Miracle-dz/UniFAR-FTUs huggingface dataset:
Observational Quantification of Climatic and Human Influences on Vegetation Greening in China

This study attempts to quantify the relative contributions of vegetation greening in China due to climatic and human influences from multiple observational datasets. Satellite measured vegetation greenness, Normalized Difference Vegetation Index (NDVI), and relevant climate, land cover, and socioeconomic data since 1982 are analyzed using a multiple linear regression (MLR) method. A statistically significant positive trend of average growing-season (April–October) NDVI is found over more than 34% of the vegetated areas, mainly in North China, while significant decreases in NDVI are only seen in less than 5% of the areas. The relationships between vegetation and climate (temperature, precipitation, and radiation) vary by geographical location and vegetation type. We estimate the NDVI changes in association with the non-climatic effects by removing the climatic effects from the original NDVI time series using the MLR analysis. Our results indicate that land use change is the dominant factor driving the long-term changes in vegetation greenness. The significant greening in North China is due to the increase in crops, grasslands, and forests. The socioeconomic datasets provide consistent and supportive results for the non-climatic effects at the provincial level that afforestation and reduced fire events generally have a major contribution. This study provides a basis for quantifying the non-climatic effects due to possible human influences on the vegetation greening in China.
Topical prolyl hydroxylase domain‐2 silencing improves diabetic murine wound closure

Prolyl hydroxylase domain 2 (PHD2) has been implicated in several pathways of cell signaling, most notably in its regulation of hypoxia‐inducible factor (HIF)‐1α stability. In normoxia, PHD2 hydroxylates proline residues on HIF‐1α, rendering it inactive. However, in hypoxia, PHD2 is inactive, HIF‐1α is stabilized and downstream effectors such as vascular endothelial growth factor and fibroblast growth factor‐2 are produced to promote angiogenesis. In the present study we utilize RNA interference to PHD2 to promote therapeutic angiogenesis in a diabetic wound model, presumably by the stabilization of HIF‐1α. Stented wounds were created on the dorsum of diabetic Lepr db/db mice. Mice were treated with PHD2 small interfering RNA (siRNA) or nonsense siRNA. Wounds were measured photometrically on days 0–28. Wounds were harvested for histology, protein, and RNA analysis. Diabetic wounds treated with siRNA closed within 21±1.2 days; sham‐treated closed in 28±1.5 days. By day 7, Western blot revealed near complete suppression of PHD protein and corresponding increased HIF‐1α. Angiogenic mediators vascular endothelial growth factor and fibroblast growth factor‐2 were elevated, corresponding to increased CD31 staining in the treated groups. siRNA‐mediated silencing of PHD2 increases HIF‐1α and several mediators of angiogenesis. This corresponded to improved time to closure in diabetic wounds compared with sham‐treated wounds. These findings suggest that impaired wound healing in diabetes can be ameliorated with therapeutic angiogenesis.
Hippocampal plasticity in Alzheimer's disease: changes in highly polysialylated NCAM immunoreactivity in the hippocampal formation

The highly polysialylated neural cell adhesion molecule (PSA‐NCAM) is one of the most promising molecules that contributes to plasticity in the central nervous system. We evaluated PSA‐NCAM immunoreactivity in the hippocampal formation of Alzheimer's disease (AD) patients. We found significant increases over control levels in the optical density ratios of PSA‐NCAM immunoreactivity in the outer molecular layer/granule cell layer (ODoml/grl) and in the inner molecular layer/granule cell layer (ODiml/grl) in the dentate gyrus of AD patients. The optical density of the granule cell layer in the dentate gyrus did not differ significantly between AD patients and control subjects. However, the number of PSA‐NCAM‐immunopositive infragranule cells was higher in the AD group compared with control subjects. The major finding in the CA1, subiculum and entorhinal cortex of AD patients was the disorganization of PSA‐NCAM‐immunoreactive fibres. These results indicate that neuronal remodelling occurs, especially in the dentate gyrus of patients with AD.
A Delay Reduction Multicast Routing Protocol for Group-shared Ad Hoc Network

