Miracle-dz/UniFAR-FTUs huggingface dataset:
Mitochondrial Dynamics Associated with Oxygen-Glucose Deprivation in Rat Primary Neuronal Cultures

Our objective was to investigate the mitochondrial dynamics following oxygen-glucose deprivation (OGD) in cultured rat cortical neurons. We documented changes in morphology, protein expression, and DNA levels in mitochondria following OGD and examined the roles of mitochondrial fission [dynamin-related protein 1 (Drp1), fission protein-1 (Fis1)] and fusion [mitofusin-1 (Mfn1), mitofusin-2 (Mfn2), and optic atrophy-1 protein (OPA1)] proteins on mitochondrial biogenesis and morphogenesis. We tested the effects of two Drp1 blockers [15-deoxy-Δ12,14-Prostaglandin J2 (PGJ2) and Mitochondrial Division Inhibitor (Mdivi-1)] on mitochondrial dynamics and cell survival. One hour of OGD had minimal effects on neuronal viability but mitochondria appeared condensed. Three hours of OGD caused a 60% decrease in neuronal viability accompanied by a transition from primarily normal/tubular and lesser number of rounded mitochondria during normoxia to either poorly labeled or small and large rounded mitochondria. The percentage of rounded mitochondria remained the same. The mitochondrial voltage-dependent anion channel, Complex V, and mitoDNA levels increased after OGD associated with a dramatic reduction in Drp1 expression, less reduction in Mfn2 expression, an increase in Mfn1 expression, with no changes in either OPA1 or Fis1. Although PGJ2 increased polymerization of Drp1, it did not reduce cell death or alter mitochondrial morphology following OGD and Mdivi-1 did not protect neurons against OGD. In summary, mitochondrial biogenesis and maintained fusion occurred in neurons along with mitochondrial fission following OGD; thus Mfn1 but not Drp1 may be a major regulator of these processes.
Developing Affective Lexical Resources

Affective computing is advancing as a field that allows a new form of human computer interaction, in addition to the use of natural language. There is a wide perception that the future of human-computer interaction is in themes such as entertainment, emotions, aesthetic pleasure, motivation, attention, engagement, etc. Studying the relation between natural language and affective information and dealing with its computational treatment is becoming crucial. In this paper we present a linguistic resource for a lexical representation of affective knowledge. This resource (named WORDNET-AFFECT) was developed starting from WORDNET, through the selection and labeling of the synsets representing affective concepts.
Robust camera location estimation by convex programming

3D structure recovery from a collection of 2D images requires the estimation of the camera locations and orientations, i.e. the camera motion. For large, irregular collections of images, existing methods for the location estimation part, which can be formulated as the inverse problem of estimating n locations t1, t2, . , tn in ℝ3 from noisy measurements of a subset of the pairwise directions ti-tj/∥ti-tj∥, are sensitive to outliers in direction measurements. In this paper, we firstly provide a complete characterization of well-posed instances of the location estimation problem, by presenting its relation to the existing theory of parallel rigidity. For robust estimation of camera locations, we introduce a two-step approach, comprised of a pairwise direction estimation method robust to outliers in point correspondences between image pairs, and a convex program to maintain robustness to outlier directions. In the presence of partially corrupted measurements, we empirically demonstrate that our convex formulation can even recover the locations exactly. Lastly, we demonstrate the utility of our formulations through experiments on Internet photo collections.
Large-scale identification and characterization of alternative splicing variants of human gene transcripts using 56 419 completely sequenced and manually annotated full-length cDNAs

We report the first genome-wide identification and characterization of alternative splicing in human gene transcripts based on analysis of the full-length cDNAs. Applying both manual and computational analyses for 56 419 completely sequenced and precisely annotated full-length cDNAs selected for the H-Invitational human transcriptome annotation meetings, we identified 6877 alternative splicing genes with 18 297 different alternative splicing variants. A total of 37 670 exons were involved in these alternative splicing events. The encoded protein sequences were affected in 6005 of the 6877 genes. Notably, alternative splicing affected protein motifs in 3015 genes, subcellular localizations in 2982 genes and transmembrane domains in 1348 genes. We also identified interesting patterns of alternative splicing, in which two distinct genes seemed to be bridged, nested or having overlapping protein coding sequences (CDSs) of different reading frames (multiple CDS). In these cases, completely unrelated proteins are encoded by a single locus. Genome-wide annotations of alternative splicing, relying on full-length cDNAs, should lay firm groundwork for exploring in detail the diversification of protein function, which is mediated by the fast expanding universe of alternative splicing variants.
The Metabolic Core and Catalytic Switches Are Fundamental Elements in the Self-Regulation of the Systemic Metabolic Structure of Cells

