Miracle-dz/UniFAR-FTUs huggingface dataset:
A proposal of LARG Supply Chain Management Practices and a Performance Measurement System

Supply chains (SC) in an attempt to be more competitive, are adopting new management paradigm. Among these paradigms there are four that deserve particular mention because of their importance to better SC performance: lean, agile, resilient and green. The main objective of this paper is to propose a conceptual model for a lean, agile, resilience and green SC, with the purpose of improving their operational, economic and environmental performance. In this attempt a set of SC management practices, which were named LARG practices, and several performance measures are suggested. This model is based in the literature review about the four SC management paradigms and also SC performance measurement. Among the suggested LARG practices the ones influencing more the SC performance are the just in time and also the supplier relationships. Also the SC performance measures with more LARG practices influencing them are the inventory levels and the time, that is, the SC's operational performance is the most affected.
Quality Investigation of Au Nanoarrays for Biosensing Application

The properties and ultrafast dephasing time of the Au nanoparticle structures produced for application in biosensors are investigated in dependence on their preparation conditions. The nanostructures are produced from thin Au films (10-20 nm) sputtered on SiO2 glass and annealed by pulsed (6 ns) laser radiation at 266 nm and at fluencies in the range of 10-412 mJ/cm2. The SEM inspection reveals nearly homogeneously distributed, spherical gold particles. Their initial size distribution in the range of 20-60 nm broadens towards larger particle diameters with prolonged irradiation. This is accompanied by an increase of the uncovered surface of the glass substrate and no particle removal is observed. In the absorbance spectra of the nanostructures the broad peak centered at 545-550 nm is ascribed to resonant absorption of surface plasmons. The peak position, halfwidth and intensity depend on the shape, size and size distribution of the nanostructured particles in agreement with literature. From peak intensities of the Raman spectra recorded in the range of 300 – 1800 cm-1 for the structures covered with Rhodamine 6G the relative signal enhancement by factor between 20 and 600 for individual peaks is estimated. Results confirm that the obtained structures can be applied for SERS measurements and sensing. The dephasing times estimated from homogeneous contribution of the absorbance linewidth range from 2.2 to 4.5 fs and correspond to particle diameters of 20-60 nm. It is shown that the dephasing rate 1/T2 can be tailored for particular sensor application by selection of the substrate preparation conditions.
WTTM 2011: the third workshop on the theory of transactional memory

In conjunction with PODC 2012, the TransForm project (Marie Curie Initial Training Network) and EuroTM (COST Action IC1001) supported the 4th edition of the Workshop on the Theory of Transactional Memory (WTTM 2012). The objective of WTTM was to discuss new theoretical challenges and recent achievements in the area of transactional computing. The workshop took place on July 19, 2012, in Madeira, Portugal. This year's WTTM was a milestone event for two reasons. First, because the same year, the two seminal articles on hardware and software transactional memories [15, 21] were recognized as outstanding papers on principles of distributed computing, whose significance and impact on the theory and practice of distributed computing have been evident for at least a decade. Second, the winners of this prestigious ACM/EATCS Edsger W. Dijkstra Prize, Maurice Herlihy, Eliot Moss, Nir Shavit and Dan Touitou, were present at the workshop and three of them discussed their current progress with other outstanding researchers from the field. This report is intended to give highlights of the problems discussed during the workshop.
Cooling of HTS applications in the temperature range of 66 K to 80 K

High temperature superconducting power cables require forced flow cooling. Today subcooled liquid nitrogen is circulated by a pump and cooled back by either an open or closed cycle refrigeration system. The temperature range of the nitrogen loop preferably is in the level of 80 K and below. The paper describes and compares refrigeration cycles for cooling of power cables. Possibilities of different coolants for the cable are also discussed. Efficiency calculations have shown that a helium Brayton cycle is the best choice in the investigated temperature range. However, cold compressors are also a good alternative.
The Anode Biocatalyst with Simultaneous Transition Metals Pollution Control

