Miracle-dz/UniFAR-FTUs huggingface dataset:
Model Predictive Stabilization Control of High-Speed Autonomous Ground Vehicles Considering the Effect of Road Topography

This paper presents a model predictive control (MPC) scheme for the stabilization of high-speed autonomous ground vehicles (AGVs) considering the effect of road topography. Accounting for the road curvature and bank angle, a single-track dynamic model with roll dynamics is derived. Variable time steps are utilized for vehicle model discretization, enabling collision avoidance in the long-term without compromising the prediction accuracy in the near-term. Accordingly, safe driving constraints including the sideslip envelope, zero-moment-point and lateral safety corridor are developed to handle stability and obstacle avoidance. Taking these constraints into account, an MPC problem is formulated and solved at each step to determine the optimal steering control commands. Moreover, feedback corrections are integrated into the MPC to compensate the unmodeled dynamics and parameter uncertainties. Comparative simulations validate the capability and real-time ability of the proposed control scheme.
Koszul duality for locally constant factorization algebras

Generalising Jacob Lurie's idea on the relation between the Verdier duality and the iterated loop space theory, we study the Koszul duality for locally constant factorisation algebras. We formulate an analogue of Lurie's "nonabelian Poincare duality" theorem (which is closely related to earlier results of Graeme Segal, of Dusa McDuff, and of Paolo Salvatore) in a symmetric monoidal stable infinity category carefully, using John Francis' notion of excision. Its proof depends on our earlier study of the Koszul duality for E_n-algebras. As a consequence, we obtain a Verdier type equivalence for factorisation algebras by a Koszul duality construction.
The contribution of DNA repair pathways to genome editing and evolution in filamentous pathogens

Abstract DNA double-strand breaks require repair or risk corrupting the language of life. To ensure genome integrity and viability, multiple DNA double-strand break repair pathways function in eukaryotes. Two such repair pathways, canonical non-homologous end joining and homologous recombination, have been extensively studied, while other pathways such as microhomology-mediated end joint and single-strand annealing, once thought to serve as back-ups, now appear to play a fundamental role in DNA repair. Here, we review the molecular details and hierarchy of these four DNA repair pathways, and where possible, a comparison for what is known between animal and fungal models. We address the factors contributing to break repair pathway choice, and aim to explore our understanding and knowledge gaps regarding mechanisms and regulation in filamentous pathogens. We additionally discuss how DNA double-strand break repair pathways influence genome engineering results, including unexpected mutation outcomes. Finally, we review the concept of biased genome evolution in filamentous pathogens, and provide a model, termed Biased Variation, that links DNA double-strand break repair pathways with properties of genome evolution. Despite our extensive knowledge for this universal process, there remain many unanswered questions, for which the answers may improve genome engineering and our understanding of genome evolution.
Effects of Small Molecule Ligands on ACKR3 Receptors

Chemokines such as stromal derived factor 1 and their G protein coupled receptors are well-known regulators of the development and functions of numerous tissues. C-X-C motif chemokine ligand 12 (CXCL12) has two receptors: C-X-C chemokine motif receptor 4 (CXCR4) and atypical chemokine receptor 3 (ACKR3). ACKR3 has been described as an atypical “biased” receptor because it does not appear to signal through G proteins and, instead, signals solely through the β-arrestin pathway. In support of this conclusion, we have shown that ACKR3 is unable to signal through any of the known mammalian Gα isoforms and have generated a comprehensive map of the Gα activation by CXCL12/CXCR4. We also synthesized a series of small molecule ligands which acted as selective agonists for ACKR3 as assessed by their ability to recruit β-arrestin to the receptor. Using select point mutations, we studied the molecular characteristics that determine the ability of small molecules to activate ACKR3 receptors, revealing a key role for the deeper binding pocket composed of residues in the transmembrane domains of ACKR3. The development of more selective ACKR3 ligands should allow us to better appreciate the unique roles of ACKR3 in the CXCL12/CXCR4/ACKR3-signaling axis and better understand the structural determinants for ACKR3 activation. SIGNIFICANCE STATEMENT We are interested in the signaling produced by the G protein coupled receptor atypical chemokine receptor 3 (ACKR3), which signals atypically. In this study, novel selective ligands for ACKR3 were discovered and the site of interactions between these small molecules and ACKR3 was defined. This work will help to better understand the unique signaling roles of ACKR3.
Cerambycid pheromones affect catches of Phymatodes aeneus (Coleoptera: Cerambycidae) and Thanasimus undatulus (Coleoptera: Cleridae) in ethanol-baited multiple-funnel traps in the Pacific Northwest, United States of America

