Miracle-dz/UniFAR-FTUs huggingface dataset:
CreativeSVG: A Creativity Support Tool for Abstract Background Design with Generative Vector Graphics

Great graphic designs do not just come out overnight; they take many iterations to polish the design. Designers create different versions of their work and compare the versions in iterations. However, the exploration of different design is time-consuming and tedious. This paper presents a design tool, CreativeSVG, that aims to facilitate the ideation and iteration of abstract background design by two features: 1) the variations of a specific graphic for the selected design features 2) the transition between two chosen graphics. Preliminary user feedback shows that our tool augments user creativity and increases design efficiency to a certain extend.
J. Gen. Appl. Microbiol., 59, 67‒73 (2013)

Flower-visiting insects can infect the flower organs and the flower nectar with yeasts carried on their bodies or in their digestive tracts (e.g. Pozo et al., 2011; Sandhu and Waraich, 1985). The association of flowers and pollinating or non-pollinating insects feeding on pollen and nectar with yeasts has been demonstrated by numerous works over the past three decades (e.g. Lachance et al., 2001b; Limtong et al., 2012; Pozo et al., 2012; Sandhu and Waraich, 1985; Sipiczki, 2010). Species of Metschnikowia, Starmerella and related anamorphic Candida species seem to be frequent colonists of insect-visited flowers (e.g. Lachance et al., 2001b; Nakase et al., 2010; Pimentel et al., 2005; Rosa et al., 2007). Most species of the Starmerella clade have been reported from bees or sugarrich microhabitats associated with bees (Pimentel et al., 2005; Rosa et al., 1999, 2003, 2007; Spencer et al., 1970; Teixeira et al., 2003). This report describes a novel species of the Starmerella clade isolated from flowers of leguminous plants in East Caucasus.
THE DEVELOPMENT AND EVALUATION OF THE STIGMA OF ILLEGALITY AND MARGINALIZATION OF LATINXS (SIML) SCALE

Abstract Drawing on two online studies among predominantly U.S.-born and lawful permanent resident Latinxs, we developed a self-report scale intended to capture how discrimination related to perceived legal status, as well as perceptions of racial/ethnic marginalization of Latinxs in U.S. society, are experienced among a wide swath of the Latinx population. We also explore how these processes may be associated with psychological distress in this population. In line with the immigration scholarship that has identified a spillover effect of immigration enforcement and the racialization of legal status beyond the undocumented population, our exploratory factor analysis results from Study I (N = 355 Latinxs) collected in fall of 2013 revealed four factors among our study population: Fear of Deportation, Marginalization of Latinxs in U.S. Society, Marginalization Due to Perceived Illegality, and Fear Due to Perceived Illegality. Results from a confirmatory factor analysis from a separate study conducted in spring of 2016 (Study II; N = 295 Latinxs) provided evidence in support of the structure identified in Study I. Results also revealed evidence of the association between the Stigma of Illegality and Marginalization of Latinxs (SIML) subscales and psychological distress, measured as anxiety and depression. Implications of these findings are discussed.
Concepts, logic, and cognitive adequacy

The project aims to study and develop a computational logic framework inspired and informed by the theories of concepts as they can be found across the disciplines of Cognitive Science and Experimental Psychology. It concentrates on the representation of different phenomena permeating human cognition, focusing mainly on aspects linked to the categorisation task (e.g. typicality effect, exceptions handling, concept vagueness) and the concept combination task (dominance effect, overextension, underextension, alignment of features).
Turning Inside Out: Filamentous Fungal Secretion and Its Applications in Biotechnology, Agriculture, and the Clinic

Filamentous fungi are found in virtually every marine and terrestrial habitat. Vital to this success is their ability to secrete a diverse range of molecules, including hydrolytic enzymes, organic acids, and small molecular weight natural products. Industrial biotechnologists have successfully harnessed and re-engineered the secretory capacity of dozens of filamentous fungal species to make a diverse portfolio of useful molecules. The study of fungal secretion outside fermenters, e.g., during host infection or in mixed microbial communities, has also led to the development of novel and emerging technological breakthroughs, ranging from ultra-sensitive biosensors of fungal disease to the efficient bioremediation of polluted environments. In this review, we consider filamentous fungal secretion across multiple disciplinary boundaries (e.g., white, green, and red biotechnology) and product classes (protein, organic acid, and secondary metabolite). We summarize the mechanistic understanding for how various molecules are secreted and present numerous applications for extracellular products. Additionally, we discuss how the control of secretory pathways and the polar growth of filamentous hyphae can be utilized in diverse settings, including industrial biotechnology, agriculture, and the clinic.
Measuring the Effect of ITS Feedback Messages on Students' Emotions

