Miracle-dz/UniFAR-FTUs huggingface dataset:
SUPERNOVA FEEDBACK KEEPS GALAXIES SIMPLE

Galaxies evolve continuously under the influence of self-gravity, rotation, accretion, mergers, and feedback. The currently favored cold dark matter cosmological framework suggests a hierarchical process of galaxy formation, wherein the present properties of galaxies are decided by their individual histories of being assembled from smaller pieces. However, recent studies have uncovered surprising correlations among the properties of galaxies, to the extent of forming a one-parameter set lying on a single fundamental line. It has been argued in the literature that such simplicity is hard to explain within the paradigm of hierarchical galaxy mergers. One of the puzzling results is the simple linear correlation between the neutral hydrogen mass and the surface area, implying that widely different galaxies share very similar neutral hydrogen surface densities. In this work, we show that self-regulated star formation, driven by the competition between gravitational instabilities and mechanical feedback from supernovae, can explain the nearly constant neutral hydrogen surface density across galaxies. We therefore recover the simple scaling relation observed between the neutral hydrogen mass and surface area. This result furthers our understanding of the surprising simplicity in the observed properties of diverse galaxies.
Event Segmentation

One way to understand something is to break it up into parts. New research indicates that segmenting ongoing activity into meaningful events is a core component of perception and that this has consequences for memory and learning. Behavioral and neuroimaging data suggest that event segmentation is automatic and that people spontaneously segment activity into hierarchically organized parts and subparts. This segmentation depends on the bottom-up processing of sensory features such as movement and on the top-down processing of conceptual features such as actors' goals. How people segment activity affects what they remember later; as a result, those who identify appropriate event boundaries during perception tend to remember more and to learn more proficiently.
Proposing a streaming Big Data analytics (SBDA) platform for condition based maintenance (CBM) and monitoring transportation systems

Statistics demonstrate that public transportation plays a significant role in people’s movement in metropolises. However, transit systems are aging and are facing rising maintenance costs. Technologies such as Condition-Based Maintenance (CBM) could be used in order to monitor performance conditions of transportation and industrial assets in real-time to detect when and what maintenance is required. CBMs could help to identify risk scenarios in real-time, enhance reliability, reduce call out costs, increase productivity, and better asset functioning visibility. Since the high volume of maintenance data is generated from the different source, managing assets conditions with traditional inspection system such as planned maintenance (PM) is impossible. Therefore, providing a comprehensive performance management program is essential. My research is motivated by interesting challenges increasing from the growing size, variety, and complexity of maintenance data in CBM systems. This paper presents a knowledge-based approach of CBM using streaming big data analysis (SBDA) in order to solve real-time big data management, storage and computation challenges and predictive data analytics in CBM systems. This platform could detect changes in asset’s behaviour before they stop.
Hedonic Pricing of Bulls

Bulls account for half of the genetic input when making improvements in cattle herds. Therefore, to make a rapid, less costly improvement a cattle producer is more likely to change bulls than cows. One of the problems that breeders who supply bulls face is that the attributes of bulls come bundled together so that it is difficult to determine what the value of improvements in a bull might be worth. This research estimates what values beef producers implicitly place on particular characteristics when deciding which bull will best fit the needs of their farm. A hedonic pricing model was estimated using actual transaction data and reveals the value buyers of bulls implicitly place on specific traits. For example, a ribeye area of 12.8 in2 at the mean sale price reveals a buyer would be willing to pay an additional $80.39 for a bull with an additional square inch. Likewise, a bull with a 1242 lb. 365-day weight at the mean sale price reveals a buyer would be willing to pay an additional $1.83 for an additional pound. Therefore, this research reveals an incentive for bull producers to focus on improving the genetic makeup of their bulls they offer for sale.
Passive Image Forensic Method to Detect Resampling Forgery in Digital Images

The digital images are becoming important part in the field of information forensics and security, because of the popularity of image editing tools, digital images can be tampered in a very efficient manner without leaving any visual clue. As a consequence, the content of digital images cannot be taken as for granted. Therefore it is must to create forensic techniques which is capable of detecting tampering in image. In general, the image forgery technologies often utilizes the scaling, rotation or skewing operations to tamper some regions in the image, in which the resampling is demanded. Forged area is often resized & rotated to make it proportional with respect to neighboring unforged area. This is called as resampling operation which changes certain characteristics of the pasted portion. By observing the detectable periodic distribution properties generated from the resampling, propose a method based on the Peak Value Identification Classifier to detect the tampered regions and find the Peak Signal to Noise Ratio (PSNR) to know about quality of resampled image. The experimental results show that the proposed method outperforms the conventional methods in terms of recall and precision.
Households' Dependence on Protected Forests: Evidence from the Western Ghats

