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Overcoming challenges in 5G performance evaluation and QoE management
As the 5G technology is being rolled out in phases, the world over, there is a need for efficient and effective 5G network planning and Quality of Experience. One way a country planning to adopt 5G could plan the logistics of laying out the network, could be through learning best practices from peers. Which peer to follow is subjective to each country in question. Therefore, in choosing these references/benchmark countries, a thorough knowledge of their performance is vital. Yet another factor that impacts 5G network planning is effective QoE management. Proper QoS provisioning over the network is very important even as countries strive to cater the best possible services to their citizens. This is made possible by identifying improvement needs of countries on its user QoE. By quantifying this need, suitable benchmarks could be set and achieved in the short or long terms thereby enabling the countries to provide better services to their people. Determining the right benchmarking and evaluation technique is the need of the hour. 2025 -
Machine learning for healthcare
Machine learning currently drives healthcare innovation, enabling novelty in solving complex medical problems. This chapter will present an in-depth critical review of various machine learning techniques applicable in healthcare in general, focusing on practical applications and recent advancements. It will further discuss supervised and unsupervised learning to semi-supervised learning methods, thereby detailing their uses for disease prediction, segmentation of patients, and image analysis in medical science. Among the most important areas in ML includes data preprocessing and feature engineering issues in health-care datasets. This further includes treatments for missing data, dimensionality reduction, and class imbalance. This chapter also discusses extensive case studies with state-of-the-art approaches that give insight into how the ML approach is changing health care decision-making, increasing diagnostic precision, and improving patient outcomes. Interpretability, scalability, and the mitigation of bias are further discussed as some of the challenges in the implementation of ML in healthcare. Ethical considerations regarding the need to develop responsible AI in healthcare and regulatory compliance are also discussed. It aims to serve as a handbook for researchers, practitioners, and policy analysts operating at the intersection between ML and healthcare. 2026 -
The Role of Artificial Intelligence in Electric and Autonomous Vehicles
The?? use of Artificial Intelligence (AI) is changing the whole car landscape. Indeed, AI is the main driving force behind the most innovative electric and autonomous vehicles. The technology is making transportation environmentally friendly, intelligent, and cost-effective. The chapter demonstrates the role of AI in self-driving cars and electric vehicles through various examples, such as autonomous driving, battery performance, charging systems, predictive maintenance, safety, efficiency, and fleet management. AI is the reason that cars can now drive themselves, whereby it is the technology that enables navigation, object detection, and systems like Tesla Autopilot. Besides, it is heavily involved in battery management as it lowers the battery life through usage, overheating, and prolongs the battery life. The chapter also talks about AI technology that supports smart EV charging, allowing integration of renewable sources and even making charging more comfortable and hassle-free. Predictive maintenance is yet another significant area where the AI system is monitoring the health of the car, the earliest detection of the faults, and extending the lifespan of EV components. Implementation of AI in safety vehicles is a great advancement in this industry. In conjunction with this technology, AI-based safety systems, like driver assistance, hazard detection, and emergency response, provide safety to the cars. Moreover, the technology enhances energy efficiency, range prediction, and real-time vehicle performance. The chapter concludes with a discussion about the coming of reflection in the AI realm of environmental sustainability, intelligent fleet management, and challenges of the future. In summary, this article accentuates how AI is rewiring the future of electric and self-driving vehicles and why its role is key for researchers, industry professionals, and ??policymakers. 2026 -
Sentiment analysis of sentences used in Indian local languages using Transfer Learning
