ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Food waste-Energy-Water-Emissions (FEWE) nexus in the food service sector: Comparing a restaurant meal from imported ingredients versus an imported ready-to-eat meal

The food service sector (FSS) is expanding due to the tendency of people to eat out. The growth of the FSS raises sustainability concerns about different activities across the life cycle of food systems. Analysing energy and material flows in the food systems enables decision-makers to prioritise procurement, kitchen management, and menu design. This study adopted Food waste-Energy-Water-Emissions (FEWE) nexus framework based on the life cycle assessment (LCA) methodology to evaluate the environmental impacts of two different systems of FSS. The effects of pasta cooked at Landmark Mandarin Oriental Hotel (LMO) in Hong Kong using imported ingredients were determined. Then the impacts of the pasta cooked at Artisan Food Company (ART) in Australia and shipped to Hong Kong as a ready-to-eat meal were found. Lastly, we discussed the FEWE nexus trade-offs among the impact results. The ART meal's indirect global warming potential (GWP) causes higher carbon emissions than the LMO meal. Also, the indirect cumulative energy demand (CED) of the ART and LMO meals showed no energy footprint difference. Similarly, indirect water consumption (WC) of the ART and LMO meals do not differ. The direct CED of the ART meal is higher than that of the LMO meal. While the ART meal has higher direct GWP than the LMO, the direct WC of the ART and LMO meals do not differ. Moreover, the indirect ART food waste (FW) is less than the LMO one, while direct FW for both ART and LMO meals is negligible. Conclusively, the localisation of meal preparation in Hong Kong results in better environmental performance than importing ready-to-eat meal.
Toward Edge-Assisted Video Content Intelligent Caching With Long Short-Term Memory Learning

Nowadays video content has contributed to the majority of Internet traffic, which brings great challenge to the network infrastructure. Fortunately, the emergence of edge computing has provided a promising way to reduce the video load on the network by caching contents closer to users.But caching replacement algorithm is essential for the cache efficiency considering the limited cache space under existing edge-assisted network architecture. To investigate the challenges and opportunities inside, we first measure the performance of five state-of-the-art caching algorithms based on three real-world datasets. Our observation shows that state-of-the-art caching replacement algorithms suffer from following weaknesses: 1) the rule-based replacement approachs (e.g., LFU,LRU) cannot adapt under different scenarios; 2) data-driven forecast approaches only work efficiently on specific scenarios or datasets, as the extracted features working on one dataset may not work on another one. Motivated by these observations and edge-assisted computation capacity, we then propose an edge-assisted intelligent caching replacement framework <italic>LSTM-C</italic> based on deep Long Short-Term Memory network, which contains two types of modules: 1) four basic modules manage the coordination among content requests, content replace, cache space, service management; 2) three learning-based modules enable the online deep learning to provide intelligent caching strategy. Supported by this design, LSTM-C learns the pattern of content popularity at long and short time scales as well as determines the cache replacement policy. Most important, LSTM-C represents the request pattern with built-in memory cells, thus requires no data pre-processing, pre-programmed model or additional information. Our experiment results show that LSTM-C outperforms state-of-the-art methods in cache hit rate on three real-traces of video requests. When the cache size is limited, LSTM-C outperforms baselines by on average respectively, which are fast enough for online operations.
Association investigations between ACE1 and ACE2 polymorphisms and severity of COVID-19 disease

