Miracle-dz/UniFAR-FTUs huggingface dataset:
Scaling Information Infrastructure: The Case of Next Generation IP in Internet

An information infrastructure has to scale, and hence change, as it expands. This creates a dilemma. The expansion fuels new patterns of use, which require changes, while on the other hand, the diffusion of and investments in the information infrastructure have a strong, conservative influence-the intertia of the installed base. The changes required to implement the scaling have to be in small steps. An information infrastructure is not ''changed,'' but rather it undergoes transitions. These transitions are highly involved sociotechnical negotiations. This article is based on a case study of the efforts to change the Internet Protocol (IP) in the Internet to facilitate further growth. The revision of IP is the most serious challenge to the continued scaling of the Internet during its nearly 30 years of existence.
Scheduling Algorithms for Multicarrier Wireless Data Systems

We consider the problem of scheduling multicarrier wireless data in systems such as IEEE 802.16 (WiMAX). Each scheduling decision involves assigning carriers to users for each time slot, subject to the constraint that each carrier is assigned to at most one user, but multiple carriers can potentially be assigned to the same user. One important aspect of our problem is that a scheduler knows the channel rates across all users and all carriers whenever a scheduling decision is made. This “global” information may give a potential for enhancing performance via an optimized allocation of carriers to users. We analyze this problem in a situation where finite queues are fed by a data arrival process. The well-known MaxWeight algorithm for the single-carrier setting maximizes the product of queue size and service rate. We focus on how to adapt MaxWeight to the multicarrier setting. If the same objective is pursued, more service than needed may be assigned to drain a queue, thereby creating wastage. While a simple variant in the objective forbids this wastage, it turns an easy-to-compute old objective into an intractable new objective. We state the hardness of the new optimization problems and propose several extremely simple algorithms with provable performance bounds. We conclude with supporting simulation examples.
CD66a Interactions Between Human Melanoma and NK Cells: A Novel Class I MHC-Independent Inhibitory Mechanism of Cytotoxicity1

NK cells are able to kill virus-infected and tumor cells via a panel of lysis receptors. Cells expressing class I MHC proteins are protected from lysis primarily due to the interactions of several families of NK receptors with both classical and nonclassical class I MHC proteins. In this study we show that a class I MHC-deficient melanoma cell line (1106mel) is stained with several Ig-fused lysis receptors, suggesting the expression of the appropriate lysis ligands. Surprisingly, however, this melanoma line was not killed by CD16-negative NK clones. The lack of killing is shown to be the result of homotypic CD66a interactions between the melanoma line and the NK cells. Furthermore, 721.221 cells expressing the CD66a protein were protected from lysis by YTS cells and by NK cells expressing the CD66a protein. Redirected lysis experiments demonstrated that the strength of the inhibitory effect is correlated with the levels of CD66a expression. Finally, the expression of CD66a protein was observed on NK cells derived from patients with malignant melanoma. These findings suggest the existence of a novel class I MHC-independent inhibitory mechanism of human NK cell cytotoxicity. This may be a mechanism that is used by some of the class I MHC-negative melanoma cells to evade attack by CD66a-positive NK cells.
Learning influence and susceptibility from information cascade

For information propagation on social networks, one key problem is inferring propagation probability, i.e., the probability that one piece of information is propagated from one individual to the other. Existing methods mainly address this problem in a pair-wise manner, determining the propagation probability among pairs of individuals. This over-represented manner makes them suffer severe overfitting problem for pair of individuals without observed interactions, and thus limits their prediction accuracy. In this paper, instead of inferring the pair-wise propagation probability, we learn two low-rank vectors for each individual, representing its influence and susceptibility respectively. Based on this concise representation, we propose a probabilistic model to effectively learn individuals' influence and susceptibility from the log of information cascades. We evaluate the performance of our method on the dataset from the largest social media in China, and show that our method outperforms existing methods at inferring propagation probability.
Neurocognitive habilitation therapy for children with fetal alcohol spectrum disorders: an adaptation of the Alert Program®.

OBJECTIVE This study evaluated the effectiveness of neurocognitive habilitation, a group therapy intervention for foster and adoptive caregivers and their children who were prenatally exposed to alcohol. METHOD Participants were recruited from clients seeking evaluation for fetal alcohol syndrome (FAS) and alcohol-related neurodevelopmental disorder (ARND) and were randomly assigned to treatment and no-treatment control groups. Forty children participated in the treatment program and were compared with 38 control participants using the Behavior Rating Inventory of Executive Function (BRIEF) and the Roberts Apperception Test for Children (RATC). RESULTS Significant differences between the treatment and control groups were demonstrated on the BRIEF and on the RATC, suggesting that the intervention improved executive functioning and emotional problem-solving skills. CONCLUSION These findings yield promising evidence of the effectiveness of the neurocognitive habilitation intervention in improving executive functioning and emotional problem solving in children with FAS or ARND.
DETERMINATION OF GENOTОXIC EFFECTS OF SOME FOOD ADDITIVES ON SOME HUMAN CANCER CELLS BY FLOW CYTOMETRY ANALYSIS

