Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining the language of solitude versus loneliness in tweets

People have widely different experiences of being alone. Sometimes being alone is relaxing and restorative other times it gives way to feelings of loneliness. Researchers conceptually distinguish between solitude, which tends to be viewed more positively, and loneliness, which is more negative. However, it is unclear whether these terms are used differently in everyday language. We sought to compare the emotional content of over 19 million tweets containing the terms solitude and lonely/loneliness. Using a computational linguistics approach, we found that solitude tends to be used in more positive and less emotionally activated (i.e., lower arousal) contexts compared to lonely. We also found that the word alone tends to be used somewhat differently from solitude and lonely. These results have implications both for how we understand different experiences of time alone in general and for what kind of language we should use when discussing these experiences.
Examining cognitive diagnostic modeling in classroom assessment conditions

Abstract Cognitive diagnostic models (CDMs) are a family of psychometric models designed to provide categorical classifications for multiple latent attributes. CDMs provide more granular evidence than other psychometric models and have potential for guiding teaching and learning decisions in the classroom. However, CDMs have primarily been conducted using large samples. This study examines estimating CDMs in small sample conditions to aid formative learning. Three CDMs were compared across simulated classroom assessment conditions: deterministic input, noisy "and" gate (DINA) model, non-parametric cognitive diagnosis (NPCD), and supervised artificial neural network (SANN). We found all models estimated examinee classifications at the smallest sample size. Accuracy of individual attribute mastery classifications was acceptably high for the models under certain conditions. Effective item discrimination was the most important factor to accurately classify. The DINA and NPCD models were more resilient to measurement error than the SANN. Recommendations for application of CDMs in the classroom are provided.
Efficient and Privacy-Preserving Multi-User Outsourced K-Means Clustering

In recent years, with the development of the Internet, the data on the network presents an outbreak trend. Big data mining aims at obtaining useful information through data processing, such as clustering, clarifying and so on. Clustering is an important branch of big data mining and it is popular because of its simplicity. A new trend for clients who lack of storage and computational resources is to outsource the data and clustering task to the public cloud platforms. However, as datasets used for clustering may contain some sensitive information (e.g., identity information, health information), simply outsourcing them to the cloud platforms can't protect the privacy. So clients tend to encrypt their databases before uploading to the cloud for clustering. In this paper, we focus on privacy protection and efficiency promotion with respect to k-means clustering, and we propose a new privacy-preserving multi-user outsourced k-means clustering algorithm which is based on locality sensitive hashing (LSH). In this algorithm, we use a Paillier cryptosystem encrypting databases, and combine LSH to prune off some unnecessary computations during the clustering. That is, we don't need to compute the Euclidean distances between each data record and each clustering center. Finally, the theoretical and experimental results show that our algorithm is more efficient than most existing privacy-preserving k-means clustering.
Analysis on floral nectar characteristics among the selected black locust (Robinia spp.) individuals

This study aimed to determine the value of honey source on Robinia by analyzing flower morphology and nectar characteristics in floral nectar of eight selected individuals. The mean nectar volume secreted by genus Robinia was 1.7 ± 1.0 µL. Among the samples, PR (R. margaretta) and HR (R. pseudoacacia) secreted the highest and lowest nectar volumes—3.0 ± 1.1 and 1.1 ± 0.7 µL, respectively. The mean sugar concentration was 44.8 ± 6.1% (range, 40.1–51.4%). The ANOVA results revealed a statistically significant difference in nectar volume and sugar concentration among the eight individuals (p < 0.05). The free sugar content ranged from 0.39 (HR) to 0.78 (KR) mg/μL, and nectar sugar contents ranged from 0.31 (HR) to 1.53 (PR) mg per flower. The sucrose/hexose ratio ranged from 0.5 to 3.6, and sucrose was high in all samples. The results of the Kruskal-Wallis H test revealed significant differences in free sugar content (mg/µL), nectar sugar content per flower and sucrose/hexose ratio (p < 0.05). There were close correlations between nectar characteristics and flower morphology as followed; 1) nectar volume and nectar sugar content per flower (r = 0.976), 2) nectar volume and calyx length (r = 0.952), 3) sugar concentration in nectar and length of inflorescence (r = 0.952). Asparagine was the most abundant (average; 60.2%) amino acid, followed in decreasing order by alanine (6.9%), glutamine (5.2%), and serine (4.7%). The results of Kruskal-Wallis H tests showed that the rate of amino acids of alanine, glutamine, glutamic acid, and arginine significantly differed among the samples (p < 0.05).
Decoupling of Microstrip Antennas With Defected Ground Structure Using the Common/Differential Mode Theory

