bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Lyophilized Xenodermotransplants in Repairing the Atria’s Structure and the Peculiarities of Regenerative Processes after Thermal Trauma in an Experiment
Authors: Osowski Adam , Hetmaniuk Iryna , Fedchyshyn Olena , Sas Mykhailo , Lomakina Yuliia , Tkachuk Nataliia , Budarna Olena , Fik Volodymyr , Fedoniuk Larisa , Wojtkiewicz Joanna
Published: June 2023

The effects of severe burn injuries on the cardiovascular system, specifically the atria and auricles of the heart, were investigated. The potential benefits of using lyophilized xenodermotransplants as a treatment option were also evaluated. The experiments were conducted on adult guinea pigs divided into three groups: intact animals, animals with burns, and animals with burns who underwent early necrectomy followed by wound closure with lyophilized xenodermotransplants. Third-degree burns caused significant ultrastructural changes in atrial cardiomyocytes, leading to long-term destructive changes in the structural components of the atria. However, the use of lyophilized xenodermotransplants had a positive effect on the atrial ultrastructure over time. This study highlights the complex and varied effects of burn injuries on the body and the potential benefits of lyophilized xenodermotransplants in treating severe burn injuries. By preventing destructive changes in the heart and activating regenerative processes, lyophilized xenodermotransplants can improve the condition of the heart after thermal injury. Further research and development in this area are necessary for understanding the potential of lyophilized xenodermotransplants in tissue repair and regeneration.
Approaches to Performance Assessment in Reverse Supply Chains: A Systematic Literature Review
Authors: Nunes Denilson Ricardo de Lucena , Nascimento Danyelle de Sousa , Matos Jennifer Rodrigues , Melo André Cristiano Silva , Martins Vitor William Batista , Braga Antônio Erlindo
Published: June 2023

Background: The interest in the topic of performance assessment in reverse supply chains (RSC) is increasing, although the body of research is still in its early stages. As this is a developing field, it is crucial to expand discussions on topics that have not yet been thoroughly examined, such as the intrinsic bias of indicators and metrics that may be associated with specific operational, economic, environmental perspectives, etc. Such perspectives should be considered in the decision-making process within the context of reverse logistics (RL) and waste management (WM). The aim of this research was to identify different perspectives employed in the development of proposed models in the literature. Methods: A systematic literature review was conducted to analyze thirty papers from Scopus, Web of Science, and Science Direct databases without time restrictions. Results: The review identified various ways in which authors grouped perspectives, including qualitative and quantitative, sustainability, and operational perspectives, among others. Conclusions: This study revealed several gaps in the field, including limited studies on RSC performance assessment and a lack of studies linking performance assessment to decision-making components.
Low-Density Unsaturated Polyester Resin with the Presence of Dual-Initiator
Authors: Zhu Jinjian , Wang Xiaojun , Chen Minzhuang
Published: June 2023

Dual-initiation is a new orientation of many studies in the curing of unsaturated polyester resin and the manufacture of low-density unsaturated polyester resin (LDUPR) composite materials. In our research, two kinds of low-temperature (40–70 °C) initiators (cyclohexanone peroxide (CYHP) and methyl ethyl ketone peroxide (MEKP)), one kind of medium-temperature (70–130 °C) initiator (tert-butyl peroxy-2-ethylhexanoate (TBPO)), and three kinds of high-temperature (≥130 °C) initiators (tert-butyl benzoate peroxide (TBPB), tert-amyl carbonate peroxide-2-ethylhexanoate (TAEC), and tert-butyl carbonate peroxide-2-ethylhexanoate (TBEC)) were applied to constitute different dual-initiators. Those dual-initiators were a low-temperature dual-initiator (CYHP/MEKP), medium-low-temperature dual-initiators (CYHP/TBPO and MEKP/TBPO), and high-temperature dual-initiators (TAEC/TBPB, TAEC/TBEC, and TBEC/TBPB). In the low-temperature and medium-low-temperature ranges, the LDUPR sample displayed the highest specific compression strength (Ps) of 42.08 ± 0.26 MPa·g−1·cm3 in the presence of the MEKP/TBPO dual-initiator. In the high-temperature range, the LDUPR sample exhibited the highest specific compression strength (Ps) of 43.32 ± 0.45 MPa·g−1·cm3 for the existence of the TAEC/TBPB dual-initiator. It is pointed out that the dual-initiator released more active free radicals, accelerating the initial curing time and the peak time of UPR. More active free radicals caused both high-activity (short-chain) molecules and low-activity (long-chain or intertwined) molecules in resin to cross-link, prolonging UPR’s curing process by approximately two minutes and resulting in an improvement of UPR’s cross-linking. In the presence of a dual-initiator, the integrated and planar microstructure of LDUPR samples performed uniformly distributed dimples, dispersed external forces, and enhanced samples’ specific compressive strength.
Design and Experiments of Electro-Hydrostatic Actuator for Wheel-Legged Robot with Fast Force Control Response
Authors: Zhao Huipeng , Zhou Junjie , Ma Sanxi , Du Shanxiao , Liu Hui , Han Lijin
Published: June 2023