Mobile ad hoc network is a wireless mobile network that does not have any base station or other central control infrastructures. Design of efficient multicast routing protocols in such networks is challenging. Shared tree routing protocol is a widely used multicast routing protocol in ad hoc network. However, it has problems encountered in end-to-end delay. In this paper we have proposed a protocol as an extension of the existing multicast Ad hoc On-demand Distance Vector (MAODV) routing to improve the inherent problem of large end-to-end delay in shared tree method. Our protocol is referred to as Delay reduction multicast routing protocol (DRMRP). The protocol uses n-hop local ring search to establish new forwarding path and limit the scope of flooding. With this mechanism simulation results demonstrate excellent reduction of average end-to-end delay as well as high packet delivery ratio.
The COST278 broadcast news segmentation and speaker clustering evaluation - overview, methodology, systems, results

This paper describes a large scale experiment in which eight research institutions have tested their audio partitioning and labeling algorithms on the same data, a multi-lingual database of news broadcasts, using the same evaluation tools and protocols. The experiments have provide more insight in the cross-lingual robustness of the methods and they have demonstrated that by further collaborating in thedomains of speaker change detection and speaker clustering it should be possible to achieve further technological progress in the near future.
Broadband Circularly Polarized Slot Antenna Array Fed by Asymmetric CPW for L-Band Applications

A novel broadband circularly polarized (CP) slot antenna array fed by asymmetric coplanar waveguide (CPW) with an inverted L-shaped strip for L-band applications is proposed. Broadband CP is obtained by an array composed of elliptically polarized elements using sequential rotation feed technique. Experimental results show that the VSWR les 1.5 impedance bandwidth and the 3-dB axial ratio bandwidth can be greatly raised to be as high as 52% (1.151.95 GHz) and 49% (1.151.9 GHz), respectively. The proposed antenna can provide a peak antenna gain of about 8 dBi at 1.5 GHz, with gain variations less than 1.5 dB for frequencies within the CP bandwidth. Good agreement is observed between simulation and measurement.
Modeling and decision making in spatio-temporal processes for environmental surveillance

The need for efficient monitoring of spatio-temporal dynamics in large environmental surveillance applications motivates the use of robotic sensors to achieve sufficient spatial and temporal coverage. A common approach in machine learning to model spatial dynamics is to use the nonparametric Bayesian framework known as Gaussian Processes (GPs) (c.f., [1]) which are fully specified by a mean and a covariance function. However, defining suitable covariance functions that are able to appropriately model complex space-time dependencies in the environment is a challenging task. In this paper, we develop a generic approach for constructing several classes of covariance functions for spatio-temporal GP modeling. The GP models are then extended to perform efficient path planning in continuous space while maximizing the information gain. Extensive empirical evaluation for the different classes of covariance functions using real world sensing datasets is discussed, including experiments on a tethered robotic system - Networked Info Mechanical System (NIMS).
A survey on trust in Internet of Things

Internet of Things (IoT) brings a new paradigm of ‘talking’ sensors or objects with the help of the Internet. Important data from objects are sent for mining or processing purpose into critical information. Internet makes the data vulnerable to the threat of attacks, so some secure ways are needed to secure the data communications process. Restriction access only to certain trustable objects can also be an alternative solution for mitigating attacks. In this paper we made a literature survey on trust in the area of IoT. Furthermore, some research challenges that can be developed with the topic of trust in the IoT area also described.
Simulation of Path Planning of Mobile Robot in Dynamic Environment

