Miracle-dz/UniFAR-FTUs huggingface dataset:
Community-led initiatives’ everyday politics for sustainability – Conflicting rationalities and aspirations for change?

Community-based initiatives are widely seen to play an essential role in a societal move towards a low carbon, sustainable future. As part of this, there is often an assumption that such initiatives share expectations (i.e. a guiding vision) of large-scale change and that their activities contribute to this change. Here, we ask to what extent this assumption reflects members’ own perspectives on and interpretations of the aims and ambitions of their community initiative, and what this implies for a larger vision of sustainability transitions. In doing so, we respond to calls for a better understanding of the ‘everyday politics’ of what could be seen as processes of societal transitions in practice. We conducted qualitative interviews with members of five community initiatives in Italy, Finland and the UK. In each of these initiatives, we found a range of aspirations (i.e. outcome-related aims) and rationalities (i.e. procedural guiding principles). While some of these aims and ways of working were compatible with each other, we identified three major tensions that could be found across our study initiatives. These tensions centred on (i) the degree of politicisation of the initiative, (ii) the extent to which financial aims should take priority and (iii) questions of organisational form. We interpret these tensions as conflicting expressions of larger, societal-level discourses, and argue that this diversity and resulting conflicts need to be acknowledged – both in transition research and at the practical level – to avoid co-optation and disenfranchisement.
Extension for Design Pattern Identification Using Similarity Scoring Algorithm

This paper provides studies in area of design pattern identification in existing software systems. The target was to design and prototype specific extensions of a selected method with better and more precise results. This paper summarizes separate phases of a project analysis of different design pattern representations, analysis of different methods, algorithms for identification of design patterns in software systems, selection of a concrete method for extensions, design, implementation and tests of an extended method. In this paper, the extensions like feature weighting, feature filtering and additional lexicographical analysis are described. Designed and prototyped extensions were experimentally tested on more than 3000 classes of open source systems from different software engineering areas. Based on the test results, the general conclusion for designed extensions are formulated.
Genetic analysis of prokaryotic and eukaryotic DNA-binding proteins in Escherichia coli.

This report describes an Escherichia coli genetic system that permits bacterial genetic methods to be applied to the study of essentially any prokaryotic or eukaryotic site-specific DNA binding protein. It consists of two parts. The first part is a set of tools that facilitate construction of customized E.coli strains bearing single copy lacZYA reporters that are repressed by a specific target protein. The second part is a pair of regulatable protein expression vectors that permit in vivo production of the target protein at levels appropriate for genetic experiments. When expressed in a properly designed reporter strain, the target protein represses the lac genes, resulting in an E.coli phenotype that can be quantitatively measured or exploited in large scale genetic screens or selections. As a result, large plasmid-based libraries of protein genes or pools of mutagenized variants of a given gene may be examined in relatively simple genetic experiments. The strain construction technique is also useful for generating E.coli strains bearing reporters for other types of genetic systems, including repression-based and activation-based systems in which chimeric proteins are used to examine interactions between foreign protein domains.
Long Timescale Credit Assignment in NeuralNetworks with External Memory

Credit assignment in traditional recurrent neural networks usually involves back-propagating through a long chain of tied weight matrices. The length of this chain scales linearly with the number of time-steps as the same network is run at each time-step. This creates many problems, such as vanishing gradients, that have been well studied. In contrast, a NNEM's architecture recurrent activity doesn't involve a long chain of activity (though some architectures such as the NTM do utilize a traditional recurrent architecture as a controller). Rather, the externally stored embedding vectors are used at each time-step, but no messages are passed from previous time-steps. This means that vanishing gradients aren't a problem, as all of the necessary gradient paths are short. However, these paths are extremely numerous (one per embedding vector in memory) and reused for a very long time (until it leaves the memory). Thus, the forward-pass information of each memory must be stored for the entire duration of the memory. This is problematic as this additional storage far surpasses that of the actual memories, to the extent that large memories on infeasible to back-propagate through in high dimensional settings. One way to get around the need to hold onto forward-pass information is to recalculate the forward-pass whenever gradient information is available. However, if the observations are too large to store in the domain of interest, direct reinstatement of a forward pass cannot occur. Instead, we rely on a learned autoencoder to reinstate the observation, and then use the embedding network to recalculate the forward-pass. Since the recalculated embedding vector is unlikely to perfectly match the one stored in memory, we try out 2 approximations to utilize error gradient w.r. t. the vector in memory.
Impact of the H275Y and I223V Mutations in the Neuraminidase of the 2009 Pandemic Influenza Virus In Vitro and Evaluating Experimental Reproducibility

