Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-effects of user-generated messages on pro-environmental identity

Abstract An experiment tested whether user-generated pro-environmental messages (UGC) enhanced environmental self-identity among message creators. Participants were randomly assigned to create a message about saving energy, view a message with similar content ostensibly created by similar others, or view irrelevant messages. Those who created their own messages had greater post-message self-identity than those in the other two conditions. Additionally, those who created their own messages had greater post-message intentions to save energy in the near future than those in the other two conditions, and behavioral intentions were positively correlated with self-identity. Implications for campaigns and educational efforts are discussed.
Durbin-Watson Statistic For The Least Trimmed Squares

The famous Durbin-Watson statistic is studied for the residuals from the least trimmed squared regression analysis. Having proved asymptotic linearity of corresponding functional (namely sum of h smallest squared residuals), an asymptotic representation of the least trimmed squares estimator is established. It is then used to modify D-W considerations which led to the analytically tractable form of D-W statistic. It appeared that in the modified D-W statistic for the least trimmed squares the terms which are different from the terms appearing in D-W statistic for the ordinary least squares, contain only a finite number of summands. Since all these terms are uniformly with respect to the number of observations bounded in probability, it is clear that asymptotically both versions, the first one for the ordinary least squares and the second for the least trimmed squares, are equivalent. Nevertheless some rough analysis of behaviour for finite samples is included at the end of paper.
GALAXIES PROBING GALAXIES AT HIGH RESOLUTION: CO-ROTATING GAS ASSOCIATED WITH A MILKY WAY ANALOG AT z = 0.4

We present results on gas flows in the halo of a Milky-Way-like galaxy at z = 0.413 based on high-resolution spectroscopy of a background galaxy. This is the first study of circumgalactic gas at high spectral resolution toward an extended background source (i.e., a galaxy rather than a quasar). Using long-slit spectroscopy of the foreground galaxy, we observe spatially extended Hα emission with a circular rotation velocity km s−1. Using echelle spectroscopy of the background galaxy, we detect and absorption lines at an impact parameter kpc that are blueshifted from systemic in the sense of the foreground galaxy’s rotation. The strongest absorber ( Å) has an estimated column density ( cm−2) and line-of-sight velocity dispersion ( km s−1) that are consistent with the observed properties of extended disks in the local universe. Our analysis of the rotation curve also suggests that this gaseous disk is warped with respect to the stellar disk. In addition, we detect two weak absorbers in the halo with small velocity dispersions ( km s−1). While the exact geometry is unclear, one component is consistent with an extraplanar gas cloud near the disk–halo interface that is co-rotating with the disk, and the other is consistent with a tidal feature similar to the Magellanic Stream. We can place lower limits on the cloud sizes ( kpc) for these absorbers given the extended nature of the background source. We discuss the implications of these results for models of the geometry and kinematics of gas in the circumgalactic medium.
Raman Scattering and Nd<formula formulatype="inline"><tex>$^{3+}$</tex> </formula> Laser Operation in NaLa(WO<formula formulatype="inline"> <tex>$_{4}$</tex></formula>)<formula formulatype="inline"><tex>$_{2}$</tex> </formula>

The continuous-wave laser operation of Nd-doped tetragonal NaLa(WO 4)2 crystal is studied at room temperature by optical pumping in the spectral region overlapping AlGaAs diode laser emission. This crystal has inhomogeneously broadened optical bands. From the room-temperature spectroscopic parameters determined it is found that the optimum Nd concentration for the 4F3/2rarr4IJ laser channels must be in the 3-5 at. % range. For J=11/2 and 13/2 channels (lambdaap1.06 and 1.3 mum) the most favourable polarization configuration is parallel to the crystallographic c axis, while for J=9/2 little polarization dependence of the laser efficiency is predicted. Laser operation was achieved with a 3.35 at. % Nd-doped sample grown by the Czochralski method. The laser operation was tested in an hemispherical optical cavity pumped by a Ti:sapphire laser. Stimulated emission at lambda=1056 nm was achieved for a wide spectral pumping range, lambda=790-820 nm. Stimulated Raman scattering was achieved in the picosecond regime with an efficiency similar to that of monoclinic KY(WO4)2 reference compound
Effect of Impulsive Noise on IRS-Aided Communication Systems

