Influence of intimate partner violence and male involvement on maternal healthcare services utilisation in Nigeria.

Introduction: Low maternal health care services utilisation, especially antenatal care attendance and skilled birth attendance, has been documented to be responsible for maternal mortality and morbidity in Nigeria. While available evidence suggests mixed findings on uptake of maternal health care services in the context of abusive spousal relationships, male involvement in household and health decision-making has been established to promote uptake of maternal health care services. Yet, studies which consider mediating influence of intimate partner violence on male involvement and maternal health care services uptake are sorely missing in Nigeria. We hypothesised that maternal health care services uptake in abusive marital unions has implications for male involvement in pregnancy care and this has been largely overlooked in Nigeria. Materials and methods: This study extracted data from the 2018 Nigeria Demographic and Health Survey (NDHS). The 2018 NDHS is a nationally representative secondary data which collected population, demographic and health information on women, men and households in Nigeria. The secondary data used a two-stage stratified and multistage sampling technique to collect information from the respondents. In this study, data were extracted for women who were sexually active, within the reproductive age (15-49 years) and not pregnant in five years prior the survey (n = 7,847). Results: The results indicated (77%) antenatal care attendance and (47%) skilled delivery. The mediating influence of IPV on male involvement resulted in women who experienced sexual violence more likely to use heath facility for antenatal care (OR = 3.20; C.I: 1.20-8.50). Women whose partners were involved in health decision making had lower odds of antenatal care attendance (OR = 0.64; C.I: 0.44-0.94). Also, women whose partners were involved in spending their earnings had lower probability of antenatal care attendance (OR = 0.72; C.I: 0.55-0.96). Yet, the mediating influence of intimate partner violence on male involvement resulted in a lower likelihood of use of skilled delivery for emotionally abused women (OR = 0.58; C.I: 0.39-0.85). Women whose partners were involved in spending their earnings had higher odds of using skilled delivery (OR = 2.15; C.I: 1.79-2.56). Yet, women whose partners were involved in their health decision-making had lower odds of using skilled delivery (OR = 0.46; C.I: 0.34-0.62). Conclusion: This study held the philosophical stance that intimate partner violence mediated the influence of male involvement on maternal health care uptake while intimate partner violence had an inconsistent influence on maternal health care uptake. Policies and interventions should aim at addressing deep-rooted gender norms which promote IPV and limit male involvement in pregnancy care in Nigeria. Programme and policy interventions should focus on enhancing socioeconomic status of women.

Inferring networks from time series: A neural approach.

Network structures underlie the dynamics of many complex phenomena, from gene regulation and foodwebs to power grids and social media. Yet, as they often cannot be observed directly, their connectivities must be inferred from observations of the dynamics to which they give rise. In this work, we present a powerful computational method to infer large network adjacency matrices from time series data using a neural network, in order to provide uncertainty quantification on the prediction in a manner that reflects both the degree to which the inference problem is underdetermined as well as the noise on the data. This is a feature that other approaches have hitherto been lacking. We demonstrate our method's capabilities by inferring line failure locations in the British power grid from its response to a power cut, providing probability densities on each edge and allowing the use of hypothesis testing to make meaningful probabilistic statements about the location of the cut. Our method is significantly more accurate than both Markov-chain Monte Carlo sampling and least squares regression on noisy data and when the problem is underdetermined, while naturally extending to the case of nonlinear dynamics, which we demonstrate by learning an entire cost matrix for a nonlinear model of economic activity in Greater London. Not having been specifically engineered for network inference, this method in fact represents a general parameter estimation scheme that is applicable to any high-dimensional parameter space.

Modeling of Schottky diode and optimal matching circuit design for low power RF energy harvesting.

