Miracle-dz/UniFAR-FTUs huggingface dataset:
Sea Surface Flow Estimation via Ensemble-based Variational Data Assimilation

In this paper, we propose a data assimilation method for consistently estimating the velocity fields from a whole image sequence depicting the evolution of sea surface temperature transported by oceanic surface flow. The estimator is conducted through an ensemble-based variational data assimilation, which is designed by combining the advantages of two approaches: the ensemble Kalman filter and the variational data assimilation. This idea allows us to obtain the optimal initial condition as well as the full system trajectory. In order to extract the velocity fields from fluid images, a surface quasi-geostrophic model representing the generic evolution of the temperature field of the flow, and the optical flow constraint equation derived from the image intensity constancy assumption, are involved in the assimilation context. Numerical experimental evaluation is presented on a synthetic fluid image sequence.
Role of Ipratropium Bromide and Tiotropium in Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) remains a major public health problem. It is the fourth leading cause of chronic morbidity and mortality in the United States and is projected to rank fifth in 2020 in burden of worldwide, according to a study published by the World Bank/World Health Organization [1]. Chronic Obstructive Pulmonary Disease is characterized by chronic airflow limitation that is not fully reversible and usually progressive characteristic symptoms include chronic and progressive dyspnoea, cough and sputum production, which result in significant impairment in exercise capacity and quality of life [2]. Worsening lungs function is also associated with frequently increasing disease severity [3].
The correlation of fasting blood glucose levels with the severity of diabetic foot ulcers and the outcome of treatment strategies

Background: The prevalence of type 2 diabetes mellitus (T2DM) and related complications are rapidly rising worldwide. Diabetic Foot Ulcer (DFU) carries a high risk of proximal or distal amputation. This study explored the correlation of fasting blood glucose levels with the grades of DFUs and the outcome of treatment strategies offered. Materials and Methods: The data of all consecutive patients admitted to the surgical unit with DFUs was recorded for demographic information, grades of DFUs, fasting blood glucose, limb vascularity, treatment strategies offered and the outcome of treatment were recoded. Results: Of a total of 252 patients, 144 (57.1%) had fasting blood glucose level of ≥ 220 mg (%) and 14 (5.6%) had values between 80-100 mg (%). Majority of patients (131; 51.9%) presented with grades 4 and 5 DFUs. A total of 123 amputations were performed, however, only 83 (32.9%) improved and 154 (61.1%) did not (p value 0.00). Conclusion: In this study the majority of patients had poorly controlled T2DM with advanced stage of DFUs that necessitated amputations. An interdisciplinary approach with optimal control of fasting blood glucose and an early detection and aggressive treatment of tissue infection can reduce the frequency of lower limb amputations and T2DM-related morbidity.
Needs-Satisfaction, Motivation, and Achievement in High School Students: Testing Predictive Models by Gender and Ethnicity

Student motivation is one proposed contributing factor to disparate rates of high school achievement. Guided by self-determination theory (SDT; Ryan & Deci, 2000a), the purpose of the present study is to investigate whether a process model of the relationship between motivation and achievement varied by gender and racial subsamples of students within one large high school (see Figure 1). First, I examined the reliability and structural validity of the measures within the model. Second, I examined the extent to which the climate of one large urban high school was related to individual perceptions of autonomy, competence, and relatedness across gender and racial/ethnic subgroups. Then, I used structural equation modeling to test a process model in which autonomous motivation mediated the relationship between perceived climate or needs-satisfaction and achievement (with and without accounting for prior year achievement). The sample consisted of 863 students from an urban high school in the Western United States. The reliability and structural validity for the Basic Psychological Needs Scale (BNS) were below acceptable ranges, whereas the reliability and structural validity for the Academic Motivation Scale (AMS) were within the acceptable ranges. The relationships among needs-satisfaction, autonomous motivation, and achievement were not fully consistent with SDT; that is, competence and relatedness were significantly related to achievement (r = .20, r = .19, respectively, p .01). European American and Asian American students showed significantly and meaningfully higher mean-level GPA than African American and Latino students, whereas differences among groups in needs-satisfaction and autonomous motivation were not both meaningful and significant. The process model without prior achievement explained 1% of the variance in achievement and fit indices approached acceptable ranges, whereas the model with prior year achievement showed unacceptable fit indices. This study highlights the importance of valid and reliable measures of psychological constructs before examining their relationships to achievement. Additionally, the value of studying hypothesized models across gender and racial subsamples is demonstrated. Lastly, this study illuminates the importance of continually testing theories, even those that are relatively well established.
A Review of Trailing Edge Bluntness and Tip Noise from Wind Turbine Blades

