Miracle-dz/UniFAR-FTUs huggingface dataset:
KS An Empirical Assessment of Assortative Matching in the Labor Market Rute

In labor markets with worker and firm heterogeneity, the matching between firms and workers may be assortative, meaning that the most productive workers and firms team up. We investigate this with longitudinal population-wide matched employer-employee data from Portugal. Using dynamic panel data methods, we quantify a firm-specific productivity term for each firm, and we relate this to the skill distribution of workers in the firm. We find that there is positive assortative matching, in particular among long-lived firms. Using skill-specific estimates of an index of search frictions, we find that the results can only to a small extent be explained by heterogeneity of search frictions across worker skill groups. JEL Classification: J21, J24, D24, J63.
On obtaining Knuth, Morris, and Pratt's string matcher by partial evaluation

We present the first formal proof that partial evaluation of a quadratic string matcher can yield the precise behaviour of Knuth, Morris, and Pratt's linear string matcher.Obtaining a KMP-like string matcher is a canonical example of partial evaluation: starting from the naive, quadratic program checking whether a pattern occurs in a text, one ensures that backtracking can be performed at partial-evaluation time (a binding-time shift that yields a staged string matcher); specializing the resulting staged program yields residual programs that do not back up on the text, a la KMP. We are not aware, however, of any formal proof that partial evaluation of a staged string matcher precisely yields the KMP string matcher, or in fact any other specific string matcher.In this article, we present a staged string matcher and we formally prove that it performs the same sequence of comparisons between pattern and text as the KMP string matcher. To this end, we operationally specify each of the programming languages in which the matchers are written, and we formalize each sequence of comparisons with a trace semantics. We also state the (mild) conditions under which specializing the staged string matcher with respect to a pattern string provably yields a specialized string matcher whose size is proportional to the length of this pattern string and whose time complexity is proportional to the length of the text string. Finally, we show how tabulating one of the functions in this staged string matcher gives rise to the 'next' table of the original KMP algorithm.The method scales for obtaining other linear string matchers, be they known or new.
DIFFERENTIAL SUSCEPTIBILITY OF HUMAN SP-B GENETIC VARIANTS ON LUNG INJURY CAUSED BY BACTERIAL PNEUMONIA AND THE EFFECT OF A CHEMICALLY MODIFIED CURCUMIN

ABSTRACT Staphylococcus aureus is a common cause of nosocomial pneumonia frequently resulting in acute respiratory distress syndrome (ARDS). Surfactant protein B (SP-B) gene expresses two proteins involved in lowering surface tension and host defense. Genotyping studies demonstrate a significant association between human SP-B genetic variants and ARDS. Curcumins have been shown to attenuate host inflammation in many sepsis models. Our hypothesis is that functional differences of SP-B variants and treatment with curcumin (CMC2.24) modulate lung injury in bacterial pneumonia. Humanized transgenic mice, expressing either SP-B T or C allele without mouse SP-B gene, were used. Bioluminescent labeled S. aureus Xen 36 (50 &mgr;L) was injected intratracheally to cause pneumonia. Infected mice received daily CMC2.24 (40 mg/kg) or vehicle alone by oral gavage. Dynamic changes of bacteria were monitored using in vivo imaging system. Histological, cellular, and molecular indices of lung injury were studied in infected mice 48 h after infection. In vivo imaging analysis revealed total flux (bacterial number) was higher in the lung of infected SP-B-C mice compared with infected SP-B-T mice (P < 0.05). Infected SP-B-C mice demonstrated increased mortality, lung injury, apoptosis, and NF-&kgr;B expression compared with infected SP-B-T mice. Compared with controls, CMC2.24 treatment significantly reduced the following: mortality, total bacterial flux and lung tissue apoptosis, inflammatory cells, NF-&kgr;B expression (P < 0.05), and MMPs-2, -9, -12 activities (P < 0.05). We conclude that mice with SP-B-C allele are more susceptible to S. aureus pneumonia than mice with SP-B-T allele, and that CMC2.24 attenuates lung injury thus reducing mortality.
Eliminating Redundancy by Spectral Relaxation for Multi-Document Summarization

This paper focuses on redundancy, overlapping information in multi-documents, and presents a method for detecting salient, key sentences from documents that discuss the same event. To eliminate redundancy, we used spectral clustering and classified each sentence into groups, each of which consists of semantically related sentences. Then, we applied link analysis, the Markov Random Walk (MRW) Model to deciding the importance of a sentence within documents. The method was tested on the NTCIR evaluation data, and the result shows the effectiveness of the method.
A proposal for regime change/duration classification in chaotic systems

