nils-herrmann/clean_scirepeval huggingface dataset:
Brain damage from anticancer treatments in adults.

Treatment-induced brain toxicity remains a major cause of morbidity in adult patients with cancer. Contrasting with the 40-year-old unresolved controversy about the primary damaging event (vascular versus parenchymal) in the physiopathology, numerous prospective clinical trials have recently addressed the question of brain toxicity. Despite remarkable efforts in methodological design, they often only partially answer the questions of which treatment modalities are responsible, which brain functions are mainly impaired, how long the impairment duration is and which characteristics make patients vulnerable.



Real advances in the design of safer radiation procedures have been counterbalanced by a wider use of combined radiotherapy-chemotherapy regimens, the development of radiosurgery and the increasing number of long-term survivors. Although classic radionecrosis or chemonecrosis has become less common, more subtle changes such as progressive cognitive dysfunction are increasingly reported after radiotherapy (radiation-induced leukoencephalopathy) or chemotherapy, administered alone or in combination as reviewed here. The methodological aspects of published studies are questioned and suggestions are provided that may improve the design of future trials.



The abovementioned issue is of clinical importance given the number of patients treated for brain tumors, including patients with brain metastases, and the number of patients who are at high risk for brain metastasis who could benefit from prophylactic cranial irradiation. Moreover, drugs used in nonbrain tumors are now recognized to impair brain normal functioning.
Intended and unintended pregnancies worldwide in 2012 and recent trends.

Periodic estimation of the incidence of global unintended pregnancy can help demonstrate the need for and impact of family planning programs. We draw upon multiple sources of data to estimate pregnancy incidence by intention status and outcome at worldwide, regional, and subregional levels in 2012 and to assess recent trends using previously published estimates for 2008 and 1995. We find that 213 million pregnancies occurred in 2012, up slightly from 211 million in 2008. The global pregnancy rate decreased only slightly from 2008 to 2012, after declining substantially between 1995 and 2008. Eighty-five million pregnancies, representing 40 percent of all pregnancies, were unintended in 2012. Of these, 50 percent ended in abortion, 13 percent ended in miscarriage, and 38 percent resulted in an unplanned birth. The unintended pregnancy rate continued to decline in Africa and in the Latin America and Caribbean region. If the aims of the London Summit on Family Planning are carried out, the incidence of unwanted and mistimed pregnancies should decline in the coming years.
Von Willebrand disease type 1: a diagnosis in search of a disease.

Von Willebrand disease (VWD) type 1 is reported to be common but frequently is difficult to diagnose. Many people have nonspecific mild bleeding symptoms, von Willebrand factor (VWF) levels display low heritability, and low VWF levels (15% to 50% of normal) are weak risk factors for bleeding. Therefore, bleeding and low VWF levels often associate by chance. Even with stringent diagnostic criteria based on a triad of bleeding symptoms, a low VWF level, and a positive family history, the prevalence of "false-positive" VWD type 1 is comparable to the published prevalence of the disease. Consequently, many patients diagnosed with VWD type 1 do not have a specific hemorrhagic disease at all, which limits the utility of the diagnosis. This unfortunate reality is a consequence of trying to force patients into binary categories of "diseased" or "healthy" that are incompatible with the continuous biologic context in which VWF functions. The problem may be avoided by substituting an empirical epidemiologic approach like that applied to other modest risk factors for disease such as elevated cholesterol and high blood pressure. Such a risk management strategy could be generalized to include other hemorrhagic and thrombotic risk factors.
Bladder cancer: clinical and pathological profile.

