Miracle-dz/UniFAR-FTUs huggingface dataset:
Theme Issue “Renaissance for Paleozoic Eolution Studies: Radiation and Extinction”: Preface for Part 2

This is the Part 2 of the thematic issue; Part 1 was published in Paleontological Research (PR) vol. 25 in 2021. Part 2 adds two more articles that introduce new views and concepts for Paleozoic paleontology, i.e., one for Early-Middle Paleozoic microfossil studies from the long-term terra incognito, central Asia, and the other for essential reconsideration of the causes for the Phanerozoic major extinctions from a non-conventional cosmoclimatology viewpoint. Obut (2023) introduces the latest knowledge on Early Paleozoic micropaleontology from Siberia where precious pieces of information are potentially archived for the lost ocean called the Paleo-Asian Ocean. In addition to classic fossils, such as graptolites and trilobites, a long list of conodonts and radiolarians recently became available from cherts, mudstones, and some limestones. These new fossil data provide prime clues for reconstructing the biogeographic provinciality and geotectonic setting of the Paleo-Asian Ocean. It is noteworthy that the essential research scheme for those ancient mid-oceanic sediments was imported from Japan (e.g. Buslov and Watanabe, 1996; Iwata et al., 1997; Uchio et al., 2004; Ota et al., 2007), and thus is highly suitable for publication in PR. Isozaki (2023) reviews studies on the causes of the Phanerozoic mass extinctions, emphasizing the categorization of previously proposed causes into four distinct groups (see Isozaki, 2019). Besides the currently widely discussed possible causes, such as bolide impact and a large igneous province, a new possibility—non-bolide extraterrestrial effects—is explored on the basis of the astrophysical observations of galaxies (e.g. Rocha-Pinto et al., 2000; Ruiz-Lara et al., 2020) and a new line of material evidence from deep-sea cherts in Japan. The latest finding of an unusually high helium isotope ratio (3He/4He) from the Permo-Triassic boundary extinction interval (Onoue et al., 2019; Takahata et al., 2019) suggests that our Solar System had encountered a dark cloud and that abundant interplanetary dust particles have Theme Issue “Renaissance for Paleozoic evolution studies: radiation and extinction”: Preface for Part 2
Morphometric and Cladistic Analyses of a Theropod Tooth from the Itsuki Formation of the Tetori Group in the Kuzuryu District, Ono City, Fukui Prefecture, Japan

Abstract. An isolated theropod tooth was found in the Hauterivian–Barremian Itsuki Formation of the Tetori Group in the Kuzuryu district, Ono City, Fukui Prefecture, central Japan. The present specimen, OMFJ V-1, shows a thick lanceolate basal cross-section and small mesial and distal denticles. A cladistic analysis based on the dental characters suggested that OMFJ V-1 be classified as belonging to Allosauroidea or Tyrannosauroidea. Principal component and linear discriminant analyses also suggested that OMFJ V-1 belongs to either of these two theropod clades. The posterior probabilities obtained in the linear discriminant analyses indicated that the confidence of the classification as Allosauroidea is slightly higher than that for Tyrannosauridae. However, because these analyses also supported possibilities of OMFJ V-1 belonging to other theropod clades to lesser extents, its taxonomic referral remains ambiguous. If OMFJ V-1 belongs to Tyrannosauroidea, it would indicate that a medium-sized tyrannosauroid already appeared in central Japan during the Hauterivian–Barremian age. On the other hand, if OMFJ V-1 belongs to Allosauroidea, it would indicate that at least two medium-to-large-sized theropods, allosaurids and tyrannosaurids, lived almost coevally in this region. The third possibility is that OMFJ V-1 belongs to Megaraptora. If such affinities are established, it would represent the oldest record of this clade of theropods.
BROADBAND PHOTOMETRY OF 105 GIANT ARCS: REDSHIFT CONSTRAINTS AND IMPLICATIONS FOR GIANT ARC STATISTICS

