Miracle-dz/UniFAR-FTUs huggingface dataset:
Thromboxane mediation of cardiopulmonary effects of embolism.

Humoral factors released from platelets during pulmonary embolism may be the cause of several attendant cardiopulmonary abnormalities. This study examines the role of thromboxanes (Tx) after experimental embolism induced with 0.5 g/kg autologous clot in four groups of five dogs: (a) untreated embolized controls; (b) pretreatment with the Tx synthetase inhibitor, imidazole 25 mg/kg . h i.v. , starting 30 min before embolization; (c) pretreatment with the cyclooxygenase inhibitor indomethacin, 5 mg/kg, 12 h per os and 1 mg/kg, 1 h i.v. before the experiment; (d) treatment with prostacyclin (PGI(2)) 100 etag/kg . min i.v. for 1 h, 1 h after embolization. Within 30 min, embolization led to increases of 6-keto-PGF(1alpha), the stable hydrolysis product of PGI(2), from 0.11+/-0.08 etag/ml (mean+/-SD) to 0.33+/-0.10 etag/ml (P < 0.005) and TxB(2), the stable product of TxA(2), from 0.10+/-0.04 etag/ml to 0.38+/-0.06 etag/ml (P < 0.001). Increases were observed in total dead space (V(D)/V(T)) from 0.46+/-0.03 to 0.61+/-0.08 (P < 0.025, physiologic shunting (Q(S)/Q(T)) from 16+/-4% to 38+/-9% (P < 0.01), pulmonary vascular resistance (PVR) from 2.27+/-0.59 mm Hg.min/liter to 9.21+/-1.90 mm Hg.min/liter (P < 0.005) and mean pulmonary arterial pressure from 14+/-6 mm Hg to 34+/-1 mm Hg (P < 0.001). Cardiac index (CI) fell from 139+/-11 ml/kg.min to 95+/-17 ml/kg.min in 4 h (P < 0.025). Imidazole pretreatment prevented a rise of TxB(2), but not 6-keto-PGF(1alpha); indomethacin blocked both. Both agents maintained V(D)/V(T) at base line and limited increases in Q(S)/Q(T) and PVR. CI was higher after imidazole pretreatment compared with controls (P < 0.025). Indomethacin led to intermediate levels of CI. PGI(2) lowered TxB(2) (P < 0.025), V(D)/V(T) (P < 0.025), Q(S)/Q(T) (P < 0.025) and PVR (P < 0.05) within 30 min. During PGI(2) infusion, CI was higher than controls. Concentrations of TxB(2) correlated with V(D)/V(T), r = 0.79 and Q(S)/Q(T), r = 0.69 (P < 0.001). Treatment of three dogs with the imidazole derivative ketoconazole, 10 mg/kg IV, 30 min after 0.75 g/kg autologous clot resulted in a lowering of physiologic dead space, but no other improvement of cardiopulmonary function. These results show that a number of cardiopulmonary abnormalities induced by pulmonary embolism are related directly or indirectly to platelet secretions and that V(D)/V(T) is closely allied to TxA(2) levels.
The neural signatures of distinct psychopathic traits

Recent studies suggest that psychopathy may be associated with dysfunction in the neural circuitry supporting both threat- and reward-related processes. However, these studies have involved small samples and often focused on extreme groups. Thus, it is unclear to what extent current findings may generalize to psychopathic traits in the general population. Furthermore, no studies have systematically and simultaneously assessed associations between distinct psychopathy facets and both threat- and reward-related brain function in the same sample of participants. Here, we examined the relationship between threat-related amygdala reactivity and reward-related ventral striatum (VS) reactivity and variation in four facets of self-reported psychopathy in a sample of 200 young adults. Path models indicated that amygdala reactivity to fearful facial expressions is negatively associated with the interpersonal facet of psychopathy, whereas amygdala reactivity to angry facial expressions is positively associated with the lifestyle facet. Furthermore, these models revealed that differential VS reactivity to positive versus negative feedback is negatively associated with the lifestyle facet. There was suggestive evidence for gender-specific patterns of association between brain function and psychopathy facets. Our findings are the first to document differential associations between both threat- and reward-related neural processes and distinct facets of psychopathy and thus provide a more comprehensive picture of the pattern of neural vulnerabilities that may predispose to maladaptive outcomes associated with psychopathy.
Mentoring for Mentors: The Music Mentor Plus Program

The Music Mentor Plus program was designed to introduce mentoring strategies teachers can implement during supervision of student teachers and early field experience interns, while also fostering connections between field-based modeling and university methods course content. Throughout the 2015–2016 school year, seven music teachers and two university music education faculty members engaged in a series of live workshops and ongoing electronic communication. Participants joined in discussions and role-play activities and completed readings and reflection assignments. In this article, we present an outline of the program as well as reflections on the experience from the faculty leaders and participating teachers.
Connectivity Based k-Hop Clustering in Wireless Networks

