Miracle-dz/UniFAR-FTUs huggingface dataset:
Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape

The permutation symmetry of neurons in each layer of a deep neural network gives rise not only to multiple equivalent global minima of the loss function, but also to first-order saddle points located on the path between the global minima. In a network of $d-1$ hidden layers with $n_k$ neurons in layers $k = 1, \ldots, d$, we construct smooth paths between equivalent global minima that lead through a `permutation point' where the input and output weight vectors of two neurons in the same hidden layer $k$ collide and interchange. We show that such permutation points are critical points with at least $n_{k+1}$ vanishing eigenvalues of the Hessian matrix of second derivatives indicating a local plateau of the loss function. We find that a permutation point for the exchange of neurons $i$ and $j$ transits into a flat valley (or generally, an extended plateau of $n_{k+1}$ flat dimensions) that enables all $n_k! $ permutations of neurons in a given layer $k$ at the same loss value. Moreover, we introduce high-order permutation points by exploiting the recursive structure in neural network functions, and find that the number of $K^{\text{th}}$-order permutation points is at least by a factor $\sum_{k=1}^{d-1}\frac{1}{2! ^K}{n_k-K \choose K}$ larger than the (already huge) number of equivalent global minima. In two tasks, we illustrate numerically that some of the permutation points correspond to first-order saddles (`permutation saddles'): first, in a toy network with a single hidden layer on a function approximation task and, second, in a multilayer network on the MNIST task. Our geometric approach yields a lower bound on the number of critical points generated by weight-space symmetries and provides a simple intuitive link between previous mathematical results and numerical observations.
PROGRAM SLICING OF EXPLICITLY PARALLEL PROGRAMS

The main contribution of this thesis is the development of a technique for static interprocedural slicing of shared memory parallel programs. While static interprocedural slicing for sequential codes is well understood and used in a variety of applications, there are no algorithms yet developed for static interprocedural slicing of shared memory parallel programs. To facilitate the static slicing of parallel programs, a new intermediate program representation, the threaded System Dependence Graph (tSDG), is developed to encompass the parallel and worksharing constructs utilized in OpenMP. The concept of transitive dependence is redefined to include dependences caused by conflict edges in shared memory parallel programs, thus enabling interprocedural slicing of the new program representation. An algorithm for interprocedural slicing over the tSDG representation is presented. The slicing algorithm builds on the algorithms already developed for interprocedural slicing of sequential programs and the algorithms developed for intraprocedural slicing of parallel programs.
Topological states.

Topological phases are characterised by a topological invariant that remains unchanged by deformations in the Hamiltonian. Materials exhibiting topological phases include topological insulators, superconductors exhibiting strong spin-orbit coupling, transition metal dichalcogenides, which can be made atomically thin and have direct band gaps, as well as high mobility Weyl and Dirac semimetals. Devices harnessing topological electron states include topological (spin) transistors, spin-orbit torque devices, non-linear electrical and optical systems, and topological quantum bits.
High-level power estimation of VLSI systems

The goal of this paper is to present an innovative conceptual framework suitable for achieving accurate and efficient estimation of power dissipation for data-path intensive architectures described at RT and behavioral levels. The aim is to provide the designer with the capability of analyzing different solutions in the architectural design space, before the synthesis tasks. The proposed methodology addresses all the elements composing a typical data-path architecture, such as storage units, functional units and multiplexers. The paper includes experimental results demonstrating the validity of the proposed approach.
Spherical Large Intelligent Surfaces

As an emerging technology and evolution that goes beyond massive multi-input multi-output (MIMO), large intelligent surface (LIS) has gained much interest. LIS acts as an electromagnetic surface that can transmit, redirect, and receive radiating signals across its entire contiguous surface. It allows for unprecedented energy-focusing, data-transmission and terminal-positioning, and can fulfill the most grand visions for future communication systems. Earlier proposed LISs are in two-dimensional (2D), i.e., planar shapes. In this paper, we extend LISs to be three-dimensional (3D) and deployed as spherical surfaces. Compared to 2D LIS, a spherical LIS has advantages in wide coverage, simple positioning technique, and flexible deployment as reflecting surface.
RegDem: Increasing GPU Performance via Shared Memory Register Spilling

GPU utilization, measured as occupancy, is limited by the parallel threads' combined usage of on-chip resources, such as registers and the programmer-managed shared memory. Higher resource demand means lower effective parallel thread count, and therefore lower program performance. Our investigation found that registers are often the occupancy limiters. The de-facto nvcc compiler-based approach spills excessive registers to the off-chip memory, ignoring the shared memory and leaving the on-chip resources underutilized. To mitigate the register demand, this paper presents a binary translation technique, called RegDem, that spills excessive registers to the underutilized shared memory by transforming the GPU assembly code (SASS). Most GPU programs do not fully use shared memory, thus allowing RegDem to use it for register spilling. The higher occupancy achieved by RegDem outweighs the slightly higher cost of accessing shared memory instead of placing data in registers. The paper also presents a compile-time performance predictor that models instructions stalls to choose the best version from a set of program variants. Cumulatively, these techniques outperform the nvcc compiler with a 9% geometric mean, the highest observed being 18%.
The number of rooted forests in circulant graphs

