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Burnout is attributed to negative work environments and threatens patient and clinician safety. Psychological safety is the perception that the work environment is safe for interpersonal risk-taking and may offer insight into the relationship between the work environment and burnout. In this cross-sectional analysis of survey data from 621 nurse practitioners in California, we found that one-third (34%) experienced high burnout. Four factors in the work environment were negatively associated with burnout and positively associated with psychological safety. Significant mediation effects of psychological safety were observed on the relationships between each work environment factor and both emotional exhaustion and depersonalization. The largest mediation effects were observed on the total effects of Nurse Practitioner-Physician Relations and Practice Visibility on Emotional Exhaustion (37% and 32%, respectively) and Independent Practice and Support and NP-Administration Relations on Depersonalization (32% and 29%, respectively). We found, overall, that psychological safety decreased the strength of the negative relationship between work environment and burnout. We argue that research, practice, and policy efforts to mitigate burnout and improve the work environment should consider psychological safety as a metric for system-level well-being.

Electrochemical carbon dioxide reduction represents a promising path to utilize CO2 as a feedstock for generating valuable products such as fuels and chemicals. Faradaic efficiencies near 100% have been achieved for certain CO2 reduction products such as CO, but the electrolyzer outlet streams usually contain large fractions of unreacted CO2, dropping the product concentrations below 1% in many cases. The system disclosed here recycles the unreacted CO2 together with the products and flows them back into the CO2 reduction reactor, enabling much higher CO2 conversion rates without dropping the gas flow rate. However, simple recirculation is shown to accumulate significant amounts of hydrogen, impeding effective CO2 reduction. In this looped system, an electrochemical H2 pump is placed in series with the CO2 reactor, which effectively removes all the H2 from the recycled gas stream, increasing the concentrations of carbon-containing products. The system was initially tested with a CO-generating catalyst and CO concentrations above 70% were achieved in the recycled gas stream, compared to a maximum CO concentration of 8% in single-pass configuration. Results with a CO2 reactor targeting ethylene as the main product show that ethylene concentrations of at least 10% can be achieved, which is roughly 20 times higher compared to a single-pass system.

Electrochemical CO2 reduction (CO2R) using heterogenized molecular catalysts usually yields 2-electron reduction products (CO, formate). Recently, it has been reported that certain preparations of immobilized cobalt phthalocyanine (CoPc) produce methanol (MeOH), a 6-electron reduction product. Here, we demonstrate the significant role of intermediate mass transport in CoPc selectivity to methanol. We first developed a simple, physically mixed, polymer (and polyfluoroalkyl, PFAS)-free preparation of CoPc on multiwalled carbon nanotubes (MWCNTs) which can be integrated onto Au electrodes using a poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT:PSS) adhesion layer. After optimization of catalyst preparation and loading, methanol Faradaic efficiencies and partial current densities of 36% (±3%) and 3.8 (±0.5) mA cm-2, respectively, are achieved in the CO2-saturated aqueous electrolyte. The electrolyte flow rate has a large effect. A linear flow velocity of 8.5 cm/min produces the highest MeOH selectivity, with higher flow rates increasing CO selectivity and lower flow rates increasing the hydrogen evolution reaction, suggesting that CO is an unbound intermediate. Using a continuum multiphysics model assuming CO is the intermediate, we show qualitative agreement with the optimal inlet flow rate. Polymer binders were not required to achieve a high Faradaic efficiency for methanol using CoPc and MWCNTs. We also investigated the role of formaldehyde as an intermediate and the role of strain, but definitive conclusions could not be established.

