Miracle-dz/UniFAR-FTUs huggingface dataset:
Reinforcement of natural rubber

In this article, we report on recent investigations on filled natural rubber. These investigations include a mechanical characterization as well as a molecular analysis based on measurements of chain orientation. It is demonstrated that at intermediate strains, the increase in the moduli can be explained by the inclusion of rigid particles in the soft matrix and from molecular interactions between the rubber and the filler. These interactions can be evaluated by equilibrium swelling and by orientational measurements. With regard to the unfilled formulation, carbon black– and silanized-filled natural rubber exhibit increases in the cross-linking density ascribed to filler-polymer links, whereas a large decrease in the orientational level, evidenced by birefringence and by infrared dichroism, is observed when silica is added without any coupling agent. Finally, two specific effects—the Payne and Mullins effects, both related to energy dissipation phenomena—are discussed. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 2301–2316, 2002
Biodiversity, Stability, and Productivity in Competitive Communities

Three markedly different models of multispecies competition—one mechanistic, one phenomenological, and one statistical—all predict that greater diversity increases the temporal stability of the entire community, decreases the temporal stability of individual populations, and increases community productivity. We define temporal stability as the ratio of mean abundance to its standard deviation. Interestingly, the temporal stability of entire communities is predicted to increase fairly linearly, without clear saturation, as diversity increases. Species composition is predicted to be as important as diversity in affecting community stability and productivity. The greater temporal stability of more diverse communities is caused by higher productivity at higher diversity (the “overyielding” effect), competitive interactions (the “covariance” effect), and statistical averaging (the “portfolio” effect). The relative contribution of each cause of temporal stability changes as diversity increases, but the net effect is that greater diversity stabilizes the community even though it destabilizes individual populations. This theory agrees with recent experiments and provides a degree of resolution to the diversity‐stability debate: both sides of the longstanding debate were correct, but one addressed population stability and the other addressed community stability.
Analysis of Various Forecasting Approaches for Linear Supply Chains based on Different Demand Data Transformations

Supply Chain Management (SCM) has become a popular topic in recent years. One of the main discussion points is the effective management of inventories along the supply chain. Several inventory policies have been analyzed and compared to overcome the traditional tradeoff between high service levels and high inventory costs and vice versa. This paper describes how different demand data aggregation affects reorder point calculations in continuous inventory review systems and analyzes the impact on inventories, safety stocks, and service levels of the supply chain members. Based on a linear three-stage supply chain, four different forecasting scenarios based on simple means and variance calculations as well as moving average and moving variance estimations have been tested. To analyze potential effects for different supply chain settings, four demand patterns were implemented (stationary, season, trend, trend and season). The simulations reveal different effects depending on demand data aggregation and customer demand structure. Since the assumption of normally distributed demand data is violated for upstream suppliers in linear supply chains, difficulties arise particularly in calculating safety stocks. Aggregating order data can mitigate some of the biases in several cases. It is shown that forecasting monthly aggregated orders outperforms the other strategies in terms of lower mean inventories and safety stocks, but may lead to slightly lower service levels.
A Distributed Power Management Game for Multi-Antenna Multiple-Access for "Ad-Hoc" Networks

This paper focuses on the competitively optimal power-control and signal-shaping for "ad-hoc" networks composed by Multiple-Antenna noncooperative transmit/receive terminals affected by spatially colored Multiple-Access Interference (MAI). For this purpose, the MAI-impaired network is modeled as a noncooperative strategic game, and sufficient conditions for the existence and uniqueness of the Nash Equilibrium are provided. Specifically, the following main results are achieved. First, we develop an iterative, fully decentralized, asynchronous and scalable power-control and signal-shaping algorithm that is competitively optimal and maximizes the information throughput sustained by links active over the network. Second, we test that the proposed decentralized access algorithm outperforms the (conventional) centralized orthogonal ones (as TDMA) in terms of aggregate network throughput. Third, we show that, when the throughput requested by the users are no sustainable by the network, the proposed algorithm converges to the allowable operating point at the minimum Euclidean distance from the requested one. Finally, we propose two fully decentralized Connection Admission Procedures (CAPs) that rely on the proposed decentralized access algorithm and optimize the tradeoff between aggregated networking throughput and users QoS requirements.
Nonparametric Online Regression while Learning the Metric

