic zoonosis in Africa, monkeypox infection, which has spread to multiple non-endemic countries since early May 2022, was declared a Public Health Emergency of International Concern by the World Health Organization on July 23, 2022. As of August 8, 2022, over 28,000 confirmed and probable monkeypox cases were reported globally, including 6 deaths from the African continent and 4 deaths from the non-endemic regions. Although the current outbreak mostly belongs to the West African clade, which has a lower-case fatality ratio of <1%, there is limited data among immune-weakened individuals infected with monkeypox. It is still unknown if pregnant people are more susceptible to monkeypox. In addition, it is unclear whether having monkeypox increases the risk of birth defects. This commentary addresses reported cases of monkeypox infection in pregnancy and the possible maternal and fetal outcomes, including congenital monkeypox, miscarriage, or stillbirth. Factors behind the escalating global monkeypox outbreak, as well as the prevention and control of monkeypox via the One Health approach, are discussed to shed light on curbing the continuous emergence of monkeypox.
Identification and characterization of novel abdominal and pelvic brown adipose depots in mice

Brown adipose tissue (BAT) generates heat through non-shivering thermogenesis, and increasing BAT amounts or activity could facilitate obesity treatment and provide metabolic benefits. In mice, BAT has been reported in perirenal, thoracic and cranial sites. Here, we describe new pelvic and lower abdominal BAT depots located around the urethra, internal reproductive and urinary tract organs and major lower pelvic blood vessels, as well as between adjacent muscles where the upper hind leg meets the abdominal cavity. Immunohistochemical, western blot and PCR analyses revealed that these tissues expressed BAT markers such as uncoupling protein 1 (UCP1) and CIDEA, but not white adipose markers, and β3-adrenergic stimulation increased UCP1 amounts, a classic characteristic of BAT tissue. The newly identified BAT stores contained extensive sympathetic innervation with high mitochondrial density and multilocular lipid droplets similar to interscapular BAT. BAT repositories were present and functional neonatally, and showed developmental changes between the neonatal and adult periods. In summary, several new depots showing classical BAT characteristics are reported and characterized in the lower abdominal/pelvic region of mice. These BAT stores are likely significant metabolic regulators in the mouse and some data suggests that similar BAT depots may also exist in humans.
Rock temperatures as an indicator of weathering processes affecting rock art

To aid rock art conservation, rock temperatures have been monitored at different depths and at low (30 min) and high (1 min) acquisition rates in a painted rock shelter in the uKhahlamba-Drakensberg Park (South Africa). Preliminary data for winter (cold and dry) show that in that season cryoclasty is unlikely to occur (rare subzero thermal events and probable reduced moisture availability) and thermal shocks are improbable (highest measured Delta T/Delta t < 2 degrees C min(-1)). High amplitude (about 30 degrees C) rock temperature cycles accompanied by reversals of the thermal gradient have been observed to occur almost daily and hint at the possibility of thermal stress fatigue. Copyright (c) 2006 John Wiley & Sons, Ltd.
Toward Accurate Binarized Neural Networks With Sparsity for Mobile Application

While binarized neural networks (BNNs) have attracted great interest, popular approaches proposed so far mainly exploit the symmetric sign function for feature binarization, i.e., to binarize activations into -1 and +1 with a fixed threshold of 0. However, whether this option is optimal has been largely overlooked. In this work, we propose the Sparsity-inducing BNN (Si-BNN) to quantize the activations to be either 0 or +1, which better approximates ReLU using 1-bit. We further introduce trainable thresholds into the backward function of binarization to guide the gradient propagation. Our method dramatically outperforms the current state-of-the-art, lowering the performance gap between full-precision networks and BNNs on mainstream architectures, achieving the new state-of-the-art on binarized AlexNet (Top-1 50.5%), ResNet-18 (Top-1 62.2%), and ResNet-50 (Top-1 68.3%). At inference time, Si-BNN still enjoys the high efficiency of bit-wise operations. In our implementation, the running time of binary AlexNet on the CPU can be competitive with the popular GPU-based deep learning framework.
Noise Parameter Estimation for Poisson Corrupted Images Using Variance Stabilization Transforms

