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Growing literature documents that jump variations are important for comprehending the evolution of asset prices. In this paper, we provide a novel insight on the jump components. Specifically, we forecast the equity premium using the weighted least squares (WLS) approach that assigns the inverse of variance weight to observations, and detect the role of jump contributions in it. The results indicate that the WLS models with jump-robust variance weights generate superior out-of-sample performance both statistically and economically relative to that with the jump-involved weights, suggesting that eliminating the jump variation in the variance weight helps to predict the stock returns. The predictive source of the jump-robust variance stems from its efficient measure of the continuous price process and forecast error variance reduced. Furthermore, we demonstrate that the jump component in the variance weight should rather be dumped than collected in terms of minimizing the forecast losses. [ABSTRACT FROM AUTHOR]

Amorphous porous organic polymers (aPOPs) are a type of highly crosslinked polymers. These polymers are generally constructed from rigid organic building blocks, which have become an important subclass of POPs with diverse applications. In the early stage of development, a wide range of carbon-based building blocks and network forming chemistry afforded a large library of aPOPs with rich structures and properties. Recently, implanting main group elements with diverse geometric structures and electronic configurations into aPOPs has proven to be a useful tool to fine-tune the structures and properties of these polymers. Herein, we outline the recent advances in the field of main group (MG)-aPOPs where main-group elements either played unique roles in tuning the structures and properties of MG-aPOPs, or offered new strategies in the synthesis of MG-aPOPs. Furthermore, this Review discusses various challenges remaining in the field from the perspectives of synthetic strategies and characterization techniques, and presents some specific studies that may potentially address the challenges. Incorporating main group elements into amorphous porous organic polymers has enabled the fine tuning of the structures and properties of these materials. Here, the authors review studies in which the geometric structures and electronic properties of main group elements have influenced material structures and properties, and whereby their incorporation has enabled new strategies to synthesize such materials. [ABSTRACT FROM AUTHOR]

Improving the utilization rate of loaded-drugs is of huge importance for generating chitosan-based (CS) micro-carriers. This study aims to fabricate a novel CS microspheres co-delivered curcumin (Cur) and gallic acid (Ga) to assess drug loading and release kinetics, the blood compatibility and anti-osteosarcoma properties. The present study observes the interaction between CS and Cur/Ga molecules and estimates the change in crystallinity and loading and release rate. In addition, blood compatibility and cytotoxicity of such microspheres are also evaluated. Cur-Ga-CS microspheres present high entrapment rate of (55.84 ± 0.34) % for Ga and (42.68 ± 0.11) % for Cur, possibly attributed to surface positive charge (21.76 ± 2.46) mV. Strikingly, Cur-Ga-CS microspheres exhibit slowly sustainable release for almost 7 days in physiological buffer. Importantly, these microspheres possess negligibly toxic to blood and normal BMSC cells, but strong anti-osteosarcoma effect on U2OS cells. Overall, Cur-Ga-CS microspheres are promising to become a novel anti-osteosarcoma agent or sustainable delivery carrier in biomedical applications. [ABSTRACT FROM AUTHOR]

Gallbladder cancer (GBC) performs strongly invasive and poor prognosis, and adenocarcinoma is the most common histological type in it. Statistically, the 5-year survival rate of patients with advanced GBC is less than 5%. Such dismal outcome might be caused by chemotherapy resistance and native biology of tumor cells, regardless of emerging therapeutic strategies. Early diagnosis, depending on biomarkers, receptors and secretive proteins, is more important than clinical therapy, guiding the pathologic stage of cancer and the choice of medication. Therefore, it is in urgent need to understand the specific pathogenesis of GBC and strive to find promising novel biomarkers for early screening in GBC. Non-coding RNAs (ncRNAs), especially microRNAs (miRNAs, miRs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), are confirmed to participate in and regulate the occurrence and development of GBC. Exceptionally, lncRNAs and circRNAs could act as competing endogenous RNAs (ceRNAs) containing binding sites for miRNAs and crosstalk with miRNAs to target regulatory downstream protein-coding messenger RNAs (mRNAs), thus affecting the expression levels of specific proteins to participate in and regulate the development and progression of GBC. It follows that ncRNAs may become promising biomarkers and potential therapeutic targets for GBC. In this review, we mainly summarize the recent research progress of miRNAs and lncRNAs in regulating the development and progression of GBC, chemoresistance, and predicting the prognosis of patients, and highlight the potential applications of the lncRNA/circRNA–miRNA–mRNA cross-regulatory networks in early diagnosis, chemoresistance, and prognostic evaluation, aiming to better understand the pathogenesis of GBC and develop new diagnostic and therapeutic strategies. [ABSTRACT FROM AUTHOR]

