Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Binary Subspace Learning on large-scale cross media data

Due to the ubiquitous existence of large-scale data in today's real-world applications including learning on cross media data, we propose a semi-supervised learning method named Multiple Binary Subspace Regression (MBSR) for cross media data classification. In order to mine the common features among the data with multiple modalities, we project the original cross-media data into the same low-rank representation simultaneously by mapping to the corresponding subspaces for dimension reduction. All the subspaces are set to be binary, which only involve the addition operations and omit the multiplication operations in the subsequent computation owing to the good property of the binary values. The dimension reduction to a binary subspace and the classification on this subspace are also optimized simultaneously leading to a semi-supervised model. For dealing with large-scale data, our learning method is easily implemented to run in a MapReduce-based Hadoop system. Empirical studies demonstrate its competitive performance on convergence, efficiency, and scalability in comparison with the state-of-the-art literature.
Influence of Climate Warming on Arctic Mammals? New Insights from Ancient DNA Studies of the Collared Lemming Dicrostonyx torquatus

Background Global temperature increased by approximately half a degree (Celsius) within the last 150 years. Even this moderate warming had major impacts on Earth's ecological and biological systems, especially in the Arctic where the magnitude of abiotic changes even exceeds those in temperate and tropical biomes. Therefore, understanding the biological consequences of climate change on high latitudes is of critical importance for future conservation of the species living in this habitat. The past 25,000 years can be used as a model for such changes, as they were marked by prominent climatic changes that influenced geographical distribution, demographic history and pattern of genetic variation of many extant species. We sequenced ancient and modern DNA of the collared lemming (Dicrostonyx torquatus), which is a key species of the arctic biota, from a single site (Pymva Shor, Northern Pre Urals, Russia) to see if climate warming events after the Last Glacial Maximum had detectable effects on the genetic variation of this arctic rodent species, which is strongly associated with a cold and dry climate. Results Using three dimensional network reconstructions we found a dramatic decline in genetic diversity following the LGM. Model-based approaches such as Approximate Bayesian Computation and Markov Chain Monte Carlo based Bayesian inference show that there is evidence for a population decline in the collared lemming following the LGM, with the population size dropping to a minimum during the Greenland Interstadial 1 (Bølling/Allerød) warming phase at 14.5 kyrs BP. Conclusion Our results show that previous climate warming events had a strong influence on genetic diversity and population size of collared lemmings. Due to its already severely compromised genetic diversity a similar population reduction as a result of the predicted future climate change could completely abolish the remaining genetic diversity in this population. Local population extinctions of collared lemmings would have severe effects on the arctic ecosystem, as collared lemmings are a key species in the trophic interactions and ecosystem processes in the Arctic.
Cellular and molecular phenotypes depending upon the RNA repair system RtcAB of Escherichia coli

RNA ligases function pervasively across the three kingdoms of life for RNA repair, splicing and can be stress induced. The RtcB protein (also HSPC117, C22orf28, FAAP and D10Wsu52e) is one such conserved ligase, involved in tRNA and mRNA splicing. However, its physiological role is poorly described, especially in bacteria. We now show in Escherichia coli bacteria that the RtcR activated rtcAB genes function for ribosome homeostasis involving rRNA stability. Expression of rtcAB is activated by agents and genetic lesions which impair the translation apparatus or may cause oxidative damage in the cell. Rtc helps the cell to survive challenges to the translation apparatus, including ribosome targeting antibiotics. Further, loss of Rtc causes profound changes in chemotaxis and motility. Together, our data suggest that the Rtc system is part of a previously unrecognized adaptive response linking ribosome homeostasis with basic cell physiology and behaviour.
Performance Enhanced for CryptDB Based on AES-NI Acceleration

CryptDB is a database management system that provides the capability of executing SQL queries over encrypted data with a series of encryption algorithms to support SQL operations. However, these encryption algorithms incur a high system overhead, in which the AES algorithm is the most frequently used one. In this paper, we accelerate the CryptDB by substituting the ASE to a new encryption instruction set AES-NI. Evaluations prove that our acceleration can improve the performance for typical OLTP workloads YCSB under the conditions of caching the query by 3~10% in comparison with original CryptDB.
Zazen and cardiac variability.

