Miracle-dz/UniFAR-FTUs huggingface dataset:
From Low Probability to High Confidence in Stochastic Convex Optimization

Standard results in stochastic convex optimization bound the number of samples that an algorithm needs to generate a point with small function value in expectation. More nuanced high probability guarantees are rare, and typically either rely on "light-tail" noise assumptions or exhibit worse sample complexity. In this work, we show that a wide class of stochastic optimization algorithms for strongly convex problems can be augmented with high confidence bounds at an overhead cost that is only logarithmic in the confidence level and polylogarithmic in the condition number. The procedure we propose, called proxBoost, is elementary and builds on two well-known ingredients: robust distance estimation and the proximal point method. We discuss consequences for both streaming (online) algorithms and offline algorithms based on empirical risk minimization.
On the evaluation of the norm of an integral operator associated with the stability of one-electron atoms

The norm of an integral operator occurring in the partial wave decomposition of an operator B introduced by Brown and Ravenhall in a model for relativistic one-electron atoms is determined. The result implies that B is non-negative and has no eigenvalue at 0 when the nuclear charge does not exceed a speciﬁed critical value.
Failure of low-level laser therapy to boost healing of venous leg ulcers in surgically and conservatively treated patients

Summary Objective: To evaluate in a randomized open-label clinical trial the ability of adjuvant low-level laser therapy (LLLT) to improve healing of venous leg ulcers in surgically and conservatively treated patients. Patients and methods: Eighty three patients with venous leg ulcers were included in this study. Patients in groups 1 and 2 were treated surgically while patients in groups 3 and 4 were treated conservatively. Patients in groups 1 and 3 were additionally treated with the LLLT (GaAlAs laser, 810 nm, 4 J/cm2, 65 mW) once daily, 6 times a week for 7 weeks. Results: After therapy comparison of completely healed wounds, statistically significant differences were seen between groups 1 and 3 (p=0.02), 1 and 4 (p= 0.02), 2 and 3 (p= 0.02), 2 and 4 (p=0.02) in favor of groups 1 and 2. Comparison of the relative change of wound total surface area indicated statistically significant differences between groups 1 and 3 (p=0.002), 1 and 4 (p=0.002), 2 and 3 (p=0.002), 2 and 4 (p=0.002) in favor of groups 1 and 2. Comparison of the other parameters also demonstrated a more efficient therapy effects in groups 1 and 2 than in group 3 and 4. There were no statistical differences in all examined parameters between groups 1 and 2 (p>0.05), 3 and 4 (p>0.05). Conclusion: The application of the LLLT does not enhance healing of venous leg ulcers in surgically and conservatively treated patients. A well conducted surgical operation is much more efficient than conservative pharmacological procedures.
Automatic Summarization of Spacecrafts’ House-keeping Data

Early detection and treatment of system faults is significantly important for managing any spacecraft missions. The house-keeping data (HK data) telemetrated from spacecrafts to the ground stations is a major information source to monitor the status of the spacecrafts. Because HK data is generally so huge and primitive that operators can hardly grasp the whole status of spacecrafts, it will be of great help to make computers process the HK data, check their status, and then reduce the burden on the human operators. While many approaches to detect anomalies of spacecrafts which require a tremendous amount of priori knowledge are proposed, we intend to make full use of stored HK data, and especially, focus on automated summarization of HK data. To summarize HK data, we pay much attention to two kinds of “changes”, or event patterns and mode change points. In this paper, we describe a method for detecting event patterns and mode change points respectively, and demonstrate how effective our approach is by applying it to the actual HK data of ETS-VII.
Opening up the politics of standard setting through discourse theory: the case of IFRS for SMEs

