This study aims to explore the effect of microstructural parameters on notch fatigue damage behavior of the TC21 alloy. Different levels of lamellar microstructures were achieved through distinct aging temperatures of 550, 600, and 650 °C. The findings reveal that increasing aging temperature primarily contributes to the augmentation of α colony (αc) thickness, grain boundaries α phase (GBα) thickness, and α fine (αfine) size, alongside a reduction in α lath (αlath) thickness and αfine content. The notch alters stress distribution and relaxation effects at the root, enhancing notched tensile strength while weakening plasticity. Moreover, the increased thickness of GBα emerges as a critical factor leading to the increase area of intergranular cleavage fracture. It is noteworthy that more thickness αlath and smaller αfine facilitate deformation coordination and enhance dislocation accumulation at the interface, leading to a higher propensity for microvoids and microcracks to propagate along the interface. Conversely, at elevated aging temperatures, thinner αlath and larger αfine are more susceptible to fracture, resulting in the liberation of dislocations at the interface. The reduction in αlath thickness is crucial for triggering the initiation of multi-system dislocations at the interface, which promotes the development of persistent slip bands (PSBs) and dislocation nets within αlath. This phenomenon induces inhomogeneous plastic deformation and localized hardening, fostering the formation of microvoids and microcracks.

This paper proposes a new cascaded three-phase multilevel inverter based on a cascaded submultilevel and single-phase H-bridge structure. The voltage source of the traditional single-phase H-bridge is replaced with the proposed cascaded submultilevel. Cascading two basic units forms the submultilevel unit. The basic and submultilevel units generate positive voltage only hence the need for an H-bridge to generate both polarities of load voltage. Five algorithms of source voltage are proposed and the optimal algorithm selected to generate the peak load voltage and output levels. The proposed three-phase cascaded multilevel inverter generates 31-level of load voltage. The per-phase component distribution of the proffered inverter are twelve power switches, four dc sources and twelve driver circuits accordingly. Principal merits of the proposed 31-level inverter are high quality load waveforms, production of high levels of load voltage utilizing reduced component quantity, simple cascaded layout, decreased inverter area, minimal inverter cost, minimum inverter losses and utilizing lower rated switches. Also, the proposed topology is highly suited for employment in PV-DVR and other power systems. To validate these advantages of the proposed multilevel inverter, contrastive analysis of the proposed inverter and existing topologies are studied. Finally, the functionality of the proposed inverter is substantiated by simulation in PSCAD/ EMTDC software.

This paper presents a novel improvement of MuSIASEM (Multiscale Integrated Analysis of the Societal and Ecological Metabolism) by incorporating a new regional analysis of the electricity metabolism across levels. An analysis of Mexico illustrates this toolkit and shows that the industry sector had Economic Energy Intensity (EEI) with 40.3 MWh/MMXN reached a higher value than the commerce and services sector with 0.84 MWh/MMXN. Regarding the Economic Labor Productivity (ELP) indicator (AV/h), the industrial sector with 208.5 TMXN/Kh reached a higher value than the Commercial and services sector with 114.3 TMXN/Kh. With reference to the Exosomatic Metabolic Rate (EMR), the Household sector obtained 59.3 KWh/Kh whereas the paid sector reached 2,486.4 KWh/Kh. Disaggregation of the EMR indicator into economic sectors shows that the Industrial sector obtained 8.4 KWh/Kh and the commercial and services sector reached 0.10 KWh/Kh. The lack of complete data for the agricultural sector does not allow us to calculate EEI, ELP, and EMR indicators accurately. Considering the analysis of indicators by regions, regarding the EEI rate, the Central region had the lowest value with 12.7 MWh/MMXN, followed by the Northeast with 21.4 MWh/MMXN and Western with 29.4 MWh/ MMXN, which means that they require less electricity to produce more added value. In terms of the ELP indicator, it was found regions with higher values were Northeast with 182.3 MMXN/Mh, Central with 177.5 MMXN/Mh, and North with 127 MMXN/Mh, which means that these regions produce more added value per hour of work. About the EMR, it is observed that regions in the northern part of the country had higher values: Northwest with 337 KWh/Kh, Baja California Sur with 334 KWh/Kh, Baja California with 328 KWh/Kh, North with 313 KWh/Kh and Northeast with 274 KWh/Kh, which means that these regions consume more electricity per hour. This innovative approach is useful for governance because it helps to understand and reduce asymmetries across regions, resulting in more social equality and a better economic equilibrium across sectors and regions.

The present article analyzes the connection between, on the one hand, gender equality and, on the other hand, loneliness and social isolation. It hypothesizes that modern relational institutions, that support gender equality, such as no-fault divorce laws, reduce loneliness in close relationships. This hypothesis is put to the test through a multilevel analysis of the ISSP 2017. The analysis reveals that the data agrees, to a large extent, with the theoretical arguments. The prevalence of loneliness is higher in countries with higher levels of gender inequality (as measured by the Gender Inequality Index [GII]). This can be attributed to a moderation effect: at lower levels of gender inequality, partnerships provide better protection from loneliness. These results are robust to controls for demographic composition, level of health, educational attainment, income poverty, and interview mode. Last, the analyses show that the threat of emotional isolation is more widespread in countries with low gender inequality. This finding, however, is only significant before controlling for demographic composition, level of health, educational attainment, income poverty, and interview mode, and it requires further analysis. The concluding section relates these findings to the popular tendency to argue that modern society has created a “loneliness epidemic.”

In modern inverter applications, multilevel converters are used thanks to their capability of reducing the passive fi lter volumes, improving the overall THD, sharing the power sources across the several converter cells, and providing a reconfi guration ability in case of failure. However, increasing the number of cells makes more complex the control of the converter. This article proposes a decentralized control technique based on the use of elementary modular controllers, associated with each converter cell and communicating with their close neighbors to obtain the balancing of the powers they supplied. Each modular controller can be dynamically removed or added to allow reconfi guration of the converter for functional safety purpose. This method is applied to a 240V/3A 5-cells Cascaded Full-Bridge Multilevel Converter. The response of the system to load transients and cell voltage disturbances demonstrates the robustness of the proposed decentralized control method. Thanks to the use of modular controllers, the number of levels of the converter can be extended to the order N without adding complexity to its control.

