Miracle-dz/UniFAR-FTUs huggingface dataset:
pH-driven shifts in overall and transcriptionally active denitrifiers control gaseous product stoichiometry in growth experiments with extracted bacteria from soil

Soil pH is a strong regulator for activity as well as for size and composition of denitrifier communities. Low pH not only lowers overall denitrification rates but also influences denitrification kinetics and gaseous product stoichiometry. N2O reductase is particularly sensitive to low pH which seems to impair its activity post-transcriptionally, leading to higher net N2O production. Little is known about how complex soil denitrifier communities respond to pH change and whether their ability to maintain denitrification over a wider pH range relies on phenotypic redundancy. In the present study, we followed the abundance and composition of an overall and transcriptionally active denitrifier community extracted from a farmed organic soil in Sweden (pHH2O = 7.1) when exposed to pH 5.4 and drifting back to pH 6.6. The soil was previously shown to retain much of its functioning (low N2O/N2 ratios) over a wide pH range, suggesting a high functional versatility of the underlying community. We found that denitrifier community composition, abundance and transcription changed throughout incubation concomitant with pH change in the medium, allowing for complete reduction of nitrate to N2 with little accumulation of intermediates. When exposed to pH 5.4, the denitrifier community was able to grow but reduced N2O to N2 only when near-neutral pH was reestablished by the alkalizing metabolic activity of an acid-tolerant part of the community. The genotypes proliferating under these conditions differed from those dominant in the control experiment run at neutral pH. Denitrifiers of the nirS-type appeared to be severely suppressed by low pH and nirK-type and nosZ-containing denitrifiers showed strongly reduced transcriptional activity and growth, even after restoration of neutral pH. Our study suggests that low pH episodes alter transcriptionally active populations which shape denitrifier communities and determine their gas kinetics.
Land cover discrimination at Brazilian Amazon using region based classifier and stochastic distance

Given the different nature of optical and radar data, it is reasonable the idea that each type of data can contribute in complementary ways for different applications. This paper aims at analyzing the potential joint usage of optical and Synthetic Aperture Radar (SAR) data for land use and land cover classification in a region located in the Brazilian Amazon. To achieve this objective, we evaluated region-based classifications using separated and fused optical and SAR data. Data were images from the Landsat 5/TM sensor and amplitude multipolarized images from the ALOS/PALSAR sensor. The images were classified using a region-based classifier based on the Bhattacharyya distance between Gaussian distributions. The TM data alone is better for classify land cover classes with occurrence of trees or shrubs, while SAR data contribute to improve the classification results in low vegetated areas.
Peroxidase-Generated Apoplastic ROS Impair Cuticle Integrity and Contribute to DAMP-Elicited Defenses

Cuticular defects trigger a battery of reactions including enhanced reactive oxygen species (ROS) production and resistance to necrotrophic pathogens. However, the source of ROS generated by such impaired cuticles has remained elusive. Here, we report the characterization of Arabidopsis thaliana ohy1 mutant, a Peroxidase 57 (PER57) – overexpressing line that demonstrates enhanced defense responses that result both from increased accumulation of ROS and permeability of the leaf cuticle. The ohy1 mutant was identified in a screen of A. thaliana seedlings for oligogalacturonides (OGs) insensitive/hypersensitive mutants that exhibit altered growth retardation in response to exogenous OGs. Mutants impaired in OG sensitivity were analyzed for disease resistance/susceptibility to the necrotrophic phytopathogens Botrytis cinerea and Pectobacterium carotovorum. In the ohy1 line, the hypersensitivity to OGs was associated with resistance to the tested pathogens. This PER57 overexpressing line exhibited a significantly more permeable leaf cuticle than wild-type plants and this phenotype could be recapitulated by overexpressing other class III peroxidases. Such peroxidase overexpression was accompanied by the suppressed expression of cutin biosynthesis genes and the enhanced expression of genes associated with OG-signaling. Application of ABA completely removed ROS, restored the expression of genes associated with cuticle biosynthesis and led to decreased permeability of the leaf cuticle, and finally, abolished immunity to B. cinerea. Our work demonstrates that increased peroxidase activity increases permeability of the leaf cuticle. The loss of cuticle integrity primes plant defenses to necrotrophic pathogens via the activation of DAMP-responses.
Applications for protein sequence–function evolution data: mRNA/protein expression analysis and coding SNP scoring tools

