Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunomodulatory Effects of the Lutzomyia longipalpis Salivary Gland Protein Maxadilan on Mouse Macrophages

ABSTRACT Infection with Leishmania major is enhanced when the sand fly Lutzomyia longipalpis salivary peptide maxadilan (MAX) is injected along with the parasite. Here we determined the effect that MAX has on the secretion of cytokines and nitric oxide (NO) and on parasite survival in macrophages (MΦs). The cytokines produced by MΦs can enhance a type 1 response, which will increase NO and the killing of intracellular pathogens such as L. major, or a type 2 response, leading to antibody production that is ineffective against intracellular pathogens such as L. major. A mouse macrophage cell line (RAW 264.7) was stimulated with various concentrations of MAX and lipopolysaccharide (LPS), and the supernatants were collected after 1, 2, and 3 days. Supernatants were assayed for interleukin-12p70 (IL-12p70), IL-10, IL-6, transforming growth factor β (TGF-β), NO, and tumor necrosis factor alpha (TNF-α). Our results indicate that the addition of MAX upregulates the cytokines associated with a type 2 response (IL-10, IL-6, and TGF-β) but downregulates type 1 cytokines (IL-12p70 and TNF-α) and NO. MAX was also added to L. major-infected mouse peritoneal exudate cells (PECs), and the parasite load increased significantly. The enhanced parasite load correlated with decreased NO production by PECs that were stimulated with LPS and gamma interferon in the presence of MAX. The ability of MAX to foster a type 2 response, to enhance parasite survival, and to decrease NO argues that MAX may be crucial for the early survival of Leishmania in the vertebrate host, and therefore, MAX holds considerable promise as an antigenic component for a vaccine against Leishmania.
IEEE 802.3az: the road to energy efficient ethernet

Ethernet is the dominant wireline communications technology for LANs with over 1 billion interfaces installed in the U.S. and over 3 billion worldwide. In 2006 the IEEE 802.3 Working Group started an effort to improve the energy efficiency of Ethernet. This effort became IEEE P802.3az Energy Efficient Ethernet (EEE) resulting in IEEE Std 802.3az-2010, which was approved September 30, 2010. EEE uses a Low Power Idle mode to reduce the energy consumption of a link when no packets are being sent. In this article, we describe the development of the EEE standard and how energy savings resulting from the adoption of EEE may exceed $400 million per year in the U.S. alone (and over $1 billion worldwide). We also present results from a simulation-based performance evaluation showing how packet coalescing can be used to improve the energy efficiency of EEE. Our results show that packet coalescing can significantly improve energy efficiency while keeping absolute packet delays to tolerable bounds. We are aware that coalescing may cause packet loss in downstream buffers, especially when using TCP/IP. We explore the effects of coalescing on TCP/IP flows with an ns-2 simulation, note that coalescing is already used to reduce packet processing load on the system CPU, and suggest open questions for future work. This article will help clarify what can be expected when EEE is deployed.
Construction of texture features

One well-known and effective method used for computationally efficient texture classification is the use of statistical information on 3times3 pixel blocks such as local binary patterns (LBP). However, there has been negligible research on sizes of pixel blocks beyond 3times3 while using the histogram approach. Specifically, larger or non-square features might give better classification results. Our proposed method constructs features, with arbitrary size and shape, that will give the best results for classifying a specific texture, and still keeping the feature vectors as short as possible. In this work, we show the selected features and the performance of our method with a minimum distance classifier and with a neural network and provide quantitative comparisons to the 3times3 block method on both the Brodatz and Ponce texture databases.
Where are the passengers?: a grid-based gaussian mixture model for taxi bookings

