In financial systems, ensuring their security and integrity in an increasingly digitalized environment is very crucial. Blockchain technology, because of its decentralized, immutable, and transparent nature, presents a revolutionary approach to cybersecurity audits in financial systems. This paper discusses the role of blockchain in enhancing trust and transparency in cybersecurity audits. With distributed ledger technology, blockchain ensures tamper-proof audit trails, real-time monitoring, and automated compliance through smart contracts. Such features will help enhance the detection and mitigation of vulnerabilities, accountability, and the strength of stakeholder confidence. In addition, integrating blockchain with advanced analytics and AI can further optimize audit processes with predictive insights to improve the resilience of financial infrastructures. This study analyzes use cases, challenges, and the transformative potential of blockchain-driven cybersecurity audits in securing financial systems. To achieve the maximum usage of blockchain's potential and handle its shortcomings, recommendations are offered on regulatory alignment, scalability, and adoption strategies. The future of financial ecosystems will thus be protected through blockchain with the advent of trust and transparency.

Advances in digital technology and the rise of cyber threats have created an increasingly complex cybersecurity environment. Using more cloud services and connected devices has allowed enterprises to increase the attack surface, growing systems' susceptibility to hacking. The current study aims to investigate artificial intelligence-driven (AI) cyberattacks targeting devices studying enemies. Reviewing adversary machine learning insights reveals critical weaknesses in AI design and the vulnerability of adversary attacks to affect images, leading to misclassification and security threats. Case studies like the Microsoft Tay chatbot tragedy and the Tesla Model S attack proved these vulnerabilities-Apart from how world applications undermine public security and trust in AI systems, the implications for society and the economy happened as emphasis needs to be placed on addressing ethical issues such as bias and privacy when implementing AI in cybersecurity. The study suggests that organizations should adopt adversarial training to increase the robustness of the machine learning model against adversary attacks. Similarly, moral explanation requires multiple approaches. International companies must understand cybersecurity legislation, including EU and UK legislation, to develop effective breach response strategies. The study recommends that organizations adopt a multifaceted approach to enhance defences against adversarial attacks, including updating models with adversarial examples, regularization, developing anomaly detection systems, and addressing bias and privacy concerns.

not-yet-known not-yet-known not-yet-known unknown Spatiotemporal environmental heterogeneity is a major evolutionary driver, which can cause profound phylogeographic complexity, particularly at the periphery of species ranges. Ringed seals display a highly disjoint distribution with an abundant subspecies occurring throughout the circumpolar Arctic, as well as three relict subspecies in Fennoscandia; the Baltic Sea, Lake Saimaa and Lake Ladoga. Traditionally regarded as originating from a single colonisation event from the paleo-Skagerrak-Kattegat region after the Last Glacial Maximum (LGM), recent studies have challenged this perception. Here, we analyse 246 mitogenomes and 180 skulls to unravel the diversity and spatiotemporal pattern of diversification in Fennoscandian ringed seals. Contrary to previous assumptions, our results reveal a complex evolutionary history characterised by several Fennoscandian colonisation events and pre-LGM diversification from Arctic ringed seals. We hypothesis that Lake Saimaa seals originate directly from the Arctic, possibly via the Karelia seaway, Ladoga via a similar route as well as from paleo-Skagerrak-Kattegat-Baltic, while the Baltic ringed seal have mixed evolutionary origins, which may be traced to distinct European glacial refugia, as well as ongoing gene-flow with the Arctic. Lake Saimaa and to some extent Lake Ladoga ringed seals have experienced a loss of diversity and evolved divergent skull morphologies as a result of colonisation bottlenecks, isolation and dietary specialisation, while Baltic Sea ringed seals have retained remarkably high levels of diversity. Our study supports the current classification of Lake Saimaa, Lake Ladoga and Baltic Sea ringed seals as distinct subspecies, and highlights the need for management and conservation efforts to mitigate cumulative impacts of human activities and climate change on Fennoscandian ringed seals.

