nils-herrmann/clean_scirepeval huggingface dataset:
Deep learning for tissue microarray image based outcome prediction in patients with colorectal cancer
Venue: SPIE Medical Imaging

Recent advances in computer vision enable increasingly accurate automated pattern classification. In the current study we evaluate whether a convolutional neural network (CNN) can be trained to predict disease outcome in patients with colorectal cancer based on images of tumor tissue microarray samples. We compare the prognostic accuracy of CNN features extracted from the whole, unsegmented tissue microarray spot image, with that of CNN features extracted from the epithelial and non epithelial compartments, respectively. The prognostic accuracy of visually assessed histologic grade is used as a reference. The image data set consists of digitized hematoxylin eosin (H and E) stained tissue microarray samples obtained from 180 patients with colorectal cancer. The patient samples represent a variety of histological grades, have data available on a series of clinicopathological variables including long term outcome and ground truth annotations performed by experts. The CNN features extracted from images of the epithelial tissue compartment significantly predicted outcome (hazard ratio (HR) 2.08; CI95% 1.04 4.16; area under the curve (AUC) 0.66) in a test set of 60 patients, as compared to the CNN features extracted from unsegmented images (HR 1.67; CI95% 0.84 3.31, AUC 0.57) and visually assessed histologic grade (HR 1.96; CI95% 0.99 3.88, AUC 0.61) As a conclusion, a deep learning classifier can be trained to predict outcome of colorectal cancer based on images of H and E stained tissue microarray samples and the CNN features extracted from the epithelial compartment only resulted in a prognostic discrimination comparable to that of visually determined histologic grade.
How participatory planning processes for transit oriented development contribute to social sustainability

Transit oriented development (TOD) is a relatively recent neighbourhood development concept associated with the three dimensions of urban sustainability (environmental, economic and social) Traditionally, TOD has been associated with environmental and economic benefits. Recent research has shown evidence of positive social outcomes related to the spatial characteristics of TOD areas. But the social sustainability that can be drawn from TOD interventions may multiply when designed through participatory planning processes. Here, I combine TOD literature with that of collaborative urban planning to highlight the potential of participatory TOD for urban social sustainability.
Pharmacological and psychotherapeutic interventions for management of obsessive compulsive disorder in adults: a systematic review and network meta analysis
Venue: The lancet. Psychiatry

Several interventions are available for management of obsessive compulsive disorder in adults, but few studies have compared their relative efficacy in a single analysis. We aimed to simultaneously compare all available treatments using both direct and indirect data.  In this systematic review and network meta analysis, we searched the two controlled trials registers maintained by the Cochrane Collaboration Common Mental Disorders group for trials published up to Feb 16, 2016. We selected randomised controlled trials in which an active psychotherapeutic or pharmacological intervention had been used in adults with obsessive compulsive disorder. We allowed all comorbidities except for schizophrenia or bipolar disorder. We excluded studies that focused exclusively on treatment resistant patient populations defined within the same study. We extracted data from published reports. The primary outcome was symptom severity as measured by the Yale Brown Obsessive Compulsive Scale. We report mean differences with 95% credible intervals compared with placebo.   We identified 1480 articles in our search and included 53 articles (54 trials; 6652 participants) in the network meta analysis. Behavioural therapy (mean difference 14*48 [95% credible interval 18*61 to 10*23] 11 trials and 287 patients) cognitive therapy 13*36 18*40 to 8*21] six trials and 172 patients) behavioural therapy and clomipramine 12*97 19*18 to 6*74] one trial and 31 patients) cognitive behavioural therapy and fluvoxamine 7*50 13*89 to 1*17] one trial and six patients) cognitive behavioural therapy 5*37 9*10 to 1*63] nine trials and 231 patients) clomipramine 4*72 6*85 to 2*60] 13 trials and 831 patients) and all SSRIs (class effect 3*49 [95% credible interval 5*12 to 1*81] 37 trials and 3158 patients) had greater effects than did drug placebo. Clomipramine was not better than were SSRIs 1*23 3*41 to 0*94] Psychotherapeutic interventions had a greater effect than did medications, but a serious limitation was that most psychotherapeutic trials included patients who were taking stable doses of antidepressants (12 [80% of the 15 psychotherapy trials explicitly allowed antidepressants)  A range of interventions is effective in the management of obsessive compulsive disorder, but considerable uncertainty and limitations exist regarding their relative efficacy. Taking all the evidence into account, the combination of psychotherapeutic and psychopharmacological interventions is likely to be more effective than are psychotherapeutic interventions alone, at least in severe obsessive compulsive disorder.
Cognitive Dysfunction in Obsessive Compulsive Disorder
Venue: Current Psychiatry Reports

