Miracle-dz/UniFAR-FTUs huggingface dataset:
ROBUST FACE RECOGNITION FROM MULTI-VIEW VIDEOS

The recognition of the persons from videos has numerous applications in Video Surveillances and Computer Vision. Face detection in still images is applied in many of the devices and in many of the applications. Face detection in videos is a recent technique which ensures the identification of person in the video. In a video normally the pose of the persons and the illumination variations were normally present. The main challenge of detecting face images in videos is the pose and the illumination variations and sudden changes in the movement of the object. The videos taken from cameras are taken. The surveillance videos were normally not so clear and there may be some illumination variations and blurness at some places due to rapid movement of the objects. The proposed system analyzes and recognizes the exact face image from the video while the existing systems deals with the recognition of the face images from still images. The proposed system is capable of identifying the face images in the video in a better manner even though there are pose variations illumination variations and blurs occurring due to rapid motions of the subjects in the video. The videos were converted into frames. Preprocessing is applied to the video frames using median filter to remove the unwanted noises from the frames. The face of the person is detected and the face is masked. The face region is masked so that we identify the face images of the particular person more clearly. The gradient value of the image and the histogram values were calculated. These will be helpful in the identification of the face positions continuously. Based on the detected face the position of the person is determined in each frame and the person is tracked continuously. Hog features are extracted and then RBF kernel function is applied along with spherical harmonics function. The Hog features are more reliable and they are useful in the identification of the face image of the particular person.Face images is retrieved from the dataset which is trained based on the distance calculated using Bhattacharya coefficient. The Bhattacharya distance is used for identifying the face image from the Dataset. The results shows that the recognition rate of the proposed system is increased compared to other existing systems. The system is more reliable for the identification of the face images from the videos.
Diabetic Retinopathy Evaluation using the support vector machine

- Diabetic retinopathy is a micro vascular complication which is characterized by several changes in the retina. These changes need to be detected early so that steps for further handling and treatment can be determined. Laser therapy is one of the common therapies for patients with Diabetic Retinopathy. This therapy is a manual examination of the scanned results of the fundus retinal image. Manual examinations that generate ophthalmologist sight differ from each other. To overcome this problem, a special program is needed to analyze the fundus image of the eye. To create a special program for analyzing the fundus images of the eye required several stages of research. The study begins by preprocessing eye fundus images, getting rid of the optic dick form the fundus of the eye and then separating the vascular tissue of the damaged area of the retina. Damaged areas of the retina consist of dark and bright lesions. Mathematical morphology methods are used to detect the presence of dark lesion. As diabetes progresses, the vision of a patient may start to deteriorate and lead to diabetic retinopathy. The main stages of diabetic retinopathy are no proliferative diabetic retinopathy(NPDR) and pro liferative retinopathy(PDR). In this paper, we have proposed a computer based approach for the detection of diabetic retinopathy stages using color fundus images. The features are extracted from the raw image, using the image processing techniques and fed to the support vector machine (SVM) for classification. The results showed a sensitivity of 99.45% for the classifier and specificity of 100%.
Carbon and nitrogen dynamics, carbon sequestration and energy saving in soils under different tillage, stubble mulching and fertilizer management in rice–wheat cropping system

Soil organic carbon plays the crucial role in maintaining soil quality. The impact carbon and nitrogen dynamics and rate of SOC sequestration in tillage and crop residue application is still in investigation in this environment. A field experiment was initiated in 2009-10 and continued up to 2015-16 to compare the organic carbon build up in the soil due to tillage and crop residue application. The soil organic carbon data represents the cumulative after five crop cycle. About 5 t ha of standing rice and wheat crop was retained for succeeding crop in retained treatments. Result showed that, soil organic carbon build up was affected significantly by tillage and residue level in upper depth of 0-15 cm but not in lower depth of 1530 cm. Higher SOC content of 19.44 g kg of soil was found in zero tilled residue retained plots followed by 18.53 g kg in permanently raised bed with residue retained plots. Whereas, the lowest level of SOC content of 15.86 g kg of soil were found in puddled transplanted rice followed by wheat planted under conventionally tilled plots. Zero tilled residue retained plots sequestrated 0.91gkgyr SOC in the year 2015-16 which was 22.63% higher over the conventionally tilled residue removed plots after seven seasons of experimentation. The zero tilled soil had values of dehydrogenase, urease, phosphatase and β-glucosidase activities, and water aggregate stability higher than conventional tilled soils but lowers than the soil under permanent raised beds with residue retention. The enzyme activities and water aggregate stability reflected early changes in soil the profile to a greater extent than did physical-chemical and chemical properties. Similarly, treatments that included organic manure had significantly higher SOC concentrations and stocks than mineral or unfertilized treatments. The organic manure treatments also had higher concentrations of non-labile but at the same time a higher proportion of labile C than the mineral or unfertilized treatments. This was confirmed by the carbon management index (CMI) which was significantly increased by organic manure addition. This study demonstrates that fertilization strategies that include organic manure can increase the pool of stable C in the surface soil layer, while at the same time increasing concentrations and proportions of labile C.Therefore, CA in rice-wheat system can help directly in building–up of soil organic carbon and improve the fertility status of soil.
Genes Discriminating between Breast Cancers Responsive or Resistant to the Aromatase Inhibitor, Letrozole

