Miracle-dz/UniFAR-FTUs huggingface dataset:
Interannual Variability of the Intraseasonal Oscillation and Its Impact on the Summertime Wave Patterns and Tropical Cyclones over the Western North Pacific

AbstractIn this study, intraseasonal oscillations (ISOs) and submonthly wave patterns were separated into maximal variance (MaxV) and minimal variance (MinV) years on the basis of ISO variance from July to October. The mean-state 850-hPa streamfunction for submonthly cases indicated that, in the MinV years, tropical cyclones (TCs) formed near areas southeast of those in the MaxV years. ISOs propagated northward in the MaxV years, whereas a weaker westward-propagating tendency was observed in the MinV years. Track analysis of the centers of the submonthly cyclonic anomalies suggested that the background flow dictated the propagation routes of the easterly cyclonic anomalies in the MaxV years. However, the propagation routes of the westerly cyclonic anomalies were barely affected by the background flow. Further analysis of the ISO mean flow patterns showed that in the MaxV years, the propagation routes of the westerly cyclonic anomalies were more likely controlled by the anomalous easterly flow generated by.
Metacognitive Awareness Towards Academic Learning

This descriptive research aimed to discover the level of metacognitive awareness towards academic learning to students of English Education Study Program of IKIP PGRI Pontianak. Cross sectional survey was implemented and 420 respondents were involved from all academic years and various backgrounds. The 52 items in Metacognitive Awareness Inventory by Schraw & Dennison (1994) wereadoptedwitheightindicatorsfromtwomainfactorsandthedatawasanalyzedindescriptivestatistics.Itisreportedthatthereisahighlevelofmetacognitive awarenesswiththescoreof86%. Thisfavorableoutcomewillbringasigniﬁcant beneﬁttostudentsbecausemetacognitiveawarenessisdirectlycorrelatedtovar-iousindicatorsofacademicsuccess,includingtheoverallgradepointaverage. Additionally,threeofthemostprominentindicatorsareDebuggingStrategies, ConditionalKnowledge,andEvaluation.Meanwhile,theleastappliedindicator isInformationManagementStrategies.Twocertainitemsthathaveaconsiderably muchlowerscorearetheoneaboutrememberinginformationandtheoneabout usingpicturesordiagraminthelearningprocess.Thisshowcasesthestudents’ uniquestrengthandweaknessinthemetacognitiveawarenessfactorsthatneedto behighlightedintheiracademiclearning.
When a Door Closes, a Window Opens? Long-term Labor Market Effects of Involuntary Separations

This study estimates the earning losses of workers experiencing an involuntary job separation. We employ, for the ﬁrst time in the earning losses literature, a Poisson pseudo-maximum-likelihood estimator with ﬁxed e ↵ ects that has several advantages with respect to conventional ﬁxed e ↵ ects models. The Poisson estimator allows considering the full set of involuntary separations, including those with zero labor market earnings because of unemployment. By including individuals with zero earnings and by using our new method, the loss in the year of separation becomes larger than in previous studies. The loss starts with roughly 30 percent and, although it quickly shrinks, it remains at around 15 percent in the following years. In addition, we ﬁnd that compared to other reasons for separation, the earning loss pattern is unique for involuntary separations, because no other type of separation implies such permanent scarring. This latter ﬁnding makes us conﬁdent that the self-reported involuntariness of a separation is a reliable source of information.
Photon Statistics in Disordered Lattices