The wheel-legged robot combines the functions of wheeled vehicles and legged robots: high speed and high passability. However, the limited performance of existing joint actuators has always been the bottleneck in the actual applications of large wheel-legged robots. This paper proposed a highly integrated electro-hydrostatic actuator (EHA) to enable high-dynamic performance in giant wheel-legged robots (>200 kg). A prototype with a high force-to-weight ratio was developed by integrating a micropump, a miniature spring accumulator, and a micro-symmetrical cylinder. The prototype achieves a large output force of more than 9400 N and a high force-to-weight ratio of more than 2518 N/kg. Compared with existing EHA-based robots, it has a higher force-to-weight ratio and can bear larger loads. A detailed EHA model was presented, and controllers were designed based on sliding mode control and PID methods to control the output position and force of the piston. The model’s accuracy is improved by identifying uncertain parameters such as friction and leakage coefficient. Finally, both simulations and experiments were carried out. The results verified the fast response of force control (step response within 50 ms, the force tracking control frequency about 6.7 Hz) and the developed EHA’s good potential for future large wheel-legged robots.
Solution NMR Backbone Assignment of the C-Terminal Region of Human Dynein Light Intermediate Chain 2 (LIC2-C) Unveils Structural Resemblance with Its Homologue LIC1-C
Authors: Henen Morkos A. , Paukovich Natasia , Prekeris Rytis , Vögeli Beat
Published: June 2023

Dynein, a homodimeric protein complex, plays a pivotal role in retrograde transportation along microtubules within cells. It consists of various subunits, among which the light intermediate chain (LIC) performs diverse functions, including cargo adaptor binding. In contrast to the vertebrate LIC homolog LIC1, LIC2 has received relatively limited characterization thus far, despite partially orthogonal functional roles. In this study, we present a near-to-complete backbone NMR chemical shift assignment of the C-terminal region of the light intermediate chain 2 of human dynein 1 (LIC2-C). We perform a comparative analysis of the secondary structure propensity of LIC2-C with the one previously reported for LIC1-C and show that the two transient helices in LIC1 that interact with motor adaptors are also present in LIC2.
Research on Forest Fire Detection Algorithm Based on Improved YOLOv5
Authors: Li Jianfeng , Lian Xiaoqin
Published: June 2023

Forest fires are one of the world’s deadliest natural disasters. Early detection of forest fires can help minimize the damage to ecosystems and forest life. In this paper, we propose an improved fire detection method YOLOv5-IFFDM for YOLOv5. Firstly, the fire and smoke detection accuracy and the network perception accuracy of small targets are improved by adding an attention mechanism to the backbone network. Secondly, the loss function is improved and the SoftPool pyramid pooling structure is used to improve the regression accuracy and detection performance of the model and the robustness of the model. In addition, a random mosaic augmentation technique is used to enhance the data to increase the generalization ability of the model, and re-clustering of flame and smoke detection a priori frames are used to improve the accuracy and speed. Finally, the parameters of the convolutional and normalization layers of the trained model are homogeneously merged to further reduce the model processing load and to improve the detection speed. Experimental results on self-built forest-fire and smoke datasets show that this algorithm has high detection accuracy and fast detection speed, with average accuracy of fire up to 90.5% and smoke up to 84.3%, and detection speed up to 75 FPS (frames per second transmission), which can meet the requirements of real-time and efficient fire detection.
Reinforcement Learning Recommendation Algorithm Based on Label Value Distribution
Authors: Guo Zhida , Fu Jingyuan , Sun Peng
Published: June 2023

Reinforcement learning is an important machine learning method and has become a hot popular research direction topic at present in recent years. The combination of reinforcement learning and a recommendation system, is a very important application scenario and application, and has always received close attention from researchers in all sectors of society. In this paper, we first propose a feature engineering method based on label distribution learning, which analyzes historical behavior is analyzed and constructs, whereby feature vectors are constructed for users and products via label distribution learning. Then, a recommendation algorithm based on value distribution reinforcement learning is proposed. We first designed the stochastic process of the recommendation process, described the user’s state in the interaction process (by including the information on their explicit state and implicit state), and dynamically generated product recommendations through user feedback. Next, by studying hybrid recommendation strategies, we combined the user’s dynamic and static information to fully utilize their information and achieve high-quality recommendation algorithms. Finally, the algorithm was designed and validated, and various relevant baseline models were compared to demonstrate the effectiveness of the algorithm in this study. With this study, we actually tested the remarkable advantages of relevant design models based on nonlinear expectations compared to other homogeneous individual models. The use of recommendation systems with nonlinear expectations has considerably increased the accuracy, data utilization, robustness, model convergence speed, and stability of the systems. In this study, we incorporated the idea of nonlinear expectations into the design and implementation process of recommendation systems. The main practical value of the improved recommendation model is that its performance is more accurate than that of other recommendation models at the same level of computing power level. Moreover, due to the higher amount of information that the enhanced model contains, it provides theoretical support and the basis for an algorithm that can be used to achieve high-quality recommendation services, and it has many application prospects.
Wavelets in Combination with Stochastic and Machine Learning Models to Predict Agricultural Prices
Authors: Garai Sandip , Paul Ranjit Kumar , Rakshit Debopam , Yeasin Md , Emam Walid , Tashkandy Yusra , Chesneau Christophe
Published: June 2023

