Miracle-dz/UniFAR-FTUs huggingface dataset:
Drag and lift forces on random assemblies of wall-attached spheres in low-Reynolds-number shear flow

Direct numerical simulations of the shear flow over assemblies of uniformly sized, solid spheres attached to a flat wall have been performed using the lattice-Boltzmann method. The random sphere assemblies comprised monolayers, double layers and triple layers. The Reynolds number based on the sphere radius and the overall shear rate was much smaller than 1. The results were interpreted in terms of the drag force (the force in the streamwise direction) and lift force (the force in the wall-normal direction) experienced by the spheres as a function of the denseness of the bed and the depth of the spheres in the bed. The average drag and lift forces decay monotonically as a function of the surface coverage of the spheres in the top layer of the bed. The sphere-to-sphere variation of the drag and lift forces is significant due to interactions between spheres via the interstitial fluid flow.
Mean squared error of prediction approach to the analysis of a combined array

The combined array provides a powerful, more statistically rigorous alternative to Taguchi's crossed-array approach to robust parameter design. The combined array assumes a single linear model in the control and the noise factors. One may then find conditions for the control factors which will minimize an appropriate loss function that involves the noise factors. The most appropriate loss function is often simply the resulting process variance, recognizing that the noise factors are actually random effects in the process. Because the major focus of such an experiment is to optimize the estimated process variance, it is vital to understand the resulting prediction properties. This paper develops the mean squared error for the estimated process variance for the combined array approach, under the assumption that the model is correctly specified. Specific combined arrays are compared for robustness. A practical example outlines how this approach may be used to select appropriate combined arrays within a particular experimental situation.
Baxter ℚ-operator and separation of variables for the open SL(2,ℝ) spin chain

We construct the Baxter -operator and the representation of the Separated Variables (SoV) for the homogeneous open SL(2,) spin chain. Applying the diagrammatical approach, we calculate Sklyanin's integration measure in the separated variables and obtain the solution to the spectral problem for the model in terms of the eigenvalues of the -operator. We show that the transition kernel to the SoV representation is factorized into the product of certain operators each depending on a single separated variable. As a consequence, it has a universal pyramid-like form that has been already observed for various quantum integrable models such as periodic Toda chain, closed SL(2,) and SL(2,) spin chains.
The Extremely Low Luminosity White Dwarf ESO 439–26

We present a detailed analysis of the extremely low luminosity white dwarf ESO 439-26. The measured trigonometric parallax of π = 0. ″0237 ± 0. ″0030, together with the observed V magnitude of 20.52, yields an absolute visual magnitude of MV = 17.4 ± 0.3. ESO 439-26 thus lies more than 1 mag faintward of the observed cutoff of the white-dwarf luminosity function in the Galactic disk and could therefore be the coolest and hence oldest white dwarf ever detected. However, we show from a detailed analysis of the optical energy distribution that the intrinsic low luminosity of ESO 439-26 is the result of its small radius, or large mass. Our best solution is reached with Teff = 4560 ± 100 K, log g = 9.04 ± 0.14, and a pure-helium atmospheric composition. Evolutionary models are used to derive a mass of M = 1.21 ± 0.07 M☉ and a cooling age of 6.4 ± 0.3 Gyr, a value that is smaller than the current estimates of the age of the Galactic disk.
MoCA: a modular RGB color arena for swarm robotics experiments

We present MoCA : an open-source modular system to perform experiments with robot swarms. Robot swarms are self-organized and highly redundant groups of robots that act collectively to achieve a shared goal. The collective behavior of a robot swarm emerges from the interaction that individual robots have with their peers, and with objects in the scenario where they operate. MoCA provides tools to create, simulate, and physically deploy scenarios where robots react to the color displayed by programmable RGB modules. Users of MoCA can create these scenarios—also known as robot arenas— by assembling the RGB modules in polygonal structures that enclose the workspace of the robots. We describe the hardware and software architecture of MoCA , and we point to the repositories that have the resources to build and operate the system; as well as a plug-in to simulate the system in ARGoS3. MoCA has been used to conceive scenarios and missions in two swarm robotics studies: (i) swarms of e-puck robots that operate with control software produced via optimization; and (ii) swarms of e-puck robots that coordinate using indirect communication. The robot platform we target is the e-puck robot and the implementation of MoCA we present here is made to work with this robot.
LADIS: Language Disentanglement for 3D Shape Editing

