Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovery of a Double Blue Straggler Sequence in M15: New Insight into the Core-collapse Process

In this paper we report the discovery of a double blue straggler star (BSS) sequence in the core of the core-collapsed cluster M15 (NGC 7078). We performed a detailed photometric analysis of the extremely dense core of the cluster using a set of images secured with the Advanced Camera for Survey in the High Resolution Channel mode on board the Hubble Space Telescope. The proper combination of the large number of single frames in the near-UV (F220W), and blue (F435W) filters allowed us to perform a superb modeling of the point-spread function and an accurate deblending procedure. The color–magnitude diagram revealed the presence of two distinct parallel sequences of blue stragglers. In particular, the blue BSS sequence is characterized by the intriguing presence of two different branches. The first branch appears extremely narrow, it extends up to 2.5 mag brighter than the cluster main-sequence turnoff (MS-TO) point, and it is nicely reproduced by a 2 Gyr old collisional isochrone. The second branch extends up to 1.5 mag from the MS-TO and it is reproduced by a 5.5 Gyr old collisional isochrone. Our observations suggest that each of these branches is mainly constituted by a population of nearly coeval collisional BSSs of different masses generated during two episodes of high collisional activity. We discuss the possibility that the oldest episode corresponds to the core-collapse (CC) event (occurred about 5.5 Gyr ago), while the most recent one (occurred about 2 Gyr ago) is associated with a core oscillation in the post-CC evolution. The discovery of these features provides further strong evidence in support of the connection between the BSS properties and globular cluster dynamical evolution, and it opens new perspectives on the study of CC and post-CC evolution.
A Min‐Max conditional covariance algorithm for structure learning of Gaussian graphical models

The Gaussian graphical models provide a useful statistical framework for analyzing the linear dependence among continuous random variables. In this paper, we propose a learning algorithm to reconstruct the graph structure of the high‐dimensional Gaussian random vector from observation data. The algorithm is constituted by two conditional covariance threshold tests to identify the presence of the edges. We present a procedure called Min‐Max conditional covariance to estimate the test statistics and prove that the proposed algorithm has high computational efficiency and asymptotic consistency. The performance of the proposed methods is confirmed through numerical simulations on synthetic data and through a real‐world application to foreign exchange data.
Inventory optimization model considering consumer shift and inventory transshipment in dual-channel supply chains

In this paper we consider a dual-channel supply chain which consists of an online store and multiple independent retail stores. In this system, customer shift induces inventory competition while transshipment brings inventory cooperation, both of which inuences inventory optimization and control. Therefore we respectively construct inventory optimization models under the two situations: customer shift and inventory transshipment. Specifically, unilateral customer shift and inventory transshipment are considered, and a one-for-one replenishment strategy is applied. We first solve the equilibrium state probability of on-hand inventory through Markov chain theory, then optimize performance measure (i.e., the total costs) to obtain the optimal basic inventory level. Finally, we analyze the impact of customer shift rate and inventory transshipment rate on the inventory strategies through numerical simulation, and further compare the differences in inventory decisions between the above two situations, which prove that inventory cooperation brought by inventory transshipment is not necessarily better than inventory competition brought by customer shift. In addition, we discuss several insights that are evident from the parametric analysis of the model.
Students’ negotiations of belonging in geoscience: experiences of faculty–student interactions when entering university

ABSTRACT In this study, we explore how interactions with faculty influence first-year geoscience students’ negotiations of belonging in a study programme. We situate the study within the field of retention and use the concepts of belonging and culture to analyse our empirical material, collected through ethnographic fieldwork. We explore how faculty–student interactions during geoscientific fieldwork and in an “interview exercise” give students access to explicit and tacit knowledge about doing geoscience research, the department culture and possible careers in geoscience. The analysis shows that faculty–student interactions offer important avenues for the students’ negotiations of how they belong in the study programme (who they are) and in assessing their future possibilities (who they want to become). However, while positive for some students, the perceived needs to be highly devoted to the discipline and to perform in the field poses challenges for other students’ sense of belonging in the geoscience programme. By situating activities in the wider context of the culture of the study programme and analysing the combined effect of different faculty–students interactions, we find that institutions must offer first-year students possibilities for creating a sense of belonging that are varied, authentic and inclusive.
Binding of the regulatory domain of MutL to the sliding β-clamp is species specific

