Miracle-dz/UniFAR-FTUs huggingface dataset:
An optimization method for train driving trajectory in urban rail systems

In urban rail systems, the kinetic energy of trains can be converted into electrical energy when the train applies regenerative braking. The converted energy is called recovery energy that can be transmitted backward to the power supply network for accelerating nearby trains. The previous studies in using recovery energy focus on optimizing timetable to synchronize the traction and braking times of trains. Instead of optimizing timetable, this paper develops a train trajectory optimization model to minimize the net energy consumption by improving the efficiency of recovery energy utilization. A genetic algorithm(GA) is used to find the optimal train trajectory. Finally, we present a numerical example based on Beijing Yizhuang subway line data to illustrate the effectiveness of the developed model on energy saving.
A Proof of Strong Normalization for F 2 , F ! and Beyond

We present an evaluation technique for proving strong normalization (SN). We use the technique to give SN proofs for F 2 , F-bounded quantiication, subtypes, and F ! The evaluation technique derives SN as a corollary of the soundness of the typing rules under an appropriate evaluation semantics. The evaluation semantics yields simpler type sets than those used in the earlier SN proofs. The type sets discussed here form a complete lattice under classical union and intersection. The simpliied type sets allow a simpliied treatment of a variety of type constructors.
Multisite tyrosine phosphorylation of the N‐terminus of Mint1/X11α by Src kinase regulates the trafficking of amyloid precursor protein

Mint/X11 is one of the four neuronal trafficking adaptors that interact with amyloid precursor protein (APP) and are linked with its cleavage to generate β‐amyloid peptide, a key player in the pathology of Alzheimer's disease. How APP switches between adaptors at different stages of the secretory pathway is poorly understood. Here, we show that tyrosine phosphorylation of Mint1 regulates the destination of APP. A canonical SH2‐binding motif (202YEEI) was identified in the N‐terminus of Mint1 that is phosphorylated on tyrosine by C‐Src and recruits the active kinase for sequential phosphorylation of further tyrosines (Y191 and Y187). A single Y202F mutation in the Mint1 N‐terminus inhibits C‐Src binding and tyrosine phosphorylation. Previous studies observed that co‐expression of wild‐type Mint1 and APP causes accumulation of APP in the trans‐Golgi. Unphosphorylatable Mint1 (Y202F) or pharmacological inhibition of Src reduced the accumulation of APP in the trans‐Golgi of heterologous cells. A similar result was observed in cultured rat hippocampal neurons where Mint1(Y202F) permitted the trafficking of APP to more distal neurites than the wild‐type protein. These data underline the importance of the tyrosine phosphorylation of Mint1 as a critical switch for determining the destination of APP.
A supported psychoeducational intervention to improve family mental health following discharge from paediatric intensive care: feasibility and pilot randomised controlled trial

Objective To assess feasibility and pilot a supported psychoeducational tool to improve parent and child mental health following discharge from a paediatric intensive care unit (PICU), in preparation for a large randomised controlled trial (RCT). Design Feasibility assessment and single-centre, parallel group, pilot RCT. A concealed computer generated list was used to randomise participants, with an allocation of 2:1 in favour of the intervention. Setting A PICU in an acute care hospital in London, UK. Participants 31 parents of children aged 4–16 years-old admitted to PICU. Intervention Parents received a psychoeducational tool supported by a telephone call. The psychoeducational tool outlined the possible psychological reactions in children and parents alongside management advice. The telephone call addressed each family's postdischarge experience, reinforced the psychoeducational material and encouraged parents to put into practice the advice given. Main outcome measures The primary outcome was the number of feasibility criteria successfully met (linked to the intervention and the study design). Secondary outcomes were questionnaire data collected at 3–6-month follow-up assessing mental health in parents and children. Results 31 parents were randomised (intervention n=22; treatment as usual, TAU n=9). 23 parents were included in the analysis of secondary outcomes (intervention n=17; TAU n=6). 3 (of 6) intervention and 1 (of 6) study design feasibility criteria were fully met. All unmet criteria could be addressed with minor or significant modifications to the protocol. At follow-up there was a tendency for parents who received the intervention to report lower post-traumatic stress symptoms in themselves and fewer emotional and behavioural difficulties in their children than TAU parents. This needs to be explored in a fully powered trial. Conclusions This feasibility and pilot RCT provided valuable information on the intervention and trial design for a full RCT. Trials registration number NCT01737021; Results.
Predicting bacterial growth conditions from bacterial physiology

