Miracle-dz/UniFAR-FTUs huggingface dataset:
A Portable Chemotaxis Platform for Short and Long Term Analysis

Flow-based microfluidic systems have been widely utilized for cell migration studies given their ability to generate versatile and precisely defined chemical gradients and to permit direct visualization of migrating cells. Nonetheless, the general need for bulky peripherals such as mechanical pumps and tubing and the complicated setup procedures significantly limit the widespread use of these microfluidic systems for cell migration studies. Here we present a simple method to power microfluidic devices for chemotaxis assays using the commercially available ALZET® osmotic pumps. Specifically, we developed a standalone chemotaxis platform that has the same footprint as a multiwell plate and can generate well-defined, stable chemical gradients continuously for up to 7 days. Using this platform, we validated the short-term (24 hours) and long-term (72 hours) concentration dependent PDGF-BB chemotaxis response of human bone marrow derived mesenchymal stem cells.
A theory of plenoptic multiplexing

Multiplexing is a common technique for encoding high-dimensional image data into a single, two-dimensional image. Examples of spatial multiplexing include Bayer patterns to capture color channels, and integral images to encode light fields. In the Fourier domain, optical heterodyning has been used to acquire light fields. In this paper, we develop a general theory of multiplexing the dimensions of the plenoptic function onto an image sensor. Our theory enables a principled comparison of plenoptic multiplexing schemes, including noise analysis, as well as the development of a generic reconstruction algorithm. The framework also aides in the identification and optimization of novel multiplexed imaging applications.
Biochemical and Molecular Characterization of a Serine Keratinase from Brevibacillus brevis US575 with Promising Keratin-Biodegradation and Hide-Dehairing Activities

Dehairing is one of the highly polluting operations in the leather industry. The conventional lime-sulfide process used for dehairing produces large amounts of sulfide, which poses serious toxicity and disposal problems. This operation also involves hair destruction, a process that leads to increased chemical oxygen demand (COD), biological oxygen demand (BOD), and total suspended solid (TSS) loads in the effluent. With these concerns in mind, enzyme-assisted dehairing has often been proposed as an alternative method. The main enzyme preparations so far used involved keratinases. The present paper reports on the purification of an extracellular keratinase (KERUS) newly isolated from Brevibacillus brevis strain US575. Matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF/MS) analysis revealed that the purified enzyme was a monomer with a molecular mass of 29121.11 Da. The sequence of the 27 N-terminal residues of KERUS showed high homology with those of Bacillus keratinases. Optimal activity was achieved at pH 8 and 40°C. Its thermoactivity and thermostability were upgraded in the presence of 5 mM Ca2+. The enzyme was completely inhibited by phenylmethanesulfonyl fluoride (PMSF) and diiodopropyl fluorophosphates (DFP), which suggests that it belongs to the serine protease family. KERUS displayed higher levels of hydrolysis, substrate specificity, and catalytic efficiency than NUE 12 MG and KOROPON® MK EG keratinases. The enzyme also exhibited powerful keratinolytic activity that made it able to accomplish the entire feather-biodegradation process on its own. The kerUS gene encoding KERUS was cloned, sequenced, and expressed in Escherichia coli. The biochemical properties of the extracellular purified recombinant enzyme (rKERUS) were similar to those of native KERUS. Overall, the findings provide strong support for the potential candidacy of this enzyme as an effective and eco-friendly alternative to the conventional chemicals used for the dehairing of rabbit, goat, sheep and bovine hides in the leather processing industry.
Waiting in motion: mapping postcolonial fiction, new mobilities, and migration through Mohsin Hamid’s Exit West

ABSTRACT While mobilities studies have often drawn on postcolonial theory, few studies draw on the unique contributions of postcolonial literature. This article charts new directions for mobilities studies and postcolonial literature through an analysis of Mohsin Hamid’s 2017 novel Exit West. The novel shows how the ‘new mobilities paradigm’ could be usefully extended by paying more attention to migration as an expression of the way that mobility and immobility exist in complex relation to one another, especially with regard to the affective and existential experiences of waiting that persist even after arrival. I suggest that contemporary fiction, such as Exit West, interacts with and shapes cultural imaginaries around mobilities and migrancy; Hamid’s use of irrealist and fantastic modes challenges readers to entertain normative claims about the world. In addition to outlining the potential contributions of postcolonial fiction to mobilities studies, I conclude with an overview of the new directions that mobilities studies offer for postcolonial studies as well.
One-Year Brain Atrophy Evident in Healthy Aging

