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In recent years, applying slag micro-powder as a substitute for cement in preparing alkali-activated slag cement stabilized sand (AASCSS) mixtures has become increasingly widespread. In the severe cold regions of Xinjiang, multi-objective optimization of the mechanical and frost resistance properties of AASCSS is particularly crucial. This paper adopts slag micro-powder to replace Portland cement, together with lime and desulfurization gypsum as activators, to explore the effects of activator type and dosage on the mechanical and frost-resistance properties of AASCSS. A prediction model for the mechanical and frost-resistance properties of AASCSS based on projection-pursuit regression (PPR) was proposed and established. Using the developed PPR model, contour plots of the comprehensive performance were calculated, simplifying the multi-objective problem into two single-objective problems focusing on mechanical and frost resistance properties for analysis. This method avoids subjective weighting and hypothesis-based modeling. By analyzing the contour plots of comprehensive performance, the optimal performance indices for mechanical and frost–thaw properties and the corresponding types and dosages of activators can be directly determined. When the required 7-day unconfined compressive strength in road engineering is 5.6 MPa, the optimal value of the freeze–thaw performance index (BDR) is 94.08%. At this point, the corresponding lime content is 2.1%, and the desulfurization gypsum content is 3.3%. The research results provide a reference for applying slag to road-based materials. [ABSTRACT FROM AUTHOR]

Molecular hydrogen, the smallest and lightest molecule, serves as an intense reducing agent. Its distinct characteristics, including minimal size and neutral charge, enhance bioavailability and facilitate significant biological effects. Previously considered physiologically inert, hydrogen has gained recognition as a powerful therapeutic agent, known for its antioxidative and anti-inflammatory properties. Electrolyzed hydrogen water (EHW), enriched with molecular hydrogen, demonstrates remarkable antioxidative capabilities, indicating potential benefits for various diseases. Inflammation-induced reactive oxygen species (ROS) amplify inflammation, leading to secondary oxidative stress and creating a crosstalk between ROS and inflammatory responses. This crosstalk contributes to the pathogenesis and progression of chronic diseases. EHW interrupts this crosstalk, reducing inflammatory cytokines and oxidative stress across various disease models, suggesting therapeutic potential. EHW is also known for its anti-inflammatory effects, extending to pain management, as evidenced in models like sciatic nerve ligation and inflammatory pain. In an inflammatory bowel disease (IBD) model, EHW effectively alleviates abdominal pain, mitigating 2,4,6-trinitrobenzene sulfonic acid (TNBS)-induced inflammation and oxidative stress, offering insights for clinical applications. Additionally, hydrogen selectively targets harmful radicals, and EHW intake helps balance stress-induced hormonal dysregulation, potentially easing disorders associated with chronic stress. [ABSTRACT FROM AUTHOR]

With the proposal of the Beijing–Hangzhou Grand Canal Cultural Belt, the Beijing–Hangzhou Grand Canal has become an indispensable component of China's economic development pattern. Despite relatively high regional-economic-development levels along the canal, there still exists a common imbalance in regional development which will hinder the high-quality collaborative development of the region, highlighting the importance of measuring this disparity. This study adopts the district and county as spatial scales and selects five dimensions: economic growth, livelihood benefits, green ecology, innovation drive, and food guarantee in order to construct a comprehensive socio-economic index. Entropy weight method, Moran index, and Theil index analyses are used to examine the recent ten-year evolution laws in regional socio-economic spatial patterns along the Beijing–Hangzhou Grand Canal. Results indicate that socio-economic indicators designed for each dimension effectively measure both individual districts' and counties' economic situations as well as those of entire regions. In 2021, limited significance was observed regarding the level of regional economic agglomeration along the Grand Canal region, suggesting a tendency towards fragmented development rather than forming a well-coordinated model. Over the decade from 2011 to 2021, there was an increase in social and economic agglomeration. From a city unit perspective, developmental disparities among districts and counties within cities follow three distinct patterns. Cities at different stages of development can learn from each other's models to enhance integration cooperation and collectively promote high-quality economic advancements in the Grand Canal region. [ABSTRACT FROM AUTHOR]

School bullying among primary and secondary school students has received increasing attention, and identifying relevant factors is a crucial way to reduce the risk of bullying victimization. Machine learning methods can help researchers predict and identify individual risk behaviors. Through a machine learning approach (i.e., the gradient boosting decision tree model, GBDT), the present longitudinal study aims to systematically examine individual, family, and school environment factors that can predict the risk of bullying victimization among primary and secondary school students a year later. A total of 2767 participants (2065 secondary school students, 702 primary school students, 55.20% female students, mean age at T1 was 12.22) completed measures of 24 predictors at the first wave, including individual factors (e.g., self-control, gender, grade), family factors (family cohesion, parental control, parenting style), peer factor (peer relationship), and school factors (teacher–student relationship, learning capacity). A year later (i.e., T2), they completed the Olweus Bullying Questionnaire. The GBDT model predicted whether primary and secondary school students would be exposed to school bullying after one year by training a series of base learners and outputting the importance ranking of predictors. The GBDT model performed well. The GBDT model yielded the top 6 predictors: teacher–student relationship, peer relationship, family cohesion, negative affect, anxiety, and denying parenting style. The protective factors (i.e., teacher–student relationship, peer relationship, and family cohesion) and risk factors (i.e., negative affect, anxiety, and denying parenting style) associated with the risk of bullying victimization a year later among primary and secondary school students are identified by using a machine learning approach. The GBDT model can be used as a tool to predict the future risk of bullying victimization for children and adolescents and to help improve the effectiveness of school bullying interventions. [ABSTRACT FROM AUTHOR]

