Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding migrant selection : the case of Poland

In this paper I study the selection of emigrants from Poland in two destination countries, UK and Germany. I use unique dataset from the country of origin that allows me to use pre-migration information to analyse the selection of emigrants with respect to the non-emigrant population. In addition to the pre-migration labour market data, I also know the destination country for each individual from the same dataset. I link this piece of information with data from the destination country. I compare wages of emigrants to the United Kingdom and Germany with wages of non-emigrants in Poland and account for unobservable selection. Using the Roy's 1951 model, adapted to migration selection in Borjas (1987), as a theoretical framework for my analysis, I test for selection by using both observable (education) and unobservable (wage residuals) skills. While I nd positive selection in terms of education for Polish emigrants to the UK (against the model's predictions as the return to observable skills is higher in Poland), in terms of unobserved characteristics they are more likely to be negatively selected (consistent with the model's prediction). For emigrants to Germany the empirical evidence is not in favour of the Roy model for both unobserved and observed characteristics, as selection is likely to be the result of immigration policies. *University College London and NIESR. Contact details: a.rosso@niesr.ac. uk. I am grateful to Christian Dustmann, Ian Preston for support and guidance throughout this project. I thank Iga Magda for her invaluable help with the data, Uta Schoenberg, Tommaso Frattini, Anna Raute, Luigi Minale, Jan Stuhler, Marco Alfano, Lucia Corno, Thomas Cornelissen for their helpful feedback. I thank participants to the 4th Norface Migration Network Conference on "Migration: Global Development, New Frontiers" for their comments and suggestions. All errors are my own.
Genetic structure of a raccoon population ( Procyon lotor ) in Müritz National Park – a result of landscape resistance or space-use behaviour ?

Understanding the mechanisms shaping the genetic population structure is important for addressing many questions in evolution, ecology, and practical wildlife management (e.g., EPPS et al. 2007, SEGELBACHER et al. 2010). Current studies often focus on testing for landscapegenetic relationships, because the heterogeneity of the environment can infl uence the occurrence, abundance, dispersal, and thus, gene fl ow, in plants and animals (MANEL et al. 2003, HOLDEREGGER & WAGNER 2008). Among the most popular approaches for such studies is the statistical comparison of genetic and ‘effective’ landscape distances. While the genetic distances measure how close individual animals are genetically, the effective distances estimate how close they are in the landscape, while accounting for potential movement barriers or varying landscape resistances to gene fl ow. If a signifi cant association is found between these two distances, it is concluded that landscape resistance, as estimated from the effective distances, infl uences gene fl ow and resulting genetic structures. NIKO BALKENHOL, Berlin; BERIT A. KÖHNEMANN, Tharandt; SUSANNE GRAMLICH, Landau; FRANK-UWE MICHLER, Tharandt
B to C Ecommerce Websites ’ Success Factors in the Indian Context

Business to consumer electronic commerce is witnessing tremendous growth in the Indian market. As the adoption of online shopping increases, it is vital for e-retailers to understand the factors that drive an ecommerce website’s success. In this study, a survey was conducted among 252 online shoppers to explore the key factors that were associated with an ecommerce website’s success in the Indian context. Eight factors, site usage experience, service quality, delivery, reputation and size of the store, security & privacy, information quality & accessibility, attractive prices and multiple payment options, were identified through exploratory factor analysis. In addition, discriminant analysis carried out to assess the differences between more and less frequent shoppers showed that site usage experience, information quality & accessibility and multiple payment options were considered more important by more frequent shoppers.
Assessment of sunflower yield maps and discrimination of late-season weed patches by using field spectroradiometry and remote sensing : the case of Ridolfia segetum Moris

Weed control strategies are commonly applied over the entire agricultural fields, although weeds are spatially distributed in patches. To reduce the consumption of herbicides applying them only where weed patches are present, it is necessary to develop accurate maps of weed patches. These weed maps can be obtained in late-season through high spatial resolution remote sensing and can be used for site-specific control next season. This is especially helpful taken into account that most weeds are stable in time and location. The main objective of this contribution is to describe the remote sensing requirements for predicting yield and mapping weeds, and to outline some results of our group in this research area by explaining the case study of R. segetum in sunflower. We have chosen this weed as it is one of the most widely distributed, hard to control and competitive broadleaf weeds in sunflower.
A dynamic model of HIV transmission for evaluation of the costs and benefits of vaccine programs