In order to to predict regime duration in a given chaotic system, for a set of output prototypes are available, we propose to use a clustering technique for the definition of classes of regime duration, which are then used by a chosen classifier. In this way, the exact boundaries between classes are allowed to emerge from the data, as long as prototypical values fall in distinct classes. We investigate the use of both unsupervised and semi-supervised fuzzy clustering techniques FCM and ssFCM, as well as the traditional k-Means technique. To classify the data, we use neuro-fuzzy system ANFIS and two decision trees (J48 and NBTree). We apply the procedure on the well-known Lorenz strange attractor, having bred vector counts as input variables.
Improving Word Alignment Using Syntactic Dependencies

We introduce a word alignment framework that facilitates the incorporation of syntax encoded in bilingual dependency tree pairs. Our model consists of two sub-models: an anchor word alignment model which aims to find a set of high-precision anchor links and a syntaxenhanced word alignment model which focuses on aligning the remaining words relying on dependency information invoked by the acquired anchor links. We show that our syntaxenhanced word alignment approach leads to a 10.32% and 5.57% relative decrease in alignment error rate compared to a generative word alignment model and a syntax-proof discriminative word alignment model respectively. Furthermore, our approach is evaluated extrinsically using a phrase-based statistical machine translation system. The results show that SMT systems based on our word alignment approach tend to generate shorter outputs. Without length penalty, using our word alignments yields statistically significant improvement in Chinese-English machine translation in comparison with the baseline word alignment.
Analysis of tribological behaviour of zirconia reinforced Al-SiC hybrid composites using statistical and artificial neural network technique

The tribological performance of aluminium hybrid composites reinforced with micro SiC (5 wt%) and nano zirconia (0, 3, 6 and 9 wt%) fabricated through powder metallurgy technique were investigated using statistical and artificial neural network (ANN) approach. The influence of zirconia reinforcement, sliding distance and applied load were analyzed with test based on full factorial design of experiments. Analysis of variance (ANOVA) was used to evaluate the percentage contribution of each process parameters on wear loss. ANOVA approach suggested that wear loss be mainly influenced by sliding distance followed by zirconia reinforcement and applied load. Further, a feed forward back propagation neural network was applied on input/output date for predicting and analyzing the wear behaviour of fabricated composite. A very close correlation between experimental and ANN output were achieved by implementing the model. Finally, ANN model was effectively used to find the influence of various control factors on wear behaviour of hybrid composites.
Favorable Outcomes Using an eHealth Approach to Promote Physical Activity and Nutrition Among Young African American Women

Background: Internet and mobile devices are widely used and provide alternative approaches for promoting healthy lifestyles, yet less information is available describing outcomes of these approaches when used with young African American (AA) women at risk for developing hypertension. Objective: In this study, we evaluated a Web-based, culturally relevant lifestyle change intervention targeting AA women (referred to as the eHealth study). Methods: African American women, aged 18 to 45 years, with untreated prehypertension and Internet access were eligible for a 12-week study that incorporated social cognitive theory strategies. Participants were randomized to (1) lifestyle physical activity (PA) or (2) Dietary Approaches to Stop Hypertension (DASH) online education modules. Results: The 14 DASH and 12 PA participant attributes were similar at baseline. The DASH participants had a significant change in total DASH score (P = .001) and large effect sizes for DASH components (vegetables, 0.84; nonfat dairy, 0.71; fruit, 0.62). The PA participants had a favorable change (+39%) in pedometer steps (P = .055). With respect to weight change, a large effect size was observed for PA (0.84) and smaller for DASH participants (0.18). Seventy-one percent of DASH and 48% of PA participants completed program activities, corresponding to a moderate difference in program engagement between groups (d = 0.58). Conclusion: Our eHealth platform provides an alternative approach for reaching young AA women and was successful with respect to improving PA and dietary behaviors. Furthermore, the eHealth approach has the potential as a powerful program for changing health behaviors for other at-risk populations.
Adaptive Noise Cancellation using Multirate Techniques

Abstract—This paper presents development of a new adaptive structure based on multirate filter and testing the same for deterministic, speech and music signals. A new class of FIR filtering algorithm based on the multirate approach is proposed. They not only reduce the computational complexity in FIR filtering, but also retain attractive implementation related properties such as regularity and multiply-and-accumulate (MAC)-structure. By virtue of the advantages of multirate FIR filtering algorithm, the proposed scheme can reduce the required computational complexity and reserve the MAC structure. It is observed that the convergence rate and steady state error is improved. An application of this approach in Adaptive Noise Canceller is considered.
Minimum Enclosing Circle Problem with Base Point

