Miracle-dz/UniFAR-FTUs huggingface dataset:
Field- and Lab-Based Potentiometric Titrations of Microbial Mats from the Fairmont Hot Spring, Canada

ABSTRACT Potentiometric titrations are an effective tool to constrain the protonation constants and site concentrations for microbial surface ligands. Protonation models developed from these experiments are often coupled with data from metal adsorption experiments to calculate microbial ligand-metal binding constants. Ultimately, the resulting surface complexation models can be used to predict metal immobilization behavior across diverse chemical conditions. However, most protonation and metal-ligand thermodynamic constants have been generated in laboratory experiments that use cultured microbes which may differ in their chemical reactivity from environmental samples. In this study, we investigate the use of in situ field potentiometric titrations of microbial mats at a carbonate hot spring located at Fairmont Hot Springs, British Columbia, with the aim to study microbial reactivities in a natural field system. We found that authigenic carbonate minerals complicated the potentiometric titration process due to a “carbonate spike” introduced by the contribution of inorganic carbonate mineral dissolution and subsequent carbonate speciation changes during the transition from low to high pH. This inhibits the determination of microbial surface ligand variety and concentrations. Our preliminary study also highlights the need for developing novel probes to quantify in situ microbial mat reactivity in future field investigations.
A Convolutional Neural Network for Aspect Sentiment Classification

With the development of the Internet, natural language processing (NLP), in which sentiment analysis is an important task, became vital in information processing.Sentiment analysis includes aspect sentiment classification. Aspect sentiment can provide complete and in-depth results with increased attention on aspect-level. Different context words in a sentence influence the sentiment polarity of a sentence variably, and polarity varies based on the different aspects in a sentence. Take the sentence, 'I bought a new camera. The picture quality is amazing but the battery life is too short. 'as an example. If the aspect is picture quality, then the expected sentiment polarity is 'positive', if the battery life aspect is considered, then the sentiment polarity should be 'negative'; therefore, aspect is important to consider when we explore aspect sentiment in the sentence. Recurrent neural network (RNN) is regarded as a good model to deal with natural language processing, and RNNs has get good performance on aspect sentiment classification including Target-Dependent LSTM (TD-LSTM) ,Target-Connection LSTM (TC-LSTM) (Tang, 2015a, b), AE-LSTM, AT-LSTM, AEAT-LSTM (Wang et al., 2016). There are also extensive literatures on sentiment classification utilizing convolutional neural network, but there is little literature on aspect sentiment classification using convolutional neural network. In our paper, we develop attention-based input layers in which aspect information is considered by input layer. We then incorporate attention-based input layers into convolutional neural network (CNN) to introduce context words information. In our experiment, incorporating aspect information into CNN improves the latter's aspect sentiment classification performance without using syntactic parser or external sentiment lexicons in a benchmark dataset from Twitter but get better performance compared with other models.
Structural Analysis of Phosphoserine Aminotransferase (Isoform 1) From Arabidopsis thaliana– the Enzyme Involved in the Phosphorylated Pathway of Serine Biosynthesis

