Miracle-dz/UniFAR-FTUs huggingface dataset:
Fungal pathogens of Proteaceae

Species of Leucadendron, Leucospermum and Protea (Proteaceae) are in high demand for the international floriculture market due to their brightly coloured and textured flowers or bracts. Fungal pathogens, however, create a serious problem in cultivating flawless blooms. The aim of the present study was to characterise several of these pathogens using morphology, culture characteristics, and DNA sequence data of the rRNA-ITS and LSU genes. In some cases additional genes such as TEF 1-α and CHS were also sequenced. Based on the results of this study, several novel species and genera are described. Brunneosphaerella leaf blight is shown to be caused by three species, namely B. jonkershoekensis on Protea repens, B. nitidae sp. nov. on Protea nitida and B. protearum on a wide host range of Protea spp. (South Africa). Coniothyrium-like species associated with Coniothyrium leaf spot are allocated to other genera, namely Curreya grandicipis on Protea grandiceps, and Microsphaeropsis proteae on P. nitida (South Africa). Diaporthe leucospermi is described on Leucospermum sp. (Australia), and Diplodina microsperma newly reported on Protea sp. (New Zealand). Pyrenophora blight is caused by a novel species, Pyrenophora leucospermi, and not Drechslera biseptata or D. dematoidea as previously reported. Fusicladium proteae is described on Protea sp. (South Africa), Pestalotiopsis protearum on Leucospermum cuneiforme (Zimbabwe), Ramularia vizellae and R. stellenboschensis on Protea spp. (South Africa), and Teratosphaeria capensis on Protea spp. (Portugal, South Africa). Aureobasidium leaf spot is shown to be caused by two species, namely A. proteae comb. nov. on Protea spp. (South Africa), and A. leucospermi sp. nov. on Leucospermum spp. (Indonesia, Portugal, South Africa). Novel genera and species elucidated in this study include Gordonomyces mucovaginatus and Pseudopassalora gouriqua (hyphomycetes), and Xenoconiothyrium catenata (coelomycete), all on Protea spp. (South Africa).
Medical Augmented Reality based on Commercial Image Guided Surgery

Utilizing augmented reality for applications in medicine has been a topic of intense research for several years. A number of challenging tasks need to be addressed when designing a medical AR system. These include the import and management of medical datasets and preoperatively created planning data, the registration of the patient with respect to a global coordinate system, and accurate tracking of the camera used in the AR setup as well as the respective surgical instruments. Most research systems rely on specialized hardware or algorithms for realizing augmented reality in medicine. Such base technologies can be expensive or very time-consuming to implement. In this paper, we propose an alternative approach of building a surgical AR system by harnessing existing, commercially available equipment for image guided surgery (IGS). We describe the prototype of an augmented reality application, which receives all necessary information from a device for intraoperative navigation.
A novel neuroscience-inspired architecture: For computer vision applications

The theory behind deep learning, the human visual system was investigated and general principles of how it functions are extracted. Our finding is that there are neuroscience theories that are not utilized in deep learning. Therefore, in this work, a novel model utilizing some of those theories is developed. The new model addresses the parallel nature of the human brain compared to the hierarchal (serial) brain model that is followed by current deep learning systems. The validation of the proposed model was conducted using "Shape" feature dimension. The results show up to 2% accuracy rate compared to our implementation of DeepFace, a high performing face recognition algorithm that was developed by Facebook, is achieved under the same hardware/ software conditions; and we were able to speed up the training up to 21% per a training patch compared to DeepFace.
Steroidogenesis-related gene expression in the rat ovary exposed to melatonin supplementation

OBJECTIVE: To analyze steroidogenesis-related gene expression in the rat ovary exposed to melatonin supplementation. METHODS: Thirty-two virgin adult female rats were randomized to two groups as follows: the control group GI received vehicle and the experimental group GII received melatonin supplementation (10 µg/night per animal) for 60 consecutive days. After the treatment, animals were anesthetized and the collected ovaries were immediately placed in liquid nitrogen for complementary deoxyribonucleic acid microarray analyses. A GeneChip® Kit Rat Genome 230 2.0 Affymetrix Array was used for gene analysis and the experiment was repeated three times for each group. The results were normalized with the GeneChip® Operating Software program and confirmed through analysis with the secondary deoxyribonucleic acid-Chip Analyzer (dChip) software. The data were confirmed by real-time reverse transcription polymerase chain reaction analysis. Genes related to ovarian function were further confirmed by immunohistochemistry. RESULTS: We found the upregulation of the type 9 adenylate cyclase and inhibin beta B genes and the downregulation of the cyclic adenosine monophosphate response element modulator and cytochrome P450 family 17a1 genes in the ovarian tissue of GII compared to those of the control group. CONCLUSION: Our data suggest that melatonin supplementation decreases gene expression of cyclic adenosine monophosphate, which changes ovarian steroidogenesis.
Influence of level of motion on perceived video quality in MPEG-2 coding

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.
Exploitation, Violence, and Suicide Risk Among Child and Adolescent Survivors of Human Trafficking in the Greater Mekong Subregion.