Purpose The purpose of this paper is to investigate an element of the internal politics of standard setting by reference to the International Accounting Standards Board’s (IASB) movement to the International Financial Reporting Standard for Small and Medium-Sized Entities (IFRS for SMEs). The authors examine the politics of the IASB’s expertise in technocratic governance by focussing on how the IASB defined SMEs, gave the standard a title and issued a guide for micro-entities. Design/methodology/approach The narrative case study focusses on central “moments” in the development of IFRS for SMEs. The authors employ Laclau and Mouffe’s condensation, displacement and overdetermination to illustrate embedded politics in articulating IFRS for SMEs. Findings The authors extend literature on the internal politics of standard setting, such as agenda setting, by examining the condensing of disagreements between experts and political pressures and processes into central decision moments in IFRS for SMEs. The authors illustrate these moments as overdetermined, manifesting in an act of displacement through the production of a micro-entity guide. This form of politics is hidden due to the IASB’s attempt to protect their technocratic neutrality through fixing meaning. Originality/value The authors make three contributions: first, overdetermination through condensation and displacement illustrates the embedded nature of politics in regulatory settings, such as the IASB. Second, the authors provide a theoretical explanation of the IASB’s movement from listed entities to IFRS for SMEs, drawing on Laclau and Mouffe. Third, the authors reinforce the necessity of interrogating the internal politics of standard setting to challenge claims of technocracy.
Characterization of Multi Crystalline PV Modules under Standard Test Conditions and its Comparison with other Module Types

Photovoltaic modules based on the relatively high efficiency crystalline technology are gaining importance in the photovoltaic market. Improving module performance is driven by a focus on lifetime yields and requirements of space – constraints sites. The materials used not only in thin film technologies but also crystalline pose problems in terms of measuring how much power is generated under STC. The fact that the modules power rates vary depends both on the amount of time they have been exposed to the sun and on their history of sunlight exposure in order to know the current state of the module. It is necessary to determine an easily accomplishable testing method that ensures the repeatability of the measurements of the power generated. This is essential because in order to have a reliable sample of the PV module population of a large PV plant, a huge no of modules must be measured. This paper shows different tests performed on different commercial crystalline PV modules both multi and mono, in order to find the best way to obtain measurements. A correlation was tested between sun exposure and power measured. A method for obtaining indoor measurements that takes periods of sunlight exposure into account is proposed. Also, temperature and irradiance coefficients were also determined for different technologies in order to obtain accurate measurements. Tests are operated in outdoor exposure and natural sunlight located in Gurgaon Region of Haryana (India) as specific composite climate environment, characterized by high irradiation and temperature levels.
Thermodynamic Function Of Life

Darwinian Theory depicts life as being overwhelmingly consumed by a fight for survival in a hostile environment. However, from a thermodynamic perspective, life is a dynamic, out of equilibrium process, stabilizing and coevolving in concert with its abiotic environment. The living component of the biosphere of greatest mass, the plants and cyanobacteria, are involved in the transpiration of vast amounts of water. Transpiration is part of the global water cycle, and it is this cycle that distinguishes Earth from its apparently life barren neighboring planets, Venus and Mars. The water cycle, including the absorption of sunlight in the biosphere, is by far the greatest entropy producing process occurring on Earth. Life, from this perspective, can therefore be viewed as performing an important thermodynamic function; acting as a dynamic catalyst by aiding process such as the water cycle, hurricanes, and ocean and wind currents to produce entropy. The role of animals in this view is that of unwitting but dedicated servants of the plants and cyanobacteria, helping them to grow and to spread into initially inhospitable areas.
Cloning and characterization of a novel oocyte-specific gene Fbos encoding an F-box protein in rainbow trout (Oncorhynchus mykiss)

