Miracle-dz/UniFAR-FTUs huggingface dataset:
Iodine intake before and after mandatory iodization in Denmark: results from the Danish Investigation of Iodine Intake and Thyroid Diseases (DanThyr) study

Iodine deficiency is still common in some European countries. In Denmark an iodine fortification programme was introduced in 1998 and a monitoring programme was established prior to iodization. This study reports the change in urinary iodine excretion caused by fortification and investigates determinants of iodine intake after fortification. Iodine excretion in casual urine samples was assessed in 4649 subjects in 1997–8 and in 3570 comparable subjects in 2004–5 in women 18–22, 25–30, 40–45 and 60–65 years of age and in men 60–65 years of age living in Aalborg (western part of Denmark) or Copenhagen (eastern part of Denmark). These areas had moderate and mild iodine deficiency, respectively, before iodine fortification. All subjects filled in a FFQ and a questionnaire regarding lifestyle factors. Iodine excretion, expressed as the estimated 24 h urinary iodine excretion and as urinary iodine concentration, increased significantly in all age and sex groups. However, the iodine intake was still below the recommended in the youngest age groups in both cities and in women 40–45 years of age living in Aalborg. Intake of milk and salt had strong significant direct associations with iodine excretion (P < 0·001). It is concluded that although the median iodine intake in the whole study population is at the recommended level, some groups still have an intake below the recommended. It is important to have a moderate milk intake to obtain a sufficient iodine intake in Denmark.
Using Social Media for Emergency Response and Urban Sustainability: A Case Study of the 2012 Beijing Rainstorm

With the proliferation of social media, information generated and disseminated from these outlets has become an important part of our everyday lives. For example, this type of information has great potential for effectively distributing political messages, hazard alerts, or messages of other social functions. In this work, we report a case study of the 2012 Beijing Rainstorm to investigate how emergency information was timely distributed using social media during emergency events. We present a classification and location model for social media text streams during emergency events. This model classifies social media text streams based on their topical contents. Integrated with a trend analysis, we show how Sina-Weibo fluctuated during emergency events. Using a spatial statistical analysis method, we found that the distribution patterns of Sina-Weibo were related to the emergency events but varied among different topics. This study helps us to better understand emergency events so that decision-makers can act on emergencies in a timely manner. In addition, this paper presents the tools, methods, and models developed in this study that can be used to work with text streams from social media in the context of disaster management and urban sustainability.
Cost Allocation in Ancillary Service Markets

Market designs for reserve capacity in power systems face new challenges in terms of demand side participation (DSP) and renewable energy in-feed. In order to enhance power system flexibility and to reduce the amounts required of reserve capacity two key issues have to be tackled: First, financial incentives for DSP to participate in Ancillary Service markets. Second, incentives for intermittent sources and demand to adhere to their forecasted in-feed schedule. Therefore, we consider the public good aspect of reliable electricity supply and treat deviations from the schedule in in-feed or consumption as negative externalities in electricity market operation. Our contributions are twofold: First, we present a novel methodology which incorporates the individual evaluation of reserves via a suitable cost allocation framework and therefore enhances DSP to ensure operational security. Second, we provide a framework to establish market based adaptive in-feed premiums for renewable energy sources and to assess investments in DSP and distributed storage in order to reduce the amount of reserve capacity procured by the System Operator. A simulation study shows that our approach leads to a Pareto-efficient reduction in the amount of procured reserves and hence social costs.
Image Processing Algorithms for Digital Mammography: a Pic- Torial Essay 1

Digital mammography systems allow manipulation of fine differences in image contrast by means of image processing algorithms. Different display algorithms have advantages and disadvantages for the specific tasks required in breast imaging––diagnosis and screening. Manual intensity windowing can produce digital mammograms very similar to standard screen-film mammo-grams but is limited by its operator dependence. Histogram-based intensity windowing improves the conspicuity of the lesion edge, but there is loss of detail outside the dense parts of the image. Mixture-model intensity win-dowing enhances the visibility of lesion borders against the fatty background, but the mixed parenchymal densities abutting the lesion may be lost. Contrast limited adaptive histogram equalization can also provide subtle edge information but might degrade performance in the screening setting by enhancing the visibility of nuisance information. Unsharp masking enhances the sharpness of the borders of mass lesions, but this algorithm may make even an indistinct mass appear more circumscribed. Peripheral equalization displays lesion details well and preserves the peripheral information in the surrounding breast, but there may be flattening of image contrast in the nonperipheral portions of the image. Trex processing allows visualization of both lesion detail and breast edge information but reduces image contrast. Abbreviations: CLAHE = contrast-limited adaptive histogram equalization, HIW = histogram-based intensity windowing, MIW = manual intensity windowing, MMIW = mixture-model intensity windowing
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An analog implementation of a deep machinelearning system for ef cient feature extraction is presented in this work. It features online unsupervised trainability and non-volatile oating-gate analog storage. It utilizes a massively parallel recon gurable current-mode analog architecture to realize ef cient computation, and leverages algorithm-level feedback to provide robustness to circuit imperfections in analog signal processing. A 3-layer, 7-node analog deep machine-learning engine was fabricated in a 0.13 μm standard CMOS process, occupying 0.36 mm2 active area. At a processing speed of 8300 input vectors per second, it consumes 11.4 μW from the 3 V supply, achieving 1×1012 operation per second per Watt of peak energy ef ciency. Measurement demonstrates real-time cluster analysis, and feature extraction for pattern recognition with 8-fold dimension reduction with an accuracy comparable to the oating-point software simulation baseline.
Norrin Promotes Vascular Regrowth after Oxygen-Induced Retinal Vessel Loss and Suppresses Retinopathy in Mice

