Miracle-dz/UniFAR-FTUs huggingface dataset:
The Clebsch graph on the crossroads of Algebraic Geometry and Algebraic Graph Theory

The Clebsch graph Cl is a strongly regular graph (SRG) with the parameters (16,5,10,0,2)S and primitive rank 3 automorphism group of order 1920, isomorphic to the spilt extension E16 : S5. It is one of the six known primitive triangle free SRGs with 5,10,16,56,77 and 100 vertices. All these graphs appear as (induced) subgraph of the graph NL2(10) with 100 vertices, discovered by Dale Mesner in 1956 and also known as the Higman-Sims graph, see [6] for details. The question about the existence of other primitive triangle-free SRGs remains open for a long while and seems to be one of the most challenging problems in AGT. The name Clebsch graph was coined by J.J. Seidel in [8], sometimes this name is attributed to the complementary to Cl graph of valency 10. Many nice models of Cl appear on the home page of Andries Brouwer [1]. Being originally educated in classical geometry of XIXth century, Seidel was referring to the paper [2]. While the name itself was commonly used for about half a century, it seems that its roots were not discussed properly in literature. According to procedure, described by A. Rudvalis [7], starting from Cl, one gets a symmetric design on 16 vertices, usually called biplane. All biplanes on 16 points are well-known, see e.g. [5]. The one, which appears from Cl is sometimes called the nicest biplane B6 (on 16 points). According to the procedure by Rudvalis, which involves polarities of designs, the graph Cl is reconstrutable from B6. A remarkable issue is that some of the objects equivalent to biplanes on 16 points were also discoverdd in AG, in the framework of Kummer surfaces, see [4]. The new incaranation of the classical results by Hudson in modern clothes of AG appears in [3]. In this talk we are trying to tie all these loose ends, using in particular facilites of computer packages. In fact, Clebsch studied in his classical paper [2] a class of quartic surfaces in P3 obtained as the image of four generic cubic homogeneous polynomials in three variables, that vanish at a given set of of five points in generic position in P2. In modern terms we can construct the surface by looking at the blowup of P2 in five points in general position. The blowup surface is smooth and can be embedded in P4. This is a Del Pezzo surface of degree 4 in P4 and projecting this surface from a generic point not on the surface, we obtain the Clebsch quartic in P3. The surface has 16 lines on it obtained as the images of the exceptional divisor, the
Designing a Lens Flare correcting ISP

Lens ﬂare occurs in photography when rays from a very bright light have internal reﬂections and scatter in the lens system of a camera, overlaying the captured image with artifacts such as blown out starbursts, colored shapes, rain-bow patterns and haze. While sometimes used for an artistic effect, lens ﬂares can also be undesirable. In this project we aimed to train a deep learning network to automatically remove lens glare from images, predicting what would have been captured without internal reﬂections or scatting in the lens system. We use a VGG16 based U-net to capture both local and global information when predicting the resulting image. We create a dataset of training pairs of the same image with and without lens ﬂare by adding synthetic lens ﬂare to real HDR images. We developed our architecture to accept raw Bayer-array data as this data has been shown to capture more of the information native to the scene, and has a much higher dynamic range. The current trained model seems to eliminate rainbowing by adding to the two other channels (instead of subtracting from the over-represented channel). This unfortunately means that the PSNR of the synthetically corrupted signal is higher than that of the ’corrected signal’ when compared to the ground truth.SSNR is also lower in the ’corrected signal’. This project is a work in progress and our future steps are discussed in the paper.
E-learning readiness of teachers of two state agricultural universities: A comparative study in Northern India