The growing number of online communication channels has led to a dramatic increase in the volume of user-generated content across all media. Sentiment analysis is given more force by having access to these varying perspectives and feelings. Due to a lack of standardised labelled data, sentiment analysis becomes much more difficult. The goal of sentiment analysis is to determine, from a text sample, an individual's likely emotional reaction to a given event or point of view. When estimating the tone of a text, polarity analysis is commonly used. Negative, Positive and neutral are the labels used by sentiment classifiers. This chapter provides a framework for effective sentiment analysis of sentences from four local language datasets, including Hindi, English, Bangla, and Marathi, using transfer learning. The results show that the BERT model achieves a high level of accuracy when evaluated using random forests, nae Bayes, and decision trees. 2026 -
In-silico analysis of the mechanism of action ofNerium oleanderbioactive compounds againstHelicoverpa armigera
Helicoverpa armigera is one of the most destructive agricultural pests worldwide, noted for its wide host range, high fecundity, and rapid development of resistance to synthetic insecticides. To address this threat, sustainable botanical alternatives are urgently needed. In this study, Nerium oleander, a toxic ornamental plant rich in secondary metabolites, was evaluated as a potential botanical insecticide through in silico assays. Methanolic extracts were subjected to phytochemical screening, confirming the presence of alkaloids, saponins, cardiac glycosides, coumarins, and terpenoids. Gas Chromatography-Mass Spectrometry (GC-MS) profiling identified 20 major compounds, including terpenoids, fatty acids, sterols, and phenolics, with 2-methoxy-4-vinylphenol (2.7 %), neophytadiene (1.7 %), and phytol (0.9 %) among the key constituents. Cytochrome P450, a central detoxification enzyme in insects, was chosen as the molecular target. Docking analysis revealed strong binding affinities, with phytol (?6.92 kcal/mol, Ki 8.12 ?M), neophytadiene (?6.43 kcal/mol, Ki 14.57 ?M), and 2-methoxy-4-vinylphenol (?5.87 kcal/mol, Ki 45.13 ?M) demonstrating significant inhibitory potential. These findings indicate that N. oleander metabolites may disrupt detoxification pathways in H. armigera, providing a mechanistic basis for their insecticidal action and supporting the plant's promise as a candidate for integrated pest management. 2025 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. LtdThis is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/ -
Unveiling the realm of AI governance in outer space and its importance in national space policy
This article explores the notable legal concerns that may arise from the growing utilisation of artificial intelligence and machine learning in outer space. Whether it is conducting space exploration, clearing orbital debris, or extracting resources from specific areas in space, these activities are becoming more popular. Therefore, it is necessary to establish a regulatory framework to ensure consistency and objective standards. In order for national space legislation to effectively address the challenges presented by activities involving robots with different levels of autonomy and numerous objectives, it is essential to appraise the nature of these challenges. The article aims to investigate the relationship between the Montreal Declaration for a Responsible Development of Artificial Intelligence, 2017, and outer space laws and principles. It also examines the legal status of autonomous space objects, such as planetary rovers that are currently in operation or will be in the near future. Ultimately, the article highlights the importance of national space policy in addressing the appropriate regulation of artificial intelligence in outer space. In conclusion, this article has also discussed the potential effectiveness of utilising artificial intelligence-based methodologies and strategies to enhance current space policy. 2024 IAA -
Balancing commercialization and sustainability in outer space: Addressing new challenges
One notable aspect of NewSpace is the growing influence of private non-state actors. Nation-states have also implemented policies that facilitate the involvement of private non-state players in space activities. The lack of progress in international space law since the Moon Agreement of 1979 highlights the need to reconsider and update the existing legal system. Therefore, it is necessary to create a different framework based on the concept of commercial reality. The article emphasises the impact of NewSpace on the technological and commercial aspects of the outer space industry. An analysis is conducted on the crucial requirement for regulatory reform in the field of outer space law and policy, which arises from these advancements in the future. The persistent obstacle in addressing the commercial development of NewSpace is the lack of clarity surrounding property rights in outer space, particularly concerning the ownership and utilisation of space resources. This article examines the issue presented by the national space laws, which have conflicting and inconsistent views on property rights in outer space. The article also aims to investigate the practicality of establishing an international framework for space cooperation. The importance of the New Age institutional mechanism for international collaboration and the agenda for the proposed mechanism are emphasized. The proposed institutional framework aims to achieve a balance between commercialization and profit-driven market pressures, considering their potential negative effects on the sustainable usage of outer space. In conclusion, the article discusses India's appropriate course of action in response to the emerging problems in the field of space exploration. 2025 IAA -
