Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the children's views on foods and consumption of selected food groups: outcome from focus group approach

The food choices in childhood have high a probability of being carried through into their adulthood life, which then contributes to the risk of many non-communicable diseases. Therefore, there is a need to gather some information about children's views on foods which may influence their food choices for planning a related dietary intervention or programme. This paper aimed to explore the views of children on foods and the types of foods which are usually consumed by children under four food groups (snacks, fast foods, cereals and cereal products; and milk and dairy products) by using focus group discussions. A total of 33 school children aged 7-9 years old from Selangor and Kuala Lumpur participated in the focus groups. Focus groups were audio-taped, transcribed and analyzed according to the listed themes. The outcomes show that the children usually consumed snacks such as white bread with spread or as a sandwich, local cakes, fruits such as papaya, mango and watermelon, biscuits or cookies, tea, chocolate drink and instant noodles. Their choices of fast foods included pizza, burgers, French fries and fried chicken. For cereal products, they usually consumed rice, bread and ready-to-eat cereals. Finally, their choices of dairy products included milk, cheese and yogurt. The reasons for the food liking were taste, nutritional value and the characteristics of food. The outcome of this study may provide additional information on the food choices among Malaysian children, especially in urban areas with regard to the food groups which have shown to have a relationship with the risk of childhood obesity.
LagOver: Latency Gradated Overlays

We propose a new genre of overlay network for disseminating information from popular but resource constrained sources. We call this communication primitive as latency gradated overlay, where information consumers self- organize themselves according to their individual resource constraints and the latency they are willing to tolerate in receiving the information from the source. Such a communication primitive finds immediate use in applications like RSS feeds aggregation. We propose heuristic algorithms to construct LagOver based on preferably some partial knowledge of the network at users (no knowledge slows the construction process) but no global coordination. The algorithms are evaluated based on simulations and show good characteristics including convergence, satisfying peers' latency and bandwidth constraints even in presence of moderately high membership dynamics. There are two points worth noting. First, optimizing jointly for latency and capacity (i.e., placing nodes that have free capacity close to the source) as long as latency constraint of other nodes are not violated performs better than optimizing for latency only. The joint optimization strategy has faster convergence of the LagOver network, and can deal with adversarial workloads that optimization of only latency can not deal with. Secondly, somewhat counter-intuitively, in order to do the aforementioned joint optimization, it is sufficient to find random nodes based on only the latency constraint, since even if the capacity of individual nodes is saturated it does not matter since the LagOver network can potentially be reconfigured.
Combining semantic and syntactic document classifiers to improve first story detection

In this paper we describe a type of data fusion involving the combination of evidence derived from multiple document representations. Our aim is to investigate if a composite representation can improve the online detection of novel events in a stream of broadcast news stories. This classification process otherwise known as first story detection FSD (or in the Topic Detection and Tracking pilot study as online new event detection [1]), is one of three main classification tasks defined by the TDT initiative. Our composite document representation consists of a semantic representation (based on the lexical chains derived from a text) and a syntactic representation (using proper nouns). Using the TDT1 evaluation methodology, we evaluate a number of document representation combinations using these document classifiers.
International Union of Pharmacology. XII. Classification of opioid receptors.

Facing the rapidly spreading novel coronavirus disease (COVID-19), evidence to inform decision-making at both the clinical and policy-making level is highly needed. Based on the results of a study by Petrilli et al, we have developed a calculator using patient data at admission to predict the risk of critical illness (intensive care unit admission, use of mechanical ventilation, discharge to hospice, or death). We report a retrospective validation of the risk calculator on 145 consecutive patients admitted with COVID-19 to a single hospital in Israel. Of the 18 patients with critical illness, 17 were correctly identified by the model(sensitivity: 94.4%, 95% CI, 72.7% to 99.9%; specificity: 81.9%, 95% CI, 74.1% to 88.2%). Of the 127 patients with non-critical illness, 104 were correctly identified. This, despite considerable differences between the original and validation study populations. Our results show that data from published knowledge can be used to provide reliable, patient level, automated risk assessment, potentially reducing the cognitive burden on physicians and helping policy makers better prepare for future needs.
Analysis model for measuring information flow in social networks

Recently, as the need to advertise using social networks has increased, viral marketing has become one of the most effective approaches used to spread information, in a virus-like manner, to a large number of people. This approach is able to match customers and products more efficiently than when using traditional marketing approaches. However, the complex social structure of the digital network means it is difficult to assess the actual performance of such information sharing. This paper proposes the use of an analysis model in order to measure information flows across social networks. Many factors affect the performance of information flows across social networks, as they depend, not only on the number of communications required to reach the target audience, but also on the individual and social parameters used by the target audience, such as the number of friends who may be interested in the target product and their preferences. This study assesses the importance of those parameters affecting customer product awareness.
Simulation of Tribosystems and Tribometrology

