Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Truncation Strategy for the Higher-Order Singular Value Decomposition

We present an alternative strategy for truncating the higher-order singular value decomposition (T-HOSVD). An error expression for an approximate Tucker decomposition with orthogonal factor matrices is presented, leading us to propose a novel truncation strategy for the HOSVD, which we refer to as the sequentially truncated higher-order singular value decomposition (ST-HOSVD). This decomposition retains several favorable properties of the T-HOSVD, while reducing the number of operations required to compute the decomposition and practically always improving the approximation error. Three applications are presented, demonstrating the effectiveness of ST-HOSVD. In the first application, ST-HOSVD, T-HOSVD, and higher-order orthogonal iteration (HOOI) are employed to compress a database of images of faces. On average, the ST-HOSVD approximation was only $0.1\%$ worse than the optimum computed by HOOI, while cutting the execution time by a factor of $20$. In the second application, classification of handwritten digits, ST-HOSVD achieved a speedup factor of $50$ over T-HOSVD during the training phase, and reduced the classification time and storage costs, while not significantly affecting the classification error. The third application demonstrates the effectiveness of ST-HOSVD in compressing results from a numerical simulation of a partial differential equation. In such problems, ST-HOSVD inevitably can greatly improve the running time. We present an example wherein the $2$ hour $45$ minute calculation of T-HOSVD was reduced to just over one minute by ST-HOSVD, representing a speedup factor of $133$, while even improving the memory consumption.
An approach for object manipulation using cooperative agents

This paper explores a cooperative manipulation method for orienting and translating convex objects in the plane. The manipulation task is performed by two agents using the concept of "virtual fence". During the manipulation, each agent makes a point contact with the object, and two agents push together along a straight-line. One advantage of a virtual fence over physical fence is that virtual fence can manipulate non-polygonal parts, and reduce the position and orientation uncertainties simultaneously. Moreover, the coordination between agents increases the flexibility of the manipulation system. We first identify two manipulation primitives, equilibrium and non-equilibrium pushes, and characterize the motion of the object under these two pushing actions. Then, we study the planning problem in the framework of switched system, and develop a fully analytical solution to the planning problem. Finally, manipulation examples and experiments are provided to demonstrate the proposed manipulation method
Improving n-Similarity by genetic algorithm and its application in text document resemblance

In this paper, some methods of similarity measures between objects are presented and their properties are reviewed. The study is conducted to propose a new method based on genetic algorithm in order to reduce the time complexity of finding n most similar objects among the huge number of objects. This method is tested on two applications. The first one aims at finding the most similar residents in a condominium, and the second one aims at finding the most similar n-groups of text documents out of a great dataset. The simulation results show that the proposed method can efficiently improves the order of time complexity especially for the second application.
Cultural Issues in Globally Distributed Information Systems Development: A Survey and Analysis

Global information technology offshore outsourcing and globally distributed information systems development have become increasingly prevalent and diversified, thus demand great academic efforts to address a wide variety of issues. Although some studies have begun to synthesize relevant theoretical and empirical research of the complex phenomena, there is a lack of synthesized efforts to provide an in-depth discourse of cultural issues in globally distributed information systems development. This research provides a preliminary review and analysis on how culture is conceptualized and how cultural issues are investigated in the published literature on offshore outsourcing and globally distributed information systems development. Our findings show that national level of cultural influences is the dominant level being studied, although the socio-cultural context of globally distributed information systems development is complex and multi-leveled in nature. While some common cultural dimensional models are still widely used, several studies adopt the emergent and dynamic view of culture to investigate the cross-cultural information systems development work.
Mazur's principle for U(2,1) Shimura varieties

Mazur's principle gives a criterion under which an irreducible mod l Galois representation arising from a classical modular form of level Np (with p prime to N) also arises from a classical modular form of level N. We consider the analogous question for Galois representations arising from certain unitary Shimura varieties. In particular, we prove an analoge of Mazur's principle for U(2,1) Shimura varities. We also give a conjectural criterion for a Galois representation arising in the cohomology of a unitary Shimura variety whose level subgroup is parahoric at p to also arise in the cohomology of a Shimura variety with "less level structure at p".
Homology modelling and identification of active site residue in the nucleoprotein of influenza virus through in silico strategy for drug target

