ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Identification of a necroptosis-related prognostic gene signature associated with tumor immune microenvironment in cervical carcinoma and experimental verification

Cervical carcinoma (CC) has been associated with high morbidity, poor prognosis, and high intratumor heterogeneity. Necroptosis is the significant cellular signal pathway in tumors which may overcome tumor cells' apoptosis resistance. To investigate the relationship between CC and necroptosis, we established a prognostic model based on necroptosis-related genes for predicting the overall survival (OS) of CC patients. The gene expression data and clinical information of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients were obtained from The Cancer Genome Atlas (TCGA). We identified 43 differentially expressed necroptosis-related genes (NRGs) in CESC by examining differential gene expression between CESC tumors and normal tissues, and 159 NRGs from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Gene ontology (GO) and KEGG enrichment analysis illustrated that the genes identified were mainly related to cell necrosis, extrinsic apoptosis, Influenza A, I - kappaB kinase/NF - kappaB, NOD - like receptor, and other signaling pathways. Subsequently, least absolute shrinkage and selection operator (LASSO) regression and univariate and multivariate Cox regression analyses were used to screen for NRGs that were correlated with patient prognosis. A prognostic signature that includes CAMK2A, CYBB, IL1A, IL1B, SLC25A5, and TICAM2 was established. Based on the prognostic model, patients were stratified into either the high-risk or low-risk subgroups with distinct survival. Receiver operating characteristic (ROC) curve analysis was used to identify the predictive accuracy of the model. In relation to different clinical variables, stratification analyses were performed to demonstrate the associations between the expression levels of the six identified NRGs and the clinical variables in CESC. Immunohistochemical (IHC) validation experiments explored abnormal expressions of these six NRGs in CESC. We also explored the relationship between risk score of this necroptosis signature and expression levels of some driver genes in TCGA CESC database and Gene Expression Omnibus (GEO) datasets. Significant relationships between the six prognostic NRGs and immune-cell infiltration, chemokines, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoints in CESC were discovered. In conclusion, we successfully constructed and validated a novel NRG signature for predicting the prognosis of CC patients and might also play a crucial role in the progression and immune microenvironment in CC.
Analysis on spatial development mode of eco-sports tourism in Grand Canal landscape environment culture belt

The development mode of sports tourism is based on the ecological environment. In order to reduce the negative impact of sports tourism on the environment, the development of ecological sports tourism based on the perspective of ecology is the top priority for the healthy and sustainable development of sports tourism. On the basis of summarizing and analyzing the previous research results, this paper expounds the elements and value of ecological sports culture tourism resources, introduces the ecological sports tourism complex model of landscape environmental culture belt, and expounds the cultural connotation characteristics of ecological sports tourism environment. Environmental science is mainly reflected in the promotion of the benign cycle of natural ecological environment, the protection of living things, the protection of water bodies and the treatment of water pollution, and the good protection of atmospheric environment, geology, and geomorphology. Based on the development of ecological sports tourism space with landscape environment culture belt, this paper introduces the resource development system of Beijing-Hangzhou Canal ecological sports culture tourism, constructs the landscape space development mode of ecological sports tourism, and analyzes the landscape space structure of ecological sports tourism. Based on landscape culture with the basis of sports tourism resources, analyzes the influence factors of sports tourism spatial structure from the direction of the depth and breadth of two dimensions expand sports events and the ecological sports cultural tourism, the depth of the fusion depth aspects emphatically at sporting events, and the ecological sports cultural tourism into the connotation of mining, breadth aspect focuses on the formats of the extension of rich and associated industries. To study the important carrier of promoting the development of ecological sports culture resources and sports industry in the Canal, to plan the layout and establish the sports culture tourism industry base reasonably, and to form the sports culture tourism industry ecosphere. The results show that the scale and speed of the development of sports tourism not only depend on the attractive sports tourism resources but also highly depend on the level of economic and social development in the region. The supply of sports tourism must take the demand of sports tourism market as the guide, combine sports activities with tourism activities in an ecological and organic way, develop various sports items to meet the needs of tourists, and realize the ecological, economic, and social benefits of ecological sports tourism. The research results of this paper provide reference for the further development of eco-sports tourism in landscape environment and culture belt.
Sustainability in manufacturing operations scheduling: A state of the art review