A compact structure with slot splitting meandered lines defected ground is proposed to reduce the mutual coupling between two microstrip antennas with a center-to-center distance of 0. 38λ. The meandered line defected ground structure is symmetrically etched on the ground between the microstrip antennas. The proposed structure is optimized and explained by the common/differential mode theory. For experimental verification, the structure is fabricated and measured. Simulation and measurement results with excellent agreement show that the mutual coupling can be reduced significantly using the proposed structure. In addition, significant improvement is achieved in radiation efficiency, realized gain, and the decoupled array's envelope correlation coefficient.
CFD-DEM Numerical Simulation and Experimental Validation of Heat Transfer and Two-Component Flow in Fluidized Bed

Abstract Based on the improved computational fluid dynamics and discrete element method (CFD-DEM), heat transfer and two-component flow of biomass and quartz sand have been studied from experiments and numerical simulation in this paper. During experiments, the particle temperature and moving images are respectively recorded by infrared thermal imager and high speed camera. With the increase of the velocity, the mixing index (MI) and the cooling rate of the particles are rising. Due to larger heat capacity and mass, the temperature of biomass drops slower than that of quartz sand. Fictitious element method is employed to solve the incompatibility of the traditional CFD-DEM where the cylindrical biomass are considered as an aggregation of numerous fictitious sphere particles arranged in certain sequence. By the comparison of data collected by infrared thermal imager and the simulated results, it can be concluded that experimental data is basically agreement with numerical simulation results. Directly affected by inflow air (25℃), the average temperature of particles in the bed height area (h >30 mm) is about 3 degrees lower than that of the other heights. When the superficial gas velocity is larger, the fluidization is good, and the gas temperature distribution is more uniform in the whole area. On the contrary, bubbles are not easy to produce and the fluidization is restricted at lower superficial gas velocity. Gas-solid heat transfer mainly exists under the bed height of 10 mm, and decreases rapidly on fluidized bed height. The mixing index (MI) is employed to quantitatively discuss the mixing effectiveness, which first rises accelerate, then rising speed decreases, finally tends to a upper limit.
Crisis and populism: a comparative study of populist and non-populist candidates and rhetoric in the news media coverage of election campaigns

ABSTRACT This research investigates links between the Euro Crisis and populism and asks whether there are patterns of populism in different election campaigns, namely is there country-specific populist rhetoric or similar anti-elite criticisms? Through content analysis, we examine the mainstream media coverage of populist and non-populist actors in the countries that were most affected by the Euro Crisis (Greece, Ireland, Portugal, Spain) and in Poland, a country that, despite not being part of the Euro, has been experiencing a significant rise of populism recently. These are also countries underrepresented in systematic empirical political communication research and that represent different levels of success of populism. Our findings show that although mainstream news media tends to be negative towards populist candidates, there are important cross-country differences with potential impact on the electoral success and failure of populist actors.
Experimental Investigation on the Mechanical Properties of a Sandwich Structure Made of Flax/Glass Hybrid Composite Facesheet and Honeycomb Core

