ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
R-theta local neighborhood pattern for unconstrained facial image recognition and retrieval

In this paper R-Theta Local Neighborhood Pattern (RTLNP) is proposed for facial image retrieval. RTLNP exploits relationships amongst the pixels in local neighborhood of the reference pixel at different angular and radial widths. The proposed encoding scheme divides the local neighborhood into sectors of equal angular width. These sectors are again divided into subsectors of two radial widths. Average grayscales values of these two subsectors are encoded to generate the micropatterns. Performance of the proposed descriptor has been evaluated and results are compared with the state of the art descriptors e.g. LBP, CSLBP, CSLTP, LDP, LTrP, MBLBP, and SLBP. The most challenging facial constrained and unconstrained databases, namely; AT&T, CARIA-Face-V5-Cropped, LFW, and Color FERET have been used for showing the efficiency of the proposed descriptor. Proposed descriptor is also tested on near infrared (NIR) face databases; CASIA NIR-VIS 2.0 and PolyU-NIRFD to explore its potential with respect to NIR facial images. Better retrieval rates of RTLNP as compared to the existing state of the art descriptors show the effectiveness of the descriptor.
Decreased anti-Mullerian hormone concentration in follicular fluid of female smokers undergoing artificial reproductive techniques

Background: Several reports indicate that women who smoke have an increased risk of failure to conceive compared with their non-smoker counterparts. Here, we assessed the effect of smoking during the Assisted Reproduction Therapy (ART) on a potential marker of ovarian reserve, anti-mullerian hormone (AMH) in the follicular fluid (FF). Materials and Methods: This was a cohort prospective study to assess the association between cigarette smoking and AMH concentrations in FF in fifty-six women undergoing their first ART cycle. Self-reported smoking status over time was also collected through personal interview. The main outcome measured was the association between current smoking and AMH concentrations in FF. Smoking status was assessed by FF cotinine concentrations. Analysis of covariance was performed to test statistical interaction between the main outcome and confounders. Results: The mean concentration of AMH in follicular fluid was significantly decreased among smokers (1.02+/-0.14 vs. 1.74+/-0.15, P<0.05). No statistical interaction was found between this difference in AMH concentrations and confounders like age and BMI. Thus, our data support the idea that AMH is decreased in active smokers across the fertile age. Conclusions: The hypothesis of decreased AMH concentration in follicular fluid in female smokers was confirmed. The mechanisms through which cigarette smoking induces this fall in AMH are unknown and additional research is needed to improve our comprehension of the negative impact of smoking on ART outcomes. (C) 2012 Elsevier Ltd. All rights reserved.
Implementation and Analyses of an Eco-Driving Algorithm for Different Battery Electric Powertrain Topologies Based on a Split Loss Integration Approach

Eco-driving algorithms optimize the speed profile to reduce the energy consumption of a vehicle. This paper presents an eco-driving algorithm for battery electric powertrains that applies a split loss integration approach to incorporate the component losses. The algorithm consistently uses loss models to overcome the drawbacks of efficiency maps, which cannot represent no-load losses at zero torque. The use of loss models is crucial since the optimal solution includes gliding, during which there are no-load losses. An analysis shows, that state-of-the-art nonlinear programming algorithms cannot represent these no-load losses at zero torque with a small modeling error. To effectively compute the powertrain losses with only a small error in comparison to the measurement data, we introduce a tailored combination of nonlinear inequality constraints that interleave two polynomial fits. This approach can properly represent reality. We parameterize the algorithm and validate the vehicle model used with real-world measurement data. Furthermore, we investigate the influence of the proposed interleaved fits by comparing them to a single continuous high-order polynomial fit and to the state of the art. The algorithm is published open source.
Prognostic Factors in Acute Myeloid Leukemia with t(8;21)/ AML1-ETO: Strategies to Define High-Risk Patients