Background: In Ethiopia, 8.6% of maternal deaths are attributed to abortion. Despite the legalization of abortion and improved accessibility of safe abortion services, almost six in 10 abortions in Ethiopia are performed outside of the health facility. Abortion considered as an indicator for various aspects of reproductive health and healthcare access within a particular region or country. Despite the significance of the problem, there is a limited understanding of the magnitude of abortion and the contributing factors in the study area. Therefore, this study aimed to assess the prevalence of abortion and determinant factors among reproductive-age women in the Sidama regional state of Ethiopia.Methods: A community-based cross-sectional study was conducted from October to November 11, 2022, among 1,130 women of reproductive age. We utilized a multi-stage sampling method to select eligible women. A structured and pretested questionnaire was utilized to collect the data using Open Data Kit (ODK) mobile application. Due to the hierarchical nature of the data, a multilevel logistic regression model was applied. Variables with p-values < 0.25 on bi-variable analysis were included in a multivariable regression model. In the multivariable regression model, variables with a p-value < 0.05 were declared as statistically significant factors of abortion. Results: Nearly one-fifth (19.5%) of the women had a history of abortion. From the individual level determinates; women with formal education (AOR=0.44; 95% CI: 0.24-0.79), and planned pregnancy (AOR=0.41; 95% CI: 0.28-0.61) had lower odds of abortion. While from the community related factors; urban residence increased the odds of abortion (AOR=2.25; 95% CI: 1.20-4.20) as compared to the rural residence.Conclusion: the prevalence of abortion among reproductive age women of Northern Zone of Sidama Region was high. Education and a planned pregnancy serve as protective factors for abortion, while the risk of abortion increased among women reside in urban area. Therefore, to lower the abortion rate, it is better to implement a comprehensive approach, focusing on education, family planning, and urban-specific intervention.

The objective of this research is to mitigate vibrations in induction motors. To achieve this goal, a discontinuous pulse width modulation (PWM) control strategy based on carrier wave modulation is proposed for multilevel inverters. This study provides justification for the reduction of machine vibrations compared to existing control techniques documented in the technical literature. Additionally, the proposed technique offers the advantage of attenuating the Total Harmonic Distortion of the multilevel inverter's output voltage while simultaneously achieving a higher RMS value for the same DC level. By modifying a parameter of the carrier wave, the control strategy allows for variations in the electrical spectrum while avoiding natural mechanical resonance frequencies, thereby reducing motor vibrations. Laboratory results demonstrating the application of different modulation strategies in a multilevel inverter for an induction motor and a comparison with the presented strategy are provided.

With the development of the photovoltaic industry, there will be an increasing demand for efficient, high-power density, and low-cost grid interface converters. Compared with two-level inverters, multilevel inverters have the following advantages: (1) lower device voltage ratings; (2) better output filtering spectrum; (3) lower electromagnetic interference (EMI) noise; and (4) higher switching speed capability. However, the complex switching circuit of the multilevel inverter will bring more parasitic inductance, resulting in more serious switching overvoltage (ringing). Consider that commonly used overvoltage absorption schemes are effective only for overvoltage or sup-pression of oscillations. Therefore, a new overvoltage absorption circuit is proposed in this paper, which can not only alleviate the overvoltage and ringing phenomena but also suppress the effect of voltage jumps during low-frequency switching on high-frequency input voltage. This overvoltage absorption circuit is characterized by low overvoltage, fast ringing damping, and minimum ca-pacitance. Experiments and simulations are conducted to verify the effectiveness of this overvoltage absorption circuit using a three-level ANPC inverter as a prototype. The results show that the proposed overvoltage absorption circuit can significantly reduce the overvoltage level, shorten the oscillation time, and reduce the voltage difference between the upper and lower DC bus capacitors.

Introduction Prostate Cancer (PCa) exhibits one of the widest racial and socioeconomic disparities. PCa disparities have also been widely linked to location as living in more deprived regions was associated with lower healthcare access and worse outcomes. This study aims to examine PCa survival across various US counties in function of different socioeconomic profiles and discuss the role of potential intermediary factors. Methods The SEER database linked to county-level SES was utilized. Five-year PCa-specific survival using the Kaplan Meier method was performed for 5 racial/ethnic categories in function of SES quintiles. Multilevel Cox proportional hazards regression was performed to assess the relationship between county-level SES and PCa survival. Multivariate regression analysis was performed to examine the role of healthcare utilization and severity. Results 279,000 PCa records were extracted, 5-year PCa-specific survival was 94%. Overall, living in counties with worst poverty/income quintile and highest proportions of foreign-born/language-isolated increased PCa mortality by 23% each. No association was observed with county-level High-School education, while Bachelor’s-level education decreased mortality risk by 23%. Associations varied considerably upon racial/ethnic stratification. Multilevel analyses showed varying contributions of individual and area-level factors to survival within minorities. The relationship between SES and PCa survival appeared to be influenced by healthcare utilization and disease stage/grade. Discussion Racial/ethnic categories responded differently under similar county-level SES and individual-level factors to the point where disparities reversed in Hispanics. The inclusion of Healthcare utilization and severity factors may provide partial early support for their role as intermediaries. Healthcare access (insurance) might not necessarily be associated with better PCa survival, through performing biopsy and or/surgery. County-level education plays an important role in PCa decision-making as it might elucidate discussions of other non-invasive management options. Conclusion Findings of this study demonstrate that interventions need to be tailored according to each group's needs. This potentially informs the focus of public health efforts in terms of planning and prioritizing. This study could also direct further research delving into pathways between area-level characteristics with PCa survival.

There is a growing need to utilize community interventions to address modifiable behaviors that lead to poor health outcomes like obesity, diabetes, and heart disease. Poor health outcomes can be tied to community-level factors such as food deserts (identified areas with low access to fresh fruit, vegetables, and other healthful whole foods) and individual behaviors like sedentary lifestyles, consuming large portion sizes, and eating high-calorie fast food and processed foods. Through a social ecological approach with family, organization and community, the Faithful Families Cooking and Eating Smart (FFCES) intervention was created to address these concerns in a rural South Carolina community. FFCES used gatekeepers to identify 18 churches and 4 apartment complexes in low-income areas. 176 participants completed both pre- and post- survey measures. Student’s t-test measures found statistically significant change in participant perception of food security (0.39, p-value=0.005), self-efficacy with physical activity and healthy eating (0.26, p-value=000), and cooking confidence (0.17, p-value=.01). There was not significant change in cooking behaviors as assessed through the Cooking Behaviors Scale. FFCES shows that a social ecological approach can be effective at increasing and improving individual healthy behaviors and addressing community-level factors in low-income rural communities.