Taxi bookings are events where requests for taxis are made by passengers either over voice calls or mobile apps. As the demand for taxis changes with space and time, it is important to model both the space and temporal dimensions in dynamic booking data. Several applications can benefit from a good taxi booking model. These include the prediction of number of bookings at certain location and time of the day, and the detection of anomalous booking events. In this paper, we propose a Grid-based Gaussian Mixture Model (GGMM) with spatio-temporal dimensions that groups booking data into a number of spatio-temporal clusters by observing the bookings occurring at different time of the day in each spatial grid cell. Using a large-scale real-world dataset consisting of over millions of booking records, we show that GGMM outperforms two strong baselines: a Gaussian Mixture Model (GMM) and the state-of-the-art spatio-temporal behavior model, Periodic Mobility Model (PMM), in estimating the spatio-temporal distribution of bookings at specific grid cells during specific time intervals. GGMM can achieve up to 95.8% (96.5%) reduction in perplexity compared against GMM (PMM). Further, we apply GGMM to detect anomalous bookings and successfully relate the anomalies with some known events, demonstrating GGMM's effectiveness in this task.
Body Fat and Body-Mass Index among a Multiethnic Sample of College-Age Men and Women

Obesity prevalence and average body composition vary by US race and gender. Asian Americans have the lowest prevalence of obesity. Relying on body-mass index (BMI) to estimate obesity prevalence may misclassify subgroups that appear normally weighted but have excess body fat. We evaluated percentage body fat (PBF) and BMI to determine whether BMI reflects PBF consistently across different races. 940 college students were recruited from a local public university over four consecutive years. We measured PBF by bioelectrical impedance analysis (BIA), weight by physicians' scales, and height with stadiometers. Our sample comprised Asians (49%), Caucasians (23%), Hispanics (7%), and Other (21%). Participants averaged 21.4 years old; BMI was 22.9 kg/m2; PBF was 24.8%. BMI and PBF varied significantly by race and gender (P value = 0.002 and 0.005 for men; 0.0009 and 0.0008 for women). Asian-American women had the lowest BMI (21.5 kg/m2) but the second highest PBF (27.8%). Linear association between BMI and PBF was the weakest (r 2 = 0.09) among Asian-American women and BMI had the poorest sensitivity (37%) to detect PBF. The high PBF with low BMI pattern exhibited by Asian-American women suggests that they could escape detection for obesity-related disease if BMI is the sole measure that estimates body composition.
Subcarrier opportunistic proportional fair scheduling for OFDMA systems

Resource allocation (RA) for OFDMA has been extensively researched with the objective of maximizing capacity while serving users in a fair manner. However, most of the previous works have focused on achieving these requirements per symbol (instantaneously). On the other hand proportional fair (PF) scheduling which is widely deployed in 3G data networks achieves the system objectives over a certain time, thus adding flexibility and increasing the system throughput. PF scheduling has been modified to work in OFDMA in a few studies, but they have extended the scheme without making use of the additional capacity increase that can be achieved by considering individual relative subcarrier responses. In this paper we propose a simple subcarrier opportunistic proportional fair (SOPF) scheduling scheme specifically suited to OFDMA. It includes a measure that makes the allocation assign the subcarrier to the user who has the best response relative to the average response of that subcarrier with the rest of the users. The result is that our SOPF scheme achieves a capacity-fairness measure above the traditional PF scheme.
Design and Analysis of High Performance Voltage Controlled Ring Oscillator Using Replica Bias Circuit

In present paper, extremely robust design of Ring oscillator using various circuitry and differential stages of cmos inverter have been presented. In this design improvement in power consumption and several other parameters viz. slew rate, Tran conductance, leakage power and leakage current has been achieved by varying the input voltage. This paper describes power consumption variation of [2.811 to1.283] mW by varying input voltage from [1.8 to1.0] V at 180nm technology and improved power consumption of [190.12 to 48.40] ÂμW by varying input voltage from [1.7 to 0.7] V at 45nm technology with the generation of rapid frequency of 2.4 GHz. In this context, we have simulated a high speed ring oscillator using cascaded differential five stage delay cells by applying DC inversion, a biasing circuit and a tuning circuit using the cadence virtuoso tool, which is exceedingly applicable in ultra high speed Wi-Fi communications.
Long Non-Coding RNAs Differentially Expressed between Normal versus Primary Breast Tumor Tissues Disclose Converse Changes to Breast Cancer-Related Protein-Coding Genes

