Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceptual and Ergonomic Issues in Mobile Augmented Reality for Urban Operations

Twenty-five years ago a computing revolution occurred as computers moved to the desktop. Today, a similar revolution is beginning that will fundamentally transform how we access information. As computers become ever lighter and less expensive, they are moving off the desktop and are becoming mounted in vehicles, appliances and tools, as well as worn on our bodies. In twenty years imbedded and worn computers will be ubiquitous, and so effectively using them will be critical for the Navy-after-next. They will provide “information everywhere,” and they are going to require fundamentally new paradigms for displaying and interacting with information. An important sub-category of display and interaction, especially for worn and vehicle-mounted computers, will be augmented reality (AR), where information is rendered onto see-through glasses or windshields so that it overlays relevant parts of the real world (see Figure 1).
TOWARD AN UNDERSTANDING OF THE RELATIONSHIP BETWEEN L2 READING COMPREHENSION AND GRAMMATICAL COMPETENCE

L2 strategy research has shown that poor readers tend to process language in a word-forword fashion, directing attention to the words and structures of a passage, whereas moreskilled readers focus on meaningful relations to and within the material. Given these tendencies, a comparison of performance on form-focused grammar activities and meaning-driven reading comprehension activities among beginning students of French was conducted. A negative correlation between success on either activity was expected. Conflicting findings of varying significance are discussed.
OPTIMAL RESOURCE ALLOCATION AND TOLL PATTERNS IN USER-OPTIMISED TRANSPORT NETWORKS

VERY GENERAL FORMULATION OF THE PROBLEM FACED BY ANY TRANSPORT PLANNING GROUP IS DISCUSSED: THAT OF OPTIMALLY ALLOCATING ITS ROAD IMPROVEMENT BUDGET TO AN EXISTING NETWORK SO AS TO MINIMIZE TRAVEL TIME AND CONGESTION FOR USERS OF THE NETWORK UNDER ITS JURISDICTION. IF CONGESTION TOLLS ARE RULED OUT AS A MEANS OF BURDENING TRAVELERS WITH THE COSTS THEY IMPOSE ON OTHERS, THEN THE DETERMINATION OF THE INVESTMENT PATTERN THAT MINIMIZES COSTS TO USERS PLUS A CAPITAL RENTAL CHARGE ON THE INVESTMENT ITSELF IS COMPUTATIONALLY INFEASIBLE. IF, ON THE OTHER HAND, INDIVIDUALS ARE FORCED TO EXPLICITLY CONSIDER THE IMPACT THEIR TRAVEL HAS ON OTHERS BY MEANS OF CONGESTION TOLLS, THEN THE CHOICE OF AN OPTIMAL INVESTMENT PATTERN BECOMES COMPUTATIONALLY FEASIBLE BY STANDARD MARGINAL PRODUCTIVITY METHODS. THE PROBLEM OF RESOURCE ALLOCATION IS PRESENTED IN THE CASE OF AN EXTREMELY SIMPLE NETWORK CONSISTING OF TWO PARALLEL LINKS CONNECTING A COMMON ORIGIN AND DESTINATION. THE FINAL SECTION THEN SHOWS THAT THE RESULTS SHOWN TO HOLD IN SIMPLE SYSTEMS HOLD FOR NETWORKS OF AN ARBITRARY DEGREE OF COMPLEXITY, AND DEALS WITH THE NECESSITY OF PATH, RATHER THAN LINK, TOLLS. /AUTHOR/
Gender recognition using neural networks and ASR techniques

The paper presents the simple technique of speaker gender recognition that uses MFCC features typically applied in automatic speech recognition. Artiﬁcial neural network is used as a classiﬁer. The speech signal is ﬁrst divided into 20 ms frames. For each frame, Mel-Frequency Cepstral Coefﬁcients are extracted and the created feature vector is provided into a neural network classiﬁer, which individually classiﬁes each frame as male or female sample. Finally, the whole utterance is classiﬁed by selecting the class, for which the sum of corresponding neural network outputs is greater. The advantage of the method is that it can be easily combined with speech recognition, because both processes (gender recognition and speech recognition) are based on the same features. This way, no additional logic and no extra computational power is needed to extract features necessary for gender recognition. The method was experimentally evaluated using speech samples in English and in Polish. The comparison with other methods described in literature based on other feature extraction methods shows the superiority of the proposed approach, especially in cases where the recognition is carried out in noisy environment or using poor audio equipment.
Regularization Parameter Selections via Generalized Information Criterion

