Miracle-dz/UniFAR-FTUs huggingface dataset:
A consistent implementation for inelastic materials in an ALE formulation for steady state rolling contact

The numerical analysis of rolling contact for rubber materials is a challenging task, especially due to the many nonlinearities inherent to the material, large deformations, friction, and energy dissipation, among others. Industrial applications can be found in ball bearings, rollers, and most commonly in tires of vehicles, applications where reliable numerical simulations lead to the improvement of durability, performance and safety. While a transient analysis stands as a practical and powerful tool for the simulation of rotating bodies, the large amount of computational resources required represents its biggest disadvantage. An alternative frequently used lays in a steady state simulation by means of an Arbitrary Lagrangian Eulerian (ALE) formulation, where the rotational velocity and axial loads are assumed to remain constant. Within this framework, the reference configuration is neither attached to the material particles nor fixed in space and special attention should be paid to the history variables of inelastic materials. In this work, a viscoelastic material model is implemented in an in‐house finite element code, based on a generalized Maxwell model. The implementation takes into consideration the contribution of all elements connected in circumferential direction and a consistent linearization is made for each of them, leading to an assembled stiffness matrix with more non‐zero values than a standard one. This approach is combined with smeared reinforcement embedded in base elements. The reinforcing layers are described by a hyperelastic material model, providing additional advantages for the modeling and simulation of reinforced rollers and tires. Numerical results for different examples show the capabilities of this implementation and the efficiency of the numerical algorithms is discussed. Important remarks and an outlook for further research concludes this presentation. (© 2016 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Updated consensus statement: Intravenous immunoglobulin in the treatment of neuromuscular disorders report of the AANEM ad hoc committee

Intravenous immune globulin (IVIG) is an immune‐modulating biologic therapy that is increasingly being used in neuromuscular disorders despite the paucity of high‐quality evidence for various specific diseases. To address this, the AANEM created the 2009 consensus statement to provide guidance on the use of IVIG in neuromuscular disorders. Since then, there have been several randomized controlled trials for IVIG, a new FDA‐approved indication for dermatomyositis and a revised classification system for myositis, prompting the AANEM to convene an ad hoc panel to update the existing guidelines.New recommendations based on an updated systemic review of the literature were categorized as Class I‐IV. Based on Class I evidence, IVIG is recommended in the treatment of chronic inflammatory demyelinating polyneuropathy, Guillain‐Barré Syndrome (GBS) in adults, multifocal motor neuropathy, dermatomyositis, stiff‐person syndrome and myasthenia gravis exacerbations but not stable disease. Based on Class II evidence, IVIG is also recommended for Lambert‐Eaton myasthenic syndrome and pediatric GBS. In contrast, based on Class I evidence, IVIG is not recommended for inclusion body myositis, post‐polio syndrome, IgM paraproteinemic neuropathy and small fiber neuropathy that is idiopathic or associated with tri‐sulfated heparin disaccharide or fibroblast growth factor receptor‐3 autoantibodies. Although only Class IV evidence exists for IVIG use in necrotizing autoimmune myopathy, it should be considered for anti‐hydroxy‐3‐methyl‐glutaryl‐coenzyme A reductase myositis given the risk of long‐term disability. Insufficient evidence exists for the use of IVIG in Miller‐Fisher syndrome, IgG and IgA paraproteinemic neuropathy, autonomic neuropathy, chronic autoimmune neuropathy, polymyositis, idiopathic brachial plexopathy and diabetic lumbosacral radiculoplexopathy.
Retrospective Evaluation of Mycoplasma genitalium Prevalence and Macrolide Resistance in a Study Cohort of Pregnant Women in Birmingham, AL, From 1997 to 2001