The vast amount of protein sequence data now available, together with accumulating experimental knowledge of protein function, enables modeling of protein sequence and function evolution. The PANTHER database was designed to model evolutionary sequence–function relationships on a large scale. There are a number of applications for these data, and we have implemented web services that address three of them. The first is a protein classification service. Proteins can be classified, using only their amino acid sequences, to evolutionary groups at both the family and subfamily levels. Specific subfamilies, and often families, are further classified when possible according to their functions, including molecular function and the biological processes and pathways they participate in. The second application, then, is an expression data analysis service, where functional classification information can help find biological patterns in the data obtained from genome-wide experiments. The third application is a coding single-nucleotide polymorphism scoring service. In this case, information about evolutionarily related proteins is used to assess the likelihood of a deleterious effect on protein function arising from a single substitution at a specific amino acid position in the protein. All three web services are available at .
Graphane sheets and crystals under pressure

Eight isomeric two-dimensional graphane sheets are found in a theoretical study. Four of these nets—two built on chair cyclohexanes, two on boat—are more stable thermodynamically than the isomeric benzene, or polyacetylene. Three-dimensional crystals are built up from the two-dimensional sheets, and their hypothetical behavior under pressure (up to 300 GPa) is explored. While the three-dimensional graphanes remain, as expected, insulating or semiconducting in this pressure range, there is a remarkable inversion in stability of the five crystals studied. Two stacking polytypes that are not the most stable at ambient pressure (one based on an unusual chair cyclohexane net, the other on a boat) are significantly stabilized with increasing pressure relative to stackings of simple chair sheets. The explanation may lie in the balance on intra and intersheet contacts in the extended arrays.
Fractional Spectral Collocation Method

We develop an exponentially accurate fractional spectral collocation method for solving steady-state and time-dependent fractional PDEs (FPDEs). We first introduce a new family of interpolants, called fractional Lagrange interpolants, which satisfy the Kronecker delta property at collocation points. We perform such a construction following a spectral theory recently developed in [M. Zayernouri and G. E. Karniadakis, J. Comput. Phys., 47 (2013), pp. 2108--2131] for fractional Sturm--Liouville eigenproblems. Subsequently, we obtain the corresponding fractional differentiation matrices, and we solve a number of linear FODEs in addition to linear and nonlinear FPDEs to investigate the numerical performance of the fractional collocation method. We first examine space-fractional advection-diffusion problem and generalized space-fractional multiterm FODEs. Next, we solve FPDEs, including the time- and space-fractional advection-diffusion equation, time- and space-fractional multiterm FPDEs, and finally the space.
CSE 190 a Project Report : Golf Club Head Tracking

Computer vision and graphics technologies have been used extensively in developing golf instruction and entertainment systems. In this project, we work towards constructing the trajectory of a golf swing from high quality video, since this information can enable many of these types of applications. We build on previous work that estimates a 2D spatio-temporal trajectory model from video, and we explore different ways of improving the estimation procedure. We also identify the importance of incorporating multiple camera angles to construct full 3D trajectory models.
Analysis of Music Based On Multimodal Structure Segmentation of Audio & Lyrics Information

In this paper the approach goes towards combining the audio analysis with method of multimodal structure segmentation with also the most important part of any song that is lyrics. In particular, since lyrics contain rich information about the semantic structure of a song, our approach incorporates lyrics to overcome the existing difficulties associated with large acoustic variation in music . In further, further design a constrained clustering algorithm for music segmentation and evaluate its performance on commercial recordings. Index Terms Lyrics, music information retrieval, music, segmentation
Brain-Computer Interfaces : Classifying Real and Imagined Movements and Effects of tDCS

EEG-based brain-computer interfaces (BCIs) often suffer from a low signal-to-noise ratio. In this context, we investigate whether transcranial direct current stimulation (tDCS) produces significant changes in the amplitude of event-related potentials (ERPs) for real and imagined finger tapping. For real taps, we find that anodal tDCS produces significant changes in the motor area and we describe two regions of interest around 80 and 230 ms, corresponding to two positive ERP peaks. For imagined taps, changes are visible but usually not significant in the motor area. However, a cluster with significantly decreased amplitude is found for cathodal tDCS in the parietal area for imagined taps, which may be linked to visuomotor processing. The results suggest that tDCS improves the signal-to-noise ratio of the EEG. We also describe the implementation of a brain-computer interface with robotic feedback and perform a pilot study to explore left versus right hand movement classification. We find considerable variability in classification accuracies among participants (88.5%, 87.5% and 65.5%). We report activity related to the imagined hand movement in the mu and beta frequency bands (10-28 Hz) and we propose a link between beta band activity and classification accuracy. We discuss the variability among participants and the main challenges in the context of building a BCI. Table of
Study on the prediction of energy demand based on master slave neural network

