Deep Level Research Articles

A Study on the Key Factors for the Sustainable Development of Shared Mobility Based on TDM Theory: The Case Study from China

This study is based on an investigation of shared mobility in Chinese cities, which identifies the factors affecting the sustainable development of shared mobility based on the theoretical framework of TDM (travel demand management). Through a literature review and expert interviews, the FUZZY-DEMATEL-ISM-MICMAC integration model was used to screen 21 influencing factors from aspects that fit the research theme. Triangular fuzzy numbers are used to quantify the subjective scores of nine expert groups and weaken the subjective influence of expert scores. The logical relationships among DEMATEL technology-building factors and ISM technology-based factors are divided into levels. The MICMAC technique is used to divide the types of factors according to the driving power and dependency. The results show that (1) the influence factors of the “soft strategy” and “hard strategy” in the framework of TDM are determined. In the soft strategy, we should focus on “shared mobility education” (shared mobility education, shared mobility publicity and shared mobility “environment” information) and “community organization” (community organization and advocacy and organizational interaction). In the hard strategy, we should focus on “traffic planning and measures”, “dedicated lanes”, “parking facilities”, and “financial subsidies”. (2) The ISM recursive structure model is divided into five layers. Among them, shared mobility education, shared mobility operating technology, and organizational interaction are at the deep root level, which can continuously influence other factors in the long run. (3) In MICMAC, the number of related factors is large. When making decisions on these factors, managers should comprehensively consider the correlation of factors and adjust the use of factors from an overall perspective. This study can help managers identify the key factors affecting the sustainability of shared mobility and make targeted recommendations.

Exploring the Impact of Animal Assisted Interventions on the Occupational Participation of People Living with Dementia

Abstract Background Animal Assisted Intervention (AAI) is defined as a goal-directed intervention designed to promote improvement in social, emotional, physical and cognitive functioning (AAII 2020). AAIs are a growing area in dementia research and practice (Lai et al. 2019). There is a significant gap in implementing and researching AAI in a UK context (Fine 2019). Caring for pets and service animals is considered an instrumental activity of daily living (AOTA 2008) and AAI has been shown to enhance the occupational participation of other client populations (Winkle et al. 2012; Herlache-Pretzer et al. 2017; Andreasen et al. 2017). It is unclear what impact AAI has on the occupational participation of people living with dementia (PLWD). Methods Interpretative Phenomenological Analysis was proposed to facilitate deep level interpretations of the experience of occupational participation for PLWD who have an assistance dog. Over a two-month period, the researcher proposed to complete four thirty-minute video observations capturing PLWD participating in a chosen occupation in their home environment. The researcher further proposed to maintain a reflexive journal and document notable observations throughout the research process to enhance the development of themes. Results PLWD have the right to access personally meaningful occupations (WFOT 2006). Assistance dogs may have the potential to facilitate positive occupational experiences such as occupational identity, occupational competence and occupational adaptation. Conclusion Occupational therapists who claim to be guided by the principals of client-centred practice (RCOT 2015a) must strive to look beyond traditional interventions to effectively meet the individual needs and preferences of PLWD (Brodrick and Barry 2016). Education and further research (Fine 2019) are required to raise the profile of AAI in a UK context. Future research would benefit from exploring the experience of occupational participation in social environmental contexts for PLWD (who have an assistance dog), to gain whole experiential accounts of this phenomenon.

Development of Two Novel Dibenzosilole-Based Conjugated Polymers with Thieno[3,4-c]pyrrole-4,6-dione for Use in Polymer Solar Cells

The donor-acceptor (D-A) strategy has proven to be one of the most effective methods for tuning the band gaps, absorption characteristics, and optoelectronic properties in conjugated polymers. Two novel D-A conjugated polymers, PDBSTPD-1T and PDBSTPD-2T, were synthesized using dibenzosilole (DBS) and thieno[3,4-c]pyrrole-4,6-dione (TPD) as the building blocks. These polymers were linked through either a single thiophene or two thiophene rings as π-bridges and were copolymerized using a Suzuki coupling reaction. The effect of the incorporation of the different π-bridges on the electrical/optical properties of the prepared copolymers was also investigated. The synthesized polymers, PDBSTPD-1T and PDBSTPD-2T, were soluble in organic solvents and demonstrated high molar mass along with excellent thermal stability. The conjugation of the electron-accepting TPD unit with the electron-donating DBS unit produced relatively deep HOMO levels, which were fine-tuned to be −5.44 and −5.36 eV via the addition of the different π-bridges. PDBSTPD-1T and PDBSTPD-2T displayed absorption wavelengths between 350 and 650 nm with high Eg opt of 2.01 and 1.97 eV, respectively. X-ray diffraction analysis presented several diffraction peaks, and the π-π stacking distances of PDBSTPD-1T and PDBSTPD-2T were 3.45 and 3.65°A, respectively.

