Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of cell cycle regulators and frequency of TP53 mutations in high risk gastrointestinal stromal tumors prior to adjuvant imatinib treatment

Despite of multitude investigations no reliable prognostic immunohistochemical biomarkers in GIST have been established so far with added value to predict the recurrence risk of high risk GIST besides mitotic count, primary location and size. In this study, we analyzed the prognostic relevance of eight cell cycle and apoptosis modulators and of TP53 mutations for prognosis in GIST with high risk of recurrence prior to adjuvant treatment with imatinib. In total, 400 patients with high risk for GIST recurrence were randomly assigned for adjuvant imatinib either for one or for three years following laparotomy. 320 primary tumor samples with available tumor tissue were immunohistochemically analyzed prior to treatment for the expression of cell cycle regulators and apoptosis modulators cyclin D1, p21, p16, CDK4, E2F1, MDM2, p53 and p-RB1. TP53 mutational analysis was possible in 245 cases. A high expression of CDK4 was observed in 32.8% of all cases and was associated with a favorable recurrence free survival (RFS), whereas high expression of MDM2 (12.2%) or p53 (35.3%) was associated with a shorter RFS. These results were independent from the primary KIT or PDGFRA mutation. In GISTs with higher mitotic counts was a significantly increased expression of cyclin D1, p53 and E2F1. The expression of p16 and E2F1 significantly correlated to a non-gastric localization. Furthermore, we observed a significant higher expression of p21 and E2F1 in KIT mutant GISTs compared to PDGFRA mutant and wt GISTs. The overall frequency of TP53 mutations was low (n = 8; 3.5%) and could not be predicted by the immunohistochemical expression of p53. In summary, mutation analysis in TP53 plays a minor role in the subgroup of high-risk GIST before adjuvant treatment with imatinib. Strong expression of MDM2 and p53 correlated with a shorter recurrence free survival, whereas a strong expression of CDK4 correlated to a better recurrence free survival.
Validity of the Symbol Digit Modalities Test as a cognition performance outcome measure for multiple sclerosis

Cognitive and motor performance measures are commonly employed in multiple sclerosis (MS) research, particularly when the purpose is to determine the efficacy of treatment. The increasing focus of new therapies on slowing progression or reversing neurological disability makes the utilization of sensitive, reproducible, and valid measures essential. Processing speed is a basic elemental cognitive function that likely influences downstream processes such as memory. The Multiple Sclerosis Outcome Assessments Consortium (MSOAC) includes representatives from advocacy organizations, Food and Drug Administration (FDA), European Medicines Agency (EMA), National Institute of Neurological Disorders and Stroke (NINDS), academic institutions, and industry partners along with persons living with MS. Among the MSOAC goals is acceptance and qualification by regulators of performance outcomes that are highly reliable and valid, practical, cost-effective, and meaningful to persons with MS. A critical step for these neuroperformance metrics is elucidation of clinically relevant benchmarks, well-defined degrees of disability, and gradients of change that are deemed clinically meaningful. This topical review provides an overview of research on one particular cognitive measure, the Symbol Digit Modalities Test (SDMT), recognized as being particularly sensitive to slowed processing of information that is commonly seen in MS. The research in MS clearly supports the reliability and validity of this test and recently has supported a responder definition of SDMT change approximating 4 points or 10% in magnitude.
Spike Detection Based on Normalized Correlation with Automatic Template Generation

A novel feedback-based spike detection algorithm for noisy spike trains is presented in this paper. It uses the information extracted from the results of spike classification for the enhancement of spike detection. The algorithm performs template matching for spike detection by a normalized correlator. The detected spikes are then sorted by the OSortalgorithm. The mean of spikes of each cluster produced by the OSort algorithm is used as the template of the normalized correlator for subsequent detection. The automatic generation and updating of templates enhance the robustness of the spike detection to input trains with various spike waveforms and noise levels. Experimental results show that the proposed algorithm operating in conjunction with OSort is an efficient design for attaining high detection and classification accuracy for spike sorting.
Multi-attention Recurrent Network for Human Communication Comprehension

Human face-to-face communication is a complex multimodal signal. We use words (language modality), gestures (vision modality) and changes in tone (acoustic modality) to convey our intentions. Humans easily process and understand face-to-face communication, however, comprehending this form of communication remains a significant challenge for Artificial Intelligence (AI). AI must understand each modality and the interactions between them that shape the communication. In this paper, we present a novel neural architecture for understanding human communication called the Multi-attention Recurrent Network (MARN). The main strength of our model comes from discovering interactions between modalities through time using a neural component called the Multi-attention Block (MAB) and storing them in the hybrid memory of a recurrent component called the Long-short Term Hybrid Memory (LSTHM). We perform extensive comparisons on six publicly available datasets for multimodal sentiment analysis, speaker trait recognition and emotion recognition. MARN shows state-of-the-art results performance in all the datasets.
Selective Laser Melting of Duplex Stainless Steel Powders: An Investigation