This research is aimed at developing the sandwich structure with a hybrid composite facesheet and investigate its mechanical properties (tensile, edgewise compression, and flexural). The combination of renewable and synthetic materials appears to reduce the weight, cost, and environmental impact compared to pure synthetic materials. The hybrid composite facesheets were fabricated with different ratios and stacking sequence of flax and glass fibers. The nonhybrid flax and glass composite facesheet sandwich structures were fabricated for comparison. The overall mechanical performance of the sandwich structures was improved by increasing the glass fiber ratio in the hybrid composites. The experimental tensile properties of the hybrid facesheet and the edgewise compression strength and ultimate flexural facing stress of the hybrid composites sandwich structures were achieved higher when the results were normalized to the same fiber volume fraction of glass composite. The hybrid composite sandwich structure showed improved compression and flexural facing stress up to 68% and 75%, respectively, compared to nonhybrid flax composites. The hybrid composite using glass in the outer layer achieved the similar flexural stiffness of the nonhybrid glass composite with only a 6% higher thickness than the glass composite sandwich structure.
CSNet: Cascade stereo matching network using multi‐information cost volume

The disparity map produced by matching a pair of rectiﬁed stereo images provides estimated depth information and accurate distance calculations for autonomous driving. For most stereo matching networks, cost volume plays a crucial role in the accuracy of disparity maps. To increase the accuracy of disparity maps, an improved cost volume method called multi-information cost volume (MICV) is proposed, with the fusion of concatenation volume and improved correlation volume, which is calculated both in inner product space and Euclidean space, to measure the correlation similarity between features in the left and right images. The inclusion of a squeeze and excitation (SE) module further improves MICV by adjusting the contribution of the correlation volume. To reﬁne the disparity map and enhance the semantics of small objects, a cascade stereo network called CSNet is proposed, with a dilation feature fusion unit (DFFU) to calculate and integrate disparity maps from three different scale branches. The smaller scale branches are gradually integrated into the larger scale branches to implement the transmission of semantic information. The proposed method was evaluated using several established benchmarks including the Sceneow, KITTI2012 and KITTI2015 datasets. Experimental results demonstrate that authors’ method produces more accurate disparity maps compared with existing state-of-the-art methods.
Sources of Subseasonal‐To‐Seasonal Predictability of Atmospheric Rivers and Precipitation in the Western United States

Atmospheric rivers (ARs) account for a large portion of winter precipitation in the western US. To evaluate the sources of AR and precipitation predictability at subseasonal‐to‐seasonal timescales, we examine the relationships between two climate modes, the El Niño/Southern Oscillation (ENSO) and Madden‐Julian oscillation (MJO), and winter hydroclimate in the western US. Our analysis uses a large ensemble of the Weather Research and Forecast (WRF) model simulations from 1981 to 2017, facilitating the assessment of uncertainty in climate mode‐AR relationship due to climate variability and short length of observations. Over the North Pacific basin, we find ENSO‐related latitudinal shifts of ARs, but ENSO has little effect on basin‐wide averaged AR frequency. Over the western US, there is some uncertainty in the ENSO‐AR connection due to the impacts of ENSO indices and datasets. However, extreme El Niño events defined by the ENSO longitude index are consistently linked to increased landfalling AR activity. The MJO can lead to significantly enhanced or suppressed landfalling AR activity in the large‐ensembles, depending on the phase of MJO and time lag, while observations are too short in length to robustly show this signal. ENSO substantially modulates the MJO‐AR relationship, triggering variegated responses of landfalling ARs and AR precipitation in La Niña and El Niño years. Our findings highlight the need to evaluate concurrent effects of different climate modes on ARs and precipitation, and may shed light on a path toward more accurate subseasonal‐to‐seasonal prediction of ARs and precipitation over the western US.
Comparison of quantitative and qualitative scoring approaches for radiation-induced pulmonary fibrosis as applied to a preliminary investigation into the efficacy of mesenchymal stem cell delivery methods in a rat model

