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Lattice thermal conduction in cadmium arsenide
Lattice thermal conductivity (LTC) of cadmium arsenide (Cd3As2) is studied over a wide temperature range (1-400 K) by employing the Callaway model. The acoustic phonons are considered to be the major carriers of heat and to be scattered by the sample boundaries, disorder, impurities, and other phonons via both Umklapp and normal phonon processes. Numerical calculations of LTC of Cd3As2 bring out the relative importance of the scattering mechanisms. Our systematic analysis of recent experimental data on thermal conductivity (TC) of Cd3As2 samples of different groups, presented in terms of LTC, ? L, using a nonlinear regression method, reveals good fits to the TC data of the samples considered for T < ? 50 K, and suggests a value of 0.2 for the Gruneisen parameter. It is, however, found that for T > 100 K the inclusion of the electronic component of TC, ? e, incorporating contributions from relevant electron scattering mechanisms, is needed to obtain good agreement with the TC data over the wide temperature range. More detailed investigations of TC of Cd3As2 are required to better understand its suitability in thermoelectric and thermal management devices. 2022 Chinese Physical Society and IOP Publishing Ltd. -
Lattice thermal conduction in suspended molybdenum disulfide monolayers with defects
In this study, we investigated the effect of lattice defects comprising vacancies and boundaries on the lattice thermal conductivity (LTC), ? p , of suspended molybdenum disulfide monolayers (MLs) over a wide temperature range (1 < T < 500 K). Using the phonon Boltzmann formalism, the acoustic phonons were considered to be scattered by the sample and grain boundaries, isotopic impurities, vacancies, and other phonons via Umklapp and normal (N-) processes. ? p was evaluated using a modified Callaway model by considering the in-plane longitudinal acoustic and transverse acoustic phonons, and out-of-plane flexural acoustic phonon modes. We demonstrated the need to include the often neglected non-resistive N-processes when evaluating the LTC. Numerical calculations of the temperature dependence of the LTC for crystalline and polycrystalline MoS 2 MLs showed the dominance of sample-dependent scattering mechanisms at low temperatures (T < 100 K) and of phonon-phonon scattering at higher temperatures, where the N-processes played an important role. The effects of vacancies and boundaries were to alter the behavior and suppress the magnitude of the LTC. The suppression due to vacancies was greater in crystalline MLs with specular surfaces and in polycrystalline MLs with larger grain sizes. The calculations compared well with recent thermal conductivity data obtained for polycrystalline samples. The need for further investigations is suggested. 2018 Elsevier Ltd -
Launch power determination algorithm for dynamic traffic provisioning in mixed-line-rate optical wavelength division multiplexed networks
In transparent mixed-line-rate (MLR) optical networks, different line rates, on different wavelengths, can coexist on the same fibre. However, along the path, signal experiences various physical layer impairments (PLIs), and its quality also degrades. A major factor that affects transmission quality is launch power of the optical signal. On one hand, power must be high enough to ensure less noise at receiver; on the other hand, it must be lower than the limit where PLIs start to distort the signal. Further, high launch power is disruptive to both, the actual lightpath and its neighbours. In this study, we investigate the problem of determining appropriate launch power for provisioning dynamic connection requests in transparent MLR networks. We propose a heuristic that determines the appropriate launch power of a lightpath. The PLI-average (PLI-A) approach is based on the optical reach of signals, is practical, and can adapt to the needs of network operators. Results show that performances of the proposed approach are better than the existing schemes. Copyright 2015 Inderscience Enterprises Ltd. -
Launch power determination algorithm for dynamic traffic provisioning in mixed-line-rate optical wavelength division multiplexed networks /
International Journal Of Internet Protocol Technology, Vol.9, Issue 1, pp.23-33, ISSN No: 1743-8209. -
Law, Regulation, and the Evolution of Corporate Governance: Driving Sustainability
This chapter examines how corporate governance is changing to promote sustainable development as a result of legal and regulatory advancements. Governance frameworks that were before almost entirely centered on shareholder earnings are increasingly being redesigned to incorporate social and environmental responsibility. The chapter emphasizes the increasing focus on transparency, Environmental, Social and Governance (ESG) integration, and stakeholder inclusion by examining changing regulations, international frameworks, and market-based efforts. It also looks at new developments like climate-related disclosures, board-level sustainability oversight, and legal reactions to greenwashing. Global ESG standards should be harmonized, and corporate legal frameworks should incorporate sustainability, according to the findings. The chapter makes the case for a move toward long-term, purpose-driven business structures by establishing sustainability as the primary pillar of governance. This change is a reflection of a wider realization that effective governance is critical to both corporate success and the welfare of the world. 2026 by IGI Global Scientific Publishing. -
