Miracle-dz/UniFAR-FTUs huggingface dataset:
Political participation profiles

Abstract The literature on the participation paradox, stealth democracy, political transformation and populism implicitly refers to the existence of different participation profiles, but its empirical evidence focuses on separate actions. While several studies have examined the existence of distinct combinations of actions, such participation profiles have rarely been placed within a theoretical framework or connected to the motivations and resources that shape participation. In this article these connections are given a theoretical basis and empirically tested via latent class analysis of a unique set of 12 different political activities. After establishing the participation profiles, it is assessed how political motivations (e.g. interest, efficacy) and resources (time and skills) explain profile membership by using fractional multinomial logistic regression models. Combining these two steps helps to reassess what levels of political participation actually imply for the functioning of our democracies. Crucially, the participation elite is small; faithful voters are numerous but not particularly engaged; and systemically dissatisfied citizens tend to disengage – only a few try to transform the system. Supplemental data for this article can be accessed online at: https://doi.org/10.1080/01402382.2021. 2017612 .
Paclitaxel treatment enhances lymphatic metastasis of B16F10 melanoma cells via CCL21/CCR7 axis

Chemotherapeutic drugs have been successfully used to treat several cancers, including melanoma. However, metastasis occasionally occurs after chemotherapy. Here, we reported that paclitaxel (PTX) treatment for B16F10 tumour in mice led to an enhanced lymphatic metastasis of the melanoma cells, although a significant inhibition of tumour growth at the injection site was observed. Further study demonstrated that PTX upregulated the expression of C-C chemokine receptor type 7 (CCR7) in B16F10 cells, enhancing their migration through the activation of JNK and p38 signalling pathways. Loss of CCR7 or blockade of C-C motif chemokine ligand 21 (CCL21)/CCR7 axis abolished the pro-migration effect of PTX on B16F10 melanoma cells. Importantly, combination of PTX and CCR7 mAb could simultaneously delay the tumour growth and reduce the lymphatic metastasis in B16F10 melanoma. The blockade of CCL21/CCR7 axis may collectively serve as a strategy for lymphatic metastasis in some melanoma after chemotherapy.
Geographic Variation in Migratory Grasshopper Recruitment under Projected Climate Change

Climate change is expected to alter prevailing temperature, precipitation, cloud cover, and humidity this century, thereby modifying insect demographic processes and possibly increasing the frequency and intensity of rangeland and crop impacts by pest insects. We leveraged ten years of migratory grasshopper (Melanoplus sanguinipes) field surveys to assess the response of nymph recruitment to projected climate conditions through the year 2040. Melanoplus sanguinipes is the foremost pest of grain, oilseed, pulse, and rangeland forage crops in the western United States. To assess nymph recruitment, we developed a multi-level, joint modeling framework that individually assessed nymph and adult life stages while concurrently incorporating density-dependence and accounting for observation bias connected to preferential sampling. Our results indicated that nymph recruitment rates will exhibit strong geographic variation under projected climate change, with population sizes at many locations being comparable to those historically observed, but other locations experiencing increased insect abundances. Our findings suggest that alterations to prevailing temperature and precipitation regimes as instigated by climate change will amplify recruitment, thereby enlarging population sizes and potentially intensifying agricultural pest impacts by 2040.
The effect of online individual ethics cases on moral reasoning in business negotiation: An experimental study

Abstract There is increasing interest in the effectiveness of online case-based instruction. Although some prior research has emphasized the importance of online discussion and communication for these cases, recent work suggests that individual completion of these cases is also effective. In this research, participants individually read ethics cases and respond to questions from a popular online ethics case bank before completing the Self-reported Inappropriate Negotiation Strategies questionnaire. Students who individually engaged with the longer online case were less likely to endorse deceptive business negotiation tactics versus the control group, whereas students who engaged with the shorter online case were not.
Argumentative practices and patterns in debating climate change on Twitter

