Validation of thoracolumbar injury classification and Severity Score in the management of acute and subacute Osteoporotic vertebral compression fractures - A pilot study and a suggested modification.

Objective: To retrospectively assess the Thoracolumbar Injury Classification and Severity Score (TLICS) in patients with osteoporotic vertebral compression fractures (OVCF) and compare the treatment given with that predicted by the TLICS score.

Methods: All medical records of patients presenting from January 2014 to November 2017 for acute atraumatic or low impact OVCF were screened, and eligible patients were retrospectively reviewed. The TLICS score was determined based upon magnetic resonance imaging (MRI) findings and clinical records.

Intense Imagery Movements May Lead to Maladaptive Daydreaming: A Case Series and Literature Review.

Background: This case series highlights the connection between childhood intense imagery movements (IIM) and adult-reported maladaptive daydreaming (MD). Motor stereotypies occur in typically developing children and also with co-occurring neurodevelopmental differences. A subgroup with complex motor stereotypies reports accompanying intense imagery, often enhanced by the movements.

Diffusive persistence on disordered lattices and random networks.

To better understand the temporal characteristics and the lifetime of fluctuations in stochastic processes in networks, we investigated diffusive persistence in various graphs. Global diffusive persistence is defined as the fraction of nodes for which the diffusive field at a site (or node) has not changed sign up to time t (or, in general, that the node remained active or inactive in discrete models). Here we investigate disordered and random networks and show that the behavior of the persistence depends on the topology of the network.

Pufferfish Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems.

A new bio-inspired metaheuristic algorithm named the Pufferfish Optimization Algorithm (POA), that imitates the natural behavior of pufferfish in nature, is introduced in this paper. The fundamental inspiration of POA is adapted from the defense mechanism of pufferfish against predators. In this defense mechanism, by filling its elastic stomach with water, the pufferfish becomes a spherical ball with pointed spines, and as a result, the hungry predator escapes from this threat.

Giant Armadillo Optimization: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems.

In this paper, a new bio-inspired metaheuristic algorithm called Giant Armadillo Optimization (GAO) is introduced, which imitates the natural behavior of giant armadillo in the wild. The fundamental inspiration in the design of GAO is derived from the hunting strategy of giant armadillos in moving towards prey positions and digging termite mounds. The theory of GAO is expressed and mathematically modeled in two phases: (i) exploration based on simulating the movement of giant armadillos towards termite mounds, and (ii) exploitation based on simulating giant armadillos' digging skills in order to prey on and rip open termite mounds.

Leveraging a novel NFT-enabled blockchain architecture for the authentication of IoT assets in smart cities.

The concept of smart city architecture requires a comprehensive solution that can combine real-time response applications for cyber-physical systems. However, the architecture faces challenges that can obstruct the operations in terms of systems, processes, and data flow as far as the breach risk is concerned. Though the field has been researched with the existence of centralized and distributed architectures to support smart cities.

Lyrebird Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems.

In this paper, a new bio-inspired metaheuristic algorithm called the Lyrebird Optimization Algorithm (LOA) that imitates the natural behavior of lyrebirds in the wild is introduced. The fundamental inspiration of LOA is the strategy of lyrebirds when faced with danger. In this situation, lyrebirds scan their surroundings carefully, then either run away or hide somewhere, immobile.

Kookaburra Optimization Algorithm: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems.

In this paper, a new bio-inspired metaheuristic algorithm named the Kookaburra Optimization Algorithm (KOA) is introduced, which imitates the natural behavior of kookaburras in nature. The fundamental inspiration of KOA is the strategy of kookaburras when hunting and killing prey. The KOA theory is stated, and its mathematical modeling is presented in the following two phases: (i) exploration based on the simulation of prey hunting and (ii) exploitation based on the simulation of kookaburras' behavior in ensuring that their prey is killed.

OOBO: A New Metaheuristic Algorithm for Solving Optimization Problems.

This study proposes the One-to-One-Based Optimizer (OOBO), a new optimization technique for solving optimization problems in various scientific areas. The key idea in designing the suggested OOBO is to effectively use the knowledge of all members in the process of updating the algorithm population while preventing the algorithm from relying on specific members of the population. We use a one-to-one correspondence between the two sets of population members and the members selected as guides to increase the involvement of all population members in the update process.

Golf Optimization Algorithm: A New Game-Based Metaheuristic Algorithm and Its Application to Energy Commitment Problem Considering Resilience.

In this research article, we uphold the principles of the No Free Lunch theorem and employ it as a driving force to introduce an innovative game-based metaheuristic technique named Golf Optimization Algorithm (GOA). The GOA is meticulously structured with two distinctive phases, namely, exploration and exploitation, drawing inspiration from the strategic dynamics and player conduct observed in the sport of golf. Through comprehensive assessments encompassing fifty-two objective functions and four real-world engineering applications, the efficacy of the GOA is rigorously examined.

rBahadur: efficient simulation of structured high-dimensional genotype data with applications to assortative mating.