Pheidole oxyops Forel, 1908 is a generalist ant, which forages actively for plant debris to dead arthropods. In addition, its nest has an entrance that allows the ants gather resources passively by capturing falling preys into the nest. Our objective was to verify if different day periods, temperature and residual soil accumulation (ground pile in the side of nest entrance) could influence the patterns of foraging activity. Foraging activities were registered in the morning, afternoon and twilight. We measured direction and vector of trails, air temperature and humidity during foraging events. Our results showed that foraging routes are independent of residual soil accumulation and other nearby nests. However, air temperature and the time daily period are significant factors to foragers’ exits. Higher air temperatures influenced negatively the exits. In the period of the afternoon, the ants do not show any preference for routes, different from the morning and twilight. In addition, foraging activities were significantly more frequent during twilight period. Leaving the nest at twilight could allow ants foraging in an environment with less exposition to potential predators and competitors. Moreover, it may be also related to opportunism to hunt other nocturnal insects.

This study analyses regional development in one of the poorest provinces in China, Guizhou Province, between 2000 and 2012 using a multiscale and multi-mechanism framework. In general, regional inequality has been declining since 2000. In addition, economic development in Guizhou Province presented spatial agglomeration and club convergence, which shows how the development pattern of one core area, two-wing areas and a contiguous area at the edge of the province have been developed between 2006 and 2012. Multilevel regression analysis revealed that industrialization and investment level were the primary driving forces of regional economic disparity in Guizhou Province. The influences of marketization and decentralization on regional economic disparity were relatively weak. Investment level reinforced regional economic disparity and the development of core-periphery structure in the province. However, investment level actually weakened the regional economic disparity in Guizhou Province when the variable of time was considered. In addition, both the topography and urban–rural differentiation were the two main reasons for forming a core-periphery structure in Guizhou Province.

This paper investigates the potential of utilising multilevel quasi-interpolation techniques on Chebyshev sparse grids for complex numerical computations. The paper starts by laying down the motivations for choosing Chebyshev sparse grids and quasi-interpolation methods with Gaussian kernels. It delves into the practical aspects of implementing these techniques. Various numerical experiments are performed to evaluate the efficiency and limitations of the multilevel quasi-sparse interpolation methods with dimensions two dimension and three dimension. The work ultimately aims to provide a comprehensive understanding of the computational efficiency and accuracy achievable through this approach, comparing its performance with traditional methods.

Grayscale Lithography (GSL) is an alternative approach to the standard Binary Lithography in MEMSfabrication, enabling the fabrication of complicated arbitrary 3D structures on the wafer, without the need for multiple masks and exposure steps. Despite its advantages, GSL’s effectiveness is highly dependent on controlled lab conditions, equipment consistency, and finely-tuned photoresist exposure and etching processes. This works presents a thorough investigation of the challenges of GSL for Silicon (Si) wafers and presents a detailed approach on how to minimize the fabrication inaccuracies, aiming to replicate the intended design as closely as possible. Utilizing a maskless laser writer, all aspects of the GSL as analyzed, from photoresist (PR) exposure parameters to Si etching conditions. A practical application of GSL is demonstrated in the fabricationof 4 μm deep Silicon Fresnel Lenses for Long Wave Infrared imaging (8-12 μm). The surface topography of a Fresnel lens is a good case to apply GSL as it has varying shapes and size features that need to be preserved.. The final fabricated lens profiles show good match with the initial design and demonstrate successful etching of coarse and fine features and demonstrating images taken with an LWIR camera.

Information encryption and anti-counterfeiting play an important role in many aspects of daily life, such as in minimizing economic losses, protecting secure communication and public security, and so on. Owing to the high information capacity and ease of operation, luminescent materials for advanced information encryption and anti-counterfeiting are essential to meet the increasing demand on encryption security. Herein, we summarize two emerging luminescent materials for information encryption and anti-counterfeiting, the AIE materials and room-temperature phosphorescent materials. At last, we discuss the opportunities and anticipations of these two information encryption and anti-counterfeiting materials.

Recently, resistive random access memory (RRAM) has been an outstanding candidate among various emerging nonvolatile memories for high density storage and in-memory computing applications. However, the traditional RRAM, which accommodates two states depending on applied voltage, cannot meet the high density requirement in the era of big data. Many research groups have demonstrated that RRAM possesses the possibility of multi-level cell to overcome the demand of mass storage. Among numerous semiconductor materials, gallium oxide, as the fourth-generation semiconductor material, is highly-profile due to its excellent material proper-ties, and already be widely used in optoelectronics, high-power, resistive switching device and so on, due to its wide bandgap and transparent properties. In this study, we have successfully demonstrated the Al/GO/Ga2O3/ITO RRAM to achieve the possibility of two-bit storage. Compared to the single-layer counterpart, the bilayer structure has excellent electrical properties and stable reliability. The endurance characteristics could be enhanced above 100 switching cycles with an ON/OFF ratio of over 103. Moreover, the filament models are also described in this thesis to clarify the transport mechanisms.

Multilevel functional principal components analysis (mFPCA) is used to treat dynamical changes in shape in this article. Results of standard (single-level) FPCA are presented here also as a comparison. Monte Carlo (MC) simulation is used to create univariate data (i.e., a single “outcome” variable) that contains two distinct classes of trajectory with time. MC simulation is also used to create multivariate data of sixteen 2D points that represent (broadly) an eye; this data also has two distinct classes of trajectory (an eye blinking and an eye widening in surprise). This is followed-up by an application of mFPCA and single-level FPCA to “real” data consisting of twelve 3D landmark outlining the mouth that are tracked over all phases of a smile. By consideration of eigenvalues, results for the MC datasets find correctly that variation due to differences in groups between the two classes of trajectories variation are larger than variation within each group. In both cases, differences in standardized component scores between the two groups are observed, as expected. Modes of variation are shown to model the univariate MC data correctly, and good model fits are found for both the “blinking” and “surprised” trajectories for the MC “eye” data. Results for the “smile” data show that the smile trajectory is modelled correctly, namely: the corners of the mouth are drawn backwards and wider during a smile. Furthermore, the first mode of variation at level 1 of the mFPCA model show only subtle and minor changes in mouth shape due to sex, whereas the first mode of variation at level 2 of the mFPCA model govern whether the mouth is upturned or downturned. These results are all an excellent test of mFPCA, which show that mFPCA presents a viable method of modelling dynamical changes in shape.