Objectives: Compare a quantitative, algorithm-driven, and qualitative, pathologist-driven, scoring of radiation-induced pulmonary fibrosis (RIPF). And using these scoring models to derive preliminary comparisons on the effects of different mesenchymal stem cell (MSC) administration modalities in reducing RIPF. Methods 25 rats were randomized into 5 groups: non-irradiated control (CG), irradiated control (CR), intraperitoneally administered granulocyte-macrophage colony stimulating factor or GM-CSF (Drug), intravascularly administered MSC (IV), and intratracheally administered MSC (IT). All groups, except CG, received an 18 Gy conformal dose to the right lung. Drug, IV and IT groups were treated immediately after irradiation. After 24 weeks of observation, rats were euthanized, their lungs excised, fixed and stained with Masson’s Trichrome. Samples were anonymized and RIPF was scored qualitatively by a certified pathologist and quantitatively using ImageScope. An analysis of association was conducted, and two binary classifiers trained to validate the integrity of both qualitative and quantitative scoring. Differences between the treatment groups, as assessed by the pathologist score, were then tested by variance component analysis and mixed models for differences in RIPF outcomes. Results: There is agreement between qualitative and quantitative scoring for RIPF grades from 4 to 7. Both classifiers performed similarly on the testing set (AUC = 0.923) indicating accordance between the qualitative and quantitative scoring. For comparisons between MSC infusion modalities, the Drug group had better outcomes (mean pathologist scoring of 3.96), correlating with significantly better RIPF outcomes than IV [lower by 0.97, p = 0.047, 95% CI = (0.013, 1.918)] and resulting in an improvement over CR [lower by 0.93, p = 0.037, 95% CI = (0.062, 1.800]. Conclusion: Quantitative image analysis may help in the assessment of therapeutic interventions for RIPF and can serve as a scoring surrogate in differentiating between severe and mild cases of RIPF. Preliminary data demonstrate that the use of GM-CSF was best correlated with lower RIPF severity. Advances in knowledge Quantitative image analysis can be a viable supplemental system of quality control and triaging in situations where pathologist work hours or resources are limited. The use of different MSC administration methods can result in different degrees of MSC efficacy and study outcomes.
A Photochemical Method for Light and Electronmicroscopy

Summary. A detailed description is given of a method by which gold can be visualized in frozen, paraffin and Epon sections. Histological sections from animals treated with gold compounds are exposed to UV-light from 30 min to several hours. The reduced, metallic gold is then visualized by means of a photographic developer containing silver lactate. Light- and electronmicroscope photographs showing gold in different organs from rats and mice treated with aurothioglucose, aurothiosulfate and aurothiomalate are presented.
SINTESIS SURFAKTAN METIL ESTER SULFONAT (MES) DARI METIL LAURAT

Synthesis of surfactant methyl ester sulfonate (MES) of methyl laurate has been done. This study aims to determine the best mole ratio between the methyl esters of lauric acid with sulfonated agent NaHSO3 in sulfonated methyl laurate. Mole variation used in this study are 1:1; 1:1,2; 1:1,4 and 1;1,6 (v/w). Best value MES emulsion stability, acid value and the surface tension is 94,5 minutes,1.3 ml KOH/ g sample, 39.3 dyne/cm in 1:4 ratio produces. MES synthesis produced by sulfonate group shown in the FTIR spectra in the wave number around 1366.52 to 1015.30 cm.
The Judgement for Development of Virtual Surgical Planning and Three-Dimensional Bio-Printing for Superior Reconstruction of Mandibular Defect by Fibular Graft on Head-Neck Cancer

Oncological resection of the mandible creates a miserable aesthetical and functional deficit that results in physical, functional, nutritional as well as psychosocial impairments compromising the patient’s residual life standard. Corrections of these types of defects require a compound plan. Hidalgo in 1989 first documented the utilization of the free fibula flap for mandibular reconstruction. This technique was quickly well-received due to its obvious advantages, as the flap provides a considerable length of bone (up to 25 cm), adequately sized pedicle, low donor site morbidity, and capability of complex anterolateral defect reconstruction. Additionally, it included an unmatched ability to allow sufficient periosteal blood supply after osteotomy for the reconstruction of composite deThe Judgement for Development of Virtual Surgical Planning and Three-Dimensional Bio-Printing for Superior Reconstruction of Mandibular Defect by Fibular Graft on Head-Neck Cancer
Mediating Role of Social Self efficacy in linking Positive Thinking to Satisfaction with Life among First Year University Students