Is connection the key? The mediating role of psychological safety in the relationship between relatedness to employee engagement
This study examines the influence of Relatedness Needs (RL) on Employee Engagement (EE) in Bengaluru's Information Technology (IT) Industry, with the mediating role of psychological safety (PS). As the information technology industry experiences continuous innovation and is associated with a high-pressure work environment, aligning the organizational needs with the employee's needs is critical to ensure organizational success. Employees with higher RL needs satisfaction will exhibit positive commitment and higher engagement, contributing to the long-term productivity and success of the organisation. This study examines the extent to which PS, indicating a safe environment promoting transparent communication, sharing ideas and engaging in collaborative decision-making without the fear of negative consequences, mediates the relationship between RL and EE. To test the study's hypothesis, AMOS, Smart-PLS, and structural equation modeling were used to analyse data collected from 304 employees working across companies in Bengaluru's Information Technology (IT) industry. Our findings suggest that having a stronger RL boosts EE through the mediating role of PS characterised by trustworthiness, a sense of safety and fairness at the workplace. The results suggest that fostering higher RL and ensuring a strong PS is vital for sustained EE and reducing turnover intention. This study offers valuable insights into the Information technology (IT) companies intending to boost workforce engagement in a highly pressured work environment. 2025 The Authors -
Trust green, pay more: Decoding green brand loyalty and willingness to pay more for electric vehicles through green transparency and green perceived value
The StimulusOrganismResponse framework is applied in this study to explore the impact of Green Transparency (stimuli) and Green Perceived Value (stimuli) on Green Brand Trust (organism) and, subsequently, on Green Brand Loyalty (response) and Willingness to Pay More (response). Self-Brand Connection is examined as a moderator. An online survey was distributed to 557 EV consumers. We employed both PLS-SEM (SmartPLS 4) and CB-SEM (AMOS 29) to test the direct, mediating, and moderating effects, with CB-SEM used as a robustness check for model stability. The results show that both Green Transparency and Green Perceived Value are positive antecedents of Green Brand Trust. Green Brand Trust, in turn, positively influences Green Brand Loyalty and Willingness to Pay More and mediates the effects of the two stimuli. The results also confirm that Self-Brand Connection significantly and positively strengthens the Green Brand Trust?Green Brand Loyalty and Green Brand Trust?Willingness to Pay More relationships. This study establishes Green Brand Trust as a core green consumer behavior mechanism and identity alignment as a catalyst for Green Brand Loyalty and Willingness to Pay More, offering actionable guidance to EV brands for credibility building, customer retention, and sustainable consumption. 2026 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/ -
The rapid diagnosis of intraamniotic infection with nanopore sequencing
Background: Intraamniotic infection (defined as intraamniotic inflammation with microorganisms) is an important cause of the preterm labor syndrome. Methods for the detection of microorganisms in amniotic fluid are culture and/or polymerase chain reaction assay. However, both methods take time, and the results are rarely available for clinical decision-making. Nanopore sequencing technology offers real-time, long-read sequencing that can produce rapid results. Objective: To determine 1) the diagnostic performance of the 16S rDNA nanopore sequencing method for the identification of microorganisms in patients with intraamniotic inflammation and 2) the relationship between microbial burden and the intensity of the amniotic fluid inflammatory response. Study Design: We performed a prospective cohort study that included singleton pregnancies presenting with symptoms of preterm labor with intact membranes or of preterm prelabor rupture of the membranes. Amniotic fluid samples were