Miracle-dz/UniFAR-FTUs huggingface dataset:
Engineering gate dielectric surface properties for enhanced polymer field-effect transistor performance

The modification of silicon dioxide (SiO2) gate dielectrics with silane self-assembled monolayers (SAMs) via silylation was conducted to study their impacts on polymer field-effect transistor (FET) performance. SAMs formed from silylating agents with long alkyl chains such as octadecyl gave high field-effect mobility but a lower on/off ratio because of lower SAM coverage of the gate dielectric surface. In contrast, SAMs from silylating agents with phenyl or medium alkyl chains (octyl) provided a high on/off ratio from high SAM surface coverage but lower mobility due to their inefficiency in promoting molecular ordering of the channel semiconductor. By treating the SiO2 dielectric surface with two silylating agents, one with an octadecyl chain and one with an octyl or phenyl chain, in a proper sequence, a high-performance “hybrid” dual-silane SAM could be created, enabling attainment of both a high mobility and on/off ratio, together with other desirable FET properties.
Sorption – desorption of imidacloprid insecticide on Indian soils of five different locations

Sorption-desorption processes govern the movement of all chemicals including pesticides in soils. The present investigation was undertaken to study the sorption-desorption of imidacloprid, using a batch method, on soils of five different location of India. Sorption data were fitted to Freundlich isotherm. The log K value was the highest for loam type soil (1.830) and the lowest for clay type soil (1.661). The value of 1/n was the maximum for silt loam soil (0.909) but minimum for loam soil (0.723). Simple correlation analysis indicated that among soil properties only electrical conductivity showed a higher but marginally non-significant negative correlation with log K (r = -0.826) indicating that higher concentration of solutes solutes are conducive to low sorption capacity of soil. The desorption data conformed to two surfaces Freundlich desorption isotherm. The values of 1/n 1 ' corresponding to easily desorbed fraction of imidacloprid showed significant negative correlation with soil pH (r = -0.886, significant at p ≤0.05) but significant positive correlation with clay content (r = 0.980, significant at p ≤0.01). The desorption index for easily desorbed fraction of imidacloprid (n 1 ’/n) also had significant negative correlation with soil pH (r = 0.953, significant at p ≤0.05). From cumulative desorption data, it appeared that bioavailability of imidacloprid would be lower in neutral soil than acidic or alkaline soils.
Mental health of patients with mental illness during the COVID-19 pandemic lockdown: a questionnaire-based survey weighted for attrition

Abstract Background Individuals with pre-existing mental illness may be particularly vulnerable to the negative impact that the coronavirus disease 2019 (COVID-19) pandemic seems to have on mental health. Accordingly, the objective of the present study was to assess whether patients with mental illness experienced deterioration in mental health during the COVID-19 lockdown of Denmark in the Spring of 2020. Methods We conducted a cross-sectional, questionnaire-based survey coupled with sociodemographic and clinical data from the medical records of all invitees. The latter enabled analysis of attrition and weighting of results. The online questionnaire included the 18-item Brief Symptom Inventory (BSI-18), the five-item World Health Organization Well-Being Index (WHO-5), and 14 questions evaluating worsening or improvement in symptoms during lockdown using the pre-pandemic period as reference. Results A total of 992 randomly drawn patients with mental illness from the psychiatric services of the Central Denmark Region responded to the questionnaire (response rate = 21.6%). The weighted mean WHO-5 and BSI-18 scores were 38 and 28, respectively. A total of 52% of the respondents reported that their mental health had deteriorated during the lockdown, while 33% reported no change, and 16% reported improvement. The most commonly reported reasons for deterioration were loneliness, disruption of routines, concerns regarding the coronavirus, less contact with family/friends, boredom, and reduced access to psychiatric care. Conclusion More than half of the patients reported worsening of their mental health during the pandemic lockdown. There should be an increased emphasis on ensuring both social and clinical support for individuals with mental illness during pandemics.
Learning from the Experiences of COVID-19 Survivors: A Descriptive Study

