ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Using a 2x-thru standard to achieve accurate de-embedding of measurements

The broadband measurement of interconnects and on-board devices requires the usage of test fixtures in order to connect to the measurement instrumentation. Proper assessment of the device performance requires removal of the effects of these test fixtures which is done using a de-embedding procedure. Previous de-embedding procedures such as Thru-Reflect-Line (TRL), Line-Reflect-Match (LRM) and other similar methods require the measurement of multiple standards. Alternatively, some methods such as thru de-embedding techniques require measurement of one standard with explicit computation of only two or three of the four error terms. This is justified by using the sometimes questionable assumption of fixture reciprocity. Prior art also does not include derivation of all of the required equations. Proposed and explained in detail here is the usage of a 2x-thru standard which is manipulated to derive complete fixture models without making assumptions about reciprocity or symmetry. Subsequently these models are mathematically removed from the indirect measurement, thus isolating the performance of the DUT. In contrast to prior art, this method uses only one standard instead of three, and it computes all four terms to make a complete fixture model. Several test cases are presented which illustrate the accuracy and validity of the 2x-thru method for broadband applications.
Associations of urinary phthalate metabolites and lipid peroxidation with sperm mitochondrial DNA copy number and deletions

Background: Phthalates, a chemical class of plasticizers, are ubiquitous environmental contaminants that have been associated with oxidative stress. Mitochondria DNA copy number (mtDNAcn) and DNA deletions (mtDNAdel) are emerging biomarkers for cellular oxidative stress and environment exposures. Objectives: To examine associations of urinary phthalate metabolite and isoprostane concentrations on sperm mtDNAcn and mtDNAdel in male partners undergoing assisted reproductive technologies (ART). Methods: Ninety-nine sperm samples were collected from male partners undergoing ART at Baystate Medical Center in Springfield, MA as part of the Sperm Environmental Epigenetics and Development Study (SEEDS). Seventeen urinary phthalate metabolite concentrations were analyzed by the Centers for Disease Control using tandem mass spectrometry. Urinary 15-F2t-isoprostane concentrations, a biomarker of lipid peroxidation, were measured using a competitive enzyme-linked immunosorbent assay. A triplex qPCR method was used to determine the relative quantification of mtDNAcn and mtDNAdel. Results: Sperm mtDNAcn and mtDNAdel were positively correlated (Spearman rho = 0.31; p =.002). Adjusting for age, BMI, current smoking, race, and measurement batch, urinary monocarboxy-isononyl phthalate (MCNP) concentrations were positively associated with mtDNAcn (13 = 1.63, 95% CI: 0.14, 3.11). Other urinary phthalate metabolite and isoprostane concentrations were not associated with sperm mtDNAcn or mtDNAdel. Conclusions: Among this cohort of male ART participants, those with higher MCNP had higher mtDNAcn; other phthalate metabolites and isoprostane were not associated with mtDNAcn and mtDNAdel. Given our relatively small sample size, our results should be interpreted with caution. Future research is needed to replicate the findings in larger studies and among sperm samples obtained from the general population.
An approach to collaboration of growing self-organizing maps and adaptive resonance theory maps

Collaboration of growing self-organizing maps (GSOM) and adaptive resonance theory maps (ART) is considered through traveling sales-person problems (TSP). The ART is used to parallelize the GSOM: it divides the input space of city positions into subspaces automatically. One GSOM is allocated to each subspace and grows following the input data. After all the GSOMs grow sufficiently they are connected and we obtain a tour. Basic experimental results suggest that we can find semi-optimal solution much faster than serial methods.
Site-specific Interaction Mapping of Phosphorylated Ubiquitin to Uncover Parkin Activation

