Miracle-dz/UniFAR-FTUs huggingface dataset:
Facile and Selective Synthetic Approach for Ruthenium Complexes Utilizing a Molecular Sieve Effect in the Supporting Ligand

It is extremely important for synthetic chemists to control the structure of new compounds. We have constructed ruthenium-based mononuclear complexes with the tridentate 2,6-di(1,8-naphthyridin-2-yl)pyridine (dnp) ligand to investigate a new synthetic approach using a specific coordination space. The synthesis of a family of new ruthenium complexes containing both the dnp and triphenylphosphine (PPh3) ligands, [Ru(dnp)(PPh3)(X)(L)]n+ (X = PPh3, NO2−, Cl−, Br−; L = OH2, CH3CN, C6H5CN, SCN−), has been described. All complexes have been spectroscopically characterized in solution, and the nitrile complexes have also been characterized in the solid state through single-crystal X-ray diffraction analysis. Dnp in the present complex system behaves like a “molecular sieve” in ligand replacement reactions. Both experimental data and density functional theory (DFT) calculations suggest that dnp plays a crucial role in the selectivity observed in this study. The results provide useful information toward elucidating this facile and selective synthetic approach to new transition metal complexes.
Spatial distribution of copper in relation to recreational boating in a California shallow-water basin

The overall effect of the number of boats on the copper (Cu) levels in the water column and sediment, along with their spatial variability within Shelter Island Yacht Basin (SIYB), San Diego Bay, California was examined. We identified a horizontal gradient of increasing dissolved Cu and Cu in sediment from outside to the head of SIYB which was coincident with the increasing number of boats. Spatial models of Cu distribution in water and sediment indicated the presence of ‘hotspots’ of Cu concentration. From outside to the head of SIYB, dissolved Cu ranged from 1.3 μ g L−1 to 14.6 μ g L−1 in surface water, and 2.0 μ g L−1 to 10.2 μ g L−1 in bottom water. Cu in sediment exceeded the Effect Range Low of 34 mg kg−1 (i.e. where adverse effects to fauna may occur), with a peak concentration of 442 mg kg−1 at the head of the basin. Free Cu++ in surface water was several orders of magnitude higher than in sediment porewater. High-resolution data of Cu species together with probability maps presented in this paper will allow managers to easily visualise and localise areas of impaired quality and to prioritise which areas should be targeted to improve Cu-related conditions.
Evaluation of total choline from in-vivo volume localized proton MR spectroscopy and its response to neoadjuvant chemotherapy in locally advanced breast cancer

Results of the proton magnetic resonance spectroscopy carried out on normal, benign breast disease and locally advanced breast cancer patients are presented. The in-vivo MR spectra of malignant breast tissue of patients (n = 67) suffering from infiltrating ductal carcinoma are dominated by the water resonance, while the spectra of the unaffected contralateral breast tissue of these patients are mainly dominated by resonance arising from lipids which is similar to the spectra of normal breast tissue obtained from volunteers (controls, n = 16). In addition to the water and lipid peaks, in majority of the patients (∼80%) the water suppressed spectra showed a resonance at 3.2 ppm due to choline containing compounds (TCho) before treatment. In patients receiving neoadjuvant chemotherapy, absence/reduction in choline was observed in 89% of the patients. TCho was also observed in 2 of 14 benign lesions. The sensitivity and specificity of in-vivo MRS in detecting TCho in malignant tumours was 78% and 86%, respectively. Observation of TCho before treatment and its disappearance (or reduction) after treatment may be a useful indicator of response of locally advanced breast cancer to neoadjuvant chemotherapy. © 2001 Cancer Research Campaign
Research Paper: A Rule-based Approach for Identifying Obesity and Its Comorbidities in Medical Discharge Summaries