IMPORTANCE Human trafficking and exploitation of children have profound health consequences. To our knowledge, this study represents the largest survey on the health of child and adolescent survivors of human trafficking. OBJECTIVE To describe experiences of abuse and exploitation, mental health outcomes, and suicidal behavior among children and adolescents in posttrafficking services. We also examine how exposures to violence, exploitation, and abuse affect the mental health and suicidal behavior of trafficked children. DESIGN, SETTING, AND PARTICIPANTS A survey was conducted with 387 children and adolescents aged 10 to 17 years in posttrafficking services in Cambodia, Thailand, or Vietnam, which along with Laos, Myanmar, and Yunnan Province, China, compose the Greater Mekong Subregion. Participants were interviewed within 2 weeks of entering services from October 2011 through May 2013. MAIN OUTCOMES AND MEASURES Depression, posttraumatic stress disorder, anxiety, suicidal ideation, self-injury, and suicide attempts. RESULTS Among the 387 children and adolescent study participants, most (82%) were female. Twelve percent had tried to harm or kill themselves in the month before the interview. Fifty-six percent screened positive for depression, 33% for an anxiety disorder, and 26% for posttraumatic stress disorder. Abuse at home was reported by 20%. Physical violence while trafficked was reported by 41% of boys and 19% of girls. Twenty-three percent of girls and 1 boy reported sexual violence. Mental health symptoms were strongly associated with recent self-harm and suicide attempts. Severe physical violence was associated with depression (adjusted odds ratio [AOR], 3.55; 95% CI, 1.64-7.71), anxiety (AOR, 2.13; 95% CI, 1.12-4.05), and suicidal ideation (AOR, 3.68; 95% CI, 1.77-7.67). Sexual violence while trafficked was associated with depression (AOR, 2.27; 95% CI, 1.22-4.23) and suicidal ideation (AOR, 3.43; 95% CI, 1.80-6.54). CONCLUSIONS AND RELEVANCE Children and adolescents in posttrafficking care showed high symptom levels of depression, anxiety, and posttraumatic stress disorder, which are strongly associated with self-harm or suicidal behaviors. Mental health screening and reintegration risk assessments are critical components of posttrafficking services, especially in planning for family reunification and other social integration options.
A Component Model and Infrastructure for a Fluid Web

The Web is evolving from a space for publication/consumption of documents to an environment for collaborative work, where digital content can travel and be replicated, adapted, decomposed, fusioned, and transformed. We call this the fluid Web perspective. This view requires a thorough revision of the typical document-oriented approach that permeates content management on the Web. This paper presents our solution for the Fluid Web, which allows moving from the document-oriented to a content-oriented perspective, where "content" can be any digital object. The solution is based on two axes: a self-descriptive unit to encapsulate any kind of content artifact - the digital content component (DCC) and a fluid Web infrastructure that provides management and deployment of DCCs through the Web, and whose goal is to support collaboration on the Web. Designed to be reused and adapted, DCCs encapsulate data and software using a single structure, thus allowing homogeneous composition and processing of any digital content, executable or not. These properties are exploited by our fluid Web infrastructure, which supports DCC multilevel annotation and discovery mechanisms, configuration management, and version control. Our work extensively explores taxonomic ontologies and semantic Web standards, which serve as a semantic bridge, unifying DCC management vocabularies, and improving DCC description/indexing/discovery. DCCs and infrastructure have been implemented and are illustrated by means of a running example, for a scientific application
Bounded vector signatures and their applications

Although malleability is undesirable in traditional digital signatures, schemes with limited malleability properties enable interesting functionalities that may be impossible to obtain otherwise (e.g., homomorphic signatures). In this paper, we introduce a new malleable signature scheme called bounded vector signatures. The proposed scheme allows a user to sign a multi-dimensional vector of values, along with a description of the context within which the vector should be interpreted. The scheme includes a unique malleability property, which we refer to as the stretch property, that allows the components of the signed vector to be increased up to a pre-defined limit without access to the signing key. Decreasing these values, however, remains computationally infeasible. We prove the security of our construction under the strong RSA and decisional Diffie-Hellman assumptions in the random oracle model. Finally, we underscore the utility of bounded vector signatures by discussing their use in distributed systems security applications.
Cointegration and Market Integration: An Application to the Potato Markets in Rural West Bengal, India