Toxicogenomics is the study of the relationships between the structure and activity of the genome and the adverse biological effects of exogenous agents. Different kinds of additives are widely applied in food industry. Yeast cells were grown with the food additives, and culture growth. This study aimed to select and genetically determine the possible genotоxic effects of three food additives (MSG, SB and Saffron) on human cell lines. Flow cytometric analysis demonstrated that treatment of human hepatocellular carcinoma cells (Caco-3) cells with food additives increased G2/M phase cell cycle arrest. The quantitative real time-PCR was used to measure the mRNA levels of p53, Bax, and Bcl-2 genes. The data showed that food additives changed transcriptional levels of these related genes. The mRNA expression of p53 and Bax were up-regulated, but, the transcription of Bcl2 was significantly down-regulated compared to the control. Protein-protein interaction maps provided a valuable framework for a better understanding of the functional organization of the proteome. These data indicated that food additives decreased cell viability in malignant and non-malignant cells as well as confirmed the occurrence of their cytоtoxic effects. It is evident from the aforementioned discussion that the studied food additives could inflect some serious health hazards if they are added haphazardly in foods and preveradges. Therefore, strict control of their use in accordance with the special regulations set by the Food and Drug Administration (FDA) and World Health Organization (WHO) to insure their biosafety for human consumption.
Taxol-induced bundling of brain-derived microtubules

Taxol has two obvious effects in cells. It stabilizes microtubules and it induces microtubule bundling. We have duplicated the microtubule- bundling effect of taxol in vitro and report preliminary characterization of this bundling using electron microscopy, sedimentation, and electrophoretic analyses. Taxol-bundled microtubules from rat brain crude extracts were seen as massive bundles by electron microscopy. Bundled microtubules sedimented through sucrose five times faster than control microtubules. Electrophoretic analysis of control and taxol-bundled microtubules pelleted through sucrose revealed no striking differences between the two samples except for a protein doublet of approximately 100,000 daltons. Taxol-induced microtubule bundling was not produced by using pure tubulin or recycled microtubule protein; this suggested that taxol-induced microtubule bundling was mediated by a factor present in rat brain crude extracts. Taxol cross- linked rat brain crude extract microtubules were entirely labile to ATP in the millimolar range. This ATP-dependent relaxation was also demonstrated in a more purified system, using taxol-bundled microtubules pelleted through sucrose and gently resuspended. Although the bundling factor did not recycle with microtubule protein, it was apparently retained on isolated taxol-stabilized microtubules. The bundling factor was salt extracted from taxol-stabilized microtubules and its retained activity was demonstrated in an add-back experiment with assembled phosphocellulose-purified tubulin.
Separation of torque components using Frozen Permeability and Maxwell Stress Tensor

Local force distribution in motors has been widely studied to analyze the origins of torque ripple and vibration. In most cases, there are multiple force waves which need to be identified and analyzed individually. While separation of these forces and the corresponding fields is simpler if the core is below saturation limits, special techniques are required if significant portion of the core is in saturation. In this paper, Frozen Permeability and Maxwell Stress Tensor are used to separate components of air-gap forces in an Interior Permanent Magnet Synchronous Motor. The combined use of Frozen Permeability and Maxwell Stress Tensor is existing in literature. However, the approach proposed in this work allows to view reaction torque as sum of two components that have dissimilar ripple content. Nature of torque-ripple due to these two components is studied by varying the slot-design.
Hierarchical neural networks (HNN) for Chinese continuous speech recognition

To integrate the hierarchy structure of discrimination between all HMM states for Chinese Initials and Finals, we constructed in this paper Hierarchical Neural Networks (HNN), which differ from Jordan's HME in such extensions as more complex parameterization for gate and/or expert and dimension-reduced expert network. With these extensions, we can reuse those pre-trained simple node networks in a hierarchy structure (HNN), and fine-tune them jointly by Generalized Expectation Maximization (GEM) algorithm. The proposed HNNs were used within hybrid HMM-ANN models to perform the estimation of posterior probabilities for HMM states. Instead of using a large monolithic neural network, the HNN system can be trained in a short time compared with MLP estimator and result in a speed-up in decoding time over the conventional systems. We have applied the proposed hybrid HMM-HNN method to the recognition task of Chinese Continuous Speech. , achieve a promising word error rate of 26.4%.
VETA: a Matlab toolbox for the collection and analysis of electromyography combined with transcranial magnetic stimulation

