Miracle-dz/UniFAR-FTUs huggingface dataset:
Persistent organic pollutants, mitochondrial dysfunction, and metabolic syndrome

The number of individuals with metabolic syndrome is increasing worldwide, constituting a major social problem in many countries. Recently, epidemiological and experimental studies have associated insulin resistance or type 2 diabetes with elevated body burdens of persistent organic pollutants (POPs). It has been proposed that mitochondrial dysfunction plays a key role in this association. Mitochondrial DNA abnormalities are known to cause pancreas beta cell damage, insulin resistance, and diabetes mellitus. Recently, much evidence has emerged showing that environmental toxins, including POPs, affect mitochondrial function and subsequently induce insulin resistance. In this review, we present a novel concept in which metabolic syndrome is the result of mitochondrial dysfunction, which in turn is caused by exposure to POPs. The potential mechanism including POPs for mitochondrial dysfunction on metabolic syndrome is also discussed. We propose that the mitochondrial paradigm for the etiology of metabolic syndrome will facilitate the prevention and treatment of this major health problem.
Herb Hydraulics: Inter- and Intraspecific Variation in Three Ranunculus Species1[OPEN]

Small herbaceous species are vulnerable to water stress but adjusted to their habitat conditions and internally coordinated to avoid hydraulic failure. The requirements of the water transport system of small herbaceous species differ considerably from those of woody species. Despite their ecological importance for many biomes, knowledge regarding herb hydraulics remains very limited. We compared key hydraulic features (vulnerability to drought-induced hydraulic decline, pressure-volume relations, onset of cellular damage, in situ variation of water potential, and stomatal conductance) of three Ranunculus species differing in their soil humidity preferences and ecological amplitude. All species were very vulnerable to water stress (50% reduction in whole-leaf hydraulic conductance [kleaf] at −0.2 to −0.8 MPa). In species with narrow ecological amplitude, the drought-exposed Ranunculus bulbosus was less vulnerable to desiccation (analyzed via loss of kleaf and turgor loss point) than the humid-habitat Ranunculus lanuginosus. Accordingly, water stress-exposed plants from the broad-amplitude Ranunculus acris revealed tendencies toward lower vulnerability to water stress (e.g. osmotic potential at full turgor, cell damage, and stomatal closure) than conspecific plants from the humid site. We show that small herbs can adjust to their habitat conditions on interspecific and intraspecific levels in various hydraulic parameters. The coordination of hydraulic thresholds (50% and 88% loss of kleaf, turgor loss point, and minimum in situ water potential) enabled the study species to avoid hydraulic failure and damage to living cells. Reversible recovery of hydraulic conductance, desiccation-tolerant seeds, or rhizomes may allow them to prioritize toward a more efficient but vulnerable water transport system while avoiding the severe effects that water stress poses on woody species.
Prediction of Chemical Respiratory and Contact Sensitizers by OX40L Expression in Dendritic Cells Using a Novel 3D Coculture System