Breast cancer, the second leading cause of cancer death in women, is a highly heterogeneous disease, characterized by distinct genomic and transcriptomic profiles. Transcriptome analyses prevalently assessed protein-coding genes; however, the majority of the mammalian genome is expressed in numerous non-coding transcripts. Emerging evidence supports that many of these non-coding RNAs are specifically expressed during development, tumorigenesis, and metastasis. The focus of this study was to investigate the expression features and molecular characteristics of long non-coding RNAs (lncRNAs) in breast cancer. We investigated 26 breast tumor and 5 normal tissue samples utilizing a custom expression microarray enclosing probes for mRNAs as well as novel and previously identified lncRNAs. We identified more than 19,000 unique regions significantly differentially expressed between normal versus breast tumor tissue, half of these regions were non-coding without any evidence for functional open reading frames or sequence similarity to known proteins. The identified non-coding regions were primarily located in introns (53%) or in the intergenic space (33%), frequently orientated in antisense-direction of protein-coding genes (14%), and commonly distributed at promoter-, transcription factor binding-, or enhancer-sites. Analyzing the most diverse mRNA breast cancer subtypes Basal-like versus Luminal A and B resulted in 3,025 significantly differentially expressed unique loci, including 682 (23%) for non-coding transcripts. A notable number of differentially expressed protein-coding genes displayed non-synonymous expression changes compared to their nearest differentially expressed lncRNA, including an antisense lncRNA strongly anticorrelated to the mRNA coding for histone deacetylase 3 (HDAC3), which was investigated in more detail. Previously identified chromatin-associated lncRNAs (CARs) were predominantly downregulated in breast tumor samples, including CARs located in the protein-coding genes for CALD1, FTX, and HNRNPH1. In conclusion, a number of differentially expressed lncRNAs have been identified with relation to cancer-related protein-coding genes.
On Matching Schemas Automatically

Abstract Schema matching is a basic problem in many database application domains, such as data integration,E-business, data warehousing, and semantic query processing. In current implementations, schemamatching is typically performed manually, which has significant limitations. On the other hand, inprevious research many techniques have been proposed to achieve a partial automation of the Matchoperation for specific application domains. We present a taxonomy that covers many of the existingapproaches, and we describe these approaches in some detail. In particular, we distinguish betweenschema- and instance-level, element- and structure-level, and language- and constraint-based match-ers. Based on our classification we review some previous match implementations thereby indicatingwhich part of the solution space they cover. We intend our taxonomy and review of past work to beuseful when comparing different approaches to schema matching, when developing a new matchalgorithm, and when implementing a schema matching component.
Dendritic reorganization of abdominal motoneurons during metamorphosis of the moth, Manduca sexta

During metamorphosis in the hawkmoth Manduca sexta, muscles of the abdominal body wall undergo a reorganization. Many die at the end of larval life and are replaced in the adult by newly generated muscles. We have identified several of the motoneurons innervating these muscles and followed them through metamorphosis. The morphology of larval motoneurons is correlated with their target location. Those with medial targets have bilateral dendritic fields, whereas those with lateral targets have dendrites restricted to one side of the segmental ganglion. Some motoneurons innervate the same muscle in all stages of life, but the majority lose their larval targets following entry into the pupal stage. Although some of the latter group also die at this time, most survive to innervate a new adult target. These “respecified” motoneurons undergo a period of dramatic dendritic growth during metamorphosis. The results demonstrate that these identified neurons are capable, under the appropriate conditions of existing in more than one stable morphology.
Searching with a Corrupted Heuristic

