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Abstract Background Sensor-based interventions (SI) have been suggested as an alternative rehabilitation treatment to improve older adults’ functional performance. However, the effectiveness of different sensor technologies in improving gait and balance remains unclear and requires further investigation. Methods Ten databases (Academic Search Premier; Cumulative Index to Nursing and Allied Health Literature, Complete; Cochrane Central Register of Controlled Trials; MEDLINE; PubMed; Web of Science; OpenDissertations; Open grey; ProQuest; and Grey literature report) were searched for relevant articles published up to December 20, 2022. Conventional functional assessments, including the Timed Up and Go (TUG) test, normal gait speed, Berg Balance Scale (BBS), 6-Minute Walk Test (6MWT), and Falling Efficacy Scale-International (FES-I), were used as the evaluation outcomes reflecting gait and balance performance. We first meta-analyzed the effectiveness of SI, which included optical sensors (OPTS), perception sensors (PCPS), and wearable sensors (WS), compared with control groups, which included non-treatment intervention (NTI) and traditional physical exercise intervention (TPEI). We further conducted sub-group analysis to compare the effectiveness of SI (OPTS, PCPS, and WS) with TPEI groups and compared each SI subtype with control (NTI and TPEI) and TPEI groups. Results We scanned 6255 articles and performed meta-analyses of 58 selected trials (sample size = 2713). The results showed that SI groups were significantly more effective than control or TPEI groups (p

We evaluated the effects of cottonseed meal protein hydrolysate (CPH) on the intestinal microbiota of yellow-feather broilers. We randomly divided 240 chicks into four groups with six replicates: basal diet with 0% (CON), 1% (LCPH), 3% (MCPH), or 5% (HCPH) CPH. The test lasted 63 days and included days 1–21, 22–42, and 43–63 phases. The ACE, Chao1, and Shannon indices in the MCPH and HCPH groups of 42-day-old broilers were higher than those in the CON group (p

Abstract Background Falls pose a severe threat to the health of older adults worldwide. Determining gait and kinematic parameters that are related to an increased risk of falls is essential for developing effective intervention and fall prevention strategies. This study aimed to investigate the discriminatory parameter, which lay an important basis for developing effective clinical screening tools for identifying high-fall-risk older adults. Methods Forty-one individuals aged 65 years and above living in the community participated in this study. The older adults were classified as high-fall-risk and low-fall-risk individuals based on their BBS scores. The participants wore an inertial measurement unit (IMU) while conducting the Timed Up and Go (TUG) test. Simultaneously, a depth camera acquired images of the participants’ movements during the experiment. After segmenting the data according to subtasks, 142 parameters were extracted from the sensor-based data. A t-test or Mann-Whitney U test was performed on the parameters for distinguishing older adults at high risk of falling. The logistic regression was used to further quantify the role of different parameters in identifying high-fall-risk individuals. Furthermore, we conducted an ablation experiment to explore the complementary information offered by the two sensors. Results Fifteen participants were defined as high-fall-risk individuals, while twenty-six were defined as low-fall-risk individuals. 17 parameters were tested for significance with p-values less than 0.05. Some of these parameters, such as the usage of walking assistance, maximum angular velocity around the yaw axis during turn-to-sit, and step length, exhibit the greatest discriminatory abilities in identifying high-fall-risk individuals. Additionally, combining features from both devices for fall risk assessment resulted in a higher AUC of 0.882 compared to using each device separately. Conclusions Utilizing different types of sensors can offer more comprehensive information. Interpreting parameters to physiology provides deeper insights into the identification of high-fall-risk individuals. High-fall-risk individuals typically exhibited a cautious gait, such as larger step width and shorter step length during walking. Besides, we identified some abnormal gait patterns of high-fall-risk individuals compared to low-fall-risk individuals, such as less knee flexion and a tendency to tilt the pelvis forward during turning.

