Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Bounds for Lambda Policy Iteration

We consider the discrete-time infinite-horizon discounted stationary optimal control problem formalized by Markov Decision Processes. We study Lambda Policy Iteration, a family of algorithms parameterized by lambda, originally introduced by Ioffe and Bertsekas. Lambda Policy Iteration generalizes the standard algorithms Value Iteration and Policy Iteration, and has some connections with TD(Lambda) introduced by Sutton & Barto. We consider the discrete-time infinite-horizon discounted stationary optimal control problem formalized by Markov Decision Processes. We study Lambda Policy Iteration, a family of algorithms parameterized by lambda, originally introduced by Ioffe and Bertsekas. Lambda Policy Iteration generalizes the standard algorithms Value Iteration and Policy Iteration, and is closely related to TD(lambda) introduced by Sutton and Barto. We deepen the original theory developped by Ioffe and Bertsekas by providing convergence rate bounds which generalize standard bounds for Value Iteration described for instance by Puterman. We also develop the theory of this algorithm when it is used in an approximate form. Doing so, we extend and unify the separate analyses developped by Munos for Approximate Value Iteration and Approximate Policy Iteration. The main contribution of this paper is that we show that doing Approximate Lambda Policy Iteration is sound.
Network coding tree algorithm for multiple access system

Network coding is famous for its capability in significantly improving the throughput of network. The successful decoding of the network coded data relies on some side information of the original data. In that framework, independent data flows are usually decoded first and then network coded by relay nodes. If appropriate signal design is adopted, physical layer network coding is a natural way in wireless networks. In this work, a network coding tree algorithm which enhances the efficiency of the multiple access system (MAS) is presented. For MAS, researchers try to avoid the collisions but collisions happen frequently under heavy load. By introducing network coding into MAS, our proposed algorithm achieves a better trade-off between average delay and system throughput. When multiple users transmit signal in a time slot, the sum signals are saved and used to jointly decode the collided frames after some component frames of the network coded frame are received. Splitting tree structure is extended to our proposed algorithm for collision solving. The system throughput and average delay of frames are presented in a recursive way. Besides, extensive simulations show that network coding tree algorithm enhances the system performance in terms of system throughput and average frame delay compared with other algorithms.
UFMC: The 5G modulation technique

This, paper describes the aspects of Universal Filtered MultiCarrier (UFMC) system and highlights the merits of new modulation method for emerging fifth generation (5G) Wireless Communication Systems. Orthogonal Frequency Division Multiplexing (OFDM) is an excellent choice for fourth generation (4G). 4G modulation methods suffer from the problem of high Peak to Average Power Ratio (PAPR). Side band leakage is another problem in OFDM. Our current 4G systems rely on the OFDM waveform, which is not capable of supporting the diverse applications 5G will offer. The traffic generated by 5G is expected to have very different characteristics and requirements when compared to current wireless technology. As result other multiple access schemes are being investigated. The way to overcome the known limitations of OFDM is UFMC technique. This paper discusses PAPR and Bit Error Rate (BER) of UFMC system for various mapping schemes. Mat lab simulations show that BER values for UFMC are increasing with increase in number of bits per subcarrier. BER of UFMC system is less for 4QAM (Quadrature Amplitude Modulation) mapping method when compared to the other mapping methods but PAPR of UFMC is high when compared with OFDM. PAPR for UFMC is 8.237 and for OFDM it is 8.843 at SNR=5dB when 16QAM Mapping is used. For all other mapping methods PAPR of UFMC system is high compared to PAPR of OFDM. Therefore as a compromise between BER and PAPR of UFMC system, 16QAM mapping method is preferable for UFMC system.
Electrospun water soluble polymer mat for ultrafast release of Donepezil HCl