Sustainability in manufacturing systems is an urgent requirement for today's manufacturing companies. This paper focuses on sustainable manufacturing operations scheduling, a subject which has been attracting increasing interest from researchers in recent years. This paper presents a state of the art review of this field. First, it characterizes what can be considered as sustainable manufacturing operations scheduling, and introduces the relevant challenges and issues. An analysis of the literature is then proposed, and organized according to three keys. The shortcomings in the literature are then discussed in depth, and subsequently urgent problems that must be solved through research in order to meet industry requirements are pointed out. (C) 2015 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
LEARN: Learned Experts' Assessment-Based Reconstruction Network for Sparse-Data CT

Compressive sensing (CS) has proved effective for tomographic reconstruction from sparsely collected data or under-sampled measurements, which are practically important for few-view computed tomography (CT), tomosynthesis, interior tomography, and so on. To perform sparse-data CT, the iterative reconstruction commonly uses regularizers in the CS framework. Currently, how to choose the parameters adaptively for regularization is a major open problem. In this paper, inspired by the idea of machine learning especially deep learning, we unfold the state-of-the- art "fields of experts"-based iterative reconstruction scheme up to a number of iterations for data-driven training, construct a learned experts' assessment-based reconstruction network (LEARN) for sparse-data CT, and demonstrate the feasibility and merits of our LEARN network. The experimental results with our proposed LEARN network produces a superior performance with the well-known Mayo Clinic low-dose challenge data set relative to the several state-of- the-art methods, in terms of artifact reduction, feature preservation, and computational speed. This is consistent to our insight that because all the regularization terms and parameters used in the iterative reconstruction are now learned from the training data, our LEARN network utilizes application-oriented knowledge more effectively and recovers underlying images more favorably than competing algorithms. Also, the number of layers in the LEARN network is only 50, reducing the computational complexity of typical iterative algorithms by orders of magnitude.
Contactless Heterogeneous 3-D ICs for Smart Sensing Systems

A heterogeneous contactless transceiver circuit is designed to provide inter-tier signalling for a 3-D system considering specific bonding constraints. The system is composed of two tiers, a 65 nm processing tier and a 0.35 mu m sensing tier. Face-to-back integration is chosen to support fluidic sensing. Half duplex communication between the tiers is provided through inductive links. Each tier is considered to be fabricated in a different technology to enable low manufacturing cost and benefit from the advantages each technology offers. Both the uplink and downlink transceivers achieve data rates that reach 1 Gbps with non-return-to-zero data encoding. Energy efficiency is the predominant objective, with the uplink dissipating 5.28 pJ/b and 8.67 pJ/b for the downlink. A 6.8x power reduction is demonstrated when using heterogeneous technologies, compared to a state-of-the-art 0.35 mu m transceiver, while the dissipated energy is decreased by 37.5% as compared to a state-of-the-art 65 nm transceiver. Process variation analysis is also performed to ensure the proposed circuit operates correctly across several process corners, covering a broad design space. To improve system robustness, an overhead of 2.3% on the peak power and <1% on the average power is shown, respectively.
Universal platform for accurately damage-free mapping of sEVs cargo information

