We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Synthetic Aperture Radar Interferometry (InSAR) is an active remote sensing method that uses repeated radar scans of the Earth's solid surface to measure relative deformation at centimeter precision over a wide swath. It has revolutionized our understanding of the earthquake cycle, volcanic eruptions, landslides, glacier flow, ice grounding lines, ground fluid injection/withdrawal, underground nuclear tests, and other applications requiring high spatial resolution measurements of ground deformation. This book examines the theory behind and the applications of InSAR for measuring surface deformation. The most recent generation of InSAR satellites have transformed the method from investigating 10's to 100's of SAR images to processing 1000's and 10,000's of images using a wide range of computer facilities. This book is intended for students and researchers in the physical sciences, particularly for those working in geophysics, natural hazards, space geodesy, and remote sensing. This title is also available as Open Access on Cambridge Core.
American silk moth, Antheraea polyphemus Cramer 1775 (Lepidoptera: Saturniidae), native to North America, has potential significance in sericulture for food consumption and silk production. To date, the phylogenetic relationship and divergence time of A. polyphemus with its Asian relatives remain unknown. To end these issues, two mitochondrial genomes (mitogenomes) of A. polyphemus from the USA and Canada respectively were determined. The mitogenomes of A. polyphemus from the USA and Canada were 15,346 and 15,345 bp in size, respectively, with only two transitions and five indels. The two mitogenomes both encoded typical mitochondrial 37 genes. No tandem repeat elements were identified in the A+T-rich region of A. polyphemus. The mitogenome-based phylogenetic analyses supported the placement of A. polyphemus within the genus Antheraea, and revealed the presence of two clades for eight Antheraea species used: one included A. polyphemus, A. assamensis Helfer, A. formosana Sonan and the other contained A. mylitta Drury, A. frithi Bouvier, A. yamamai Guérin-Méneville, A. proylei Jolly, and A. pernyi Guérin-Méneville. Mitogenome-based divergence time estimation further suggested that the dispersal of A. polyphemus from Asia into North America might have occurred during the Miocene Epoch (18.18 million years ago) across the Berling land bridge. This study reports the mitogenome of A. polyphemus that provides new insights into the phylogenetic relationship among Antheraea species and the origin of A. polyphemus.
Cryphodera guangdongensis n. sp. was collected from the soil and roots of Schima superba in Guangdong province, China. The new species is characterised by having a nearly spherical female, with dimensions of length × width = 532.3 (423.8–675.3) × 295.6 (160.0–381.2) μm, stylet length of 35.7 (31.1–42.1) μm, protruding vulval lips, a vulval slit measuring 54.2 (47.4–58.9) μm, an area between the vulva and anus that is flat to concave, and a vulva–anus distance 49.3 (41.1–57.6) μm. The male features two lip annules, a stylet length of 31.7 (27.4–34.8) μm and basal knobs that are slightly projecting anteriorly, while lateral field is areolated with three incisures and spicules length of 27.1 (23.7–31.0) μm. The second stage juvenile is characterised by a body length of 506.1 (441.8–564.4) μm long, two to three lip annules, a stylet length 31.2 (29.7–33.2) μm which is well developed, basal knobs projecting anteriorly, a lateral field that is areolate with three incisures, and a narrow rounded tail measuring 63.2 (54.2–71.3) μm long, with a hyaline region of 35.6 (27.4–56.6) μm long that is longer than the stylet. Based on morphology and morphometrics, the new species is closely related to C. sinensis and C. japonicum within the genus Cryphodera. The phylogenetic trees constructed based on the ITS-rRNA, 28S-rRNA D2–D3 region, and the partial COI gene sequences indicate that the new species clusters with other Cryphodera species but maintains in a separated subgroup. A key to the species of the genus Cryphodera is also provided in this study.