Electrochemical CO2 reduction on Cu is a promising approach to produce value-added chemicals using renewable feedstocks, yet various Cu preparations have led to differences in activity and selectivity toward single and multicarbon products. Here, we find, surprisingly, that the effective catalytic activity toward ethylene improves when there is a larger fraction of less active sites acting as reservoirs of *CO on the surface of Cu nanoparticle electrocatalysts. In an adaptation of chemical transient kinetics to electrocatalysis, we measure the dynamic response of a gas diffusion electrode (GDE) cell when the feed gas is abruptly switched between Ar (inert) and CO. When switching from Ar to CO, CO reduction (COR) begins promptly, but when switching from CO to Ar, COR can be maintained for several seconds (delay time) despite the absence of the CO reactant in the gas phase. A three-site microkinetic model captures the observed dynamic behavior and shows that Cu catalysts exhibiting delay times have a less active *CO reservoir that exhibits fast diffusion to active sites. The observed delay times and the estimated *CO reservoir sizes are affected by catalyst preparation, applied potential, and microenvironment (electrolyte cation identity, electrolyte pH, and CO partial pressure). Notably, we estimate that the *CO reservoir surface coverage can be as high as 88 ± 7% on oxide-derived Cu (OD-Cu) at high overpotentials (-1.52 V vs SHE) and this increases in reservoir coverage coincide with increased turnover frequencies to ethylene. We also estimate that *CO can travel substantial distances (up to 10s of nm) prior to desorption or reaction. It appears that active C-C coupling sites by themselves do not control selectivity to C2+ products in electrochemical COR; the supply of CO to those sites is also a crucial factor. More generally, the overall activity of Cu electrocatalysts cannot be approximated from linear combinations of individual site activities. Future designs must consider the diversity of the catalyst network and account for intersite transportation pathways.

Background: Through the human-centered design process (HCD), students, referred to as learners, can use a personal lens to contextualize engineering concepts and solve real-world problems (Goldman and Kabayadondo 2016). The Ignite program, created by the Center for Global Women's Health Technologies (GWHT) at Duke University, integrates the HCD process into science, technology, engineering, and math (STEM) education to advance social justice through an iterative research-topractice methodology. Ignite fosters secondary school students' ability to engineer viable solutions to pressing global issues outlined by the United Nations as Sustainable Development Goals (SDGs). Purpose: This work evaluates the efficacy of the Ignite Water curriculum as a scalable and sustainable intervention for STEM opportunity gaps, SDG #4, and clean water, SDG #6. Ultimately, this work investigates the ability of a community-centered design thinking initiative to transform learners' behavioral indicators, including their knowledge, attitude, and awareness. Methods: Knowledge, Attitudes and Practices (K.A.P.) methodology was used to capture changes in three indicators of behavior change: (1) learners' relevant content knowledge, (2) their attitudes towards STEM and (3) awareness of healthy water management practices. The mixed methods research tabulated survey data and interviews to determine best practices for STEM intervention programs. Of the 697 participants, 523 learners across 6 schools served as a sample population for this study. Results: The innovative Ignite program engaged a diverse population in engineering solutions for water pollution in Lake Atitlán, Guatemala. The intervention increased students' knowledge and awareness related to the local water contamination; especially, the causes of contamination and the treatment options. Female learners demonstrated an increase in self-efficacy in engineering careers, while male learners' self-efficacy for math and community problem-solving increased. Overall, learners' knowledge and awareness of water pollution and their attitudes towards STEM improved. Trainers echoed key findings in semi-structured interviews. Conclusions: Ignite, the sustainable and scalable intervention for social impact, integrated the HCD process with the SDGs to promote local problem solving, improve self-efficacy and broaden participation in engineering.

Seaweed extract has gained popularity in agriculture due to global trend of promoting sustainable agricultural development. Seaweed contains phytohormones such as IAA and gibberellin and minerals that induce seeds germination. While conventional extraction of seaweeds has been carried out with different organic solvents such as ethanol and methanol, the present study uses natural and commonly available organic liquids i.e., water, vinegar, fermented buttermilk, and cow urine as extracting agents to make them suitable for regenerative agriculture. The organic solvents used in this study have a known nutritional composition and facilitate the enhancement of plant defense systems. Three seaweed species, Caulerpa racemosa, Gracilaria edulis, and Sargassum wightii, were extracted with different solvents at various concentrations and compared. The mineral analysis and FTIR characterization of different seaweeds and their extracts showed variation in composition and functional groups. Seaweed species, however, showed no variation in seed germination. Fermented buttermilk and water extract improved the germination properties of blackgram between 0.1–5% concentrations and led to higher increase in shoot and root length and biomass yield. The hormetic response by blackgram to the seaweed extract was observed starting at an average of 2% concentration with toxicity at 5% concentration and above for water and fermented buttermilk extract. However, vinegar and cow urine extracted seaweed showed toxicity symptoms even at lower concentrations (0.1%) inhibiting germination. Therefore, water and buttermilk extract may be recommended at 0.5–1% for enhanced germination.