Advances in Information and Communication technologies (ICTs) have comprehensively transformed the academic landscape in education sector in India. Consequently, the process of teaching and learning along with educational programmes and pedagogy of instruction are being restructured, reformed and realigned to meet the expectations of a whole new breed of students entering the technical institutions. ICT applications in education sector can greatly enhance the quality of learning outcomes. The learners, through multifaceted ICT applications, can control the content, time and pace of learning. However, we need to assess the e-learning readiness of an educational institution and its different stakeholder before implementing any e-learning strategy. The present study was undertaken to assess and analyse the e-learning readiness of two premier State Agriculture Universities (SAUs) of North India. The study findings indicate the two SAUs under study are ‘ready but needs improvement’ on certain areas. The findings will prove to be useful for policy makers, educationists and researchers in determining the changes and challenges facing agriculture higher education in India and catalyse the plans for making all the SAUs in India to be e-ready.
Functional linear models driven by point processes

We introduce a new class of functional models where a point process is part of the model and plays a key role in it. We focus on a functional linear model where the kernel is a stochastic point process, N. If N is a Poisson process, we derive unbiased and consistent estimators of the intensity of N, in the homogeneous case, and of the expectation measure of N, in the non homogeneous case. We observe that confidence intervals and bands for these quantities can also determined. Asymptotic normality of these estimators is obtained under regularity conditions on the functional noise.
End-to-end memory networks with word abstraction and contextual numbering for goal-oriented tasks

An end-to-end dialog system is useful because it does not need to make assumptions about the domain or dialog state structure. Additionally, it can achieve high versatility with only datasets. The sixth Dialog System Technology Challenge (DSTC6) introduced an end-to-end goal-oriented dialog task, in which several crucial skills are tested for a dialog system to achieve the goal of restaurant reservations. In this paper, we propose a method that combines end-to-end memory networks with the abstraction of named entities and contextual numbering to make the model effective in dealing with out-of-vocabulary words and learning context in a dialog. An evaluation with DSTC6 shows that our methods can effectively improve performance when the system must generate an API call to query the knowledge base or propose options. We consider that a system incorporating our methods can be scaled up to a new domain with only a knowledge base.
Determination of Stature from the length of Cranial Sutures- A Study from Central India

Background:Skulls frequently represent the only skeletal remains of an unidentified corpse brought for forensic examination. This study aims to determine the correlation between the cadaveric supine length and the length of three cranial sutures viz. coronal, sagittal, and lambdoid. Material and Methods: A cross-sectional study was conducted in the department of forensic medicine, Gandhi Medical College, Bhopal between the period of January 2016-June 2017. A total of 500 dead bodies were examined for this study. We utilized the correlation coefficient and the linear regression methods to predict a relationship between the stature and the length of cranial sutures. Results:The age range of dead bodies brought for examination was 20 to 89 years, mean age 38.07(standard deviation 13.61) and the median age was 35. There were total of 307 males and 193 females. On statistical analysis, both the coronal and the sagittal sutures showed a positive correlation with the supine length which was statistically significant. The lambdoid suture did not show any significant correlation with supine cadaveric stature. Conclusion: With some assumptions, the supine length can be estimated from the length of cranial sutures with a fair degree of accuracy. ------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 08-07-2020 Date of Acceptance: 23-07-2020 ------------------------------------------------------------------------------------------------------------------------------------
Harnessing Evanescent Waves by Bianisotropic Metasurfaces

The exponentially decaying nature of evanescent waves renders it difficult to capture, extract and engineer the wealth of energy and information that they can carry. Utilizing the out‐of‐plane electric dipoles and in‐plane magnetic diploes produced by a bianisotropic C‐aperture metasurface, in this work, it is shown that evanescent waves can be effectively molded. More specifically, it is demonstrated that the phase, polarization state or beam profile of the emission from evanescent waves can be controlled via the orientation of C‐aperture nanostructures. The work opens a new avenue for metasurfaces to work in the critical near‐field region to efficiently harness evanescent waves, and promises many potential applications, including on‐chip free‐electron light sources, tabletop particle detectors and near‐field energy harvesting.
Enhancing the B2B Selling Process Through Social Media

