Sex assessment is an important step of the forensic process. Dental remains are often the only remains left to examine due to their resistance to decay and external factors. Contemporary forensic odontology literature describes multiple methods for sex assessment from mandibular parameters, all of which require manual measurements and expert training. This study aims to explore the applicability of deep learning and image analysis methods to automate this task, thus allowing for easier reproducibility of assessments, reduction of the time experts lose on repetitive tasks, and potentially better performance. We have evaluated state-of-the-art deep learning models and components on the largest dataset of individual adult tooth x-ray images, consisting of 76293 samples. This study also explores the usage of decayed or structurally altered teeth, with which contemporary methods struggle. Two types of models are constructed, a family of models specialized for specific tooth types, and a general model that can assess the sex from any tooth type. We examine the performance of those models per tooth type and age group, as well as the impact of decayed and structurally altered teeth. The specialized models achieve an overall accuracy of 72.40%, and the general model reaches an overall accuracy of 72.68%.

Networked industrial systems capitalize on recent advancements in sensing, communications, computing and storage to improve productivity, operational and cost efficiency. The proliferation of effective techniques for knowledge extraction drive a paradigm shift in industrial environments and provide a fertile ground for enhanced process monitoring and control capabilities. In an effort to shed light on industrial data management operations, this paper presents two different approaches for dealing with information processing tasks of aggregated sensor measurements. Such tasks constitute part of an end-to-end process monitoring solution which is implemented in an open-source platform following a modular, scalable and interpretable procedure. A mapping of the industrial data processing components to the operational principles and architecture of a cyber-physical system reveals useful insights for an automated supervision of critical processes and workflows.

Abstract. Alongside climate change, the introduction of non-native species (NNS) is widely recognized as one of the main threats to aquatic biodiversity and human wellbeing. Non-native species and biodiversity are generally low priority issues on the political agendas of many countries, particularly in European countries outside the European Union (EU). The objectives and tasks of this study were to address the policy regulation, education level, education practices, and socioeconomic perceptions of NNS in the Balkans. A questionnaire-based survey was conducted in Albania, Bosnia and Herzegovina, Montenegro, North Macedonia and Turkey (Balkan EU candidate and potential candidate members), in Croatia and Greece (Balkan EU Member States) and Italy (non-Balkan EU Member State). The EU Alien Regulation (1143/2014) concerning NNS is implemented in EU Member States and Montenegro, whereas Albania, Bosnia and Herzegovina and Turkey have not reported specific policy regulations for NNS. Permanent monitoring programmes specifically designed for NNS have not yet been established in the EU Member States. Most countries tackle the issue of NNS through educational activities as part of specific projects. Education level is indicative of the implementation of NNS policy regulation, and efforts are needed for the proper development of relative study programmes. Public awareness and educational preparedness concerning NNS in the Balkans were identified as poor. Strong programmes for management and education should be developed to increase public awareness to prevent further biodiversity losses in the Balkan region.

The experimental investigation of Newton’s law of universal gravitation requires expensive and sensitive equipment. Therefore, it is often not possible to conduct such an experiment within a typical physics class. An alternative is to investigate the universal gravitation law by using simulations. In this paper, we are presenting such an augmented reality simulation (GravityAR). The simulation has been developed for mobile devices and runs on an Android operating system, making it very accessible for students and teachers at all educational levels. It allows the user to investigate how the gravitational force between two spherical bodies depends on their masses and mutual distance. Additionally, the simulation can be used to determine the value of the gravitational constant (G).

