Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Fast Fourier Transforms in Some Advanced Electroanalytical Methods

In the most of electrochemical (EC) experiments, measurements mostly are performed in the time domain. However, in some cases, we require more information for the obtained data such as knowledge about the frequency content and behavior of the electroanalytical signals and of complete systems. Fortunately, there exists a defined method for transforming data from the time domain into the frequency domain, where information exist about the spectral content of EC data. The method for this propos is Fourier Transform (FT), which has the ability to convert a time domain data to the complex frequency domain, meaning the spectral data contains information about both the amplitude and phase of the sinusoidal components that make up the signal. In addition, the inverse FT, converts the generated complex frequency-domain signal data back into the time-domain without losing wanted information. Accordingly, it can say that both the timeand frequency-domain data complement and the two domains can provide a different view of the same EC data. Application of fast Fourier transformation (FFT) algorithm for numerical EC data provides the complex spectrum according to magnitude and phase, which can be used for real time analysis. In this direction, in modern electrochemistry, FFT has been used for digital signal processing and filtering. Also, the FFT process returns a vector of real and imaginary elements, which represent the various resolved harmonics in impedance spectroscopy, AC and square wave voltammetry (Popkirov, 1996). On the other hand, it must be noted that in all EC data collection, to hold on the sampling theorem for FFT, the bandwidth of the input signal is limited by an analog low pass filter (cutoff frequency fc = fin,max) ahead of the Analog to Digital (A/D) converter. In fact, after collecting data in the computer memory, they are used for calculating the signal in the frequency domain. This chapter serves as summary application of the FFT analysis techniques implemented in EC measurement platform. By reading through this document, you will receive a comprehension of the fundamental concepts in FFT-based measurements used throughout EC application, providing you insights to better understanding of the measurement
Atomistic and mesoscale simulations of free solidification in comparison

Solidification of an undercooled Lennard-Jones system is considered by atomistic and mesoscale simulations. The influence of the parameters of a Nosé–Hoover thermostat on the temperature profile in the molecular dynamics box during the free solidification of the sample is analyzed. Direct comparison of the temperature profiles and of the interface dynamics in molecular dynamics with phase-field simulations is given.
Mouse models for understanding the molecular mechanism of bone disease in Hutchinson-Gilford progeria syndrome

Aging is a complex process affecting all people. Intense research is applied to elucidate the biological basis of aging and disease that develop with aging. Studies of progeroid syndromes, where aging happens in an accelerated speed, might be useful to understand the molecular mechanisms in physiological aging. Hutchinson-Gilford progeria syndrome (HGPS or progeria) is a very rare, fatal genetic disease, with an incidence of 1 in 4-8 million live births, which causes segmental premature aging in children. Affected individuals are born looking healthy, but develop symptoms of disease within their first years of life. Signs of progeria include growth retardation, loss of body fat and hair, skin changes, stiffness of joints, hip dislocations and generalized atherosclerosis and cardiovascular disease. Children with HGPS die of heart disorders or stroke at an average age of 13 years. The aim of this thesis is to increase the understanding of the molecular mechanisms underlying progeria. For this purpose, we developed tissuespecific inducible mouse models for the most common HGPS mutation in the LMNA gene (c.1824C<T, p.G608G). We demonstrate that the disease pathology in HGPS is reversible in a mouse model with keratin 5-targeted transgenic expression of the HGPS mutation. The mice had a progressive phenotype with similar abnormalities to those seen in the skin and teeth of HGPS patients. These abnormalities improved in mice following 6 and 13 weeks of suppressed expression of the HGPS mutation. Our results give hope for the future development of treatments for children with HGPS. We report our negative experience with a previously functional transactivator mice that failed to target the expression of the lamin A minigenes to the bone. To share this result with the scientific community will help to raise caution and to point out the importance for controls. LIST OF PUBLICATIONS I. Sagelius H, Rosengardten Y, Schmidt E, Sonnabend C, Rozell B, Eriksson M. Reversible phenotype in a mouse model of Hutchinson-Gilford progeria syndrome. Journal of Medical Genetics. 2008; 45 (12): 794-801. II. Schmidt E, Eriksson M. A previously functional tetracyclineregulated transactivator fails to target gene expression to the
RDEC: Integrating Regularization into Deep Embedded Clustering for Imbalanced Datasets