OBJECTIVE Evaluate the effectiveness of a simple rule-based approach in classifying medical discharge summaries according to indicators for obesity and 15 associated co-morbidities as part of the 2008 i2b2 Obesity Challenge. METHODS The authors applied a rule-based approach that looked for occurrences of morbidity-related keywords and identified the types of assertions in which those keywords occurred. The documents were then classified using a simple scoring algorithm based on a mapping of the assertion types to possible judgment categories. MEASUREMENTS RESULTS for the challenge were evaluated based on macro F-measure. We report micro and macro F-measure results for all morbidities combined and for each morbidity separately. Results Our rule-based approach achieved micro and macro F-measures of 0.97 and 0.77, respectively, ranking fifth out of the entries submitted by 28 teams participating in the classification task based on textual judgments and substantially outperforming the average for the challenge. CONCLUSIONS As shown by its ranking in the challenge results, this approach performed relatively well under conditions in which limited training data existed for some judgment categories. Further, the approach held up well in relation to more complex approaches applied to this classification task. The approach could be enhanced by the addition of expert rules to model more complex medical reasoning.
Dynamics of CD8+ T Cell Responses during Acute and Chronic Lymphocytic Choriomeningitis Virus Infection1

Infection of mice with lymphocytic choriomeningitis virus (LCMV) is frequently used to study the underlying principles of viral infections and immune responses. We fit a mathematical model to recently published data characterizing Ag-specific CD8+ T cell responses during acute (Armstrong) and chronic (clone 13) LCMV infection. This allows us to analyze the differences in the dynamics of CD8+ T cell responses against different types of LCMV infections. For the four CD8+ T cell responses studied, we find that, compared with the responses against acute infection, responses against chronic infection are generally characterized by an earlier peak and a faster contraction phase thereafter. Furthermore, the model allows us to give a new interpretation of the effect of thymectomy on the dynamics of CD8+ T cell responses during chronic LCMV infection: a smaller number of naive precursor cells is sufficient to account for the observed differences in the responses in thymectomized mice. Finally, we compare data characterizing LCMV-specific CD8+ T cell responses from different laboratories. Although the data were derived from the same experimental model, we find quantitative differences that can be solved by introducing a scaling factor. Also, we find kinetic differences that are at least partly due to the infrequent measurements of CD8+ T cells in the different laboratories.
How Has Financial Liberalization A ected Emerging Markets ' External Capital Structure ? An Explanation of the Link between Financial Openness , Sudden Stops and External Balances ∗

This paper argues that occasionally binding borrowing limits and non-trivial equity trading costs signi cantly increase the probability of a Sudden Stop post nancial liberalization, which in turn, signi cantly alters the long run external capital structure of an emerging market economy. Upon opening the capital account, agents in the emerging market have an incentive to accumulate debt and sell domestic equity in order to share risk with the rest of the world. Due to a lower cost of capital, equity prices spike allowing agents to accumulate a relatively large amount of debt without being constrained in the near term. As domestic agents accumulate debt and sell equity to re-balance their portfolio, however, adjustment costs force equity prices to subsequently fall. With a lower value of equity, agents within the emerging market face a greater risk of hitting their "margin requirement", triggering a debt de ation crisis. In the long run, the probability of a sudden stop is small as agents accumulate pre-cautionary savings to avoid the sudden stop. However, the adjustment of the external capital structure is permanent. Calibrating the model to Mexico, we solve numerically for the transitional dynamics of a small closed economy as it opens and match both qualitatively and quantitatively the simulated dynamics to the data. JEL Codes:
Very short-term demand forecasting for fused magnesium furnaces based on specific penalty function

As the manufacturing equipment of the refractory-fused magnesia, fused magnesium furnace (FMF) has the following characteristics: huge power consumption, peak load impact and strong fluctuations. During the smelting process, the total load of the FMF group often produce electricity demand spikes, which are unfavorable to the production. More seriously, the demand may exceed the contract value and this case will affect the safe operation of the furnace and grid. As the randomness of the furnace, in different working conditions, increases the uncertainty of the demand of FMF group, accurate demand forecasting is very important for monitoring the demand trends. In order to meet the asymmetric requirements for forecasting error, this paper presents a asymmetrical penalty function, uses a combination of methods BAT-RBF to design the predictor, in which the BAT algorithm are used to optimize the weight coefficients of the RBF network. In addition, some experiments based on the field data of Liaoning, by comparison with other methods, demonstrates the effectiveness and feasibility of the proposed method.
Labor Market Returns, Marriage Opportunities, or the Education System? Explaining Gender Differences in Numeracy in Indonesia

