Miracle-dz/UniFAR-FTUs huggingface dataset:
An Optimal Offline Algorithm for List Update

For the static list update problem, given an ordered list $\rho_0$ (an ordering of the list $L$ = \{ $a_a, a_2, ., a_l$ \}), and a sequence $\sigma = (\sigma_1, \sigma_2, ., \sigma_m)$ of requests for items in $L$, we characterize the list reorganizations in an optimal offline solution in terms of an initial permutation of the list followed by a sequence of $m$ {\em element transfers}, where an element transfer is a type of list reorganization where only the requested item can be moved. Then we make use of this characterization to design an $O(l^{2} (l-1)! m)$ time optimal offline algorithm.
Interpolative based implementation of a photovoltaic panel

The paper presents a solution that provides for photovoltaic control systems estimations of coordinates of the maximum power point (MPP) using interpolation. The solution overcomes the problematic issues of the classical search methods and it performs correctly even for rapidly changing environmental conditions. Assuming knowledge about the PV panel characteristics, a reference value generator is designed to estimate the total radiation and the temperature of the panel and to output the voltage coordinate of the MPP using a two dimensional interpolative block. In order to follow the MPP, a DC-DC converter is used and its duty cycle is controlled through a discrete-time PI controller with ARW. The models, used to analyze the behavior of two photovoltaic systems, one with buck converter and one with boost converter, are given. The study emphasizes the ability of the system to follow in real time the changes of environmental conditions.
Functional identification of a Leishmania gene related to the peroxin 2 gene reveals common ancestry of glycosomes and peroxisomes

Glycosomes are membrane-bounded microbody organelles that compartmentalize glycolysis as well as other important metabolic processes in trypanosomatids. The compartmentalization of these enzymatic reactions is hypothesized to play a crucial role in parasite physiology. Although the metabolic role of glycosomes differs substantially from that of the peroxisomes that are found in other eukaryotes, similarities in signals targeting proteins to these organelles suggest that glycosomes and peroxisomes may have evolved from a common ancestor. To examine this hypothesis, as well as gain insights into the function of the glycosome, we used a positive genetic selection procedure to isolate the first Leishmania mutant (gim1-1 [glycosome import] mutant) with a defect in the import of glycosomal proteins. The mutant retains glycosomes but mislocalizes a subset glycosomal proteins to the cytoplasm. Unexpectedly, the gim1-1 mutant lacks lipid bodies, suggesting a heretofore unknown role of the glycosome. We used genetic approaches to identify a gene, GIM1, that is able to restore import and lipid bodies. A nonsense mutation was found in one allele of this gene in the mutant line. The predicted Gim1 protein is related the peroxin 2 family of integral membrane proteins, which are required for peroxisome biogenesis. The similarities in sequence and function provide strong support for the common origin model of glycosomes and peroxisomes. The novel phenotype of gim1-1 and distinctive role of Leishmania glycosomes suggest that future studies of this system will provide a new perspective on microbody biogenesis and function.
Multi-view Reconstruction of Highly Specular Surfaces in Uncontrolled Environments

Reconstructing the surface of highly specular objects is a challenging task. The shapes of diffuse and rough specular objects can be captured in an uncontrolled setting using consumer equipment. In contrast, highly specular objects have previously deterred capture in uncontrolled environments and have only been reconstructed using tailor-made hardware. We propose a method to reconstruct such objects in uncontrolled environments using only commodity hardware. As input, our method expects multi-view photographs of the specular object, its silhouettes and an environment map of its surroundings. We compare the reflected colors in the photographs with the ones in the environment to form probability distributions over the surface normals. As the effect of inter-reflections cannot be ignored for highly specular objects, we explicitly model them when forming the probability distributions. We recover the shape of the object in an iterative process where we alternate between estimating normals and updating the shape of the object to better explain these normals. We run experiments on both synthetic and real-world data, that show our method is robust and produces accurate reconstructions with as few as 25 input photographs.
Spectral Dimensionality Reduction via Maximum Entropy

We introduce a new perspective on spectral dimensionality reduction which views these methods as Gaussian random elds (GRFs). Our unifying perspective is based on the maximum entropy principle which is in turn inspired by maximum variance unfolding. The resulting probabilistic models are based on GRFs. The resulting model is a nonlinear generalization of principal component analysis. We show that parameter tting in the locally linear embedding is approximate maximum likelihood in these models. We directly maximize the likelihood and show results that are competitive with the leading spectral approaches on a robot navigation visualization and a human motion capture data set.
DNN based detection of pronunciation erroneous tendency in data sparse condition