Clustering is a fundamental machine learning task and can be used in many applications. With the development of deep neural networks (DNNs), combining techniques from DNNs with clustering has become a new research direction and achieved some success. However, few studies have focused on the imbalanced-data problem which commonly occurs in real-world applications. In this paper, we propose a clustering method, regularized deep embedding clustering (RDEC), that integrates virtual adversarial training (VAT), a network regularization technique, with a clustering method called deep embedding clustering (DEC). DEC optimizes cluster assignments by pushing data more densely around centroids in latent space, but it is sometimes sensitive to the initial location of centroids, especially in the case of imbalanced data, where the minor class has less chance to be assigned a good centroid. RDEC introduces regularization using VAT to ensure the model's robustness to local perturbations of data. VAT pushes data that are similar in the original space closer together in the latent space, bunching together data from minor classes and thereby facilitating cluster identification by RDEC. Combining the advantages of DEC and VAT, RDEC attains state-of-the-art performance on both balanced and imbalanced benchmark/real-world datasets. For example, accuracies are as high as 98.41% on MNIST dataset and 85.45% on a highly imbalanced dataset derived from the MNIST, which is nearly 8% higher than the current best result.
Preserving species populations in the boreal zone in a changing climate: contrasting trends of bird species groups in a protected area network

A protected area network should ensure the maintenance of biodiversity. Because of climate change, species ranges are expected to move polewards, causing further demand for the protected area network to be efficient in preserving biota. We compared population changes of different bird species groups according to their habitat preferences in boreal protected areas in Finland on the basis of large-scale censuses carried out in 1981–1999 and in 2000–2009. Population densities of common forest habitat generalists remained the same between the two periods, while densities of species of conservation concern showed contrasting trends: species preferring old-growth forests increased, but those living on mires and wetlands, and species of Arctic mountains decreased. These trends are most probably connected with climate change, but successional changes in protected areas and regional habitat alteration should also be taken into account. Of species preferring old-growth forests, a larger proportion are southern than among species of mires and wetlands, or of Arctic mountains, most or all of which, respectively, had a northerly distribution. In general, northern species have decreased and southern increased with the exception of northern species of old-growth forests which had not declined. On the other hand, bird species of mires and wetlands decreased also in the northernmost protected areas although mires had not been drained in the region in contrast with southern and central Finland thus indicating that regional-scale direct habitat loss did not cause the decline of these species in the north. It is suggested that climate change effects on species in natural boreal and Arctic habitats most probably are habitat-specific with large differences in response times and susceptibility.
Construction of gender-specific pediatric templates for spatial normalization within SPM99

Spatial normalization transforms an individual brain into a standard stereotaxic space in order to compare imaging results across individuals. However, most approaches rely on information from a template composed from one or more adult brains, with the applicability of this adult data depending on the differences between the populations making up the template (adult) and the brains to be normalized (pediatric). Therefore, spatial misregistration must be expected especially in younger children. To provide a closer template, we created gender-specific pediatric templates from a large collection of healthy children and examined their differences. These templates can be integrated into SPM99.
Virulent Aeromonas veronii Strain BLB-01 Associated with Mass Mortality of Clarias batrachus (Linnaeus, 1758)

1 ICAR-Central Institute of Fisheries Education, Kakinada Centre FWFF, Balabhadrapuram, Andhra Pradesh-533007, India 2 ICAR-Central Institute of Fisheries Education, Kakinada Centre, Beach Road, Kakinada, Andhra Pradesh-533007, India 3 ICAR-Central Marine Fisheries Research Institute, Kochi, India 4 ICAR-Central Institute of Fisheries Education, Panch Marg, Off Yari Road, Mumbai-400061, India *Corresponding author
Max-margin learning with the Bayes factor

We propose a new way to answer probabilistic queries that span multiple datapoints. We formalize reasoning about the similarity of different datapoints as the evaluation of the Bayes Factor within a hierarchical deep generative model that enforces a separation between the latent variables used for representation learning and those used for reasoning. Under this model, we derive an intuitive estimator for the Bayes Factor that represents similarity as the amount of overlap in representation space shared by different points. The estimator we derive relies on a query-conditional latent reasoning network, that parameterizes a distribution over the latent space of the deep generative model. The latent reasoning network is trained to amortize the posterior-predictive distribution under a hierarchical model using supervised data and a max-margin learning algorithm. We explore how the model may be used to focus the data variations captured in the latent space of the deep generative model and how this may be used to build new algorithms for few-shot learning.
BACTERIAL AND ARCHAEAL DIVERSITY IN ABYSSAL COLD SEEP SEDIMENTS FROM THE DONGSHA AREA OF THE SOUTH CHINA SEA

