Search Results (73)

This study evaluated the effects of locally sourced ingredient dietary, with or without supplementation of black soldier fly (Hermetia illucens; BSF) larvae, on laying hen welfare. A total of 150 Lohman White hens aged 30 weeks were assigned to three treatments over ten weeks: a standard corn–soybean diet (CONTROL), an alternative diet incorporating triticale, faba beans and rapeseed meal (ALTER), and the ALTER diet supplemented with 5% dried BSF larvae provided separately (ALTER + BSF). Welfare assessments included larvae consumption time, a novel object test, an avoidance distance test, body condition scoring, and ethological observation of natural behaviors. Hens fed ALTER diet initially showed increased incidence of comb pecking wounds, which declined over the trial, along with reduced morning grooming compared to the CONTROL group (p = 0.009). However, the ALTER diet significantly improved plumage cleanliness (p < 0.001). Supplementation with BSF larvae partially mitigated early stress responses, maintained plumage cleanliness, and improved exploratory behavior and habituation to novelty (p < 0.001). Hens showed sustained and increased motivation to consume BSF larvae with an average consumption time of 5.5 min. Additionally, BSF supplementation was associated with increased resting and the emergence of dustbathing behavior during the afternoon (p < 0.05). No aggressive behaviors were observed, and no significant dietary effects were found for human fearfulness throughout the trial. In conclusion, dried BSF larvae can serve as effective environmental enrichment, improving hens’ adaptability to locally sourced diets in rural farming systems. Full article

Dual-comb ranging enables rapid, high-precision absolute distance measurements, but its performance is constrained by intrinsic phase noise, which induces temporal jitter and degrades pulse-to-pulse mutual coherence. Here, we propose a deep learning network Wavelet-Fused DenseNet (WFDNet) for hardware-free computational phase correction in dual-comb ranging. Through integration of complex wavelet decomposition and physics-guided feature encoding, the network, trained on model-generated data, can directly extract multi-scale time–frequency features to correct phase distortions and recover temporal coherence of the signals. Results from both simulated and experimental scenarios reveal that the approach can effectively suppress spectral noise and retrieve robust and unambiguous phases information, achieving high ranging accuracy with a standard deviation of 0.6 μm. Full article

Regular physical activity is essential for physical and mental health, yet participation among Norwegian university students remains below nationally recommended levels. This study explored facilitators and barriers for physical activity among first-year students, using the COM-B model as a conceptual framework. Fifteen physically active first-year students from two higher education campuses in Bodø were interviewed in spring 2025, and the data were analysed using inductive thematic analysis. Analysis showed that students’ activity behaviours were shaped by a dynamic interaction between physical and psychological capabilities, particularly in relation to technical competence, previous injuries, and self-regulation strategies. Opportunity-related factors—such as time constraints, financial limitations, commuting distance, and access to facilities—substantially influenced students’ ability to maintain regular activity, while social support from friends, family, and peers functioned as an important facilitator. Motivation emerged through a mixture of automatic processes—including stress reduction, enjoyment, and habits—and reflective processes such as goal-setting and health-oriented decision-making. For students in physically demanding study programmes, professional identity and body-related expectations also contributed to their engagement. Overall, this study highlights the need for institutional strategies that simultaneously address structural, social, and psychological factors to support sustainable physical activity habits during the transition to university life. Full article

Chain topology offers a chemistry-preserving route to tune block copolymer (BCP) self-assembly by modifying intrachain correlations and relaxation pathways without changing monomer interactions. Here, we perform a unit-matched comparison of four lamella-forming AB architectures reconstructed from an identical constitutive diblock unit ($N_0$): a linear diblock (DB), a linear multiblock (MB), a comb-like architecture (CB), and a star-like architecture (SB). Using dynamical density functional theory (DDFT), we quantify topology-dependent bulk ordering thresholds and show that architectural reconfiguration systematically stabilizes the ordered phase, reducing the order–disorder transition relative to DB (MB/CB/SB $\approx 0.793/0.762/0.752$ of the diblock value), in semi-quantitative agreement with random phase approximation (RPA) spinodal trends. We also compare topology-dependent directed self-assembly in a common trench geometry under matched reduced quench depth $\Delta \left(\chi N_0\right)=\chi N_0-{\left(\chi N_0\right)}_{\mathrm{ODT}}$, thereby isolating kinetic differences at comparable thermodynamic distance from bulk ordering. A Fourier-based alignment order parameter $\alpha \left(t\right)$ reveals sigmoidal alignment kinetics over decades in time and is well captured by a logistic form in $lnt$, enabling compact descriptors ($t_{50}$, $t_{90}$, and a steepness parameter k) that separate alignment onset from late-stage defect annihilation, while selective sidewalls robustly template sidewall-parallel lamellae across all topologies, the late-stage kinetics remain strongly connectivity dependent and can exhibit long-tailed completion associated with slow late-stage defect annihilation. These results demonstrate a dual role of topology in DSA: lowering the segregation strength required for bulk ordering while reshaping defect-mediated alignment pathways under confinement. Full article

Local Lorentz Invariance is one of the fundamental postulates of General Relativity, making its experimental verification of paramount importance. Given that various frontier theoretical models predict potential symmetry breaking, the Standard Model Extension framework has been established to systematically study such phenomena. Within the Standard Model Extension gravitational sector, the high-order Lorentz-violating terms with mass dimension $d=6$ exhibit a rapid signal decay with distance, providing a distinct detection advantage in short-range gravity experiments. This work is dedicated to optimizing the testing schemes for $d=6$ Lorentz-violating coefficients. Based on a high-precision torsion balance platform, we propose a novel scheme featuring a comb-stripe design. The improvements are twofold: first, the spatial orientation of the experimental apparatus is optimized to leverage the modulation effects of the Earth’s rotation, thereby enhancing the capability to distinguish and constrain different violation parameters; second, the test and source masses are reconfigured into specifically designed stripe patterns to significantly amplify the fringe-field signals sensitive to Lorentz-violating effects. This paper systematically elaborates on the theoretical foundation and design principles of the new scheme. By performing a detailed comparison of the constraint potentials of various stripe configurations, the five-stripe geometry is identified as the optimal experimental configuration. This study provides a new experimental methodology for exploring physics beyond the Standard Model at higher levels of precision. Full article

This study addresses the issue of cross-interference that occurs when locked continuous light and signal photons are collinear during interferometer measurements. To tackle this, a temperature-controlled Fabry–Pérot cavity filter with a heterogeneous cascaded structure is proposed and applied. The system consists of six filtering stages, created by designing Fabry–Pérot cavities of three different lengths, each used twice (to match optical frequencies), along with temperature control settings. By applying differentiated linewidth regulation, the approach effectively suppresses interference from locked light while significantly enhancing the signal-to-noise ratio in photon detection. This method overcomes the challenge of interference from same-frequency noise photons in atomic ensemble-entangled sources, achieving a noise–photon extinction ratio on the order of 10⁶ and surpassing the frequency resolution limit of a single filter. Experimental results demonstrate that the system reduces the noise floor in the detection optical path to below 10⁻¹⁶, while maintaining a photon transmission efficiency above 53% for the signal. This technology effectively addresses key challenges in noise suppression and photon state fidelity optimization in optical fiber quantum communication, offering a scalable frequency–photon noise filtering solution for long-distance quantum communication. Furthermore, its multi-parameter cooperative filtering mechanism holds broad potential applications in areas such as quantum storage and optical frequency combs. Full article

Urbanization and traffic congestion caused by the surge in car ownership have exacerbated energy consumption and carbon emissions, and dynamic traffic flow prediction and energy-saving route planning have become the key to solving this problem. Dynamic traffic flow prediction accurately captures the spatio-temporal changes of traffic flow through advanced algorithms and models, providing prospective information for traffic management and travel decision-making. Energy-saving route planning optimizes travel routes based on prediction results, reduces the time vehicles spend on congested road sections, thereby reducing fuel consumption and exhaust emissions. However, there are still many shortcomings in the current relevant research, and the existing research is mostly isolated and applies a single model, and there is a lack of systematic comparison of the adaptability, generalization ability and fusion potential of different models in various scenarios, and the advantages of heterogeneous graph neural networks in integrating multi-source heterogeneous data in traffic have not been brought into play. This paper systematically reviews the relevant global studies from 2020 to 2025, focuses on the integration path of dynamic traffic flow prediction methods and energy-saving route planning, and reveals the advantages of LSTM, graph neural network and other models in capturing spatiotemporal features by combing the application of statistical models, machine learning, deep learning and mixed methods in traffic forecasting, and comparing their performance with RMSE, MAPE and other indicators, and points out that the potential of heterogeneous graph neural networks in multi-source heterogeneous data integration has not been fully explored. Aiming at the problem of disconnection between traffic prediction and path planning, an integrated framework is constructed, and the real-time prediction results are integrated into path algorithms such as A* and Dijkstra through multi-objective cost functions to balance distance, time and energy consumption optimization. Finally, the challenges of data quality, algorithm efficiency, and multimodal adaptation are analyzed, and the development direction of standardized evaluation platform and open source toolkit is proposed, providing theoretical support and practical path for the sustainable development of intelligent transportation systems. Full article

