bluuebunny/crossref_metadata_2025 huggingface dataset:
Extraction of Germanium from Low-Grade Germanium-Bearing Lignite by Reductive Volatilization
Authors: Yang Rengao , Song Weifeng , Rao Shuai , Tao Jinzhang , Wang Dongxing , Cao Hongyang , Liu Zhiqiang
Published: July 2023

Germanium (Ge) as an important strategic metal is widely used in many modern-technology fields such as optical fiber and thermal solar cells. In this study, the volatilization behavior of Ge from low-grade germanium-bearing lignite was investigated in detail through reductive volatilization. The results indicated that temperature and air flow rate in the semi-closed roasting system played a significant role in the process. The optimal volitation efficiency of Ge reached 98% at 1100 °C for 2 h with air flow rate of 0.7 L/min in a maffle furnace, respectively. Under optimal conditions, the contents of Ge lowered to 30 ppm in the roasting residue. Analysis of the enriched ash yielded 71,600 ppm for Ge. Chemical phase analysis of the Ge in the enrichment ash showed that soluble Ge accounted for 82.18% of the total Ge, which could be viewed as an excellent material for Ge extraction by chlorinated distillation.
Explainable Artificial Intelligence to Investigate the Contribution of Design Variables to the Static Characteristics of Bistable Composite Laminates
Authors: Saberi Saeid , Nasiri Hamid , Ghorbani Omid , Friswell Michael I. , Castro Saullo G. P.
Published: July 2023

Material properties, geometrical dimensions, and environmental conditions can greatly influence the characteristics of bistable composite laminates. In the current work, to understand how each input feature contributes to the curvatures of the stable equilibrium shapes of bistable laminates and the snap-through force to change these configurations, the correlation between these inputs and outputs is studied using a novel explainable artificial intelligence (XAI) approach called SHapley Additive exPlanations (SHAP). SHAP is employed to explain the contribution and importance of the features influencing the curvatures and the snap-through force since XAI models change the data into a form that is more convenient for users to understand and interpret. The principle of minimum energy and the Rayleigh–Ritz method is applied to obtain the responses of the bistable laminates used as the input datasets in SHAP. SHAP effectively evaluates the importance of the input variables to the parameters. The results show that the transverse thermal expansion coefficient and moisture variation have the most impact on the model’s output for the transverse curvatures and snap-through force. The eXtreme Gradient Boosting (XGBoost) and Finite Element (FM) methods are also employed to identify the feature importance and validate the theoretical approach, respectively.
Measuring Point Planning and Fitting Optimization of the Flange and Spigot Structures of Aeroengine Rotors
Authors: Zhou Tianyi , Hu Lei , Jin Xiaoxiao , Li Ting , Zhang Yan , Chen Jianfeng , Gao Hang
Published: July 2023

An optimized measuring point planning and fitting method for rotor flange and spigot structures was proposed to achieve precise measurement of position and pose of the aeroengine rotors during docking processes. Firstly, the impact of circumferential phase angle, distribution range angle, total number of measuring points, and number of distribution rings on measurement uncertainty was analyzed. The measuring point planning schemes for flange and spigot were proposed. Secondly, the Gauss Newton iterative solution principle considering damping factors was clarified. Subsequently, an optimized iterative reweighting method consisting of weight iterative estimation, singular value detection under the Chauvenet criterion, and clustering detection was proposed for fitting the flange annular end face. A mapping point total least squares method with practical geometric significance was proposed for fitting the spigot cylinder face. Finally, measuring and fitting experiments were performed. The singular measuring point detection methods were verified. Under the optimized fitting methods, the goodness of fit and average orthogonal distance of flange and spigot structures are 0.756 and 0.089 mm, respectively, which have higher fitting accuracy than the other traditional methods.
LSTM-Based Stacked Autoencoders for Early Anomaly Detection in Induction Heating Systems
Authors: Qais Mohammed H. , Kewat Seema , Loo Ka Hong , Lai Cheung-Ming , Leung Aldous
Published: July 2023

Due to the contactless operation of cookware on induction heating systems, the temperature of the cookware is measured remotely using thermal sensors placed on the center of the coil. Hence, the measurement error of these sensors increases if the cookware placement is not centered on the top of the coil. Therefore, this study presents a new data-driven anomaly detection method to detect overheated cookware using the thermal sensor of the case temperature of the inverter module. This method utilizes the long short-term memory (LSTM)-based autoencoder (AE) to learn from large training data of temperatures of cookware and the inverter. The learning of the LSTM-AE model is achieved by minimizing the residual error between the input and reconstructed input data. Then, the maximum residual error can be set to be a threshold value between the normal and abnormal operation. Finally, the learned LSTM-AE model is tested using new testing data that include both normal and abnormal cases. The testing results revealed that the LSTM-AE model can detect cookware overheating by using the inverter temperature only. In addition, the LSTM-AE model can detect the faults in the inverter side, such as poor air ventilation and a faulted cooling fan. Furthermore, we utilized different deep learning algorithms, such as the recurrent neural network (RNN) and the fully connected layers, in the internal layers of the AE. The results demonstrated that the LSTM-AE could detect anomalies earlier than the other models.
Bayesian Network Structure Learning Using Improved A* with Constraints from Potential Optimal Parent Sets
Authors: He Chuchao , Di Ruohai , Tan Xiangyuan
Published: July 2023