The influence of sleep education supported and unsupported with social media reminders on the sleep quality in adolescents aged 14-18: a three-center, parallel-arm, randomized controlled study.

Poor sleep quality is a global health problem for adolescent. The aim of this study was to examine how sleep education, with or without social media reminders, affects sleep quality in adolescents aged 14 to 18. The study was a three-center, parallel-arm, randomized controlled study, recruiting participants from September 9, 2019, to January 6, 2020. Adolescents with poor sleep quality and sleepiness, using smartphones apps and internet browser, without chronic diseases, and obesity, and without mental problems were included in the study. Primary outcomes were sleep quality, sleepiness, sleep hygiene, and sleep parameters at week 5 as measured by subjective report scales and actigraphy. Sleep quality was measured by the Pittsburgh Sleep Quality Index (Poor sleep quality = PSQI > 5), sleepiness by the Cleveland Adolescent Sleepiness Questionnaire (CASQ > 16), and sleep hygiene developed by the researchers in the literature of Adolescent Sleep Habits Form. A total of 55 participants (mean [SD] age, 15.64 [1.22] years) participated. PSQI and CASQ scores of adolescents in sleep education that were not supported by social media reminders decreased compared to the baseline (p = 0.01, p = 0.02). Adolescent PSQI score in sleep education supported by social media reminders decreased from baseline, their sleep hygiene score increased (p = 0.02). There were no significant differences between the groups in terms of sleep parameters (total sleep duration, deep and light sleep levels, nighttime sleeping, and morning wake-up times) (p > 0.05). This study suggests that sleep education, supported by reminders via social media, can be used to improve the quality of sleep of adolescents. ClinicalTrials.gov Identifier: NCT05071989.

Abstract B164: Sustaining statewide transdisciplinary collaborations to address cancer disparities

Abstract Background: Wisconsin’s cancer disparities are evident when considered by race/ethnicity, geography, and socio-economic status. Addressing these disparities requires deeper integration of social and scientific problem-solving and a systems approach. Given the nature of disparities, it also demands that we not just seek equitable outcomes but collaborate in ways that reflect equity in the process. To achieve this, we developed a transdisciplinary approach inclusive of community, clinicians, and researchers and builds capacity to understand, at a deep level, factors that underpin disparities and design newer sustainable solutions. Methods: The Community and Cancer Science Network (CCSN) Integration Hub was established within the Medical College of Wisconsin Cancer Center to provide leadership and capacity building to eight transdisciplinary teams working to address cancer disparities. The Integration Hub and its teams use a co- leadership structure with a community and academic PI as well as a facilitator and evaluator. The Integration Hub has four primary strategies: identifying and addressing knowledge gaps in cancer disparities, building capacity for transdisciplinary collaboration, cultivating networks and relationships, and disseminating through feedback loops that touch communities, academic medicine, and policy. Our approach is grounded in the principles of deep equity, considerations across the biology to policy spectrum, and systems thinking. Results: In its third year, CCSN adapted and adopted tools to understand its effectiveness in building a collaborative environment for transdisciplinary approaches to problem-solving and to set strategy for sustainability. Results from a partner survey administered to team members (n=73) highlighted that the CCSN model contributes to fostering learning conditions that support a strong transdisciplinary approach including a supportive learning environment, concrete learning practices, leadership that reinforces learning and a reflection of core principles as well as embedding a transdisciplinary orientation in team members. The Integration Hub leadership also completed the Organizational Mapping Tool for Coalitions, Alliances and Networks (OMT-CAN) to assess critical dimensions of network health. The assessment helps identify strengths and identify areas for improvements. CCSN network leaders (n=21) rated the network moderate to strong in culture and relationships; joint action, planning, learning and evaluation; and in purpose, goals and strategy. The team further identified the need to work on refining structure, identity and participation; its capacity for strategic communications; and advocacy and organizing. Discussion: To integrate social and scientific problem-solving and address cancer disparities requires the resourcing of credible capacity building networks that can broker equitable relationships between academic medicine and community members and organizations. The CCSN Integration Hub offers a strong model embedded within a cancer center that accomplishes those goals. Citation Format: Tobi Cawthra, Laura Pinsoneault, Kristen Gardner-Volle, Alexis Krause, Kim Kinner, Melinda Stolley. Sustaining statewide transdisciplinary collaborations to address cancer disparities [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B164.