One of the dominant noise sources from rotating machinery equipment is from trailing edge section of an airfoil as found in wind turbine blades. A computational study of noise mechanism due to trailing edge of blade for a three bladed 2 megawatt wind turbine was performed using the semi empirical noise model. The model predicts the sound power levels from trailing edge bluntness source using boundary layer displacement thickness on pressure and suction side of airfoil. At low Mach number flows (0.1884) and moderate to high Reynolds number (4.73 x 10 5 – 3.35 x 10 6 ) in span wise direction of blade, the pressure field on the surface of blade close to trailing edge causes the noise to radiate as result of interaction of the turbulent boundary layer. The trailing edge bluntness noise levels are illustrated for wind speed regime from 4 22 m/s. The extent of reduction in A-weighted total sound power level was analyzed using the trailing edge thickness and trailing edge angle between the lower and upper surfaces of airfoil. The influence of blade tip pitch angle configuration and tip geometry are also examined using tip noise mechanism. The results showed good agreement between total A-weighted sound power levels including tip and the validated experiments.
Using occupancy as a state variable for monitoring the Critically Endangered Alaotran gentle lemur Hapalemur alaotrensis

Although monitoring is an essential tool for biodiversity conservation, monitoring pro- grammes are often poorly designed and thus unlikely to produce results that are meaningful for man- agement. Monitoring is especially challenging when dealing with rare and elusive species in areas where conservation resources are particularly limited. In such cases, monitoring techniques aimed at estimating occupancy represent an attractive alternative to traditional methods concerned with esti- mating population size, as the collection of detection/non-detection data is in general less costly and easier to implement. In this study, we evaluated the use of occupancy as a state variable for the mon- itoring of the Alaotran gentle lemur Hapalemur alaotrensis, a Critically Endangered primate exclu- sively inhabiting the dense marshes around Lake Alaotra in Madagascar. We used a likelihood-based modelling approach that explicitly accounts for detectability. This showed that the probability of detection of H. alaotrensis was extremely low and depended on site characteristics that can vary in space and time, confirming the need to account for imperfect detection when monitoring this species. We used our models to explore factors affecting the probability of occupancy and detection to iden- tify management implications, and also developed recommendations for the ongoing monitoring of this species. The method applied in this study provides an efficient tool for the monitoring of an elu- sive species and has the potential to provide a flexible sampling framework for local community- based monitoring initiatives.
Improving the Productivity in Isolating a Naturally Occurring Bioactive Compound Using Supercritical Fluid Extraction and Preparative Supercritical Fluid Chromatography

■ ■ Both SFE and SFC reduce the use of organic solvents and provide an easy sample recovery under mild conditions, thereby increasing the overall purification productivity and cost-effectiveness. IN T RO DU C T IO N Natural products are a productive source of leads for new drugs due to their high chemical diversity, biochemical specificity, and many “drug-likeness” molecular properties. A large portion of today’s existing drugs on the market are either directly derived from naturally occurring compounds or inspired by a natural product. In addition, natural products are also used in the forms of food supplements, nutraceuticals, alternative medicines, and as active ingredients in cosmetics.
PROPERTIES OF GEOPOLYMER CEMENTS

Geopolymer cement, high-alkali (K-Ca)-Poly(sialate-siloxo) cement, results from an inorganic polycondensation reaction, a so-called geopolymerisation yielding three dimensional zeolitic frameworks. High-tech Geopolymer K-Poly(sialate-siloxo) binders, whether used pure, with fillers or reinforced, are already finding applications in all fields of industry. These applications are to be found in the automobile and aeronautic industries, non-ferrous foundries and metallurgy, civil engineering, plastics industries, etc. Geopolymer cement hardens rapidly at room temperature and provides compressive strengths in the range of 20 MPa, after only 4 hours at 2 0°C, when tested in accordance with the standards applied to hydraulic binder mortars. The final 28-day compression strength is in the range of 70-100 MPa.The behaviour of geopolymeric cements is similar to that of zeolites and feldspathoids; they immobilize hazardous materials within the geopolymeric matrix, and act as a binder to convert semi-solid wastes into adhesive solids. Their unique properties which include high early strength, low shrinkage, freeze-thaw resistance, sulphate resistance and corrosion resistance, make them ideal for long term containment in surface disposal facilities. These high-alkali cements do not generate any Alkali-Aggregate-Reaction. Preliminary study involving 27 Al and 29 Si MASNMR spectroscopy and the proposed structural model, reveal
InPrivate Digging: Enabling Tree-based Distributed Data Mining with Differential Privacy