Acute myeloid leukemia (AML) with t(8;21)/AML1-ETO is considered to have favorable prognosis. However, outcome is not universally satisfactory. The aim of this study was to search for potential prognostic risk factors which can help individualized treatment in t(8;21) AML patients. All available clinical and laboratory indicators were analyzed retrospectively in 103 t (8;21) AML patients. All patients were followed up for median of 30 months (range 0.3-73 months). CD56 and IDH1 were found to be closely related to high recurrence (p = 0.002; p = 0.001) and incidence of cumulative recurrence (p = 0.001; p < 0.0001). C-KIT was associated with a high cumulative incidence of non-relapse mortality (p < 0.0001). Elevated galectin-3 (gal-3) had a significantly adverse effect on overall survival (OS) and disease-free survival (DFS) of patients receiving standard-dose cytarabine-based consolidation chemotherapy. In multivariable analysis, gal-3 (p = 0.01), CD56 (p = 0.002), IDH1 (p = 0.007) and C-KIT (p = 0.041) were the independent unfavorable factors for OS. CD56 (p = 0.019), IDH1 (p = 0.001) and consolidation chemotherapy regimen (p = 0.041) were the independent risk factors in terms of DFS. A scoring system incorporating gal-3, CD56, IDH1 and C-KIT proved to be helpful for predicting OS in t (8;21) AML patients. Our results revealed that those carrying four factors mentioned above should be considered to be high-risk patients.
Species-specific effects and the ecological role of programmed cell death in the microalgae Ankistrodesmus (Sphaeropleales, Selenastraceae)

Reports of programmed cell death (PCD) in phytoplankton raise questions about the ecological evolutionary role of cell death in these organisms. We induced PCD by nitrogen deprivation and unregulated cell death (non-PCD) in one strain of the green microalga Ankistrodesmus densus and investigated the effects of the cell death supernatants on phylogenetically related co-occurring organisms using growth rates and maximum biomass as proxies of fitness. PCD-released materials from A. densus CCMA-UFSCar-3 significantly increased growth rates of two conspecific strains compared to healthy culture (HC) supernatants and improved the maximum biomass of all A. densus strains compared to related species. Although growth rates of non-A. densus with PCD supernatants were not statistically different from HC treatment, biomass gain was significantly reduced. Thus, the organic substances released by PCD, possibly nitrogenous compounds, could promote conspecific growth. These results support the argument that PCD may differentiate species or subtypes and increases inclusive fitness in this model unicellular chlorophyte. Further research, however, is needed to identify the responsible molecules and how they interact with cells to provide the PCD benefits.
Long-term intake of aspartame-induced cardiovascular toxicity is reflected in altered histochemical parameters, evokes oxidative stress, and trigger P53-dependent apoptosis in a mouse model

Aspartame (ASP) is probably the best known artificial sugar substitute that is used widely in food. Many experimental studies have reported the toxicity of long-term administration of ASP in various organ tissues. However, there is little evidence available about the nature and mechanisms of the adverse effects of long-term consumption of ASP on the cardiovascular system. This study was conducted to evaluate the possible effects of ASP on heart tissue. For this study 36 mature male mice were divided into one control group and three groups which received respectively 40 mg/kg, 80 mg/kg and 160 mg/kg ASP orally, for 90 days. ASP at the doses of 80 and 160 mg/kg increased the serum content of malondialdehyde (MDA), but decreased serum nitric oxide (NO), creatine kinase (CK) and CK-MB, as well as blood superoxide dismutase (SOD) levels. Serum level of total anti-oxidant capacity (TAC) in blood was also reduced in serum at the dose of 80 mg/kg. Histochemical staining, including Periodic acid-Schiff, Masson's trichrome and Verhoeff-van Gieson staining, indicated that ASP at doses of 80 and 160 mg/kg reduced glycogen deposition and decreased the number of collagen and elastic fibres in the cardiac tissue. The cardiac expression of pro-apoptotic genes, including P53, Bax, Bcl-2 and Caspase-3, was modulated at the dose of 160 mg/kg. Moreover, transcription of Caspase-3 was up-regulated at the dose of 80 mg/kg. In conclusion, long-term consumption of ASP any higher than the acceptable daily intake (40 mg/kg) appears to act by promoting oxidative stress, has the potential to alter both histopathological and biochemical parameters, and induces P53-dependent apoptosis in cardiac tissue.
Convolutional Invasion and Expansion Networks for Tumor Growth Prediction