We developed a dynamic model of HIV transmission to evaluate the costs and benefits of HIV vaccine programs in a population of homosexual men. We examined how changes in high-risk sexual behavior and the growth pattern of the epidemic influence the cost effectiveness of preventive vaccines, which prevent infection in uninfected people, and of therapeutic vaccines, which delay the onset of symptoms in HIV-infected people. We found that the effect of reductions in condom use are more important for therapeutic vaccines than for preventive vaccines, even if the preventive vaccines are imperfect. Therapeutic vaccines may increase HIV seroprevalence in the population, unless the vaccine program is accompanied by increased condom use. Epidemic growth patterns also influence the cost effectiveness of both preventive and therapeutic vaccines, but the effects are more pronounced for preventive vaccines. Preventive vaccines that are cost effective in a late-stage epidemic are even more cost effective— or even cost saving—in an early-stage epidemic.
Segmentation of Lung Images using Region Based Neural Networks

In this article, a neural network-basedsegmentation approach for CT lung images was proposedusingthe combination of Neural Networks and region growing which combines the regions of different pixels. The proposed approachexpresses a method for segmenting the lung region from lung Computer Tomography (CT)images.This method is proposed to obtain an optimal segmented region.The first step begins by the process of finding the areawhich represents the lung region. In order to achieve this, the regions of all the pixel present in the entire image is grown. Second step is, thegrown region values are given as input to the Echo state neural networks inorder to obtain the segmented lung region. The proposed algorithm is trained and testedfor1,361CT lungslicesfor the process of evaluating segmentation accuracy. Anaverageof 98.50% is obtained as the segmentation accuracy for the inputlung CT images
Classification and Detection of Plant Disease using Feature Extraction Methods

Today scientific knowledge relentlessly bringing change and comfort in day to day life. With this goal in mind plant disease identification and management is projected in carried work to prevent the plants from many diseases. Every country has prominent place for agricultural productivity and hence it is required to take care of plants for the sustainable growth of the country. To detect plant diseases Image processing steps are used to extract features from the images of plant leaves. The images are classified to define the disease detected through Graphical user interface (GUI) and it also calculates the affected region and it is shown as percentage of disease detection. The algorithms used are K-means clustering and Support vector machine for comparison and percentage of disease detection. The analysis of the work is carried through objective values such as mean, Entropy, variance, kurtosis, skewness, contrast and homogeneity. However contrast enhancement is also done for low intensity images. The resultant values are future enhanced with a hardware placed to monitor the status and update the information in Internet of things (IOT) for effective management of the plant disease detection.
Adaptive Filtration of Parameters of the UAV Movement Based on the TDOA-Measurement Sensor Networks

In modern conditions unmanned aerial vehicles (UAVs) generate new classes of threats, including their use for terrorist purposes. A feature of modern UAVs is the ability to perform sudden maneuvers and to keep the same position in the point in space. For the description of the UAV movement with various types of maneuver it is used a rectangular coordinate system. We use the model in the form of stochastic dynamic system with random structure in the discrete time in which the change type UAV movement occurs at random times. When a UAV emits a sign, its location can be determined by wireless sensor networks (WSN) using the TDOA method. On the basis of a mathematical apparatus of the mixed Markov processes for in discrete time optimal and quasi-optimal adaptive algorithms for filtration of UAV movement parameters based on the TDOA-measurement, sensor networks are synthesized. Devices that realize these algorithms are multichannel and belong to the class of devices with feedback between channels. At the same time, in a quasi-optimal algorithm, a sequential procedure of the arriving measurements from sensors of a sensor network is realized, which allows to avoid the inversion of large-dimensional matrices. An analysis of the quasi-optimal adaptive algorithm is performed using statistical modeling. On the intervals of hovering and of the UAV movements without maneuver, the developed algorithm allows to increase significantly the accuracy of the estimation of the UAV coordinates, and also to recognize various types of its movement with high probability level.
Survey on DDoS defense mechanisms

It is a prominent attack used by the attackers to cripple an online service. The method of implementation can either be from a single source or a list of common users (zombie army) who are modulated from the command centers. Hence, in the latter case, they are called denial‐of‐service attacks. A substantial amount of distributed users has malware software that turns all these systems into bots without the user's consent. This aspect adds more to the complexity of detecting the attacker who is well masqueraded. These serve as a severe problem for Internet services and the network. It is mandatory to distinguish between a legitimate and a malicious user. There are many defense mechanisms that combat these types of attacks. This presentation mainly highlights the details of denial‐of‐service attacks and their various mechanisms and types and compares studies on different mechanisms that have been proposed. Finally, this gives an insight into future prospects in the research field for secured Internet services.
Analysis of the interaction of an electron with radial electric fields in the presence of a disclination