Detecting pronunciation erroneous tendency (PET) can provide second languages learners with detailedly instructive feedbacks in the computer aided pronunciation training (CAPT) systems. Due to the data sparseness, DNN-HMM achieved limited improvement over GMM-HMM in our previous work. Instead of directly employing DNN-HMM to detect PETs, this paper investigated how to further improve the performance by DNN based features extracting in data sparse condition. Firstly, the probabilities of articulatory features derived from the top layer of DNN were fed into DNN-HMM. Secondly, the bottleneck features (BNF) extracted from the middle hidden layer were incorporated with original MFCC and then fed into SGMM-HMM. The experimental results showed that the new features converted from original acoustic features with DNN were more discriminative, and SGMM with BNF outperformed DNN in detecting PETs. The SGMM-HMM obtained the best detection results, achieving FRR of 5.3%, FAR of 29.6% and DA of 90%.
Acupuncture Attenuates Renal Sympathetic Activity and Blood Pressure via Beta-Adrenergic Receptors in Spontaneously Hypertensive Rats

The sympathetic nervous system, via epinephrine and norepinephrine, regulates β-adrenergic receptor (β-AR) expression, and renal sympathetic activation causes sustained increases in blood pressure by enhanced renin release. In this study, we aim to investigate the effect and underlying mechanism of acupuncture at Taichong (LR3) on renal sympathetic activity in spontaneously hypertensive rats. Unanesthetized rats were subject to daily acupuncture for 2 weeks. Mean blood pressure (MBP) and heart rate variability (HRV) were monitored at days 0, 7, and 14 by radiotelemetry. After euthanasia on the 14th day, blood and the kidneys were collected and subject to the following analyses. Epinephrine and norepinephrine were detected by ELISA. The expression of β-ARs was studied by western blotting and PCR. The renin content was analyzed by radioimmunoassay. 14-day acupuncture significantly attenuates the increase of MBP. The HRV indices, the standard deviation of all normal NN intervals (SDNN), and the ratio of the low-frequency component to the high-frequency component (LF/HF) were improved following acupuncture. Renal sympathetic activation induced upregulation of epinephrine, norepinephrine, and renin content were attenuated by acupuncture. In addition, acupuncture decreased β1-AR expression and improved β2-AR expression. These results indicated that acupuncture relieves the increased MBP via the regulation of renal sympathetic activity and β-ARs.
Automated Preoperative Planning of Acetabulam Size and Angle Detection for Hemi-arthroplasty

Conventional pre-operative planning for Hemi-arthroplasty is performed with caliper, protractor, transparent templates and x-ray sheets. This technique is time consuming with many errors. Computer-aided pre-operative planning systems can assist surgeons in selecting correct sized implantable acetabulam and accurate planning of an operation. This paper describes the pre-operative planning by digital image processing techniques for Total Hip Replacement by using 2D digital X-ray images which leads to the development of a software for surgeons and radiographers. The authors have used advanced image processing techniques and algorithms in image enhancement, calibration, planning, templating and reporting to overcome problems faced while doing all these manually. The proposed methodology provides accurate, computer programmed, user-friendly and dimensionally correct solution. The technique seems to be reliable and acceptable to patients, radiographers and surgeons
Extension of thickened and hot lithospheres: Inferences from laboratory modeling

The extension of a previously thickened lithosphere is studied through a series of analogue experiments. The models deformed in free and boundary‐controlled gravity spreading conditions that simulate the development of wide rift‐type and core complex‐type structures. In models, the development of structures mainly depends on boundary velocity and therefore on bulk strain rate. Wide rifts are of tilted block‐type at high strain rate and of horst‐ and graben‐type at low strain rate. The development of metamorphic core complex‐type structures is enhanced by low strain rates and by the presence of weak heterogeneities within the ductile crust. Core complexes result from a necking instability of the upper crust creating a graben, which further widens, allowing the rise and exhumation of a ductile layer dome. An upward convex detachment, flat on top of the dome and steeper on dome limb, appears not to be the primary cause of the core complex development but its consequence.
Identifying climatic drivers of tropical forest dynamics

Abstract. In the context of climate change, identifying and then predicting the impacts of climatic drivers on tropical forest dynamics is becoming a matter of urgency. To look at these climate impacts, we used a coupled model of tropical tree growth and mortality, calibrated with forest dynamic data from the 20-year study site of Paracou, French Guiana, in order to introduce and test a set of climatic variables. Three major climatic drivers were identified through the variable selection procedure: drought, water saturation and temperature. Drought decreased annual growth and mortality rates, high precipitation increased mortality rates and high temperature decreased growth. Interactions between key functional traits, stature and climatic variables were investigated, showing best resistance to drought for trees with high wood density and for trees with small current diameters. Our results highlighted strong long-term impacts of climate variables on tropical forest dynamics, suggesting potential deep impacts of climate changes during the next century.
Motorway traffic state estimation based on extended Kalman filter

