Miracle-dz/UniFAR-FTUs huggingface dataset:
The Determinants of Local Leader Influence in Elections : A Lab-inthe-Field Experiment in Senegal ∗

The implications of clientelism for electoral accountability are mixed. Political intermediaries redistribute needed resources; they also exploit their position to advance personal interests. I argue that two dimensions determine the accountability of local leaders: competitive selection and autonomy of leaders from their community. Exploiting variation in local institutions, I situate this study in three types of communities in Senegal where leaders are known to be influential in political decisionmaking. A novel coordination game measures when and why communities vote for a leader-preferred outcome relative to an instrumentally-preferred one. I find that voters are more likely to sacrifice personal gain when leaders are more autonomous and uncompetitively selected. An experimental manipulation of the game emphasizing the anonymity of elections reveals that fear of sanctions motivates voters to follow their leader, but only in contexts with autonomous leaders. Conversely, anticipation of future reciprocity better explains why voters follow more dependent leaders. ∗I am grateful to the USAID-supported Conflict and Development Lab at Texas A&M University, the Scowcroft Institute, as well as the Program to Enhance Scholarly Activities and the Bush School at Texas A&M University for financial support for this project. UC Berkeley’s Center for Effective Global Action and Stanford’s Center for Democracy, Development and the Rule of Law provided support for the pilot phase. I thank Guy Grossman, James Fearon and members of Experiments on Government and Politics (EGAP) for invaluable advice on the research design. I also thank Eddy Malesky, Dominika Koter, Gina Reinhart, and participants of the Midwest Group on African Political Economy and the Program on International Conflict and Cooperation at Texas A&M for comments on this draft. I am indebted to Fodé Sarr, Kelsey Barrera, Susana Svojsik and Kwame Twumasi-Ankrah for superior research assistance and to Susana for additionally assisting with qualitative data analysis. All errors are my own. †The Bush School of Government & Public Service, Texas A&M University. jgottlieb@tamu.edu.
IP Fast Reroute

In this work, a new innovative Multicast Repair (M-REP) IPFRR mechanism, which uses an IP multicast technology, is presented. The proposed M-RER mechanism uses Protocol Independent Multicast Dense Mode (PIM-DM) with modified algorithm of the Reverse Path Forwarding (RPF). The key contribution of this work is the fact that the proposed M-REP IPFRR mechanism is independent of the link-state routing protocols and the internal algorithm does not explicitly calculate the alternative path.
Data Clustering with Principle Component for the Complete Must-Link Constraints

This research aims to develop an integrated method to solve a special constrained clustering problem constructed by Complete Must-Link (CML) constraints. Constrained clustering analysis is a semi-supervised learning to accommodate the information while it is available, to improve efficiency and purity of clustering. The CML clustering problem can be considered as aggregating pre-defined data groups. Through the transitive closure process of data aggregation, the data in each group are replaced by their centroid for clustering analysis. This causes information missing issue which means the data distribution or shape of the original groups are omitted, especially when the groups are intersected each other. In this research, a new method named CML-PCA is proposed for CML constrained clustering problem. The principal component analysis (PCA) which provides the supplemental information describing original partition blocks is suggested to be included in the distance matrix of the constrained clustering algorithm if they are intersected each other. The intersected ratio is invented to determine whether CML data partitions are intersected or not. The proposed algorithm is tested by using the simulated dataset and real-world data sets. From the experimental result, the proposed CML-PCA outperforms the traditional agglomerative clustering method when multiple validation indices were compared
Diffusion of Innovation and Capability Theory in the Context of E-Government

E-government (EG) enables governments to provide citizens easier and electronic access to information and modernized services through personal computers, kiosks, telephones, and other resources. Information and communication technology (ICT) is the prime driving force of EG. Therefore, before implementing an EG project, it is vital to investigate the capability of developing countries to adopt ICT and research the impact of adopting ICT in that society. The authors argue that the purposes of implementing EG can only be accomplished and the full benefits of EG realized if a majority of the population of developing countries has the ability to adopt ICT, the main driver of EG. Therefore, it is essential for policy makers of developing countries to study the adoption capability of ICT of citizens prior to launching EG. Otherwise, there is the strong possibility that EG projects could not accomplish the purpose of its implementation and could fail to reduce the digital divide, establish equal rights for all citizens, and promote good governance.
Technology shocks and the labour-input response : Evidence from firm-level data