Abstract C011: The Critical Role of Developmental Evaluation in Supporting and Enhancing an Equitable Transdisciplinary Approach to Address Cancer Disparities

Abstract Background: Complex problems such as cancer disparities require deeper integration of social and scientific problem-solving and a broader systems approach. Given the nature of disparities, it also demands that we not just seek equitable outcomes but collaborate in ways that reflect equity in the process. To address breast and lung cancer disparities, we developed a unique transdisciplinary approach that creates teams inclusive of community, clinicians, and researchers and builds capacity to understand at a deep level the factors that underpin disparities and design and implement newer sustainable solutions. Methods: This study focuses on a phase I planning period for a transdisciplinary process with five teams locally embedded where lung and breast cancer disparities are significant. A leadership team that included primary investigators from academic medicine and public health supported community-based facilitators and evaluators responsible for guiding local teams. Deep equity, considerations on the biology to policy spectrum, and systems thinking are grounding principles in our approach. At the end of phase I, an evaluator facilitated After-Action Reviews (AAR) to assess effectiveness in maintaining fidelity to the framework and to identify successful practices and areas for improvement. These data informed changes to our approach to implementation to further root our commitment to equity during implementation. Seven AAR sessions were conducted: individual teams members, facilitators and evaluators, and the leaderships team (n-=50). The evaluator triangulated the data from the different AARs and facilitated a discussion of the integrated findings to the expanded leadership team. Results: The AAR highlighted three primary themes for critical self-reflection including (1) strengthening the understanding and use of our approach, (2) reducing ambiguity while preserving slack (e.g. flexibility with resources) and creativity, and (3) integrating project’s partners intentionally into our wider transdisciplinary network. In examining these themes, we identified several strategies for improving our transdisciplinary approach during implementation and for wider replication of our framework with future integrated science-social problem solving. These areas included improved systems for 360-degree communication, clear expectations of roles, and additional support for transdisciplinary collaboration and application of grounded principles to better self-organize a transdisciplinary system within a wider less resilient system like academic medicine. Discussion: To successfully innovate socially and scientifically within complexities of cancer disparities, we need to push beyond conventional models of research and program intervention. This means incorporating methods across fields and sectors including evaluation. An After-Action Review is an effective evaluation tool for assessing a complex process with numerous contributors to ensure a stronger outcome including more refined and relevant research questions and sustainability program, policy and practice. Citation Format: Tobi Cawthra, Laura Pinsoneault, Jerica Broeckling, Kristen Gardner-Volle, Tim Meister, Kailey Taebel, Jada Proctor, Felicia Fairfield, Kelly Hackett, David Frazer, Staci Young, Melinda Stolley. The Critical Role of Developmental Evaluation in Supporting and Enhancing an Equitable Transdisciplinary Approach to Address Cancer Disparities [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C011.

Characterization Study of Deep-Level Defect Spatial Distribution, Emission Mechanisms, and Structural Identification