Obsessive compulsive disorder (OCD) is a mental disorder featuring obsessions (intrusive thoughts) and compulsions (repetitive behaviors performed in the context of rigid rituals) There is strong evidence for a neurobiological basis of this disorder, involving limbic cortical regions and related basal ganglion areas. However, more research is needed to lift the veil on the precise nature of that involvement and the way it drives the clinical expression of OCD. Altered cognitive functions may underlie the symptoms and thus draw a link between the clinical expression of the disorder and its neurobiological etiology. Our extensive review demonstrates that OCD patients do present a broad range of neuropsychological dysfunctions across all cognitive domains (memory, attention, flexibility, inhibition, verbal fluency, planning, decision making) but some methodological issues temper this observation. Thus, future research should have a more integrative approach to cognitive functioning, gathering contributions of both experimental psychology and more fundamental neurosciences.
Thermodynamic study of b cyclodextrin dye inclusion complexes using gradient flow injection technique and molecular modeling.
Venue: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

Gradient flow injection technique diode array spectrophotometry was applied for b cyclodextrin (b CD) dye inclusion complex studies. A single injection of a small amount of mixed b CD dye solution (100ml) into the carrier solution of the dye and recording the spectra gave the titration data. The mole ratio data were calculated by calibrating the dispersion pattern using a calibrator dye (rose bengal) Model based multivariate methods were used to analyze the spectral mole ratio data and, as a result, estimate stability constants and concentration spectral profiles. Reliability was tested by applying this method to study the b CD host guest complexes with several dyes as guest molecules. Singular value decomposition (SVD) was used to select the chemical model and reduce noise. Molecular modeling provided the ability to predict the guest conformation orientation (posing) within the cavity of b CD and the nature of the involved interactions. Among those dyes showing observable spectral variation, the stoichiometric ratio of b CD: dye (and log Kf) of methyl orange, fluorescein, phenol red, 4 (2 pyridylazo) resorcinol (PAR) and crystal violet were calculated to be 1:1 (4.26+ 0.01) 1:1 (1.53+ 0.08) 1:1 (3.11+ 0.04) 1:1 (1.06+ 0.12) and 2:1 (5.27+ 0.03) respectively. Compared with the classical method of titration, this method is simple and fast and has the advantage of needing reduced human interference. Molecular modeling facilitates a better understanding of the type of interactions and conformation of guest molecules in the b CD cavity. The details of the proposed method are discussed in this paper.
An improved sobel edge detection method based on generalized type 2 fuzzy logic
Venue: Soft Comput.