The interaction of helminth infections with type 2 diabetes (T2D) has been a major area of research in the past few years. This paper, therefore, focuses on the systematic review of the effects of helminthic infections on metabolism and immune regulation related to T2D, with mechanisms through which both direct and indirect effects are mediated. Specifically, the possible therapeutic role of helminths in T2D management, probably mediated through the modulation of host metabolic pathways and immune responses, is of special interest. This paper discusses the current possibilities for translating helminth therapy from basic laboratory research to clinical application, as well as existing and future challenges. Although preliminary studies suggest the potential for helminth therapy for T2D patients, their safety and efficacy still need to be confirmed by larger-scale clinical studies.
To address the problems of accuracy degradation, localization drift, and even failure of Simultaneous Localization and Mapping (SLAM) algorithms in unstructured environments with sparse geometric features, such as outdoor parks, highways, and urban roads, a multi-metric light detection and ranging (LiDAR) SLAM system based on the fusion of geometric and intensity features is proposed. Firstly, an adaptive method for extracting multiple types of geometric features and salient intensity features is proposed to address the issue of insufficient sparse feature extraction. In addition to extracting traditional edge and planar features, vertex features are also extracted to fully utilize the geometric information, and intensity edge features are extracted in areas with significant intensity changes to increase multi-level perception of the environment. Secondly, in the state estimation, a multi-metric error estimation method based on point-to-point, point-to-line, and point-to-plane is used, and a two-step decoupling strategy is employed to enhance pose estimation accuracy. Finally, qualitative and quantitative experiments on public datasets demonstrate that compared to state-of-the-art pure geometric and intensity-assisted LiDAR SLAM algorithms, our proposed algorithm achieves superior localization accuracy and mapping clarity, with an ATE accuracy improvement of 28.93% and real-time performance of up to 62.9 ms. Additionally, test conducted in real campus environments further validates the effectiveness of our approach in complex, unstructured scenarios.
The ban on antibiotics as feed additives requires modern intensive farming with more comprehensive diseases control approaches. Currently, synbiotics serve as promising alternatives to enhance growth performance and improve health in the poultry industry. In this research, we investigated beneficial effects of Lactobacillus reuteri (LR) with its combination of gluco-oligosaccharides (GlcOS) supplementation on growth performance and intestinal health of broilers. A total of 900 1-day-old male Lingnan yellow-feather broilers were randomly allocated into the control group (CON group, and two experimental groups feeding basal diet supplementing LR (LR group) and its combination with GlcOS (RG group), respectively. The findings indicated beneficial effects of growth performance in experimental groups (LR and RG groups), as evidenced by decreasing the feed-to-gain ratio (F/G) in both experimental groups (P < 0.05) and increasing the average daily gain (ADG) in the RG group (P < 0.05). Simultaneously, both experimental groups increased the villus height/crypt depth ratio (VH:CD) (P < 0.001). Furthermore, the RG group showed increased activity of digestive enzymes (P < 0.05) and upregulated mRNA expression of tight junction protein and transportation protein (P < 0.05), while decreased the serum levels of d-lactic acid and diamine oxidase (P < 0.05), suggesting the improvement of the nutrient digestion and absorption, as well as the mucosal barrier integrity. Moreover, increased abundance of beneficial bacteria, including Bacteroides, Muribaculaceae and Prevotellaceae_UCG-001 (P < 0.05), leading to a finely altered gut microbiome and metabolome. Collectively, the findings of this research revealed that dietary supplemented LR and its combination with GlcOS could enhance the intestinal morphology, digestion, absorption and barrier function, and improve the cecal microbiota structure and metabolic function finally achieving the effect of improving growth performance of broilers. Overall, the effect of the combination of LR and GlcOS was synergistic, providing a future alternative to antibiotics as growth promoter.
The NutriLight system presents a novel dietary approach designed to enhance health communication, promote sustainable eating habits, and address limitations in existing dietary patterns. Using a traffic light scoring system, it simplifies dietary recommendations, making them more accessible and adaptable across diverse populations. Unlike rigid diets, NutriLight categorises foods into green, yellow, and red groups, encouraging balance rather than restriction. This flexibility allows for cultural adaptations, ensuring relevance in different dietary contexts while supporting planetary health. Additionally, NutriLight mitigates the risk of nutrient deficiencies by emphasising whole, minimally processed foods and reducing overconsumption of unhealthy options. While promising, its effectiveness depends on proper implementation, localised adaptation, and long-term evaluation to confirm its health benefits. By bridging the gap between nutritional science and practical application, NutriLight has the potential to serve as an effective tool in public health nutrition, fostering healthier and more sustainable dietary choices worldwide.
Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilise machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicentre cohort study including hospitalised oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined as a positive diagnosis of malnutrition upon patient admission which turned negative one month later. Time-series data on body weight and skeletal muscle were modelled using a long short-term memory architecture to predict RM. The model was named as WAL-net, and its performance, explainability, clinical relevance and generalisability were evaluated. We investigated 4254 patients with cancer-associated malnutrition (discovery set = 2977, test set = 1277). There were 2783 men and 1471 women (median age = 61 years). RM was identified in 754 (17·7 %) patients. RM/non-RM groups showed distinct patterns of weight and muscle dynamics, and RM was negatively correlated to the progressive stages of cancer cachexia (r = –0·340, P < 0·001). WAL-net was the state-of-the-art model among all ML algorithms evaluated, demonstrating favourable performance to predict RM in the test set (AUC = 0·924, 95 % CI = 0·904, 0·944) and an external validation set (n 798, AUC = 0·909, 95 % CI = 0·876, 0·943). Model-predicted RM using baseline information was associated with lower future risks of underweight, sarcopenia, performance status decline and progression of malnutrition (all P < 0·05). This study presents an explainable deep learning model, the WAL-net, for early identification of RM in patients with cancer. These findings might help the management of cancer-associated malnutrition to optimise patient outcomes in multidisciplinary cancer care.
Milk fat is a crucial component for evaluating the production performance and nutritional value of goat milk. Previous research indicated that the composition of ruminal microbiota plays a significant role in regulating milk fat percentage in ruminants. Thus, this study aimed to identify key ruminal microorganisms and blood metabolites relevant to milk fat synthesis in dairy goats as a mean to explore their role in regulating milk fat synthesis. Sixty clinically healthy Xinong Saanen dairy goats at mid-lactation and of similar body weight, and similar milk yield were used in a feeding study for 15 days. Based on daily milk yield of dairy goats and the results of milk component determination on the 1st and 8th days, five goats with the highest milk fat content (H group) and five goats with the lowest milk fat content (L group) were selected for further analysis. Before the morning feeding on the 15th day of the experiment, samples of milk, blood and ruminal fluid were collected for analyses of components, volatile fatty acids, microbiota and metabolites. Results revealed that acetate content in the rumen of H group was greater compared with L group. H group had abundant beneficial bacteria including Ruminococcaceae_UCG-005, Saccharofermentans, Ruminococcaceae-UCG-002 and Prevotellaceae_UCG-3, which were important for plant cellulose and hemicellulose degradation and immune regulation. Metabolomics analysis revealed H group had greater relative concentrations of 4-acetamidobutanoic acid and azelaic acid in serum, and had lower relative concentrations of Arginyl-Alanine, SM(d18:1/12:0) and DL-Tryptophan. These altered metabolites are involved in the sphingolipid signaling pathway, arginine and proline metabolism. Overall, this study identified key ruminal microorganisms and serum metabolites associated with milk fat synthesis in dairy goats. These findings offer insights for enhancing the quality of goat milk and contribute to a better understanding of the regulatory mechanisms involved in milk fat synthesis in dairy goats.