This paper measures the evolution of the gender differences in numeracy among school age children using a longitudinal dataset from Indonesia. A unique feature of the dataset is that it uses an identical test for two survey rounds, which implies that any changes in the gender gap are caused by actual changes in numeracy. To my knowledge, this is the first study that is able to distinguish actual changes in numeracy from changes in the difficulty of the tests. I find that girls outperform boys by 0.09 standard deviations when the sample was around 11 years old. Seven years later, the gap has increased to 0.19 standard deviations. This gap is equivalent to around 18 months of schooling. I find evidence for two explanations for the widening gap. The first is that households invest more resources in girls relative to boys. This behavior appears to be rational, driven by the higher labor market returns to numeracy for girls than for boys. In contrast, I find no marriage market returns to numeracy for either gender. The second explanation is that the Indonesian education system appears to play some role in promoting the gender gap. A particular source of this appears to be the teachers, as the gender gap in numeracy only occurs in schools where more than half of the teachers are female.
Human upper body identification from images

Estimating human pose in static images is challenging due to the high dimensional state space, presence of image clutter and ambiguities of image observations. In this paper we propose a method to automatically segment human subjects in images, based on dominant colors, and given the face captured by a face detector. The posture is estimated using a 2D model combined with anthropometric data. Experimental results showed that the proposed technique performs well in non trivial images.
Molecular Characterization of LjABCG1, an ATP-Binding Cassette Protein in Lotus japonicus

LjABCG1, a full-size ABCG subfamily of ATP-binding cassette proteins of a model legume, Lotus japonicus, was reported as a gene highly expressed during the early stages of nodulation, but have not been characterized in detail. In this study we showed that the induction of LjABCG1 expression was remarkable by methyl jasmonate treatment, and reporter gene experiments indicated that LjABCG1 was strongly expressed in the nodule parenchyma and cell layers adjacent to the root vascular tissue toward the nodule. LjABCG1 was suggested to be localized at the plasma membrane based on the fractionation of microsomal membranes as well as separation via aqueous two-phase partitioning. The physiological functions of LjABCG1 in symbiosis and pathogenesis were analyzed in homologous and heterologous systems. LjABCG1 knock-down L. japonicus plants did not show clear phenotypic differences in nodule formation, and not in defense against Pseudomonas syringae, either. In contrast, when LjABCG1 was expressed in the Arabidopsis pdr8-1 mutant, the penetration frequency of Phytophthora infestans, a potato late blight pathogen, was significantly reduced in LjABCG1/pdr8-1 than in pdr8-1 plants. This finding indicated that LjABCG1, at least partially, complemented the phenotype of pdr8 in Arabidopsis, suggesting the multiple roles of this protein in plant-microbe interactions.
Simultaneous localization and scene reconstruction with monocular camera

In this paper, we propose an online scene reconstruction algorithm with monocular camera since there are many advantages on modeling and visualization of an environment with physical scene reconstruction instead of resorting to sparse 3D points. The goal of this algorithm is to simultaneously track the camera position and map the 3D environment, which is close to the spirit of visual SLAM. There're plenty of visual SLAM algorithms in the current literature which can provide a high accuracy performance, but many of them rely on stereo cameras. It's true that we'll face many more challenges to accomplish this task with monocular camera. However, the advantages of cheaper and easier deployable hardware setting have made monocular approach more attractive. Specifically, we apply a maximum a posteriori Bayesian approach with optimization technique to simultaneously track the camera and build a dense point cloud. We also propose a feature expansion method to expand the density of points, and then online reconstruct the scene with a delayed approach. Furthermore, we utilize the reconstructed model to accomplish visual localization task without extracting the features. Finally, a number of experiments have been conducted to validate our proposed approach, and promising performance can be observed.
Towards discriminative lexicon optimization

