Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial Neural Network Model for Prediction of Liquefaction Potential in Soil Deposits

With the increase in population, the evaluation of liquefaction is becoming more important for land use planning and development. In soil deposits under undrained condition, earthquakes induce cyclic shear stresses, may lead to soil liquefaction. Artificial neural network (ANN) is one of the, artificial intelligence (AI) approaches that can be classified as machine learning. Simplified methods have been practiced by researchers to assess nonlinear liquefaction potential of soil. In order to address the collective knowledge built up in conventional liquefaction engineering, an alternative general regression neural network model is proposed in this paper. To meet this objective, a total of 30 boreholes are introduced into the model. The data includes the results of field test from (Babol, Mazandaran, Iran). The results produced by the proposed Artificial Neural Network model compared well with the determined liquefaction decision obtained by simplified methods. It provides a viable liquefaction potential assessment tool that assist geotechnical engineers in making an accurate and realistic predictions. Furthermore, this study integrates knowledge learned from field test and seismic parameters to the ongoing development of liquefaction analysis. The results show that there is liquefaction potential in western part of Babol, and in southern part of Babol no liquefaction potential were seen. In middle part and eastern part low liquefaction potential were predicted by ANNs. This study shows that neural networks are a powerful computational tool which can analyze the complex relationship between soil liquefaction potential and effective parameters in liquefaction.
Increased frequency of X-bearing sperm in males from an infertility clinic: analysis by two-color fluorescence in situ hybridization

Semen samples from 34 men visiting the Lübeck infertility clinic were investigated using a two-color FISH method to determine the ratio of X- and Y-bearing sperm. The overall ratio was significantly shifted to a preponderance of X-containing sperm. A statistical comparison with seven reports from the literature which included 53 normal probands demonstrated in our patients a significant tendency of a preponderance of X-bearing sperm and significantly less Y-bearing sperm. Furthermore, the Lübeck sperm samples are remarkably more heterogeneous in respect to their variability of X- and Y-bearing spermatozoa than in the other mentioned studies with normal probands. These phenomena have to be evaluated in further studies on groups of infertile males showing similar infertility histories.
The mouse 14-3-3 epsilon isoform, a kinase regulator whose expression pattern is modulated in mesenchyme and neuronal differentiation.

Kidney development is a complex, little understood process based on inductive interactions and intricate epithelial and mesenchymal morphogenesis. Here, we report the use of subtractive hybridization to clone cDNAs expressed in early nephrogenesis. cDNA made from E14.5 mouse kidney was hybridized with adult mouse liver mRNA employing a technique based on labeling the driver mRNA with photoactivatable biotin and using streptavidin to remove RNA:cDNA complexes. An aliquot of the unhybridized cDNA identified several clones including three isolates that proved to be the epsilon isoform of the 14-3-3 gene family that is, among other functions, implicated in protein kinase C regulation. Northern blot analysis showed a 2.0-kb transcript widely present in mouse embryos from E7.5 onward, but, as expected from the subtractive strategy, absent in adult liver. In situ hybridization was carried out on mouse embryos aged E8.5 to E15.5. These showed that, in the E8.5 embryo, the 14-3-3 epsilon gene was expressed throughout the embryo, but that, within a day, expression was more marked in mesenchyme than elsewhere (e.g., epithelial tissue, where it was generally low), although levels in neural tissue rose again by about E12.5. This difference was maintained until E15.5 when expression levels started to drop in most tissues, with those of the nervous system, tooth, and kidney being exceptions. Perhaps the most intriguing feature of the expression pattern, however, was that, while the gene was strongly expressed in early mesenchyme, the level of expression decreased as the mesenchyme differentiated. This change was particularly noted in mesenchymal condensations that would become cartilage, bone, and myotome-derived muscle, in the presumptive muscle layer of the gut, and in the kidney. In this last case, the gene was strongly expressed in stem cells and mesenchyme, but expression levels dropped markedly as early nephrogenic condensates epithelialized. The results as a whole thus argue for the 14-3-3 epsilon isoform playing roles in neural development and in early mesenchyme, with this latter function being lost or replaced as the tissue differentiates.
IRIS Recognition based on Non Linear Dimensionality Reduction of IRIS Code with KPCA and SVM based Classification