Abstract In 2012, we evaluated the effects of hardwood cerambycid pheromones (syn-2,3-hexanediol, 3-hydroxyhexan-2-one, and 3-hydroxyoctan-2-one) on catches of bark and woodboring beetles in ethanol-baited multiple-funnel traps in two field trials in Oregon and Washington, United States of America. Catches of Phymatodes aeneus LeConte (Coleoptera: Cerambycidae) in ethanol-baited traps increased with the addition of 3-hydroxyhexan-2-one lures or the 3,2-hydroxyketone lure blend (3-hydroxyhexan-2-one + 3-hydroxyoctan-2-one). Catches of the predator Thanasimus undatulus (Say) (Coleoptera: Cleridae) in ethanol-baited traps increased with the addition of 3-hydroxyhexan-2-one lures but not syn-2,3-hexanediol lures or 3-hydroxyoctan-2-one lures. The 3,2-hydroxyketone lure blend decreased catches of the corthyline ambrosia beetle, Gnathotrichus sulcatus (LeConte) (Coleoptera: Curculionidae), but not the xyleborine ambrosia beetle, Xyleborinus saxesenii (Ratzeburg), (Coleoptera: Curculionidae). Catches of Ptilinus basalis LeConte (Coleoptera: Anobiidae) in ethanol-baited traps increased with the addition of the 3,2-hydroxyketone lure blend.
Application of recommender systems and time series models to monitor quality at HIV/AIDS health facilities

Abstract The US government invests substantial sums to control the HIV/AIDS epidemic. To monitor progress toward epidemic control, PEPFAR, or the President’s Emergency Plan for AIDS Relief, oversees a data reporting system that includes standard indicators, reporting formats, information systems, and data warehouses. These data, reported quarterly, inform understanding of the global epidemic, resource allocation, and identification of trouble spots. PEPFAR has developed tools to assess the quality of data reported. These tools made important contributions but are limited in the methods used to identify anomalous data points. The most advanced consider univariate probability distributions, whereas correlations between indicators suggest a multivariate approach is better suited. For temporal analysis, the same tool compares values to the averages of preceding periods, though does not consider underlying trends and seasonal factors. To that end, we apply two methods to identify anomalous data points among routinely collected facility-level HIV/AIDS data. One approach is Recommender Systems, an unsupervised machine learning method that captures relationships between users and items. We apply the approach in a novel way by predicting reported values, comparing predicted to reported values, and identifying the greatest deviations. For a temporal perspective, we apply time series models that are flexible to include trend and seasonality. Results of these methods were validated against manual review (95% agreement on non-anomalies, 56% agreement on anomalies for recommender systems; 96% agreement on non-anomalies, 91% agreement on anomalies for time series). This tool will apply greater methodological sophistication to monitoring data quality in an accelerated and standardized manner.
‘It starts when teachers are training’: The role of generalist and designated teachers in the educational experiences of children in care

This article assesses the significance of generalist and designated schoolteachers for the educational experiences of children in care. Data were gathered from semi-structured interviews with 21 care-experienced individuals aged between 18 and 27 and three senior employees of a children’s services department in an English local authority. Participants discussed the importance of relationships with key adults and peers, the complexity of disclosing their care status and their commitment to education. The results show that generalist teachers offer considerable support to children, far beyond their statutory responsibilities, but that the designated teacher role, although important, is not understood or utilised by their fellow teachers and the majority of pupils who are in care.
Parallel Cover Trees and their Applications

The cover tree is the canonical data structure that efficiently maintains a dynamic set of points on a metric space and supports nearest and k-nearest neighbor searches. For most real-world datasets with reasonable distributions (constant expansion rate and bounded aspect ratio mathematically), single-point insertion, single-point deletion, and nearest neighbor search (NNS) only cost logarithmically to the size of the point set. Unfortunately, due to the complication and the use of depth-first traversal order in the cover tree algorithms, we were unaware of any parallel approaches for these cover tree algorithms. This paper shows highly parallel and work-efficient cover tree algorithms that can handle batch insertions (and thus construction) and batch deletions. Assuming constant expansion rate and bounded aspect ratio, inserting or deleting m points into a cover tree with n points takes O(m log n) expected work and polylogarithmic span with high probability. Our algorithms rely on some novel algorithmic insights. We model the insertion and deletion process as a graph and use a maximal independent set (MIS) to generate tree nodes without conflicts. We use three key ideas to guarantee work-efficiency: the prefix-doubling scheme, a careful design to limit the graph size on which we apply MIS, and a strategy to propagate information among different levels in the cover tree. We also use path-copying to make our parallel cover tree a persistent data structure, which is useful in several applications. Using our parallel cover trees, we show work-efficient (or near-work-efficient) and highly parallel solutions for a list of problems in computational geometry and machine learning, including Euclidean minimum spanning tree (EMST), single-linkage clustering, bichromatic closest pair (BCP), density-based clustering and its hierarchical version, and others. To the best of our knowledge, many of them are the first solutions to achieve work-efficiency and polylogarithmic span assuming constant expansion rate and bounded aspect ratio.
Capturing recovery capital: using photovoice to unravel recovery and desistance

