Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental Economics for Sustainable Growth: A Handbook for Practitioners

Part 1 Introduction and structure: objectives of the book description of the chapters. Part 2 Sustainable development vision in a global context: the earliest definition of sustainable development economic dimension of sustainable development environmental sustainability social sustainability measures of strong and weak sustainability sustainable development vision in a political context integrating environment and development strategies and political economy. Part 3 Macroeconomic policies and the environment: macroeconomic policies and the environment tools and methods of macroeconomic analysis conclusions case studies. Part 4 An introduction to environmental management at the sectoral level: partial or sectoral market equilibrium consumer and producer surplus market failures policy and institutional failures shadow pricing environmental management principles conclusions case studies. Part 5 Policies, instruments and the environment: analytical tools optimality of private decisions environmental instruments instruments in practice lessons and conclusions to the chapter problem set solution to problem set. Part 6 Laws, regulations and institutions: legal system for environmental protection international legal instruments environmental laws environmental institutions conclusions annexes. Part 7 National environmental strategies (NES): past experience identifying and prioritizing problems defining priorities for action - diagnozing causes defining priorities for action - finding solutions plan implementation conclusions questions for discussion. Part 8 Economy-wide policies and the valuation of environmental impacts: the project cycle and environmental assessment appraisal of a project with environmental impacts step 1 - EA and the with-without analysis step 2 - financial and economic appraisal step 3 - shadow pricing for market failures step 4 - discount rate and comparison of costs and benefits step 5 - decision-making with participation conclusion. Part 9 Economic principles and overview of valuation methods: total economic value of an environmental asset basic concepts of valuation methods overview of valuation methods economics underlying valuation methods. Part 10 Revealed preferences - direct proxy methods: productivity change method (PCM) substitute cost method (SCM) case studies. Part 11 Revealed preference - indirect proxy methods: travel cost method hedonic price method (HPM) - the conceptual framework case studies. Part 12 Stated preference - contingent valuation methods: contingent valuation method - the conceptual framework CVM methodology numerical examples. Part 13 Use of monetary value of environmental and natural resources for benefit cost analysis - an application to a soil moisture conservation project in Tunisia: background methodology exercise - case study of the BCA for the Tunisia soil moisture conservation project solution set discussion. Part 14 Use of monetary values
ENDOGENOUS RECOMBINANT GROWTH

We extend Weitzman's (1998) recombinant growth framework to include endogenous RD the other attracts stagnating economies. Sustained growth depends on a condition relating the slopes of the characteristic curves as well as on a minimal endowment requirement. A growing economy reaches the turnpike at a most rapid R&D rate and evolves along it thereafter. In the long run, the rate of growth and the income shares devoted to R&D, saving and consumption approach constant values that depend on the asymptotic characteristic slopes.
Differential microRNA expression is associated with androgen receptor expression in breast cancer

The androgen receptor (AR) is frequently expressed in breast cancer; however, its prognostic value remains unclear. AR expression in breast cancer has been associated with improved outcomes in estrogen receptor (ER)-positive breast cancer compared with ER-negative disease. Eliminating AR function in breast cancer is critically important for breast cancer progression. However, the mechanism underlying AR regulation remains poorly understood. The study of microRNAs (miRNAs) has provided important insights into the pathogenesis of hormone-dependent cancer. To determine whether miRNAs function in the AR regulation of breast cancer, the present study performed miRNA expression profiling in AR-positive and -negative breast cancer cell lines. A total of 153 miRNAs were differentially expressed in AR-positive compared with AR-negative breast cancer cells; 52 were upregulated and 101 were downregulated. A number of these have been extensively associated with breast cancer cell functions, including proliferation, invasion and drug-resistance. Furthermore, through pathway enrichment analysis, signaling pathways associated with the prediction targets of the miRNAs were characterized, including the vascular endothelial growth factor and mammalian target of rapamycin signaling pathways. In conclusion, the results of the present study indicated that the expression of miRNAs may be involved in the mechanism underlying AR regulation of breast cancer, and may improve understanding of the role of AR in breast cancer.
Biologically active APRIL is secreted following intracellular processing in the Golgi apparatus by furin convertase