Layered natural oxide based soft actuators for controlling artificial motion by chemical stimulus
The chemical stimuli-based soft-actuators with complex actuation properties are of significant interest in the field of biomechanical and biomedical applications such as prosthetics. Soft actuators can manipulate and precisely control the fluid motion at the microscale and may play an important role in fluid transportation in many biological systems. Here, we have presented a two-dimensional (2D) material-based 3D printed system for the fabrication of porous soft actuators that display different actuations under the organic fluid stimulus. The few atomic layered thin chromite sheets (natural ores) show significant changes in their physical properties due to the strong interaction with organic molecules. The composite film is capable of showing controllable and sophisticated motions such as twisting, bending, rolling, and flipping in response to chemical stimuli. The introduction of porosity in the composite film dramatically increases the dynamic performances, detection range, and sensitivity. As a result, a high actuation (twisting angle) of ?540 5 and response time of ?0.9 s was achieved, which significantly enhanced the device performance. Finally, to offer further flexibility and controlled structural alterations, we designed a snail, leaf, and worm-like soft actuators that expand the practical applications. 2025 Elsevier Ltd -
LBP-GLZM Based Hybrid Model for Classification of Breast Cancer
Classifying mammogram images is difficult because of their complex backgrounds and the differences in resolutions across the images. One of the toughest parts is telling the difference between harmless (benign) and harmful (malignant) tissue. This is hard because the differences between them are incredibly subtle. As a consequence, the distinctive features embedded within tissue patches become not just relevant but critical for the accurate and automatic classification of these images. Traditionally, efforts to automate this classification process have encountered limitations when relying on a singular feature or a restricted set of characteristics. The subtle variations in texture within these images often render such approaches insufficient in achieving high-quality categorization results. Recognizing this, the present investigation undertakes a more comprehensive approach by incorporating distinct feature extraction techniques - specifically, the utilization of Local Binary Pattern (LBP) and Gray Level Zone Matrix (GLZM). These techniques are adept at capturing and delineating the nuanced texture features inherent in mammogram images. By extracting and analyzing these textural nuances, the aim is to construct a hybrid model capable of classifying mammograms into three distinct categories: malignant, benign, and without the necessity for further examination or follow-up. This proposed hybrid model holds significant promise in the field of mammography classification by leveraging the strengths and complementary attributes of multiple feature extraction methods. The integration of LBP and GLZM aims not only to enhance the accuracy of classification but also to improve the robustness of the system in identifying subtle yet crucial differences in tissue textures. Ultimately, the goal is to create a hybrid feature extraction framework that augments the diagnostic capabilities of mammography, providing more precise and reliable categorization of breast tissue for effective medical decision-making and patient care. 2024 IEEE. -
LCLC Based AC-DC Single-Stage Resonant Converter with Natural Power Factor Correction
LLC-based AC-DC resonant converters make excellent EV chargers because of their high efficiency, high power density, and soft switching properties. Efficiency is increased and the need for a larger series inductor is lowered by connecting a capacitor across the magnetising inductance of the LLC resonant architecture (LCLC configuration). Switching frequency control is commonly used to regulate the converter's output DC voltage. However, there is a significant relationship between the converter's power factor and switching frequency. As a result, any changes in load may result in a lower power factor for the converter. This paper suggests a single-stage topology based on the LCLC resonant structure. The LCLC resonant configuration ensures zero voltage switching (ZVS) of the IGBTs used in the converter. Converters have a power factor correction (PFC) stage on the front of the converter to achieve natural power factor correction. Since the PFC stage and the resonant stage are controlled by the same switches, the converter is smaller and less expensive. A bridgeless rectification method is applied in the proposed topology to reduce the number of switching devices. MATLAB/Simulink simulations are used to validate the topology. 2023 IEEE. -