We measure the photometric properties of 105 giant arcs that were identified in systematic searches for galaxy-cluster-scale strong lenses in the Second Red-Sequence Cluster Survey and the Sloan Digital Sky Survey. The cluster lenses span 0.2 < zl < 1.2 in redshift, with a median . Using broadband color criteria we sort the entire arc sample into redshift bins based on u−g and g−r colors, and also r−z colors for the ∼90% of arcs that have z-band data. This analysis yields broad redshift constraints with 71+5− 4% of the arcs at z ⩾ 1.0, 64+6− 4% at z ⩾ 1.4, 56+5− 4% at z ⩾ 1.9, and 21+4− 2% at z ⩾ 2.7. The remaining 29+03− 5% have z < 1. The inferred median redshift is , in good agreement with a previous determination from a smaller sample of brighter arcs (g ≲ 22.5). This agreement confirms that zs = 2.0 ± 0.1 is the typical redshift for giant arcs with g ≲ 24 that are produced by cluster-scale strong lenses and that there is no evidence for strong evolution in the redshift distribution of arcs over a wide range of g-band magnitudes (20 ⩽ g ⩽24). Establishing that half of all giant arcs are at z ≳ 2 contributes significantly toward relieving the tension between the number of arcs observed and the number expected in a ΛCDM cosmology, but there is considerable evidence to suggest that a discrepancy persists. Additionally, this work confirms that forthcoming large samples of giant arcs will supply the observational community with many magnified galaxies at z ≳ 2.
Body Mass Index as a Proxy Indicator for Poor Oral Hygiene Habits in Adult Diabetic Patients

Abstract Aim To analyse if body mass index (BMI) could be used as a fast proxy indicator of poor oral hygiene habits (POHH) among the adult population with diabetes mellitus. Methods Adults, aged 25-74, from the Slovenian 2016 nationwide cross-sectional survey based on the Countrywide Integrated Non-Communicable Disease Intervention (CINDI) Health Monitor methodology, who reported being diabetic, were included in the study (n=560). We assessed the relationship between POHH and BMI, adjusted to confounders, using multiple binary logistic regression. Results In the total sample, the POHH prevalence was 50.9%. Taking into account BMI, POHH prevalence in participants with normal BMI values was only 37.8%, in the overweight group it was 1.22-times higher (46.0%), while in the obese group it was 1.63-times higher (61.6%) (p<0.001). Also, the odds for POHH were 2.64-times higher in the obese group in comparison to the normal BMI group (95% CI: 1.55-4.51; p<0.001). After adjustment for confounders, this OR decreased only moderately (OR=2.45; 95% CI: 1.35-4.44; p=0.003). Conclusions BMI could be used as a readily assessable, fast, simple, and cheap tool indicating higher odds for having POHH among the diabetic population. By defining the high-risk group it could be easier for physicians and dentists to take further referrals and actions for promoting oral health in this group. The suggested tool can save time and could have an important positive impact on the quality of life of diabetics, as well as on health expenditures.
On a Conditional Procedure for Selecting a Subset Containing the Best of Several Binomial Populations.

Abstract : Let (Pi sub 1), (Pi sub 2),. , (Pi sub k) be k independent binomial populations such that the observation (X sub i) from (pi sub i) has frequency b(n; p sub 1) for i=1,. ,k. The authors consider the problem of selecting a subset of these k populations which contains the population associated with the largest p sub i. The authors derive a lower bound for the infimum of the probability of a correct selection by using Gupta-Huang procedure which is based on the statistic max (X sub j) - (X sub i) being conditioned on the total number of observations, the summation from 1 to k of (X sub i). An upper bound is discussed for the expected size of the selected subset for some special cases. Tables are computed for the conservative values of the constant which is needed to carry out the procedure, for k=2(1)10, n=1(1)10 and P*=0.75, 0.90, 0.95 and 0.99. (Modified author abstract)
lncRNA FAM230B is highly expressed in colorectal cancer and suppresses the maturation of miR-1182 to increase cell proliferation

