Miracle-dz/UniFAR-FTUs huggingface dataset:
The specificity of extracellular glycoprotein complexes in mediating cellular adhesion

Complexes containing glycoproteins and glycosaminoglycans were released into the culture medium by both smooth and skeletal muscle cells. The particles, termed adherons, from three smooth muscle cell lines promoted cell-substratum adhesion of a clonal sympathetic nerve cell line, PC12. In contrast, the glycoprotein complexes from three skeletal muscle preparations inhibited the adhesion of PC12 cells to Petri dish surfaces. The skeletal muscle adherons all sedimented in calcium-free sucrose gradients with an S value of 16, while the smooth muscle particles had a sedimentation value of 12. Although both classes of adherons contained fibronectin and collagen, hyaluronic acid was present only in those from skeletal muscle. An antiserum prepared against skeletal muscle adherons blocked myoblast adhesion to skeletal muscle adherons but did not alter PC12 adhesion to smooth muscle adherons. These data suggest that the glycoprotein complexes released by muscle have some intrinsic specificity with respect to their ability to mediate cellular adhesion.
Back to the User

hree hundred years ago, alchemy became chemistry. Arcane art became science when its practitioners abandoned secrecy to embrace process transparency and peer review. Today, software engineering is undergoing a similar transition, moving from closed to open source development. Only when we complete this transition, adopting open source development as a normal practice, can software development assume its place as a mature engineering discipline.
Ieee Intelligent Transportation Systems Magazine @bullet 6 @bullet Summer 2017 Smart Parking Guidance, Monitoring and Reservations: a Review

—As the urban population is increas­ ing, more and more cars are circulating in the city to search for parking spaces which con­ tributes to the global problem of traffic conges­ tion. To alleviate the parking problems, smart parking systems must be implemented. In this paper, the background on parking problems is introduced and relevant algorithms, systems, and techniques behind the smart parking are reviewed and discussed. This paper provides a good insight into the guidance, monitoring and reservations components of the smart car park­ ing and directions to the future development.
An efficient VLIW DSP architecture for baseband processing

The VLIW processors with static instruction scheduling and thus deterministic execution times are very suitable for high-performance real-time DSP applications. But the two major weaknesses in VLIW processors prevent the integration of more functional units (FU)for a higher instruction issuing rate & the dramatically growing complexity in the register file (RF), and the poor code density. We propose a novel ring-structure RF, which partitions the centralized RF into 2N subblocks with an explicit N-by-N switch network for N FU. Each subblock only requires access ports for a single FU. We also propose the hierarchical VLIW encoding with variable-length RISC-like instructions and NOP removal. The ring-structure RF saves 91.88% silicon area and reduces 77.35% access time of the centralized RF. Our simulation results show that the proposed instruction set architecture with the exposed ring-structure RF has comparable performance with the state-of-the-art DSP processors. Moreover, the hierarchical VLIW encoding can save 32%/spl sim/50% code sizes.
Il potere di voto nel sistema parlamentare italiano in regime proporzionale e la dinamica della spesa pubblica dal 1960 al 1990

We study the Granger causality between the Shapley-Shubik index of voting power and Italian public expenditures from 1960 to 1990. The received wisdom that public expenditures' growth is determined by a cross-action of "all" the political groups elected by proportional electoral systems is not empirically verified for Italy. We show that only the most relevant (in terms of power) political groups cause the expenditures' growth. Moreover, the statistically significant causal relation from public expenditure to political powers suggests that the existing expenditures, once originated, were (amongst the) determinants for maintaining and strengthening the political power.
Stereo vision for the stabilization of a quadrotor

Stereo vision is a broad field that is part of computer vision. Autonomous mobile robots make use of stereo vision to detect obstacles and measure their relative distance to them for path planning. Technically, it consists of the processing of two images simultaneously adquired by two cameras, from a given scene. Stereo vision is a field with multiple applications and many resources had been invested for research in this subject. In this paper, we present a stereo vision based controller design and its implementation on a mini helicopter with 4 rotors known as quadrotor. The dynamic model is obtained using the well known Euler-Lagrange approach. Experiment results show good performance of the proposed controller using "real-time" optical flow and image processing from two cameras.
Exploring How Symptoms of Attention-Deficit/Hyperactivity Disorder Are Related to Reading and Mathematics Performance

