Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated Approach to Personalized Procedural Map Generation Using Evolutionary Algorithms

In this paper, we propose the strategy of integrating multiple evolutionary processes for personalized procedural content generation (PCG). In this vein, we provide a concrete solution that personalizes game maps in a top-down action-shooter game to suit an individual player's preferences. The need for personalized PCG is steadily growing as the player market diversifies, making it more difficult to design a game that will accommodate a broad range of preferences and skills. In the solution presented here, the geometry of the map and the density of content within that geometry are represented and generated in distinct evolutionary processes, with the player's preferences being captured and utilized through a combination of interactive evolution and a player model formulated as a recommender system. All these components were implemented into a test bed game and experimented on through an unsupervised public experiment. The solution is examined against a plausible random baseline that is comparable to random map generators that have been implemented by independent game developers. Results indicate that the system as a whole is receiving better ratings, that the geometry and content evolutionary processes are exploring more of the solution space, and that the mean prediction accuracy of the player preference models is equivalent to that of existing recommender system literature. Furthermore, we discuss how each of the individual solutions can be used with other game genres and content types.
Spatially-Coupled Codes and Threshold Saturation on Intersymbol-Interference Channels

Recently, it has been observed that terminated low-density-parity-check (LDPC) convolutional codes (or spatially-coupled codes) appear to approach capacity universally across the class of binary memoryless channels. This is facilitated by the “threshold saturation” effect whereby the belief-propagation (BP) threshold of the spatially-coupled ensemble is boosted to the maximum a-posteriori (MAP) threshold of the underlying constituent ensemble. In this paper, we consider the universality of spatially-coupled codes over intersymbol-interference (ISI) channels under joint iterative decoding. More specifically, we empirically show that threshold saturation also occurs for the considered problem. This can be observed by first identifying the EXIT curve for erasure noise and the GEXIT curve for general noise that naturally obey the general area theorem. From these curves, the corresponding MAP and the BP thresholds are then numerically obtained. With the fact that regular LDPC codes can achieve the symmetric information rate (SIR) under MAP decoding, spatially-coupled codes with joint iterative decoding can universally approach the SIR of ISI channels. For the dicode erasure channel, Kudekar and Kasai recently reported very similar results based on EXIT-like curves [1].
The value of initial lactate in patients with carbon monoxide intoxication: in the emergency department

Patients with carbon monoxide (CO) poisoning have been found to have a correlation between initial clinical severity on admission and blood lactate levels. Recently, it is suggested that the lactate level may be a useful prognostic factor in cases study. The purpose of this study was to determine whether lactate levels were associated with the short-term outcome of patients with CO poisoning and identify the characteristics of patients with high initial lactate levels. Eighty patients that presented to the Chonnam National University Hospital after CO poisoning, over 5 years, were enrolled in this retrospective study. Fifty-six (70.0%) patients had high lactate (>2.1 mmo/L) on admission. Thirty-three (41.3%) patients had medical complications and one patient (1.3%) died. The patients with high initial lactate had an altered mental status more frequently, higher WBC, glucose and carboxyhemoglobin (COHb), and lower base deficit on admission. The multivariate analysis showed that lactate was an independent factor associated with serious complications and the need for intensive medical treatment, along with advanced age, WBC, and altered mental status on admission. The results of this study show that the initial lactate was useful for patient prognosis after CO poisoning.
Legionella pneumophila aortitis in a heart transplant recipient

Abstract: We describe the case of a patient with a culture‐proven infection of the ascending aorta caused by Legionella pneumophila 16 months after cardiac transplantation. Serology follow‐up and surveillance culture of the hospital water supply suggested a nosocomial acquisition of the infection during the post‐transplantation period. The diagnosis was made after 5 months of recurrent unexplained febrile episodes. A Teflon ring implanted around the aortic suture line during the intervention may have contributed to the unusual localization of the infection. The patient was successfully treated with antibiotics and aortic reconstruction.
Research on planar frequency selective fabrics with Jerusalem-shaped units

Planar frequency selective fabrics (FSFs) with Jerusalem-shaped units were proposed in this paper. In accordance with the previous work, the design process was specifically for 10 GHz. Through simulation and optimization procedures, the ideal structure parameters were obtained, and the proposed FSFs with optimized parameters showed good stability to differential and integral algorithms, transmission modes and incidence angles of electromagnetic (EM) waves. To further explore the internal EM transmission mechanism of FSFs, the surface currents at 4, 10 and 14 GHz were analyzed comparatively. Based on the simulated results, 10 samples with the polyester fabric substrate were fabricated through the computer-based carving method and the transmission characteristics were tested using the Shielding Room Method. The fabricated FSFs indeed showed good frequency response characteristics, as expected, and the comparison of measured and simulated results verified the validity of the design procedures. The influence rules of structure parameters (p, a, b, c) were further studied in detail by changing their values properly, and the simplified equivalent circuit model was proposed to explore the corresponding physical mechanism, which could provide physical insight into the performance of the FSFs.
Novel flavonoid-based biodegradable nanoparticles for effective oral delivery of etoposide by P-glycoprotein modulation: an in vitro, ex vivo and in vivo investigations

