Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Nonlinear Local Reinforcement Learning Rules Through Neuroevolution

We consider the problem of designing local reinforcement learning rules for artificial neural network (ANN) controllers. Motivated by the universal approximation properties of ANNs, we adopt an ANN representation for the learning rules, which are optimized using evolutionary algorithms. We evaluate the ANN rules in partially observable versions of four tasks: the mountain car, the acrobot, the cart pole balancing, and the nonstationary mountain car. For testing whether such evolved ANN-based learning rules perform satisfactorily, we compare their performance with the performance of SARSA() with tile coding, when the latter is provided with either full or partial state information. The comparison shows that the evolved rules perform much better than SARSA() with partial state information and are comparable to the one with full state information, while in the case of the nonstationary environment, the evolved rule is much more adaptive. It is therefore clear that the proposed approach can be particularly effective in both partially observable and nonstationary environments. Moreover, it could potentially be utilized toward creating more general rules that can be applied in multiple domains and transfer learning scenarios.
Elasticity Improvement of Cassandra

Load size for a service on the Internet changes remarkably every hour. Thus, it is expected for service system scales to change dynamically according to load size. KVS (key-value store) is a scalable DBMS (database management system) widely used in large-scale Internet services. In this paper, we focus on Cassandra, a popular open-source KVS implementation, and discuss methods for improving dynamic scaling performance. First, we evaluate node joining time, which is the time to complete adding a node to a running KVS system, and show that its bottleneck process is disk I/O in the existing nodes. Second, we analyze disk accesses in the bottleneck nodes and indicate that some heavily accessed files cause a large number of disk accesses. Third, we propose a method for improving elasticity, which means decreasing node adding and removing time, of Cassandra. The method reduces disk accesses significantly by keeping the heavily accessed file in the page cache. Lastly, we evaluate elasticity of our methods. Our experimental results demonstrate that the method can improve the scaling-up and scaling-down performance of Cassandra.
F-manifolds with flat structure and Dubrovin's duality

This work continues the study of $F$--manifolds $(M,\circ)$, first defined by Hertling and Manin and investigated in [He]. The notion of a compatible flat structure $\nabla$ is introduced, and it is shown that many constructions known for Frobenius manifolds do not in fact require invariant metrics and can be developed for all such triples $(M,\circ ,\nabla). $ In particular, we extend and generalize recent Dubrovin's duality.
Improving Wi-Fi Based Indoor Positioning Using Bluetooth Add-Ons

Location-Based Services (LBSs) constitutes one of the most popular classes of mobile services. However, while current LBSs typically target outdoor settings, we lead large parts of our lives indoors. The availability of easy-to-use and low-cost indoor positioning services is essential in also enabling indoor LBSs. Existing indoor positioning services typically use a single technology such as Wi-Fi, RFID or Bluetooth. Wi-Fi based indoor positioning is relatively easy to deploy, but does often not offer good positioning accuracy. In contrast, the use of RFID or Bluetooth for positioning requires considerable investments in equipment in order to ensure good positioning accuracy. Motivated by these observations, we propose a hybrid approach to indoor positioning. In particular, we introduce Bluetooth hotspots into an indoor space with an existing Wi-Fi infrastructure such that better positioning is achieved than what can be achieved by each technology in isolation. We design a flexible and extensible system architecture with an effective online position estimation algorithm for the hybrid system. The system is evaluated empirically in the building of our department. The results show that the hybrid approach improves positioning accuracy markedly.
The importance of catastrophizing for successful pharmacological treatment of peripheral neuropathic pain

