Miracle-dz/UniFAR-FTUs huggingface dataset:
Language standardization in sociolinguistics and international business: Theory and practice across the table

This chapter addresses the issue of language standardization from two perspectives, bringing together a theoretical perspective offered by the discipline of sociolinguistics with a practical example from international business. We introduce the broad concept of standardization and embed the study of language standardization in the wider discussion of standards as a means of control across society. We analyse the language policy and practice of the Danish multinational, Grundfos, and use it as a “sociolinguistic laboratory” to “test” the theory of language standardization initially elaborated by Einar Haugen to explain the history of modern Norwegian. The table is then turned and a model from International Business by Piekkari, Welch and Welch is used to illuminate recent Norwegian language planning. It is found that the Grundfos case works well with the Haugen model, and the International Business model provides a valuable practical lesson for national language planners, both showing that a “comparative standardology” is a valuable undertaking. More voices “at the table” will allow both theory and practice to be further refined and for the role of standards across society to be better understood.
Author ' s personal copy Gender differences in the functional and structural neuroanatomy of mathematical cognition

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t a r t i c l e i n f o Keywords: Gender Sex differences Mental arithmetic fMRI Frontal lobe Parietal cortex Intra-parietal sulcus Lingual gyrus Parahippocampal gyrus Dorsal visual stream Ventral visual stream Default mode network Despite ongoing debate about the nature of gender differences in mathematics achievement, little is known about gender similarities and differences in mathematical cognition at the neural level. We used fMRI to compare brain responses in 25 females and 24 males during a mental arithmetic task involving 3-operand addition and subtraction. We also used voxel-based morphometry (VBM) to examine gender differences in brain structure. Although females and males did not differ in accuracy or response times (effect size d b 0.3), significant gender differences in functional brain activation were observed in the right dorsal and ventral visuospatial information processing streams (d N 1.1). Males showed greater dorsal stream activation in the right intra-parietal sulcus areas important for numerical cognition, and angular gyrus regions of the default mode network that are typically deactivated during complex cognitive tasks, as well as greater ventral stream activation in the right lingual and parahippocampal gyri. VBM revealed an opposite pattern of gender differences—compared to males, females had greater regional density and greater regional volume in dorsal and ventral stream regions where males showed greater fMRI activation. There were no brain areas where females showed greater functional activation than males, and no brain areas where males showed greater structural density or volume than females. Our findings provide evidence for gender differences in the functional and structural organization of the right hemisphere brain areas involved in mathematical cognition. Together with the lack of behavioral differences, our results point to more efficient use of neural processing resources in females. In the past few decades, scientists and the public alike have debated the existence of gender differences in mathematical skills The question of gender differences in mathematics has been particularly contentious because of its widespread implications for academic achievement, career choice, and professional success in engineering and the sciences (Jacobs, 2005). Despite the stereotypic view that males are " better " at mathematics, evidence for …
A Model of the Tapping Zone

Model Overview and Background Information The tapping zone of a maple tree is defined as the area around the circumference of the stem that can be utilized for sap collection. For sap collection with tubing, it can be thought of as a radial band of wood based at the point on a tree where the dropline meets the lateral tubing of the sap collection system. The physical boundaries of the tapping zone are defined by the depth of the taphole, the length of the sap dropline, and the circumference of the tree (Figure 1). Each year, tapping for sap collection not only permanently removes a small amount of wood from the taphole itself, but, in addition, the tree’s response to the taphole wound generates a “stained” column of wood extending above and below the taphole that remains permanently nonconductive to sap (Figure 2). However, stem growth also adds new conductive wood to the outside of the tree each year. This outward growth functionally shifts the tapping zone outward over time so that some of the nonconductive wood generated by previous tapping is embedded deeper into the tree and is thus no longer within the tapping zone boundaries. Thus, the volume of the tapping zone of a particular tree, and the relative amounts of conductive and nonconductive wood within it over time, are dependent on the tree’s size and growth rate, as well as tapping practices – tapping depth, spout size, dropline length, and the number of taps. And, these volumes can be calculated for any given time using these input parameters (Figure 3). Based on these premises, we developed a model that calculates the proportions of conductive and nonconductive wood in the tapping zone of a tree over time given user-input values for tree diameter and tapping practices. (The model is described in greater detail below.) Nonconductive wood (“NCW”) is generally brownish in color, and can be observed in cross-sections (cookies) or lateral sections (boards) of cut trees (Figure 2), and detected as relatively dry, brown wood chips when a damaged area is inadvertently drilled into during tapping (Figure 4). Tapholes drilled into NCW will produce little or no sap, and an excessive buildup of NCW can affect the physiological functioning of water transport and negatively impact tree health. The total proportion of the tree’s tapping zone that is comprised of this NCW will determine how frequently it is hit during tapping
Research on Service Robot Vision Alignment Algorithm Based on the SIFT Characteristic

