Objective and objectives: Patients with cognitive disorders such as Alzheimer’s disease (AD) and mild cognitive impairment (MCI) frequently exhibit depressive symptoms. Depressive symptoms can be evaluated with various measures and questionnaires. The geriatric depression scale (GDS) is a scale that can be used to measure symptoms in geriatric age. Many questionnaires sum up symptom scales. However, core symptoms of depression in these patients and connections between these symptoms have not been fully explored yet. Thus, the objectives of this study were (1) to determine core symptoms of two cognitive disorders, Alzheimer’s disease and mild cognitive impairment, and (2) to investigate the network structure of depressive symptomatology in individuals with cognitive impairment in comparison with those with Alzheimer’s disease. Materials and Methods: This study encompassed 5354 patients with cognitive impairments such as Alzheimer’s disease (n = 1889) and mild cognitive impairment (n = 3464). The geriatric depression scale, a self-administered questionnaire, was employed to assess depressive symptomatology. Using exploratory graph analysis (EGA), a network analysis was conducted, and the network structure was evaluated through regularized partial correlation models. To determine the centrality of depressive symptoms within each cohort, network parameters such as strength, betweenness, and closeness were examined. Additionally, to explore differences in the network structure between Alzheimer’s disease and mild cognitive impairment groups, a network comparison test was performed. Results: In the analysis of centrality indices, “worthlessness” was identified as the most central symptom in the geriatric depression scale among patients with Alzheimer’s disease, whereas “emptiness” was found to be the most central symptom in patients with mild cognitive impairment. Despite these differences in central symptoms, the comparative analysis showed no statistical difference in the overall network structure between Alzheimer’s disease and mild cognitive impairment groups. Conclusions: Findings of this study could contribute to a better understanding of the manifestation of depressive symptoms in patients with cognitive impairment. These results are expected to aid in identifying and prioritizing core symptoms in these patients. Further research should be conducted to explore potential interventions tailored to these core symptoms in patients with Alzheimer’s disease and mild cognitive impairment. Establishing core symptoms in those groups might have clinical importance in that appropriate treatment for neuropsychiatric symptoms in patients with cognitive impairment could help preclude progression to further impairment. Full article

The use of whole-cell biocatalysts in microbial cell factories is of great interest to produce added-value compounds. Through large-scale fermentative processes, which use secondary raw materials as substrates, it is possible to recycle and upgrade agro-industrial by-products. This review addresses the main fermentative processes and bioreactors currently used for the valorization of orange peel, a by-product of the Citrus processing industry. Among the main added-value products, bioethanol, organic acids, enzymes, single cell proteins (SCPs), dyes and aromatic compounds have been industrially produced using orange peel via solid state fermentation and submerged fermentation. This approach fits within the circular economy goals in terms of clean technology and renewable energy, valorization and recycling, upgrade of industrial by-products and sustainability. Full article

Cadmium ion (Cd²⁺) stress is a major abiotic stressor affecting plant photosynthesis. However, the impact of sustained high-concentration Cd stress on the photosynthetic electron transport chain of aquatic plants is currently unclear. Here, prompt fluorescence (PF), delayed fluorescence (DF), and P700 signals were simultaneously measured to investigate the effect of Cd stress on photosynthesis in water dropwort [Oenanthe javanica (Blume) DC.]. We aimed to elucidate how Cd stress continuously affects the electron transport chain in this species. The PF analysis showed that with prolonged Cd stress, the F_J, F_I and F_P steadily decreased, accompanied by a positive shift in the K-band and L-band. Moreover, JIP-test parameters, including TR_O/ABS, ABS/CS_O, TR_O/CS_O and PI_ABS, were significantly reduced. The P700 signals showed that exposure to Cd stress hindered both the fast decrease and slow increase phases of the MR transient, ultimately resulting in a gradual reduction in both V_PSI and V_{PSII − PSI}. The DF analysis showed a gradual decrease in the I₁ and I₂ values as the duration of stress from Cd increased. The above results suggested that Cd stress affected the photosynthetic electron transport in water dropwort by influencing the amount of active PSII and PSI, primarily affecting PSII RCs in the early to mid-stages and PSI reductive activity in the later stage. Full article

