As a consequence of climate change, temperature and rainfall regimes are being modified, threatening the survival of the current gardening concept in many areas of the world. This situation highlights the need to investigate the potential of other species, especially in more sensitive areas such as the Mediterranean Basin. The aim of this research is to study the resilience of adapted species to promote sustainable gardening. To achieve this, seven species belonging to three families (Amaranthaceae, Lamiaceae and Asteraceae) used or potentially used as ornamentals were selected to compare their tolerance at the germinative stage to different levels of temperature (10 °C to 35 °C) and water stress created by PEG 6000 (−0.10 MPa to −2.5 MPa). Germination percentage, mean germination time, base temperature, thermal time, base water potential and hydrotime were calculated. The results showed a good response to high temperature and low osmotic potential in most of the species, and germination even increased under certain stress levels. Salsola oppositifolia presented by far the best results in terms of germination under high-water-stress conditions and the second best at high temperatures. The extraordinary response of Celosia argentea, an alien species, highlighted the risk of it becoming an invasive species. Full article

The study of pear dormancy mechanisms is currently a major research area in pear production and has high economic significance for agricultural production. We selected the southern sand pear cultivar Pyrus pyrifolia ‘Huanghua’ as the test material to study the pear dormancy process through microscopic observation of pear flower buds. The endodormancy period is abbreviated as D_bud. Similarly, the endodormancy release initiation period and the ecodormancy period are referred to as DB_bud and G_bud, respectively. Meanwhile, RNA sequencing was used to obtain the gene expression profile of Pyrus pyrifolia ‘Huanghua’ flower buds. The RNA sequencing results indicated that there were 224 differentially expressed genes (DEGs) in endodormancy (D) vs. endodormancy release initiation period (DB), while 975 were identified between endodormancy and ecodormancy (G). Finally, a total of 868 DEGs were found in the DB vs. G comparison. The expression levels of the genes Pbr009498.1 (LAX1-1), Pbr012348.1 (LAX1-2), Pbr021158.1 (GH35), and Pbr031621.1 (LAX2) encoding IAA were significantly higher during the DB_bud than during the D_bud. The expression level of Pbr025864.2 (IAA13) during the D_bud was significantly higher than the DB_bud and G_bud. The Pbr041942.1 (GID1B) gene also showed a significant increase during ecodormancy. Taken together, these results suggest that these genes, annotated as LAX1, GH35, LAX2, IAA13, and GID1C, are involved in endodormancy maintenance and in the transition from endodormancy to ecodormancy in Pyrus pyrifolia ‘Huanghua’. Full article

Climate change exacerbates drought, globally impacting crop production and necessitating the adoption of sustainable strategies. This study investigates the potential synergistic effects of salicylic acid (SA) and Bacillus butanolivorans KJ40 (KJ40) on napa cabbage (Brassica rapa subsp. pekinensis) under water-deficit stress conditions by watering withheld for five days. Results demonstrate that the combined application of KJ40 and SA, particularly at concentrations of 0.5 mM and 1 mM, significantly enhances plant growth and mitigates the negative impacts of water deficit. Moreover, the combination treatment with SA (0.5 mM) and KJ40 (1 × 10⁸ cells/mL) reduces lipid oxidation and enhances antioxidant enzyme activity, indicating improved plant stress tolerance. Analysis of soil microbial profiles reveals alterations in metabolic activity and substrate utilization patterns, suggesting potential changes in rhizosphere dynamics. Additionally, this study examines the impact of SA on KJ40 population dynamics in soil, revealing concentration-dependent effects on bacterial survival. Overall, the combination of KJ40 and SA was effective in mitigating water-deficit stress in napa cabbage. These findings highlight the combination as a novel synergistic strategy to enhance plant resilience to water-deficit stress, offering insights into plant–microbe interactions and soil ecosystem dynamics. Full article