Due to the unique affinity of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the angiotensin-converting enzyme 2 (ACE2) receptor in patients, the foremost recent evidence indicated that ACE1 and ACE2 polymorphisms could affect the susceptibility of individuals to SARS-CoV-2 infection and also the disease outcome. Here, we aimed to assess the possible association between two polymorphisms and the severity of disease in patients. In the present study, 146 patients with COVID-19 who were admitted to the Mazandaran University of Medical Sciences hospitals between March 2020 and July 2020 were enrolled in this case-control study. The patients were divided into four groups based on clinical symptoms and severity of the diseases (mild, moderate, severe, and critical). After DNA extraction, the ACE gene I/D polymorphism (rs4646994) and ACE2 gene polymorphism (rs2285666) were genotyped using Gap-PCR and PCR-RFLP techniques, respectively. Then, five samples from each obtained genotype were confirmed by Sanger sequencing technique. Data were analyzed with SAS software version 9.1 using appropriate statistical procedures. The ACE gene I/D polymorphism (rs4646994) genotypes were classified into three types: I/I, I/D, and D/D. Our finding indicated that the prevalence of ACE1 D/D genotype was significantly higher in severe and critical COVID-19 patients (P = 0.0016). Additionally, the analysis revealed a remarkable association between rs4646994 SNP and the HB and ESRI levels in patients (P < 0.05). Although the ACE2 rs2285666 SNP was not related to the severity of disease, this variant was significantly associated with ALT, ESRI, and P. These results provide preliminary evidence of a genetic association between the ACE-D/D genotype and the D allele of ACE1 genotype and the disease severity. Therefore, our findings might be useful for identifying the susceptible population groups for COVID-19 therapy.
On the Quasi-Saturation in State-of-the-Art Power MOSFETs

The quasi-saturation (QS) effect in a power MOSFET has been discovered several decades ago. As the field has evolved and the dimensions in power MOSFETs have changed from tens of micrometers to submicrometer levels, and the gate geometry has evolved from planar to trench, the origin and the effect of the QS need to be re-assessed. This letter first discusses the origin of the QS effect in the state-of-the-art power MOSFETs and subsequently analyses the phenomenon of majority carrier injection (or diffusion) and its contribution to the increased carrier concentration in the drift region, specific to quasi-saturation.
[Counter-Experts: Environment, Activism and the Regional Epistemologies of Social Movements]

With the demand for "counter-knowledge" in the social movements of the 1970s and 1980s, "counter-experts" became an integral part of politics. In the field of environmental activism, counter-experts were particularly well represented in regions and agglomerations with high levels of industrial pollution. This essay argues that awareness correlated with a mode of knowledge production that was typical for the environmental sciences in the twentieth century. The history of the environmental sciences throughout that period was shaped by regional epistemologies, often emerging in the context of large-scale infrastructural projects. Many counter-experts therefore had strong ties with the field of the environmental sciences. The article traces three influential counter-experts in the Frankfurt Main region by 1980: the pastor Kurt Oeser; scientific green activist Jutta Ditfurth; and the project of a "social natural science" related to the Darmstadt philosopher Gernot Böhme.
Convolutional Weighted Parametric Multichannel Wiener Filter for Reverberant Source Separation

In this letter, we address the problem of simultaneous separation and dereverberation of overlapped speech recorded in reverberant conditions. The majority of state-of-the-art techniques are tailored for either of the two problems, which for the joint task leads to sub-optimum performance or solutions which involve subsequent, cascade processing. In contrast, we propose a jointly optimum approach in which we formulate a single optimization criterion that minimizes variance of undesired signal components at the output of a convolutional filter, weighted with the desired speech variance, subject to a constraint which allows to control the amount of distortions in the estimated speech signal. We then derive a closed-form solution of the proposed convolutional weighted parametric multichannel Wiener (CW-PMW) filter which integrates linear-prediction based dereverberation and speech-distortion weighted Wiener filtering in a jointly optimum manner. The results of experiments performed using measured and simulated data indicate superior performance of the proposed approach in comparison with state-of-the-art, which includes sub-optimum cascades of optimum filters for individual tasks, as well as the recently presented jointly optimum, weighted power minimization distortionless response (WPD) beamformer.
Targeting human thymidylate synthase: Ensemble-based virtual screening for drug repositioning and the role of water