Edge detectors have traditionally been an essential part of many computer vision systems. There are different methods that have been proposed for improving edge detection in real images. This paper proposes an edge detection method based on the Sobel technique and generalized type 2 fuzzy logic systems. To limit the complexity of handling generalized type 2 fuzzy logic, the theory of \alpha $a planes is used. Simulation results are obtained with the Sobel operator (without fuzzy logic) then with a type 1 fuzzy logic system (T1FLS) an interval type 2 fuzzy logic system (IT2FLS) and with a generalized type 2 fuzzy logic system (GT2FLS) The proposed generalized type 2 fuzzy edge detection method is tested with synthetic images with promising results. To illustrate the advantages of using generalized type 2 fuzzy logic in combination with the Sobel operator, the figure of merit of Pratt measure is applied to measure the accuracy of the edge detection process.
Improved Otsu segmentation based on sobel operator
Venue: 2016 3rd International Conference on Systems and Informatics (ICSAI)

The classical maximum variance algorithm which could be called Otsu is stable, however, the threshold calculation is rather low which leads to an undesirable performance in terms of segmenting the target from the background during the strip detection process. The poor segmentation process will have negative impact for the subsequent steps, such as the target extraction and the target recognition. In order to overcome this disadvantage, we proposed an improved thresholding segmentation approach based on the maximum variance algorithm. The proposed approach consists of two major steps. The first is to adapt the Sobel operator to extract the grayscale information at the edge. The second is to apply Otsu on the extracted grayscale information. According to our experimental results, the proposed approach achieved the desirable segmentation performance.
An Improved Sobel Edge Detection Operator

The paper proposes an improved gradient algorithm which is based on the existing sobel edge detection. The algorithm is not only simple, but also can solve the coordination problem between the detection precision and anti noise performance. Experimental results prove that using the modified gradient algorithm to detect image edge is not only clear outline, good real time, but also has better anti noise performance.  The edge is the basic characteristics of the image, and which contains a wealth of internal information  The various detection methods in the existing do not have an absolute advantage; they also solve some problems at the same time corresponding with this or that deficiencies. For example, some algorithms have a strong anti noise performance, but the detection accuracy is not high  Contrary to improve detection accuracy and anti noise performance is getting worse. Although some will be both to certain extent coordinated, but the algorithm becomes complicated  it makes the results of the implementation time lengthened. In order to solve these contradictions, this paper puts forward an improved gradient algorithm, and verified the algorithm has the advantage in the anti noise performance through simulation experiments. The Traditional Sobel Edge Detection Operator The traditional sobel operator comprises two groups of 3x3 matrixes  which only have the horizontal and vertical directions of the template, but there are many directions of the edge. In order to detect the edge of the eight directions such as 45 135 etc, it was suggested that the improved sobel edge detection operator [6] which adds six directions of the template based on the traditional sobel algorithm, so it becomes eight directions of the template as shown in Fig. 1. Fig. 2 is schematic diagram of the direction. Although the sobel edge detection operator takes eight directions of the template image convolution, it increases the edge detection of direction [6,7] but due to increase the computational complexity, the speed of edge detection is reduced.  Eight direction template 6th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2016)
Edge Detection Based on Improved Sobel Operator

Sobel algorithm is an important method of image edge detection. Comparing the Sobel operator with several other edge detection operators used frequently and making a further study on the classical Sobel operator, the advantages of Sobel operator are its fast detection speed, meanwhile it has an effect on smoothing and suppressing noise. Also, Sobel operator has a good effect on edge detection. Although Sobel operator has advantages in many aspects, it exists some problems: the Sobel operator is a kind of edge detection in horizontal and vertical direction, so it neglects edge points in other directions. It can not achieve a true detection for the points on image edge. In this paper, the algorithm is based on the Sobel operator, an increase of 45 degrees and 135 degrees 2 direction template, while the main edge of the oblique, re assigned the weight of the operator template. At the same time, in order to achieve an effect of detection, binarization method is used to make an edge thinning for detected image. According to simulation experiments, they show this method is simple and feasible, and the detective result is more concrete and abundant than traditional Sobel edge detection. Some problems are improved, such as traditional Sobel edge is rough and detection is incomplete. Keywords sobel operator; binarization; edge detection; edge thinning
A New Pre Training Method for Training Deep Learning Models with Application to Spoken Language Understanding
Venue: INTERSPEECH

