ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
MC-LSTM: Real-Time 3D Human Action Detection System for Intelligent Healthcare Applications

Due to the movement expressiveness and privacy assurance of human skeleton data, 3D skeleton-based action inference is becoming popular in healthcare applications. These scenarios call for more advanced performance in application-specific algorithms and efficient hardware support. Warnings on health emergencies sensitive to response speed require low latency output and action early detection capabilities. Medical monitoring that works in an always-on edge platform needs the system processor to have extreme energy efficiency. Therefore, in this paper, we propose the MC-LSTM, a functional and versatile 3D skeleton-based action detection system, for the above demands. Our system achieves state-of-the-art accuracy on trimmed and untrimmed cases of general-purpose and medical-specific datasets with early-detection features. Further, the MC-LSTM accelerator supports parallel inference on up to 64 input channels. The implementation on Xilinx ZCU104 reaches a throughput of 18 658 Frames-Per-Second (FPS) and an inference latency of 3.5 ms with the batch size of 64. Accordingly, the power consumption is 3.6 W for the whole FPGA+ARM system, which is 37.8x and 10.4x more energy-efficient than the high-end Titan X GPU and i7-9700 CPU, respectively. Meanwhile, our accelerator also keeps a 4 similar to 5x energy efficiency advantage against the low-power high-performance Firefly-RK3399 board carrying an ARM Cortex-A72+A53 CPU. We further synthesize an 8-bit quantized version on the same hardware, providing a 48.8% increase in energy efficiency under the same throughput.
Explicit Modeling of Human-Object Interactions in Realistic Videos

We introduce an approach for learning human actions as interactions between persons and objects in realistic videos. Previous work typically represents actions with low-level features such as image gradients or optical flow. In contrast, we explicitly localize in space and track over time both the object and the person, and represent an action as the trajectory of the object w.r.t. to the person position. Our approach relies on state-of-the-art techniques for human detection [32], object detection [10], and tracking [39]. We show that this results in human and object tracks of sufficient quality to model and localize human-object interactions in realistic videos. Our human-object interaction features capture the relative trajectory of the object w.r.t. the human. Experimental results on the Coffee and Cigarettes dataset [25], the video dataset of [19], and the Rochester Daily Activities dataset [29] show that 1) our explicit human-object model is an informative cue for action recognition; 2) it is complementary to traditional low-level descriptors such as 3D-HOG [23] extracted over human tracks. We show that combining our human-object interaction features with 3D-HOG improves compared to their individual performance as well as over the state of the art [23], [29].
Accurate and Efficient Optic Disc Detection and Segmentation by a Circular Transformation

Under the framework of computer-aided diagnosis, this paper presents an accurate and efficient optic disc (OD) detection and segmentation technique. A circular transformation is designed to capture both the circular shape of the OD and the image variation across the OD boundary simultaneously. For each retinal image pixel, it evaluates the image variation along multiple evenly-oriented radial line segments of specific length. The pixels with the maximum variation along all radial line segments are determined, which can be further exploited to locate both the OD center and the OD boundary accurately. Experiments show that OD detection accuracies of 99.75%, 97.5%, and 98.77% are obtained for the STARE dataset, the ARIA dataset, and the MES-SIDOR dataset, respectively, and the OD center error lies around six pixels for the STARE dataset and the ARIA dataset which is much smaller than that of state-of-the-art methods ranging 14-29 pixels. In addition, the OD segmentation accuracies of 93.4% and 91.7% are obtained for STARE dataset and ARIA dataset, respectively, that consists of many severely degraded images of pathological retinas that state-of-the-art methods cannot segment properly. Furthermore, the algorithm runs in 5 s, which is substantially faster than many of the state-of-the-art methods.
K-means Cluster Algorithm Applied for Geometric Shaping Based on Iterative Polar Modulation in Inter-Data Centers Optical Interconnection

