Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective variables for urban traffic incident detection

Past studies on automatic traffic incident detection have mainly focused on the incidents on freeways, which are controlled-access roads. There are not many works on urban traffic incident detection. In addition, the traffic data used in detecting an incident are still mostly collected from fixed sensors such as loop detectors. With the advances in mobile sensing and vehicular technology, it is foreseeable that mobile sensors will be used increasingly in the near future. In fact, traffic data will be collected directly by vehicles. Detecting traffic incidents in an urban road network with the traffic data collected by mobile sensors poses several challenges. First, the urban roads are uncontrolled-access roads, which are typically full of flow-disruptive entities such as traffic signals, intersections, crossings, bus stops, etc. These entities can disrupt the traffic flow in a similar way that an incident does, making it more difficult to detect an incident. Second, it is still not clear which traffic variables, collected by mobile sensors, can be used in detecting an incident in an urban environment. In this paper, we investigate and identify the traffic variables that are effective in detecting an incident in an urban road network. Particularly, speed, acceleration, lane-change ratio and travel time are studied. The results show that these four traffic variables are generally effective for traffic incident detection. However, among the four variables, the least effective one is the travel time.
Tibial nerve stimulation with a miniature, wireless stimulator in chronic peripheral neuropathic pain

Peripheral neuropathic pain (PNP) and complex regional pain syndrome (CRPS) can be effectively treated with peripheral nerve stimulation. In this clinical trial report, effectiveness of novel, miniature, wirelessly controlled microstimulator of tibial nerve in PNP and CRPS was evaluated. In this pilot study the average preoperative visual analog scale (VAS) score in six patients was 7.5, with 1, 3 and 6 months: 2.6 (p=0.03), 1.6 (p=0.03), and 1.3 (p=0.02), respectively. The mean average score in the six patients a week preceding the baseline visit was 7.96, preceding the 1, 3 and 6 month visits: 3.32 (p=0.043), 3.65 (p=0.045), and 2.49 (p=0.002), respectively. The average short-form McGill pain score before surgery was 23.8, and after 1, 3 and 6 months it was 11.0 (p=0.45), 6.3 (p=0.043), and 4.5 (p=0.01), respectively. Applied therapy caused a reduction of pain immediately after its application and clinical improvement was sustained on a similar level in all patients for six months. No complications of the treatment were observed. Intermittent tibial nerve stimulation by using a novel, miniature, wirelessly controlled device can be effective and feasible in PNP and CRPS. It is a safe, minimally invasive, and convenient neuromodulative method.
Hepcidin Plays a Key Role in 6-OHDA Induced Iron Overload and Apoptotic Cell Death in a Cell Culture Model of Parkinson's Disease

Elevated brain iron levels have been implicated in the pathogenesis of Parkinson’s disease (PD), however the underlying mechanisms are not clear. Hepcidin, a hormone primarily produced by hepatocytes, acts as a key regulator of cellular iron homeostasis. To investigate hepcidin’s role in 6‐hydroxydopamine (6‐OHDA) induced neurodegeneration, we down regulated hepcidin (32.3% P<0.0001) using siRNA interference technique in N27 dopaminergic neuronal cells and compared with a negative control. Our results show that hepcidin knockdown upregulated ferroportin expression and decreased intracellular free iron as measured with calcein fluorescence quenching method, by 35% and 24% in control and 6‐OHDA treatments. In addition, hepcidin knockdown protected 6‐OHDA induced apoptosis by attenuating oxidative damage. 6‐OHDA increased protein carbonyls by 146.4% (p<0.05), caspase‐3 activity by 154.6% (p<0.001) and DNA fragmentation by 54.3% (p<0.01), whereas hepcidin knockdown almost completely blocked the 6‐OHDA induced protein carbonyls, caspase‐3 activation and DNA fragmentation. Collectively, our results show that hepcidin plays a key role in reducing cellular iron burden and oxidative damage by possibly regulating iron export mediated by ferroprotin. This hepcidin dependent iron regulation in dopaminergic degeneration may provide a novel therapeutic strategy for slowing down the progression of PD.
Folded Logic Decomposition

The past decade of logic synthesis research has been characterized by a constant quest for smaller circuit area and faster circuit speed. While enjoying enormous success, the runtime of classic logic synthesis algorithms cannot keep up with the exponential growth of circuit complexity predicted by Moore’s law. In this paper, we propose a new technique where the regularity of the logic circuits, be it the apparent regularity in arithmetic-intensive circuits, or the hidden regularity in random logic, is automatically discovered and exploited to improve synthesis speed. We show that with this technique, the task of functional decomposition, the core engine of logic synthesis, can be made orders of magnitude faster than usual for arithmetic circuits, and on average eight times faster than usual for arbitrary random circuits.
Adaptive content composition system for Next Generation Networks

