ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Improving the Quality of Delay-Based PUFs via Optical Proximity Correction

Silicon physically unclonable functions (PUFs) are circuits that exploit modern manufacturing variations to generate unique signatures for chip authentication and cryptographic key generation. Existing research has focused on improving PUF quality at architectural or design levels, but has ignored opportunities available during fabrication, which is the source of systematic and random variation in (ICs)/PUFs. For typical ICs (where security is not a concern), optical proximity correction (OPC) is used to suppress both these types of variations. However, several prior works have shown that only systematic variations negatively impact PUF quality and random variations are beneficial for PUFs. In this paper, we propose two PUF-aware OPC cost functions: 1) P-OPC generates a PUF lithography mask that increases all variations in PUF circuitry (the opposite of state-of-the-art OPC), and 2) SVC-OPC generates mask patterns that reduce the systematic variation found in PUFs for better quality. Simulation results for ring oscillator (RO) PUFs show that the proposed techniques can improve PUF signature quality compared to current state-of-the-art OPC.
Color and sharpness assessment of single image dehazing

Image dehazing is the process of enhancing a color image of a natural scene that contains an undesirable veil of fog for visualization or as a pre-processing step for computer vision systems. In this work, we investigate the performances of eleven state-of-the-art image quality metrics in evaluating dehazed images, and discuss challenges in designing an efficient dehazing evaluation metric. This is done through a composite study based on the agreement between subjective and objective evaluations. Accordingly, we evaluate five state-of-the-art dehazing algorithms. We use two semi-indoor scenes, degraded with several levels of fog. One important aspect of these scenes is that the fog-free images are available and can therefore serve as ground-truth data for dehazing methods evaluation. This study shows that the best working dehazing method depends on the density of fog. There seems to be a clear distinction between what people perceive as good quality in terms of color restoration and in terms of sharpness restoration. Most metrics show limitations in providing proper quality prediction of dehazing. According to the introduction and analysis, a contribution of this work is to point out the flaws in the evaluation and development of dehazing methods. Our observations might be considered when designing efficient methods and metrics dedicated to image dehazing.
Bruno Schulz's 1933 Monograph: On the Hereditary Etiology of Schizophrenia

In his 1933 article, Bruno Schulz reported a follow-up and reanalysis of the schizophrenic probands and their relatives first studied by Rüdin 20 years earlier that sought to clarify whether schizophrenia was a valid "unit-character" for Mendelian genetic analysis. He proposed a range of subgroupings of probands, particularly traditional subtyping, presence or absence of identifiable causal influences, and outcome. He then compared those subgroupings in several ways, most commonly by the risk for schizophrenia in their siblings and by the level of resemblance among proband-sibling affected pairs. Of his many findings, those of greatest interest included (1) probands with possible and probable physical causes, particularly those with head trauma, had substantially lower risk of illness in siblings, (2) probands with a hebephrenic subtype had a striking elevation of risk for schizophrenia in siblings, (3) probands with psychological causes had higher rates of good outcome, (4) proband-sibling pairs resembled one another for the classical schizophrenic subtypes, and (5) an absence of any cases of schizophrenia in siblings of a small group of schizophrenic probands with birth complications, convulsions, and skull deformities. Schulz used this sample in a fundamentally different way than Rüdin. Rather than seeking for Mendelian transmission patterns, Schulz used family data to evaluate hypothesis about clinical/etiological heterogeneity, thereby presaging many subsequent family studies of psychiatric disorders. While Schulz did not claim to have proved the etiologic heterogeneity of schizophrenia, he raised important questions, still unanswered, about whether schizophrenia is a legitimate "unit-character" appropriate for genetic analysis.
Investigation of androgen receptor-dependent alternative splicing has identified a unique subtype of lethal prostate cancer

A complete proteomics study characterizing active androgen receptor (AR) complexes in prostate cancer (PCa) cells identified a diversity of protein interactors with tumorigenic annotations, including known RNA splicing factors. Thus, we chose to further investigate the functional role of AR-mediated alternative RNA splicing in PCa disease progression. We selected two AR-interacting RNA splicing factors, Src associated in mitosis of 68 kDa (SAM68) and DEAD (Asp-Glu-Ala-Asp) box helicase 5 (DDX5) to examine their associative roles in AR-dependent alternative RNA splicing. To assess the true physiological role of AR in alternative RNA splicing, we assessed splicing profiles of LNCaP PCa cells using exon microarrays and correlated the results to PCa clinical datasets. As a result, we were able to highlight alternative splicing events of clinical significance. Initial use of exon-mini gene cassettes illustrated hormone-dependent AR-mediated exon-inclusion splicing events with SAM68 or exon-exclusion splicing events with DDX5 overexpression. The physiological significance in PCa was investigated through the application of clinical exon array analysis, where we identified exon-gene sets that were able to delineate aggressive disease progression profiles and predict patient disease-free outcomes independently of pathological clinical criteria. Using a clinical dataset with patients categorized as prostate cancer-specific death (PCSD), these exon gene sets further identified a select group of patients with extremely poor disease-free outcomes. Overall, these results strongly suggest a nonclassical role of AR in mediating robust alternative RNA splicing in PCa. Moreover, AR-mediated alternative spicing contributes to aggressive PCa progression, where we identified a new subtype of lethal PCa defined by AR-dependent alternative splicing.
Insights into microbial interactive mechanism regulating dissimilatory nitrate reduction processes in riparian freshwater aquaculture sediments

