Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk Factors for Failure and Complications of Intradiscal Electrothermal Therapy: A Pilot Study

Study Design. A bi-institutional, retrospective clinical data analysis. Objectives. To determine risk factors for failure and complications of intradiscal electrothermal therapy, a treatment for discogenic back pain. Summary of the Background Data. Intradiscal electrothermal therapy is a relatively new treatment for discogenic back pain. Though previous studies have shown it to be an effective treatment, there are few published studies examining complications and none examining risk factors for failure. Methods. The authors treated 79 patients with discogenic back pain using intradiscal electrothermal therapy. Complications were assessed by patient report and, when indicated, further diagnostic testing. Success or failure was determined by visual analogue pain scores at 6-month follow-up. Variables examined for their relationship to failure and complications were age, sex, duration of pain, number of levels heated, smoking history, diabetes, obesity, leg pain, and previous back surgery. Results. Forty-eight percent of patients reported more than 50% pain relief at their 6-month follow-up. There were eight complications (10%), most of which were self-limited and transient. The only risk factor associated with intradiscal electrothermal therapy failure was obesity (P = 0.01). Whereas 54% of nonobese patients reported good pain relief at 6 months, only one out of 10 obese patients had successful intradiscal electrothermal therapy. The obese patients in our study were more likely to have a complication from intradiscal electrothermal therapy than they were to obtain pain relief. Conclusion. The only risk factor found to be associated with IDET outcome was obesity, which was a strong predictor of failure. Obesity should be considered a relative contraindication to performing IDET.
Design and control of a grid-tied three-phase three-level diode clamped single-stage photovoltaic converter

This paper introduces a single-stage grid-connected photovoltaic power conversion system based on a three-phase three-level Neutral Point Clamped (NPC) converter. The main benefits of the proposed structure are the elimination of the intermediate DC/DC power conversion stage that is usually used to boost the dc-voltage and ensure MPPT operation. Therefore, two control schemes based on a current controller and an MPPT algorithm are handled in only one processing stage. The MPPT algorithm computes in real-time the dc voltage that should be applied across the PV generator so as to extract the maximum power. The output of the MPPT algorithm is thereafter considered as a reference of a current controller that should perform a perfect tracking of the dc-voltage reference and also near unity input power factor operation. The proposed photovoltaic power conversion topology and control method are tested by numerical simulations. The obtained results demonstrate that the designed PV conversion system provides effective response in steady state, fast and perfect tracking of the maximum power point, and robust in case of a partial shading.
An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI

In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer's Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy control-sized or Alzheimer's Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer's Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state-of-the-art classifierst is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer's Disease, or even further the understand of how Alzheimer's Disease affects the hippocampus.
Spatially Distributed Snow Modeling for a Comprehensive Study of the Sacramento and San Joaquin Basins, California

This project developed, implemented, and demonstrated spatially distributed snow modeling and monitoring procedures for estimating snowmelt inputs to the Sacramento and San Joaquin river basins, California. The Distributed Snow Process Model (DSPM) used a temperature index algorithm, SSARR_grid, for estimating liquid water arriving at the ground surface each hourly time step in each model cell with 2-km spatial resolution. DSPM used interpolated air temperature and precipitation fields, as well as initial snow conditions. Air temperature interpolation incorporated hourly ambient lapse rates based on observed air temperatures in an inverse-distancesquared technique. Precipitation interpolation used an inverse-distance-squared method. We developed a linear function that specified the melt factor used by SSARR_grid in each cell depending on the accumulated temperature index. In this test, DSPM relied on maps of snow water equivalent (SWE) for initiation and validation. We estimated the spatial distribution of SWE by combining estimates of snow cover area (SCA) with interpolations of SWE based on snow sensor and course measurements. SCA retrieval algorithms used measurements from the NOAA Advanced Very High Resolution Radiometer (AVHRR) to estimate snow extent as fractional cover per pixel. SWE interpolations for this project used an algorithm similar to the temperature interpolation. The results showed that 1) SWE maps predicted by DSPM with no updating over periods up to several days have fair agreement with maps produced from AVHRR merged with ground measurements, 2) cloud cover conditions permit the construction of SWE maps from AVHRR and ground measurements with sufficient frequency to improve model results through updating, and 3) preliminary runs of HEC–HMS to route the snowmelt water capture the timing and magnitude of the flow using these spatially distributed inputs.
Synthesis and in Vitro Cytotoxic Activity of Compounds with Pro-Apoptotic Potential