Noise is present in all images captured by real-world image sensors. Poisson distribution is said to model the stochastic nature of the photon arrival process and agrees with the distribution of measured pixel values. We propose a method for estimating unknown noise parameters from Poisson corrupted images using properties of variance stabilization. With a significantly lower computational complexity and improved stability, the proposed estimation technique yields noise parameters that are comparable in accuracy to the state-of-art methods.
A new family of CMOS inverter-based OTAs for biomedical and healthcare applications

This paper presents a new family of innovative operational transconductance amplifier (OTA) topologies based on CMOS inverter structures, with improved gain and energy-efficiency. This new family of OTA designs is suitable for biomedical and healthcare circuits and systems, due to the high energy-efficiency, improved gain and low level of noise contribution, when compared to the state-of-the-art in this field. In this paper, two fully-differential implementations are presented, a first one with a double CMOS branch biased by two pairs of voltage-combiners structures in both NMOS and PMOS configurations, and a second one with folded voltage-combiners specifically targeting low voltage applications, e.g., supplies below 1 V. The usage of voltage-combiners to bias the OTAs improves the gain and the gain-bandwidth product, therefore improving the energy-efficiency figure-of-merit. High values of figure-of-merit are achieved in both implementations, i.e., more than 1600 MHz x pF/mA and 2000 MHz x pF/mA, gain values above 53 dB and 50 dB under supply sources of 2 V and 0.7 V respectively. The folded voltage-combiners biased OTA is able to operate correctly under a voltage supply down to 0.7 V with proper DC biasing. The results are finally compared with state-of-the-art in this field and the potential of the circuits is fulfilled using a state-of-the-art layout-aware integrated-circuit optimization framework, AIDA, particularly relevant in order to overcome the device stacking problematic for lower voltages.
Differences in trunk control between early and late pregnancy during gait

The aim of this study was to compare gait characteristics, including the functional ability of the trunk, between women before and during the third trimester of pregnancy. Gait measurements were performed on 27 pregnant women, who were divided into two groups using the threshold of 28 gestational weeks. The subjects were instructed to walk at their preferred speed. In addition to stride-time coefficient of variation, root mean square (RMS) and autocorrelation coefficient, coefficient of attenuation (CoA) of acceleration was computed as an index to assess the functional ability of the trunk. Differences of gait characteristics between the groups were determined by the Mann-Whitney U test. Gait characteristics that showed a significant difference between the groups were further analyzed with adjustment by age, height, weight and gait velocity by using multiple regression analysis. Women during the third trimester of pregnancy showed significantly smaller RMS in the anteroposterior direction at the lower trunk than those before the third trimester of pregnancy, even after adjusting for age, height, weight and gait velocity [β=0.47; 95% confidence interval (CI) 0.07-0.25]. CoA in the anteroposterior direction was also significantly lower in women during the third trimester of pregnancy than in those before the third trimester of pregnancy after adjustment by age, height, weight and gait velocity (β=0.44; 95% CI 0.39-18.52). The present cross-sectional study suggests the possibility that the functional ability of the trunk during gait declines in late pregnancy.
A seasonal pulse of ungulate neonates influences space use by carnivores in a multi-predator, multi-prey system