Children with attention-deficit/hyperactivity disorder (ADHD) tend to perform more poorly on tests of reading and mathematical performance than their typical peers. Quantitative genetic analyses allow for a better understanding of the etiology of ADHD and reading and mathematics outcomes, by examining their common and unique genetic and environmental influences. Analyses were conducted on a sample 271 pairs of 10-year-old monozygotic and dizygotic twins drawn from the Western Reserve Reading and Mathematics Project. In general, the results suggested that the associations among ADHD symptoms, reading outcomes, and math outcomes were influenced by both general genetic and general shared-environment factors. The analyses also suggested significant independent genetic effects for ADHD symptoms. The results imply that differing etiological factors underlie the relationships among ADHD and reading and mathematics performance. It appears that both genetic and common family or school environments link ADHD with academic performance.
On content-driven search-keyword suggesters for literature digital libraries

We propose and evaluate a "content-driven search keyword suggester" for keyword-based search in literature digital libraries. Suggesting search keywords at an early stage, i.e., while the user is entering search terms, is helpful for constructing more accurate, less ambiguous, and focused search keywords for queries. Our search keyword suggestion approach is based on an a priori analysis of the publication collection in the digital library at hand, and consists of the following steps. We (i) parse the document collection using the Link Grammar parser, a syntactic parser of English, (ii) group publications based on their "most-specific" research topics, (iii) use the parser output to build a hierarchical structure of simple and compound tokens to be used to suggest search terms, (iv) use TextRank, a text summarization tool, to assign topic-sensitive scores to keywords, and (v) use the identified research-topics to help user aggregate search keywords prior to the actual search query execution. We experimentally show that the proposed framework, which is optimized to work on literature digital libraries, promises a more scalable, high quality, and user-friendly search-keyword suggester when compared to its competitors. We validate our proposal experimentally using a subset of the ACM SIGMOD Anthology digital library as a testbed, and by employing the research-pyramid model to identify the "most-specific" research topics.
Ontologies and Planners A Statement of Interest

• decoupling planner user interface from planner and executive software components, by declarative specifications of information. In this statement of interest, I will briefly discuss challenges and opportunities in each of these areas. I will also briefly discuss the de facto standard ontology, PDDL (Ghallab et al. 1998; McDermott 2000; Fox & Long 2002), and how it relates to these topics. I have tried to capture some of my own puzzlement about how to make use of the riches of knowledge representation offered by ontology researchers. Ontology research seems to hold out the promise to greatly reduce and simplify the amount of domain engineering needed to build a practical planning system. And yet.
Encoding Through Patterns: Regression Tree–Based Neuronal Population Models

Although the existence of correlated spiking between neurons in a population is well known, the role such correlations play in encoding stimuli is not. We address this question by constructing pattern-based encoding models that describe how time-varying stimulus drive modulates the expression probabilities of population-wide spike patterns. The challenge is that large populations may express an astronomical number of unique patterns, and so fitting a unique encoding model for each individual pattern is not feasible. We avoid this combinatorial problem using a dimensionality-reduction approach based on regression trees. Using the insight that some patterns may, from the perspective of encoding, be statistically indistinguishable, the tree divisively clusters the observed patterns into groups whose member patterns possess similar encoding properties. These groups, corresponding to the leaves of the tree, are much smaller in number than the original patterns, and the tree itself constitutes a tractable encoding model for each pattern. Our formalism can detect an extremely weak stimulus-driven pattern structure and is based on maximizing the data likelihood, not making a priori assumptions as to how patterns should be grouped. Most important, by comparing pattern encodings with independent neuron encodings, one can determine if neurons in the population are driven independently or collectively. We demonstrate this method using multiple unit recordings from area 17 of anesthetized cat in response to a sinusoidal grating and show that pattern-based encodings are superior to those of independent neuron models. The agnostic nature of our clustering approach allows us to investigate encoding by the collective statistics that are actually present rather than those (such as pairwise) that might be presumed.
An InP HBT common-base amplifier with tunable transimpedance for 40 Gb/s applications

This work features a 40 Gb/s common-base transimpedance amplifier (TIA) design that employs electronically tunable transimpedance to compensate for various combinations of photodetector and hybrid interconnect parasitics. A tuning transimpedance BW range of 10 GHz is demonstrated using this approach. Integrated with a 40 fF photodetector, the transimpedance amplifier achieves 62.3 dB-ohm (1.3 kohm) differential transimpedance with a bandwidth of 39.3 GHz while consuming only 165 mW. This corresponds to a transimpedance-BW product per DC power of 310 ohms-GHz/mW. To the author's knowledge, this work is the first published demonstration of a tunable transimpedance amplifier for 40 Gb/s applications, and is among the highest TZ-BWP per DC power reported for a 40 Gb/s TIA.
Euro Area Inflation Differentials: Unit Roots, Structural Breaks and Non-Linear Adjustment