Floral scent is an essential and genetically complex trait in herbaceous peonies (Paeonia lactiflora Pall.); however, specific genes related to metabolic and regulatory networks remain scantily studied. Our study integrated metabolite profiling and RNA-sequencing to screen floral scent biosynthetic genes. Hence, the major molecules identified by headspace collection combined with cultivar-specific GC-MS analysis were geraniol, β-caryophyllene, 2-phenylethanol (2-PE), citronellol, and 1,8-cineole. Genes related to terpenoids and 2-PE biosynthesis were identified after the assembly and annotation of the P. lactiflora transcriptomes. Eight angiosperm-specific terpene synthases (TPSs) from the TPS-a and TPS-b clades, as well as enzymes linked to 2-PE synthesis such as aromatic amino acid decarboxylase (AADC), phenylacetaldehyde reductase (PAR), and geranial reductase (GER) were identified. The biochemical analysis of the enzymes encoded by PlPAR1 and PlGER1 generated 2-PE from phenylacetaldehyde (PAld). The pairwise alignment of AADC1 reveals a splice variant lacking a 124 bp fragment, thus highlighting the possible role of alternative splicing in modulating floral scent composition. This study offers insights into the molecular-level biosynthesis of terpenoids and 2-PE in Peonia taxa, and provides the basis for the functional characterization, breeding, and bioengineering of prospective candidate genes for the production of floral volatiles in the Paeonia genus. Full article

Due to the high respiration rate and ethylene production at the cut surface of bamboo (Dendrocalamus latifloxus Munro) shoots after harvesting, browning and lignification at the cut surface reduce their quality and shelf life. Due to the demand of consumers, using physical treatment to inhibit microbial growth and maintain quality has become more and more popular. In this study, bamboo shoots were treated with hot water at 70 °C for 30 s after harvesting and then stored at 1, 3, or 5 °C for 4 weeks to measure the quality change. Our results show that the L* value and h° angle at the cut surface of the bamboo shoots were significantly higher, but the respiration rate was significantly lower when stored at 1 °C compared with those at 3 and 5 °C. In terms of quality, the bamboo shoots showed lower firmness and cutting force values, and no decay was observed at 1 °C. The results from the shelf simulation test with rewarming of the cold-treated bamboo shoots at ambient temperature (25 °C) for 1 day indicated that the L* value and h° angle were significantly higher for the bamboo shoots stored at 1 °C compared with those stored at 3 and 5 °C. Taken together, browning and lignification at the cut surface were effectively inhibited, quality was maintained, and the storage life could be extended to 4 weeks at 1 °C. Full article

Scaffold-guided breast tissue regeneration (SGBTR) can transform both reconstructive and cosmetic breast surgery. Implant-based surgery is the most common method. However, there are inherent limitations, as it involves replacement of tissue rather than regeneration. Regenerating autologous soft tissue has the potential to provide a more like-for-like reconstruction with minimal morbidity. Our SGBTR approach regenerates soft tissue by implanting additively manufactured bioresorbable scaffolds filled with autologous fat graft. A pre-clinical large animal study was conducted by implanting 100 mL breast scaffolds (n = 55) made from medical-grade polycaprolactone into 11 minipigs for 12 months. Various treatment groups were investigated where immediate or delayed autologous fat graft, as well as platelet rich plasma, were added to the scaffolds. Computed tomography and magnetic resonance imaging were performed on explanted scaffolds to determine the volume and distribution of the regenerated tissue. Histological analysis was performed to confirm the tissue type. At 12 months, we were able to regenerate and sustain a mean soft tissue volume of 60.9 ± 4.5 mL (95% CI) across all treatment groups. There was no evidence of capsule formation. There were no immediate or long-term post-operative complications. In conclusion, we were able to regenerate clinically relevant soft tissue volumes utilizing SGBTR in a pre-clinical large animal model. Full article

