Candidate Positions Research Articles

The Trump Advantage in Policy Recall Among Voters

Research in political science suggests campaigns have a minimal effect on voters’ attitudes and vote choice. We evaluate the effectiveness of the 2016 Trump and Clinton campaigns at informing voters by giving respondents an opportunity to name policy positions of candidates that they felt would make them better off. The relatively high rates of respondents’ ability to name a Trump policy that would make them better off suggests that the success of his campaign can be partly attributed to its ability to communicate memorable information. Our evidence also suggests that cable television informed voters: respondents exposed to higher levels of liberal news were more likely to be able to name Clinton policies, and voters exposed to higher levels of conservative news were more likely to name Trump policies; these effects hold even conditioning on respondents’ ideology and exposure to mainstream media. Our results demonstrate the advantages of using novel survey questions and provide additional insights into the 2016 campaign that challenge one part of the conventional narrative about the presumed non-importance of operational ideology.

How and when candidate race affects inferences about ideology and group favoritism

Abstract How does a candidate's racial background affect the inferences voters make about them? Prior work finds that Black candidates are perceived to be more liberal. Using two survey experiments, we test whether this effect persists when candidate partisanship and issue positions are specified and also consider other consequential voter perceptions. We make two contributions. First, we show that while Black candidates are perceived to be more liberal than White candidates with the same policy positions, this difference is smaller for Black candidates who adopt more conservative positions on race-related issues. Second, we find that voters, both Black and White, believe Black candidates will prioritize the interests of Black constituents over those of White constituents, regardless of candidate positions.

Minimum Energy Atomic Deposition: A novel, efficient atomistic simulation method for thin film growth

Thin-film growth is an area of research concerned with complex phenomena happening at atomic scales. Therefore, molecular simulation has been an important tool to confront experimental results to theoretical assumptions. However, the traditional thin film growth simulation methods, i.e., Molecular Dynamics (MD) and kinetic Monte-Carlo (kMC) and combinations thereof, suffer from limitations inherent to their design, i.e., limitations in system size and simulation time for MD and predetermined reaction rates and reaction sites for kMC. Consequently, it is practically impossible to simulate the evolution of polycrystalline growth resulting in ∼100nm thick films with realistic stress fields and defect structures, such as grain boundaries, stacking faults, etc. In this work, we propose a versatile and efficient atomistic simulation method (Minimum Energy Atomic Deposition) which works by direct insertion of atoms at points of minimal potential energy through efficient scanning of candidate positions and rapid relaxation of the system. This method allows simulating ≥100nm film thickness while mimicking experimental growth rates and high crystallinity and low-defect concentration and enables in-depth studies of atomic growth mechanisms, the evolution of crystal defects, and residual stress build-up. We demonstrate the efficiency and versatility of the method through the deposition of Al on Si, Al on Al, and Si on Si. The simulation results are systematically compared with experimental observations of thin-film deposition, yielding consistent observations. The method has been implemented in open-source LAMMPS software, making it easily accessible to the research community.

High-ranking officials of the plenipotentiary representative offices of the President of the Russian Federation in the federal districts: recruitment channels and careers

The article covers the analysis of the main recruitment channels for high-ranking officials of the plenipotentiary representative offices of the President of the Russian Federation in the federal districts. As the empirical basis of the study serves the biographical database, that includes information on 154 presidential bureaucrats as of April 2023. Recruitment of people from various socio-professional groups to the apparatus of the plenipotentiary representative offices reveals a number of trends caused by interacting push (specific features of the candidate's position and associated resources and interests) and pull (place in the power system and functional specialisation of the plenipotentiary representative offices, specifics of leadership positions in them, as elements of the opportunity structure, as well as personal connections) factors. One of the most important trends is militarisation: most officials of the plenipotentiary representative offices have work experience in law enforcement agencies and even spent there most of their previous careers. Recruiting security officials who are, in terms of career, “ideal-typical” federal officials and professionally socialised within the framework of rigid, centralised hierarchies probably strengthens the autonomy of the plenipotentiary representations from actors and interests external to federal power, including regional administrations, that these bodies are called upon to control. The logic of autonomisation is also in line with the fact that one of the main suppliers (especially direct) of key officials of the plenipotentiary representations is the Presidential Administration, first of all, the apparatus of the representations themselves. However, a significant minority of presidential officials have experience working in regional administrations (especially among deputies and assistants to plenipotentiaries), as well as in business, both public and private (especially among plenipotentiaries and their deputies). At the same time positions in these structures rarely serve as a direct springboard to a key position in the plenipotentiary representations. Finally, the role of legislative bodies as a channel for recruiting presidential officials is insignificant. In general, the author's findings are consistent with the results of previous studies, indicating the relative stability of recruitment trends.

