Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Shielding Gas Composition and Welding Parameters on the N-content and Corrosion Properties of Welds in N-alloyed Stainless Steel Grades

TIG welding using different heat inputs, arc lengths and shielding gas nitrogen contents was performed. The aim was to evaluate the possibilities to avoid nitrogen losses on welding or even increase the weld metal nitrogen content and thereby improve the corrosion properties and, in the case of duplex grades, also to improve the phase balance. Three different nitrogen-alloyed duplex grades and one superaustenitic grade were investigated. The corrosion resistance in terms of CPT, Critical Pitting Temperatue, of the super duplex material was found to be strongly correlated to the nitrogen content of the weld metal. In the case of the superaustenitic weld metal, the increased nitrogen content was found to be associated with an increased pore formation, leading to a lower corrosion resistance and thereby masking the positive effect of the increased introgen content. In order to illuminate the nitrogen exchange reactions between the arc, weld pool, and shielding gas, stationary weld experiments were also performed. The results from these stationary trials indicated that the net weld pool nitrogen content could be qualitatively understood if the various fluxes involved in the nitrogen transport between the plasma arc, weld pool and weld pool-shielding gas were considered. At short times the weld pool was limited in area and the nitrogen content of the weld pool increased due to high nitrogen activity in the arc. At longer times the nitrogen escaped from the weld pool to the shielding gas. This flux became then the dominating factor due to the increased weld pool area exposed to the shielding gas. The situation then approached the equilibrium conditions that were expected from the gas nitrogen activity and weld pool alloy composition according to thermodynamic calculations using the Thermo-Calc database.
Role of Endocytosis and Low pH in Murine Hepatitis Virus Strain A59 Cell Entry

ABSTRACT Infection by the coronavirus mouse hepatitis virus strain A59 (MHV-A59) requires the release of the viral genome by fusion with the respective target membrane of the host cell. Fusion is mediated by the viral S protein. Here, the entry pathway of MHV-A59 into murine fibroblast cells was studied by independent approaches. Infection of cells assessed by plaque reduction assay was strongly inhibited by lysosomotropic compounds and substances that interfere with clathrin-dependent endocytosis, suggesting that MHV-A59 is taken up via endocytosis and delivered to acidic endosomal compartments. Infection was only slightly reduced in the presence of substances inhibiting proteases of endosomal compartments, precluding that the endocytic uptake is required to activate the fusion potential of the S protein by its cleavage. Fluorescence confocal microscopy of labeled MHV-A59 confirmed that virus is taken up via endocytosis. Bright labeling of intracellular compartments suggests their fusion with the viral envelope. No fusion with the plasma membrane was observed at neutral pH conditions. However, when virus was bound to cells and the pH was lowered to 5.0, we observed a strong labeling of the plasma membrane. Electron microscopy revealed low pH triggered conformational alterations of the S ectodomain. Very likely, these alterations are irreversible because low-pH treatment of viruses in the absence of target membranes caused an irreversible loss of the fusion activity. The results imply that endocytosis plays a major role in MHV-A59 infection and the acidic pH of the endosomal compartment triggers a conformational change of the S protein mediating fusion.
Re-ordering Source Sentences for SMT

We propose a pre-processing stage for Statistical Machine Translation (SMT) systems where the words of the source sentence are re-ordered as per the syntax of the target language prior to the alignment process, so that the alignment found by the statistical system is improved. We take a dependency parse of the source sentence and linearize it as per the syntax of the target language, before it is used in either the training or the decoding phase. During this linearization, the ordering decisions among dependency nodes having a common parent are done based on two aspects: parent-child positioning and relation priority. To make the linearization process rule-driven, we assume that the relative word order of a dependency relation's relata does not depend either on the semantic properties of the relata or on the rest of the expression. We also assume that the relative word order of various relations sharing a relata does not depend on the rest of the expression. We experiment with a publicly available English-Hindi parallel corpus and show that our scheme improves the BLEU score.
Wireless Fault-Tolerant Controllers in Cascaded Industrial Workcells Using Wi-Fi and Ethernet

A Wireless Networked Control System using 802.11b is used to model fault-tolerance at the controller level of an industrial workcell. The fault-tolerance study in this paper presents the cascading of two independent workcells where each controller must be able to handle the load of both cells in case of failure of the other one. The intercommunication is completely wireless between the cells and this feature is investigated. The model incorporates unmodified 802.11b and 802.11g for communication. Sensors send sampled data to both controllers and the controllers to exchange a watchdog. The fault-free and faulty models are both simulated using OPNET Network Modeler. External interference on the critical intercommunication link is also investigated. Results of simulations are presented based on a 95% confidence analysis, guaranteeing correct system performance.
Observation of the controlled assembly of preclick components in the in situ click chemistry generation of a chitinase inhibitor