As an exquisite asset of Chinese traditional culture, traditional opera occupies a place of high esteem within the world's cultural and artistic treasury. The impact of emerging cultures has threatened the future of traditional opera culture, necessitating a thorough examination of the historical context of the Grand Canal and traditional opera. There is insufficient research on the spatial evolution of the traditional opera culture along the Grand Canal; thus, this study takes ancient opera stages, a representative cultural relic of traditional opera, as an entry point and employs methods such as kernel density analysis and standard deviation ellipse analysis to analyze the spatial and temporal distribution patterns of the traditional opera culture along the Grand Canal. The results showed that: (i) Nationwide, opera stages in the areas along the Grand Canal exhibit a significant clustering characteristic. (ii) The changes in the number and locations of opera stages in the areas along the Grand Canal are closely related to the rise and fall of the Canal. The opera stages emerged along the Canal, gradually prospered with the development of the Canal, and finally clustered in a band-like cluster along the Grand Canal. (iii) From the Ming Dynasty to the founding of the People's Republic of China, the opera stages in the areas along the Grand Canal spread in the "southeast–northwest" direction, which was consistent with the main direction of the Grand Canal, indicating its driving influence. (iv) On the centennial scale, from the 14th century to the 20th century, the evolution characteristics of the distribution centroid of opera stages in the areas along the Grand Canal were closely related to the key time nodes of Grand Canal construction and basin expansion. This study reveals the relationship between the Grand Canal and the spatial pattern evolution of traditional opera culture, aiming to promote the construction of the Grand Canal cultural belt. [ABSTRACT FROM AUTHOR]

A structural landform is defined by its surface morphology, controlled by tectonics, lithology (arrangement and resistance), and folded structures, and demonstrated by the characteristics and relationships between geological and geomorphic elements. It is very important to use geographic information system (GIS) technology to accurately describe and express elements of structural landforms and their relationships. In this study, a GIS approach for expressing structural landforms, based on "forms–elements–relationships", was developed. The contributions of this paper are as follows: (1) Combined with the surface morphological characteristics, the structural landforms were abstracted into geological and geomorphic elements, and the characteristics and relationships of these elements were analyzed. (2) The elements of structural landforms and their relationships were abstracted into spatial objects and topological relationships. The spatial objects of the structural landform were designed based on the types and characteristics of structural landform elements. The topological relationships were developed based on the definition of the structural landform morphotype. (3) The structural landform markup language (SLML) method of "forms–elements–relationships" was created. (4) Two typical structural landforms, namely, Qixia Mountain and Gaoli Mountain, were used as examples to verify the feasibility and effectiveness of the GIS approach for expressing structural landforms. This paper describes and expresses the "forms–elements–relationships" of structural landforms from the perspective of GIS, which is expected to promote the joint development of structural geomorphology and GIS. [ABSTRACT FROM AUTHOR]

Road intersection is a kind of important navigation landmark, while existing detection methods exhibit clear limitations in terms of their robustness and efficiency. A real-time algorithm for road intersection detection and location in large-scale sparse point clouds is proposed in this paper. Different from traditional approaches, our method establishes the augmented viewpoints beam model to perceive the road bifurcation structure. Explicitly, the spatial features from point clouds are jointly extracted in various viewpoints in front of the robot. In addition, the evaluation metrics are designed to self-assess the quality of detection results, enabling our method to optimize the detection process in real time. Considering the scarcity of datasets for intersection detection, we also collect and annotate a VLP-16 point cloud dataset specifically for intersections, called NCP-Intersection. Quantitative and qualitative experiments demonstrate that the proposed method performs favorably against the other parallel methods. Specifically, our method performs an average precision exceeding 90% and an average processing time of approximately 88 ms/frame. [ABSTRACT FROM AUTHOR]

Single LiNbO3 (LNO) crystals are widely utilized in surface acoustic wave devices, optoelectronic devices, and novel ferroelectric memory devices due to their remarkable electro-optic and piezoelectric properties, and high saturation and remnant polarizations. However, challenges remain regarding their nanofabrication that hinder their applications. The prevailing etching techniques for LNO encompass dry etching, wet etching, and focused-ion-beam etching, each having distinct merits and demerits. Achieving higher etching rates and improved sidewall angles presents a challenge in LNO nanofabrication. Building upon the current etching researches, this study explores various etching methods using instruments capable of generating diverse plasma densities, such as dry etching in reactive ion etching (RIE) and inductively coupled plasma (ICP), proton exchange-enhanced etching, and wet chemical etching following high-temperature reduction treatment, as well as hybrid dry and wet etching. Ultimately, after employing RIE dry etching combined with wet etching, following a high-temperature reduction treatment, an etching rate of 10 nm/min and pretty 90° sidewall angles were achieved. Furthermore, high etching rates of 79 nm/min with steep sidewall angles of 83° were obtained using ICP dry etching. Additionally, using SiO2 masks, a high etching rate of 108 nm/min and an etching selectivity ratio of 0.86:1 were achieved. Distinct etching conditions yielded diverse yet exceptional results, providing multiple processing paths of etching for the versatile application of LNO. [ABSTRACT FROM AUTHOR]

With the rapid development of the Internet, enterprises have integrated internal and external innovation resources through the establishment of open innovation communities, guided users to participate in innovation activities, and promoted product improvement and development. Users' continuous contribution behavior is a key factor for open innovation communities to achieve sustainable development, yet most communities do not collect enough data on them. This study investigates the mechanism of user benefits on continuous contribution behavior in open innovation communities based on the Stimulus–Organism–Response (S-O-R) theory, which creatively takes self-verification as a member of the organism (O). This was chosen to overcome the aforementioned issues. Based on the questionnaire data of 469 users in open innovation communities, the SEM method was applied to test the relationship between user benefits, self-verification, and continuous contribution behavior, and the moderating role of future work self-salience on self-verification. The empirical results show that user benefits positively affected both continuous contribution behavior and self-verification. Self-verification positively affected continuous contribution behavior and mediated the relationship between economic, functional, and self-fulfillment benefits and continuous contribution behavior. Meanwhile, future work self-salience positively moderated the relationship between these three types of benefits and self-verification. These findings provide a theoretical basis for the sustainable development of open innovation communities and guiding users to engage in continuous contribution behavior. [ABSTRACT FROM AUTHOR]

