LLukas22/scidocs huggingface dataset:
Online Learning: Examining the Successful Student Profile

Can anyone learn anywhere at anytime or are there required pre-requisite skills or strategies to achieve such learning? Certainly, it seems logical to assume that access, availability of hardware, and knowledge of software are some of the items required, but are there others? Are there strategies and skills that can be taught to promote greater success? Does the successful online learner need to possess specific skills or strategies to be successful? This paper details Phase I of a longitudinal study investigating distance learning students' technical skills, cognitive/metacognitive learning strategies, motivation, and stages of concern as they enter an online Masters of Education in Educational Technology degree program. Preliminary results indicate that the program seems to attract relatively new, young in-service teachers that are confident in their technology skills that might be seen as leaders in their field. Because the degree program demands a great deal of peer collaboration within the course work, particular attention was paid to data regarding the cognitive learning strategy of peer collaboration and help seeking. Although, these students indicated that they would utilize peer collaboration as a learning strategy, they might be more apt to utilize it from a help seeking aspect. However, they also indicated that if they did seek help it would probably be from the instructor first. Online courses and degree programs are becoming available through most of our universities. In fact, many institutions fear that they will be extinct if they do not offer Web-based distance education courses (Roblyer, 1999). Although many studies have provided evidence that distance learning is able to offer learning opportunities that are equal to traditional learning environments (Moore & Kearsley, 1996), online courses and online degree programs beg many questions of validity and value of the actual learning opportunities offered. Given that online learning can be of equal quality to those that are face-to-face, the questions become: Can anyone learn anywhere at anytime or are there required prerequisite skills or strategies needed to achieve such learning? Certainly, it seems logical to assume that access, availability of hardware, and knowledge of software are some of the items required, but are there others? Are there strategies and skills that can be taught to promote greater success? Does the successful online learner need to possess specific skills or strategies to be successful? The purpose of this paper is to provide an overview and some preliminary results of a longitudinal study currently being conducted at a southwestern university that is examining its online Masters of Education in Educational Technology (M.Ed. in Ed.
A comparison of albumin-bolus therapy versus normal saline-bolus therapy for hypotension in neonates

Objective:We compared responses to bolus infusion of 5% albumin (ALB) or normal saline (NS) for hypotension in neonates.Study Design:Hypotensive infants were given 10 ml kg−1 of NS or ALB. A second bolus was given for persistent hypotension. Dopamine therapy was started for hypotension after the second bolus. The primary response was increase in arterial blood pressure toward normal range 1 h postinfusion. Secondary measures included duration of normotension, meeting criteria for second bolus, meeting criteria for vasopressor support and cost comparison.Result:Those receiving ALB (N=49 ALB and 52 NS) were more likely to achieve a normotensive state (ALB=57.1%, NS=32.1% P=0.01) 1 h following the initial bolus therapy. Subsequently, the NS group was also more likely to qualify for vasopressor infusion (ALB=24.5%, NS=44.2% P=0.02). Overall cost for either therapy was equivalent.Conclusion:In hypotensive neonates, ALB results in a greater likelihood of achieving normotension and decreased subsequent use of vasopressors when compared to NS.
Minutiae-based Fingerprint Extraction and Recognition

In our electronically inter-connected society, reliable and user-friendly recognition and verification system is essential in many sectors of our life. The person’s physiological or behavioral characteristics, known as biometrics, are important and vital methods that can be used for identification and verification. Fingerprint recognition is one of the most popular biometric techniques used in automatic personal identification and verification. Many researchers have addressed the fingerprint classification problem and many approaches to automatic fingerprint classification have been presented in the literature; nevertheless, the research on this topic is still very active. Although significant progress has been made in designing automatic fingerprint identification systems over the past two decades, a number of design factors (lack of reliable minutia extraction algorithms, difficulty in quantitatively defining a reliable match between fingerprint images, poor image acquisition, low contrast images, the difficulty of reading the fingerprint for manual workers, etc.) create bottlenecks in achieving the desired performance. Nowadays, investigating the influence of the fingerprint quality on recognition performances also gains more and more attention. A fingerprint is the pattern of ridges and valleys on the surface of a fingertip. Each individual has unique fingerprints. Most fingerprint matching systems are based on four types of fingerprint representation schemes (Fig. 1): grayscale image (Bazen et al., 2000), phase image (Thebaud, 1999), skeleton image (Feng, 2006; Hara & Toyama, 2007), and minutiae (Ratha et al., 2000; Bazen & Gerez, 2003). Due to its distinctiveness, compactness, and compatibility with features used by human fingerprint experts, minutiae-based representation has become the most widely adopted fingerprint representation scheme. The uniqueness of a fingerprint is exclusively determined by the local ridge characteristics and their relationships. The ridges and valleys in a fingerprint alternate, flowing in a local constant direction. The two most prominent local ridge characteristics are: 1) ridge ending and, 2) ridge bifurcation. A ridge ending is defined as the point where a ridge ends abruptly. A ridge bifurcation is defined as the point where a ridge forks or diverges into branch ridges. Collectively, these features are called minutiae. Detailed description of fingerprint minutiae will be given in the next section. The widespread deployment of fingerprint recognition systems in various applications has caused concerns that compromised fingerprint templates may be used to make fake fingers, which could then be used to deceive all fingerprint systems the same person is enrolled in.
Estimated glomerular filtration rate as an independent predictor of atherosclerotic vascular disease in older women