Microbial diversity of an active cold seep from the Dongsha area of South China Sea was characterized by collecting a 5.5-m core and by using 16S rRNA gene analysis. DNA was extracted from three vertical zones (top, middle and bottom) of the core and the 16S rRNA gene was amplified by polymerase chain reaction (PCR), cloned and sequenced. Six clone libraries were constructed with a total of 395 sequences. Pore water chemistry suggested a couple d reaction between sulfate reduction and methane oxidation. Phylogenetic analysis indicated presence of sulfate-reducing bacteria and anaerobic methane-oxidizing archaea. The archaeal diversity was high at the surface, but decreased sharply with increased depth. Marine Benthic Group (MBG)-D and halobacteriales were the dominant groups at the surface sediments, and the MBG-B group became predominated with increased depth, reaching 38.9% and 62.5% in the middle and bottom sediments, respectively. Similarly, the bacterial diversity was higher at the top and decreased with depth. Proteobacteria was the dominant group in the top of the core, but became minor deeper within the sediments. With increased depth, Chloroflexi and JS1 became predominant groups and reached up to 78.8% and 70.3%, respectively. Overall, our results suggested that microbial diversity in So uth China Sea cold seep was high and community structure and diversity changed greatly with depth, in response to changes in the physical and chemical conditions of the sediments.
Delayless identification in ANC systems using Subband adaptive techniques

Subband techniques have been developed to use low order subfilters instead of full band higher order filters and consequently reduce the complexity and increase the convergence speed of the adaptive algorithm. In this paper the performance of two delayless subband adaptive algorithms for identification of an unknown system in an active noise control scheme are compared. This is carried out by using a common speech signal as the excitation input for identification of the secondary path model. The performances of the algorithms are measured in terms of the achieved minimum mean square error and misalignment error. The results are also compared to the time domain NLMS algorithm. The compared delayless structures are working in the closed loop form with DFT analysis filterbanks. Adaptation in the auxiliary loop and with help of weight transformation eliminates signal path delay and hence the unknown secondary path can be modelled accurately.
Exact Grid Side Current Control Modeling for a Medium Voltage Wind Farm

The low switching frequency of medium voltage drives requires an accurate current control model to design the controller, as delays and discretization process are no longer negligible. In addition, the grid impedance and the feed-forward voltage also affect the response of the system. This paper presents a procedure that exactly models the current control loop of a medium voltage wind farm. The modeling procedure is experimentally validated. An exact current control model allows the designer to tune the controller and analyze the stability of a wind farm under different circumstances, such as different grid short circuit ratios (SCR) with a high reliability. The differences with the experimental results will only be limited to deviations between the impedances of the model and real plant.
COMPARISON OF THE EFFECTS OF GROWTH REGULATORS ON IN VITRO REGENERATION OF RIDGE GOURD AND SPONGE GOURD THROUGH SHOOT

Context: Luffa cylindrica and Luffa acutangula are highly cross pollinated crops and propagated mainly by seeds. Genetic stability cannot be maintained easily by seed propagation. It can be maintain by developing special vegetative technique through tissue culture. Objectives: To compare the effects of growth regulators between two species of Luffa using shoot tips for develop the rapid, simple and efficient in vitro regeneration protocol. Materials and Methods: Shoot tips used were collected from in vivo grown plants. They were excised from plants and surface sterilized by HgCl 2 treatment. The isolated tips were cultured on semisolid MS medium supplemented with different concentrations and combinations of different growth regulators. Results: The highest result of direct shoot multiplication of ridge gourd was observed using 2 mg/l BAP + 0.2 mg/l GA and in case of sponge gourd it was 1.5 mg/l BAP. For callus induction significant result was found using 4 mg/l BAP + 0.2 mg/l NAA in ridge gourd and 3 mg/l BAP + 0.2 mg/l NAA in sponge gourd. Indirect regeneration was performed by subculturing organogenic callus of sponge gourd on MS with 1.5 mg/l BAP + 0.2 mg/l GA 3 and the callus of ridged gourd on MS + 1.5 mg/l BAP + 0.2 mg/l NAA + 0.2 mg/l nicotinic acid. Regenerated shoots of both species were rooted well on MS containing NAA at low concentration. Conclusion: Hormonal differences and simple rapid in vitro regeneration protocol of L. cylindrica and L. acutangula have been established. Keywords: Growth regulators; in vitro regeneration; ridge gourd; sponge gourd . DOI: http://dx.doi. org/10.3329/jbs.v18i0. 8781 JBS 2010; 18(0): 88-93
Autonomous image to model registration

Current production of geospatial site models is a labor intensive process. Consequently, automated/semi-automated solutions are sought to improve the production timeline. Automated image to model registration algorithms enable the identification of regions for focused data revision and the association of information for model refinement. Image to model registration is a sensor collection parameter estimation problem to optimize the spatial correspondence of information between the image and the model. This paper describes an automated algorithm based on the association of edge features to extract tie-points for sensor parameter estimation. These features are generated from the model through a predicted image of the site using the sensor model and available collection geometry. A key feature of this algorithm is the explicit incorporation of uncertainty in the registration process. Sample results using IKONOS satellite imagev are provided.
An attempt at using mass media data to analyze the political economy around some key ICTD policies in India