The development of economy, the progress of the society and the modern civilization is inseparable from the energy. Along with rapid development of economy and society, the energy demand grows continuously. Therefore energy demand forecasting has important theoretic and realistic significance. The BP neural network is usually applied to energy demand forecasting. But traditional BP neural network easily gets into part minimum, which leads to non convergence of algorithm and fail training. The master slave neural network (MSNN) is consisted with two Hopfield networks as master network and a BP network as slave network because of its good dynamic evolution performance. It can solve the problem well. Compared with BP neural netwok, MSNN has smaller system error and quicker asymptotic convergence rate. This paper proposes the energy forecasting new model and it is applied to predict energy demand in the last five years. The result shows that MSNN has a more rapid convergence rate. Besides it has smaller network system errors. It predicts ultimately energy demand well. Therefore, the MSNN can improve effect of energy demand forecasting better.
Some improvements to Turner's algorithm for bracket abstraction

A computer handles λ-terms more easily if these are translated into combinatory terms. This translation process is called bracket abstraction. The simplest abstraction algorithm—the (fab) algorithm of Curry (see Curry and Feys [6])—is lengthy to implement and produces combinatory terms that increase rapidly in length as the number of variables to be abstracted increases. There are several ways in which these problems can be alleviated: (1) A change in order of the clauses in the algorithm so that (f) is performed as a last resort. (2) The use of an extra clause (c), appropriate to βη reduction. (3) The introduction of a finite number of extra combinators. The original 1924 form of bracket abstraction of Schönfinkel [17], which in fact predates λ-calculus, uses all three of these techniques; all are also mentioned in Curry and Feys [6]. A technique employed by many computing scientists (Turner [20], Peyton Jones [16], Oberhauser [15]) is to use the (fab) algorithm followed by certain “optimizations” or simplifications involving extra combinators and sometimes special cases of (c). Another is either to allow a fixed infinite set of (super-) combinators (Abdali [1], Kennaway and Sleep [10], Krishnamurthy [12], Tonino [19]) or to allow new combinators to be defined one by one during the abstraction process (Hughes [7] and [8]). A final method encodes the variables to be abstracted as an n-tuple—this requires only a finite number of combinators (Curien [5], Statman [18]).
Ontology based reasoning for solving passenger train optimization problem

The Logistic processes generally lead to complex physical flows dealing with various logistic elements. It has been widely observed that the quality of uncontrolled processes decline with the evolving complexity. It may make them incoherent and quasi obsoletes. Thus, the continuous optimization of logistic processes is essential for the consistent continuity of logistic activities, and henceforth, it supports their desired growth. In this paper, we propose a reasoning system that uses the conceptual domain of logistics and their optimization. The proposed approach is mainly based on the definition of logistic terminologies using ontology. We intend, that a logistic expert may use defined terms to specify a problem. These can be matched to extract the involved logistic processes. It may assist a logistics expert to identify and/or precisely specify the logistic problem. Furthermore, it may identify the logistic processes, that can be executed, to resolve the problem and consequently to resolve the inherent optimization problems. We have been experimenting the different solutions of the Passenger Transportation Problem and eventually built a software framework (based on the composition of web services), to semi-automatically assist the resolution procedure of identified optimization problems.
High incidence of limb skeletal variants in a peripheral population of the red-backed salamander, Plethodon cinereus (Amphibia: Plethodontidae), from Nova Scotia

A single population of Plethodon cinereus from northwestern Nova Scotia shows a high incidence of limb skeletal variants, which is exceptional for this morphologically conservative species. Included are nine carpal patterns and five tarsal patterns, which result from the variable occurrence of 11 different combinations of fused adjacent mesopodial elements, and frequent absence of one or more ossified phalanges; one instance of increased phalangeal number also is noted. Primitive plethodontid carpal and tarsal patterns, which characterize P. cinereus from other parts of its range, occur in 69 and 71% of the carpi and tarsi examined, respectively. Modal phalangeal formulae also are those typical of P. cinereus generally. Several mesopodial variants resemble those seen in other plethodontid genera; they may have appeared independently in P. cinereus. Others are unique to this population. Both the genetic basis and geographical extent of this variation are unknown.
Visually Exploring and Querying XML with BaseX

XML documents are widely used as a generic container for textual contents. As they are increasingly growing in size, XML databases are emerging to efficiently store and query their contents. Besides, due to the hierarchic structure of XML documents, hierarchic visualizations are needed to facilitiate cognitive access to query results. BaseX is a simple database prototype, mapping XML documents to a table based tree encoding. An integrated treemap visualization and a query interface allow visual access to the documents and demonstrate the efficiency of the underlying data storage.
Investigation of peatland restoration (grip blocking) techniques to achieve best outcomes for methane and greenhouse gas emissions/balance. Controlled Environment (Mesocosm) Experiment. Final Report to Defra. Project code SP1202

(2011). Investigation of peatland restoration (grip blocking) techniques to achieve best outcomes for methane and greenhouse gas emissions/balance. Copyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyright owners. For more information on Open Research Online's data policy on reuse of materials please consult the policies page.
Respiratory motion prediction by fuzzy logic approaches : ANFIS vs . Interval Type-2 Non Singleton Fuzzy System