Bladder tumours represent a heterogeneous group of cancers. The natural history of these bladder cancers is that of recurrence of disease and progression to higher grade and stage disease. Furthermore, recurrence and progression rates of superficial bladder cancer vary according to several tumour characteristics, mainly tumour grade and stage. The most recent World Health Organization (WHO) classification of tumours of the urinary system includes urothelial flat lesions: flat hyperplasia, dysplasia and carcinoma in situ. The papillary lesions are broadly subdivided into benign (papilloma and inverted papilloma), papillary urothelial neoplasia of low malignant potential (PUNLMP) and non-invasive papillary carcinoma (low or high grade). The initial proposal of the 2004 WHO has been achieved, with most reports supporting that categories are better defined than in previous classifications. An additional important issue is that PUNLMP, the most controversial proposal of the WHO in 2004, has lower malignant behaviour than low-grade carcinoma. Whether PUNLMP remains a clinically useful category, or whether this category should be expanded to include all low-grade, stage Ta lesions (PUNLMP and low-grade papillary carcinoma) as a wider category of less aggressive tumours not labelled as cancer, needs to be discussed in the near future. This article summarizes the recent literature concerning important issues in the pathology and the clinical management of patients with bladder urothelial carcinoma. Emphasis is placed on clinical presentation, the significance of haematuria, macroscopic appearance (papillary, solid or mixed, single or multiple) and synchronous or metachronous presentation (field disease vs monoclonal disease with seeding), classification and microscopic variations of bladder cancer with clinical significance, TNM distribution and the pathological grading according to the 2004 WHO proposal.
Performance evaluation of a specific IgE assay developed for the ADVIA centaur immunoassay system.

To develop and evaluate a liquid phase immunoassay for accurate determination of allergen-specific IgE (sIgE) as a useful tool in the diagnosis of allergy patients.



A fully automated, quantitative sIgE assay was developed for the ADVIA Centaur technology platform using a unique calibration method based on a recombinant reference allergen. Compared to most other IgE-assays, the assay employs a reverse sandwich architecture using monoclonal mouse anti-human IgE antibody covalently bound to paramagnetic particles in the solid phase and capturing the sample IgE. Bound sIgE reacts with liquid biotin-labeled allergen, which is detected as chemiluminescence using acridiniumester-labeled streptavidin.



The ADVIA Centaur sIgE assay (Centaur assay) has exclusive reactivity to human IgE and performs with excellent linearity in the assay range 0.35-100 kU/L and high precision (imprecision within-run <2.6%, between-run <4.9%, and total imprecision <7.1%). The analytical sensitivity is <0.10 kU/L. Using Pharmacia CAP system FEIA (CAP) as a comparative method, positive/negative concordance was 94% at 0.35 kU/L cut-off, and the Centaur assay has a sensitivity of 90% and a specificity of 98%. Validation of the assay in a general population sample (The Copenhagen allergy study) revealed that sIgE was highly associated with a clinical diagnosis of inhalation allergy.



The Centaur assay is an allergen-specific assay for measurement of IgE without interference from other types of immunoglobulins or nonspecific IgE. The assay performs with a linear reaction, high assay range, and good reproducibility. The assay correlates well with the CAP system and is in agreement with clinical diagnosis.
Distance-based k-nearest neighbors outlier detection method in large-scale traffic data

This paper presents a k-nearest neighbors (kNN) method to detect outliers in large-scale traffic data collected daily in every modern city. Outliers include hardware and data errors as well as abnormal traffic behaviors. The proposed kNN method detects outliers by exploiting the relationship among neighborhoods in data points. The farther a data point is beyond its neighbors, the more possible the data is an outlier. Traffic data here was recorded in a video format, and converted to spatial-temporal (ST) traffic signals by statistics. The ST signals are then transformed to a two-dimensional (2D) (x, y) -coordinate plane by Principal Component Analysis (PCA) for dimension reduction. The distance-based kNN method is evaluated by unsupervised and semi-supervised approaches. The semi-supervised approach reaches 96.19% accuracy.
Dose-dependent augmentation of cardiac systolic function with the selective cardiac myosin activator, omecamtiv mecarbil: a first-in-man study

Decreased systolic function is central to the pathogenesis of heart failure in millions of patients worldwide, but mechanism-related adverse effects restrict existing inotropic treatments. This study tested the hypothesis that omecamtiv mecarbil, a selective cardiac myosin activator, will augment cardiac function in human beings.