An accurate description of changes in the brain in healthy aging is needed to understand the basis of age-related changes in cognitive function. Cross-sectional magnetic resonance imaging (MRI) studies suggest thinning of the cerebral cortex, volumetric reductions of most subcortical structures, and ventricular expansion. However, there is a paucity of detailed longitudinal studies to support the cross-sectional findings. In the present study, 142 healthy elderly participants (60–91 years of age) were followed with repeated MRI, and were compared with 122 patients with mild to moderate Alzheimer's disease (AD). Volume changes were measured across the entire cortex and in 48 regions of interest. Cortical reductions in the healthy elderly were extensive after only 1 year, especially evident in temporal and prefrontal cortices, where annual decline was ∼0.5%. All subcortical and ventricular regions except caudate nucleus and the fourth ventricle changed significantly over 1 year. Some of the atrophy occurred in areas vulnerable to AD, while other changes were observed in areas less characteristic of the disease in early stages. This suggests that the changes are not primarily driven by degenerative processes associated with AD, although it is likely that preclinical changes associated with AD are superposed on changes due to normal aging in some subjects, especially in the temporal lobes. Finally, atrophy was found to accelerate with increasing age, and this was especially prominent in areas vulnerable to AD. Thus, it is possible that the accelerating atrophy with increasing age is due to preclinical AD.
A Distributed Controller for Managing Speculative Functional Units in High Level Synthesis

Speculative functional units (SFUs) are arithmetic functional units that operate using a predictor for the carry signal. The carry prediction helps to shorten the critical path of the functional unit. The average case performance of these units is determined by the hit rate of the prediction. In case of mispredictions, the SFUs need to be coordinated by the datapath control mechanism to perform corrections and to maintain the datapath in the correct state. Devising a control mechanism for correcting mispredictions without adversely impacting overall performance is the most important challenge. In this paper, we present techniques for designing a datapath controller for seamless deployment of SFUs in high level synthesis. We have developed two techniques based on two main control paradigms: centralized and distributed control. The centralized approach stops the execution of the entire datapath for each misprediction and resumes execution once the correct value of the carry is known. The distributed approach decouples the functional unit suffering from the misprediction from the rest of the datapath. Hence, it allows the remainder of the functional units to carry on execution and be at different scheduling states at different times. We tested datapaths utilizing both linear structures and logarithmic structures for speculative arithmetic functional units. Our results show that it is possible to reduce execution time by as much as 38% (33% on average) for linear structures and by as much as 37.2% (25% on average) for logarithmic structures.
Variations of the spectral index of dust emissivity from Hi-GAL observations of the Galactic plane

Context. Variations in the dust emissivity are critical for gas mass determinations derived from far-infrared observations, but also for separating dust foreground emission from the Cosmic Microwave Background (CMB). Hi-GAL observations allow us for the first time to study the dust emissivity variations in the inner regions of the Galactic plane at resolution below 1°. Aims. We present maps of the emissivity spectral index derived from the combined Herschel PACS 160 μm, SPIRE 250 μm, 350 μm, and 500 μm data, and the IRIS 100 μm data, and we analyze the spatial variations of the spectral index as a function of dust temperature and wavelength in the two science demonstration phase Hi-GAL fields, centered at l = 30° and l = 59°. Methods. Applying two different methods, we determine both dust temperature and emissivity spectral index between 100 and 500 μm, at an angular resolution (θ) of 4'. Results. Combining both fields, the results show variations of the emissivity spectral index in the range 1.8–2.6 for temperatures between 14 and 23 K. The median values of the spectral index are similar in both fields, i.e. 2.3 in the range 100–500 μm, while the median dust temperatures are equal to 19.1 K and 16.0 K in the l = 30° and l = 59° field, respectively. Statistically, we do not see any significant deviations in the spectra from a power law emissivity between 100 and 500 μm. We confirm the existence of an inverse correlation between the emissivity spectral index and dust temperature, found in previous analyses.
The Limits of Feedforward Vision: Recurrent Processing Promotes Robust Object Recognition when Objects Are Degraded

Everyday vision requires robustness to a myriad of environmental factors that degrade stimuli. Foreground clutter can occlude objects of interest, and complex lighting and shadows can decrease the contrast of items. How does the brain recognize visual objects despite these low-quality inputs? On the basis of predictions from a model of object recognition that contains excitatory feedback, we hypothesized that recurrent processing would promote robust recognition when objects were degraded by strengthening bottom–up signals that were weakened because of occlusion and contrast reduction. To test this hypothesis, we used backward masking to interrupt the processing of partially occluded and contrast reduced images during a categorization experiment. As predicted by the model, we found significant interactions between the mask and occlusion and the mask and contrast, such that the recognition of heavily degraded stimuli was differentially impaired by masking. The model provided a close fit of these results in an isomorphic version of the experiment with identical stimuli. The model also provided an intuitive explanation of the interactions between the mask and degradations, indicating that masking interfered specifically with the extensive recurrent processing necessary to amplify and resolve highly degraded inputs, whereas less degraded inputs did not require much amplification and could be rapidly resolved, making them less susceptible to masking. Together, the results of the experiment and the accompanying model simulations illustrate the limits of feedforward vision and suggest that object recognition is better characterized as a highly interactive, dynamic process that depends on the coordination of multiple brain areas.
An approximation to the response time for shortest queue routing