We study algorithms for online nonparametric regression that learn the directions along which the regression function is smoother. Our algorithm learns the Mahalanobis metric based on the gradient outer product matrix $\boldsymbol{G}$ of the regression function (automatically adapting to the effective rank of this matrix), while simultaneously bounding the regret ---on the same data sequence--- in terms of the spectrum of $\boldsymbol{G}$. As a preliminary step in our analysis, we extend a nonparametric online learning algorithm by Hazan and Megiddo enabling it to compete against functions whose Lipschitzness is measured with respect to an arbitrary Mahalanobis metric.
Nanostructured High‐Entropy Alloys with Multiple Principal Elements: Novel Alloy Design Concepts and Outcomes

A new approach for the design of alloys is presented in this study. These high-entropy alloys with multi-principal elements were synthesized using well-developed processing technologies. Preliminary results demonstrate examples of the alloys with simple crystal structures, nanostructures, and promising mechanical properties. This approach may be opening a new era in materials science and engineering.
Adult Attachment Ratings (AAR): An Item Response Theory Analysis

The Adult Attachment Ratings (AAR) include 3 scales for anxious, ambivalent attachment (excessive dependency, interpersonal ambivalence, and compulsive care-giving), 3 for avoidant attachment (rigid self-control, defensive separation, and emotional detachment), and 1 for secure attachment. The scales include items (ranging from 6–16 in their original form) scored by raters using a 3-point format (0 = absent, 1 = present, and 2 = strongly present) and summed to produce a total score. Item response theory (IRT) analyses were conducted with data from 414 participants recruited from psychiatric outpatient, medical, and community settings to identify the most informative items from each scale. The IRT results allowed us to shorten the scales to 5-item versions that are more precise and easier to rate because of their brevity. In general, the effective range of measurement for the scales was 0 to +2 SDs for each of the attachment constructs; that is, from average to high levels of attachment problems. Evidence for convergent and discriminant validity of the scales was investigated by comparing them with the Experiences of Close Relationships–Revised (ECR–R) scale and the Kobak Attachment Q-sort. The best consensus among self-reports on the ECR–R, informant ratings on the ECR–R, and expert judgments on the Q-sort and the AAR emerged for anxious, ambivalent attachment. Given the good psychometric characteristics of the scale for secure attachment, however, this measure alone might provide a simple alternative to more elaborate procedures for some measurement purposes. Conversion tables are provided for the 7 scales to facilitate transformation from raw scores to IRT-calibrated (theta) scores.
Bifrost inbox organizer: giving users control over the inbox

Many email users, especially managers, receive too many email messages to read in the time available to them. The solutions available today often require programming skills on the part of the user to define rules for prioritizing messages or moving messages to folders. We propose a different approach: categorize messages in the inbox with predefined rules that do not require maintenance and are scalable to handle anything from 50 to thousands of messages.
STELLAR AND TOTAL BARYON MASS FRACTIONS IN GROUPS AND CLUSTERS SINCE REDSHIFT 1