BackgroundWith the development of emerging technologies, digital behavior change interventions (DBCIs) help to maintain regular physical activity in daily life. ObjectiveTo comprehensively understand the design implementations of habit formation techniques in current DBCIs, a systematic review was conducted to investigate the implementations of behavior change techniques, types of habit formation techniques, and design strategies in current DBCIs. MethodsThe process of this review followed the PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. A total of 4 databases were systematically searched from 2012 to 2022, which included Web of Science, Scopus, ACM Digital Library, and PubMed. The inclusion criteria encompassed studies that used digital tools for physical activity, examined behavior change intervention techniques, and were written in English. ResultsA total of 41 identified research articles were included in this review. The results show that the most applied behavior change techniques were the self-monitoring of behavior, goal setting, and prompts and cues. Moreover, habit formation techniques were identified and developed based on intentions, cues, and positive reinforcement. Commonly used methods included automatic monitoring, descriptive feedback, general guidelines, self-set goals, time-based cues, and virtual rewards. ConclusionsA total of 32 commonly design strategies of habit formation techniques were summarized and mapped to the proposed conceptual framework, which was categorized into target-mediated (generalization and personalization) and technology-mediated interactions (explicitness and implicitness). Most of the existing studies use the explicit interaction, aligning with the personalized habit formation techniques in the design strategies of DBCIs. However, implicit interaction design strategies are lacking in the reviewed studies. The proposed conceptual framework and potential solutions can serve as guidelines for designing strategies aimed at habit formation within DBCIs.

Water-based adsorption chillers (ADC) driven by low-grade thermal energy are environment-friendly alternatives to the traditional compression ones to realize the net zero carbon target. Aluminophosphates molecular sieve (AlPOs) is an excellent material for water-based adsorption applications. However, AlPOs suffers from relatively high cost attributed to the extensive use of expensive structure direct agents (SDAs). This study employed a dual-template method, using cheap organic amine as a dual-template, to synthesize low-cost and excellent adsorbent AlPOs with SFO topology (AlPO-SFO). AlPO-SFO synthesized with dual templates shows high crystallinity, large micropore volume, excellent water uptake, and low regeneration temperature. AlPO-SFO guided by 4-dimethylaminopyridine (4-DMAPy) and diethanolamine (DEOA) molar composition of 0.4 and 0.1 exhibits large microporous volume (0.30 ml g−1), high water uptake (0.26 g g−1 at P/P0 = 0.25) and low regeneration temperature (65 °C). Importantly, this AlPO-SFO exhibits a high coefficient of performance (COP) of 0.89 for cooling at a low driven temperature of 64 °C. The additive amine providing alkaline medium ensures the practical synthesis of AlPO-SFO when expensive 4-DMAPy decreases, endowing the 42 % reduction of the raw material cost. The results provide a cheaper synthesis route of AlPO-SFO, which is conducive to its large-scale production as a distinguished adsorbent for adsorption chillers.

