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With the rapid advancement of computer vision, machine learning, and consumer electronics, eye tracking has emerged as a topic of increasing interest in recent years. It plays a key role across diverse domains including human–computer interaction, virtual reality, and clinical and healthcare applications. Near-eye tracking (NET) has recently been developed to possess encouraging features such as wearability, affordability, and interactivity. These features have drawn considerable attention in the health domain, as NET provides accessible solutions for long-term and continuous health monitoring and a comfortable and interactive user interface. Herein, this work offers an inaugural concise review of NET for health, encompassing approximately 70 related articles published over the past two decades and supplemented by an in-depth examination of 30 literatures from the preceding five years. This paper provides a concise analysis of health-related NET technologies from aspects of technical specifications, data processing workflows, and the practical advantages and limitations. In addition, the specific applications of NET are introduced and compared, revealing that NET is fairly influencing our lives and providing significant convenience in daily routines. Lastly, we summarize the current outcomes of NET and highlight the limitations. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) water pollution threatens environmental systems and human health. Adsorption is the preferred method for purifying water bodies polluted by Cd, and the development of effective adsorption materials is critical. The performance of original phosphate rock powder (PRP) as an adsorption medium for purifying water bodies polluted by Cd was compared with that of phosphate rock powder modified with fulvic acid, chitosan, MnO2, and sulfhydryl, respectively, and their appearance and adsorption properties were investigated. The surface structures of all modified powders were rougher than the original, and their functional groups were richer. The greatest Cd2+ adsorption capacity, 1.88 mg g−1, was achieved with chitosan-modified PRP (CMPRP). This was 106.59% greater than that of PRP. The capacities of fulvic acid and MnO2 were 15.38% and 4.40% greater than that of the original, respectively. When the fulvic acid-modified PRP, CMPRP, and manganese dioxide PRP reached adsorption equilibrium, the removal rates of Cd2+ were 51.86%, 93.26%, and 46.70%, respectively. Moreover, the removal rate of Cd2+ by CMPRP was 104.43% higher than that of PRP. The main Cd2+ adsorption mechanisms for the MPRPs were electrostatic interactions, ion exchange, co-precipitation, and complexation. Moreover, the processing of the phosphate rock powder was straightforward, harmless to the environment, and could be effectively used for the removal of Cd. These results show that CMPRP is promising as a new adsorption material to treat Cd-contaminated water. [ABSTRACT FROM AUTHOR]

Several cobalt(II) complexes Co1–Co3 bearing pyridine–oxime ligands (L1 = pyridine-2-aldoxime for Co1; L2 = 6-methylpyridine-2-aldoxime for Co2; L3 = phenyl-2-pyridylketoxime for Co3) and picolinaldehyde O-methyl oxime (L4)-supported Co4 were synthesized and well characterized by FT-IR, mass spectrum and elemental analysis. The single-crystal X-ray diffraction of complex Co2 reveals that the cobalt center of CoCl2 is coordinated with two 6-methylpyridine-2-aldoxime ligands binding with Npyridine and Noxime atoms, which feature a distorted octahedral structure. These Co complexes Co1–Co4 displayed extremely high activity toward isoprene polymerization upon activation with small amount of AlClEt2 in toluene, giving polyisoprene with high activity up to 16.3 × 105 (mol of Co)−1(h)−1. And, the generated polyisoprene displayed high molecular weights and narrow molecular distribution with a cis-1,4-enriched selectivity. The type of cobalt complexes, cocatalyst and reaction temperature all have effects on the polymerization activity but not on the microstructure of polymer. [ABSTRACT FROM AUTHOR]