Abstract Long non-coding RNA FAM230B and microRNA (miR-1182) have been characterized as critical players in cancer biology, while their roles in colorectal cancer (CRC) are unclear. We predicted that they could interact with each other and therefore explored the interaction between them in CRC. CRC and paired non-tumor tissue samples were collected from 60 CRC patients, and the expression of FAM230B and miR-1182 (premature and mature) in these samples was analyzed with RT-qPCR. The direct interaction between FAM230B and premature miR-1182 was analyzed with RNA-RNA pull-down assay, and the subcellular location of FAM230B was detected with subcellular fractionation assay. The interaction between FAM230B and miR-1182 was explored with overexpression assay, and their roles in regulating CRC cell proliferation, viability, and colony formation were assessed by BrdU assay, MTT assay, and colony formation assay, respectively. We found that FAM230B and premature miR-1182 were highly upregulated in CRC, while mature miR-1182 was downregulated in CRC. FAM230B was detected in both nucleus and cytoplasm, and it directly interacted with miR-1182. FAM230B overexpression increased the expression levels of premature miR-1182 but decreased the expression levels of mature miR-1182 in CRC cells. FAM230B promoted CRC cell proliferation, increased cell viability, accelerated colony formation, and suppressed the role of miR-1182 in inhibiting CRC cell proliferation. In conclusion, FAM230B is upregulated in CRC and it suppresses the maturation of miR-1182 to promote tumor growth.
Effectiveness of Pulmonary Rehabilitation Performed Through Exercise Training for Patients with Stable COPD: A Meta-analysis of Randomized Controlled Trials

Abstract Background The application of pulmonary rehabilitation (PR) in chronic obstructive pulmonary disease (COPD) improves functional capacity and health-related quality of life (HRQoL) at all stages of disease severity. The aim of this study was to determine the effects of PR, performed through exercise training (PR-ET), on functional capacity and HRQoL in patients with stable COPD. Methods The meta-analysis was performed by including randomized controlled trials (RCTs) involving patients with stable COPD who participated in different types of PR-ET in which six-minute walk distance (6MWD) and/ or St. George’s Respiratory Questionnaire total scores (SGRQ) were measured. The data search was conducted in December 2020 and January 2021. Results The first meta-analysis showed a statistically significant positive effect (MD=31.73m; p<0.00001) of PR-ET on 6MWD. Similarly, the second meta-analysis found a statistically significant favourable effect of pulmonary rehabilitation through exercise training on SGRQ total scores (MD=-8.09; p=0.002). Conclusions PR, which includes several different types of exercise training, has a positive effect on the functional capacity and HRQoL of patients with stable COPD. Further studies should be conducted to determine the effects of home-based PR-ET and PR-ET >8 weeks on SGRQ total scores.
Practical recommendations for machine learning in underground rock engineering – On algorithm development, data balancing, and input variable selection

Research has demonstrated that machine learning algorithms (MLAs) are a powerful addition to the rock engineering toolbox, and yet they remain a largely untapped resource in engineering practice. The reluctance to adopt MLAs as part of standard practice is often attributed to the ‘opaque’ nature of the algorithms, the complexity in developing them, and the difficulty in determining how the algorithms use the datasets. This article presents tools and processes for developing MLAs, input selection, and data balancing for practical underground rock engineering. MLAs for classification and regression – two main machine learning applications – are presented in terms of developing MLA to extract information from the dataset to obtain the desired output. Engineering verification metrics are selected based on their suitability for specific output. Methods for input selection and data balancing are discussed with a focus on selecting appropriate input data for the problem without introducing bias or excess complexity. Each tool and process for algorithm development, data preparation, and input selection is illustrated with a case study. This article demonstrates that geotechnical practitioners can extract additional value by applying MLAs to rock engineering problems. Once an understanding of the functions of MLAs is reached, the building blocks and open‐source code are available to be adapted to suit the rock mass behaviour of interest.
Uncertain disturbed systems: Robust H2‐OUFIR filtering under measurement errors

