Heat-Induced Morphological Changes in Silver Nanowires: A review

Silver Nanowires (AgNWs) are gaining widespread attention for their remarkable electrical, optical, and mechanical properties, which make them ideal for a variety of cutting-edge applications such as flexible electronics, transparent conductive films, and sensors. However, their stability and performance when exposed to high temperatures are crucial for their practical use. This review sightsees into how heat affects the shape and structure of AgNWs, exploring the mechanisms behind these changes and what they mean for real-world applications. We cover topics like the melting behavior of tiny metallic wires, the role of surface atoms moving around, and how environmental factors can influence their stability. Additionally, we discuss how these heat-induced changes can impact the efficiency of devices that use AgNWs, like transparent heaters. By bringing together findings from recent research, this review aims to provide a clear understanding of how AgNWs behave under heat and offer insights into improving their design and use in high-temperature situations

Phytochemical Screening and In vitro Antibacterial Evaluation of Plectranthus amboinicus (Lour) Spreng

Plectranthus amboinicus is a medicinal plant widely recognized in Ethiopia but requires scientific validation to support its potential for drug development. This study aimed to evaluate the phytochemical properties and antibacterial activities of P. amboinicus crude extracts against selected pathogenic bacteria. The experiment followed a Completely Randomized Design (CRD) using a laboratory bioassay with three replications. The factorial arrangement included two extract sources (leaf and stem), two solvents (ethanol and distilled water), three concentration levels (100 mg/mL, 120 mg/mL and 150 mg/mL), four bacterial species and three replications, resulting in a 2x2x3x4x3 design. The disc diffusion method was employed to assess bacterial susceptibility, while the Minimum Inhibitory Concentration (MIC) was determined using the broth dilution method and the Minimum Bactericidal Concentration (MBC) was evaluated on nutrient agar. Gram positive bacterial species demonstrated the highest susceptibility, with MIC values ranging from 25 mg/mL to 100 mg/mL and MBC values between 50 mg/mL and 100 mg/mL. The study findings revealed that extracts from the leaves of P. amboinicus were particularly effective against the tested pathogens, highlighting the plant’s antibacterial potential. Furthermore, phytochemical screening confirmed the presence of secondary metabolites and bioactive compounds, supporting the use of P. amboinicus as a medicinal plant. These results provide a scientific basis for its traditional application in treating bacterial infections. However, further research is necessary to investigate its efficacy against a broader range of bacterial and fungal pathogens

Acoustic-Based Species Recognition in Frogs (Order Anura) via Hidden Markov Models (HMMs)

Biological indictors of ecosystem health often involve the investigation of various species of amphibians. Frogs (Order Anura) generate a variety of vocalizations (calls or croaks) to fend off predators and attract mates that can be automatically analyzed by utilizing machine learning methods on recordings from large repositories. Hidden Markov Models (HMMs) are widely-used classifiers that have been successfully applied in both human speech processing and bioacoustics to study vocalizations captured by recordings; however, there has been limited usage of HMMs in analyzing large-scale frog datasets, which highlights the need to evaluate their effectiveness for this application. The cepstral coefficients and time derivatives (feature extraction) were extracted from the 1459 vocalizations, and the HMMs were applied to model both the temporal and spectral variations of acoustically comparable vocalizations. Based on the experiments for automatic classification of 9 species of frogs using leave-one-out cross-validation, the classification accuracy ranged from 87.3886% (9 element feature vector, 1275/1459 correct classifications) to 100.0000% (39 element feature vector, 1459/1459 correct classifications). For future work, the HMMs could be applied to other species of frogs for automatic classification and detection of the vocalizations

The Role of Vertebral Artery Blood Flow Alteration as a Cause of Vertigo in Cervical Spondylosis: An Observational Study

Background: Vertigo is a symptom, not a disease in itself, and can be caused by a variety of underlying conditions with diverse origins, including inner ear, brainstem, cerebellum, and even internal, vestibular, or psychosomatic factors. Vertigo related to cervical spondylosis often presents with a distinct set of characteristics: it tends to be recurrent, brief in duration, triggered by changes in head position, and not typically accompanied by nystagmus (involuntary eye movements). These features can help differentiate it from vertigo caused by other conditions. Our study is first prospective study from Himalayan belt of North India, where we set out to examine whether vertebral artery compression, specifically during neck rotation, plays a role in the development of vertigo in patients diagnosed with cervical spondylosis.Result: Based on our study, we found that following variables were significantly (p<0.05) associated with variable “Vertigo in Spondylosis cases” : right VA diameter (mm) (right rotation position), change in right VA diameter (%)(right rotation position), right VA EDV (right and left rotation position), left VA diameter (mm) (right rotation position), left VA diameter (mm) (left rotation position), change in left VA diameter (%)(left rotationM position), left VA PSV (left rotation position), left VA EDV (right and left rotation position).Conclusion: Our observations suggest a vascular component to dizziness, experienced by patients with CS. In patients with CS and significant osteophyte formation, compression of VA becomes pronounced. Head rotation exacerbates this compression, resulting in vertigo due to Vertebro-Basilar Insufficiency (VBI)