Background: There are still many unanswered questions about the novel coronavirus, however, a largely underutilized source of knowledge are the millions of people who have recovered after contracting the virus. This includes majority of undocumented cases of the COVID-19 which are classified as mild or moderate and received little to no clinical care during the course of illness. Objective: To document and glean insights from the experiences of persons with first-hand experience with coronavirus, especially the so-called mild to moderate cases that self-resolved in isolation. Methods: This online-based survey study called C19 Insider Scoop recruited adult participants that are 18-years or older who reside in the United States and tested positive for COVID-19 or antibodies. Participants were recruited through various methods including online support groups for COVID-19 survivors, advertisement in local news outlets, and advertisement through professional and other networks. The main outcomes measured include knowledge on contraction/transmission of the virus, symptoms, and personal experiences on road to recovery. Results: A total of 72 participants (53 females/19 males, ages 18 - 73 yrs. old, mean = 41-yrs.) from 22 U.S. states participated in this study. We found that the top known source of how people contracted the COVID-19 virus was through a family or household member (n=26 or 35%). This was followed by essential workers contracting the virus through the workplace (n=13 or 18%). Participants reported up to 27 less-documented symptoms that they experienced during their illness such as brain/memory fog, palpitations, ear pain/discomfort and neurological problems. In addition, 47 out of 72 participants (65%) reported that their symptoms lasted longer than the commonly cited 2-weeks even for mild cases of COVID-19. In our study, the mean recovery time was 4.5-weeks, and exactly one-half of survivors (50%) still experienced lingering symptoms of COVID-19 after an average of 65-days following illness onset. Additionally, 37 participants (51%) reported that they experienced stigma associated with having COVID-19. Conclusion: This study presents preliminary findings which suggests that emphasis on family/household spread of COVID-19 may be lacking and there is a general underestimation of the recovery time even for mild cases of the virus. Although a larger study is needed to validate these results, it is important to note that as more people experience COVID-19, insights from prior survivors can enable a more informed public, pave the way for others who may be affected, and guide further research.
Convenient Synthesis of 2-Aminothiophene Derivatives by Acceleration of Gewald Reaction Under Ultrasonic Aqueous Conditions

Under ultrasound irradiation and in the presence of H2O/Et2NH, ethyl cyanoacetate or malononitrile can combine with α-methylene carbonyl compounds and elemental sulfur to efficiently yield 2-aminothiophene derivatives within a few minutes. Products are easily obtained by simple filtration because of their spontaneous precipitation in the reaction mixtures.
Educational Downgrading: Adult Education and Downward Mobility

Scholarship on adult education throughout the life course focuses on the relationship between education and upward mobility. Scholars rarely examine how adults’ educational aspirations or trajectories are affected by downward mobility or an increasingly precarious labor market. Drawing on in-depth qualitative interviews with 21 job seekers in the post–Great Recession labor market in the United States, this article advances the concept of educational downgrading: returning to school in pursuit of a credential lower than the highest level of education one previously sought or attained. We explore three pathways to downgrading connected to downward mobility: occupational dead ends, career reversals, and educational inflation. In the process, we highlight how individuals adjust their practical educational aspirations as they navigate a contemporary economy in which careers are unstable and credentials are needed for many kinds of jobs across the occupational hierarchy.
Effect of acidification with sulphuric acid on the volatilization of ammonia from cow and pig slurries