A high consumption of solid fats is linked to increased inflammation and a risk of cardiovascular diseases. Hence, in recent years, there has been increasing interest in the development of oleogels as a fat substitute in food products. Oleogels are edible gels that contain a large amount of liquid oils entrapped in a 3D network and that can potentially be applied to spreads, bakery goods, meat, and dairy products in order to lower their saturated fat content while maintaining a desirable food texture and mouthfeel. In this work, alginate cryogels were studied as templates for three different edible oils in the process of oleogel formation. Two different freezing regimes to obtain cryogels were employed in order to evaluate better the textural and morphological capabilities of cryogels to adsorb and retain edible oils. It was shown that rapid freezing in liquid nitrogen produces alginate cryogels with a lower density, higher porosity, and a greater ability to adsorb the tested oils. The highest uptake and holding oil capacity was achieved for olive oil, which reached a value of 792%,and 82%, respectively. The best chewiness was found for an oleogel containing olive oil, whereas oleogels with the other two tested oils showed better springiness. Hence, the results presented in this work demonstrated that alginate-based cryogels can be effectively used as templates for oleogels and potentially find applications in the food industry. Full article

An appropriate drying method is crucial for producing high-quality dried apricots. In this study, the effects of four drying methods, hot air drying (HAD), infrared drying (IRD), pulse vacuum drying (PVD), and vacuum freeze-drying (VFD), on the drying kinetics and physical and nutritional characteristics of apricot slices were evaluated. PVD required the shortest time (16.25 h), followed by IRD (17.54 h), HAD (21.39 h), and VFD (34.64 h). VFD resulted in the best quality of apricot slices, with the smallest color difference (ΔE = 13.64), lowest water activity (0.312 ± 0.015) and browning degree (0.35), highest color saturation (62.84), lowest hardness (8.35 ± 0.47 N) and shrinkage (9.13 ± 0.65%), strongest rehydration ability (3.58 ± 0.11 g/g), a good microstructure, and high nutrient-retention rates (ascorbic acid content: 53.31 ± 0.58 mg/100 g, total phenolic content: 12.64 ± 0.50 mg GAE/g, and carotenoid content: 24.23 ± 0.58 mg/100 g) and antioxidant activity (DPPH: 21.10 ± 0.99 mmol Trolox/g and FRAP: 34.10 ± 0.81 mmol Trolox/g). The quality of PVD-treated apricot slices was second-best, and the quality of HAD-treated apricot slices was the worst. However, the energy consumption required for VFD was relatively high, while that required for PVD was lower. The results of this study provide a scientific basis for the large-scale industrial production of dried apricots. Full article

3-Methylthio-1-propanol (3-Met) is an important flavor compound in various alcoholic beverages such as Baijiu and Huangjiu. To maintain the content of 3-Met in these alcoholic beverages, it is necessary to screen a micro-organism with high yield of 3-Met from the brewing environment. In this study, the ability of yeast strains from the Baijiu brewing to produce 3-Met was analyzed, aiming to obtain yeast with high-yield 3-Met, and its fermentation conditions were optimized. Firstly, 39 yeast strains were screened using 3-Met conversion medium. The results showed that the majority of the strains from Baijiu brewing sources could produce 3-Met, and nearly half of the strains produced more than 0.5 g/L of 3-Met. Among these, yeast F10404, Y03401, and Y8#01, produced more than 1.0 g/L of 3-Met, with yeast Y03401 producing the highest amount at 1.30 g/L. Through morphological observation, physiological and biochemical analysis, and molecular biological identification, it was confirmed that yeast Y03401 was a Saccharomyces cerevisiae. Subsequently, the optimal fermentation conditions for 3-Met production by this yeast were obtained through single-factor designs, Plackett–Burman test, steepest ascent path design and response surface methodology. When the glucose concentration was 60 g/L, yeast extract concentration was 0.8 g/L, L-methionine concentration was 3.8 g/L, initial pH was 4, incubation time was 63 h, inoculum size was 1.6%, shaking speed was 150 rpm, loading volume was 50 mL/250 mL, and temperature was 26 °C, the content of 3-Met produced by S. cerevisiae Y03401 reached a high level of 3.66 g/L. It was also noteworthy that, in contrast to other study findings, this yeast was able to create substantial amounts of 3-Met even in the absence of L-methionine precursor. Based on the clear genome of S. cerevisiae and its characteristics in 3-Met production, S. cerevisiae Y03401 had broad prospects for application in alcoholic beverages such as Baijiu. Full article

