Miracle-dz/UniFAR-FTUs huggingface dataset:
Downlink Synchronization for OTFS-Based Cellular Systems in High Doppler Environments

This paper proposes a downlink synchronization and cell identity (CID) estimation technique for cellular systems based on orthogonal time-frequency space (OTFS). In the proposed technique, each base station (BS) transmits one detection preamble (DP) and two OTFS symbols (pilot and secondary-CID (SCID) signal (SS)). The DP based on a linear frequency-modulated (LFM) waveform, called proposed-LFM (pLFM), carries the primary-CID (PCID) for symbol timing (ST) synchronization, whereas the SS based on the Zadoff-Chu (ZC) sequence mapped in the delay-Doppler domain carries the SCID. The pLFM is obtained by discretizing the LFM waveform, increasing the frequency sweeping parameter beyond the limit of the operational bandwidth, and incorporating the PCID into the LFM waveform. The autocorrelation and cross-correlation functions of the pLFM are analyzed to examine its correlation properties under the influence of a high Doppler shift. To reduce the undesirable correlation properties (side peak and time ambiguity), a receiver processing (RP) scheme is developed for the pLFM. It is found that the pLFM with RP is suitable for the DP design because it can provide an accurate ST in high-mobility scenarios. In addition, the influence of OTFS modulation on the ZC sequence is derived and a low-complexity detection algorithm based on message passing is applied to detect SCID at the user equipment. The simulation results demonstrate that the proposed downlink synchronization and CID estimation techniques are suitable for OTFS-based cellular systems in high-Doppler environments.
Detection of Pin Defects in Aerial Images Based on Cascaded Convolutional Neural Network

Pins are standard fasteners in power transmission lines, and the hidden dangers of pins falling off dramatically affects their safe operation. If a pin is missed, it is called pin defects in this paper. As the pin is a small target and has a complex background, traditional detection algorithms were used to identify pin defects from aerial images which suffer from poor accuracy and low efficiency. This paper proposed a target detection method based on cascaded convolutional neural networks. First, a small-scale shallow full convolutional neural network was used to obtain the region of interest; then, a deeper convolutional neural network conducted target classification and positioning on the obtained region of interest. Next, a nonlinear multilayer perceptron was introduced, the convolution kernel was decomposed, and the multi-scale feature maps were fused. At this point, an angle variable was added to the classification cross-entropy loss function. Multi-task learning and offline hard sample mining strategies were used in the training phase. The proposed method was tested on a self-built pin dataset and the remote sensing image RSOD dataset, and the experimental results proved its effectiveness. Our method can accurately identify pin defects in aerial images, thereby solving the engineering application problem of pin defect detection in transmission lines.
The Value of Fuel Economy: Evidence from the Chinese Passenger Vehicle Market

In this study I estimate Chinese consumers' valuation of fuel economy in the new car market using new vehicle registration records and online website comment data. I find that the new vehicle market displays full valuation, ranging from 85-105% under different specifications and assumptions of annual vehicle kilometer traveled. Consumer accessibility to reliable fuel economy information has a positive impact on valuation ratio. One policy implication of these findings is, for new car markets, a gasoline tax or carbon tax could be the most efficient tool given the high valuation of fuel economy. The Simulation results suggest that increasing the gasoline tax is a very effective way to reduce total gasoline consumption from automobiles and help China fulfill its pledge to peak its carbon emission by 2030.
Discovering Popular Paths and Management of Billboard Ads by Mining User Trajectory Data

