Miracle-dz/UniFAR-FTUs huggingface dataset:
Personalized Book Recommendation to Young Readers: Two Online Prototypes and A Preliminary User Evaluation

Online learning platforms that aim to improve reading interests and proficiency of young readers, particularly students in elementary schools, rarely have automated personalized recommendation services. This study attempts to bridge this gap by developing and evaluating two book recommenders that are integrated into an online learning platform for young readers. A preliminary user experiment was conducted to measure the effectiveness and usability of the recommender prototypes. Results of think-aloud usability testing, post-test questionnaires, and a semi-structured interview verified the feasibility of adding these book recommenders to improve personalization of the online learning platform. Further improvements of the recommenders were also suggested. The user evaluation framework provides a reference for future studies on personalized learning material recommendation.
An Authoritative Approach to Citation Classification

The ability to understand not only that a piece of research has been cited, but why it has been cited has wide-ranging applications in the areas of research evaluation, in tracking the dissemination of new ideas and in better understanding research impact. There have been several studies that have collated datasets of citations annotated according to type using a class schema. These have favoured annotation by independent annotators and the datasets produced have been fairly small. We argue that authors themselves are in a primary position to answer the question of why something was cited. No previous study has, to our knowledge, undertaken such a large-scale survey of authors to ascertain their own personal reasons for citation. In this work, we introduce a new methodology for annotating citations and a significant new dataset of 11,233 citations annotated by 883 authors. This is the largest dataset of its type compiled to date, the first truly multi-disciplinary dataset and the only dataset annotated by authors. We also demonstrate the scalability of our data collection approach and perform a comparison between this new dataset and those gathered by two previous studies.
A Multimodal Music Recommendation System with Listeners' Personality and Physiological Signals

This preliminary study explored multiple information sources for music recommendation system (MRS), including users' personality traits measured by the Ten-Item Personality Inventory (TIPI) and physiological signals recorded by a wearable wristband. A dataset of 23 participants and 628 song listening records were obtained from a user experiment, with matched personality, physiological signals as well as music acoustic features. Based on the dataset, a machine learning experiment with four regression algorithms was conducted to compare recommendation performances across different combinations of feature sets. Results show that personality features contributed significantly to the improvement of recommender accuracy, while physiological features contributed less. Analysis of top features in the best performing model revealed the importance of some physiological features. Future studies are called for to further investigate multimodal MRS through exploiting user properties and context data.
Challenges and Opportunities for Accessible Seoul Metropolitan Buses: An Interview Study of People with Visual Impairments

Nowadays, a number of people with visual impairments (PVI) access public buses in the Seoul metropolitan area. Existing studies reported the challenges PVI faced when they use buses in multiple cities. Nevertheless, little is known about the accessibility issues of Seoul metropolitan buses (SMB). To reduce the gap, we conducted semi-structured interviews with nine PVI to investigate the challenges and opportunities for accessible SMB. We discovered ten challenges PVI faced when they use SMB. Based on the identified challenges, we propose three opportunities for improving accessibility of the SMB system.
Understanding Learner Behavior Through Learning Design Informed Learning Analytics

A goal of learning analytics is to inform and improve learning design. Previous studies have attempted to interpret learners' clickstream data based on learning science theories. Many of these interpretations are made without reference to the specific learning designs of the courses being analyzed. Here, we report on a learning design informed analytics exploration of an introductory MOOC on Computer Science and Python programming. The learning resources (videos) and practice resources (short exercises and problem sets) are analyzed according to the knowledge types and cognitive process levels respectively, both based on a revised Bloom's Taxonomy. A heat map visualization of the access intensity on a learner resource access transition matrix and social network analysis are used to analyze learners' behavior with respect to the different resource categories. The results show distinctively different patterns of access between groups of students with different course performance and different academic backgrounds.
How to Organize Digital Tools to Help Scholars in Digital Humanities Research?

In recent years, Digital Humanities (DH) tools play a more and more important role in humanities research and education. But there is lack of well-developed classification system to organize these tools, which makes it difficult for humanities scholars to find suitable digital support at various stages of research work. An effective classification system for DH tools should be designed according to the process of humanities research, thus help humanities scholars to locate suitable tools accordingly. In this study, we interviewed 20 humanities scholars and analyzed 60 widely-used DH tools. We derived 9 research tasks (processing, exploration, collection, collation, analysis, interpretation, presentation, reading and communication) and 4 research stages of humanities research process from interviews, and 4 categories of research techniques (text analysis, network analysis, geospatial analysis, and temporal analysis) from analyzing DH tools. Thus, a two-dimensional classification system was developed based on the humanities research process and applied research techniques. Then the collected DH tools were organized into this classification system, and a navigation website was developed to enable humanities scholars to find digital humanities resources effectively and efficiently.
Susceptibility of Pseudomonas aeruginosa isolated from urine to some antibiotics