Influenza A virus poses a serious threat towards public health globally. Its genome encodes a nucleoprotein (NP) (498-amino acid) which plays a vital role in viral RNA replication and host specificity. Homology modelling was used to generate the 3-D structure of four different strains (H5N1, H6N1, H3N2 and H7N1) using a known protein template crystal structure (PDB code No. 2IQH). The validation of 3-D structure was done with the help of PROCHECK encompassing amino acid residues in the most favoured region of all strains. The identification of catalytic amino acid residue in the active site domain in 3-D structure of NP was also done. The structure and catalytic amino acid residue present in the NP may help to target and design the antiviral drugs against influenza.
Two-Photon Characterization of Substituted ( T 8 )

An efficient source of alternative energy has yet to be developed. Solar energy, the most viable and sustainable source of renewable energy, remains less effective due to limitations in absorbing materials to convert direct sunlight into useful solar cell devices. However, this flaw can be circumvented if solar panels had the capability to convert infrared radiation into useable energy. The focus of this study is the evaluation of the non-linear optical properties of silsesquioxane (caged {T8}) molecules through ultrafast two-photon spectroscopy to determine their applicability in creating more effective solar energy devices (Laine et al, 2010; Sulaiman et al, 2008). The two photon absorption measurements were carried out using 770 to 830nm, 30 femto-second pulses. The results revealed that there are maxima for the cross sections near 800nm for the different caged molecules studied. The increase in cross section is correlated with increasing substitution of electron donating groups on the cage. This data provides further support for these materials to be used in applications of near infrared solar absorption devices.
On the application of LDPC codes to arbitrary discrete-memoryless channels

We discuss three structures of modified low-density parity-check (LDPC) code ensembles designed for transmission over arbitrary discrete memoryless channels. The first structure is based on the well-known binary LDPC codes following constructions proposed by Gallager and McEliece, the second is based on LDPC codes of arbitrary (q-ary) alphabets employing modulo-q addition, as presented by Gallager, and the third is based on LDPC codes defined over the field GF(q). All structures are obtained by applying a quantization mapping on a coset LDPC ensemble. We present tools for the analysis of nonbinary codes and show that all configurations, under maximum-likelihood (ML) decoding, are capable of reliable communication at rates arbitrarily close to the capacity of any discrete memoryless channel. We discuss practical iterative decoding of our structures and present simulation results for the additive white Gaussian noise (AWGN) channel confirming the effectiveness of the codes.
Algorithm for Spatial Clustering with Obstacles

In this paper, we propose an efficient clustering technique to solve the problem of clustering in the presence of obstacles. The proposed algorithm divides the spatial area into rectangular cells. Each cell is associated with statistical information that enables us to label the cell as dense or non-dense. We also label each cell as obstructed (i.e. intersects any obstacle) or non-obstructed. Then the algorithm finds the regions (clusters) of connected, dense, non-obstructed cells. Finally, the algorithm finds a center for each such region and returns those centers as centers of the relatively dense regions (clusters) in the spatial area.
Extensive pancreas regeneration following acinar-specific disruption of Xbp1 in mice.

BACKGROUND & AIMS Progression of diseases of the exocrine pancreas, which include pancreatitis and cancer, is associated with increased levels of cell stress. Pancreatic acinar cells are involved in development of these diseases and, because of their high level of protein output, they require an efficient, unfolded protein response (UPR) that mediates recovery from endoplasmic reticulum (ER) stress following the accumulation of misfolded proteins. METHODS To study recovery from ER stress in the exocrine organ, we generated mice with conditional disruption of Xbp1 (a principal component of the UPR) in most adult pancreatic acinar cells (Xbp1fl/fl). We monitored the effects of constitutive ER stress in the exocrine pancreas of these mice. RESULTS Xbp1-null acinar cells underwent extensive apoptosis, followed by a rapid phase of recovery in the pancreas that included expansion of the centroacinar cell compartment, formation of tubular complexes that contained Hes1- and Sox9-expressing cells, and regeneration of acinar cells that expressed Mist1 from the residual, surviving Xbp1+ cell population. CONCLUSIONS XBP1 is required for homeostasis of acinar cells in mice; ER stress induces a regenerative response in the pancreas that involves acinar and centroacinar cells, providing the needed capacity for organ recovery from exocrine pancreas disease.
Using latent features to measure the diversity of recommendation lists

One of the well-known issues with content recommender system is that they tend to become over-specialized, which often has a negative influence on user experience. This can be solved by diversification of the recommendation list, a process that implements a tradeoff between accuracy and diversity of recommended items. Normally, item metadata is used in the diversity measure. In certain cases however, the item metadata may not be available thus a different approach to measure diversity is required. The aim of this preliminary study is to determine whether latent features can be used to measure the diversity of recommended items. In order to resolve this we generated recommendation lists for 43 different users using the LDOS-CoMoDa dataset. We then evaluated the diversity of these lists using the standard intra-list diversity measure. In addition we calculated the diversity of each list by comparing the latent features (calculated using the matrix factorization approach) of each item on the list. The comparison of both value sets showed that they show similar characteristics which implies that latent feature space offers an alternative method of evaluating item diversity when no metadata is present.
An approach for analyzing and correcting spelling errors for non-native Arabic learners