Learning the structure of a Bayesian network and considering the efficiency and accuracy of learning has always been a hot topic for researchers. This paper proposes two constraints to solve the problem that the A* algorithm, an exact learning algorithm, is not efficient enough to search larger networks. On the one hand, the parent–child set constraints reduce the number of potential optimal parent sets. On the other hand, the path constraints are obtained from the potential optimal parent sets to constrain the search process of the A* algorithm. Both constraints are proposed based on the potential optimal parent sets. Experiments show that the time efficiency of the A* algorithm can be significantly improved, and the ability of the A* algorithm to search larger Bayesian networks can be improved by the two constraints. In addition, compared with the globally optimal Bayesian network learning using integer linear programming (GOBNILP) algorithm and the max–min hill-climbing (MMHC) algorithm, which are state of the art, the A* algorithm enhanced by constraints still performs well in most cases.
A Generalization of the Grey Lotka–Volterra Model and Application to GDP, Export, Import and Investment for the European Union
Authors: Sterpu Mihaela , Rocșoreanu Carmen , Soava Georgeta , Mehedintu Anca
Published: July 2023

This study proposes a generalized grey Lotka–Volterra model with a finite number of variables. The model is obtained by applying the grey modelling method to estimate the parameters of a finite dimensional quadratic Lotka–Volterra system. Subsequently, the model is used to analyze the competition and cooperation relationship between four macroeconomic indicators, namely Gross Domestic Product, Export, Import and Investment, and to obtain short-time forecasting for them. The data used in the empirical investigation cover the time periods 2005–2022 and 2011–2022, for the European Union. The empirical results are compared to the ones obtained by using the grey model GM(1,1) and the two-dimensional grey Lotka–Volterra model. Finally, economic interpretations of the empirical findings are formulated.
Impact of Cooperation and Intra-Specific Competition of Prey on the Stability of Prey–Predator Models with Refuge
Authors: Pal Soumyadip , Al Basir Fahad , Ray Santanu
Published: July 2023

The main objective of this study is to find out the influences of cooperation and intra-specific competition in the prey population on escaping predation through refuge and the effect of the two intra-specific interactions on the dynamics of prey–predator systems. For this purpose, two mathematical models with Holling type II functional response functions were proposed and analyzed. The first model includes cooperation among prey populations, whereas the second one incorporates intra-specific competition. The existence conditions and stability of different equilibrium points for both models were analyzed to determine the qualitative behaviors of the systems. Refuge through intra-specific competition has a stabilizing role, whereas cooperation has a destabilizing role on the system dynamics. Periodic oscillations were observed in both systems through Hopf bifurcation. From the analytical and numerical findings, we conclude that intra-specific competition affects the prey population and continuously controls the refuge class under a critical value, and thus, it never becomes too large to cause predator extinction due to food scarcity. Conversely, cooperation leads the maximal number of individuals to escape predation through the refuge so that predators suffer from low predation success.
A Randomized, Multicenter, Double-Blind, Parallel, Non-Inferiority Clinical Study to Compare the Efficacy and Safety of Unicenta and Melsmon for Menopausal Symptom Improvement
Authors: Kim Seongmin , Lee Sanghoon , Ahn Ki-Hoon , Park Hyun-Tae , Song Jae-Yun , Hong Soon-Cheol , Kim Tak
Published: July 2023

This study was conducted to evaluate the efficacy and safety of Unicenta in female subjects with menopausal symptoms by analyzing the changes in the Kupperman index (primary endpoint) and hormonal changes (secondary endpoint). It was a randomized, multi-center, double-blind, parallel, non-inferiority clinical study conducted at two different tertiary medical centers. A Unicenta injection was shown to be non-inferior to Melsmon based on the Kupperman index in both the intent-to-treat and per-protocol populations (p = 0.789 and p = 0.826, respectively). Additionally, there were no statistically significant differences in hormone levels (estradiol, follicular-stimulating hormone) or in the evaluation of facial flushes. There was no statistically significant difference in the incidence rate of adverse events between the two groups (p = 0.505). The study demonstrated that Unicenta is not inferior to Melsmon in terms of the change in the Kupperman index after 12 days of injection. The efficacy and safety of Unicenta were shown, resulting in the improvement of menopausal symptoms.
Comparing the Anterior-Based Muscle-Sparing Approach with the Direct Anterior Approach in Hip Arthroplasty: A Systematic Review and Pairwise Meta-Analysis
Authors: Chang Jae Suk , Kang Min Wook , Lee Dong Hwan , Kim Ji Wan , Kim Chul-Ho
Published: July 2023

Background and Objectives: The anterior-based muscle-sparing (ABMS) approach, which utilizes the interval between the tensor fasciae latae posteriorly, offers several advantages, such as the reduced risk of nerve injury and the freedom to choose various implants. Herein, we aimed to compare the outcome of ABMS to the direct anterior (DA) approach using pairwise meta-analysis techniques. Materials and Methods: A systematic search of the MEDLINE (PUBMED), Embase, and Cochrane Library databases was performed for studies published up to 7 June 2023, which compared the ABMS approach with the DA approach for hip arthroplasty. We compared (1) perioperative outcomes (operation time, visual analog scale (VAS) score, total opioid consumption, length of hospital stay (LOS), and the number of patients discharged to their homes); (2) postoperative complications (neuropraxia/nerve injury, dislocation, surgical site infection, intraoperative fracture, and reoperation rate); and (3) implant position (cup inclination, cup anteversion, and stem alignment). Results: Ten studies were eligible for meta-analysis, including 1737 patients who underwent hip arthroplasty with the ABMS approach and 1979 with the DA approach. The pooled analysis showed no differences in all outcome variables, including perioperative outcomes, postoperative complications, and the implant position between the two surgical approaches. Conclusions: In current meta-analysis, the ABMS approach demonstrated comparable results to the conventional DA approach in terms of both clinical and radiologic outcomes as well as postoperative complications. Furthermore, the ABMS approach has the advantage of a broader indication and fewer limitations in terms of the surgical position compared to the DA approach. Therefore, the ABMS approach can be even more beneficial as an option within MSA, surpassing the utility of the DA approach.
Comorbidities of COVID-19 Patients
Authors: Silaghi-Dumitrescu Radu , Patrascu Iulia , Lehene Maria , Bercea Iulia
Published: July 2023

The novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) responsible for the coronavirus disease outbreak initiated in 2019 (COVID-19) has been shown to affect the health of infected patients in a manner at times dependent on pre-existing comorbidities. Reported here is an overview of the correlation between comorbidities and the exacerbation of the disease in patients with COVID-19, which may lead to poor clinical outcomes or mortality. General medical issues are also reviewed, such as the types of symptoms present in people infected with SARS-CoV-2, the long-term effects of COVID-19 disease, and the types of treatment that are currently used.
Influence of Risk Factors on the Well-Being of Elderly Women with Knee Osteoarthritis
Authors: Minaković Ivana , Svorcan Jelena Zvekić , Janković Tanja , Glomazić Hajdana , Smuđa Mirjana , Živanović Dejan , Javorac Jovan , Kolarš Bela
Published: July 2023

Background and Objectives: Knee osteoarthritis (KOA) is a widespread chronic joint disease characterized by functional limitations and pain. Functioning restrictions exert a detrimental impact on societal integration, relationships, and psychological well-being, resulting in significant emotional distress in KOA patients. The objective of this study is to examine how various risk factors impact the emotional well-being of individuals with KOA. Materials and Methods: This prospective cross-sectional study involved 154 postmenopausal women treated at the Special Hospital for Rheumatic Diseases in Novi Sad, Serbia. The experimental group comprised 97 individuals with chronic knee pain and structural knee damage (Kellgren–Lawrence (KL) scale II-IV), while the control group had 53 individuals with chronic knee pain but no structural knee damage (KL scale 0-I). The collected data consisted of sociodemographic factors, general characteristics, associated diseases, and laboratory results. Adequate anthropometric measurements were conducted, and all subjects were required to complete the SF-36 RAND questionnaire. Results: The analysis identified several variables that independently influenced emotional well-being. These included pain intensity (beta (β) 0.21; 95% CI: 0.03–0.20; p < 0.01), social functioning (beta (β) 0.47; 95% CI: 0.23–0.43; p < 0.001), physical functioning (beta (β) 0.23; 95% CI: 0.04–0.21; p < 0.01), and education level (8–12 years: beta (β) 0.25; 95% CI: 1.47–9.41; p < 0.01; >12 years: beta (β) 0.27; 95% CI: 2.51–12.67; p < 0.01). However, the multivariate model revealed that only social functioning (beta (β) 0.57; 95% CI: 0.27–0.53; p < 0.001) and education level (8–12 years: beta (β) 0.21; 95% CI: 1.10–8.260; p < 0.05; >12 years: beta (β) 0.21; 95% CI: 1.18–10.30; p < 0.05) were significantly associated with emotional well-being in KOA patients. Conclusions: The findings of this study indicate that a reduced social functioning and a lower educational attainment are linked to a poorer emotional well-being among patients with KOA.
Predicting Urinary Stone Composition in Single-Use Flexible Ureteroscopic Images with a Convolutional Neural Network
Authors: Oh Kyung Tak , Jun Dae Young , Choi Jae Young , Jung Dae Chul , Lee Joo Yong
Published: July 2023

Background and Objectives: Analysis of urine stone composition is one of the most important factors in urolithiasis treatment. This study investigated whether a convolutional neural network (CNN) can show decent results in predicting urinary stone composition even in single-use flexible ureterorenoscopic (fURS) images with relatively low resolution. Materials and Methods: This study retrospectively used surgical images from fURS lithotripsy performed by a single surgeon between January 2018 and December 2021. The ureterorenoscope was a single-use flexible ureteroscope (LithoVue, Boston Scientific). Among the images taken during surgery, a single image satisfying the inclusion and exclusion criteria was selected for each stone. Cases were divided into two groups according to whether they contained any calcium oxalate (the Calcium group) or none (the Non-calcium group). From 506 total cases, 207 stone surface images were finally included in the study. In the CNN model, the transfer learning method using Resnet-18 as a pre-trained model was used, and only endoscopic digital images and stone classification data were input to achieve minimally supervised learning. Results: There were 175 cases in the Calcium group and 32 in the Non-calcium group. After training and validation, the model was tested using the test set, and the total accuracy was 81.8%. Recall and precision of the test results were 88.2% and 88.2% in the Calcium group and 60.0% and 60.0% in the Non-calcium group, respectively. The area under the receiver operating characteristic curve of the model, which represents its classification performance, was 0.82. Conclusions: Single-use flexible ureteroscopes have financial benefits but low vision quality compared with reusable digital flexible ureteroscopes. As far as we know, this is the first artificial intelligence study using single-use fURS images. It is meaningful that the CNN performed well even under these difficult conditions because these results can further expand the possibilities of its use.
Application Scenarios of a Tactile Surface Roughness Measurement System for In Situ Measurement in Machine Tools
Authors: Sulz Clemens , Bleicher Friedrich
Published: July 2023