BACKGROUND
Estimated glomerular filtration rate (eGFR) levels have been shown to predict atherosclerotic vascular disease hospitalization and mortality. We sought to investigate the role of renal function in the prediction of 10-year atherosclerotic vascular hospitalization and deaths in an unselected population of elderly women and compared these predictions to Framingham equations.


METHODS
Complete 10-year verified mortality and hospitalization discharge records for atherosclerotic vascular disease were collected for a prospective study of 1,239 unselected female subject's ≥ 70 from the Calcium Intake Fracture Outcome Study (CAIFOS) with 10 years of follow-up. eGFR was compared to the current Framingham risk scores.


RESULTS
The eGFR at baseline using the Modification of Diet in Renal Disease Study (MDRD) equation was 65.2 ± 14.5 mL/min/1.73 m(2) and 66.3 ± 13.5 mL/min/1.73 m(2) using the Chronic Kidney Disease EPIdemiology (CKD-EPI) equation. Over 10 years 30% of participants sustained an ASVD hospitalization or death. For every standard deviation (SD) reduction in eGFR using MDRD the odds ratio (OR) for ASVD hospitalization and deaths increased by 1.34 (1.18-1.53), P < 0.00 and 1.31 (1.14-1.50), P < 0.001 in a model adjusted for Framingham 10-year general cardiovascular risk. Addition of eGFR by the MDRD equation to Framingham risk factors improved the net reclassification index by 5.9%, P = 0.018 and the integrated discrimination improvement by 0.010 ± 0.003, P < 0.001 Similar results were seen using the CKD-EPI equation.


CONCLUSION
Estimated glomerular filtration rate predicts ASVD outcomes independently of Framingham risk score predictions in elderly women and improves clinical prediction particularly of early ASVD.
Arterial stiffness is associated with orthostatic hypotension in elderly subjects with history of falls.

OBJECTIVES
To test the hypothesis that impaired hemodynamic orthostatic changes commonly observed in the elderly may be related to age-related increase in arterial wall stiffness.


DESIGN
Convenience sample of consecutive patients admitted for falls.


SETTING
Acute- and intermediate-care geriatric ward of a French hospital.


PARTICIPANTS
Fifty-seven elderly patients (46 women) consecutively admitted to a geriatric ward with a history of recent falls.


MEASUREMENTS
Orthostatic hypotension (OH) was assessed using blood pressure measurements in the supine position and 1, 2, and 3 minutes after standing. Arterial wall stiffness was assessed using upper-limb and aortic pulse-wave velocities, measured with an external pressure transducer connected to a computer.


RESULTS
OH was present in 18 patients with a mean age+/-standard deviation of 85.4+/-7.6 (5 men, 13 women) and absent in 39 patients aged 83.7+/-6.2 (6 men, 33 women). Upper-limb pulse-wave velocity was significantly higher, by 16%, in patients with OH than those without (9.91 vs 8.53 m/s; P<.02). Significant correlations were found between upper-limb pulse-wave velocity and systolic blood pressure changes after 1 minute of standing (r=0.263, P<.05) and maximal diastolic blood pressure change after standing (r=0.351, P<.01).


CONCLUSION
Upper-limb arterial wall stiffness was significantly greater in elderly patients with OH than in patients without OH and was significantly related to blood pressure changes after standing. These results highlight the possible role of age-related changes in the arterial tree in the hemodynamic response to orthostatic challenges.
Self-adjusting trees in practice for large text collections

Splay and randomised search trees are self-balancing binary tree structures with little or no space overhead compared to a standard binary search tree. Both trees are intended for use in applications where node accesses are skewed, for example in gathering the distinct words in a large text collection for index construction. We investigate the efficiency of these trees for such vocabulary accumulation. Surprisingly, unmodified splaying and randomised search trees are on average around 25% slower than using a standard binary tree. We investigate heuristics to limit splay tree reorganisation costs and show their effectiveness in practice. In particular, a periodic rotation scheme improves the speed of splaying by 27%, while other proposed heuristics are less effective. We also report the performance of efficient bit-wise hashing and red-black trees for comparison.
Examining the Role of Social Media in Disaster Management from an Attribution Theory Perspective

