Miracle-dz/UniFAR-FTUs huggingface dataset:
Nuclear and cytoplasmic c‐Ski differently modulate cellular functions

c‐Ski is a proto‐oncogene product that induces morphologic transformation, anchorage independence, and myogenic differentiation when it is over‐expressed in mesenchymal cells. c‐Ski also inhibits signaling of transforming growth factor‐β (TGF‐β) superfamily members through interaction with Smad proteins. Although c‐Ski is predominantly localized in the nucleus, aberrant cytoplasmic localization of it has also been reported in some tumor tissues and cell lines. In the present study, we identified the nuclear localization signal (NLS) in c‐Ski. By introducing a mutation to abolish NLS activity, we examined the function of cytoplasmic c‐Ski. Although cytoplasmic c‐Ski suppressed TGF‐β superfamily‐induced Smad signaling through sequestration of activated Smad complex to the cytoplasm, it failed to exhibit some of the activities that require nuclear localization of c‐Ski, including suppression of basal transcription of the Smad7 gene. These findings indicate that subcellular localization of c‐Ski affects its biologic activities. We also found that c‐Ski accumulated in the cytoplasm when proteasome activity was inhibited. Mapping of the regions required for cytoplasmic accumulation by proteasome inhibitors suggests that subcellular localization of c‐Ski may be regulated by proteasome‐sensitive processes through amino acid residues 94–210 and 491–548.
Reliable and Load Balanced Multi-path Routing for Multiple Sinks in Wireless Sensor Networks

Wireless Sensor Networks, the existing techniques for sink deployment consider load balancing and multipath routing. But the fault detection and recovery of sinks are rarely considered. In this paper, we propose to develop a Fault detection and recovery mechanism for multiple sinks. The nodes are grouped into clusters based on the data generation rate and multiple sinks are deployed in the clusters in which the data generation rate is more. An energy efficient multi path tree is constructed towards the sink and the aggregated data from the sensors are transmitted to their nearest sinks through this multi path tree. The rate adjustment value and the inter arrival delay of each path is calculated and sent back as a feedback to the source to by the respective sinks. Then the path with the minimum feedback value is chosen as the best path for transmission. When a failure occurs in a sink, then it can be detected based on delay and remaining energy. Once the fault sink is detected, then the data is transferred to another sink or the sinks are deployed again. From our simulation results, we show that an efficient load balanced multi path routing for multiple sinks is obtained and the fault detection and recovery can be made effectively.
Matching pursuit and atomic signal models based on recursive filter banks

The matching pursuit algorithm can be used to derive signal decompositions in terms of the elements of a dictionary of time-frequency atoms. Using a structured overcomplete dictionary yields a signal model that is both parametric and signal adaptive. In this paper, we apply matching pursuit to the derivation of signal expansions based on damped sinusoids. It is shown that expansions in terms of complex damped sinusoids can be efficiently derived using simple recursive filter banks. We discuss a subspace extension of the pursuit algorithm that provides a framework for deriving real-valued expansions of real signals based on such complex atoms. Furthermore, we consider symmetric and asymmetric two-sided atoms constructed from underlying one-sided damped sinusoids. The primary concern is the application of this approach to the modeling of signals with transient behavior such as music; it is shown that time-frequency atoms based on damped sinusoids are more suitable for representing transients than symmetric Gabor atoms. The resulting atomic models are useful for signal coding and analysis modification synthesis.
Risk Prediction Model for Heart Failure and Cardiomyopathy After Adjuvant Trastuzumab Therapy for Breast Cancer

