Miracle-dz/UniFAR-FTUs huggingface dataset:
CapLibrate: Self-Calibration of an Energy Harvesting Power Supply with Supercapacitors

Achieving perpetual and self-sustaining operation of wireless sensor nodes is an important topic of current research in the field of energy harvesting. Closely related to this is the employment of energy budgeting, i.e., effective utilization of available and future energy resources without pushing a node towards the hazard of energy depletion. Therefore, reliable prediction of node lifetime in context of the available energy within a given time is required. This in turn requires self-calibration of the sensor nodes and their energy harvesting supply. In this paper, we explore and assess models for a supercapacitorbased harvesting supply. The parameters of the models are discussed and determined, so that fast, reliable, and energyefficient calibration becomes possible. Moreover, measurement results for a specific hardware platform are discussed and a roadmap for a self-calibration algorithm is presented.
Bounding the Probability of Error for High Precision Optical Character Recognition

We consider a model for which it is important, early in processing, to estimate some variables with high precision, but perhaps at relatively low recall. If some variables can be identified with near certainty, they can be conditioned upon, allowing further inference to be done efficiently. Specifically, we consider optical character recognition (OCR) systems that can be bootstrapped by identifying a subset of correctly translated document words with very high precision. This "clean set" is subsequently used as document-specific training data. While OCR systems produce confidence measures for the identity of each letter or word, thresholding these values still produces a significant number of errors. We introduce a novel technique for identifying a set of correct words with very high precision. Rather than estimating posterior probabilities, we bound the probability that any given word is incorrect using an approximate worst case analysis. We give empirical results on a data set of difficult historical newspaper scans, demonstrating that our method for identifying correct words makes only two errors in 56 documents. Using document-specific character models generated from this data, we are able to reduce the error over properly segmented characters by 34.1% from an initial OCR system's translation.
Assessing Water Scarcity and Watershed Development in Maharashtra, India: A Case Study of the Baliraja Memorial Dam

In the drought-prone regions of Maharashtra State, a growing social movement for equitable water distribution is engaging the help of engineers to build technical projects. This movement aims to challenge the state’s agroindustrial development model favoring water-intensive sugarcane farming by redistributing water. This article examines the Baliraja Memorial Dam, located in southwestern Maharashtra. Through the dam, 400 families in the villages of Balawadi and Tandulwadi will receive a share of water for irrigation and domestic needs. This article explores the Baliraja Dam as an appropriate technology project designed jointly by village farmers, engineers, and social activists. Through this unique alliance, Baliraja was designed to meet the needs of ecological restoration, community empowerment, and democratic technological design. The pioneering success of the Baliraja effort has prompted other communities to pressure the state irrigation bureaucracy to address the ecological and human costs of prolonged drought and water misuse.
Work-group and organizational support : A test of distinct dimensions

Using data from 467 members of a large firm in the United States, this paper found that perceived work-group support is a distinct construct from perceived organizational support. To reinforce the uniqueness of the constructs, the work-group and organizational support constructs exhibited meaningful, differential relationships with six of eight variables reflecting different levels of exchange relationships and commitments. The implications of these findings are discussed.
Co-presence Analysis and Economic Patterns: Mediterranean Imports in the Celtic World

This article presents one of the first steps of a project which aims at exploring the diffusion patterns of Mediterranean imported goods in Late Iron Age Europe (250 to 25 BC), and the organisation of the commercial interactions of these goods. It brings together two archaeologists and a mathematician in the study of a wide inventory of 57,735 Italian and Greek imports discovered from England to Serbia. This large amount of new and unpublished data is analysed through the joint use of network analysis tools and formal statistical methods. The analysis focuses on detecting patterns in the association of imported artefacts that are often found on the same sites. The objectives are to highlight groups of imports that may have circulated together, and to emphasise regional selections by local populations. At this stage of the study, two main systems of imports have been highlighted, used respectively in West and Central Europe. Interesting leads that will need further investigation include the imports status and the role they played in Celtic societies, as acculturated objects or more as objects for acculturation.
Contribution of the evaluation of the clinical signals in patients with patellofemoral pain syndrome

