Predicting stock price of construction companies using weighted ensemble learning.

Modeling the behavior of stock price data has always been one of the challenging applications of Artificial Intelligence (AI) and Machine Learning (ML) due to its high complexity and dependence on various conditions. Recent studies show that this will be difficult to do with just one learning model. The problem can be more complex for companies in the construction sector, due to the dependency of their behavior on more conditions. This study aims to provide a hybrid model for improving the accuracy of prediction for the stock price index of companies in the construction section. The contribution of this paper can be considered as follows: First, a combination of several prediction models is used to predict stock prices so that learning models can cover each other's errors. In this research, an ensemble model based on Artificial Neural Network (ANN), Gaussian Process Regression (GPR), and Classification and Regression Tree (CART) is presented for predicting the stock price index. Second, the optimization technique is used to determine the effect of each learning model on the prediction result. For this purpose, first, all three mentioned algorithms process the data simultaneously and perform the prediction operation. Then, using the Cuckoo Search (CS) algorithm, the output weight of each algorithm is determined as a coefficient. Finally, using the ensemble technique, these results are combined and the final output is generated through weighted averaging on optimal coefficients. The proposed system was implemented, and its efficiency was evaluated by real stock data of construction companies. The results showed that using CS optimization in the proposed ensemble system is highly effective in reducing prediction error. According to the results, the proposed system can predict the price index with an average accuracy of 96.6 %, which shows a reduction of at least 2.4 % in prediction error compared to the previous methods. Comparing the evaluation results of the proposed system with similar algorithms indicates that our model is more accurate and can be useful for predicting the stock price index in real-world scenarios.

Wnt/ß-catenin signalling, epithelial-mesenchymal transition and crosslink signalling in colorectal cancer cells.

Colorectal cancer (CRC), with its significant incidence and metastatic rates, profoundly affects human health. A common oncogenic event in CRC is the aberrant activation of the Wnt/ß-catenin signalling pathway, which drives both the initiation and progression of the disease. Persistent Wnt/ß-catenin signalling facilitates the epithelial-mesenchymal transition (EMT), which accelerates CRC invasion and metastasis. This review provides a summary of recent molecular studies on the role of the Wnt/ß-catenin signalling axis in regulating EMT in CRC cells, which triggers metastatic pathogenesis. We present a comprehensive examination of the EMT process and its transcriptional controllers, with an emphasis on the crucial functions of ß-catenin, EMT transcription factors (EMT-TFs). We also review recent evidences showing that hyperactive Wnt/ß-catenin signalling triggers EMT and metastatic phenotypes in CRC via "Destruction complex" of ß-catenin mechanisms. Potential therapeutic and challenges approache to suppress EMT and prevent CRC cells metastasis by targeting Wnt/ß-catenin signalling are also discussed. These include direct ß-catenin inhibitors and novel targets of the Wnt pathway, and finally highlight novel potential combinational treatment options based on the inhibition of the Wnt pathway.

Soybean steroids improve crop abiotic stress tolerance and increase yield.

Sterols have long been associated with diverse fields, such as cancer treatment, drug development, and plant growth; however, their underlying mechanisms and functions remain enigmatic. Here, we unveil a critical role played by a GmNF-YC9-mediated CCAAT-box transcription complex in modulating the steroid metabolism pathway within soybeans. Specifically, this complex directly activates squalene monooxygenase (GmSQE1), which is a rate-limiting enzyme in steroid synthesis. Our findings demonstrate that overexpression of either GmNF-YC9 or GmSQE1 significantly enhances soybean stress tolerance, while the inhibition of SQE weakens this tolerance. Field experiments conducted over two seasons further reveal increased yields per plant in both GmNF-YC9 and GmSQE1 overexpressing plants under drought stress conditions. This enhanced stress tolerance is attributed to the reduction of abiotic stress-induced cell oxidative damage. Transcriptome and metabolome analyses shed light on the upregulation of multiple sterol compounds, including fucosterol and soyasaponin II, in GmNF-YC9 and GmSQE1 overexpressing soybean plants under stress conditions. Intriguingly, the application of soybean steroids, including fucosterol and soyasaponin II, significantly improves drought tolerance in soybean, wheat, foxtail millet, and maize. These findings underscore the pivotal role of soybean steroids in countering oxidative stress in plants and offer a new research strategy for enhancing crop stress tolerance and quality from gene regulation to chemical intervention.

