All articles published by MDPI are made immediately available worldwide under an open access license. No special
permission is required to reuse all or part of the article published by MDPI, including figures and tables. For
articles published under an open access Creative Common CC BY license, any part of the article may be reused without
permission provided that the original article is clearly cited. For more information, please refer to
https://www.mdpi.com/openaccess.
Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature
Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for
future research directions and describes possible research applications.
Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive
positive feedback from the reviewers.
Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world.
Editors select a small number of articles recently published in the journal that they believe will be particularly
interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the
most exciting work published in the various research areas of the journal.
Although enzymes have been used for thousands of years, their application in industrial processes has gained importance since the 20th century due to technological and scientific advances in several areas, including biochemistry [...]
Full article
Flavobacterium psychrophilum is currently one of the most important pathogens in aquaculture worldwide, causing high losses to farmed salmonids particularly during early growth stages with significant economic impact. Despite previous attempts, no effective vaccine has been developed, and protection against introduction into farms
[...] Read more.
Flavobacterium psychrophilum is currently one of the most important pathogens in aquaculture worldwide, causing high losses to farmed salmonids particularly during early growth stages with significant economic impact. Despite previous attempts, no effective vaccine has been developed, and protection against introduction into farms is difficult due to the ubiquitous occurrence of the pathogen. A better understanding of the mechanism of disease development is essential for targeted therapeutic and preventive measures in farms. Unfortunately, the pathogenesis of diseases caused by F. psychrophilum has not been elucidated yet. Previously, several putative virulence factors have been identified. Some appear to be essential for disease development, while others are probably dispensable. The importance of some factors has not yet been explored. This review focuses on the supposed virulence factors of F. psychrophilum and the current knowledge about their importance in the pathogenesis of the disease.
Full article
This paper develops a model for lithium-ion batteries under dynamic stress testing (DST) and federal urban driving schedule (FUDS) conditions that incorporates associated hysteresis characteristics of 18650-format lithium iron-phosphate batteries. Additionally, it introduces the adaptive sliding mode observer algorithm (ASMO) to achieve robust
[...] Read more.
This paper develops a model for lithium-ion batteries under dynamic stress testing (DST) and federal urban driving schedule (FUDS) conditions that incorporates associated hysteresis characteristics of 18650-format lithium iron-phosphate batteries. Additionally, it introduces the adaptive sliding mode observer algorithm (ASMO) to achieve robust and swiftly accurate estimation of the state of charge (SOC) of lithium-iron-phosphate batteries during electric vehicle duty cycles. The established simplified hysteresis model in this paper significantly enhances the fitting accuracy during charging and discharging processes, compensating for voltage deviations induced by hysteresis characteristics. The SOC estimation, even in the face of model parameter changes under complex working conditions during electric vehicle duty cycles, maintains high robustness by capitalizing on the easy convergence and parameter insensitivity of ASMO. Lastly, experiments conducted under different temperatures and FUDS and DST conditions validate that the SOC estimation of lithium-iron-phosphate batteries, based on the adaptive sliding-mode observer and the simplified hysteresis model, exhibits enhanced robustness and faster convergence under complex working conditions and temperature variations during electric vehicle duty cycles.
Full article
by
Jose Carlos Santos Salgado, Paulo Ricardo Heinen, Josana Maria Messias, Lummy Maria Oliveira-Monteiro, Mariana Cereia, Carem Gledes Vargas Rechia, Alexandre Maller, Marina Kimiko Kadowaki, Richard John Ward and Maria de Lourdes Teixeira de Moraes Polizeli
The endo-1,4-β-xylanases (EC 3.2.1.8) are the largest group of hydrolytic enzymes that degrade xylan, the major component of hemicelluloses, by catalyzing the hydrolysis of glycosidic bonds β-1,4 in this polymer, releasing xylooligosaccharides of different sizes. Xylanases have considerable potential in producing bread, animal
[...] Read more.