Methicillin-resistant Staphylococcus aureus (MRSA) is a major global challenge due to its resistance to β-lactam antibiotics. This resistance stems from the mecA gene, which encodes penicillin-binding protein 2a (PBP2a). PBP2a enables bacterial survival by catalyzing peptidoglycan synthesis while exhibiting low affinity for β-lactams. Its active site is shielded by protective loops, adopting a closed conformation that limits drug access. These structural changes are regulated by an allosteric site distant from the active site. Given the urgent need for new therapeutic strategies, this review focuses on PBP2a’s conformational dynamics and allosteric regulation in β-lactam resistance. Additionally, it explores ligand interactions that influence PBP2a inhibition and their potential in restoring antibiotic efficacy. Understanding these mechanisms will aid the design of adjuvants targeting the allosteric site, offering a promising strategy to enhance β-lactam effectiveness against MRSA.

not-yet-known not-yet-known not-yet-known unknown Background and purpose: Idiopathic pulmonary fibrosis (IPF), evokes scarring of the lung due to extracellular matrix deposition by fibroblasts. Evidence suggests that inhaled treprostinil slows the decline in pulmonary function in IPF. The molecular mechanisms by which cAMP mobilizing agents, alter human lung fibroblast (HLF) expression of matrix proteins remain unclear. We posit that the antifibrotic properties of treprostinil are driven by differential cAMP mobilizing responses mediated by the IP receptor. Experimental approach: As a model of lung fibrosis, TGF-β-stimulated primary HLF were used to measure collagen 1A1, PAI1, and growth factor levels in the presence and absence of cAMP mobilizing agents. The necessity of receptor activation in inhibiting TGF-β-induced fibrosis was determined using soluble receptor inhibitors and selective inhibition of receptor expression with siRNA. Key results: Treprostinil decreased TGF-β-induced extracellular matrix and growth factors production by HLF, the magnitude of the inhibition was greater than other cAMP mobilizing GPCR agonists despite comparable increases in cAMP levels. Treprostinil inhibition of TGF-β-induced collagen 1A1, PAI-1, and IGFBP3 was mediated through the activation of the IP receptor. The EP2 receptor was partially involved in the inhibition of TGF-β-induced collagen 1A1 by treprostinil or prostaglandin E2. β2 agonists had little effect on TGF-β-induced collagen 1A1, PAI-1, and IGFBP3 expression. The inhibitory effects on TGF-β-induced matrix expression by treprostinil required Gαs activation. Treprostinil inhibition of TGF-β-induced IGFBP3 expression also correlated with the inhibition of TGF-β-induced phosphorylation of AKT. Conclusion and implications: Understanding the differential effects of cAMP mobilizing pathways on HLF fibrotic signatures can provide insight into developing novel targets to manage IPF.

The nociceptin/orphanin FQ (N/OFQ)-Nociceptin Opioid Peptide (NOP) receptor system, is a relatively new discovery in the context of the human opioid system. The NOP receptor although like the classical Mu Opioid Receptor (MOP), in its intracellular signaling pathways, exhibits starkly distinct effects on pain modulation. Preclinical rodent studies with NOP receptor agonists revealed significant findings on the effect of N/OFQ in pain modulation. The effects were influenced by a variety of factors such as dosage, site of administration, and pain modality. Conversely, studies performed on primates indicated consistent potent analgesic effects, notably lacking typical opioid side effects like respiratory depression and dependence. Furthermore, bifunctional NOP/MOP agonists have shown potential as viable alternatives to traditional opioids due to their improved safety profiles. These dual-action compounds demonstrate strong analgesic effects while mitigating dose-limiting adverse reactions typically associated with MOP receptor activation. This review highlights the physiological role of the nociceptin system and provides a comprehensive overview of recent advancements in the development of selective NOP agonists and bifunctional NOP/MOP agonists, such as AT-121, BU08028, BU10038, Cebranopadol, which have demonstrated promise in preclinical studies. We also discuss future trends in nociceptin agonist research, emphasizing their potential to serve as novel, effective analgesics with a superior safety profile compared to traditional opioids.