The rate of automation in European industry is increasing continuously. In production metrology, the trend is shifting from measurement laboratories towards integration of metrology into the production process. Increasing levels of automation and the current skills shortage are driving demand for autonomous production systems. In this project, a roughness measurement system was developed that is fully integrated into machine tools and enables fully automatic roughness measurement of part surfaces during the machining process. Using a skidless measurement system, it was possible to obtained measured roughness values comparable to those obtained in measuring rooms under optimal conditions. The present paper shows the development process of the prototype and provides an overview of different application scenarios for in situ measurement of machine tools. In situ roughness measurement has high potential in the future of metrology in industrial applications. Not only can surfaces be measured directly in the process, sub-processes can be triggered based on the measured values, allowing the production process to react flexibly to actual conditions. Potential improvements in metrology and significant optimizations of the entire production chain are highlighted in this paper.
Microbial Synthesis of Lactic Acid from Cotton Stalk for Polylactic Acid Production
Authors: Paswan Meenakshi , Adhikary Sudipto , Salama Heba Hassan , Rusu Alexandru Vasile , Zuorro Antonio , Dholakiya Bharatkumar Z. , Trif Monica , Bhattacharya Sourish
Published: July 2023

Cotton stalk, a waste product in agriculture, serves as a beneficial, low-cost material as a medium for microbial synthesis of lactic acid as desired for polylactic acid synthesis. Cotton stalk was used as a substrate for microbial lactic acid synthesis, and a novel strain of Lactococcus cremoris was reported to synthesize 51.4 g/L lactic acid using cellulose recovered from the cotton stalk. In total, 18 Lactobacillus isolates were isolated from kitchen waste, soil, sugarcane waste, and raw milk samples screened for maximum lactic acid production. It was found that one of the Lactococcus cremoris isolates was found to synthesize maximum lactic acid at a concentration of 51.4 g/L lactic acid in the hydrolysate prepared from cotton stalk. The upstream process parameters included 10% inoculum size, hydrolysate containing reducing sugars 74.23 g/L, temperature 37 °C, agitation 220 rpm, production age 24 h. Only the racemic (50:50) mixture of D-LA and L-LA (i.e., D/L-LA) is produced during the chemical synthesis of lactic acid, which is undesirable for the food, beverage, pharmaceutical, and biomedical industries because only the L-form is digestible and is not suitable for biopolymer, i.e., PLA-based industry where high optically purified lactic acid is required. Furthermore, polylactic acid was synthesized through direct polycondensation methods using various catalysts such as chitosan, YSZ, and Sb2O3. PLA is biocompatible and biodegradable in nature (its blends and biocomposites), supporting a low-carbon and circular bioeconomy.
Metallo-Beta-Lactamase-like Encoding Genes in Candidate Phyla Radiation: Widespread and Highly Divergent Proteins with Potential Multifunctionality
Authors: Maatouk Mohamad , Merhej Vicky , Pontarotti Pierre , Ibrahim Ahmad , Rolain Jean-Marc , Bittar Fadi
Published: July 2023

The Candidate Phyla Radiation (CPR) was found to harbor a vast repertoire of genes encoding for enzymes with potential antibiotic resistance activity. Among these, as many as 3349 genes were predicted in silico to contain a metallo-beta-lactamase-like (MBL-like) fold. These proteins were subject to an in silico functional characterization by comparing their protein profiles (presence/absence of conserved protein domains) to other MBLs, including 24 already expressed in vitro, along with those of the beta-lactamase database (BLDB) (n = 761). The sequence similarity network (SSN) was then used to predict the functional clusters of CPR MBL-like sequences. Our findings showed that CPR MBL-like sequences were longer and more diverse than bacterial MBL sequences, with a high content of functional domains. Most CPR MBL-like sequences did not show any SSN connectivity with expressed MBLs, indicating the presence of many potential, yet unidentified, functions in CPR. In conclusion, CPR was shown to have many protein functions and a large sequence variability of MBL-like folds, exceeding all known MBLs. Further experimental and evolutionary studies of this superfamily of hydrolyzing enzymes are necessary to illustrate their functional annotation, origin, and expansion for adaptation or specialization within a given niche or compared to a specific substrate.
Use of Monoclonal Antibodies in Pregnant Women Infected by COVID-19: A Case Series
Authors: Crispino Pietro , Marocco Raffaella , Di Trento Daniela , Guarisco Gloria , Kertusha Blerta , Carraro Anna , Corazza Sara , Pane Cristina , Di Troia Luciano , del Borgo Cosimo , Lichtner Miriam
Published: July 2023