Composing learning material for online education and ensuring quality of delivery (low latency and high bandwidth) is a challenge to researchers in e-learning. The problem is compounded when the computing platforms are heterogeneous. Besides, e-learning as an application presents a highly fluctuating load to the underlying IP Multimedia Subsystem. <i>Viewed</i> <i>in</i> <i>this</i> <i>light,</i> <i>it</i> <i>appears</i> <i>that</i> <i>an</i> <i>e-learning</i> <i>system</i> <i>with</i> <i>inherent</i> <i>abilities</i> <i>to</i> <i>integrate</i> <i>various</i> <i>multimedia</i> <i>elements</i> <i>that</i> <i>can</i> <i>adapt</i> <i>its</i> <i>output</i> <i>to</i> <i>suit</i> <i>network</i> <i>parameters</i> <i>is</i> <i>the</i> <i>need</i> <i>of</i> <i>the</i> <i>hour</i>. In this paper, we propose a new architecture for the e-learning application & called ACCS & Adaptive Content Composition System & which is capable of composing a knowledge molecule (composed of different media elements) that can parametrically relate to the underlying IP Multimedia Subsystem (IMS), for ensuring a desired QoS. The ACCS architecture has two dominant layers above the IMS; viz., knowledge management sub-layer and network services adaptation sub-layer. We study the performance of ACCS with synthetic workloads under controlled conditions using a network test-bed, called GeNIe.
Matching matrix elements and shower evolution for top-pair production in hadronic collisions

We study the matching of multijet matrix elements and shower evolution in the case of top production in hadronic collisions at the Tevatron and at the LHC. We present the results of the matching algorithm implemented in the ALPGEN Monte Carlo generator, and compare them with results obtained at the parton level, and with the predictions of the MC@NLO approach. We highlight the consistency of the matching algorithm when applied to these final states, and the excellent agreement obtained with MC@NLO for most inclusive quantities. We nevertheless identify also a remarkable difference in the rapidity spectrum of the leading jet accompanying the top quark pair, and comment on the likely origin of this discrepancy.
Cryptanalysis and Enhancement of a Password-Based Authentication Scheme

Password-based authentication has been used extensively as a one of authentication techniques. Wu et al. presented a robust password authentication technique, in which they can face guessing, stolen-verifier, replaying, and impersonation attacks. However, in this paper, we are going to show that Wu et al. protocol is vulnerable to theft attack and consequentially construct a modified authentication scheme to prevent the shortcomings as a recovery. Proposed technique maintains the Wu et al's security features as well as remedies its security weakness.
Allotetraploid and autotetraploid models of linkage analysis

As a group of important plant species in agriculture and biology, polyploids have been increasingly studied in terms of their genome structure and organization. There are two types of polyploids, allopolyploids and autopolyploids, each resulting from a different genetic origin, which undergo meiotic divisions of a distinct complexity. A set of statistical models has been developed for linkage analysis, respectively for each type, by taking into account their unique meiotic behavior, i.e. preferential pairing for allopolyploids and double reduction for autopolyploids. We synthesized these models and modified them to accommodate the linkage analysis of less informative dominant markers. By reanalysing a published data set of varying ploidy in Arabidopsis, we corrected the estimates of the meiotic recombination frequency aimed to study the significance of polyploidization.
Decisions Regarding Production Location within the Swedish Textile and Apparel Industry today and in 2025

The textile and apparel industry is known for being at the forefront in manufacturing sourcing in new countries and collaboration with external manufacturers is very common. Studying how textile and apparel companies take decisions regarding production location is interesting since they represent one of the most global industries in the world, and some elements could be applicable in other industries where offshore production is a newer, less exploited phenomenon. This report includes a study that was performed in order to investigate where Swedish textile and apparel companies produce today, how it will change within then years and what factors that lie behind the decisions. The applied research strategy was a survey in the form of a questionnaire that included 119 Swedish textile and apparel companies. Interviews were also performed with some of the participants that represented large actors within the industry. The research showed that Swedish textile and apparel companies produce globally, but that the major part of production is performed in Europe and Asia. The largest share of the industry’s production is located in China followed by Sweden, the Baltic countries and other European regions. In Asia, Bangladesh and India have the second and third largest production share after China. The results indicate a stagnation of production in Asia as well as an increase of production in Europe and Africa until 2025. The study showed that location decisions are affected by internal factors, specific for the company and their products, and external factors specific for the location. Economic factors are by many companies considered as the most important factors but the availability of the right competence is also important together with existing relationships and political stability in the area. The results indicated that large companies are more likely to move their production and that there is a positive relationship between previous moves and change of production within the next ten years.
Analogical Processing: A Simulation and Empirical Corroboration