Selective laser melting gained substantial momentum in the recent past and quite a few alloy systems have been researched and made available for commercial use; titanium, aluminum, stainless and tool steels, cobalt chrome, and Inconel being the most popular examples. Despite the application potential, and the successful processing of powder forms by traditional powder metallurgy methods, selective laser melting of duplex stainless steels was not attempted so far. The response of a duplex stainless steel alloy to processing by selective laser melting with varying process conditions is evaluated in the current research. Experimental results ascertained that the complete cycle starting from duplex powders, consolidating into 3D forms by selective laser melting and then post-process heat treatment to bring the microstructures back to duplex forms is feasible. Within the current experimental domain, the multi-layer samples are close to 90% density and showed a maximum dimensional variation of 2–3%, while the austenite to ferrite ratio is 45:55 after the post-process heat treatment.
High power factor electronic ballast using resonant converter for compact fluorescent lamp

This paper proposes a novel single stage single switch resonant inverter with high power factor for electronic ballast. The power factor correction circuit is at the input side. It is designed to operate at discontinuous conduction mode. The lamp power is controlled by adjusting the duty ratio of the active switch of the power factor correction circuit. The circuit operation is analyzed in detail to derive the design equations. Circuit parameters are designed based on design considerations. Finally, prototype electronic ballast for a 40‐W compact fluorescent lamp is built and tested. The efficiency and the performance of the proposed converter are verified for the designed prototype. Copyright © 2016 John Wiley & Sons, Ltd.
Angiotensin II reduces the surface abundance of KV1.5 channels in arterial myocytes to stimulate vasoconstriction

Several different voltage‐dependent K+ (KV) channel isoforms are expressed in arterial smooth muscle cells (myocytes). Vasoconstrictors inhibit KV currents, but the isoform selectivity and mechanisms involved are unclear. We show that angiotensin II (Ang II), a vasoconstrictor, stimulates degradation of KV1.5, but not KV2.1, channels through a protein kinase C‐ and lysosome‐dependent mechanism, reducing abundance at the surface of mesenteric artery myocytes. The Ang II‐induced decrease in cell surface KV1.5 channels reduces whole‐cell KV1.5 currents and attenuates KV1.5 function in pressurized arteries. We describe a mechanism by which Ang II stimulates protein kinase C‐dependent KV1.5 channel degradation, reducing the abundance of functional channels at the myocyte surface.
High-Dimensional Bayesian Optimization via Additive Models with Overlapping Groups

Bayesian optimization (BO) is a popular technique for sequential black-box function optimization, with applications including parameter tuning, robotics, environmental monitoring, and more. One of the most important challenges in BO is the development of algorithms that scale to high dimensions, which remains a key open problem despite recent progress. In this paper, we consider the approach of Kandasamy et al. (2015), in which the high-dimensional function decomposes as a sum of lower-dimensional functions on subsets of the underlying variables. In particular, we significantly generalize this approach by lifting the assumption that the subsets are disjoint, and consider additive models with arbitrary overlap among the subsets. By representing the dependencies via a graph, we deduce an efficient message passing algorithm for optimizing the acquisition function. In addition, we provide an algorithm for learning the graph from samples based on Gibbs sampling. We empirically demonstrate the effectiveness of our methods on both synthetic and real-world data.
PRSUPR: Automation and analysis software for wavelength dispersive electron-beam microanalysis on a PC

to-use computer program that includes state-of-the-art matrix Hardware configuration for PRSUPR is easily accomplished corrections and integrated quantitative corrections for spectral by editing a simple text file containing the various hardwareinterferences. Also essential is the ability to operate on a powdependent parameters such as take-off angle, number of specerful microcomputer in order to provide onJine graphics and trometers, stage and spectrometer limits, etc. and is completely fast data processing oflarge volumes ofdata. documented for the nonprogfammer. The hardware supported In order to meet these demands, we have developed a software by pRSUpR is completely documented for easy installation. program called PRSUPR (Donovan and Rivers, 1990) with a Suooorted hardware includes DC servo or stepper motor concomplete automation, acquisition, and quantitative analysis trjfirs using optical quadrature encoder feedback for motion package. The software provides a wide range of features for control and also high speed 32-bit digital pulse counters or stanwavelength dispersive electron-beam microanalysis. dard RS-232 serial hardware for X-ray and beam count input. PRSUPR operates under DOS on any IBM PC or compatible In addition, source code outlines are provided for modification with a 286, 386, or 486 processor with 640K RAM, a hard disk, by programmers interfacing to other unsupported hardware. and a math coprocessor. Real-time multitasking for running aupRSUpR supports VGA, EGA, CGA, and Hercules graphics tomated analyses in background is supported with a 386 or 486 display adapters for various data plotting functions such as auprocessor under a suitable multitasking environment. tomated peak scanning and peaking, digitized polygon boundary
A Rapid and Scalable Method for Multilocus Species Delimitation Using Bayesian Model Comparison and Rooted Triplets