OBJECTIVE: As patellofemoral pain syndrome (PFPS) is a common disorder characterized by multifactorial etiology and whose the most prevalent symptom is a diffuse pain, usually located on the retropatellar region, however, it also shows signs and symptoms that can be related as excessive subtalar pronation, external tibial torsion, patellar displacement alterations, painful range of motion of the knee, pain in the patellar borders, muscular tightness and changes in quadriceps angle (Q Angle), the objective of this work was to determine the frequency of these signs and symptoms associated to a previous knee pain questionnaire. METHODS: Thirty-nine sedentary female volunteers had been evaluated, divided in two groups, PFPS (19) and Control (20). These subjects were evaluated for signs and symptoms described above, in addition to pain assessment by questionnaire. RESULTS: The results demonstrated a high frequency of pain in six of the thirteen questions in relation to the control group. CONCLUSION: According to these findings, we conclude that the functional evaluation of individuals with PFPS should consist of a previous knee pain questionnaire and an evaluation of the characteristic signs and symptoms for examination of the entire lower limb during static and functional situations. Level of Evidence II, Diagnostic Studies.
Cytoplasmic Calcium Increases in Response to Changes in the Gravity Vector in Hypocotyls and Petioles of Arabidopsis Seedlings1

Plants respond to a large variety of environmental signals, including changes in the gravity vector (gravistimulation). In Arabidopsis (Arabidopsis thaliana) seedlings, gravistimulation is known to increase the cytoplasmic free calcium concentration ([Ca2+]c). However, organs responsible for the [Ca2+]c increase and the underlying cellular/molecular mechanisms remain to be solved. In this study, using Arabidopsis seedlings expressing apoaequorin, a Ca2+-sensitive luminescent protein in combination with an ultrasensitive photon counting camera, we clarified the organs where [Ca2+]c increases in response to gravistimulation and characterized the physiological and pharmacological properties of the [Ca2+]c increase. When the seedlings were gravistimulated by turning 180°, they showed a transient biphasic [Ca2+]c increase in their hypocotyls and petioles. The second peak of the [Ca2+]c increase depended on the angle but not the speed of rotation, whereas the initial peak showed diametrically opposite characters. This suggests that the second [Ca2+]c increase is specific for changes in the gravity vector. The potential mechanosensitive Ca2+-permeable channel (MSCC) inhibitors Gd3+ and La3+, the Ca2+ chelator 1,2-bis(2-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid (BAPTA), and the endomembrane Ca2+-permeable channel inhibitor ruthenium red suppressed the second [Ca2+]c increase, suggesting that it arises from Ca2+ influx via putative MSCCs in the plasma membrane and Ca2+ release from intracellular Ca2+ stores. Moreover, the second [Ca2+]c increase was attenuated by actin-disrupting drugs cytochalasin B and latrunculin B but not by microtubule-disrupting drugs oryzalin and nocodazole, implying that actin filaments are partially involved in the hypothetical activation of Ca2+-permeable channels. These results suggest that the second [Ca2+]c increase via MSCCs is a gravity response in the hypocotyl and petiole of Arabidopsis seedlings.
Detecting cartoons: a case study in automatic video-genre classification

This paper presents a new approach for classifying individual video frames as being a 'cartoon' or a 'photographic image'. The task arose from experiments performed at the TREC-2002 video retrieval benchmark: 'cartoons' are returned unexpectedly at high ranks even if the query gave only 'photographic' image examples. Distinguishing between the two genres has proved difficult because of their large intra-class variation. In addition to image metrics used in prior cartoon-classification work, we introduce novel metrics like ones based on the pattern spectrum of parabolic size distributions derived from parabolic granulometries and the complexity of the image signal approximated by its compression ratio. We evaluate the effectiveness of the proposed feature set for classification (using support vector machines) on a large set of keyframes from the TREC-2002 video track collection and a set of Web images. The paper reports the identification error rates against the number of images used as training set. The system is compared with one that classifies Web images as photographs or graphics and its superior performance is evident.
Object occlusion and object removal detection

In general, there have methods to detect object removal event, but when people blocking the object an object, it is possible detect the event as removed. Thus, if we can make the system can classify between occlusion event and removal event, this can increase the accuracy and performance of the system. In this paper, we present a method that can detect and classify object occlusion and object removal event. The detection and classification uses Canny edge detector, and the classification can be done by determining the edge similarity of the object between background and current image. The system is tested in different places and it gives an acceptable and satisfied result.
Preoperative serum albumin as a prognostic factor in patients with upper urinary tract urothelial carcinoma.