Modelling and simulation are more and more upcoming tools in various fields in engineering. Most tasks request specialization in terms of the technical background as well as of the mathematical methods used. In this paper an overview is given about some commonly available software tools for simulation with respect to the specific conditions in the field of tribology as an interdisciplinary subject. Aspects of geometry, material characteristics and chemical processes have to be considered. The combination resp. integration of different simulation aims is currently a very interesting task. The focus on processes in the nano domain led to new highly specific simulation tools like molecular dynamics, which enables the simulation of complex tribological processes. Some examples of modelling and simulation are given based on research projects as the are currently running or have been recently finished at the Austrian Center of Competence for Tribology: Targets of these works are problems concerning stresses in tribocontacts, behaviour of lubricants and thermal situations of sliding elements.
Multiple Objectives in Portfolio Selection

We begin this paper by first comparing the theory of present-day portfolio selection, which is a theory for standard investors (whose utility functions take on only the single argument of portfolio return), with a developing theory for non-standard investors (whose utility functions are allowed to take on additional arguments). Examples of additional arguments are dividends, liquidity, social responsibility, amount of short selling, and so forth. Then, with portfolio selection for non-standard investors taking on the form of a multi-objective stochastic programming problem, equivalent deterministic formulations involving more than mean and variance are explored. With the nondominated sets of nonstandard investors no longer frontiers, but now surfaces, the tools and techniques that must be imported from multiple criteria optimization to compute and analyze them are next discussed. The paper concludes with a list of research topics that are candidates for extending the multiple criteria portfolio selection material of this paper.
= 4 SYM to two loops: compact expressions for the non-compact symmetry algebra of the (1,1|2) sector

We begin a study of higher-loop corrections to the dilatation generator of = 4 SYM in non-compact sectors. In these sectors, the dilatation generator contains infinitely many interactions, and therefore one expects very complicated higher-loop corrections. Remarkably, we find a short and simple expression for the two-loop dilatation generator. Our solution for the non-compact (1,1|2) sector consists of nested commutators of four (g1) generators and one simple auxiliary generator. Moreover, the solution does not require the planar limit; we conjecture that it is valid for any gauge group. To obtain the two-loop dilatation generator, we find the complete (g3) symmetry algebra for this sector, which is also given by concise expressions. We check our solution using published results of direct field theory calculations. By applying the expression for the two-loop dilatation generator to compute selected anomalous dimensions and the bosonic (2) sector internal S-matrix, we confirm recent conjectures of the higher-loop Bethe ansatz of hep-th/0412188.
An Intelligent Car Park Management System based on Wireless Sensor Networks

Wireless sensor networks (WSNs) have attracted increasing attentions from both academic and industrial communities. It can be deployed in various kinds of environments to monitor and collect information. In this paper, we describe a WSN-based intelligent car parking system. In the system, low-cost wireless sensors are deployed into a car park field, with each parking lot equipped with one sensor node, which detects and monitors the occupation of the parking lot. The status of the parking field detected by sensor nodes is reported periodically to a database via the deployed wireless sensor network and its gateway. The database can be accessed by the upper layer management system to perform various management functions, such as finding vacant parking lots, auto-toll, security management, and statistic report. We have implemented a prototype of the system using crossbow motes. The system evaluation demonstrates the effectiveness of our design and implementation of the car parking system
One-sided communication for high performance computing applications

Parallel programming presents a number of critical challenges to application developers. Traditionally, message passing, in which a process explicitly sends data and another explicitly receives the data, has been used to program parallel applications. With the recent growth in multi-core processors, the level of parallelism necessary for next generation machines is cause for concern in the message passing community. The one-sided programming paradigm, in which only one of the two processes involved in communication actively participates in message transfer, has seen increased interest as a potential replacement for message passing. One-sided communication does not carry the heavy per-message overhead associated with modern message passing libraries. The paradigm offers lower synchronization costs and advanced data manipulation techniques such as remote atomic arithmetic and synchronization operations. These combine to present an appealing interface for applications with random communication patterns, which traditionally present message passing implementations with difficulties. This thesis presents a taxonomy of both the one-sided paradigm and of applications which are ideal for the one-sided interface. Three case studies, based on real-world applications, are used to motivate both taxonomies and verify the applicability of the MPI one-sided communication and Cray SHMEM one-sided interfaces to real-world problems. While our results show a number of short-comings with existing implementations, they also suggest that a number of applications could benefit from the one-sided paradigm. Finally, an implementation of the MPI one-sided interface within Open MPI is presented, which provides a number of unique performance features necessary for efficient use of the one-sided programming paradigm.
An efficient technique for exploring register file size in ASIP design