The valorization of greenhouse gases, especially when focused on carbon dioxide, currently belongs to the main challenges of pro-environmental chemical processes. One of the important technologies in this field is dry methane reforming (DMR), leading to the so-called synthesis gas (CO + H₂). However, to be efficient and economically viable, an active and stable catalyst is required. Ni-based systems can be recommended in this regard. This research aimed to investigate how nickel content can influence the activity of model NiO_x/CeO₂ catalysts in DMR. A series of NiO_x/CeO₂ samples of various nickel loadings (0–10 wt.%) were prepared through dry impregnation. The obtained samples were characterized through XRD, RS, N₂-BET, DRIFT, SEM, UV/Vis-DR, and XPS. Nonlinear changes in surface properties of the investigated samples with increasing nickel concentration were found. The observed changes are mirrored both in the determined nickel speciation and in the corresponding catalytic activity. The highest activity was found for the catalyst containing 3 wt.%. of nickel. Full article

Achilles tendon (AT) pathologies are common musculoskeletal conditions that can significantly impair function. Despite various traditional treatments, recovery is often slow and may not restore full functionality. The use of extracellular vesicles (EVs) has emerged as a promising therapeutic option due to their role in cell signaling and tissue regeneration. This systematic review aims to consolidate current in vivo animal study findings on the therapeutic effects of EVs on AT injuries. An extensive literature search was conducted using the PubMed, Scopus, and Embase databases for in vivo animal studies examining the effects of EVs on AT pathologies. The extracted variables included but were not limited to the study design, type of EVs used, administration methods, efficacy of treatment, and proposed therapeutic mechanisms. After screening, 18 studies comprising 800 subjects were included. All but one study reported that EVs augmented wound healing processes in the AT. The most proposed mechanisms through which this occurred were gene regulation of the extracellular matrix (ECM), the enhancement of macrophage polarization, and the delivery of therapeutic microRNAs to the injury site. Further research is warranted to not only explore the therapeutic potential of EVs in the context of AT pathologies, but also to establish protocols for their clinical application. Full article

Infants presenting with unexpected pneumoperitoneum upon abdominal X-ray, indicating a gastrointestinal perforation (GIP), have a surgical emergency with potential morbidity and mortality. Preoperative determination of the location of perforation is challenging but will aid the surgeon in optimizing the surgical strategy, as colon perforations are more challenging than small bowel perforations. Therefore, the aim of this study is to provide an overview of preoperative patient characteristics, determine the differences between the small bowel and colon, and determine underlying causes in a cohort of infants with unexpected GIP. Methods: All infants (age ≤ 6 months) who presented at our center with unexpected pneumoperitoneum (no signs of pneumatosis before) undergoing surgery between 1996 and 2024 were retrospectively included. The differences between the location of perforation were analyzed using chi-squared and t-tests. Bonferroni correction was used to adjust for multiple tests. Results: In total, 51 infants presented with unexpected pneumoperitoneum at our center, predominantly male (N = 36/51) and premature (N = 40/51). Among them, twenty-six had small bowel, twenty-two colon, and three stomach perforations. Prematurity (p = 0.001), birthweight < 1000 g (p = 0.001), respiratory support (p = 0.001), and lower median arterial pH levels (p = 0.001) were more present in patients with small bowel perforation compared with colon perforations. Pneumatosis intestinalis was more present in patients with colon perforation (p = 0.004). All patients with Hirschsprung disease and cystic fibrosis had colon perforation. The final diagnoses were mainly focal intestinal perforations (N = 27/51) and necrotizing enterocolitis (N = 9/51). Conclusion: Infants with unexpected GIP, birthweight <1000 g, and prematurity have more risk for small bowel perforation. In case of colon perforation, additional screening (for Hirschsprung and cystic fibrosis) should be considered. Full article