PurposeThe purpose of this paper is to investigate practices of argumentation on Twitter discussions about climate change.Design/methodology/approachConversational threads were collected from the Twitter API. Fundamental concepts from argumentation theory and linking practices were operationalised through a coding schema for content analysis. Tweets were analysed in the context of the discussions and coded according to their argumentative approach, interaction type and argumentation stage. Linked and embedded sources were analysed in order to find how they were used in arguments, the plausibility and soundness of the message, the consistency and trustworthiness of the linked source and its adequacy with the target audience.FindingsAmong the interactions between arguers, this study found five typical practices and several patterns involving the dynamics of the conversations, the strategy of the argumentation and the linking practices. Although the rhetorical approach was prominent, the agreement was rarely achieved. The arguers used a variety of sources to justify or support their positions, often embedding non-textual content. These linking practices, together with the strategy adopted and the topics discussed, suggest the involvement of a multiple audience engaged in discussing ad lib scientific artefacts, topics and outputs.Originality/valueWhile Twitter has been the focus for many research papers, the conversational threads have been given little attention so far. With the Twitter API making conversations more accessible for research, this paper does not only give insight into multiple audience group argumentation dynamics but also provides a method to study the conversations from an argumentation theory perspective.
Driver Behavior Profiling and Recognition Using Deep-Learning Methods: In Accordance with Traffic Regulations and Experts Guidelines

The process of collecting driving data and using a computational model to generate a safety score for the driver is known as driver behavior profiling. Existing driver profiles attempt to categorize drivers as either safe or aggressive, which some experts say is not practical. This is due to the “safe/aggressive” categorization being a state that describes a driver’s conduct at a specific point in time rather than a continuous state or a human trait. Furthermore, due to the disparity in traffic laws and regulations between countries, what is considered aggressive behavior in one place may differ from what is considered aggressive behavior in another. As a result, adopting existing profiles is not ideal. The authors provide a unique approach to driver behavior profiling based on timeframe data segmentation. The profiling procedure consists of two main parts: row labeling and segment labeling. Row labeling assigns a safety score to each second of driving data based on criteria developed with the help of Malaysian traffic safety experts. Then, rows are accumulated to form timeframe segments. In segment labeling, generated timeframe segments are assigned a safety score using a set of criteria. The score assigned to the generated timeframe segment reflects the driver’s behavior during that time period. Following that, the study adopts three deep-learning-based algorithms, namely, Deep Neural Network (DNN), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), to classify recorded driving data according to the established profiling procedure, and selects the most suitable one for a proposed recognition system. Various techniques were used to prevent the classification algorithms from overfitting. Using gathered naturalistic data, the validity of the modulated algorithms was assessed on various timeframe segments ranging from 1 to 10 s. Results showed that the CNN, which achieved an accuracy of 96.1%, outperformed the other two classification algorithms and was therefore recommended for the recognition system. In addition, recommendations were outlined on how the recognition system would assist in improving traffic safety.
Three Persons, Two Cuts: A New Cake-Cutting Algorithm

Summary We describe a 3-person, 2-cut envy-free cake-cutting algorithm, inspired by a continuous moving-knife procedure, that does not require that the players continuously move knifes across the cake. By having the players submit their value functions over the cake to a referee—rather than move knives according to these functions—the referee can ensure that the division is not only envy-free but also maximin. In addition, the referee can use the value functions to find a maximally equitable division, whereby the players receive equally valued shares that are maximal, but this allocation may not be envy-free.
Assessing Trauma Center Accessibility for Healthcare Equity Using an Anti-Covering Approach

Motor vehicle accidents are one of the most prevalent causes of traumatic injury in patients needing transport to a trauma center. Arrival at a trauma center within an hour of the accident increases a patient’s chances of survival and recovery. However, not all vehicle accidents in Tennessee are accessible to a trauma center within an hour by ground transportation. This study uses the anti-covering location problem (ACLP) to assess the current placement of trauma centers and explore optimal placements based on the population distribution and spatial pattern of motor vehicle accidents in 2015 through 2019 in Tennessee. The ACLP models seek to offer a method of exploring feasible scenarios for locating trauma centers that intend to provide accessibility to patients in underserved areas who suffer trauma as a result of vehicle accidents. The proposed ACLP approach also seeks to adjust the locations of trauma centers to reduce areas with excessive service coverage while improving coverage for less accessible areas of demand. In this study, three models are prescribed for finding optimal locations for trauma centers: (a) TraCt: ACLP model with a geometric approach and weighted models of population, fatalities, and spatial fatality clusters of vehicle accidents; (b) TraCt-ESC: an extended ACLP model mitigating excessive service supply among trauma center candidates, while expanding services to less served areas for more beneficiaries using fewer facilities; and (c) TraCt-ESCr: another extended ACLP model exploring the optimal location of additional trauma centers.
Association of Depression with Polypharmacy among Diabetic Patients of Geriatric Age Group in Tertiary Care Teaching Hospital

