Original Design Research Articles

Cavitation intensity prediction and optimization for a Venturi cavitation reactor using deep learning

The Venturi reactor, widely used in process intensification through hydrodynamic cavitation technology, has proven highly effective in various chemical and environmental applications. The cavitation intensity of a Venturi is primarily influenced by shape parameters such as the convergent angle (β1), throat diameter (dth), throat length (lth), and divergent angle (β2). However, the impact of these parameters on cavitation intensity has not been sufficiently clarified. In this study, the structural optimization of a Venturi reactor was accomplished by integrating deep neural networks with particle swarm optimization. The Cavitation Intensity Prediction Network model, which combines artificial neural networks and numerical simulation, was used to establish the nonlinear relationship between shape parameters and cavitation intensity. Partial dependence plots and individual conditional expectation plots were utilized to clarify the influence of each parameter. The findings reveal that the cavitation intensity of the optimal Venturi is 2.76 times greater than that of the original design. Reducing β1 resulted in a swift conversion of static pressure into dynamic pressure, but it also caused an uneven distribution of fluid velocity. To reduce this unevenness and allow the dynamic pressure in the throat to reach its peak, which is advantageous for cavitation generation, lth should be extended. dth directly influenced the efficiency of converting static pressure into dynamic pressure and was a key factor in determining cavitation intensity. β2 indirectly impacted cavitation intensity by modulating the space available for cavitation development. The insights gained from this study may provide valuable guidance for designing Venturis in process intensification applications.

Nail Designs Research with Camouflage Patterns

This study aims to analyze the design characteristics of camouflage patterns and apply them to nail art to propose original and stylish designs. In line with the trend of modern women expressing their individuality through nail art, this research explores the concept of camouflage, its historical development, and other characteristics based on previous studies, and proposes nail art designs incorporating camouflage patterns. By utilizing various colors and materials, this study presents camouflage nail designs that add a unique touch to everyday life. The research results include five distinct nail art designs: First, a classic camouflage design using colors and patterns similar to natural environments; second, a geometric camouflage design utilizing geometric patterns; third, a unique camouflage design using mix-and-match patterns; fourth, an abstract camouflage design based on geometric patterns; and fifth, a minimalist camouflage design using black and white. By integrating camouflage patterns that have influenced numerous artists and designers, this study presents unique and character-filled nail art designs through a combination of various colors and patterns. The study explores the contemporary significance of camouflage patterns and their diversity, proposing new nail art designs that extend the scope of materials and techniques. It aims to expand the artistic domain of nail art, contributing to both academic development and the advancement of the nail industry. This study holds significance as a resource for expanding the practical and popular design domain of nail art, aiding in the development of new nail art designs.

Utility of dairy microbiome as a tool for authentication and traceability.

Milk microbiome contributes substantially to the formation of specific organoleptic and physicochemical characteristics of dairy products. The assessment of the composition and abundance of milk microbiota is a challenging task strongly influenced by many environmental factors. Specific dairy products may be designated by the Protected Designation of Origin (PDO) and Protected Geographical Indication (PGI) labeling, which however, occasionally fail to differentiate them according to specific quality characteristics, which are defined by different microbiota-driven reactions. Combining the above limitations, the scope of the present study, was to summarize the existing information toward three main issues. First, to assess the influence level of the diet type and grazing to rumen-GI tract, mammary gland, and udder microbiome formation in ruminants. Second, to discuss the factors affecting milk microbiota, as well as the effect of the endo-mammary route on milk microbial taxa. Lastly, to evaluate "milk microbiome" as a tool for product differentiation, according to origin, which will contribute to a more robust PDO and PGI labeling. Although the limitations are still a matter of fact (especially considering the sample collection, process, evaluation, and avoidance of its contamination), significant progress has been made, regarding the identification of the factors affecting dairy products' microbiota and its core composition. In conclusion, although so far not totally efficient in dairy products molecular identification, with the progress in soil, water, plant, and animal host's microbiota assembly's characterization, microbiomics could provide a powerful tool for authentication and traceability of dairy products.