Simple Summary: Gastric cancer (GC) is one of the most common malignancies with limited therapeutic targets available. CDR1as, an endogenous circular RNA with a closed loop structure, has been reported to be a crucial regulator and promising biomarker in various tumors. However, whether and how CDR1as participates in GC progression remains not well characterized. In this study, we explored the biological roles, the downstream molecular mechanism and the upstream regulator of CDR1as in GC. We found that CDR1as mediated by human antigen R (HuR) promotes GC growth through the miR-299-3p/TGIF1 axis, which provides new insights into GC pathogenesis and brings a new potential target for clinical GC therapy. Background: Gastric cancer (GC) remains a common malignancy worldwide with a limited understanding of the disease mechanisms. A novel circular RNA CDR1as has been recently reported to be a crucial regulator of human cancer. However, its biological role and mechanism in the GC growth are still far from clear. Methods: Small interfering RNAs (siRNAs), lentivirus or plasmid vectors were applied for gene manipulation. The CDR1as effects on the GC growth were evaluated in CCK8 and colony formation assays, a flow cytometry analysis and mouse xenograft tumor models. A bioinformatics analysis combined with RNA immunoprecipitation (RIP), RNA pull-down assays, dual-luciferase reporter gene assays, Western blot, reverse transcription–quantitative polymerase chain reaction (RT-qPCR) and functional rescue experiments were used to identify the CDR1as target miRNA, the downstream target gene and its interaction with human antigen R (HuR). Results: The CDR1as overexpression promoted the GC growth in vitro and in vivo and reduced the apoptotic rate of GC cells. Its knockdown inhibited the GC cell proliferation and viability and increased the cell apoptotic rate. Proliferation-related proteins PCNA and Cyclin D1 and apoptosis-related proteins Bax, Bcl-2, Caspase-3 and Caspase-9 were regulated. Mechanically, the cytoplasmic CDR1as acted as a miR-299-3p sponge to relieve its suppressive effects on the GC cell growth. Oncogenic TGIF1 was a miR-299-3p downstream target gene that mediated the promotive effects of CDR1as and regulated the PCNA and Bax levels. HuR interacted with CDR1as via the RRM2 domain and positively regulated the CDR1as level and its oncogenic role as well as downstream target TGIF1. Conclusions: CDR1as promotes the GC growth through the HuR/CDR1as/miR-299-3p/TGIF1 axis and could be used as a new therapeutic target for GC. [ABSTRACT FROM AUTHOR]

Background: With environmental and lifestyle changes, recent epidemiological studies have shown that the prevalence of Ulcerative Colitis (UC) is on the rise, while treatment options are limited. There is an urgent need to explore the underlying mechanisms of vitamin D (VD) as an effective treatment. Methods: Dextran sulfate sodium-induced mice and lipopolysaccharide-induced HCT116 cells were used to establish the classic UC models in vivo and in vitro, respectively. Typical symbols of inflammation (IL-6, COX-2), oxidative stress (MDA, MPO, GSH), and ferroptosis (ACSL4, GPX4, SLC7A11, and Iron) were analyzed by Western blot, Immunohistochemistry, RT-PCR, and relative assay kits. The inflammation factors and oxidative stress injury of cells transfected with ACSL4+/+ plasmids were tested by Western blot, MDA, and MPO methods. Results: Vitamin D attenuated the levels of COX-2, IL-6, Iron, MDA, and MPO and improved SOD1 and GSH contents in DSS + VD and LPS + VD groups, compared with model groups. Ferrostatin-1 (Fer-1) could relieve the levels of COX-2, IL-6, Iron, MDA, and MPO while increasing the contents of SOD1 and GSH in DSS + Fer-1 and LPS + Fer-1 compared to model groups. VD downregulated the expression of ACSL4 and upregulated GPX4 in tissues and cells. After transfected with ACSL4+/+ plasmids, we found VD's role of downregulating inflammation and oxidative stress was relieved. Conclusions: Vitamin D can relieve UC by inhibiting ferroptosis both in mice and in cells through the negative regulation of ACSL4, providing new insight into the therapeutic function of VD on UC. [ABSTRACT FROM AUTHOR]

Some chronic diseases, including Parkinson's disease (PD), diabetic foot, flat foot, stroke, elderly falling, and knee osteoarthritis (KOA), are related to orthopedic organs, nerves, and muscles. The interaction of these three parts will generate a comprehensive result: gait. Furthermore, the lesions in these regions can produce abnormal gait features. Therefore, monitoring the gait features can assist medical professionals in the diagnosis and analysis of these diseases. Nowadays, various insole systems based on different sensing techniques have been developed to monitor gait and aid in medical research. Hence, a detailed review of insole systems and their applications in disease management can greatly benefit researchers working in the field of medical engineering. This essay is composed of the following sections: the essay firstly provides an overview of the sensing mechanisms and parameters of typical insole systems based on different sensing techniques. Then this essay respectively discusses the three stages of gait parameters pre-processing, respectively: pressure reconstruction, feature extraction, and data normalization. Then, the relationship between gait features and pathogenic mechanisms is discussed, along with the introduction of insole systems that aid in medical research; Finally, the current challenges and future trends in the development of insole systems are discussed. [ABSTRACT FROM AUTHOR]