Financial Stability and Financial Distortions: A Saddle Path Equilibrium between the Crowding Out Effect and the Financial Accelerator

Various methods of modeling based on stress testing and macrofinancial modeling have been adopted in the literature on financial stability assessment and all display merits as well as drawbacks. The literature on the subject matter of financial stability assessment is still in its infancy and requires novelties with respect to methodologies adopted in the assessment process. The eviction effect or the crowding out effect and the financial accelerator are two issues that are compromisingly involving for financial stability, economic policy making and the nexus between the macroeconomic imperfections and financial imbalances. As far as interactions between key determinants of financial stability are concerned, there is a longstanding dissensus on the impact of the crowding out effect on financial stability as it is an issue intertwined compromising public policy and financial matters whereby the crowding out effect is found to be acting like an actor partially offsetting and slowing down the negative effects of the financial accelerator on financial stability in what we call a saddle path unstable equilibrium following the tendency of the trend of the effect of the financial accelerator on financial stability temporarily then abruptly turning the tendency of the effect of the financial accelerator on financial stability sequentially to mitigate instability partially. This raises concerns about a novel method to assess financial stability and the likely merits of modeling financial stability taking into consideration these two items of commensurate relevance and importance to highlight two main economic effects namely the double dividend theory in presence of distortions and the close relationship of economic and financial matters in face of the hindrance of providing a clear insight into interactions and cross effects among determinants of financial stability. The main scope of going deeper into the intertwined relationship between the eviction effect and the financial accelerator is to better fathom financial stability while at the same time waiving the drawbacks of conventional methods of financial stability assessment that always impair features of commensurate relevance to herald specific concern about microfinancial considerations or macrofinancial considerations and in some instances prioritizing rare innovations or contrariwise neglecting them roughly. The proposed saddle path equilibrium modeling shows clearly the cross effects and interactions of relevant features composing financial stability assessment while at the same time including key microeconomic features relevant to systemic risk in a comprehensive way. The approach highlights indeed the role played by equity and credit in affecting financial stability. It provides impetus on the effect of government bonds and securities between the credit market and the stock market sectors that makes improvement in stock market sector trading of government securities or attract ability to banking placement or incur draining loanable funds through increase in stock market profitability and deteriorates credit market financial stability by the demand pull effect through the effect of liquidity risk on credit risk in the face of limited tolerance to overall risk incurred by banks and the search for yield motivation of banks. The effect on financial stability through the Stock market sector or what we call the saddle path unstable equilibrium between crowding out effect and the financial accelerator constitutes the cornerstone of our research and will be thoroughly analyzed and scrutinized throughout the mathematical proofs provided in the research referring to the polynomial distributions of risk, the gaussian pivot for multivariate discrete functions, the saddle path unstable equilibrium and the reference to sensitivity analyses and constitutes the novelty provided by this research in face of the drawbacks of available measurement methods displayed in the literature of relevance for the subject matter

Investigation into Online Banking and its Prevailing Fraud Factors: A Comprehensive Analysis

This study explores the investigation of security concerns surrounding online banking, the prevailing fraud factors that affect banks and customers and discusses effective measures towards preventing fraudulent activities using combination of authentication and verification methods. Employing a qualitative research approach, data was collected through online interviews during the pandemic lockdown and restrictions. Findings reveal that while online banking has transformed financial transactions by offering unprecedented convenience and efficiency, it has simultaneously exposed both banks and customers to significant fraud risks. The study discusses user perceptions of online security, the impact of fraud on reputation and customer trust and recommends integrated fraud detection, prevention, and resolution measures. These insights provide a critical contribution to the ongoing development of robust online banking security protocols. The study further discusses preventative measures that aid fraud mitigation and prevention in online banking