Electrostatic spinning (Electrospinning, ES) was applied to prepare Donepezil HCl loaded nanofibers as a poten- tial orally dissolving dosage form. Electrospinning of water solutions of different polymers were performed in order to fab- ricate a consistent and removable web on the collector with ultra-fast dissolution in water based media. Poly(vinyl-alcohol) of low molecular weight was found to be the most appropriate for this purpose. Morphology of the prepared nanofibers was characterized by scanning electron microscope as a function of viscosity and drug content. Diameters of the fibers were between 100 and 300 nm with narrow distribution. In vitro drug release of the webs was immediate (less than 30 s) after immersion independently of their drug content owing to the formed huge surface area, while cast films with the same com- positions and commercial tablets needed 30 min or more for complete dissolution. The developed technology for the prepa- ration of orally dissolving web (ODW) formulations is a promising way for producing effective and acceptable dosage forms for children, older people and patients with dysphagia.
Tetravalent normal edge-transitive Cayley graphs on a certaingroup of order $6n$

Let U6n = ⟨a, b|a = b = 1, a−1ba = b−1⟩ be a group of order 6n. In this paper tetravalent normal edge-transitive Cayley graphs on U6n are considered. In this way several nonequivalent normal edge-transitive Cayley graphs on U6n are obtained whose automorphism groups are given exactly.
A novel geocasting protocol for multi-interface tactical ad hoc networks

Geocasting is an efficient protocol for disseminating tactical messages to nodes within a specific area. Most of the geocasting protocols consider a single interface and single channel-based network. In such networks, the performance of geocasting does not scale with the increase in network size and the traffic load. One of the development trends in tactical networks is that communication equipment has multiple interfaces and channels. Thus, we propose an efficient geocasting protocol using multiple interfaces and channels in tactical ad hoc networks. The proposed scheme consists of two phases: packet forwarding and local flooding. In the forwarding scheme, the orthogonal channels are guaranteed at minimum two hops when a packet is delivered from a source to a geocast region and latency is reduced by using multiple channels in multi-hop packet delivery. In the local flooding, the latency and packet delivery ratio are enhanced by using the main channel and sub-channels in a distributed manner. Our simulation study using ns-2 shows that the proposed protocol outperforms the performance compared with other existing protocols.
Effect size, confidence interval and statistical significance: a practical guide for biologists

Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta‐analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta‐analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non‐normal error structure and/or variances, and (4) when data are non‐independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner’s instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.
Multirapid Serial Visual Presentation Framework for EEG-Based Target Detection

Target image detection based on a rapid serial visual presentation (RSVP) paradigm is a typical brain-computer interface system with various applications, such as image retrieval. In an RSVP paradigm, a P300 component is detected to determine target images. This strategy requires high-precision single-trial P300 detection methods. However, the performance of single-trial detection methods is relatively lower than that of multitrial P300 detection methods. Image retrieval based on multitrial P300 is a new research direction. In this paper, we propose a triple-RSVP paradigm with three images being presented simultaneously and a target image appearing three times. Thus, multitrial P300 classification methods can be used to improve detection accuracy. In this study, these mechanisms were extended and validated, and the characteristics of the multi-RSVP framework were further explored. Two different P300 detection algorithms were also utilized in multi-RSVP to demonstrate that the scheme is universally applicable. Results revealed that the detection accuracy of the multi-RSVP paradigm was higher than that of the standard RSVP paradigm. The results validate the effectiveness of the proposed method, and this method can provide a whole new idea in the field of EEG-based target detection.
antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers

Microbial secondary metabolites are a potent source of antibiotics and other pharmaceuticals. Genome mining of their biosynthetic gene clusters has become a key method to accelerate their identification and characterization. In 2011, we developed antiSMASH, a web-based analysis platform that automates this process. Here, we present the highly improved antiSMASH 2.0 release, available at http://antismash.secondarymetabolites. org/. For the new version, antiSMASH was entirely re-designed using a plug-and-play concept that allows easy integration of novel predictor or output modules. antiSMASH 2.0 now supports input of multiple related sequences simultaneously (multi-FASTA/GenBank/EMBL), which allows the analysis of draft genomes comprising multiple contigs. Moreover, direct analysis of protein sequences is now possible. antiSMASH 2.0 has also been equipped with the capacity to detect additional classes of secondary metabolites, including oligosaccharide antibiotics, phenazines, thiopeptides, homo-serine lactones, phosphonates and furans. The algorithm for predicting the core structure of the cluster end product is now also covering lantipeptides, in addition to polyketides and non-ribosomal peptides. The antiSMASH ClusterBlast functionality has been extended to identify sub-clusters involved in the biosynthesis of specific chemical building blocks. The new features currently make antiSMASH 2.0 the most comprehensive resource for identifying and analyzing novel secondary metabolite biosynthetic pathways in microorganisms.
The Sit-to-Stand Movement: Differences in Performance Between Patients After Primary Total Hip Arthroplasty and Revision Total Hip Arthroplasty With Acetabular Bone Impaction Grafting