This paper presents a low-profile miniaturized dual-band antenna utilizing the quarter-mode substrate integrated waveguide (QMSIW) structure. The two modes of TE110 and TE220 of a single QMSIW structure are employed, enabling a dual-band operation. The frequency ratio between the two bands can be tuned by loading a capacitive structure, which is comprised of a capacitive-loaded patch and a short circuit post, inside the QMSIW structure. By introducing parasitic QMSIW structures through magnetic coupling, a dual-band antenna with enhanced bandwidths is achieved. The antenna has dimensions of smaller than 400 mm2 (0.048λL2) with a uniform height of 1.4 mm (0.016λL). Measurement results indicate that the −6 dB impedance bandwidths of the antennas can cover the 5G N78 (3.3–3.6 GHz) and N79 (4.8–5 GHz) bands, and the average efficiencies is better than −2.5 dB. To the authors’ knowledge, the proposed designs offer dual-wideband operation while having the smallest planar dimension compared to the previously reported antennas. Furthermore, an extended electric coupling dual-band antenna configuration is also described and measured, which achieves similar bandwidth extension as the proposed antenna.
Multidisciplinary research is deepening our understanding of high-altitude pastoralism on the Tibetan Plateau, but such studies also highlight a strong riverine bias in the location of excavated sites. In a move to address this skewing of the dataset, the authors propose the exploration of modern highland corrals with shovel testing and test excavations as a labour-efficient survey method, streamlined through the identification of potential sites from satellite imagery. Three prehistoric sites were successfully located using this method, the earliest dating to the first millennium BC, encouraging the reconsideration of current survey strategies in Tibet and other mountainous regions.
Clinical high risk for psychosis (CHR) is often managed with antipsychotic medications, but their effects on neurocognitive performance and clinical outcomes remain insufficiently explored. This study investigates the association between aripiprazole and olanzapine use and cognitive and clinical outcomes in CHR individuals, compared to those receiving no antipsychotic treatment.
Methods
A retrospective analysis was conducted on 127 participants from the Shanghai At Risk for Psychosis (SHARP) cohort, categorized into three groups: aripiprazole, olanzapine, and no antipsychotic treatment. Neurocognitive performance was evaluated using the MATRICS Consensus Cognitive Battery (MCCB), while clinical symptoms were assessed through the Structured Interview for Prodromal Syndromes (SIPS) at baseline, 8 weeks, and one year.
Results
The non-medicated group demonstrated greater improvements in cognitive performance, clinical symptoms, and functional outcomes compared to the medicated groups. Among the antipsychotic groups, aripiprazole was associated with better visual learning outcomes than olanzapine. Improvements in neurocognition correlated significantly with clinical symptom relief and overall functional gains at follow-up assessments.
Conclusions
These findings suggest potential associations between antipsychotic use and cognitive outcomes in CHR populations while recognizing that observed differences may reflect baseline illness severity rather than medication effects alone. Aripiprazole may offer specific advantages over olanzapine, underscoring the importance of individualized risk-benefit evaluations in treatment planning. Randomized controlled trials are needed to establish causality.
As a novel type of catalytic Janus micromotor (JM), a double-bubble-powered Janus micromotor has a distinct propulsion mechanism that is closely associated with the bubble coalescence in viscous liquids and corresponding flow physics. Based on high-speed camera and microscopic observation, we provide the first experimental results of the coalescence of two microbubbles near a JM. By performing experiments with a wide range of Ohnesorge numbers, we identify a universal scaling law of bubble coalescence, which shows a cross-over at dimensionless time $\tilde{t}$ = 1 from an inertially limited viscous regime with linear scaling to an inertial regime with 1/2 scaling. Due to the confinement from the nearby solid JM, we observe asymmetric neck growth and find the combined effect of the surface tension and viscosity. The bubble coalescence and detachment can result in a high propulsion speed of ∼0.25 m s−1 for the JM. We further characterise two contributions to the JM’s displacement propelled by the coalescing bubble: the counteraction from the liquid due to bubble deformation and the momentum transfer during bubble detachment. Our findings provide a better understanding of the flow dynamics and transport mechanism in micro- and nano-scale devices like the swimming microrobot and bubble-powered microrocket.
Carbon storage in saline aquifers is a prominent geological method for reducing CO2 emissions. However, salt precipitation within these aquifers can significantly impede CO2 injection efficiency. This study examines the mechanisms of salt precipitation during CO2 injection into fractured matrices using pore-scale numerical simulations informed by microfluidic experiments. The analysis of varying initial salt concentrations and injection rates revealed three distinct precipitation patterns, namely displacement, breakthrough and sealing, which were systematically mapped onto regime diagrams. These patterns arise from the interplay between dewetting and precipitation rates. An increase in reservoir porosity caused a shift in the precipitation pattern from sealing to displacement. By incorporating pore structure geometry parameters, the regime diagrams were adapted to account for varying reservoir porosities. In hydrophobic reservoirs, the precipitation pattern tended to favour displacement, as salt accumulation occurred more in larger pores than in pore throats, thereby reducing the risk of clogging. The numerical results demonstrated that increasing the gas injection rate or reducing the initial salt concentration significantly enhanced CO2 injection performance. Furthermore, identifying reservoirs with high hydrophobicity or large porosity is essential for optimising CO2 injection processes.
Hand, foot, and mouth disease (HFMD) shows spatiotemporal heterogeneity in China. A spatiotemporal filtering model was constructed and applied to HFMD data to explore the underlying spatiotemporal structure of the disease and determine the impact of different spatiotemporal weight matrices on the results. HFMD cases and covariate data in East China were collected between 2009 and 2015. The different spatiotemporal weight matrices formed by Rook, K-nearest neighbour (KNN; K = 1), distance, and second-order spatial weight matrices (SO-SWM) with first-order temporal weight matrices in contemporaneous and lagged forms were decomposed, and spatiotemporal filtering model was constructed by selecting eigenvectors according to MC and the AIC. We used MI, standard deviation of the regression coefficients, and five indices (AIC, BIC, DIC, R2, and MSE) to compare the spatiotemporal filtering model with a Bayesian spatiotemporal model. The eigenvectors effectively removed spatial correlation in the model residuals (Moran’s I < 0.2, p > 0.05). The Bayesian spatiotemporal model’s Rook weight matrix outperformed others. The spatiotemporal filtering model with SO-SWM was superior, as shown by lower AIC (92,029.60), BIC (92,681.20), and MSE (418,022.7) values, and higher R2 (0.56) value. All spatiotemporal contemporaneous structures outperformed the lagged structures. Additionally, eigenvector maps from the Rook and SO-SWM closely resembled incidence patterns of HFMD.
Spatial intensity modulation in amplified laser beams, particularly hot spots, critically constrains attainable pulse peak power due to the damage threshold limitations of four-grating compressors. This study demonstrates that the double-smoothing grating compressor (DSGC) configuration effectively suppresses modulation through directional beam smoothing. Our systematic investigation validated the double-smoothing effect through numerical simulations and experimental measurements, with comprehensive spatiotemporal analysis revealing excellent agreement between numerical and practical pulse characteristics. Crucially, the DSGC enables a 1.74 times energy output boost compared to conventional compressors. These findings establish the DSGC as a pivotal advancement for next-generation ultrahigh-power laser systems, providing a viable pathway toward hundreds of PW output through optimized spatial energy redistribution.
Mapping reviews (MRs) are crucial for identifying research gaps and enhancing evidence utilization. Despite their increasing use in health and social sciences, inconsistencies persist in both their conceptualization and reporting. This study aims to clarify the conceptual framework and gather reporting items from existing guidance and methodological studies. A comprehensive search was conducted across nine databases and 11 institutional websites, including documents up to January 2024. A total of 68 documents were included, addressing 24 MR terms and 55 definitions, with 39 documents discussing distinctions and overlaps among these terms. From the documents included, 28 reporting items were identified, covering all the steps of the process. Seven documents mentioned reporting on the title, four on the abstract, and 14 on the background. Ten methods-related items appeared in 56 documents, with the median number of documents supporting each item being 34 (interquartile range [IQR]: 27, 39). Four results-related items were mentioned in 18 documents (median: 14.5, IQR: 11.5, 16), and four discussion-related items appeared in 25 documents (median: 5.5, IQR: 3, 13). There was very little guidance about reporting conclusions, acknowledgments, author contributions, declarations of interest, and funding sources. This study proposes a draft 28-item reporting checklist for MRs and has identified terminologies and concepts used to describe MRs. These findings will first be used to inform a Delphi consensus process to develop reporting guidelines for MRs. Additionally, the checklist and definitions could be used to guide researchers in reporting high-quality MRs.
