Miracle-dz/UniFAR-FTUs huggingface dataset:
Arsenic levels in drinking water and the prevalence of skin lesions in West Bengal, India.

BACKGROUND A cross-sectional survey was conducted between April 1995 and March 1996 to investigate arsenic-associated skin lesions of keratosis and hyperpigmentation in West Bengal, India, and to determine their relationship to arsenic water levels. METHODS In all, 7683 participants were examined and interviewed, and the arsenic levels in their drinking water measured. RESULTS Although water concentrations ranged up to 3400 microg/l of arsenic, over 80% of participants were consuming water containing <500 microg/l. The age-adjusted prevalence of keratosis was strongly related to water arsenic levels, rising from zero in the lowest exposure level (<50 microg/l) to 8.3 per 100 for females drinking water containing >800 microg/l, and increasing from 0.2 per 100 in the lowest exposure category to 10.7 per 100 for males in the highest exposure level (> or =800 microg/l). However, 12 cases with keratosis (2 females and 10 males) were drinking water containing <100 microg/l of arsenic. Findings were similar for hyperpigmentation, with strong dose-response relationships. Among those with hyperpigmentation, 29 cases were exposed to drinking water containing <100 microg/l. Calculation by dose per body weight showed that men had roughly two to three times the prevalence of both keratosis and hyperpigmentation compared to women apparently ingesting the same dose of arsenic from drinking water. Subjects who were below 80% of the standard body weight for their age and sex had a 1.6 fold increase in the prevalence of keratoses, suggesting that malnutrition may play a small role in increasing susceptibility. CONCLUSION The surprising finding of cases who had arsenic-associated skin lesions with apparently low exposure to arsenic in drinking water needs to be confirmed in studies with more detailed exposure assessment. Further research is also needed concerning susceptibility factors which might be present in the exposed population.
IL-15 as a mediator of CD4+ help for CD8+ T cell longevity and avoidance of TRAIL-mediated apoptosis

CD4+ helper T cells contribute to the induction and maintenance of antigen-specific CD8+ T cells. Their absence results in short-lived antigen-specific CD8+ T cells and defective secondary CD8+ T cell responses because of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-mediated apoptosis. Here, we show that IL-15 codelivered with vaccines can overcome CD4+ T cell deficiency for promoting longevity of antigen-specific CD8+ T cells and avoidance of TRAIL-mediated apoptosis. In both priming and secondary responses, IL-15 down-regulates proapoptotic Bax, an intermediate in TRAIL-mediated apoptosis, and increases anti-apoptotic Bcl-XL in CD8+ T cells. Thus, IL-15 is sufficient to mimic CD4+ T cell help. Antigen-specific CD4+ T cells induce dendritic cells (DCs) to produce IL-15. IL-15 is also necessary for optimal help, because helper cells do not deliver effective help through IL-15−/− DCs. Therefore, IL-15 codelivered with vaccines can overcome CD4+ helper T cell deficiency for induction of functionally efficient CD8+ T cells and maintenance of CD8+ cytotoxic T lymphocytes (CTLs), and IL-15 is probably one of the natural mediators of help. These findings suggest new vaccine strategies against infections and cancers, especially in individuals with CD4-deficiency.
Fault Detection Based on Multi-Scale Local Binary Patterns Operator and Improved Teaching-Learning-Based Optimization Algorithm

Aiming to effectively recognize train center plate bolt loss faults, this paper presents an improved fault detection method. A multi-scale local binary pattern operator containing the local texture information of different radii is designed to extract more efficient discrimination information. An improved teaching-learning-based optimization algorithm is established to optimize the classification results in the decision level. Two new phases including the worst recombination phase and the cuckoo search phase are incorporated to improve the diversity of the population and enhance the exploration. In the worst recombination phase, the worst solution is updated by a crossover recombination operation to prevent the premature convergence. The cuckoo search phase is adopted to escape the local optima. Experimental results indicate that the recognition accuracy is up to 98.9% which strongly demonstrates the effectiveness and reliability of the proposed detection method.
Non-uniform step-size based split step fourier method for mitigating fiber transmission impairments in N-channel 224Gbit/s PolMux-16QAM system

