Miracle-dz/UniFAR-FTUs huggingface dataset:
Ordinal Regression to Evaluate Student Ratings Data

ORDINAL REGRESSION TO EVALUATE STUDENT RATINGS DATA Emily B. Bell Department of Statistics Master of Science Student evaluations are the most common and often the only method used to evaluate teachers. In these evaluations, which typically occur at the end of every term, students rate their instructors on criteria accepted as constituting exceptional instruction in addition to an overall assessment. This presentation explores factors that influence student evaluations using the teacher ratings data of Brigham Young University from Fall 2001 to Fall 2006. This project uses ordinal regression to model the probability of an instructor receiving a good, average, or poor rating. Student grade, instructor status, class level, student gender, total enrollment, term, GE class status, and college are used as explanatory variables.
Identification through heteroskedasticity: a likelihood-based approach

In this paper we show how the analysis of identification of simultaneous equations systems with different volatility regimes can be addressed in a conventional likelihood-based setup, generalizing previous works in different directions. We discuss general conditions for identification and one of the results shows that an adequate number of different levels of heteroskedasticity is sufficient to identify the parameters of the structural form without the inclusion of any kind of restriction. A FullInformation Maximum Likelihood (FIML) algorithm is discussed and the small sample performances of estimators and tests on the parameters are studied through Monte Carlo simulations. Finally, this methodology is used to investigate the relationships between sovereign bond yields for some highly indebted EU countries.
Digital twin oriented multi-objective flexible job shop scheduling model and its hybrid particle swarm optimization

To solve the problems of low efficiency and insufficient dynamic response of job shop scheduling in the discrete manufacturing process, a multi-objective flexible job shop scheduling model for digital twin and its solution method are proposed. Firstly, a digital twin scheduling model with physical entity, virtual model and production plan is constructed, and four factors are taken as optimization goals. Then, a hybrid particle swarm optimization method is designed to increase the refined optimization ability, and the obtained Pareto optimal solution set is analyzed by grey relational analysis to obtain a satisfactory solution which coincides with the actual production. Finally, a three-dimensional model which is completely mapped with the real job shop scheduling is built by Plant Simulation software. The scheduling process is simulated and optimized by combining with the production data of an enterprise, which verifies the feasibility and applicability of this method, and will effectively guide the production practice.
Hierarchical Multifeature Fusion via Audio-Response-Level Modeling for Depression Detection

The clinical diagnosis of major depressive disorder (MDD) relying heavily on the subjective judgment assisted by questionnaires, could result in a low detection rate of MDD. Automatic depression detection (ADD) technology based on physiological and psychological information provides an objective and quantitative way for MDD detection. As a useful data modality, audio signals have attracted increasing interest in mental disorder detection. However, most recent audio-based depression detection methods underestimate the importance of subtly organizing audio data. They either simply use equally split audio segments, or directly build the model upon the entire data sequence, which pose challenges to learning task-specific features. To address this issue, we propose to reorganize the audio data at response level. Based on that, we construct a novel end-to-end model that hierarchically learns discriminative features for accurate depression detection. The stages of intraresponse fusion and interresponse fusion facilitate the extraction and aggregation of ADD-specific information from multiple kinds of acoustic features. Experimental results show that our proposed method significantly outperforms other state-of-the-art audio-based methods. In addition, the flexibility and the robustness of our model are also validated.
In search of the functional base of risk-taking: inexperience and safety

Abstract This study is aimed at challenging the notion that risk-taking is based merely on some mechanistic foundation like control deficiencies or process imbalances. We hypothesize that risk-taking has an adaptive function and is an optimal strategy for an agent who (1) has scarce knowledge about the current environment or (2) is in a position in which a potential loss is not threatening. We argue that the two above are related to age which, in turn, may explain association between age and risk-taking commonly reported in the developmental literature. We investigate the possible influence of the age-related variables on the risk propensity in two ways: by inducing rich or scarce knowledge and safe or unsafe position in the experimental environment with task parameters and, simultaneously by examining actual differences between adolescents and adults. The results of two experiments that used a novel compound risk task provide support for the first hypothesis concerning knowledge about the environment. On the other hand, the results falsify the second “safe position” hypothesis. Also, the second experiment reveals that one’s status relative to resources can influence risk-taking, but it does so in a way that is different from our initial assumption.
Interference Effect on Resonance Searches and the Diboson Excess

