Miracle-dz/UniFAR-FTUs huggingface dataset:
Children in distress : a guide for screening children's art

The authors have developed a simple, one-page art screening form for use with the "human figure drawing" (HFD) and the "kinetic family drawing" (KFD), which has brought a standardization to the interview of these children and the interpretation of their art. This is invaluable to front-line clinicians, private practitioners, trauma centers, child protective services, and the legal system.
Modern Rescue Missions: A Survey of the International Union of Gospel Missions

While the skid-row rescue mission has been an institution for over a century, modern missions are experiencing many changes. We conducted a survey of the International Union of Gospel Missions, the largest organization of missions in the United States. Missions still relied almost exclusively on private, individual contributions though some missions accepted state, federal, and United Way funds. The missions continued to offer “soap, sleep, soup, and salvation,” but they also offered medical care, psychological counseling, vocational training, benefits counseling, and alcoholism treatment. Most missions required attendance at a religious service to receive service including alcoholism treatment. About half of the missions had alcoholism treatment programs. Most of the programs used psychological counseling, but some programs also offered vocational training and Alcoholics Anonymous. Most of the programs were professionally staffed. The programs emphasized spiritual conversion as the key to successful rehabilitation. Many missions were serving new populations.
The Effect of GSM Mobile Phone Electromagnetic Field on Femur Fracture Healing in a Rat Model

1 Ali Murat Kalender1, Uğur Göktaş2, Davut Özbağ3, Cemil Ertürk4, Mehmet Okumuş5, Savaş Güner6, Mehmet Akif Altay4, Ahmet Ün7 1Ortopedi ve Travmatoloji Ana Bilim Dalı, Kahramanmaraş Sütçü İmam Üniversitesi Tıp Fakültesi, 2Kahramanmaraş, Anestezi ve Reanimasyon Ana Bilim Dalı, Yüzüncü Yıl Üniversitesi Tıp Fakültesi, Van, 3Anatomi Ana Bilim Dalı, Kahramanmaraş Sütçü İmam Üniversitesi Tıp Fakültesi, Kahramanmaraş, 4Ortopedi ve Travmatoloji Ana Bilim Dalı Harran Üniversitesi Tıp Fakültesi, Şanlıurfa, 5Acil Tıp Ana Bilim Dalı, Kahramanmaraş Sütçü İmam Üniversitesi Tıp Fakültesi, Kahramanmaraş, 6Ortopedi ve Travmatoloji Ana Bilim Dalı, Yüzüncü Yıl Üniversitesi Tıp Fakültesi, Van, 7Ortadoğu Sağlık Merkezi Hastanesi Şanlıurfa, Türkiye Cep telefonunun Kırık İyileşmesine Etkisi / The Effect of Mobile Phone on Fracture Healing The Effect of GSM Mobile Phone Electromagnetic Field on Femur Fracture Healing in a Rat Model
Formal Specification of AML

In our work we present a formal specification of Agent Modeling Language (AML), which was defined in PhD thesis wrote by R. Červenka. It provides precise and unambiguous description of AML, which can help in better understanding of the language, opening the door to its wider applicability and further improvements. We also show how to formally specify an abstract multi-agent system (MAS) by means of the concepts of AML. This part demonstrates and proves well-formedness of the used concepts and provides a basis for further research in the area of MAS theories and formal specification of agent-based systems.
Characterization and Provenance of Building Materials from the Roman Pier at San Cataldo (Lecce, Southern Apulia, Italy): a Lithostratigraphical and Micropaleonthological Approach

