LLukas22/scidocs huggingface dataset:
Is there a lack of information on HPV vaccination given by health professionals to young women?

OBJECTIVE
The aim of this survey is to compare the main sources of information about vaccination against Human papillomavirus (HPV) of young women aged over-18 and under-18 years.


METHODS
A multicenter study was carried out in Italy through the administration of a questionnaire. Univariate analyses were conducted to evaluate possible differences between age groups and different locations (chi-square test and Fisher test where possible).


RESULTS
The sample consisted of 987 young women. The main sources of information about HPV vaccination are represented by magazines/books (23.1%) and TV (20.5%) for the over-18s, while for the under-18s the sources are general practitioners (22.6%) and pediatricians (15.4%). The over-18s with health professionals as parents consult mostly gynecologists (27.7%) and general practitioners (20.5%).


DISCUSSION
This study highlights lack of information on HPV vaccination given by health professionals to young women and underlines the need to improve education about cervical cancer, prevention and HPV vaccination.
AutoFocus: A Tool for Distributed Systems Specification

We describe the concept of AutoFocus, a tool for the speci-cation of distributed systems. AutoFocus is based on the formal development method Focus and uses graphical description formalisms embedded into its semantical framework, thus ooering well-accepted notations while retaining the ability for exact consistency checks of a system under development. The tool uses a client/server architecture, with a central repository and distributed client applications in a computer network. The paper at hand focuses on the architectural and implementation-related issues of AutoFocus.
Learning with kernels

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Growth of conductive and insulative highly-orientated aluminum nitride thin films using laser molecular beam epitaxy

Abstract Conductive and insulative highly-orientated aluminum nitride thin films were grown on Si (111) and sapphire (0001) substrates using laser molecular beam epitaxy by only changing the nitrogen pressure. The microstructure of AlN films was characterized by X-ray diffraction and scanning electron microscopy, while the electrical and optical properties were measured by current–voltage, capacitance–voltage and ultraviolet–visible-near infrared spectroscopy. The results show that the AlN films deposited under 1 Pa nitrogen pressure are insulative with a resistivity of 10 11 –10 12  Ω·cm, while they become conductive with a resistivity of 9.3 × 10 − 1  Ω·cm grown under 2 × 10 − 2  Pa because of the presence of aluminum particles. Electric properties of the AlN films are strongly influenced by aluminum particles. The presence of metallic aluminum also decreases the optical transmittance of the AlN films from 85% to 20%.
Coordinated Max-Min SIR Optimization in Multicell Downlink - Duality and Algorithm

Typical formulations of max-min weighted SIR problems involve either a total power constraint or individual power constraints. These formulations are unable to handle the complexities in multicell networks where each base station can be subject to its own sum power constraint. This paper considers the max-min weighted SIR problem subject to multiple weighted-sum power constraints, where the weights can represent relative power costs of serving different users. First, we derive the uplink-downlink duality principle by applying Lagrange duality to the single-constraint problem. Next, we apply nonlinear Perron-Frobenius theory to derive a closed-form solution for the multiple-constraint problem. Then, by exploiting the structure of the closed-form solution, we relate the multiple-constraint problem with its single-constraint subproblems and establish the dual uplink problem. Finally, we further apply nonlinear Perron-Frobenius theory to derive an algorithm which converges geometrically fast to the optimal solution.
Where to Look: Focus Regions for Visual Question Answering

We present a method that learns to answer visual questions by selecting image regions relevant to the text-based query. Our method maps textual queries and visual features from various regions into a shared space where they are compared for relevance with an inner product. Our method exhibits significant improvements in answering questions such as "what color," where it is necessary to evaluate a specific location, and "what room," where it selectively identifies informative image regions. Our model is tested on the recently released VQA [1] dataset, which features free-form human-annotated questions and answers.
Deadline-constrained workflow scheduling algorithms for Infrastructure as a Service Clouds

The advent of Cloud computing as a newmodel of service provisioning in distributed systems encourages researchers to investigate its benefits and drawbacks on executing scientific applications such as workflows. One of the most challenging problems in Clouds is workflow scheduling, i.e., the problem of satisfying the QoS requirements of the user as well as minimizing the cost of workflow execution. We have previously designed and analyzed a two-phase scheduling algorithm for utility Grids, called Partial Critical Paths (PCP), which aims to minimize the cost of workflow execution while meeting a userdefined deadline. However, we believe Clouds are different from utility Grids in three ways: on-demand resource provisioning, homogeneous networks, and the pay-as-you-go pricing model. In this paper, we adapt the PCP algorithm for the Cloud environment and propose two workflow scheduling algorithms: a one-phase algorithmwhich is called IaaS Cloud Partial Critical Paths (IC-PCP), and a two-phase algorithm which is called IaaS Cloud Partial Critical Paths with Deadline Distribution (IC-PCPD2). Both algorithms have a polynomial time complexity which make them suitable options for scheduling large workflows. The simulation results show that both algorithms have a promising performance, with IC-PCP performing better than IC-PCPD2 in most cases. © 2012 Elsevier B.V. All rights reserved.
Microstructure and mechanical properties of Hastelloy X produced by HP-SLM (high power selective laser melting)