Abstract The characterization of defects in semiconductor materials and devices is crucial for enhancing the performance and reliability of semiconductor products. This tutorial review focuses on Deep Level Transient Spectroscopy (DLTS) as the primary analytical tool, thoroughly discussing its distinct advantages in deep-level defect characterization. However, it is unable to reveal the concentration-depth distribution of deep-level defects, neglects the dependency of carrier emission rates on the electric field, and fails to accurately identify defect structures.
To overcome these limitations, two enhanced DLTS techniques have been developed to extend the capabilities of DLTS. These enhancements include the utilization of graded fill pulse technology to accurately map defect distributions at various depths within devices, facilitating individual defect characterization across different layers of multilayered structures; the application of varying electric field strengths to samples to delve into the intricate physical mechanisms of defects during carrier emission processes; and the adjustment of the duration of electric pulse injection to monitor signal growth trends, deducing the microstructure of defects. The paper integrates research findings from a wide array of field experts, meticulously outlines a description of how to obtain the depth distribution of defect concentration in devices, furnishes quantitative criteria for both the Poole-Frenkel effect and phonon-assisted tunneling mechanisms of carrier emission, and provides specific examples for distinguishing between interface states/bulk defects and point defects/extended defects. This enhances both the theoretical and practical knowledge in this field. The advanced DLTS techniques outlined provide crucial guidance for defect characterization and performance optimization in semiconductor devices with new structures and materials.

Darker Patterns? AI-generated Persuasion and the Regulatory Void in Indian Law

Increased time spent by users in virtual environments globally coupled with the choice architectures created by artificial intelligence (AI) systems within these virtual environments means that the AI systems can ‘persuade’ users to take certain actions or abstain from them. In this article, we address this issue through the lens of ‘dark patterns’. Dark patterns are features of the user interface that shape the actions of the users in different ways, getting them to act in ways that they might not act otherwise and that are not necessarily beneficial for them. Recently, regulatory action has been undertaken in various jurisdictions to contain the menace of dark patterns, including in India. But can these measures prevent dark patterns that are powered by AI systems? In this article, we argue that they cannot, as AI-powered dark patterns work at a deep level of behavioural change, making users’ choices appear uninfluenced by manipulation. The laws pertaining to unfair trade practices, transparency and labelling obligations are also not sufficient to deal with these problems. We conclude with an appeal for a holistic approach to AI-powered dark patterns that engage in persuasive behaviour.

Sn2+/Pb2+ Doping‐Induced Highly Transparent Boroaluminate Microcrystalline Glass With Deep Traps for Long‐Term Optical Storage and Time‐Lapse X‐ray Imaging

AbstractThe development of microcrystalline glass‐ceramics with high transparency and deep trap energy levels is crucial for the cost‐effective and large‐scale production of scintillators and optical data storage applications. In this study, the incorporation of highly electronegative divalent tin (Sn2+) plays a key role in modulating the network structure of borate glass. This leads to the successful synthesis of SrAl2O4:Eu2+ microcrystalline glass with high transparency, reaching up to 80%, and excellent crystallinity. Additionally, a series of non‐optically active ions with different valence states is co‐doped with Eu2+ to fine‐tune the trap levels of the SrAl2O4 microcrystals. All samples maintain high crystallinity and exhibit good transparency. In particular, the Pb2+ ion co‐doped samples achieve an increased trap energy level of 1.28 eV, significantly enhancing their capacity to capture X‐rays and ultraviolet light. Density functional theory calculations reveal that this enhancement is due to severe lattice distortion caused by Pb2+ ions occupying interstitial sites in SrAl2O4. Utilizing the SrAl2O4:Eu2+, Pb2+ glass‐ceramics materials, X‐ray imaging with a delay of up to 210 s and optical information storage for >60 d is achieved. This study provides valuable insights into the crystal growth and trap modulation of persistent luminescent materials within a three‐dimensional glass network structure.

Seawater temperature drives the diversity of key cyanobacteria (Synechococcus and Prochlorococcus) in a warming sea