For service robot vision localization requirements, the localization technology research based on the image SIFT characteristic was introduced. The space examination, the precise positions of characteristic points, the direction parameters of the assigned operator and the description of the characteristic point were analyzed. At the same time, the stability under the condition of image zoom, rotation and affine transformation was analyzed according to experiments. Experiments result shows that the SIFT characteristic has the proportion zoom invariability, the revolving invariability, the part affine invariability and a high recognition rate at complex environments. On the basis of above work, the vision localization method based on SIFT characteristic turns out to be an applicable technology in in-building complex environment.
Understanding vegetation response to climate variability from space with hyper-spectral, multi-angular observations

Many vegetation properties are related to features of reflectance spectra in the region 400 nm - 2500 nm. and to emittance in region 8 mm - 14 mm Detailed observations of spectral reflectance reveal subtle features related to biochemical components of leaves such as chlorophyll and water. Exchange of energy between the biosphere and the atmosphere is an important mechanism determining the response of vegetation to climate variability. This requires measurements of the component temperature of foliage and soil. The latter are closely related to the angular variation in thermal infrared emittance. The architecture of vegetation canopies determines complex changes of observed reflectance and emittance spectra with view and illumination angle. Quantitative analysis of reflectance and emittance spectra requires, therefore, an accurate characterization of the anisotropy of radiance. This can be achieved with nearly - simultaneous observations at different view angles. The Surface Processes and Ecosystem Changes Through Response Analysis (SPECTRA) Mission has been conceived to perform these observations at high spatial resolution by taking advantage of the spacecraft agility. Scientific preparations are pursued along two avenues: a) the nature of the expected data and candidate algorithms are evaluated by generating and using synthetic hyper - spectral multi - angular/radiometric data; b) algorithms are evaluated with actual hyper - spectral data collected with a variety of airborne systems and concurrent ground measurements; Campaigns have been performed using radiometric observations provided by ATSR, AATSR, AirMISR, CHRIS - PROBA and a variety of airborne hyperspectral systems. The paper will cover highlights of these studies.
Interference-Cooperation in Multi-User/Multi-Operator Receivers

In a multi-user scenario where users belong to different operators, any interference mitigation method needs unavoidably some degree of cooperation among service providers. In this paper we propose a cooperation strategy based on the exchange of mutual interference among operators, rather than of decoded data, to let every operator to recover an augmented degree of diversity either for channel estimation and multi-user detection. In xDSL scenario where multiple operators share the same cable binder the interference-cooperation (IC) approach outperforms data-exchange methods and preserves to certain degree the privacy of the users as signals can be tailored to prevent each operator to infer parameters (channel and data) of the users from the other operators. The IC method is based on Expectation Maximization estimation shaped to account for the degree of information that each operator can exchange with the others during the two steps of multi-user channel estimation and multi-user detection. Convergence of IC is guaranteed into few iterations and it does not depend on the structure of the interference. IC performance attains those of centralized receivers (i.e., one fusion-center that collects all the received signals from all the users/operators), with some loss when in heavily interfered multi-user channel such as in twisted-pair communications allocated beyond 50-100MHz spectrum.
ASSESSMENT OF LIDAR-DERIVED TREE HEIGHTS ESTIMATED FROM DIFFERENT FLIGHT ALTITUDE DATA IN MOUNTAINOUS FORESTS WITH POOR LASER PENETRATION RATES

In this study, the effects of different flight altitudes on tree height estimates with a small-footprint scanning lidar were investigated and assessed in mountainous forests with poor laser penetration rates. The study area was closed-canopy evergreen coniferous plantations dominated by Japanese cedar (Cryptomeria japonica) and hinoki cypress (Chamaecyparis obtusa) in Japan. The stand age ranged from 33 to 100 years and the area was undulating terrain with a variation in elevation ranging from 135 to 391 m above sea level. A total of 33 circular sample plots (0.04 ha) were established and predominant mean tree heights for each plot were calculated using individual tree heights within each sample plot. Data from three different flight altitudes (500 m, 1000 m, and 1500 m) were acquired with Optech ALTM3100 sensor in late summer 2006. The settings of lidar system were paid attention as the laser footprints should cover the targeted area without omission, i.e. the laser spot spacing should be close to footprint diameter in the resultant data. Owing to this idea, we were able to theoretically avoid missing treetops and passing through the canopy gaps just by chance for a given transmitted laser pulse. The results of this study demonstrate that the higher platform altitude would reduce both the penetration rates and the intensities of laser pulses, and affect not only the quality of digital surface model, but also the quality of digital terrain model more significantly in forests with undulating topographies, thus indicating the less accurate estimates of lidarderived tree heights.
What has my classifier learned? Visualizing the classification rules of bag-of-feature model by support region detection