A new prenylated indole alkaloid—Penicimutamide C N-oxide (1), a new alkaloid penicimutamine A (2), along with six known alkaloids were isolated from an endophytic fungus Pallidocercospora crystallina. A simple and accurate method was used to determine the N-O bond in the N-oxide group of 1. By using a β-cell ablation diabetic zebrafish model, compounds 1, 3, 5, 6 and 8 showed significantly hypoglycemic activities under the concentration of 10 μM. Further studies revealed that compounds 1 and 8 lowered the glucose level through promoting glucose uptake in zebrafish. In addition, all eight compounds showed no acute toxicity, teratogenicity, nor vascular toxicity in zebrafish under the concentrations range from 2.5 μΜ to 40 μM. Importantly, these results provide new lead compounds for the development of antidiabetes strategies. [ABSTRACT FROM AUTHOR]

It is extremely important to monitor the health status of welding robots for the safe and stable operation of a body-in-white (BIW) welding production line. In the actual production process, the robot degradation rate is slow and the effective data are poor, which can reflect a degradation state in the large amount of obtained monitoring data, which causes difficulties in health status evaluation. In order to realize the accurate evaluation of the health status of welding robots, this paper proposes a health status evaluation method based on the evidential reasoning (ER) rule, which reflects the health status of welding robots by using the running state data monitored in actual engineering and through the qualitative knowledge of experts, which makes up for the lack of effective data. In the ER rule evaluation model, the covariance matrix adaptive evolutionary strategy (CMA-ES) algorithm is used to optimize the initial parameters of the evaluation model, which improved the accuracy of health status evaluations. Finally, a BIW welding robot was taken as an example for verification. The results show that the proposed model is able to accurately estimate the health status of the welding robot by using the monitored degradation data. [ABSTRACT FROM AUTHOR]

Water cadmium (Cd) pollution has widely aroused concerns due to high Cd toxicity in water bodies and its serious health risks to humans. Adsorption has been identified as an effective and widely utilized technology for water purification with heavy metal pollution. To develop a newly identified adsorbent of modified zeolite that can easily and effectively purify Cd-polluted water, NaOH modification (JZ), high-temperature modification (HZ), humic acid modification (FZ), Na2S modification (SZ), and ultrasonic modification (CZ) zeolites were developed, and their appearances and adsorption and desorption characteristics were investigated. The results showed that the adsorption capacity of Cd by JZ and SZ were improved by 68.87% and 32.06%, respectively, relative to that by natural zeolite (NZ); however, HZ, FZ, and CZ decreased the adsorption capacity. JZ had a higher adsorption capacity than SZ and could remove 99.90% Cd at an initial concentration of 100 mg/L. The dominant adsorption mechanism of Cd by JZ was the chemisorption of the monolayer. The preferred temperature and pH that enhanced Cd adsorption by JZ were 25–35 °C and 4–8, respectively. With an equilibrium adsorption capacity of 9.37–9.74 mg/g at an initial concentration of 280 mg/L, JZ reached its maximum saturated adsorption capacity; compared with SZ and NZ, the adsorption capacity increase was 27.83–68.81%. The R2 fitted by JZ's Langmuir model and quasi-second-order dynamics model were both above 0.93. In summary, JZ was recognized as a novel absorbent for Cd-polluted water purification. [ABSTRACT FROM AUTHOR]

To improve the spatial density and quality of measurement points in multitemporal interferometric synthetic aperture radar, distributed scatterers (DSs) should be processed. An essential procedure in DS interferometry is phase estimation, which reconstructs a consistent phase series from all available interferograms. Influenced by the well-known suboptimality of coherence estimation, the performance of the state-of-the-art phase estimation algorithms is severely degraded. Previous research has addressed this problem by introducing the coherence bias correction technique. However, the precision of phase estimation is still insufficient because of the limited correction capabilities. In this paper, a modified phase estimation approach is proposed. Particularly, by incorporating the information on both interferometric coherence and the number of looks, a significant bias correction to each element of the coherence magnitude matrix is achieved. The bias-corrected coherence matrix is combined with advanced statistically homogeneous pixel selection and time series phase optimization algorithms to obtain the optimal phase series. Both the simulated and Sentinel-1 real data sets are used to demonstrate the superiority of this proposed approach over the traditional phase estimation algorithms. Specifically, the coherence bias can be corrected with considerable accuracy by the proposed scheme. The mean bias of coherence magnitude is reduced by more than 29%, and the standard deviation is reduced by more than 18% over the existing bias correction method. The proposed approach achieves higher accuracy than the current methods over the reconstructed phase series, including smoother interferometric phases and fewer outliers. [ABSTRACT FROM AUTHOR]