During the Middle Miocene Climate Transition (MMCT; ~14.7–13.8 Ma), the global climate experienced rapid cooling, leading to modern-like temperatures, precipitation patterns, and permanent ice sheets. However, proxy records indicate that atmospheric pCO2 and regional climate conditions (SST, ice volume) were highly variable from 17 to 12.5 Ma and these changes were not always synchronous. Here, we report on a series of middle Miocene simulations using the water isotope enabled earth system model (iCESM1.2) to explore the potential for multiple equilibrium states to explain the observed decoupling between pCO2 and regional climates. Our simulations indicate that initial ocean conditions can significantly influence deep water formation in the North Atlantic and lead to multiple ocean equilibria. When the model is initiated from a cold state, residual cool surface water temperatures in the North Atlantic intensify Atlantic Meridional Ocean Circulation (AMOC) and inhibit Arctic sea-ice formation. When initiated from a warm state, the AMOC remains weak. The different ocean states drive differences in equator-to-pole sea surface temperature gradients and sea ice distributions through heat redistribution changes. These equilibria cause variations in temperature gradients and sea ice distribution due to changes in heat redistribution. Additionally, changes in ocean circulation and a reduced temperature gradient in the North Atlantic increase North Atlantic precipitation when the AMOC is strong. These findings underscore the importance of the ocean’s initial state in shaping regional climate responses to atmospheric pCO2, potentially explaining regional climate pattern variability observed during the Miocene.

A document by Grahith Pai Baidebettu. Click on the document to view its contents.

1. INTRODUCTIONAs the number of patients who prefer to avoid the unaesthetic appearance of conventional orthodontic appliances continues to grow, so does the popularity of lingual fixed appliances.[1]With more examples of successful treatment being seen, dental practitioners will be more apt to refer patients to orthodontists proficient in this technique. However, patients wearing lingual appliances experience more pain, speech difficulties, and problems maintaining adequate oral hygiene[2], which may cause them to lose their patience in the technique. Moreover, lingual orthodontic treatment is a field that not all orthodontists can excel at. As a result, iatrogenic treatment outcomes are sometimes observed.Iatrogenic is described as a situation that leads to reversible or irreversible damage to patients who undergo any type of treatment. Iatrogenic usually occurs due to inaccurate growth prediction, incorrect choice of orthodontic appliances, technical failure by the dentist, poor patient cooperation, or lack of control of space and anchorage.[3] This is recognized in orthodontic publications mainly in terms of failures in patient compliance that result in poor treatment, no improvement, or damage. For this case, the patient has been wearing lingual brackets for 1,5 years with minimal improvement. We need to find an alternative solution that maintains a similar focus on aesthetics.Clear aligner in-house is an alternative approach to lingual orthodontics in cases where patients have high aesthetic demands. Indeed, the most obvious advantage of in-house aligner (IHA) is that it provides a more comfortable feeling than lingual orthodontics and does not cause tongue damage and tooth decay due to difficulty in oral hygiene. Moreover, there was no difference in the treatment duration with in-house aligners and fixed appliances.[4]This case report presents an approach using IHA to close space, correct midlines and canine relationships after treatment with lingual bracket therapy with minimal improvement in 1,5 years. The reasons for discontinuing lingual brackets treatment in this case include the poor quality of the previous lingual fixed appliance therapy, difficulty maintaining oral hygiene and discomfort, which led to the patient’s exhaustion with the treatment.