The endo-1,4-β-xylanases (EC 3.2.1.8) are the largest group of hydrolytic enzymes that degrade xylan, the major component of hemicelluloses, by catalyzing the hydrolysis of glycosidic bonds β-1,4 in this polymer, releasing xylooligosaccharides of different sizes. Xylanases have considerable potential in producing bread, animal feed, food, beverages, xylitol, and bioethanol. The fungus Aspergillus tamarii Kita produced xylanases in Adams’ media supplemented with barley bagasse (brewer’s spent grains), a by-product from brewery industries. The culture extract exhibited two xylanase activities in the zymogram, identified by mass spectrometry as glycosyl hydrolase (GH) families 10 and 11 (GH 10 and GH 11). The central composite design (CCD) showed excellent predictive capacity for xylanase production (23.083 U mL−1). Additionally, other enzyme activities took place during the submerged fermentation. Moreover, enzymatic saccharification based on a mixture design (MD) of three different lignocellulosic residues was helpful in the production of fermentable sugars by the A. tamarii Kita crude extract.
Full article
Increasingly common and associated with healthcare settings, Candida infections are very important, since some species of this genus can develop antifungal resistance. We contribute data on the epidemiology, antifungal susceptibility, and genetic diversity of Candida non-albicans and non-auris affecting critically ill
[...] Read more.
Increasingly common and associated with healthcare settings, Candida infections are very important, since some species of this genus can develop antifungal resistance. We contribute data on the epidemiology, antifungal susceptibility, and genetic diversity of Candida non-albicans and non-auris affecting critically ill patients in a fourth-level hospital in Colombia. Ninety-seven isolates causing invasive infections, identified by conventional methods over 18 months, were studied. Data from patients affected by these yeasts, including sex, age, comorbidities, treatment, and outcome, were analysed. The antifungal susceptibility of the isolates was determined, and the ribosomal DNA was sequenced. Candida parapsilosis, Candida tropicalis, Candida glabrata, Candida dubliniensis, and Candida guilliermondii caused 48.5% of all cases of invasive candidiasis. The species were mainly recovered from blood (50%). Patients were mostly men (53.4%), between 18 days and 93 years old, hospitalized in the ICU (70.7%). Overall mortality was 46.6%, but patients in the ICU, using antibiotics, with diabetes mellitus, or with C. glabrata infections were more likely to die. Resistant isolates were identified in C. parapsilosis, C. tropicalis, and C. glabrata. This study provides epidemiological data for the surveillance of emerging Candida species, highlighting their clinical impact, as well as the emergence of antifungal resistance and clonal dispersal.
Full article
This study aims to empirically examine the relationship between cryptocurrency and various facets of the financial system. It seeks to provide a comprehensive understanding of how cryptocurrencies interact with, and influence, the stock market, the U.S. dollar’s strength, inflation rates, and traditional banking
[...] Read more.
This study aims to empirically examine the relationship between cryptocurrency and various facets of the financial system. It seeks to provide a comprehensive understanding of how cryptocurrencies interact with, and influence, the stock market, the U.S. dollar’s strength, inflation rates, and traditional banking operations. This is carried out using linear regression models, Granger causality tests, case studies, including the collapse of the Futures Exchange (FTX), and the successful integration of Binance. The study unveiled a strong positive correlation between cryptocurrency market capitalization and key financial indicators like the Dow Jones Industrial Average, Consumer Price Index, and traditional banking operations. This indicates the growing significance of cryptocurrencies within the global financial landscape. However, a mild association was found with the U.S. dollar, suggesting a limited influence of cryptocurrencies on traditional fiat currencies currently. Despite certain limitations such as reliance on secondary data, methodological choices, and geographic focus, this research provides valuable insights for policymakers, financial industry stakeholders, and academic researchers, underlining the necessity for continued study into the complex interplay between cryptocurrencies and financial stability.
Full article
A general methodology for loan amortization under arbitrary discount functions is discussed. It is shown that it is always possible to uniquely define a scheme for constructing the loan amortization schedule with an arbitrary assigned discount function. It is also shown that, even
[...] Read more.
A general methodology for loan amortization under arbitrary discount functions is discussed. It is shown that it is always possible to uniquely define a scheme for constructing the loan amortization schedule with an arbitrary assigned discount function. It is also shown that, even if the loan amortization is carried out from the sequence of principal payments and the sequence of accrued interest, the underlying discount function can be uniquely determined at the maturities corresponding to the installment payment dates. As a special case of the proposed approach, we derive the amortization method according to the law of simple interest.
Full article
Atherosclerotic disease, including coronary heart disease (CHD), is one of the chronic inflammatory conditions, and an imbalance between pro-inflammatory and anti-inflammatory cytokines plays a role in the process of atherosclerosis. Interleukin (IL)-27, one of the IL-12 family members, is recognized to play a
[...] Read more.
