Standard Modules Research Articles

Highly Improved PID Stability for Cu(In,Ga)Se2 Solar Modules Due to a Filled P1 Groove

Two types of Cu(In,Ga)Se2 (CIGS) thin-film solar modules, differing only in the patterning procedures, were exposed to a high voltage (1 kV) across the thickness of the soda-lime glass substrate. Both module types utilized a cell stack, and in particular, a molybdenum back contact, which was optimized for CIGS solar cells with enhanced stability against potential-induced degradation (PID). A standard module with regular patterning lines for monolithic interconnection consists of P1, P2, and P3 lines, with P1 separating the back contact, P2 establishing the contact between the front contact TCO of one cell to the Mo back contact of the next cell, and P3 isolating the front contact from one cell to the next cell. However, modules employing this cell stack with regular patterning lines P1, P2, and P3 suffered considerably from PID while modules with a P1 groove filled with an insulator showed greatly enhanced stability similar to the pure single cell without P1 patterning. PID manifests once a specific quantity of charge has been transmitted through the soda-lime glass substrate, while the molybdenum back contact of the cell functions as the cathode, maintaining a negative bias relative to the substrate’s backside. As a consequence of PID, sodium is increased in the adsorber for susceptible cells. Therefore, inhibiting sodium transport through the P1 groove by filling it with an insulating material enhances the PID stability of the modules considerably. As a result, the modules with a filled P1 groove showed similar stability to the single solar cells with an improved PID stable cell stack, while modules without a filled P1 patterning were much more susceptible to PID, although a cell stack with greatly enhanced PID stability was used. In summary, the presented strategy to fill the P1 groove offers a viable and novel path to improved PID stability of CIGS modules.

A two-stage robust reversible watermarking using polar harmonic transform for high robustness and capacity

Designing the robust reversible watermarking (RRW) with high robustness and capacity while maintaining invisibility and reversibility is a challenging problem. To alleviate this problem, we present a two-stage RRW scheme using the polar harmonic transform (PHT). In the first stage, it selects robust PHT moments for robust watermarking, develops an adaptive normalization strategy, and constructs a robust watermark embedding method. Specifically, the PHT moments with high robustness are first chosen via experimental simulations. The adaptive normalization strategy is then developed to adjust the robust watermark's embedding strength for the selected moments, aiming at achieving higher robustness. By adjusting quantized errors to integers, the standard distortion-compensated quantization index modulation (DC-QIM) is optimized. And the optimized DC-QIM for embedding robust watermark facilitates decreasing the number of bits of quantized errors representation and thus increasing the embedding capacity. In the second stage, the reversible watermarking is conducted to achieve reversibility in the absence of attacks. That is, distortions caused by the robust watermark embedding are inserted by a reversible watermarking technique. The proposed scheme performs better than state-of-the-arts in terms of bit error rate (BER) performance, according to extensive experimental results. Our code is available at https://github.com/yichao-tang/PHT-RRW.

Development of a Reference Process Model for the Modularization of Production‐Related Logistics in the Chemical Industry

AbstractTrends towards product differentiation, fast changing market conditions, and shorter product lifecycles demand flexible production solutions for the chemical industry. Modular production systems promise to provide the required capacities as needed in a short period of time. However, the potential of modular production systems can only be fully utilized if they are embedded in modular and thus flexible logistics processes. For this reason, standardized logistic modules need to be defined. Process standardization is the starting point for reducing the number of variants and minimizing the number modules. Thus, in this paper a reference process model is developed. The standardized processes defined in this model are then used to form modules by applying a method from cluster analysis.

In vitro modeling of polyclonal infection dynamics within the human airways by Haemophilus influenzae differential fluorescent labeling.

