ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Multiorientation scene text detection via coarse-to-fine supervision-based convolutional networks

Text detection in natural scenes has long been an open challenge and a lot of approaches have been presented, in which the deep learning-based methods have achieved state-of-the-art performance. However, most of them merely use coarse-level supervision information, limiting the detection effectiveness. We propose a deep method utilizing coarse-to-fine supervisions for multiorientation scene text detection. The coarse-to-fine supervisions are generated in three levels: coarse text region (TR), text central line, and fine character shape. With these multiple supervisions, the multiscale feature pyramids and deeply supervised nets are integrated in a unified architecture, and the corresponding convolutional kernels are learned jointly. An effective top-down pipeline is developed to obtain more precise text segmentation regions and their relationship from coarse TR. In addition, the proposed method can handle texts in multiple orientations and languages. Four public datasets, i.e., ICDAR2013, MSRA-TD500, USTB, and street view text dataset, are used to evaluate the performance of our proposed method. The experimental results show that our method achieves the state-of-the-art performance. (C) 2018 SPIE and IS&T
Comparison of efficacy, safety and satisfaction of latanoprost versus minoxidil, betamethasone and in combination in patients with alopecia areata: A blinded multiple group randomized controlled trial

Alopecia areata (AA), a polygenic and chronic autoimmune disease and there is no definitive cure. We aimed to evaluate latanoprost effects in patients with AA. In this controlled randomized double-blind clinical trial, we enrolled patients with AA randomly assigned to six groups of 18; Group 1 received latanoprost eye drops; group 2 minoxidil 5% solution; group 3 latanoprost eye drops and minoxidil 5% solution; group 4 betamethasone and minoxidil 5% solution; group 5 betamethasone solution and latanoprost eye drops; group 6 (the control group) betamethasone solution. The alopecia severity in patients before and after treatment was assessed by severity of alopecia tool (SALT). One hundred and eight patients, 50% male (mean age: 32.6 ± 10.4) were studied. The overall SALT score decreased in all. After 2 weeks, patients receiving betamethason-minoxidil and betamethason-latanoprost showed more decline in their SALT than other groups. In final, there was statistically significant difference among betamethasone-latanoprost group with minoxidil, betamethasone-minoxidil and betamethasone groups. Regrowth was higher in latanoprost and betamethasone-latanoprost groups than minoxidil. Topical latanoprost added to therapeutic efficacy of topical betamethason and minoxidil in treating patchy AA, suggesting it being beneficial and safe adjuvant therapy and add to efficacy of topical treatments without any adverse effects.
Highly fluorescent nickel based metal organic framework for enhanced sensing of Fe3+ and Cr2O72- ions

Heavy metal contamination has sparked widespread concern among the populace. The significant issues necessitate the creation of high-performance fluorescent pigments that can identify harmful elements in water. The present study deals with metal organic framework [MOF] based on nickel [Ni-BDC MOF]. The Ni-BDC MOF was prepared by facile solvothermal method using nickel nitrate hexahydrate and terephthalic acid ligand as precursors. The MOF was characterized by various techniques in order to examine the crystal, morphological, structural, composition, thermal and optical properties. The detailed characterizations revealed that the synthesized Ni-BDC MOF are well-crystalline with high purity and possessing 3D rhombohedral microcrystals with rough surface. The MOF demonstrate good luminescence performance and excellent water stability. According to the Stern Volmer plot, the tests set up under optimized conditions demonstrate a linear correlation between the fluorescence intensity and concentration of both ions, i.e. Fe3+, and Cr2O72- ions. The linear range and detection limit for Fe3+ and Cr2O72- were found to be 0-1.4 nM and 0.159 nM, and 0-1 nM and 0.120 nM, respectively. The mechanisms for the selective detection of cations and anions were also explored. The recyclability for the prepared MOF was checked up to five cycles which showed excellent stability with just a slight reduction in efficiency. The constructed sensor was also used to assess the presence of Fe3+ and Cr2O72- ions in actual water samples. The results of the different experiments revealed that the prepared MOF is a good material for detecting Fe3+ and Cr2O72- ions.
Predictive Set Point Modulation Charging of Autonomous Rail Transit Vehicles

