Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence for 4-chlorobenzoic acid dehalogenation mediated by plasmids related to pSS50

The biodegradation of 4-chlorobiphenyl usually proceeds through the intermediate 4-chlorobenzoate. Few bacterial strains can degrade 4-chlorobiphenyl to 4-chlorobenzoate and 4-chlorobenzoate to CO2. This study demonstrates that the 4-chlorobiphenyl-degrading Alcaligenes sp. strain ALP83 can degrade 4-chlorobenzoate to 4-hydroxybenzoate. The dehalogenase activity is correlated with a 10-kb fragment carried on plasmid pSS70.
Validation of the Volunteer Motivation Scale and its relations with work climate and intention among Chinese volunteers

Grounded in self-determination theory (SDT; Deci & Ryan, 1985), this two-phase research examines the reliability and validity of the Volunteer Motivation Scale with Chinese volunteers (VMS-C) and its relationship with the supportive work climate and intention to continue being a volunteer. In Study 1, the initial item pool of the VMS-C with 18 items measuring six motivation types was administrated to Chinese volunteers (N = 362). Factor analysis led to a five-factor model with 15 items. This model was cross-validated using confirmatory factor analysis. The five factors were intrinsic motivation, identified regulation, introjected regulation, external regulation and amotivation. In Study 2, the relationships between different types of motivation (i.e. autonomous motivation, controlled motivation, amotivation) and two variables of interests, namely, supportive work climate and intention to stay, were investigated (N = 228). It was found that autonomous motivation (i.e. intrinsic motivation, identified regulation) were positively related to both supportive work climate and intention to stay. Controlled motivation (i.e. introjected regulation, external regulation) and amotivation were negatively associated with the two variables. The current findings are consistent with SDT. More studies guided by the theory in the volunteering area are recommended.
Impact of Arthritis and Multiple Chronic Conditions on Selected Life Domains — United States, 2013

About half of U.S. adults have at least one chronic health condition, and the prevalence of multiple (two or more) chronic conditions increased from 21.8% in 2001 to 25.5% in 2012. Chronic conditions profoundly affect quality of life, are leading causes of death and disability, and account for 86% of total health care spending. Arthritis is a common cause of disability, one of the most common chronic conditions, and is included in prevalent combinations of multiple chronic conditions. To determine the impact of having arthritis alone or as one of multiple chronic conditions on selected important life domains, CDC analyzed data from the 2013 National Health Interview Survey (NHIS). Having one or more chronic conditions was associated with significant and progressively higher prevalences of social participation restriction, serious psychological distress, and work limitations. Adults with arthritis as one of their multiple chronic conditions had higher prevalences of adverse outcomes on all three life domains compared with those with multiple chronic conditions but without arthritis. The high prevalence of arthritis, its common co-occurrence with other chronic conditions, and its significant adverse effect on life domains suggest the importance of considering arthritis in discussions addressing the effect of multiple chronic conditions and interventions needed to reduce that impact among researchers, health care providers, and policy makers.
A Consistent Model for the Large-Scale Steady Surface Atmospheric Circulation in the Tropics*

The authors present a new model of the tropical surface circulation, forced by changes in sensible heat and evaporative flux anomalies that are associated with prescribed sea surface temperature anomalies. The model is similar to the Lindzen and Nigam (LN) boundary layer model, also driven by the above flux anomalies; but here, since the boundary layer is assumed well mixed and capped by an inversion, the model reduces to a twolayer, reduced-gravity system. Furthermore, the rate of exchange of mass across the boundary layer‐free atmosphere interface is dependent on the moisture budget in the boundary layer. When moist convection is diagnosed to occur, detrainment operates on the timescale associated with the life cycle of deep convection, approximately eight hours. Otherwise, the detrainment is assumed to be associated with the mixing out of the stable tropical boundary layer, which has a timescale of about one day. The model provides a diagnostic estimate of the anomalies in precipitation. However, it is assumed that the latent heat is released above the boundary layer, and it drives a circulation that does not impact the boundary layer. The authors discuss the derivations of the Gill‐Zebiak (GZ) and Lindzen‐Nigam models and highlight some apparent inconsistencies between their derivation and the values of several of the parameters that are required for these models to achieve realistic solutions for the circulations. Then, the new reduced-gravity boundary model equations are rewritten in the form of the GZ and LN models. Using realistic values for the parameters in the new model geometry, it is shown that the constants combine in the rewritten equations to produce the physically doubtful constants in the GZ and LN models, hence, the reason for the apparent success of these models.
An adaptive detection approach for autonomous forest path following using stereo vision

