This study marks the first identification and genomic characterization of Comamonas kerstersii isolates from diarrheal patients in Bangladesh. C. kerstersii is a gram-negative opportunistic bacterium that has also been reported in several clinical samples, including urine, blood, stool, peritoneal liquid, and sputum. We carried out the whole genome sequencing of three C. kerstersii isolates with the aim of analyzing genomic features in 3 different strains isolated from Bangladesh for the first time. Phylogenetic analysis suggests that these three strains share a clonal relationship. Seven AMR genes, aph(6)-Id, aph(3”)-Ib, mph(E), mph(F), msr(E), sul2, and tet(A), have been observed in all the strains. We identified several virulence factors, including copper homeostasis genes, type IV pili, and type VI secretion system. Phage regions and IncQ1 plasmid were also detected. These initial findings highlight the need for extensive genomic surveillance of C. kerstersii in different diarrheal patients, along with investigating their genotype-phenotype correlation to understand the molecular pathogenesis in detail.

The persistence and efficacy of biocontrol agents (BCAs) in agricultural fields are crucial for sustainable crop production. In this study, using a novel qPCR probe protocol, we investigated the persistence of the introduced bacterial strain Pseudomonas sivasensis CF10PS3 in the wheat phyllosphere. The CF10PS3 strain, known for its biocontrol properties against wheat pathogens, was applied through foliar spray, and its persistence was monitored over seven weeks. Our qPCR assays, designed to specifically detect CF10PS3, distinguished it from naturally occurring P. sivasensis strains, providing precise insights into its dynamics in the field. The experimental results indicated that CF10PS3 was already present on the wheat leaves before application, suggesting its natural adaptation to the foliar environment. Following initial application, a significant increase in CF10PS3 was observed, though subsequent environmental factors such as rain and wind caused notable fluctuations in its population. Despite these variations, the introduced strain showed considerable persistence, with population levels significantly higher than those in untreated plots by the end of the study period. This research underscores the importance of understanding BCA dynamics in the field, highlighting the influence of environmental conditions on their efficacy. Specific qPCR probes proved effective in monitoring introduced strains, offering valuable insights for optimizing BCA application strategies. Our findings contribute to developing robust biocontrol methods, promoting sustainable agricultural practices and enhancing crop protection.

Introduction Collaboration is crucial for innovative scientific contributions, often facilitated through consortia, which are particularly valuable for translating medical innovations to patient care. Despite the rise in consortia, there is limited literature available on how to establish a consortium. This paper aims to provide a comprehensive business and strategy plan for establishing and maintaining biomedical consortia. Methods We explored academic databases and used a snowball sampling method to expand our literature pool, including papers relevant to consortia design such as business and strategy plans. Thematic analysis identified recurring themes, and critical evaluations informed our recommendations, supplemented by experiences from establishing the Neuropsychiatric International Consortium of Frontotemporal Dementia (NIC-FTD). Discussion Our review and experience highlight three key elements for launching and maintaining a successful consortium: (1) Establishment steps and considerations, (2) Consortium agreement and strategy planning, and (3) Maintenance strategies. This paper offers practical guidance for scientists and physicians in establishing and maintaining effective consortia by providing a Consortium Strategy Plan. Conclusion This paper provides a detailed Consortium Strategy Plan with the aim to aid the successful establishment and maintenance of biomedical consortia and to support innovative scientific collaboration.

