Miracle-dz/UniFAR-FTUs huggingface dataset:
Complementary/alternative therapies in patients with breast cancer

Breast cancer is the most common cancer type in women. Surgery, radiotherapy, chemotherapy, hormonal therapy are the treatment options that are used one or more for the treatment of breast cancer, however it is known that some of the cancer patients use complementary/alternative medicine (CAM) other than their treatments. In this study we aimed to investigate the frequency of CAM use and the type of CAM used in patients with breast cancer.
A Survey on Fusion-Based Indoor Positioning

Demands for indoor positioning based services (IPS) in commercial and military fields have spurred many positioning systems and techniques. Complex electromagnetic environments (CEEs) may, however, degenerate the accuracy and robustness of some existing single systems and techniques. To overcome this drawback, fusion-based positioning of multiple systems and/or techniques have been proposed to revamp the positioning performance in CEEs. In this paper, we survey the fusion-based indoor positioning techniques and systems from seminal works to elicit the state of the art within our proposed unified fusion-based positioning framework, which consists of three fusion characteristics: source, algorithm, and weight spaces. Different from other surveys, this survey summarizes and analyzes the existing fusion-based positioning systems and techniques from three characteristics. Meanwhile, discussions in terms of lessons, challenges, and countermeasures are also presented. This survey is invaluable for researchers to acquire a clear concept of indoor fusion-based positioning systems and techniques and also to gain insights from this survey to further develop other advanced fusion-based positioning systems and techniques in the future.
The Effect of A Flipped Classroom on Students’ Achievements, Academic Engagement and Satisfaction Levels

In this study, a flipped classroom was compared with blended learning and face-to-face learning environments and the aim was to identify the effect of these learning environments on students’ achievements, academic engagement and satisfaction levels. Based on this aim, one control and two experimental groups were formed. The students in Experiment-I learned the theoretical aspect of the course through the materials in the online learning environment which were prepared prior to the class study time in context with the “flipped classroom”. The students in Experiment-II learned the theoretical aspect of the course in the classroom in accordance with the blended learning model and fulfilled active learning activities out of class study time. The students in the control group learned the theoretical aspect of the course in the classroom according to the current curriculum and conducted active learning activities at their homes. It was found that the scores for the students in the experimental groups with regard to academic achievement and engagement were higher than the scores for those in the control group and the differences between the groups were statistically significant. It was revealed that the students were also generally satisfied with the flipped classroom.
Lecturers’ perceptions and experiences of Blackboard Collaborate as a distance learning and teaching tool via Open Universities Australia (OUA)

ABSTRACT Australian tertiary institutions offer online units to provide flexibility for students unable to attend classes on campus due to the constraints of distance and scheduling. While lecture materials and discussions can be accessed asynchronously, a synchronous element allows lecturers and students to interact in real time. Blackboard Collaborate, featuring videoconferencing, text, voice chat and interactive whiteboard, is a synchronous tool which can encourage a collaborative learning environment. This study explored seven lecturers’ perceptions of, and experiences with Blackboard Collaborate in an Australian university setting. Quantitative data was collected and statistically analysed from responses to closed-ended items in an online survey. Qualitative data was gathered and thematically analysed from open-ended item responses and semi-structured interviews. Lecturers found that the use of Blackboard Collaborate motivated students, helped them to share knowledge, facilitated timely responses to student queries, enhanced interaction via multimodality and built virtual learning and teaching communities. Negative aspects were also noted, however, and included lecturers having to cope with technical glitches, a lack of face-to-face co-presence, delayed turn-taking in live sessions and difficulties with engagement due to suitable session scheduling.
Ethics-Based Computer Science in Bilingual and Multicultural Schools

For decades, schools have adapted to a technologically-dependent world—developing courses, faculty positions and curricula to begin explicitly teaching with and about technology. Recognizing the need for deepening education in this area, the Lycée Français de New York, a bilingual and multicultural school, developed the digital learning department to lead the school’s thinking and practice around technology and computer science education. Over time, the department shifted its focus from first only the use of computer applications, to an emphasis on computer programming, to a more recent era which includes technology ethics as an equally important area of study. In serving a bilingual school, the Lycée’s digital learning team adapted teaching methods for a bilingual student body. The multiculturalism of the school presents the opportunity for fertile ethics discussions, since cultural values often impact values regarding technology use.
Predictors of survival after surgery among patients with large cell neuroendocrine carcinoma of the lung