Assessing statistical neural networks potentiality to distinguish PDO Kalamata and Molaoi olive oil varieties

Several regional areas in Greece produce high quality olive oil by cultivating certain varieties. Olive oil varieties of Kalamata and Molaoi are of special interest, since they produce extra virgin olive oil. Concretely, Kalamata is a city located in southwestern Greece. Intuitively, Molaoi is a town located in southeastern Greece. Subsequently, both geographic locations are known for their famous olive oil quality. Continually, Protected Designation of Origin (PDO) Kalamata olive oil, established by Council regulation (EC) No 510/2006, is considered an exceptional extra virgin olive oil variety. Specifically, there is a need to distinguish PDO Kalamata olive oil from other olive oil varieties is Greece such as the Molaoi olive oil, since PDO Kalamata olive oil is the main variety exported in the global olive oil market. Distinguishing PDO Kalamata from Molaoi olive oil is possible by incorporating statistical neural networks. Concretely, applying neural network experimentation enables differentiation between variations of certain chemical characteristics observed in certain geographic locations of Greece. In this paper, we use statistical neural networks to distinguish the geographical origin of PDO Kalamata olive oil compared with Molaoi olive oil based on synchronous excitation−emission fluorescence spectroscopy of provided olive oils samples evaluated in the chemical laboratory. Evaluation based on certain experimentation phase and subsequent data visualization of the adopted statistical neural networks are promising for distinguishing the samples of PDO Kalamata olive oil with high values of prediction accuracy. Such ability enables olive oil industry to assess extra virgin olive oil profitable potentiality in global market.

4.D. Scientific session: From policy to implementation: Learnings around health system reforms and Universal Health Coverage

Abstract In this session, the authors and audience have the opportunity to engage in discussions around health policy integrity and reform implementation. Introducing and implementing health system reform has been a perennial issue for countries around the world over the past number of decades. Recently, the introduction and implementation of Universal Health Coverage (UHC) has been of particular focus, with 193 countries committed to introducing UHC by 2030. At the same time, European countries that previously established national health systems are introducing new reforms in the hope of making their health systems more efficient and equitable. However, there are a number of challenges along the path of policy development and implementation with which all countries must grapple, and how individual countries go about reforming their health systems depends on their social, political, cultural and economic contexts. Learnings from around the world have highlighted that reforms can be challenged or stalled in both the design and implementation phases. This workshop, which conceptualises implementation as the “acid test” of a policy, thus explores, through three case studies, the factors that facilitate or challenge the implementation of reforms. At the same time, we discuss policy integrity, exploring reasons for why policies pivot away from original design and intent. Furthermore, we discuss the implications of health reform on equity, cognisant that the primary objective of this collective reform work is to reduce the financial burden of healthcare on households and improve access. The first presentation will provide the framework for audience discussions, outlining international lessons in relation to UHC reforms and equity. The second presentation will provide a snapshot of the Finnish experience of introducing a “big bang” structural reform. The third presentation highlights lessons from the Portuguese experience of primary healthcare reforms, the opportunity these offer for creating patient-centred care and the integral role that politics and governance play in the reform process. Finally, the Irish case study highlights the experiences of a High Income County attempting to introduce UHC much later than its European counterparts, and negotiations between the public and private sectors. Through this, we hope to hold the tensions and stimulate debate about policy robustness and resilience, and reform implementation. Each presenter will be given a strict deadline of 10 minutes each by the chair and then the audience will be invited to debate the problems identified and strategies proposed to discuss: (i) what are the facilitators and barriers to reform implementation, (ii) what are the factors that encourage policy integrity and change and (iii) whether greater cooperation across Europe regarding health reforms can be more effective in supporting robust health systems. Key messages • For reforms to be facilitated, there must be cohesion and commitment across the political, social, economic and cultural systems, and no fragmentation across health system functions. • As policy implementation is attempted, there is a tension between remaining true to key values and adapting to new circumstances.