SEVs (small extracellular vesicles) contents signatures appear to mirror pathological changes of diseases, and mapping sEVs contents profile is a promising approach for non-invasive diagnosis of the disease. Herein, we propose a universal system for accurately and damage-freely mapping of sEVs content profile using dual-recognition triggered CHA (catalytic hairpin assembly) and DNAzyme based signal amplification strategy. After immunoassay based capture of CD63 positive sEVs by anti-CD63 lgG coated on the surface of polystyrene plates, probes are incubated with fixed sEVs to penetrate sEVs membrane and act to sense sEVs contents. In detection step, integrated CHA and DNAzyme based strategy is initiated by released initiator from capture probe after recognizing targets, forming a dual circle signal recycling process, realizing signal amplification for high sensitivity. Given the attractive analytical features that i) a universal platform for indistinctive sEVs nucleic acids and protein molecules detection; ii) high sensitivity derived from dual circle signal recycling process; iii) enzyme-free characteristic of integrated CHA and DNAzyme minimizes the interference to sEVs biological activity; iv) mapping of sEVs contents profiles indicates a brand-new strategy for non-invasive diagnosis of the disease, the present approach shows great promise for analyzing additional different analytes in clinical and experimental researches.
Theoretical Analysis of AM and FM Interference Robustness of Integrating DDR Receiver for Human Body Communication

Prolific growth of miniaturized devices has led to widespread use of wearable devices and physiological sensors. The state-of-art technique for connecting these devices and sensors is through wireless radio waves. However, wireless body area wireless body area network (WBAN) suffers from limited security (wireless signals from energy-constrained sensors can be snooped by nearby attackers), poor energy-efficiency (up conversion and down conversion), and self-interference. Human body communication (HBC), which uses human body as a conducting medium, has emerged as a new alternative physical layer for WBAN, as it can enable communication with better energy efficiency and enhanced security. Broadband (BB) HBC uses the human body channel as a broadband communication medium and can enable higher energy efficiency compared to narrowband HBC. However, due to the antenna effect of human body, ambient interferences get picked up from the environment, proving to be one of the primary bottlenecks for BB-HBC systems. In this paper, we analyze the performance of an integrating dual data rate (I-DDR) receiver, which enables interference robust BB-HBC, under continuous wave (CW), amplitude modulated (AM), and frequency modulated (FM) interferences. Theoretical derivations along with simulations provide key insights into the behavior of I-DDR receiver under different interference scenarios, highlighting the efficacy (>22 dB improvement in SIR tolerance for both FM and AM) of the technique. Finally, measurements are carried out by applying the I-DDR principle on signals transmitted through the human body and captured on an oscilloscope. Measurements from an I-DDR receiver fabricated in TSMC 65 nm technology shows <10(-4) BER in presence of CW, AM, and FM interference with -21 dB SIR further demonstrating the efficacy of the I-DDR method in interference rejection.
Coal mining and environmental sustainability in South Africa: do institutions matter?

This study investigates the effects of coal mining on environmental sustainability in South Africa in relation to the moderating role of institutions. To achieve the study's objectives, the fully modified least square (FMOLS), dynamic least squares (DOLS), canonical cointegrating regression (CCR), Bayer-Hanck cointegration and Toda-Yamamoto causality test are employed for the period 1984-2018. Results from the study show that coal mining contributes to environmental degradation in South Africa, while its interaction with institutional quality mitigates the severity of this negative impact. Furthermore, there is evidence that economic growth has a bidirectional causality with ecological footprint and coal mining, while institutional quality also Granger causes ecological footprint. To promote a sustainable environment, there is a need for the government and the institutions to form the foundation for the shift toward environmental sustainability, with particular attention paid to the development and implementation of greenhouse policy.
Bees swarm optimization guided by data mining techniques for document information retrieval