In order to improve the stability of the in-orbit electrical performance of space-borne antennas, a mechanical-electrical-thermal integrated method is proposed for the design of cable-membrane-truss antenna. The functional surface of the antenna is a Kapton membrane (or metal wire mesh) coated with a metal layer, which is fixed on the surrounding deployable truss through a tensioning cable mesh. Firstly, the coupling relationship between the mechanical characteristics of the cable-membrane-truss structure, the spatial thermal environment, and the electrical performance of the antenna reflector is studied, and a mechanical electrical thermal multi-field coupling analysis model is established. Then, with the initial pretension of the cable membrane as the design value and the minimum and maximum directional coefficient of the antenna at each position in orbit as the optimization objective, the cable-membrane-truss antenna mechanical electrical thermal integrated design optimization model was established, and a 30 meter aperture satellite antenna integrated optimization design simulation was conducted. The simulation results show that using the proposed mechanical-electrical-thermal integrated design method in this paper, the stability of the in-orbit electrical performance of the cable-membrane-truss antenna is improved by approximately 39.1%. This method can improve the stability of in-orbit electrical performance of space-borne antennas.

It is more difficult to discriminate the direction of large sinusoidal gratings than small ones, if both are high contrast. This is presumed to reflect center surround suppression (CSS) within the visual system. CSS is altered in multiple psychological disorders, and its magnitude has been linked to overall intelligence. The present study examines the degree to which two novel factors, physiological arousal and chronic stress, are related to CSS. Stress was measured through a questionnaire, while acute arousal was induced through strenuous aerobic exercise. In both resting and aroused states, participants were presented with a psychophysical motion discrimination task that quantified CSS as the difference in accuracy between a small and a large stimulus across six presentation times. Chronic stress was positively correlated with CSS for the presentation times where the effect peaked. There was no difference in CSS or baseline motion perception performance between exercise-induced aroused states and calm states. The results suggest that CSS does not vary as a function of acute arousal, but rather on a longer-term basis in accordance with stress.

Hepatitis A virus (HAV) has a low endemic circulation pattern in Argentina. Notifications of clinical cases occur especially in susceptible young adults in whom outbreaks have recently been reported. The aim of this study was to provide updated information on HAV immune status of the adult population from central Argentina. A retrospective analysis was carried out recording the results of IgG-anti HAV in 4235 samples of people without prior vaccination from Córdoba, Argentina (2019 and 2022). Epidemiological data was recorded: sex, age, HIV status, income-status. The overall prevalence of anti-HAV was 70.1%. It increased with age, was associated with the low-income population and was significantly higher in female patients (p<0.0001). Individuals under 35 years old exhibited anti-HAV IgG rates <54%. Considering the high proportion of young adult individuals susceptible to HAV infection found, together with evidence of HAV circulation in the region, which can be easily introduced by unvaccinated immigrants or travelers from medium/high endemic countries and the existence of a safe, efficient vaccine, we strongly recommend to increase the study of HAV immunity in individuals >18 years old in our region. In case they are negative, it is recommended vaccination.

Narcissism is a complex dimension related to the self and characterized by grandiosity and/or vulnerability. Grandiosity is related to explicit dominance, self-importance and entitlement while vulnerability is characterized by the feelings of incompetence, inadequacy and negative affect. According to psychodynamic scholars shame can be considered as the core narcissistic affect, however different dynamics might characterize the experience of shame in grandiose and vulnerable narcissism. Although narcissism and shame have received a certain attention in the literature, a comprehensive review of empirical research examining the relationship between these constructs is still missing. Therefore, our systematic review comprised 25 studies on narcissism in its different manifestations and its relation with shame, as different from guilt. We subdivided our articles in three main clusters: 1) correlational studies of narcissistic personality features, 2) studies on narcissistic personality disorder (NPD) and 3) experimental task studies. Overall our findings show that: i) shame is mainly related to vulnerable narcissism while narcissistic grandiosity seems to be a defensive structure towards threatening affect for the self; ii) guilt doesn’t seem to be consistently related to narcissism across studies; iii) NPD studies confirmed the findings of grandiosity as a defensive structure to preserve the self of the individual, while, on the other hand, when NPD is more vulnerable (e.g., depressive, suicidal, etc.), it seems to be more prone to experience shame; iv) experimental studies investigating narcissism in different scenarios, like performance judgements, dishonesty and spirituality, again confirmed the different dynamics between grandiosity and vulnerability related to shame.