obtained for the evaluation of bacteria in the amniotic cavity using cultivation and polymerase chain reaction-based 16S Sanger sequencing methods. Participants were classified into 4 groups according to the results of an amniotic fluid culture, 16S Sanger sequencing, and an amniotic fluid interleukin 6 concentration: 1) no intraamniotic infection and intraamniotic inflammation (interleukin 6 <2.6 ng/mL, and no microorganisms in the amniotic cavity, as determined by culture or 16S Sanger sequencing); 2) microbial invasion of the amniotic cavity without intraamniotic inflammation, defined by the presence of bacteria detected by culture or 16S Sanger sequencing; 3) sterile intraamniotic inflammation (interleukin 6 ?2.6 ng/mL without microbial invasion of the amniotic cavity); and 4) intraamniotic infection (interkeukin 6 ?2.6 ng/mL with microbial invasion of the amniotic cavity). Patients who underwent a mid-trimester amniocentesis, had no intraamniotic infection or intraamniotic inflammation, and delivered at term represented the control group. 16S rDNA nanopore sequencing was performed and the diagnostic indices for the identification of intraamniotic infection were determined. Bioinformatic analysis was carried out to identify microorganisms, and a read count of at least 100 or a read count exceeding that of the background species from the control group, along with a relative abundance of no less than 1%, was used. Results: 1) The 16S nanopore sequencing had a sensitivity of 88.9% (8/9), specificity of 95.4% (41/43), positive predictive value of 80.0% (8/10), negative predictive value of 97.6% (41/42), positive likelihood ratio of 19.1 (95% confidence interval, 4.875.4), negative likelihood ratio of 0.1 (95% confidence interval, 0.020.7), and an accuracy of 94.2% (49/52) for the identification of intraamniotic infection (prevalence, 17% [9/52]); 2) the microbial load determined by the 16S nanopore sequencing had a strong positive correlation with the intensity of an intraamniotic inflammatory response (amniotic fluid interleukin 6 concentration; Spearman's correlation 0.9; P=.002); and 3) a subgroup of patients with intraamniotic inflammation did not have bacteria determined by culture, Sanger sequencing, or nanopore 16S, thus confirming the existence of sterile intraamniotic inflammation. Conclusion: The 16S nanopore sequencing has high diagnostic indices, predictive values, likelihood ratios, and accuracy in the diagnosis of intraamniotic infection. 2025 The Author(s) -
New biomarkers for the detection of fetal death derived from large-scale proteomic analysis of maternal plasma
Background Normal pregnancy involves the modulation of thousands of maternal plasma proteins, and protein values not within the normal range may indicate the development of adverse pregnancy outcomes. A decrease in placental growth factor and an increase in soluble fms-like tyrosine kinase 1 in maternal plasma were shown to be associated with fetal death at the time of diagnosis and to predict this devastating pregnancy outcome at 24 to 28 weeks of gestation. However, these proteomic dysregulations are also present in other obstetrical syndromes, and more specific and sensitive biomarkers are needed to implement preventive strategies. Objective This study aimed to identify candidate protein biomarkers that can improve the prediction of fetal death relative to placental growth factor and soluble fms-like tyrosine kinase 1. Study Design This retrospective case-control study included 38 patients who experienced fetal death (cases) and 23 patients with uncomplicated pregnancies (controls). Plasma samples were collected at the time of diagnosis (2041 weeks of gestation) from cases and during routine care from gestational agematched controls. An aptamer-based multiplex assay was used to measure the abundance of >7000 protein analytes. Differential protein abundance was assessed using linear models with adjustment for gestational age at sample collection. Significance was inferred using a moderated t test adjusted P value of <.1 and a fold change of >1.25. Hypergeometric tests were performed to identify gene ontology biological processes enriched among proteins with significant changes in abundance. Random forest models were trained and evaluated via cross-validation to distinguish between fetal death cases and controls and to pinpoint the most salient predictors. Results Among the 7146 protein assays tested, 97 assays (1.4%) corresponding to 87 unique proteins differed significantly in abundance between fetal death cases and controls: 63 of 87 proteins (72%) were less abundant in fetal death cases, and 24 of 87 proteins (26%) were more abundant in fetal death cases. Dysregulated proteins were involved in pregnancy-related processes, such as angiogenesis and lactation. Random forest models effectively differentiated fetal death cases from controls, achieving an area under the receiver operating characteristic