A drug repositioning computational approach was carried to search inhibitors for human thymidylate synthase. An ensemble-based virtual screening of FDA-approved drugs showed the drugs Imatinib, Lumacaftor and Naldemedine to be likely candidates for repurposing. The role of water in the drug-receptor interactions was revealed by the application of an extended AutoDock scoring function that included the water forcefield. The binding affinity scores when hydrated ligands were docked were improved in the drugs considered. Further binding free energy calculations based on the Molecular Mechanics Poisson-Boltzmann Surface Area method revealed that Imatinib, Lumacaftor and Naldemedine scored -130.7 ± 28.1, -210.6 ± 29.9 and -238.0 ± 25.4 kJ/mol, respectively, showing good binding affinity for the candidates considered. Overall, the analysis of the molecular dynamics trajectory of the receptor-drug complexes revealed stable structures for Imatinib, Lumacaftor and Naldemedine, for the entire simulation time.
Electromagnetic field diffraction of a paraboloidal mirror under oblique incidence

Asymptotic ray theory (ART) or Geometrical optics approximation shows singularity in the focal region of focusing systems. Maslov's method is a technique which overcomes the defect of asymptotic ray theory (ART). In this research work, electromagnetic field expressions for a paraboloidal mirror are derived in which incident electromagnetic field is considered to be oblique. In this work polarization of the incidence wave are studied under two cases, when the field is parallel and perpendicular to the assumed meridional plane of incidence. The procedure used to calculate the electromagnetic field in the focal region of paraboloidal mirror is Maslov's method. The numerical integration is performed for the integrals obtained by this technique in order to get information about intensity of field in focal region.
ECOLOGICAL INTEGRATION OF LARGE-SCALE LANDSCAPE OPERA FROM THE PERSPECTIVE OF ECOLOGICAL ART

The landscape live performance is a newly emerging form of performance in recent years. While gaining positive benefits in politics, economy and culture, the negative problems of ecological environment have also aroused widespread concern. Based on the principle of ecological art, this paper discusses the integration of large-scale landscape opera and environment. Therefore, the research results should establish the concept of sustainable development, through self-innovation, ecological awareness, return to the essence of art, and extend the industrial chain, so as to make it develop along a healthy and benign track.
Candidate List Reduction Based on the Analysis of Fingerprint Indexing Scores

This correspondence proposes new candidate list reduction criteria for fingerprint indexing approaches. The basic idea is that, given a query fingerprint, the initial set of scores produced by an indexer could contain useful information to reduce the candidate list. Novel reduction criteria have been proposed, and extensive experiments have been carried out over five publicly available benchmarks, using two state-of-the-art fingerprint indexing techniques. Although quite simple, the proposed criteria achieved remarkable results, allowing a substantial reduction of the candidate list: for instance, at 1% error rate, the average penetration rate of a state-of-the-art minutiae-based indexer decreases from 27% to 3.9% on FVC2000 DB2. The new reduction criteria are applicable to any indexing approach, since they only require a list of scores as input.
Estimation of dietary intake of 90Sr in Japan after the Fukushima Daiichi Nuclear Power Plant accident: market basket study, 2013-2018

Radionuclide contamination in foods has been a public concern in Japan after the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident. To estimate time and regional trends of daily intake and annual committed effective dose of strontium-90 (90Sr) after the accident, we analysed Market basket samples using a low background 2π gas-flow counter. Samples were collected from six regions, once a year from 2013 to 2018. There appeared to be little variation in estimated daily intake and annual committed effective dose of 90Sr across the time periods and regions. The estimated maximum annual committed effective dose of 90Sr was 0.00076 mSv/year, a value sufficiently lower than the intervention exemption level, 1 mSv/year, in foods in Japan. There was no noticeable difference between the range of estimated daily intake of 90Sr in this study compared with daily intake measured before the FDNPP accident. These results suggested that no obvious increase in dietary intake of 90Sr was observed after the FDNPP accident, and that the effects on commercial foods from 90Sr due to the FDNPP accident were negligible.
Western gray whale behavioral response to seismic surveys during their foraging season

