Miracle-dz/UniFAR-FTUs huggingface dataset:
Early network failure detection system by analyzing Twitter data

Mobile network failures have occurred many times in recent years. Some network failures become “silent” failures that mobile carriers cannot detect because of incomplete rules concerning failure detection by the network operating system. However, the increasing number of services and devices, and the increasing complexity of the network make it hard to generate rules that cover all network failures. Therefore, monitoring the network performance from a subscriber's perspective is very important. The traditional way to obtain feedback from subscribers is to use call centers and email. However, it is difficult to detect problems early or in their entirety through those channels because subscribers typically do not call a call center until they are certain the problem was caused by a network. In this paper, we discuss a way to monitor a social networking service (SNS) (Twitter in particular) to find out about problems that affect subscribers. A previous study showed the possibility of early detection of network problems by monitoring Twitter. However, since Twitter includes many conversation topics, it is difficult to find tweets that relate to network problems. Searching by a particular keyword is insufficient since it produces a lot of false positive results that contain the keyword but not the topic of the network problem. We solved this problem by using machine learning to suppress the false positive results. We implemented and evaluated a system to detect network failures from Twitter. As a result, we were able to identify 6 out of 6 large network problems and to suppress the number of false positives to only 6 events, whereas keyword matching detected 94 false positive events. Some of the problems were detected faster than through a call center. Furthermore, we conducted research in order to determine the appropriate machine learning algorithm, parameters, and volume of training data. We also propose a method to estimate the location where the tweeters were located.
Older adults' medication management in the home: How can robots help?

Successful management of medications is critical to maintaining healthy and independent living for older adults. However, medication non-adherence is a common problem with a high risk for severe consequences [5], which can jeopardize older adults' chances to age in place [1]. Well-designed robots assisting with medication management tasks could support older adults' independence. Design of successful robots will be enhanced through understanding concerns, attitudes, and preferences for medication assistance tasks. We assessed older adults' reactions to medication hand-off from a mobile manipulator with 12 participants (68-79 years). We identified factors that affected their attitudes toward a mobile manipulator for supporting general medication management tasks in the home. The older adults were open to robot assistance; however, their preferences varied depending on the nature of the medication management task. For instance, they preferred a robot (over a human) to remind them to take medications, but preferred human assistance for deciding what medication to take and for administering the medication. Factors such as perceptions of one's own capability and robot reliability ifluenced their attitudes.
The Guanine-Nucleotide Exchange Factor SGEF Plays a Crucial Role in the Formation of Atherosclerosis

The passage of leukocytes across the endothelium and into arterial walls is a critical step in the development of atherosclerosis. Previously, we showed in vitro that the RhoG guanine nucleotide exchange factor SGEF (Arhgef26) contributes to the formation of ICAM-1-induced endothelial docking structures that facilitate leukocyte transendothelial migration. To further explore the in vivo role of this protein during inflammation, we generated SGEF-deficient mice. When crossed with ApoE null mice and fed a Western diet, mice lacking SGEF showed a significant decrease in the formation of atherosclerosis in multiple aortic areas. A fluorescent biosensor revealed local activation of RhoG around bead-clustered ICAM-1 in mouse aortic endothelial cells. Notably, this activation was decreased in cells from SGEF-deficient aortas compared to wild type. In addition, scanning electron microscopy of intimal surfaces of SGEF−/− mouse aortas revealed reduced docking structures around beads that were coated with ICAM-1 antibody. Similarly, under conditions of flow, these beads adhered less stably to the luminal surface of carotid arteries from SGEF −/− mice. Taken together, these results show for the first time that a Rho-GEF, namely SGEF, contributes to the formation of atherosclerosis by promoting endothelial docking structures and thereby retention of leukocytes at athero-prone sites of inflammation experiencing high shear flow. SGEF may therefore provide a novel therapeutic target for inhibiting the development of atherosclerosis.
A novel artificial nerve graft for repairing long-distance sciatic nerve defects: a self-assembling peptide nanofiber scaffold-containing poly(lactic-co-glycolic acid) conduit

