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Empowering solar cells with non-toxic Cu2O and Zn(O,S): a sustainable approach for CIGS solar cells
Get PDFThis study investigates the incorporation of a non-toxic p-type Cu2O layer as a back-contact hole collector on the Cu(In,Ga)Se2 (CIGS) absorber layer in thin-film solar cells, alongside a wide-bandgap and non-toxic Zn(O,S) buffer layer as the n-type material. Simulations analyze the effects of absorber layer thickness, Ga concentration, defect density, and recombination on the photovoltaic performance, as well as the influence of various metal work functions, back-contact and alternative buffer layers. The proposed design achieves a significant improvement in current density, reaching 36.8 mA/cm2 compared to 33.2 mA/cm2 in a reference cell using a Zn(O,S) buffer layer and no Cu2O. The Cu2O layer enhances hole conduction at the rear contact due to its p-type nature, thereby improving device efficiency. Additionally, the Zn(O,S) buffer layer, with its larger bandgap of 2.7 eV compared to the 2.4 eV of CdS, reduces parasitic absorption losses and significantly enhances photocurrent in the UV spectrum. As a result, the solar cell's conversion efficiency improves from 22.11% to 25.35% with the inclusion of Cu2O and the substitution of CdS with Zn(O,S). These findings demonstrate that Cu2O is a promising back-contact hole collector, and the proposed CIGS solar cell design offers a pathway to developing high-efficiency thin-film solar cells
Differences and commonalities in barriers and facilitators experienced by participants enrolled in an online behavioral weight management program: a qualitative comparison
Get PDFOnline behavioral weight management programs offer a scalable solution to address overweight and obesity but often face high dropout rates and variable success. Understanding the barriers and facilitators experienced by participants who achieve weight loss targets versus those who do not is critical for optimizing programs. This study compared the barriers and facilitators reported by participants achieving ≥5% weight loss with those achieving <5%, using a social–ecological framework to capture influences across individual, interpersonal, and environmental levels. The framework was chosen to reflect the complex, interacting factors beyond the individual that shape behavior. Forty-eight participants completed semi-structured telephone interviews exploring factors affecting their weight loss journey. Interviews were analyzed using a thematic framework approach. Across both groups, key facilitators included willpower, knowledge, social support, and perceived safety in the local environment, with their absence acting as barriers. Food availability at home and in the workplace was also reported as a barrier due to temptation. Social roles could challenge behavior change, though perceiving themselves as role models provided motivation. Program-specific factors, such as group dynamics and difficulty using the platform, were barriers for both groups. Notable differences emerged between groups in responding to challenges. The ≥ 5% weight loss group proactively addressed stressors and sought solutions, while the < 5% weight loss group reported greater difficulty overcoming barriers, more interpersonal stressors, and dissatisfaction with their weight targets. This is the first study to compare qualitative experiences across social–ecological domains between participants achieving ≥5% and <5% weight loss during program participation. Findings highlight the need to address environmental infrastructure, interpersonal skills, and communication of weight targets to improve program effectiveness. Future research should examine how these factors can identify individuals at risk of not achieving 5% weight loss and inform tailored interventions
Silicon chip-based dual Fabry-Pérot biosensor employing the Vernier effect for enhanced sensitivity
Get PDFIt is desirable to keep the cost, size, power and complexity of optical biosensors as low as possible to increase their suitability for mass manufacture and deployment outside of the lab in applications such as security, environmental sensing and medical diagnostics. Many optical biosensors suffer from low free spectral range and sensitivity, with strategies such as the Vernier effect being employed to combat this. Whilst the Vernier effect has been applied extensively in fibres or lateral chip-scale devices such as ring resonators and Mach Zehnder interferometers, limited attention has been given to biosensors based on vertical, dual-cavity chip-based Vernier structures. Here through simulations, we show a vertical dual Fabry Pérot / etalon stack utilising the high refractive index and mature processing of silicon combined with the Vernier effect to achieve theoretical sensitivity values in the range of 4200 - 93155 nm/RIU and limit of detection values of order 10-6 - 10-5 RIU using 1550 nm light. We simulate a number of different device dimensions and show that practical considerations such as thermal stability and fabrication tolerances, may necessitate operating the Verniers at lower sensitivity enhancements (e.g. ~16000 nm/RIU) as a price for better stability. This enhancement is still significantly higher sensitivity than a single, non-Vernier cavity (~1000 nm/RIU). One of the key advantages of this approach versus lateral scale devices is the removal of waveguides, which greatly eases light coupling. The devices presented also do not require nano or even microscale features in the lateral plane, nor any multilayer Bragg mirrors to achieve these high sensitivity values. This work provides an initial design study to guide future fabrication and experimental verification