Subterranean environments, characterized by features such as relative stability, are widely regarded as valuable natural laboratories for studying ecological and evolutionary processes. This stability is often assumed to shape biodiversity dynamics and community structure over time. Accordingly, it is expected that faunal composition, along with the influence of substrate on invertebrate communities, remains consistent. To test this assumption, we applied a standardized methodology to assess potential changes in subterranean communities across seven limestone caves. Two sampling events, conducted five years apart, were used to evaluate whether these communities are influenced by habitat structure and how their responses evolve over time. Our analysis focused on detecting temporal shifts in community dynamics by comparing two constructed models and examining variations in faunal composition. While invertebrate richness remained stable, we observed significant changes in faunal composition, high temporal beta diversity, and distinct community responses to substrate structure. These results suggest that subterranean environments possess ecological carrying capacity, maintaining richness while exhibiting shifts in community composition. Moreover, the cave substrate is continually remodeled, influencing community responses in distinct ways. In conclusion, this study highlights the non-stationary nature of subterranean ecosystems and emphasizes the importance of utilizing multiple biodiversity metrics to enhance scientific understanding and inform effective management strategies. Investigating temporal dynamics is essential for identifying ecological processes and evaluating their impacts on ecosystem functionality.

Huntington’s disease (HD) was initially described in 1872 by George Huntington (an American physician). HD is a progressive neurodegenerative disease characterized by chorea, cognitive, psychiatric and motor impairments with extreme phenotypes that include irregular circadian rhythm, weight reduction and muscle atrophy. The global distribution of this progressive neurodegenerative disease is reported to be 2.71 in 100,000 individuals. Since HD manifestations become apparent in mid or later stages of life, the individuals in their mid-life who are unaffected carriers of HD gene mutations could have passed on to their offsprings resulting in the existence of substantial population of young mutant huntington (Htt) carriers who are currently asymptomatic and undiagnosed for HD. Notably, aggregation of intracellular mutant Htt with neurotoxic outcomes is stated to be a significant hallmark of HD. Considering its genetic predictability, HD could be one of the most perceptive neurodegenerative diseases to early intervention. This makes HD as a potent model system to develop therapeutic interventions for other similar neurodegenerative diseases. Taken together, this comprehensive review is intended to cover all aspects of this fatal and dynamic autosomal dominant neurodegenerative disorder including pathogenesis, inter-correlation of various molecular signaling pathways involved in HD progression, preclinical HD animal models, various therapeutic interventions and HD associated diagnostic biomarkers.

The article discusses the critical accumulation of huge economic, engineering and social problems in the US and their connection with the extreme polarization of political struggle. These long-standing US problems, taken and considered TOGETHER, look like a diagnosis of a serious disease. The author discusses issues such as (in comparison with other high-income countries): poorly guarded border, transparent to illegal immigrants and drugs; a huge number of drug-addicted youth and extremely high mortality rates from drug overdoses; ultra-expensive services: medical, university, housing, others; poor maternal and child health care and high infant mortality; too many poor families for such a rich country; poor quality school education; poor filled state budget and large national debt; huge trade deficit; moving thousands of manufacturing facilities and millions of jobs overseas (as a result of misunderstood ideas of ”free trade”); dilapidated infrastructure and poor protection from natural disasters; the political competition between the two main political parties in America has escalated into a dead-end political confront. All these problems have led America to a decline in living standards within the country as well as a partial loss of authority and leadership in the world.

Across multiple studies using diverse samples, we analyze attitudes toward increasing representation of minoritized groups in political spaces. When individuals understand how structural biases impact their own group, they are more likely to recognize the broader influence of these biases on other groups and support systemic change (e.g., Craig et al., 2020). Building on previous research, we examine the role of racial resentment and perceptions of structural bias in maintaining inequality and test how these perceptions predict support for increased political representation by individuals from underrepresented groups (e.g., women, LGBTQ+ groups, immigrants). Results show that feelings of racial resentment predict more negative attitudes toward increased diversity in representation, while beliefs about structural bias predict more positive attitudes, even after accounting for established ideological and identity factors. Our findings suggest efforts to foster support for diversity might be better served by increasing awareness of structural inequalities than appealing to shared identity.