The 2009 pandemic H1N1 (H1N1pdm09) influenza virus is naturally susceptible to neuraminidase (NA) inhibitors, but mutations in the NA protein can cause oseltamivir resistance. The H275Y and I223V amino acid substitutions in the NA of the H1N1pdm09 influenza strain have been separately observed in patients exhibiting oseltamivir-resistance. Here, we apply mathematical modelling techniques to compare the fitness of the wild-type H1N1pdm09 strain relative to each of these two mutants. We find that both the H275Y and I223V mutations in the H1N1pdm09 background significantly lengthen the duration of the eclipse phase (by 2.5 h and 3.6 h, respectively), consistent with these NA mutations delaying the release of viral progeny from newly infected cells. Cells infected by H1N1pdm09 virus carrying the I223V mutation display a disadvantageous, shorter infectious lifespan (17 h shorter) than those infected with the wild-type or MUT-H275Y strains. In terms of compensating traits, the H275Y mutation in the H1N1pdm09 background results in increased virus infectiousness, as we reported previously, whereas the I223V exhibits none, leaving it overall less fit than both its wild-type counterpart and the MUT-H275Y strain. Using computer simulated competition experiments, we determine that in the presence of oseltamivir at doses even below standard therapy, both the MUT-H275Y and MUT-I223V dominate their wild-type counterpart in all aspects, and the MUT-H275Y outcompetes the MUT-I223V. The H275Y mutation should therefore be more commonly observed than the I223V mutation in circulating H1N1pdm09 strains, assuming both mutations have a similar impact or no significant impact on between-host transmission. We also show that mathematical modelling offers a relatively inexpensive and reliable means to quantify inter-experimental variability and assess the reproducibility of results.
Dairy Products and Ovarian Cancer: A Pooled Analysis of 12 Cohort Studies

Background: Dairy foods and their constituents (lactose and calcium) have been hypothesized to promote ovarian carcinogenesis. Although case-control studies have reported conflicting results for dairy foods and lactose, several cohort studies have shown positive associations between skim milk, lactose, and ovarian cancer. Methods: A pooled analysis of the primary data from 12 prospective cohort studies was conducted. The study population consisted of 553,217 women among whom 2,132 epithelial ovarian cases were identified. Study-specific relative risks and 95% confidence intervals were calculated by Cox proportional hazards models and then pooled by a random-effects model. Results: No statistically significant associations were observed between intakes of milk, cheese, yogurt, ice cream, and dietary and total calcium intake and risk of ovarian cancer. Higher lactose intakes comparing ≥30 versus <10 g/d were associated with a statistically significant higher risk of ovarian cancer, although the trend was not statistically significant (pooled multivariate relative risk, 1.19; 95% confidence interval, 1.01-1.40; Ptrend = 0.19). Associations for endometrioid, mucinous, and serous ovarian cancer were similar to the overall findings. Discussion: Overall, no associations were observed for intakes of specific dairy foods or calcium and ovarian cancer risk. A modest elevation in the risk of ovarian cancer was seen for lactose intake at the level that was equivalent to three or more servings of milk per day. Because a new dietary guideline recommends two to three servings of dairy products per day, the relation between dairy product consumption and ovarian cancer risk at these consumption levels deserves further examination. (Cancer Epidemiol Biomarkers Prev 2006;15(2):364–72)
Feature normalization using MVAW processing for spoken language recognition

This study presents a noise robust front-end postprocessing technology. After cepstral feature analysis, the feature normalization is usually applied for noisy reduction in spoken language recognition. We investigate a highly effective MVAW processing based on standard MFCC and SDC features on NIST-LRE 2007 tasks. The procedure includes mean subtraction, variance normalization, auto-regression moving-average filtering and feature warping. Experiments were conducted on a common GMM-UBM system. The results indicated significant improvements in recognition accuracy.
Sibling relationship quality: a longitudinal study of twins and their families