Wavelet decomposition in signal processing has been widely used in the literature. The popularity of machine learning (ML) algorithms is increasing day by day in agriculture, from irrigation scheduling and yield prediction to price prediction. It is quite interesting to study wavelet-based stochastic and ML models to appropriately choose the most suitable wavelet filters to predict agricultural commodity prices. In the present study, some popular wavelet filters, such as Haar, Daubechies (D4), Coiflet (C6), best localized (BL14), and least asymmetric (LA8), were considered. Daily wholesale price data of onions from three major Indian markets, namely Bengaluru, Delhi, and Lasalgaon, were used to illustrate the potential of different wavelet filters. The performance of wavelet-based models was compared with that of benchmark models. It was observed that, in general, the wavelet-based combination models outperformed other models. Moreover, wavelet decomposition with the Haar filter followed by application of the random forest (RF) model gave better prediction accuracy than other combinations as well as other individual models.
Synchrosqueezing Transform Based on Frequency-Domain Gaussian-Modulated Linear Chirp Model for Seismic Time–Frequency Analysis
Authors: Bing Pingping , Liu Wei , Zhang Haoqi , Zhu Li , Zhu Guiping , Zhou Jun , He Binsheng
Published: June 2023

The synchrosqueezing transform (SST) has attracted much attention as a post-processing technique since it was proposed. In recent years, improvements to SST have been made. However, the existing methods are mainly based on the time-domain signal model, and the weak frequency modulation assumption for the components composing the signal is always taken into account. Thus, the signals characterized by a rapidly changing instantaneous frequency (IF) may fail to be adequately tackled. To address this problem, the paper presents a novel seismic time–frequency analysis method via synchrosqueezing transform where a frequency-domain Gaussian modulated linear chirp model is utilized to deduce the SST. The group delay (GD) rather than the IF estimator is implemented to compute an estimation of the ridge. Furthermore, a new synchrosqueezing operator is constructed to rearrange the energy around the ridge. A synthetic example verifies the efficiency and robustness of the proposed SST method, which generates better results than some classic time–frequency analysis (TFA) approaches, e.g., short-time Fourier transform (STFT) and STFT-based SST (FSST). A field dataset further demonstrates this method’s potential in the delineation of subsurface geological structures.
Synchronization of Markov Switching Inertial Neural Networks with Mixed Delays under Aperiodically On-Off Adaptive Control
Authors: Guo Beibei , Xiao Yu
Published: June 2023

In this paper, the issue of exponential synchronization in Markov switching inertial neural networks with mixed delays is investigated via aperiodically on–off adaptive control. The inertial term is considered, which extends the existing network modes with first-order differential term. Combined with the Lyapunov method, graph theory, and the differential inequalities technique, two types of synchronization criteria are presented which take into account all of the time delay information and reduce the conservativeness. Finally, some numerical simulations are provided in order to show the validity of the theoretical results.
Dynamics of Newtonian Liquids with Distinct Concentrations Due to Time-Varying Gravitational Acceleration and Triple Diffusive Convection: Weakly Non-Linear Stability of Heat and Mass Transfer
Authors: Singh Pervinder , Gupta Vinod K. , Animasaun Isaac Lare , Muhammad Taseer , Al-Mdallal Qasem M.
Published: June 2023

One of the practical methods for examining the stability and dynamical behaviour of non-linear systems is weakly non-linear stability analysis. Time-varying gravitational acceleration and triple-diffusive convection play a significant role in the formation of acceleration, inducing some dynamics in the industry. With an emphasis on the natural Rayleigh–Bernard convection, more is needed on the significance of a modulated gravitational field on the heat and mass transfer due to triple convection focusing on weakly non-linear stability analysis. The Newtonian fluid layers were heated, salted and saturated from below, causing the bottom plate’s temperature and concentration to be greater than the top plate’s. In this study, the acceleration due to gravity was assumed to be time-dependent and comprised of a constant gravity term and a time-dependent gravitational oscillation. More so, the amplitude of the modulated gravitational field was considered infinitesimal. The case in which the fluid layer is infinitely expanded in the x-direction and between two concurrent plates at z=0 and z=d was considered. The asymptotic expansion technique was used to retrieve the solution of the Ginzburg–Landau differential equation (i.e., a system of non-autonomous partial differential equations) using the software MATHEMATICA 12. Decreasing the amplitude of modulation, Lewis number, Rayleigh number and frequency of modulation has no significant effect on the Nusselt number proportional to heat-transfer rates (Nu), Sherwood number proportional to mass transfer of solute 1 (Sh1) and Sherwood number proportional to mass transfer of solute 2 (Sh2) at the initial time. The crucial Rayleigh number rises in value in the presence of a third diffusive component. The third diffusive component is essential in delaying the onset of convection.
Multimodal Prompt Learning in Emotion Recognition Using Context and Audio Information
Authors: Jeong Eunseo , Kim Gyunyeop , Kang Sangwoo
Published: June 2023

Prompt learning has improved the performance of language models by reducing the gap in language model training methods of pre-training and downstream tasks. However, extending prompt learning in language models pre-trained with unimodal data to multimodal sources is difficult as it requires additional deep-learning layers that cannot be attached. In the natural-language emotion-recognition task, improved emotional classification can be expected when using audio and text to train a model rather than only natural-language text. Audio information, such as voice pitch, tone, and intonation, can give more information that is unavailable in text to predict emotions more effectively. Thus, using both audio and text can enable better emotion prediction in speech emotion-recognition models compared to semantic information alone. In this paper, in contrast to existing studies that use multimodal data with an additional layer, we propose a method for improving the performance of speech emotion recognition using multimodal prompt learning with text-based pre-trained models. The proposed method is using text and audio information in prompt learning by employing a language model pre-trained on natural-language text. In addition, we propose a method to improve the emotion-recognition performance of the current utterance using the emotion and contextual information of the previous utterances for prompt learning in speech emotion-recognition tasks. The performance of the proposed method was evaluated using the English multimodal dataset MELD and the Korean multimodal dataset KEMDy20. Experiments using both the proposed methods obtained an accuracy of 87.49%, F1 score of 44.16, and weighted F1 score of 86.28.
Functional Subspace Variational Autoencoder for Domain-Adaptive Fault Diagnosis
Authors: Li Tan , Fung Che-Heng , Wong Him-Ting , Chan Tak-Lam , Hu Haibo
Published: June 2023