OBJECTIVE This study examined the effects of "tanden breathing" by Zen practitioners on cardiac variability. Tanden breathing involves slow breathing into the lower abdomen. METHODS Eleven Zen practitioners, six Rinzai and five Soto, were each studied during 20 minutes of tanden breathing, preceded and followed by 5-minute periods of quiet sitting. During this time, we measured heart rate and respiration rate. RESULTS For most subjects, respiration rates fell to within the frequency range of 0.05 to 0.15 Hz during tanden breathing. Heart rate variability significantly increased within this low-frequency range but decreased in the high-frequency range (0.14-0.4 Hz), reflecting a shift of respiratory sinus arrhythmia from high-frequency to slower waves. Rinzai practitioners breathed at a slower rate and showed a higher amplitude of low-frequency heart rate waves than observed among Soto Zen participants. One Rinzai master breathed approximately once per minute and showed an increase in very-low-frequency waves (<0.05 Hz). Total amplitude of heart rate oscillations (across frequency spectra) also increased. More experienced Zen practitioners had frequent heart rhythm irregularities during and after the nadir of heart rate oscillations (ie, during inhalation). CONCLUSIONS These data are consistent with the theory that increased oscillation amplitude during slow breathing is caused by resonance between cardiac variability caused by respiration and that produced by physiological processes underlying slower rhythms. The rhythm irregularities during inhalation may be related to inhibition of vagal modulation during the cardioacceleratory phase. It is not known whether they reflect cardiopathology.
The problem of synthetically generating IP traffic matrices: initial recommendations

There exist a wide variety of network design problems that require a traffic matrix as input in order to carry out performance evaluation. The research community has not had at its disposal any information about how to construct realistic traffic matrices. We introduce here the two basic problems that need to be addressed to construct such matrices. The first is that of synthetically generating traffic volume levels that obey spatial and temporal patterns as observed in realistic traffic matrices. The second is that of assigning a set of numbers (representing traffic levels) to particular node pairs in a given topology. This paper provides an in-depth discussion of the many issues that arise when addressing these problems. Our approach to the first problem is to extract statistical characteristics for such traffic from real data collected inside two large IP backbones. We dispel the myth that uniform distributions can be used to randomly generate numbers for populating a traffic matrix. Instead, we show that the lognormal distribution is better for this purpose as it describes well the mean rates of origin-destination flows. We provide estimates for the mean and variance properties of the traffic matrix flows from our datasets. We explain the second problem and discuss the notion of a traffic matrix being well-matched to a topology. We provide two initial solutions to this problem, one using an ILP formulation that incorporates simple and well formed constraints. Our second solution is a heuristic one that incorporates more challenging constraints coming from carrier practices used to design and evolve topologies.
Evaluation of syllable stress using single class classifier

Evaluation of syllable stress in speech utterances is an important and challenging task in the area of speaker evaluation. In this paper, we propose a method to classify correct utterances of English words based on the evaluation of the lexical syllable stress pattern. Here we use only correctly stressed utterances of the words as training samples since a statistically signiﬁcant pool of incorrectly stressed utterances is difﬁcult to obtain. The underlying assumption here is that the correct utterances of a word form a compact cluster or a collection of compact clusters (with speaker dependent variations) in a suitably chosen multi-dimensional attribute space. We experimentally demonstrate the effectiveness of the proposed method on several English words and also compare with the standard classiﬁers where samples from both correct and incorrect utterances were used.
Visual recognition of driver hand-held cell phone use based on hidden CRF

In this paper, we propose an automatic system that recognizes driver's abnormal behavior, i.e. cell phone use. Driver's actions are captured using a camera mounted above the dash board. Then the observed features are input into a Hidden Conditional Random Fields (HCRF) model. To incorporate long range dependencies, features are collected within a local window from neighbor sites. We evaluate the presented algorithm on the real video segments, and the results show that the system can successfully recognize the behavior.
Role of Surface Ligand Chemistry on Shape Evolution and Optoelectronic Properties of Direct Band Gap Semiconductors

Author: McLeod, Meghan, Teunis. PhD Institution: Purdue University Degree Received: August 2017 Title: Role of Surface Ligand Chemistry on Shape Evolution and Optoelectronic Properties of Direct Band Gap Semiconductors Major Professor: Rajesh Sardar The expansion of the applications of direct band gap semiconductor nanocrystals (NCs) has been a result of the control colloidal synthetic methods offer on the optoelectronic properties. These properties are readily controlled by the surface chemistry and even a small change in the surface passivating ligand can show profound effects. Furthermore, the choice of surface passivating ligand also impacts the NC shape evolution, which in turn influence the surface area, quantum yield, and charge transport properties that are critical to optimize device fabrication. In this dissertation, the unique aspects of surface chemistry that control both NC shape evolution and optoelectronic properties are investigated. We began by investigating how surface chemistry controls the shape evolution of methyl ammonium lead bromide (CH3NH3PbBr3) perovskite NCs. In addition to the surface passivating ligand, the reaction temperature and solvent system were also examined. Through a series of control experiments, the critical parameter for the formation of quantum wires (QWs) was found to be the presence of a long chain acid, while the quantum platelets (QPLs) required a long chain amine and chlorinated solvent, and quantum cube (QC) formation was kinetically driven. The higher ordered stacking of the QPLs and bundling of the QWs was also found to be controlled by surface ligand chemistry.
ELECTROMAGNETIC COUPLING THROUGH ARBITRARY APERTURES IN PARALLEL CONDUCTING PLANES