Recent studies have explored the potential benefits of the intelligent reflecting surface (IRS) in different wireless communication scenarios. However, no work has quantitatively analyzed the performance of IRS-aided communication systems impaired by non-Gaussian noise. In this article, motivated by this research gap, we study the effect of impulsive noise on IRS-aided communication systems. Specifically, the channel impairments are modeled by Middleton's class A noise (MCA) and Weibull fading. By leveraging the Laguerre series, accurate channel distributions are derived. Building upon these expressions, new closed-form expressions of average bit-error-rate (BER), average channel capacity (ACC), and outage probability (OP) are obtained. To gain further insight into the system performance at high signal-to-noise ratio (SNR) regime, the asymptotic expressions of BER, OP, and ACC are derived. In addition, a tight upper bound of ACC is obtained. The effect of the impulsive index $ (A)$ on the systems performance metrics is investigated for different parameter settings. Moreover, it is shown that IRS-assisted communication systems outperforms a multi-hop relaying network impaired by impulsive noise. The results reveal that the system performance impaired by impulsive noise can be significantly improved by increasing the reflecting elements (REs). The derived expressions are in excellent agreement with Monte-Carlo simulations.
Effect of Hoku point massage on postpartum afterpains intensity among multiparous women

Afterpains are high prevalent complaints. They lead to neuro-hormonal stress responses. Hoku point massage is used to relieve afterpains. Objective: determine the effect of Hoku point massage on postpartum afterpains intensity among multiparous women. Material and Methods: A quasi-experimental design was conducted at El-Shatby Maternity Hospital. A purposive sample of 100 women who were meeting the inclusion criteria. The control group was receiving routine hospital care and the experimental group was receiving Hoku point massage. Results: statistically significant difference was found between the control and experimental group regarding socio-demographic and reproductive data as well as physiological stability, as evidenced by vital signs, while there was a highly statically significant difference between the control and experimental groups in the favor of Hoku point massage. Conclusions and recommendations: Hoku point massage was effective in the reduction of postpartum afterpains intensity. multiparous women who receive Hoku point massage showed observable behaviors indicating less afterpains intensity than those who do not receive it. Researchers recommended that strict protocols should be established in maternity care units for a comprehensive and routine assessment of afterpains. Further studies should be conducted to verify the findings of this study.
ASSESSMENT OF SMALL-HOLDER RICE FARMERS’ ADOPTION LEVEL OF CLIMATE-SMART AGRICULTURAL PRACTICES IN KWARA STATE, NIGERIA

The study assessed the adoption level of climate-smart agricultural practices by smallholder rice farmers in Kwara State, Nigeria. Cross-sectional survey approach was adopted. A multistage sampling procedure was used to selected 424 samples from the population of 3,727 smallholder rice farmers from the three agricultural zones in Kwara State. Four research questions were raised. Interview schedule was designed by the researcher as instrument for data collection. Data collected was analysed using descriptive statistics in form of percentage, frequency counts, mean and standard deviation. The results indicated high adoption of climate-smart agricultural practices in the study area. It is recommended that Kwara State Government and Non-governmental organizations should provide incentives inform of subsidized inputs to farmers.
Religious Education for Schools Within Conflict-Prone Zones: An Inclusive Multicultural Approach

The multicultural approach plays a vital role in learning religious education in order to recognize the diversity that exists, especially in conflict-prone zone schools. This study aims to describe a multicultural approach in learning religious education in conflict-prone zones. Through exercising Garfinkel’s ethnomethodology analysis, this qualitative research was conducted at SMAN 2 Pasaman and SMAN 1 Luhak Nan Duo senior high schools within conflict-prone zones of West Pasaman, West Sumatra. The dynamics of school philosophy towards inclusive multicultural approaches in religious education for schools in conflict-prone zones indicated that academic culture within said schools must be capable of creating a more harmonious atmosphere among ethnic diversities, mainly that of Javanese, Minangkabaunese, and Bataknese. The application of multicultural approaches in religious education for such schools in conflict-prone zones showed that the planning, implementation, and evaluation of religious education must be carried out while simultaneously considering the diversity of these ethnicities. The employment of an inclusive multicultural approach in association with schools in conflict-prone zones showed that the school’s physical environment is strategic for the interaction of various ethnicities, such as with Javanese, Minang, and Batak ethnicities at SMAN 2 Pasaman and SMAN 1 Luhak Nan Duo. This research is useful as input in making and improving policies by schools and the government regarding the implementation of religious education with a multicultural approach in conflict-prone zone schools.
Characteristics of Particleboard from Sorghum and Nypa Fruit Skin Fiber Bonded with Citric Acid-Sucrose Adhesive