Background Adjuvant trastuzumab improves survival for women with human epidermal growth factor receptor 2‐positive breast cancer, but increases risk for heart failure (HF) and cardiomyopathy (CM). However, clinical trials may underestimate HF/CM risk because they enroll younger subjects with fewer cardiac risk factors. We sought to develop a clinical risk score that identifies older women with breast cancer who are at higher risk of HF or CM after trastuzumab. Methods and Results Using the Surveillance, Epidemiology and End Results (SEER)‐Medicare database, we identified women with breast cancer who received adjuvant trastuzumab. Using a split‐sample design, we used a proportional hazards model to identify candidate predictors of HF/CM in a derivation cohort. A risk score was constructed using regression coefficients, and HF/CM rates were calculated in the validation cohort. The sample consisted of 1664 older women (mean age 73.6 years) with 3‐year HF/CM rate of 19.1%. A risk score consisting of age, adjuvant chemotherapy, coronary artery disease, atrial fibrillation or flutter, diabetes mellitus, hypertension, and renal failure was able to classify HF/CM risk into low (0 to 3 points), medium (4 to 5 points), and high (≥6 points) risk strata with 3‐year rates of 16.2%, 26.0%, and 39.5%, respectively. Conclusions A 7‐factor risk score was able to stratify 3‐year risk of HF/CM after trastuzumab between the lowest and highest risk groups by more than 2‐fold in a Medicare population. These findings will inform future research aimed at further developing a clinical risk score for HF/CM for breast cancer patients of all ages.
Experimental and theoretical study of polarization-dependent optical transitions in InAs quantum dots at telecommunication-wavelengths (1300-1500 nm)

The design of some optical devices, such as semiconductor optical amplifiers for telecommunication applications, requires polarization-insensitive optical emission at long wavelengths (1300–1550 nm). Self-assembled InAs/GaAs quantum dots (QDs) typically exhibit ground state optical emissions at wavelengths shorter than 1300 nm with highly polarization-sensitive characteristics, although this can be modified by the use of low growth rates, the incorporation of strain-reducing capping layers, or the growth of closely-stacked QD layers. Exploiting the strain interactions between closely stacked QD layers also affords greater freedom in the choice of growth conditions for the upper layers, so that both a significant extension in their emission wavelength and an improved polarization response can be achieved due to modification of the QD size, strain, and composition. In this paper, we investigate the polarization behavior of single and stacked QD layers using room temperature sub-lasing-threshold electrolumin.
F1‐catalysed ATP hydrolysis is required for mitochondrial biogenesis in Saccharomyces cerevisiae growing under conditions where it cannot respire

Mutant strains of yeast Saccharomyces cerevisiae lacking a functional F1‐ATPase were found to grow very poorly under anaerobic conditions. A single amino acid replacement (K222 > E222) that locally disrupts the adenine nucleotide catalytic site in the β‐F1 subunit was sufficient to compromise anaerobic growth. This mutation also affected growth in aerated conditions when ethidium bromide (an intercalating agent impairing mtDNA propagation) or antimycin (an inhibitor of respiration) was included in the medium. F1‐deficient cells forced to grow in oxygen‐limited conditions were shown to lose their mtDNA completely and to accumulate Hsp60p mainly under its precursor form. Fluorescence microscopy analyses with a modified GFP containing a mitochondrial targeting presequence revealed that aerobically growing F1‐deficient cells stopped importing the GFP when antimycin was added to the medium. Finally, after total inactivation of the catalytic α3β3 subcomplex of F1, mitochondria could no longer be energized by externally added ATP because of either a block in assembly or local disruption of the adenine nucleotide processing site. Altogether these data strengthen the notion that in the absence of respiration, and whether the proton translocating domain (F0) of complex V is present or not, F1‐catalysed hydrolysis of ATP is essential for the occurrence of vital cellular processes depending on the maintenance of an electrochemical potential across the mitochondrial inner membrane.
Geo-located community detection in Twitter with enhanced fast-greedy optimization of modularity: the case study of typhoon Haiyan

