Miracle-dz/UniFAR-FTUs huggingface dataset:
Protein Consumption in Diet of Adult Indians : A General Consumer Survey (PRODIGY)

A PROtein consumption in Diet of adult Indians, a consumer surveY (PRODIGY) was conducted in seven major cities in 1260 respondents across India in order to assess the consumer understanding of protein in their day to day life. It was observed that around 9 out of 10 consumers had a diet deficient in proteins. This was regardless of the gender and the socio-economic group A and B interviewed.
Water quality model for nonpoint source pollutants incorporating bioretention with EPA SWMM

The first aim of this study is to develop a calibrated water quality model of the non-point source pollutants over the experimental drainage area. And, the second aim is to incorporate the bioretention into the water quality model to observe its performance on pollutant removal. The study makes use of the Environmental Protection Agency Storm Water Management Model (EPA SWMM) which is being described in literature as a reliable software tool, and of the Rain fall-Watershed-Bioretention (RWB) System which is a previously developed experimental system that consists of an artificial rainfall system, drainage area and bioretention column. Within this scope, zinc (Zn), copper (Cu), lead (Pb), total nitrogen (TN) and total phosphate (TP) are defined as pollutants in the model. Bioretention is then integrated into the model, and all values related to bioretention are entered in the program. Hydrographs and pollutographs, showing the effects of non-point source pollution sources at the outlet of the drainage area, are obtained from the model before and after bioretention implementation. The values measured at the outlets of the drainage area and bioretention are compared with the results obtained from the model, and the model is calibrated accordingly. Based on the calibration results, the pollutant build-up and pollutant wash-off coefficients are obtained for the water quality model. Moreover, the effect and performance of bioretention on the quality of surface runoff are examined by evaluating the results of the model and the experiment. It is observed that the reductions of peak flow and of water contamination are very high after bioretention. Moreover, it is concluded that although the non-point source pollution model performance of EPA SWMM without bioretention is successful in representing peak concentration and the shape of the pollutographs, the model performance with bioretention needs further improvement.
An Efficient Approach for Solving Fractional Dynamics of a Predator-Prey System

In this work, we execute a generally new analytical technique, the modified generalized Mittag-Leffler function method (MGMLFM) for solving nonlinear partial differential equations containing fractional derivative emerging in predator-prey biological population dynamics system. This dynamics system are given by a set of fractional differential equations in the Caputo sense. A new solution is constructed in a power series. The stability of equilibrium points is studied. Moreover, numerical solutions for different cases are given and the methodology is displayed. We conducted a comparing between the results obtained by our method with the results obtained by other methods to illustrate the reliability and effectiveness of our main results.
Real-time High Dynamic Range Image-based Lighting

In this work we present a real time method of lighting virtual objects using measured scene radiance. To compute the illumination of CG objects inserted in a virtual environment, the method uses previously generated high dynamic range (HDR) image-based lighting information of the scene, and performs all calculations in graphics hardware to achieve real-time performance. This work is not intended to be a breakthrough in real-time processing or in HDR image-based lighting (IBL) of CG objects, but still we expect to provide the reader with the overall IBL technique knowledge upto-date, an in-depth understanding of the HDR rendering (HDRR) pipeline in current graphics cards’ hardware, and interesting images’ post-effects which deliver higher realism for the scene final viewer.
Quality of Medical Care in Mammography Divisions: A Report and Review of the Literature