Downy mildew is a major threat to the economic value of spinach. The most effective approach to managing spinach downy mildew is breeding cultivars with resistance genes. The resistance allele RPF2 is effective against races 1–10 and 15 of Peronospora farinosa f. sp. Spinaciae (P. effusa) and is widely used as a resistance gene. However, the gene and the linked marker of RPF2 remain unclear, which limit its utilization. Herein, we located the RPF2 gene in a 0.61 Mb region using a BC1 population derived from Sp39 (rr) and Sp62 (RR) cultivars via kompetitive allele specific PCR (KASP) markers. Within this region, only one R gene, Spo12821, was identified based on annotation information. The amino acid sequence analysis showed that there were large differences in the length of the LRR domain between the parents. Additionally, a molecular marker, RPF2-IN12821, was developed based on the sequence variation in the Spo12821, and the evaluation in the BC1 population produced a 100% match with resistance/susceptibility. The finding of the study could be valuable for improving our understanding of the genetic basis of resistance against the downy mildew pathogen and breeding resistance lines in the future. [ABSTRACT FROM AUTHOR]

Insole plantar stress detection (PSD) techniques play an important role in gait monitoring. Among the various insole PSD methods, piezoelectric- and piezoresistive-based architectures are broadly used in medical scenes. Each year, a growing number of new research outcomes are reported. Hence, a deep understanding of these two kinds of insole PSD sensors and state-of-the-art work would strongly benefit the researchers in this highly interdisciplinary field. In this context, this review article is composed of the following aspects. First, the mechanisms of the two techniques and corresponding comparisons are explained and discussed. Second, advanced materials which could enhance the performance of current piezoelectric and piezoresistive insole prototypes are introduced. Third, suggestions for designing insole PSD prototypes/products for different diseases are offered. Last, the current challenge and potential future trends are provided. [ABSTRACT FROM AUTHOR]

With the rapid development of Internet of Things (IoT) technologies, traditional disease diagnoses carried out in medical institutions can now be performed remotely at home or even ambient environments, yielding the concept of the Internet of Health Things (IoHT). Among the diverse IoHT applications, inertial measurement unit (IMU)-based systems play a significant role in the detection of diseases in many fields, such as neurological, musculoskeletal, and mental. However, traditional numerical interpretation methods have proven to be challenging to provide satisfying detection accuracies owing to the low quality of raw data, especially under strong electromagnetic interference (EMI). To address this issue, in recent years, machine learning (ML)-based techniques have been proposed to smartly map IMU-captured data on disease detection and progress. After a decade of development, the combination of IMUs and ML algorithms for assistive disease diagnosis has become a hot topic, with an increasing number of studies reported yearly. A systematic search was conducted in four databases covering the aforementioned topic for articles published in the past six years. Eighty-one articles were included and discussed concerning two aspects: different ML techniques and application scenarios. This review yielded the conclusion that, with the help of ML technology, IMUs can serve as a crucial element in disease diagnosis, severity assessment, characteristic estimation, and monitoring during the rehabilitation process. Furthermore, it summarizes the state-of-the-art, analyzes challenges, and provides foreseeable future trends for developing IMU-ML systems for IoHT. [ABSTRACT FROM AUTHOR]

Wearables developed for human body signal detection receive increasing attention in the current decade. Compared to implantable sensors, wearables are more focused on body motion detection, which can support human–machine interaction (HMI) and biomedical applications. In wearables, electromyography (EMG)-, force myography (FMG)-, and electrical impedance tomography (EIT)-based body information monitoring technologies are broadly presented. In the literature, all of them have been adopted for many similar application scenarios, which easily confuses researchers when they start to explore the area. Hence, in this article, we review the three technologies in detail, from basics including working principles, device architectures, interpretation algorithms, application examples, merits and drawbacks, to state-of-the-art works, challenges remaining to be solved and the outlook of the field. We believe the content in this paper could help readers create a whole image of designing and applying the three technologies in relevant scenarios. [ABSTRACT FROM AUTHOR]

Low carbon and digitalization are the general trends of manufacturing upgrading and transformation. Digital technology enables the whole process of green manufacturing and breaks down the spatial barrier. To achieve the dual carbon goals, the pressure-state-response (PSR) model, in which digital technology enables the green innovation of the manufacturing industry, was theoretically analyzed in this study. The measurement system of the digital green innovation (DGI) in the manufacturing industry was constructed according to the PSR framework. An evaluation model based on the analytic hierarchy process and the deviation maximization technique for order preference by similarity to an ideal solution method was constructed to measure the level of DGI. The results of this study from Chinese manufacturing are as follows. (i) The measurement system of the level of DGI in manufacturing industry includes a pressure system, state system and response system. (ii) In the past five years, the comprehensive index of the DGI in manufacturing industry has generally shown a trend of fluctuating rise. There are overall low and unbalanced phenomena in all regions. The gap decreased from 0.1320 to 0.1187, showing a gradually narrowing trend. (iii) Compared with other regions, the composite index of DGI is generally higher in the regions with a better ecological environment in the east and a more developed economy in the north. State parameters are higher than pressure and response parameters in most areas. (iv) Compared with other regions, the composite index of DGI in western and southern regions is lower, and the parameters of pressure, status and response are basically coordinated. (v) The application degree of digital technology, the emission intensity of waste water/exhaust gas of output value of one hundred million yuan and the expenditure intensity of digital technology adopted by enterprises are the key influencing factors of DGI in the manufacturing industry. This study not only proposed an evaluation index system of the digital green innovation level, but also puts forward policy guidance and practical guidance of digital technology to accelerate the green and intelligent manufacturing industry. [ABSTRACT FROM AUTHOR]