The current paper aims to contribute to the literature on community renewable energy by considering two projects developed in the north-west of Italy, in the Piedmont region. The case-studies are analysed by combining two theoretical perspectives: the multilevel perspective and the sociotechnical imaginary approach. On the one hand, applying the first perspective helps reconstruct the context and circumstances that have permitted Piedmont’s energy community projects to emerge. In particular, attention is given to the windows of opportunity created by the passing of the Milleproroghe decree at the national level and by the ensuing regional law 12/2018, which acknowledged the establishment of energy communities in the Piedmont. On the other hand, the sociotechnical imaginary approach allows identifying collective ideas and meanings that emerge when individuals or groups promote a sociotechnical innovation. In our cases, two main future changes are associated with community renewable energy: an integral ecology approach and a stronger sense of community on the one hand, and local development opportunities for rural areas characterised by depopulation, low employment rate and high energy demand, on the other.

The exponential growth of population and the consistent food demand has compelled humanity to seek alternatives to traditional farming and innovative technologies to increase production. Exploring offshore for natural resources and alleviating pressure on land has been an ongoing research field, especially in the energy and aquaculture sector. However, the idea of floating farming is still in its infancy and requires significant innovations. The work presented here shed further light on this area by proposing a comprehensive model of ‘Integrated, multicultural, Multileveled Floating Farm (MFF).’ Various aspects of planning, design, constructions and operations of such MFF are discussed. An integrated waste management system is proposed to improve sustainability. The conceptual design and associated financial analysis demonstrated that such integration of various modes of farming could be profitable and sustainable at the same time. The cost estimation and profit analysis are presented in the context of Singapore, and a conservative approach is followed for the calculation. However, the model can easily be extended for application in other countries.

The past two decades has seen a growing demand for high-power, high-voltage utility scale inverters mostly fueled by the integration of large solar PV and wind farms. Multilevel inverters have emerged as the industry choice for these megawatt range inverters because their reduced voltage stress, capable of generating an almost sinusoidal voltage, in-built redundancy, among others. This paper present a new Switched-Source Multilevel Inverter (SS MLI) architecture. The new inverter show superior over existing topologies. It has reduced voltage stress on the semiconductor, uses less number of switches –reduced size/weight/cost and increased efficiency. The new SSMLI is comprised of two voltage sources (V₁, V₂) and 6 switches. It is capable of generating 5-level output voltage in symmetric modes (i.e., V₁ = V₂), and 7-level output voltage in asymmetric modes (i.e., V₁ ≠ V₂). To demonstrate the validity of the proposed inverter, simulations results using MATLAB^® /Simulink^® for 5- and 7-level output voltages are presented . The simulations are also verified experimentally using a laboratory prototype.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In some applications of microgrid and distributed generation, it is required to feed islanded or stand-alone loads with high-quality voltage to provide low total harmonic distortion (THD). To fulfil these demands, an LC filter is connected to the output terminals of power electronics converters. A cascaded voltage and current control loop with pulse-width modulation schemes are used to regulate the voltage and current in these systems. However, these strategies have some drawbacks, particularly when multiple-input multiple-output plants (MIMO) are controlled using single-input single-output (SISO) design methods. This methodology usually produces a sluggish transient response and cross-coupling between different control loops. In this paper, a model predictive control (MPC) strategy based on the concept of optimal switching sequences (OSS) is designed to control voltage and current in an LC filter connected to a three-level neutral-point clamped converter. The strategy solves two well-formulated optimisation problems to achieve control of the LC filter variables and the voltages of the DC-link capacitors. Hardware-in-the-Loop (HIL) results are obtained to validate the feasibility of the proposed strategy, using a PLECS-RT HIL platform and a DSP Microlab Box controller. In addition to the good dynamic performance of the proposed OSS-MPC, it is demonstrated by the HIL results that the control algorithm is capable of obtaining low total harmonic distortion (THD) in the output voltage for different conditions.

The participation of civil society is essential for environmental health policies to be effective. The objective of this study was to know the perceptions of government officials, members of civil society, and academics about environmental health problems and its governance in Bucaramanga Metropolitan Area, Colombia. In the region there is a strong citizen movement that defends the moorland ecosystem (paramo) as source of drinking water, of large-scale mining projects. A multi-method study was carried out including the review of newspaper and scientific articles, a citizen survey, and interviews and focus groups with identified key stakeholders. The findings indicate that government officials prioritize their actions on issues related to air and water pollution and environmental education. In contrast, citizens prioritize water availability from the moorland ecosystem. There are some advances in the management of environmental health, mainly related to greater citizen awareness. The participation of civil society in the environmental health governance must be enforced to broaden the issues of interest and prioritize the activities in the short- and long-term policy planning. An experience between high school students and the academy that measures air pollutants can be the first meeting point with government officials in the pathway to improve the environmental governance in the territory.

The purpose of this study was to identify the factors that affect the mortality among adult HIV/TB co-infected patients and to see the nutritional difference among mortality in residence level. Retrospective cohort studies of 417 patients which fulfill our criteria were included. Multilevel logistic regression models were used. MLwiN and SPSS software are used to estimate the parameter. The variance of the random factor in the empty model was significant which indicates that there were residential differences in TB-HIV co-infected mortality and it shows multilevel analysis was an appropriate approach for further analysis. The prevalence of HIV/TB co-infected patients' death was 12.9% in study time. Functional status, age of patients, WHO clinical stages, nutritional status, CD4 counts, regimen, and BMI were found to be significant determinants of HIV/TB co-infected mortality. In our study, patients with the bedridden category of functional status, the fourth stages of WHO clinical stages (stage IV), patients with higher age, patients whose treatments were second-line regimen and low CD4 cell counts were more at risk of death. The study also revealed that; poor nutritional status increased the risk of mortality among HIV/TB co-infected patients and it varies among the residence of the patients (rural area were more at risk).

Single-level Principal Components Analysis (PCA) and multi-level PCA (mPCA) methods are applied here to a set of (2D frontal) facial images from a group of 80 Finnish subjects (34 male; 46 female) with two different facial expressions (smiling and neutral) per subject. Inspection of eigenvalues gives insight into the importance of different factors affecting shapes, including: biological sex, facial expression (neutral versus smiling), and all other variations. Biological sex and facial expression are shown to be reflected in those components at appropriate levels of the mPCA model. Dynamic 3D shape data for all phases of a smile made up a second dataset sampled from 60 adult British subjects (31 male; 29 female). Modes of variation reflected the act of smiling at the correct level of the mPCA model. Seven phases of the dynamic smiles are identified: rest pre-smile, onset 1 (acceleration), onset 2 (deceleration), apex, offset 1 (acceleration), offset 2 (deceleration), and rest post-smile. A clear cycle is observed in standardized scores at an appropriate level for mPCA and in single-level PCA. mPCA can be used to study static shapes and images, as well as dynamic changes in shape. It gave us much insight into the question “what’s in a smile?”