This paper presents the functional subspace variational autoencoder, a technique addressing challenges in sensor data analysis in transportation systems, notably the misalignment of time series data and a lack of labeled data. Our technique converts vectorial data into functional data, which captures continuous temporal dynamics instead of discrete data that consist of separate observations. This conversion reduces data dimensions for machine learning tasks in fault diagnosis and facilitates the efficient removal of misalignment. The variational autoencoder identifies trends and anomalies in the data and employs a domain adaptation method to associate learned representations between labeled and unlabeled datasets. We validate the technique’s effectiveness using synthetic and real-world transportation data, providing valuable insights for transportation infrastructure reliability monitoring.
An Underground Mine Ore Pass System Optimization via Fuzzy 0–1 Linear Programming with Novel Torricelli–Simpson Ranking Function
Authors: Halilović Dževdet , Gligorić Miloš , Gligorić Zoran , Pamučar Dragan
Published: June 2023

In this work, we propose a 3D dynamic optimization model that enables the design of an underground mine ore pass system with uncertainties. Ore transportation costs and ore pass development costs are quantified by triangular fuzzy numbers. Transportation costs are treated as production costs, and they vary over the duration of mining operation, while development costs of ore passes are treated as an investment, and they are treated as constant. The developed model belongs to the class of fuzzy 0–1 linear programming models, where the fuzzy objective cost function achieves a minimum value, with respect to given set of techno-dynamic constraints. Searching for optimal value in the fuzzy environment is a hard task, and because of that, we developed a new ranking function which transforms the fuzzy optimization model into a crisp one. A triangular fuzzy number can be presented as a triangular graph G(V,E) composed of vertices and edges. The x-coordinate of the Torricelli point of a triangular graph presents the crisp value of a triangular fuzzy number. The use of this model lets us know the optimal number of ore passes, optimal location of ore passes, and optimal dynamic ore transportation plan.
Pulmonary Valve Endocarditis during and beyond Euro ENDO Registry: A Single Center Case Series
Authors: Srdanović Ilija , Stefanović Maja , Miljković Tatjana , Bjelić Snežana , Trajković Miloš , Pantić Teodora , Velicki Lazar , Milovančev Aleksandra
Published: June 2023

Background: Pulmonary valve infective endocarditis (PVIE) is a rare form of infective endocarditis (IE) and is associated with high mortality and severe complications. Guidelines for treatment of this form of IE are scarce and based on general recommendations. We report a case series of PVE. Detailed Case Description: Case 1—A 36-year-old female with congenital pulmonary artery stenosis, dyspnea and leg edema symptoms for 2 months. Blood cultures yielded Staphylococcus spp. and Corynebacterium sp., and echocardiography revealed multiple floating vegetation at the pulmonic valve and surrounding structures. The clinical course was complicated with sepsis and multi-organ failure. Urgent surgery with pulmonary homograft implantation resulted in successful five-year outcome. Case 2—In a 38-year-old male with previous tetralogy of Fallot correction and symptoms of fatigue, fever, myalgia, and photophobia, echocardiography was suggestive of PVIE. The clinical course was complicated with septic shock, multi-organ failure, ischemic stroke with hemorrhagic transformation and death on the 12th day of hospitalization. Case 3—A 41-year-old male without previous medical history was hospitalized due to prolonged fatigue, fever, dyspnea, and leg edema. He was diagnosed with multi-valve infective endocarditis, affecting the aortic, tricuspid, and pulmonary valve. Acute heart failure and hemodynamic instability indicated urgent surgery with aortic valve replacement and reconstruction of the tricuspid and pulmonary valves. At four-year follow up he was doing well. Conclusion: Symptoms in PVIE may be versatile, and diagnosis is often delayed. High level of suspicion, early recognition, and echocardiography are cornerstones in diagnostics. Despite the standpoint that medical therapy is first-line, the role of surgery needs to be advocated in particular cases.
Antegrade Posterior Column Acetabulum Fracture Screw Fixation via Posterior Approach: A Biomechanical Comparative Study
Authors: Berk Till , Zderic Ivan , Schwarzenberg Peter , Drenchev Ludmil , Skulev Hristo Kostov , Pfeifer Roman , Pastor Tatjana , Richards Geoff , Gueorguiev Boyko , Pape Hans-Christoph
Published: June 2023

