Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated study of the water–ecosystem–economy in the Heihe River Basin

The ecological water diversion project in the Heihe River Basin is the first successful case in China in which the ecological systems in a river basin have been rescued. This project serves as a valuable example for the management of ecosystems in other inland river basins. This paper reviews the integrated studies of the water-ecosystem-economy relationship in the Heihe River Basin and concludes that sustainable development in inland river basins requires the basin to be considered as a whole, with the relationships between the upstream, midstream and downstream areas of the basin coordinated appropriately. Successful development in these basins will be reflected in an improved output per cubic meter of water and the implementation of integrated river basin management practices.
How a Public Health Goal Became a National Law

This case study provides insights into policy strategy and advocacy best practices that resulted in passage of the Healthy, Hunger-Free Kids Act of 2010, a public health law that resulted in improvements to school foods and beverages across the country. Congress reauthorizes child nutrition programs such as the National School Lunch Program and School Breakfast Program every 5 years. The Healthy, Hunger-Free Kids Act of 2010 is the legislation that reauthorized the child nutrition programs through September 30, 2015, and continues in effect today. We conducted stakeholder interviews and reviewed the legislative and regulatory history of the Healthy, Hunger-Free Kids Act of 2010 and advocates’ files. We formed an external advisory committee which helped to develop the interview questions and list of interviewees and reviewed the content of the case study. This case study focuses on the provisions that address the nutritional quality of school meals, snacks, and beverages and covers the period from 2004 to 2016. Overall, the case study demonstrates a number of key lessons to help inform other nutrition and public health policy initiatives, as well as continued implementation and defense of school nutrition. For instance, how advocates used research to develop and advocate for policy change, compromises that were needed to advance the policies, changes in attitudes about school food policy over time, framing and messaging, the role of state and local policy that contributed to national change, and how challenges were resolved between stakeholders.
Mobile Users' Self-Disclosure Behaviour on WeChat: Application of Social Cognitive Theory

One of the most challenging issues confronting social media operators is how to increase users’ activity and self-disclosure behaviour. However, more and more users are lowering their disclosures on social media, such as WeChat in China. Using social cognitive theory as a starting point while utilizing mobile instant messaging software WeChat as an example, this paper studies the dynamics that influence users’ self-disclosure behaviour on WeChat from two aspects: individual factors and environment factors. A structural equation model is used to verify a conceptual model. The results show that, firstly, mobile users’ self-disclosure behaviour on WeChat can be affected by both individual factors and environment factors. Specifically, individual factors, such as privacy concerns, negatively affect users’ self-disclosure behaviour, while environmental factors, such as social influences, positively affect users’ self-disclosure behaviour. More importantly, the research points to significant differences in self-disclosure behaviour between mobile users of different genders and ages. As such, the conclusions of this paper should provide key information for optimized operation of WeChat and other mobile information systems.
Development of a quantitative and conformation-sensitive ATR-FTIR biosensor for Alzheimer's disease: The effect of deuteration on the detection of the Aβ peptide

Alzheimer's disease (AD) is the most common form of dementia worldwide and represents a growing socio-economical issue. To date, no reliable diagnosis can be obtained at an early-stage of the disease, though it is now recognized that the aggregation of the amyloid β (Aβ) peptide is responsible for the onset of the disease. Recent studies have shown that soluble amyloid oligomers present in the physiological fluids were the most neurotoxic species and correlated best with the first signs of cognitive decline, which makes them good biomarkers in the development of a diagnostic tool.
The effect of 12-week service training on self-confidence in racket sport