In this paper we derive an approximation for the mean response time of a multiple queue system in which shortest queue routing is used. We assume there are &Kgr; identical queues with infinite capacity and service times that are exponentially distributed. Arrivals of jobs to this system are Poisson and are routed to a queue of minimal length. We develop an approximation which is based on both theoretical and experimental considerations and, for &Kgr; ≤ 8, has an relative error of less than one half of one percent when compared to simulation. For &Kgr; = 16, the relative error is still acceptable, being less than 2 percent. An application to a model of parallel processing and a comparison of static and dynamic load balancing schemes are presented.
Error resistant space-time coding for emerging 4G-WLANs

Multiple-antenna wireless systems with space-time block-codes exploit channel-diversity for improving performance without loss in spectral efficiency. Up to date, most work on this area assumed that perfect channel estimates are available at the receiver so to make feasible fully coherent decoding. However, accurate channel-estimates require long training sequences that lower spectral efficiency. Therefore, in this contribution we focus on architecture, optimized design and performance of multiple-antenna block-coded systems with imperfect channel-estimates. After considering emerging fourth-generation WLANs (4GWLANs) as a possible application scenario, new performance bounds and optimized design criteria are presented together with a new family of robust-space block-codes that "self-match" to channel estimation errors.
You are What You Eat! Tracking Health Through Recipe Interactions

On today’s World Wide Web, social recommender systems have become a commodity regardless of application domain. Even tangible items such as food and clothes have become social. Together with a seemingly endless amount of personalization and recommender systems ranging from movies, music, or consumer products, recipe recommender systems are attracting many users looking for inspiration on the next thing to purchase or cook. There is however a conceptual difference between recommending consumer goods for leisure and entertainment, and recommending food. What people eat has a direct effect on their health, an aspect commonly overlooked in the context of recommendation. In this work, we present an early analysis of users’ interactions with recipes (ratings) on the online social network Allrecipes.com. We compare the interaction patterns of users from locations known to have poor health to users from locations known to have good health in order to identify whether there is an observable difference between the two populations. Our results point to a statistically significant difference between the healthy and unhealthy groups, a difference that could potentially be used to create health-conscious, personalized, recommendation services to aid people in their daily lives.
Federal Reserve Bank of San Francisco Working Paper Series China's Exporters and Importers: Firms, Products, and Trade Partners China's Exporters and Importers: Firms, Products, and Trade Partners

This paper provides a detailed overview of China's participation in international trade using newly available data on the universe of globally engaged Chinese firms over the 2003-2005 period. We document the distribution of trade flows, product-and trade-partner intensity across both exporting and importing firms, and study the relationship between firms' intensive and extensive margins of trade. We also compare trade patterns across firms of different organizational structure, distinguishing between domestic private firms, domestic state‐owned firms, foreign-owned firms, and joint ventures. We explore the variation in foreign ownership across sectors, and find results consistent with recent theoretical and empirical work on the role of credit constraints and contractual imperfections in international trade and investment. Finally, we examine the rapid expansion of China's trade over the 2003‐2005 period, and decompose it into its extensive and intensive margins. We also use monthly data and study the frequent churning and reallocation of trade flows across firms and across products and trade partners within firms.
The impact of fluid attraction and fluid identity on mental health

Abstract Using data from the National Longitudinal Study of Adolescent Health, this study examined the impact of sexuality factors and satisfaction with partner on stress, anxiety, and depressive symptoms. Multiple regression was used to evaluate the impact of predictors such as sexuality factors and relationship satisfaction on the dependent variables: stress, anxiety, and depression. Three main results were discovered. First, sexual minority females who have lower levels of education and are dissatisfied with their relationship experience significantly higher stress, while sexual minority males do not differ from heterosexual males in terms of relationship satisfaction or stress. Second, sexual minority females who have lower levels of education and who are dissatisfied with their relationship experience significantly higher anxiety, while sexual minority males do not differ from heterosexual males in terms of relationship satisfaction or anxiety. Finally, female sexual minorities who have lower levels of education reported fluid attraction, fluid identity, dissatisfaction with their relationship, and have significantly higher depression when compared to male sexual minorities or heterosexuals. Further research should examine gender and fluidity in greater detail.
Innovation Method for Dynamic Independent Component Analysis: A New Concept and Algorithm