The demand of delivering various services is driving inter-data centers optical interconnection towards 400 G/800 G, which calls for increasing capacity and spectrum efficiency. The aim of this study is to effectively increase capacity while also improving nonlinear noise anti-interference. Hence, this paper presents a state-of-the-art scheme that applies the K-means cluster algorithm in geometric shaping based on iterative polar modulation (IPM). A coherent optical communication simulation system was established to demonstrate the performance of our proposal. The investigation reveals that the gap between IPM and Shannon limit has significantly narrowed in terms of mutual information. Moreover, when compared with IPM and QAM using the blind phase searching under the same order at HD-FEC threshold, the IPM-16 using the K-means algorithm achieves 0.9 dB and 1.7 dB gain; the IPM-64 achieves 0.3 dB and 1.1 dB gain, and the IPM-256 achieves 0.4 dB and 0.8 dB gain. The robustness of nonlinear noise and high capacity enable this state-of-the-art scheme to be used as an optional modulation format not only for inter-data centers optical interconnection but also for any high speed, long distance optical fiber communication system.
Video Error Correction Using Soft-Output and Hard-Output Maximum Likelihood Decoding Applied to an H.264 Baseline Profile

Error concealment has long been identified as the last line of defense against transmission errors. Since error handling is outside the scope of video coding standards, decoders may choose to simply ignore corrupted packets or attempt to decode their content. In this paper, we present a novel joint source-channel decoding approach that can be applied to received video packets containing transmission errors. Soft-output information is combined with our novel syntax-element-level maximum likelihood decoding framework to effectively extract valid macroblocks from corrupted H.264 slices. Simulation results show that our video error correction strategy provides an average peak signal-to-noise ratio (PSNR) improvement near 2 dB compared to the error concealment approach used by the H.264 reference software, as well as an average PSNR improvement of 0.8 dB compared to state-of-the-art error concealment. The proposed method is also applicable when only hard-information is available, in which case it performs better than state-of-the-art error concealment especially in high error conditions. Finally, in our simulations, the proposed method increased the decoder computational complexity by only 5% to 20%, making it applicable for real-time applications.
Constrained Statistical Modelling of Knee Flexion From Multi-Pose Magnetic Resonance Imaging

Reconstruction of the anterior cruciate ligament (ACL) through arthroscopy is one of the most common procedures in orthopaedics. It requires accurate alignment and drilling of the tibial and femoral tunnels through which the ligament graft is attached. Although commercial computer-assisted navigation systems exist to guide the placement of these tunnels, most of them are limited to a fixed pose without due consideration of dynamic factors involved in different knee flexion angles. This paper presents a new model for intraoperative guidance of arthroscopic ACL reconstruction with reduced error particularly in the ligament attachment area. The method uses 3D preoperative data at different flexion angles to build a subject-specific statistical model of knee pose. To circumvent the problem of limited training samples and ensure physically meaningful pose instantiation, homogeneous transformations between different poses and local-deformation finite element modelling are used to enlarge the training set. Subsequently, an anatomical geodesic flexion analysis is performed to extract the subject-specific flexion characteristics. The advantages of the method were also tested by detailed comparison to standard Principal Component Analysis (PCA), nonlinear PCA without training set enlargement, and other state-of-the-art articulated joint modelling methods. The method yielded sub-millimetre accuracy, demonstrating its potential clinical value.
Utilizing CyTOF to Examine Hematopoietic Stem and Progenitor Phenotype

Regulation of hematopoiesis is dependent upon interactions between hematopoietic stem/progenitor cells and niche components, requiring a highly diverse array of different cell-cell interactions and cell signaling events. The overwhelming diversity of the components that can regulate hematopoiesis, especially when factoring in how the cell surface and intracellular protein expression profiles of hematopoietic stem/progenitor cells and niche components differ between homeostatic conditions and stressed conditions such as aging and irradiation, can make utilizing techniques like flow cytometry daunting, particularly while examining small cell populations such as hematopoietic stem cells (HSCs). Due to the complexity of the hematopoietic system, high-dimensional single-cell genomics and proteomics are constantly performed to understand the heterogeneity and expression profiles within this system. This chapter describes one such single-cell assay, which utilizes mass cytometry Time of Flight (CyTOF) technology to determine differences in expression profile within HSC, using changes in HSC populations due to gender and aging.
Denoising of Diffusion MRI Data via Graph Framelet Matching in x-q Space