This paper addresses the design of traffic state estimator for traffic flow in motorway stretches. Motorway traffic dynamics is modelled by a stochastic macroscopic traffic flow model, while a traffic state estimator is designed based on the extended-Kalman-filtering methodology. Besides the estimation of normal traffic variables, the developed traffic state estimator deals with the on-line estimation of unknown model parameters. Simulation investigations were conducted to test the traffic state estimator under various traffic conditions in a motorway stretch.
An Efficient Source Authentication for Multicast Based on Merkle Hash Tree

Source authentication is necessary in many multicast applications, especially in the real-time applications such as stream-video and online-news. In these applications, we should assure that all the packets received are from the same legal source and this can be done efficiently. In this paper, we propose an efficient scheme to decrease both communication cost and computation cost of source authentication. Owing to packets may arrive in an irregular sequence, so we consider checking its real order of content. After all, there are some analyses about comparing the efficiency and costs with other researches.
Evidence of Temporal Artifacts in Social Networks

There has been extensive research on social networks and methods for specific tasks such as: community detection, link prediction, and tracing information cascades; and a recent emphasis on using temporal dynamics of social networks to improve method performance. The underlying models are based on structural properties of the network, some of which we believe to be artifacts introduced from common misrepresentations of social networks. Specifically, representing a social network or series of social networks as an accumulation of network snapshots is problematic. In this paper, we use a dataset with timestamped interactions to demonstrate how cumulative graphs differ from activity-based graphs and may introduce temporal artifacts.
Hip-Hop and Spoken Word Therapy in Urban School Counseling

This study involved a secondary analysis of data collected across the 2016–2017 academic year to determine the impact on students’ social and emotional well-being of a new hip-hop lyricism course implemented by a school counselor. The new course introduced hip-hop and spoken word therapy into a specially designed classroom curriculum to meet the emotional and stress-coping needs of youth, allowing for improvements in the development of coping skills, emotional self-awareness, and self-image.
N ov 2 00 8 Applications of Multi-Valued Quantum Algorithms

This paper generalizes both the binary Deutsch-Jozsa and Grover algorithms to n-valued logic using the quantum Fourier transform. Our extended Deutsch-Jozsa algorithm is not only able to distinguish between constant and balanced Boolean functions in a single query, but can also find closed expressions for classes of affine logical functions in quantum oracles, accurate to a constant term. Furthermore, our multi-valued extension of the Grover algorithm for quantum database search requires less qudits and hence a substantially smaller memory register, as well as less wasted information states, to implement. We note several applications of these algorithms and their advantages over the binary cases.
The Open University ’ s repository of research publications and other research outputs Academics ’ online connections : Characterising the structure of personal networks on academic social networking sites and Twitter Conference Item

Academic social networking sites (SNS), such as Academia.edu and ResearchGate, seek to bring the benefits of online social networking to academics’ professional lives. Online academic social networking offers the potential to revolutionise academic publishing, foster novel collaborations, and empower academics to develop their professional identities online. However, the role that such sites play in relation to academic practice and other social media is not well understood at present. Arguably, the defining characteristic of academic social networking sites is the connections formed between profiles (in contrast to the traditional static academic homepage, for example). The social network of connections fostered by SNSs occupies an interesting space in relation to online identity, being both an attribute of an individual and shaped by the social context they are embedded within. As such, personal network structures may reflect an expression of identity (as “public displays of connection” (Donath & boyd, 2004) or “relational self portraits[s]” (Hogan & Wellman, 2014)), while social capital has been linked to network structures (Crossley et al., 2015). Network structure may therefore have implications for the types of roles that a network can play in professional life. What types of network structures are being fostered by academic SNS and how do they relate to academics’ development of an online identity? This presentation will discuss findings from a project which has used a mixed-methods social network analysis approach to analyse academics’ personal networks online. The personal networks of 55 academics (sampled from survey participants, to reflect a range of disciplines and job positions) on both one academic SNS (either Academia.edu or ResearchGate) and Twitter were collected and analysed. Differences in network structure emerged according to platform, with Twitter networks being larger and less dense, while academic SNS networks were smaller and more highly clustered. There were differences between academic SNS and Twitter in the brokerage positions occupied by the participant. The results are discussed in relation to other salient studies relating network structure in online social networks to social capital, and implications for academic practice. Future work, including co-interpretive interviews to explore the significance of network structures with participants, is introduced.
Swedish Financial Sector Integration with Baltic Stock Markets - A Cointegration Approach