This paper evaluates the open and closed loop DC-DC converter operation within a DC coupling multilevel inverter architecture to obtain an infinite level stepped sinusoidal voltage. Adding a cascade controller to the DC-DC converter should reduce the settling time and increase the number of levels in the output voltage waveform, it could decrease the speed error and phase shift concerning the sinusoidal reference signal. The proposed methodology consists of implementing an experimental multilevel inverter with DC coupling, through a single-phase bridge inverter energized from a BUCK converter, trigger signals for the two converters are obtained from a control circuit based in an ATMEGA644P microcontroller, and a digital controller is also implemented to evaluate the operation of the BUCK converter in open and closed loop and observe its influence in the stepped sinusoidal output voltage. The evaluation is performed to energize a resistive load with common output voltage in multilevel inverters, that is 3, 5, 7, 11, and infinity levels. Results show that during the design stage, fast dynamic elements, like the storage capacitor, can be used to obtain a minimum THD because the settling time is sufficiently fast and the speed error remains small and there isn’t a need for a controller. A digital controller requires processing time and although in theory, it can reduce the settling time to a minimum, the processor introduces latency in the control signals generation, producing the opposite effect. Controller complexity of the digital controller must be considered because it increases processing time and influences the efficiency of the closed-loop operation.

3D facial surface imaging is a useful tool in dentistry and in terms of diagnostics and treatment planning. Between-groups PCA (bgPCA) is a method that has been used to analyse shapes in biological morphometrics, although various “pathologies” of bgPCA have recently been proposed. Monte Carlo (MC) simulated datasets were created here in order to explore “pathologies” of multilevel PCA (mPCA), where mPCA with two levels is equivalent to bgPCA. The first set of MC experiments involved 300 uncorrelated normally distributed variables, whereas the second set of MC experiments used correlated multivariate MC data describing 3D facial shape. We confirmed previous results of other researchers that indicated that bgPCA (and so also mPCA) can give a false impression of strong differences in component scores between groups when there is none in reality. These spurious differences in component scores via mPCA reduced strongly as the sample sizes per group were increased. Eigenvalues via mPCA were also found to be strongly effected by imbalances in sample sizes per group, although this problem was removed by using weighted forms of covariance matrices suggested by the maximum likelihood solution of the two-level model. However, this did not solve problems of spurious differences between groups in these simulations, which was driven by very small sample sizes in one group here. As a “rule of thumb” only, all of our experiments indicate that reasonable results are obtained when sample sizes per group in all groups are at least equal to the number of variables. Interestingly, the sum of all eigenvalues over both levels via mPCA scaled approximately linearly with the inverse of the sample size per group in all experiments. Finally, between-group variation was added explicitly to the MC data generation model in two experiments considered here. Results for the sum of all eigenvalues via mPCA predicted the asymptotic amount for the total amount of variance correctly in this case, whereas standard “single-level” PCA underestimated this quantity.

Framed in a context with an emerging economy and with a high percentage of school failure, this study aimed to identify the factors that turn students with socioeconomic disadvantages into resilient students. Two questions guided the research: Can resilience be supported in students in adverse socioeconomic situations? What factors influence building resilient students? A cross-sectional study was carried out from 2011 to 2015 in Chile, using a multilevel logistic regression model with three levels, considering the hierarchical data structure. The behavior of 63100 to 76400 sampled students was analyzed. Results show five relevant factors in building resilience: self-efficacy in language, minor aggressions and violence perceived by students, norms and values of the establishment, interest in study, and self-efficacy. Some risk factors identified were an atmosphere of less respect and trust, engagement in physical education activities and good performance in carrying them out. These results could orient educational leaders interested in supporting the educational community in order to improve the academic success of disadvantaged students.

A modular switched-capacitor (SC) DC-DC converter (MSCC) is introduced in this paper. It is designed to boost a low input voltage to a high voltage level and can be applied for photovoltaics and electric vehicles. This topology has high extensibility for high voltage gain output. The merits of the converters also lie in the fault tolerance operation and the voltage regulation with a minimum change in the duty ratio. Those features are built in when designing the modules and then integrating these into the DC-DC converter. Converter performance including voltage gain, voltage and current stress are focused and tested. The converter is modelled analytically, and its control algorithm is analyzed in detailed. Both simulation and experiment are carried out to verify the topology under normal operation and fault mode operation.

Introduction: One of the key strategies to achieve sustainable development goal by reduce preventable maternal deaths below 70 per 100,000 is increasing awareness about major obstetrics danger sign. Mother's awareness of obstetric danger signs in developing country is relatively low regardless of attempts trough many local and national program. It is crucial to increase women’s knowledge of obstetric danger signs through education and awareness-raising efforts. Despite its importance to reduce maternal deaths, Studies are limited only to the Northern Ethiopia. Objective: This study aimed to assess prevalence of knowledge of obstetric danger signs and associated factors among women who delivered in the last 12 months in Sidama region, Ethiopia. Methods: We conducted a community-based cross-sectional study from October to November, 2022. A multi-stage sampling procedure was utilized to select study participants. A structured and pretested questionnaire was utilized to collect data. A multilevel mixed-effects negative binomial regression model was used to control effects of clusters and confounders.Results: Out of 1,140 study participants, only 1,130 study participants took part in the study making a response rate of 99.12%. The overall prevalence of knowledge of obstetrics danger sign was estimated as 22.3% (95%CI: 18.7, 25.9). Government employed women (AIRR = 1.37; 95% CI: 1.2, 1.6), women who had access to mass media (AIRR = 1.16; 95% CI: 1.08, 1.25), women who had received model family training (AIRR = 1.15; 95% CI: 1.1, 1.25), autonomous women (AIRR = 1.15; 95% CI: 1.04, 1.25), women who had faced health problems during pregnancy (APR = 1.21; 95% CI: 1.11, 1.32) and urban women (APR = 1.22; 95% CI: 1.09, 1.62) were factors associated positively with knowledge of obstetrics danger sign. Conclusion: The prevalence of knowledge of obstetrics danger sign is found to be lower compared with the national average. Residence, mass-media exposure, model family planning, problem faced during pregnancy and women autonomy are the main predictors of knowledge of obstetrics danger sign. Public health policy makers should enhance health literacy at for focused on rural community. Awareness creation should be improved through mass media. Health providers should educate women during maternity health services to empower women for decision making process.