Background Little is known about the functional performance of patients after revision total hip arthroplasty with major acetabular bone impaction grafting. In general, these patients are assumed to perform worse due to a more advanced stage of periarticular tissue degeneration and multiple surgeries compared with patients with primary total hip arthroplasty (THA). Objective The main purpose of this study was to quantify the differences in performance of the sit-to-stand (STS) movement between patients with primary THA and patients with revision THA. Design and Methods In this study, the STS movement was analyzed kinematically (knee and hip angular extension velocity) and kinetically (loading symmetry ratio). Ten patients after primary THA and 10 patients after revision THA with acetabular bone impaction grafting were compared using these 3 rising parameters. Results The patients with revision THA performed the STS movement comparably to the patients with primary THA; there were no differences in knee and hip velocity or leg asymmetry during rising. Limitations The study focused only on kinetic and kinematic aspects, and only patients who were satisfied with their THA were involved. Conclusions This study showed that patients after a revision THA with acetabular bone impaction grafting and cement did not perform the STS movement differently, either kinematically or kinetically, compared with patients with a primary THA.
Word Clustering and Disambiguation Based on Co-occurrence Data

We address the problem of clustering words (or constructing a thesaurus) based on co-occurrence data, and using the acquired word classes to improve the accuracy of syntactic disambiguation. We view this problem as that of estimating a joint probability distribution specifying the joint probabilities of word pairs, such as noun verb pairs. We propose an efficient algorithm based on the Minimum Description Length (MDL) principle for estimating such a probability distribution. Our method is a natural extension of those proposed in (Brown et al., 1992) and (Li and Abe, 1996), and overcomes their drawbacks while retaining their advantages. We then combined this clustering method with the disambiguation method of (Li and Abe, 1995) to derive a disambiguation method that makes use of both automatically constructed thesauruses and a hand-made thesaurus. The overall disambiguation accuracy achieved by our method is 85.2%, which compares favorably against the accuracy (82.4%) obtained by the state-of-the-art disambiguation method of (Brill and Resnik, 1994).
Climate Change Perceived-Impact Severity, Its Determinants and Role in the Planning of National Adaptation Policy: The Case of Rice Farming in Indonesia

This paper identifies the characteristics of the farmer that affect the degree of farmer’s perceived-impact of climate change (CC). We use data from the Indonesian Rice Farm Household survey consisting of 87,330 farmers. An ordered probit regression model was used to estimate the effect of each variable on the degree of perceived-impact of CC. The results of this study confirm the previous empirical studies. Several variables that have been identified as having a positive effect on farmer adaptation practices such as farmer education, land tenure, irrigation infrastructure, cropping system, chemical fertilizer application, access to extension services and participation in farmer group affect the degree of CC perceived-impact negatively. However, a different result was found in the estimation of the gender variable. We found that female farmer has a higher resilience toward CC than the male farmer does. Furthermore, the female farmer has a more positive perception about future farming conditions than the male does. Finally, we suggest that the implementation of national adaptation policy should prioritize more to the farmer with insecure land tenure and utilize and expand the channel of agricultural extension services to deliver the planned adaptation policy.
Area recovery under depth constraint by Cut Substitution for technology mapping for LUT-based FPGAs