The need for reducing dependence on fossil fuels and the promoting the use of renewable fuels requires the development of alternative sources such as waste biomass for environmental benefits and alternative global energy supplies [1]. Microbial fuel cells (MFCs) provide new opportunities for the sustainable production of energy from biodegradable and reduced compounds, and thus, have attracted substantial research efforts to develop various devices for generating electricity and removing wastes [1, 2]. The development of processes that can use bacteria to produce electricity represents a highly effective method for bioenergy produc‐ tion as the bacteria are self-replicating, and thus the catalysts of organic matter oxidation are self-sustaining [2]. The substrates used in MFCs range from carbohydrates (e.g. glucose, sucrose, cellulose, starch), volatile fatty acids (e.g. formate, acetate, butyrate), alcohols (e.g. ethanol, methanol), amino acids, proteins and even inorganic components such as sulfides or acid mine drainages [2, 3-9]. The type of substrate fed to a MFC potentially has an impact on the structure and composition of the microbial community. Untill now, no clear image of the effect of the type of substrate on electricity generation by the microbial fuel cells is available.
Patients younger than 40 years with gastric carcinoma

In the general population, Helicobacter pylori (H. pylori), particularly the cagA positive strain, has been associated with intestinal‐type gastric carcinoma. Gastric carcinomas are rarely observed in patients age ≤40 years. Host‐related factors have been thought to be more important than environmental agents in these early‐onset cancers. The aim of this study was to ascertain the possible role of H. pylori infection and that of cagA positive strains in the development of gastric carcinoma in these young patients.
The cleverSuite approach for protein characterization: predictions of structural properties, solubility, chaperone requirements and RNA-binding abilities

Motivation: The recent shift towards high-throughput screening is posing new challenges for the interpretation of experimental results. Here we propose the cleverSuite approach for large-scale characterization of protein groups. Description: The central part of the cleverSuite is the cleverMachine (CM), an algorithm that performs statistics on protein sequences by comparing their physico-chemical propensities. The second element is called cleverClassifier and builds on top of the models generated by the CM to allow classification of new datasets. Results: We applied the cleverSuite to predict secondary structure properties, solubility, chaperone requirements and RNA-binding abilities. Using cross-validation and independent datasets, the cleverSuite reproduces experimental findings with great accuracy and provides models that can be used for future investigations. Availability: The intuitive interface for dataset exploration, analysis and prediction is available at http://s.tartaglialab. com/clever_suite. Contact: gian.tartaglia@crg.es Supplementary information: Supplementary data are available at Bioinformatics online.
Dose-Dependent Nonlinear Effect of l-DOPA on Paired Associative Stimulation-Induced Neuroplasticity in Humans

Dopamine is one of the major neuromodulators in the CNS, which is involved in learning and memory processes. A nonlinear, inverted U-shaped dose–response curve of its effects on cognition has been observed in animal studies. The basis for this nonlinear effect might be a similar effect of dopamine on neuroplasticity. Whereas it has been shown that dopamine affects paired associative stimulation (PAS)-induced plasticity, which might reflect learning-related processes to a larger degree than other noninvasive plasticity induction protocols in the human motor cortex in principle, its dose-dependency has not been explored previously. We studied the effect of different dosages of the dopamine precursor l-DOPA on motor cortex plasticity induced by facilitatory and inhibitory PAS of the motor cortex in 12 healthy humans. They received 25, 100, or 200 mg of l-DOPA or placebo medication combined with either excitability-enhancing or -diminishing PAS. Cortical excitability level was monitored before and for up to 2 d after plasticity induction by assessment of transcranial magnetic stimulation-induced motor-evoked potentials. Low-dose l-DOPA abolished the aftereffects of PAS and medium-dose l-DOPA prolonged facilitatory plasticity. High-dose l-DOPA reversed the excitability enhancement accomplished by facilitatory PAS to diminution. Thus, the results show a clear nonlinear effect of l-DOPA dosage on associative plasticity, different from that on nonfocal plasticity. This might help to explain dopaminergic effect on cognition and could be relevant for understanding the pathophysiology and treatment of neuropsychiatric diseases accompanied by alterations of the dopaminergic system.
Improving the Identification of High Risk Precursor B Acute Lymphoblastic Leukemia Patients with Earlier Quantification of Minimal Residual Disease

