ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
SLAP: A Secure and Lightweight Authentication Protocol for machine-to-machine communication in industry 4.0

Fourth industrial revolution aims to provide a platform which enables machines to collect data, analyze them and make an appropriate decision. Machine-to-machine communication in industry 4.0 helps in better decision-making by monitoring and analyzing different real-time data. Internet Engineering Task Force defines a standard '6LoWPAN' to promote such type of machine-to-machine communication. Although 6LoWPAN attempts to solve important issues, security is not properly addressed and is a major concern during communication. To improve the security and efficiency in the existing state of the arts, we have proposed SLAP, a new secure and lightweight authentication protocol using only hash operation and XOR operation. Our analysis demonstrates that the proposed protocol is safe with respect to various known attacks (i.e., replay attack, man-in-the-middle attack, impersonation attack, modification attack, tracing attack) and efficient compared to the existing state of the arts.
CT Male Pelvic Organ Segmentation via Hybrid Loss Network With Incomplete Annotation

Sufficient data with complete annotation is essential for training deep models to perform automatic and accurate segmentation of CT male pelvic organs, especially when such data is with great challenges such as low contrast and large shape variation. However, manual annotation is expensive in terms of both finance and human effort, which usually results in insufficient completely annotated data in real applications. To this end, we propose a novel deep framework to segment male pelvic organs in CT images with incomplete annotation delineated in a very user-friendly manner. Specifically, we design a hybrid loss network derived from both voxel classification and boundary regression, to jointly improve the organ segmentation performance in an iterative way. Moreover, we introduce a label completion strategy to complete the labels of the rich unannotated voxels and then embed them into the training data to enhance the model capability. To reduce the computation complexity and improve segmentation performance, we locate the pelvic region based on salient bone structures to focus on the candidate segmentation organs. Experimental results on a large planning CT pelvic organ dataset show that our proposed method with incomplete annotation achieves comparable segmentation performance to the state-of-the-art methods with complete annotation. Moreover, our proposed method requires much less effort of manual contouring from medical professionals such that an institutional specific model can be more easily established.
Automatic High-Level Data-Flow Synthesis and Optimization of Polynomial Datapaths Using Functional Decomposition

This paper concentrates on high-level data-flow optimization and synthesis techniques for datapath intensive designs such as those in Digital Signal Processing (DSP), computer graphics and embedded systems applications, which are modeled as polynomial computations over Z(2n1) x Z(2n2) x ... x Z(2nd) to Z(2m). Our main contribution in this paper is proposing an optimization method based on functional decomposition of multivariate polynomial in the form of f(x) = g(x) o h(x) + f(0) = g(h(x)) + f(0) to obtain good building blocks, and vanishing polynomials over Z(2m) to add/delete redundancy to/from given polynomial functions to extract further common sub-expressions. Experimental results for combinational implementation of the designs have shown an average saving of 38.85 and 18.85 percent in the number of gates and critical path delay, respectively, compared with the state-of-the-art techniques. Regarding the comparison with our previous works, the area and delay are improved by 10.87 and 11.22 percent, respectively. Furthermore, experimental results of sequential implementations have shown an average saving of 39.26 and 34.70 percent in the area and the latency, respectively, compared with the state-of-the-art techniques.
Sparse-plus-dense-RANSAC for estimation of multiple complex curvilinear models in 2D and 3D

The detection of multiple complex structures in noisy, outlier-rich two- and three-dimensional data is a challenging model estimation problem. In this paper, we build on the RANSAC method to select multiple model instances, focusing especially on curve estimation. Estimation of complex curves such as splines has so far received little attention in the context of model estimation, but has primarily been considered as a segmentation problem. Our proposed curve estimation is based on Sparse-Plus-Dense RANSAC, a framework in which estimation is performed on sparse points, guided by dense image data. This approach is extended to complex curvilinear models, in two- and three-dimensional data. The estimation is hierarchical, based on a merging step that uses an intuitive cost function. Results are presented on synthetic and real X-ray data, showing that the proposed approach performs comparably to state-of-the-art multiple model estimation in the synthetic data, while it significantly outperforms state-of-the-art in the real X-ray sequences. It also achieves correct localization of the model endpoints, which is a crucial aspect in the context of the clinical application. (C) 2012 Elsevier Ltd. All rights reserved.
Accounting for predator species identity reveals variable relationships between nest predation rate and habitat in a temperate forest songbird

