Gender-affirming vaginoplasty (GAV) comprises the construction of a vulva and a neovaginal canal. Although technical nuances of vulvar construction vary between surgeons, vulvar construction is always performed using the homologous penile and scrotal tissues to construct the corresponding vulvar structures. Therefore, the main differentiating factor across gender-affirming vaginoplasty techniques is the tissue that is utilized to construct the neovaginal canal. These tissue types vary markedly in their availability, histology, and ease of harvest and have different advantages and disadvantages to their use as neovaginal lining. In this narrative review, the authors provide a comprehensive overview of the tissue types and associated operative approaches used for construction of the neovagina in GAV. Tissue choice is guided by several factors, such as histological similarity to natal vaginal mucosa, tissue availability, lubrication potential, additional donor site morbidity, and the specific goals of each patient. Skin is used to construct the neovagina in most cases with a combination of pedicled penile skin flaps and scrotal and extra-genital skin grafts. However, skin alternatives such as peritoneum and intestine are increasing in use. Peritoneum and intestine are emerging as options for primary vaginoplasty in cases of limited genital skin or revision vaginoplasty procedures. The increasing number of gender-affirming vaginoplasty procedures performed and the changing patient demographics from factors such as pubertal suppression have resulted in rapidly evolving indications for the use of these differing vaginoplasty techniques. This review sheds light on the use of less frequently utilized tissue types described for construction of the neovaginal canal, including mucosal tissues such as urethral and buccal mucosa, the tunica vaginalis, and dermal matrix allografts and xenografts. Although the body of evidence for each vaginoplasty technique is growing, there is a need for large prospective comparison studies of outcomes between these techniques and the tissue types used to line the neovaginal canal to better define indications and limitations. Full article

Sustained attention is pivotal for tasks like studying and working for which focus and low distractions are necessary for peak productivity. This study explores the effectiveness of adaptive transcranial direct current stimulation (tDCS) in either the frontal or parietal region to enhance sustained attention. The research involved ten healthy university students performing the Continuous Performance Task-AX (AX-CPT) while receiving either frontal or parietal tDCS. The study comprised three phases. First, we acquired the electroencephalography (EEG) signal to identify the most suitable metrics related to attention states. Among different spectral and complexity metrics computed on 3 s epochs of EEG, the Fuzzy Entropy and Multiscale Sample Entropy Index of frontal channels were selected. Secondly, we assessed how tDCS at a fixed 1.0 mA current affects attentional performance. Finally, a real-time experiment involving continuous metric monitoring allowed personalized dynamic optimization of the current amplitude and stimulation site (frontal or parietal). The findings reveal statistically significant improvements in mean accuracy (94.04 vs. 90.82%) and reaction times (262.93 vs. 302.03 ms) with the adaptive tDCS compared to a non-stimulation condition. Average reaction times were statistically shorter during adaptive stimulation compared to a fixed current amplitude condition (262.93 vs. 283.56 ms), while mean accuracy stayed similar (94.04 vs. 93.36%, improvement not statistically significant). Despite the limited number of subjects, this work points out the promising potential of adaptive tDCS as a tailored treatment for enhancing sustained attention. Full article

Black sexual minority men (BSMM) continue to bear a disproportionate burden of HIV in the United States, with the highest incidence and prevalence in the southern region of the country. In Texas, BSMM living with HIV (BSMM+) have the lowest rates of viral suppression of all SMM and have lower antiretroviral treatment (ART) adherence than white and Hispanic SMM. Long-acting injectable ART (LAI-ART) can potentially overcome several barriers to daily oral ART adherence (e.g., stigma, forgetfulness, pill fatigue). However, little is known about the knowledge, willingness, barriers, and facilitators regarding LAI-ART among BSMM+. From July 2022 to September 2023, we conducted in-depth, semi-structured interviews with 27 BSMM+ from the Houston and Dallas Metropolitan Areas, Texas. Data were analyzed using a thematic analysis approach. Most men knew about LAI-ART, but their understanding varied based on their existing sources of information. Some men were enthusiastic, some were cautious, and some reported no interest in LAI-ART. Barriers to LAI-ART included a lack of public insurance coverage of LAI-ART; fear of needles and side effects; the frequency of injection visits; the requirement of viral suppression before switching from oral ART to LAI-ART; and satisfaction with oral daily ART. Motivators of LAI-ART uptake included the eliminated burden of daily pills and reduced anxiety about possibly missing doses. BSMM+ may be among those who could most benefit from LAI-ART, though more research is needed to understand which factors influence their willingness and how the barriers to LAI-ART might be addressed, particularly among diverse communities of SMM of color. Full article