Background. Large cell neuroendocrine carcinoma (LCNEC) represents a rare entity in non-small cell lung cancer, with only partially understood biology and poor survival. A diagnosis is difficult to obtain on the basis of small biopsy specimens, but surgical procedures may be indicated in only a small fraction of patients. The aim of this study was to assess the clinical and immunohistochemical features of patients with LCNEC to identify predictors of outcome and long-term survival. Methods. The clinical and pathologic data of 57 surgical patients with LCNEC between March 2003 and December 2012 were retrospectively reviewed. The tumor specimens wereexaminedforexpressionofneuronalspecificenolase, synaptophysin, CD 56, chromogranin-A, and the somatostatin receptor by immunohistochemistry. Statistical analysiswasperformedtodeterminesignificantpredictors for overall survival and recurrence-free survival. Results. Fifty-seven patients (41 men, 16 women) underwent thoracic operations with curative intent. Complete resection was achieved in 91% of cases. The results of staining for CD56, synaptophysin, neuronal specific enolase, chromogranin-A, and somatostatin were positive in 86%, 81%, 68%, 61%, and 21%, respectively. Recurrence occurred in 28 patients (49%). Overall survival and recurrence-free survival were 50% and 45%, respectively, after 3 years. Advanced nodal status (N1, p < 0.025; N2, p < 0.02) and simultaneous expression of CD56 and chromogranin-A (p < 0.04) were significantly associated with poorer outcome. Conclusions. LCNEC is a rare neuroendocrine pulmonary malignancy that is associated with poor prognosis and high recurrence rates. Surgical treatment can achieve satisfactory results in selected cases. Neuroendocrine marker profiles may predict prognosis and may influence the decision for adjuvant therapy or follow-up intervals. (Ann Thorac Surg 2015;99:983–90) 2015 by The Society of Thoracic Surgeons
Calculation of Special Angles in Trigonometry via Visual Mathematical Hand Mnemonic Tactic (VMHMT)

In 2016, the Mathematical Society of the Philippines (MSP) testified that among Filipino learners of ages 14-18, 85% experienced the dilemma on dealing with the evaluation of special angles in Trigonometry wherein 45% was from public high schools. This study aimed to determine the potential of a visual mathematical hand mnemonic tactic (VMHMT) as fast and accurate classroom mathematical mnemonic strategy in evaluating special angles in Trigonometry. A 20-item multiple choice type test with 50-minute time allotment. Reliability of the test items was also measured via Pearson’s. The test was administered three times with 7-day interval for each strategy with uniform starting time. ANOVA results showed no significant difference among the three manual strategies in terms of accuracy of answers (p=0.373) which means that the accuracy of the VMHMT is comparable with that of the other existing manual strategies. Meanwhile, significant difference was obtained in terms of speed of calculations (p=0.000) wherein the use of unit circle rendered longest time for calculations (M=21.234) while the VMHMT (M=14.70) and table of trigonometric ratios (M=14.23) appeared to be very fast. Learners find the strategy more relevant and experiential which could make a more lifelong learning.
Validity and practicality of guided discovery learning models for chemistry learning in senior high school

This paper is part of a dissertation study that aims to reveal the level of validity and practicality of guided discovery learning (GDL) model developed for senior high school chemistry learning. This research and development study used 4D instructional design model. Instruments used were observation sheets and questionnaires. The product was validated by 12 experts and tested on 8 chemistry teachers and 96 students in three public senior high schools in Padang, Indonesia in 2016/2017 academic year. Observation results were analyzed by percentage technique while data of validity and practicality of GDL-PK model were analyzed with Cohen’s kappa formula. Analysis showed that the average values of kappa moment (k) were 0.87 for validity test and 0.91 for practicality test belonging to very high degree category. Analysis of observation result showed that the average percentages of model implementation were 94% in SMAN X Padang, 97% in SMAN Y Padang, and 87% in SMAN Z Padang having very high degree category. Results showed that GDL-PK model was valid and practical and could be fully implemented by teachers and students in chemistry learning. Therefore, the developed GDL-PK model was feasible as teachers’ and prospective teachers’ considerations for senior high school chemistry learning.
Volatility modeling and limit-order book analytics with high-frequency data

