Miracle-dz/UniFAR-FTUs huggingface dataset:
A Review of Advancements in Nasal Airway Measurement

Medical therapies and operative techniques for intra-nasal disease are constantly evolving; it is therefore imperative that outcomes from treatments and operative techniques can be objectively measured to ensure surgical efficacy. Investigations that measure the nasal airway can help to guide the management of sino-nasal diseases, which can subsequently have a significant impact on patients’ quality of life. Subjective methods of measurement include; anterior rhinoscopy, rigid nasendoscopy, VAS score and SNOT-22. Objective measures include; nasal peak flow testing, acoustic rhinometry, anterior/posterior rhinomanometry and imaging studies. Unfortunately, many objective measurement techniques correlate poorly with patients’ perceptions of disease severity, which questions the clinical relevance of these techniques. Robust, objective methods for measuring the nasal airway may help to guide future treatments, and should ideally correlate with patients’ symptoms to truly tackle the burden of nasal disease.
Co-registration of CT-SPECT images for tumor localization and dosimetry

Objectives Co-registration of SPECT and CT images may substantially improve tumor diagnosis by combining the functional information from scintigraphic images with the anatomical localization obtainable from CT images. Additionally, when CT-based attenuation maps are used in attenuation and scatter corrections, quantitative analysis of the data can help radiotherapy planning by providing accurate dosimetry for tumors and critical organs. Since CT and SPECT are usually performed on different days and using separate imaging systems, they clearly require co-registration. However, even if the scans are done on a combined SPECT/CT camera substantial image misalignments have been reported due to patient movement, therefore these images may also need to be co-registered. Co-registration however poses a major challenge, especially in high target-to-background images where tumors are well visible but almost none of the other body elements, providing no landmarks for registration. This situation would be much improved if anatomical markers, such as bone structures that are clearly visible in CT, could be used in co-registration. Methods In order to facilitate co-registration our method proposes an injection of bone radiotracer simultaneously with a tumor agent. This approach not only helps co-registration but may additionally diagnose potential metastases. Our automatic co-registration method uses mutual information as the registration criterion. To improve the robustness and accuracy of the algorithm, a multi-resolution approach is used in which registration is performed in a coarse-to-fine manner. During registration, the metric value is optimized over the parameter space defined by the translation parameters using a gradient-descent minimization scheme. The algorithm was tested on clinical data corresponding to pelvic and thoracic CT and SPECT-bone studies. Results Validation was done by visual inspection of 2D and 3D images and by observing the convergence in the similarity metric and the transformation parameters. Additionally, the effect of initial misalignment of the paired volumes and the reproducibility of the registration were evaluated. In all studies, registration with multi-resolution converged close to a final alignment. Initial misalignments of up to 50mm in the X and Y-axes, and 10mm in the Z-axis resulted in 61 of 66 successful registrations for the pelvic and 54 of 66 for the thoracic studies. The translation errors were 0.712mm±0.313mm and 1.312mm±0.623mm, respectively. The average computation time (on a 3.0GHz PC) was < 4 minutes for the entire registration procedure. Conclusion An automatic SPECT-CT co-registration method based on bone tomoscintigraphy has been developed and validated.
Shared attention reflected in EEG, electrodermal activity and heart rate

Monitoring directed auditory attention in groups can be helpful in a range of contexts. Concurrent change in physiological variables across multiple listeners (physiological synchrony – PS) may be a suitable marker of attentional focus as caused by shared affective or cognitive processes. We here determine PS for EEG (electroencephalography), EDA (electrodermal activity) and heart rate in participants who were instructed to either attend to an audiobook (n = 13) or to interspersed auditory events (n = 13) such as emotional sounds, and beeps that attending participants needed to keep track of. Even though all participants heard the exact same audio track, for both EEG and EDA, PS was higher for participants linked to participants in their own attentional group than to participants in the other attentional group. No such effect was found in heart rate. For a single individual, EEG PS allowed attribution to the correct attentional group in 85% of the cases, for EDA this was 81%. Hearing is not the same as attending - our results are promising for monitoring group affective and cognitive processes and how an individual relates to that. Copyright © 2019 for this paper by its authors.
Research of Simulation of Creative Stage Scene Based on the 3DGans Technology

