Miracle-dz/UniFAR-FTUs huggingface dataset:
Conformational changes of a chemically modified HRP: formation of a molten globule like structure at pH 5

Horseradish peroxidase is an all alpha-helical enzyme, which widely used in biochemistry applications mainly because of its ability to enhance the weak signals of target molecules. This monomeric heme-containing plant peroxidase is also used as a reagent for the organic synthesis, biotransformation, chemiluminescent assays, immunoassays, bioremediation, and treatment of wastewaters as well. Accordingly, enhancing stability and catalytic activity of this protein for biotechnological uses has been one of the important issues in the field of biological investigations in recent years. In this study, pH-induced structural alterations of native (HRP), and modified (MHRP) forms of Horseradish peroxidase have been investigated. Based on the results, dramatic loss of the tertiary structure and also the enzymatic activity for both forms of enzymes recorded at pH values lower than 6 and higher than 8. Ellipticiy measurements, however, indicated very slight variations in the secondary structure for MHRP at pH 5. Spectroscopic analysis also indicated that melting of the tertiary structure of MHRP at pH 5 starts at around 45 °C, which is associated to the pKa of His 42 that has a serious role in keeping of the heme prostethic group in its native position through natural hydrogen bond network in the enzyme structure. According to our data, a molten globule like structure of a chemically modified form of Horseradish peroxidase at pH 5 with initial steps of conformational transition in tertiary structure with almost no changes in the secondary structure has been detected. Despite of some conformational changes in the tertiary structure of MHRP at pH 5, this modified form still keeps its catalytic activity to some extent besides enhanced thermal stability. These findings also indicated that a molten globular state does not necessarily preclude efficient catalytic activity.
Openness and Wage Inequality in Developing Countries: The Latin American Challenge to East Asian Con

The experience of East Asia in the 1960s and 1970s supports the theory that greater openness to trade tends to narrow the wage gap between skilled and unskilled workers in developing countries. In Latin America since the mid-1980s, however, increased openness has widened wage differentials. This conflict of evidence is probably not the result of differences between East Asia and Latin America. Instead, the conflict is probably the result of differences between the 1960s and the 1980s, specifically, the entry of China into the world market and, perhaps, the advent of new technology biased against unskilled workers.
AUTOMATIC ALIGNMENT OF MUSIC AUDIO AND LYRICS

This paper proposes an algorithm for aligning singing in pol yphonic music audio with textual lyrics. As preprocessing, t he system uses a voice separation algorithm based on melody transcription and sinusoidal modeling. The alignment is based on a hidden Markov model speech recognizer where the acoustic model is adapted to singing voice. The textual input is preprocess ed to create a language model consisting of a sequence of phonemes, pauses and possible instrumental breaks. Viterbi algorith m is used to align the audio features with the text. On a test set consis ting of 17 commercial recordings, the system achieves an average absolute error of 1.40 seconds in aligning lines of the lyrics.
Location Recommendation Incorporating Temporal and Spatial Effects

Services using the position information of users have been popularized by the spread of smart phones and tablet devices. One such service is location based social networking (LBSN). As users of LBSN have increased, vast amounts of check-in data have become available that record where users have been and when. In this paper, we assume that a user's check-in behavior is influenced by temporal and geographical factors. For the temporal factor, we consider the temporal impact to be different for each location and understand it by smoothing check-in data on the basis of Gaussian distribution. On the other hand, for the geographical factor, we assume that a user's check-in behavior depends on the area he visits on a daily basis and propose methods to reflect detected user's behavior range in the conventional system by utilizing spatial effects. In addition, we demonstrate that integrating these factors further improves recommendation accuracy. In our experiments, we show that our proposals outperform the state-of-the-art location recommender systems by using two LBSN datasets.
- 1-Inventory Record Inaccuracy : An Empirical Analysis

This study explores the systematic variation in inventory record inaccuracy (IRI) observed both within and across stores. Traditional inventory models, with a few exceptions, do not account for the existence of IRI and those that do treat record inaccuracy as random. Examining nearly 370,000 inventory records from 37 stores of one retailer, we found 65% to be inaccurate. That is, the recorded inventory quantity of an item fails to match the quantity found in the store. We identify factors associated with this inaccuracy that are stock keeping unit(SKU) and store-specific. SKU-specific factors such as item cost, selling quantity, and method of distribution account for the observed variation in IRI within stores. Store-specific factors such as the density and variety of inventory observed at each store account for the variation in IRI across stores. 1 University of Chicago GSB, 5807 South Woodlawn Ave, Chicago IL, 60637, 773-702-2388 (ph), 773-834-3976 (fx), ndehorat@ChicagoGSB.edu 2 Harvard Business School, Boston, MA 02163, 617-495-6937 (ph), 617-496-5265 (fx), araman@hbs.edu
Ethnic diversity matters: Putting implicit associations between weapons and ethnicity in context

