Miracle-dz/UniFAR-FTUs huggingface dataset:
Internationalization Strategy and Performance of Small and Medium Sized Enterprises

Focusing on the timing and geographical scope of import and export activities of Belgian small and medium sized enterprises (SMEs), the paper analyzes the importance, structural features and performance implications of firms that recently started to export following the geographical configuration of their international trade operations and their year of establishment. The analysis allows us to separate firms that started to export in the period 1998-2005 into four distinct groups: born internationals, i.e. firms which were established less than five years before their first year of exporting and exporting to less than five countries in the same region (regional focus), born globals; young firms but with a more internationally diversified export portfolio, born again globals, i.e. firms similar to born globals but established longer than five years before their first exports and traditional internationalizers, firms established more than five years before their first export operations characterized by a narrow geographical scope of their exports. We find SME export growth to be driven by a small group of born global firms, accounting for 60 per cent of the total increase in SME exports between 1998 and 2005. Analyzing the structural feature of the different types of firms, we find born globals to be more productive and characterized by a higher R&D spending and intangible asset intensity compared to other types of traders. We next test if the typology matters for the observed export performance differences across firms over time. We find that born globals grow faster in terms of export sales, have a stronger commitment to export markets and are more likely to continue exporting. Born globals also have the highest failure rate, traditional internationalizers the lowest. These findings suggest strong risk/return tradeoffs among the strategies chosen by the different types of firms. Performing a dynamic analysis of changes in trade configurations of firms over the observation period, we investigate how these changes have an impact on performance. Specific attention is paid to firms that stop importing/exporting. Especially firms that move from being exporters to become two-way traders, i.e. also starting to import goods from other countries show the most marked increases in turnover and productivity. The final part of the study analyzes the relationship between export and import activities to particular countries following the sequence in which they occur. We find that the probability to start importing from a country is 4 times higher for firms already exporting to that country than for trading SMEs without prior export experience in that country.
Species Identification of Archaeological Skin Objects from Danish Bogs: Comparison between Mass Spectrometry-Based Peptide Sequencing and Microscopy-Based Methods

Denmark has an extraordinarily large and well-preserved collection of archaeological skin garments found in peat bogs, dated to approximately 920 BC – AD 775. These objects provide not only the possibility to study prehistoric skin costume and technologies, but also to investigate the animal species used for the production of skin garments. Until recently, species identification of archaeological skin was primarily performed by light and scanning electron microscopy or the analysis of ancient DNA. However, the efficacy of these methods can be limited due to the harsh, mostly acidic environment of peat bogs leading to morphological and molecular degradation within the samples. We compared species assignment results of twelve archaeological skin samples from Danish bogs using Mass Spectrometry (MS)-based peptide sequencing, against results obtained using light and scanning electron microscopy. While it was difficult to obtain reliable results using microscopy, MS enabled the identification of several species-diagnostic peptides, mostly from collagen and keratins, allowing confident species discrimination even among taxonomically close organisms, such as sheep and goat. Unlike previous MS-based methods, mostly relying on peptide fingerprinting, the shotgun sequencing approach we describe aims to identify the complete extracted ancient proteome, without preselected specific targets. As an example, we report the identification, in one of the samples, of two peptides uniquely assigned to bovine foetal haemoglobin, indicating the production of skin from a calf slaughtered within the first months of its life. We conclude that MS-based peptide sequencing is a reliable method for species identification of samples from bogs. The mass spectrometry proteomics data were deposited in the ProteomeXchange Consortium with the dataset identifier PXD001029.
Current Status and Prospects of Fishery Resources of the Indian Continental Shelf