Data mining has heralded the major breakthrough in data analysis, serving as a “super cruncher” to discover hidden information and valuable knowledge in big data systems. For many applications, the collection of big data usually involves various parties who are interested in pooling their private data sets together to jointly train machine-learning models that yield more accurate prediction results. However, data owners may not be willing to disclose their own data due to privacy concerns, making it imperative to provide privacy guarantee in collaborative data mining over distributed data sets. In this paper, we focus on tree-based data mining. To begin with, we design novel privacy-preserving schemes for two most common tasks: regression and binary classification, where individual data owners can perform training locally in a differentially private manner. Then, for the first time, we design and implement a privacy-preserving system for gradient boosting decision tree (GBDT), where different regression trees trained by multiple data owners can be securely aggregated into an ensemble. We conduct extensive experiments to evaluate the performance of our system on multiple real-world data sets. The results demonstrate that our system can provide a strong privacy protection for individual data owners while maintaining the prediction accuracy of the original trained model.
Kernel-mode exploits primer

This paper investigates the process of exploiting kernelmode vulnerabilities on Windows and Linux. First, the common elements of kernel-mode exploits will be introduced. Issues of Windows driver programming and exploiting Windows kernel-mode vulnerabilities with the Metasploit framework will be addressed next, followed by a description of an example exploit. Then, the focus will shift to Linux and a discussion of possible vulnerability types in kernel-mode. Finally, the integration of Linux kernel-mod e exploits with the Metasploit 3.0 framework will be discusse d on the basis of an exemplary exploit.
An Exploratory Analysis of the Relationship between Student Earnings and Postsecondary Retention

Policy makers are becoming increasingly concerned about the high percentage of students who attend postsecondary education without completing a degree. Researchers have studied numerous potential determinants of retention behavior for postsecondary students, such as financial aid, socioeconomic status, academic preparedness, academic and social integration, and expected future wages. However, none of these studies considers students’ earnings while in school as a potential determinant of retention. Using an administrative data from postsecondary institutions matched with administrative earnings data from the state’s unemployment insurance department, our results indicate that student earnings are negatively correlated to student retention in Kentucky postsecondary institutions. Our preferred model, hazard, indicates that a percentage increase in earnings reduces time to stopout with a probability of 1.767%. Even after controlling for student intentions, students are more likely to stopout at the rate of 1.050%. Ability as measured by first-term GPA in KCTCS and credits earned in the first semester positively affects retention. * Corresponding author. We thank Christina Whitfield, Alicia Crouch, Rion McDonald, and Aphy Brough at the Kentucky Community and Technical College System (KCTCS) for providing access to and help with their administrative data as well John Butler for his comments. This project was supported with a grant from the University of Kentucky Center for Poverty Research (UKCPR) through the U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation, grant number 3048106739. The opinions and conclusions expressed herein are solely those of the authors and should not be construed as representing the opinions or policy of the UKCPR or any agency of the local, state, or Federal government.
Privatization and Profit Efficiency: Evidence from Commercial Banks of Pakistan

This paper investigates the profit efficiency of commercial banks where the banking sector has completed more than two decade of changeover from nationalization policy to privatization and restructuring policy by employing stochastic frontier true effect and true random effect models. Intermediation approach has been used to choose input and output variables of banks. A balanced panel data of 22 commercial banks of Pakistan over the period 1995-2014 have been used for the empirical analysis. The paper found that commercial banks are on average 73% profit efficient. However foreign banks report high profit efficiency score followed private domestic banks and then state owned banks. We also compared the cost and profit efficiency of commercial banks and found that commercial banks are more cost efficient than profit efficient.
Isolation, optimization and production of biopolymer (poly 3-hydroxy butyrate) from marine bacteria

The synthetic polymer plastics become an integral part of contemporary life. Excess use of plastics and indiscriminate dumping of it in soil and water is polluting the environment and other living organisms. To overcome this problem, the production and applications of eco-friendly biodegradable products (such as bioplastics) from microbes are becoming inevitable from the last decade and also good alternatives of synthetic polymers. Keeping this point in mind the present study aimed at isolating and identifying the poly 3- hydroxybutyrate (PHB) producing bacteria from marine sources that can be effectively utilized for the synthesis of bioplastics. For isolation of poly 3-hydroxybutyrate producing bacteria, spread plate technique was followed using E2 mineral medium. After incubation, based on the morphological characteristics 32 strains were isolated and identified from the sand dunes plants of rhizosphere vegetation of Chennai coast. While staining with Sudan Black, six strains viz., AMET 5103, AMET 5111, AMET 5113, AMET 5121, AMET 5124 and AMET 5128 were identified as poly 3-hydroxybutyrate producing bacterial strains. Based on the dry weight of total biopolymer content, the strain AMET 5111 showed the maximum accumulation and was selected for optimizing at different pH, temperature, salinity, carbon and nitrogen source, incubation period and peak time of poly 3-hydroxybutyrate accumulation. Based on the biochemical tests, the strain AMET 5111 was found to be Pseudomonas spp. The optimum pH, temperature and salinity were found to be 7.0, 30°C and 5%. The peak time of poly 3-hydroxybutyrate accumulation was found to be 36hrs. The best carbon and nitrogen sources were found to be sucrose and (NH4)2HPO4. The selected strain was massively cultured using the optimized media and poly 3-hydroxybutyrate was extracted by solvent extraction.
A Novel Interaction Paradigm For Exploring Spatio-Temporal Data