Rock masses are inherently heterogeneous, with numerous fractures that significantly affect their mechanical properties, fracture characteristics, and acoustic emission features due to the interactions between fractures or between fractures and the rock mass. Microbially induced calcite precipitation (MICP) technology, as an emerging non-destructive biological grouting reinforcement method, can repair fractured rock masses and alter their internal conditions. To investigate the mechanical properties, failure process evolution, and MICP repair effects of sandstone before and after repair, uniaxial compression tests were conducted on prefabricated, fractured (0.7–2.0 mm width) filled and unfilled rock samples, with acoustic emission monitoring throughout the process. Acoustic emission signal characteristics of the rock samples under stress were comparatively analyzed, determining the rock failure process and the microscopic failure types at compression-density stages, elastic stages, and destruction stages. The results show that the properties of the filled specimens improved, the failure process was mitigated, and the final failure stage was dominated by tension signals, accounting for over 60% of the total. The filling effect was better than 1.5–2.0 mm when the fracture width was 0.7–1.0 mm. The study deeply reveals the evolutionary process of compressive failure of the two types of rocks under different fracture widths, and by correlating the acoustic emission parameters with the stress–strain process, it provides a theoretical basis for repairing rock fractures using microbial engineering technology and offers experimental evidence and possible directions for the improvement and optimization of MICP technology. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by memory loss and personality changes that ultimately lead to dementia. Currently, 50 million people worldwide suffer from dementia related to AD, and the pathogenesis underlying AD pathology and cognitive decline is unknown. While AD is primarily a neurological disease of the brain, individuals with AD often experience intestinal disorders, and gut abnormalities have been implicated as a major risk factor in the development of AD and relevant dementia. However, the mechanisms that mediate gut injury and contribute to the vicious cycle between gut abnormalities and brain injury in AD remain unknown. In the present study, a bioinformatics analysis was performed on the proteomics data of variously aged AD mouse colon tissues. We found that levels of integrin β3 and β-galactosidase (β-gal), two markers of cellular senescence, increased with age in the colonic tissue of mice with AD. The advanced artificial intelligence (AI)-based prediction of AD risk also demonstrated the association between integrin β3 and β-gal and AD phenotypes. Moreover, we showed that elevated integrin β3 levels were accompanied by senescence phenotypes and immune cell accumulation in AD mouse colonic tissue. Further, integrin β3 genetic downregulation abolished upregulated senescence markers and inflammatory responses in colonic epithelial cells in conditions associated with AD. We provide a new understanding of the molecular actions underpinning inflammatory responses during AD and suggest integrin β3 may function as novel target mediating gut abnormalities in this disease. [ABSTRACT FROM AUTHOR]

The evaluation of landslide susceptibility is of great significance in the prevention and management of geological hazards. The accuracy of the landslide susceptibility prediction model based on machine learning is significantly higher than that of traditional expert knowledge and the conventional mathematical statistics model. The correct and reasonable selection of non-landslide samples in the machine learning model greatly improves the prediction accuracy and reliability of the regional landslide susceptibility model. Focusing on the problem of selecting non-landslide samples in the machine learning model for landslide susceptibility evaluation, this paper proposes a landslide susceptibility evaluation method based on the combination of an information model and machine learning in traditional mathematical statistics. First, the influence factors for landslide susceptibility evaluation are screened by the correlation analysis method. Second, the information value model is used to delimit areas with low and relatively low landslide susceptibility, and non-landslide points are randomly selected. Third, a landslide susceptibility evaluation method combined with IV-ML, such as logistic regression (IV-LR), random forest (IV-RF), support vector machine (IV-SVM), and artificial neural network (IV-ANN), is established. Finally, the landslide susceptibility factors in the Dabie Mountain area of Anhui Province are analyzed, and the accuracy of the landslide susceptibility evaluation results using the IV-LR, IV-RF, IV-SVM, and IV-ANN and LR, RF, SVM, and ANN methods are compared. The accuracy is evaluated by examining the ACC, AUC, and kappa values of the model. The results indicate that the evaluation effect of the IV-ML models (IV-LR, IV-RF, IV-SVM, IV-ANN) on landslide susceptibility is significantly higher than that of the ML models (LR, RF, SVM, ANN). [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD), a neurodegenerative disease, is one of the most intractable illnesses which affects the elderly. Clinically manifested as various impairments in memory, language, cognition, visuospatial skills, executive function, etc., the symptoms gradually aggravated over time. The drugs currently used clinically can slow down the deterioration of AD and relieve symptoms but cannot completely cure them. The drugs are mainly acetylcholinesterase inhibitors (AChEI) and non-competitive N-methyl-D-aspartate receptor (NDMAR) antagonists. The pathogenesis of AD is inconclusive, but it is often associated with the expression of beta-amyloid. Abnormal deposition of amyloid and hyperphosphorylation of tau protein in the brain have been key targets for past, current, and future drug development for the disease. At present, researchers are paying more and more attention to excavate natural compounds which can be effective against Alzheimer's disease and other neurodegenerative pathologies. Marine natural products have been demonstrated to be the most prospective candidates of these compounds, and some have presented significant neuroprotection functions. Consequently, we intend to describe the potential effect of bioactive compounds derived from marine organisms, including polysaccharides, carotenoids, polyphenols, sterols and alkaloids as drug candidates, to further discover novel and efficacious drug compounds which are effective against AD. [ABSTRACT FROM AUTHOR]