The current business climate has generated considerable uncertainty and disrupted supply chain processes. Suppliers have frequently been identified as the primary source of hazards responsible for supply chain disruptions. Using a strategic approach to supplier selection that prioritizes providers with resilience features, mitigating the risk exposure inherent in supply chains is possible. This study proposes a comprehensive gray multiple-criteria decision making (MCDM) method incorporating resilience attributes to supplier selection. To determine criteria weights, the gray PSI and gray BWM methodologies were used, and to evaluate and prioritize resilient providers, the gray MCRAT and gray COBRA methodologies were applied. According to the results obtained by the suggested methodology, the supplier that demonstrated the greatest degree of resilience was determined to be the provider categorized as SPIR 4. The sequential sequence of the SPIR numbers is as follows: SPIR 5, SPIR 1, SPIR 3, SPIR 2, and SPIR 6. The data demonstrate that the developed approach produced accurate results. Full article

At present, low-speed high-torque permanent magnet motors are widely used in the sampling industry, manufacturing industry and energy industry. However, the research on low-speed high-torque permanent magnet motors is far from enough. The primary difficulty in the initial design of low-speed high-torque permanent magnet motors is the selection of pole–slot ratio. The pole–slot ratio has a great influence on the electromagnetic performance such as torque ripple and the maximum output torque of low-speed motors. Choosing the appropriate pole–slot ratio scheme can make the design of a low-speed motor more efficient. In addition, the optimization design of the motor is also a necessary process. At present, there are many studies on optimization algorithms. However, the research on sample point sampling and surrogate model fitting is not enough. Choosing the appropriate sample point sampling method and surrogate model fitting method can help one obtain a more accurate surrogate model, which lays a foundation for the optimization of the motor. Based on the above analysis, this paper first selects four representative pole–slot ratio schemes for comprehensive comparison of their electromagnetic performances. Secondly, two sample point sampling methods and three surrogate model fitting methods are combined to obtain six surrogate models, and the accuracy of the six surrogate models is compared and analyzed. Finally, a 37kW,160rpm prototype is made, and the comparison of the surrogate model optimization prediction results, the finite element simulation calculation results and the measured results is carried out to further prove the accuracy of the selected surrogate model. The work performed in this paper provides a certain reference value for the initial design and optimization experiment design of low-speed high-torque permanent magnet motor. Full article

As a key guarantee and cornerstone of building quality, the importance of deformation prediction for deep foundation pits cannot be ignored. However, the deformation data of deep foundation pits have the characteristics of nonlinearity and instability, which will increase the difficulty of deformation prediction. In response to this characteristic and the difficulty of traditional deformation prediction methods to excavate the correlation between data of different time spans, the advantages of variational mode decomposition (VMD) in processing non-stationary series and a gated cycle unit (GRU) in processing complex time series data are considered. A predictive model combining particle swarm optimization (PSO), variational mode decomposition, and a gated cyclic unit is proposed. Firstly, the VMD optimized by the PSO algorithm was used to decompose the original data and obtain the Internet Message Format (IMF). Secondly, the GRU model optimized by PSO was used to predict each IMF. Finally, the predicted value of each component was summed with equal weight to obtain the final predicted value. The case study results show that the average absolute errors of the PSO-GRU prediction model on the original sequence, EMD decomposition, and VMD decomposition data are 0.502 mm, 0.462 mm, and 0.127 mm, respectively. Compared with the prediction mean square errors of the LSTM, GRU, and PSO-LSTM prediction models, the PSO-GRU on the PTB0 data of VMD decomposition decreased by 62.76%, 75.99%, and 53.14%, respectively. The PTB04 data decreased by 70%, 85.17%, and 69.36%, respectively. In addition, compared to the PSO-LSTM model, it decreased by 8.57% in terms of the model time. When the prediction step size increased from three stages to five stages, the mean errors of the four prediction models on the original data, EMD decomposed data, and VMD decomposed data increased by 28.17%, 3.44%, and 14.24%, respectively. The data decomposed by VMD are more conducive to model prediction and can effectively improve the accuracy of model prediction. An increase in the prediction step size will reduce the accuracy of the deformation prediction. The PSO-VMD-GRU model constructed has the advantages of reliable accuracy and a wide application range, and can effectively guide the construction of foundation pit engineering. Full article