The paper attempts to examine the market integration with the help of cointegration test on the prices of potato of Hooghly district in West Bengal. The analysis has been made at two levels, namely at the level of wholesale markets and at the retail markets. The cointegration test by Johansen and Jeselius (1990) applied to weekly prices of three important potato markets in Hooghly district suggest that the markets are integrated. Our results revealed that price signals and information are transmitted smoothly across the markets. These results have important policy implications. In a situation when potato markets are spatially integrated the government may think of reducing or even withdrawing its efforts to influence the price in the market. The finding of the market integration appears to be quite significant for the success of price policy and market liberalisation programs undertaken in India.
Implementing Real-Time Optimization Models: A Case Application From The Motor Carrier Industry

Online models for real-time operations planning face a host of implementation issues that do not arise in more strategic arenas. We use the seemingly simple problem of assigning drivers to loads in the truckload motor carrier industry as an instance to study the issues that arise in the process of implementing a real-time dispatch system. Although the project was moderately successful, our focus is not on documenting the benefits, but rather on summarizing the challenges that arose. The most significant theme running through the implementation hurdles we encountered was the lack of information available to the model. Computers are very good at processing vast quantities of information; humans are very good at challenging the information that is in the computer and augmenting computer-provided data with head knowledge. Our study includes a careful comparison of actual decisions with model recommendations, using a six-month database of actual transactions. This comparison is the first we have seen of its kind and provides the most rigorous evaluation of an online dispatch model that we have seen. Although the model was well used, the results demonstrate that significant improvements could have been obtained if the level of model utilization had been even higher.
Exploiting Uniform Assignments in First-Order MPE

The MPE (Most Probable Explanation) query plays an important role in probabilistic inference. MPE solution algorithms for probabilistic relational models essentially adapt existing belief assessment method, replacing summation with maximization. But the rich structure and symmetries captured by relational models together with the properties of the maximization operator offer an opportunity for additional simplification with potentially significant computational ramifications. Specifically, these models often have groups of variables that define symmetric distributions over some population of formulas. The maximizing choice for different elements of this group is the same. If we can realize this ahead of time, we can significantly reduce the size of the model by eliminating a potentially significant portion of random variables. This paper defines the notion of uniformly assigned and partially uniformly assigned sets of variables, shows how one can recognize these sets efficiently, and how the model can be greatly simplified once we recognize them, with little computational effort. We demonstrate the effectiveness of these ideas empirically on a number of models.
Inquiry-based requirements analysis

This approach emphasizes pinpointing where and when information needs occur; at its core is the inquiry cycle model, a structure for describing and supporting discussions about system requirements. The authors use a case study to describe the model's conversation metaphor, which follows analysis activities from requirements elicitation and documentation through refinement. <<ETX>>
Modeling and Parameter Identification of Harmonic Drive Systems

The unique performance features of harmonic drives, such as high gear ratios and high torque capacities in a compact geometry, justify their widespreaa industrial application. However, harmonic drive can exhibit surprisingly more complex dynamic behavior than conventional gear transmission. In this paper a systematic way to capture and rationalize the dynamic behavior of the harmonic drive systems is developed. Simple and accurate models for compliance, hysteresis, and friction are proposed, and the model parameters are estimated using least-squares approximation for linear and nonlinear regression models. A statistical measure of variation is defined, by which the reliability of the estimated parameter for different operating condition, as well as the accuracy and integrity of the proposed model is quantified. By these means, it is shown that a linear stiffness model best captures the behavior of the system when combined with a good model for hysteresis. Moreover, the frictional losses of harmonic drive are modeled at both low and high velocities, The model performance is assessed by comparing simulations with the experimental results on two different harmonic drives. Finally, the significance of individual components of the nonlinear model is assessed by a parameter sensitivity study using simulations.
Analyzing network reliability with imperfect nodes using OBDD

The nodes as well as the links may fail in a real network. Almost all the existing tree-based partitioning algorithms are inefficient in finding the disjoint paths in a large network even if all the nodes are perfect. The number of disjoint paths will increase dramatically if a network has imperfect nodes. In this paper, strategies based on edge expansion diagram using OBDD are proposed to efficiently evaluate the reliability of a network with imperfect nodes. The fixed sink algorithm is proposed to further speed up the process for k-terminal networks. The essential variable is also defined to help us identify the most critical part of the network. Our methods are better than previous numeric algorithms and have two significant results. First, it takes only about 65 seconds to identify the essential variable for a 2/sup 99/-path network on a SPARC 20 with 128 MB of memory. Second, the overhead due to considering imperfect nodes is as low as 0.2% in average for seven st3/spl times/n networks, where n = 13, 14,. , 19.
The State of Molecular Biomarkers for the Early Detection of Lung Cancer