Propagation of coherent waves through disordered media, whether optical, acoustic, or radio waves, results in a spatially redistributed random intensity pattern known as speckle – a statistical phenomenon. The subject of this dissertation is the statistics of monochromatic coherent light traversing disordered photonic lattices and its dependence on the disorder class, the level of disorder and the excitation configuration at the input. Throughout the dissertation, two disorder classes are considered, namely, diagonal and off-diagonal disorders. The latter exhibits disorder-immune chiral symmetry – the appearance of the eigenmodes in skew-symmetric pairs and the corresponding eigenvalues in opposite signs. When a disordered photonic lattice, an array of evanescently coupled waveguides, is illuminated with an extended coherent optical field, discrete speckle develops. Numerical simulations and analytical modeling reveal that discrete speckle shows a set of surprising features, that are qualitatively indistinguishable in both disorder classes. First, the fingerprint of transverse Anderson localization – associated with disordered lattices, is exhibited in the narrowing of the spatial coherence function. Second, the transverse coherence length (or speckle grain size) freezes upon propagation. Third, the axial coherence depth is independent of the axial position, thereby resulting in a coherence voxel of fixed volume independently of position. When a single lattice site is coherently excited, I discovered that a thermalization gap emerges for light propagating in disordered lattices endowed with disorder-immune chiral symmetry. In these systems, the span of sub-thermal photon statistics is inaccessible to the input coherent light, which – once the steady state is reached – always emerges with super-thermal statistics no matter how small the disorder level. An independent constraint of the input field for the chiral symmetry to be activated and the gap to be observed is formulated. This unique feature enables a new form of photon-statistics interferometry: by exciting two lattice sites with a variable relative phase, as in a traditional two-path interferometer, the excitation-symmetry of the chiral mode pairs is judiciously broken and interferometric control over the photon statistics is exercised, spanning sub-thermal and super-thermal regimes. By considering an ensemble of disorder realizations, this phenomenon is
Bayesian Method for Source Local Deduplication in Cloud Backup Services

: Data deduplication technique is widely deployed in cloud backup storage system to reduce storage space and to minimize the transmission of redundant data for proper utilization of network bandwidth. During cloud backup service, redundancy of typical backup data dominated heavily by duplicate chunks. The intrinsic drawback of this system is detecting the similar chunks.The storage server consists of large volume of chunks, making the duplicate detection process much more complicated which decreases deduplication efﬁciency and increases deduplication overhead. In this paper we propose Bayesian method for source local deduplication for ﬁnding out duplicate chunks. For ﬁnding chunk similarity, the learning based similarity metrics are developed. The data features are used to train Bayesian system. Our experimental results shows that precision, recall and F measure values are high compared to SVM and GP. Due to these high values the proposed Bayesian method increases deduplication efﬁciency and reduces deduplication overhead. Therefore the proposed Bayesian method yields better performance than Support Vector Machine Model and Genetic approach.
A non-convex optimization algorithm for joint DDE calibration and imaging in radio interferometry

Radio-interferometric imaging aims to estimate an unknown sky intensity image from degraded observations, acquired through an antenna array. In the theoretical case of a perfectly calibrated array, it has been shown that solving the corresponding imaging problem by iterative algorithms based on convex optimization and compressive sensing theory can be competitive with classical algorithms as CLEAN. However, in practice, antenna-based gains are unknown and have to be calibrated. Future radio telescopes, such as the SKA, aim at improving imaging resolution and sensitivity by orders of magnitude. At this precision level, the direction-dependency of the gains must be accounted for, and radio-interferometric imaging can be understood as a blind deconvolution problem. In this context, the underlying minimization problem is non-convex, and adapted techniques have to be designed. In this work, leveraging recent developments in non-convex optimization, we propose the first joint calibration and imaging method in radio interferometry, with proven convergence guarantees. Our approach, based on a block-coordinate forward-backward algorithm, jointly accounts for visibilities and suitable priors on both the image and the direction-dependent effects (DDEs). As demonstrated in recent works, sparsity remains the prior of choice for the image, while DDEs are modelled as smooth functions of the sky, i.e. spatially band-limited. Finally, we show through simulations the good performance of our method, for the reconstruction of both point sources images and complex extended sources. MATLAB code is available on GitHub.
Investigation of p‐contact performance for indium rich InGaN based light emitting diodes and solar cells