Recent advancements in Cognitive Technical Systems (CTS) have significantly transformed human-computer interaction (HCI) by introducing efficient and natural operating principles. These systems heavily rely on data from multiple sensors, which are integrated using fusion algorithms to enhance their functionality. This study proposes a novel cognitive HCI approach, leveraging body sensor data analytics through machine learning within a Mobile Health Communication D2D cloud framework. The core of this research involves employing a Boltzmann Perceptron Basis Encoder Neural Network to analyze various datasets collected from body sensors within the D2D cloud network. The experimental analysis evaluates the efficacy of this approach across different performance metrics, highlighting its superiority over existing methods. The proposed technique demonstrates enhanced efficiency in processing and interpreting monitored data, contributing to advancements in personalized healthcare and interactive computing environments.

For decades, the broad application of the Metabolic Theory of Ecology (MTE) to predict ecological patterns and processes has been a major source of contention among ecologists. Nevertheless, the MTE could potentially explain and predict the responses of functionally important organisms, such as pollinating insects, to a warming climate. Here, we tested whether the main predictions of the MTE hold for four species of globally distributed pollinating insects: Eristalis tenax, Lucilia sericata, Apis mellifera, and Bombus terrestris. We used a closed respirometry system to measure insect CO2 production rates across a continuous range of temperatures (15- 35°C). We tested four major hypotheses derived from the MTE: 1) metabolism will scale with body mass following a ¾ power-law relationship, 2) metabolism positively scales exponentially with temperature according to Arrhenius’ Law, 3) the slopes (i.e., activation energy) of the temperature-metabolism relationship falls within the range of -0.60 and -0.70 eV, and 4) hypotheses 1-3 hold, both within and among species. Our findings suggest that the MTE, as it stands, is only partially applicable across different species of insect pollinators, such that MTE-derived predictions of temperature responses can be made. Nevertheless, the scaling relationships presented in this study provide species-specific metabolic scaling coefficients that are crucial for developing predictive models of pollinator species responses to climate change.

Field monitoring plays a crucial role in understanding insect dynamics within ecosystems. It facilitates pest distribution assessment, control measure evaluation, and prediction of pest outbreaks. Additionally, it provides important information on bioindicators with which the state of biodiversity and ecological integrity in specific habitats and ecosystems can be accurately assessed. However, traditional monitoring systems can present various difficulties, leading to a limited temporal and spatial resolution of the obtained information. Despite recent advancements in automatic insect monitoring traps, also called e-traps, most of these systems focus exclusively on studying agricultural pests, rendering them unsuitable for monitoring diverse insect populations. To address this issue, we introduce the Field Automatic Insect Recognition (FAIR)-Device, a novel non-lethal field tool that relies on semi-automatic image capture and species identification using artificial intelligence via the iNaturalist platform. Our objective was to develop a low-effort, cost-effective, and non-specific monitoring solution capable of providing high-resolution data for assessing insect diversity. During a 26-day proof-of-concept evaluation, the FAIR-Device recorded 24.8 GB of video, identifying 431 individuals from 9 orders, 50 families, and 69 genera. While improvements are possible, our device demonstrated potential as a cost-effective, non-lethal tool for monitoring insect biodiversity. Looking ahead, we envision new monitoring systems such as e-traps as valuable tools for real-time insect monitoring, offering unprecedented insights for ecological research and agricultural practices.