Phosphoserine aminotransferase (PSAT) is a pyridoxal 5′-phosphate (PLP)-dependent enzyme that catalyzes the conversion of 3-phosphohydroxypyruvate (3-PHP) to 3-phosphoserine (PSer) in an L-glutamate (Glu)-linked reversible transamination reaction. This process proceeds through a bimolecular ping–pong mechanism and in plants takes place in plastids. It is a part of the phosphorylated pathway of serine biosynthesis, one of three routes recognized in plant organisms that yield serine. In this three-step biotransformation, 3-phosphoglycerate (3-PGA) delivered from plastidial glycolysis and Calvin cycle is oxidized by 3-PGA dehydrogenase. Then, 3-PHP is subjected to transamination with Glu to yield PSer and α-ketoglutarate (AKG). In the last step of the pathway, serine is produced by the action of phosphoserine phosphatase. Here we present the structural characterization of PSAT isoform 1 from Arabidopsis thaliana (AtPSAT1), a dimeric S-shaped protein that truncated of its 71-residue-long chloroplast-targeting signal peptide. Three crystal structures of AtPSAT1 captured at different stages of the reaction: (i) internal aldimine state with PLP covalently bound to the catalytic K265, (ii) holoenzyme in complex with pyridoxamine-5′-phosphate (PMP) after transfer of the amino group from glutamate and (iii) the geminal diamine intermediate state wherein the cofactor is covalently bound to both, K265 and PSer. These snapshots over the course of the reaction present detailed architecture of AtPSAT1 and allow for the comparison of this plant enzyme with other PSATs. Conformational changes of the protein during the catalytic event concern (i) the neighborhood of K265 when the amino group is transferred to the cofactor to form PMP and (ii) movement of the gate-keeping loop (residues 391–401) upon binding of 3-PHP and PSer. The latter conformational change of the loop may likely be one of key elements that regulate catalytic activity of PSATs.
Parkinson ’ s Disease and Lewy Body Dementia and Driving : A Review of the Literature

There is significant research about Parkinson’s disease and driving, however, very little is known about Lewy Body dementia and driving ability, though the two diseases are closely linked. The purpose of this study was to review the literature about Parkinson’s disease and driving and Lewy Body dementia and driving. Articles from 1993-2013 that were published in English, used human data, and made a connection between Lewy body dementia and driving or Parkinson’s disease and driving were used in the final review. The following databases were searched: EBSCOhost, PubMed, Google Scholar, Proquest, Web of Knowledge, and Publishing Connect. One article about Lewy Body dementia and driving was located that met the inclusion criteria, whereas 21 articles met the inclusion criteria for Parkinson’s disease and driving. Results indicate that drivers with Parkinson’s disease perform poorly behind the wheel compared to healthy matched controls, thus fitness to drive should be questioned.
Reach‐averaged sediment routing model of a canyon river

Spatial complexity in channel geometry indicates that accurate prediction of sediment transport requires modeling in at least two dimensions. However, a one‐dimensional model may be the only practical or possible alternative, especially for longer river reaches of practical concern in river management or landscape modeling. We have developed a one‐dimensional model of the Colorado River through upper Grand Canyon that addresses this problem by reach averaging the channel properties and predicting changes in sand storage using separate source and sink functions coupled to the sand routing model. The model incorporates results from the application of a two‐dimensional model of flow, sand transport, and bed evolution, and a new algorithm for setting the near‐bed sand boundary condition for sand transported over an exposed bouldery bed. Model predictions were compared to measurements of sand discharge during intermittent tributary inputs and varying discharges controlled by dam releases. The model predictions generally agree well with the timing and magnitude of measured sand discharges but tend to overpredict sand discharge during the early stages of a high release designed to redistribute sand to higher‐elevation deposits.
LOCAL VARIABILITY IN THE ORBIT OF SATURN'S F RING

We present an analysis of the orbit of Saturn's F ring using images recorded by the Imaging Science Subsystem of the Cassini spacecraft. A total of 9805 observations have been made from 10 image sequences obtained between 2006 November 23 and 2009 July 28. Each sequence of up to 240 images spans a single orbit of the F ring, allowing 10 independent high-precision estimates of the ring orbit to be made over this ∼3 year period. The ring has been modeled as an inclined uniformly precessing ellipse. The results show a variability in the orbital elements with, for example, the semi-major axis scattered between 140211.2 ± 0.1 km and 140232.9 ± 0.4 km and the fitted periapses locked to the value obtained from a combined fit using the entire three-year span of observations. We show that the observed scatter between the individual estimates of the ring orbit reflect the differing past histories of the particular segments of ring being fitted and that the values are scattered within the limits expected from a single gravitational encounter with the nearby moon, Prometheus. In the combined fit, the scatter averages out to reveal a small systematic bias with respect to the results of Bosh et al. and Albers et al. We believe this is a consequence of the proximity of Prometheus to the ring in the image sequences chosen for this analysis. Finally, we note a close empirical commensurability between the apsidal precession rate, , of the F ring and the synodic period between Prometheus and the F ring, such that nProm − nFring ≈ 2, where nProm and nFring are the mean motions, and discuss its implications.
Effects of Different Treatment Strategies and Tumor Stage on Survival of Patients with Advanced Laryngeal Carcinoma: A 15-Year Cohort Study