Path planning of a robot [1] is a problem in which a problem space or a problem domain with a number of obstacles is given and the aim is to find a collision free path which a robot can follow in order to reach its destination from the start position. Here in this paper environment is represented by ordered grids, each of which represents a location in the mobile robot movement space. Along with this we would be able to place dynamic no. of static and movable obstacles at run time. The boundary of obstacles is formed by their actual boundary plus minimum safety distance considering the size of the mobile robot, which makes it possible to treat the mobile robot a point in the environment. The path [2] which the robot will follow is desired to be optimal in terms of distance and time taken by the robot to reach the destination. Here in this problem we have used Genetic Algorithm for path planning which is a search algorithm based on the mechanics of natural selection and natural genetics. Potential solutions of a problem are chromosomes, which form a population of possible solutions which compete with each other on the basis of fitness function. A selection mechanism based on the fitness is applied to the population and the individuals strive for the survival.
Nonthermal Influences on Mg/Ca in Planktonic Foraminifera: A Review of Culture Studies and Application to the Last Glacial Maximum

Planktonic foraminiferal Mg/Ca is one of the most widely applied sea surface temperature proxies. While the influence of salinity on Mg/Ca has led the accuracy of Mg/Ca‐temperatures to be questioned, the effect of seawater carbonate chemistry (pH) is seldom accounted for down‐core. Using published data sets, we review controls on Mg/Ca in laboratory cultures of planktonic foraminifera Globigerinoides ruber (white), Trilobatus sacculifer, Globigerina bulloides, and Orbulina universa. All are characterized by a temperature sensitivity of ~6% per °C and a salinity sensitivity of ~4% per salinity unit; all except T. sacculifer are sensitive to carbonate chemistry (−5 to −9% per 0.1 pH units). We demonstrate the down‐core manifestation of these sensitivities using data spanning the last deglaciation and an Earth System Model forced with last glacial maximum conditions. While the effects of salinity are relatively minor, seawater carbonate chemistry exerts a large bias on Mg/Ca temperature if unaccounted for; however, as local pH changes beyond the effect of atmospheric CO2 are relatively small across most of the ocean (less than ±0.05 pH units, 2σ), atmospheric CO2 can be used to accurately correct Mg/Ca temperatures. We present protocols to correct Mg/Ca for pH down‐core using either atmospheric CO2 or (preferably) boron isotopes in a new software package “MgCaRB. ”
Mistrusting Companies, Mistrusting the Tobacco Industry: Clarifying the Context of Tobacco Prevention Efforts That Focus on the Tobacco Industry∗

Campaigns to prevent adolescent smoking increasingly depict the tobacco industry as deceitful and exploitative. This study was undertaken to determine how adolescents' expectations about the trustworthiness of companies, in general, influence the pathway through which anti-tobacco industry campaigns prevent smoking. Structural equation modeling was used with survey data from 6,670 adolescents, ages 12 to 17. In the first model, statistically significant coefficients were associated with paths from mistrust of companies to mistrust of the tobacco industry, from mistrust of the tobacco industry to anti-tobacco industry attitudes, and from anti-tobacco industry attitudes to smoking. In models stratified by mistrust of companies, paths from mistrust of the tobacco industry to anti-tobacco industry attitudes and from anti-tobacco industry attitudes to smoking appeared comparable among youth with both high and low mistrust of companies. These results suggest that anti-tobacco industry campaigns resonate with youth because of youths' trust-related values and expectations.
Air-water gas exchange : mechanisms governing the combined effects of wind and rain on the gas transfer velocity and field measurements in a eutrophic region of the Everglades of the effects of wind