Significance Several in situ click chemistry studies have been reported. To date, there is evidence to indicate that proteins act as mold between azide and alkyne fragments by X-ray analysis of protein–ligand complexes. However, only “postclick” structural evidence has been available. We succeeded in obtaining crystal structures of a chitinase complexed with an azide inhibitor and an O-allyl oxime fragment as a mimic of a click partner, revealing a mechanism for accelerating triazole formation in chitinase. This is an example to express the “preclick” state of in situ click chemistry and a demonstration to show that the in situ click chemistry approach will benefit from this analysis for future plans. We also performed density functional theory calculations to explore the chitinase-contributed Huisgen cycloaddition. The Huisgen cycloaddition of azides and alkynes, accelerated by target biomolecules, termed “in situ click chemistry,” has been successfully exploited to discover highly potent enzyme inhibitors. We have previously reported a specific Serratia marcescens chitinase B (SmChiB)-templated syn-triazole inhibitor generated in situ from an azide-bearing inhibitor and an alkyne fragment. Several in situ click chemistry studies have been reported. Although some mechanistic evidence has been obtained, such as X-ray analysis of [protein]–[“click ligand”] complexes, indicating that proteins act as both mold and template between unique pairs of azide and alkyne fragments, to date, observations have been based solely on “postclick” structural information. Here, we describe crystal structures of SmChiB complexed with an azide ligand and an O-allyl oxime fragment as a mimic of a click partner, revealing a mechanism for accelerating syn-triazole formation, which allows generation of its own distinct inhibitor. We have also performed density functional theory calculations based on the X-ray structure to explore the acceleration of the Huisgen cycloaddition by SmChiB. The density functional theory calculations reasonably support that SmChiB plays a role by the cage effect during the pretranslation and posttranslation states of selective syn-triazole click formation.
Patients’ perspectives on providing a stool sample to their GP: a qualitative study

Background Stool specimen collection is challenging and informal feedback has indicated that participants find the process difficult. Increasing stool specimen returns would improve the investigation of outbreaks of diarrhoeal and food-borne disease. Aim To explore the barriers to stool sample collection and specimen return to ascertain which factors may help to improve the process. Design and setting Qualitative patient interview study in Gloucester, UK. Method A two-stage purposive sampling process was used to identify patients who had either previous experience or no experience of collecting a stool sample. The interview schedule, based on the theory of planned behaviour, was used to facilitate interviews with 26 patients. Interview transcripts were analysed using a modified framework analysis. Results Barriers to collection included embarrassment, fear of results, concerns around hygiene and contamination, discretion and privacy, and lack of information. Personal gain was identified as the main incentive to collecting and returning a stool sample. The need for an information leaflet on stool collection was emphasised by most patients. Conclusions GPs could make a number of small changes that could make a big difference for patients and potentially increase stool sample return. If they, rather than receptionists, distributed collection kits it may be easier for patients to ask any questions they had regarding collection. In addition, the provision of a stool-collection information leaflet could increase patients’ confidence regarding collecting the sample, and providing drop-off boxes for specimens could help prevent patients’ embarrassment regarding handing their stool over to a receptionist.
LOCAL WHITTLE ESTIMATION OF FRACTIONAL INTEGRATION FOR NONLINEAR PROCESSES

We study asymptotic properties of the local Whittle estimator of the long memory parameter for a wide class of fractionally integrated nonlinear time series models. In particular, we solve the conjecture posed by Phillips and Shimotsu (2004, Annals of Statistics 32, 656–692) for Type I processes under our framework, which requires a global smoothness condition on the spectral density of the short memory component. The formulation allows the widely used fractional autoregressive integrated moving average (FARIMA) models with generalized autoregressive conditionally heteroskedastic (GARCH) innovations of various forms, and our asymptotic results provide a theoretical justification of the findings in simulations that the local Whittle estimator is robust to conditional heteroskedasticity. Additionally, our conditions are easily verifiable and are satisfied for many nonlinear time series models.We thank Liudas Giraitis for providing the manuscript by Dalla, Giraitis, and Hidalgo (2006). We are grateful to the two referees and the editor for their detailed comments, which led to substantial improvements. We also thank Michael Stein for helpful comments on an earlier version. The work is supported in part by NSF grant DMS-0478704.
Effect of dissemination of evidence in reducing injuries from falls.