Pain is an unpleasant subjective experience that is usually modified by complex multidimensional neuropsychological processes. Increasing numbers of neuroimaging studies in humans have characterized the hierarchical brain areas forming a pain matrix, which is involved in the different dimensions of pain components. Although mechanistic investigations have been performed extensively in rodents, the homologous brain regions involved in the multidimensional pain components have not been fully understood in the rodent brain. Herein, we successfully identified several brain regions activated in response to mechanical allodynia in neuropathic pain rat models using an alternative neuroimaging method based on 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG PET) scanning. Regions such as the medial prefrontal cortex, primary somatosensory cortex hindlimb region, and the centrolateral thalamic nucleus were identified. Moreover, brain activity in these regions was positively correlated with mechanical allodynia-related behavioral changes. These results suggest that FDG PET imaging in neuropathic pain model rats enables the evaluation of regional brain activity encoding the multidimensional pain aspect. It could thus be a fascinating tool to bridge the gap between preclinical and clinical investigations. [ABSTRACT FROM AUTHOR]

Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the digestive tract and is typically accompanied by characteristic symptoms, such as abdominal pain, diarrhea, and bloody stool, severely deteriorating the quality of the patient's life. Electrolyzed hydrogen water (EHW) has been shown to alleviate inflammation in several diseases, such as renal disease and polymyositis/dermatomyositis. To investigate whether and how daily EHW consumption alleviates abdominal pain, the most common symptom of IBD, we examined the antioxidative and anti-inflammatory effects of EHW in an IBD rat model, wherein colonic inflammation was induced by colorectal administration of 2,4,6-trinitrobenzene sulfonic acid (TNBS). We found that EHW significantly alleviated TNBS-induced abdominal pain and tissue inflammation. Moreover, the production of proinflammatory cytokines in inflamed colon tissue was also decreased significantly. Meanwhile, the overproduction of reactive oxygen species (ROS), which is intricately involved in intestinal inflammation, was significantly suppressed by EHW. Additionally, expression of S100A9, an inflammatory biomarker of IBD, was significantly suppressed by EHW. These results suggest that the EHW prevented the overproduction of ROS due to its powerful free-radical scavenging ability and blocked the crosstalk between oxidative stress and inflammation, thereby suppressing colonic inflammation and alleviating abdominal pain. [ABSTRACT FROM AUTHOR]

Simple Summary: The oriental fruit moth Grapholita molesta is an important worldwide fruit tree pest. Its hosts mainly include peach, pear, apple, plum and other Rosaceae fruit trees. In order to explore the mechanism of host adaptation, it is necessary to comprehensively study the effects of feeding and the differences in transcriptional levels of G. molesta. In this study, the growth and development parameters, protease activities, midgut transcriptome analysis and key gene validation of G. molesta fed on five hosts and artificial diet were determined. This study indicated that the significant differences in the growth and development parameters and protease activities, transcriptome of KEGG enrichment and WGCNA analysis of G. molesta fed on different hosts. The transcriptional level of the trypsin gene was consistent with that of qRT-PCR. The trypsin gene played an important role in feeding different hosts of G. molesta. We revealed the adaptive mechanism to different hosts of G. molesta in various aspects and laid a solid foundation for further exploring the molecular mechanism of host adaptation. Grapholita molesta is an important fruit tree worldwide pest which feeds on hosts extensively and does serious harm. In this paper, the growth and development parameters and protease activities of G. molesta fed on different hosts were compared. Using Illumina RNA sequencing technology, 18 midgut samples from five different hosts (apple, pear, plum, peach and peach shoots) and artificial diet were sequenced and compared with the reference genome, resulting in 15269 genes and 2785 predicted new genes. From 15 comparative combinations, DEGs were found from 286 to 4187 in each group, with up-regulated genes from 107 to 2395 and down-regulated genes from 83 to 2665. KEGG pathway analysis showed that DEGs were associated with amino acid metabolism, starch and sucrose metabolism, carbohydrate metabolism, and hydrolase activity. A total of 31 co-expression gene modules of different hosts were identified by WGCNA. qRT-PCR showed that the expression pattern of the trypsin gene was consistent with RNA sequencing. In this study, growth and development parameters, protease activity, DEGs, enrichment analysis and qRT-PCR were combined to reveal the adaptation process to different hosts of G. molesta in many aspects. The results of this study provide a basis for further exploration of the molecular mechanism of host adaptation of G. molesta. [ABSTRACT FROM AUTHOR]

A method for batch preparation of fucoxanthin from brown algae was established, which possessed the advantages of high yield and high purity. The ultrasonic-assisted extraction method was used to obtain a crude extract from Sargassum fusiforme as the separation sample. Then the crude extract was separated by elution-extrusion countercurrent chromatography. The optimum preparation conditions of fucoxanthin were determined as follows: n-hexane-ethanol-water (20:9:11, v:v:v) as a two-phase solvent system, the mobile phase flow rate was 5 mL min−1, the revolution speed was 800 r min−1, the loading capacity was 60 mg 10 mL−1 and the temperature was 25 °C. By this method, 12.8 mg fucoxanthin with a purity of 94.72% was obtained from the crude extract of Sargassum fusiforme. In addition, when the loading capacity was 50 mg 10 mL−1, the purity of fucoxanthin reached 96.01%. Two types of by-products, chlorophyll and pheophytin, could also be obtained during the process of separation. This optimal method was further applied to separate fucoxanthin from Laminaria japonica and Undaria pinnatifida, and 6.0 mg and 9.7 mg fucoxanthin with a purity of 96.24% and 92.62% were acquired, respectively. Therefore, it was demonstrated that the preparation method of fucoxanthin established in this study had an applicability to brown algae, which improved the utilization value of raw materials. [ABSTRACT FROM AUTHOR]