The overarching goal of this thesis was to examine sibling relationship quality in young twin children, as well as the ways in which this key bond is associated with other familial relationships within the home environment. The three articles included were part of a longitudinal and multi-method study, run by myself and my colleague - the Twins, Family and Behaviour study. Accounts were collected from 282 mothers and 132 fathers of twins, over a two-year time period. Parents completed postal questionnaires and a telephone interview, and observations via Skype recorded them interacting with each of their children. The research was unique, as it employed a number of novel measures and sophisticated analyses that have not yet been used within a longitudinal twin sample such as this. Results showed that, contrary to expectations, no mean level differences emerged when monozygotic twin pairs, dizygotic twin pairs, and non-twin pairs were compared on their sibling relationship quality (Paper 1). Behavioural genetic modelling also revealed that sibling interactions were mainly influenced by the shared environment, common to both children within the dyad, but also by the genetic propensities of the siblings themselves (Paper 1). Using the innovative Preschool Five Minute Speech Sample interview, we found that mothers who expressed more family-wide positive, and less family-wide negative, emotion towards their children reported more positivity within the sibling relationship – even when controlling for questionnaire measures of the mother-child relationship (Paper 2). Finally, opposing the majority of past literature, cross-lagged tests evidenced that earlier positivity within the sibling bond was predictive of later marital satisfaction, and of positivity within both the mother-child and the father-child bond (Paper 3). The implications of the findings include: the generalisability of studies of twins in childhood to the wider non-twin sibling population (Paper 1); the usefulness of maternal speech sample measures in capturing unique variance in sibling relationship quality (Paper 2); and the impact of affectionate sibling exchanges on entire family systems (Paper 3). Future research would benefit from exploring the nature of the relationship between twin brothers and sisters further, using both younger and older children’s reports of their family interactions, within a more ethnically and socioeconomically diverse sample.
On-line Summarization of Time-series Documents using a Graph-based Algorithm

As enormous amount of electronic documents on the Web have been increasing, the necessity of automatic summarization has also been increasing to help people grasp the essential points of the documents. Many summarization techniques dealing with single document and multi-documents have been studied. However, due to the increase of the documents which report the change of topics along a timeline, called time-series documents, in recent years, a summarization technique which generates a summary of timeseries documents, called timeline summarization, has been actively studied as an area of automatic summarization. There are different difficulties in summarizing time-series documents from other type of automatic summarization. The basic approach for timeline summarization is to extract sentences which describe major events in object documents in chronological order to generate a timeline summary. However, unlike the prior studies of timeline summarization, we particularly focus on online summarization of time-series documents and propose an on-line graph-based timeline summarization method. With our proposed method, a summary of time-series documents can be generated at any point of time when it is required. We conduct experiments to investigate the ability of our proposed method, evaluate the results with ROUGEmetrics, and show our proposed method produces a better summary compared to other representative summarization methods.
Vehicle detection and tracking at nighttime for urban autonomous driving

This paper proposes a method for on road detecting and tracking of multi vehicles at nighttime in urban environment. The features of vehicles including root and part filters are learned as a weighted deformable object model through the combination of a latent support vector machine (LSVM) and histograms of oriented gradients (HOG). Detected vehicles are tracked through a particle filter which estimates near optimum likelihoods by calculating the maximum HOG features compatibility for both root and parts of the tracked vehicles. Tracking likelihoods are iteratively used as a priori probability to generate vehicle hypothesis regions. Extensive experiments with close range IR camera in urban scenarios showed that the efficiency of the proposed method for detecting and tracking of multi vehicles at night time.
Evaluation of Insulin Medium or Chondrogenic Medium on Proliferation and Chondrogenesis of ATDC5 Cells

Background. The ATDC5 cell line is regarded as an excellent cell model for chondrogenesis. In most studies with ATDC5 cells, insulin medium (IM) was used to induce chondrogenesis while chondrogenic medium (CM), which was usually applied in chondrogenesis of mesenchymal stem cells (MSCs), was rarely used for ATDC5 cells. This study was mainly designed to investigate the effect of IM, CM, and growth medium (GM) on chondrogenesis of ATDC5 cells. Methods. ATDC5 cells were, respectively, cultured in IM, CM, and GM for a certain time. Then the proliferation and the chondrogenesis progress of cells in these groups were analyzed. Results. Compared with CM and GM, IM promoted the proliferation of cells significantly. CM was effective for enhancement of cartilage specific markers, while IM induced the cells to express endochondral ossification related genes. Although GAG deposition per cell in CM group was significantly higher than that in IM and GM groups, the total GAG contents in IM group were the most. Conclusion. This study demonstrated that CM focused on induction of chondrogenic differentiation while IM was in favor of promoting proliferation and expression of endochondral ossification related genes. Combinational use of these two media would be more beneficial to bone/cartilage repair.
Production prediction of conventional and global positioning system–based earthmoving systems using simulation and multiple regression analysis

Accurate estimation of construction production, which is composed of productivity and unit costs, allows con- struction planners and managers to have excellent control over current processes and to correctly predict the production of similar projects in the future. Due to the need for accurate production estimation, selection of the appropriate construction technology is a critical factor in the success of a project. This paper presents a methodology for developing a model capa- ble of predicting productivity and unit costs using several procedures, such as actual data collection, input data generation using construction simulation, and multiple regression analysis. An earthmoving operation was analyzed to estimate the proposed methodology's prediction of construction production. A global positioning system (GPS)-based earthmoving system was selected as the new construction technology to be compared with the conventional system, to evaluate the decision-making process at a jobsite. The proposed methodology is expected to provide users with a basis for selecting appropriate technology. The case study presented in this paper demonstrates how to utilize the proposed methodology and analyze its predicted results.
Image representation and processing through multiscale local jet features