Memory-based heuristics are a popular and effective class of admissible heuristic functions. However, corruptions to memory they use may cause these heuristics to become inadmissible. Corruption can be caused by the physical environment due to radiation and network errors, or it can be introduced voluntarily in order to decrease energy consumption. We introduce memory error correction schemes that do not require additional memory and exploit knowledge about the behavior of consistent heuristics. This is in contrast with error correcting code approaches which can limit the amount of corruption but at the cost of additional energy and memory consumption. Search algorithms using our methods are guaranteed to find a solution if one exists and its suboptimality is bounded. Moreover, our methods are resilient to any number of memory errors that may occur. An experimental evaluation is also provided to demonstrate the applicability of our approach.
Potent Modulation of the Voltage-Gated Sodium Channel Nav1.7 by OD1, a Toxin from the Scorpion Odonthobuthus doriae

Voltage-gated sodium channels are essential for the propagation of action potentials in nociceptive neurons. Nav1.7 is found in peripheral sensory and sympathetic neurons and involved in short-term and inflammatory pain. Nav1.8 and Nav1.3 are major players in nociception and neuropathic pain, respectively. In our effort to identify isoform-specific and high-affinity ligands for these channels, we investigated the effects of OD1, a scorpion toxin isolated from the venom of the scorpion Odonthobuthus doriae. Nav1.3, Nav1.7, and Nav1.8 channels were coexpressed with β1-subunits in Xenopus laevis oocytes. Na+ currents were recorded with the two-electrode voltage-clamp technique. OD1 modulates Nav1.7 at low nanomolar concentrations: 1) fast inactivation is dramatically impaired, with an EC50 value of 4.5 nM; 2) OD1 substantially increases the peak current at all voltages; and 3) OD1 induces a substantial persistent current. Nav1.8 was not affected by concentrations up to 2 μM, whereas Nav1.3 was sensitive only to concentrations higher than 100 nM. OD1 impairs the inactivation process of Nav1.3 with an EC50 value of 1127 nM. Finally, the effects of OD1 were compared with a classic α-toxin, AahII from Androctonus australis Hector and a classic α-like toxin, BmK M1 from Buthus martensii Karsch. At a concentration of 50 nM, both toxins affected Nav1.7. Nav1.3 was sensitive to AahII but not to BmK M1, whereas Nav1.8 was affected by neither toxin. In conclusion, the present study shows that the scorpion toxin OD1 is a potent modulator of Nav1.7, with a unique selectivity pattern.
Iterative Discrete Particle Swarm Optimization Algorithm and Its Application to Batch Process Optimization

To solve dynamic optimization problems of batch processes without state independent and end-point constraints, an iterative discrete particle swarm optimization (IDPSO) algorithm was developed. The main idea of the algorithm was to execute the discrete particle swarm optimization (DPSO) iteratively then the control profile would converge to an optimal one. For the method, the control region and time interval were discretized to a finite number of decision variables and DPSO was then used to search for the best control vector. The searching space contracted as iterations proceeded hence the performance index and control profile could achieve the best value. The results of each iterated calculation were filtered by a three-point linear smooth operator, which makes the optimal trajectory smooth and steady. The simulation result of a batch process shows that the IDPSO algorithm can solve the dynamic optimization problems effectively if there is no state independent and end-point constraints.
Measurement of platelet collagen receptor density in human subjects.