The vast amount of information characterizing nowadays’s high-frequency financial datasets poses both opportunities and challenges. Among the opportunities, existing methods can be employed to provide new insights and better understanding of market’s complexity under different perspectives, while new methods, capable of fully-exploit all the information embedded in high-frequency datasets and addressing new issues, can be devised. Challenges are driven by data complexity: limit-order book datasets constitute of hundreds of thousands of events, interacting with each other, and affecting the event-flow dynamics. This dissertation aims at improving our understanding over the effective applicability of machine learning methods for mid-price movement prediction, over the nature of long-range autocorrelations in financial time-series, and over the econometric modeling and forecasting of volatility dynamics in high-frequency settings. Our results show that simple machine learning methods can be successfully employed for mid-price forecasting, moreover adopting methods that rely on the natural tensorrepresentation of financial time series, inter-temporal connections captured by this convenient representation are shown to be of relevance for the prediction of future mid-price movements. Furthermore, by using ultra-high-frequency order book data over a considerably long period, a quantitative characterization of the long-range autocorrelation is achieved by extracting the so-called scaling exponent. By jointly considering duration series of both interand crossevents, for different stocks, and separately for the bid and ask side, long-range autocorrelations are found to be ubiquitous and qualitatively homogeneous. With respect to the scaling exponent, evidence of three cross-overs is found, and complex heterogeneous associations with a number of relevant economic variables discussed. Lastly, the use of copulas as the main ingredient for modeling and forecasting realized measures of volatility is explored. The modeling background resembles but generalizes, the well-known
US Rheumatologists' Attitudes, Practice Habits, Barriers, and Knowledge Gaps in Assessing and Monitoring Patients with Rheumatoid Arthritis according to Recent Recommendations

Objective: To assess the attitudes, practice habits, and educational needs of rheumatologists in the US related to the assessment and monitoring of rheumatoid arthritis (RA) patients according to contemporary practice guidelines and treatment paradigms. Methods: A 22-question online survey of US rheumatologists assessed the extent of compliance with, and barriers to, the use of a multitude of newly introduced guidelines and consensus statements aimed at improving outcomes of patients with RA. Several different quantitative and qualitative question types were used: multiple choice; agreement ratings; attitudinal and frequency-of-use ratings of different tools, guidelines, and clinical practice strategies; and open-ended inquiries on current challenges and barriers. Results: The margin of error of our sample size (n = 96) (±9.9%) was identical to that from a related survey of Canadian rheumatologists. A total of 77% of the rheumatologists in our survey were in private practices. Only 21% routinely used the 2010 American College of Rheumatology (ACR)/European League Against Rheumatism Classification Criteria to confirm an RA diagnosis. Due to barriers and knowledge and practice gaps, treat-to-target recommendations were not routinely applied, ACR-recommended scales and composite indices were not used, and the 7 ACR-endorsed RA quality indicators were not implemented. The recommended tools were deemed too time- and resource-consuming. Lack of or decreased insurance coverage and time constraints were barriers to using the RA quality indicators. Conclusion: Our survey found a lack of knowledge and competence associated with the appropriate clinical use of RA disease activity measures, an integral component of treating to target. Respondents indicated only “sometimes” using evidence-based treatment recommendations. Educational initiatives are needed to address these gaps, as the goal of practice guidelines is to improve patient outcomes via optimal implementation of disease management strategies.
Data mining of social manifestations in Twitter: An ETL approach focused on sentiment analysis

The objective of this study was to analyze sentiments of users of online social network twitter to understand how people manifested toward the article published by the magazine Veja on 04-18-16 entitled "bela, recatada e do lar" (beautiful, demure and from home) in an attempt to understand how this behavior evolved in two weeks and to assess which events had aroused greater reaction from people. To this end, a data mining technique known as sentiment analysis was used with the help of the ETL (Extract, Transform and Load) methodology and the Naive Bayes probabilistic learning algorithm. Moreover, the null hypothesis was formulated and tested to see whether two events that took place during the collection period influenced, in fact, the polarity of analyzed sentiments in the generated database.
Understanding the Role of Practice in Learning for Geriatric Individuals

This article reviews the literature on the role of practice in learning for geriatric individuals. It concentrates on understanding how practice, an often-used method of instruction, affects learning in the older patient from a cognitive standpoint. The article also reviews the need to consider memory, cognition, and learning principles for adults. In addition, a discussion of the internal and external factors that affect practice and provide the most benefit to older patients is included, as well as strategies that support and interfere with learning.
The expression of the true self in the online world: a literature review

ABSTRACT The true self is one of the essential parts of people’s self-concept and identity, but it is not easily expressed in face-to-face communications. On the Internet, people can express what they intrinsically think and believe with fewer concerns about others’ disapproval and judgments. Increasingly more researchers have started to investigate people’s expression of the true self in the online context. However, the existing research is quite diverse and fragmented. A rigorous and comprehensive review of the emerging literature is called for. The present study conducted a systematic literature review to examine what is already known about the expression of the true self online. This paper analysed the selected studies on the basis of research contexts, research methods, and research themes. Our review offers readers an easy access to the current status of research in this field; it also provides some insightful suggestions for future studies.
Dynamics of cyclone evacuation behavior among southwestern coastal residents in Bangladesh: A case study of cyclone Sidr