The purpose of this study was to evaluate the quality of medical care and the status of radiological practice and equipment performance according to the protocols established by International Atomic Energy Agency (IAEA), in mammography divisions of Shiraz, Iran. In addition, a review of the literature is also presented. Five diagnostic mammography divisions, namely; Namazi, Faghihi, Hafez, Zeinabieh, and MRI were studied. Protocol related to staff and health physicist duties was investigated by arranging a standard questionnaire. Results showed that, approximately 47% of the staff had not passed necessary training in radiation protection and quality assurance radiation program in the beginning of their work. Moreover, about 80% of them had not their licenses renewed by attending the training classes again. More attention should be given to training and protection of the staff and quality control of the mammography machines and equipments. [Siavashpour Z, Mehdizadeh S, Farshadi A, Baradaran-Ghahfarokhi M, Nasri H. Quality of Medical Care in Mammography Divisions: A Report and Review of the Literature. Life Sci J 2014;11(9s):438-444]. (ISSN:1097-8135). http://www.lifesciencesite. com. 90
EFFECT OF TEMPERATURE REGIMES ON PERFORMANCE OF WHEAT (TRITICUM SP.) GENOTYPES

A field experiment was conducted during Rabi, 2015-16 to study the effect of temperature on performance of wheat (Triticum sp.) genotypes at Main Agricultural Research Station, University of Agricultural Sciences, Dharwad (Karnataka), India. The experiment consisted of two dates of sowing viz., 2nd November 2015 (D1 temperature regime), 15 th December 2015 (D2 temperature regime) and nine wheat genotypes belonging to three species, viz., Triticum aestivum, Triticum durum and Triticum dicoccum. Significant reduction in plant height, dry matter accumulation, yield and yield attributes was observed under D2 temperature regime. The reason might be prevailing of favorable temperature required for wheat crop for higher photosynthate accumulation consequently resulting in higher yield parameters under D1 temperature regime. DDK-1045 recorded maximum plant height at harvest under both D1 (82.87 cm) and D­2 (74.55 cm) temperature regimes. HW-1098 recorded maximum total dry matter accumulation at harvest under both D1 (18.96 g hill -1) and D­2 (16.41 g hill -1) temperature regimes. HW-1098 recorded maximum grain yield under both D1 (8102 kg ha -1) and D­2 (6093 kg ha -1) temperature regimes. Under D1 temperature regime UAS-415 recorded maximum 1000 grain weight (45.95 g) while under D2 temperature regime HW1098 recorded maximum 1000 grain weight (40.84 g). The genotype HW-1098 recorded higher harvest index and more number of tillers m-2 under both the temperature regimes which might be attributed to higher yield.
195-206 Doherty M_A 08.indd

The authors reported findings from 3 studies examining the efficacy of Five Standards pedagogy in raising student achievement. Studies 1 and 2 were randomized designs; Study 3 was a quasi-experimental design. Samples included 53 teachers and 622 predominantly low-income Latino students in Grades 1–4. Studies assessed model fidelity with the standards performance continuum and student achievement with norm-referenced, criterion-referenced, standards-based, and computerized adaptive tests. Of 34 comparisons, only 3 comparisons favored Five Standards pedagogy, with minor differences and no observable benefits for English learners. Findings do not support claims of efficacy and indicate the instructional model needs further development before dissemination as effective diversity pedagogy.
Reading Idioms: A Comparative Eye-Tracking Study of Native English Speakers and Native Korean Speakers

Reading Idioms: A Comparative Eye-Tracking Study of Native English Speakers and Native Korean Speakers Sarah Lynne Miner Department of Linguistics and English Language, BYU Master of Arts This quantitative study used eye-tracking technology to compare the attentional focus of 32 native English speakers and 26 native Korean speakers at the university level as they read idiomatic and literal phrases within well-formed sentences. Results revealed that native Korean speakers read both literal and idiomatic sentences slower than native English speakers. Additionally, native Korean speakers read idiomatic sentences slower than literal sentences, whereas native English speakers did not show a significant difference. Variables relating to language socialization, language development and idiom knowledge were also investigated to find which variables were correlated with reading measures. Of the variables tested, idiom knowledge was the only one that had significant effect on reading measures. These findings suggest that Korean speakers take longer to process English idioms as lexical units, though idiom familiarity seems to mitigate this effect.
STUDY OF ASCITIC FLUID FOR DIAGNOSIS OF SPONTANEOUS BACTERIAL PERITONITIS (SBP) IN ADULT PATIENTS WITH CIRRHOSIS

