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Immigrants are highly entrepreneurial. But, what is the broader relationship between high-skilled immigration and regional entrepreneurship activity beyond the ventures that immigrants establish themselves? Using administrative data on newly awarded H-1B visas in the United States, we document a positive relationship between high-skilled immigration and regional entrepreneurship. A doubling of immigrants to a metropolitan statistical area is followed by a 6% increase in entrepreneurship within three years. In contrast, continuing H-1Bs and the arrival of unskilled immigrants (H-2B visas) do not increase regional entrepreneurship. Focusing on Indian immigrants (representing about 70% of all H-1B visas), we find the effect is stronger in metropolitan statistical areas with a larger local Indian population, but not other nationalities, suggesting that presence of conationals facilitates the relationship between high-skilled immigration and regional entrepreneurship. We present this and other evidence as consistent with a knowledge transfer mechanism.

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Magnetite nanoparticles (Fe3O4-NPs) have been demonstrated to be involved in direct interspecies electron transfer between syntrophic bacteria, yet a comprehensive assessment of the ability of Fe3O4-NPs to cope with process instability and volatile fatty acids (VFAs) accumulation in scaled-up anaerobic reactors is still lacking. Here, we investigated the start-up characteristics of an expanded granular sludge bed (EGSB) with Fe3O4-NPs as an adjuvant at high organic loading rate (OLR). The results showed that the methane production rate of R1 (with Fe3O4-NPs) was approximately 1.65 folds of R0 (control), and effluent COD removal efficiency was maintained at approximately 98.32% upon 20 kg COD/(m3·d) OLR. The components of volatile fatty acids are acetate and propionate, and the rapid scavenging of propionate accumulation was the difference between R1 and the control. The INT-ETS activity of R1 was consistently higher than that of R0 and R2, and the electron transfer efficiencies increased by 68.78% and 131.44%, respectively. Meanwhile, the CV curve analysis showed that the current of R1 was 40% higher than R3 (temporary addition of Fe3O4-NPs), indicating that multiple electron transfer modes might coexist. High-throughput analysis further revealed that it was difficult to reverse the progressive deterioration of system performance with increasing OLR by simply reconfiguring bacterial community structure and abundance, demonstrating that the Fe3O4-NPs-mediated DIET pathway is a prerequisite for establishing multiple electron transfer systems. This study provides a long-term and multi-scale assessment of the gaining effect of Fe3O4-NPs in anaerobic digestion scale-up devices, and provides technical support for their practical engineering applications.

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OBJECTIVES: To determine how social factors influence career decisions of dental service providers, particularly focusing on examining the impact of dentists' origins. METHODS: Online survey of Hessian panel dentists, with pairwise comparisons to a set of factors impacting their decision-making process. An Analytic Hierarchy Process examined the weighting of influencing drivers in career choice. RESULTS: Dentists from rural backgrounds were more likely to establish practices in rural areas than those from urban origins. Origin correlated with entrepreneurial intentions and a strong association of rural origin. Dentists who grew up in rural areas were 4.19 times more likely to start a business. CONCLUSION: These findings may support efficient resource allocation and support for rural dental businesses.

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Anammox bacteria (AnAOB) can be easily enriched under high temperatures and high substrate concentrations, while the application of the mainstream anammox process in low substrate municipal sewage is still relatively uncommon. Therefore, this study investigated the enrichment of AnAOB under conditions of low ammonia nitrogen and nitrite concentration at 25 °C. Results showed that using inoculated aerobic sludge, four ASBRs (R1, R2, R3 and R4) were successfully initiated with different influent substrate (NO2--N/NH4+-N) ratios of 1.2, 1.32, 1.4 and 1.5, respectively, with reactor start-up times were 162, 150, 120 and 134 days, respectively. The values of ΔNO2--N/ΔNH4+-N in reactors were stable at 1.17, 1.32, 1.43 and 1.53 respectively. The increase in influent substrate ratios resulted in improved TN removal rates and accelerated consumption of chemical oxygen demand (COD) during the initial start-up stage. The maximum TN removal rates achieved in the four reactors were 76.09%, 79.24%, 82.82% and 82.63%, respectively. The color of sludge gradually changes from yellowish-brown to reddish-brown. Furthermore, the surface of sludge exhibited a porous mineral structure, with crater-like cavities. The dominant anammox species in the system was identified as Candida Brocadia (3.04%). According to qPCR, the abundance of hzsB in the system is 1.65 × 1012 copies/g VSS, confirming the effective enrichment of AnAOB.