Gray whales utilizing their foraging grounds off northeastern Sakhalin Island, Russia, have been increasingly exposed to anthropogenic activities related to oil and gas development over the past two decades. In 2015, four seismic vessels, contracted by two operators, conducted surveys near and within the gray whale feeding grounds. Mitigation and monitoring plans were developed prior to the survey and implemented in the field, with real-time data transfers to assist the implementation of measures aimed at minimizing impacts of acoustic exposure. This study examined the behavioral response of gray whales relative to vessel proximities and sounds generated during seismic exploration. Five shore-based teams monitored gray whale behavior from 1 June to 30 September using theodolite tracking and focal follow methodologies. Behavioral data were combined with acoustic and benthic information from studies conducted during the same period. A total of 1270 tracks (mean duration = 0.9 h) and 401 focal follows (1.1 h) were collected with gray whales exposed to sounds ranging from 59 to 172 dB re 1 μPa2 SPL. Mixed models were used to examine 13 movement and 10 respiration response variables relative to "natural," acoustic, and non-acoustic explanatory variables. Water depth and behavioral state were the largest predictors of gray whale movement and respiration patterns. As vessels approached whales with increasing seismic/vessel sound exposure levels and decreasing distances, several gray whale movement and respiration response variables significantly changed (increasing speed, directionality, surface time, respiration intervals, etc.). Although the mitigation measures employed could have reduced larger/long-term responses and sensitization to the seismic activities, this study illustrates that mitigation measures did not eliminate behavioral responses, at least in the short-term, of feeding gray whales to the activities.
Intravenous tryptophan administration attenuates cortisol secretion induced by intracerebroventricular injection of noradrenaline

This study was conducted to investigate the possibility of suppression of stress-induced cortisol (CORT) secretion by tryptophan (TRP) administration and to better understand its regulatory mechanisms by using a noradrenaline (NA) injection into the third ventricle (3V) as a stress model in cattle. A total of 25 Holstein steers with a cannula in the 3V were used. First, the increase in CORT secretion was observed following a NA injection into the 3V in a dose-dependent manner, verifying the appropriateness of this treatment as a stress model of CORT secretion (Experiment 1). The effect of prior-administration of TRP into peripheral blood with a dose that has been demonstrated to increase brain 5-hydroxytryptamine levels on the elevation of plasma CORT induced by NA or corticotropin-releasing hormone (CRH) was then examined (Experiment 2). The prior administration of TRP suppressed NA-induced, but not CRH-induced, CORT elevation. These results suggest that an increase in TRP absorption into peripheral blood could suppress the stress-induced CORT secretion in cattle via the attenuation of the stimulatory effect of NA on the hypothalamic CRH release.
Venous Thromboembolism Prophylaxis in Inflammatory Bowel Disease: A Two-year Retrospective Study of Patients Presenting With Inflammatory Bowel Disease to a Community Hospital

Objective We set out to determine the rate of pharmacological venous thromboembolism (VTE) prophylaxis among patients admitted with inflammatory bowel disease (IBD) and indirectly compare it to national trends. We also assessed the demographic and clinical correlates for non-prescription of pharmacologic VTE prophylaxis among IBD patients with and without a flare. Methods We extracted data from 123 patients admitted to our facility with IBD from September 2018 to August 2020 retrospectively. Out of this cohort, 26 patients were excluded and 96 were included in our analysis. Baseline characteristics were analyzed using descriptive statistics. Multiple logistic regression was used to evaluate the correlates of pharmacological VTE prophylaxis use in individuals with IBD and to analyze the predictors of VTE prophylaxis use in patients with IBD flares. Results Out of the 96 patients with IBD included in this study, 61 (63.5%) presented with an IBD flare, and among those with a flare, 26/61 (42.6%) received VTE prophylaxis. IBD patients aged ≥ 65 years and of Black race were less likely to be placed on pharmacological VTE prophylaxis (adjusted odds ratio (AOR) 0.20, 95% CI (0.06 - 0.70), p-value 0.012) and (AOR 0.16, 95% CI (0.05 - 0.50), p-value 0.002) respectively. Among those with a flare, the presence of bright red bleeding per rectum was associated with a low rate of pharmacologic VTE use (AOR 0.01, 95% CI (0.00 -1.78), p-value 0.001). Overall the rate of VTE prophylaxis use in the IBD patient cohort was 56.3% and this was irrespective of flare status. Conclusion Our study showed the low rate of pharmacologic VTE prophylaxis use in IBD patients at this center and this finding was in line with national trends. Interestingly age and the race of patients played a major role in the decision to provide pharmacological VTE prophylaxis but the reason for this finding was not explored by our study. A larger multi-center study is needed to further evaluate these relationships.
The impact of perceived and internalised stigma on clinical and functional recovery among people with mental illness