Bone drilling is a common procedure used to create pilot holes for inserting screws to secure implants for fracture fixation. However, this process can increase bone temperature and the excessive heat can lead to cell death and thermal osteonecrosis, potentially causing early fixation failure or complications. We applied a three-dimensional dynamic elastoplastic finite element model to evaluate the propagation and distribution of heat during bone drilling and assess the thermally affected zone (TAZ) that may lead to thermal necrosis. This model investigates the parameters influencing bone temperature during bone drilling, including drill diameter, rotational speed, feed force, and predrilled hole. The results indicate that our FE model is sufficiently accurate in predicting the temperature rise effect during bone drilling. The maximum temperature decreases exponentially with radial distance. When the feed forces are 40 and 60 N, the maximum temperature does not exceed 45 °C. However, with feed forces of 10 and 20 N, both the maximum temperatures exceed 45 °C within a radial distance of 0.2 mm, indicating a high-risk zone for potential thermal osteonecrosis. With the two-stage drilling procedure, where a 2.5 mm pilot hole is predrilled, the maximum temperature can be reduced by 14 °C. This suggests that higher feed force and rotational speed and/or using a two-stage drilling process could mitigate bone temperature elevation and reduce the risk of thermal osteonecrosis during bone drilling. Full article

Degenerative disc disease (DDD) is a pervasive condition that limits quality of life and burdens economies worldwide. Conventional pharmacological treatments primarily aimed at slowing the progression of degeneration have demonstrated limited long-term efficacy and often do not address the underlying causes of the disease. On the other hand, orthobiologics are regenerative agents derived from the patient’s own tissue and represent a promising emerging therapy for degenerative disc disease. This review comprehensively outlines the pathophysiology of DDD, highlighting the inadequacies of existing pharmacological therapies and detailing the potential of orthobiologic approaches. It explores advanced tools such as platelet-rich plasma and mesenchymal stem cells, providing a historical overview of their development within regenerative medicine, from foundational in vitro studies to preclinical animal models. Moreover, the manuscript delves into clinical trials that assess the effectiveness of these therapies in managing DDD. While the current clinical evidence is promising, it remains insufficient for routine clinical adoption due to limitations in study designs. The review emphasizes the need for further research to optimize these therapies for consistent and effective clinical outcomes, potentially revolutionizing the management of DDD and offering renewed hope for patients. Full article

Nonsense mutations are genetic mutations that create premature termination codons (PTCs), leading to truncated, defective proteins in diseases such as cystic fibrosis, neurofibromatosis type 1, Dravet syndrome, Hurler syndrome, Beta thalassemia, inherited bone marrow failure syndromes, Duchenne muscular dystrophy, and even cancer. These mutations can also trigger a cellular surveillance mechanism known as nonsense-mediated mRNA decay (NMD) that degrades the PTC-containing mRNA. The activation of NMD can attenuate the consequences of truncated, defective, and potentially toxic proteins in the cell. Since approximately 20% of all single-point mutations are disease-causing nonsense mutations, it is not surprising that this field has received significant attention, resulting in a remarkable advancement in recent years. In fact, since our last review on this topic, new examples of nonsense suppression approaches have been reported, namely new ways of promoting the translational readthrough of PTCs or inhibiting the NMD pathway. With this review, we update the state-of-the-art technologies in nonsense suppression, focusing on novel modalities with therapeutic potential, such as small molecules (readthrough agents, NMD inhibitors, and molecular glue degraders); antisense oligonucleotides; tRNA suppressors; ADAR-mediated RNA editing; targeted pseudouridylation; and gene/base editing. While these various modalities have significantly advanced in their development stage since our last review, each has advantages (e.g., ease of delivery and specificity) and disadvantages (manufacturing complexity and off-target effect potential), which we discuss here. Full article

