Huge Value Research Articles

Interpretation of dielectric spectroscopy measurements of ferroelectric nematic liquid crystals

The magnitude of the relative permittivity of the ferroelectric nematic phase (NF) has been the subject of lively scientific discussion since the phase was recently discovered. Dielectric spectroscopy measurements (DSMs) give a huge value of relative permittivity, which depends on the cell thickness, but this is argued to result from a misinterpretation of the DSM results. We have conducted DSM using a set of cells differing in thickness of the NF layer, type of electrodes, and presence/absence of nanoscale-thick surface polymer layers. To model the DSM results, cells are presented by an equivalent electric circuit that includes a capacitor due to the NF layer with frequency dependent complex relative permittivity, capacitors due to surface layers, and a resistor describing the limited conductivity of electrodes. DSM results for different cells with the same liquid crystal in the NF phase are semiquantitatively reproduced by the same set of physical parameters if a huge relative permittivity of the NF, which is even orders of magnitude larger than the measured apparent values, is assumed. We show that the capacitance of surface layers should also be considered in cells with no polymer alignment layer on the electrodes. Published by the American Physical Society 2024

Sprayable Nanocomposites Hydrogel for Wound Healing and Skin Regeneration.

Wound management remains a critical challenge worldwide and imposes a huge financial burden on every nation. Hydrogels are promising for biomedical applications because of their extracellular matrix (ECM) like structure, good biocompatibility and multifunctional bioactivity. However, the poor mechanical properties and inconvenient operation of traditional hydrogels make it difficult to meet the complex and multifaceted needs of clinical practice. In recent years, the multifunctional nanocomposites hydrogel with especially sprayable feature have shown enhanced mechanical properties and facile operation, which enable their huge clinical applications value. A unique and powerful nanocomposite hydrogels (NCH) platform is developed by combining the many advantages of nanomaterials and hydrogels, which can achieve efficient trauma repair. This work reviews important advances on the preparation, functions and applications of sprayable NCH platforms. The challenges and future trends in the field with the aim of providing researchers with clarity on the past, present, and future of the emerging field of sprayable NCH are also proposed in detail.

Recent Research Progress on Surface Modified Graphite Carbon Nitride Nanocomposites and Their Photocatalytic Applications: An Overview

Semiconductors with visible light catalytic characteristics can realize the degradation of pollutants, CO2 reduction, and hydrogen preparation in sunlight. They have huge application value in the fields of environmental repair and green energy. Graphite phase nitride (g-C3N4, CN) is widely used in various fields such as photocatalytic degradation of pollutants due to its suitable gap width, easy preparation, low cost, fast visible light response, and rich surface activity sites. However, the absorption rate of ordinary CN on visible light is low, and the carriers are easy to recombination, making the lower optical catalytic activity. Therefore, in order to improve the photocatalytic characteristics of the CN, it is necessary to make the surface modification. This article first introduces several main methods for the current surface modification of CN, including size regulation, catalyst embedding, defect introduction, heterostructure construction, etc., and then summarizes the optical catalytic application and related mechanisms of CN. Finally, some challenges and development prospects of CN in preparation and photocatalytic applications are proposed.

A Financial Analysis and Valuation of Diamondback Energy

Because of the importance of its products and huge value, the oil and gas industry itself occupies an important position in the national economic system. However, the development of this industry is unbalanced and insufficient, with large differences in market size, liquidity, solvency, profitability, valuation, and growth potential, and few companies have achieved good performance in all of these dimensions. This study delves into the unbalanced development and varied performance metrics among key petrochemical companies listed in the U.S. stock market, utilizing both fundamental analysis and non-financial analysis method, as well as to conduct a specific study on the competitive situation of Diamondback Energy. This study has elucidated that Diamondback Energy lags behind its peers in terms of liquidity and solvency. However, it is worth noting that despite macroeconomic challenges such as economic downturns and industry-wide downturns, its profitability remains relatively strong within the industry. Additionally, it holds a certain advantage over its peers in terms of financial valuation and growth potential, making it a growth-oriented enterprise. The study suggests that investors should consider market volatility and the company's management risk when entering the oil and gas industry in order to maximize returns.

