Miracle-dz/UniFAR-FTUs huggingface dataset:
Belief Updating and Paranoia in Individuals with Schizophrenia.

BACKGROUND Persecutory delusions are among the most common delusions in schizophrenia and represent the extreme end of the paranoia continuum. Paranoia is accompanied by significant worry and distress. Identifying cognitive mechanisms underlying paranoia is critical for advancing treatment. We hypothesized that aberrant belief updating, which is related to paranoia in human and animal models, would also contribute to persecutory beliefs in individuals with schizophrenia. METHODS Belief updating was assessed in 42 schizophrenia and 44 healthy participants, using a 3-option probabilistic reversal learning (3-PRL) task. Hierarchical Gaussian filter (HGF) was used to estimate computational parameters of belief updating. Paranoia was measured using the Positive and Negative Syndrome Scale (PANSS) and the revised Green et al. Paranoid Thoughts Scale (R-GPTS). Unusual thought content was measured with the Psychosis Symptom Rating Scale (PSYRATS) and the Peters et al. Delusions Inventory (PDI-21). Worry was measured using the Dunn Worry Questionnaire. RESULTS Paranoia was significantly associated with elevated win-switch rate and prior on volatility in both schizophrenia and across the whole sample. These relationships were specific to paranoia and did not extend to unusual thought content or measures of anxiety. Intriguingly, we observed a significant indirect effect of paranoia on the relationship between prior beliefs about volatility and worry. CONCLUSIONS This work provides evidence that relationships between belief updating parameters and paranoia extend to schizophrenia, may be specific to persecutory beliefs, and contribute to theoretical models implicating worry in the maintenance of persecutory delusions.
Unit and Ubiquitous Internet of Things

Although the Internet of Things (IoT) will play a key role in the development of next generation information, network, and communication technologies, many are still unclear about what makes IoT different from similar concepts.Answering fundamental questions about IoT architectures and models, Unit and Ubiquitous Internet of Things introduces essential IoT concepts from the perspectives of mapping and interaction between the physical world and the cyber world. It addresses key issues such as strategy and education, particularly around unit and ubiquitous IoT technologies. Supplying a new perspective on IoT, the book covers emerging trends and presents the latest progress in the field. It also: Outlines a fundamental architecture for future IoT together with the IoT layered model Describes various topological structures, existence forms, and corresponding logical relationships Establishes an IoT technology system based on the knowledge of IoT scientific problems Provides an overview of the core technologies, including basic connotation, development status, and open challenges The book examines ubiquitous sensing, networking, and communications, as well as information management involved in unit IoT. It describes global IoT applications and includes coverage of ubiquitous, local, industrial, national, and transnational IoT. Presenting detailed case studies that illustrate various application scenarios, the text considers the main IoT supporting technologies including resource management, loop control in actuation, session management, space-time consistency, security and privacy, energy management, spectrum management, nanotechnology, quantum technology, and big data.
Temperature and current density distribution in a bimetallic conductor through a coupled model

In this paper, we analyze theoretically the conduction heat transfer that results from an alternating electrical current that flows continuously in an aluminum conductor steel reinforced (ACSR), taking into account that the electrical resistivity is a linear function of temperature. This effect, necessarily produce a situation that forces us to analyze simultaneously the electrical and thermal effects in both materials. In this way we obtain a thermo-electric model. In this way, and by simultaneous numerical solution of Maxwell's equations and heat diffusion equation, it is possible to determine both the current density distribution and the temperature gradients during its transient state. Also, we show the influence of the steel core on the current density and temperature distributions. The results are presented in dimensionless form, in order to reduce the number of physical variables involved. In particular, we show the influence of the skin effect and the variation of the resistivity with temperature on current density and temperature gradients. The above shows that the electrical operation of the networks is subject to several factors that may make more difficult the full utilization of electrical transport.
EVALUATION OF A GAMIFICATION METHODOLOGY IN HIGHER EDUCATION

The gamification neologism is applied to using game-thinking and game mechanics to solve problems and to engage audiences. In the previous year we applied the concept in the context of the Higher Education, in the course of computer science. We used several game design mechanisms in several aspects of the learning process. A reward mechanism was central to the gamification approach, providing automatic classification of students and constant and up-to-date feedback of their progress within the course. Each chapter of the course’s content was mapped to a level, in a total of five. The student had to complete all the levels to be able to succeed in the course. Each level provided three difficult levels, which the student could choose and, according to this choice, adopt a classification grade. Several learning experiences were designed. Centered in the student, the learning experiences were designed to be active, meaningful, with social meaning, integrative, and diversified, giving the student the main learning role. The inherent increase in complexity demands the integration of different dimensions of knowledge, better achieved through diversified strategies. In this sense, we designed traditional practical assignment exercises in parallel with educational games, including card games, board games, tabletop role-playing games and quizzes.
Machine noise monitoring and fault diagnosis based on blind signal processing

