Miracle-dz/UniFAR-FTUs huggingface dataset:
The Geographical Determinants of Within-City Heterogeneity in Urban Density

This paper studies the impact of building land limitations on within-city variation in urban density and its components crowding, residential coverage, and building height. We utilise geographical obstacles like steep inclines or water bodies as exogenous source of building land limitations within parts of cities. We combine novel high resolution (10m x 10m) geo-spatial data on geography, building height and footprints with Norwegian register data. Our unit of observation are neighborhoods with an average size of 0.3 sqkm. The data indicates a high heterogeneity among the components of urban density for similar total density levels. Our main finding is that local building land limitations increase local urban density and all of its components, with the effect being particularly strong for building heights. Hence, we find support for policies that use building land restrictions to alter urban density within parts of cities. Moreover, we show that geography is another important source of inner-city heterogeneity in urban density, in addition to distance to the city center. JEL-Codes: R230, R310, R210, C800.
Design of Hesitation Gestures for Nonverbal Human-Robot Negotiation of Conflicts

When the question of who should get access to a communal resource first is uncertain, people often negotiate via nonverbal communication to resolve the conflict. What should a robot be programmed to do when such conflicts arise in Human-Robot Interaction? The answer to this question varies depending on the context of the situation. Learning from how humans use hesitation gestures to negotiate a solution in such conflict situations, we present a human-inspired design of nonverbal hesitation gestures that can be used for Human-Robot Negotiation. We extracted characteristic features of such negotiative hesitations humans use, and subsequently designed a trajectory generator (Negotiative Hesitation Generator) that can re-create the features in robot responses to conflicts. Our human-subjects experiment demonstrates the efficacy of the designed robot behaviour against non-negotiative stopping behaviour of a robot. With positive results from our human-robot interaction experiment, we provide a validated trajectory generator with which one can explore the dynamics of human-robot nonverbal negotiation of resource conflicts.
Accessible Web Development

There are a growing number of jobs related to web development, yet there is little formal literature about the accessibility of web development with a screen reader. This article describes research to explore (1) web development accessibility issues and their impact on blind learners and programmers; (2) tools and strategies used to address issues; and (3) opportunities for creating inclusive web development curriculum and supportive tools. We conducted a Comprehensive Literature Review (CLR) to formulate accessibility issue categories, then interviewed 12 blind programmers to validate and expand on both issues in education and practice. The CLR yielded five issue categories: (1) visual information without an accessible equivalent, (2) orienting, (3) navigating, (4) lack of support, and (5) knowledge and use of supportive technologies. Our interview findings validated the use of CLR-derived categories and revealed nuances specific to learning and practicing web development. Blind web developers grapple with the inaccessibility of demonstrations and explanations of web design concepts, wireframing software, independent verification of computed Cascading Style Sheets (CSS), and navigating browser-based developer tool interfaces. Tools and strategies include seeking out alternative education materials to learn independently, use of CSS frameworks, collaboration with sighted colleagues, and avoidance of design and front-end development. This work contributes to our understanding of accessibility issues specific to web development and the strategies that blind web developers employ in both educational and applied contexts. We identify areas in which greater awareness and application of accessibility best practices are required in Web education, a need to disseminate existing screen reader strategies and accessible tools, and to develop new tools that support Web design and validation of CSS. Finally, this research signals future directions for the development of accessible web curriculum and supportive tools, including solutions that leverage artificial intelligence, tactile graphics, and supportive-online communities of practice.
Wide Area Network Autoscaling for Cloud Applications