This work designs and implements a single-stage rectifier-based RF energy harvesting device. This device integrates a receiving antenna and a rectifying circuit to convert ambient electromagnetic energy into useful DC power efficiently. The rectenna is carefully engineered with an optimal matching circuit, achieving high efficiency with a return loss of less than -10 dB. The design uses a practical model of the Schottky diode, where both RF and DC characteristics are derived through extensive experimental measurements. The results from both experiments and simulations confirm the effectiveness of the design, showing its proficiency in efficient RF energy harvesting under low-power conditions. The antenna produced operates in the wifi band with a gain close to 4 dBi and a bandwidth of 100 MHz. With a load resistance of 1600 Ω, the proposed device achieves an impressive RF-to-DC conversion efficiency of approximately 52% at a low incident power of -5 dBm. These findings highlight the potential and reliability of rectenna systems for practical and efficient RF energy harvesting applications. The study significantly contributes to our understanding of rectenna-based energy harvesting, providing valuable insights for future design considerations and applications in low-power RF systems.

Elevating understanding: Linking high-altitude hypoxia to brain aging through EEG functional connectivity and spectral analyses.

High-altitude hypoxia triggers brain function changes reminiscent of those in healthy aging and Alzheimer's disease, compromising cognition and executive functions. Our study sought to validate high-altitude hypoxia as a model for assessing brain activity disruptions akin to aging. We collected EEG data from 16 healthy volunteers during acute high-altitude hypoxia (at 4,000 masl) and at sea level, focusing on relative changes in power and aperiodic slope of the EEG spectrum due to hypoxia. Additionally, we examined functional connectivity using wPLI, and functional segregation and integration using graph theory tools. High altitude led to slower brain oscillations, that is, increased δ and reduced α power, and flattened the 1/f aperiodic slope, indicating higher electrophysiological noise, akin to healthy aging. Notably, functional integration strengthened in the θ band, exhibiting unique topographical patterns at the subnetwork level, including increased frontocentral and reduced occipitoparietal integration. Moreover, we discovered significant correlations between subjects' age, 1/f slope, θ band integration, and observed robust effects of hypoxia after adjusting for age. Our findings shed light on how reduced oxygen levels at high altitudes influence brain activity patterns resembling those in neurodegenerative disorders and aging, making high-altitude hypoxia a promising model for comprehending the brain in health and disease.

Exposure to high-altitude hypoxia, with reduced oxygen levels, can replicate brain function changes akin to aging and Alzheimer's disease. In our work, we propose high-altitude hypoxia as a possible reversible model of human brain aging. We gathered EEG data at high altitude and sea level, investigating the impact of hypoxia on brainwave patterns and connectivity. Our findings revealed that high-altitude exposure led to slower and noisier brain oscillations and produced altered brain connectivity, resembling some remarkable changes seen in the aging process. Intriguingly, these changes were linked to age, even when hypoxia's effects were considered. Our research unveils how high-altitude conditions emulate brain patterns associated with aging and neurodegenerative conditions, providing valuable insights into the understanding of both normal and impaired brain function.

Numerical simulation and study on heat and mass transfer in a hybrid ultrasound/convective dryer.

Susceptibility of airborne ultrasonic power to augment heat and mass transfer during hot air dehydration of peppermint leaves was investigated in the present study. To predict the moisture removal curves, a unique non-equilibrium mathematical model was developed. For the samples dried at temperatures of 40‒70 °C and the power intensities of 0‒104 kW m-3, the diffusion of moisture inside the leaves and coefficients for of mass and heat transfer varied from 0.601 × 10-4 to 5.937 × 10-4 s-1, 4.693 × 10-4 to 7.975 × 10-4 m s-1 and 49.2 to 78.1 W m-2 K-1, respectively. In general, at the process temperatures up to 60 °C, all the studied transfer parameters were augmented in the presence of ultrasonic power.

In Situ Photogenerated Radicals of Hydroxyl Substituted Pyrene-Based Triphenylamines with Enhanced Transport and Free Doping/Post-Oxidation for Efficient Perovskite Solar Cells.