This study provides insights into understanding social media utilization in the B2B selling process. More specifically, this research details how the different functional blocks of social media are leveraged to benefit the various stages of the selling process. This study adopts a multiple case study design, including six cases from technology-related Canadian firms. Overall, findings show that the functional blocks of social media are mostly leveraged in the prospecting and preapproach stages of the selling process. Furthermore, the marketing strategy of the seller firm seems to influence which functional blocks are leveraged in the process. At last, findings also show that social media should be complemented by analytical tools and traditional media to optimize the selling process with higher lead quality and to facilitate trust-building with potential and existing customers.
‘Women take care and men take charge’: The case of leadership and gender in the Public and Commercial Services Union

This article presents the findings of a case study that aimed to understand the specific leadership styles that are valued by women and men lay representatives in the Public and Commercial Services Union (PCS) and to determine the gendered implications for increasing women’s leadership and representation in trade unions. Survey responses from PCS lay representatives (reps) show the majority of women and men agreed that the leadership style they value, and that makes a good union leader, is post-heroic (communal) leadership. This approach is associated with leadership characteristics such as being helpful, sensitive and kind and are generally practised by women. This contrasts with male union leaders who are associated with a traditional, heroic (agentic) leadership style characterised by confidence, self-reliance and decisiveness. Although some differences exist that highlight gender issues, both women and men lay reps have positive attitudes towards increasing women’s representation and participation in union leadership.
Robust inference in deconvolution

Kotlarski's identity has been widely used in applied economic research based on repeated‐measurement or panel models with latent variables. However, how to conduct inference for these models has been an open question for two decades. This paper addresses this open problem by constructing a novel confidence band for the density function of a latent variable in repeated measurement error model. The confidence band builds on our finding that we can rewrite Kotlarski's identity as a system of linear moment restrictions. Our approach is robust in that we do not require the completeness. The confidence band controls the asymptotic size uniformly over a class of data generating processes, and it is consistent against all fixed alternatives. Simulation studies support our theoretical results. Deconvolution measurement error robust inference uniform confidence band C14 C57
Feature selection using simple and efﬁcient machine learning models. Case studies and software tools

Feature selection (FS) of relevant variables from the original input space is a crucial issue in Machine Learning research, especially in environmental data mining. Besides reducing the dimensionality, removing irrelevant information, increasing learning accuracy and improving the interpretability of the results, feature selection is also often used to optimize data collection, as it identiﬁes which kind of data are more important to gather. There are three fundamental classes of FS – ﬁlters, wrappers and embedding [1]. FS can be considered either as a pre-processing step or as a dynamic process integrated into the modelling procedure, which helps to reduce the prediction error and uncertainty. The present research deals with an experimental study of FS using both simulated data and monthly wind speed data in Switzerland for the year 2008 collected by the MeteoSwiss meteorological network (118 stations). The raw data were embedded into a thirteen-dimensional input feature space generated from the Digital Elevation Model [2]. To identify the relevant features to be used in the prediction of wind speed, two efﬁcient and fast machine learning models, namely Extreme Learning Machine (ELM) [3] and General Regression Neural Network (GRNN) [4], have been implemented. An exhaustive search over the thirteen-dimensional space, giving rise to the 8191 possible models, has been performed with the two algorithms for the twelve monthly datasets. Best models were selected according to the smallest root mean squared error. Subsequently, the obtained results were independently tested by applying a Random Forest model and an Anisotropic General Regression Neural Network (AGRNN). The results obtained on the wind speed dataset conﬁrm the idea that the best subset of features is changing according to the studied month/season, which agrees with a physical understanding of the phenomenon. The future research will consider an extension of the approach to higher dimensional space and forward
Seed priming with endophytes: A novel approach for future prospects

