Greater Effect Research Articles

Influences of reaction parameters and complexation pretreatments on the distribution of phosphorus during hydrothermal carbonization of dewatered sewage sludge

This study investigated the effects of reaction parameters and pretreatments with complexing agents, namely ethylenediaminetetraacetic acid (EDTA), glutamate diacetic acid (GLDA), and citric acid (CA), on the phosphorus contents and forms in the sludge hydrothermal carbonization products. The results showed that reaction temperature had the greatest effect on the distribution and forms of phosphorus in liquid and solid products. High reaction temperatures inhibited the transfer of phosphorus from the solid phase to the liquid phase. Indeed, the proportions of phosphorus in the liquid phases only accounted for 3.56 % at reaction temperature and time of 160 °C and 60 min, respectively. However, this proportion increased to 16.32, 12.62, and 13.15 % following complexation pretreatments with EDTA, GLDA, and CA at 0.1 mol/L, respectively. In addition, the complexation pretreatments enhanced the transfer of phosphorus from the solid phase to the liquid phase. The total phosphorus contents in the liquid phase (TPL) reached 896.46 mg/L. The finding can be explained by the binding of the complexing agents with metal ions, such as Mg, Ca, Al, and Fe, transferring phosphorus originally bound to these metal ions to the liquid phase. In addition, the results demonstrated the effectiveness of the magnesium ammonium phosphate (MAP) crystallization method for recovering phosphorus from the EDTA-pretreated liquid product. X-ray diffraction (XRD) and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) analyses showed high purity and crystallinity of the obtained struvite to some extent.

Failure behaviors and acoustic emission characteristics of flawed granite of different grain sizes: Insights from true triaxial experiments with a free face

In this study, a group of experiments using true triaxial stress conditions with free face loading are performed on granite specimens with non-penetrating double flaws. The crack development and failure characteristics of these specimens are explored by integrating video of the free face and acoustic emission technology, with the combination of the four different intermediate principal stresses and three different grain sizes of the granite chosen as variables. First, surface flaws with a depth of 50 mm are found to have limited influence on the specimen’s failure mode. The intermediate principal stress has a greater effect as it inhibits the development of surface cracks; however, surface cracks develop much more readily in coarse-grained specimens than in other specimens. Second, when the intermediate principal stress exceeds 10 MPa, the rock burst failure phenomenon occurs in the specimen. Third, irrespective of changes in the intermediate principal stress and granite specimen grain size, the specimens primarily fail by tensile-shear failure and shear failure. Extending inward from the free face in the σ3 direction, according to the failure types, the failure types can be classified into tensile failure, shear failure, and tensile-shear failure. Finally, using the stress state synthesis method, the specimen’s stress state and crack distribution mechanism on the σ2 loading plane are analyzed.

Abstract 4761: Understanding three-drug combinations: optimizing scheduling while avoiding toxicity

Abstract The promise of combination therapies in managing tumor resistance is constrained by the therapeutic window (the difference between efficacious and toxic doses). We have sought to understand the impact of dose scheduling on the emergence of resistance, using a mathematical model-based approach linking pharmacokinetics (PK) to a parsimonious evolutionary model of tumor growth incorporating the emergence of drug resistance. Here, we analyze the potential of a three-drug combination to minimize toxicity while preventing the emergence of resistance. We simulated eight tumor subpopulations representing resistance to one, two or three hypothetical drugs, using an exponential growth model with growth penalties based on drug concentrations. We used the model to simulate the effects of pairs of antagonistic, synergistic, and additive drugs on the growth of sensitive and resistant populations in a tumor. Final tumor volume and resistant population were used to compare the efficacy of various drug schedules. We assumed an overlapping neutropenia-like toxicity as the dose-limiting toxicity for the three drug combination, which we have previously shown to be proportional to the peak moving average drug concentration over 18 days. Final tumor volume and peak toxicity were used to compare the effectiveness of various dosing strategies and interaction combinations. Synchronous dosing results in the greatest drug interaction effect between any two drugs. When all interactions between the three drugs are either antagonistic or synergistic, the greatest effect is observed when all drugs are dosed simultaneously. The drugs are most toxic when all three are dosed simultaneously or nearly simultaneously. Our work shows that time sensitivity—that is, the magnitude of the changes in efficacy associated with small changes in schedule—varies with phase offset. Scheduling is most time sensitive when all drugs are dosed simultaneously or nearly simultaneously; dosing of two drugs simultaneously is less time sensitive. Three-drug combinations are an effective means of preventing complete resistance. While simultaneous dosing of two or more drugs confers the greatest efficacy, such simultaneous dosing results in greater peak toxicity because of higher simultaneous drug concentrations. A potential compromise is the simultaneous dosing of two of the three drugs, which results in an intermediate toxicity. Dosing of two drugs simultaneously is also less time sensitive, advantageous in a practical sense as it is more robust to patient dosing error. While the approach used here is based on hypothetical drug properties, it provides a framework that is readily applicable to real-world drug combinations, with the potential for practical insights to guide the framing of the Target Product Profile for three-drug combinations. Citation Format: Madison Stoddard, Lin Yuan, Debra Van Egeren, Andrew Chen, Dean Bottino, Arijit Chakravarty. Understanding three-drug combinations: optimizing scheduling while avoiding toxicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4761.