When an ITS gives supportive, empathetic, or motivational feedback messages to the learner, does it alter the learner’s emotional state, and can the ITS detect the change? We investigated this question on a dataset of n = 36 African-American undergraduate students who interacted with iPad-based cognitive skills training software that issued various feedback messages. Using both automatic facial expression recognition and heart rate sensors, we estimated the eﬀect of the diﬀerent messages on short-term changes to students’ emotions. Our re-sults indicate that, except for a few speciﬁc messages (“Great Job”, and “Good Job”), the evidence for the existence of such eﬀects was meager, and the eﬀect sizes were small. Moreover, for the “Good Job” and “Great Job” actions, the eﬀects can easily be explained by the student having recently scored a point, rather than the feedback itself. This suggests that the emotional impact of such feedback, at least in the particular context of our study, is either very small, or it is undetectable by heart rate or facial expression sensors.
Localization and Counting of Humans based on Satellite and Aerial Imagery

This thesis is concerned with methods of object detection. Specifically with person localization on satellite and aerial imagery. I describe here the creation and preparation of a dataset and then the algorithms and their settings to obtain the best predictive model. In this work, I use the state of the art algorithms based on deep neural networks (Faster R-CNN [1], RetinaNet [2]).
The Role of Brand Commitment in the Retail Sector: The Relation with Open Innovation

Firm–employee relationships are a prerequisite for customer–firm relationships and, consequently, to organizational success. The development of such relationships can be particularly challenging for retailers because of the complexity of the service component inherent to the environment in which they usually operate. For this reason, organizations need to align employee behaviors with the corporate brand promise so that they can perform a more active role as brand ambassadors. This issue becomes even more complex for organizations with a presence in foreign markets. This study focuses on how the adoption of in-role branding behavior by front-line employees (FLEs) can be influenced by the level of commitment FLEs display towards the corporate brand and how commitment is consequently influenced by corporate brand identity and corporate brand identity FLES’ perception of their role within the organization. The object of the study was the employees of Falabella, a multinational retailer based in Chile with a strong presence in the Colombian market. Results obtained demonstrate that brand commitment positively and significantly impacts FLE brand-oriented behavior in the retail context examined. More specifically, brand identity and role clarity positively impact brand commitment, leading to a positive impact on FLE brand behavior and job satisfaction. The results of this study offer valuable insight for scholars and practitioners regarding employee brand behavior’s engendering process within a retail environment in an emerging market.
Single-cell bisulfite sequencing of spermatozoa from lean and obese humans reveals potential for the transmission of epimutations

Epigenetic marks in gametes modulate developmental programming after fertilization. Spermatozoa from obese men exhibit distinct epigenetic signatures compared to lean men, however, whether epigenetic differences are concentrated in a sub-population of spermatozoa or spread across the ejaculate population is unknown. Here, by using whole-genome single-cell bisulfite sequencing on 87 motile spermatozoa from 8 individuals (4 lean and 4 obese), we found that spermatozoa within single ejaculates are highly heterogeneous and contain subsets of spermatozoa with marked imprinting defects. Comparing lean and obese subjects, we discovered methylation differences across two large CpG dense regions located near PPM1D and LINC01237. These findings confirm that sperm DNA methylation is altered in human obesity and indicate that single ejaculates contain subpopulations of spermatozoa carrying distinct DNA methylation patterns. Distinct epigenetic patterns of spermatozoa within an ejaculate may result in different intergenerational effects and therefore influence strategies aiming to prevent epigenetic-related disorders in the offspring.
Multi-Level Perspective on Sustainability Transition towards Nature-Based Solutions and Co-Creation in Urban Planning of Belgrade, Serbia

In recent years, nature-based solutions have been increasingly promoted as a climate change adaptation instrument, strongly advocated to be co-created. Achieving clear, coherent, and ambitious urban greening strategies, embedded in urban planning and developed in a co-creative, participatory and inclusive manner, is highly challenging within the EU enlargement context. In this article, such challenges are studied through two recent urban development initiatives in Belgrade, the Capital of Serbia: the first initiative focuses on planning the new Linear Park, within the framework of the CLEVER Cities Horizon 2020 project; the second initiative envisages the transformation of the privatised Avala Film Complex in the Košutnjak Urban Forest, primarily led by private interests but supported by the local authorities. The multiple-case study research method is applied, with an exploratory purpose and as a basis for potential future research on evaluation of co-creation processes for NBS implementation. The theoretical basis of this article is founded in the research on sustainability transitions, focusing on multi-level perspective (MLP) framework. The urban planning system in Belgrade and Serbia is observed as a socio-technical regime of the MLP. In such framework, we recognize co-creative planning of the Linear Park as a niche innovation. We interpret opposition towards planning of the Avala Film Complex as escalation, or an extreme element of the socio-technical landscape, comprised of civic unrests and political tensions on one side, combined with the climate crisis and excessive pollution on the other side. Moreover, the article examines informal urban planning instruments that can be implemented by the practitioners of niche innovations, that could support urban planners and NBS advocates in the Serbian and EU enlargement contexts to face the challenges of motivating all stakeholders to proactively, constructively and appropriately engage in co-creation.
NIMS: a database on nucleobase compounds and their interactions in macromolecular structures

