Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Driven Artificial Neural Network LSTM Hybrid Predictive Model Applied for International Stock Index Prediction

In this paper, a neural network long short term memory hybrid model focusing on stock index forecasting is modeled, presented, and investigated. This model is tuned by artificial intelligence, and neural networks in Python environment. Accordingly, it can perform the prediction with a high accuracy, and near to the real value. Four layers of input layer, hidden layer, attention layer, as well as the output layer set up the proposed hybrid model. The input data, and API-based server connection are performed in input layer. The hidden layer performs the calculations, and measurements. Price value forecasting, and prediction-train graphs done by the attention layer, and output layer, respectively. The proposed system conceptualized the effect of artificial intelligence (AI), and machine learning (ML) on financial markets. Finally, it is concluded this model can be utilized in other wide range of financial applications.
An Agile and Lean Process Model for Mobile App Development: Case Study into Austrian Industry

With recent advances in mobile technology, mobile devices have emerged from a luxury to a necessity in our daily lives. App development has been growing into a fast-paced market with volatile requirements. From a software developing point of view, responsive and adaptable software process models are advised to cope with such competitive markets. Over the last decade agile and lean methodologies have become very popular for software development in general, but there has only been limited research about the applicability of these methods in the area of mobile applications. This study aims to address the identified research gap and drafts a lean-agile process model that can compete with the requirements of today’s market. Our model ALP-mobile, an agile and lean process for mobile app development, combines elements of Scrum, Kanban and eXtreme Programming (XP). We drafted our model based on previous work and pilot interviews. We then presented it to multiple mobile-app-centric companies in Austria for an initial validation of strengths and weaknesses by industry experts. Our study shows large support and potential for our model among the interviewed experts calling for further increments and practical evaluation in future research.
Therapeutic Modulation of DNA Damage and Repair Mechanisms in Blood Cells

Hematopoietic stem cells (HSCs) are a rare population of pluripotent cells that predominantly reside in the bone marrow. Under the appropriate microenvironmental cues, HSCs can undergo self-renewal, expansion, and differentiation into all types of progenitor and terminally differentiated blood cells required for survival of the host (Figure 1). Due to the importance of this cell population for survival, protection of its genome from endogenous and exogenous genotoxic insults is a necessity. However, the intracellular molecular signaling network in hematopoietic cells that control surveillance of the genome as well as maintain genome stability is still largely unexplored. As more is learned regarding how these cells detect a genotoxic event and seek to repair the damaged nucleotides (i.e. DNA adducts), it will become even more feasible to design strategies to protect these life-sustaining cells when the host is exposed to a genotoxic event. Maintenance of genome stability in both the hematopoietic stem and progenitor cell (HSPC) populations is essential for the sustainment of normal hematopoiesis. For example, transient depletion of bone-marrow derived HSC induced by irradiation or chemotherapy can induce these primitive cells to expand so that the bone marrow can be fully reconstituted; blood-cell development can then continue with minimal disruption. However, once therapy-mediated DNA damage is too high, a DNA-damage threshold is reached resulting in subsequent cell death, myelosuppression, and if not treated, life-threatening bone-marrow failure (Figure 1). With the basal level of DNA repair relatively low in these cells, this does present a challenge to maintain normal hematopoiesis in individuals exposed to prolonged or high levels of genotoxic stress. The reduced ability to repair DNA damage in HSPCs that give rise to multiple mature blood-cell lineages can cause detrimental and long-lasting effects to the host resulting in abnormal cell function, cell death, cellular transformation, and eventually leukemogenesis (Figure 1). Numerous studies have shown that HSPCs are intrinsically more sensitive than other cell types and tissues mostly due to intrinsic limitations in DNA-repair capacity. Buschfort-Papewalis et al previously demonstrated that when human HSPCs (phenotypically defined as CD34+ cells) or differentiated cells (phenotypically defined as CD34cells) from the same donor were exposed to alkylating agents, an overall decrease in repair capacity of the more primitive CD34+ cells compared the more differentiated cells CD34cells was observed. When human CD34+ cells were exposed to a variety of chemotherapeutic drugs, single-strand DNA breaks as well as DNA adducts were found at higher levels and persisted for longer time periods than in CD34cells (Buschfort-Papewalis et al., 2002), providing evidence that the kinetics of DNA repair are slower overall in the
Inductive peaking in wideband CMOS current amplifiers