On the basis of introducing the unified model of blind signal processing (BSP), the typical BSP algorithms were comprehensively concluded, and the present research status of BSP in machine noise monitoring and fault diagnosis was summarized. Those were emphatically discussed, such as mixed models, blind source separation and blind deconvolution of mechanical noise, blind source separation combined with other technologies and machine noise monitoring and diagnosis system based on BSP. Finally, the further main research problems were pointed out.
Rebonds: Structural Affordances, Negotiation, and Creation

This paper presents a comparative recording analysis of the seminal work for solo percussion Rebonds (Iannis Xenakis, 1989), in order to demonstrate how performances of a musical work can reveal—or even create—aspects of musical structure that score-centered analysis cannot illuminate. In doing so I engage with the following questions. What does a pluralistic, dynamic conception of structure look like for Rebonds? How do interpretive decisions recast performers as agents of musical structure? When performances diverge from the score in the omission of notes, the softening of accents, the insertion of dramatic tempo changes, or the altering of entire passages, do conventions that arise out of those performance practices become part of the structural fabric of the work? Are these conventions thus part of the Rebonds “text”?
Facilitators and Barriers of Mother Engagement in a Home-based Parenting Program Following Concerns of Child Maltreatment

The current study aimed to explore mothers’ perceptions of facilitators and barriers to engagement in the HoPES program, an intensive home-visiting intervention for families with young children identified as having child maltreatment concerns. Seven mothers who had participated in the program participated in semi-structured interviews about their experiences. Thematic analysis was conducted using NVivo Version 12. Themes relating to facilitators of engagement included the following: (1) clinician behaviours; (2) treatment relevance/acceptability; (3) strong therapeutic relationship; (4) mothers’ cognitions and beliefs about treatment and (5) program delivery. Themes relating to barriers to engagement included the following: (1) contextual/external barriers to treatment; (2) treatment relevance/acceptability; (3) mothers’ cognitions and beliefs about treatment and (4) program processes. This study highlights the important role which services and clinicians have in engaging parents at risk of child maltreatment. Specifically, the prioritisation of the therapeutic relationship through all intervention processes, and the utilisation of strength-based approaches, may facilitate engagement.
Evaluation Framework for Algorithms Segmenting Short Axis Cardiac MRI.

The motivation of the segmentation challenge is to quantitatively analyze global and regional cardiac function from cine magnetic resonance (MR) images, clinical parameters such as ejection fraction (EF), left ventricle myocardium mass (MM), and stroke volume (SV) are required. Calculations of these parameters depend upon accurate delineation of endocardial and epicardial contours of the left ventricle (LV). Manual delineation is time-consuming and tedious and has high inter-observer variability. Thus, fully automatic LV segmentation is desirable.The automatic segmentation of the LV in cine MR typically faces four challenges: 1) the overlap between the intensity distributions within the cardiac regions; 2) the lack of edge information; 3) the shape variability of the endocardial and epicardial contours across slices and phases; and 4) the inter-subject variability of these factors. A number of methods have been proposed for (semi-) automatic LV segmentation, including using a probability atlas [1], dynamic programming [2-3], fuzzy clustering [4], a deformable model [5], an active appearance model [6], a variational and level set [7-10], graph cuts [11-12] and an image-driven approach [13]. For a complete review of recent literature describing cardiac segmentation techniques, see [14]. Although the segmentation results have improved, accurate LV segmentation is still acknowledged as a difficult problem.The goals of this contest are to compare LV segmentation methods by providing an evaluation system, and a database of images and expert contours. Comparing segmentation results across research studies can be difficult due to unspecified differences in the method or implementation of evaluation metrics. This contest will provide open-source code for contour evaluation. Furthermore, the database will provide a set of images such that confounding segmentation differences due to image quality or pathology could be eliminated.
Intraventricular Meningiomas: Clinical-Pathological and Genetic Features of a Monocentric Series

Intraventricular meningiomas (IVMs) are rare (0.5–5%) and usually low-grade (90% grade I) brain neoplasms. Their recurrence rate is lower than that of extra-axial meningiomas, but their surgical resection can be burdened with life-threatening complications, which represent the major cause of the reported 4% mortality. The aim of this study is to characterize the molecular portrait of IVMs to identify potential therapeutic targets. For this, we explored mutations and copy number variations (CNV) of 409 cancer-related genes and tumor mutational burden (TMB) of six cases, using next-generation sequencing. Five IVMs were grade I and one was grade II; none recurred, in spite of partial surgical resection in one case. NF2 mutation was the only recurring alteration and was present in three of the six IVMs, in association with SMARCB1 mutation in one case. None of the cases was hypermutated (TMB > 10 mutations/Mb). NF2-mutant progressing or recurring IVMs could potentially be treated with targeted therapies applied to other NF2-mutant tumors, as an alternative to surgery or radiosurgery, while in view of their low TMB they are unlikely candidates to immune check-point inhibition.
Epigenetic targeting of transposon relics: beating the dead horses of the genome?