SUMMARY Pig and cow slurries were applied to bare soil surfaces in the laboratory. Volatilization of NH3 was measured using ventilated enclosures for 3·25 days after slurry application. Slurries were acidified to pH values between 7 and 4 with 5 M H2SO4. Lowering cow slurry pH to 5·5 decreased NH2 volatilization by 95%, while lowering pig slurry pH to 6·0 decreased NH3 volatilization by 82%. A field experiment, measuring the volatilization of NH3 for 2 h after application to grassland stubble of slurry acidified to pH values between 7·5 and 5, gave similar results to the laboratory study. Titration curves were constructed within the pH range of 9 to 4 with cow and pig slurries. There was a significant (P < 0·05) positive correlation between the NH4+-N content of the slurries and the volume of acid required to attain a target pH of 6·0 for pig slurries and a pH of 5·5 for cow slurries. One litre of slurry containing 2 g of NH4+-N required c. 20 ml of 5 M H2SO4 for acidification.
Mechanistic studies on the decomposition of water soluble azo-radical-initiators

Spin trapping with nitrones coupled with the use of electron paramagnetic resonance (EPR) is one of the most effective techniques to observe reactive radical oxygen species (RROS), even though the distinction between, for example, alkoxyl and alkylperoxyl radicals is not an easy task. In the light of this very problem, this work summarizes our results using three nitrones as spin traps and three water soluble amidino-azo-initiators as sources for alkylperoxyl and/or alkoxyl radicals. The principal conclusion of this study is that only the corresponding alkoxyl radicals were found to add to the nitrones, and no evidence was found for the alkylperoxyl radical-spin adducts. The spin traps 5-(diethoxyphosphoryl)-5-methyl-4,5-dihydro-3H-pyrrole N-oxide (DEPMPO) as well as methyl-N-durylnitrone (MDN) rendered a discriminative spin adduct assignment much simpler as compared to 5,5-dimethyl-4,5-dihydro-3H-pyrrole N-oxide (DMPO), where liquid chromatography–electrospray mass spectrometry (LC–ESMS) was employed to substantiate the EPR results. For the kinetic decomposition behavior of the azo initiators it was found that at pH 6.2 2,2′-azobis(2-methylpropionamidine) dihydrochloride (AAPH) undergoes hydrolysis to the corresponding amides while the cyclic initiators 2,2′-azobis[2-(2-imidazolin-2-yl)propane] dihydrochloride (VA-44) and 2,2′-azobis{2-[2-(4-methyl)imidazolin-2-yl]propane} dihydrochloride (Me-VA-44) are resistant towards hydrolysis over the employed timescale of 30 h.
Using FALCES against bias in automated decisions by integrating fairness in dynamic model ensembles

: As regularly reported in the media, automated classifications and decisions based on machine learning models can cause unfair treatment of certain groups of a general population. Classically, the machine learning models are designed to make highly accurate decisions in general. When one machine learning model is not sufficient to define the possibly complex boundary between classes, multiple “specialized” models are used within a model ensemble to further boost accuracy. In particular, dynamic model ensembles pick the most accurate model for each query object, by applying the model that performed best on similar data. Given the labeled data on which models are trained, it is not surprising that any bias possibly present in the data will reflect in the classifiers using the models. To mitigate this, recent work has proposed fair model ensembles , that instead of focusing (solely) on accuracy also optimize global fairness , which is quantified using bias metrics. However, such global fairness that globally minimizes bias may exhibit imbalances in different regions of the data, e.g., caused by some local bias maxima leading to local unfairness . In this paper, we propose to bridge the gap between dynamic model ensembles and fair model ensembles and investigate the problem of devising locally fair and accurate dynamic model ensembles, which ultimately optimize for equal opportunity of similar subjects. Our evaluation shows that our approach outperforms the state-of-the-art for different types and degrees of bias present in training data in terms of both local and global fairness, while reaching comparable accuracy.
Combining Programming-by-Example with Transformation Discovery from large Databases

: Data transformation discovery is one of the most tedious tasks in data preparation. In particular, the generation of transformation programs for semantic transformations is tricky because additional sources for look-up operations are necessary. Current systems for semantic transformation discovery face two major problems: either they follow a program synthesis approach that only scales to a small set of input tables, or they rely on extraction of transformation functions from large corpora, which requires the identification of exact transformations in those resources and is prone to noisy data. In this paper, we try to combine approaches to benefit from large corpora and the sophistication of program synthesis. To do so, we devise a retrieval and pruning strategy ensemble that extracts the most relevant tables for a given transformation task. The extracted resources can then be processed by a program synthesis engine to generate more accurate transformation results than state-of-the-art.
Precise, Compact, and Fast Data Access Counters for Automated Physical Database Design