Overexpression of CD44 as a predictor of metastatic potential in patients with colorectal cancer

Objective. To correlate CD44 expression with the clinicopathological characteristics of patients with colorectal carcinoma (CRC).
 Materials and methods. This study included 90 patients with CRC who underwent curative surgical resection. Standard histopathological techniques and immunohistochemistry analysis was used to investigate CD44 expression. Semi–quantitative scoring was used to categorize CD44 expression levels. Patients' clinicopathological characteristics were retrospectively examined.
 Results. Overexpression of CD44 was found in 46.7% of all patients with CRC. Patients with right colon cancer had the highest CD44 expression (54,6%). Overexpression of CD44 was present in 69.6% of patients with metastatic lesions in visceral organs. We found statistically significant differences between CD44 overexpression and the presence of visceral metastases (p = 0.015), different T categories (p = 0.011), N status (p = 0.006), and G differentiation (p = 0.011). Our results showed that the disease stage has the greatest effect on CD44 overexpression (p <0.001).
 Conclusion. Overexpression of CD44 could be a reliable predictor of metastatic potential and poor prognosis in patients with CRC.

Effects of the Molecular Structure of Malodor Substances and Their Masking on 1,2-Dioleoyl-sn-glycero-3-phosphocholine Molecular Layers.

Certain odors have been shown not only to cause health problems and stress but also to affect skin barrier function. Therefore, it is important to understand olfactory masking to develop effective fragrances to mask malodors. However, olfaction and olfactory masking mechanisms are not yet fully understood. To understand the mechanism of the masking effect that has been studied, the responses of several target substance (TS) molecules-1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) mixed molecular layers to odorant (OD) molecules were examined as a simple experimental model of epithelial cellular membranes injured by TS molecules. Here, we examined trans-2-nonenal, 1-nonanal, trans-2-decenal, and 1-decanal as TS molecules to clarify the effects of double bonds and hydrocarbon chain lengths on the phospholipid molecular layer. In addition, benzaldehyde and cyclohexanecarboxaldehyde were utilized as OD molecules to clarify the masking effect of the aromatic ring. Surface pressure (Π)-area (A) isotherms were measured to clarify the adsorption or desorption of TS and OD molecules on the DOPC molecular layer. In addition, Fourier transform infrared spectroscopy was performed to clarify the interactions among DOPC, TS, and OD molecules. We found that TS molecules with and without double bonds had different effects on the DOPC molecular layer and that molecules with shorter chain lengths had greater effects on the DOPC molecular layer. Furthermore, OD molecules with aromatic rings counteracted the effects of the TS molecules. On the basis of this research, not only a detailed mechanism by which odor molecules affect lipid membranes without mediating olfactory receptors is elucidated but also more effective OD molecules with masking effects are proposed.