Chemoresistance, radioresistance, and facile spreading of laryngeal squamous cell carcinoma (LSCC) make the practically clinical treatment invalid. Such dismal outcome mainly originates from the lack of effective biomarkers which are highly desirable to understand the pathogenesis of LSCC, and strives to find promising novel biomarkers to improve early screening, effective treatment, and prognosis evaluation in LSCC. Recently, long non-coding RNAs (lncRNAs), a kind of non-coding RNAs longer than 200 nucleotides, can participate in the process of tumorigenesis and progression through many regulatory modalities, such as epigenetic transcriptional regulation and post-transcriptional regulation. Meanwhile, microRNAs (miRNAs, miRs), essentially involved in the post-transcriptional regulation of gene expression, are aberrantly expressed in cancer-related genomic regions or susceptible sites. An increasing number of studies have shown that lncRNAs are important regulators of miRNAs expression in LSCC, and that miRNAs can also target to regulate the expression of lncRNAs, and they can target to regulate downstream messenger RNAs (mRNAs) transcriptionally or post-transcriptionally, thereby affecting various physiopathological processes of LSCC. Complex cross-regulatory networks existing among lncRNAs, miRNAs, and mRNAs can regulate the tumorigenesis and development of LSCC. Such networks may become promising biomarkers and potential therapeutic targets in the research field of LSCC. In this review, we mainly summarize the latest research progress on the regulatory relationships among lncRNAs, miRNAs, and downstream mRNAs, and highlight the potential applications of lncRNA–miRNA–mRNA regulatory networks as biomarkers for the early diagnosis, epithelial–mesenchymal transition (EMT) process, chemoresistance, radioresistance, and prognosis of LSCC, aiming to provide important clues for understanding the pathogenesis of LSCC and developing new diagnostic and therapeutic strategies. [ABSTRACT FROM AUTHOR]

Since demand for data is significantly heterogeneous in cloud storage systems (CSSs), there is traffic congestion in nodes storing hot data. In erasure-coded CSSs, traffic congestion can be alleviated by degraded reads sacrificing the bandwidth of surviving nodes. Local reconstruction codes (LRCs) reduce the bandwidth consumption of degraded reads, but cannot provide skewed throughput gain for the hot data. In this paper, we propose a scalable local reconstruction code (SLRC) that relies on LRCs but is more flexible in improving the throughput of a specific data block. First, we develop the local maximum throughput (LMT) to measure the maximum throughput of the hot data blocks by analyzing the actual read arrival rate of LRCs. Further, we elaborate on the structure of SLRC and analyze their performance metrics, which include storage overhead, reconstruction cost, and LMT. To select the appropriate code, we present the minimum reconstruction cost, minimum storage overhead, and minimum penalty algorithms. Finally, we implement extensive experiments on several typical SLRCs on the Hadoop distributed file system. Higher LMT and lower bandwidth consumption can be provided by SLRCs for hot data block degraded reads in CSSs compared with RS codes and LRCs. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is the third most common malignant tumor worldwide and the fourth major cause of cancer-related death, with high morbidity and increased mortality year by year. Although significant progress has been made in the therapy strategies for CRC, the great difficulty in early diagnosis, feeble susceptibility to radiotherapy and chemotherapy, and high recurrence rates have reduced therapeutic efficacy resulting in poor prognosis. Therefore, it is urgent to understand the pathogenesis of CRC and unravel novel biomarkers to improve the early diagnosis, treatment and prediction of CRC recurrence. Long non-coding RNAs (lncRNAs) are non-coding RNAs with a length of more than 200 nucleotides, which are abnormally expressed in tumor tissues and cell lines, activating or inhibiting specific genes through multiple mechanisms including transcription and translation. A growing number of studies have shown that lncRNAs are important regulators of microRNAs (miRNAs, miRs) expression in CRC and may be promising biomarkers and potential therapeutic targets in the research field of CRC. This review mainly summarizes the potential application value of lncRNAs as novel biomarkers in CRC diagnosis, radiotherapy, chemotherapy and prognosis. Additionally, the significance of lncRNA SNHGs family and lncRNA–miRNA networks in regulating the occurrence and development of CRC is mentioned, aiming to provide some insights for understanding the pathogenesis of CRC and developing new diagnostic and therapeutic strategies. [ABSTRACT FROM AUTHOR]