Nest predation is the primary cause of nest failure in most ground-nesting bird species. Investigations of relationships between nest predation rate and habitat usually pool different predator species. However, such relationships likely depend on the specific predator involved, partly because habitat requirements vary among predator species. Pooling may therefore impair our ability to identify conservation-relevant relationships between nest predation rate and habitat. We investigated predator-specific nest predation rates in the forest-dependent, ground-nesting wood warbler Phylloscopus sibilatrix in relation to forest area and forest edge complexity at two spatial scales and to the composition of the adjacent habitat matrix. We used camera traps at 559 nests to identify nest predators in five study regions across Europe. When analyzing predation data pooled across predator species, nest predation rate was positively related to forest area at the local scale (1000 m around nest), and higher where proportion of grassland in the adjacent habitat matrix was high but arable land low. Analyses by each predator species revealed variable relationships between nest predation rates and habitat. At the local scale, nest predation by most predators was higher where forest area was large. At the landscape scale (10,000 m around nest), nest predation by buzzards Buteo buteo was high where forest area was small. Predation by pine martens Martes martes was high where edge complexity at the landscape scale was high. Predation by badgers Meles meles was high where the matrix had much grassland but little arable land. Our results suggest that relationships between nest predation rates and habitat can depend on the predator species involved and may differ from analyses disregarding predator identity. Predator-specific nest predation rates, and their relationships to habitat at different spatial scales, should be considered when assessing the impact of habitat change on avian nesting success.
A 0.83-mu W QRS Detection Processor Using Quadratic Spline Wavelet Transform for Wireless ECG Acquisition in 0.35-mu m CMOS

Healthcare electronics count on the effectiveness of the on-patient signal preprocessing unit to moderate the wireless data transfer for better power efficiency. In order to reduce the system power in long-time ECG acquisition, this work describes an on-patient QRS detection processor for arrhythmia monitoring. It extracts the concerned ECG part, i.e., the RR-interval between the QRS complex for evaluating the heart rate variability. The processor is structured by a scale-3 quadratic spline wavelet transform followed by a maxima modulus recognition stage. The former is implemented via a symmetric FIR filter, whereas the latter includes a number of feature extraction steps: zero-crossing detection, peak (zero-derivative) detection, threshold adjustment and two finite state machines for executing the decision rules. Fabricated in 0.35-mu m CMOS the 300-Hz processor draws only 0.83 mu W, which is favorably comparable with the prior arts. In the system tests, the input data is placed via an on-chip 10-bit SAR analog-to-digital converter, while the output data is emitted via an off-the-shelf wireless transmitter (TI CC2500) that is configurable by the processor for different data transmission modes: 1) QRS detection result, 2) raw ECG data or 3) both. Validated with all recordings from the MIT-BIH arrhythmia database, 99.31% sensitivity and 99.70% predictivity are achieved. Mode 1 with solely the result of QRS detection exhibits 6 x reduction of system power over modes 2 and 3.
N6-methyladenosine modification in trophoblasts promotes circSETD2 expression, inhibits miR-181a-5p, and elevates MCL1 transcription to reduce apoptosis of trophoblasts

