Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Local School Control Raise Student Outcomes?: Theory and Evidence on the Roles of School Autonomy and Community Participation

School autonomy and parental participation have been frequently proposed as ways of making schools more productive. Less clear is how governments can foster decentralized decision-making by local schools. This paper shows that across eight Latin-American countries, most of the variation in local control over school decisions exists within and not between countries. That implies that the exercise of local authority to manage schools is largely a local choice only modestly influenced by constitutional stipulations regarding jurisdiction over school personnel, curriculum and facilities. As a consequence, estimated impacts of local school autonomy, parental participation or school supplies on student performance must account for the endogeneity of local efforts to manage schools. Empirical tests confirm that local managerial effort by the principal and the parents and the adequacy of school supplies are strongly influenced by parental human capital and the size and remoteness of the community, and that these effects are only partially moderated by central policies regarding the locus of control over the schools. Correcting for endogeneity, parental participation and adequacy school supplies have strong positive effects on 4th grade test performance, but school autonomy has no discernable impact on school outcomes.
Finger Gaiting For Rotation of Sphere by Multifingered Robot Hand

Fine manipulation by multifingered robot hand is a new avenue in the area of robotic research. The ability to manipulate a part in a dexterous hand depends generally on the contact conditions between the fingers and object. It can be easily observed in fine manipulation where small motions and low velocities lead to dexterous grasp. In this paper we study a strategy for dexterous manipulation, which we call finger gaiting. We show how the finger gaiting may be used to control the fingers of a robot hand to generate the rotational motion of grasped object. A simulation for multifingered robotic hand has been developed for finger gaiting. Paper also investigates the problem of dexterous manipulation, how can robots affects the world around them by means of their end-effector? Dexterous manipulation is fundamental to robot operating independently, but progress in this area has been low.
Fluorescence Technique Description for Measuring Ca 2+ in Mice Sperm

Recently, fluorescence technique becomes very useful. It can allow for addressing a fundamental problem of cellular mechanism besides characterizing the species inside the cell to facilitate the diagnostic and prognostic value. Manipulation with fluorescent dyes provides many possibilities for their use as tags, probes, and sensors. These types can be intrinsic or extrinsic to the cell. They can become not only silent observers, but also participants, modulators or disruptors of specific activities outline the biological functions can be successfully studied quantitatively and qualitatively with fluorescence techniques.
Flip-Chip Approach for 500 GHz Broadband Interconnects

This paper presents the design and characterization of a broadband transition in the range dc to 500 GHz using the flip-chip concept. The extremely wideband performance is attained by optimizations in both process technology and electromagnetic design. On the process technology side, a thin-film process with scaled dimensions of 10 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> for via diameter and 2 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> bump height is employed for the chip and the carrier substrate. On the electromagnetic side, in addition to impedance matching, a detailed analysis of parasitic modes is considered for the design. The measurement results show less than 0.9-dB insertion loss per transition at 500 GHz and reflections below −18 dB over the entire dc to 500 GHz band.
Failure as a Service (FaaS): A Cloud Service for Large- Scale, Online Failure Drills

Cloud computing is pervasive, but cloud service outages still take place. One might say that the computing forecast for tomorrow is “cloudy with a chance of failure. ” One main reason why major outages still occur is that there are many unknown large-scale failure scenarios in which recovery might fail. We propose a new type of cloud service, Failure as a Service (FaaS), which allows cloud services to routinely perform large-scale failure drills in real deployments.
Isolation and Characterization of Tumor Cells from the Ascites of Ovarian Cancer Patients: Molecular Phenotype of Chemoresistant Ovarian Tumors

Tumor cells in ascites are a major source of disease recurrence in ovarian cancer patients. In an attempt to identify and profile the population of ascites cells obtained from ovarian cancer patients, a novel method was developed to separate adherent (AD) and non-adherent (NAD) cells in culture. Twenty-five patients were recruited to this study; 11 chemonaive (CN) and 14 chemoresistant (CR). AD cells from both CN and CR patients exhibited mesenchymal morphology with an antigen profile of mesenchymal stem cells and fibroblasts. Conversely, NAD cells had an epithelial morphology with enhanced expression of cancer antigen 125 (CA125), epithelial cell adhesion molecule (EpCAM) and cytokeratin 7. NAD cells developed infiltrating tumors and ascites within 12–14 weeks after intraperitoneal (i.p.) injections into nude mice, whereas AD cells remained non-tumorigenic for up to 20 weeks. Subsequent comparison of selective epithelial, mesenchymal and cancer stem cell (CSC) markers between AD and NAD populations of CN and CR patients demonstrated an enhanced trend in mRNA expression of E-cadherin, EpCAM, STAT3 and Oct4 in the NAD population of CR patients. A similar trend of enhanced mRNA expression of CD44, MMP9 and Oct4 was observed in the AD population of CR patients. Hence, using a novel purification method we demonstrate for the first time a distinct separation of ascites cells into epithelial tumorigenic and mesenchymal non-tumorigenic populations. We also demonstrate that cells from the ascites of CR patients are predominantly epithelial and show a trend towards increased mRNA expression of genes associated with CSCs, compared to cells isolated from the ascites of CN patients. As the tumor cells in the ascites of ovarian cancer patients play a dominant role in disease recurrence, a thorough understanding of the biology of the ascites microenvironment from CR and CN patients is essential for effective therapeutic interventions.
FPGA based system prototype for face location and recording of people getting on a public transport bus