Coastal fisheries are an important source of food, employment and foreign exchange. In Indra, the marine fish production Increased by about six times in the last 50 years reaching about 3.2 million tonnes in 2008. I provides employment to about one million fishermen and earns foreign exchange of nearly Rs. 1,00,000 million. Most of the marine fish landings are from fishing operations In coastal shelf area" especially from the shallower region ranging from 5 to 100 m depth. In the last few years, the production from coastal fisheries is almost stagnant as these fisheries are adversely affected by a number of problems and Issues, with serious consequences on the availability of fish and income to the fishers. As fisheries continue to be open access without any effective controls in place to limit the growth of fishing capacity and fishing effort or limit catches through a quota regime, the sector attracts more number of vessels and operators tend to invest more in technological improvements of fishing craft and gear.
Covariate-modulated rectangular latent Markov models with an unknown number of regime profiles

We derive a multivariate latent Markov model with number of latent states that can possibly change at each time point. We model both the manifest and latent distributions conditionally on explanatory variables. Bayesian inference is based on a transdimensional Markov Chain Monte Carlo approach, where Reversible Jump is separately performed for each time occasion. In a simulation study, we show how our approach can recover the true underlying sequence of latent states with high probability, and that it has lower bias than competitors. We conclude with an analysis of the well-being of 100 nations, as expressed by the dimensions of the Human Development Index, for six-time points spanning a period of 22 years. R code with an implementation is available as supplementary material, together with files for reproducing the data analysis.
Computational Aeroacoustics: An Overview

Abstract : An overview of recent advances in computational aeroacoustics (CAA) is presented. CAA algorithms must not be dispersive and dissipative. It should propagate waves supported by the Euler equations with the correct group velocities. Computation domains are inevitably finite in size. To avoid the reflection of acoustic and other outgoing waves at the boundaries of the computation domain, it is required that special boundary conditions be imposed at the boundary region. These boundary conditions either absorb all the outgoing waves without reflection or allow the waves to exit smoothly. High-order schemes, invariably, supports spurious short waves. These spurious waves tend to pollute the numerical solution. They must be selectively damped or filtered out. All these issues and relevant computation methods are briefly reviewed. Jet screech tones are known to have caused structural fatigue in military combat aircrafts. Numerical simulation of the jet screech phenomenon is presented as an example of a successful application of CAA.
Differential Transformation Method (DTM) for Approximate Solution of Ordinary Differential Equation (ODE)

This paper presents the differential transformation method to evaluate approximate solution of ordinary differential equation along with its application in electrical circuit problem in various time domain. The method has been well established with six test problems and comparison has been made between analytical and numerical results to obtain convergence to a fair degree of accuracy.The results obtained suggest that the present technique can be treated as an efficient and alternative method for solving initial and boundary value problems.
Incremental Acquisition of a Minimalist Grammar using an SMT-Solver

A central question in cognitive linguistics is how children everywhere can readily acquire Knowledge of Language (KoL) from (restrictive) Primary Linguistic Data (PLD) (Chomsky, 1986; Berwick et al., 2011; Chomsky, 2013). This study addresses this question by introducing a novel procedure, implemented as a working computer program, that uses an interactive theorem prover to incrementally infer a Minimalist Grammar (MG) (Stabler, 1996). The procedure, which is inspired by (Rayner et al., 1988) and builds on earlier work by (Indurkhya, 2020), takes the form of a computational model of child language acquisition (Berwick, 1985; Chomsky, 1965). The procedure takes as input a sequence of paired interface conditions i.e. each entry is a Phonological Form (PF), encoding a sentence, paired with a Logical Form (LF), which encodes thematic roles for each predicate as well as agreement relations; the input sequence, which corresponds to the PLD that a child is exposed to, is organized into a sequence of batches that the procedure consumes incrementally. The procedure outputs an MG lexicon, consisting of a set of (word, feature-sequence) pairings, that yields, for each entry in the input sequence, a minimalist derivation that satisfies the listed interface conditions; the output MG lexicon corresponds to the KoL that the child acquires from processing the PLD. The procedure, which models a child language learner, operates as follows. The initial state of the the learner is an empty MG lexicon. The procedure incrementally constructs an MG lexicon: at each step the procedure takes as input a batch of the PLD and the lexicon that constitutes the current state of the learner, and then it augments the input lexicon with the minimal set of additional lexical entries needed to ensure that the augmented lexicon will yield, for each entry in the batch of PLD, a minimalist derivation that satisfies the listed interface conditions.1 When processing a batch of the PLD,
Changes in the Timing of Phytoplankton Blooms Related to Diminished Ice Cover in the Arctic