Bacterial physiology reflects the environmental conditions of growth. A widely studied problem in systems biology is to predict bacterial phenotype from growth conditions, using mechanistic models such as flux balance analysis (FBA). However, the inverse prediction of growth conditions from phenotype is rarely considered. Here we develop a computational framework to carry out this inverse prediction on a computational model of bacterial physiology. We use FBA to calculate bacterial phenotypes from growth conditions in E. coli, and then we assess how accurately we can predict the original growth conditions from the phenotypes. Prediction is carried out via regularized multinomial regression. Our analysis provides several important physiological and statistical insights. First, we show that by analyzing metabolic end products we can consistently predict growth conditions. Second, prediction is reliable even in the presence of small amounts of impurities. Third, flux through a relatively small number of reactions per growth source (∼10) is sufficient for accurate prediction. Fourth, combining the predictions from two separate models, one trained only on carbon sources and one only on nitrogen sources, performs better than models trained to perform joint prediction. Finally, that separate predictions perform better than a more sophisticated joint prediction scheme suggests that carbon and nitrogen utilization pathways, despite jointly affecting cellular growth, may be fairly decoupled in terms of their dependence on specific assortments of molecular precursors. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi. org/10.1101/002287 doi: bioRxiv preprint first posted online Jan. 31, 2014;
Relating cell and tissue mechanics: Implications and applications

The Differential Adhesion Hypothesis (DAH) posits that differences in adhesion provide the driving force for morphogenetic processes. A manifestation of differential adhesion is tissue liquidity and a measure for it is tissue surface tension. In terms of this property, DAH correctly predicts global developmental tissue patterns. However, it provides little information on how these patterns arise from the movement and shape changes of cells. We provide strong qualitative and quantitative support for tissue liquidity both in true developmental context and in vitro assays. We follow the movement and characteristic shape changes of individual cells in the course of specific tissue rearrangements leading to liquid‐like configurations. Finally, we relate the measurable tissue‐liquid properties to molecular entities, whose direct determination under realistic three‐dimensional culture conditions is not possible. Our findings confirm the usefulness of tissue liquidity and provide the scientific underpinning for a novel tissue engineering technology. Developmental Dynamics 237:2438–2449, 2008. © 2008 Wiley‐Liss, Inc.
A hybrid approach with collaborative filtering for recommender systems

The proliferation of powerful smart devices is revolutionizing mobile computing systems. A particular set of applications that is gaining wide interest is recommender systems. Recommender systems provide their users with recommendations on variety of personal and relevant items or activities. They can play a significant role in today's life whether in E-commerce or for daily decisions that we need to make. We introduce a hybrid approach for solving the problem of finding the ratings of unrated items in a user-item ranking matrix through a weighted combination of user-based and item-based collaborative filtering. The proposed technique provides improvements in addressing two major challenges of recommender systems: accuracy of recommender systems and sparsity of data by simultaneously incorporating users' correlations and items ones. The evaluation of the system shows superiority of the solution compared to stand-alone user-based collaborative filtering or item-based collaborative filtering.
BPR implementation process: an analysis of key success and failure factors

This paper provides a holistic view of the Business Process Re‐engineering (BPR) implementation process. It reviews the literature relating to the hard and soft factors that cause success and failure for BPR implementation, classifies these factors into subgroups, and identifies key factors of success and failure. Finally, it explains how these factors influence the process of BPR implementation.
Intracellular cyclic AMP not calcium, determines the direction of vesicle movement in melanophores: direct measurement by fluorescence ratio imaging

Intracellular movement of vesiculated pigment granules in angelfish melanophores is regulated by a signalling pathway that triggers kinesin and dyneinlike microtubule motor proteins. We have tested the relative importance of intracellular Ca2+ ([Ca2+]i) vs cAMP ([cAMP]i) in the control of such motility by adrenergic agonists, using fluorescence ratio imaging and many ways to artificially stimulate or suppress signals in these pathways. Fura-2 imaging reported a [Ca2+]i elevation accompanying pigment aggregation, but this increase was not essential since movement was not induced with the calcium ionophore, ionomycin, nor was movement blocked when the increases were suppressed by withdrawal of extracellular Ca2+ or loading of intracellular BAPTA. The phosphatase inhibitor, okadaic acid, blocked aggregation and induced dispersion at concentrations that suggested that the protein phosphatase PP-1 or PP-2A was continuously turning phosphate over during intracellular motility. cAMP was monitored dynamically in single living cells by microinjecting cAMP-dependent kinase in which the catalytic and regulatory subunits were labeled with fluorescein and rhodamine respectively (Adams et al., 1991. Nature (Lond.). 349:694- 697). Ratio imaging of F1CRhR showed that the alpha 2-adrenergic receptor-mediated aggregation was accompanied by a dose-dependent decrease in [cAMP]i. The decrease in [cAMP]i was both necessary and sufficient for aggregation, since cAMP analogs or microinjected free catalytic subunit of A kinase-blocked aggregation or caused dispersal, whereas the cAMP antagonist RpcAMPs or the microinjection of the specific kinase inhibitor PKI5-24 amide induced aggregation. Our conclusion that cAMP, not calcium, controls bidirectional microtubule dependent motility in melanophores might be relevant to other instances of non-muscle cell motility.
Behavioral Economics: Where Is It Heading?