The present study aimed to develop and validate a conceptual model linking public and internalised stigma to recovery attitudes, processes and outcomes among people with mental illness. Specifically, we sought to examine whether perceptions of public stigma (i.e., perceived stigma) would affect experiences of internalised stigma (i.e., self-stigma) and thereby influence recovery attitudes (i.e., recovery orientation), recovery processes (i.e., service engagement) and recovery outcomes (i.e., clinical recovery and functional recovery). A total of 205 people with mental illness from Hong Kong, China, completed questionnaire measures on perceived stigma, self-stigma, recovery orientation, service engagement, clinical recovery and functional recovery. The associations among these variables were analysed using path analyses and bootstrap analyses. Path analyses showed that perceived stigma was related to greater self-stigma, which was, in turn, linked to lower recovery orientation and then lesser service engagement and ultimately poorer clinical recovery and functional recovery. Bootstrap analyses further demonstrated that perceived stigma had significant indirect effects on recovery orientation via self-stigma, on service engagement via self-stigma and recovery orientation and on clinical recovery and functional recovery via self-stigma, recovery orientation and service engagement. Theoretically, our findings reveal how public and internalised stigma may adversely affect recovery attitudes, processes and outcomes among people with mental illness. Practically, our findings point to the vital and urgent need to develop effective interventions to mitigate stigma and self-stigma at community and individual levels in order to reduce the deleterious impact of stigma on recovery.
Use of intraoperative coronary angiography to guide surgical intervention in coronary artery bypass graft surgery

Following coronary artery bypass graft surgery, graft patency is a major factor contributing to patient morbidity and mortality. There are several modalities available for assessing graft patency intra-op used by both the anesthesiologist and surgeon. However, these modalities have their own advantages and disadvantages which will be summarized in this case report. As illustrated by this case, angiography continues to be the gold standard for coronary anatomy assessment and can be performed easily using a portable digital fluoroscopic system.
Multi-Instance Deep Learning: Discover Discriminative Local Anatomies for Bodypart Recognition

In general image recognition problems, discriminative information often lies in local image patches. For example, most human identity information exists in the image patches containing human faces. The same situation stays in medical images as well. "Bodypart identity" of a transversal slice-which bodypart the slice comes from-is often indicated by local image information, e.g., a cardiac slice and an aorta arch slice are only differentiated by the mediastinum region. In this work, we design a multi-stage deep learning framework for image classification and apply it on bodypart recognition. Specifically, the proposed framework aims at: 1) discover the local regions that are discriminative and non-informative to the image classification problem, and 2) learn a image-level classifier based on these local regions. We achieve these two tasks by the two stages of learning scheme, respectively. In the pre-train stage, a convolutional neural network (CNN) is learned in a multi-instance learning fashion to extract the most discriminative and and non-informative local patches from the training slices. In the boosting stage, the pre-learned CNN is further boosted by these local patches for image classification. The CNN learned by exploiting the discriminative local appearances becomes more accurate than those learned from global image context. The key hallmark of our method is that it automatically discovers the discriminative and non-informative local patches through multi-instance deep learning. Thus, no manual annotation is required. Our method is validated on a synthetic dataset and a large scale CT dataset. It achieves better performances than state-of-the-art approaches, including the standard deep CNN.