Electro-Thermo-Magnetic Effect-Induced Large Thermoelectric Performance of Calcium Cobaltite Nanocomposites.

As attractive thermoelectric oxides, Ca3Co4O9-based materials have been intensively studied for their applications in recent years. However, their thermoelectric performance is enormously limited due to the contradiction of electrical resistivity and thermal conductivity. Herein, BaFe12O19 nanospheres were introduced into the Ca3Co4O9 matrix. The metallic Ag, ferrites, and matrix phase survived together, and a high density of nanoscale BaFe12O19 precipitation was observed. The reduction of work function could lead to band bending and form an interface potential due to the electro-thermo-magnetic effect contributing to the hole migration. As a result, a huge ZT value of 0.51 for the 8 wt % BaFe12O19/Ca3Co4O9 nanocomposites was obtained at 1073 K, accompanied by a low electrical resistivity of 6.7 mΩ·cm and a high Seebeck coefficient of 217.5 μV/K. In addition, a significant reduction of thermal conductivity (1.11 W/(m·K)) occurred, which was due to the nanoscale ferromagnetic phase effectively scattering the mid- and short-wavelength heat-carrying phonons. The synergistic enhancement of thermoelectric performance confirmed that the electro-thermo-magnetic effect is an effective way to solve the challenging problem of performance deterioration in oxide thermoelectric materials.

A study on value addition of cow dung-based anaerobic sludge for biomethane and bio-oil production via co-liquefaction with rice straw and clam shells as a catalyst.

The waste management sector is moving towards sustainable approaches for facilitating resource-recovery possibilities. Agriculture residue (rice straw), cow dung (cattle waste), and clam shells from the ocean are the primary waste materials possessing a huge value addition opportunity. In this study, the effective usage of rice straw and anaerobic sludge from cow dung for bio-energy production was studied. Cow dung was initially anaerobically processed for the generation of biomethane and sludge in a digester for a retention time of 40 days. The anaerobic sludge with rice straw was hydrothermally processed in varying proportions of 1 : 0, 0 : 1, 1 : 1,1 : 2, 2 : 1, 3 : 1, 1 : 3 and temperatures of 240-360 °C for 1 hour with varying biomass loads of 50, 75, 100, 125, and 150 g. Additionally, clam shells, one of the best bioresources, were used as a catalyst in the hydrothermal process at concentrations of 0.2-1 wt%. The maximum bio-oil produced was 36.23 wt% at a temperature of 320 °C, with a biomass load of 100 g, mixed proportion of 2 : 1 and catalyst loading of 0.6 wt%. The produced bio-oil comprised hydrocarbons, aldehydes, and carboxylic acids, as confirmed through GC-MS. In the anaerobic study, ≈0.018 m3 cumulative gas was produced at a retention time of 40 days. The biochar had a higher carbon content and its feasibility for further usage shows promise towards sustainability.

Mesh-controllable multi-level-of-detail text-to-3D generation

Text-to-3D generation is a challenging but significant task and has gained widespread attention. Its capability to rapidly generate 3D digital assets holds huge potential application value in fields such as film, video games, and virtual reality. However, current methods often face several drawbacks, including long generation times, difficulties with the multi-face Janus problem, and issues like chaotic topology and redundant structures during mesh extraction. Additionally, the lack of control over the generated results limits their utility in downstream applications. To address these problems, we propose a novel text-to-3D framework capable of generating meshes with high fidelity and controllability. Our approach can efficiently produce meshes and textures that match the text description and the desired level of detail (LOD) by specifying input text and LOD preferences. This framework consists of two stages. In the coarse stage, 3D Gaussians are employed to accelerate generation speed, and weighted positive and negative prompts from various observation perspectives are used to address the multi-face Janus problem in the generated results. In the refinement stage, mesh vertices and faces are iteratively refined to enhance surface quality and output meshes and textures that meet specified LOD requirements. Compared to the state-of-the-art text-to-3D methods, extensive experiments demonstrate that the proposed method performs better in solving the multi-face Janus problem, enabling the rapid generation of 3D meshes with enhanced prompt adherence. Furthermore, the proposed framework can generate meshes with enhanced topology, offering controllable vertices and faces with textures featuring UV adaptation to achieve multi-level-of-detail(LODs) outputs. Specifically, the proposed method can preserve the output’s relevance to input texts during simplification, making it better suited for mesh editing and rendering efficiency. User studies also indicate that our framework receives higher evaluations compared to other methods.