Abstract Background The incidence of pancreatic cancer (PC) is higher in diabetic patients due to disturbances in glucose and lipid metabolism caused by insulin resistance (IR). However, the effect of diabetes as well as IR on the prognosis of PC patients remains inconclusive. Our study aims to assess the impact of IR on the prognosis of PC patients with diabetes. Methods We conducted a retrospective analysis of 172 PC patients with diabetes in our institute from 2015 to 2021. Prognostic assessment was performed using univariate/multifactorial analysis and survival analysis. The predictive efficacy of metabolic indices was compared using receiver operator characteristic (ROC) curve analysis. Results One hundred twenty‐one of 172 patients died during follow‐up, with a median follow‐up of 477 days and a median overall survival (OS) of 270 days. Survival analysis showed a significant difference in OS by IR related parameters, which were triglyceride‐glucose index (TyG), triglyceride‐glucose index‐body mass index (TyG‐BMI), and triglyceride/high‐density lipoprotein cholesterol ratio (TG/HDL‐c). The ROC curve indicated that TyG, TyG‐BMI, and TG/HDL‐c had prognostic efficacy for PC with diabetes. We next optimized TyG‐BMI and obtained a new parameter, namely glucose‐lipid metabolism index (GLMI), and the patients were classified into GLMI low group and high group based on the calculated cutoff value. The GLMI high group had higher TyG, TyG‐BMI, TyG/HDL‐c, BMI, TG, total cholesterol (TC), TC/HDL‐c, fasting plasma glucose, CA199, and more advanced tumor stage compared to low group. Univariate and multivariate analyses showed that GLMI was an independent prognostic factor. Furthermore, the patients of GLMI high group had worse OS compared to low group and the ROC curves showed GLMI had better predictive ability than TyG and TyG‐BMI. Conclusions IR is associated with the outcome of PC patients with diabetes and higher level of IR indicates worse prognosis. GLMI has a good predictive value for PC with diabetes.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with an extremely poor prognosis. Cancer stem cells (CSCs) are considered to be responsible for the poor survival, recurrence and therapy resistance of PDAC. Ferroptosis plays a crucial role in the sustain and survival of CSCs. Here, we employed a rigorous evaluation of multiple datasets to identify a novel stemness-based and ferroptosis-related genes (SFRGs) signature to access the potential prognostic application. This work we retrieved RNA-sequencing and clinical annotation data from the TCGA, ICGC, GTEx and GEO database, and acquired 26 stem cell gene sets and 259 ferroptosis genes from StemChecker database and FerrDb database, respectively. Based on consensus clustering and ssGSEA analysis, we identified two expression patterns of CSCs traits (C1 and C2). Then, WGCNA analysis was implemented to screen out hub module genes correlated with stemness. Furthermore, differential expression analysis, Pearson correlation analysis, and the Least absolute shrinkage and selection operator (LASSO) and Cox regression were performed to identify the SFRGs and to construct model. In addition, the differences in prognosis, tumor microenvironment (TME) components and therapy responses were evaluated between two risk groups. Finally, we verified the most influential marker ARNTL2 experimentally by western blot, qRT-PCR, sphere formation assay, mitoscreen assay, intracellular iron concentration determination and MDA determination assays. In conclusion, we developed a stemness-based and ferroptosis-related prognostic model, which could help predict overall survival for PDAC patients. Targeting ferroptosis may be a promising therapeutic strategy to inhibit PDAC progression by suppressing CSCs.

Recent reports have shown that wild crabs may be important hosts involved in the transmission and spread of the parasitic Hematodinium in cultured marine crustaceans. Therefore, monitoring the prevalence of Hematodinium infections in wild crabs is necessary to develop effective strategies for the prevention and control of Hematodinium disease. Here we report a wild crab species, Macrophthalmus (Macrophthalmus) abbreviatus Manning & Holthuis, 1981, as a new natural host for Hematodinium sp. infection. It is one of the common wild crab species dwelling in the ponds or waterways connected to the polyculture ponds located on the coast of Rizhao or Weifang, Shandong Peninsula, China. According to the results of PCR detection and phylogenetic analysis targeting the internal transcribed spacer 1 (ITS 1) region, these Hematodinium sp. isolates were identified as H. perezi and fell into the genotype II category within H. perezi. A high monthly prevalence of H. perezi infection was observed during the 2021–2022 field survey, ranging from 33.3% to 90.6% in M. abbreviatus originating from Weifang (n=304 wild crabs) and from 53.6% to 92.9% in those from Rizhao (n=42 wild crabs). Artificial inoculation infection experiments demonstrated that M. abbreviatus could be infected by H. perezi, and massive Hematodinium cells and typical histopathological changes were observed in the hepatopancreas and gill tissues of the infected crabs. To our knowledge, this is the first report of M. abbreviatus as a new natural host for H. perezi infection. Results in the present study extend the known host spectrum for this emerging parasite pathogen, and also provide valuable information for epidemic surveillance of the Hematodinium disease as well.

Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated nuclease 9 (Cas9) screening is a simple screening method for locating loci under specific conditions, and it has been utilized in tumor drug resistance research for finding potential drug resistance-associated genes. This screening strategy has significant implications for further treatment of malignancies with acquired drug resistance. In recent years, studies involving genome-wide CRISPR/Cas9 screening have gradually increased. Here we review the recent application of genome-wide CRISPR/Cas9 screening for drug resistance, involving mitogen-activated protein kinase (MAPK) pathway inhibitors, poly (ADP-ribose) polymerase inhibitors (PARPi), alkylating agents, mitotic inhibitors, antimetabolites, immune checkpoint inhibitors (ICIs), and cyclin-dependent kinase inhibitors (CDKI). We summarize drug resistance pathways such as the KEAP1/Nrf2 pathway MAPK pathway, and NF-κB pathway. Also, we analyze the limitations and conditions for the application of genome-wide CRISPR/Cas9 screening techniques.

Calf intestines are colonized by rich and complex microbial communities, playing a crucial role in animal physiology, metabolism, nutrition, and immune function. In this study, we provide insight into the composition of fecal microbial bacteria and fungi, respectively, as well as the cross-kingdom interactions. We investigated the intestinal microbiota of different breeds of calves by characterizing the bacterial and fungal communities in the rectal feces of Holstein calves and German Simmental × Holstein cross F1 generation (GXH) using 16S rRNA and ITS amplicon sequencing techniques. PICRUSt2 (version 2.2.0) were used to determine microbial diversity and function and explore the reasons why Holstein calves are more susceptible to diarrhea. The results revealed no significant difference in the diversity of fecal microbiota among the groups (p > 0.05). We identified Firmicutes, Bacteroidetes, and Proteobacteria as the dominant bacterial phyla in the fecal bacterial communities of the two breeds of calves. Ascomycota and Basidiomycota play important roles in the fungal community but differ in relative abundance. Bacteroides was the dominant genus at the group level for calf fecal microbiota in both breeds. The relative abundance of Prevotella, Escherichia-Shigella, Peptostreptococcus, and Butyricicoccus was higher in Holstein calves, and the relative abundance of Faecalibacterium, Megamonas, Butyricicoccus, and Alloprevotella was lower than GXH group. Aspergillus and Cladosporium were the dominating genera of fecal fungi in both groups of calves. LEfSe analysis revealed 33 different bacteria and 23 different fungi between the two groups, with more differential strains found in GXH. In addition, the feces fungi-bacteria interkingdom interactions varied among breeds. Thus, the composition and structure of bacterial and fungal communities in calf feces varied by breed, indicating a potential association between breed and microbial communities. We also found differences in the network between bacterial–fungal kingdoms. We explain the reasons for Holstein calves being more prone to diarrhea. This indicated that breed makes differences in calf diarrhea rates by influencing gut microbial composition and interactions.

The ability of cancer stem cells (CSCs) to self-renew, differentiate, and generate new tumors is a significant contributor to drug resistance, relapse, and metastasis. Therefore, the targeting of CSCs for treatment is particularly important. Recent studies have demonstrated that CSCs are more susceptible to ferroptosis than non-CSCs, indicating that this could be an effective strategy for treating tumors. Ferroptosis is a type of programmed cell death that results from the accumulation of lipid peroxides caused by intracellular iron-mediated processes. CSCs exhibit different molecular characteristics related to iron and lipid metabolism. This study reviews the alterations in iron metabolism, lipid peroxidation, and lipid peroxide scavenging in CSCs, their impact on ferroptosis, and the regulatory mechanisms underlying iron metabolism and ferroptosis. Potential treatment strategies and novel compounds targeting CSC by inducing ferroptosis are also discussed.