Dementia poses a substantial global health challenge, warranting an exploration of its intricate pathophysiological mechanisms and potential intervention targets. Leveraging multi-omic technology, this study utilizes data from 2251 participants to construct classification models using lipidomic, gut metabolomic, and cerebrospinal fluid (CSF) proteomic markers to distinguish between the states of cognitive decline, namely, the cognitively unimpaired state, mild cognitive impairment, and dementia. The analysis identifies three CSF proteins (apolipoprotein E, neuronal pentraxin-2, and fatty-acid-binding protein), four lipids (DEDE.18.2, DEDE.20.4, LPC.O.20.1, and LPC.P.18.1), and five serum gut metabolites (Hyodeoxycholic acid, Glycohyodeoxycholic acid, Hippuric acid, Glyceric acid, and Glycodeoxycholic acid) capable of predicting dementia prevalence from cognitively unimpaired participants, achieving Area Under the Curve (AUC) values of 0.879 (95% CI: 0.802–0.956), 0.766 (95% CI: 0.700–0.835), and 0.717 (95% CI: 0.657–0.777), respectively. Furthermore, exclusively three CSF proteins exhibit the potential to predict mild cognitive impairment prevalence from cognitively unimpaired subjects, with an AUC of 0.760 (95% CI: 0.691–0.828). In conclusion, we present novel combinations of lipids, gut metabolites, and CSF proteins that showed discriminative abilities between the states of cognitive decline and underscore the potential of these molecules in elucidating the mechanisms of cognitive decline. Full article

Currently, various light-emitting diode (LED) lighting systems are being developed because LEDs are one of the most used lighting sources for work environments, buildings, homes, and public roads in terms of some of their applications. Similarly, they have low energy consumption, quick responses, and excellent optimal performance in their operation. However, these systems still need to precisely regulate lighting, maintain stable voltage and current in the presence of faults and disturbances, and have a wide range of operations in the event of trajectory changes or monitoring tasks regarding the desired voltage and current. This work presents the design and application of two types of robust controllers (structure-at-infinity control and geometric control) applied to an LED driver using a buck converter. The controllers aim to follow the desired trajectories, attenuate disturbances at the power supply input, and compensate for faults in the actuator (MOSFET) to keep the capacitor voltage and inductor current stable. When comparing the results obtained with the two controllers, it was observed that both present excellent performance in the presence of constant disturbances. However, in scenarios in which variable faults and path changes are implemented, the structure-at-infinity control method shows an overimpulse of output voltage and current ranging from 39 to 42 volts and from 0.3 to 0.45 A, with a margin of error of 1%, and it can generate a failure in the LED driver using a buck converter. On the other hand, when using geometric control, the results are satisfactory, achieving attenuating constant disturbances and variable faults, reaching the desired voltage (40 v to 35 v) and current (0.3 to 0.25 A) with a margin of error of 0.05%, guaranteeing a system without overvoltages or the accelerated degradation of the components due to magnetic conductivity. Full article

The conventional approach of the local convergence analysis of an iterative method on ${\mathbb{R}}^m$, with m a natural number, depends on Taylor series expansion. This technique often requires the calculation of high-order derivatives. However, those derivatives may not be part of the proposed method(s). In this way, the method(s) can face several limitations, particularly the use of higher-order derivatives and a lack of information about a priori computable error bounds on the solution distance or uniqueness. In this paper, we address these drawbacks by conducting the local convergence analysis within the broader framework of a Banach space. We have selected an important family of high convergence order methods to demonstrate our technique as an example. However, due to its generality, our technique can be used on any other iterative method using inverses of linear operators along the same line. Our analysis not only extends in ${\mathbb{R}}^m$ spaces but also provides convergence conditions based on the operators used in the method, which offer the applicability of the method in a broader area. Additionally, we introduce a novel semilocal convergence analysis not presented before in such studies. Both forms of convergence analysis depend on the concept of generalized continuity and provide a deeper understanding of convergence properties. Our methodology not only enhances the applicability of the suggested method(s) but also provides suitability for applied science problems. The computational results also support the theoretical aspects. Full article

