gebhart/patrepeval huggingface dataset:
Abstract 19457: Cardioprotective Effects of the Novel Mitochondrial-Derived Peptide, Humanin, in a Porcine Model of Myocardial Ischemia-Reperfusion Injury (2016)

Background: Humanin, a novel mitochondria-associated peptide, has previously been shown to exert potent cytoprotective and anti-apoptotic effects in rodent models of myocardial ischemia/reperfusion...
Radiosynthesis of [11C]LY2795050 for Preclinical and Clinical PET Imaging Using Cu(II)-Mediated Cyanation (2018)

Copper-mediated <sup>11</sup>C-cyanation reactions have enabled the synthesis of PET radiotracers from a range of readily available precursors and avoid the need to use more toxic Pd catalysts. In this work we adapt our recently developed <sup>11</sup>C-cyanation of arylpinacolboronate (BPin) esters for the cGMP synthesis of [<sup>11</sup>C]LY2795050, a selective antagonist radiotracer for the kappa opioid receptor (KOR). [<sup>11</sup>C]LY2795050 was synthesized in 6 ± 1% noncorrected radiochemical yield (based on [<sup>11</sup>C]HCN, <i>n</i> = 3) using an automated synthesis module. Quality control testing confirmed the suitability of doses for preclinical and clinical PET imaging (radiochemical purity >99%; specific activity >900 mCi/μmol; residual Cu < 0.1 μg/mL). PET imaging was conducted in rodent and nonhuman primates, showing good brain uptake of [<sup>11</sup>C]LY2795050 and the expected distribution of KOR. Analogous imaging with [<sup>11</sup>C]carfentanil (a selective mu opioid receptor (MOR) radiotracer) revealed the anticipated regional differences in MOR and KOR distribution in the primate brain.
A novel scheduling algorithm for IP traffic in adaptive modulation system (2003)

One property, bandwidth uneven distributed with time slots (BUDTS) in the adaptive modulation wireless system destroys an implicit assumption of traditional traffic scheduling algorithm that the bandwidth is evenly distributed with time slots. Therefore, new scheme fit for such circumstance is needed. We propose a novel algorithm, named adaptive differentiated compensation fair queuing (ADCFQ), to provide basic QoS requirement and fair residual bandwidth sharing to all backlogged flows, as well as the compensation mechanism to the lagged flows due to burst channel error. Simulation shows that in ADCFQ, the effect of uneven bandwidth distribution is well considered.
Supplemental video 4 from NCI Imaging Data Commons (2023)

Supplemental video 4 from NCI Imaging Data Commons
The Chelation-controlled Mukaiyama Aldol Reaction of Chiral α- and β-Alkoxy Aldehydes (2013)

Abstract The concept of treating chiral α- and β-alkoxy aldehydes with bicoordinate Lewis acids such as TiCl4, SnCl4, or MgBr2 followed by the addition of carbon nucleophiles for achieving chelation control with 1,2- and 1,3-asymmetric induction, respectively, was introduced three decades ago and has since evolved into a general method. In the case of enol silanes, the chelation-controlled Mukaiyama aldol reaction is involved, which has been used in recent natural products syntheses.
Konzeptionelle Grundlagen (2003)

Der Begriff Innovation (lat. innovatio) bedeutet „Neuerung“ oder „Erneuerung“ und beschreibt etwas, „das bisher in dieser Form nicht bestanden hat“70. Innovation wurde in verschiedenen wissenschaftlichen Disziplinen untersucht.71 In der Betriebswirtschaftslehre geht die Beschäftigung mit Innovationen auf Schumpeter zurück.72 Dieser sprach allerdings nicht explizit von Innovationen, sondern von neuen Kombinationen von Produktionsmitteln und deren mutativen Durchsetzung.73 Der Begriff Innovation wird in der Literatur sehr facettenreich beschrieben;74 entsprechend wurde eine Vielzahl von Definitionen entwickelt.75 Diese Vielzahl an Definitionen zeigt einerseits die Existenz einer in der Managementliteratur nicht ungewöhnlichen Modeerscheinung, sie ist andererseits jedoch auch ein Ausdruck der Bestrebungen, Innovation als Phänomen verstehen, beschreiben und damit auch gestalten zu wollen.76
Phase II Study of Clofarabine in Pediatric Patients With Refractory or Relapsed Acute Myeloid Leukemia (2009)