We study the relationship between technology shocks and labor input on Swedish rm-level data using a production function approach to identify technology shocks. Taking standard steps yields a contractionary contemporaneous labor-input response in line with previous studies. This nding may, however, be driven by measurement errors in the labor-input variable. Relying on a unique feature of our data set, which contains two independently measured rm-speci c labor input measures, we can evaluate the potential bias. We do not nd any evidence supporting that this bias would conceal any true positive contemporaneous e¤ect. The results thus point away from standard exible-price models and towards models emphasizing rm-level rigidities. Keywords: Technology Shocks; Labor Input; Business Fluctuations; Micro Data JEL classi cations: C33; D24; E32 We would like to thank Malin Adolfson, Susanto Basu, Oskar Nordström-Skans and seminar participants at Sveriges Riksbank for useful comments and Björn Andersson and Magnus Lundin for help with preparing the data. Part of this project was conducted while Carlsson was visiting the Robert Schuman Center for Advanced Studies at the European University Institute, whose hospitality is much appreciated. Carlsson gratefully acknowledges nancial support from the Jan Wallander and Tom Hedelius Foundation. The views expressed in this paper are solely the responsibility of the authors and should not be interpreted as reecting the views of the Executive Board of Sveriges Riksbank. yCorresponding Author: Research Department, Sveriges Riksbank, SE 103 37 Stockholm, Sweden. E-mail: mikael.carlsson@riksbank.se. zDepartment of Economics, Uppsala University.
Monte Carlo modeling of spin injection through a Schottky barrier and spin transport in a semiconductor quantum well

We develop a Monte Carlo model to study injection of spin-polarized electrons through a Schottky barrier from a ferromagnetic metal contact into a nonmagnetic low-dimensional semiconductor structure. Both mechanisms of thermionic emission and tunneling injection are included in the model. Due to the barrier shape, the injected electrons are nonthermalized. Spin dynamics in the semiconductor heterostructure is controlled by the Rashba and Dresselhaus spin-orbit interactions and described by a single electron spin density matrix formalism. In addition to the linear term, the third-order term in momentum for the Dresselhaus interaction is included. Effect of the Schottky potential on the spin dynamics in a two-dimensional semiconductor device channel is studied. It is found that the injected current can maintain substantial spin polarization to a length scale in the order of 1μm at room temperature without external magnetic fields.
Nanocone Structures Enhancing Nitrogen-Vacancy Center Emissions in Diamonds

In this study, nitrogen-vacancy center emissions from nanocone structures fabricated on diamond surfaces by gold film annealing and inductively coupled plasma etching techniques were characterized. First, the diamond substate deposited with gold film was annealed to form a nano-sized dot mask. Second, through inductively coupled plasma etching, nanocone-shaped structures were fabricated using optimized gold dots as masks. Finally, the as-fabricated nanocone and planar structures were investigated with photoluminescence experiments at temperatures ranging from room temperature to 80 K, with the results showing approximately two-fold higher emission values for nitrogen-vacancy centers from nanocones.
Capturing Causal Complexity: Heuristics for Configurational Theorizing

Management scholars study phenomena marked by complex interdependencies among multiple explanatory factors that combine to bring about an outcome of interest. Yet, theorizing about causal complexity can prove challenging for the correlational theorizing that is predominant in the field of management, given its “net effects thinking” that emphasizes the unique contribution of individual explanatory factors. In contrast, configurational theories and thinking are well-suited to explaining causally complex phenomena. In this article, we seek to advance configurational theorizing by providing a model of the configurational theorizing process which consists of three iterative stages—scoping, linking and naming. In each stage, we develop and offer several heuristics aimed at stimulating configurational theorizing. That is, these theorizing heuristics are intended to help scholars discover configurations of explanatory factors, probe the connections among these factors, and articulate the orchestrating themes that underpin their coherence. We conclude with a discussion of how configurational theorizing advances theory development in the field of management and organizations, and beyond.
Ab initio modeling of the two-dimensional energy landscape of screw dislocations in bcc transition metals

A density functional theory (DFT) study of the 1/2� 111� screw dislocation was performed in the following body-centered cubic transition metals: V, Nb, Ta, Cr, Mo, W, and Fe. The energies of the easy, hard, and split core configurations,aswellasthepathwaysbetweenthem,wereinvestigatedandusedtogeneratethetwo-dimensional (2D) Peierls potential, i.e. the energy landscape seen by the dislocation as a function of its position in the (111) plane. In all investigated elements, the nondegenerate easy core is the minimum energy configuration, while the split core configuration, centered in the immediate vicinity of a � 111� atomic column, has a high energy near or above that of the hard core. This unexpected result yields 2D Peierls potentials very different from the usually assumed landscapes. The 2D Peierls potential in Fe differs from the other transition metals, with a monkey saddle instead of a local maximum located at the hard core. An estimation of the Peierls stress from the shape of the Peierls barrier is presented in all investigated metals. A strong group dependence of the core energy is also evidenced, related to the position of the Fermi level with respect to the minimum of the pseudogap of the electronic density of states.
Analysis of Omega-Gate Nanowire SOI MOSFET Under Analog Point of View