This paper explores advances in the data mining field to solve the fundamental Document Information Retrieval problem. In the proposed approach, useful knowledge is first discovered by using data mining techniques, then swarms use this knowledge to explore the whole space of documents intelligently. We have investigated two data mining techniques in the preprocessing step. The first one aims to split the collection of documents into similar clusters by using the k-means algorithm, while the second one extracts the most closed frequent terms on each cluster already created using the DCI_Closed algorithm. For the solving step, BSO (Bees Swarm Optimization) is used to explore the cluster of documents deeply. The proposed approach has been evaluated on well-known collections such as CACM (Collection of ACM), TREC (Text REtrieval Conference), Webdocs, and Wikilinks, and it has been compared to state-of-the-art data mining, bio-inspired and other documents information retrieval based approaches. The results show that the proposed approach improves the quality of returned documents considerably, with a competitive computational time compared to state-of-the-art approaches. (C) 2017 Elsevier Ltd. All rights reserved.
Challenges in Anaesthesia Management of a 15-Year-Old Female With Ovarian Teratoma for Exploratory Laparotomy: A Case Report

Rarely, an ovarian tumour will develop the growing teratoma syndrome. Growing teratoma syndrome of the cystic type has been linked to difficulties with anaesthesia because of the abdominal pressure the tumour exerts on the thorax. There haven't been any reports of this kind of ovarian tumour associated with ascites and bilateral pleural effusion in a paediatric age group. Here, we describe our anaesthetic experience in a case of developing solid-type ovarian teratoma syndrome with deranged lung status and haemodynamics. The patient was a 15-year-old female who was diagnosed with ovarian teratoma. She was scheduled for surgery when she arrived at our hospital with a 13 cm solid mass and respiratory distress. The patient's liver profile was abnormal; she had ascites, pleural effusion and a severely worsened lung condition. The patient was planned for an exploratory laparotomy and debulking surgery after preoperative optimisation. To prevent the re-expansion pulmonary oedema (RPO) following the excision of the tumour, a volume-restricted postoperative ventilation strategy was planned. Following enhanced recovery after surgery (ERAS) protocol and specific anaesthetic measures, we successfully managed the anaesthesia in a case of teratoma syndrome with a large abdominal tumour with successful recovery and early discharge from hospital.
Self-Supervised Vision Transformers for Malware Detection

Malware detection plays a crucial role in cyber-security with the increase in malware growth and advancements in cyber-attacks. Previously unseen malware which is not determined by security vendors are often used in these attacks and it is becoming inevitable to find a solution that can self-learn from unlabeled sample data. This paper presents SHERLOCK, a self-supervision based deep learning model to detect malware based on the Vision Transformer (ViT) architecture. SHERLOCK is a novel malware detection method which learns unique features to differentiate malware from benign programs with the use of image-based binary representation. Experimental results using 1.2 million Android applications across a hierarchy of 47 types and 696 families, shows that self-supervised learning can achieve an accuracy of 97% for the binary classification of malware which is higher than existing state-of-the-art techniques. Our proposed model is also able to outperform state-of-the-art techniques for multi-class malware classification of types and family with macro-F1 score of.497 and.491 respectively.
What about Your Body Ornament? Experiences of Tattoo and Piercing among Italian Youths

Background: tattooing and piercing are increasingly common, especially among youths. However, several health complications may be associated with these practices if basic hygiene rules are not respected. This multicenter study was aimed at exploring tattoo and piercing experiences reported by a large sample of Italian undergraduate students through a public health perspective. Methods: tattooed and/or pierced students attending 12 Italian universities were asked to complete a web-based questionnaire regarding their body art experience. Results: out of 1472 respondents, 833 (56.6%) were tattooed and 1009 (68.5%) were pierced. The greatest proportion of tattooed students (93.9%) got her/his first tattoo in a tattoo studio, while most of the pierced were serviced in a jewelry store (48.0%). The pierced ones were less informed on health issues related to the procedure (56.0% versus 77.8% of tattooed p < 0.001), and tattooists were reportedly more attentive to hygiene rules (instrument sterilization 91.5% versus 79.1% of piercers, p < 0.001; use of disposable gloves 98.2% versus 71% of piercers, p < 0.001). Conclusions: educational interventions for both professionals and communities are needed to improve the awareness and the control of health risks related to body art throughout the Italian territory.
Light bullets in transparent dielectrics

