Search Results (48)

Alzheimer’s disease (AD), a prevalent neurodegenerative disorder in the elderly, poses significant humanistic and economic burdens worldwide. Previously, we identified Trp-Leu-Pro (WLP), a novel antioxidant peptide derived from the sea squirt (Halocynthia roretzi); however, its effects on AD remained unexplored. In this study, we developed a rapid and efficient method to generate AD cerebral organoids with consistent quality using okadaic acid (OKA) exposure. This study aimed to evaluate the protective effects of WLP on OKA-induced AD pathology in cerebral organoids and elucidate its underlying mechanisms. Our results demonstrated that cerebral organoids exposed to 25 nM OKA successfully recapitulated hallmark AD pathologies, including amyloid-beta (Aβ) plaque deposits, neurofibrillary tangles (NFTs) formed by hyperphosphorylated tau proteins, and neuronal loss. WLP treatment significantly enhanced cell viability, increased the proportion of neuronal progenitor cells, and reduced Aβ plaques and NFTs in OKA-induced cerebral organoids. Furthermore, transcriptomic analysis revealed that the neuroprotective effects of WLP are primarily mediated through the regulation of synapse-related and oxidative stress pathways. These findings highlight the potential of WLP as a promising nutraceutical candidate for AD prevention. Full article

Lactic acid bacteria (LAB) fermentation has been claimed as an effective way of modifying the sensory properties of plant-based foods. However, not much has been published on the influence of different LAB strains on the flavour of the volatile organic compounds (VOCs) produced. Using a defined medium (DM) and proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS), we assessed the VOCs produced by seven LAB strains, Levilactobacillus brevis WLP672 (LB672), Lactobacillus delbrueckii WLP677 (LD677), Pediococcus damnosus WLP661 (PD661), Lactiplantibacillus plantarum LP100 (LP100), Pediococcus pentosaceus PP100 (PP100), Pediococcus damnosus 5733 (PD5733), and Lentilactobacillus buchneri 5335 (LU5335), at three time points during fermentation (0, 7, and 14 days) at either 25 or 35 °C. Significant variations in VOC production were observed among LAB strains, growing in the same DM composition at either 25 °C or 35 °C. Specifically, the concentration of m/z 87.043 (t.i. diacetyl) was significantly (p < 0.05) higher at 7 days of fermentation at 35 °C by LP100, followed by PP100 at 35 °C and PD661 at 25 °C compared to the other strains at either 25 or 35 °C. The concentration of m/z 115.112 (t.i. 2-heptanone) was significantly (p < 0.05) higher at 7 days of fermentation at either 25 or 35 °C by LP100 compared to the other strains at all temperature and time points. The concentration of m/z 49.011 (t.i. methanethiol) was significantly (p < 0.05) higher after 7 days of fermentation at 35 °C by LB672 compared to the other strains at either 25 or 35 °C. The concentration of m/z 71.085 (t.i. 3-methyl butanol) was significantly (p < 0.05) higher after 7 days of fermentation at either 25 or 35 °C by PD661, LU5335, or PD5733 compared to the other strains studied. A notable increase in specific VOC concentrations was observed at 35 °C compared to 25 °C. This research demonstrates that LAB strains generate distinct VOC profiles in a DM based on strains and fermentation conditions. Therefore, this knowledge provides a basis for controlling and enhancing flavour in plant-based fermentations. Full article

This paper presents a comprehensive review of advancements in wafer-level packaging (WLP) technology, with a particular focus on its application in surface acoustic wave (SAW) and bulk acoustic wave (BAW) filters. As wireless communication systems continue to evolve, there is an increasing demand for higher performance and miniaturization, which has made acoustic wave devices—especially SAW and BAW filters—crucial components in the Radio Frequency (RF) front-end systems of mobile devices. This review explores key developments in WLP technology, emphasizing novel materials, innovative structures, and advanced modeling techniques that have enabled the miniaturization and enhanced functionality of these filters. Additionally, the paper discusses the role of WLP in addressing challenges related to size reduction and integration, facilitating the creation of multi-functional devices with low manufacturing costs and high precision. Finally, it highlights the opportunities and future directions of WLP technology in the context of next-generation wireless communication standards. Full article