Neutralization with liquid digestate and CO2 was compared herein to adjust the pH of lime-treated corn stover. The effects on the thermophilic (55 °C) anaerobic digestion were also analyzed. Liquid digestate neutralization (LDN) caused a decrease in pH from 10.5 to 7.5 in 60 h and accumulation of acetic/isobutyric acids. The CO2 neutralization (CN) under solid-state conditions reduced the pH from 10.5 to 8.5 in 30 min, which is faster than that of LDN and did not affect the subsequent anaerobic digestion. Biomethane production rate indicates that LDN contributed to the performance of anaerobic digestion, but this was not sufficient to compensate for the loss of total biomethane yield, resulting in a negative net profit (i.e., revenue from increased energy production minus reagent cost). For CN under solid-state conditions, the biomethane production was highest in both liquid- and solid-state anaerobic digestion, and also obtained a net profit of 98.74–100.89 RMB/tonne dry biomass. Therefore, the solid-state condition CN is a more efficient and economic method for adjusting initial pH of lime-treated corn stover. [ABSTRACT FROM AUTHOR]

The primary purpose of this study is to investigate the influence of the vertical guiding laser beam waist on cold atom guiding efficiency. In this study, a double magneto-optical trap (MOT) apparatus is used. With an unbalanced force in the horizontal direction, a cold atomic beam is generated by the first MOT. The cold atoms enter the second chamber and are then re-trapped and cooled by the second MOT. By releasing a second atom cloud, the process of transferring the cold atoms from MOT to the dipole trap, which is formed by a red-detuned converged 1064-nm laser, is experimentally demonstrated. And after releasing for 20 ms, the atom cloud is guided to a distance of approximately 3 mm. As indicated by the results, the guiding efficiency depends strongly on the laser beam waist; the efficiency reaches a maximum when the waist radius (w0) of the laser is in the range of 15 to 25 μm, while the initial atom cloud has a radius of 133 μm. Additionally, the properties of the atoms inside the dipole potential trap, such as the distribution profile and lifetime, are deduced from the fluorescence images. [ABSTRACT FROM AUTHOR]

Innovation is a key factor for a country's overall national strength and core competitiveness. The spatial pattern of innovation reflects the regional differences of innovation development, which can provide guidance for the regional allocation of innovation resources. Most studies on the spatial pattern of innovation are at urban and above spatial scale, but studies at urban internal scale are insufficient. The precision and index of the spatial pattern of innovation in the city needs to be improved. This study proposes to divide spatial units based on geographic coordinates of patents, designs the innovation capability and innovation structure index of a spatial unit and their calculation methods, and then reveals the spatial patterns of innovation and their evolutionary characteristics in Shenzhen during 2000–2018. The results show that: (1) The pattern of innovation capacity of secondary industry exhibited a pronounced spatial spillover effect with a positive spatial correlation. The innovation capacity and innovation structure index of the secondary industry evolved in a similar manner; i.e., they gradually extended from the southwest area to the north over time, forming a tree-like distribution pattern with the central part of the southwest area as the "root" and the northwest and northeast areas as the "canopy". (2) The pattern of innovation capacity of tertiary industry also had a significant spatial spillover effect with a positive spatial correlation. There were differences between the evolutions of innovation capacity and innovation structure index of tertiary industry. Specifically, its innovation capacity presented a triangular spatial distribution pattern with three groups in the central and eastern parts of the southwest area and the south-eastern part of the northwest area as the vertices, while its innovative structure showed a radial spatial distribution pattern with the southwestern part of the southwest area as the source and a gradually sparse distribution toward the northeast. (3) There were differences between the evolution modes of secondary and tertiary industries. Areas with high innovation capacity in the secondary industry tended to be more balanced, while areas with high innovation capacity in the tertiary industry did not necessarily have a balanced innovation structure. Through the method designed in this paper, the spatial pattern of urban innovation can be more precise and comprehensive revealed, and provide useful references for the development of urban innovation. [ABSTRACT FROM AUTHOR]

Knowing the GIS expression of geological phenomena is an important basis for the combination of geology and GIS. Regional geological structures include folds, faults, strata, rocks, and other typical geological phenomena and are the focus of geological GIS research. However, existing research on the GIS expression of regional geological structure focuses on the expression of the spatial and attribute characteristics of geological structures, and our knowledge of the expression of the semantic, relationship, and evolution processes of geological structures is not comprehensive. In this paper, a regional geological structure scene expression model with the semantic terms positional accuracy, geometric shape, relationship type, attribute type, and time-type attributes and operations is proposed. A regional geological structure scenario markup language (RGSSML) and a method for mapping it with graphics are designed to store and graphically express regional geological structure information. According to the geological time scale, a temporal reference coordinate system is defined to dynamically express the evolution of regional geological structures. Based on the dynamic division of the time dimension of regional geological structures, the expression method of "time dimension + space structure" for the regional geological structure evolution process is designed based on the temporal model. Finally, the feasibility and effectiveness of the regional geological structure scene expression method proposed in this paper is verified using the Ningzhen Mountain (Nanjing section) as an example. The research results show that the regional geological structure scene expression method designed in this paper has the following characteristics: (1) It can comprehensively express the spatial characteristics, attribute characteristics, semantics, relationships, and evolution processes of regional geological structures; (2) it can be used to realize formalized expression and unified storage of regional geological information; and (3) it can be used to realize dynamic expression of the regional geological structure evolution process. Moreover, it has significant advantages for the expression of regional geological structure semantics, relationships, and evolution processes. This study improves our knowledge of the GIS expression of regional geological structures and is expected to further promote the combination and development of geology and GIS. [ABSTRACT FROM AUTHOR]

The impulse response of the fractional oscillation equation was investigated, where the damping term was characterized by means of the Riemann–Liouville fractional derivative with the order α satisfying 0 ≤ α ≤ 2 . Two different analytical forms of the response were obtained by using the two different methods of inverse Laplace transform. The first analytical form is a series composed of positive powers of t, which converges rapidly for a small t. The second form is a sum of a damped harmonic oscillation with negative exponential amplitude and a decayed function in the form of an infinite integral, where the infinite integral converges rapidly for a large t. Furthermore, the Gauss–Laguerre quadrature formula was used for numerical calculation of the infinite integral to generate an analytical approximation to the response. The asymptotic behaviours for a small t and large t were obtained from the two forms of response. The second form provides more details for the response and is applicable for a larger range of t. The results include that of the integer-order cases, α = 0, 1 and 2. [ABSTRACT FROM AUTHOR]