In the past decade, the bag-of-feature model has established itself as the state-of-the-art method in various visual classification tasks. Despite its simplicity and high performance, it normally works as a black box and the classification rule is not transparent to users. However, to better understand the classification process, it is favorable to look into the black box to see how an image is recognized. To fill this gap, we developed a tool called Restricted Support Region Set (RSRS) Detection which can be utilized to visualize the image regions that are critical to the classification decision. More specifically, we define the Restricted Support Region Set for a given image as such a set of size-restricted and non-overlapped regions that if any one of them is removed the image will be wrongly classified. Focusing on the state-of-the-art bag-of-feature classification system, we developed an efficient RSRS detection algorithm and discussed its applications. We showed that it can be used to identify the limitation of a classifier, predict its failure mode, discover the classification rules and reveal the database bias. Moreover, as experimentally demonstrated, this tool also enables common users to efficiently tune the classifier by removing the inappropriate support regions, which can lead to a better generalization performance.
Role stressors and organizational commitment: public sector employment in St Lucia

Purpose - The purpose of this paper is to investigate the relationships among role conflict, role ambiguity, the three dimensions of organizational commitment, and turnover intentions. In addition, the paper tests the moderating effect of perceived alternatives in the relationship between continuance commitment and turnover intentions. Design/methodology/approach - The research was a cross-sectional study of employees in the public sector in St Lucia. In total, 226 usable questionnaires were obtained. Hierarchical regression analyses were used to test the hypotheses. Findings - It was found that role ambiguity and conflict were negatively associated with affective and normative commitment. Also, there were negative relationships between the three dimensions of organizational commitment and turnover intentions. There was no significant relationship between employees' role stressors and their continuance commitment. Employees with continuance commitment develop turnover cognitions when alternative jobs are available. Research limitations/implications - More research using data from the public sector in developing countries is advocated. Studies should incorporate three dimensions of organizational commitment and also assess pay satisfaction. Moderators that might change employees' normative and affective commitment should be explored. Practical implications - It is suggested that the sector should reduce role stressors to enhance employees' commitment. Employees should be offered competitive salaries to minimize turnover of employees with affective and normative commitment. This will serve to minimize retention of mainly employees with high continuance commitment. Originality/value - This is one of the few studies that have examined organizational commitment in the public sector using data from a developing country.
Obstacle Avoidance for Autonomous Ground Vehicles in Outdoor Environments

The paper presents an obstacle avoidance algorithm to be used for autonomous ground vehicles applications. The proposed method improves some of the limitations of the recently developed null space based behavioral control. The technique divides the problem into tasks, which are associated to increasing priority. Activities with lower priority do not interfere with those having higher priority. The scenario is supposed known only partially, and the complete environment is reconstructed during the mission, with the aid of stereoscopic vision sensors. The validity of the method is currently verified via computer simulations.
Sequential and Automatic Image-Sequence Registration of Road Areas Monitored from a Hovering Helicopter

In this paper, we propose an automatic and sequential method for the registration of an image sequence of a road area without ignoring scene-induced motion. This method contributes to a larger work, aiming at vehicle tracking. A typical image sequence is recorded from a helicopter hovering above the freeway. The demand for automation is inevitable due to the large number of images and continuous changes in the traffic situation and weather conditions. A framework is designed and implemented for this purpose. The registration errors are removed in a sequential way based on two homography assumptions. First, an approximate registration is obtained, which is efficiently refined in a second step, using a restricted search area. The results of the stabilization framework are demonstrated on an image sequence consisting of 1500 images and show that our method allows a registration between arbitrary images in the sequence with a geometric error of zero in pixel accuracy.
A Refined Differential Evolution Algorithm Based Fuzzy Classifier for Intrusion Detection

The growing prevalence of network attacks is a well-known problem which can impact the availability, confidentiality, and integrity of critical information for both individuals and enterprises. The security of networked computers plays a strategic role in modern computer systems. The most important reason is the difficulties in obtaining adequate attack data for the supervised classifiers to model the attack patterns, and the data acquisition task is always time-consuming and greatly relies on the domain experts. This task is so complicated because the determination of normal and abnormal behaviors in computer networks is hard, as the boundaries cannot be well defined. One of the difficulties in such a prediction process is the generation of false alarms in many anomaly based intrusion detection systems. This paper proposes a refined differential evolution (RDE) search algorithm to generate fuzzy rules capable of detecting intrusive behaviors. In the presented algorithm the global population is divided into subpopulations, each assigned to a distinct processor. Each subpopulation consists of the same class fuzzy rules. These rules evolve independently in the proposed parallel manner. A series of experimental results on the well-known KDD Cup 1999 data set demonstrate that the proposed method is more robust and effective than the state-of-theart previous intrusion detection methods, as well as can be further optimized as discussed in this paper for real applications of intrusion detection system.
Saccharomyces cerevisiae Dmc1 and Rad51 Proteins Preferentially Function with Tid1 and Rad54 Proteins, Respectively, to Promote DNA Strand Invasion during Genetic Recombination*

