nils-herrmann/clean_scirepeval huggingface dataset:
An Inhibitor of Mutant IDH1 Delays Growth and Promotes Differentiation of Glioma Cells
Venue: Science
Year: 2013

IDHology Among the most exciting drug targets to emerge from cancer genome sequencing projects are two related metabolic enzymes, isocitrate dehydrogenases 1 and 2 (IDH1, IDH2) Mutations in the IDH1 and IDH2 genes are common in certain types of human cancer. Whether inhibition of mutant IDH activity might offer therapeutic benefits is unclear (see the Perspective by Kim and DeBerardinis) F. Wang et al. (p. 622, published online 4 April) isolated a small molecule that selectively inhibits mutant IDH2, describe the structural details of its binding to the mutant enzyme, and show that this compound suppresses the growth of patient derived leukemia cells harboring the IDH2 mutation. Rohle et al. (p. 626, published online 4 April) show that a small molecule inhibitor of IDH1 selectively slows the growth of patient derived brain tumor cells with the IDH1 mutation. A small molecule that inhibits a mutant enzyme in tumors slows malignant growth by inducing cancer cell differentiation.  The recent discovery of mutations in metabolic enzymes has rekindled interest in harnessing the altered metabolism of cancer cells for cancer therapy. One potential drug target is isocitrate dehydrogenase 1 (IDH1) which is mutated in multiple human cancers. Here, we examine the role of mutant IDH1 in fully transformed cells with endogenous IDH1 mutations. A selective R132H IDH1 inhibitor (AGI 5198) identified through a high throughput screen blocked, in a dose dependent manner, the ability of the mutant enzyme (mIDH1) to produce R 2 hydroxyglutarate (R 2HG) Under conditions of near complete R 2HG inhibition, the mIDH1 inhibitor induced demethylation of histone H3K9me3 and expression of genes associated with gliogenic differentiation. Blockade of mIDH1 impaired the growth of IDH1 mutant but not IDH1 wild type glioma cells without appreciable changes in genome wide DNA methylation. These data suggest that mIDH1 may promote glioma growth through mechanisms beyond its well characterized epigenetic effects.
BART Seq: cost effective massively parallelized targeted sequencing for genomics, transcriptomics, and single cell analysis
Venue: Genome Biology
Year: 2019

We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, which are all pre selected and optimized in silico. By applying the matrices in a novel workflow named Barcode Assembly foR Targeted Sequencing (BART Seq) we analyze developmental states of thousands of single human pluripotent stem cells, either in different maintenance media or upon Wnt/b catenin pathway activation, which identifies the mechanisms of differentiation induction. Moreover, we apply BART Seq to the genetic screening of breast cancer patients and identify BRCA mutations with very high precision. The processing of thousands of samples and dynamic range measurements that outperform global transcriptomics techniques makes BART Seq first targeted sequencing technique suitable for numerous research applications.
Different Nanomaterials for Soil Remediation Affect Avoidance Response and Toxicity Response in Earthworm (Eisenia fetida)
Venue: Bulletin of Environmental Contamination and Toxicology
Year: 2020

The application of nano level passivating agents in the remediation of soil heavy metal pollution has received widespread attention, but its harm to soil animals should also be addressed. This study explored the effect of three nanomaterials nanohydroxyapatite apatite (n HAP) nano zeolite (n zeolite) and nanometer iron oxide (n Fe3O4) on catalase (CAT) peroxidase (POD) and superoxide dismutase (SOD) activity and malondialdehyde (MDA) content through filter paper contact test. The effects of nanomaterials spiked at 1.5%wt of soils on earthworm avoidance behavior were also be studied, and the crystallinity and surface charge of three nanomaterials were characterized. The results showed that the activities of CAT, SOD and POD and the content of MDA have been changed at different level. And earthworms have obvious avoidance behavior to the three kinds of nanomaterials. Therefore, nanomaterials do have adverse effects on earthworms, and their biological toxicity should be considered when selecting passivating agents for soil heavy metal pollution remediation.
Droplet Regulation and Dropwise Condensation Heat Transfer Enhancement on Hydrophobic Superhydrophobic Hybrid Surfaces
Year: 2018