The aim of this study is to investigate the effect of twelve-week service training on self-confidence in racquet sports. The universe of the study consists of the secondary schools in the province of Van, and the sample consists of 60 students from 10 to 14 years of age in Hasan Ali Yücel Secondary School in Van and TOBB Secondary School. Self-Concept Scale developed by "Piers-Harris" (1984) and adapted to Turkish Öner (1996) to evaluate their self-confidence before and after the study. In evaluating the performances, Dewitt-Dugan Tennis Test, Target Service Test, French-Stalter Badminton Service tests were applied. After the normality test was done, Independent-Sample T test was used for binary independent variables and paired-sample T test for dependent groups. The effect of self-confidence on the hit was tested by regression analysis. Significance level (p ˂ 0.05) was evaluated. When the finding of the study were examined, no change was observed between pre-test and post-test of the control group, while significant changes were observed between pre-test and post-test of the experimental group. As a result of this study, that can be said that 12-week service training positively affect self-confidence of rackets sports athletes.
The underlying basis for the trade-off between leaf size and leafing intensity

Summary Recent studies have reported a consistent trade-off between leaf size (mass) and leafing intensity (the number of leaves produced per unit of supporting stem tissue volume); however, a theoretical basis for this trade-off has not been described. We explore the mechanistic basis for this trade-off and assess the relationship in the light of other prominent theories for allometric biomass partitioning. We show algebraically how the allocation of mass to leaves versus stems and the density of stem tissue can potentially influence this trade-off. To assess these possible effects, we compared the relationship between leaf size and leafing intensity, expressed on both mass and volume basis, at the level of a single branch as well as the entire above-ground plant in 61 forbs over a 3-year period. Our results support the idea that the trade-off between leaf size and volume-based leafing intensity depends on both biomass investment (leaves vs. stems) and stem bulk density (mass vs. volume), whereas the trade-off between leaf size and mass-based leafing intensity only depends on the biomass investment. Similar exponents in the scaling of leaf mass vs. stem mass and stem mass vs. stem volume at branch and whole plant levels lead to similar trade-offs. An isometric trade-off between leaf size and volume-based leafing intensity is consistent with a constant biomass partitioning between leaves and stems as well as constant stem tissue density. Conversely, an allometric trade-off between leaf size and volume-based leafing intensity arises when biomass allocation is allometric and stem bulk density varies with plant size.
Statistics for citizen science: extracting signals of change from noisy ecological data

Policy‐makers increasingly demand robust measures of biodiversity change over short time periods. Long‐term monitoring schemes provide high‐quality data, often on an annual basis, but are taxonomically and geographically restricted. By contrast, opportunistic biological records are relatively unstructured but vast in quantity. Recently, these data have been applied to increasingly elaborate science and policy questions, using a range of methods. At present, we lack a firm understanding of which methods, if any, are capable of delivering unbiased trend estimates on policy‐relevant time‐scales. We identified a set of candidate methods that employ data filtering criteria and/or correction factors to deal with variation in recorder activity. We designed a computer simulation to compare the statistical properties of these methods under a suite of realistic data collection scenarios. We measured the Type I error rates of each method–scenario combination, as well as the power to detect genuine trends. We found that simple methods produce biased trend estimates, and/or had low power. Most methods are robust to variation in sampling effort, but biases in spatial coverage, sampling effort per visit, and detectability, as well as turnover in community composition, all induced some methods to fail. No method was wholly unaffected by all forms of variation in recorder activity, although some performed well enough to be useful. We warn against the use of simple methods. Sophisticated methods that model the data collection process offer the greatest potential to estimate timely trends, notably Frescalo and occupancy–detection models. The potential of these methods and the value of opportunistic data would be further enhanced by assessing the validity of model assumptions and by capturing small amounts of information about sampling intensity at the point of data collection.
Comparison of machine learning techniques to predict cardiovascular disease