Assault and robbery on the public transport is a social problem. Almost every day, people lose possessions and, in some cases, thieves or citizens get hurt or even die, in the process. In Mexico, attempts to reduce or prevent crime include vigilance by armed agents [1] and video cameras on public transport [2]. This work contributes to crime reduction and/or prevention on public transport by taking photographic records of people as they get on the bus, using an FPGA based system with camera and Secure Digital (SD) storage. An FPGA is used as the processing device which contains all the necessary logic to obtain the images from the camera, process them to locate the face, extract face region and store them into a SD media using an uncompressed BMP file. For face area location single channel image was used to extract regional attributes and their interregional relationship, resulting in a face detection algorithm with tolerance to skin tones and light conditions.
Clusterability Detection and Initial Seed Selection in Large Data Sets

The need for a preliminary assessment of the clustering tendency or clusterability of massive data sets is known. A good clusterability detection method should serve to in uence a decision as to whether to cluster at all, as well as provide useful seed input to a chosen clustering algorithm. We present a framework for the de nition of the clusterability of a data set from a distance-based perspective. We discuss a graphbased system for detecting clusterability and generating seed information including an estimate of the value of k { the number of clusters in the data set, an input parameter to many distance-based clustering methods. The output of our method is tunable to accommodate a wide variety of clustering methods. We have conducted a number of experiments using our methodology with stock market data and with the well-known BIRCH data sets, in two as well as higher dimensions. Based on our experiments and results we nd that our methodology can serve as the basis for much future work in this area. We report our results and discuss promising future directions.
Evolutionary state of magnetic chemically peculiar stars

Context. The photospheres of about 5–10% of the upper main sequence stars exhibit remarkable chemical anomalies. Many of these chemically peculiar (CP) stars have a global magnetic field, the origin of which is still a matter of debate. Aims. We present a comprehensive statistical investigation of the evolution of magnetic CP stars, aimed at providing constraints to the theories that deal with the origin of the magnetic field in these stars. Methods. We have collected from the literature data for 150 magnetic CP stars with accurate Hipparcos parallaxes. We have retrieved from the ESO archive 142 FORS1 observations of circularly polarized spectra for 100 stars. From these spectra we have measured the mean longitudinal magnetic field, and discovered 48 new magnetic CP stars (five of which belonging to the rare class of rapidly oscillating Ap stars). We have determined effective temperature and luminosity, then mass and position in the H-R diagram for a final sample of 194 magnetic CP stars. Results. We found that magnetic stars with $M > 3 ~M_\odot$ are homogeneously distributed along the main sequence. Instead, there are statistical indications that lower mass stars (especially those with $M \le 2~M_\odot$) tend to concentrate in the centre of the main sequence band. We show that this inhomogeneous age distribution cannot be attributed to the effects of random errors and small number statistics. Our data suggest also that the surface magnetic flux of CP stars increases with stellar age and mass, and correlates with the rotation period. For stars with $M > 3~M_\odot$, rotation periods decrease with age in a way consistent with the conservation of the angular momentum, while for less massive magnetic CP stars an angular momentum loss cannot be ruled out. Conclusions. The mechanism that originates and sustains the magnetic field in the upper main sequence stars may be different in CP stars of different mass.
Muscle synergy analysis of a set of lower extremity movements in quiet standing scenario: A preliminary study

Human joint movement is resulted from consequential contractions of multiple muscles, and the associated multiple muscles operate in a coordinate manner which is usually called muscle synergy. In a physiological sense, muscle synergy reflects the human muscles natural coordination patterns, driven by neural commands dispatched from the central nerve system (CNS). For different specific movement of human, the related muscle groups can present different coordination patterns correspondingly. This paper investigates the muscle synergy patterns with different movement in sagittal plane for one healthy subject during quiet standing scenario without disturbance of external force. Non-negative matrix factorization (NMF) algorithm is applied to extract the muscle synergies of eight muscles of lower extremity corresponding to specific movement, e.g., back leaning, squatting, and stepping. The paper analyzes the muscle synergy patterns considering combinations of knee and ankle joint flexion directions.
Single target detection and tracking using direction-of-arrival spectrum