The use of animal models in chemical safety testing will be significantly limited due to the recent introduction of the 3Rs principle of animal experimentation in research. Although several in vitro assays to predict the sensitizing potential of chemicals have been developed, these methods cannot distinguish chemical respiratory sensitizers and skin sensitizers. In the present study, we describe a novel in vitro assay that can discriminate respiratory sensitizers from chemical skin sensitizers by taking advantage of the fundamental difference between their modes of action, namely the development of the T helper 2 immune response, which is critically important for respiratory sensitization. First, we established a novel three-dimensional (3D) coculture system of human upper airway epithelium using a commercially available scaffold. It consists of human airway epithelial cell line BEAS-2B, immature dendritic cells (DCs) derived from human peripheral blood CD14+ monocytes, and human lung fibroblast cell line MRC-5. Respective cells were first cultured in individual scaffolds and subsequently assembled into a 3D multi-cell tissue model to more closely mimic the in vivo situation. Then, three typical chemicals that are known respiratory sensitizers (ortho-phthaldialdehyde, hexamethylene diisocyanate, and trimellitic anhydride) and skin sensitizers (oxazolone, formaldehyde, and dinitrochlorobenzene) were added individually to the 3D coculture system. Immunohistochemical analysis revealed that DCs do not migrate into other scaffolds under the experimental conditions. Therefore, the 3D structure was disassembled and real-time reverse transcriptase-PCR analysis was performed in individual scaffolds to analyze the expression levels of molecules critical for Th2 differentiation such as OX40 ligand (OX40L), interleukin (IL)-4, IL-10, IL-33, and thymic stromal lymphopoietin. Both sensitizers showed similarly augmented expression of DC maturation markers (e.g., CD86), but among these molecules, OX40L expression in DCs was most consistently and significantly enhanced by respiratory sensitizers as compared to that by skin sensitizers. Thus, we have established a 3D coculture system mimicking the airway upper epithelium that may be successfully applied to discriminate chemical respiratory sensitizers from skin sensitizers by measuring the critical molecule for Th2 differentiation, OX40L, in DCs.
Wideband Absorber With Combination of Plasma and Resistive Frequency Selective Surface

In this paper, by combination of plasma and resistive frequency-selective surface (FSS), a wideband absorber is designed which covers the X- and Ku-bands. A plasma layer is supposed to be confined above a dielectric substrate that a resistive FSS and solid metal ground are etched on its top and bottom sides, respectively. To analyze the absorber structure with a transmission line method, an equivalent circuit model for resistive FSS embedded between plasma and dielectric layers is introduced. By comparison with simulation, it is shown that the model has a good accuracy in a wideband of frequency. Also, the values of the circuit model elements are extracted and their behaviors are investigated through the variation of surface resistivity. It is shown that embedding resistive FSS in conventional plasma absorber consisting of a plasma layer over a ground plane reduces the thickness of the plasma layer and makes it easier to implement the absorber.
Associations of Serum Retinol, α-Tocopherol, and γ-Tocopherol with Biomarkers among Healthy Japanese Men

Retinol, α-tocopherol, and γ-tocopherol are fat-soluble vitamins acting as antioxidants via the prevention of lipid oxidation. Little is known about circulatory levels in healthy individuals. The present cross-sectional study aimed at elucidating the relationship between these antioxidants and clinical biomarkers in 206 male (median age 41 years, range 23–67) employees from companies located in the Okayama Prefecture, Japan. Subjects younger than 40 years (n = 94) showed a positive association of the frequency of alcohol consumption with the circulating retinol (β = 0.344, p = 0.001) and γ-tocopherol levels (β = 0.219, p = 0.041), and an inverse association of fast insulin with serum retinol (β = −0.301, p = 0.009). In participants older than 40 years (n = 112) we found that an inverse association of HOMA-R with serum retinol (β = −0.262, p = 0.021), α-tocopherol (β = −0.236, p = 0.035), and γ-tocopherol levels (β = −0.224, p = 0.052); and cigarette smoking was inversely associated with the levels of serum α-tocopherol (β = −0.286, p = 0.008) and γ-tocopherol (β = −0.229, p = 0.040). We further found negative relationships between serum ferritin and the retinol (β = −0.211, p = 0.032) and α-tocopherol levels (β = −0.223, p = 0.022) in men over 40 years of age. The present study suggests that the circulatory levels of antioxidant vitamins may modulate the action of insulin and that higher levels of iron might decrease the levels of antioxidant vitamins in the blood.
T-cell interferon gamma receptor binding in interferon beta-1b-treated patients with multiple sclerosis.