Existing methods for generating synthetic genotype data are ill-suited for replicating the effects of assortative mating (AM). We propose rb_dplr, a novel and computationally efficient algorithm for generating high-dimensional binary random variates that effectively recapitulates AM-induced genetic architectures using the Bahadur order-2 approximation of the multivariate Bernoulli distribution. The rBahadur R library is available through the Comprehensive R Archive Network at https://CRAN.

Green Anaconda Optimization: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems.

A new metaheuristic algorithm called green anaconda optimization (GAO) which imitates the natural behavior of green anacondas has been designed. The fundamental inspiration for GAO is the mechanism of recognizing the position of the female species by the male species during the mating season and the hunting strategy of green anacondas. GAO's mathematical modeling is presented based on the simulation of these two strategies of green anacondas in two phases of exploration and exploitation.

Segmentation for Multi-Rock Types on Digital Outcrop Photographs Using Deep Learning Techniques.

The basic identification and classification of sedimentary rocks into sandstone and mudstone are important in the study of sedimentology and they are executed by a sedimentologist. However, such manual activity involves countless hours of observation and data collection prior to any interpretation. When such activity is conducted in the field as part of an outcrop study, the sedimentologist is likely to be exposed to challenging conditions such as the weather and their accessibility to the outcrops.

Longitudinal relations between abusive supervision, subordinates' emotional exhaustion, and job neglect among Pakistani Nurses: The moderating role of self-compassion.

The main purpose of this study was to investigate reciprocal relationships between abusive supervision, subordinates' emotional exhaustion, and job neglect, and to examine the mediating role of emotional exhaustion in the cross-lagged relationship between abusive supervision and job neglect. Besides, we tested the moderating role of self-compassion in the cross-lagged relationship between abusive supervision and emotional exhaustion. We applied a two-wave cross-lagged panel design with a time lag of six months.

Linking Perceived Organizational Politics to Workplace Cyberbullying Perpetration: The Role of Anger and Fear.

The introduction of information and communication technologies in the workplace has extended the scope of bullying behaviors at work to the online context. However, less is known about the role of situational factors in encouraging cyberbullying behavior in the workplace. The purpose of this study is to investigate the role of perceived organizational politics in fueling cyberbullying in the workplace, and to examine the central role of negative emotions in this process.

Smile makeover treatments.

The demand for aesthetic smile makeover treatments is increasing, especially with the rise in social media use. Historically, healthy tooth structure was sacrificed in order to achieve rapid results but this would invariably lead to compromise of the occlusion and a less-than-ideal result.Multi-disciplinary treatment planning, including the use of orthodontic treatment, is now routinely used in order to achieve optimal results.

The changing landscape of childhood tic disorders following COVID-19.

The article describes classification, aetiology and features of typical tic disorders (Tourette syndrome) and their management with an additional focus on a surge in atypical tic presentations following the COVID-19 pandemic, often described as functional tics, or functional tic-like movements. We discuss what explains their atypical nature and what might underpin this increase in incidence. Lastly the article provides an overview of management of functional tics, so readers can understand how management of these differs from typical tic disorders.

Automated Real-Time Identification of Medicinal Plants Species in Natural Environment Using Deep Learning Models-A Case Study from Borneo Region.

The identification of plant species is fundamental for the effective study and management of biodiversity. In a manual identification process, different characteristics of plants are measured as identification keys which are examined sequentially and adaptively to identify plant species. However, the manual process is laborious and time-consuming.

A Comparative Analysis on Blockchain versus Centralized Authentication Architectures for IoT-Enabled Smart Devices in Smart Cities: A Comprehensive Review, Recent Advances, and Future Research Directions.

Smart devices have become an essential part of the architectures such as the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Internet of Everything (IoE). In contrast, these architectures constitute a system to realize the concept of smart cities and, ultimately, a smart planet. The adoption of these smart devices expands to different cyber-physical systems in smart city architecture, i.

Modelling epidemic spread in cities using public transportation as a proxy for generalized mobility trends.

We study how public transportation data can inform the modeling of the spread of infectious diseases based on SIR dynamics. We present a model where public transportation data is used as an indicator of broader mobility patterns within a city, including the use of private transportation, walking etc. The mobility parameter derived from this data is used to model the infection rate.

Auxiliary ATP binding sites support DNA unwinding by RecBCD.

The RecBCD helicase initiates double-stranded break repair in bacteria by processively unwinding DNA with a rate approaching ∼1,600 bp·s, but the mechanism enabling such a fast rate is unknown. Employing a wide range of methodologies - including equilibrium and time-resolved binding experiments, ensemble and single-molecule unwinding assays, and crosslinking followed by mass spectrometry - we reveal the existence of auxiliary binding sites in the RecC subunit, where ATP binds with lower affinity and distinct chemical interactions as compared to the known catalytic sites. The essentiality and functionality of these sites are demonstrated by their impact on the survival of E.