Ascitic fluid infections are a frequent complication among patients with cirrhosis and ascites, of which Spontaneous Bacterial Peritonitis (SBP) is the most common, potentially fatal cause of deterioration in patients with advanced cirrhosis with ascites. One hundred consecutive hospitalized patients of cirrhosis with ascites were included in this prospective study. Ascitic fluid was analysed by culture by the conventional method and direct bedside inoculation in tryptic soy broth (TSB), cell count and biochemical parameters. The cases were categorized into three groups – Classic Spontaneous Bacterial Peritonitis (SBP), Culture Negative Neutrocytic ascites (CNNA) and Monomicrobial non-neutrocytic bacterascites (MNB). Statistical analysis was done by Chi Square test, Paired and Unpaired ‘t’ tests. Out of 100 patients of cirrhosis with ascites, 58% were SBP cases and 42 % were non-SBP cases. Amongst the 58 SBP cases, 53.45% cases were of Classic SBP, 36.21 % were CNNA and 10.34% cases were of MNB. Alcoholism (84.48 %) was the commonest etiology in SBP cases. Escherichia coli was the commonest bacteria isolated, followed by Pseudomonas aeruginosa and Acinetobacter species. Mean ascitic fluid polymorphonuclear count (PMN) count was 755.19 ± 788.04 / mm 3 . Overall susceptibility of bacteria to aminoglycosides, quinolones and cephalosporins was 92.31%, 79.17% and 58.33% respectively. Hepatic encephalopathy was the major complication (46.55%) in SBP cases. Highest mortality was seen in CNNA (66.67 %), followed by Classic SBP (45.16 %). SBP is a serious complication in patients with advanced cirrhosis. It has high prevalence, high recurrence rate and poor long term prognosis. A diagnostic paracentesis should always be performed routinely within 24 hours of admission and ascitic fluid sample should be sent for culture, cytology and estimation of biochemical parameters, so as to initiate prompt management in these patients and achieve a better survival rate.
Processing pronouns and PRO

This paper presents results from five experiments investigating the online interpretation of PRO and pronouns as subjects of adjunct clauses. The experiments attempted to provide evidence on the timecourse of interpretation for PRO/pronouns, and whether this interpretation causes reactivation of the semantic content of the antecedent in memory, using the N400 component of ERPs and self-paced reading times. The results were inconclusive. Although facilitation was seen in the N400 for some conditions, the effect of the interpretation of PRO and pronouns was small and insignificant, even though PRO and the pronoun did affect offline cloze results. Self-paced reading times also did not indicate differences in processing due to PRO/pronoun resolution. These results suggest either that interpreting PRO and pronouns does not reactivate the semantic content of their antecedents sufficient to cause facilitation of related material, or that any such facilitation is not reflected in the N400 or self-paced reading times.
Learning Linear Influence Models in Social Networks from Transient Opinion Dynamics

Social networks, forums, and social media have emerged as global platforms for forming and shaping opinions on a broad spectrum of topics like politics, sports, and entertainment. Users (also called actors) often update their evolving opinions, influenced through discussions with other users. Theoretical models and their analysis on understanding opinion dynamics in social networks abound in the literature. However, these models are often based on concepts from statistical physics. Their goal is to establish specific phenomena like steady state consensus or bifurcation. Analysis of transient effects is largely avoided. Moreover, many of these studies assume that actors’ opinions are observed globally and synchronously, which is rarely realistic. In this article, we initiate an investigation into a family of novel data-driven influence models that accurately learn and fit realistic observations. We estimate and do not presume edge strengths from observed opinions at nodes. Our influence models are linear but not necessarily positive or row stochastic in nature. As a consequence, unlike the previous studies, they do not depend on system stability or convergence during the observation period. Furthermore, our models take into account a wide variety of data collection scenarios. In particular, they are robust to missing observations for several timesteps after an actor has changed its opinion. In addition, we consider scenarios where opinion observations may be available only for aggregated clusters of nodes—a practical restriction often imposed to ensure privacy. Finally, to provide a conceptually interpretable design of edge influence, we offer a relatively frugal variant of our influence model, where the strength of influence between two connecting nodes depends on the node attributes (demography, personality, expertise, etc.). Such an approach reduces the number of model parameters, reduces overfitting, and offers a tractable and explicable sketch of edge influences in the context of opinion dynamics. With six real-life datasets crawled from Twitter and Reddit, as well as three more datasets collected from in-house experiments (with 102 volunteers), our proposed system gives a significant accuracy boost over four state-of-the-art baselines.
The reduced immersed method for real-time fluid-elastic solid interaction and contact simulation