Performance estimation is a crucial operation which drives the design space exploration in an application-specific instruction set processor synthesis. With the increase in the level of integration, the design space has considerably expanded, which makes the simulation-driven techniques inadequate due to their slow speed. Alternatively, there are approaches which estimate performance by scheduling the application on the available processor resources without generating code. These are much more effective in exploring a large design space. The technique reported in this paper presents a scheduler-based approach for register file-size exploration. The performance is estimated by computing the number of spills for a particular register file size. The concept of register reuse chains is used for local register allocation, while live variable analysis done across the blocks is used to estimate global register needs. The technique is fast, accurate, retargetable, and does not require code generation. We have generated and validated execution-time estimates for selected benchmarks for a RISC (ARM7TDMI) and a VLIW (TM-1000) processor. Further, we have shown that this approach is much faster than simulator-based techniques.
Deficiency in the repair of DNA damage by homologous recombination and sensitivity to poly(ADP-ribose) polymerase inhibition.

Deficiency in either of the breast cancer susceptibility proteins BRCA1 or BRCA2 induces profound cellular sensitivity to the inhibition of poly(ADP-ribose) polymerase (PARP) activity. We hypothesized that the critical role of BRCA1 and BRCA2 in the repair of double-strand breaks by homologous recombination (HR) was the underlying reason for this sensitivity. Here, we examine the effects of deficiency of several proteins involved in HR on sensitivity to PARP inhibition. We show that deficiency of RAD51, RAD54, DSS1, RPA1, NBS1, ATR, ATM, CHK1, CHK2, FANCD2, FANCA, or FANCC induces such sensitivity. This suggests that BRCA-deficient cells are, at least in part, sensitive to PARP inhibition because of HR deficiency. These results indicate that PARP inhibition might be a useful therapeutic strategy not only for the treatment of BRCA mutation-associated tumors but also for the treatment of a wider range of tumors bearing a variety of deficiencies in the HR pathway or displaying properties of 'BRCAness. '
Vectorial capacity and vector control: reconsidering sensitivity to parameters for malaria elimination

Background Major gains have been made in reducing malaria transmission in many parts of the world, principally by scaling-up coverage with long-lasting insecticidal nets and indoor residual spraying. Historically, choice of vector control intervention has been largely guided by a parameter sensitivity analysis of George Macdonald's theory of vectorial capacity that suggested prioritizing methods that kill adult mosquitoes. While this advice has been highly successful for transmission suppression, there is a need to revisit these arguments as policymakers in certain areas consider which combinations of interventions are required to eliminate malaria. Methods and Results Using analytical solutions to updated equations for vectorial capacity we build on previous work to show that, while adult killing methods can be highly effective under many circumstances, other vector control methods are frequently required to fill effective coverage gaps. These can arise due to pre-existing or developing mosquito physiological and behavioral refractoriness but also due to additive changes in the relative importance of different vector species for transmission. Furthermore, the optimal combination of interventions will depend on the operational constraints and costs associated with reaching high coverage levels with each intervention. Conclusions Reaching specific policy goals, such as elimination, in defined contexts requires increasingly non-generic advice from modelling. Our results emphasize the importance of measuring baseline epidemiology, intervention coverage, vector ecology and program operational constraints in predicting expected outcomes with different combinations of interventions.
Assessing the efficacy of a diegetic game interface with Oculus Rift

The announced availability of new high-performance head-mounted displays is exciting the imagination of the consumer market and suggesting that we may soon have more immersive game playing opportunities. Leveraging on the commercialization of such devices, the expectation to enjoy a new generation of virtual reality-based games relies also on the development of game interfaces suitable to allow players to enjoy an adequate sense of presence and immersion, while playing. This paper shows, with results from field trials with the Oculus Rift head mounted display, that a diegetic game interface may help to enhance the feeling of “being in the flow of the game”, even when it is used to convey to players contextual gaming information (e.g., a game configuration menu). To this aim, a simple diegetic interface has been developed based on the design expedient of incorporating into the virtual game space some virtual devices (such as smart watches and tablets) through which contextual information is displayed to players.
Complex real-time environmental monitoring of the Hudson River and estuary system