Cloning and characterization of a novel oocyte-specific gene Fbos encoding an F-Box protein in rainbow trout (Oncorhynchus mykiss) Lei Wang Oocyte-specific genes play critical roles in oogenesis, folliculogenesis and early embryonic development. Through analysis of expressed sequence tags (ESTs) from a rainbow trout oocyte cDNA library, we identified a novel transcript which is represented by multiple ESTs derived only from the oocyte cDNA library. Analysis of tissue distribution of the novel Fbos gene by reverse transcription polymerase chain reaction revealed that the novel gene is only expressed in unfertilized oocytes but not in 10 somatic tissues examined. Northern blot analysis showed the transcript size is approximately 2.1 kb. The full-length cDNA sequence for the novel gene Fbos was obtained by assembly of sequences from the EST clones and a 5’end sequence from a 5’RACE product. The complete cDNA is 1966 bp in length containing an open reading frame, which encodes a predicted protein of 514 amino acids. The amino acid sequence does not share homology with any known proteins in the NCBI databases. However, a search of the Pfam protein database revealed that the protein contains an F-box motif at the N-terminus, indicating that this novel oocyte-specific protein is a member of the rapidly expanding family of F-box proteins. F-box proteins are components of ubiquitinligase complexes, in which they bind substrates for ubiquitin-mediated proteolysis. F-box proteins have also been associated with cellular functions such as signal transduction and regulation of the cell cycle. Real time PCR analysis of the mRNA expression of the novel gene during oogenesis and early embryogenesis demonstrated that the expression of the novel gene is extremely high during early previtellogenesis and decreases dramatically after fertilization. This result is confirmed by in situ hybridization which showed that the novel transcript is highly abundant in early previtellogenic oocytes. Western blot analysis using antibodies generated against a synthetic peptide of the novel protein detected a protein band of ~51 kDa in a protein sample prepared from oocytes. The specific expression of this gene in oocyte and its developmental pattern of expression suggest a role for this novel gene in the regulation of early oocyte or follicle development.
Predicting the Image Propagation Path in Online Social Networks

Predicting the popularity of content is important and intriguing for both users and hosts of social media sites, such as Facebook, Google+, Instagram, Twitter, and Pinterest. Existing approaches for popularity prediction have largely focused on predicting a single metric, like the total number of comments, likes or shares of posts. We instead propose to learn and predict the entire diffusion path of an image in a social network. To this end, we design a tree-structured long short-term memory (LSTM) network, dubbed as Diffusion-LSTM. By combining user social features and image features together with the encoded diffusion path history stored in an explicit memory cell, our Diffusion-LSTM is able to keep track of the posting history of an image and predicts its diffusion path better than alternate baselines that rely only on either image or social features, or do not encode the posting history. Our model generalizes to new users who are not included in the training set, through a mapping between individual users and user prototypes. Finally, we also demonstrate that our Diffusion-LSTM can generate meaningful diffusion trees that closely resemble ground-truth trees.
ApGAN: Approximate GAN for Robust Low Energy Learning From Imprecise Components

A Generative Adversarial Network (GAN) is an adversarial learning approach which empowers conventional deep learning methods by alleviating the demands of massive labeled datasets. However, GAN training can be computationally-intensive limiting its feasibility in resource-limited edge devices. In this paper, we propose an approximate GAN (ApGAN) for accelerating GANs from both algorithm and hardware implementation perspectives. First, inspired by the binary pattern feature extraction method along with binarized representation entropy, the existing Deep Convolutional GAN (DCGAN) algorithm is modified by binarizing the weights for a specific portion of layers within both the generator and discriminator models. Further reduction in storage and computation resources is achieved by leveraging a novel hardware-configurable in-memory addition scheme, which can operate in the accurate and approximate modes. Finally, a memristor-based processing-in-memory accelerator for ApGAN is developed. The performance of the ApGAN accelerator on different data-sets such as Fashion-MNIST, CIFAR-10, STL-10, and celeb-A is evaluated and compared with recent GAN accelerator designs. With almost the same Inception Score (IS) to the baseline GAN, the ApGAN accelerator can increase the energy-efficiency by <inline-formula><tex-math notation="LaTeX">$\sim 28.6\times$</tex-math><alternatives><mml:math><mml:mrow><mml:mo>∼</mml:mo><mml:mn>28</mml:mn><mml:mo>. </mml:mo><mml:mn>6</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="roohi-ieq1-2949042.gif"/></alternatives></inline-formula> achieving 35-fold speedup compared with a baseline GPU platform. Additionally, it shows 2.5× and 5.8× higher energy-efficiency and speedup over CMOS-ASIC accelerator subject to an 11 percent reduction in IS.
Patterns of Degenerative Joint Disease among males anD females at WinDover ( 8 Br 246 ) anD their relationshiP to grave gooDs