DeLoSo: Detecting Logic Synthesis Optimization Faults Based on Configuration Diversity

Logic synthesis tools are the core components of digital circuit design, which convert programs written in hardware description languages into gate-level netlists, and optimize the netlists. However, the netlist optimization is complex, with numerous optimization parameters to be configured. Any minor optimization faults in logic synthesis tools may cause circuit diagrams to significantly deviate from the original design, posing risks in target systems. We propose DeLoSo, the De tector of Lo gic S ynthesis o ptimization faults, the first method specifically designed to identify potential faults in the optimization processes of logic synthesis tools. DeLoSo relies on netlist differences and parameter variations to guide the generation of diverse Logic Synthesis Optimization Configuration (LSOC) combinations to thoroughly test the optimization process. DeLoSo consists of three components: LSOC generator, which generates diverse LSOC combinations through configuration recombination and mutation; LSOC diversity evaluator, which assesses the diversity of optimization configurations; and LSOC validator, which validates the generated LSOC combinations to discover optimization faults. DeLoSo identified 19 faults in two established logic synthesis tools (i.e., Vivado and Yosys); 15 of them have been fixed by vendors. Particularly, the community maintainers of Yosys have considered incorporating DeLoSo into Yosys’ existing test suite.

A Case Study on the Possibility of Extending the Service Life of the Demining Machine Belt.

The operational practice of the design of the Bozena 5 demining machine has shown that its belts are the critical component that fundamentally affects the functionality of the entire machine. This article is a practical continuation and extension of the previous research results from the point of view of materials (research of the uniaxial fatigue life in bending and torsion), calculation (creation of the necessary mathematical, analytical and numerical models for the research) and construction (i.e., patented design of the belt tensioning of this machine). All these actions are aimed at a single objective-to achieve a condition that guarantees a sufficient service life without malfunctions, since repairing these machines in the field is often impossible. Therefore, this study examined the fatigue life of welded joints (uniaxial bending and torsion) of S960 QL and S500MC steels welded by MAG technology. Subsequently, the data were compared with previous results (electron and laser welds) and the influence of each type of weld on the fatigue life relative to the base material was discussed. It was found that conventional MAG technology had a more significant negative impact on the fatigue life of the base material than non-conventional technologies. This trend was particularly true for the bending stress. At the same time, the bending stress was identified by the FEM analysis as the dominant load on the belt. The maximum stress in the belt link under the considered boundary conditions was approximately 240 MPa (in bending). This stress corresponded to the continuous fatigue life (more than 107 cycles) for both base materials tested (S960QL, S500MC). In the whole studied spectrum of controlled deformation amplitudes (Manson-Coffin), the life of MAG welds was lower in comparison with the base material and with welds made by unconventional technologies. All the activities carried out so far (research on microstructure, hardness, strength, residual stresses, tribological properties and fatigue life) have shown that the original belt design (S500MC) using MAG technology has significant deficiencies in the state of optimal life. It is expected that the proposed material change (use of S960QL instead of S500MC) and work with advanced technologies will bring this state significantly closer.

Steered molecular dynamics simulation as a post-process to optimize the iBRAB-designed Fab model.

Therapeutic monoclonal antibodies are an effective method of treating acute infectious diseases. However, knowing which of the produced antibodies in the vast number of human antibodies can cure the disease requires a long time and advanced technology. The previously introduced iBRAB method relies on studied antibodies to design a broad-spectrum antibody capable of neutralizing antigens of many different Influenza A viral strains. To evaluate the antigen-binding fragment as an applicable drug, the therapeutic antibody profiles providing guidelines collected from clinically staged therapeutic antibodies were used to access different measurements. Although the evaluated values were within an accepted range, the modification in the amino acid sequence is required for better properties. Thus, using the steered molecular dynamics(SMD) simulation to determine the binding capacity of amino acids in the functional region, the profile of interacted amino acids of Fab with the antigen was established for modified reference. As a result, the model was modified with amino acids elimination at positions 96-97 in the heavy chain and 26-27, 91, 96-97, and 102-103 in the light chain, which has better Therapeutic Antibody Profiler evaluations than the original designation. Thus again, SMD simulation is a promising computational approach for post-modification in rational drug design.