Leaching of minerals in subbituminous Indian coal and characterisation of the products by SEM
Coal is chemically and physically a complex and heterogeneous material, consisting of organic and inorganic mineral constituents. Presence of minerals in excess will pollute water, air and soil. Concerted efforts are needed to reduce 'ash forming' inorganic elements and to develop clean methods of using coal. This paper reports the demineralization of sub bituminous coal with EDTA, HCl, HF, chloroform and acid mixture. The residual coal from each treatment was analyzed using Scanning Electron Microscopy (SEM) and Ultimate analysis. All the micrographs were bright field and revealed several features corresponding to the mineral grains. It comprised of lithophiles like aluminium, silicates and calcium. The absences of some morphological features correspond to inorganic elements in residual coal samples confirming 'demineralization'. This result was further confirmed with the CHNS analysis. It was evident from the results that amongst the leachants used, Hydrofluoric acid and acid mixture had significant effect in removing the mineral matter, sulphur and oxygenated functional groups. Global Science Publications. -
Lead-free inorganic metal perovskites beyond photovoltaics: Photon, charged particles and neutron shielding applications
Over the last few years, lead-free inorganic metal perovskites have gained impressive ground in empowering satellites in space exploration owing to their material stability and performance evolution under extreme space environments. The present work has examined the versatility of eight such perovskites as space radiation shielding materials by computing their photon, charged particles and neutron interaction parameters. Photon interaction parameters were calculated for a wide energy range using PAGEX software. The ranges of heavy charged particles (H, He, C, N, O, Ne, Mg, Si and Fe ions) in these perovskites were estimated using SRIM software in the energy range 1 keV10 GeV, and that of electrons was computed using ESTAR NIST software in the energy range 0.01 MeV1 GeV. Further, the macroscopic fast neutron removal cross-sections were also calculated to estimate the neutron shielding efficiencies. The examined shielding parameters of the perovskites varied depending on the radiation type and energy. Among the selected perovskites, Cs2TiI6 and Ba2AgIO6 displayed superior photon attenuation properties. A 3.5 cm thick Ba2AgIO6-based shield could reduce the incident radiation intensity to half its initial value, a thickness even lesser than that of Pb-glass. Besides, CsSnBr3 and La0.8Ca0.2Ni0.5Ti0.5O3 displayed the highest and lowest range values, respectively, for all heavy charged particles. Ba2AgIO6 showed electron stopping power (on par with Kovar) better than that of other examined materials. Interestingly, La0.8Ca0.2Ni0.5Ti0.5O3 demonstrated neutron removal cross-section values greater than that of standard neutron shielding materials - aluminium and polyethylene. On the whole, the present study not only demonstrates the employment prospects of eco-friendly perovskites for shielding space radiations but also suggests future prospects for research in this direction. 2022 Korean Nuclear Society -
Leadership and Equity in Health Reform: Overcoming Discrimination and Promoting Mental Well-Being Among Migrant Workers
This chapter examines leadership and governance responses to workplace discrimination and mental- health inequities among migrant workers within Indias healthreform landscape, using Kerala as an empirical case. Drawing on quantitative evidence linking discrimination with psychological distress, diminished self- esteem, and reduced well- being, the chapter situates these outcomes within established frameworks such as health equity, social determinants of mental health, and traumainformed leadership. It advances a compassion- driven leadership model that integrates behavioral insights, inclusive policy design, public- health marketing, and participatory governance to address structural and systemic inequities. By moving beyond descriptive narratives, the chapter demonstrates how ethical and inclusive leadership can translate evidence into equitable reform. It argues that sustainable health reform must embed human dignity, social justice, and mental well- being at the core of governance, rather than prioritizing efficiency alone. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Leadership and Owner-Manager Well-Being: Examining the Role of Leadership and Owner-Manager Well-Being in Driving Sustainable Innovation