The high-performance hole transporting material (HTM) is one of the most important components for the perovskite solar cells (PSCs) in promoting power conversion efficiency (PCE). However, the low conductivity of HTMs and their additional requirements for doping and post-oxidation greatly limits the device performance. In this work, three novel pyrene-based derivatives containing methoxy-substituted triphenylamines units (PyTPA, PyTPA-OH and PyTPA-2OH) are designed and synthesized, where different numbers of hydroxyl groups are connected at the 2- or 2,7-positions of the pyrene core. These hydroxyl groups at the 2- or 2,7-positions of pyrene play a significantly role to enhance the intermolecular interactions that are able to generate in situ radicals with the assistance of visible light irradiation, resulting in enhanced hole transferring ability, as well as an enhanced conductivity and suppressed recombination. These pyrene-core based HTMs exhibit excellent performance in PSCs, which possess a higher PCE than those control devices using the traditional spiro-OMeTAD as the HTM. The best performance can be found in the devices with PyTPA-2OH. It has an average PCE of 23.44% (PCEmax = 23.50%), which is the highest PCE among the reported PSCs with the pyrene-core based HTMs up to date. This research offers a novel avenue to design a dopant-free HTM by the combination of the pyrene core, methoxy triphenylamines, and hydroxy groups.

Halogenated 9H-Indeno[1,2-b]Pyrazine-2,3-Dicarbonitrile End Groups Based Asymmetric Non-Fullerene Acceptors for Green Solvent-Processable, Additive-Free, and Stable Organic Solar Cells.

Non-fullerene acceptors (NFAs) significantly enhance photovoltaic performance in organic solar cells (OSCs) using halogenated solvents and additives. However, these solvents are environmentally detrimental and unsuitable for industrial-scale production, and the issue of OSCs' poor long-term stability persists. This report introduces eight asymmetric NFAs (IPCnF-BBO-IC2F, IPCnF-BBO-IC2Cl, IPCnCl-BBO-IC2F, and IPCnCl-BBO-IC2Cl, where n = 1 and 2). These NFAs comprise a 12,13-bis(2-butyloctyl)-3,9-diundecyl-12,13-dihydro-[1,2,5]thiadiazolo[3,4-e]thieno[2'',3'':4',5']thieno[2',3':4,5]pyrrolo[3,2-g]thieno[2',3':4,5]thieno-[3,2-b]indole (BBO) core. One end of the core attaches to a mono- or di-halogenated 9H-indeno[1,2-b]pyrazine-2,3-dicarbonitrile (IPC) end group (IPC1F, IPC1Cl, IPC2F, or IPC2Cl), while the other end connects to a 2-(5,6-dihalo-3-oxo-2,3-dihydro-1H-inden-1-ylidene)malononitrile (IC) end group (IC2F or IC2Cl). The optical and electronic properties of these NFAs can be finely tuned by controlling the number of halogen atoms. Crucially, these NFAs demonstrate excellent compatibility with PM6 even in o-xylene, facilitating the production of additive-free OSCs. The di-halogenated IPC-based NFAs outperform their mono-halogenated counterparts in photovoltaic performance within OSCs. Remarkably, the di-halogenated IPC-based NFAs maintain 94‒98% of their initial PCEs over 2000 h in air without encapsulation, indicating superior long-term device stability. These findings imply that the integration of di-halogenated IPCs in asymmetric NFA design offers a promising route to efficient, stable OSCs manufactured through environmentally friendly processes.

Green hydrogen generation in alkaline solution using electrodeposited Ni-Co-nano-graphene thin film cathode.

Green hydrogen generation technologies are currently the most pressing worldwide issues, offering promising alternatives to existing fossil fuels that endanger the globe with growing global warming. The current research focuses on the creation of green hydrogen in alkaline electrolytes utilizing a Ni-Co-nano-graphene thin film cathode with a low overvoltage. The recommended conditions for creating the target cathode were studied by electrodepositing a thin Ni-Co-nano-graphene film in a glycinate bath over an iron surface coated with a thin copper interlayer. Using a scanning electron microscope (SEM) and energy-dispersive X-ray (EDX) mapping analysis, the obtained electrode is physically and chemically characterized. These tests confirm that Ni, Co, and nano-graphene are homogeneously dispersed, resulting in a lower electrolysis voltage in green hydrogen generation. Tafel plots obtained to analyze electrode stability revealed that the Ni-Co-nano-graphene cathode was directed to the noble direction, with the lowest corrosion rate. The Ni-Co-nano-graphene generated was used to generate green hydrogen in a 25% KOH solution. For the production of 1 kg of green hydrogen utilizing Ni-Co-nano-graphene electrode, the electrolysis efficiency was 95.6% with a power consumption of 52 kwt h-1, whereas it was 56.212. kwt h-1 for pure nickel thin film cathode and 54. kwt h-1 for nickel cobalt thin film cathode, respectively.