Taking the mausoleums in the main urban area of Nanjing city as the study object, with the support of GIS technology, this paper extracts eight influencing factors (surface roughness, elevation, surface cutting depth, surface peaks, outfall, river system, slope, and aspect) corresponding to geomantic elements ("Long", "Sha", "Shui", and "Xue") in the geographical environments of mausoleums. The AHP is applied in the correlation weight method to calculate the weights of the eight influencing factors, while the information content method is applied in the grading method to calculate the numerical index of each factor. The feng shui (geomantic) suitability of the mausoleums in the main urban area of Nanjing is evaluated using the AHP-weighted information content method and by combining expert knowledge and experience with mathematical statistical techniques. According to the feng shui (geomantic) suitability evaluation results obtained for the mausoleums in the study area, the relatively low-suitability area accounts for 14.55% of the entire study area, the low-suitability area accounts for 25.40%, the suitable area accounts for 29.13%, the relatively high-suitability area accounts for 22.00%, and the high-suitability area accounts for 8.92%. Finally, through a sensitivity analysis of the model, a verification analysis applied using random mausoleums and a feng shui (geomantic) analysis of the Ming Xiaoling Mausoleum, the feng shui (geomantic) suitability evaluation results obtained for the mausoleums analyzed herein are found to be consistent with the actual distribution of the mausoleum sites. The research shows that the AHP-weighted information method based on GIS is suitable for evaluating the feng shui (geomantic) suitability of mausoleums. [ABSTRACT FROM AUTHOR]

At the end of the 20th century, the phenomenon of urban shrinkage received widespread attention, with population decline as its core characteristic. In 2020, the Taiwanese population had negative growth and faced a low fertility rate and an aging population. This study used exploratory spatial data analysis to identify shrinking cities in Taiwan based on census data and population registers. The results indicated that Taiwan has 11 shrinking counties and 202 shrinking towns. Urban shrinkage occurred in the 1980s and continued from the suburbanization stage to the re-urbanization stage. Five types of spatial patterns in the 11 shrinking counties were observed. In the majority of the shrinking counties, towns with high population densities were unable to avoid shrinkage. A global spatial autocorrelation analysis indicated that shrinkage and non-shrinkage have become increasingly apparent at the town level since 2005. A local spatial autocorrelation analysis indicates that the spatial clustering of towns with population growth or decline from 2000 to 2020 has changed. Based on each town's development, a two-step cluster analysis was conducted in which all towns were divided into four categories. Shrinking towns exist in each category, but with a different proportion. Based on the results of two-step cluster analysis combined with spatial analysis, this study discovered that both urbanization and suburbanization cause shrinkage in Taiwan, but the affected localities are distinct. For most shrinking counties, their spatial model indicates a relationship between shrinking and the urbanization of their towns. Keelung City and Chiayi City have the most potential to reverse the shrinkage. This study helps authorities better manage growth and implement regional revitalization. [ABSTRACT FROM AUTHOR]

The Humen Estuary, one of the largest outlets of the Pearl River, is a long and wide tidal channel with a considerable tidal flow every year. Storm surges, always superposing spring tide, travel from the estuary and endanger the safety of people living around the river. However, little research has quantified the relationship between the hydraulic characteristics and the geometry features in this estuary. In this regard, an analytical model, combined with a numerical model, is applied to investigate the characteristics of tidal waves and surge propagations in the estuary. Given the geometric, topographic, and tidal parameters at the mouth of the estuary, the tidal damping and wave celerity can be computed. The numerical results were used to calibrate and verify the analytical model. The results indicate that the analytical model can describe the astronomical tidal dynamics very well in correspondence with the numerical results. However, the analytical model cannot predict the tide well when a tropical cyclone-induced surge is superimposed on the astronomical tide. The reason is that this model does not take the wind stress and the pressure depression into account. After reducing Manning's coefficient, we found that the analytical results could be close to the numerical results. Finally, we analyzed the characteristics of the tidal wave in the Humen Estuary using the analytical solution and its parameters. [ABSTRACT FROM AUTHOR]

Efficient conversion of renewable biomass into value-added chemicals and biofuels is regarded as an alternative route to reduce our high dependence on fossil resources and the associated environmental issues. In this context, biomass-based furfural and levulinic acid (LA) platform chemicals are frequently utilized to synthesize various valuable chemicals and biofuels. In this review, the reaction mechanism and catalytic system developed for the generation of furfural and levulinic acid are summarized and compared. Special efforts are focused on the different catalytic systems for the synthesis of furfural and levulinic acid. The corresponding challenges and outlooks are also observed. [ABSTRACT FROM AUTHOR]

Based on the significant hotspots analysis method (Getis-Ord Gi* significance statistics), space-time cube model (STC) and the Mann–Kendall trend test method, this paper proposes a G-STC-M spatio-temporal analysis method based on Archaeological Sites. This method can integrate spatio-temporal data variable analysis and the space-time cube model to explore the spatio-temporal distribution of Archaeological Sites. The G-STC-M method was used to conduct time slice analysis on the data of Archaeological Sites in the study area, and the spatio-temporal variation characteristics of Archaeological Sites in East China from the Tang Dynasty to the Qing Dynasty were discussed. The distribution of Archaeological Sites has temporal hotspots and spatial hotspots. Temporally, the distribution of Archaeological Sites showed a gradual increasing trend, and the number of Archaeological Sites reached the maximum in the Qing Dynasty. Spatially, the hotspots of Archaeological Sites are mainly distributed in Jiangsu (30°~33° N, 118°~121° E) and Anhui (29°~31° N, 117°~119° E) and the central region of Zhejiang (28°~31° N, 118°~121° E). Temporally and spatially, the distribution of Archaeological Sites is mainly centered in Shanghai (30°~32° N, 121°~122° E), spreading to the southern region. [ABSTRACT FROM AUTHOR]