Damaged mitochondria are eliminated through autophagy machinery. A cytosolic E3 ubiquitin ligase Parkin, a gene product mutated in familial Parkinsonism, is essential for this pathway. Recent progress has revealed that phosphorylation of both Parkin and ubiquitin at Ser(65) by PINK1 are crucial for activation and recruitment of Parkin to the damaged mitochondria. However, the mechanism by which phosphorylated ubiquitin associates with and activates phosphorylated Parkin E3 ligase activity remains largely unknown. Here, we analyze interactions between phosphorylated forms of both Parkin and ubiquitin at a spatial resolution of the amino acid residue by site-specific photo-crosslinking. We reveal that the in-between-RING (IBR) domain along with RING1 domain of Parkin preferentially binds to ubiquitin in a phosphorylation-dependent manner. Furthermore, another approach, the Fluoppi (fluorescent-based technology detecting protein-protein interaction) assay, also showed that pathogenic mutations in these domains blocked interactions with phosphomimetic ubiquitin in mammalian cells. Molecular modeling based on the site-specific photo-crosslinking interaction map combined with mass spectrometry strongly suggests that a novel binding mechanism between Parkin and ubiquitin leads to a Parkin conformational change with subsequent activation of Parkin E3 ligase activity.
Analysis of Per- and Poly(fluoroalkyl) Substances (PFASs) in Highly Consumed Seafood Products from U.S. Markets

Seafood consumption has been identified as one of the major contributors of per- and poly(fluoroalkyl) substances (PFASs) to the human diet. To assess dietary exposure, highly consumed seafood products in the United States were selected for analysis. The analytical method previously used for processed food was extended to include four additional long-chain perflurocarboxylic acids (PFCAs), which have been reported in seafood samples. This method was single-lab-validated, and method detection limits were reported at 345 ng kg-1 for perfluorobutanoic acid (PFBA) and 207 ng kg-1 for perfluoropentanoic acid (PFPeA) and below 100 ng kg-1 for the rest of the PFAS analytes. The 81 seafood samples (clams, crab, tuna, shrimp, tilapia, cod, salmon, pollock) were analyzed for 20 PFASs using the updated analytical method. Most of the seafood packaging was also analyzed by Fourier transform infrared-attenuated total reflectance (FTIR-ATR) to identify packaging potentially coated with PFASs. None of the packaging samples in this study were identified as having PFASs. A wide range of concentrations was observed among the seafood samples, ranging from below the method detection limit to the highest concentration of 23 μg kg-1 for the sum of PFASs in one of the canned clam samples. Such a wide range is consistent with those reported in previous studies. The highest concentrations were reported in clams and crabs, followed by cod, tuna, pollock, tilapia, salmon, and shrimp. Technical perfluorooctanoic acid (PFOA) dominated the profile of the clam samples, which has been consistently found in other clam samples, especially in Asia. Long-chain PFCAs, specifically perfluoroundecanoic (PFUdA) and perfluorododecanoic (PFDoA), were the most frequently detected analytes across all seafood samples. The trends observed are comparable with those in the literature where benthic organisms tend to have the highest PFAS concentrations, followed by lean fish, fatty fish, and aquaculture. The results from this study will be used to prioritize future studies and to inform steps to reduce consumer exposure to PFASs.
Economic appraisal of hybrid solar-biomass thermophotovoltaic power generation

The techno-economic parameters that influence the commercial deployment of hybrid thermophotovoltaic (TPV) solar power generation are determined using annual system simulations. It has been found that a TPV cell price of (sic)5/cm(2) or less together with a TPV operating temperature under 800 degrees C is required for a hybrid solar-biomass TPV power plant to be economically competitive with the state-of-the-art hybrid solar-biomass Rankine cycle power plants.
Carbon Nanotube FET Technology for Radio-Frequency Electronics: State-of-the-Art Overview

Carbon-based electronics is an emerging field. Its present progress is largely dominated by the materials science community due to the many still existing materials-related obstacles for realizing practically competitive transistors. Compared to graphene, carbon nanotubes provide better properties for building field-effect transistors, and thus, have higher chances for eventually becoming a production technology. This paper provides an overview on the state-of-the-art of CNTFET technology from an electrical engineering and radio frequency analog applications point of view. Important material properties, resulting device structures, their fabrication, and the most relevant modeling concepts are briefly reviewed. Furthermore, recent results on device and circuit performance and the future prospects are presented in the context of practical requirements and applications.
Sex differences in body fluid homeostasis: Sex chromosome complement influences on bradycardic baroreflex response and sodium depletion induced neural activity