: Today’s database management systems offer numerous tuning knobs that allow an adaptation of database system behavior to specific customer needs, e.g., maximal throughput or minimal memory consumption. Because manual tuning by database experts is complicated and expensive, academia and industry devised tools that automate physical database tuning. The effectiveness of such advisor tools strongly depends on the availability of accurate statistics about the executed database workload. For advisor tools to run online, workload execution statistics must also be collected with low runtime and memory overhead. However, to the best of our knowledge, no approach collects precise, compact, and fast workload execution statistics for a physical database design tool. In this paper, we present data structures that solve the problem of providing workload execution statistics with high precision, low memory consumption, and low runtime overhead. In particular, we show how existing approaches can be combined and for which advisor tools, new data structures need to be designed. We evaluate our data structures in a prototype of a commercial database and show that they outperform previous approaches using real-world and synthetic benchmarks.
Management considerations in the adult with surgically modified d-transposition of the great arteries

Dextro-transposition of the great arteries (D-TGA) has undergone a significant evolution in surgical repair, leading to survivors with vastly different postsurgical anatomy which in turn guides their long-term cardiovascular morbidity and mortality. Atrial switch repair survivors are limited by a right ventricle in the systemic position, arrhythmia and atrial baffles prone to obstruction or leak. Functional assessment of the systemic right ventricle is complex, requiring multimodality imaging to include specialised echocardiography and cross-sectional imaging (MRI and CT). In the current era, most neonates undergo the arterial switch operation with increasing understanding of near-term and long-term outcomes specific to their cardiac anatomy. Long-term observations of the Lecompte manoeuvre or coronary stenoses following transfer continue, with evolving understanding to improve surveillance. Ultimately, an understanding of postsurgical anatomy, specialised imaging techniques and interventional and electrophysiological procedures is essential to comprehensive care of D-TGA survivors.
Characterization of defined metal-containing supramolecular block copolymers

The characterization of metal-containing supramolecular polymers by gel permeation chromatography (GPC) or matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS) is complicated because of the interaction of the charged materials with the GPC column material in the first case and fragmentation due to the applied laser energy in the latter case. In this contribution we report recent advances made for the characterization of supramolecular polymers based on terpyridine metal complexes utilizing GPC and MALDI-TOF MS. In particular for GPC analysis, the choice of solvent and additive was found to be crucial for a successful characterization. Furthermore, MALDI-TOF MS spectra of these compounds are not straightforward to interpret. Both aspects are discussed in detail with the result of a better understanding and improved analysis possibilities of the mentioned supramolecular polymers.
GIBBS MEASURES FOR SEMIDEFINITE PROGRAMMING

These notes document an ongoing study of Gibbs measures for semideﬁnite programming. Soft and hard constraint models are introduced and the partition function is explicitly computed in terms of Harish-Chandra (HC) integrals. The structure of this formula involves a generalized heat ﬂow in a dual space, along with a Hamilton-Jacobi limit as β → ∞ .
Hybrid Feature Selection and Ensemble Learning Methods for Gene Selection and Cancer Classification

A promising research field in bioinformatics and data mining is the classification of cancer based on gene expression results. Efficient sample classification is not supported by all genes. Thus, to identify the appropriate genes that help efficiently distinguish samples, a robust feature selection method is needed. Redundancy in the data on gene expression contributes to low classification performance. This paper presents the combination for gene selection and classification methods using ranking and wrapper methods. In ranking methods, information gain was used to reduce the size of dimensionality to 1% and 5%. Then, in wrapper methods K-nearest neighbors and Naïve Bayes were used with Best First, Greedy Stepwise, and Rank Search. Several combinations were investigated because it is known that no single model can give the best results using different datasets for all circumstances. Therefore, combining multiple feature selection methods and applying different classification models could provide a better decision on the final predicted cancer types. Compared with the existing classifiers, the proposed assembly gene selection methods obtained comparable performance. Keywords—Microarray; gene selection; ensemble classification; cancer classification; gene expression
Attitude towards obesity and its treatment – analysis of the attitudes of patients with obesit