Weapons are implicitly associated with Black Americans. We examined the extent to which this implicit stereotype fluctuates as a function of the ethnic diversity of contexts. Across 351 U.S. metropolitan areas, we tested whether three distinct indicators of ethnic diversity predicted implicit associations between the concept of “weapons” (vs. “harmless objects”) and Black Americans vs. White Americans. As predicted, implicit Black–weapon stereotypes were weaker in areas characterized by the presence of multiple ethnic groups (variety) and greater dispersion of ethnic groups at the neighborhood level (integration). Additionally, the negative association between integration and implicit stereotypes was strongest when minority representation was low compared to high. Considering multiple dimensions of ethnic diversity proved useful to document reliable relations between implicit associations and characteristics of local contexts.
How to extract frequent links with frequent itemsets in social networks?

In the area of the link mining, frequent pattern discovery tasks generally consist in the search for subgraphs frequently found in a network or a set of networks. Very recently, new axes of this problem has been proposed through the search for frequent links. Unlike traditional approaches that focus solely on structural regularities, frequent link mining methods exploit both the network structure and the attributes of nodes for extracting regularities in the links existing between node groups that share common characteristics. However, extracting frequent links is still a particularly challenging and computationally intensive issue since it is much dependent on the number of links. In this study, we propose a solution that is able to reduce the computing time by reducing the search to only a subset of of nodes. Experiments were conducted to understand the effects of different thresholds of the subset size on the loss of patterns and the gain in terms of computation time. Our solution proves to be efficient for a rather wide range of thresholds.
Cryptanalysis of the New Multilinear Map over the Integers

This article describes a polynomial attack on the new multilinear map over the integers presented by Coron, Lepoint and Tibouchi at Crypto 2015 (CLT15). This version is a fix of the first multilinear map over the integers presented by the same authors at Crypto 2013 (CLT13) and broken by Cheon et al. at Eurocrypt 2015. The attack essentially downgrades CLT15 to its original version CLT13, and leads to a full break of the multilinear map for virtually all applications. In addition to the main attack, we present an alternate probabilistic attack underpinned by a different technique, as well as an instant-time attack on the optimized variant of the scheme.
Targeted Quantitative Analysis of Streptococcus pyogenes Virulence Factors by Multiple Reaction Monitoring*S

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.
Reputation management for collaborative content distribution

We propose a reputation-based trust management system, ROCQ, to reduce unauthentic and corrupted file transfers in end-user collaborative content-distribution systems. Such systems are characterized by the splitting of large files into (optionally encoded) blocks and the simultaneous downloading of several blocks from different nodes to speed up content distribution. All nodes must cooperate and provide correct content for such systems to function smoothly. If malicious nodes are present, they can quickly bring the system to a halt by introducing fake blocks in the network making it impossible to reconstruct the original file. ROCQ (reputation, opinion, credibility and quality) uses feedback from past interactions among nodes to create node reputations. This allows detection of malicious nodes in a transaction-based network. We study the performance of ROCQ as used in a content distribution network. We find that ROCQ decreases the likelihood of a user receiving fake blocks by up to 16%, and, hence, significantly reduces bandwidth waste.
Calibration of a pole-mounted camera using a neural network

The intelligent soft arm control (ISAC) system is a robotic aid for the physically challenged. ISAC's current task is to feed the physically challenged. To accomplish this task ISAC needs to recognize the objects on the table, pick up the utensil it needs and bring it to the user's mouth. A camera is being used to recognize the objects on the table and a pair of cameras is being used to locate the user's mouth in real time. This report describes the calibration of the vision system dedicated to object recognition. The camera used in this system is mounted on a pole which is attached to the base of the robot. This setup makes the ISAC system compact as well as allowing the camera to view more than just one particular location, since it rotates with the base of the robot. Once an object is located in the image, the position of the object must be converted to robot coordinates so that the robot can use it. Unfortunately, the image plane is not parallel to the table in this setup. This causes the mapping from the image coordinates to the robot coordinates to be nonlinear. This nonlinearity was the motivation behind using a neural network to "learn" the mapping from image coordinates to robot coordinates
Local likelihood modeling by adaptive weights smoothing