Objective Catastrophizing may be a negative predictor of pain-related outcomes. We evaluated the impact of catastrophizing upon success of first-line pharmacotherapy in the management of neuropathic pain (NeP) due to peripheral polyneuropathy. Methods Patients with confirmed NeP with NeP Visual Analog Scale (VAS) pain severity score ≥4 (0–10 scale) completed the Coping Strategies Questionnaire (CSQ) catastrophizing subscale at baseline. Pharmacological therapy consisting of first-line agents gabapentin, pregabalin, or a tricyclic antidepressant was initiated. Other measures examined included the Karnofsky Performance Scale, Beck Depression Inventory, EuroQol Quality of Life Health Questionnaire, and Modified Brief Pain Inventory. At 3 and 6 months, questionnaires were repeated and adverse effect reporting was completed. Outcome measures assessed were pharmacotherapy success (≥30% relief of NeP) and tolerability over 6 months of follow-up. Bivariate relationships using Pearson product-moment correlations were examined for baseline CSQ catastrophizing subscale score and the change in the NeP VAS scores and medication discontinuation. Results Sixty-six patients were screened, 62 subjects participated, and 58 subjects (94%) completed the final follow-up visit. Greater catastrophizing was associated with poor pain relief response and greater likelihood of discontinuation of pharmacotherapy, reports of greater disability, and impaired quality of life. Duration of pain was negatively associated with likelihood of pharmacotherapy success. Conclusion Catastrophizing exerts maladaptive effects on outcomes with pharmacotherapy in NeP patients. Detection of catastrophizing during clinical visits when pharmacological therapy is being considered can be a predictive factor for patient outcomes.
Generation of Radially Polarized Beams Using Optically Patterned Liquid Crystals

Radially polarizing liquid crystal (LC) devices aligned optically were investigated for applications in laser technology. Presently, radially polarized beams are generated through complex laser resonator configurations or buffing of LC alignment layers. Optically aligned LC devices offer several advantages over these methods, including their simple fabrication, low cost, high laser damage threshold, and scalability. This project researched the fabrication of the LC devices using a high-damage-threshold coumarin-based photopolymer irradiated with polarized UV light on a rotating stage coupled with a slit. Radially polarizing LC devices have been fabricated and characterized. This will lead to more research to improve the fabrication technique and make larger devices.
FLEXIBLE SPECIALISATION, INDUSTRIAL CLUSTERS AND DISTRICTS AND ‘SECOND’ AND ‘THIRD GENERATION’ LOCAL AND REGIONAL POLICIES

The Institute of Social Studies is Europe's longest-established centre of higher education and research in development studies. Postgraduate teaching programmes range from six-week diploma courses to the PhD programme. Research at ISS is fundamental in the sense of laying a scientific basis for the formulation of appropriate development policies. The academic work of ISS is disseminated in the form of books, journal articles, teaching texts, monographs and working papers. The Working Paper series provides a forum for work in progress which seeks to elicit comments and generate discussion. The series includes the research of staff, PhD participants and visiting fellows, and outstanding research papers by graduate students. ABSTRACT This paper observes that the conceptual bases for local regional industrial policies has been undergoing substantial changes. A distinction is made between several generations of policies. The 'first generation' of regional policies was based on the importance of exogenous growth factors. The 'second generation' of policies focussed on local endogenous factors. The theoretical base supporting these policies received strong impulses since the mid-80s from new insights derived from flexible specialization and industrial districts literature. A new and 'third generation' of policies is emerging that goes beyond endogenous growth, and seeks to superceed the division between exogenous and endogenously oriented policies. The analysis of growth and competitiveness has moved from the firm itself, and clusters of firms and to incorporate basic and institutional conditions fostering growth. This article provides an overview of contributions to the theory of regional industrial development underlying second and third generations of regional policies. A distinction is made between macro-regional theories and those that have an industrial organization and district focus. The review includes a selected number of case studies drawn mainly from Europe and Latin America. 2 1 CONTENTS
‘We will never escape these debts’: Undergraduate experiences of indebtedness, income-contingent loans and the tuition fee rises