In this paper we describe several new clustering algorithms for nodes in a mobile ad hoc network. The main contribution is to generalize the cluster definition and formation algorithm so that a cluster contains all nodes that are at distance at most k hops from the clusterhead. We also describe algorithms for modifying cluster structure in the presence of topological changes. We also proposed an unified framework for most existing and new clustering algorithm where a properly defined weight at each node is the only difference in otherwise the same algorithm. This paper studied node connectivity and node ID as two particular weights, for k=1 and k=2. Finally, we propose a framework for generating random unit graphs with obstacles.
Robust face recognition using wavelets and neural networks

For humans recognize a person looking at his face is a trivial and daily task that brain performs in seconds and almost ever with high precision. Nevertheless, even when this task seems easy, face recognition remains as a challenge when implemented in a computer. In this article, a new methodology for accomplish two of the three stages involved in the design of an automatic face recognition system is presented: for feature extraction stage the discrete wavelet transform is used, and for the recognition stage a personalized multilayer neural network is proposed. Experiments were performed using 300 images from the public database of faces Faces94. The results show a recognition rate of 95%. This demonstrates that the proposed approach is a feasible and effective solution to the face recognition problem. Keywords— Face recognition; neural networks; wavelets
The twisted circular form of polyoma viral DNA.

The major part of the DNA from polyoma virus has been shown to consist of circular base-paired duplex molecules without chain ends.1–3 The intertwined circular form accounts for the ease of renaturation4 of this DNA and the failure of the strands to separate in strand-separating solvents.1–3
Trajectories of internalizing problems during the transition to adolescence in children with and without conduct problems

Children with conduct problems are at greater risk for internalizing problems. The objectives of this study were to (1) examine trajectories of internalizing problems among children with and without clinically significant conduct problems during the transition to adolescence; and (2) identify how academic achievement, peer rejection, parent socioeconomic status, maternal distress, parental warmth, child temperament, and receptive verbal functioning explained differences between the two groups. Children with conduct problems (N = 388, 45% girls) and a comparison sample without conduct problems (N = 299, 52% girls) were recruited from Quebec, Canada, when they were between the ages of 7 and 10 years, and were followed across 4 years. Mothers and teachers provided information on internalizing problems each year. Having clinically significant conduct problems was associated with higher initial levels of internalizing problems according to mothers and teachers, but not with changes in internalizing problems over time. With regards to teacher ratings, academic achievement, peer rejection, and negative emotionality partially explained differences in internalizing problems for youth with and without conduct problems. For mother ratings, maternal distress, negative emotionality, and peer rejection completely explained the association for girls, and partially explained the association for boys. Findings supported a multi-rater approach for understanding risk for internalizing problems among children with and without conduct problems. In particular, they highlight the importance of differences across context for understanding factors associated with vulnerability to internalizing problems.
A novel MIMO communication system based on time varying linear transformation and Tanner codes

A novel concatenated multi-input multi-output (MIMO) communication system based on time varying linear transformation (TVLT) and Tanner codes is proposed in this paper. The girth 4 property of Tanner codes is discussed briefly. Combined with the outstanding distance property of Tanner codes, TVLT can provide full diversity and maximum coding gain at the same time without exhaustive search for the good space-time codes as usual. Corresponding joint iterative detector /decoder structure of receiver is given which greatly simplifies the demodulation /decoding process. Compared with present Turbo codes or conventional convolution codes concatenated MIMO system, the new concise system achieves higher coding gain and full diversity together, which is verified by simulation results.
Adaptive Stream Processing using Dynamic Batch Sizing

The need for real-time processing of "big data" has led to the development of frameworks for distributed stream processing in clusters. It is important for such frameworks to be robust against variable operating conditions such as server failures, changes in data ingestion rates, and workload characteristics. To provide fault tolerance and efficient stream processing at scale, recent stream processing frameworks have proposed to treat streaming workloads as a series of batch jobs on small batches of streaming data. However, the robustness of such frameworks against variable operating conditions has not been explored. In this paper, we explore the effects of the batch size on the performance of streaming workloads. The throughput and end-to-end latency of the system can have complicated relationships with batch sizes, data ingestion rates, variations in available resources, workload characteristics, etc. We propose a simple yet robust control algorithm that automatically adapts the batch size as the situation necessitates. We show through extensive experiments that it can ensure system stability and low latency for a wide range of workloads, despite large variations in data rates and operating conditions.
Large-Memory Nodes for Energy Efficient High-Performance Computing

