Miracle-dz/UniFAR-FTUs huggingface dataset:
Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin-Destination Flows

This paper examines two different approaches for real-time estimation/prediction of time-dependent Origin--Destination (O--D) flows. Both approaches lend themselves to formulation as state-space models. The first approach is an extension of previous work by the authors. The key idea in this approach is to define the state-vector in terms of deviations in O--D flows instead of the O--D flows themselves. We demonstrate that approximations to this model make the real-time estimation process computationally more tractable with little deterioration in quality of estimates. In the second approach, the state vector is defined in terms of deviations of departure rates from each origin and the shares headed to each destination. This approach attempts to capture the differential variation of departure rates and shares over time. Performance of the proposed models is evaluated using actual traffic data from different sources. Preliminary results indicate that the filtering procedure is robust and that, compared to the original model, a formulation based on departure rates and shares yields better predictions with some loss of accuracy in filtered estimates.
Concurrent vowel identification. III. A neural model of harmonic interference cancellation

This paper presents a “neural cancellation filter” capable of segregating weak targets from competing harmonic backgrounds, and a model of concurrent vowel segregation based upon it. The elementary cancellation filter comprises a delay line and an inhibitory synapse. Filters within each peripheral channel are tuned to the period of the competing sound to suppress its correlates within the neural discharge pattern. In combination with a pattern matching model based on autocorrelation functions summed over channels, the cancellation filter forms a model of concurrent vowel identification. The model predicts the number of vowels reported for each stimulus (when subjects are allowed to report one or two) and identification rates. It belongs to the class of “harmonic cancellation” models that are supported by experimental evidence that vowel identification is better when competing sounds are harmonic than inharmonic. Two alternative schemes using the same filter are also considered. One derives a “place” repre.
Accumulation of the Drosophila Torso-like protein at the blastoderm plasma membrane suggests that it translocates from the eggshell

The eggshell serves as a depository for proteins that play an important role in early embryonic development. In particular, the Drosophila eggshell is responsible for transferring asymmetries from the egg chamber to specify the regions at both ends of the embryo through the uneven activation of the Torso (Tor) receptor in its membrane. This process relies on the restricted expression of the gene torso-like (tsl) in subpopulations of follicle cells during oogenesis and its protein accumulation at both poles of the eggshell, but it is not known how this signal is transmitted to the embryo. Here, we show that Tsl accumulates at the embryonic plasma membrane, even in the absence of the Tor receptor. However, during oogenesis, we detected Tsl accumulation only at the eggshell. These results suggest that there is a two-step mechanism to transfer the asymmetric positional cues from the egg chamber into the early embryo: initial anchoring of Tsl at the eggshell as it is secreted, followed by its later translocation to the egg plasma membrane, where it enables Tor receptor activation. Translocation of anchored determinants from the eggshell might then regulate the spatial and temporal control of early embryonic developmental processes. Summary: The translocation of Torso-like from the eggshell membrane to the oocyte plasma membrane regulates the spatial and temporal control of body plan specification during Drosophila oogenesis.
A Threshold Selection Technique

Threshold selection for picture segmentation is relatively easy when the frequency distribution of gray levels in the picture is strongly bimodal, with the two peaks comparable insize and separated by a deep valley. This report describes a method of handling cases in which the peaks are very unequal in size and the valley is broad. A Laplacian operation is applied to the picture to determine points that lie on or near the edges of objects. Threshold selection becomes easier when the frequency distribution of gray levels of these points is used.
Heuristic Strategies for Recommendation of Exception Handling Code

Software developers have difficulties in implementing exception handling code in their systems. In particular, they fail in implementing appropriate handling actions. Not surprisingly, recurring failures and performance issues are often related to the poor exception handling actions implemented in real software systems. In this paper we propose, implement and evaluate a set of three heuristic strategies used to recommend exception handling code in programming tasks. Given a method in which the developer wants to handle an exception, the heuristics recommend a list of code fragments implementing exception handling. The heuristics' goal is to accurately find code fragments implementing exception handling and recommend these fragments according to the context of developers' implementation task. Hence, the proposed heuristics may assist developers in the process of discovering exception handling actions relevant to their context by providing concrete examples. We believe that a recommender system based on the proposed heuristics may be used in the future as a tool for aiding exception handling implementation.
Discovery of technical expertise from open source code repositories