The behavioral mechanisms by which predators encounter prey are poorly resolved. In particular, the extent to which predators engage in active search for prey versus incidentally encountering them has not been well studied in many systems and particularly not for neonate prey during the birth pulse. Parturition of many large herbivores occurs during a short and predictable temporal window in which young are highly vulnerable to predation. Our study aims to determine how a suite of carnivores responds to the seasonal pulse of newborn ungulates using contemporaneous global positioning system (GPS) locations of four species of predators and two species of prey. We used step-selection functions to assess whether coyotes, cougars, black bears, and bobcats encountered parturient adult female ungulates more often than expected by chance in a low-density population of mule deer and a high-density population of elk. We then assessed whether the carnivore species that encountered parturient prey more often than expected by chance did so by shifting their habitat use toward areas with a high probability of encountering neonates. None of the four carnivore species encountered GPS-collared parturient mule deer more often than expected by chance. By contrast, we determined that cougar and male bear movements positioned them in the proximity of GPS-collared parturient elk more often than expected by chance which may provide evidence of searching behavior. Although both male bears and cougars exhibited behavior consistent with active search for neonates, only male bears used elk parturition habitat in a way that dynamically tracked the phenology of the elk birth pulse suggesting that maximizing encounters with juvenile elk was a motivation when selecting resources. Our results suggest that there is high interspecific and intersexual variability in foraging strategies among large mammalian predators and their prey.
P-PseudoLabel: Enhanced Pseudo-Labeling Framework With Network Pruning in Semi-Supervised Learning

Semi-supervised learning (SSL) methods for classification tasks exhibit a significant performance gain because they combine regularization and pseudo-labeling methods. General pseudo-labeling methods only depend on the model's prediction when assigning pseudo-labels, but this approach often leads to the generation of incorrect pseudo-labels, due to the network being biased toward easy classes or to the presence of confusing samples in the training set, which further decreases model performance. To address this issue, we propose a novel pseudo-labeling framework that dramatically reduces the ambiguity of pseudo-labels for confusing samples in SSL. We operate our method, called Pruning for Pseudo-Label (P-PseudoLabel), using the Easy-to-Forget (ETF) Sample Finder, which compares the outputs of the model and the pruned model to identify confusing samples. Next, we perform negative learning using the confusing samples to decrease the risk of providing incorrect information and to improve performance. Our method achieves better performance than those of recent state-of-the-art SSL methods on the CIFAR-10, CIFAR-100, and Mini-ImageNet datasets, and is on par with the state-of-the-art methods on SVHN and STL-10.
MBL2 gene polymorphisms related to HIV-1 infection susceptibility and treatment response

Human Mannose-binding lectin (MBL) is a protein encoded by MBL2 gene involved in the activation of the lectin-complement pathway. Several studies emphasized the role of MBL2 gene in several infectious diseases' susceptibility, including HIV-1 infection. We aim to investigate the impact of 10 MBL2 gene polymorphisms located in the promoter, 5'UTR and exon 1 regions on HIV-1 physiopathology. The polymorphisms genotyping of 400 individuals, which 200 were HIV-1 positive patients and 200 were controls, was performed by PCR-sequencing. Our results showed that rs503037 and rs1800451 polymorphisms are associated with a high risk of HIV-1 infection susceptibility while rs7096206 and rs11003123 showed a protective effect. A significant association between haplotype CGA and HIV-1 infection susceptibility was also found in the exon 1 region. Moreover, rs11003124, rs7084554, rs36014597 and rs11003123 polymorphisms revealed an association with treatment response outcome as measured by RNA viral load. This study highlights the importance of MBL2 polymorphisms in the modulation of HIV-1 infection susceptibility and the contribution to treatment response outcomes among Moroccan subjects.
Optimism of the Will. Antonio Gramsci Takes in Max Weber