“There is plenty of energy at the bottom”: A spectral conversion approach for upconversion-powered water-splitting PEC cell

An avant-garde step towards the use of the long infrared tail of the incident solar radiation with untapped and crucial applications in photocatalysis and energy harvesting schemes is presented: “there is plenty of energy at the bottom”. In detail, a pure photonic approach to enhance titanium dioxide (TiO2) photocatalytic activity is proposed, by using rare-earth doped luminescent glassy materials, capable of performing NIR-to-UV-VIS spectral conversion (up-conversion). Therefore we report infrared-driven boosting of green hydrogen production in a photo-electrochemical water-splitting cell using TiO2 electrodes, revisiting the original design of Fujishima and Honda fifty years later. This proof-of-concept comprises infrared-induced hydrogen and oxygen evolution via water-splitting and determines univocally the role of a solely photonic effect to split water. Thus, the conversion of the incident NIR radiation, before its interaction with the photocatalyst, emerges as a significant contribution to the state-of-the-art for an effective harvest of the near-infrared portions of sunlight.

Metabolic Profiling and Stable Isotope Analysis of Wines: Pilot Study for Cross-Border Authentication.

Globalization and free market dynamics have significantly impacted state economies, particularly in the wine industry. These forces have introduced greater diversity in wine products but have also heightened the risk of food fraud, especially in high-value commodities like wine. Due to its market value and the premium placed on quality, wine is frequently subject to adulteration. This issue is often addressed through regulatory trademarks on wine labels, such as Protected Designation of Origin (PDO) and Protected Geographic Indication (PGI). In this context, the metabolic profiles (organic acids, carbohydrates, and phenols) and stable isotope signatures (δ13C, δ18O, D/HI, and D/HII) of red and white wines from four agroclimatically similar regions were examined. The study explored how factors such as grape variety, harvest year, and geographical origin affect wine composition, with a particular focus on distinguishing samples from cross-border areas. Multivariate statistical analysis was used to assess the variability in wine composition and to identify distinct groups of samples. Preliminary results revealed that organic acids and volatile compounds were found in lower concentrations than carbohydrates but were significantly higher than phenols, with levels ranging between 1617 mg/L and 6258 mg/L. Carbohydrate content in the wines varied from 8285 mg/L to 14662 mg/L. Principal Component Analysis (PCA) indicated certain separation trends based on the variance in carbohydrates (e.g., fructose, glucose, galactose) and isotopic composition. However, Discriminant Analysis (DA) provided clear distinctions based on harvest year, variety, and geographical origin.

The Design and Performance Analysis of a 15 g/mol Helium–Xenon Mixture Centrifugal Compressor

One of the primary parts of a closed Brayton cycle that uses a helium–xenon mixture as the working medium is a centrifugal compressor. Nowadays, there has been minimal research on the theoretical underpinnings and design procedures of a helium–xenon mixture centrifugal compressors, and the internal flow mechanisms remain poorly understood. In this study, we present a redesign of the 15 g/mol helium–xenon centrifugal compressor originally developed by Bruno M, utilizing a helium–xenon mixture as the working fluid to enhance compressor performance and facilitate an in-depth analysis of the internal flow dynamics. The findings indicate a significant expansion of the stable operating range of the redesigned compressor under identical outlet conditions, with a 33.27% increase in flow margin and substantial improvements in the pressure ratio. Furthermore, under consistent inlet conditions, at an operational flow rate of 0.8657 kg/s, the redesigned compressor exhibits a pressure ratio that is 2.11% greater than that of the original design, along with a variable efficiency increase of 1.1%.

The Enderby Bark Shield: A New Model for the Ancient World

A 2300 year old bark shield found in Enderby, Leicestershire, in 2015 is the only known example of its type. Made from the bark of a willow tree, it has a woven basket boss, a roundwood handle, and a rim of split roundwood edging and lime bast bindings. Pre-Roman shields made from organic materials rarely survive in Britain and Ireland and those without metal components are exceptionally rare. Contemporaneous wooden shields are known from anaerobic environments in Scandinavia but, unlike Enderby, none of these has a body of tree bark. The complexity of the design of the Enderby shield, the skill with which it was made, and the similarities between this and metal examples suggests it was a tried and tested design, rather than a one-off. With no other example against which to compare it, experiments in reproducing the shield have been used as a tool for interpretation and have proved vital to understanding the original design. As a result of this research, it is proposed that this single artefact represents a more commonly available form of shield in the 1st millennium bc than does any metal enhanced version.