Norrin is a secreted protein that is involved in retinal angiogenesis and activates the Wnt-signaling pathway. We studied the role of Norrin in microvascular endothelial cells in vitro, and in a mouse model of retinopathy characterized by oxygen-induced vascular loss followed by hypoxia-induced pathological neovascularization. Recombinant Norrin significantly increased proliferation, viability, migration, and tube formation in vitro. Two independent transgenic mouse strains with ectopic overexpression of Norrin from the lens (βB1-Crystallin-Norrin), or the retinal pigment epithelium (Rpe65-Norrin) were generated and exposed to high oxygen. Following oxygen treatment, vascular loss was significantly smaller in retinae of transgenic mice from both strains as compared to wild-type littermates. In addition, the anatomical correct regrowth of vessels was significantly increased, while pathological neovascularization was suppressed. In vitro and in vivo effects of Norrin could be blocked by adding DKK (Dickkopf)-1, an inhibitor of Wnt/β-catenin signaling. Treatment of microvascular endothelial cells with Norrin caused a substantial increase in the expression of angiopoietin-2 (Ang-2). When inhibitory antibodies against Ang-2 were added to Norrin, the proliferative effects of Norrin were significantly suppressed. We conclude that Norrin is a potent factor to induce angiogenesis in microvascular endothelial cells, which has the distinct potential to suppress the damaging effects of oxygen-induced retinopathy in vivo. The effects of Norrin appear to be mediated, at least partially, via the induction of Ang-2.
Synthesis of monodisperse nanoparticles of barium titanate: toward a generalized strategy of oxide nanoparticle synthesis.

The physical properties of materials as they progress from the bulk to the nanoscale regime (1 00 nm) continue to be of immense interest and increasing importance for future technological applications. Nanocrystals display properties generally found to be scientifically different from the bulk material or the atomic or molecular species from which they can be derived. Examples of this phenomenon are manifold. 1-3 The study of semiconductor nanocrystal quantum dots is a well-established field, yielding rich, useful ,and application-oriented research. 4 A coherent field of study is currently emerging for the systematic examination of nanocrystal oxides with the aim of producing nanoparticles with narrow size distributions and size tunability in the nanoscale regime. Among the important characteristics of nanoparticle systems are facile manipulation and reversible assembly which allow for the possibility of incorporation of nanoparticles into electric, electronic, or optical devices. Such “bottom up” or “self-assembly” approaches are the benchmark of nanotechnology. Ferroelectric materials have been under investigation due to the prospect that the stable polarization states could be used to encode the 1 and 0 of the Boolean algebra that form the basis of memory and logic circuitry (FRAM). The family of complex ferroelectric oxides such as BaTiO 3, Pb(Zr,Ti)O3, and (Ba,Sr)TiO3 has far reaching applications in the electronics industry for transducers, actuators, and high-k dielectrics. 5 Ferroelectricity is the phenomenon designated to crystals in possession of a spontaneous polarization and hysteresis effects with respect to the dielectric displacement in the presence of an applied electric field. The precise nature of ferroelectricity at the nanoscale, such as critical size dependent suppression in particles and thin films, 6
Optimization of Heavy Chain and Light Chain Signal Peptides for High Level Expression of Therapeutic Antibodies in CHO Cells