This study investigates the long-run relationships and short-run dynamic linkages between the stock exchanges of Baltic countries and Swedish financial sector over the sample period 2000-2011. Johansen method of multivariate cointegration is utilized to determine long-run relationship, while Impulse response functions and Granger causality analyses, based on Error Correction Model (VECM), are employed to estimate the short-run dynamics among variables in the system. The empirical investigations suggest that there is relatively weak long-run relationship between indices of Lithuanian, Latvian, Estonian stock markets and Swedish stock and Swedish financial sector. However, we find some evidence that indicates long-run financial linkages between the performance of some Swedish banks which have high financial exposure in the Baltic countries and Baltic state stock market indices. In the short-run, the impulse response functions and Granger causality analyses indicate that Baltic stock markets have unidirectional effect on Swedish financial sector at immediate day of initial shock. Despite of the fact that the long-run identifications do not support a high long-run financial integration in this region, however, in the short term dynamics provide some evidence of increasing financial integration.
Breaking the Efficiency Barrier for Ambient Microwave Power Harvesting With Heterojunction Backward Tunnel Diodes

Harvesting low-density ambient microwave power as an alternative power source for small ubiquitous wireless nodes has been proposed in recent papers discussing emerging technologies like the Internet of Things and Smart Cities. However, a literature review of the state-of-the-art Schottky diode based microwave rectifiers shows that a maximum efficiency has been reached for such devices operating in the low-power regime, as is the case for ambient microwave power-harvesters. This work examines the underlying physical mechanisms responsible for this RF-to-dc power conversion efficiency limitation, and explores a high I-V curvature backward tunnel diode to overcome this efficiency limitation. Measurements of the 2.4 GHz RF-to-dc power conversion efficiency at -40 dBm input power demonstrates that the backward tunnel diode outperforms the HSMS-285B Schottky diode by a factor of 10.5 and the Skyworks SMS7630 by a factor of 5.5 in a lossless matching network scenario. A prototype built using a new GSG probe embedded with a matching circuit showed a total power conversion efficiency of 3.8% for -40 dBm input power and 18.2% for -30 dBm input power at 2.35 GHz.
Variation of pollinator assemblages and pollen limitation in a locally specialized system: the oil-producing Nierembergia linariifolia (Solanaceae).

BACKGROUND AND AIMS Few studies have examined the dynamics of specialist plant-pollinator interactions at a geographical scale. This knowledge is crucial for a more general evolutionary and ecological understanding of specialized plant-pollinator systems. In the present study, variations in pollinator activity, assemblage composition and pollen limitation were explored in the oil-producing species Nierembergia linariifolia (Solanaceae). METHODS Pollen limitation in fruit and seed production was analysed by supplementary hand pollination in five wild populations. Pollinator activity and identity were recorded while carrying out supplementary pollination to assess the effect of pollinators on the degree of pollen limitation. In two populations, pollen limitation was discriminated into quantitative and qualitative components by comparing supplementation and hand cross-pollination in fruit set and seed set. The effect of flower number per plant on the number of flowers pollinated per visitor per visit to a plant was examined in one of these populations as a possible cause of low-quality pollination by increasing geitonogamy. RESULTS AND CONCLUSIONS Although pollen limitation was evident along time and space, differences in magnitude were detected among populations and years that were greatly explained by pollinator activity, which was significantly different across populations. Floral display size had a significant effect on the visitation rate per flower. Limitation by quality clearly affected one population presumably due to a high proportion of geitonogamous pollen. The great inter-population variation in plant-pollinator interaction (both in pollinator assemblages composition and pollinator activity) and fitness consequences, suggests that this system should be viewed as a mosaic of locally selective processes and locally specialized interactions.
The effect of cost of credit on money demand: empirical evidence from Malaysia

This paper investigates the dynamic of long-run relationship between cost of credit and real money balances in Malaysia. The Johansen-Juselius (1990) likelihood ratio tests support the importance of the cost of credit in the real broad money demand function. The sample period spans from 1978:q1 through 1997:q4. The results provide empirical evidence for the long-run relationship between cost of credit and broad money balances in Malaysia.
DEM EXTRACTION FROM A COLOR-CODED RELIEF SCANNED MAP

The focus of this paper is in extracting a digital elevation model (DEM) from a color-coded relief scanned map. The map is preprocessed using a WHMM (Wavelet domain Hidden Markov Model) based algorithm for denoising. Then a linework removal algorithm – two methods are presented: one based on WHMMs and one that uses a vector gradient edge detector – is applied. Each distinct elevation region must be solid colored using distinct colors. In order to achieve this, for the printed scanned map, we used a median filtering, and a color clustering process – based on a minimum variance quantization algorithm. The gap filling problem can be solved with a multi-pass majority filter algorithm. The elevation contours are extracted by detecting the borders between colors through a sliding-neighborhood operation. The color-coded contours are converted into a sparse elevation data set by means of the map’s legend. Laplacian partial differential equations are used to interpolate the sparse DEM. The LSQR iterative solver is applied in order to solve the system of equations.