Ozone-Catalytic Treatment of Automotive Exhaust

In the paper, an original design of an ozone-catalytic device, in which the process of ozone formation occurs directly inside the catalyst monolith of the honeycomb structure, is proposed for solving the problem of exhaust gases purification at the "cold start" of an automobile engine. For the considered device, various regimes of operation were examined, and the equations allowing us to calculate the concentrations of ozone depending on time were obtained. The developed mathematical model shows a significant decrease in ozone concentration after the "cold start" is over and the temperature of the exhaust gases increases, because of changes in the balance of various chemical reactions. Thus, the ozone concentration is maximum during a cold start, precisely when the lower temperatures do not allow other reactions than those of oxidation of toxic gases with ozone, and decreases by the time the catalytic unit warms up, when effective neutralization of toxic impurities becomes possible without the participation of ozone. The results of the mathematical modeling were confirmed by testing this device for purifying exhaust gases of a YaMZ-238M2 engine. The test results show that the use of ozone-catalytic reactions significantly increases the efficiency of neutralizing toxic impurities under cold start conditions, compared to the case when only catalytic reactions with oxygen without the participation of ozone are used.

Sustainability Assessment of the Performance of Parmigiano Reggiano PDO Firms: A Comparative Analysis of Firms’ Legal Form and Altitude Range

Geographical indications (GIs), protected by the European Union with the collective marks of PDO (protected designation of origin), PGI (protected geographical indication), and TSG (traditional specialty guaranteed), play an important role in the social and economic system. They not only guarantee food needs, but promote correct consumer information, protect local food, and play a role in the environmental and social sustainability of rural areas. In Italy, Parmigiano Reggiano (PR-RE) PDO cheese is ranked second in foods with the GI protection mark by turnover. This research aims to assess the financial sustainability of the firms registered in the PR-RE PDO consortium using financial statement (FINSTAT) analysis. Financial ratios (FR) and the EM-Score were applied to assess firms’ performance, financial risk, and credit score. The analysis distinguished firms by legal form, cooperative and non-cooperative, and altitude range—plain hill and mountain. The main findings of the research were as follows: (1) a better performance of lowland non-cooperative firms and lower financial risk, (2) a longer duration of the inventory cycle of cooperative firms, and (3) a greater financial risk in mountain cooperatives. The results provide indications for improving firms’ performance and for designing financial instruments for the sector. To our knowledge, this is the first research to carry out an analysis of all the available FINSTATs of firms in the PR-RE PDO sector.

Key Drivers of Consumption, Conceptual, Sensory, and Emotional Profiling of Cheeses Based on Origin and Consumer Familiarity: A Case Study of Local and Imported Cheeses in Greece

The origin of a product, consumer familiarity, and purchasing identity are factors that affect the perception of cheese consumption. The present study aims at identifying consumers’ conceptualizations and attitudes towards local Greek cheeses of the North-Aegean Sea islands, such as Ladotyri, Graviera, Kasseri, Kaskavali, Melichloro, and Kalathaki, some of which have a Protected Designation of Origin (PDO) status, as opposed to cheeses of non-Greek origin, such as Cheddar, Regatto, and Gouda. Sensory and emotional attributes of local, local PDO, and imported cheeses, as well as drivers associated with consumers’ choice and acceptance above and beyond their sensory attributes, were studied using three methods: (a) flash profile to gain insight into the sensory positioning of products and description of samples; (b) qualitative analysis of focus groups to pinpoint consumer knowledge, preference, and consumption criteria; and (c) a new methodology for natural language processing and sentiment analysis of social media posts to determine consumer conceptualizations. Social media posts have proven to be a valuable source of linguistic and cultural data for cheeses. Local cheeses, including PDO products, were found to be linked to village life and family gatherings, home, tradition, and childhood memories, with saltiness and hardness being their main sensory attributes. Imported cheeses were linked to fast food, pizza, and snacking, with elasticity and gumminess as prominent sensory qualities. The main criteria for purchase were intended usage and versatility, taste and texture, price, and familiarity. The findings provide key sensory attributes, information about consumer purchasing criteria, and relevant vocabulary for the promotion of cheeses as agri-food and gastronomic identity key products.