The Renovation Scheme of Historical and Cultural Blocks in the City--Taking Yongqing Fang of Guangzhou as an Example

Since 2006, Guangzhou has started the old city renovation work on the Enning Road plot, and the transformation planning has been discussed for more than ten years, it finally changed from "large-scale relocation, large-scale demolition and large-scale construction" to "protection, renewal and utilization", and put forward the urban renewal model of "micro-transformation" in 2016. The renovation was relatively successful, turning Yongqing Fang into a famous scenic spot in Guangzhou and adding huge commercial value. Therefore, the researchers decided to study the value of the "micro-renovation" case of Yongqing Fang in Guangzhou for the renovation plan of historical and cultural blocks in the city. The method of field investigation was adopted in this study. Data and pictures were obtained from field shooting and measurement, as well as some from the official office of Yongqingfang and academic literature. The results show that the "micro transformation" model proposed in the renovation of Yongqing Fang is of innovative significance, which provides a new idea and perspective for the renovation of historical and cultural blocks in the city.

Edge and dense attention U-net for atrial scar segmentation in LGE-MRI

The segmentation of atrial scars in LGE-MRI images has huge potential value for clinical diagnosis and subsequent treatment. In clinical practice, atrial scars are usually manually calibrated by experienced experts, which is time-consuming and prone to errors. However, automatic segmentation also faces difficulties due to myocardial scars’ small size and variable shape. The present study introduces a dual branch network, incorporating edge attention, and deep supervision strategy. Edge attention is introduced to fully utilize the spatial relationship between the scar and the atrium. Besides, dense attention is embedded in bottom layer to solve feature disappearance. At the same time, deep supervision accelerates the convergence of the model and improves segmentation accuracy. The experiments were conducted on the 2022 atrial and scar segmentation challenge dataset. The results demonstrate that the proposed method has achieved superior performance.

Packaging code and data for reproducible research: A case study of journey time statistics

The effective and ethical use of data to inform decision-making offers huge value to the public sector, especially when delivered by transparent, reproducible, and robust data processing workflows. One way that governments are unlocking this value is through making their data publicly available, allowing more people and organisations to derive insights. However, open data is not enough in many cases: publicly available datasets need to be accessible in an analysis-ready form from popular data science tools, such as R and Python, for them to realise their full potential. This paper explores ways to maximise the impact of open data with reference to a case study of packaging code to facilitate reproducible analysis. We present the jtstats project, which consists of a main Python package, and a smaller R version, for importing, processing, and visualising large and complex datasets representing journey times, for many transport modes and trip purposes at multiple geographic levels, released by the UK Department for Transport (DfT). jtstats shows how domain specific packages can enable reproducible research within the public sector and beyond, saving duplicated effort and reducing the risks of errors from repeated analyses. We hope that the jtstats project inspires others, particularly those in the public sector, to add value to their data sets by making them more accessible.

Development of Healthy and Clean-Label Crackers Incorporating Apple and Carrot Pomace Flours

The valorization of fruit and vegetable side-streams from the juice industry is an important contribution to the optimization of food resources and is an environmentally friendly practice in line with the concepts of circular economy and sustainability. The aim of this work is to incorporate them back into the food value chain by adding them as ingredients in staple foods like crackers. This is also important in terms of food fortification, as they are rich in nutrients and bioactive compounds. Crackers are popular snacks with a huge global market value, enjoyed by consumers of all ages. The current study aims to integrate flour from dried apple and carrot pomaces, resulting from juice processing, as natural ingredients with potential health benefits. The incorporation levels ranged from 20 to 40% dry weight in crackers, and their impact on physicochemical and mechanical properties was evaluated, as well as bioactivity (potential impact on health) and sensory acceptance. The addition of pomaces resulted in significant changes in texture and color, as well as enhancing the antioxidant activity of the crackers. Crackers containing pomace flours, except for the cracker with 40% carrot pomace, showed a high overall sensory acceptability and good intentions to buy.