Abstract The β-clamp is a protein hub central to DNA replication and fork management. Proteins interacting with the β-clamp harbor a conserved clamp-binding motif that is often found in extended regions. Therefore, clamp interactions have –almost exclusively– been studied using short peptides recapitulating the binding motif. This approach has revealed the molecular determinants that mediate the binding but cannot describe how proteins with clamp-binding motifs embedded in structured domains are recognized. The mismatch repair protein MutL has an internal clamp-binding motif, but its interaction with the β-clamp has different roles depending on the organism. In Bacillus subtilis, the interaction stimulates the endonuclease activity of MutL and it is critical for DNA mismatch repair. Conversely, disrupting the interaction between Escherichia coli MutL and the β-clamp only causes a mild mutator phenotype. Here, we determined the structures of the regulatory domains of E. coli and B. subtilis MutL bound to their respective β-clamps. The structures reveal different binding modes consistent with the binding to the β-clamp being a two-step process. Functional characterization indicates that, within the regulatory domain, only the clamp binding motif is required for the interaction between the two proteins. However, additional motifs beyond the regulatory domain may stabilize the interaction. We propose a model for the activation of the endonuclease activity of MutL in organisms lacking methyl-directed mismatch repair.
Parents’ views and experiences of talking about autism with their children

The way an autism diagnosis is disclosed to parents has been found to play a crucial role in their acceptance of, and the way they cope with, their child’s diagnosis. Yet, research into parents’ subsequent experiences of disclosing a diagnosis to their children, and talking to their families about autism more generally, is limited. Using an online survey, the current study examined 558 parents’ experiences of talking about autism with their autistic and non-autistic children. Results demonstrated that most parents (n = 379, 67.9%) had told their autistic children about their diagnosis. Despite few parents (n = 163, 20.4%) receiving advice or support regarding the disclosure of the diagnosis, those that had disclosed felt satisfied with the process (n = 319, 84.2%) and felt confident in talking about autism with their children (n = 339, 92.4%). Those who had not told their autistic children about the diagnosis largely planned to discuss this with their child in the future (n = 100, 73.5%), felt confident in doing so (n = 95, 70.9%) and were satisfied with their decision (n = 95, 70.4%). Analysis of open-ended data, using thematic analysis, highlighted the importance of openness and the need to tailor explanations to individual children’s needs, while acknowledging that disclosure could often be challenging for parents.
Accurate Monocular 3D Object Detection via Color-Embedded 3D Reconstruction for Autonomous Driving

In this paper, we propose a monocular 3D object detection framework in the domain of autonomous driving. Unlike previous image-based methods which focus on RGB feature extracted from 2D images, our method solves this problem in the reconstructed 3D space in order to exploit 3D contexts explicitly. To this end, we first leverage a stand-alone module to transform the input data from 2D image plane to 3D point clouds space for a better input representation, then we perform the 3D detection using PointNet backbone net to obtain objects’ 3D locations, dimensions and orientations. To enhance the discriminative capability of point clouds, we propose a multi-modal feature fusion module to embed the complementary RGB cue into the generated point clouds representation. We argue that it is more effective to infer the 3D bounding boxes from the generated 3D scene space (i.e., X,Y, Z space) compared to the image plane (i.e., R,G,B image plane). Evaluation on the challenging KITTI dataset shows that our approach boosts the performance of state-of-the-art monocular approach by a large margin.
Regulation of Skeletal Muscle DRP-1 and FIS-1 Protein Expression by IL-6 Signaling