We propose a numerical methodto solve the problem of coupling through finite, but otherwise arbitrary apertures in perfectly conducting and vanishingly thin parallel planes. The problem is given a generic formulation using the Methodof Moments andthe Green's function in the region between the two planes is evaluated using Ewald's method. Numerical applications using Glisson's basis functions to solve the problem are demonstratedandcomparedwith previously publishedresults andthe output of FDTD software.
Enhancing Shear Thickening

A cornstarch suspension is the quintessential particulate system that exhibits shear thickening. By adding large non-Brownian spheres to a cornstarch suspension, we show that shear thickening can be significantly enhanced. More precisely, the shear-thickening transition is found to be increasingly shifted to lower critical shear rates. This influence of the large particles on the discontinuous shear-thickening transition is shown to be more dramatic than that on the viscosity or the yield stress of the suspension.
Nonlinear finite element analysis of short and long reinforced concrete columns confined with GFRP tubes

This paper presents three-dimensional nonlinear finite element models to understand the uniaxial behavior of concrete-filled fiber reinforced polymer tubes. A stress–strain confined model was introduced for the concrete, a damage criteria based on Hashin's failure model was used to model damage and failure of GFRP tubes, and steel bars were modeled based on classic metal plasticity model. A comparison between experimental results found in the literature and the finite element model was conducted regarding the load-deflection curves and the failure pattern of different test specimens. The model was found to be efficient in capturing the loads and deformations of slender concrete-filled fiber reinforced polymer tube columns. It was then used in a parametric study to understand the effect of different parameters (including fiber orientation, number of layers of (glass-fiber reinforced polymer) and steel reinforcement ratio) on the behavior of concrete-filled fiber reinforced polymer tube under axial compressive loading. It was observed that the behavior of the columns was greatly affected by the investigated analysis parameters.
Designing Better Schools: The Meaning and Measure of Enabling School Structures

Common usage of the term bureaucracy is pejorative. To most people, bureaucracy is synonymous with red tape, rigid rules, autocratic superiors, and alienated and apathetic employees. But organizations of any size, including schools, have bureaucratic structures because they need appropriately designed formal procedures and hierarchical structures to prevent chaos and promote efficiency. Two conflicting views of the consequences of bureaucracy emerge from the literature. Some studies demonstrate that structure alienates and frustrates, whereas other research finds structure increases satisfaction and innovation. This study is consistent with an earlier attempt to reconcile these two theoretically opposing perspectives by creating and testing a new construct termed enabling structure. Evidence is mounting that schools can be designed with formalized procedures and hierarchical structures that help rather than hinder.
Scheduling Locomotives and Car Transfers in Freight Transport

We present a new model for a strategic locomotive scheduling problem arising at the Deutsche Bahn AG. The model is based on a multicommodity minimum cost flow formulation that is also used for public bus scheduling problems. However, several new aspects have to be additionally taken into account such as cyclic departures of the trains, time windows on starting and arrival times, network load-dependent travel times, and a transfer of cars between trains. The model is formulated as an integer linear programming problem (ILP). The formulation is improved by preprocessing and additional cutting planes. Solutions are obtained using a randomized greedy heuristic in combination with commercial ILP solvers. Computational results are presented for several real-world test instances.
Wireless Information and Energy Transfer for Decode-and-Forward Relying MIMO-OFDM Networks

This paper investigates the system achievable rate and optimization for the multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) system with an energy harvesting (EH) relay. Firstly we propose a time switchingbased relaying (TSR) protocol to enable the simultaneous information processing and energy harvesting at the relay. Then, we discuss its achievable rate performance theoretically and formulated an optimization problem to maximize the system achievable rate. As the problem is difficult to solve, we design an Augmented Lagrangian Penalty Function (ALPF) method for it. Extensive simulation results are provided to demonstrate the accuracy of the analytical results and the effectiveness of the ALPF method.
Cognitive, physical, sensory, and functional affordances in interaction design

In reaction to Norman's (1999) essay on misuse of the term affordance in human-computer interaction literature, this article is a concept paper affirming the importance of this powerful concept, reinforcing Norman's distinctions of terminology, and expanding on the usefulness of the concepts in terms of their application to interaction design and evaluation. We define and use four complementary types of affordance in the context of interaction design and evaluation: cognitive affordance, physical affordance, sensory affordance, and functional affordance. The terms cognitive affordance (Norman's perceived affordance) and physical affordance (Norman's real affordance) refer to parallel and equally important usability concepts for interaction design, to which sensory affordance plays a supporting role. We argue that the concept of physical affordance carries a mandatory component of utility or purposeful action (functional affordance). Finally, we provide guidelines to help designers think about how these four kinds of affordance work together naturally in contextualized HCI design or evaluation.
Matrix Factorization with Column L0-Norm Constraint for Robust Multi-subspace Analysis