Standardized clinical procedures for antibiotic administration rely on pathogen identification and antibiotic susceptibility testing, often performed on single-colony bacterial isolates. For respiratory pathogens, this could be questionable, as chronic patients may be persistently colonized by multiple clones or lineages from the same bacterial pathogen species. Indeed, multiple strains of nontypeable Haemophilus influenzae, with different antibiotic susceptibility profiles, can be co-isolated from cystic fibrosis and chronic obstructive pulmonary disease sputum specimens. Despite this clinical evidence, we lack information about the dynamics of H. influenzae polyclonal infections, which limits the optimization of therapeutics. Here, we present the engineering and validation of a plasmid toolkit (pTBH, toolbox for Haemophilus), with standardized modules consisting of six reporter genes for fluorescent or bioluminescent labeling of H. influenzae. This plasmid set was independently introduced in a panel of genomically and phenotypically different H. influenzae strains, and two of them were used as a proof of principle to analyze mixed biofilm growth architecture and antibiotic efficacy, and to visualize the dynamics of alveolar epithelial co-infection. The mixed biofilms showed a bilayer architecture, and antibiotic efficacy correlated with the antibiotic susceptibility of the respective single-species strains. Furthermore, differential kinetics of bacterial intracellular location within subcellular acidic compartments were quantified upon co-infection of cultured airway epithelial cells. Overall, we present a panel of novel plasmid tools and quantitative image analysis methods with the potential to be used in a whole range of bacterial host species, assay types, and/or conditions and generate meaningful information for clinically relevant settings. IMPORTANCE Genomic diversity of nontypeable H. influenzae strains confers phenotypic heterogeneity. Multiple strains of H. influenzae can be simultaneously isolated from clinical specimens, but we lack detailed information about polyclonal infection dynamics by this pathogen. A long-term barrier to our understanding of this host-pathogen interplay is the lack of genetic tools for strain engineering and differential labeling. Here, we present a novel plasmid toolkit named pTBH (toolbox for Haemophilus), with standardized modules for fluorescent or bioluminescent labeling, adapted to H. influenzae requirements but designed to be versatile so it can be utilized in other bacterial species. We present detailed experimental and quantitative image analysis methods, together with proof-of-principle examples, and show the ample possibilities of 3D microscopy, combined with quantitative image analysis, to model H. influenzae polyclonal infection lifestyles and unravel the co-habitation and co-infection dynamics of this respiratory pathogen.

High field suppression of bremsstrahlung emission in high-intensity laser–plasma interactions

The interaction of high-intensity lasers with plasma is predicted to produce extreme quasi-static magnetic fields with magnitudes approaching Megatesla levels. In relativistically transparent plasmas, these fields can enhance direct laser acceleration and allow efficient gamma-ray emission by accelerated electrons. However, due to the so-called magnetic suppression effect, the magnetic field can also affect radiating electron trajectories and, thus, reduce the emission probability of the bremsstrahlung. This is the first study to examine the bremsstrahlung suppression mechanism in the context of high-intensity laser–plasma interactions. Our paper describes a new module that integrates the suppression effect into the standard bremsstrahlung module of the EPOCH particle-in-cell code by considering the impact of magnetic fields and extending the analysis to electric fields. We also investigate this suppressing mechanism's effect on the emitting electron's dynamics. Our findings show that this mechanism not only suppresses low-energy emissions but also has an impact on the dynamics of the radiating electrons.

Model Predictive Direct Self-Control for Six-Step Operation of Permanent-Magnet Synchronous Machines

The optimization of voltage utilization can boost electric drives' power and torque capabilities, which is of particular interest in transportation applications. However, this is a weak point of most control approaches, like linear field-oriented control (FOC) methods using standard modulation schemes. This paper introduces the model predictive direct self-control (MPDSC) strategy, a modification of direct self-control (DSC) for its application in a digital implementation to achieve maximum voltage utilization (i.e., six-step operation) for permanent magnet synchronous machines. This solution is suitable for highly utilized machines with heavy magnetic (cross-)saturation and low sampling to fundamental frequency ratio. The modifications include using load angle regulation to control the selected operating point and model prediction to compensate for the actuation delay. The proposed system can achieve six-step operation with accurate torque control and robustness against disturbances and parameter estimation inaccuracies. Comprehensive simulation and experimental results demonstrate the performance of the proposed MPDSC while operating at the voltage constraint. In particular, a transient rise time of 2.3 ms to maximum torque, current reduction for equal torque-speed operating point of up to 18 %, and maximum torque increase for equal current amplitude of up to 15 % compared to conventional FOC have been empirically observed.