As they increase in popularity, social media are regarded as important sources of information on geographical phenomena. Studies have also shown that people rely on social media to communicate during disasters and emergency situation, and that the exchanged messages can be used to get an insight into the situation. Spatial data mining techniques are one way to extract relevant information from social media. In this article, our aim is to contribute to this field by investigating how graph clustering can be applied to support the detection of geo-located communities in Twitter in disaster situations. For this purpose, we have enhanced the fast-greedy optimization of modularity (FGM) clustering algorithm with semantic similarity so that it can deal with the complex social graphs extracted from Twitter. Then, we have coupled the enhanced FGM with the varied density-based spatial clustering of applications with noise spatial clustering algorithm to obtain spatial clusters at different temporal snapshots. The method was experimented with a case study on typhoon Haiyan in the Philippines, and Twitter’s different interaction modes were compared to create the graph of users and to detect communities. The experiments show that communities that are relevant to identify areas where disaster-related incidents were reported can be extracted, and that the enhanced algorithm outperforms the generic one in this task.
3-Ishwarone and 3-Ishwarol, rare sesquiterpenes in essential oil from leaves of Peperomia oreophila Hensch.

The essential oil from Peperomia oreophila leaves (Piperaceae) was submitted to fractionation in silica gel column. This separation procedure yielded a fraction composed of a hydrocarbon sesquiterpene mixture which was identified as b-elemene, a-ylangene, a-guaiene and b-selinene. Besides, spathulenol and two sesquiterpenes with the rare ishwarane skeleton: 3-ishwarol and 3-ishwarone were also identified. 3-ishwarone was the major component of the crude oil (78% weight). Since the alcohol obtained was not sufficient to allow a complete structural determination, the original ketone was reduced to 3-ishwarol in order to give additional quantities. After the two sesquiterpenes purification, they were characterized by spectrometric techniques (1H-1H COSY, HMQC, HMBC and NOESY).
Camdoop: Exploiting In-network Aggregation for Big Data Applications

Large companies like Facebook, Google, and Microsoft as well as a number of small and medium enterprises daily process massive amounts of data in batch jobs and in real time applications. This generates high network traffic, which is hard to support using traditional, oversubscribed, network infrastructures. To address this issue, several novel network topologies have been proposed, aiming at increasing the bandwidth available in enterprise clusters. We observe that in many of the commonly used workloads, data is aggregated during the process and the output size is a fraction of the input size. This motivated us to explore a different point in the design space. Instead of increasing the bandwidth, we focus on decreasing the traffic by pushing aggregation from the edge into the network. We built Camdoop, a MapReduce-like system running on CamCube, a cluster design that uses a direct-connect network topology with servers directly linked to other servers. Camdoop exploits the property that CamCube servers forward traffic to perform in-network aggregation of data during the shuffle phase. Camdoop supports the same functions used in MapReduce and is compatible with existing MapReduce applications. We demonstrate that, in common cases, Camdoop significantly reduces the network traffic and provides high performance increase over a version of Camdoop running over a switch and against two production systems, Hadoop and Dryad/DryadLINQ.
The pharmacokinetics and effects on blood pressure of multiple doses of the novel anti-migraine drug zolmitriptan (311C90) in healthy volunteers.