The picocyanobacteria genera Prochlorococcus and Synechococcus play a significant role globally, dominating the primary production in warm and oligotrophic tropical and subtropical areas, which represent the largest oceanic ecosystem. Genomic studies have revealed high microdiversity within these genera. It is anticipated that ocean warming may cause decreased biodiversity in marine tropical areas, as increasing temperatures may lead to the development of a new thermal niche in these regions. Thus, our study aimed to characterize the microdiversity of picocyanobacteria in the Red Sea, one of the warmest oligotrophic seas on the planet, which is experiencing warming at a rate that exceeds the global average. We identified picocyanobacteria microdiversity in the open waters of the Eastern Red Sea basin, where seawater temperatures ranged from 22.2 to 32.4°C throughout the water column (from surface to 160 m depth). Both Prochlorococcus and Synechococcus populations were characterized to deep taxonomic levels, applying amplicon sequencing targeting the petB gene, revealing up to 15 different (sub)clades. Synechococcus dominated the basin, representing an average of 68.8% of the total reads assigned to both cyanobacteria. The subclade Synechococcus IIa and Prochlorococcus clade HLII were ubiquitous in the water column of the Eastern Red Sea basin, representing 73% and 56% of the Synechococcus and Prochlorococcus assigned reads, respectively. Maximum cyanobacteria richness was observed at approximately 27.5°C, declining at higher and lower temperatures (polynomial fit, R2 = 0.2, p<0.0001). Synechococcus IIa dominated in the warmest surface waters (>30°C) of the Red Sea, displacing other (sub)clades to more saline and nutrient-poor waters, thereby reducing community diversity (polynomial fit, R2 = 0.77, p<0.0001). Our study contributes to identifying changes in picocyanobacterial diversity when exposed to temperatures exceeding current oceanic thermal limits, through the analysis of Red Sea communities already inhabiting such higher-temperature niches.

Optical and electrical studies on the TS defect in 4H-SiC

Abstract When annealing a 4H silicon carbide (SiC) crystal, a sequence of optically active defect centers
occurs among which the TS center is a prominent example. Here, we present low-temperature photoluminescence
analyses on the single defect level. They reveal that the three occurring spectral
signatures TS1, TS2 and TS3 originate from one single defect. Their polarization dependences expose
three different crystallographic orientations in the basal plane, which relate to the projections of
the nearest neighbor directions. Accordingly, we find a three-fold level-splitting in ensemble studies,
when applying mechanical strain. This dependency is quantitatively calibrated. A complementary
electrical measurement, deep level transient spectroscopy, reveals a charge transition level of the TS
defect at 0.6 eV above the valence band. For a future identification, this accurate characterization
of its optical and electronic properties along with their response to mechanical strain is a milestone.

Pushing the Limits of Photoconductivity via Hot Electrons in Deep Trap States in Plasmonic Architectures.

Although extensive research on the mechanisms of photoconductivity enhancement in plasmonic Schottky structures has been conducted, the photoconductive interplay between hot electrons and trapping states remains elusive. In this study, we explored the photoconductive relationship between plasmonic hot-carriers and defect sites present in plasmonic architectures consisting of N-face n-GaN and Au nanoprisms. Our experimental results clearly verified that the plasmonic hot-electrons generated by interband transitions preferentially occupied deep trap levels in n-GaN, thereby considerably enhancing the photoconductivity through the combination of photogating and photovoltaic effects. Our quantitative evaluation demonstrated that a mere 63% increase in hot-electron trapping leads to a 1.7-fold increased photocurrent under localized surface plasmon resonance (LSPR) excitation compared to the figure of photocurrent under non-LSPR stimulus. Our findings provide novel insights into the mechanisms of photoconductive enhancement for advanced plasmonic applications.

Long-term carrier lifetime instabilities in n-type FZ- and Cz-silicon under illumination at elevated temperature

Even though n-type Si wafers show a lower extent of light-induced degradation, similar degradation and regeneration behavior as in p-type Si materials has been observed for various n-type Si monocrystalline materials. In this work, the long-term behavior of minority charge carrier lifetime in non-diffused n-type FZ-Si and Cz-Si wafers during illumination at elevated temperatures is investigated. Thereby, various influencing factors such as peak firing temperature and treatment temperature are considered. Degradation and a very strong regeneration effect, which exceeds the initial effective lifetime value, can be observed in the samples. Since surface-related saturation current density remains almost constant during degradation and regeneration, the effect seems to be bulk related. The extent of degradation and regeneration could be shown to be firing temperature-dependent. It could also be shown for n-type FZ-Si wafers that higher firing temperatures result in an increased H2 content within the silicon bulk. Investigations of the injection-dependent defect density revealed that the defect formed during degradation is not a deep level Shockley-Read-Hall defect. Observations at different treatment temperatures and constant illumination of 0.9(1) sun photon flux equivalent have shown that a higher treatment temperature leads to faster degradation and regeneration kinetics. Similarly, higher injection rates also speed up regeneration kinetics. Since degradation also occurs in darkness, the bulk related degradation effect in n-type FZ-Si is charge carrier-induced and not necessarily light-induced.