Natural language interaction is a promising direction for democratizing 3D shape design. However, existing methods for text-driven 3D shape editing face challenges in producing decoupled, local edits to 3D shapes. We address this problem by learning disentangled latent representations that ground language in 3D geometry. To this end, we propose a complementary tool set including a novel network architecture, a disentanglement loss, and a new editing procedure. Additionally, to measure edit locality, we define a new metric that we call part-wise edit precision. We show that our method outperforms existing SOTA methods by 20% in terms of edit locality, and up to 6.6% in terms of language reference resolution accuracy. Our work suggests that by solely disentangling language representations, downstream 3D shape editing can become more local to relevant parts, even if the model was never given explicit part-based supervision.
An Algorithm for Learning Switched Linear Dynamics from Data

We present an algorithm for learning switched linear dynamical systems in discrete time from noisy observations of the system’s full state or output. Switched linear systems use multiple linear dynamical modes to fit the data within some desired tolerance. They arise quite naturally in applications to robotics and cyber-physical systems. Learning switched systems from data is a NP-hard problem that is nearly identical to the k -linear regression problem of fitting k > 1 linear models to the data. A direct mixed-integer linear programming (MILP) approach yields time complexity that is exponential in the number of data points. In this paper, we modify the problem formulation to yield an algorithm that is linear in the size of the data while remaining exponential in the number of state variables and the desired number of modes. To do so, we combine classic ideas from the ellipsoidal method for solving convex optimization problems, and well-known oracle separation results in non-smooth optimization. We demonstrate our approach on a set of microbenchmarks and a few interesting real-world problems. Our evaluation suggests that the benefits of this algorithm can be made practical even against highly optimized off-the-shelf MILP solvers.
X-RAY VARIABILITY OF ACTIVE GALACTIC NUCLEI IN THE SOFT AND HARD X-RAY BANDS

We investigate the X-ray variability characteristics of hard X-ray-selected active galactic nuclei (AGNs)—based on Swift/Burst Alert Telescope—in the soft X-ray band using the Rossi X-ray Timing Explorer/All-Sky Monitor (RXTE/ASM) data. The uncertainties involved in the individual dwell measurements of the ASM are critically examined, and a method is developed to combine a large number of dwells with appropriate error propagation to derive long-duration flux measurements (greater than 10 days). We also provide a general prescription to estimate the errors in variability derived from rms values from unequally spaced data. Though the derived variability for individual sources is not of very high significance, we find that, in general, the soft X-ray variability is higher than that in hard X-rays, and the variability strengths decrease with energy for the diverse classes of AGNs. We also examine the strength of variability as a function of the break timescale in the power density spectrum (derived from the estimated mass and bolometric luminosity of the sources) and find that the data are consistent with the idea of higher variability at timescales longer than the break timescale.
Sacred Ecology: The Environmental Impact of African Traditional Religions

Do religions codify ecological principles? This paper explores theoretically and empirically the role religious beliefs play in shaping environmental interactions. We study African Traditional Religions (ATR) which place forests within a sacred sphere. We build a model of non-market interactions of the mean-field type where the actions of agents with heterogeneous religious beliefs continuously affect the spatial density of forest cover. The equilibrium extraction policy shows how individual beliefs and their distribution among the population can be a key driver of forest conservation. The model also characterizes the role of resource scarcity in both individual and population extraction decisions. We test the model predictions empirically relying on the unique case of Benin, where ATR adherence is freely reported. Using an instrumental variable strategy that exploits the variation in proximity to the Benin-Nigerian border, we find that a 1 standard deviation increase in ATR adherence has a 0.4 standard deviation positive impact on forest cover change. We study the impact of historically belonging to the ancient Kingdom of Dahomey, birthplace of the Vodun religion. Using the original boundaries as a spatial discontinuity, we find positive evidence of Dahomey affiliation on contemporary forest change. Lastly, we compare observed forest cover to counterfactual outcomes by simulating the absence of ATR beliefs across the population.
Handbook of Biometric Anti-Spoofing - Trusted Biometrics under Spoofing Attacks