Tumor necrosis factor (TNF) ligand family members are synthesized as transmembrane proteins, and cleavage of the membrane‐anchored proteins from the cell surface is frequently observed. The TNF‐related ligands APRIL and BLyS and their cognate receptors BCMA/TACI form a two ligand/two receptor system that has been shown to participate in B‐ and T‐cell stimulation. In contrast to BLyS, which is known to be cleaved from the cell surface, we found that APRIL is processed intracellularly by furin convertase. Blockage of protein transport from the endoplasmic reticulum to the Golgi apparatus by Brefeldin A treatment abrogated APRIL processing, whereas monensin, an inhibitor of post‐Golgi transport, did not interfere with cleavage of APRIL, but blocked secretion of processed APRIL. Thus, APRIL shows a unique maturation pathway among the TNF ligand family members, as it not detectable as a membrane‐anchored protein at the cell surface, but is processed in the Golgi apparatus prior to its secretion.
Molecular dynamics simulations of three protegrin-type antimicrobial peptides : interplay between charges at the termini , b-sheet structure and amphiphilic interactions

Molecular dynamics simulations of three protegrin-type antimicrobial peptides: interplay between charges at the termini,-sheet structure and amphiphilic interactions This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. Molecular dynamics simulations of three protegrin-type antimicrobial peptides: interplay between charges at the termini, b-sheet structure and amphiphilic interactions We have carried out molecular dynamics simulations of the naturally occurring protegrin PG-1 peptide and two of its mutants, PC-9 and PC-13 in the presence of a dodecyl-phosphocholine (DPC) micelle. The effects of mutations that disrupt the b-sheet structure in the case of PC-9 and reduce the charge at the C-terminus in the case of PC-13 are analyzed. It is found that the surface-bound conformations of the peptides are severely affected by both mutations. PG-1 exhibits a conformation in which the C-terminus and the b-hairpin turn interact strongly with the micelle lipid head groups, while its N-terminal strand bends away from the micelle and resides in the aqueous region; PC-13 exhibits strong interactions with the micelle at its N-terminus as well as the b-hairpin turn region, while retaining a much more compact conformation than PG-1; PC-9 achieves a highly distorted conformation relative to the homologous PG-1 structure, which allows both its termini and the b-hairpin region to interact with the micelle. These significant differences observed as a result of seemingly minor mutations to the sequences of the three peptides are explained in terms of the interplay between residue charges, structural rigidity and amphiphilic interactions. Conservative inferences are made bridging these biophysical interactions and the pharmacological profiles of the peptides.
Instant Quality Control of Large Batch Processing Jobs

The most common way to identify success or failure of a job running in a batch-processing mode is by examining a completion code sent by the job to the host operating system. Yet, for a variety of reasons the completion code may inaccurately indicate a successful termination of the job. This article describes a different approach to monitoring the quality of batch processing jobs while in operation. A pattern of behavior is suggested for a program. The pattern reflects ratios of consumption of various hardware resources. The ratios are determined by collecting historical performance variables of the job and analyzing the data by means of statistical methods. Once a pattern is ste, the performance variables of every individual run of the program are compared with the precalculated pattern of behavior and if the deviation is beyond certain limits an alarm is triggered.The proposed quality control technique has been tested on real applications, as well as on some artificial programs. The findings suggest that the technique is reliable in that it successfully distinguishes between proper and malfunctioning runs of a program.
What Rocks the Vote? Citizens' Views of Community Leaders and Political Engagement

OF THESIS WHAT ROCKS THE VOTE? CITIZENS’ VIEWS OF COMMUNITY LEADERS AND POLITICAL ENGAGEMENT Political engagement has an established body of research. However, one key area that has not been investigated in the field is the relationship between political engagement and type of community lived in. This study explores this relationship between type of community, past political engagement, perceptions of community leaders, attitude about political engagement, and socieodemographic characteristics. A conceptual model was developed based on existing literature. Utilizing a statewide survey conducted in 2009 that yielded 1,154 respondents with a response rate of 30.2% was used to explore these relationships. Using statistical procedures that test correlation were utilized to investigate the relationship between the key study variables. In addition, a regression model was created to be able to predict an individual’s political engagement. The result concluded that type of community does not significantly play a role in determining an individual’s political engagement. However other insights were revealed that showcase the complexity of political engagement and raise other questions about the role an individual’s attitude towards political engagement, and perception of community leaders affects their political engagement.
Statistical modeling of large distribution sets