The stratification of patients with acute lymphoblastic leukemia (ALL) into treatment risk groups based on quantification of minimal residual disease (MRD) after induction therapy is now well accepted but the relapse rate of about 20% in intermediate risk patients remains a challenge. The purpose of this study was to further improve stratification by MRD measurement at an earlier stage. MRD was measured in stored day 15 bone marrow samples for pediatric patients enrolled on ANZCHOG ALL8 using Real-time Quantitative PCR to detect immunoglobulin and T-cell receptor gene rearrangements with the same assays used at day 33 and day 79 in the original MRD stratification. MRD levels in bone marrow at day 15 and 33 were highly predictive of outcome in 223 precursor B-ALL patients (log rank Mantel-Cox tests both P<0.001) and identified patients with poor, intermediate and very good outcomes. The combined use of MRD at day 15 (≥1×10−2) and day 33 (≥5×1−5) identified a subgroup of medium risk precursor B-ALL patients as poor MRD responders with 5 year relapse-free survival of 55% compared to 84% for other medium risk patients (log rank Mantel-Cox test, P = 0.0005). Risk stratification of precursor B-ALL but not T-ALL could be improved by using MRD measurement at day 15 and day 33 instead of day 33 and day 79 in similar BFM-based protocols for children with this disease.
User Studies on Security : Good vs . Perfect

Increasingly, our daily activities are supported by networked computing. Coincident with this trend, criminals have been exploiting the vulnerabilities of networks to cause all sorts of mayhem, resulting in harm to people’s privacy and property. It is ironic that some of this damage is caused by people’s own inattention to secure practices. Understanding the behaviors that expose people to risks should result in better security systems and practices. Furthermore, research in the area of usable security has explored user interface mechanisms to reduce user susceptibility to various forms of attacks and to improve users’ ability to interact with protection mechanisms. Several studies report some success at reducing risky behavior in the laboratory setting [1, 7, 6]. Our personal experience in this area includes the investigation of the usability and security of novel security mechanisms:
Preemptive Virtual Clock: A flexible, efficient, and cost-effective QOS scheme for networks-on-chip

Future many-core chip multiprocessors (CMPs) and systems-on-a-chip (SoCs) will have numerous processing elements executing multiple applications concurrently. These applications and their respective threads will interfere at the on-chip network level and compete for shared resources such as cache banks, memory controllers, and specialized accelerators. Often, the communication and sharing patterns of these applications will be impossible to predict off-line, making fairness guarantees and performance isolation difficult through static thread and link scheduling. Prior techniques for providing network quality-of-service (QOS) have too much algorithmic complexity, cost (area and/or energy) or performance overhead to be attractive for on-chip implementation. To better understand the preferred solution space, we define desirable features and evaluation metrics for QOS in a network-on-a-chip (NOC). Our insights lead us to propose a novel QOS system called preemptive virtual clock (PVC). PVC provides strong guarantees, reduces packet delay variation, and enables efficient reclamation of idle network bandwidth without per-flow buffering at the routers and with minimal buffering at the source nodes. PVC averts priority inversion through preemption of lower-priority packets. By controlling preemption aggressiveness, PVC enables a trade-off between the strength of the guarantees and overall throughput. Finally, PVC simplifies network management through a flexible allocation mechanism that enables per-application bandwidth provisioning independent of thread count and supports transparent bandwidth recycling among an application's threads.
Spectral Clustering by Ellipsoid and Its Connection to Separable Nonnegative Matrix Factorization