Spellcheckers are widely used in many software products for identifying errors in users' writings. However, they are not designed to address spelling errors made by non-native learners of a language. As a matter of fact, spelling errors made by non-native learners are more than just misspellings. Non-native learners' errors require special handling in terms of detection and correction, especially when it comes to morphologically rich languages such as Arabic, which have few related resources. In this paper, we address common error patterns made by non-native Arabic learners and suggest a two-layer spell-checking approach, including spelling error detection and correction. The proposed error detection mechanism is applied on top of Buckwalter's Arabic morphological analyzer in order to demonstrate the capability of our approach in detecting possible spelling errors. The correction mechanism adopts a rule-based edit distance algorithm. Rules are designed in accordance with common spelling error patterns made by Arabic learners. Error correction uses a multiple filtering mechanism to propose final corrections. The approach utilizes semantic information given in exercising questions in order to achieve highly accurate detection and correction of spelling errors made by non-native Arabic learners. Finally, the proposed approach was evaluated using real test data and promising results were achieved.
Time Series Clustering Based on I-k-Means and Multi-Resolution PLA Transform

In this paper, we introduce an approach using I-k-Means algorithm combined with kd-tree for clustering of time series data transformed by the multiresolution dimensionality reduction method, MPLA. Taking advantage of the multiresolution property of MPLA representation, we can use an anytime clustering algorithm such as the I-k-Means, a popular partitioning clustering algorithm for time series. Our approach also uses kd-tree to resolve the dilemma associated with the choices of initial centroids and significantly improve the execution time and clustering quality. Our experiments show that our approach performs better than k-means and classical I-k-Means in terms of clustering quality and running time.
Bacterial Adhesion of Streptococcus suis to Host Cells and Its Inhibition by Carbohydrate Ligands

Streptococcus suis is a Gram-positive bacterium, which causes sepsis and meningitis in pigs and humans. This review examines the role of known S. suis virulence factors in adhesion and S. suis carbohydrate-based adhesion mechanisms, as well as the inhibition of S. suis adhesion by anti-adhesion compounds in in vitro assays. Carbohydrate-binding specificities of S. suis have been identified, and these studies have shown that many strains recognize Galα1-4Gal-containing oligosaccharides present in host glycolipids. In the era of increasing antibiotic resistance, new means to treat infections are needed. Since microbial adhesion to carbohydrates is important to establish disease, compounds blocking adhesion could be an alternative to antibiotics. The use of oligosaccharides as drugs is generally hampered by their relatively low affinity (micromolar) to compete with multivalent binding to host receptors. However, screening of a library of chemically modified Galα1-4Gal derivatives has identified compounds that inhibit S. suis adhesion in nanomolar range. Also, design of multivalent Galα1-4Gal-containing dendrimers has resulted in a significant increase of the inhibitory potency of the disaccharide. The S. suis adhesin binding to Galα1-4Gal-oligosaccharides, Streptococcal adhesin P (SadP), was recently identified. It has a Galα1-4Gal-binding N-terminal domain and a C-terminal LPNTG-motif for cell wall anchoring. The carbohydrate-binding domain has no homology to E. coli P fimbrial adhesin, which suggests that these Gram-positive and Gram-negative bacterial adhesins recognizing the same receptor have evolved by convergent evolution. SadP adhesin may represent a promising target for the design of anti-adhesion ligands for the prevention and treatment of S. suis infections.
Royal College of General Practitioners Guidance for the use of substitute prescribing in the treatment of opioid dependence in primary care

Guidance for the use of substitute prescribing in the treatment of opioid dependence in primary care Acknowledgements: Thanks to the Royal College of General Practitioners (RCGP) Regional Leads and the many others, who have contributed to developing this guide. a) These guidelines have been: Updated in line with Guidance on methadone and buprenorphine for the management of opioid dependence and Drug Misuse: opioid detoxification (NICE 2007) and Drug Misuse and Dependence — Guidelines for Clinical Management (2007). b) Combined and adapted from: 1. Guidance for the use of buprenorphine for the treatment of opioid dependence in primary care (2004) 2. Guidance for the use of methadone for the treatment of opioid dependence in primary care (2005) Disclaimer This publication is intended for the use of medical practitioners in the UK and not for patients. The authors, editors and publishers have taken care to ensure that the information contained in this book is correct to the best of their knowledge, at the time of publication. While efforts have been made to ensure the accuracy of the information presented, particularly related to the prescription of drugs, the authors, editors and publishers cannot accept liability for information that is subsequently shown to be wrong. Readers are advised to check that the information, especially that related to drug usage, complies with information contained in the British Formulary, or equivalent, or manufacturers datasheets, and that it complies with the latest legislation and standards of practice.
Effect of arousal increase in predictable and random task switching: evidence for the involvement of the anterior attentional network in random but not in predictable task switching.