Experimental evaluation of thermal efficiency, electrical efficiency, and power production of low-concentrating photovoltaic-thermal system with micro-jet channel

The efficient behavior of a low-concentrating photovoltaic-thermal system with a micro-jet channel (LCPV/T-JET) and booster mirror reflector is experimentally evaluated here. Micro-jets promote the thermal management of PV solar cells by implementing jet water as active cooling, which is still in the early stages of development. The booster mirror reflector concentrates solar irradiance into solar cells and improves the thermal, electrical, and combined efficiencies of the LCPV/T-JET system. The LCPV/T-JET system was tested under ambient weather conditions in the city of Bangi, Selangor, Malaysia, and all data was recorded between 10:00 a.m. and 4:00 p.m. Parametric studies were conducted to compare the performance of the LCPV/T-JET system to that of a conventional PV module. It is found that the short-circuit current of a standard PV module could be increased by 28% and 11.7%, with and without the use of jet water and booster mirror reflectors, respectively. Moreover, the power supplied by the PV component increases to 31% and 16%, respectively, with and without jet water and a booster mirror reflector. The characteristic curves for current–voltage and power–voltage curves also confirmed the superior thermoelectric properties of the LCPV/T-JET system. The measurements reveal a drop in the electrical efficiency of solar cells from 14.5% to 12.25% as the temperature of the cells increases from 32.5 °C to 66.5 °C between 10:00 a.m. and 1:00 p.m. Meanwhile, the thermal and overall efficiencies declined from 84% to 81.5% and 96% to 93%, respectively.

Genetic counseling graduate program faculty perspectives on sharing education materials among programs.

Rapid advancements in genetics care requires responsive genetic counseling (GC) training capable of integrating new discoveries and practice into their curricula. The utilization of shared or standardized educational resources may address this need. Recognizing the potential of shared resources, the Pharmacogenetics (PGx) Working Group of the NSGC Precision Medicine Special Interest Group (SIG) launched a standardized education module using a flipped-classroom format to provide all GC programs equal access to PGx expertise and alleviate the burden of curriculum development. Following the initial success of the program, we aimed to explore the utilization of shared and standardized education resources more broadly, and better understand the perspectives of GC program faculty regarding their use. Twenty-nine program faculty representing at least 14 programs responded to an online survey. The majority (n = 21) reported sharing educational materials with another GC program, and 90% of those reported the shared materials to be beneficial as they promote collaboration, efficiency, address a gap in content, and provide access to experts. Similar benefits were described when using a standardized curriculum, which was defined as standardized lectures and activities created about a particular topic and made available to all genetic counseling programs; 16 participants indicated they would be very likely or likely to use a standardized curriculum. A secondary aim of the survey was to assess the existing PGx module that utilizes a flipped-classroom format. Overall, the PGx module was well received, indicating that a standardized shared module is well-suited for instruction on emerging and specialty topics. All participants believed the flipped-classroom format to be very or somewhat beneficial. In summary, results indicate that shared educational materials, including standardized education modules, are a potential solution to challenges related to efficiency and access to content experts in GC education, and program leadership is receptive to using them.

Reconfigurable hybrid micro-grid with standardized power module for high performance energy conversion

This paper proposes a reconfigurable power module system for hybrid micro-grid to reduce the designing cost with standardized software and hardware components. The developed system is composed of three layers including application function layer, interconnection layer and physical layer with the capability to be interfaced with different types of energy resources for the hybrid micro-grid. By implementing the multi-layer power module system, the energy conversion designing procedures for different types of resources can be generalized and automated with less cost on the specified application scenarios. The control functions for different energy resources can be extracted from the application function layer. The desired number of standardized power modules can be integrated from the physical layer to form different power converter topologies. The coordination of the power converter, micro-controller, sampling, high level control is managed by the interconnection layer to construct the complete energy conversion system. The major advantageous results cover three aspects. Firstly, the proposed reconfigurable system generalizes the energy conversion of the hybrid micro-grid with different AC and DC resources. Secondly, the designing procedures of the hybrid micro-grid energy conversion system are simplified with less cost for various interfaced applications. Thirdly, the energy conversion performance and reliability of the micro-grid is improved with standardized power modules and self-restoration capability. The experimental test verified the proposed system.