This paper proposes a variant of the normalized cut algorithm for spectral clustering. Although the normalized cut algorithm applies the K-means algorithm to the eigenvectors of a normalized graph Laplacian for finding clusters, our algorithm instead uses a minimum volume enclosing ellipsoid for them. We show that the algorithm shares similarity with the ellipsoidal rounding algorithm for separable nonnegative matrix factorization. Our theoretical insight implies that the algorithm can serve as a bridge between spectral clustering and separable NMF. The K-means algorithm has the issues in that the choice of initial points affects the construction of clusters and certain choices result in poor clustering performance. The normalized cut algorithm inherits these issues since K-means is incorporated in it, whereas the algorithm proposed here does not. An empirical study is presented to examine the performance of the algorithm.
ShiftFFT: An Efficient Approach to Mitigate Adjacent Channel Interference in OFDM Systems

Adjacent channel interference (ACI) in wireless systems is commonly mitigated through the use of guard bands and filters. Guard bands are not used for any transmissions and are therefore wasted spectrum. The use of sharp filters can reduce the size of required guard bands but they are costly and often not present in devices that are already deployed. We focus on OFDM wireless systems, which form the basis for almost all modern wireless networks, and pro- pose a novel technique called ShiftFFT that can be deployed at an OFDM receiver to mitigate ACI from legacy OFDM transmitters. ShiftFFT exploits the presence of over-provisioned cyclic prefixes in most OFDM wireless standards to optimize the starting time of the FFT operation at the receiver, which we show to have significant potential to reduce the amount of guard band required to avoid ACI and thereby enable efficient spectrum use. We evaluate ShiftFFT with a SDR testbed and using simulations across diverse settings, and show that using it can significantly reduce the guard band required by at least 10MHz in most cases while maintaining the same packet error rate performance.
On Linear Embeddings and Unsupervised Feature Learning

The ability to train deep architectures has led to many developments in parametric, non-linear dimensionality reduction but with little attention given to algorithms based on convolutional feature extraction without backpropagation training. This paper aims to fill this gap in the context of supervised Mahalanobis metric learning. Modifying two existing approaches to model latent space similarities with a Student’s t-distribution, we obtain competitive classification performance on CIFAR-10 and STL-10 with k-NN in a 50-dimensional space compared with a linear SVM with significantly more features. Using simple modifications to existing feature extraction pipelines, we obtain an error of 0.40% on MNIST, the best reported result without appending distortions for training.
Measuring unsupervised acoustic clustering through phoneme pair merge-and-split tests

Subphonetic discovery through segmental clustering is a central step in building a corpus-based synthesizer. To help decide what clustering algorithm to use we employed mergeand-split tests on English fricatives. Compared to reference of 2%, Gaussian EM achieved a misclassification rate of 6%, Kmeans 10%, while predictive CART trees performed poorly.
Force field for computation of conformational energies, structures, and vibrational frequencies of aromatic polyesters

A CFF931 all‐atom force field for aromatic polyesters based on ab initio calculations is reported. The force field parameters are derived by fitting to quantum mechanical data which include total energies, first and second derivatives of the total energies, and electrostatic potentials. The valence parameters and the ab initio electrostatic potential (ESP) derived charges are then scaled to correct the systematic errors originating from the truncation of the basis functions and the neglect of electron correlation in the HF/6‐31G* calculations. Based on the force field, molecular mechanics calculations are performed for homologues of poly(p‐hydroxybenzoic acid) (PHBA) and poly(ethylene terephthalate) (PET). The force field results are compared with available experimental data and the ab initio results. © 1994 by John Wiley & Sons, Inc.
KIR2DS3 is associated with protection against acute myeloid leukemia.