Time series of satellite-derived surface chlorophyll-a concentration (Chl) in 1997–2009 were used to examine for trends in the timing of the annual phytoplankton bloom maximum. Significant trends towards earlier phytoplankton blooms were detected in about 11% of the area of the Arctic Ocean with valid Chl data, e.g. in the Hudson Bay, Foxe Basin, Baffin Sea, off the coasts of Greenland, in the Kara Sea and around Novaya Zemlya. These areas roughly coincide with areas where ice concentration has decreased in early summer (June), thus making the earlier blooms possible. In the selected areas, the annual phytoplankton bloom maximum has advanced by up to 50 days which may have consequences for the Arctic food chain and carbon cycling. Outside the Arctic, the annual Chl maximum has become earlier in boreal North Pacific but later in the North Atlantic.
Critical Assessment of Automatic Traffic Sign Detection Using Three-Dimensional LiDAR Point Cloud Data

Traffic signs are important roadside appurtenances that provide critical guidance to road users including regulations, destinations, and safety related information. Traffic signs need to be inventoried by transportation agencies for asset management and maintenance purposes. However, the traditional method of manually inventorying signs is dangerous, labor-intensive, and time-consuming. There is a need for a safer and more effective traffic sign inventory method. This paper is the first that critically assesses the use of an automatic method for traffic sign detection using 3D LiDAR point cloud data in support of traffic sign inventory. The contribution of this paper is three-fold: 1) it presents an automatic method for traffic sign inventory using 3D LiDAR point cloud data; 2) it critically assesses the performance of the presented method in terms of detection rate and false negative/false positive cases; 3) it suggests the adequate parameter values to achieve a good traffic sign detection rate. Actual data, collected on Interstate 95 (major arterial) and 37th Street in Savannah, Georgia (local road), is used to assess the performance. Results show that the presented method can correctly detect 94.0% and 91.4% of the traffic signs on both roadways, respectively, with less than 7 false positive cases. The results demonstrate that the presented method using 3D LiDAR point cloud data is promising for traffic sign inventory. Future research directions are recommended.
A Study on the PM 2.5 Source Characteristics Affecting the Seoul Area Using a Chemical Mass Balance Receptor Model

The purpose of this study is to study the source characteristics affecting the Seoul area using a chemical mass balance (CMB) receptor model. This study was also to evaluate the source profiles, which were directly measured and developed. Asian Dust Storm usually occurred in the spring, and very high concentrations were observed in the fall among the sampling periods. So the ambient data collected in the spring and fall were evaluated. The CMB model results as well as the source profiles were validated using the diagnostic categories, such as: source contribution estimate, t-statistic, R-square, Chi-square, and percent of total mass explained. In the spring months, the magnitude of mass contributors was in the following order: Chinese aerosol $(31.7\%)>$ secondary aerosols (: ammonium sulfate and ammonium nitrate $8.9\%)>$ vehicles (: gasoline vehicle and diesel vehicles $14.7\%)>$biomass burning $(15.5\%)>$ geological material . In the fall months, the general trend of the mass contributors was the following: biomass burning $(31.1\%)>$ vehicles (: gasoline vehicle and diesel vehicles $21.8\%)>$ secondary aerosols (: ammonium sulfate and ammonium nitrate $13.9\%)>$ Chinese aerosol . The results show that the mass in the Seoul area was mainly affected by the Chinese area.
Cementless total hip arthroplasty in rheumatoid arthritis

