Aligning Large Language Models to a Domain-specific Graph Database

Graph Databases (Graph DB) are widely applied in various fields, including finance, social networks, and medicine. However, translating Natural Language (NL) into the Graph Query Language (GQL), commonly known as NL2GQL, proves to be challenging due to its inherent complexity and specialized nature. Some approaches have sought to utilize Large Language Models (LLMs) to address analogous tasks like text2SQL. Nevertheless, when it comes to NL2GQL taskson a particular domain, the absence of domain-specific NL-GQL data pairs makes it difficult to establish alignment between LLMs and the graph DB. To address this challenge, we propose a well-defined pipeline. Specifically, we utilize ChatGPT to create NL-GQL data pairs based on the given graph DB with self-instruct. Then, we use the created data to fine-tune LLMs, thereby achieving alignment between LLMs and the graph DB. Additionally, during inference, we propose a method that extracts relevant schema to the queried NL as the input context to guide LLMs for generating accurate GQLs.We evaluate our method on two constructed datasets deriving from graph DBs in finance domain and medicine domain, namely FinGQL and MediGQL. Experimental results demonstrate that our method significantly outperforms a set of baseline methods, with improvements of 5.90 and 6.36 absolute points on EM, and 6.00 and 7.09 absolute points on EX, respectively.Comment: 13 pages,2 figure

Effect of the heating rate on the thermal explosion behavior and oxidation resistance of 3D-structure porous NiAl intermetallic

Porous NiAl intermetallic compounds demonstrate great potential in various applications by their high porosity and excellent oxidation resistance. However, to obtain a controllable NiAl intermetallic structure by tuning different process parameters remains unclear. In this work, porous NiAl intermetallic compounds were fabricated by economic and energy-saving thermal explosion (TE) reaction. The relationship between microstructure and process parameters was revealed using three-dimensional X-ray microscopy (3D-XRM) with high resolution and non-destructive characteristics. The geometrical features and quantitative statistics of the porous NiAl obtained at different heating rates (2, 10, 20 \ub0C min−1) were compared. The result of the closed porosity calculation showed that a lower heating rate (2 \ub0C min−1) promoted the Kirkendall reaction between Ni and Al, resulting in a high closed porosity (5.25%). However, at a higher heating rate (20 \ub0C min−1), a homogeneous NiAl phase was observed using the threshold segmentation method, indicating uniform and complete TE reaction can be achieved at a high heating rate. The result of the 3D fluid simulation showed that the sample heated at 10 \ub0C min−1 had the highest permeability (2434.6 md). In this study, we systematically investigated the relationship between the heating rates and properties of the porous NiAl intermetallic, including the phase composition, porosity, exothermic mechanism, oxidation resistance, and compression resistance. Our work provides constructive directions for designing and tailoring the performance of porous NiAl intermetallic compounds

Effect of additives on microstructure of coal-based graphite

The Taixi anthracite was used as the raw materials, and mixed with different masses of additives, namely silicon oxide, titanium oxide, and iron oxide, to prepare the coal-based graphite by high temperature graphitization. The microstructure of coal-based graphite was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), laser confocal Raman spectroscopy (Raman) and Specific surface area and porosity analyzer.The results show that the graphitization degree of the coal-based graphite can reach over 89% after high temperature heat treatment at 2800 °C , which significantly improves the microcrystalline structure of anthracite and achieves orderly rearrangement of sp2 hybrid carbon atoms in the coal. Under the same additive mixing level, the graphitization degree and stacking height of coal-based graphite with titanium dioxide as additive are relatively high, the difference between the layer spacing and the ideal graphite layer spacing is the smallest, and the degree of ordering of carbon materials is the highest. The Raman spectroscopy results showed that the order degree of coal -based graphite prepared under different additives was significantly different, and the order degree of TXSC3, TXTC2 and TXIC3 coal-based graphite was the highest among the additives. Under the electron microscope, it is found that under the conditions of three additives, the scales, spherical and two shapes of coal-based graphite can be prepared separately. It can be seen from the specific surface area and pore size distribution data of coal-based graphite that they have similar low-temperature nitrogen adsorption-desorption isotherms