Order selection for heterogeneous semiparametric hidden Markov models.

Hidden Markov models (HMMs), which can characterize dynamic heterogeneity, are valuable tools for analyzing longitudinal data. The order of HMMs (ie, the number of hidden states) is typically assumed to be known or predetermined by some model selection criterion in conventional analysis. As prior information about the order frequently lacks, pairwise comparisons under criterion-based methods become computationally expensive with the model space growing. A few studies have conducted order selection and parameter estimation simultaneously, but they only considered homogeneous parametric instances. This study proposes a Bayesian double penalization (BDP) procedure for simultaneous order selection and parameter estimation of heterogeneous semiparametric HMMs. To overcome the difficulties in updating the order, we create a brand-new Markov chain Monte Carlo algorithm coupled with an effective adjust-bound reversible jump strategy. Simulation results reveal that the proposed BDP procedure performs well in estimation and works noticeably better than the conventional criterion-based approaches. Application of the suggested method to the Alzheimer's Disease Neuroimaging Initiative research further supports its usefulness.

Controlling the Architecture of Freeze-Dried Collagen Scaffolds with Ultrasound-Induced Nucleation.

Collagen is a naturally occurring polymer that can be freeze-dried to create 3D porous scaffold architectures for potential application in tissue engineering. The process comprises the freezing of water in an aqueous slurry followed by sublimation of the ice via a pre-determined temperature-pressure regime and these parameters determine the arrangement, shape and size of the ice crystals. However, ice nucleation is a stochastic process, and this has significant and inherent limitations on the ability to control scaffold structures both within and between the fabrication batches. In this paper, we demonstrate that it is possible to overcome the disadvantages of the stochastic process via the use of low-frequency ultrasound (40 kHz) to trigger nucleation, on-demand, in type I insoluble bovine collagen slurries. The application of ultrasound was found to define the nucleation temperature of collagen slurries, precisely tailoring the pore architecture and providing important new structural and mechanistic insights. The parameter space includes reduction in average pore size and narrowing of pore size distributions while maintaining the percolation diameter. A set of core principles are identified that highlight the huge potential of ultrasound to finely tune the scaffold architecture and revolutionise the reproducibility of the scaffold fabrication protocol.

MSH7 confers quantitative variation in pollen fertility and boosts grain yield in maize.

Fertile pollen is critical for the survival, fitness, and dispersal of flowering plants, and directly contributes to crop productivity. Extensive mutational screening studies have been carried out to dissect the genetic regulatory network determining pollen fertility, but we still lack fundamental knowledge about whether and how pollen fertility is controlled in natural populations. We used a genome-wide association study (GWAS) to show that ZmGEN1A and ZmMSH7, two DNA repair-related genes, confer natural variation in maize pollen fertility. Mutants defective in these genes exhibited abnormalities in meiotic or post-meiotic DNA repair, leading to reduced pollen fertility. More importantly, ZmMSH7 showed evidence of selection during maize domestication, and its disruption resulted in a substantial increase in grain yield for both inbred and hybrid. Overall, our study describes the first systematic examination of natural genetic effects on pollen fertility in plants, providing valuable genetic resources for optimizing male fertility. In addition, we find that ZmMSH7 represents a candidate for improvement of grain yield.

Expression of Cry1Ab/2Aj Protein in Genetically Engineered Maize Plants and Its Transfer in the Arthropod Food Web.