Acute myocardial infarction (AMI) and the heart failure (HF) which may follow are among the leading causes of death and disability worldwide. As such, new therapeutic interventions are still needed to protect the heart against acute ischemia/reperfusion injury to reduce myocardial infarct size and prevent the onset of HF in patients presenting with AMI. However, the clinical translation of cardioprotective interventions that have proven to be beneficial in preclinical animal studies, has been challenging. One likely major reason for this failure to translate cardioprotection into patient benefit is the lack of rigorous and systematic in vivo preclinical assessment of the efficacy of promising cardioprotective interventions prior to their clinical evaluation. To address this, we propose an in vivo set of step-by-step criteria for IM proving P reclinical A ssessment of C ardioprotective T herapies (‘IMPACT’), for investigators to consider adopting before embarking on clinical studies, the aim of which is to improve the likelihood of translating novel cardioprotective interventions into the clinical setting for patient benefit.

Two-wave with diffuse power (TWDP) is one of the most promising distribution for description of a small-scale fading in the emerging mmWave band. However, traditional error performance analysis in these channels faces two fundamental issues. It is mostly based on conventional TWDP parameterization which is not in accordance with the model’s underlying physical mechanisms and which hinders accurate observation of the impact of a model parameters on a system’s performance metrics. In addition, the existing average bit/symbol error probability (ABEP/ASEP) expressions for most modulations and diversity schemes are available as approximations, which are accurate only for specific combinations of TWDP parameters. Accordingly, in this paper, the exact ASEP expressions are derived for M-ary rectangular quadrature amplitude modulation (RQAM) with coherent detection and for M-ary DPSK modulation, and are given in terms of physically justified parameters. Besides, in order to relax computational complexity of proposed exact ASEPs in high signal-to-noise ratio (SNR) region, their asymptotic counterparts are derived as the simple closed-form expressions, matching the exact ones for SNR>30dB. Results are verified by Monte-Carlo simulation.

Electrochemically deposited copper coatings obtained from sulfate baths on brass substrates in the regime of direct current (DC) with and without an application of ultrasound mixing of electrolytes (DC/US) have been studied. The aim of the research was analysis of the influence of current density, ultrasonic mixing of electrolyte and presence of additives on the electrodeposited coatings, in order to obtain uniform compact coatings suitable for potential application in MEMS devices. Structural, electrical and mechanical behavior of thin copper coatings were investigated using SEM, AFM, four- point probe method and Vickers hardness test.

This article discusses how to create an interactive virtual training program at the intersection of neuroscience, robotics, and computer science for high school students with equity of access. A four-day microseminar, titled Swarming Powered by Neuroscience (SPN), was conducted virtually through a combination of presentations and interactive computer game simulations. The SPN microseminar was delivered by subject matter experts in neuroscience, mathematics, multi-agent swarm robotics, and education. The objective of this research was to determine if taking an interdisciplinary approach to high school education would enhance the students learning experiences in fields such as neuroscience, robotics, or computer science. This study found an improvement in student engagement for neuroscience by 16.6%, while interest in robotics and computer science improved respectively by 2.7% and 1.8%. The majority of students (64%) strongly agreed that they enjoyed learning from an interdisciplinary team of experts and 70% strongly agreed that the microseminar emphasized the need to have instruction teams with diverse disciplinary backgrounds. The curriculum materials, developed for the SPN microseminar, can be used by high school teachers to further evaluate interdisciplinary instructions across life and physical sciences and computer science.

Background: Patients with immunocompromised disorders have mainly been excluded from clinical trials of vaccination against COVID-19. Thus, the aim of this prospective clinical trial was to investigate the safety and efficacy after two doses of BNT162b2 mRNA vaccination in five selected groups of immunocompromised patients and healthy controls. Methods: 539 study subjects (449 patients and 90 controls) were included in the clinical trial. The patients had either primary (n=90), or secondary immunodeficiency disorders due to human immunodeficiency virus infection (n=90), allogeneic hematopoietic stem cell transplantation/chimeric antigen receptor T cell therapy (n=90), solid organ transplantation (SOT) (n=89), or chronic lymphocytic leukemia (CLL) (n=90). The primary endpoint was seroconversion rate two weeks after the second dose. The secondary endpoints were safety and documented SARS-CoV-2 infection. Findings: Adverse events were generally mild, but one case of fatal suspected unexpected serious adverse reaction occurred. 72.2% of the immunocompromised patients seroconverted compared to 100% of the controls (p=0.004). Lowest seroconversion rates were found in the SOT (43.4%) and CLL (63.3%) patient groups with observed negative impact of treatment with mycophenolate mofetil and ibrutinib, respectively. Interpretation: The results showed that the mRNA BNT162b2 vaccine was safe in immunocompromised patients. The rate of seroconversion was substantially lower than in healthy controls, with a wide range of rates and antibody titres among predefined patient groups and subgroups. This clinical trial highlights the need for additional vaccine doses in certain immunocompromised patient groups and/or subgroups to improve immunity.