Modern cloud orchestrators like Kubernetes provide a versatile and robust way to host applications at scale. One of their key features is autoscaling, which automatically adjusts cloud resources (compute, memory, storage) in order to adapt to the demands of applications. However, the scope of cloud autoscaling is limited to the datacenter hosting the cloud and it doesn't apply uniformly to the allocation of network resources. In I/O-constrained or data-in-motion use cases this can lead to severe performance degradation for the application. For example, when the load on a cloud service increases and the Wide Area Network (WAN) connecting the datacenter to the Internet becomes saturated, the application flows experience an increase in delay and loss. In many cases this is dealt with overprovisioning network capacity, which introduces additional costs and inefficiencies. On the other hand, thanks to the concept of "Network as Code", the WAN exposes a set of APIs that can be used to dynamically allocate and de-allocate capacity on-demand. In this paper we propose extending the concept of cloud autoscaling into the network to address this limitation. This way, applications running in the cloud can communicate their networking requirements, like bandwidth or traffic profile, to a Software-Defined Networking (SDN) controller or Network as a Service (NaaS) platform. Moreover, we aim to define the concepts of vertical and horizontal autoscaling applied to networking. We present a prototype that automatically allocates bandwidth to the underlay network, according to the requirements of the applications hosted in Kubernetes. Finally, we discuss open research challenges.
TCN-Based Diagnostic Model for the Severity of Coronary Atherosclerotic Heart Disease Using Wrist Pulse Wave Sequence

The pulse wave at the human radial artery is closely related to the health status of the cardiovascular system. In this paper, the morphological features of the pulse wave were used to establish a diagnostic model for the severity of coronary atherosclerotic heart disease (CAD). Features of waveform variations were extracted from pulse wave sequences by building a deep learning network, Temporal Convolutional Network (TCN), which mined more detailed waveform information and obtained more comprehensive features of waveform morphology than the classical time domain features extraction method, thus established a TCN-based CAD severity diagnostic model (TCSDM) with better performance. The 64 features extracted by TCN have shown significant differences between the three classes of CAD samples at the 0.05 level, which have provided additional basis for the model's classification decisions. The accuracy of TCSDM has reached 91.17%, an 11.93% improvement compared to the Random Forest-based diagnostic model using classical time domain features. The proposed method for the acquisition of pulse wave morphological features can effectively extract the differential features of different pulse waves. And this method has a great application value in the remote diagnosis of CAD severity because it's non-invasive, rapid and low-cost.
IntQOE: Integrated End-to-end QoE Optimization for Edge Computing Enabled Web Application

Global microservice spanning multi-clusters is an important setting for edge computing enabled web applications, which are usually quality of experience (QoE) sensitive. The end-to-end QoE optimization is important but challenging for such a setting. Although the existing QoE-aware load balancing solution has been verified in the single cluster setting, to apply it into the multi-cluster setting like the edge computing setting, we found the global server load balancer (GSLB) may make the end-to-end QoE suboptimal. Because of some unpredictable behaviors, the end-to-end QoE optimization over the GSLB and the edge cluster is difficult. To address this, we design IntQOE, a load balance coordination system, which allows accurate and efficient information exchange between the upstream load balancer (the resource controller in the edge cluster) and the downstream load balancer (GSLB). Using a trace-driven simulation, we demonstrate that IntQOE can get stable near-optimal QoE. To compare with latency-based GSLB, IntQOE can improve the end-to-end QoE by over 30% on average.
Psychometric assessment of the Swedish version of the injustice experience questionnaire among patients with chronic pain