PURPOSE The study evaluated whether preoperative measures of the C-reactive protein-systemic inflammatory response may predict cancer survival independent of tumor stage in patients with upper urinary tract urothelial carcinoma (UTUC). MATERIALS AND METHODS Between September 1999 and October 2010, 181 patients submitted to radical nephroureterectomy were available for evaluation. Multivariate survival analyses were performed using Cox's proportional hazards model and the coefficient for each factor was divided by the highest coefficient, multiplied by 4, and rounded to the nearest integer. RESULTS Multivariate analyses showed that tumor location, pathologic T stage, lymphovascular invasion, margin status, and albumin level were independent contributors. The bootstrap-corrected C statistics of the model were 0.813 for disease-specific survival and 0.755 for overall survival, respectively. For time to disease-specific and overall mortality for patients, integrated area under the curve values were 0.792 and 0.739, respectively. When patients were clustered into three groups according to their model-predicted survival, the 5-year disease-specific survival in the low-, intermediate- and high-risk group was 95.4%, 76.2%, and 36.9%, respectively (p<0.001), and were 87.8%, 54.4%, and 31.8%, respectively, for overall survival (p<0.001). Decision curve analysis revealed that the use of model was associated with net benefit gains relative to the treat-all strategy. CONCLUSIONS Pretreatment albumin is a simple biomarker based on routinely available well-standardized measures, and is not an expensive and time-consuming process. Hypoalbuminemia is an independent marker of poor prognosis in patients with upper urinary tract urothelial carcinoma.
Constrained MIMO nonlinear predictive control based derivate-free state estimators

This paper presents a constrained multivariable model predictive control for discrete nonlinear systems based on Divided Difference filters (DDFs) which are derivate free state estimators. The estimators are used simultaneously for both nonlinear model predictive control (NMPC) formulation by determining the state variation at each time step, and for a state feedback closed loop implementation. The proposed combination presents a high performance in set-points tracking and control law stability when implemented in presence of low and high noisy measurements compared to the NMPC based Extended Kalman Filter (EKF).
Essential oil of Lippia multiflora Moldenke: A review.

Lippia multiflora Moldenke is a tropical to subtropical herbaceous aromatic plant widely distributed throughout tropical Africa, South and Central American countries. It has been traditionally used in various communities for different purposes ranging from therapeutic febrifuge in form of tea and fumigants to non-therapeutic drink for relaxation and sedation, and as well as condiments. Of most economic and scientific importance is the essential oil in the aerial part of the plant, the “lippia oil”. The therapeutic properties of the plant are largely attributed by researchers to the oil. This review is aimed at collating all the scientific data available on the oil and drawing attention to its chemical components, pharmacological activities and resources for industrial exploration and exploitation.
Attribution studies of observed land precipitation changes with nine coupled models

Global‐land mean observations of 20th century precipitation are compared to modelled values using an optimal regression technique for nine general circulation models. The combined influence of major anthropogenic and natural forcings is detected in five cases. Comparing the accuracy of precipitation and temperature simulation of each model, we find that low temperature simulation accuracy produces low precipitation simulation accuracy, but temperature accuracy does not determine precipitation accuracy in general. Model formulation appears to be more important for accurate precipitation simulation than inclusion of a more complete set of forcings. The implications for possible constraints on land precipitation are discussed.
Plate mode propagation losses in solidly mounted resonators

This paper investigates the acoustic losses of propagating eigenmodes through the acoustic mirror of a solidly mounted resonator (SMR), aiming to clarify how resonator properties are influenced by reflection coefficients for the thickness shear (TS) wave as well as that for the thickness extensional (TE) wave. To this end, we analyze the effective acoustic admittance for several test structures with different mirror properties. Leaky modes are distinguished from plate-like modes and the propagation losses are quantified by calculating mode quality factors. The dependence of the propagation properties of leaky eigenmodes is compared to the mirror properties in terms of bulk wave transmission coefficients obtained by the one-dimensional Mason's model. It is shown that the TE-like main mode couples with TS-like spurious modes, which then influences the leaky loss of the main mode as well. The coupling strength is strongly frequency dependent and drastically changes with the mirror design. This result explains previous experimental results reported on SMR design.
4.2: Self‐Calibrating Tiled Displays

This paper presents seamless tiled displays via completely distributed network of projector‐camera systems that calibrates itself without any user intervention. This makes projection‐based tiled displays very easy to deploy and maintain. The decentralized calibration methodology presented to achieve this also enables advanced capabilities like scalability, reconfigurability and fault‐tolerance.
Regression Test-Selection Technique Using Component Model Based Modification: Code to Test Traceability

Regression testing is a safeguarding procedure to validate and verify adapted software, and guarantee that no errors have emerged. However, regression testing is very costly when testers need to re-execute all the test cases against the modified software. This paper proposes a new approach in regression test selection domain. The approach is based on meta-models (test models and structured models) to decrease the number of test cases to be used in the regression testing process. The approach has been evaluated using three Java applications. To measure the effectiveness of the proposed approach, we compare the results using the re-test to all approaches. The results have shown that our approach reduces the size of test suite without negative impact on the effectiveness of the fault detection.
A Strategy for Residual Component-Based Multiple Structured Dictionary Learning