Multilocus sequence data provide far greater power to resolve species limits than the single locus data typically used for broad surveys of clades. However, current statistical methods based on a multispecies coalescent framework are computationally demanding, because of the number of possible delimitations that must be compared and time-consuming likelihood calculations. New methods are therefore needed to open up the power of multilocus approaches to larger systematic surveys. Here, we present a rapid and scalable method that introduces 2 new innovations. First, the method reduces the complexity of likelihood calculations by decomposing the tree into rooted triplets. The distribution of topologies for a triplet across multiple loci has a uniform trinomial distribution when the 3 individuals belong to the same species, but a skewed distribution if they belong to separate species with a form that is specified by the multispecies coalescent. A Bayesian model comparison framework was developed and the best delimitation found by comparing the product of posterior probabilities of all triplets. The second innovation is a new dynamic programming algorithm for finding the optimum delimitation from all those compatible with a guide tree by successively analyzing subtrees defined by each node. This algorithm removes the need for heuristic searches used by current methods, and guarantees that the best solution is found and potentially could be used in other systematic applications. We assessed the performance of the method with simulated, published, and newly generated data. Analyses of simulated data demonstrate that the combined method has favorable statistical properties and scalability with increasing sample sizes. Analyses of empirical data from both eukaryotes and prokaryotes demonstrate its potential for delimiting species in real cases.
Hardware efficient implementation of histograms of oriented gradients for pedestrian detection

Pedestrian detection is a challenging work in advanced driver-assisted systems (ADAS) for autonomous vehicles. Among many feature extraction algorithms, histograms of oriented gradients (HOG) has been widely used for pedestrian detection. However, the original HOG involves complicated arithmetic operations and requires large buffers to store the extracted features. In this paper, we propose several simplifications for operations in HOG, leading to significant reduction in hardware cost.
Who is Vouching for the Input Voucher? Decentralized Targeting and Elite Capture in Tanzania

Input subsidy programs carry support as instruments to increase agricultural productivity, provided they are market-smart. This requires especially proper targeting to contain the fiscal pressure, with decentralized targeting of input vouchers currently the instrument of choice. Nonetheless, despite clear advantages in administrative costs, the fear of elite capture persists. These fears are borne out in the experience from the 2008 input voucher pilot program in Kilimanjaro, Tanzania, examined here. Elected village officials received about 60 percent of the distributed vouchers, a factor that significantly reduced the targeting performance of the program, especially in more unequal and remote communities. When targeting the poor, greater coverage and a focus on high trust settings helped mitigate these concerns. The findings highlight the continuing need for scrutiny when relying on decentralized targeting. A clearer sense of purpose (increasing productivity among poorer farmers versus increasing aggregate output) could also enhance the targeting performance.
Representation Learning of Logic Words by an RNN: From Word Sequences to Robot Actions

An important characteristic of human language is compositionality. We can efficiently express a wide variety of real-world situations, events, and behaviors by compositionally constructing the meaning of a complex expression from a finite number of elements. Previous studies have analyzed how machine-learning models, particularly neural networks, can learn from experience to represent compositional relationships between language and robot actions with the aim of understanding the symbol grounding structure and achieving intelligent communicative agents. Such studies have mainly dealt with the words (nouns, adjectives, and verbs) that directly refer to real-world matters. In addition to these words, the current study deals with logic words, such as “not,” “and,” and “or” simultaneously. These words are not directly referring to the real world, but are logical operators that contribute to the construction of meaning in sentences. In human–robot communication, these words may be used often. The current study builds a recurrent neural network model with long short-term memory units and trains it to learn to translate sentences including logic words into robot actions. We investigate what kind of compositional representations, which mediate sentences and robot actions, emerge as the network's internal states via the learning process. Analysis after learning shows that referential words are merged with visual information and the robot's own current state, and the logical words are represented by the model in accordance with their functions as logical operators. Words such as “true,” “false,” and “not” work as non-linear transformations to encode orthogonal phrases into the same area in a memory cell state space. The word “and,” which required a robot to lift up both its hands, worked as if it was a universal quantifier. The word “or,” which required action generation that looked apparently random, was represented as an unstable space of the network's dynamical system.
Characterization and Growing Development of Spodoptera exigua (Lepidoptera: Noctuidae) Larvae Infected by Heliothis virescens ascovirus 3h (HvAV-3h)