We apply the nonconcave penalized likelihood approach to obtain variable selections as well as shrinkage estimators. This approach relies heavily on the choice of regularization parameter, which controls the model complexity. In this paper, we propose employing the generalized information criterion, encompassing the commonly used Akaike information criterion (AIC) and Bayesian information criterion (BIC), for selecting the regularization parameter. Our proposal makes a connection between the classical variable selection criteria and the regularization parameter selections for the nonconcave penalized likelihood approaches. We show that the BIC-type selector enables identification of the true model consistently, and the resulting estimator possesses the oracle property in the terminology of Fan and Li (2001). In contrast, however, the AIC-type selector tends to overfit with positive probability. We further show that the AIC-type selector is asymptotically loss efficient, while the BIC-type selector is not. Our simulation results confirm these theoretical findings, and an empirical example is presented. Some technical proofs are given in the online supplementary material.
Using the Process Approach to Teach Writing in 6 Hong Kong Primary Classrooms.

Background: In most primary schools in Hong Kong, a product-oriented approach is used in teaching writing. The process approach to writing has been seen as an improvement over the traditional methods of writing instruction in recent years. However, the effectiveness of using the process approach to teach writing is still inconclusive. It is necessary to confirm its effectiveness through further research studies. Aims: This study investigates how effective process writing is in helping about 200 students in the upper primary school level and the lower primary school level improve their writing skills and their attitude towards writing. Sample and method: Six primary school teachers, 3 in the lower primary school level and 3 in the upper primary school level, each implemented an innovative two-month process writing programme in her school. The effectiveness of the programme was investigated through post-interviews and the comparison of a pre- and post-questionnaire, a pre-test and a post-test, and pre- and post- observations of the strategies used by the students in doing their pre-tests and post-tests. Results: It is found that the programme brought about positive results across all classes and in both the upper and lower level in general though the results in each classroom slightly differed. Conclusions/Recommendations: The process approach seems to be an effective approach even at as low a level as P.3 in the primary school. Process writing seems to be a feasible solution to heightening the writing abilities and confidence of students, especially those who have higher English proficiency and those at the upper primary level.
Adaptive-Frame-Based Dynamic Slot Assignment Protocol for Tactical Data Link System

In multi-hop self-organizing tactical data link system, some real-time message streams need more than one slot to transmit in a frame, and have strict rate requirements and distance constraints. It is very difficult to guarantee Quality of Service (QoS) in thus system. To solve the problem , we propose a TDMA slot assignment protocol, named adaptive-frame-based dynamic slot assignment protocol (ADSAP), which can change the frame length dynamically by setting frame length as a power of 2 slots. ADSAP assigns one or multiple unassigned slots to a node according to its message stream model. If there is no unassigned slot available, the frame length can be enlarged to generate unassigned slots, and if there is too many unassigned slots in the frame of a node, ADSAP can shrink the frame to improve channel utilization. Furthermore, we verify the effectiveness of our proposed protocol by simulation experiments. The results show that our proposed protocol can meet the needs of the information delivering in tactical data link, and has better performance as compared with the conventional protocols.
A framework for personalizing web search with concept-based user profiles