It is generally argued that in rural areas people depend more on natural environment like forest due to the economic compulsions arising out of poverty (Dasgupta and Maler, 1995). A number of forest resources are complimentary in production and consumption to other goods and services and supplement household incomes especially in times of acute economic stress (Falconer and Arnold, 1989). The contribution of non-timber forest products to the total households’ income is found to be a significant factor that support rural livelihood (Nadkarni et al., 1989; Appasamy, 1993; Chopra, 1993; Mallik, 2000). To take the case of Orissa, the nontimber forest products contribute about 22.4 to 54.5 per cent of the total households’ income (Mallik, 2000). However, serious constraints on the access and appropriation of these products have been enforced by the state while establishing protected areas as a part of the forest policy. There is evidence to show that setting up of protected forest areas and managing biological resources has worked against the interest of the local population (Kothari et al., 1989). Sometimes, this has resulted in the illegal exploitation of resources and increased conflicts between local people and the State (McNeely, 1993). As a result, formulating strategies to reduce pressures on protected forest areas arising out of socio-economic reasons have become the prime concern of environmental policy makers and international donor agencies (World Bank, 1996). Among the various measures, the recent India-Ecodevelopment Project initiated with the assistance of World Bank aims to address the impact of the local people on the protected areas and the impact of protected areas on the local people merits special mention. The thrust of the project is on the improvement of protected area management with the involvement of local people and their welfare (World Bank, 1996). In order for the people to participate or involve in the management of protected forests, they ought to have or perceive a stake over the resource. Although forests are a source of livelihood, there have been only very limited attempts, so far to understand the stakes of the people living in protected areas where people’s participation in protected area management has been invited through the India-
Spatio-temporal estimation with Bayesian maximum entropy and compressive sensing in communication constrained networks

Large scale monitoring applications require large numbers of sensors deployed in a region for accurate and high resolution spatio-temporal measurements and estimation. This can be achieved practically by deploying a mix of high capacity, high precision, expensive and low capacity, low precision, cheap sensors in the monitored region. However, the resource constrained nature of low-capacity sensors, and the availability of limited numbers of high-capacity sensors are a challenge to achieving highly accurate estimations. In this paper we propose a framework combining Bayesian compressive sensing and a robust Bayesian maximum entropy based spatio-temporal estimation technique to address this important problem. Evaluation on real wireless sensor network data reveals the trade-off between the spatio-temporal estimation accuracy and the communication overhead incurred in the network, and provides a mechanism to choose the right compressive ratios, such that a given estimation accuracy is achieved for a known communication overhead in the network.
A pilot evaluation of a social media literacy intervention to reduce risk factors for eating disorders

OBJECTIVE This pilot study investigated the effectiveness of a social media literacy intervention for adolescent girls on risk factors for eating disorders. METHOD A quasi-experimental pre- to post-test design comparing intervention and control conditions was used. Participants were 101 adolescent girls (Mage = 13.13, SD = 0.33) who were allocated to receive three social media literacy intervention lessons (n = 64) or to receive classes as usual (n = 37). Self-report assessments of eating disorder risk factors were completed one week prior to, and one week following the intervention. RESULTS Significant group by time interaction effects revealed improvements in the intervention condition relative to the control condition for body image (body esteem-weight; d = .19), disordered eating (dietary restraint; d = .26) and media literacy (realism scepticism; d = .32). DISCUSSION The outcomes of this pilot study suggest that social media literacy is a potentially useful approach for prevention of risk for eating disorders in adolescent girls in the current social media environment of heightened vulnerability. Replication of this research with larger, randomized controlled trials, and longer follow-up is needed.
StrandDisplacementAppliedto AssayswithNucleicAcidProbes

This novel method for the detectionof specificnucleic acid sequences has potential applicationsto clinical diagnosis. Duringhybridization,a signal-bearingnucleicacid strand is displaced by the target nucleic acid from a partiallysinglestranded complementaryprobe strand of nucleicacid. The probe:signalstrand complex is prepared by hybridizingsingle-stranded probe that is entirely complementary to the target nucleic acid with a shorter signal sequence that is complementary to a portionof the probestrand.The sample nucleicacid Is added to thishybridcomplexunderhybridization conditions.The target sequence, if present in the sample, will hybridizefirst to the unoccupiedprobe sequences, andthen willdisplacethe labeled strandby branchmigration. By this“stranddisplacement”the signalstrandsare freed in solution, where they may be separated from those still hybridized;the quantityof label measuredis directlyproportionalto the amountof analytesequencesinthe sample.This method,demonstratedhere for model and syntheticDNAs, can easily be adapted for the detectionof any RNA or DNA sequence and obviates the need for immobilization of sample. A wide variety of labelingtechniquescan be used, and the displacementcan be performed in solutionor with the hybrid complex attached to a solid support. This assay circumventsnonspecificbindingof label to the filter matrix and the laboriouswashing steps inherent in other assays involvingnucleicacid probes.
Average power estimation under nonsinusoidal conditions