This paper compares the performance of the Structure-Mapping Engine (SME), a cognitive simulation of analogy, with two aspects of human performance. Gentner's Structure-Mapping theory predicts that soundness is highest for relational matches, while accessibility is highest for surface matches. These 'predictions have been borne out in psychological studies, and here we demonstrate that SME replicates these results. In particular, we ran SME on the same stories used in the psychological studies with two different kinds of match rules. In analogy mode, SME closely captures the human soundness ordering. In mereappearance mode, SME captures the accessibility ordering. We briefly review the psychological studies, describe our computational experiments, and discuss the utility of SME as a cognitive modeling tool.
Understanding New Cooperative Models: An Ownership–Control Rights Typology

This article examines new agricultural cooperative organizational models from an ownership rights perspective. The article adopts a definition of ownership rights comprising both residual claim and control rights. We argue that new cooperative organizational models differ in how ownership rights are assigned to the economic agents (members, patrons, and investors) tied contractually to the firm. The article proposes a typology of discrete organizational models, in which the traditional cooperative structure and the investor-oriented firm are characterized as polar forms. The typology also includes five nontraditional models that cooperatives may adopt to ameliorate perceived financial constraints.
A latent semantic retrieval and clustering system for personal photos with sparse speech annotation

In this demo we present a user-friendly latent semantic retrieval and clustering system for personal photos with sparse spontaneous speech tags annotated when the photos were taken. Only 10% of the photos need to be annotated by spontaneous speech of a few words regarding one or two semantic categories (e.g. what or where), while all photos can be effectively retrieved using high-level semantic queries in words (e.g. who, what, where, when) and clustered by the semantics as well. We use low-level image features to construct the relationships among photos, but train semantic models using Probabilistic Latent Semantic Analysis (PLSA) based on fused speech and image features to derive the "topics" of the photos. The sparse speech annotations serve as the user interface for the whole personal photo archive, while photos not annotated are automatically related by fused features and semantic topics of PLSA.
Analysing the performance of the algorithms used to localize the iris region in eye images submitted to severely compressed images

This work aims to evaluate how does the performance of the iris localization algorithms is influenced by severe compression of eye images used in an automatic iris recognition system. The correct localization of the iris region is essential to guarantee the credibility of the biometric recognition. As it is the first processing stage of the system, it is the first stage that can have its efficiency depredated by the quality loss of the images to be processed. Fractal compression and JPEG2000 compression were applied to a public iris images database. Two traditional methods which localize the circular borders of the iris and a method for detection of eyelids and eyelashes were applied to the compressed images and their efficiencies were evaluated. The results obtained with the simulations, when the images were submitted to several compression levels, lead to the important conclusion that segmentation stage does not represent a barrier for the utilization of compressed images in an iris recognition system.
Identification of dynamic plants using Fuzzy Wavelet Network: A multimodal memetic approach

Fuzzy Wavelet Neural Network (FWNN) is a subject in computer science which integrates fuzzy logic, neural network, and wavelet functions to achieve an admissible modeling tool. Training is the most important issue in FWNN. Many training methods have been proposed in the literature. However, there is no trying to train FWNN with multimodal optimization. It is desirable to obtain multiple global and local optima in a single run. In this paper, a multimodal memetic algorithm is proposed for training FWNN. A Particle Swarm Optimization (PSO) using ring neighborhood topology is employed to maintain diversity in different niches. Local searches are active during PSO running to improve the exploitation ability of the proposed method. Experimental results over two system identification problems show the superior performance of the proposed multimodal memetic algorithm.
Limitations to photosynthesis by proton motive force-induced photosystem II photodamage

The thylakoid proton motive force (pmf) generated during photosynthesis is the essential driving force for ATP production; it is also a central regulator of light capture and electron transfer. We investigated the effects of elevated pmf on photosynthesis in a library of Arabidopsis thaliana mutants with altered rates of thylakoid lumen proton efflux, leading to a range of steady-state pmf extents. We observed the expected pmf-dependent alterations in photosynthetic regulation, but also strong effects on the rate of photosystem II (PSII) photodamage. Detailed analyses indicate this effect is related to an elevated electric field (Δψ) component of the pmf, rather than lumen acidification, which in vivo increased PSII charge recombination rates, producing singlet oxygen and subsequent photodamage. The effects are seen even in wild type plants, especially under fluctuating illumination, suggesting that Δψ-induced photodamage represents a previously unrecognized limiting factor for plant productivity under dynamic environmental conditions seen in the field. DOI: http://dx.doi. org/10.7554/eLife.16921. 001
Inflation Expectations and Central Bank Communication in Turkey