Online Question and Answer websites for developers have emerged as the main forums for interaction during the software development process. The veracity of an answer in such websites is typically verified by the number of 'upvotes' that the answer garners from peer programmers using the same forum. Although this mechanism has proved to be extremely successful in rating the usefulness of the answers, it does not lend itself very elegantly to model the expertise of a user in a particular domain. In this paper, we propose a model to rank the expertise of the developers in a target domain by mining their activity in different opensource projects. To demonstrate the validity of the model, we built a recommendation system for StackOverflow which uses the data mined from GitHub.
Operator Variational Inference

Variational inference is an umbrella term for algorithms which cast Bayesian inference as optimization. Classically, variational inference uses the Kullback-Leibler divergence to define the optimization. Though this divergence has been widely used, the resultant posterior approximation can suffer from undesirable statistical properties. To address this, we reexamine variational inference from its roots as an optimization problem. We use operators, or functions of functions, to design variational objectives. As one example, we design a variational objective with a Langevin-Stein operator. We develop a black box algorithm, operator variational inference (OPVI), for optimizing any operator objective. Importantly, operators enable us to make explicit the statistical and computational tradeoffs for variational inference. We can characterize different properties of variational objectives, such as objectives that admit data subsampling---allowing inference to scale to massive data---as well as objectives that admit variational programs---a rich class of posterior approximations that does not require a tractable density. We illustrate the benefits of OPVI on a mixture model and a generative model of images.
Streambox: Modern Stream Processing on a Multicore Machine

Recently, there is an emerging interest in datacenter resource disaggregation, an architecture that breaks monolithic servers into independent hardware components connected through network. OSes built for monolithic computers can not handle the distributed nature of disaggregated hardware components. Datacenter distributed systems are built for managing clusters of monolithic computers, not individual hardware components. When traditional OS operations spread across hardware components over the network, these distributed systems fall short. Clearly, we need a new operating system for the disaggregated architecture. We propose the concept of decomposed operating system for the disaggregated datacenter architecture. The basic idea is simple: When hardware is disaggregated, the operating system should be also.
Spatial consequences of urban densification policy: Floor-to-area ratio policy in Tehran, Iran

The purpose of this paper is to investigate the effect of the urban densification policies made after the Islamic Revolution on the urban spatial structure of Tehran as the most important metropolis in Iran. The Hot Spot approach based on the Getis Ord Local G statistical test and Arc GIS 10.2 software was employed in this study. The advantage of the Geo-statistic technique used in this study is that this model does not require the exact location of the city centre to map and determine its spatial structure. The results show that the spatial structure of Tehran was affected by the non-spatial densification policies for 30 years (until Tehran’s Master Plan in 2007). Furthermore, these policies were greatly dependent on the financial benefits from the sale of the FAR permission and fines related to the ignorance of the lawful regulations. There is a spatial imbalance between the population and activity distribution patterns in the structure of Tehran. However, the negative spatial consequences of the densification policies are declining capacity of the city centre and the inner wards in retaining the population, and growing population density in the northern outer wards of Tehran.
A Moist Entropy Budget View of the South Asian Summer Monsoon Onset

Using a high‐resolution global model with explicit representation of convection, the physical processes involved in the abrupt onset of South Asian summer monsoon are investigated within a moist entropy budget framework. The monsoon onset is a two‐stage transition. During the first stage, which starts around 2 months before onset, the source terms of column‐integrated moist entropy gradually increase, while the export by the large‐scale circulation slowly strengthens. The second stage is marked by a sudden increase of radiative heating and surface latent heat flux 10 days prior to the onset, followed by abrupt strengthening of large‐scale export of moist entropy. When either cloud‐radiative or wind‐evaporation feedback is disabled in numerical experiments, the monsoon experiences much smoother and weaker onset. The evolution of the system in a gross moist stability plane demonstrates that these positive feedbacks destabilize the system and are responsible for the abruptness of the transition.
Impacts of nucleating aerosols on the evolution of an idealized tropical cyclone