Aiming to the feature of the modern stage scenery, combined with 3DGANs technology, we make research into the creation of creative stage scenes to rapidly display problem scene design, reduce the cost of stage design and the data error of virtual and actual simulated eﬀect of the stage. We improve the data of the creative stage scene at the beginning of the design to increase eﬃciency of the rehearsal stage to enable the simulation scene more intuitive to the displaying of the stage scene and provide the basis for dynamic management of the stage. In this paper, simulation of virtual reality stage scene will be realized through 3DGANs technology. Firstly, the stage data will be extracted and the data of the creative stage scene will be modiﬁed. Secondly, the data of the registration of 3D surface image data on the creative scene in the data will be modiﬁed by using ge-netic algorithm. Finally, the simulation experiments will be conducted by using 3DGANs technology to generate creative stage scenes. The results indicated that simulation of the creative stage scene generated by 3DGANs technology would synchronize with the real-time stage eﬀect in which multi-thread processing can improve processor utilization, shorten the reading time of the video image data, eﬀectively reduce the switching time be-tween diﬀerent tasks, improve the amount of the amount of throughput and concurrency system and to oﬀer a key support for virtual simulation and dynamic management of stage creative scene based on the 3DGANs technology.
Progress in Microbes and Molecular Biology Genomic analysis o f severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains isolated in Malaysia

: Using seven complete genomes of human SARS-CoV-2 (retrieved from GISAID) isolated in Malaysia for phylogenetic tree construction, the current study showed that these strains formed four distinct clades when compared with other representative strains from Asia, Europe and US. In light of that, the genome sequences of these strains isolated in Malaysia suggested that there is currently more than one “ type ” ”of strain within the country. Complementing with epidemiological and experimental studies, these findings allow better understanding the prevalence of certain types in Malaysia and permits further in-depth studies on the virulence and pathogenic mechanisms of these strains which is particularly critical to speed up the development of effective treatment regime.
Models of forecasting destructive influence risks for information processes in management systems

Introduction: One of the side effects of introducing modern information technologies in the management of economic, social,organizational and technical systems is the stronger dependence of the management quality on intentional or accidental destructiveinfluences which violate the integrity, confidentiality and availability of the information used. This determines the relevanceof developing appropriate information security systems. The substantiation of the development of such systems requires solvingthe problems of comparative assessment of the destructive impact risks and the cost of their prevention. Purpose: Predicting thedanger of a destructive impact on information processes in control systems. Method: The prediction is based on representingthe destructive effects in the form of a random sequence of events which lead to disruptions in the information processes. Theconsequences of failures are also represented by certain random variables. Results: Methodical approaches are proposed in orderto build models for predicting temporal and volumetric characteristics of damage from destructive influences on information processesin the management of economic, social, organizational and technical systems. In these models, we suggest to assess thedanger of destructive impacts by the probability of the onset of a destructive event at a certain time moment, and by the amountof damage caused by it. The basis for the construction of prediction models is the presentation of damage indicators in the formof step functions of time. The constructive representation of these functions is based on the conditional deterministic approach.The completeness of a priori information usage in determining specific parameters of the damage functions is ensured by applyingthe maximum uncertainty principle. The measure for the uncertainty is entropy. The conditional deterministic approachfor higher uncertainty levels was developed in a stochastic approach. On its basis, classes of stochastic models were proposed,corresponding to various information situations. These models allow you to estimate not only the expected values of damageindicators due to the failure in taking measures to ensure information security while managing targeted systems, but also theirprobabilistic characteristics. Practical relevance: The proposed approaches are the basis for the creation of particular models andtechniques in the interests of well substantiated decisions on the formation of the structure of the organization and managementof information security subsystems.
Identification of Soybean Leaf Spot Diseases using Deep Convolutional Neural Networks