Diffusion magnetic resonance imaging (DMRI) suffers from lower signal-to-noise-ratio (SNR) due to MR signal attenuation associated with the motion of water molecules. To improve SNR, the non-local means (NLM) algorithm has demonstrated state-of-the-art performance in noise reduction. However, existing NLM algorithms do not take into account explicitly the fact that DMRI signal can vary significantly with local fiber orientations. Applying NLM naively can hence blur subtle structures and aggravate partial volume effects. To overcome this limitation, we improve NLM by performing neighborhood matching in non-flat domains and removing noise with information from both x-space (spatial domain) and q-space (wavevector domain). Specifically, we first encode the q-space sampling domain using a graph. We then perform graph framelet transforms to extract robust rotation-invariant features for each sampling point in x-q space. The resulting features are employed for robust neighborhood matching to locate recurrent information. Finally, we remove noise via an NLM framework. To adapt to the various types of noise in multi-coil MR imaging, we transform the signal before denoising so that it is Gaussian-distributed, allowing noise removal to be carried out in an unbiased manner. Our method is able to more effectively locate recurrent information in white matter structures with different orientations, avoiding the blurring effects caused by naively applying NLM. Experiments on synthetic, repetitively-acquired, and infant DMRI data demonstrate that our method is able to preserve subtle structures while effectively removing noise.
Correlation between Electrolyte Chemistry and Solid Electrolyte Interphase for Reversible Ca Metal Anodes

The development of rechargeable Ca metal batteries (RCMBs) is hindered by the Ca2+ passivating solid electrolyte interphases (SEIs). The cation solvation structure dictated by electrolyte chemistry plays a critical role in the SEIs properties. While a relatively weak cation-solvent binding is preferred in Li metal anodes to promote anion-derived SEIs, we demonstrate an enhanced Ca deposition/stripping reversibility under a strong cation-solvent interaction, which is materialized in strongly-solvating solvent and highly-dissociated salt combinations. Such electrolyte formulations benefit the formation of solvent-occupied solvation structure and minimize the anion reduction, resulting in organic-rich/CaF2 -poor SEIs for reversible Ca metal anodes. Furthermore, RCMBs paired with an organic cathode using the optimized electrolytes are demonstrated as a proof-of-concept. Our work reveals the paradigm shift in SEIs design for Ca metal anodes, opening up new opportunities for emerging RCMBs.
Uncertainty quantification and management in additive manufacturing: current status, needs, and opportunities

One of the major barriers that hinder the realization of significant potential of metal-based additive manufacturing (AM) techniques is the variation in the quality of the manufactured parts. Uncertainty quantification (UQ) and uncertainty management (UM) can resolve this challenge based on the modeling and simulation of the AM process. This paper reviews the research state of the art and discusses needs and opportunities in the UQ/UM of the AM processes, with a focus on laser powder bed fusion AM. The major methods and models of laser powder bed fusion AM process are summarized first. The current research work in UQ of AM processes is then reviewed. Based on the review of AM process models and current UQ approaches for the AM process, this paper presents insights into how the current state of the art UQ and UM techniques can be applied to AM to improve the product quality. Future research needs in UQ and UM of AM are also discussed. Laser sintering of metal nanoparticles, which is part of the micro-AM process, is used as an example to illustrate the application of UQ and UM in the AM.
Spontaneous colonic perforation with collagenous colitis in an elderly patient