Abstract Now, the present power generation and distribution companies are working on renewable energy systems because their features are low-level atmospheric pollution, producing less greenhouse pollutants, more reliability, good static performance, and high robustness. In this work, the sunlight Photovoltaic (PV) system is selected because of its advantages are easily available in the atmosphere, high flexibility, zero carbon footprint, easy to maintain, and less transportation cost. However, solar networks produce nonlinear I-V characteristics. Due to the non-linear nature of the solar system, the extraction of peak voltage from the PV module is a very tough task. So, in this article, a variable modified step grey wolf method is integrated with the adaptive-neuro-fuzzy-inference-system to improve the energy production of solar systems. The features of this proposed maximum power point tracking controller are fast identification of the solar system operating point, generating the less fluctuated oriented converter load power, providing more MPP tracking accuracy, less dependence on the solar system installation, and useful for all environmental bad weather conditions. Another problem of solar systems is less voltage production which is improved by introducing a wide voltage gain-boost converter circuit. The features of this converter circuit are less development cost because it does not require more power electronics switches. Here, the proposed IGWM with an AFLC-fed sunlight system is investigated by using MATLAB/Simulink.

SynerGNet is a novel approach to predicting drug synergy against cancer cell lines. In this study, we discuss in detail the construction process of SynerGNet, emphasizing its comprehensive design tailored to handle complex data patterns. Additionally, we investigate a counterintuitive phenomenon when integrating more augmented data into the training set results in an increase in testing loss alongside improved predictive accuracy. This sheds light on the nuanced dynamics of model learning. Further, we demonstrate the effectiveness of strong regularization techniques in mitigating overfitting, ensuring the robustness and generalization ability of SynerGNet. Finally, the continuous performance enhancements achieved through the integration of augmented data are highlighted. By gradually increasing the amount of augmented data in the training set, we observe substantial improvements in model performance. For instance, compared to models trained exclusively on the original data, the integration of the augmented data can lead to a 5.5% increase in the balanced accuracy and a 7.8% decrease in the false positive rate. Through rigorous benchmarks and analyses, our study contributes valuable insights into the development and optimization of predictive models in biomedical research.

Abstract Experiences in early childhood form the bedrock of future human potential. In impoverished settings, structured early childhood education (ECE) in preschool years can augment overall childhood and later human abilities. The current study evaluates preschool learning exposure and childhood cognition, using longitudinal follow-up of a community-based birth cohort in Vellore, south India. The birth cohort study site in Vellore recruited 251 newborns between 2010 and 2012 from dense urban settlements and further followed up into childhood. Preschool enrolment details were obtained from parents. Childhood cognition was assessed by Weschler’s preschool primary scale of intelligence (WPPSI) and Malin’s intelligence scale for Indian Children (MISIC) at 5 and 9 years of age respectively. Bivariate and multivariate regression analyses were performed with adjustments for socio-economic status (SES), maternal education, stunting status and home environment. Out of 251 new-borns recruited into the MAL-ED birth cohort, 212 (84.46%) and 205 (81.7%) children were available for the 5 year and 9 year follow-up respectively. At 5 years, structured ECE of 18 to 24 months duration was significantly associated with higher cognition scores, with the highest increase in processing speed [β: 19.55 (11.26–27.77)], followed by full-scale intelligence [β: 6.75 (2.96–10.550)], even after adjustments for SES, maternal cognition, home factors and early childhood stunting status. Similarly adjusted analysis at 9 years showed that children who attended 1.5–2 years of structured ECE persisted to have higher cognition, especially in the performance domain [β: 8.82 (2.60–15.03)], followed by the full-scale intelligence [β: 7.24 (2.52–11.90)]. Follow-up of an Indian birth cohort showed that structured ECE exposure was associated with better school entry cognition as well as mid-childhood cognition. Strengthening ECE through a multi-pronged approach could facilitate to maximize cognitive potential of human capital.