Digital green innovation management activities are the core of low-carbon intelligent development of prefabricated construction enterprises (PCEs) for sustainable urban development. PCEs have to seek joint venture partners to avoid the financial risk of digital green innovation projects. The purpose of this study is to develop a conceptual partner selection framework for the digital green innovation management of prefabricated construction towards urban building 5.0. In this study, first, symbiosis theory and six analysis methods were integrated to innovatively build a 3W1H-P framework system for the joint venture capital partner selection of digital green innovation projects. Second, the dual combination weighting method was innovatively proposed to avoid subjective and objective deviation in attribute weight and time weight. Finally, empirical research was carried out to verify the scientific nature, reliability, and practicability of the framework system and selection model. The results of this study show that the framework system and selection model proposed can be used to assist PCEs to select joint investment partners of digital green and innovative projects for sustainable urban development. [ABSTRACT FROM AUTHOR]

In recent years, teleoperation has experienced rapid development. Numerous teleoperation applications in diverse areas have been reported. Among all teleoperation-related components, computer vision (CV) is treated as one of the must-have technologies, because it allows users to observe remote scenarios. In addition, CV can further help the user to identify and track the desired targets from complex scenes. It has been proven that efficient CV methods can significantly improve the operation accuracy and relieve user's physical and mental fatigue. Therefore, furthering understanding about CV techniques and reviewing the latest research outcomes is necessary for teleoperation designers. In this context, this review article was composed. [ABSTRACT FROM AUTHOR]

Simple Summary: Using 138 snap bean accessions as plant materials, we investigated their suture strings across two years. With the goal of identifying the gene(s) responsible for the formation of suture strings, we conducted a genome-wide association study. A strong association signal was found in a 266.19 kb region on Chr02. Within the region, 23 candidate genes were identified. Importantly, the sequence and gene expression of PvGUX1_1 differed significantly between sutured pods and non-sutured pods. In addition, PvGUX1_1 was also a domesticated locus that diverged from PvGUX1_2 during an early stage. The results obtained in this study can provide important information for the improvement of pod quality in snap beans. Suture strings are a particularly important pod trait that determine the quality and texture of snap beans (Phaseolus vulgaris L.). The St locus on chromosome 2 has been described as a major locus associated with suture strings. However, the gene and genetic basis underlying this locus remain unknown. Here, we investigated the suture strings of 138 snap bean accessions across two years. A total of 3.66 million single-nucleotide polymorphisms (SNPs) were obtained by deep resequencing. Based on these SNPs, we identified a strong association signal on Chr02 and a promising candidate gene, PvGUX1_1. Further analysis revealed that the 2 bp deletion in the exon of PvGUX1_1 was significantly associated with stringlessness. Comparative mapping indicated that PvGUX1_1 was a domesticated locus and diverged from PvGUX1_2 during an early stage. Our study provides important insights into the genetic mechanism of suture string formation and useful information for snap bean improvement. [ABSTRACT FROM AUTHOR]

Automatic terrain classification in lower limb rehabilitation systems has gained worldwide attention. In this field, a simple system architecture and high classification accuracy are two desired attributes. In this article, a smart neuromuscular–mechanical fusion and machine learning-based terrain classification technique utilizing only two electromyography (EMG) sensors and two ground reaction force (GRF) sensors is reported for classifying three different terrains (downhill, level, and uphill). The EMG and GRF signals from ten healthy subjects were collected, preprocessed and segmented to obtain the EMG and GRF profiles in each stride, based on which twenty-one statistical features, including 9 GRF features and 12 EMG features, were extracted. A support vector machine (SVM) machine learning model is established and trained by the extracted EMG features, GRF features and the fusion of them, respectively. Several methods or statistical metrics were used to evaluate the goodness of the proposed technique, including a paired-t-test and Kruskal–Wallis test for correlation analysis of the selected features and ten-fold cross-validation accuracy, confusion matrix, sensitivity and specificity for the performance of the SVM model. The results show that the extracted features are highly correlated with the terrain changes and the fusion of the EMG and GRF features produces the highest accuracy of 96.8%. The presented technique allows simple system construction to achieve the precise detection of outcomes, potentially advancing the development of terrain classification techniques for rehabilitation. [ABSTRACT FROM AUTHOR]