Air-water gas exchange is an important process in many biogeochemical cycles, including the global carbon cycle. Quantifying the movement of gases across the air-water interface is important to understand cycling on global and regional scales, to constrain the magnitude of the oceanic source or sink of biologically and climatically important trace gases, and to study local ecosystem dynamics. Although our knowledge of the mechanisms driving gas exchange due to individual processes, such as wind or rain, has improved greatly over the past few decades, there are regions where multiple processes may be significant in determining rates of gas exchange, and questions remain regarding the combined effects on the gas transfer velocity. Additionally, while many field studies have been conducted to measure gas exchange in a variety of environments, including lakes and wetlands, and to parameterize the gas transfer velocity in terms of its governing mechanisms and driving forces, the applicability of these parameterizations has not yet been established for all systems. In the first study presented here, the mechanisms responsible for gas exchange under conditions of wind and rain were studied in the laboratory and quantified. Measured variables included turbulent kinetic energy, bubble formation frequency, wave slope, wind speed profiles and raindrop impact velocity, allowing calculation of the kinetic energy flux due to wind and rain. It was determined that the impact of rain on air-water gas exchange is significantly reduced at elevated wind speeds (12 20 m s in this study). While this result differs quantitatively from two previous studies at the same facility, the findings can all be described by a model for gas exchange in which the gas transfer velocity depends on wind speed, u10, and the excess mixing of rain beyond a critical depth of dissipation of TKE due to wind. This mixing is accounted for by taking into account depth scales relevant to rain and wind, zR and zu, which are assumed to scale by the kinetic energy fluxes of rain and wind, respectively. The parameterization k600 = au 2 10 + b(KEFrain − cKEFwind) describes the results from each of the two previous studies as well as the present study. While this model predicts that the effect of rain would be negligible in high-wind, low-rain regions of the oceans such as the Southern Ocean, rain may be very important to take into account in regions with characteristically high rain rates and low wind speeds.
A Compact Equivalent Circuit Model of HVLDMOS and Application in HIVC Design

In this paper, a novel equivalent circuit of high voltage LDMOS is presented, which can be embedded into SPICE and applied in high voltage integrated circuits design. Compared with the conventional circuit models of LDMOS, this model does not divide the on-state region of LDMOS into a linear region and a saturation region. Consequently, the formulas for the circuit model contain fewer parameters easily extracted. This paper first creates an I-V equation which is not only available in the on-state region but also suitable to the sub-threshold region based on numerical simulation, and then we obtain a very simple equivalent circuit. The method of parameters extraction in the model is also offered in details. In the end we give an application of designing a CMOS inverter and verify it by MEDICI
Evaluation of the economic impact of geographical indications : three case studies

Cette these evalue l'impact economique des politiques de qualite liee a l'origine en mobilisant des methodes d'evaluation que nous adaptons a la specificite des demarches de certification, notamment a leur dimension spatiale. Dans un premier temps, nous analysons l'effet de l'adoption d’une Appellation d’Origine Protegee (AOP) sur le prix ainsi que sur les couts de production des producteurs de lait AOP en Franche-Comte, en exploitant la discontinuite geographique a la frontiere (Geographic Regression Discontinuity). Dans un second temps, nous utilisons les methodes d'appariement statistique pour analyser les heterogeneites regionales en termes de prix et de couts de production entre les regions Auvergne, Rhone-Alpes et Franche-Comte avant de nous interesser aux effets a une echelle nationale. Enfin, nous evaluons l'effet de l'adoption d'une Indication Geographique Protegee (IGP) sur les prix payes aux producteurs de Cafe de Colombie a l'aide des methodes comparatives (synthetic control methods). En moyenne, les resultats montrent un effet positif de l'adoption de l'indication geographique sur la performance economique des exploitations. Cependant, cet effet est heterogene entre les filieres et les regions d'origine des produits.
The Performance of Subspace Algorithm Cointegration Analysis: A Simulation Study

