Huge Amount
Recently Published Documents





2022 ◽  
Vol 23 (2) ◽  
pp. 890
Kanyakorn Riewruja ◽  
Suphattra Phakham ◽  
Patlapa Sompolpong ◽  
Rangsima Reantragoon ◽  
Aree Tanavalee ◽  

Osteoarthritis (OA) is a degenerative joint disease leading to joint pain and stiffness. Due to lack of effective treatments, physical and psychological disabilities caused by OA have a detrimental impact on the patient’s quality of life. Emerging evidence suggests that intra-articular injection of platelet-rich plasma (PRP) may provide favorable results since PRP comprises not only a high level of platelets but also a huge amount of cytokines, chemokines, and growth factors. However, the precise mechanism and standardization method remain uncertain. This study aimed to examine cytokine profiling in both PRP and platelet-poor plasma (PPP) of knee OA patients and to determine the effects of PRP on OA chondrocytes and knee OA patients. PRP contained a wide variety of cytokines, chemokines, growth factors, and autologous intra-articular PRP injection resulted in favorable outcomes in knee OA patients. Significant increases in levels of IL-1, IL-2, IL-7, IL-8, IL-9, IL-12, TNF-α, IL-17, PDGF-BB, bFGF, and MIP-1β were detected in PRP compared to PPP (p < 0.001). An in vitro study showed a marked increase in proliferation in OA chondrocytes cultured with PRP, compared to PPP and fetal bovine serum (p < 0.001). In a clinical study, knee OA patients treated with PRP showed improvement of physical function and pain, assessed by physical performance, Western Ontario and McMaster Universities Arthritis Index and visual analog scale. Our findings from both in vitro and clinical studies suggest that intra-articular PRP injection in knee OA patients may be a potential therapeutic strategy for alleviating knee pain and delaying the need for surgery.

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Yue Liu ◽  
Junqi Ma ◽  
Xingzhen Tao ◽  
Jingyun Liao ◽  
Tao Wang ◽  

In the era of digital manufacturing, huge amount of image data generated by manufacturing systems cannot be instantly handled to obtain valuable information due to the limitations (e.g., time) of traditional techniques of image processing. In this paper, we propose a novel self-supervised self-attention learning framework—TriLFrame for image representation learning. The TriLFrame is based on the hybrid architecture of Convolutional Network and Transformer. Experiments show that TriLFrame outperforms state-of-the-art self-supervised methods on the ImageNet dataset and achieves competitive performances when transferring learned features on ImageNet to other classification tasks. Moreover, TriLFrame verifies the proposed hybrid architecture, which combines the powerful local convolutional operation and the long-range nonlocal self-attention operation and works effectively in image representation learning tasks.

Critical Care ◽  
2022 ◽  
Vol 26 (1) ◽  
Yunjoo Im ◽  
Danbee Kang ◽  
Ryoung-Eun Ko ◽  
Yeon Joo Lee ◽  
Sung Yoon Lim ◽  

Abstract Background Timely administration of antibiotics is one of the most important interventions in reducing mortality in sepsis. However, administering antibiotics within a strict time threshold in all patients suspected with sepsis will require huge amount of effort and resources and may increase the risk of unintentional exposure to broad-spectrum antibiotics in patients without infection with its consequences. Thus, controversy still exists on whether clinicians should target different time-to-antibiotics thresholds for patients with sepsis versus septic shock. Methods This study analyzed prospectively collected data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Adjusted odds ratios (ORs) were compared for in-hospital mortality of patients who had received antibiotics within 1 h to that of those who did not. Spline regression models were used to assess the association of time-to-antibiotics as continuous variables and increasing risk of in-hospital mortality. The differences in the association between time-to-antibiotics and in-hospital mortality were assessed according to the presence of septic shock. Results Overall, 3035 patients were included in the analysis. Among them, 601 (19.8%) presented with septic shock, and 774 (25.5%) died. The adjusted OR for in-hospital mortality of patients whose time-to-antibiotics was within 1 h was 0.78 (95% confidence interval [CI] 0.61–0.99; p = 0.046). The adjusted OR for in-hospital mortality was 0.66 (95% CI 0.44–0.99; p = 0.049) and statistically significant in patients with septic shock, whereas it was 0.85 (95% CI 0.64–1.15; p = 0.300) in patients with sepsis but without shock. Among patients who received antibiotics within 3 h, those with septic shock showed 35% (p = 0.042) increased risk of mortality for every 1-h delay in antibiotics, but no such trend was observed in patients without shock. Conclusion Timely administration of antibiotics improved outcomes in patients with septic shock; however, the association between early antibiotic administration and outcome was not as clear in patients with sepsis without shock.