In this study, we developed a novel artificial nerve graft termed self-assembling peptide nanofiber scaffold (SAPNS)-containing poly(lactic-co-glycolic acid) (PLGA) conduit (SPC) and used it to bridge a 10-mm-long sciatic nerve defect in the rat. Retrograde tracing, behavioral testing and histomorphometric analyses showed that compared with the empty PLGA conduit implantation group, the SPC implantation group had a larger number of growing and extending axons, a markedly increased diameter of regenerated axons and a greater thickness of the myelin sheath in the conduit. Furthermore, there was an increase in the size of the neuromuscular junction and myofiber diameter in the target muscle. These findings suggest that the novel artificial SPC nerve graft can promote axonal regeneration and remyelination in the transected peripheral nerve and can be used for repairing peripheral nerve injury.
PTAS for maximum weight independent set problem with random weights in bounded degree graphs

Finding the largest independent set in a graph is a notoriously difficult N P-complete combinatorial optimization problem. Moreover, even for graphs with largest degree 3, no polynomial time approximation algorithm exists with a 1.0071-factor approximation guarantee, unless P = N P [BK98]. We consider the related problem of finding the maximum weight independent set in a bounded degree graph, when the node weights are generated i.i. d. from a common distribution. Surprisingly, we discover that the problem becomes tractable for certain distributions. Specifically, we construct a randomized PTAS (Polynomial-Time Approximation Scheme) for the case of exponentially distributed weights and arbitrary graphs with degree at most 3. We extend our result to graphs with larger constant degrees but for distributions which are mixtures of exponential distributions. At the same time, we prove that no PTAS exists for computing the expected size of the maximum weight independent set in the case of exponentially distributed weights for graphs with sufficiently large constant degree, unless P=NP. Our algorithm, cavity expansion, is new and is based on the combination of several powerful ideas, including recent deterministic approximation algorithms for counting on graphs and local weak convergence/correlation decay methods.
On the Efficiency of Random Walk Routing in Multihop Wireless Network

In this paper, we propose a novel routing metric, namely biased delivery probability (BDP), for measuring the wireless node's capacity of forwarding data packet to the destination. BDP essentially assigns different weights to the multipaths information associated with different hop counts. An theoretical theory is established to compute the weights for different scenarios. Using BDP routing metric, we design a prioritized random walk routing (PRR) protocol for multihop wireless network, which incorporates random network coding strategy, and can force the coded packet only randomly "walk" through the higher priority node set, instead of randomly encountered nodes. In such a way, it provides a loop-free random walk forwarding and guarantees the packets consequently go through the right "direction" step by step to the destination. Extensive simulation results show that the PRR protocol can dramatically improve the network performance over existing forwarding scheme, in terms of the throughputs, the end to end delay and the number of transmissions.
Shine: search heterogeneous interrelated entities

Heterogeneous entities or objects are very common and are usually interrelated with each other in many scenarios. For example, typical Web search activities involve multiple types of interrelated entities such as end users, Web pages, and search queries. In this paper, we define and study a novel problem: <UL>S</UL>earch <UL>H</UL>eterogeneous <UL>IN</UL>terrelated <UL>E</UL>ntities (SHINE). Given a SHINE-query which can be any type(s) of entities, the task of SHINE is to retrieve multiple types of related entities to answer this query. This is in contrast to the traditional search,which only deals with a single type of entities (e.g., Web pages). The advantages of SHINE include: (1) It is feasible for end users to specify their information need along different dimensions by accepting queries with different types. (2) Answering a query by multiple types of entities provides informative context for users to better understand the search results and facilitate their information exploration. (3) Multiple relations among heterogeneous entities can be utilized to improve the ranking of any particular type of entities. To attain the goal of SHINE, we propose to represent all entities in a unified space through utilizing their interaction relationships. Two approaches, M-LSA and E-VSM, are discussed and compared in this paper. The experiments on 3 data sets (i.e., a literature data set, a search engine log data set, and a recommendation data set) show the effectiveness and flexibility of our proposed methods.
Synthesis, Characterization and Improvement of a Dye Sensitized Solar Cell