BACKGROUND Falling is a common and morbid condition among elderly persons. Effective strategies to prevent falls have been identified but are underutilized. METHODS Using a nonrandomized design, we compared rates of injuries from falls in a region of Connecticut where clinicians had been exposed to interventions to change clinical practice (intervention region) and in a region where clinicians had not been exposed to such interventions (usual-care region). The interventions encouraged primary care clinicians and staff members involved in home care, outpatient rehabilitation, and senior centers to adopt effective risk assessments and strategies for the prevention of falls (e.g., medication reduction and balance and gait training). The outcomes were rates of serious fall-related injuries (hip and other fractures, head injuries, and joint dislocations) and fall-related use of medical services per 1000 person-years among persons who were 70 years of age or older. The interventions occurred from 2001 to 2004, and the evaluations took place from 2004 to 2006. RESULTS Before the interventions, the adjusted rates of serious fall-related injuries (per 1000 person-years) were 31.2 in the usual-care region and 31.9 in the intervention region. During the evaluation period, the adjusted rates were 31.4 and 28.6, respectively (adjusted rate ratio, 0.91; 95% Bayesian credibility interval, 0.88 to 0.94). Between the preintervention period and the evaluation period, the rate of fall-related use of medical services increased from 68.1 to 83.3 per 1000 person-years in the usual-care region and from 70.7 to 74.2 in the intervention region (adjusted rate ratio, 0.89; 95% credibility interval, 0.86 to 0.92). The percentages of clinicians who received intervention visits ranged from 62% (131 of 212 primary care offices) to 100% (26 of 26 home care agencies). CONCLUSIONS Dissemination of evidence about fall prevention, coupled with interventions to change clinical practice, may reduce fall-related injuries in elderly persons.
Superluminescent fiber laser source in the mid-infrared via dual-pumping

By dual pumping the upper and lower laser level of the <sup>5</sup>I<sub>6</sub> → <sup>5</sup>I<sub>7</sub> transition (2.9 μm) of Ho<sup>3+</sup> we demonstrate a power-scalable fiber laser that can be modulated between continuous wave lasing and superluminesence.
Event-driven power management

Energy consumption of electronic devices has become a serious concern in recent years. Power management (PM) algorithms aim at reducing energy consumption at the system-level by selectively placing components into low-power states. Formerly, two classes of heuristic algorithms have been proposed for PM: timeout and predictive. Later, a category of algorithms based on stochastic control was proposed for PM. These algorithms guarantee optimal results as long as the system that is power managed can be modeled well with exponential distributions. We show that there is a large mismatch between measurements and simulation results if the exponential distribution is used to model all user request arrivals. We develop two new approaches that better model system behavior for general user request distributions. Our approaches are event-driven and give optimal results verified by measurements. The first approach we present is based on renewal theory. This model assumes that the decision to transition to low-power state can be made in only one state. Another method we developed is based on the time-indexed semi-Markov decision process (TISMDP) model. This model has wider applicability because it assumes that a decision to transition into a lower-power state can be made upon each event occurrence from any number of states. This model allows for transitions into low-power states from any state, but it is also more complex than our other approach. It is important to note that the results obtained by renewal model are guaranteed to match results obtained by TISMDP model, as both approaches give globally optimal solutions. We implemented our PM algorithms on two different classes of devices: two different hard disks and client-server wireless local area network systems such as the SmartBadge or a laptop. The measurement results show power savings ranging from a factor of 1.7 up to 5.0 with insignificant variation in performance.
Compression techniques applied to multiple speech recognition systems

Speech recognition systems typically contain many Gaussian distributions, and hence a large number of parameters. This makes them both slow to decode speech, and large to store. Techniques have been proposed to decrease the number of parameters. One approach is to share parameters between multiple Gaussians, thus reducing the total number of parameters and allowing for shared likelihood calculation. Gaussian tying and subspace clustering are two related techniques which take this approach to system compression. These techniques can decrease the number of parameters with no noticeable drop in performance for single systems. However, multiple acoustic models are often used in real speech recognition systems. This paper considers the application of Gaussian tying and subspace compression to multiple systems. Results show that two speech recognition systems can be modelled using the same number of Gaussians as just one system, with little effect on individual system performance. Index Terms: Automatic speech recognition, graphemes, subspace compression, Gaussian tying
Log-based Abnormal Task Detection and Root Cause Analysis for Spark