The half-bridge converter series Y-connection microgrid (HCSY-MG) is a new type of series microgrid. In order to reduce the harmonic content in HCSY-MG grid-connected current and at the same time simplify the parameter design process of the LCL filter, this study proposed an LCL filter parameter design method based on an improved particle swarm optimization-least squares support vector machine (PSO-LSSVM) by analyzing the harmonic characteristics of the HCSY-MG grid-connected current. In addition, to enhance the convergence speed of PSO-LSSVM, the inertia factor during its parameters’ update is made to adjust adaptively according to the direction of two consecutive parameter changes to constitute an improved PSO-LSSVM. Through simulation and comparative analysis, it is demonstrated that the improved PSO-LSSVM can enhance the convergence speed; the proposed filter parameter design method can effectively reduce the harmonic content in the HCSY-MG grid-connected current and is simpler and more comprehensive than the existing design method.

Routine assessments of gait and balance have been recognized as an effective approach for preventing falls by issuing early warnings and implementing appropriate interventions. However, current limited public healthcare resources cannot meet the demand for continuous monitoring of deteriorations in gait and balance. The objective of this study was to develop and evaluate the feasibility of a prototype surrogate system driven by sensor technology and multi-sourced heterogeneous data analytics, for gait and balance assessment and monitoring. The system was designed to analyze users’ multi-mode data streams collected via inertial sensors and a depth camera while performing a 3-m timed up and go test, a five-times-sit-to-stand test, and a Romberg test, for predicting scores on clinical measurements by physiotherapists. Generalized regression of sensor data was conducted to build prediction models for gait and balance estimations. Demographic correlations with user acceptance behaviors were analyzed using ordinal logistic regression. Forty-four older adults (38 females) were recruited in this pilot study (mean age = 78.5 years, standard deviation [SD] = 6.2 years). The participants perceived that using the system for their gait and balance monitoring was a good idea (mean = 5.45, SD = 0.76) and easy (mean = 4.95, SD = 1.09), and that the system is useful in improving their health (mean = 5.32, SD = 0.83), is trustworthy (mean = 5.04, SD = 0.88), and has a good fit between task and technology (mean = 4.97, SD = 0.84). In general, the participants showed a positive intention to use the proposed system in their gait and balance management (mean = 5.22, SD = 1.10). Demographic correlations with user acceptance are discussed. This study provides preliminary evidence supporting the feasibility of using a sensor-technology-augmented system to manage the gait and balance of community-dwelling older adults. The intervention is validated as being acceptable, viable, and valuable.

The surrounding rock during a coal mine excavation is prone to significant engineering disasters such as considerable deformation and rock bursts. Pressure release can improve the stress field of a deep rock mass and prevent the occurrence of dangers such as roadway collapse and coal and gas outbursts. This paper uses the ANSYS 19.0/LS-DYNA finite element software to simulate the crush area and fracture zone of a detonation charge with different diameters under in situ stress. The stability of the surrounding rock was analyzed based on the impact stress and velocity, and was verified by field tests. The research results show that the blasting load primarily affects the damaged area near the borehole, while the in situ stress affects far-field crack propagation. The crack propagates in the direction of high surrounding rock pressure. When the uncoupling index is 1.5, the impact pressure of a 60 mm diameter cartridge is eight times that of a 20 mm diameter cartridge. The impact speed can reach two times that of the 20 mm diameter cartridge. The high-energy event at the roof is transferred to the front of the working face, the distribution is no longer concentrated, and a better pressure-relief blasting effect is achieved. The research results can help guide the prevention and control measures of rock bursts and other mining disasters.

Abstract Electrocatalysts that start a reaction as molecules do not always end the reaction as molecules, and even when they do, they might not be molecules during catalysis. In this Perspective, we discuss knowledge learned from the study of Cu‐based molecularly structured electrocatalysts––including metal coordination complexes, metal‐organic frameworks, single‐atom catalysts, and polymeric materials––that restructure under electrochemical CO2 reduction reactions. Recent reports are summarized with an emphasis on the nature and significance of post‐mortem and in situ characterization for the proper identification of active sites. We demonstrate that molecular and material structures determine whether electrocatalysts restructure and how they restructure, that understanding of restructuring processes can help us identify active sites for catalysis, and that this knowledge can be leveraged to design precatalysts that generate highly active catalysts under reaction conditions. In addition, we provide recommended practices for studying the integrity of heterogeneous molecular catalysts during and after CO2 reduction reactions. Key Points Heterogeneous molecular Cu catalysts have been observed to restructure to metallic Cu clusters under reaction conditions. Dynamic or reversible restructuring confounds identification of real active sites. Both ex situ and in situ techniques are recommended for robust catalyst characterization.