In 1982, during the construction of a housing project in east central Florida, a backhoe operator removing earth from the rim of a pond noticed a pale object in the spoil heap. That object was the first of 168 well-preserved individuals that were later excavated over three field seasons from the site now known as Windover (8BR246), an Archaic mortuary pond used for the interment of the dead. Dated to over 7,000 BP (Doran and Dickel 1988), the remains from Windover have afforded genetic, isotopic, paleobotanical, mortuary, and bioarchaeological analyses that have shed light on life and health during Florida’s Archaic period (Doran et al. 1986; Smith et al. 2002; Wentz et al. 2006; Tuross et al. 1994; Dickel 2002; Wentz 2006). The exceptional preservation also provided for a large assortment of grave goods, one of the largest and most ancient assemblages of textiles in North America (Andrews et al. 2002), and preserved human brain matter from 91 crania. In 2006, a doctoral dissertation completed by the author applied the Western Hemisphere Health Index (Steckel and Rose 2002) to the Windover population to assess levels of pathology in a hunter/gatherer population. During the course of that research, data on occurrences of degenerative joint disease (DJD) revealed variation in patterns of involvement between adult males and females. An earlier analysis of mortuary patterns based on grave goods (Hamlin 2001) assessed the role of gender and task division among the Windover population. The patterns of DJD were then compared and contrasted with task division based on mortuary analysis in order to interpret behavior within this ancient population.
Video Processing Based Decision Making and Learning in Lawn Tennis

Object tracking, in the last couple of years, has evolved as an area of one of the most active research in computer vision, particularly because of the developing significance of visual surveillance for the purpose of security. Object tracking could be defined as a general framework that comprises various distinctive computer vision projects that aims to track, recognize, classify and characterize objects of interest from sequences of image, and on the following level to comprehend and explain the behaviour of these objects. The final objective in designing brilliant object tracking systems is to take place of the current passive surveillance and to uproot, or if nothing else, minimize the requirement for an individual observer to control and analyze the visual data. In the present day environment the use of internet has grown tremendously. The use of internet is everywhere, in entertainment, learning e-commerce etc. This paper, presents a lawn tennis system for foreground, background and object detection system. The system can be used for lawn tennis coaching, player and ball tracking. Thus the presented system can also be used for line calls and tracing of Aces. The presented system is also able to detect shadows which are very effective in TV referrals.
C O ] 2 0 D ec 2 01 8 Almost pary Sequences

In this paper we study almost p-ary sequences and their autocorrelation coefficients. We first study the number l of distinct out-of-phase autocorrelation coefficients for an almost p-ary sequence of period n + s with s consecutive zero-symbols. We prove an upper bound and a lower bound on l. It is shown that l can not be less than min{s, p, n}. In particular, it is shown that a nearly perfect sequence with at least two consecutive zero symbols does not exist. Next we define a new difference set, partial direct product difference set (PDPDS), and we prove the connection between an almost p-ary nearly perfect sequence of type (γ1, γ2) and period n + 2 with two consecutive zero-symbols and a cyclic (n+ 2, p, n, n−γ2−2 p + γ2, 0, n−γ1−1 p + γ1, n−γ2−2 p , n−γ1−1 p ) PDPDS for arbitrary integers γ1 and γ2. Then we prove a necessary condition on γ2 for the existence of such sequences. In particular, we show that they don’t exist for γ2 ≤ −3.
Comparative Study of Linear Interaction Analysis and DNS for Shock-Vorticity Interaction: Scaling of Non-Linear Terms