Quantum secret sharing (QSS) faces inherent limitations in scaling to multi-user networks due to excess noise introduced by highly asymmetric beam splitters (HABSs) in chain-structured topologies. To overcome this challenge, we propose an optical frequency comb-based continuous-variable QSS (OFC CV-QSS) scheme that establishes parallel frequency channels between users and the dealer via OFC-generated multi-wavelength carriers. By replacing the chain-structured links with dedicated frequency channels and integrating the Chinese remainder theorem (CRT) with a decentralized architecture, our design eliminates excess noise from all users using HABS while providing mathematical- and physical-layer security. Simulation results demonstrate that the scheme achieves a more than 50% improvement in maximum transmission distance compared to chain-based QSS, with significantly slower performance degradation as users scale to 20. Numerical simulations confirm the feasibility of this theoretical framework for multi-user quantum networks, offering dual-layer confidentiality without compromising key rates. Full article

Terahertz (THz) frequencies, spanning from 0.1 to 1 THz, are poised to play a pivotal role in the development of future 6G wireless communication systems. These systems aim to utilize photonic technologies to enable ultra-high data rates—on the order of terabits per second—while maintaining low latency and high efficiency. In this work, we present a novel photonic method for generating sub-THz vector signals within the THz band, employing a semiconductor optical amplifier (SOA) and phase modulator (PM) to create an optical frequency comb, combined with in-phase and quadrature (IQ) modulation techniques. We demonstrate, both through simulation and experimental setup, the generation and successful transmission of a 0.1 THz vector. The process involves driving the PM with a 12.5 GHz radio frequency signal to produce the optical comb; then, heterodyne beating in a uni-traveling carrier photodiode (UTC-PD) generates the 0.1 THz radio frequency signal. This signal is transmitted over distances of up to 30 km using single-mode fiber. The resulting 0.1 THz electrical vector signal, modulated with quadrature phase shift keying (QPSK), achieves a bit error ratio (BER) below the hard-decision forward error correction (HD-FEC) threshold of ${3.8 \times 10}^{-3}$. To the best of our knowledge, this is the first experimental demonstration of a 0.1 THz photonic vector THz wave based on an SOA and a simple PM-driven optical frequency comb. Full article

This study was conducted to objectively evaluate the degree of detangling needed to develop the effectiveness of cosmetic hair ingredients to prevent hair tangles. To evaluate the degree of hair tangling, the frictional force applied when combing the hair was measured. The tooth spacing of the comb used in the evaluation was examined, and it was confirmed that the 4 mm interval comb was suitable as there was a large difference in combability between different treatments and the deviation was small. To create samples to standardize hair tangles, spinning 25 cm or more of wet hair on a spinner for 5 min was found to be best for observing differences between treatments. In the case of hair shorter than 25 cm, tangles did not occur even when spun using a tool, but a suitable sample for evaluating tangles was obtained by rubbing the hair by hand about 15 times. When testing combability, the distance the comb moves until it reaches 9.8 N is considered to be proportional to the detangling efficacy, and the degree of tangling is evaluated based on the section detangling rate, which is the distance the comb travels to reach 9.8 N divided by the total tress length. As a result of evaluating the contact angle of tangled hair using an atomic force microscope (AFM) and a scanning electron microscope (SEM), it was found that the contact angle of the cuticle surface for the tangled part was larger than that of the straight part and the cuticle was damaged. After immersing tangled hair in rice bran extract containing six OH groups, the contact angle changed from 103° to 95°, which is the level of the straight part, and an increase in the section detangling rate of the hair was observed. As a result, it was suggested that the detangling efficacy could be evaluated by applying this evaluation method using the section detangling rate. Full article

Optical frequency combs have been widely used in spectrum analysis, coherent optical communication, and accurate distance measurement. We propose a straightforward method to improve the flatness of optical frequency combs. First, we derived the output of the optical signal for the configuration of a cascaded MZM and two PMs. Second, we identified the parameter value when the flatness was optimal after traversing different parameter spaces. The optimal flatness conditions could be automatically determined from an existing sample dataset by using neural networks and Bayesian optimization, which significantly reduced the calculation cost. Furthermore, a broad spectrum and low power consumption were also achieved. Finally, the generated optical frequency comb signal was divided into eight carriers with 50 GHz intervals, and the optical transmission system was verified by applying a 16-QAM modulation of 40 GBaud/s to each channel. The constellation diagram proved the feasibility of this optical comb generation scheme. Full article