This article presents a linear time algorithm to solve a variant of the minimum enclosing circle (MEC) problem. The inputs are a point set S of size n, and a point b in the plane called the free point. Our goal is to locate a circle center o∗ such that the maximum distance of all points in S to o∗ divided by the distance from o∗ to b is minimized. The original investigation by Qiu et al. [5] found an O(n log n) algorithm using the furthest point Voronoi diagram of the point set S. This problem can be formulated as a generalized linear programming problem when the domain for the optimal solution is restricted and therefore, can be solved in linear expected time [3]. We describe here a simple deterministic linear time algorithm based on Meggido’s prune-and-search solution to the standard problem [4]. We extend our technique to solve similar variants of the MEC problem where the free point is replaced with other geometric objects such as a free line, a free line segment, and a set of free points.
Investigation of Polymer Coatings Formed by Polyvinyl Alcohol and Silver Nanoparticles on Copper Surface in Acid Medium by Means of Deep Convolutional Neural Networks

In order to assemble effective protective coatings against corrosion, electrochemical techniques such as linear potentiometry and cyclic voltammetry were performed on a copper surface in 0.1 mol·L−1 HCl solution containing 0.1% polyvinyl alcohol (PVA) in the absence and presence of silver nanoparticles (nAg/PVA). A recent paradigm was used to distinguish the features of the coatings, that is, a deep convolutional neural network (CNN) was implemented to automatically and hierarchically extract the discriminative characteristics from the information given by optical microscopy images. In our study, the material surface morphology, controlled by the CNN without the interference of the human factor, was successfully conducted to extract the similarities/differences between unprotected and protected surfaces in order to establish the PVA and nAg/PVA performance to retard copper corrosion. The CNN results were confirmed by the classical investigation of copper behavior in hydrochloric acid solution in the absence and presence of polyvinyl alcohol and silver nanoparticles. The electrochemical measurements showed that the corrosion current density (icorr) decreased and polarization resistance (Rp) increased, with both PVA and nAg/PVA being effective inhibitors for copper corrosion in an acid environment, forming polymer protective coatings by adsorption on the metal surface. Furthermore, scanning electron microscopy (SEM) certifies the formation of polymer coatings, revealing a specific morphology of the copper surface in the presence of PVA and nAg/PVA, very different from that of corroded copper in uninhibited solutions. Finally, the correlation of the CNN information with experimental data was reported.
Tag recommendation in software information sites

Nowadays, software engineers use a variety of online media to search and become informed of new and interesting technologies, and to learn from and help one another. We refer to these kinds of online media which help software engineers improve their performance in software development, maintenance and test processes as software information sites. It is common to see tags in software information sites and many sites allow users to tag various objects with their own words. Users increasingly use tags to describe the most important features of their posted contents or projects. In this paper, we propose TagCombine, an automatic tag recommendation method which analyzes objects in software information sites. TagCombine has 3 different components: 1. multilabel ranking component which considers tag recommendation as a multi-label learning problem; 2. similarity based ranking component which recommends tags from similar objects; 3. tag-term based ranking component which considers the relationship between different terms and tags, and recommends tags after analyzing the terms in the objects. We evaluate TagCombine on 2 software information sites, StackOverflow and Freecode, which contain 47,668 and 39,231 text documents, respectively, and 437 and 243 tags, respectively. Experiment results show that for StackOverflow, our TagCombine achieves recall@5 and recall@10 scores of 0.5964 and 0.7239, respectively; For Freecode, it achieves recall@5 and recall@10 scores of 0.6391 and 0.7773, respectively. Moreover, averaging over StackOverflow and Freecode results, we improve TagRec proposed by Al-Kofahi et al. by 22.65% and 14.95%, and the tag recommendation method proposed by Zangerle et al. by 18.5% and 7.35% for recall@5 and recall@10 scores.
Defining (trained) grapheme-color synesthesia

There is a current debate over the possibility and validity of synesthesia training experiments (Deroy and Spence, 2013; Rothen and Meier, 2014). In order to test whether a trainee should be considered to have acquired a trained form of synesthesia, a precise definition and specific diagnostic criteria of synesthesia are necessary. There is currently not one specific checklist available including all specific diagnostic methods and criteria, exacerbating the determination and interpretation of differences between (potentially) trained and genuine synesthesia. In order to facilitate communication surrounding these issues, we propose a practical guideline for diagnosing the specific characteristics that are typical of grapheme-color synesthesia (GCS). These guidelines can be applied to developmental cases of GCS, cases of trainees who may show synesthetic traits, and other types of acquired forms of GCS at the level of a single individual.
A real-time peak discovering method for audio fingerprinting

