Miracle-dz/UniFAR-FTUs huggingface dataset:
Color normalization of histology slides using graph regularized sparse NMF

Computer based automatic medical image processing and quantification are becoming popular in digital pathology. However, preparation of histology slides can vary widely due to differences in staining equipment, procedures and reagents, which can reduce the accuracy of algorithms that analyze their color and texture information. To re- duce the unwanted color variations, various supervised and unsupervised color normalization methods have been proposed. Compared with supervised color normalization methods, unsupervised color normalization methods have advantages of time and cost efficient and universal applicability. Most of the unsupervised color normaliza- tion methods for histology are based on stain separation. Based on the fact that stain concentration cannot be negative and different parts of the tissue absorb different stains, nonnegative matrix factorization (NMF), and particular its sparse version (SNMF), are good candidates for stain separation. However, most of the existing unsupervised color normalization method like PCA, ICA, NMF and SNMF fail to consider important information about sparse manifolds that its pixels occupy, which could potentially result in loss of texture information during color normalization. Manifold learning methods like Graph Laplacian have proven to be very effective in interpreting high-dimensional data. In this paper, we propose a novel unsupervised stain separation method called graph regularized sparse nonnegative matrix factorization (GSNMF). By considering the sparse prior of stain concentration together with manifold information from high-dimensional image data, our method shows better performance in stain color deconvolution than existing unsupervised color deconvolution methods, especially in keeping connected texture information. To utilized the texture information, we construct a nearest neighbor graph between pixels within a spatial area of an image based on their distances using heat kernal in lαβ space. The representation of a pixel in the stain density space is constrained to follow the feature distance of the pixel to pixels in the neighborhood graph. Utilizing color matrix transfer method with the stain concentrations found using our GSNMF method, the color normalization performance was also better than existing methods.
Predictors of Survival in 211 Patients with Stage IV Pulmonary and Gastroenteropancreatic MIBG-Positive Neuroendocrine Tumors Treated with 131I-MIBG

This retrospective analysis identifies predictors of survival in a cohort of patients with meta-iodobenzylguanidine (MIBG)–positive stage IV pulmonary and gastroenteropancreatic neuroendocrine tumor (P/GEP-NET) treated with 131I-MIBG therapy, to inform treatment selection and posttreatment monitoring. Methods: Survival, symptoms, imaging, and biochemical response were extracted via chart review from 211 P/GEP-NET patients treated with 131I-MIBG between 1991 and 2014. For patients with CT follow-up (n = 125), imaging response was assessed by RECIST 1.1 if images were available (n = 76) or by chart review of the radiology report if images could not be reviewed (n = 49). Kaplan–Meier analysis and Cox multivariate regression estimated survival and progression-free survival benefits predicted by initial imaging, biochemical response, and symptomatic response. Results: All patients had stage IV disease at the time of treatment. Median survival was 29 mo from the time of treatment. Symptomatic response was seen in 71% of patients, with the median duration of symptomatic relief being 12 mo. Symptomatic response at the first follow-up predicted a survival benefit of 30 mo (P < 0.001). Biochemical response at the first clinical follow-up was seen in 34% of patients, with stability of laboratory values in 48%; response/stability versus progression extended survival by 40 mo (P < 0.03). Imaging response (20% of patients) or stability (60%) at the initial 3-mo follow-up imaging extended survival by 32 mo (P < 0.001). Additionally, multiple 131I-MIBG treatments were associated with 24 mo of additional survival (P < 0.05). Conclusion: Therapeutic 131I-MIBG for metastatic P/GEP-NETs appears to be an effective means of symptom palliation. Imaging, biochemical, and symptomatic follow-up help prognosticate expected survival after 131I-MIBG therapy. Multiple rounds of 131I-MIBG are associated with prolonged survival.
Mikko Acoustic Model Compression with MAP adaptation