Erythritol is a polyol with a sweet taste but low energy value. Thanks to its valuable properties, as well as growing social awareness and nutritional trends, its popularity is growing rapidly. The aim of this study was to increase the effectiveness of erythritol production from glucose using new UV mutants of the yeast Yarrowia lipolytica obtained in the Wratislavia K1 strain. The ability of the new strains to biosynthesize erythritol and utilize this polyol was examined in shake-flask cultures and fed-batch processes conducted in a stirred tank reactor with a total glucose concentration of 300 and 400 g/L. The Wratislavia K1 strain produced erythritol most efficiently (97.5 g/L; 192 h) at an initial glucose concentration of 250 g/L (total: 300 g/L). New strains were assessed under such conditions, and it was noted that the highest erythritol concentration (145 g/L; 183 h) was produced by the K1UV15 strain. A significant improvement in the erythritol biosynthesis efficiency (148 g/L; 150 h) was achieved upon the increase in (NH₄)₂SO₄ to 3.6 g/L. Further, in the culture with such a concentration of the nitrogen source and increased total glucose level (400 g/L), the K1UV15 strain produced 226 g/L of erythritol within 281 h. Full article

The fast development of China’s urbanization has led to a notable release of emerging pollutants, including microplastics (MPs) and endocrine disruptors (EDCs). Generally, these pollutants enter the coastal environment through the discharge of wastewater treatment plants (WWTPs) and finally threaten the organisms in the receiving waterbody. The study investigated the environmental behavior of MPs and EDCs in two typical WWTPs in one of the megacities in China, Shanghai. The abundance of MPs in the influent ranged from 321 to 976 items/L. Four shapes (films, fragments, fibers, and microbead) were found, while fibers and films dominated. Transparent (31–63%) and white (20–47%) MPs were more frequently observed, while polyethylene terephthalate, cellulose, and cellophane were the main polymetric materials. The size of the MPs fell between 15.8 μm and 2220 μm, and the smaller one (<500 μm) dominated. The removal efficiencies of the two WWTPs for MPs ranged from 64% to 92%, and both WWTPs performed better for large pieces of MPs (>500 μm). For EDCs, total concentrations in the influent were detected, ranging from 113 to 2780 ng/L. Two groups, including phenolic estrogens (PEs) and steroid estrogens (SEs), were detected, and PEs, especially bisphenol A (BPA), were the predominant individuals among the studied EDCs. Specifically, PEs ranged from 82.8 to 2637 ng/L, while SEs ranged from 27.3 to 143 ng/L. The removal efficiencies of the WWTPs for EDCs varied (82.8–100%) as well, possibly due to the different treatment compartments and contamination load in the influent. Seasonal variations for both MPs and EDCs were observed. Specifically, concentrations of MPs and EDCs in WWTPs influent were higher in the wet season, as well as the removal efficiency. Furthermore, there was a correlation observed between the concentrations of MPs and EDCs, suggesting that MPs and EDCs may originate from the same source and that EDCs released by MPs cannot be ignored during treatment. Finally, the study evaluated the environmental risk of the effluents. MPs led to a minor risk (Level I), while EDCs might lead to an adverse impact on algae (RQs = 0.0014–0.024) and fish (RQs = 3.4–30.2). In summary, WWTPs received considerable amounts of MPs and EDCs. Although the WWTPs removed the contaminants efficiently, the environmental risk of the effluent needs to be noted. Full article