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Startups always face challenges during every scaling-up phase, so they need leaders who are resilient. Entrepreneurial resilience is the capacity of startup leaders to continue functioning in the face of various challenges. This research aims to explore how the dynamic interaction between entrepreneurial mindfulness and ambidextrous leadership influences the resilience of startup leaders during the scaling-up phase. The ability of startup leaders to execute entrepreneurial decisions and demonstrate ambidextrous leadership is crucial for increasing performance capacity. This study adopts a quantitative approach, utilizing a survey of startup leaders who have successfully undergone the scaling-up process, and analyzes the survey results using the SMART PLS program. Research findings suggest that entrepreneurial mindfulness influences decision-making, risk management, and strategic adaptability. This research examines how ambidextrous leadership, characterized by simultaneously exploring new opportunities and exploiting existing resources, enhances leaders' adaptive capacity in uncertain environments. These findings highlight the synergistic relationship between entrepreneurial awareness and ambidextrous leadership, collectively impacting startup leaders' ability to foster resilience during the scale-up journey. This research contributes to the existing literature by offering insights into practical strategies used by resilient leaders to enhance organizational performance and adaptability. In conclusion, this research emphasizes the importance of cultivating a mindful entrepreneurial mindset and adopting ambidextrous leadership practices for startup leaders aiming to thrive in a volatile scaling landscape. These findings not only contribute to individual leadership development but also inform organizational strategies and interventions aimed at fostering resilience and sustainable growth in the startup ecosystem.

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BACKGROUND: The rise of telehealth and telemedicine during the pandemic allowed patients and providers to develop a sense of comfort with telehealth, which may have increased the demand for virtual-first care solutions with spillover effects into venture capital funding. OBJECTIVE: We aimed to understand the size and type of digital health investments occurring in the prepandemic and pandemic periods. METHODS: We examined health care companies founded from March 14, 2019, to March 14, 2020 (prepandemic) versus those founded from March 15, 2020, to March 14, 2022, after pandemic onset. Data were obtained from Crunchbase, a publicly available database that catalogs information about venture capital investments for companies. We also compared companies founded prepandemic to those founded after the first year of the pandemic (pandemic steady-state). We performed a Wilcoxon rank sum test to compare median funding amounts. We compared the 2 groups of companies according to the type of funding round raised, geography, health care subcategory, total amount of funding per year since founding, and number of founders. RESULTS: There were 2714 and 2218 companies founded prepandemic and during the pandemic, respectively. The companies were similarly distributed across geographies in the prepandemic and pandemic periods (P=.46) with no significant differences in the number of founders (P=.32). There was a significant difference in total funding per year since founding between prepandemic and pandemic companies (US $10.8 million vs US $20.9 million; P<.001). The distribution of funding rounds differed significantly for companies founded in prepandemic and pandemic periods (P<.001). On excluding data from the first year of the pandemic, there were 581 companies founded in the pandemic steady-state period from March 14, 2021, to March 14, 2022. Companies founded prepandemic had a significantly greater mean number of founders than those founded during the pandemic (P=.02). There was no significant difference in total funding per year since founding between prepandemic and steady-state pandemic companies (US $10.8 million vs US $14.4 million; P=.34). The most common types of health care companies included wellness, biotech/biopharma, and software companies. Distributions of companies across health care subcategories were not significantly different before and during the pandemic. However, significant differences were identified when data from the first year of the pandemic were excluded (P<.001). Companies founded during the steady-state pandemic period were significantly more likely to be classified as artificial intelligence (7.3% vs 4.7%; P=.005), software (17.3% vs 12.7%; P=.002), and insurance (3.3% vs 1.7%; P=.003), and were significantly less likely to be classified as health care diagnostics (2.4% vs 5.1%; P=.002). CONCLUSIONS: We demonstrate no significant changes in the types of health care companies founded before versus during the pandemic, although significant differences emerge when comparing prepandemic companies to those founded after the first year of the pandemic.