Speaker adaptation is an important step in optimization and personalization of the performance of automatic speech recognition (ASR) for individual users. While many applications target in rapid adaptation by various global transformations, slower adaptation to obtain a higher level of personalization would be useful for many active ASR users, especially for those whose speech is not recognized well. This paper studies the outcome of combinations of maximum a posterior (MAP) adaptation and compression of Gaussian mixture models. An important result that has not received much previous attention is how MAP adaptation can be utilized to radically decrease the size of the models as they get tuned to a particular speaker. This is particularly relevant for small personal devices which should provide accurate recognition in real-time despite a low memory, computation, and electricity consumption. With our method we are able to decrease the model complexity with MAP adaptation while increasing the accuracy.
Generic Test Automation

Test automation, that involves the conversion of manual test cases to executable test scripts, is important to hold out efficient regression testing of GUI-based applications. However, test automation takes significant investment of your time and skilled effort. Moreover, it’s not a one-time investment because the application or its environment evolves and test scripts require continuous patching. Thus, it’s difficult to perform test automation in a cost-efficient manner. This projected system gives solution to simplifying testing efforts, which is the main objective of test automation. We have presented a process of Test Automation using keyword driven approach. The input in the form of natural language Test cases which intern gets converted to keyword and that will be executed under framework to produce reports. The technique is based upon looking for keywords that describes actions on the target and calling functions associated with those. Using this framework, we can improve reusability of test code. The effectiveness and efficiency of testing can be magnified with the help of Generic Test Automation.
Privacy-Preserving Data Aggregation Protocol for Fog Computing-Assisted Vehicle-to-Infrastructure Scenario

Vehicle-to-infrastructure (V2I) communication enables moving vehicles to upload real-time data about road surface situation to the Internet via fixed roadside units (RSU). Thanks to the resource restriction of mobile vehicles, fog computation-enhanced V2I communication scenario has received increasing attention recently. However, how to aggregate the sensed data from vehicles securely and efficiently still remains open to the V2I communication scenario. In this paper, a light-weight and anonymous aggregation protocol is proposed for the fog computing-based V2I communication scenario. With the proposed protocol, the data collected by the vehicles can be efficiently obtained by the RSU in a privacy-preserving manner. Particularly, we first suggest a certificateless aggregate signcryption (CL-A-SC) scheme and prove its security in the random oracle model. The suggested CL-A-SC scheme, which is of independent interest, can achieve the merits of certificateless cryptography and signcryption scheme simultaneously. Then we put forward the anonymous aggregation protocol for V2I communication scenario as one extension of the suggested CL-A-SC scheme. Security analysis demonstrates that the proposed aggregation protocol achieves desirable security properties. The performance comparison shows that the proposed protocol significantly reduces the computation and communication overhead compared with the up-to-date protocols in this field.
New Regularization Method for EXAFS Analysis

As an alternative to the analysis of EXAFS spectra by conventional shell fitting, the Tikhonov regularization method has been proposed. An improved algorithm that utilizes a priori information about the sample has been developed and applied to the analysis of U L3‐edge spectra of soddyite, (UO2)2SiO4⋅2H2O, and of U(VI) sorbed onto kaolinite. The partial radial distribution functions g1(UU), g2(USi), and g3(UO) of soddyite agree with crystallographic values and previous EXAFS results.
Assessing Quality in the Treatment of Obsessive-Compulsive Disorders: The Development of the Obsessive-Compulsive Disorder Cognitive Therapy Scale (OCD-CTS).