Sorghum (Sorghum bicolor L.) and nypa fruit skin fiber (Nypa fruticans Wurmb.) can be used as raw materials in the manufacture of eco-friendly particleboard (PB) using natural adhesives based on citric acid and sucrose. This study aimed to determine the characteristics of PB from sorghum and nypa fruit skin fiber using citric acid-sucrose adhesive and also to determine the optimum composition of raw materials and adhesives in the manufacture of PB. The PB panel was made by mixing raw materials and adhesives with variations in the composition of nypa fruit skin fiber:sorghum raw materials 100:0, 25:75, 50:50, and 0:100, and variations in the concentration of citrate-sucrose adhesive were 20% and 30%. The target dimensions and density of PB were 25 cm x 25 cm x 0.9 cm and 0.8 g/cm3, respectively. The PB was hot-pressed for 10 min at 200oC with a pressure of 11 MPa. The physical and mechanical properties of PB were determined using the Japanese Industrial Standard (JIS) A 5908:2003 standard. The results showed that the PB has average values of moisture content of 11.94%, density of 0.79 g/cm3, water absorption of 52.96%, thickness swelling of 13.21%, modulus of elasticity of 1029.55 N/mm2, modulus of rupture of 6.46 N/mm2, internal bonding of 0.18 N/mm2, and screw holding power of 43.12 N. Variation of raw materials composition has a significant effect moisture content, water absorption, thickness swelling, modulus of elasticity, and modulus of rupture. Applying 30% adhesive content significantly affected water absorption, thickness swelling, and screw holding power. Keywords: citric acid-sucrose, nypa fruit skin, particleboard, sorghum
Are reported accuracies in the clinical speech machine learning literature overoptimistic?

Building clinical speech analytics models that will reliably translate in-clinic requires a realistic characterization of their performance. So, how well do we estimate the accuracy of published models in the literature? We evaluate the relationship be-tween sample size and reported accuracy across 77 journal publications that use speech to classify between healthy controls and patients with dementia. The studies are combined across three meta-analyses that use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. The results show that reported accuracy declines as a function of increasing sample size, with small sample size studies yielding an overoptimistic estimate of the accuracy. For correctly trained models, this is unexpected as the ability of a machine learning model to predict group membership ought to remain the same or improve with additional training data. We posit that the overoptimism is the result of a combination of publication bias and overfitting and suggest mitigation strategies.
Towards Automated Dialog Personalization using MBTI Personality Indicators

As conversational interfaces mature in both capacity and usage, the need to personalize towards specific user characteristics becomes apparent, in order to improve users’ acceptance, satisfaction and trust in the conversations. We utilize the concept of Myers-Briggs personality type indicators in order to adapt chatbot behavior. In a user study, we investigate the impact and realization of the so-called “law of attraction” by providing users with a chatbot that mirrors their own personality. This entails predicting the personality from the user behavior, in this work chat messages, by utilizing a pre-trained language model rather than composing many resources like lexicons. We conduct a user study with aligned and misaligned personality and analyze the effect on usability. Results show that alignment significantly improves major usability factors such as satisfaction, perceived naturalness, recommendation likelihood, appropriateness and trustworthiness of our interaction. Further, comparing different language models, contrastive learning approaches outperform previous methods. Predicting the thinking vs. feeling and in-troversion vs. extroversion indicator dichotomies, we achieve 76.14% F 1 and 69.11% F 1 , respectively, with setting a new state-of-the-art performance in the literature for the former. Finally, our work adds transparency to the design of linguistic personality cues, hitherto rarely reported in the literature.
Stars as Laboratories for Fundamental Physics: The Astrophysics of Neutrinos, Axions, and Other Weakly Interacting Particles

Preface Acknowledgments 1: The Energy-Loss Argument 2: Anomalous Stellar Energy Losses Bounded by Observations 3: Particles Interacting with Electrons and Baryons 4: Processes in a Nuclear Medium 5: Two-Photon Coupling of Low-Mass Bosons 6: Particle Dispersion and Decays in Media 7: Nonstandard Neutrinos 8: Neutrino Oscillations 9: Oscillations of Trapped Neutrinos 10: Solar Neutrinos 11: Supernova Neutrinos 12: Radiative Particle Decays from Distant Sources 13: What Have We Learned from SN 1987A? 14: Axions 15: Miscellaneous Exotica 16: Neutrinos: The Bottom Line App. A. Units and Dimensions App. B. Neutrino Coupling Constants App. C. Numerical Neutrino Energy-Loss Rates App. D. Characteristics of Stellar Plasmas References Acronyms Symbols Subject Index
Isosorbide and 2,5-Furandicarboxylic Acid Based (Co)Polyesters: Synthesis, Characterization, and Environmental Degradation

Poly(2,5-furandicarboxylate)s incorporating aliphatic moieties represent a promising family of polyesters, typically entirely based on renewable resources and with tailored properties, notably degradability. This study aims to go beyond by developing poly(isosorbide 2,5-furandicarboxylate-co-dodecanedioate) copolyesters derived from isosorbide (Is), 2,5-furandicarboxylic acid (FDCA), and 1,12-dodecanedioic acid (DDA), and studying their degradation under environmental conditions, often overlooked, namely seawater conditions. These novel polyesters have been characterized in-depth using ATR-FTIR, 1H, and 13C NMR and XRD spectroscopies and thermal analysis (TGA and DSC). They showed enhanced thermal stability (up to 330 °C), and the glass transition temperature increased with the content of FDCA from ca. 9 to 60 °C. Regarding their (bio)degradation, the enzymatic conditions lead to the highest weight loss compared to simulated seawater conditions, with values matching 27% vs. 3% weight loss after 63 days of incubation, respectively. Copolymerization of biobased FDCA, Is, and DDA represents an optimal approach for shaping the thermal/(bio)degradation behaviors of these novel polyesters.
Novel Augmentation Schemes for Device Robust Acoustic Scene Classification