Abstract A receptor level interaction of etoposide with P-glycoprotein (P-gp) and subsequent intestinal efflux has an adverse effect on its oral absorption. The present work is aimed to enhance the bioavailability of etoposide by co-administering it with quercetin (a P-gp inhibitor) in dual-loaded polymeric nanoparticle formulation. Poly-lactic-co-glycolic acid (PLGA) nanoparticles were optimized for various parameters like o/w phase volume ratio, poly-vinyl alcohol concentration, PLGA concentration and sonication time. The cytotoxicity studies (MTT assay) revealed a 9- and 11-fold decrease in the IC 50 values for etoposide-loaded nanoparticles (ENP) and etoposide + quercetin dual-loaded nanoparticles (EQNP) when compared to that of free etoposide, respectively, and the results were further supported by florescent-activated cell sorter studies. The confocal imaging of the intestinal sections treated with ENP and EQNP containing fluorescent probe (rhodamine) showed the superiority of the EQNP to permeate deeper. Furthermore, pharmacokinetic studies on rats revealed that EQNP exhibited a 2.4-fold increase in bioavailability of etoposide than ENP with no quercetin. The developed loaded nanoparticles have the high potential to enhance the bioavailability of the etoposide and sensitize the resistant cells.
Dissipative particle dynamics simulation on the self-assembly of linear ABC triblock copolymers under rigid spherical confinements

Abstract Although a great deal of unique nanostructures were already obtained from polymer self-assemblies in terms of conventional parameters, the self-assembly under the confinement is still not well understood. Here, dissipative particle dynamics simulations were used to explore the self-assemble behaviors of linear ABC triblock copolymers under rigid spherical confinements. First several unusual morphologies, such as multilayer onion, coupled helix, and stacked lamella, were distinguished from the total 210 simulations. Second, the influences of three important parameters (block sequence, wall selectivity, and spherical radius) on the morphologies were discussed in detail. Finally, the dynamics evolution of several typical aggregates was examined. This simulation enriches micelle morphologies for the self-assembly of linear ABC triblock copolymers under rigid spherical confinements and is helpful to understand the formation of valuable nanostructures from linear ABC terpolymers.
Enhanced-performance wireless conformal "smart skins" utilizing inkjet-printed carbon-nanostructures

This paper introduces for the first time the integration of a UHF radio frequency identification (RFID) antenna with reduced graphene oxide (rGO), developed using direct-write techniques and utilizing an RFID chip for chemical gas detection. The module is realized by inkjet printing on a low-cost paper-based substrate, and the RFID tag is designed for the North America UHF RFID band. The electrical impedance of the rGO thin film changes in the presence of very small quantities of certain toxic gases, resulting in a variation of the backscattered power level which is easily detected by the RFID reader to realize reliable wireless toxic gas sensing. The inkjet printed RFID tag demonstrated a change in backscattered power of 9.18% upon exposure of 40 ppm NO2 for 5 minutes.
Simulation-based model selection for dynamical systems in systems and population biology

Motivation: Computer simulations have become an important tool across the biomedical sciences and beyond. For many important problems several different models or hypotheses exist and choosing which one best describes reality or observed data is not straightforward. We therefore require suitable statistical tools that allow us to choose rationally between different mechanistic models of, e.g. signal transduction or gene regulation networks. This is particularly challenging in systems biology where only a small number of molecular species can be assayed at any given time and all measurements are subject to measurement uncertainty. Results: Here, we develop such a model selection framework based on approximate Bayesian computation and employing sequential Monte Carlo sampling. We show that our approach can be applied across a wide range of biological scenarios, and we illustrate its use on real data describing influenza dynamics and the JAK-STAT signalling pathway. Bayesian model selection strikes a balance between the complexity of the simulation models and their ability to describe observed data. The present approach enables us to employ the whole formal apparatus to any system that can be (efficiently) simulated, even when exact likelihoods are computationally intractable. Contact: ttoni@imperial.ac. uk; m.stumpf@imperial.ac. uk Supplementary information: Supplementary data are available at Bioinformatics online.
Locating the central sulcus: comparison of MR anatomic and magnetoencephalographic functional methods.