This portfolio presents a combination of study, practice and research submitted for The Doctorate of Psychology (PsychD) in Clinical Psychology Conversion Programme. The Professional Dossier includes an initial study plan outlining a plan of work for the duration of study. My Curriculum Vitae is elaborated by reflections on my professional development since first qualifying as a Clinical Psychologist and describes the milestones that have led the way. To demonstrate professional competence, a case study gives an account of applying a standard cognitive-behavioural treatment for obsessive-compulsive disorder in a new way. The Academic Dossier is aimed to enhance my knowledge of a specialist area of clinical psychology. The first critical review of the literature about hoarding extends my current expertise and practice in obsessional problems, and paves the way to further developing the service in which I work. Whilst it was tempting to stay with my particular area of clinical interest, I recognised the value of taking a step back to review the literature in a different area. The choice of blood-injury-injection phobia was not as arbitrary as it may seem a clinician at the Centre for Anxiety Disorders and Trauma. Finally, the Research Dossier brings to fruition the development of a new scale for measuring competence in the cognitive-behavioural treatment of obsessive-compulsive disorder, and describes an investigation of its psychometric properties. A copy of manual which accompanies the rating scale is included in the Appendix.
A Multilingual Wikified Data Set of Educational Material

We present a parallel wikified data set of parallel texts in eleven language pairs from the educational domain. English sentences are lined up to sentences in eleven other languages (BG, CS, DE, EL, HR, IT, NL, PL, PT, RU, ZH) where names and noun phrases (entities) are manually annotated and linked to their respective Wikipedia pages. For every linked entity in English, the corresponding term or phrase in the target language is also marked and linked to its Wikipedia page in that language. The annotation process was performed via crowdsourcing. In this paper we present the task, annotation process, the encountered difficulties with crowdsourcing for complex annotation, and the data set in more detail. We demonstrate the usage of the data set for Wikification evaluation. This data set is valuable as it constitutes a rich resource consisting of annotated data of English text linked to translations in eleven languages including several languages such as Bulgarian and Greek for which not many LT resources are available.
Study on modeling method of leaky coaxial cable network channel in underground coal mine

To study the high speed data communication and fault diagnosis of the leaky coaxial cable (leaky cable) network in underground coal mine, a method based on multipath propagation for establishing the leaky cable network channel model is proposed. The multipath propagation of the leaky cable network and the transfer characteristic of the leaky cable are analyzed. The transfer function between the network terminals is solved based on the multipath propagation, and the channel model of the leaky cable network is established. The results have been verified successfully by comparing the measurement results with simulations based on the model, which is obvious that simulation and measurement differ only in minor details.
The Cognitive and Emotional Effects of Cognitive Bias Modification in Interpretations in Behaviorally Inhibited Youth

Cognitive bias modification (CBM) procedures follow from the view that interpretive biases play an important role in the development and maintenance of anxiety. As such, understanding the link between interpretive biases and anxiety in youth at risk for anxiety (e.g., behaviorally inhibited children) could elucidate the mechanisms involved in the development of pediatric anxiety. However, to date, the majority of CBM-I work only studies adult populations. The present article presents the results of a CBM study examining effects of positive interpretive bias modification on mood, stress vulnerability, and threat-related attention bias in a group of behaviorally inhibited children (n = 45). Despite successful modification of interpretive bias in the at-risk youth, minimal effects on stress vulnerability or threat-related attention bias were found. The current findings highlight the need for continued research on cognitive biases in anxiety.
A novel document distance based on concept vector space

A novel metric to measure the distance between documents is proposed in this paper. By utilizing the recent results in word embeddings which can present semantical information between words by real-value vectors, we model a document as a concept vector space, where the concepts are a series of key words extracted based on the text by dependency parsing and linguistic knowledge. A new document distance is defined on the concept vector space to measure the relatedness or similarity between two documents, which can be used in many natural language processing (NLP) task such as document classification, news clustering, etc. The proposed metric has no hyperparameters to tuning and is easily to compute. Further we give a demonstration on a few real world document classification datasets based on k-nearest neighbor (kNN) algorithm. The experiment results show that the new document distance can lead to an impressive quality improvement on document classification.
SIK2 attenuates proliferation and survival of breast cancer cells with simultaneous perturbation of MAPK and PI3K/Akt pathways

