Miracle-dz/UniFAR-FTUs huggingface dataset:
Adjacent Pixel Values Blocking and Prediction Error Expansion Based High Fidelity Reversible Data Hiding Scheme

This paper presents a novel reversible data hiding method based on pixel value blocking and prediction-error expansion. A cover image is divided into non-overlapping sub-blocks of two pixels. Watermark bits are embedded in two phases. In Phase-I, for each sub-block, second pixel value is predicted by the first pixel value and depending on prediction-error within a threshold limit secret bit is embedded into second pixel. Also secret bit is embedded into first pixel just by adjusting the location map without effecting into the pixel value. Then another compressed location map value is used to indicate overflow/underflow or the sub-blocks are outer threshold limit. Again in Phase-II, for each sub-block, first pixel value is predicted by the second pixel value and by depending on prediction-error within a threshold limit secret bit is embedded into first pixel. Also secret bit is embedded into second pixel by adjusting location map without effecting into the pixel value and another compressed location map value is used to indicate overflow/underflow or the sub-blocks of outer threshold limit. All secret bits can be recovered and restored the cover image completely from watermarked image. Experimental result of comparison of this scheme with recent existing scheme using different standard images shows that the embedding capacity with visual quality and PSNR values of the proposed scheme is larger than the existing scheme.
Contact and Commitment to Development: Evidence from quasi‐random missionary assignments

Public support for global development in rich countries is critical for sustaining effective government and individual action. But the causes of public support are not well understood. Does spending time living in a developing country play a role in generating individual commitment to development? Addressing this question is fraught with selection bias, as individuals are rarely exogenously assigned to spend time in different countries. In this paper I address this question using a natural experiment—the quasi-random assignment of missionaries from the Church of Jesus Christ of Latter-day Saints to two-year missions in different world regions. I provide the first causal estimates of the effect of travel to a developing country on attitudes to global development. Data comes from a new survey gathered through mission alumni Facebook groups. Missionaries assigned to low-income and middle-income world regions (Africa, Asia, Latin America, and the Caribbean) have similar prior characteristics to those assigned to high-income Europe. Those assigned to Africa self-report greater interest in global development and greater charitable attitudes and behaviours. However they also express stronger opposition to immigration from poor countries, and are less likely to be involved in political campaigns to address global development. Spending time in lowerincome countries may lead to greater support for charity but less support for political change. www.cgdev. org Lee Crawfurd
Inhibitory Effect of Mesima Reishi UE-1 on Tumor Growth and Angiogenesis

Objective To study the inhibitory effect of Mesima Reishi UE-1 on growth and angiogenesis of Lewis pulmonary carcinoma.Methods The models of Lewis pulmonary carcinoma were used to test the effect of UE-1 on tumor growth, and microvessel density was investigated in entity tumor by immunohistochemical technique. The count of tumor-induced new vessel was used to manifest the effect of UE-1 on Lewis pulmonary carcinoma angiogenesis. The inhibition of UE-1 on chick chorioallantoic membrane (CAM) angiogenesis was studied by CAM assay.Results The average weight and volume of Lewis pulmonary carcinoma in UE-1 group were lower than those in control group(P0.05). The MVD of entity tumor in UE-1 group was also lower than that in control group(P0.05). The number of vesssels oriented toward the tumor mass in UE-1 group was less than that in control(P0.05). The CAM assay showed that UE-1 polysaccharide had anti-angiogenic effect.Conclusion Mesima Reishi UE-1 can inhibit the growth of Lewis pulmonary carcinoma. The inhibitory mechanism may be related to anti-angiogenic activity of UE-1.
Word Ranking based Document Clustering