Energy consumption is by far the most important contributor to HPC cluster operational costs, and it accounts for a significant share of the total cost of ownership. Advanced energy-saving techniques in HPC components have received significant research and development effort, but a simple measure that can dramatically reduce energy consumption is often overlooked. We show that, in capacity computing, where many small to medium-sized jobs have to be solved at the lowest cost, a practical energy-saving approach is to scale-in the application on large-memory nodes. We evaluate scaling-in; i.e. decreasing the number of application processes and compute nodes (servers) to solve a fixed-sized problem, using a set of HPC applications running in a production system. Using standard-memory nodes, we obtain average energy savings of 36%, already a huge figure. We show that the main source of these energy savings is a decrease in the node-hours (node_hours = #nodes x exe_time), which is a consequence of the more efficient use of hardware resources. Scaling-in is limited by the per-node memory capacity. We therefore consider using large-memory nodes to enable a greater degree of scaling-in. We show that the additional energy savings, of up to 52%, mean that in many cases the investment in upgrading the hardware would be recovered in a typical system lifetime of less than five years.
A Framework for Composing High-Performance OpenCL from Python Descriptions

Parallel processors have become ubiquitous; most programmers today have access to parallel hardware such as multi-core processors and graphics processors. This has created an implementation gap, where efficiency programmers with knowledge of hardware details can attain high performance by exploiting parallel hardware, while productivity programmers with application-level knowledge may not understand low-level performance trade-offs. Ideally, we would like to be able to write programs in productivity languages such as Python or MATLAB, and achieve performance comparable to the best hand-tuned code.One approach toward achieving this ideal is to write libraries that get high efficiency on certain operations, and call these libraries from the productivity environment. We propose a framework that addresses two problems with this approach: that it fails to fuse operations for efficiency, and that it may not consider runtime information such as shapes and sizes of data structures. With our framework, efficiency programmers write and/or generate customized OpenCL snippets at runtime and the framework automatically fuses, compiles, and executes these operations based on a Python description.We evaluate the framework with case studies of two very different applications: space-time adaptive radar processing and optical flow. For a space-time adaptive radar processing application, our framework's implementation is competitive with a hand-coded implementation that uses a vendor-optimized library. For optical flow, a computer vision application, the framework achieves frame rates that are between 0.5x and 0.97x hand-coded OpenCL performance.
A fractional delay-locked loop for on chip clock generation applications

A fractional multiplying delay-locked loop (FMDLL) for high-speed on-chip clock generation applications is presented. The proposed DLL architecture overcomes some drawbacks of phase-locked loops (PLLs) such as jitter accumulation and stability while maintaining the advantageous of a PLL as a multi-rate fractional frequency multiplier. The output frequency range can be tuned from 1GHz to 2.5GHz with selectable multiplication ratios of M + 0.05 /spl times/ AT where 1 /spl ges/ K /spl ges/ 19. To generate some finer ratios, K could be changed between two consecutive integer numbers. In this situation, a digital delta-sigma modulator could be used to suppress the spurs existing in the output spectrum.
The mean firing rate of atrial fibrillation as estimated from the ECG evaluation using a biophysical model

The correspondence between the firing rates of atrial myocytes during atrial fibrillation and the dominant frequencies observed in the Fourier spectra of the corresponding surface ECG signals was studied. The observations were based on signals simulated using a biophysical model of the atria and of the volume conduction effects of the thorax. Different substrates for AF were generated, each resulting in a different type of AF dynamics. The results indicate that the full Fourier spectrum yields more information on the complexity of a particular variant of AF than the analysis of just its dominant frequency. The same applies to analyzing the spectra of multiple leads rather using just single lead signals.
Unequal error protection of PCA-coded face images for transmission over mobile channels

In this paper, a system for reliable communication of coded grey-level face images over noisy channels is proposed. Principal Component Analysis (PCA) is used for face image coding and an unequal error protection (UEP) joint source channel coding scheme is proposed for mobile communication applications. Coded images are protected with convolutional codes for transmission over mobile channels. Recognition rates obtained with UEP system approach the 95% recognition performance for images from the ORL face database.
Analysis of low cost beamforming techniques for LMS Communication Rx terminal

The user demand for communication on the move has grown exponentially over past decade which are currently being served using terrestrial communication. Similar, demands also exist for land mobile satellite (LMS) communication (like TV broadcast reception, multimedia communication etc). High antenna gain is required to sustain a reasonably high data rate links, which demands for bigger antenna and tracking system. The handheld LMS terminals can support low data rate links where as vehicle mounted transportable LMS terminals can support high data rate links as use of bigger antenna is not an issue. The antenna used for transportable terminals should have low profile and needs tracking system to point its narrow beam towards the satellite. The low profile requirement can be met by planner antenna technology. The tracking requirement can be met by beamforming techniques without disturbing profile. The user terminals are also cost sensitive. Hence, its implementation should be cost effective with current technology. A comprehensive survey of different beamforming techniques and architectures is presented to meet the demands of LMS Communication terminal. A proof of concept (POC) model has been developed to evaluate the performance of selected technique and architecture.
Improving Reusability of Test Symbols for Test Data Compression

