Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy of a web-based self-help tool to reduce problem gambling in Switzerland: study protocol of a two-armed randomised controlled trial

Introduction The past-year prevalence of problem gambling worldwide averages 2.3%. Switzerland exhibits a slightly lower past-year prevalence rate, of 1.1%, among adults. Only a minority of these adults attend outpatient treatment. Surveyed problem gamblers have explained that they wanted to handle the problem on their own. The option of a web-based self-help programme could potentially reach those users who hesitate to approach treatment centres and help them to reduce or stop their problem gambling. The effectiveness of such web-based interventions has been shown in other countries. Methods and analysis This two-armed randomised controlled trial (RCT) will examine the efficacy of a web-based self-help intervention, relative to an active control condition with a self-help manual, at reducing problem gambling. The active intervention programme, spanning 8 weeks, consists of nine modules developed to reduce gambling and attenuate psychopathological comorbidity, including depression, anxiety and stress-related disorder symptoms, relying on motivational interviewing and cognitive behavioural therapy. With a target sample size of 352, questionnaire data will be collected at baseline, and at 8 and 24 weeks after baseline. Primary outcomes will be the number of days one has gambled in the last 30 days. Secondary outcomes will include money and time spent on gambling activities, changes in gambling-related problems (Problem Gambling Severity Index, Gambling Symptom Assessment Scale), use of alcohol and cigarettes, and psychopathological comorbidity. All data analysis will comply with the intention-to-treat principle. Ethics and dissemination The RCT will be conducted in accordance with the Declaration of Helsinki; the consort eHealth Guidelines for studies on medical devices; the European Directive on medical devices 93/42/EEC, Swiss Law and Swiss Regulatory Authority requirements. The study was approved by the ethics committee of the Canton of Zurich. Results will be published in a scientific peer-reviewed journal. Participants will be informed via e-mail about study results via a lay-person-friendly summary of trial findings. Trial registration number Current Controlled Trials registry (ISRCTN16339434).
Clinicopathologic characteristics of mixed epithelial/mesenchymal metaplastic breast carcinoma (carcinosarcoma): a meta-analysis of Chinese patients.

Breast carcinosarcoma is a rare and aggressive subtype of metaplastic breast cancer. Data focusing on breast carcinosarcoma is limited. The purposes of this study are to describe the clinicopathological features of breast carcinosarcoma and to evaluate post-surgical outcomes. MATERIAL AND METHODS All case reports about breast carcinosarcoma in China were collected from eligible papers published in Chinese core periodicals between 1990 and 2015 with key words of breast carcinosarcoma, breast cancer, carcinosarcoma, or metaplastic carcinoma. The survival rates, clinical behaviour, and pathological characteristics were analysed. RESULTS The mean age of the cohort of 215 patients was 53 years (range, 25-82 years). The tumour size ranged from 2.5 cm to 18 cm. The incidence of pathologically confirmed lymph node metastases was 30.81%. The epithelial component in a tumour may be composed of invasive ductal carcinoma (84.21%), squamous cell carcinoma (7.89%), lipid-rich carcinoma (6.58%), or adenocarcinoma (1.31%). Mesenchymal components may contain different elements ranging from fibrosarcoma (63.16%) to chondrosarcoma (19.73%), osteosarcoma (9.21%), liposarcoma (3.95%), or leiomyosarcoma (3.95%). The five-year survival of the breast carcinosarcoma in 149 patients is 62.6% (CI: 54.9%~0.703%). CONCLUSIONS Breast carcinosarcoma is a rare subtype of metaplastic breast cancer. It is characterised by large tumour size, higher rates of axillary nodal involvement, higher rates of both local and distant recurrence, and is difficult to diagnose with preoperative core needle biopsies. Adjuvant treatment after surgical operation may improve the five-year OS of patients with breast carcinosarcoma.
Effect of Aging on Chemical Composition and Rheological Properties of Neat and Modified Bitumen

The aim of this research was to define the effect of oxidative aging on the chemical and rheological properties of neat and styrene-butadiene-styrene (SBS) polymer-modified bitumen. The experimental research had two objectives: firstly, the short and long-term effects of aging on the properties of neat and polymer-modified bitumen were investigated. Then, the aging indexes based on chemical and rheological properties to describe the age of unknown bitumen were established. Aging characteristics such as the Gaestel index, sulfoxide and carbonyl indexes, linear viscoelastic strain range, crossover temperature, and Glover–Rowe parameter were analysed for laboratory aged and naturally aged neat and polymer-modified bitumen. The functional composition of aged bitumen was evaluated by measuring absorption with Fourier transform infrared (FT-IR) attenuated total reflection (ATR) spectrometer. The saturates, aromatics, resins, and asphaltenes (SARA) fractions were determined with thin layer chromatography with flame-ionization detection (TLC-FID) to determine the colloidal instability index (Gaestel index). Finally, the complex shear modulus was determined with dynamic shear rheometer (DSR) to evaluate the influence of aging on the bitumen mechanical performance.
Sluggish cognitive tempo and exposure to interpersonal trauma in children