Институт самовыдвижения на муниципальных выборах в России в условиях пропорциональной избирательной системы

The use of the proportional electoral system to form a representative authority of a municipal structure gives a non-party citizen no opportunity to exercise the right of self-nomination as in such conditions, he/she is suggested to include his/her candidacy in a party list. The article analyzes legal provisions that regulate this procedure, compares the legal position of a self-nominated candidate and a nonparty candidate that interacts with an electoral association, identifies problems of such interaction and certain aspects of determination of election results and mandate distribution.

Do candidates’ policy positions matter in regional elections? Evidence from the 2021 elections to the Welsh Senedd

ABSTRACT An oft-cited benefit of candidate-based elections is that voters can hold individual candidates accountable for their issue stances. However, voters may not always be aware of candidates’ policy positions, a concern which becomes especially salient in regional elections. Using mass online survey data and a fixed effects approach, we investigate the extent to which voters were influenced by the policy positions of individual candidates when voting in the 2021 elections to the Welsh Senedd. We find that candidates’ policy positions did matter, but that this effect was small, limited to issues voters deemed to be particularly important, and only emerges among voters with high political interest. That said, our findings also suggest that the influence of candidates’ policy positions on voting behaviour was not substantially smaller when compared to national elections in the UK and elsewhere. We discuss options for improving voter responsiveness to candidates’ issue stances.

Irregular array optimization for beamforming with a polar coordinate-based partition coding approach

Abstract An innovative irregular array configuration optimization method for enhancing beamforming is introduced. This study presents partition coding to optimize sensor positioning and quantity of a non-uniform concentric circular array. This novel approach transcends traditional techniques by integrating structural partitioning and performance optimization to quantify the array’s geometry-performance correlation. Sensor candidate positions are mapped in polar coordinates, with each configuration translated into a sensor position matrix form. A significant innovation lies in the adaptation of the partition coding genetic algorithm to enhance the encoding of candidate positions and to refine crossover and mutation operations, underpinned by an elite retention strategy for selecting the optimal array configuration. Both simulation and experimental results substantiate the method’s effectiveness, achieving high-resolution acoustic mapping with commendably low computational complexity.

A DNN robust video watermarking method in dual-tree complex wavelet transform domain

Deep learning is increasingly being applied in the field of robust watermarking. However, the existing deep learning-based video watermarking methods only uses spatial domain information as the input and the robustness against attacks such as H.264/AVC compression is still not strong. Therefore, this paper proposes a deep learning-based robust video watermarking method in dual-tree complex wavelet transform (DT-CWT) domain. The video frames are transformed into the DT-CWT domain and the suitable high-pass subbands are selected as candidate embedding positions. Then, the 2D and 3D convolutions are combined to extract both intra-frame spatial features and inter-frame temporal features for finding the stable and imperceptible coefficients for watermark embedding in the candidate positions. The convolutional attention module (CBAM) is used to further adjust the embedding coefficients and strengths. In addition, the attack layer, where a differentiable proxy is specially designed in this paper for the simulation of non-differentiable H.264/AVC compression, is introduced to generate distorted watermarked videos for improving the robustness against different attacks. Experimental results show that our method is superior to both the existing deep learning-based methods and traditional methods in the robustness against both spatial and temporal attacks while preserving high video quality. The source code is available at https://github.com/imagecbj/A-DNN-Robust-Video-Watermarking-Method-in-DT-CWT-Domain.