RNA expression profiles from breast cancer biopsies taken before and after 10–14 days of neoadjuvant treatment with the aromatase inhibitor, letrozole, together with change in expression between the time points were compared in tumors classified as clinically responsive or resistant to treatment. Statistical analysis for microarrays identified 31 expression variables (six pretreatment, four on-treatment, and 21 change parameters) that were significantly different (P,0.001) between 37 responsive tumors and 15 resistant cases. Notably, 18 of 21 change variables coded for ribosomal proteins. Gene ontology terms corresponding to the 31total variables were highly statistically enriched for ‘‘translation’’ and ‘‘structural components of ribosomes’’. These data highlight the importance of changes in the expression of ribosomal proteins as early markers distinguishing between breast cancers clinically responsive and resistant to neoadjuvant letrozole.
Upregulating beta-hexosaminidase activity in rodents prevents alpha-synuclein lipid associations and protects dopaminergic neurons from alpha-synuclein-mediated neurotoxicity

Sandhoff disease (SD) is a lysosomal storage disease, caused by loss of β-hexosaminidase (HEX) activity resulting in the accumulation of ganglioside GM2. There are shared features between SD and Parkinson’s disease (PD). α-synuclein (aSYN) inclusions, the diagnostic hallmark sign of PD, are frequently found in the brain in SD patients and HEX knockout mice, and HEX activity is reduced in the substantia nigra in PD. In this study, we biochemically demonstrate that HEX deficiency in mice causes formation of high-molecular weight (HMW) aSYN and ubiquitin in the brain. As expected from HEX enzymatic function requirements, overexpression in vivo of HEXA and B combined, but not either of the subunits expressed alone, increased HEX activity as evidenced by histochemical assays. Biochemically, such HEX gene expression resulted in increased conversion of GM2 to its breakdown product GM3. In a neurodegenerative model of overexpression of aSYN in rats, increasing HEX activity by AAV6 gene transfer in the substantia nigra reduced aSYN embedding in lipid compartments and rescued dopaminergic neurons from degeneration. Overall, these data are consistent with a paradigm shift where lipid abnormalities are central to or preceding protein changes typically associated with PD.
University of Birmingham Drought in a human-modified world

In the current human-modiﬁed world, or Anthropocene, the state of water stores and ﬂuxes has become dependent on human as well as natural processes. Water deﬁcits (or droughts) are the result of a complex interaction between meteorological anomalies, land surface processes, and human inﬂows, outﬂows, and storage changes. Our current in-ability to adequately analyse and manage drought in many places points to gaps in our understanding and to inadequate data and tools. The Anthropocene requires a new framework for drought deﬁnitions and research. Drought deﬁnitions need to be revisited to explicitly include human processes driving and modifying soil moisture drought and hydrological drought development. We give recommendations for robust drought deﬁnitions to clarify timescales of drought and prevent confusion with related terms such as water scarcity and overexploitation. Additionally, our understanding and analysis of drought need to move from single driver to multiple drivers and from uni-directional to multi-directional. We identify research gaps and propose analysis approaches on (1) drivers, (2) modiﬁers, (3) impacts, (4) feedbacks, and (5) changing the baseline of drought in the Anthropocene. The most pressing research questions are related to the attribution of drought to its causes, to linking drought impacts to drought characteristics, and to societal adaptation and responses to drought. Example questions include Published the European Geosciences
Supplement to Birnbaum and Quan (2020): Detecting violations of the true and error model and examination of robustness of parameter estimates using simulated data