A new strategy for multiple structured dictionary learning is proposed. It is motivated by the fact that a signal and its residual after sparse approximation do not necessarily possess the same geometric structure. Based on the geometric structure of each residual component, the most appropriate dictionary is selected. A single-atom sparse representation vector of this residual is calculated and the chosen dictionary is updated. For a given training signal, the process of model (dictionary) selection and one-atom representation is repeated until the desired sparsity or approximation error is reached. Thus, the proposed strategy provides a mechanism whereby each signal can update the most relevant dictionaries based on the structure of its residuals. Simulations conducted over natural images show that, in comparison to standard single or multiple dictionary learning and sparse representation approaches, the proposed strategy significantly improves the representation quality.
Detecting Curvilinear Structure in Images

Humans have a well developed ability to detect curvilinear structure in noisy images. Good algorithms for performing this process would be very useful in machine vision for image segmentation and object recognition. Previous approaches to this problem such as those due to Parent and Zucker and Sha''shua and Ullman have been based on relaxation. We have developed a simple feedforward and parallel approach to this problem based on the idea of developing filters tuned to local oriented circular arcs. This provides a natural second order generalization of the idea of directional operators popular for edge detection. Curve detection can then be done by methods very similar to those used for edge detection. Experimental results are shown on both synthetic and natural images. We also review data from an experiment investigating human preattentive line segregation and present predictions from our model that agree with this data.
Educating children on the autism spectrum: preconditions for inclusion and notions of ‘best autism practice’ in the early years

This article draws together findings from expert evidence and empirical studies to identify the preconditions for developing inclusive learning environments for young children on the autism spectrum. It concludes that in order to develop ‘best practice’, practitioners need to adapt interventions to the unique needs of the individual child, work in partnership with parents and other professionals, create enabling environments and be informed by a developmental approach to learning. Practitioners need to have knowledge of the autism spectrum and how it impacts on the child. Careful assessment of the individual child is also crucial. Finally, it is important to ensure that these young children receive direct teaching in communication and language, social understanding and skills, as well as learning with and through peers.
Temporal patterns of imidacloprid resistance throughout a growing season in Leptinotarsa decemlineata populations

Abstract BACKGROUND The Colorado potato beetle, Leptinotarsa decemlineata (Say), is a major agricultural pest of commercial potatoes. Pest managers use a combination of control tactics to limit populations, including multiple insecticides. Finding a window of insecticide susceptibility and understanding genetic responses to insecticide exposure during a growing season may provide novel management recommendations for L. decemlineata. RESULTS We examined temporal changes (during one growing season) in phenotypic response between a susceptible population and an imidacloprid‐resistant population. Beetles remained more susceptible to imidacloprid in the susceptible population throughout the growing season. Estimated mean LC50 values varied throughout the growing season in the resistant population, with increased susceptibility among overwintered and recently emerged adult beetles compared with a heightened level of resistance in the second generation. RNA transcript abundance was compared among multiple time points through the growing season, showing that cuticular proteins and cytochrome p450s were highly upregulated during peaks of measured resistance. CONCLUSION Temporal variation in imidacloprid susceptibility of L. decemlineata was observed, which included early time points of susceptibility and later peaks in resistance. Heightened resistance occurred during the second generation and correlated to increased transcript abundance of multiple mechanisms of resistance, including multiple cuticular protein and cytochrome p450 transcripts. © 2016 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Immune-mediated inhibition of metastases after treatment with local radiation and CTLA-4 blockade in a mouse model of breast cancer.

PURPOSE Ionizing radiation therapy (RT) is an important component in the management of breast cancer. Although the primary tumor can be successfully treated by surgery and RT, metastatic breast cancer remains a therapeutic challenge. Here we tested the hypothesis that the combination of RT to the primary tumor with CTLA-4 blockade can elicit antitumor immunity inhibiting the metastases. EXPERIMENTAL DESIGN The poorly immunogenic metastatic mouse mammary carcinoma 4T1 was used as a model. Mice were injected s.c. with 4T1 cells, and treatment was started 13 days later when the primary tumors measured 5 mm in average diameter. Mice were randomly assigned to four treatment groups receiving: (1) control IgG (IgG), (2) RT + IgG, (3) 9H10 monoclonal antibody against CTLA-4, (4) RT + 9H10. RT was delivered to the primary tumor by one or two fractions of 12 Gy. 9H10 and IgG were given i.p. thrice after RT. RESULTS Consistent with the fact that 4T1 is poorly immunogenic, 9H10 alone did not have any effect on primary tumor growth or survival. RT was able to delay the growth of the primary irradiated tumor, but in the absence of 9H10 survival was similar to that of control mice. In contrast, mice treated with RT + 9H10 had a statistically significant survival advantage. The increased survival correlated with inhibition of lung metastases formation and required CD8+ but not CD4+ T cells. CONCLUSIONS The combination of local RT with CTLA-4 blockade is a promising new immunotherapeutic strategy against poorly immunogenic metastatic cancers.