Personalized search is an important means to improve the performance of a search engine. In this article, we propose a framework that supports mining a user's conceptual preferences from users' clickthrough data resulting from Web search. The discovered preferences are utilized to adapt a search engine's ranking function. In this framework, an extended set of conceptual preferences was derived for a user based on the concepts extracted from the search results and the clickthrough data. Then, a concept-based user profile (CUP) representing the user profile as a concept ontology tree is generated. Finally, the CUP is input to a support vector machine (SVM) to learn a concept preference vector for adapting a personalized ranking function that reranks the search results. In order to achieve more flexible personalization, the framework allows a user to control the amount of specific CUP ontology information to be exposed to the personalized search engine. We study various parameters, such as conceptual relationships and concept features, arising from CUP that affect the ranking quality. Experiments confirm that our approach is able to significantly improve the retrieval effectiveness for the user. Further, our proposed control parameters of CUP information can adjust the exposed user information more smoothly and maintain better ranking quality than the existing methods.
Cell-Associated Flagella Enhance the Protection Conferred by Mucosally-Administered Attenuated Salmonella Paratyphi A Vaccines

Background Antibiotic-resistant Salmonella enterica serovar Paratyphi A, the agent of paratyphoid A fever, poses an emerging public health dilemma in endemic areas of Asia and among travelers, as there is no licensed vaccine. Integral to our efforts to develop a S. Paratyphi A vaccine, we addressed the role of flagella as a potential protective antigen by comparing cell-associated flagella with exported flagellin subunits expressed by attenuated strains. Methodology S. Paratyphi A strain ATCC 9150 was first deleted for the chromosomal guaBA locus, creating CVD 1901. Further chromosomal deletions in fliD (CVD 1901D) or flgK (CVD 1901K) were then engineered, resulting in the export of unpolymerized FliC, without impairing its overall expression. The virulence of the resulting isogenic strains was examined using a novel mouse LD50 model to accommodate the human-host restricted S. Paratyphi A. The immunogenicity of the attenuated strains was then tested using a mouse intranasal model, followed by intraperitoneal challenge with wildtype ATCC 9150. Results Mucosal (intranasal) immunization of mice with strain CVD 1901 expressing cell-associated flagella conferred superior protection (vaccine efficacy [VE], 90%) against a lethal intraperitoneal challenge, compared with the flagellin monomer-exporting mutants CVD 1901K (30% VE) or CVD 1901D (47% VE). The superior protection induced by CVD 1901 with its cell-attached flagella was associated with an increased IgG2a∶IgG1 ratio of FliC-specific antibodies with enhanced opsonophagocytic capacity. Conclusions Our results clearly suggest that enhanced anti-FliC antibody-mediated clearance of S. Paratyphi A by phagocytic cells, induced by vaccines expressing cell-associated rather than exported FliC, might be contributing to the vaccine-induced protection from S. Paratyphi A challenge in vivo. We speculate that an excess of IgG1 anti-FliC antibodies induced by the exported FliC may compete with the IgG2a subtype and block binding to specific phagocyte Fc receptors that are critical for clearing an S. Paratyphi A infection.
Magnetic resonance imaging methods in developmental science: A primer

Abstract Structural and functional magnetic resonance imaging (MRI) are increasingly common research methods among investigators interested in typically and atypically developing populations. However, the effective use of these tools requires an understanding of the basis of the magnetic resonance signal, as well as some of the additional experimental complications that arise when collecting MRI data from developmental populations. This primer provides a foundation for investigators who wish to utilize MRI methods in their research and whose primary interest involves typically and atypically developing populations. The basic concepts of MRI physics are introduced, as well as the typical MRI scanner components and their role in MRI data acquisition. In addition, a variety of scan types (structural, functional, diffusion tensor) are discussed, along with a number of important experimental design factors that can impact the quality and utility of the data collected. Special consideration is given to working with pediatric and special populations.
Determinants of Fish Export Performance in Oman

Abstract The objective of this study was to identify the key variables affecting export performance at the firm level and draw the policy implications necessary to enhance Oman fish exports. The methodology adopted is inspired from the international marketing literature, which postulates that export performance is determined by both internal factors, under the control of the firm, and external factors. Empirically, the study used an econometric model and a firm survey data to investigate the link between export intensity, defined as the proportion of export sale to total sale and 4 sets of firm-level specific factors: (1) firm size and competencies, (2) management characteristics, (3) management perceptions and attitude, and (4) marketing strategy. Results show that both the age and firm size, measured by the number of years in business and the number of employees, had no significant effect on export performance. Managers' education level, previous work experience, commitment to exporting activities, diversification, and availability of information on foreign markets are all significant variables, positively affecting export performance. These results underscore a role of the private sector in upgrading their human and physical capital and the role of a government as a public good provider in securing information and providing financial incentives to reduce risk associated with diversifying export
Mitochondrial Serine Acetyltransferase Functions as a Pacemaker of Cysteine Synthesis in Plant Cells1[C][W][OA]

Cysteine (Cys) synthesis in plants is carried out by two sequential reactions catalyzed by the rate-limiting enzyme serine acetyltransferase (SAT) and excess amounts of O-acetylserine(thiol)lyase. Why these reactions occur in plastids, mitochondria, and cytosol of plants remained unclear. Expression of artificial microRNA (amiRNA) against Sat3 encoding mitochondrial SAT3 in transgenic Arabidopsis (Arabidopsis thaliana) plants demonstrates that mitochondria are the most important compartment for the synthesis of O-acetylserine (OAS), the precursor of Cys. Reduction of RNA levels, protein contents, SAT enzymatic activity, and phenotype strongly correlate in independent amiSAT3 lines and cause significantly retarded growth. The expression of the other four Sat genes in the Arabidopsis genome are not affected by amiRNA-SAT3 according to quantitative real-time polymerase chain reaction and microarray analyses. Application of radiolabeled serine to leaf pieces revealed severely reduced incorporation rates into Cys and even more so into glutathione. Accordingly, steady-state levels of OAS are 4-fold reduced. Decrease of sulfate reduction-related genes is accompanied by an accumulation of sulfate in amiSAT3 lines. These results unequivocally show that mitochondria provide the bulk of OAS in the plant cell and are the likely site of flux regulation. Together with recent data, the cytosol appears to be a major site of Cys synthesis, while plastids contribute reduced sulfur as sulfide. Thus, Cys synthesis in plants is significantly different from that in nonphotosynthetic eukaryotes at the cellular level.
Mechanism of action of hydroxyl-docosahexaenoic acid molecule in the treatment of Alzheimer’s disease: identification of potential receptors in brain

Alzheimer’s disease (AD) is a neurodegenerative disorder very alive in today’s society. One of the drugs tested in animals which has shown neuroprotective properties is LP226A1 (a DHA α-hydroxylated derivative). The aim of this work was focused on the investigation of the mechanism of action of this drug. Specifically, our work was focused on searching for and isolating of LP226A1 binding proteins (LP226BPs) by separation of membrane proteins from mouse cortex by ion exchange (IEX) and hydrophobicity (HIC) chromatography using different sodium chloride (NaCl) concentrations as eluent. The resulting fractions from those techniques were tested in radio-binding assays to LP226A1 in order to test the presence of LP226BPs. Interestingly, our results showed two different protein fractions from IEX with evident binding to LP226A1. One of them was further separated by HIC in order to get LP226BP-enriched fractions. This additional analysis revealed other two fractions which showed binding to LP226A1 and that might be considered as semi-purified LP226BPs. On the other hand, affinity chromatography was addressed to isolate LP226BPs from soluble protein fractions. For this purpose, the drug was anchored to nitrocellulose. Such anchorage was confirmed by gas chromatography. This LP226A1-bound nitrocellulose was used as stationary phase for affinity chromatography, and indeed, this was incubated with soluble protein from mouse cortex and treated under different conditions in order to promote interaction between anchored LP226A1 with soluble proteins from the medium. Captured proteins were eluted and the resulting samples were analysed by electrophoresis and coomassie blue staining. The results showed that binding of soluble proteins was not via LP226A1, and in fact, they were non-specifically bound to the nitrocellulose membrane. Finally, western blot analysis was performed to analyse FA2H expression (enzyme in charge of fatty acid α-hydroxylation) in human brain samples from AD patients and healthy controls. These results showed a percentage of AD patients with up-regulated levels of FA2H as compared with healthy controls which might indicate a neuronal response to counteract the early onset of the neuropathology
The Oblivion Problem: Exploiting Forgotten Items to Improve Recommendation Diversity