Abstract Objectives The use of the Injustice Experience Questionnaire (IEQ) in psychological assessment of individuals with chronic pain is supported by research. The psychometric properties of the Swedish version, the IEQ-S, has not yet been evaluated. Hence, the aim was to investigate structural validity, and concurrent criterion validity of the IEQ-S against the Work Ability Index (WAI), the Pain Catastrophizing Scale (PCS-SW), the Patient Health Questionnaire 9-item depression module (PHQ-9), and the Generalized anxiety disorder 7-item scale (GAD-7). Internal consistency and test-retest reliability were also studied. Methods Sixty-five participants, referred to a University hospital, with a pain duration over three months were consecutively sampled. They completed the IEQ-S at admission and again within six weeks. A confirmatory factor analysis was performed for the study of structural validity. Concurrent criterion validity was evaluated using Spearman’s correlation coefficient. Internal consistency reliability for the full IEQ-S was calculated using the Cronbach’s alpha. Test-retest reliability was calculated using an Intraclass Correlation Coefficient (ICC). Results The median total score (0–48, where high scores indicate high levels of injustice) at admission (test 1) was 27.0 (n=64), 25th percentile=15.3, 75th percentile=37.8, range=3–48 points. A one-factor model was supported with item-loadings between 0.67–0.92. Spearman’s correlation coefficient between the IEQ-S and the WAI (n=56) was r S =−0.46; the PCS-SW (n=63) was r S =0.68, the PHQ-9 (n=64) was r S =0.50 and the GAD-7 (n=64) was r S =0.57, p<0.01. Cronbach’s alpha was 0.94 (n=64). The ICC was 0.80 (n=55), with a 95% confidence interval, ranging between 0.69–0.88. Conclusions Our study supported structural validity and concurrent criterion validity of the IEQ-S against other measures of psychological constructs and work ability. It also supported the internal consistency reliability of the IEQ-S and the test-retest reliability with a retest interval up to six weeks, was good. These findings support the use of the IEQ-S as an adjunct tool to assess appraisals of injustice in patients with chronic pain who are referred to tertiary care in Sweden. The added value might be identification of those who are at risk for slow or no improvement in their pain condition over time, and sick-leave, but this has to be confirmed in future studies. Ethical committee number EPN Uppsala D-No 2016-376.
“The Return of the Prodigal Son” Oxidative Stress, Antioxidant Solutions and their Place in the Modern Medical Practice

When discussing “antioxidants” or “oxidative stress” most of us feel a sense of confusion while these terms are rooted in the collective mind of the medical body as part of discussions from areas where scientific proof is not always strictly necessary. Antioxidants are more often associated with cosmetic products or diets that are intensely discussed about in media circles where the medical world does not seek the scientific truths. Unlike “inflammation” and “anti-inflammatories”, subjects that are recognized as deeply rooted in the complicated puzzle of the medical rationale for not only rheumatoid ailments, but also the digestive, renal or even cardiovascular ones. Ed torial
Evaluation of cognation judgments undermines computational phylogeny of the Arawakan language family

The goal of this paper is to critically examine the linguistic analyses underlying Walker & Ribeiro (2011), a widely cited computational phylogenetic study of the Arawakan language family. To the extent that their claims concerning the internal classification of this vast group of languages hinges on their cognation judgments, and that their more ambitious claims concerning prehistoric migration routes of Arawakan-speaking peoples depend, in turn, on this proposed internal classification, I show that outright rejection of their results is highly commendable. Errors include both false negatives, where cognation relations between comparanda were missed, as well as false positives, where non-cognate material in different languages were judged to be reflexes of single Proto-Arawakan etyma. No clear pattern seems to emerge from their cognation decisions, and the resulting judgments seem to be, in many cases, so strongly detached from even impressionistic assessments of similarity that the resulting distribution of cognation scores could have been produced independently of the data. The paper ends with a plea for greater sobriety in the historical linguistics of native South America, which should focus on clear and well-supported applications of the comparative method before embarking on endeavors that depend on this traditional work for their success. More importantly, though, South Americanists should avoid groundless statements on the supposed uselessness, or exhaustion, of the comparative method as a tool for uncovering the linguistic history of the continent.
Connectivity between the hippocampus and default mode network during the relief – but not elicitation – of curiosity supports curiosity-enhanced memory enhancements