A large number of tropical cyclones (TCs) have been observed to interact with the Saharan Air Layer (SAL), which is an elevated atmospheric layer over the eastern North Atlantic Ocean characterized by hot, dry, and dusty air drifted from the Saharan desert. Hurricane Cindy (1999), Floyd (1999), Debby (2000), Joyce (2000), Felix (2001) and Erin (2001) are such examples (Dunion and Velden, 2004). Dunion and Velden (2004) showed that the SAL tends to suppress Atlantic tropical cyclone activity by introducing dry, stable air into the storm and inhibiting convection. However, the role of dust in the SAL acting as nucleating aerosols on the tropical cyclone development has yet to be investigated.
Prediction of the Bilinear Stress-Strain Curve of Engineering Material by Nanoindentation Test

Instrumented indentation is widely used to probe the elastic and plastic properties of engineering materials. Finite Element Method (FEM) has been widely used for numerical simulation of indentation tests on bulk and film material in order to analyze its deformation response. This study proposed an improved technique to determine the stress-strain curve of bulk material. FEM in conjunction with an abductive network is used to predict the stress-strain relationship of bilinear elastic-plastic material from the nanoindentation test’s force-displacement curve.
DP-Miner: Design Pattern Discovery Using Matrix

Design patterns document expert design experience in software system development. They have been applied in many existing software systems. However, pattern information is generally lost in the source code. Discovering design patterns from source code may help understand system designs and further change the systems. In this paper, we present a novel approach to discovering design patterns by defining the structural characteristics of each design pattern in terms of weight and matrix. Our discovery process includes several analysis phases. Our approach is based on the XMI standard so that it is compatible with other techniques following such standard. We also develop a toolkit to support our approach. An industrial size case study is conducted to evaluate our approach and tool
CR-EST: a resource for crop ESTs

The crop expressed sequence tag database, CR-EST (http://pgrc.ipk-gatersleben.de/cr-est/), is a publicly available online resource providing access to sequence, classification, clustering and annotation data of crop EST projects. CR-EST currently holds more than 200 000 sequences derived from 41 cDNA libraries of four species: barley, wheat, pea and potato. The barley section comprises approximately one-third of all publicly available ESTs. CR-EST deploys an automatic EST preparation pipeline that includes the identification of chimeric clones in order to transparently display the data quality. Sequences are clustered in species-specific projects to currently generate a non-redundant set of ∼22 600 consensus sequences and ∼17 200 singletons, which form the basis of the provided set of unigenes. A web application allows the user to compute BLAST alignments of query sequences against the CR-EST database, query data from Gene Ontology and metabolic pathway annotations and query sequence similarities from stored BLAST results. CR-EST also features interactive JAVA-based tools, allowing the visualization of open reading frames and the explorative analysis of Gene Ontology mappings applied to ESTs.
Under Consideration for Publication in Theory and Practice of Logic Programming a Pigeon-hole Based Encoding of Cardinality Constraints

In this paper, we propose a new encoding of the cardinality constraint ∑ n i=1 x i b. It makes an original use of the general formulation of the PigeonHole principle to derive a formula in conjunctive normal form (CNF). Our PigeonHole based CNF encoding can be seen as a nice and simple way to express the semantic of the cardinality constraint, that can be defined as how to put b pigeons into n holes. To derive an efficient CNF encoding that ensures constraint propagation, we exploit the set of symmetries of the PigeonHole based formulation to derive an efficient CNF encoding of the cardinality constraint. More interestingly, the final CNF formula contains is b × (n − b) variables and clauses and belongs to the well-known Reverse-Horn tractable CNF formula, which can be decided by unit propagation. Our proposed PigeonHole based encoding is theoretically compared with the currently well-known CNF encoding of the cardinality constraint.
MAPPING GLOBAL OCEAN SURFACE ALBEDO FROM SATELLITE OBSERVATIONS: MODELS, ALGORITHMS, AND DATASETS

Abstract. Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.
MOM22 is a receptor for mitochondrial targeting sequences and cooperates with MOM19.

