Miracle-dz/UniFAR-FTUs huggingface dataset:
Experiments with a Venue-Centric Model for Personalisedand Time-Aware Venue Suggestion

Location-based social networks (LBSNs), such as Foursquare, fostered the emergence of new tasks such as recommending venues a user might wish to visit. In the literature, recommending venues has typically been addressed using user-centric recommendation approaches relying on collaborative filtering techniques. Such approaches not only require many users with detailed profiles to be effective, but they also cannot recommend venues to users who are not actually members of the LBSN. In contrast, in this paper, we introduce a venue-centric yet personalised probabilistic approach that suggests personalised and popular venues for users to visit in the near future. In our approach, we probabilistically incorporate two components, a popularity component for predicting the popularity of a venue at a given point in time, as estimated from the attendance of the venue in the LBSN (i.e. number of check-ins), and a personalisation component for identifying its interestingness with respect to the estimated preferences of the user. The popularity of each venue is predicted using time series forecasting models that are trained on the recent attendance trends of the venue, while the users' interests are modelled from the entity pages that they like on Facebook. Using three major cities, we conduct a user study to evaluate the effectiveness of the two components of our approach in suggesting venues for different types of users at different times of the day. Our experimental results show that an approach that combines the popularity and personalisation components is able to consistently outperform the recommendation service of the leading Foursquare LBSN. We also find that combining popularity and personalisation is effective for both new visitors and residents, while former visitors prefer popular venues.
Exploring Social Influence for Recommendation - A Probabilistic Generative Model Approach

In this paper, we propose a probabilistic generative model, called unified model, which naturally unifies the ideas of social influence, collaborative filtering and content-based methods for item recommendation. To address the issue of hidden social influence, we devise new algorithms to learn the model parameters of our proposal based on expectation maximization (EM). In addition to a single-machine version of our EM algorithm, we further devise a parallelized implementation on the Map-Reduce framework to process two large-scale datasets we collect. Moreover, we show that the social influence obtained from our generative models can be used for group recommendation. Finally, we conduct comprehensive experiments using the datasets crawled from last.fm and whrrl.com to validate our ideas. Experimental results show that the generative models with social influence significantly outperform those without incorporating social influence. The unified generative model proposed in this paper obtains the best performance. Moreover, our study on social influence finds that users in whrrl.com are more likely to get influenced by friends than those in last.fm. The experimental results also confirm that our social influence based group recommendation algorithm outperforms the state-of-the-art algorithms for group recommendation.
Pharmacogenetics of human ABC transporter ABCC11: new insights into apocrine gland growth and metabolite secretion

Cell secretion is an important physiological process that ensures smooth metabolic activities and tissue repair as well as growth and immunological functions in the body. Apocrine secretion occurs when the secretory process is accomplished with a partial loss of cell cytoplasm. The secretory materials are contained within secretory vesicles and are released during secretion as cytoplasmic fragments into the glandular lumen or interstitial space. The recent finding that the non-synonymous single nucleotide polymorphisms (SNP) 538G > A (rs17822931; Gly180Arg) in the ABCC11 gene determines the type of earwax in humans has shed light on the novel function of this ABC (ATP-binding cassette) transporter in apocrine glands. The wild-type (Gly180) of ABCC11 is associated with wet-type earwax, axillary osmidrosis, and colostrum secretion from the mammary gland as well as the potential risk of mastopathy. Furthermore, the SNP (538G > A) in the ABCC11 gene is suggested to be a clinical biomarker for the prediction of chemotherapeutic efficacy. The aim of this review article is to provide an overview on the discovery and characterization of genetic polymorphisms in the human ABCC11 gene and to explain the impact of ABCC11 538G > A on the apocrine phenotype as well as the anthropological aspect of this SNP in the ABCC11 gene and patients’ response to nucleoside-based chemotherapy.
Azithromycin, rifabutin, and rifapentine for treatment and prophylaxis of Mycobacterium avium complex in rats treated with cyclosporine