Tumor growth is associated with cell invasion and mass-effect, which are traditionally formulated by mathematical models, namely reaction-diffusion equations and biomechanics. Such models can be personalized based on clinical measurements to build the predictive models for tumor growth. In this paper, we investigate the possibility of using deep convolutional neural networks to directly represent and learn the cell invasion andmass-effect, and to predict the subsequent involvement regions of a tumor. The invasion network learns the cell invasion from information related to metabolic rate, cell density, and tumor boundary derived from multimodal imaging data. The expansion network models the mass-effect from the growing motion of tumor mass. We also study different architectures that fuse the invasion and expansion networks, in order to exploit the inherent correlations among them. Our network can easily be trained on population data and personalized to a target patient, unlike most previous mathematical modeling methods that fail to incorporate population data. Quantitative experiments on a pancreatic tumor data set show that the proposed method substantially outperforms a state-of-the-art mathematical model-based approach in both accuracy and efficiency, and that the information captured by each of the two subnetworks is complementary.
Enhancement-fusion feature pyramid network for object detection

Scale variation is one of the challenges of object detection. Most state-of-the-art object detectors depend on feature pyramid networks (FPN) for multiscale learning to deal with this problem, in which feature fusion is an essential operation. However, feature fusion does not sufficiently address the difficulty of the detection task. This paper presents an enhancement-fusion feature pyramid network (EFPN) to obtain reliable object representations for object detectors. Specifically, it contains a feature enhancement module (FEM) and a bottom-up path module (BPM). The FEM is used to eliminate the negative impact of the uneven distribution of object scales on the model performance. Then, a BPM is proposed to address the fusion inconsistency in the FPN. Additionally, an attention module (A(c)) is added to eliminate the information loss in the bottom-up aggregation process. EFPN is evaluated by combining it with state-of-the-art detection methods. Extensive experimental results on two datasets MS-COCO and VOC2007 demonstrate the effectiveness of the proposed method.
Low-Power Area-Efficient Fault Tolerant Adder in Current Mode Multi Valued Logic Using Berger Codes

In this paper, we propose a low-power yet area-efficient fault tolerant adder by using Berger codes. The proposed Berger code checker is designed by using the current mode multi-valued logic (CM-MVL) circuits. The proposed structure, which is more area and power efficient than state-of-the-art fault tolerant adders, is able to detect all single and multi-bit unidirectional faults. The efficiency of the proposed fault tolerant adder is evaluated by comparing its characteristics to those of two state-of-the-art fault detection schemes in adders as well as the conventional duplex and parity bit checkers in a 90 nm technology. The results reveal that the proposed 64-bit Berger code checker for adders imposes up to 6.7% and 27.2% delay and area penalties, respectively with a cost of static power dissipation. In the proposed scheme, in sub threshold regime, the power penalty is just 1%, while its area overhead is only 31%. The drawback of using this scheme in sub threshold regime is that delay time introduced to the circuit is unacceptable. So, depending on the application, we should choose one of the above-mentioned schemes.
DBRS2: dense boundary regression for semantic segmentation

Most of the current semantic segmentation approaches have achieved state-of-the-art performance relying on fully convolutional networks. However, the consecutive operations such as pooling or convolution striding lead to spatially disjointed object boundaries. We present a dense boundary regression architecture (DBRS2), which aims to use boundary cues to aid high-level semantic segmentation task. Specifically, we first propose a multilevel guided low-level boundary (MG-LB) learning method, where we exploit multilevel convolutional features as guidance for low-level boundary detection. The predicted MG-LB boundaries are used to enable consistent spatial grouping and enhance precise adherence to segment boundaries. Then, we present a significant global energy model based on boundary penalty and appearance penalty, which are respectively defined on the predicted boundaries and coarse segmentations obtained by the DeepLabv3 network. Finally, the refined segmentations are regressed by minimizing the global energy model. Extensive experiments over PASCAL VOC 2012, ADE20K, CamVid, and BSD500 datasets demonstrate that the proposed approach can obtain state-of-the-art performance on both semantic segmentation and boundary detection tasks. (C) 2018 SPIE and IS&T
Genome-wide analysis of long non-coding RNAs under diel light exhibits role in floral development and the circadian clock in Arabidopsis thaliana

