Miracle-dz/UniFAR-FTUs huggingface dataset:
Endoplasmic Reticulum Retention Signal-Dependent Glycylation of the Hsp70/Grp170-Related Pgp1p in Tetrahymena

ABSTRACT Glycylation is an uncommon posttranslational modification. It has been found that tubulin glycylation is essential for cell survival in Tetrahymena. Here we describe PGP1, a Tetrahymena gene encoding an Hsp70 homologue that is a novel glycylated protein. Pgp1p is a conserved glycoprotein that localizes within the lumen of the endoplasmic reticulum (ER). We demonstrate that PGP1 is essential for viability and present evidence that both glycosylation and ER retention are necessary but not sufficient for glycylation.
Simulation of Vehicle Collisions in Real Time

This paper describes how typical vehicle simulations require numerical integration at an integration time step of no larger than 0.01 seconds, usually less than half that time. This does not leave enough time to carry out the complex calculations required for detailed collision calculations in real time. This paper presents a method that strikes a compromise, which, although not carrying all the detail necessary for very accurate collision calculations, allows useful simulations to proceed in real time. The method has three parts: collision detection, estimation of the momentum transfer expected to result from the collision, and application of forces to provide the desired momentum transfer. The method uses a common scene graph for collision detection, which allows the system to work with most of the common scene database formats without the need of specialized preprocessing. All of the collision detection and response calculations employ open-source code and are designed to work well at speeds required by real-time vehicle simulation. Examples based on the VDANL vehicle dynamics simulation illustrate the utility of the methodology.
How to get your article rejected.

As an Associate Editor, I handle a considerable number of manuscripts submitted to Stress and Health for consideration for publication. Many of these articles are rejected from the journal. Sometimes manuscripts are rejected because they are deemed not to make a sufficiently original contribution to the field or contain ‘fatal flaws’. Often there is very little that can be done in such cases, other than to identify an original question or repeat the study ironing out the fatal flaw. However, many manuscripts are rejected for reasons that have little to do with the reported research, which may be original and competently conducted. Instead, the researcher may have failed to make a convincing case for the inclusion of the research in the journal, omitted crucial details or committed errors in their writing, some of which border on the felonious. In some cases, so blatant is the lack of detail, omissions or errors that I can only conclude that the author’s aim was to get their manuscript rejected. So great is this apparent need for rejection that I feel duty-bound to provide a set of guidelines to assist authors in getting their manuscripts rejected from Stress and Health. What follows therefore is my comprehensive set of guidelines on what to do when preparing a manuscript for publication in Stress and Health, or any social science journal for that matter, if you want to substantially increase the chances of your manuscript being rejected. I anticipate that authors following these guidelines will have no troubles in getting a reject decision and the best thing is that these guidelines will probably work for most journals. Along the way I will cite some recent examples of articles published in Stress and Health whose authors made a real hash of getting rejected by disregarding most of my guidelines. If you are keen to get that rejection letter from the Associate Editor of the journal to which you plan to submit your work, you would do well to avoid following their example.
Nonlinear robust optimization of uncertainty affine dynamic systems under the L-infinity norm

In this paper, we discuss robust optimal control techniques for dynamic systems which are affine in the uncertainty. Here, the uncertainty is assumed to be time-dependent but bounded by an L-infinity norm. We are interested in finding a tight upper bound for the worst case excitation of the inequality state constraints requiring to solve a parameterized lower-level maximization problem. In this paper, we suggest to replace this lower level maximization problem by an equivalent minimization problem using a special version of modified Lyapunov equations. This new reformulation offers advantages for robust optimal control problems where the uncertainty is time-dependent, i.e. infinite dimensional, while the inequality state constraints need to be robustly regarded on the whole time horizon.
Etching of lithium niobate: micro- and nanometer structures for integrated optics

Measurements of complex permittivity using transient techniques and Fourier transforms require computation which can be lengthy. In the invention, a synthesizer generates a succession of waveforms each containing a small number of harmonically related frequency components. These waveforms are applied to a capacitive potentiometer formed by a reference capacitor and a sample head. The voltages across the potentiometer and the sample head are passed by way of an analog-to-digital converter to a microprocessor which calculates Fourier transforms and indicates permittivity versus frequency. By limiting the frequency components, the computation time is reduced and a quick scan to find spectral regions of interest is possible. These regions can then be examined at higher resolution by changing a clock frequency which determines the generation of the frequency components.
Cigarette smoke induces cell motility via platelet-activating factor accumulation in breast cancer cells: a potential mechanism for metastatic disease

