Search Results (15)

This study presents a topology optimization approach to enhance the discharging performance of a latent heat thermal energy storage (LHTES) system using paraffin wax as the phase-change material (PCM) and a high-conductivity aluminium structure. Solidification is primarily governed by conduction, and the average heat transfer rate during this process is significantly lower than during melting; therefore, the optimization focused on the discharge phase. In a previous study, a novel LHTES device based on a Cartesian lattice was investigated experimentally and numerically. The validated numerical model from that study was adopted as the reference and used in a 2D topology optimization study based on the Solid Isotropic Material with Penalization (SIMP) method. The objective was to promote more uniform temperature distribution and reduce discharging time while maintaining the same aluminium volume fraction as in the reference device. Topology optimization produced a branched fin design, which was then extruded into a 3D model for comparison with the reference geometry. The optimized design resulted in improved temperature uniformity and a faster solidification process. Specifically, the time required to solidify 90% of the PCM was reduced by 12.3%, while the time to release 90% of the latent heat during the solidification process improved by 7.6%. Full article

Accurate stock price prediction requires the integration of heterogeneous data streams, yet conventional techniques struggle to simultaneously leverage fine-grained micro-stock features and broader macroeconomic indicators. To address this gap, we propose MambaLLM, a novel framework that fuses macro-index and micro-stock inputs through the synergistic use of state-space models (SSMs) and large language models (LLMs). Our two-branch architecture comprises (i) Micro-Stock Encoder, a Mamba-based temporal encoder for processing granular stock-level data (prices, volumes, and technical indicators), and (ii) Macro-Index Analyzer, an LLM module—employing DeepSeek R1 7B distillation—capable of interpreting market-level index trends (e.g., S&P 500) to produce textual summaries. These summaries are then distilled into compact embeddings via FinBERT. By merging these multi-scale representations through a concatenation mechanism and subsequently refining them with multi-layer perceptrons (MLPs), MambaLLM dynamically captures both asset-specific price behavior and systemic market fluctuations. Extensive experiments on six major U.S. stocks (AAPL, AMZN, MSFT, TSLA, GOOGL, and META) reveal that MambaLLM delivers up to a 28.50% reduction in RMSE compared with suboptimal models, surpassing traditional recurrent neural networks and MAMBA-based baselines under volatile market conditions. This marked performance gain highlights the framework’s unique ability to merge structured financial time series with semantically rich macroeconomic narratives. Altogether, our findings underscore the scalability and adaptability of MambaLLM, offering a powerful, next-generation tool for financial forecasting and risk management. Full article

Accurately predicting stock prices remains a challenging task due to the volatile and complex nature of financial markets. In this study, we propose a novel hybrid deep learning framework that integrates a large language model (LLM), a Linear Transformer (LT), and a Convolutional Neural Network (CNN) to enhance stock price prediction using solely historical market data. The framework leverages the LLM as a professional financial analyst to perform daily technical analysis. The technical indicators, including moving averages (MAs), relative strength index (RSI), and Bollinger Bands (BBs), are calculated directly from historical stock data. These indicators are then analyzed by the LLM, generating descriptive textual summaries. The textual summaries are further transformed into vector representations using FinBERT, a pre-trained financial language model, to enhance the dataset with contextual insights. The FinBERT embeddings are integrated with features from two additional branches: the Linear Transformer branch, which captures long-term dependencies in time-series stock data through a linearized self-attention mechanism, and the CNN branch, which extracts spatial features from visual representations of stock chart data. The combined features from these three modalities are then processed by a Feedforward Neural Network (FNN) for final stock price prediction. Experimental results on the S&P 500 dataset demonstrate that the proposed framework significantly improves stock prediction accuracy by effectively capturing temporal, spatial, and contextual dependencies in the data. This multimodal approach highlights the importance of integrating advanced technical analysis with deep learning architectures for enhanced financial forecasting. Full article

The hypervapotron structure was considered to be a feasible configuration to meet the high heat-dissipating requirement of divertors in nuclear fusion devices. In this work, symmetric CuCrZr-based transverse microchannels (TMHC) and longitudinal microchannels (LMHC) with an integrated hypervapotron channel were proposed and manufactured, and subcooled flow boiling experiments were conducted using deionized water at an inlet temperature of 20 °C with a traditional flat-type hypervapotron channel (FHC) for comparison. The LMHC and TMHC obtained lower wall temperatures than the FHC for all conditions, and the TMHC yielded the lowest temperatures. The heat transfer coefficients of the LMHC and TMHC outperformed the FHC due to the enlarged heat transfer area, and the TMHC had the greatest heat transfer coefficient (maximumly increased by 132% compared to the FHC) because the transverse-arranged microchannels were conductive, promoting the convection and liquid replenishment ability by introducing branch flow between fins; however, the microchannels of the LMHC were insensible to flow velocities due to the block effect of longitudinal microchannels. The LMHC obtained the largest pressure drop, and the pressure drop for the FHC and TMHC were comparable since the transverse-placed microchannels had little effect on frictional pressure loss. The TMHC attained the greatest comprehensive thermohydraulic performance which might bring significant insight to the structural design of hypervapotron devices. Full article