Autonomous rail transit (ART) vehicle is a new type of urban rail transportation, which has good development prospects. It is powered by onboard supercapacitors, which are charged at midway stations. It requires short charging time and fast charging speed. Usually, multiple chargers are used in parallel for charging. However, this will cause an overshoot phenomenon during charging, and the overshoot of multiple chargers will be superimposed on the supercapacitor, affecting the stability and life of both supercapacitors and chargers. In this paper, we propose a predictive set point modulation charging method, which can reduce the system's overshoot and increase the reliability of the system. First, the state-space averaging method is used to establish the electronic physical model of the multicharger system. Secondly, a predictive set point modulation charging control method is designed, and the closed-loop model of the proposed charging system is developed using the buck diagram. The effectiveness of the proposed method is verified through extensive simulation and experiments. The experimental results show that compared with the classical design method, the proposed method can effectively suppress the current overshoot.
A brief morning rest period benefits cardiac repair in pressure overload hypertrophy and postmyocardial infarction

Rest has long been considered beneficial to patient healing; however, remarkably, there are no evidence-based experimental models determining how it benefits disease outcomes. Here, we created an experimental rest model in mice that briefly extends the morning rest period. We found in 2 major cardiovascular disease conditions (cardiac hypertrophy, myocardial infarction) that imposing a short, extended period of morning rest each day limited cardiac remodeling compared with controls. Mechanistically, rest mitigates autonomic-mediated hemodynamic stress on the cardiovascular system, relaxes myofilament contractility, and attenuates cardiac remodeling genes, consistent with the benefits on cardiac structure and function. These same rest-responsive gene pathways underlie the pathophysiology of many major human cardiovascular conditions, as demonstrated by interrogating open-source transcriptomic data; thus, patients with other conditions may also benefit from a morning rest period in a similar manner. Our findings implicate rest as a key driver of physiology, creating a potentially new field - as broad and important as diet, sleep, or exercise - and provide a strong rationale for investigation of rest-based therapy for major clinical diseases.
Copper-Catalyzed 1,2-Dicarbonylative Cyclization of Alkenes with Alkyl Bromides via Radical Cascade Process

Herein, we developed a new procedure on 1,2-dicarbonylative cyclization of 4-aryl-1-butenes with alkyl bromides. Using simple copper catalyst, two molecules of carbon monoxide were introduced into the double bond with the formation of four new C-C bonds and a new ring. Various α-tetralones and 2,3-dihydroquinolin-4-ones were formed in moderate to good yields.
Introducing Patents with Indirect Connection (PIC) for Establishing Patent Strategies

A patent system requires novelty and progressiveness so that new patents do not infringe on the rights of prior art. Patent investigation including a prior art search is essential to the process of commercialization of technology. In general, patent investigation has been conducted by experts based on their qualitative judgement. However, the number of patents has increased so fast that it has become difficult to handle the quantitative burdens of the search with a conventional approach. There have been previous studies dealing with patent investigation to find similar technologies. They had limitations as they did not utilize the citation relationship and similarity between patents in a comprehensive way. In addition, they could not properly reflect the sequential citation relationship of patents though this is effective in discovering similar patents. In this study, we propose an efficient methodology to discover similar technologies by comprehensively considering the similarity and citation relationship between patents. In particular, we intended to reflect the citation sequence and indirect citation relationship in the process of searching for similar patents. For this, we introduced the concept of "patents with indirect connections" (PICs) and devised an algorithm to efficiently detect patent pairs having such a relationship. The proposed methodology of this study contributes to preventing patent litigation in advance by discovering patents with such potential risks. It is expected that this method will provide patent applicants with the opportunity to establish appropriate strategies against competitors with similar technologies. In order to examine the practical applicability of the proposed method, Korean patents related to machine learning and deep learning were collected. As a result of the experiment, it was possible to identify 24 pairs of similar patents without a direct citation relationship and derive appropriate counter strategies.
Students' continuance intention to use MOOCs: empirical evidence from India