Using biomarkers to select the most at-risk population, to detect the disease while measurable and yet not clinically apparent has been the goal of many investigations. Recent advances in molecular strategies and analytic platforms, including genomics, epigenomics, proteomics, and metabolomics, have identified increasing numbers of potential biomarkers in the blood, urine, exhaled breath condensate, bronchial specimens, saliva, and sputum, but none have yet moved to the clinical setting. Therefore, there is a recognized gap between the promise and the product delivery in the cancer biomarker field. In this review, we define clinical contexts where risk and diagnostic biomarkers may have use in the management of lung cancer, identify the most relevant candidate biomarkers of early detection, provide their state of development, and finally discuss critical aspects of study design in molecular biomarkers for early detection of lung cancer. Cancer Prev Res; 5(8); 992–1006. ©2012 AACR.
Adoption of Mobile ERP in Traditional-ERP Organizations: The Effect of Computer Self-Efficacy

The objective of this research-in-progress paper is to investigate the employees’ intention to use mobile ERP under the effect of computer self-efficacy in regular-ERP firms. Mobile ERP, business software that integrates core business functions into a single system, has been increasingly penetrating the ERP market but to the best of our knowledge there is no study has examined its usage intention among traditionalERP organizations. The updated DeLone and MacLean IS success model with its three quality factors is employed in this study as a theoretical framework. Conclusion and potential contribution are discussed.
Probabilistic Tree Automata

The purpose of this paper is meant to be three-fold. First it will introduce the reader to the concepts of Probabilistic Languages and Probabilistic Grammars. Second, it indicates that previous definitions of probabilistic finite automaton have always been restricted to 1 of 8 classes of automaton and shows that other classes are useful. Third, the probabilistic concept is extended from finite automata to higher level automata (such as probabilistic PDAs and probabilistic Turing automata). A specific application of this theory is given in the development of Probabilistic Tree Automata. Theorems concerning these automata and operations on them are presented. It is indicated that this type of automaton is relevant because it characterizes Probabilistic Context Free Languages. The results are taken from the author's PhD Thesis.4
Analysis of Channel Coding in Fading Channels for MIMO Systems

ireless communication systems are being designed to integrate features that include high data rates as well as high quality of service in the existing communication framework. For this an orthogonal space-time block code (OSTBC) technique improves error performance of synchronous data links without sacrificing data rate or requiring more bandwidth. Trellis coded modulation (TCM) enables efficient transmission scheme and to achieve high coding gain by integrating coding and modulation. In this work an OSTBC concatenated with TCM is implemented for information transmission over different antenna configurations, from Single-Input Single-Output (SISO) to Multi-Input Multi- Output (MIMO) channels. The channel used is a quasi-static Rayleigh fading channel with additive white Gaussian noise (AWGN). The proposed model takes the advantages of the concatenation scheme: the spatial diversity gain offered by OSTBC and the coding gain offered by TCM. Using MATLAB Simulink the system performance is compared with using only TCM or OSTBC and TCM concatenated with OSTBC. Significant performance improvement of the system is achieved using this scheme. The proposed scheme achieved full transmits diversity and coding gain of more than 2dB without using interleavers/deinterleavers. It is observed that performance of MIMO system is better than SISO or MISO (Multi-Input Single- Output) system.
Left ventricular dysfunction in the haemodialysis population

Cardiovascular disease in the haemodialysis population continues to contribute to mortality and morbidity. Disorders of left ventricular geometry and function are highly prevalent and lead to increased mortality in this highly vulnerable population. Left ventricular dysfunction (LVDys), often as a result of hypertension, ischaemic cardiac disease or dilated cardiomyopathy, has not been uniformly defined in the literature making diagnosis and therapy problematic. Although routinely available, screening by echocardiography is critically volume dependent and prone to underestimation in left ventricular ejection fraction. Few randomized control trials are available to guide management with the majority of evidence requiring extrapolation from the non-dialysis population. Beyond medication, interventional cardiac procedures such as implantable cardiac defibrillator implantation and cardiac resynchronization therapy show promise. Conversion to alternative dialysis modalities such as peritoneal dialysis, short-daily or nocturnal dialysis have been attempted and are actively being explored.
Reformulation of macroscopic transport models based on the moments of the scattering integral [semiconductor device modeling applications]

We present a formulation of non-parabolic macroscopic transport models which avoids the commonly used relaxation time approximation by using an expansion of the scattering integral into the odd moments of the distribution function. The parameters of this expansion and the other closure relations are directly calculated via analytical models of the distribution function. We compare models of order four and six to demonstrate the substantially improved accuracy of the six moments description over the conventional four moments energy-transport formalism.