This paper presents several new inductive-peaking techniques for bandwidth enhancement of low-voltage CMOS current amplifiers. The techniques improve the bandwidth by utilizing the resonance characteristics of LC network by employing bond wire capacitance or on-chip spiral inductors. Both series-peaking and shunt-peaking techniques are considered. It shows that the shunt-peaking technique needs a lower peaking inductance. A novel negative current feedback mechanism is used to reduce the value of the series-peaking inductance at the cost of current gain. The proposed techniques do not affect the supply voltage and the DC biasing conditions. Theoretical analysis and simulation results demonstrate that the inductive peaking techniques increase the bandwidth significantly.
A Persistent Structured Hierarchical Overlay Network to Counter Intentional Churn Attack

The increased use of structured overlay network for a variety of applications has attracted a lot of attention from both research community and attackers. However, the structural constraints, open nature anybody can join and anybody may leave, and unreliability of its participant nodes significantly affect the performance of these applications and make it vulnerable to a variety of attacks such as eclipse, Sybil, and churn. One attack to compromise the service availability in overlay network is intentional churn join/leave attack, where a large number of malicious users will join and leave the overlay network so frequently that the entire structure collapses and becomes unavailable. The focus of this paper is to provide a new robust, efficient, and scalable hierarchical overlay architecture that will counter these attacks by providing a structure that can accommodate the fleeting behaviour of nodes without causing much structural inconsistencies. The performance evaluation showed that the proposed architecture has more failure resilience and self-organization as compared to chord based architecture. Experimental results have demonstrated that the effect of failures on an overlay is proportional to the size of failure.
An inhibitory compound produced by Pseudomonas with effectiveness on Vibrio harveyi

Persistence of the antivibrio property of the potential antagonistic probiotics, Pseudomonas MCCB 102 and 103, at diierent temperatures, pH and in organic solvents was studied. The antivibrio compound was extracted, puri¢ed and characterized using thin-layer chromatography, high-pressure liquid chromatography, liquid chromatography-mass spectroscopy, UV^Vis and nuclear magnetic resonance spectroscopy and identi¢ed as N-methyl-1-hydroxyphenazine, a phenazine antibiotic. The toxicity of the compound was tested in Penaeus monodon haemocyte culture and the IC50 value was found to be 1.4 0.31mg L 1 . The compound was found to be bacteriostatic at 0.5 mg L 1 . Its stability to varying temperature, pH, organic solvents, prolonged shelflife and vibriostatic nature point to its suitability for prophylatic aquaculture application.
4-Nitrophenol–2,4,6-triamino-1,3,5-triazine–water (2/1/1)

In the title adduct, 2C6H5NO3·C3H6N6·H2O, the melamine and the two independent nitrophenol molecules are essentially planar, with maximum deviations of 0.0294 (10), 0.0706 (12) and 0.0742 (12) Å, respectively. In the crystal, N—H⋯N, O—H⋯N, N—H⋯O and O—H⋯O hydrogen bonds link the components into a three-dimensional network. In addition, weak π–π interactions [centroid–centroid distances = 3.728 (3) and 3.749 (3) Å] are observed.
Depth Perception in Alzheimer's Disease

Abnormal depth perception contributes to visuospatial deficits in Alzheimer's disease. Disturbances in stereopsis, motion parallax, and the interpretation of static monocular depth cues may result from neuropathology in the visual cortex. We evaluated 15 patients with mild Alzheimer's disease and 15 controls matched for age, sex, and education on measures of local stereopsis (stereoscopic testing), global stereopsis (random dots), motion parallax (Howard-Dolman apparatus), and monocular depth perception by relative size, interposition, and perspective. Compared to controls, the patients were significantly impaired in over-all depth perception. This impairment was largely due to disturbances in local stereopsis and in the interpretation of depth from perspective, independent of other visuospatial functions. Patients with Alzheimer's disease have disturbed interpretation of monocular as well as binocular depth cues. This information could lead to optic interventions to improve their visual depth perception.
The design and validation of an early childhood STEM classroom observational protocol

Across K-12 education, there has been recent attention to the learning opportunities available to students in science, technology, engineering, and mathematics (STEM) learning. Early childhood education (ECE) has been excluded from this process. The scholarly literature contains good evidence for including science teaching and learning at the ECE level, however, little is currently known about how a STEM curriculum might best be implemented in the early years. Additionally, data collection tools specifically developed for ECE STEM are limited. In this paper, we outline the steps we have taken to design and validate a classroom observation protocol (COP) intended to capture aspects of STEM instruction in an early childhood setting and to help educators envision and adjust their own teaching practices. The detailed explanation of the development and validation of this data collection tool offers other educators and researchers a path for collecting evidence of STEM practices in their own classrooms and/or research environments.International Research in Early Childhood Education, vol. 6, no. 1, p. 24-37
Adaptive Finite Elements for Elliptic Optimization Problems with Control Constraints