Because of its light weight, low cost, flexibility and easy production techniques, Dye Sensitized Solar Cells (DSSCs) have become one of the promising PV-technologies for the future. Even though the DSSCs have been researched for over 20 years, the efficiencies reported are low compared to the commercial PV-cells of today, and further improvements have to be accomplished before DSSCs become a competitive technology. In this work DSSCs have been, for the first time, fabricated in its entirety at Western Norway University of Applied Sciences (HVL). As the synthesis of nanomaterials for the DSSCs and fabrication of DSSC are done for the first time locally, a large part of the work has been attributed to thoroughly document the procedure in the synthesis and fabrication processes. Variety of nanomaterial characterizations are done at UiB and the IV characterization of the fabricated DSSCs are done at HVL. The primary objective of this study is to establish a fabrication process for the DSSCs. In this study, a microwave-assisted method for synthesizing the semiconductor TiO2 nanostructures is applied, because this method reduces the synthesis time with up to 12 hours, compared to conventional methods like hydrothermal and sol-gel. XRD characterization of the nanostructures of TiO2 synthesized with the microwave-assisted method has revealed the desired anatase phase. The DSSCs produced with the same experimental procedure gave a range of different efficiencies, with the highest being (4.365±0.007)%. Even though the DSSCs fabricated in this study did not give the desired reproducibility through various tests and processes, the basic procedures for fabrication of DSSC have been established. The reason for lack of reproducibility is probably complex, but it is the author’s viewpoint that the contributing factor is the technique used to paste the active TiO2 layer to the conductive glass, referred to as the doctor blade-technique. This coating is done manually and is difficult to standardize. An attempt has been done to standardize the procedures and suggestions are given for further improvements. As part of the desire to increase the efficiencies of the DSSCs, attempts are made to dope TiO2 with Fluorine and Nitrogen. Characterization of both the Nitrogen and Fluorine doped TiO2 samples show indication of doping, but this process needs further optimization. Studies carried out in this master project provides a foundation for further research on the synthesis of TiO2 based nanostructures with and without doping with external atoms, and fabrication techniques for DSSCs necessary for reproducibility and to enhance the efficiencies of DSSCs.
The primary structure of staphylococcal enterotoxin B. 3. The cyanogen bromide peptides of reduced and aminoethylated enterotoxin B, and the complete amino acid sequence.

Abstract Cyanogen bromide treatment of reduced, aminoethylated enterotoxin B yielded seven major peptides plus homoserine and homoserine lactone, as was expected from the number of methionine residues present in the enterotoxin B molecule. The cyanogen bromide peptides were fractionated on Sephadex G-50 and further purified by rechromatography on Sephadex G-50 or paper electrophoresis at pH 1.9. They contained a total of 239 amino acid residues. Tryptic peptides of each of the cyanogen bromide peptides were purified and their amino acid composition was determined. The order of these peptides in each cyanogen bromide peptide and the order of the cyanogen bromide peptides in enterotoxin B were established. Based on the information from tryptic, chymotryptic, and cyanogen bromide peptides, the complete amino acid sequence of enterotoxin B was established. Staphylococcal enterotoxin B is a single polypeptide chain containing 239 amino acid residues.
Assessing Sexual Attitudes and Behaviors of Young Women: A Joint Model with Nonlinear Time Effects, Time Varying Covariates, and Dropouts