The field of pattern mining has emerged to discover potentially useful hidden knowledge (information or patterns) from the voluminous data. The rapid development of data acquisition technologies like sensors contributes to the generation of massive spatial trajectory data from the users using a global positioning system in their mobile phones, cars, watches, and others. The trajectory of the user is defined as the sequence of locations of the user during the transit. Mining patterns from the user trajectory data is an active research area. Research efforts are being made to propose approaches to process user trajectory data and propose approaches for better travel path identification, transportation management, user-activity recognition. The Google Maps system is one of the useful application that exploits user trajectory data. In this thesis, we proposed a pattern mining based framework for computing the popular paths by analyzing the user trajectory data. Furthermore, we proposed a pattern mining framework to allocate the advertisements in billboards with the goal of improving the revenue of the billboard operator. First, we investigated the problem of finding the paths based on user preferences, which we designate as popular paths. Such user preferences may include roads with relatively high thoroughfare (i.e., better for safety), smoother roads with better infrastructure (e.g., fewer potholes), roads with more facilities or points of interest nearby, lighted roads as opposed to dark and unsafe streets, roads with relatively lower crime rates, roads with better scenic beauty and so on. In practice, given that users naturally follow some of these paths significantly more as compared to other paths, the popularity of a given path often reflects such user preferences. Moreover, users typically prefer diverse paths over similar paths for gaining flexibility in path selection. Given a set of user traversals in a road network and a set of paths between a given source and destination pair, we address the problem of performing top-k ranking of the paths based on both path popularity and path diversity. We proposed a model to compute the popularity score of the given path. Given a road network, a set of user traversals, and the source and destination pair, we have proposed an efficient framework by extending the transactional framework and frequent pattern mining technique for computing the popularity score of the given path between the source and destination pair. We conducted an extensive performance evaluation with two real datasets to demonstrate the effectiveness of the proposed approach. Second, we have proposed an efficient framework to improve the billboard operator’s revenue in the billboard advertisement scenario based on the user traversal data. A billboard operator manages the ad slots of a set of billboards. Normally, a user traversal is exposed to multiple billboards. It is possible to
THE INFLUENCE OF ETHICAL WORK CLIMATES ON PUBLIC SECTOR SUPPLIER SELECTION DECISIONS

This study examined the relationship between ethical work climates (EWCs) and supplier selection decisions (SSD), and the moderating roles of party politics and personal values on this relationship. A total of 600 senior level personnel from 40 Nigerian public sector organizations were surveyed. Results show that both high and low levels of external political pressures significantly reduce the perception that organisational SSDs are ruled-based and pro-social in nature. Furthermore, regardless of the level of perception of instrumental personal values by employees, instrumental ethical climates significantly determine SSDs; principled/cosmopolitan climate and benevolent/cosmopolitan climate only become significant perceptible determinants when there is less room for the accommodation of personal goals during SSD processes. We conclude that the EWC dimensions do really reflect the Nigerian public sector SSD outcomes. Important implications for theory and practice are also presented.
Climate change and Northern Hemisphere lake and river ice phenology from 1931–2005

Abstract. At high latitudes and altitudes one of the main controls on hydrological and biogeochemical processes is the breakup and freeze-up of lake and river ice. This study uses 3510 time series from across 678 Northern Hemisphere lakes and rivers to explore historical patterns in lake and river ice phenology across five overlapping time periods (1931–1960, 1946–1975, 1961–1990, 1976–2005, and 1931–2005). These time series show that the number of annual open-water days increased by 0.63 d per decade from 1931–2005 across the Northern Hemisphere, with trends for breakup and, to a lesser extent, freeze-up closely correlating with regionally averaged temperature. Breakup and freeze-up trends display a spatiotemporally complex evolution and reveal considerable caveats with interpreting the implications of ice phenology changes at lake and river sites that may only have breakup or freeze-up data, rather than both. These results provide an important contribution by showing regional variation in ice phenology trends through time that can be hidden by longer-term trends. The overlapping 30-year time periods also show evidence for an acceleration in warming trends through time. Understanding the changes on both long- and short-term timescales will be important for determining the causes of this change, the underlying biogeochemical processes associated with it, and the wider climatological significance as global temperatures rise.
The Impact of Export Promotion with Matchmaking on Exports and Service Outsourcing

The paper analyzes the effects of support for attending trade fairs on exports, foreign direct investments (FDI), and service outsourcing, using Japanese firm-level data on both performances and trade-fair participation. To solve self-selection problem into the service, I utilize a difference-in-differences matching estimation approach with unique firm characteristics, as well as a linear estimation approach with multiple fixed-effects. The results show that there are positive effects of attending trade-fairs on exporting status. Furthermore, attending a trade fair induces firms to outsource their market research activity.
Forthcoming in the Journal of Development Economics

Understanding the constraints to agricultural growth in Africa relies on the accurate measurement of smallholder labor. Yet, serious weaknesses in these statistics persist. The extent of bias in smallholder labor data is examined by conducting a randomized survey experiment among farming households in rural Tanzania. Agricultural labor estimates obtained through weekly surveys are compared with the results of reporting in a single end-of-season recall survey. The findings show strong evidence of recall bias: people in traditional recall-style modules reported working up to four times as many hours per person-plot relative to those reporting labor on a weekly basis. Recall bias manifests both in the intensive and extensive margins of labor reporting: while hours are over-reported in recall, the number of people and plots active in agricultural work are under-reported. The evidence suggests that this recall bias is driven not only by failures in memory, but also by the mental burdens of reporting on highly variable agricultural work patterns to provide a typical estimate. All things equal, studies suffering from this bias would understate agricultural labor productivity. JEL Codes: C8, O12, Q12
Macrophages by Specifically Sensitized Lymphocytes