We investigate if the discrepancy between estimates of the total baryon mass fraction obtained from observations of the cosmic microwave background (CMB) and of galaxy groups/clusters persists when a large sample of groups is considered. To this purpose, 91 candidate X-ray groups/poor clusters at redshift 0.1 ⩽ z ⩽ 1 are selected from the COSMOS 2 deg2 survey, based only on their X-ray luminosity and extent. This sample is complemented by 27 nearby clusters with a robust, analogous determination of the total and stellar mass inside R 500. The total sample of 118 groups and clusters with z ⩽ 1 spans a range in M 500 of ∼1013–1015 M ☉. We find that the stellar mass fraction associated with galaxies at R 500 decreases with increasing total mass as M −0.37 ± 0.04 500, independent of redshift. Estimating the total gas mass fraction from a recently derived, high-quality scaling relation, the total baryon mass fraction (f stars+gas 500 = f stars 500 + f gas 500) is found to increase by ∼25%, when M 500 increases from 〈M〉 = 5 × 1013 M ☉ to 〈M〉 = 7 × 1014 M ☉. After consideration of a plausible contribution due to intracluster light (11%–22% of the total stellar mass) and gas depletion through the hierarchical assembly process (10% of the gas mass), the estimated values of the total baryon mass fraction are still lower than the latest CMB measure of the same quantity (WMAP5), at a significance level of 3. 3σ for groups of 〈M〉 = 5 × 1013 M ☉. The discrepancy decreases toward higher total masses, such that it is 1σ at 〈M〉 = 7 × 1014 M ☉. We discuss this result in terms of nongravitational processes such as feedback and filamentary heating.
What Do Family Caregivers of Alzheimer’s Disease Patients Desire in Smart Home Technologies?

Summary Objectives: The authors’ aim was to investigate the representations, wishes, and fears of family caregivers (FCs) regarding 14 innovative technologies (IT) for care aiding and burden alleviation, given the severe physical and psychological stress induced by dementia care, and the very slow uptake of these technologies in our society. Methods: A cluster sample survey based on a selfadministered questionnaire was carried out on data collected from 270 families of patients with Alzheimer’s disease or related disorders, located in the greater Paris area. Multiple Correspondence Analysis was used in addition to usual statistical tests to identify homogenous FCs clusters concerning the appreciation or rejection of the considered technologies. Results: Two opposite clusters were clearly defined: FCs in favor of a substantial use of technology, and those rather or totally hostile. Furthermore the distributions of almost all the answers of appreciations were U-shaped. Significant relations were demonstrated between IT appreciation and FC‘s family or gender statuses (e.g., female FCs appreciated a tracking device for quick recovering of wandering patients more than male FCs: p = 0.0025, N = 195). Conclusions: The study provides further evidence of the contrasted perception of technology in dementia care at home, and suggests the development of public debates based on rigorous assessment of practices and a strict ethical aim to protect against misuse.
Exploiting hierarchy in heterogeneous environments

Heterogeneous cluster environments are becoming an increasingly popular platform for executing parallel applications. Efficient heterogeneous parallel applications must account for the differences inherent in such an environment. Specifically, faster machines should possess more data items than their slower counterparts and communication should be minimized over slow network links. We propose the -Heterogeneous Bulk Synchronous Parallel (HBSP ) model, which is based on the BSP model of computation, as a framework for developing applications for heterogeneous systems. The BSP model is appropriate for -level (one communication network) heterogeneous systems. HBSP extends BSP hierarchically to address level heterogeneous machines. The utility of the model is demonstrated through the design and analysis of the gather and one-to-all broadcast operations. Experimental results demonstrate the improved performance that results from effectively exploiting the heterogeneity of the underlying system. By hiding the non-uniformity of the underlying system from the application developer, the HBSP model offers a framework that encourages the design of heterogeneous parallel software.
The Location Decisions of Foreign Investors in China: Untangling the Effect of Wages Using a Control Function Approach

There is almost no support for the proposition that capital is attracted to low wages from firm-level studies. We examine the location choices of 2,884 firms investing in China between 1993 and 1996 to offer two main contributions. First, we find that the location of labor-intensive activities is highly elastic to provincial wage differences. Generally, investors' wage sensitivity declines as the skill intensity of the industry increases. Second, we find that unobserved location-specific attributes exert a downward bias on estimated wage sensitivity. Using a control function approach, we estimate a downward bias of 50 to 90 in wage coefficients estimated with standard techniques.
Effect of Refining Slag on the Inclusions of Hard Wire Steel during Melting Process