The prevalence of Helicobacter pylori (H. pylori), a pathogen, has decreased globally in the last decade. To date, the management of H. pylori has focused on a reactive approach, whereby those diagnosed are treated with antimicrobials and acid suppression in combination. This review article provides an overview of the shift in the management of H. pylori from a reactive approach towards a proactive ‘screen and treat’ approach; the article reflects the current pharmacological landscape for H. pylori treatment by exploring similarities such as the first-line prescription of quadruple therapy in most countries and provides a summary table of the best practice guidance from Europe, Asia, and North America. It explores significant ongoing challenges in management, such as rising antimicrobial resistance rates, and explores a potential ‘work smart’ approach to antimicrobial susceptibility testing. We explore the role of registry databases in providing data on treatment efficacy and safety and how they can support a strategic approach to H. pylori treatment. We question if such a database’s availability, update, and regular audit should serve as a key quality indicator in a population screening programme. Despite a call for vaccination against H. pylori and decades of research, not many have made it to a phase-three clinical trial. We explore the challenges that have complicated the development of such a vaccine, such as the genetic diversity of H. pylori, immunotolerance, and limitations of mouse models in research; we reflect on how these challenges are contributing to a low likelihood of having a vaccine in the short–medium term. Lastly, it explores the heterogeneity in research on probiotics and their role as an adjunct in the management of H. pylori. Full article

Dental caries is a global health problem that requires better prevention measures. One of the goals is to reduce the prevalence of the cariogenic Gram-positive bacterium Streptococcus mutans. We have recently shown that naturally occurring arachidonic acid (AA) has both anti-bacterial and anti-biofilm activities against this bacterium. An important question is how these activities are affected by other anti-bacterial compounds commonly used in mouthwashes. Here, we studied the combined treatment of AA with chlorhexidine (CHX), cetylpyridinium chloride (CPC), triclosan, and fluoride. Checkerboard microtiter assays were performed to determine the effects on bacterial growth and viability. Biofilms were quantified using the MTT metabolic assay, crystal violet (CV) staining, and live/dead staining with SYTO 9/propidium iodide (PI) visualized by spinning disk confocal microscopy (SDCM). The bacterial morphology and the topography of the biofilms were visualized by high-resolution scanning electron microscopy (HR-SEM). The effect of selected drug combinations on cell viability and membrane potential was investigated by flow cytometry using SYTO 9/PI staining and the potentiometric dye DiOC2(3), respectively. We found that CHX and CPC had an antagonistic effect on AA at certain concentrations, while an additive effect was observed with triclosan and fluoride. This prompted us to investigate the triple treatment of AA, triclosan, and fluoride, which was more effective than either compound alone or the double treatment. We observed an increase in the percentage of PI-positive bacteria, indicating increased bacterial cell death. Only AA caused significant membrane hyperpolarization, which was not significantly enhanced by either triclosan or fluoride. In conclusion, our data suggest that AA can be used together with triclosan and fluoride to improve the efficacy of oral health care. Full article

Freshwater environments are primary receiving systems of wastewater and effluents, which carry low concentrations of antibiotics and antimicrobial-resistant (AMR) bacteria and genes. Aquatic microbial communities are thus exposed to environmentally relevant concentrations of antibiotics (ERCA) that presumably influence the acquisition and spread of environmental AMR. Here, we analyzed ERCA exposure with and without the additional presence of municipal wastewater treatment plant effluent (W) and swine manure run-off (M) on aquatic biofilm resistomes. Microscopic analyses revealed decreased taxonomic diversity and biofilm structural integrity, while metagenomic analysis revealed an increased abundance of resistance, virulence, and mobile element-related genes at the highest ERCA exposure levels, with less notable impacts observed when solely exposed to W or M effluents. Microbial function predictions indicated increased gene abundance associated with energy and cell membrane metabolism and heavy metal resistance under ERCA conditions. In silico predictions of increased resistance mechanisms did not correlate with observed phenotypic resistance patterns when whole communities were exposed to antimicrobial susceptibility testing. This reveals important insight into the complexity of whole-community coordination of physical and genetic responses to selective pressures. Lastly, the environmental AMR risk assessment of metagenomic data revealed a higher risk score for biofilms grown at sub-MIC antibiotic conditions. Full article