Consistent with the idea that curiosity enhances information seeking, it has been shown that activity within both the dopaminergic circuit and hippocampus supports curiosity-enhanced learning. However, the role of whole-brain mechanisms involved in cognitive control (fronto-parietal network; FPN) and memory integration (default mode network; DMN) that might underpin curiosity states and their effects on memory remain elusive. We hypothesised that the FPN and DMN should distinguish between high- and low-curiosity conditions and be recruited more heavily for later remembered information associated with high-curiosity. Here, we used functional magnetic resonance imaging whilst participants completed a trivia paradigm, in which we presented trivia questions associated with high- and low-curiosity, followed by the associated answer. After a short delay, we tested memory for trivia answers. We adopted a network-based parcellation of the brain into subnetworks of the FPN and DMN to examine how neural activity within, and functional connectivity between, each subnetwork predicts curiosity-enhanced memory. Across elicitation and relief of curiosity, we found focal recruitment of FPNA and widespread recruitment of DMN subnetworks in support of curiosity and curiosity-enhanced memory. Most importantly, during the elicitation of curiosity, functional subcortical connectivity and across cortical networks, but not subcortical-cortical coupling, correlated with curiosity-enhanced memory. However, during the relief of curiosity, coupling between subcortical regions and DMNA emerged in support of curiosity-enhanced memory. Taken together, our results provide the first evidence about how neuromodulatory mechanisms via the hippocampal-dopaminergic circuit trigger states of curiosity and thereby communicate to higher-order cortical regions to facilitate curiosity-enhanced memory. Significant statement Does neural activity within, and functional connectivity between, the dopaminergic-hippocampal network, fronto-parietal network (FPN), and default mode network (DMN) underpin curiosity states and their effects on memory? Here, we show how the dopaminergic system together with the hippocampus interact specifically with subnetwork DMNA potentially reflecting how subcortical regions support the enhancement of memory intergration of semantic information associated with curiosity. As DMNA (the core DMN subnetwork) was also functionally coupled with the whole DMN network and the semantic control network (FPNA), these findings provide a plausible neuromodulatory mechanism through which hippocampal-dopaminergic input triggers curiosity and then communicates to higher-order brain regions via DMNA to facilitate curiosity-enhanced memory.
Miniature Inverted-repeat Transposable Elements Drive Rapid MicroRNA Diversification in Angiosperms

MicroRNAs (miRNAs) are rapidly evolving endogenous small RNAs programing organism function and behavior. Although models for miRNA origination have been proposed based on sporadic cases, the genomic mechanisms driving swift diversification of the miRNA repertoires in plants remain elusive. Here, by comprehensively analyzing 20 phylogenetically representative plant species, we identified miniature inverted-repeat transposable elements (MITEs) as the predominant genomic sources for de novo miRNAs in angiosperms. Our data illustrated a transposition-transcription process whereby properly sized MITEs transposed into active genic regions could be converted into new miRNAs, termed MITE-miRNAs, in as few as 20 generations. We showed that this molecular domestication mechanism leads to a possible evolutionary arms race between the MITEs and the host genomes that rapidly and continuously changes the miRNA repertoires. We found that the MITE-miRNAs are selected for targeting genes associated with plant adaptation and habitat expansion, thereby constituting a genomic innovation potentially underlying angiosperm megadiversity.
Theoretical Comparative Study of Quantum Dot Solar Cell Behavior for Single and Multi-Intermediate Bands

AbstractIn this paper, the mathematical model of the intermediate band quantum dot solar cell (IBQDSC) is investigated by using one and two intermediate bands (IBs). The IBs arise from the quantum dot (QD) semiconductor material within the barrier bandgap energy. Some factors, such as the thickness of the quantum dot (TQD) and the thickness of the barrier or inter-dot distances between quantum dots (TB), are studied to show their influence on the performance of the IBQDSC. In the proposed model, the cubic shape of QDs from InAs0.9N0. 1 and the barrier or bulk semiconductor material from GaAs0.98Sb0. 02 are utilized. The time-independent Schrodinger equation is solved by employing the Kronig-Penney model. From the obtained results, after a homogenous range of the TQD and TB is assigned for each one IB (1IB) and two IBs (2IBs) quantum dot solar cells (QDSCs), various comparative studies between the induced efficiency and the parameters of 1IB and 2IB QDSCs are investigated for one and maximum sun concentratio.
Overexpression of the Gene Encoding Neurosecretory Protein GL Precursor Prevents Excessive Fat Accumulation in the Adipose Tissue of Mice Fed a Long-Term High-Fat Diet