IL-6 signals through the ubiquitously expressed glycoprotein 130 (gp130) transmembrane protein to activate intracellular signaling that includes signal transducer and activator of transcription 3 (STAT3) and extracellular signal-regulated kinase 1/2 (ERK1/2). Dynamin-1-like protein (DRP-1) and mitochondrial fission 1 protein (FIS-1) are key proteins in the process of mitochondrial fission and have emerged as IL-6-sensitive targets. The purpose of this study was to examine the regulation of DRP-1 and FIS-1 expression by IL-6 and gp130 signaling in myotubes and skeletal muscle. Fully differentiated C2C12 myotubes were treated with 100 ng of IL-6 for 24 hours in the presence of gp130siRNA, C188-9 (STAT3 inhibitor), or PD98059 (ERK1/2 inhibitor). Male C57BL/6 (B6) and muscle-specific gp130 knockout mice (KO) had IL-6 systemically overexpressed for 2 weeks by transient transfection with 50 ng of an IL-6-expressing or control plasmid in the quadriceps muscles, and the tibialis anterior muscle was analyzed to determine systemic effects of IL-6. IL-6 induced DRP-1 and FIS-1 expression in myotubes 124% and 82% (p = .001) and in skeletal muscle 97% and 187% (p = .001). Myotube gp130 knockdown suppressed the IL-6 induction of DRP-1 68% (p = .002) and FIS-1 65% (p = .001). Muscle KO suppressed the IL-6 induction of DRP-1 220% (p = .001) and FIS-1 121% (p = .001). ERK1/2 inhibition suppressed the IL-6 induction of DRP-1 59% (p = .0003) and FIS-1 102% (p = .0001) in myotubes, while there was no effect of STAT3 inhibition. We report that chronically elevated IL-6 can directly induce DRP-1 and FIS-1 expression through gp130 signaling in cultured myotubes and skeletal muscle. Furthermore, ERK 1/2 signaling is necessary for the IL-6 induction of DRP-1 and FIS-1 expression in myotubes.
Practical Accuracy Limits of Radiation-Aware Magneto-Inductive 3D Localization

The key motivation for the low-frequency magnetic localization approach is that magnetic near-fields are well predictable by a free-space model, which should enable accurate localization. Yet, limited accuracy has been reported for practical systems and it is unclear whether the inaccuracies are caused by field distortion due to nearby conductors, unconsidered radiative propagation, or measurement noise. Hence, we investigate the practical performance limits by means of a calibrated magneto-inductive system which localizes an active single-coil agent with arbitrary orientation, using 4 mW transmit power at 500 kHz. The system uses eight single-coil anchors around a 3m χ 3m area in an office room. We base the location estimation on a complex baseband model which comprises both reactive and radiative propagation. The link coefficients, which serve as input data for location estimation, are measured with a multiport network analyzer while the agent is moved with a positioner device. This establishes a reliable ground truth for calibration and evaluation. The system achieves a median position error of 3.2 cm and a 90th percentile of 8.3 cm. After investigating the model error we conjecture that field distortion due to conducting building structures is the main cause of the performance bottleneck. The results are complemented with predictions on the achievable accuracy in more suitable circumstances using the Cramér-Rao lower bound.
Environmental Benefits of Internet-Enabled C2C Closed Loop Supply Chains: A Quasi-Experimental Study of Craigslist

Recently, online matching platforms (e.g., Craigslist, FreeCycle, Gumtree) have enabled consumers to directly connect with each other to buy/sell used consumer goods (electronics, furniture, packaging, etc.) that would have otherwise ended up in the waste stream. Such matching platforms can facilitate the creation of consumer-to-consumer (C2C) closed-loop supply chains (CLSCs) for used goods, which can enhance product reuse and limit reliance on recycling and disposal alternatives. Yet, the true environmental benefits of these internet-enabled C2C CLSCs remain to be ascertained. In this study, I use a quasi-experimental setup to examine how Craigslist’s entry into various U.S. geographic markets impacts a key environmental outcome: municipal solid waste (MSW). I assemble a data set from various disparate sources to test my hypothesis. I find that, on average, Craigslist’s entry into a geographic market results in a 2%–6% annual reduction in MSW per capita generated. I conduct a variety of robustness check.
Priorização de Requisitos em Startups no Armazém da Criatividade (Porto Digital): Resultados Preliminares