The fermentation of grape seed meal, a non-conventional feed resource, improves its conventional nutritional composition, promotes the growth and development of livestock and fat metabolism by influencing the structure and diversity of intestinal bacteria. In this study, the nutritional components of Fermented grape seed meal (FGSM) and their effects on the growth performance, carcass quality, serum biochemistry, and intestinal bacteria of yellow feather broilers were investigated. A total of 240 male 14-day-old yellow-feathered broilers were randomly selected and divided into four groups, with three replicates of 20 chickens each. Animals were fed diets containing 0% (Group I), 2% (Group II), 4% (Group III), or 6% (Group IV) FGSM until they were 56 days old. The results showed that Acid soluble protein (ASP) and Crude protein (CP) contents increased, Acid detergent fiber (ADF) and Neutral detergent fiber (NDF) contents decreased, and free amino acid content increased in the FGSM group. The non-targeted metabolome identified 29 differential metabolites in FGSM, including organic acids, polyunsaturated fatty acids, and monosaccharides. During the entire trial period, Average daily gain (ADG) increased and Feed conversion ratio (FCR) decreased in response to dietary FGSM supplementation (p < 0.05). TP content in the serum increased and BUN content decreased in groups III and IV (p < 0.05). Simultaneously, the serum TG content in group III and the abdominal fat rate in group IV were significantly reduced (p < 0.05). The results of gut microbiota analysis showed that FGSM could significantly increase the Shannon and Simpson indices of broilers (35 days). Reducing the relative abundance of Bacteroidetes significantly altered cecal microbiota composition by increasing the relative abundance of Firmicutes (p < 0.05). By day 56, butyric acid content increased in the cecal samples from Group III (p < 0.05). In addition, Spearman’s correlation analysis revealed a strong correlation between broiler growth performance, abdominal fat percentage, SCFAs, and gut microbes. In summary, the addition of appropriate levels of FGSM to rations improved broiler growth performance and reduced fat deposition by regulating gut microbes through differential metabolites and affecting the microbiota structure and SCFA content of the gut.

Abstract Background Barthel Index (BI) is one of the most widely utilized tools for assessing functional independence in activities of daily living. Most existing BI studies used populations with specific diseases (e.g., Alzheimer’s and stroke) to test prognostic factors of BI scores; however, the generalization of these findings was limited when the target populations varied. Objectives The aim of the present study was to utilize electronic health records (EHRs) and data mining techniques to develop a generic procedure for identifying prognostic factors that influence BI score changes among community-dwelling elderly. Methods Longitudinal data were collected from 113 older adults (81 females; mean age = 84 years, SD = 6.9 years) in Hong Kong elderly care centers. Visualization technologies were used to align annual BI scores with individual EHRs chronologically. Linear mixed-effects (LME) regression was conducted to model longitudinal BI scores based on socio-demographics, disease conditions, and features extracted from EHRs. Results The visualization presented a decline in BI scores changed by time and health history events. The LME model yielded a conditional R2 of 84%, a marginal R2 of 75%, and a Cohen’s f2 of 0.68 in the design of random intercepts for individual heterogeneity. Changes in BI scores were significantly influenced by a set of socio-demographics (i.e., sex, education, living arrangement, and hobbies), disease conditions (i.e., dementia and diabetes mellitus), and EHRs features (i.e., event counts in allergies, diagnoses, accidents, wounds, hospital admissions, injections, etc.). Conclusions The proposed visualization approach and the LME model estimation can help to trace older adults’ BI score changes and identify the influencing factors. The constructed long-term surveillance system provides reference data in clinical practice and help healthcare providers manage the time, cost, data and human resources in community-dwelling settings.