In this paper, complementary Huffman coding techniques are proposed for test data compression/decompression of complex SOC designs during manufacturing testing. Instead of the compatible relationship between test data blocks, complementary features between test blocks are also exploited. Based on this property, more test data blocks can share the same codeword and the size of the modified Huffman tree can be reduced. This will not only reduce the area overhead of the decoding circuitry but also substantially increase the compression ratio. A graph model is also proposed for don’t-care assignment of test cube. This problem can be transformed to the clique partitioning problem whose complexity is basically NP-hard. Therefore, in order to exploit the compatible and complementary relationships between test blocks, a heuristic algorithm is proposed for filling test cubes. Thereafter, given the set of test vectors, two algorithms are proposed for complementary Huffman encoding. The compression ratio and hardware overhead of the decoding circuitry are analyzed. According to experimental results, the area overhead of the decompression circuit is lower than that of the full Huffman coding technique. However, it is a little bit higher than that of the selective Huffman coding technique. Moreover, the compression ratio is higher than that of the selective and optimal selective Huffman coding techniques.
LUT-based FPGA technology mapping for power minimization with optimal depth

In this paper, we study the technology mapping problem for LUT-based FPGAs targeting power minimization. We present the PowerMap algorithm to generate a mapping solution to minimize power consumption while keeping the delay optimal. We compute min-height K-feasible cuts for critical nodes to optimize the depth and compute min-weight K-feasible cuts for noncritical nodes to minimize the power consumption of the mapping solution. We have implemented PowerMap in C and tested it on a number of MCNC benchmark circuits. Compared to FlowMap, a delay-optimal mapper, our algorithm reduces the power consumption by 17.8% and uses 9.4% less LUTs without any depth penalty.
First results of an automated model-based segmentation system for subcortical structures in human brain MRI data

We propose an automated model-based approach for segmenting subcortical structures, especially the basal ganglia, from 3D human brain MRI images. Our hybrid approach combines an automatic tissue classification scheme, a landmark detection algorithm and a discrete active surface model (ASM) to achieve its goal. A priori knowledge is incorporated into the different stages of the model and is used to retain shape and neighborhood information about the structures of interest throughout the segmentation process. The system is designed to require as little user interaction as possible. Sample results are given for the Brain Web simulated brain data set and for a real data set
An Iterative Method for Calculating the Optimum Size of Inverter in PV Systems for Malaysia

This paper presents an iterative method for optimizing inverter size in photovoltaic (PV) system for five sites in Malaysia. The sizing ratio which is the ratio of PV rated power to inverter's rated power is optimized at different load levels using different commercial inverters models. Hourly solar radiation and ambient temperature records are used to develop a Matlab model for a PV array and inverter. The model aims to estimate the inverter's efficiency in terms of PV array output power and inverter rated power. The results showed that the optimum sizing ratios for Kuala Lumpur, Johor Bharu, Ipoh, Kuching and Alor Setar are 1.21, 1.43, 1.31, 1.37 and 1.26, respectively. Streszczenie. W artykule zaprezentowano iteracyjną metode optymalizacji rozmiaru przeksztaltnika w systemach fotovoltaicznych na przykladzie pieciu usytuowan w Malezji. Optymalizacje przeprowadzono dla roznych obciązen bazując na komercjalnych modelach przeksztaltnikow. Uwzgledniono naslonecznienie dobowe i temperature otoczenia. Na przyklad dla Kuala Lumpur optymalny stosunek mocy fotowoltaicznej do mocy przeksztaltnika wynosil 1.21. (Iteracyjna metoda obliczania optymalnego rozmiaru przeksztaltnika w systemach fotowoltaicznych na przykladzie Malezji)
Intelligent Caching in Heterogeneous Reasoning andMediator Systems

Heterogeneous Reasoning and Mediator Systems (HERMES), rst proposed by Lu, Nerode and Subrahmanian, may be used to access and logically integrate information from external databases and/or software packages using functions already deened in those domains. When processing queries in HERMES, we need to execute these external programs, and this is often an expensive process, especially when these programs are located at remote sites on, say a network. Consequently, the problem of minimizing access to such external routines without compromising completeness is an important one. In this paper, we will present methods to cache the results of previous computations and use the knowledge about external programs to make intelligent use of the cached information to reduce calls to external programs.