Natural antiretroviral compounds as the inhibitors of the SARS-CoV-2 M protein

The intricate structure of the membrane protein in SARS-CoV-2 presents a challenge for experimental analysis. This protein plays a crucial role in both the viral infection cycle and virus development. Consequently, it represents a compelling target for therapeutic interventions and vaccine development. Given our limited understanding of its experimental structure, we employed homology modeling to generate a structural approximation of the SARS-CoV-2 membrane protein. Subsequently, we conducted a 100 ns molecular dynamics simulation of the developed model. Ten poses, each at 10 ns dynamics, of the model structure, were extracted from the dynamical pathway which were utilized for the molecular docking of the natural ligands chosen from the ZINC12 database. Further, molecular dynamics simulation of 100 ns of the top two protein–ligand complexes from clusters having better docking scores, incorporating a membrane environment, have been carried out. Through this simulation, we identified active site residues and analyzed the binding positions of potential drug candidates. Our analysis focused on identifying drugs that exhibited better free energy of binding and remained stable for the longest duration during the molecular dynamics simulations. The results provide insights into potential candidates SA_0124 and BMC_0005 for targeting the modeled SARS-CoV-2 membrane protein, offering valuable contributions to ongoing drug discovery efforts.

Integration of Steam Recovered from Molten Salts in a Solar Integrated Combined Cycle

In the current context of the energy transition, Integrated Solar Combined Cycle (ISCC) power plants are an alternative that are able to reduce carbon emissions from combined cycle (CC) power plants. In addition, the coupling to an energy storage system based on molten salts benefits hybridization, allowing the energy surplus to be to stored to cover peaks in energy demand. Because it is a recent technology, the determination of the optimal injection points for the solar-generated steam into the combined cycle is a critical issue. In this work, a thermodynamic model of a hybrid natural gas and solar thermal CC power plant has been developed using Thermoflex to analyze the integration effects in terms of efficiency and power. For all the steam injection candidate positions, the effects of ‘power boosting’ and ‘fuel saving’ operation modes have been simulated, considering operation conditions that are compatible with the useful range of molten salts. The results show that injection of steam at the high-pressure line before the steam turbine increases the cycle’s gross efficiency with respect to the reference case, estimating a reduction of carbon emissions of 6696 kg/h in the ‘fuel saving’ mode and an increase in gross power of 14.4 MW in the ‘power boosting’ mode. Hence, adapting current combined cycles for hybridization with solar power is a viable solution in the transition period towards more sustainable energy sources.

Characterization of Candidate Solutions for X-Ray Pulsar Navigation

X-ray pulsar based navigation (XNAV) can be used to estimate spacecraft state information based on observation of distant pulsars. XNAV system concepts typically require an initial position estimate since there are many candidate positions which may produce the same measurement. If position ambiguity can be resolved, XNAV may enable full state estimation without prior information. This study seeks to efficiently find candidate spacecraft positions and determine how to select pulsars to minimize the number of candidate solutions within a given domain. A numeric scheme for determining candidate positions is developed for an arbitrary number of observed pulsars. Pulsar selection criteria are developed in terms of relative direction, period, and phase accuracy. Results indicate that it is more time efficient to observe additional pulsars rather than improve the accuracy of pulsar measurements. A smaller angular separation and increased period of the observed pulsars reduces the number of candidate solutions within a given domain. Phase measurement accuracy should be improved simultaneously for all pulsars rather than prioritizing a single pulsar. These selection criteria are verified by evaluating the number of candidate solutions for permutations of 34 real pulsars.

Mode of candidacy, electoral prospects, and the ideological deviation of candidacy-seeking politicians from their party leadership

Politicians who seek their parties' nomination as candidates for public office start communicating their ideological profile to the selectorate months before the party decides on who will run as candidates. However, some politicians tend to steer away from their party leadership, while others stick closer to the party line. We argue that not only the mode of candidacy but one's expected chances of winning the election during the candidate selection period are defining factors in understanding why some candidates deviate further from their party leadership position than others. We use novel data on the degree of intra-party competition among the main German parties in all 299 electoral districts and on the ideological positions of candidates, measured using their Twitter statements in the run-up to the 2021 Bundestag election, to evaluate our expectations. In line with existing studies, we find that candidates who seek only their party's nomination via lists deviate less from party leadership than candidates who seek nomination as a district candidate. In contrast to our expectations, candidates who seek their nomination in an electoral district do not deviate more ideologically from their party when they can expect to win the district seat on election day based on published polls during the candidate selection period.