This paper presents a retrospective analysis of the development of notions in nonlinear optics: from beam self-focusing and pulse filamentation to light bullets ??? wave packets extremely compressed in space and time during laser light propagation in the bulk of a transparent medium. We describe the state of the art in studies of mid-IR light bullets in condensed media and air.
Current progress in the biology of members of the Sporothrix schenckii complex following the genomic era

Sporotrichosis has been attributed for more than a century to one single etiological agent, Sporothrix schencki. Only eight years ago, it was described that, in fact, the disease is caused by several pathogenic cryptic species. The present review will focus on recent advances to understand the biology and virulence of epidemiologically relevant pathogenic species of the S. schenckii complex. The main subjects covered are the new clinical and epidemiological aspects including diagnostic and therapeutic challenges, the development of molecular tools, the genome database and the perspectives for study of virulence of emerging Sporothrix species.
Spodoptera frugiperda in Togo 5 years on: early impact of the invasion and future developments

The infestation of the fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) in Africa since 2016 has been a major threat to maize production. Previous studies in Togo and Ghana from 2016 to 2018 did not correlate FAW infestation to yield losses. Thus, the aim of this study which assesses the impact of FAW infestation by inspecting 150 maize farms throughout the five Agro-Ecological Zones (AEZs) of Togo for FAW plant damage, and third instar larvae were used to infest 10-day-old maize plants in netted plots under controlled conditions at an experiment station (Station d'Expérimentations Agronomiques de Lomé) in 2019 and 2020. As control plots at the experiment station, plots were both netted and treated with emamectin benzoate, simply netted, or open to natural infestation. The number of larvae, egg masses, percent damaged plants, and damage proportions of leaves and ears were scored until harvest. Infestations and damages on maize plant throughout Togo were similar between the two years but were higher in the southern part of the county (AEZ5). At the experiment station, the yield losses were significantly considerable and increased from 25% infestation. The losses were 0.37 t ha-1 for 25% infestation, 0.34 t ha-1 for 30%, 0.59 t ha-1 for the open plots, 0.70 t ha-1 for simple netted and 50% infestation, 1.03 t ha-1 for 75%, and 1.27 t ha-1 for 100% infestation. This current study suggested thorough inspection on maize farms to set off management practices from 25% of infestation.
In vitro antifungal synergy between amphiphilic aminoglycoside K20 and azoles against Candida species and Cryptococcus neoformans

Several azoles are widely used to treat human fungal infections. Increasing resistance to these azoles has prompted exploration of their synergistic antifungal activities when combined with other agents. The amphiphilic aminoglycoside, K20, was recently shown to inhibit filamentous fungi, yeasts and heterokonts, but not bacteria. In this study, in vitro synergistic growth inhibition by combinations of K20 and azoles (fluconazole, itraconazole, voriconazole, clotrimazole, or posaconazole) were examined against Candida species and Cryptococcus neoformans. Checkerboard microbroth dilution, time-kill curve, and disk diffusion assays revealed that K20 has synergistic inhibitory activities with all five azoles against C. albicans including azole-resistant C. albicans strains ATCC 64124 and ATCC 10231. Four (fluconazole, itraconazole, clotrimazole, posaconazole) and three (fluconazole, itraconazole, voriconazole) azoles were synergistically inhibitory with K20 against C. lusitaniae and C. tropicalis, respectively. Only posaconazole showed synergy with K20 against two Cryptococcus neoformans strains (90-26 and VR-54). Time-kill curves with azole-resistant C. albicans 64124 and azole-sensitive C. albicans MYA-2876 confirmed the K20-azole synergistic interactions with a ≥ 2 log10 decrease in colony-forming units (CFU)/ml compared with the corresponding azoles alone. These results suggest that combinations of K20 and azoles offer a possible strategy for developing therapies against candidiasis.