Atherosclerotic disease, including coronary heart disease (CHD), is one of the chronic inflammatory conditions, and an imbalance between pro-inflammatory and anti-inflammatory cytokines plays a role in the process of atherosclerosis. Interleukin (IL)-27, one of the IL-12 family members, is recognized to play a dual role in regulating immune responses with both pro-inflammatory and anti-inflammatory properties. IL-27 is secreted from monocytes, T cells, and endothelial cells, and its expression is upregulated in atherosclerotic plaques. We previously reported that no significant difference was observed in plasma IL-27 levels between patients with stable CHD and those without it. However, the prognostic value of IL-27 levels has not been fully elucidated. We studied the relation of plasma IL-27 levels to cardiovascular events in 402 patients undergoing elective coronary angiography for suspected CHD. We defined cardiovascular events as cardiovascular death, myocardial infarction, unstable angina, stroke, or coronary revascularization. Of the 402 study patients, CHD was present in 209 (52%) patients. Plasma IL-27 levels were not markedly different between patients with CHD and those without it (median 0.23 vs. 0.23 ng/mL). During a follow-up of 7.6 ± 4.5 years, cardiovascular events were observed in 70 patients (17%). In comparison to the 332 patients with no event, the 70 patients who had cardiovascular events showed significantly higher IL-27 levels (median 0.29 vs. 0.22 ng/mL) and more frequently had an IL-27 level of >0.25 ng/mL (59% vs. 40%) (p < 0.01). The Kaplan–Meier analysis demonstrated a lower event-free survival rate in patients with an IL-27 level >0.25 ng/mL than in those with an IL-27 level ≤0.25 ng/mL (p < 0.02). The multivariate Cox proportional hazards regression analysis showed that IL-27 level (>0.25 ng/mL) was a significant predictor for cardiovascular events (hazard ratio: 1.82; 95%CI: 1.13–2.93, p < 0.02), independent of CHD. Thus, high IL-27 levels in plasma were related to an increased risk of further cardiovascular events in patients who underwent elective coronary angiography.
Full article
The global burden of liver disease is enormous, which highlights the need for effective hepatoprotective agents. It was reported that allicin exhibits protective effects against a range of diseases. In this study, we further evaluated allicin’s effect and mechanism in acute hepatic injury.
[...] Read more.
The global burden of liver disease is enormous, which highlights the need for effective hepatoprotective agents. It was reported that allicin exhibits protective effects against a range of diseases. In this study, we further evaluated allicin’s effect and mechanism in acute hepatic injury. Liver injury in mice was induced by intraperitoneal injection with 1% CCl4 (10 mL/kg/day). When the first dose was given, CCl4 was given immediately after administration of different doses of allicin (40, 20, and 10 mg/kg/day) as well as compound glycyrrhizin (CGI, 80 mg/kg/day), and then different doses of allicin (40, 20, and 10 mg/kg/day) as well as compound glycyrrhizin (CGI, 80 mg/kg/day) were administrated every 12 h. The animals were dissected 24 h after the first administration. The findings demonstrated a significant inhibition of CCl4-induced acute liver injury following allicin treatment. This inhibition was evidenced by notable reductions in serum levels of transaminases, specifically aspartate transaminase, along with mitigated histological damage to the liver. In this protective process, allicin plays the role of reducing the amounts or the expression levels of proinflammatory cytokines, IL-1β, IL-6. Furthermore, allicin recovered the activities of the antioxidant enzyme catalase (CAT) and reduced the production of malondialdehyde (MDA) in a dose-dependent manner, and also reduced liver Caspase 3, Caspase 8, and BAX to inhibit liver cell apoptosis. Further analysis showed that the administration of allicin inhibited the increased protein levels of Nuclear factor-erythroid 2-related factor 2 (Nrf2) and NAD(P)H:quinone oxidoreductase 1 (NQO1), which is related to inflammation and oxidative stress. The in vitro study of the LPS-induced RAW264.7 inflammatory cell model confirmed that allicin can inhibit important inflammation-related factors and alleviate inflammation. This research firstly clarified that allicin has a significant protective effect on CCl4-induced liver injury via inhibiting the inflammatory response and hepatocyte apoptosis, alleviating oxidative stress associated with the progress of liver damage, highlighting the potential of allicin as a hepatoprotective agent.