The effect of the refining slag composition on the total oxygen content and inclusions in steel was investigated in 100 t UHP Electric Furnace – LF – Billet CC process. The test steel was 77B hard wire steel and Si-Mn alloy was used as the deoxidizer. Three types slag were used in the industrial tests, which including CaO-CaF2, CaO-CaF2 adding CaC and CaO-Al2O3 refining slag. The results shown that the lowest total oxygen contents of rolled bar can be gained using the CaO-CaF2 refining slag adding CaC, which is 0.0036%, while the total oxygen contents of rolled bar using CaO-Al2O3 refining slag is higher a little than the heats using CaO-CaF2 refining slag. The CaO-SiO2 and CaO-Al2O3-SiO2 compound inclusions with the size of about 5 μm are the main inclusions in the heats refining by the CaO-CaF2 refining slag in the rolled bar, but the pure, indeformable Al2O3 inclusion can also be found with the size of about 10 μm. The CaO-Al2O3-SiO2 and Al2O3-SiO2-MnO compound inclusions are the main inclusions in the heats refining by the CaO-CaF2-CaC refining slag, but most of the inclusion shape is irregular with bigger size of about 10 μm. Similar with the heat using CaO-CaF2 refining slag, the pure Al2O3 inclusion with edge angle can be found in the rolled bar. The inclusions in the rolled bar treated by CaO-Al2O3 refining slag are CaO-Al2O3-SiO2 compound inclusions, most of which are nearly globular shape with the relative small size of about 5 μm. All of the inclusions in rolled bar lie on the low melting zone in the CaO-Al2O3-SiO2 ternary phase diagram in the heats using CaO-Al2O3 refining slag. The similar condition appeared on the most of the inclusions in the heats using CaO-CaF2 and CaO-CaF2 refining slag adding CaC, while part of which are lied on the high melting zone. Therefore, considering of the plastic deformation ability, the CaO-Al2O3 refining slag is the best slag for the melting process of hard wire steel.
Influence of titanium and nitrogen on hot ductility of C–Mn–Nb–Al steels

AbstractThe influence of small additions of titanium on the hot ductility of C–Mn–Nb–Al steels has been examined. Titanium and nitrogen levels varied in the ranges 0·014–0·045 and 0·004–0·011 wt-%, respectively, so that a wide range of Ti/N ratios could be studied. The tensile specimens were cast and cooled at average cooling rates of 25, 100, and 200 K min-1 to test temperatures in the range 1100–800°C and strained to failure at a strain rate of 2 × 10-3 s-1. It was found that ductility in the titanium containing niobium steels improved with a decrease in the cooling rate, an increase in the size of the titanium containing precipitates, and a decrease in the volume fraction of precipitates. Coarser particles could be obtained by increasing the Ti/N ratio above the stoichiometric ratio for TiN and by testing at higher temperatures. However, ductility was generally poor for these titanium containing steels and it was equally poor when niobium was either present or absent. For steels with ∼0·005 wt-%N ducti.
Performances and Characteristics of DIGRank, Ranking in the Incomplete Networks

Page Rank has been widely used in ranking retrieval results on the web, finding the top influential papers in citation networks or detecting valuable users in online social networks. However, in practice, it is usually hard to obtain a complete structure of any above networks to rank nodes. Thus, some researchers have begun to explore how to get estimated ranks efficiently without acquiring the whole network. They have proposed some approximating methods, however, it is difficult to determine which method is the best one or which is suitable to a certain application. In this case, we set experiments in small-world and scale-free generated networks to certify the feasibility and characteristics of four approximating methods. We also use eleven real networks to mention different optimal conditions for these methods. We find the DIG Rank method performs better than other local estimation methods in almost every given sub graph. Besides, Mean field approach method tends to perform well in networks that have low average shortest path length, small amount of nodes with the same low in degree, or weak community structure. Finally, we apply the most versatile method DIG Rank to Sina micro-blog website to precisely classify users in a group as elites, grassroots or mummy users.
On-line Reference Assignment for Anaphoric and Non-Anaphoric Nouns: A Unified, Memory-Based Model in ACT-R