Optimizing algorithms is crucial for categorizing CT brain images for conditions like tumors, cancer and aneurysm. In Machine learning model training, optimizers guide convergence, impacting accuracy and efficiency. This research evaluates the performance of various optimizers, including SGD, Adam, Nadam, Adadelta, Adagrad and RMSprop in classifying brain CT images of diverse optimizers focuses on the evaluation of performance. Our primary objective is to enhance the accuracy of image diagnosis for urgent medical conditions like tumors, cancers, and aneurysms. Using Python and Keras, we systematically explored the efficacy of these optimizers in training Convolutional Neural Networks (CNNs). A Convolutional Neural Network (CNN) execution relies upon factors like weight introduction, improvement techniques, cluster size, learning rate, initiation and misfortune capabilities, network design, and information quality. Specifically it delves into using these optimizers, representing distinct approaches to training Convolutional Neural networks (CNN’s). Our comparative analysis revealed that Adagrad achieved the highest accuracy, with a diagnostic classification accuracy of 99.11%, a loss of 0.0341, a validation loss of 0.0025, and a validation accuracy of 1.00. These results suggest that Adagrad is the best choice for classifying aneurysm, tumor, and cancer patients, positioning it as a potential candidate for future research. Our research mapped sustainable development goal number 3 which is Good health and wellbeing.

Dementia is a progressive and irreversible deterioration of cognition which has a significant impact on the person's activities of daily living and quality of life. Currently, there is no curative treatment of dementia and the treatment options currently used in clinical practice has limited therapeutic reach. Although there are ongoing clinical trials, this review article begins with the question of why statins are no longer clinically indicated in mild cognitive impairment or mild to moderate dementia? This review will explore the evidence in support and against the neuroprotective effects of statins in cognitive impairment. Whilst exploring the evidence around statins, there emerged a possibility of another molecule called cyclodextrin which could potentially not only be a more effective neuroprotective alternative to statins, but possibly an agent which could potentially improve the early or mild cognitive deficits. This literature review will hopefully support in formulating a potential research question for future clinical trials in the treatment of dementia.

Background: Pancreatic cancer is the fourth leading cause of cancer deaths worldwide, a particularly lethal cancer, with the majority of cases dead inside the first year. Mortality statistics have barely changed in over fifty years. Case history: This case history recounts the atypical presentation of a rare pancreatic adenocarcinoma as an aggressive pancreatic pseudocyst, that required multiple drainage/ablative surgeries, mostly in a short time span of 3 months, and recurring. Biopsy revealed its true nature as a rare mucinous adenocarcinoma, by then stage 4 with peritoneal metastases, therefore deemed inoperable, the worst prognosis. Palliative FOLFOX chemotherapy followed by SABR radiotherapy were proposed, with the PARP inhibitor, Olaparib planned as maintenance treatment. These therapies were not expected to radically change the prognostic outlook. However, on compassionate grounds, some experimental therapies, were combined, intended to synergise with the palliative protocols. These therapies included daily high dose methylcobalamin injections, twice weekly, intravenous high dose, vitamin C, liposomal alpha lipoic acid, a ketogenic diet, anti-cachectic medium chain triglyceride oil, high dose vitamin D and a functional food containing colostrum, naturally high in the activated vitamin D binding protein, as well as in lactoferrin, haptocorrin and other immune modulating components. In addition, a quartet of off label drugs, which early research shows have some anti-cancer actions, were prescribed: doxycycline, metformin, atorvastatin and the antiprotozoan drug, mebendazole. Outcome: The patient responded well to these protocols, and was on the road to recovery within 6 months, and in complete remission for almost two years now. The rationale for such therapies is reviewed and analysed, and weighting is assessed for the individual therapies. We propose that such an integrative combination of standard/non standard, research based therapies may provide a blueprint for survival in pancreatic cancer that deserves formal clinical trials. &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&

An estimated 20,000 angiosperm species conceal pollen inside tubular poricidal anthers or within modified petals. A bee releases pollen by vibrating its thorax and transferring the force through its mandibles while biting the flower. While the floral morphology of buzz-pollinated plants is diverse, the behaviors, dimensions and guilds of buzzing bees are limited. Floral modifications should reflect the relative sizes of their co-adapted pollinator species but we do not know what drives these size associations. We show that the optimal excitation point in the vibration system of bumblebee-pollinated louseworts (Pedicularis) occurs precisely where bumblebees bite these flowers. This leads to trait matching between a bumblebee’s individual body length and the beak length of the flowers of each lousewort species. As bumblebees do not visit flowers with beaks (galea) longer than their bodies it guarantees they bite the optimal excitation point for pollen discharge.