This study aimed to compare the chemical composition of aqueous extracts from different aerial plant parts (leaves, stems, and flowers) of Onopordum nervosum ssp. platylepis growing in different regions (Sousse, Kairouan, and Nabeul) in Tunisia, as well as their antioxidant and milk-clotting properties for both spontaneously grown and cultivated plants. Results showed that phenolic composition varies significantly among ecotypes and plant organs (p < 0.05), with flowers containing the highest amounts of total phenols and flavonoids in both plant types. The flowers from Nabeul (NA) region showed the highest amounts of total phenols and higher phenolic contents compared to leaves and stems, with 44.75 mg GAE/g and 39.79 mg GAE/g in spontaneous and cultivated plants, respectively. However, flowers of spontaneously plants grown in Sousse (SO) showed the highest total flavonoid contents (11.42 mg QE/g). Additionally, the findings indicated that flowers contained higher concentrations of mono- and disaccharides than leaves and stems. The antioxidant activity showed that the radical scavenging activity of O. platylepis aqueous extracts is significantly affected by the organ and genotype (p < 0.05). NA genotype revealed the highest potency in inhibiting free radicals, with flowers having the lowest IC50s values in 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) tests, registering 0.13 ± 0.02 and 0.14 ± 0.01 mg/mL, respectively. Milk-clotting activity was limited to flowers of this thistle. Moreover, SO and NA genotypes were identified as the most potent populations to coagulate milk in spontaneous and cultivated plants. The principal component analysis confirms the organ and genotype variability in this thistle, with the first two axes explaining 64.15% of the variance and highlighting a distinct flower group. The obtained results suggest that the domestication of this thistle could be useful for the conservation of biodiversity and the promotion of genotypes with potential technological properties. Full article

Background and Purpose: Early differentiation between acute ischaemic (AIS) and haemorrhagic stroke (ICH), based on cerebral and peripheral hemodynamic parameters, would be advantageous to allow for pre-hospital interventions. In this preliminary study, we explored the potential of multiple parameters, including dynamic cerebral autoregulation, for phenotyping and differentiating each stroke sub-type. Methods: Eighty patients were included with clinical stroke syndromes confirmed by computed tomography within 48 h of symptom onset. Continuous recordings of bilateral cerebral blood velocity (transcranial Doppler ultrasound), end-tidal CO₂ (capnography), electrocardiogram (ECG), and arterial blood pressure (ABP, Finometer) were used to derive 67 cerebral and peripheral parameters. Results: A total of 68 patients with AIS (mean age 66.8 ± SD 12.4 years) and 12 patients with ICH (67.8 ± 16.2 years) were included. The median ± SD NIHSS of the cohort was 5 ± 4.6. Statistically significant differences between AIS and ICH were observed for (i) an autoregulation index (ARI) that was higher in the unaffected hemisphere (UH) for ICH compared to AIS (5.9 ± 1.7 vs. 4.9 ± 1.8 p = 0.07); (ii) coherence function for both hemispheres in different frequency bands (AH, p < 0.01; UH p < 0.02); (iii) a baroreceptor sensitivity (BRS) for the low-frequency (LF) bands that was higher for AIS (6.7 ± 4.2 vs. 4.10 ± 2.13 ms/mmHg, p = 0.04) compared to ICH, and that the mean gain of the BRS in the LF range was higher in the AIS than in the ICH (5.8 ± 5.3 vs. 2.7 ± 1.8 ms/mmHg, p = 0.0005); (iv) Systolic and diastolic velocities of the affected hemisphere (AH) that were significantly higher in ICH than in AIS (82.5 ± 28.09 vs. 61.9 ± 18.9 cm/s), systolic velocity (p = 0.002), and diastolic velocity (p = 0.05). Conclusion: Further multivariate modelling might improve the ability of multiple parameters to discriminate between AIS and ICH and warrants future prospective studies of ultra-early classification (<4 h post symptom onset) of stroke sub-types. Full article

The crack resistance of concrete structures with low reinforcement ratios requires a broader examination. It is particularly important in the case of foundations working in changing subsoil conditions. Unfavorable phenomena occurring in the subsoil (e.g., ground subsidence, landslips, non-uniform settlement) can lead to unexpected cracking. Therefore, it is necessary to check the effectiveness of the low reinforcement provided. As there are limited studies on lightly reinforced concrete structures, we performed our own experimental investigation and numerical calculations. In the beams analyzed, the reinforcement ratio varied from 0.05% to 0.20%. It was found that crack resistance in concrete members depends on the reinforcement ratio and steel bar distribution. A comprehensive method was proposed for estimating the crack resistance of lightly reinforced concrete members in which both the reinforcement ratio and the reinforcement dispersion ratio were taken into account. Furthermore, the method considered the size effect and the fracture properties of concrete. The proposed method provides the basis for extrapolation of the test results obtained for small elements and conclusions for members with large cross-sections, such as foundations, which frequently use lightly reinforced concrete. Full article