In recent years, there has been an increasing interest in understanding the Massive open online courses (MOOCs) due to its gaining popularity. Even though the number of online platforms and programs has grown during the COVID-19 pandemic, there is still a high rate of dropout and non-completion. In this work, the expectation-confirmation model is combined with MOOC features such as perceived openness, perceived reputation, and other factors i.e., perceived enjoyment, and perceived computer self-efficacy to investigate the learner's continued intention to use MOOC. A survey was undertaken and the data was collected from 383 students pursuing their degrees (undergraduate and post-graduate) in Karnataka state, India. The collected data were analyzed with structural equation modelling in Smart PLS 3. The study confirms a significant influence of confirmation and perceived usefulness on satisfaction, and direct significant influence of perceived computer self-efficacy, satisfaction, and perceived usefulness on continuance intention. Also, the results demonstrated the significant influence of confirmation on perceived enjoyment and usefulness and the effect of computer self-efficacy on usefulness. The findings in this study indicate that the MOOC platforms should focus on confirming learner expectations and the usefulness of courses to ensure student satisfaction and continuance of courses.
Relationships between paranoid thinking, self-esteem and the menstrual cycle

This study aimed to investigate whether paranoid experiences and levels of self-esteem fluctuate over the menstrual cycle and whether levels of self-esteem are lower when perceived persecution is felt to be deserved. Measures of anxiety, depression, persecution, deservedness and self-esteem were completed on-line by 278 women over their menstrual cycle. Responses were compared at the paramenstrual (3 days before and after menses onset) and mid-cycle phase. At the paramenstrual phase persecution, negative self-esteem, anxiety and depression were higher and positive self-esteem was lower than at mid-cycle. A greater proportion of women experienced persecution as deserved at the paramenstrual phase. This was associated with higher depression and negative self-esteem scores. Increased levels of deservedness significantly strengthened the relationship between persecution and negative, but not positive, self-esteem. These findings suggest that the paramenstrual phase is a time of vulnerability to increased paranoid experiences, an increased likelihood that feelings of persecution will feel deserved and lowered self-esteem. The findings support the view that interpersonal sensitivities may be key to menstrual cycle symptoms and have an impact on relationships. Further, the study illustrated that ideas developed for psychosis could make a valuable contribution to understanding and managing this aspect of menstruation-related distress.
Therapeutic Options for Brain Metastases in Gynecologic Cancers

Brain metastases (BM) are rare in gynecologic cancers. Overall BM confers a poor prognosis but other factors such as number of brain lesions, patient age, the presence of extracranial metastasis, the Karnofsky Performance Status (KPS) score, and the type of primary cancer also impact prognosis. Taking a patient's whole picture into perspective is crucial in deciding the appropriate management strategy. The management of BM requires an interdisciplinary approach that frequently includes oncology, neurosurgery, radiation oncology and palliative care. Treatment includes both direct targeted therapies to the lesion(s) as well as management of the neurologic side effects caused by mass effect. There is limited evidence of when screening for BM in the gynecology oncology patient is warranted but it is recommended that any cancer patient with new focal neurologic deficit or increasing headaches should be evaluated. The primary imaging modality for detection of BM is MRI, but other imaging modalities such as CT and PET scan can be used for certain scenarios. New advances in radiation techniques, improved imaging modalities, and systemic therapies are helping to discover BM earlier and provide treatments with less detrimental side effects.
Erythema induratum of bazin - Skin lesions with pyrexia of unknown origin undiagnosed for 4 years