Exploring the Interplay of Bud Load and Pruning Type in Shaping ‘Xinomavro’ (Vitis vinifera L.) Vine Growth, Yield, and Berry Composition

‘Xinomavro’ (V. vinifera L.) is an important native red wine grape variety in Northern Greece, particularly in PDO (protected designation of origin) regions. Despite its significance, there is limited research on the effects of pruning type and severity on ‘Xinomavro’ vine physiology, yield, and berry quality across diverse environmental conditions. This study aimed to address this knowledge gap and provide growers with crucial information for optimizing vineyard management practices. The study was conducted over two consecutive years (2016 and 2017) in a vineyard in Thessaloniki, Northern Greece. Four treatments (B12: 12 buds on 6 spurs, B24: 24 buds on 12 spurs, M12: 12 buds on 2 canes, and M24: 24 buds on 4 canes) combining two bud load levels (12 or 24 count nodes) and two pruning types (short spurs or long canes) were applied to ‘Xinomavro’ vines in a complete block randomized design. The vine water status, gas exchange, canopy characteristics, yield components, and berry composition were measured. Bud load and pruning type significantly influenced vine canopy development, microclimate, and yield components. Short pruning with high bud load (B24) resulted in denser canopies and higher yields, whereas cane pruning (M12 and M24) led to more open canopies and improved berry quality indicators. Treatment effects on berry composition were inconsistent across years but showed a tendency for higher anthocyanin and total phenol content in cane-pruned vines. This study demonstrates that pruning type (short or long fruiting units) may have a greater impact on vine growth, yield, and berry composition than bud load alone in ‘Xinomavro’ vines. Cane pruning appears to be a more effective strategy for achieving vine balance and potentially improving grape quality under given experimental conditions.

Digital transformation and green innovation performance: unraveling the role of green knowledge sharing and top management environmental awareness

PurposeThis research focuses on analyzing the impact of digital transformation (DT) on the green innovation performance of Spanish wineries, as well as the mediating effect of green knowledge sharing (GKS) on this main relationship, as well as the moderating role of top management environmental awareness (TMEA) on the GKS-green innovation performance linkage. In addition, age, size and protected designation of origin (PDO) membership are used to increase the precision of the cause–effect relationships examined.Design/methodology/approachThe study proposes a conceptual model based on previous studies, which is tested using partial least squares structural equation modeling, with data collected from 196 Spanish wineries between September 2022 and January 2023.FindingsThe results of the research reveal the existence of a positive and significant relationship between the development of DT and green innovation performance of Spanish wineries, as well as the partial mediation of GKS in this link and a positive moderation of TMEA in the GKS-green innovation performance bond.Practical implicationsWinery executives should prioritize aligning DT with TMEA to drive green innovation performance. Additionally, it is recommended that they actively promote GKS within their wineries to enhance sustainability performance and strengthen their competitive positioning in an eco-conscious market.Originality/valueThe originality of the study derives from its pioneering character, as the research enters unexplored terrain by investigating the role of the GKS as a mediator in the relationship between DT and green innovation performance, as no previous research has ventured in this direction.

Two-stage group-sequential designs with delayed responses – what is the point of applying corresponding methods?