Most cancer deaths are a result of metastasis rather than the primary tumor. Although cigarette smoking has been determined as a risk factor for several cancers, its role in metastasis has not been studied in detail. We propose that cigarette smoking contributes to metastatic disease via inhibition of breast cancer cell platelet‐activating factor acetylhydrolase (PAF‐AH), resulting in PAF accumulation and a subsequent increase in cell motility. We studied several breast cell lines, including immortalized mammary epithelial cells (MCF‐10A), luminal A hormone positive MCF‐7, basal‐like triple negative MDA‐MB‐468, and claudin‐low triple‐negative highly metastatic MDA‐MB‐231 breast tumor cells. We exposed cells to cigarette smoke extract (CSE) for up to 48 h. CSE inhibited PAF‐AH activity, increased PAF accumulation, and increased cell motility in MDA‐MB‐231 metastatic triple negative breast cancer cells. The calcium‐independent phospholipase A2 (iPLA2) inhibitor, (S) bromoenol lactone ((S)‐BEL) was used to prevent the accumulation of PAF and further prevented the increase in cell motility seen previously when cells were exposed to CSE. Thus, iPLA2 or PAF may represent a therapeutic target to manage metastatic disease, particularly in triple‐negative breast cancer patients who smoke.
Modelling the prepausal lengthening effect for speech recognition: a dynamic Bayesian network approach

Speech has a property that the speech unit preceding a speech pause tends to lengthen. This work presents the use of a dynamic Bayesian network to model the prepausal lengthening effect for robust speech recognition. Specifically, we introduce two distributions to model inter-state transitions in prepausal and non-prepausal words, respectively. The selection of the transition distributions depends on a random variable whose value is influenced by whether a pause will appear between the current and the following word. Two experiments are presented here. The first one considers pauses hypothesised during speech decoding. The second one employs an extra component for speech/non-speech determination. By modelling the prepausal lengthening effect we achieve a 5.5% relative reduction in word error rate on the 500-word task of the SVitchboard corpus.
Improving understanding of website privacy policies with fine-grained policy anchors

Website privacy policies state the ways that a site will use personal identifiable information (PII) that is collected from fields and forms in web-based transactions. Since these policies can be complex, machine-readable versions have been developed that allow automatic comparison of a site's privacy policy with a user's privacy preferences. However, it is still difficult for users to determine the cause and origin of conformance conflicts, because current standards operate at the page level - they can only say that there is a conflict on the page, not where the conflict occurs or what causes it. In this paper we describe fine-grained policy anchors, an extension to the way a website implements the Platform for Privacy Preferences (P3P), that solves this problem. Fine grained policy anchors enable field-level comparisons of policy and preference, field-specific conformance displays, and faster access to additional conformance information. We built a prototype user agent based on these extensions and tested it with representative users. We found that fine-grained anchors do help users understand how privacy policy relates to their privacy preferences, and where and why conformance conflicts occur.
Securing the PRESENT Block Cipher Against Combined Side-Channel Analysis and Fault Attacks

In this paper, we present and evaluate a hardware implementation of the PRESENT block cipher secured against both side-channel analysis and fault attacks (FAs). The side-channel security is provided by the first-order threshold implementation masking scheme of the serialized PRESENT proposed by Poschmann et al. For the FA resistance, we employ the Private Circuits II countermeasure presented by Ishai et al. at Eurocrypt 2006, which we tailor to resist arbitrary 1-bit faults. We perform a side-channel evaluation using the state-of-the-art leakage detection tests, quantify the resource overhead of the Private Circuits II countermeasure, subdue the implementation to established differential FAs against the PRESENT block cipher, and contemplate on the structural resistance of the countermeasure. This paper provides the detailed instructions on how to successfully achieve a secure Private Circuits II implementation for the data path as well as the control logic.
A corpus-based lexicon building in Indonesian political context through Indonesian online news media

Considering public opinion has always been a necessity for most people including governments and politicians. This information provides more direct means in determining public views which important for their decision-making process. With technology and the Internet nowadays, people are able to assess public opinion by using opinion mining or sentiment analysis. There are several known methods for this technology, for instance is lexicon-based method which is inherited from sentiment classification approach. This method uses lexicon in determining sentiment of particular object within related data sets. This paper solely concentrates on building the lexicon for the method. By focusing on Indonesian politic, we create a corpus-based approach to build a contextual lexicon which uses news articles as corpora. We determine the initial seed words and have it validated by domain experts for our experiment Based on the tests that we have done, we find that 51.79 per cent of the terms in our lexicon are relevant to our research domain. We use this finding to evaluate and improve our method as we continue the research to obtain more relevant result.
Cleavage of AL amyloid proteins and AL amyloid deposits by cathepsins B, K, and L