Full article
by
Mackenzie L. Griffin, Colleen E. Bryan, Tara M. Cox, Brian C. Balmer, Russell D. Day, Laura Garcia Barcia, Antoinette M. Gorgone, Jeremy J. Kiszka, Jenny A. Litz, Robin M. Perrtree, Teri K. Rowles, Lori H. Schwacke, Randall S. Wells and Eric Zolman
Bottlenose dolphins (Tursiops spp.) inhabit bays, sounds, and estuaries (BSEs) throughout the southeast region of the U.S.A. and are sentinel species for human and ecosystem-level health. Dolphins are vulnerable to the bioaccumulation of contaminants through the coastal food chain because they are
[...] Read more.
Bottlenose dolphins (Tursiops spp.) inhabit bays, sounds, and estuaries (BSEs) throughout the southeast region of the U.S.A. and are sentinel species for human and ecosystem-level health. Dolphins are vulnerable to the bioaccumulation of contaminants through the coastal food chain because they are high-level predators. Currently, there is limited information on the spatial dynamics of mercury accumulation in these dolphins. Total mercury (THg) was measured in dolphin skin from multiple populations across the U.S. Southeast Atlantic and Gulf of Mexico coasts, and the influence of geographic origin, sex, and age class was investigated. Mercury varied significantly among sampling sites and was greatest in dolphins in St. Joseph Bay, Florida Everglades, and Choctawhatchee Bay (14,193 ng/g ± 2196 ng/g, 10,916 ng/g ± 1532 ng/g, and 7333 ng/g ± 1405 ng/g wet mass (wm), respectively) and lowest in dolphins in Charleston and Skidaway River Estuary (509 ng/g ± 32.1 ng/g and 530 ng/g ± 58.4 ng/g wm, respectively). Spatial mercury patterns were consistent regardless of sex or age class. Bottlenose dolphin mercury exposure can effectively represent regional trends and reflect large-scale atmospheric mercury input and local biogeochemical processes. As a sentinel species, the bottlenose dolphin data presented here can direct future studies to evaluate mercury exposure to human residents in St. Joseph Bay, Choctawhatchee Bay, and Florida Coastal Everglades, as well as additional sites with similar geographical, oceanographic, or anthropogenic parameters. These data may also inform state and federal authorities that establish fish consumption advisories to determine if residents in these locales are at heightened risk for mercury toxicity.
Full article
by
João Pedro Rudrigues de Souza, Jeremie Garnier, Julia Mançano Quintarelli, Myller de Sousa Tonhá, Henrique Llacer Roig, Patrick Seyler and Jurandir Rodrigues de Souza
Artisanal small-scale gold mining (ASGM), an increasingly prevalent activity in South America, generates mercury-contaminated tailings that are often disposed of in the environment, leading to the introduction of mercury into ecosystems and the food web, where it bioaccumulates. Therefore, studying the geochemical processes
[...] Read more.
Artisanal small-scale gold mining (ASGM), an increasingly prevalent activity in South America, generates mercury-contaminated tailings that are often disposed of in the environment, leading to the introduction of mercury into ecosystems and the food web, where it bioaccumulates. Therefore, studying the geochemical processes involved in the desorption and dissolution of mercury in these tailings is essential for critical risk evaluations in the short and long term. For this purpose, sequential extraction procedures (SEPs) can be useful because they help to identify the phases to which Hg is associated, although they also have limitations such as a lack of selectivity and specificity. In this work, we propose a modified four-step SEP: exchangeable mercury (F1), oxidizable mercury (F2), mercury bound to Fe oxides (F3), and strongly bound mercury (F4). To test this adapted sequential extraction method, we evaluated the Hg contamination in mercury-contaminated tailings of the Amazon basin. The results revealed a total mercury concentration of 103 ± 16 mg·kg−1 in the tailings, with a significant portion in F1 (28% of the total), where Hg was bioavailable. The large Hg concentration in F3 (36%) suggested that Fe oxides likely contribute to mercury retention. Together, the SEP results emphasize the urgent need for improved surveillance of gold mining activities and responsible tailings management practices to mitigate environmental contamination and safeguard the health of the Amazon ecosystem.
Full article
There is a need to increase the consumption of whole wheat bread (WWB) due to its health benefits by overcoming its poor technological quality and improving its sensory characteristics. In this study, sourdough bread-making and frozen dough technology were combined to provide fresh
[...] Read more.