This study deals with the characterization of building materials used in a monumental pier of Roman age, located at San Cataldo, the main coastal harbour of the Roman town of Lupiae, modern Lecce (Southern Italy). In the manufacture of the outer curtains three different lithologies have been recognized, all comprised in Pietra Leccese Formation, which crops out in a broad geographical area of Salento Peninsula. Microfossils recovered from limestone blocks are used to suggest a provenance for the source-rock. Microfossils include planktonic foraminifera characteristic of the upper Miocene (Tortonian-Messinian) foraminiferal MMi11 (Neogloboquadrina acostaensis Biozone) and MMi13 (Globorotalia miotumida Biozone) biozones. The analysed lithic materials show biostratigraphical characteristics very similar to some samples from Acaya-Struda zone (some 10 km South-West from the ancient harbour): comparative analysis has been performed, supporting a clear identification of the geological origin of limestone blocks. In hydraulic concrete different lithic materials have been used and mixed with a strong mortar. Macroscopic field observation clearly define that limestone clasts, variable in size, derive from the Pliocene Uggiano la Chiesa Formation, that widely crops out locally at San Cataldo; granular fractions of mortar probably derive from beaches and/or sandy dunes, available in the surrounding area, as well.
Fault estimation algorithms: design and verification

The research in this thesis is undertaken by observing that modern systems are becoming more and more complex and safety-critical due to the increasing requirements on system smartness and autonomy, and as a result health monitoring system needs to be developed to meet the requirements on system safety and reliability. The state-of-the-art approaches to monitoring system status are model based Fault Diagnosis (FD) systems, which can fuse the advantages of system physical modelling and sensors' characteristics. A number of model based FD approaches have been proposed. The conventional residual based approaches by monitoring system output estimation errors, however, may have certain limitations such as complex diagnosis logic for fault isolation, less sensitiveness to system faults and high computation load. More importantly, little attention has been paid to the problem of fault diagnosis system verification which answers the question that under what condition (i.e., level of uncertainties) a fault diagnosis system is valid. To this end, this thesis investigates the design and verification of fault diagnosis algorithms. It first highlights the differences between two popular FD approaches (i.e., residual based and fault estimation based) through a case study. On this basis, a set of uncertainty estimation algorithms are proposed to generate fault estimates according to different specifications after interpreting the FD problem as an uncertainty estimation problem. Then FD algorithm verification and threshold selection are investigated considering that there are always some mismatches between the real plant and the mathematical model used for FD observer design. Reachability analysis is drawn to evaluate the effect of uncertainties and faults such that it can be quantitatively verified under what condition a FD algorithm is valid. First the proposed fault estimation algorithms in this thesis, on the one hand, extend the existing approaches by pooling the available prior information such that performance can be enhanced, and on the other hand relax the existence condition and reduce the computation load by exploiting the reduced order observer structure. Second, the proposed framework for fault diagnosis system verification bridges the gap between academia and industry since on the one hand a given FD algorithm can be verified under what condition it is effective, and on the other hand different FD algorithms can be compared and selected for different application scenarios. It should be highlighted that although the algorithm design and verification are for fault diagnosis systems, they can also be applied for other systems such as disturbance rejection control system among many others.
Precision without Precisions: Handling uncertainty with a single predictive model

The predictive processing theory of cognition and neural encoding dictates that hierarchical regions in the neocortex learn and encode predictive hypotheses of current and future stimuli. To better handle uncertainty these regions must also learn, infer, and encode the precision of stimuli. In this treatment we investigate the potential of handling uncertainty within a single learned predictive model. We exploit the rich predictive models formed by the learning of temporal sequences within a Hierarchical Temporal Memory (HTM) framework, a cortically inspired connectionist system of self-organizing predictive cells. We weight a cell’s feedforward response by the degree of its own temporal expectations of a response. We test this model on data that has been saturated with temporal or spatial noise, and show significant improvements over traditional HTM systems. In addition we perform an experiment based on the Posner cuing task and show that the system displays phenomena consistent with attention and biased competition. We conclude that the observed effects are similar to those of precision encoding.
Efficacy and Safety of Agents in IgA Nephropathy: An Update Network Meta-Analysis