A retrospective evaluation of Mycoplasma genitalium infection in 203 pregnant persons participating in a study conducted between 1997 and 2001 showed a prevalence of 11% (95% confidence interval, 6.9%–15.7%), and no macrolide resistance–associated mutations were detected. Abstract In a prospective study conducted in 2020 to 2021, macrolide resistance–associated mutations were found in 41% of pregnant persons in Birmingham, AL, with Mycoplasma genitalium detected. We retrospectively evaluated M. genitalium in 203 pregnant persons participating in a study conducted in 1997 to 2001 in Birmingham and adjacent areas and found a prevalence of 11% (95% confidence interval, 6.9%–15.7%), but no macrolide resistance–associated mutations.
Deconvolution of petroleum mixtures using mid-FTIR analysis and non-negative matrix factorization

The aim of this study is to develop an efficient, robust and cost effective methodology capable of both identifying the chemical fractions in complex commercial petroleum products and numerically estimating their concentration within the mixture sample. We explore a methodology based on attenuated total reflectance fourier transform infrared (ATR-FTIR) analytical signals, combined with a modified factorization algorithm to solve this ‘mixture problem’, first in qualitative and then in quantitative mode. The proposed decomposition approach is self-adapting to data without prior knowledge and is able of accurately estimating the weight contributions of constituents in the entire chemical compound. The results of the presented work to petroleum analysis indicate that it is possible to deconvolve the mixing process and recover the content in a chemically complex petroleum mixture using the infrared signals of a limited number of samples and the principal substances forming the mixture. A focus application of the proposed methodology is the quality control of commercial gasoline by identifying and quantifying the individual fractions utilized for its formulation via a fast, robust and efficient procedure based on mathematical analysis of the acquired spectra.
An ankyrin repeat chaperone targets toxic oligomers during amyloidogenesis

Numerous age‐linked diseases are rooted in protein misfolding; this has motivated the development of small molecules and therapeutic antibodies that target the aggregation of disease‐linked proteins. Here we explore another approach: molecular chaperones with engineerable protein scaffolds such as the ankyrin repeat domain (ARD). We tested the ability of cpSRP43, a small, robust, ATP‐ and cofactor‐independent plant chaperone built from an ARD, to antagonize disease‐linked protein aggregation. cpSRP43 delays the aggregation of multiple proteins including the amyloid beta peptide (Aβ) associated with Alzheimer's disease and α‐synuclein associated with Parkinson's disease. Kinetic modeling and biochemical analyses show that cpSRP43 targets early oligomers during Aβ aggregation, preventing their transition to a self‐propagating nucleus on the fibril surface. Accordingly, cpSRP43 rescued neuronal cells from the toxicity of extracellular Aβ42 aggregates. The substrate‐binding domain of cpSRP43, composed primarily of the ARD, is necessary and sufficient to prevent Aβ42 aggregation and protect cells against Aβ42 toxicity. This work provides an example in which an ARD chaperone non‐native to mammalian cells harbors anti‐amyloidal activity, which may be exploited for bioengineering.
Weighted Half Exponential Power Distribution and Associated Inference

The weighted exponential distribution has been generalized by many authors in recent years. Here, we introduce a new generalization, called the weighted half exponential power distribution, that can be used to model negative or positive skewed data. Various structural properties of the distribution are derived. The method of maximum likelihood is used to estimate the parameters of the distribution. Finally, a real data application is presented to compare the goodness-of-t of the various generalized weighted exponential distributions. Mathematics Subject Classication: 60E05, 62F10
Articulating Space: Geometric Algebra for Parametric Design - Symmetry, Kinematics, and Curvature

Author(s): Colapinto, Pablo | Advisor(s): Peljhan, Marko | Abstract: To advance the use of geometric algebra in practice, we develop computational methods for parameterizing spatial structures with the conformal model. Three discrete parameterizations – symmetric, kinematic, and curvilinear – are employed to generate space groups, linkage mechanisms, and rationalized surfaces. In the process we illustrate techniques that directly benefit from the underlying mathematics, and demonstrate how they might be applied to various scenarios. Each technique engages the versor – as opposed to matrix – representation of transformations, which allows for structure-preserving operations on geometric primitives. This covariant methodology facilitates constructive design through geometric reasoning: incidence and movement are expressed in terms of spatial variables such as lines, circles and spheres. In addition to providing a toolset for generating forms and transformations in computer graphics, the resulting expressions could be used in the design and fabrication of machine parts, tensegrity systems, robot manipulators, deployable structures, and freeform architectures. Building upon existing algorithms, these methods participate in the advancement of geometric thinking, developing an intuitive spatial articulation that can be creatively applied across disciplines, ranging from time-based media to mechanical and structural engineering, or reformulated in higher dimensions.
Rejoinder: “Coauthorship and citation networks for statisticians”