In this paper, we develop a new method to produce explicit formulas for the number $f_{G}(n)$ of rooted spanning forests in the circulant graphs $ G=C_{n}(s_1,s_2,\ldots,s_k)$ and $ G=C_{2n}(s_1,s_2,\ldots,s_k,n). $ These formulas are expressed through Chebyshev polynomials. We prove that in both cases the number of rooted spanning forests can be represented in the form $f_{G}(n)=p\,a(n)^2,$ where $a(n)$ is an integer sequence and $p$ is a prescribed natural number depending on the parity of $n$. Finally, we find an asymptotic formula for $f_{G}(n)$ through the Mahler measure of the associated Laurent polynomial $P(z)=2k+1-\sum\limits_{i=1}^k(z^{s_i}+z^{-s_i}). $
Spectral Energy Distributions of Companion Galaxies to z ∼ 6 Quasars

Massive, quiescent galaxies are already observed at redshift z ∼ 4, i.e., ∼1.5 Gyr after the big bang. Current models predict them to be formed via massive, gas-rich mergers at z > 6. Recent ALMA observations of the cool gas and dust in z ≳ 6 quasars have discovered [C ii]- and far-infrared-bright galaxies adjacent to several quasars. In this work, we present sensitive imaging and spectroscopic follow-up observations, with HST/WFC3, Spitzer/IRAC, VLT/MUSE, Magellan/FIRE, and LBT/LUCI-MODS, of ALMA-detected, dust-rich companion galaxies of four quasars at z ≳ 6, specifically acquired to probe their stellar content and unobscured star formation rate. Three companion galaxies do not show significant emission in the observed optical/IR wavelength range. The photometric limits suggest that these galaxies are highly dust-enshrouded, with unobscured star formation rates SFRUV < few M⊙ yr−1, and a stellar content of M* < 1010 M⊙ yr−1. However, the companion to PJ167−13 shows bright rest-frame UV emission (F140W AB = 25.48). Its spectral energy distribution resembles that of a star-forming galaxy with a total SFR ∼ 50 M⊙ yr−1 and M* ∼ 9 × 109 M⊙. All the companion sources are consistent with residing on the galaxy main sequence at z ∼ 6. Additional, deeper data from future facilities, such as the James Webb Space Telescope, are needed in order to characterize these gas-rich sources in the first gigayear of cosmic history.
Normal approximation and confidence region of singular subspaces

This paper is on the normal approximation of singular subspaces when the noise matrix has i.i. d. entries. Our contributions are three-fold. First, we derive an explicit representation formula of the empirical spectral projectors. The formula is neat and holds for deterministic matrix perturbations. Second, we calculate the expected projection distance between the empirical singular subspaces and true singular subspaces. Our method allows obtaining arbitrary $k$-th order approximation of the expected projection distance. Third, we prove the non-asymptotical normal approximation of the projection distance with different levels of bias corrections. By the $\lceil \log(d_1+d_2)\rceil$-th order bias corrections, the asymptotical normality holds under optimal signal-to-noise ration (SNR) condition where $d_1$ and $d_2$ denote the matrix sizes. In addition, it shows that higher order approximations are unnecessary when $|d_1-d_2|=O((d_1+d_2)^{1/2})$. Finally, we provide comprehensive simulation results to merit our theoretic discoveries. Unlike the existing results, our approach is non-asymptotical and the convergence rates are established. Our method allows the rank $r$ to diverge as fast as $o((d_1+d_2)^{1/3})$. Moreover, our method requires no eigen-gap condition (except the SNR) and no constraints between $d_1$ and $d_2$.
A spatial Solow model with transport cost in an unbounded economy

In this paper we introduce capital transport cost in a unidimensionl spatial Solow model with capital-induced labor migration, considered in an unbounded domain. We show that exists a critical value for this transport cost such that: if transport cost is bigger than this critical value, economy converges to a homogeneous steady-state, and if it is smaller than this critical value, the economy develops stable economic agglomerations or cycles, depending on the parameters of the model, and provided the capital-induced labor migration is intense enough. In this way, we get a result consistent with the standard core-periphery model used in the New Economic Geography literature, but using a macroeconomic framework. JEL Classification: R12, O40.
Identifying success in the application of information and communication technology as a curriculum teaching and learning tool