Background Laryngeal cancer is the second most common cancer in the head and neck. Since laryngeal cancer management is a complex process, there is still no standard strategy to treat this disease in order to increase the survival rate of the patients especially among those with advanced form of the disease. Methods A cohort study was undertaken to analyze factors predicting survival of the patients in advanced stage laryngeal cancer in the Southern Iran among all patients newly diagnosed with laryngeal cancer between 2000 and 2015. Results Data of a total number of 415 patients who have had been diagnosed with advanced laryngeal cancer during this period was used for analysis. The patients' 1-, 3-, 5-, and 10-year survival rates were 81%, 62%, 53%, and 38%, respectively. Multivariable Cox regression analyses indicated a significant relationship between patients' survival and age at diagnosis (P < 0.001), disease stage (P = 0.002), tumor grade (P = 0.008), positive L. node (P = 0.008), and type of treatment (P < 0.001). As expected, treatment strategy was identified as the most effective factor in survival of the patients. According to the results, patients who undergone surgical treatment experienced a longer survival than those who received other treatments. Conclusion This study showed that the survival of patients depends on several factors, among which, treatment strategy is the most important. Combination of total laryngectomy plus chemoradiation provides superior local control and better survival compared to either radiotherapy or chemoradiation in patients with advanced laryngeal cancer.
Exploring the Impact of Strategic Proactivity on Perceived Corporate Social Responsibility in Nigeria’s Petroleum Industry: A Structural Equation Modeling Approach

In the past few years, there has been a gradual re-orientation taking place in the relationship between business and society in the Nigerian petroleum industry. The re-emergence of democracy has led to an increased awareness about the role of oil companies in their host-communities. Oil companies are aware of this, and have devoted increased effort towards contributing to their host-communities. Despite the fact that, of recent, these oil companies are contributing more than ever, there is an increase in the conflict between these companies and the stakeholders in their host-communities. This is threatening their sustainability. This problem highlights a gap in theory and practice of CSR. In recent times, there have been calls for shift of scholarly focus towards a performance based CSR theory and practice. This paper empirically tested this performance based perspective by exploring the interactive process that leads to CSR outcomes. This was done through a quantitative research study. 623 members of Eket and Ibeno youth councils took part in a survey from which 591 valid samples were generated. A structural equation modelling (SEM) statistical technique was employed. The results showed a positive relationship between strategic proactivity and perceived CSR, with perceived economic value dimension demonstrating partial mediating impact on the relationship.
Feelings and Perceptions of Happiness and Sadness Induced by Music: Similarities, Differences, and Mixed Emotions

The authors examined similarities and differences between (1) listeners’ perceptions of emotions conveyed by 30-s pieces of music and (2) their emotional responses to the same pieces. Using identical scales, listeners rated how happy and how sad the music made them feel, and the happiness and the sadness expressed by the music. The music was manipulated to vary in tempo (fast or slow) and mode (major or minor). Feeling and perception ratings were highly correlated but perception ratings were higher than feeling ratings, particularly for music with consistent cues to happiness (fast-major) or sadness (slow-minor), and for sad-sounding music in general. Associations between the music manipulations and listeners’ feelings were mediated by their perceptions of the emotions conveyed by the music. Happiness ratings were elevated for fast-tempo and major-key stimuli, sadness ratings were elevated for slow-tempo and minor-key stimuli, and mixed emotional responses (higher happiness and sadness ratings) were elevated for music with mixed cues to happiness and sadness (fast-minor or slow-major). Listeners also exhibited ambivalence toward sad-sounding music.
Part of the Package