While transgenic Bacillus thuringiensis (Bt) maize provides pest resistance and a reduced application of chemical pesticides, a comprehensive environmental risk assessment is mandatory before its field release. This research determined the concentrations of Bt protein in plant tissue and in arthropods under field conditions in Gongzhuling City, northeastern China, to provide guidance for the selection of indicator species for non-target risk assessment studies. Bt maize expressing Cry1Ab/2Aj and non-transformed near-isoline were grown under identical environmental and agricultural conditions. Cry1Ab/2Aj was detected in plant tissues and arthropods collected from Bt maize plots during pre-flowering, flowering, and post-flowering. The expression of Cry1Ab/2Aj varied across growth stages and maize tissues, as well as in the collected arthropods at the three growth stages. Therefore, representative species should be chosen to cover the whole growing season and to represent different habitats and ecological functions. Dalbulus maidis (Hemiptera: Cicadellidae), Rhopalosiphum padi (Hemiptera: Aphididae), Heteronychus arator (Coleoptera: Scarabaeidae), and Somaticus angulatus (Coleoptera: Tenebrionidae) are suitable non-target herbivores. Propylea japonica (Coleoptera: Coccinellidae), Paederus fuscipes (Coleoptera: Staphylinidae), Chrysoperla nipponensis (Neuroptera: Chrysopidae), and spiders are suggested predators. Apis cerana and Apis mellifera ligustica (both Hymenoptera: Apidae) represent pollinators and Folsomia candida (Collembola: Isotomidae) decomposers.

Semiparametric probit regression model with misclassified current status data.

Current status data arise when each subject under study is examined only once at an observation time, and one only knows the failure status of the event of interest at the observation time rather than the exact failure time. Moreover, the obtained failure status is frequently subject to misclassification due to imperfect tests, yielding misclassified current status data. This article conducts regression analysis of such data with the semiparametric probit model, which serves as an important alternative to existing semiparametric models and has recently received considerable attention in failure time data analysis. We consider the nonparametric maximum likelihood estimation and develop an expectation-maximization (EM) algorithm by incorporating the generalized pool-adjacent-violators (PAV) algorithm to maximize the intractable likelihood function. The resulting estimators of regression parameters are shown to be consistent, asymptotically normal, and semiparametrically efficient. Furthermore, the numerical results in simulation studies indicate that the proposed method performs satisfactorily in finite samples and outperforms the naive method that ignores misclassification. We then apply the proposed method to a real dataset on chlamydia infection.

Co-expression of four penaeidins in transgenic rice seeds: an alternative strategy for substitute antibiotic agricultural products.

The co-expression of multiple antimicrobial peptides (AMPs) in genetically modified (GM) crops can give plants a broader antibacterial spectrum and lower the pathogen risk of drug resistance. Therefore, four penaeidins (shrimp-derived AMPs) were fused and encoded in an artificial gene (PEN1234), driven by the seed-specific promoter Pzein, with the aim of co-expression in seeds of transgenic rice. The resistant rice plants, acquired via Agrobacterium-mediated transformation and glufosinate screening, were identified by PCR and the modified disk-diffusion method, and eight GM lines with high AMP content in the seeds were obtained. Among them, the PenOs017 line had the largest penaeidin content, at approximately 251-300 µg/g in seeds and 15-47 µg/g in roots and leaves. The AMPs in the seeds kept their antibacterial properties even after the seed had been boiled in hot water and could significantly inhibit the growth of methicillin-resistant Staphylococcus aureus, and AMPs in the leaves could effectively inhibit Xanthomonas oryzae pv. Oryzae. The results indicate that PenOs017 seeds containing AMPs are an ideal raw-material candidate for antibiotic-free food and feed, and may require fewer petrochemical fungicides or bactericides for disease control during cultivation than conventional rice.

Hyper-expression of GFP-fused active hFGF21 in tobacco chloroplasts.

Human fibroblast growth factor 21 (hFGF21) is a promising candidate for metabolic diseases. In this study, a tobacco chloroplast transformation vector, pWYP21406, was constructed that consisted of codon-optimized encoding gene hFGF21 fused with GFP at its 5' terminal; it was driven by the promoter of plastid rRNA operon (Prrn) and terminated by the terminator of plastid rps16 gene (Trps16). Spectinomycin-resistant gene (aadA) was the marker and placed in the same cistron between hFGF21 and the terminator Trps16. Transplastomic plants were generated by the biolistic bombardment method and proven to be homoplastic by Southern blotting analysis. The expression of GFP was detected under ultraviolet light and a laser confocal microscope. The expression of GFP-hFGF21 was confirmed by immunoblotting and quantified by enzyme-linked immunosorbnent assay (ELISA). The accumulation of GFP-hFGF21 was confirmed to be 12.44 ± 0.45% of the total soluble protein (i.e., 1.9232 ± 0.0673 g kg-1 of fresh weight). GFP-hFGF21 promoted the proliferation of hepatoma cell line HepG2, inducing the expression of glucose transporter 1 in hepatoma HepG2 cells and improving glucose uptake. These results suggested that a chloroplast expression is a promising approach for the production of bioactive recombinant hFGF21.