ABSTRACT Transposable elements (TEs) have been seen as selfish genetic elements that can propagate in a host genome. Their propagation success is however hindered by a combination of mechanisms such as mutations, selection, and their epigenetic silencing by the host genome. As a result, most copies of TEs in a given genome are dead relics: their sequence is too degenerated to allow any transposition. Nevertheless, these TE relics often, but not always, remain epigenetically silenced, and if not to prevent transposition anymore, one can wonder the reason for this phenomenon. The mere self-perpetuating loop inherent to epigenetic silencing could alone explain that even when inactive, TE copies remain silenced. Beyond this process, nevertheless, antagonistic selective forces are likely to act on TE relic silencing. Especially, without the benefit of preventing transposition, TE relic silencing may prove deleterious to the host fitness, suggesting that the maintenance of TE relic silencing is the result of a fine, and perhaps case-by-case, evolutionary trade-off between beneficial and deleterious effects. Ultimately, the release of TE relics silencing may provide a ‘safe’ ground for adaptive epimutations to arise. In this review, we provide an overview of these questions in both plants and animals.
Maximising Evaluation Influence in an International Development Donor Agency

This article examines how current theories of evaluation use and evaluation influence can assist an international development donor agency, namely the Australian Agency for International Development (AusAID), maximise the outcomes and track the consequences of evaluations of its country programs. It considers those theories most relevant to AusAID's evaluation interests and contexts, that is: instrumental use; conceptual (or enlightenment) use; process use; and evaluation influence. It finds that evaluation influence has much to offer in terms of linking evaluation outcomes to the achievement of program outcomes. By considering the mechanisms that can mediate evaluation influence, the framework underpinning evaluation influence theory builds on many of the central tenets identified in evaluation use theories and encourages the consideration of an evaluation as an intervention in itself. The principal benefit of doing so is to understand when, and why, some use of evaluation occurs and when and why it does not. Evaluation influence theory holds the potential for AusAID to maximise its evaluation efforts and strengthen its country programs. The systematic consideration of which mechanisms can influence the intermediate and long-term outcomes that lead to social betterment is the key to realising this potential. Empirical research into these mechanisms could both assist and be assisted by AusAID embracing an approach of valuing evaluations as an intervention in themselves.
Predicition Of Compressive Strength In Light-Weight Self-Compacting Concrete By ANFIS Analytical Model

Abstract Light-weight Self-Compacting Concrete (LWSCC) might be the answer to the increasing construction requirements of slenderer and more heavily reinforced structural elements. However there are limited studies to prove its ability in real construction projects. In conjunction with the traditional methods, artificial intelligent based modeling methods have been applied to simulate the non-linear and complex behavior of concrete in the recent years. Twenty one laboratory experimental investigations on the mechanical properties of LWSCC; published in recent 12 years have been analyzed in this study. The collected information is used to investigate the relationship between compressive strength, elasticity modulus and splitting tensile strength in LWSCC. Analytically proposed model in ANFIS is verified by multi factor linear regression analysis. Comparing the estimated results, ANFIS analysis gives more compatible results and is preferred to estimate the properties of LWSCC.
Factors Influencing Beekeeping Practices in Sikonge, Tanzania

Introduction Beekeeping is a common rural based economic activity in the world (Abebe, 2007; Adgaba et al., 2014; Bekuma, 2018) and has long been practised primarily for gathering honey which is an important bee product in many societies (Lee, 2014). Recently, great potential of beekeeping has been recognized as it is not only the source of honey but also other important bee products. These include bee wax, bee venom and bee pollen (Tutuba & Vanhaverbeke, 2018). Beekeeping has been greatly acknowledged to have functions such as improving environment and as an alternative source of improving people’s livelihood (John, 2014). Beekeeping has gradually evolved from traditional to commercial practice. Thus, commercialized beekeeping is viewed to be an economic occupation involving application of new innovation and improved technologies in management of honey bee colonies, apiary management, forage, production and product management (Tutuba & Vanhaverbeke, 2018). Beekeeping is more than honey hunting; rather it is the modern art and science of managing honey bees for receiving their commercial potential (Abebe, 2007; Sharma & Das, 2018; Tutuba & Vanhaverbeke, 2018). It is still claimed that the sector has not received enough attention in many tropical developing countries (Adgaba et al., 2014; Bekuma, 2018). Tropical developing countries have great potential for beekeeping because of having many bee colonies. In addition, the tropical areas are endowed with massive forests, which produce forage for honey bees to produce good quality and large quantity of honey. However, both good quality and quantity of honey is affected by the level of technology such as innovation in apiary setting, proper management of beehives and production process (Bett, 2017).
Attitude Estimation of a Quadcopter with one fully damaged rotor using on-board MARG Sensors