This paper is related to the use of social media for disaster management by humanitarian organizations. The past decade has seen a significant increase in the use of social media to manage humanitarian disasters. It seems, however, that it has still not been used to its full potential. In this paper, we examine the use of social media in disaster management through the lens of Attribution Theory. Attribution Theory posits that people look for the causes of events, especially unexpected and negative events. The two major characteristics of disasters are that they are unexpected and have negative outcomes/impacts. Thus, Attribution Theory may be a good fit for explaining social media adoption patterns by emergency managers. We propose a model, based on Attribution Theory, which is designed to understand the use of social media during the mitigation and preparedness phases of disaster management. We also discuss the theoretical contributions and some practical implications. This study is still in its nascent stage and is research in progress.
Acupuncture for acute non-specific low back pain: a randomised, controlled, double-blind, placebo trial.

OBJECTIVE
To assess the efficacy of Yamamoto's acupuncture method on pain, drug intake, functional capacity and quality of life for the treatment of acute non-specific low back pain (ANLBP).


METHODS
A prospective, randomised, parallel-group, double-blind, placebo-controlled trial was performed in 80 men and women with ANLBP who were randomly assigned to five acupuncture sessions (intervention group (IG), n=40) and to five non-penetrating acupuncture sessions (sham group (SG), n=40). Patients were evaluated at baseline and at 3, 7, 14, 21 and 28 days. The measurements used were: visual analogue scale (VAS) for cumulative pain (before intervention, VAS1) and immediate pain (after intervention, VAS2); function (Roland-Morris Disability Questionnaire (RM)); quality of life (SF-36); improvement rating; and number of anti-inflammatory tablets taken. The primary endpoint was a decrease of at least 2 cm in VAS1.


RESULTS
Pain VAS improved significantly in the IG from day 14 onwards compared with the SG, but the difference did not reach the prespecified clinically relevant value of 2 cm. The IG was significantly superior to the SG in the following outcomes: cumulative pain, function, pain (SF-36) and vitality (SF-36) at days 14, 21 and 28 (p<0.05); limitation in physical aspects (SF-36) at all times (p=0.007 and p=0.02); and functional capacity (SF-36) at days 21 and 28 (p<0.05). The IG also took significantly fewer anti-inflammatory tablets than the SG (p=0.004) at all evaluation times and the improvement rating was better than the SG (p<0.001).


CONCLUSIONS
Yamamoto's new scalp acupuncture was more effective than sham treatment with regard to decrease in pain and anti-inflammatory intake as well as improving functional status and quality of life for patients with ANLBP.


CLINICALTRIALSGOV
NCT 01124955.
A survey of envelope processes and their applications in quality of service provisioning

Provisioning of quality of service (QoS) guarantees has become an increasingly important and challenging topic in the design of the current and the next-generation Internet. The class of envelope processes (EPs) is one of the key elements for many QoS provisioning mechanisms. An arrival EP A(τ) (or a service curve) bounds the cumulative traffic of a flow (or the cumulative service a flow receives) over any interval of length τ. Such bounds can be deterministic or probabilistic, and can be used for provisioning of deterministic or statistical service guarantees. In this article we provide a survey on arrival EPs and service curves. We provide an overview of various EPs proposed in the literature during the last 15 years and discuss their applications and performance in QoS provisioning. We aim to provide a big picture of the existing work. There is considerable research effort addressing QoS issues in resource-constrained access networks (such as wireless networks) and in the new multiprotocol label switching (MPLS) and peer-to-peer (P2P) networking paradigms. We aim to provide a comprehensive survey of existing work, which can yield useful insights, and help the development of new QoS metrics, mechanisms, and architectures for emerging network environments.
Causal Inference and Causal Explanation with Background Knowledge

This paper presents correct algorithms for answering the following two questions; (i) Does there exist a causal explanation con­ sistent with a set of background knowledge which explains all of the observed indepen­ dence facts in a sample? (ii) Given that there is such a causal explanation what are the causal relationships common to every such
Hydrophobic Silica Aerogels – Solvent Removal From Water

Hydrophobic silica monolith aerogels were prepared by incorporating methyltrimethoxysilane (MTMS) in standard sol-gel synthesis following by drying of gels in supercritical CO2 at 40°C. The hydrophobicity of the aerogels was tested by measuring the contact angle (θ). Adsorption capacity measurements show that hydrophobic silica aerogels are excellent adsorbents for different toxic organic compounds from water. In comparison to granulated active carbon (GAC) they exhibit capacities which are more than 70 times higher for all tested compounds.
Interoperability of clinical decision-support systems and electronic health records using archetypes: A case study in clinical trial eligibility

Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support patient recruitment in the framework of a clinical trial for colorectal cancer screening. The utilisation of archetypes not only has proved satisfactory to achieve interoperability between CDSSs and EHRs but also offers various advantages, in particular from a data model perspective. First, the VHR/data models we work with are of a high level of abstraction and can incorporate semantic descriptions. Second, archetypes can potentially deal with different EHR architectures, due to their deliberate independence of the reference model. Third, the archetype instances we obtain are valid instances of the underlying reference model, which would enable e.g. feeding back the EHR with data derived by abstraction mechanisms. Lastly, the medical and technical validity of archetype models would be assured, since in principle clinicians should be the main actors in their development.
Domain Specific Web Crawler : A Survey

The ―Domain Specific web crawler‖ is a system or a program which we will design to search information from web. A crawler is an automation tool that traverses the web page for the purpose of extracting information. In domain specific Web crawler, the crawler crawls the pages, which are relevant to our domain. To find the domain related web page we need to visit a Web page and calculate the relevance value. Based on relevance value the selection of page is decided.For a crawler it is not an easy task to download the domain specific Web pages. It focus will be to identify Web pages for a particular domain in web. The usage of internet is immense on a large scale for the past many years. In this survey we are going to discuss about types of crawler ,crawling algorithm , relevancy check and machine learning. KEYWORD: Crawler, Ant, Spider, bot, agent, Automation, Search Engine, Focused, web mining, text analysis
Exploring cross-sectional associations between common childhood illness, housing and social conditions in remote Australian Aboriginal communities

BACKGROUND
There is limited epidemiological research that provides insight into the complex web of causative and moderating factors that links housing conditions to a variety of poor health outcomes. This study explores the relationship between housing conditions (with a primary focus on the functional state of infrastructure) and common childhood illness in remote Australian Aboriginal communities for the purpose of informing development of housing interventions to improve child health.


METHODS
Hierarchical multi-level analysis of association between carer report of common childhood illnesses and functional and hygienic state of housing infrastructure, socio-economic, psychosocial and health related behaviours using baseline survey data from a housing intervention study.


RESULTS
Multivariate analysis showed a strong independent association between report of respiratory infection and overall functional condition of the house (Odds Ratio (OR) 3.00; 95%CI 1.36-6.63), but no significant association between report of other illnesses and the overall functional condition or the functional condition of infrastructure required for specific healthy living practices. Associations between report of child illness and secondary explanatory variables which showed an OR of 2 or more included: for skin infection--evidence of poor temperature control in the house (OR 3.25; 95%CI 1.06-9.94), evidence of pests and vermin in the house (OR 2.88; 95%CI 1.25-6.60); for respiratory infection--breastfeeding in infancy (OR 0.27; 95%CI 0.14-0.49); for diarrhoea/vomiting--hygienic state of food preparation and storage areas (OR 2.10; 95%CI 1.10-4.00); for ear infection--child care attendance (OR 2.25; 95%CI 1.26-3.99).


CONCLUSION
These findings add to other evidence that building programs need to be supported by a range of other social and behavioural interventions for potential health gains to be more fully realised.
Fuzzy clustering using kernel method

Classical fuzzy C -means (FCM) clustering is performed in the input space, given the desired number of clusters. Although it has proven effective for spherical data, it fails when the data structure of input patterns is non-spherical and complex. In this paper, we present a novel kernel-based fuzzy C-means clustering algorithm (KFCM). Its basic idea is to transform implicitly the input data into a higher dimensional feature space via a nonlinear map, which increases greatly possibility of linear separability of the patterns in the feature space, then perform FCM in the feature space. Another good attribute of KFCM is that it can automatically estimate the number of clusters in the dataset. The experimental results show that the proposed method has better performance in the Ring dataset.
Increase of feather quality during moult: a possible implication of feather deformities in the evolution of partial moult in the great tit Parus major

P. L. Pap (correspondence), Department of Taxonomy and Ecology, Babeş-Bolyai University, RO-400006 Cluj Napoca, Clinicilor Street 5-7, Romania. E-mail: peterpl@hasdeu.ubbcluj.ro. Z. Barta and J. Tökölyi, Behavioural Ecology Research Group, Department of Evolutionary Zoology, University of Debrecen, H-4010 Debrecen, Hungary. C. I. Vágási, Department of Taxonomy and Ecology, Babeş-Bolyai University, RO-400006 Cluj Napoca, Clinicilor Street 5-7, Romania.