Iris recognition technique has come a long way since a comprehensive method was first proposed by Daugman two decades back. But with evolution of technology and processing environment, several techniques are being proposed and tested. The study clearly shows that IRIS segmentation based on the Daugman’s technique and IRIS recognition based on the Gabor features extracted from the segmented IRIS images is the most efficient technique for recognition. IRIS recognition research can be understood as two point agenda: extracting better features from segmented IRIS images and use a better classifier than the Hamming distance based classification. With the increase of number of features recognition error decreases and accuracy increases, but other complexities like space complexity for storing the features and time complexity for optimizing the features by kernel based classifier is difficult. Hence in this work we emphasize on extracting the most significant feature set from the segmented IRIS and project the features in a high dimensional space using KPCA dimensionality reduction technique. The features are classified using Multiclass support vector machine. Results show that the recognition rate and FAR of the proposed technique are very high when compared to Multi Class SVM.
High-frequency photoacoustic imaging of erythrocyte aggregation and oxygen saturation: probing hemodynamic relations under pulsatile blood flow

In this paper, we investigate the feasibility of high-frequency photoacoustic (PA) imaging to study the shear rate dependent relationship between red blood cell (RBC) aggregation and oxygen saturation (SO2) in a simulated blood flow system. The PA signal amplitude increased during the formation of aggregates and cyclically varied at intervals corresponding to the beat rate (30, 60, 120, 180 and 240 bpm) for all optical wavelengths of illumination (750 and 850 nm). The SO2 also cyclically varied in phase with the PA signal amplitude for all beat rates. In addition, the mean blood flow velocity cyclically varied at the same interval of beat rate, and the shear rate (i.e. the radial gradient of flow velocity) also cyclically varied. On the other hand, the phase of the cyclic variation in the shear rate was reversed compared to that in the PA signal amplitude. This study indicates that RBC aggregation induced by periodic changes in the shear rate can be correlated with the SO2 under pulsatile blood flow. Furthermore, PA imaging of flowing blood may be capable of providing a new biomarker for the clinical application in terms of monitoring blood viscosity, oxygen delivery and their correlation.
Object-Oriented Pattern-Based Parallel Programming with Automatically Generated Frameworks

The CO2P3S parallel programming system uses design patterns and object-oriented programming to reduce the complexities of parallel programming. The system generates correct frameworks from pattern template specifications and provides a layered programming model to address both the problems of correctness and openness. This paper describes the highest level of abstraction in CO2P3S, using two example programs to demonstrate the programming model and the supported patterns. Further, we introduce phased parallel design patterns, a new class of patterns that allow temporal phase relationships in a parallel program to be specified, and provide two patterns in this class. Our results show that the frameworks can be used to quickly implement parallel programs, reusing sequential code where possible. The resulting parallel programs provide substantial performance gains over their sequential counterparts.
Influence of the centrosome on the structure of nucleated microtubules

The capacity of the centrosome to influence the lattice structure of nucleated microtubules was studied in vitro. Brain microtubules self- assembled to give predominantly (98%) 14-protofilament microtubules. However, under exactly the same conditions of assembly they grew off of purified centrosomes from neuroblastoma cells to give mostly (82%) 13- protofilament microtubules. Thus, the nucleation sites on the centrosome constrained the microtubule lattice to yield the number of protofilaments usually found in vivo.
Deep Model for Dropout Prediction in MOOCs

Dropout prediction research in MOOCs aims to predict whether students will drop out from the courses instead of completing them. Due to the high dropout rates in current MOOCs, this problem is of great importance. Current methods rely on features extracted by feature engineering, in which all features are extracted manually. This process is costly, time consuming, and not extensible to new datasets from different platforms or different courses with different characters. In this paper, we propose a model that can automatically extract features from the raw MOOC data. Our model is a deep neural network, which is a combination of Convolutional Neural Networks and Recurrent Neural Networks. Through extensive experiments on a public dataset, we show that the proposed model can achieve results comparable to feature engineering based methods.
An Approach towards the Fulfilment of Security Requirements for Decision Support Systems in the Field of Evidence-Based Healthcare

