Miracle-dz/UniFAR-FTUs huggingface dataset:
Processing EEG signals for Clinical Interpretation in Seizure-Suspected Patients

Epilepsy is one of the most common neurological disorders, affecting around 1 in 200 of the population. However, identifying epilepsy can be difficult because seizures tend to be relatively infrequent events and an electroencephalogram (EEG) does not always show abnormalities. The aim of this project is to develop a new methods that could improve the diagnosis of epilepsy, leading to earlier treatment and to a better quality of life for epileptic patients. The above methods must be composed with a flexible hardware development in order to discriminate noise and had signals from correct EEG, MEG (Magnetoencephalogram) and Eye Image recognition. Even if there are EEG signal classifiers, it is suitable to perform a correct signal processing according to particular clinical reference, that is, it is difficult to have a classifier for all circumstances but it is possible to adapt EEG processing on current patient. This paper deals with a new approach of developing an architecture with a an embedded coding included in a framework agreement between University and IRCCS "E. Medea".
Towards Practical and Near-Optimal Coflow Scheduling for Data Center Networks

In current data centers, an application (e.g., MapReduce, Dryad, search platform, etc.) usually generates a group of parallel flows to complete a job. These flows compose a coflow and only completing them all is meaningful to the application. Accordingly, minimizing the average Coflow Completion Time (CCT) becomes a critical objective of flow scheduling. However, achieving this goal in today's Data Center Networks (DCNs) is quite challenging, not only because the schedule problem is theoretically NP-hard, but also because it is tough to perform practical flow scheduling in large-scale DCNs. In this paper, we find that minimizing the average CCT of a set of coflows is equivalent to the well-known problem of minimizing the sum of completion times in a concurrent open shop. As there are abundant existing solutions for concurrent open shop, we open up a variety of techniques for coflow scheduling. Inspired by the best known result, we derive a 2-approximation algorithm for coflow scheduling, and further develop a decentralized coflow scheduling system, D-CAS, which avoids the system problems associated with current centralized proposals while addressing the performance challenges of decentralized suggestions. Trace-driven simulations indicate that D-CAS achieves a performance close to Varys, the state-of-the-art centralized method, and outperforms Baraat, the only existing decentralized method, significantly.
Mesenchymal stem cell-like properties of CD133+ glioblastoma initiating cells

Glioblastoma is composed of dividing tumor cells, stromal cells and tumor initiating CD133+ cells. Recent reports have discussed the origin of the glioblastoma CD133+ cells and their function in the tumor microenvironment. The present work sought to investigate the multipotent and mesenchymal properties of primary highly purified human CD133+ glioblastoma-initiating cells. To accomplish this aim, we used the following approaches: i) generation of tumor subspheres of CD133+ selected cells from primary cell cultures of glioblastoma; ii) analysis of the expression of pluripotency stem cell markers and mesenchymal stem cell (MSC) markers in the CD133+ glioblastoma-initiating cells; iii) side-by-side ultrastructural characterization of the CD133+ glioblastoma cells, MSC and CD133+ hematopoietic stem cells isolated from human umbilical cord blood (UCB); iv) assessment of adipogenic differentiation of CD133+ glioblastoma cells to test their MSC-like in vitro differentiation ability; and v) use of an orthotopic glioblastoma xenograft model in the absence of immune suppression. We found that the CD133+ glioblastoma cells expressed both the pluripotency stem cell markers (Nanog, Mush-1 and SSEA-3) and MSC markers. In addition, the CD133+ cells were able to differentiate into adipocyte-like cells. Transmission electron microscopy (TEM) demonstrated that the CD133+ glioblastoma-initiating cells had ultrastructural features similar to those of undifferentiated MSCs. In addition, when administered in vivo to non-immunocompromised animals, the CD133+ cells were also able to mimic the phenotype of the original patient's tumor. In summary, we showed that the CD133+ glioblastoma cells express molecular signatures of MSCs, neural stem cells and pluripotent stem cells, thus possibly enabling differentiation into both neural and mesodermal cell types.
A Genetic Algorithm-Based Approach for Building Accurate Decision Trees