In the field of rehabilitation, the electromyography (EMG) signal plays an important role in interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the EMG signal suffers from difficulty in recognizing slight body movements, and the detection accuracy is strongly influenced by environmental factors. To address the above issues, multisensory integration-based EMG pattern recognition (PR) techniques have been developed in recent years, and fruitful results have been demonstrated in diverse rehabilitation scenarios, such as achieving high locomotion detection and prosthesis control accuracy. Owing to the importance and rapid development of the EMG centered multisensory fusion technologies in rehabilitation, this paper reviews both theories and applications in this emerging field. The principle of EMG signal generation and the current pattern recognition process are explained in detail, including signal preprocessing, feature extraction, classification algorithms, etc. Mechanisms of collaborations between two important multisensory fusion strategies (kinetic and kinematics) and EMG information are thoroughly explained; corresponding applications are studied, and the pros and cons are discussed. Finally, the main challenges in EMG centered multisensory pattern recognition are discussed, and a future research direction of this area is prospected. [ABSTRACT FROM AUTHOR]

Simple Summary: Nowadays, as demand for reducing feed waste is increasing, it is imperative to apply enzyme preparations to achieve maximum effectiveness of feed. This study investigated the effects of dietary supplementation with phytase and protease in low-energy and low-protein diet on the growth performance, serum metabolism parameters, and intestinal digestive enzyme activities of meat ducks, which provided new insights into the positive roles of phytase and protease in growth performance, serum metabolism parameters, and intestinal digestive enzyme activities. This study contributes to the improvement in appropriate applications of exogenous enzyme preparations for poultry industry. Two experiments were conducted to investigate the effects of dietary supplementation with protease and phytase on growth performance, serum physiochemical parameters, and activities of digestive enzymes in jejunal digesta of meat ducks. Experiment 1 was carried out to determine the effects of different protease or phytase on growth performance, serum physiochemical parameter, and activities of digestive enzymes in jejunal digesta of meat ducks to select the optimal phytase or protease. According to the hatching age and initial weight, a total of 5040 Cherry Valley ducks (15 days of age) were randomly assigned into six treatments. Treatments included a basal control diet (CON) and 5 basal diets supplemented with different enzyme preparations, which were phytase preparation A (PA, 160 g/t), phytase preparation B (PB, 800 g/t), protease preparation A (PTA, 80 g/t), protease preparation B (PTB, 300 g/t) and protease preparation C (PTC, 200 g/t). The enzyme activities were as follows: Phytase A and B as well as protease A, B, and C were 50,000, 10,000, 250,000, 50,000, and 60,000 U/g, respectively. Each treatment had 7 replicates with 120 meat ducks per replicate. Experiment 1 lasted for 28 days. The results showed that: compared with the CON group, the PA group significantly decreased contents of serum phosphorus and calcium (p < 0.05), and the PTA, PTB, and PTC groups had higher activities of trypsin in jejunal digesta (p < 0.05), and the activity of jejunal chymotrypsin in PTA group was greater (p < 0.05). Experiment 2 was carried out to determine the effects of dietary supplementation with protease and phytase in low-energy and low-protein diet on growth performance, serum physiochemical parameters, and activities of digestive enzymes in jejunal digesta of meat ducks. According to the hatching age and initial weight, a total of 5760 Cherry Valley ducks (15 days of age) were randomly assigned into four treatments on the basis of a trial of 2 × 2 factorial design. Treatments included a basal control diet (PC), basal diet supplemented with enzymes (PCE), low-energy and low-protein diet (LEP), and low-energy and low-protein diet supplemented with enzymes (LEPE), the nutrient levels of energy and CP of basal diet were 2747.2 cal·ME/kg and 16.80%, respectively, and the nutrient levels of energy and CP of low-energy and low-protein diet decreased 45.90 kcal·ME/kg and 0.52% on the basis of basal diet, respectively. According to the results of experiment 1, phytase A and protease A were determined as the optimal enzyme combination of Experiment 2, and additional dosage of which were identical with Experiment 1. Each treatment had 6 replicates with 240 meat ducks per replicate. Experiment 2 lasted for 28 days. The results showed that: compared with PC and LEP groups, PCE and LEPE groups had higher final weight and average daily gain (ADG) (p < 0.05), higher activities of trypsin and chymotrypsin in jejunal digesta (p < 0.05), lower contents of serum calcium and phosphorus as well as higher levels of high-density lipoprotein in the serum (p < 0.05). In conclusion, dietary supplementation with phytase and protease in different energy and protein diets could increase digestive enzymes in jejunal digesta, effect serum physiochemical parameters, improve metabolic status, and increase the growth performance of meat ducks. Meanwhile, with the dietary supplementation with phytase and protease in the lower energy and protein diet, the growth performance could reach to the degree of the higher energy and increased protein diet, but without the addition of phytase and protease. [ABSTRACT FROM AUTHOR]

