Miracle-dz/UniFAR-FTUs huggingface dataset:
Denoising and Segmentation of 3D Brain Images

This paper presents an algorithm for medical 3D image denoising and segmentation using redundant discrete wavelet transform. First, we present a two stage denoising algorithm using the image fusion concept. The algorithm starts with globally denoising the brain images (3D volume) using Perona Malik’s algorithm and RDWT based algorithms followed by combining the outputs using entropy based fusion approach. Next, a region segmentation algorithm is proposed using texture information and k-means clustering. The proposed algorithms are evaluated using brain 3D image/volume data. The results suggest that the proposed algorithms provide improved performance compared to existing algorithms.
Unintended Benefits: Leadership Skills and Behavioral Change among Guatemalan Fieldworkers Employed in a Longitudinal Household Air Pollution Study

The RESPIRE and CRECER studies measured the effects of reduced household air pollution (HAP) from wood-fired cookstoves on respiratory health in rural highland Guatemala. This article examines behavior change and leadership skill development in local community members who were hired as fieldworkers to assist with research. Fieldworkers administered household questionnaires, shared functions similar to community health workers, and bridged health resources to communities. A mixed-methods design for data collection (in-depth interviews, focus groups, impact drawings, knowledge questionnaire, and retrospective pre-test) was used. Purposive sampling included 10 fieldworkers and 13 local service providers. Fieldworkers showed an increase in knowledge, positive attitudes, and practices around HAP. They developed new technical, interpersonal, and leadership skills. Fieldworkers played a crucial role in building confianza (trust) with the community, bridging resources, and improving outside researchers' relationships with locals. Recommendations for future researchers include inclusion of additional training courses and adoption of community participatory approaches.
Timing-aware FPGA partitioning for real-time applications under dynamic partial reconfiguration

Heterogeneous system-on-chips (SoC) that include both general-purpose processors and field programmable gate arrays (FPGAs) are emerging as very promising platforms to develop modern cyber-physical systems, combining the typical flexibility enabled by software with the speedup achievable by custom hardware accelerators. Furthermore, the dynamic partial reconfiguration (DPR) capabilities of modern FPGAs make such platforms even more attractive, offering the possibility of virtualizing the FPGA area to support several hardware accelerators in time sharing. However, heterogeneous platforms originate considerable challenges in the design and development process of applications, especially if timing and energy constraints are concerned. The FRED framework has been recently proposed to support the development of real-time applications upon such platforms, using a static slotted-based partitioning of the FPGA area to ensure predictable delays when managing custom hardware accelerators by DPR. This paper addresses the problem of designing a suitable FPGA partitioning to support the execution of a real-time application within the FRED framework. The problem is formulated as a mixed-integer linear program that is in charge of (i) designing the size of the slots (in terms of FPGA resources), (ii) allocating hardware tasks to the slots, and (iii) selecting which hardware tasks must be statically allocated to the FPGA, while ensuring bounded worst-case response times on the tasks.
Isotope databases for the determination of age and provenance of elephant ivory

5. Germany is particularly thankful to the continuous support of Botswana, Burkina Faso, Malawi, Mozambique and South Africa which supported this project with the provision of samples from their ivory stockpiles. Several European museums and collections as well as numerous trophy hunters gratefully provided ivory samples. The BMU appreciates the cooperation with the International Council for Game and Wildlife Conservation (CIC) and TRAFFIC which actively promoted this project.
Implicit Application of Polynomial Filters in a k-Step Arnoldi Method

The Arnoldi process is a well-known technique for approximating a few eigenvalues and corresponding eigenvectors of a general square matrix. Numerical difficulties such as loss of orthogonality and assessment of the numerical quality of the approximations, as well as a potential for unbounded growth in storage, have limited the applicability of the method. These issues are addressed by fixing the number of steps in the Arnoldi process at a prescribed value k and then treating the residual vector as a function of the initial Arnoldi vector. This starting vector is then updated through an iterative scheme that is designed to force convergence of the residual to zero. The iterative scheme is shown to be a truncation of the standard implicitly shifted QR-iteration for dense problems and it avoids the need to explicitly restart the Arnoldi sequence. The main emphasis of this paper is on the derivation and analysis of this scheme. However, there are obvious ways to exploit parallelism through the matrix-vector .
Asymmetrical Round Trip Based Synchronization-Free Localization in Large-Scale Underwater Sensor Networks

