Miracle-dz/UniFAR-FTUs huggingface dataset:
Political action through environmental shareholder resolution filing: applicability to Canadian Oil Sands?

Research on the efficacy of social and environmental shareholder resolutions often fails to consider their strategic value in the context of policy outreach. Research on investor-driven governance networks and shareholder activism as a social movement illuminates strategies for organized shareholder coalitions to use a coordinated resolution filing campaign to shape the rules and norms under which business operates. These strategies are examined through qualitative case study analysis of two environmental shareholder campaigns: one organized by Ceres (Coalition for Environmentally Responsible Economies) addressing climate change and the other organized by Investor Environmental Health Network (IEHN) addressing hydraulic fracturing. These case studies show that resolution filing with broad investor appeal and linked to a policy agenda can achieve change beyond targeted companies. Case study insights may contribute to the formation of a Canadian shareholder coalition organized around improved corporate disclosure of Oil Sands risks and improved government monitoring of environmental impacts. Investor groups, mostly Canadian, have framed the environmental and social issues in terms that resonate with the investment community and policy makers. Investor activists in Canada, the US and Europe have filed a number of shareholder resolutions at Oil Sands companies. This marks progress towards investor coalition formation with coordinated shareholder action and a multi-jurisdictional reach.
External scaffold of spherical immature poxvirus particles is made of protein trimers, forming a honeycomb lattice

During morphogenesis, poxviruses undergo a remarkable transition from spherical immature forms to brick-shaped infectious particles lacking helical or icosahedral symmetry. In this study, we show that the transitory honeycomb lattice coating the lipoprotein membrane of immature vaccinia virus particles is formed from trimers of a 62-kD protein encoded by the viral D13L gene. Deep-etch electron microscopy demonstrated that anti-D13 antibodies bound to the external protein coat and that lattice fragments were in affinity-purified D13 preparations. Soluble D13 appeared mostly trimeric by gel electrophoresis and ultracentrifugation, which is consistent with structural requirements for a honeycomb. In the presence or absence of other virion proteins, a mutated D13 with one amino acid substitution formed stacks of membrane-unassociated flat sheets that closely resembled the curved honeycombs of immature virions except for the absence of pentagonal facets. A homologous domain that is present in D13 and capsid proteins of certain other lipid-containing viruses support the idea that the developmental stages of poxviruses reflect their evolution from an icosahedral ancestor.
A 25 GHz 3.3 dB NF low noise amplifier based upon slow wave transmission lines and the 0.18 μm CMOS technology

A 25 GHz low noise amplifier using standard 0.18 mum digital CMOS technology is presented. Matching networks were based upon slow wave transmissions lines. Peak gain of 12.8 dB at 24 GHz and in-band minimum noise figure less than 4 dB were obtained at a power consumption of 8 mW. These record results demonstrate the usefulness of the slow wave transmission line approach. A compact model of slow wave transmission lines is briefly described as well.
Policy Uncertainty, Total Factor Productivity and Growth

The coil carrier for a print head is constructed from nested sheet metal bodies with upwardly bent legs, being aligned in pairs and held together by a common sleeve having an end face which has a singular relationship to a common end face of all the arms. The several armatures pivot on edges of respective one of the legs of each pair and are held by retraction springs against the common end face.
Hole Approximation-Dissemination Scheme for Bounded-Stretch Routing in Sensor Networks

The routing stretch in a sensor network with a large hole can be controlled if the network nodes have certain information about the hole location and shape, possibly by using some mechanism for hole boundary approximation and information dissemination. However, a finer approximation (for smaller stretch) leads to higher cost of dissemination, which could be unaffordable for the sensors. We provide an insightful analysis to this fundamental trade-off of the hole approximation problem, using a geometric model. Based on this we discuss an efficient approximation-dissemination scheme using a natural, heuristic approximation technique. For reasonable conditions (network is dense enough apart from the hole), we assure that the routing stretch is under a predefined threshold > 1 while the dissemination cost is also under tight control. Our initial experiment results also confirm that our approach is significantly more efficient and economical, compared to existing proposals.
A Hybrid Image Filtering Method for Computer-Aided Detection of Microcalcification Clusters in Mammograms

The presence of microcalcification clusters (MCs) in mammogram is a major indicator of breast cancer. Detection of an MC is one of the key issues for breast cancer control. In this paper, we present a highly accurate method based on a morphological image processing and wavelet transform technique to detect the MCs in mammograms. The microcalcifications are firstly enhanced by using multistructure elements morphological processing. Then, the candidates of microcalcifications are refined by a multilevel wavelet reconstruction approach. Finally, MCs are detected based on their distributions feature. Experiments are performed on 138 clinical mammograms. The proposed method is capable of detecting 92.9% of true microcalcification clusters with an average of 0.08 false microcalcification clusters detected per image.
Positive and negative functions of B lymphocytes in tumors