The pattern of cytokines expression and dynamic changes of renal function at 6 months in patients with Omicron COVID-19.

To analyze the dynamic changes of renal function longitudinally and investigate the cytokine profiles at 6 months in patients with Omicron COVID-19. Forty-seven patients with a proven diagnosis of Omicron COVID-19 from January to February 2022 attended a 6-month follow-up after discharge at Tianjin First Central Hospital. The demographic parameters, clinical features, and laboratory indexes were collected during hospitalization and 6 months after discharge. The serum cytokine levels at 6 months were also assessed. Patients were grouped according to with or without kidney involvement at admission. The levels of serum creatinine and estimated glomerular filtration rate (eGFR) were all normal both in the hospital and at follow-up. Whereas, compared with renal function in the hospital, serum creatinine levels at 6 months increased remarkably; meanwhile, eGFR decreased significantly in all patients. The serum levels of interleukin (IL)-2, IL-4, IL-5, IL-6, IL-10, and TNF-α and IFN-γ significantly decreased and TGF-ß remarkably increased in the kidney involvement group. The serum levels of IL-2 and IL-5 were positively correlated with age; contrarily, TGF-ß showed a negative correlation with aging. The younger was an independent risk factor of the higher TGF-ß levels. Omicron patients showed a decline in renal function at follow-up, reflecting the trend of CKD. Serum cytokine profiles were characterized with the majority of cytokines decreased and TGF-ß increased in the kidney involvement group; the latter may be used as a sign of CKD. The tendency of CKD is one of the manifestations of long COVID and deserves attention.

Feature screening with latent responses.

A novel feature screening method is proposed to examine the correlation between latent responses and potential predictors in ultrahigh-dimensional data analysis. First, a confirmatory factor analysis (CFA) model is used to characterize latent responses through multiple observed variables. The expectation-maximization algorithm is employed to estimate the parameters in the CFA model. Second, R-Vector (RV) correlation is used to measure the dependence between the multivariate latent responses and covariates of interest. Third, a feature screening procedure is proposed on the basis of an unbiased estimator of the RV coefficient. The sure screening property of the proposed screening procedure is established under certain mild conditions. Monte Carlo simulations are conducted to assess the finite-sample performance of the feature screening procedure. The proposed method is applied to an investigation of the relationship between psychological well-being and the human genome.

Additive hazards model with time-varying coefficients and imaging predictors.

Conventional hazard regression analyses frequently assume constant regression coefficients and scalar covariates. However, some covariate effects may vary with time. Moreover, medical imaging has become an increasingly important tool in screening, diagnosis, and prognosis of various diseases, given its information visualization and quantitative assessment. This study considers an additive hazards model with time-varying coefficients and imaging predictors to examine the dynamic effects of potential scalar and imaging risk factors for the failure of interest. We develop a two-stage approach that comprises the high-dimensional functional principal component analysis technique in the first stage and the counting process-based estimating equation approach in the second stage. In addition, we construct the pointwise confidence intervals for the proposed estimators and provide a significance test for the effects of scalar and imaging covariates. Simulation studies demonstrate the satisfactory performance of the proposed method. An application to the Alzheimer's disease neuroimaging initiative study further illustrates the utility of the methodology.

Differential assembly of root-associated bacterial and fungal communities of a dual transgenic insect-resistant maize line at different host niches and different growth stages.