The addition of “behavioral” to economics has given rise to a highly successful field of research. But, is it just a fashionable new trend or is it here to stay? More to the point, how does it differ from its close relative psychology? To answer these questions, the present article considers what behavioral economics is, and where it started, with the aim of trying to forecast what the status of it will be in the future. In forecasting where behavioral economics might be heading, the argument proposed here is that the best clues can be found in psychological research. If, as has been proposed here, behavioral economics partners research trends in psychology, then the futures of both will almost certainly be moving in the same direction. Both are beginning to, and will start to rely on online tools/mobile phone applications to collect richer data revealing dynamic tends over long time horizons, and as technology continues to facilitate ways of looking at group behaviour online, then larger scale studies examining interactions amongst multiple groups of people will become the norm rather than the exception. More specifically this article speculates on the future research focus of researchers in behavioral economics and the extent to which this will overlap with psychological research on judgment and decision-making.
A Scalable Implementation of Malware Detection Based on Network Connection Behaviors

When hundreds of thousands of applications need to be analyzed within a short period of time, existing static and dynamic malware detection methods may become less desirable because they could quickly exhaust system and human resources. Additionally, many behavioral malware detection methods may not be practical because they require the collection of applications' system-level and network-level activities, which may not always be available. In this paper, we propose a malware behavioral clustering approach to detect malware variants based on applications' simple network connection data, which can be easily collected from anti-virus (AV) products. This approach is highly scalable and has been used on huge volumes of real-world data. Our experiments demonstrate that, at a false positive rate lower than 0.001%, the proposed method achieved a detection rate of 80%+ in identifying spambots and achieved a 50%+ detection rate on average when detecting 3 popular malware families. In addition, the proposed method was deployed in a real environment and it detected malware instances more than one week earlier on average than two other leading AV products.
Modeling and analysis of an innovative waste heat recovery system for helicopters

The efficiency of helicopters is limited due to the high power losses of combustion engines, a fraction of which can be recovered and provided to the electrical bus by exploiting the heat found in the exhaust gases and through power electronics converters. The first system recovers energy through a thermoelectric generator, whereas the second through a permanent magnet generator rotated by a steam turbine. A third power converter, connected to a supercapacitor bank, compensates the peak currents demanded by the loads. Since extensive simulations have to be run in order to validate the feasibility of those systems, average models of the power converters are derived, and their accuracy is examined. Finally, based on those average models, the developed control strategy is examined.
Generation of a novel mouse model for the inducible depletion of macrophages in vivo

Macrophages play an essential role in tissue homeostasis, innate immunity, inflammation, and wound repair. Macrophages are also essential during development, severely limiting the use of mouse models in which these cells have been constitutively deleted. Consequently, we have developed a transgenic model of inducible macrophage depletion in which macrophage‐specific induction of the cytotoxic diphtheria toxin A chain (DTA) is achieved by administration of doxycycline. Induction of the DTA protein in transgenic animals resulted in a significant 50% reduction in CD68+ macrophages of the liver, spleen, and bone over a period of 6 weeks. Pertinently, the macrophages remaining after doxycycline treatment were substantially smaller and are functionally impaired as shown by reduced inflammatory cytokine production in response to lipopolysaccharide. This inducible model of macrophage depletion can now be utilized to determine the role of macrophages in both development and animal models of chronic inflammatory diseases. genesis 51:41‐49, 2013. © 2012 Wiley Periodicals, Inc.
MRI reconstruction from partial k-space data by iterative stationary wavelet transform thresholding

One approach to accelerating data acquisition in magnetic resonance imaging is acquisition of partial k-space data and recovery of missing data based on the sparsity of the image in the wavelet transform domain. We hypothesize that the application of stationary wavelet transform (SWT) thresholding as a sparsity-promoting operation results in improved artifact removal performance in comparison with the regular decimated wavelet transform (DWT). On this grounds, we develop an iterative SWT thresholding reconstruction. We demonstrate that an acceleration factor of 3 can be achieved using this approach on a human brain scan while only suffering a 9.61% penalty in signal to noise ratio without compromising the spatial resolution of the image.
Southern Cross University ePublications @ SCU Southern Cross Business School 2009 Incentives to export for Australian export market ventures

This study examines the impact that various incentives to export have on the export marketing performance of Australian export market ventures. The incentives to export used in this study were adapted from Sullivan and Bauerschmidt (1990). The unit of analysis was Australian export market ventures engaged in exporting to foreign markets. Data were gathered via a self-administered mail survey directed to the Managing Director of 694 Australian export market ventures identified by a government department as being involved in exporting. The findings indicate that the only export incentive that was a significant antecedent of export marketing performance was the chance to diversify into new markets.
Combining translation and language model scoring for domain-specific data filtering