Parsing the neuroanatomy of schizophrenia to enhance the translational validity of preclinical models - a multidisciplinary perspective
Get PDFPeople with schizophrenia can experience a range of symptoms, typically classified as positive (such as hallucinations, delusions), negative (such as avolition, anhedonia) or cognitive (such as attentional or working memory impairments). The accumulation of evidence from EEG, and structural and functional imaging, combined with post-mortem neurochemistry and pathology, has gradually focussed attention on altered function in a core neural circuitry as underlying the aetiology of schizophrenia. The principal circuits apparently fundamental to positive symptoms (e.g. auditory pathway, including auditory cortex) overlap with those apparently fundamental to negative/cognitive symptoms (e.g. ventral striatum, ventral tegmental area) at prefrontal cortex and reticular thalamus. This review summarises the various strands of evidence that lead to these conclusions, considers how this circuitry might be selectively affected according to our understanding of the causes of the disease, and then highlights how the knowledge of regionally-specific electrophysiological, imaging and neurochemical endophenotypes could be better exploited for translational purposes
Understanding the difference in symptoms and outcomes between glioblastoma patients diagnosed based on histological or molecular criteria: a retrospective cohort analysis from the Histo-Mol GBM collaborative
Get PDFPurpose: Since the 2021 World Health Organisation (WHO) classification, glioblastoma could be diagnosed based on classical histological features (hGBM) or molecular criteria (mGBM). However, prior studies included patients who required reclassification as a mGBM, potentially biasing survival analyses. The Histo-Mol GBM collaborative performed an international multicentre retrospective real-world cohort study of glioblastoma patients diagnosed according to WHO CNS 5. Methods: We identified consecutive patients diagnosed in 2021 with IDH wildtype glioblastoma according to WHO CNS 5. Clinicopathological, treatment, and survival data were collected and compared between mGBM and hGBM. Results: 1828 patients diagnosed with glioblastoma were included. 75 mGBM patients (8.4% of tested patients) were identified, with no difference in age (median 61 vs 64, p = 0.057), gender (p = 0.937), or proportion with performance status 0–1 (82.7% vs 68.3%, p = 0.052) compared to hGBM. mGBM patients had an extended interval from MRI to surgery (median 23 vs 14 days, p < 0.001) and more frequently underwent biopsy (69.3% vs 30.3%, p < 0.001), but equivalent proportions received oncological treatment (80.0% vs 78.7%, p = 0.784). Overall survival (OS) from surgery was not different (p = 0.063). However, OS from initial MRI, stratified by surgical extent, demonstrated improved OS for mGBM patients (hazard ratio (HR) 0.56, 95% confidence interval (CI): 0.43–0.73). Propensity score matching identified improved survival following resection (HR 0.48, 95% CI: 0.24–0.95; median OS: 26.0 versus 14.0 months, p = 0.031) but not biopsy (HR 1.10, 95% CI: 0.71–1.72). Conclusion: In this large real-world cohort, mGBMs had longer OS than hGBMs following resection with implications for prognostication and clinical decision making
A survey of microwave-implemented superconducting qubit control and readout circuits
Get PDFSuperconducting qubits are pivotal in advancing quantum computing, poised for scale but limited by the complexity and fidelity of their control and readout systems, relying on RF and signal processing infrastructure. This survey serves as a comprehensive and technically grounded review of control and readout architectures tailored for superconducting qubits. Synthesizing insights from device physics, circuit design, microwave engineering, signal processing, and cryogenic integration, this work details the practicalities of RF pulse generation, signal synthesis, and readout signal analysis for quantum systems. it covers key requirements, parameters, and pulse engineering techniques, including commonly used envelopes like Gaussian and DRAG designs. Moving to the system level, this survey systematically classifies and critically analyses current architectural strategies (covering key areas like frequency conversion, waveform management, and system infrastructure) and technology platforms (including adaptive classical control stacks, cryogenic CMOS circuits, and novel interconnects and interfaces), evaluating their trade-offs in performance. Extensive literature analysis identifies prevailing limitations such as wiring complexity, thermal budget constraints, latency, and power consumption, while highlighting underexplored opportunities for on-chip signal processing and novel interconnects, drawing analogies to advanced communication systems design. By consolidating diverse control paradigms and critically evaluating their trade-offs, this survey provides a unified foundation for designing next-generation quantum control stacks. Finally, a forward-looking roadmap outlines key trends in monolithic integration, cryo-compatible digital architectures, and physics-informed hardware co-design, offering both a retrospective synthesis and a prospective vision for quantum hardware engineering beyond the NISQ era
Copyright, Contract and Video Games: Terms of Play
No full textThis book uncovers how video game contracts act as monologues of power, moulding players to align with proprietary ideologies.