Clinical and basic findings indicate that angiotensin II (ANG II) differentially modulates hydroelectrolyte and cardiovascular responses in male and female. But are only the activational and organizational hormonal effects to blame for such differences? Males and females not only differ in their sex (males are born with testes and females with ovaries) but also carry different sex chromosome complements and are thus influenced throughout life by different genomes. In this review, we discuss our recent studies in order to evaluate whether sex chromosome complement is in part responsible for gender differences previously observed in ANG II bradycardic-baroreflex response and sodium depletion-induced sodium appetite and neural activity. To test the hypothesis that XX or XY contributes to the dimorphic ANG II bradycardic-baroreflex response, we used the four core genotype mouse model, in which the effects of gonadal sex (testes or ovaries) and sex chromosome complement (XX or XY) are dissociated. The results indicate that ANG II bradycardic-baroreflex sexual dimorphic response may be ascribed to differences in sex chromosomes, indicating an XX-sex chromosome complement facilitatory bradycardic-baroreflex control of heart rate. Furthermore, we evaluated whether genetic differences within the sex chromosome complement may differentially modulate the known sexually dimorphic sodium appetite as well as basal or induced brain activity due to physiological stimulation of the renin-angiotensin system by furosemide and low-sodium treatment. Our studies demonstrate an organizational hormonal effect on sexually dimorphic induced sodium intake in mice, while at the brain level (subfornical organ and area postrema) we showed a sex chromosome complement effect in sodium-depleted mice, suggesting a sex chromosome gene participation in the modulation of neural pathways underlying regulatory response to renin-angiotensin stimulation.
Non-traumatic bladder rupture

Spontaneous bladder rupture, while rare, carries a high risk of morbidity and mortality if left untreated. Here, we describe a case report of spontaneous bladder rupture in a patient initially presenting with foley malfunction. Despite foley replacement, the patient continued to endorse abdominal pain and clinically deteriorate, thus raising our suspicion for possible bladder rupture. Recognizing and understanding the different variations of spontaneous bladder rupture is paramount for timely appropriate intervention.
Evolving Type-2 Fuzzy Classifier

Evolving fuzzy classifiers (EFCs) have achieved immense success in dealing with nonstationary data streams because of their flexible characteristics. Nonetheless, most real-world data streams feature highly uncertain characteristics, which cannot be handled by the type-1 EFC. A novel interval type-2 fuzzy classifier, namely evolving type-2 classifier (eT2Class), is proposed in this paper, which constructs an evolving working principle in the framework of interval type-2 fuzzy system. The eT2Class commences its learning process from scratch with an empty or initially trained rule base, and its fuzzy rules can be automatically grown, pruned, recalled, and merged on the fly referring to summarization power and generalization power of data streams. In addition, the eT2Class is driven by a generalized interval type-2 fuzzy rule, where the premise part is composed of the multivariate Gaussian function with an uncertain nondiagonal covariance matrix, while employing a subset of the nonlinear Chebyshev polynomial as the rule consequents. The efficacy of the eT2Class has been rigorously assessed by numerous real-world and artificial study cases, bench-marked against state-of-the-art classifiers, and validated through various statistical tests. Our numerical results demonstrate that the eT2Class produces more reliable classification rates, while retaining more compact and parsimonious rule base than state-of-the-art EFCs recently published in the literature.
Low-depth shotgun sequencing resolves complete mitochondrial genome sequence of Labeo rohita