— In this paper, we designed a Deep Convolutional Neural Network based on LeNet to perform soybean leaf spot disease recognition and classification using affected areas of disease spots. The affected areas of disease spots were segmented from the leaves images using the Unsupervised fuzzy clustering algorithm. The proposed Deep Convolutional Neural Network model achieved a testing accuracy of 89.84%, and poor per class recognition results in 1378 images misclassified, and 1271 images correct classified. TheVGG16 achieved the best performance reaching a 93.54% success rate, and better per class recognition results in 1245 images misclassified, and 1404 images correct classified.
How does Corporate Social Responsibility influence Export Performance

This paper argues that corporate social responsibility (CSR) may contribute to product differentiation in export markets and thus improve export performance. Drawing on the extant literature on export performance and corporate social responsibility, we formulate several hypotheses relating different kinds of product differentiation, such as differentiation by innovation, quality and CSR, to export performance. We test our arguments by observing a period of decreasing export competitiveness in a leading emerging economy (Brazil). Using a large-scale survey design with 252 questionnaires completed by medium and large sized Brazilian exporters, we used structural equations modeling to test our hypotheses. The results suggest that CSR product differentiation predicts export performance better than product quality differentiation and almost as well as product innovation differentiation. Multi-group analysis further revealed that the positive and significant effect of CSR product differentiation on export performance is likely to be contingent on the number of countries targeted (diversification). Our study contributes to literature on export performance and CSR by introducing an important explanatory variable of firm performance. Based on our results, we formulate several recommendations for export management.
The Opioid Crisis: A Contextual Framework and Call for Systems Science Research

a Harvard Medical School, Harvard University, Boston, MA b Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA c Grayken Center for Addiction, Boston Medical Center, Boston, MA d MIT Sloan School of Management, Boston, MA e T.H. Chan School of Public Health, Harvard University, Boston, MA f Harvard Kennedy School, Harvard University, Cambridge, MA g Division of Alcohol and Drug Abuse, McLean Hospital, Belmont, MA
Faculty Beliefs about the Nature of Intelligence

Educators shape the learning experiences of students in the classroom. Their views on intelligence influence the beliefs students have about their own abilities to learn. Astin (2016) cautioned, "The faculty culture regards smartness in an almost reverential fashion" (p. 4). Research on academic mindsets has focused mainly on secondary education (e.g., Dweck, 2016; Yeager & Dweck, 2012). There is a gap in the literature about educator views about intelligence in higher education. The purpose of this study was to measure the beliefs that faculty from various academic disciplines hold about the nature of their own intelligence and the intelligence of their students. Faculty at one land grant institution participated in an eight-term Mindset survey. Position was the only statistically significant demographic factor.
Causality, prediction and improvements that (don’t) add up

A recent Dagstuhl workshop focused on the problem of performance prediction in IR and related fields and formulated a mid-term research program [1]. As a core problem, the development of appropriate models for predicting performance was identified. In this paper, we want to show the relationship of this issue to causal inference [2], and how methods from this area may be helpful in our field. As a starting example, let us assume that we want to model the effect of different types of document term weighting (DTW) – binary vs. tf – and query term weighting (QTW) – binary vs idf – methods on retrieval quality, where we model the latter as P@10, which can also be regarded as the probability that a random document from the top 10 is relevant. This relationship can be modeled as a Bayesian inference network. Since the variables DTW and QTW are obviously not independent factors wrt. performance, the arrows point towards the P@10 node. (In contrast, in the binary independence retrieval model, the arrows would point from the P@10/relevance node towards the different terms).
Environmental adaptation for Autistic children using Virtual reality