OBJECTIVE To investigate the effects of interferon beta treatment on T-cell interferon gamma binding (which is a possible marker for T-cell-dependent immune function) in patients with multiple sclerosis (MS). DESIGN Assay interferon gamma binding on T lymphocytes from patients with stable relapsing-remitting MS before, 3 months after, and 6 months after initiating interferon beta-1b treatment. SETTING The study was performed on ambulatory patients in a tertiary care center, where patients were diagnosed as having definite MS. PATIENTS Eighteen patients with clinically definite, stable, relapsing-remitting MS (13 women and 5 men; mean age [+/-SD] 32.6+/-7.1 years) were selected consecutively. Clinical status was defined according to the Kurtzke Expanded Disability Status Scale. All patients were treated with 8 x 10(6) IU interferon beta-1b subcutaneously every other day. Eighteen age- and sex-matched healthy subjects with no family history of neuropsychiatric disorders formed the control group. RESULTS T lymphocytes from untreated patients with MS had significantly smaller amounts of interferon gamma receptors than those from control subjects (638+/-7 [SE] vs 707+/-11 [SE] receptors per cell). After 3 months of interferon beta-1b treatment, they showed a significant increase in interferon gamma binding (681+/-9 [SE] receptors per cell). After 6 months, T-cell interferon gamma maximal receptor values were even higher (700+/-7 [SE] receptors per cell), only slightly lower than those of control subjects. CONCLUSION Given that reduced interferon gamma binding might be related to lymphocyte activation, our data seem to demonstrate that the major effect of interferon beta-lb treatment is a decrease in T-cell activation.
Whole-genome expression profiling of the marine diatom Thalassiosira pseudonana identifies genes involved in silicon bioprocesses

Formation of complex inorganic structures is widespread in nature. Diatoms create intricately patterned cell walls of inorganic silicon that are a biomimetic model for design and generation of three-dimensional silica nanostructures. To date, only relatively simple silica structures can be generated in vitro through manipulation of known diatom phosphoproteins (silaffins) and long-chain polyamines. Here, we report the use of genome-wide transcriptome analyses of the marine diatom Thalassiosira pseudonana to identify additional candidate gene products involved in the biological manipulation of silicon. Whole-genome oligonucleotide tiling arrays and tandem mass spectrometry identified transcripts for >8,000 genes, ≈3,000 of which were not previously described and included noncoding and antisense RNAs. Gene-specific expression profiles detected a set of 75 genes induced only under low concentrations of silicon but not under low concentrations of nitrogen or iron, alkaline pH, or low temperatures. Most of these induced gene products were predicted to contain secretory signals and/or transmembrane domains but displayed no homology to known proteins. Over half of these genes were newly discovered, identified only through the use of tiling arrays. Unexpectedly, a common set of 84 genes were induced by both silicon and iron limitations, suggesting that biological manipulation of silicon may share pathways in common with iron or, alternatively, that iron may serve as a required cofactor for silicon processes. These results provide insights into the transcriptional and translational basis for the biological generation of elaborate silicon nanostructures by these ecologically important microbes.
Topological analysis of cascading failures in Bay Area power grid

The power grid networks are vulnerable to various attacks which may lead to cascading failures. Severe cascading failures can cause large scale power outage and preventing them is believed to be one of the greatest challenges in power grid systems. In this paper, we study cascading failures using the Bay Area power grid data. We adopt two topology based models, which describe the definition of load and the reaction of the network upon substation failure or overloading. Traditionally, it is often believed that the attacker will knock down the node (i.e. substation) with the highest load, which represents the strongest attack strategy. However, our study shows that the effectiveness of the traditional load based attack strategy varies under different network models. Specifically, the load based strategy is not the strongest attack in the network model that assumes the overloaded substations completely fail to function. Under another network model in which the overloaded substations still function but with reduced efficiency in power delivery, attacking the node with the high load can cause severe cascading failure. In the worst case, attacking a single node with the second highest load can result in 44% loss of network efficiency.
Gravity with Gravitas: A Solution to the Border Puzzle