Efficient Dropwise condensation on nanostructured superhydrophobic surfaces (SHS) has received extensive attention. However, good heat performance only occurs in two conditions: the presence of non condensable gas, or low surface subcooling. For industrial pure steam condensation, large droplets tend to be pinned on the surfaces due to the large contact angle hysteresis (CAH) and impede heat transfer process. In this study, the SHSs and hydrophobic surface (HS) were integrated in spaced band pattern with different width and CAH. It was observed that the condensed droplets experience a fast horizontal shifting from hydrophobic zones to superhydrophobic zones driven by adhesive force. In this way, the departure path of droplets were altered and the refreshing frequencies are increased for both SHS and HS regions. The heat transfer coefficients for some 1 mm x 1 mm hybrid surfaces were found to be elevated by about 25% at subcooling of 6K compared to the weighted mean value of individual HSs and SHSs. For surfaces with short dividing distance (about 0.5 mm x 0.5 mm) the bridging effects between droplets in SHS regions were also observed, which is undesirable for heat transfer. These work indicates that strong adhesive force of SHSs can function as a promoter of droplet condensation for hybrid surfaces with proper choice of dividing width.
Affective Embodiment: The effect of avatar appearance and posture representation on emotions in VR
Venue: 2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)
Year: 2020

Avatar embodiment allows for the study of self perception. Avatars can communicate an identity through appearance customization, and signal an emotional state through facial expression and body posture. Following these ideas, I have developed two lines of research to study the experience of avatar embodiment on mental health. In one, I explore how avatar representation intersects with identity. I examine how issues with equitable representation in avatar customization affects users. In the second, I explore the potential of embodied VR to affect emotional states. I manipulate how avatar postures are represented and examine the effects on user's emotional states. Overall, my research asks what kinds of emotions and values are avatars capable of communicating and how that can affect an individual's experience of a virtual world and be translated into therapeutic interventions.
Perfectionism and achievement goals revisited: The 3 x 2 achievement goal framework
Year: 2017

Perfectionistic strivings (PS) and perfectionistic concerns (PC) have shown different profiles with the 2 x 2 achievement goals in sport. Whether PS and PC also show comparable profiles with the achievement goals of the expanded 3 x 2 framework, however, is unclear.  We examined self reported perfectionistic strivings, perfectionistic concerns, and the 3 x 2 achievement goals in 136 junior athletes (mean age 17.0 years)  The results of structural equation modeling showed that PS were positively associated with task self and other approach goals and negatively with task and self avoidance goals. In contrast, PC were positively associated with task self and other avoidance goals and negatively with task and self approach goals.  The findings suggest that PS and PC show different profiles also with the 3 x 2 achievement goals which may help explain why the two perfectionism dimensions show differential relations with achievement related outcomes in sport. HighlightsWe examined perfectionistic strivings (PS) and perfectionistic concerns (PC).Profiles were compared using the 3 x 2 achievement goal framework.PS and PC showed unique profiles.PS were positively associated with approach goals.PC were positively associated with avoidance goals.
Ulnar Nerve Management with Distal Humerus Fracture Fixation: A Meta Analysis.
Venue: Hand clinics
Year: 2018

Ulnar nerve dysfunction following distal humerus fractures is a well recognized phenomenon. There is no consensus regarding optimal handling of the ulnar nerve during surgical management of these fractures between in situ management and transposition. Using an electronic database to identify retrospective studies involving surgical fixation of distal humerus fractures yielded 46 studies, 5 trials meeting the authors' inclusion criteria, totaling 362 patients. An overall incidence of 19.3% for ulnar neuropathy was identified. Of those patients undergoing in situ release, the incidence was 15.3% Of those who underwent transposition, there was a 23.5% incidence of ulnar neuropathy.
Penicillin binding protein 3 is a common adaptive target among Pseudomonas aeruginosa isolates from adult cystic fibrosis patients treated with b lactams.
Venue: International journal of antimicrobial agents
Year: 2019

