Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient estimation algorithms for neighborhood variance and other moments

The neighborhood variance problem is as follows. Given a (directed or undirected) graph with values associated with each node, compute a data structure that for any given node v and r ≥ 0, would quickly produce an estimate of the variance of all values of nodes that lie within distance r from v. The problem can be generalized to other moment functions and to arbitrary distance-dependent decay.These problems are motivated by applications where the relevance of a measurement observed (or data present) at a certain location decreases with its distance, and thus the aggregate value varies by location. The centralized version of the problem is motivated by applications to query processing on graphical databases. The distributed version of the problem falls in a model we recently introduced for spatially decaying aggregation and is motivated by sensor or p2p networks.We present novel algorithms for the centralized and distributed versions of the problem. Our algorithms are nearly optimal, the centralized version requires Õ(m) time and the distributed version requires polylogarithmic communication per node or edge (depending on assumptions).
The relative roles of inheritance and long-term passive margin lithospheric evolution on the modern structure and tectonic activity in the southeastern United States

We perform inversions for the shear-wave velocity structure of the southeastern United States (SEUS) using Rayleigh-wave phase and amplitude data from the broadband stations of the South Eastern Suture of the Appalachian Margin Experiment (SESAME) and EarthScope Transportable Array (TA). Our tomographic images of shear-wave velocities in the upper mantle beneath the SEUS provide new constraints on the evolution of mantle lithosphere, both from the inheritance of structures from repeated Wilson cycles and from processes that have occurred while at a passive margin setting. Our images also allow us to correlate these structures to evidence of Eocene to recent tectonism observed at the surface. We find evidence for both inherited structures and more recently evolved structures, both of which bear some correlation to observations of ongoing tectonism. Our results suggest that lithospheric mantle continues to evolve while in a passive margin setting and that even relatively “stable” continental mantle lithosphere is subject to episodes of delamination, foundering, and erosion due to processes that are still not well under stood. Our results provide structural constraints on the types of processes that may be ongoing and on possible explanations for the numerous observations of comparatively recent tectonic activity occurring along this passive margin setting.
Internet of things (IoT) security: Current status, challenges and prospective measures

The paper presents a survey and analysis on the current status and concerns of Internet of things (IoT) security. The IoT framework aspires to connect anyone with anything at anywhere. IoT typically has a three layers architecture consisting of Perception, Network, and Application layers. A number of security principles should be enforced at each layer to achieve a secure IoT realization. The future of IoT framework can only be ensured if the security issues associated with it are addressed and resolved. Many researchers have attempted to address the security concerns specific to IoT layers and devices by implementing corresponding countermeasures. This paper presents an overview of security principles, technological and security challenges, proposed countermeasures, and the future directions for securing the IoT.
Reliability and Validity of the Persian Version of Templer Death Anxiety Scale-Extended in Veterans of Iran–Iraq Warfare

Objective: The purpose of this study was to determine the validity and reliability of the Persian version of Templer Death Anxiety Scale-Extended (DAS-E) in veterans of Iran–Iraq Warfare. Methods: In this cross-sectional study, 211 male veterans of Iran–Iraq Warfare completed the 51 item DAS-E. Principal components analysis with varimax rotation was used to assess domain structure of the DAS-E. Internal consistency reliability was assessed with Cronbach’s alpha. Test–retest reliability was assessed with intra-class correlation coefficients for absolute agreement for the individual items and domains. Results: The construct validity of the scale was obtained using exploratory factor analysis that showed four factors with Eigen values of greater than 1 (1, 11 items, α = 0.83; 2, 7 items; α = 0.87; 3, 5 items, α = 0.73; and 4, 4 items, α = 0.75). Test–retest and internal consistency (total alpha) was 0.91 and 0.89, respectively. Conclusion: The DAS-E demonstrated suitable validity and reliability among the veterans under study. The factor analysis demonstrated that the DAS-E has a multi-dimensional structure. With consideration of the proper psychometric characteristics, this scale can be used to further research about death anxiety in this population.
On porting sequential programs to parallel machines