A lot of work has been done in deriving the pronunciation dictionary automatically from training data. These attempts focussed mainly on maximum likelihood or similar techniques. Due to the complexity and variability of the pronunciation process it is di cult to nd an adequate pronunciation model. The model will deviate from the truth. Hence, the application of maximum likelihood techniques is likely to be suboptimal. For this reason we present an approach, where the pronunciation model is learned discriminatively from data. The corresponding theory utilizes (1) probabilistic weighting of pronunciation variants of words and (2) discriminative model combination (DMC) based on Viterbi-approximations. We will show that the derived theory adjusts the weighting of pronunciation variants with respect to the word error rate, to the frequency of occurence of the speci c pronunciation in the training data, and to the likelihood of the acoustic observation sequence given the pronunciation.
Block-delayed partitioned Viterbi algorithm BD-PVA

A new block-delayed partitioned Viterbi algorithm (BD-PVA) receiver for the MIMO frequency-selective fading channel is proposed. The classic PVA has a trellis detector for each transmit antenna and feeds back tentative decisions between these trellis detectors. The proposed algorithm uses more reliable temporary decisions in the feedback loop instead of the tentative decisions, thus resulting in an improved BER performance. MIMO systems with higher number of antennas exhibit a more remarkable BER performance improvement since they rely more on the feedback between the trellis detectors.
Prevention of otitis media by adenoidectomy in children younger than 2 years.

OBJECTIVES To test the effect of adenoidectomy in connection with tympanostomy compared with tympanostomy only in preventing otitis media in children younger than 2 years. DESIGN Prospective trial with randomized and nonrandomized arms. SETTING Primary care study clinics. PARTICIPANTS AND INTERVENTIONS The study participants were selected from 2497 children who had been enrolled in the Finnish Otitis Media Vaccine Trial at the age of 2 months. A total of 306 children, aged 1 to 2 years, who had experienced recurrent episodes of otitis media were randomized into 2 treatment groups: tympanostomy with or without adenoidectomy. Of the 306 children, 137 were operated on according to random basis (randomized trial). The 169 children whose parents declined participation in the randomized trial were operated on according to the parents' preferences (nonrandomized trial). All children were followed up until 2 years of age. The mean follow-up time was 7 months. MAIN OUTCOME MEASURE The rate of acute otitis media episodes. RESULTS The average reduction in the rate of all acute otitis media episodes in the adenoidectomy group was 19% (95% confidence interval [CI], -14% to 43%) among children enrolled in the randomized trial and 25% (95% CI, -13% to 50%) in the nonrandomized trial. The reduction in the randomized trial was mainly due to reduction in the rate of pneumococcal otitis media (58%, 95% CI, 16%-79%). CONCLUSION In children younger than 2 years, concurrent adenoidectomy during the insertion of tympanostomy tubes does not seem to have a major advantage over the insertion of tympanostomy tubes alone in preventing otitis media.
Modulation by estradiol of serotonin receptors in brain

Estrogens were found to exert a biphasic effect on the density of serotonin receptors in the female rat brain: an acute reduction in serotonin receptor density throughout the brain is followed 48 to 72 hr later by a selective increase in those brain regions known to contain estrogen receptors--hypothalamus, preoptic area, and amygdala. The acute reduction in serotonin receptor density can be mimicked by estradiol in vitro. We conclude that estradiol may have a fast, direct effect on brain membranes to modify serotonin receptor availability, while exerting a slow effect on the same receptors through an interaction with intracellular estrogen receptors in those brain regions that contain them. The observation that female sex hormones are involved in the regulation of serotonin receptors may have important implications in the understanding of female sexual behavior in the female rat and in the understanding of hormone-linked emotional disturbances in women.
COPII–Golgi protein interactions regulate COPII coat assembly and Golgi size