This chapter discusses the use of biometrics techniques within forensic science. common and familiar biometric features, face, and then examines. Handbook of Biometric Anti-Spoofing Download Book (PDF, 10713kb) Blomme J (2003) Evaluation of biometric security systems against artificial fingers. Slides : PDF. Videos : Part 1, Part 2, Part 3 He is the co-Editor of the Handbook of Biometric Anti-Spoofing published by Springer. He is Guest Editor.
Construction of ceRNA network and key gene screening in cervical squamous intraepithelial lesions

Background: This study aimed to construct an endogenous competition network for cervical squamous intraepithelial lesions using differential gene screening. Methods: GSE149763 was used to screen differentially expressed long non-coding RNAs (lncRNAs) and mRNAs to predict correlated microRNAs (miRNAs). The correlated miRNAs and GSE105409 were used to screen differentially expressed miRNAs for differential co-expression analysis, and the co-expressed differentially expressed miRNAs were used to predict correlated mRNAs. Differentially expressed mRNAs, miRNAs, and lncRNAs were visualized, and differential gene screening, enrichment, and pathway analysis were performed. Results: The ceRNA network of cervical squamous intraepithelial was successfully established and a potential differentially expressed network was identified. The key genes were VEGFA and FOS, and the key pathway was the MAPK signaling pathway. Conclusions: The differential expression and potential effects of the lncRNA BACH1-IT1/miR-140-5p/VEGFA axis, key genes, VEGFA and FOS, and MAPK signaling in CIN were clarified, and the occurrence and potential effects of CIN were further clarified. The underlying molecular mechanism provides a certain degree of reference for subsequent treatments and experimental research.
Effects of acupuncture in the treatment of occipital neuralgia: A systematic review and meta-analysis

Background: Acupuncture is used to treat subjects with occipital neuralgia, which is 1 of the main causes of occipital pain; however, its effect is conflicting. Hence, the current study aims to evaluate the effects of acupuncture in the treatment of occipital neuralgia. Methods: In a systematic search of PubMed, Embase, OVID, China National Knowledge Infrastructure, Cochrane Library, Chinese Biomedical Literature Database, Wanfang databases, and Google Scholar until July 2021, 15 studies aimed to evaluate the effects of acupuncture in the treatment of occipital neuralgia were included. Human-related trials were considered in different languages. The size of the study was not considered a limit for its inclusion and the study intervention should focus on comparing the impact of acupuncture in the intervention group compared with the control group. The odds ratio (OR) and the mean difference (MD) with 95% confidence intervals (CIs) were calculated with a random or fixed-effect model for different subgroup analyses. Publication bias was assessed using the Egger test, while the risk of bias was assessed using the Review manager software. Results: Acupuncture had a significantly higher effective rate of treatment (OR, 5.40; 95% CI, 2.48 to 11.77, P < .001) compared to control in the treatment of occipital neuralgia and lower visual analogue scale (MD, −2.45; 95% CI, −2.69 to −2.21, P < .001). Acupuncture plus medication had a significantly higher effective rate of treatment (OR, 3.96; 95% CI, 2.10 to 7.47, P < .001) compared to medication in the treatment of occipital neuralgia. Acupuncture analysis for safety issues showed a significant reduction of adverse events compared with the medication group. Conclusion: Acupuncture alone or acupuncture plus medication had a significantly beneficial effect on the effective rate of treatment, safety and visual analog scale compared to medication in the treatment of occipital neuralgia. Further studies are required to validate these findings.
Gastrointestinal bleeding caused by rupture of a posterior inferior pancreaticoduodenal artery pseudoaneurysm: A case report