Parkinson’s disease (PD) is a debilitating neurodegenerative disease with a relentlessly progressive course of illness. This study aimed to assess the dyadic dynamics of benefit finding (BF), demoralization, and stigma on the depression severity of PD patients and their caregivers. This study used a cross-sectional design with purposive sampling. In total, 120 PD patients and 120 caregivers were recruited from the neurological ward or neurological outpatient clinic of a medical center in Taiwan from October 2021 to September 2022. PD patients and their caregivers were enrolled and assessed using the Mini International Neuropsychiatric Interview, the Benefit Finding scale, Demoralization Scale, Stigma Subscale of the Explanatory Model Interview Catalogue, and Taiwanese Depression Questionnaire. Among the 120 patients and 120 caregivers that successfully completed the study, 41.7% (N = 50) and 60% (N = 72) were female, respectively. The most common psychiatric diagnoses of both the PD patients (17.5%) and their caregivers (13.3%) were depressive disorders. Using structural equation modeling, we found that the stigma, BF, and demoralization of PD patients might contribute to their depression severity. Demoralization and stigma of PD patients’ caregivers might also contribute to the depression severity of PD patients. Caregivers’ BF and demoralization were significantly linked with their depression severity. PD patients’ BF degree and their caregivers’ BF degree had significant interactive effects. Both patients’ and their caregivers’ stigma levels had significant interactive effects. Clinicians should be aware of and manage these contributing factors between PD patients and their caregivers in order to prevent them from exacerbating each other’s depression. Full article

Aircraft propellers produce relatively large in-plane loads, called propeller 1P loads, during maneuvers such as turning, diving, and lifting, and these loads can negatively affect the flight and control of the aircraft. In order to study the change rule of 1P aerodynamic loads, in this paper, a mathematical model of the propeller 1P aerodynamic loads has been developed based on the blade element momentum theory. This mathematical model was then corrected using the Pitt–Peters incoming flow correction method, the Prandtl tip correction method, and the propeller root flow correction method. Based on this mathematical model, a calculation procedure for the propeller 1P aerodynamic loads was developed using MATLAB software, and the accuracy of the procedure was verified by comparing the results with CFD simulation results. Numerical simulations show that the results calculated based on the proposed mathematical model for the coefficients of thrust, power, bending moment, and the tangential force of the propeller have an error of less than ±6.00% compared to the CFD simulation results. For a small inflow angle, the coefficients of bending moment and tangential force of the whole propeller fluctuate in a small range. But, as the inflow angle increases, the fluctuation range of the aerodynamic characteristic parameters of the propeller increases and the fluctuation becomes more complicated. Through numerical calculations, it has been shown that the mathematical model presented herein is reliable and accurate. In addition, it greatly shortens the calculation time and improves the calculation efficiency. It is expected that the proposed model can provide a certain help for the strength design of the propeller structure and the study of the aerodynamic performance of the whole aircraft. Full article

The Khibiny Mountains (hereafter called Khibiny Mts.) are one of the most urbanized and industrialized regions in the Russian Arctic. There are combined a developed mining complex, elaborate infrastructure, a well-known tourist resort, and a large population, all amidst an exceptionally rich biodiversity of plants. In this study, we analyzed the current knowledge of the spatial distribution of rare and endangered vascular plants and vegetation and the impacts of human activities on these ecosystems. Approximately 28% of the protected vascular plant species in the Murmansk Region were registered within the confines of the Khibiny Mts. In particular, although only a handful of protected species had a widespread presence, most rare species were confined to the southern reaches of the mountain range, with only a select few extending into other parts. Papaver lapponicum was the only species that thrived across the entire territory, including industrial areas. The studied territory contained nine specially protected areas spanning 123,220 hectares. Nature monuments adjacent to mining sites and urban centers play an important role in preserving regional biodiversity. However, the expansion of the mining industry, alongside deforestation and wildfires, poses considerable threats to the biodiversity of the Khibiny Mts. A comprehensive biodiversity conservation strategy implemented in this region balances the local and expansive territorial protection of rare species and habitats, ensuring environmental preservation while facilitating social and economic progress, a noteworthy example of environmental protection in the Arctic. Full article