Electron transport layers (ETLs) used as components of photocathodes for light-driven CO2 reduction (CO2R) in aqueous media should have good electronic transport, be stable under CO2R conditions, and, ideally, be catalytically inert for the competing hydrogen evolution reaction (HER). Here, using planar p-Si (100) as the absorbing material, we show that TaOx satisfies all three of the above criteria. TaOx films were synthesized by both pulsed laser deposition (PLD) and radio-frequency (RF) sputtering. In both cases, careful control of the oxygen partial pressure during growth was required to produce ETLs with acceptable electron conductivity. p-Si/TaOx photocathodes were interfaced with ca. 10 nm of a CO2R catalyst: Cu or Au. Under front illumination with simulated AM 1.5G in CO2-saturated bicarbonate buffer, we observed, for both metals, faradaic efficiencies for CO2R products of ∼50% and ∼30% for PLD TaOx and RF sputtered TaOx, respectively, at photocurrent densities up to 8 mA cm−2. p-Si/TiO2/Cu photocathodes were also evaluated but produced mostly H2 (>97%) due to reduction of the TiO2 to Ti metal under CO2R conditions. In contrast, a dual ETL photocathode (p-Si/TiO2/TaOx/Cu) was selective for CO2R, which suggests a strategy for separately optimizing selective charge collection and the stability of the ETL/water interface. The maximum photovoltage obtained with p-Si/TaOx/Cu devices was 300 mV which was increased to 430-460 mV by employing ion implantation to make pn+-Si/TaOx/Cu structures. Photocathodes with RF sputtered TaOx ETLs are stable for CO2R for at least 300 min. Techno-economic analysis shows that the reported system, if scaled, could allow for an economically viable production of feedstocks for chemical synthesis under the adoption of specific CO2 credit schemes, thus becoming a significant component of carbon-neutral manufacturing.

Purpose: To critically review the clinical factors, dosimetry, and their correlation with early outcomes in patients with chordomas and chondrosarcomas treated with pencil beam scanning (PBS) proton beam therapy (PBT). Methods and Materials: Consecutive 64 patients diagnosed with chordoma or chondrosarcoma treated at our center were studied. Patient, tumor, and treatment-related factors including dosimetry were captured. Early and late toxicities and early outcomes were evaluated and correlated with clinical and dosimetric factors using standard statistical tools. Results: The median age of patients was 39 years (range, 4-74 years), and most common site was skull base (47%), followed by sacrum (31%) and mobile spine (22%). The median prescription dose to the high-risk clinical target volumes for chordoma and chondrosarcoma was 70.4 cobalt gray equivalent (CGE) and 66 CGE at 2.2 CGE per fraction, respectively. At presentation, 55% presented after a recurrence/progression of which 17% had received previous radiation and 32% had a significant neural compression. At the time of PBT, 25% of patients had suboptimal neural separation. Three-fourths of patients had at least an acceptable target coverage. Although 11% had a tier 1 compromise (gross tumor volume [GTV] D98 < 90%), 14% had a tier 2 compromise (GTVD98 < 59 CGE). With a median follow-up of 27.5 months, 2-year local control and progression-free survival was 86.7% and 81.8% for chordomas and 87.5% and 77.1% for chondrosarcomas, respectively. Residual GTV of >25 cm3 and a tier 2 compromise were associated with inferior local control (hazard ratio [HR], 0.19; P = .019; HR, 0.061; P = .022, respectively) and progression-free survival (HR, 0.128; P = 0.014; HR, 0.194; P =.025, respectively) on multivariate analysis. Despite multiple surgeries, a majority presented with recurrent disease and previous radiations and grade 3 acute and late toxicities were limited and comparable with others in the literature. Conclusions: Despite multiple surgeries, adequate neural separation was challenging to achieve. Severe dosimetric compromise (GTV D98 < 59 CGE) led to inferior early outcomes. Adequate neural separation is key to avoiding dosimetric compromise and achieving optimal local control.