In dealing with a very large data set, it might be impractical to construct a decision tree using all of the points. Even when it is possible, this might not be the best way to utilize the data. As an alternative, subsets of the original data set can be extracted, a tree can be constructed on each subset, and then parts of individual trees can be combined in a smart way to produce an improved final set of feasible trees or a final tree. In this paper, we take trees generated by a commercial decision tree package, namely, C4.5, and allow them to crossover and mutate (using a genetic algorithm) for a number of generations in order to yield trees of better quality. We conduct a computational study of our approach using a real-life marketing data set. In this study, we divide the data set into training, scoring, and test sets, and find that our approach produces uniformly high-quality decision trees. In addition, we investigate the impact of scaling and demonstrate that our approach can be used effectively on very large data sets.
A Population-Based 16-Year Study on the Risk Factors of Surgical Site Infection in Patients after Bone Grafting

AbstractBone grafting is a commonly used orthopedic surgical procedure that will provide bone formation in bone defects or regions of defective bone healing. A major complication following bone grafting is a postoperative recipient graft site infection that is associated with substantial mortality and increased use of medical resources. The purpose of the study was to identify the risk factors associated with infection after bone-grafting surgery.Data from 1,303,347 patients listed in the Taiwan National Health Insurance Research Database (NHIRD) and admitted to hospitals from 1997 through 2012 who underwent primary bone grafting (mean age: 46.57 years old; mean length of hospital stay: 8.04 days) were analyzed. The incidence of infection by age, hospital stay, gender, income, chronic disease (tuberculosis [TB]; diabetes mellitus [DM]; acquired immunodeficiency syndrome [AIDS]), fracture complications (nonunion; delayed union fracture), types of graft and hospital was evaluated.Three percent of the patients developed a postoperative recipient graft site infection. Multivariable analysis revealed that patients were more likely to develop a post bone-grafting surgery infection if they were older, had a longer hospital stay, were male, had a lower income, or had comorbid TB, DM, or AIDS. Patients were more likely to develop an infection if they had a nonunion, an alloplast graft, or treated in a local clinic.Our findings should provide a clinically relevant reference for surgeons who perform bone grafting. Patients should be informed of the potential risks.
Hierarchical Abstraction of Phase Response Curves of Synchronized Systems of Coupled Oscillators

We prove that a group of injection-locked oscillators, each modelled using a nonlinear phase macromodel, responds as a single oscillator to small external perturbations. More precisely, we show that any group of injection-locked oscillators has a single effective PRC [1] or PPV [2], [3] that characterises its phase/timing response to small external perturbations. This result constitutes a foundation for understanding and predicting synchronization/timing hierarchically in large, complex systems that arise in nature and engineering.
Human limb segmentation in depth maps based on spatio-temporal Graph-cuts optimization

We present a framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs. First, from a set of random depth features, Random Forest is used to infer a set of label probabilities for each data sample. This vector of probabilities is used as unary term in α-β swap Graph-cuts algorithm. Moreover, depth values of spatio-temporal neighboring data points are used as boundary potentials. Results on a new multi-label human depth data set show high performance in terms of segmentation overlapping of the novel methodology compared to classical approaches.
Random walks on graphs to model saliency in images

We formulate the problem of salient region detection in images as Markov random walks performed on images represented as graphs. While the global properties of the image are extracted from the random walk on a complete graph, the local properties are extracted from a k-regular graph. The most salient node is selected as the one which is globally most isolated but falls on a compact object. The equilibrium hitting times of the ergodic Markov chain holds the key for identifying the most salient node. The background nodes which are farthest from the most salient node are also identified based on the hitting times calculated from the random walk. Finally, a seeded salient region identification mechanism is developed to identify the salient parts of the image. The robustness of the proposed algorithm is objectively demonstrated with experiments carried out on a large image database annotated with “ground-truth” salient regions.
Y Chromosome Haplogroup Distribution in Indo-European Speaking Tribes of Gujarat, Western India