Abstract This article critically examines how undergraduate students in a red brick university in the North of England have experienced the threefold rise in tuition fees since 2012, with particular attention on how they have begun to understand and negotiate the process of indebtedness. Drawing on a corpus of 118 interviews conducted with a group of 40 undergraduates across their whole student lifecycle, analysis is directed toward examining how students have variously sought to respond to the policy, reconcile the debt with their decision to study at university and, begin to negotiate a life of everyday indebtedness. The findings are located in the context of wider neoliberal policy trends that have continued to emphasise ‘cost-sharing’ as a mechanism for increased investment within the higher education sector generally, and individual fiscal responsibility specifically. Given the lack of any other viable career pathways for both lower and higher income students, they had to accept indebtedness as inevitable and take what comfort they could from the discourses of ‘foregone gain’ that they had been presented with. Evidently, and as the students in our sample well recognised, whether those discourses actually reflect the future remains to be seen. There is also no evidence within our data that students anticipated the subsequent changes to the repayment terms and conditions – a fact that is likely to compound feelings of economic powerlessness and constrain their capacity for financial agency yet further.
Ultrasound Elasticity Imaging for Determining the Mechanical Properties of Human Posterior Tibial Tendon: A Cadaveric Study

Posterior tibial tendon dysfunction (PTTD) is a common degenerative condition leading to a severe impairment of gait. There is currently no effective method to determine whether a patient with advanced PTTD would benefit from several months of bracing and physical therapy or ultimately require surgery. Tendon degeneration is closely associated with irreversible degradation of its collagen structure, leading to changes to its mechanical properties. If these properties could be monitored in vivo, they could be used to quantify the severity of tendonosis and help determine the appropriate treatment. The goal of this cadaveric study was, therefore, to develop and validate ultrasound elasticity imaging (UEI) as a potentially noninvasive technique for quantifying tendon mechanical properties. Five human cadaver feet were mounted in a materials testing system (MTS), while the posterior tibial tendon (PTT) was attached to a force actuator. A portable ultrasound scanner collected 2-D data during loading cycles. Young's modulus was calculated from the strain, loading force, and cross-sectional area of the PTT. Average Young's modulus for the five tendons was (0.45 ± 0.16 GPa) using UEI, which was consistent with simultaneous measurements made by the MTS across the whole tendon (0.52 ± 0.18 GPa). We also calculated the scaling factor (0.12 ± 0.01) between the load on the PTT and the inversion force at the forefoot, a measurable quantity in vivo. This study suggests that UEI could be a reliable in vivo technique for estimating the mechanical properties of the PTT, and as a clinical tool, help guide treatment decisions for advanced PTTD and other tendinopathies.
An effect evaluation of the psychosocial work environment of a university unit after a successfully implemented employeeship program

Purpose This study examined whether a successful implementation of an intervention could result in an effect evaluated independently from a process evaluation. It achieved this by evaluating the effects of an intervention, the ‘employeeship program’, designed to strengthen the psychosocial work environment through raising employees’ awareness and competence in interpersonal relationships and increasing their responsibility for their everyday work and working environment. Design/methodology/approach An employeeship intervention program was developed to improve the psychosocial work environment through reducing conflict among employees and strengthening the social community, empowering leadership, and increasing trust in management. An earlier process evaluation of the program found that it had been implemented successfully. The present effect evaluation supplemented this by examining its effect on the psychosocial work environment using two waves of the organization’s internal survey and comparing changes .
Boosting performance of bio-entity recognition by combining results from multiple systems

The task of biomedical named-entity recognition is to identify technical terms in the domain of biology that are of special interest to domain experts. While numerous algorithms have been proposed for this task, biomedical named-entity recognition remains a challenging task and an active area of research, as there is still a large accuracy gap between the best algorithms for biomedical named-entity recognition and those for general newswire named-entity recognition. The reason for such discrepancy in accuracy results is generally attributed to inadequate feature representations of individual entity recognition systems and external domain knowledge.In order to take advantage of the rich feature representations and external domain knowledge used by different systems, we propose several Meta biomedical named-entity recognition algorithms that combine recognition results of various recognition systems. The proposed algorithms -- majority vote, unstructured exponential model and conditional random field -- were tested on the GENIA biomedical corpus. Empirical results show that the F score can be improved from 0.72, which is attained by the best individual system, to 0.96 by our Meta entity recognition approach.
IPFIX Mediation framework of the SLAmeter tool

