Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-wavelength surface-tension-driven Bénard convection: experiment and theory

Surface-tension-driven Bénard (Marangoni) convection in liquid layers heated from below can exhibit a long-wavelength primary instability that differs from the more familiar hexagonal instability associated with Bénard. This long-wavelength instability is predicted to be significant in microgravity and for thin liquid layers. The instability is studied experimentally in terrestrial gravity for silicone oil layers 0.007 to 0.027 cm thick on a conducting plate. For shallow liquid depths (<.017 cm for 0.102 cm2 s−1 viscosity liquid), the system evolves to a strongly deformed long-wavelength state which can take the form of a localized depression (‘dry spot’) or a localized elevation (‘high spot’), depending on the thickness and thermal conductivity of the gas layer above the liquid. For slightly thicker liquid depths (0.017–0.024 cm), the formation of a dry spot induces the formation of hexagons. For even thicker liquid depths (>0.024 cm), the system forms only the hexagonal convection cells. A two-layer nonlinear theory is developed to account properly for the effect of deformation on the interface temperature profile. Experimental results for the long-wavelength instability are compared to our two-layer theory and to a one-layer theory that accounts for the upper gas layer solely with a heat transfer coefficient. The two-layer model better describes the onset of instability and also predicts the formation of localized elevations, which the one-layer model does not predict. A weakly nonlinear analysis shows that the bifurcation is subcritical. Solving for steady states of the system shows that the subcritical pitchfork bifurcation curve never turns over to a stable branch. Numerical simulations also predict a subcritical instability and yield long-wavelength states that qualitatively agree with the experiments. The observations agree with the onset prediction of the two-layer model, except for very thin liquid layers; this deviation from theory may arise from small non-uniformities in the experiment. Theoretical analysis shows that a small non-uniformity in heating produces a large steady-state deformation (seen in the experiment) that becomes more pronounced with increasing temperature difference across the liquid. This steady-state deformation becomes unstable to the long-wavelength instability at a smaller temperature difference than that at which the undeformed state becomes unstable in the absence of non-uniformity.
EVALUATING THE WISDOM OF CROWDS

Estimating and forecasting are difficult tasks. This is true whether the activity requires the determination of uncertain future event outcomes, or whether the estimation effort is complex in itself and based on insufficient information. Consequently, such tasks are frequently assigned to experts. Surprisingly, recent research suggests that collectives of non-experts can outperform individual experts, as long as certain conditions are met. The resulting capability has been described as collective intelligence or “wisdom of crowds”. Our research explores this collective intelligence, for real and simulated crowds. An empirical test demonstrates that even a relatively small crowd of 30 subjects can demonstrate expertlike performance. A further investigation through simulation shows that the performance of a collective predictably compares to that of an expert, with the expert outperforming small crowds but being outperformed by large collectives. The relationship between performance and log of collective size follows a linear function.
Experiments in Binning Image Statistics

Various vision tasks require the computation of image statistics and aggregating them into histograms. These histograms are usually compared using the χ distance which gives a rough idea of the similarity of the two image patches. For example, in [2] a histogram of key-points is collected on a rectangular grid for the category recognition task. Other researchers, [3], have used local image statistics around a point to find corresponding points. In general, image statistics produce a vast array of number of varying magnitudes. Some form of aggregation is required to ensure robustness. Although k-means clustering is a commonly used device in this setting, the Euclidean distance on which it is based is not always the appropriate measure of distance. A pre-processing step where the statistics are aggregated into histograms is quite helpful. In this study, we study the issues surrounding binning these statistics by feature location and feature magnitude. Where, a feature can be interpreted as the response of an arbitrary filter or key-point detection algorithm. We claim that the optimal binning strategy depends on the particular feature being computed. Towards this end, we try various strategies on a fixed set of features and evaluate their performance on a specific task. The task that we consider is object categorization using the CalTech 101 dataset [1]. The overall approach is to use a nearest neighbour classifier using the χ distance between the feature histograms of the test image and the training images. In the subsequent sections we describe the features that we collected and the performance of various binning strategies that we evaluated on these features.
On the Fraction of Internal Tide Energy Dissipated Near Topography