The combination of electromyography (EMG) and transcranial magnetic stimulation (TMS) offers a powerful non-invasive approach for investigating corticospinal excitability in both humans and animals. Acquiring and analyzing the data produced with this combination of tools requires overcoming multiple technical hurdles. Due in part to these technical hurdles, the field lacks standard routines for EMG data collection and analysis. This poses a problem for study replication and direct comparisons. Although software toolboxes already exist that perform either online EMG data visualization or offline analysis, there currently are no openly available toolboxes that flexibly perform both and also interface directly with peripheral EMG and TMS equipment. Here, we introduce Visualize EMG TMS Analyze (VETA), a MATLAB-based toolbox that supports simultaneous EMG data collection and visualization as well as automated offline processing and is specially tailored for use with motor TMS. The VETA toolbox enables the simultaneous recording of EMG, timed administration of TMS, and presentation of behavioral stimuli from a single computer. These tools also provide a streamlined analysis pipeline with interactive data visualization. Finally, VETA offers a standard EMG data format to facilitate data sharing and open science.
Activity of Hippocampal Formation Neurons in the Monkey Related to a Conditional Spatial Response Task

SUMMARY AND CONCLUSIONS To analyze neurophysiologically the functions of the primate hippocampus, the activity of 905 single hippocampal formation neurons was analyzed in two rhesus monkeys performing a conditional spatial response task known to be impaired in monkeys and in man by damage to the hippocampus or fornix. In the task, the monkey learned to make one spatial response, touching a screen three times when he saw one visual stimulus on the video monitor, and a different spatial response, of withdrawing his hand from the screen, when a different visual stimulus was shown. Fourteen percent of the neurons fired differentially to one or the other of the stimulus-spatial response associations. The mean la-tency of these differential responses was 154 k 44 (SD) ms. The firing of these neurons was shown to reflect a combination of the particular stimulus and the particular response associated by learning in the stimulus-response association task and could not be accounted for by the motor requirements of the task, nor wholly the stimulus aspects of the task, as demonstrated by testing their firing in related visual discrimination tasks. Responsive neurons were found throughout the hippocampal formation, but were particularly concentrated in the subicular complex and the CA3 subfield. These results show that single hippocampal neurons respond to combinations of the visual stimuli and the spatial responses with which they must become associated in conditional spatial response tasks and are consistent with the suggestion that part of the mechanism of this learning involves associations between visual stimuli and spatial responses learned by single hippocampal neurons.
The biogenesis pathway of tRNA-derived piRNAs in Bombyx germ cells

Abstract Transfer RNAs (tRNAs) function in translational machinery and further serves as a source of short non-coding RNAs (ncRNAs). tRNA-derived ncRNAs show differential expression profiles and play roles in many biological processes beyond translation. Molecular mechanisms that shape and regulate their expression profiles are largely unknown. Here, we report the mechanism of biogenesis for tRNA-derived Piwi-interacting RNAs (td-piRNAs) expressed in Bombyx BmN4 cells. In the cells, two cytoplasmic tRNA species, tRNAAspGUC and tRNAHisGUG, served as major sources for td-piRNAs, which were derived from the 5′-part of the respective tRNAs. cP-RNA-seq identified the two tRNAs as major substrates for the 5′-tRNA halves as well, suggesting a previously uncharacterized link between 5′-tRNA halves and td-piRNAs. An increase in levels of the 5′-tRNA halves, induced by BmNSun2 knockdown, enhanced the td-piRNA expression levels without quantitative change in mature tRNAs, indicating that 5′-tRNA halves, not mature tRNAs, are the direct precursors for td-piRNAs. For the generation of tRNAHisGUG-derived piRNAs, BmThg1l-mediated nucleotide addition to −1 position of tRNAHisGUG was required, revealing an important function of BmThg1l in piRNA biogenesis. Our study advances the understanding of biogenesis mechanisms and the genesis of specific expression profiles for tRNA-derived ncRNAs.
Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV) function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks.
Can Pacing Be Regulated by Post-Activation Potentiation? Insights from a Self-Paced 30 km Trial in Half-Marathon Runners