This study investigates the influence of leadership roles and owner-manager well-being on sustainable innovation in kirana (grocery) stores. As key contributors to local economies, these micro-enterprises face increasing pressure to adopt innovative and sustainable practices to remain competitive. The study uses data collected from 51 kirana store owners to explore the direct effects of leadership roles and well-being on fostering sustainable innovation. Correlation and regression analyses are employed to examine these relationships. Leadership roles are assessed in terms of strategic decision-making, vision, and the ability to motivate and guide teams. Meanwhile, owner-manager well-being encompasses physical health, emotional resilience, and overall satisfaction, reflecting the capacity of individuals to adapt and implement innovative practices. Findings reveal significant positive relationships between both leadership roles and owner-manager well-being with sustainable innovation. Leaders who exhibit strong strategic and adaptive capabilities are more likely to drive innovations. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Leadership and Performance Evaluation Strategies for Remote Healthcare Teams in the Digital Era: Effective Leadership in Remote Healthcare
Electroencephalography (EEG)- based Brain- Computer Interface (BCI) technology has appeared as a promising path for healthcare, contributing to novel solutions for detecting, treating, and dealing with neurological conditions. By capturing and construing the electrical activities of brain signals, EEG- based BCIs empow er direct brain communication with external devices, circumventing traditional neural conduits. This chapter delves into the progress of EEG- based BCI devices, emphasizing their implication in healthcare, the technical challenges tangled, and their potential to transform patient care. The key objective is to deliver a detailed exploration of the development procedure of EEG- based BCI devices, emphasizing their applications in healthcare. The chapter includes the principles of EEG signal acquisition, the design and engineering of BCI systems, the employment of machine learning algorithms for signal decoding, and the clinical validation required for medical use. Moreover, it will discuss the prospective effect of these devices on healthcare and future research directions. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Leadership for Digital Transformation
The chapter explores the critical role of leadership in navigating the complexities of digital transformation, emphasizing the integration of technology, culture, and strategy to drive sustainable organizational change. Through comprehensive case studies, it highlights successful transformation journeys at Microsoft, Tesla, and Walmart, alongside challenges faced by organizations like General Electric. The discussion delves into frameworks such as Transformational Leadership Theory, Agile methodologies, and Digital Maturity Models, underscoring their importance in fostering adaptability, innovation, and inclusivity. Key themes include addressing resistance to change, bridging digital skills gaps, and embedding ethical practices in leadership strategies. The chapter concludes by providing actionable recommenda- tions for future leaders to harness emerging technologies, balance innovation with sustainability, and build resilient organizations in an interconnected global economy. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Leadership strategies for change and innovation
Organizational innovation and change development depends heavily on leadership activities. This chapter investigates how leaders should integrate charismatic and authentic methods with transformational concepts to create the best possible leadership practice for long-term organizational success and innovation promotion. The chapter also demonstrates that leadership success will emerge from blending different leadership styles since any one approach alone is inadequate for solving current organizational challenges. Strong leaders who learn to unite multiple leadership approaches gain enhanced abilities to encourage their personnel while promoting innovative initiatives. 2025, IGI Global Scientific Publishing. All rights reserved. -
Leadership Style and Work Engagement: A Comparison of Private and Public Sector Firms in India
Post-privatization, public sector organizations were encouraged to borrow and learn from private sector firms. The popular belief was that the human resource practices followed by private sector organizations were far superior and more effective than those of the public sector organizations. However, this claim lacks empirical proof. This study adds to this body of knowledge by comparing the level of work engagement in private and public sector firms of India. Given that the leadership is crucial in setting the tone of an organization, the study also analyses the dominant leadership styles and their relationship to the levels of work engagement. The study is descriptive in nature and utilizes a structured questionnaire to collect data. Individuals currently employed in Indian public and private sector firms, in managerial roles, were invited to record their responses. The final sample consisted of 240 employees, with equal representation from both sectors. The collected data was then analysed using SPSS. The findings suggested that the dominant leadership styles were not significantly different in public and private sector organizations. Private sector employees were found to be more engaged and the leadership style appeared to be significantly related to the levels of engagement in public sector firms only. 2021 MDI. -
