Miracle-dz/UniFAR-FTUs huggingface dataset:
Preconditioners for the Discontinuous Galerkin time-stepping method of arbitrary order

We develop a preconditioner for systems arising from space-time finite element discretizations of parabolic equations. The preconditioner is based on a transformation of the coupled system into block diagonal form and an efficient solution strategy for the arising 2 × 2 blocks. The suggested strategy makes use of an inexact factorization of the Schur complement of these blocks, for which uniform bounds on the condition number can be proven. The main computational effort of the preconditioner lies in solving implicit Euler-like problems, which allows for the usage of efficient standard solvers. Numerical experiments are performed to corroborate our theoretical findings.
Wet steam ﬂow in 1100 MW turbine

The paper deals with the wet steam ﬂow in a steam turbine operating in a nuclear power plant. Using a pneumatic and an optical probe, the static pressure, steam velocity, steam wetness and the ﬁne water droplets diameter spectra were measured before and beyond the last turbine low-pressure stage. The results of the experiment serve to understand better the wet steam ﬂow and map its liquid phase in this area. The wet steam data is also used to modify the condensation model used in computational ﬂuid dynamics simulations. The condensation model, i.e. the nucleation rate and the growth rate of the droplets, is adjusted so that results of the numerical simulations are in a good agreement with the experimental results. A 3D computational ﬂuid dynamics simulations was performed for the low-pressure part of the turbine considering non-equilibrium steam condensation. In the post-processing of the of the numerical calculation result, the thermodynamic wetness loss was evaluated and analysed. Loss analysis was performed for the turbine outputs of 600, 800, and 1100 MW, respectively.
Drug-Drug Interaction Extraction-Based System: an NLP Approach

Purpose: Poly-medicated patients, especially those over 65, have increased. Multiple drug use and inappropriate prescribing increase drug-drug interactions, adverse drug reactions, morbidity, and mortality. This issue was addressed with several CDSS alerts. Health professionals have not followed these systems due to their poor alert quality and incomplete databases. Methods: Recent research shows a growing interest in using Text Mining via NLP to extract drug-drug interactions from unstructured data sources to support clinical prescribing decisions. NLP text mining and machine learning classiﬁer training for drug relation extraction were used in this process. Results: In this context, the proposed solution allows to develop an extraction system for drug-drug interactions from unstructured data sources. The system produces structured information, which can be inserted into a database that contains information acquired from three diﬀerent data sources. Conclusion: The architecture outlined for the drug-drug interaction extraction system is capable of receiving unstructured text, identifying drug entities sentence by sentence, and determining whether or not there are interactions between them.
Neurosyphilis Mimicking Herpes Encephalitis Mesiotemporal T2-Weighted Hyperintensity

Summary: Bilateral mesiotemporal hyperintensity on T2-weighted and ﬂuid-attenuated inversion recovery MR images of a patient with a clinical syndrome of encephalitis is considered to be a classic ﬁnding for herpes simplex virus infection. We report a case of neurosyphilis with identical MR imaging abnormalities and a similar clinical presentation. Because syphilis is not routinely tested for, awareness of this mimicry of herpes simplex virus encephalitis is important, considering the potential therapeutic implications.
Correcting for Multiple Testing During Diagnostic Accuracy Studies

ABSTRACT During diagnostic accuracy studies, hypotheses are often tested on more than one accuracy measure. One common example is to make inferences both on the area under the receiver operating characteristic curve (AUC) and on the sensitivity and specificity at a particular operating point. This represents a unique multiple testing situation as the AUC is a function of the sensitivity and specificity. Through a large simulation study, we showed that a naïve approach of testing all three accuracy measures at a 0.05-level greatly elevates the family-wise Type I error rate (i.e., up to 10%). When a gatekeeping approach to controlling the FWER was appropriate (family 1: AUC, family 2: sensitivity and specificity), adjustment in the second family was necessary to control the FWER across all scenarios. When a nonhierarchical approach was appropriate, the methods of Xie (2012) offered increased power over Holm's step-down procedure, but required assumptions about the correlation among the test statistics. In our simulations, the correlation between the test statistics of the AUC and sensitivity and between the test statistics of the AUC and specificity ranged from 0.3 to 0.6, while there was no correlation between the test statistics of the sensitivity and specificity.
A Comparative Study of Psychological Burden and Sexual Dysfunction in Patients with Polycystic Ovarian Syndrome and Healthy Controls, and Its Correlation with Sexual Hormones