Internal tides have been implicated as a major source of mechanical energy for mixing in the ocean interior. Indeed, microstructure and tracer measurements have indicated that enhanced turbulence levels occur near topography where internal tides are generated. However, the details of the energy budget and the mechanisms by which energy is transferred from the internal tide to turbulence have been uncertain. It now seems that the energy levels associated with locally enhanced mixing near topography may constitute only a small fraction of the available internal tide energy flux. In this study, the generation, radiation, and energy dissipation of deep ocean internal tides are examined. Properties of the internal tide at the Mid-Atlantic Ridge and Hawaiian Ridge are considered. It is found that most internal tide energy is generated as low modes. The Richardson number of the generated internal tide typically exceeds unity for these motions, so direct shear instability of the generated waves is not the dominant energy transfer mechanism. It also seems that wave-wave interactions are ineffective at transferring energy from the large wavelengths that dominate the energy flux. Instead, it seems that much of the generated energy radiates away from the generation site in low mode waves. These low modes must dissipate somewhere in the ocean, though this likely occurs over O(1000 km) distances as the waves propagate. Additionally, a small fraction of energy flux is generated as high mode waves. These have slower group speeds, higher shear, and faster wave-wave interaction rates than the low modes, and so are likely to dissipate as turbulence close to the topography of the generation site. Preliminary estimates suggest that turbulent dissipation near sites of generation accounts for 30% or less of the total generated energy flux. Based on these estimates, a parameterization of the mixing sustained by high mode internal tide generation is proposed.
Semantic inter-media image retrieval in photographic collections

In this paper we propose a method for semantic inter-media photographic retrieval, exploiting the advantages of both textual and content-based frameworks: the relatively high initial precision and diversity of results from visual and text retrieval, and the robust overall precision and recall of text retrieval. The method employs simple block-based visual retrieval which, at early precision, outperforms MPEG-7 features ScalableColor, ColorLayout and EdgeHistogram, allowing for reliable auto-relevance feedback. The query expansion applied respects the semantic constraints of the original query and enhances precision and confidence through redundancy. The proposed method was tested on a benchmark data set of 20,000 diverse tourist photographs and obtained promising results.
Encountering unexpected difficult airway: relationship with the intubation difficulty scale

Background An unexpected difficult intubation can be very challenging and if it is not managed properly, it may expose the encountered patient to significant risks. The intubation difficulty scale (IDS) has been used as a validated method to evaluate a global degree of intubation difficulty. The aims of this study were to evaluate the prevalence and characteristics of unexpected difficult intubation using the IDS. Methods We retrospectively reviewed 951 patients undergoing elective surgery in a single medical center. Patients expected to have a difficult intubation or who had history of difficult intubation were excluded. Each patient was assessed by the IDS scoring system with seven variables. Total prevalence of difficult intubation and the contributing individual factors were further analyzed. Results For the 951 patients, the difficult intubation cases presenting IDS > 5 was 5.8% of total cases (n = 55). The prevalence of Cormack-Lehane Grade 3 or 4 was 16.2% (n = 154). Most of the difficult intubation cases were managed by simple additional maneuvers and techniques such as stylet application, additional lifting force and laryngeal pressure. Conclusions Unexpected difficult airway was present in 5.8% of patients and most was managed effectively. Among the components of IDS, the Cormack-Lehane grade was most sensitive for predicting difficult intubation.
The Exciting Star of the Berkeley 59/Cepheus OB4 Complex and Other Chance Variable Star Discoveries

A study is presented regarding the nature of several variable stars sampled during a campaign of photometric monitoring from the Abbey Ridge Observatory: 3 eclipsing binaries, 2 semiregulars, a luminous Be star, and a star of uncertain classification. For one of the eclipsing systems, BD+66 1673, spectroscopic observations reveal it to be an O5 V((f))n star and the probable ionizing star of the Berkeley 59/Cep OB4 complex. An analysis of spectroscopic observations and BV photometry for Berkeley 59 members in conjunction with published observations imply a cluster age of ~2 Myr, a distance of d = 883+-43 pc, and a reddening of E(B-V) =1.38+-0.02. Two of the eclipsing systems are Algol-type, but one appears to be a cataclysmic variable associated with an X-ray source. ALS 10588, a B3 IVn star associated with the Cepheid SV Vul, is of uncertain classification, although consideration is given to it being a slowly pulsating B star. The environmental context of the variables is examined using spectroscopic parallax, 2MASS photometry, and proper motion data, the latter to evaluate the membership of the variable B2 Iabe star HDE 229059 in Berkeley 87, an open cluster that could offer a unique opportunity to constrain empirically the evolutionary lineage of young massive stars. Also presented are our null results for observations of a sample of northern stars listed as Cepheid candidates in the Catalogue of Newly Suspected Variables.
NATURAL GRADIENT LEARNING WITH A NONHOLONOMIC CONSTRAINT FOR BLIND DECONVOLUTION OF MULTIPLE CHANNELS

This paper addresses natural gradient learning algorithms with a nonholonomic constraint and their application to multichannel blind deconvolution First we incorporate a nonholonomic constraint into the natural gradient learn ing algorithm for multichannel blind deconvolution that has been developed by Amari Douglas Cichocki Yang and present a slightly modi ed algorithm which works e ciently for the case where we overestimate the number of sources or the number of sources is not known in advance Sec ond we also derive a natural gradient learning algorithm that can be used to train a linear feedback network with FIR synapses Again a nonholonomic constraint is incor porated It is applied to the blind equalization of single input multiple output SIMO channels and is compared with the spatio temporal anti Hebbian rule which is the extension of the anti Hebbian rule The algorithms are rigorously derived and their validity is con rmed by com puter simulations
Predicting Ads' Click-Through Rate with Decision Rules