Large Separable Kernel Attention: Rethinking the Large Kernel Attention design in CNN

Visual Attention Networks (VAN) with Large Kernel Attention (LKA) modules have been shown to provide remarkable performance, that surpasses Vision Transformers (ViTs), on a range of vision-based tasks. However, the depth-wise convolutional layer in these LKA modules incurs a quadratic increase in the computational and memory footprints with increasing convolutional kernel size. To mitigate these problems and to enable the use of extremely large convolutional kernels in the attention modules of VAN, we propose a family of Large Separable Kernel Attention modules, termed LSKA. LSKA decomposes the 2D convolutional kernel of the depth-wise convolutional layer into cascaded horizontal and vertical 1-D kernels. In contrast to the standard LKA design, the proposed decomposition enables the direct use of the depth-wise convolutional layer with large kernels in the attention module, without requiring any extra blocks. We demonstrate that the proposed LSKA module in VAN can achieve comparable performance with the standard LKA module and incur lower computational complexity and memory footprints. We also find that the proposed LSKA design biases the VAN more toward the shape of the object than the texture with increasing kernel size. Additionally, we benchmark the robustness of the LKA and LSKA in VAN, ViTs, and the recent ConvNeXt on the five corrupted versions of the ImageNet dataset that are largely unexplored in the previous works. Our extensive experimental results show that the proposed LSKA module in VAN provides a significant reduction in computational complexity and memory footprints with increasing kernel size while outperforming ViTs, ConvNeXt, and providing similar performance compared to the LKA module in VAN on object recognition, object detection, semantic segmentation, and robustness tests.

Modelling the Influence of the Tube Support Plate on the Eddy Current Testing of the Steam Generator: Numerical Tools and Experimental Validation

Eddy current testing (ECT) of Steam Generator (SG) tubes is part of the maintenance program of Nuclear Power Plants. Tube Support Plates (TSP) are usually only considered as extraneous signals for tube inspection. However, for long-term operation of SGs, there is a safety concern related to the build-up of deposits in the TSPs flow holes. The clogging-up of the TSPs flow holes affect the safe thermal-hydraulic operation of SGs. The deposits come from the feedwater train and are mostly iron oxides (magnetite) with a weak electrical conductivity and magnetic permeability. The ability of ECT probes to detect and characterize TSPs deposits is therefore of great interest. The most common and industrial ECT technique, the bobbin coil, averages the surrounding electromagnetic field over 360°, whereas the geometry of tri-foiled and quadri-foiled TSPs, and thus of clogging, is rather complex and non-axisymmetric, hence motivating the evaluation of the performance of conventional ECT rotating probes used for SGs tubes inspection. Although simulation is a powerful tool to support such a study, it requires dedicated models to be made available to NDT experts, and CEA develops ECT physical models in CIVA for this purpose. In addition to standard fast CIVA modules based on 3D semi-analytical or 2D numerical calculations restricted to canonical or axisymmetric parts, respectively, CEA develops a module dedicated to the simulation of SG tube inspection based on a 3D numerical simulation. This module allows tube deformation such as ovalization, bending or tube expansion. It also allows the addition of external objects such as anti-vibration bars, different geometries of tube support plates and now their clogging by deposits. This model is used to study various influent parameters and to perform benchmarks in the framework of a scientific collaboration between the CEA and the IRSN, related for example to the inspection of the U-bend tubes or of a friction wear under the anti-vibration bars. Here, the specificity of the TSPs and their clogging justifies further investigations between CEA and IRSN to qualify the simulation model before evaluating the influence of material and geometry properties of the deposit as well as the performance of the inspection techniques. We present the main characteristics of the simulation module in CIVA.