Abstract In order to increase the production rate during selective laser melting (SLM), a high power laser with a large beam diameter is used to build fully dense Hastelloy X parts. Compared to SLM with a low power and small diameter beam, the productivity was increased from 6 mm 3 /s to 16 mm 3 /s, i.e. 2.6 times faster. Besides the productivity benefit, the influence of the use of a high power laser on the rapid solidification microstructure and concomitant material properties is highlighted. The current paper compares the microstructure and tensile properties of Hastelloy X built with low and high power lasers. The use of a high power laser results in wider and shallower melt pools inducing an enhanced morphological and crystallographic texture along the building direction (BD). In addition, the increased heat input results in coarser sub-grains or high density dislocation walls for samples processed with a high power laser. Additionally, the influence of hot isostatic pressing (HIP) as a post-processing technique was evaluated. After HIP, the tensile fracture strain increased as compared to the strain in the as-built state and helped in obtaining competitive mechanical properties as compared to conventionally processed Hastelloy X parts.
Vaccination of patients with advanced ovarian carcinoma with the anti-idiotype ACA125: immunological response and survival (phase Ib/II).

PURPOSE
A Phase I/IIb multicenter study was conducted to evaluate the safety and immunogenicity of the anti-idiotypic antibody vaccine ACA125 that functionally imitates the tumor antigen CA125 in 119 patients with advanced ovarian carcinoma. A preliminary report on the initial 42 patients demonstrated safety and immunogenicity.


EXPERIMENTAL DESIGN
Using the complete intention-to-treat population (n = 119) who received a mean of 9.7 ACA125 applications, survival was analyzed with respect to immunological responses.


RESULTS
In 81 patients (68.1%), a specific anti-anti-idiotypic antibody (Ab3) response could be induced. Additionally, the development of CA125-specific antibodies (Ab1') and antibody-dependent cell-mediated cytotoxicity of CA125-positive tumor cells was observed in 50.4% and 26.9% of patients, respectively. The median survival of all patients was 19.4 months (range, 0.5-56.1 months). Ab3-positive patients showed a significantly longer survival (median, 23.4 months; P < 0.0001) as compared with Ab3-negative patients (median, 4.9 months). A positive Ab3 response remained associated with longer survival when controlling for other prognostic factors including FIGO (International Federation of Gynecologists and Obstetricians) stage, response to and type of first-line chemotherapy, number of previous treatments, or concomitant antitumor therapy. With regard to safety, repeated vaccination was well tolerated. No serious adverse events related to the application of ACA125 occurred.


CONCLUSIONS
Although the uncontrolled design of this study prevents definitive conclusions with respect to subgroups, the data support a relationship between Ab3 response and survival time. Thus, the need for further randomized, controlled clinical trials to establish efficacy of the vaccine ACA125 seems to be indicated.
Laparoscopic cholecystectomy, Calot's triangle, and variations in cystic arterial supply

Background: The extrahepatic biliary tree with the exact anatomic features of the arterial supply observed by laparoscopic means has not been described heretofore. Iatrogenic injuries of the extrahepatic biliary tree and neighboring blood vessels are not rare. Accidents involving vessels or the common bile duct during laparoscopic cholecystectomy, with or without choledocotomy, can be avoided by careful dissection of Calot's triangle and the hepatoduodenal ligament. Methods: We performed 244 laparoscopic cholecystectomies over a 2-year period between January 1, 1995 and January 1, 1997. Results: In 187 of 244 consecutive cases (76.6%), we found a typical arterial supply anteromedial to the cystic duct, near the sentinel cystic lymph node. In the other cases, there was an atypical arterial supply, and 27 of these cases (11.1%) had no cystic artery in Calot's triangle. A typical blood supply and accessory arteries were observed in 18 cases (7.4%). Conclusion: Young surgeons who are not yet familiar with the handling of an anatomically abnormal cystic blood supply need to be more aware of the precise anatomy of the extrahepatic biliary tree.
Reliability and validity of the Asthma Trigger Inventory applied to a pediatric population.

OBJECTIVE
To test the reliability and validity of the Asthma Trigger Inventory (ATI) applied to a pediatric population.


METHOD
Children with asthma (N = 272, 56% male, age 7-17) and their primary caregivers answered together an asthma trigger inventory, ATI (Ritz, Steptoe, Bobb, Harris, & Edwards, 2006) developed for adults. Cronbach's alpha, principal component analysis (PCA), hierarchical regression, and correlations of the ATI subscales with skin prick tests, psychological questionnaires, and disease severity were used to assess the psychometric properties of the ATI.