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PURPOSE: A volume isotropic simultaneous interleaved bright- and black-blood examination (VISIBLE) can simultaneously acquire images with suppressed vascular signals (black-blood images) and images without suppression (bright-blood images). We aimed to improve of the bright-blood images by adjusting the k-space filling and using startup echo. METHODS: The k-space arrangement of bright-blood images in the conventional VISIBLE followed a low-to-high frequency order, whereas that in the proposed VISIBLE sequence was in the reversed order, and a startup echo was added. The effects of startup echo on the signal-to-noise ratio (SNR) were evaluated using phantoms, considering both white matter (WM) and post-contrast blood. Data from copper sulfate phantoms were acquired in 1D Fourier transform mode using both the conventional and proposed methods of the two VISIBLE sequences. The signal behavior with each sequence was evaluated. Fourteen patients with a total of 21 metastases were included in the study. For each patient, VISIBLE images of both conventional and proposed methods were obtained consecutively after the contrast agent administration. Using clinical images, we conducted a comparison of the SNR and contrast-to-noise ratio (CNR) for tumors, normal WM, and blood vessels between the conventional and proposed VISIBLE sequences. RESULTS: There was no significant difference in SNRs for both black- and bright-blood images between the conventional sequence and the proposed sequence with different number of startup echoes, however, the SNR of the proposed sequence decreased with increasing number of startup echoes in both black- and bright-images. The signal behavior of the bright-blood image reached a "steady state" when the startup echo exceeded 20. The SNRs of blood vessels in the bright-blood images did not differ significantly between conventional and proposed VISIBLE sequences. The SNRs of WM in the bright-blood images was significantly larger in the conventional sequence than in the proposed sequence. The SNRs of tumors in bright blood images was significantly larger in the proposed sequence than in the conventional sequence. The CNRs between tumors and WM, vessels and WM in the bright-blood images were significantly higher in the proposed sequence than in the conventional sequence. CONCLUSION: The use of the startup echo in combination with the high-to-low frequency k-space ordering method resulted in improved CNR of the bright-blood images in the VISIBLE sequence.

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The involvement of academic research in drug discovery is consistently growing. However, academic projects seldom advance to clinical trials. Here, we assess the landscape of drug discovery within the National Centre of Competence in Research (NCCR) TransCure launched by the Swiss National Science Foundation to foster basic research and early-stage drug discovery on membrane transporters. This included transporters in central nervous system (CNS) disorders, which represent a huge unmet medical need. While idea championship, sustainable funding, collaborations between disciplines at the interface of academia and industry are important for translational research, Popperian falsifiability, strong intellectual property and a motivated startup team are key elements for innovation. This is exemplified by the NCCR TransCure spin-off company Synendos Therapeutics, a clinical stage biotech company developing the first selective endocannabinoid reuptake inhibitors (SERIs) as novel treatment for neuropsychiatric disorders. We provide a perspective on the challenges related to entering an uncharted druggable space and bridging the often mentioned "valley of death". The high attrition rate of drug discovery projects in the CNS field within academia is often due to the lack of meaningful animal models that can provide pharmacological proof-of-concept for potentially disruptive technologies at the earliest stages, and the absence of solid intellectual property.

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As found in behavioral decision theory, venture capitalists (VCs) rely on heuristics and bias, owing to their bounded rationality, either by limited alternatives or information and resources. India's booming startup scene challenges VCs in decision-making owing to information overload from numerous evolving ventures, which hinders informed judgment. VC investment behavior, due diligence, and cognitive factors related to decision-making have always drawn the attention of researchers. We provide an alternative approach for an optimal decision by VCs by identifying the attributes that influence investment or funding decisions at an early stage of a venture in tech-based industries. Through a literature review, we identify eight attributes, both on internal and external criteria, that venture investors consider when making investment decisions. Based on interviews with 20 experts, we further identify eight key tech-based sectors. Using grey system theory, we then determine the rankings of eight tech startups for investors' early-stage investment decisions. This study presents a linguistic variable-based approach of grey numbers to decide weights and ratings, the grey possibility degree to compare and rank different tech startups, and based on the results, suggests the ideal tech startup. We find that agritech ranks first; thus, investors should prefer venturing into such startups for early-stage investment. E-commerce and edutech ranked second and third, respectively, followed by electric vehicle infrastructure, insurtech, fintech, space tech, and software as a service.