PURPOSE To compare MR anatomic and magnetoencephalographic (MEG) functional methods in locating the central sulcus. METHODS Eleven healthy subjects and five patients with focal cerebral lesions were studied. The central sulcus was located anatomically with MR by two independent observers using axial vertex and sagittal (midline and lateral) images. Locations via the MEG functional method were based on detecting the somatosensory-evoked magnetic fields elicited by painless tactile stimuli. RESULTS The axial method yielded the most consistent interrater results, with complete agreement in 76% of sections in both control subjects and patients. The intermethod discordance of the sagittal midline and lateral methods was 32% in control subjects and 33% in patients. The concordance of MR and MEG methods ranged from 55% to 84% in control subjects and 65% to 67% in patients. CONCLUSION MR anatomic techniques can usually identify the central sulcus, but in the presence of anatomic distortion, the MEG functional method adds significant information.
ALOHA Random Access that Operates as a Rateless Code

Various applications of wireless Machine-to-Machine (M2M) communications have rekindled the research interest in random access protocols, suitable to support a large number of connected devices. Slotted ALOHA and its derivatives represent a simple solution for distributed random access in wireless networks. Recently, a framed version of slotted ALOHA gained renewed interest due to the incorporation of successive interference cancellation (SIC) in the scheme, which resulted in substantially higher throughputs. Based on similar principles and inspired by the rateless coding paradigm, a frameless approach for distributed random access in the slotted ALOHA framework is described in this paper. The proposed approach shares an operational analogy with rateless coding, expressed both through the user access strategy and the adaptive length of the contention period, with the objective to end the contention when the instantaneous throughput is maximized. The paper presents the related analysis, providing heuristic criteria for terminating the contention period and showing that very high throughputs can be achieved, even for a low number for contending users. The demonstrated results potentially have more direct practical implications compared to the approaches for coded random access that lead to high throughputs only asymptotically.
A Pareto following variation operator for evolutionary dynamic multi-objective optimization

Tracking the Pareto-front in a dynamic multi-objective optimization problem (MOP) is a challenging task. Evolutionary algorithms are a representative meta-heuristic capable of meeting this challenge. Typically, the stochastic variation operators used in an evolutionary algorithm work in decision (or design) variable space, thus there are no guarantees that the new individuals produced are non-dominated and/or are unique in the population. In this paper, we introduce a novel variation operator that manipulates the values in both objective space and design variable space in such a way that it can avoid re-exploration of dominated solutions. The proposed operator, inspired by the theory of dynamic system identification, is based on integral transformation. Here, we approximate the next expected Pareto-front, and from this expected front, we generate corresponding correct decision variables. We show empirically that our algorithm can approximate the Pareto-optimal set for given static benchmark MOPpsilas and that it can track changes in the Pareto-front for particular dynamic MOPpsilas.
Design and Evaluation of an Intelligent Rate Controller for Heterogeneous Networks

This paper proposes an intelligent rate controller for the Internet traffic. Called the IntelRate (Intelligent Rate), it is a router-based controller and uses the fuzzy logic control approach to adjust the source sending rate based on the instantaneous queue size of the router. Unlike other explicit congestion control protocols, the IntelRate controller need not evaluate the link states (such as bottleneck bandwidth or the number of flows in the link) while performing well to the sudden changes in traffic load or bandwidth. Simulation results and comparisons have verified the effectiveness of our scheme, and showed the IntelRate controller is more stable and robust upon large network changes than other existing protocols that rely on the estimation of available bandwidth in order to compute the admissible source sending rate.
Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain

We present an algorithm for blindly recovering constituent source spectra from magnetic resonance (MR) chemical shift imaging (CSI) of the human brain. The algorithm, which we call constrained nonnegative matrix factorization (cNMF), does not enforce independence or sparsity, instead only requiring the source and mixing matrices to be nonnegative. It is based on the nonnegative matrix factorization (NMF) algorithm, extending it to include a constraint on the positivity of the amplitudes of the recovered spectra. This constraint enables recovery of physically meaningful spectra even in the presence of noise that causes a significant number of the observation amplitudes to be negative. We demonstrate and characterize the algorithm's performance using /sup 31/P volumetric brain data, comparing the results with two different blind source separation methods: Bayesian spectral decomposition (BSD) and nonnegative sparse coding (NNSC). We then incorporate the cNMF algorithm into a hierarchical decomposition framework, showing that it can be used to recover tissue-specific spectra given a processing hierarchy that proceeds coarse-to-fine. We demonstrate the hierarchical procedure on /sup 1/H brain data and conclude that the computational efficiency of the algorithm makes it well-suited for use in diagnostic work-up.
Fast and precise positioning of rotary table systems by feedforward disturbance compensation considering interference force

This paper presents a model-based feedforward compensation approach for the fast and precise positioning of a rotary table system with two actuators. Since the interference force between the primary and slave actuators deteriorates the positioning performance, the interference model as well as the disturbance model are mathematically modeled to apply the model-based feedforward compensation. The effectiveness of the proposed approach has been verified using a prototype.
Detection of Plasmid-Mediated AmpC β-Lactamase Genes in Clinical Isolates by Using Multiplex PCR