Pseudomonas aeruginosa is a member of genus Pseudomonas that it is Gram – negative , glucose nonfermenting aerobic rod , isolated from chronic UTI . It is resistant to high concentration of salts and dyes , weak antiseptics and commonly used antibiotics. Because of the increasing in drug – resistant of strains of P. aeruginosa especially that which isolated from UTI, this study was done among the patients attending hospitals in Al-Najaf city during January to December 2009 to maintain the susceptibility pattern of organism isolated from urine specimens. A total 72(100%) samples of P. aeruginosa were isolated from urine specimens of patients. The bacteria isolated were identified by colony morphology , microscopy and relevant biochemical tests. Antimicrobial sensitivity pattern was tested using standard guidelines. Almost all of the P. aeruginosa isolates were sensitive to Amikacin(100%) , Norfloxacin(86 % ( Ciprofloxacin(83 %) & Tobramycin(83%) but highly resistant to Doxycycline.
Evasive behavior of spotted and spinner dolphins (Stenella attenuata and S. longirostris) during fi shing for yellowfi n tuna (Thunnus albacares) in the eastern Pacifi c Ocean

The tuna fi shery in the eastern Pacifi c Ocean (EPO) sets purse seines in three major modes: school, log, and dolphin fi shing. Yellowfi n tuna (Thunnus albacares) and certain species of dolphins are found to associate in the EPO. The spotted dolphin (Stenella attenuata) is by far the most important species from the point of view of its frequency of association with tuna and its use by fi shermen for catching tuna (Perrin, 1969). The frequent appearance of spinner dolphins (Stenella longirostris) in sets also makes this species signifi cant, although in almost all cases it appears in mixed herds with the spotted dolphin (National Research Council, 1992). During “dolphin fi shing” or “fi shing on dolphins,” the net is set around the tuna and the dolphins after a period of chase. Once a dolphin herd is sighted with high-power binoculars (25×), four Evasive behavior of spotted and spinner dolphins (Stenella attenuata and S. longirostris) during fi shing for yellowfi n tuna (Thunnus albacares) in the eastern Pacifi c Ocean
Combinatorial CRISPR screening reveals functional buffering in autophagy

Functional genomics studies in model organisms and human cell lines provided important insights into gene functions and their context-dependent role in genetic circuits. However, our functional understanding of many of these genes and how they combinatorically regulate key biological processes, remains limited. To enable the SpCas9-dependent mapping of gene-gene interactions in human cells, we established 3Cs multiplexing for the generation of combinatorial gRNA libraries in a distribution-unbiased manner and demonstrate its robust performance. The optimal number for combinatorial hit calling was 16 gRNA pairs and the skew of a library’s distribution was identified as a critical parameter dictating experimental scale and data quality. Our approach enabled us to investigate 247,032 gRNA-pairs targeting 12,736 gene-interactions in human autophagy. We identified novel genes essential for autophagy and provide experimental evidence that gene-associated categories of phenotypic strengths exist in autophagy. Furthermore, circuits of autophagy gene interactions reveal redundant nodes driven by paralog genes. Our combinatorial 3Cs approach is broadly suitable to investigate unexpected gene-interaction phenotypes in unperturbed and diseased cell contexts.
Threatened medicinal plants of Gurez valley, Kashmir Himalayas: distribution pattern and current conservation status

Due to increasing demand and subsequent pressures on medicinal plants, it is imperative to understand their distribution and conservation status in their natural habitats. We studied the distribution pattern and current conservation status of six threatened medicinal plants in alpine grassland of Gurez valley, Kashmir, by random quadrate sampling (n = 315) in different habitat types. Informal interviews and group discussions with family elders were held to obtain information on different uses of medicinal plants. Our results indicate that Podophyllum hexandrum Royle is most common and has the highest density, while Picrorhiza kurroa Royle ex Benth and Dactylorhiza hatagirea (D. Don) Soo are least frequent. Flat tableland (FL) situated above the tree line and moist rocky slopes (MR) were the most preferred habitats followed by moist meadow (MM) while the shady slopes (SSs) and flat meadow (FM) (stable) were least preferred. The plant species are used to cure different ailments at a household level while a few are also sold commercially. However, the degree and nature of use varies between the communities. Our findings can help to formulate a conservation strategy for the hitherto unknown grasslands of Gurez valley. While the low and localized distribution of all studied species deserves effective conservation strategies, the scope of such measures should also be user specific to address the reliance of local communities on these plants.
Structural-Electromagnetic Simulation Coupling and Conformal Antenna Design Tool

Airborne and spaceborne radar has long been an effective tool for remote sensing, surveillance, and reconnaissance. Most airborne systems utilize antenna arrays that are installed inside the moldline of the aircraft or in radomes that protect the array from in-flight loads. While externally-mounted arrays can offer the advantage of larger apertures, sensor-vehicle interactions often result in performance degradation of both systems. The presence of an externally-mounted array will increase the vehicle’s drag and potentially affect the dynamics and control of the vehicle. In addition, in-flight structural loads will deform the array, thus resulting in relative phase errors. While there exist a multitude of physics-based simulation tools to determine the effects of the array on the aircraft performance, existing tools are not sufficient for generating deformed arrays necessary for determining in-flight array performance. In response to this need, a computer tool for analyzing antennas undergoing structural loads is developed. The Antenna Deformation Tool (ADT) has two primary uses: generating deformed geometry from the output of a structural Finite Element Model (FEM) for use in an Electromagnetic (EM) simulation, and designing conformal antenna arrays. The two commercial software packages ADT is optimized for are MSC NASTRAN and ANSYS HFSS. Specifically, ADT is designed to generate a deformed 3D Computer Aided Design (CAD) model from a NASTRAN structural mesh. The resulting CAD model is compatible with HFSS electromagnetic simulation software for the assessment of the effects of loads on performance. The main purpose for the development of ADT is to facilitate studies of how structural deformations affect airborne antenna arrays performance and to provide the capability to perform studies easily and quickly
A functional hierarchy for choice in medial prefrontal cortex

Hierarchical approaches to functional neuroanatomy propose that choice-relevant brain regions have overlapping functions and can be organized into a series that progressively transforms information about options into choices. Here, we examined responses of neurons in four regions of the medial prefrontal cortex as macaques performed two-option risky choices. All four regions encoded economic variables in similar proportions and showed putative signatures of key choice-related computations. We found evidence for a hierarchical organization proceeding from areas 14→25→32→24. Specifically, we found that decodability of eight distinct task variables increased along that path, consistent with the idea that hierarchically later regions make these variables more separable. We also found longer intrinsic timescales in the same series, further supporting the idea of a hierarchy. Together these results highlight the importance of the medial wall in choice, endorse a specific hierarchical organization, and argue against a modular functional neuroanatomy of choice.
From Motivation to Organizational Identity of Members in Non-profit Organizations: The Role of Collectivism

This study contributes to our understanding of organizational identity through dichotomous motivations of altruism and egoism in non-profit organizations (NPO). By applying an empirical analysis of NPO members, organizational identity is found to be well explained by altruistic motivation and egoistic motivation. More importantly, this study finds that collectivism positively moderates the relationship between altruistic motivation and organizational identity, and negatively moderates the relationship between egoistic motivation and organizational identity. It is noticeable that altruistic motivations have a stronger impact on organizational identity when collectivism is high, while egoistic motivations have a stronger impact on organizational identity when collectivism is low. Finally, this study generates helpful management implications based on research findings. It is suggested that the managers of NPOs could enhance members’ organizational identity by taking motivations and collectivism into consideration, that is to say, in order to build up organizational identity of NPO members, both righteousness and shared interests matter simultaneously.
Ecological Validation and Reliability of Hexoskin Wearable Body Metrics Tool in Measuring Pre-exercise and Peak Heart Rate During Shuttle Run Test in Professional Handball Players

The aim of the study was to assess the validity and reliability of wearable body metric Hexoskin “smart shirt” in measuring heart rate (HR) at pre-exercise and during peak effort in a field test incorporating vigorous movements of the upper body. Measurements were recorded simultaneously using the Hexoskin and Polar Team Pro. Nine male professional handball players (age: 21.8 ± 2.4 years; weight: 83 ± 10.26 kg; height: 1.81 ± 0.09 m; and BMI: 25.17 ± 2.23) volitionally participated in the study by completing two 400 m shuttle run test trials (10 shuttles), each separated by a 48 to 72 h recovery period. Results indicated significant correlations between Hexoskin and Polar Team Pro system in pre-exercise HR. Hexoskin provided erroneous measurements in four of the nine athletes during peak effort. Subsequent correction yielded no consistency between the Polar Team Pro system and Hexoskin between the first and the second trial. Hexoskin showed significant reliability in pre-exercise HR. However, Hexoskin picked up excessive artifact during vigorous physical activity in four of the nine athletes rendering the results in these cases useless. Nevertheless, in athletes where artifact was not an issue, ICC yielded a good estimate. The main findings indicate that Hexoskin has good validity and reliability in measuring pre-exercise HR in handball players and hence may be used with high confidence in slow motion activities. However, vigorous physical activity with jarring multidirectional upper body movements posed a challenge for Hexoskin.
Comparing the Impact of Programming Assessment Type: In-Class Vs Take-Home