This paper presents a simulation study that assesses the finite sample performance of the subspace algorithm cointegration analysis developed in Bauer und Wagner (2002b). The method is formulated in the state space framework, which is equivalent to the VARMA framework, in a sense made precise in the paper. This implies applicability to VARMA processes. The paper proposes and compares six different tests for the cointegrating rank. The simulations investigate four issues: the order estimation, the size performance of the proposed tests, the accuracy of the estimation of the cointegrating space and the forecasting performance. of the state space models estimated by the proposed method. The simulations are performed on a set of trivariate processes with cointegrating ranks ranging from zero to three as well as on processes of output dimension four and cointegrating rank two. We analyze the influence of the sample size on the results as well as the sensitivity of the results with respect to stable poles approaching the unit circle. All results are compared to benchmark results obtained by applying the Johansen procedure on VAR models fitted to the data. The simulations show advantages of subspace algorithm cointegration analysis for the small sample performance of the tests for the cointegrating rank in many cases. However, we find that the accuracy of the subspace algorithm based estimation of the cointegrating space is unsatisfactory for the four-dimensional simulated systems. The forecasting performance is grosso modo comparable to the results obtained by applying the Johansen methodology on VAR approximations, although for very small sample sizes the forecasts based on VAR approximations outperform the subspace forecasts. The appendix provides critical values for the test statistics
Scenario analysis of pollutants loads to European regional seas for the year 2020. Part I: Policy options and alternative measures to mitigate land based emission of nutrients

A spatially explicit statistical approach (GREEN model) applied to continental Europe on a sub-catchment basis, is used to link input from anthropogenic activities and nutrient loads into European Seas (namely nitrogen and phosphorous). Effectiveness of environmental legislation is assessed at the horizon 2020, emphasizing the regional differences between European countries as well as the respective contribution of anthropogenic changes and hydrological fluctuation in nutrient exports. The set of scenarios analyzed includes a business as usual situation, a full implementation of on going policy options, a change in European diet based on a strong reduction of meat intake, and optimized management of agricultural practices. All prospective analyses are implemented for EU-27 and are discussed in terms of capacities to mitigate land based emissions of nutrient, and also according to their impacts on the loads of nutrient exported to European coastal areas. How to obtain EU publications Our priced publications are available from EU Bookshop (http://bookshop.europa.eu), where you can place an order with the sales agent of your choice. The Publications Office has a worldwide network of sales agents. You can obtain their contact details by sending a fax to (352) 29 29-42758. The mission of the JRC is to provide customer-driven scientific and technical support for the conception, development, implementation and monitoring of EU policies. As a service of the European Commission, the JRC functions as a reference centre of science and technology for the Union. Close to the policy-making process, it serves the common interest of the Member States, while being independent of special interests, whether private or national. LB -N A -2 5 1 5 9 EN -N
Effective label acquisition for collective classification

Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes. A variety of techniques have been introduced and methods that combine attribute information and neighboring label information have been shown to be effective for collective labeling of the nodes in a network. However, in part because of the correlation between node labels that the techniques exploit, it is easy to find cases in which, once a misclassification is made, incorrect information propagates throughout the network. This problem can be mitigated if the system is allowed to judiciously acquire the labels for a small number of nodes. Unfortunately, under relatively general assumptions, determining the optimal set of labels to acquire is intractable. Here we propose an acquisition method that learns the cases when a given collective classification algorithm makes mistakes, and suggests acquisitions to correct those mistakes. We empirically show on both real and synthetic datasets that this method significantly outperforms a greedy approximate inference approach, a viral marketing approach, and approaches based on network structural measures such as node degree and network clustering. In addition to significantly improving accuracy with just a small amount of labeled data, our method is tractable on large networks.
A comparison of search-based planners for a legged robot

Path planning for multi-DoF legged robots is a challenging task due to the high dimensionality and complexity of the planning space. We present our first attempt to build a path planning framework for the hydraulic quadruped - HyQ. Our approach adopts a similar strategy to [1], where planning is divided into a task-space and a joint-space part. The task-space planner finds a path for the center of gravity (COG) of the robot, while then the footstep planner generates the appropriate footholds under reachability and stability criteria. Next the joint-space planner translates the task-space COG trajectories into robot joint angles. We present a comparison of a set of search-based planning algorithms; Dijkstra, A* and ARA*, and evaluate these over a set of given terrains and a number of varying start and end points. All test runs support that our approach is a simple yet robust solution. We report comparisons in path length, computation time, and path cost, between the aforementioned planning algorithms.