Recommender Systems (RSs) have become a crucial tool to assist users in their choices on various commercial applications. Despite recent advances, there is still room for more effective tech niques that are applicable to a larger range of domains. A major challenge recurrently researched is the lack of diversity in the recom mendation lists provided by current RSs. That is, besides being effective to suggest interesting items to users, a good RS should provide useful and diversified items. In order to address this proble m, we evaluate the use of forgotten items in recommendation. By forgotten items, we mean items that have been very relevant to users in the past but are not anymore. Therefore, we formally define th e Oblivion Problem, which is the problem of recommending forgotten items, propose a methodology for verifying it in real scenarios, and perform a deep characterization of this problem in a relevant music domain, the Last.fm system. Applying our methodology to Last.fm has demonstrated the existence of the oblivion problem in practice, as well as showed the utility of this methodology. Further, the behavior exhibited by forgotten items in Last.fm suggests that defining techniques that incorporate such items into RSs con sists in a promising research direction.
Structural change and new entrants in UK agriculture: examining the role of county farms and the Fresh Start initiative in Cornwall

In the context of the trend towards fewer and larger farms, and an ageing farming population, this paper examines the attempts by two schemes – the County Farms Estate (CFE) and the Fresh Start (FS) initiative in Cornwall – to provide opportunities for new farmers to enter agriculture in an affordable manner. The number of county farms has continued to decline since the 1950s through processes of farm amalgamation and disposal by county and unitary authorities. While the average size of those remaining has risen, this has not been at the same rate as that engendered through general processes of structural change in UK agriculture. FS has provided a range of support to help improve the vibrancy of the farming industry in Cornwall, but its overall impact has been limited. The extent to which these schemes have either contributed to or slowed down the process of structural change in UK agriculture is debatable.
Single Frequency Inverse Obstacle Scattering: A Sparsity Constrained Linear Sampling Method Approach

The linear sampling method (LSM) offers a qualitative image reconstruction approach, which is known as a viable alternative for obstacle support identification to the well-studied filtered backprojection (FBP), which depends on a linearized forward scattering model. Of practical interest is the imaging of obstacles from sparse aperture far-field data under a fixed single frequency mode of operation. Under this scenario, the Tikhonov regularization typically applied to LSM produces poor images that fail to capture the obstacle boundary. In this paper, we employ an alternative regularization strategy based on constraining the sparsity of the solution's spatial gradient. Two regularization approaches based on the spatial gradient are developed. A numerical comparison to the FBP demonstrates that the new method's ability to account for aspect-dependent scattering permits more accurate reconstruction of concave obstacles, whereas a comparison to Tikhonov-regularized LSM demonstrates that the proposed approach significantly improves obstacle recovery with sparse-aperture data.
Classification Improvement Based on Automatic Clustering Assisted Feature Combination

this paper, we demonstrate a feature combination process based on automatic clustering. This procedure delivers a better classification result than the traditional classification models. In our experiment, we detect the best cluster number for each feature based on the distribution off feature data with a specially designed cluster number decision formula called HCV function. This function estimates the best intra-and inter-cluster relationship with a harmonic-based mean calculation. With HCV, we successfully decrease the number of parameters needed in our feature combination process in respect to our previous method. According to the experiment, we found a better ROC performance than traditional classifier and other configurations with our design.
Building a Flexible Software Factory Using Partial Domain Specific Models

This paper describes some experiences in building a software factory by defining multiple small domain specific languages (DSLs) and having multiple small models per DSL. This is in high contrast with traditional approaches using monolithic models, e.g. written in UML. In our approach, models behave like source code to a large extend, leading to an easy way to manage the model(s) of large systems.
Normalization as a Preprocessing Engine for Data Mining and the Approach of Preference Matrix

This study is emphasized on different types of normalization. Each of which was tested against the ID3 methodology using the HSV data set. Number of leaf nodes, accuracy, and tree growing time are three factors that were taken into account. Comparisons between different learning methods were accomplished as they were applied to each normalization method. A simple matrix was designed to check for the best normalization method based on the factors and their priorities. Recommendations were concluded