In the context of smart grid planning and construction, how to tackle the future distribution network, a comprehensive evaluation of smart distribution network planning has become an urgent problem to be solved. To address this issue, this research provides a method for comprehensive evaluation that combines subjective and objective weighing approaches. Firstly, a set of evaluation index system is constructed and quantified based on the characteristics of the future distribution network; after that a comprehensive evaluation model is established and a subjective and objective weighting method combining AHP-entropy weighting method is used to weight the indicators; Finally, the actual data from the distribution network is evaluated and scored. Based on the scoring verification results, the correctness and effectiveness of the method proposed in this paper are verified.

Sb2(S, Se)3 solar cells have shown great promise due to the advantages of low cost, non-toxic and high stability. However, traditional devices commonly use noble metal as the back electrode, which not only increases device cost but also limits device stability. Herein, carbon materials are used to replace the noble metals in Sb2(S, Se)3 solar cells. In addition, to grow high-quality Sb2(S, Se)3 films, a two-step hydrothermal method was developed. The carbon-based Sb2(S, Se)3 solar cells based on the above film achieved a power conversion efficiency (PCE) of 2.76%. After inserting a stable P3HT layer at the Sb2(S, Se)3 film/carbon interface, hole extraction was enhanced and the PCE was promoted to 4.15%. This work brings out a promising route to produce emerging solar cells with cost-effective and stable materials.

Abstract Background Poor balance has been cited as one of the key causal factors of falls. Timely detection of balance impairment can help identify the elderly prone to falls and also trigger early interventions to prevent them. The goal of this study was to develop a surrogate approach for assessing elderly’s functional balance based on Short Form Berg Balance Scale (SFBBS) score. Methods Data were collected from a waist-mounted tri-axial accelerometer while participants performed a timed up and go test. Clinically relevant variables were extracted from the segmented accelerometer signals for fitting SFBBS predictive models. Regularized regression together with random-shuffle-split cross-validation was used to facilitate the development of the predictive models for automatic balance estimation. Results Eighty-five community-dwelling older adults (72.12 ± 6.99 year) participated in our study. Our results demonstrated that combined clinical and sensor-based variables, together with regularized regression and cross-validation, achieved moderate-high predictive accuracy of SFBBS scores (mean MAE = 2.01 and mean RMSE = 2.55). Step length, gender, gait speed and linear acceleration variables describe the motor coordination were identified as significantly contributed variables of balance estimation. The predictive model also showed moderate-high discriminations in classifying the risk levels in the performance of three balance assessment motions in terms of AUC values of 0.72, 0.79 and 0.76 respectively. Conclusions The study presented a feasible option for quantitatively accurate, objectively measured, and unobtrusively collected functional balance assessment at the point-of-care or home environment. It also provided clinicians and elderly with stable and sensitive biomarkers for long-term monitoring of functional balance.

Abstract Hetero-element doped lithium orthosilicates have been considered as advanced tritium breeders due to the superior performances. In this work, Li4Si1−x Ti x O4 ceramics were prepared by proprietary hydrothermal process and multistage reactive sintering. The reaction mechanism of Li4Si1−x Ti x O4 was put forward. XRD and SEM analyses indicate that insertion of Ti leads to lattice expansion, which promotes the grain growth and changes the fracture mode. The compressive tests show that the crush load increases almost four times by increasing x from 0 to 0.2. However, the thermal conductivity and ionic conductivity are the best when x = 0.05 and x = 0.1, respectively. Thermal cycling stability of Li4Si1−x Ti x O4 pebbles was further appraised through investigating the changes of microstructure and crush load. After undergoing thermal cycling, the Li4Si1−x Ti x O4 still show higher crush load compared with Li4SiO4, despite Ti segregation in some samples. The x = 0.05 sample exhibits excellent thermal cycling stability. In summary, proper amount of Ti doping can improve the crush load, thermal and ionic conductivity, and thermal cycling stability of Li4SiO4.