The purpose of this thesis is to examine and compare the accuracy of different data mining classication systems through different machine learning techniques to predict cardiovascular disease. This comparison shows the different accuracy rates of different techniques and reasons behind their variations. The Cleveland dataset for heart diseases has been used in this study which contains 303 instances. The data has been divided into two sections named as training and testing datasets. The 10fold Cross Validation has been used here in order to work with the expanded dataset. The k-Nearest Neighbors, Support Vector Machine, Decision Tree, Random Forest, Gaussian Naive Bayes, Logistic Regression and Deep Belief Network machine learning techniques have been investigated in this research. Besides, ensemble learning method voting classifier has been applied on the data set. By the end of the implementation part, we have found Gaussian Naive Bayes is giving the maximum accuracy in our dataset and deep belief network is performing very poor. The reasons of variations of these different techniques by analyzing their characteristics and behavior with respect to the dataset has been understood by the study conducted for this thesis.
Biocomposites based on collagen and phosphorylated dextran for bone regeneration

The aim of this study was the development of biocomposite scaffolds (membranes and matrices) based on natural polymers used for bone tissue engineering. The novelty featured in this paper is the use of phosphorylated dextran (PDex) as natural component in collagen-based biocomposites. The PDex both in acid form and as mixed salts of Mg–Na, Zn–Na, Ca-Na was characterized by Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR) spectroscopy, potentiometric and conductometric titration and energy dispersive x-ray spectroscopy (EDX) analysis. The biocomposite scaffolds were obtained by freeze-drying as matrices and by free-drying as membranes with specific microporous morphological structures that depended on drying process of collagen gels with PDex. The biocomposites were physical–chemical characterized by differential scanning calorimetry (DSC) and, water and water vapor absorption. The biocompatibility was evaluated in vitro with human osteosarcoma MG 63 cell lines. The results showed that biocompatibility was improved by the use of PDex as mixed salts of Mg–Na, Zn–Na, Ca-Na in collagen biocomposites.
Radiologic Interpretation of Nutrition at Base of Spine (RIBS) - A novel nutritional marker in the critically ill surgical patient

Background and aims: Critically ill patients are frequently at risk of malnutrition. However, there is no single universal method of quantifying nutritional status in the intensive care unit (ICU). The aim of this study was to create and validate an objective tool to measure body composition as an indicator of nutritional status in critically ill patients. Method: Retrospective chart review conducted of patients admitted to the surgical ICU (SICU) from January 2012 through July 2014. Radiologic Interpretation at Base of Spine (RIBS) scores generated from the ratio of fat and muscle on CT scans of the spine in the axial and coronal planes. Demographic data, RIBS axial and coronal scores, laboratory markers of nutrition, length of stay (LOS), ventilator days, and in-hospital mortality were recorded and analyzed for statistical significance. Result: Data were collected on 58 SICU patients admitted for at least one month. Each patient had a minimum of two CT A/P scans performed one month apart. RIBS axial scores were found to have statistically significant correlation with BMI, BSA, and albumin. The intraclass correlation coefficients for inter-rater and intrarater assessment ranged from 0.9037 to 0.9966 (p ≤ 0.05) and from 0.9577 to 0.9989 (p ≤ 0.05), respectively. There was no significant association between baseline RIBS axial or coronal scores and postoperative outcomes (SICU LOS, ventilation days, in-hospital mortality). Conclusion: RIBS axial scoring is a reliable and reproducible tool that correlates with BMI, BSA and albumin and therefore can be used as an independent marker of nutrition. *Correspondence to: Lisa Santoriello, Ave G12, Glen Oaks, New York, USA, Tel: (516)413-9587; E-mail: Lisantori819@gmail.com
Ecology of the acanthocephalan Sclerocollum rubrimaris Schmidt and Paperna, 1978 (Rhadinorhynchidae: Gorgorhynchinae) from wild populations of rabbitfish (genus Siganus) in the northern Red Sea