In this paper we present the post-processing algorithm, cut substitution, for technology mapping for LUT-based FPGAs to minimize the area under depth minimum constraint. The problem to generate a LUT's network whose area is minimum under depth minimum constraint seems to be as difficult as NP-hard class problem. Cut substitution is the process to generate a local optimum solution by eliminating redundant LUTs while the depth of network is maintained. The experiments shows that the proposed method derives the solutions whose area are 9% smaller than the solutions of a previous state-of-the-art, DAOmap on average.
Sferesv2: Evolvin' in the multi-core world

This paper introduces and benchmarks Sferesv2, a C++ framework designed to help researchers in evolutionary computation to make their code run as fast as possible on a multi-core computer. It is based on three main concepts: (1) including multi-core optimizations from the start of the design process; (2) providing state-of-the art implementations of well-selected current evolutionary algorithms (EA), and especially multiobjective EAs; (3) being based on modern (template-based) C++ techniques to be both abstract and efficient. Benchmark results show that when a single core is used, running time of classic EAs included in Sferesv2 (NSGA-2 and CMA-ES) are of the same order of magnitude than specialized C code. When n cores are used, typical speed-ups range from 0.75n to 0.9n; however, parallelization efficiency critically depends on the time to evaluate the fitness function.
Neuroanatomical Changes Associated with Pharmacotherapy in Posttraumatic Stress Disorder

Abstract: Brain imaging studies have mapped out the neural circuitry of posttraumatic stress disorder (PTSD), implicating brain areas sensitive to stress such as the hippocampus. Animal studies show that antidepressants promote hippocampal neurogenesis and block the effects of stress on the hippocampus. We found that treatment of PTSD patients for a year with the serotonin reuptake inhibitor (SSRI) paroxetine resulted in a 5% increase in hippocampal volume and a 35% improvement in verbal declarative memory function. Patients subjectively reported an improvement in cognition and work performance. These studies are consistent with the idea that antidepressants have a beneficial effect on hippocampal function in PTSD patients.
Understanding Low-Dose Exposure and Field Effects to Resolve the Field-Laboratory Paradox: Multifaceted Biological Effects from the Fukushima Nuclear Accident

Many reports about the biological effects of the Fukushima nuclear accident on vari - ous wild organisms have accumulated in recent years. Results from field-based labora tory experiments using the pale grass blue butterfly have clearly demonstrated that this butterfly is highly sensitive to “low-dose” internal exposure from field-contaminated host-plant leaves. These experimental results are fully consistent with the filed-collection results reporting high abnormality rates. In contrast, this butterfly is highly resistant against the internal exposure to chemically pure radioactive cesium chloride under labo ratory conditions. To resolve this field-laboratory paradox, I propose that the field effects, which are a collection of indirect effects that work through different modes of action than do the conventional direct effects, play an important role in the “low-dose” exposure results in the field. In other words, exclusively focusing on the effects of direct radiation, as predicted by dosimetric analysis, may be too simplistic. In this chapter, I provide a working definition and discuss the possible variation in the field effects. I include an example on the misunderstanding of the field effects In the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) 2017 Report. Lastly, I discuss a theoretical application of the butterfly model to humans .
Do you think your passwords are secure?

Many systems rely on passwords for authentication. Due to numerous accounts for different services, users have to choose and remember a significant number of passwords. Password-Manager applications address this issue by storing the user's passwords. They are especially useful on mobile devices, because of the ubiquitous access to the account passwords. Password-Managers often use key derivation functions to convert a master password into a cryptographic key suitable for encrypting the list of passwords, thus protecting the passwords against unauthorized, off-line access. Therefore, design and implementation flaws in the key derivation function impact password security significantly. Design and implementation problems in the key derivation function can render the encryption on the password list useless, by for example allowing efficient bruteforce attacks, or - even worse - direct decryption of the stored passwords. In this paper, we analyze the key derivation functions of popular Android Password-Managers with often startling results. With this analysis, we want to raise the awareness of developers of security critical apps for security, and provide an overview about the current state of implementation security of security-critical applications.
Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples.