A numerical study of spatio-temporal COVID-19 vaccine model via finite-difference operator-splitting and meshless techniques.

In this paper, a new spatio-temporal model is formulated to study the spread of coronavirus infection (COVID-19) in a spatially heterogeneous environment with the impact of vaccination. Initially, a detailed qualitative analysis of the spatio-temporal model is presented. The existence, uniqueness, positivity, and boundedness of the model solution are investigated. Local asymptotical stability of the diffusive COVID-19 model at steady state is carried out using well-known criteria. Moreover, a suitable nonlinear Lyapunov functional is constructed for the global asymptotical stability of the spatio-temporal model. Further, the model is solved numerically based on uniform and non-uniform initial conditions. Two different numerical schemes named: finite difference operator-splitting and mesh-free operator-splitting based on multi-quadratic radial basis functions are implemented in the numerical study. The impact of diffusion as well as some pharmaceutical and non-pharmaceutical control measures, i.e., reducing an effective contact causing infection transmission, vaccination rate and vaccine waning rate on the disease dynamics is presented in a spatially heterogeneous environment. Furthermore, the impact of the  aforementioned interventions is investigated with and without diffusion on the incidence of disease. The simulation results conclude that the random motion of individuals has a significant impact on the disease dynamics and helps in setting a better control strategy for disease eradication.

Utilization of Haar wavelet collocation technique for fractal-fractional order problem.

This work is devoted for establishing adequate results for the qualitative theory as well as approximate solution of "fractal-fractional order differential equations" (F-FDEs). For the required numerical results, we use Haar wavelet collocation (H-W-C) method which has very rarely utilized for F-FDEs. We establish the general algorithm for F-FDEs to compute numerical solution for the considered class. Also, we establish a result devoted to the qualitative theory via Banach fixed point result. A results devoted to Ulam-Hyers (U-H) stability are also included. Two pertinent examples are given along with the comparison and different norms of errors displayed in figures as well as tables.

Guiding Army Commanders' Decision-making Process in Managing Their Suicide Prevention Programs.

PURPOSE OF REVIEW: This paper focuses on how mental health professionals working with Army commanders can help them make decisions based on valid population-based metrics. We first summarize the scope of the impact of suicides on the Army. We then describe the process by which decision-making can be optimized. RECENT FINDINGS: The currently available tools in the US Army including BH Pulse, Unit Risk Inventory, The Azimuth Check, and the Army Readiness Assessment Program have a role in assisting mental health professionals. The specific advantages of BH Pulse over the other tools are highlighted. The US Army has been committed to enhancing its suicide prevention program through comprehensive policies, procedures, and provisions of resources. Commanders are expected to interact with the suicide prevention programs in their units and maximize the systems in place to prevent suicides and other negative mental health outcomes. Commanders are expected to receive cues and signals from a variety of data sources to assist their decision-making process. We discuss the specific advantages of BH Pulse and recommend its routine use for primary prevention and utilizing this tool after incidents to make data-driven, justifiable decisions. Finally, recommendations are provided on enhancing a unit's suicide prevention program.

Perspectives on the Ethics of Antibiotic Overuse and on the Implementation of (New) Antibiotics.

The continuing rise in global antimicrobial resistance is seen by many governments and international organizations as a major threat to worldwide health. This means that many publications have already described the problems concerning the overuse of currently available antibiotics and potential solutions to this crisis, including the development of new alternatives to antibiotics. However, in this manuscript, the authors approach the subject of increasing global antimicrobial resistance from two perspectives not normally covered by previous publications, namely the ethical use of antibiotics and potential issues relating to the implementation of new antibiotics.

Progress in Alternative Strategies to Combat Antimicrobial Resistance: Focus on Antibiotics.

Antibiotic resistance, and, in a broader perspective, antimicrobial resistance (AMR), continues to evolve and spread beyond all boundaries. As a result, infectious diseases have become more challenging or even impossible to treat, leading to an increase in morbidity and mortality. Despite the failure of conventional, traditional antimicrobial therapy, in the past two decades, no novel class of antibiotics has been introduced. Consequently, several novel alternative strategies to combat these (multi-) drug-resistant infectious microorganisms have been identified. The purpose of this review is to gather and consider the strategies that are being applied or proposed as potential alternatives to traditional antibiotics. These strategies include combination therapy, techniques that target the enzymes or proteins responsible for antimicrobial resistance, resistant bacteria, drug delivery systems, physicochemical methods, and unconventional techniques, including the CRISPR-Cas system. These alternative strategies may have the potential to change the treatment of multi-drug-resistant pathogens in human clinical settings.

Correction to: Optimal control analysis of COVID-19 vaccine epidemic model: a case study.

[This corrects the article DOI: 10.1140/epjp/s13360-022-02365-8.].

Optimal control analysis of COVID-19 vaccine epidemic model: a case study.

The purpose of this research is to explore the complex dynamics and impact of vaccination in controlling COVID-19 outbreak. We formulate the classical epidemic compartmental model by introducing vaccination class. Initially, the proposed mathematical model is analyzed qualitatively. The basic reproductive number is computed and its numerical value is estimated using actual reported data of COVID-19 for Pakistan. The sensitivity analysis is performed to analyze the contribution of model embedded parameters in transmission of the disease. Further, we compute the equilibrium points and discussed its local and global stability. In order to investigate the influence of model key parameters on the transmission and controlling of the disease, we perform numerical simulations describing the impact of various scenarios of vaccine efficacy rate and other controlling measures. Further, on the basis of sensitivity analysis, the proposed model is restructured to obtained optimal control model by introducing time-dependent control variables u 1 ( t ) for isolation, u 2 ( t ) for vaccine efficacy and u 3 ( t ) for treatment enhancement. Using optimal control theory and Pontryagin's maximum principle, the model is optimized and important optimality conditions are derived. In order to explore the impact of various control measures on the disease dynamics, we considered three different scenarios, i.e., single and couple and threefold controlling interventions. Finally, the graphical interpretation of each case is depicted and discussed in detail. The simulation results revealed that although single and couple scenarios can be implemented for the disease minimization but, the effective case to curtail the disease incidence is the threefold scenario which implements all controlling measures at the same time.

CcCIPK14 Gene Function Analysis to Illuminate the Efficient Root Transgenic System.

An efficient and stable transformation system is fundamental for gene function study and molecular breeding of plants. Here, we describe the use of an Agrobacterium rhizogenes mediated transformation system on pigeon pea. The stem is infected with A. rhizogenes carrying a binary vector, which induced callus after 7 days and adventitious roots 14 days later. The generated transgenic hairy root was identified by morphological analysis and a GFP reporter gene.To further illustrate the application range of this system, CcCIPK14 (Calcineurin B-like protein-interacting protein kinases) was transformed into pigeon pea using this transformation method. The transgenic plants were treated with jasmonic acid (JA) and abscisic acid (ABA), respectively, for the purpose of testing whether CcCIPK14 responds to those hormones. The results demonstrated that (1) exogenous hormones could significantly upregulate the expression levelof CcCIPK14, especially in CcCIPK14 over-expression (OE) plants; (2) the content of Genistein in CcCIPK14-OE lines was significantly higher than the control; (3) the expression level of two downstream key flavonoid synthase genes, CcHIDH1 and CcHIDH2, were up-regulated in the CcCIPK14-OE lines; and (4) the hairy root transgenic system can be used to study metabolically functional genes in non-model plants.

Daily variation in sleep characteristics in individuals with and without post traumatic stress disorder.

BACKGROUND: Sleep disturbances are common in individuals with post traumatic stress disorder (PTSD). However, little is known about how daily variation in sleep characteristics is related to PTSD. This study examined the night-to-night and weekday versus weekend variation in sleep duration, sleep quality, trouble falling asleep, and difficulty staying asleep in individuals with and without PTSD. METHODS: Participants (N = 157; 80 with PTSD, 77 without PTSD) completed daily self-reports of their nighttime sleep characteristics for 15 consecutive days. Linear mixed models were used to examine the associations between the 7 days of the week and weekday versus weekend variation in sleep characteristics and PTSD. RESULTS: Individuals with PTSD reported shorter sleep duration, lower sleep quality, more trouble falling asleep, and more difficulty staying asleep than individuals without PTSD. The pattern of change across the week and between weekdays and weekends was different between those with and without PTSD for sleep quality and trouble falling asleep. Among those with PTSD, sleep duration, sleep quality, and trouble falling asleep differed across the 7 days of the week and showed differences between weekdays and weekends. For those without PTSD, only sleep duration differed across the 7 days of the week and showed differences between weekdays and weekends. Neither group showed 7 days of the week nor weekday versus weekend differences in difficulty staying asleep. CONCLUSIONS: On average those with PTSD had shorter sleep duration, poorer sleep quality, and greater trouble falling and staying asleep. In particular, the day of week variation in sleep quality and trouble falling asleep specifically distinguishes those with PTSD from those without PTSD. Our findings suggest that clinical care might be improved by assessments of sleep patterns and disturbances across at least a week, including weekdays and weekends. Future studies should explore the mechanisms related to the patterns of sleep disturbance among those with PTSD.