curve of 72% for the combination of placental growth factor and soluble fms-like tyrosine kinase 1, which increased to 86% when up to 50 additional proteins were included in the models (Delong test: P =.004). In addition, the point estimate of sensitivity increased from 53% to 74% (false-positive rate of approximately 10% for both). Glycoprotein hormones alpha chain (CGA), DnaJ homolog subfamily B member 9 (DNAJB9), and DNA-directed RNA polymerase III subunit RPC10 (POLR3K) emerged as the top 3 candidates to improve discrimination relative to placental growth factor and soluble fms-like tyrosine kinase 1. The significant proteomic changes in a subset of fetal death cases diagnosed first with preeclampsia relative to controls were highly correlated ( r =0.78; P <.001) with those reported in late preeclampsia cases leading to live births. On average, for each 2-fold change in protein abundance in late preeclampsia leading to live birth, there was an 8.6-fold change in preeclampsia leading to fetal death. Despite this overall correlation, transcobalamin 2, glucose-6-phosphate 1-dehydrogenase, and hepcidin, among others, demonstrated dysregulation only in preeclampsia leading to fetal death, suggesting both shared and distinct pathways perturbed in the 2 syndromes. Conclusion Our findings suggest that new maternal plasma proteins improve the discrimination of fetal death from controls relative to known biomarkers and that, although the signatures of fetal death and of preeclampsia are correlated, fetal death not only represents a much heightened disease state but also involves distinct perturbed pathways. Future studies are needed to determine whether the biomarkers can predict fetal death. 2026 Elsevier Inc. -
The effect of spatial and intensity level augmentation of structural magnetic resonance images on autism diagnosis model
In deep learning, the robustness and generalizability of models significantly depend on diverse and heterogeneous training data. Acquiring such an extensive dataset is challenging in fields like disorder prediction due to data scarcity, which can be attributed to factors such as privacy concerns, limited patient population, or inadequate facilities. Data augmentation can be an ideal solution to this problem, particularly in the field of disorder prediction, like autism, using medical imaging. Data augmentation can expand and balance datasets by generating high-quality and varied data, thereby improving the generalizability of deep learning models. This study proposed two types of augmentation methods: 1. Spatial level 2. Intensity level augmentation techniques. Eight different levels of augmentations were experimented with across these categories. This study found that the combination of spatial and intensity level augmentations enhanced the model's generalizability and robustness, achieving an AUC value of 0.7433. Additionally, it was observed that the Left to Right flip method, under spatial augmentation, diminished the model's performance, whereas random noise injection, under intensity level augmentation, improved prediction accuracy. 2026 Elsevier B.V. -
The competencycontrol paradox in parenting adolescents: Evidence from an Indian mixed-methods study
Background: Adolescence is a critical developmental period during which parenting practices interact with temperament and sociocultural context to shape mental health and adaptation. Most parenting models are derived from Western settings, with limited evidence from India. Methods: This simultaneous mixed methods study drew on cross sectional data from the Indian Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA) cohort, including adolescents aged 1217 years (parent report n?=?931; child report n?=?836). Exploratory factor analysis was conducted on parent and child versions of the Alabama Parenting Questionnaire. Qualitative data were obtained through in-depth interviews with 31 adolescents and their parents and analysed using thematic analysis. Findings were integrated at the interpretation stage. Findings: The original APQ structure did not replicate. Parent reports yielded three dimensionsInvolvement/Positive Parenting, Poor Monitoring, and Corporal Punishmentwhile child reports yielded five, distinguishing fathers and mothers involvement. Inconsistent disciplining did not emerge as a distinct construct. Qualitative findings indicated high involvement and behavioural and psychological control, largely driven by academic goals. Adolescents experienced these practices as both supportive and restrictive, with parental openness shaping communication. Contextual pressures, including resource constraints and urban stressors, contributed to a competencycontrol paradox. Interpretations: Parenting of adolescents in India must be understood within its relational and sociocultural ecology. While involvement and control function as primary supports, excessive control may constrain broader competency development. Integrating parent and adolescent perspectives is essential for culturally grounded research and intervention. 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Exploring the efficiency and scalability of using algae as a biomass feedstock for biofuel production