This study assesses how inflation expectations respond to inflation targets, forecasts, and realizations with a particular focus on whether the sensitivity of expectations to inflation realizations increases with the level of inflation. For the sample period between April 2006 and May 2012, our findings indicate that forecasts, targets, and past inflation are important determinants of inflation expectations. Moreover, expectations are more sensitive to inflation realizations at higher levels of inflation. Interestingly, we find that sensitivity of expectations to inflation has decreased over time, especially since the end of 2011 despite a very rapid and sizable increase in CPI inflation due to one-off factors. Our results suggest that the implementation of tight monetary policy and intensive communication efforts by Central Bank of the Republic of Turkey might have reduced the sensitivity of expectations to the inflation realizations.
The Effect of Electroconvulsive Therapy on Autobiographical Memory: A Systematic Review

Objectives: In the last 20 years, an increasing number of articles have been published about effects of electroconvulsive therapy (ECT) on memory. Here, we review autobiographical memory studies in particular because there have been conflicting reports about the extent and persistence of ECT effects and the period before treatment from which memories are most likely to be affected. Methods: Five psychological and medical databases (MEDLINE, PubMed, PsychINFO, ScienceDirect, and Web of Knowledge) were searched from 1980 to 2007, yielding 15 studies of ECT and autobiographical memory. Results: Evidence suggests that autobiographical memory impairment does occur as a result of ECT. Objective measures found memory loss to be relatively short term (<6 months posttreatment), whereas subjective accounts reported amnesia to be more persistent (>6 months post-ECT). Electroconvulsive therapy predominantly affects memory of prior personal events that are near the treatment (within 6 months). Autobiographical memory loss is reduced by using brief pulse ECT rather than sine wave-unilateral positioning of electrodes rather than bilateral-and by titrating electrical current relative to the patient's own seizure threshold. Conclusions: Further research is required to determine memory loss associated with ECT, controlling for the direct effects of the depressive state.
Cash-on-Hand & College Enrollment: Evidence from Population Tax Data and Policy Nonlinearities

We estimate causal effects of cash-on-hand on college enrollment decisions of students from low-income families. Using population-level, administrative data from United States income tax returns, we exploit variation in tax refunds received in the spring of the high school senior year. The variation in tax refunds results from the kink point between the phase-in and maximum credit portions of the Earned Income Tax Credit schedule. The results suggest tax refunds received in the spring of the high school senior year have meaningful effects on college enrollment.
Transforming Rules and Trees into Comprehensible Knowledge Structures

The problem of transforming the knowledge bases of expert systems using induced rules or decision trees into comprehensible knowledge structures is addressed. A knowledge structure is developed that generalizes and subsumes production rules, decision trees, and rules with exceptions. It gives rise to a natural complexity measure that allows them to be understood, analyzed and compared on a uniform basis. The structure is a directed acyclic graph with the semantics that nodes are premises, some of which have attached conclusions, and the arcs are inheritance links with disjunctive multiple inheritance. A detailed example is given of the generation of a range of such structures of equivalent performance for a simple problem, and the complexity measure of a particular structure is shown to relate to its perceived complexity. The simplest structures are generated by an algorithm that factors common sub-premises from the premises of rules. A more complex example of a chess dataset is used to show the value of this technique in generating comprehensible knowledge structures.
Outage and SER performance of an opportunistic multi-user underlay cognitive network

Consider a multi-user underlay cognitive network where multiple cognitive users concurrently share the spectrum with a primary network and a single secondary user is selected for transmission. The channel is assumed to have independent but not identical Nakagami-m fading. Closed form expressions for the outage performance and the symbol-error-rate performance of the opportunistic multi-user secondary network are derived when a peak interference power constraint is imposed on the secondary network in addition to the limited peak transmit power of each secondary user.
Economic growth and lower class investments in nineteenth century Austria

The paper examines investment behavior in the lower-class population in the Alpine lands of the Habsburg Monarchy between 1820 and 1913. In order to determine how the lowerclass population responded to institutional changes in the financial market, the paper distinguishes between investments in various kinds of assets and examines the specific preferences of the lower-class population for savings deposits, securities, private debt claims, cash, real estate and movable belongings. In addition to professional factors, the analysis uses overall wealth, family status, age, cultural and regional factors, and the time factor as independent variables. Finally, the article determines whether the structures of portfolios show any additional systematic variation that cannot be explained by the effect of those factors.
A new parallel architecture for low power linear feedback shift registers

Low power dissipation is very critical in today's electronic designs. Components which are widely used in design, such as sequence generators like linear feedback shift registers (LFSR), should consume as little power as possible. Two recent works on parallel architecture of LFSR, one by M. Lowy and another by M.E. Hamid and C.I. H. Chen, have reduced dynamic power consumption significantly compared to the conventional architecture and showed the way to generate multiple outputs. In this paper we propose design improvements on these parallel architectures. The proposed method reduces dynamic power dissipation significantly, simplifies design process for single and multiple output generation, and eliminates the need of some hardware.