ABSTRACT Background: Childhood adversity has been suggested, but not yet empirically examined, as a factor in sluggish cognitive tempo (SCT) in childhood. Objective: This study was an examination of SCT in relation to childhood adversity, and its association with exposure to non-interpersonal and interpersonal trauma. Method: Caregivers (N = 161) and a sub-sample of children, 8–17 years old, were recruited from mental health and pediatric practices/programs and interviewed. Results: SCT was positively associated with interpersonal trauma but not non-interpersonal trauma. Two hierarchical regression analyses revealed that interpersonal trauma exposure was associated with SCT score over and above symptoms of other psychopathologies. Conclusion: Results suggest that SCT is associated with interpersonal trauma exposure in children. Further research is needed to examine the association between SCT and interpersonal trauma exposure, and trauma-related biopsychosocial impairments.
Techniques for investigating mitochondrial gene expression

The mitochondrial genome encodes 13 proteins that are components of the oxidative phosphorylation system (OXPHOS), suggesting that precise regulation of these genes is crucial for maintaining OXPHOS functions, including ATP production, calcium buffering, cell signaling, ROS production, and apoptosis. Furthermore, heteroplasmy or mis-regulation of gene expression in mitochondria frequently is associated with human mitochondrial diseases. Thus, various approaches have been developed to investigate the roles of genes encoded by the mitochondrial genome. In this review, we will discuss a wide range of techniques available for investigating the mitochondrial genome, mitochondrial transcription, and mitochondrial translation, which provide a useful guide to understanding mitochondrial gene expression.
Anti-Inflammatory and Anticancer Properties of Bioactive Compounds from Sesamum indicum L.—A Review

The use of foodstuff as natural medicines has already been established through studies demonstrating the pharmacological activities that they exhibit. Knowing the nutritional and pharmacological significance of foods enables the understanding of their role against several diseases. Among the foods that can potentially be considered as medicine, is sesame or Sesamum indicum L. , which is part of the Pedaliaceae family and is composed of its lignans such as sesamin, sesamol, sesaminol and sesamolin. Its lignans have been widely studied and are known to possess antiaging, anticancer, antidiabetes, anti-inflammatory and antioxidant properties. Modern chronic diseases, which can transform into clinical diseases, are potential targets of these lignans. The prime example of chronic diseases is rheumatic inflammatory diseases, which affect the support structures and the organs of the body and can also develop into malignancies. In line with this, studies emphasizing the anti-inflammatory and anticancer activities of sesame have been discussed in this review.
Sequential phosphorylation of NDEL1 by the DYRK2-GSK3β complex is critical for neuronal morphogenesis

Neuronal morphogenesis requires multiple regulatory pathways to appropriately determine axonal and dendritic structures, thereby to enable the functional neural connectivity. Yet, however, the precise mechanisms and components that regulate neuronal morphogenesis are still largely unknown. Here, we newly identified the sequential phosphorylation of NDEL1 critical for neuronal morphogenesis through the human kinome screening and phospho-proteomics analysis of NDEL1 from mouse brain lysate. DYRK2 phosphorylates NDEL1 S336 to prime the phosphorylation of NDEL1 S332 by GSK3β. TARA, an interaction partner of NDEL1, scaffolds DYRK2 and GSK3β to form a tripartite complex and enhances NDEL1 S336/S332 phosphorylation. This dual phosphorylation increases the filamentous actin dynamics. Ultimately, the phosphorylation enhances both axonal and dendritic outgrowth and promotes their arborization. Together, our findings suggest the NDEL1 phosphorylation at S336/S332 by the TARA-DYRK2-GSK3β complex as a novel regulatory mechanism underlying neuronal morphogenesis.
Machine Learning for High School Students

In this study, we developed a machine learning method for object recognition that can be implemented using knowledge that high school students attain during their normal math and IT classes. We then tailored a two-hour interactive lesson in which the students were divided into groups to implement solutions to six distinct problems required by the method. The solutions were later put together by the teacher into a working web application (HTML + JavaScript). The lesson was taught on three occasions in Romanian schools to students between 13 and 19 years old. The students were excited about the lesson, and the collected data measuring students' intrinsic motivation suggests that the given tasks and the type of instruction were motivating them. The students also found the lesson achievable regardless the level of their previous programming background. The students were even able to suggest viable improvements to the method. The lesson is presented in short in this (17 minute) YouTube video1. Furthermore, we utilized the developed machine learning tool in a workshop with primary school children. Observations from this workshop suggest wider applicability of the tool, as well as further research questions on machine learning in K-12 settings.
Intelligent Network Application in Computer-aided Diagnosis