Introduction: Weighting is widely used in applied statistics especially while dealing with survey data. In recent years, multilevel modeling under complex survey designs has increased, resulting into demand for level weights. However, survey data that are accessible to the public for use usually do not contain level weights that are useful in multilevel modeling, but final survey weights that are only appropriate for single level analyses. In this paper, we demonstrate how the final survey weights can be used to estimate level weights for multilevel data analysis, and compare a model that applied level weights with one that applied the final survey weights. Methods: A framework for approximating level weights proposed by the Demographic Health Survey (DHS) program was used to estimate the level weights. Models were fitted using a multilevel mixed effects logistic regression method. Estimates from a model that applied survey weights was compared to those from a model that applied level weights. Results: Application of final survey weights instead of level weights underestimated standard errors and led to loss of precision of model estimates. Conclusions: Use of level weights produces estimates with high precision and yields correct values of standard errors hence appropriately informing inference.

This retrospective study aimed to investigate the effect of known risk factors on nonsurgical periodontal treatment (NSPT) response using a pocket depth fine-tuning multilevel linear model (MLM). Thirty-seven patients (24 males and 13 females) with moderate to severe chronic periodontitis were treated with nonsurgical periodontal therapy. Follow-up visits at 3, 6, and 12 months included measurement of several clinical periodontal parameters. Data were extracted from a database system. Probing depth (PD) and Clinical Attachment Loss (CAL) reductions after NSPT in an overall of 1416 initially affected sites (baseline PD ≥ 4 mm), distributed on 536 teeth, were analyzed against known risk factors at three hierarchical levels (patient, tooth and site). The variance component models fitted to assess the three-level variance of PD and CAL decrease for each post-treatment follow-up showed that all levels contributed significantly to the overall variance (P < 0.001). Patients that underwent NSPT and were continually monitored had very curative results. All three hierarchical levels included risk factors who had impact on the to influence the magnitude of PD and CAL reduction. Specifically, the tooth’s type, surfaces involved and teeth mobility site-level risk factors showed the highest influence on these reductions, being highly relevant factors for the NSPT success.

We consider a class of density-driven flow problems. We are particularly interested in the problem of the salinization of coastal aquifers. We consider the Henry saltwater intrusion problem with uncertain porosity, permeability, and recharge parameters as a test case. The reason for the presence of uncertainties is the lack of knowledge, inaccurate measurements, and inability to measure parameters at each spatial or time location. This problem is nonlinear and time-dependent. The solution is the salt mass fraction, which is uncertain and changes in time. Uncertainties in porosity, permeability, recharge, and mass fraction are modeled using random fields. This work investigates the applicability of the well-known multilevel Monte Carlo (MLMC) method for such problems. The MLMC method can reduce the total computational and storage costs. Moreover, the MLMC method runs multiple scenarios on different spatial and time meshes and then estimates the mean value of the mass fraction. The parallelization is performed in both the physical space and stochastic space. To solve every deterministic scenario, we run the parallel multigrid solver ug4 in a black-box fashion. We use the solution obtained from the quasi-Monte Carlo method as a reference solution.

Multi-threshold image segmentation is a relevant research field in further higher-level image preprocessing and computer vision. This paper adopts the Bayesian Forecasting Evolutionary Algorithm (BFEA) for natural scenery image segmentation using multilevel thresholding. An update method for the prediction vector is designed for image segmentation. The design idea of the BFEA algorithm for multilevel thresholding is based on the basic principle of Evolutionary Computation, the probability distribution of promising solutions, and the Bayesian theorem. BFEA could effectively solve the curse of dimensionality. Extensive experiments have demonstrated that the proposed algorithm dominated the state-of-the-art population-based thresholding method in term of the quality of image, function fitness value, optimal threshold value, SSIM value, PSNR value, computation time, dimensionality issue and convergence rate. The proposed method is very effective for color image segmentation.

Ice covering on overhead transmission lines would cause damage to transmission system and long-term power outage. Among various de-icing devices, modular multilevel converter (MMC) based DC de-icer (MMC-DDI) is recognized as a promising solution due to its excellent technical performance. Its principle feasibility has been well studied, but few literature discuss its economy or hardware optimization, thus the designed MMC-DDI for high voltage transmission lines is usually too large and too expensive for engineering applications. To fill this gap, this paper presents a quantitative analysis on the converter characteristics of MMC-DDI, and calculates the minimal converter rating and its influencing factors. It reals that, for a given de-icing requirement, the converter rating varies greatly with its AC-side voltage. Then an optimization configuration is proposed to reduce the converter rating and improve its economy. The proposed configuration is verified in a MMC-DDI for a 500kV transmission line as a case study. The result shows, in the case of outputting same de-icing characteristics, the optimized converter rating is reduced from 151 MVA to 68 MVA, and total cost of MMC-DDI is reduced by 48%. This analysis and conclusion are conductive to the optimized design of multilevel DC de-icer, then to its engineering application.

This paper presents the design and implementation of a digital control system for modular multilevel converters (MMC) and its use in a 5-kW small scale prototype. To achieve higher system control reliability and multi-functionality, the proposed architecture has been built with an effective split of the control tasks between a master controller and six slave controllers, one for each of the six arms of the converter. The MMC prototype have been used for testing both converter and system level controls in a reduced scale laboratory set up of a Multi-Terminal DC transmission network (MTDC). The whole control has been tested in order to validate the proposed control strategies. The tests performed at system level allowed to explore the advantages of using an MMC in a MTDC system.

The resilience of towns and cities refers to their ability to adapt and recover when confronted with pressures or challenges. This study employs ten variables as indicators to assess the resilience of urban areas by analyzing official data and constructing a multilevel mixed-effects structural equation model. The empirical findings demonstrate that enhancing resilience significantly influ-ences urban service functions, such as strengthening healthcare systems, stabilizing the real estate market, and addressing socio-economic challenges. Specifically, factors such as healthcare re-sources, housing demand, population structure, and social security exhibit varying levels of resil-ience, which profoundly impact the spatial distribution of these factors and socio-economic de-velopment. Disparities in healthcare resource allocation, demographic aging trends, and shifts in the housing market closely correlate with resilience levels in different regions. Additionally, the study emphasizes that improving resilience not only boosts the reliability and security of urban services but also ensures that communities receive necessary support and protection during times of adversity. Consequently, policymakers should recognize the pivotal role of urban resilience in resource allocation and social equity, devising corresponding strategies to enhance the resilience of these areas.