Purpose To determine the efficacy and safety of clofarabine in pediatric patients with refractory or relapsed acute myeloid leukemia (AML). Patients and Methods A phase II, open-label, multicenter study was conducted with single-agent clofarabine in pediatric patients with refractory or relapsed AML. Clofarabine was administered intravenously over 2 hours at the pediatric maximum-tolerated dose (MTD) of 52 mg/m 2 daily for 5 consecutive days. Cycles were repeated every 2 to 6 weeks. Responses determined by an independent response review panel. Results The 42 patients treated on the study had a median age of 13 years (range, 2 to 22 years) and had received a median number of two (range, one to five) prior regimens. The response rate was 26% and included one complete response without platelet recovery and 10 partial responses. The median duration of response was 20 weeks (range, 2 to ≥ 156 weeks). Six of 28 patients who were refractory to the immediately preceding therapy achieved response. Thirteen patients (31%), including seven responders, proceeded to hematopoietic stem-cell transplantation (HSCT) after treatment with clofarabine and survived between 24 to ≥ 160 weeks. Five patients (12%) remain alive post-transplantation at ≥ 63, ≥ 71, ≥ 86, ≥ 114, and ≥ 130 weeks. The most common grade 3 or greater adverse events without regard to causality were febrile neutropenia, catheter-related infection, epistaxis, hypotension, nausea, and fever. Transient elevation of liver enzymes and hypokalemia occurred frequently. Five patients died within 30 days of clofarabine administration secondary to progressive disease, and another five died as a result of an adverse event. Conclusion Clofarabine is active in pediatric patients with multiply relapsed or refractory AML. Responses allowed several refractory patients to proceed to HSCT. The toxicity profile was expected in this patient population.
Approximate static aeroelastic analysis of composite wings (2018)

Purpose The purpose of this paper is to consider divergence of composite plate wings as well as slender wings with thin-walled cross-section of small-size airplanes. The main attention is paid to establishing of closed-form mathematical solutions for models of wings with coupling effects. Simplified solutions for calculating the divergence speed of wings with different geometry are established. Design/methodology/approach The wings are modeled as anisotropic plate elements and thin-walled beams with closed cross-section. Two-dimensional plate-like models are applied to analysis and design problems for wings of large aspect ratio. Findings At first, the equations of elastic deformation for anisotropic slender, plate-like wing with the large aspect ratio are studied. The principal consideration is delivered to the coupled torsion-bending effects. The influence of anisotropic tailoring on the critical divergence speed of the wing is examined in closed form. At second, the method is extended to study the behavior of the large aspect ratio, anisotropic wing with box-like wings. The static equations of the wing with box-like profile are derived using the theory of anisotropic thin-walled beams with closed cross-section. The solutions for forward-swept wing with box-like profiles are given in analytical formulas. The formulas for critical divergence speed demonstrate the dependency upon cross-sectional shape characteristics and anisotropic properties of the wing. Research limitations/implications The following simplifications are used: the simplified aerodynamic theory for the wings of large aspect ratio was applied; the static aeroelastic instability is considered (divergence); according to standard component methodology, only the component of wing was modeled, but not the whole aircraft; the simplified theories (plate-lime model for flat section or thin-walled beam of closed-section) were applied; and a single parameter that defines the rotation of a stack of single layers over the face of the wing. Practical implications The simple, closed-form formulas for an estimation of critical static divergence are derived. The formulas are intended for use in designing of sport aircraft, gliders and small unmanned aircraft (drones). No complex analysis of airflow and advanced structural and aerodynamic models is necessary. The expression for chord length over the span of the wing allows for accounting a board class of wing shapes. Social implications The derived theory facilitates the use of composite materials for popular small-size aircraft, and particularly, for drones and gliders. Originality/value The closed-form solutions for thin-walled beams in steady gas flow are delivered in closed form. The explicit formulas for slender wings with variable chord and stiffness along the wing span are derived.
Breast cancer genome and transcriptome integration implicates specific mutational signatures with immune cell infiltration (2016)