We discuss the performance enhancement of digital backward propagation by step-size selection for implementing split-step Fourier method (SSFM) in 224Gbit/s PolMux-16QAM system. The two DBP algorithms based on the step-size selection methods; (a) constant step-size based modified DBP (M-DBP) and (b) non-uniform, i.e. logarithmic, step-size based DBP (L-DBP), are compared for diverse fiber types i.e. Standard Single Mode Fiber (SMF), Non-Zero Dispersion Shifted Fiber (NZDSF), Large Effective Area Pure-Silica-Core-Fiber (LA-PSCF) and Large Effective Area Fiber (LEAF). Non-uniform step-size distribution enhances the transmission distance upto 32% in large effective area pure-silica-core-fiber (LA-PSCF) link as compared to SMF by employing M-DBP, while we have observed an additional 13% increase in transmission distance by employing L-DBP. Furthermore, the impact of reconfigurable add-drop multiplexers (ROADMs) are also investigated in 10×224Gbit/s system with 50GHz channel spacing grid. ROADMs reduce the signal bandwidth and collectively increase the peak to average power ratio, resulting in higher non-linearities that limits the performance of digital backward propagation. The results also depict that heterogeneous fiber links significantly reduce the nonlinear threshold point (NLT) of the transmission system.
Yeast pheromone response pathway: characterization of a suppressor that restores mating to receptorless mutants

Saccharomyces cerevisiae haploid cells, alpha and a, mate after being appropriately stimulated by the pheromone secreted by the opposite cell type (a-factor and alpha-factor, respectively). The binding of a pheromone to its receptor is a signal that initiates a series of intracellular changes that lead to the specific physiological alterations required for mating. To identify components of the signal transduction pathway, we sought pseudorevertants that restored mating competence to receptor mutants (MAT alpha ste3::LEU2). The suppressor srm1-1 was isolated as a recessive mutation that conferred temperature-sensitive growth to all strains and mating ability to MAT alpha ste3::LEU2 strains at the nonpermissive temperature. In addition, when srm1-1 mutants were shifted to the nonpermissive temperature, they exhibited two phenotypes characteristic of pheromone response, induction of FUS1 transcription and accumulation of cells in the G1 phase of the cell cycle. The srm1-1 mutation also suppressed a deletion of the alpha-factor-receptor gene in a cells. Together, these phenotypes suggest that the wild-type SRM1 product is a component of the pheromone response pathway. Deletion of STE4 or STE5, which are required in both haploid cell types for mating and response to pheromone, was not suppressed by srm1-1, suggesting that the SRM1 product may function before the STE4 and STE5 products. SRM1 is an essential gene and is expressed in both haploid cell types as well as in the product of their mating, a/alpha diploids. Homozygous srm1-1 a/alpha diploids were temperature sensitive although they did not arrest in G1. Thus, the SRM1 product may also have a role in the vegetative life cycle of cells.
Adenosine A1 receptor‐dependent and independent pathways in modulating renal vascular responses to angiotensin II

Renal afferent arterioles are the effector site for autoregulation of glomerular perfusion and filtration. There is synergistic interaction between angiotensin II (ANG II) and adenosine (Ado) in regulating arteriolar contraction; however, the mechanisms are not clear. In this context, this study investigated the contribution of A1 receptor‐dependent and independent signalling mechanisms.
Rad9 Protects Cells from Topoisomerase Poison-induced Cell Death*