We report on the optimization of p‐GaN layers for high indium (In) content InGaN applications by optimizing temperature, precursor CP2Mg flow rate and III/V ratio and report also on the optimization of p‐contact performance. Using MOVPE, a 150 nm thick p‐type GaN with moderate Mg doping and a 50 nm contact layer with high Mg doping concentration were grown on standard GaN templates at growth temperatures in the range of 850–1000 °C. Hall measurement yields hole concentration of 4.8 × 1017 cm−3 for the optimized sample. SIMS shows Mg concentration of 1.7 × 1020 cm−3 on average in the heavily doped and 4 × 1019 cm−3 on average in the moderately doped p‐GaN layer for the optimized p‐GaN. A multilayer Pd/Ag/Ni/Au metal contact has been deposited on this p‐GaN and studied using the CTLM technique. Optimization of both p‐GaN layers and p‐contact processing led to a low resistance contact with specific contact resistivity of 6 × 10−4 Ω cm2. We believe, the very high Mg concentration of the surface layer in intimate contact with the contact metal reduces the Schottky barrier height and band bending. This optimization of p‐GaN is an important step towards high efficiency green LEDs and solar cells.
Using Meeting Artifacts to Learn About Unobserved Group Dynamics

It can be useful to model small-group interactions in meetings, but in many cases we do not have audio or video recordings of the meeting itself. However, we very often have meeting artifacts in the form of notes, summaries, slides, and emails. In this work, we investigate whether analysis of some of these artifacts can shed light on aspects of the unobserved group interaction that are not explicitly mentioned within the meeting artifact documents. We present some early positive results on the feasibility of this task.
Balancing Human Rights and Restorative Justice: A Study Case for Compulsory Attendance Order Sentence in Malaysia

Compulsory Attendance Order (CAO) is an alternative punishment provided under the Offenders Compulsory Attendance Act 1954 [Act 461]. It serves as a punishment in lieu of custodial sentence such as imprisonment, and usually imposed by the court on person who has been convicted of certain offences. Based on the case laws in Malaysia, although imposing CAO as a punishment is quite a rarity, however there were few notable instances where the CAO punishment was imposed on the offenders. This article intends to explain the concept of CAO punishment in Malaysia, and to elucidate the readers on the relevant laws regulating this area of law. Comparative studies on the legal provisions in United Kingdom and Hong Kong will be made, particularly on the aspect of purpose and age requirement in imposing CAO punishment. This article further provides several suggestions to ensure that the effectiveness of CAO punishment is maintained and further improved.
Phase-field modelling of fatigue crack propagation TME131 Project in Applied Mechanics 2023

Fracture prediction and modeling are crucial in studying the behavior of materials under stress. This research focuses on utilizing the phase field method for accurate fracture prediction, which offers distinct advantages over traditional methods by representing fractures implicitly as smooth fields. The phase field method was implemented and analyzed using Matlab and COMSOL as tools, aiming to investigate and gain insights into the ease and feasibility of phase-field modelling for fatigue fracture problems. This was conducted mainly by introducing a fatigue degradation function, with the purpose of simulating the degrading process of the material after repeated cyclic loading. Through comprehensive analysis, quantities of interest such as the history variable, accumulated strain energy, and damage variable were examined. The obtained trends and results were found to align with existing literature, although neither calibration nor validation was conducted due to time limitations. Suggestions for future work include implementing a force-controlled load, calibration of the fatigue degradation function for a larger amount of load cycles, and validation with experimental data. Nevertheless, the results obtained from the fatigue implementation can provide a solid foundation for continued research. In conclusion, the progress during the project highlighted the potential of the phase-field model to predict fatigue fracture by modelling the crack through a damage field. Hence, fatigue prediction using phase-field modelling has the potential to make significant progress and thus contribute to less computationally expensive simulations for more complex fatigue fracture problems.
Critical Phenomena in Nonequilibrium Systems