Paid advertisements displayed alongside search results constitute a major source of income for search companies. Optimizations leading to more clicks on ads are a target goal shared by advertisers and search engines. In this context, an ad’s quality can be measured by the probability of it being clicked assuming it was noticed by the user (click-through rate, CTR). There are two problems here. First, the real CTR is heavily aected by the ad’s position, not only by its content. Second, it is not possible to directly calculate CTR for new ads. In this paper we build upon a large data set with real ad clicks and impressions, acquired thanks to Microsoft’s Beyond Search program. First, we describe the data set and anomalies found inside it. We then address the problem of computing CTR for existing ads using maximum likelihood estimation. Finally, we present an algorithm learning an ensemble of decision rules that can be used for predicting the CTR for unseen ads and giving recommendations to improve ads’ quality.
Role of handshaking packets in improving peer to peer BotNet detection

BotNet is a network based attack that has emerged as a serious threat to Internet community and has been a common weapon for committing cybercrimes such as spam generation, stealing sensitive information, click fraud and DDOS attacks. Botnet is a network of hosts remotely controlled and coordinated under a common command and control infrastructure. P2P BotNets represent a recent and most challenging class of BotNets currently available which are hard to detect due to their decentralized architecture. A P2P botnet detection technique based on network behavior analysis has been proposed in this work. We have aggregated features from the most popular prior works based on network behavior analysis and augmented them with a new set of features which are particularly emphasizing on control packets. We study the behavior of these control packets particularly the handshaking signals exchanged in botnet traffic with respect to normal traffic. Results and analysis clearly show that proposed control packets based features play a major role in botnet detection. Further, to decide how many handshaking packets are to be considered, we perform correlation analysis and results for the same are also mentioned.
Sensor network partitioning based on homogeneity

Discovering communities from sensor networks is an important problem in many real-world applications. The problem desiderata requires to partition the network according to the homogeneity of the sensor measurement and at the same time the partitioning result to be as independent as possible of the typical local change in the network topology. This poses new challenges to the current graph partitioning methodologies. We develop a graph partitioning approach from the perspective of homogeneity. In order to avoid the inherent incompatibility of the current graph partitioning methodologies, an objective functional is designed to be asymptotically close to the Mumford-Shah functional [1]. An variational algorithm ZERO-CUT and a fast approximation algorithm GREEDY-SACK are developed to solve the objective functional. We evaluate the performance of the proposed algorithms on both synthetic and real-world graphs in different applications to demonstrate its advantage and promise in solving the problem of discovering communities from sensor networks.
Secondary organic aerosol formation from photooxidation of naphthalene and alkylnaphthalenes: implications for oxidation of intermediate volatility organic compounds (IVOCs)

Abstract. Current atmospheric models do not include secondary organic aerosol (SOA) production from gas-phase reactions of polycyclic aromatic hydrocarbons (PAHs). Recent studies have shown that primary emissions undergo oxidation in the gas phase, leading to SOA formation. This opens the possibility that low-volatility gas-phase precursors are a potentially large source of SOA. In this work, SOA formation from gas-phase photooxidation of naphthalene, 1-methylnaphthalene (1-MN), 2-methylnaphthalene (2-MN), and 1,2-dimethylnaphthalene (1,2-DMN) is studied in the Caltech dual 28-m3 chambers. Under high-NOx conditions and aerosol mass loadings between 10 and 40 μg m−3, the SOA yields (mass of SOA per mass of hydrocarbon reacted) ranged from 0.19 to 0.30 for naphthalene, 0.19 to 0.39 for 1-MN, 0.26 to 0.45 for 2-MN, and constant at 0.31 for 1,2-DMN. Under low-NOx conditions, the SOA yields were measured to be 0.73, 0.68, and 0.58, for naphthalene, 1-MN, and 2-MN, respectively. The SOA was observed to be semivolatile under high-NOx conditions and essentially nonvolatile under low-NOx conditions, owing to the higher fraction of ring-retaining products formed under low-NOx conditions. When applying these measured yields to estimate SOA formation from primary emissions of diesel engines and wood burning, PAHs are estimated to yield 3–5 times more SOA than light aromatic compounds over photooxidation timescales of less than 12 h. PAHs can also account for up to 54% of the total SOA from oxidation of diesel emissions, representing a potentially large source of urban SOA.
Parents' Perception, Students' and Teachers' Attitude Towards School Sex Education