Geothermal energy has been recognized as an important clean renewable energy. Accurate assessment of geothermal resources is an essential foundation for their development and utilization. The North Jiangsu Basin (NJB), located in the Lower Yangtze Craton, is shaped like a wedge block of an ancient plate boundary and large-scale carbonate thermal reservoirs are developed in the deep NJB. Moreover, the NJB exhibits a high heat flow background because of its extensive extension since the Late Mesozoic. In this study, we used the Monte Carlo method to evaluate the geothermal resources of the main reservoir shallower than 10 km in the NJB. Compared with the volumetric method, the Monte Carlo method takes into account the variation mode and uncertainties of the input parameters. The simulation results show that the geothermal resources of the sandstone thermal reservoir in the shallow NJB are very rich, with capacities of (6.6–12) × 1020 J (mean 8.6 × 1020 J), (5.1–16) × 1020 J (mean 9.1 × 1020 J), and (3.2–11) × 1020 J (mean 6.6 × 1020 J) for the Yancheng, Sanduo and Dai'nan sandstone reservoir, respectively. In addition, the capacity of the geothermal resource of the carbonate thermal reservoir in the deep NJB is far greater than the former, reaching (9.9–15) × 1021 J (mean 12 × 1021 J). The results indicate capacities of a range value of (1.2–1.7) × 1021 J (mean 1.4 × 1022 J) for the whole NJB (<10 km). [ABSTRACT FROM AUTHOR]

Anomaly detection is of great significance in condition-based maintenance of power plant equipment. The conventional fixed threshold detection method is not able to perform early detection of equipment abnormalities. In this study, a general anomaly detection framework based on a long short-term memory-based autoencoder (LSTM-AE) network is proposed. A normal behavior model (NBM) is established to learn the normal behavior patterns of the operating variables of the equipment in space and time. Based on the similarity analysis between the NBM output distribution and the corresponding measurement distribution, the Mahalanobis distance (MD) is used to describe the overall residual (OR) of the model. The reasonable range is obtained using kernel density estimation (KDE) with a 99% confidence interval, and the OR is monitored to detect abnormalities in real-time. An induced draft fan is chosen as a case study. Results show that the established NBM has excellent accuracy and generalizability, with average root mean square errors of 0.026 and 0.035 for the training and test data, respectively, and average mean absolute percentage errors of 0.027%. Moreover, the abnormal operation case shows that the proposed framework can be effectively used for the early detection of abnormalities. [ABSTRACT FROM AUTHOR]

Vertex concavity-convexity detection for spatial objects is a basic algorithm of computer graphics, as well as the foundation for the implementation of other graphics algorithms. In recent years, the importance of the vertex concavity-convexity detection algorithm for three-dimensional (3D) spatial objects has been increasingly highlighted, with the development of 3D modeling, artificial intelligence, and other graphics technologies. Nonetheless, the currently available vertex concavity-convexity detection algorithms mostly use two-dimensional (2D) polygons, with limited research on vertex concavity-convexity detection algorithms for 3D polyhedrons. This study investigates the correlation between the outer product and the topology of the spatial object based on the unique characteristic that the outer product operation in the geometric algebra has unified and definitive geometric implications in space, and with varied dimensionality. Moreover, a multi-dimensional unified vertex concavity-convexity detection algorithm framework for spatial objects is proposed, and this framework is capable of detecting vertex concavity-convexity for both 2D simple polygons and 3D simple polyhedrons. [ABSTRACT FROM AUTHOR]

Maintaining topological consistency is a crucial issue for 3D cadastral modeling as this helps to represent the cadastral boundary clearly and accurately. As a result, 3D cadastral data models are mainly built on the basis of topological models that allow topology to be expressed clearly. However, topological models in Euclidean space cannot directly represent objects' geometric information. As geometric information is important in 3D spatial analysis, 3D cadastral data models based on topological models cannot realize topological calculation and analysis. Previous research has proved that geometric and topological information for cadastral objects can be integrated and represented by conformal geometric algebra (CGA) expressions. This paper aims to realize 3D topological analysis in the cadastral field using CGA's advantages in geometric relations computation. A calculation framework is designed on the basis of the outer product to achieve the purpose of multidimensional unity for 3D cadastral topological analysis in this paper. A calculation framework of topological relations between a boundary point (or a boundary line) and a cadastral parcel is developed. A total of 13 types of topological relations between a boundary point and a cadastral parcel and 48 types of topological relations between a boundary line and a cadastral parcel are obtained. The study indicates that the advantages of CGA in multidimensional unified representation and calculation can be used to solve problems encountered by topological models in Euclidean space. [ABSTRACT FROM AUTHOR]