In the current scenario of climate change, numerous strategies have been employed in the area of sustainable agriculture or plant science to generate plants which can withstand various types of biotic and abiotic stresses. Seed priming has been developed as a crucial method to germinate the seed or increase plants resistance against various biotic and abiotic stresses. Seed priming with microbial inoculum, termed as ‘bio-priming’, involves the application of beneficial microbes, such as bacteria, fungi and actinomycetes to seed that enhance the germination, vigour, protection from diseases and pests leading to increase in yield. Seed priming with the use of endophytic microbial strains appears as more beneficial or stable than rhizospheric microbial strains due to better colonization adaptability and suitability under biotic and abiotic stress conditions. Microbial endophytes are symbionts dwelling within plant tissues without appearance of disease symptoms on host plant and have been recently investigated for their plant growth-promoting properties and their beneficial functions associated with plant responses under salinity, drought, temperature, heavy metal stress, and nutrient stress through different mechanisms and also provide protection from diseases and pests.
Multiscale modeling of continuous crushing of granular media : the 1 role of grain microstructure 2 3

10 Natural granular materials such as sands often possess complex microstructural features including 11 cleavage and minerals interfaces. Those features bring apparent mechanical anisotropy to particles 12 and are known to have pronounced influence on particle crushing characteristics. This paper 13 presents a multiscale simulation of continuous crushing of granular sand under one-dimensional 14 compression in consideration of particle-scale anisotropy through modeling planes of weakness 15 inside individual particles, with reference to granular materials rich in minerals and containing 16 cleavages. The multiscale modeling is based on a coupled peridynamics and non-smooth contact 17 dynamics method where peridynamics is used to model crushing of individual particles and non18 smooth contact dynamics is employed to simulate discrete granular system. Weak microstructural 19 planes are simulated by breaking a fraction of peridynamic bonds as an initial condition. 20 Simulation results show that anisotropic particles containing weak planes result in larger number 21 of fragments and exhibit relatively higher fractal dimension with respect to particle size. Particle 22 shape is found to approach a steady state profile with continuous crushing. Anisotropic particles 23 generally bear smaller sphericity, aspect ratio, elongation and flatness than those isotropic particles. 24 The anisotropy in particles seems to mitigate shape effect on particle strength and crushing energy. 25 Macromechanical yield stress of the sample is related to single particle strength monotonically but 26 the relationship appears to be non-linear when different microstructural features are involved. 27
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Skeletal stem cells (SSCs) reside in the postnatal bonemarrowand give rise to cartilage, bone, hematopoiesis-supportive stroma and marrow adipocytes indefined in vivoassays.These lineagesemerge inaspecific sequence during embryonic development and post natal growth, and together comprise a continuous anatomical system, the bone-bone marroworgan.SSCsconjoin skeletal andhematopoieticphysiology, and are a tool for understanding and ameliorating skeletal and hematopoietic disorders. Here and in the accompanying poster, we concisely discuss the biology of SSCs in the context of the development and postnatal physiology of skeletal lineages, to which their use in medicine must
Morpho-anatomical and histochemical studies on Coccinia grandis ( L . ) Voigt . ( Cucurbitaceae )

Coccinia grandis L. Voigt. Commonly known as “Ivy gourd” is a tropical plant of Cucurbitaceae. (Umamaheswari M., et.al. 2008) It is common in many countries of Asia and Africa. The present study aims at its morpho anatomy and histochemical aspects. Anatomy of plants parts has been carried out. For histochemical studies the free hand sections of leaves, stem and roots were taken and treated with the respective reagents for localizing components, viz. Alkaloids, Tannin, and Phenolic compounds in the tissues were micro-photographed and the results were tabulated. This study will enable to understand better the phytocompounds and their pharmaceutical exploitation.
VLOGA PERIFITONSKIH ALG PRI DOLOČANJU EKOLOŠKO SPREJEMLJIVEGA PRETOKA VODE V TEKOČIH VODAH THE ROLE OF PERIPHYTIC ALGAE IN THE DETERMINATION OF THE ECOLOGICALLY ACCEPTABLE FLOW IN RUNNING WATERS

ions, the physicochemical composition of water downstream of the dams is no longer defined by conditions in the upper reaches of the river, but by tributaries downstream of the catchment area. A constant flow, as well as a rare occurrence of high waters downstream of the dams has given rise to a great diversity of periphyton and to differences in the periphyton biomass here, compared with reference sites upstream of the dams.
Predicted visual sensitivity for short-wavelength light in the brood parasitic cuckoos of New Zealand