Quadcopters are becoming increasingly popular across diverse sectors. Since rotor damages occur frequently, it is essential to improve the attitude estimation and thus ultimately the ability to control a damaged quadcopter. This research is based on a state-of-the-art method that makes it possible to control the quadcopter despite the total failure of a single rotor, where the attitude and position of the quadcopter are provided by an external system. In the present research, a novel attitude estimator called Adaptive Fuzzy Complementary Kalman Filter (AFCKF) has been developed and validated that works independently of any external systems. It is able to estimate the attitude of a quadcopter with one fully damaged rotor while only relying on the on-board MARG (Magnetometer, Accelerometer, Rate Gyroscope) sensors. The AFCKF provides significantly better attitude estimates for flights with a damaged rotor than mainstream filters, estimating the roll and pitch of the quadcopter with an RMS error of less than 1.7 degrees and a variance of less than 2 degrees. The proposed filter also provides accurate yaw estimates despite the fast spinning motion of the damaged quadcopter, and thus outperforms existing methods at the cost of only a small increase in computation.
A hybrid approach to medical decision-making: diagnosis of heart disease with machine-learning model

Heart disease is one of the most widely spreading and deadliest diseases across the world. In this study, we have proposed hybrid model for heart disease prediction by employing random forest and support vector machine. With random forest, iterative feature elimination is carried out to select heart disease features that improves predictive outcome of support vector machine for heart disease prediction. Experiment is conducted on the proposed model using test set and the experimental result evidently appears to prove that the performance of the proposed hybrid model is better as compared to an individual random forest and support vector machine. Overall, we have developed more accurate and computationally efficient model for heart disease prediction with accuracy of 98.3%. Moreover, experiment is conducted to analyze the effect of regularization parameter (C) and gamma on the performance of support vector machine. The experimental result evidently reveals that support vector machine is very sensitive to C and gamma.
Technological Process Applied for the Coating the Pipe Profiles in the Manufacturing Industry

This paper deals with the specific technological process applied for the powder coating the pipe profiles as a part of interior, exterior and design manufacturing materials. In the introduction and first chapter of the paper, the main characteristics, possibilities, benefits and deficiencies of this progressive coating technology utilization applied in the manufacturing industry are described. The main part of the paper specifies the whole technological process related to the pipe profiles coating, contains the design of the specialized equipment (hanging hook) for hanging the pipe profiles on the beam and presents the sample calculation of the coating consumption for the specific metal element. This equipment was constructed and practically verified by the authors in real manufacturing environment. In conclusion, the possible applications of this coating technology for structurally similar materials are emphasized. The aim of the powder coating technology utilization simultaneously with using the proposed hanging equipment is to apply the coating specifically to those parts where it is desirable. This leads to reduction of the overall capital and operating costs and increasing the efficiency of the manufacturing process. In addition, the coating technology is considered to be environmentally friendly due to recyclability of the redundant coating.
Wafer-Scale Fabrication of Silicon Nanocones via Controlling Catalyst Evolution in All-Wet Metal-Assisted Chemical Etching

All-wet metal-assisted chemical etching (MACE) is a simple and low-cost method to fabricate one-dimensional Si nanostructures. However, it remains a challenge to fabricate Si nanocones (SiNCs) with this method. Here, we achieved wafer-scale fabrication of SiNC arrays through an all-wet MACE process. The key to fabricate SiNCs is to control the catalyst evolution from deposition to etching stages. Different from conventional MACE processes, large-size Ag particles by solution deposition are obtained through increasing AgNO3 concentration or extending the reaction time in the seed solution. Then, the large-size Ag particles are simultaneously etched during the Si etching process in an etching solution with a high H2O2 concentration due to the accelerated cathode process and inhibited anode process in Ag/Si microscopic galvanic cells. The successive decrease of Ag particle sizes causes the proportionate increase of diameters of the etched Si nanostructures, forming SiNC arrays. The SiNC arrays exhibit a stronger light-trapping ability and better photoelectrochemical performance compared with Si nanowire arrays. SiNCs were fabricated by using n-type 1–10 Ω cm Si(100) wafers in this work. Though the specific experimental conditions for preparing SiNCs may differ when using different Si wafers, the summarized diagram will still provide valuable guidance for morphology control of Si nanostructures in MACE processes.