Labeo rohita, popularly known as rohu, is a widely cultured species in whole Indian subcontinent. In the present study, we used in-silico approach to resolve complete mitochondrial genome of rohu. Low-depth shotgun sequencing using Roche 454 GS FLX (Branford, Connecticut, USA) followed by de novo assembly in CLC Genomics Workbench version 7.0.4 (Aarhus, Denmark) revealed the complete mitogenome of L. rohita to be 16 606 bp long (accession No. KR185963). It comprised of 13 protein-coding genes, 22 tRNAs, 2 rRNAs and 1 putative control region. The gene order and organization are similar to most vertebrates. The mitogenome in the present investigation has 99% similarity with that of previously reported mitogenomes of rohu and this is also evident from the phylogenetic study using maximum-likelihood (ML) tree method. This study was done to determine the feasibility, accuracy and reliability of low-depth sequence data obtained from NGS platform as compared to the Sanger sequencing. Thus, NGS technology has proven to be competent and a rapid in-silico alternative to resolve the complete mitochondrial genome sequence, thereby reducing labors and time.
Dynamic trophic shifts in bacterial and eukaryotic communities during the first 30 years of microbial succession following retreat of an Antarctic glacier

We examined microbial succession along a glacier forefront in the Antarctic Peninsula representing ∼30 years of deglaciation to contrast bacterial and eukaryotic successional dynamics and abiotic drivers of community assembly using sequencing and soil properties. Microbial communities changed most rapidly early along the chronosequence, and co-occurrence network analysis showed the most complex topology at the earliest stage. Initial microbial communities were dominated by microorganisms derived from the glacial environment, whereas later stages hosted a mixed community of taxa associated with soils. Eukaryotes became increasingly dominated by Cercozoa, particularly Vampyrellidae, indicating a previously unappreciated role for cercozoan predators during early stages of primary succession. Chlorophytes and Charophytes (rather than cyanobacteria) were the dominant primary producers and there was a spatio-temporal sequence in which major groups became abundant succeeding from simple ice Chlorophytes to Ochrophytes and Bryophytes. Time since deglaciation and pH were the main abiotic drivers structuring both bacterial and eukaryotic communities. Determinism was the dominant assembly mechanism for Bacteria, while the balance between stochastic/deterministic processes in eukaryotes varied along the distance from the glacier front. This study provides new insights into the unexpected dynamic changes and interactions across multiple trophic groups during primary succession in a rapidly changing polar ecosystem.
Polymorphism of Purpurin and Low-level Detection of the Noncentrosymmetric form by Second Harmonic Generation Microscopy

Nonlinear optical imaging based on second harmonic generation (SHG) provides rapid and highly selective detection of polar crystals. Purpurin (PUR) is a natural product with multiple pharmacological activities. Two polymorphs of PUR show distinct crystal packing and structural symmetry, where form I crystallizes in a polar space group and form II crystallizes in a centrosymmetric crystal structure. The two polymorphs are monotropically related, with form I being the thermodynamically stable form, as suggested by slurry experiments, in-situ Raman spectroscopy and crystal structure prediction (CSP). The specificity of SHG to the polar crystals of form I allows rapid polymorphism detection at the limit of individual crystals. SHG is also able to detect low levels of form I in a tablet matrix dominated by amorphous excipients. This study shows that SHG microscopy can achieve the rapid and sensitive detection of noncentrosymmetric crystals in solid dosage forms, which is especially helpful for the early detection of unwanted polymorphic conversion or crystallization of amorphous drugs in formulations and final products.
A precise resonance frequency measurement method based on ISO-standardized setups for contactless chip cards

A method for measuring the resonance frequency of contactless chip cards is proposed in this article. Compared to the vector network analyzer (VNA) based state-of-the-art method, the method gives a more accurate definition of resonance frequency, removes the subjectivity associated with the state-of-the-art method, and makes the measurement integrable into ISO-standardized test setups. Signal processing and system modeling are applied in order to determine the maximum active power in the chip card over a chosen frequency range. This is achieved by using a transfer function obtained from the model and by setting a chirp signal as input to the system. The determined maximum of active power is mapped to the corresponding frequency in the chirp signal, which is defined as the resonance frequency. The proposed method is verified by simulations and by comparing measurement results with the state-of-the-art. The results show that the proposed method offers significant advantages over the state-of-the-art method.
HFNet-SLAM: An Accurate and Real-Time Monocular SLAM System with Deep Features