We address a significant problem in parallel processing research, namely, how to port existing sequential programs to run efficiently on parallel machines (the "dusty deck" problem). Conventional domain-independent techniques are inadequate for solving this problem because they miss significant opportunities of parallelism. We present experimental evidence to support our claim, analyze why current techniques are inadequate, and propose a knowledge-based reverse engineering approach for attacking this problem. <<ETX>>
All-round two-wheeled quadrotor helicopters with protect-frames for air–land–sea vehicle (controller design and automatic charging equipment)

This paper presents a new all-round Air–Land–Sea Unmanned Aerial Vehicle (UAV) and the automatic battery charging device. The new UAV is a quadrotor helicopter with two rolling protect-frames, which not only can fly in the air but also can move on the ground, the wall, the ceiling, and the water in all directions. In this paper, firstly, the dynamic equation is derived of the new UAV, which is described by a set of nonlinear equations. Secondly, some tracking problems are considered in both the flight mode and the ground one under uncertain inertia parameters, and useful adaptive control systems based on the input–output linearization are proposed for the position tracking control. The design problem is reduced to that of a linear system, and the design method is simple and straightforward. Finally, a new automatic battery charging device is developed for the UAV. It is the unique point that the connection operation to the charging terminal is carried out by ground rolling motion without precise landing from the air. Consequently, even if in windy outdoor and narrow indoor space, the proposed method can complete the battery charge safely and surely. Graphical Abstract
Summer habitat selection by ringed seals (Pusa hispida) in the drifting sea ice of the northern Barents Sea

Ringed seals are a central component of the Arctic ecosystem; they have a circumpolar distribution and are both important predators of lower trophic animals (invertebrates and fishes) and prey for polar bears and coastal human populations. They depend on sea ice for reproduction, moulting and resting, and they consume significant amounts of ice-associated prey. The population of ringed seals in Svalbard, Norway, uses both coastal and offshore habitats, the latter being important during seasonal migrations undertaken by some animals, mostly juveniles. This study examined habitat preferences of 18 satellite-tracked ringed seals (mostly young animals, but also a few adults) during late summer/autumn migrations to the drift ice in the northern Barents Sea. Resource selection functions showed that ringed seals preferred being close to the 50% sea-ice concentration threshold; a 120 km increase in the distance to the 50% sea-ice concentration threshold halved the probability of selection of a given area. In addition, higher sea-ice concentrations (80–100%) were between 1.4 and 2.2 times as likely to be selected as lower sea-ice concentrations or open water. Ringed seals use the marginal ice zone of the Barents Sea during summer/autumn. This offshore habitat has shifted northward during recent decades, which is likely causing negative effects on ringed seals by increasing the energetic cost of offshore migrations.
A 1.2V 12.8GB/s 2Gb mobile Wide-I/O DRAM with 4×128 I/Os using TSV-based stacking

Mobile DRAM is widely employed in portable electronic devices due to its feature of low power consumption. Recently, as the market trend renders integration of various features in one chip, mobile DRAM is required to have not only low power consumption but also high capacity and high speed. To attain these goals in mobile DRAM, we designed a 1Gb single data rate (SDR) Wide-I/O mobile SDRAM with 4 channels and 512 DQ pins, featuring 12.8GB/s data bandwidth.
A unified approach to word statistics

E-&nation of the frequency of occurrences of a given set of patterns in a DNA sequence has numerous applications and has been extensivley studied recently. We provide a unified framework for this evaluation that adapts to various constraints and allow to extend previous results. We assume succesively that the patterns may, then may not, overlap. We derive asymptotic and exact formulae for the moments in a Markovian model We show that our formulae, that occasionnally simplify previous results, are computable at low cost, which makes them useful for practical applications.
A 52GHz Phased-Array Receiver Front-End in 90nm Digital CMOS