This article considers uncertain disturbed systems represented under initial and measurement errors in linear discrete‐time state‐space. A novel bias‐constrained a posteriori H2$$ {H}_2 $$ optimal unbiased finite impulse response (OUFIR) state observer is derived, in which the requirements of the initial state is removed by embedding the unbiasedness constraint. A suboptimal bias‐constrained H2$$ {H}_2 $$ ‐FIR filtering algorithms using linear matrix inequality is also obtained. Based on an example of uncertain system and error matrices, it is shown that the H2$$ {H}_2 $$ ‐OUFIR state observer offers a better tradeoff between the accuracy and robustness than the OFIR filter, maximum likelihood FIR filter, and Kalman filter. It loses in robustness to the unbiased FIR filter, but provides a better accuracy. The performance of the proposed filter is verified experimentally based on daily glucose measurements in diabetic persons with timing jitter.
A Note on the Recursions of Multichannel Complex Subset Autoregressions - Financial and Economic Forecasting (Chapter 2)

The recursive algorithm to select the optimum multivariate real subset autoregressive model (AR) [1] is generalized to apply to multichannel complex subset AR's. It is initiated by fitting all 'forward' and 'backward' one-lag AR's. The method then allows one to develop successively all complex subset AR's of size (the number of lags with nonzero coefficient matrices) from 1 to K. Finally, the best subsets of each size with the minimum generalized residual power for that size are compared to any one of three model selection criteria to find the optimum multichannel complex subset AR.
Automated geological model updates during TBM operation – An approach based on probabilistic machine learning concepts

Geological models are commonly used to predict the position of relevant geological features, such as rock types or faults in the subsurface. These models can contain significant uncertainties, as the geological input parameters are often not perfectly known. Predictions of geological features, for example, on the level of a tunnel during an excavation process, are therefore uncertain. This work shows how these uncertainties can be estimated using probabilistic concepts. Furthermore, an approach is presented to automatically adjust the geological model predictions using measurements of the tunnel boring machine (TBM) operation. To this aim, the geological forward model is combined with a measurement model and both are integrated in a probabilistic machine learning framework. This integration enables a Bayesian inference process using computational methods, enabling an update of the parameters of the geological and measurement models. Based on the inferred parameter distributions, the model predictions on the tunnel level are subsequently updated. The application of the concept in a simple schematic application shows that such a combination can accurately and precisely predict features ahead of the operation within the limits of the model capabilities. In future work, the methods need to be tested with a real case study to evaluate the accuracy of predictions using real‐world TBM data and more complex geological models. The framework presented here could directly be extended to this purpose.
Theories of systems with limited information content

We introduce a hierarchical classification of theories that describe systems with fundamentally limited information content. This property is introduced in an operational way and gives rise to the existence of mutually complementary measurements, i.e. a complete knowledge of future outcome in one measurement is at the expense of complete uncertainty in the others. This is a characteristic feature of the theories and they can be ordered according to the number of mutually complementary measurements, which is also shown to define their computational abilities. In the theories multipartite states may contain entanglement, and tomography with local measurements is possible. The classification includes both classical and quantum theory and also generalized probabilistic theories with a higher number of degrees of freedom, for which operational meaning is given. We also discuss thought experiments discriminating standard quantum theory from the generalizations.
The CoRoT satellite in flight : description and performance

Context. CoRoT is a space telescope dedicated to stellar seismology and the search for extrasolar planets. The mission is led by the CNES in association with French laboratories and has a large international participation. The European Space Agency (ESA), Austria, Belgium, and Germany contribute to the payload, and Spain and Brazil contribute to the ground segment. Development of the spacecraft, which is based on a PROTEUS low earth orbit (LEO) recurrent platform, commenced in October 2000, and the satellite was launched on December 27, 2006. Aims. The instrument and platform characteristics prior to launch have been described in ESA publication (SP-1306). In the present paper we explain the behaviour in flight, based on raw and corrected data. Methods. Five runs have been completed since January 2007. The data used here are essentially those acquired during the commissioning phase and from a long run that lasted 146 days. These enable us to give a complete overview of the instrument and platform behaviour for all environmental conditions. The ground based data processing is not described in detail because the most important method has been published elsewhere. Results. We show that the performance specifications are easily satisfied when the environmental conditions are favourable. Most of the perturbations, hence data corrections, are related to LEO perturbations: high energy particles inside the South Atlantic Anomaly (SAA), eclipses and temperature variations, and line of sight fluctuations due to the attitude control system. Straylight due to the reflected light from the earth, which is controlled by the telescope and baffle design, appears to be negligible.
The development of compulsive coping behaviors depends on the engagement of dorsolateral striatum dopamine-dependent mechanisms