Designing and validation of Yoga module for workers with prolonged standing

BackgroundProlonged standing is a part of several professions, which can have physical and psychosocial implications. Yoga as a mind-body therapy may be useful to prevent and manage such health issues. However, there is a lack of a standardized yoga module addressing the health issues of workers with prolonged standing. ObjectivesThus, the present study was undertaken to design and validate a specific yoga module for the target population. MethodsA yoga module was prepared by reviewing yoga texts for the specific needs of the target population. This was validated for content validity for the experts on a Likert scale.71 yoga experts validated the module. The content validity ratio (CVR) above 0.70 was considered to be valid. ResultsThe validated yoga module consists of joint loosening and strengthening exercises, asana, pranayama and relaxation techniques. The average CVR for the module was found to be 0.80. ConclusionThe designed yoga module is found to be valid by the experts. The module needs to be assessed for feasibility and efficacy in the target population.

Future changes in hydrological drought across the Yangtze River Basin: identification, spatial–temporal characteristics, and concurrent probability

Hydrological droughts have caused greater damage due to climate change and rapid socio-economic development. Exploring future hydrological drought variations is imperative for drought defense and infrastructure construction. This study aims to investigate future changes in hydrological droughts across the Yangtze River Basin during 2025 ∼ 2100. The Distributed Time-Variant Gain Model coupled with the Standard Operation Policy module (DTVGM-SOP) was employed to project future runoff driven by the bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) data. Subsequently, future spatial–temporal changes in the characteristics of hydrological droughts were analyzed based on the Standardized Runoff Index (SRI). Lastly, future changes in the probability of concurrent hydrological droughts were evaluated using the bivariate copula functions. Results show that: (1) The DTVGM-SOP model can satisfactorily simulate monthly streamflow with a high Nash-Sutcliff Efficiency (NSE) of 0.75 ∼ 0.92. Future annual maximum discharge and annual average discharge in the mainstream and the northern tributaries are expected to increase by 3.34%∼58.19% and 3.11%∼32.66% respectively, while annual maximum discharge in the southern tributaries decreases by 0.54%∼20.09%. (2) The future annual and seasonal hydrological drought frequency is expected to decrease in most regions, while the frequency in spring increases in the Qinghai Tibet Plateau. The duration and severity of future hydrological droughts are expected to decrease by 9.52%∼78.69% and 5.13%∼81.36% in the whole basin except the source area and the Yalong River Basin. (3) Future concurrent hydrological droughts will be mitigated with decreasing frequency. The probability of concurrent hydrological droughts is expected to decrease by 46.15%∼96.47%, while future changes in the conditional probability of the mainstream are diverse in different concurrent scenarios with a range of −93.41%∼40.09%. The findings are helpful to improve the understanding of future hydrological drought variations in the Yangtze River Basin and provide essential information for damage reduction.

Feasibility and techno-economic analysis of PV-battery priority grid tie system with diesel resilience: A case study

Ethiopia is close to the equator and has enormous potential as a solar energy resource that has yet to be realized. The country has some small-scale diesel-based power generation, and all universities and government agencies have installed standby generator sets for supplying power when the grid is interrupted. Ethiopia is a developing nation with a significant reliance on oil imports and insufficient rural electrification, which exacerbates the problem of poverty. The increased cost of oil, frequent hard currency expenditures for oil, and exaggerated maintenance costs for the generators are the main reasons to undertake this feasibility study. As the assessments show, the annual average interruption was more than 800 h in the past five years in the Debre Markos University distribution feeder. A preliminary study on the techno-economic feasibility of the existing diesel generator set and PV system with the same rated power of 500 kW is conducted in this work. As the break-even point of the economic comparison shows, the existing diesel generator is not economically feasible as compared to the proposed PV-battery priority grid tie system due to high running and service costs. The study also shows the technical feasibility of solar energy, as the P–V and I–V characteristic curves illustrated on a single standard solar module indicate. As the economic comparison break-even point shows, the diesel-based generator set is not economical after 5 years due to the high operational and maintenance costs. As the results show, the proposed PV/Battery Priority system with a diesel generator for resilience is more environmentally friendly, reducing the carbon footprint by 94%.