Rifampicin is one of the mainstays in treating staphylococcal prosthetic joint infection (PJI). However, discontinuation due to intolerance, drug interactions, and adverse events is common. Two-stage revision surgery remains the gold standard, with the number of revision arthroplasties steadily increasing. This study aims to evaluate the effectiveness and safety of a novel two-stage revision protocol for staphylococcal prosthetic joint infection (PJI) utilizing bone cement spacers loaded with multiple high doses of antibiotics. Additionally, it seeks to analyze outcomes in patients ineligible for rifampicin treatment. A retrospective review of 43 cases of staphylococcal hip and knee prosthetic joint infections (PJIs) from 2012 to 2020 was conducted. In all instances, a commercial cement containing 1 g of gentamicin and 1 g of clindamycin, augmented with 4 g of vancomycin and 2 g of ceftazidime, was employed to cast a spacer manually after thorough surgical debridement. We report an eradication rate of 82%, with no significant differences observed (p = 0.673) between patients treated with (84%, n = 19) and without rifampicin (79%, n = 24). There were no disparities in positive culture rates (7%), spacer replacement (18%), or survival analysis (p = 0.514) after an average follow-up of 68 months (range 10–147) in the absence of systemic toxicity and surgical complications superimposable to those previously reported. In conclusion, two-stage revision with local high doses of ceftazidime, vancomycin, gentamicin, and clindamycin demonstrates high effectiveness in treating staphylococcal PJIs. Notably, systemic rifampicin does not influence the outcomes. This protocol, with multiple high doses of antibiotics loaded into the bone cement spacer, is presented as a viable and safe alternative for patients unsuitable for rifampicin treatment. Full article

Management of suspected early-onset sepsis (EOS) is undergoing continuous evolution aiming to limit antibiotic overtreatment, yet current data on the level of overtreatment are only available for a select number of countries. This study aimed to determine antibiotic initiation and continuation rates for suspected EOS, along with the incidence of culture-proven EOS in The Netherlands. In this retrospective study from 2019 to 2021, data were collected from 15 Dutch hospitals, comprising 13 regional hospitals equipped with Level I-II facilities and 2 academic hospitals equipped with Level IV facilities. Data included birth rates, number of neonates started on antibiotics for suspected EOS, number of neonates that continued treatment beyond 48 h and number of neonates with culture-proven EOS. Additionally, blood culture results were documented. Data were analysed both collectively and separately for regional and academic hospitals. A total of 103,492 live-born neonates were included. In 4755 neonates (4.6%, 95% CI 4.5–4.7), antibiotic therapy was started for suspected EOS, and in 2399 neonates (2.3%, 95% CI 2.2–2.4), antibiotic treatment was continued beyond 48 h. Incidence of culture-proven EOS was 1.1 cases per 1000 live births (0.11%, 95% CI 0.09–0.14). Overall, for each culture-proven EOS case, 40.6 neonates were started on antibiotics and in 21.7 neonates therapy was continued. Large variations in treatment rates were observed across all hospitals, with the number of neonates initiated and continued on antibiotics per culture-proven EOS case varying from 4 to 90 and from 4 to 56, respectively. The high number of antibiotic prescriptions compared to the EOS incidence and wide variety in clinical practice among hospitals in The Netherlands underscore both the need and potential for a novel approach to the management of neonates with suspected EOS. Full article

Disulfidptosis, a newly identified mode of programmed cell death, is yet to be comprehensively elucidated with respect to its multi-omics characteristics in tumors, specific pathogenic mechanisms, and antitumor functions in liver cancer. This study included 10,327 tumor and normal tissue samples from 33 cancer types. In-depth analyses using various bioinformatics tools revealed widespread dysregulation of disulfidptosis-related genes (DRGs) in pan-cancer and significant associations with prognosis, genetic variations, tumor stemness, methylation levels, and drug sensitivity. Univariate and multivariate Cox regression and LASSO regression were used to screen and construct prognosis-related hub DRGs and predictive models in the context of liver cancer. Subsequently, single cell analysis was conducted to investigate the subcellular localization of RPN1, a hub DRG, in various solid tumors. Western blotting was performed to validate the expression of RPN1 at both cellular and tissue levels. Additionally, functional experiments, including CCK8, EdU, clone, and transwell assays, indicated that RPN1 knockdown promoted the proliferative and invasive capacities of liver cancer cells. Therefore, this study elucidated the multi-omics characteristics of DRGs in pan-cancer and established a prognostic model for liver cancer. Additionally, this study revealed the molecular functions of RPN1 in liver cancer, suggesting its potential as a therapeutic target for this disease. Full article