Cloud computing offers scalable and adaptable resources on demand, and has emerged as an essential technology for contemporary enterprises. Nevertheless, it is still challenging work to efficiently handle cloud resources because of dynamic changes in load requirement. Existing forecasting approaches are unable to handle the intricate temporal symmetries and nonlinear patterns in cloud workload data, leading to degradation of prediction accuracy. In this manuscript, a Symmetry-Aware Multi-Dimensional Attention Spiking Neural Network with Optimization Techniques for Accurate Workload and Resource Time Series Prediction in Cloud Computing Systems (MASNN-WL-RTSP-CS) is proposed. Here, the input data from the Google cluster trace dataset were preprocessed using Multi Window Savitzky–Golay Filter (MWSGF) to remove noise while preserving important data patterns and maintaining structural symmetry in time series trends. Then, the Multi-Dimensional Attention Spiking Neural Network (MASNN) effectively models symmetric patterns in workload fluctuations to predict workload and resource time series. To enhance accuracy, the Secretary Bird Optimization Algorithm (SBOA) was utilized to optimize the MASNN parameters, ensuring accurate workload and resource time series predictions. Experimental results show that the MASNN-WL-RTSP-CS method achieves 35.66%, 32.73%, and 31.43% lower Root Mean Squared Logarithmic Error (RMSLE), 25.49%, 32.77%, and 28.93% lower Mean Square Error (MSE), and 24.54%, 23.65%, and 23.62% lower Mean Absolute Error (MAE) compared with other approaches, like ICNN-WL-RP-CS, PA-ENN-WLP-CS, and DCRNN-RUP-RP-CCE, respectively. These advances emphasize the utility of MASNN-WL-RTSP-CS in achieving more accurate workload and resource forecasts, thereby facilitating effective cloud resource management. Full article

In advanced microelectronic packaging, high thermo-mechanical loads arise on the solder interconnects. Accurate and efficient modeling of the mechanical behavior is crucial in the design of the package, and the simulation results can provide a basis for estimations of the reliability of the assembly. However, the accuracy of the simulation results depends on the accuracy of the modeled geometry and the modeling simplifications and assumptions employed to achieve computational cost-efficient calculations. In this work, finite element analysis (FEA) of a Fan Out—Wafer Level Packaging (FO-WLP) layout was carried out considering the following variations: modeling domain (2-D and pseudo-3-D) was defined for creating the efficient calculation framework, where soldering material (SAC 305 and SACQ), incorporation of intermetallic compound (IMC), bond pad edge geometry (sharp and blunt) were modeled for cycles of thermal load. Stress and strain analysis was carried out to evaluate the solder behavior for the parameter variations. Furthermore, fatigue indicators were evaluated. An efficient planar simulation framework with 2-D and pseudo-3-D meshed geometries provides a quick estimate for the lower and upper bound for the strain, stress and strain energy-related parameters, respectively. This calculation framework can be employed for extensive parameter studies solved rapidly at low computational costs. Full article

This paper presents a novel framework for 3D face reconstruction from single 2D images and addresses critical limitations in existing methods. Our approach integrates modified adversarial neural networks with graph neural networks to achieve state-of-the-art performance. Key innovations include (1) a generator architecture based on Graph Convolutional Networks (GCNs) with a novel loss function and identity blocks, mitigating mode collapse and instability; (2) the integration of facial landmarks and a non-parametric efficient-net decoder for enhanced feature capture; and (3) a lightweight GCN-based discriminator for improved accuracy and stability. Evaluated on the 300W-LP and AFLW2000-3D datasets, our method outperforms existing approaches, reducing Chamfer Distance by 62.7% and Earth Mover’s Distance by 57.1% on 300W-LP. Moreover, our framework demonstrates superior robustness to variations in head positioning, occlusion, noise, and lighting conditions while achieving significantly faster processing times. Full article

Bacterial fermentation is considered to be a cost-effective means of generating desired flavour compounds from plant-based substrates. However, the wide range of substrates present in plants makes it challenging to understand how individual components impact on flavour volatile organic compound (VOC) production. To simplify this, a defined medium can be used to better understand VOCs production with regard to individual compounds. In the current study, the VOCs produced by the lactic acid bacterium, Levilactobacillus brevis WLP672, growing in a defined medium containing different carbon sources (either glucose (DM), fructose (DMFr) or citrate (DMCi)) under a range of fermentation conditions (time: 0, 7, and 14 days; and temperature: 25 and 35 °C) were assessed using proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS). Among the detected mass peaks (m/z), after 7 days of fermentation, the concentrations of m/z 45.033 (t.i. acetaldehyde), m/z 49.011 (t.i. methanethiol), and m/z 89.060 (t.i. ethyl acetate) were significantly (p < 0.05) higher in DM at 35 °C than all other treatments at either temperature. The knowledge obtained will help to produce desirable LAB fermentation flavour VOCs or VOC mixtures that could be used in developing plant-based analogues with acceptable sensory properties. Full article