In this paper we develop a posteriori error estimates for finite element discretization of elliptic optimization problems with pointwise inequality constraints on the control variable. We derive error estimators for assessing the discretization error with respect to the cost functional as well as with respect to a given quantity of interest. These error estimators provide quantitative information about the discretization error and guide an adaptive mesh refinement algorithm allowing for substantial saving in degrees of freedom. The behavior of the method is demonstrated on numerical examples.
Media Cultures and the Representation of Science in Korea and the United States: The BSE Case in 2008

In 2008 the Korean government decided to resume importing US beef, leading to a nationwide controversy over the risk of bovine spongiform encephalopathy (BSE), or mad cow disease. Korean media coverage of BSE during this controversy demonstrates how media reporting on scientific matters interacts with political controversy over science-related risks. In Korea, where media organizations tend to be associated with particular political ideologies, the media emphasized the uncertainty of scientific accounts in the BSE case and reinforced the politicization of science by selectively mobilizing contrasting scientific claims and scientific authorities based on each media outlet's political position. The distinctive role of such a media culture in the science-related political discourse is further highlighted when we consider US media coverage of BSE risk during the same period: in that coverage, the baseline technical risk-related issues were taken for granted and the BSE controversy in Korea was presented largely as a trade issue.
A literature review of state of-charge estimation techniques applicable to lithium poly-carbon monoflouride (LI/CFx) battery

Almost as long as rechargeable batteries have existed, systems able to give an indication about the state-of-charge (SoC) of a battery have been around. Several methods, including those of direct measurements, bookkeeping and adaptive systems are known in the art for determining the SoC of a cell or battery of cells. An accurate SoC determination method and an understandable and reliable SoC display to the user will improve the performance and reliability, and will ultimately lengthen the lifetime of the battery. However, many examples of poor accuracy and reliability can be found in practice. This review presents an overview on battery technology and the state-of-the-art of SoC methods. The goal of all the presented SoC indication methods is to design an SoC indication system capable of providing an accurate SoC indication under all realistic user conditions, including those of spread-in both battery and user behaviour, a large temperature and current range and ageing of the battery.
Intelligent Adaptive Backstepping Control System for Magnetic Levitation Apparatus

We propose an intelligent adaptive backstepping control system using a recurrent neural network (RNN) to control the mover position of a magnetic levitation apparatus to compensate for uncertainties, including friction force. First, we derive a dynamic model of the magnetic levitation apparatus. Then, we suggest an adaptive backstepping approach to compensate disturbances, including the friction force, occurring in the motion control system. To further increase the robustness of the magnetic levitation apparatus, we propose an RNN estimator for the required lumped uncertainty in the adaptive backstepping control system. We further propose an online parameter training methodology, derived by the gradient descent method, to increase the learning capability of the RNN. The effectiveness of the proposed control scheme has been verified by experiment. With the proposed adaptive backstepping control system using RNN, the mover position of the magnetic levitation apparatus possesses the advantages of good transient control performance and robustness to uncertainties for the tracking of periodic trajectories
Diagnostic classification of non-specific low back pain. A new system integrating patho-anatomic and clinical categories

Identifying relevant subgroups of nonspecific low back pain patients may improve research efficiency and clinical outcomes. This article presents available data supporting the rationale behind a new pathoanatomic oriented classification system for low back pain. A systematic framework was used to assess issues of validity, reliability, feasibility, and generalizability. Results from studies examining elements of the 12 categories of the classification system are presented to allow the assessment to be made. Particular emphasis has been given to the evidence of diagnostic accuracy of the criteria based on data from history taking and clinical tests. The classification system was found to be potentially useful for research purposes. Further testing of the classification system is required.
Unsupervised Classifiers, Mutual Information and 'Phantom Targets'

We derive criteria for training adaptive classifier networks to perform unsupervised data analysis. The first criterion turns a simple Gaussian classifier into a simple Gaussian mixture analyser. The second criterion, which is much more generally applicable, is based on mutual information. It simplifies to an intuitively reasonable difference between two entropy functions, one encouraging 'decisiveness,' the other 'fairness' to the alternative interpretations of the input. This 'firm but fair' criterion can be applied to any network that produces probability-type outputs, but it does not necessarily lead to useful behavior.
Teaching and Learning Styles