This paper examines the time series properties of inflation differentials in twelve EMU countries. We compute three alternative measures of inflation differentials using deviations from the policy reference value implied by the Maastricht Treaty, the ECB target, and deviations from the EMU average inflation. The evidence from standard linear unit root tests indicate that inflation differentials are highly persistent. However, when we account for endogenously determined structural breaks, we obtain greater support for stationarity. In addition, when we allow for the possibility that inflation differentials can be charterised by a non-linear mean reverting process we find evidence of stationarity. Our empirical results suggest that once we allow for structural breaks or non-linearities, inflation differentials do not consistently intensify real divergence in the euro area
A Grid Algorithm for Injection Gate Location Optimization Based on MDG

The injection mold optimization problems always require huge computer resources, so the grid is a good choice for solving these problems. But for the heterogeneous, distributed and dynamic characters of the grid resources, it is difficult to finish the complex problems efficiently in collaborative way by grid. Based on the Globus Toolkits 4, a four-layer Mold Design Grid (MDG) platform was constructed to meet resource sharing for the complex injection mold optimization. By using multi-population genetic strategy and information-entropy based searching technique, a grid algorithm was presented to optimize the gate location of injection mold on MDG. It deals with the massive high coupling task-blocks in collaborative way and reduces the times of the iteration efficiently. Examples have been conducted successfully by using the proposed grid algorithm on MDG, and results indicate that the proposed grid algorithm performs high speedup and efficiency.
A Smart Voxelization Algorithm Zhao Dong Wei Chen Hujun Bao Hongxin Zhang Qunsheng Peng State Key

In this paper we present a real-time voxelization algorithm which is implemented with newest programmable graphics hardware. The algorithm first converts geometric model into discrete voxel space. The resultant voxels are then encoded as 2D textures and stored in three intermediate sheet buffers called directional sheet buffers according the orientation of the boundary surface. These buffers are finally synthesized into one worksheet. The whole pipeline traverses the geometric model only once and is accomplished entirely in GPU (graphics processing unit), yielding a real-time and configurable voxelization engine. The algorithm is simple to implement and can be added easily to diverse applications such as volume-based modelling, transparent rendering and collision detection.
Grounding Social Theory in the Natural Sciences

All social relationships and the coordination of any activity between humans depend upon the transmission, reception, storage and processing units of information measured in bytes. Bytes provide a basis for grounding the study of social relationship and institutions in the natural sciences because their transmission or storage requires changes in energy or physical states. All humans are restricted in their ability to obtain data, information, knowledge, wisdom, or manage complexity, because of their physiological and neurological limits to transact bytes. This introduces an instrumental criterion for investigating, evaluating and designing the informational architecture of organisations and social relationships. Transaction Byte Analysis (TBA) is introduced as a framework to subsume Transaction Cost Economics (TCE). TCE is based on the normative need to economise the social construct of cost while TBA is based on the instrumental need to economise bytes. Human limits in transacting bytes are quantified and used to explain information overload and bounded rationality. Four modes of information and control with their strengths and weaknesses are identified and related to four modes of governing relationships. Unlike TCE and many other theories, TBA accepts that individuals can be either, or both, cooperative/competitive, trusting/suspicious and/or altruistic/selfish. Laws of governance are introduced that provide methods for obtaining reliable results from unreliable components. These provide criteria for evaluating or designing social organisations to reliably achieve their purpose. The utility of TBA as a framework for investigating the form and effectiveness of institutions is illustrated with micro and macro examples.
Roles-based Access Control Modeling and Testing for Web Applications

Web applications are widely used in people's everyday life. They have permeated financial sectors, banking sectors, e-business and online shopping. Usually, different users have different permissions on these applications. Additionally, role-based access control (RBAC) mechanisms have been wildly integrated into web applications. The security and correctness of web applications are the most fundamental, crucial aspects to the success of business and organizations. In existing research work on modeling of RBAC, the user's roles and permissions are fixed and static, and do not consider that with the evolution and running of the system, the roles and permissions are dynamic. To the best of our knowledge, research work on role-based access control modeling and testing for web application has been seldom done. In this paper, taking the dynamic feature of roles and permissions into account, we propose an approach to modeling and testing web applications with role-based access control. We give out an algorithm to capture and compute the dynamicity of roles and permissions in running time. The FSM is employed to model the behavior of web applications, and then the augmented FSM (AFSM) is plied as a tool to model role-based access control. Finally, using the construction algorithm, the tests are generated automatically which satisfy the corresponding test coverage criteria.
The Accuracy of Producers' Probability Beliefs: Evidence and Implications for Insurance Valuation