This research seeks to identify generic factors that have contributed to the successful integration of information and communication technology (ICT) across the curriculum in the secondary section of an international school in Brazil. The research took a case‐study approach, focusing on one ‘successful’ department to identify characteristics which may have contributed to its uptake and development of the use of ICT. Data were collected through questionnaires and interviews. The features most strongly linked to the success of this department were the positive attitude towards ICT from the staff and their willingness to learn and venture into unfamiliar territory. The main barriers were often associated with a range of hardware issues.
DEVELOPMENT AND STANDARDIZATION OF NOVEL SIDDHA FORMULATION AATHISESHA VISHAHARA MAATHIRAI FOR THE TREATMENT OF SNAKE ENVENOMATION

Snake envenomation is considered to be one of the most important global health issues and snakebite remains an underestimated cause of accidental death in modern India. Because a large proportion of global totals of snakebites arise from India. It is estimated that in India alone, there are more than 2, 00,000 venomous bites per year, of which 35,000–50,000 are fatal. Globally, traditional healers are practicing siddha preparations to cure snake envenomations. Siddha system of medicine has number of formulations which are effective against snake bite. One such novel formulation is Aathisesha vishahara maathirai (AVM), however, the documentation on standardization of such formulation is very minimal, as a measure of understanding the current need of drug standardization the present study was undertaken to prepare and systematically standardize the formulation AVM by sophisticated instrumentation techniques as per AYUSH guidelines. The results obtained from physiochemical analysis clearly reveals that total ash value of AVM is about 8.40% in which acid insoluble ash is 0.35%. Extraction value of drugs renders most significant information about partition of the active component the results of extract value study shows that alcohol soluble extract of AVM is 5.89% and water soluble extract is 6.99%. Similarly disintegration time of AVM is 21 mins and uniformity of weight is about 0.704 gms. Phytochemical evaluation of AVM shows the presence of bio-active phyto components such as alkaloids, terpenoids, steroids, tannins, polyphenols and proteins. Results of ICPMS analysis reveals the WORLD JOURNAL OF PHARMACY AND PHARMACEUTICAL SCIENCES SJIF Impact Factor 6.041 Volume 6, Issue 1, 900-917 Research Article ISSN 2278 – 4357 *Corresponding Author Dr. S. Vanathi Post Graduate Department of Nanju Noolum Maruthuva Neethi Noolum, National Institute of Siddha, Tambaram Sanatoruim, Chennai 600047, Tamilnadu, India. Article Received on 26 October. 2016, Revised on 16 Nov. 2016, Accepted on 06 Dec. 2016 DOI: 10.20959/wjpps20171-8349
The Effect of Supplementary Irrigation on Leaf Area, Speci c Leaf Weight, Grain Yield and Water Use Ef ciency in Durum Wheat (Triticum durum Desf.) Cultivars

The main aim of the present study is to understand the impact of irrigation on Leaf area, SpeciŞc Leaf Weight, Grain yield and Water use efŞciency. Ten durum wheat (Triticum durum Desf.) genotypes of diverse origin were evaluated under two conditions (Irrigated and non irrigated conditions). After flowering, ten flag leaf of each plot were cut for measuring the length, width and mass of leaf. Leaf area (LA) while SpeciŞc Leaf Weight (SLW) was measured mathematically . Water use efŞciency of yield was calculated using the following equation: WUE evapo-transpired water. In this study the difference between Leaf area under stressed and non stressed condition equal 17.24%. In addition, water stress reduced the speciŞc leaf weight (41.86%). Irrigation condition affects positively the grain yield (12.42%) and negatively water use efŞciency (12.11%). WUEwas the highest with a deŞcit irrigation consisting of two-thirds of the water required at full irrigation (i.e. WUEfull irrigation was lower)
Efficient Data Authentication

We address the problem of authenticating data in untrusted, or adversarial, computing environments: when the distributor of the data is not the source of the data, and thus is not trusted by the end-user, how can data received be proven authentic? Data authentication constitutes a fundamental problem in information security and an interesting new dimension in data management and data structure design. At the same time, the problem captures the security needs of many computing applications that exchange and use sensitive information in hostile distributed environments and its importance increases given the current trend in modern system design towards decentralized architectures with minimal trust assumptions. Solutions should not only be provably secure, but efficient and easily implementable. This dissertation presents an extensive study of data authentication. We examine the problem for both structured and unstructured data, provide formal definitions, and design new efficient techniques for authenticating general classes of query problems, such as graph and geometric search problems, and data streams. We also study the complexity of data authentication, deriving lower bounds for the important special case of authenticating set membership queries, and design new optimal constructions. Moreover, we provide a new general framework for authenticating any query over structured data, which decouples the answer-validation and answer-generation procedures. Finally, we design totally decentralized authentication structures that provide authentication for data distributed over any peer-to-peer overlay network.
Three-Dimensional Porous LiFePO4: Design, Architectures and High Performance for Lithium Ion Batteries