Lactic acid bacteria (LAB) fermentation is a viable approach for producing plant-based flavour compounds; however, little is understood about the impact of different LAB strains and medium compositions on the production of volatile organic compounds (VOCs). This study investigated the impact of the addition of individual amino acids (AAs) (L-leucine, L-isoleucine, L-phenylalanine, L-glutamic acid, L-aspartic acid, L-threonine, or L-methionine) to a defined medium (DM) on the generation of VOCs (after 0, 7, and 14 days) by one of three LAB strains (Levilactobacillus brevis WLP672 (LB672), Lactiplantibacillus plantarum LP100 (LP100), and Pediococcus pentosaceus PP100 (PP100)), using proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS). The concentration of m/z 45.031 (t.i. acetaldehyde) was significantly (p < 0.05) higher after 7 days of fermentation by LP100 in the DM supplemented with threonine compared to all other media fermented by all three strains. The concentrations of m/z 49.012 (t.i. methanethiol) and m/z 95.000 (t.i. dimethyl disulfide) were significantly (p < 0.05) higher after 7 days of fermentation by either LP100, PP100, or LB672 in the DM supplemented with methionine compared to all other media. Information on the role of individual AAs on VOCs generation by different LAB strains will help to guide flavour development from the fermentation of plant-based substrates. Full article

A regionally developed and adapted dessert apple, ‘Wodarz’, was explored for its potential in apple cider production because of its consistent productivity when other apple cultivars have struggled with North Dakota’s climate. Due to the importance of yeast strain on the perceived quality of fermentation products, five commercial yeast strains, three wine yeasts (EC1118, Maurivin B, and 71B), and two cider yeasts (WLP775 and WY4766) were evaluated for their impact on the physicochemical properties, color, and sensory characteristics of ‘Wodarz’ cider. By assessing dynamic changes, such as spectral properties and sugar content, a comparison among yeasts was conducted across multiple dimensions. The lightness, chroma, and hue all showed variations throughout fermentation, though not across the final ciders. However, differences in the final color of the ciders were identified via ΔE calculations. Each yeast contributed different aromas and tastes to the final ciders. Among yeast strains, EC1118 had the strongest aroma intensity. Despite having subdued aroma intensity, 71B had strong acidity tastes and WLP775 had strong fruity tastes. Thus, our research suggests that yeast strains are an applicable factor in determining the final sensory attributes of local ‘Wodarz’ cider. This is the first report of fermentation outcomes using ‘Wodarz’ apples for cider. ‘Wodarz’ can be aromatically described using terms such as apple, honey, herbal, rose, and floral and fruit notes. The overall taste of ‘Wodarz’ cider is characterized by apple, honey, and rose notes followed by black pepper and grass. Full article

With the advancement of Moore’s Law reaching its limits, advanced packaging technologies represented by Flip Chip (FC), Wafer-Level Packaging (WLP), System in Package (SiP), and 3D packaging have received significant attention. While advanced packaging has made breakthroughs in achieving high performance, miniaturization, and low cost, the smaller thermal space and higher power density have created complex physical fields such as electricity, heat, and stress. The packaging interconnects responsible for electrical transmission are prone to serious reliability issues, leading to the device’s failure. Therefore, conducting multi-field coupling research on the reliability of advanced packaging interconnects is necessary. The development of packaging and the characteristics of advanced packaging are reviewed. The reliability issues of advanced packaging under thermal, electrical, and electromagnetic fields are discussed, as well as the methods and current research of multi-field coupling in advanced packaging. Finally, the prospect of the multi-field coupling reliability of advanced packaging is summarized to provide references for the reliability research of advanced packaging. Full article

Decoupling economic growth from carbon emissions is crucial for combating the climate crisis and promoting green development. However, a uniform approach to climate mitigation exacerbates regional disharmony. As a microcosm of China’s regional heterogeneity, the Yangtze River Economic Belt (YREB) is helpful in exploring regional collaborative climate governance. This paper uses the Thiel index, the Tapio decoupling model, and the Logarithmic Mean Divisia Index (LMDI) decomposition approach to explore the decoupling of economic growth from carbon emissions in YREB from 2005 to 2019. Results indicate that the carbon intensity difference is mainly from the difference within middle-rising provinces (MRP) and western less-developed provinces (WLP). YREB exhibits strong decoupling overall, but it is not sustained. The economic growth effect significantly promotes carbon emissions, which is more prominent in MRP. The energy intensity effect plays a vital role in restraining carbon emissions. The emission factor effect signals an improved energy structure in WLP. Regional coordination is needed to achieve green development; thus, provinces should set differentiated carbon emission reduction targets, and more potent tools are recommended in major carbon emitters. Full article