The statement, that information is growing has become an understatement, considering the developments over the past decade. In fact information is burgeoning. The vast plethora of existing information over the internet and the continuing proliferation of data every day calls for newer ways to handle this information overload. The information overloaded on the internet does not follow any standard of arrangement of text and also suffers with the problem of immensity. There is also a missing mechanism of archiving and organizing information over the internet. Digital Libraries which encompass thousands of books and documents require the services of tools which can identify information across various levels of granularity (as in books, chapters or even pages). Manual data creation for an exponentially increasing volume of digital objects is becoming increasingly difficult. We develop a document clustering engine which uses a word ranking module with document categorization and clustering in order to recognize objects during information overload.
Food System Dynamics in Rural Environments and Health Benefits of the Mediterranean Diet

local smaller productions achieved through techniques based on the historical and cultural traditions of that specific territory, manifested only in that specific area [5]. The modern food producing system has provided wider market opportunities for regional food products but, at the same time, led to a significant drop in the importance of local markets and, consequently, to a change for the worse in traditional nutritional behaviours of local populations. The nutritional quality of the foods available affects the health of people and the protective role of the Mediterranean Diet (MD) has been largely demonstrated [6], especially in diet related non-communicable diseases, mainly in cardiovascular risk prevention. Dontaset al. [7] reported the benefits from the adoption of a Mediterranean-based dietary pattern. Risks posed for cardiovascular disease were significantly lower among Greek Publication History:
Bio-control Activity of Composts for Supporting Growth of Pearl millet

The use of compost is very important to sustainable crop growing. Plant growth-promoting bacteria (PGPB) were studied in this work to affect the enlargement, yield and nutrient uptake by a selection of methods. Seven various plant growth-promoting characters and antagonistic capacity was selected to screen bacteria isolated from various composts. Growth supporting capability of bacteria was studied on seed germination and biomass of plant. Ten isolates stand on various plant growth-promoting characters and seed vigor index were estimated at greenhouse for plant growth-promoting action on pearl millet. Maximum increase in plant weight was by P. fluorescens ISR 33 (1110 mg), S. marcescens ISR75 (772 mg). Plant growth-promoting action of composts and bacteria was considered mutually. Application of composts with bacteria improved plant growth that P.fluorescens ISR 33 increased the shoot length maximum (53cm) and B. diffusa ISR 35 showed the minimum increment (44cm). Leaf area was found maximum (51cm 2 ) in case of Bacillus circulans ISR 35 and minimum (41 cm 2 ) in Boerhaavia diffusa ISR 35. Root length density and Plant dry weight was found maximum in P. fluorescens ISR 33 and minimum in S. marcescens ISR75.
ParaStieltjes: Parallel computation of Gauss quadrature rules using a Parareal‐like approach for the Stieltjes procedure

The computation of Gauss quadrature rules for arbitrary weight functions using the Stieltjes algorithm is a purely sequential process, and the computational cost significantly increases when high accuracy is required. ParaStieltjes is a new algorithm to compute the recurrence coefficients of the associated orthogonal polynomials in parallel, from which the nodes and weights of the quadrature rule can then be obtained. ParaStieltjes is based on the time‐parallel Parareal algorithm for solving time‐dependent problems, and thus enlarges the applicability of this time parallel technique to a further, new area of scientific computing. We study ParaStieltjes numerically for different weight functions, and show that substantial theoretical speedup can be obtained when high accuracy is needed. We also present an asymptotic approximation for the node and weight distribution of Gauss quadrature rules, which can be used effectively in ParaStieltjes.
Modelling unemployment rate in the Czech Republic

Weak aggregate output demand and high unemployment are both basic features of the economy in the Czech Republic these days. For this reason, the model formulated in this paper is based on the following transition mechanism: “High unemployment leads to low consumption demand. Production is also low as no one can afford to buy the goods, which sustains high unemployment. ” The paper contributes to the existing literature by incorporating this Keynesian principle of weak aggregate demand into the basic DiamondMortensen-Pissarides (DMP) model in a simple and novel way. Despite its simplicity, the proposed model captures the essence of the current economic crisis. The parameters of the model are econometrically estimated. The estimated model turns out to have multiple equilibria, which is interpreted from an economic point of view. Key-Words: nonlinear modelling, unemployment, vacancies, multiple equilibria
Children's Resources and Poverty in Single-mother and Male-headed Households: A Collective Consumption Evidence from Ethiopia