The paper presents a unified approach to local likelihood estimation for a broad class of nonparametric models, including e.g. the regression, density, Poisson and binary response model. The method extends the adaptive weights smoothing (AWS) procedure introduced in Polzehl and Spokoiny (2000) in context of image denoising. Performance of the proposed procedure is illustrated by a number of numerical examples and applications to density or volatility estimation, classification and estimation of the tail index parameter. We also establish a number of important theoretical results on properties of the proposed procedure.
Scalable processor core for high-speed pattern matching architecture on FPGA

In recent pattern matching architecture researches, there has been much attention to high-throughput implementations with reconfiguration on the fly on FPGAs as well as ASICs. In this paper, we propose to use self-organizing approach to synthesize two-dimensional map (cluster) of a simple processing units with lateral links for fast pattern matching of one-dimensional input event. We suggest scalable processor core with heterogeneous cluster architecture. Experimental results show that the proposed architecture has advantages over the previously developed architectures in the terms of operating frequency, time delay and data bandwidth. For state-of-the-art FPGA we achieve operating frequency 600-500 MHz for the processor core with single cluster (input pattern of 8-512 bits, rule set of 64 bits), 490-440 MHz for the processor core with multiple clusters (rule set of 128 - 4096 bits, input pattern of 512 bits). Each cluster is characterized by low pipeline time delay of 3 ~ 5 clock cycles.
BOOTSTRAPPING PRE-AVERAGED REALIZED VOLATILITY UNDER MARKET MICROSTRUCTURE NOISE

The main contribution of this paper is to propose a bootstrap method for inference on integrated volatility based on the pre-averaging approach, where the pre-averaging is done over all possible overlapping blocks of consecutive observations. The overlapping nature of the pre-averaged returns implies that the leading martingale part in the pre-averaged returns are k n -dependent with k n growing slowly with the sample size n. This motivates the application of a blockwise bootstrap method. We show that the “blocks of blocks” bootstrap method is not valid when volatility is time-varying. The failure of the blocks of blocks bootstrap is due to the heterogeneity of the squared pre-averaged returns when volatility is stochastic. To preserve both the dependence and the heterogeneity of squared pre-averaged returns, we propose a novel procedure that combines the wild bootstrap with the blocks of blocks bootstrap. We provide a proof of the first order asymptotic validity of this method for percentile and percentile-t intervals. Our Monte Carlo simulations show that the wild blocks of blocks bootstrap improves the finite sample properties of the existing first order asymptotic theory. We use empirical work to illustrate its use in practice.
The influence of heart failure on longitudinal changes in cognition among individuals 80 years of age and older.

AIM The aim of this study was to examine the relationship between heart failure and specific cognitive abilities in octogenarians with regard to level and change over time. BACKGROUND Cognitive impairment is influenced by many factors, and the impact of heart failure is debated. Intact cognitive ability is crucial for successful self-care in patients with heart failure. Middle-aged patients with heart failure seem to have an increased risk of cognitive impairment. No studies have examined the association between heart failure and longitudinal cognitive changes in octogenarians (individuals 80 years and older). DESIGN A prospective longitudinal design. METHODS Cognitive tests were carried out five times (1991-2002) in 702 octogenarians from the Swedish Twin Registry, including same-sex twin pairs. The test battery included the measurement of processing speed, visuospatial ability, short-term, episodic and semantic memory. Latent growth curve modelling was employed to measure change and performance over time and compares the group diagnosed with heart failure to individuals without a heart failure diagnosis. Results. At baseline, the participants' mean age was 83·5 years, 67% were women and 13% suffered from heart failure. Individuals diagnosed with heart failure scored significantly lower in spatial abilities and episodic memory than participants not diagnosed with heart failure. Moreover, measures of episodic memory declined more over time in individuals diagnosed with heart failure. There were no significant differences between the groups in other cognitive tests. CONCLUSION Spatial problems and episodic memory have implications for everyday life. This might contribute to decreased adherence to prescribed therapy and self-care management and lead to socio-behavioural problems because of an impaired capacity to drive, read and write. RELEVANCE TO CLINICAL PRACTICE Nurses should take into account in their assessment that cognitive impairment may restrain elderly heart failure patient's ability to make decisions and perform self-care actions. Patient education strategies should also be adapted to cognitive ability.
Numerical analysis of the propagation of light in a disordered waveguide system