Patients suffering from rheumatoid arthritis typically have a poor subchondral bone quality, endangering implant fixation. Using finite element analysis (FEA) an investigation was made to find whether a press-fit acetabular implant with a polar clearance would reduce interfacial micromotions and improve fixation compared with a standard hemispherical design. In addition, the effects of interference fit, friction, and implant material were analysed. Cups were introduced into an FEA model of a human pelvis with simulated subchondral bone plasticity. The models were loaded with a loading configuration simulating two cycles of normal walking, during which contact stresses and interfacial micromotions were monitored.Subsequently, a lever-out simulation was performed to assess the fixation strength of the various cases. A flattened cup with good bone quality produced the lowest interfacial micromotions. Poor bone decreased the fixation strength regardless of the geometry of the cup. Increasing the interference fit of the flattened cup compensated for the loss of fixation strength caused by poor bone quality. In conclusion, a flattened cup did not significantly improve implant fixation over a hemispherical cup in the case of poor bone quality. However, implant fixation can be optimized by increasing interference fit and avoiding inferior frictional properties and low-stiffness implants.
Removal of Invasive Fire-Prone Grasses to Increase Training Lands in the Pacific

Abstract : This report represents the final deliverable for the 2007 Legacy Resource Management Program project number 07-362 (Cooperative agreement W912DY-07-2-0008), titled "Removal of Invasive Fire-prone Grasses to Increase Training Lands in the Pacific". This project was developed and carried out by SWCA Environmental Consultants (SWCA) to determine the effectiveness of three different methods in reducing the surface fuel loads in a guinea grass (Panicum maximum) dominated community, thereby reducing susceptibly to sustained fires. Three control treatments were tested including mechanical removal, herbicide application and grazing using cattle to reduce the fuel loads at Marine Corps Training Area Bellows (MCTAB), on the island of O'ahu, Hawai'i. Information on the cost of the various control treatments and their long-term effectiveness in maintaining reduced fuel loads would also benefit land and resource managers in the Pacific Islands where guinea grass and frequent fires are problematic.
Are native bees and Apis mellifera equally efficient pollinators of the rupestrian grassland daisy Aspilia jolyana (Asteraceae)?

Most angiosperms rely on animals for pollination, and insects, especially bees, are the most frequent pollinators. Many native Neotropical plants are frequently visited by the invasive honeybee ( Apis mellifera) , but its role in the pollination of these plants has been little investigated. We assessed the contribution of various floral visitors, including native bees and the honeybee, on the pollination of a generalist rupestrian grassland daisy, Aspilia jolyana (Asteraceae), in Serra do Cipó, Espinhaço Mountain Range, Brazil. We recorded floral visitors and measured the seed set resulting from one single visitation. We observed a total of 442 visits, mostly by bees, with Bombus pauloensis and Apis mellifera being the most common floral visitors. Other visitors included many other species of bees, flies, hummingbirds, wasps and butterflies. Pollinators significantly increased seed set in comparison to non-visited (bagged) capitula. Moreover, there was no difference among bee species/groups in their contribution to seed set. Thus, A. jolyana benefits from its generalized pollination strategy, and frequent bee visitors, including several native species and the invasive honeybee, are equally effective pollinators for this generalist daisy of rupestrian grasslands.
Image-based material editing

Photo editing software allows digital images to be blurred, warped or re-colored at the touch of a button. However, it is not currently possible to change the material appearance of an object except by painstakingly painting over the appropriate pixels. Here we present a method for automatically replacing one material with another, completely different material, starting with only a single high dynamic range image as input. Our approach exploits the fact that human vision is surprisingly tolerant of certain (sometimes enormous) physical inaccuracies, while being sensitive to others. By adjusting our simulations to be careful about those aspects to which the human visual system is sensitive, we are for the first time able to demonstrate significant material changes on the basis of a single photograph as input.
Multi-objective optimal reactive power dispatch for distribution system

