Miracle-dz/UniFAR-FTUs huggingface dataset:
Community Pharmacy Practice Towards Cancer Health and the Need for Continuous Cancer Education: Ghana Situation

Traditionally, cancer patients are managed mostly within the secondary healthcare system. As the burden of the disease increases, secondary care has to work with the primary care to provide good support for healthy population, the patients, etc. The community pharmacists are one of the primary care providers because they are the most accessible healthcare providers in the community. For this group to meet these demands of an evolving new role and improve the health outcomes, continuous professional development (CPD) is essential. This study was set to gather information about the professional practice of Ghanaian community pharmacists on cancer health, their interest and importance in receiving continuous education on cancer. Methods: A cross-sectional study was conducted using electronic questionnaires. Key Findings: Majority (67.1%) spent less than or ten minutes of their time interacting with patients and 70.8% referred patients who consistently request for medication to a hospital. Majority of participants (43.4%) have never attended cancer continuous education and 67.6% indicated their interest in receiving cancer continuous education in the future. There was statistically significant difference between the educational level and professional interaction with cancer patients (p=0.004). Provision of cancer printed materials (p=0.00) and interest in attending cancer continuous education in the future (p=0.007) were also significantly affected by educational level. ‘Handout/booklet with self- test’ was the preferred mode of delivery for cancer education. Conclusion: community pharmacists strongly play a significant role in cancer health through their professional practice. The challenges observed can be overcome through a well-organized cancer continuous education using participants preferred medium of delivery.
Sequential assimilation of satellite-derived vegetation and soil moisture products using SURFEX_v8.0: LDAS-Monde assessment over the Euro-Mediterranean area

Abstract. In this study, a global land data assimilation system (LDAS-Monde) is applied over Europe and the Mediterranean basin to increase monitoring accuracy for land surface variables. LDAS-Monde is able to ingest information from satellite-derived surface soil moisture (SSM) and leaf area index (LAI) observations to constrain the interactions between soil–biosphere–atmosphere (ISBA, Interactions between Soil, Biosphere and Atmosphere) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Meteorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. It makes use of the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth. Transfer of water and heat in the soil rely on a multilayer diffusion scheme. SSM and LAI observations are assimilated using a simplified extended Kalman filter (SEKF), which uses finite differences from perturbed simulations to generate flow dependence between the observations and the model control variables. The latter include LAI and seven layers of soil (from 1 to 100 cm depth). A sensitivity test of the Jacobians over 2000–2012 exhibits effects related to both depth and season. It also suggests that observations of both LAI and SSM have an impact on the different control variables. From the assimilation of SSM, the LDAS is more effective in modifying soil moisture (SM) from the top layers of soil, as model sensitivity to SSM decreases with depth and has almost no impact from 60 cm downwards. From the assimilation of LAI, a strong impact on LAI itself is found. The LAI assimilation impact is more pronounced in SM layers that contain the highest fraction of roots (from 10 to 60 cm). The assimilation is more efficient in summer and autumn than in winter and spring. Results shows that the LDAS works well constraining the model to the observations and that stronger corrections are applied to LAI than to SM. A comprehensive evaluation of the assimilation impact is conducted using (i) agricultural statistics over France, (ii) river discharge observations, (iii) satellite-derived estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project and (iv) spatially gridded observation-based estimates of upscaled gross primary production and evapotranspiration from the FLUXNET network. Comparisons with those four datasets highlight neutral to highly positive improvement.
Mapping Online Data on Offline Documents

This thesis describes a method to find a part of online data in an offline document. This method is able to find the offline document that belongs to the online data from a set of offline documents, or vice versa. In order to optimize the mapping between the online and the offline data, an optimal rotation and resizing of the online data is calculated. This is useful since it produces a better mapping between online and offline data, which makes several methods that are only applicable for online data available for offline data, and vice versa. Results show that this method can be used for finding the offline document that belongs to certain online data, since it succeeded in 98.07% of the cases for the used dataset. The results also show that computing the optimal rotation and resize factor significantly improves the mapping between online and offline data. This improvement is 6.56% for the used dataset.
Supplementary File for “Dex-Net 3.0: Computing Robust Robot Suction Grasp Targets in Point Clouds using a New Analytic Model and Deep Learning”