Understanding human sexual behaviors is essential for the effective prevention of sexually transmitted infections (STI). Analysis of longitudinally measured sexual behavioral data, however, is often complicated by zero-inflation of event counts, nonlinear time trend, time-varying covariates, and informative dropouts. Ignoring these complicating factors could undermine the validity of the study findings. In this article, we put forth a unified joint modeling structure that accommodates these features of the data. Specifically, we propose a pair of simultaneous models for the zero-inflated event counts: Each of these models contains an auto-regressive structure for the accommodation of the effect of recent event history, and a nonparametric component for the modeling of nonlinear time effect. Informative dropout and time varying covariates are modeled explicitly in the process. Model fitting and parameter estimation are carried out in a Bayesian paradigm by the use of a Markov chain Monte Carlo (MCMC) method. Analytical results showed that adolescent sexual behaviors tended to evolve nonlinearly over time, and they were strongly influenced by the day-to-day variations in mood and sexual interests. These findings suggest that adolescent sex is, to a large extent, driven by intrinsic factors rather than being compelled by circumstances, thus highlighting the need of education on self-protective measures against infection risks.
Beyond proliferation: KLF5 promotes angiogenesis of bladder cancer through directly regulating VEGFA transcription

Abundant evidence has demonstrated critical roles of KLF5 in regulating cell proliferation in various cancers, however, its additional roles in other aspects of cancer development remain to be further clarified. In this study, we found that KLF5 was essential for cancer cell-endothelial cell interaction in vitro and tumor angiogenesis in nude mice based on lentivirus-mediated KLF5 knockdown bladder cancer cell models. Moreover, KLF5 insufficiency abolished the ability of bladder cancer cells to induce neovascularization in rabbit cornea. Mechanistically, the pro-angiogenic factor VEGFA was identified as a direct downstream target of KLF5, which bound to GC-boxes and CACCC elements of VEGFA promoter and regulated its transcriptional activity. In addition, there was a positive correlation between KLF5 and VEGFA expression in human bladder cancer tissues by immunohistochemistry assay and statistical analysis from TCGA and GEO data. Furthermore, we found that two pivotal pathways in bladder cancer, RTKs/RAS/MAPK and PI3K/Akt, might convey their oncogenic signaling through KLF5-VEGFA axis. Taken together, our results indicate that KLF5 promotes angiogenesis of bladder cancer through directly regulating VEGFA transcription and suggest that KLF5 could be a novel therapeutic target for angiogenesis inhibition in bladder cancer.
Assessment of advanced thermal management systems for micro-hybrid trucks and heavy duty diesel vehicles

Advanced thermal management systems (ATMS) have the potential to increase the life of the vehiclepsilas engine and cooling system components as well as decrease fuel consumption and carbon emissions. This paper presents for the first time, an overview of several ATMS topologies and provides a critical assessment as to their power saving potential. Four systems have been modeled using a 1-D simulation tool to study the steady state energy flows in a vehicle operating with a constant duty cycle. The simulation results are used to determine the cooling system power consumption and the effect on fuel economy of the vehicle. It has been observed that a full electric cooling system is not viable for a vehicle with a low voltage electrical system.
Imaging sialylated tumor cell glycans in vivo

Cell surface glycans are involved in numerous physiological processes that involve cell‐cell interactions and migration, including lymphocyte trafficking and cancer metastasis. We have used a bioorthogonal metabolic labeling strategy to detect cell surface glycans and demonstrate, for the first time, fluorescence and radionuclide imaging of sialylated glycans in a murine tumor model in vivo. Peracetylated azido‐labeled N‐acetyl‐man‐nosamine, injected intraperitoneally, was used as the metabolic precursor for the biosynthesis of 5‐azidoneuraminic, or azidosialic acid. Azidosialic acid‐labeled cell surface glycans were then reacted, by Staudinger ligation, with a biotinylated phosphine injected intraperitoneally, and the biotin was detected by subsequent intravenous injection of a fluorescent or radiolabeled avidin derivative. At 24 h after administration of NeutrAvidin, labeled with either a far‐red fluorophore or 111In, there was a significant azido‐labeled N‐acetyl‐mannosamine‐dependent increase in tumor‐to‐tissue contrast, which was detected using optical imaging or single‐photon‐emission computed tomography (SPECT), respectively. The technique has the potential to translate to the clinic, where, given the prognostic relevance of altered sialic acid expression in cancer, it could be used to monitor disease progression. —Neves, A. A. , Stöckmann, H. , Harmston, R. R. , Pryor, H. J., Alam, I. S. , Ireland‐Zecchini, H. , Lewis, D. Y. , Lyons, S. K. , Leeper, F. J., Brindle, K. M. Imaging sialylated tumor cell glycans in vivo. FASEB J. 25, 2528–2537 (2011). www.fasebj. org
The Transcriptional Control of Lymphatic Vascular Development More than 100 years