In this dose-escalating, crossover study, 34 healthy men received a 6-h double-blind intravenous infusion of omecamtiv mecarbil or placebo once a week for 4 weeks. Each sequence consisted of three ascending omecamtiv mecarbil doses (ranging from 0·005 to 1·0 mg/kg per h) with a placebo infusion randomised into the sequence. Vital signs, blood samples, electrocardiographs (ECGs), and echocardiograms were obtained before, during, and after each infusion. The primary aim was to establish maximum tolerated dose (the highest infusion rate tolerated by at least eight participants) and plasma concentrations of omecamtiv mecarbil; secondary aims were evaluation of pharmacodynamic and pharmacokinetic characteristics, safety, and tolerability. 
The maximum tolerated dose of omecamtiv mecarbil was 0·5 mg/kg per h. Omecamtiv mecarbil infusion resulted in dose-related and concentration-related increases in systolic ejection time (mean increase from baseline at maximum tolerated dose, 85 [SD 5] ms), the most sensitive indicator of drug effect (r(2)=0·99 by dose), associated with increases in stroke volume (15  mL), fractional shortening (8% ), and ejection fraction (7% ; all p<0·0001). Omecamtiv mecarbil increased atrial contractile function, and there were no clinically relevant changes in diastolic function. There were no clinically significant dose-related adverse effects on vital signs, serum chemistries, ECGs, or adverse events up to a dose of 0·625 mg/kg per h. The dose-limiting toxic effect was myocardial ischaemia due to excessive prolongation of systolic ejection time.



These first-in-man data show highly dose-dependent augmentation of left ventricular systolic function in response to omecamtiv mecarbil and support potential clinical use of the drug in patients with heart failure.
Nanostructured biosensor for detecting glucose in tear by applying fluorescence resonance energy transfer quenching mechanism.

In this paper, a nanostructured biosensor is developed to detect glucose in tear by using fluorescence resonance energy transfer (FRET) quenching mechanism. The designed FRET pair, including the donor, CdSe/ZnS quantum dots (QDs), and the acceptor, dextran-binding malachite green (MG-dextran), was conjugated to concanavalin A (Con A), an enzyme with specific affinity to glucose. In the presence of glucose, the quenched emission of QDs through the FRET mechanism is restored by displacing the dextran from Con A. To have a dual-modulation sensor for convenient and accurate detection, the nanostructured FRET sensors were assembled onto a patterned ZnO nanorod array deposited on the synthetic silicone hydrogel. Consequently, the concentration of glucose detected by the patterned sensor can be converted to fluorescence spectra with high signal-to-noise ratio and calibrated image pixel value. The photoluminescence intensity of the patterned FRET sensor increases linearly with increasing concentration of glucose from 0.03mmol/L to 3mmol/L, which covers the range of tear glucose levels for both diabetics and healthy subjects. Meanwhile, the calibrated values of pixel intensities of the fluorescence images captured by a handhold fluorescence microscope increases with increasing glucose. Four male Sprague-Dawley rats with different blood glucose concentrations were utilized to demonstrate the quick response of the patterned FRET sensor to 2µL of tear samples.
The Mechanics of n-Player Differentiable Games

The cornerstone underpinning deep learning is the guarantee that gradient descent on an objective converges to local minima. Unfortunately, this guarantee fails in settings, such as generative adversarial nets, where there are multiple interacting losses. The behavior of gradient-based methods in games is not well understood – and is becoming increasingly important as adversarial and multiobjective architectures proliferate. In this paper, we develop new techniques to understand and control the dynamics in general games. The key result is to decompose the second-order dynamics into two components. The first is related to potential games, which reduce to gradient descent on an implicit function; the second relates to Hamiltonian games, a new class of games that obey a conservation law, akin to conservation laws in classical mechanical systems. The decomposition motivates Symplectic Gradient Adjustment (SGA), a new algorithm for finding stable fixed points in general games. Basic experiments show SGA is competitive with recently proposed algorithms for finding stable fixed points in GANs – whilst at the same time being applicable to – and having guarantees in – much more general games.
Unsupervised Learning for Trustworthy IoT