Atmospheric particulate pollution in China’s megacities has heightened public concern over air quality, highlighting the need for precise identification of urban pollution characteristics and pollutant transport mechanisms to enable effective control and mitigation. In this study, a new method combing the High Accuracy Surface Modeling (HASM) and Multiscale Geographically Weighted Regression (MGWR) was proposed to derive seasonal high spatial resolution PM_2.5 concentrations. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) was applied to analyze the seasonal spatial variations, transport pathways, and potential sources of PM_2.5 concentrations across China’s four megacities: Beijing, Shanghai, Xi’an, and Chengdu. The result indicates that: (1) the proposed method outperformed Kriging, inverse distance weighting (IDW), and HASM, with coefficient of determination values ranging from 0.91 to 0.94, and root mean square error values ranging from 1.98 to 2.43 µg/m³, respectively; (2) all cities show a similar seasonal pattern, with PM_2.5 concentrations highest in winter, followed by spring, autumn, and summer; Beijing has higher concentrations in the south, Shanghai and Xi’an in the west, and Chengdu in central urban areas, decreasing toward the rural area; (3) potential source contribution function and concentration weighted trajectory analysis indicate that Beijing’s main potential PM_2.5 sources are in Hebei Province (during winter, spring, and autumn), Shanghai’s are in the Yellow Sea and the East China Sea, Xi’an’s are in Southern Shaanxi Province, and Chengdu’s are in Northeastern and Southern Sichuan Province, with all cities experiencing higher impacts in winter; (4) there is a negative correlation between precipitation, air temperature, and seasonal PM_2.5 levels, with anthropogenic emissions sources such as industry combustion, power plants, residential combustion, and transportation significantly impact on seasonal PM_2.5 pollution. Full article

The rapid increase in Internet usage has led to a growing demand for bandwidth. Optical microring resonators (MRRs) are emerging as a promising solution to meet this need. MRRs generate optical frequency combs (OFCs) that provide multiple wavelengths with high phase coherence, enabling communication via wavelength division multiplexing (WDM). Spectrum allocation methods, such as the Routing, Modulation Level, and Spectrum Assignment (RMLSA) approach, play a crucial role in executing this strategy efficiently. While current algorithms have improved allocation efficiency, further development is necessary to optimize network performance. This paper presents an integer linear programming (ILP)-based method for network resource allocation, aiming to maximize the number request and the bandwidth assigned to each. The proposed approach offers a flexible cost function that prioritizes system constraints such as transmission distance and bandwidth requirements, resulting in significant improvements to the bandwidth blocking rate (BBR). By integrating multilevel modulation and using wavelengths generated by MRRs, this method efficiently handles up to 1075 requests, achieving a BBR of zero. This dynamic and adaptable allocation strategy ensures optimal resource utilization, enhancing overall network performance. Full article

Gottschelia, collected for the first time in Indochina, inspired an attempt to review the genus phylogeny to identify a more precise position of Indochinese plants. The genetic distance between African and Asian populations of G. schizopleura sensu lato was confirmed. The two groups should be treated as different species. A new combination, G. microphylla comb. nov., has been proposed for Asian plants. Aside from molecular genetics, distinguishing this species from the presumable strictly African G. schizopleura is also possible by morphological characteristics, as well as by its distribution. At the same time, at least three groups are distinguished among Asian haplotypes of G. microphylla, each of which can be interpreted as a species or, at least, subspecies. A morphological description, intravital photographs of the general habitat, and details of the morphological structures are provided. The position of Gottschelia in the phylogenetic schema of Jungermanniales does not allow us to attribute it to any of the known families and forces us to describe a new family, Gottscheliaceae, which is phylogenetically somewhat related to the Chaetophyllopsidaceae re-evaluated here and very different from Gottscheliaceae morphologically. Full article

Absolute distance measurements based on optical frequency combs (OFCs) have greatly promoted advances in both science and technology, owing to the high precision, large non-ambiguity range (NAR), and a high update rate. However, cyclic error, which is extremely difficult to eliminate, reduces the linearity of measurement results. In this study, we quantitatively investigated the impact of cyclic error on absolute distance measurement using OFCs based on two types of interferometry: synthetic wavelength interferometry and single-wavelength interferometry. The numerical calculations indicate that selecting a suitable reference path length can minimize the impact of cyclic error when combining the two types of interferometry. Recommendations for selecting an appropriate synthetic wavelength to address the tradeoff between achieving a large NAR and minimizing the risk of failure when combining the two methods are provided. The results of this study are applicable not only in absolute distance measurements but also in other applications based on OFCs, such as surface profile, vibration analysis, etc. Full article