RESULTS
The ATI subscales demonstrated excellent reliability regardless of gender, race, socioeconomic status (SES), or age. PCA confirmed and replicated the theoretical structure of the ATI. Hierarchical multiple regressions illuminated the association of ATI subscales with demographics and asthma history. Evidence in support of construct validity was found in associations between ratings of triggering and disease severity and asthma-related quality of life (PAQLQ). Criterion validity for allergy triggering was partially supported by correlations between ATI animal allergens subscale and the cat dander skin prick test, and construct validity for emotional triggering by associations between the emotional trigger subscale score and the anxiety (STAIC) and depression (CDI, CDI-P, CDRS-R, and CBCL-I) scores.


CONCLUSION
The ATI holds promise as a reliable, valid, and useful clinical and research tool to assess the type and degree of asthma triggering in a pediatric population (age 7-17) of varied gender, race, and SES.
Deep Learning-based Feature Selection for Intrusion Detection System in Transport Layer 1 )

Numerous machine learning algorithms applied on Intrusion Detection System (IDS) to detect enormous attacks. However, it is difficult for machine to learn attack properties globally since there are huge and complex input features. Feature selection can overcome this problem by selecting the most important features only to reduce the dimensionality of input features. We leverage Artificial Neural Network (ANN) for the feature selection. In addition, in order to be suitable for resource-constrained devices, we can divide the IDS into smaller parts based on TCP/IP layer since different layer has specific attack types. We show the IDS for transport layer only as a prove of concept. We apply Stacked Auto Encoder (SAE) which belongs to deep learning algorithm as a classifier for KDD99 Dataset. Our experiment shows that the reduced input features are sufficient for classification task. 한국정보보호학회 하계학술대회 논문집 Vol. 26, No. 1
Medication adherence among hypertensive patients of primary health clinics in Malaysia

PURPOSE
Poor adherence to prescribed medications is a major cause for treatment failure, particularly in chronic diseases such as hypertension. This study was conducted to assess adherence to medications in patients undergoing hypertensive treatment in the Primary Health Clinics of the Ministry of Health in Malaysia. Factors affecting adherence to medications were studied, and the effect of nonadherence to blood pressure control was assessed.


PATIENTS AND METHODS
This was a cross-sectional study to assess adherence to medications by adult patients undergoing hypertensive treatment in primary care. Adherence was measured using a validated survey form for medication adherence consisting of seven questions. A retrospective medication record review was conducted to collect and confirm data on patients' demographics, diagnosis, treatments, and outcomes.


RESULTS
Good adherence was observed in 53.4% of the 653 patients sampled. Female patients were found to be more likely to adhere to their medication regime, compared to their male counterparts (odds ratio 1.46 [95% confidence intervals [CI]: 1.05-2.04; P < 0.05]). Patients in the ethnic Chinese were twice as likely (95% CI: 1.14-3.6; P < 0.05) to adhere, compared to those in the Indian ethnic group. An increase in the score for medicine knowledge was also found to increase the odds of adherence. On the other hand, increasing the number of drugs the patient was taking and the daily dose frequencies of the medications prescribed were found to negatively affect adherence. Blood pressure control was also found to be worse in noncompliers.


CONCLUSION
The medication adherence rate was found to be low among primary care hypertensive patients. A poor adherence rate was found to negatively affect blood pressure control. Developing multidisciplinary intervention programs to address the factors identified is necessary to improve adherence and, in turn, to improve blood pressure control.
Brain MR image normalization in texture analysis of multiple sclerosis

A problem that occurs in texture analysis and quantitative analysis of magnetic resonance imaging (MRI), is that the extracted results are not comparable between consecutive or repeated scans or, within the same scan, between different anatomic regions. The reason is that there are intra-scan and inter-scan image intensity variations due to the MRI instrumentation. Therefore, image intensity normalization methods should be applied to magnetic resonance (MR) images prior to further image analysis. The objective of this work was to investigate six different MRI intensity normalization methods and propose the most appropriate for the pre-processing of brain T2-weighted MR images acquired from 22 symptomatic untreated multiple sclerosis (MS) subjects and 10 healthy volunteers. Following image normalization, texture analysis was carried out in original and normalized images for normal appearing white matter (NAMW) and MS lesions, detected in transverse T2-weighted MR images. The best normalization method (Histogram Normalization (HN)) demonstrated a smaller Kullback Leibler divergence (0.05, 0.06) suggesting appropriateness for pre-processing MR images used in texture analysis of MS brain lesions. This is a prerequisite step in the assessment of texture features as surrogate markers of disease progression.
Two Types of Compact UHF Antennas for Partial Discharge Measurement

Partial discharge (PD) online monitoring of transformers by ultra-high-frequency (UHF) approaches has been paid increasingly attention recently. High-qualified UHF antennas are focused on as one key technique. This paper presents two types of compact UHF antennas in small sizes, a Hilbert fractal antenna and a small loop antenna. PD experiments of three typically artificial insulation defects are executed and the both antennas are used for PD measurement. The spectrums of power via frequency of detected PD signals are analyzed and compared. The experimental results show that the Hilbert fractal antenna and small loop antenna are qualified for PD online UHF monitoring.
Acne keloidalis is a form of primary scarring alopecia.