Experiments were carried out to determine whether macrophages can be activated in vitro to resist challenge with heterologous microorganisms. Sensitized spleen cells from guinea pigs chronically infected with Toxoplasma gondii were cultured with normal guinea pig peritoneal macrophages in the presence and absence of Toxoplasma antigen. Macrophage monolayers incubated with sensitized spleen cells and antigen were markedly resistant to challenge from Listeria monocytogenes. Resistance was manifested by prolonged survival of the monolayers and rapid intracellular killing of the bacteria. Macrophages incubated with sensitized spleen cells but in the absence of antigen, as well as macrophages cultured with normal spleen cells, in the presence or absence of antigen, were rapidly destroyed. Sensitized spleen cells responded to the presence of Toxoplasma antigen by increased uptake of tritium-labeled thymidine. Supernatant fluid medium obtained from cultures of macrophages, sensitized spleen cells, and antigen contained a macrophage migration inhibitory factor(s). In addition, these supernatant fluids were capable of inducing increased resistance to Listeria in normal macrophages.
Applying Artificial Intelligence in Forecasting the Output of Industrial Solar Power Plant in Vietnam

This paper uses recurrent neural network (Long Short – Term Memory LSTM network) to build a model to forecast short-term generation capacity of Phong Dien solar power plant, (48 MWp – 35 MWAC) located in Thua Thien Hue Province, Viet Nam, with input factors including meteorological parameters. The authors conducted experiments to find the optimal structure of the model corresponding to the conditions of the plant and the data collection. Through this model, meteorological forecast data sets from commercial suppliers were used to forecast the plant's output power. The comments about the result as well as the further study direction are analysed and suggested.
Provably Efﬁcient Neural GTD Algorithm for Off-policy Learning

This paper studies a gradient temporal difference (GTD) algorithm using neural network (NN) function approximators to minimize the mean squared Bellman error (MSBE). For off-policy learning, we show that the minimum MSBE problem can be recast into a min-max optimization involving a pair of over-parameterized primal-dual NNs. The resultant formulation can then be tackled using a neural GTD algorithm. We analyze the convergence of the proposed algorithm with a 2-layer ReLU NN architecture using m neurons and prove that it computes an approximate optimal solution to the minimum MSBE problem as m ! 1 .
Teacher Perception of the School Nurses in Addressing Obesity Among School Children in Kuwait

Obesity in children is a global issue and it seems that no country has yet succeeded in addressing this issue. Therefore, investigating the current situation in regard to found new strategies in addressing the overweight and obesity in children by using qualitative research approaches was an important decision made at the beginning of the data collection. This study was conducted to examine the perceptions of school teachers towards the role of the school nurse in tackling obesity among children in Kuwait. Method: Twelve focus group discussions were used to collect the data to obtain in-depth details about the role of school nursing in addressing obesity among school children in sex provinces in Kuwait, The qualitative data were analysed using content analysis. NVivo 10® qualitative analysis software was used during the process of coding and the development of themes. Result: The focus group findings revealed the following key theme and perceptions among participants: The possible important role of the school nurse is minimised due to limitations of availability (not in every school) and their current roles. focus groups reported that nurses were limited to providing first aid to students, whereas nurses are able to serve in a more proactive, preventative capacity, although not asked to do so. Conclusion: school nurses were underrecognised and not appropriately utilised, as most participants in the second phase did not consider the school nurse as a part of the solution and believed that nurses were employed for emergency needs only. This is not in line with several studies that found that the activities of school nurses, such as delivering health education and taking body weight measurements, is associated with school children having a healthy body weight. Also, school nurses play a major role in advocating for the creation of a healthy environment for school children. Therefore, the current study calls for school nurses to be a part of the solution.
SentText: A Tool for Lexicon-based Sentiment Analysis in Digital Humanities

We present SentText , a web - based tool to perform and explore lexicon - based sentiment analysis on texts, specifically developed for the Digital Humanities (DH) community. The tool was developed integrating ideas of the user - centered design process and we gathered requirements via semi - structured interviews. The tool offers the functionality to perform sentiment analysis with predefined sentiment lexicons or self - adjusted lexicons. Users can explore results of sentiment analysis via various visualizations like bar or pie charts and word clouds. It is also possible to analyze and compare collections of documents. Furthermore, we have added a close reading function enabling researchers to examine the applicability of sentiment lexicons for specific text sorts. We report upon the first usability tests with positive results. We argue that the tool is beneficial to explore lexicon - based sentiment analysis in the DH but can also be integrated in DH - teaching.
Deletion of Rap‐Phr systems in Bacillus subtilis influences in vitro biofilm formation and plant root colonization