The ab initio study of n-type nitrogen and gallium co-doped diamond

Abstract In order to better understand the influence of different complexes on the diamond co-doping system, N and Ga are chosen as co-dopants in diamond. The properties of several substitutional NmGan (m+n <= 3) complexes with vacancy (Va) in the bulk diamond have been investigated by ab initio density functional technique, including their optimized lattice structures, formation energies, binding energies and thermodynamic transition levels. The calculational results show that NmGan complexes in the donor-acceptor-donor (DAD) configuration can provide ionization energies similar to phosphorus-doped diamond. All other complexes provide deep impurity levels. For the DAD configuration, the adsorption process on the diamond surface has been studied to demonstrate the feasibility of growing diamonds containing N-Ga-N in experiments. The desired complex configuration is not uniquely present in the co-doped system. Investigating these properties of different complexes beyond NGaN provides insight into the N and Ga codoped diamond system, yielding a more comprehensive understanding of its potential and limitations. Our research ideas can also be extended to other co-doped systems and help to evaluate other potential co-dopants for diamond.

Sub-bandgap excited photoluminescence probing of deep defect complexes in GaN doped by Si, Ge and C impurities

Abstract With the sub-bandgap optical excitation, thermal dynamics of holes among multiple levels in n-type GaN epilayers with different dopants of Si, Ge and C are investigated via measuring and modelling variable-temperature yellow luminescence (YL) band of the samples. In sharp contrast to the case of above-bandgap optical excitation, the variable-temperature YL band of all the studied GaN samples including unintentionally-doped sample exhibit unusual negative thermal quenching (NTQ) behavior, suggesting a possible physical mechanism, namely thermally induced migration of holes from shallower levels to the luminescent deep level. By considering the possible presence of multiple hole levels in the doped GaN samples, a phenomenological model is developed for the thermal transfer of holes among the multi-levels and the interpretation of the observed NTQ phenomenon of the YL band. Different activation energies of 347.9, 520.8 and 348.5 meV are obtained for the Ge-doped, high C-containing, and Si-doped GaN samples, respectively. The results reveal the existence of multiple hole defect levels in the n-type GaN. Possible microstructural origins causing these different hole levels are further argued. The study may shed some light on the nature of various defect complexes in the technologically important GaN epilayers. Combined microstructural and optical investigations need to be further done for elucidating various optically- and electrically-active defect complexes in GaN.

A Novel Network for Low-Dose CT Denoising Based on Dual-Branch Structure and Multi-Scale Residual Attention.

Deep learning-based denoising of low-dose medical CT images has received great attention both from academic researchers and physicians in recent years, and has shown important application value in clinical practice. In this work, a novel two-branch and multi-scale residual attention-based network for low-dose CT image denoising is proposed. It adopts a two-branch framework structure, to extract and fuse image features at shallow and deep levels respectively, to recover image texture and structure information as much as possible. We propose the adaptive dynamic convolution block (ADCB) in the local information extraction layer. It can effectively extract the detailed information of low-dose CT denoising and enables the network to better capture the local details and texture features of the image, thereby improving the denoising effect and image quality. Multi-scale edge enhancement attention block (MEAB) is proposed in the global information extraction layer, to perform feature fusion through dilated convolution and a multi-dimensional attention mechanism. A multi-scale residual convolution block (MRCB) is proposed to integrate feature information and improve the robustness and generalization of the network. To demonstrate the effectiveness of our method, extensive comparison experiments are conducted and the performances evaluated on two publicly available datasets. Our model achieves 29.3004 PSNR, 0.8659 SSIM, and 14.0284 RMSE on the AAPM-Mayo dataset. It is evaluated by adding four different noise levels σ = 15, 30, 45, and 60 on the Qin_LUNG_CT dataset and achieves the best results. Ablation studies show that the proposed ADCB, MEAB, and MRCB modules improve the denoising performances significantly. The source code is available at https://github.com/Ye111-cmd/LDMANet .