Background and Objectives: Minimally invasive surgeries for acetabulum fracture fixation are gaining popularity due to their known advantages versus open reduction and internal fixation. Antegrade or retrograde screw fixation along the long axis of the posterior column of the acetabulum is increasingly applied in surgical practice. While there is sufficient justification in the literature for the application of the anterior approach, there is a deficit of reports related to the posterior approach. The aim of this study was to evaluate the biomechanical competence of posterior column acetabulum fracture fixation through antegrade screw placement using either a standard cannulated screw or a cannulated compression headless screw (CCHS) via posterior approach. Materials and Methods: Eight composite pelvises were used, and a posterior column acetabulum fracture according to the Letournel Classification was simulated on both their left and right sides via an osteotomy. The sixteen hemi-pelvic specimens were assigned to two groups (n = 8) for either posterior column standard screw (group PCSS) or posterior column CCHS (group PCCH) fixation. Biomechanical testing was performed by applying steadily increased cyclic load until failure. Interfragmentary movements were investigated by means of motion tracking. Results: Initial stiffness demonstrated significantly higher values in PCCH (163.1 ± 14.9 N/mm) versus PCSS (133.1 ± 27.5 N/mm), p = 0.024. Similarly, cycles and load at failure were significantly higher in PCCH (7176.7 ± 2057.0 and 917.7 ± 205.7 N) versus PCSS (3661.8 ± 1664.5 and 566.2 ± 166.5 N), p = 0.002. Conclusion: From a biomechanical perspective, CCHS fixation demonstrates superior stability and could be a valuable alternative option to the standard cannulated screw fixation of posterior column acetabulum fractures, thus increasing the confidence in postoperative full weight bearing for both the patient and treating surgeon. Whether uneventful immediate postoperative full weight bearing can be achieved with CCHS fixation should primarily be investigated in further human cadaveric studies with a larger sample size.
Anterior Approach to Hip Arthroplasty with Early Mobilization Key for Reduced Hospital Length of Stay
Authors: Bontea Mihaela , Bimbo-Szuhai Erika , Macovei Iulia Codruta , Maghiar Paula Bianca , Sandor Mircea , Botea Mihai , Romanescu Dana , Beiusanu Corina , Cacuci Adriana , Sachelarie Liliana , Huniadi Anca
Published: June 2023

Background and Objectives: This study aimed to explore the preoperative factors related to early mobilization and length of stay (LOS) after total hip arthroplasty and the benefits of the anterior approach over the traditional lateral approach. Materials and Methods: Every patient benefits from information regarding details of the surgery approach, possible intra, and postoperative complications, post-operator medical care, and steps in the early mobilization protocol. The patient underwent a pre-anesthetic evaluation, was checked for preoperatory vital function, and was reevaluated for mobilization at 6, 12, 24, 36, 48, and 96 h after total hip arthroplasty using the anterior versus lateral approach. Results: The result of the statistical calculations indicates the independent negative risk factors for reaching the mobilization target: age with a coefficient of −0.046, p = 0.0154 and lateral approach with a relative risk of 0.3802 (95% CI: 0.15–0.90), p = 0.0298. Statistical data concerning the length of stay (LOS) showed significant differences in the total days spent in the hospital. The patients who were operated on using the lateral approach presented a higher body mass index than those with the anterior approach, but this difference did not reach the threshold of statistical significance. Conclusions: In our study, patient mobilization is crucial to reduce LOS.
A Combined Gas and Water Permeances Method for Revealing the Deposition Morphology of GO Grafting on Ceramic Membranes
Authors: Galata Evdokia , Veziri Charitomeni M. , Theodorakopoulos George V. , Romanos George Em. , Pavlatou Evangelia A.
Published: June 2023

The adhesion enhancement of a graphene oxide (GO) layer on porous ceramic substrates is a crucial step towards developing a high-performance membrane for many applications. In this work, we have achieved the chemical anchoring of GO layers on custom-made macroporous disks, fabricated in the lab by pressing α-Al2O3 powder. To this end, three different linkers, polydopamine (PDA), 3-Glycidoxypropyltrimethoxysilane (GPTMS) and (3-Aminopropyl) triethoxysilane (APTMS), were elaborated for their capacity to tightly bind the GO laminate on the ceramic membrane surface. The same procedure was replicated on cylindrical porous commercial ZrO2 substrates because of their potentiality for applications on a large scale. The gas permeance properties of the membranes were studied using helium at 25 °C as a probe molecule and further scrutinized in conjunction with water permeance results. Measurements with helium at 25 °C were chosen to avoid gas adsorption and surface diffusion mechanisms. This approach allowed us to draw conclusions on the deposition morphology of the GO sheets on the ceramic support, the mode of chemical bonding with the linker and the stability of the deposited GO laminate. Specifically, considering that He permeance is mostly affected by the pore structural characteristics, an estimation was initially made of the relative change in the pore size of the developed membranes compared to the bare substrate. This was achieved by interpreting the results via the Knudsen equation, which describes the gas permeance as being analogous to the third power of the pore radius. Subsequently, the calculated relative change in the pore size was inserted into the Hagen–Poiseuille equation to predict the respective water permeance ratio of the GO membranes to the bare substrate. The reason that the experimental water permeance values may deviate from the predicted ones is related to the different surface chemistry, i.e., the hydrophilicity or hydrophobicity that the composite membranes acquire after the chemical modification. Various characterization techniques were applied to study the morphological and physicochemical properties of the materials, like FESEM, XRD, DLS and Contact Angle.
Application of Digital Image Processing Techniques to Detect Through-Thickness Crack in Hole Expansion Test
Authors: Cruz Daniel J. , Amaral Rui L. , Santos Abel D. , Tavares João Manuel R. S.
Published: June 2023