Machine learning (ML) lifecycle is a cyclic process to build an efficient ML system. Though a lot of commercial and community (non-commercial) frameworks have been proposed to streamline the major stages in the ML lifecycle, they are normally overqualified and insufficient for an ML system in its nascent phase. Driven by real-world experience in building and maintaining ML systems, we find that it is more efficient to initialize the major stages of ML lifecycle first for trial and error, followed by the extension of specific stages to acclimatize towards more complex scenarios. For this, we introduce a simple yet flexible framework, MLife, for fast ML lifecycle initialization. This is built on the fact that data flow in MLife is in a closed loop driven by bad cases, especially those which impact ML model performance the most but also provide the most value for further ML model development—a key factor towards enabling enterprises to fast track their ML capabilities. Better yet, MLife is also flexible enough to be easily extensible to more complex scenarios for future maintenance. For this, we introduce two real-world use cases to demonstrate that MLife is particularly suitable for ML systems in their early phases. [ABSTRACT FROM AUTHOR]

To make clear the feasibility of controlled anaerobic digestion (AD) of organic fraction of municipal solid waste being implemented at transfer stations prior to their final disposal, the performance of solid-state AD (SSAD) of yard waste (YW) as well as the improvement by its co-digestion with food waste (FW) in combination with the aid of pH adjustment were investigated by conducting batch SSAD experiments. The results showed that AD of YW with high solid contents easily caused difficulties in the initiation stage due to accumulation of volatile fatty acids. Even with the aid of alkali to successfully initiate the initiation stage, the AD of YW with the high solid content of 29% generated such a low biogas yield as 207 mL/g VS. By contrast, co-digestion of YW and FW with pH adjustment gave the highest biogas and methane yields of 306 and 180 mL/g VS, 47.8 and 40.3% higher than those for AD of YW alone, respectively. A sufficiently long acidogenesis duration was helpful for biogas production, while the inhibitions from excessively high ammonia nitrogen concentrations and organic loading rates were apt to happen after extremely long acidogenesis durations. For co-digestion of YW and FW, adding proper amounts of alkali (CaO) on the 3rd days resluted in the best performance. [ABSTRACT FROM AUTHOR]

Interaction between seepage field and soil stress field influences soil effective stress in general consideration. In addition, water erosion in soil skeleton can also affect soil effective stress. The current studies conducted triaxial compression experiments with seepage, Duncan-Chang model analysis, ABAQUS numerical simulation and followed by a case study analysis. Experiments show that the water erosion in soil skeleton reduces effective stress strength of soil, which is quantitatively described by the reduction of equivalent confining pressure. Through analyzing the characteristics of soil stress-strain curves, the equivalent confining pressure is applied to improve Duncan-Chang model. Using the modified Duncan-Chang model as well as considering the interaction between seepage field and soil stress field, ABAQUS software package is employed to simulate triaxial compression experiments with seepage. This method is validated by comparing simulation and experimental results. Furthermore, this method is applied in the case study of the overall stability of bank slope under seepage effect and finds that the modified model is more conservative on safety assessment of slope stability. The studies provided evidences to prove the importance of considering soil skeleton eroded by water flow in slope stability analysis quantitatively and proposed a modified Duncan-Chang model for engineering application with consideration of seepage effect. [ABSTRACT FROM AUTHOR]

The digestibility of lignocellulosic biomass is limited by its high content of refractory components. The objective of this study is to investigate hydrothermal pretreatment and its effects on anaerobic digestion of sorted organic waste with submerged fermentation. Hydrothermal pretreatment (HT) was performed prior to anaerobic digestion, and three agents were examined for the HT: hot compressed water, alkaline solution, and acidic solution. The concentrations of glucose and xylose were the highest in the sample pretreated in acidic solution. Compared with that of the untreated sample, the biogas yields from digesting the samples pretreated in alkaline solution, acidic solution, and hot water increased by 364, 107, and 79 %, respectively. The decrease of chemical oxygen demand (COD) in liquid phase followed the same order as for the biogas yield. The initial ammonia content of the treated samples followed the order sample treated in acidic solution > sample treated in alkaline solution > sample treated in hot water. The concentrations of volatile fatty acids (VFAs) were low, indicating that the anaerobic digestion process was running at continuously stable conditions. [ABSTRACT FROM AUTHOR]

Solid state anaerobic digestion, as a safe and environment-friendly technology to dispose municipal solid wastes, can produce methane and reduce the volume of wastes. In order to raise the digestion efficiency, this study investigated the pretreatment of yard waste by thermal or chemical method to break down the complex lignocellulosic structure. The composition and structure of pretreated yard waste were analyzed and characterized. The results showed that the pretreatment decreased the content of cellulose and hemicelluloses in yard waste and in turn improved the hydrolysis and methanogenic processes. The thermal pretreatment sample (P1) had the highest methane yield, by increasing 88 % in comparison with digesting the raw material. The maximum biogas production reached 253 mL/g volatile solids (VS). The largest substrate mass reduction was obtained by the alkaline pretreatment (P5). The VS of the alkaline-treated sample decreased about 60 % in comparison with the raw material. [ABSTRACT FROM AUTHOR]