The increasing popularity of statistical machine translation (SMT) systems is introducing new domains of translation that need to be tackled. As many resources are already available, domain adaptation methods can be applied to utilize these recourses in the most beneficial way for the new domain. We explore adaptation via filtering, using the crossentropy scores to discard irrelevant sentences. We focus on filtering for two important components of an SMT system, namely the language model (LM) and the translation model (TM). Previous work has already applied LM cross-entropy based scoring for filtering. We argue that LM cross-entropy might be appropriate for LM filtering, but not as much for TM filtering. We develop a novel filtering approach based on a combined TM and LM cross-entropy scores. We experiment with two large-scale translation tasks, the Arabicto-English and English-to-French IWSLT 2011 TED Talks MT tasks. For LM filtering, we achieve strong perplexity improvements which carry over to the translation quality with improvements up to +0.4% BLEU. For TM filtering, the combined method achieves small but consistent improvements over the standalone methods. As a side effect of adaptation via filtering, the fully fledged SMT system vocabulary size and phrase table size are reduced by a factor of at least 2 while up to +0.6% BLEU improvement is observed.
Example-based performance driven facial shape animation

A novel performance driven facial shape animation method is presented for mapping the expressions from the source face to the target face automatically. Unlike the prior expression cloning approaches, the proposed method aims to animate a new target face with the help of real facial expression samples. The basic idea is to learn the shape deformation from samples for target face to generate corresponding expressions. The process consists of two main stages. First of all, source motion vectors are transferred by statistic face model to generate a reasonable expression on the target face. And then, local deformation constraints are proposed to refine the animation results. In the second part, the local deformation characters for each target organ are learned from the samples, which preserve the personality as well as the expression styles. Experimental results on different facial animation demonstrate the feasibility and effectiveness of the proposed method.
HLA class II susceptibility to multiple sclerosis among Ashkenazi and non-Ashkenazi Jews.

OBJECTIVE To look for HLA class II alleles and haplotypes conferring susceptibility to multiple sclerosis (MS) in the Jewish population of Israel. DESIGN Population-based cohort of clinically definite patients with MS tested prospectively over 7 years. SETTING Referral center in a neurology clinic at a university hospital in the greater Jerusalem area in Israel. PATIENTS A total of 162 consecutive patients with clinically definite MS from the 2 main ethnic Jewish groups in Israel: 104 Ashkenazi (80 with a relapsing remitting or secondary progressive and 24 with a primary chronic progressive course of the disease) and 58 non-Ashkenazi (36 with a relapsing remitting or secondary progressive course and 22 with a primary chronic progressive course of the disease), matched with 132 Ashkenazi and 120 non-Ashkenazi healthy controls. MAIN OUTCOME MEASURES The relationship between the various HLA class II alleles and haplotypes and MS, as defined by the polymerase chain reaction and sequence-specific oligonucleotide probe hybridization, among the Ashkenazi and the non-Ashkenazi Jewish sections and with respect to the different clinical courses of the disease. RESULTS The haplotype DRB1*1501, DQA1*0102, DQB1*0602 was found to be associated with MS among both Ashkenazi and non-Ashkenazi patients (P<.001 and P =.04, respectively). Among the non-Ashkenazi patients, a new association of haplotypes DRB1*1303, DQA1*05, and DQB1*030 with MS was detected (P = .03). The MS susceptibility alleles, DRB 1* 1501, DQA1*0102, and DQB1*0602 , were found in association with the Ashkenazi patients (P<.001, P=.02, and P=.01, respectively); DRB1*1501 and DRB1*1303 were more frequently observed among the non-Ashkenazi patients (P = .03, P = .04, respectively). On subdivision of the patients into clinical subgroups, associations of DRB1*0801, DQA1*0102, DQA1*0401, and DQB1*0602 with primary chronic progressive MS among the Ashkenazi patients were evident (P = .03, P = .04, P = .04 and P = .05, respectively), whereas DRB1* 1501, DRB1*03011, and DQB1*0602 were associated with relapsing remitting or secondary progressive among the non-Ashkenazi patients (P = .05, P = .05, and P = .03, respectively). CONCLUSIONS This study, unlike previous ones, is the first to show a significant association between HLA class II alleles and MS in the Jewish population. The association with the HLA-DR2-related haplotype is similar to that among non-Jewish white patients with MS. Moreover, our data support the possibility that DRB1*1501 is the susceptibility allele responsible for the association between this haplotype and MS in the Jewish population. Our study also underscores differences in HLA profiles between Ashkenazi and non-Ashkenazi patients, and between the different clinical courses of the disease. The latter may indicate that the clinical courses of MS are influenced by the genetic background.