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The application of ANAMMOX technology is constrained by sluggish growth and difficulty in enriching ANAMMOX bacteria. Long-term starvation of functioning bacteria due to limited substrate supply makes the steady operation of ANAMMOX reactors more difficult. Re-examining the start-up and recovery performance of the ANAMMOX reactor and identifying its resistance mechanism are important from the standpoint of long-term starvation. By inoculating nitrifying and denitrifying sludge under various operating circumstances, the ANAMMOX reactors were successfully started. Under various start-up procedures, the tolerance mechanism and recovery performance were examined. The outcomes demonstrated that the denitrifying sludge-inoculated reactor operated steadily with a high substrate concentration and low flow rate. After 85 days of operation, the removal efficiencies of NH4+-N, NO2--N, and total nitrogen reached 98.7%, 99.3%, and 89.3%, respectively. After 144 days of starvation and 30 days of recovery, the better nitrogen removal performance was achieved at a low substrate concentration and high flow rate, and the removal efficiencies were 99.8% （NH4+-N）, 99.8% （NO2--N）, and 93.6% （total nitrogen）. During the starvation, extracellular polymeric substances wrapped the ANAMMOX bacteria and kept them intact to resist long-term starvation stress. The expression of nirS, hzsA, and hdh genes ensured the synthesis of nitrite/nitric oxide oxidoreductase, hydrazine synthase, and hydrazine dehydrogenase to maintain ANAMMOX activity. There was no significant difference in the relative abundance of ANAMMOX bacteria before and after starvation recovery. Candidatus Kuenenia had better anti-hunger ability, and the relative abundance increased by more than 86% after 30 days of recovery, confirming its tolerance to long-term starvation.

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The proliferation of nitrite oxidizing bacteria (NOB) still remains as a major challenge for nitrogen removal in mainstream wastewater treatment process based on partial nitrification (PN). This study investigated different operational conditions to establish mainstream PN for the fast start-up of membrane aerated biofilm reactor (MABR) systems. Different oxygen controlling strategies were adopted by employing different influent NH4+-N loads and oxygen supply strategies to inhibit NOB. We indicated the essential for NOB suppression was to reduce the oxygen concentration of the inner biofilm and the thickness of aerobic biofilm. A higher NH4+-N load (7.4 g-N/(m2·d)) induced higher oxygen utilization rate (14.4 g-O2/(m2·d)) and steeper gradient of oxygen concentration, which reduced the thickness of aerobic biofilm. Employing closed-end oxygen supply mode exhibited the minimum concentration of oxygen to realize PN, which was over 46% reduction of the normal open-end oxygen mode. Under the conditions of high NH4+-N load and closed-end oxygen supply mode, the microbial community exhibited a comparative advantage of ammonium oxidizing bacteria over NOB in the aerobic biofilm, with a relative abundance of Nitrosomonas of 30-40% and no detection of Nitrospira. The optimal fast start-up strategy was proposed with open-end aeration mode in the first 10 days and closed-end mode subsequently under high NH4+-N load. The results revealed the mechanism of NOB inhibition on the biofilm and provided strategies for a quick start-up and stable mainstream PN simultaneously, which poses great significance for the future application of MABR.