Background: Diabetes mellitus, one of the common serious conditions among the elderly and depression is frequent finding as a Comorbidity. Polypharmacy is common in diabetes and In diabetic senior people, it has been linked to depression. Polypharmacy, especially among the elderly, is a consistent predictor of inappropriate medication. Approaching and analysing the prescription pattern in elderly diabetic patient will rationalize the drug utilization. The current research is to access the co-relation of polypharmacy in geriatric diabetic patient and accompanying depression. Objectives: To assess depression and polypharmacy and correlate their association in diabetic patients of geriatric age group. Methodology: This is questionnaire based cross sectional observational study. This shall be conducted in geriatric population attending Medicine department [OPD and IPD] [AVBRH], DMIMS, Sawangi [M], Wardha, Maharashtra, India. The depression will be assessed using Geriatric Depression scale. The Polypharmacy will be assessed using contingency table and odds ratio. Expected outcome: It is hypothesized that geriatric diabetic patients with depression [GDS>= 6] are at higher risk of encountering polypharmacy. Conclusion: To upgrades standards of life of senior diabetic patients, prescribing procedures should be reviewed.
Application of RALS cointegration test assessing the role of natural resources and hydropower energy on ecological footprint in emerging economy

This paper assesses the nexus between natural resource rent, hydropower energy consumption and ecological footprint for environmental sustainability incorporating with economic performance by using yearly data from 1970 to 2017. To this end, the long run steady-state relationship among investigated variables has been analyzed by using newly established Residual Least Squares (RALS) method and confirmed for Turkish economy. The directions and magnitudes of the effects of these variables on ecological footprint were tested by using Dynamic Ordinary Least Squares (DOLS) technique. The findings, except hydropower energy consumption, reveal statistically significant and positive effects of investigated variables on ecological footprint. Moreover, the inverted U-shaped EKC hypothesis was also affirmed between economic performance and ecological footprint. The causal relationship among these variables were also tested by using VECM Granger causality test The unidirectional Granger causality relationships were found that they are running from ecological footprint, and natural resource rent to economic performance, from natural resources to ecological footprint and from natural resource rent to economic performance in Turkish economy. Additionally, the bidirectional causal relationship has been detected among economic performance and ecological footprint in Turkey. The findings highlight the importance of investigated variables on ecological footprint in Turkey.
Application of ID—Monte Carlo method to state prediction of dissolved gases in transformer oil

The method combining ID3(Interactive Dicremiser version3) Algorithm and Monte Carlo Simulation is applied to forecast the transformer faults.Based on the observed and measured data,the ID3 Algorithm is used to simplify the attributes of transformer.The rules of fault generation are obtained by distributed function of Monte Carlo Simulation and ID3.The random variables are used to simulate the fault of transformer.The probabilities of fault are obtained.The data of dissolved gases in transformer oil is analyzed and processed.
Comparing Model Representations of Physiological Limits on Transpiration at a Semi‐Arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi‐empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi‐arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big‐leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.
Liquid Software-Based Edge Intelligence for Future 6G Networks

The 6G wireless network is promising to build bridges toward smart society in the digital world, which calls for innovative architectures and new solutions. The future 6G network should be sensing-based and data-driven for near-instant and massive connectivity with distributed intelligence. With a majority of intelligent applications being deployed at the edge, artificial intelligence (AI) is envisioned to play a key role in satisfying key requirements of 6G networks. Edge intelligence, as the marriage of AI and edge computing, is envisioned to fully meet the potential requirements of edge big data with energy, bandwidth, storage, and privacy concerns. However, it is an attractive issue to deal with distributed edge intelligence for the complexities and heterogeneous requirements, especially considering the time-varying channels and network dynamics. Furthermore, the ever increasing number of smart devices present great challenges for intelligent network management and newly modular network design in 6G networks, which needs to enable liquid self-management with comprehensive network intelligence. Hence, in this article, we first comprehensively give an overview on AI toward 6G networks, and characterize the requirements of a 6G network for AI applications. In particular, we investigate distributed edge intelligence challenges, requirements, and trends in future 6G networks. Then a liquid-specific and flexible software-defined network architecture for AI applications is inspired and discussed by 6G networks, which will play a crucial role in both academia and industry.
Design of adiabatic FIFO based on clocked transmission gate adiabatic logic circuit