Background: Gastrointestinal bleeding caused by a ruptured pancreatic pseudoaneurysm is rare, and a pseudoaneurysm of the posterior inferior pancreaticoduodenal artery is especially rare. A 68-year-old man was hospitalized after presenting intermittent black stools and dyspnea accompanied by severe anemia. Angiographic examination revealed that Pseudoaneurysm of the posterior inferior pancreaticoduodenal artery. Methods: Angiography was performed and revealed a pseudoaneurysm of the posterior inferior pancreaticoduodenal artery. Subsequently, a blood transfusion and endovascular embolization were performed. Results: The patient’s gastrointestinal bleeding stopped, and the hemoglobin level remained stable. During 1 year of follow-up, the patient remained in a generally good condition. Conclusion: posterior inferior pancreaticoduodenal artery pseudoaneurysmIt is rare and difficult to diagnose, gastrointestinal bleeding is a serious complication, vascular interventional embolization is effective.
Interprofessional Naloxone Student Training to Manage Suspected Opioid Overdose

Purpose The study purpose was to examine the effect of interprofessional naloxone training on students' knowledge, confidence, and interprofessional collaboration competency. The overarching goal was to decrease mortality related to opioid overdoses. Design/Methods A training session for interprofessional students consisted of a lecture presentation, demonstration, and hands-on practice regarding appropriate administration of naloxone for suspected opioid overdose. A questionnaire elicited baseline and change in knowledge, confidence, and interprofessional collaboration competency scores at pretraining and posttraining. In addition, changes in knowledge and confidence were also measured 3 weeks after the training. Thematic analysis explored training components that students perceived as valuable or needing improvement. Results Participants (N = 100) were nursing (n = 33), physician assistant (n = 37), and pharmacy (n = 30) students. Pretraining and posttraining comparison demonstrated increased knowledge (P < .001), confidence (P < .001), and collaboration scores (P < .001). At 3 weeks, knowledge and confidence remained higher than pretraining (P < .001). Knowledge was trending downward compared with posttraining (P = .09). Thematic analysis identified 4 themes: (a) indications for administration of different naloxone types, (b) learning modalities, (c) knowledge application, and (d) improvements. Conclusions An interprofessional naloxone administration training resulted in increased knowledge, confidence, and interprofessional teamwork. Educators can adapt this training for a variety of future or current healthcare professionals to improve immediate intervention and outcomes in suspected opioid overdoses.
Diagnostic value of EBV-DNA in CSF for PCNSL in AIDS patients with focal brain lesions: A meta-analysis of diagnostic test

Background: Epstein-Barr virus (EBV) infection plays a crucial role in the progression of acquired immunodeficiency syndrome related primary central nervous system lymphoma (AR-PCNSL). This study aimed at evaluating the diagnostic value of cerebrospinal spinal fluid (CSF) EBV-deoxyribonucleic acid (DNA) for PCNSL in patients with infection of human immunodeficiency (HIV) virus through a meta-analysis of diagnostic test. Methods: A systematic search in PubMed, Embase, Web of Science, Wanfang, Chinese Biomedical Database and Chinese National Knowledge Infrastructure was conducted before May 10, 2022. Heterogeneity among the studies was assessed using Q test and I2 statistics. Publication bias was assessed using the Deek’s funnel plot asymmetry test. Statistical analyses were performed using Stata 16.0 software. The pooled sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratios (DOR) and 95% confidence intervals (CI) were caculated to evaluate the diagnostic value. A symmetric receiver operating characteristic (SROC) curve and the area under the SROC curve (AUC) were constructed to evaluate the test-performance. Results: Twelve studies were included in the final analyses, with a total of 141 patients with AR-PCNSL and 590 controls. The pooled diagnostic values were sensitivity of 0.83 (95% CI: 0.73–0.90), specificity of 0.95 (95%CI: 0.89–0.98), PLR of 17.8 (95%CI: 6.8–46.1), NLR of 0.17 (95%CI: 0.10–0.30), DOR of 102 (95%CI: 28–379), and AUC of 0.94 (95%CI: 0.91–0.96). Conclusion: In summary the overall diagnostic value of CSF EBV-DNA is very high and it can be a reliable diagnostic biomarker for AR-PCNSL.
Acupuncture for Crohn’s disease: protocol for a systematic review and meta-analysis of randomized clinical trials