Cathepsin (Cath) B, CathK and CathL are cysteine proteases that participate in the lysosomal protein degradation system and are expressed in macrophages, epithelioid cells, and multinucleated histiocytic giant cells (MGCs). Both macrophages and MGCs are commonly found adjacent to immunoglobulin light chain‐associated (AL) amyloid deposits, which raised the question of whether cysteine proteases are able to cleave AL amyloid proteins and AL amyloid deposits. The present study has investigated whether recombinant human CathB, CathK, and CathL are able to degrade ALVλVI amyloid proteins and AL amyloid deposits. Using immunohistochemistry, CathB, CathK, and CathL were found adjacent to AL amyloid deposits. In vitro degradation experiments using purified AL amyloid proteins showed that CathB, CathK, and CathL degrade ALVλVI amyloid proteins. Furthermore, using unfixed tissue sections from an amyloidotic spleen as an in vitro model for extracellular proteolysis of intact amyloid deposits, it was demonstrated that all three cysteine proteases are also capable of degrading AL amyloid in situ. This is the first study to show that cysteine proteases are able to cleave AL amyloid proteins. However, the efficiency with which proteolysis occurs depends on the concentration of active protease recruited at the sites of amyloid deposition, and possibly on the structure of the AL amyloid proteins. Copyright © 2004 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
WINDOW DETECTION IN SPARSE POINT CLOUDS USING INDOOR POINTS

Abstract. This paper describes an approach for detecting windows from multi-aspect airborne laser scanning point clouds which were recorded in a forward looking view. Since the resolution of the point cloud is much lower than from terrestrial laser scanning, new methods have to be developed to detect and, in a further step, reconstruct façade structures. The façade planes are detected using point normals and a regiongrowing algorithm. The approach for window detection uses the points which are lying behind the detected façades planes (indoor points). Regularities in the appearance of these points are of special interest to enable the detection of windows which are only weakly represented in the point cloud. Therefore it is checked with a Fourier Transform if a repetitive structure can be extracted. Otherwise peaks in the density of the indoor points are used to detect the windows. The approach is tested on data from four overflights over the area around the TU München. The tests show that windows having a repetitive structure can be detected well for larger façade parts which provide enough samples but the approach shows deficits for small façade parts and in the case of disturbing intrusions.
Decadal Variations of the Mindanao Current During 1960–2010

Results from an eddy-resolving ocean model simulation, an ocean reanalysis data, and reduced-gravity ocean (RGO) model simulations reach consensus in suggesting prominent decadal fluctuations of the Mindanao Current (MC) during 1960-2010. The MC was evidently enhanced during 1974-1982 and 2002-2008 and weakened during 1983-1990 and 1994-2001, with typical amplitude of similar to 2.0Sv (1Sv10(6)m(3)/s) for decadal volume transport anomaly. These variations are closely associated with the strength of the westward flowing North Equatorial Current at 130 degrees E and not evidently related with its bifurcation latitude. Experiments using a 1.5-layer RGO model are performed to understand the mechanisms. Decadal variations of the MC are primarily caused by off-equatorial wind changes in the tropical North Pacific, and winds in the latitude range of the MC (3-13 degrees N) play the dominant role. Equatorial winds between 3 degrees S and 3 degrees N generally act to attenuate the MC variability, and subtropical winds have little contribution. For zonal distribution, local wind forcing between 120 and 160 degrees E explains 67.8% of the MC decadal variability, while those in the central and eastern Pacific have weaker effects (25.0% and 7.2%, respectively). RGO model runs forced by nine wind data sets confirm the tight relationship between the MC and the western Pacific winds since the 1980s. The anomalous westerly winds under El Nino-like condition drive upwelling in the Philippine Sea through off-equatorial Ekman pumping that strengthens the MC. The relationship prior to 1980 is sensitive to the choice of wind data set, with four data sets yielding low or negative correlations. Plain Language Summary The Mindanao Current (MC) is important in supplying water to the western Pacific warm pool and the Indonesian Throughflow. The MC variabilities on seasonal and interannual time scales have been intensively investigated, whereas decadal variability of the MC was rarely explored. In this study, we used ocean model simulations and ocean reanalysis data to explore the decadal variability of the MC during 1960-2010 and the underlying causes. It is found that the MC was stronger during 1974-1982 and 2002-2008 and weaker during 1983-1990 and 1994-2001. The typical amplitude is similar to 2.0Sv (1Sv10(6)m(3)/s). We also found that wind forcing in the tropical northwest Pacific region is most important in controlling the MC transport. These variations are largely determined by the strength of the North Equatorial Current at 130 degrees E rather than the North Equatorial Current's bifurcation latitude off the Philippine coast. Subtropical wind forcing north of 23 degrees N has little contribution, whereas equatorial winds between 3 degrees S and 3 degrees N generally act to attenuate the MC variability. A tight relationship is found between the MC and the western Pacific zonal winds in decadal variability, particularly after similar to 1980. By contrast, the correlation between the MC and El Nino-Southern Oscillation is low on decadal time scale.
On the utility of the multimodal problem generator for assessing the performance of evolutionary algorithms