Salt Inducible Kinase2 (SIK2) has been shown to contribute to tumorigenesis in multiple tumor types in a dichotomous manner. However, little is known about its contribution to breast malignancies. Here, we report SIK2 as a potential tumor suppressor in breast cancer whose expression was reduced in tumor tissues and breast cancer cell lines compared to normal counterparts. In vitro loss- and gain-of-function experiments combined with xenograft studies demonstrated that SIK2-mediated attenuation of proliferation and survival of breast cancer cells with parallel inhibition of both Ras/Erk and PI3K/Akt pathways. Our findings elucidated that SIK2 has also an inhibitory role in migration/invasion ability of breast cancer cells through regulation of epithelial mesenchymal transition. Immunostaining of patient tumors revealed that SIK2 protein level is frequently downregulated in invasive mammary carcinomas and negatively correlated with the mitotic activity of the cells in triple negative breast cancers and hormone positive tumors. Strikingly, patient survival analysis indicated that higher levels of SIK2 are significantly associated with better survival, especially in basal breast cancer cases. Overall, our findings suggest SIK2 as a potential tumor suppressor in the control of breast tumorigenesis, at least in part, via inhibiting PI3K/Akt and Ras/ERK signaling cascades simultaneously and a novel prognostic marker, especially in basal subtypes of breast cancer.
Modulation of xenobiotic metabolizing enzyme activities in rat liver by co-administration of morin, endosulfan, and 7,12-dimethylbenz[a]anthracene

Abstract Morin is a flavonoid which is present in many plants. Endosulfan and 7,12-dimethylbenz[a]anthracene (DMBA) are toxic chemicals that humans are exposed to in their daily lives. In this study, the protective role of morin was investigated in endosulfan and DMBA treated rats. Eight groups, each comprising seven 2.5-month-old adult male Wistar rats (weighing 170–255 g), were used. Endosulfan, morin, and DMBA were administered individually or in combinations, at 5 mg/kg body weight (bw) (three times/week), 25 mg/kg bw (three times/week), and 30 mg/kg bw (once/week for three weeks) via oral gavage, respectively. On day 54 of the administration period, the rats were killed. DMBA + endosulfan co-administration significantly increased CYP1A1-, CYP1A2-, CYP2E-, and GST-associated activities in the rats compared to the control. DMBA + endosulfan + morin significantly increased CYP1A1, CYP1A2, CYP3A, and GST associated activities in the rats relative to the control. Histopathological studies were performed to investigate protective effects of morin on liver damage. The results indicated that DMBA + endosulfan treatment induced liver damage, and morin reduced this damage. These findings suggest that CYP1A, CYP3A, and GST enzyme activities participate in the protective mechanism of morin against endosulfan and DMBA induced toxicity.
The Oxidant–Antioxidant Equilibrium and Inflammatory Process Indicators after an Exercise Test on the AlterG Antigravity Treadmill in Young Amateur Female Athletes

The AlterG antigravity treadmill allows running with a considerable weight reduction. Physical exercise practiced on this treadmill is an innovative method supporting the treatment of injuries in sports and rehabilitation of patients. The aim of the study was to investigate the effect of a 30 min run on the AlterG treadmill with 80% body weight reduction comparing the effect to the similar effort on the classic treadmill on the redox equilibrium and the activity of selected lysosomal enzymes and a serine protease inhibitor in the blood of amateur minor female volleyball players. Venous blood samples were taken before the exercise and 30 minutes and 24 hours after its completion. The obtained results were analysed using Tukey's test and Pearson's linear correlations were calculated. 24 h after the running test on classic treadmill, the erythrocytic superoxide dismutase activity was higher than before and 30 min after it, as well as compared to the run on AlterG treadmill (p < 0.001). The erythrocytic-conjugated diene concentration 24 h after the exercise on the classic treadmill was meaningly higher compared to that after the exercise on the AlterG treadmill (p < 0.001). The cathepsin D activity was significantly lower after the exercise in AlterG conditions compared to the baseline value and that measured after the exercise on classic treadmill (p < 0.001). It seems that the exercise on the AlterG treadmill keeps the oxidant–antioxidant equilibrium and stabilizes lysosomal membranes in young, physically active women in contrast to the exercise on the classic treadmill. This trial is registered with CTRI/2018/01/011344.
Optimal Resource Allocation for NOMA-TDMA Scheme with α-Fairness in Industrial Internet of Things