A document by Katherine Whitehouse. Click on the document to view its contents.

Mycobacterium abscessus (Mab) is highly drug resistant, and understanding regulation of antibiotic resistance is critical to future antibiotic development. Regulatory mechanisms controlling Mab’s β-lactamase (Bla Mab) that mediates β-lactam resistance remain unknown. S. aureus encodes a prototypical protease-mediated two-component system BlaRI regulating the β-lactamase BlaZ. BlaR binds extracellular β-lactams, activating an intracellular peptidase domain which cleaves BlaI to derepress blaZ. Mtb encodes homologs of BlaRI, that regulate the Mtb β-lactamase, blaC, but also additional genes related to respiration. We identified orthologs of blaRIMtb in Mab and hypothesized that they regulate blaMab. Surprisingly, neither deletion of blaRIMab nor overexpression of only blaIMab altered blaMab expression or β-lactam susceptibility. However, BlaI Mab did bind to conserved motifs upstream of several Mab genes involved in respiration, yielding a putative regulon that partially overlapped with BlaI Mtb. Prompted by evidence that respiration inhibitors including clofazimine (CFZ) induce the BlaI regulon in Mtb, we found that CFZ triggers induction of blaIRMab and its downstream regulon. Highlighting an important role for BlaRI Mab in adapting to disruptions in energy metabolism, constitutive repression of the BlaI Mab regulon rendered Mab highly susceptible to CFZ. In addition to our unexpected findings that BlaIR Mab does not regulate β-lactam resistance, this study highlights the novel role for mycobacterial BlaRI-type regulators in regulating electron transport and respiration.

Background: Behavioural and psychological symptoms of dementia (BPSD) are highly distressing manifestations that are frequently experienced in patients with vascular dementia (VaD). BPSD are difficult to manage, associated with poorer patient outcomes, and have a profound impact on caregivers. Glutamatergic neurotoxicity has been suggested to contribute to the pathogenesis of BPSD. Memantine is a moderate-affinity, uncompetitive glutamate N-methyl-D-aspartate receptor antagonist, which has been shown to have neuroprotective properties. At present, memantine is not licensed for treatment of BPSD in VaD. Objectives: Systematically analyse the data on memantine to assess its clinical efficacy and safety in the treatment of BPSD in VaD. Results: Two RCTs, comprising of 460 patients treated with memantine and 441 patients treated with placebo that met the criteria for probable VaD, were included. Memantine showed improvements in the Alzheimer’s Disease Assessment Scale, cognitive subscale (ADAS-Cog), Gottfries-Brane-Steen (GBS) Scale, Nurses’ Observation Scale for Geriatric Patients (NOSGER), Mini-Mental State Examination (MMSE), Clinical Global Impression of Change (CGIC) and adverse events, although not all findings were statistically significant. Conclusion: Memantine appeared to be beneficial in improving BPSD in VaD patients and demonstrated a good safety profile. There is currently limited literature available to support its use in clinical practice. Therefore, further studies comprising of larger sample sizes and patients with different VaD severities are required to gain better understanding of the efficacy of memantine in VaD.