Omani Jabal Akhdar goats are highly valued for their resilience, superior growth rate and twinning rate compared to other Omani goats. Therefore, understanding their genetic diversity and population structure is imperative for sustainable breeding efforts and conservation of the breed. This study aimed to assess the genetic diversity and population structure of Jabal Akhdar goats by genome-wide nucleotide polymorphisms (SNPs) using the Illumina 50K Goat Chip. Multidimensional Scaling Analysis (MDS) and Admixture analysis revealed that Jabal Akhdar goats has a distinct genetic ancestry that is a mixture between the Asian and African goat lineages which highlights the historic maritime trading and activities of the Omanis with both continents. The MDS analysis and the Reynolds unweighted distances both showed that the Jabal Akhdar goats share a close genetic ancestry with West Asian breeds such as Iranian Bezoar, the Australian Cashmere breed, and Turkish goats such as the Kil breed, all of which are adapted to cold climates and high elevations. Notably, the breed exhibited a reasonable inbreeding level (0.219), comparable to other West Asian breeds, indicating adequate levels of genetic diversity. This study represents the first genome-side characterization of the Jabal Akhdar goats breed. Despite its moderate inbreeding levels, attention should be focused on conservation efforts to safeguard the distinctive genetic diversity of Jabal Akhdar goats to prevent the erosion of its genetic diversity or admixture with exotic commercial breeds.

not-yet-known not-yet-known not-yet-known unknown This article aims to explore the application path and effectiveness of artificial intelligence (AI) technology in blended learning of horse veterinary courses. With the rapid development of AI technology, its application in the field of education is becoming increasingly widespread, bringing innovative opportunities for traditional teaching models. In response to the challenges of limited teaching resources and difficult practical operations in horse veterinary courses, this article proposes a hybrid teaching strategy empowered by AI. This strategy aims to enhance the teaching effectiveness and students’ learning experience of the horse veterinary course by integrating and optimizing teaching resources, constructing a blended online and offline teaching mode, developing intelligent teaching assistance systems, implementing virtual simulation experimental teaching, and optimizing teaching evaluation and feedback mechanisms.Through the evaluation and analysis of the implementation effect, this paper verifies the feasibility and effectiveness of AI technology in the mixed learning of horse veterinary courses, and provides new ideas and methods for the future development of horse veterinary education.

Fish passes, traditionally designed to facilitate upstream migration, are now increasingly recognized for their potential to support bidirectional fish movement and to improve habitat availability for potamodromous fish. This four-year study at the Ottensheim-Wilhering Hydro Power Plant on the Austrian Danube tracked the migration patterns of the common nase ( Chondrostoma nasus) using five PIT tag antenna arrays installed in a 14 km long, near-natural bypass system, which integrates two natural tributaries. A total of 190 nase were tagged and released in the Danube upstream the hydro power plant, and fish movement data were collected from November 2020 to June 2024. A large percentage of the tagged individuals entered the fish pass from upstream. Over the years, many individuals utilized the bypass system for extended periods and were observed repeatedly visiting the fish pass, highlighting its role not just as a migration corridor but also as a spawning and feeding habitat. These findings underscore the multifunctionality of near-natural fish passes, which not only restore longitudinal connectivity but also provide critical habitats for various life stages of rheophilic fish. The study challenges the assumption that fish passes are ineffective for downstream migration and suggests that such systems can play a significant role in supporting potamodromous fish populations in highly regulated rivers like the Austrian Danube.

Epilepsy is a neurological disorder that affects millions globally, with diagnosis often relying on electroencephalogram (EEG) analysis. However, age-specific differences in EEG patterns pose a significant challenge, particularly for teenagers. Current diagnostic tools, primarily designed for adults, fail to account for the unique neurophysiological characteristics of adolescents, leading to false-positive rates as high as 50%. This study compares EEG features between teenage and adult epileptic patients to identify key differences and address this diagnostic gap. Using feature extraction techniques, including kurtosis, skewness, and frequency-domain analysis, we observe sharper peaks and higher variability in teenage EEGs, while adult EEGs exhibit more stable patterns. These findings highlight the critical need for age-specific diagnostic tools to reduce misdiagnoses and improve epilepsy treatment outcomes. Bridging this gap, the research aims to pave the way for more accurate and personalised healthcare solutions for younger patients.