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A pilot-scale filtration system was adopted to prepare filter media with catalytic activity to remove manganese (Mn2+) and ammonium (NH4+-N). Three different combinations of oxidants (KMnO4 and K2FeO4) and reductants (MnSO4 and FeCl2) were used during the start-up period. Filter R3 started up by KMnO4 and FeCl2 (Mn7+→MnOx) exhibited excellent catalytic property, and the NH4+-N and Mn2+ removal efficiency reached over 80% on the 10th and 35th days, respectively. Filter R1 started up by K2FeO4 and MnSO4 (MnOx←Mn2+) exhibited the worst catalytic property. Filter R2 started up by KMnO4 and MnSO4 (Mn7+→MnOx←Mn2+) were in between. According to Zeta potential results, the Mn-based oxides (MnOx) formed by Mn7+→MnOx performed the highest pHIEP and pHPZC. The higher the pHIEP and pHPZC, the more unfavorable the cation adsorption. However, it was inconsistent with its excellent Mn2+ and NH4+-N removal abilities, implying that catalytic oxidation played a key role. Combined with XRD and XPS analysis, the results showed that the MnOx produced by the reduction of KMnO4 showed early formation of buserite crystals, high degree of amorphous, high content of Mn3+ and lattice oxygen with the higher activity to form defects. The above results showed that MnOx produced by the reduction of KMnO4 was more conducive to the formation of active species for catalytic oxidation of NH4+-N and Mn2+ removal. This study provides new insights on the formation mechanisms of the active MnOx that could catalytic oxidation of NH4+-N and Mn2+.

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Phenacetin (PNCT) belongs to one of the earliest synthetic antipyretics. However, impact of PNCT on nitrifying microorganisms in wastewater treatment plants and its potential microbial mechanism was still unclear. In this study, PN could be initiated within six days by PNCT anaerobic soaking treatment (8 mg/L). In order to improve the stable performance of PN, 21 times of PNCT aerobic soaking treatment every three days was conducted and PN was stabilized for 191 days. After PN was damaged, ten times of PNCT aerobic soaking treatment every three days was conducted and PN was recovered after once soaking, maintained over 88 days. Ammonia oxidizing bacteria might change the dominant oligotype to gradually adjust to PNCT, and the increase of abundance and activity of Nitrosomonas promoted the initiation of PN. For nitrite-oxidizing bacteria (NOB), the increase of Candidatus Nitrotoga and Nitrospira destroyed PN, but PN could be recovered after once aerobic soaking illustrating NOB was not resistant to PNCT. KEGG and COG analysis suggested PNCT might disrupt rTCA cycle of Nitrospira, resulting in the decrease of relative abundance of Nitrospira. Moreover, PNCT did not lead to the sharp increase of absolute abundances of antibiotic resistance genes (ARGs), and the risk of ARGs transmission was negligible.

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BACKGROUND: In 2022, the "New Capitalism Grand Design and Implementation Plan" was adopted in Japan, emphasizing the promotion and environmental development of startups. Given this context, an investigation into the startup and investment landscape in the allergy sector, both domestically and internationally, becomes imperative. METHODS: We analyzed 156 allergy-related startups from Japan, the US, and Europe from 2010 to 2021. Data on corporate information and investment trends were extracted from databases and VC websites. RESULTS: The total investment reached approximately 7.2 billion USD, with a ratio of 20:6:1 for the US, Europe, and Japan, respectively. The US showed a decline post its peak from 2016-2018, while Europe and Japan experienced growth. Notably, the US primarily invested in biopharmaceuticals for atopic dermatitis and food allergies, Europe in asthma-related apps, and Japan in healthcare apps and cross-border startups. DISCUSSION AND CONCLUSION: While Japan's investment environment in the allergy sector remains in its nascent stages and has room for development, the US and Europe are evidently ahead. Considering the rise of startups and funding limitations in Japan, external funding from regions like the US becomes a potential avenue. These findings are anticipated to contribute to the strategic activation of startups in allergy research and development.

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This study introduces a fault diagnosis algorithm based on particle filtering for open-cycle liquid-propellant rocket engines (LPREs). The algorithm serves as a model-based method for the startup process, accounting for more than 30% of engine failures. Similar to the previous fault detection and diagnosis (FDD) algorithm for the startup process, the algorithm in this study is composed of a nonlinear filter to generate residuals, a residual analysis, and a multiple-model (MM) approach to detect and diagnose faults from the residuals. In contrast to the previous study, this study makes use of the modified cumulative sum (CUSUM) algorithm, widely used in change-detection monitoring, and a particle filter (PF), which is theoretically the most accurate nonlinear filter. The algorithm is confirmed numerically using the CUSUM and MM methods. Subsequently, the FDD algorithm is compared with an algorithm from a previous study using a Monte Carlo simulation. Through a comparative analysis of algorithmic performance, this study demonstrates that the current PF-based FDD algorithm outperforms the algorithm based on other nonlinear filters.