In our search for new anticancer therapies, some compounds synthesized in our lab were selected and their potential cytotoxic activity was evaluated in vitro against two cancer cells lines including a solid tumor (UACC-62, melanoma) and a human lymphoma (JURKAT). Compounds showing cytotoxic activity were subjected to an apoptosis assay. Two compounds showed promising results.
Cache partitioning for energy-efficient and interference-free embedded multitasking

We propose a technique that leverages configurable data caches to address the problem of energy inefficiency and intertask interference in multitasking embedded systems. Data caches are often necessary to provide the required memory bandwidth. However, caches introduce two important problems for embedded systems. Caches contribute to a significant amount of power as they typically occupy a large part of the chip and are accessed frequently. In nanometer technologies, such large structures contribute significantly to the total leakage power as well. Additionally, cache outcomes in multitasking environments are notoriously difficult to predict, if not impossible, thus resulting in poor real-time guarantees. We study the effect of multiprogramming workloads on the data cache in a preemptive multitasking environment, and propose a technique which leverages configurable cache architectures to not only eliminate intertask cache interference, but also to significantly reduce both dynamic and leakage power. By mapping tasks to different cache partitions, interference is completely eliminated. Dynamic and leakage power are significantly reduced as only a subset of the cache is active at any moment. We introduce a profile-based, off-line algorithm, which identifies a beneficial cache partitioning. The OS configures the data cache during context-switch by activating the corresponding partition. Our experiments on a large set of multitasking benchmarks demonstrate that our technique not only efficiently eliminates intertask interference, but also significantly reduces both dynamic and leakage power.
Binding allocation and floorplanning in low power high-level synthesis

This work is a contribution to high level synthesis for low power systems. While device feature size decreases, interconnect power becomes a dominating factor. Thus it is important that accurate physical information is used during high-level synthesis. We propose a new power optimisation algorithm for RT-level netlists. The optimisation performs simultaneously slicing-tree structure-based floorplanning and functional unit binding and allocation. Since floorplanning, binding and allocation can use the information generated by the other step, the algorithm can greatly optimise the interconnect power. Compared to interconnect unaware power optimised circuits, it shows that interconnect power can be reduced by an average of 41.2 %, while reducing overall power by 24.1 % on an average. The functional unit power remains nearly unchanged. These optimisations are not achieved at the expense of area.
Networks of Agri‐Environmental Action: Temporality, Spatiality and Identity in Agricultural Environments

Engineering new networks between state agencies, farmers and other actors is central to contemporary agri-environmental policy. This article examines relationships between network membership, identity and changes in farming practice from the perspective of three different conceptualisations of social networks. These include social network analysis, the network society thesis and actor-network theory. Despite their common reliance on the metaphor of 'networks' to focus sociological analysis, these approaches are based on divergent ontological assumptions and suggest a number of different research foci. The paper finds that while social networks embedded in group membership and interactions among farmers appear to have had dramatic impacts on the expression of personal and group identities – particularly in relation to women – their impact on the adoption of more overtly environmentally sound farming practices has been limited in several important ways. By contrast, less visible relationships of knowledge and expertise that extend beyond the co-present interactions of producers appear to shape farming identities and practices 'at a distance', in ways that contribute to the limited impact of agri-environment group membership.
Time-Dependent Toxic and Genotoxic Effects of Zinc Oxide Nanoparticles after Long-Term and Repetitive Exposure to Human Mesenchymal Stem Cells

Zinc oxide nanoparticles (ZnO-NP) are widely spread in consumer products. Data about the toxicological characteristics of ZnO-NP is still under controversial discussion. The human skin is the most important organ concerning ZnO-NP exposure. Intact skin was demonstrated to be a sufficient barrier against NPs; however, defect skin may allow NP contact to proliferating cells. Within these cells, stem cells are the most important toxicological target for NPs. The aim of this study was to evaluate the genotoxic and cytotoxic effects of ZnO-NP at low-dose concentrations after long-term and repetitive exposure to human mesenchymal stem cells (hMSC). Cytotoxic effects of ZnO-NP were measured by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. Furthermore, genotoxicity was evaluated by the comet assay. For long-term observation over 6 weeks, transmission electron microscopy (TEM) was applied. The results of the study indicated cytotoxic effects of ZnO-NP beginning at high concentrations of 50 μg/mL and genotoxic effects in hMSC exposed to 1 and 10 μg/mL ZnO-NP. Repetitive exposure enhanced cyto- but not genotoxicity. Intracellular NP accumulation was observed up to 6 weeks. The results suggest cytotoxic and genotoxic potential of ZnO-NP. Even low doses of ZnO-NP may induce toxic effects as a result of repetitive exposure and long-term cellular accumulation. This data should be considered before using ZnO-NP on damaged skin.
Psychological assessment of adult posttraumatic states