Face recognition in general scenarios has been saturated in recent years, but there is still room to enhance model performance in extreme scenarios and fairness situations. Inspired by the successful application of Transformer and ConvNet in computer vision, we propose a FIN-Block, which gives a more flexible composition paradigm for building a novel pure convolution model and provides a foundation for constructing a new framework for general face recognition in both extreme scenarios and fairness situations. FIN-Block-A uses a combination of stacked large-size convolution kernels and parallel convolution branches to ensure a large spatial receptive field while improving the module’s deep feature embedding and extraction capabilities. FIN-Block-B takes advantage of stacked orthogonal convolution kernels and parallel branches to balance model size and performance. By applying FIN-Block with an adapted convolution kernel size in different stages, we built a reasonable and novel framework Face-Inception-Net, and the performance of the model is highly competitive with ConvNeXt and InceptionNeXt. The models were trained on CASIA-WebFace and MS-wo-RFW databases and evaluated on 14 mainstream benchmarks, including LFW, extreme scene, and fairness test sets. The proposed Face-Inception-Net achieved the highest average TAR@FAR0.001 of 95.9% in all used benchmarks, fully demonstrating effectiveness and generality in various scenarios. Full article

The lowland tapir is one of four species belonging to the Tapiridae family of the Ceratomorpha suborder, similar to Rhinocerotidae. This study describes anatomy with morphometry, histology (hematoxylin and eosin, Masson-Goldner trichrome, Movat pentachrome, mucicarmine, picro-Mallory trichrome) and histochemistry (PAS, AB pH 1.0, AB pH 2.5; AB pH2.5/PAS and HDI) of the upper and lower eyelids, and superficial gland of the third eyelid with the third eyelid, deep gland of the third eyelid, and lacrimal gland. The aim of the work is to show the features of the above-mentioned structures typical only for Tapiridae, as well as to show the presence of similarities and differences between the families forming the order Perissodactyla. The eyelashes on the upper eyelid were long, while those of the lower eyelid were short and much less prominent. In the upper and lower eyelid sebaceous glands, a characteristic simple alveolar gland producing a mucus-like secretion and poorly developed tarsal glands were observed. The marginal zone of the posterior surface of the eyelids was covered by stratified columnar epithelium with 18–21 layers of nucleated cells, while the bulbar zone of these surfaces was covered by cubic multilayer epithelium with 6–11 non-keratinized layers of cells and with sparse goblet cells. In only lower eyelids, numerous lymphoid nodules, diffuse lymphocytes and high endothelial venules were observed. The superficial gland was an acinar complex which secreted mucous and contained plasma cells within the interlobular and interlobular connective tissue. The upper and lower branches of the third eyelid were the shape of a bent “caudal fin” and were composed of hyaline cartilage, and they contained conjunctiva associated lymphoid tissue (CALT). The deep gland was also an acinar complex producing a serous character and having numerous diffuse lymphocytes. The lacrimal gland was an acinar complex producing seromucous secretions and had numerous plasma cells located in the glandular interstitium. The results of our research indicate that the features of the anatomy of the eyelids and orbital region in the lowland tapir are also typical of the family Tapiridae, but also have features common to the families Equidae and Rhinocerotidae. We confirm the presence of poorly developed tarsal glands in both eyelids as well as presence of a palpebral part of the lacrimal gland in the upper eyelid, which is typical only to Tapirus terrestris. Full article

A new species of the genus Troglonectes is described based on specimens from a karst cave in Andong Town, Xincheng County, Liuzhou City, Guangxi, China. Troglonectes canlinensis sp. nov. can be distinguished from its congener species by the following combination of characteristics: eye degenerated into a black spot; whole body covered by scales, except for the head, throat, and abdomen; incomplete lateral line; forked caudal fin; 8–10 gill rakers on the first gill arch; 13–14 branched caudal fin rays; 8–9 branched dorsal fin rays; 5–6 anal fin rays; 9–10 pectoral fin rays; upper adipose keel depth mostly 1/2 of the caudal peduncle depth; and caudal fin forked. Full article