Multiparameter and multiscale real-time environmental monitoring of a river and estuary system will be realized through the River and Estuary Observatory Network (REON) for the Hudson River in New York. In this paper, we describe a system under development that provides a holistic view of this complex and dynamic natural environment for scientific research, education, management, and environmental policy-related applications. The system incorporates a complex array of sensor technologies encompassing the physical, chemical, and biological measurement domains. REON supports Lagrangian, Eulerian, and autonomous robot sensor deployments, as well as flexible telemetry options through an open and consistent middleware architecture with advanced device management capabilities. Multimodal data streams are ingested and analyzed by an intelligent distributed streaming data analysis system known as System S. The challenges of managing high volumes of complex heterogeneous data are addressed via a distributed network of intelligent computational nodes that incorporate both autonomic algorithms and active knowledge management including a temporal component. REON provides an adaptive computing environment that provides isotropy in terms of data access and collaborative computation in contrast to traditional hierarchical control systems for sensor environments. Also presented is the underlying information infrastructure that supports a robust and integrated data modeling, simulation, and visualization manifold.
Sparsity Pattern Recovery in Bernoulli-Gaussian Signal Model

In compressive sensing, sparse signals are recovered from underdetermined noisy linear observations. One of the interesting problems which attracted a lot of attention in recent times is the support recovery or sparsity pattern recovery problem. The aim is to identify the non-zero elements in the original sparse signal. In this article we consider the sparsity pattern recovery problem under a probabilistic signal model where the sparse support follows a Bernoulli distribution and the signal restricted to this support follows a Gaussian distribution. We show that the energy in the original signal restricted to the missed support of the MAP estimate is bounded above and this bound is of the order of energy in the projection of the noise signal to the subspace spanned by the active coefficients. We also derive sufficient conditions for no misdetection and no false alarm in support recovery.
Selective nucleotide-release from dense-core granules in insulin-secreting cells

Secretory granules of insulin-secreting cells are used to store and release peptide hormones as well as low-molecular-weight compounds such as nucleotides. Here we have compared the rate of exocytosis with the time courses of nucleotide and peptide release by a combination of capacitance measurements, electrophysiological detection of ATP release and single-granule imaging. We demonstrate that the release of nucleotides and peptides is delayed by ∼0.1 and ∼2 seconds with respect to membrane fusion, respectively. We further show that in up to 70% of the cases exocytosis does not result in significant release of the peptide cargo, likely because of a mechanism that leads to premature closure of the fusion pore. Release of nucleotides and protons occurred regardless of whether peptides were secreted or not. These observations suggest that insulin-secreting cells are able to use the same secretory vesicles to release small molecules either alone or together with the peptide hormone.
Increased store-operated Ca2+ entry mediated by GNB5 and STIM1

Recent human genetic studies have shown that Gβ5 is related to various clinical symptoms, such as sinus bradycardia, cognitive disability, and attention deficit hyperactivity disorder. Although the calcium signaling cascade is closely associated with a heterotrimeric G-protein, the function of Gβ5 in calcium signaling and its relevance to clinical symptoms remain unknown. In this study, we investigated the in vitro changes of store-operated calcium entry (SOCE) with exogenous expression of Gβ5. The cells expressing Gβ5 had enhanced SOCE after depletion of calcium ion inside the endoplasmic reticulum. Gβ5 also augmented Stim1- and Orai1-dependent SOCE. An ORAI1 loss-of-function mutant did not show inhibition of Gβ5-induced SOCE, and a STIM1-ERM truncation mutant showed no enhancement of SOCE. These results suggested a novel role of GNB5 and Stim1, and provided insight into the regulatory mechanism of SOCE.
The Hedgehog Response Network: Sensors, Switches, and Routers

The Hedgehog (Hh) signaling pathway is intimately linked to cell growth and differentiation, with normal roles in embryonic pattern formation and adult tissue homeostasis and pathological roles in tumor initiation and growth. Recent advances in our understanding of Hh response have resulted from the identification of new pathway components and new mechanisms of action for old pathway components. The most striking new finding is that signal transmission from membrane to cytoplasm proceeds through recruitment, by the seven-transmembrane protein Smoothened, of an atypical kinesin, which routes pathway activation by interaction with other components of a complex that includes the latent zinc finger transcription factor, Ci.
Projected spin networks for Lorentz connection: linking spin foams and loop gravity

In the search for a covariant formulation for loop quantum gravity, spin foams have arisen as the corresponding discrete spacetime structure and, among the different models, the Barrett–Crane model seems to be the most promising. Here, we study its boundary states and introduce cylindrical functions on both the Lorentz connection and the time normal to the studied hypersurface. We call them projected cylindrical functions and explain how they would naturally arise in a covariant formulation of loop quantum gravity.