Background: Monoclonal antibodies are designed to target specific proteins of COVID-19 and can be used as a treatment for people with mild to moderate infection and at a high risk of severe disease. Casirivimab/imdevimab, sotrovimab, and Bamlanivimab/etesevimab have been authorized for emergency use in the treatment of COVID-19. However, during pregnancy, these drugs have not been extensively studied. Methods: A total of 22 pregnant women with mild to moderate infection were treated with three different monoclonal antibodies, and efficacy and safety were evaluated in the first period and until six months of follow-up. Results: No infusion/allergic reactions occurred. No fatal or adverse events were observed in the pregnant women or fetus. The time of negativization with sotrovimab was shorter in comparison to Imdevimav/casirivimab (p = 0.0187) and Bamlanivimab/etesevimab (p < 0.00001). The time of negativization with sotrovimab was earlier in comparison to Imdevimav/casirivimab (t-value: 2.92; p = 0.0052) in vaccinated patients and similar in comparison to Imdevimav/casirivimab (t-value: 1.48; p = 0.08). In unvaccinated patients, sotrovimab was faster to achieve negativization in comparison to Bamlanivimab/etesevimab (t-value: 10.75; p < 0.0005). Conclusions: Pregnant COVID-19 patients receiving sotrovimab obtained better clinical outcomes. Pregnancy or neonatal complications were not observed after monoclonal treatment, confirming the safety and tolerability of these drugs in pregnant women.
The Association between Gestational Diabetes Mellitus and Infections in Pregnancy—Systematic Review and Meta-Analysis
Authors: Yefet Enav , Bejerano Aviv , Iskander Rula , Zilberman Kimhi Tal , Nachum Zohar
Published: July 2023

We conducted a systematic review and meta-analysis to evaluate the association between gestational diabetes mellitus and infections during pregnancy. We included cross-sectional, case-control, cohort studies and clinical trials, evaluating the frequency of infections in women with and without gestational diabetes mellitus. A search was conducted in Embase, PubMed, and Web of Science electronic databases and by manually searching references, until 23 March 2022, resulting in 16 studies being selected for review, with 111,649 women in the gestational diabetes mellitus group, and 1,429,659 in the controls. Cochrane’s Q test of heterogeneity and I² were used to assess heterogeneity. Pooled odds ratio (OR) was calculated. Funnel plots and Egger test were used for assessment of publication bias. The results showed a significant association between gestational diabetes mellitus and infections (pooled-OR 1.3 95% CI [1.2–1.5]). Sub-analyses showed a significant association for urinary tract infections (pooled-OR of 1.2 95% CI [1.1–1.3]), bacterial infections (pooled-OR were 1.2 95% CI [1.1–1.4]), and SARS-CoV-2 (pooled-OR 1.5 95% CI [1.2–2.0]) but not to gingivitis or vaginal candidiasis. The results underscore the significance of acknowledging gestational diabetes mellitus as a risk factor for infections.
Development of Non-Destructive Dynamic Characterization Technique for MMCs: Predictions of Mechanical Properties for Al@Al2O3 Composites
Authors: Pingale Ajay D. , Gautam Diplesh , Owhal Ayush , Deshwal Dhruv , Belgamwar Sachin U. , Rao Venkatesh K. P.
Published: July 2023

In the past several decades, many destructive and non-destructive testing techniques have been developed to evaluate the characteristics of metal matrix composites (MMCs). This research aims to calculate the mechanical properties of the Al@Al2O3 composites by varying alumina nanoparticles (Al2O3 NPs) content using a non-invasive, position sensing detector (PSD) unit-based optical method. The composite was prepared by a powder metallurgy technique, and its characterization was conducted using SEM and XRD to understand its surface morphology and microstructure. The natural frequency and Young’s modulus of the composite were estimated experimentally. Young’s modulus was calculated using this natural frequency. The proposed study shows that Young’s modulus of the composite increases with an increase in Al2O3 NPs content in the composition, irrespective of the testing method. Along with this, natural frequency also increases with the increase in the Al2O3 NPs content. Evaluated properties were compared with the numerical modeling using COMSOL Multiphysics. The experimental and numerical results are equivalent and within the margin of error. This study illustrates the development of an experimental approach for evaluating the mechanical properties of a composite material. This experimental approach can be used whenever sample dimension and space are constrained to evaluate the mechanical behavior of nanomaterials and nanocomposites.
Nutrition and Supplements during Pregnancy: A Vital Component in Building the Health and Well-Being of Both the Mother and the Developing Baby
Authors: Qin Yushu , Xie Linglin
Published: July 2023

Maternal health is of the utmost importance during pregnancy, not just for the mother but also for the developing fetus [...]
Vertical Distribution, Community and Population Structures of the Planktonic Chaetognatha in the Western Subarctic Pacific: Insights on the Eukrohnia Species Group
Authors: Nakamura Yuya , Zhang Haochen , Yamaguchi Atsushi
Published: July 2023