Characterization and utilization potential of typical molybdenum tailings in Shaanxi Province, China.

Shaanxi Province is located in the most important molybdenum ore district in the world, but a lot of molybdenum tailings have been released, polluting the environment and wasting resources seriously. Taking eleven tailing samples collected at the main molybdenum tailings ponds in Shaanxi Province as the research object, the physical, chemical, and mineralogical characteristics were studied through scanning electron microscope, X-ray fluorescence, X-ray diffraction, inductively coupled plasma mass spectrometer, and others. The ecological risk and utilization potential of molybdenum tailings were investigated through leaching test, geo-accumulation index, potential ecological risk assessment, and other methods. The results demonstrated that the main chemical and mineralogical composition of various molybdenum tailings in Shaanxi Province is similar, and the predominant mineral composition is muscovite, quartz, microcline, and calcite. The potential ecological risk of heavy metals in six molybdenum tailings is high, while Pb and Cd are the main pollution risk elements. Molybdenum tailings contain considerable amounts of critical minerals with huge potential economic value, and molybdenum tailings with high environmental hazards could be converted into a possible source for critical minerals by recovering the critical minerals and repurposing the secondary tailings as an additive or cement substitute. This study provides an innovative idea for the pollution treatment of molybdenum tailings and indicates the prospect of molybdenum tailings as a secondary source for critical minerals.

Comparison of Bacterial Communities in Five Ectomycorrhizal Fungi Mycosphere Soil.

Ectomycorrhizal fungi have huge potential value, both nutritionally and economically, but most of them cannot be cultivated artificially. To better understand the influence of abiotic and biotic factors upon the growth of ectomycorrhizal fungi, mycosphere soil and bulk soil of five ectomycorrhizal fungi (Calvatia candida, Russula brevipes, Leucopaxillus laterarius, Leucopaxillus giganteus, and Lepista panaeola) were used as research objects for this study. Illumina MiSeq sequencing technology was used to analyze the community structure of the mycosphere and bulk soil bacteria of the five ectomycorrhizal fungi, and a comprehensive analysis was conducted based on soil physicochemical properties. Our results show that the mycosphere soil bacteria of the five ectomycorrhizal fungi are slightly different. Escherichia, Usitatibacter, and Bradyrhizobium are potential mycorrhizal-helper bacteria of distinct ectomycorrhizal fungi. Soil water content, soil pH, and available potassium are the main factors shaping the soil bacterial community of the studied ectomycorrhizal fungi. Moreover, from the KEGG functional prediction and LEfSe analysis, there are significant functional differences not only between the mycosphere soil and bulk soil. 'Biosynthesis of terpenoidsand steroids', 'alpha-Linolenic acid metabolism', 'Longevity regulating pathway-multiple species', 'D-Arginine and D-ornithine metabolism', 'Nitrotoluene degradation' and other functions were significantly different in mycosphere soil. These findings have pivotal implications for the sustainable utilization of ectomycorrhizal fungi, the expansion of edible fungus cultivation in forest environments, and the enhancement of derived economic benefits.