Soil salinity hampers durum wheat plant growth and development at various stages. The detrimental effects of salinity on plant cellular and physiological processes necessitate strategies to alleviate its negative impact and improve overall crop yield. This study investigates the efficacy of plant growth-promoting rhizobacteria (PGPR) bacteria inoculation in mitigating salinity stress on two durum wheat genotypes with contrasting degrees of salinity tolerance (Tamaroi, salt-sensitive and Line 5004, salt-tolerant) under greenhouse and field conditions. For this purpose, two halotolerant-PGPR strains, Pseudomonas jordanii strain G34 and Oceanobacillus jordanicus strain GSFE11, were utilized for the inoculation. For the greenhouse experiment, the two selected genotypes were subjected to salinity at the flag leaf stage with continuous irrigation with a Hoagland solution supplemented with 50 mM NaCl. Field experiments were conducted across two locations with contrasting salinity levels over two growing seasons. At the end of both experiments, various parameters including total weight, spike weight, grain weight, spike number, spikelet number, grains per spike and thousand kernel weight were measured. The halotolerant PGPRs, P. jordanii strain G34 and O. jordanicus strain GSFE11, proved effective in alleviating salinity-induced adverse effects and enhancing growth under greenhouse and field conditions. However, bacterial inoculation significantly improved growth in the salt-sensitive genotype and such effects were not observed in the tolerant genotype, emphasizing genotype-specific responses. Notably, inoculation with O. jordanicus increased Na⁺ and Ca²⁺ uptake in the salt-tolerant “Line 5004” without hindering growth, suggesting one of its potential mechanisms for salt tolerance. This research demonstrates the potential of halotolerant-PGPR inoculation in enhancing durum wheat production in saline environments, but also underscores the importance of understanding genotype-specific responses for tailored interventions. Full article

The analysis of plant phenotype parameters is closely related to breeding, so plant phenotype research has strong practical significance. This paper used deep learning to classify Arabidopsis thaliana from the macro (plant) to the micro level (organelle). First, the multi-output model identifies Arabidopsis accession lines and regression to predict Arabidopsis’s 22-day growth status. The experimental results showed that the model had excellent performance in identifying Arabidopsis lines, and the model’s classification accuracy was 99.92%. The model also had good performance in predicting plant growth status, and the regression prediction of the model root mean square error (RMSE) was 1.536. Next, a new dataset was obtained by increasing the time interval of Arabidopsis images, and the model’s performance was verified at different time intervals. Finally, the model was applied to classify Arabidopsis organelles to verify the model’s generalizability. Research suggested that deep learning will broaden plant phenotype detection methods. Furthermore, this method will facilitate the design and development of a high-throughput information collection platform for plant phenotypes. Full article

Rice is a major food crop for more than half of the world’s population, while its production is seriously threatened by flooding, a common environmental stress worldwide. Flooding leads to oxygen deficiency, which is a major problem for submerged plants. Over the past three decades, significant progress has been made in understanding rice adaptation and molecular regulatory mechanisms in response to flooding. At the seed germination and seedling establishment stages, the CIPK15-SnRK1A-MYBS1 signaling cascade plays a central role in determining rice submergence tolerance. However, from seedlings to mature plants for harvesting, SUB1A- and SK1/SK2-regulated pathways represent two principal and opposite regulatory mechanisms in rice. In addition, phytohormones, especially gibberellins, induce adaptive responses to flooding throughout the rice growth period. This review summarizes the significant adaptive traits observed in flooded rice varieties and updates the molecular genetics and mechanisms of submergence tolerance in rice. Full article