For audio classiﬁcation tasks, one has access to the recordings from only a few microphones while the system could be deployed for a wider range of microphones. This paper discusses augmentation methods for audio scene recognition with the aim of improving performance on recordings from unseen micro-phones. The proposed augmentation schemes can be broadly classiﬁed into two categories. The ﬁrst category, which is called the frequency response augmentation technique, aims to artiﬁ-cially generate ‘new’ microphone frequency responses. This is achieved by collecting microphone impulse responses from a publicly available library and applying image augmentation techniques on them to create a more diverse set of frequency responses. The train data is then augmented with these arti-ﬁcially generated frequency responses. The second category consists of the amplitude augmentation and random frame drop methods which are simple yet effective in further boosting the performance. We test all these augmentation methods on various architectures and observe a good classiﬁcation accuracy of 76.0% on the DCASE 2020 Task 1a set. Especially on unseen devices our best reported accuracy, without using any model ensembles, is 74.24%.
Influence of Climate Change and Meteorological Factors on Houston’s Air Pollution: Ozone a Case Study

We examined the past 23 years of ground-level O3 data and selected meteorological parameters in Houston, Texas, which historically has been one of the most polluted cities in the United States. Both 1-h and 8-h O3 exceedances have been reduced significantly down to single digit yearly occurrences. We also found that the frequency of southerly flow has increased by a factor of ~2.5 over the period 1990-2013, likely suppressing O3 photochemistry and leading to a "cleaner" Houston environment. The sea breeze was enhanced greatly from 1990 to 2013 due to increasing land surface temperatures, increased pressure gradients, and slightly stronger on-shore winds. These patterns driven by climate change produce a strengthening of the sea breeze, which should be a general result at locations worldwide.
Characteristics and outcomes of COVID-19 patients assisted by intensivists and nonintensivists

SUMMARY OBJECTIVE: The aim of this study was to assess the outcomes of critically ill patients with COVID-19 in an intensive care unit seen by a care team formed by intensive and nonintensive physicians and treatment guided by processes and protocols linked to the “choosing wisely” concept, comparing them with similar data recently published. METHODS: An observational cohort including adult patients with COVID-19 admitted to the intensive care unit of Hospital Independence between August 2020 and August 2021. Inclusion criteria were 18 years of age or older and there were no exclusion criteria. RESULTS: The study included 449 patients, of which 64.1% were referred from the ward, 21.6% from emergency rooms, and 14.2% from another hospital (continuity of attendance). The overall mortality was 48.5%, occurring mainly in the elderly and or those undergoing mechanical ventilation. We did not find any associations between different strata of body mass index and mortality. In the multivariate analysis, the time elapsed between the onset of symptoms and hospital admission, mechanical ventilation, C-reactive protein value at the end of the first week in the intensive care unit, and renal failure were independently associated with mortality. Vaccinated people comprised 8.8% of the sample, with no differences in mortality among the different vaccines, and 13.4% of patients underwent palliative treatment. CONCLUSIONS: Patients admitted for acute respiratory syndrome due to SARS-CoV-2 are severe and have a high mortality rate, mainly if submitted to invasive mechanical ventilation. The emergence of acute renal failure marks an especially severe subgroup with increased mortality. Processes and protocols linked to the “choosing-wisely” concept seemed to significantly benefit our intensive care unit since it had a large contingent of nonspecialist physicians.
Nonstationary Density Estimation and Kernel Autoregression

An asymptotic theory is developed for the kernel density estimate of a random walk and the kernel regression estimator of a nonstationary first order autoregression. The kernel density estimator provides a consistent estimate of the local time spent by the random walk in the spatial vicinity of a point that is determined in part by the argument of the density and in part by initial conditions. The kernel regression estimator is shown to be consistent and to have a mixed normal limit theory. The limit distribution has a mixing variate that is given by the reciprocal of the local time of a standard Brownian motion. The permissible range for the bandwidth parameter h_{n} includes rates which may increase as well as decrease with the sample size n, in contrast to the case of a stationary autoregression. However, the convergence rate of the kernel regression estimator is at most n^{1/4}, and this is slower than that of a stationary kernel autoregression, in contrast to the parametric case. In spite of these differences in the limit theory and the rates of convergence between the stationary and nonstationary cases, it is shown that the usual formulae for confidence intervals for the regression function still apply when h_{n} -> 0.