Based on geographic information system (GIS) technology in conjunction with two methods for assessing landslide susceptibility (LS)—namely, a method using experts' knowledge and experience, and a mathematical/statistical method—the LS of southern Anhui, China is assessed using an analytic hierarchy process (AHP) via an AHP-weighted information content method. Landslide-affecting factors are categorized into three main types and 10 subtypes. The values of spatial characteristics of the landslide-affecting factors are obtained using GIS technology. The AHP method is then employed to compare the importance and weights of landslide-affecting factors. The information content method is used to convert the measured values of the landslide-affecting factors in the study area to data reflecting regional stability. The closeness of the relationships between the classification levels of each landslide-affecting factor and landslide occurrence are calculated. The LS of the study area is assessed using the proposed method. The LS assessment shows that high LS, relatively high LS, moderate LS, relatively low LS and low LS regions account for 21.3%, 20.6%, 20.1%, 11.7% and 26.3% of the study area, respectively. Finally, the accuracy of the LS assessment results is analyzed using two methods: the assessment, including an analysis of random landslide sites for the validating models; and the area below a receiver operating characteristic (ROC) curve of area under curve (AUC) value. The results show that the proportion of landslide sites in the regions of each LS level determined using the AHP-weighted information content method increases as the LS level increases, and that the accuracies of the AHP-weighted information content method were 8.1% and 5.7% higher than those of the AHP method and information content method, respectively. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) and wind power (WT) resources can influence each other in some scenarios, and this influence tends to show that the rise of PV resources may indicate the drop of WT resources, and vice versa. This pattern of PV and WT resources influencing each other is called the complementary characteristics of PV and WT power. The complementary characteristics of the power outputs of different kinds of distributed renewable energy resources (DRERs) and the correlation between DRERs outputs and loads can impact the consumption of DRERs by the loads within the grid, which represents the rate of DRER outputs consumed by loads instead of being reduced. In this regard, this paper investigates a planning strategy for DRERs considering these two factors. An improved co-variance matrix method is applied to generate complementary samples of DRERs and correlated samples of DRERs and loads. The samples generated are used to study the impacts of the degree of correlation between DRERs and loads on the consumption ability of DRERs. The concept of the cluster is introduced as a region including DRERs with complementary characteristics. Based on the cluster partition method and the samples generated, the DRERs planning model is proposed to maximize the profits of different DRER stakeholders. The planning model is transformed into a single objective model through the ideal point method. A Benders decomposition-based method is developed to efficiently solve the proposed model, and an actual network in China is used to illustrate its performance. The results show DRER consumption can be significantly improved by the proposed planning model. [ABSTRACT FROM AUTHOR]

GIS modelling, which is often employed to establish the abstract structural forms of geological phenomena and their structural relationships, is of great importance for the expression and analysis of geological structures to describe and express such phenomena accurately and intuitively. However, current GIS modelling schemes value structural forms over structural relationships, and existing geological semantic expressions in the modelling of geological relationships are incomplete. Therefore, this paper categorizes geological relationships into three levels: geological phenomena, geological objects and geological spatial objects: (1) based on their definitions, this work categorizes geological relationships into internal composition relationships and external combined relationships for a total of two categories, eight classes and 27 small groups; (2) this work also improves the system with a total of 33 classified geological objects by transforming the relationships between geological phenomena into relationships between geological objects; and (3) based on the 27 small groups of geological relationships, through the corresponding geometric and semantic expressions between topological rules and geological rules and between relationship rules and geological rules, this work then expresses internal composition relationships as topological relationships between geological spatial objects and expresses external combined relationships as association relationships between geological spatial objects. A GIS model of geological relationships that integrates their geometries and semantics is then built. Finally, taking the Dagang-Danyang section of the Ningzhen mountains as an example, the results show that the proposed GIS modelling method can better store and express geological phenomena, geological objects and geological spatial objects in a way that integrates geometry and semantics. [ABSTRACT FROM AUTHOR]

A new hair sensor for multi-physical signal measurements, including acceleration, angular velocity and air flow, is presented in this paper. The entire structure consists of a hair post, a torsional frame and a resonant signal transducer. The hair post is utilized to sense and deliver the physical signals of the acceleration and the air flow rate. The physical signals are converted into frequency signals by the resonant transducer. The structure is optimized through finite element analysis. The simulation results demonstrate that the hair sensor has a frequency of 240 Hz in the first mode for the acceleration or the air flow sense, 3115 Hz in the third and fourth modes for the resonant conversion, and 3467 Hz in the fifth and sixth modes for the angular velocity transformation, respectively. All the above frequencies present in a reasonable modal distribution and are separated from interference modes. The input-output analysis of the new hair sensor demonstrates that the scale factor of the acceleration is 12.35 Hz/g, the scale factor of the angular velocity is 0.404 nm/deg/s and the sensitivity of the air flow is 1.075 Hz/(m/s)², which verifies the multifunction sensitive characteristics of the hair sensor. Besides, the structural optimization of the hair post is used to improve the sensitivity of the air flow rate and the acceleration. The analysis results illustrate that the hollow circular hair post can increase the sensitivity of the air flow and the II-shape hair post can increase the sensitivity of the acceleration. Moreover, the thermal analysis confirms the scheme of the frequency difference for the resonant transducer can prominently eliminate the temperature influences on the measurement accuracy. The air flow analysis indicates that the surface area increase of hair post is significantly beneficial for the efficiency improvement of the signal transmission. In summary, the structure of the new hair sensor is proved to be feasible by comprehensive simulation and analysis.

This paper presents technology for the suppression of the mechanical coupling errors for an improved decoupled dual-mass micro-gyroscope (DDMG). The improved micro-gyroscope structure decreases the moment arm of the drive decoupled torque, which benefits the suppression of the non-ideal decoupled error. Quadrature correction electrodes are added to eliminate the residual quadrature error. The structure principle and the quadrature error suppression means of the DDMG are described in detail. ANSYS software is used to simulate the micro-gyroscope structure to verify the mechanical coupling error suppression effect. Compared with the former structure, simulation results demonstrate that the rotational displacements of the sense frame in the improved structure are substantially suppressed in the drive mode. The improved DDMG structure chip is fabricated by the deep dry silicon on glass (DDSOG) process. The feedback control circuits with quadrature control loops are designed to suppress the residual mechanical coupling error. Finally, the system performance of the DDMG prototype is tested. Compared with the former DDMG, the quadrature error in the improved dual-mass micro-gyroscope is decreased 9.66-fold, and the offset error is decreased 6.36-fold. Compared with the open loop sense, the feedback control circuits with quadrature control loop decrease the bias drift by 20.59-fold and the scale factor non-linearity by 2.81-fold in the ±400°/s range.