nils-herrmann/clean_scirepeval huggingface dataset:
Neoadjuvant Chemotherapy for Breast Cancer: Functional Tumor Volume by MR Imaging Predicts Recurrence free Survival Results from the ACRIN 6657/CALGB 150007 I SPY 1 TRIAL.
Venue: Radiology

To evaluate volumetric magnetic resonance (MR) imaging for predicting recurrence free survival (RFS) after neoadjuvant chemotherapy (NACT) of breast cancer and to consider its predictive performance relative to pathologic complete response (PCR)  This HIPAA compliant prospective multicenter study was approved by institutional review boards with written informed consent. Women with breast tumors 3 cm or larger scheduled for NACT underwent dynamic contrast enhanced MR imaging before treatment (examination 1) after one cycle (examination 2) midtherapy (examination 3) and before surgery (examination 4) Functional tumor volume (FTV) computed from MR images by using enhancement thresholds, and change from baseline (DFTV) were measured after one cycle and before surgery. Association of RFS with FTV was assessed by Cox regression and compared with association of RFS with PCR and residual cancer burden (RCB) while controlling for age, race, and hormone receptor (HR) human epidermal growth factor receptor type 2 (HER2) status. Predictive performance of models was evaluated by C statistics.  Female patients (n 162) with FTV and RFS were included. At univariate analysis, FTV2, FTV4, and DFTV4 had significant association with RFS, as did HR/HER2 status and RCB class. PCR approached significance at univariate analysis and was not significant at multivariate analysis. At univariate analysis, FTV2 and RCB class had the strongest predictive performance (C statistic 0.67; 95% confidence interval [CI] 0.58, 0.76) greater than for FTV4 (0.64; 95% CI: 0.53, 0.74) and PCR (0.57; 95% CI: 0.39, 0.74) At multivariate analysis, a model with FTV2, DFTV2, RCB class, HR/HER2 status, age, and race had the highest C statistic (0.72; 95% CI: 0.60, 0.84) CONCLUSION Breast tumor FTV measured by MR imaging is a strong predictor of RFS, even in the presence of PCR and RCB class. Models combining MR imaging, histopathology, and breast cancer subtype demonstrated the strongest predictive performance in this study.
Clinical relevance of host immunity in breast cancer: from TILs to the clinic
Venue: Nature Reviews Clinical Oncology

The clinical relevance of the host immune system in breast cancer has long been unexplored. Studies developed over the past decade have highlighted the biological heterogeneity of breast cancer, prompting researchers to investigate whether the role of the immune system in this malignancy is similar across different molecular subtypes of the disease. The presence of high levels of lymphocytic infiltration has been consistently associated with a more favourable prognosis in patients with early stage triple negative and HER2 positive breast cancer. These infiltrates seem to reflect favourable host antitumour immune responses, suggesting that immune activation is important for improving survival outcomes. In this Review, we discuss the composition of the immune infiltrates observed in breast cancers, as well as data supporting the clinical relevance of host antitumour immunity, as represented by lymphocytic infiltration, and how this biomarker could be used in the clinical setting. We also discuss the rationale for enhancing immunity in breast cancer, including early data on the efficacy of T cell checkpoint inhibition in this setting.
Simulacion del proceso de produccion de bioetanol a partir de la mezcla glucosa/xilosa incluyendo los efectos de temperatura, pH y concentracion de azucares

En este trabajo se propone un modelo modificado para la produccion de bioetanol basado en la ecuacion cinetica de Monod. El modelo incluye los efectos de inhibicion de sustrato y producto, la limitacion de sustrato y algunos pseudo parametros que son funcion de las condiciones de operacion: temperatura, pH y concentracion de glucosa y xilosa. A partir de datos experimentales reportados en la literatura se lleva a cabo un analisis multivariable con el cual se ajustan los pseudo parametros. Los resultados de las simulaciones con el modelo propuesto son comparados contra los datos experimentales, y contra un modelo de parametros constantes reportado en la literatura. El error promedio obtenido con el modelo propuesto es menor que el error generado con el modelo reportado y reproduce las variables de proceso a diferentes condiciones de operacion con un error promedio del 8.2%
Scientific Evolution from Mix Integrating Mechatronics to Cyber Intelligent Mechatronics and to Claytronics Science

This paper presents for the first time national scientific developments and technical technological systems from Mix Integrating Mechatronics and Cyber Intelligent Mechatronics to Claytronics Science by highlighting the fundamental knowledge, concepts and new constructive solutions at micro nanoscale and their applications in industry economy and society. As scientific impact of this paper updating the specialists knowledges from Romania to the latest research directions from the intelligent specailized domain of Mix Integrating Mechatronics in Intelligent Mechatronics, and Cyber Intelligent Mechatronics to Claytronics Science for manufacturing new smart and hiper intelligent products demanded by the New Knowledge for New Society. The paper presents the contribution of scientific team in development of new systems and and intelligent cyber mechatronics equipments transferred and implemented in industry and in the economy in Romania.
Meaning, scope functions of philosophy of education"