Sustainability is paramount to preserving essential resources for future generations. The widespread use of fossil fuels generates significant pollution, severely impacting both terrestrial and aquatic ecosystems through phenomena such as acid rain. Despite their rapid growth, high photosynthetic efficiency, and ability to thrive in a variety of conditions, algae have become a viable alternative biomass feedstock for biofuel production. This review explores the efficiency and scalability of algae-based biofuels, focusing on key factors such as biomass yield, lipid content, and conversion technologies. Algae have a higher lipid yield compared to traditional biofuel feedstocks such as corn or soybeans, making them an attractive option for large-scale fuel production. However, several obstacles hinder the widespread adoption of algae-based biofuels, including high production costs, energy-intensive cultivation, and water consumption. This paper also examines the efficiency and suitability of various cultivation technologies, including open ponds and photobioreactors, for large-scale production. Algal biofuel production could become more economically viable and environmentally sustainable through the integration of carbon capture technology and wastewater treatment. Advances in genetic engineering and metabolic optimization are further increasing lipid productivity, offering promising prospects for large-scale applications. This review additionally provides an analysis of genetic engineering techniques aimed at increasing biofuel yields. The study emphasizes the potential of algae-based biofuels to serve as environmentally friendly alternatives to traditional fossil fuels, highlighting these innovative approaches. While the evaluation acknowledges that algae-based biofuels can reduce dependency on fossil fuels and help mitigate climate change, it also notes that further research and development are necessary to overcome current financial and technological challenges. This review explores the recent advancements in algae cultivation, harvesting techniques, and biofuel extraction processes. Its goal is to present a comprehensive understanding of the current state of algae as a sustainable and effective feedstock for biofuel production, along with future prospects. 2025 Elsevier B.V. -
Exploring boronate-appended hyperbranched amino-functionalized dendrimer-empowered sensors for the potential recognition of FSH in age-categorized human plasma samples
Boronic acids can act as ideal saccharide receptors as they possess a high affinity for diols and readily form cyclic-boronate esters when reacting in an aqueous medium. Here, we present hydrophilic amino-functionalized boronic acid dendrimer (Af-BAD) for the first time, with significantly enhanced sensitivity towards Follicle Stimulating Hormone (FSH) detection. In this study, newly synthesized Af-BAD was dip-coated on a gold substrate to create an impedance-type sensing working electrode. The effects of Af-BAD coating on the gold chip, the sensing properties for FSH recognition, sensitivity, and stability were measured by the charge transfer resistance across the electrochemical setup. The impedimetric measurements were conducted in the presence of [Fe(CN)6]3-/[Fe(CN)6]4- redox reporter at pH 7.4. The increments in the charge-transfer resistance were monitored upon increasing the FSH concentrations from 25 fg/mL to 100 pg/mL. The device achieved good sensitivity with a calculated detection limit of 4.01 fg/mL and acceptable linearity. The observed behavior was linear concerning the tested concentrations. An attempt at a real application to serum samples was also successfully conducted. Meanwhile, the level of tolerance of boronic acid dendrimer with other competing glycoproteins and monosaccharides was also tested. In this study, we also compared human plasma FSH levels in female oral cancer patients and normal controls using the Af-BAD modified device and the clinically used ELISA method. With a sound understanding of boronate materials and their affinity, amino functionalized multi-boronic acid dendrimer was developed as a highly selective conjugate toward glycoprotein FSH detection. Copyright 2025. Published by Elsevier Ltd. -
Resilience in the crucible: Compassion fatigue among Indian clinical psychologists and the need for mental health policy reform