where $b\,:\, \mathbb{R}^d \rightarrow \mathbb{R}^d$ is a Lipschitz-continuous function, $A \in \mathbb{R}^{d \times d}$ is a positive-definite matrix, $(Z_t)_{t\geqslant 0}$ is a d-dimensional rotationally symmetric $\alpha$-stable Lévy process with $\alpha \in (1,2)$ and $x\in\mathbb{R}^{d}$. We use two Euler–Maruyama schemes with decreasing step sizes $\Gamma = (\gamma_n)_{n\in \mathbb{N}}$ to approximate the invariant measure of $(X_t)_{t \geqslant 0}$: one uses independent and identically distributed $\alpha$-stable random variables as innovations, and the other employs independent and identically distributed Pareto random variables. We study the convergence rates of these two approximation schemes in the Wasserstein-1 distance. For the first scheme, under the assumption that the function b is Lipschitz and satisfies a certain dissipation condition, we demonstrate a convergence rate of $\gamma^{\frac{1}{\alpha}}_n$. This convergence rate can be improved to $\gamma^{1+\frac {1}{\alpha}-\frac{1}{\kappa}}_n$ for any $\kappa \in [1,\alpha)$, provided b has the additional regularity of bounded second-order directional derivatives. For the second scheme, where the function b is assumed to be twice continuously differentiable, we establish a convergence rate of $\gamma^{\frac{2-\alpha}{\alpha}}_n$; moreover, we show that this rate is optimal for the one-dimensional stable Ornstein–Uhlenbeck process. Our theorems indicate that the recent significant result of [34] concerning the unadjusted Langevin algorithm with additive innovations can be extended to stochastic differential equations driven by an $\alpha$-stable Lévy process and that the corresponding convergence rate exhibits similar behaviour. Compared with the result in [6], our assumptions have relaxed the second-order differentiability condition, requiring only a Lipschitz condition for the first scheme, which broadens the applicability of our approach.
Sensory neuron membrane protein (SNMP) gene play a crucial role in insect chemosensory systems. However, the role of SNMP in the host searching behaviour of Rhopalosiphum padi (Hemiptera: Aphididae), a highly destructive pest of cereal crops, has not been clearly understood. Our previous research has shown that three wheat volatile organic compounds (VOCs) – (E)-2-hexenol, linalool, and octanal can attract R. padi, but the involvement of SNMP in the aphid’s olfactory response to these wheat VOCs has not to be elucidated. In this study, only one SNMP gene was cloned and characterised from R. padi. The results revealed that the SNMP belongs to the SNMP1 subfamily and was named RpadSNMP1. RpadSNMP11 was predominantly expressed in the antennae of the aphid, with significantly higher expression levels observed in winged forms, indicating that it is involved in olfactory responses of R. padi. RpadSNMP1 expression was significantly up-regulated following starvation, and the expression of this gene showed a decreasing trend after 24 h of aphid feeding. Functional analysis through RpadSNMP1 knockdown demonstrated a significant decrease in R. padi’s ability to search for host plants. The residence time of R. padi injected with dsRpadSNMP1 significantly shortened in response to (E)-2-hexenol, linalool and octanal according to the four-arm olfactometer, indicating the crucial role of RpadSNMP1 in mediating the aphid’s response to these wheat VOCs. Molecular docking suggested potential binding interactions between RpadSNMP1 and three wheat VOCs. Overall, these findings provided evidence for the involvement of RpadSNMP1 in host plant searching and lay a foundation for developing new methods to control this destructive pest.