This paper presents Multi-Objective Differential Evolution (MODE) algorithm for multi-objective optimal reactive power dispatch to minimize real power loss, total voltage deviation and total capacity of reactive power sources in distribution system. In a distribution system integrated with distributed generation (DG), optimal reactive power dispatch can be carried out by controlling the reactive power of the DG and reactive power compensation devices like capacitor banks, FACTS devices and other sources of reactor power. Optimal reactive power dispatch (ORPD) problem has been formulated as a non-linear, constrained, multi-objective optimization problem, with equality and inequality constraints, for minimization of system real power losses, improvement voltage profile with minimum total capacity of reactive power sources. Effectiveness of the proposed MODE algorithm has been demonstrated for optimal reactive power Dispatch in the standard IEEE 33-bus radial distribution system having distributed generators and reactive power sources.
Small area estimation for health surveys

This thesis develops and evaluates Small Area Estimation (SAE) methods to provide estimates of prevalence rates of health risk factors for Local Government Areas (LGAs) in NSW using data from the NSW Population Health Survey. All outcome variables considered are dichotomous. The aim is to produce estimates that are an improvement over direct survey estimates based on a single year of data as well as over direct estimates based on data aggregated over seven years. Modified direct estimators, conventional synthetic and composite estimators, Empirical Best Linear Unbiased Predictors (EBLUP), complex synthetic estimators using a linear model, Empirical Best Predictors (EBP) and associated synthetic estimators based on the logistic model are assessed initially for the outcome variable ‘Current Smoking’ using 2006 survey data. All estimates are produced using SAS Version 9.2. Model-based SAE methods using regression models and area level random effects are found to be the most effective approach to create unbiased LGA-level estimates for ‘Current Smoking’, and are successful in creating estimates with face-validity when based on a single year of data. Of the other methods assessed neither LGA-based weighting nor generalised regression (GREG) estimates are shown to improve the direct LGA-level estimates sufficiently for them to be more useful than the current direct estimates. Conventional synthetic and composite estimators produce over-smoothed LGA-level estimates. In addition the näive estimates of the mean square error (MSE) of these estimators underestimate the bias, and estimation of the root mean square error (RMSE) is difficult. The EBLUP and EBP estimates and their associated synthetic counterparts are created and evaluated for four key outcome variables (‘Current Smoking’, ‘Risk Alcohol Consumption’, ‘Overweight or obese’ and ‘Have difficulties getting health care when needed’), by sex, for survey years 2006, 2007 and 2008. These outcome variables differ in their overall prevalence rate and level of intraclass correlation. Included in the evaluation process is an assessment of the effect of covariate specification. The
Infant mortality statistics from the 2008 period linked birth/infant death data set.

OBJECTIVES This report presents 2008 period infant mortality statistics from the linked birth/infant death data set (linked file) by a variety of maternal and infant characteristics. The linked file differs from the mortality file, which is based entirely on death certificate data. METHODS Descriptive tabulations of data are presented and interpreted. RESULTS The U.S. infant mortality rate was 6.61 infant deaths per 1,000 live births in 2008, 2 percent lower than the rate of 6.75 in 2007. Infant mortality rates ranged from 4.51 per 1,000 live births for Asian or Pacific Islander mothers to 12.67 for non-Hispanic black mothers. The rate for non-Hispanic black women declined 5 percent from 2007 to 2008. Infant mortality was higher for male infants and infants born preterm or at low birthweight. Infant mortality rates were also higher for those infants who were born in multiple deliveries, to mothers who were unmarried, and for those whose mothers were born in the 50 states or the District of Columbia. From 2007 to 2008, the neonatal mortality rate (under age 28 days) declined by 3 percent to 4.29 neonatal deaths per 1,000 live births, while the postneonatal mortality rate (aged 28 days to under 1 year) remained essentially unchanged (2.32). Preterm and low birthweight infants had the highest infant mortality rates and contributed greatly to the overall U.S. infant mortality. The three leading causes of infant death--congenital malformations, low birthweight, and sudden infant death syndrome--accounted for 46 percent of all infant deaths. In 2008, 35.4 percent of infant deaths were "preterm-related. "