Purpose Respiratory motion prediction is a chaotic time series prediction problem. In this study, respiratory motion predictability from 12 traces from breast cancer patients is examined by using Adaptive Neuro-Fuzzy Inference System (ANFIS) and Interval Type-2 Non Singleton Fuzzy System (IT2NSFLS). Methods Free breathing data curves were obtained from Real Time Position Management system (RPM system) from 12 breast cancer patients. The sampling rate was 25 Hz. Two different methods (ANFIS and IT2NSFLS) were tested over a prediction interval of 20 seconds. Results Average root mean square error (RMSE) values were calculated to be 0.1268 and 0.0538 for prediction by ANFIS and IT2NSFLS, respectively. It is also seen that IT2NSFLS is more robust and precise than ANFIS for predicting respiratory motion in breast cancer patients. Purpose In radiation therapy, it is known that the target motion often affects the conformability of the therapeutic dose distribution delivered to thoracic and abdominal tumors. Tumor motions can not only be associated with patient's stochastic movements and systematic drifts, but also involve internal movements caused by such as respiration and cardiac cycles [1]. The target motion often affects the conformability of the therapeutic dose distribution delivered to thoracic and abdominal tumors, and thus tumor motion monitoring systems have been developed. Even we can observe tumor motion accurately; however, radiotherapy systems may inherently have mechanical and computational delays to be compensated for synchronizing dose delivery with the motion. For solving the delay problem, we have compared two different fuzzy logic reasoning approaches: Adaptive Neuro Fuzzy Inference System (ANFIS) and Interval Type-2 Non Singleton Fuzzy Logic System (IT2NSFLS). Methods We describe briefly the two approaches tested for respiratory motion prediction. a) ANFIS: Combines the ability of Neural Network (NN) to learn, with the Fuzzy Logic (FL) to reason in order to form a hybrid intelligent system called ANFIS (Adaptive Neuro Fuzzy Inference System). The goal of ANFIS is to find a model or mapping that will correctly associate the inputs (initial values) with the target (predicted values). Fuzzy inference system (FIS) is a knowledge representation where each fuzzy rule describes a local behaviour of the system. If we view a FIS as a feed-forward network structure where the primary inputs and intermediate results are being sent around to compute the final output, then we can apply the same back-propagation principle for learning as in neural networks. The network structure that implements FIS and employs hybrid-learning rules …
Segmentation of Natural Image Based on Symmetry Features

Symmetry is one of the important features of many nature or artificial structures. In a natural image with a major subject, the largest symmetric region is usually the subject. This paper presents a method to segment the largest symmetric region in a nature image. Firstly, the image is segmented into regions with internal similarity. Secondly, according to their features, these regions are classified into similar groups or unique regions. Each group or unique region is examined to find its symmetry axis. Finally, these regions are analyzed and summarized to determine the largest symmetric region in the image. We use a butterfly image database to test our method. The experimental results show that the proposed method is effective.
Masculine attitudes of superiority deter men from accessing antiretroviral therapy in Dar es Salaam, Tanzania

Background This article presents part of the findings from a larger study that sought to assess the role that gender relations play in influencing equity regarding access and adherence to antiretroviral therapy (ART). Review of the literature has indicated that, in Southern and Eastern Africa, fewer men than women have been accessing ART, and the former start using ART late, after HIV has already been allowed to advance. The main causes for this gender gap have not yet been fully explained. Objective To explore how masculinity norms limit men's access to ART in Dar es Salaam. Design This article is based on a qualitative study that involved the use of focus group discussions (FGDs). The study employed a stratified purposive sampling technique to recruit respondents. The study also employed a thematic analysis approach. Results Overall, the study's findings revealed that men's hesitation to visit the care and treatment clinics signifies the superiority norm of masculinity that requires men to avoid displaying weakness. Since men are the heads of families and have higher social status, they reported feeling embarrassed at having to visit the care and treatment clinics. Specifically, male respondents indicated that going to a care and treatment clinic may raise suspicion about their status of living with HIV, which in turn may compromise their leadership position and cause family instability. Because of this tendency towards ‘hiding’, the few men who register at the public care and treatment clinics do so late, when HIV-related signs and symptoms are already far advanced. Conclusion This study suggests that the superiority norm of masculinity affects men's access to ART. Societal expectations of a ‘real man’ to be fearless, resilient, and emotionally stable are in direct conflict with expectations of the treatment programme that one has to demonstrate health-promoting behaviour, such as promptness in attending the care and treatment clinic, agreeing to take HIV tests, and disclosing one's status of living with HIV to at least one's spouse or partner. Hence, there is a need for HIV control agencies to design community-based programmes that will stimulate dialogue on the deconstruction of masculinity notions.