Homoplantaginin alleviates intervertebral disc degeneration by blocking the NF-κB/MAPK pathways via binding to TAK1

Intervertebral disc degeneration (IVDD) is a common degenerative disease which is closely related to low back pain (LBP) and brings huge economic and social burdens. In this study, we explored the therapeutic effects of Homoplantaginin (Hom) for IVDD due to its convincing anti-inflammatory and antioxidant functions. TNF-α was used to simulate the inflammatory environment for nucleus pulposus (NP) cells in vitro. We verified that Hom could alleviate the TNF-α-induced inflammation and disturbance of ECM homeostasis through blocking the NF-κB/MAPK signaling pathways. Subsequently, we screened the binding targets of Hom and confirmed that Hom could directly bind to TAK1 and inhibit its phosphorylation to down-regulate the inflammation-related pathways. The therapeutic effects of Hom on IVDD were further validated through a needle puncture rat model in vivo. Overall, Hom was a promising small molecule for IVDD early intervention, possessing huge clinical translational value.

1DCAE-TSSAMC: Two-Stage Multi-Dimensional Spatial Features Based Multi-View Deep Clustering for Time Series Data

At present, as a research hotspot for time series data (TSD), the deep clustering analysis of TSD has huge research value and practical significance. However, there still exist the following three problems: (1) For deep clustering based on joint optimization, the inevitably mutual interference existing between deep feature representation learning progress and clustering progress leads to difficult model training especially in the initial stage, the possible feature space distortion, inaccurate and weak feature representation; (2) Existing deep clustering methods are difficult to intuitively define the similarity of time series and rely heavily on complex feature extraction networks and clustering algorithms. (3) Multidimensional time series have the characteristics of high dimensions, complex relationships between dimensions, and variable data forms, thus generating a huge feature space. It is difficult for existing methods to select discriminative features, resulting in generally low accuracy of methods. Accordingly, to address the above three problems, we proposed a novel general two-stage multi-dimensional spatial features based multi-view deep clustering method 1DCAE-TSSAMC (One-dimensional deep convolutional auto-encoder based two-stage stepwise amplification multi-clustering). We conducted verification and analysis based on real-world important multi-scenario, and compared with many other benchmarks ranging from the most classic approaches such as K-means and Hierarchical to the state-of-the-art approaches based on deep learning such as Deep Temporal Clustering (DTC) and Temporal Clustering Network (TCN). Experimental results show that the new method outperforms the other benchmarks, and provides more accurate, richer, and more reliable analysis results, more importantly, with significant improvement in accuracy and spatial linear separability.

Isolation, Purification, and Identification of Bacitracin-producing Bacillus licheniformis from Fresh Feces of Healthy Pigs.

Bacillus licheniformis and bacitracin have a huge application market and value in the fields of medicine, chemistry, aquaculture, agricultural, and sideline products. Therefore, the selection of B. licheniformis with high production of bacitracin is of great importance. In this experimental protocol, Bacillus with a high yield of bacitracin was isolated, purified, and identified from the fresh feces of healthy pigs. The inhibitory effect of secondary metabolite bacitracin on Micrococcus luteus was also tested. Thin-layer chromatography and high-performance liquid chromatography were used for the qualitative and quantitative detection of bacitracin. The physiological and biochemical characteristics of B. licheniformis were determined by relevant kits. The phylogenetic relationships of B. licheniformis were determined and constructed using gene sequence detection. This protocol describes and introduces the standard isolation, purification, and identification process of B. licheniformis from animal fresh feces from multiple perspectives, providing a method for the large-scale utilization of B. licheniformis and bacitracin in factories.

Volume dependence of the charge density wave phase transitions

ABSTRACT We analyse the volume dependence of the charge density wave phase transition temperature T CDW for 16 one and two dimensional materials such as the rare earth tritellurides TbTe 3 , ErTe 3 , TmTe 3 DyTe 3 , the transition metal dichalcogenide 2H-NbSe 2 , and the quasi-one dimensional conductors K 0.3 MoO 3 , NbSe 3 , ( TaSe 4 ) 2 I . The volume dependence is taken in the form of the logarithmic derivative of T CDW in function of the strain components. We point out some characteristics of this parameter. This parameter is dimensionless with an absolute value of about 10 obtained from the measurements of the thermal expansion, the longitudinal elastic constants and pressure dependence for 11 one- and two-dimensional CDW systems. In contrast a huge positive value of about 100 is found at the lower charge density wave transition in TbTe 3 , ErTe 3 , TmTe 3 and DyTe 3 .