We would like to thank all discussants for very thoughtful and stimulating comments. We especially thank B. Silverman for a nice and timely introduction for our paper; it is well said and very much illuminating. In the past decades, the scientific community has grown substantially: we have way more researchers and annual publications than we ever had before. For example, the statistics community has grown from a tight-knit community (where one statistician may know almost all other statisticians) to a much larger one, driven by the technology advancements in computing and data acquisition. While undoubtedly we have numerous achievements in our time (of which we should be proud), we have also heard many critical criticisms, among which there are the paper by Ioannidis (2005), “Why most published research findings are false,” and the paper by Geman and Geman (2016), “Opinion: Science in the age of selfies. ” As Silverman points out, an interesting question is therefore how to scrutinize the vast volume of scientific research we have today. While we can always turn to the traditional subjective approaches, we must admit that such approaches may be biased or inadequate, and quantitative approaches, like it or not, will play an increasingly more important role. Having overseen the need for statisticians to engage a more active role in quantitative evaluation of scientific impact and productivity, Peter Hall said the following in his Presidential address at the 2011 Institute of Mathematical Statistics Annual Meeting (Miami, FL) [Hall (2011)]: “. As statisticians we should become more involved in these matters than we are. We should definitely take a greater interest in this area. ” Hall’s viewpoint is reminiscent of the recent proposal by Donoho (2015) in “50 years of data science,” where he oversaw the need of a new research discipline called “Science for Science. ” Our work is a response to Hall’s calling, and we believe that our data set will provide a fertile ground for future research on network analysis and related fields. Our effort in data collection is continued, and we now have a data set much larger than the one presented in our paper, covering papers in 36 representative journals in statistics and related fields, spanning 40 years.
Autism, pets, and the importance of seeing human

People often see the human in the nonhuman, a process called anthropomorphism. Anthropomorphism is particularly prolific regarding the humanization of pets. Some research suggests that people with autism may not anthropomorphize to the same degree as neurotypicals. In this study, we explored whether there were differences in how autistic and neurotypical pet owners anthropomorphized their pets. We also examined differences in levels of connectedness to nature and experiences of loneliness and how this corresponded to autistic traits in the entire sample. We found anthropomorphism was as common among autistic pet owners as in neurotypicals. However, autistic pet owners reported greater loneliness and were more likely to substitute pets for people. We also found that neurotypical pet owners rated pets more highly on physical, non‐anthropomorphic traits (i.e., muscular, active). In contrast, autistic pet owners were likelier to rate pets equally between physical and anthropomorphic traits. Moreover, we found that anthropomorphism and connection to nature were positively correlated with autistic traits. These findings challenge accounts stating that individuals with autism may not anthropomorphize to the same degree as neurotypicals. Implications for animal‐based interventions supporting adults on the spectrum are discussed.
4D dosimetric-blood flow model: impact of prolonged fraction delivery times of IMRT on the dose to the circulating lymphocytes