Previous studies have suggested two possible roles for Rad9 in mammalian cells subjected to replication stress or DNA damage. One model suggests that a Rad9-containing clamp is loaded onto damaged DNA, where it participates in Chk1 activation and subsequent events that contribute to cell survival. The other model suggests that Rad9 translocates to mitochondria, where it triggers apoptosis by binding to and inhibiting Bcl-2 and Bcl-xL. To further study the role of Rad9, parental and Rad9-/- murine embryonic stem (ES) cells were treated with camptothecin, etoposide, or cytarabine, all prototypic examples of three classes of widely used anticancer agents. All three agents induced Rad9 chromatin binding. Each of these agents also triggered S-phase checkpoint activation in parental ES cells, as indicated by a caffeine-inhibitable decrease in [3H]thymidine incorporation into DNA and Cdc25A down-regulation. Interestingly, the ability of cytarabine to activate the S-phase checkpoint was severely compromised in Rad9-/- cells, whereas activation of this checkpoint by camptothecin and etoposide was unaltered, suggesting that the action of cytarabine is readily distinguished from that of classical topoisomerase poisons. Nonetheless, Rad9 deletion sensitized ES cells to the cytotoxic effects of all three agents, as evidenced by enhanced apoptosis and diminished colony formation. Collectively, these results suggest that the predominant role of Rad9 in ES cells is to promote survival after replicative stress and topoisomerase-mediated DNA damage.
Compiling Java to PLT Scheme

Our experimental compiler translates Java to PLT Scheme; it enables the use of Java libraries within Scheme programs, and it makes our Scheme programming tools available when programming with Java. With our system, a programmer can extend and use classes from either language, and Java programmers can employ other Scheme data by placing it in a class using the Java native interface. PLT Scheme’s class-system, implemented with macros, provides a natural target for Java classes, which facilitates interoperability between the two languages, and PLT Scheme’s module maintains Java security restrictions in Scheme programs. Additionally, module’s restrictions provide a deeper understanding of a Java compilation unit and make Java’s implicit compilation units explicit.
Application of the Partial Element Equivalent Circuit Method to Analysis of Transient Potential Rises in Grounding Systems

This paper presents calculations of lightning transient potential rises in grounding systems. A partial element equivalent circuit (PEEC) method, adopting a modified image method, is employed in this paper. The modified image method in this paper has two options either including or neglecting images of conduction currents along conductors for calculating series impedances. The effect of retardation in the PEEC method is also investigated. Comparisons of simulation results by the proposed method with those by the method of moments, the finite-difference time-domain method, and experimental results collected from the literature show that the PEEC method with the modified image method is quite effective in the evaluation of transient potential rise in a grounding system.
GESTATIONAL DIABETES: PERINATAL AND MATERNAL COMPLICATION IN 24-28 WEEKS

Background: Gestational diabetes mellitus (GDM) is a glucose tolerance disorder that occurs or is diagnosed for the first time during pregnancy. Perinatal morbidity is more and women with GDM have more risk of developing diabetes. Uttar Pradesh is a state of India with one of the highest rate of infant as well as maternal mortality which might be, at least partially, due to GDM. Thus, appropriate assessment and management of GDM can improve the outcomes. Aims & Objectives: Primary objective of this study was to determine the prevalence of GDM and evaluate the maternal and fetal outcome in and around Kanpur. Thus, this study was undertaken to know the extent of burden on the healthcare, before scope of intervention could be defined. Materials and Methods: A prospective study (September, 2012 - October, 2014) was done at 198 healthcare facilities. 24,656 mothers were screened (24th- 28th weeks of pregnancy) as per guidelines of Diabetes in Pregnancy Study Group India (DIPSI) and Federation of Obstetric and Gynecological Societies of India (FOGSI). Results: > 94% pregnant women did not know about GDM. Prevalence of GDM was 14.42%. Stillbirth, Perinatal & neonatal mortality were respectively 2, 3.3 & 6 times higher in GDM. Most of the GDM were diagnosed in primigravida (62%). Congenital Malformation was 8 times higher. Low Birth Weight (LBW) was 35% in GDM (16% in Non GDM). GDM positive cases had 20.6% positive family history of diabetes (compared to 6.5% in non-GDM). Relative risks for PBU (post birth unit), LGA (large for gestational age), LBW (low birth weight), pre-eclampsia and jaundice were also higher. Conclusion: A well predictive screening criteria is needed. As the ignorance about GDM among pregnant ladies is high, to reduce the risk, awareness can be an area of thrust.
Infant Botulism Acquired from Household Dust Presenting as Sudden Infant Death Syndrome