-Background: Polycystic ovarian syndrome (PCOS) affects 5-10% of reproductive-age women worldwide, with a prevalence of 35% in India. PCOS is characterized by symptoms like obesity, hirsutism, acne, and infertility. These symptoms contribute to psychological distress, including stress, anxiety, and depression, among women with PCOS. Methods: Recent studies have shown high rates of anxiety and depression in women with PCOS, with depression prevalence ranging from 23% to 64% globally. Anxiety disorders affect 11.5% to 38.6% of PCOS individuals. PCOS diagnosis is based on hyperandrogenism, ovulatory dysfunction, and polycystic ovaries. However, depression and anxiety often remain undetected, resulting in inadequate treatment. Results: Women with PCOS experience higher rates of depressive episodes, social phobia, eating disorders, and suicide attempts. They also use more antidepressants and anxiolytic drugs. Sexual dysfunction is prevalent in PCOS, attributed to symptoms like obesity and hirsutism. Lower education levels and hirsutism contribute to higher sexual dysfunction rates. Increased BMI is associated with reduced sexual desire and satisfaction. PCOS women report diminished sexual attractiveness and desire. Stress, anxiety, depression negatively affect sexual function. Testosterone levels may not strongly correlate with female sexual function or well-being due to measurement challenges. Conclusion: Comprehensive research is needed to understand the psychological burden and sexual dysfunction in PCOS patients, as well as their correlation with hormone levels. PCOS affects women's mental health, with depression and anxiety often overlooked. Sexual dysfunction, influenced by physiological and psychosocial factors, is also common. Advancing our knowledge in these areas will improve diagnosis and treatment, enhancing the overall quality of life for
Various motivations for managerial (mis)reporting – an experimental study

Abstract In the experiment we model all possible consequences from misreporting for both the shareholder and for the manager, since we are interested in patterns in reporting behaviour resulting from different motivations for potential misrepresentation. This allows for examining the stability of the (mis)reporting behaviour in different treatments. Agents are primarily driven by the consequences for themselves rather than by the consequences for the principal, while deciding on misreporting. Participants are willing to sacrifice a small gain for themselves in order to prevent a greater loss for the principal. If agents misreport, they do it in order to generate positive rather than negative consequences for themselves. Reports in favour of the principal, but fruitless or even costly for the agent are very rare. The experiment indicates also that pro-social agents report more truthfully than pro-self agents.
Text Style Transfer Thesis Proposal

Text style transfer (TST) is one of the most important tasks of Natural Language Generation (NLG). The aim of TST is to automatically con-trol the style attributes of text while preserving the content. We aim to expand the capabilities and increase the output quality of systems for NLG by controlling style attributes. In order to do that, we aim to present: (i) TST models which balance the style-content trade-off well, (ii) new models for real-world downstream applications, and (iii) better evaluation metrics for this task. In this thesis proposal, we first introduce the landscape of current approaches to TST and the background for our work. Next, we report the methodology and results of our experiments. Regarding future work, we out-line our plans to continue to combat challenges in TST .
Deep Depth Estimation from Thermal Image