The Impacts of Animated Transport Safety Advertising Cross Two Cultures

ABSTRACT Transport safety campaigns are valuable for public health, as they prevent traffic fatalities and collisions. Authorities and nonprofit organizations attempt to promote transport safety by advertising via social media. Understanding the factors that make online transport safety campaigns successful is also important. However, studies exploring the impact of animated videos on transportation safety are scarce. We adopted the stimuli-organism-response (S-O-R) framework to examine the impact of music and graphics on transport users’ emotional states and behaviors. We also considered how the reactions varied across cultures. The respondents were shown animated transport safety advertisements produced by Metro Trains in Melbourne, Australia. A total of 217 valid questionnaires were collected from transportation users in Taiwan and Vietnam. In contrast, we explored the spillover effects of an animated transport safety promotion campaign across cultures. The findings show that music significantly impacts people’s emotions, which, in turn, are associated with positive behavioral intentions. Self-efficacy had the greatest effect on behavioral responses. We also found that transport users in Taiwan were more influenced by graphics, whereas those in Vietnam were more affected by music in the S-O path. Fear arousal affects the behavioral intentions of Vietnamese transportation users in the O-R path. Self-efficacy is the dominant factor affecting the ability of Taiwan’s transport users to obey traffic rules. Transport safety advertising should be designed to evoke emotions, and specific stimulus elements should be adjusted according to cultural preferences.

Triboelectric-Responsive Drug Delivery Hydrogel for Accelerating Infected Wound Healing.

Electrotherapy is of great interest in the field of tissue repair as an effective, well-tolerated, and noninvasive treatment. Triboelectric nanogenerator (TENG) has shown advantages in promoting wound healing due to its peak output characteristic and low Joule heating effect. However, it is limited in infected wound healing due to poor antimicrobial capacity. Here, a wearable triboelectric stimulator (WTS) is developed that consists of a flexible TENG (F-TENG) and a triboelectric-responsive drug delivery hydrogel (TR-DDH) for healing of bacterium-infected wounds. F-TENG can generate pulsed current to wounds by converting mechanical energy from body movements. Polypyrrole is prone to reduction and volume contraction under electrical stimulation, resulting in desorption of curcumin nanoparticles (CUR NPs) from the polypyrrole in TR-DDH. Therefore, the highly efficient and controllable release of CUR NPs can be achieved by triboelectric stimulation. According to the in vitro and in vivo experiments, WTS has the greatest antimicrobial effect and the fastest promotion of infected wound healing compared to treatment with electrical stimulation or curcumin. Finally, the safety assessment demonstrates that the WTS has excellent tissue safety for chronic wound healing. Synergistic therapy with WTS provides an efficient strategy for chronic wound healing and smart-responsive drug delivery systems.

Development of Novel Conditioning Method Using Thermal Shape Memory Characteristics of Polyurethane CMP Pad

Traditionally, the pad roughness has been maintained by wearing down the polyurethane pad with diamond disk. However, that method generates debris and reduces pad lifetime. This study propose a new approach to pad surface recovery by synthesizing a polyurethane-based raw material that exhibits shape memory behavior and can recover its shape upon heating. The findings suggest that the pad’s surface can be maintained by utilizing its shape memory trait and designing a system to heat the pad. The pad recovery tests were conducted using universal test machine (UTM) samples and found that, in terms of heat recovery, increasing the temperature had a greater effect than increasing the exposure time. CMP test was performed by using three conditioning potions: diamond disk conditioning, heat conditioning, and no conditioning. The results showed that pad asperity was recovered more efficiently with heat conditioning than with no conditioning (demonstrated by a 19% higher removal rate). The experimental results can be expected that combines diamond disk conditioning with heat conditioning could be a superior alternative for pad surface refreshment. Shape memory pads can return to their original form, leading to better chemical mechanical planarization (CMP) performance and an extended pad lifetime.