Advanced high-strength steels (AHSS) have become increasingly popular in the automotive industry due to their high yield and ultimate tensile strengths, enabling the production of lighter car body structures while meeting safety standards. However, they have some setbacks compared to conventional steels, such as edge cracking through sheet thickness caused by forming components with shear-cut edges. When characterizing the formability of sheet metal materials, the hole expansion test is an industry-standard method used to evaluate the stretch-flangeability of their edges. However, accurately visualizing the first cracking is usually tricky and may be subjective, often leading to inconsistent results and low reproducibility with some impact of the operator on both direct and post-processing measurements. To address these issues, a novel digital image processing method is presented to reduce operator reliance and enhance the accuracy and efficiency of the hole expansion test results. By leveraging advanced image processing algorithms, the proposed approach detects the appearance of the first edge cracks, enabling a more precise determination of the hole expansion ratio (HER). Furthermore, it provides valuable insights into the evolution of the hole diameter, allowing for a comprehensive understanding of the material behavior during the test. The proposed method was evaluated for different materials, and the corresponding HER values were compared with the traditional method.
The Computational Acid–Base Chemistry of Hepatic Ketoacidosis
Authors: Torrens Samuel L. , Robergs Robert A. , Curry Steven C. , Nalos Marek
Published: June 2023

Opposing evidence exists for the source of the hydrogen ions (H+) during ketoacidosis. Organic and computational chemistry using dissociation constants and alpha equations for all pertinent ionizable metabolites were used to (1) document the atomic changes in the chemical reactions of ketogenesis and ketolysis and (2) identify the sources and quantify added fractional (~) H+ exchange (~H+e). All computations were performed for pH conditions spanning from 6.0 to 7.6. Summation of the ~H+e for given pH conditions for all substrates and products of each reaction of ketogenesis and ketolysis resulted in net reaction and pathway ~H+e coefficients, where negative revealed ~H+ release and positive revealed ~H+ uptake. Results revealed that for the liver (pH = 7.0), the net ~H+e for the reactions of ketogenesis ending in each of acetoacetate (AcAc), β-hydroxybutyrate (β-HB), and acetone were −0.9990, 0.0026, and 0.0000, respectively. During ketogenesis, ~H+ release was only evident for HMG CoA production, which is caused by hydrolysis and not ~H+ dissociation. Nevertheless, there is a net ~H+ release during ketogenesis, though this diminishes with greater proportionality of acetone production. For reactions of ketolysis in muscle (pH = 7.1) and brain (pH = 7.2), net ~H+ coefficients for β-HB and AcAc oxidation were −0.9649 and 0.0363 (muscle), and −0.9719 and 0.0291 (brain), respectively. The larger ~H+ release values for β-HB oxidation result from covalent ~H+ release during the oxidation–reduction. For combined ketogenesis and ketolysis, which would be the metabolic condition in vivo, the net ~H+ coefficient depends once again on the proportionality of the final ketone body product. For ketone body production in the liver, transference to blood, and oxidation in the brain and muscle for a ratio of 0.6:0.2:0.2 for β-HB:AcAc:acetone, the net ~H+e coefficients for liver ketogenesis, blood transfer, brain ketolysis, and net total (ketosis) equate to −0.1983, −0.0003, −0.2872, and −0.4858, respectively. The traditional theory of ketone bodies being metabolic acids causing systemic acidosis is incorrect. Summation of ketogenesis and ketolysis yield H+ coefficients that differ depending on the proportionality of ketone body production, though, in general, there is a small net H+ release during ketosis. Products formed during ketogenesis (HMG-CoA, acetoacetate, β-hydroxybutyrate) are created as negatively charged bases, not acids, and the final ketone body, acetone, does not have pH-dependent ionizable groups. Proton release or uptake during ketogenesis and ketolysis are predominantly caused by covalent modification, not acid dissociation/association. Ketosis (ketogenesis and ketolysis) results in a net fractional H+ release. The extent of this release is dependent on the final proportionality between acetoacetate, β-hydroxybutyrate, and acetone.
Improving Experimental Design through Uncertainty Analysis
Authors: Hobbs Ian M. , Charboneau Joey A. , Jacobsen Todd L.
Published: June 2023

In this paper, the development of a fission-gas collecting and physical-analysis-enabling instrument was proposed for small-volume determination. Analysis specifications require a design capable of accurately and repeatably determining volumes in the range of 0.07–2.5 mL. This system relies on a series of gas expansions originating from a cylinder with known internal volume. The combined gas law is used to derive the unknown volumes from these expansions. Initial system designs included one of two known volumes, 11.85 ± 0.34 mL and 5.807 ± 0.078 mL, with a manifold volume of 32 mL. Results obtained from modeling this system’s operation showed that 0.07 mL can be determined with a relative expanded uncertainty greater than 300% (k = 2) for a single replicate, which was unacceptable for the proposed experimental design. Initial modeling showed that the volume connecting the known volume and rodlet, i.e., the manifold volume, and the sensitivity of the pressure sensor were key contributors to the expanded uncertainty of the measured rodlet volume. The system’s design limited the available options for pressure sensors, so emphasis was placed on the design of the manifold volume. The final system design reduced the manifold volume to 17 mL. These changes in design, combined with replicate analysis, were able to reduce the relative expanded uncertainty by ±12% (k = 2) for the 0.07 mL volume.
First Report of Olive Branch Dieback in Croatia Caused by Cytospora pruinosa Défago
Authors: Petrović Elena , Vrandečić Karolina , Ivić Dario , Ćosić Jasenka , Godena Sara
Published: June 2023