Transgenic technology has been widely applied to crop development, with genetically modified (GM) maize being the world's second-largest GM crop. Despite the fact that rhizosphere bacterial and fungal populations are critical regulators of plant performance, few studies have evaluated the influence of GM maize on these communities. Plant materials used in this study included the control maize line B73 and the mcry1Ab and mcry2Ab dual transgenic insect-resistant maize line 2A-7. The plants and soils samples were sampled at three growth stages (jointing, flowering, and maturing stages), and the sampling compartments from the outside to the inside of the root are surrounding soil (SS), rhizospheric soil (RS), and intact root (RT), respectively. In this study, the results of alpha diversity revealed that from the outside to the inside of the root, the community richness and diversity declined while community coverage increased. Morever, the different host niches of maize rhizosphere and maize development stages influenced beta diversity according to statistical analysis. The GM maize line 2A-7 had no significant influence on the composition of microbial communities when compared to B73. Compared to RS and SS, the host niche RT tended to deplete Chloroflexi, Gemmatimonadetes and Mortierellomycota at phylum level. Nitrogen-fixation bacteria Pseudomonas, Herbaspirillum huttiense, Rhizobium leguminosarum, and Sphingomonas azotifigens were found to be enriched in the niche RT in comparison to RS and SS, whilst Bacillus was found to be increased and Stenotrophomonas was found to be decreased at the maturing stage as compared to jointing and flowering stages. The nitrogen fixation protein FixH (clusters of orthologous groups, COG5456), was found to be abundant in RT. Furthermore, the pathogen fungus that causes maize stalk rot, Gaeumannomyces radicicola, was found to be abundant in RT, while the beneficial fungus Mortierella hyalina was found to be depleted in RT. Lastly, the abundance of G. radicicola gradually increased during the development of maize. In conclusion, the host niches throughout the soil-plant continuum rather than the Bt insect-resistant gene or Bt protein secretion were primarily responsible for the differential assembly of root-associated microbial communities in GM maize, which provides the theoretical basis for ecological agriculture.

Impact of Transgenic Cry1Ab/2Aj Maize on Abundance of Non-Target Arthropods in the Field.

Transgenic Bacillus thuringiensis (Bt) maize has broad prospects for application in China. Before commercialization, it is necessary to assess possible ecological impacts, including impacts on non-target arthropods (NTAs) in the field. In the present study, transgenic Bt maize expressing cry1Ab/2Aj and its corresponding non-transformed near isoline were planted under the same environmental and agricultural conditions, and arthropods in the field were collected during the three main growth stages of maize. In a one year trial, the results showed the composition of NTA communities in the transgenic and control maize fields were similar. There were no significant differences for community-level parameters of species richness (S), Shannon-Wiener diversity index (H'), evenness index (J) and Simpson's dominant concentration (C) between the two types of maize fields. Likewise, a Bray-Curtis dissimilarity and distance analysis showed that Cry1Ab/2Aj toxin exposure did not increase community dissimilarities between Bt and non-Bt maize plots and that the structure of the NTAs community was similar on the two maize varieties. Furthermore, planting of the transgenic cry1Ab/2Aj maize did not affect the density or composition of non-target decomposers, herbivores, predators, parasitoids and pollinator guilds. In summary, our results showed that planting of Bt maize producing Cry1Ab/Cry2Aj proteins do not adversely affect population dynamics and diversity of NTAs.

Dynamic semiparametric transformation models for recurrent event data with a terminal event.

Recurrent event data with a terminal event commonly arise in many longitudinal follow-up studies. This article proposes a class of dynamic semiparametric transformation models for the marginal mean functions of the recurrent events with a terminal event, where some covariate effects may be time-varying. An estimation procedure is developed for the model parameters, and the asymptotic properties of the resulting estimators are established. In addition, relevant significance tests are suggested for examining whether or not covariate effects vary with time, and a model checking procedure is presented for assessing the adequacy of the proposed models. The finite sample performance of the proposed estimators is examined through simulation studies, and an application to a medical cost study of chronic heart failure patients is provided.

Climate change did not alter the effects of Bt maize on soil Collembola in northeast China.