Axial length, more than aging, decreases the thickness and superficial vessel density of retinal nerve fiber layer in non-glaucomatous eyes

PurposeThis study seeks to build a normative database for the vessel density of the superficial retina (SVD) and evaluate how changes and trends in the retinal microvasculature may be influenced by age and axial length (AL) in non-glaucomatous eyes, as measured with optical coherence tomography angiography (OCTA). MethodsWe included 500 eyes of 290 healthy subjects visiting a county hospital. Each participant underwent comprehensive ophthalmological examinations and OCTA to measure the SVD and thickness of the macular and peripapillary areas. To analyze correlations between SVD and age or AL, multivariable linear regression models with generalized estimating equations were applied.ResultsAge was negatively correlated with the SVD of the superior, central, and inferior macular areas and the superior peripapillary area, with a decrease rate of 1.06%, 1.36%, 0.84%, and 0.66% per decade, respectively. However, inferior peripapillary SVD showed no significant correlation with age. AL was negatively correlated with the SVD of the inferior macular area and the superior and inferior peripapillary areas, with coefficients of −0.522%/mm, −0.733%/mm, and −0.664%/mm, respectively. AL was also negatively correlated with the thickness of the retinal nerve fiber layer and inferior ganglion cell complex (p = 0.004).ConclusionAge and AL were the two main factors affecting changes in SVD. Furthermore, AL, a relative term to represent the degree of myopia, had a greater effect than age and showed a more significant effect on thickness than on SVD. This relationship has important implications because myopia is a significant issue in modern cities.

Effect of Negative Online Reviews and Physician Responses on Health Consumers' Choice: Experimental Study.

The COVID-19 pandemic has highlighted the importance of online medical services. Although some researchers have investigated how numerical ratings affect consumer choice, limited studies have focused on the effect of negative reviews that most concern physicians. This study aimed to investigate how negative review features, including proportion (low/high), claim type (evaluative/factual), and physician response (absence/presence), influence consumers' physician evaluation process under conditions in which a physician's overall rating is high. Using a 2×2×2 between-subject decision-controlled experiment, this study examined participants' judgment on physicians with different textual reviews. Collected data were analyzed using the t test and partial least squares-structural equation modeling. Negative reviews decreased consumers' physician selection intention. The negative review proportion (β=-0.371, P<.001) and claim type (β=-0.343, P<.001) had a greater effect on consumers' physician selection intention compared to the physician response (β=0.194, P<.001). A high negative review proportion, factual negative reviews, and the absence of a physician response significantly reduced consumers' physician selection intention compared to their counterparts. Consumers' locus attributions on the negative reviews affected their evaluation process. Physician attribution mediated the effects of review proportion (β=-0.150, P<.001), review claim type (β=-0.068, P=.01), and physician response (β=0.167, P<.001) on consumer choice. Reviewer attribution also mediated the effects of review proportion (β=-0.071, P<.001), review claim type (β=-0.025, P=.01), and physician response (β=0.096, P<.001) on consumer choice. The moderating effects of the physician response on the relationship between review proportion and physician attribution (β=-0.185, P<.001), review proportion and reviewer attribution (β=-0.110, P<.001), claim type and physician attribution (β=-0.123, P=.003), and claim type and reviewer attribution (β=-0.074, P=.04) were all significant. Negative review features and the physician response significantly influence consumer choice through the causal attribution to physicians and reviewers. Physician attribution has a greater effect on consumers' physician selection intention than reviewer attribution does. The presence of a physician response decreases the influence of negative reviews through direct and moderating effects. We propose some practical implications for physicians, health care providers, and online medical service platforms.

Effect of non-metallic doping on the electronic structure and optical properties of ZrSe2

The optoelectronic properties of non-metal (B, N, O, C, F) doped and biaxial tensile strain in the x–y direction of O-doped and N-doped ZrSe2, including energy band structure, density of states, dielectric function, and absorption coefficients, have been calculated by a first-principles approach based on density-functional theory. It is shown that the doped system has a low formation energy, indicating that the structure can exist stably. The B, C, and N atom-doped systems show impurity energy levels near the Fermi energy level, narrowing the bandgap, enhancing the electron transport ability, and increasing the electrical conductivity. Biaxial stretching was applied to the ZrSe2 structure before and after O and N doping, and it was found that the stability of the ZrSe2, Zr9Se[Formula: see text]O[Formula: see text] and Zr9Se[Formula: see text]N1 structures was found to decrease gradually with increasing strain. The energy bandwidth of the doped system in the Zr9Se[Formula: see text] O1system at a tensile strain of 4% is a maximum of 0.924[Formula: see text]eV; from the density of states, it is found that there is a very obvious orbital hybridization of Se-4p and Zr-d. The doped system has the largest effect on the dielectric function at 6% tensile strain and on the absorption coefficient at 8%. In the Zr9Se[Formula: see text]N1 system, stretching 8% energy bandwidth is a maximum of 0.788[Formula: see text]eV, the tensile strain of 8% has the greatest effect on the dielectric function, and a tensile strain of 6% has the most significant effect on the absorption coefficient.