The impact of digital technology use on nurses' professional identity and relations of power: a literature review.

AIM: This study seeks to review how the use of digital technologies in clinical nursing affects nurses' professional identity and the relations of power within clinical environments. DESIGN: Literature review. DATA SOURCES: PubMed and CINAHL databases were searched in April 2023. METHODS: We screened 874 studies in English and German, of which 15 were included in our final synthesis reflecting the scientific discourse from 1992 until 2023. RESULTS: Our review revealed relevant effects of digital technologies on nurses' professional identity and power relations. Few studies cover outcomes relating to identity, such as moral agency or nurses' autonomy. Most studies describe negative impacts of technology on professional identity, for example, creating a barrier between nurses and patients leading to decreased empathetic interaction. Regarding power relations, technologically skilled nurses can yield power over colleagues and patients, while depending on technology. The investigation of these effects is underrepresented. CONCLUSION: Our review presents insights into the relation between technology and nurses' professional identity and prevalent power relations. For future studies, dedicated and critical investigations of digital technologies' impact on the formation of professional identity in nursing are required. IMPLICATIONS FOR THE PROFESSION: Nurses' professional identity may be altered by digital technologies used in clinical care. Nurses, who are aware of the potential effects of digitized work environments, can reflect on the relationship of technology and the nursing profession. IMPACT: The use of digital technology might lead to a decrease in nurses' moral agency and competence to shape patient-centred care. Digital technologies seem to become an essential measure for nurses to wield power over patients and colleagues, whilst being a control mechanism. Our work encourages nurses to actively shape digital care. REPORTING METHOD: We adhere to the JBI Manual for Evidence Synthesis where applicable. EQUATOR reporting guidelines were not applicable for this type of review. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Relationship between preinduction electroencephalogram patterns and propofol sensitivity in adult patients.

PURPOSE: To determine the precise induction dose, an objective assessment of individual propofol sensitivity is necessary. This study aimed to investigate whether preinduction electroencephalogram (EEG) data are useful in determining the optimal propofol dose for the induction of general anesthesia in healthy adult patients. METHODS: Seventy healthy adult patients underwent total intravenous anesthesia (TIVA), and the effect-site target concentration of propofol was observed to measure each individual's propofol requirements for loss of responsiveness. We analyzed preinduction EEG data to assess its relationship with propofol requirements and conducted multiple regression analyses considering various patient-related factors. RESULTS: Patients with higher relative delta power (ρ = 0.47, p < 0.01) and higher absolute delta power (ρ = 0.34, p = 0.01) required a greater amount of propofol for anesthesia induction. In contrast, patients with higher relative beta power (ρ = -0.33, p < 0.01) required less propofol to achieve unresponsiveness. Multiple regression analysis revealed an independent association between relative delta power and propofol requirements. CONCLUSION: Preinduction EEG, particularly relative delta power, is associated with propofol requirements during the induction of general anesthesia. The utilization of preinduction EEG data may improve the precision of induction dose selection for individuals.

A two-stage group-sequential design for delayed treatment responses with the possibility of trial restart.

Common statistical theory applicable to confirmatory phase III trial designs usually assumes that patients are enrolled simultaneously and there is no time gap between enrollment and outcome observation. However, in practice, patients are enrolled successively and there is a lag between the enrollment of a patient and the measurement of the primary outcome. For single-stage designs, the difference between theory and practice only impacts on the trial duration but not on the statistical analysis and its interpretation. For designs with interim analyses, however, the number of patients already enrolled into the trial and the number of patients with available outcome measurements differ, which can cause issues regarding the statistical analyses of the data. The main issue is that current methodologies either imply that at the time of the interim analysis there are so-called pipeline patients whose data are not used to make a statistical decision (like stopping early for efficacy) or the enrollment into the trial needs to be at least paused for interim analysis to avoid pipeline patients. There are methods for delayed responses available that introduced error-spending stopping boundaries for the enrollment of patients followed by critical values to reject the null hypothesis in case the stopping boundaries have been crossed beforehand. Here, we will discuss other solutions, considering different boundary determination algorithms using conditional power and introducing a design allowing for recruitment restart while keeping the type I error rate controlled.