Determining the mechanisms that modulate b lactam resistance in clinical Pseudomonas aeruginosa (P. aeruginosa) isolates can be challenging, as the molecular profiles identified in mutation based or expression based resistance determinant screens may not correlate with in vitro phenotypes. One of the lesser studied resistance mechanisms in P. aeruginosa is the modification of penicillin binding protein 3 (pbpB/ftsI) This study reported that nonsynonymous polymorphisms within pbpB frequently occur among b lactam resistant sputum isolates, and are associated with unique antibiotic susceptibility patterns.  Longitudinally collected isolates (n 126) from cystic fibrosis (CF) patients with or without recent b lactam therapy or of non clinical origin were tested for susceptibility to six b lactams (aztreonam, ceftazidime, cefsulodin, cefepime, meropenem, and piperacillin) Known b lactam resistance mechanisms were characterised by polymerase chain reaction (PCR) based methods, and polymorphisms in the transpeptidase encoding domain of pbpB identified by sequencing.  Twelve nonsynonymous polymorphisms were detected among 86 isolates (67% from five CF patients with a history of b lactam therapy, compared with one polymorphism in 30 (3.3% from three patients who had not received b lactam treatments. No nonsynonymous polymorphisms were found in ten environmental isolates. Multiple pbpB alleles, often with different combinations of polymorphisms, were detected within the population of strains from each CF patient for up to 2.6 years. Traditional patterns of ampC or mexA de repression reduced expression of oprD or the presence of extended spectrum b lactamases were not observed in resistant isolates with nonsynonymous polymorphisms in pbpB.  This study's findings suggest that pbpB is a common adaptive target, and may contribute to the development of b lactam resistance in P. aeruginosa.
Clinical Management of Critical COVID 19 Patients: Insights from the Literature and "On the Field" Experience
Venue: Journal of Neuroanaesthesiology and Critical Care
Year: 2020

The recent outbreak of the coronavirus disease (COVID 19) is a health emergency all over the world. Several health care professionals are currently putting their best efforts to deal with this situation. The aim of this review is to report insights from the literature and "on the field" experience in clinical management of critical COVID 19 patients. Respiratory support varies from high flow nasal cannula (HFNC) to noninvasive and invasive mechanical ventilation, often associated with nitric oxide, prone position, and extracorporeal membrane oxygenation (ECMO) Experienced specialists have to manage the airways minimizing any contamination and virus spread. The hemodynamic management of critical COVID 19 patients requires not only an accurate fluid strategy, but also an appropriate use of vasopressors and inotropes. Various adjuvant treatments have been proposed: antiviral drugs, immunomodulators, anticoagulants, antibiotics, and nutrition.
Dynamics of pore formation during laser powder bed fusion additive manufacturing
Venue: Nature Communications
Year: 2019

Laser powder bed fusion additive manufacturing is an emerging 3D printing technique for the fabrication of advanced metal components. Widespread adoption of it and similar additive technologies is hampered by poor understanding of laser metal interactions under such extreme thermal regimes. Here, we elucidate the mechanism of pore formation and liquid solid interface dynamics during typical laser powder bed fusion conditions using in situ X ray imaging and multi physics simulations. Pores are revealed to form during changes in laser scan velocity due to the rapid formation then collapse of deep keyhole depressions in the surface which traps inert shielding gas in the solidifying metal. We develop a universal mitigation strategy which eliminates this pore formation process and improves the geometric quality of melt tracks. Our results provide insight into the physics of laser metal interaction and demonstrate the potential for science based approaches to improve confidence in components produced by laser powder bed fusion.Laser matter interactions during laser powder bed fusion additive manufacturing remain poorly understood. Here, the authors combine in situ X ray imaging and finite element simulations to show how detrimental pores form under printing conditions and develop a strategy to suppress them.
Estimating the true global burden of mental illness.
Venue: The lancet. Psychiatry
Year: 2016