The interference between resonance signal and continuum background can be either constructive or destructive, depending on the relative sign of couplings in the signal and background amplitudes. Different interference schemes lead to asymmetric distortions of the resonance line shape, which could be distinguished in experiments, when the internal resonance width is bigger than the detector resolution. The ATLAS diboson excess is a good example to see such a line shape difference from the sign of resonance couplings. Although the current $\sim$ 2 TeV data show no significant preference for either case, due to the limited statsitics and large reducible non-interfering backgrounds, we expect that if the diboson excess is confirmed by the upcoming 14 TeV LHC data, the sign of the resonance couplings can be revealed in the line shape measurements to more than $5\sigma$ confidence level at the 3000 fb$^{-1}$ luminosity at the trilepton channel, therefore gives us further information on the underlying theory.
Gravity gradient survey with a mobile atom interferometer

The field of atom interferometry has grown rapidly over the last two decades, opening up a new direction in precision metrology. Atom interferometers have proven to be valuable tools for measuring gravitational and inertial effects. In particular, gravimeters, gradiometers, and gyroscopes based on atom interferometry have all demonstrated high accuracies competitive with state-of-the-art commercial technology. We describe here the development and operation of a compact mobile gravity gradiometer using π/2−π−π/2 sequence with two-photon stimulated Raman transitions in a dual atomic fountain setup for precision gravity gradient survey and other gravity tests. Various noise sources have been identified and overcome, and a differential acceleration sensitivity of 4.2 × 10−9g/ √ Hz has been achieved over a 70 cm baseline in the laboratory. The apparatus was then moved into a box-truck and a gravity gradient survey was conducted near a 4 story-deep building, at an accuracy of 7×10−9/s2 in gravity gradient with about three minutes integration at each survey point. The survey results agreed with a theoretical model considering detailed floor plan and building structure. In addition, technique to measure absolute gravity gradient is discussed. Finally, a complete dynamic model of the π/2− π− π/2 sequence was established, and potential algorithms to de-correlate apparatus platform noise during survey based on this model were identified.
Physical Activity and its Association with Fatigue in Men with Prostate Cancer

Fatigue negatively impacts health outcomes leading to decreased physical activity, increased depression, and decreased health-related quality of life. This study aimed to determine level/intensity of physical activity (PA) and its associations with cancer-related fatigue (CRF) in prostate cancer patients receiving radiotherapy (RT), compared to those without RT but under active surveillance (AS). A prospective, correlational design with repeated measures was used to determine changes in PA and association of PA with CRF in men with prostate cancer. Fifty-four subjects were recruited (RT=36, AS=18). PA was measured using The International Physical Activity Questionnaire ( IPAQ ) , a well-validated, self-report questionnaire. CRF was evaluated by the revised Piper Fatigue Scale (r-PFS) and Patient Reported Outcomes Measurement Information System for Fatigue (PROMIS-F), and Hamilton Depression Rating Scale (HAM-D) was used to assess depression symptoms. The metabolic equivalent of task (MET) was calculated following the IPAQ analysis guidelines to reflect the intensity/level of PA. Data were collected at 3 times and analyzed using Chi-square/ Fisher’s exact tests, t-testes, and Spearman correlation. All tests were two-sided, and p-values < 0.05 were considered statistically significant. Level of IPAQ (low, moderate, high) at the endpoint were significantly different between the two groups ( p = 0.03). IPAQ was associated with PROMIS-F ( p = 0.014), r-PFS ( p = 0.001), and HAM-D ( p = 0.01) at midpoint and endpoint in the RT group. Patients with RT reported decreased PA, compared to their baseline and to those with AS. Levels/intensity of PA was associated with CRF severity and depression in patients receiving RT. Assessment of PA and symptoms prior to the treatment may enable clinicians to identify patients who need early and aggressive intervention to prevent worsening symptoms through a decline in PA during and after RT.
What constrains people’s ability to learn about the testing effect through task experience?

ABSTRACT What constrains people’s ability to learn from experience about the effectiveness of practice testing versus restudying for memory (i.e., the testing effect)? Across two cycles, participants studied word pairs, practiced each pair through either restudying or testing, predicted how many pairs they would recall for each strategy, then completed a critical test on the pairs. During this test, participants either received feedback about the number of pairs they had correctly recalled or made postdictions about their performance for each strategy (i.e., generated their own feedback). During both cycles, participants predicted they would recall an equivalent number of tested and restudied pairs, although they actually recalled more tested pairs. However, when participants experienced a larger testing effect, they estimated recall performance more accurately for each strategy and updated their knowledge about the testing effect. Thus, peoples’ ability to learn from experience about the testing effect is primarily constrained not by a failure to initiate the metacognitive processes required to monitor and track recall performance by strategy, but by the metacognitive burden of discriminating between small differences in recall between tested versus restudied material. In summary, people can learn from experience about the testing effect when the metacognitive burden is lifted.
Fluid Dynamics and Transport Phenomena Heat transfer of nano fl uidics in hydrophilic pores : Insights from molecular dynamics simulations ☆