To investigate the impact of prolonged fraction delivery of modern intensity-modulated radiotherapy (IMRT) on the accumulated dose to the circulating blood during the course of fractionated radiation therapy. We have developed a 4D dosimetric blood flow model (d-BFM) capable of continuously simulating the blood flow through the entire body of the cancer patient and scoring the accumulated dose to blood particles (BPs). We developed a semi-automatic approach that enables us to map the tortuous blood vessels of the surficial brain of individual patients directly from standard magnetic resonance imaging data of the patient. For the rest of the body, we developed a fully-fledged dynamic blood flow transfer model according to the International Commission on Radiological Protection human reference. We proposed a methodology enabling us to design a personalized d-BFM, such it can be tailored for individual patients by adopting intra- and inter-subject variations. The entire circulatory model tracks over 43 million BPs and has a time resolution of ∆t = 10−3 s. A dynamic dose delivery model was implemented to emulate the spatial and temporal time-varying pattern of the dose rate during the step-and-shoot mode of IMRT. We evaluated how different configurations of the dose rate delivery, and a time prolongation of fraction delivery may impact the dose received by the circulating blood (CB). Our calculations indicate that prolonging the fraction treatment time from 7 to 18 min will augment the blood volume receiving any dose VD>0Gy from 36.1% to 81.5% during one single fraction. The results indicate that increasing the segment number has only a negligible effect on the irradiated blood volume, when the fraction time is kept identical. We developed a novel concept of customized 4D d-BFM that can be tailored to the hemodynamics of individual patients to quantify dose to the CB during fractionated radiotherapy. The prolonged fraction delivery and the variability of the instantaneous dose rate have a significant impact on the accumulated dose distribution during IMRT treatments. This impact should be considered during IMRT treatments design to reduce RT-induced immunosuppressive effects.
Correlation of vitamin E level during pregnancy with maternal and neonatal health outcomes: a meta-analysis and systematic review.

OBJECTIVE To investigate maternal vitamin E (tocopherol) levels during pregnancy and maternal and neonatal health (MNH) outcomes by using meta-analysis and systematic review of literature. METHODS PubMed, Web of Science and Medline database were searched from database establishment to December 2022 to collect studies on the level of vitamin E (tocopherol) and pregnancy outcomes. Seven studies were finally included, after screening based on pre-specified eligibility and exclusion criteria. Included studies must have data on maternal vitamin E levels and maternal and infant pregnancy outcomes. Literature quality assessment was made using the Newcastle-Ottawa-Scale scoring standard, and meta-analysis was performed with the use of RevMan5.3. RESULTS Seven studies (involving 6247 normal women and 658 adverse pregnancy outcomes women, 6905 total), all with a quality evaluation score ≥6 points, were included. The meta-analysis of the 7 studies revealed the presence of statistical heterogeneity in vitamin E data (P<0.1 and I2>50%), so a random-effects analysis was further carried out. Statistically lower serum vitamin E levels were determined in the adverse pregnancy outcome group compared with the normal group [SMD=4.44, 95% CI (2.44,6.43), P<0.001]. Descriptive analysis of the correlation of vitamin E levels with maternal and neonatal general information showed no statistical difference in vitamin E levels among mothers of different ages (<27 years, ≥27 years), P=0.214; however, women with BMI<18.5 kg/m2 showed a higher incidence of vitamin E deficiency than those with BMI ≥18.5 kg/m2 (χ2=15.173, P<0.05). Maternal vitamin E level with neonatal weight Z-Score >-2 was [1.793 (0.08, 4.514) mg/L], which was significantly lower than that of maternal vitamin E level with neonatal weight Z-Score ≤-2 [2.223 (0.899,6.958) mg/L], P=0.009. Maternal vitamin E levels with neonatal length Z-Score >-2 [1.746 (0.08, 4.514) mg/L] were significantly lower than those with neonatal length Z-Score ≤-2 [2.362 (1.380, 6.958) mg/L], P=0.006. CONCLUSION Maternal vitamin E level is lower in those with adverse pregnancy outcomes than that in those with non-adverse pregnancy outcomes. Still, given the limited research on the correlation of vitamin E during pregnancy with maternal BMI and neonatal body length and weight, a large-scale and well-designed cohort study is needed for further analysis.
Securing Verified IO Programs Against Unverified Code in F*