The olivine-structured lithium ion phosphate (LiFePO4) is one of the most competitive candidates of cathode materials for the sustainable lithium ion battery (LIB) systems. However, the major drawback of olivine-structured LiFePO4 is the poor intrinsic electronic and lithium ion conductivities arising from the lack of mixed valency and the one- dimensional lithium ion diffusion, which influence its high electrochemical performance, especially high rate capability. Nano-structured LiFePO4 materials offer a potential solution to enhance surface-to-volume ratio and reduce transport length for mobile charges, but they have high interfacial energy, aggregate easily and need more agglutinant in electrode, which seriously impact the electrochemical performance and practical applications of LiFePO4. Furthermore they con- tinue to experience limitations as energy and power requirements escalate with the evolution of technology. Recently, three-dimensional (3D) porous LiFePO4 architectures have been widely designed and studied. This has led to increased in- terest in the development of cathode materials and processing capabilities necessary to enable high-performance, next- generation LIB system that can deliver large amounts of energy at high rates. In this review, we focus on 3D porous LiFePO4 architectures for high power LIBs, summarize and discuss its structure, synthesis, electrochemical behaviors, mechanism, and the problems encountered in its application. The major goal is to highlight the recent progress of 3D po- rous LiFePO4 architectures with high rate capability, high energy density and application.
5 G-MLab : Developing a Wireless Reliability Measurement Framework

5G, the fifth generation radio access network, is planned to be introduced in the year 2020. With 5G for the first time the emphasis of wireless communication has shifted from high data rates to low latency, scalability, and high reliability. High reliability will allow 5G to be used in safety-critical systems. Until now wireless communication has rarely been used for safety-critical communication. In applications such as automated driving, industry 4.0 and smart grids even short losses of the ability to communicate can lead to high costs of repair after accidents, missed production or blackouts. In extreme cases even lives may be at stake. Therefore, it will be necessary to not only trust the network operator to provide high reliability, but to measure and monitor the reliability independently. The required reliability is usually defined as 99.9% or 99.999%. To detect these small, but important, differences, thousands of measurements are necessary for each location. Additionally, automotive and industrial wireless environments are highly variable in time and space due to moving vehicles and machines. Thus, it is necessary to to make many measurements spread out in space and time. This results in a total number of measurements that is practically impossible to achieve using naive automated measurements. Therefore, no methods have been developed yet that can measure the reliability of wireless communication systems. In this paper we describe how we are developing methods to measure the reliability of wireless communication networks. The goal is to apply the methods to 5G, but the results will be applicable to most other wireless networks (for example IEEE 802.11 WiFi). First we define two reference scenarios: an automotive and an industrial scenario. The scenarios describe the situations in which we will later demonstrate how our methods measure the reliability of wireless communication. By developing the scenarios with domain experts, we gain insight for which applications reliable communication is most important. This insight allows us to later test and demonstrate the usefulness of our methods in settings where they are most needed. We develop measurement methods using an incremental approach: (1) Develop a method, (2) test the method, and (3) improve the method or develop a new method. To get an initial feeling how complex the implementation of a measurement method is, we simulate the first steps. Once the initial assessment deems the methods feasible for practice, we implement it in our laboratory setup in later steps. After we refined the methods in the laboratory, we will test how well they perform in the two reference scenarios. This paper describes our approach to develop methods to measure reliability in wireless systems. Additionally, it provides preliminary results from simulations and laboratory measurements. The methods we will develop using the approach described in this paper will allow measuring and monitoring the reliability of wireless networks. This will increase the trust in wireless communication and thereby allow many visionary uses.
Deep Soft Multilabel Reference Learning 3 . 1 . Problem formulation and Overview

Although unsupervised person re-identification (RE-ID) has drawn increasing research attentions due to its potential to address the scalability problem of supervised RE-ID models, it is very challenging to learn discriminative information in the absence of pairwise labels across disjoint camera views. To overcome this problem, we propose a deep model for the soft multilabel learning for unsupervised RE-ID. The idea is to learn a soft multilabel (real-valued label likelihood vector) for each unlabeled person by comparing the unlabeled person with a set of known reference persons from an auxiliary domain. We propose the soft multilabel-guided hard negative mining to learn a discriminative embedding for the unlabeled target domain by exploring the similarity consistency of the visual features and the soft multilabels of unlabeled target pairs. Since most target pairs are cross-view pairs, we develop the cross-view consistent soft multilabel learning to achieve the learning goal that the soft multilabels are consistently good across different camera views. To enable effecient soft multilabel learning, we introduce the reference agent learning to represent each reference person by a reference agent in a joint embedding. We evaluate our unified deep model on Market-1501 and DukeMTMC-reID. Our model outperforms the state-of-theart unsupervised RE-ID methods by clear margins. Code is available at https://github.com/KovenYu/MAR.