We estimate a collective complete demand system model to recover children's resource shares and analyze their poverty. Identi cation of the sharing rule between children and adults relies on private assignable goods and distribution factors. Based on Ethiopian LSMS-ISA data for two sub-samples of families with children (married male-headed and single femaleheaded), we observe inequalities in intrahousehold resource allocation and welfare. We nd that children command less household resources and are poorer than adults which worsen with the number of children. Resource allocation is a ected by parental di erences in education and age, child education, proportions of female children and women, and number of non-biological children. Single-mothers not only are more altruistic to their children, but also avoid higher child poverty than married male heads although this seems to disappear when the number of children increases. Unlike the general belief that poor children live only with poor adults and households, our estimates show that non-poor families and adults also host poor children. Further, traditional poverty measures, which ignore intrahousehold resource allocation, are found to understate child (and adult) poverty. Lastly, regional and rural-urban disparities are found to exist. Findings have implications for fertility, gender, targeting and spatial redistribution issues.
Visual Saliency-based Theme and Aspect Ratio Preserving Image Cropping for Small Displays

—Scaling to fit an entire image in much smaller display reduces the recognizability of the objects in the image. Therefore, salient portions of an image is cropped and then scaled to fit to a small display. To do so existing methodologies do not maintain the overall theme of the image and incorporate distortion due to difference in aspect ratios of the cropped portion of the image with that of the display. Moreover, to be executed upon resource constrained hand-held devices the method must be as simple as possible. In this paper, a method for image cropping is proposed that takes care of all these matters.
Cost-Aware Feature Selection for IoT Device Classification

The classification of Internet-of-Things (IoT) devices into different types is of paramount importance, from multiple perspectives, including security and privacy aspects. Recent works have explored machine learning techniques for fingerprinting (or classifying) IoT devices, with promising results. However, the existing works have assumed that the features used for building the machine learning models are readily available or can be easily extracted from the network traffic; in other words, they do not consider the costs associated with feature extraction. In this work, we take a more realistic approach, and argue that feature extraction has a cost, and the costs are different for different features. We also take a step forward from the current practice of considering the misclassification loss as a binary value, and make a case for different losses based on the misclassification performance. Thereby, and more importantly, we introduce the notion of risk for IoT device classification. We define and formulate the problem of cost-aware IoT device classification. This being a combinatorial optimization problem, we develop a novel algorithm to solve it in a fast and effective way using the cross-entropy (CE)-based stochastic optimization technique. Using traffic of real devices, we demonstrate the capability of the CE-based algorithm in selecting features with minimal risk of misclassification while keeping the cost for feature extraction within a specified limit.
DreamCoder: Building interpretable hierarchical knowledge representations with wake-sleep Bayesian program learning

Expert problem-solving is driven by powerful languages for thinking about problems and their solutions. Acquiring expertise means learning these languages — systems of concepts, alongside skills to use them. We present DreamCoder, a system that learns to solve problems by writing programs. It builds expertise by creating programming languages for expressing domain concepts, together with neural networks guiding the language’s use. A new “wake-sleep” learning algorithm interleaves two sleep phases, alternately extending DreamCoder’s language with new symbolic abstractions, and training its network on imagined and replayed problems. DreamCoder solves classic programming problems and creative tasks like drawing pictures and building scenes. It rediscovers basics of modern functional programming, vector algebra and classical physics, including Newton’s and Coulomb’s laws. DreamCoder grows its languages compositionally from concepts learned earlier, building multi-layered symbolic representations that are interpretable and transferrable to new tasks, while still growing scalably and flexibly with experience.
Patient Characteristics and Clinical Process Predictors of Patients Leaving Without Being Seen from the Emergency Department