In the oceans, Chaetognatha can contribute significantly to the total zooplankton biomass (up to 10–30%). The genus Eukrohnia, the dominant Chaetognath genus in the western subarctic Pacific, includes E. hamata and E. bathypelagica. Although it has been pointed out that there is no genetic difference between the two species, no study has been made that treats them as the same species group. In this study, we investigated vertical distribution based on the eight vertical stratification samplings down to 1000 m depths conducted day/night at four seasons covering one year, community structure, and population structure of the three dominant Chaetognath species: Parasagitta elegans, E. hamata, and E. bathypelagica in the western subarctic Pacific. The population densities of each species at 0–1000 m water column were 0.04–0.36 ind. m−3 for P. elegans, 0.14–1.60 ind. m−3 for E. hamata, 0.24–1.54 ind. m−3 for E. bathypelagica, and 1.37–2.62 ind. m−3 for Eukrohnia juveniles. The vertical distributions were consistent both day and night, and no diel changes were observed for all species throughout the seasons. The vertical distribution of Chaetognaths evaluated by the distribution center was 61–169 m for P. elegans, 143–206 m for Eukrohnia juveniles, 134–279 m for E. hamata, and 253–612 m for E. bathypelagica. The body length of P. elegans ranged from 4 to 34 mm, and one to three cohorts were identified at each sampling occasion. While the presence of the eight stages has been reported for Eukrohnia, only one to five stages occurred, and specimens belonging to six to eight stages were not observed in the samples throughout the year. The body length of the whole Eukrohnia species ranged from 2 to 14 mm. The body length histograms of the Eukrohnia species group, including E. hamata and E. bathypelagica, and their juveniles showed the presence of two to four cohorts at each sampling date. Within the Eukrohnia species group, vertical changes in body length were present, which were characterized by the smaller specimens occurring at shallower depths, followed by an increase in body length with increasing depths. From the vertical distribution and population structure of the Eukrohnia species group (Eukrohnia juvenile + E. hamata + E. bathypelagica) in this study, there was no difficulty in treating them as one species. It may suggest that E. hamata and E. bathypelagica in the western subarctic Pacific could be treated as one species group. To clarify this point, a detailed genetic analysis of the Eukrohnia species group will be needed for future studies.
Frequency Response Analysis of FAU, LTA and MFI Zeolites Using UV-Vis and Electrochemical Impedance Spectroscopy
Authors: Murrieta-Rico Fabian N. , Antúnez-García Joel , Yocupicio-Gaxiola Rosario I. , Reyes Serrato Armando , Petranovskii Vitalii , Xiao Mufei , Sergiyenko Oleg , Flores-Fuentes Wendy , Rodríguez-Quiñonez Julio C.
Published: July 2023

Zeolites are porous materials that have cavities interconnected by channels. These crystalline materials are composed of Si-O tetrahedral structures, and according to the assembly of such tetrahedral structures, specific crystalline structures are obtained. Until now, it has been said that there are more than 245 different zeolitic frameworks, and since each one has a specific distribution of pores and cavities, each kind of zeolite has a specific area-to-volume ratio. As a result of the type of zeolite structure, the zeolite can exhibit specific properties, i.e., electrical or optical. Moreover, the physical properties of zeolites can be modified after the inclusion of another chemical species in their structure or in their voids, which can result in tuning a zeolite for specific applications. In this work, synthetic zeolites of types LTA, FAU and MFI are characterized by a number of methods. In particular, the data from UV-Vis spectroscopy are analyzed, and the effect of crystalline structure on properties such as optical bandgap, refractive index, absorption coefficient, incident photon frequency, and extinction coefficient is studied.
Exosome-Based Drug Delivery: Translation from Bench to Clinic
Authors: Koh Hee Byung , Kim Hyo Jeong , Kang Shin-Wook , Yoo Tae-Hyun
Published: July 2023

Exosome-based drug delivery is emerging as a promising field with the potential to revolutionize therapeutic interventions. Exosomes, which are small extracellular vesicles released by various cell types, have attracted significant attention due to their unique properties and natural ability to transport bioactive molecules. These nano-sized vesicles, ranging in size from 30 to 150 nm, can effectively transport a variety of cargoes, including proteins, nucleic acids, and lipids. Compared to traditional drug delivery systems, exosomes exhibit unique biocompatibility, low immunogenicity, and reduced toxicity. In addition, exosomes can be designed and tailored to improve targeting efficiency, cargo loading capacity, and stability, paving the way for personalized medicine and precision therapy. However, despite the promising potential of exosome-based drug delivery, its clinical application remains challenging due to limitations in exosome isolation and purification, low loading efficiency of therapeutic cargoes, insufficient targeted delivery, and rapid elimination in circulation. This comprehensive review focuses on the transition of exosome-based drug delivery from the bench to clinic, highlighting key aspects, such as exosome structure and biogenesis, cargo loading methods, surface engineering techniques, and clinical applications. It also discusses challenges and prospects in this emerging field.
A Comprehensive Model for Evaluating Titanium Industry Security in China
Authors: Hui Xiangwei , Qi Ming , Wang Wenhao , Yang Sen , Zhang Chengqi
Published: July 2023

Currently, China is the largest consumer of titanium (Ti), yet the development of its Ti industry is limited by numerous factors, such as industrial structure imbalance. This study aimed to evaluate the security of China’s Ti industry from 2010 to 2020, seeking to identify relevant issues and propose policy strategies. Firstly, a comprehensive evaluation system for Ti industry security was established, encompassing aspects of availability, economics, and sustainability. Secondly, the entropy weight technique for order preference by similarity to an ideal solution (TOPSIS) combination method and gray correlation method were employed to assess the safety level of China’s Ti industry chain in each year from 2010 to 2020. Additionally, the coupling degree and sensitivity were used to analyze the dimension layers and index system to determine those that negatively impact the safety level of the Ti industry chain. The analysis results reveal that the economic level exerts a significant influence on the development of the Ti industry. Accordingly, under the same level of change, while considering availability, equal attention should be provided to economic considerations for a well-rounded evaluation of the industry’s safety level.
Valorization of Peanut and Walnut Shells through Utilisation as Biosorbents for the Removal of Textile Dyes from Water
Authors: Lazarova Svetlana , Tonev Radoslav , Dimitrova Sonya , Dimova Galina , Mihailova Irena
Published: July 2023