OBJECTIVE
To better define the pathogenesis of acne keloidalis (AK).


DESIGN
Prospective, blinded study of histologic material collected from 10 patients with clinically typical AK.


SETTING
Outpatient dermatology clinic of a military tertiary care medical center.


PATIENTS
Ten male volunteers 18 years or older with early AK lesions (1- to 4-mm firm papules on the lower occipital/nuchal region).


DATA SOURCE
Biopsy specimens from small, early lesions and from clinically uninvolved skin, studied histologically with transverse sectioning.


INTERVENTION
Three separate 4-mm punch biopsy specimens of the scalp (lesional, perilesional, and "normal" scalp) were obtained from each volunteer. The specimens were processed using transverse sectioning.


MAIN OUTCOME MEASURES
The primary variables for data analysis were the presence or absence of the following histologic features: premature loss of the inner root sheath; eccentric placement of shaft, with thinning of the outer root sheath; lamellar fibroplasia surrounding the follicle; loss of sebaceous glands; evidence of follicular destruction or scarring; inflammation; and intrafollicular or perifollicular microorganisms. The number and type of hairs were also recorded.


RESULTS
The most common findings in the 19 histologically abnormal specimens were perifollicular, chronic (lymphocytic and plasmacytic) inflammation, most intense at the level of the isthmus and lower infundibulum; lamellar fibroplasia, most marked at the level of the isthmus; complete disappearance of sebaceous glands, associated with inflamed or destroyed follicles; thinning of the follicular epithelium, most marked at the level of the isthmus; and total epithelial destruction (superficial and deep), with residual "naked" hair fragments. Even some "normal" specimens contained true follicular scars, demonstrating that normal-appearing scalp skin had previously been affected by the disease.


CONCLUSIONS
Acne keloidalis is a primary form of scarring alopecia, and many of the histologic findings closely resemble those found in certain other forms of cicatricial alopecia. Extensive subclinical disease may be present in patients with AK and can account for some of the permanent hair loss. Overgrowth of microorganisms does not appear to play an important role in the pathogenesis of the disease. There is no etiologic relationship between AK and pseudofolliculitis barbae. Therapies found to be useful in other forms of inflammatory scarring alopecia are useful in the treatment of early AK.
A complete fuzzy decision tree technique

In this paper, a new method of fuzzy decision trees called soft decision trees (SDT) is presented. This method combines tree growing and pruning, to determine the structure of the soft decision tree, with re4tting and back4tting, to improve its generalization capabilities. The method is explained and motivated and its behavior is 4rst analyzed empirically on 3 large databases in terms of classi4cation error rate, model complexity and CPU time. A comparative study on 11 standard UCI Repository databases then shows that the soft decision trees produced by this method are signi4cantly more accurate than standard decision trees. Moreover, a global model variance study shows a much lower variance for soft decision trees than for standard trees as a direct cause of the improved accuracy. c © 2003 Elsevier B.V. All rights reserved.
Probabilistic Label Relation Graphs with Ising Models

We consider classification problems in which the label space has structure. A common example is hierarchical label spaces, corresponding to the case where one label subsumes another (e.g., animal subsumes dog). But labels can also be mutually exclusive (e.g., dog vs cat) or unrelated (e.g., furry, carnivore). To jointly model hierarchy and exclusion relations, the notion of a HEX (hierarchy and exclusion) graph was introduced in [8]. This combined a conditional random field (CRF) with a deep neural network (DNN), resulting in state of the art results when applied to visual object classification problems where the training labels were drawn from different levels of the ImageNet hierarchy (e.g., an image might be labeled with the basic level category "dog", rather than the more specific label "husky"). In this paper, we extend the HEX model to allow for soft or probabilistic relations between labels, which is useful when there is uncertainty about the relationship between two labels (e.g., an antelope is "sort of" furry, but not to the same degree as a grizzly bear). We call our new model pHEX, for probabilistic HEX. We show that the pHEX graph can be converted to an Ising model, which allows us to use existing off-the-shelf inference methods (in contrast to the HEX method, which needed specialized inference algorithms). Experimental results show significant improvements in a number of large-scale visual object classification tasks, outperforming the previous HEX model.