Introduction Delays in patient flow in the emergency department (ED) result in patients leaving without being seen (LWBS). This compromises patient experience and quality of care. Our primary goal was to develop a predictive model by evaluating associations between patients LWBS and ED process measures and patient characteristics. Methods This was a cross-sectional study in a 95,000 annual visit adult ED comparing patients LWBS, with controls. Data were drawn from four seasonally adjusted four-week periods (30,679 total visits). Process measures included 1) arrivals per hour; 2) “door-to-provider” time; and the numbers of 3) patients in the waiting room; 4) boarding ED patients waiting for an inpatient bed; 5) providers and nurses (RN); and 6) patients per RN. Patient characteristics collected included 1) age; 2) gender; 3) race/ethnicity; 4) arrival mode (walk-in or via emergency medical services [EMS]); and 5) acuity based on Emergency Severity Index (ESI). Univariable analyses included t-tests and Pearson’s chi-square tests. We split the data randomly into derivation and validation cohorts. We used backward selection to develop the final derivation model, and factors with a p-value ≤ 0.05 were retained. Estimates were applied to the validation cohort and measures of discrimination (receiver operating characteristic) and model fit were assessed. Results In the final model, the odds of LWBS increased with the number of patients in the waiting room (odds ratio [OR] 1.05; 95% confidence interval [CI], 1.03 to 1.06); number of boarding patients (OR 1.02; 95% CI, 1.01 to 1.03); arrival rate (OR 1.04; 95% CI, 1.02 to 1.05) and longer “door-to-provider” times (test of linear trend in the adjusted OR was p = 0.002). Patient characteristics associated with LWBS included younger age (OR 0.98; 95% CI, 0.98 to 0.99), and lower acuity (higher ESI category) (OR 2.01; 95% CI, 1.84 to 2.20). Arrival by EMS was inversely associated with LWBS (OR 0.29; 0.23 to 0.36). The area under the curve for the final model in the validation cohort was 0.85 (95% CI, 0.84 to 0.86). There was good agreement between the observed and predicted risk. Conclusion Arrival rate, “door-to-provider time,” and the numbers of patients in the waiting room and ED boarders are all associated with patients LWBS.
Disparities in Assessments of Living Standards Using National Accounts and Surveys Espen

Average per capita consumption and income from national accounts data can differ substantially from corresponding measures of consumption and income from household surveys. Using a new compilation of 1,664 household surveys matched to national accounts data, we find the gap between the data sources is larger and more robust than previously established. Survey means, on average, are 25 percent lower than corresponding means for household consumption from national accounts. The gap is largest in middle income countries, where also annualized growth rates for surveys are more than 1 percentage point lower than growth in national accounts, on average. We show how the gaps matter substantially for assessments of growth, poverty and inequality. We illustrate how typical survey measures, which do not account for these gaps, can exaggerate global poverty reduction and underestimate global inequality.
Bulletin of the Geological Society of Greece Vol. 36, 2004 APPLICATION OF 3-D VELOCITY MODELS AND RAY TRACING IN DOUBLE DIFFERENCE EARTHQUAKE LOCATION ALGORITHMS: APPLICATION TO THE MYGDONIA BASIN

In the past years there has been a growing demand for precise earthquake locations for seismotectonic and seismic hazard studies. Recently this has become possible because of the devel­ opment of sophisticated location algorithms, as well as hardware resources. This is expected to lead to a better insight of seismicity in the near future. A well-known technique, which has been re­ cently used for relocating earthquake data sets is the double difference algorithm. In its original im­ plementation it makes use of a one-dimensional ray tracing routine to calculate seismic wave travel times. We have modified the implementation of the algorithm by incorporating a three-dimensional velocity model and ray tracing in order to relocate a set of earthquakes in the area of the Mygdonia Basin (Northern Greece). This area is covered by a permanent regional network and occasionally by temporary local networks. The velocity structure is very well known, as the Mygdonia Basin has been used as an international test site for seismological studies since 1993, which makes it an ap­ propriate location for evaluating earthquake location algorithms, with the quality of the results de­ pending only on the quality of the data and the algorithm itself. The new earthquake locations re­ veal details of the area's seismotectonic structure, which are blurred, if not misleading, when resolved by standard (routine) location algorithms.
Feature Extraction Evaluation for Two Motor Imagery Recognition Based on Common Spatial Patterns, Time-Frequency Transformations and SVM