Cholelithiasis is a common biliary tract disease. However, the exact mechanism underlying gallstone formation remains unclear. Mucin plays a vital role in the nuclear formation and growth of cholesterol and pigment stones. Excessive mucin secretion can result in cholestasis and decreased gallbladder activity, further facilitating stone formation and growth. Moreover, gallstones may result in inflammation and the secretion of inflammatory factors, which can further increase mucin expression and secretion to promote the growth of gallstones. This review systematically summarises and analyses the role of mucins in gallstone occurrence and development and its related mechanisms to explore new ideas for interventions in stone formation or recurrence. Full article

Transcranial electrical stimulation (tES) is increasingly recognized for its potential to modulate cerebral blood flow (CBF) and evoke cerebrovascular reactivity (CVR), which are crucial in conditions like mild cognitive impairment (MCI) and dementia. This study explores the impact of tES on the neurovascular unit (NVU), employing a physiological modeling approach to simulate the vascular response to electric fields generated by tES. Utilizing the FitzHugh–Nagumo model for neuroelectrical activity, we demonstrate how tES can initiate vascular responses such as vasoconstriction followed by delayed vasodilation in cerebral arterioles, potentially modulated by a combination of local metabolic demands and autonomic regulation (pivotal locus coeruleus). Here, four distinct pathways within the NVU were modeled to reflect the complex interplay between synaptic activity, astrocytic influences, perivascular potassium dynamics, and smooth muscle cell responses. Modal analysis revealed characteristic dynamics of these pathways, suggesting that oscillatory tES may finely tune the vascular tone by modulating the stiffness and elasticity of blood vessel walls, possibly by also impacting endothelial glycocalyx function. The findings underscore the therapeutic potential vis-à-vis blood-brain barrier safety of tES in modulating neurovascular coupling and cognitive function needing the precise modulation of NVU dynamics. This technology review supports the human-in-the-loop integration of tES leveraging digital health technologies for the personalized management of cerebral blood flow, offering new avenues for treating vascular cognitive disorders. Future studies should aim to optimize tES parameters using computational modeling and validate these models in clinical settings, enhancing the understanding of tES in neurovascular health. Full article

Speech emotion recognition (SER) is a technology that can be applied to distance education to analyze speech patterns and evaluate speakers’ emotional states in real time. It provides valuable insights and can be used to enhance students’ learning experiences by enabling the assessment of their instructors’ emotional stability, a factor that significantly impacts the effectiveness of information delivery. Students demonstrate different engagement levels during learning activities, and assessing this engagement is important for controlling the learning process and improving e-learning systems. An important aspect that may influence student engagement is their instructors’ emotional state. Accordingly, this study used deep learning techniques to create an automated system for recognizing instructors’ emotions in their speech when delivering distance learning. This methodology entailed integrating transformer, convolutional neural network, and long short-term memory architectures into an ensemble to enhance the SER. Feature extraction from audio data used Mel-frequency cepstral coefficients; chroma; a Mel spectrogram; the zero-crossing rate; spectral contrast, centroid, bandwidth, and roll-off; and the root-mean square, with subsequent optimization processes such as adding noise, conducting time stretching, and shifting the audio data. Several transformer blocks were incorporated, and a multi-head self-attention mechanism was employed to identify the relationships between the input sequence segments. The preprocessing and data augmentation methodologies significantly enhanced the precision of the results, with accuracy rates of 96.3%, 99.86%, 96.5%, and 85.3% for the Ryerson Audio–Visual Database of Emotional Speech and Song, Berlin Database of Emotional Speech, Surrey Audio–Visual Expressed Emotion, and Interactive Emotional Dyadic Motion Capture datasets, respectively. Furthermore, it achieved 83% accuracy on another dataset created for this study, the Saudi Higher-Education Instructor Emotions dataset. The results demonstrate the considerable accuracy of this model in detecting emotions in speech data across different languages and datasets. Full article