Robust and accurate geometric understanding against adverse weather conditions is one top prioritized conditions to achieve a high-level autonomy of self-driving cars. However, autonomous driving algorithms relying on the visible spectrum band are easily impacted by weather and lighting conditions. A long-wave infrared camera, also known as a thermal imaging camera, is a potential rescue to achieve high-level robustness. However, the missing necessities are the well-established large-scale dataset and public benchmark results. To this end, in this paper, we first built a large-scale Multi-Spectral Stereo (MS2) dataset, including stereo RGB, stereo NIR, stereo thermal, and stereo LiDAR data along with GNSS/IMU information. The collected dataset provides about 195K synchronized data pairs taken from city, residential, road, campus, and suburban areas in the morning, daytime, and nighttime under clear-sky, cloudy, and rainy conditions. Secondly, we conduct an exhaustive validation process of monocular and stereo depth estimation algorithms designed on visible spectrum bands to benchmark their performance in the thermal image domain. Lastly, we propose a unified depth network that effectively bridges monocular depth and stereo depth tasks from a conditional random field approach perspective. Our dataset and source code are available at https://github.com/UkcheolShin/MS2-MultiSpectralStereoDataset.
Planck’s Units Re-visited

Planck’s units were developed over a hundred years ago and have been utilized, discussed and criticized during this period. The present paper takes a new look at the dimensional analysis of Planck from a different perspective. The result identifies the existence of five forces and suggests the possibility of these forces to be the basic building blocks of the physical world as was known during Planck’s time, as well as today. Several questions are posed such as do we know all the pertinent physical constants? Will Planck’s result change with new dimensions? Can today’s quest for understanding the gravitational force, electromagnetic, weak and strong force be combinations of the basic building blocks? Suggested possibilities for the atomic forces are proposed. In 1895 Max Planck investigated the non-dimensional analysis of the existing basic parameters of mass length, time, temperature and charge along with the known five constants that governed the laws of physics, namely the gravitational constant G, speed of light c, his own constant ħ, the Boltzman constant k b , and the Coulomb constant K e . He then utilized what is known today as the π theorem to formulate his famous Planck units. In doing this, Planck chose to write the five basic parameters (length, mass, time, charge and temperature) in terms of the five constants. It will be shown that a second alternative exists, that is of identifying forces that are a function of the basic parameters and the physical constants. It will be first shown how the π theorem would be used to obtain Planck’s units; it is then demonstrated that by reversing the emphasis on which terms are important one obtains five basic forces. It is then questioned that if new unknown dimensions and new unknown constants exist, what are the consequences upon Planck’s results and the present alternate forces? It will be demonstrated that the gravitational force, electromagnetic, weak and strong force are either one of the identified forces or a possible combination of these forces.
Group Roles Matter in Computational Robotic Activities Group Roles Matter in Computational Robotic Activities

This study examines the impact of grouping by gender and group roles on robotics performance, computational thinking skills, and learning motivation towards computer programming. One hundred ninety-one students in fourth and fifth grade completed the project. LEGO Mindstorms EV3 robotics were used to compose and program music in groups of three to four students. The robotics project was completed over the course of fourteen weeks for one hour each week. Gender-structured groups of all female, all male and mixed female and male were randomly assigned in each class. All groups in participating six classrooms were assigned one of three group roles implementation, which were fixed, rotating and no role. This study is significant towards identifying group scaffolds and supports that can produce benefits for all students in robotic activities. Results indicated that group roles matter when students are working on collaborative robotics projects. Three different implementations of group roles in robotics activities demonstrated an impact on robotics performance scores. Gender composition of the group did not impact groups’ robotics performance. Group roles also impacted student computational thinking skills, while gender composition of the group still demonstrated no significant difference. Finally, while group roles demonstrated a difference in learning motivation towards computer programming, gender composition demonstrated no difference in learning motivation towards computer programming.
Investigating the contribution of grown new particles to cloud condensation nuclei with largely varying preexisting particles – Part 1: Observational data analysis