We argue that the global burden of mental illness is underestimated and examine the reasons for under estimation to identify five main causes: overlap between psychiatric and neurological disorders; the grouping of suicide and self harm as a separate category; conflation of all chronic pain syndromes with musculoskeletal disorders; exclusion of personality disorders from disease burden calculations; and inadequate consideration of the contribution of severe mental illness to mortality from associated causes. Using published data, we estimate the disease burden for mental illness to show that the global burden of mental illness accounts for 32*4% of years lived with disability (YLDs) and 13*0% of disability adjusted life years (DALYs) instead of the earlier estimates suggesting 21*2% of YLDs and 7*1% of DALYs. Currently used approaches underestimate the burden of mental illness by more than a third. Our estimates place mental illness a distant first in global burden of disease in terms of YLDs, and level with cardiovascular and circulatory diseases in terms of DALYs. The unacceptable apathy of governments and funders of global health must be overcome to mitigate the human, social, and economic costs of mental illness.
Learning Algorithms from Bayesian Principles
Year: 2019

Machine learning algorithms are commonly derived using ideas from optimization and statistics, followed by an extensive empirical efforts to make them practical as there is a lack of underlying principles to guide this process. In this paper, we present a learning rule derived from Bayesian principles, which enables us to connect a wide variety of learning algorithms. Using this rule, we can derive a wide range of learning algorithms in fields such as probabilistic graphical models, continuous optimization, and deep learning. This includes classical algorithms such as least squares, Newton's method, and Kalman filter, as well as modern deep learning algorithms such as stochastic gradient descent, RMSprop and Adam. Overall, we show that Bayesian principles not only unify, generalize, and improve existing learning algorithms, but also help us design new ones.
A COMPARATIVE STUDY ON PERCEPTION OF CONSUMERS TOWARDS E WALLETS
Year: 2020

Mobile users now days use their smart phones to make money transfers or purchases via apps installed on the device. In addition to mobile payments, users tend to save receipts, vouchers, business cards, bills etc. in their devices as well. It is labeled as "Digital Wallet" or "Mobile Wallet" because smart phones are going to act like leather wallets. Advancement of technology opens up the new market for the suppliers. But it is important to understand consumer adoption patterns to market new products or brands. Therefore, the present study was conducted to know about the perception of consumers towards E wallets. The sample size of the present study consisted of 250 respondents which were selected using convenience sampling technique. Further the data was collected using questionnaire which comprised of multiple choice questions based on the awareness towards the adoption of e wallets.
What keeps the mobile hotel booking users loyal? Investigating the roles of self efficacy, compatibility, perceived ease of use, and perceived convenience
Venue: Int. J. Inf. Manag.
Year: 2016

Convenience, compatibility, and PEOU are positively associated with MHB loyalty.Compatibility significantly influences PEOU and perceived convenience.PEOU has a significant impact on perceived convenience. With the advancements in mobile technologies, mobile hotel booking (MHB) has become an important distribution channel for hotels and online travel agencies (OTAs) Understanding MHB users loyalty intentions toward this technology has become equally important for MHB service providers, as it is essential for them to retain their customers. However, existing literature in the context of mobile booking has mainly focused on the adoption and acceptance of this technology. The purpose of this paper is to empirically test a research model that incorporates antecedents of mobile shopping loyalty in a hotel booking context. The proposed model was tested through structural equation modeling (SEM) by using empirical data collected from 396 MHB users. Study results revealed that convenience, compatibility, and perceived ease of use (PEOU) had a significant impact on the users loyalty intentions toward MHB technology. In addition, compatibility significantly influenced PEOU and convenience and PEOU had a significant impact on loyalty and convenience. Study results provide valuable theoretical and practical implications for various players in the hotel and travel industry including hoteliers, OTAs, mobile app developers and hospitality technology vendors.
STRATEGIES OF ELECTRIC BUS IMPLEMENTATION IN SOEKARNO HATTA AIRPORT USING STRENGTH WEAKNESS OPPORTUNITY THREAT (SWOT) ANALYSIS AND QUANTITATIVE STRATEGIC PROGRAMMING MATRIX
Year: 2020