Use of fractals in determining the malignancy degree of lung nodules.

Introduction: A Computer-Assisted Detection (CAD) System for classification into malignant-benign classes using CT images is proposed. Methods: Two methods that use the fractal dimension (FD) as a measure of the lung nodule contour irregularities (Box counting and Power spectrum) were implemented. The LIDC-IDRI database was used for this study. Of these, 100 slices belonging to 100 patients were analyzed with both methods. Results: The performance between both methods was similar with an accuracy higher than 90%. Little overlap was obtained between FD ranges for the different malignancy grades with both methods, being slightly better in Power spectrum. Box counting had one more false positive than Power spectrum. Discussion: Both methods are able to establish a boundary between the high and low malignancy degree. To further validate these results and enhance the performance of the CAD system, additional studies will be necessary.

A numerical approach to optimize the performance of HTL-free carbon electrode-based perovskite solar cells using organic ETLs.

Carbon electrode-based perovskite solar cells (c-PSCs) without a hole transport layer (HTL) have obtained a significant interest owing to their cost-effective, stable, and simplified structure. However, their application is limited by low efficiency and the prevalence of high-temperature processed electron transport layer (ETL), e.g. TiO2, which also has poor optoelectronic properties, including low conductivity and mobility. In this study, a series of organic materials, namely PCBM ((Park et al., 2023; Park et al., 2023) [6,6]-phenyl-C61-butyric acid methyl ester, C72H14O2), Alq3 (Al(C9H6NO)3), BCP (2,9-Dimethyl-4,7-diphenyl-1,10-phenanthroline, C26H20N2), C60, ICBA (indene-C60 bisadduct, C78H16) and PEIE (poly (ethylenimine) ethoxylated, (C37H24O6N2)n) have been numerically analyzed in SCAPS-1D solar simulator to explore alternative potential ETL materials for HTL-free c-PSCs. The presented device has FTO/ETL/CH3NH3PbI3/carbon structure, and its performance is optimized based on significant design parameters. The highest achieved PCEs for PCBM, Alq3, BCP, C60, ICBA, and PEIE-based devices are 22.85%, 19.08%, 20.99%, 25.51%, 23.91%, and 22.53%, respectively. These PCEs are obtained for optimum absorber thickness for each case, with an acceptor concentration of 1.0 × 1017 cm-3 and defect density of 2.5 × 1013 cm-3. The C60-based cell has been found to outperform with device parameters as Voc of 1.29 V, Jsc of 23.76 mA/cm2, and FF of 82.67%. As the design lacks stability when only organic materials are employed, each of the presented devices have been analyzed by applying BiI3, LiF, and ZnO as protective layers with the performances not compromised. We believe that our obtained results will be of great interest in developing stable and efficient HTL-free c-PSCs.

Competitive organizational climate and artificial intelligence (AI) acceptance: the moderating role of leaders' power construal.

Introduction: The incorporation of Artificial Intelligence (AI) in organizations is pivotal to deal with work-related tasks and challenges effectively, yet little is known about the organizational factors that influence AI acceptance (i.e., employee favorable AI attitudes and AI use). To address this limitation in the literature and provide insight into the organizational antecedents influencing AI acceptance, this research investigated the relationship between competitive organizational climate and AI acceptance among employees. Moreover, given the critical role of a leader in employee attitude and behavior, we examined the moderating role of leaders' power construal as responsibility or as opportunity in this relationship. Methods: Study 1 was a three-wave field study among employees (N = 237, Mage = 38.28) working in various organizations in the UK. The study measured employees' perception of a competitive organizational climate at Time 1, leaders' power construal (as perceived by employees) at Time 2, and employee attitudes towards AI and their actual use of AI in the workplace at Times 2 and 3. Study 2 was a 2 (climate: highly competitive vs. low competitive) by 2 (power construal: responsibility vs. opportunity) experiment among employee participants (N = 150, Mage = 37.50). Results: Study 1 demonstrated a positive relationship between competitive climate and employee AI use over time. Furthermore, both studies revealed an interaction between competitive climate and leader's power construal in the prediction of employee AI acceptance: In Study 1, competitive climate was negatively related to AI acceptance over time when leaders construed power as opportunity. In Study 2 competitive climate was positively related to AI acceptance when leaders construed power as responsibility rather than as opportunity. Discussion: These results underscore the organizational factors that are required in order for employees to shape favorable attitudes towards AI and actually use AI at work. Importantly, this research expands the limited body of literature on AI integration in organizations.