Tirzepatide: The Most Effective Drug Therapy for Prevention of Type 2 Diabetes

Obesity is a main trigger for development of type 2 diabetes. Tirzepatide is a dual receptor agonist of glucagon-like 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) and is a potent agent for controlling glycemic control and reducing body weight. Accordingly, tirzepatide was evaluated in addition to lifestyle changes to decrease incidence of type 2 diabetes in obese subjects with obesity and prediabetes in an extension study of the SURMOUNT-1 trial. The latter was a randomized, double-blind trial of 72 weeks to evaluate the effects of tirzepatide on weight reduction in 2,539 participants with obesity; 40% (n=1,032) of those subjects had prediabetes. The authors of SURMOUNT-1 study examined the frequency of new-onset type 2 diabetes in the 1,032 subjects with pre-diabetes from baseline to week 176 and week 193 after a 17-week off tirzepatide or placebo. After 176 weeks, type 2 diabetes was diagnosed in 1.5% (n=4), 2.0% (n=5), 0.4% (n=1), and 13.3% (n=36) in subjects randomized to tirzepatide 5 mg, 10 mg, and 15 mg, and placebo, respectively. At 176 weeks, compared with placebo, risk of type 2 diabetes in the pooled tirzepatide groups, was decreased by 93%; hazard ratio (HR) 0.07, 95% CI, 0.0 to 0.1; P<0.001. This 93% reduction in incidence of type 2 diabetes was superior to that achieved by the maximum doses of the GLP-1 receptor agonists liraglutide (79% reduction) and semaglutide (73% reduction), and by the anti-obesity agent phentermine/topiramate (76% reduction). However, subjects’ characteristics in studies evaluating these 4 drugs were different. At 176 weeks, achievement of at least 5% of weight loss resulted in remission of prediabetes to normoglycemia in 96% and 83% of subjects with tirzepatide and placebo, respectively. Weight loss seems to be a main factor leading to prevention of type 2 diabetes in all previous drugs. Other mechanisms such as amelioration of beta-cell function and a decrease in insulin resistance may be involved in case of tirzepatide. Overall, tolerance to tirzepatide was satisfactory. Yet, 12.3% of individuals discontinued tirzepatide 15 mg due to adverse effects versus 5.9% in the placebo group. Gastrointestinal (GI) adverse effects were the main safety issue related to tirzepatide. In summary, tirzepatide is currently the most effective agent for diabetes prevention and reversion to normoglycemia in subjects with obesity and prediabetes. Further studies are needed to examine the long-term efficacy, safety, and cost-effectiveness of tirzepatide for prevention of type 2 diabetes. &nbsp

AI-Enhanced Mentoring for Social Entrepreneurship: Catalyzing Regenerative Finance and Sustainability Transitions

Objectives: This research investigates the intersection of Artificial Intelligence (AI), DeepTech, and social entrepreneurship (SE) in driving financial innovation for sustainability transitions within the banking, finance, and insurance sectors. It also examines the role and potential of mentoring, particularly AI-driven approaches, in guiding social entrepreneurs to develop and scale regenerative finance solutions and attract impact investment. Methods: Employing a mixed-methods approach, a Systematic Literature Review (SLR) following PRISMA guidelines was combined with Bibliometric Analysis. A comprehensive search across major academic databases yielded 99 relevant peer-reviewed articles. Analysis identified publication trends, citation metrics, and key thematic connections. Results: Findings demonstrate that AI and Deep Tech are powerful catalysts for SE in finance, enabling data-driven innovation, enhancing operational efficiency, and facilitating transformative instruments. Digital SE improves scalability. Bibliometric analysis confirmed “social entrepreneurship” centrality, linked to “deep tech startups” and “social impact.” Mentoring is critical for navigating complexities, strategic planning, and networks. AI enhanced mentoring's specific potential is currently underexplored in the literature, but it shows significant promise. Conclusions: AI and Deep Tech catalyze SE financial innovation for sustainability. Mentoring (human and AI-enhanced potential) is vital for SEs to leverage these technologies effectively, scale impact, and attract investment. Developing ecosystems, tailored AI-mentoring models, and robust impact metrics is crucial for a regenerative financial future. This study identifies critical gaps and provides a framework for future research for academics and practitioners

Ethical Dilemmas and Philosophical Insights in the Clinical Applications of Large Language Models

Large Language Models have started to become an integral part of clinical solutions. From disease diagnosis to medical report analysis, generative models have been creating significant impact. In this work, we analyze ethical dilemmas present in such situations and the philosophical underpinnings of those dilemmas. We also touch upon a few solutions to those dilemmas from philosophical as well as engineering point of view

Violence Against Women: A Multidimensional Analysis

Violence against women (VAW) is a global phenomenon deeply rooted in social, cultural, and economic inequalities. It manifests in diverse forms—physical, sexual, psychological, and economic each of which has devastating consequences for individuals and societies. This article examines the scope, different types and causes of VAW, and the short term and long term impact it has on the victims and survivors and overall on the society at large. Emphasizing the importance of systemic change, it advocates for comprehensive strategies to prevent violence, support survivors, and challenge the structural factors perpetuating gender-based violence