The advancement of Internet-of-Things (IoT) edge devices with various types of sensors enables us to harness diverse information with Mobile Crowd-Sensing applications (MCS). This highly dynamic setting entails the collection of ubiquitous data traces, originating from sensors carried by people, introducing new information security challenges; one of them being the preservation of data trustworthiness. What is needed in these settings is the timely analysis of these large datasets to produce accurate insights on the correctness of user reports. Existing data mining and other artificial intelligence methods are the most popular to gain hidden insights from IoT data, albeit with many challenges. In this paper, we first model the cyber trustworthiness of MCS reports in the presence of intelligent and colluding adversaries. We then rigorously assess, using real IoT datasets, the effectiveness and accuracy of well-known data mining algorithms when employed towards IoT security and privacy. By taking into account the spatio-temporal changes of the underlying phenomena, we demonstrate how concept drifts can masquerade the existence of attackers and their impact on the accuracy of both the clustering and classification processes. Our initial set of results clearly show that these unsupervised learning algorithms are prone to adversarial infection, thus, magnifying the need for further research in the field by leveraging a mix of advanced machine learning models and mathematical optimization techniques.
Semantic projection: recovering human knowledge of multiple, distinct object features from word embeddings

The words of a language reflect the structure of the human mind, allowing us to transmit thoughts between individuals. However, language can represent only a subset of our rich and detailed cognitive architecture. Here, we ask what kinds of common knowledge (semantic memory) are captured by word meanings (lexical semantics). We examine a prominent computational model that represents words as vectors in a multidimensional space, such that proximity between wordvectors approximates semantic relatedness. Because related words appear in similar contexts, such spaces – called “word embeddings” – can be learned from patterns of lexical co-occurrences in natural language. Despite their popularity, a fundamental concern about word embeddings is that they appear to be semantically “rigid”: inter-word proximity captures only overall similarity, yet human judgments about object similarities are highly context-dependent and involve multiple, distinct semantic features. For example, dolphins and alligators appear similar in size, but differ in intelligence and aggressiveness. Could such context-dependent relationships be recovered from word embeddings? To address this issue, we introduce a powerful, domain-general solution: “semantic projection” of word-vectors onto lines that represent various object features, like size (the line extending from the word “small” to “big”), intelligence (“dumb” → “smart”), or danger (“safe” → “dangerous”). This method, which is intuitively analogous to placing objects “on a mental scale” between two extremes, recovers human judgments across a range of object categories and properties. We thus show that word embeddings inherit a wealth of common knowledge from word co-occurrence statistics and can be flexibly manipulated to express context-dependent meanings.
Face Detection and Recognition in Color Images under Matlab

In this paper we describe our implementation of algorithms for face detection and recognition in color images under Matlab. For face detection, we trained a feedforward neural network to perform skin segmentation, followed by the eyes detection, face alignment, lips detection and face delimitation. The eyes were detected by analyzing the chrominance and the angle between neighboring pixels and, then, the results were used to perform face alignment. The lips were detected based on the analysis of the Red color component intensity in the lower face region. Finally, the faces were delimited using the eyes and lips positions. The face recognition involved a classifier that used the standard deviation of the difference between color matrices of the faces to identify the input face. The algorithms were run on Faces 1999 dataset. The proposed method achieved 96.9%, 89% and 94% correct detection rate of face, eyes and lips, respectively. The correctness rate of the face recognition algorithm was 70.7%.
Implicit learning and statistical learning: one phenomenon, two approaches