This paper extends scholarship on emerging sources of worker power in the 21st century through an examination of the solidarity activism of the Coalition of Immokalee Workers (CIW), an agricultural worker-led human rights organisation that advocates for Fair Food policies. The successes of the CIW are unexpected, since Florida’s migrant workers lack the traditional sources of worker power that bolstered the labour struggles of the 20th century. Through in-depth interviews and a survey of student-farmworker activists, we extend scholarship rooted in the power resources approach to analyse the societal forms of power – both discursive and coalitional – that the CIW has developed in their efforts to harness broad social support from actors beyond the fields. We demonstrate how CIW coalitions are sustained through solidarity narratives that clarify the stakes for student allies and the discursive frames that motivate their activism.

Seaweed is an increasingly recognized source of secondary metabolites with a significant role as a plant biostimulant. With the rising popularity of organic farming, there is a pressing need to investigate the utilization of organic solvents derived from natural sources for seaweed extraction. Understanding the composition of these extracts is crucial for elucidating their role as biostimulants in plant growth. Hence, the present study aimed to explore the phytochemical composition and untargeted metabolomics of four extracts of Caulerpa racemosa (SW), prepared organically using vinegar, fermented buttermilk, and cow urine, in comparison with the conventionally used solvent, water. Approximately 95 volatile metabolites that belong to 22 chemical classes were identified through GC–MS analysis. The major classes detected include benzene and its substituted derivatives (24%), fatty acyls (17%), phenols (12%), benzofurans (8%), organo-oxygen compounds (6%), steroids and steroid derivatives (5%), and indole and its derivatives (4%). A significant shift in the composition of volatile metabolites was observed among the organic extracts as determined through a combination of various statistical analyses. A principal component analysis (PCA) highlighted seven principal components (PCs), which accounted for 99.9% of the total variance. Hierarchical cluster analysis delineated two distinct clusters, which signify a clear differentiation among the organic extracts. Furthermore, partial least squares discriminant analysis (PLS-DA) highlighted 49 volatile metabolites of significant importance, evident from variable importance in projection (VIP) scores of more than 1. These results underscore the intricate and distinct metabolomes inherent in Caulerpa racemosa organic extracts, hinting at their potential as biostimulants for plant growth. This study establishes a foundation for deeper investigations into seaweed extraction utilizing easily accessible organic solvents, presenting potential benefits for farmers.

ShuQi Wang,1* Fatih Inci,1* Tafadzwa L Chaunzwa,1 Ajay Ramanujam,1 Aishwarya Vasudevan,1 Sathya Subramanian,1 Alexander Chi Fai Ip,1 Banupriya Sridharan,1 Umut Atakan Gurkan,1 Utkan Demirci,1,21Bio-Acoustic-MEMS in Medicine (BAMM) Laboratory, Center for Biomedical Engineering, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, 2Harvard-MIT Health Sciences and Technology, Cambridge, MA, USA, *These authors contributed equally to this workAbstract: Pathogenic agents can lead to severe clinical outcomes such as food poisoning, infection of open wounds, particularly in burn injuries and sepsis. Rapid detection of these pathogens can monitor these infections in a timely manner improving clinical outcomes. Conventional bacterial detection methods, such as agar plate culture or polymerase chain reaction, are time-consuming and dependent on complex and expensive instruments, which are not suitable for point-of-care (POC) settings. Therefore, there is an unmet need to develop a simple, rapid method for detection of pathogens such as Escherichia coli. Here, we present an immunobased microchip technology that can rapidly detect and quantify bacterial presence in various sources including physiologically relevant buffer solution (phosphate buffered saline [PBS]), blood, milk, and spinach. The microchip showed reliable capture of E. coli in PBS with an efficiency of 71.8% ± 5% at concentrations ranging from 50 to 4,000 CFUs/mL via lipopolysaccharide binding protein. The limits of detection of the microchip for PBS, blood, milk, and spinach samples were 50, 50, 50, and 500 CFUs/mL, respectively. The presented technology can be broadly applied to other pathogens at the POC, enabling various applications including surveillance of food supply and monitoring of bacteriology in patients with burn wounds.Keywords: Escherichia coli, microchip, sepsis, food safety, point-of-care