Background: Crohn’s disease (CD) is a chronic recurrent gastrointestinal disorder with a high incidence of inflammation due to intestinal inflammation. Acupuncture is commonly used as an alternative therapy for patients with CD. The aim of this study was to design a systematic review and meta-analysis protocol, to provide guidance for the establishment of systematic evaluation and meta-analysis on the efficacy and safety of acupuncture on CD. Methods: We will search PubMed, the Cochrane Library, Embase, Web of Science, and 4 Chinese databases: China National Knowledge Infrastructure (CNKI), Wanfang database, VIP database, and Chinese Biomedical Database to obtain randomized controlled trials of CD treated with acupuncture from inception to November 5, 2022. Primary outcome include CD symptoms severity and clinical efficacy, secondary outcome indicators include laboratory indicators or inflammatory markers, severity of endoscopic lesions, quality of life, and safety outcomes. We will analyze the data using RevMan V.5. 4 software. Two reviewers will assess the risk of bias and study quality by the Cochrane Collaboration Risk of Bias Tool and GRADE methods, respectively. Results: This systematic review and meta-analysis protocol will analyze the efficacy, symptom improvement, quality of life, and safety of acupuncture therapy for CD. Conclusion: This protocol outlines the planned scope and methodology of a forthcoming systematic review and meta-analysis to provide guidelines for a rigorous assessment of the efficacy and safety of acupuncture for the treatment of CD.
Towards Reliable Benchmarking for Multi-Robot Planning in Realistic, Cluttered and Complex Environments

—Multi-robot planning and coordination is a hard task to solve particularly in cluttered and complex environments. Several methods exist for solving such task. Due to the lack of adequate benchmarking tools, comparing these approaches and judging their suitability for use in realistic scenarios is hardly possible. To this end, in this work we propose a novel benchmark toolchain that aims to close this gap. Differently from the related works, our benchmark uses full-stack multi-robot navigation systems in realistic 3D simulated intralogistic and household environments. The usage of open-source frameworks ROS2, Gazebo and RMF gives the user the possibility to easily add novel robot platforms. The framework provides easy-to-use and to-extend abstractions, common metrics and interfaces to several well-known planning libraries for multi-robot systems. With all these features our framework successfully aids practitioners and researchers in comparing multi-robot planning and coordination algorithms against the state of the art.
Damped second-order Rayleigh-Timoshenko beam vibration in space—an exact complex dynamic member stiffness matrix

A uniform linear beam in a uniform linear ambient medium is studied. The beam performs stationary harmonic damped nonsynchronous space vibration in simultaneous tension, torsion, bending and shear in the presence of a large static axial load. Hysteretic and viscous dampings of the beam material and ambient medium are considered. Generalized complex Kolousek functions are derived. A 12 × 12 complex symmetric stiffness matrix is established for a supported beam member excited at its ends by prescribed harmonic translations and rotations which have the same frequency but may be out of phase. This matrix allows for an exact analysis of nonproportionally damped built-up beam structures, thus avoiding assumed mode shapes and lumped or consistent masses. A general notation is suggested. Numerical examples are given, including applications of the computer program SFVIBAT-DAMP.
Topology-dependent description of grain growth

A growth equation for individual grains is suggested by considering the interactions of the nearest-neighbor grains, which indicates that the average grain growth rate of a given topological class depends on the difference between the number of faces and the average number of faces of the nearest neighbors. For the convenience of its application, a practical equation is also proposed. They have been verified by the data of β-titanium grains, dry 3D foams, Monte Carlo Potts model simulation, vertex model simulation, and surface evolver simulation.