The self-designed HaiYang-2B (HY-2B) satellite was launched on 24 October 2018 in China at 22:57 UT in a 99.34° inclination sun-synchronous orbit. The Scanning Microwave Radiometer (SMR) on the core observatory has the capability to provide near-real-time multi-channel brightness temperature (Tb) observations, which are designed mainly for improving the level of marine forecasting and monitoring, serving the development and utilization of marine resources. After internal calibration and ocean calibration, the first effort to retrieve land surface snow parameters was performed in this study, which obtained extremely low accuracy both in snow extent and snow mass. Accordingly, land inter-sensor calibration was carried out between SMR and the Advanced Microwave Scanning Radiometer 2 (AMSR2) in order to broaden the research and application of SMR data on the Earth's land surface. Finally, we evaluated the consistency of the snow extent and snow mass derived from the initial and land-calibrated SMR data. The results indicated that a systematic SMR cold deviation whose magnitude depends on the channel is present for all the compared channels. After intercalibration, the conformity of the snow extent and snow mass were substantially improved compared to before; the relative bias of the snow extent and snow mass decreased from −49.97% to 2.97% and from −51.71% to 3.01%, respectively. [ABSTRACT FROM AUTHOR]

Small and medium enterprises (SMEs) are forced to adhere to sustainable development (SD) regulations and standards. However, SMEs encounter difficulty in assessing their performance due to the lack of an efficient and effective approach to deal with the uncertainties in hierarchical relationships and interrelationships. Moreover, interrelations exist among the proposed attributes that increase the difficulty of the assessment. To overcome these issues, exploratory factor analysis is used to screen out the less important attributes and build a hierarchal structure. The fuzzy synthetic method addresses the hierarchical structure and decision-making, and a trial evaluation laboratory assesses the interrelationships among the attributes by providing a visual interrelationship map. The results indicate that strategic and financial management are the major problems for SMEs. SD relies on enhancing sustainable supply chain performance, sustainable human resources and environmental management. This study contributes by not only filling the information gap for SD for SMEs but also providing a guideline for improvement. The theoretical and managerial implications are discussed. [ABSTRACT FROM AUTHOR]

Conventional electrical resistance tomography (ERT) sensors suffer from the fringe effect, i.e., severe distortion of the electric field on both ends of the measurement electrodes, leading to a 3D sensing region for a 2D sensor. As a result, the objects outside an ERT sensor plane affect the sensing and hence image, i.e., deteriorating the image quality. To address this issue, a multiple-plane ERT sensor scheme is proposed in this paper. With this scheme, auxiliary sensor planes are used to provide references for the fringe effect of the measurement plane, for compensation by subtracting the weighed influence of the fringe effect. Simulation results show that the proposed scheme, either three-plane or two-plane sensor, can compensate for the fringe effect induced by objects outside the measurement plane with a variety of axial object distributions, i.e., several non-conductive bars or conductive bars placed at different cross-sectional and axial positions inside the sensor. Experiments were carried out. Images obtained with single-plane and multiple-plane ERT sensors are compared, and the proposed compensation scheme has been hence verified. [ABSTRACT FROM AUTHOR]

The Reticuloendotheliosis virus (REV) primarily causes avian severe immunosuppression, in addition to other symptoms, which include avian dwarfing syndrome and chronic tumors in lymphoid and other tissue. To date, REV's molecular mechanisms leading to immunosuppression have not been fully elucidated. In the current study, we aimed to elucidate the role of microRNAs (miRNA) in regulating gene expression during REV infections. Therefore, we used a high-dose spleen necrosis virus (SNV) model of REV to inoculate one-day-old specific pathogen-free (SPF) chickens, thereby inducing congenital infections. We analyzed miRNA and mRNA expression profiles using Next Generation Sequencing (NGS) in a total of 19 spleen samples that were collected at 7, 14, and 21 days post infection (dpi). The results showed that 63 differentially expressed miRNAs (DEmiRNAs) (30 known miRNAs and 33 novel miRNAs) and 482 differentially expressed target genes (DETGs) were identified. Integration analysis identified 886 known miRNA–mRNA and 580 novel miRNA–mRNA interaction pairs, which involved miRNAs that were inversely correlated with the above DETGs. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the DETGs were considerably enriched in the immune-relevant pathways category, such as immune system, cell growth and death, signaling molecules and interaction, signal transduction, etc. We further verified selected immune-relevant miRNA and their DETGs while using quantitative RT-PCR (qRT-PCR). Overall, our data revealed valuable immune-related miRNA–mRNA interaction information that occurred during REV infections, thereby broadening our understanding of the REV-induced immunosuppression. [ABSTRACT FROM AUTHOR]