Large-scale crop phenology monitoring is critical for agronomic planning and yield prediction applications. Synthetic Aperture Radar (SAR) remote sensing is well-suited for crop growth monitoring due to its nearly all-weather observation capability. Yet, the capability of the dual-polarimetric SAR data for wheat phenology estimation has not been thoroughly investigated. Here, we conducted a comprehensive evaluation of Sentinel-1 SAR polarimetric parameters’ sensibilities on winter wheat’s key phenophases while considering the incidence angle. We extracted 12 polarimetric parameters based on the covariance matrix and a dual-pol-version H-α decomposition. All parameters were evaluated by their temporal profile and feature importance score of Gini impurity with a decremental random forest classification process. A final wheat phenology classification model was built using the best indicator combination. The result shows that the Normalized Shannon Entropy (NSE), Degree of Linear Polarization (DoLP), and Stokes Parameter g2 were the three most important indicators, while the Span, Average Alpha ($\overline{{\alpha }_2})$, and Backscatter Coefficient ${\sigma }_{VH}^0$ were the three least important features in discriminating wheat phenology for all three incidence angle groups. The smaller-incidence angle (30–35°) SAR images are better suited for estimating wheat phenology. The combination of NSE, DoLP, and two Stokes Parameters (g2 and g0) constitutes the most effective indicator ensemble. For all eight key phenophases, the average Precision and Recall scores were above 0.8. This study highlighted the potential of dual-polarimetric SAR data for wheat phenology estimation. The feature importance evaluation results provide a reference for future phenology estimation studies using dual-polarimetric SAR data in choosing better-informed indicators. Full article

Pedro I of Castile (1350–1369) founded a royal chapel in the Christianised Mosque of Seville. He intended to house there his body, that of Queen María de Padilla, and their son the Infant Alfonso (1359–1362). This mausoleum is well documented both in the king’s will and in the chronicles of López de Ayala; however, there are no material remains as it was demolished with the construction of the new cathedral in the 15th century. In this article, we seek to produce a state of the art history of the building, a compilation of all the documentary sources that exist for its analysis, and an approach to the problems that hinder its study. We have also tried, unsuccessfully, to put forward a hypothesis about its original location, but we have come up against a dead end. Despite this, we consider it essential to lay all the cards on the table and prevent the mausoleum from falling into oblivion. Full article

This study aims to investigate the effects of different hydroxy-terminated silicones on the properties of polycarbonate-silicone copolymers (ICS-PC) by introducing flexible and hydrophobic silicone into isosorbide-based polycarbonate through melt transesterification- polycondensation method. Through compatibility and transesterification experiments, it is confirmed that the alcohol-hydroxyl polydimethylsiloxane (a-PDMS) has higher reactivity and silicone conversion than the phenol-hydroxyl polydimethylsiloxane (p-PDMS), but the conversion does not exceed 81%. Polyether-modified silicone (PEMS) exhibits better compatibility and higher reactivity, thus resulting in higher conversion that can reach 86%. Effects of the type and content of silicone on the glass transition temperature (T_g), optical transparency, saturated water absorption, and mechanical strength of ICS-PCs were also discussed. It is found that p-PDMS has higher T_g, hydrophobicity, and mechanical strength with similar silicone content, but the total transmittance does not exceed 60%. In contrast, the PEMS system exhibits better optical transparency due to its improved compatibility with the PC matrix, with a total transmittance of up to 73%, T_g exceeding 150 °C while maintaining excellent flexibility and hydrophobicity. These results are helpful to further improve the comprehensive properties of bio-based polycarbonates. Full article

Binary transition metal oxide complexes (BTMOCs) in three-dimensional (3D) layered structures show great promise as electrodes for supercapacitors (SCs) due to their diverse oxidation states, which contribute to high specific capacitance. However, the synthesis of BTMOCs with 3D structures remains challenging yet crucial for their application. In this study, we present a novel approach utilizing a single-step hydrothermal technique to fabricate flower-shaped microspheres composed of a NiCo-based complex. Each microsphere consists of nanosheets with a mesoporous structure, enhancing the specific surface area to 23.66 m² g⁻¹ and facilitating efficient redox reactions. When employed as the working electrode for supercapacitors, the composite exhibits remarkable specific capacitance, achieving 888.8 F g⁻¹ at 1 A g⁻¹. Furthermore, it demonstrates notable electrochemical stability, retaining 52.08% capacitance after 10,000 cycles, and offers a high-power density of 225 W·kg⁻¹, along with an energy density of 25 Wh·kg⁻¹, showcasing its potential for energy storage applications. Additionally, an aqueous asymmetric supercapacitor (ASC) was assembled using NiCo microspheres-based complex and activated carbon (AC). Remarkably, the NiCo microspheres complex/AC configuration delivers a high specific capacitance of 250 F g⁻¹ at 1 A g⁻¹, with a high energy density of 88 Wh kg⁻¹, for a power density of 800 W kg⁻¹. The ASC also exhibits excellent long-term cyclability with 69% retention over 10,000 charge–discharge cycles. Furthermore, a series of two ASC devices demonstrated the capability to power commercial blue LEDs for a duration of at least 40 s. The simplicity of the synthesis process and the exceptional performance exhibited by the developed electrode materials hold considerable promise for applications in energy storage. Full article