The present study was carried out in the Indo-European speaking tribal population groups of Southern Gujarat, India to investigate and reconstruct their paternal population structure and population histories. The role of language, ethnicity and geography in determining the observed pattern of Y haplogroup clustering in the study populations was also examined. A set of 48 bi-allelic markers on the non-recombining region of Y chromosome (NRY) were analysed in 284 males; representing nine Indo-European speaking tribal populations. The genetic structure of the populations revealed that none of these groups was overtly admixed or completely isolated. However, elevated haplogroup diversity and FST value point towards greater diversity and differentiation which suggests the possibility of early demographic expansion of the study groups. The phylogenetic analysis revealed 13 paternal lineages, of which six haplogroups: C5, H1a*, H2, J2, R1a1* and R2 accounted for a major portion of the Y chromosome diversity. The higher frequency of the six haplogroups and the pattern of clustering in the populations indicated overlapping of haplogroups with West and Central Asian populations. Other analyses undertaken on the population affiliations revealed that the Indo-European speaking populations along with the Dravidian speaking groups of southern India have an influence on the tribal groups of Gujarat. The vital role of geography in determining the distribution of Y lineages was also noticed. This implies that although language plays a vital role in determining the distribution of Y lineages, the present day linguistic affiliation of any population in India for reconstructing the demographic history of the country should be considered with caution.
Activity-driven, event-based vision sensors

The four chips [1–4] presented in the special session on "Activity-driven, event-based vision sensors" quickly output compressed digital data in the form of events. These sensors reduce redundancy and latency and increase dynamic range compared with conventional imagers. The digital sensor output is easily interfaced to conventional digital post processing, where it reduces the latency and cost of post processing compared to imagers. The asynchronous data could spawn a new area of DSP that breaks from conventional Nyquist rate signal processing. This paper reviews the rationale and history of this event-based approach, introduces sensor functionalities, and gives an overview of the papers in this session. The paper concludes with a brief discussion on open questions.
Inhibition of TLR4 Signalling-Induced Inflammation Attenuates Secondary Injury after Diffuse Axonal Injury in Rats

Increasing evidence suggests that secondary injury after diffuse axonal injury (DAI) damages more axons than the initial insult, but the underlying mechanisms of this phenomenon are not fully understood. Recent studies show that toll-like receptor 4 (TLR4) plays a critical role in promoting adaptive immune responses and have been shown to be associated with brain damage. The purpose of this study was to investigate the role of the TLR4 signalling pathway in secondary axonal injury in the cortices of DAI rats. TLR4 was mainly localized in microglial cells and neurons, and the levels of TLR4 downstream signalling molecules, including TLR4, myeloid differentiation primary response gene 88, toll/IR-1-(TIR-) domain-containing adaptor protein inducing interferon-beta, interferon regulatory factor 3, interferon β, nuclear factor κB (NF-κB) p65, and phospho-NF-κB p65, significantly increased and peaked at 1 d after DAI. Inhibition of TLR4 by TAK-242 attenuated apoptosis, neuronal and axonal injury, and glial responses. The neuroprotective effects of TLR4 inhibition were associated with decreases in the levels of TLR4 downstream signalling molecules and inflammatory factors, including interleukin-1β, interleukin-6, and tumour necrosis factor-α. These results suggest that the TLR4 signalling pathway plays an important role in secondary injury and may be an important therapeutic target following DAI.
Line image signature for scene understanding with a wearable vision system

Wearable computer vision systems provide plenty of opportunities to develop human assistive devices. This work contributes on visual scene understanding techniques using a helmet-mounted omnidirectional vision system. The goal is to extract semantic information of the environment, such as the type of environment being traversed or the basic 3D layout of the place, to build assistive navigation systems. We propose a novel line-based image global descriptor that encloses the structure of the scene observed. This descriptor is designed with omnidirectional imagery in mind, where observed lines are longer than in conventional images. Our experiments show that the proposed descriptor can be used for indoor scene recognition comparing its results to state-of-the-art global descriptors. Besides, we demonstrate additional advantages of particular interest for wearable vision systems: higher robustness to rotation, compactness, and easier integration with other scene understanding steps.
ADHD in children and adolescents in Germany. Results of the cross-sectional KiGGS Wave 2 study and trends

Attention deficit/hyperactivity disorder (ADHD) is one of the most common mental disorders in childhood and adolescence and is associated with functional, psychosocial and cognitive impairment. As part of the second wave of the German Health Interview and Examination Survey for Children and Adolescents (2014-2017), parents of children and adolescents aged between 3 and 17 years reported whether their child was diagnosed with ADHD by a physician or psychologist. Overall, 4.4% of children and adolescents have been diagnosed with ADHD in Germany. In comparison, the KiGGS baseline study (2003-2006) showed a reduction of lifetime ADHD diagnoses of almost one percentage point over a period of ten years. The reduction of parent-reported ADHD diagnoses primarily occurred among 3- to 8-year old children and boys. The results are discussed in terms of health promotion and the introduction of health care measures.
Testes de igualdade e de comparações múltiplas para várias proporções binomiais independentes

Na teoria frequentista, inferencias sobre mais que duas proporcoes binomiais sao realizadas utilizandose a analise de variância e os procedimentos de comparacoes multiplas ou, ainda, por meio dos testes assintoticos e de metodos de computacao intensiva. Todos esses procedimentos apresentam uma limitacao, que pode ser atribuida a violacao das pressuposicoes exigidas pelos testes. Por essa razao, este trabalho foi realizado com o objetivo de propor uma abordagem bayesiana para realizar um teste global de igualdade de varias proporcoes binomiais e um teste de comparacoes multiplas de proporcoes binomiais. O desempenho desses testes foi avaliado utilizando simulacao Monte Carlo. Foram geradas k populacoes binomiais independentes com parâmetros πi e ni , i = 1, 2, . , k e simuladas amostras de Monte Carlo para cada configuracao envolvendo combinacoes das quantidades k, ni ’s e πi ’s, considerando prioris conjugadas betas com parâmetros αi e βi , fixados por tentativa e erro, buscando minimizar as taxas de erro tipo I e maximizar o poder. O TB proposto para a igualdade de varias proporcoes binomiais apresentou excelente desempenho no controle do erro tipo I e poder relativamente alto. O TCMB para proporcoes binomiais, sob H0 completa e parcial, foi conservativo e apresentou grande poder.
Power Analysis of Packet Classification on Programmable Network Processors

Packet classification algorithms are increasingly being used to provide security and Quality of Service guarantees. These algorithms are usually implemented on power hungry programmable network processors, which are used in devices such as core routers and firewalls. This paper compares the energy used by five best-known algorithms Recursive Flow Classification, HiCuts, HyperCuts, Extended Grid-of-Tries with Path Compression and Tuple Space Search with Pruning. It does this by measuring the energy used to build the search structure during preprocessing for each of the five algorithms and the average energy taken to classify a packet. To do this we implemented all five algorithms in C code and used a microarchitectural power simulation tool called Sim-Panalyzer to estimate the power dissipated by the five algorithms while running on a SA1100 StrongARM RISC processor similar to the type found on many of today's programmable network processors.
Code-aided joint channel and frequency offset estimation for DS-CDMA

This paper deals with joint data detection, synchronization and channel parameter estimation for direct-sequence code-division multiple-access systems over frequency-selective channels. In low-signal-to-noise ratio environments, conventional data-aided (DA) estimation algorithms may require an unacceptably large number of pilot symbols in order to obtain sufficiently accurate estimates of the channel and synchronization parameters. Especially, frequency offset estimation results in a significant loss in spectral efficiency. In this contribution, we consider several code-aided estimation schemes which can be incorporated in an iterative turbo detection scheme. We consider the expectation maximization algorithm, as well as the space alternating generalized expectation maximization algorithm as tools to develop code-aided estimation algorithms for a variety of scenarios. We pay special attention to the issue of computational complexity, and propose some complexity-reducing approximations. We show through computer simulations that the proposed code-aided estimation techniques considerably outperform their conventional DA counterparts.
Combining semantic techniques to enhance arabic Web content retrieval

This paper introduces an approach that combines a set of semantic techniques to enhance traditional information retrieval for the Arabic language. The approach uses a set of linguistic techniques to deal with the Web content. It expands first the initial user's query with additional related words by using lexical semantic relations (synonyms) covered in Arabic WordNet thesaurus and by domain specific words and abbreviations collected from the corpus. Second, it makes use of linguistic methods to match semantically the query objective with the text content in the search results. The paper presents the approach used and also the implementation of the system. Experimental results show that semantic retrieval outperforms the traditional information retrieval which is based only on query keywords matching.
The physiological impact of physical activity on psychological stress

______________________________________________________________________________________________ Stress is one of the single most significant factor for many physical and psychological dilemma. Longterm exposure to stress or chronic stress can lead to serious physical and psychological problems such as headaches, fatigue, depression, anxiety, stomachache, heart problems, chest pain, asthma, hypertension, liver dysfunction, diabetes, arthritis, suppressed immune system , skin conditions, irregular ministerial cycle, infertility, accelerated aging process, and premature death. As under perennial and /or continual stress condition the body releases excessive cortisol hormone that results in aforementioned issues. Physical activity may beneficial for mental and physical body system. Under intense or endurance exercise however increase total cortisol released levels far above the moderate training modalities which can be a destructive factor for people under extreme negative stress and can make worse stress health risk conditions. Thus, caution is need to be considered for people with negative stress. Nonetheless, according to the American physical activity guideline 10 minutes moderate aerobic exercise such as walking in division of 2×10 min or 3×10 min per day that can be performed throughout the week, seems to be helpful alternative for all adult in part people with psychological negative stress.
Navigating Dynamic Environments with Trajectory Deformation

Path deformation is a technique that was introduced to generate robot motion wherein a nominal path, that has been computed beforehand, is continuously deformed on-line in response to unforeseen obstacles. In an effort to improve path deformation, this paper presents a trajectory deformation scheme. The main idea is that by incorporating the time dimension and hence information on the obstacles' future behaviour, quite a number of situations where path deformation would fail can be handled. The trajectory represented as a discrete space-time curve is subject to deformation forces both external (to avoid collision with the obstacles) and internal (to maintain trajectory feasibility and connectivity). The trajectory deformation scheme has been tested successfully on a planar robot with double integrator dynamics moving in dynamic environments.
Remaining force transferring mechanism for exoskeletal robot to operate wheelchair

There are estimated to be approximately 3.5 million disabled people in Japan, and about half are handicapped in the lower or upper limb. Recently, exoskeletons have been receiving attention as potential aids for such individuals. They can make up for lost body muscle, and support walking or standing-up motions. Robots can assist disabled people by providing the force needed to support motion with the power of an actuator. When used for daily living, the operator must wear the robot mechanism in order to transfer its weight from operator to robot or peripheral device (e.g., control device, battery, compressor) for operation. Thus, the robot's usage environment is limited. We consider it important that as an assistance device supports the necessary motions of daily living, it does not affect the other motions of daily living. In the case of the disabled and elderly, often the end motor functions decline (such as the limbs), but medial region muscles remain, and these are huge. In this study, we focused on these groups of muscles. We developed a mechanism to transfer the remaining force to operational force in the hand, and designed an exoskeleton robot for the developed mechanism. In addition, we developed a control system that does not affect the operator's motion, but changes the mechanism via the original actuator when the operator is not using the robot.