Olive (Olea europaea L.) is a very important crop grown in the Mediterranean part of Croatia. Olive branch and fruit dieback symptoms were observed in two olive orchards in Istria, Croatia. The samples from symptomatic trees were collected and brought to the laboratory for analysis. Based on their morphological characterization, isolated fungi were identified as Cytospora sp. Two representative isolates (one per orchard) were taken for molecular analysis, and based on DNA sequence data of the ITS and TUB gene regions, and phylogenetic analysis of the sequences, the isolates were identified as Cytospora pruinosa Défago. To determine pathogenicity, pathogenicity tests were conducted on detached olive branches and two-year-old olive trees in the greenhouse. This is the first report of C. pruinosa causing olive branch and fruit dieback in Croatia.
Can Entomopathogenic Nematodes and Their Symbiotic Bacteria Suppress Fruit Fly Pests? A Review
Authors: Toledo Jorge , Morán-Aceves Brenda M. , Ibarra Jorge E. , Liedo Pablo
Published: June 2023

Fruit flies (Diptera: Tephritidae) are serious pests that affect fruit production and marketing. Both third instar larvae and pupae are biological stages that persist in the soil until adult emergence. Entomopathogenic nematodes (ENs) are biological control agents that are used to control agricultural pests in greenhouse or field conditions. Several studies have been carried out under laboratory and field conditions showing how ENs can be applied within an area-wide integrated pest management approach to control fruit fly species in orchards and backyard fruit trees. In this review, we analyze how soil physical characteristics and biotic factors affect the performance of these biological control agents. Of the reviewed papers, more than half evaluated the influence of soil texture, humidity, temperature, and other factors on the performance of infective juveniles (IJs). Abiotic factors that significantly influence the performance of IJs are temperature, humidity, and texture. Among the biotic factors that affect IJs are fungi, bacteria, mites, insects, and earthworms. We conclude that ENs have the potential to be applied in the drip area of fruit trees that are infested by fruit flies and contribute to their suppression. This approach, in conjunction with an area-wide pest management approach, may contribute to pest suppression and increase the sustainability of agroecosystems.
Isolation and Genomic Analysis of 3-Chlorobenzoate-Degrading Bacteria from Soil
Authors: Ara Ifat , Moriuchi Ryota , Dohra Hideo , Kimbara Kazuhide , Ogawa Naoto , Shintani Masaki
Published: June 2023

The compound 3-chlorobenzoate (3-CBA) is a hazardous industrial waste product that can harm human health and the environment. This study investigates the physiological and genetic potential for 3-chlorobenzoate (3-CBA) degradation. Six 3-CBA Gram-negative degraders with different degradation properties belonging to the genera Caballeronia, Paraburkholderia and Cupriavidus were isolated from the soil. The representative strains Caballeronia 19CS4-2 and Paraburkholderia 19CS9-1 showed higher maximum specific growth rates (µmax, h−1) than Cupriavidus 19C6 and degraded 5 mM 3-CBA within 20–28 h. Two degradation products, chloro-cis,cis-muconate and maleylacetate, were detected in all isolates using high-performance liquid chromatography and mass spectrometry. Genomic analyses revealed the presence of cbe and tfd gene clusters in strains 19CS4-2 and 19CS9-1, indicating that they probably metabolized the 3-CBA via the chlorocatechol ortho-cleavage pathway. Strain 19C6 possessed cbe genes, but not tfd genes, suggesting it might have a different chlorocatechol degradation pathway. Putative genes for the metabolism of 3-hydroxybenzoate via gentisate were found only in 19C6, which utilized the compound as a sole carbon source. 19C6 exhibited distinct characteristics from strains 19CS4-2 and 19CS9-1. The results confirm that bacteria can degrade 3-CBA and improve our understanding of how they contribute to environmental 3-CBA biodegradation.
Nosocomial Pathogens and Antimicrobial Resistance: Modern Challenges and Future Opportunities
Authors: Freitas Ana R. , Werner Guido
Published: June 2023

Antimicrobial resistance (AMR) has become a critical global health emergency in the 21st century, with the greatest burden in resource-limited settings [...]
Molecular Mimicry and HLA Polymorphisms May Drive Autoimmunity in Recipients of the BNT-162b2 mRNA Vaccine: A Computational Analysis
Authors: Talotta Rossella
Published: June 2023

Background: After the start of the worldwide COVID-19 vaccination campaign, there were increased reports of autoimmune diseases occurring de novo after vaccination. This in silico analysis aimed to investigate the presence of protein epitopes encoded by the BNT-162b2 mRNA vaccine, one of the most widely administered COVID-19 vaccines, which could induce autoimmunity in predisposed individuals. Methods: The FASTA sequence of the protein encoded by the BNT-162b2 vaccine served as the key input to the Immune Epitope Database and Analysis Resource. Linear peptides with 90% BLAST homology were selected, and T-cell, B-cell, and MHC-ligand assays without MHC restriction were searched and analyzed. HLA disease associations were screened on the HLA-SPREAD platform by selecting only positive markers. Results: By 7 May 2023, a total of 5693 epitopes corresponding to 21 viral but also human proteins were found. The latter included CHL1, ENTPD1, MEAF6, SLC35G2, and ZFHX2. Importantly, some autoepitopes may be presented by HLA alleles positively associated with various immunological diseases. Conclusions: The protein product of the BNT-162b2 mRNA vaccine contains immunogenic epitopes that may trigger autoimmune phenomena in predisposed individuals through a molecular mimicry mechanism. Genotyping for HLA alleles may help identify individuals at risk. However, further wet-lab studies are needed to confirm this hypothesis.
The Plant Growth-Promoting Potential of Halotolerant Bacteria Is Not Phylogenetically Determined: Evidence from Two Bacillus megaterium Strains Isolated from Saline Soils Used to Grow Wheat
Authors: Ait Bessai Sylia , Cruz Joana , Carril Pablo , Melo Juliana , Santana Margarida M. , Mouazen Abdul M. , Cruz Cristina , Yadav Ajar Nath , Dias Teresa , Nabti El-hafid
Published: June 2023