Abstract-Application delays caused by abnormal tasks arecommon problems in big data computing frameworks. Anabnormal task in Spark, which may run slowly withouterror or warning logs, not only reduces its resident node’sperformance, but also affects other nodes’ efficiency.Spark log files report neither root causes of abnormal tasks,nor where and when abnormal scenarios happen. AlthoughSpark provides a “speculation” mechanism to detect stragglertasks, it can only detect tailed stragglers in each stage. Sincethe root causes of abnormal happening are complicated, thereare no effective ways to detect root causes.This paper proposes an approach to detect abnormality andanalyzes root causes using Spark log files. Unlike commononline monitoring or analysis tools, our approach is a pureoff-line method that can analyze abnormality accurately. Ourapproach consists of four steps. First, a parser preprocessesraw log files to generate structured log data. Second, ineach stage of Spark application, we choose features relatedto execution time and data locality of each task, as well asmemory usage and garbage collection of each node. Third,based on the selected features, we detect where and whenabnormalities happen. Finally, we analyze the problems usingweighted factors to decide the probability of root causes. In thispaper, we consider four potential root causes of abnormalities,which include CPU, memory, network, and disk. The proposedmethod has been tested on real-world Spark benchmarks.To simulate various scenario of root causes, we conductedinterference injections related to CPU, memory, network,and Disk. Our experimental results show that the proposedapproach is accurate on detecting abnormal tasks as well asfinding the root causes
On the Complexity of Non-Projective Data-Driven Dependency Parsing

In this paper we investigate several non-projective parsing algorithms for dependency parsing, providing novel polynomial time solutions under the assumption that each dependency decision is independent of all the others, called here the edge-factored model. We also investigate algorithms for non-projective parsing that account for nonlocal information, and present several hardness results. This suggests that it is unlikely that exact non-projective dependency parsing is tractable for any model richer than the edge-factored model.
A PDMS Micropump for Implantable Drug Delivery Application

This paper presents an integrated magnetic PDMS micropump for implantable drug delivery application. The micropump mainly consists of two structural PDMS layers: a PDMS functional layer that incorporates microchannels, a pump chamber and two planar check valves into a single layer, allowing for simple design and easy system integration, and the other PDMS membrane layer covering the pump chamber and holding a thin electroplated permalloy piece on top for magnetic actuation. The micropump can be driven by the interaction between the ferromagnetic permalloy and an external electromagnet, providing a remote and wireless operation method. Test results demonstrate that this micropump is able to produce a maximal flow rate of 0.15 μL/min at the driving frequency of 2 Hz with a volume resolution of approximately 1 nL per stroke, promising its application in various implantable biomedical systems.
apid characterisation of the inherent dispersibility of respirable powders using ry dispersion laser diffraction

Understanding and controlling powder de-agglomeration is of great importance in the development of dry powder inhaler (DPI) products. Dry dispersion laser diffraction measures particle size readily under controlled dispersing conditions, but has not been exploited fully to characterise inherent powder dispersibility. The aim of the study was to utilise particle size-dispersing pressure titration curves to characterise powder cohesivity and ease of de-agglomeration. Seven inhaled drug/excipient powders (beclometasone dipropionate, budesonide, fluticasone propionate, lactohale 300, salbutamol base, salmeterol xinafoate and tofimilast) were subjected to a range of dispersing pressures (0.2–4.5 Bar) in the Sympatec HELOS/RODOS laser diffractometer and particle size measurements were recorded. Particle size-primary pressure data were used to determine the pressures required for complete de-
On Hidden Groups in Communication Networks

We describe models and efficient algorithms for detecting groups (communities) functioning in communication networks which use, intentionally or not, the surrounding background communications to disguise their existence. We call such groups hidden groups. To detect hidden groups we exploit the non-random nature of their communications as contrasted with the general background communications. We assume that the main goal of the communications of a hidden group in the network is planning and coordination of their future activity, which by the nature of planning has to involve all, or most members of the group. The implication of this basic assumption is that the communication subgraph induced by the hidden group members is connected. We describe efficient algorithms that, under certain conditions, can detect connected subgraphs that remain connected over time. Our results reveal the properties of the background network activity and hidden group communication dynamics that make detection of the hidden group easy, as well as those that make it difficult. We differentiate between two types of hidden groups: in a trusting (or non-secretive) hidden group, members are willing to communicate messages to other members via non-hidden group members; in a non-trusting (or secretive) hidden group, all information that must be passed among hidden group members cannot be passed via non-hidden group members. We find that if the background communications are dense or more structured, then the hidden group is harder to detect. Surprisingly, we also find that when the hidden group is non-trusting (secretive), it is easier to detect.