Morphological Integration of the Modern Human Mandible during Ontogeny

Craniofacial integration is prevalent in anatomical modernity research. Little investigation has been done on mandibular integration. Integration patterns were quantified in a longitudinal modern human sample of mandibles. This integration pattern is one of modularization between the alveolar and muscle attachment regions, but with age-specific differences. The ascending ramus and nonalveolar portions of the corpus remain integrated throughout ontogeny. The alveolar region is dynamic, becoming modularized according to the needs of the mandible at a particular developmental stage. Early in ontogeny, this modularity reflects the need for space for the developing dentition; later, modularity is more reflective of mastication. The overall pattern of modern human mandibular integration follows the integration pattern seen in other mammals, including chimpanzees. Given the differences in craniofacial integration patterns between humans and chimpanzees, but the similarities in mandibular integration, it is likely that the mandible has played the more passive role in hominin skull evolution

Wavelet analysis of angular distributions of secondary particles in high energy nucleus-nucleus interactions. Irregularity of particle pseudorapidity distributions

Experimental data on sulphur and oxygen nuclei interactions with photoemulsion nuclei at the energies of 200 and 60 GeV/nucleon are analyzed with the help of a continuous wavelet transform. Irregularities in pseudorapidity distributions of narrow groups of the secondary shower particles in the mentioned interactions are observed at application of the second order derivative of Gaussian as a wavelet. The irregularities can be interpreted as an existence of the preference emission angles of groups of particles. Such an effect is expected at emission of Cherenkov gluons in nucleus-nucleus collisions. Some of the positions of the observed peculiarities on the pseudorapidity axis coincide with those found by I.M.Dremin et al. (I.M.Dremin et al. Phys. Lett., 2001, v. B499, p. 97).)Comment: 11 pages, 7 figure

Matching structure and bargaining outcomes in buyer–seller networks

We examine the relationship between the matching structure of a bipartite (buyer-seller) network and the (expected) shares of the unit surplus that each connected pair in this network can create. We show that in different bargaining environments, these shares are closely related to the Gallai-Edmonds Structure Theorem. This theorem characterizes the structure of maximum matchings in an undirected graph. We show that the relationship between the (expected) shares and the tructure Theorem is not an artefact of a particular bargaining mechanism or trade centralization. However, this relationship does not necessarily generalize to non-bipartite networks or to networks with heterogeneous link values

Embedding Quizzes in On-line Prerecorded Lectures

As we transitioned to on-line education, the problem arises as to how to keep students engaged while listening to a prerecorded lecture. Listening to an hour to two hour lecture and watching a screen is not particularly engaging for the student. To this end, I embedded quizzes periodically within my prerecorded lectures of my DEN 7162 nutrition class for 1st year dental students that forced the students to engage with the lecture material.https://digitalscholarship.unlv.edu/btp_expo/1132/thumbnail.jp

Experimental study of digital image processing techniques for LANDSAT data

The author has identified the following significant results. Results are reported for: (1) subscene registration, (2) full scene rectification and registration, (3) resampling techniques, (4) and ground control point (GCP) extraction. Subscenes (354 pixels x 234 lines) were registered to approximately 1/4 pixel accuracy and evaluated by change detection imagery for three cases: (1) bulk data registration, (2) precision correction of a reference subscene using GCP data, and (3) independently precision processed subscenes. Full scene rectification and registration results were evaluated by using a correlation technique to measure registration errors of 0.3 pixel rms thoughout the full scene. Resampling evaluations of nearest neighbor and TRW cubic convolution processed data included change detection imagery and feature classification. Resampled data were also evaluated for an MSS scene containing specular solar reflections

Modelling Virtual Sensors for Indoor Environments with Machine Learning

Virtual Sensors model the sensing operation of physical sensors deployed in an area of interest by generating sensory data with accuracy and precision close to those collected by physical sensors. Their use in applications such as augmenting the infrastructure of IoT facilities and test beds, monitoring and calibrating the operation of physical sensors, and developing Digital Twins of physical systems have led virtual sensors to attract research attention. Machine learning provides methods for modelling patterns in complex and big data generated by IoT sensing devices, allowing to model the behaviour of these devices. In this work, we investigate ML methods as means of implementation for virtual sensors. In particular, we evaluate the performance of six ML methods in terms of their effectiveness, accuracy and precision in generating sensory data based on data from physical sensors. In our study, we use a multi-modal dataset comprising IoT sensory data for temperature, humidity and illumination collected over a period of two years in an office space at University of Geneva. Our results show that the best performing model at predicting an output of a missing sensor is the Random Forest method, achieving MAPE error below 3%, 5% and 18% respectively for temperature, humidity and illuminance. The worst performing models were the linear radial basis function neural network and linear regression. In future research, we plan to deploy the best performing models natively on IoT devices, making use of tinyML and extreme edge computing methods