Underwater sensor networks (UWSNs) have been proposed for many location-dependent applications such as oceanographic data collection, pollution monitoring, mine reconnaissance, etc. Accurate node localization plays an important role in realizing the potential gains of these applications. Although many localization algorithms have been proposed for terrestrial sensor networks in recent years, it is not feasible to directly use these algorithms in UWSNs since UWSNs lack a fast and reliable communication channel. Further, due to their slow convergence speeds and high communication overhead, distributed localization algorithms designed for small-scale UWSNs are not practical for large-scale underwater sensor systems. To achieve accurate and energy efficient node localization in large-scale UWSNs, an asymmetrical round trip based localization (ARTL) algorithm is proposed in this paper. This algorithm has low computational complexity and excellent scalability. Without time synchronization, this algorithm can achieve highly accurate ranging in large-scale UWSNs. Simulation results demonstrate the effectiveness of our design in terms of both localization accuracy and energy consumption.
Transcriptional Regulation of the Human Hepatic CYP3A4: Identification of a New Distal Enhancer Region Responsive to CCAAT/Enhancer-Binding Protein β Isoforms (Liver Activating Protein and Liver Inhibitory Protein)

CCAAT/enhancer-binding proteins (C/EBPs) are key transcription factors involved in the constitutive expression of several cytochrome P450 genes in the liver. Their concentration and activity change in several pathophysiological conditions. For instance, during inflammation, released cytokines induce repressive C/EBPβ-liver inhibitory protein (LIP), which antagonizes constitutive C/EBP transactivators [C/EBPα and C/EBPβ-liver activating protein (LAP)], down-regulating genes such as CYP3A4. However, the mechanism by which hepatic C/EBP factors modulate transcription of the CYP3A4 gene is not known. To elucidate the mechanism of action, we cotransfected luciferase reporter vectors, containing 5′-flanking deletions of the CYP3A4 gene, along with expression vectors for C/EBPβ-LAP, C/EBPβ-LIP, and C/EBPα, in hepatic (HepG2) and nonhepatic (HeLa) cells. Analysis of the –3557 to –6954 base pair (bp) region demonstrated the existence of a 288-bp sequence at –5.95 kilobases (kb), which showed maximal response to C/EBPβ-LAP (∼30-fold increase in HepG2 cells). Coexpression of LAP with increasing amounts of LIP reduced the activating effect by ∼70%. Site-directed mutagenesis of predicted C/EBPβ binding sites demonstrated the presence of four functional C/EBPβ-responsive motifs within this distal flanking region. Further experiments using chromatin immunoprecipitation proved the binding of endogenous C/EBPβ to the –5.95-kilobase enhancer of the CYP3A4 gene in human hepatocytes. Expression of recombinant LAP and LIP by means of adenoviral vectors resulted in their binding to this region, which was followed by activation/repression of CYP3A4. Together, our results uncover a new distal enhancer site in the CYP3A4 gene where C/EBPβ-LAP binds and activates transcription, whereas the truncated form, C/EBPβ-LIP, antagonizes LAP activity and causes gene repression.
The TGM2 gene is associated with schizophrenia in a British population