Training During Social Distancing: The Effects of Remote Virtual Psychiatric Readiness Curriculum on Military Behavioral Health Providers.

There is inconsistency in the training of military medical providers on the regulations and procedures outlining US Army-specific psychiatric readiness related competencies. These competencies are necessary to ensure the appropriate categorization of a soldier's psychiatric readiness. There exists a need for a formal, comprehensive training curriculum accessible to all providers that is time- and cost-effective. Due to the COVID-19 pandemic, there is are additional barriers of social distancing, remote virtual healthcare delivery, and geographic dispersion of healthcare personnel. To address these concerns, we developed a curriculum to target these competencies and deliver them virtually. The curriculum was developed and executed based on Kern's six-step approach to curriculum development, and the objective was to train military behavioral health providers on temporary duty limitations, administrative separations, and medical board referrals based on current US Army policies and procedures. The training was implemented virtually and conducted over the course of 3-hour training sessions to two separate groups. Evaluation of training objectives was conducted via a survey of paired before and after questions, analyzing the change in perceived confidence among learners. Among the 58 respondents, training resulted in statistically significant improvement in confidence in recognizing when a US Army soldier needs a temporary profile, writing a temporary e-profile, deciding when it is critical to contact a US Army soldier's commander, executing administrative separation, deciding when a US Army soldier is at medical retention determination point (MRDP), and in referring a US Army soldier to medical board. Results show the feasibility of virtual training to enhance medical readiness-related competencies of healthcare providers at the enterprise-level to help improve medical readiness. Limitations included immediate and subjective aspects of our results. It is unclear whether our training or similar training sessions resulted in changes in behaviors such as increased profiling or medical board referrals.

Efficient Numerical Algorithm for the Solution of Eight Order Boundary Value Problems by Haar Wavelet Method.

In this paper, the Haar technique is applied to both nonlinear and linear eight-order boundary value problems. The eight-order derivative in the boundary value problem is approximated using Haar functions in this technique and the integration process is used to obtain the expression of the lower order derivative and the approximate solution of the unknown function. For the verification of validation and convergence of the proposed technique, three linear and two nonlinear examples are taken from the literature. The results are also compared with other methods available in the literature. Maximum absolute and root mean square errors at various collocation and Gauss points are contrasted with the exact solution. The convergence rate is also measured, which is almost equivalent to 2, using different numbers of collocation points.

The pigeon pea CcCIPK14-CcCBL1 pair positively modulates drought tolerance by enhancing flavonoid biosynthesis.

Calcineurin B-like (CBL)-interacting protein kinases (CIPKs) play a central role in Ca2+ signalling and promote drought tolerance in plants. The CIPK gene family in pigeon pea (Cajanus cajan L.), a major food crop affected by drought, has not previously been characterised. Here, we identified 28 CIPK genes in the pigeon pea genome. Five CcCIPK genes were strongly upregulated in roots upon drought treatment and were selected for further characterisation. Overexpression of CcCIPK13 and CcCIPK14 increased survival rates by two- to three-fold relative to controls after 14 days of drought. Furthermore, the three major flavonoids, genistin, genistein and apigenin, were significantly upregulated in the same transgenic plants. Using CcCIPK14 as bait, we performed a yeast two-hybrid screen and identified six interactors, including CcCBL1. CcCIPK14 exhibited autophosphorylation and phosphorylation of CcCBL1 in vitro. CcCBL1-overexpressed plants displayed higher survival rates upon drought stress as well as higher expression of flavonoid biosynthetic genes and flavonoid content. CcCIPK14-overexpressed plants in which CcCBL1 transcript levels were reduced by RNA interference had lower survival rates, which indicated CcCBL1 in the same pathway as CcCIPK14. Together, our results demonstrate a role for the CcCIPK14-CcCBL1 complex in drought stress tolerance through the regulation of flavonoid biosynthesis in pigeon pea.

The functional analysis of ABCG transporters in the adaptation of pigeon pea (Cajanus cajan) to abiotic stresses.

ATP-binding cassette (ABC) transporters are a class of proteins found in living organisms that mediate transmembrane transport by hydrolyzing ATP. They play a vital role in the physiological processes of growth and development in plants. The most numerous sub-type transporter in the ABC transporter family is the ABCG group and which have the most complex function in a plant's response to abiotic stresses. Our study focused on the effect of ABCG transporters in the adaptation of the pigeon pea to adverse environments (such as drought, salt, temperature, etc.). We conducted a functional analysis of ABCG transporters in the pigeon pea and their role in response to abiotic stresses. A total of 51 ABCG genes (CcABCGs) were identified, and phylogenetic analysis was conducted. We also identified the physicochemical properties of the encoded proteins, predicted their subcellular localization, and identified of the conserved domains. Expression analysis showed that ABCG genes have different expression profiles with tissues and abiotic stresses. Our results showed that CcABCG28 was up-regulated at low temperatures, and CcABCG7 was up-regulated with drought and aluminum stress. The initial results revealed that ABCG transporters are more effective in the abiotic stress resistance of pigeon peas, which improves our understanding of their application in abiotic stress resistance.

Multidimensional analysis of actin depolymerising factor family in pigeon pea under different environmental stress revealed specific response genes in each subgroup.

Actin depolymerising factor (ADF) is an actin binding protein that is ubiquitous in animal and plant cells. It plays an important role in plant growth and development, as well as resistance to biotic and abiotic stress. The research of plant ADF family has been restricted to Arabidopsis thaliana (L.) Heynh. and some herb crops, but no woody cash crops have been reported to date. All members of the Cajanus cajan (L.) Millsp. ADF (CcADF) family were identified from the pigeon pea genome, and distributed among the four subfamilies by phylogenetic analysis. CcADFs were relatively conservative in gene structure evolution, protein structure and functional expression, and different CcADFs showed specific expression patterns under different treatments. The expression characteristics of several key CcADFs were revealed by analysing the stress response pattern of CcADFs and the time series RNA-seq of aluminium stress. Among them, CcADF9 in the first subgroup specifically responded to aluminium stress in the roots; CcADF3 in the second subgroup intensively responded to fungal infection in the leaves; and CcADF2 in the fourth subgroup positively responded to various stress treatments in different tissues. This study extended the relationship between plant ADF family and aluminium tolerance, as well as adding to the understanding of CcADF family in woody crops.

Efficient numerical technique for solution of delay Volterra-Fredholm integral equations using Haar wavelet.

In this article, a computational Haar wavelet collocation technique is developed for the solution of linear delay integral equations. These equations include delay Fredholm, Volterra and Volterra-Fredholm integral equations. First we transform the derived estimates for these equations. After that, we transform these estimates to a system of algebraic equations. Finally, we solve the obtained algebraic system by Gauss elimination technique. Numerical examples are taken from literature for checking the validity and convergence of the proposed technique. The maximum absolute and root mean square errors are compared with the exact solution. The convergence rate using distinct numbers of collocation points is also calculated, which is approximately equal to 2. All algorithms for the developed method are implemented in MATLAB (R2009b) software.

Augmented Reality Interface for Complex Anatomy Learning in the Central Nervous System: A Systematic Review.

The medical system is facing the transformations with augmentation in the use of medical information systems, electronic records, smart, wearable devices, and handheld. The central nervous system function is to control the activities of the mind and the human body. Modern speedy development in medical and computational growth in the field of the central nervous system enables practitioners and researchers to extract and visualize insight from these systems. The function of augmented reality is to incorporate virtual and real objects, interactively running in a real-time and real environment. The role of augmented reality in the central nervous system becomes a thought-provoking task. Gesture interaction approach-based augmented reality in the central nervous system has enormous impending for reducing the care cost, quality refining of care, and waste and error reducing. To make this process smooth, it would be effective to present a comprehensive study report of the available state-of-the-art-work for enabling doctors and practitioners to easily use it in the decision making process. This comprehensive study will finally summarise the outputs of the published materials associate to gesture interaction-based augmented reality approach in the central nervous system. This research uses the protocol of systematic literature which systematically collects, analyses, and derives facts from the collected papers. The data collected range from the published materials for 10 years. 78 papers were selected and included papers based on the predefined inclusion, exclusion, and quality criteria. The study supports to identify the studies related to augmented reality in the nervous system, application of augmented reality in the nervous system, technique of augmented reality in the nervous system, and the gesture interaction approaches in the nervous system. The derivations from the studies show that there is certain amount of rise-up in yearly wise articles, and numerous studies exist, related to augmented reality and gestures interaction approaches to different systems of the human body, specifically to the nervous system. This research organises and summarises the existing associated work, which is in the form of published materials, and are related to augmented reality. This research will help the practitioners and researchers to sight most of the existing studies subjected to augmented reality-based gestures interaction approaches for the nervous system and then can eventually be followed as support in future for complex anatomy learning.