This paper presents an evaluation of omega-gate nanowire n- and p-type SOI MOSFETs performance focusing on the main analog figures of merit. The different channel widths (WNW) and channel lengths (L) were also evaluated. These devices presented values of subthreshold slope near the theoretical limit at room temperature (60 mV/dec) and in the worst case a DIBL value smaller than 70 mV/V showing its immunity to short channel effects (SCEs) in the range studied. The narrowest device showed great electrostatic coupling, improving transconductance (gm), presenting an unit gain frequency over 200 GHz and intrinsic voltage gain over 80 dB. These values suggests that this device is capable of achieving good performance on new applications such as 5G communications and Internet-of-Things (IoT).
The mechanics of hearing: a comparative case study in bio-mathematical modelling

A synthesis is presented of two recent studies on modelling the nonlinear neuro- mechanical hearing processes in mosquitoes and in mammals. In each case, a hierarchy of models is considered in attempts to understand data that shows nonlinear amplification and compression of incoming sound signals. The insect’s hearing is tuned to the vicinity of a single input frequency. Nonlinear response occurs via an arrangement of many dual capacity neuro-mechanical units called scolopidia within the Johnston’s organ. It is shown how the observed data can be captured by a simple nonlinear oscillator model that is derived from homogenization of a more complex model involving a radial array of scolopidia. The physiology of the mammalian cochlea is much more complex, with hearing occurring via a travelling wave along a tapered, compartmentalized tube. Waves travel a frequency-dependent distance along the tube, at which point they are amplified and “heard”. Local models are reviewed for the pickup mechanism, within the outer hair cells of the organ of Corti. The current debate in the literature is elucidated, on the relative importance of two possible nonlinear mechanisms: active hair bundles and somatic motility. It is argued that the best experimental agreement can be found when the nonlinear terms include longitudinal coupling, the physiological basis of which is described. A discussion section summarizes the lessons learnt from both studies and attempts to shed light on the more general question of what constitutes a good mathematical model of a complex physiological process. doi:10.1017/S1446181111000733
Estimation Method of Variable Composition Rate and Error Compensation Method of Aggregative Model for Reactive Power by Variable Composition Rate

Recently, due to the expansion of electric power demands, nonlinear load such as converters and inverters connected to the electric power distribution system, and extensive application of harmonic generation sources with power electric devices, disturbance of the electric power system and its influences on industries have been continuously increasing. In this research, we develop a novel aggregation algorithm by considering the harmonics characteristics for residential loads. Using data sets acquired from various experiments, we analyzed load characteristics according to harmonics and presented the results obtained the proposed method
COMPETITIVE INTELLIGENCE AS AN ENABLER FOR FIRM COMPETITIVENESS: AN OVERVIEW

The purpose of this article is to provide an overview, from literature, about how competitive intelligence can be an enabler towards a firm’s competitiveness. This overview is done under the background of intense global competition that firms are currently experiencing. This paper used a qualitative content analysis as a data collection methodology on all identified journal articles on competitive intelligence and firm competitiveness. To identify relevant literature, academic databases and search engines were used. Moreover, a review of references in related studies led to more relevant sources, the references of which were further reviewed and analysed. To ensure reliability and trustworthiness, peer-reviewed journal articles and triangulation were used. The paper found that competitive intelligence is an important enabler of firm competitiveness. The findings from this paper will assist business managers to understand and improve their outlook of competitive intelligence as an enabler of firm competitiveness and will be of great academic value.
GENETIC ENGINEERING AS A TOOL FOR MODIFICATION OF SEED STORAGE PROTEINS AND IMPROVEMENT OF NUTRITIONAL VALUE OF CEREAL GRAIN (review)