Background: Obstructive sleep apnea (OSA) is caused by partial or complete obstruction of the upper airways. Corrective surgeries aim at removing obstructions in the nasopharynx, oropharynx, and hypopharynx. OSA is associated with increased risk of various metabolic diseases. Our objective was to evaluate the effect of surgery on the plasma metabolome. Methods: This study included 39 OSA patients who underwent Multilevel Sleep Surgery (MLS). Clinical and anthropometric measures were taken at baseline and 5 months after surgery. Results: The mean Apnea Hypopnea Index (AHI) significantly dropped from 22.0 ± 18.5 events/hour to 8.97 ± 9.57 events/hour (p-Value <0.001). The Epworth’s sleepiness Score (ESS) dropped from 12.8 ± 6.23 to 2.95 ± 2.40 (p-Value <0.001) indicating success of the surgery in treating OSA. Plasma levels of metabolites, phosphocholines (PC) PC.41.5, PC.42.3, ceremide (Cer) Cer.44.0, and triglyceride (TG) TG.53.6, TG.55.6 and TG.56.8 were decreased (p-Value<0.05) whereas lysophosphatidylcholines (LPC) 20.0 and PC.39.3 were increased (p-Value<0.05) after surgery. Conclusion: This study highlights the success of MLS in treating OSA. Treatment of OSA resulted in improvement in metabolic status that was characterized by decreased TG, PCs and Cer metabolites post-surgery indicating that the success of the surgery positively impacted the metabolic status of these patients.

The main aim of this work is to present a step-by-step procedure to model and analyze the power loss distribution of three-level Gallium Nitride (GaN) inverters. It has been applied to three distinct three-phase three-levels voltage source inverters utilized in electric traction drives: Active Neutral Point Clamped, Neutral Point Clamped and T-Type Neutral Point Clamped. The proposed analytical power loss modelling, combined to an equivalent representation of the electrical machine demonstrated to be a viable solution to achieve a time-saving and low computational burden simulation platform, leading to satisfying accuracy results. This has been confirmed by comparing the results carried out from the simulations of a 110kW permanent magnet synchronous motor drive and those determined by considering a simplified circuital representation based on the proposed analytical power loss modelling.

This paper is concerned with developing an efficient numerical algorithm for fast implementation of the sparse grid method for computing the $d$-dimensional integral of a given function. The new algorithm, called the MDI-SG ({\em multilevel dimension iteration sparse grid}) method, implements the sparse grid method based on a dimension iteration/reduction procedure, it does not need to store the integration points, nor does it compute the function values independently at each integration point, instead, it reuses the computation for function evaluations as much as possible by performing the function evaluations at all integration points in a cluster and iteratively along coordinate directions. It is shown numerically that the computational complexity (in terms of CPU time) of the proposed MDI-SG method is of polynomial order $O(Nd^3 )$ or better, compared to the exponential order $O(N(\log N)^{d-1})$ for the standard sparse grid method, where $N$ denotes the maximum number of integration points in each coordinate direction. As a result, the proposed MDI-SG method effectively circumvents the curse of dimensionality suffered by the standard sparse grid method for high-dimensional numerical integration.

Power converter technologies have become increasingly vital in various applications due to their efficient management of electrical energy. With the growing prominence of renewable energy sources like solar and wind, the high penetration of power electronic converters has been justified. However, ensuring power quality has emerged as a significant challenge for grid-connected power converters. The divergence from the ideal sinusoidal waveform in terms of magnitude and frequency impacts both grid-side currents and voltages. Several studies have proposed solutions to address power quality issues at the load side. The advancement of power converters has been fueled by the development of high-performance microprocessors and the emergence of high-speed switching devices, such as SiC-MOSFETs. This paper focuses on the design of voltage source converters, particularly those based on SiC-MOSFET semiconductor devices. The article presents the design of H-Bridge cells, discusses two-level voltage source converters based on cascade H-Bridge cells in parallel configuration with experimental fault analysis, addresses the seven-level voltage source converters topology, and explores the design and experimental results of the matrix converter. The findings underscore the importance of considering the entire converter design for improved performance at high switching frequencies. The article concludes by summarizing the main outcomes and implications of this research.

This article proposes the multilayer and multilevel cosmological model, on average, balanced with respect to the Einsteinian vacuum. This hierarchical model is based on 10 possible Kottler solutions of the extended Einstein's field equations. The extension of the Einstein field equations is associated with the addition of an infinite number of lambda_j-terms to these equations with the condition that the series (i.e., the total sum) of these terms converges to zero. A simplified ten-layer and ten-level case is considered, in which ten spherical formations are sequentially nested into each other like "nesting dolls", while the radii of these spherical formations correspond to the characteristic sizes of a discrete sequence of observed spherical objects: metagalaxy core, galactic cores, stellar (planet) core, biological cells and nuclei of atoms and elementary particles, etc. As an example, from the general ten-level (hierarchical) solution of extended Einstein's field equations, two antipodal spherical formations with a core radius commensurate with the classical electron radius are singled out. Therefore, the metric-dynamic models of these formations obtained in this way are called «electron» and «positron». The article is aimed at the development of differential geometry and the program for the complete geometrization of physics by Clifford-Einstein-Wheeler.

In Low and Lower-Middle-Income countries, the prevalence of anemia in infancy remains high. In early childhood anemia cause irreversible cognitive deficits and represents a higher risk of child mortality. The consequences of anemia in infancy are a major barrier to overcome poverty traps. The aim of this study was to analyze based on a multi-level approach, different factors associated with anemia in children 6–23 m old based on recent available Standard Demographic Health Surveys (S-DHS). We identified 52 S-DHS that had complete information in all covariates of interest in our analysis between 2005 and 2015. We performed traditional logistic regressions and multilevel logistic regression analyses to study the association between hemoglobin concentrations and household, child, maternal, socio-demographic variables. In our sample, 70 % of the 6–23 m old children were anemic. Child anemia was strongly associated with maternal anemia, household wealth, maternal education and low birth weight. Children fed with fortified foods, potatoes and other tubers had significantly lower rates of anemia. Improving overall household living conditions, increasing maternal education, delaying childbearing and introducing iron rich foods at six months of age may reduce the likelihood of anemia at in toddlerhood.

European strategic policy directions towards a sustainable blue economy have strengthened interest in maritime investments, thus increasing sectoral competition for marine space. Emerging repercussions out of such a rising interest need to be handled by Marine Spatial Planning (MSP) as a means for: properly allocating marine space to diverse uses; managing conflicts and promoting synergies among them; and pursuing a multi-use perspective of this space. A critical stage of each MSP exercise is the exploration of land-based spatial/developmental directions and their current or potential repercussions in the marine environment in order for constraints but also perspectives in policy choices/maritime uses in the MSP context to be featured; and attainment of a successful coherence or coordination between land and marine spatial/developmental policies to be ensured, by analyzing Land-Sea-Interaction (LSI) and embedding it in the MSP. The latter is the focus of this paper aiming to illuminate critical issues emerging from land-based (terrestrial) policy frameworks for feeding MSP endeavors; and is accomplished in the Northern Aegean Sea, Greece. Towards this end, a multilevel approach is adopted, delving into diverse policy contexts at the local, regional and national/European level and aiming to attain more informed MSP decisions in the specific study region.