A Collocation Method for Numerical Solution of Nonlinear Delay Integro-Differential Equations for Wireless Sensor Network and Internet of Things.

Wireless sensor network and industrial internet of things have been a growing area of research which is exploited in various fields such as smart home, smart industries, smart transportation, and so on. There is a need of a mechanism which can easily tackle the problems of nonlinear delay integro-differential equations for large-scale applications of Internet of Things. In this paper, Haar wavelet collocation technique is developed for the solution of nonlinear delay integro-differential equations for wireless sensor network and industrial Internet of Things. The method is applied to nonlinear delay Volterra, delay Fredholm and delay Volterra-Fredholm integro-differential equations which are based on the use of Haar wavelets. Some examples are given to show the computational efficiency of the proposed technique. The approximate solutions are compared with the exact solution. The maximum absolute and mean square roots errors for distant number of collocation points are also calculated. The results show that Haar method is efficient for solving these equations for industrial Internet of Things. The results are compared with existing methods from the literature. The results exhibit that the method is simple, precise and efficient.

Development of a Leader Tool for Assessing and Mitigating Suicide Risk Factors.

INTRODUCTION: Despite efforts in prevention, suicide rates in the US military remain unchanged. This article describes the development of a tool for leaders to identify and mitigate suicide risk factors. METHODS: A seven-item measure, the Leader Suicide Risk Assessment Tool (LSRAT), was constructed to allow leaders to assess and mitigate suicide drivers. During a 6-mo pilot, unit leaders completed the LSRAT for 161 at-risk soldiers. The LSRAT data were compared to clinical data from a subset of these soldiers. RESULTS: The LSRAT showed good test-retest reliability. The LSRAT scores showed significant correlations with both clinical and screening measures of suicidality. Command actions mitigated or partially mitigated 89% of risk factors identified on the LSRAT. CONCLUSIONS: This study provides initial psychometric data on a tool that prescribes concrete responses to mitigate risk. The LSRAT may be a valid and feasible tool to assist front-line commanders in identifying potential area's risk mitigation. Synchronization efforts between commanders, clinicians, and support services are crucial to ensure effective intervention to prevent suicide behavior.

Effects of Brief Depression and Anxiety Management Training on a US Army Division's Primary Care Providers.

INTRODUCTION: There is a nation-wide gap between the prevalence of mental illness and the availability of psychiatrists. This places reliance on primary care providers (PCPs) to help meet some of these mental health needs. Similarly, the US Army expects its PCPs to be able to manage common mental illnesses such as anxiety and depression. Therefore, PCPs must be able to close their psychiatric skills gaps via lifelong learning. MATERIALS AND METHODS: Following needs assessment of PCPs in a US Army division, the curriculum was developed. Objectives targeted pharmacological management of depression and anxiety. Behavioral intervention skills were also taught to treat insomnia. Didactics and case-based small groups were used. A novel psychotropic decisional tool was developed and provided to learners to assist and influence their future psychiatric practice. Pre-training, immediate post-training, and 6-month assessments were done via survey to evaluate confidence and perceived changes in practice. The curriculum was executed as a quality improvement project using the Plan, Do, Study, Act framework. RESULTS: Among 35 learners, immediate confidence in selecting optimal psychotropic and perceived knowledge, skill to change the dose or type of medication, and confidence in prescribing behavioral sleep improved significantly with large effect sizes. At 6-month follow-up, learners reported that they were more likely to adjust medications for anxiety or depression and were more likely to start a new medication for anxiety or depression because of the training with moderate effect sizes. Use and satisfaction with the psychotropic decisional tool are also reported. CONCLUSIONS: Our psychotropic decisional tool illustrates a novel algorithmic approach for operationalizing the management of depression and anxiety. Similar approaches can improve the skills of a variety of PCPs in the management of psychiatric disorders. Further studies in the military operational setting are needed to assess the effects of similar educational interventions on access to behavioral health care, suicidal behaviors, and unit medical readiness.