WHY GOOGLE GLASSES FAILED?

In this research paper we are basically trying to find out why Google Glasses failed as a product in the market. Google Glasses was launched back in 2012 as a product that created a lot of buzz in the market as “Wearable Smart Glasses”. But it never managed to effectively capitalise on the hype that surrounded the product and failed in capturing the market share and did not turn out as a money-making product. On the contrary, Google lost $895 million and incurred heavy losses and ultimately had to give up on the product. It failed to captivate the imagination of the people and people were not really interested in the product. When we dig deeper into the problem, we found several loopholes and flaws in the product, and in the basic business idea on the fundamental level. First of all, the designers of the idea and the product lacked the clarity as to whether the glasses would be considered as a fashionable device or just stand out as a utilitarian product. The problem was also with the price of the product, as this was so expensive that only the rich could afford and hence inaccessible to the masses and a limited target market. The people were also concerned with the privacy aspect as the current generation is quite conscious about their data being recorded and people did not really like this aspect of Google Glasses. People were even concerned with the safety of this product. People were not really great fans of the design of the glasses and generally regarded the product as uncool. Moreover, the grim problem of low battery life on the glasses was another major flaw. Nobody likes it, if they have to charge their product every now and then, it really drops the satisfaction level, and this happened with Google Glasses as well. The design of the glasses was unappealing and the glasses regularly faced heating and language issues. So overall these were the factors we found out that contributed in the product ending up as a huge failure in the market, despite the fact that it had a huge brand value as the likes of Google backing it up.

The prospect exploration of artificial intelligence technology and its application

With the rapid development of science and technology, artificial intelligence technology has become one of the most popular research fields in today's society. From intelligent voice assistants to self-driving cars, to medical diagnostics and financial risk control, AI technology has shown huge potential and value in all fields. This paper deeply explores the current situation, development trend and its application prospect of artificial intelligence technology in various industries. This paper briefly introduces the development process of artificial intelligence technology, including its origin, development status and key technologies. Then, it focuses on the application cases of AI technology in healthcare, finance, education, industry and other fields, and evaluates its impact and potential value. It discusses the challenges of artificial intelligence technology, such as data security and privacy protection, algorithm fairness and moral considerations. In view of these problems, the corresponding solution strategies and development suggestions are put forward. The future development trend of artificial intelligence technology is discussed, including the research and application of cutting-edge technologies such as deep learning, natural language processing and emotional computing. The conclusion pointed out that artificial intelligence technology will continue to change human life in the future and bring more innovation and breakthrough to various industries.

Promoting a Cobalt Complex of Qingzhuan Dark Tea Polysaccharides on Fracture Healing in Rats.

Fractures occur commonly with multiple injuries, and their incidence has increased in recent years. Trace amounts of cobalt are necessary for many living organisms as it stimulates hematopoiesis and improves bone health. However, cobalt is also toxic, as it might cause allergic reactions and tissue destruction. These factors limit the application of cobalt in some medical fields. We studied the tea polysaccode-cobalt complex (TPS-Co) prepared from Qingzhuan Dark Tea polysaccharides. We used 6-week-old Sprague-Dawley rats to establish a femoral fracture model and evaluated the effects of CoCl2 and TPS-Co on the healing of femoral fractures. In this study, treatment with TPS-Co for the same content of cobalt intake decreased the side effects associated with CoCl2 treatment and accelerated the healing of femoral fractures in rats. This treatment method promoted angiogenesis by upregulating the expression of vascular endothelial growth factor and hypoxia-inducible factor. Bone formation was promoted via the upregulation of the expression of bone morphogenetic protein 2 and serum bone alkaline phosphatase. TPS-Co was found to actively regulate bone and vascular systems, resulting in significant bone regeneration effects. Therefore, the Qingzhuan Dark Tea polysaccharide cobalt complex might be used as an additive or drug to promote fracture healing, and thus, it might have a huge market value.