Responding to Max Weber's dour predictions, we enlist Antonio Gramsci's optimism to suggest how culture can spike development. Weber's sociological focus took culture to mean shared beliefs and practices. As a culture that derives from the Protestant Ethic, capitalism waged a war on pleasure. Weber warned that this unfeeling rationality would generate an iron cage to trap our humanity, but his book has been read, paradoxically, as a manual for the lock down. Gramsci, on the contrary, understood culture in its humanistic sense, as a field of aesthetic pleasure, innovation, and debate. For him, a precondition for transformational social change was the broad engagement of masses as empowered collectives (Weber favored charismatic leaders); and pleasure in idiosyncratic forms of artistic as well as rooted expression was the fuel for participating in personal and shared advances. This pleasure in art and collective interpretation contrasts with the exclusionary rituals of commodified pleasure typical of capitalist consumerism. Gramsci's confidence in the transformational role of creative culture provides a framework for understanding a new wave of inclusive artistic practices that originate in the Global South and that revive the arts as vehicles for active citizenship. Participatory art can re-enchant today's sorely disenchanted socio-cultural world of mature capitalism.
RSDNet: Learning to Predict Remaining Surgery Duration from Laparoscopic Videos Without Manual Annotations

Accurate surgery duration estimation is necessary for optimal OR planning, which plays an important role in patient comfort and safety as well as resource optimization. It is, however, challenging to preoperatively predict surgery duration since it varies significantly depending on the patient condition, surgeon skills, and intraoperative situation. In this paper, we propose a deep learning pipeline, referred to as RSDNet, which automatically estimates the remaining surgery duration (RSD) intraoperatively by using only visual information from laparoscopic videos. The previous state-of-the-art approaches for RSD prediction are dependentonmanual annotation, whose generation requires expensive expert knowledge and is time-consuming, especially considering the numerous types of surgeries performed in a hospital and the large number of laparoscopic videos available. A crucial feature of RSD-Net is that it does not depend on any manual annotation during training, making it easily scalable to many kinds of surgeries. The generalizability of our approach is demonstrated by testing the pipelineon two large datasets containing different types of surgeries: 120 cholecystectomy and 170 gastric bypass videos. The experimental results also show that the proposed network significantly outperforms a traditional method of estimating RSD without utilizing manual annotation. Further, this paper provides a deeper insight into the deep learning network through visualization and interpretation of the features that are automatically learned.
ArtiaX: An electron tomography toolbox for the interactive handling of sub-tomograms in UCSF ChimeraX

Cryo-electron tomography analysis involves the selection of macromolecular complexes to be used for subsequent sub-tomogram averaging and structure determination. Here, we describe a plugin developed for UCSF ChimeraX that allows for the display, selection, and editing of particles within tomograms. Positions and orientations of selected particles can be manually set, modified and inspected in real time, both on screen and in virtual reality, and exported to various file formats. The plugin allows for the parallel visualization of particles stored in several meta data lists, in the context of any three-dimensional image that can be opened with UCSF ChimeraX. The particles are rendered in user-defined colors or using colormaps, such that individual classes or groups of particles, cross-correlation coefficients, or other types of information can be highlighted to the user. The implemented functions are fast, reliable, and intuitive, exploring the broad range of features in UCSF ChimeraX. They allow for a fluent human-machine interaction, which enables an effective understanding of the sub-tomogram processing pipeline, even for non-specialist users.
Adaptive Decoupling of Nonideal Machine and Sensor Properties for Extraction of Fine Details When Using the Motor Drive as a Diagnostic Sensor

This paper presents methods to enhance the quality of spatial information that can be extracted when using the motor drive as a diagnostic sensor. When using the state-of-the-art motor drive-based techniques for extracting spatial information related to the state of wear in a gear train driven by an ac machine, position sensor-induced periodic position measurement errors and machine-induced spatial harmonic torque ripple can degrade the quality and the detail of the information that can be extracted. In this work, this degradation of information is displayed experimentally, and it is demonstrated that the quality of the spatial information extracted can be significantly improved through implementation of existing model reference adaptive system (MRAS)based nonideal sensor property decoupling techniques and newly developed MRAS-based spatial harmonic torque ripple decoupling techniques. Furthermore, it is identified and demonstrated in this work that by removing the gear mesh harmonic component from the gear wear information extracted using the state-of-the-art techniques, and then calculating the spatial rate of change of this new information, a new signal is generated that strongly correlates to local gear tooth defects in a gear train driven by an ac machine.