Background Experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a metabolic core formed by a set of enzymatic reactions which are always active under all environmental conditions, while the rest of catalytic processes are only intermittently active. The reactions of the metabolic core are essential for biomass formation and to assure optimal metabolic performance. The on-off catalytic reactions and the metabolic core are essential elements of a Systemic Metabolic Structure which seems to be a key feature common to all cellular organisms. Methodology/Principal Findings In order to investigate the functional importance of the metabolic core we have studied different catalytic patterns of a dissipative metabolic network under different external conditions. The emerging biochemical data have been analysed using information-based dynamic tools, such as Pearson's correlation and Transfer Entropy (which measures effective functionality). Our results show that a functional structure of effective connectivity emerges which is dynamical and characterized by significant variations of bio-molecular information flows. Conclusions/Significance We have quantified essential aspects of the metabolic core functionality. The always active enzymatic reactions form a hub –with a high degree of effective connectivity- exhibiting a wide range of functional information values being able to act either as a source or as a sink of bio-molecular causal interactions. Likewise, we have found that the metabolic core is an essential part of an emergent functional structure characterized by catalytic modules and metabolic switches which allow critical transitions in enzymatic activity. Both, the metabolic core and the catalytic switches in which also intermittently-active enzymes are involved seem to be fundamental elements in the self-regulation of the Systemic Metabolic Structure.
De Novo Characterization of Fall Dormant and Nondormant Alfalfa (Medicago sativa L.) Leaf Transcriptome and Identification of Candidate Genes Related to Fall Dormancy

Alfalfa (Medicago sativa L.) is one of the most widely cultivated perennial forage legumes worldwide. Fall dormancy is an adaptive character related to the biomass production and winter survival in alfalfa. The physiological, biochemical and molecular mechanisms causing fall dormancy and the related genes have not been well studied. In this study, we sequenced two standard varieties of alfalfa (dormant and non-dormant) at two time points and generated approximately 160 million high quality paired-end sequence reads using sequencing by synthesis (SBS) technology. The de novo transcriptome assembly generated a set of 192,875 transcripts with an average length of 856 bp representing about 165.1 Mb of the alfalfa leaf transcriptome. After assembly, 111,062 (57.6%) transcripts were annotated against the NCBI non-redundant database. A total of 30,165 (15.6%) transcripts were mapped to 323 Kyoto Encyclopedia of Genes and Genomes pathways. We also identified 41,973 simple sequence repeats, which can be used to generate markers for alfalfa, and 1,541 transcription factors were identified across 1,350 transcripts. Gene expression between dormant and non-dormant alfalfa at different time points were performed, and we identified several differentially expressed genes potentially related to fall dormancy. The Gene Ontology and pathways information were also identified. We sequenced and assembled the leaf transcriptome of alfalfa related to fall dormancy, and also identified some genes of interest involved in the fall dormancy mechanism. Thus, our research focused on studying fall dormancy in alfalfa through transcriptome sequencing. The sequencing and gene expression data generated in this study may be used further to elucidate the complete mechanisms governing fall dormancy in alfalfa.
A combinatorial auction improves school meals in Chile: a case of OR in developing countries

The Chilean State delivers essential meal services at schools for low-income students. Junta Nacional de Auxilio Escolar y Becas, the institution in charge of covering 1,300,000 children, leases the meal service to private enterprises. We developed an integer linear programming model to assign the meal contracts, in a process known as combinatorial auctions. The resulting model, which is NP-hard, led to significant improvements in efficiency and also contributed to making the process more transparent. The results are apparent in substantial improvements in quality and coverage of the service, and important savings to the country, which are equivalent to feeding 300,000 children in addition. We developed techniques to solve the combinatorial models and also to analyze and compare multiple scenarios to find robust solutions. For the objective function of this problem, we analyzed several options to consider different kinds of social benefits. In this paper, we describe the problem, the methodology and the results. We also present empirical results based on 6 years of experience. Finally, we discuss the relevance and impact of using operations research in these central issues in developing countries.
The MJO‐Kelvin wave transition

As the Madden‐Julian oscillation (MJO) moves eastward from the Indian to the Pacific ocean, it typically accelerates, becomes less strongly coupled to convection, and becomes more similar to a dry Kelvin wave. This transition is analyzed using observations of outgoing longwave radiation and ERA Interim reanalyses of surface pressure and 850 hPa zonal wind. Two individual example events as well as composites are shown. The transitions are well defined, with distinct disturbances on either side of the transition whose identities as MJO or Kelvin waves are clear. In some cases there appears to be a pre‐existing Kelvin wave passing through the MJO from the west to the east, but this feature is not apparent in the composites. The transitions occur at different longitudes in different events, over a wide range from the eastern Indian to the central Pacific oceans.
The Affective Domain in Mathematics Learning