Most of the transportation in Indonesia still uses oil as their fuel, thus Indonesia is currently facing one of the Energy Security issues which are oil availability. Nowadays, Indonesia doesn't have sufficient oil production, consequently, Indonesia must import oil to meet its daily demand. Furthermore, Indonesia also dealing with an environmental issue from the transportation sector, which is air pollution. Air pollution is one of the non military threats that threaten the lives of many people in Indonesia. The non military defense is an effort made to ward off non military threats. One of the ways to fight air pollution is to reduce the use of oil in the transportation sector. Currently, the development of innovative technology in the field of transportation is increasingly oriented to electric vehicles (EV) This is due to EVs that do not produce gas emissions, increase energy efficiency, and reduce oil consumption. In August 2018, a one week trial runs on an electric bus at Soekarno Hatta Airport conducted to looking for responses from passengers when boarding an electric bus as an airport shuttle bus. Therefore, this study will be further determining the strategies of electric bus implementation at Soekarno Hatta Airport. The method used is a qualitative method using a case study approach and Strength Weakness Opportunity Threat Analysis with Quantitative Strategic Programming Matrix. This study concludes that the strategy that has to be implemented first for electric bus implementation in Soekarno Hatta Airport is Strength Opportunity 3 (SO3) strategy, which is collaborating with Bus Companies to become a pioneer in electric bus implementation in Indonesia's Airport and improve the Eco Airports Status.
Do Nonpartisan Programmatic Policies Have Partisan Electoral Effects? Evidence from Two Large Scale Experiments
Venue: The Journal of Politics
Year: 2020

A vast literature demonstrates that voters around the world who benefit from government discretionary spending increase their electoral support for the incumbent party. But, contrary to theories of political accountability, some suggest that voters also reward incumbent parties for "programmatic" spending, over which incumbents have no discretion, even when passed with support from all major parties. Why voters would attribute responsibility when none exists is unclear, as is why minority parties would support legislation that costs them votes. We study two prominent programmatic policies. For the first, we design and implement one of the largest randomized social experiments ever. For the second, we reanalyze studies that came to opposite conclusions, using a large scale randomized experiment and a natural experiment. By improving statistical methods and correcting data errors, we show that evidence from all analyses of both policies is consistent: programmatic policies have no measurable effect on voter support for incumbents.
MAXIMIN EFFECTS IN INHOMOGENEOUS LARGE SCALE DATA BY NICOLAI MEINSHAUSEN
Year: 2015

Large scale data are often characterized by some degree of inhomogeneity as data are either recorded in different time regimes or taken from multiple sources. We look at regression models and the effect of randomly changing coefficients, where the change is either smoothly in time or some other dimension or even without any such structure. Fitting varying coefficient models or mixture models can be appropriate solutions but are computationally very demanding and often return more information than necessary. If we just ask for a model estimator that shows good predictive properties for all regimes of the data, then we are aiming for a simple linear model that is reliable for all possible subsets of the data. We propose the concept of "maximin effects" and a suitable estimator and look at its prediction accuracy from a theoretical point of view in a mixture model with known or unknown group structure. Under certain circumstances the estimator can be computed orders of magnitudes faster than standard penalized regression estimators, making computations on large scale data feasible. Empirical examples complement the novel methodology and theory.