2022 ◽  
Vol 10 (1) ◽  
pp. 74
Ioannis Tagarakis ◽  
Georgios Tagarakis

Aim. To investigate the contribution of the Hellenic Red Cross to the Greek Society during the first five and more severe years (2010-2014) of the profound financial crisis in Greece. Material And Methods. We retrospectively investigated the actions and contribution of the Hellenic Red Cross for the aforementioned five-year period. The research material was accumulated by research in the Internet, the archives, and the official webpage of the Hellenic Red Cross (Google, official web page of the ICRC and IFRC), from the Hellenic Ministry of Health and the Hellenic Ministry of Immigration and Asylum. Results. A huge amount of over 247 actions were detected for the research period. More than 17,708 people were examined and treated from the specialized medical personnel of the Hellenic Red Cross and 3,266 individuals were trained in basic first aid and hygiene. The final amount of 297,757€ were donated and 5,880 welfare packages were delivered. Conclusions. The current study has concluded that the contribution of the Hellenic Red Cross to the Greek society during the most severe phase of the recent financial crisis was outstanding and consists an example for any other Non-Governmental, Non for Profit Organizations in the future.

Shuyao Tian ◽  
Zhen Zhao ◽  
Tao Hou ◽  
Liancheng Zhang

In the hyperspectral imaging device, the sensor detects the reflection or radiation intensity of the target at hundreds of different wavelengths, thus forming a spectral image composed of hundreds of continuous bands. The traditional processing method of sampling first and then compressing not only cannot fundamentally solve the problem of huge amount of data, but also causes waste of resources. To solve this problem, a spectral image reconstruction method based on compressed sampling in spatial domain and transform coding in spectral domain is designed by using the sparsity of single-band two-dimensional image and the spectral redundancy of spatial coded data. Based on Bayesian theory, a compressed sensing measurement matrix of adaptive projection is proposed. Combining these two algorithms, an adaptive Grouplet-FBCS algorithm is constructed to reconstruct the image using smooth projection Landweber. Experimental results show that, compared with existing image block compression sensing algorithms, this algorithm can significantly improve the quality of image signal reconstruction.

2022 ◽  
Vol 22 (1) ◽  
Saskia Maria De Gani ◽  
Fabian Marc Pascal Berger ◽  
Elena Guggiari ◽  
Rebecca Jaks

Abstract Background COVID-19 has developed into a worldwide pandemic which was accompanied by an «infodemic» consisting of much false and misleading information. To cope with these new challenges, health literacy plays an essential role. The aim of this paper is to present the findings of a trend study in Switzerland on corona-specific health literacy, the use of and trust in information sources during the COVID-19 pandemic, and their relationships. Methods Three online surveys each with approximately 1′020 individuals living in the German-speaking part of Switzerland (age ≥ 18 years) were conducted at different timepoints during the COVID-19 pandemic, namely spring, fall and winter 2020. For the assessment of corona-specific health literacy, a specifically developed instrument (HLS-COVID-Q22) was used. Descriptive, bivariate, and multivariate data analyses have been conducted. Results In general, a majority of the Swiss-German population reported sufficient corona-specific health literacy levels which increased during the pandemic: 54.6% participants in spring, 62.4% in fall and 63.3% in winter 2020 had sufficient corona-specific health literacy. Greatest difficulties concerned the appraisal of health information on the coronavirus. The most used information sources were television (used by 73.3% in spring, 70% in fall and 72.3% in winter) and the internet (used by 64.1, 64.8 and 66.5%). Although health professionals, health authorities and the info-hotline were rarely mentioned as sources for information on the coronavirus, respondents had greatest trust in them. On the other hand, social media were considered as the least trustworthy information sources. Respondents generally reporting more trust in the various information sources, tended to have higher corona-specific health literacy levels. Conclusions Sufficient health literacy is an essential prerequisite for finding, understanding, appraising, and applying health recommendations, particularly in a situation where there is a rapid spread of a huge amount of information. The population should be supported in their capability in appraising the received information and in assessing the trustworthiness of different information sources.