The working principle and structure of first in first out(FIFO) and clocked transmission gate adiabatic logic(CTGAL) were investigated,and a design scheme of adiabatic FIFO based on CTGAL was proposed.The design scheme considers the circuit structure in transistor level by using the principle of adiabatic computing,which can effectively avoid the inevitable problems of metastability and asynchronism signals treatments in FIFO based on conventional complementary metal oxide semiconductor(CMOS) logic.A 16-depth adiabatic FIFO based on CTGAL was achieved.HSPICE simulation verified the valid functionality of the designed circuit,and showed that the proposed circuit could attain energy saving of 71%,compared to the adiabatic FIFO based on efficient charge recovery logic(ECRL).
Multiple Mutations and Overexpression in the CYP51A and B Genes Lead to Decreased Sensitivity of Venturia effusa to Tebuconazole

Multiple demethylation-inhibiting (DMI) fungicides are used to control pecan scab, caused by Venturia effusa. To compare the efficacy of various DMI fungicides on V. effusa, field trials were conducted at multiple locations applying fungicides to individual pecan terminals. In vitro assays were conducted to test the sensitivity of V. effusa isolates from multiple locations to various concentrations of tebuconazole. Both studies confirmed high levels of resistance to tebuconazole. To investigate the mechanism of resistance, two copies of the CYP51 gene, CYP51A and CYP51B, of resistant and sensitive isolates were sequenced and scanned for mutations. In the CYP51A gene, mutation at codon 444 (G444D), and in the CYP51B gene, mutations at codon 357 (G357H) and 177 (I77T/I77L) were found in resistant isolates. Expression analysis of CYP51A and CYP51B revealed enhanced expression in the resistant isolates compared to the sensitive isolates. There were 3.0- and 1.9-fold increases in gene expression in the resistant isolates compared to the sensitive isolates for the CYP51A and CYP51B genes, respectively. Therefore, two potential mechanisms—multiple point mutations and gene over expression in the CYP51 gene of V. effusa isolates—were revealed as likely reasons for the observed resistance in isolates of V. effusa to tebuconazole.
Mobile Internet Access and the Desire to Emigrate

In this paper, we present theory and global evidence on how mobile internet access affects desire and plans to emigrate. Our theory predicts that mobile internet access increases desire and plans to emigrate. Our empirical analysis combines survey data on 606,827 individuals from 2,107 subnational districts in 110 countries with data on worldwide 3G mobile internet rollout from 2008 to 2018. We show that an increase in mobile internet access increases the desire and plans to emigrate. Instrumenting 3G rollout by lightning strike intensity and previous 2G infrastructure suggests that the effects are causal. The effect on the desire to emigrate is particularly strong in high-income countries and for above-median-income individuals in lower-middle-income countries. In line with our theory, an important mechanism is that access to the mobile internet lowers the cost of acquiring information on potential destinations. In addition to this, increased internet access reduces perceived material well-being and trust in government. Using municipal-level data from Spain, we also document that 3G rollout increased actual migration flows.
UDK 630*235: 632.95(497.6) USE OF PETICIDES IN FOREST NURSERIES IN THE TERRITORY OF FEDERATION OF BOSNIA AND HERZEGOVINA Upotreba pesticida u šumskim rasadnicima na području Federacije Bosne i Hercegovine

Seedlings are produced by implementation of technical-technological procedures at specially prepared area which we call nurseries. With produced seedlings is additionally completed natural restoration of forests, forestation of bare lands, and plantations are established, melioration of degraded forest and brush-wood is conducted, eroded lands are repaired, etc. In the actual Registry of the Ministry of Agriculture, Water Management and Forestry of Federation of Bosnia and Herzegovina are registered 11 nurseries which produce forest and horticultural seedlings. In their production program dominant are three conifer tree species: Norway spruce (Picea abies), Scots pine (Pinus silvestris) and Black pine (Pinus nigra). Seedlings of broadleaves tree species in total production participate with only 2%. In nurseries is implemented the concept of integral protection of plants in the form of program which is consisted of combination of agrotechnical, mechanical, physical, biological and chemical measures. Chemical measures are based on the use of pesticides in integral protection of plants. Pesticides are organic and non-organic chemical compounds, as well as the products of living organisms which are used in agriculture and forestry for prevention of occurrence, control and suppression of caused of plant diseases, pest and weed, as well as for protection of agricultural and food products. Main goal of this research was to identify the quantity indicators of use of pesticides in production of seedlings of forest trees in forest nurseries in Federation of Bosnia and Herzegovina. The research has covered three nurseries in Zenica-Doboj Canton and three nurseries in Central-Bosnia Canton. The research is related to the period from 2007 to 2011.