More than 100 years ago, Florence Sabin suggested that lymphatic vessels develop by sprouting from preexisting blood vessels, but it is only over the past decade that the molecular mechanisms underpinning lymphatic vascular development have begun to be elucidated. Genetic manipulations in mice have identified a transcriptional hub comprised of Prox1, CoupTFII, and Sox18 that is essential for lymphatic endothelial cell fate specification. Recent work has identified a number of additional transcription factors that regulate later stages of lymphatic vessel differentiation and maturation. This review highlights recent advances in our understanding of the transcriptional control of lymphatic vascular development and reflects on efforts to better understand the activities of transcriptional networks during this discrete developmental process. Finally, we highlight the transcription factors associated with human lymphatic vascular disorders, demonstrating the importance of understanding how the activity of these key molecules is regulated, with a view toward the development of innovative therapeutic avenues. Mathias Francois, Natasha L. Harvey, and Benjamin M. Hogan Division of Molecular Genetics and Development, Institute for Molecular Bioscience, University of Queensland, Brisbane; Division of Haematology, Centre for Cancer Biology, SA Pathology, Adelaide; and School of Medicine, University of Adelaide, Adelaide, Australia m.francois@imb.uq. edu.au b.hogan@imb.uq. edu.au
Suppression of cellular immunity by surgical stress.

BACKGROUND Suppression of cellular immunity is one of the host responses to surgical stress. In cancer patients this immunosuppression may accelerate the growth and metastasis of residual cancer cells, so it is desirable to restrict immunosuppression by surgical stress to a minimum. However, the extent and duration of immunosuppression caused by operations on gastrointestinal cancer, as well as the mechanisms involved, have not been determined. METHODS To clarify these points, we investigated immunocyte function and measured the blood levels of hormones, cytokines, and acute phase reactants from before to after operation in 20 patients with stage I gastrointestinal cancer. RESULTS In patients exposed to surgical stress, peripheral blood lymphocyte numbers and function were suppressed until at least 2 weeks postoperatively. This immunosuppression was mainly due to a decrease of helper-inducer T cells, cytotoxic T cells, natural killer cells, and interleukin-2 receptor-positive cells, as well as an increase of suppressor T cells. In addition, hypersecretion of cortisol and overproduction of immunosuppressive acidic protein were observed. CONCLUSIONS Cellular immunosuppression by surgical stress was mainly due to an increase of lymphocyte subsets that depress cellular immunity coupled with a decrease of the subsets that promote it. Overproduction of cortisol and immunosuppressive acidic protein in response to surgical stress may play an important role in the development of immunosuppression.
Molding CNNs for text: non-linear, non-consecutive convolutions

The success of deep learning often derives from well-chosen operational building blocks. In this work, we revise the temporal convolution operation in CNNs to better adapt it to text processing. Instead of concatenating word representations, we appeal to tensor algebra and use low-rank n-gram tensors to directly exploit interactions between words already at the convolution stage. Moreover, we extend the n-gram convolution to non-consecutive words to recognize patterns with intervening words. Through a combination of low-rank tensors, and pattern weighting, we can efficiently evaluate the resulting convolution operation via dynamic programming. We test the resulting architecture on standard sentiment classification and news categorization tasks. Our model achieves state-of-the-art performance both in terms of accuracy and training speed. For instance, we obtain 51.2% accuracy on the fine-grained sentiment classification task.