The present research focuses on the application of peanut and walnut shells, in their natural state, for the removal of methylene blue (MB) from water solutions in batch and dynamic (flow-through) conditions. Under batch conditions, at a 100 mg/L MB concentration of aqueous solution, the optimum dose of the studied biosorbents was determined to be 2.5 g/L, reaching about 95–97% efficiency of MB removal for both materials. Langmuir and Freundlich isotherms were used to model and evaluate the experimental data under different initial concentrations of MB (25 to 100 mg/L). The determined maximum adsorption capacities are 41.50 mg/g for walnut shells and 46.80 mg/g for peanut shells. Under flow-through conditions, breakthrough curves are determined for three sizes of fractions (<0.25 mm, 0.315–0.5 mm, and 0.8–1.6 mm). For peanut shells, the smaller the particle size, the higher the adsorption capacity and the column breakthrough time. For walnut shells, however, the particle size seems to have a more complex influence on the adsorption process parameters, and this phenomenon deserves future investigation. The adsorption capacity for one and the same fraction size of 0.315–0.5 mm and initial MB concentration of 50 mg/L is higher under dynamic flow conditions, i.e., 51 mg/g compared to 20 mg/g for walnut shells and 46 mg/g compared to 17.5 mg/g for peanut shells.
Comparison of Postoperative Serum Biomarkers after Total Hip Arthroplasty through Minimally Invasive versus Conventional Approaches: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Ramadanov Nikolai , Marinova-Kichikova Polina , Hable Robert , Dimitrov Dobromir , Becker Roland
Published: July 2023

Background: An effective way to objectively assess intraoperative tissue damage in total hip arthroplasty (THA) is to determine and compare postoperative serum biomarkers (laboratory parameters) such as creatine kinase (CK), C-reactive protein (CRP), and hemoglobin (Hb). This meta-analysis aims to compare the intraoperative tissue damage in THA through minimally invasive (MI) and conventional approaches (CAs) using postoperative serum biomarkers. Methods: We searched databases for randomized controlled trials (RCTs) comparing MI THA and CA THA. We calculated mean differences (MDs) with 95% confidence intervals (CIs) for continuous outcomes, using the Hartung–Knapp–Sidik–Jonkman method and a common effect/random effects model. Results: A total of 13 RCTs, involving 1186 THA patients, were included in our meta-analysis. In two out of eleven examined outcome parameters, MI THA showed better results than CA THA. In nine out of eleven examined outcome parameters, MI THA showed no significant difference compared to CA THA. MI THA had a 16 mg/L lower CRP value 3 days postoperatively than CA THA (I2 = 66%, p = 0.03, MD = −15.65, 95% CI −30.10 to −1.21). MI THA had a 3 mg/L lower CRP value 4 days postoperatively than CA THA (I2 = 0%, p = 0.98, MD = −3.00, 95% CI −3.27 to −2.74). Conclusions: Overall, there was no significant difference between MI THA and CA THA in terms of postoperative serum biomarkers, with a slight advantage of MI THA in CRP values. These results do not provide sufficient evidence to recommend changing the surgical approach from CA THA to MI THA. Level of evidence I: a systematic review of all relevant randomized controlled trials.
Efficacy of Corticosteroids and Intravenous Immunoglobulins in a Patient with Toxic Epidermal Necrolysis Secondary to Sulfadoxine: A Case Report and Literature Review
Authors: Escolà-Rodríguez Alba , Marcos-Fendian Ángel , Bastida Carla , Gil Lianes Javier , Castro Pedro , Mascaró José Manuel , Soy Muner Dolors
Published: July 2023

Toxic epidermal necrolysis (TEN) is a rare life-threatening mucocutaneous reaction characterized by epidermal detachment. Treatment success relies on early diagnosis, rapid withdrawal of the causative drug and supportive care. However, clinical evidence for therapeutic management and specific treatment is insufficient and controversial. We describe the successful management of a TEN case secondary to sulfadoxine managed in our intensive care unit. The patient presented a generalized exanthema with mucocutaneous detachment affecting 45% of the body surface area, positive Nikolsky sign, perianal enanthema and conjunctival hyperemia. Treatment with intravenous immunoglobulins and corticosteroids was prescribed, as well as calcium folinate to prevent myelotoxicity of the causative drug. In this case, hemodialysis was dismissed due to the low efficiency of this technique in removing the triggering drug. Our case report confirms the efficacy of corticosteroids, IGIV, topical treatment on mucocutaneous lesions and supportive care for the management of TEN secondary to sulfadoxine.
Hydrological Model Performance in the Verde River Basin, Minas Gerais, Brazil
Authors: de Oliveira Conceição de M. M. , Alvarenga Lívia A. , Beskow Samuel , da Cunha Zandra Almeida , Vargas Marcelle Martins , Melo Pâmela A. , Tomasella Javier , Santos Ana Carolina N. , Carvalho Vinicius S. O. , Silva Vinicius Oliveira
Published: July 2023

In hydrological modelling, it is important to consider the uncertainties related to a model’s structures and parameters when different hydrological models are used to represent a system. Therefore, an adequate analysis of daily discharge forecasts that takes into account the performance of hydrological models can assist in identifying the best extreme discharge forecasts. In this context, this study aims to evaluate the performance of three hydrological models—Lavras Simulation of Hydrology (LASH), Variable Infiltration Capacity (VIC), and Distributed Hydrological Model (MHD-INPE) in the Verde River basin. The results demonstrate that LASH and MHD can accurately simulate discharges, thereby establishing them as crucial tools for managing water resources in the study region’s basins. Moreover, these findings could serve as a cornerstone for future studies focusing on food and water security, particularly when examining their connection to climate change scenarios.
Quantifying the Potential Contribution of Submerged Aquatic Vegetation to Coastal Carbon Capture in a Delta System from Field and Landsat 8/9-Operational Land Imager (OLI) Data with Deep Convolutional Neural Network
Authors: Liu Bingqing , Sevick Tom , Jung Hoonshin , Kiskaddon Erin , Carruthers Tim
Published: July 2023