The gravity model has been widely used to infer substantial trade flow effects of institutions such as customs unions and exchange rate mechanisms. McCallum [1995] found that the US-Canada border led to trade between provinces that is a factor 22 (2,200%) times trade between states and provinces, a spectacular puzzle in light of the low formal barriers on this border. We show that the gravity model usually estimated does not correspond to the theory behind it. We solve the 'border puzzle' by applying the theory seriously. We find that national borders reduce trade between the US and Canada by about 44%, while reducing trade among other industrialized countries by about 30%. McCallum's spectacular headline number is the result of a combination of omitted variables bias and the small size of the Canadian economy. Within-Canada trade rises by a factor 6 due to the border. In contrast, within-US trade rises 25%.
New adaptive color quantization method based on self-organizing maps

Color quantization (CQ) is an image processing task popularly used to convert true color images to palletized images for limited color display devices. To minimize the contouring artifacts introduced by the reduction of colors, a new competitive learning (CL) based scheme called the frequency sensitive self-organizing maps (FS-SOMs) is proposed to optimize the color palette design for CQ. FS-SOM harmonically blends the neighborhood adaptation of the well-known self-organizing maps (SOMs) with the neuron dependent frequency sensitive learning model, the global butterfly permutation sequence for input randomization, and the reinitialization of dead neurons to harness effective utilization of neurons. The net effect is an improvement in adaptation, a well-ordered color palette, and the alleviation of underutilization problem, which is the main cause of visually perceivable artifacts of CQ. Extensive simulations have been performed to analyze and compare the learning behavior and performance of FS-SOM against other vector quantization (VQ) algorithms. The results show that the proposed FS-SOM outperforms classical CL, Linde, Buzo, and Gray (LBG), and SOM algorithms. More importantly, FS-SOM achieves its superiority in reconstruction quality and topological ordering with a much greater robustness against variations in network parameters than the current art SOM algorithm for CQ. A most significant bit (MSB) biased encoding scheme is also introduced to reduce the number of parallel processing units. By mapping the pixel values as sign-magnitude numbers and biasing the magnitudes according to their sign bits, eight lattice points in the color space are condensed into one common point density function. Consequently, the same processing element can be used to map several color clusters and the entire FS-SOM network can be substantially scaled down without severely scarifying the quality of the displayed image. The drawback of this encoding scheme is the additional storage overhead, which can be cut down by leveraging on existing encoder in an overall lossy compression scheme.
Regional Differences in Water Content, Collagen Content, and Collagen Degradation in the Cervix of Nonpregnant Cows

Abstract The cow could be a suitable model for studies concerning functional changes of the cervix. However, as in many species, the bovine cervix becomes softer in texture during the follicular phase of the estrous cycle compared to the luteal phase. In the present study, we explored if changes in the collagen network take place that could be responsible for this phenomenon and if regional differences in water content, collagen content, and collagen degradation along the cross-sectional and longitudinal axes of the cervix were present. Two groups of nonpregnant animals with different progesterone status were studied. One group (n = 11) was under high progesterone influence, and the other group (n = 12) was under low progesterone influence. The water content was derived from the weight of the samples before and after lyophilization. The collagen content and the ratio of collagenous to noncollagenous proteins (hydroxyproline:proline ratio) were determined by performing amino acid analysis on hydrolyzed samples using high-performance liquid chromatography. Collagen denaturation was quantified with a colorimetric assay by determining the amount of hydroxyproline released from samples treated with α-chymotrypsine. The water content of the superficial layer of the submucosa was always significantly (P < 0.01) higher than the water content of the deep layer in the vaginal, mid, and uterine segments, but this was unrelated to the progesterone status of the animals. No effect of the tissue layers or of the progesterone status of the animals on the collagen content was observed, but an effect of segment was noted. The collagen content (µg/mg dry wt) in the vaginal segment of the cervix was significantly higher than in the mid (P < 0.05) and the uterine (P < 0.01) segments. The hydroxyproline:proline ratio showed the same pattern as the collagen content. The percentage of collagen denaturation in the superficial layer was always significantly (P < 0.01) higher than that in the deep layer, but no effect of the progesterone status or of the segment along the longitudinal axis was seen. It is concluded that regional differences in collagen biochemistry are present in the cervix of nonpregnant cows, which may account for the difference in firmness of different parts along the circular or the longitudinal axis of the cervix. However, differences in texture of the cervix between the two groups of cows could not be explained by differences in the collagen content, percentage of collagen denaturation, or water content.
Finding Time for Collaboration