Preeclampsia (PE) is an obstetric disorder. N6-methyladenosine (m6A) modification is related to PE trophoblast biological behaviors. This study explored the mechanism of m6A-modified circSETD2 in trophoblast biological behaviors. Chorionic trophoblast apoptosis and circSETD2 expression in PE rat models were detected. HTR8/SVneo cells were induced by CoCl2 to establish PE trophoblast models. circSETD2 was silenced or overexpressed to evaluate its effect on cell proliferation, invasion, and apoptosis. m6A level of circSETD2 in trophoblasts was changed by pcDNA3.1-METTL3 and pcDNA3.1-FTO. The targeting relations among miR-181a-5p, circSETD2, and MCL1 were verified by dual-luciferase assay. miR-181a-5p and MCL1 expressions were interfered with to confirm the effect of m6A-modified circSETD2. m6A methylation level was changed in PE rats for in vivo validation. PE rats showed diminished circSETD2 expression and increased apoptosis index. circSETD2 overexpression promoted trophoblast proliferation and invasion, and reduced apoptosis. METTL3 overexpression increased total m6A, circSETD2 m6A, and circSETD2 levels. m6A modification mediated circSETD2 upregulation. circSETD2 was a sponge of miR-181a-5p to elevate MCL1 transcription. miR-181a-5p overexpression or MCL1 silencing annulled the role of m6A-modified circSETD2. circSETD2 inhibition negated suppression of METTL3 overexpression on chorionic trophoblast apoptosis in vivo. Collectively, m6A modification of circSETD2 suppressed miR-181a-5p and increased MCL1 transcription, thus regulating trophoblasts.
How to interpret a meta-analysis?

There is an enormous and ever-growing quantity of healthcare information available and practitioners must transform it into knowledge to be able to use it in their clinical practice. Even readers who do not conduct scientific studies themselves need to understand the scientific method in detail to be able to critically evaluate scientific articles. Evidence-based healthcare (EBH) can be defined as the link between good scientific research and clinical practice and systematic reviews constitute one of the forms of research excellence proposed within EBH. Systematic reviews employ rigorous methods that reduce the occurrence of bias. Systematic reviews with meta-analyses generally optimize the results found, because quantitative analysis of the studies included in the review yields additional information. In this paper, we will discuss how to interpret a meta-analysis and how to apply subset and sensitivity analysis strategies and we will also describe possible sources of heterogeneity and common errors that can affect a meta-analysis.
Molecular Detection for Unconcentrated Gas With ppm Sensitivity Using 220-to-320-GHz Dual-Frequency-Comb Spectrometer in CMOS

Millimeter-wave/terahertz rotational spectroscopy of polar gaseous molecules provides a powerful tool for complicated gas mixture analysis. In this paper, a 220-to-320-GHz dual-frequency-comb spectrometer in 65-nm bulk CMOS is presented, along with a systematic analysis on fundamental issues of rotational spectrometer, including the impacts of various noise mechanisms, gas cell, molecular properties, detection sensitivity, etc. Our comb spectrometer, based on a high-parallelism architecture, probes gas sample with 20 comb lines simultaneously. It does not only improve the scanning speed by 20x, but also reduces the overall energy consumption to 90 mJ/point with 1 Hz bandwidth (or 0.5 s integration time). With its channelized 100-GHz scanning range and sub-kHz specificity, wide range of molecules can be detected. In the measurements, state-of-the-art total radiated power of 5.2 mW and single sideband noise figure of 14.6-19.5 dB are achieved, which further boost the scanning speed and sensitivity. Finally, spectro-scopic measurements for carbonyl sulfide (OCS) and acetonitrile (CH3CN) are presented. With a path length of 70 cm and 1 Hz bandwidth, the measured minimum detectable absorption coefficient reaches alpha(gas,min) = 7.2 x 10(-7) cm(-1). For OCS that enables a minimum detectable concentration of 11 ppm. The predicted sensitivity for some other molecules reaches ppm level (e.g., 3 ppm for hydrogen cyanide), or 10 ppt level if gas preconcentration with a typical gain of 10(5) is used.
Impact of negative pressure wound drainage compared with natural wound drainage after thyroid tumour surgery: A meta-analysis