The circadian clock is regulated by signaling networks that enhance a plant's ability to coordinate internal events with the external environment. In this study, we examine the rhythmic expression of long non-coding RNAs (lncRNAs) using multiple transcriptomes of Arabidopsis thaliana in the diel light cycle and integrated this information to have a better understanding of the functions of lncRNAs in regulating the circadian clock. We identified 968, 1050, and 998 lncRNAs at 8 h light, 16 h light and 8 h dark conditions, respectively. Among these, 423, 486, and 417 lncRNAs were uniquely present at 8 h light, 16 h light, and 8 h dark, respectively, whereas 334 lncRNAs were common under the three conditions. The specificity of identified lncRNAs under different light conditions was verified using qRT-PCR. The identified lncRNAs were less GC-rich and expressed at a significantly lower level than the mRNAs of protein-coding genes. In addition, we identified enriched motifs in lncRNA transcribing regions that were associated with light-responsive genes (SORLREP and SORLIP), flower development (AGAMOUS), and circadian clock (CCA1) under all three light conditions. We identified 10 and 12 different lncRNAs targeting different miRNAs with perfect and interrupted complementarity (endogenous target mimic). These predicted lncRNA-interacting miRNAs govern the function of a set of genes involved in the developmental process, reproductive structure development, gene silencing and transcription regulation. We demonstrated that the lncRNA transcribing regions were enriched for epigenetic marks such as H3.3, H3K4me2, H3K4me3, H4K16ac, H3K36ac, H3K56ac and depleted for heterochromatic (H3K9me2 and H3K27me1) and repressive (H3K27me3) histone modifications. Further, we found that hypermethylated genomic regions negatively correlated with lncRNA transcribing regions. Overall, our study showed that lncRNAs expressed corresponding to the diel light cycle are implicated in regulating the circadian rhythm and governing the developmental stage-specific growth.
Effect and comparison of different working fluids on a two-stage organic rankine cycle (ORC) concept

This paper presents Aspen Plus (V7.3) simulations of a two-stage organic rankine cycle concept with internal heat recovery. The proposed system is compared to state-of-the-art processes with four different working fluids distinguished by the slope of the saturated vapor curve in the corresponding T-s-diagram. The heat source is defined as exhaust gas (490 C and 1 bar) from an internal combustion engine, which is fired with biogas from a biomass digestion plant. In a first consideration the exhaust gas outlet is constrained to 130 C to stay above the acid dew point (study 1). In a second study the pinch point of the exhaust gas heat exchanger is set to 10 K. For wet and isentropic fluids the thermodynamic efficiencies of the two-stage cycle exceed the corresponding values of reference processes by up to 2.25%, while the recuperator design benefits dry fluids compared to the two-stage concept. (C) 2013 Elsevier Ltd. All rights reserved.
Image denoising with morphology- and size-adaptive block-matching transform domain filtering

BM3D is a state-of-the-art image denoising method. Its denoised results in the regions with strong edges can often be better than in the regions with smooth or weak edges, due to more accurate block-matching for the strong-edge regions. So using adaptive block sizes on different image regions may result in better image denoising. Based on these observations, in this paper, we first partition each image into regions belonging to one of the three morphological components, i.e., contour, texture, and smooth components, according to the regional energy of alternating current (AC) coefficients of discrete cosine transform (DCT). Then, we can adaptively determine the block size for each morphological component. Specifically, we use the smallest block size for the contour components, the medium block size for the texture components, and the largest block size for the smooth components. To better preserve image details, we also use a multi-stage strategy to implement image denoising, where every stage is similar to the BM3D method, except using adaptive sizes and different transform dimensions. Experimental results show that our proposed algorithm can achieve higher PSNR and MSSIM values than the BM3D method, and also better visual quality of denoised images than by the BM3D method and some other existing state-of-the-art methods.
Cu nanoclusters decorated Ti3C2 nanosheets composite with tetraenzyme mimic activities and the application for smartphone-assisted detection of hypoxanthine