To the Editor: We are writing to provide data on a novel approach for measuring platelet collagen receptors in human subjects. Immediately after vascular injury, circulating platelets are exposed to collagen, a matrix protein that both supports platelet adhesion and activates platelets through platelet collagen receptors.1 Collagen signals generated at a site of arterial vessel injury are therefore likely to be among the first platelet activating signals that generate the coronary thrombi responsible for myocardial infarction. The molecular basis of platelet collagen responses has recently been elucidated by the identification and characterization of two platelet collagen receptors: the immune receptor homologue glycoprotein VI (GPVI)2 and the integrin α2β1. 3 GPVI is required for platelet activation in response to collagen,4,5 whereas α2β1 plays an accessory role to support platelet responses to immobilized collagen in the setting of high shear forces.6 Preliminary findings from both laboratory and clinical studies suggest that the surface density of the platelet collagen receptors GPVI and α2β1 may regulate the degree of platelet activation by collagen and its clinical outcome.7–11 Despite these preliminary findings, the precise role of platelet collagen receptor density as a risk factor for MI remains poorly understood, with the few reported studies yielding apparently contradictory results. A study examining the correlation of platelet GPVI receptor polymorphisms with surface receptor density in normal individuals found one common allele (associated with the coding region polymorphism T683C) that correlated with lower GPVI receptor density and reduced collagen-mediated platelet aggregation.8 In contrast, …
University of Hagen at QA@CLEF 2006: Interpretation and Normalization of Temporal Expressions

The German question answering (QA) system InSicht participated in QA@CLEF for the third time. InSicht realizes a deep QA approach: it builds on full sentence parses, inferences on semantic representations, and matching between semantic representations derived from questions and document sentences. InSicht was improved for QA@CLEF 2006 in the following main areas: temporal expressions are better normalized and temporal deictic expressions are resolved to explicit date representations; the coreference module was extended by a fallback strategy for increased robustness; equivalence rules can introduce negative information that should not occur in document sentences used for answering questions; answer candidates are clustered in order to avoid multiple occurrences of one real-world entity in the answers to a list question; and finally a shallow QA subsystem that produces a second answer stream was integrated into InSicht. The current system is evaluated on the German questions from QA@CLEF 2006. An ablation study indicates which changes had the most positive effects.
Mutational analysis of DNAse I gene in Pakistani SLE patients

Systemic Lupus Erythematosus (SLE) is one of the classic examples of autoimmune diseases among human beings and is a rare disease in Pakistani population. Clinically, it is a quite diverse and complicated autoimmune disease in a sense that it involves multiple organs of the body and mimics other diseases as well. Mutational analysis of DNAse I gene exon 8 was performed because most of the mutations were reported in these regions with reference to SLE. Genes were amplified by Step-down PCR technique in order to get the bands of our interest. Extracted DNA bands were sequenced to analyze mutations. Thirteen SLE samples showed a missense mutation in DNAse I gene. The codon CAA changed to CGA (+2373 A>G) so the glutamine amino acid was replaced by arginine at position 244 of Deoxyribonuclease I protein.
Robust device modeling with process variation consideration and dimension reduction techniques

Nowadays the highest device integration affects the design process in several ways. The process variations (PV) significantly impact the circuit performance. As a consequence, a major consideration is determining the production yield relation to the technology based manufacturing variations. The traditional Monte Carlo based sampling analysis became computationally not practical solution due to the extensive parameter set and computationally demanding transistor models. Hence the overall simulation time increases rapidly. Additionally the higher device integration requires dealing with numerous local and global parameters. Clearly all these factors can bottleneck the efforts of achieving fast design cycle, resulting in dramatic computational cost increase along with the decrease of the transistor size. Statistical analysis can be facilitated by estimating a direct relation of circuit performance factors to the PV parameters. The compact transistor models such as BSIM or PSP use a large number of parameters and equations. However various performance factors can be related to few circuit parameters. For complementary gates we propose new macro model, where all static and dynamic characteristics are related to set of Finite Points. All timing and power related quantities can be predicted by evaluating the model equations. The dynamic characterization relies on charge distribution at each node. The affect of all PV is represented with parameterizing the FP sensitivity to the all variational sources. In overall the new gate model employ same computational structure for different gates and related to traditional BSIM models is in far more simple computational form. This results in more efficient Monte Carlo analysis. Large scale circuit analysis based on the FP models can be used for estimation of various global performance parameters. These circuit measures such as propagation delay for example is evaluated gradually from the circuit input to desired output.