We propose a simple and efficient approach for pre training deep learning models with application to slot filling tasks in spoken language understanding. The proposed approach leverages unlabeled data to train the models and is generic enough to work with any deep learning model. In this study, we consider the CNN2CRF architecture that contains Convolutional Neural Network (CNN) with Conditional Random Fields (CRF) as top layer, since it has shown great potential for learning useful representations for supervised sequence learning tasks. The proposed pre training approach with this architecture learns the feature representations from both labeled and unlabeled data at the CNN layer, covering features that would not be observed in limited labeled data. At the CRF layer, the unlabeled data uses predicted classes of words as latent sequence labels together with labeled sequences. Latent labeled sequences, in principle, has the regularization effect on the labeled sequences, yielding a better generalized model. This allows the network to learn representations that are useful for not only slot tagging using labeled data but also learning dependencies both within and between latent clusters of unseen words. The proposed pre training method with the CRF2CNN architecture achieves significant gains with respect to the strongest semi supervised baseline.
Nonylphenol induces liver toxicity and oxidative stress in rat.
Venue: Biochemical and biophysical research communications

Nonylphenol (NP) is one of the most widely used synthetic xenoestrogens in detergents, plastic products, paints and the most important environmental degradation factor. In this study, the effects NP was investigated on hepatic oxidative stress related gene expression in rats.  Wistar male rats weighing 150 200 g were divided into control and NP receiving groups. NP was given in three doses (5, 25, and 125 mg/kg) All doses were given by gavage and the experiment continued for a consecutive 35 days. AST, ALT and ALP determined by the colorimetric method. The RNA was extracted from the rats liver tissue and RT PCR was used to investigate the changes in gene expression. For this purpose, primers and specific probes of HO1 and Gadd45b genes as well as B actin as control were prepared and the expression of each gene was separately assessed with ABI 7300. Hematoxylin and eosin staining was performed for evaluating of cell death.  The data from our study indicated nonylphenol increased alkaline phosphatase level but not changed aspartate aminotransferase and alanine aminotransferase in serum. That various doses of NP result in a dose dependent increase in the expression of HO 1 gene. The intensified expression of HO 1 was statistically significant just at the doses of 25 and 125 mg/kg compared to control group (p 0.05) In addition, it was shown that different doses of nonylphenol raised the expression of Gadd45b gene and this increase was significantly evident at 5 mg/kg (p 0.05) Histological evaluation also indicated that NP increased hepatocytes cell death.  We conclude that NP increased serum alkaline phosphatase, lead to liver damage and can increase the expression of HO1 and Gadd45b genes and may modify the toxic effects on liver through induction of oxidative stress.
PENGARUH KOMUNIKASI INTERPERSONAL PIMPINAN TERHADAP KINERJA PEGAWAI BASARNAS BENGKULU

Dalam hal komunikasi yang terjadi antar pegawai, kompetensi komunikasi yang baik akan mampu memperoleh dan mengembangkan tugas yang diembannya, sehingga tingkat kinerja suatu organisasi (perkantoran) menjadi semakin baik. Dan sebaliknya, apabila terjadi komunikasi yang buruk akibat tidak terjalinnya hubungan yang baik, sikap yang otoriter atau acuh, perbedaan pendapat atau konflik yang berkepanjangan, dan sebagainya, dapat berdampak pada hasil kerja yang tidak maksimal. Tujuan penelitian ini adalah untuk mengetahui pengaruh komunikasi interpesonal pimpinan terhadap Kinerja Pegawai Basarnas Provinsi Bengkulu Penelitian ini adalah penelitian lapangan dengan pendekatan kuantitatif asosiatif. Dimana penulis ingin mengetahui apakah Komunikasi Interpersonal Pimpinan (X) berpengaruh terhadap Kinerja PEGAWAI(Y) Hasil pengujian parsial uji t) dengan hasil nilai koefisien regresi sebesar 0,111 dan nilai probabilitas sebesar 0,04 yang lebih kecil dari 0,05 menunjukan Komunikasi interpersonal pimpinan mempunyai arah yang positif dan berpengaruh signifikan terhadap kinerja PEGAWAIkarena nilai signifikan lebih <0,05. Nilai dari koefisien korelasi parsial antara komunikasi interpersonal pimpinan terhadap kinerja PEGAWAIadalah sebesar 0.498 yang berarti terdapat pengaruh yang sangat kuat dimana komunikasi interpersonal pimpinan mempengaruhi kinerja PEGAWAIsebesar 49.8% dengan asumsi variabel lain tetap.  Komunikasi Interpersonal, Basarnas Bengkulu
Guidelines for studying developmental prosopagnosia in adults and children.
Venue: Wiley interdisciplinary reviews. Cognitive science