The Markov True and Error (MARTER) model (Birnbaum & Wan, 2020) has three components: a risky decision making model with one or more parameters, a Markov model that describes stochastic variation of parameters over time, and a true and error (TE) model that describes probabilistic relations between true preferences and overt responses. In this study, we simulated data according to 57 generating models that either did or did not satisfy the assumptions of the True and Error fitting model, that either did or did not satisfy the error independence assumptions, that either did or did not satisfy transitivity, and that had various patterns of error rates. A key assumption in the TE fitting model is that a person’s true preferences do not change in the short time within a session; that is, preference reversals between two responses by the same person to two presentations of the same choice problem in the same brief session are due to random error. In a set of 48 simulations, data generating models either satisfied this assumption or they implemented a systematic violation, in which true preferences could change within sessions. We used the true and error (TE) fitting model to analyze the simulated data, and we found that it did a good job of distinguishing transitive from intransitive models and in estimating parameters not only when the generating model satisfied the model assumptions, but also when model assumptions were violated in this way. When the generating model violated the assumptions, statistical tests of the TE fitting models correctly detected the violations. Even when the data contained violations of the TE model, the parameter estimates representing probabilities of true preference patterns were surprisingly accurate, except for error rates, which were inflated by model violations. In a second set of simulations, the generating model either had error rates that were or were not independent of true preferences and transitivity either was or was not satisfied. It was found again that the TE analysis was able to detect the violations of the fitting model, and the analysis correctly identified whether the data had been generated by a transitive or intransitive process; however, in this case, estimated incidence of a preference pattern was reduced if that preference pattern had a higher error rate. Overall, the violations could be detected and did not affect the ability of the TE analysis to discriminate between transitive and intransitive processes.
Glacier disequilibrium in the Convoy Range, Transantarctic Mountains, Antarctica

Field work for a geological map of the Convoy Range included mapping glaciers, moraines and surficial deposits. A range of glaciological indicators, including supraglacial and other moraines and margin morphology, has been used to assess the present equilibrium of the glaciers. Fields of rafted supraglacial moraine have accumulated over long periods of time at specific low-gradient, low-velocity locations. As the glacier regime changes, the shape of the moraine field distorts, signalling a change in flow pattern. By reversing the ice flow vectors directed at the moraine field, the directions from whence the debris came are shown. Unsorting the contortions of supraglacial moraine fields reveals the nature of the changes in glacier regime. Moraine-field configurations all suggest that local glaciers are expanding in response to higher local precipitation, estimated to have occurred between 2000 and 8000 year BP, most likely coincident with the world-wide “climatic optimum” of about 6000 year BP. Ice-cliff morphology, fresh terminal moraines and boulder trains indicate that larger local glaciers are currently receding from a Holocene maximum, while the margin of the large Mackay Ice Sheet outlet glacier shows no evidence of recent recession and is probably close to its Holocene maximum. In contrast, areas of present snow cover are expanding, superimposing a recent positive balance (decades to hundreds of years), which has yet to reverse a general recession of mid- to high-altitude glaciers. Local hollows in some névé areas imply that glacier flow is not in equilibrium with snow accumulation.
Estimation of advective fluxes from CO2 flux profile observations at the Cabauw Tower

The exchange of carbon dioxide (CO2) between the atmosphere and the terrestrial biosphere is an important link in climate related research. In this field of research, there is a need to quantify regional scale vertical fluxes of CO2 to bridge the gap between ecosystem scale and the global scale. These regional scale fluxes may be obtained by accurate observations higher up in the atmosphere. In doing so, complicating factors arise such as storage of CO2 beneath the level of observation and advection. The question of advective contribution to the net ecosystem exchange (NEE) of CO2 is investigated at the 213 m tall-tower near Cabauw, The Netherlands. In addition, vertical and temporal variability of CO2 at Cabauw is studied. This site is particularly interesting because advection is assumed to be small under convective conditions, because of the relatively homogeneous and flat surrounding landscape. Moreover, the Cabauw tower is equipped with CO2 flux and concentration instrumentation at several levels, which enables detailed advection estimations based on a scalar budget methodology. To judge advection under convective conditions a summer half year was studied. During monthly averaged diurnal cycles the advective contribution to NEE was found to be in the order of 20%, but also showed a significantly noisy signal in general. The advection is typically alternately CO2 enriching and depleting. However, with a fairly constant easterly wind direction over the course of a month the advective contribution was observed to be persistently and significantly enriching during daytime. This is probably related to the presence of a village in the footprint of the flux observations. This study shows that in assessments of NEE for Cabauw and similar landscapes advection should be considered.
Formation and disintegration of the Antarctic ice sheet