In this paper we deal with a ubiquitous problem in data management: hierarchical model estimation for large distribution sets. This particular problem arises in many applications. Classification, top-k query processing, clustering and outlier detection are just a few possible applications. Our aim is to continuously and incrementally estimate the model parameters of 'typical' distributions that describe the characteristics of a database. Our approach to model estimation can handle arbitrary types of data (e.g., categorical and numerical data) in databases, incrementally, quickly, and with little resource consumption. Moreover, this paper proposes not only incremental algorithms for model fitting, but also a modeling framework in which the learning approach recognizes hierarchical groups, each of whose distributions has similar characteristics, and separately updates the model parameters of each group without scanning all the distributions in the database. Thus, it can provide a response, i.e., the parameters of typical distribution models, with an arbitrary level of granularity, at any time. Just as importantly, we demonstrate the utility of our approach by showing how it can be applied to two specific problems that arise in the context of data management.
Hate Speech and the Language of Racism in Latin America: A Lens for Reconsidering Global Hate Speech Restrictions and Legislation Models

In Latin America, like many countries in Europe, hate speech is prohibited. Yet, Latin America is rarely included in the transnational discussion regarding the regulation of hate speech. Instead, the discussion is captured by the binary comparisons between the advisability of Europe’s hate speech regulations as opposed to the United States free speech acceptance of hate speech. As a result, the ability to fundamentally examine the connections between hate speech and inequality, in addition to the most effective legal mechanisms for addressing it, are undermined. It is especially critical to broaden the hate speech debate now that we are seeing an apparent rise in the occurrence of hate speech worldwide. Expanding the transnational hate speech discussion to incorporate the Latin American context, can help to provide insights about which legal structures are pragmatically more effective. For persons of African-descent frequently subjected to the blows of racist hate speech in Latin America, there is little effective enforcement of the criminal law sanctions that predominate. In contrast, civil law remedies have shown greater success at responding to the harms of hate speech. This Article begins by presenting in Section I, the social science research regarding the harms of hate speech. Section II then examines the international law sanctions against hate speech and the ways in which they have inspired Latin American hate speech laws. The enforcement of the Latin American hate speech laws will then be assessed in Section III, and the Brazilian litigation regarding the “Look At Her Hair” song lyrics will be examined as a case study in Section IV. With the benefit of the Brazilian case study, the Article then concludes that the predominant criminal law approach is a poor vehicle for regulating hate speech. What is needed is a framework for civil remedies that is better formulated to address the harms of hate speech and its hindrance to racial equality.
The Technology of Nonviolence: Social Media and Violence Prevention

Tunisian and Egyptian protestors famously made use of social media to rally supporters and disseminate information as the "Arab Spring" began to unfold in 2010. Less well known, but with just as much potential to bring about social change, are ongoing local efforts to use social media and other forms of technology to prevent deadly outbreaks of violence. In The Technology of Nonviolence, Joseph Bock describes and documents technology-enhanced efforts to stop violence before it happens in Africa, Asia, and the United States. Once peacekeeping was the purview of international observers, but today local citizens take violence prevention into their own hands. These local approaches often involve technology--including the use of digital mapping, crowdsourcing, and mathematical pattern recognition to identify likely locations of violence--but, as Bock shows, technological advances are of little value unless they are used by a trained cadre of community organizers. After covering general concepts in violence prevention and describing technological approaches to tracking conflict and cooperation, Bock offers five case studies that range from "low-tech" interventions to prevent ethnic and religious violence in Ahmedebad, India, to an anti-gang initiative in Chicago that uses Second Life to train its "violence interrupters. " There is solid evidence of success, Bock concludes, but there is much to be discovered, developed, and, most important, implemented.
LNA – Active Bandpass Filter for Receiver-Indicator of Glonass + GPS

For the receiver-indicator of GLONASS+GPS a Low Noise Amplifier (LNA) with an integrated active bandpass filter has been developed. The LNA has the structure and characteristics of an active bandpass filter: NF = 1.2 dB in the frequency band from 1572 to 1612 MHz with the gain coefficient not less than 16 dB and off–band rejection at the frequencies of 1.4 GHz and 1.8 GHz of not less that 55 dB. The upper linearity boundary of IICP is equal to 7 dBm. The LNA has been produced by the hybrid integral technology. It has bulk dimensions of 22x 10x3 mm3 and is united with the receiving antenna into one functional module. Application of the LNA – active bandpass filter – allows one to increase considerably the interference immunity of the receiver-indicator of GLONASS+GPS.
Energy – Efficient MAC Protocol (EE-MAC Protocol)