Accumulating evidence indicated that B lymphocytes exerted complex functions in tumor immunity. On the one hand, B lymphocytes can inhibit tumor development through antibody generation, antigen presentation, tumor tissue interaction, and direct killing. On the other hand, B lymphocytes have tumor-promoting functions. A typical type of B lymphocytes, termed regulatory B cells, is confirmed to attenuate immune response in a tumor environment. In this paper, we summarize the current understanding of B-cell functions in tumor immunology, which may shed light on potential therapeutic strategies against cancer.
Closed-Loop Adaptive Switched-Capacitor Step-Down DC-DC Converter for Piezoelectric Energy Harvesting

generator, perform an adaptive charging operation stage by stage (from the lower voltage to the higher one) for the protection of the battery load. Finally, the closed-loop ASCC is designed by OrCAD Pspice, and simulated for some cases: steady-state and dynamic responses (source/loading variation). All results are illustrated to show the efficacy of the proposed scheme.
Effect of the traffic bursts in the network queue

This thesis studies the effect of the traffic bursts in the queue. Knowledge of the queueing behavior provides opportunity for additional control and improved performance. Most existing work on queueing today is based on Long-Range-Dependence (LRD) and Self-similarity, two well-known properties of network traffic at large scales. However, network traffic shows bursty behavior on small scales which are not captured by traditional self-similar models. We leverage a decomposition of traffic into two components. The alpha component is the bursty part of the traffic consisting of only few high bandwidth connections. The beta component collects the residual traffic and is a Gaussian LRD process. The alpha component is highly non-Gaussian and bursty. We propose two models for the alpha component, a heavy-tailed self-similar process and a high rate ON/OFF source. Our results explain how size and type of bursts affect the queueing behavior.
Self-referenced, trimmed and compensated RF CMOS harmonic oscillators as monolithic frequency generators

Self-referenced, trimmed and temperature-compensated radio frequency (RF) CMOS LC, or harmonic oscillators (CHOs) are presented as high-accuracy and low-jitter monolithic frequency generators. CHOs are discussed within the context of recent efforts toward replacement of piezoelectric frequency references with silicon MEMS technology. In contrast, CHOs are self-referenced solid-state oscillators which can be fabricated in a standard microelectronic process technology. The CHO architecture and recent implementations are presented. Frequency- and time-domain performance of CHOs is reported and compared to the incumbent piezoelectric oscillators and emerging MEMS-referenced synthesizers. It is shown that CHOs achieve frequency error as low as plusmn26 ppm over 90degC and 1/6th the period jitter of MEMS-referenced synthesizers at the same frequency.
Analysis of the cross-dipole planar antennas using Theory of Characteristic Modes

The resonance characteristics of cross-dipole planar antennas are analyzed by using Theory of Characteristic Modes (TCM) in this paper. The resonant frequency, bandwidth, current distribution and other characteristics of the antenna are compared here. Unlike the traditional analysis methods, the mode decomposition is proposed here. It considering the radiating structure as a whole, seek the support mode of the structure, and complete the antenna design according to the mode characteristics. This analyzed method is simple, accurate, and could explain the antenna design problems completely.
Challenging the State: Devolution and the Battle for Partisan Credibility: A Comparison of Belgium, Italy, Spain, and the United Kingdom

1. The Centre-Periphery Conflict and Two Paradoxes 2. Centre-periphery Party Competition 3. Political Devolution and Credibility Constraints 4. Parties and Voters in Two Dimensions: A First Examination of the Landscape 5. The Emergence of the Peripheral Party Threat 6. Devolution: Making Electoral Moves Credible 7. State Parties' Electoral Strategies after Devolution 8. Peripheral Parties' Electoral Strategies after Devolution 9. Conclusions
Optimal Mesh Size in the Numerical Integration of an Ordinary Differential Equation