Philosophy is a search for a general understanding of values and reality by chiefly speculative rather than observational means. It signifies a natural and necessary urge in human beings to know themselves and the world in which they live and move and have their being. Western philosophy remained more or less true to the etymological meaning of philosophy in being essentially an intellectual quest for truth. Philosophy is intensely spiritual and has always emphasized the need for practical realization of Truth. Philosophy is a comprehensive system of ideas about human nature and the nature of the reality we live in. It is a guide for living, because the issues it addresses are basic and pervasive, determining the course we take in life and how we treat other people. Hence we can say that all the aspects of human life are influenced and governed by the philosophical consideration. As a field of study philosophy is one of the oldest disciplines. It is considered as a mother of all the sciences. In fact it is at the root of all knowledge. Education has also drawn its material from different philosophical bases. Education, like philosophy is also closely related to human life. Therefore, being an important life activity education is also greatly influenced by philosophy.
Asynchronous data translation framework for converting relational tables to document stores

Although Not Only SQL (NoSQL) techniques have some new features such as query optimization and caching in the era of big data, it is not mature enough to replace traditional Relational Database Management System (RDBMS) In a long period of time, the hybrid solution of RDBMS and NoSQL is a main steam technology. In this paper, we present an asynchronous data framework to translate relational tables into schema free document stores. The challenge of this framework is how to ensure that the translation is transparent and pervasive to the application with minimal impact on RDBMS performance. To better describe the translation process, we present the intermediate cell state model (CSM) to describe versioning incremental state. We address this challenges by translating the binary log of RDBMS to CSM repository, and the repository is reset to the NoSQL when encountering schema adjustment asynchronously. Finally, we leverage the CSM rectification algorithm and NoSQL synchronization algorithm to implement the whole framework. The experimental results illustrate that this translation has a less minimal impact on RDBMS performance and lower cost than other solutions.
Querying a multi version trajectory data warehouse
Venue: Int. J. Bus. Inf. Syst.

Trajectory data warehouses, which gather data about mobile objects' activities may be autonomous and consequently may change frequently their structures and contents. This kind of change can alter the trajectory data warehouse associated schema, the analysis process and thus the decision making requirements on which the initial conceptual model is performed. For this reason, a TDW maintenance technique is needed to adapt the defined schema. In this paper, we will focus on maintaining a trajectory data warehouse after schema changes using for that the versioning approach which allows the existence of many versions of a same trajectory data warehouse. However, querying such data warehouse versions is considered as a big challenge since data returned by queries may vary according to queried versions. Hence, a solution to ensure data mapping between different versions is required in order to give valid results necessary for providing elements leading to efficient decisions.
Oblivious Transfer with Fine Grained Access Control from Ciphertext Policy Attribute Based Encryption in the Standard Model

In this work, an oblivious transfer with complex access control scheme that is constructed based on ciphertext policy attribute based encryption (CP ABE) scheme is proposed. In this scheme, the database server can enforce fine grained access control for each record where the authorized user is allowed to access, but the unauthorized user cannot, whereas it learns neither which record a user accesses, nor which attributes a user has. This scheme has the advantages as follows: First, it allows the expressive access control policies where access structures are based on linear secret sharing scheme that directly supports AND, OR and Threshold gates. Second, the communication complexity in this scheme is constant in the numbers of records which have been accessed. Third, this scheme is constructed in prime order bilinear group. Fourth, this scheme is secure in the standard model. To the best of our knowledge, this scheme is the first to obtain these features simultaneously.
CONCOLOR: Constrained Non Convex Low Rank Model for Image Deblocking
Venue: IEEE Transactions on Image Processing

Due to independent and coarse quantization of transform coefficients in each block, block based transform coding usually introduces visually annoying blocking artifacts at low bitrates, which greatly prevents further bit reduction. To alleviate the conflict between bit reduction and quality preservation, deblocking as a post processing strategy is an attractive and promising solution without changing existing codec. In this paper, in order to reduce blocking artifacts and obtain high quality image, image deblocking is formulated as an optimization problem within maximum a posteriori framework, and a novel algorithm for image deblocking using constrained non convex low rank model is proposed. The lp (0 p 1) penalty function is extended on singular values of a matrix to characterize low rank prior model rather than the nuclear norm, while the quantization constraint is explicitly transformed into the feasible solution space to constrain the non convex low rank optimization. Moreover, a new quantization noise model is developed, and an alternatively minimizing strategy with adaptive parameter adjustment is developed to solve the proposed optimization problem. This parameter free advantage enables the whole algorithm more attractive and practical. Experiments demonstrate that the proposed image deblocking algorithm outperforms the current state of the art methods in both the objective quality and the perceptual quality.
What is more important: defibrillation or compression?
Venue: Journal of thoracic disease