Our primary numeric metrics of performance were: 1) Average Precision (AP). The area under the precisionrecall curve, which measures precision over possible thresholds on the probability of success predicted by the policy. This is useful for industrial applications where a robot may take an alternative action (e.g. probing, asking for help) if the planned grasp is predicted to fail. 2) Success Rate. The fraction of all grasps that were successful. We argue that these metrics alone do not give a complete picture of how useful a suction grasp policy would work in practice. Average Precision (AP) penalizes a policy for having poor recall (a high rate of false negatives relative to true positives), and success rate penalizes a policy with a high number of failures. However, not all failures should be treated equally: some failures are predicted to occur by the GQ-CNN (low predicted probability of success) while the others are the result of an overconfident prediction. In practice, a suction grasp policy would be part of a larger system (e.g. a state machine) that could decide whether or not to execute a grasp based on the continuous probability of success output by the GQ-CNN. As long as the policy is not overconfident, such as system can detect failures before they occur and take an alternative action such as attempting
Students with Growth Mindset Learn More in School: Evidence from California’s CORE School Districts

VERSION: October 2019 While the importance of social-emotional learning for student success is well established, educators and researchers have less knowledge and agreement about which social-emotional skills are most important for students and how these skills distribute across student subgroups. Using a rich longitudinal dataset of 221,840 fourth through seventh grade students in California districts, this paper describes growth mindset gaps across student groups, and confirms, at a large scale, the predictive power of growth mindset for achievement gains, even with unusually rich controls for students’ background, previous achievement, and measures of other social-emotional skills. Average annual growth in English language arts and math corresponding to differences between students with fixed and growth mindset in a same school and grade level is 0.07 and 0.05 standard deviations respectively, after adjusting for students’ characteristics and previous achievement. This estimate is equivalent to 48 and 35 additional days of learning.
Mitk-di

Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of brain structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop algorithms that provide detailed information on the white matter fibre architecture and disorders in the brain. High angular resolution diffusion imaging (HARDI) provides an extraordinarily high level of detail, including entire manifolds of information at each voxel. The lack of standardized software tools for data I/O, model reconstruction, interactive visualization, feature extraction and statistics impedes development and sustainable evaluation in HARDI research. In this paper, a new toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITK-DI, is presented and its features are summarized at each stage of the pipeline from raw data processing to comprehensive statistics. MITK-DI aims at integrating novel diffusion imaging techniques into the MITK toolkit to provide a comprehensive software framework for performant data processing, analysis and interactive visualization. An examplary application of the framework is shown using phantom and in-vivo datasets from a clinical MR scanner. Visualizations are presented that reveal details for which there would be no direct way to appreciate using conventional display of scalaror RGB-images.
Improve Computer-Aided Diagnosis With Machine

In computer-aided diagnosis (CAD), machine learn- ing techniques have been widely applied to learn a hypothesis from diagnosed samples to assist the medical experts in making a diagnosis. To learn a well-performed hypothesis, a large amount of diagnosed samples are required. Although the samples can be easily collected from routine medical examinations, it is usually impossible for medical experts to make a diagnosis for each of the collected samples. If a hypothesis could be learned in the presence of a large amount of undiagnosed samples, the heavy burden on the medical experts could be released. In this paper, a new semisupervised learning algorithm named Co-Forest is pro- posed. It extends the co-training paradigm by using a well-known ensemble method named Random Forest, which enables Co-Forest to estimate the labeling confidence of undiagnosed samples and easily produce the final hypothesis. Experiments on benchmark data sets verify the effectiveness of the proposed algorithm. Case studies on three medical data sets and a successful application to microcalcification detection for breast cancer diagnosis show that undiagnosed samples are helpful in building CAD systems, and Co-Forest is able to enhance the performance of the hypothesis that is learned on only a small amount of diagnosed samples by utilizing the available undiagnosed samples.
Person-Centered Relational Therapy: An Organismic Perspective

Author Note. Address for correspondence: Keith Tudor, School of Psychotherapy, Auckland University of Technology, Private Bag 92006, Auckland 1020, New Zealand. E-mail: keith.tudor@aut.ac. nz Abstract. Person-centered therapy is the original relationship therapy. In the context of the increasing interest in the “relational turn” in therapy, this paper reconsiders the therapeutic relationship and the relational in person-centered theory and practice. The paper distinguishes and develops an organismic relational perspective, as distinct from a self-relational perspective, and thus extends Rogers’ use of the term “organismic” to include the client–therapist relationship as well as the integral relationship people have with their environment. In this and another paper (Tudor, 2010a), the author argues that an organismic perspective also emphasizes homonomy, or a trend to belonging, alongside autonomy, and thus offers a counterpoint to the emphasis on individuation and individualism prevalent in Western culture and psychology.
A multi-input, multi-output model on fuzzy rule-based systems to predict macroeconomic variables in Iran