Fostering employee-customer identification: The impact of relational job design

By integrating insights from the literature on relational job design and relational identification, we provide theoretical and empirical account of whether relational job design can foster employee-customer identification (ECID) and subsequently, enhance service performance. This research suggests that relational job characteristics likely foster service employees’ ECID by relating employees to the positive impact they have on customers as well as by leading employees to gain valuable personal resources from customer interactions. Using time-lagged data collected from 255 frontline service employees matched with 92 supervisors in 47 restaurants, we found that job impact on customers positively influenced service performance, and this influence was mediated by ECID. Results also showed that job contact with customers positively influenced service performance, and this influence was partially mediated by ECID

Effect of moisture on anthracite crushing behavior and grinding energy consumption

The change of water occurrence form and content in coal will change the physical characteristics and pore structure of coal, and then affect its crushing process.In order to study the effect of moisture contained in coal on on the crushing behavior of coal particles,anthracite coal was used as the research object. A Hastelloy grinding equipped with a power measuring device was applied to simulate the crushing environment in a medium-speed coal mill. The individual and mixed crushing experiments were carried out in multi-time batches of coal samples with different water content. Thus, the effects of water occurrence on coal crushing rate, pulverized coal fineness, and grinding energy consumption were studied. The experimental results showed that compared with the original coal samples, the initial particle size material crushing rate of homogenized soaked coal samples decreases significantly due to the increase of water content, its grindability index first decreased and then increased with increasing the water content when the homogenized immersed coal sample was crushed separately, and the fineness of pulverized coal t10 was positively correlated with water content. When dry and wet coal samples were mixed and crushed, the crushing rate and fine-grained material generation rate of 13.34% moisture content samples were much higher than that of homogenized soaked coal samples with the same moisture content, and their its grindability index was larger than that of the original coal; The grindability index of the blended coal samples with other moisture contents was slightly smaller than that of the homogenized soaked coal samples, and this difference became larger with the increase of moisture content, while the crushing rate and the yield of fine-grained materials differed less from that of the homogenized impregnated coal samples. Also, the result indicated that the classical energy-particle size relationship model may be used to characterize the individual and mixed crushing processes of samples with different moisture gradients. The internal and external moisture reduced the ability of anthracite to resist crushing to varying degrees, and increasing the water content during separate crushing improved the energy efficiency significantly. So, the water content parameters were introduced into the energy consumption model to characterize the crushing process of various moisture coal samples. By exploring the influence mechanism of water content in coal on energy consumption of coal crushing, it reveals the way of energy loss in the process of coal crushing and provides theoretical guidance for optimizing coal crushing process and reducing energy consumption

Comparison of energy efficiency between E and MPS type vertical spindle pulverizer based on the experimental and industrial sampling tests

0.5%–2% gross power generation of coal power plant is consumed by vertical spindle pulverizer (VSP), and it is essential to select a VSP with better operational performance. Simulated studies of lab-scale mills, which show the similar breakage mechanism with VSP, and industrial sampling on VSPs are conducted to compare energy efficiencies of E and MPS type VSPs (with the grinding media of balls and tread rollers, respectively). The classical energy-size reduction model is modified with the addition of particle size in the exponential form to compare the grinding energy efficiency (product fineness for the certain specific energy) of two lab-scale mills. Also, differences in structure and operational parameters of lab-scale mills are considered. For the industrial sampling tests of two VSPs, recorded data and size distribution of sampled materials are preliminarily compared. Product t10 is selected as the bridge to connect the specific grinding energy and size distribution of products. The modified breakage model is combined with the King's equation to compare the energy efficiency on the premise of feed in the same fineness. Comprehensive comparison of the results obtained from both lab-scale and industrial-scale VSPs suggests that the MPS type VSP shows the higher grinding energy efficiency and lower total energy consumption

Identification and Characterization of MicroRNAs from Barley (Hordeum vulgare L.) by High-Throughput Sequencing