Disparities with global standards about growth references of mid-upper arm circumference-for-age for Pakistani children aged 6-60 months.

AIM: Growth reference values about mid-upper arm circumference (MUAC) are vital for assessing children's nutritional status. However, Pakistan lacks these reference values and growth charts. This study aims to develop these for children aged 6-60 months and compare them with global standards. METHODS: The data were acquired from the 2018 National Nutrition Survey of Pakistan, which was conducted by the United Nations Children's Fund (UNICEF) during 2018-2019. The final study cohort comprised 57 285 children, with 51% being boys. Percentile values and charts for MUAC-for-age were developed using generalised additive models for location, scale and shape with the Box-Cox power exponential distribution. RESULTS: The mean MUAC was 14.21 cm (±2.07 cm) and 14.13 cm (±2.12 cm) for the boys and girls, respectively. At 60 months of age, the P3 and P97 percentiles for girls were slightly higher than those for boys. The median percentiles of Pakistani children were smaller than the World Health Organisation 2007 standards and with international references. CONCLUSION: We observed disparities in MUAC-for-age growth references among Pakistani children compared to global standards, highlighting regional, age and gender variations. This underscores the need for developing countries like Pakistan to establish their growth references.

An H2O2 Self-Charging Zinc Battery with Ultrafast Power Generation and Storage.

Self-charging power systems are considered as promising alternatives for off-grid energy devices to provide sustained electricity supply. However, the conventional self-charging systems are severely restricted by the energy availability and time-consuming charging process as well as insufficient capacity. Herein, we developed an ultrafast H2O2 self-charging aqueous Zn/NaFeFe(CN)6 battery, which simultaneously integrates the H2O2 power generation and energy storage into a battery configuration. In such battery, the chemical energy conversion of H2O2 can generate electrical energy to self-charge the battery to 1.7 V through the redox reaction between H2O2 and NaFeFe(CN)6 cathode. The thermodynamically and kinetically favorable redox reaction contributes to the ultrafast H2O2 self-charging rate and the extremely short self-charging time within 60 seconds. Moreover, the rapid H2O2 power generation can promptly compensate the energy consumption of battery to provide continuous electricity supply. Impressively, this self-charging battery shows excellent scalability of device architecture and can be designed to a H2O2 single-flow battery of 7.06 Ah to extend the long-term energy supply. This work not only provides a route to design self-charging batteries with fast charging rate and high capacity, but also pushes forward the development of self-charging power systems for advanced large-scale energy storage applications.

Cost and environmental analysis and optimization of a new and green three-level waste heat recovery-based cogeneration cycle: A comparative study.

Effective and maximum utilization of waste heat from industrial processes and fossil plants can improve thermodynamic performance and declined the environmental impacts of waste heat discharge to the atmosphere. Here, the multi-aspect assessment and optimization of a novel cogeneration power and cooling load cycle (CPCC) is developed. The considered cogeneration process is designed under a three-level waste heat recovery process consisting of an ORC (organic Rankine cycle) unit and an ejection-based refrigeration process. Thermodynamic performance, cost feasibility and environmental assessments of the suggested process have been comprehensively evaluated and discussed. A two-objective optimization is developed to minimize the total cost and maximize the exergy efficiency. Moreover, the comprehensive CPCC behavior is compared with a reference system (a single-level recovery/ORC process and a compression-based refrigeration process). The performance of the considered CPCC is also examined under various environmentally compatible refrigerants. The environmental analysis is based on two indicators (i.e., life cycle-climate performance and total equivalent-warming impacts). Due to the multi-level recovery of waste heat, the environmental impacts of emitting waste heat into the environment are significantly reduced. The outcomes revealed that the R1234/yf is considered as the most suitable refrigerant that can causes to optimum achievements for both systems. The exergetic performance is improved by about 10.3% compared to that reference system, while the exergy destruction and total annual cost of the CPCC, respectively, are reduced by approximately 7.4% and 21.6% compared to the reference cycle. It was also found that about 11,640 tons of carbon dioxide can be reduced by using the ejector in the refrigeration process.