Translocation of a nascent protein from the cytosol into the ER mediated by its signal peptide is a critical step in protein secretion. The aim of this work was to develop a platform technology to optimize the signal peptides for high level production of therapeutic antibodies in CHO cells. A database of signal peptides from a large number of human immunoglobulin (Ig) heavy chain (HC) and kappa light chain (LC) was generated. Most of the HC signal peptides contain 19 amino acids which can be divided into three domains and the LC signal peptides contain 22 amino acids. The signal peptides were then clustered according to sequence similarity. Based on the clustering, 8 HC and 2 LC signal peptides were analyzed for their impacts on the production of 5-top selling antibody therapeutics, namely, Herceptin, Avastin, Remicade, Rituxan, and Humira. The best HC and LC signal peptides for producing these 5 antibodies were identified. The optimized signal peptides for Rituxan is 2-fold better compared to its native signal peptides which are available in the public database. Substitution of a single amino acid in the optimized HC signal peptide for Avastin reduced its production significantly. Mass spectrometry analyses revealed that all optimized signal peptides are accurately removed in the mature antibodies. The results presented in this report are particularly important for the production of these 5 antibodies as biosimilar drugs. They also have the potential to be the best signal peptides for the production of new antibodies in CHO cells.
X-ray computed tomography uncovers root–root interactions: quantifying spatial relationships between interacting root systems in three dimensions

Research in the field of plant biology has recently demonstrated that inter- and intra-specific interactions belowground can dramatically alter root growth. Our aim was to answer questions related to the effect of inter- vs. intra-specific interactions on the growth and utilization of undisturbed space by fine roots within three dimensions (3D) using micro X-ray computed tomography. To achieve this, Populus tremuloides (quaking aspen) and Picea mariana (black spruce) seedlings were planted into containers as either solitary individuals, or inter-/intra-specific pairs, allowed to grow for 2 months, and 3D metrics developed in order to quantify their use of belowground space. In both aspen and spruce, inter-specific root interactions produced a shift in the vertical distribution of the root system volume, and deepened the average position of root tips when compared to intra-specifically growing seedlings. Inter-specific interactions also increased the minimum distance between root tips belonging to the same root system. There was no effect of belowground interactions on the radial distribution of roots, or the directionality of lateral root growth for either species. In conclusion, we found that significant differences were observed more often when comparing controls (solitary individuals) and paired seedlings (inter- or intra-specific), than when comparing inter- and intra-specifically growing seedlings. This would indicate that competition between neighboring seedlings was more responsible for shifting fine root growth in both species than was neighbor identity. However, significant inter- vs. intra-specific differences were observed, which further emphasizes the importance of biological interactions in competition studies.
An evolution strategy for the multiobjectiveoptimizationTo

This paper presents an evolution strategy for the multiobjective optimization with any constraints. The main advantage of the evolution strategy is to allow to handle simultaneously multiple objectives and constraints, and to achieve the good approximation of the complete paretoooptimal set. However, it is essentially a global search method for the scalar optimization. As a generall purpose optimization approach, this evolution strategy is implemented in the MATLABBbased 1 environment and used to solve many optimization problems, especially control system design problems ((1, 2]).
An Improved Stochastic Optimization Model for Water Supply Pumping Systems in Urban Networks

This study investigates a pump scheduling problem for the collection, transfer and storage of water in water supply systems in urban networks. The objective of this study is to determine a method to minimize the electricity costs associated with pumping operations. To address the dynamic and random nature of water demand, we propose a two-stage stochastic programming model with recourse, where the random variables are represented by a finite, discrete set of realizations or scenarios. The developed mathematical model is an extension of a previously developed deterministic model in the literature and reflects the basic assumption that a fixed cost could be incurred by the activating/deactivating activities of the hydraulic pumps. To control the possible violations of the water demand constraints for different scenarios, we also analyze a robustness technique in an attempt to obtain “almost feasible” solutions. In addition, we adopt the so-called Mean Absolute Deviation criterion, which is a risk-aversion criterion, to obtain second-stage costs that are less dependent on the realizations of the scenarios. The scenarios were generated using a Monte Carlo simulation procedure that may use any probability distribution to produce empirical probabilities of the random variables. Because the proposed pump scheduling problem with fixed cost is a two-stage stochastic mixed 0− 1 program, we developed an efficient hybrid heuristic to obtain acceptable solutions for practical scenarios with a reasonable computational time. The overall results evidence the stability of the scenario generation method, the sensitivity of the solution based on the key parameters of the mathematical model, and the efficiency of the heuristic in solving large scenarios. Finally, we show that it is possible to conserve resources by solving the stochastic programming model rather than adopting simpler approaches based on the expected value.
Functional Tradeoffs Underpin Salinity-Driven Divergence in Microbial Community Composition