We consider an elastic medium with a disclination and investigate the topological effects on the interaction of a spinless electron with radial electric fields through the WKB (Wentzel, Kramers, Brillouin) approximation. We show how the centrifugal term of the radial equation must be modified due to the influence of the topological defect in order that the WKB approximation can be valid. Then, we search for bound states solutions from the interaction of a spinless electron with the electric field produced by this linear distribution of electric charges. In addition, we search for bound states solutions from the interaction of a spinless electron with radial electric field produced by uniform electric charge distribution inside a long non-conductor cylinder.
Multi-Principal Multi-Agent Contract Design: Theory and Application to Device-to-Device Communications

How to stimulate the devices to participate is a key problem in the device-to-device (D2D) communications, especially when there are multiple base stations in practice. On one hand, the base station needs to lower the price to compete with other base stations for attracting more devices. On the other hand, the base station needs to increase the price to obtain more benefit. In this paper, we propose an optimal multiprincipal multiagent contract design to tackle such a challenge. Specifically, we formulate the multiprincipal contract design problem as a game theoretic optimization problem, where the objective of each principle (base station) through contract design is to maximize its overall utility obtaining from the trade with agents (devices) subject to the individual rationality and incentive compatibility constraints. By solving the game theoretic optimization problems, we can obtain the equilibrium contract where the contracts of different principals reach an equilibrium and any deviation from a single principal will lead to the degradation of its own utility. Moreover, under the equilibrium, both the individual rationality and incentive compatibility constraints are satisfied, i.e., all agents will choose the corresponding contract according to their types to reach the optimal nonnegative utilities. Simulation results show that compared with the monoprincipal contract design, both the utilities of devices and the social welfare can be improved with the multiprincipal contract design.
Natural Occurrence and Distribution of Arbuscular Mycorrhizal Fungi : A Review

Arbuscular mycorrhizal (AM) association constitutes an important component of soil microbial community belongs to the fungal phylum Glomeromycota. They improve plant growth, nutrient uptake, promote plant diversity, help in rehabilitation and reclamation of waste land, biohardening, phytoremediation, soil aggregation and also help to control plant pathogens. Their diversity and composition vary among different habitat of the globe. They occur in a wide spectrum of agricultural crops, most shrubs, tropical tree species and some temperate tree species. It has been found in some gymnosperms, pteridophytes, bryophytes and in some floating and submerged aquatic plants. It is important to study biodiversity of such beneficial fungi from efficient utilization and conservation point of view.
Canadian Water Quality Guidelines for the Protection of Aquatic Life-Diisopropanolamine

DIPA (C6H15NO2; CAS 110-97-4) is used in a number of commercial, industrial, and household applications. It is known under a variety of synonyms, including bis(2hydroxypropyl)amine, 1,1’-iminobis(2-propanol) and 1,1’iminodipropan-2-ol. It has a molecular weight of 133.19 g·mol, a density of 0.989 g·cm at 25°C, an aqueous solubility of 870,000 mg·L at 25°C, a mean Kd in aquifer materials of 2.2 L·kg, a vapour pressure at 42°C of 2.7 x 10 kPa, and a Henry’s law constant of 1.72 x 10 atm·m·mol.
Quantifying Infra-Marginality and Its Trade-off with Group Fairness

In critical decision-making scenarios, optimizing accuracy can lead to a biased classifier, hence past work recommends enforcing group-based fairness metrics in addition to maximizing accuracy. However, doing so exposes the classifier to another kind of bias called infra-marginality. This refers to individual-level bias where some individuals/subgroups can be worse off than under simply optimizing for accuracy. For instance, a classifier implementing race-based parity may significantly disadvantage women of the advantaged race. To quantify this bias, we propose a general notion of $\eta$-infra-marginality that can be used to evaluate the extent of this bias. We prove theoretically that, unlike other fairness metrics, infra-marginality does not have a trade-off with accuracy: high accuracy directly leads to low infra-marginality. This observation is confirmed through empirical analysis on multiple simulated and real-world datasets. Further, we find that maximizing group fairness often increases infra-marginality, suggesting the consideration of both group-level fairness and individual-level infra-marginality. However, measuring infra-marginality requires knowledge of the true distribution of individual-level outcomes correctly and explicitly. We propose a practical method to measure infra-marginality, and a simple algorithm to maximize group-wise accuracy and avoid infra-marginality.
Measurement of Large-Signal COSS and COSS Losses of Transistors Based on Nonlinear Resonance