The biomechanical effects of bimaxillary osteotomies to the patients with mandibular retraction under incisal clenching.

The purpose of this study is to investigate the biomechanical effect of bimaxillary osteotomies on patients with mandibular retraction. Mandibular retraction, as a typical maxillofacial deformity, and has great adverse effects on TMJ. Bimaxillary osteotomies are widely used to correct symptoms of mandibular retraction. It is necessary to understand the effect of surgery on temporomandibular disc (TMJ). Five patients with mandibular retraction and 10 asymptomatic subjects were involved in this study. Finite element models of preoperative, postoperative and control group were constructed based on the CT data. Nine sets of concentrated forces were used to simulate the muscle effect and contact method was used to simulate the interaction within the TMJs and dentitions. The results showed that bimaxillary osteotomies could effectively improve the maxillofacial morphology and alleviate the overload in TMJ. The facial asymmetry and right chewing side preference could cause imbalanced stress distributions in the TMJs and interfere the surgical treatment.

Body fluids should be identified before estimating the time since deposition (TsD) in microbiome-based stain analyses for forensics.

Identification and the time since deposition (TsD) estimation of body fluid stains from a crime scene could provide valuable information for solving the cases and are always difficult for forensics. Microbial characteristics were considered as a promising biomarker to address the issues. However, changes in the microbiota may damage the specific characteristics of body fluids. Correspondingly, incorrect body fluid identification may result in inaccurate TsD estimation. The mutual influence is not well understood and limited the codetection. In the current study, saliva, semen, vaginal secretion, and menstrual blood samples were exposed to indoor conditions and collected at eight time points (from fresh to 30 days). High-throughput sequencing based on the 16S rRNA gene was performed to characterize the microbial communities. The results showed that a longer TsD could decrease the discrimination of different body fluid stains. However, the accuracies of identification still reached a quite high value even without knowing the TsD. Correspondingly, the mean absolute error (MAE) of TsD estimation significantly increased without distinguishing the types of body fluids. The predictive TsD of menstrual blood reached a quite low MAE (1.54 ± 0.39 d). In comparison, those of saliva (6.57 ± 1.17 d), semen (6.48 ± 1.33 d), and vaginal secretion (5.35 ± 1.11 d) needed to be further improved. The great effect of individual differences on these stains limited the TsD estimation accuracy. Overall, microbial characteristics allow for codetection of body fluid identification and TsD estimation, and body fluids should be identified before estimating TsD in microbiome-based stain analyses.IMPORTANCEEmerged evidences suggest microbial characteristics could be considered a promising tool for identification and time since deposition (TsD) estimation of body fluid stains. However, the two issues should be studied together due to a potential mutual influence. The current study provides the first evidence to understand the mutual influence and determines an optimal process for codetection of identification and TsD estimation for unknown stains for forensics. In addition, we involved aged stains into our study for identification of body fluid stains, rather than only using fresh stains like previous studies. This increased the predictive accuracy. We have preliminary verified that individual differences in microbiotas limited the predictive accuracy of TsD estimation for saliva, semen, and vaginal secretion. Microbial characteristics could provide an accurate TsD estimation for menstrual blood. Our study benefits the comprehensive understanding of microbiome-based stain analyses as an essential addition to previous studies.