There is a need to increase the consumption of whole wheat bread (WWB) due to its health benefits by overcoming its poor technological quality and improving its sensory characteristics. In this study, sourdough bread-making and frozen dough technology were combined to provide fresh WWB at any time with better quality. Also, it was aimed to investigate the effects of three types of sourdough (type I, II, and IV) on the final quality of WWB during frozen storage (−30 °C, 14 and 28 days). The tan δ of WWB with type I sourdough was highest at the end of the frozen storage. Freezable water content was lower on day 0 for WWB with type II and IV sourdough than other bread types. No significant effect of frozen storage was observed in bread types in terms of an α helix structure, except for WWB with type I sourdough. A lower hardness increment was shown in WWB with baker’s yeast and WWB with type II sourdough over 14 days of frozen storage when compared to other bread types. WWB with type I sourdough and WWB with type IV sourdough were differentiated from other bread samples in volatile compound (VC) analysis on frozen storage days 28 and 0, respectively. The frozen storage of WWB with baker’s yeast and WWB with type II sourdough caused no notable changes in the VCs profile. These results suggest that a less detrimental effect of frozen storage was observed in WWB with type II sourdough, indicating a more favorable choice for producing WWB with sourdough.
Full article
In the present study, the combined effect of an AgIon® antimicrobial absorbent (Ζ) pad and a chitosan coating (C) on the preservation of fresh beef stored aerobically at 5 °C was investigated. Microbiological, physicochemical, and sensory attributes were monitored for up to
[...] Read more.
In the present study, the combined effect of an AgIon® antimicrobial absorbent (Ζ) pad and a chitosan coating (C) on the preservation of fresh beef stored aerobically at 5 °C was investigated. Microbiological, physicochemical, and sensory attributes were monitored for up to 10 days of storage. The microbiological data indicated that the C and chitosan coating plus absorbent pad (CZ) treatments were the most efficient in reducing total viable counts (TVC) by 4.09 and 3.53 log cfu/g compared to the control W and Z treatments on day 4 of storage (p < 0.05). An analogous reduction in the counts of the other microbial groups monitored was recorded. pH values were ca. 5.7 for treatments W and Z and 5.45 for treatments C and CZ on day 4 of storage (p < 0.05). The total volatile basic nitrogen (TVB-N) values remained <20 mg/100 g for all treatments on day 4 and for treatments C and CZ on day 10 of storage. The total color difference values decreased (p < 0.05) during storage for treatments W and Z, but remained constant for treatments C and CZ. Based on sensory, microbiological and physico-chemical data, beef shelf life was ca ^# + 3 days for samples W and Z and at least 10 + 3 days for samples C and CZ. Between the two antimicrobial treatments, chitosan was considerably more effective than the AgIon® antimicrobial absorbent pad, which showed practically no antimicrobial activity in direct contact with beef meat.
Full article
The traditional fermentation process of soy sauce employs a hyperhaline model and has a long fermentation period. A hyperhaline model can improve fermentation speed, but easily leads to the contamination of miscellaneous bacteria and fermentation failure. In this study, after the conventional koji
[...] Read more.
The traditional fermentation process of soy sauce employs a hyperhaline model and has a long fermentation period. A hyperhaline model can improve fermentation speed, but easily leads to the contamination of miscellaneous bacteria and fermentation failure. In this study, after the conventional koji and moromi fermentation, the fermentation broth was pasteurized and diluted, and then inoculated with three selected microorganisms including Corynebacterium glutamicum, Corynebacterium ammoniagenes, and Lactiplantibacillus plantarum for secondary fermentation. During this ten-day fermentation, the pH, free amino acids, organic acids, nucleotide acids, fatty acids, and volatile compounds were analyzed. The fermentation group inoculated with C. glutamicum accumulated the high content of amino acid nitrogen of 0.92 g/100 mL and glutamic acid of 509.4 mg/100 mL. The C. ammoniagenes group and L. plantarum group were rich in nucleotide and organic acid, respectively. The fermentation group inoculated with three microorganisms exhibited the best sensory attributes, showing the potential to develop a suitable fermentation method. The brewing speed of the proposed process in this study was faster than that of the traditional method, and the umami substances could be significantly accumulated in this low-salt fermented model (7% w/v NaCl). This study provides a reference for the low-salt and rapid fermentation of seasoning.