A model of the Antarctic ice sheet has been used to simulate the ice sheet in warmer climates, in order to investigate what kind of ice-sheet geometries one can reasonably expect under what kind of climatic conditions and to discover which physical mechanisms may be involved to explain them. The results of these experiments reveal the considerable stability of; in particular, the East Antarctic ice sheet. It would require a temperature rise of between 17 and 20 K above present levels to remove this ice sheet from the subglacial basins in the interior of the continent and of 25 K to melt down the Antarctic ice sheet completely. For a temperature rise below 5 K, the model actually predicts a larger Antarctic ice sheet than today as a result of increased snowfall, whereas the west Antarctic ice sheet was round not to survive temperatures more than 8–10 K above present values. Furthermore, basal temperature conditions in these experiments point to the problems involved in raising the base of the ice sheet to the pressure-melting point over the large areas necessary to consider the possibility of sliding instability. These results bear on a lively debate regarding the late Cenozoic glacial history of Antarctica. Particularly, based on these findings, it is difficult to reconcile a highly variable East Antarctic ice sheet until the Pliocene with modest warming recorded in, for instance, the deep-sea records for the late Neogene.
An OpenCL-based parallel acceleration of aSobel edge detection algorithm Using IntelFPGA technology

This paper examines the feasibility of using commercial out-of-the-box Reconfigurable Field Programmable Gate Array (FPGA) technology and the OpenCL framework to create efficient Sobel edge-detection implementation, which is considered a fundamental part in the field of image and video processing. The revised proposed approach was created at a high level of abstraction and executed on high commodity Intel FPGA platform. This was performed in a manner that was designed to allow the high-level compiler/synthesis tool to manipulate a task a parallelism model. The most promising FPGA and the naive implementations were compared to their single-core CPU software equivalents while manipulating local-memory, pipelining, loop unrolling, vectorization, internal channels mechanisms and memory coalescing to provide a much more effective hardware design. The run-time and the power consumption attributes were estimated for each implementation. The proposed FPGA based implementations were found to have significantly better runtime and power consumption with approximately up to 37 folds of improvement in the whole execution/transfer time, and up to 53 folds of improvement in energy consumption when compared to a specific single-core CPU based implementation.
Novel Approach for Evaluating Detector Systematics in the MicroBooNE LArTPC

One of the primary challenges in current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) is understanding detector effects and quantifying the associated systematic uncertainties. MicroBooNE has pioneered the evaluation of detector-related systematic uncertainties for such experiments. This note presents a novel technique for assessing detector systematics based on low-level comparisons between data and simulation. The method can be used to better understand detector-related uncertainties while remaining agnostic to the details of the detector model in simulation. We believe similar approaches could be applied to future LArTPC experiments, including SBN and DUNE.
Competitive Effects of Front-of-Package Nutrition Labeling Adoption on Nutritional Quality: Evidence from Facts Up Front–Style Labels

“Facts Up Front” nutrition labels are a front-of-package (FOP) nutrition labeling system that presents key nutrient information on the front of packaged food and beverage products in an easy-to-read format. The authors conduct a large-scale empirical study to examine the effect of adoption of FOP labeling on products’ nutritional quality. The authors assemble a unique data set on packaged food products in the United States across 44 categories over 16 years. By using a difference-in-differences estimator, the authors find that FOP adoption in a product category leads to an improvement in the nutritional quality of other products in that category. This competitive response is stronger for premium brands and brands with narrower product line breadth as well as for categories involving unhealthy products and those that are more competitive in nature. The authors offer evidence regarding the role of nutrition information salience as the underlying mechanism; they also perform supplementary analyses to rule out potential self-selection issues and conduct a battery of robustness checks and falsification tests. The authors discuss the implications of the findings for public policy makers, consumers, manufacturers, and food retailers.
Prediction Configural Frequency Analysis (P-CFA) for Indicating Interaction between The Level of Education of Children and Parents

Configural frequency analysis is an analysis that can see the existence of discrepancy on the model marked by the existence of a significant difference between the frequency of observation and frequency of expectation. This analysis focuses on whether or not the interaction among categories from different variables, and not the interaction among variables. In its development, a person can use this analysis to predict certain events. The basic difference between CFA and P-CFA is that there is no difference between the status of variables on CFA, while p-cfa makes the difference between the predictors and criterias. In addition, Log linier model does not differentiate between independent variables and dependent variables. It is also able to detect the relationship among some variables, including the possibility of a causal relationship. Therefore, this model can be used as the base models in the CFA. In general, CFA and P-CFA usually used to see the characteristics of the causes of an event. Hence, this research will present the concept of the p-cfa and how it works for the real data. The data on this paper is on the level of education of children and parents living in the district of Bandung. From the results, it is known that the parents, both the father and mother of the children who are graduated from high school tend to be followed by their children to be graduated from high school especially if the children studied in urban areas.