Background/Aims: The present network meta-analysis of randomized controlled trials (RCTs) was to explore the efficacy and safety of different pharmacologic interventions in IgA nephropathy with proteinuria more than 0.75 g/d. Methods: We systematically searched the Cochrane Library, Embase, and PubMed database for studies compared the rate of clinical remission and/or serious adverse events in IgA nephropathy patients with proteinuria (> 0.75 g/d) up to August 1, 2018. We ranked the comparative effects of all drugs against placebo on the surface under the cumulative ranking area (SUCRA) probabilities. Results: There were 29 RCTs comprising 2517 participants included for the comparisons of 9 interventions. The rank of the most effective treatments for inducing clinical remission was renin-angiotensin system inhibitors (RASi) in combination with steroid, tonsillectomy combined with steroid pulse therapy, and azathioprine plus RASi with SUCRA of 82.9%, 80.5%, and 67.6%, respectively. RASi in combination with steroid (SUCRA 3.9%) was the most effective in prevention of end-stage renal disease or doubling serum creatinine, followed by RASi monotherapy (SUCRA 38.4%) and azathioprine combined with steroid (SUCRA 49.0%). As for the occurrence of serious adverse events, azathioprine combined with RASi (SUCRA 88.0%) and steroid plus RASi (SUCRA 74.6%) showed the first and second highest incidence of adverse events, respectively. Conclusion: RASi combined with steroid demonstrated the most effective therapeutic approach for IgA nephropathy patients in terms of reducing proteinuria and stabilizing renal function.
Single Channel Speech Enhancement Using Spectral Subtraction Based on Minimum Statistics

Speech is an elementary source of human interaction. The quality and intelligibility of speech signals during communication are generally degraded by the surrounding noise. Corrupted speech signals need therefore to be enhanced to improve quality and intelligibility. In the field of speech processing, much effort has been devoted to develop speech enhancement techniques in order to restore the speech signal by reducing the amount of disturbing noise. This thesis focuses on a single channel speech enhancement technique that performs noise reduction by spectral subtraction based on minimum statistics. Minimum statistics means that the power spectrum of the non-stationary noise signal is estimated by finding the minimum values of a smoothed power spectrum of the noisy speech signal and, thus, circumvents the speech activity detection problem. The performance of the spectral subtraction method is evaluated using single channel speech data and for a wide range of noise types with various noise levels. This evaluation is used in order to find optimum method parameter values, thereby improving this algorithm to make it more appropriate for speech communication purposes. The system is implemented in MATLAB and validated by considering different performance measure and for different Signal to Noise Ratio Improvement (SNRI) and Spectral Distortion (SD). The SNRI and SD were calculated for different filter bank settings such as different number of subbands and for different decimation and interpolation ratios. The method provides efficient speech enhancement in terms of SNRI and SD performance measures.
A kindergarten experiment in linguistic e-learning

As part of the Blasq project, we are developing a set of linguistic games to be used in kindergartens. The ﬁ rst of these games is Crazipes, that we are currently testing in a Danish kindergarten, with the support of the local teachers. Here we discuss the architecture of the game, its potentials as a linguistic e-learning tool, together with the design and methodology adopted for the study. Some early results are also discussed.
Tree: a knowledge-based system for generating images of trees