The aim of this research was to determine the minimal requirements for shear reinforcement for reactive powder concrete (RPC) rectangular cross-sectional beams with a compressive strength of 157 MPa and a steel fiber volume content of 2.0% that remained constant for all the tested beams. Additionally, the recommendations of KCI-2012 and AFGC-2013 for the design of RPC beams as well as the shear design requirements of ACI 314-2014 when applied to RPC beams were studied. Utilizing a three-dimensional finite element program, a computational model was designed for forecasting the deformations and shear strength of the examined RPC beams. Both the shear-span-to-depth relationship (a/d) and the minimal reinforcement web ratio, represented by the distance between stirrups and the diameter of the stirrup bars, are the key study parameters in this regard. According to this study’s experimental findings, increasing the given reinforcement of the web ratio has little influence on both the ultimate shear strength as well as the diagonal cracking strength of the beams. Additionally, the findings demonstrated that the ACI 318-2014 maximum stirrup spacing requirement of 0.5 d can safely be extended to 0.75 d for beams that are relatively short. Compared to what ACI 318-2014 mandates, the suggestions of AFGC-2013 and KCI-2012 are more cautious and safe. According to the AFGC-2013 criteria, the mean proportion of V_fb to projected V_u,AFGC is roughly 58.3%, whereas the mean proportion of vs. and V_c is just 41.7%. The deformation response and ultimate shear strength of the examined RPC beams were well predicted by the designed model using finite elements when metal fibers were taken into account. Full article

Various complex defects can occur on the surfaces of small automobile parts during manufacturing. Compared with other datasets, the auto parts defect dataset used in this paper has low detection accuracy due to various defects with large size differences, and traditional target detection algorithms have been proven to be ineffective, which often leads to missing detection or wrong identification. To address these issues, this paper introduces a defect detection algorithm based on YOLOv7. To enhance the detection of small objects and streamline the model, we incorporate the ECA attention mechanism into the network structure’s backbone. Considering the small sizes of defect targets on automotive parts and the complexity of their backgrounds, we redesign the neck portion of the model. This redesign includes the integration of the BiFPN feature fusion module to enhance feature fusion, with the aim of minimizing missed detections and false alarms. Additionally, we employ the Alpha-IoU loss function in the prediction phase to enhance the model’s accuracy, which is crucial for reducing false detection. The IoU loss function also boosts the model’s efficiency at converging. The evaluation of this model utilized the Northeastern University steel dataset and a proprietary dataset and demonstrated that the average accuracy (mAP) of the MBEA-YOLOv7 detection network was 76.2% and 94.1%, respectively. These figures represent improvements of 5.7% and 4.7% over the original YOLOv7 network. Moreover, the detection speed for individual images ranges between 1–2 ms. This enhancement in detection accuracy for small targets does not compromise detection speed, fulfilling the requirements for real-time, dynamic inspection of defects. Full article

For technical application with continuous operation of sorption-enhanced (SE) reactions, e.g., Fischer–Tropsch, a special reactor concept is required. SE processes are promising due to the negative effects of water on conversion and catalyst. The reactor concept of two interconnected slurry bubble columns combines the reaction with in situ water removal in the first, and sorbent regeneration in the second column with continuous exchange of slurry between the two. The liquid circulation rate (LCR) between the columns is studied in a cold flow model, measured by an ultrasonic sensor. The effects of different operating and geometric parameters, e.g., superficial gas velocity, liquid level and tube diameter on gas holdup and LCR are discussed and modelled via artificial intelligence methods, i.e., extremely randomized trees and neural networks. It was found that the LCR strongly depends on the gas holdup. The maximum of 4.28 L min⁻¹ was reached with the highest exit, widest tube and highest superficial gas velocity of 0.15 m s⁻¹. The influence of liquid level above the exit was marginal but water quality has to be considered. Both models offer predictions of the LCR with errors < 6%. With an extension of the models, particle circulation can be studied in the future. Full article