Abstract Purpose Photovoice, a community-based participatory research strategy, allows participants to take up an active role in data collection by discussing their views and life (conditions) based on the photographs they have taken. In this methodological article, we present a case study in which photovoice was used to unravel the meaning of recovery capital. Recovery capital is an overarching concept to understand the personal, social and community resources helping people to recover. Method Seven participants in recovery from drug use and desistance from offending took photographs of their lived experiences related to recovery capital. During face-to-face interviews, these photographs were discussed, focusing on recovery capital components. Results The case study led to in-depth insights into the photographs’ meanings and stories from the point of view of the participants. Conclusion This contribution investigates the role of photovoice in expanding our understanding of recovery capital. By means of a case study we highlight the several steps taken by the researcher and the advantages and shortcomings of this method. It appears that photovoice offers great value for eliciting insights in the lived experiences of participants and for participants to grow empowerment and agency. This article hopes to inspire researchers to consider photovoice for their (future) research projects.
Brief Announcement: Distributed Lightweight Spanner Construction for Unit Ball Graphs in Doubling Metrics

Resolving an open question from 2006, we prove the existence of light-weight bounded-degree (1+ε)-spanners for unit ball graphs in the metrics of bounded doubling dimension, and we design a simple O(log*n)-round distributed algorithm in the LOCAL model for finding such spanners using only 2-hop neighborhood information. We further study the problem in the two dimensional Euclidean plane and we propose a construction with similar properties that has a low-intersection property as well. Lastly, we provide experimental results that confirm the performance of our algorithms.
Differential Frequency Heterodyne Time-of-Flight Imaging for Instantaneous Depth and Velocity Estimation

In this study, we discuss the imaging of depth and velocity using heterodyne-mode time-of-flight (ToF) cameras. In particular, Doppler ToF (D-ToF) imaging utilizes heterodyne modulation to measure the velocity from the Doppler frequency shift, which uniquely facilitates the instantaneous radial velocity estimation. However, theoretical discussion on D-ToF is limited to orthogonal frequency and sinusoidal waveform modulation. This study extends the formulation of the D-ToF imaging, and proposes an arbitrary-frequency, arbitrary-waveform framework considering a phase-compensated, symmetrical two-dimensional correlation map. With the proposed framework, the optimal heterodyne frequency for frequency decoding is found. A differential frequency sampling and decoding method is then proposed, which computes the frequency and phase from as few as four simultaneously captured images. With an experiment platform we built, it is confirmed that the minimum velocity sensing error is half that of the orthogonal frequency method, and the sensible phase range is approximately 2.5 times larger. The conclusions in this study allow the ToF velocity imaging to be applied at the optimal sample frequencies for a wide range of ToF sensors. This pushes one step further to the practical use of ToF velocity imaging.
Massively Parallel Algorithms for b-Matching

This paper presents an O(log log đ) round massively parallel algorithm for 1 + ε approximation of maximum weighted b-matchings, using near-linear memory per machine. Here đ denotes the average degree in the graph and ε is an arbitrarily small positive constant. Recall that b-matching is the natural and well-studied generalization of the matching problem where different vertices are allowed to have different numbers of incident edges in the matching.
Nondeterministic Evaluation Mechanism for User Recruitment in Mobile Crowd-Sensing

Based on the Internet of Behavior (IoB), mobile crowd-sensing (MCS) utilizes the Internet of Things (IoT) to recruit users by analyzing behavioral patterns. MCS is widely used in numerous large-scale and complex monitoring services, but it cannot provide stable and high-quality services due to nondeterministic user mobility and behaviors, which has a vital impact on recruiting high-quality users. In this article, a stochastic semi-algebraic hybrid system (SSAHS) model is constructed to characterize the user mobility and behaviors of the MCS systems. Based on the definition of probabilistic path and task execution rate, a nondeterministic evaluation mechanism is proposed to measure nondeterministic user mobility and behaviors and to give the probability of the user completing the MCS task under the specified time bound and space conditions. The greater the probability is, the higher the quality of the user. Furthermore, a user recruitment scheme based on a nondeterministic evaluation mechanism (NUR) is developed. The NUR employs historical user data to predict user mobility and behaviors; high-quality users are recruited to quickly upload reliable sensing data. We conduct simulation experiments based on a real-world user trace dataset, Geolife.The results show that compared with competing recruitment strategies, NUR achieves a higher quality of service for the same MCS sensing tasks.
Combining Human and Machine Confidence in Truthfulness Assessment