The authors address the problem of estimating the average power of electrical systems under nonsinusoidal conditions. Firstly, a time-domain based algorithm is proposed, which smooths sampled data using suitable coefficients, prior to their numerical integration. Then, the algorithm performance is quantified with respect to narrow- and wide-band noise and finally, simulation results are presented showing its effectiveness in estimating average power when starting from multifrequency voltage and current samples.
CIELAB Color Space based High Resolution Satellite Image Segmentation using Modified Fuzzy C-Means Clustering

This paper presented a novel approach for the segmentation of high resolution satellite images using the spatial information incorporated modified fuzzy c-means clustering algorithm. The images after preprocessing and geo referencing, the satellite images are available in RGB color space. In this device dependent and non uniform color space, the intensity and color information are mixed and also the effectiveness of the color information mainly depends upon the type of light sources used. So RGB color space is not preferred for the segmentation and pattern recognition. In this paper, this problem is solved by the application of perceptually uniform CIELab color space. Even though FCM algorithm is one of the efficient approaches for image segmentation, it doesn"t give any spatial information which is important for clustering problems. In modified FCM clustering algorithm, the spatial information is incorporated as a function of the weighted sum of the membership function. Moreover, the noisy pixels can be eliminated by image enhancement process. The result and efficiency of the proposed approach is compared with other soft computing and non-soft computing methods.
Financial Analysts' Forecast Precision : Swedish Evidence

The future is uncertain. We therefore make predictions and forecasts of the future in order to be able to plan and react to future events. For this purpose, financial analysts are argued to have a responsibility towards investors and the market, in helping to keep the market efficient. Given that financial analysts act in a rational way we argue that analysts should strive to maximize forecast accuracy. The purpose of this study is to investigate how accurate financial analysts’ forecasts of Swedish firms’ future values are, and what information that analysts use that significantly affect the analysts’ forecast accuracy. To investigate this we first examine whether financial analysts contribute with value to investors by comparing their forecast precision against a simple time-series model. Our findings show that financial analysts produce significantly more accurate forecasts than a time-series model in the short term. Furthermore, given that rational analysts act in their own best interest while making accurate forecasts, we argue that analysts will incorporate and use the information that is available to them for the purpose of maximizing forecast accuracy. We investigate this by testing if the analysts’ forecast accuracy is affected by; the forecast horizon, the number of analysts following a firm, the firm size, the corporate visibility, the predictability of earnings, and trading volume. We find that the forecast accuracy is better when the amount of analysts following a firm is high, the firm size is larger, the forecasted company’s corporate visibility in the news is more frequent, and the predictability of earnings is higher. The trading volume does not have a significant effect on analysts’ forecast accuracy. To conclude, we question the value of financial analysts’ forecasts for longer forecast horizons.
Radiation tolerant VLSI circuits in standard deep submicron CMOS technologies for the LHC experiments: practical design aspects

We discuss design issues related to the extensive use of Enclosed Layout Transistors (ELT's) and guard rings in deep submicron CMOS technologies in order to improve radiation tolerance of ASIC's designed for the LHC experiments (the Large Hadron Collider at present under construction at CERN). We present novel aspects related to the use of ELT's: noise measured before and after irradiation up to 100 Mrad (SiO/sub 2/), a model to calculate the W/L ratio and matching properties of these devices. Some conclusions concerning the density and the speed of IC's conceived with this design approach are finally drawn.
Kenya Rural Enterprise Program : case study of a microfinance scheme

This report summarizes the findings of an action research conducted on the operations of Kenya Rural Enterprise Programme (K-REP), a microfinance institution (MFI) in Kenya. The program was established in 1984 by World Education, Inc., a US-based private voluntary organization. It was designed as an intermediary nongovernmental organization (NGO) to provide credit and technical assistance to other NGOs. Member savings are required in order to borrow from K-REP. The institution obtains funds from commercial banks for on-lending to its borrowers. K-REP lends to clients who under normal circumstances would find it difficult to access credit from commercial banks. It involves the beneficiary groups in making major decisions. The clients have been able to expand their business and increase the numbers of their employees, and have been introduced to the banking system. Lessons learned and innovations that K-REP developed fall in three broad categories: organizational, operational, and outreach. First, K-REP develops a group-based credit model following experimentation with a pilot Juhudi Scheme, an indigenous credit system. Second, K-REP shifted towards a minimalist approach by which it provided credit to its clients with minimal amounts of training and social services. These two changes led to a significant increase in outreach, both in number of clients and loan volume, under the Juhudi Scheme.
Adaptive subtraction of multiples using the L1‐norm