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BACKGROUND: Estimating program costs when planning community-based mental health programs can be burdensome. Our aim was to retrospectively document the cost for the first year of planning and implementing Healthy Minds Healthy Communities (HMHC), a mental health promotion and prevention multi-level intervention initiative. This Program is among the first to use the Community Initiated Care (CIC) model in the US and is aimed at building community resilience and the capacity for communities to provide mental health support, particularly among those disproportionately impacted by COVID-19. Our objective is to share our methods for costing a program targeting 10 zip codes that are ethnically and linguistically diverse and provide an example for estimating the cost of a mental health prevention and promotion programs consisting of multiple evidence-based interventions. METHODS: We used a semi-structured interview process to collect cost data through the first year of program planning, start-up and initial implementation from key staff. We calculated costs for each activity, grouped them by major project categories, and identified the cost drivers of each category. We further validated cost estimates through extensive literature review. The cost analysis was done from the provider's perspective, which included the implementing agency and its community partners. We delineated costs that were in-kind contributions to the program by other agency, and community partners. Sensitivity analyses were conducted to estimate uncertainty around parameters. RESULTS: For the first year of the development and implementation of the program, (funded through program and in-kind) is estimated at $1,382,669 (2022 US$). The costs for the three main activity domains for this project are: project management $135,822, community engagement $364,216 and design and execution $756,934. Overall, the cost drivers for the first year of this intervention were: hiring and onboarding staff, in-person community building/learning sessions, communications and marketing, and intervention delivery. CONCLUSION: Implementation of community-based mental health promotion and prevention programs, when utilizing a participatory approach, requires a significant amount of upfront investment in program planning and development. A large proportion of this investment tends to be human capital input. Developing partnerships is a successful strategy for defraying costs.

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Background: Drug development in cancer medicine depends on high-quality clinical trials, but these require large investments of time to design, operationalize, and complete; for oncology drugs, this can take 8-10 years. Long timelines are expensive and delay innovative therapies from reaching patients. Delays often arise from study startup, a process that can take 6 months or more. We assessed how study-specific factors affected the study startup duration and the resulting overall success of the study. Method: Data from The University of Kansas Cancer Center (KUCC) were used to analyze studies initiated from 2018 to 2022. Accrual percentage was computed based on the number of enrolled participants and the desired enrollment goal. Accrual success was determined by comparing the percentage of enrollments to predetermined threshold values (50%, 70%, or 90%). Results: Studies that achieve or surpass the 70% activation threshold typically exhibit a median activation time of 140.5 days. In contrast, studies that fall short of the accrual goal tend to have a median activation time of 187 days, demonstrating the shorter median activation times associated with successful studies. Wilcoxon rank-sum test conducted for the study phase (W=13607, p-value=0.001) indicates that late-phase projects took longer to activate compared to early-stage projects. We also conducted the study with 50% and 90% accrual thresholds; our findings remained consistent. Conclusions: Longer activation times are linked to reduced project success, and early-phase studies tend to have higher success than late-phase studies. Therefore, by reducing impediments to the approval process, we can facilitate quicker approvals, increasing the success of studies regardless of phase.