Abstract Background The Dokdo sea lion (Zalophus japonicus), commonly referred to as Ganchi in Korea and also known as the Japanese sea lion, was endemic to the Northwest Pacific coast before becoming extinct in the 1950s. Little is known about its origins, speciation compared to other Otariidae species or how the rapid decline affected the species’ genetic diversity. Results To raise the Dokdo sea lion from this relative obscurity, we sequenced DNA from 16 Z. japonicus’ bone fragments, obtained from Dokdo and Ulleungdo islands in Korea. Our analysis establishes Z. japonicus as the earliest diverged species within its genus, significantly redefining its evolutionary relationship with the California (Z. californianus) and Galapagos (Z. wollebaeki) sea lions. This genome-scale analysis clarifies the phylogeny of Z. japonicus, shedding light on its speciation and the evolutionary pathways that shaped its genetic diversity before its extinction. In addition, we discovered, population decline of the Z. japonicus started already 1,000 years ago, however, Z. japonicus genome maintained a relatively high heterozygosity despite, nearing extinction. Conclusions Our genome-scale analysis eliminated ambiguity in Z. japonicus phylogeny, and shed light on the evolutionary pathways underlying its speciation. This study highlights the importance of the genome-scale analysis for extinct species to understand their complex evolutionary histories and conservation status.

Background and purpose: In this study, we applied an induced pluripotent stem cell (iPSC)-based model of inherited erythromelalgia (IEM) to screen a library of 295 small molecules aiming to identify candidate pain-modulating compounds. Experimental approach: Human iPSC-derived nociceptor-like cells, which exhibit action potentials in response to noxious stimulation, were evaluated using whole-cell patch-clamp and microelectrode array (MEA) techniques. Key results: Nociceptors derived from individuals with IEM showed spontaneous electrical activity characteristic of genetic pain disorders. The drug screen identified four compounds (AZ106, AZ129, AZ037, and AZ237) that significantly decreased spontaneous firing with minimal toxicity. The calculated IC50 values indicate the potential efficacy of these compounds. Electrophysiological analysis confirmed the compounds’ ability to reduce action potential generation in IEM patient-specific iPSC-derived neurons. Conclusions and implications: This high-throughput approach demonstrates the reproducibility and effectiveness of human neuronal disease modelling, offering a promising avenue for discovering new analgesics. These findings address a critical gap in current therapeutic strategies for both general and neuropathic pain, warranting further investigation. This study highlights the innovative use of patient-derived iPSC neuronal models in pain research and emphasises the potential for personalised medicine in developing targeted analgesics.

Interaction with pollinators has been proposed as one of the most important factors shaping the diversity of flowering plants. Spatial variation in the directions of the selective pressure exerted by pollinators drives the evolution of adaptive differentiation. Thus, across-population studies of flower traits and plant-pollinator interaction are therefore an important step to understanding the diverse selective pressures that drive floral evolution in zoogamous angiosperms. In this study, we combine observational data and field experiments to describe the assemblages of pollinators, breeding systems, and reward properties in studied populations of the Middle East geophyte, Fritillaria persica. Natural populations of this species include two floral color morphs with greenish or purple flowers, in both morphs the nectaries of the outer whorl are covered by the tepals of the inner one. Our study documented geographical variation in the pollination system of two color morphs of F. persica. Visitors recorded in both populations were similar qualitatively, however, their contribution varied. Nectar sugar concentration and profile were generally constant in studied populations, we recorded differences only in nectar volume and concentration of amino acids. These results suggest that the observed variation in nectar production is likely to be a result of environmental factors, rather than pollinator-mediated selection. In the context of reward, we also tested how uncovering the hidden nectar reward from outer tepals influences potential pollinators. Uncovering hidden reward did not change the time spent in one flower or inflorescence penetration, however, it increased the number of seeds produced. The similarity of nectar properties and pollinator assemblages suggests that in the context of pollination, F. persica represents a rather generalistic strategy, and observed differences may be caused by abiotic factors.