This review addresses recent developments in nonequilibrium statistical physics. Focusing on phase transitions from fluctuating phases into absorbing states, the universality class of directed percolation is investigated in detail. The survey gives a general introduction to various lattice models of directed percolation and studies their scaling properties, fieldtheoretic aspects, numerical techniques, as well as possible experimental realizations. In addition, several examples of absorbing-state transitions which do not belong to the directed percolation universality class will be discussed. As a closely related technique, we investigate the concept of damage spreading. It is shown that this technique is ambiguous to some extent, making it impossible to define chaotic and regular phases in stochastic nonequilibrium systems. Finally, we discuss various classes of depinning transitions in models for interface growth which are related to phase transitions into absorbing states.
D O I DEOLOGICAL AND P OLITICAL M OTIVES R EALLY M ATTER IN THE P UB-LIC C HOICE OF L OCAL S ERVICES M ANAGEMENT ? E VIDENCE FROM U RBAN W ATER S ERVICES IN S PAIN

- According to the literature, local government decisions regarding the management of municipal services are mainly based on pragmatic reasons, ideological and political motives having little influence. However, in some municipal services, such as the urban water service, ideological and political factors could play a more relevant role when it comes to deciding the management alternative. The aim of this paper is to study the influence of ideological and political motives on the choice of management for the urban water service in 734 municipalities located in the south of Spain. One of our contributions is that we use a considerably more detailed set of variables representing political and ideo-logical motives than most of the previous research. Similarly, the value of the variables that explain local politicians’ decisions is that observed at the time decision making occurs and not at a later date. Our results reveal that the two largest parties disputing the centre of the Spanish political spectrum employ similar strategies when choosing a management alternative for the water service. However, the city councils governed by the most left-wing party are more reluctant to privatise. Finally, political variables such as stakeholder lobbying affect local government decision making.
Climate Shocks and (very) Long-Run Productivity (cid:3)

The present study examines the link between temperature and long-run productivity for a balanced panel of 21 countries, covering the period 1000(cid:150)1800 CE. Collectively the countries examined accounted for about 2/3 of the global population by 1700. Each epoch in the analysis is a century long, which thus allows time for human adaptation after a temperature shock has occurred. Our principal (cid:133)nding is that lower temperatures worked to reduce productivity growth during the period in focus, consistent with contributions to the literature in economic history that argue the Little Ice Age was as a contractionary shock.
RNF4 interacts with multiSUMOylated ETV4 [version 2; peer review: 2 approved]

Protein SUMOylation represents an important regulatory event that changes the activities of numerous proteins. Recent evidence demonstrates that polySUMO chains can act as a trigger to direct the ubiquitin ligase RNF4 to substrates to cause their turnover through the ubiquitin pathway. RNF4 uses multiple SUMO interaction motifs (SIMs) to bind to these chains. However, in addition to polySUMO chains, a multimeric binding surface created by the simultaneous SUMOylation of multiple residues on a protein or complex could also provide a platform for the recruitment of multi-SIM proteins like RNF4. Here we demonstrate that multiSUMOylated ETV4 can bind to RNF4 and that a unique combination of SIMs is required for RNF4 to interact with this multiSUMOylated platform. Thus RNF4 can bind to proteins that are either polySUMOylated through a single site or multiSUMOylated on several sites and raises the possibility that such multiSIM-multiSUMO interactions might be more widespread.
Implicit Projection: Improving Team Situation Awareness for Tacit Human-Robot Interaction via Virtual Shadows