Resumo As startups de software vêm ganhando destaque no mercado; na maioria das vezes, estão associadas ao conceito de desenvolvimento de produtos de software inovadores e que lidam com limitações de tempo e recursos. Pesquisas apontam que as startups não são versões menores de grandes empresas e que as práticas existentes de desenvolvimento de software não podem ser repassadas diretamente para as startups sem os devidos ajustes. Poucos estudos abordam e exploram como a priorização de requisitos é praticada em startups. Apesar de ser uma atividade essencial para garantir o sucesso dos projetos, isto é, para satisfazer às necessidades mais importantes e críticas dos stakeholders, assim como para o planejamento de releases. O objetivo deste artigo é explorar através de um estudo qualitativo as práticas de priorização de requisitos utilizadas em startups e os desafios associados a essas práticas. Com isso, será obtido conhecimento que poderá fortalecer novas pesquisas relacionadas à priorização de requisitos no contexto de startups, permitindo auxiliar também profissionais com a intenção de iniciar startups de software.
Regime Type and COVID-19 Response

From late 2019 to the first half of 2020, the world has witnessed the epic spread and destruction of the novel coronavirus which was discovered in Wuhan, China. The huge number of infections and deaths caused by the virus, the collapse of the healthcare system and the economic consequences have few modern equivalents. While governments of all countries are responding to the pandemic, a heated debate rages about which political system, democracy versus authoritarian, is better positioned to respond to the pandemic. While the worldwide effort to contain the virus continues, we offer a preliminary comparison between democracies and authoritarian regimes in their responses to COVID-19, and policy suggestions for democracies to improve their governance and their ability to respond to crises.
Making Sense of the Cognitive Task of Medication Reconciliation Using a Card Sorting Task

Objective: To explore cognitive strategies clinicians apply while performing a medication reconciliation task, handling incomplete and conflicting information. Background: Medication reconciliation is a method clinicians apply to find and resolve inconsistencies in patients’ medications and medical conditions lists. The cognitive strategies clinicians use during reconciliation are unclear. Controlled lab experiments can explore how clinicians make sense of uncertain, missing, or conflicting information and therefore support the development of a human performance model. We hypothesize that clinicians apply varied cognitive strategies to handle this task and that profession and experience affect these strategies. Method: 130 clinicians participated in a tablet-based experiment conducted in a large American teaching hospital. They were asked to simulate medication reconciliation using a card sorting task (CaST) to organize medication and medical condition lists of a specific clinical case. Later on, they were presented with new information and were asked to add it to their arrangements. We quantitatively and qualitatively analyzed the ways clinicians arranged patient information. Results: Four distinct cognitive strategies were identified (“Conditions first”: n = 76 clinicians, “Medications first”: n = 7, “Crossover”: n = 17, and “Alternating”: n = 10). The strategy clinicians applied was affected by their experience (p = .02) but not by their profession. At the appearance of new information, clinicians moved medication cards more frequently (75.2 movements vs. 49.6 movements, p < .001), suggesting that they match medications to medical conditions. Conclusion: Clinicians apply various cognitive strategies while reconciling medications and medical conditions. Application: Clinical information systems should support multiple cognitive strategies, allowing flexibility in organizing information.
The Discourse of Propaganda in Traveloka’s YouTube Advertising Videos