The effects of 400 Hz anodal and cathodal transcranial pulsed current stimulation of the primary motor cortex (400 Hz a-tPCS M1, 400 Hz c-tPCS M1) on corticospinal excitability (CSE) and corticocortical excitability (CCE) remain underexplored. This study examined the effects of 400 Hz a-tPCS M1, 400 Hz c-tPCS M1, and sham stimulation on CSE, CCE, and hand dexterity, providing insights for potential clinical applications in motor deficits. In this double-blinded, randomized, counterbalanced crossover trial, 26 healthy young adults completed three experimental sessions: 400 Hz a-tPCS M1, 400 Hz c-tPCS M1, and sham stimulation, spaced 48 hours apart. Transcranial magnetic stimulation assessed CSE and CCE, while the Purdue Pegboard Test (PPT) evaluated hand dexterity. The results showed polarity-specific effects. A single session of 400 Hz a-tPCS M1 significantly increased CSE and improved hand dexterity, evidenced by faster PPT completion times (p < 0.05). Conversely, 400 Hz c-tPCS M1 reduced CSE but did not influence PPT performance (p > 0.05). Sham stimulation showed no significant changes. These findings suggest that 400 Hz a-tPCS M1 enhances motor excitability and dexterity, while 400 Hz c-tPCS M1 selectively reduces CSE. This study lays a foundation for exploring high-frequency tPCS in clinical motor rehabilitation.

This paper introduces a unique implementation of Whisper by OpenAI, intended primarily for Telco applications. Whisper, initially released with support for 98 languages [6], represents a significant stepping stone in the world of Natural Language Processing. In this paper, we outline a hybrid model approach that enables a more diverse and cost-effective adaptation of the model for industrial deployment. We evaluate the C++ version against Whisper's original Python model, demonstrating comparable accuracy with a significantly reduced computational footprint. Our results show that the hybrid Whisper-Transformer model achieves effective real-time transcription while maintaining contextual accuracy, representing a scalable, cost-effective ASR solution for industrial applications.

Global change is altering ecosystems in ways that threaten the critical functions on which biodiversity depends. Despite this, we know very little about how drivers of global change broadly affect food webs. While an industry of studies documents shifts in whole carbon pathways within food webs in response to anthropogenic pressures, a comprehensive synthesis is lacking. To address this, we provide empirical examples across diverse ecosystems and conduct a systematic literature review to reveal the prevalence of asymmetric rewiring -- a phenomenon whereby drivers of global change consistently but disproportionally alter the flow of some carbon pathways relative to others. Further, using food web models, we show how asymmetric rewiring erodes resilience and disrupts key functions, such as primary and secondary production. Global change is complex and multidimensional, making it challenging to understand how human activities affect ecosystem processes. Our work critically synthesizes empirical evidence to uncover a remarkably general response in food webs to global environmental change that needs to be better understood to protect nature and the services that human societies rely on in a rapidly changing world.

In the realm of software development, ensuring the security of a product is of paramount importance. Beyond software components, product security encompasses hardware, firmware, and other elements, including designing and implementing security measures that protect the product holistically, considering physical security, supply chain security, and operational security. However, with the increasing prev alence of cyber threats, organizations face numerous challenges in safeguarding their software products. Many organizations consider security a bottleneck, as insecure software puts the business at risk. To address this lack, we have conducted an empirical study to investigate the challenges and practices of product security in the context of the software development process. Our semi-structured interviews with 22 practitioners across various industries emphasized the relevance of product security practices within this domain. However, the findings also uncovered new challenges that hinder the integration of these practices. The insights derived from this research capture practitioners' perspectives on product security, enabling organizations to address security concerns proactively and devise effective strategies to protect their software products during the development process.