The prediction of economic variables is one of the main issues in a country's macro decisions. Since in many cases there is no historical data for this purpose and it is necessary to have more than one output, it is necessary to use expert opinions and consequently, model expert opinions in the form of mathematical functions, adds to the complexity of the task and the importance of the problem. To solve such problems, this paper presents a ten-step process using fuzzy rule-based systems. At the first step, the three inputs that include: the price of OPEC oil, the level of Iran and Saudi relations and the level of political tension in OPEC member countries and also the three output variables that include: the amount of employment, the economic growth, and the oil price forecast, have been modeled in the form of trapezoidal and triangular functions. Then, these variables have been converted to linear functions. In the next steps, the three-dimensional decision tables were designed and then by using the fuzzy rule-based systems (if, . Then.), the preconditions and sequences (results) of the decision rules were written and coded in the Matlab software. The results indicate that the outputs are in line with the existing economic realities of Iran and that three input variables to a certain extent can cause changes in the three output variables. Less technical so far with problems with this complexity of problems are capable of results with this obvious.
Protodioscin from herbal plant Tribulus terrestris L improves the male sexual functions, probably via DHEA

SUMMARY An interesting correlation of dehydroepiandrosterone-sulphate (DHEA-S) level with the incident of low sex drive and higher occurrence of impotence was discovered in studies with patients diagnosed with diabetes mellitus. To test further the relationship between DHEA-S and erectile dysfunction (ED), we conducted a clinical trial of 30 non-diabetic men with ED, 30 non-diabetic men without ED and 15 diabetic men with ED. These men are given extract of Tribulus terrestris (Libilov) at 3 x 250 mg / day for 3 weeks. The DHEA-S levels, as well as other blood and liver parameters were evaluated. We found a significant increase of DHEA-S levels in diabetic and non-diabetic subjects after treatment, and a significant increase in the frequency of successful intercourse by 60% in both the diabetic and non-diabetic groups with or without ED.
THE IMPLEMENTATION OF DUAL PATHWAY CREATIVITY MODEL IN TOURISM SECTOR IN WEST SUMATRA

This research examined the implementation of the Dual Pathway Creativity Model (DPCM) as a function of cognitive flexibility and cognitive persistence in employees working at companies engaged in the tourism sector in West Sumatra. Dual Pathway Creativity Model (DPCM) suggests a more comprehensive theory about employee creativity. DPCM argues that a flexible and pleasant environment can encourage flexibility and creativity. However, problems and a less flexible environment might also encourage creativity, but through a different process compared to a flexible environment. This research used a purposive sampling technique with 96 respondents, consisting of employees working in the tourism sector. The results showed that cognitive flexibility had a positive effect on employee creativity in the tourism sector in West Sumatra, while cognitive persistence had a negative effect on employee creativity in the tourism sector in West Sumatra.
Law's Halo and the Moral Machine

How will we assess the morality of decisions made by artificial intelli­gence—and will our judgments be swayed by what the law says? Focusing on a moral dilemma in which a driverless car chooses to sacrifice its passenger to save more people, this study offers evidence that our moral intuitions can be influenced by the presence of the law.
Role of Opioid System in Empathy-like Behaviours in Rats

Background Empathy is defined as the ability to simulate the mental states of others. Recent studies have demonstrated empathy-like behaviors in other animals including rats and mice. The objective of the current study was to evaluate the effect of acute administration of morphine and naloxone on cognition and nociception changes following observing conspecifics undergoing nociceptive stimulus. Methods Adult male Wistar rats were used (n = 8 for each group). One cagemate received formalin injection into the hindpaw five times within a nine-day period and the other cagemate observed the pain while being pretreated with saline, morphine, or naloxone [10 mg/kg, intraperitoneal (i.p.)]. Pain behaviors, anxiety-like behaviour, locomotion, balance and muscle strength were evaluated in the observer animals. Findings Observing a cagemate in pain increased anxiety-like behavior and reduced thermal pain threshold in the observer animals. Administration of morphine reversed these effects and naloxone did not affect the responses. Conclusion Results of the current study reveal an important role for opioid receptors (ORs) in empathy for pain, so that activation of this system dampens the empathy-like responses.
Prenatal exposure to antibiotics and the risk of inflammatory diseases in children: a population-based study