Erythema induratum of Bazin is characterized by chronic, tender, erythematous, indurated subcutaneous nodules on the lower extremities caused by tuberculin hypersensitivity. A 21-year-old woman presented with recurrent episodes of multiple erythematous scaly lesions over both lower limbs below the knee and low-grade fever for 4 years. She was treated from various outside hospitals with multiple courses of antibiotics and nonsteroidal anti-inflammatory drugs without improvement. The histopathology of the skin lesion was suggestive of erythema induratum. She had complete resolution of her skin lesions and fever following 6 months of treatment with antitubercular drugs. A delay in the diagnosis of rare presentations of tuberculosis can result in the administration of ineffective and potentially damaging treatments.
Effect of dietary replacement of fish meal by poultry by-product meal on the growth performance, immunity, and intestinal health of juvenile red swamp crayfish, procambarus clarkia

The present study was conducted to investigate the dietary replacement of fish meal with poultry by-product meal (PBM) on the growth performance, immunity, antioxidant properties, and intestinal health of red swamp crayfish (Procambarus clarkia). A diet containing 20% fish meal (FM) and complex plant ingredients as the main protein resources was set as the FM group (crude protein 32%, crude lipid 6%). Four diets replacing 25%, 50%, 75%, and 100% fish meal of the FM diet with PBM were set as the PBM25, PBM50, PBM75, and PBM100 groups, respectively. Compared to the FM group, the PBM100 diet significantly decreased growth performance and feed utilization of crayfish, while markedly increasing the activity of serum aspartate aminotransferase. The immune response was depressed in crayfish fed the PBM100 diet as the activities of serum lysozyme and phenoloxidase, gene expression of anti-lipopolysaccharide factors (alf), cyclophilin A (cypa), crustin, and hemocyanin-1 (hep-1) in hepatopancreas were remarkably decreased. The activities of antioxidases and expression of antioxidant-relevant genes in the hepatopancreas were not influenced by PBM inclusion. Crayfish fed different diets exhibited no obvious symptoms of enteritis, but the PBM100 diet destructed intestinal morphology by significantly decreasing the average length of longitudinal ridges. The α-diversity and overall community structure were not significantly influenced but variations were found in the relative abundance of some genera by PBM inclusion. In summary, CAP could successfully replace 75% dietary FM in a basal diet containing 20% fish meal, while higher CAP level compromised growth performance, immunity, and intestinal histology of crayfish.
Catch Effectiveness Revealed by Site-Related Differences in Capture-Mark-Recapture Methods: A Butterfly Metapopulation Study

Understanding metapopulation structures is very important in the context of ecological studies and conservation. Crucial in this respect are the abundances of both the whole metapopulation and its constituent subpopulations. In recent decades, capture-mark-recapture studies have been considered the most reliable means of calculating such abundances. In butterfly studies, individual insects are usually caught with an entomological net. But the effectiveness of this method can vary for a number of reasons: differences between fieldworkers, in time, between sites etc. This article analyses catch effectiveness data with respect to two subpopulations of the Apollo butterfly (Parnassius apollo) metapopulation in the Pieniny National Park (Polish Carpathians). The results show that this parameter varied significantly between sites, probably because of differences in microrelief and plant cover. In addition, a method is proposed that will include information on catch effectiveness for estimating the sizes of particular subpopulations and will help to elucidate the structure of the entire metapopulation.
Hi-Net: Hybrid-Fusion Network for Multi-Modal MR Image Synthesis