The evolution of the phenotype has historically been studied by segregating it into categories, as traits within a category often exhibit close associations. However, individuals can be considered as integrated phenotypes, suggesting that their analysis may not correspond to an artificial categorization. Nonetheless, variations in the intensity or persistence of selective pressures over time can lead to mismatches in phenotypic evolution. Despite the potential for selective pressures to induce phenotypic changes, closely related species tend to exhibit similarities due to their common ancestry. In this study, we calculated and compared the phylogenetic signal of phenotypic traits of lizard species in the genus Sceloporus. We categorized these traits as either morphological or life-history traits, with a total of eight traits in each category. These traits include trunk length, limb length, head length, clutch size, hatchling length, age at first brood, and size at maturity. We found that the amount of phylogenetic signal varies across Sceloporus traits. The intensity of the phylogenetic signal was higher in traits derived from morphometric measurements, regardless of their category. The remaining traits exhibited notable variation, ranging from phylogenetically conserved traits such as reproductive mode to the absence of phylogenetic signal, as seen in relative clutch mass. Furthermore, we observed that traits possibly influenced by the same evolutionary mechanism exhibit similar amount of phylogenetic signal, regardless of category. Finally, we discuss the potential implications of phylogenetic signal in the evolution of Sceloporus phenotypes.

A document by Professor Barbara Gołębiewska. Click on the document to view its contents.

There is an urgent need for woodland expansion to help mitigate climate change and biodiversity loss. However, the process of natural regeneration of forest ecosystems is often slow, requiring active reforestation approaches. Factors limiting regeneration are complex, but there is increasing evidence that natural expansion of woodlands onto sites that have been treeless for a long period of time may be limited by the loss of microbial woodland-soil properties. This study explored the potential role of mycorrhizal associations in facilitating obligate ectomycorrhizal (ECM) tree establishment. We determined the spatial distribution patterns of ECM tree seedlings – Pinus sylvestris and Betula spp. - outwith the existing woodlands, in relation to established dual-mycorrhizal Salix. There was very strong evidence that ECM tree seedlings were more likely to be found growing within groups around dual-mycorrhizal Salix than as isolated individuals, supporting the view that Salix drives the current spatial distribution patterns by supporting tree establishment. We suggest that the ability of Salix to form dual-mycorrhizal associations with both arbuscular (AM) and ECM fungi allows these plants to become established across the open AM dominated vegetation. Over time these plants can become colonised by ECM fungi via aerial spores and then act as a source of inoculum for obligate ECM tree seedlings, which land as seeds in the vicinity of Salix. This study highlights the potential role of dual-mycorrhizal Salix as a nurse plant in supporting secondary forest succession of obligate ECM boreal/temperate woodland species onto adjacent open areas through nucleation. Overall, we concluded that there is potential for existing ECM networks to aid tree establishment and propose a nature-based approach to maximize reforestation efforts by targeting existing symbiotic fungal networks as nucleation points for tree planting. Our findings contribute to understanding the ecological dynamics involved in woodland expansion and restoration.

There exist different modeling techniques and advanced tools based on these modeling techniques for modeling and simulation of complex engineering systems. The tools provide flexible, user-friendly environment to researchers and help them in design optimization and performance analysis. The basic aim of this research is to identify optimized modeling methodology and tools for the modeling and simulation of biomechatronic system i.e., lower limb rehabilitation exoskeleton (LLRE). For this purpose, firstly the LLRE is modeled using three different modeling approaches. These include conventional/ mathematical modeling, modeling through bond graph technique and modeling using Simscape TM. Modeling through the first two approaches is analytical and graphical respectively while Simscape deals with physical signals while modeling and results in model that is much closer to physical hardware. Secondly, a comparative analysis has been carried out in which dynamic responses of models from different modeling methods have been compared upon certain parameters. This comparison resulted in dynamic responses verification and model validation. Along with that the comparison of different approaches has been carried out and the optimized approach for modeling of bio-mechatronics system such as LLRE is identified. Modeling through Simscape has been identified as optimized approach for modeling of LLRE. This contribution in the field of biomechatronics system control will provide the researchers with an insight about the modeling. This will further pave the way for better model based robust control design. Future work includes comparison of actual hardware dynamic responses with optimized modeling approach.