In recent years, genetic engineering has become an effective tool for the genetic improvement of cultivated plants including changes in the composition grain storage proteins of cereal crops that are the main source of nutrition for humans. The review describes the approaches used in these studies: the introduction of genetic constructs (i) providing the synthesis of proteins that are absent in recipient cultivars; (ii) inducing RNA-silencing of genes encoding proteins with low nutritional value, (iii) regulating the pool of amino acids in the endosperm. The studies are referred, which reported on the introduction of additional genes of high molecular weight glutenins (1Dx5, 1Ax1, 1Bx17, 1By18, 1Dy10 and others) into the genomes of different lines and cultivars of wheat. In these studies, the transgenic lines with increased dough strength and elasticity were obtained. In addition to the practical importance, these studies allow understanding the role of individual genes of high and low molecular weight glutenins in the formation of wheat flour quality traits. The examples of marker-free transgenic wheat lines expressing 1Dy10 and 1Bx14 genes, as well as transfer of high molecular weight glutenin genes into the genomes of other cereals (rye, corn, sorghum) are given. The possibilities of using the RNAi technology to obtain new information about the mechanisms of development of protein bodies, vitreous endosperm formation, and the role of different classes of prolamins and glutenins in the technological properties of flour and dough are discussed. The examples of the creation of transgenic maize with improved nutritional value via RNA-silencing of prolamin genes, transgenic sorghum with improved protein digestibility (obtained by silencing gene of the -kafirin, the protein that forms outer layer of the protein bodies, resistant to pepsin digestion), transgenic wheat with suppression of gliadin synthesis, which flour has a low toxicity to humans with celiac disease, forced to comply gluten-free diet, are given. An example of natural RNA-silencing is given Partivularly, in the rice mutant with reduced level of glutelin, a deletion between the two coding sequences, one of which has an inverted orientation has been detected in the Lgc1 locus. The genetic engineering approaches to increase the lysine content are described, e.g. introduction of genes that enhance its synthesis, such as dihydrodipicolinate synthase (DHPS) insensitive to feedback inhibition and aspartate kinase; suppression of zlkr/sdh gene regulating its catabolism; introduction of genes that control the synthesis of proteins with high lysine content (histones and other lysine-rich proteins). The prospects of using genetic engineering methods to create varieties with improved nutritional value are associated with the use of marker-free technologies, increasing accuracy of insertion of genetic constructs, using the methods of genome editing by artificially engineered nucleases.
Discovery and Recognition of Emerging Human Activities Using a Hierarchical Mixture of Directional Statistical Models

Human activity recognition plays a significant role in enabling pervasive applications as it abstracts low-level noisy sensor data into high-level human activities, which applications can respond to. With more and more activity-aware applications deployed in real-world environments, a research challenge emerges—discovering and learning new activities that have not been pre-defined or observed in the training phase. This paper tackles this challenge by proposing a hierarchical mixture of directional statistical models. The model supports incrementally, continuously updating the activity model over time with the reduced annotation effort and without the need for storing historical sensor data. We have validated this solution on four publicly available, third-party smart home datasets, and have demonstrated up to 91.5 percent accuracies of detecting and recognising new activities.
Re‐examining the role of chondrules in producing the elemental fractionations in chondrites

Abstract— The matrices of all primitive chondrites contain presolar materials (circumstellar grains and interstellar organics) in roughly CI abundances, suggesting that all chondrites accreted matrix that is dominated by a CI‐like component. The matrix‐normalized abundances of the more volatile elements (condensation temperatures <750–800 K) in carbonaceous and ordinary chondrites are also at or slightly above CI levels. The modest excesses may be due to low levels of these elements in chondrules and associated metal. Subtraction of a CI‐like matrix component from a bulk ordinary chondrite composition closely matches the average composition of chondrules determined by instrumental neutron activation analysis (INAA) if some Fe‐metal is added to the chondrule composition.
Quantifying the Impact of Data Sharing on Outbreak Dynamics (QIDSOD)

In this project, we will explore the range of data-related decisions made during public health emergencies like the ongoing COVID-19 pandemic and analyze the flow of information, data, and metadata within networks of such decisions. Data sharing is now considered a key component of addressing present, future, and even past public health emergencies, from local to global levels. Researchers, research institutions, journals and others have taken steps towards increasing the sharing of data around the ongoing COVID-19 pandemic and in preparation for future pandemics. We will quantify the effects of data flow modifications to identify parameter sets under which specific modes of sharing or withholding information have the largest effects on outbreak dynamics. For these high-impact parameter sets, we will then assess the current and past availability of corresponding data, metadata, and misinformation, and estimate the effects on outbreak mitigation and preparedness efforts.
Changes in Phylogenetic Community Structure of the Seedling Layer Following Hurricane Disturbance in a Human-Impacted Tropical Forest

Disturbance plays a key role in shaping forest composition and diversity. We used a community phylogeny and long-term forest dynamics data to investigate biotic and abiotic factors shaping tropical forest regeneration following both human and natural disturbance. Specifically, we examined shifts in seedling phylogenetic and functional (i.e., seed mass) community structure over a decade following a major hurricane in a human-impacted forest in Puerto Rico. Phylogenetic relatedness of the seedling community decreased in the first five years post-hurricane and then increased, largely driven by changes in the abundance of a common palm species. Functional structure (based on seed mass) became increasingly clustered through time, due to canopy closure causing small-seeded, light-demanding species to decline in abundance. Seedling neighbor density and phylogenetic relatedness negatively affected seedling survival, which likely acted to reduce phylogenetic relatedness within seedling plots. Across the study site, areas impacted in the past by high-intensity land use had lower or similar phylogenetic relatedness of seedling communities than low-intensity past land use areas, reflecting interactive effects of human and natural disturbance. Our study demonstrates how phylogenetic and functional information offer insights into the role of biotic and abiotic factors structuring forest recovery following disturbance.