Background. Knowledge is one of the key individual measures for prevention and treatment of overweight and obesity. Objectives. We wanted to find out what the attitudes of obese patients towards their own disease were. It was also our goal to identify the sources of knowledge on obesity and learn about their significance in the perception of the disease. Material and methods. The study was conducted between February and March 2019. 621 patients suffering from obesity participated in it. The study was conducted with the use of the CAWI technique and an original, self-made research tool. Results. 81.1% of our respondents revealed that they did not accept their obesity. For the patients, electronic media was the main source of knowledge concerning the disease. 30.4% of respondents declared that they make use of information obtained from other patients. A similar percentage (30.1%) stated that they used academic publications. Only 19.2% received knowledge about the illness from medical staff, most frequently from primary care physicians (77.8%), doctors of other specialisations (74.5%) and nutritionists (63.2%). Patients indicated a low level of knowledge concerning patients’ rights, possibilities for getting psychological support and rehabilitation during the disease. Conclusions. Most patients declared a will to start obesity treatment. A large group (30%) required encouragement to start therapy and obtain support during obesity treatment. Medical staff are in need of information support, thanks to which they will be able to serve as a reliable source of knowledge concerning obesity treatment methods.
Designing Stable Elections: A Survey

We survey the design of elections that are resilient to attempted interference by third parties. For example, suppose votes have been cast in an election between two candidates, and then each vote is randomly changed with a small probability, independently of the other votes. It is desirable to keep the outcome of the election the same, regardless of the changes to the votes. It is well known that the US electoral college system is about 5 times more likely to have a changed outcome due to vote corruption, when compared to a majority vote. In fact, Mossel, O'Donnell and Oleszkiewicz proved in 2005 that the majority voting method is most stable to this random vote corruption, among voting methods where each person has a small influence on the election. We discuss some recent progress on the analogous result for elections between more than two candidates. In this case, plurality should be most stable to corruption in votes. We also survey results on adversarial election manipulation (where an adversary can select particular votes to change, perhaps in a non-random way), and we briefly discuss ranked choice voting methods (where a vote is a ranked list of candidates).
Dermatologic findings in patients with exogenous obesity: A prospective- clinical investigation

Obesity caused by overnutrition without any underlying organic problem is referred to as exogenous (primary) obesity. The aim of this study was to investigate dermatologic findings and their associations with anthropometric parameters in patients with exogenous obesity. From the patients with presenting symptom of obesity, we included 66 with the diagnosis of exogenous obesity. We excluded the patients with following diseases that might cause dermatologic symptoms: Diabetes mellitus, hyperthyroidism, hypothyroidism, polycystic ovarian syndrome, renal diseases, and hepatic diseases. After comprehensive dermatologic examination, we noted all findings for each patient. We performed a statistical analysis to assess the association between dermatological findings and body- mass index, waist circumference, hip circumference and waist/hip ratio. Sixty-four (97%) patients had at least one dermatologic finding. The most common dermatologic findings were plantar hyperkeratosis (63.6%), stria (56.1%), acrochordon (56.1%), and hyperhidrosis (54.5%). Presence of plantar hyperkeratosis, stria, and hyperhidrosis were significantly higher in females compared with males (p=0.013, p=0.004, p=0.032, respectively). The mean body mass index was significantly higher in patients with acanthosis nigricans and keratosis pilaris (p=0.016). The mean waist circumference was significantly higher in patients with hirsutism (p