Where does masculinity come from? How is masculinity expressed? How is it perceived? What does it mean to be masculine or to have masculinity? The definition of masculinity remains elusive. While typically (though not always), maleness is conferred with the penis—anaccidentof birth—masculinityis often held to be “difficult to achieve. ” Rites of passage, behavioral conventions, social roles, and political institutions have all been examined as sources for the production of masculinity. Female-to-male (FTM) transgendered and transsexual individuals, sometimes also called transmen, do not follow the traditional prescriptive paths to maleness, yet they often possess an undeniable masculinity. Through personal observation, literature review, and survey research, this article explores some of the concepts and embodiments of masculinity that are manifest among transmen. Some additional sources are Halberstam (Female Masculinity), Devor (Gender Blending), and Cromwell (Transmen and FTMs). These works are contrasted with that of various masculinity scholars.
Therapeutic effects of providing MMPI-2 test feedback to college students awaiting therapy.

This study investigated the benefits of sharing Minnesota Multiphasic Personality Inventory-2 (MMPI-2) test results verbally with clients. Ss were randomly selected from a college counseling center's waiting list: 32 received test feedback according to a collaborative model developed by Finn (1990) and 29 received only examiner attention. Groups did not differ on age, sex, days between examiner contact, and initial levels of distress and self-esteem
Biological Effects of Oil-in-ice in the Arctic

Given the reluctance to conduct large-scale oil spill experiments in ice and the good fortune not to have spills of opportunity to study, it should not be surprising that our knowledge of the fate of oil in ice is limited, and our understanding of the effects of the oil on the epontic (sea ice) biota is even more restricted. Many questions remain about transport rates of various hydrocarbon components through sea ice. Results to date on the effects on the microbial communities are mixed. Biodiversity has been found to increase and decrease, cell counts have increased and decreased, and photosynthetic rates increase and decrease. Some of the conflicting results may be due to the findings coming from a mixture of laboratory and in-situ results. The impact of oil-in-ice on zooplankton appears to depend on the species, the characteristics of the oil, and environmental factors. Recent work has focused on standardizing tests to ensure results between experiments are comparable. The complexities of the winter ice habitat are difficult to recreate and need to be considered when interpreting the results.
Dividends and Taxes in the UK

The tax treatment of company dividend payments is an area where corporate taxation interacts with the personal income tax. This interaction raises some awkward issues, such as whether shareholders who are exempt from personal income tax should also be exempt from corporation tax, and if so, then how this can be achieved. The solutions adopted are often complex and certainly diverse, as witnessed by the range of different approaches used in the OECD countries, described in OECD (1991). Since 1973, the UK has operated a partial imputation system, under which some tax relief on dividend income is given to all shareholders in recognition of corporation tax paid by the firm. For taxpaying shareholders, part of the corporation tax charge is credited against their income tax liability on dividend income; for taxexempt shareholders, this credit is paid to them in cash by the Inland Revenue. Taxexempt shareholders include pension funds and the pension component of insurance companies. This approach certainly has some merits, but one problem is that this tax relief is only available for the part of company profits that is paid out to
Multiple Mode SAR Raw Data Simulation and Parallel Acceleration for Gaofen-3 Mission