Owing to the recent increase in mobile banking customers, studies exploring self-service channels and customer responses as distribution channels in the retail banking industry are also rapidly expanding. Moreover, with the emergence of big data and a series of artificial intelligence (AI) technologies, customer pattern analysis using deep learning, insurance fraud prevention, software development and various types of blockchain-based FinTech technologies, offline banks are disappearing. Accordingly, many commercial banks are attempting to find technological alternatives. However, maintaining a profitable bank branch is a crucial factor in the relationship between service quality and customer satisfaction because excellent service quality prevents existing customers from leaving. This study sought to quantitatively prove the change in customer service quality and profit due to the introduction of technology in the financial industry. We microscopically compared the effects between bank branch closures and changes in net profit using a time-series analysis. Specifically, we quantitatively analyzed actual customer attrition behavior with a time-series analysis across the three quarters before and after the closure of 88 branches of major commercial banks in South Korea in the Seoul metropolitan area and nearby cities. The findings prove that branch closures and multi-channel effects in the financial sector are gradually being resolved through immediate technology acceptance, contrary to popular concern. Full article

In the dynamic and unstructured environment where horticultural crops grow, obstacles and interference frequently occur but are rarely addressed, which poses significant challenges for robotic harvesting. This work proposed a tactile-enabled robotic grasping method that combines deep learning, tactile sensing, and soft robots. By integrating fin-ray fingers with embedded tactile sensing arrays and customized perception algorithms, the robot gains the ability to sense and handle branch interference during the harvesting process and thus reduce potential mechanical fruit damage. Through experimental validations, an overall 83.3–87.0% grasping status detection success rate, and a promising interference handling method have been demonstrated. The proposed grasping method can also be extended to broader robotic grasping applications wherever undesirable foreign object intrusion needs to be addressed. Full article

Analytical, computational and experimental investigations directed at improving the performance of latent heat thermal energy storage systems that utilize high thermal conductivity fins in direct contact with phase change materials are reviewed. Researchers have focused on waste heat recovery, thermal management of buildings/computing platforms/photovoltaics/satellites and energy storage for solar thermal applications. Aluminum (including various alloys), brass, bronze, copper, PVC, stainless steel and steel were the adopted fin materials. Capric-palmitic acid, chloride mixtures, dodecanoic acid, erythritol, fluorides, lauric acid, naphthalene, nitrite and nitrate mixtures, paraffins, potassium nitrate, salt hydrates, sodium hydrate, stearic acid, sulfur, water and xylitol have been the adopted fusible materials (melting or fusion temperature T_m range of −129.6 to 767 °C). Melting and solidification processes subject to different heat exchange operating conditions were investigated. Studies of thawing have highlighted the marked role of natural convection, exhibiting that realizing thermally unstable fluid layers promote mixing and expedited melting. Performance of the storage system in terms of the hastened charge/discharge time was strongly affected by the number of fins (or fin-pitch) and fin length, in comparison to fin thickness and fin orientation. Strength of natural convection, which is well-known to play an important role on thawing, is diminished by introduction of fins. Consequently, a designer must consider suppression of buoyancy and the extent of sacrificed PCM in selecting the optimum positions and orientation of the fins. Complex fin shapes featuring branching arrangements, crosses, Y-shapes, etc. are widely replacing simple planar fins, satisfying the challenge of forming short-distance conducting pathways linking the temperature extremes of the storage system. Full article

Latent heat thermal energy storage (LHTES) technology can alleviate the mismatch between the supply and demand of solar energy and industrial waste heat, but the low thermal conductivity of phase change materials (PCMs) is an issue that needs to be solved. In this work, the effects of the bifurcated fins on melting and solidification are studied, and local and global entropy generation are discussed. The radial lag time and the circumferential lag time were defined to evaluate thermal penetration and thermal uniformity. Subsequently, a novel arc-shaped fin configuration was proposed to further enhance the heat transfer. The results showed that attaching the bifurcated fins could effectively reduce the global entropy generation. Increasing the trunk fin length was beneficial to enhance the thermal uniformity and promote the melting process, while increasing the branch fin was more effective in the solidification process. Overall, thermal uniformity determined the phase change process. More importantly, the concentric arc-shaped fins significantly reduced the heat transfer hysteresis region, showed better thermal performance than straights fins, and the energy storage and release time were reduced by 52.7% and 51.6%, respectively. Full article