Bt maize is being increasingly cultivated worldwide as the effects of climate change are increasing globally. Bt maize IE09S034 and its near-isogenic non-Bt maize Zong 31 were used to investigate whether climate change alters the effects of Bt maize on soil Collembola. Warming and drought conditions were simulated using open-top chambers (OTC), and their effects on soil Collembola were evaluated. We found that the maize type had no significant effect on Collembola; however, the abundance and diversity of Collembola were significantly higher in the OTC than outside at the seedling stage; they were significantly lower in the OTC at the heading and mature stages. The interactions of the maize type with the OTC had no effect on these parameters. Therefore, Bt maize had no significant effect on soil Collembola, and the effects of climate warming and drought on soil Collembola depended on the ambient climatic conditions. When the temperature was low, collembolan abundance and diversity were promoted by warming; however, when the temperature was high and the humidity was low, collembolan abundance and diversity were inhibited by warming and drought. The climate changes simulated by the OTC did not alter the effects of Bt maize on soil Collembola.

Joint analysis of informatively interval-censored failure time and panel count data.

Interval-censored failure time and panel count data, which frequently arise in medical studies and social sciences, are two types of important incomplete data. Although methods for their joint analysis have been available in the literature, they did not consider the observation process, which may depend on the failure time and/or panel count of interest. This study considers a three-component joint model to analyze interval-censored failure time, panel counts, and the observation process within a unique framework. Gamma and distribution-free frailties are introduced to jointly model the interdependency among the interval-censored data, panel count data, and the observation process. We propose a sieve maximum likelihood approach coupled with Bernstein polynomial approximation to estimate the unknown parameters and baseline hazard function. The asymptotic properties of the resulting estimators are established. An extensive simulation study suggests that the proposed procedure works well for practical situations. An application of the method to a real-life dataset collected from a cardiac allograft vasculopathy study is presented.

Effect of Deacidification Treatment on the Flavor Quality of Zaosu Pear-Kiwifruit Wine.

Conventional pear-kiwifruit wine has a bland flavor and sour taste, because of excessive l-malic acid content and, consequently, little consumer appeal. An Oenococcus oeni strain, GF-2, has good malolactic fermentation (MLF) performance and high glucosidase activity. Through a Box-Behnken design, the optimum MLF parameters for deacidification by GF-2 were determined: initial pH of 3.4, 5% v/v inoculation, and temperature of 20 °C, which reduced the malic acid content by 98.3%. The changes in the content of organic acids, polyphenols, and aromatic compounds after MLF were compared with chemical deacidification. MLF significantly decreased the total concentration of organic acids by 29.7% and promoted the accumulation of aromatic esters, higher alcohols, and terpenoids, but chemical deacidification markedly decreased aromatic compound content by 59.8%. MLF wine achieved the highest sensory scores for aroma, taste, and overall acceptability. Therefore, MLF with O. oeni GF-2 has great potential to markedly improve the quality of commercial pear-kiwifruit wine.

Engineered chimeric insecticidal crystalline protein improves resistance to lepidopteran insects in rice (Oryza sativa L.) and maize (Zea mays L.).

The insecticidal crystalline proteins (Crys) are a family of insect endotoxin functioning in crop protection. As insects keep evolving into tolerance to the existing Crys, it is necessary to discover new Cry proteins to overcome potential threatens. Crys possess three functional domains at their N-termini, and the most active region throughout evolution was found at the domain-III. We swapped domain-IIIs from various Cry proteins and generated seven chimeric proteins. All recombinants were expressed in Escherichia coli and their toxicity was assessed by dietary exposure assays. Three of the seven Crys exhibited a high toxicity to Asian corn borer over the controls. One of them, Cry1Ab-Gc, a chimeric Cry1Ab being replaced with the domain-III of Cry1Gc, showed the highest toxicity to rice stem borer when it was over-expressed in Oryza sativa. Furthermore, it was also transformed into maize, backcrossed into commercial maize inbred lines and then produced hybrid to evaluate their commercial value. Transgenic maize performed significant resistance to the Asian corn borer without affecting the yield. We further showed that this new protein did not have adverse effects on the environment. Our results indicated that domain III swapped of Crys could be used as an efficient method for developing new engineered insecticidal protein.