Evidence-based medicine is a new healthcare scientific paradigm aiming at the prevention, diagnosis and treatment of diseases using medical evidence. Because of the complex nature of the clinician’s task to gather all the necessary knowledge about given diseases, the practice of evidence-based medicine could not be envisioned without IT support. Integration of external evidence-based data sources into the existing clinical information system and finding of appropriate therapy alternatives for a given patient and a given disease is a major research challenge. With the rapid changes taking place in the field of health care, decision support systems play an increasingly important role. We propose a data warehouse solution, as an easy-to-use decision support platform, to enable the integration of a wide range of data sources. Caused by the innovative character of the field, no explicit common security regulations and standards yet exist. Defining these measures is a process, where both the patient’s individual rights (patient’s privacy and data protection) and the collective, societal demands (scientific progress and development of new technologies) need to be considered. This paper discusses the security measures to be enforced in order to protect the extraordinary sensitive nature of health data while using clinical data sources for knowledge discovery and the development of evidence based guidelines. In this paper, we first give a short introduction into decision support systems and data warehouses. Subsequently we briefly present the relevant characteristics of evidence-based medicine. In the * This research has been partly funded by the Austrian Federal Ministry for Education, Science and Culture, and the European Social Fund (ESF) under grant 31.963/46-VII/9/2002. 2 sequel, the paper sketches how data warehouse can be used to support the practice of evidence-based medicine by the physicians at the point of care as well as how it can support clinical management in their decision making process. Consequently, we propose a security concept for protecting privacy of high-sensitive patient data. This security concept comprises depersonalisation, pseudonymisation and role-based access. This paper shows the need of a high-secure decision support system in order to facilitate the practical use of evidence-based medicine with respect to the privacy regulations. We consider the proposed data warehouse approach as a suitable solution for this problem.
Steffensen iterations for power updates in CDMA wireless networks ∗

In this paper we present a new algorithm for mobile power updates in wireless CDMA systems. The algorithm in fact represents accelerated Jacobi iterations for mobile power updates of the algorithm popularly known as the DPC (distributed power control) algorithm. The new algorithm, with more rapid convergence, is obtained using Steffensen fixed-point iterations initialized by two Jacobi iterations. With minor extensions the Steffensen iteration algorithms presented can be used to accelerate the constrained version of the DPC algorithm. We present simulation results using realistic data to illustrate the improved convergence of the new algorithm as compared with the DPC and the second-order power control (SOPC).
Seismic models for near-surface explosion yield estimation in alluvium and sedimentary rock

Author(s): Templeton, DC; Rodgers, AJ; Ford, SR; Harben, PE; Ramirez, AL; Foxall, W; Reinke, RE | Abstract: © 2018, Seismological Society of America. All rights reserved. Seismic ground-motion data provide valuable constraints on explosion characteristics, such as yield and height-of-burst/depth-of-burial (HOB/DOB). This study investigated a range of seismic amplitude features and their efficacy in minimizing errors associated with yield estimation. Using a set of explosion recordings from experiments conducted in alluvium and sedimentary rock geologies, we investigated the effectiveness of three different seismic feature types over a range of different frequencies. Using both velocity and displacement data, we investigated the zero-to-peak (ZTP) amplitude of the first arriving P wave, the peak-to-peak (PTP) amplitude of the first arriving P wave, and the Prms amplitude over various time windows starting with the P wave. These three basic features were measured on both vertical component only data and the vertical–radial vector sum. In total, there were 56 different combinations investigated. Our seismic models combine the effects of scaled range and scaled HOB/DOB on the observed seismic features. The results show that the vertical–radial vector sum of the ZTP amplitudes measured on displacement seismograms most consistently produce models with the smallest difference between predicted amplitude values and observed amplitude values when accounting for both alluvium and sedimentary rock lithology. The improvement in fit to the data when incorporating the difference in source lithology is significant. If an alluvium lithology is assumed for a sedimentary rock lithology, the difference in yield could be up to ∼3.0 times the appropriate yield in the far field.
Transforming growth factor β1 is associated with angiogenesis, metastasis, and poor clinical outcome in prostate cancer

Prostate tumors express high levels of transforming growth factor‐β1 (TGF‐β1) and seem to acquire resistance to its antiproliferative effects with tumor progression. Moreover, TGF‐β1 could be involved in tumor‐promoting processes such as angiogenesis, cell migration, and immunosuppression.
“ Out of the Box ” Information Extraction : a Case Study using Bio-Medical Texts

A major obstacle to Information Extraction (IE) from text is the knowledge engineering required for each new domain: specifying the relations of interest, manually encoding extraction rules, or selecting and hand-tagging the training examples necessary to automatically learn such rules. The history of IE is one of increasing automation, and recent systems have reduced manual effort to “50 person hours” [8]. This paper presents the first IE system tested on new domains “out of the box”—without any manual effort. The paper reports on a case study assessing the performance of the ReVerb Open IE system on a sample of MedLine abstracts and on a biology textbook. To date, ReVerb has only been tested on massive, highly redundant Web corpora. Since scientific language is more complex than typical Web text, and since our bio-medical texts exhibit essentially no redundancy, we expected a priori ReVerb to yield modest precision. In fact, ReVerb achieves precision 0.9 (at recall of 0.28) on MedLine, and precision 0.9 (at recall of 0.14) on the biology textbook; biology recall climbs to 0.57 at precision 0.7. Error analysis revealed two main sources of error – conditionally true statements and n-ary relations. Improving ReVerb to identify these cases doubled recall (at precision 0.9) on the biology textbook, and yielded small gains on our other corpora as well.
Software Piracy Prevention: Splitting on Client