Full article
Protein–protein and protein–mineral interactions can result in defects, such as sedimentation and age gelation, during the storage of high-protein beverages. It is well known that age gelation can be delayed by adding cyclic polyphosphates such as sodium hexametaphosphate (SHMP). This study aims to
[...] Read more.
Protein–protein and protein–mineral interactions can result in defects, such as sedimentation and age gelation, during the storage of high-protein beverages. It is well known that age gelation can be delayed by adding cyclic polyphosphates such as sodium hexametaphosphate (SHMP). This study aims to assess the influence of different phosphate chain lengths of SHMP on the physicochemical properties of high-protein dispersions. The effect of adding different SHMP concentrations at 0%, 0.15%, and 0.25% (w/w) before and after heating of 6%, 8%, and 10% (w/w) milk protein concentrate dispersions was studied. The phosphate chain lengths of SHMPs used in this study were 16.47, 13.31, and 9.88, and they were classified as long-, medium-, and short-chain SHMPs, respectively. Apparent viscosity, particle size, heat coagulation time (HCT), color, and turbidity were evaluated. It was observed that the addition of SHMP (0.15% and 0.25%) increased the apparent viscosity of MPC dispersions. However, the chain length and the concentration of the added SHMP had no significant (p > 0.05) effect on the apparent viscosity after heating the dispersions. The HCT of a dispersion containing 6%, 8%, and 10% protein with no SHMP added was 15.28, 15.61, and 11.35 min, respectively. The addition of SHMP at both levels (0.15% and 0.25%) significantly increased the HCT. Protein dispersions (6%, 8%, and 10%) containing 0.25% short-chain SHMP had the highest HCT at 19.29, 19.61, and 16.09 min, respectively. Therefore, the chain length and concentration of added SHMP significantly affected the HCT of unheated protein dispersion (p < 0.05).
Full article
The aim of this research was to optimize the production process of fermented gluten-free quinoa bread. To this end, the effect of different hydrocolloids on the technological, fermentative, and nutritional properties of quinoa-based gluten-free doughs and breads was evaluated. For this purpose, 3%
[...] Read more.
The aim of this research was to optimize the production process of fermented gluten-free quinoa bread. To this end, the effect of different hydrocolloids on the technological, fermentative, and nutritional properties of quinoa-based gluten-free doughs and breads was evaluated. For this purpose, 3% of four different hydrocolloids (sodium alginate, k-carrageenan, xanthan gum, and hydroxypropyl methylcellulose (HPMC)) were used in gluten-free doughs composed of 50% quinoa flour, 20% rice flour, and 30% potato starch. The rheological and fermentative properties of the doughs were evaluated, as well as the chemical composition, specific volume, crust and crumb color, and alveolar structure profile of gluten-free breads. The results highlighted the differences in dough rheology during mixing and fermentation of the doughs. In particular, HPMC showed a good gas retention (93%) during the fermentation of quinoa dough by registering the highest maximum dough development height (Hm). The gluten-free quinoa breads obtained were characterized by significantly different quality parameters (p < 0.05). The use of 3% HPMC resulted in breads with the lowest baking loss, the highest volume, and the most open crumb structure.
Full article
When constructing an investment portfolio, it is important to maximize returns while minimizing risks. This portfolio optimization can be considered as a multi-objective optimization problem that is solved by means of multi-objective evolutionary algorithms. The use of multi-objective evolutionary algorithms (MOEAs) provides an
[...] Read more.
When constructing an investment portfolio, it is important to maximize returns while minimizing risks. This portfolio optimization can be considered as a multi-objective optimization problem that is solved by means of multi-objective evolutionary algorithms. The use of multi-objective evolutionary algorithms (MOEAs) provides an effective approach for dealing with the complex data involved in multi-objective optimization problems. However, current MOEAs often rely on a single strategy to obtain optimal solutions, leading to premature convergence and an insufficient population diversity. In this paper, a new MOEA called the Synergistic MOEA with Diffusion Population Generation (DPG-SMOEA) is proposed to address these limitations by integrating MOEAs with diffusion models. To train the diffusion model, a mixed memory pool strategy is optimized, which collects improved solutions from the MOEA/D-AEE, an optimized MOEA, as training samples. The trained model is then used to generate offspring. Considering the cold-start mechanism of the diffusion model, particularly during the training phase where it is not suitable for generating initial offspring, this paper adjusts and optimizes the collaborative strategy to enhance the synergy between the diffusion model and MOEA/D-AEE. Experimental validation of the DPG-SMOEA demonstrates the advantages of using diffusion models in low-dimensional and relatively continuous data analysis. The results show that the DPG-SMOEA performs well on the low-dimensional Hang Seng Index test dataset, while achieving average performance on other high-dimensional datasets, consistent with theoretical predictions. Overall, the DPG-SMOEA achieves better results compared to MOEA/D-AEE and other multi-objective optimization algorithms.