The domain-general learning mechanisms elicited in incidental learning situations are of potential interest in many research fields, including language acquisition, object knowledge formation and motor learning. They have been the focus of studies on implicit learning for nearly 40 years. Stemming from a different research tradition, studies on statistical learning carried out in the past 10 years after the seminal studies by Saffran and collaborators, appear to be closely related, and the similarity between the two approaches is strengthened further by their recent evolution. However, implicit learning and statistical learning research favor different interpretations, focusing on the formation of chunks and statistical computations, respectively. We examine these differing approaches and suggest that this divergence opens up a major theoretical challenge for future studies.
Supply Chain Management and Retailing

Retailers are now the dominant partners in most suply systems and have used their positions to re-engineer operations and partnership s with suppliers and other logistic service providers. No longer are retailers the pass ive recipients of manufacturer allocations, but instead are the active channel con trollers organizing supply in anticipation of, and reaction to consumer demand. T his paper reflects on the ongoing transformation of retail supply chains and logistics. If considers this transformation through an examination of the fashion, grocery and selected other retail supply chains, drawing on practical illustrations. Current and fut ure challenges are then discussed.  Retailers were once the passive recipients of produ cts allocated to stores by manufacturers in the hope of purchase by consumers and replenished o nly at the whim and timing of the manufacturer. Today, retailers are the controllers of product supply in anticipation of, and reaction to, researched, understood, and real-time customer demand. Retailers now control, organise, and manage the supply chain from producti on to consumption. This is the essence of the retail logistics and supply chain transforma tion that has taken place since the latter part of the twentieth century. Retailers have become the channel captains and set the pace in logistics. Having extended their channel control and focused on corporate effi ci ncy and effectiveness, retailers have
Hard- and soft-tissue contributions to the esthetics of the posed smile in growing patients seeking orthodontic treatment.

The purpose of this investigation was to broaden the understanding of how various skeletal, dental, and soft-tissue relationships are related to the esthetics of the smile in patients with malocclusions before orthodontic treatment.



Images of the posed smile were captured from digital video clips of 60 growing patients (33 girls, 27 boys) seeking orthodontic treatment; they were judged by panels of laypersons and orthodontists. Discriminant analysis identified determinants of the "pleasing smile" from the results of a visual analog scale. Quantitative measurements of the soft and hard tissues were made by using the smile images, cephalometric radiographs, and study models. The esthetics of the smile were correlated with specific skeletal, dental, and soft-tissue structures in the anteroposterior, vertical, and transverse dimensions (Pearson test on non-topographic correlations).



The esthetic smile judgments of orthodontists agreed with those of laypersons (r >0.93). The vertical thicknesses of the lips were the most significant component of a pleasant smile, for both the orthodontists (upper lip) and laypersons (lower lip) (discriminant power: 75%). The vertical thickness of the upper lip had a significant positive correlation with the position of the maxillary incisor.



Vertical lip thickness proved to be the most influential variable in smile esthetics. The significant relationship of incisor protrusion with the vertical thickness of the vermilion border of the upper lip must be considered when planning orthodontic treatment.
Centralized, Parallel, and Distributed Information Processing during Collective Sensemaking

Widespread rumoring can hinder attempts to make sense of what is going on during disaster scenarios. Understanding how and why rumors spread in these contexts could assist in the design of systems that facilitate timely and accurate sensemaking. We address a basic question in this line: To what extent does rumor evolution occur (1) through reliance on a centralized information source, (2) in parallel information silos, or (3) through a web of complex informational interactions? We develop a conceptual model and associated analysis algorithms that allow us to distinguish between these possibilities. We analyze a case of rumoring on Twitter during the Boston Marathon Bombing. We find that rumor spreading was predominantly a parallel process in this case, which is consistent with a hypothesis that information silos may underlie the persistence of false rumors. Special attention towards detecting and resolving parallel information threads during collective sensemaking may hence be warranted.