Abstract Spodoptera exigua (Hübner) is a very serious worldwide pest capable of causing severe economic losses in numerous agricultural crops. The need for an effective, highly virulent, pathogenic microorganism for use as a biological control agent against S. exigua larvae is particularly important. Heliothis virescens ascovirus 3 h (HvAV-3h)-containing hemolymph with a titer of 9.58 × 1012 genome copies per ml was used to inoculate S. exigua larvae per os with a 1.06 × 1010 dosage per larva for the first- to second instar and 9.58 × 109 genome copies per larva for the third- to fifth instars. Intrahemocoelic injections were also used with a dosage of 1.53 × 109 genome copies per larva for third- to fifth instar. The postinjection mortality, body weight, and food intake of the S. exigua larvae were observed and recorded. The corrected mortality rates for the first- through fifth instar inoculated per os were 21.88 ± 0.98, 22.22 ± 4.00, 8.89 ± 4.01, 6.66 ± 3.33, and 8.89 ± 2.94%, respectively. The early instars were significantly easier to infect with virus compared to the later instar. The corrected mortality of the third, fourth, and fifth instars inoculated by injection was 96.58 ± 3.42, 98.83 ± 1.17, and 97.78 ± 2.22%, respectively. Compared to the healthy larval population, survival time of the diseased larval population was considerably extended. In addition, food intake was greatly reduced, and the body weight remained fairly constant in the third- and fourth instar. The body weight declined in the fifth instar corresponding to a reduction in food intake.
Perfect timing: splicing and transcription rates in living cells

An important step toward understanding gene regulation is the elucidation of the time necessary for the completion of individual steps. Measurement of reaction rates can reveal potential nodes for regulation. For example, measurements of in vivo transcription elongation rates reveal regulation by DNA sequence, gene architecture, and chromatin. Pre‐mRNA splicing is regulated by transcription elongation rates and vice versa, yet the rates of RNA processing reactions remain largely elusive. Since the 1980s, numerous model systems and approaches have been used to determine the precise timing of splicing in vivo. Because splicing can be co‐transcriptional, the position of Pol II when splicing is detected has been used as a proxy for time by some investigators. In addition to these ‘distance‐based’ measurements, ‘time‐based’ measurements have been possible through live cell imaging, metabolic labeling of RNA, and gene induction. Yet splicing rates can be convolved by the time it takes for transcription, spliceosome assembly and spliceosome disassembly. The variety of assays and systems used has, perhaps not surprisingly, led to reports of widely differing splicing rates in vivo. Recently, single molecule RNA‐seq has indicated that splicing occurs more quickly than previously deduced. Here we comprehensively review these findings and discuss evidence that splicing and transcription rates are closely coordinated, facilitating the efficiency of gene expression. On the other hand, introduction of splicing delays through as yet unknown mechanisms provide opportunity for regulation. More work is needed to understand how cells optimize the rates of gene expression for a range of biological conditions. WIREs RNA 2017, 8:e1401. doi: 10.1002/wrna.1401
Lightweight MPI Communicators with Applications to Perfectly Balanced Quicksort

MPI uses the concept of communicators to connect groups of processes. It provides nonblocking collective operations on communicators to overlap communication and computation. Flexible algorithms demand flexible communicators. E.g., a process can work on different subproblems within different process groups simultaneously, new process groups can be created, or the members of a process group can change. Depending on the number of communicators, the time for communicator creation can drastically increase the running time of the algorithm. Furthermore, a new communicator synchronizes all processes as communicator creation routines are blocking collective operations. We present RBC, a communication library based on MPI, that creates range-based communicators in constant time without communication. These RBC communicators support (non) blocking point-to-point communication as well as (non) blocking collective operations. Our experiments show that the library reduces the time to create a new communicator by a factor of more than 400 whereas the running time of collective operations remains about the same. We propose Janus Quicksort, a distributed sorting algorithm that avoids any load imbalances. We improved the performance of this algorithm by a factor of 15 for moderate inputs by using RBC communicators. Finally, we discuss different approaches to bring nonblocking (local) communicator creation of lightweight (range-based) communicators into MPI.