We conducted a meta-analysis to compare the effectiveness of negative pressure wound drainage to that of spontaneous wound drainage after thyroid tumour surgery. A thorough analysis of the literature up to July 2022 revealed that, of the 1234 patients who used surgery for thyroid tumours, 615 used negative pressure wound drainage and 619 used natural wound drainage. To measure the influence of negative pressure wound drainage in comparison to natural wound drainage following thyroid tumour surgery, mean difference (MD) and odds ratio (OR) with 95% confidence intervals (CIs) were measured using the contentious and dichotomous approaches with a random or fixed-effect model. Subjects who used negative pressure wound drainage had significantly higher averages for drained material (OR, 12.52; 95% CI, 6.78-18.26, P = 0.001), shorter drain placement times (MD, -1.06; 95% CI, 1.57 to -0.55, P = .001), lower rates of infection at the surgical site (OR, 0.17; 95% CI, 0.05-0.60, P = .006), higher rates of wound healing (OR, 5.91; 95% CI, 1.56-22.34, P = .009), and lower rate of wound seroma (OR, 0.21; 95% CI, 0.10-0.42, P < .001) in subjects after thyroid tumour surgery in comparison to subjects who used natural wound drainage after thyroid tumour surgery. Those who used negative pressure wound drainage had significantly higher averages of drained material, shorter drain placement times, lower rates of wound infection at the surgical site, higher rates of wound healing, and lower rates of wound seroma. Care must be used when analysing the results because of the small sample size of 7 of the 13 studies included in the meta-analysis and the lack of studies in several comparisons.
Spinal CircKcnk9 Regulates Chronic Visceral Hypersensitivity of Irritable Bowel Syndrome

Dysregulation of circular RNAs (circRNAs) has been reported to be functionally associated with chronic pain, but it is unknown whether and how circRNAs participate in visceral hypersensitivity. The expression of circKcnk9 was increased in spinal neurons of irritable bowel syndrome (IBS)-like rats. ShcircKcnk9 attenuated visceral hypersensitivity and inhibited c-Fos expression in IBS-like rats, whereas overexpression of spinal circKcnk9 induced visceral hypersensitivity and increased c-Fos expression in control rats. Furthermore, circKcnk9 was found to act as a miR-124-3p sponge. MiR-124-3p antagomir restored pain responses downregulated by shcircKcnk9 in IBS-like rats. Finally, the signal transducer and activator of transcription 3 (STAT3), validated as a target of miR-124-3p, could play a critical role in visceral hypersensitivity by regulating NSF/GluR2. PERSPECTIVE: Spinal circKcnk9 functions as a miR-124-3p sponge to promote visceral hypersensitivity by regulating the STAT3/NSF/GluR2 pathway. This pathway might provide a novel epigenetic mechanism of visceral hypersensitivity and a potential circRNA therapeutic target for IBS.
High-performance semiconductor optical amplifier modules at 1300 nm

Semiconductor-based optical amplifiers (SOAs) offer solutions to a variety of amplification requirements covering operational wavelengths ranging from 600 to 1600 nm. This letter reports on the design and performance of buried heterostructure SOA modules exhibiting state-of-the-art performance within the 1300-nm operational window. The first, a high-gain variant, is optimized for preamplification applications while the second is designed for use as a booster amplifier. Record low noise figure performances for packaged devices are reported.
Sedimentary processes, metal enrichment and potential ecological risk of metals in lacustrine sediments of Svalbard, Arctic