Cardiac arrest (CA) is one of the leading causes of death and is responsible for approximately 400,000 deaths per year in the United States (1) A recent investigation (American Heart Association) showed that more than 200,000 inpatients had CA in 2013 in the United States (2) China has approximately 540,000 deaths from CA each year, ranking first in the world. However, the success rate of rescue for CA is extremely low and the success rate of prehospital resuscitation for patients with CA is only 4.2% in the capital of China, Beijing (medically developed area) (3)
Family Systems Theory

Family systems theory places primary focus on exchanges of behavior that take place in a given moment of interaction between members of the family. The theory maintains that patterns of interaction between family members call forth, maintain, and perpetuate both problem and nonproblematic behavior. Nonpathology oriented, family system theory seeks to identify and bring forth reconstitutive behavioral exchanges between family members. Emphasis is placed on identifying and interrupting repeating sequences of behavioral exchanges of which the problem behavior is a part. When these problem perpetuating patterns are successfully interrupted, the problem behavior dissipates and treatment is complete.  family; interaction; pattern; sequence; system; transaction; triangle
Gated Siamese Convolutional Neural Network Architecture for Human Re identification
Venue: ECCV

Matching pedestrians across multiple camera views, known as human re identification, is a challenging research problem that has numerous applications in visual surveillance. With the resurgence of Convolutional Neural Networks (CNNs) several end to end deep Siamese CNN architectures have been proposed for human re identification with the objective of projecting the images of similar pairs (i.e. same identity) to be closer to each other and those of dissimilar pairs to be distant from each other. However, current networks extract fixed representations for each image regardless of other images which are paired with it and the comparison with other images is done only at the final level. In this setting, the network is at risk of failing to extract finer local patterns that may be essential to distinguish positive pairs from hard negative pairs. In this paper, we propose a gating function to selectively emphasize such fine common local patterns by comparing the mid level features across pairs of images. This produces flexible representations for the same image according to the images they are paired with. We conduct experiments on the CUHK03, Market 1501 and VIPeR datasets and demonstrate improved performance compared to a baseline Siamese CNN architecture.
A Siamese Long Short Term Memory Architecture for Human Re identification
Venue: ECCV

Matching pedestrians across multiple camera views known as human re identification (re identification) is a challenging problem in visual surveillance. In the existing works concentrating on feature extraction, representations are formed locally and independent of other regions. We present a novel siamese Long Short Term Memory (LSTM) architecture that can process image regions sequentially and enhance the discriminative capability of local feature representation by leveraging contextual information. The feedback connections and internal gating mechanism of the LSTM cells enable our model to memorize the spatial dependencies and selectively propagate relevant contextual information through the network. We demonstrate improved performance compared to the baseline algorithm with no LSTM units and promising results compared to state of the art methods on Market 1501, CUHK03 and VIPeR datasets. Visualization of the internal mechanism of LSTM cells shows meaningful patterns can be learned by our method.
Perceptual Visual Security Index Based on Edge and Texture Similarities
Venue: IEEE Transactions on Information Forensics and Security

With the development in recent decades of various efficient image encryption algorithms, such as selective encryption, a great demand has arisen for methods of evaluating the visual security of encrypted images. Existing solutions usually adopt well known metrics of visual quality assessment to measure the quality of encrypted images, but they often exhibit undesired behavior on perceptually encrypted images of low quality. In this paper, we propose a novel visual security index (VSI) based on the human visual system. The proposed VSI evaluates two aspects of the content similarity between plain and encrypted images: the edge similarity extracted via multi threshold edge detection and the texture similarity measured by means of the co occurrence matrix. These two components are further integrated to obtain the proposed VSI through adaptive similarity weighting. Extensive experiments were performed on two publicly available image databases. Our experimental results demonstrate that compared with many existing state of the art visual security metrics, the proposed VSI exhibits a better performance and stability on low quality images.
Generating Images with Perceptual Similarity Metrics based on Deep Networks
Venue: NIPS

Image generating machine learning models are typically trained with loss functions based on distance in the image space. This often leads to over smoothed results. We propose a class of loss functions, which we call deep perceptual similarity metrics (DeePSiM) that mitigate this problem. Instead of computing distances in the image space, we compute distances between image features extracted by deep neural networks. This metric better reflects perceptually similarity of images and thus leads to better results. We show three applications: autoencoder training, a modification of a variational autoencoder, and inversion of deep convolutional networks. In all cases, the generated images look sharp and resemble natural images.
Evolutionary Improved Swarm Based Hybrid K Means Algorithm for Cluster Analysis