Presented paper deals with the IP Flow Information Export (IPFIX) Mediation. The IPFIX Mediation was elaborated by IPFIX Working Group. This paper summarizes the design and implementation of the IPFIX Mediation framework into the SLAmeter monitoring tool. The analytical part is devoted to the IPFIX Mediation problem. The core part of the paper is represented by the design and description of the implementation workflow of IPFIX Mediation framework. The main contribution of this work is to extend the application domains of the SLAmeter monitoring tool.
Exploiting Secure and Energy-Efficient Collaborative Spectrum Sensing for Cognitive Radio Sensor Networks

Cognitive radio sensor network (CRSN) has emerged as a promising solution to address the spectrum scarcity problem in traditional sensor networks, by enabling sensor nodes to opportunistically access licensed spectrum. To protect the transmission of primary users and enhance spectrum utilization, collaborative spectrum sensing is generally adopted for improving spectrum sensing accuracy. However, as sensor nodes may be compromised by adversaries, these nodes can send false sensing reports to mislead the spectrum sensing decision, making CRSNs vulnerable to spectrum sensing data falsification (SSDF) attacks. Meanwhile, since the energy consumption of spectrum sensing is considerable for energy-limited sensor nodes, SSDF attack countermeasures should be carefully devised with the consideration of energy efficiency. To this end, we propose a secure and energy-efficient collaborative spectrum sensing scheme to resist SSDF attacks and enhance the energy efficiency in CRSNs. Specifically, we theoretically analyze the impacts of two types of attacks, i.e., independent and collaborative SSDF attacks, on the accuracy of collaborative spectrum sensing in a probabilistic way. To maximize the energy efficiency of spectrum sensing, we calculate the minimum number of sensor nodes needed for spectrum sensing to guarantee the desired accuracy of sensing results. Moreover, a trust evaluation scheme, named FastDtec, is developed to evaluate the spectrum sensing behaviors and fast identify compromised nodes. Finally, a secure and energy-efficient collaborative spectrum sensing scheme is proposed to further improve the energy efficiency of collaborative spectrum sensing, by adaptively isolating the identified compromised nodes from spectrum sensing. Extensive simulation results demonstrate that our proposed scheme can resist SSDF attacks and significantly improve the energy efficiency of collaborative spectrum sensing.
On the Use of Diminished-1 Adders for Weighted Modulo 2n + 1 Arithmetic Components

The contribution of this paper is twofold. We firstly show that an augmented diminished-1 adder can be used for the modulo 2n +1 addition of two n-bit operands in the weighted representation, if it is driven by operands whose sum has been decreased by 1. This scheme outperforms solutions that are based on the use of binary adders and/or weighted modulo 2n + 1 adders in both area and delay terms. We then apply this scheme in the design of residue generators (RGs) and multi-operand modulo adders (MOMAs). The resulting arithmetic components remove at least a whole parallel adder out of the critical path of the currently most efficient proposals. Experimental results indicate savings of more than 30% in execution time and of approximately 19% in implementation area when the proposed architectures are used.
Structure of the Hybrid-2 type intramolecular human telomeric G-quadruplex in K+ solution: insights into structure polymorphism of the human telomeric sequence

Formation of the G-quadruplex in the human telomeric sequence can inhibit the activity of telomerase, thus the intramolecular telomeric G-quadruplexes have been considered as an attractive anticancer target. Information of intramolecular telomeric G-quadruplex structures formed under physiological conditions is important for structure-based drug design. Here, we report the first structure of the major intramolecular G-quadruplex formed in a native, non-modified human telomeric sequence in K+ solution. This is a hybrid-type mixed parallel/antiparallel-G-stranded G-quadruplex, one end of which is covered by a novel T:A:T triple capping structure. This structure (Hybrid-2) and the previously reported Hybrid-1 structure differ in their loop arrangements, strand orientations and capping structures. The distinct capping structures appear to be crucial for the favored formation of the specific hybrid-type intramolecular telomeric G-quadruplexes, and may provide specific binding sites for drug targeting. Our study also shows that while the hybrid-type G-quadruplexes appear to be the major conformations in K+ solution, human telomeric sequences are always in equilibrium between Hybrid-1 and Hybrid-2 structures, which is largely determined by the 3′-flanking sequence. Furthermore, both hybrid-type G-quadruplexes suggest a straightforward means for multimer formation with effective packing in the human telomeric sequence and provide important implications for drug targeting of G-quadruplexes in human telomeres.
A work-stealing scheduler for X10's task parallelism with suspension

The X10 programming language is intended to ease the programming of scalable concurrent and distributed applications. X10 augments a familiar imperative object-oriented programming model with constructs to support light-weight asynchronous tasks as well as execution across multiple address spaces. A crucial aspect of X10's runtime system is the scheduling of concurrent tasks. Work-stealing schedulers have been shown to efficiently load balance fine-grain divide-and-conquer task-parallel program on SMPs and multicores. But X10 is not limited to shared-memory fork-join parallelism. X10 permits tasks to suspend and synchronize by means of conditional atomic blocks and remote task invocations. In this paper, we demonstrate that work-stealing scheduling principles are applicable to a rich programming language such as X10, achieving performance at scale without compromising expressivity, ease of use, or portability. We design and implement a portable work-stealing execution engine for X10. While this engine is biased toward the efficient execution of fork-join parallelism in shared memory, it handles the full X10 language, especially conditional atomic blocks and distribution. We show that this engine improves the run time of a series of benchmark programs by several orders of magnitude when used in combination with the C++ backend compiler and runtime for X10. It achieves scaling comparable to state-of-the art work-stealing scheduler implementations---the Cilk++ compiler and the Java fork/join framework---despite the dramatic increase in generality.
Exactly solvable dynamics of the Eigen and the Crow-Kimura models

David B. Saakian, Olga Rozanova , and Andrei Akmetzhanov 4∗ Yerevan Physics Institute, Alikhanian Brothers St. 2, Yerevan 375036, Armenia Institute of Physics, Academia Sinica, Nankang, Taipei 11529, Taiwan Mathematics and Mechanics faculty, Moscow State University, Main building, Moscow 119992 Russia and Institute for Problems in Mechanics, Russian Academy of Sciences, Vernadsky Ave. 101-1, Moscow 115926, Russia (Dated: August 12, 2009)
Insights into the Evolution of a Cryptic Radiation of Bats: Dispersal and Ecological Radiation of Malagasy Miniopterus (Chiroptera: Miniopteridae)

The past decade has seen a proliferation of new species of Miniopterus bats (family Miniopteridae) recognized from Madagascar and the neighboring Comoros archipelago. The interspecific relationships of these taxa, their colonization history, and the evolution of this presumed adaptive radiation have not been sufficiently explored. Using the mitochondrial cytochrome-b gene, we present a phylogeny of the Malagasy members of this widespread Old World genus, based on 218 sequences, of which 82 are new and 136 derived from previous studies. Phylogenetic analyses recovered 18 clades, which divide into five primary lineages: (1) M. griveaudi; (2) M. mahafaliensis, M. sororculus and X3; (3) M. majori, M. gleni and M. griffithsi; (4) M. brachytragos; M. aelleniA, and M. aelleniB; and (5) M. manavi and M. petersoni recovered as sister species, which were in turn linked to a group comprising M. egeri and five genetically distinct populations referred to herein as P3, P4, P5, P6 and P7. Beast analysis indicated that the initial divergence within the Malagasy Miniopterus radiation took place 4.5 Myr; most species diverged between 4 and 2.5 Myr, and a secondary period was between 1.25 and 1 Myr. DNA K2P-distances between recognized taxa ranged from 12.9% to 2.5% and intraspecific variation was less than 1.8%. Of the 18 identified clades, Latin binomials are only associated with 11, which indicates much greater differentiation than currently recognized for Malagasy Miniopterus. These data are placed in a context of the dispersal history of this genus on the island and patterns of ecological diversity.