Etiology of Posttraumatic States Symptomatology and Phenomenology Critical Issues in Trauma-Relevant Assessment Assessment of Traumatic Events Diagnostic Interviews General Objective and Projective Measures Trauma-Specific Objective Measures Putting it All Together Assessment of Pre-Trauma Functioning Traumatic Events Moderating Influences Posttraumatic Response.
When diplomacy fails: difficulty understanding hints following severe traumatic brain injury

Background: In the absence of aphasia, many people with severe traumatic brain injuries (TBI) have difficulty with communication. In particular, they have difficulty understanding conversational inference. Poor social cognition is also prevalent following TBI. Aims: This study aimed to examine the role of social cognition in the ability to recognise conversational inference in the form of hints. Methods and procedures: 31 adults (22 men: mean age 45 years) with chronic (mean time since injury = 15.12 years) and severe TBI (mean post traumatic amnesia (PTA) of 32.74 days) and 24 adults (14 men: mean age 46.1 years) from the community participated. They were compared for their comprehension of two kinds of video vignettes in which professional actors made progressively more explicit hints. In one version, the conversational tone was neutral, in the other emotional. They were also assessed on an independent measure of social cognition (TASIT). Outcomes & results: The adults with TBI recognised neutral hints at a normal rate but, unlike the community controls, were not facilitated by overtly emotional hints. Social cognition performance was related to performance on both types of hint. Improved performance on the emotional hints was not uniquely predicted by social cognition but, rather, by processing speed and possibly also stress in the group with TBI. Conclusions: People with TBI appear to have difficulty using emotional cues to infer speaker meaning. This may reflect cognitive slowing and also anxiety and stress. This has implications for both remediation of such deficits and for educating others who interact with people with TBI.
An effective robust fingertip detection method for finger writing character recognition system

This paper proposes an effective and robust fingertip detection method in 2D plane and applies it to a novel vision based human computer interaction system: finger writing character recognition system (FWCRS). The fingertip detection approach consists of two stages. First, based on the grid sampling and the analysis of sampled hand contour, the fingertip was detected roughly. Then, the location of fingertip was localized precisely based on circle feature matching. Experiments suggest that the proposed fingertip detection method is capable of detecting fingertip in a reliable manner even in a complex background under different light conditions without any markers. To demonstrate the strength of the method, the method was run on 5 sequences with varying light condition, different degrees of clutter background and different speeds of finger movement, experiment shows that the correct rate can reach 98.5%. The finger writing character recognition system in this paper is particularly advantageous for human-computer interaction (HCI) in that users can communicate with computers by their favorite mean: handwriting. At the same time, they can perform handwriting with only their finger directly.
Rapid identification of capybara (Hydrochaeris hydrochaeris) using allele-specific PCR.

The capybara is the largest rodent in the world and is widely distributed throughout Central and South America (Paula et al., 1999). It is an animal of economic interest due to the pleasant flavor of its meat and higher protein content in comparison to beef and pork meat. The hide, hair and fat also have economic advantages. Thus, as an animal with such high economic potential, it is the target of hunters, even though hunting capybara is prohibited by law in Brazil (Fauna Law, number 9.605/98). Due to their similarities, capybara meat is easily confused with pork. This occurs due to the apprehension of the meat from hunters, as well as in some restaurants that serve capybara meat that was slaughtered illegally. In both cases, when the meat is confiscated, those re sponsible for the crimes claim it is pork, hindering the enforcement of the law. Therefore, an effective method of identifying this meat is important both in terms of combating the predatory hunting of capybara and protecting the rights of consumers to know the origin of what they are consuming. The objective of the present work was to identify capybara meat using allele-specific primers through PCR (Polymerase Chain Reaction) and discriminate it in relation to other types of meat, especially pork. To carry out the present work, oligonucleotides were constructed using the gene sequence alignments of Transthyretin (TTH1), Growth Hormone Receptor (GHR)
Efeitos do Square Stepping Exercise nas capacidades funcionais e funções executivas em frequentadores do Centro do Idoso de Rio Claro - SP

With aging process, there is a natural biological decline that eventually may lead to a functional and cognitive decrease. It is important that older people preserve these functions so they can live an independent life. Some declines in old people who attend Geriatric Day-Care tend to be more severe and recurrent. The Square Stepping Exercise (SSE) is a program created by Shigematsu & Okura (2006), in order to improve the balance of its practitioners, thereby decreasing the risk of falls. It is also believed that the SSE stimulates cognition, and thus, executive functions. The present study, with a longitudinal design, evaluated the effects of SSE in balance performance and executive functions of elderly from the “Centro-Dia do Idoso Padre Casagrande” from Rio Claro – SP. A group of 15 people (GT, n = 15), which performed a four month SSE intervention, and a control group (GC; n = 17) answered the following evaluations. : Questionnaire Registration Data and Anamnesis, Questionnaire Baeck Modified for Elderly, Mini-Mental State Examination, Modified Card Sorting Test, Geriatric Depressive Scale, Questionnaire Pfeffer for Instrumental Activities, Berg Balance Scale and Time Up and Go Test. Although significant improvements have not been observed in GT, the results showed a decline in instrumental activities performance in GC, as well as maintenance in executive functions and balance, and also an improvement in depressive symptoms in GT. This way, Square Stepping Exercise can be considered an activity that helps maintaining functional capacity, among them balance, and executive function in elderly people. Key-Words: Square Stepping Exercise; Geriatric Day-Care; Executive Function; Balance.
Reactive Visual Navigation Based on Omnidirectional Sensing – Path Following and Collision Avoidance

Described here is a visual navigation method for navigating a mobile robot along a man-made route such as a corridor or a street. We have proposed an image sensor, named HyperOmni Vision, with a hyperboloidal mirror for vision-based navigation of the mobile robot. This sensing system can acquire an omnidirectional view around the robot in real time. In the case of the man-made route, road boundaries between the ground plane and wall appear as a close-looped curve in the image. By making use of this optical characteristic, the robot can avoid obstacles and move along the corridor by tracking the close-looped curve with an active contour model. Experiments that have been done in a real environment are described.
A density functional study of the adsorption of methane-thiol on the (111) surfaces of the Ni-group metals: I. Molecular and dissociative adsorption

The molecular and dissociative adsorption of methane-thiol (CH3SH) in the high-coverage limit on the (111) surfaces of the Ni-group metals has been investigated using ab initio density functional techniques. In molecular form, methane-thiol is bound to the surface only by weak polarization-induced forces in a slightly asymmetric configuration with the C–S axis tilted by 35–60° relative to the surface normal. On Ni and Pd surfaces the S atom occupies a position close to a bridge site; on Pt it is located close to an on-top position. The length of the S–H bond is only slightly stretched relative to its value in the gas phase, indicating only a very modest degree of activation for dehydrogenation. A strong covalent adsorbate/substrate bond is formed upon adsorption of a methane-thiolate (CH3S) radical. On Ni(111) in the energetically most favorable configuration the S atom occupies a position in a threefold hollow, slightly displaced towards a bridge site. The C–S axis is tilted by about 35° across the bridge. On Pd(111) and Pt(111) the S atom of thiolate occupies a position between a hollow and a bridge site, with the C–S axis tilted even more strongly across a neighboring threefold hollow. On all three surfaces our calculations demonstrate the existence of multiple metastable adsorption configurations, including upright CH3S bound in the center of a threefold hollow as reported in some earlier studies. Dehydrogenation of the adsorbed methane-thiol to form co-adsorbed methane-thiolate and atomic hydrogen is an exothermic process, which is not activated on Ni(111) but activated on Pd(111) and Pt(111).
Neighborhood Preserving Non-negative Tensor Factorization for image representation

Non-negative Matrix Factorization (NMF) has become a powerful tool for image representation due to its enhanced semantic interpretability under non-negativity. Unfortunately, two types of neighborhood information essential to representation are lost in NMF. For individual image, the local structure information is missing in the vectorization, which can then be avoided by Non-negative Tensor Factorization (NTF). For image data points, they often reside on a low dimensional submanifold embedded in a high dimensional ambient space. NMF and NTF are incapable of encoding the local geometrical information, which can nevertheless be resuscitated by manifold learning. To simultaneously model both of the neighborhood relationship within and among image data, this paper proposes a novel algorithm called Neighborhood Preserving Non-negative Tensor Factorization (NPNTF) by incorporating locally linear embedding regularization into tensor factorization. Experimental results on image clustering show the superior performance of NPNTF with more natural and discriminating representation ability.