The intense exploration of nucleotide-binding protein structures has created a whirlwind in the field of structural biology and bioinformatics. This has led to the conception and birth of NIMS. This database is a collection of detailed data on the nucleobases, nucleosides and nucleotides, along with their analogues as well as the protein structures to which they bind. Interaction details such as the interacting residues and all associated values have been made available. As a pioneering step, the diffraction precision index for protein structures, the atomic uncertainty for each atom, and the computed errors on the interatomic distances and angles are available in the database. Apart from the above, provision has been made to visualize the three-dimensional structures of both ligands and protein-ligand structures and their interactions in Jmol as well as JSmol. One of the salient features of NIMS is that it has been interfaced with a user-friendly and query-based efficient search engine. It was conceived and developed with the aim of serving a significant section of researchers working in the area of protein and nucleobase complexes. NIMS is freely available online at http://iris.physics. iisc.ernet. in/nims and it is hoped that it will prove to be an invaluable asset.
Preclinical Studies in Anti-Trypanosomatidae Drug Development

The trypanosomatid parasites Trypanosoma brucei, Trypanosoma cruzi and Leishmania are the causative agents of human African trypanosomiasis, Chagas Disease and Leishmaniasis, respectively. These infections primarily affect poor, rural communities in the developing world, and are responsible for trapping sufferers and their families in a disease/poverty cycle. The development of new chemotherapies is a priority given that existing drug treatments are problematic. In our search for novel anti-trypanosomatid agents, we assess the growth-inhibitory properties of >450 compounds from in-house and/or “Pathogen Box” (PBox) libraries against L. infantum, L. amazonensis, L. braziliensis, T. cruzi and T. brucei and evaluate the toxicities of the most promising agents towards murine macrophages. Screens using the in-house series identified 17 structures with activity against and selective toward Leishmania: Compounds displayed 50% inhibitory concentrations between 0.09 and 25 μM and had selectivity index values >10. For the PBox library, ~20% of chemicals exhibited anti-parasitic properties including five structures whose activity against L. infantum had not been reported before. These five compounds displayed no toxicity towards murine macrophages over the range tested with three being active in an in vivo murine model of the cutaneous disease, with 100% survival of infected animals. Additionally, the oral combination of three of them in the in vivo Chagas disease murine model demonstrated full control of the parasitemia. Interestingly, phenotyping revealed that the reference strain responds differently to the five PBox-derived chemicals relative to parasites isolated from a dog. Together, our data identified one drug candidate that displays activity against Leishmania and other Trypanosomatidae in vitro and in vivo, while exhibiting low toxicity to cultured mammalian cells and low in vivo acute toxicity.
Memristor-CMOS Hybrid Neuron Circuit with Nonideal-Effect Correction Related to Parasitic Resistance for Binary-Memristor-Crossbar Neural Networks

Voltages and currents in a memristor crossbar can be significantly affected due to nonideal effects such as parasitic source, line, and neuron resistance. These nonideal effects related to the parasitic resistance can cause the degradation of the neural network’s performance realized with the nonideal memristor crossbar. To avoid performance degradation due to the parasitic-resistance-related nonideal effects, adaptive training methods were proposed previously. However, the complicated training algorithm could add a heavy computational burden to the neural network hardware. Especially, the hardware and algorithmic burden can be more serious for edge intelligence applications such as Internet of Things (IoT) sensors. In this paper, a memristor-CMOS hybrid neuron circuit is proposed for compensating the parasitic-resistance-related nonideal effects during not the training phase but the inference one, where the complicated adaptive training is not needed. Moreover, unlike the previous linear correction method performed by the external hardware, the proposed correction circuit can be included in the memristor crossbar to minimize the power and hardware overheads for compensating the nonideal effects. The proposed correction circuit has been verified to be able to restore the degradation of source and output voltages in the nonideal crossbar. For the source voltage, the average percentage error of the uncompensated crossbar is as large as 36.7%. If the correction circuit is used, the percentage error in the source voltage can be reduced from 36.7% to 7.5%. For the output voltage, the average percentage error of the uncompensated crossbar is as large as 65.2%. The correction circuit can improve the percentage error in the output voltage from 65.2% to 8.6%. Almost the percentage error can be reduced to ~1/7 if the correction circuit is used. The nonideal memristor crossbar with the correction circuit has been tested for MNIST and CIFAR-10 datasets in this paper. For MNIST, the uncompensated and compensated crossbars indicate the recognition rate of 90.4% and 95.1%, respectively, compared to 95.5% of the ideal crossbar. For CIFAR-10, the nonideal crossbars without and with the nonideal-effect correction show the rate of 85.3% and 88.1%, respectively, compared to the ideal crossbar achieving the rate as large as 88.9%.
Impatience for Information: Curiosity Is Here Today, Gone Tomorrow