Several lines of evidence have suggested an interesting link between gluten ingestion and schizophrenia. Increased levels of gliadin antibodies have been observed in patients with schizophrenia. Tissue transglutaminase (transglutaminase 2, TGM2) is involved in the production of gliadin antibodies. To investigate genetic association of the TGM2 gene with schizophrenia, we detected eight single nucleotide polymorphisms (SNPs) present in the gene among 131 family trios composed of fathers, mothers and affected offspring with schizophrenia. Data analysis with the UNPHASED program showed allelic association for rs2076380 (χ2 = 5.51, P = 0.019), rs7270785 (χ2 = 8.13, P = 0.004), rs4811528 (χ2 = 6.13, P = 0.013) and rs6023526 (χ2 = 6.13, P = 0.013). The global P‐value was 0.029 for 10,000 permutations with the TDT analysis. The strongest association was observed for the rs7270785–rs4811528 haplotypes (χ2 = 16.18, df = 3, P = 0.001), and the global P‐value was 0.008 for 10,000 permutations with the 2‐SNP haplotype analysis. The 8‐SNP haplotype analysis also revealed a strong haplotypic association (χ2 = 44.82, df = 18, P = 0.0004) and the 1‐df test showed that the A‐T‐A‐A‐T‐G‐A‐G haplotype was excessively transmitted (χ2 = 16.98, corrected P = 0.0007). The present results suggest that the TGM2 gene may be involved in the development of schizophrenia. © 2008 Wiley‐Liss, Inc.
A Geosimulation Approach for Data Scarce Environments: Modeling Dynamics of Forest Insect Infestation across Different Landscapes

Insect infestation behaves as a complex system, characterized by non-linear spatial dynamics and emergent patterns that evolve from smaller to larger spatial scales. The emerald ash borer (EAB) is an invasive species that has infested and killed millions of ash trees across North America. Existing EAB models use traditional statistical approaches that often cannot address the spatiotemporal complexity emerging from EAB infestation processes. Moreover, these studies of insect infestation are limited by a lack of sufficient time series data. The objective of this study is to develop a geosimulation approach to overcome the challenge of data scarcity and represent EAB infestation at a regional scale. Geographic information systems (GIS), multi-criteria evaluation (MCE), and cellular automata (CA) are used to model EAB spread across different hypothetical landscape types. Simulation results represent EAB propagation and indicate different dynamics of spread for each landscape. Urban environments are identified as being at the greatest risk to the infestation. The proposed approach offers a theoretical framework and a modeling tool to represent the propagation of EAB infestation that can be applied with real geospatial datasets and potentially used in forest management strategies.
Prospective relevance of dietary patterns at the beginning and during the course of primary school to the development of body composition

Primary school years seem to represent a critical period for the development of overweight and obesity. However, only a few studies have analysed the prospective relationship between dietary patterns and weight status in children. The aims of the present study were to identify dietary patterns at the beginning of and during the primary school period and to examine their relevance to the development of body composition. Nutritional and anthropometric data from 371 participants of the Dortmund Nutritional and Longitudinally Designed (DONALD) Study at the beginning (ages 6 and 7 years) and end (ages 10 and 11 years) of the primary school period were used. Principal component analyses (PCA) were conducted to identify dietary patterns, which were regressed on changes in BMI and fat mass index (FMI) between ages 6 and 7 years and ages 10 and 11 years. Reduced rank regression (RRR) was used to directly extract patterns explaining variation in changes in BMI and FMI between ages 6 and 7 years and ages 10 and 11 years. PCA yielded interpretable patterns of dietary changes at the beginning of and during the primary school period, which were not related to changes in body composition. Conversely, RRR allowed identifying predictive patterns: higher baseline intakes of white bread and lower baseline intakes of whole-grain products as well as increases in the consumption of savoury snacks, sausages and cheese during primary school years independently predicted increases in BMI and FMI during the primary school period. In conclusion, selection of unfavourable carbohydrate sources at the beginning of the primary school period and increases in the consumption of processed savoury foods during primary school years may adversely affect the development of body composition during the course of primary school.
The Balance Between the Novel Protein Target of Wingless and the Drosophila Rho-Associated Kinase Pathway Regulates Planar Cell Polarity in the Drosophila Wing