Full article
Nowadays, the call for sustainable development is becoming stronger in all countries of the world, and environmental, social, and governance (ESG) performance, as a vivid practice of this concept, has gradually received extensive attention from enterprises and investors. Financial institutions have an important
[...] Read more.
Nowadays, the call for sustainable development is becoming stronger in all countries of the world, and environmental, social, and governance (ESG) performance, as a vivid practice of this concept, has gradually received extensive attention from enterprises and investors. Financial institutions have an important position in the national economy as an important tool for the state to regulate the macroeconomy. Whether ESG performance can improve financial institutions’ efficiency is of key significance for boosting sustainable development. Based on data from China’s listed financial institutions from 2015 to 2021, this study aims to investigate the impact of ESG performance on financial institutions. The robust nonparametric boundary model and fixed-effects model are employed for analysis. The empirical results demonstrate that ESG performance and its sub-indicators of environmental performance and social responsibility performance can significantly enhance financial institutions’ efficiency. In particular, this effect is more pronounced in the securities industry and diversified financial industry, as well as in non-state and small-scale financial institutions. The results remain unchanged after a series of robustness tests. Furthermore, the mechanism tests indicate that ESG performance can enhance financial institutions’ efficiency by reducing downside risk and agency costs.
Full article
This study aims to analyze the impact of uniform and eccentric load conditions on the performance of internal feedback hydrostatic thrust and journal bearing. Two distinct models are established: a three-degrees-of-freedom uniform load model and a five-degrees-of-freedom eccentric load model. The support stiffness,
[...] Read more.
This study aims to analyze the impact of uniform and eccentric load conditions on the performance of internal feedback hydrostatic thrust and journal bearing. Two distinct models are established: a three-degrees-of-freedom uniform load model and a five-degrees-of-freedom eccentric load model. The support stiffness, overturning stiffness, and flow rate for both thrust and journal bearings are calculated. Additionally, numerical analysis is conducted to examine the influence of oil film thickness, inlet pressure, and restrictor size on the operational characteristics of the bearings, revealing the interplay between an eccentric load and journal bearing speed. The validity of the theoretical algorithm is verified through finite element simulation. The research outcomes hold significant guiding implications for the design and application of internal feedback hydrostatic bearings.
Full article
Wavelet decomposition is pivotal for underwater image processing, known for its ability to analyse multi-scale image features in the frequency and spatial domains. In this paper, we propose a new biorthogonal cubic special spline wavelet (BCS-SW), based on the Cohen–Daubechies–Feauveau (CDF) wavelet construction
[...] Read more.
Wavelet decomposition is pivotal for underwater image processing, known for its ability to analyse multi-scale image features in the frequency and spatial domains. In this paper, we propose a new biorthogonal cubic special spline wavelet (BCS-SW), based on the Cohen–Daubechies–Feauveau (CDF) wavelet construction method and the cubic special spline algorithm. BCS-SW has better properties in compact support, symmetry, and frequency domain characteristics. In addition, we propose a K-layer network (KLN) based on the BCS-SW for underwater image enhancement. The KLN performs a K-layer wavelet decomposition on underwater images to extract various frequency domain features at multiple frequencies, and each decomposition layer has a convolution layer corresponding to its spatial size. This design ensures that the KLN can understand the spatial and frequency domain features of the image at the same time, providing richer features for reconstructing the enhanced image. The experimental results show that the proposed BCS-SW and KLN algorithm has better image enhancement effect than some existing algorithms.
Full article
The Solow residual method, traditionally pivotal for calculating total factor productivity (TFP), is typically not applied to green TFP calculations due to its exclusion of undesired outputs. Diverging from traditional approaches and other frontier methodologies such as Data Envelopment Analysis (DEA) and Stochastic
[...] Read more.