Fermentation by lactic acid bacteria (LAB) is a promising approach to meet the increasing demand for meat or dairy plant-based analogues with realistic flavours. However, a detailed understanding of the impact of the substrate, fermentation conditions, and bacterial strains on the volatile organic compounds (VOCs) produced during fermentation is lacking. As a first step, the current study used a defined medium (DM) supplemented with the amino acids L-leucine (Leu), L-isoleucine (Ile), L-phenylalanine (Phe), L-threonine (Thr), L-methionine (Met), or L-glutamic acid (Glu) separately or combined to determine their impact on the VOCs produced by Levilactobacillus brevis WLP672 (LB672). VOCs were measured using headspace solid-phase microextraction (HS-SPME) gas chromatography–mass spectrometry (GC-MS). VOCs associated with the specific amino acids added included: benzaldehyde, phenylethyl alcohol, and benzyl alcohol with added Phe; methanethiol, methional, and dimethyl disulphide with added Met; 3-methyl butanol with added Leu; and 2-methyl butanol with added Ile. This research demonstrated that fermentation by LB672 of a DM supplemented with different amino acids separately or combined resulted in the formation of a range of dairy- and meat-related VOCs and provides information on how plant-based fermentations could be manipulated to generate desirable flavours. Full article

Obesity and overweight rates in Malta are high. Recent studies report that nearly one third of Maltese women are affected by obesity and another third are in the overweight category, respectively the causes of obesity are complex and multifactorial, highlighting the need to further understand the main issues within a specific target population to develop effective and sustainable weight loss strategies. The overall aims of this local study were to investigate the main weight management challenges and facilitators experienced by Maltese women. An adapted, translated, and anonymised quantitative survey targeting adult Maltese females aged 18–65 years was shared in local media from November till December 2020. The questionnaire addressed weight loss (WL) strategies utilised; WL influences; barriers to WL (using close-ended questions); and suggestions for weight loss programmes (WLP) (using open-ended questions). Results were analysed using SPSS software (IBM, version 27). Data analysis included Chi- squared, Friedman and Kruskal–Wallis tests. Results: 193 respondents returned the survey. The majority (n = 93, 48.2%) were aged between 18–29 years; over half had a tertiary education level (n = 112, 58%), and they had a median Body Mass Index (BMI) of 25.3 kg/m². The three most commonly reported weight loss methods were ‘calorie controlled’ (n = 129, 66.8%), ‘fasting’ (n = 61, 31.6%), and the ‘Mediterranean diet (based on local dietary guidelines)’ (n = 51, 26.4%). Respondents thought that ‘drinking more water’; ‘consuming smaller food portions’; and ‘removing sugary products’ helped WL, whereas ‘being abroad’ or being ‘sad or stressed’ did not (mean rating scores [MRS]: 4.19, 4.13, 4.11, 3.97, 3.90, respectively). The main barriers to exercise were ‘lack of motivation’; and ‘finding it difficult to stick with routine’ (MRS: 3.24 and 3.16). Suggestions for WL included receiving more educational information (n = 20, 31.2%), making WL/exercise programmes affordable (n = 14, 21.9%), and receiving more support (n = 7, 10.9%). This local study pinpoints issues such as cost, motivation, and mental wellbeing considerations. The development of frameworks for further guidance and support on sustainable and healthy weight loss is suggested. Full article

Accurate and reliable water level prediction plays a crucial role in the optimal management of water resources and reservoir scheduling. Water level data have the characteristics of volatility and temporality; a single water level prediction model can only be applied to specific hydrological conditions and reservoirs. Therefore, in this paper, we present a robust lightweight model for water level prediction, namely WLP-VBL, by using a combination of VMD, BA, and LSTM. The proposed WLP-VBL model consists of three steps: first, the water level dataset is decomposed by EMD to obtain a number of decomposition layers K, and then VMD is used to decompose the original water level dataset into K intrinsic modal functions (IMFs) to produce a clearer signal. Next, the IMF data are sent to an LSTM neural network optimized by BA for prediction, and finally each component is superimposed to obtain the predicted value. In order to evaluate the effectiveness of the model, experiments were carried out on water level data for the Gan River. The results indicate that: (1) Compared with state-of-the art methods, e.g., LSTM, VMD-LSTM, and EMD-LSTM, WLP-VBL exhibited the best performance. The MSE and MAE of WLP-VBL decreased by 69.6~74.7% and 45~98.5%, respectively. (2) The proposed model showed stronger robustness for water level prediction, and was able to handle highly volatile and noisy data. Full article