We introduce the Reduced Immersed Method (RIM) for the real-time simulation of two-way coupled incompressible fluids and elastic solids and the interaction of multiple deformables with (self-)collisions. Our framework is based on a novel discretization of the immersed boundary equations of motion, which model fluid and deformables as a single incompressible medium and their interaction as a unified system on a fixed domain combining Eulerian and Lagrangian terms. One advantage for real-time simulations resulting from this modeling is that two-way coupling phenomena can be faithfully simulated while avoiding costly calculations such as tracking the deforming fluid-solid interfaces and the associated fluid boundary conditions. Our discretization enables the combination of a PIC/FLIP fluid solver with a reduced-order Lagrangian elasticity solver. Crucial for the performance of RIM is the efficient transfer of information between the elasticity and the fluid solver and the synchronization of the Lagrangian and Eulerian settings. We introduce the concept of twin subspaces that enables an efficient reduced-order modeling of the transfer. Our experiments demonstrate that RIM handles complex meshes and highly resolved fluids for large time steps at high framerates on off-the-shelf hardware, even in the presence of high velocities and rapid user interaction. Furthermore, it extends reduced-order elasticity solvers such as Hyper-Reduced Projective Dynamics with natural collision handling.
FirmFuzz: Automated IoT Firmware Introspection and Analysis

While the number of IoT devices grows at an exhilarating pace their security remains stagnant. Imposing secure coding standards across all vendors is infeasible. Testing individual devices allows an analyst to evaluate their security post deployment. Any discovered vulnerabilities can then be disclosed to the vendors in order to assist them in securing their products. The search for vulnerabilities should ideally be automated for efficiency and furthermore be device-independent for scalability. We present FirmFuzz, an automated device-independent emulation and dynamic analysis framework for Linux-based firmware images. It employs a greybox-based generational fuzzing approach coupled with static analysis and system introspection to provide targeted and deterministic bug discovery within a firmware image. We evaluate FirmFuzz by emulating and dynamically analyzing 32 images (from 27 unique devices) with a network accessible from the host performing the emulation. During testing, FirmFuzz discovered seven previously undisclosed vulnerabilities across six different devices: two IP cameras and four routers. So far, 4 CVE's have been assigned.
Curve-pleated structures

In this paper we study pleated structures generated by folding paper along curved creases. We discuss their properties and the special case of principal pleated structures. A discrete version of pleated structures is particularly interesting because of the rich geometric properties of the principal case, where we are able to establish a series of analogies between the smooth and discrete situations, as well as several equivalent characterizations of the principal property. These include being a conical mesh, and being flat-foldable. This structure-preserving discretization is the basis of computation and design. We propose a new method for designing pleated structures and reconstructing reference shapes as pleated structures: we first gain an overview of possible crease patterns by establishing a connection to pseudogeodesics, and then initialize and optimize a quad mesh so as to become a discrete pleated structure. We conclude by showing applications in design and reconstruction, including cases with combinatorial singularities. Our work is relevant to fabrication in so far as the offset properties of principal pleated structures allow us to construct curved sculptures of finite thickness.
Automatic detection of intracranial aneurysm from digital subtraction angiography with cascade networks