Background Sex education is described as education about human sexual anatomy, sexual reproduction, sexual intercourse, reproductive health, emotional relations, reproductive rights and responsibilities, abstinence, contraception, family planning, body image, sexual orientation, sexual pleasure, values, decision making, communication, dating, relationships, sexually transmitted infections (STIs) and how to avoid them, and birth control methods. This study was conducted to explore perception of parents about school sex education and assess the attitude of teachers and students towards school sex education. Methods A cross-sectional quantitative and qualitative study was conducted on randomly selected 386 students, total census of 94 teachers and 10 parents in Merawi Town from March 13–27, 2011. Data were collected using self-administered structured questionnaire and in-depth interview guideline. Multiple linear regression analysis was performed using total score to determine the effect of the independent variables on the outcome variable and thematic analysis was used to analyze the qualitative data. Results All study participants have favourable attitude towards the importance of school sex education. They also agreed that the content of school sex education should include abstinence-only and abstinence-plus based on mental maturity of the students. That means at early age (Primary school) the content of school sex education should be abstinence-only and at later age (secondary school) the content of school sex education should be added abstinence-plus. The students and the teachers said that the minimum and maximum introduction time for school sex education is 5 year and 25 year with mean of 10.97(SD±4.3) and 12.36(SD±3.7) respectively. Teacher teaching experiences and field of studies have supportive idea about the starting of school sex education. Watching romantic movies, reading romantic materials and listening romantic radio programs appear to have a contribution on the predictor of students' attitude towards the starting time of school sex education. Conclusion All study participants have a need to start sex education at school. All study participants said that at early age (Primary school) the content of school sex education is abstinence-only and at later age (secondary school) is added abstinence-plus. School Sex education should be under considers the need of students, teachers and parents.
Impact of knowledge management and corporate social capital on firm performance—Taking firms in Xinjiang region as an example

Focused on the concept of knowledge based view (KBV), and based on the 116 firms in Xinjiang region, the paper outlines the impact of two types of firms resources (knowledge resources, corporate social capital) on firm performance (strategic and financial ) direct, relevant and coordinated effects. Although the results show that the two resources are likely to improve firm performance, but also knowledge management is the main driving force to enhance strategic and financial performance. In addition, the domestic and multinational enterprise ownership plays a moderating effect role.
Will It Rain Profit With Broadcast Clouds?

Wireless data providers send data such as stock prices, news headlines, traffic and weather information, and advertisements. Since wireless bandwidth is a constrained resource that determines the cost of the provider, it must be used efficiently. To conserve the bandwidth, data broadcasting techniques could be used. Existing research in data broadcasting has addressed the problems of what to broadcast and how to schedule the broadcasts. However, these methods do not focus on the bandwidth cost, rather they aim to minimize the cost of the client. In this paper, we propose the concept of “broadcast clouds” that also uses broadcasting but considers the data provider’s cost. Our approach bunches together wireless cells based on a bandwidth saving principle, and prepares a common broadcast for these. This would reduce the bandwidth cost and presumably increase the service provider’s profit. We present a heuristic to form the broadcast clouds and measure its performance via simulation. Our approach is particularly advantageous when the data items have locality and the clients are mobile and changing cells.
Dyslexic Children Are Confronted with Unstable Binocular Fixation while Reading

Reading requires three-dimensional motor control: saccades bring the eyes from left to right, fixating word after word; and oblique saccades bring the eyes to the next line of the text. The angle of vergence of the two optic axes should be adjusted to the depth of the book or screen and - most importantly - should be maintained in a sustained manner during saccades and fixations. Maintenance of vergence is important as it is a prerequisite for a single clear image of each word to be projected onto the fovea of the eyes. Deficits in the binocular control of saccades and of vergence in dyslexics have been reported previously but only for tasks using single targets. This study examines saccades and vergence control during real text reading. Thirteen dyslexic and seven non-dyslexic children read the French text “L'Allouette” in two viewing distances (40 cm vs. 100 cm), while binocular eye movements were measured with the Chronos Eye-tracking system. We found that the binocular yoking of reading saccades was poor in dyslexic children (relative to non-dyslexics) resulting in vergence errors; their disconjugate drift during fixations was not correlated with the disconjugacy during their saccades, causing considerable variability of vergence angle from fixation to fixation. Due to such poor oculomotor adjustments during reading, the overall fixation disparity was larger for dyslexic children, putting larger demand on their sensory fusion processes. Moreover, for dyslexics the standard deviation of fixation disparity was larger particularly when reading at near distance. We conclude that besides documented phoneme processing disorders, visual/ocular motor imperfections may exist in dyslexics that lead to fixation instability and thus, to instability of the letters or words during reading; such instability may perturb fusional processes and might – in part - complicate letter/word identification.