Objectives: Compassion fatigue (CF) significantly affects mental health professionals, especially in high-stress, resource-limited contexts. Despite its impact on therapeutic outcomes, little is known about how Indian clinical psychologists experience and manage CF. This study explored the lived experiences of CF among RCI-licensed Indian clinical psychologists, focusing on protective and risk factors in the post-pandemic context. Methods: A qualitative phenomenological design using Interpretative Phenomenological Analysis (IPA) was employed. Ten clinical psychologists from urban and semi-urban India were purposively sampled. Semi-structured interviews explored experiences of CF, resilience, and self-efficacy. Thematic analysis was informed by Figley's Compassion Fatigue Model and the Conservation of Resources Theory. Results: Four major themes emerged: (1) Professional Competence and Growth; (2) Therapeutic Relationship; (3) Professional Challenges, including vicarious trauma and boundary-setting; and (4) Self-Care and Support. Participants frequently reported emotional exhaustion and vicarious trauma, but also described post-traumatic growth and reflective practice as buffers. Conclusions: The findings underscore the need for policy-level interventions to address CF among Indian clinical psychologists. Enhancing clinical supervision, integrating trauma-informed curricula, and strengthening institutional support systems are critical for sustaining practitioner resilience and ethical therapeutic care in India's mental health landscape. Key practitioner message: Addressing compassion fatigue through supervision, policy reform, and resilience-building is vital for therapist well-being and service sustainability. 2026 Elsevier Inc. -
Radiation attenuation parameters and intrinsic efficiency of a few semiconductor crystals for radiation detection applications
This study investigates the effectiveness of nine inorganic semiconductor crystals ? LiGaSe2, LiInSe2, CsHgInS3, SnS, GaTe, BiI3, Sb2Te3, Tl4CdI6, and TlBr ? for radiation detection applications based on photon and charged particle (electrons, protons, and heavy ions) interaction parameters. Mass attenuation coefficient (?/?), half value layer (HVL), relaxation length (?), effective atomic number (Zeff), electron density (Neff), equivalent atomic number (Zeq), and exposure buildup factor (EBF) were computed using PAGEX software. These results, along with their intrinsic efficiencies calculated, were compared with that of standard materials (NaI(Tl), CdZnTe, and CdTe). The ?/? values of the studied semiconducting materials are ranked in the decreasing order as: TlBr, Tl4CdI6, BiI3, CsHgInS3, Sb2Te3, GaTe, SnS, LiInSe2, and LiGaSe2. TlBr, Tl4CdI6, BiI3, and Sb2Te3 show superior photon detection capabilities compared to the reference materials. TlBr and Tl4CdI6 have the highest intrinsic efficiency across nearly all energy regions, while LiGaSe2 has the lowest. Interaction parameters like range and Zeff for charged particles were also computed using standard databases, with SnS and Sb2Te3 showing the least range for all the charged particles studied throughout the entire energy region. The study indicates that TlBr and Tl4CdI6 have strong potential for developing next-generation radiation detectors with enhanced sensitivity, addressing needs in healthcare and national security. 2025 Elsevier Ltd -
Ultrasmall cobalt boride-decorated P, K-doped gC3N4 for plasmon-driven degradation of high concentration tetracycline
The widespread contamination of aquatic ecosystems by pharmaceutical pollutants, particularly tetracycline (TC) antibiotics, poses significant environmental risks. gC3N4 is widely studied as a photocatalyst for environmental remediation, yet its practical use remains limited. To overcome these limitations, we developed gC3N4 by co-doping phosphorus (P) and potassium (K), and further decorating with ultrasmall cobalt boride (CoB) nanoparticles. Elemental co-doping with P and K modulates the electronic structure of gC3N4 by narrowing the bandgap, introducing shallow impurity bands, and enhancing charge separation through directional charge redistribution, supported by spectroscopic analysis and DFT simulations. The introduction of plasmonic CoB nanoparticles leads to the formation of Schottky junctions, while also inducing localized surface plasmon resonance (LSPR) that significantly amplifies the photocatalytic activity. CoB/P-K-gC3N4 exhibited a 21-fold increase in TC degradation rate compared to pristine gC3N4, where 84.8 % of 100 ppm TC was degraded using 10 mg of photocatalyst in one hour, achieving high removal activity of 7.1 mgpollutant/gcatalyst/min. The catalyst also demonstrated excellent structural stability and sustained photocatalytic efficiency over multiple reuse cycles. Electrochemical studies showed a higher charge carrier density along with a noticeable decline in charge transfer resistance, while photoluminescence and time-resolved fluorescence analysis confirmed a suppressed electron-hole recombination rate. This study demonstrates the synergistic interplay of co-doping and plasmonic enhancement in advancing next-generation photocatalysts for sustainable water purification. 2025 Elsevier B.V.