The computational model in present paper confirms that memory-based accounts are sufficient to account for a high rate of success at first-pass referent retrieval for anaphoric (and non-anaphoric) nouns. Because even definite noun phrases can often be non-anaphoric (e.g., Poesio & Vieira, 1998), an adequate model must account for how a reader makes an explicit or implicit decision about the anaphoric status of a noun (herein: The Anaphoric Classification Problem). We explain why we are inclined to reject the conventional intuition that: the failure to find/retrieve a referent within the discourse then, serially, leads to treating a (possibly anaphoric) noun as a new referent. Instead, we extend the memory-based account to address this classification problem. We suggest that LTM contains both generic referent types and specific referent tokens, which simultaneously compete for retrieval via resonance. The nature of what is retrieved (token vs. type) determines whether the reader effectively treats a noun as anaphoric or not. Our model predicts whether an anaphor in a given text will be misinterpreted as a new referent during first-pass processing. The influence of anaphor word choice is explained, and encompasses metaphoric anaphors.
What Does Social Media Say about Your Stress?

With the rise of social media such as Twitter, people are more willing to convey their stressful life events via these platforms. In a sense, it is feasible to detect stress from social media data for proactive health care. In psychology, stress is composed of stressor and stress level, where stressor further comprises of stressor event and subject. By far, little attention has been paid to estimate exact stressor and stress level from social media data, due to the following challenges: 1) stressor subject identification, 2) stressor event detection, and 3) data collection and representation. To address these problems, we devise a comprehensive scheme to measure a user's stress level from his/her social media data. In particular, we first build a benchmark dataset and extract a rich set of stress-oriented features. We then propose a novel hybrid multi-task model to detect the stressor event and subject, which is capable of modeling the relatedness among stressor events as well as stressor subjects. At last, we lookup an expert-defined stress table with the detected subject and event to estimate the stressor and stress level. Extensive experiments on real-world datasets well verify the effectiveness of our scheme.
Gold and silver nanoparticles as high-value colourants and multi-functional entities for natural fibres and minerals

Significant opportunities exist in both the scientific and industrial sectors for the development of novel multi-functional materials that combine the inherent properties of all precursor components in a synergistic manner, thereby providing new products and opportunities. Processes that add value to natural materials in a facile and refined manner are particularly sought after. Thus this research combines useable substrates, notably natural protein fibres and minerals with gold or silver nanoparticles, producing high value, multi-functional materials that display the strength, softness and shine (of the protein fibres), or high surface area and dispersibility (of the minerals) with the high value and wealth associated with the noble metal nanoparticles, their broad spectrum of intense colours, anti-microbial, insecticide and anti-static properties. This adds significant worth to the substrates, transforming them from commodities to valuable materials. Silk, merino wool and crossbred wool were the natural fibres employed kaolinite and halloysite clays the minerals. They were combined with gold and silver nanoparticles of various sizes and shapes (and hence colours) producing the following composite materials: • Gold nanoparticle-merino wool composites • Gold nanoparticle-crossbred wool composites • Gold nanoparticle-silk composites • Silver nanoparticle-kaolinite composites • Silver nanoparticle-halloysite composites The most successful method for producing silver nanoparticle-clay composites involved the external preparation of silver nanoparticles and their subsequent attachment to the clay substrates by means of a layer-by-layer deposition approach, which capitalised on electrostatic interactions between oppositely charged polyelectrolytes capping the nanoparticles and bound to the clay surfaces. Three general approaches were employed in the production of the gold nanoparticle-natural fibre composite materials. The nanoparticles were either synthesised ex-situ and subsequently attached to the fibres, or the natural fibres were utilised as redox active biotemplates in which the wool or silk absorbed and subsequently reduced Au³⁺ to nanoparticulate Au⁰ on and within the fibres. Thirdly, a seed mediated growth approach was employed in which additional Au³⁺ was reduced to nanoparticulate Au⁰ on the surface of gold nanoparticles already bound to the fibres. This was facilitated by an external reductant.