This present study was conducted to analyze the propaganda techniques used by Traveloka in their YouTube social media advertising strategy. The material of analysis were videos taken from 2015 to 2019. Anaylsis of propaganda techniques proposed by Filene in 1937 and followed by Abd. Kadir, Hasan & Sauffiyan, 2014 were used to identify how Traveloka persuade its customers. Finding shows that Traveloka used six techniques of propaganda in its advertising videos to; glittering generality, plain folks, card staking, visual symbol of power, music of propaganda and arousal of emotion to promote its products. The use of propaganda technique is very likely becoming one of the main reasons behind their customers and target audiences use of their services.
Gig Economy: A Dynamic Principal-Agent Model

The gig economy, where employees take short-term, project-based jobs, is increasingly spreading all over the world. In this paper, we investigate the employer's and the worker's behavior in the gig economy with a dynamic principal-agent model. In our proposed model the worker's previous decisions influence his later decisions through his dynamically changing participation constraint. He accepts the contract offered by the employer when his expected utility is higher than the irrational valuation of his effort's worth. This reference point is based on wages he achieved in previous rounds. We formulate the employer's stochastic control problem and derive the solution in the deterministic limit. We obtain the feasible net wage of the worker, and the profit of the employer. Workers who can afford to go unemployed and need not take a gig at all costs will realize high net wages. Conversely, far-sighted employers who can afford to stall production will obtain high profits.
SWIR Photodetection and Visualization Realized by Incorporating an Organic SWIR Sensitive Bulk Heterojunction

Short‐wavelength infrared (SWIR) photodetection and visualization has profound impacts on different applications. In this work, a large‐area organic SWIR photodetector (PD) that is sensitive to SWIR light over a wavelength range from 1000 to 1600 nm and a SWIR visualization device that is capable of upconverting SWIR to visible light are developed. The organic SWIR PD, comprising an organic SWIR sensitive blend of a near‐infrared polymer and a nonfullerene n‐type small molecule SWIR dye, demonstrates an excellent capability for real‐time heart rate monitoring, offering an attractive opportunity for portable and wearable healthcare gadgets. The SWIR‐to‐visible upconversion device is also demonstrated by monolithic integration of an organic SWIR PD and a perovskite light‐emitting diode, converting SWIR (1050 nm) to visible light (516 nm). The most important attribute of the SWIR visualizing device is its solution fabrication capability for large‐area SWIR detection and visualization at a low cost. The results are very encouraging, revealing the exciting large‐area SWIR photodetection and visualization for a plethora of applications in environmental pollution, surveillance, bioimaging, medical, automotive, food, and wellness monitoring.
Decomposing Real Wage Changes in the United States

We employ CPS data to analyze the sources of hourly real wage changes in the United States for 1976 to 2016 at various quantiles of the wage distribution. We account for the selection bias from the annual hours of work decision by developing and implementing an estimator for nonseparable selection models with censored selection rules. We then decompose wage changes into composition, structural and selection effects. Composition effects have increased wages at all quantiles but the patterns of wage changes are generally determined by the structural effects. Evidence of changes in the selection effects only appear at lower quantiles of the female wage distribution. The combination of these various components produce a substantial increase in wage inequality. This increase has been exacerbated by the changes in females' working hours.
Robust Nearly-Efficient Estimation of Large Panels With Factor Structures

This paper studies estimation of linear panel regression models with heterogeneous coefficients, when both the regressors and the residual contain a possibly common, latent, factor structure. Our theory is (nearly) efficient, because based on the GLS principle, and also robust to the specification of such factor structure because it does not require any information on the number of factors nor estimation of the factor structure itself. We first show how the unfeasible GLS estimator not only affords an efficiency improvement but, more importantly, provides a bias-adjusted estimator with the conventional limiting distribution, for situations where the OLS is affected by a first-order bias. The technical challenge resolved in the paper is to show how these properties are preserved for a class of feasible GLS estimators in a double-asymptotics setting. Our theory is illustrated by means of Monte Carlo exercises and, then, with an empirical application using individual asset returns and firms' characteristics data.