Discovering peaks is a premise of audio fingerprinting algorithms for audio information retrieval, which focus on spectrogram peak pairs. In this paper, we discuss finding peaks in a two-direction scanning method which use a dynamic threshold vector to find local maximal point as peaks. And then an improved method using a slide window with two grids is proposed for discovering peaks at real-time. In this method, two key steps are executed alternately: scanning and sliding. In each scanning step, new peaks are found. When the slide window method is used, experiments on a database with 400,000 songs show that the average query time is shorten and the recall rate is slightly decreased.
Comorbidity of postural orthostatic tachycardia syndrome and chronic fatigue syndrome in an Australian cohort

Patients with chronic fatigue syndrome (CFS) are frequently diagnosed with comorbid postural orthostatic tachycardia syndrome (POTS), suggesting a shared pathogenesis. The aim of this study was to examine the relationship between demographic characteristics, autonomic functioning and fatigue levels amongst CFS patients with and without comorbid POTS.
Erbium-doped polymer waveguide amplifiers for PCB-integrated optical links

Optical technologies are increasingly considered for use in high-performance electronic systems to overcome the performance bottleneck of electrical interconnects when operating at high frequencies and provide high-speed communication between electronic chips and modules. Polymer waveguides are leading candidates for implementing board-level optical interconnections as they exhibit favourable mechanical, thermal and optical properties for direct integration onto conventional printed circuit boards (PCBs). Numerous system demonstrators have been reported in recent years featuring different types of polymer materials and opto-electronic (OE) PCB designs. However, all demonstrated polymer-based interconnection technologies are currently passive, which limits the length of the on-board links and the number of components that can be connected in optical bus architectures. In this paper therefore, we present work towards the formation of low-cost optical waveguide amplifiers that can be readily integrated onto standard PCBs by combining two promising optical technologies: siloxane-based polymers and ultra-fast laser plasma implantation (ULPI). Siloxane-based waveguides exhibit high-temperature resistance in excess of 300°C and low loss at different wavelength ranges, while ULPI has been demonstrated to produce very high dopant concentrations in glass thin films with values of 1.63×1021 cm−3 recently reported in Er-doped silica layers. Here we present detailed simulation studies that demonstrate the potential to achieve a internal gain of up to 8 dB/cm from such structures and report on initial experimental work on Er-doped films and waveguides demonstrating photoluminescence and good lifetimes.
DNA DIRECTED ASSEMBLY OF GOLD-TIPPED METALLIC SINGLE-WALLED CARBON NANOTUBES INTO ELECTRICAL DEVICES

Carbon nanotubes have rightfully been regarded as a wonder material since their discovery by Iijima in 1991 and the subsequent elucidation of their many material properties. Their extreme strength is 10-fold higher than any industrial fiber. Their current density carrying capability is orders of magnitude higher than copper without failure from electromigration. Their high thermal conductivity bests diamond, and their structural versatility leads to either semiconducting or metallic electronic character. These properties all make the integration of carbon nanotubes into functional devices of high value. However, they remain a material of largely unrealized potential due to several challenges that arise in their integration into devices. Integration challenges of primary importance are the ability to sort the metallic species from the semiconducting species in a scalable manner and to exercise orientational control in placing the sorted species into electrical devices. Our research demonstrates a path that robustly addresses these important concerns. First we selectively and non-covalently functionalize the tips of only the metallic species with gold. This result allows for metallic tubes to be selectively used in DNA-directed assembly on electrode structures, solving both selectivity and orientation integration challenges. The performance of the resulting electronic device
Foreground segmentation with efficient selection from ICP outliers in 3D scene

Foreground segmentation enables dynamic reconstruction of the moving objects in static scenes. After KinectFusion had proposed a novel method that constructs the foreground from the Iterative Closest Point (ICP) outliers, numerous studies proposed filtration methods to reduce outlier noise. To this end, the relationship between outliers and the foreground is investigated, and a method to efficiently extract the foreground from outliers is proposed. The foreground is found to be directly connected to ICP distance outliers rather than the angle and distance outliers that have been used in past research. Quantitative results show that the proposed method outperforms prevalent foreground extraction methods, and attains an average increase of 11.8% in foreground quality. Moreover, real-time speed of 50 fps is achieved without heavy graph-based refinements, such as GrabCut. The proposed depth features surpass current 3D GrabCut, which only uses RGB-N.
Notizie sul restauro della facciata di San Petronio = Report on the conservation of the facade of San Pe tronio

Study of materials and their decay. Possible surface protection applied in the past; use of wax, ceresin, casein, lime, cleaning and protective treatment. Use of adhesives and fillers. Facing with paper the most damaged parts of the sculpture. Localized use of airbrasive cleaning after consolidation. Brass cramps to replace iron -- ICCROM -- ICCROM