In this paper, a CMOS implementation of phased-array receiver front-end, based on a widely tunable QVCO is presented. Each path achieves 30dB of gain and a minimum NF of 7.1dB, yielding a system NF of 4.1dB. The overall current draw is 54mA from a 1.2V supply. Additionally, a calibration procedure to mitigate the analog impairments imposed by the proposed implementation is demonstrated.
English abstract : Tales of Entrepreneurship Contributions to understanding entrepreneurial life

The 'dominant idea' of entrepreneurship is that entrepreneurship is something extraordinary, performed by 'special' people (cf. Ogbor, 2000, Nodoushani & Nodoushani, 2000). This thesis, however, answers a repeated call in entrepreneurship research to view entrepreneurship as an 'ordinary' activity, performed by 'ordinary' persons. More precisely, it follows and builds upon the proposition that entrepreneurship should be seen as something nearly everyone can perform Understanding the 'ordinary' in entrepreneurship means entering the entrepreneurial 'realm of experience' (the entrepreneurial life-world). And thus looking at all entrepreneurial activities, also those activities that could be looked upon as (too) mundane, (too) ordinary. It also means looking at how activities are formed, how they flow and change. In other words: the dynamics of entrepreneurial activity; entrepreneurial life as becoming process (see Figure 1). This thesis makes extensive use of narrative; according to Steyaert (1997), narrative is of particular use when it comes to understanding process aspects of the phenomenon under review. It is not merely that narratives relate of processes (sequences of events) that makes them so useful, but more that the relationally constructing of narratives is a process of creating 'reality' (Hosking, 2004). A narrative (or story) in its broadest sense is anything told or recounted by an individual, group of individuals, organisation etc. Narratives and stories can take many forms. They can be oral, written or filmed (Barthes, 1977, Linde, 2001), fictional or non-fictional. What makes a story a story and not 'just' an account of events and facts is a sequence of events, connected by a plot (cf.
A long journey into reproducible computational neuroscience

Computational neuroscience is a powerful ally in our quest to understand the brain. Even the most simple model can shed light on the role of this or that structure and propose new hypothesis concerning the overall brain organization. However, any model in Science is doomed to be proved wrong or incomplete and replaced by a more accurate one. In the meantime, for such replacement to happen, we have first to make sure that models are actually reproducible such that they can be tested, evaluated, criticized and ultimately modified, replaced or even rejected. This is where the shoe pinches. If we cannot reproduce a model in the first place, we're doomed to re-invent the wheel again and again, preventing us from building an incremental computational knowledge of the brain.
Carbon‐Based Estimate of Nitrogen Fixation‐Derived Net Community Production in N‐Depleted Ocean Gyres

Accurate estimation of net community production (NCP) in the ocean is important for determining the future trend for carbon dioxide concentrations in the atmosphere and thus for understanding the global carbon cycle and climate change. Most methods for measuring NCP rely on analysis of dissolved fixed inorganic nitrogen species (N), which are believed to be limiting factors for NCP. However, in the vast areas of the ocean gyres only low levels of N are available for phytoplankton during much of the year. In this study the NCP was estimated by summing the seasonal reduction in the concentration of dissolved inorganic carbon (CT) in the surface mixed layer, corrected for changes associated with salinity variation, net air‐sea CO2 flux, horizontal C advection, non‐Redfield diffusive C and N fluxes (deviations from the C:N ratio of 7), and anthropogenic nitrogen deposition. The mixed layer reduction in CT was calculated from an annual CT cycle, deduced from comprehensive records of surface pCO2 and total alkalinity, using an established thermodynamic model. This method yielded a value of 0.6 ± 0.2 Pg of C, which represents the NCP that occurred during the warming period (approximately 8 months) in the nitrate‐depleted (<0.2 μmol/kg) ocean. Our estimate is broadly consistent with the global N2 fixation rate estimated using the 15N‐based method and suggests that N2 fixation by microorganisms is a major driver for this NCP.
Performance Prediction of Speech Recognition Using Average-Voice-Based Speech Synthesis