Abstract. This study employed multiple techniques to investigate the contribution of grown new particles to the number concentration of cloud condensation nuclei (CCN) at various supersaturation (SS) levels at a rural mountain site in the North China Plain from 29 June to 14 July 2019. On 8 new particle formation (NPF) days, the total particle number concentrations (Ncn) were 8.4 ± 6.1×103 cm−3, which was substantially higher compared to 4.7 ± 2.6×103 cm−3 on non-NPF days. However, the CCN concentration (Nccn) at 0.2 % SS and 0.4 % SS on the NPF days was significantly lower than those observed on non-NPF days (p<0.05). This was due to the lower cloud activation efficiency of preexisting particles resulting from organic vapor condensation and smaller number concentrations of preexisting particles on NPF days. A case-by-case examination showed that the grown new particles only yielded a detectable contribution to Nccn at 0.4 % SS and 1.0 % SS during the NPF event on 1 July 2019, accounting for 12 % ± 11 % and 23 % ± 12 % of Nccn, respectively. The increased Nccn during two other NPF events and at 0.2 % SS on 1 July 2019 were detectable but determined mainly by varying preexisting particles rather than grown new particles. In addition, the hygroscopicity parameter values, concentrations of inorganic and organic particulate components, and surface chemical composition of different sized particles were analyzed in terms of chemical drivers to grow new particles. The results showed that the grown new particles via organic vapor condensation generally had no detectable contribution to Nccn but incidentally did. However, this conclusion was drawn from a small size of observational data, leaving more observations, particularly long-term observations and the growth of preexisting particles to the CCN required size, needed for further investigation.
A Feature Fusion Human Ear Recognition Method Based on Channel Features and Dynamic Convolution

Ear images are easy to capture, and ear features are relatively stable and can be used for identification. The ear images are all asymmetric, and the asymmetry of the ear images collected in the unconstrained environment will be more pronounced, increasing the recognition difficulty. Most recognition methods based on hand-crafted features perform poorly in terms of recognition performance in the face of ear databases that vary significantly in terms of illumination, angle, occlusion, and background. This paper proposes a feature fusion human ear recognition method based on channel features and dynamic convolution (CFDCNet). Based on the DenseNet-121 model, the ear features are first extracted adaptively by dynamic convolution (DY_Conv), which makes the ear features of the same class of samples more aggregated and different types of samples more dispersed, enhancing the robustness of the ear feature representation. Then, by introducing an efficient channel attention mechanism (ECA), the weights of important ear features are increased and invalid features are suppressed. Finally, we use the Max pooling operation to reduce the number of parameters and computations, retain the main ear features, and improve the model’s generalization ability. We performed simulations on the AMI and AWE human ear datasets, achieving 99.70% and 72.70% of Rank-1 (R1) recognition accuracy, respectively. The recognition performance of this method is significantly better than that of the DenseNet-121 model and most existing human ear recognition methods.
Remarks on the complete synchronization for the Kuramoto model with frustrations

The synchronous dynamics of many limit-cycle oscillators can be described by phase models. The Kuramoto model serves as a prototype model for phase synchronization and has been extensively studied in the last 40 years. In this paper, we deal with the complete synchronization problem of the Kuramoto model with frustrations on a complete graph. We study the robustness of complete synchronization with respect to the network structure and the interaction frustrations, and provide sufficient frameworks leading to the complete synchronization, in which all frequency differences of oscillators tend to zero asymptotically. For a uniform frustration and unit capacity, we extend the applicable range of initial configurations for the complete synchronization to be distributed on larger arcs than a half circle by analyzing the detailed dynamics of the order parameters. This improves the earlier results [S. -Y. Ha, H. Kim and J. Park, Remarks on the complete frequency synchronization of Kuramoto oscillators, Nonlinearity 28 (2015) 1441–1462; Z. Li and S. -Y. Ha, Uniqueness and well-ordering of emergent phase-locked states for the Kuramoto model with frustration and inertia, Math. Models Methods Appl. Sci. 26 (2016) 357–382. ] which can be applicable only for initial configurations confined in a half circle.
Parent and Provider Perspectives on Early Intervention in Ohio: A Community Collaborative Approach