The Role of the Press in Free and Fair Elections in Uganda: A Case Study of Daily Monitor News Paper

The media is an essential component of any democratic election. This is illustrated in a way that keeps voters informed about the policies and agendas of different political parties and contenders. Until voters are aware of each candidate's position on every issue, they will not be able to completely exercise their right to vote. Conversely, the media can aid voters in their self-education by providing a comparative analysis of important issues. Numerous individuals have viewed the media's above-mentioned job as idealistic and unachievable, asserting that regular reporting on events is rife with "fake news" and falls short of the criteria of superior journalism. Descriptive statistics were used to examine the coded data, and information was generated and presented in the form of graphs, tables, and charts exhibiting frequencies and percentages. The study suggests that false news has existed since the internet's prehistory and is prevalent today. It highlights the negative impact of false news on media organizations, leading to credibility loss and costly investigations. Despite ethical journalism rules, media organizations face threats of closure or censorship. The general population is a significant source of fake news. False news in Uganda leads to various consequences, such as media organization closure, damage to brand reputation, and mistrust of news industries. It can also cause underdevelopment, increased demonstrations, hatred, and even innocent deaths. Despite adhering to ethical journalism rules, media organizations face threats of closure or censorship. False news in media organizations can lead to credibility loss, costly investigations, and threats of closure or censorship, while the general population is a significant source, causing incidents like demonstrations, hatred, deaths, and celebrity reputation damage. Key words: Media, Democracy, Citizenship, Marketization, Election.

GNSS direct position estimation-inspired positioning with pseudorange correlogram for urban navigation

Multipath (MP) reception has been among the main issues for accurate and reliable positioning in urban environments. It has been shown to introduce positioning errors of up to tens of meters for conventional two-step (2SP) receivers. The direct position estimation (DPE) has been introduced as a more robust positioning algorithm compared to the conventional two-step (2SP) receivers in terms of MP mitigation. However, its high computational load prevents DPE from real-time positioning for commercial receivers. Thus, we present a novel grid-based maximum likelihood estimation (MLE) algorithm based on DPE by making use of pseudorange measurements to obtain the correlogram on a predefined searching space. Unlike DPE, which performs correlations at the intermediate frequency (IF) level, correlations are done by directly comparing the code phase of each candidate position, velocity, and timing with the incoming pseudorange. This way, the proposed method retains MP mitigation properties from DPE through the use of MLE from DPE and allows for a significantly reduced computational load compared to DPE. The proposed method was tested with both open-sourced datasets collected in urban environments as well as IF simulation data, and its performance is evaluated against a 2SP receiver. Results show that the proposed method manages to acquire the MP mitigation capability of DPE and outperforms 2SP by up to around 23% in the tested urban datasets and 91% in the simulation data, at a much-reduced computational time. The resilience of our proposed method against MP and NLOS could even potentially offer applications in geodetic networks, where robust estimators are traditionally employed to counteract outliers.

The impact of the war on Gaza on the US presidential election

The War on Gaza, caused by a recurring occupation of Palestinian land by Israel, has long been a focal point of international attention and debate. The escalation of killings and wanton destruction of Palestinian land and people in the ongoing genocide in Gaza has not only had profound humanitarian implications for the Palestinian people but has also reverberated across the global political landscape, including in the context of U.S. presidential elections. This article provides an analytical examination of the impact of the Massacre in Gaza on U.S. presidential elections, with a focus on the electoral dynamics, public opinion, and policy responses. Through a comprehensive review of literature and analysis of electoral outcomes, this article explores the ways in which the War on Gaza has influenced electoral campaigns, candidate positions, and voter perceptions, and assesses its implications for U.S. foreign policy towards the Middle East.

Modified Archimedes optimization algorithm for global optimization problems: a comparative study

Archimedes Optimization Algorithm (AOA) is a recent optimization algorithm inspired by Archimedes’ Principle. In this study, a Modified Archimedes Optimization Algorithm (MDAOA) is proposed. The goal of the modification is to avoid early convergence and improve balance between exploration and exploitation. Modification is implemented by a two phase mechanism: optimizing the candidate positions of objects using the dimension learning-based (DL) strategy and recalculating predetermined five parameters used in the original AOA. DL strategy along with problem specific parameters lead to improvements in the balance between exploration and exploitation. The performance of the proposed MDAOA algorithm is tested on 13 standard benchmark functions, 29 CEC 2017 benchmark functions, optimal placement of electric vehicle charging stations (EVCSs) on the IEEE-33 distribution system, and five real-life engineering problems. In addition, results of the proposed modified algorithm are compared with modern and competitive algorithms such as Honey Badger Algorithm, Sine Cosine Algorithm, Butterfly Optimization Algorithm, Particle Swarm Optimization Butterfly Optimization Algorithm, Golden Jackal Optimization, Whale Optimization Algorithm, Ant Lion Optimizer, Salp Swarm Algorithm, and Atomic Orbital Search. Experimental results suggest that MDAOA outperforms other algorithms in the majority of the cases with consistently low standard deviation values. MDAOA returned best results in all of 13 standard benchmarks, 26 of 29 CEC 2017 benchmarks (89.65%), optimal placement of EVCSs problem and all of five real-life engineering problems. Overall success rate is 45 out of 48 problems (93.75%). Results are statistically analyzed by Friedman test with Wilcoxon rank-sum as post hoc test for pairwise comparisons.