Background: DNA strand exchange proteins Dmc1 and Rad51 and translocases Tid1 and Rad54 function in DNA break repair during meiosis. Results: We biochemically demonstrate that Dmc1 and Rad51 are specifically stimulated by Tid1 and Rad54, respectively. Conclusion: Dmc1-Tid1 and Rad51-Rad54 represent functional pairs for DNA pairing and joint molecule formation. Significance: The separate and independent functioning of these proteins offers insight into DNA pairing in meiosis. The Saccharomyces cerevisiae Dmc1 and Tid1 proteins are required for the pairing of homologous chromosomes during meiotic recombination. This pairing is the precursor to the formation of crossovers between homologs, an event that is necessary for the accurate segregation of chromosomes. Failure to form crossovers can have serious consequences and may lead to chromosomal imbalance. Dmc1, a meiosis-specific paralog of Rad51, mediates the pairing of homologous chromosomes. Tid1, a Rad54 paralog, although not meiosis-specific, interacts with Dmc1 and promotes crossover formation between homologs. In this study, we show that purified Dmc1 and Tid1 interact physically and functionally. Dmc1 forms stable nucleoprotein filaments that can mediate DNA strand invasion. Tid1 stimulates Dmc1-mediated formation of joint molecules. Under conditions optimal for Dmc1 reactions, Rad51 is specifically stimulated by Rad54, establishing that Dmc1-Tid1 and Rad51-Rad54 function as specific pairs. Physical interaction studies show that specificity in function is not dictated by direct interactions between the proteins. Our data are consistent with the hypothesis that Rad51-Rad54 function together to promote intersister DNA strand exchange, whereas Dmc1-Tid1 tilt the bias toward interhomolog DNA strand exchange.
The effect of prior surgery on blood oxygen level-dependent functional MR imaging in the preoperative assessment of brain tumors.

BACKGROUND AND PURPOSE Blood oxygen level-dependent functional MR imaging (BOLD fMRI) is a clinically useful technique for preoperative mapping of eloquent cortices in patients with brain tumors. The purpose of this study was to determine the effect on BOLD fMRI accuracy of susceptibility artifacts caused by prior surgery by comparing volumes of activation in the primary motor cortex (PMC) of patients with and without prior brain surgery. METHODS The volumes of fMRI activation of the PMC were measured for the tumor and nontumor sides in patients with (n = 13) and without (n = 30) prior neurosurgery. Statistical comparisons of the volumes were performed by using paired t tests and linear regression analysis. The location and degree of susceptibility artifact were subjectively assessed. RESULTS No significant difference was found between the mean tumor and nontumor volumes of fMRI activations in patients without prior surgery (P = .51). In patients who had prior surgery, the volume of activation was significantly smaller on the side of the prior operation when compared with the contralateral side (P = .001). The volume of activation on the side of the tumor was also significantly smaller in the patients with prior surgery compared with those without prior surgery (P < .001). Nevertheless, the PMC was identified in all cases, and its location was confirmed intraoperatively. CONCLUSION Prior surgery is associated with a decrease in the volume of fMRI activation in patients with prior surgery; however, by examining the T2 images, an astute radiologist can recognize this phenomenon, draw the appropriate conclusions, and correctly identify the PMC.
Model‐based Clustering of Categorical Time Series with Multinomial Logit Classification

A common problem in many areas of applied statistics is to identify groups of similar time series in a panel of time series. However, distance‐based clustering methods cannot easily be extended to time series data, where an appropriate distance‐measure is rather difficult to define, particularly for discrete‐valued time series.Markov chain clustering, proposed by Pamminger and Fruhwirth‐Schnatter [6], is an approach for clustering discrete‐valued time series obtained by observing a categorical variable with several states. This model‐based clustering method is based on finite mixtures of first‐order time‐homogeneous Markov chain models.In order to further explain group membership we present an extension to the approach of Pamminger and Fruhwirth‐Schnatter [6] by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule by using a multinomial logit model.The parameters are estimated for a fixed number of clusters within a Bayesian framework using an Markov ch.