Effects of Pollen on Hydrometeors and Precipitation in a Convective System

AbstractAnemophilous (wind‐driven) pollen is one type of primary biological aerosol particle, which can rupture under high humidity conditions and form smaller sub‐pollen particles (SPPs). Both pollen and SPPs can reach the upper troposphere under convective conditions, acting as cloud condensation nuclei (CCN) and ice nucleating particles (INPs), thus influencing cloud formation and precipitation. However, the impacts of these biological aerosols on cold cloud formation and local climate remain unclear as there are large uncertainties on their emission flux and ice nucleating abilities. Here, we incorporate pollen emission and rupture processes in the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) simulations and update the Morrison microphysics scheme within WRF‐Chem using aerosol‐aware INP parameterizations to account for pollen in addition to other anthropogenic and biogenic aerosol. INP parameterizations for pollen and SPP are derived from laboratory experiments. When including pollen rupture rates as observed in a series of chamber studies, SPP concentrations increase, leading to an increase of cloud ice and water by up to 50% and potentially extending the duration of the convective system. Among all simulated hydrometeors, graupel and raindrops exhibit the largest enhancements from the inclusion of SPPs, with intensifying precipitation at the backside of the convective system and a greater spatial extent. Sensitivity simulations indicate that SPPs have a greater effect on cloud microphysical processes than whole pollen grains, and further observational evidence is needed to constrain these processes.

Alexander Hamilton's Constitutional Jurisprudence and the Bank Bill

Abstract Alexander Hamilton's view of law was more than pragmatic. Forward looking, and innovative, it saw law as a creative tool. Often misread, and dismissed, as mere policy preference, it was in fact sophisticated and superbly articulated jurisprudence. In the years between the ratification debate and the proposal for the First Bank of the United States, Hamilton displayed this jurisprudence to great effect.

Effect of Cold Plasma on the Germination and Seedling Growth of Durum Wheat Genotypes

Cold atmospheric pressure plasma (CAP) has attracted increased interest in recent years for possible biomedical, environmental and agricultural applications. A wide range of cold plasma treatment effects is observed in agricultural applications, like effects on the seed germination and seedling growth, but more systematic investigations are needed. The aim of this study was to identify the most appropriate combinations of the plasma source and duration of treatment positively affecting seed germination. In addition, the effect of cold plasma on the seedling growth and osmotic stress tolerance was studied. The seeds of three Bulgarian durum wheat cultivars were treated with cold plasma in twelve variants. The results obtained were processed statistically via two-way ANOVA. The treatment of seeds with a plasma torch for 20 s and the treatment with underwater diaphragm discharge for 5 min when the seeds were placed in both cameras in two different positions (relative to the electrodes between which the plasma is supplied, “+” and “−”) have the greatest positive effect on the all traits related to germination. The analysis of variance reveals that the variation in germination energy, shoot length and root length after the cold plasma treatment of seeds is mainly due to the interaction between the genotype and treatment variant and to a small degree due to the genotype. The treatment of seeds with cold plasma improves the osmoregulation ability of cells and therefore increases the drought resistance of genotypes.

Effect of Vermicompost and Nitrogen Fertilizer on the Growth and Production of Aloe Vera

Purpose: The effect of vermicompost and nitrogen fertilizers on the growth and production of Aloe vera were conducted using factorial based on Randomized Complete Block Design (RCBD).&#x0D; Background: Vermicompost can be used in sustainable agriculture to support growing populations by increasing water holding capacity, nutrient supply, high porosity, adequate ventilation and drainage, and production of plant hormones that have beneficial effects on seed germination.&#x0D; Methods: According to the RCBD method, treatments were included: four levels of vermicompost (V0: Control, V1: 75, V2: 150 and V3: 200 g per pot) and four levels of nitrogen fertilizer (N0: control, N1: 500, N2: 1000, and N3: 1500 mg per pot) using urea.&#x0D; Results: The results showed that application of 150 g of vermicompost and 1000 mg of nitrogen had the highest effect on growth traits, and application of 200 g of vermicompost and 1500 mg of nitrogen had the greatest effect on sucker characteristics, so that the highest number of suckers was obtained by using 200 g of vermicompost and 1000 and 1500 mg of nitrogen. However, simultaneous application of 150 g of vermicompost and 1000 mg of nitrogen had the greatest effect on plant height, number of leaves, and leaf diameter, and treatment with 200 g of vermicompost and 1500 mg of nitrogen had the greatest effect on the number of suckers, stem weight, number of leaves, sucker height, total biomass and Aloin content.&#x0D; Conclusions: Therefore, simultaneous use of vermicompost and nitrogen fertilizer in Aloe vera cultivation plays an important role in the production and enhancement of sucker and plant yield.