This paper looks in detail at how an evolutionary algorithm attempts to solve instances from the multimodal problem generator. The paper shows that in order to consistently reach the global optimum, an evolutionary algorithm requires a population size that should grow at least linearly with the number of peaks. A close relationship is also shown between the supply and decision making issues that have been identified previously in the context of population sizing models for additively decomposable problems.The most important result of the paper, however, is that solving an instance of the multimodal problem generator is like solving a peak-in-a-haystack, and it is argued that evolutionary algorithms are not the best algorithms for such a task. Finally, and as opposed to what several researchers have been doing, it is our strong belief that the multimodal problem generator is not adequate for assessing the performance of evolutionary algorithms.
A compressed sensing radar detection scheme for closing vehicle detection

A compressed sensing radar detection scheme for closing vehicle detection is proposed in this paper. Because most of the man-made signals are cyclostationary, the cyclic autocorrelation domain of the target return signal is sparse. The compressed sensing radar detection scheme in this paper is designed based on the sparsity of the cyclic autocorrelation of the target return signal. From the measurements based on the compressed sensing of the cyclic autocorrelation, the actual cyclic autocorrelation of the signal can be reconstructed. From the simulation, the dissertation can be made that a very simple OMP algorithm can get a high probability of detection.
Global Dynamics of Stored Precipitation Water in the Topsoil Layer From Satellite and Reanalysis Data

The amount of soil water in the topsoil layer (from 0 to 10 cm) has been regarded as a key factor in controlling land‐atmosphere interaction by determining the fraction of net radiation. In the present study, we investigate spatial trends of the stored precipitation fraction in the topsoil layer for varying vegetation and aridity indices by utilizing four satellites and two reanalysis data sets on a global scale. Using the Budyko framework, we relate climate regimes to the stored precipitation fraction on a global scale. A positive relation between the stored precipitation fraction with aridity index and a negative relation between the stored precipitation fraction and free parameter, vegetation optical depth, and isohydric slope are discovered. Even though the stored precipitation fraction values were calculated from different soil moisture and precipitation sources, they share an similar spatial trend: the drier and less vegetated the soil is, the more precipitation is retained in the top layer of the soil. Specifically, the topsoil retains 37% ± 11% of precipitated water three days after a rainfall event where the aridity index was greater than 5. Over wet and forest areas, due to large runoff fluxes and plants intercepting water before the precipitated water reached the ground, the topsoil retains 21% ± 2% of precipitated water three days after a rainfall event. Furthermore, by using the modeled data sets in the calculation of the stored precipitation fraction metric, we are able to conduct a sensitivity analysis of FP(f) metrics with respect to different sampling frequency values.
Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data

ABSTRACT When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data.
A revisit to human action recognition from depth sequences: Guided SVM-sampling for joint selection

This paper revisits the problem of human action recognition from skeleton joint locations, and analyses the tradeoff of sampling the joint space with respect to the recognition performance and computational complexity. The provided insights led to the design of a new algorithm for automatically selecting the most appropriate set of joints for each action. During the training stage, the approach applies a guided joint sampling strategy for learning different SVM classifiers, selecting the classifier that maximizes confidence and ambiguity metrics. Experimental results on three action datasets show that pre-selecting the most varying skeleton joints for each action dramatically reduces the computational complexity while keeping competitive recognition rates.