Malaria is an infectious disease caused by plasmodium parasites that can be propagated through the bite of female mosquitos. According to WHO's latest World malaria report, an estimated malaria death of 435,000 occurs from 2015 to 2017. Microscopy examination, including stained thin and thick blood smears, is the gold standard for malaria diagnosis. Thick blood smears are used to detect the presence of malaria parasites, and thin blood smears are used to differentiate parasite species. Microscopy examination is of low cost and but is time-consuming and error-prone. Therefore, automatic parasite detection with high accuracy is of important clinical values. To this end, this paper proposes an automatic parasite detection algorithm based on Faster R-CNN, which can automatically detect small objects of malaria parasites. Based on public dataset, we compare our method with ERT and CNN in detection precision. Experimental results show that our method achieves an average precision of 94.61% in the test set.
A Systematic Review of Computational Thinking Approach for Programming Education in Higher Education Institutions

This study examined how computational thinking (CT) has been used to teach problem-solving skills and programming education in the recent past. This study specifically (i) identified articles that discussed CT approach for programming education at higher education institutions (HEIs), (ii) classified the different CT approaches and tools employed for programming education at HEIs, (iii) synthesised and discussed results that are reported by relevant studies that utilized CT for teaching programming at HEIs. A systematic literature review methodology was adopted in this study. Out of 161 articles retrieved, 33 of them that met the inclusion criteria were reviewed. Our study revealed that the use of CT at HEIs for programming education began in 2010; many studies did not specify the context of use, but the use of CT is found to be gaining grounds in many contexts, especially the developed countries; course design approach was mostly employed by educators to introduce CT at HEIs for programming education. Furthermore, this study pointed out how CT approach can be explored for designing a smart learning environment to support students in learning computer programming.
Preventing zero-day exploits of memory vulnerabilities with guard lines

Exploitable memory errors are pervasive due to the widespread use of unsafe programming languages, such as C and C++. Despite much research, techniques for detecting memory errors at runtime have seen limited adoption due to high performance overhead, incomplete memory safety, or non-trivial microarchitectural changes. This paper describes Guard Lines, a hardware / software memory error detector that detects common types of spatial and temporal memory errors at runtime without imposing a significant performance penalty (on average only 4%). Guard Lines provides memory safety by defining certain regions of memory as inaccessible "guards," which are created in software during memory allocation. If a program ever accesses guarded memory, the hardware raises an exception indicating a memory safety violation. Guard Lines requires minimal microarchitectural changes, and it uses a novel metadata design to efficiently track the guard locations. This paper describes the design, implementation, security analysis, and performance evaluation of Guard Lines and demonstrates its feasibility to protect real-world applications against exploitable memory vulnerabilities.
Obfuscation: where are we in anti-DSE protections? (a first attempt)

Obfuscation is widely used to protect software against man-at-the-end attacks. Recent attacks based on semantic methods, especially dynamic symbolic execution (DSE), have proven extremely powerful against standard obfuscation techniques, leading several teams to investigate anti-DSE protections. Yet, the domain is in its infancy, and the current state of research on the topic is quite unclear. We propose a systematic review of anti-DSE techniques. In particular, we propose a classification and identify strengths and weaknesses of the current lines of research, as well as promising future directions.
Oracle bone inscription detection: a survey of Oracle bone inscription detection based on deep learning algorithm

The goal of this paper is to serve as a guide for selecting a detection architecture for Oracle Bone Inscription (OBI) that achieves the right speed/memory/accuracy balance for a given platform. Many successful systems have been proposed in recent years, but directly migrating these methods to OBI data may lead to unsatisfying performance due to the corrosion, noise, and distribution. We present a unified implementation of the Faster R-CNN [1], SSD [2], YOLOv3 [3], RFBnet [4], and RefineDet [5] systems which we view as experiment architectures and trace out the speed/accuracy trade-off. The method with the best overall performance was selected as the baseline. Then a series of improvements were made according to the characteristics of the data. The experiment shows that our method reaches the F-measure of 80.1, nearly 2% higher than the baseline. Experimental data and algorithms will soon be available at http://jgw.aynu. edu.cn.
Jam Today, Jam Tomorrow

Game jams, which are game creation events in which developers design and build a game over a short period of time, have been shown to support participatory, active STEM learning. Game jams have expanded from their origins as physically co-located experiences and many are now conducted exclusively online. Though the co-located game jam has been noted as educational, little is known about how learning happens within online game jams. To better understand the ways online game jams support self-development, we interviewed fifteen online jam participants about their learning experiences during their jams. Additionally, we observed and analyzed several jams using activity theory. We found that online game jams support participants' learning through extensive feedback from others during and after the jam. Such feedback sessions were a key social and participatory learning elements for online jams, providing much-need social support. In contrast to the group-focused development in offline jams many participants in our study chose to develop games alone. Many individuals participated in online game jams regularly, treating them as a broader experience than singular events. We use these findings to discuss how we might better design for self-directed learning online and offer suggestions on how to better attune online game jams to the needs of participants.
In-Route Task Selection in Spatial Crowdsourcing