Fish have colonized nearly all aquatic niches, making them an invaluable resource to understand vertebrate adaptation and gene family evolution, including the evolution of complex neural networks and modulatory neurotransmitter pathways. Among ancient regulatory molecules, the gaseous messenger nitric oxide (NO) is involved in a wide range of biological processes. Because of its short half-life, the modulatory capability of NO is strictly related to the local activity of nitric oxide synthases (Nos), enzymes that synthesize NO from L-arginine, making the localization of Nos mRNAs a reliable indirect proxy for the location of NO action domains, targets, and effectors. Within the diversified actinopterygian nos paralogs, nos1 (alias nnos) is ubiquitously present as a single copy gene across the gnathostome lineage, making it an ideal candidate for comparative studies. To investigate variations in the NO system across ray-finned fish phylogeny, we compared nos1 expression patterns during the development of two well-established experimental teleosts (zebrafish and medaka) with an early branching holostean (spotted gar), an important evolutionary bridge between teleosts and tetrapods. Data reported here highlight both conserved expression domains and species-specific nos1 territories, confirming the ancestry of this signaling system and expanding the number of biological processes implicated in NO activities. Full article

Using phase change materials (PCMs) in energy storage systems provides various advantages such as energy storage at a nearly constant temperature and higher energy density. In this study, we aimed to conduct a numerical simulation for augmenting a PCM’s melting performance within multiple tubes, including branched fins. The suspension contained Al₂O₃/n-octadecane paraffin, and four cases were considered based on a number of heated fins. A numerical algorithm based on the finite element method (FEM) was applied to solve the dimensionless governing system. The average liquid fraction was computed over the considered flow area. The key parameters are the time parameter ($100 \le t\le 600 \mathrm{s})$ and the nanoparticles’ volume fraction ($0\%\le \phi \le 8\%)$. The major outcomes revealed that the flow structures, the irreversibility of the system, and the melting process can be controlled by increasing/decreasing number of the heated fins. Additionally, case four, in which eight heated fins were considered, produced the largest average liquid fraction values. Full article

In stepped-sine testing of strongly nonlinear structures with the classical force-control strategy, corrective force perturbations of a standard controller used to capture the reference signal in the proximity of turning points of frequency response curves may often lead to a premature jump before reaching the actual resonance peak. Accordingly, a classical force-control approach is not suitable to identify backbone curves of strongly nonlinear structures. This paper shows that currently available commercial modal test equipment can accurately identify backbone curves of strongly nonlinear structures by using Response-Controlled stepped-sine Testing (RCT) and the Harmonic Force Surface (HFS) concept, both recently proposed by the authors. These methods can be applied to systems where there are many nonlinearities at several different (and even unknown) locations. However, these techniques are not applicable to systems where internal resonances occur. In RCT, the displacement amplitude of the driving point, rather than the amplitude of the applied force, is kept constant during the stepped-sine testing. Spectra of the harmonic excitation force measured at several different displacement amplitude levels are used to build up a smooth HFS. Isocurves of constant amplitude forcing on the HFS lead to constant-force frequency response curves with accurately measured turning points and unstable branches (if there are any), which makes it possible to identify backbone curves of strongly nonlinear structures experimentally. The validation of the proposed approach is demonstrated with numerical and experimental case studies. A five degree-of-freedom (DOF) lumped system with five cubic stiffness elements, which create strong conservative nonlinearity, is used in the numerical example. Experimental case studies consist of a cantilever beam and a control fin actuation mechanism of a real missile structure. The cantilever beam is supported at its free-end by two metal strips constrained at both ends to create strong stiffening nonlinearity. The control fin actuation mechanism exhibits very complex and strong nonlinearity due to backlash and friction. Full article

The financial landscape of sub-Sahara Africa is undergoing major changes due to the advent of FinTech, which has seen mobile payments boom in the region. This paper examines the salient role of mobile payments in traditional banks’ drive toward financial accessibility in sub-Sahara Africa by using panel econometric approaches that consider the issues of independencies among cross-sectional residuals. Using data from the World Development Index (WDI) 2011–2017 on 11 countries in the region, empirical results from cross-sectional dependence (CD) tests, panel unit root test, panel cointegration test, and the fully modified ordinary least squares (FMOLS) approach indicates that (i) the panel time series data are cross-sectionally independent, (ii) the variables have the same order of integration and are cointegrated, and (iii) growth in mobile payment transactions had a significant positive relationship with formal account ownership, the number of ATMs, and number of new bank branches in the long-run. The paper therefore confirms that the institutional structure of traditional banks that makes them competitive, irrespective of emerging disruptive technologies, has stimulated overall financial accessibility in the region leading to overall sustainable growth in the financial sector. We conclude the paper with feasible policy suggestions. Full article