Automatic detection of intracranial aneurysm based on Digital Subtraction Angiography (DSA) images is a challenging task for the following reasons: 1) effectively leverage the temporal information of the DSA sequence; 2) effectively extract features by avoiding unnecessary interference in the raw DSA images of large resolution; 3) effectively distinguish the vascular overlap from intracranial aneurysm in DSA images. To better identify intracranial aneurysm from DSA images, this paper proposed an automatic detection framework with cascade networks. This framework is consisted of a region localization stage (RLS) and an intracranial aneurysm detection stage (IADS). The RLS stage can significantly reduce the interference from unrelated regions and determine the coarse effective region. The IADS stage fully employed the spatial and temporal features to accurately detect aneurysm from DSA sequence. This method was verified in the posterior communicating artery (PCoA) region of internal carotid artery (ICA). In clinical trials, the accuracy of the baseline method was 62.5% with area under curve (AUC) of 0.650, and the time cost of the detection was approximately 62.546s. However, the accuracy of this method was 85.5% with AUC of 0.918, and the time cost of detection was about 3.664s. The experimental results showed that the proposed method significantly improved the accuracy and speed of intracranial aneurysm automatic detection.
Learning adaptive hierarchical cuboid abstractions of 3D shape collections

Abstracting man-made 3D objects as assemblies of primitives, i.e., shape abstraction, is an important task in 3D shape understanding and analysis. In this paper, we propose an unsupervised learning method for automatically constructing compact and expressive shape abstractions of 3D objects in a class. The key idea of our approach is an adaptive hierarchical cuboid representation that abstracts a 3D shape with a set of parametric cuboids adaptively selected from a hierarchical and multi-level cuboid representation shared by all objects in the class. The adaptive hierarchical cuboid abstraction offers a compact representation for modeling the variant shape structures and their coherence at different abstraction levels. Based on this representation, we design a convolutional neural network (CNN) for predicting the parameters of each cuboid in the hierarchical cuboid representation and the adaptive selection mask of cuboids for each input 3D shape. For training the CNN from an unlabeled 3D shape collection, we propose a set of novel loss functions to maximize the approximation quality and compactness of the adaptive hierarchical cuboid abstraction and present a progressive training scheme to refine the cuboid parameters and the cuboid selection mask effectively. We evaluate the effectiveness of our approach on various 3D shape collections and demonstrate its advantages over the existing cuboid abstraction approach. We also illustrate applications of the resulting adaptive cuboid representations in various shape analysis and manipulation tasks.
SceneGit

Version control systems are the foundation of collaborative workflows for text documents. For 3D environments though, version control is still an open problem due to the heterogeneous data of 3D scenes and their size. In this paper, we present a practical version control system for 3D scenes comprised of shapes, materials, textures, and animations, combined together in scene graphs. We version objects at their finest granularity, to make repositories smaller and to allow artists to work concurrently on the same object. Since, for some scene data, computing an optimal set of changes between versions is not computationally feasible, version control systems use heuristics. Compared to prior work, we propose heuristics that are efficient, robust, and independent of the application. We test our system on a variety of large scenes edited with different workflows, and show that our approach can handle all cases well while remaining efficient as scene size increases. Compared to prior work, we are significantly faster and more robust. A user study confirms that our system aids collaboration.
Modeling curved folding with freeform deformations

We present a computational framework for interactive design and exploration of curved folded surfaces. In current practice, such surfaces are typically created manually using physical paper, and hence our objective is to lay the foundations for the digitalization of curved folded surface design. Our main contribution is a discrete binary characterization for folds between discrete developable surfaces, accompanied by an algorithm to simultaneously fold creases and smoothly bend planar sheets. We complement our algorithm with essential building blocks for curved folding deformations: objectives to control dihedral angles and mountain-valley assignments. We apply our machinery to build the first interactive freeform editing tool capable of modeling bending and folding of complicated crease patterns.