In the integration of a system of ordin'~ry differential equations, the simplest approach is to use a fixed step size. However, over some parts of the range of i~tegra~ion it: is generally possible to ~ake a larger step size wilhoue, seriously affecd~g the "local ~nmcatiou error. " This gives rise to the currently popular "halving and doubling" me~hod, in which one changes the step size ir~ such a way as to keep the local truncation error more or less constant. This, however, is not necessarily optimal since a smM1 local truncation error in some parts of the range of integration can give rise to a large total truncation error. The basic problem is then to choose the step size in an optimal way; i.e. for a fixed mmff)er of mesh points, how should one distribute the mesh points in o:der to achieve the smallest error ~ at the end of the range of integration. (One might ask instead that the integral of the square of the truncation error over the range of integration should be minimized instead of the error at the end of the interval. This is reasonable when the error over the entire range is of interest instead of simply the error at the end. This problem does not seem to have a simple closed fonn solution and we will not discuss it here.) The problem in this generality is extremely diffmult; hence we will first approximate it, by a simpler problem, and we will solve the simpler problem eom-pletely. Specifically, we use the results of P. Henriei [1] on the asymptotic behavior of the tnmcation error in order to get the simpler problem. In order to solve ~he simpler problem we make the following assumptions: (1 There is only one differential equation. (Otherwise, a simple closed form solution such as given here does not seem to exist; instead one has an unpleasant integral equation to solve.) (2) The (approximate) local truncation error has one sign throughout the range of integration. (Otherwise, the solution becomes very strange; one may find that it is necessary to make as large an error as possible over some parts of the range of integration.) (3) The functions involved are sufficiently smooth so that the results of Henrici are valid. We will also make some further smoothness assumptions as we go along. For practical investigation one can sometimes weaken these assumptions. Thus if there …
Transcription of the pst Operon of Clostridium acetobutylicum Is Dependent on Phosphate Concentration and pH

ABSTRACT The pst operon of Clostridium acetobutylicum ATCC 824 comprises five genes, pstS, pstC, pstA, pstB, and phoU, and shows a gene architecture identical to that of Escherichia coli. Deduced proteins are predicted to represent a high-affinity phosphate-specific ABC (ATP-binding cassette) transport system (Pst) and a protein homologous to PhoU, a negative phosphate regulon regulator. We analyzed the expression patterns of the pst operon in Pi-limited chemostat cultures during acid production at pH 5.8 or solvent production at pH 4.5 and in response to Pi pulses. Specific mRNA transcripts were found only when external Pi concentrations had dropped below 0.2 mM. Two specific transcripts were detected, a 4.7-kb polycistronic mRNA spanning the whole operon and a quantitatively dominating 1.2-kb mRNA representing the first gene, pstS. The mRNA levels clearly differed depending on the external pH. The amounts of the full-length mRNA detected were about two times higher at pH 5.8 than at pH 4.5. The level of pstS mRNA increased by a factor of at least 8 at pH 5.8 compared to pH 4.5 results. Primer extension experiments revealed only one putative transcription start point 80 nucleotides upstream of pstS. Thus, additional regulatory sites are proposed in the promoter region, integrating two different extracellular signals, namely, depletion of inorganic phosphate and the pH of the environment. After phosphate pulses were applied to a phosphate-limited chemostat we observed faster phosphate consumption at pH 5.8 than at pH 4.5, although higher optical densities were recorded at pH 4.5.
Algorithms with low computational cost for monitoring and analysis of Colombia soundscapes

Studies focused on soundscape are important on biological conservation, because natural sounds are permanent and with dynamic properties, they have been linked to the welfare of the environment and the structure of the landscape. These studies usually analyze the sound in time and frequency domains, with computationally heavy and centralized algorithms. However, new technologies for real time analysis requires distributed algorithms with low computational cost. Hence, the present work evaluates the computational cost of alternative methods with potential applicability in analysis of time-varying signals. The analyzed methods are short time Fourier transform, harmonic expansion, wavelet transform (analytical and non-analytical Morlet, Mexican hat, and Paul) and orthogonal polynomial expansion (Legendre, Chebyshev, and Hermite). A comparison between these methods is presented, in which processing time, memory consumption, quality of reconstruction and grouping index are some of the features selected, resulting in a useful computational cost ranking. The methods are applied to several signals generated with different procedures, such as artificial modulated signals and natural recorded sounds (provided by The Alexander von Humboldt Institute). In conclusion, Harmonic expansion, Chebyshev expansion, Legendre expansion and Short Time Fourier Transform are the best methods with excellent performance in all features.
Failure rates in introductory programming revisited