In recent years, motor imagery has been used as a communication alternative in brain computer interface systems. In this paper an evaluation of five different types of feature extraction methods to recognize two motor imagery signals based on common spatial patterns (CSP), and time-frequency transformations are evaluated; CSP, continuous Wavelet transform (CWT), Stockwell transform (ST), and the following combinations CSP+CWT and CSP+ST. The classifier employed to recognize between right-hand, and left-hand was a support vector machine. The proposed methods were evaluated in two know datasets and compared with other state of the art methods. The best performance achieved with the proposed methods, considering a correct recognition rate, was 79.87% ± 10.73% and 73.25% ± 08.04% with the datasets BCI Competition IV dataset 2a and EEGdataset, showing better performances than the reported works. Besides, the CSP+SVM method requires a processing time of only 1.73 seconds which make it suitable for real time applications.
Comparison of the Use of Dowel-Supported and Cement-Supported Transpedicular Screws In Fresh Frozen Calf Vertebrae: An Experimental Study

DOI: 10.21276/sjbr.2018. 3.6. 3 Abstract: The aim of this experimental was to compare the durability of the use of the study transpedicular screw supported by dowel or bone cement. In this experimental study which was performed on fresh frozen calf vertebrae, two groups were formed. 7 fresh frozen calf vertebrae were used in each group (n=7). A transpedicular screw supported by a dowel was placed to the left side of the vertebrae and a transpedicular screw supported by bone cement was placed to the right side. Then mechanical pulling force was applied to these groups. The force at which the pull out of the screw occurred and the expansion value up to the moment of pulling out were recorded. There was no fracture in any subject. There was no statistically significant difference between groups in terms of pulling out and expansion value (p = 0.58). There is no difference in durability between the uses of a transpedicular screw supported by a dowel or bone cement.
Effect of Autranellacongolensis on Lipid Profile of Rats’ Brain with Experimentally Induced Alzheimer’s Disease

Lipids are essentials components of the brain. Changes in brain lipid composition affect the physical and functional properties of the neuronal cell membrane and have been implicated in the physiopathology of Alzheimer disease (AD). We evaluated in this study the effect of hydroethanolicbark extract of A. Congolensis on lipid profile of rats’ brain with experimentally induced AD. The experimental model consisted of female rats, which received orally for 8 consecutive weeks a single dose of 50 mg/Kg b.w. /day of aluminum trichloride (AlCl3) (except control group) followed by distilled water (disease control group) or doses of the extract (150 or 300 mg/Kg b.w./day) or vitamin E (100 mg/Kg b.w./day) or galanthamine (2 mg/Kg b.w. /day). Brain cholesterol, phospholipids and plasmalogenlevels and fluidity were evaluated. Brain membranes ATPase activities, Ca2+, Mg2+and glucose levels were also assayed. Significant modifications of brain lipid composition and fluidity were observed in disease control group compared with control. In addition, Na+, K+-ATPase and Mg2+-ATPase activities significantly decreased, the level of intracellular Ca2+ increased, Mg2+ content decreased and brain glucose level was significantly higher. Standard drugs (vitamin E,galanthamine) showed a negative effect on brain lipid profile. The extract of 150 mg showed significant improvements of brain lipid profile and fluidity. It also indicated improved brain ATPase activities, ions and glucose brain homeostasis. The extract (150 mg/Kg b.w. dose) by maintaining the brain lipid composition may protect neuronal cell membraneand probably preventing the progression of AD.