The abundance, host relationships and microhabitat of Sclerocollum rubrimaris Schmidt & Paperna. 1978 (Rhadinorhynchidae: Gorgorhynchinae) were investigated in wild populations of the herbivorous rabbitfish (Siganus spp.) from the Gulf of Eilat, northern Red Sea. Siganus rivulatus (Forsskal, 1775) and S. argenteus (Quoy & Gaimard, 1825), judging by the high infection prevalences, are the primary definite hosts, whereas S. luridus (Ruppell, 1828) was only rarely infected and thus regarded as an accessory host. Overdispersion of S. rubrimaris suprapopu-lations was greatest in S. rivulatus. Juvenile worms occurred year-round, but enhanced recruitment was evident in both host populations between February and July. A high parasite abundance observed during spring (March-May) was correlated with an extensive period of pre-spawning algal grazing by the host fish. In S. rivulatus, parasite abundance increased with increasing host size, whereas in S. argenteus it was highest in young hosts, and decreased in larger fish. The variability of infection patterns in the three rabbitfish species probably stems not only from parasite specificity but also from the different habitats, feeding habits and diet preferences. Sclerocollum rubrimaris has a restricted host range and is not known to infect other herbivorous coral reef fish. The main region of attachment of S. rubrimaris is the anterior 5–25% of the gut in both S. rivulatus and S. argenteus, and the mean position of immature worms is significantly more posterior than that of sexually mature individuals.
Estimation of amounts of microbial and dietary nitrogen compounds entering the duodenum of cattle

Summary Young steers with rumen and simple duodenal cannulas were given diets of approximately equal amounts of flaked maize and hay (A) or of flaked maize and straw supplemented with decorticated groundnut meal (DCGM) (B), fishmeal (C), heated soya-bean meal (D) or raw soya-bean meal (E) or of dried grass (F). A cow with rumen and re-entrant duodenal cannulas was given diets of hay and dairy cubes. Some steers received doses of 32P-labelled inorganic phosphate twice daily with their concentrate feed. This led to small diurnal variations in inorganic P–32P specific activity but at similar daily sampling times the 32P specific activity in rumen bacterial nucleic acids reached a steady state after dosing for about 4 days. Contributions of microbial-N to non-ammonia-N (NA-N) entering the duodenum were then estimated by comparing nucleic acid 32P/NA-N ratios in related samples of rumen bacteria and duodenal contents. Similar estimates were made in these and other animals using α-, ε-diaminopimelic acid (DAP) and ribonucleic acid (RNA) as bacterial markers. Estimates for steers given diets A, B, C and F based upon ‘32P-labelled RNA nucleotides’ were, on average, 85% of those based upon total RNA. The differences were attributed mainly to the latter being elevated by the presence of small amounts of dietary RNA. When RNA-based estimates of the proportion of microbial-N in NA-N in duodenal contents for these and other steers which were nearly free of protozoa were multiplied by 0·85 (‘adjusted RNA’) the values were, on average, similar to those based upon DAP. Similar estimates for the cow based upon ‘adjusted RNA’ measurements were, however, about twice those based upon DAP, probably because the cow contained a high protozoal population and the DAP based, method did not account for protozoal N. For some steers total flows at the duodenum of organic matter (OM), microbial-N (mean based upon ‘adjusted RNA’ and DAP) and residual food N were estimated by reference to chromic oxide. Average values for g microbial-N synthesized/kg OM truly digested in the rumen for the different diets ranged from 15 to 22 (mean 20). Mean degradabilities of food N (residual food N at duodenum/N intake) were 0·57, 0·71, 0·71, 0·70 and 0·84 for diets A, B, C, D and E respectively. No differences between diets were significant at P < 0·05.
Enhancing Large Dam Safety Using IoT Technologies: A Case of a Smart Dam

This paper investigates how to transform a manual monitoring system into a smart environment using IoT technologies. Large dams are of huge importance as water reservoirs and potential energy sources primarily because of their use for electric energy generation. Monitoring and predicting dams' behavior are quite challenging. Due to a variety of limitations, environmental obstacles and dam system complexity, the application of RFID, Bluetooth, and IoT technologies has proven to be an adequate, affordable and reliable dam safety solution. This paper introduces a comprehensive model of dam safety management and monitoring based on pervasive technologies. The model described in this work has been applied within the large dam "Iron Gate 1", on the river Danube in the Republic of Serbia. The results show that the use of new technologies in the dam monitoring process can reduce human error and improve overall process.
MECHANISM OF HOST‐PLANT RECOGNITION