Magnetic resonance imaging (MRI) is a widely used neuroimaging technique that can provide images of different contrasts (i.e., modalities). Fusing this multi-modal data has proven particularly effective for boosting model performance in many tasks. However, due to poor data quality and frequent patient dropout, collecting all modalities for every patient remains a challenge. Medical image synthesis has been proposed as an effective solution, where any missing modalities are synthesized from the existing ones. In this paper, we propose a novel Hybrid-fusion Network (Hi-Net) for multi-modal MR image synthesis, which learns a mapping from multi-modal source images (i.e., existing modalities) to target images (i.e., missing modalities). In our Hi-Net, a modality-specific network is utilized to learn representations for each individual modality, and a fusion network is employed to learn the common latent representation of multi-modal data. Then, a multi-modal synthesis network is designed to densely combine the latent representation with hierarchical features from each modality, acting as a generator to synthesize the target images. Moreover, a layer-wise multi-modal fusion strategy effectively exploits the correlations among multiple modalities, where a Mixed Fusion Block (MFB) is proposed to adaptively weight different fusion strategies. Extensive experiments demonstrate the proposed model outperforms other state-of-the-art medical image synthesis methods.
Recent advances in high performance conducting solid polymer electrolytes for lithium-ion batteries

Lithium-ion batteries (LIBs) as an important energy storage technology have found more and more applications in electric vehicles, electronic devices as well as grid energy storage systems. However, due to the safety issues from the flammability of combustible organic liquid electrolytes, recently solid polymer electrolytes (SPEs) have attracted more interest. Conventional SPEs are dual-ion conductors where both anions and cations possess slightly free movement and favor the concentration polarization phenomena, which may reduce their performances and lifetime. To overcome these issues, the conducting solid polymer electrolytes (CSPEs) are developed where the anions are linked via covalent bonds to the polymeric and inorganic backbones or anion acceptors, which may greatly accelerate the transportation of lithium ions and increase their lithium-ion transference number (LTN) and ionic conductivity as well as reduce the formation of concentration polarization and Li dendrite growth. Herein, a comprehensive overview of the latest development in CSPEs for LIBs is described, which emphasizes the correlations among their synthetic strategies, structures, and electrochemical performances. Finally, the state of the art, future perspectives, and core challenges are provided for designing the next generation of CSPEs in high performance LIBs.
GROUPS-NET: Group meetings aware routing in multi-hop D2D networks

Device-to-device (D2D) communication will allow direct transmission between nearby mobile devices in the next generation cellular networks. A fundamental problem in multi-hop D2D networks is the design of forwarding algorithms that achieve, at the same time, high delivery ratio and low network overhead. In this work, we study group meetings' properties by looking at their structure and regularity with the goal of applying such knowledge in the design of a forwarding algorithm for D2D multi-hop networks. We introduce a forwarding protocol, namely GROUPS-NET, which is aware of social group meetings and their evolution over time. Our algorithm is parameter-calibration free and does not require any knowledge about the social network structure of the system. In particular, different from the state of the art algorithms, GROUPS-NET does not need communities' detection, which is a complex and expensive task. We validate our algorithm by using different publicly available data sources. In real-world large scale scenarios, our algorithm achieves approximately the same delivery ratio of the state-of-the-art solution with 40% less network overhead. (C) 2017 Elsevier B.V. All rights reserved.
Power Electronic Converters in Electric Aircraft: Current Status, Challenges, and Emerging Technologies

The electric revolution is underway in the transportation sector, and the aviation industry is poised to embrace fundamental disruption. Moving to electric aircraft brings undeniable benefits in terms of environmental impact, cost savings, maintenance, noise pollution, and safety. Nevertheless, several technical challenges are yet to be overcome to build electric airplanes that meet public needs while gaining acceptance and trust. From urban air mobility to long-haul flight applications, hundreds of projects are under research to push toward more electrification. At the heart of each aircraft architecture, power electronics plays a crucial role in the new era of transportation. This article aims to provide a comprehensive analysis of state-of-the-art power electronics in electric aircraft. A review of the current status of aircraft electrification will be provided, and technology surveys of power electronic converters will be detailed. Challenges for forthcoming power electronics in response to the future trends of the electrical network will be explained. Finally, emerging technologies regarding wide bandgap devices, advanced topologies and control, thermal management, passive components, and system integration will be discussed.