The rupture of unstable plaques is a major cause of acute cardiovascular events. The early assessment of carotid plaques can significantly reduce the cardiovascular risks, so developing evaluation models suitable for data from different centers is of great clinical importance. This study leverages plaque datasets from multiple centers to develop a Weighted multi-source carotid artery plaque Unsupervised Classification Framework (WUCF). The multi-source domain adaptation module of the WUCF focuses on maintaining feature consistency between each independent source and target center, while also integrating a specialized domain discriminator expert. This ensures that the knowledge from each source center is effectively learned and combined for accurate predictions in the target domain. The experimental evaluation of WUCF, using datasets from three centers, has demonstrated the method’s superiority and robustness. Full article

Schizophrenia is a chronic mental disorder that affects millions of people around the world. Neurologists commonly use EEG signals to distinguish schizophrenia patients from normal controls, but their manual analysis is tedious and time-consuming. This has motivated the need for automated methods based on machine learning. However, the methods based on hand-engineered features need human experts to decide which features should be extracted. Though deep learning has recently shown good results for schizophrenia detection, the existing deep models have high parameter complexity, making them prone to overfitting because the available data are limited. To overcome these limitations, we propose a method based on an ensemble-like approach and a lightweight one-dimensional convolutional neural network to discriminate schizophrenia patients from healthy controls. It splits an input EEG signal for analysis into smaller segments, where the same backbone model analyses each segment. In this way, it makes decisions after scanning an EEG signal of any length without increasing the complexity; i.e., it scales well with an EEG signal of any length. The model architecture is simple and involves a small number of parameters, making it easy to implement and train using a limited amount of data. Though the model is lightweight, enough trials are still needed to learn the discriminative features from available data. To tackle this issue, we introduce a simple data augmentation scheme. The proposed method achieved an accuracy of 99.88% on a public benchmark dataset; it outperformed the state-of-the-art methods. It will help neurologists in the rapid and accurate detection of schizophrenia patients. Full article

The performance of facial recognition systems significantly decreases when faced with a lack of training images. This issue is exacerbated when there is only one image per subject available. Probe images may contain variations such as illumination, expression, and disguise, which are difficult to recognize accurately. In this work, we present a model that generates six facial variations from a single neutral face image. Our model is based on a CGAN, designed to produce six highly realistic facial expressions from one neutral face image. To evaluate the accuracy of our approach comprehensively, we employed several pre-trained models (VGG-Face, ResNet-50, FaceNet, and DeepFace) along with a custom CNN model. Initially, these models achieved only about 76% accuracy on single-sample neutral images, highlighting the SSPP challenge. However, after fine-tuning on the synthetic expressions generated by our CGAN from these single images, their accuracy increased significantly to around 99%. Our method has proven highly effective in addressing SSPP issues, as evidenced by the significant improvement achieved. Full article

To study the variation laws and effects of asphalt mastic under the cooperative interaction of different temperatures and humidities, cyclic conditions for different temperature ranges were set to conduct indoor experimental simulations of thermal–humidity coupling cycles. Firstly, the macroscopic performance changes in styrene butadiene styrene polymer (SBS)-modified asphalt mastic were evaluated by the penetration test, softening point test, ductility test, Brookfield rotational viscosity test, and double-edge notched tensile (DENT) test; then, the mechanism of performance changes was explored from the perspective of chemical composition by combining this with Fourier transform infrared spectroscopy (FTIR). The research results show that with the increase in thermal–humidity coupling cycles, SBS-modified asphalt mastic exhibited aging phenomena such as hardening and embrittlement, and its macroscopic performance deteriorated; under the same test conditions, the interval with a higher temperature difference had a greater impact on the performance of the mastic; the sulfoxide index (IS-O) of SBS-modified asphalt mastic increases after thermal–humidity coupling cycles, while the isoprene index (IB) decreases. Full article