Submerged aquatic vegetation (SAV) are highly efficient at carbon sequestration and, despite their relatively small distribution globally, are recognized as a potentially valuable component of climate change mitigation. However, SAV mapping in tidal marshes presents a challenge due to optically complex constituents in the water. The emergence and advancement of deep learning-based techniques in the field of habitat mapping with remote sensing imagery provides an opportunity to address this challenge. In this study, an analytical framework was developed to quantify the carbon sequestration of SAV habitats in the Atchafalaya River Delta Estuary from field and remote sensing observations using deep convolutional neural network (DCNN) techniques. A U-Net-based model, Wetland-SAV Network, was trained to identify the SAV percent cover (high, medium, and low) as well as other estuarine habitat types from Landsat 8/9-OLI data. The areal extent of SAV was up to 8% of the total area (47,000 ha). The habitat areas and habitat-specific carbon fluxes were then used to quantify the net greenhouse gas (GHG) flux of the study area for with/without SAV scenarios in a carbon balance model. The total net GHG flux was in the range of −0.13 ± 0.06 to −0.86 ± 0.37 × 105 tonne CO2e y−1 and increased up to 40% (−0.23 ± 0.10 to −0.90 ± 0.39 × 105 tonne CO2e y−1) when SAV was accounted for within the calculation. At the hectare scale, the inclusion of SAV resulted in an increase of ~60% for the net GHG sink in shallow areas adjacent to the emergent marsh where SAV was abundant. This is the first attempt at remotely mapping SAV in coastal Louisiana as well as a first quantification of net GHG flux at the scale of hectares to thousands of hectares, accounting for SAV within these sub-tropical coastal delta marshes. Remote sensing and deep learning models have high potential for mapping and monitoring SAV in turbid sub-tropical coastal deltas as a component of the increasing accuracy of net GHG flux estimates at small (hectare) and large (coastal basin) scales.
Separation of (2E,4E)-deca-2,4-dienal from a Biocatalytic Reaction Mixture Using Hydrophobic Adsorbents
Authors: Ostrihoňová Marta , Antošová Monika , Dobiašová Hana , Čuchorová Justína , Vranková Kvetoslava , Polakovič Milan
Published: July 2023

Biocatalytic oxidation of a fatty acid preparation by enzymes released from a plant extract provided (2E,4E)-deca-2,4-dienal (2,4-DDAL), a valuable natural aroma. The post-reaction mixture contained several other compounds, from which 2,4-DDAL must be recovered. These included the main by-product trans-2-hexenal (2-HAL) and the unreacted substrate composed mainly of linoleic, palmitic, and oleic acids. The adsorption capacity and selectivity of 17 hydrophobic adsorbents were examined in batch equilibrium experiments. The highest binding capacity for 2,4-DDAL was around 30 mg/g. Due to a large excess of fatty acids in the mixture, the total adsorbed amounts of other components analyzed reached the values up to 150 mg/g. In addition, 2-HAL was always adsorbed more strongly than 2,4-DDAL, whereas fatty acids were mostly not adsorbed as effectively. The best-performing adsorbent, AmberLite FPX66, had a selectivity ratio of 6 for 2,4-DDAL with respect to the key impurity and linoleic acid. Ethanol, isopropanol, and acetone were examined as potential desorbents using batch adsorption experiments on AmberLite FPX66 from 2,4-DDAL solutions in organic solvents. Ethanol was found to be the best choice. Based on the batch equilibrium data, a column elution experiment was performed to purify 2,4-DDAL from the biocatalytic reaction mixture using elution with 96% ethanol.
Stakeholders’ Roles in the Delivery of Sustainable Housing Projects in Lagos State, Nigeria
Authors: Leo-Olagbaye Feyisetan , Odeyinka Henry , Rathnasiri Pavithra
Published: July 2023

The role stakeholders play is fundamental to the realisation of sustainable development. Consequentially, there is a need for the major stakeholders to be fully aware of their respective roles. Thus, this paper focused on assessing the stakeholders’ roles in sustainable housing projects in Lagos State, Nigeria. A structured questionnaire survey was used to collect data from 259 stakeholders involved in sustainable housing projects in Lagos State, Nigeria. A total of 203 responses were obtained, representing a 78% response rate. Primary data regarding the extent of stakeholders’ awareness of their roles in sustainable housing were collected. The data collected were analysed using mean ranking analysis and analysis of variance (ANOVA). The data collected were used to determine the extent of awareness of the stakeholders’ role in sustainable housing projects in Lagos State, Nigeria. The results showed that all the stakeholders were aware of their respective roles in the delivery of sustainable housing projects and were highly conscious of them. Although their extent of awareness was at varying levels, there was no statistically significant difference of opinions amongst the different categories of stakeholders in the delivery of sustainable housing projects. The study concluded that Government and Project Managers have key roles to play as major stakeholders in the delivery of sustainable housing projects. The knowledge of the awareness of stakeholders’ roles in the delivery of sustainable housing projects provides invaluable information to stakeholders regarding the important roles to focus attention on in achieving sustainable housing projects. The study provides a veritable basis for understanding and aligning stakeholder roles in sustainable housing project delivery.