Recognition of targeting signals is a crucial step in protein sorting within the cell. So far, only a few components capable of deciphering targeting signals have been identified, and insights into the chemical nature of the interaction between the signals and their receptors are scarce. Using highly purified mitochondrial outer membrane vesicles, we demonstrate that MOM22 and MOM19, components of the protein import complex of the outer membrane, bind preproteins at the mitochondrial surface in a reversible fashion. Interaction specifically and directly occurs with the N‐terminal presequence and is abolished after inactivation of either MOM22 or MOM19. Binding is salt sensitive, suggesting that recognition involves electrostatic forces between the positive charges of the presequence and the acidic cytosolic domain of MOM22. MOM19 and MOM22 can be cross‐linked with high efficiency. We propose that the two proteins form a complex which functions as the presequence receptor at the mitochondrial surface and facilitates the movement of preproteins into the translocation pore.
Fast methods for estimating the Numerical rank of large matrices

We present two computationally inexpensive techniques for estimating the numerical rank of a matrix, combining powerful tools from computational linear algebra. These techniques exploit three key ingredients. The first is to approximate the projector on the non-null invariant subspace of the matrix by using a polynomial filter. Two types of filters are discussed, one based on Hermite interpolation and the other based on Chebyshev expansions. The second ingredient employs stochastic trace estimators to compute the rank of this wanted eigen-projector, which yields the desired rank of the matrix. In order to obtain a good filter, it is necessary to detect a gap between the eigenvalues that correspond to noise and the relevant eigenvalues that correspond to the nonnull invariant subspace. The third ingredient of the proposed approaches exploits the idea of spectral density, popular in physics, and the Lanczos spectroscopic method to locate this gap.
A Practical Algorithm for Intersecting Weighted Context-free Grammars with Finite-State Automata

It is well known that context-free parsing can be seen as the intersection of a context-free language with a regular language (or, equivalently, the intersection of a context-free grammar with a finite-state automaton). The present article provides a practical efficient way to compute this intersection by converting the grammar into a special finite-state automaton (the GLR(0)-automaton) which is subsequently intersected with the given finite-state automaton. As a byproduct, we present a generalisation of Tomita's algorithm to recognize several inputs simultaneously.
An effective heuristic for due-date-constrained Bag-of-Tasks scheduling problem for total cost minimization on hybrid clouds

Bag-of-Tasks (BoT) applications consisting of multiple tasks widely exist in numerous fields. As customers use cloud resources in a pay-as-you-go way, they are willing to execute BoT applications on clouds. Cloud providers and customers establish contracts in which applications' due dates are specified. If an application cannot be finished before the due date, the cloud provider should pay a tardiness penalty. When the private cloud has insufficient available resources to afford all customer-submitted BoT applications, the cloud provider has to outsource some tasks to public clouds with resource-used costs. The key challenge here is how to schedule tasks on hybrid clouds to minimize the total cost, including all applications' tardiness penalties and the cost of using public clouds' resources. We study and formulate this problem as an Integer Programming. Accordingly, we propose an effective greedy heuristic (GH) including two phases (task ordering and task scheduling). GH uses an Earlier Latest Start Time First method (ELSTF) for task ordering with the result that a task sequence is obtained. A Task Dispatching method (TD) is established for the task scheduling, in which each task in the obtained task sequence is scheduled one by one. Experimental results demonstrate that the proposed GH outperforms the baseline (RoundRobin) remarkably. ELSTF and TD are also verified to be effective.
Energy Storage Valuation Under Different Storage Forms and Functions in Transmission and Distribution Applications

In this paper, we analyze and quantify functional value streams of energy storage under different forms (state in which energy is stored) and network location (e.g., transmission or distribution sides). First, we consider a transmission-connected thermal form of storage coupled with concentrating solar power. Using the California power grid as a case study, we show that the coupled unit is significantly less volatile in its response and, through its load following, day-ahead dispatching, and regulation capabilities, it produces significant cost savings. Another case study examines the value of the electrical form of storage in a distribution network and in coupling with photovoltaics. The energy storage is used to mitigate component overloads and to reduce the subsequent infrastructure investments, and smooth out the intermittency of renewable generation. Storage value is quantified formally and under optimal control configuration of storage charge and discharging. Finally, a case study is constructed to examine the functional value of substation-sited storage with respect to investment deferral for the substation transformer.