This thesis deals with the design and implementation of a knowledge based system for generating a variety of tree images. Since it is meant to be used in a highly interactive design setting, the system must produce convincing images at high speed. It also has to allow the user effective and convenient parametric manipulation of generated trees. To speed up the process of tree generation, the Direct Image Synthesis approach is introduced. This approach saves considerable amounts of time in bypassing the modeling phase of commonly used object based approaches. As it operates upon images and not 3D objects, the Direct Image Synthesis approach encourages the application of rule based principles of depiction analogous to those used by a painter. These depiction techniques prove to be an efficient alternative to computationally expensive rendering techniques in computer graphics. The model uses Structured Recursion for construction of the tree image to make the modeling process more intuitive. Structured Recursion enables functional differentiation between the Trunk, Bough, Branch and the $Twig$ which are considered the principal elements in perception of a tree. This differentiation makes possible the implementation of Top-Down (perceptual) modeling process and strengthens the model's ability to depict a variety of species. The hierarchical structure of the model, which is conceptualized after the principles of abstraction in painting, follows directly from the application of Structured Recursion. The parameters of the model encode those characteristics of a tree that define its form, texture and color. They are meant to be readily understood and to allow easy and versatile manipulation of the tree image. The thesis includes an in depth discussion on the definition and behavior of each parameter as well as on the relationship and the nature of dependency among them. The Chapter "Setting the Parameters to Generate Types of Trees" discusses the patterns of manipulating the tree image by gradual adjustment of parameter values and presents a series of tree images accompanied by the tables of their parameter values. Preliminary research on methods to express distance in the composition of tree images has been undertaken. Leonardo da Vinci's rules from the Perspective of Disappearance and the Aerial Perspective are applied to the model. A comparative assessment of the Object Based and Image Processing Approach is also performed.
On the use of electro-magnetic midsagittal articulometer (EMMA) systems

An overview of electro-magnetic midsagittal articulometry is presented, with emphasis on the use of a system we developed at MIT. The text is based on the voice-over from a videotape that was prepared for a special session of the Acoustical Society of America. An overview of the development of the technique and principles of operation is followed by a description of preparing for and running an experiment. Controls for assuring accuracy of the data are described, and examples of analysis techniques and extracted data are presented
Information extraction for Chinese free text based on pattern match combine with heuristic information

Describes an approach to information extraction for Chinese free text. An automatic learning algorithm of pattern rules for Chinese free text and employment of heuristic information are described. The method that combines pattern rule matching with heuristic information is utilized to perform the information extraction task. Experimental results have proved this method to be effective in improving the extraction result in complex situations and increasing recall noticeably.
Deep learning architecture for recognition of abnormal activities

The video surveillance is one of the key areas in computer vision researches. The scientific challenge in this field involves the implementation of automatic systems to obtain detailed information about individuals and groups behaviors. In particular, the detection of abnormal movements of groups or individuals requires a fine analysis of frames in the video stream. In this article, we propose a new method to detect anomalies in crowded scenes. We try to categorize the video in a supervised mode accompanied by unsupervised learning using the principle of the autoencoder. In order to construct an informative concept for the recognition of these behaviors, we use a technique of representation based on the superposition of human silhouettes. The evaluation of the UMN dataset demonstrates the effectiveness of the proposed approach.
Gaze-Driven Design Insights to Amplify Debugging Skills: A Learner-Centered Analysis Approach

This study investigates how multimodal user-generated data can be used to reinforce learner reflection, improve teaching practices, and close the learning analytics loop. In particular, the aim of the study is to utilize user gaze and action-based data to examine the role of a mirroring tool (i.e., Exercise View in Eclipse) in orchestrating basic behavioural regulation during debugging. The results demonstrated that students who processed the information presented in the Exercise View and acted upon it, improved their performance and achieved a higher level of success than those who failed to do so. The findings shed light on what constitutes relevant data within a particular learning context in programming using gaze patterns. Moreover, these findings could guide the collection of essential learner-centred analytics for designing usable, modular learning environments based on data-driven approaches.
A Reinforcement Learning-Based Trust Model for Cluster Size Adjustment Scheme in Distributed Cognitive Radio Networks

Cognitive radio enables secondary users (SUs) to explore and exploit the underutilized licensed channels (or white spaces) owned by the primary users. To improve the network scalability, the SUs are organized into clusters. This article proposes a novel artificial intelligence-based trust model approach that uses reinforcement learning (RL) to improve traditional budget-based cluster size adjustment schemes. The RL-based trust model enables the clusterhead to observe and learn about the behaviors of its SU member nodes, and revoke the membership of malicious SUs in order to ameliorate the effects of intelligent and collaborative attacks, while adjusting the cluster size dynamically according to the availability of white spaces. The malicious SUs launch attacks on clusterheads causing the cluster size to become inappropriately sized while learning to remain undetected. In any attack and defense scenario, both the attackers and the clusterhead adopt RL approaches. Simulation results have shown that the single-agent RL (SARL) attackers have caused the cluster size to reduce significantly; while the SARL clusterhead has slightly helped increase its cluster size, and this motivates a rule-based approach to efficiently counterattack. Multi-agent RL attacks have shown to be less effective in an operating environment that is dynamic.
Testing strategies to reduce morbidity and mortality from Lynch syndrome