Aquaculture can substantially alter the accumulation and cycling of nutrients in sediments. However, the microbial mechanisms mediating sediment dissimilatory nitrate (NO3-) reduction in freshwater aquaculture ponds are still unclear, which rule the removal and retention of N element. In the present study, three microbial NO3- reduction processes in riparian aquaculture pond sediments (i.e., crab, shrimp and fish ponds) and natural freshwater sediments (i.e., lakes and rivers) were investigated via isotopic tracing and molecular analyses. The potential rates of denitrification, anaerobic ammonium oxidation (anammox) and dissimilatory nitrate reduction to ammonium (DNRA) significantly increased in the aquaculture ponds compared with the natural freshwaters. Denitrification contributed 90.40-94.22% to the total NO3- reduction (product as N2), followed by 2.49-5.82% of anammox (product as N2) and 2.09-5.18% of DRNA (product as NH4+). The availability of C and N substrates, rather than functional gene abundance, regulated the activities of NO3- reductions and microbiome composition. Microbial mechanism based on network analysis indicated that heterotrophic denitrifiers and DNRA bacteria (e.g., Bacillus, Micromonospora, Mycobacterium and Brachybacterium) determined the community structure and function for N conversions in aquaculture ponds, whereas the such microbial network in natural freshwater sediments was manipulated by autotrophic denitrifiers (e.g., Desulfuromonas, Polaromonas, Solitalea). Collectively, this study provides an in-depth exploration of microbial nitrogen removal in freshwater aquaculture areas and supports management strategies for N pollution caused by reclamation for aquaculture in riparian zones.
Indication criteria for monoclonal antibody treatment for COVID-19 in the era of vaccination: is an update needed?

This study describes a cohort of 223 patients who received anti-S protein monoclonal antibody (mAb) treatment for COVID-19 after having met the indication criteria set by the national guidelines in the Czech Republic at the time. The authors compare the vaccinated and unvaccinated subpopulations of this cohort. The results show that most of the patients (73.5%) already had significant circulating levels of anti-S antibodies detectable at the time of treatment. The authors confirm a positive correlation between number of vaccine doses and S-protein antibody levels. The data show, that vaccinated patients are overall less likely to be hospitalized than unvaccinated ones. The authors recommend a change in the national guidelines for mAb treatment in the Czech Republic.
被撤回的出版物: Recent Advances in 3D Object Detection in the Era of Deep Neural Networks: A Survey (Retracted Article)

With the rapid development of deep learning technology and other powerful tools, 3D object detection has made great progress and become one of the fastest growing field in computer vision. Many automated applications such as robotic navigation, autonomous driving, and virtual or augmented reality system require estimation of accurate 3D object location and detection. Under this requirement, many methods have been proposed to improve the performance of 3D object localization and detection. Despite recent efforts, 3D object detection is still a very challenging task due to occlusion, viewpoint variations, scale changes, and limited information in 3D scenes. In this paper, we present a comprehensive review of recent state-of-the-art approaches in 3D object detection technology. We start with some basic concepts, then describe some of the available datasets that are designed to facilitate the performance evaluation of 3D object detection algorithms. Next, we will review the state-of-the-art technologies in this area, highlighting their contributions, importance, and limitations as a guide for future research. Finally, we provide a quantitative comparison of the results of the state-of-the-art methods on the popular public datasets.
Sexually transmitted infection screening and reproductive health counseling in adolescent renal transplant recipients: Perceptions and practice patterns. A study from the Midwest Pediatric Nephrology Consortium

We wanted to identify practice patterns and perceived barriers among pediatric nephrologists regarding STI screening and reproductive health counseling in adolescent renal transplant recipients. We created an online Likert-scaled survey. Response rate was 54%. The majority (83%) believed STI risk in their patients was similar to or higher than healthy teens. Interestingly, while 67% felt moderately or very confident in asking about sexual activity and counseling about safer sex, only 43% routinely or always inquired about sexual activity, and only 42% routinely or always counseled about safer sex. Fifty-four percent routinely or always discussed contraceptive options and implications of unintentional pregnancy. Fifty-one percent routinely or always referred patients to a gynecologist or adolescent provider for contraception prescription. The most common counseling mechanism was informal discussions in clinic (87%). Ten percent had no mechanism in place. Major barriers included time limitations, adolescents' fear regarding confidentiality, and lack of professional training. This is the first report of perceptions and practice patterns of pediatric nephrologists regarding STI screening and reproductive health counseling. Providers seem to recognize the importance of counseling; however, translation into practice remains low. Professional training in this area and increased encounter time could improve counseling delivery and thereby reduce risk in this population.
Transform Coding Based on Source Filter Model in the MDCT Domain