The medium-voltage DC (MVDC) technology has gained increasing interests in recent years. Power electronics devices dominate those grids. Accurate simulation of such a grid, with detailed models of switching semiconductors, can quickly became very time-consuming, according to the number of connected devices to be simulated. A simulation approach based on interactions on a continuous time model can be very interesting, especially for developing a system level control model of such a modern MVDC distribution grid. Aim of this paper is to present all the steps required for obtaining a continuous time modelling of a +/- 10 kV MVDC grid case study, including Solid State Transformer (SST) and Modular Multilevel Converter (MMC) based Active Front End (AFE). Additional aim of this paper is to supply an educational content about the use of the continuous time simulation approach, thanks to a detailed description of the various devices modelled into the presented MVDC grid. The results of a certain number of simulation scenarios are eventually presented.

The persistence of geographic inequities in vaccination coverage often evidences the presence of zero-dose and missed communities and vulnerabilities to vaccine-preventable diseases. These inequities were exacerbated in many places during the COVID-19 pandemic, due to severe disruptions to vaccination services. Understanding changes in zero-dose prevalence and associated risk factors in the context of the COVID-19 pandemic is, therefore, critical to designing effective strategies to reach vulnerable populations. Using data from nationally representative household surveys conducted before the COVID-19 pandemic in 2018 and during the pandemic in 2021 in Nigeria, we fitted Bayesian geostatistical models to map the distribution of three vaccination coverage indicators: receipt of DTP1, MCV1 and any of the four basic vaccines (BCG, OPV0, DTP1 and MCV1), and corresponding zero-dose estimates independently at 1x1 km resolution and the district level during both time periods. We also explored changes in the factors associated with non-vaccination at the national and regional levels using multilevel logistic regression models. Our results revealed no increases in zero-dose prevalence due to the pandemic at the national level, although considerable increases were observed in a few districts. We found substantial subnational heterogeneities in vaccination coverage and zero-dose prevalence both before and during the pandemic, showing broadly similar patterns in both time periods. Areas with relatively higher zero-dose prevalence occurred mostly in the north and a few places in the south in both time periods. We also found consistent areas of low coverage and high zero-dose prevalence using all three zero-dose indicators, revealing areas in greatest need. At the national level, risk factors related to socioeconomic/ demographic status (e.g., maternal education), maternal access to and utilization of health services and remoteness were strongly associated with the odds of zero dose in both time periods, while those related to communication were mostly relevant before the pandemic. These associations were also supported at the regional level, but we additionally identified risk factors specific to zero dose in each region; for example, communication and cross-border migration in the northwest. Our findings can help guide tailored strategies to reduce zero-dose prevalence and boost coverage levels in Nigeria.

Family support is offered to Australian parents of young children using a mix of targeted and universal child and family health services. A feature of the universal services is the ability for nurses to work in partnership with families and to offer flexibility depending on need. This model of progressive universalism relies on the voluntary engagement of families, including families with complex needs. In this study, the capacity to engage and retain families, including those at risk for child maltreatment and family violence, was examined. Child and Family Health Nurses (n=129) participated in a pragmatic, multilevel mixed-methods study using the McCurdy and Daro (2001) Integrated Theory of Parent Involvement. A questionnaire was used in the first phase of the study to collect the quantitative data. Focus groups were then held with 27 participants recruited from phase one. Both homogeneous and heterogenous practices identified from the questionnaire were the focus of the discussions. Three phases of practice were identified and described: enrolment, retention and conclusion of the nurse-parent relationship and are presented and discussed in this paper. The retention of families with complex needs relies on flexible, advanced, and multidimensional nursing practices.

In an era of rapid technological advancements, complex global challenges, and intense market competition, the ability to generate and scale innovative solutions has become a critical imperative for organizations, policymakers, and societies worldwide. However, the existing academic landscape has lacked a cohesive, multidisciplinary framework for comprehensively understanding the multifaceted nature of innovation. Innovationology, a newly established scientific discipline, aims to address this gap by providing a unifying, transdisciplinary approach to the study and practice of transformative innovation. This comprehensive article introduces Innovationology as a cutting-edge science that integrates insights from diverse fields, including management, psychology, sociology, economics, and technology studies. Innovationology posits that innovation is a multilayered, context-dependent phenomenon, shaped by the intricate interplay of individual, team, organizational, and ecosystem-level factors. By synthesizing the latest theoretical advancements and empirical evidence, this article presents a holistic model of Innovationology that illuminates the key determinants of radical, game-changing innovations capable of disrupting existing industries and creating new market spaces. The article delves deep into the individual cognitive, behavioral, and motivational drivers of innovativeness, the team dynamics and organizational structures that foster collaborative innovation, and the ecosystem-level characteristics that catalyze the emergence and scaling of transformative innovations. Importantly, the article explores the crucial role of contextual factors, such as socio-cultural norms, institutional support, and resource availability, in shaping innovation outcomes. This article also establishes the epistemological foundations of Innovationology, grounding it in a transdisciplinary, holistic, and pragmatic approach to knowledge generation. Innovationology embraces a pluralistic epistemology that acknowledges the complexity and context-dependence of innovation, drawing on diverse methodological approaches to capture the multifaceted nature of this phenomenon. Furthermore, the article outlines the object of Innovationology, which is to provide a comprehensive, evidence-based understanding of the drivers, processes, and outcomes of transformative innovation. Innovationology seeks to elucidate the multilevel determinants of innovation, the dynamic interplay between various factors, and the contextual influences that shape innovation trajectories. By establishing a unifying, transdisciplinary framework, Innovationology aims to bridge the gap between innovation theory and practice, empowering a wide range of stakeholders to unlock the transformative potential of innovation. Importantly, this article outlines the practical applications of Innovationology, providing comprehensive strategies and evidence-based interventions for cultivating innovative mindsets, designing innovation-conducive organizational systems, and navigating the challenges of innovative ecosystems. The implications of Innovationology for entrepreneurs, corporate leaders, policymakers, and innovation scholars are discussed in detail. By establishing Innovationology as a distinct, authoritative scientific discipline, this article sets the foundation for a more holistic, context-sensitive understanding of innovation and its multifaceted drivers. The insights generated by this new science can empower global organizations, institutions, and policymakers to address the complex, interconnected challenges of the 21st century through the strategic deployment of transformative innovations.