(1) Background: Increasing salinity, further potentiated by climate change and soil degradation, will jeopardize food security even more. Therefore, there is an urgent need for sustainable agricultural practices capable of maintaining high crop yields despite adverse conditions. Here, we tested if wheat, a salt-sensitive crop, could be a good reservoir for halotolerant bacteria with plant growth-promoting (PGP) capabilities. (2) Methods: We used two agricultural soils from Algeria, which differ in salinity but are both used to grow wheat. Soil halotolerant bacterial strains were isolated and screened for 12 PGP traits related to phytohormone production, improved nitrogen and phosphorus availability, nutrient cycling, and plant defence. The four ‘most promising’ halotolerant PGPB strains were tested hydroponically on wheat by measuring their effect on germination, survival, and biomass along a salinity gradient. (3) Results: Two halotolerant bacterial strains with PGP traits were isolated from the non-saline soil and were identified as Bacillus subtilis and Pseudomonas fluorescens, and another two halotolerant bacterial strains with PGP traits were isolated from the saline soil and identified as B. megaterium. When grown under 250 mM of NaCl, only the inoculated wheat seedlings survived. The halotolerant bacterial strain that displayed all 12 PGP traits and promoted seed germination and plant growth the most was one of the B. megaterium strains isolated from the saline soil. Although they both belonged to the B. megaterium clade and displayed a remarkable halotolerance, the two bacterial strains isolated from the saline soil differed in two PGP traits and had different effects on plant performance, which clearly shows that PGP potential is not phylogenetically determined. (4) Conclusions: Our data highlight that salt-sensitive plants and non-saline soils can be reservoirs for halotolerant microbes with the potential to become effective and sustainable strategies to improve plant tolerance to salinity. However, these strains need to be tested under field conditions and with more crops before being considered biofertilizer candidates.
Enhancing the Catalytic Activity of Glycolate Oxidase from Chlamydomonas reinhardtii through Semi-Rational Design
Authors: Feng Yingting , Shao Shuai , Zhou Xueting , Wei Wan , Liu Xun , Tang Yi , Hua Yuhao , Zheng Jianyong , Zhang Yinjun , Ying Xiangxian
Published: June 2023

Glycolate oxidase is a peroxisomal flavoprotein catalyzing the oxidation of glycolate to glyoxylate and plays crucial metabolic roles in green algae, plants, and animals. It could serve as a biocatalyst for enzymatic production of glyoxylate, a fine chemical with a wide variety of applications in perfumery, flavor, and the pharmaceutical and agrochemical industries. However, the low catalytic activity of native glycolate oxidase and low levels of active enzyme in heterologous expression limit its practical use in industrial biocatalysis. Herein, the glycolate oxidase from Chlamydomonas reinhardtii (CreGO) was selected through phylogenetic tree analysis, and its low level of soluble expression in E. coli BL21(DE3) was improved through the use of the glutathione thioltransferase (GST), the choice of the vector pET22b and the optimization of induction conditions. The semi-rational design of the fusion enzyme GST-Gly-Ser-Gly-CreGO led to the superior variant GST-Gly-Ser-Gly-CreGO-Y27S/V111G/V212R with the kcat/Km value of 29.2 s−1·mM−1, which was six times higher than that of the wild type. In contrast to GST-Gly-Ser-Gly-CreGO, 5 mg/mL of crude enzyme GST-Gly-Ser-Gly-CreGO-Y27S/V111G/V212R together with 25 μg/mL of catalase catalyzed the oxidation of 300 mM of methyl glycolate for 8 h, increasing the yield from 50.4 to 93.5%.
Outer Membrane Porins Contribute to Antimicrobial Resistance in Gram-Negative Bacteria
Authors: Zhou Gang , Wang Qian , Wang Yingsi , Wen Xia , Peng Hong , Peng Ruqun , Shi Qingshan , Xie Xiaobao , Li Liangqiu
Published: June 2023

Gram-negative bacteria depend on their cell membranes for survival and environmental adaptation. They contain two membranes, one of which is the outer membrane (OM), which is home to several different outer membrane proteins (Omps). One class of important Omps is porins, which mediate the inflow of nutrients and several antimicrobial drugs. The microorganism’s sensitivity to antibiotics, which are predominantly targeted at internal sites, is greatly influenced by the permeability characteristics of porins. In this review, the properties and interactions of five common porins, OmpA, OmpC, OmpF, OmpW, and OmpX, in connection to porin-mediated permeability are outlined. Meanwhile, this review also highlighted the discovered regulatory characteristics and identified molecular mechanisms in antibiotic penetration through porins. Taken together, uncovering porins’ functional properties will pave the way to investigate effective agents or approaches that use porins as targets to get rid of resistant gram-negative bacteria.