The present work set out to analyze the beliefs, attitudes, and emotional reactions that students experience in the process of learning mathematics. The aim was to be able to demonstrate that the existence of positive attributes, beliefs, and attitudes about themselves as learners are a source of motivation and expectations of success in dealing with this subject. We used a sample of 346 students of the second cycle of Obligatory Secondary Education (ESO) of high schools in Badajoz. The participants responded to a questionnaire on beliefs and attitudes about mathematics. It was found that neither the students' gender nor their year of studies influenced their beliefs about their self-concept of mathematics.
Global Coverage of Total Precipitable Water Using a Microwave Variational Algorithm

This study introduces a variational approach to retrieve total precipitable water (TPW) over all surface backgrounds including ocean, land, snow, sea-ice, and coastal areas, from microwave sensors. The product has been used routinely by forecasters since its recent operational implementation. The emissivity is accounted for by including its spectrum within the retrieved state vector, which allows for a pixel-to-pixel variation of the emissivity, a factor usually preventing the TPW retrieval over land. The algorithm, implemented operationally at the National Atmospheric and Oceanic Administration (NOAA), is called the Microwave Integrated Retrieval System (MiRS). Its main characteristic, besides its applicability over all surfaces, is its validity under all weather conditions. With a generic design, the algorithm is being applied to the following microwave sensors: (1) AMSU and MHS onboard NOAA-18; (2) NOAA-19 and Metop-A; as well as (3) SSMI/S onboard DMSP-F16 platform. The assessment of the MiRS performances is done by undertaking extensive comparisons to the National Center for Environmental Prediction (NCEP) and the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses, to a network of radiosondes and to existing well-established algorithms over ocean, encompassing a wide variety of meteorological situations. The performance of MiRS TPW is shown to depend on the sensor, the reference data source as well as on the surface background considered. It is shown to behave quite well over all surfaces and in all weather conditions, except when there is rain. Although this study focuses on the retrieval of TPW with an emphasis on non-oceanic surfaces, the underlying application of this study is the potential improvement in the variational data assimilation of Numerical Weather Prediction (NWP) models. Indeed, the same dynamic approach could be employed in order to assimilate more surface-sensitive microwave channels, over a multitude of surfaces.
Observing Software Testing Practice from the Viewpoint of Organizations and Knowledge Management

The objective of this qualitative study was to understand the complex practice of software testing, and based on this understanding, to develop hypotheses on testing organizations and knowledge management. The population of the study consisted of organizational units (OUs) that develop and test technical software for automation or telecommunication domains. First, a survey of testing practices was conducted and 26 OUs were interviewed. From this sample, five OUs were further selected for an in-depth case study. The study used grounded theory as its research method and the data was collected from 41 theme-based interviews. The analysis yielded hypotheses that included that the business orientation of an OU affects testing organization, knowledge management strategy, and outsourcing of testing. Further, identifying and avoiding barriers and using enablers improve knowledge transfer between development and testing. The results of this study can be used in developing the testing organization and the knowledge management strategy of an OU.
An Adaptive Cache Coherence Protocol Optimized for Producer-Consumer Sharing

Shared memory multiprocessors play an increasingly important role in enterprise and scientific computing facilities. Remote misses limit the performance of shared memory applications, and their significance is growing as network latency increases relative to processor speeds. This paper proposes two mechanisms that improve shared memory performance by eliminating remote misses and/or reducing the amount of communication required to maintain coherence. We focus on improving the performance of applications that exhibit producer-consumer sharing. We first present a simple hardware mechanism for detecting producer-consumer sharing. We then describe a directory delegation mechanism whereby the "home node" of a cache line can be delegated to a producer node, thereby converting 3-hop coherence operations into 2-hop operations. We then extend the delegation mechanism to support speculative updates for data accessed in a producer-consumer pattern, which can convert 2-hop misses into local misses, thereby eliminating the remote memory latency. Both mechanisms can be implemented without changes to the processor. We evaluate our directory delegation and speculative update mechanisms on seven benchmark programs that exhibit producer-consumer sharing using a cycle-accurate execution-driven simulator of a future 16-node SGI multiprocessor. We find that the mechanisms proposed in this paper reduce the average remote miss rate by 40%, reduce network traffic by 15%, and improve performance by 21%. Finally, we use Murphi to verify that each mechanism is error-free and does not violate sequential consistency
APPROXIMATION OF GENERALIZED HOMOMORPHISMS IN QUASI–BANACH ALGEBRAS