On January 2020, the WHO Director General declared that the outbreak constitutes a Public Health Emergency of International Concern. The world has faced a worldwide spread crisis and is still dealing with it. The present paper represents a white paper concerning the tough lessons we have learned from the COVID-19 pandemic. Thus, an international and heterogenous multidisciplinary panel of very differentiated people would like to share global experiences and lessons with all interested and especially those responsible for future healthcare decision making. With the present paper, international and heterogenous multidisciplinary panel of very differentiated people would like to share global experiences and lessons with all interested and especially those responsible for future healthcare decision making.

Eurasian jays have been reported to protect their caches by responding to cues about either the visual perspective or current desire of an observing conspecific, similarly to other corvids. Here, we used established paradigms to test whether these birds can – like humans – integrate multiple cues about different mental states and perform an optimal response accordingly. Across five experiments, which also include replications of previous work, we found little evidence that our jays adjusted their caching behaviour in line with the visual perspective and current desire of another agent, neither by integrating these social cues nor by responding to only one type of cue independently. These results raise questions about the reliability of the previously reported effects and highlight several key issues affecting reliability in comparative cognition research.

Abstract Bamboo has been widely used in construction for its high strength, lightweight and low cost. It usually fails from the skin because of macroscopic fiber splitting. Previous research focused on the strength of bamboo at structural scale without insight to its chemistry and microstructure of the skin and how they relate to its facture. In this research, we combine multiscale computational modeling with experimental methods to characterize the distribution of silica particles within the bamboo skin and investigate their effect on fracture. We use microscope to characterize the chemical and microscopic feature of bamboo skin and find silica particles generally distributed in bamboo skin and their pairwise distances follow a normal distribution. We use molecular dynamics simulations and finite element analysis to investigate the effect of silica particles and their unique distribution on the fracture of bamboo skin. It is noted that the silica forms a perfect bonding interface to cellulose fibers and the particles significantly increase the critical stress up to 6.28% than pure cellulose matrix for cracks that randomly occurs. We find that such an enhancement in critical stress against random cracks is only guaranteed by the distribution of silica particles in bamboo skin, as such an enhancement is not observed for other randomly assigned silica particles, suggesting that the silica distribution in bamboo skin is optimal for critical stress improvement for random cracks. This research output can inspire the development of more durable and sustainable bamboo products as well as innovative synthetic composite materials.

Purpose The purpose of this paper is to assess and compare the symmetric and asymmetric effects of consumer sentiment on house prices in each state of the USA. This is the first study that uses state-level data. Design/methodology/approach Both linear and nonlinear autoregressive distributed lag approaches are used to assess the asymmetric effects of consumer sentiment on house prices in each state of the USA. Findings When the authors estimated a linear symmetric model, this paper found short-run effects of consumer sentiment on house prices in 34 states that lasted into the long-run in only 13 states. The comparable numbers by estimating a nonlinear asymmetric model were 47 and 22, respectively. The increase in the number of states where consumer sentiment affects house prices was attributed to the nonlinear adjustments of consumer sentiment. Originality/value The authors deviate from previous research and assess the impact of consumer sentiment on house prices by using data from each state of the USA. The authors also deviate from previous research by demonstrating that the effects could be asymmetric. No study has done this at the state-level.