Azithromycin, rifabutin, and rifapentine were used to treat or prevent disseminated Mycobacterium avium complex (MAC) infections produced in rats immunosuppressed with cyclosporine. Animals with bacteremic infections were treated 1 week after intravenous inoculation with 10(7) CFU of MAC with azithromycin, 100 mg/kg of body weight administered subcutaneously for 5 days and then 75 mg/kg on Monday, Wednesday, and Friday, or with rifabutin or rifapentine, 20 mg/kg administered intraperitoneally on Monday through Friday. All three drugs showed efficacy after 1 and 2 months. Rifabutin cleared the organisms from tissues more rapidly than azithromycin or rifapentine. To approximate prophylaxis, treatment was started 2 weeks before intravenous inoculation with 10(4) organisms. MAC infections were undetectable in treated animals after 4 months, while control animals had disseminated infections. These findings support the rationale for clinical trials of treatment and prophylaxis with these agents. The cyclosporine-treated rat appears to be a useful model in which to evaluate compounds for the treatment and prophylaxis of disseminated MAC infections.
The relation of wood structure and strain energy release rate in fractured wood-glue composites

approved: Robert L. Krahmer Comprehending the anatomical nature of wood and its role in the resultant fracture of glued wood products stressed to failure is paramount in the full, advantageous use of both wood and adhesive in the production of the strongest possible products. Any relation of wood structure to a measure of fracture resistance, such as strain energy release rate (GIc), can only aid in the design of stronger and better wood-adhesive composites. A contoured double cantilever beam (CDCB) test specimen configuration, manufactured using Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) and phenol-formaldehyde adhesive bonds, is utilized and is shown to be an effective means for evaluating Ic The regions of crack arrest and initiation and the path of failure are described on an anatomical basis in specimens constructed with sawn and jointed surface preparations and RL and TL systems of crack propagationAn attempt is made to relate the path of failure to wood structure and GIc at three structural levels: macroscopic, microscopic, and ultrastructural. Redacted for Privacy Fracture initiation (GI) and arrest (GIa) energies showed no statistically significant responses (5% level) to modification in surface preparations or crack propagation systems. However, an interaction of these two production variables may exist and should be investigated further. Failure types and their relative occurrence (ranked from most common to least common) were wood failures of the intrawall, transwall parallel to the fiber axis, and transwall perpendicular to the fiber axis types; interphase failure; interface failure; and adhesive failure. These failures exhibited some similarities to failures reported for plywood and solid wood, although the frequency of intrawall failure was higher in this investigation. Wood-adhesive composite CDCB specimens generally exhibited higher G1c values than did solid wood CDCB specimens from the same material. Higher GIc values were generally characteristic of wood failure near the interface/interphase area in the better bonds, while lower values characterized wood failure away from this area or poor bonding. This trend of decreasing GIc with increasing distance from the bondline was more consistent for the TL system than the RL system fractures. The conclusion was made that a recognizable difference should be evident in the fracture path or location of the fracture initiation when GIc values differ greatly. There is a need for the development of improved methods for pinpointing the crack front location across the entire width of the test piece, which, at present, is not available for wood. A modification of the GIc equation based on strength of materials formulae, to account for multiple moduli of elasticity (E) is also recommended. THE RELATION OF WOOD STRUCTURE AND STRAIN ENERGY RELEASE RATE IN FRACTURED WOOD-GLUE COMPOSITES
A scheme for load balancing in heterogenous distributed hash tables

We present a scheme for evenly partitioning the key space in distributed hash tables among the participating nodes. The scheme is based on the multiple random choices paradigm [3, 19], and handles both node joins and leaves. It achieves, with high probability, a ratio of at most 4 between the loads of the most and least burdened nodes, in the face or arbitrary node arrivals and departures. Each join or leave operation incurs message cost that is, with high probability, Oh(log2n), where n is the number of nodes, and causes the relocation of keys from at most one node (for joins) or three nodes (for leaves). A version of our scheme is suitable for heterogeneous systems, where the capacities of nodes to serve keys can vary widely.
Getting to the heart of the matter

Case history A 57 year old man, previously fit, presented to rheumatology clinic in November 1995 with a five year history of flitting arthralgia of the knees, elbows, and shoulders. The rheumatoid factor was negative and C reactive protein (CRP) normal. The diagnosis was unclear but shoulder joint injections with corticosteroid by the family doctor had given temporary symptomatic relief. The following month he was assessed by a neurologist with complaints of continuous headache and episodic visual blurring. Examination and computed tomography of the brain were normal. Stress related anxiety was diagnosed. In May 1996 the patient was admitted to hospital with severe central chest pain. Electrocardiogram showed anterior ST increase consistent with a myocardial infarction and streptokinase was given. Subsequent coronary angiography was performed that showed normal coronary arteries and normal left ventricular function; coronary spasm was evoked as the mechanism for the presentation. The following month, June 1996, the patient was again admitted to hospital this time with complaints of lethargy, generalised headache, proximal myalgia but no stiffness or weakness, visual blurring, …
Scaling up Superoptimization