Bacterial community composition and functional potential change subtly across gradients in the surface ocean. In contrast, while there are significant phylogenetic divergences between communities from freshwater and marine habitats, the underlying mechanisms to this phylogenetic structuring yet remain unknown. We hypothesized that the functional potential of natural bacterial communities is linked to this striking divide between microbiomes. To test this hypothesis, metagenomic sequencing of microbial communities along a 1,800 km transect in the Baltic Sea area, encompassing a continuous natural salinity gradient from limnic to fully marine conditions, was explored. Multivariate statistical analyses showed that salinity is the main determinant of dramatic changes in microbial community composition, but also of large scale changes in core metabolic functions of bacteria. Strikingly, genetically and metabolically different pathways for key metabolic processes, such as respiration, biosynthesis of quinones and isoprenoids, glycolysis and osmolyte transport, were differentially abundant at high and low salinities. These shifts in functional capacities were observed at multiple taxonomic levels and within dominant bacterial phyla, while bacteria, such as SAR11, were able to adapt to the entire salinity gradient. We propose that the large differences in central metabolism required at high and low salinities dictate the striking divide between freshwater and marine microbiomes, and that the ability to inhabit different salinity regimes evolved early during bacterial phylogenetic differentiation. These findings significantly advance our understanding of microbial distributions and stress the need to incorporate salinity in future climate change models that predict increased levels of precipitation and a reduction in salinity.
The Smoothing of Official Interest Rates

Central banks tend to move official interest rates in a sequence of relatively small steps in the same direction, a practice known as interest-rate smoothing. This paper documents this practice, examines its implications and discusses reasons why central banks move interest rates in this way. The practice of interest-rate smoothing is evident in many countries. In the most recent interest-rate cycle in Australia, the target cash rate was increased three times in 1994 and has been reduced four times in 1996 and 1997. Similarly, in the United States, the federal funds target rate was increased seven times in 1994 and 1995, and then reduced three times in 1995 and 1996. The fact that official interest rates are moved multiple times in the same direction leads to a clear cycle in interest rates. Some commentators have argued that this interest-rate cycle contributes to, rather than ameliorates, the business cycle. By implication, the argument is that if interest rates exhibited a less cyclical pattern, with central banks being prepared to move rates in large steps and more decisively, the amplitude of the business cycle could be reduced. In contrast, the central argument of this paper is that some degree of interest-rate smoothing represents optimal behaviour on the part of central banks. The lags between a change in monetary policy and its effect on economic activity, and the fact that the economy is subject to shocks from many sources, mean that frequent changes in the level and direction of interest rates are unlikely to reduce substantially the variability of inflation and output. Furthermore, frequent directional changes in the level of official interest rates risk rendering ineffectual the ‘announcement’ effects of monetary policy, increasing instability in financial markets and reducing the credibility and accountability of the monetary authorities. None of these developments would be expected to contribute to the stability of either output or inflation.
A NOTE ON THE EFFICIENCY OF QUANTITY-FORCING FREIGHT RATES.

This note argues that a quantity-forcing rail freight transportation contract with an average price that exceeds marginal cost may not be inefficient. The basis for this argument lies in the economics of vertical exchange. I present a model where two railroads are competing to move a shipper's freight to the shipper's delivered market. Both railroads offer a tariff, and given these tariffs, the shipper then decides how much output he will move by each railroad to market. Our major result is that railroad optimal quantity forcing contracts induce the shipper to choose the same output he would have had the railroads been forced to price at marginal cost. Thus, deregulated quantity-forcing contracts are efficient.
BER analysis of BPSK and QPSK constellations in the presence of ADC quantization noise

Quantization noise (QN) due to limited analog to digital converter (ADC) word length gives rise to degradation in system performance, especially in high frequency communication systems with sampling rates in the range of giga samples per second (Gsps). In this paper, expressions are derived for the evaluation of the bit error rate (BER) of binary phase shift keying (BPSK) and quadrature PSK (QPSK) signal constellations as a function of ADC word length (NADC) and signal to noise ratio (SNR) due to additive white Gaussian noise (AWGN). It is shown that unlike the AWGN case, system performance is dependent on the signal constellation rotation when QN due to the ADC is dominant. The newly derived expressions are then used to investigate the impact of constellation rotation on the system BER performance. It is shown that considerable performance gains can be achieved with an appropriate rotation of the signal constellation.
Accurate And Efficient Global Approximation using Adaptive Polynomial RSM for Complex Mechanical and Vehicular Performance Models

— Global approximation using metamodel for complex mathematical function or computer model over a large variable domain is often needed in sensibility analysis, computer simulation, optimal control, and global design optimization of complex, multiphysics systems. To overcome the limitations of the existing response surface (RS), surrogate or metamodel modeling methods for complex models over large variable domain, a new adaptive and regressive RS modeling method using quadratic functions and local area model improvement schemes is introduced. The method applies an iterative and Latin hypercube sampling based RS update process, divides the entire domain of design variables into multiple cells, identifies rougher cells with large modeling error, and further divides these cells along the roughest dimension direction. A small number of additional sampling points from the original, expensive model are added over the small and isolated rough cells to improve the RS model locally until the model accuracy criteria are satisfied. The method then combines local RS cells to regenerate the global RS model with satisfactory accuracy. An effective RS cells sorting algorithm is also introduced to improve the efficiency of model evaluation. Benchmark tests are presented and use of the new metamodeling method to replace complex hybrid electrical vehicle powertrain performance model in vehicle design optimization and optimal control are discussed.