This paper describes a performance prediction technique of a speech recognition system using a small amount of target speakers’ data. In the conventional HMM-based technique, a speaker-dependent model was used and thus a considerable amount of training data was needed. To reduce the amount of training data, we introduce an average voice model as a prior knowledge for the target speakers’ acoustic models, and adapt it to the target speakers’ ones using speaker adaptation. Experimental results show that the use of average voice model effectively save the amount of training data of the target speakers, and the prediction accuracy is signiﬁcantly improved compared to the conventional technique especially when a smaller amount of training data is available.
Programming Nanopore Ion Flow for Encoded Multiplex MicroRNA Detection

Many efforts are being made in translating the nanopore into an ultrasensitive single-molecule platform for various genetic and epigenetic detections. However, compared with current approaches including PCR, the low throughput limits the nanopore applications in biological research and clinical settings, which usually requires simultaneous detection of multiple biomarkers for accurate disease diagnostics. Herein we report a barcode probe approach for multiple nucleic acid detection in one nanopore. Instead of directly identifying different targets in a nanopore, we designed a series of barcode probes to encode different targets. When the probe is bound with the target, the barcode group polyethylene glycol attached on the probe through click chemistry can specifically modulate nanopore ion flow. The resulting signature serves as a marker for the encoded target. Therefore counting different signatures in a current recording allows simultaneous analysis of multiple targets in one nanopore. The principle of this approach was verified by using a panel of cancer-derived microRNAs as the target, a type of biomarker for cancer detection.
Experiments in tagger combination: arbitrating, guessing, correcting, suggesting

The paper reports experiments with several strategies of tagger combination, using two well known taggers, TreeTagger and Hunpos. The most successful experiment,which achieved the best score in the Evalita 2009 Open Task, is a hybrid solution combining an easiest first iterative strategy with hand-written arbitration rules and a quality lexicon. The system used in the Closed Task uses a similar combination of two variants of Hunpos, together with correction/guessing rules.
Multiwavelength Properties of the X-Ray Sources in the Groth-Westphal Strip Field

We summarize the multiwavelength properties of X-ray sources detected in the 80 ks XMM-Newton observation of the Groth-Westphal strip, a contiguous strip of 28 Hubble Space Telescope Wide Field Planetary Camera 2 (WFPC2) images. Among the ≈150 X-ray sources detected in the XMM-Newton field of view, 23 are within the WFPC2 fields. Ten spectroscopic redshifts are available from the Deep Extragalactic Evolutionary Probe and Canada-France Redshift Survey projects. Four of these show broad Mg II emission and can be classified as type 1 active galactic nuclei (AGNs). Two of those without any broad lines, nevertheless, have [Ne V] emission, which is an unambiguous signature of AGN activity. One is a narrow-line Seyfert 1 and the other a type 2 AGN. As a follow-up, we have made near-infrared spectroscopic observations using the OHS/CISCO spectrometer for five of the X-ray sources for which we found no indication of AGN activity in the optical spectrum. We have detected Hα + [N II] emission in four of them. A broad Hα component and/or a large [N II]/Hα ratio is seen, suggestive of AGN activity. Nineteen sources have been detected in the Ks band, and four of these are extremely red objects (EROs) (I814-Ks > 4). The optical counterparts for the majority of the X-ray sources are bulge-dominated. The I814-Ks color of these bulge-dominated hosts are indeed consistent with evolving elliptical galaxies, while contaminations from star formation/AGNs seems to be present in their V606-I814 color. Assuming that the known local relations among the bulge luminosity, central velocity dispersion, and the mass of the central blackhole still hold at z ∼ 1, we compare the AGN luminosity with the Eddington luminosity of the central blackhole mass. The AGN bolometric luminosity to Eddington luminosity ratio ranges from 0.3% to 10%.
The Galaxy Luminosity Function and Luminosity Density at Redshift z = 0.1