-Because of the difficulty in recharging or replacing the batteries of each node in a Wireless Sensor Network, the energy efficiency of the system is a major issue in the area of network design. Other critical parameters such as delay, adaptability to traffic conditions, scalability, system fairness, and throughput and bandwidth utilization are mostly dealt as secondary objectives. Some sensor network applications adopt IEEE 802.11-like MAC protocol, which is however, not a good solution for sensor network applications because it suffers from energy inefficiency problem. The adaptive Sensor-MAC (S-MAC) proposes enhanced schemes such as periodic sleep and overhearing avoidance to provide a better choice for different sensor network applications. In this research paper we propose an energy efficient MAC (EE-MAC) protocol, which is based on adaptive S-MAC with added transmission power control techniques. The main contribution of our work is to introduce a controlled power transmission of RTS, CTS, DATA and ACK frames according to the adaptive S-MAC protocol. We simulate our proposed protocol i.e., EE-MAC protocol using ns-2.33 simulator for two parameters energy consumption and throughput, for determining the behavior of the proposed protocol. The simulation results show that our proposed EE-MAC protocol performs better than adaptive S-MAC protocol in terms of energy consumption and throughput.
Fast Outlier Detection Using a Grid-Based Algorithm

As one of data mining techniques, outlier detection aims to discover outlying observations that deviate substantially from the reminder of the data. Recently, the Local Outlier Factor (LOF) algorithm has been successfully applied to outlier detection. However, due to the computational complexity of the LOF algorithm, its application to large data with high dimension has been limited. The aim of this paper is to propose grid-based algorithm that reduces the computation time required by the LOF algorithm to determine the k-nearest neighbors. The algorithm divides the data spaces in to a smaller number of regions, called as a “grid”, and calculates the LOF value of each grid. To examine the effectiveness of the proposed method, several experiments incorporating different parameters were conducted. The proposed method demonstrated a significant computation time reduction with predictable and acceptable trade-off errors. Then, the proposed methodology was successfully applied to real database transaction logs of Korea Atomic Energy Research Institute. As a result, we show that for a very large dataset, the grid-LOF can be considered as an acceptable approximation for the original LOF. Moreover, it can also be effectively used for real-time outlier detection.
Adopting Data Mining Techniques on the Recommendations of Library Collections

In this research, the researchers explored not only the cluster of the readers with similar characteristics, but also the connection between the readers and the book collections of the library by using Data Mining techniques. By doing this, the library will be able to improve the interaction with its readers, and further increase the usage of library collections. The Modified Attribute-Oriented Induction (MAOI) method was introduced to deal with the multi-valued attribute table and further sort the readers into different clusters. Instead of using concept hierarchy and concept trees, MAOI method implemented the concept climbing and generalization of multi-valued attribute table with Boolean Algebra and modified Karnaugh Map, and described the clusters with concept description. On the other hand, the Chinese books in the library collections were classified into four groups with New Classification Science for Chinese Libraries (CCL). Not only the attributes of readers, but also the attributes of library collections borrowed by readers are included in the multi-valued attribute table. After the completion of induction, the reading preferences of the readers with the same characteristics can be learned.
Mexican Americans and the Mass Media

This book reports in detail the procedures and findings of project CASA (Communication and Spanish-Speaking Americans)--the most comprehensive, programmatic esearch effort to focus on Mexican-Americans and mass media. Media usage, access, credibility, gratifications, sources of information, and content preferences about a variety of media (from TV to comic books) were accessed. Focus group interviews with hispanic community leaders and with local newspaper publishers were also conducted, in addition to content and readability analyses of the local daily newspaper portrayals of Hispanics.
Provably Good 2D Shape Reconstruction from Unorganized Cross‐Sections

This paper deals with the reconstruction of 2‐dimensional geometric shapes from unorganized 1‐dimensional cross‐sections. We study the problem in its full generality following the approach of Boissonnat and Memari [ BM07 ] for the analogous 3D problem. We propose a new variant of this method and provide sampling conditions to guarantee that the output of the algorithm has the same topology as the original object and is close to it (for the Hausdorff distance).