Improvement in the quality of cluster centers and minimization of intra cluster distance are two most challenging areas of K means clustering algorithm. Due to predetermined number of clusters, it is difficult to predict the exact value of k. Furthermore, in case of non globular clusters, K means fails to get optimal cluster center in a data set. In this paper, a hybrid improved particle swarm optimization based evolutionary K means clustering method has been proposed to obtain the optimal cluster center. The hybridization of improved PSO and genetic algorithm (GA) along with K means algorithm improves the convergence speed as well as helps to find the global optimal solution. In the first stage, IPSO has been used to get a global solution in order to get optimal cluster centers. Then, the crossover steps of GA are used to improve the quality of particles and mutation is used for diversification of solution space in order to avoid premature convergence. The performance analysis of the proposed method is compared with other existing clustering techniques like K means, GA K means, and PSO K means.
Risk Assessment and Early Warning System for High Speed Railway during the Construction and Operation of Underpass Bridges

AbstractPotential risk assessment and early warning system are essentially important to ensure the safety of high speed railway (HSR) bridges. This paper presents an in depth methodology of this risk assessment and early warning. Firstly, the risk sources, occurrence probabilities, and hazard consequences were investigated by consulting specialists. For kernel risk sources, such as excavation and dewater activities, finite element models were established to evaluate the deformation of foundations and approach embankments in various conditions. Then, with combined quantitative and qualitative analysis, the as low as reasonably possible (ALARP) criterion was utilized to obtain the results of risk assessment. On the early warning system, autoregressive integrated moving average (ARIMA) method was used to predict the continuous deformation and to analyze the kernel indices that may affect the railway operations. At last, the forewarning interval of each index that can be used in the construction monitoring wa.
Complications of Cushing's syndrome: state of the art.
Venue: The lancet. Diabetes endocrinology

Cushing's syndrome is a serious endocrine disease caused by chronic, autonomous, and excessive secretion of cortisol. The syndrome is associated with increased mortality and impaired quality of life because of the occurrence of comorbidities. These clinical complications include metabolic syndrome, consisting of systemic arterial hypertension, visceral obesity, impairment of glucose metabolism, and dyslipidaemia; musculoskeletal disorders, such as myopathy, osteoporosis, and skeletal fractures; neuropsychiatric disorders, such as impairment of cognitive function, depression, or mania; impairment of reproductive and sexual function; and dermatological manifestations, mainly represented by acne, hirsutism, and alopecia. Hypertension in patients with Cushing's syndrome has a multifactorial pathogenesis and contributes to the increased risk for myocardial infarction, cardiac failure, or stroke, which are the most common causes of death; risks of these outcomes are exacerbated by a prothrombotic diathesis and hypokalaemia. Neuropsychiatric disorders can be responsible for suicide. Immune disorders are common; immunosuppression during active disease causes susceptibility to infections, possibly complicated by sepsis, an important cause of death, whereas immune rebound after disease remission can exacerbate underlying autoimmune diseases. Prompt treatment of cortisol excess and specific treatments of comorbidities are crucial to prevent serious clinical complications and reduce the mortality associated with Cushing's syndrome.
Why local governments rarely use PPPs in their road development projects: Understanding the barriers

The purpose of this paper is to identify barriers that prevent local governments from applying PPPs in their road development projects.  Based on insights from a literature review, interviews were held with relevant staff to identify barriers. These were verified and their relative significance was determined through the use of a questionnaire, before being reflected upon and compared with literature findings.  The research identified 37 barriers to local governments using PPPs in road development projects and showed that four barriers consistently stand out. First, the application of PPPs requires local governments to adapt their current working methods, which amounts to a large impediment to local governments applying PPPs. Second, local government employees believe that applying PPPs might effectively exclude local contractors from involvement in projects. Finally, local governments experience the whole PPP approach (the third barrier) and the PPP contract (the fourth) as overly complicated.  To increase the use of PPPs for infrastructure provision at the local level, one has to focus on removing dominant local barriers as identified in this research.  Although local level PPPs have seen increasing interest, this is one of the first studies paying attention to the barriers to using PPPs for local road development projects
Desiree's Baby

The little one awoke in his arms and began to cry for "Dada." That was as much as she could do or say. Some people thought she might have strayed there of her own accord, for she was of the toddling age. The prevailing belief was that she had been purposely left by a party of Texans, whose canvas covered wagon, late in the day, had crossed the ferry that Coton Mais kept, just below the plantation. In time Madame Valmonde abandoned every speculation but the one that Desiree had been sent to her by a beneficent Providence to be the child of her affection, seeing that she was without child of the flesh. For the girl grew to be beautiful and gentle, affectionate and sincere, the idol of Valmonde.