Article history: Received 21 October 2015 Received in revised form 20 January 2016 Accepted 28 January 2016 Available online 12 May 2016 Nanofluidics in hydrophilic nanopores is a common issue in many natural and industrial processes. Among all, the mass transport of nanofluidics is most concerned. Besides that, the heat transfer of a fluid flow in nano or micro channels is always considered with adding nanoparticles into the flow, so as to enhance the heat transfer by convection between the fluid and the surface. However, for some applications with around 1 nm channels such as nano filtration or erosion of rocks, there should be no nanoparticles included. Hence, it is necessary to figure out the heat transfermechanism in the single phase nanofluidics.Via non-equilibriummolecular dynamics simulations, we revealed the heat transfer inside nanofluidics and the one between fluid and walls by setting simulation into extremely harsh condition. It was found that the heat was conducted bymolecular motion without temperature gradient in the area of low viscous heat, while it was transferred to the walls by increasing the temperature of fluids. If the condition back to normal, it was found that the viscous heat of nanofluidics could be easily removed by the fluid-wall temperature drop of less than 1 K. © 2016 The Chemical Industry and Engineering Society of China, and Chemical Industry Press. All rights reserved.
The Influencing Factors of Customer Satisfaction of O2O Food Takeout Platforms – A Social Institutional Environment Perspective

Online-to-offline (O2O) takeout platforms have become an important way of food consumption in modern life. However, some problems, such as unlicensed operation and poor service, have been exposed. Therefore, it is very important to identify the factors that affect customer trust and satisfaction. However, there are very few studies on consumer satisfaction of takeout platforms in the existing literature. This paper builds a model according to the development of the O2O takeout industry and verifies it by questionnaires and web crawler data. Finally, SPSS data analysis software is used to analyze the variables. The results show that internal mechanisms and social environments affect the trust of users regarding O2O platforms. Also, with the improvement of users' trust, their perceived level of risk will decline, and their satisfaction will increase. Finally, suggestions of optimizing the platform mechanisms and improving service quality and attitude are advised.
Affine model of stress stiffening in semiflexible filament networks

(Dated: August 29, 2008)We present a revised theoretical study of the aﬃne assumption applied to semiﬂexible networks.Drawing on simple models of semiﬂexible worm-like chains we derive an expression for the probabilitydistribution of crosslink separations valid at all separations. This accounts for both entropic andmechanical ﬁlament stretching. From this we obtain the free energy density of such networksexplicitly as a function of applied strain. We are therefore able to calculate the elastic moduli ofsuch networks for any imposed strain or stress. We ﬁnd that accounting for the distribution ofcross-link separations destroys the simple scaling of modulus with stress that is well known in singlechains, and that such scaling is sensitive to the mechanical stretch modulus of individual ﬁlaments. We compare this model to three experimental data sets, for networks of diﬀerent types of ﬁlaments,and ﬁnd that a properly treated aﬃne model can successfully account for the data. We ﬁnd thatfor networks of stiﬀer ﬁlaments, such as F-actin, to ﬁt data we require a much smaller eﬀectivepersistence length than usually assumed to be characteristic of this ﬁlament type. We propose thatsuch an eﬀectively reduced rigidity of ﬁlaments might be a consequence of network formation.
Sensory uncertainty punctuates motor learning independently of movement error when both feedforward and feedback control processes are engaged

Integrating sensory information during movement and adapting motor plans over successive movements are both essential for accurate, flexible motor behavior. When an ongoing movement is off target, feedback control mechanisms update the descending motor commands to counter the sensed error. Over longer timescales, errors induce adaptation in feedforward planning so that future movements become more accurate and require less online adjustment from feedback control processes. Both the degree to which sensory feedback is integrated into an ongoing movement and the degree to which movement errors drive adaptive changes in feedforward motor plans have been shown to scale inversely with sensory uncertainty. However, since they have only been studied in isolation of each other, little is know about how they respond to sensory uncertainty in real-world movement contexts where they co-occur. Here, we show that sensory uncertainty impacts feedforward adaptation of reaching movements differently when feedback integration is present versus when it is absent. In particular, participants gradually adjust their movements from trial-to-trial in a manner that is well characterised by a slow and consistent envelope of error reduction. Riding on top of this slow envelope, participants display large and abrupt changes in their initial movement vectors that clearly correlate with the degree of sensory uncertainty present on the previous trial. However, these abrupt changes are insensitive to the magnitude and direction of the sensed movement error. These results prompt important questions for current models of sensorimotor learning under uncertainty and open up exciting new avenues for future exploration. Author Summary A large body of literature shows that sensory uncertainty inversely scales the degree of error-driven corrections made to motor plans from one trial to the next. However, by limiting sensory feedback to the endpoint of movements, these studies prevent corrections from taking place during the movement. Here, we show that when such corrections are promoted, sensory uncertainty punctuates between-trial movement corrections with abrupt changes that closely track the degree of sensory uncertainty but are insensitive to the magnitude and direction of movement error. This result marks a significant departure from existing findings and opens up new paths for future exploration.
Optical properties of porous-system-based nanocomposites