Developmental prosopagnosia (DP) is a neurodevelopmental condition characterized by severe face identity recognition problems that results from a failure to develop the mechanisms necessary for adequate face processing (Duchaine BC, Nakayama K. Developmental prosopagnosia: a window to content specific face processing.  It occurs in children and adults with normal visual acuity, and without intellectual impairments or known brain injuries. Given the importance of face recognition in daily life, and the detrimental effects of impaired face recognition, DP is an important area of study. Yet conventions for classifying individuals as DP for research purposes are poorly defined. In this focus paper, we discuss: (1) criteria for an operational definition of DP; 2) tests of face recognition and conventions for classifying individuals as DP; and 3) important considerations regarding common associations and dissociations, and cognitive heterogeneity in DP. We also highlight issues unique to studying DP in children, a relatively new endeavor that is proving to be an important complement to the work with adults. Ultimately, we hope to identify challenges researchers face when studying DP, and offer guidelines for others to consider when embarking on their own research pursuits on the topic. For further resources related to this article, please visit the WIREs website.
On the causal structure between CO2 and global temperature
Venue: Scientific reports

We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aerosol direct and indirect forcing, and on short time periods, volcanic forcings. In contrast the causality contribution from natural forcings (solar irradiance and volcanic forcing) to the long term trend is not significant. The spatial explicit analysis reveals that the anthropogenic forcing fingerprint is significantly regionally varying in both hemispheres. On paleoclimate time scales, however, the cause effect direction is reversed: temperature changes cause subsequent CO2/CH4 changes.
On the proportionality between global temperature change and cumulative CO2 emissions during periods of net negative CO2 emissions

Recent research has demonstrated that global mean surface air warming is approximately proportional to cumulative CO2 emissions. This proportional relationship has received considerable attention, as it allows one to calculate the cumulative CO2 emissions 'carbon budget' compatible with temperature targets and is a useful measure for model inter comparison. Here we use an Earth system model to explore whether this relationship persists during periods of net negative CO2 emissions. Negative CO2 emissions are required in the majority of emissions scenarios limiting global warming to 2 degC above pre industrial, with emissions becoming net negative in the second half of this century in several scenarios. We find that for model simulations with a symmetric 1% per year increase and decrease in atmospheric CO2, the temperature change (DT) versus cumulative CO2 emissions (CE) relationship is nonlinear during periods of net negative emissions, owing to the lagged response of the deep ocean to previously increasing atmospheric CO2. When corrected for this lagged response, or if the CO2 decline is applied after the system has equilibrated with the previous CO2 increase, the DT versus CE relationship is close to linear during periods of net negative CO2 emissions. A proportionality constant the transient climate response to cumulative carbon emissions (TCRE) can therefore be calculated for both positive and net negative CO2 emission periods. We find that in simulations with a symmetric 1% per year increase and decrease in atmospheric CO2 the TCRE is larger on the upward than on the downward CO2 trajectory, suggesting that positive CO2 emissions are more effective at warming than negative emissions are at subsequently cooling. We also find that the cooling effectiveness of negative CO2 emissions decreases if applied at higher atmospheric CO2 concentrations.