The network of early intervention (EI) for families with children who are deaf or hard of hearing (DHH) consists of multiple professionals that partner with parents. As part of a community collaborative initiative, diverse perspectives were gathered via online surveys in a state-wide needs assessment to evaluate the landscape of EI in Ohio. The qualitative and quantitative feedback were analyzed in light of the Joint Committee on Infant Hearing’s (2007) goals, the 2013 early intervention supplement to those goals, and 2019 update. Care coordination and equitable access emerged as top priorities across all three stakeholder groups queried (audiologists, EI providers, and parents). Through a theory of change framework, these results offer a pathway to strengthening EI to promote the well-being of families and children who are DHH
Excess electrons at anatase TiO2 surfaces and interfaces: insights from first principles simulations

TiO2 is an important technological material with widespread applications in photocatalysis, photovoltaics and self-cleaning surfaces. Excess electrons from intrinsic defects, dopants and photoexcitation play a key role in the properties of TiO2 that are relevant to its energy-related applications. The picture of excess and photoexcited electrons in TiO2 is based on the polaron model, where the electron forms a localized state that is stabilized by an accompanying lattice distortion. Here, we focus on excess and photoexcited electrons in anatase, the TiO2 polymorph most relevant to photocatalysis and solar energy conversion. For anatase, evidence of both small and large electron polarons has been reported in the literature. In addition, several studies have revealed a remarkable dependence of the photocatalytic activity of anatase on the crystal surface. After an overview of experimental studies, we briefly discuss recent progress in the theoretical description of polaronic states in TiO2, and finally present a more detailed account of our computational studies on the trapping and dynamics of excess electrons near the most common anatase surfaces and aqueous interfaces. The results of these studies provide a bridge between surface science experiments under vacuum conditions and observations of crystal-face-dependent photocatalysis on anatase, and support the idea that optimization of the ratio between different anatase facets can help enhance the photocatalytic activity of this material.
Does Eviction Affect Crime? Quasi-Experimental Evidence from Boston

This paper provides quasi-experimental evidence of the effects of eviction on the frequency of crime incidents in the immediate vicinity of a property. Anecdotal evidence suggests that eviction is destructive to its victims, but little is known about its impact on immediately surrounding areas. I use a doubly robust difference-in-differences research design based on the staggered conclusion of eviction cases in Boston, Massachusetts between April 2019 and March 2020. Using properties where eviction was unsuccessful as the counterfactual for properties where eviction was successful, I find negative effects of eviction on crime incidents within 500 meters of a property that persist for three years after case resolution, even conditional on 15 pre-treatment characteristics including income, population density, and race. My point estimate of the average post-treatment effect of eviction on crime incidents has magnitude equal to 3.89 percent of the mean number of crimes per month within 500 meters of a property in 2017. I find strong evidence that the mechanism driving these impacts is the removal of individuals who are crime incident targets, accomplices, and/or perpetrators from the immediate vicinity of the property. I find evidence against several alternative explanations for my results, including that they are driven by a pandemic-related shift in crime trends. Estimates remain significantly different from zero even when the radius considered around each property is adjusted.
Analytical solutions for semiconductor luminescence including Coulomb correlations with applications to dilute bismides

In this paper we introduce analytical solutions of interband polarization, which is the self-energy of the Dyson equation for the photon Green’s functions, and apply them to studying photoluminescence of Coulomb-correlated semiconductor materials. The accuracy of the easily programmable solutions is proven by consistently demonstrating the low-temperature s-shape of the luminescence peak of dilute bismide semiconductors. The different roles of homogeneous versus inhomogeneous broadening at low and high temperatures are described, as well as the importance of many body effects, which are in very good agreement with experiments.