Humans greatly differ in how they cope with stress, a natural behavior learnt through negative reinforcement. Some individuals engage in displacement activities, others in exercise or comfort eating, and others still in alcohol use. Across species, adjunctive behaviors, such as polydipsic drinking, are used as a form of displacement activity that reduces distress. Some individuals, in particular those that use alcohol to self-medicate, tend to lose control over such coping behaviors, which become excessive and compulsive. However, the psychological and neural mechanisms underlying this individual vulnerability have not been elucidated. Here we tested the hypothesis that the development of compulsive adjunctive behaviors stems from the functional engagement of the dorsolateral striatum (DLS) dopamine-dependent habit system after a prolonged history of adjunctive responding. We measured in longitudinal studies in male Sprague Dawley rats the sensitivity of early established vs compulsive polydipsic water or alcohol drinking to a bilateral infusion of the dopamine receptor antagonist α-flupentixol into the anterior DLS (aDLS). While most rats acquired a polydipsic drinking response with water, others only did so with alcohol. Whether reliant on water or alcohol, the acquisition of this coping response was insensitive to aDLS dopamine receptor blockade. In contrast, after prolonged experience, adjunctive drinking became dependent on the aDLS dopamine-dependent habit system at a time it was compulsive in vulnerable individuals. These data suggest that habits may develop out of negative reinforcement and that the engagement of their underlying striatal system is necessary for the manifestation of adjunctive behaviors. Significance statement Harnessing the individual variability that rodents, like humans, show to engage in adaptive or maladaptive coping strategies, which can result in the development of compulsive disorders, here we demonstrate that the functional engagement of the dorsolateral striatum-dependent habit system precipitates the transition to compulsion in rats that have acquired a polydipsic adjunctive drinking response with water or alcohol as a means to cope with distress. The results of this study not only provide evidence for the emergence of instrumental habits under negative reinforcement, but they also reveal that compulsive behaviors that originate from the loss of control over coping strategies are mediated by the dorsolateral striatum-dependent habit system.
Experience-dependent flexibility in a molecularly diverse central-to-peripheral auditory feedback system

Brainstem olivocochlear neurons (OCNs) modulate the earliest stages of auditory processing through feedback projections to the cochlea and have been shown to influence hearing and protect the ear from sound-induced damage through unclear mechanisms. Here, we used single-nucleus sequencing, anatomical reconstructions, and electrophysiology to characterize OCNs during postnatal development and after sound exposure. We identified markers for known OCN subtypes, medial (MOC) and lateral (LOC) OCNs, and show that they express distinct cohorts of physiologically relevant genes that change over development. In addition, we discovered a neuropeptide-enriched LOC subtype that produces Neuropeptide Y along with other neurotransmitters. Throughout the cochlea, both LOC subtypes extend arborizations over wide frequency domains. Moreover, LOC neuropeptide expression is strongly upregulated days after acoustic trauma, potentially providing a sustained protective signal to the cochlea. OCNs are therefore poised to have diffuse, dynamic effects on early auditory processing over timescales ranging from milliseconds to days.
A scalable implementation of the recursive least-squares algorithm for training spiking neural networks

Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a popular way to study computations performed by the nervous system. As the size and complexity of neural recordings increase, there is a need for efficient algorithms that can train models in a short period of time using minimal resources. We present optimized CPU and GPU implementations of the recursive least-squares algorithm in spiking neural networks. The GPU implementation can train networks of one million neurons, with 100 million plastic synapses and a billion static synapses, about 1000 times faster than an unoptimized reference CPU implementation. We demonstrate the code’s utility by training a network, in less than an hour, to reproduce the activity of > 66, 000 recorded neurons of a mouse performing a decision-making task. The fast implementation enables a more interactive in-silico study of the dynamics and connectivity underlying multi-area computations. It also admits the possibility to train models as in-vivo experiments are being conducted, thus closing the loop between modeling and experiments.