Leisure-time physical activity mitigated the cognitive effect of PM2.5 and PM2.5 components exposure: Evidence from a nationwide longitudinal study

BackgroundExposure to fine particulate matter (PM2.5) impairs cognition, while physical activity (PA) improves cognitive function. However, whether taking PA with PM2.5 exposure is still beneficial to cognition remains unknown. MethodsWe utilized national representative longitudinal data from the China Family Panel Study (CFPS), comprising a total sample of 108,099 from 2010 to 2018 in three waves. Cognitive performance and leisure-time PA were measured using the standard cognitive module and Godin-Shephard Leisure-Time Physical Activity Questionnaire. Gridded overall PM2.5 and major chemical components of PM2.5 were estimated using a two-stage machine learning model and matched to each participant based on their residential location. Mixed-effect models and difference-in-difference models were employed to investigate the individual and joint effects of total PM2.5, PM2.5 components, and leisure-time PA on cognition. ResultsEvery 1 μg/m3 increase in PM2.5 was associated with a −0.035 (95% confidence interval [CI] = −0.052, −0.018) point change in cognitive score. All PM2.5 components exhibited negative associations with cognitive change, with black carbon (BC) contributing the most significant cognitive decline (β = −1.025, 95% CI = −1.367, −0.683). Every one-time (or one-hour) increase in leisure-time PA frequency (or PA time) per week was associated with an increase in cognitive score by 0.576 (0.270) points (PA frequency: 95% CI = 0.544, 0.608, PA time: 95% CI = 0.248, 0.293). PA frequency (β = −0.005, 95% CI = −0.006, −0.003) and PA time (β = −0.002, 95% CI = −0.003, −0.001) exhibited interactive effects with PM2.5. Increased PA frequency and time were more beneficial to cognitive function in the low PM2.5 exposure group compared to those exposed to high PM2.5 levels. Moreover, relative to lower PM2.5 exposure, the cognitive benefits of physically active individuals with higher PM2.5 exposure were attenuated but still improved cognition when compared to those with no PA. ConclusionEngaging in leisure-time PA provides cognitive benefits even under PM2.5 exposure, although PM2.5 exposure attenuates these benefits. Among all PM2.5 components, BC demonstrated the most significant cognitive hazard and interaction with leisure-time PA. Promoting PA as a preventive measure may offer a cost-effective and convenient strategy to mitigate the negative impact of PM2.5 exposure on cognition. There is no excuse to avoid PA under PM2.5 exposure, as its cognitive benefits persist even in polluted environments.

Effect of Ho:YAG laser on kidney tissue with Virtual Basket™ and Bubble Blast™ pulse modulation: an experimental ex vivo study.

There is a lack of studies in the literature on effects of Virtual Basket™ (VB) and Bubble Blast™ (BB) laser pulse modulations of the Ho:YAG laser on tissue. We aimed to compare the effects of standard modulation (SM), VB, and BB pulse modulations of Ho:YAG laser on kidney tissue. An ex vivo experiment was conducted using veal kidneys. The Quanta System Cyber Ho 100W laser generator with a broad setting spectrum at 15-80W, 10-40Hz, 1.5-2J, and medium pulse duration were tested. Incision depth (ID), vaporization area (VA), coagulation area (CA), and total laser area (TLA = VA + CA) were evaluated. Histopathological measurement outcomes were grouped as a low-power group (15, 20, and 30 W) and a high-power group (40, 60, and 80W) according to the power outputs used. A total of 108 experiments were performed. In saline and high-power output (40, 60, 80 W), mean VA, TLA, and ID, histopathological measurements were higher in BB pulse modulation than VB and SM pulse modulations (p: 0.03, p: 0.001, and p: 0.003, respectively). In contrast, mean CA and LE measurements were higher in SM than in VB and BB pulse modulations (p < 0.001 and p < 0.001, respectively). There was no statistically significant difference in mean histopathological measurements of VA, CA, TLA, and ID, among SM, VB, and BB pulse modulations in the low-power output group in saline (p > 0.05). VB can allow controlled dissection, as it does not create a large VA during surgical procedures. BB should be used in a controlled manner in soft tissue surgery due to its strong effect on tissues.

Combinatorial relations among relations for level 2 standard Cn(1)-modules

For an affine Lie algebra ĝ, the coefficients of certain vertex operators that annihilate level k standard ĝ-modules are the defining relations for level k standard modules. In this paper, we study a combinatorial structure of the leading terms of these relations for level k = 2 standard ĝ-modules for affine Lie algebras of type Cn(1) and the main result is the construction of combinatorially parameterized relations among the coefficients of annihilating fields. It is believed that the constructed relations among relations will play a key role in the construction of Gröbner-like basis of the maximal ideal of the universal vertex operator algebra Vgk for k = 2.