A recent comprehensive whole genome analysis of a large breast cancer cohort was used to link known and novel drivers and substitution signatures to the transcriptome of 266 cases. Here, we validate that subtype-specific aberrations show concordant expression changes for, for example, TP53, PIK3CA, PTEN, CCND1 and CDH1. We find that CCND3 expression levels do not correlate with amplification, while increased GATA3 expression in mutant GATA3 cancers suggests GATA3 is an oncogene. In luminal cases the total number of substitutions, irrespective of type, associates with cell cycle gene expression and adverse outcome, whereas the number of mutations of signatures 3 and 13 associates with immune-response specific gene expression, increased numbers of tumour-infiltrating lymphocytes and better outcome. Thus, while earlier reports imply that the sheer number of somatic aberrations could trigger an immune-response, our data suggests that substitutions of a particular type are more effective in doing so than others.
The Analysis of Diglucosyl Gallic Acid and Cationic Surfactant Mixtures for Damaged Hair (2020)

毛髪はダメージを受けると表面の疎水性，強度，弾性が低下することがしられている。われわれはダメージ毛に，ジグルコシル没食子酸（以下，DGA）とカチオン性界面活性剤であるトリメチルステアリルアンモニウムクロリド（以下，STAC）の水溶液を用いて上記3つの物性値変化を検証した。その結果，DGAとSTACを用いた場合，ダメージを受けていない毛髪と同等値までその値が回復することが明らかになった。これらの物性値変化に対し，DGAおよびSTACが作用する毛髪部位を明らかにするため，飛行時間型2次イオン質量分析法（ToF-SIMS）および走査型電子顕微鏡（SEM）を用いて解析を行った。その結果，DGAおよびSTACはキューティクル表面およびキューティクル層へ作用していることが示唆された。
Validation of Align Technology's Treat IIITM digital model superimposition tool and its case application (2003)

Using the palate, as a stable reference seemed to work well and the evaluation of the single case showed that many, but not all, of the planned movements occurred.
SegFormer: Simple and Efficient Design for Semantic Segmentation with\n Transformers (2021)

We present SegFormer, a simple, efficient yet powerful semantic segmentation\nframework which unifies Transformers with lightweight multilayer perception\n(MLP) decoders. SegFormer has two appealing features: 1) SegFormer comprises a\nnovel hierarchically structured Transformer encoder which outputs multiscale\nfeatures. It does not need positional encoding, thereby avoiding the\ninterpolation of positional codes which leads to decreased performance when the\ntesting resolution differs from training. 2) SegFormer avoids complex decoders.\nThe proposed MLP decoder aggregates information from different layers, and thus\ncombining both local attention and global attention to render powerful\nrepresentations. We show that this simple and lightweight design is the key to\nefficient segmentation on Transformers. We scale our approach up to obtain a\nseries of models from SegFormer-B0 to SegFormer-B5, reaching significantly\nbetter performance and efficiency than previous counterparts. For example,\nSegFormer-B4 achieves 50.3% mIoU on ADE20K with 64M parameters, being 5x\nsmaller and 2.2% better than the previous best method. Our best model,\nSegFormer-B5, achieves 84.0% mIoU on Cityscapes validation set and shows\nexcellent zero-shot robustness on Cityscapes-C. Code will be released at:\ngithub.com/NVlabs/SegFormer.\n
Multi-Scale Defense of Adversarial Images (2019)

Deep learning has achieved great success in image classification. However, recent researches show that existing deep learning-based classifiers remain weak for recognizing adversarial images. In this paper, an effective multi-scale defense method is proposed to solve the problem. In our method, an input image is first evolved by Gaussian kernels of different intensities to generate a multi-scale representation of the image. These evolved images are then fed into a classifier trained with a multi-scale strategy to yield multi-scale confidences. Finally, an average confidence is exploited to generate classification result. Furthermore, by monitoring the change of confidence values during the image evolution process, our method is able to achieve an indication of the attacking risk. Experimental results show that our method performs favorably against a number of state-of-the-art methods.
Lurasidone HCl (Latuda), an Oral, Once-Daily Atypical Antipsychotic Agent for the Treatment of Patients with Schizophrenia. (2011)

In a given year, approximately 2.4 million American adults, or about 1.1% of the population 18 years of age and older, have schizophrenia.1,2 Men and women are affected with equal frequency. A severe, chronic brain disorder, schizophrenia is characterized by an onset in early adulthood, a lifelong course, debilitating symptoms, deterioration in functional ability, and lack of social acceptability, making it among the most disabling, and economically catastrophic disorders.2 Symptoms appear in men in their late teens or early 20s, whereas women are generally affected in their 20s or early 30s.3 In the U.S., annual direct and indirect costs of the disorder total more than $62 billion.4