ABSTRACT Clostridium botulinum type B was detected by multiplex PCR in the intestinal contents of a suddenly deceased 11-week-old infant and in vacuum cleaner dust from the patient's household. C. botulinum was also isolated from the deceased infant's intestinal contents and from the household dust. The genetic similarity of the two isolates was demonstrated by pulsed-field gel electrophoresis and randomly amplified polymorphic DNA analysis, thereby confirming that dust may act as a vehicle for infant botulism that results in sudden death.
Time-series deformation monitoring over mining regions with SAR intensity-based offset measurements

Underground mining can induce large vertical displacements that often lead to the loss of coherence in repeat-pass interferometric synthetic aperture radar (SAR) images. Using SAR intensity images, this paper employs the image offset tracking method to map SAR slant range changes due to ground deformation over areas of mining. The rationale of slant range offset measurement with respect to the vertical deformation is analysed and the prerequisite of applying the slant range offset method to monitor vertical deformation is discussed. Results from the slant range offset method are used to produce time-series of cumulative ground displacements via least square estimate. We use six Advanced Land Observation Satellite (ALOS)-Phased Array L-band SAR (PALSAR) images over two coalfields in Inner Mogolia, China, to illustrate the proposed method and its effectiveness. We achieve deformation measurements with a precision of ∼0.2 m, with the maximum vertical displacement over the mining sites reaching ∼4.5 m. Finally, we use time-series results to outline common features identified in mining-induced deformation. Our results are supported by in situ investigations.
An architecture of a VR simulation system for cardiac intervention

Cardiovascular diseases account for a major cause of deaths in many developed countries. To treat cardiovascular diseases, cardiac minimally intervention is widely used as an effective yet complicated solution. Training of cardiac intervention is thus playing a crucial role. This paper addresses the use of Virtual Reality (VR) technology for the simulated training of cardiac intervention. In particular, the paper describes the architecture of a VR simulation system for cardiac intervention focusing on VR hardware, software and methodology is used in As an enabling technology, Graphics Processing Unit (GPU) is applied in this work to enhance cardiac modeling, cardiac visualization, and cardiac interactive simulation with the VR simulation environment.
Electrically Evoked Responses in the Rabbit Cortex Induced by Current Steering With Penetrating Optic Nerve Electrodes.

Purpose Current steering is a neural stimulation strategy that uses simultaneous stimulation of adjacent electrodes to produce additional intermediate stimulation sites and thus improves spatial resolution. We investigated the feasibility of current steering using electrophysiological and computational methods after implanting paired penetrating electrodes into the rabbit's optic nerve (ON). Methods Penetrating electrodes at different interelectrode distances were implanted into the ON and electrically evoked cortical potentials (EEPs) in V1 recorded with a 6 × 8 array. The current thresholds, EEP amplitudes, and spatial distributions were analyzed during current steering. Computational simulation studies were performed based on finite element models to calculate the area and spatial distribution of recruited ON fibers using a current steering stimulation strategy. Results Threshold reduction and EEP amplitude enhancement were found with simultaneous stimulation of closely spaced electrode pairs. Spatially shifted cortical responses were achieved using current steering, whereas the amplitudes and spatial spreads of the responses were similar to that elicited by a single electrode. Computational simulations suggested that the centroid of the ON recruitment area could be modulated by current steering while the total recruitment area did not show any appreciable variability at a fixed current intensity. Conclusions Current steering is a useful strategy to enhance the spatial resolution of an ON prosthesis without increasing the number of physical electrodes. This study provides useful information for optimizing the design of stimulation strategies with a penetrating ON prosthesis.
Topographic constrained land cover classification in mountain areas using fully convolutional network