In this paper, an image-based segmentation method to improve autonomous robot navigation in the forest is presented. The detection is supported by a filtered image generated from a stereo-based pre-processing which is a byproduct of our obstacles detection system. To cope with the large variability of forest paths, the classifier is dynamically adapted to the current situation and the segmentation relies on different image features to ensure robustness against illumination changes. Furthermore, it is summarized how the detection results are transformed to the 3D space, using a plane which is extracted from the stereo data, to be stored and maintained in a probabilistic grid map.
Representing the environments for phonological processes in an accent-independent lexicon for synthesis of English

[2], there is also variation amongst consonants, particularly post-vocalic ? U? (as in ‘horse’, RP versus Scottish English) and postalveolar ? M? (as in ‘news’, RP versus General American). This paper reports on work developing an accent-independent lexicon for use in synthesising speech in English. Lexica which use phonemic transcriptions are only suitable for one accent, and developing a lexicon for a new accent is a long and laborious process. Potential solutions to this problem include the use of conversion rules to generate lexica of regional pronunciations from standard accents [1] and encoding of regional variation by means of keywords [2]. The latter proposal forms the basis of the current work. There are some additional consonants which are not covered in [2]. These are only used in a limited geographical area, such as ? (cid:211)? which is used in Wales and ? [? which is used in Scotland and Ireland. Both of these are used mainly for local words or names, such as ? (cid:211)? in the Welsh name ‘Llewelyn’, or ? [? in the Scottish word ‘loch’. To some extent their use is predictable from the spelling and the pronunciation in other accents, but in a keyword system it is simpler to use key-consonants for these and encode them in the lexicon rather than try to produce them by rule. However, even if we use a keyword system for lexical transcription there are a number of remaining theoretical and methodological problems if we are to synthesise and recognise accents to a high degree of accuracy; these problems are discussed in the following paper.
Q-learning of sequential attention for visual object recognition from informative local descriptors

This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects irrelevant local descriptors based on an information theoretic saliency measure, providing candidates for foci of interest (FOI). The second stage investigates the information in the FOI using a codebook matcher and providing weak object hypotheses. The third stage integrates local information via shifts of attention, resulting in chains of descriptor-action pairs that characterize object discrimination. A Q-learner adapts then from explorative search and evaluative feedback from entropy decreases on the attention sequences, eventually prioritizing shifts that lead to a geometry of descriptor-action scanpaths that is highly discriminative with respect to object recognition. The methodology is successfully evaluated on indoors (COIL-20 database) and outdoors (TSG-20 database) imagery, demonstrating significant impact by learning, outperforming standard local descriptor based methods both in recognition accuracy and processing time.
Synthesis, Docking and Anti-inflammatory Activity of Some Newer Triazole Derivatives as Potential PDE7 Inhibitors

Phosphodiesterase 7 (PDE7), one of the members of PDE family has been reported as potential therapeutic target involved in inflammation. The present work was designed to synthesize and evaluate the anti-inflammatory activity of some newer substituted triazole derivatives as potential PDE7 inhibitors. A series of substituted triazole derivatives was synthesized and evaluated by in silico studies to determine the binding interactions for the best-fit conformations in the binding site of the PDE7 protein. The selected compounds from in silico studies were evaluated further for their anti-inflammatory activity in the animal models. Amongst the synthesized molecules, compound 3 showed higher anti-inflammatory activity. The in vivo results showed accordance to that of in silico results. Most of the synthesized molecules were found to have drug-like properties as devised by Lipinski’s rule of five. These molecules can act as the starting hits for the design of safe, effective and orally bioavailable PDE7 inhibitors for the treatment of various inflammatory disorders.
An islanding detection method for distributed generations using voltage unbalance and total harmonic distortion of current

Distributed generation (DG) units are rapidly increasing and most of them are interconnected with distribution network to supply power into the network as well as local loads. Islanding operations of DG usually occur when power supply from the main utility is interrupted due to several reasons but the DG keeps supplying power into the distribution networks. These kinds of islanding conditions cause negative impacts on protection, operation, and management of distribution systems; therefore, it is necessary to effectively detect the islanding conditions and swiftly disconnect DG from distribution network. Generally, if there are large changes in loading for DG after loss of the main power supply, then islanding conditions are easily detected by monitoring several parameters: voltage magnitude, phase displacement, and frequency change. However, in case of small changes in loading for DG, the conventional methods have some difficulty in detecting such a particular islanding condition. This paper presents a new islanding detection algorithm for DG effectively working in the most of DG loading conditions. This paper proposes two new parameters for detecting islanding operation of DG: voltage unbalance and total harmonic distortion of current. The proposed method effectively combines the conventional parameters with the newly proposed parameters for detecting the islanding conditions. The proposed methods were verified using the radial distribution network of IEEE 34 bus.
Information filtering for mobile augmented reality