Image tracking and retrieval strategies are of vital importance in visual Simultaneous Localization and Mapping (SLAM) systems. For most state-of-the-art systems, hand-crafted features and bag-of-words (BoW) algorithms are the common solutions. Recent research reports the vulnerability of these traditional algorithms in complex environments. To replace these methods, this work proposes HFNet-SLAM, an accurate and real-time monocular SLAM system built on the ORB-SLAM3 framework incorporated with deep convolutional neural networks (CNNs). This work provides a pipeline of feature extraction, keypoint matching, and loop detection fully based on features from CNNs. The performance of this system has been validated on public datasets against other state-of-the-art algorithms. The results reveal that the HFNet-SLAM achieves the lowest errors among systems available in the literature. Notably, the HFNet-SLAM obtains an average accuracy of 2.8 cm in EuRoC dataset in pure visual configuration. Besides, it doubles the accuracy in medium and large environments in TUM-VI dataset compared with ORB-SLAM3. Furthermore, with the optimisation of TensorRT technology, the entire system can run in real-time at 50 FPS.
Low-Complexity and High-Speed Architecture Design Methodology for Complex Square Root

In this paper, we propose a low-complexity and high-speed VLSI architecture design methodology for complex square root computation using COordinate Rotation DIgital Computer (CORDIC). The proposed methodology is independent of angle computation in the CORDIC unlike the state-of-the-art methodologies. The proposed methodology is modelled in VHDL and synthesized under the TSMC 45-nm CMOS technology @ 1 GHz frequency. The synthesis results show that the proposed design saves 18.39%, 4.06% and 17.26%, 2.56% on chip area and power consumption when compared with the state-of-the-art methodologies without loss in accuracy. The proposed design saves the latency of 16 and 14 clock cycles when compared with the state-of-the-art implementations. The proposed design can process 23.4 and 127.344 billion additional samples per one joule energy when compared with the state-of-the-art designs.
Learning Temporal Relations from Semantic Neighbors for Acoustic Scene Classification

Convolutional networks have achieved the state-of-the-art performance on Acoustic Scene Classification (ASC). Given the Log Mel-Spectrogram of an audio sample, the network can extract useful semantic contents in a certain range receptive field by stacking local convolutional operations. However, the temporal relations between different receptive fields are not captured explicitly. In this letter, we propose an end-to-end 3D Convolutional Neural Network (CNN) for ASC, named SeNoT-Net, which can generate effective audio representations by capturing temporal relations from semantic neighbors of different receptive fields over time. The SeNoT-Net treats the Log-Mel spectrogram as an ordered segment-level sequence. For each segment, the residual block can produce the semantic feature maps, then the semantic neighbors over time (SeNoT) module is applied to capture the relations between each feature point in the feature maps and its top-$k$ semantic neighbors. The proposed SeNoT-Net outperforms most of the state-of-the-art CNN models on both DCASE 2018 and 2019 ASC datasets.
Distributed Consensus-Based Coordination of Flexible Demand and Energy Storage Resources

Distributed, consensus-based algorithms have emerged as a promising approach for the coordination of distributed energy resources (DER) due to their communication, computation, privacy and reliability advantages over centralized approaches. However, state-of-the-art consensus-based algorithms address the DER coordination problem in independent time periods and therefore are inherently unable to capture the time-coupling operating characteristics of flexible demand (FD) and energy storage (ES) resources. This paper demonstrates that state-of-the-art algorithms fail to converge when these time-coupling characteristics are considered. In order to address this fundamental limitation, a novel consensus-based algorithm is proposed which includes additional consensus variables. These variables express relative maximum power limits imposed on the FD and ES resources which effectively mitigate the concentration of the FD and ES responses at the same time periods and steer the consensual outcome to a feasible and optimal solution. The convergence and optimality of the proposed algorithm are theoretically proven while case studies numerically demonstrate its convergence, optimality, robustness to initialization and information loss, and plug-and-play adaptability.