Collagenous colitis (CC) is a variant of microscopic colitis that causes chronic, non-bloody, and watery diarrhea. The natural history of CC is generally benign and serious complications are rare. Perforation, especially spontaneous perforation, is a particularly rare complication. A 90-year-old woman presented with acute abdominal pain. She was diagnosed with peritonitis due to colonic perforation, and partial colectomy was performed. Macroscopic findings showed well-circumscribed longitudinal ulcer, and a pathological examination revealed descending colon perforation with CC. She had no history of examination and the case was considered to be spontaneous. The postoperative course was uneventful and she had no recurrence of CC after changing from the suspected drug (lansoprazole) to an H2-blocker. The characteristics of perforation by CC are characteristic longitudinal ulcer and micro-perforation. If it can be diagnosed accurately, conservative treatment may be an option. In spontaneous cases, the history of medication and the site of perforation may assist in this decision.
A simple and versatile strategy for sensitive SIDA-UHPLC-MS/MS analysis of Alternaria toxins in olive oil

Alternaria toxins are naturally occurring contaminants found in natural products. Given the prevalence of Alternaria toxins and the complexity of oil-rich matrices, achieving ultra-trace analysis has become a daunting task. A new sample pretreatment technique, i.e., cold-induced liquid-liquid microextraction combined with serially-coupled-columns for SIDA-UHPLC-MS/MS, was developed and reported for the first time. Theoretical and experimental investigations on the mechanism and key parameters revealed that the proposed method achieved simultaneous purification and enrichment in one-step sample extraction with a superior limit of quantitation (0.15-1.5 μg kg-1), without further sample manipulation, such as fat removal or solvent exchange procedures prior to LC-MS. The method was validated taking into consideration EU guidelines and showed acceptable linearity (r ≥ 0.9991), accuracy with recoveries between 75 and 114% and precision with RSD≤9.7% for all of the analytes studied. It was successfully applied to the analysis of twenty samples sourced from the Mediterranean region in order to gain first insights into Alternaria toxins contaminations in olive oils. This technical approach is well suited for large-scale studies in a high-throughput and cost-effective quality assurance laboratory environments, and it has the potential to detect ultra-trace levels of toxins in complex samples, which may lead to the development of new and sustainable sample preparation procedures.
Evaluating Postoperative Immobilization Following Hip Reconstruction in Children With Cerebral Palsy

Objectives Currently, there is no standardized protocol for postoperative immobilization techniques in patients with cerebral palsy undergoing hip reconstructive procedures. The purpose of this study was to evaluate the effects of several methods of postoperative immobilization and to determine which postoperative immobilization technique has the fewest complications. Materials and methods A retrospective cohort study of pediatric patients with cerebral palsy who underwent hip reconstructive procedures, in which a hip spica cast, Petrie cast, or abduction pillow was placed for postoperative hip immobilization, was conducted. Patients who underwent revision surgery and those without cerebral palsy were excluded from the analysis. The final cohort consisted of 70 cases. Demographics, laterality of surgery, procedure type, hip immobilization technique, and 30-day postoperative complications were recorded. Complications were defined as those related to casting immobilization, such as re-dislocation or loss of surgical fixation, and soft tissue complications, such as pressure ulcers or any superficial or deep wound infection. Results Of the 70 patients, 27 received spica casting, 28 received Petrie casting, and 15 received an abduction pillow. The complication rates, as defined in the methods section, were 14.8% for the spica cast group, 17.9% for Petrie cast, and 26.7% for abduction pillow. There was no significant difference in complication rates among spica cast, Petrie cast, or abduction pillow groups (P=0.76). Conclusions There was no significant difference in length of stay, pain control duration, or complication rates among the three methods of immobilization. Clinicians should be advised of the comparable outcomes among the postoperative immobilization techniques.
Organochlorine pesticides in follicular fluid of women undergoing assisted reproductive technologies from central China