MXene-based nanozymes have increased research enthusiasm in the field of food safety and environment monitoring. Herein, the Cu NCs/Ti3C2 NSs nanocomposites were prepared by modifying copper nanoclusters (Cu NCs) on the surface of Ti3C2 nanosheets (NSs) with a simple two-step method. The Cu NCs/Ti3C2 NSs nanocomposites had outstanding tetraenzyme mimic activities, i.e. peroxidase (POD)-mimics, catalase (CAT)-mimics, ascorbic acid oxidase (AAO)-mimics and superoxide dismutase (SOD)-mimics. Modification of Cu NCs on Ti3C2 NSs can enhance tetraenzyme mimic activities because of the synergistic catalytic effect between Cu NCs and Ti3C2 NSs. The catalytic mechanism and steady-state kinetics of Cu NCs/Ti3C2 NSs were also investigated. Based on the POD-mimic activity of Cu NCs/Ti3C2 NSs, a simple and rapid colorimetric method was established for the on-site detection of hypoxanthine (Hx), with the linear range of 5-200 μM and limit of detection (LOD) was 0.25 μM. The visible color change with the increase of Hx concentration can be recognized by a smartphone APP to transfer the red (R), green (G) and blue (B) value for the quantitative analysis of Hx, with the linear range of 10-200 μM, which provided a convenient method for the real-time detection of Hx. This work not only provides a significant route to fabricate nanocomposite with outstanding tetraenzyme mimic activities but also offers a low-cost and rapid method for monitoring the freshness of aquatic products.
Stemming the Leak: A Novel Treatment for Gastro-Bronchial Fistula

Laparoscopic sleeve gastrectomy (LSG) is a commonly used procedure in bariatric patients that often has excellent results. Despite its advantages, LSG is burdened by specific intraoperative and postoperative early and late complications. One of the life-threatening complications is gastric fistula, usually treated with a multidisciplinary surgical-endoscopic approach. In case of failure of the latter, alternative nonoperative techniques such as the use of autologous stem cells truly represents an innovative possibility, with only few cases described in literature. Here, we report the case of a 25-year-old man with post-LSG broncho-gastric fistula treated with application of autologous stem cells after the failure of the conventional surgical/endoscopic approach.
The sarcoplasmic protein profile of breast muscle in Turkeys in response to different dietary ratios of limiting amino acids and Clostridium perfringens-induced inflammation

In this study, the effects of the Arginine/Lysine (Arg/Lys) ratio in low- and high-methionine (Met) diets on the sarcoplasmic protein profile of breast muscles from turkeys reared under optimal or challenge (Clostridium perfringens infection) conditions were determined. One-day-old Hybrid Converter female turkey poults (216 in total) obtained from a commercial hatchery on hatching day, and on the basis of their average initial body weight were randomly allocated to 12 pens (4 m2 each; 2.0 m × 2.0 m) containing litter bedding and were reared over a 42-day experimental period. Diets with high levels of Lys contained approximately 1.80% and 1.65% Lys and were offered in two successive feeding periods (days 1-28 and days 29-42). The supplemental levels of Lys were consistent with the nutritional specifications for birds at their respective ages as established in the Management Guidelines for Raising Commercial Turkeys. The experiment was based on a completely randomized 3 × 2 × 2 factorial design with three levels of Arg (90%, 100% and 110%) relative to the content of dietary Met (30 or 45%) and without (-) or with (+) C. perfringens challenge at 34, 36, or 37 d of age. Meat samples were investigated in terms of pH, color, and sarcoplasmic protein profile. The experimental factors did not influence meat quality but the dietary Arg content affected meat color. The sarcoplasmic protein profile was influenced by all studied factors, and glycolytic enzymes were the most abundant. This study evidenced strong association between the challenge conditions and the involvement of glycolytic enzymes in cell metabolism, particularly in inflammatory processes, and DNA replication and maintenance in turkeys. The results showed an effect of C. perfringens infection and feeding with different doses of Arg and Met may lead to significant consequences in cell metabolism.