Planar cell polarity (PCP) signaling is mediated by the serpentine receptor Frizzled (Fz) and transduced by Dishevelled (Dsh). Wingless (Wg) signaling utilizes Drosophila Frizzled 2 (DFz2) as a receptor and also requires Dsh for transducing signals to regulate cell proliferation and differentiation in many developmental contexts. Distinct pathways are activated downstream of Dsh in Wg- and Fz-signaling pathways. Recently, a number of genes, which have essential roles as downstream components of PCP signaling, have been identified in Drosophila. They include the small GTPase RhoA/Rho1, its downstream effector Drosophila rho-associated kinase (Drok), and a number of genes such as inturned (in) and fuzzy (fy), whose biochemical functions are unclear. RhoA and Drok provide a link from Fz/Dsh signaling to the modulation of actin cytoskeleton. Here we report the identification of the novel gene target of wingless (tow) by enhancer trap screening. tow expression is negatively regulated by Wg signaling in wing imaginal discs, and the balance between tow and the Drok pathway regulates wing-hair morphogenesis. A loss-of-function mutation in tow does not result in a distinct phenotype. Genetic interaction and gain-of-function studies provide evidence that Tow acts downstream of Fz/Dsh and plays a role in restricting the number of hairs that wing cells form.
Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation

We consider the estimation of a signal from the knowledge of its noisy linear random Gaussian projections. A few examples where this problem is relevant are compressed sensing, sparse superposition codes, and code division multiple access. There has been a number of works considering the mutual information for this problem using the replica method from statistical physics. Here we put these considerations on a firm rigorous basis. First, we show, using a Guerra-Toninelli type interpolation, that the replica formula yields an upper bound to the exact mutual information. Secondly, for many relevant practical cases, we present a converse lower bound via a method that uses spatial coupling, state evolution analysis and the I-MMSE theorem. This yields a single letter formula for the mutual information and the minimal-mean-square error for random Gaussian linear estimation of all discrete bounded signals. In addition, we prove that the low complexity approximate message-passing algorithm is optimal outside of the so-called hard phase, in the sense that it asymptotically reaches the minimal-mean-square error. In this work spatial coupling is used primarily as a proof technique. However our results also prove two important features of spatially coupled noisy linear random Gaussian estimation. First there is no algorithmically hard phase. This means that for such systems approximate message-passing always reaches the minimal-mean-square error. Secondly, in the limit of infinitely long coupled chain, the mutual information associated to spatially coupled systems is the same as the one of uncoupled linear random Gaussian estimation.
Texture Feature Classification of Liver Sonography Using Fuzzy Similarity Measures

It is difficult to differentiate diffuse liver diseases, namely cirrhotic and fatty livers from normal one by visual inspection from the ultrasound images. The need for computerized tissue characterization is thus justified to assist quantitatively the sonographer for accurate differentiation. In this paper a novel approach of tissue characterization using pattern recognition techniques is developed. Textural analysis methods based on co- occurrence matrix and gray-level gradient variations were applied to extract quantitative parameters for over 150 cases of three liver pathologies namely cirrhotic, fatty and normal livers. In addition to these textural feature descriptors an attenuation and speckle parameters were computed from the B-mode images. A fuzzy similarity measures as an approximate reasoning technique of matching between an unknown case defined by a feature vector and a family of prototypes were used for the classification steps. Finally we tested different textural methods and we could obtain a good results ranging from 80-95% of sensitivities and specificity for different liver pathologies.
A Data Mining Framework for Building Dengue Infection Disease Model (人工知能学会全国大会(第26回)文化,科学技術と未来) -- (International Organized Session「Application Oriented Principles of Machine Learning and Data Mining」)

Dengue infection is a virus-caused diseased that is spread by mosquitoes. Currently, there is no specific treatment, moreover there is no vaccine to prevent the people from the disease. Symptoms of this infection show rapid and violent to patients in a short time. Two classification problems are explored in this study, which are the Dengue Classification Problem and the Day of defervescence of fever (day0) detection problem. Two data mining models, fuzzy logic and decision tree, are studied in this work. We propose to use the knowledge obtained from the decision tree with the fuzzy logic approach in order to obtain better performance. The experimental result shows that using fuzzy logic approach for Dengue Classification is a suitable method. We get 97.39% of the average accuracy from fuzzy logic approach. Consider the day0 detection problem, using the attributes obtained from the dengue patient can provide the early warning on one day before the day0 with the sensitivity as 71.11% by using fuzzy logic.
Transition models for change‐point estimation in logistic regression