A strategy for multiple removal consists of estimating a model of the multiples and then adaptively subtracting this model from the data by estimating shaping filters. A possible and efficient way of computing these filters is by minimizing the difference or misfit between the input data and the filtered multiples in a least‐squares sense. Therefore, the signal is assumed to have minimum energy and to be orthogonal to the noise. Some problems arise when these conditions are not met. For instance, for strong primaries with weak multiples, we might fit the multiple model to the signal (primaries) and not to the noise (multiples). Consequently, when the signal does not exhibit minimum energy, we propose using the L1‐norm, as opposed to the L2‐norm, for the filter estimation step. This choice comes from the well‐known fact that the L1‐norm is robust to ‘large’ amplitude differences when measuring data misfit. The L1‐norm is approximated by a hybrid L1/L2‐norm minimized with an iteratively reweighted least‐squares (IRLS) method. The hybrid norm is obtained by applying a simple weight to the data residual. This technique is an excellent approximation to the L1‐norm. We illustrate our method with synthetic and field data where internal multiples are attenuated. We show that the L1‐norm leads to much improved attenuation of the multiples when the minimum energy assumption is violated. In particular, the multiple model is fitted to the multiples in the data only, while preserving the primaries.
Research on Wireless Power transmission system between satellites

The Wireless Power Transfer (WPT) technology is a promising way to break the limit of capability and operation for satellites and make the satellites much lighter, smaller and more flexible and durable. This paper introduces the system integration techniques of WPT between satellites including the energy control subsystem, the laser-WPT subsystem and the microwave-WPT subsystem, and discusses the mechanisms of laser WPT subsystem and the ground demonstration platform of the microwave-WPT subsystem. Finally, this paper gives the experimental results of the WPT on the ground.
Measuring efficiency consistent with maximising net benefit

Conventional methods of specifying effects or quality of service variables in economic efficiency measures as outputs framed from a utility bearing perspective reflect underlying economic objectives such as minimising average cost per unit of effect. However, in service industries such as health care where effects of services are incremental and non-tradable once received, an economic objective of minimising average cost per unit effect has been rejected in favour of maximising (incremental) net benefit. More generally, the maximisation of net benefit, which explicitly values effects at the willingness to pay threshold, has previously been shown to provide a necessary and sufficient condition for pareto improvement with public expenditure under uncertainty. In this paper a correspondence method is identified which allows the incorporation of effects in ratio measures of efficiency consistent with the maximisation of net benefit. Framing effects from a disutility perspective and comparing service providers on the cost-disutility plane, with an input specification of effects is demonstrated to allow identification of peers and measures of economic, technical, allocative and scale efficiency consistent with maximising net benefit. This method is illustrated in comparing the relative efficiency of 45 hospitals in New South Wales.
Information and communication needs of Chinese American breast cancer patients: perspectives on survivorship care planning.

BACKGROUND The existing knowledge on the survivorship experiences of Chinese American breast cancer survivors (CABCS) has arisen largely from aggregated data across multiethnic or multicancer studies that have focused on quality of life. Little is known about Chinese American perspectives and preferences for survivorship care. OBJECTIVE To examine the experiences of CABCS to better understand their information and communication needs and their preferences for survivorship care plans (SCPs). METHODS 16 CABCS, aged 37-72 years, were recruited through community-based organizations in the Northeast United States to participate in one-on-one telephone interviews about their breast cancer survivorship experience. The semistructured interviews were conducted in Mandarin, Cantonese, or English. Two investigators transcribed and translated the audio recordings into English and analyzed the interview transcripts using established methods of qualitative content analysis. RESULTS Three main themes were identified through analysis of interview transcripts: the need for evidence-based and culturally and linguistically appropriate health information; the role of language or communication barriers and culture in accessing care and communicating with providers; and preferences for SCP elements and format. LIMITATIONS The sample may not be representative of the entire population of CABCS. CONCLUSIONS The findings provide insight into the information and communication needs and SCP preferences of CABCS. Understanding the cultural nuances that underlie these needs and preferences is critical for improving CABCS's quality of life after treatment for cancer. SCPs that incorporate Chinese-language resources and address the unique cultural needs of this population should be developed and they should include information about diet and nutrition as well as traditional Chinese medicine.