Let A be a quasi–Banach algebra with quasi-norm k . k A and B be a p-Banach algebra with p-norm k . k B. A linear mapping f : A → B is called a generalized homomorphism if there exists a homomorphism h ′ : A → B such that f(ab) = f(a)h ′ (b) for all a, b ∈ A. In this paper, we investigate generalized homomorphisms on quasi– Banach algebras, associated with the following functional equation rf( a + b r ) = f(a) + f(b). Moreover, we prove the generalized Hyers–Ulam–Rassias stability and superstability of generalized homomorphisms in quasi–Banach algebras.
Incremental Validity of Mindfulness‐Based Attention in Relation to the Concurrent Prediction of Anxiety and Depressive Symptomatology and Perceptions of Health

This investigation evaluated the role of mindfulness‐based attention in concurrently predicting anxiety and depressive symptomatology and perceived health functioning in a community sample of 170 young adults (95 females; mean age (Mage) = 22.2 years, SD = 7.6). Partially consistent with prediction, results indicated that, relative to negative and positive affectivity and emotional expression and processing associated with approach‐oriented coping, mindfulness‐based attention incrementally predicted anhedonic depressive, but not anxious arousal, symptoms. Additionally, consistent with prediction, mindfulness‐based attention demonstrated incremental validity in relation to perceived health, and the degree of impairment of health in terms of physical and mental functioning. Results are discussed in relation to the construct development of mindfulness‐based attention, and specifically, the role(s) of this factor in emotional and physical health processes.
Centre De Referència En Economia Analítica Barcelona Economics Working Paper Series the Persistence of Inflation in Oecd Countries: a Fractionally Integrated Approach the Persistence of Inflation in Oecd Countries: a Fractionally Integrated Approach. Barcelona Economics Wp Nº 259

The statistical properties of inflation and, in particular, its degree of persistence and stability over time is a subject of intense debate and no consensus has been achieved yet. The goal of this paper is to analyze this controversy using a general approach, with the aim of providing a plausible explanation for the existing contradictory results. We consider the inflation rates of 21 OECD countries which are modelled as fractionally integrated (FI) processes. First, we show analytically that FI can appear in inflation rates after aggregating individual prices from firms that face different costs of adjusting their prices. Then, we provide robust empirical evidence supporting the FI hypothesis using both classical and Bayesian techniques. Next, we estimate impulse response functions and other scalar measures of persistence, achieving an accurate picture of this property and its variation across countries. It is shown that the application of some popular tools for measuring persistence, such as the sum of the AR coefficients, could lead to erroneous conclusions if fractional integration is present. Finally, we explore the existence of changes in inflation inertia using a novel approach. We conclude that the persistence of inflation is very high (although non-permanent) in most post-industrial countries and that it has remained basically unchanged over the last four decades.
An adaptive MHD method for global space weather simulations

A 3D parallel adaptive mesh refinement (AMR) scheme is described for solving the partial-differential equations governing ideal magnetohydrodynamic (MHD) flows. This new algorithm adopts a cell-centered upwind finite-volume discretization procedure and uses limited solution reconstruction, approximate Riemann solvers, and explicit multi-stage time stepping to solve the MHD equations in divergence form, providing a combination of high solution accuracy and computational robustness across a large range in the plasma /spl beta/ (/spl beta/ is the ratio of thermal and magnetic pressures). The data structure naturally lends itself to domain decomposition, thereby enabling efficient and scalable implementations on massively parallel supercomputers. Numerical results for MHD simulations of magnetospheric plasma flows are described to demonstrate the validity and capabilities of the approach for space weather applications.
Geometry-Aware Network for Non-rigid Shape Prediction from a Single View

We propose a method for predicting the 3D shape of a deformable surface from a single view. By contrast with previous approaches, we do not need a pre-registered template of the surface, and our method is robust to the lack of texture and partial occlusions. At the core of our approach is a geometry-aware deep architecture that tackles the problem as usually done in analytic solutions: first perform 2D detection of the mesh and then estimate a 3D shape that is geometrically consistent with the image. We train this architecture in an end-to-end manner using a large dataset of synthetic renderings of shapes under different levels of deformation, material properties, textures and lighting conditions. We evaluate our approach on a test split of this dataset and available real benchmarks, consistently improving state-of-the-art solutions with a significantly lower computational time.