Using a catalog of 147,986 galaxy redshifts and fluxes from the Sloan Digital Sky Survey (SDSS), we measure the galaxy luminosity density at z = 0.1 in five optical bandpasses corresponding to the SDSS bandpasses shifted to match their rest-frame shape at z = 0.1. We denote the bands 0.1u, 0.1g, 0.1r, 0.1i, 0.1z with λeff = (3216, 4240, 5595, 6792, 8111 Å), respectively. To estimate the luminosity function, we use a maximum likelihood method that allows for a general form for the shape of the luminosity function, fits for simple luminosity and number evolution, incorporates the flux uncertainties, and accounts for the flux limits of the survey. We find luminosity densities at z = 0.1 expressed in absolute AB magnitudes in a Mpc3 to be (-14.10 ± 0.15, -15.18 ± 0.03, -15.90 ± 0.03, -16.24 ± 0.03, -16.56 ± 0.02) in (0.1u, 0.1g, 0.1r, 0.1i, 0.1z), respectively, for a cosmological model with Ω0 = 0.3, ΩΛ = 0.7, and h = 1 and using SDSS Petrosian magnitudes. Similar results are obtained using Sérsic model magnitudes, suggesting that flux from outside the Petrosian apertures is not a major correction. In the 0.1r band, the best-fit Schechter function to our results has ϕ* = (1.49 ± 0.04) × 10-2 h3 Mpc-3, M* - 5 log10 h = -20.44 ± 0.01, and α = -1.05 ± 0.01. In solar luminosities, the luminosity density in 0.1r is (1.84 ± 0.04) × 108 h L0.1r,☉ Mpc-3. Our results in the 0.1g band are consistent with other estimates of the luminosity density, from the Two-Degree Field Galaxy Redshift Survey and the Millennium Galaxy Catalog. They represent a substantial change (~0.5 mag) from earlier SDSS luminosity density results based on commissioning data, almost entirely because of the inclusion of evolution in the luminosity function model.
Damage indicator defined as the distance between ARMA models for structural health monitoring

A new damage indicator denoted by the distance between ARMA models is proposed in this paper to identify structural damage including its location and severity. Two definitions are introduced as the distance, either the cepstral metric or subspace angles of ARMA models. However, the accuracy is deteriorated when the multiple inputs have strong correlations. To overcome this difficulty, a pre‐whitening filter is applied. Thus, the proposed damage indicator is applicable for varieties of excitation types in civil engineering, such as wind, traffic loading and earthquake excitations. A five‐storey building model is used for performance verification when subjected to different excitations. Ambient force and earthquake input have been used as excitations acting on the structure. Two calculating methods of the proposed damage indicators are both evaluated. When the excitations are mutually correlated, by using the pre‐whitening filter, the damage identification ability of the proposed damage indicator improves significantly, especially for damage localization. The damage indicator increases monotonically with damage severity, which provides the potential for damage quantification. Copyright © 2007 John Wiley & Sons, Ltd.
A Network That Learns Strassen Multiplication

We study neural networks whose only non-linear components are multipliers, to test a new training rule in a context where the precise representation of data is paramount. These networks are challenged to discover the rules of matrix multiplication, given many examples. By limiting the number of multipliers, the network is forced to discover the Strassen multiplication rules. This is the mathematical equivalent of finding low rank decompositions of the n × n matrix multiplication tensor, Mn. We train these networks with the conservative learning rule, which makes minimal changes to the weights so as to give the correct output for each input at the time the input-output pair is received. Conservative learning needs a few thousand examples to find the rank 7 decomposition of M2, and 105 for the rank 23 decomposition of M3 (the lowest known). High precision is critical, especially for M3, to discriminate between true decompositions and "border approximations".