Based on the curiosity‐as‐drive theory and the theory of information gaps, we argue that curiosity—that is, the desire to seek out novel information for its own sake—is highly transient, and while people may be tempted by immediate answers, they may be less motivated when they need to wait for information. Contrary to standard economic models, we predict an immediacy effect (or present bias) for information even in those cases when waiting does not affect the objective value of information. Furthermore, we argue that this immediacy effect is independent from motivated emotion‐management; that is, introducing delays makes people less willing to obtain information for its own sake even when information does not elicit strong anticipatory feelings. We test these hypotheses in two pre‐registered experiments (N = 2406) featuring real effort and monetary incentives and find that introducing a delay in information provision significantly reduces participants' willingness to obtain information. In Study 1, we also show that people display a stronger immediacy effect for information than for monetary rewards. In Study 2, we demonstrate that people are impatient for information regardless of how they expect to feel after receiving the information, and even when the perceived instrumental value of information remains unaffected by the delay. The strong impatience for information in both studies is consistent with the notion that curiosity acts as a drive, and as such, is highly transient.
Bayesian Error-in-Variables Models for the Identification of Power Networks

The increasing integration of intermittent renewable generation, especially at the distribution level,necessitates advanced planning and optimisation methodologies contingent on the knowledge of thegrid, specifically the admittance matrix capturing the topology and line parameters of an electricnetwork. However, a reliable estimate of the admittance matrix may either be missing or quicklybecome obsolete for temporally varying grids. In this work, we propose a data-driven identificationmethod utilising voltage and current measurements collected from micro-PMUs. More precisely,we first present a maximum likelihood approach and then move towards a Bayesian framework,leveraging the principles of maximum a posteriori estimation. In contrast with most existing con-tributions, our approach not only factors in measurement noise on both voltage and current data,but is also capable of exploiting available a priori information such as sparsity patterns and knownline parameters. Simulations conducted on benchmark cases demonstrate that, compared to otheralgorithms, our method can achieve significantly greater accuracy.
Transport threshold in a quantum model for the KscA ion channel

The mechanism behind the high throughput rate in K+ channels is still an open problem. However, recent simulations have shown that the passage of potassium through the K+ channel core, the so-called selectivity filter (SF), is water-free against models where the strength of Coulomb repulsion freezes ions conduction. Thus, it has been suggested that coherent quantum hopping might be relevant in mediating ion conduction. Within the quantum approach and the hypothesis of desolvated ions along the pathway, we start with several particles in a source to see how they go across a SF, modeled by a linear chain of sites, to be collected in a drain. We show that the average SF occupancy is three ions, and the ion transfer rate is ∼108 ions s−1, results which agree with the recent findings in the literature.
Martingale representations in progressive enlargement by multivariate point processes

We show that all local martingales with respect to the initially enlarged natural filtration of a vector of multivariate point processes can be weakly represented up to the minimum among the explosion times of the components. We also prove that a strong representation holds if any multivariate point process of the vector has almost surely infinite explosion time and discrete mark’s space. Then we provide a condition under which the components of the multidimensional local martingale driving the strong representation are pairwise orthogonal.
Optimal Gradient-based Algorithms for Non-concave Bandit Optimization

Bandit problems with linear or concave reward have been extensively studied, but relatively few works have studied bandits with non-concave reward. This work considers a large family of bandit problems where the unknown underlying reward function is non-concave, including the low-rank generalized linear bandit problems and two-layer neural network with polynomial activation bandit problem. For the low-rank generalized linear bandit problem, we provide a minimax-optimal algorithm in the dimension, refuting both conjectures in [LMT21, JWWN19]. Our algorithms are based on a unified zeroth-order optimization paradigm that applies in great generality and attains optimal rates in several structured polynomial settings (in the dimension). We further demonstrate the applicability of our algorithms in RL in the generative model setting, resulting in improved sample complexity over prior approaches. Finally, we show that the standard optimistic algorithms (e.g., UCB) are sub-optimal by dimension factors. In the neural net setting (with polynomial activation functions) with noiseless reward, we provide a bandit algorithm with sample complexity equal to the intrinsic algebraic dimension. Again, we show that optimistic approaches have worse sample complexity, polynomial in the extrinsic dimension (which could be exponentially worse in the polynomial degree).