Natural isolates of the soil-dwelling bacterium Bacillus subtilis form robust biofilms under laboratory conditions and colonize plant roots. B. subtilis biofilm gene expression displays phenotypic heterogeneity that is influenced by a family of Rap-Phr regulatory systems. Most Rap-Phr systems in B. subtilis have been studied independently, in different genetic backgrounds and under distinct conditions, hampering true comparison of the Rap-Phr systems’ impact on bacterial differentiation. Here, we investigated each of the 12 Rap-Phr systems of B. subtilis NCIB 3610 for their effect on biofilm formation. By studying single Δrap-phr mutants, we show that despite redundancy between the cell-cell communication systems, deletion of each of the 12 Rap-Phr systems influences matrix gene expression, which could possibly enable fine-tuning of the timing and level of matrix production in response to specific conditions. Furthermore, some of the Δrap-phr mutants demonstrated altered biofilm formation in vitro and colonization of Arabidopsis thaliana roots, but not necessarily similarly in both processes, indicating that the pathways regulating matrix gene expression and other factors important for biofilm formation may be differently regulated under these distinct conditions. Significance Statement Natural isolates of Bacillus subtilis form robust biofilms in vitro and on plant roots. The formation of these heterogeneous populations is regulated by diverse Rap-Phr systems. However, most Rap-Phr systems in B. subtilis have been studied independently and in different genetic backgrounds. Here, we report that all 12 Rap-Phr systems affect matrix gene expression, while some of them affect development of in vitro biofilms and plant root colonization. Our study highlights the importance of the Rap-Phr systems in environmental adaptation of B. subtilis, specifically during biofilm formation in the rhizosphere.
CMBX Microstructure: Liquidity measures with limited information

Roll (1984), Thompson and Waller (1987) and Christopoulos (2020) provide techniques for estimation of bid-ask spreads from mid-market closing prices. This study investigates daily observations of Aaa and Baa commercial mortgage backed securities credit default swap indices (CMBX) risk premia over the period 11/2007-4/2019 using these models. The analysis of liquidity with bid-ask spread estimates yields intuitive results mapping to the prior literature using market factors and CMBX liquidity indices introduced in Christopoulos and Jarrow (2018). As such, estimates of bid-ask spreads provide new insights into the liquidity of the CMBX sector which is characterized by limited pricing information.
Attachment and Relationship Quality: A Longitudinal Cross-Lagged Panel Model Examining the Association of Attachment Styles and Relationship Quality in Married Couples

Attachment and Relationship Quality: A Longitudinal Cross-Lagged Panel Model Examining the Association of Attachment Styles and Relationship Quality in Married Couples Meagan Cahoon Alder School of Family Life, BYU Doctor of Philosophy This is a longitudinal cross-lagged panel model examining the bi-directional association of attachment styles and relationship quality in a community sample of 355 married couples, with at least one child between 10-14 years of age at the beginning of the study and 17-21 years of age at the end of the study. An Actor-Partner Interdependence Model (APIM), was used to test for actor and partner effects, thereby accounting for the non-independent nature of the data. Two separate APIM models were tested with Male Attachment predicting Female Relationship Quality and Female Attachment predicting Male Relationship Quality. Results indicate that own attachment was a stronger predictor of partner relationship quality over time than was own relationship quality to partner attachment; although male relationship quality did predict female attachment from T1 to T3, it was not significant at all other time points. Clinical implications and future research are discussed.
2 - Teacher Education, Common Purpose and the Forging of Multiple Publics in South Africa

In an important scholarly intervention on African publics, Raufu Mustapha argues that the multiplicity of publics is not an obstacle but instead a creative resource that can be used to forge common purpose through public deliberation. However, he does not elaborate how common purpose operates and to what effect. In this article, we examine the dynamics of common purpose among student teachers in South Africa. Teachers inculcate the dispositions and habits of public deliberation in young people. How teachers are trained and where they teach is therefore crucial to understanding the constitution of publics. We analyse data from a cohort of student teachers regarding their reasons for becoming teachers, their future plans and their anxieties about their profession. We find little evidence of race and class differences among student teachers. Instead, the evidence suggests that student teachers shared a common purpose informed by hyper-particularistic notions of the public, which was not only raced and classed, but also limited to a narrow understanding of their own community. In light of this, we seek to explain how policy contributes to the conditions under which common purpose leads to segregated publics, closing off the generative possibilities of multiple publics.