Miracle-dz/UniFAR-FTUs huggingface dataset:
Undervolting in WSNs — A feasibility analysis

The energy consumption of electric circuits depends on the applied voltage level. This is used by dynamic voltage scaling approaches where the voltage is lowered up to a datasheet specified level. To reduce the energy consumption even further, it would be possible to power the electric circuits below the specified voltage levels. Considering Wireless Sensor Nodes, this `undervolting' would save a substantial amount of energy and, hence, would lead to a significant longer lifetime of nodes and networks. Contrariwise, operating processors or nodes outside their specifications adds some extra incertitude to the system. In this paper, we analyze the effects of undervolting for a typical wireless sensor node in theory and practice. A prototype implementation is used to characterize the influence of lower-than-recommended voltage levels on the MCU. In addition, the impact of different temperatures is considered as well as the behaviour of an undervolted transceiver unit and, therefore, the effects on the wireless communication. While classical computer applications may contain too many hazards to outweigh the improved energy consumption when using undervolting, we show that it is particularly suitable for Wireless Sensor Networks (WSNs) with a huge potential of saving energy and the opportunity of novel power management approaches on every layer.
A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data

Abstract. In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in the radar line of sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on 6 years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. It is shown that this in part can be explained by detection by the radar sidelobes and by scattering off increased levels of dust and turbulence. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. It is shown that, when weather echoes give rise to higher reflectivity values than those of the wind farm, the negative impact of the wind turbines is greatly reduced for all spectral moments.
New Efficient 2-D Lattice Structures for General Autoregressive Modeling of Random Fields

In this paper, we present a new efficient general 2-D autoregressive (AR) lattice modeling technique of random fields. Our proposed approach is capable of simultaneously providing all possible types of 2-D causal quarter-plane (QP) and asymmetric half-plane (ASHP) AR models for an arbitrary rectangular shape of the prediction support region (PSR). It is shown that it is also possible to obtain various noncausal half-plane AR models without any additional computational cost. This new lattice structure introduces only one row or one column of new observation points into the existing rectangular PSR when the order of the model increases in the horizontal or vertical direction at each of the recursive order incrementation stage, respectively. Starting with a given random data field, a set of auxiliary forward and backward prediction error fields (PEFs) for the horizontal and vertical directions are generated. After recursive order updates to the desired size of the rectangular PSR, all types of causal QP/ASHP and noncausal half-plane 2-D lattice models are obtained by deriving the appropriate PEF from the remaining ones. In addition to developing the basic theory, the presentation includes the derivation of the synthesis model transfer functions from the calculated lattice parameters. It is shown that the proposed auxiliary horizontal and vertical backward prediction error filters inherently generates the mutually orthogonal realization vectors and thus are optimum for all stages. The theory has been confirmed by computer simulations.
Iranian Journal of Basic Medical Sciences Population-based Seroprevalence of Htlv-i Infection in Golestan Province, South East of Caspian Sea, Iran

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective(s): Human T-cell lymphotropic virus type-1 is an oncornavirus that causes adult T cell leukemia (ATL) HTLV-I-associated myelopathy⁄tropical spastic paraparesis (HAM/TSP). Golestan province is located in North West of Khorasan province known as an endemic area for HTLV-I in Iran. This study aimed to evaluate seroprevalence of HTLV-I in Golestan province. Materials and Methods: In this cross-sectional descriptive study in 2007, blood samples were collected from 2034 healthy people residing in different parts of Golestan province. Sera were assessed for HTLV-I/II–specific antibodies by ELISA method and reactive samples were confirmed by Western blot. Demographic and serologic data were entered in SPSS version 11.5 and statistical analysis was performed.
Contrast-Based Fully Automatic Segmentation of White Matter Hyperintensities: Method and Validation