Are teachers ‘‘born’’ or ‘‘made? ’’ This is a fundamental question that hints at the frustration felt by most teachers at some point in time. The joy of a learner’s success will strengthen our commitment to teaching, but we must also deal with the disappointment of a student’s failure. Most of us have suffered repeated interactions with ‘‘problem’’ students, many have failed to gain recognition as good teachers, and some clinicians have tried to teach and left disappointed, complaining that they are not good teachers. Few educators, if any, can be considered great ‘‘natural’’ teachers without room for improvement. In academic medicine, are ‘‘good’’ teachers to be found and treasured, or taught and encouraged? Teaching is a skill, similar to all the other skills that we learn in life. Grounded in knowledge, the application of teaching involves an understanding of what ‘‘teaching’’ is, knowledge of the subject, and how to effectively communicate with the learner. As with any skill, teaching requires practice, constructive feedback, and reflection to lead to improvement. Unfortunately, teaching in medicine is often an afterthought. Skills required for teaching are typically not part of medical school or postgraduate curriculum. Most physicians entering academic medicine try to emulate those whom they consider good teachers, but imitation rarely results in long-term success.
Motion estimation using segmented Gibbs-modeled vector fields

The approach described in this paper improves block-based motion estimation and compensation by introduction of a block segmentation dividing each block into two parts. For each block a segmentation pattern is derived from the motion vectors, which circumvents the transmission of the segmentation as side information. Motion vectors are estimated for both parts of a block. Although the number of motion vectors increases, the coding overhead can be kept sufficiently low by incorporating a Gibbs-criterion into the motion estimation criterion to trade off coding rate versus prediction error.
K-CV parameter optimization method in the application of SVM classification data

The SVM can realize data classification and prediction, the selection of penalty parameter c and kernel function g in training models directly affect the forecasting accuracy of the classification, the article use the K-CV method for c, g parameters optimization and processing, in wine species identification as an example to predict classification, improves the forecast accuracy, has reached the expected prediction effect.
Analyzing and applying agent oriented programming methods for teaching purposes

In this thesis we discuss ways to improve teaching methods for agent oriented programming. The research approach consists of several steps. First data is gathered from groups of students participating in a first year agent programming project that uses the Unreal Tournament 2004 environment. The stronger and weaker groups are analyzed in a qualitative way to establish differences in programming styles between the stronger groups and weaker groups. The focus of the analysis is on software quality and code constructs. This analysis establishes what the key success factors of the stronger groups are. The results of this analysis are applied while developing the HactarV2 agent system for the Multi-Agent Programming Contest together with other students. During the Unreal Tournament project we found that stronger groups spend more time and energy on testing than weaker groups. It was also established that they pay more attention to documentation, software quality factors and the style of their code. Finally a code pattern similar to the Strategy design pattern showed up much more often with the stronger groups than with the weaker groups. When these methods were applied during the Multi-Agent Programming Contest project it was established that some of the documentation methods do not work as intended and that code style sometimes has to be sacrificed for the sake of efficiency. On the other hand the use of testing was proven again and the use of the code pattern turned out to work better than expected. The fact that the HactarV2 team won the Programming Contest is a clear indication that these methods work. The conjecture of this thesis is that the quality of an agent system can be improved by the right approach to testing and documentation during the development and by applying code patterns that make behavioral control easier. Teaching these approaches and patterns to students will improve their skill level of agent-based programming.
Neuropsychological dysfunction in antipsychotic-naive first-episode unipolar psychotic depression.

OBJECTIVE The profile of neuropsychological impairment associated with unipolar psychotic depression remains unclear. The authors used a neuropsychological test battery to characterize the neuropsychiatric profile of patients with unipolar psychotic depression, relative to that of patients with nonpsychotic unipolar depression, patients with schizophrenia, and healthy comparison subjects. METHOD Study subjects included antipsychotic-naive patients with a first episode of psychotic unipolar depression (N=20), antipsychotic-naive and unmedicated patients with nonpsychotic unipolar depression (N=14), antipsychotic-naive patients with first-episode schizophrenia (N=86), and healthy volunteers (N=81). Groups were matched on age, sex, race, education, parental socioeconomic status, and estimated premorbid intelligence. Psychotic patients were followed clinically for 2 years to confirm diagnosis. All participants completed a standard neuropsychological battery, including tests of general intelligence, executive function, attention, verbal memory, motor skills, and visual-spatial perception. RESULTS Patients with psychotic depression had a pattern of neuropsychological dysfunction that was similar to but less severe than that of patients with schizophrenia. In contrast, patients with nonpsychotic unipolar depression had a neuropsychological profile that was similar to that of healthy individuals but that included mild dysfunction on tests of attention. Neuropsychological test performance was generally independent of acute clinical symptoms, but some pairwise group differences were attenuated by covariation for symptom severity. CONCLUSIONS The similar neuropsychological profiles for schizophrenia and psychotic depression suggest that these psychotic disorders may have common pathophysiological features. The dramatic differences in performance between the patients with psychotic depression and those with nonpsychotic depression point to a marked distinction in neurocognitive function associated with the expression of psychosis in depressed patients.