This paper presents a track-before-detect algorithm based on the particle filter for simultaneously detecting and tracking a single target with nearly constant velocity. The measurement data available to the algorithm is the raw direction-of-arrival spectrum of the received wideband signals at a single observation platform. The proposed method does not require prior information on the target existence probability and it is capable of detecting a target of very low signal-to-noise ratio (-30dB). Simulation results show that the proposed algorithm demonstrates good performance in detecting and tracking a target with reasonably low errors in the estimated target states over the observation period.
The EU Fiscal Compact: Constitutionalization of Austerity and Preemption of Democracy in Europe

In the article on the EU Fiscal Compact we are trying to show that the Fiscal Compact as adopted in its current form does not necessarily lead to the improved quality of fiscal policy in the Eurozone. At the same time it disproportionally interfers with the autonomous fiscal policies of the member states and with their constitutional arrangements. In combination with the indiscriminatory implementation of austerity policy across EU the Fiscal Compact may further supress socio-economic developments in many of the EU countries and their regions. We are of the opinion that the Fiscal Compact in its current form – if adopted and strictly implemented as envisaged – may further deteriorate the socio-economic situation in many parts of the EU. Alternatively, we propose more decentralized approach toward fiscal consolidation in the EU member states and their regions. Such an approach would be more tailored to the different needs and different situations and would allow more proactive development approach for many local communities, regions and member states in the EU. Therefore, more bottom-up instead of top-down approach to fiscal consolidation and to more inclusive, more balanced and more diverse development may be viewed as an alternative approach to the EU integration process.
Node Immunization over Infectious Period

Locating nodes to immunize in computer/social networks to control the spread of virus or rumors has become an important problem. In real world contagions, nodes may get infected by external sources when the propagation is underway. While most studies formalize the problem in a setting where contagion starts at one time point, we model a more realistic situation where there are likely to be many breakouts of contagions over a time window. We call this the node immunization over infectious period (NIIP) problem. We show that the NIIP problem is NP-hard and remains so even in directed acyclic graphs. We propose a NIIP algorithm to select $k$ nodes to immunize over a time period. Simulation is performed to estimate a good distribution of $k$ over the time period. For each time point, the NIIP algorithm will make decisions which nodes to immunize given the estimated value of $k$ for that time point. Experiments show that the proposed NIIP algorithm outperform the state-of-the-art algorithms in terms of both effectiveness and efficiency.
Survival of the Stillest: Predator Avoidance in Shark Embryos

Sharks use highly sensitive electroreceptors to detect the electric fields emitted by potential prey. However, it is not known whether prey animals are able to modulate their own bioelectrical signals to reduce predation risk. Here, we show that some shark (Chiloscyllium punctatum) embryos can detect predator-mimicking electric fields and respond by ceasing their respiratory gill movements. Despite being confined to the small space within the egg case, where they are vulnerable to predators, embryonic sharks are able to recognise dangerous stimuli and react with an innate avoidance response. Knowledge of such behaviours, may inform the development of effective shark repellents.
Talking past each other: Academic and media framing of literacy

The technological and social shifts of the past several decades have brought about new modes of learning, participation and civic engagement. As young people work, play and socialize in online spaces, the academic community is exploring the challenges and possibilities of education in the digital age. New definitions of literacy emerge to address the importance of digital skills, play and collaboration. This paper explores the diverging perspectives on literacy adopted by new media scholars and old media outlets. Thematic coverage in the New York Times from the last four years is analysed and compared to academic texts produced in the same period. Measures of salience for literacy as a topic are used in conjunction with framing analysis based on semantic mapping. The results of this study suggest that mainstream media employ a legacy literacy frame, stressing basic language competencies and traditional institutions. That perspective is markedly different from the academic discourse, which emphasizes a host of new social, technological and critical evaluation skills.
Antibody against nerve growth factor-inducible large external (NILE) glycoprotein labels nerve fiber tracts in the developing rat nervous system