Combinatorial drug therapy has emerged as a critically important strategy in medical research and patient treatment and involves the use of multiple drugs in concert to achieve a synergistic effect. This approach can enhance therapeutic efficacy while simultaneously mitigating adverse side effects. However, the process of identifying optimal drug combinations, including their compositions and dosages, is often a complex, costly, and time-intensive endeavor. To surmount these hurdles, we propose a novel microfluidic device capable of simultaneously generating multiple drug concentration gradients across an interlinked array of culture chambers. This innovative setup allows for the real-time monitoring of live cell responses. With minimal effort, researchers can now explore the concentration-dependent effects of single-agent and combination drug therapies. Taking neural stem cells (NSCs) as a case study, we examined the impacts of various growth factors—epithelial growth factor (EGF), platelet-derived growth factor (PDGF), and fibroblast growth factor (FGF)—on the differentiation of NSCs. Our findings indicate that an overdose of any single growth factor leads to an upsurge in the proportion of differentiated NSCs. Interestingly, the regulatory effects of these growth factors can be modulated by the introduction of additional growth factors, whether singly or in combination. Notably, a reduced concentration of these additional factors resulted in a decreased number of differentiated NSCs. Our results affirm that the successful application of this microfluidic device for the generation of multi-drug concentration gradients has substantial potential to revolutionize drug combination screening. This advancement promises to streamline the process and accelerate the discovery of effective therapeutic drug combinations. Full article

Brain–computer interface (BCI) for motor imagery is an advanced technology used in the field of medical rehabilitation. However, due to the poor accuracy of electroencephalogram feature classification, BCI systems often misrecognize user commands. Although many state-of-the-art feature selection methods aim to enhance classification accuracy, they usually overlook the interrelationships between individual features, indirectly impacting the accuracy of feature classification. To overcome this issue, we propose an adaptive feature learning model that employs a Riemannian geometric approach to generate a feature matrix from electroencephalogram signals, serving as the model’s input. By integrating the enhanced adaptive L1 penalty and weighted fusion penalty into the sparse learning model, we select the most informative features from the matrix. Specifically, we measure the importance of features using mutual information and introduce an adaptive weight construction strategy to penalize regression coefficients corresponding to each variable adaptively. Moreover, the weighted fusion penalty balances weight differences among correlated variables, reducing the model’s overreliance on specific variables and enhancing accuracy. The performance of the proposed method was validated on BCI Competition IV datasets IIa and IIb using the support vector machine. Experimental results demonstrate the effectiveness and superiority of the proposed model compared to the existing models. Full article

We conducted a systematic investigation into the spectral and pulse characteristics of C and L-band Nonlinear Polarization Rotation (NPR) mode-locked fiber lasers effectively employing nonlinear polarization rotation technology. In our experimental setup, we achieved a stable mode-locked state at 1560.076 nm, exhibiting a 3 dB spectral bandwidth of 9.1 nm. As the pump power increased, we observed spectral shifts accompanied by shifts in the first Kelly sideband and the generation of new Kelly sidebands. In this paper, the phenomenon of spectral deviation is elucidated through the interplay of self-phase modulation, group velocity drift, and polarization-dependent isolator (PD-ISO) filter effect, with an analysis of the formation and deviation of Kelly sidebands. Notably, spectral shift persisted even when the pump power exceeded 200 mW. However, continuous pump power escalation led to soliton splitting, resulting in the formation of new soliton beams. Based on the simultaneous generation of spectral shift and pulse splitting, our study contributes to an enhanced understanding of soliton dynamics in ultrafast fiber lasers and lays a foundation for the application of high-repetition-frequency harmonic mode-locked lasers with tunable wavelengths. Full article

This study aims to summarize design indexes for rich bottom layer mixtures (RBLMs) and design asphalt mixtures with superior performance to reduce reflective cracks and fatigue cracking resulting from semi-rigid base cracking in the asphalt layer. First, this study synthesizes the research results about RBLMs and introduces the related design indexes. After that, using ABAQUS 6.13, finite element analysis was performed to analyze the change in bottom stress when the base cracked and the interlayer bond weakened. SBS-modified asphalt mixtures (SMMs) and composite-modified asphalt mixtures (CMMs) were subsequently developed as RBLMs utilizing the Marshall test method and applied on a test road. The research findings reveal that design indexes for RBLMs include a volume of air voids (VVs) within the range of 2.0–3.0%, a maximum flexural strain exceeding 3500με, and a dynamic stability surpassing 1000 cycles/mm. Both mixtures satisfy the design requirements, with the CMM demonstrating superior performance and offering promising application prospects. Future research endeavors will concentrate on prolonged monitoring of the test section to authenticate the effectiveness of an RBL in practical road applications. Full article