Cyclone Sidr struck the southwestern coast of Bangladesh on November 15, 2007, resulting in 3,406 deaths and damaged properties of about US $1.7 billion. Despite the government’s sincere efforts, thousands of coastal residents did not comply with the evacuation orders. This article attempts to identify the sociodemographic factors affecting evacuation choices during the cyclone. Following systematic random sampling technique, a total of 384 heads of household was surveyed in the southwestern coast of Bangladesh. The bivariate results indicate that single women, older residents, people with small possessions, and people with higher level of education and occupation are more likely to evacuate. Moreover, level of education, household’s status of food security, trust in cyclone warning, and perceived severity of cyclone are also found as significant predictors of evacuation choice. Trust in cyclone warning has been found as the single best predictor. This article recommends improvement in the cyclone warning system, establishment of more public cyclone shelters, and implementation of different campaigns in coastal areas to increase the use of public shelters.
Generic interactive pixel‐level image editing

Several image editing methods have been proposed in the past decades, achieving brilliant results. The most sophisticated of them, however, require additional information per‐pixel. For instance, dehazing requires a specific transmittance value per pixel, or depth of field blurring requires depth or disparity values per pixel. This additional per‐pixel value is obtained either through elaborated heuristics or through additional control over the capture hardware, which is very often tailored for the specific editing application. In contrast, however, we propose a generic editing paradigm that can become the base of several different applications. This paradigm generates both the needed per‐pixel values and the resulting edit at interactive rates, with minimal user input that can be iteratively refined. Our key insight for getting per‐pixel values at such speed is to cluster them into superpixels, but, instead of a constant value per superpixel (which yields accuracy problems), we have a mathematical expression for pixel values at each superpixel: in our case, an order two multinomial per superpixel. This leads to a linear least‐squares system, effectively enabling specific per‐pixel values at fast speeds. We illustrate this approach in three applications: depth of field blurring (from depth values), dehazing (from transmittance values) and tone mapping (from brightness and contrast local values), and our approach proves both favorably interactive and accurate in all three. Our technique is also evaluated with a common dataset and compared favorably.
Hand Contamination among Food Handlers

Introduction: Food handlers act as a vehicle for microorganisms causing a potential risk to the public health. Hands contamination of food handlers can be used as an indicator of their behavior regarding food-related practice and personal hygiene. Aim of the Study: To assess hand contamination among food handlers working in Menoufia University and Shebin Al-Kom Educational hospital kitchens and the effect of a health education session over them. Subjects and Methods: A seventy two food handlers were the target group of this study. A prestructured questionnaire was filled including socio-demographic data beside questions regarding risk factors for contamination and personal hygiene practices during dealing with food. Hand rinse sample was taken from each participant to detect the contaminants. A brief and simple health education session was held regarding personal hygiene practices. Three months later, the same kitchen was revisited to appraise the participants’ hygiene compliance where another hand sample rinses were taken. Results: Both Staphylococcus Epidermidis and Escherichia coli (41.7%) followed by Staphylococcus aureus (29.2%) were the prevalent organisms. A significant reduction in hand
Bidirectional LSTM Autoencoder for Sequence Based Anomaly Detection in Cyber Security

- Cyber-security is concerned with protecting information, a vital asset in today’s world. The volume of data that is generated can be usefully analyzed when cyber-security systems are effectively implemented with the aid of software support. Our approach is to determine normal behavior of a system based on sequences of system call traces made by the kernel processes in the system. This paper describes a robust and computationally efficient anomaly based host based intrusion detection system using an Encoder-Decoder mechanism. Using CuDNNLSTM networks, it is possible to obtain a set of comparable results with reduced training times. The Bidirectional Encoder and a unidirectional Decoder is trained on normal call sequences in the ADFA-LD dataset. Intrusion Detection is evaluated based on determining the probability of a sequence being reconstructed by the model representing normal data. The sequences with a low probability value are classified as an anomaly.
Treatment of metastatic disease to the tibia, ankle, and foot

Skeletal metastatic disease to the lower extremity is rare. However, when it does happen it is a source of significant morbidity to the patient. The orthopaedic surgeon must be acutely cognizant of the need to prevent or treat fractures and provide immediate and full weight bearing for these patients. Anatomic considerations must be considered, and different treatment modalities are used based on where the metastatic lesion is located. Surgical management of metastatic foci distal to the knee include curettage with cement or bone graft augmentation and stabilization, en bloc resection with reconstruction, and amputation. Regardless of what construct is used, the reconstruction should be expected to last for the lifetime of the patient with minimal possibility of local recurrence or progression. For this reason, biologic considerations must be made. Surgical treatment options for metastases from highly aggressive tumors should be kept simple and allow for immediate weight bearing whereas those from more indolent tumors should focus on ensuring the longevity of the construct. Adjuvants such as bisphosphonates or chemotherapeutic agents can be used and added to the bone cement at time of surgery.