Ultrastrong and Reusable Solar‒Thermal‒Electric Generators by Economical Starch Vitrimers.

In frigid regions, it is imperative to possess functionality materials that are ultrastrong, reusable, and economical, providing self-generated heat and electricity. One promising solution is a solar‒thermal‒electric (STE) generator, composed of solar‒thermal conversion phase change composites (PCCs) and temperature-difference power-generation-sheets. However, the existing PCCs face challenges with conflicting requirements for solar‒thermal conversion efficiency and mechanical robustness, mainly due to monotonous functionalized aerogel framework. Herein, a novel starch vitrimer aerogel is proposed that incorporates orientational distributed carboxylated carbon nanotubes (CCNT) to create PCC. This innovative design integrates large through-holes, mechanical robustness, and superior solar‒thermal conversion. Remarkably, PCC with only 0.8 wt.% CCNT loading achieves 85.8 MPa compressive strength, 102.4 °C at 200 mW cm-2 irradiation with an impressive 92.9% solar-thermal conversion efficiency. Noteworthy, the STE generator assembled with PCC harvests 99.1 W m-2 output power density, surpassing other reported STE generators. Strikingly, even under harsh conditions of -10 °C and 10 mW cm‒2 irradiation, the STE generator maintains 20 °C for PCC with 325 mV output voltage and 45 mA current, showcasing enhanced electricity generation in colder environments. This study introduces a groundbreaking STE generator, paving the way for self-sufficient heat and electricity supply in cold regions.

Emerging Vanadium-Doped Cobalt Chloride Carbonate Hydroxide for Flexible Electrochromic Micro-Supercapacitor: Charged-State Prediction from RGB Input by ANN Model.

Multifunctional devices integrated with electrochromic and supercapacitance properties are fascinating because of their extensive usage in modern electronic applications. In this work, vanadium-doped cobalt chloride carbonate hydroxide hydrate nanostructures (V-C3H NSs) are successfully synthesized and show unique electrochromic and supercapacitor properties. The V-C3H NSs material exhibits a high specific capacitance of 1219.9 F g-1 at 1 mV s-1 with a capacitance retention of 100% over 30 000 CV cycles. The electrochromic performance of the V-C3H NSs material is confirmed through in situ spectroelectrochemical measurements, where the switching time, coloration efficiency (CE), and optical modulation (∆T) are found to be 15.7 and 18.8 s, 65.85 cm2 C-1 and 69%, respectively. A coupled multilayer artificial neural network (ANN) model is framed to predict potential and current from red (R), green (G), and blue (B) color values. The optimized V-C3H NSs are used as the active materials in the fabrication of flexible/wearable electrochromic micro-supercapacitor devices (FEMSDs) through a cost-effective mask-assisted vacuum filtration method. The fabricated FEMSD exhibits an areal capacitance of 47.15 mF cm-2 at 1 mV s-1 and offers a maximum areal energy and power density of 104.78 Wh cm-2 and 0.04 mW cm-2, respectively. This material's interesting energy storage and electrochromic properties are promising in multifunctional electrochromic energy storage applications.

Is renewable energy development endangering power supply reliability?

The development of renewable energy is indispensable to promoting the low-carbon transition of power systems. Nevertheless, it also brings uncertainty to the reliability of power systems. Herein, the panel model and panel threshold model are established based on the provincial data in China from 2012 to 2020. The results reveal that the negative effect of renewable energy development (RED) on power supply reliability (PSR) is gradually lessening. If the development of renewable energy is a rational way, power supply reliability can be improved. Additionally, energy-exporting regions bear more risks of RED than energy-importing regions. If the coal prices are stable and natural disasters are manageable, the RED can enhance the PSR. However, if they are not stable or controllable, a high proportion of renewable energy in the power system could cause even more severe problems with PSR. Based on these critical results, some suggestions are made to promote the formation of a new power system.