Whilst working on an upcoming meta-analysis that synthesized fifty years of research on predictors of programming performance, we made an interesting discovery. Despite several studies citing a motivation for research as the high failure rates of introductory programming courses, to date, the majority of available evidence on this phenomenon is at best anecdotal in nature, and only a single study by Bennedsen and Caspersen has attempted to determine a worldwide pass rate of introductory programming courses. In this paper, we answer the call for further substantial evidence on the CS1 failure rate phenomenon, by performing a systematic review of introductory programming literature, and a statistical analysis on pass rate data extracted from relevant articles. Pass rates describing the outcomes of 161 CS1 courses that ran in 15 different countries, across 51 institutions were extracted and analysed. An almost identical mean worldwide pass rate of 67.7% was found. Moderator analysis revealed significant, but perhaps not substantial differences in pass rates based upon: grade level, country, and class size. However, pass rates were found not to have significantly differed over time, or based upon the programming language taught in the course. This paper serves as a motivation for researchers of introductory programming education, and provides much needed quantitative evidence on the potential difficulties and failure rates of this course.
Political cycles in income from privatization: The case of Albania

The phenomenon of manipulation of the economy by the incumbent for electoral purpose is called Political Business Cycles (PBC). Using policy control economic instruments, such as fiscal and monetary instruments, governments may manipulate the economy to gain electoral advantage by producing growth and decreasing unemployment before elections. Earlier research on PBC in Albania found clear evidence of fiscal expansion before elections. In addition to increased income from taxes and borrowing, another source of financing the increased fiscal expansion in transition countries may be income from privatization, which is also the object of the analysis of this paper. In our analysis we apply standard econometric approach, used widely for research related to PBC. We test if income from privatization increases before elections. We find statistically significant increase of income from privatization before general (parliamentary) elections, which may lead us to conclude that one of the reasons may be to finance increased expenditures before elections. Another motivation, behind this behavior of the incumbent, may be rent - seeking. These results are of particular interest, as it is for the first time that income from privatization is analyzed in conjunction with PBC.
Sign language detection using 3D visual cues

A 3D visual hand gesture recognition method is proposed that detects correctly performed signs from stereo camera input. Hand tracking is based on skin detection with an adaptive chrominance model to get high accuracy. Informative high level motion properties are extracted to simplify the classification task. Each example is mapped onto a fixed reference sign by Dynamic Time Warping, to get precise time correspondences. The classification is done by combining weak classifiers based on robust statistics. Each base classifier assumes a uniform distribution of a single feature, determined by winsorization on the noisy training set. The operating point of the classifier is determined by stretching the uniform distributions of the base classifiers instead of changing the threshold on the total posterior likelihood. In a cross validation with 120 signs performed by 70 different persons, 95% of the test signs were correctly detected at a false positive rate of 5%.
Creative practice based on Freescale processor smart car with photoelectric sensor

This paper presents the design of a smart car system based on the Freescale MC9S12SX128 processor. Infrared photoelectric sensor was used to percept the path information. The motor driving system was designed with the MOSFET circuit and controlled by the PID algorithm. With the speed feedback module and steering gear module, the smart car can run along the track steadily and rapidly.
Machine learning with the internet of virtual things

Peripheral devices working in the context of the Internet of Things, specifically sensors, produce large amounts of data that can be used to infer knowledge. In this area, machine learning technologies are increasingly used to establish versatile models. In this article, we present a new architecture capable of running machine learning algorithms in a sensor network. This approach has advantages in terms of confidentiality and energy efficiency-related data transfer. First, we argue that some types of machine learning algorithms are consistent with this approach, particularly those based on the use of generative algorithms. Subsequently we detail our proposed architecture based on Internet of Things and Web of Things paradigms facilitating the integration in sensor networks. The convergence of generative models and Web Objects leads to the concept of virtual sensors exposing high-level knowledge using data from various sensors. Finally, we demonstrate the feasibility and performance of our proposal using a real scenario.
An Integrated Framework to Recommend Personalized Retention Actions to Control B2C E-Commerce Customer Churn

Considering the level of competition prevailing in Business-to-Consumer (B2C) E-Commerce domain and the huge investments required to attract new customers, firms are now giving more focus to reduce their customer churn rate. Churn rate is the ratio of customers who part away with the firm in a specific time period. One of the best mechanism to retain current customers is to identify any potential churn and respond fast to prevent it. Detecting early signs of a potential churn, recognizing what the customer is looking for by the movement and automating personalized win back campaigns are essential to sustain business in this era of competition. E- Commerce firms normally possess large volume of data pertaining to their existing customers like transaction history, search history, periodicity of purchases, etc. Data mining techniques can be applied to analyse customer behaviour and to predict the potential customer attrition so that special marketing strategies can be adopted to retain them. This paper proposes an integrated model that can predict customer churn and also recommend personalized win back actions.