This work in progress designs scenarios in a virtual environment for autism spectrum disorder (VE4ASD) in order to reduce the time and costs associated with taking autistic children to real environments as each needs to be accompanied by a mentor. It presents the user's interaction with the VR system and shows the relationship among the child, the other user (specialist or parent) and VR content. The VR prototype of VE4ASD is implemented as a proof of concept using MiddleVR for Unity3D. The VR database will be supported by SQL and Python. It will provide an effective educational tool for autistic individuals, helping them to adapt to new environments. Most of the previous studies have used the English language but this proposal will use the Arabic language, which will provide a beneficial contribution to the field of Arabic language research. We expect this study will reduce time, costs and human errors. Making the tool available to more people who want to assist children with autism and their families will lead to the development of early intervention strategies.
ncreased cerebral and renal endothelial nitric oxide ynthase gene expression after cardiopulmonary bypass in he rat

l doi:10.1016/j.jtcvs. 2006.06. 047 bjective: Hemodilution and endothelial nitric oxide synthase genetic polymorhism may contribute to cerebral and renal injury after cardiopulmonary bypass. his study tested the hypothesis that cardiopulmonary bypass and anemia stimulate n increase in cerebral and renal endothelial nitric oxide synthase gene expression n an experimental model of cardiopulmonary bypass.
Analysis of serum leptin levels as a biomarker in metabolic syndrome in type 2 diabetic patients in Okhla industrial area

Background: Metabolic syndrome is a progressive disorder which includes a wide array of disorders i.e. central obesity, hypertension, dyslipidemia, hyperglycemia, and insulin resistance. In patients with metabolic syndrome there is an increased risk of mortality due to coronary heart disease, stroke, vascular dysfunction etc. Obesity is one of the most crucial epidemics of modern times and hormone leptin plays an important role in regulation of body weight and energy balance.Methods: A total of 355 individuals were selected from the OPD, Department of general medicine at ESIC hospital, Okhla and it comprised of 196 males and 159 females suffering from type 2 diabetes mellitus with metabolic syndrome. The data was collected over a year i.e. June 2018 to July 2019. After baseline clinical and anthropometric evaluation, Fasting Blood Sugar (FBS), Post Prandial Blood Sugar (PPBS), lipid profile, Insulin (fasting), and leptin levels of the patients were analyzed.Results: Blood sugar fasting, blood sugar post prandial, lipid profile, leptin and insulin levels were increased significantly in female patients as compared to male patients with type 2 diabetic patients and metabolic syndrome.Conclusions: Based on the study results, it was found that leptin correlate significantly with metabolic syndrome and could be used as a biomarker for the early detection of the disease.
Quality assurance of some locally processed meat products

One hundred random samples of meat products represented by 25 samples each of minced meat, beef burger, sausage and luncheon which were collected from different supermarkets in Cairo and Giza cities, Egypt. Each sample was packed in plastic bag and transferred immediately to the laboratory in an icebox with a minimum period of delay to be examined organoleptically, bacteriologically and chemically. Organoleptic evaluation, regarding color, odor and taste, the percentages of undesirable samples were 28%, 28% and 24%, 20%, 20% and 16%, 24%, 20% and 24% and16%, 16% and 24% of minced meat, beef burger, luncheon and sausage, respectively. Bacteriologicalevaluation, regarding minced beef, the mean values of APC, Enterobacteriaceae and Staphylococcus aureus count was 3.3x10, 4.27x10 and 0.2x10,respectively and the number of positive samples to E.coli and salmonella was 4 and 3. Regarding beef burger, the mean values of APC, Enterobacteriaceae and Staphylococcus aureus count was 1.6x10, 7.12x10 and 0.1x10 , respectively and the number of positive samples to E.coli and salmonella was 3 and one. Regarding luncheon, the mean values of APC, Enterobacteriaceae and Staphylococcus aureus count was 2.3x10, 5x10 and <10 , respectively and the number of positive samples to E.coli and salmonella was 3 and 2. Regarding sausage, the mean values of APC ,Enterobacteriaceae and Staphylococcus aureus count was 4.5x10, 7x10 and0.3x10,respectively and the number of positive samples to E.coli and salmonella was 5 and 6. Chemical examination, regarding minced beef, the results revealed that the mean values of pH, TVN and TBA were 5.89, 24.69 and 0.70, respectively and the percentages of accepted samples regarding TVN and TBA were 60 % and 76%, respectively. Regarding beef burger, the mean values of pH, TVN and TBA were 5.8, 17.01 and 0.44, respectively. Regarding sausage, The mean values of pH, TVN and TBA were 5.9, 16.23 and 0.45, respectively and the percentages of accepted samples of sausage regarding TVN and TBA were 92% and 100%, respectively. Regarding luncheon, the mean values of pH, TVN and TBA were 5.9, 22.01 and 0.25 respectively.
Supplementary Material for Global Feature Guided Local Pooling