The literature on teacher worklives also concludes that even when change efforts are not under way, collaborative time for teachers is necessary. Successful schools are distinguishable from unsuccessful ones by the frequency and extent to which teachers discuss practice, collaboratively design materials, and inform and critique one another (Little 1982). This sort of interaction appears necessary to continuing growth and improvement in the individual as well as to sustaining a good school (Wildman and Niles 1987).
The Promise of Premise: Harnessing Question Premises in Visual Question Answering

In this paper, we make a simple observation that questions about images often contain premises – objects and relationships implied by the question – and that reasoning about premises can help Visual Question Answering (VQA) models respond more intelligently to irrelevant or previously unseen questions. When presented with a question that is irrelevant to an image, state-of-the-art VQA models will still answer purely based on learned language biases, resulting in non-sensical or even misleading answers. We note that a visual question is irrelevant to an image if at least one of its premises is false (i.e. not depicted in the image). We leverage this observation to construct a dataset for Question Relevance Prediction and Explanation (QRPE) by searching for false premises. We train novel question relevance detection models and show that models that reason about premises consistently outperform models that do not. We also find that forcing standard VQA models to reason about premises during training can lead to improvements on tasks requiring compositional reasoning.
Adaptability of a hybrid route choice model to incorporating driver behavior dynamics under information provision

This paper proposes a seamless framework to incorporate the day-to-day and within-day dynamics of driver route choice decisions under real-time information provision by adapting a hybrid probabilistic-possibilistic model previously developed by the authors. The day-to-day dynamics are captured through the update of driver perception and route choice rules based on the current day's experience. The within-day dynamics are captured through the en-route adjustment of the weights of the driver route choice rules in response to situational factors. Experiments are conducted to analyze the model's ability to capture driver behavior dynamics, and the associated prediction accuracy. The results suggest that the framework can reflect the evolution of driver route choice behavior over time, and adapt to the within-day variability in ambient driving conditions. This is illustrated by its ability to capture phenomena such as inertia, compliance, delusion, freezing, and perception update under information provision, in addition to the effects of familiarity and route complexity. In the within-day context, the results highlight the sensitivity to the situational factors unfolding in real-time. The results also illustrate the better prediction power of the hybrid model compared to that of a traditional multinomial probit model; however, this gap reduces with increasing heterogeneity in driver behavioral class fractions. Elsewhere, the authors show that the proposed framework can be used to predict the ambient driver class fractions, thereby addressing a key deployment limitation of existing dynamic network models for real-time traffic control through route guidance.
Parameter Estimation of Jelinski-Moranda Model Based on Weighted Nonlinear Least Squares and Heteroscedasticity

Parameter estimation method of Jelinski-Moranda (JM) model based on weighted nonlinear least squares (WNLS) is proposed. The formulae of resolving the parameter WNLS estimation (WNLSE) are derived, and the empirical weight function and heteroscedasticity problem are discussed. The effects of optimization parameter estimation selection based on maximum likelihood estimation (MLE) method, least squares estimation (LSE) method and weighted nonlinear least squares estimation (WNLSE) method are also investigated. Two strategies of heteroscedasticity decision and weighting methods embedded in JM model prediction process are also investigated. The experimental results on standard software reliability analysis database-Naval Tactical Data System (NTDS) and three datasets used by J.D. Musa demonstrate that WNLSE method can be superior to LSE and MLE under the relative error (RE) criterion.