Under experimental conditions, the Golgi apparatus can undergo de novo biogenesis from the endoplasmic reticulum (ER), involving a rapid phase of growth followed by a return to steady state, but the mechanisms that control growth are unknown. Quantification of coat protein complex (COP) II assembly revealed a dramatic up-regulation at exit sites driven by increased levels of Golgi proteins in the ER. Analysis in a permeabilized cell assay indicated that up-regulation of COPII assembly occurred in the absence GTP hydrolysis and any cytosolic factors other than the COPII prebudding complex Sar1p–Sec23p–Sec24p. Remarkably, acting via a direct interaction with Sar1p, increased expression of the Golgi enzyme N-acetylgalactosaminyl transferase-2 induced increased COPII assembly on the ER and an overall increase in the size of the Golgi apparatus. These results suggest that direct interactions between Golgi proteins exiting the ER and COPII components regulate ER exit, providing a variable exit rate mechanism that ensures homeostasis of the Golgi apparatus.
DiMLex: A Lexicon of Discourse Markers for Text Generation and Understanding

Discourse markers ('cue words') are lexical items that signal the kind of coherence relation holding between adjacent text spans; for example, because, since, and for this reason are different markers for causal relations. Discourse markers are a syntactically quite heterogeneous group of words, many of which are traditionally treated as function words belonging to the realm of grammar rather than to the lexicon. But for a single discourse relation there is often a set of similar markers, allowing for a range of paraphrases for expressing the relation. To capture the similarities and differences between these, and to represent them adequately, we are developing DiMLex, a lexicon of discourse markers. After describing our methodology and the kind of information to be represented in DiMLex, we briefly discuss its potential applications in both text generation and understanding.
Compressing Large Amounts of NetFlow Data Using a Pattern Classification Scheme

The storage of large amounts of network data is a challenging problem, in particular if it still needs to be actively consulted as for example in the case of network forensics. Here we propose a method to compress NetFlow data while simultaneously adding domain knowledge. Our method is based on a pattern classification scheme by considering all flows from a single source IP address simultaneously. Each pattern can be described by at most 19 attributes that give a good statistical description of the original NetFlow data, while minimising information loss. We estimate that on average a factor of about 300 in storage space can be gained. The process is explained using a real world dataset from a large, high-speed, network, and a formal rationale is provided.
Evaluating goal ordering structures for testing harbour security policies

Large, complex systems can exhibit unforeseen behaviours. In the case of surveillance and security systems, these behaviours can be weaknesses that should be discovered by automated testing and ameliorated. Previous work has shown that such automated testing can be done using particle swarm optimization to learn behaviours that allow a set of attackers to defeat the system. However, for the optimization to succeed, it must have some knowledge about what constitutes a successful attack in order to guide the swarm. This knowledge is encapsulated in a goal ordering structure. In this paper, we examine the goal ordering structure and its role in the learning of system weakness. We specifically look at applications in harbour surveillance and security, and show how knowledge of the likely properties of a successful attack can be added to the goal ordering structure. Our experimental results show that adding knowledge to the goal ordering structure improves the search, when that knowledge is correctly inserted into the structure.
Distributed control of wireless ad-hoc networks connectivity incorporating realistic channel models

In this paper, we propose a distributed method to control the connectivity of wireless ad hoc networks taking into account the impairments resulting from the propagation through realistic channel models incorporating fading, noise and packet collision. We illustrate a mechanism to estimate the algebraic connectivity of the expected graph and we show that the method is robust against random packet drops. Then, we show how the algebraic connectivity of the expected graph Laplacian depends on the transmit power of each node. The interesting result is that there exists an optimal power that maximizes the algebraic connectivity, as a tradeoff between the degree of each node and the number of collisions. Finally, we propose a distributed algorithm to evaluate the optimal transmission power that maximizes the network connectivity in the presence of realistic MAC protocols.