Policy making is influenced by a number of factors, including electoral politics, ideological biases of actors involved in the policy making process, and the interlocks between corporate and government entities. This influence is also exercised by shaping public opinion through mass media. In this paper, we study four ICTD policies in India, and explore the political economy around them by using data about how these policies are covered in the mass media. We study which actors are covered more in media, how they speak on the policy issues, and which aspects are given more coverage for these policies. We find that politicians get the highest coverage in mass media regarding discussions on policies, and that the politicians and business-persons often express similar ideologies related to these policies. We also observe that mass media is often biased towards issues related to its middle class reader base with a strong sense of technology driven high-modernism, and negative aspects of these policies and issues faced by the poor due to improper policy implementation are often not given significant coverage. Our key contribution is a methodology of using automated analysis of mass media data to reveal the factors that might be shaping the political economy behind policy making.
A Peculiar Feature of the Seasonal Migration of the South American Rain Band

Seasonal migration of tropical rainfall is examined in the South American sector and compared with that over Africa, using satellite and reanalysis data. While the African rain band moves continuously back and forth across the equator following the seasonal march of the sun, the South American one displays a peculiar asymmetry between its northward and southward migration. The rain band moves gradually northward from October to July from the Amazon toward the Caribbean Sea, while its return to the Amazon is an abrupt event, with convection developing rapidly in October around 10 � S without going through the equator. Over the equatorial Amazon during July–October, equivalent potential temperature (ye) is kept low by the easterly advection of low temperature and humidity air from the equatorial Atlantic, coinciding with the seasonal development of ocean upwelling and a cold tongue in sea surface temperature. The low ye values prevent convection from developing in the equatorial Amazon while warm SST supports convection on the north coast of South America during August–October. Meanwhile solar radiation continues to heat up the land surface to the south, eventually triggering the onset of deep convection there in October.
ON CLASSIFICATION OF FOOT GESTURES VIA SURFACE ELECTROMYOGRAPHY

A fundamental problem for individuals with amputations proximal to the elbow is the lack of methods for controlling an upper limb prosthetic. Myoelectric control is limited in flexibility when few residual muscle sites are available, and noninvasive approaches to this problem are needed when surgical techniques such as targeted muscle reinnervation are not suitable. Controlling an upper limb prosthetic with the leg is one such approach. In this case study, we investigate recognition of foot gestures via surface electromyography using methods commonly employed in upper limb gesture recognition research. For comparison with the current standard in gesture recognition, electromyographic sensors recorded muscle activity from the forearm while participants performed gestures with the dominant hand. Then, participants performed an analogous set of foot gestures with sensors on the lower leg. Participants found the mapping between the hand and foot to be intuitive, and offline results show that classification accuracy for the two cases is comparable, motivating further work in applying this idea to upper limb prosthetic control.
Rangeland responses to pastoralists' grazing management on a Tibetan steppe grassland, Qinghai Province, China

Livestock grazing is the principal land use in arid central Asia, and range degradation is considered a serious problem within much of the high-elevation region of western China termed the Qinghai-Tibetan Plateau (QTP). Rangeland degradation on the QTP is variously attributed to poor livestock management, historical-cultural factors, changing land tenure arrangements or socioeconomic systems, climate change, and damage from small mammals. Few studies have examined currently managed pastures using detailed data capable of isolating fine-scale livestock–vegetation interactions. The aim of the study was to understand how differences among livestock (primarily sheep) management strategies of pastoralists during winter affected subsequent rangeland condition and productivity. Plant species composition, annual herbage mass, and indicators of erosion were quantified during four summers (2009–2012) on winter pastures managed by 11 different pastoralists on QTP steppe rangeland in Qinghai Province, China. Data came from repeated-measurements on 317 systematically located permanent plots, as well as pastoralist interviews and the use of GPS-equipped livestock. Relationships between annual weather variation and herbage mass were modelled using an independent set of vegetation measurements obtained from livestock exclosures. Account was taken of inherent site differences among pastures. Annual variation in herbage mass was found to be best fitted by a model containing a negative function of winter-season temperature and a positive function of spring-season temperature. Accounting for annual and site effects, significant differences among pastoralists were found for most response variables, suggesting that individual heterogeneity among management approaches had consequences, even among neighbouring pastoralists. Annual herbage mass of preferred plant species was positively associated, whereas that of unpreferred species was negatively associated, with mean sheep density and intensity of use. However, the proportion of bare soil, an index of erosion, and annual herbage mass of unpreferred forbs were found to have positive relationships with sheep grazing pressure during the preceding winter, whereas live vegetation cover and annual herbage mass of preferred grasses were negatively related. Thus, on a spatial scale, pastoralists responded adaptively to the cover of preferred plant species while not responding to total annual herbage mass. Pastoralists stocked pastures more heavily, and livestock used regions within pastures more intensively, where preferred species had a higher cover. However, where sheep grazing pressure was high, downward temporal trends in the herbage mass of preferred species were exacerbated. Pastures that were stocked at a lower density did not experience the negative trends seen in those with a higher density.