Fluent teaming is characterized by tacit interaction without explicit communication. Such interaction requires team situation awareness (TSA) to facilitate. However, existing approaches often rely on explicit communication (such as visual projection) to support TSA, resulting in a paradox. In this paper, we consider implicit projection (IP) to improve TSA for tacit human-robot interaction. IP minimizes interruption and can thus reduce the cognitive demand to maintain TSA in teaming. We introduce a novel process for achieving IP via virtual shadows (referred to as IPS). We compare our method with two baselines that use explicit projection to maintain TSA. Results via human factors studies demonstrate that IPS supports better TSA and significantly improves unsolicited human responsiveness to robots, a key feature of fluent teaming. Participants acknowledged robots implementing IPS more favorable as a teammate. Simultaneously, our results also demonstrate that IPS is comparable to, and sometimes better than, the best-performing baselines on information accuracy.
Robust Visual Tracking with Improved Subspace Representation Model

In this paper, we propose a robust visual tracking with an improved subspace representation model. Different from traditional subspace representation model, we use sparse representation, but not the collaborative representation to reconstruct the observation samples, which can avoid the redundant object features in subspace effectively. Moreover, to reject the outliers in the process of tracking, we also propose the combination of sparse box templates and Laplacian residual. To solve the minimization problem of object representation efficiently, a fast numerical algorithm that accelerated proximal gradient (APG) approach is proposed for the Lagrangian function. Finally, experimental results on several challenging video sequences show better performance than LSST and many state-of-the-art trackers.
SLIPI-LIF/Mie For Droplet Sizing In 3D: A Study Of Calibration Variations As A Function Of Injection Pressure

SLIPI-LIF/Mie (standing for Structured Laser Illumination Planar Imaging Laser-Induced Fluorescence / Mie scattering ratio) is a well-recognized technique for providing spatially resolved 2D measurement of the droplet Sauter Mean Diameter (SMD) within optically dense sprays. This can indeed be achieved as the SLIPI approach allows suppressing the unwanted intensity contribution of multiple light scattering. For droplet sizing, a calibration procedure is then required, where the LIF/Mie intensity ratio as a function of the SMD is deduced, using for example Phase Doppler Anemometry (PDA). We show here that for a given operating condition a single calibration curve is reliable at any position in the spray. However, we observe that this calibration is dependent on the liquid injection pressure. Thus, the calibration curves must be modified for each injection pressure employed. The knowledge of this calibration curve variation is essential during any parametric spray study, where the operating conditions are modified. The need of performing the calibration procedure in the exact same conditions than for the experimental measurements is shown here. A correction of the calibration curve as a function of injection pressure is also proposed in this article. Note that further investigations will be needed to understand the observed trend. Finally, the methodology has been applied over a series of 15 planes spaced by 2 mm to reconstruct the droplet SMD in 3D.
DO PERSONALITIES AND MOTIVATION AFFECT JOB PERFORMANCE? AN EVIDENCE FROM A RURAL BANK IN CENTRAL JAVA

Good employee performance is the main thing for the company. Poor performance will cause the company to suffer losses, or it can even experience bankruptcy and liquidation. Until now, many rural banks in Indonesia are experiencing liquidation, so it is necessary to find a solution to improve the performance of rural bank employees in Indonesia so that liquidation can be avoided. This research aims to examine whether the big five personalities of employees and employee motivation can affect job performance. Data were collected from 50 employees of a rural bank X, in Central Java. Multiple regression analysis was used to analyze the data. The findings of this study are that the big five personality does not have a significant effect, while employee motivation has a significant effect. However, simultaneously these two variables can affect job performance.
Moist convection and its upscale effects in simulations of the Indian monsoon with explicit and parametrized convection

In common with many global models, the Met Office Unified Model (MetUM) climate simulations show large errors in Indian summer monsoon rainfall, with a wet bias over the equatorial Indian Ocean, a dry bias over India, and with too weak low‐level flow into India. The representation of moist convection is a dominant source of error in global models, where convection must be parametrized, with the errors growing quickly enough to affect both weather and climate simulations. Here we use the first multi‐week continental‐scale MetUM simulations over India, with grid spacings that allow explicit convection, to examine how convective parametrization contributes to model biases in the region.