Interaction of shock waves with turbulence is a complex problem in high-speed flows. Linear interaction analysis (LIA) is a theoretical tool used to predict the shock-induced turbulence amplification. It is based on the elementary interaction of a two-dimensional disturbance wave with a normal shock. In this work, we assess the accuracy of LIA when compared to high-order numerical simulation of shock-vorticity wave interaction. We present results for a range of upstream wave amplitudes and orientations, at different shock Mach numbers. The deviation between LIA and DNS is, as expected, a strong function of wave inclination angle and mean flow Mach number. We perform secondorder error analysis using Rankine-Hugoniot relations to find scaling parameters that can characterize these deviations. We find that the deviations scale with the square of the sine of the downstream vorticity wave angle at a given Mach number and with the square of the mean compression ratio across the shock at a given upstream incidence angle.
ASSESSING PROTEIN MODELS: AN EVALUATION OF THE PERFORMANCE OF DIFFERENT SCORE TYPES

We examine the performance of different scoring schemes for the evaluation of structural models of proteins. The scores investigated include knowledge based potentials, secondary structure prediction and spatial compactness of the alignment. We find that the most discriminative scores are alignment score and secondary structure score. The alignment score is composed of knowledge based potentials and amino acid substitution scores. Using these scores, a coverage of approximately 30% is obtained for error rates below 1%.
Preconditioning of mesenchymal stem cells by three-dimensional culture system

The Research Center for Radiation Emergency Medicine is aimed at proposing and providing the best possible treatment methods to anyone involved in radiation accidents, anytime and anywhere. All of our efforts are made to attain this ultimate goal. Specifically, we are focusing on three projects (Fig.1). The first project is directed toward the establishment of the most appropriate methodologies for evaluating radiation exposure, especially from contamination with actinides accompanied by trauma. The term “actinide” refers to 14 heavy-metal elements (atomic numbers 90103) with unique characteristics. The second project is aimed at exploring and supplying effective drugs to reduce the radiotoxicity and metallic toxicity of internally contaminated actinides. In Japan, NIRS is the only institution which is authorized to perform these two research projects using actinides including uranium and plutonium. The third project is targeted at a possible application of mesenchymal stem cells (MSCs) as regenerative medicine to treat radiation exposure injuries. MSCs can differentiate into various normal tissues and support regeneration of damaged tissues. Tissue regeneration failure is a characteristic of radiation injury, and therefore, the application of MSCs to treat this injury is plausible. 1. Research project to evaluate radiation exposure Precise evaluation of radiation exposure in radiation accidents is essential to treat patients and provide their prognosis. Evaluation of radiation exposure dose is difficult, especially in the case of internal contamination by actinides (Fig.2). Actinides, including uranium and plutonium, have unique characteristics; they are mostly alpha emitters and have long effective half-lives in the body. Alpha particles from the actinides are easily attenuated in water. This should be taken into account when counting for an actinide wound using conventional alpha detectors, such as a ZnS (Ag) survey meter. The activity determination of the actinides is difficult especially in the case of traumatic skin lesions with oozing blood. A new technique for the actinide wound counting is thus highly required in radiation emergency medicine. Chromosomal analysis is also a useful method for evaluating ra-
NDP: rethinking datacenter networks and stacks two years after

The key goals of datacenter networks are to simultaneously provide wire-level latency for RPC-style applications and high-throughput for network-bound applications such as storage. Folded Clos networks [1, 11] are used in datacenters worldwide; such networks use many cheap commodity switches to provide the illusion of a big non-blocking switch to all hosts in a datacenter, offering many paths between any two pairs of hosts.
A process orientation for word-of-mouth referrals

The traditional word-of-mouth referral model suggests that people talk to others within their social network; who in turn talk to other people within their social networks; inferring that the communication extends outwards from the original person at an exponential rate of growth. However, as our understanding of social network theory, communication and consumer behaviour has improved, is it time to update the traditional activity based word-of-mouth referrals model to a more process orientated model? This conceptual paper provides a review of the extant literature on word-of-mouth referrals importance for firms and suggests a new model for word-of-mouth referrals.