We can straightforwardly replace the pooling layers explicitly embedded in CNNs, such as avg/max-pooling, with the proposed pooling layer of the same pool size and the striding step size; see Fig. Aii&iii in which skip-pooling is replaced with the proposed one. Those explicit pooling layers are found in such as VGG models [8] and the second layer (of maxpooling) in ResNet models [3, 10]. On the other hand, in the ResNet models, the strided convolution implicitly contains a pooling to downsize the feature map, and the proposed pooling is also applicable to it as follows.
Does Dependent Interviewing Really Increase Efficiency and Reduce Respondent Burden

ABSTRACT Dependent interviewing techniques, where substantive information from previous interviews is fed forward and used in the formulation of questions or to prompt post-response edit checks, are increasingly employed by panel surveys. While there is substantial evidence that dependent interviewing improves the quality of longitudinal data, claims of improved efficiency of data collection and reduced respondent burden are mostly anecdotal. This paper uses data from a large experiment to systematically compare the effects of different question designs on efficiency and burden. The comparison highlights the wide variety of design options for dependent interviewing questions and their corresponding effects. In the present setup, efficiency gains were mainly due to reductions in coding costs for occupation and industry questions. The paper concludes by identifying the conditions under which dependent interviewing offers the largest scope for efficiency gains and burden reduction. Keywords
A Comparative Study of Image Segmentation Algorithms

Elliptic curve discrete logarithm problem(ECDLP) is one of problems on which the security of pairing-based cryptography is based. This paper considers Pollard’s rho method to evaluate the security of ECDLP on Barreto-Naehrig(BN) curve that is an efficient pairing-friendly curve. Some techniques are proposed to make the rho method efficient. Especially, the group structure on BN curve, distinguished point method, and Montgomery trick are well-known techniques. This paper applies these techniques and shows its optimization. According to the experimental results for which a large-scale parallel system with MySQL is applied, 94-bit ECDLP was solved about 28 hours by parallelizing 71 computers. Keywords—Pollard’s rho method, BN curve, Montgomery multiplication.
VALIDATION OF AEROSOL PRODUCTS FROM ESA/AATSR OVER CHINA AND AOD FUSION BASED ON UNCERTAINTIES

Abstract. Aerosols play an important role in climate changes and environmental changes as well as on human health. ADV v3.11, ORAC v4.10, and SU v4.32 was three new versions of Advanced Along-Track Scanning Radiometer (AATSR) aerosol datasets which are published on Climate Change Initiative (CCI). In order to evaluate the accuracy of three AATSR aerosol optical depth (AOD) datasets, and to improve the spatial coverage and accuracy of AATSR AOD dataset, this study completed two works: the first part is validated the accuracy of three AOD datasets; the second part is fused three AATSR AOD datasets based on uncertainty of each dataset. After comparing with AERONET and CARSNET ground-based data over China, results show that the root-mean-square error (RMSE) for ADV v3.11, ORAC v4.10, SU v4.32 and fused AOD are 0.22, 0.17, 0.18, 0.17 respectively.