We previously identified a novel small hypothalamic protein, neurosecretory protein GL (NPGL), which induces feeding behavior and fat accumulation in rodents depending on their diet. In the present study, we explored the effects of NPGL on feeding behavior and energy metabolism in mice placed on a long-term high-fat diet with 60% calories from fat (HFD 60). Overexpression of the NPGL precursor gene (Npgl) over 18 weeks increased food intake and body mass. The weekly body mass gain of Npgl-overexpressing mice was higher than that of controls until 7 weeks from induction of overexpression, after which it ceased to be so. Oral glucose tolerance tests showed that Npgl overexpression maintained glucose tolerance and increased blood insulin levels, and intraperitoneal insulin tolerance tests showed that it maintained insulin sensitivity. At the experimental endpoint, Npgl overexpression was associated with increased mass of the perirenal white adipose tissue (WAT) and decreased mass of the epididymal WAT (eWAT), resulting in little effect on the total WAT mass. These results suggest that under long-term HFD 60 feeding, Npgl overexpression may play a role in avoiding metabolic disturbance both by accelerating energy storage and by suppressing excess fat accumulation in certain tissues, such as the eWAT.
Software for Non-Parametric Image Registration of 2-Photon Imaging Data

Functional 2-photon microscopy is a key technology for imaging neuronal activity. The recorded image sequences, however, can contain non-rigid movement artifacts which requires high-accuracy movement correction. Variational optical flow (OF) estimation is a group of methods for motion analysis with established performance in many computer vision areas. However, it has yet to be adapted to the statistics of 2-photon neuroimaging data. In this work, we present the motion compensation method Flow-Registration that outperforms previous alignment tools and allows to align and reconstruct even low signal-to-noise ratio 2-photon imaging data and is able to compensate high-divergence displacements during local drug injections. The method is based on statistics of such data and integrates previous advances in variational OF estimation. Our method is available as an easy-to-use ImageJ / FIJI plugin as well as a MATLAB toolbox with modular, object oriented file IO, native multi-channel support and compatibility with existing 2-photon imaging suites.
Low affinity integrin states have faster binding kinetics than the high affinity state

Integrin conformational ensembles contain two low-affinity states, bent-closed and extended-closed, and an active, high-affinity, extended-open state. It is widely thought that integrins must be activated before they bind ligand; however, one model holds that activation follows ligand binding. As ligand-binding kinetics are not only rate limiting for cell adhesion but also have important implications for the mechanism of activation, we measure them here for integrins α4β1 and α5β1 and show that the low-affinity states bind substantially faster than the high-affinity state. On and off-rate measurements are similar for integrins on cell surfaces and ectodomain fragments. Although the extended-open conformation’s on-rate is ∼20-fold slower, its off-rate is ∼25,000-fold slower, resulting in a large affinity increase. The tighter ligand-binding pocket in the open state may slow its on-rate. These kinetic measurements, together with previous equilibrium measurements of integrin conformational state affinity and relative free energy on intact cells, are key to a definitive understanding of the mechanism of integrin activation.
Distinct mechanisms underlie H2O2 sensing in C. elegans head and tail

Environmental oxidative stress threatens cellular integrity and should therefore be avoided by living organisms. Yet, relatively little is known about environmental oxidative stress perception. Here, using microfluidics, we showed that like I2 pharyngeal neurons, the tail phasmid PHA neurons function as oxidative stress sensing neurons in C. elegans, but display different responses to H2O2 and light. We uncovered that different but related receptors, GUR-3 and LITE-1, mediate H2O2 signaling in I2 and PHA neurons. Still, the peroxiredoxin PRDX-2 is essential for both, and might promote H2O2-mediated receptor activation. Our work demonstrates that C. elegans can sense a broad range of oxidative stressors using partially distinct H2O2 signaling pathways in head and tail sensillae, and paves the way for further understanding of how the integration of these inputs translates into the appropriate behavior. Graphical abstract