Developing a code optimizer is challenging, especially for new, idiosyncratic ISAs. Superoptimization can, in principle, discover machine-specific optimizations automatically by searching the space of all instruction sequences. If we can increase the size of code fragments a superoptimizer can optimize, we will be able to discover more optimizations. We develop LENS, a search algorithm that increases the size of code a superoptimizer can synthesize by rapidly pruning away invalid candidate programs. Pruning is achieved by selectively refining the abstraction under which candidates are considered equivalent, only in the promising part of the candidate space. LENS also uses a bidirectional search strategy to prune the candidate space from both forward and backward directions. These pruning strategies allow LENS to solve twice as many benchmarks as existing enumerative search algorithms, while LENS is about 11-times faster. Additionally, we increase the effective size of the superoptimized fragments by relaxing the correctness condition using contexts (surrounding code). Finally, we combine LENS with complementary search techniques into a cooperative superoptimizer, which exploits the stochastic search to make random jumps in a large candidate space, and a symbolic (SAT-solver-based) search to synthesize arbitrary constants. While existing superoptimizers consistently solve 9--16 out of 32 benchmarks, the cooperative superoptimizer solves 29 benchmarks. It can synthesize code fragments that are up to 82% faster than code generated by gcc -O3 from WiBench and MiBench.
mRNA localization to Pbodies in yeast is biphasic with many mRNAs captured in a late Bfr1pdependent wave

ABSTRACT The relocalization of translationally repressed mRNAs to mRNA processing bodies Pbodies is a key consequence of cellular stress across many systems. Pbodies harbor mRNA degradation components and are implicated in mRNA decay, but the relative timing and control of mRNA relocalization to Pbodies is poorly understood. We used the MS2GFP system to follow the movement of specific endogenous mRNAs in live Saccharomyces cerevisiae cells after nutritional stress. It appears that the relocalization of mRNA to Pbodies after stress is biphasic some mRNAs are present early, whereas others are recruited much later concomitant with recruitment of translation initiation factors, such as eIF4E. We also find that Bfr1p is a latephaselocalizing Pbody protein that is important for the delayed entry of certain mRNAS to Pbodies. Therefore, for the mRNAs tested, relocalization to Pbodies varies both in terms of the kinetics and factor requirements. This work highlights a potential new regulatory juncture in gene expression that would facilitate the overall rationalization of protein content required for adaptation to stress.
Lithium Batteries for Wireless Sensor Networks

Non-rechargeable batteries with a life of 20 years and more are required today for many smart metering and AMR applications in the US. Tadiran's non-rechargeable lithium thionyl chloride batteries offer a proven life of 25 years. Kohler's new touchless commercial faucet was designed to run even 30 years on a hybrid lithium battery. Similar requirements exist for wireless sensor networks. They can be achieved by diligent optimisation of the power source. This optimisation rests on three pillars: capacity increase, decrease of self discharge and the minimisation of voltage losses. When pulse currents of up to 2.5 Amperes are required Tadiran's PulsesPlusTM technology, combining a secondary high rate element (Hybrid Layer Capacitor, HLC) with a primary high energy cell (3.6 Volts, 1340 Wh / dm) is the system of choice. The icing on the cake: Tadiran's TLI battery is a high-end highpower rechargeable element for use in combination with energy harvesting devices or other electrical low power energy sources.
A physiological concentration of glucocorticoid inhibits the pro‐inflammatory cytokine‐induced proliferation of adult rat cardiac fibroblasts: Roles of extracellular signal‐regulated kinase 1/2 and nuclear factor‐κB

1. Inflammation‐induced proliferation of cardiac fibroblasts plays an important role in cardiac remodelling. Pharmacological doses of exogenous glucocorticoids (GC) are the most effective therapy for inflammatory diseases. Similarly, physiological concentrations of endogenous GC have recently been shown to have anti‐inflammatory effects. Therefore, the aim of the present study was to determine whether a physiological concentration of GC could inhibit pro‐inflammatory cytokine‐stimulated proliferation of cardiac fibroblasts and to explore the mechanisms involved.
Running agent-based models on a discrete-event simulator

One of the main obstacles hindering the use of large-scale agent-based simulation in practice is its scalability. The ability to run realistic and complex agent-based models is desirable to provide empirically and practically useful results. One of the suggested solutions is to run the agent-based models on top of a scalable parallel discrete-event simulation engine. This proposal raises a question whether an equivalent discrete-event model can be built for any agent-based model. This paper proves that an equivalent discrete-event model can be found for any agent-based model that conforms to a given specification. I show that a translator can be built to convert the agent-based model into an equivalent discrete-event model automatically and transparently. The advantage of this approach is that modellers do not need to change their modelling paradigm and at the same time a highly scalable parallel discrete-event simulator can be used to run the model.
On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning

We address the problem of finding the maximizer of a nonlinear function that can only be evaluated, subject to noise, at a finite number of query locations. Further, we will assume that there is a constraint on the total number of permitted function evaluations. We introduce a Bayesian approach for this problem and show that it empirically outperforms both the existing frequentist counterpart and other Bayesian optimization methods. The Bayesian approach places emphasis on detailed modelling, including the modelling of correlations among the arms. As a result, it can perform well in situations where the number of arms is much larger than the number of allowed function evaluation, whereas the frequentist counterpart is inapplicable. This feature enables us to develop and deploy practical applications, such as automatic machine learning toolboxes. The paper presents comprehensive comparisons of the proposed approach with many Bayesian and bandit optimization techniques, the first comparison of many of these methods in the literature.
Graphical Models for Utility Elicitation

This paper deals with preference representation and elicitation in the context of multiattribute utility theory under risk. Assuming the decision maker behaves according to the EU model, we investigate the elicitation of generalized additively decomposable utility functions on a product set (GAI-decomposable utilities). We propose a general elicitation procedure based on a new graphical model called a GAI-network. The latter is used to represent and manage independences between attributes, as junction graphs model independences between random variables in Bayesian networks. It is used to design an elicitation questionnaire based on simple lotteries involving completely specified outcomes. Our elicitation procedure is convenient for any GAIdecomposable utility function, thus enhancing the possibilities offered by UCP-networks.
Evaluation of a human immunodeficiency virus test algorithm utilizing a recombinant protein enzyme immunoassay

Many truly human immunodeficiency virus (HIV) antibody-negative serum samples may be unnecessarily subjected to costly and time-consuming Western blots (immunoblots). An investigation was undertaken to evaluate the efficiency of using a recombinant protein-based enzyme immunosorbent assay (EIA; Cambridge BioScience [CBC] Recombigen HIV EIA) as an adjunct to whole viral lysate EIA. A total of 2,212 serum samples which had been screened by viral lysate EIA were tested by CBC EIA in parallel with the Western blot. The sensitivity and specificity of the CBC kit were 99.9 and 99.7%, respectively. Positive and negative predictive values were 99.7 and 99.9%, respectively. The high sensitivity of this kit and its high negative predictive value make it an attractive addition to an HIV testing algorithm by reducing the number of Western blot tests on truly antibody negative serum samples.
Influence of actuator size and location on robust stability of actively controlled flexible beams

Abstract This paper addresses the influence of the actuator size on the closed loop stability of collocated and non-collocated transfer functions utilized in the structural control of flexible beams. Besides the well known robustness advantages of collocated transfer functions it is shown, that if the actuator is small compared to the flexible structure, a non-collocated actuator/sensor configuration provides larger stability margins. It is shown, that this effect arises from the uncertainty associated with the steady state gain of collocated transfer functions. The applicability to other types of boundary conditions and limitations due to length and spatial frequencies of the beam are also addressed.
Comparison of four methods for the biofunctionalization of gold nanorods by the introduction of sulfhydryl groups to antibodies

Introducing sulfhydryl groups to biomolecules to functionalize gold nanorods (GNRs) is an attractive method that involves the creation of a strong Au–S bond. Previously, we developed a facile method to functionalize GNR surfaces by thiolating antibodies using Traut’s reagent. In the current study, we evaluated several methods for the introduction of thiol groups onto the surface of GNRs by using Traut’s reagent, dithiotreitol (DTT), dithiolaromatic PEG6-CONHNH2, and thiol-polyethylene glycolamine (SH-PEG-NH2) combined with EDC reaction. We showed that the four above-mentioned thiolation methods can efficiently functionalize GNRs and simplify the functionalization procedures. The formed GNR-bioconjugates showed superior stability without compromising the biological activity. The GNR nanochip prepared with these four thiolated antibodies can detect human IgG targets with specificity. However, SH-PEG-NH2 combined with EDC reaction may affect the amount of functionalized GNRs because of the efficiency of thiol moiety linkage to antibodies, thereby affecting the sensitivity of the GNR sensor. The introduction of a thiol group to antibodies by using Traut’s reagent, DTT, and PEG6-CONHNH2 allowed for direct immobilization onto the GNR surface, improved the efficacy of functionalized GNRs, and increased the sensitivity in response to target detection as a biosensor. Given that PEG6-CONHNH2 modification requires glycosylated biomolecules, Traut’s reagent and DTT thiolation are recommended as universal applications of GNR biofunctionalization and can be easily extended to other sensing applications based on other gold nanostructures or new biomolecules.