Сравнительный анализ стандартов медицинской помощи взрослым по профилю «Онкология», утвержденных до и после 2019 года на предмет возможности планирования программы государственных гарантий.

In the healthcare system in Russian Federation, in recent decades, standards of medical care have been formed, which are tabular forms indicating medical services, medicines, medical devices implanted in the human body, blood components and clinical nutrition (components), indicating average frequency indicators. P u r p o s e – a comparative analysis of the standards of medical care for adults in the oncology profile, approved by orders of the Ministry of Health of Russia in the period from 2012 to 2018, and the standards developed on the basis of clinical guidelines and approved in the period from 2019 to 2022, with a view to the possibility of planning a state guarantee program based on them. M a t e r i a l s a n d m e t h o d s . The comparison was performed by comparing the standards of medical care in the context of types of medical care, the conditions for providing medical care, localizations and nosological forms according to ICD‑10 blocks, types of medical interventions and assessing consistency with planning units of the state guarantees program. R e s u l t s . The standards of medical care in the oncology profile, approved in the period from 2012 to 2018, were developed in the context of the types of medical interventions and were not coordinated either with the planning units of the state guarantees program or with the methods of payment by diagnosis-related group. The introduction of a methodology for the formation of standards of medical care based on clinical guidelines using standardized modules of medical care made it possible to revise the principle of the formation of standards for the oncology profile and harmonize them with the planning units of the state guarantees program and methods of payment by diagnosis-related group. F i n d i n g s . Structuring the process of developing medical care standards based on clinical guidelines and developing a methodology for their formation makes it possible to realize the economic function of medical care standards.

Optimal Design of Multilayer Optical Color Filters for Building‐Integrated Photovoltaic (BIPV) Applications

Herein, the application of a comprehensive modeling framework that can help optimize the design of multilayered optical filters for coloring photovoltaic (PV) modules is presented based on crystalline silicon solar cells. To overcome technical issues related to the implementation of color filters (CFs) on PV modules, like glare and color instability, colorimetry metrics, such as the hue, chroma, luminance color space, and the quantitative concept of difference between two colors are extensively deployed. It is showcased in this work that designing colored modules with high hue and chroma stability is possible by using a front‐side texturing with edged geometry, like V‐shaped grooves and inverted pyramids, while obtaining colors with relatively high luminance values, indicating good brightness. Furthermore, it is argued that adapting the rear surface of the front glass with a random textured layout where the CF is applied can improve color and luminance stability without significant loss of chroma while eliminating glare. Finally, the models can be used to optimize the number of layers for a given CF, reducing unnecessary optical losses. Compared to a standard PV module, performance simulation of optimized, bright‐colored PV modules predicts relative energy yield losses ranging from 7% to 25%.

Robotic Modules for the Programmable Chemputation of Molecules and Materials.

Before leveraging big data methods like machine learning and artificial intelligence (AI) in chemistry, there is an imperative need for an affordable, universal digitization standard. This mirrors the foundational requisites of the digital revolution, which demanded standard architectures with precise specifications. Recently, we have developed automated platforms tailored for chemical AI-driven exploration, including the synthesis of molecules, materials, nanomaterials, and formulations. Our focus has been on designing and constructing affordable standard hardware and software modules that serve as a blueprint for chemistry digitization across varied fields. Our platforms can be categorized into four types based on their applications: (i) discovery systems for the exploration of chemical space and novel reactivity, (ii) systems for the synthesis and manufacture of fine chemicals, (iii) platforms for formulation discovery and exploration, and (iv) systems for materials discovery and synthesis. We also highlight the convergent evolution of these platforms through shared hardware, firmware, and software alongside the creation of a unique programming language for chemical and material systems. This programming approach is essential for reliable synthesis, designing experiments, discovery, optimization, and establishing new collaboration standards. Furthermore, it is crucial for verifying literature findings, enhancing experimental outcome reliability, and fostering collaboration and sharing of unsuccessful experiments across different research labs.