AIMS Zolmitriptan (311C90), a novel, selective, centrally and peripherally acting 5-HT1D-receptor agonist is under development as an acute treatment for migraine. The tolerability, pharmacokinetics and effects on blood pressure and heart rate of multiple doses of 5 or 10 mg (5 doses administered over 24 h) were compared, in healthy adult volunteers, with those after placebo and single doses of zolmitriptan. METHODS Twelve subjects participated in a randomized, balanced, crossover comparison. Plasma and urine concentrations of zolmitriptan and its metabolites, pulse rate and blood pressure were measured at intervals after drug. Ten volunteers completed the study. RESULTS Zolmitriptan was well tolerated after single and multiple doses throughout the study. There was no evidence of significant changes in the pharmacokinetic parameters of zomitriptan or its metabolites after the last dose compared to the first, except for an expected rise in peak concentrations and a small, apparent increase in the amount of drug excreted in urine and hence in CLR. After the last 10 mg dose, mean dosing interval zolmitriptan AUC was 80.3 ng ml-1 h compared with 86.5 ng ml-1 h after the single 10 mg dose (95% CI for ratio 0.76-1.13). There was no evidence of changes in the pharmacokinetic parameters of zolmitriptan and its metabolites after 10 mg compared with 5 mg, except a small increase in zolmitriptan CLR. There were no statistically significant increases in peak systolic or diastolic blood pressure after the last doses of zolmitriptan compared to placebo or in peak blood pressure after the last dose compared to the first. There were no significant differences between blood pressure immediately before the first and last doses of each multiple dose regimen. Peak erect systolic blood pressure after the last 10 mg dose (137 mmHg) was significantly lower than that after placebo (147 mmHg, 95% CI for difference -18, -2) and that after the last 5 mg dose (148 mmHg, 95% CI -19, -3). CONCLUSIONS Repeated doses of 5 or 10 mg zolmitriptan are well tolerated despite higher plasma concentrations than expected from single doses.
Analysis of drug combinations: current methodological landscape

Combination therapies exploit the chances for better efficacy, decreased toxicity, and reduced development of drug resistance and owing to these advantages, have become a standard for the treatment of several diseases and continue to represent a promising approach in indications of unmet medical need. In this context, studying the effects of a combination of drugs in order to provide evidence of a significant superiority compared to the single agents is of particular interest. Research in this field has resulted in a large number of papers and revealed several issues. Here, we propose an overview of the current methodological landscape concerning the study of combination effects. First, we aim to provide the minimal set of mathematical and pharmacological concepts necessary to understand the most commonly used approaches, divided into effect‐based approaches and dose–effect‐based approaches, and introduced in light of their respective practical advantages and limitations. Then, we discuss six main common methodological issues that scientists have to face at each step of the development of new combination therapies. In particular, in the absence of a reference methodology suitable for all biomedical situations, the analysis of drug combinations should benefit from a collective, appropriate, and rigorous application of the concepts and methods reviewed here.
Evaluation of Mouse Oocyte In Vitro Maturation Developmental Competency in Dynamic Culture Systems by Design and Construction of A Lab on A Chip Device and Its Comparison with Conventional Culture System

Objective In conventional assisted reproductive technology (ART), oocytes are cultured in static microdrops within Petri dishes that contain vast amounts of media. However, the in vivo environment is dynamic. This study assesses in vitro oocyte maturation through the use of a new microfluidic device. We evaluate oocyte fertilization to the blastocyct stage and their glutathione (GSH) contents in each experimental group. Materials and Methods In this experimental study, we established a dynamic culture condition. Immature oocytes were harvested from ovaries of Naval Medical Research Institute (NMRI) mice. Oocytes were randomly placed in static (passive) and dynamic (active) in vitro maturation (IVM) culture medium for 24 hours. In vitro matured oocytes underwent fertilization, after which we placed the pronucleus (PN) stage embryos in microdrops and followed their developmental stages to blastocyst formation after 3 days. GSH content of the in vitro matured oocytes was assessed by monochlorobimane (MCB) staining. Results We observed significantly higher percentages of mature metaphase II oocytes (MII) in the passive and active dynamic culture systems (DCS) compared to the static group (P<0.01). There were significantly less mean numbers of germinal vesicle (GV) and degenerated oocytes in the passive and active dynamic groups compared to the static group (P<0.01). Fertilization and blastocyst formation rate in the dynamic systems were statistically significant compared to the static cultures (P<0.01). There was significantly higher GSH content in dynamically matured oocytes compared to statically matured oocytes (P<0.01). Conclusion Dynamic culture for in vitro oocyte maturation improves their developmental competency in comparison with static culture conditions.
Editor's Comments: The Craft of Writing Theory Articles—Variety and Similarity in AMR