We introduce SCIO*, a formally secure compilation framework for statically verified programs performing input-output (IO). The source language is an F* subset in which a verified program interacts with its IO-performing context via a higher-order interface that includes refinement types as well as pre- and post-conditions about past IO events. The target language is a smaller F* subset in which the compiled program is linked with an adversarial context that has an interface without refinement types, pre-conditions, or concrete post-conditions. To bridge this interface gap and make compilation and linking secure we propose a formally verified combination of higher-order contracts and reference monitoring for recording and controlling IO operations. Compilation uses contracts to convert the logical assumptions the program makes about the context into dynamic checks on each context-program boundary crossing. These boundary checks can depend on information about past IO events stored in the state of the monitor. But these checks cannot stop the adversarial target context before it performs dangerous IO operations. Therefore linking in SCIO* additionally forces the context to perform all IO actions via a secure IO library, which uses reference monitoring to dynamically enforce an access control policy before each IO operation. We prove in F* that SCIO* soundly enforces a global trace property for the compiled verified program linked with the untrusted context. Moreover, we prove in F* that SCIO* satisfies by construction Robust Relational Hyperproperty Preservation, a very strong secure compilation criterion. Finally, we illustrate SCIO* at work on a simple web server example.
Divide-and-Conquer Fusion

Combining several (sample approximations of) distributions, which we term sub-posteriors, into a single distribution proportional to their product, is a common challenge. Occurring, for instance, in distributed 'big data' problems, or when working under multi-party privacy constraints. Many existing approaches resort to approximating the individual sub-posteriors for practical necessity, then find either an analytical approximation or sample approximation of the resulting (product-pooled) posterior. The quality of the posterior approximation for these approaches is poor when the sub-posteriors fall out-with a narrow range of distributional form, such as being approximately Gaussian. Recently, a Fusion approach has been proposed which finds an exact Monte Carlo approximation of the posterior, circumventing the drawbacks of approximate approaches. Unfortunately, existing Fusion approaches have a number of computational limitations, particularly when unifying a large number of sub-posteriors. In this paper, we generalise the theory underpinning existing Fusion approaches, and embed the resulting methodology within a recursive divide-and-conquer sequential Monte Carlo paradigm. This ultimately leads to a competitive Fusion approach, which is robust to increasing numbers of sub-posteriors.
THE CHROMATIC NUMBER OF 
$\boldsymbol {(P_6,C_4,\mbox {diamond})}$
 -FREE GRAPHS

Abstract The diamond is the complete graph on four vertices minus one edge; $P_n$ and $C_n$ denote the path and cycle on n vertices, respectively. We prove that the chromatic number of a $(P_6,C_4,\mbox {diamond})$ -free graph G is no larger than the maximum of 3 and the clique number of G.
Toward Oral Thanatomicrobiology—An Overview of the Forensic Implications of Oral Microflora

Introduction: The oral cavity is home to numerous microorganisms including bacteria, fungi, and viruses which together form the oral microflora. It is the second most diverse microbial site in the human body after the gastrointestinal tract. Microbial degradation is a common phenomenon that occurs after death, with the early and advanced stages of decomposition being closely associated with oral microbial activity. Methods: This article reviews the current state of knowledge on the role of the oral microflora in postmortem events, and highlights the growing importance of terms such as forensic microbiology and thanatomicrobiome. This article also discusses next-generation sequencing, metagenomic sequencing studies, and RNA sequencing to study the oral thanatomicrobiome and epinecrotic communities in forensic oral genetics. Results: The indigenous microorganisms in the oral cavity are among the first to respond to the process of decomposition. DNA/RNA sequencing is a relatively simple, precise, and cost-effective method to estimate biological diversity during various stages of postmortem decomposition. The field of thanatomicrobiology is rapidly evolving into a key area in forensic research. Conclusion: This article briefly narrates oral microflora and its implications in forensic odontology. The role of microbial activity in postmortem events is gaining importance in forensic research, and further studies are needed to fully understand the potential applications of advanced technology in the study of the oral thanatomicrobiome.