In the era of interactive technologies, the player emerges as a vital yet curiously overlooked figure. While copyright law governs the creation and distribution of these technologies, it sidesteps the player, leaving private contracts to define their role and obligations. Using video games as a case study, this book fills the gap left by copyright law, offering an innovative socio-legal methodology to interrogate and challenge harmful contractual norms.
By analysing contracts as a form of critical discourse, the book exposes the contradictions and idealisations embedded in these agreements, which often serve to reinforce industry priorities. It is an essential resource for scholars in intellectual property law, video game studies, and socio-legal research, contributing to pressing debates on user rights and the shifting balance of power in interactive industries.
With its fresh perspective on the interplay of copyright, contract, and cultural participation, the book redefines the player's role in a rapidly evolving digital landscape, offering new tools to understand and critique the legal frameworks shaping this most interactive of industries
Machine learning-driven optimization of metabolic balance for β-carotene production
No full textBalancing metabolic pathways is critical for engineering microbial platforms to efficiently and robustly synthesize value-added bioproducts. In the oleaginous yeast Yarrowia lipolytica engineered for β-carotene production, lipid synthesis supports carotenoid storage but also competes with carotenoid synthesis for cellular resources, necessitating precise regulation for optimal resource allocation. In this study, we establish a machine learning framework that captures the complex interactions among three key metabolic modules for β-carotene synthesis: the mevalonate pathway (precursor supply for β-carotene), lipid synthesis (storage capacity), and the β-carotene synthetic cluster (product formation). This computational framework enables the prediction of β-carotene output based on gene combinations and guides iterative gene integration strategies across these interconnected pathways to optimize production. Using this approach, the best-performing strain YLT226 achieved a 7-fold increase in β-carotene titer compared to the initial strain YLT001 through nine rounds of guided gene integration. This work provides a promising strategy for understanding and engineering metabolic flux distributions
Behavioural and genetic correlates of malnutrition
Get PDFChildhood undernutrition is a global public health challenge, affecting children unevenly within the same household. This study assessed the behavioural and genetic correlates of malnutrition among children aged 1–3 years in a district of the Greater Accra Region, Ghana. A cross-sectional study involving 262 child-caregiver pairs was conducted. Children were classified as wasted, stunted or healthy based on anthropometric indices. Feeding behaviours - including appetite, food refusal, force-feeding, and maternal feeding anxiety were assessed using the International Complementary Feeding Evaluation Tool. Saliva samples were used to genotype nine single nucleotide polymorphisms (SNPs) associated with appetite and energy regulation, and a polygenic risk score (PGRS) was generated. Wasted children had significantly lower appetite z-scores (Mean difference MD (Confidence interval CI)): -0.37 (-0.65, -0.09) and higher z-scores for food refusal (0.30 (0.03, 0.58)) and caregiver feeding anxiety (0.67 (0.39, 0.94)) compared to healthy children. Maternal feeding anxiety attenuated the association between appetite and WHZ while remaining a strong independent predictor. No associations were found between feeding behaviour and stunting. Although force-feeding was common (33% of children), it did not differ by nutritional status. The SNP rs2274333, showed a higher frequency of homozygosity for the AA genotype in wasted children. The PGRS was significantly associated with low appetite (p=0.046) but not with food refusal or nutritional status. Children with wasting had a lower appetite and a higher food refusal. This is associated with high levels of maternal feeding anxiety, but does not seem to have a strong genetic basis
Mathematical modelling of biofilm growth on medical implants incorporating nutrient-dependent phenotypic switching
Get PDFBiofilm infections on medical implants are difficult to eradicate because insufficient nutrient availability promotes antibiotic-tolerant persister cells that survive treatment and reseed growth. Existing mathematical models usually omit nutrient-dependent phenotypic switching between proliferative and persister states. Without this mechanism, models cannot capture how environmental conditions control the balance between active growth and dormancy, which is central to biofilm persistence. We present a continuum model that couples nutrient transport with the dynamics of proliferative bacteria, persisters, dead cells, and extracellular polymeric substances. The switching rates between proliferative and persister phenotypes depend on local nutrient concentration through two thresholds, enabling adaptation across nutrient-poor, intermediate, and nutrient-rich regimes. Simulations show that nutrient limitation produces a high and sustained proportion of persister cells even when biomass is reduced, whereas nutrient-rich conditions support reversion to proliferative growth and lead to greater biomass. The model also predicts that persister populations peak at times that vary with nutrient availability, and these peaks coincide with turning points in biofilm growth, identifying critical intervention windows. By directly linking nutrient availability to phenotypic switching, our model reveals mechanisms of biofilm persistence that earlier models could not capture, and it points toward strategies that target nutrient-driven adaptation as a means to improve the control of implant-associated infections
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