Enhancing Industrial Digitalisation through an Adaptable Component for Bridging Semantic Interoperability Gaps

Digital transformation has a great effect on industries but also in the perception of their products with high consequences on society as a whole, as driver for innovation. However, there are still many barriers to the adoption of digital technologies, especially in small and medium-sized enterprises (SMEs). In the present study we propose a new software component that facilitates the adoption of industrial reference architectures (RAs) based on the semantic interoperability concept. Among these RAs, FIWARE has become a key enabler for flexible and resource effective digitalisation of shop floor processes. The proposed software component aims to enable full interoperability between these more widely used technologies and industrial standards and protocols such as OPC UA. As a result, a flexible, open, and adaptable implementation assists the automatic translation of messages from different standards enabling semantic interoperability of shop floor processes. The component aims to enable industrial SMEs to bring current barriers to digitalisation towards a more human-centred, resilient, and sustainable industry and society.

Text‐based corn futures price forecasting using improved neural basis expansion network

AbstractThe accurate forecasting of agricultural futures prices is critical for ensuring national food security. Therefore, this study proposes a text‐based deep learning forecasting model. This model first uses the ChineseBERT + a text convolution neural network to classify Weibo text and obtain a raw sentiment index. Then, complete ensemble empirical mode decomposition with adaptive noise, variational mode decomposition, correlation coefficient, and sample entropy are combined to decompose and reconstruct the raw sentiment index and obtain a denoised sentiment index. Subsequently, the neural basis expansion analysis with exogenous variables is improved by designing a weight coefficient and Optuna is used to optimize the designed weight coefficient and the hyperparameters. Finally, the SHapley Additive exPlanations value is used to increase the interpretability of prediction results. Corn futures prices for the Dalian Exchange are used in forecasting to validate the accuracy and stability of the proposed model. Experimental results show that the proposed denoising sentiment index contributes more to the improvement of predictive model performance than the raw sentiment index. The proposed text‐based deep predictive model demonstrates strong predictive ability for prediction horizons of 30 and 60 days. SHapley Additive exPlanations value analysis shows that the three features with greater effects on corn futures prices are as follows: “Corn Spot Price of Zhengzhou market,” “CBOT_corn_futures_price,” and “Pork futures price.”

Application of ANN in Construction: Comprehensive Study on Identifying Optimal Modifier and Dosage for Stabilizing Marine Clay of Qingdao Coastal Region of China

Nowadays, the use of new compound chemical stabilizers to treat marine clay has gained significant attention. However, the complex non-linear relationship between the influencing factors and the unconfined compressive strength of chemically treated marine clay is not clear. In order to study the influence of various factors (dosage, type of stabilizer, curing age) on the unconfined compressive strength of solidified soil during chemical treatment, experiments were performed to determine the unconfined compressive strength of soft marine clay modified with various types of stabilizers. Further, an artificial neural network (ANN) model was used to establish a prediction model based on the unconfined compressive strength test data and to verify the performance. Sensitivity and optimization analyses were further conducted to explore the relative significance of parameters as well as the optimal dosage amount. Research has found that when the content of aluminate cement is 89.5% and the content of curing agent is 30%, the unconfined compressive strength significantly increases after 28 days of solidification, and the change in quicklime content has the greatest effect on the improvement in the unconfined compressive strength. The influence of modifiers on the unconfined compressive strength is in the order: potassium hydroxide &gt; kingsilica &gt; quick lime &gt; bassanite. The values of each factor were obtained when the unconfined compressive strength was the maximum, which provided support for the optimization of the treatment scheme. The analysis of chemical treatment is no longer limited to the linear relationship according to the test results, which proves the feasibility of non-linear relationship analysis based on the artificial neural network.