LGB+ identity and its implications for the policy positions of parliamentary candidates

Abstract Several studies concentrate on the representation of minority groups and the policy goals that members of these groups highlight when becoming candidates for public offices. However, we do not know much about the degree of parliamentary representation of sexual minorities and what ideological profile politicians with an LGB+ identity adopt. We aim at filling this gap by analysing the ideological stances of LGB+ candidates on key policy dimensions. Using data from the 2021 German candidate study, we find that the self-identification as LGB+ contributes significantly to adopting progressive stances on the socio-cultural dimension and more favourable positions on welfare state expansion, regardless of further important factors like party affiliation. Moreover, candidates who consider themselves LGB+ do take on significantly less traditional positions on the socio-cultural dimension compared to the position of their party, indicating that increasing descriptive representation of LGB+ individuals in parliament leads to a strengthening of more progressive voices in parliament and a stronger substantive representation of LGB+ interests.

The Site/Group Extended Data Format and Tools.

Comparative sequence analysis permits unraveling the molecular processes underlying gene evolution. Many statistical methods generate candidate positions within genes, such as fast or slowly evolving sites, coevolving groups of residues, sites undergoing positive selection, or changes in evolutionary rates. Understanding the functional causes of these evolutionary patterns requires combining the results of these analyses and mapping them onto molecular structures, a complex task involving distinct coordinate referential systems. To ease this task, we introduce the site/group extended data format, a simple text format to store (groups of) site annotations. We developed a toolset, the SgedTools, which permits site/group extended data file manipulation, creating them from various software outputs and translating coordinates between individual sequences, alignments, and three-dimensional structures. The package also includes a Monte-Carlo procedure to generate random site samples, possibly conditioning on site-specific features. This eases the statistical testing of evolutionary hypotheses, accounting for the structural properties of the encoded molecules.

Partisan communication in two-stage elections: the effect of primaries on intra-campaign positional shifts in congressional elections

Abstract The influence of congressional primary elections on candidate positioning remains disputed and poorly understood. We test whether candidates communicate artificially “extreme” positions during the nomination, as revealed by moderation following a primary defeat. We apply a scaling method based on candidates language on Twitter to estimate positions of 988 candidates in contested US House of Representatives primaries in 2020 over time, demonstrating validity against NOMINATE (r > 0.93) where possible. Losing Democratic candidates moderated significantly after their primary defeat, indicating strategic position-taking for perceived electoral benefit, where the nomination contest induced artificially “extreme” communication. We find no such effect among Republicans. These findings have implications for candidate strategy in two-stage elections and provide further evidence of elite partisan asymmetry.

Task-Wise Sampling Convolutions for Arbitrary-Oriented Object Detection in Aerial Images.

Arbitrary-oriented object detection (AOOD) has been widely applied to locate and classify objects with diverse orientations in remote sensing images. However, the inconsistent features for the localization and classification tasks in AOOD models may lead to ambiguity and low-quality object predictions, which constrains the detection performance. In this article, an AOOD method called task-wise sampling convolutions (TS-Conv) is proposed. TS-Conv adaptively samples task-wise features from respective sensitive regions and maps these features together in alignment to guide a dynamic label assignment for better predictions. Specifically, sampling positions of the localization convolution in TS-Conv are supervised by the oriented bounding box (OBB) prediction associated with spatial coordinates, while sampling positions and convolutional kernel of the classification convolution are designed to be adaptively adjusted according to different orientations for improving the orientation robustness of features. Furthermore, a dynamic task-consistent-aware label assignment (DTLA) strategy is developed to select optimal candidate positions and assign labels dynamically according to ranked task-aware scores obtained from TS-Conv. Extensive experiments on several public datasets covering multiple scenes, multimodal images, and multiple categories of objects demonstrate the effectiveness, scalability, and superior performance of the proposed TS-Conv.