The NILE (nerve growth factor-inducible large external) glycoprotein is a 230,000-dalton molecule found on the surface of PC12 cells. Immunologically cross-reactive glycoproteins in the molecular weight range of 215,000 to 230,000 have been found on many types of neurons in culture. Using immunohistochemical methods, we have shown that NILE- related glycoproteins are present in neuronal fiber tracts of the developing rat brain. Antibody against the NILE glycoprotein specifically labels processes that appear identical to those recognized by antibodies against the neurofilament triplet of proteins. These processes are clearly distinct from the radial glial fibers recognized by antibody against the intermediate filament protein vimentin. NILE glycoprotein is not distributed uniformly over the entire neuronal surface but is concentrated on neurites and is much less abundant on cell bodies. NILE-positive fiber tracts are first seen in the spinal cord and rhombencephalon on embryonic day 11 and over the next 2 days appear in the mesencephalon and diencephalon. Staining in the telencephalon is not seen until embryonic day 15. The appearance of NILE immunoreactivity in these various regions closely parallels the appearance of neurofilament polypeptides, suggesting that NILE-related glycoproteins are present during the early phases of fiber tract formation. This idea is supported by the finding that the NILE glycoprotein can be found postnatally in parts of the nervous-system such as the cerebellar cortex and olfactory bulb which undergo major histogenesis during the postnatal period. In the cerebellum the appearance of NILE immunoreactivity in the two major fiber zones, the molecular layer and the white matter, parallels the development of the fiber structure of these layers. These findings support tissue culture studies which suggest a role for the NILE glycoprotein in mediating nerve fiber fasciculation.
Intra-cavity absorption sensor based on erbium-doped fiber laser

The sensitivity of power to relative cavity loss of the intra-cavity sensor based on erbium-doped fiber laser is investigated. Theoretical analysis and simulation show that the coupling ratio of coupler and the pump power have a great effect on sensitivity of ring intra-cavity sensor. And we have experimentally found that the sensitivity can be significantly enhanced as pump power approaches the threshold and the coupling ratio is higher.
On Economic Perspectives of Internet Security : The Problem of Designing Optimal Cyber-Insurance Contracts

In Internet security, traditional protection mechanisms such as anti-virus software, firewalls, and other add-ons are not capable of completely eliminating security risks [3]. As noted in [7], the management of information security needs to be addressed through economic, psychological, and policymaking approaches, in combination with engineering approaches. As a realistic and futuristic solution, recent efforts suggest alleviating existing Internet security problems through cyber-insurance schemes [5][6] an alternative approach to handling residual risk, where residual risk is transferred to a different entity, i.e, insurance companies, in return for a fee, termed the insurance premium. Cyber-insurance is analogous to the widely popular technique of ‘insurance’ in modern life [1]. Cyber-insurance companies could take the form of government agencies or public/private Internet service providers (ISPs) such as phone and cable companies (e.g., AT&T, Comcast). For instance, ISPs could act as insurance agencies and make it mandatory for its clients to certify their computing devices, and in return provide them with insurance services that include monetary compensations, data backups, real-time network traffic monitoring and filtering [4]. Existing research [5][6] has shown that cyber-insurance is a powerful incentive mechanism that increases the level of self-protection amongst Internet users, and thereby the overall network security (social welfare). The works are based on the notion that increasing level of self-protection amongst Internet users makes individual users robust to the success of threat attacks, and in turn makes the whole network more threat-proof. In this extended abstract, we address the problem of enforcing optimal cyber-insurance contracts between the insurer and the insured, where optimality may be defined w.r. t to maximizing social welfare or w.r. t maximizing insurer commercial profits. We define an insurance contract as a (premium, coverage) tuple that is enforced between the insurer (say an ISP) and the insured, prior to the ISP providing Internet service, as part of terms of the agreement between the two.
Prediction of Stock Trading Signal Based on Support Vector Machine

The prediction of stock trading signal is studied in this paper. Considering the excellent performance of Support Vector Machine (SVM) in pattern recognition, we apply SVM to construct a prediction model to find the stock trading signal. In addition, Piecewise linear representation (PLR) is good at extracting valuable information from a time sequence. PLR is used for checking of turning points in this study. The experiments on some real stocks show that SVM obtains a better result in prediction accuracy and profitability than traditional Back Propagation neural network does.
Fundos estruturais e crescimento económico na União Europeia

Structural Funds are the most used instrument by the European Union (EU) to promote economic growth and accelerate the convergence between its Member States. This study focus on the effects of the Structural Funds on economic growth of 25 European Union Member States. The approach to empirical analysis is based upon the use of panel data for the period between 1986 and 2011. We also intend to test the hypothesis of conditional convergence and assess the impact of investment, measured by gross domestic savings as a percentage of GDP, on economic growth. The analysis covers three post-enlargement sub-periods for different groups of countries, namely from 1986 to 1993 for the EU-12, 1994-2003 for the EU-15 and from 2004 to 2011 for the EU-25. The econometric methodology is based upon panel data estimations which correspond to the linear generalized method of moments estimator (GMM), following Arellano and Bond (1991) approach. The empirical results concerning the impact of Structural Funds on GDP per capita growth on different countries point to a non-linear effect. This, either positive or negative relationship depends on the group of countries and on the period considered, corroborating main economic literature conclusion. At the same time, the existence of convergence is confirmed throughout all considered periods and the investment is recognized as the main source of economic growth. JEL Classification: C23, O47