State-of-the-art voice codecs have been developed to extend the input bandwidth to enhance quality while maintaining interoperability with a legacy codec. Most of them employ a modified discrete cosine transform (MDCT) for coding their extended band We propose a source filter model-based coding algorithm of MDCT spectral coefficients, apply it to the ITU-T G.711.1 super wideband (SWB) extension codec, and subjectively test it to validate the model. A subjective test shows abetter quality over the standardized SWB codec.
A Novel Ionic Conductive Polyurethane Based on Deep Eutectic Solvent Continuing Traditional Merits

Artificial intelligence (AI) has become increasingly popular along with the development of the bionic neural system. Ionic conductors play an important role in the AI system due to the ability of bionic sensing and signal transporting. Traditional low-polarity elastomers possess outstanding mechanical strength and stability, such as polyurethane, which is difficult to be directly endowed with ionic conductivity without impairing its properties. Herein, we have first put forward a new approach to synthesize a liquid-free ionic conductive polyurethane (CPU) through one-step copolymerization between a green deep eutectic solvent (DES) and a prepolymer of polyurethane. The as-prepared CPU can retain the native properties of the traditional polyurethane (PU) such as the homogeneous phase, ease of molding, high transparency (about 93.3%), and excellent mechanical properties. By introducing the DES as the covalent cross-linking agent and ionic conductor at the same time, the CPU also has fine ionic conductivity (3.78 × 10-5 S cm-1), environmental resistance like anti-freezing (-20 °C), and solvent resistance. Based on the excellent conductivity and mechanical strength, the flexible CPU can be applied as a sensing element in pressure sensors. The CPU-based sensor has presented long-term stability, high sensitivity, and wide-ranging response (0.17-3.28 MPa) to the applied pressure, which will be suitable for the industrial demands for practical applications.
FrWF-Based LMBTC: Memory-Efficient Image Coding for Visual Sensors

After the successful development of JPEG2000, many state-of-the-art wavelet-based image coding algorithms have been developed. However, the traditional discrete wavelet transform (DWT) is implemented with memory intensive and time-consuming algorithms and, therefore, has very high system resource requirements. In particular, the very large requirement of memory poses a serious limitation for multimedia applications on memory-constrained portable devices, such as digital cameras and sensor nodes. In this paper, we propose a novel wavelet-based image coder with low memory requirements and low complexity that preserves the compression efficiency. Our encoder employs the fractional wavelet filter (FrWF) to calculate the DWT coefficients, which are quantized and encoded with a novel low memory block tree coding (LMBTC) algorithm. The LMBTC is a listless form of the wavelet block tree coding algorithm. Simulation results demonstrate that the proposed coder significantly reduces memory requirements and computational complexity and has competitive coding efficiency in comparison with other state-of-the-art coders. The FrWF combined with the LMBTC is, thus, a viable option for image communication over wireless sensor networks.
A decision support model for scheduling exhibition projects in art museums

The main purpose of scheduling exhibition projects for art museums is to provide the visitors with more exhibitions and to utilize the galleries as fully as possible Because the combinations of possible exhibitions for all galleries at any given time are numerous, it is difficult for the art museum's planner to make an optimal decision. Therefore, this paper developed a decision support model with genetic algorithms, called SCHEMA (SCHeduling Exhibitions for Museum of Art). In the model the galleries are the resource which the exhibitions utilize in the sequence of their priority values The model's evaluation shows to be significantly effective in planning time, percent usage of the gallery. and the number of exhibitions scheduled. Because all the complex computations are done by the model. the decision making process of the scheduling stage is speeded up considerably. (C) 2009 Elsevier Ltd. All rights reserved.
An efficient approach for scene categorization based on discriminative codebook learning in bag-of-words framework

This paper proposes an efficient technique for learning a discriminative codebook for scene categorization. A state-of-the-art approach for scene categorization is the Bag-of-Words (BoW) framework, where codebook generation plays an important role in determining the performance of the system. Traditionally, the codebook generation methods adopted in the BoW techniques are designed to minimize the quantization error, rather than optimize the classification accuracy. In view of this, this paper tries to address the issue by careful design of the codewords such that the resulting image histograms for each category will retain strong discriminating power, while the online categorization of the testing image is as efficient as in the baseline BoW. The codewords are refined iteratively to improve their discriminative power offline. The proposed method is validated on UIUC Scene-15 dataset and NTU Scene-25 dataset and it is shown to outperform other state-of-the-art codebook generation methods in scene categorization. (C) 2013 Elsevier B.V. All rights reserved.
A survey study on trust-based security in Internet of Things: Challenges and issues