This paper presents the output state feedback approach, a unique adaptive control mechanism for power system dynamic stability. A new adaptive stabilizing method for synchronous power systems based on Minimal Control Synthesis (MCS) is proposed. Industrial applications can benefit from synchronous power systems. It boosts production and power efficiency. The MCS adaptive control structure uses hyper-stability theory. Power System Stabilizers (PSSs) have been used in industry for years to improve power system dynamic stability and dampening. most power systems are very dynamic and non-linear. Traditional PSS uses linearized power system model and fixed parameter linear control theory. Fixed parameter controllers can’t sustain power system dynamic stability. The MCS method’s key virtue is that it requires only a minimal framework and little computational resources. The controller manages plant nonlinearities, mild disturbances, and parameter changes using proportional and integral type adaptation to meet hyper-stability criteria. Stabilizing signals are created at the machine system’s excitation input for well-defined closed-loop performance. Synthesizing an output feedback control from observed feedback signals is desirable and technically achievable. The proposed control structure overcomes the difficulties of generating an online parameter estimator and choosing a reference model compared to MRAC or STAC. The investigated power system has an endless bus connected to a synchronous machine. Simulations verify the controller’s ability to moderate machine oscillations caused by minor power system disturbances. The results and MATLAB/Simulink operational simulation results end this research. The mode damping ratio is 0.0142, which is within the predicted range of 0.1 to 0.5.

This study presents an innovative framework that integrates artificial intelligence (AI) into automotive product life cycle management (PLM) and Stage Gate decisions within the Product Development Process (PDP). Our goal is to revolutionize the automotive industry by enhancing the efficiency and effectiveness of PLM through the application of AI technologies. We identify the unique challenges faced in automotive PLM, such as complex supply chains, rapidly changing customer demands, and the need for cross-functional collaboration. Additionally, we detail how our specialized AI framework addresses these challenges by providing solutions that improve manufacturing, maintenance, product design, testing, and quality control processes. Our findings demonstrate that AI-driven solutions can significantly optimize various stages of the product life cycle, leading to streamlined development processes. The study also outlines actionable recommendations derived from our research to refine the AI framework, along with suggested avenues for future research. This groundbreaking approach has the potential to transform PLM practices in the automotive sector, enabling companies to better respond to evolving market demands, and ultimately enhancing overall industry performance. By embracing Artificial Intelligence and Deep Learning Models, companies can position themselves for greater success in a competitive landscape.

Widely distributed (WD) species are known to exhibit phenotypic variations across their distributional range. However, there is no consensus regarding the underlying factors that contribute to this variation. Here we explore whether factors such as geological events, dispersal constraints, and hybridization events govern the genetic diversity within a WD species. We studied the widespread ginger lily Hedychium spicatum, found in the understory of the Asian tropical montane forests and is morphologically variable across its geographical range. Using single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs) we investigated the genetic structure of H. spicatum using model-based and model-free approaches. Our results show that H. spicatum is shaped by historical factors such as i) demographic fluctuations due to glaciation in the Himalayas, ii) dispersal constraints, and more recent factors such as iii) ploidy variations, and iv) hybridization events. We identified intermediates, hybrid species, and cryptic species across its distributional range, which are a result of multiple instances of gene flow between the widely distributed H. spicatum and at least four co-occurring, congeneric hedychiums. We show that the Western Ghats population is an example of long-distance migration from the Himalayas, which is undergoing progenitor-derivative speciation, confusing taxonomists to wrongly identify H. venustum as a new species, rather than an admixed variant of H. spicatum. In summary, the morphological, genetic, and taxonomic complexities within H. spicatum highlights the emergent-system-like characteristics in this WD species, and that WD species provide a glimpse of speciation on a spatial scale.