BackgroundIn group-sequential designs, it is typically assumed that there is no time gap between patient enrollment and outcome measurement in clinical trials. However, in practice, there is usually a lag between the two time points. This can affect the statistical analysis of the data, especially in trials with interim analyses. One approach to address delayed responses has been introduced by Hampson and Jennison (J R Stat Soc Ser B Stat Methodol 75:3-54, 2013), who proposed the use of error-spending stopping boundaries for patient enrollment, followed by critical values to reject the null hypothesis if the stopping boundaries are crossed beforehand. Regarding the choice of a trial design, it is important to consider the efficiency of trial designs, e.g. in terms of the probability of trial success (power) and required resources (sample size and time).MethodsThis article aims to shed more light on the performance comparison of group sequential clinical trial designs that account for delayed responses and designs that do not. Suitable performance measures are described and designs are evaluated using the R package rpact. By doing so, we provide insight into global performance measures, discuss the applicability of conditional performance characteristics, and finally whether performance gain justifies the use of complex trial designs that incorporate delayed responses.ResultsWe investigated how the delayed response group sequential test (DR-GSD) design proposed by Hampson and Jennison (J R Stat Soc Ser B Stat Methodol 75:3-54, 2013) can be extended to include nonbinding lower recruitment stopping boundaries, illustrating that their original design framework can accommodate both binding and nonbinding rules when additional constraints are imposed. Our findings indicate that the performance enhancements from methods incorporating delayed responses heavily rely on the sample size at interim and the volume of data in the pipeline, with overall performance gains being limited.ConclusionThis research extends existing literature on group-sequential designs by offering insights into differences in performance. We conclude that, given the overall marginal differences, discussions regarding appropriate trial designs can pivot towards practical considerations of operational feasibility.

Did Biden-Harris’s reforms on the Paycheck Protection Program reduce racial disparities in lending?

AbstractIntroduced under the Trump-Pence Administration, the Paycheck Protection Program (PPP) provided short-term relief loans to small American businesses during the peak of the Coronavirus pandemic. The initial design of the PPP faced significant criticism from researchers due to racial disparities, among other issues, in its lending process. Minority groups received smaller PPP loan amounts during the original two tranches released in 2020. To increase equitable access for all, in February 2021 the Biden-Harris Administration enforced swift changes to the initial PPP aimed at favouring access to PPP loans for minority-owned small businesses that had been disadvantaged by the program’s original design under the Trump-Pence Administration. By exploiting a granular dataset of 1,759,270 PPP loans granted between Q2 2020 and Q2 2021 and by implementing a difference-in-differences approach (DID), this paper provides novel evidence on the effectiveness of the Biden reforms in reducing racial disparities within the Paycheck Protection Program. Indeed, we observe a significant increase in the volume of PPP loans granted to minority-owned businesses in the period following the Biden-Harris Administration’s reforms. Furthermore, among different minority groups, the reforms appear most effective for Native American minority groups (including American Indians, Alaska Natives, Native Hawaiians and/or Other Pacific Islanders), followed by Black Americans and Asian business owners. Our findings offer novel contributions to the existing literature on institutional discrimination, particularly regarding the initial PPP design. Our findings are especially valuable for policy makers as they underscore the importance of radical changes in addressing racial disparities. Our paper also offers evidence of how a public credit guarantee program should be designed to empower and promote economic inclusion for all, regardless of ethnicity, aligning with the UN’s Sustainable Development Goals.

Automatic Design of Robot Swarms under Concurrent Design Criteria: A Study Based on Iterated F‐Race

Automatic design is an appealing approach to realizing robot swarms. In this approach, a designer specifies a mission that the swarm must perform, and an optimization algorithm searches for the control software that enables the robots to perform the given mission. Traditionally, research in automatic design has focused on missions specified by a single design criterion, adopting methods based on single‐objective optimization algorithms. In this study, we investigate whether existing methods can be adapted to address missions specified by concurrent design criteria. We focus on the bi‐criteria case. We conduct experiments with a swarm of e‐puck robots that must perform sequences of two missions: each mission in the sequence is an independent design criterion that the automatic method must handle during the optimization process. We consider modular and neuroevolutionary methods that aggregate concurrent criteria via the weighted sum, hypervolume, or ‐norm. We compare their performance with that of Mandarina, an original automatic modular design method. Mandarina integrates Iterated F‐race as an optimization algorithm to conduct the design process without aggregating the design criteria. Results from realistic simulations and demonstrations with physical robots show that the best results are obtained with modular methods and when the design criteria are not aggregated.