The accuracy of producers' subjective probability beliefs is examined through a survey of large cash-grain farmers in Illinois. Findings reveal that their subjective probability beliefs about important weather variables are systematically mis-calibrated. The nature and extent of differences between subjective probability beliefs and probabilities based on long-term historic weather data are shown empirically, and through fitted calibration functions. The economic significance of inaccurate subjective probability beliefs is established in the context of insurance valuation. The results demonstrate that significant errors in producers' risk assessments and insurance valuation arise as a consequence of producers' systematically inaccurate probability beliefs.
Study on Profit Distribution in Upstream-Supply Chain with Manufacturer Dominating

This article mainly considers the profit distribution method in an upstream supply chain with manufacturer dominating, based on the balance of inventory cost and transportation cost. The profit distribution model is established to study three methods of profit distribution. The distribution coefficient lambda, which is specific and operative, can be got from the model solution. A numerical example is given to compare the three methods. Finally, the suitable case that matches each method is discussed and the implementing effect of each method is compared.
Two essays in the Indiana family cap provision

I use 1995 and 2()()() data from the Indiana Welfare Refonn Evaluation Project to investigate the effectiveness of a child cap. a provision that prevents families on welfare from receiving additional benefits for children conceived while the mother was receiving welfare. My principal focus is the relationship between the child cap and fertility, use of birth control. and practice of abstinence. I found that while individual characteristics were important in predicting fertility and use of birth control or abstinence. the child cap prOVision does not have a significant impact on any of our study variables.
Learning Object Recognition in a NeuroBotic System

Object localisation and identification is a crucial problem for advanced mobile service robots. We developed an object recognition system that localises and identifies objects using a colour-based visual attention control algorithm and a hierarchical neural network for object classification utilising hierarchical class grouping. The approach is evaluated in a test scenario where a robot is situated in front of a table. The robot has to identify and manipulate objects lying on this table. We evaluated the total object recognition performance and compared the effectiveness of different feature sets. The approach showed very encouraging results and meets real-time constraints.
Employment Effects of a Payroll-Tax Cut: Evidence from a Regional Tax Exemption Experiment

In this paper we evaluate the effects of a regional experiment that reduced payroll taxes by 3-6 percentage points in Northern Finland for three years. We match each firm in the target region with a similar firm in the control region and estimate the effect of the payroll-tax reduction by comparing employment and wage changes within the matched pairs before and after the start of the experiment. According to our results the reduction in payroll taxes led to somewhat faster wage growth in the target region. The increase in wages offset roughly half of the impact of the payroll-tax cut on the labour costs. The remaining labour cost reduction had no significant effects on employment.
Dividend and Capital Gains Taxation in a Cross-Section of Firms

I reconsider the effect of capital income taxation on firm size and firm growth by embedding the nucleus theory of firm development of Sinn (1991) into a framework of monopolistic competition with new firm creation. In a turnover of firms, firm destruction is counterbalanced by a permanent creation of new firms. Young firms are set up using an initial capital infusion of new equity and undergo an intermediate stage of internal growth until they finally reach a steady payout stage. The cross-section then contains firms of all ages and development stages. Dividend and capital gains tax have important effects on initial firm size and growth but also on the creation of new firms and thus on diversity in the economy. First, a differential treatment of dividends and capital gains introduces a distortion in the allocation of capital across firms. Second, dividend as well as capital gains tax are anticipated at the start-up stage of firms. While leaving the firm specific capital stock unaffected, the capitalisation is shown to depress firm creation and aggregate capital accumulation.
Inter-vehicle P2P communication experimental on-board terminal

It is expected that vehicles have on-board terminals to communicate with the fixed network and also with surrounding vehicles in the near future. This paper explains our developed inter-vehicle P2P (peer-to-peer) communication experimental on-board terminal, we nicknamed it "V-ant", which has the feature of adopting AODV (ad-hoc on-demand distance vector) protocol, control of AODV packets transmission direction using GPS data, and adaptive media switching between vehicle-to-vehicle ad-hoc communication, communication through access points, and PHS (personal handy-phone system in Japan).
Derivation of parallel-efficient structural recursive functions from declarative graph queries

Graphs play an important role today in managing big data, while structural recursion is powerful to process graphs by its flexibility. Designing efficient structural recursive functions to query distributed graphs is still a big challenge because of the performance constraints imposed by the bulk semantics of structural recursion. In this paper, we propose a solution that systematically generates parallel-efficient structural recursive functions from high-level declarative graph queries. Therefore, the complexity in developing efficient structural recursive functions is relaxed by our solution.