The propagation properties of light in a disordered waveguide system composed of randomly different cores in size are presented by numerically solving the coupled mode equation. The propagation constants of the modes are assumed to be a random variable. When one of cores is illuminated at the input end of the waveguide system the coherent part of the amplitude of light decreases exponentially with increasing distance and at large distance only the incoherent part propagates. The incoherent part is concentrated into a narrow region near the illuminated core in the cross section of the waveguide system and the distribution does not almost change along the waveguide axis.
Energy efficient routing based on ant colony algorithm in mine equipment monitoring

ZACA-EEC (Zigbee Ant Colony Algorithm Energy Efficient Cluster) routing protocol is proposed to replace AODV in Zigbee with the aim of increasing reliability for mine equipment monitoring in this paper, which can prolong the lifetime of network remarkably. Taking hydraulic support as an example, the distribution of monitoring nodes can be simplified as chain hierarchy topology, then Free-space model is used to study the topology's optimal cluster of energy, meanwhile, ant colony algorithm is a good method of solving the problem how to select cluster header. Simulation results show that compared with the AODV and LEACH-C, lifetime of ZACA-EEC respectively increase by an average of 65% and 3.5%, and the maximum packet loss rate is 0.87% which is 12% as AODV in the same case, in additional CHSBI (Cluster Header Selection Balance Index) of ZACA-EEC with a mean is 5.6 times that of LEACH-C.
Touch and emotion: Modeling of developmental differentiation of emotion lead by tactile dominance

Emotion is one of the important elements for humans to communicate with others. Humans are known to share basic emotions such as joy and anger although their developmental changes have been studied less. We propose a computational model for the emotional development in infancy. Our model reproduces the differentiation of emotion from pleasant/unpleasant states to six basic emotions as known in psychological studies. The key idea is twofold: the tactile dominance in infant-caregiver interaction and the inherent ability of tactile sense to discriminate pleasant/unpleasant states. Our model consists of probabilistic neural networks called Restricted Boltzmann Machines. The networks are hierarchically organized to first extract important features from tactile, auditory, and visual stimuli and then to integrate them to represent an emotional state. Pleasant/unpleasant information is directly provided to the highest level of the network to facilitate the emotional differentiation. Experimental results show that our model with the tactile dominance leads to better differentiation of emotion than others without such dominance.
Network Intrusion Detection and Response System for Mobile Ad hoc Networks

As wireless network growing rapidly it becomes very important to have intrusion detection system in it. Mobile ad hoc networks are particularly vulnerable to denial of service attacks (DoS) due to their open decentralized architecture, highly dynamic topology and shared wireless medium in which they exist. We implemented the network intrusion detection system (NIDS) for mobile ad-hoc networks to indentify misbehaving nodes that agree to forward packets but fail to do so, and an response system that helps routing protocols to avoid these nodes. Simulation result shows increase in throughput.
LRU-SEQ: a novel replacement policy for transition energy reduction in instruction caches

Leakage energy will be the major energy consumer in future deep sub-micron designs. Especially the memory sub-system of future SOCs will be negatively affected by this trend. In order to reduce the leakage energy, memory banks are transitioned to a low-energy state when possible. This transition itself costs some energy which is termed as the transition energy. In this paper we present, as the first approach of its kind, a novel energy saving replacement policy called LRU-SEQ for instruction caches. Evaluation of the policy on various architectures in a system-level environment has shown that up to 23% energy savings can be obtained. Considering the negligible hardware impact, LRU-SEQ offers a viable choice for an energy saving policy.
Image retargeting using importance diffusion

This paper presents a simple and effective image retargeting method that preserves visually important parts while reducing unwanted distortions of an image. Our approach is based on a novel importance diffusion scheme, which propagates importance of removed pixels to their neighbors for preserving visual contexts and avoiding over-shrinkage of unimportant parts. Importance diffusion enables even a simple row/column removal method, which removes the least important rows/columns repeatedly, to produce visually pleasant results. It also provides control over the trade-off between uniform and non-uniform sampling for the row/column removal and seam carving methods. Experimental result demonstrates that importance diffusion successfully improves the retargeting results of row/column removal and seam carving.
Short paper: Study on cognitive radio in IEEE 802.15.4 wireless sensor networks

Most of the proposed cognitive radio sensor networks (CRSNs) are not really based on the IEEE 802.15. 4. In this paper, we introduce the proposed IEEE 802.15. 4 based zb-CRSN framework which can perform spectrum sensing in the inactive portion. The spectrum decision algorithm of first detected idle channel first (FDIC) and shorter idle time first (SITF) are proposed to aid in selecting available licensed channel for sensor nodes from more than one spectrum sensing results.