We consider the optical properties of semiconductor – insulator and insulator – insulator nanocomposites, including porous materials such as silicon, gallium phosphide, aluminum oxide, and structures based on them. The main focus is on the effect of form birefringence, which is caused by the anisotropy of pores in the materials under study. The applicability of the effective medium model for describing the optical properties of nanocomposites is discussed. The effects of light localization due to the scattering of light in such inhomogeneous media are analyzed.
Adhesive curing effect of bonded piezoelectric transducer on electromechanical impedance-based concrete structural damage detection

Complete understanding of the adhesive curing effect of a bonded piezoelectric lead zirconate titanate (PZT) sensor on the electromechanical admittance (EMA, inverse of impedance) facilitates the accurate diagnosis of structural damages when employing the impedance technique for structural health monitoring. This article analytically and experimentally investigated the curing effect of adhesive layer on the EMA-based concrete structural damage detection. Curing effect was theoretically incorporated into shearing mechanism of adhesive layer to formulate a new one-dimensional PZT-structural impedance model. Analytical analysis of the curing effect on the EMA signature as well as the EMA-based damage diagnosis was calculably interpreted through the model. Proof-of-concept experiment was performed on testing a four-point bending reinforced concrete (RC) beam bonded with multiple PZT patches under adhesive curing. Experimental results demonstrated that singular shift in the EMA spectra under adhesive curing could be turned into three typical shifts when structural damage occurred, which cogently validated the analytical results. Quantifiable signal index further provided useful information for the identification of crack occurrence, progression, and reinforcement yielding of the RC beam. Results of this study potentially promoted the real-life engineering applications of impedance technique inclusive of deficient adhesive condition.
Precision Mapping of Thalamic Deep Brain Stimulation Lead Positions Associated With the Microlesion Effect in Tourette Syndrome

BACKGROUND: The microlesion effect refers to the improvement of clinical symptoms after deep brain stimulation (DBS) lead placement and is suggested to indicate optimal lead placement. Very few studies have reported its implications in neuropsychiatric disorders. OBJECTIVE: To evaluate the magnitude of the microlesion effect in Tourette syndrome and the relationship between the microlesion effect and the anatomic location of implanted DBS leads. METHODS: Six male patients were included. Their median age at surgery and follow-up period were 25 years (range, 18-47) and 12 months (range, 6-24), respectively. All patients were videotaped pre- and postoperatively, and tic frequencies were counted. We also analyzed the precision of lead placement and evaluated the normative connectome associated with the microlesion area. RESULTS: The microlesion effect was observed as an improvement in tic symptoms in all patients, and the long-term clinical outcomes were favorable. The median motor tic frequency was 20.2 tics/min (range, 9.7-60) at baseline and decreased to 3.2 tics/min (1.2-11.3) in patients on postoperative day 1 (P = .043) and to 5.7 tics/min (range, 1.9-16.6) in patients on postoperative day 7 (P = .028). Phonic tic tended to improve immediately after surgery although the changes were not significant. Image analyses revealed that the precise position of the electrode was directed toward the anteromedial centromedian nucleus. Normative connectome analysis demonstrated connections between improvement-related areas and wide areas of the prefrontal cortex. CONCLUSION: This study shows that the microlesion effect may seem as an immediate improvement after optimal DBS lead placement in patients with Tourette syndrome.
Cardiovascular risk in a rural psychiatric inpatient population: Retrospective case cohort study

Aims and Method: To evaluate cardiovascular risk in a rural inpatient psychiatric unit over a one-year period. Care records were analysed for risk factor recording, and cardiovascular risks estimated using the QRISK3 calculator, which estimates 10-year risk of myocardial infarction or stroke. Results: Of eligible patients, risk factor recording as part of routine care was completed in 86% of possible QRISK3 inputs, enabling QIRSK3 estimation in all eligible patients. QRISK3 for this group was raised (Relative risk: 3.8, 95%CI: 2.5 - 5.0). High risk of cardiovascular disease (QRISK3 score >10%) was detected in 28% of patients. Clinical Implications: This service evaluation demonstrated significant unmet need for cardiovascular risk reduction that could be identified as part of routine care. An opportunity exists to integrate mental and physical healthcare by routinely assessing cardiovascular risk in psychiatric inpatients. Resources and training are needed to produce this risk information and act on it.