We propose a unified framework for representing and processing images using a feature space related to local similarity. We choose the multiscale and versatile local jet feature space to represent the visual data. This feature space may be reduced by vector quantisation and/or be represented by data structures enabling efficient nearest neighbours search (e.g. kd-trees). We show the interest of the local jet feature space processing through three fundamental low level tasks: noise reduction, motion estimation and background modelling/subtraction. We also show the potential of our system in terms of visual representation for higher level (e.g. object modelling and recognition) tasks.
RaHeC: A Mechanism of Resource Management for Heterogeneous Clouds

Heterogeneous cloud provides a feasible and attractive kind of infrastructure to the cloud applications which want to obtain high performance, availability or profit. Meanwhile, the cloud providers consider heterogeneous cloud as an ideal form to manage their computing resource since it can improve the utilization of their computing resources and extend the computing power of an individual provider. In this paper, we analyze the structure of heterogeneous cloud, and propose a framework of multi-objective constrained resource management, including dynamic profit-driven provisioning, availability-aware placement and power-saved consolidation. The result of our experiments has demonstrated the feasibility and effectiveness of the proposed framework.
Higher intake of fruits, vegetables or their fiber reduces the risk of type 2 diabetes: A meta‐analysis

Some previous studies reported no significant association of consuming fruit or vegetables, or fruit and vegetables combined, with type 2 diabetes. Others reported that only a greater intake of green leafy vegetables reduced the risk of type 2 diabetes. To further investigate the relationship between them, we carried out a meta‐analysis to estimate the independent effects of the intake of fruit, vegetables and fiber on the risk of type 2 diabetes.
An easy-to-implement Benchmarking Tool for Mobile Tablet-PC Visual Pose Estimation

Recently, researchers are interested in mobile device based computer vision applications. An accurate visual pose estimation is a common and important subtask. To quantitatively evaluate the accuracy, ground truth visual pose datasets are needed. However, the lack of inexpensive and easy benchmarking tool for mobile device based visual poses estimation makes it difficult, if not impossible, to quantitatively evaluate the estimated visual poses. In this paper, a novel and easy-to-implement experimental setup is proposed to generate ground truth visual pose data for handheld tablet-PC. The tablet-PC screen is leveraged to display a calibration pattern every time the on-board camera captures an image. The tablet-PC screen image is captured by another camera and is used to estimate the visual pose of the tablet-PC. An experimental environment is setup for parameter calibration and pose accuracy verification. Extensive experimental results with quantitative analysis demonstrate the accuracy and the generality of our tool.
NV-Heaps: making persistent objects fast and safe with next-generation, non-volatile memories

Persistent, user-defined objects present an attractive abstraction for working with non-volatile program state. However, the slow speed of persistent storage (i.e., disk) has restricted their design and limited their performance. Fast, byte-addressable, non-volatile technologies, such as phase change memory, will remove this constraint and allow programmers to build high-performance, persistent data structures in non-volatile storage that is almost as fast as DRAM. Creating these data structures requires a system that is lightweight enough to expose the performance of the underlying memories but also ensures safety in the presence of application and system failures by avoiding familiar bugs such as dangling pointers, multiple free()s, and locking errors. In addition, the system must prevent new types of hard-to-find pointer safety bugs that only arise with persistent objects. These bugs are especially dangerous since any corruption they cause will be permanent. We have implemented a lightweight, high-performance persistent object system called NV-heaps that provides transactional semantics while preventing these errors and providing a model for persistence that is easy to use and reason about. We implement search trees, hash tables, sparse graphs, and arrays using NV-heaps, BerkeleyDB, and Stasis. Our results show that NV-heap performance scales with thread count and that data structures implemented using NV-heaps out-perform BerkeleyDB and Stasis implementations by 32x and 244x, respectively, by avoiding the operating system and minimizing other software overheads. We also quantify the cost of enforcing the safety guarantees that NV-heaps provide and measure the costs of NV-heap primitive operations.
Snack time in the lab

This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007 challenge in ten out of twenty categories. The system relies heavily on deformable parts. While deformable part models have become quite popular, their value had not been demonstrated on difficult benchmarks such as the PASCAL challenge. Our system also relies heavily on new methods for discriminativ training. We combine a margin-s nsiti e approach for data mining hard negative examples with a formalism we call latent SVM. A latent SVM, like a hidden CRF, leads to a non-convex training problem. However, a latent SVM is semi-convex and the training problem becomes convex once latent information is specified for the positive examples. We believe that our training methods will eventually make possible the effective use of more latent information such as hierarchical (grammar) models and mo els involving latent three dimensional pose.