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Anaerobic digestion (AD) has become a popular technique for organic waste management while offering economic and environmental advantages. As AD becomes increasingly prevalent worldwide, research efforts are primarily focused on optimizing its processes. During the operation of AD systems, the occurrence of unstable events is inevitable. So far, numerous conclusions have been drawn from full and lab-scale studies regarding the driving factors of start-up perturbations. However, the lack of standardized practices reported in start-up studies raises concerns about the comparability and reliability of obtained data. This study aims to develop a knowledge database and investigate the possibility of applying machine learning techniques on experimentation-extracted data to assist start-up planning and monitoring. Thus, a standardized database referencing 75 cases of start-up of one-stage wet continuously-stirred tank reactors (CSTR) processing agricultural, industrial, or municipal organic effluent in mono-digestion from 31 studies was constructed. 10 % of the total observations included in this database concern failed start-up experiments. Then, correlations between the parameters and their impacts on the start-up duration were studied using multivariate analysis and a model-based ranking methodology. Insights into trends of choices were highlighted through the correlation analysis of the database. As such, scenarios favoring short start-up duration were found to involve relatively low retention times (average initial and final hydraulic retention times, (HRTi) and (HRTf) of 26.25 and 20.6 days, respectively), high mean organic loading rates (average OLRmean of 5.24 g VS·d-1·L -1) and the processing of highly fermentable substrates (average feed volatile solids (VSfeed) of 81.35 g L-1). The model-based ranking of AD parameters demonstrated that the HRTf, the VSfeed, and the target temperature (Tf) have the strongest impact on the start-up duration, receiving the highest relative scores among the evaluated AD parameters. The database could serve as a reference for comparison purposes of future start-up studies allowing the identification of factors that should be closely controlled.

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Biochar-assisted anaerobic digestion (AD) remains constrained due to the inefficient decomposition of complex organics, even with the direct interspecies electron transfer (DIET) pathway. The coupling of electrochemistry with the anaerobic biological treatment could shorten lengthy retention time in co-digestion by improving electron transfer rates and inducing functional microbial acclimation. Thus, this work investigated the potential of improving the performance of AD by coupling low-magnitude electric fields with biochar derived from the anaerobically digested biogas residue. Different voltages (0.3, 0.6, and 0.9 V) were applied at various stages to assess the impact on biochar-assisted AD. The results indicate that an external voltage of 0.3 V, coupled with 5 g/L of biochar, elevates CH4 yield by 45.5% compared to biogas residue biochar alone, and the coupled approach increased biogas production by up to 143% within 10 days. This finding may be partly explained by the enhanced utilization of substrates and the increased amounts of specific methanogens such as Methanobacterium and Methanosarcina. The abundance of the former increased from 4.0 to 11.3%, which enhances the DIET between microorganisms. Furthermore, the coupling method shows better potential for enhancing AD compared to preparing iron-based biochar, and these results present potential avenues for its broader applications.

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BACKGROUND: Communities That HEAL (CTH) is a novel, data-driven community-engaged intervention designed to reduce opioid overdose deaths by increasing community engagement, adoption of an integrated set of evidence-based practices, and delivering a communications campaign across healthcare, behavioral-health, criminal-legal, and other community-based settings. The implementation of such a complex initiative requires up-front investments of time and other expenditures (i.e., start-up costs). Despite the importance of these start-up costs in investment decisions to stakeholders, they are typically excluded from cost-effectiveness analyses. The objective of this study is to report a detailed analysis of CTH start-up costs pre-intervention implementation and to describe the relevance of these data for stakeholders to determine implementation feasibility. METHODS: This study is guided by the community perspective, reflecting the investments that a real-world community would need to incur to implement the CTH intervention. We adopted an activity-based costing approach, in which resources related to hiring, training, purchasing, and community dashboard creation were identified through macro- and micro-costing techniques from 34 communities with high rates of fatal opioid overdoses, across four states-Kentucky, Massachusetts, New York, and Ohio. Resources were identified and assigned a unit cost using administrative and semi-structured-interview data. All cost estimates were reported in 2019 dollars. RESULTS: State-level average and median start-up cost (representing 8-10 communities per state) were $268,657 and $175,683, respectively. Hiring and training represented 40%, equipment and infrastructure costs represented 24%, and dashboard creation represented 36% of the total average start-up cost. Comparatively, hiring and training represented 49%, purchasing costs represented 18%, and dashboard creation represented 34% of the total median start-up cost. CONCLUSION: We identified three distinct CTH hiring models that affected start-up costs: hospital-academic (Massachusetts), university-academic (Kentucky and Ohio), and community-leveraged (New York). Hiring, training, and purchasing start-up costs were lowest in New York due to existing local infrastructure. Community-based implementation similar to the New York model may have lower start-up costs due to leveraging of existing infrastructure, relationships, and support from local health departments.

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