Objective: Present study was an attempt to examine how social self-efficacy plays a role in developing positive thinking among university freshers with regards to the challenges that have to be faced in the new University setup. It also aimed to find out if the freshly enrolled University students were satisfied with their lives. Positive thinking changes the way of how an individual live a life. By changing one’s thoughts about different perspective into positive ones overcoming challenges of life becomes easier. Consequently, with positive thoughts people feel socially strong and satisfied with life. Method: In the present study, total 480 (Boys=218 Girls=262) newly admitted students in Undergraduate Programs from Faculty of Social sciences, Bahauddin Zakariya University Multan, Pakistan with age range of 17-22 years (M=18.57 & SD=.835) participated. Participants responded on Life Oriented Test- Revised [LOT-R (Scheier et al. 1994)], Social Self-Efficacy Scale [SSES (Muris, 2001)] and Satisfaction with Life Scale [SWLS (Diener et al., 1985)] respectively. Data analyses consisted of Pearson product moment correlation coefficient and linear regression by utilizing SPSS (25.0) whereas Process Macro 3.5. 0 was used to verify mediation model. Results: Findings indicated that positive thinking does not predict satisfaction with life directly whereas it significantly predicts social self-efficacy (path a) and social self-efficacy predicts satisfaction with life (path b). Thus, results showed that social self-efficacy fully mediates the relationship of positive thinking with satisfaction in life among students. Conclusion: Social self-efficacy has been found as an imperative facet of students’ life so it should be considered while designing curricula and other activities related to students. Keywords: Positive thinking, Satisfaction with life, Social self-efficacy, University freshers.
Updating and Organizing Our Knowledge of Risk and Protective Factors for Lone-Actor Terrorism1

This chapter updates builds upon previous descriptive analyses of lone-actor terrorists, their behaviours, ideological backgrounds and degrees of ‘loneness’. It offers greater conceptual clarity, updated data and a more expansive set of variables from previous analyses. Individual vulnerability indicators examined here include potential indicators of cognitive susceptibility to moral change, and self-selection and social selection into radicalizing settings, notably membership of a social network containing one or more radicalized individual. We also examine exposure settings, attack-preparation behaviours and explore sub-set analyses of the data. The analyses informed by a Risk Analysis Framework which offers a multilevel, integrated meta-model of these events and allows for the synthesis of disparate findings. The analyses provide key insights into the behaviour of lone-actors, which could inform intelligence gathering and investigative practice, as such analyses already do in other crime prevention domains.
Mental Health Consultations on College Campuses: Examining the Predictive Ability of Social Media

The mental health of college students is a growing concern, and gauging the mental health needs of college students is difficult to assess in real-time and in scale. While social media has shown potential as a viable “passive sensor” of mental health, the construct validity and in-practice reliability of such computational assessments remain largely unexplored. Towards this goal, we study how assessing the mental health of college students using social media data correspond with ground-truth data of on-campus mental health consultations. For a large U.S. public university, we obtained ground-truth data of on-campus mental health consultations between 2011–2016, and collected 66,000 posts from the university’s Reddit community. We adopted machine learning and natural language methodologies to measure symptomatic mental health expressions of depression, anxiety, stress, suicidal ideation, and psychosis on the social media data. Seasonal auto-regressive integrated moving average (SARIMA) models of forecasting on-campus mental health consultations showed that incorporating social media data led to predictions with r=0.86 and SMAPE=13.30, outperforming models without social media data by 41%. Our language analyses revealed that social media discussions during high mental health consultations months consisted of discussions on academics and career, whereas months of low mental health consultations saliently show expressions of positive affect, collective identity, and socialization. This study reveals that social media data can improve our understanding of college students’ mental health, particularly their mental health treatment needs.