In this letter, we present a new measurement technique to evaluate the large-signal output capacitance (<italic>C</italic><sub>OSS</sub>) of transistors as well as the <italic>C</italic><sub>OSS</sub> energy dissipation (<italic>E</italic><sub>DISS</sub>), based on the nonlinear resonance between a known inductor and the output capacitance of the device under test. The method is simple and robust, and only requires a single voltage measurement to extract the large-signal <italic>C</italic><sub>OSS</sub> both in charging and discharging transients. By changing the circuit parameters, it is possible to tune the resonance frequency (even above 40 MHz) and the voltage swing (even above 1 kV) with d<italic>v</italic>/d<italic>t</italic> exceeding 100 V/ns, even though the method relies only on a low-voltage dc source, without the need for high-voltage RF amplifiers. The single-pulse operation of the method enables measuring <italic>C</italic><sub>OSS</sub> and <italic>E</italic><sub>DISS</sub> at very high frequency and d<italic>v</italic>/d<italic>t</italic> values without any thermal runaway. Using the proposed method, we extracted large-signal <italic>C</italic><sub>OSS</sub> and <italic>E</italic><sub>DISS</sub> of power transistors based on different semiconductor technologies. The obtained results were verified by Sawyer–Tower method and data reported in the literature. In particular, dv/dt-independent <italic>C</italic><sub>OSS</sub> losses were measured in cascode GaN transistors. The precise characterization of large-signal <italic>C</italic><sub>OSS</sub> of transistors presented in this letter is essential for the design of power converters, especially those operating at high switching frequencies.
5 Why terrorism terrifies us

Over the past decade, evolutionary scientists have provided many theoretical and practical insights to understanding the social dynamics and underlying motivations that foster terrorism. Several researchers have shown, for instance, that contrary to most criminological models of violent groups, such as gangs, the strongest predictors of terrorist recruitment are neither poverty nor lack of education (e.g. Atran, 2009; Hafez, 2009). Rather, would-be terrorists are often compelled by feelings of victimization and revenge on behalf of one’s kin, motivations that are likely “instinctual” and evolved to deter intergroup violence (see McCullough, 2008). Evolutionary perspectives have also complemented rational choice models of political violence by showing that seemingly irrational violent-behaviors, such as suicide bombings, are parochially altruistic (Ginges et al., 2009; Qirko, 2009; Victoroff, 2009). This means that terrorists can elicit suicide bombings from otherwise normal (i.e. nonpsychotic) recruits by promising benefits to their kin and manipulating cues of genetic relatedness among group members (Atran, 2004; 2012; Azam, 2005). Additionally, evolutionary scholars have shown that terrorist organizations do not use religion simply to brainwash recruits (vs., Harris, 2004), but to provide systematic organization for group activity. For religion aids in forming coalition identities (Graham & Haidt, 2010), strengthening cooperative bonds (Sosis & Alcorta, 2008; Sosis et al., 2012), and strengthening group commitments to extreme acts, including violence (Atran, 2003; Norenzayan & Shariff, 2008). Despite these insights, evolutionary scholars have rarely considered why terrorism terrifies us. At first glance, asking why we respond to terrorism as we do may seem like a trivial question, but it is not. Because exposure to violence influences reproductive decision-making (Wilson & Daly, 1997), migration (Knauft, 1987), and revenge (McCullough, 2008), terrorism must entail fitness consequences for survivors (Sharma, 2003). Furthermore, because exposure to terrorism results in approach and avoidance behaviors (e.g. increased anxieties, in-group identification, vigilance toward out-groups, etc.), which are evident in numerous communities after attacks (e.g. Fischer
What People Know and Do Not Know About Nutrition

The tremendous growth in scientific knowledge of the relationship between diet and health has been integrated into current dietary recommendations and sparked national campaigns to educate Americans on healthier eating habits. In this chapter, we look at how much the typical American knows about nutrition, whether the average level of nutrition knowledge has increased, and what implications this has for changing eating habits.
A BIOSYNTHESIS METHOD TO PRODUCE RESVERATROL IN SACCHAROMYCES CEREVISIAE WITH SECRETION EXPRESSION OF GRAPE ANTI-OXIDANT RESVERATROL SYNTHASE GENE DURING WINE FERMENTATION

Resveratrol (Res), a stilbenic compound, recently has become the focus of a number of studies in medicine and plant physiology, and Saccharomyces cerevisiae (S. cerevisiae) has become a popular host for production of non-native compounds. As the last and key enzyme of the biosynthesis pathway, the amount and expression level of Resveratrol Synthase (RS) positive correlation on the production of Res. In this study, a signal peptide sequence, secreted by α-factor of S. cerevisiae, was connected with the RS gene, resulting a pYCα secretory plasmid construction. The RS gene was secretory expressed in S. cerevisiae successfully. Subsequently, a white wine fermentation was carried out by the recombinant strain. The Res concentration of the white wine fermented by the recombinant strain was 36% higher than the control. This has great interests for establishing a controllable way to produce RS and lays the foundation for exploring the Res biosynthesis method.