Four symptom clusters have been observed in large groups of patients.5 Positive symptoms (psychosis) are correlated with hospital admission and a first-time diagnosis. Delusions are the most common psychotic symptom and occur in 65% of patients with schizophrenia.6,7 Hallucinations and disorganized thinking occur in approximately 50% of these patients. Auditory hallucinations are the most common sensory disturbance, but visual, tactile, olfactory, and gustatory hallucinations may occur.8 Most patients experience a combination of delusions, hallucinations, and thought disorganization.6

Negative symptoms represent a loss of affective responsiveness, verbal expression, personal motivation, enjoyment, social drive, or attention to the environment.9 All cognitive domains are also affected by the disorder, including attention, language, memory, and executive function.10 The combination of blunted, inappropriate, and odd expressions is the most common affective disturbance in schizophrenia.11 Depressive symptoms are the most common mood disturbance in schizophrenia.12

In 2002, direct annual health care costs were estimated at $22.7 billion for the U.S., $7.6 billion in other direct costs, and $32.4 billion in lost economic productivity and caregiver costs, for a total of $62.7 billion.4 Schizophrenia accounts for 2.5% of all health care expenditures, 25% of hospital beds, and 20% of all Social Security benefit days. 13 Genetic and environmental risk factors contribute to the development of schizophrenia, with alterations in neurotransmitter pathways (e.g., with dopamine) and enlarged sulci and ventricles found on brain imaging.14
Extended treatment with bupropion SR for cigarette smoking cessation. (2006)

The authors present results of a randomized clinical trial of the efficacy of extended treatment with bupropion SR in producing longer term cigarette smoking cessation. Adult smokers (N = 362) received open-label treatment (11 weeks) that combined relapse prevention training, bupropion SR, and nicotine patch followed by extended treatment (14 weeks) with bupropion SR or matching placebo. Abstinence percentages were relatively high (week 11: 52%; week 25: bupropion, 42%; placebo, 38%; week 52: bupropion, 33%; placebo, 34%), but bupropion SR did not surpass placebo. Gender and baseline craving level were identified as significant, independent moderators of treatment response. Men were more likely to abstain than women (week 11: 59% vs. 43%, p = .001; week 25: 48% vs. 31%, p = .001; week 52: 39% vs. 27%, p = .01). Because most smokers suffer relapse with any current cessation treatment, the comparatively high abstinence percentages achieved in this trial are of interest.
Brain White Matter Abnormality Induced by Chronic Spinal Cord Injury in the Pediatric Population: A Preliminary Tract-based Spatial Statistic Study (2021)

Objectives: Tract-based spatial statistics (TBSS) is a diffusion tensor imaging (DTI)–based processing technique that aims to improve the objectivity and interpretability of analysis of multisubject diffusion imaging studies. This study used TBSS to measure quantitative changes in brain white matter structures following spinal cord injury (SCI). Methods: Eighteen SCI subjects aged 8–20 years old (mean age, 16.5 years) were scanned using a conventional single-shot EPI DTI protocol using a 3.0T Siemens MR scanner. All participants underwent a complete International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) examination to determine the level and severity of injury. Five participants were classified as American Spinal Injury Association Impairment Scale (AIS) A, nine as AIS B, and four as AIS C/D. Imaging parameters used for data collection were as follows: 20 directions, b = 1000 s/mm2, voxel size = 1.8 mm x 1.8 mm, slice thickness = 5 mm, TE = 95 ms, TR = 4300 ms, slices = 30, TA = 4:45 min. To generate TBSS, nonparametric permutation tests were used for voxel-wise statistical analysis of the fractional anisotropy (FA) skeletons between AIS groups. A two-tailed t test was applied to extract voxels with significant differences at p &amp;lt; .05. Results: Notable significant changes occurred throughout the corticospinal, spinothalamic, and dorsal column/medial lemniscus tracts. Altered regions in the temporal, occipital, and parietal lobes were also identified. Conclusion: These results suggest that white matter structures are altered differently between people with different AIS classifications. TBSS has the potential to serve as a screening tool to identify white matter changes in regions of interest.
High SARS-CoV-2 Prevalence among Healthcare Workers in Cochabamba, Bolivia (2022)