Abstract Objective: Lynch syndrome (LS) has an autosomal dominant inheritance pattern and is associated with increased risk for colorectal cancer (CRC) and other cancers. Various strategies are used to identify patients at risk and offer surveillance and preventive programs, the cost effectiveness of which is much dependent on the prevalence of LS in a population. Universal testing (UT) is proposed as an effective measure, targeting all newly diagnosed CRC patients under a certain age. Materials and methods: LS cases were identified in a cohort of 572 consecutive CRC patients. Immunohistochemistry was performed in 539 cases, using antibodies against mismatch repair proteins MLH1, PMS2, MSH2, and MSH6. Microsatellite instability and gene mutation screening were performed in 57 cases. Results: In total 11 pathogenic variants were detected, identifying LS in 1.9% of new CRC cases. Comparing the results with current clinical methods, 2 pathogenic variants were found with Amsterdam criteria and 9 when using either Bethesda guidelines or our institution’s prior clinical criteria. Pathogenic variants in MSH6 were the most common in our series. We also found different outcomes using different age cut offs. Conclusion: Our study demonstrates that UT of tumors before age on onset at 75 years would most likely be cost-efficient and essentially equivalent to applying the Bethesda guidelines or our institution’s prior clinical criteria on all new CRC.
Playing with Being in Digital Asia: Gamic Orientalism and the Virtual Dōjō

Seeking to address the general question, ‘Where is Digital Asia? ’, this paper explores the various ways in which the digital and virtual realm interacts with the problematic and contested category of Asia. Beginning with a discussion of the relationship between Asia and Digital Asia, as both cartographic and ideological sites, it moves on to connect Digital Asia with the discourse of techno-Orientalism. Using the example of the videogame as an instance of a digital location that can be visited and explored, this article suggests that the gamic quality of interactivity adds a new, experiential dimension to the ideological structure of (techno-)Orientalism, hence positing the utility of a new form of ‘Gamic Orientalism’. Focussing on the ‘digital dōjō’ as the site of Gamic Orientalism and Digital Asia par excellence, this paper concludes with a discussion of the ways in which gamers represent their engagement with this site in a manner that echoes the way martial artists talk about the significance of their art as self-cultivation. Illustrated with texts from the bushidō canon and interviews with gamers, this playful and experimental piece posits the possibility of ‘virtual bushidō’ as the ultimate expression of Gamic Orientalism, suggesting that Digital Asia is finally located in an ideologically conditioned mode of engagement with the digital medium rather than in any cartographically defined space.
Research for Cold-Start Problem in Network-Based Recommendation Algorithm

Network-based recommendation algorithm presents a good recommended result in many aspects. The algorithm is also facing the problem of cold-start. This paper proposes a solution for cold-start problem which makes use of an algorithm based on items similarity to calculate the similarity between the new item and other items in the system, and then link the new item to the user-item matrix. Finally the new items can be recommended to users by the network-based recommendation algorithm what the traditional network-based recommendation algorithm can't do. Therefore, the problem is solved on certain degree.
The Design of Rijndael: AES - The Advanced Encryption Standard

This book, by the designers of the block cipher, presents Rijndael from scratch. The underlying mathematics and the wide trail strategy as the basic design idea are explained in detail and the basics of differential and linear cryptanalysis are reworked. Subsequent chapters review all known attacks against the Rijndael structure and deal with implementation and optimization issues. In addition, other ciphers related to Rijndael are presented.