Purpose Given the co-existence of post-activation potentiation (PAP) and fatigue within muscle, it is not known whether PAP could influence performance and pacing during distance running by moderating fatigue. The aim of this study was to assess the influence of PAP on pacing, jumping and other physiological measures during a self-paced 30 km trial. Methods Eleven male endurance-trained runners (half-marathon runners) volunteered to participate in this study. Runners participated in a multi-stage 30 km trial. Before the trial started, determination of baseline blood lactate (bLa) and countermovement jump (CMJ) height was performed. The self-paced 30 km trial consisted of 6 × 5 km splits. At the end of each 5 km split (60 s break), data on time to complete the split, CMJ height, Rating of Perceived Exertion (RPE) and blood lactate were collected while heart rate was continuously monitored. Results There was a significant decrease in speed (e.g. positive pacing strategy after the 4th split, p<0.05) with a progressive increase in RPE throughout the trial. Compared with baseline, CMJ height was significantly (p<0.05) greater than baseline and was maintained until the end of the trial with an increase after the 5th split, concomitant with a significant reduction in speed and an increase in RPE. Significant correlations were found between ΔCMJ and ΔSPEED (r = 0.77 to 0.87, p<0.05) at different time points as well as between RPE and speed (r = -0.61 to -0.82, p<0.05). Conclusion Our results indicates that fatigue and potentiation co-exist during long lasting endurance events, and that the observed increase in jump performance towards the end of the trial could be reflecting a greater potentiation potentially perhaps counteracting the effects of fatigue and preventing further reductions in speed.
Onomastics 2.0 - The Power of Social Co-Occurrences

Onomastics is "the science or study of the origin and forms of proper names of persons or places. " ["Onomastics". Merriam-Webster.com, 2013. this http URL (11 February 2013)]. Especially personal names play an important role in daily life, as all over the world future parents are facing the task of finding a suitable given name for their child. This choice is influenced by different factors, such as the social context, language, cultural background and, in particular, personal taste. With the rise of the Social Web and its applications, users more and more interact digitally and participate in the creation of heterogeneous, distributed, collaborative data collections. These sources of data also reflect current and new naming trends as well as new emerging interrelations among names. The present work shows, how basic approaches from the field of social network analysis and information retrieval can be applied for discovering relations among names, thus extending Onomastics by data mining techniques. The considered approach starts with building co-occurrence graphs relative to data from the Social Web, respectively for given names and city names. As a main result, correlations between semantically grounded similarities among names (e.g., geographical distance for city names) and structural graph based similarities are observed. The discovered relations among given names are the foundation of "nameling" [this http URL], a search engine and academic research platform for given names which attracted more than 30,000 users within four months, underpinningthe relevance of the proposed methodology.
Anti-hepatocellular carcinoma activity and mechanism of chemopreventive compounds: ursolic acid derivatives

Abstract Context: Hepatocellular carcinoma (HCC) is a common cancer around the world, with high mortality rate. Currently, there is no effective drug for the therapy of HCC. Ursolic acid (UA) is a natural product which exists in various medicinal herbs and fruits, exhibiting multiple biological effects such as its outstanding anticancer and hepatoprotective activity, which has drawn many pharmacists’ attention. Objective: This paper summarizes the current status of the hepatoprotective activity of UA analogues and explains the related mechanism, providing a clear direction for the development of novel anti-HCC drugs. Methods: All of the data resources were derived from PubMed. By comparing the IC50 values and analyzing the structure–activity relationships, we listed compounds with good pharmacological activity from the relevant literature, and summarized their anti-HCC mechanism. Results: From the database, 58 new UA derivatives possessing wonderful anticancer and hepatoprotective effects were listed, and the relevant anti-HCC mechanism were discussed. Conclusion: UA’s anti-HCC effect is the result of combined action of many mechanisms. These 58 new UA derivatives, particularly compounds 45 and 53, can be used as potential drugs for the treatment of liver cancer.
Phylogeography of the Recent Expansion of Helicoverpa armigera (Lepidoptera: Noctuidae) in South America and the Caribbean Basin

Abstract The Old World bollworm, Helicoverpa armigera (Hübner), is one of the most destructive agricultural pests worldwide. It was first recorded in Brazil in 2013, yet despite this recent introduction, H. armigera has spread throughout much of Latin America. Where H. armigera has become established, it is displacing or hybridizing with the congeneric New World pest Helicoverpa zea. In addition to the adaptive qualities that make H. armigera a megapest, such as broad range pesticide resistance, the spread of H. armigera in the New World may have been hastened by multiple introductions into South America and/or the Caribbean. The recent expansion of the range of H. armigera into the New World is analyzed herein using mtDNA of samples from South America, the Caribbean Basin, and the Florida Peninsula. Phylogeographic analyses reveal that several haplotypes are nearly ubiquitous throughout the New World and native range of H. armigera, but several haplotypes have limited geographic distribution from which a secondary introduction with Euro-African origins into the New World is inferred. In addition, host–haplotype correlations were analyzed to see whether haplotypes might be restricted to certain crops. No specialization was found; however, some haplotypes had a broader host range than others. These results suggest that the dispersal of H. armigera in the New World is occurring from both natural migration and human-mediated introductions. As such, both means of introduction should be monitored to prevent the spread of H. armigera into areas such as the United States, Mexico, and Canada, where it is not yet established.