iv LIST OF TABLES . vi ABBREVIATIONS . vii CHAPTER 1: INTRODUCTION . 1 1.1. Inflammatory bowel disease (IBD) . 2 1.2. Connective tissue disorders (CTD) . 4 1.3. Cleanliness and disease: The “hygiene hypothesis” . 5 1.3. 1. Epidemiological studies related to hygiene hypothesis. 6 1.4. Transition to the “old friends” theory . 7 1.5. Human gut microbiota . 9 1.5. 1. Dysbiosis . 12 1.5. 2. Functions of gut microbiota . 12 1.6 Antibiotics causing dysbiosis and inflammatory diseases . 19 CHAPTER 2: METHODS . 21 2.1 Primary exposure: Prenatal exposure to antibiotics . 23 2.2. Outcomes: Childhood IBD and CTD . 24 2.3. Potential confounders . 24 Demographic covariates . 25
INFLUENCE OF DIFFERENT CHEMICAL AGENTS ON THE ADULTERED MILK PHYSICAL PROPERTIES CORRECTION

In the milk industry, one of the most common frauds is the mixing of milk with water with the goal of improving the quantity. After the water adding to the milk, the counterfitert adds different substances to bring the physical properties in the right range. The aim of this study is to evaluate the influence of adulteration agents on the milk physical properties. For this purpose, the milk was adultered with different percentages of water (0, 5, 10 and 20 % respectively). The milk adultered with 20 % water was mixed with four substantces in order to bring the density and crioscopic temperature in the right range. The substantces used for the density and crioscopic temperature corrections were: NaCl, NH 4 Cl, NH 4 NO 3 and CH 4 ON 2 . The NaCl, NH 4 Cl, NH 4 NO 3 and CH 4 ON 2 were mixed with the milk substituted with 20% eater in three different levels (0.25, 0.5 and 1% respectively in the case of NaCl, and 0.05, 0.10 and 0.20% respectively in the case of the other adulterants). All the four chemical substances brought the density and crioscopic temperature in the normal range but in different percentages.
Actions Speak Louder Than Words? Word of Mouth vs. Silence of Mouth, an application store observation

The impact of word of mouth and silence of mouth has been researched multiple times in the area of traditional shopping and online shopping on websites. The researches came to the conclusions that these two forms of interaction have an influence on the customer purchase of the item or service. Be that as it may, a new sort of retailing has been on the rise as of late. More and more customers are purchasing or downloading gaming applications on their mobile devices such as smartphones and tablets. These products lack tangibility just like services but aren’t classified as a service. With applications becoming increasingly popular, it is starting to get more important to understand the social drivers of a successful application. This paper researches how word of mouth and silence of mouth affects application adoption decisions in mobile software distribution platforms and what the magnitude of these two social interactions is. To research the effect of the two social interactions, the ordered probit model was employed. Ordered probit model is an ordered choice model which allows one to map an underlying continuous preference to a categorical, yet ordered dependent variable. In the case of this research, the underlying preference is based on the perceived quality of the application, and the dependent variable is the categorized number of installations. The perceived quality was determined with the social interactions word of mouth and silence of mouth. These two phenomenons are portrayed in the Play Store as the average rating and the ranking. With support of the ordered probit model, a hit-rate table was constructed, which allows us to show the model performance in terms of predictability. This research showed that the average rating and ranking influence the adoption. Namely, the higher an application is rated, thus higher valued by the consumers, the more likely it is for an application to be in one of the higher number of installation categories. Ranking also influences the adoption as was expected based on the literature review. The higher the ranking, the more likely an application is going to be in a higher installation category.
AES Hybridization with DWT Audio Steganography MSc Internship Cyber Security

Simple text exchanged on the internet can be intercepted and confidentiality can be compromised by an intruder. In this paper, a solution is proposed that uses a combination of encryption and steganography to maintain the confidentiality of the simple text exchanged. From the time people have started using the internet, security has become a major concern. Steganography provides security up to some level, there has been a huge amount of research done in relation to steganography. Steganography is considered to be secure only until someone knows that the steganography is applied, the moment attacker knows that the steganography is applied steganography fails. Steganography can be easily broken, and the original text can be obtained. In the proposed system, if the intruder/attacker breaks steganography, he/she will not be able to get the original text as it would be encrypted. The proposed technique provides a high quality of Peak Signal-to-Noise Ratio (PSNR) and Signal to Noise Ratio (SNR) when steganography is applied. There is no major audible distortion after the encrypted text is hidden in the audio file.