The Internet of Things (IoT) is an emerging communication technology which connects all of the network-enabled devises in all of the world. It is being pervasively utilized in the variety in-dustrial applications such as infrastructure monitoring, utilities, controlling, mission-critical, and security-sensitive applications. Similar to other conventional networks, the IoT applications are also vulnerable to the different kinds of security breaches, threats, and attacks. To mitigate such related problems, various cryptographic, trust-based approaches, and models have been pre-sented in the literature. To address the issue, this paper presents a subjective survey study on IoT trust security and challenges to investigate solutions provided for trust management & handling in the IoT context. The subjective survey is designed based on the commonalities and differences of the presented state-of-the-arts in literature. Then, it classifies the studied state-of-the-art schemes that are based on the trust handling method and summarizes their main contributions and properties. A comparison on the various published papers of these trust-based schemes is tabulated based on the relevant concepts and evaluation metrics derived from literature. Therefore, the paper highlights potentials, existing gaps, and the future research direction in the trust management of the IoT context for further processing and improvement.
Intensity Values of Terrestrial Laser Scans Reveal Hidden Black Rock Art Pigment

The intensity values of terrestrial laser scanning (TLS) can be used to reveal painted black rock art behind graffiti and moss. The effect was observed in Gumahon cave in Penablanca, Philippines where previously unnoticed black pigment was exposed underneath moss, red and white painted graffiti, and etched name graffiti. The application of TLS intensity values for this purpose has not, to our knowledge, been previously reported. The significance of this finding is that archaeologists are provided a new method of detecting obfuscated rock art that can aid interpretation. The method can be applied in similar contexts as black painted rock art is common in limestone caves across Southeast Asia and Micronesia, but also ubiquitous globally.
Fabrication of a novel electrochemical immunosensor for the sensitive detection of carcinoembryonic antigen using a double signal attenuation strategy

Carcinoembryonic antigen (CEA), an acidic protein, is a characteristic antigen produced by the tumor of various cancers (eg, breast, cervical, rectal, lung, etc.). Therefore, the detection of cancer antigens is very important for the early diagnosis and treatment of cancer. In this study, a novel of "signal off" strategy for electrochemical immunosensor was developed to detect CEA. To this end, Prussian blue nanoparticles (PB NPs), an electroactive substance, were used as the immunological platform. In addition, CuO2@SiO2 nanocomposites, which release Cu2+ and H2O2 under acidic conditions, were synthesized. The generated Cu2+ can replace the high spin iron (FeIII) in PB NPs, which in turn reduces the oxidation peak current of PB NPs. Due to the peroxidase-like nature of PB NPs, they can react with self-generated H2O2 to generate hydroxyl radicals (·OH), which can further convert 4-chloro-1 naphthol (4-CN) into a non-conductive polymer that accumulates on the electrode surface, this leads to a further reduction in the electrical signal of the PB NPs. Moreover, the self-generated Cu2+ and H2O2 can reduce the introduction of exogenous substances and improve the detection accuracy. Square wave voltammetry (SWV) revealed that the electrical signal of PB NPs gradually decreased with increasing CEA concentration. In addition, the electrical signal of PB NPs exhibited a good linearity in the range from 0.01 pg mL-1 to 80 ng mL-1, where in the logarithm of CEA concentration and the detection limit was as low as 0.0032 pg mL-1.
Small molecule inhibitors targeting the cancers

Compared with traditional therapies, targeted therapy has merits in selectivity, efficacy, and tolerability. Small molecule inhibitors are one of the primary targeted therapies for cancer. Due to their advantages in a wide range of targets, convenient medication, and the ability to penetrate into the central nervous system, many efforts have been devoted to developing more small molecule inhibitors. To date, 88 small molecule inhibitors have been approved by the United States Food and Drug Administration to treat cancers. Despite remarkable progress, small molecule inhibitors in cancer treatment still face many obstacles, such as low response rate, short duration of response, toxicity, biomarkers, and resistance. To better promote the development of small molecule inhibitors targeting cancers, we comprehensively reviewed small molecule inhibitors involved in all the approved agents and pivotal drug candidates in clinical trials arranged by the signaling pathways and the classification of small molecule inhibitors. We discussed lessons learned from the development of these agents, the proper strategies to overcome resistance arising from different mechanisms, and combination therapies concerned with small molecule inhibitors. Through our review, we hoped to provide insights and perspectives for the research and development of small molecule inhibitors in cancer treatment.