BACKGROUND Interaction between killer cell immunoglobulin-like receptors (KIR) and human leukocyte antigen (HLA) class I molecules is important for regulation of natural killer (NK) cell function. OBJECTIVE The aim of this study was to investigate the impact of compound KIR-HLA genotype on susceptibility to acute leukemia. METHODS Cohorts of Iranian patients with acute myeloid leukemia (AML; n=40) and acute lymphoid leukemia (ALL; n=38) were genotyped for seventeen KIR genes and their three major HLA class I ligand groups (C1, C2, Bw4) by a combined polymerase chain reaction-sequence-specific primers (PCR-SSP) assay. The results were compared with those of 200 healthy control individuals. RESULTS We found a significantly decreased frequency of KIR2DS3 in AML patients compared to control group (12.5% vs. 38%, odds ratio=0.23, p=0.0018). Also, the KIR3DS1 was less common in AML group than controls (27.5% vs. 44.5%, p=0.0465, not significant after correction). Other analyses including KIR genotypes, distribution and balance of inhibitory and activating KIR+HLA combinations, and co-inheritance of activating KIR genes with inhibitory KIR+HLA pairs were not significantly different between leukemia patients and the control group. However, in AML patients a trend toward less activating and more inhibitory KIR-HLA state was observed. Interestingly, this situation was not found in ALL patients and inhibition enhancement through increase of HLA ligands and inhibitory combinations was the main feature in this group. CONCLUSION Our findings may suggest a mechanism for escape of leukemic cells from NK cell immunity.
Supporting the Commander's information requirements: Automated support for Battle Drill processes using R-CAST

This paper discusses a novel approach that addresses the problem of supporting the Commander's dynamic information requirements through automation of the Military Decision-Making Process (MDMP) for time-constrained environments and training purposes, as part of the Tactical Human Integration of Networked Knowledge (THINK) Army Technology Objective - Research (ATO-R) initiative. We demonstrate this capability with automated user support for the execution of battle drills. Our approach is based on adapting the R-CAST cognitively-inspired agent architecture towards a context-aware anticipation of information requirements. R-CAST is a computational model of the Recognition-Primed Decision (RPD) model, which models human decision making under time stress. R-CAST agents support and collaborate with human decision making teams as both “smart aids” and “effective teammates” by anticipating, investigating, seeking, and interpreting information relevant to decision making. A key feature of R-CAST is that the proactive sharing of information relevant to decision making is automatically generated by the computational RPD model. The fundamental research question being addressed is whether the inclusion of R-CAST in Army staff processes improves said staff understanding and execution of battle tasks. We adapted R-CAST to Battle Drill #26 (i.e., responding to an IED event) as a proof of concept for team decision making under stress and constant switching of modalities. We demonstrate that the use of R-CAST cognitive agents effectively assists the Battle Manager in the S3 cell with auto-filling certain forms required by doctrine in response to the dynamism of the current state of the environment, improving cognitive performance in this task. Our novel approach integrates relevant context in communication, information, and socio-cognitive networks, coupled with cognitive modeling. We report initial findings that we can use the R-CAST cognitive framework to effectively and efficiently develop individual intelligent training tools that understand and support the dynamic information requirements of Commanders.
On network-based leader-following consensus of linear multi-agent systems

In this paper, the problem of network-based leader-following consensus is addressed for linear multi-agent systems with input saturation. First, a network-based consensus protocol with input saturation constraints is introduced to accommodate some network-induced effects such as delay, data quantization and time-varying sampling interval. Next, the Lyapunov-Krasovskii method is utilized to show the exponential convergence of the leader-following error system to a bounded set region under a delay-dependent stability condition, together with estimation of the region of initial conditions. Then with leveraging this stability condition, the gain matrix of the network-based consensus controller is designed for linear multi-agent systems.
AN EFFICIENT ALGORITHM FOR THE MINIMUM-RANGE IDEAL PROBLEM

Suppose we are given a partially ordered set, a real-valued weight associated with each element and a positive integer k. We consider the problem which asks to find an ideal of size k of the partially ordered set such that the range of the weights is minimum. We call this problem the minimum-range ideal problem. This paper shows a new and fast 0 ( n log n + m) algorithm for this problem, where n is the number of elements and m is the smallest number of arcs to represent the partially ordered set. It is also proved that this problem has an ^2(n log n + m) lower bound. This means that the algorithm presented in this paper is optimal.