Automatically detecting online misinformation at scale is a challenging and interdisciplinary problem. Deciding what is to be considered truthful information is sometimes controversial and also difficult for educated experts. As the scale of the problem increases, human-in-the-loop approaches to truthfulness that combine both the scalability of machine learning (ML) and the accuracy of human contributions have been considered. In this work, we look at the potential to automatically combine machine-based systems with human-based systems. The former exploit superviseds ML approaches; the latter involve either crowd workers (i.e., human non-experts) or human experts. Since both ML and crowdsourcing approaches can produce a score indicating the level of confidence on their truthfulness judgments (either algorithmic or self-reported, respectively), we address the question of whether it is feasible to make use of such confidence scores to effectively and efficiently combine three approaches: (i) machine-based methods, (ii) crowd workers, and (iii) human experts. The three approaches differ significantly, as they range from available, cheap, fast, scalable, but less accurate to scarce, expensive, slow, not scalable, but highly accurate.
THEORY OF COARSE-GRAINED INFORMATION

Measurement should be objective in principle. However, the accuracy of measurement often depends on various factors, including instruments of measurement, adopted intentionally or made available accidentally, and from a practical point of view, it is important to choose a suitable degree of the accuracy of measurement for the intention of measurement. The present paper discusses some information-theoretical aspects of the relationship between the degree of the accuracy of nominal description of objects and the interdependence among groups of those objects within a formal framework of clustering, where a new entropic measure of interdependence is applied to estimate the change of the interdependence when the nominal description becomes morecoarse' so that several objects appear to be identical, and are grouped into the same class. The degree of interdependence is often measured by (sum of entropies of partial systems) - (entropy of the whole). Close examination shows, however, that instead of simple formal entropy we should take rather (the number of the members of a group)× (entropy of the group). The result also implies that in integration of information channels the average entropy plays an important role. A brief discussion is also made on elicitation of so-called information granules.
Dynamics of sleep and feeding homeostasis in Drosophila glia and neurons

In the brain, a homeostatic signal is thought to represent sleep need, steadily increasing during wakefulness and gradually decreasing during sleep. Here, we find that ensheathing glia of Drosophila show the dynamics expected of a sleep homeostat. Calcium levels in these cells – monitored in central brain areas such as the central complex and mushroom bodies – integrate different kinds of behavioral effort across time and reset during sleep. Ensheathing glia track sleep-wake behavior more reliably than other sleep related neurons. Interestingly, sleep-related dFB neurons integrate hunger and are modulated by walking, suggesting a role in feeding homeostasis. Ensheathing glia act as a system for tracking sleep need distributed across brain areas, establishing an interaction between sleep homeostasis and behavior at the level of identified cells and circuits in the fly brain.
Patterns of mortality in domesticated ruminants in Ethiopia

Background In Ethiopia, there are limited data on the causes of ruminant mortality and reproductive losses which is hampering the development of interventions to improve livestock health. The present study aimed to establish the causes and magnitude of mortality and reproductive losses in cattle, sheep and goats across all smallholder production systems in Ethiopia. Methods The study, consisting of three data sources, was conducted to collect data on mortality and reproductive losses in cattle, sheep and goats. Nine regional states; Afar, Amhara, Benishangul Gumuz, Gambela, Harari, Oromia, Southern Nations, Nationalities, and Peoples’ Region, Somali, and Tigray were surveyed, as well as the city administrations of Dire Dawa and Addis Ababa. Questionnaire surveys were conducted with farmers and key stakeholders, as well as data collected from regional diagnostic laboratories. Data from the Living Standards Measurement Study were also included. Generalised linear mixed and hurdle models were used for data analysis, with results summarized using predicted outcomes. Results Analyses indicated that most herds experienced zero mortality and reproductive losses, with rare occasions of larger losses. Diseases causing deaths varied greatly both geographically and over time. There was little agreement between the different datasets. While the models aid the understanding of patterns of mortality and reproductive losses, the degree of variation observed limited the predictive scope. Conclusions The models revealed some insight into why mortality rates are variable over time and are therefore less useful in measuring production or health status, and it is suggested that alternative measures of productivity, such as young stock mortality, would be more stable over time and likely more indicative.