The inner time-structure information is consideredfor the dynamic independent component analysis (DICA)model, and the new concept of innovation and correspondingalgorithm are presented. When the innovation is applied inDICA, a new linear mixing model of innovation DICA (IDICA)can be obtained in which the assumptions of independence andnon-Gaussianity for the basic ICA model are also satisfied,and the non-Gaussianity of latent components increase.What’s more, the mixing matrix (or demixing matrix)estimated from IDICA model is also available for originalDICA model. Then the new algorithm of (IDICA) is presented,and the effects of IDICA are discussed. It is validated that itcan accelerate the convergence rate with the increasing of thelatent component’s non-Gaussianity, but has little influence onthe convergence accuracy. In performing innovation, theadaptive filter based on Minimum Square Error (MSE) isproposed. The experimental results show the new method’sefficient and available.
BRAVE NEW HOPF ALGEBROIDS AND THE ADAMS SPECTRAL SEQUENCE FOR R-MODULES

This note is intended to draw attention to some phenomena arising naturally within the framework of brave new ring spectra which has recently been constructed by May et al [5]. Actually, our first contact with the algebraic aspects was in the framework of Robinson’s theory of A∞ ring spectra [2, 3], however their most natural interpretation seems to be within the commutative theory. Since writing this document, we became aware of recent work of A. Lazarev [6] in which similar algebra plays a part, see also [4].
Multi-type Co-clustering of General Heterogeneous Information Networks via Nonnegative Matrix Tri-Factorization

Many kinds of real world data can be modeled by a heterogeneous information network (HIN) which consists of multiple types of objects. Clustering plays an important role in mining knowledge from HIN. Several HIN clustering algorithms have been proposed in recent years. However, these algorithms suffer from one or moreof the following problems: (1) inability to model general HINs, (2) inability to simultaneously generate clusters for all types of objects, (3) inability to use similarity information of the objects with the same type. In this paper, we propose a powerful HIN clustering algorithm which can handle general HINs, simultaneously generate clusters for all types of objects, and use the similarity information of the same type of objects. First, we transform a general HIN into a meta-path-encoded relationship set. Second, we propose a nonnegative matrix tri-factorization multi-type co-clustering method, HMFClus, to cluster all types of objects in HIN simultaneously. Third, we integrate the information between the objects with the same type into HMFClus by using a similarity regularization. Extensive experiments on real world datasets show that the proposed algorithm outperforms the state-of-the-art methods.
Functional and Structural Overview of G-Protein-Coupled Receptors Comprehensively Obtained from Genome Sequences

An understanding of the functional mechanisms of G-protein-coupled receptors (GPCRs) is very important for GPCR-related drug design. We have developed an integrated GPCR database (SEVENS http://sevens.cbrc.jp/) that includes 64,090 reliable GPCR genes comprehensively identified from 56 eukaryote genome sequences, and overviewed the sequences and structure spaces of the GPCRs. In vertebrates, the number of receptors for biological amines, peptides, etc. is conserved in most species, whereas the number of chemosensory receptors for odorant, pheromone, etc. significantly differs among species. The latter receptors tend to be single exon type or a few exon type and show a high ratio in the numbers of GPCRs, whereas some families, such as Class B and Class C receptors, have long lengths due to the presence of many exons. Statistical analyses of amino acid residues reveal that most of the conserved residues in Class A GPCRs are found in the cytoplasmic half regions of transmembrane (TM) helices, while residues characteristic to each subfamily found on the extracellular half regions. The 69 of Protein Data Bank (PDB) entries of complete or fragmentary structures could be mapped on the TM/loop regions of Class A GPCRs covering 14 subfamilies.
RESCUR Surfing the Waves: an evaluation of a resilience programme in the early years

ABSTRACT RESCUR Surfing the Waves is a recently developed resilience curriculum for early years and primary schools in Europe. It seeks to develop in marginalized young learners the requisite competences needed to overcome the various challenges in their lives to achieve academic success and social and emotional wellbeing. The competences include developing a growth mindset, making use of one’s strengths, self-determination, effective communication skills and healthy relationships, and overcoming challenges and obstacles. This paper presents the findings of a study on the implementation of the programme in five kindergarten centres in Malta over a 1-year period. A pre- and post-intervention study in 20 classrooms (97 children) showed an improvement in resilience skills, prosocial behavior and learning engagement, but not in internalized and externalized problem behaviors. A small scale study in two nurture classes at two of the schools found similar findings. The findings suggest that there are indications that the programme as a proportionate universal intervention for early years leads to an improvement in social and academic behaviours, but more rigorous research is needed to substantiate these findings.