2022 ◽  
Ying Zhao ◽  
Jinjun Chen

Huge amount of unstructured data including image, video, audio, and text are ubiquitously generated and shared, it is a challenge to protect sensitive personal information in them, such as human faces, voiceprints, and authorships. Differential privacy is the standard privacy protection technology that provides rigorous privacy guarantees for various data. This survey summarizes and analyzes differential privacy solutions to protect unstructured data content before they are shared with untrusted parties. These differential privacy methods obfuscate unstructured data after they are represented with vectors, and then reconstruct them with obfuscated vectors. We summarize specific privacy models and mechanisms together with possible challenges in them. We also conclude their privacy guarantees against AI attacks and utility losses. Finally, we discuss several possible directions for future research.

Shrinidhi Kanchi ◽  
Alain Pagani ◽  
Hamam Mokayed ◽  
Marcus Liwicki ◽  
Didier Stricker ◽  

Document classification is one of the most critical steps in the document analysis pipeline. There are two types of approaches for document classification, known as image-based and multimodal approaches. The image-based document classification approaches are solely based on the inherent visual cues of the document images. In contrast, the multimodal approach co-learns the visual and textual features, and it has proved to be more effective. Nonetheless, these approaches require a huge amount of data. This paper presents a novel approach for document classification that works with a small amount of data and outperforms other approaches. The proposed approach incorporates a hierarchical attention network(HAN) for the textual stream and the EfficientNet-B0 for the image stream. The hierarchical attention network in the textual stream uses the dynamic word embedding through fine-tuned BERT. HAN incorporates both the word level and sentence level features. While the earlier approaches rely on training on a large corpus (RVL-CDIP), we show that our approach works with a small amount of data (Tobacco-3482). To this end, we trained the neural network at Tobacco-3428 from scratch. Thereby, we outperform state-of-the-art by obtaining an accuracy of 90.3%. This results in a relative error reduction rate of 7.9%.

Suresh K

We are on a planet that orbits the Sun which emits a huge amount of energy. The climate we experience is a result of an energy gradient across Earth and an imbalance in energy across the world due to axial tilt of Earth rotation.

2022 ◽  
Iacopo Bianchi ◽  
Archimede Forcellese ◽  
Michela Simoncini ◽  
Alessio Vita ◽  
Vincenzo Castorani ◽  

Abstract Toe caps are fundamental components of safety footwear used to prevent injuries which can be caused by falling objects. They can be realized by exploiting different materials (metal, composites and plastics) and manufacturing processes (stamping, injection molding, compression molding, etc.). However, they have always to fulfill the stringent requirements of safety regulations. In addition, in order to guarantee an ergonomic use, they must be as light as possible. It is estimated that at least 300 million pairs of safety footwear, with 600 million of toe caps, end up in landfill or are incinerated every year. This huge amount of wastes generates a relevant environmental impact, mainly attributable to toe caps manufacturing. In this context, it is important to develop new solutions which minimize the environmental impacts of toe caps manufacturing. Among others, the reuse of carbon fiber prepreg scraps has been recognized as a valid method to produce effective toe caps. In this paper, a detailed analysis of the environmental impacts associated to toe caps realized with reclaimed prepreg scraps has been conducted exploiting the Life Cycle Assessment methodology. The results have been compared to those obtained by analyzing toe caps realized in steel, aluminum, polycarbonate and glass fiber composite. Results demonstrate that the reclaim process for carbon fiber prepreg scraps can be a valid circular economy model to produce more sustainable toe caps for safety footwear.

Sign in / Sign up

Export Citation Format

Share Document