Female infertility rates have increased by approximately 4% since the 1980s. There is evidence of adverse effects on female fertility in relation to exposure of chemical pollution in recent years. Follicular fluid samples were collected from 127 woman patients (aged 20-35) who underwent assisted reproductive technologies (ART) and had no records indicating occupational exposure to OCPs. Seventeen OCPs were analyzed in this study. The results showed that methoxychlor was dominant accounted for 13.4% of total OCPs with a mean concentration of 167.9 +/- 33.9 ng/g lipid weight (lw), followed by heptachlor-epoxide, hexachlorocyclohexanes, endrin and DDT. The concentrations of OCPs in the follicular fluid samples in the present study were moderate in comparison with those reported from developed or industrialized countries. All these pollutants can accumulate in different tissues of human body through diet, drinking water and respiration. No correlation between patient age and OCP concentrations was observed in this study. (C) 2015 Elsevier Ltd. All rights reserved.
Ocular manifestations of central insulin resistance

Central insulin resistance, the diminished cellular sensitivity to insulin in the brain, has been implicated in diabetes mellitus, Alzheimer's disease and other neurological disorders. However, whether and how central insulin resistance plays a role in the eye remains unclear. Here, we performed intracerebroventricular injection of S961, a potent and specific blocker of insulin receptor in adult Wistar rats to test if central insulin resistance leads to pathological changes in ocular structures. 80 mg of S961 was stereotaxically injected into the lateral ventricle of the experimental group twice at 7 days apart, whereas buffer solution was injected to the sham control group. Blood samples, intraocular pressure, trabecular meshwork morphology, ciliary body markers, retinal and optic nerve integrity, and whole genome expression patterns were then evaluated. While neither blood glucose nor serum insulin level was significantly altered in the experimental or control group, we found that injection of S961 but not buffer solution significantly increased intraocular pressure at 14 and 24 days after first injection, along with reduced porosity and aquaporin 4 expression in the trabecular meshwork, and increased tumor necrosis factor α and aquaporin 4 expression in the ciliary body. In the retina, cell density and insulin receptor expression decreased in the retinal ganglion cell layer upon S961 injection. Fundus photography revealed peripapillary atrophy with vascular dysregulation in the experimental group. These retinal changes were accompanied by upregulation of pro-inflammatory and pro-apoptotic genes, downregulation of anti-inflammatory, anti-apoptotic, and neurotrophic genes, as well as dysregulation of genes involved in insulin signaling. Optic nerve histology indicated microglial activation and changes in the expression of glial fibrillary acidic protein, tumor necrosis factor α, and aquaporin 4. Molecular pathway architecture of the retina revealed the three most significant pathways involved being inflammation/cell stress, insulin signaling, and extracellular matrix regulation relevant to neurodegeneration. There was also a multimodal crosstalk between insulin signaling derangement and inflammation-related genes. Taken together, our results indicate that blocking insulin receptor signaling in the central nervous system can lead to trabecular meshwork and ciliary body dysfunction, intraocular pressure elevation, as well as inflammation, glial activation, and apoptosis in the retina and optic nerve. Given that central insulin resistance may lead to neurodegenerative phenotype in the visual system, targeting insulin signaling may hold promise for vision disorders involving the retina and optic nerve.
Melanoma arising in a nevus of Ito: novel genetic mutations and a review of the literature on cutaneous malignant transformation of dermal melanocytosis

Dermal melanocytosis refers to a spectrum of benign melanocytic proliferations that includes Mongolian spot, nevus of Ota and nevus of Ito. These lesions most commonly occur in persons of Asian or African descent and are often present at birth or develop during childhood. Very rarely, dermal melanocytoses undergo malignant transformation. There have been only 13 reports in the literature of primary cutaneous melanoma arising in dermal melanocytoses. We report a case of a Chinese woman with melanoma arising in a congenital nevus of Ito. We performed targeted next-generation sequencing of the tumor which revealed mutations of GNAQ and BAP1, suggesting that alterations in these two genes led to malignant transformation of the nevus of Ito. We also provide a summary of reports in the literature regarding primary cutaneous melanoma arising in the context of dermal melanocytosis.