In engineering education, educational technologies and teaching interventions are often used to maintain the student retention high. Most of them are strongly related to either in-class or take-home assessment. This paper compares the impact of both assessments on student performance for one academic semester. The findings are expected to re-align the focus of educational technology and teaching intervention research. Fifty-five laboratory sessions were analysed, involving five Introductory Programming classes with a total of 87 Information Technology and Information System undergraduates. The study shows that, by considering only significant changes, in-class assessment leads to higher assessment mark as the students can easily seek help and focus on the tasks. Technical problems are also unlikely to occur as the classroom (or the laboratory in our case) is well-facilitated.
Profil Tuberkulosis Pada Anak Di Instalasi Rawat Jalan RSUD. Raden Mattaher Jambi

ABSTRACT Background: Tuberculosis (TB) in children is a very worrying phenomenon because it potentially causes a variety of problems, starting from cases of failure to growth, disability and even death. The symptoms of Tuberculosis in children are often non specific, so that, over diagnosis and followed by over treatment are often happen. In another cases, under diagnosis and under treatment are also found. TB diagnosis in children refers on finding the mycobacterium (MTB) from sputum, gastric lavage, biopsy, etc. But, these kind of examinations are difficult and rare to get and it makes almost of tuberculosis diagnosis in children enforced by clinical symptoms, radiological imaging and tuberculin test. Objective: The aim of this research is to know the profile of patients with tuberculosis in children in outpatient installation of Raden Mattaher Hospital Jambi. Methods: Descriptive-prospective research. The subject of this research is all children who gets treatment in outpatient policlinic of pediatrics and already diagnosed as TB (New case) by pediatrician which based on criteria and scoring system from IDAI. Results: Tuberculosis in boys (60%), comparing with girls 3 : 2. Age group under 5 years (56%) and primary school age (44%). Children with poor nutrition and malnutrition (60%). Children with BCG immunization and positive scar (60%), and children with BCG Immunization and negative scar (43%). The most presenting symptoms and signs were cough (96%), fever (84%), history contact of adult with tuberculosis (60%), positive Tuberculin Test (42%) and Radiographic findings of Tuberculosis (78%) Conclusion: The most common patients was in age group under 6 years (56%) and 6-12 years (42%). The most important high risk of tuberculosis infection in children is contact of adult with tuberculosis. Therefore, it is important to detect infection of tuberculosis in adult and find out its transmission in order to early detecting of child with high risk of tuberculosis infection. Prevention of tuberculosis in children is one of the most important thing to do. Keyword: Tuberculosis in children. Contact of adult with tuberculosis. Clinical symptoms and Tuberculin Test.
Evaluation of polygenic prediction methodology within a reference-standardized framework

Background The predictive utility of polygenic scores is increasing, and many polygenic scoring methods are available, but it is unclear which method performs best. This study evaluates the predictive utility of polygenic scoring methods within a reference-standardized framework, which uses a common set of variants and reference-based estimates of linkage disequilibrium and allele frequencies to construct scores. Methods Six polygenic score methods were tested: p-value thresholding and clumping (pT+clump), SBLUP, lassosum, LDPred, PRScs and SBayesR, evaluating their performance to predict outcomes in UK Biobank and the Twins Early Development Study (TEDS). Strategies to identify optimal p-value threshold and shrinkage parameters were compared, including 10-fold cross validation, pseudovalidation (with no validation sample), and multi-polygenic score elastic net models. Results lassosum, PRScs and LDPred performed strongly using 10-fold cross-validation to identify the most predictive p-value threshold or shrinkage parameter, giving a relative improvement of 14-17% over pT+clump in the correlation between observed and predicted outcome values. Using pseudovalidation, the best method was PRScs, with a relative improvement of >11% over other pseudovalidation methods (lassosum, SBLUP, SBayesR, LDPred), and only 1% less than the best polygenic score identified by 10-fold cross validation. Elastic net models containing polygenic scores based on a range of parameters consistently improved prediction over any single polygenic score. Conclusion Within a reference-standardized framework, the best polygenic prediction was achieved using lassosum and PRScs, modeling multiple polygenic scores derived using multiple parameters. This study will help researchers performing polygenic score studies to select the most powerful and predictive analysis methods.
Point Cloud vs. Mesh Features for Building Interior Classification

Interpreting 3D point cloud data of the interior and exterior of buildings is essential for automated navigation, interaction and 3D reconstruction. However, the direct exploitation of the geometry is challenging due to inherent obstacles such as noise, occlusions, sparsity or variance in the density. Alternatively, 3D mesh geometries derived from point clouds benefit from preprocessing routines that can surmount these obstacles and potentially result in more refined geometry and topology descriptions. In this article, we provide a rigorous comparison of both geometries for scene interpretation. We present an empirical study on the suitability of both geometries for the feature extraction and classification. More specifically, we study the impact for the retrieval of structural building components in a realistic environment which is a major endeavor in Building Information Modeling (BIM) reconstruction. The study runs on segment-based structuration of both geometries and shows that both achieve recognition rates over 75% F1 score when suitable features are used.