Empowering Educators: The Impact of Reverse Mentoring on Developing Scientific Mindset and Research Skills

The integration of educational research into teaching practice is an important component in fostering the professional development of educators. Recognizing mentoring activities as an effective method for fostering such research-driven teaching practice, this study set out to explore the effectiveness of reverse mentoring in cultivating a scientific mindset and enhancing research skills among school-based teacher educators. The defining feature of reverse mentoring is the reversal of the mentor and mentee roles, with student teachers mentoring school-based teacher educators. These school-based teacher educators here represent in-service teachers who teach in schools on a daily basis while simultaneously supporting the training of future teachers. Through a semi-structured interview study, nine reverse mentoring projects implemented in Austria and Greece were analyzed. The findings highlight the importance of the thematic focus of the reverse mentoring projects, motivations for participation, insights into collaboration dynamics, learning outcomes, and suggestions for process improvement. Learning outcomes are reported in new teaching methods, content knowledge, and improved collaboration capabilities. A framework categorizing reverse mentoring collaboration into basic, guided, and deep levels is discussed. Suggestions for further research are provided to validate and expand upon the findings of this study.

Analysis of deep level defects in nitrogen post-deposition annealed Ga2O3/SiC hetero-structured Schottky diodes grown by mist-CVD

Analysis of deep level defects in nitrogen post-deposition annealed Ga2O3/SiC hetero-structured Schottky diodes grown by mist-CVD

Metal Oxide vs Organic Semiconductor Charge Extraction Layers for Halide Perovskite Indoor Photovoltaics

Halide perovskite indoor photovoltaics (PVs) are highly promising to autonomously power the billions of microelectronic sensors in the emerging and disruptive technology of the Internet of Things (IoT). However, how the wide range of different types of hole extraction layers (HELs) impacts the indoor light harvesting of perovskite solar cells is still elusive, which hinders the material selection and industrial‐scale fabrication of indoor perovskite photovoltaics. In the present study, new insights are provided regarding the judicial selection of HELs at the buried interface of halide perovskite indoor photovoltaics. This study unravels the detrimental and severe light‐soaking effect of metal oxide transport layer‐based PV devices under the indoor lighting effect for the first time, which then necessitates the interface passivation/engineering for their reliant performance. This is not a stringent criterion under 1 sun illumination. By systematically investigating the charge carrier dynamics and sequence of measurements from dark, light‐soaked, interlayer‐passivated device, the bulk and interface defects are decoupled and reveal the gradual defect passivation from shallow to deep level traps. Thus, the present study puts forward a useful design strategy to overcome the deleterious effect of metal oxide HELs and employ them in halide perovskite indoor PVs.

Influence of Mo doping on the structural, Raman scattering, and magnetic properties of NiO nanostructures

In this work, the Ni1-xMoxO, (x = 0.000, 0.025, 0.050, 0.075, 0.100, and 0.150) nanoparticles were prepared employing the coprecipitation method. The X-ray diffraction (XRD) confirmed that all the samples have a face-centered cubic (FCC) structure with no secondary phases by the effect of the Mo-doping. The Mo-dopants yielded smaller crystallites, reaching a size of 9 nm with x = 0.150. The transmission electron microscope (TEM) images revealed agglomerated NiO nanoparticles with nearly spherical shapes varied to elliptical-like shapes upon increasing Mo concentration. The energy dispersive X-ray (EDX) confirmed the purity of the synthesized samples. The XPS analysis confirmed the valence states of the presented elements in the samples as Ni2+, Ni3+, Mo6+, and O2− ions. The XPS detected the reduction of the nickel and oxygen vacancies, by studying the ratio of Ni2+/Ni3+ and lattice oxygen (OL) to vacant oxygen (OV) peaks. The Raman analysis demonstrated the active vibrational modes of NiO, for all the samples, along with stretching Mo = O bonds for the doped samples. The Photoluminescence (PL) spectroscopy was employed to study the near band edge and deep level emissions, giving insight to the defect levels within the band gap. The PL affirmed the decrease of the oxygen vacancies upon Mo-doping. Besides, the magnetic hysteresis measurements at room temperature revealed the superparamagnetic contribution embedded in the antiferromagnetic matrix of NiO. The magnetization was tuned by Mo doping concentration, where it affected the saturation magnetization, coercivity, and remnant magnetization. Mo dopant can modify the magnetic property of NiO nanoparticles and can be a potential candidate in biomedical field and data storage applications.Graphical