The Solow residual method, traditionally pivotal for calculating total factor productivity (TFP), is typically not applied to green TFP calculations due to its exclusion of undesired outputs. Diverging from traditional approaches and other frontier methodologies such as Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), this paper integrates undesired outputs and three types of spatial spillover effects into the conventional Solow framework, thereby creating a new spatiotemporal econometric Solow residual method (STE-SRM). Utilizing this novel method, the study computes the industrial green TFPs for 280 Chinese cities from 2003 to 2019, recalculates these TFPs using DEA-SBM and Bayesian SFA for the same cities and periods, and assesses the accuracy of the STE-SRM-derived TFPs through comparative analysis. Additionally, the paper explores the statistical properties of China’s urban industrial green TFPs as derived from the STE-SRM, employing Dagum’s Gini coefficient and spatial convergence analyses. The findings first indicate that by incorporating undesired outputs and spatial spillover into the Solow residual method, green TFPs are computable in alignment with the traditional Solow logic, although the allocation of per capita inputs and undesired outputs hinges on selecting the optimal empirical production function. Second, China’s urban industrial green TFPs, calculated using the STE-SRM with the spatial Durbin model with mixed effects as the optimal model, show that cities like Huangshan, Fangchenggang, and Sanya have notably higher TFPs, whereas Jincheng, Datong, and Taiyuan display lower TFPs. Third, comparisons of China’s urban industrial green TFP calculations reveal that those derived from the STE-SRM demonstrate broader but more concentrated results, while Bayesian SFA results are narrower and less concentrated, and DEA-SBM findings sit between these extremes. Fourth, the study highlights significant spatial heterogeneity in China’s urban industrial green TFPs across different regions—eastern, central, western, and northeast China—with evident sigma convergence across the urban landscape, though absolute beta convergence is significant only in a limited subset of cities and time periods.
Full article
In the dynamic landscape of cyberspace, organizations face a myriad of coordinated advanced threats that challenge the traditional defense paradigm. Cyber Threat Intelligence (CTI) plays a crucial role, providing in-depth insights into adversary groups and enhancing the detection and neutralization of complex cyber
[...] Read more.
In the dynamic landscape of cyberspace, organizations face a myriad of coordinated advanced threats that challenge the traditional defense paradigm. Cyber Threat Intelligence (CTI) plays a crucial role, providing in-depth insights into adversary groups and enhancing the detection and neutralization of complex cyber attacks. However, attributing attacks poses significant challenges due to over-reliance on malware samples or network detection data alone, which falls short of comprehensively profiling attackers. This paper proposes an IPv4-based threat attribution model, IPAttributor, that improves attack characterization by merging a real-world network behavior dataset comprising 39,707 intrusion entries with commercial threat intelligence from three distinct sources, offering a more nuanced context. A total of 30 features were utilized from the enriched dataset for each IP to create a feature matrix to assess the similarities and linkage of associated IPs, and a dynamic weighted threat segmentation algorithm was employed to discern attacker communities. The experiments affirm the efficacy of our method in pinpointing attackers sharing a common origin, achieving the highest accuracy of 88.89%. Our study advances the relatively underexplored line of work of cyber attacker attribution, with a specific interest in IP-based attribution strategies, thereby enhancing the overall understanding of the attacker’s group regarding their capabilities and intentions.
Full article
With the increasing demand for road traffic safety assessment, global concerns about road safety have been rising. This is particularly evident with the widespread adoption of V2X (Vehicle-to-Everything) technology, where people are more intensively focused on how to leverage advanced technological means to
[...] Read more.
With the increasing demand for road traffic safety assessment, global concerns about road safety have been rising. This is particularly evident with the widespread adoption of V2X (Vehicle-to-Everything) technology, where people are more intensively focused on how to leverage advanced technological means to effectively address challenges in traffic safety. Through the research of driving style recognition technology, accurate assessment of driving behavior and the provision of personalized safety prompts and warnings have become crucial for preventing traffic accidents. This paper proposes a risk field construction technique based on environmental data collected by in-vehicle sensors. This paper introduces a driving style recognition algorithm utilizing risk field visualization and mask learning technologies. The research results indicate that, compared to traditional classical models, the improved algorithm performs excellently in terms of accuracy, stability, and robustness, enhancing the accuracy of driving style recognition and enabling a more effective evaluation of road safety.
Full article