Switch cost does not disappear as more preparation time for the next task is allowed. Tornay and Milán showed that the residual cost is smaller when tasks switch randomly than when they alternate in predictable sequences. They proposed that the difference was due to control mechanisms (anterior attentional network) being activated in the random condition because of its overall difficulty. Besides, it has been shown that increasing arousal levels inhibits the anterior attentional network. Therefore, Tornay and Milán's account predicts that high arousal should result in switch cost for the random condition increasing to the levels of predictable switching. In this work, this prediction was tested by assessing the interaction between increased arousal and switch cost with both predictable and random-task switching. The results may help to solve the ongoing controversy about the causes of switch cost.
Graph-Theoretic Measures of Multivariate Association and Prediction

Interpoint-distance-based graphs can be used to define measures of association that extend Kendall's notion of a generalized correlation coefficient. The authors present particular statistics that provide distribution-free tests of independence sensitive to alternatives involving non-monotonic relationships. Moreover, since ordering plays no essential role, the ideas that fully applicable in a multivariate setting. The authors also define an asymmetric coefficient measuring the extent to which (a vector) X can be used to make single-valued predictions of (a vector) Y. The authors discuss various techniques for proving that such statistics are asymptotically normal. As an example of the effectiveness of their approach, the authors present an application to the examination of residuals from multiple regression. 18 references, 2 figures, 1 table.
Estimates of Ultrasonographic Markers for Gestational Age Assessment of Singleton Pregnancies among Indian Population

This paper presents the revised estimates of various ultrasonographic markers used in practice for estimation of gestational age among singleton Indian population. Accurate estimation of gestational age plays a vital role in efficient obstetric planning and also helps us to estimate fetal malformation or growth retardation. Incorrect estimation of gestational age can result in grave complication for the patient and liability for health care providers. But the spectacular improvement in ultrasound imaging quality in the past decade has contributed to the rapid increase in its use as a diagnostic tool in the past decade. The ultrasound based growth chart used in practice date back to 1980’s. These charts have been found to estimate the gestational age with an accuracy of 2 weeks which is high compared to the state-of-the-art scanning systems. Hence in this paper an effort has been made to review the various ultrasonographic markers for fetal growth estimation and also propose revised estimates for US charts for singleton Indian population. Results indicate that using the proposed scheme, it may be possible to estimate the gestational age with an accuracy of 2 to 3 days.
Avoiding Redundant Specialization during Partial Evaluation

Existing partial evaluators use a strategy called polyvariant specialization, which involves specializing program points on the known portions of their arguments, and re-using such specializations only when these known portions match exactly. We show that this re-use criterion is overly restrictive, and misses opportunities for sharing in residual programs, thus producing large residual programs containing redundant specializations. We develop a criterion for re-use based on computing the domains of specializations, describe an approximate implementation of this criterion based on types, and show its implementation in our partial evaluation system FUSE. In addition, we describe several extensions to our mechanism to make it compatible with more powerful specialization strategies and to increase its efficiency. After evaluating our algorithm''s usefulness, we relate it to existing work in partial evaluation and machine learning.
Correction of Logical Errors in C programs using Genetic Algorithm Techniques

In this paper, we propose a logical error correction system for C programs. Although there has been considerable research in the field of error detection, there have been few advances in logical error correction. Our solution combines statistical control flow techniques for error detection and genetic programming techniques for error correction. We assume that logical errors are confined to expressions in the input program. In this context, the expressions are mined and statistically ranked on the basis of their error relevance. This initial data forms the input to the genetic algorithm that generates new and improved expression sets for the input program. A main genetic algorithm controls the evolution of expression sets while the individual expressions are modulated by genetic programming techniques. These sets of expressions are tested with the standard test bench and their fitness is declared to the genetic algorithm. The genetic algorithm produces new generations of expression sets until at least one set passes the testing criteria. This algorithm can also be extended to debug codes in other programming languages.