Leading and learning in inhospitable terrain
This chapter explores the obstacles that minority women in K-12 education leadership must overcome, emphasizing the critical importance of acknowledging barriers and prejudices. Notwithstanding its underrepresentation, their leadership demonstrates a steadfast dedication to diversity and offers distinctive viewpoints. Mentorship programs, educational institutions, and policymakers all play a crucial role in promoting diversity via inclusive practices and supportive policies. The recommendations include fostering an environment of inclusiveness, providing training on diversity, implementing precise career trajectories, and acknowledging and commemorating the accomplishments of a wide range of individuals. Collaborative endeavours and inclusive approaches aim to establish educational leadership that is fair, diverse, and student-focused. Addressing inequalities is critical to establishing inclusive and resilient educational environments where mental health should be regarded as a fundamental right, highlighting the convergence of mental health and human rights. 2024, IGI Global. All rights reserved. -
Leaf Disease Analysis and Crop Suggestion Based on Soil Classification
Agriculture is a major contributor to the Indian financial system. As we realize approximately 60% of the population of Indiansrely on agriculture. Nowadays among the farmers who are educated, people also do agriculture. Farmers are dealing with problems related to low earningsbecause of loss of productivity. Farmers are thinking in the event that they use extra fertilizers they may get a precise yield, but it can grow the greater funding. If they do like this the bodily properties of soil may additionally decrease, and they are able to get the expected yield. To conquer this trouble, farmers have to realize which crop might healthy the specific piece of land. If they pick out the right sort of crop that is cultivated then robotically, the yield of the crop will grow. Hence, crop advice systems can be very beneficial to farmers. The yield of the crop can also depend on many factors like pH, nitrogen, phosphorus, potassium, and rainfall. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Leaf Disease Detection in Crops based on Single-Hidden Layer Feed-Forward Neural Network and Hierarchal Temporary Memory
Insects, mites, and fungi are common causes in plant disease, which can significantly reduce yields if not addressed promptly. Farmers are losing money as a result of crop illnesses. As the average under cultivation increases, it becomes more of a burden for farmers to keep an eye on everything. In this study, the median filter is used as a preprocessing step to transform the input image into a grayscale representation which used YCbCr color space. Otsu's segmentation is used to divide photographs that contain bright items on a dark background. Feature extraction using Grey Level Co-occurrence Matrix (GLCM). The proposed technique, known as ELM-HTM combines a simple yet adaptable extreme learning machine (ELM) with a Hierarchical Temporal Memory (HTM). This approach outperforms the ELM and HTM model with an accuracy of about 98.8%. 2023 IEEE. -
Leaf Disease Identification in Rice Plants Using CNN Model
Rice is a staple food crop for more than 10 countries. High consumption of rice demands better yield of crop. Fungal, bacterial and viral are different classes of diseases damaging rice crops which results in low and bad yield as per quality and quantity of the crop. Some of the most common diseases affecting plants are fungal blast, fungal brown spot, fungal sheath blight, bacterial blight and viral tungro. The deep learning CNN model with ResNet50V2 architecture was used in this paper to identify disease on the paddy leaves. Mobile application proposed in this paper will help farmers to detect disease on the leaves during their regular visit. Images were captured using this application. The captured images were tested using the trained deep learning model embedded with mobile application. This model predicts and displays input images along with the probabilities compared to each disease. The mobile application also provides necessary remedies for the identified disease with the help of hyperlink available in mobile application. The achieved probability that the model can truly classify the input image in this project was 97.67%, and the obtained validation accuracy was 98.86%. A solution with which farmers can identify diseases in rice leaves and take necessary actions for better crop yield has been demonstrated in this paper. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.