We aim to study the subspace structure of data approximately generated from multiple categories and remove errors (e.g., noise, corruptions, and outliers) in the data as well. Most previous methods for subspace analysis learn only one subspace, failing to discover the intrinsic complex structure, while state-of-the-art methods use data itself as the basis (self-expressiveness property), showing degraded performance when data contain errors. To tackle the problem, we propose a novel method, called Matrix Factorization with Column L0-norm constraint (MFC0), from the matrix factorization perspective. MFC0 simultaneously discovers the multi-subspace structure of either clean or contaminated data, and learns the basis for each subspace. Specifically, the learnt basis with the orthonormal constraint shows high robustness to errors by adding a regularization term. Owing to the column l0-norm constraint, the generated representation matrix can be (approximate) block-diagonal after reordering its columns, with each block characterizing one subspace. We develop an efficient first-order optimization scheme to stably solve the nonconvex and nonsmooth objective function of MFC0. Experimental results on synthetic data and real-world face datasets demonstrate the superiority over traditional and state-of-the-art methods on both representation learning, subspace recovery and clustering.
Neuropeptide Y protects cerebral cortical neurons by regulating microglial immune function

Neuropeptide Y has been shown to inhibit the immunological activity of reactive microglia in the rat cerebral cortex, to reduce N-methyl-D-aspartate current (INMDA) in cortical neurons, and protect neurons. In this study, after primary cultured microglia from the cerebral cortex of rats were treated with lipopolysaccharide, interleukin-1β and tumor necrosis factor-α levels in the cell culture medium increased, and mRNA expression of these cytokines also increased. After primary cultured cortical neurons were incubated with the lipopolysaccharide-treated microglial conditioned medium, peak INMDA in neurons increased. These effects of lipopolysaccharide were suppressed by neuropeptide Y. After addition of the neuropeptide Y Y1 receptor antagonist BIBP3226, the effects of neuropeptide Y completely disappeared. These results suggest that neuropeptide Y prevents excessive production of interleukin-1β and tumor necrosis factor-α by inhibiting microglial reactivity. This reduces INMDA in rat cortical neurons, preventing excitotoxicity, thereby protecting neurons.
Large-scale systems security evolution: control theory approach

Rapidly expanding information technologies field clearly discovers tendency of increasing computer systems' heterogeneity and distribution level. In this paper authors reveal the hidden attributes of IT security evolution towards more assumptions about attacker power and less assertions on provided security level. The proposed view of IT security evolution makes it possible to classify security providing technologies in terms of control theory. This comparison, in turn, allows to borrow a rich theoretical framework of appropriate control theory methods (for non-linear, non-stationary, discrete-continuous automatic control systems) and adopt them for cyber security purposes. Moreover, proposed control theory view enables prediction of the future security evolution stages and allows to partially determine them.
Broadband Millimeter-Wave LNAs (47–77 GHz and 70–140 GHz) Using a T-Type Matching Topology

This paper presents the design and characterization of two broadband millimeter-wave LNAs realized in 0.25- μm and 0.13- μm SiGe BiCMOS technologies. Both circuits adopt a T-type matching topology to achieve the wide bandwidth (47-77 GHz for the V-band LNA and 70-140 GHz for the W/F-band LNA). The measured maximum gain is about 23 dB for both LNAs. The measured noise figure (NF) is below 7.2 dB (from 50 to 75 GHz) for the V-band LNA and below 7 dB (from 78 to 110 GHz) for the W/F-band LNA. Both LNAs are differential circuits and consume 52/54 mW dc power. To the best of the authors' knowledge, both LNAs achieve the widest bandwidth in corresponding frequency bands with very competitive gain and NF.
Study of deep-stall characteristics and longitudinal special phenomena of T-tail aircraft

Deep-stall seriously threatens the safety of aircrafts; a detailed research has been carried out to make a full study on the influencing factors in avoidance of flight accidents in this paper. The Bifurcation analysis and catastrophe theory method (BACTM) is employed to analyze the deep-stall characteristics of four different configuration T-tail aircrafts with various pitching-moment curves, and some potential nonlinear motion phenomena are given using the phase plane α - q and time histories of the angle of attack. In addition, taking into account the actual flight conditions, effect of atmospheric turbulence is also investigated. The results indicate that the reversal slope of pitching-moment curves may cause the deep-tall condition. Other influencing factors include the depth, the width, the location of the reversal slope, as well as the control-effectiveness of the elevator. Moreover, atmospheric turbulence speeds up aircrafts entering the deep stall condition. The research results have some reference values for the stall recovery