Summarizing source code by natural language aims to help developers better understand existing code, making software development more efficient. Since source code is highly structured, recent research uses code structure information like Abstract Semantic Tree (AST) to enhance the structure understanding rather than a normal translation task. However, AST can only represent the syntactic relationship of code snippets, which can not reflect high-level relationships like control and data dependency in the program dependency graph. Moreover, researchers treat the AST as the unique structure information of one code snippet corresponding to one summarization. It will be easily affected by simple perturbations as it lacks the understanding of code with similar structure. To handle the above problems, we build CogCol, a Code graph-based Contrastive learning model. CogCol is a Transformer-based model that converts code graphs into unique sequences to enhance the model’s structure learning. In detail, CogCol uses supervised contrastive learning by building several kinds of code graphs as positive samples to enhance the structural representation of code snippets and generalizability. Moreover, experiments on the widely used open-source dataset show that CogCol can significantly improve the state-of-the-art code summarization models under Meteor, BLEU, and ROUGE. Full article

With the world’s population continuing to grow, ensuring sustainable protein sources for everyone is becoming increasingly challenging. Despite meat being considered unsustainable, people find it challenging to abstain from consuming it. However, one solution to this dilemma could be the incorporation of mealworms into conventional meat products, i.e., sausages. The incorporation of mealworms into sausage formulations appears to shift the fatty acid profile towards higher levels of monounsaturated fats and polyunsaturated fatty acids (PUFAs), particularly omega-3s, potentially enhancing the nutritional value and offering health benefits. Therefore, our study aimed to improve the nutritional value and safety parameters of traditional sausages by enriching them with the flour of mealworm larvae. For this purpose, the larvae were reared on a sustainable substrate with brewery by-products, brewer’s yeast, and carrots. They were used frozen and freeze-dried in sausage recipes, replacing pork in different proportions. The analysis of the product’s chemical safety parameters (biogenic amines, nitrates and nitrites, volatile fatty acids (FA), and peroxide) and nutritional value (including collagen, cholesterol, amino acids, FA, and hydroxyproline) was carried out in an accredited laboratory. The results of our study have demonstrated that the incorporation of mealworms into sausages, particularly through freeze-drying, increased fat content and enhanced the profile of FA, including omega-3s while reducing protein and cholesterol levels, and altering collagen content, suggesting improved nutritional value and potential health benefits without compromising the safety of the product. Therefore, we are highlighting that the addition of mealworms influences the quality of amino acids positively and maintains biogenic amine levels within safe limits, alongside a negligible impact on nitrates and nitrites and a reduction in peroxide values. These findings indicate an overall improvement in sausage quality and safety without compromising safety. Full article

Aim: This study systematically explored the biological effects and mechanisms of PGC on gastric cancer (GC) cells in vitro and in vivo. Method: The critical biological roles of PGC in GC were assessed via EdU staining, Hoechst staining, flow cytometry, mouse models, CCK-8, wound healing, transwell, and sphere-forming assays. The interaction study with IQ-domain GTPase-activating protein 1 (IQGAP1) was used by Liquid chromatography-mass spectrometry co-immunoprecipitation, immunofluorescence staining, CHX-chase assay, MG132 assay, and qRT-PCR. Results: PGC inhibited the proliferation, viability, epithelial–mesenchymal transition, migration, invasion, and stemness of GC cells and promoted GC cell differentiation. PGC suppressed subcutaneous tumor growth and peritoneal dissemination in vivo. The interaction study found PGC inhibits GC cell migration and invasion by downregulating IQGAP1 protein and IQGAP1-mediated Rho-GTPase signaling suppression. In addition, PGC disrupts the stability of the IQGAP1 protein, promoting its degradation and significantly shortening its half-life. Moreover, the expression levels of PGC and IQGAP1 in GC tissues were significantly negatively correlated. Conclusion: PGC may act as a tumor suppressor in the development and metastasis of GC. PGC can downregulate its interacting protein IQGAP1 and inhibit the Rho-GTPase pathway, thereby participating in the inhibition of GC cell migration and invasion. Full article