Augmented reality is a potentially powerful paradigm for annotating the (real) environment with computer-generated material. These benefits will be even greater when augmented reality systems become mobile and wearable. However, to minimize the problem of clutter and to maximize the effectiveness of the display, algorithms must be developed to select only the most important information for the user. In this paper, we describe a region-based information filtering algorithm. The algorithm takes account of the state of the user (location and intent) and the state of individual objects about which information can be presented. It can dynamically respond to changes in the environment and the user's state. We also describe how simple temporal, distance and angle cues can be used to refine the transitions between different information sets.
A decision tree based quasi-identifier perturbation technique for preserving privacy in data mining

Classification is an important issue in data mining, and decision tree is one of the most popular techniques for classification analysis. Some data sources contain private personal information that people are unwilling to reveal. The disclosure of person-specific data is possible to endanger thousands of people, and therefore the dataset should be protected before it is released for mining. However, techniques to hide private information usually modify the original dataset without considering influences on the prediction accuracy of a classification model. In this paper, we propose an algorithm to protect personal privacy for classification model based on decision tree. Our goal is to hide all person-specific information with minimized data perturbation. Furthermore, the prediction capability of the decision tree classifier can be maintained. As demonstrated in the experiments, the proposed algorithm can successfully hide private information with fewer disturbances of the classifier.
Democratising the global order: from communicative freedom to communicative power

Abstract While there is much discussion of the need for democracy in transnational institutions, there is less discussion of the conditions for their democratisation. To address this deficit, a general account of democratisation is necessary. I propose that democratisation is dependent on the joint realisation of two conditions: communicative freedom and communicative power. Democratisation thus requires, first, publics and associations in which communicative freedom is realised on the one hand; and, second, institutions that link such freedom to the exercise of communicative power to decision making on the other. In order for these conditions to be met, civil society must be expanded into the public sphere. The transformation of communicative freedom into communicative power can be promoted only by institutions that recognise the decisional status of publics, which in turn depend on civil society to generate the deliberative benefits of the plurality of perspectives. Communicative power is not merely spontaneously generated through publics, but also through publics expressly formed through democratic institutional design.
AN APPROACH TO QUALITATIVE PRACTICES IN PSYCHOLOGY FROM AN INTEGRATIVE PERSPECTIVE

he aim of this work is not so much to give an account of the latest advances in the area known as “qualitative methods” as to try and make professional psychologists aware of how useful this type of strategic approach can be in their everyday activity. To this end we must convince them that such methodological strategies are not opposed to quantitative strategies. We shall argue that they are compatible and even complementary practices. Moreover, we should highlight the fact that qualitative practices are not pre-scientific, subjective, irrational or lacking in rigour. And this is the case not only in Psychology, but also in other disciplines that make use of these types of methodological strategies with fewer inhibitions. For example, Qualitative Organic Analysis is a basic practice in Organic Chemistry that permits the identification of the chemical family to which a compound belongs, and can guide subsequent analyses; in a quite different context, to understand the healthcare priorities of a refugee community and guarantee the effectiveness of a social-health intervention plan, a community health team will need to make a qualitative study of the community’s representations of health and illness. It will thus be necessary to observe and participate in the community and rigorously reconstruct the way of life in which such conceptions take on meaning. Although all of this information may require subsequent quantitative treatment, without this initial qualitative approach the healthcare team will run the risk of unfairly projecting their own needs on the community, of misjudging the situation and of losing effectiveness. In any case, the reader should bear in mind that we start out from a position of disadvantage with respect to the rest of the articles in this volume, which come with obvious guarantees. In part because Psychology has mortgaged much of its self-esteem as a discipline for the possibility of
Popular misconceptions