Although a wide variety of change‐point models are available for continuous outcomes, few models are available for dichotomous outcomes. This paper introduces transition methods for logistic regression models in which the dose–response relationship follows two different straight lines, which may intersect or may present a jump at an unknown change‐point. In these models, the logit includes a differentiable transition function that provides parametric control of the sharpness of the transition at the change‐point, allowing for abrupt changes or more gradual transitions between the two different linear trends, as well as for estimation of the location of the change‐point. Linear‐linear logistic models are particular cases of the proposed transition models. We present a modified iteratively reweighted least squares algorithm to estimate model parameters, and we provide inference procedures including a test for the existence of the change‐point. These transition models are explored in a simulation study, and they are used to evaluate the existence of a change‐point in the association between plasma glucose after an oral glucose tolerance test and mortality using data from the Mortality Follow‐up of the Second National Health and Nutrition Examination Survey. Copyright 2002 John Wiley & Sons, Ltd.
Inherently linear time symmetric pulse width modulation

This paper proposes a new category of pulse-width-modulation (PWM), time-symmetric PWM (TSPWM). This TSPWM technique removes the intrinsic harmonic distortion from PWM without using calibration or adding circuit complexity. To demonstrate the proposed technique, a PWM modulator using TSPWM is implemented as the voltage-to-time interface that modulates the voltage input to binary pulses at modulation frequency of 25MHz. It is followed by a first order noise-shaped switched-ring-oscillator (SRO) time-to-digital converter (TDC) quantizing the pulse train at sample rate of 400MHz. Built in 0. 18μm, the prototype chip shows a SFDR improvement of 24dB on the TDC output when TSPWM is used.
ACUTE TOXICITY OF SURFACTANTS AND DETERGENT -BASED DECONTAMINANTS IN MICE AND RATS

Summary Detergent-based mixtures and pure surfactants used as decontaminants in mass casualty scenarios were investigated for their acute 24 h toxicity. Commercial detergents Neodekont TM , Argos TM , Dermogel TM , and FloraFree TM were tested in male Wistar rats after percutaneous, peroral and intramuscular administration. Pure surfactants althosan MB, sodium alkylbenzene sulphonate, triton X, benzyl dimethyl dodecyl ammonium chloride, and N-dodecyl pyridinium bromide were investigated in male ICR mice. Estimated LD 50 of surfactants varied from 6 ml.kg -1 ), thus could be considered as safe if used as external skin decontaminant or if low volume is accidentally ingested.
How Many Thymocytes Audition for Selection?

T cell maturation requires the rearrangement of clonotypic T cell receptors (TCR) capable of interacting with major histocompatibility complex (MHC) ligands to initiate positive and negative selection. Only 3–5% of thymocytes mature to join the peripheral T cell pool. To investigate the basis for this low success rate, we have measured the frequency of preselection thymocytes capable of responding to MHC. As many as one in five MHC-naive thymocytes show upregulation of activation markers on exposure to MHC-expressing thymic stroma in short-term reaggregate culture. The majority of these cells display physiological changes consistent with entry into the selection process within 24 h. By exposing TCR transgenic thymocytes to a range of MHC–peptide complexes, we show that CD69 induction is indicative of thymocyte selection, positive or negative. Our data provide evidence that the fraction of thymocytes that qualify to enter the thymic selection process far exceeds the fraction that successfully complete it, and suggest that most MHC-reactive thymocytes are actively eliminated in the course of selection.
Multi Dimensional ICA to Separate Correlated Sources

We present a new method for the blind separation of sources, which do not fulfill the independence assumption. In contrast to standard methods we consider groups of neighboring samples ("patches") within the observed mixtures. First we extract independent features from the observed patches. It turns out that the average dependencies between these features in different sources is in general lower than the dependencies between the amplitudes of different sources. We show that it might be the case that most of the dependencies is carried by only a small number of features. Is this case - provided these features can be identified by some heuristic - we project all patches into the subspace which is orthogonal to the subspace spanned by the "correlated" features. Standard ICA is then performed on the elements of the transformed patches (for which the independence assumption holds) and robustly yields a good estimate of the mixing matrix.