Recognition and preference of host plants involve the integration of a complex of neural and metabolic events. These include: the sensing and encoding characteristics of the sense organs, decoding mechanisms in the central nervous system, assessment of acrossfiber patterns and deterrent/stimulant ratios, pre‐ and post‐ingestion factors such as level of satiety, nutritional balance, and experiential factors such as induction and aversionlearning.
Fully Convolutional Network-based MultiTask Learning for Rectum and Rectal Cancer Segmentation

In this study, we present a fully automatic method to segment both rectum and rectal cancer based on Deep Neural Networks (DNNs) with axial T2-weighted Magnetic Resonance images. Clinically, the relative location between rectum and rectal cancer plays an important role in cancer treatment planning. Such a need motivates us to propose a fully convolutional architecture for Multi-Task Learning (MTL) to segment both rectum and rectal cancer. Moreover, we propose a bias-variance decomposition-based method which can visualize and assess regional robustness of the segmentation model. In addition, we also suggest a novel augmentation method which can improve the segmentation performance as well as reduce the training time. Overall, our proposed method is not only computationally efficient due to its fully convolutional nature but also outperforms the current state-of-the-art for rectal cancer segmentation. It also scores high accuracy in rectum segmentation without any prior study reported. Moreover, we conclude that supplementing rectum information benefits the rectal cancer segmentation model, especially in model variance.
Effects of food abundance and wind on the use of tree lines by an insectivorous bat, Pipistrellus pipistrellus

We tested the hypotheses that the distance bats fly from tree lines depend on food abundance and protection from wind. We monitored the activity of pipistrelle bats (Pipistrellus pipistrellus) and measured insect abundance and wind speed and direction at fixed distances up to 50 m from tree lines. We compared bat behaviour in different situations: with and without wind and with low and high insect abundances in adjacent open areas. In all situations, pipistrelle bats' activity decreased with increasing distance from the tree line. Within nights, we found no effect of wind speed on bat activity (sound recorded per 5 min) on the leeward side of the tree lines. Between nights, however, bats concentrated their activities closer to the tree lines at high wind speeds or angles of incidence of wind from 45° to 90°. A significant relationship between bat and insect abundances was found only when the tree line was bordered by insect-rich grassland. Since wind and insect abundance only partly explained the distances bats flew from tree lines, two alternative explanations, namely predator avoidance and the use of tree lines as acoustic landmarks, are discussed. Pipistrelle bats using a double row of trees as a commuting route at dusk flew mainly between the tree lines, regardless of insect abundance or wind speed. It is argued that predator avoidance explains this behaviour, being a constraint on movements of bats at relatively high light levels. At high wind speeds and angles of incidence greater than 45°, the proportion of pipistrelle bats commuting on the leeward side of the tree lines increased.
Will the Convention on Biological Diversity put an end to biological control

Will the Convention on Biological Diversity put an end to biological control? Under the Convention on Biological Diversity countries have sovereign rights over their genetic resources. Agreements governing the access to these resources and the sharing of the benefits arising from their use need to be established between involved parties. This also applies to species collected for potential use in biological control. Recent applications of access and benefit sharing principles have already made it difficult or impossible to collect and export natural enemies for biological control research in several countries. If such an approach is widely applied it would impede this very successful and environmentally safe pest management method based on the use of biological diversity. The International Organization for Biological Control of Noxious Animals and Plants has, therefore, created the "Com- mission on Biological Control and Access and Benefit Sharing". This commission is carrying out national and international activities to make clear how a benefit sharing regime might seriously frustrate the future of biological control. In addition, the IOBC Com- mission members published information on current regulations and perceptions concerning exploration for natural enemies and drafted some 30 case studies selected to illustrate a variety of points relevant to access and benefit sharing. In this article, we summarize our concern about the effects of access and benefit sharing systems on the future of biological control.