Consider a city’s road network and a worker who is traveling on a given path from a starting point s to a destination d (e.g., from school or work to home) in said network. Consider further that there is a set of tasks in the network available to be performed, where each such task takes a certain amount of time to be completed and yields a positive reward if completed, and, finally, that the worker is willing to deviate from his/her path as long as the travel time to the selected tasks plus the time taken for completing them does not exceed a given time budget. We call this problem the In-Route Task Selection (IRTS) problem and consider two variants thereof. In the first one, named IRTS-SP, we assume that the worker only specifies s and d and he/she wants to consider alternative paths that deviate (cost-wise) as little as possible from the cost of the shortest path connecting s and d. In the second variant, named IRTS-PP, we assume that the worker has a preferred path from s to d and wants to travel along that one path for as long as possible. The latter is practically relevant in cases where the worker has a path other than the shortest one that is more desirable for non-objective reasons, e.g., availability of public transit, bicycle-friendliness or perceived safety. Common to both variants though, we assume that the worker wants to maximize the rewards collected by completing tasks. Clearly, there are now two conflicting criteria for the worker to contemplate when considering which tasks to perform: minimizing path deviation and maximizing collected reward. In this context, we investigate both IRTS variants using the skyline paradigm in order to obtain the set of non-dominated solutions w.r. t. the tradeoffs between earned rewards and deviation from either the cost of the shortest path, in the case of IRTS-SP, or the actual preferred path, in the case of IRTS-PP. Returning the skyline set of solutions to workers is of practical interest as it empowers them, e.g., it allows them to decide, at query time, which tasks suit them better. We propose exact and heuristic approaches in order to solve both variants of the IRTS problem. Our experiments, using real city-scale datasets, show that while the exact approaches serve as benchmarks, they do not scale due to the NP-hardness of the problems. The overall best heuristic approach, on the other hand, can solve relatively large instances of the IRTS problems within practical query processing time, e.g., at par with less effective greedy heuristics, while still producing very good approximate skyline sets, e.g., often yielding less than 10% relative error w.r. t. the exact solution.
"Mothers as Candy Wrappers": Critical Infrastructure Supporting the Transition into Motherhood

The transition into motherhood is a complicated and often unsupported major life disruption. To alleviate mental health issues and to support identity re-negotiation, mothers are increasingly turning to online mothers' groups, particularly private and secret Facebook groups; these can provide a complex system of social, emotional, and practical support for new mothers. In this paper we present findings from an exploratory interview study of how new mothers create, find, use, and participate in ICTs, specifically online mothers' groups, to combat the lack of formal support systems by developing substitute networks. Utilizing a framework of critical infrastructures, we found that these online substitute networks were created by women, for women, in an effort to fill much needed social, political, and medical gaps that fail to see 'woman and mother' as a whole being, rather than simply as a 'discarded candy wrapper'. Our study contributes to the growing literature on ICT use by mothers for supporting and negotiating new identities, by illustrating how these infrastructures can be re-designed and appropriated in use, for critical utilization.
Imikode: A VR Game to Introduce OOP Concepts

This research paper presents Imikode, a virtual reality (VR)--based learning game to support the teaching and learning of object-oriented programming (OOP) concepts in computing education. The system was implemented using Google Cardboard SDK and works with any Cardboard compatible headset. The teacher can use Imikode to introduce OOP class in an immersive and engaging way. This early prototype provides basic features to help introduce OOP concepts. We aim at extending it using Artificial Intelligence (AI), by adding a conversational agent able to parse erroneous statements and provide adequate instructions on how to fix them.
Altruism and Wellbeing as Care Work in a Craft-based Maker Culture

This paper aims to examine motivations of participants for being involved in a crafts-based, women-only maker organization. Over a period of three months, we observed and interviewed ten women aged 42 - 78 to explore how they experienced being involved in knitting, sewing, crocheting, card making and other similar craft forms. Using the ethos of care as a lens to interpret our data, we found that our participants perceived making as an 'outlet' for them to perform activities that support their physical and mental wellbeing. Moreover, they perceived making as a tool to support others in need and help the larger community rather than a self-serving achievement. We also observed how the use of technology was inherent into their craft making activities that supported not only the making processes but also sharing these with others. Our findings highlight the 'care work' that goes into making in such a social setting that generally goes unnoticed when the focus is purely on instrumental and objective aspects of making. We believe that these findings will inform CSCW researchers to think about the not-so-visible qualities of making that elevate care (for self and for others), and to support these via the design of innovative technologies.