White matter hyperintensities (WMH) on T2 or FLAIR sequences have been commonly observed on MR images of elderly people. They have been associated with various disorders and have been shown to be a strong risk factor for stroke and dementia. WMH studies usually required visual evaluation of WMH load or time-consuming manual delineation. This paper introduced WHASA (White matter Hyperintensities Automated Segmentation Algorithm), a new method for automatically segmenting WMH from FLAIR and T1 images in multicentre studies. Contrary to previous approaches that were based on intensities, this method relied on contrast: non linear diffusion filtering alternated with watershed segmentation to obtain piecewise constant images with increased contrast between WMH and surroundings tissues. WMH were then selected based on subject dependant automatically computed threshold and anatomical information. WHASA was evaluated on 67 patients from two studies, acquired on six different MRI scanners and displaying a wide range of lesion load. Accuracy of the segmentation was assessed through volume and spatial agreement measures with respect to manual segmentation; an intraclass correlation coefficient (ICC) of 0.96 and a mean similarity index (SI) of 0.72 were obtained. WHASA was compared to four other approaches: Freesurfer and a thresholding approach as unsupervised methods; k-nearest neighbours (kNN) and support vector machines (SVM) as supervised ones. For these latter, influence of the training set was also investigated. WHASA clearly outperformed both unsupervised methods, while performing at least as good as supervised approaches (ICC range: 0.87–0.91 for kNN; 0.89–0.94 for SVM. Mean SI: 0.63–0.71 for kNN, 0.67–0.72 for SVM), and did not need any training set.
Submillimeter Observations of a Sample of Broad Absorption Line Quasars

The broad absorption line (BAL) features seen in a small fraction of quasar optical/UV spectra are attributed to bulk outflows away from the quasar core. Observations suggest that dust plays a key role in these systems, although whether the inferred dust properties are a signature of orientation effects or whether they are indicative of an evolutionary sequence remains an outstanding issue. Submillimeter detections of BAL quasars (BALQSOs), which would clearly help to resolve this issue, have so far been sparse. This Letter reports on new submillimeter observations of seven BALQSOs. The strongest influence on the observed flux is found to be the redshift, with the two highest redshift sources appearing intrinsically more submillimeter-luminous than the lower redshift ones. Since this trend is also seen in other high-redshift active galactic nuclei (AGNs), including non-BAL quasars, it implies that the dust emission properties of these systems are no different from those of the general AGN population, which is difficult to reconcile with the evolutionary interpretation of the BAL phenomenon.
Implementation of Emotional Controller for Interior Permanent Magnet Synchronous Motor Drive

This paper presents for the first time the real-time implementation of an emotional controller for interior permanent magnet synchronous motor (IPMSM) drives. The proposed novel controller is called brain emotional learning based intelligent controller (BELBIC). The utilization of BELBIC is based on emotion processing mechanism in brain, and is essentially an action, which is based on sensory inputs and emotional cues. The emotional learning occurs mainly in the amygdala. The amygdala is mathematically modeled, and the BELBIC controller is introduced. This type of controller is insensitive to noise and variance of the parameters. The controller is successfully implemented in real-time using a digital signal processor board ds1102 for a laboratory 1-hp IPMSM. The results show superior control characteristics especially very fast response, simple implementation and robustness with respect to disturbances and manufacturing imperfections. The proposed method enables the designer to shape the response in accordance with the multiple objectives of choices
Molecular Profiles of Neurofibromatosis Type 1-Associated Plexiform Neurofibromas

Purpose: Neurofibromatosis type 1 (NF1) is an autosomal dominant disorder with a complex variety of clinical symptoms. The hallmark of NF1 is the development of heterogeneous benign neurofibromas, which may appear as dermal neurofibromas or plexiform neurofibromas. NF1 patients with plexiform neurofibromas are at risk of developing malignant peripheral nerve sheath tumors. Experimental Design: To obtain additional insight into the molecular pathogenesis of plexiform neurofibromas, we used real-time quantitative reverse transcription-PCR assays to quantify the mRNA expression of 349 selected genes in plexiform neurofibromas in comparison with dermal neurofibromas and patient-matched malignant peripheral nerve sheath tumors. Results: Thirty genes were significantly up-regulated in plexiform neurofibromas compared with dermal neurofibromas. None were down-regulated. The up-regulated genes mainly encoded transcription factors and growth factors and secreted proteins, cytokines, and their receptors, pointing to a role of paracrine and autocrine signaling defects in the genesis of plexiform neurofibromas. We also identified a gene expression profile, based on MMP9, FLT4/VEGFR3, TNFRSF10B/TRAILR2, SHH, and GLI1, which discriminated those plexiform neurofibromas most likely to undergo malignant transformation. Conclusion: Our study has identified a limited number of signaling pathways that could be involved, when altered, in plexiform neurofibroma development. Some of the up-regulated genes could be useful diagnostic or prognostic markers or form the basis of novel therapeutic strategies.
Quantitative assessment of cold atmospheric plasma anti‐cancer efficacy in triple‐negative breast cancers