MicroRNAs (miRNAs) are a class of endogenous RNAs that regulates the gene expression involved in various biological and metabolic processes. Barley is one of the most important cereal crops worldwide and is a model organism for genetic and genomic studies in Triticeae species. However, the miRNA research in barley has lagged behind other model species in grass family. To obtain more information of miRNA genes in barley, we sequenced a small RNA library created from a pool of equal amounts of RNA from four different tissues using Solexa sequencing. In addition to 126 conserved miRNAs (58 families), 133 novel miRNAs belonging to 50 families were identified from this sequence data set. The miRNA* sequences of 15 novel miRNAs were also discovered, suggesting the additional evidence for existence of these miRNAs. qRT-PCR was used to examine the expression pattern of six randomly selected miRNAs. Some miRNAs involved in drought and salt stress response were also identified. Furthermore, the potential targets of these putative miRNAs were predicted using the psRNATarget tools. Our results significantly increased the number of novel miRNAs in barley, which should be useful for further investigation into the biological functions and evolution of miRNAs in barley and other species

Rescue from excitotoxicity and axonal degeneration accompanied by age-dependent behavioral and neuroanatomical alterations in caspase-6-deficient mice

Apoptosis, or programmed cell death, is a cellular pathway involved in normal cell turnover, developmental tissue remodeling, embryonic development, cellular homeostasis maintenance and chemical-induced cell death. Caspases are a family of intracellular proteases that play a key role in apoptosis. Aberrant activation of caspases has been implicated in human diseases. In particular, numerous findings implicate Caspase-6 (Casp6) in neurodegenerative diseases, including Alzheimer disease (AD) and Huntington disease (HD), highlighting the need for a deeper understanding of Casp6 biology and its role in brain development. The use of targeted caspase-deficient mice has been instrumental for studying the involvement of caspases in apoptosis. The goal of this study was to perform an in-depth neuroanatomical and behavioral characterization of constitutive Casp6-deficient (Casp6−/−) mice in order to understand the physiological function of Casp6 in brain development, structure and function. We demonstrate that Casp6−/− neurons are protected against excitotoxicity, nerve growth factor deprivation and myelin-induced axonal degeneration. Furthermore, Casp6-deficient mice show an age-dependent increase in cortical and striatal volume. In addition, these mice show a hypoactive phenotype and display learning deficits. The age-dependent behavioral and region-specific neuroanatomical changes observed in the Casp6−/− mice suggest that Casp6 deficiency has a more pronounced effect in brain regions that are involved in neurodegenerative diseases, such as the striatum in HD and the cortex in AD

Separation Process of Fine Coals by Ultrasonic Vibration Gas-Solid Fluidized Bed

Ultrasonic vibration gas-solid fluidized bed was proposed and introduced to separate fine coals (0.5–0.125 mm fraction). Several technological methods such as XRF, XRD, XPS, and EPMA were used to study the composition of heavy products to evaluate the separation effect. Results show that the ultrasonic vibration force field strengthens the particle separation process based on density when the vibration frequency is 35 kHz and the fluidization number is 1.8. The ash difference between the light and heavy products and the recovery of combustible material obtain the maximum values of 47.30% and 89.59%, respectively. The sulfur content of the heavy product reaches the maximum value of 6.78%. Chemical state analysis of sulfur shows that organic sulfur (-C-S-), sulfate-sulfur (-SO4), and pyrite-sulfur (-S2) are confirmed in the original coal and heavy product. Organic sulfur (-C-S-) is mainly concentrated in the light product, and pyrite-sulfur (-S2) is significantly enriched in the heavy product. The element composition, phase composition, backscatter imagery, and surface distribution of elements for heavy product show concentration of high-density minerals including pyrite, quartz, and kaolinite. Some harmful elements such as F, Pb, and As are also concentrated in the heavy product

Impact of particle density on the classification efficiency of the static air classifier in Vertical Spindle Mill

In order to investigate the impact of density on the classification behavior of particles in the static classifier of Vertical Spindle Mill, the sensitivity of overflow yield to the increase of air amount for narrowly sized pyrite, carborundum, quartz and coal samples were compared in a lab-scale classifier, respectively. Response surface methodology is used to analyze the combined effect of size and density on the classification. Wide size classification was also conducted and results show that both the yield and R90 of overflow increase with the decreasing of density, and the growth of air amount would also lead them to rise. The Whiten’s model was applied to illustrate the influence of density on the sharpness of classification, corrected cut size and fishhook effect. Results show that material with a lower density would have a higher fishhook effect parameter, classification sharpness and corrected cut size. The increase of air amount would result in a more evident fishhook effect for the high density material. Based on the Whiten’s model, a new classification efficiency model with the addition of particle density in various forms was established. This new model could describe the classification efficiency of materials with different density in the identical experiment conditions