ABSTRACT Therapeutic options for infections caused by gram-negative organisms expressing plasmid-mediated AmpC β-lactamases are limited because these organisms are usually resistant to all the β-lactam antibiotics, except for cefepime, cefpirome, and the carbapenems. These organisms are a major concern in nosocomial infections and should therefore be monitored in surveillance studies. Six families of plasmid-mediated AmpC β-lactamases have been identified, but no phenotypic test can differentiate among them, a fact which creates problems for surveillance and epidemiology studies. This report describes the development of a multiplex PCR for the purpose of identifying family-specific AmpC β-lactamase genes within gram-negative pathogens. The PCR uses six sets of ampC-specific primers resulting in amplicons that range from 190 bp to 520 bp and that are easily distinguished by gel electrophoresis. ampC multiplex PCR differentiated the six plasmid-mediated ampC-specific families in organisms such as Klebsiella pneumoniae, Escherichia coli, Proteus mirabilis, and Salmonella enterica serovar Typhimurium. Family-specific primers did not amplify genes from the other families of ampC genes. Furthermore, this PCR-based assay differentiated multiple genes within one reaction. In addition, WAVE technology, a high-pressure liquid chromatography-based separation system, was used as a way of decreasing analysis time and increasing the sensitivity of multiple-gene assays. In conclusion, a multiplex PCR technique was developed for identifying family-specific ampC genes responsible for AmpC β-lactamase expression in organisms with or without a chromosomal AmpC β-lactamase gene.
Nickel Resistance Determinants in Bradyrhizobium Strains from Nodules of the Endemic New Caledonia Legume Serianthes calycina

ABSTRACT Bradyrhizobium strains, isolated in New Caledonia from nodules of the endemic legume Serianthes calycina growing in nickel-rich soils, were able to grow in the presence of 15 mM NiCl2. The genomes of these strains harbored two Ni resistance determinants, the cnr and nre operons. By constructing a cnrA mutant, we demonstrated that the cnr operon determines the high nickel resistance in Bradyrhizobium strains.
Context-Aware Recruitment Scheme for Opportunistic Mobile Crowdsensing

The ubiquity of mobile devices coupled with the advances in Internet of Things (IoT) technologies has led to the development of large-scale applications that can collect information about people and their environments in real-time. Such applications are referred to as Mobile Crowdsensing (MCS). In MCS, tasks are allocated to participants (mobile devices) by a remote server according to the application requirements. The key challenge is reducing the energy consumption of the participating mobile devices. One of the effective approaches to reduce energy consumption of MCS applications is to improve efficiency of task allocation. An efficient task allocation approach can optimize several aspects of MCS applications such as task coverage (minimum number of participants required for a MCS task), data quality, and sensing costs. In this paper, we propose a novel Context-Aware Task Allocation (CATA) approach that aims to allocate sensing tasks to the best participant set while improving energy efficiency in MCS applications. Another important feature of the proposed CATA approach is that it preserves the privacy of participants' by only disclosing the less sensitive data to the server. The proposed approach employs local and global task allocation methods to enable two levels of data sharing and privacy. We describe the series of experiments that were conducted to validate our proposed approach in terms of coverage and efficiency.
Protein expression of sensory and motor nerves

The present study utilized samples from bilateral motor branches of the femoral nerve, as well as saphenous nerves, ventral roots, and dorsal roots of the spinal cord, to detect differential protein expression using two-dimensional gel electrophoresis and nano ultra-high performance liquid chromatography electrospray ionization mass spectrometry tandem mass spectrometry techniques. A mass spectrum was identified using the Mascot search. Results revealed differential expression of 11 proteins, including transgelin, Ig kappa chain precursor, plasma glutathione peroxidase precursor, an unnamed protein product (gi|55628), glyceraldehyde-3-phosphate dehydrogenase-like protein, lactoylglutathione lyase, adenylate kinase isozyme 1, two unnamed proteins products (gi|55628 and gi|1334163), and poly(rC)-binding protein 1 in motor and sensory nerves. Results suggested that these proteins played roles in specific nerve regeneration following peripheral nerve injury and served as specific markers for motor and sensory nerves.
Automatic Acquisition of Training Data for Statistical Parsers

The limitations of existing data sets for training parsers has led to a need for additional data. However, the cost of manually annotating the amount and range of data required is prohibitive. For a number of simple facts like those sought in Question Answering, we compile a corpus of sentences extracted from the Web that contain the fact keywords. We use a state-of-the-art parser to parse these sentences, constraining the analysis of the more complex sentences using information from the simpler sentences. This allows us to automatically create additional annotated sentences which we then use to augment our existing training data.