ABSTRACT Mountains are an important kind of landform on the earth’s surface. Due to harsh mountainous environment, such as steep slopes and cliffs, remote sensing has become an indispensable tool for surveying mountain areas instead of traditional ground surveys. However, the accuracy of current land cover products derived from remote sensing in mountain areas is still low. In this paper, we propose a three-level architecture for land cover classification in mountain areas. Topographic partitioning is first performed in order to partition a large area into several smaller zones, and then, multiresolution segmentation is implemented in each individual zone. Thus, we can obtain initial geo-semantic objects with terrain, spectrum and texture homogeneities. A fully convolutional network (FCN)-based classifier (U-Net) is further introduced for supervised classification of land cover. From the perspectives of both visual interpretation and quantitative evaluation, the proposed method achieved robust and high-precision results for all land cover types. We also investigate the contributions of multimodal features for classification accuracy improvement. First, the results showed that additional features resulted in higher classification accuracies than 3-features only; 6-features achieved the best performance on farmland, impervious surfaces and coniferous forests, while 5-features performed well on water and broad-leaved forests. The elevation feature did not have a positive effect on water and broad-leaved forests, which can be explained by their physical distribution in the landscape. Second, the most significant improvement was achieved on water (Kappa coefficient increased from 0.741 to 0.924), followed by coniferous forests (Kappa coefficient increased from 0.629 to 0.805), whereas only a minor improvement was observed for the other three types. Furthermore, the accuracies of farmland and impervious surfaces remained relatively high even without the assistance of additional features, and texture feature plays a key role. The final land cover map was generated by combining the optimal results of each type via a hierarchical integrating strategy. The overall accuracy of classification achieved 90.6%.
Plagiarism, Palimpsest and Intertextuality

Writing, according to Kristeva, is an act of plagiarism. We write palimpsests on top of other writing, acknowledging implicitly that we are derivative, that our work is intertextual, borrowed, sampled, ‘internalised’, ‘bowerbirded’ from other works. In my teaching of Creative Writing, I encourage students to intentionally ‘borrow’ in this way; in my own writing, I blatantly steal. It is what writers do. How different, however, is intertextual borrowing to copying other people's work and passing it off as your own? I will examine recent examples of writers who have been shamed and stripped of their awards because of their intertextual ‘borrowings’, and compare this to Kristeva's notion of text as a ‘mosaic of quotations’ as well as Roland Barthes's idea of text as ‘a new tissue of past citations’, and explore the fine line between plagiarism, palimpsest and intertextuality.
Image denoising using multi-stage sparse representations

This paper presents a novel image denoising method based on multiscale sparse representations. The denoising is performed in a multi-stage framework where sparse representations are obtained in different scales to capture multiscale image features. Based on the multi-stage structure, we introduce a new stopping criterion for sparse coding to capture image structures more accurately than previous methods. Furthermore we propose a thresholding technique to effectively avoid artifacts which are usually introduced due to the erroneous pursuit for noise-induced structures. Experimental results demonstrate that the proposed method achieves PSNR performance comparable to other state-of-the-art methods while producing denoised images with superior visual quality.
Forecasting tourist arrivals with machine learning and internet search index

The queries entered into search engines register hundreds of millions of different searches by tourists, not only reflecting the trends of the searchers' preferences for travel products, but also offering a forecasting of their future travel behavior. This paper proposed a forecasting framework based on internet search index and machine learning to forecast tourist arrivals, and compared the forecasting performance of two different search engines data, Baidu and Google. The empirical results suggest that the proposed KELM models by fusing Baidu index and Google index can significantly improve the forecasting performance and outperform other benchmark models in terms of forecasting accuracy.
Eﬃcient Tracking of MR Tensor Fields Using a Multilayer Neural Network

—In this paper, a recently developed ﬁber tracking algorithm to be used with diﬀusion tensor (DT) ﬁelds acquired via magnetic resonance imaging (MRI) is improved and applied to real brain DT-MR images. The method performs satisfactorily in regions where branching and crossing ﬁbers exist and oﬀers the capability of reporting a probability value for the computed tracts. This certainty ﬁgure takes into account both the anisotropy and the information provided by all the eigenvectors and eigenvalues of the diﬀusion matrix at each voxel. In previous papers of the authors, a simpler algorithm was applied only to elementary synthetic DT-MR images. As now presented, this algorithm is now adequately used with more intricate synthetic images and is applied to real white matter DT-MR images with successful results. Besides, the parer presents a novel neural network that is used to estimate the crucial parameters of the algorithm. Numerical experiments show a performance gain over previous approaches, specially with respect to convergence and computational load. The tracking of white matter ﬁbers in the human brain will improve the diagnosis and treatment of many neuronal diseases.