No substitutes exist for an intimate knowledge of your organisms, the characters you plan to study, and the tools and technology you need to obtain ecological and evolutionary data. We started in this field during the late 1960s and 1970s, respectively, when life was easier, just seining fish and counting scales, fin rays, teeth, chromosomes, etc. Then, we adopted allozymes and needed to learn some biochemistry, population biology, statistical genetics and some computer programming. During the 1980s, when mitochondrial DNA entered the scene, we required students to take molecular biology courses and learn the chemistry and skills to conduct RFLP analyses and Sanger sequencing on slab gels. Then came the 1990s revolution — PCR, dye-terminating chemistry, automated sequencing, and genotyping with microsatellites and other markers. Now, we progress into the genomic era. High-throughput sequencing and genotyping with thousands of multilocus SNPs are relatively inexpensive and commercially available to biologists with limited experience in genetics or molecular biology. Sophisticated new computer programs to analyse and interpret these expanding datasets are available to researchers with limited statistical or theoretical expertise. As biologists from various subdisciplines engage in molecular ecological studies, how do they critically evaluate this explosion of technology, theory and data? Often, unfortu-
Stratification Pattern of Static and Scale-Invariant Dynamic Measures of Heartbeat Fluctuations Across Sleep Stages in Young and Elderly

Cardiac dynamics exhibit complex variability characterized by scale-invariant and nonlinear temporal organization related to the mechanism of neuroautonomic control, which changes with physiologic states and pathologic conditions. Changes in sleep regulation during sleep stages are also related to fluctuations in autonomic nervous activity. However, the interaction between sleep regulation and cardiac autonomic control remains not well understood. Even less is known how this interaction changes with age, as aspects of both cardiac dynamics and sleep regulation differ in healthy elderly compared to young subjects. We hypothesize that because of the neuroautonomic responsiveness in young subjects, fractal and nonlinear features of cardiac dynamics exhibit a pronounced stratification pattern across sleep stages, while in elderly these features will remain unchanged due to age-related loss of cardiac variability and decline of neuroautonomic responsiveness. We analyze the variability and the temporal fractal organization of heartbeat fluctuations across sleep stages in both young and elderly. We find that independent linear and nonlinear measures of cardiac control consistently exhibit the same ordering in their values across sleep stages, forming a robust stratification pattern. Despite changes in sleep architecture and reduced heart rate variability in elderly subjects, this stratification surprisingly does not break down with advanced age. Moreover, the difference between sleep stages for some linear, fractal, and nonlinear measures exceeds the difference between young and elderly, suggesting that the effect of sleep regulation on cardiac dynamics is significantly stronger than the effect of healthy aging. Quantifying changes in this stratification pattern may provide insights into how alterations in sleep regulation contribute to increased cardiac risk.
Effects of soy isoflavone supplementation on cognitive function in Chinese postmenopausal women: a double-blind, randomized, controlled trial

Objective:To investigate whether soy-derived isoflavone extract improves performance in cognitive function and quality of life in Chinese postmenopausal women. Design:The study was a 6-month double-blind, randomized, placebo-controlled, parallel group trial. Participants were community-dwelling women aged 55 to 76 years; 191 eligible women were randomly assigned to receive a daily oral intake of 80 mg soy-derived isoflavones or an identical-appearing placebo for 6 months. Standardized neuropsychological tests of memory, executive function, attention, motor control, language, and visual perception and a global cognitive function assessment were administered face-to-face individually at baseline and at 6-months posttreatment. The validated Chinese version of the Short Form-36 was used for quality of life measurements. Results:Of the participants, 88% (168 women: 80 among the supplementation group and 88 among the placebo group) completed the trial. Intention-to-treat analysis, conducted for 176 participants with 6-month assessment results, revealed no significant differences in outcome measures between treatment groups. Subgroup analysis among the good compliers only (consumed at least 80% of the supplements or placebo; n = 168) and among the age groups younger or older than 65 years also indicated no significant differences for any outcome measures. Types of complaints of adverse events were similar in both treatment groups and included mainly gastrointestinal and musculoskeletal problems. Conclusions:This 6-month trial indicates that 80-mg soy-derived isoflavone supplementation did not improve performance on standard neuropsychological tests and overall quality of life in generally healthy Chinese postmenopausal women.
Psychoinformatics

Psychologists live in an increasingly data-rich world, and our ability to make continued progress in understanding the mind and brain depends on finding new ways to organize and synthesize an ever-expanding body of knowledge. In this article, I review current research in psychoinformatics—an emerging discipline that uses tools and techniques from the computer and information sciences to improve the acquisition, organization, and synthesis of psychological data. I focus on several areas where the application of informatics approaches has already paid large dividends, leading to advances including novel data-collection approaches, the adaptation of computational techniques and insights, the enhanced aggregation and organization of psychological data, large-scale data mining and synthesis, and improved research and publication practices. I argue that in the coming years, informatics approaches are likely to play the same instrumental role in shaping psychological research that they have already played in other fields, such as genetics and neuroscience.