Gaofen-3 is China's first meter-level multipolarization synthetic aperture radar (SAR) satellite with 12 imaging modes for the scientific and commercial applications. In order to evaluate the imaging performance of these modes, the multiple mode SAR raw data simulation is highly demanded. In the paper, the multiple mode SAR simulation framework will be briefly introduced to expose how the raw data simulation guarantees the development of Gaofen-3 and its ground processing system. As an engineering simulation, the complex working modes and practical evaluation requirements of Gaofen-3 mission put forward to the higher demand for simulation simplification and data input/output (I/O) efficiency. To meet the requirements, two improvements have been proposed. First, the stripmap mode based multiple mode decomposition method is introduced to make a solid and simplified system simulation structure. Second, the cloud computing and graphics processing unit (GPU) are integrated to simulate the practical huge volume raw data, resulting in improved calculation and data I/O efficiency. The experimental results of sliding spotlight imaging prove the effectiveness of the Gaofen-3 mission simulation framework and the decomposition idea. The results for efficiency assessment show that the GPU cloud method greatly improves the computing power of a 16-core CPU parallel method about $40\times$ speedup and the data throughput with the Hadoop distributed file system. These results prove that the simulation system has the merits of coping with multiple modes and huge volume raw data simulation and can be extended to the future space-borne SAR simulation.
Non-Local Graph Convolutional Networks for Skeleton-Based Action Recognition

Traditional deep methods for skeleton-based action recognition usually structure the skeleton as a coordinates sequence or a pseudo-image to feed to RNNs or CNNs, which cannot explicitly exploit the natural connectivity among the joints. Recently, graph convolutional networks (GCNs), which generalize CNNs to more generic non-Euclidean structures, obtains remarkable performance for skeleton-based action recognition. However, the topology of the graph is set by hand and fixed over all layers, which may be not optimal for the action recognition task and the hierarchical CNN structures. Besides, the first-order information (the coordinate of joints) is mainly used in former GCNs, while the second-order information (the length and direction of bones) is less exploited. In this work, a novel two-stream nonlocal graph convolutional network is proposed to solve these problems. The topology of the graph in each layer of the model can be either uniformly or individually learned by BP algorithm, which brings more flexibility and generality. Meanwhile, a two-stream framework is proposed to model both of the joints and bones information simultaneously, which further boost the recognition performance. Extensive experiments on two large-scale datasets, NTU-RGB+D and Kinetics, demonstrate the performance of our model exceeds the state-of-the-art by a significant margin.
Per-decision Multi-step Temporal Difference Learning with Control Variates

Multi-step temporal difference (TD) learning is an important approach in reinforcement learning, as it unifies one-step TD learning with Monte Carlo methods in a way where intermediate algorithms can outperform either extreme. They address a bias-variance trade off between reliance on current estimates, which could be poor, and incorporating longer sampled reward sequences into the updates. Especially in the off-policy setting, where the agent aims to learn about a policy different from the one generating its behaviour, the variance in the updates can cause learning to diverge as the number of sampled rewards used in the estimates increases. In this paper, we introduce per-decision control variates for multi-step TD algorithms, and compare them to existing methods. Our results show that including the control variates can greatly improve performance on both on and off-policy multi-step temporal difference learning tasks.
Phylogeny of Syrphidae (Diptera) inferred from combined analysis of molecular and morphological characters

Syrphidae (Diptera) commonly called hoverflies, includes more than 5000 species world-wide. The aim of this study was to address the systematic position of the disputed elements in the intrafamilial classification of Syrphidae, namely the monophyly of Eristalinae and the placement of Microdontini and Pipizini, as well as the position of particular genera (Nausigaster, Alipumilio, Spheginobaccha). Sequence data from nuclear 28S rRNA and mitochondrial COI genes in conjunction with larval and adult morphological characters of fifty-one syrphid taxa were analysed using optimization alignment to explore phylogenetic relationships among included taxa. A species of Platypezidae, Agathomyia unicolor, was used as outgroup, and also including one representative (Jassidophaga villosa) of the sister-group of Syrphidae, Pipunculidae. Sensitivity of the data was assessed under six different parameter values. A stability tree sum- marized the results. Microdontini, including Spheginobaccha, was placed basally, and Pipizini appeared as the sister-group to subfamily Syrphinae. The monophyly of subfamily Eristalinae was supported. The results support at least two independ- ent origins of entomophagy in syrphids, and frequent shifts between larval feeding habitats within the saprophagous eristalines.