After identifying the fundamental weakness of existing privacy prevention, this paper proposes a software-splitting technique in which we put the split contents on the client instead of the remote trust server. Unlike traditional static client identification techniques, this new technique would encrypt the extracted contents from the software by a key relating to the hardware characteristics, and then decrypt them dynamically during the main program running. This method not only makes it harder to create an additional available copy based on diversity, but also prevents illegal uses on the copy.
Gene Expression Profiling of Embryonic Stem Cells Leads to Greater Understanding of Pluripotency and Early Developmental Events1

Abstract Embryonic stem cells are characterized by their ability to propagate indefinitely in culture, maintaining a normal karyotype and their undifferentiated state. They have the potential of differentiating into any specialized cell type in the body. An understanding of the transcriptional profile related to pluripotency and early development is necessary to better tap their developmental potential and also maintain their undifferentiated phenotype. Currently, several techniques are in use to ascertain the gene expression profile of embryonic stem cells. This review summarizes the information generated using microarray and other approaches on the gene expression analyses of stem cells in both mouse and human cell lines. We also discuss specific approaches useful in future studies aimed at further deciphering the pluripotent nature of human embryonic stem cells.
Flow Injection Potentiometric Assay of Hexoprenaline in Its Pure State, Pharmaceutical Preparations, and Biological Samples

Different hexoprenaline (Hx2SO4) conventional and coated wire electrodes were constructed and evaluated. Membranes were based on hexoprenalinium phosphotungstate (Hx-PTA) and hexporenalinium phosphomolybdate (Hx-PMA). The electrodes were fully characterized in terms of their composition, response time, life span, pH, and temperature and then were applied to the potentiometric determination of the hexoprenalinium ion in its pure state, pharmaceutical preparations, and biological samples, urine and plasma, under batch and flow injection conditions. The selectivity of the electrodes towards many inorganic cations, sugars, amino acids, and some other brochodilatures of close chemical composition was also tested.
An amino-terminal extension is required for the secretion of chick agrin and its binding to extracellular matrix

Agrin is an extracellular matrix (ECM) protein with a calculated relative molecular mass of more than 200 kD that induces the aggregation of acetylcholine receptors (AChRs) at the neuromuscular junction. This activity has been mapped to its COOH terminus. In an attempt to identify the functions of the NH2-terminal end, we have now characterized full-length chick agrin. We show that chick agrin encoded by a previously described cDNA is not secreted from transfected cells. Secretion is achieved with a construct that includes an additional 350 bp derived from the 5' end of chick agrin mRNA. Recombinant agrin is a heparan sulfate proteoglycan (HSPG) of more than 400 kD with glycosaminoglycan side chains attached only to the NH2-terminal half. Endogenous agrin in tissue homogenates also has an apparent molecular mass of > 400 kD. While the amino acid sequence encoded by the 350-bp extension has no homology to published rat agrin, it includes a stretch of 15 amino acids that is 80% identical to a previously identified bovine HSPG. The extension is required for binding of agrin to ECM. AChR aggregates induced by recombinant agrin that includes the extension are considerably smaller than those induced by agrin fragments, suggesting that binding of agrin to ECM modulates the size of receptor clusters. In addition, we found a site encoding seven amino acids at the NH2-terminal end of agrin that is alternatively spliced. While motor neurons express the splice variant with the seven amino acid long insert, muscle cells mainly synthesize isoforms that lack this insert. In conclusion, the cDNAs described here code for chick agrin that has all the characteristics previously allocated to endogenous agrin.
1 High-throughput functional annotation of influenza A virus 1 genome at single-nucleotide resolution 2

17 A novel genome-wide genetics platform is presented in this study, which permits functional 18 interrogation of all point mutations across a viral genome in parallel. Here we generated the first 19 fitness profile of individual point mutations across the influenza virus genome. Critical residues 20 on the viral genome were systematically identified, which provided a collection of subdomain 21 data informative for structure-function studies and for effective rational drug and vaccine design. 22 Our data was consistent with known, well-characterized structural features. In addition, we 23 have achieved a validation rate of 68% for severely attenuated mutations and 94% for neutral 24 mutations. The approach described in this study is applicable to other viral or microbial genomes 25 where a means of genetic manipulation is available. 26 . CC-BY 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi. org/10.1101/005702 doi: bioRxiv preprint first posted online May. 31, 2014;