In this paper, a joint non-orthogonal multiple access and time division multiple access (NOMA-TDMA) scheme is proposed in Industrial Internet of Things (IIoT), which allowed multiple sensors to transmit in the same time-frequency resource block using NOMA. The user scheduling, time slot allocation, and power control are jointly optimized in order to maximize the system α -fair utility under transmit power constraint and minimum rate constraint. The optimization problem is nonconvex because of the fractional objective function and the nonconvex constraints. To deal with the original problem, we firstly convert the objective function in the optimization problem into a difference of two convex functions (D.C.) form, and then propose a NOMA-TDMA-DC algorithm to exploit the global optimum. Numerical results show that the NOMA-TDMA scheme significantly outperforms the traditional orthogonal multiple access scheme in terms of both spectral efficiency and user fairness.
A universal microarray detection method for identification of multiple Phytophthora spp. using padlock probes.

The genus Phytophthora consists of many species that cause important diseases in ornamental, agronomic, and forest ecosystems worldwide. Molecular methods have been developed for detection and identification of one or several species of Phytophthora in single or multiplex reactions. In this article, we describe a padlock probe (PLP)-based multiplex method of detection and identification for many Phytophthora spp. simultaneously. A generic TaqMan polymerase chain reaction assay, which detects all known Phytophthora spp. , is conducted first, followed by a species-specific PLP ligation. A 96-well-based microarray platform with colorimetric readout is used to detect and identify the different Phytophthora spp. PLPs are long oligonucleotides containing target complementary sequence regions at both their 5' and 3' ends which can be ligated on the target into a circular molecule. The ligation is point mutation specific; therefore, closely related sequences can be differentiated. This circular molecule can then be detected on a microarray. We developed 23 PLPs to economically important Phytophthora spp. based upon internal transcribed spacer-1 sequence differences between individual Phytophthora spp. Tests on genomic DNA of many Phytophthora isolates and DNA from environmental samples showed the specificity and utility of PLPs for Phytophthora diagnostics.
Balancing the Trade-Offs between Data Availability and Query Delay in MANET ’ s

The mobile devices are free to move haphazardly and organize themselves arbitrarily. In other words, ad hoc network do not rely on any fixed infrastructure. The Communication in MANET takes place by using multi-hop paths. Nodes in the MANET share the wireless medium and the topology of the network changes erratically and dynamically. In MANET, breaking of communication link is very frequent, as nodes are free to move to anywhere. Due to this network partition, mobile nodes in one partition are not able to access data hosted by nodes in other partitions, and hence significantly degrade the performance of data access. So to deal with this problem, we apply data replication techniques. Most of the mobiles have limited amount of storage and bandwidth. So it is impossible for them to hold all the data needed for replica. To overcome this problem we are implementing some of the following techniques: The One-To-One Optimization (OTOO) Scheme, the Reliable Neighbor (RN) Scheme and Reliable Grouping (RG) Scheme.
A buffer dynamic stabilizer for low-latency adaptive video streaming

HTTP-based adaptive streaming is today's predominating video delivery model over Internet. However, state-of-the-art bitrate adaptation algorithms are not suitable for low-latency adaptive video streaming due to a distinct lack of buffer dynamic stabilization at the client. A small buffer size lacks resilience to the buffer fluctuation imposed by the mismatch between the network throughput and the average bitrate of the selected video chunk. This paper introduces a bitrate adaptation algorithm that minimizes buffer deviation from the desired level despite a buffering delay as small as a chunk-duration. We demonstrate the performance of our algorithm with respect to the quality-of-experience (QoE) using two evaluation frameworks and compare it against two well-known streaming algorithms, FESTIVE and DASH VLC plugin. The preliminary results show that our algorithm achieves at least 11% higher QoE in the simulation framework and 4% in the emulation framework.