Cold atmospheric plasma has emerged as a novel oncotherapeutic approach that has undergone a fast growth in the past few years. However, there is no quantitative assessment of the factors influencing its anti‐tumor efficacy and the mechanism driving its activity remains mysterious. Through the use of 18 orthogonal experiments followed by linear model construction, we identified four deterministic parameters, that is, “treatment time,” “liquid surface area,” “thickness of medium,” and “number of cells,” which play deterministic roles on the anti‐tumor efficacy of plasma. We propose “Reactive Species Diffusion Model” and “Signal Transduction Model” to explain the mechanics determining the activity of plasma treated medium and its cell‐death induction efficacy. We, in addition, proposed the use of deterministic parameters in defining plasma dose in the liquid form to more objectively reflect its multi‐modality nature. Our study contributes in elucidating plasma activity and efficacy in a quantitative way, which guides other plasma related investigations and accelerates plasma clinical applications as a type of precision oncotherapy.
Does E-Government Improve Government Capacity? Evidence from Tax Administration and Public Procurement

Using a cross-country data set on e-government systems, this paper analyzes whether e-filing of taxes and e-procurement adoption improves the capacity of governments to raise and spend resources through the lowering of tax compliance costs, improvement of public procurement competitiveness, and reduction of corruption. The paper finds that information and communications technology can help improve government capacity, but the impact of e-government varies by type of government activity and is stronger in more developed countries. Implementation of e-filing systems reduces tax compliance costs as measured by the number of tax payments, time required to prepare and pay taxes, likelihood and frequency of firms being visited by a tax official, perception of tax administration as an obstacle, and incidence of bribery. The effects of e-procurement are weaker, with the number of firms securing or attempting to secure a government contract increasing with e-procurement implementation only in countries with higher levels of development and better quality institutions. The paper finds no systematic relationship between e-procurement and bureaucratic corruption.
The Role of Social Media in Promoting Women's Health Education in Saudi Arabia

Social media has the potential to improve women's health in developing countries through health education and promotion. In the Arab world, women's health interventions are lacking. However, with a high penetration rate of social media in the Arab world, there is good opportunity to utilize social media platforms such as Twitter to promote women's health. In this paper, we analyze the Tweet feeds of Saudi-based Twitter account to promote women's health. A total of 5167 Tweets were extracted and analyzed retrospectively, using NVivo Ncapture between June 2014 and March 2015. There were a total number of 3449 followers by March 20, 2015. Results showed that a majority of the Twitter followers (61%, n=2104) were seeking gynecological information, followed by pregnancy related information (27%, n=931), breast-feeding advice (9%, n=310), and other health related information (3%, n=103). Results also showed an increased level of health awareness and comprehension among Twitter followers. Further research is needed to promote women's health in Saudi Arabia and the Arab world through social media platforms such as Twitter and similar platforms including Instagram, Facebook, and YouTube which are also popular in the Arab world.
Participatory Air Pollution Monitoring Using Smartphones

Air quality monitoring is extremely important as air pollution has a direct impact on human health. In this paper we introduce a low-power and low-cost mobile sensing system for participatory air quality monitoring. In contrast to traditional stationary air pollution monitoring stations, we present the design, implementation, and evaluation of GasMobile, a small and portable measurement system based on o-the-shelf components and suited to be used by a large number of people. Vital to the success of participatory sensing applications is a high data quality. We improve measurement accuracy by (i) exploiting sensor readings near governmental measurement stations to keep sensor calibration up to date and (ii) analyzing the eect of mobility on the accuracy of the sensor readings to give user advice on measurement execution. Finally, we show that it is feasible to use GasMobile to create collective high-resolution air pollution maps.
Existence Theorems for Mixed Riemann–Liouville and Caputo Fractional Differential Equations and Inclusions with Nonlocal Fractional Integro-Differential Boundary Conditions

In this paper, we discuss the existence and uniqueness of solutions for a new class of single and multi-valued boundary value problems involving both Riemann–Liouville and Caputo fractional derivatives, and nonlocal fractional integro-differential boundary conditions. Our results rely on modern tools of functional analysis. We also demonstrate the application of the obtained results with the aid of examples.
Identification and functional analysis of the genes for naphthalenesulfonate catabolism by Sphingomonas xenophaga BN 6