High detection accuracy in piezoelectric-based force sensing in interactive displays has gained global attention. To achieve this, artificial neural networks (ANN)—successful and widely used machine learning algorithms—have been demonstrated to be potentially powerful tools, providing acceptable location detection accuracy of 95.2% and force level recognition of 93.3% in a previous study. While these values might be acceptable for conventional operations, e.g., opening a folder, they must be boosted for applications where intensive operations are performed. Furthermore, the relatively high computational cost reported prevents the popularity of ANN-based techniques in conventional artificial intelligence (AI) chip-free end-terminals. In this article, an ANN is designed and optimized for piezoelectric-based touch panels in interactive displays for the first time. The presented technique experimentally allows a conventional smart device to work smoothly with a high detection accuracy of above 97% for both location and force level detection with a low computational cost, thereby advancing the user experience, and serviced by piezoelectric-based touch interfaces in displays. [ABSTRACT FROM AUTHOR]

Dental care is consistently reported as one of the primary medical needs of children with disabilities (IDC). The aim of the present study was to explore the influence of oral health behaviors on the caries experience in children with intellectual disabilities in Guangzhou, China. A cross-sectional study was carried out in 477 intellectually disabled children, 12 to 17 years old, who were randomly selected from special educational schools in Guangzhou. A self-administered parental questionnaire was used to collect data on socio-demographic characteristics and oral health behavior variables, and 450 valid questionnaires were returned. Multiple regression analysis was used to examine the factors associated with dental caries. The average age of those in the sample was 14.6 years (SD = 1.3), 68.4% of whom were male, and the caries prevalence rate was 53.5% (DMFT = 1.5 ± 2.0). The factors significantly affecting the development of dental caries in IDC included gender, the presence or absence of cerebral palsy, and the frequency of dental visits and toothbrushing. In conclusion, the presence of cerebral palsy contributed to an increase risk of caries experience in intellectually disabled children, while toothbrushing more than twice a day and routine dental visits were caries-protective factors. Oral health promotion action may lead to a reduction in dental caries levels in IDC.

Candida albicans is strongly associated with severe early childhood caries (S-ECC). However, the roles of secreted aspartyl proteinases (Saps), an important virulence factor of C. albicans, in the progress of S-ECC are not clear. In our study, the Saps activities were evaluated by the yeast nitrogen base-bovine serum albumi (YNB-BSA) agar plate method and by the MTT method with bovine serum albumin (BSA) as the substrate. Genotypes of C. albicans and gene expression of Sap1-5 were evaluated. The relationships of Saps activities and genotypes with S-ECC were analyzed. The results showed that enzyme activities of Saps in the S-ECC group were significantly higher than those in the caries free (CF) group (p<0.05). Genotypes A, B and C were detected in the S-ECC group, and genotypes A and C were detected in the CF group. In the genotype A group, Saps activity in the S-ECC group was significantly different from that in the CF group (p<0.05). The gene expression level of Sap1 in the S-ECC group was significantly higher than that in the CF group (p=0.001), while Sap4 expression was significantly lower than that in the CF group (p=0.029). It can be concluded that Sap1-5 are the predominant proteinase genes expressed in C. albicans from dental biofilm and Sap1 may play an important role in the development of S-ECC.

The aqueous solubility (logW) and n-octanol/water partition coefficient (logP(OW)) are important properties for pharmacology, toxicology and medicinal chemistry. Based on an understanding of the dissolution process, the frontier orbital interaction model was suggested in the present paper to describe the solvent-solute interactions of organohalogen compounds and a general three-parameter model was proposed to predict the aqueous solubility and n-octanol/water partition coefficient for the organohalogen compounds containing nonhydrogen-binding interactions. The model has satisfactory prediction accuracy. Furthermore, every item in the model has a very explicit meaning, which should be helpful to understand the structure-solubility relationship and may be provide a new view on estimation of solubility.