Over the years, a host of articles and editorial commentaries in this journal and elsewhere have been written with the aim of helping management scholars understand (1) what theory is and (2) how to develop better (i.e., more novel, useful, and interesting) theory (e.g., Bacharach, 1989; Kilduff, 2006; LePine & King, 2010; Suddaby, 2010; Sutton & Staw, 1995; Thompson, 2011; Weick, 1989; Whetten, 1989). However, it is also worth remembering that journals don’t publish big ideas; they publish manuscripts where authors have successfully communicated their big ideas in such a way that they can be readily understood and evaluated by others (Daft, 1995; Kilduff, 2006; King & Lepak, 2011). As the mission statement for this journal notes, “AMR publishes novel, insightful, and carefully crafted conceptual work” (emphasis mine). Of course, a necessary part of the crafting is in the conceptualization of good theory, but equally important is structuring the paper well. To use an analogy, the organization of a manuscript (i.e., “macrostructure”; Daft, 1995) and the quality of the writing therein are like a window. A manuscript’s window is “dirty” when its organization is awkward, unclear, or a poor fit with the concepts being explained, or when the writing is sloppy. The effect is to distract the reader by causing him or her to focus on the window (the poor structure), rather than to look through it to the underlying message. In early rounds of the journal review process, editors and reviewers all too often have to advise authors to clean up their paper (e.g., streamline the writing, coordinate the text with the figures, add or reword propositions) before they can begin to actually evaluate the merits of any theoretical contribution. And that is if the authors are lucky; confusing structure or poor writing may so dominate a manuscript that it diminishes any perceived potential theoretical contribution the paper might have, leading to a first-round rejection. Although in reality the two are often inextricably connected (Van Maanen, 1995), in this essay I focus on the window—that is, on the craft of constructing a theory paper—rather than on the process of generating theory per se. And while there is much to be said about grammar, sentence structure, language usage, and specifics of writing technique (what Daft calls “microstructure”), I mostly focus on issues of manuscript organization and presentation, including the title and abstract, headings and sections, the use (or nonuse) of formal propositions, and the use of tables and figures. In a recent editorial essay King and Lepak recommended that aspiring authors “outline or map out the structure of exemplar articles and then customize the learning gained in this process to come up with new and more effective approaches for communicating fundamentally good ideas” (2011: 209). Modeling this approach, I use AMR Best Articles from the last ten years (published 2001 through 2010) to illustrate both the structural variety and the similarities in articles published in AMR.
The Lazy Learning Toolbox. For Use with Matlab

Lazy learning is a memory-based technique that, once a query is received , extracts a prediction interpolating locally the neighboring examples of the query which are considered relevant according to a distance measure. This toolbox implements a data-driven method to select on a query-by-query basis the optimal number of neighbors to be considered for each prediction. As an eecient way to identify and validate local models , the recursive least squares algorithm is adopted. Furthermore, beside the winner-takes-all strategy for model selection, the toolbox implements also a local combination, performed on a query-by-query basis, of the most promising models. This manual describes the functions included in the toolbox as well as the algorithms implemented and the underlying theory.
Wireless Sensor Network

The history of sensor network technology originates in the first distributed sensing idea implementations. The continuous work of researchers and engineers over sensor networks which lately became wireless sensor networks (WSNs). Wireless sensor network is one of the g r o wi n g technology for sensing and performing the different tasks. Such networks are beneficial in many fields, such as emergencies, health monitoring, environmental control, military, industries and these networks prone to mali-cious users' and physical attacks due to radio range of network, un-trusted transmission, unattended nature and get access easily. Security is a fundamental requirement for these networks. In this paper, our center of attention is on physical attacks and issues in wireless sensor networks. Through this review, easily identify the purpose and capabilities of the attackers. Further, we discuss well-known approaches of security detection against physical attacks. The template is used to format your paper and style the text. All margins, column widths, line spaces, and text fonts are prescribed; please do not alter them.