Different lineages of birds show varying sensitivity to light in the ultraviolet (UV) wavelengths. In several avian brood parasite-host systems, UV-reflectance of the parasite eggs is important in discriminating own from foreign eggs by the hosts. In turn, for parasitic females it may be beneficial to lay eggs into host clutches where eggs more closely match the parasite's own eggs. While the visual sensitivities of numerous cuckoo- and cowbird-host species have been described, less is known about those of their respective parasites. Such sensory characterization is important for understanding the mechanisms underlying potential perceptual coevolutionary processes between hosts and parasites, as well as for better understanding each species' respective visual sensory ecology. We sequenced the short wavelength-sensitive type 1 (SWS1) opsin gene to predict the degree of UV- sensitivity in both of New Zealand's obligate parasitic cuckoo species, the Shining Cuckoo (Chalcites (Chrysococcyx) lucidus) and the Long-tailed Cuckoo (Urodynamis (Eudynamis) taitensis). We show that both species are predicted to possess SWS1 opsins with maximal sensitivity in the human-visible violet portion of the short-wavelength light spectrum, and not in the UV. Future studies should focus on the (mis)matching in host-parasite visual sensitivities with respect to host-parasite egg similarity as perceived by the avian visual system and the behavioral outcomes of foreign egg rejection.
CRITICAL THRESHOLDS IN A MULTI-DIMENSIONAL NONLOCAL MODEL FOR CONSERVATION LAWS

A nonlocal model for scalar nonlinear conservation laws in arbitrary space dimensions is considered, which includes the 1-D model for radiating gases. Such an equation is shown to feature the so called critical threshold phenomena. We present a lower threshold for the breakdown of solutions and an upper threshold for the global existence of the smooth solution. The threshold criterion is shown to depend only on the relative size of the minimum velocity divergence of the initial profile and L∞ bound of the initial velocity. Finally a small scaling limit is carried out for situations where the entropy solution of the limiting equation is considered.
Group Size and Conformity in Charitable Giving: Evidence from Empirical Analysis of Japanese Online Donations

We investigate the impacts of multiple earlier donations on the amounts that subsequent donors contributed to JapanGiving, an online fundraising platform. The platform’s webpage displays amounts of the preceding five donations chronologically. We find that when the most recent three or more sequential donations are identical, a new donor will likely match the modal amount. Only the preceding two modal donations do not influence a new donor to contribute the modal amount. Our findings connect economic studies of charity and social psychology studies of conformity. Donors are more likely to choose the donation amount that more of others have chosen. 1 JSPS Research Fellow and Graduate School of Economics, Osaka University, Mihogaoka 6-1, Ibaraki city, Osaka, Japan. Email: ssasaki.econ@gmail.com I thank the Japan Society for the Promotion of Science for financial support (Grant Number 14J04581). This research would not have been possible without support from JapanGiving. I thank its founders, Daigo Sato and Takuya Kajikawa. I especially thank Fumio Ohtake for discussions, comments, and encouragement. I thank Sarah Smith, Richard Steinberg, Mark Ottoni-Wilhelm, Sera Linardi, Rene Bekkers, Brenda Gainer, Atta A. Ceesay, Takanori Ida, Takahiro Hoshino, Katsunori Yamada, Miki Kohara, Yoshiaki Nomura and Naoto Yamauchi. I also thank participants at the 8th ISTR Asia Pacific Regional Conference 2013, ARNOVA’s 42nd Annual Conference 2013, ABEF’s 7th Annual Conference 2013, the Japanese Economic Association Fall Meeting 2014, the 9th Applied Econometrics Conference 2014, the Second SPI Annual Conference 2014 and ABEF’s 8th Annual Conference 2014 as well as seminar participants at Osaka University and the University of Chicago (Science of Philanthropy Initiative webinar). All errors in this paper are my responsibility. 2