Complex spatio-temporal data is difficult to visualize and even further to interact with, especially by several users at the same time. However, visualization and exploration of such data are essential for experts to understand complex data environments, such as for mitigating the adverse effects of disease spread. This paper presents an alternative approach to that of current spatiotemporal data visualizations to access, interpret, and manipulate spatio-temporal datasets as a single user or as a team. Our approach uses tangible and visual tools such as mini-robots, tabletop displays and augmented reality tools, to facilitate the data exploration and interpretation. We also introduce a simple use case that illustrates one of the possible utilization of the system. While tangibles have been introduced to represent information, we are investigating manners in which we can depict even more complex datasets. Our system will provide a novel approach to manipulate 3D and 4D datasets that classic tools such as a 2D mouse or a tactile screen would not allow.
Observations on the Absorption of Radioactive Strontium and Yttrium by Marine Algae

Certain marine algae were treated with sea water containing carrier-free radioactive strontium (mixture of Sr89 and Sr90), to test whether these ions were taken up by the weeds. At the same time the behaviour of radioactive yttrium (Y90), which occurred as a short-lived daughter-product of Sr90, was investigated by the expedient of studying the ‘decay’ characteristics of specimens of water and weed. Promising possibilities of this technique, by which an isotope is made available for study by applying its parent substance, are pointed out. Radioactive strontium is extracted from sea water by the brown sea-weeds, in particular by Fucus serratus. It is held that this effect is simply a result of ionic exchange, and that the algae regularly contain many times as much strontium in their cell fluids as exists in sea water.
Learning Coupled Forward-Inverse Models with Combined Prediction Errors

Challenging tasks in unstructured environments require robots to learn complex models. Given a large amount of information, learning multiple simple models can offer an efficient alternative to a monolithic complex network. Training multiple models-that is, learning their parameters and their responsibilities-has been shown to be prohibitively hard as optimization is prone to local minima. To efficiently learn multiple models for different contexts, we thus develop a new algorithm based on expectation maximization (EM). In contrast to comparable concepts, this algorithm trains multiple modules of paired forward-inverse models by using the prediction errors of both forward and inverse models simultaneously. In particular, we show that our method yields a substantial improvement over only considering the errors of the forward models on tasks where the inverse space contains multiple solutions.
Heavy metals content of canned tuna fish marketed in Tabriz, Iran

BACKGROUND: Some heavy metals are dangerous to health and there is rising concern about the quality of foodstuffs in some parts of the world. Fish, particularly Tuna fish, can concentrate huge quantities of several metals from water and they even play a significant role in human nourishment. OBJECTIVES: In this study, the concentrations of mercury and four trace metals in five brands of canned tuna samples purchased within the Tabriz city (Iran) were determined after digestion via the Association of Official Analytical Chemists techniques. METHODS: A total of 40 samples were collected. Lead and cadmium levels were determined via graphite tube atomic absorption spectrophoto- metry, whereas nickel and tin levels were determined via flame atomic absorption spectrophotometry, and mercury levels were determined via hydride generation atomic absorption spectro- photometry. RESULTS: The ranges obtained for the elements were Pb (0.01-0.242), Ca (0.0-1.05), Ni (0.113-0.589), Sn (0.05- 0.9), and Hg (0.1-0.205) mg/kg wet weight. CONCLUSIONS: The results showed that tuna fabricated and marketed in Tabriz (Iran) had safe level of heavy metals that were lower than the averages of EC/FAO/WHO levels for these toxic metals.
Lipophilicity (LogD7.4) of N-Aryl Benzo Hydroxamic Acids

Hydroxamic acids are polyfunctional molecules which show a wide spectrum of biological and medicinal activities. Lipophilicity is known to be important for absorption, permeability and in vivo distribution of organic compound. Lipophilicity is also a major structural factor that influences the pharmacokinetic and pharmacodynamic behaviour of compound. Global Journal of Pharmacy & Pharmaceutical Sciences ISSN: 2573-2250
Unique normal forms near a degenerate elliptic fixed point in two-parametric families of area-preserving maps

We derive simplified normal forms for an area-preserving map in a neighbourhood of a degenerate resonant elliptic fixed point. Such fixed points appear in generic families of area-preserving maps. We also derive a simplified normal form for a generic two-parametric family. The normal forms are used to analyse bifurcations of n-periodic orbits. In particular, for n ⩾ 6 we find regions of parameters where the normal form has ‘meandering’ invariant curves.