Rapid and reversible impairment of episodic memory by a high-fat diet in mice.

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. This work was supported by an EASTBIO BBSRC PhD studentship to F.H.M., L.M.W., C.G., A.C.M., G.W.H. and F.M.C. are supported by Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS).Peer reviewedPublisher PD

Dynamic multilateral markets

We study dynamic multilateral markets, in which players' payoffs result from intra-coalitional bargaining. The latter is modeled as the ultimatum game with exogenous (time-invariant) recognition probabilities and unanimity acceptance rule. Players in agreeing coalitions leave the market and are replaced by their replicas, which keeps the pool of market participants constant over time. In this infinite game, we establish payoff uniqueness of stationary equilibria and the emergence of endogenous cooperation structures when traders experience some degree of (heterogeneous) bargaining frictions. When we focus on market games with different player types, we derive, under mild conditions, an explicit formula for each type's equilibrium payoff as the market frictions vanish

A pilot study to evaluate the application of a generic protein standard panel for quality control of biomarker detection technologies

<p>Abstract</p> <p>Background</p> <p>Protein biomarker studies are currently hampered by a lack of measurement standards to demonstrate quality, reliability and comparability across multiple assay platforms. This is especially pertinent for immunoassays where multiple formats for detecting target analytes are commonly used.</p> <p>Findings</p> <p>In this pilot study a generic panel of six non-human protein standards (50 - 10^7 pg/mL) of varying abundance was prepared as a quality control (QC) material. Simulated "normal" and "diseased" panels of proteins were prepared in pooled human plasma and incorporated into immunoassays using the Meso Scale Discovery^®(MSD^®) platform to illustrate reliable detection of the component proteins. The protein panel was also evaluated as a spike-in material for a model immunoassay involving detection of ovarian cancer biomarkers within individual human plasma samples. Our selected platform could discriminate between two panels of the proteins exhibiting small differences in abundance. Across distinct experiments, all component proteins exhibited reproducible signal outputs in pooled human plasma. When individual donor samples were used, half the proteins produced signals independent of matrix effects. These proteins may serve as a generic indicator of platform reliability.</p> <p>Each of the remaining proteins exhibit differential signals across the distinct samples, indicative of sample matrix effects, with the three proteins following the same trend. This subset of proteins may be useful for characterising the degree of matrix effects associated with the sample which may impact on the reliability of quantifying target diagnostic biomarkers.</p> <p>Conclusions</p> <p>We have demonstrated the potential utility of this panel of standards to act as a generic QC tool for evaluating the reproducibility of the platform for protein biomarker detection independent of serum matrix effects.</p

Cells and gene expression programs in the adult human heart

Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and strategies to improve therapeutic opportunities require deeper understanding of the molecular processes of the normal heart. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavor. Here, using large-scale single cell and nuclei transcriptomic profiling together with state-of-the-art analytical techniques, we characterise the adult human heart cellular landscape covering six anatomical cardiac regions (left and right atria and ventricles, apex and interventricular septum). Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, revealing distinct subsets in the atria and ventricles indicative of diverse developmental origins and specialized properties. Further we define the complexity of the cardiac vascular network which includes clusters of arterial, capillary, venous, lymphatic endothelial cells and an atrial-enriched population. By comparing cardiac cells to skeletal muscle and kidney, we identify cardiac tissue resident macrophage subsets with transcriptional signatures indicative of both inflammatory and reparative phenotypes. Further, inference of cell-cell interactions highlight a macrophage-fibroblast-cardiomyocyte network that differs between atria and ventricles, and compared to skeletal muscle. We expect this reference human cardiac cell atlas to advance mechanistic studies of heart homeostasis and disease