The Svalbard archipelago is a glacial environment bestowed with various lakes that act as a natural archive for understanding environmental conditions. The accumulation of sediments in lake basins and their distribution are affected by different mechanisms. Therefore, to understand the distribution of sediments, factors controlling the transport and metal enrichment in the lake environment, core sediments were studied from four lakes (L-A, L-1, L-2 and L-3). Also, the potential ecological risk index (PERI) was computed to determine the impact of metal enrichment on the sediment-associated biota. The results obtained showed that the distribution of trace elements was mainly controlled by the major elements like Al, Ti, Fe, and Mn attributed to their lithogenic origin. Index of geoaccumulation (Igeo) of all four lakes showed a moderate level of enrichment of metals like Cr and Cd indicating an enhanced supply of these metals probably from the catchment rocks and anthropogenic activities. A comparison of metals with Arctic Sediment Quality Guidelines (ASQGs) showed that Cd, Cr and Cu were enriched in the sediments of all the cores indicating the occurrence of adverse biological effects. Furthermore, a potential ecological risk index (PERI) revealed high Cd indicating considerable potential ecological risk to the sediment-associated biota. Thus, trace element influx to the lakes needs to be monitored with due emphasis on Cd contamination.
Phase I dose-escalation study of milademetan in patients with relapsed or refractory acute myeloid leukemia

Long-term survival in patients with acute myeloid leukemia (AML) remains low, and current treatment modalities are inadequate. Milademetan (DS-3032, RAIN-32), a small-molecule specific murine double minute 2 inhibitor, has shown a p53 status-dependent antitumor effect in vitro studies. This is the first phase I study report of milademetan monotherapy in relapsed/refractory (R/R) AML patients evaluating the safety, tolerability, pharmacokinetics, and preliminary tumor response for further clinical development. Fourteen patients received 90 (starting dose, n = 4), 120 (n = 6), or 160 mg (n = 4) of oral milademetan once daily in a 14/28 treatment cycle. The median total treatment duration was 1.5 cycles. Dose-limiting toxicity did not occur, and the maximum tolerated dose was not reached. Thus, the recommended dose was defined as 160 mg. The most common adverse events (AEs) were decreased appetite (64.3%), febrile neutropenia (50%), nausea (42.9%), and anemia (35.7%). No deaths or AEs leading to treatment discontinuation occurred. Five serious treatment-emergent AEs occurred in 4 patients. Plasma concentration increased linearly with milademetan dose. However, trends in the safety and efficacy of oral milademetan in patients with R/R AML warrant further clinical investigation. This study can inform future milademetan studies in hematologic malignancies.
Detection of double-compression in JPEG images for applications in steganography

This paper presents a method for the detection of double JPEG compression and a maximum-likelihood estimator of the primary quality factor. These methods are essential for construction of accurate targeted and blind steganalysis methods for JPEG images. The proposed methods use support vector machine classifiers with feature vectors formed by histograms of low-frequency discrete cosine transformation coefficients. The performance of the algorithms is compared to selected prior art.
Towards farm-level health management of offshore wind farms for maintenance improvements

This paper studies a conceptual architecture for health management of offshore wind farms. To this aim, various necessary enablers of a health management system are presented to improve reliability and availability while optimizing maintenance costs. The main focus lies on improving existing condition monitoring systems based on concepts of condition-based maintenance and reliability centered maintenance. A brief review of the relevant state-of-the-art is presented and gaps to be filled towards realization of such health management system are discussed.
Face detection by structural models

Despite the successes in the last two decades, the state-of-the-art face detectors still have problems in dealing with images in the wild due to large appearance variations. Instead of leaving appearance variations directly to statistical learning algorithms, we propose a hierarchical part based structural model to explicitly capture them. The model enables part subtype option to handle local appearance variations such as closed and open month, and part deformation to capture the global appearance variations such as pose and expression. In detection, candidate window is fitted to the structural model to infer the part location and part subtype, and detection score is then computed based on the fitted configuration. In this way, the influence of appearance variation is reduced. Besides the face model, we exploit the co-occurrence between face and body, which helps to handle large variations, such as heavy occlusions, to further boost the face detection performance. We present a phrase based representation for body detection, and propose a structural context model to jointly encode the outputs of face detector and body detector. Benefit from the rich structural face and body information, as well as the discriminative structural learning algorithm, our method achieves state-of-the-art performance on FDDB, AFW and a self-annotated dataset, under wide comparisons with commercial and academic methods. (C) 2013 Elsevier B.V. All rights reserved.