Received 19 December 2005 Revised 13 March 2006 Accepted 14 March 2006 Sphingomonas xenophaga BN6 degrades various (substituted) naphthalenesulfonates to the corresponding (substituted) salicylates. A gene cluster was identified on the plasmid pBN6 which coded for several enzymes participating in the degradative pathway for naphthalenesulfonates. A DNA fragment of 16 915 bp was sequenced which contained 17 ORFs. The genes encoding the 1,2-dihydroxynaphthalene dioxygenase, 2-hydroxychromene-2-carboxylate isomerase, and 29-hydroxybenzalpyruvate aldolase of the naphthalenesulfonate pathway were identified on the DNA fragment and the encoded proteins heterologously expressed in Escherichia coli. Also, the genes encoding the ferredoxin and ferredoxin reductase of a multi-component, ring-hydroxylating naphthalenesulfonate dioxygenase were identified by insertional inactivation. The identified genes generally demonstrated the highest degree of homology to enzymes encoded by the phenanthrene-degrading organism Sphingomonas sp. P2, or the megaplasmid pNL1 of the naphthaleneand biphenyl-degrading strain Sphingomonas aromaticivorans F199. The genes of S. xenophaga BN6 participating in the degradation of naphthalenesulfonates also shared the same organization in three different transcriptional units as the genes involved in the degradation of naphthalene, biphenyl, and phenanthrene previously found in Sphingomonas sp. P2 and S. aromaticivorans F199. The genes were flanked in S. xenophaga BN6 by ORFs which specify proteins that show the highest homologies to proteins of mobile genetic elements.
Observations of the Optical Afterglow of GRB 050319: The Wind-to-ISM Transition in View

The collapse of a massive star is believed to be the most probable progenitor of a long gamma-ray burst (GRB). Such a star is expected to have its environment modified by the stellar wind. The effect of such a circumstellar wind medium is expected to be seen in the evolution of a GRB afterglow, but so far this has not been conclusively found. We claim that a signature of the transition from wind to constant density medium of the circumburst medium is visible in the afterglow of GRB 050319. Along with the optical observations of the afterglow of GRB 050319, we present a model for the multiband afterglow of GRB 050319. We show that the break seen in the optical light curve at ~0.02 days could be explained as being due to the transition from wind to constant density medium of the circumburst medium, in which case, to our knowledge, this could be the first ever detection of such a transition at any given frequency band. Detection of such a transition could also serve as confirmation of the massive star collapse scenario for GRB progenitors, independent of supernova signatures.
Validating Prediction Models of Kidney Transplant Outcome Using Single Center Data

Prediction of kidney transplant outcome represents an important and clinically relevant problem. Although several prediction models have been proposed based on large, national collections of data, their utility at the local level (where local data distributions may differ from national data) remains unclear. We conducted a comparative analysis that modeled the outcome data of transplant recipients in the national US Renal Data System (USRDS) against a representative local transplant dataset at the University of Utah Health Sciences Center, a regional transplant center. The performance of an identical set of prediction models was evaluated on both national and local data to assess how well national models reflect local outcomes. Compared with the USRDS dataset, several key characteristics of the local dataset differed significantly (e.g., a much higher local graft survival rate; a much higher local percentage of white donors and recipients; and a much higher proportion of living donors). This was reflected in statistically significant differences in model performance. The area under the receiver operating characteristic curve values of the models predicting 1, 3, 5, 7, and 10-year graft survival on the USRDS data were 0.59, 0.63, 0.76, 0.91, and 0.97, respectively. In contrast, in the local dataset, these values were 0.54, 0.58, 0.58, 0.61, and 0.70, respectively. Prediction models trained on a national set of data from the USRDS performed better in the national dataset than in the local data. This might be due to the differences in the data characteristics between the two datasets, suggesting that the wholesale adoption of a prediction model developed on a large national dataset to guide local clinical practice should be done with caution.
Palaeo-precipitation is a major determinant of palm species richness patterns across Madagascar: a tropical biodiversity hotspot

The distribution of rainforest in many regions across the Earth was strongly affected by Pleistocene ice ages. However, the extent to which these dynamics are still important for modern-day biodiversity patterns within tropical biodiversity hotspots has not been assessed. We employ a comprehensive dataset of Madagascan palms (Arecaceae) and climate reconstructions from the last glacial maximum (LGM; 21 000 years ago) to assess the relative role of modern environment and LGM climate in explaining geographical species richness patterns in this major tropical biodiversity hotspot. We found that palaeoclimate exerted a strong influence on palm species richness patterns, with richness peaking in areas with higher LGM precipitation relative to present-day even after controlling for modern environment, in particular in northeastern Madagascar, consistent with the persistence of tropical rainforest during the LGM primarily in this region. Our results provide evidence that diversity patterns in the World's most biodiverse regions may be shaped by long-term climate history as well as contemporary environment.