Healthcare workers (HCWs) are at increased risk of SARS-CoV-2 infection. The aim of the study was to estimate the SARS-CoV-2 seroprevalence among HCWs in Cochabamba, Bolivia and to determine the potential risk factors. In January 2021, a cross-sectional SARS-CoV-2 seroprevalence study was conducted in 783 volunteer clinical and non-clinical HCWs in tertiary care facilities. It was based on IgG detection using ELISA, chemiluminiscence, and seroneutralisation tests from dried blood spots. Analysis revealed a high seroprevalence (43.4%) of SARS-CoV-2 IgG antibodies. The combination of anosmia and ageusia (OR: 68.11; 95%-CI 24.83-186.80) was predictive of seropositivity. Belonging to the cleaning staff (OR: 1.94; 95%-CI 1.09-3.45), having more than two children in the same house (OR: 1.74; 95%-CI 1.12-2.71), and having been in contact with a close relative with COVID-19 (OR: 3.53; 95%-CI 2.24-5.58) were identified as risk factors for seropositivity in a multivariate analysis. A total of 47.5% of participants had received medication for COVID-19 treatment or prevention, and only ~50% of symptomatic subjects accessed PCR or antigenic testing. This study confirms a massive SARS-CoV-2 attack rate among HCWs in Cochabamba by the end of January 2021. The main risk factors identified are having a low-skilled job, living with children, and having been in contact with an infected relative in the household.
Efficient Learning of Inverse Dynamics Models for Adaptive Computed Torque Control (2022)

Modelling robot dynamics accurately is essential for control, motion optimisation and safe human-robot collaboration. Given the complexity of modern robotic systems, dynamics modelling remains non-trivial, mostly in the presence of compliant actuators, mechanical inaccuracies, friction and sensor noise. Recent efforts have focused on utilising data-driven methods such as Gaussian processes and neural networks to overcome these challenges, as they are capable of capturing these dynamics without requiring extensive knowledge beforehand. While Gaussian processes have shown to be an effective method for learning robotic dynamics with the ability to also represent the uncertainty in the learned model through its variance, they come at a cost of cubic time complexity rather than linear, as is the case for deep neural networks. In this work, we leverage the use of deep kernel models, which combine the computational efficiency of deep learning with the non-parametric flexibility of kernel methods (Gaussian processes), with the overarching goal of realising an accurate probabilistic framework for uncertainty quantification. Through using the predicted variance, we adapt the feedback gains as more accurate models are learned, leading to low-gain control without compromising tracking accuracy. Using simulated and real data recorded from a seven degree-of-freedom robotic manipulator, we illustrate how using stochastic variational inference with deep kernel models increases compliance in the computed torque controller, and retains tracking accuracy. We empirically show how our model outperforms current state-of-the-art methods with prediction uncertainty for online inverse dynamics model learning, and solidify its adaptation and generalisation capabilities across different setups.
TRICEP: Technologies of RFID and image recognition in a checkout enhancement platform (2019)

The presence of the Internet, Machine Learning, as well as the Internet of Things, have greatly improved many aspects of various industries globally. One of the main benefactors of these technological advancements in the industry, is with retail stores. Beginning from informative websites, online transactions, user-friendly retail applications, and recently, intelligent mobile applications; these have paved the way for retail industries, to improve in various aspects such as process improvement, transaction speed, data accuracy, inventory tracking, customer experience, and others. Organization such as Amazon Go makes use of deep learning, computer vision, and various sensors to provide a “Just Walk Out” shopping experience, allowing for the currently most advanced shopping technology. TPiSHOP, FutureProof Grocery, Future Store, and Regi-Robo Robotic Checkout and Bagging System focuses on allowing self-scanning of items via RFID or QR codes, with some of them having additional self-checkout capabilities. Although these technologies are already available in many countries and many retail industries have started to use them, they are typically known to be very costly to implement and use proprietary technologies, while some of them have not been fully tested nor integrated for use in production. The research investigates an approach to improve retail industries by developing a cost-effective and integrated checkout enhancement platform that implements RFID and image recognition using deep learning, a smart shopping basket, and a real-time integrated tool to improve the customer transaction process.