Abstract Background Patients with coexisting type 2 diabetes and hypertension generally exhibit poor adherence to self-management, which adversely affects their disease control. Therefore, identification of the factors related to patient adherence is warranted. In this study, we aimed to examine (i) the socio-demographic correlates of patient adherence to a set of self-management behaviors relevant to type 2 diabetes and hypertension, namely, medication therapy, diet therapy, exercise, tobacco and alcohol avoidance, stress reduction, and self-monitoring/self-care, and (ii) whether health attitudes and self-efficacy in performing self-management mediated the associations between socio-demographic characteristics and adherence. Methods We performed a secondary analysis of data collected in a randomized controlled trial. The sample comprised 148 patients with coexisting type 2 diabetes mellitus and hypertension. Data were collected by a questionnaire and analyzed using logistic regression. Results Female patients were found to be less likely to exercise regularly (odds ratio [OR] = 0.49, P = 0.03) and more likely to avoid tobacco and alcohol (OR = 9.87, P

Abstract Background The poorly known mycobacterial species Mycobacterium monacense is a rapidly growing non-tuberculous mycobacterium that was first described in 2006 (Reischl et al., Int J Syst Evol Microbiol 56:2575-8, 2006); it has been reported that its isolation is usually associated with skin and lung infections, especially in immunosuppressed patients (Hogardt et al., Jpn J Infect Dis 61:77-8, 2008; Taieb et al., J Hand Surg Am 33:94-6, 2008; Therese et al., Lung India 28:124-6, 2011; Shojaei et al., Ann Lab Med 32:87-90, 2012; Romero et al., New Microbes New Infect 10:112-5, 2016 ). The clinical significance of Mycobacterium monacense is not yet fully understood. Here, we report the first isolation of Mycobacterium monacense from the blood culture of a patient in China with severe pneumonia. Case presentation On June 26, 2018, a 38-year-old man was admitted to the intensive care unit with breathing difficulty. One day prior, he was discovered with his face immersed in a small pond (non-chlorinated water) and with limb convulsions. He had undergone craniocerebral surgery after trauma 5 years earlier, which left him with epilepsy as a sequela. Bilateral diffuse ground-glass opacity was found in the lungs on chest X ray and chest CT image at admission. The result of the HIV serology test of the patient was negative. The patient was diagnosed with severe pneumonia. Drug-susceptible Klebsiella pneumoniae and Candida glabrata were isolated in the BALF, and yellow-pigmented colonies were isolated from blood cultures of the patient. The strain isolated from blood was identified by 16S rDNA sequencing as Mycobacteria monacense, which is a rapidly growing mycobacterium (RGM). The patient was treated with a combination of cefoperazone sulbactam, linezolid and voriconazole for 10 days, and the symptoms improved. During the one-year follow-up time, the patient did not relapse. Conclusions We report the first case of M. monacense isolated from blood cultures in a patient with severe pneumonia, which provided evidence that the environmental microorganism possessed pathogenic characteristics.

The quality of emergency training determines the professional ability of emergency personnel. To evaluate the safety of emergency training for building collapse ruin training scenarios, an approach combining analytic hierarchy process (AHP) and gray-fuzzy evaluation is proposed. According to the characteristics of building collapse ruin training scenarios and the principle of index selection, a safety evaluation index system for this training is constructed from four aspects: human, machine, environment, and management. AHP is used to determine the weight of each evaluation index, and the evaluation model is established base of the gray-fuzzy evaluation method. Based on the combination of the two methods, the quantitative results on training safety was obtained and the most important factor that have the greatest impact on training safety was found. Using this presented assessment method, the safety of an building collapse ruin training scenario for a domestic emergency training facility are assessed, the defects in its emergency capacity are determined, and measures and suggestions are recommended to provide scientific and effective basis for improving emergency capacity.

To evaluate the safety of emergency training for industrial accident scenarios, an approach combining analytic hierarchy process (AHP) and gray-fuzzy evaluation is proposed. According to the characteristics of industrial emergency training scenarios, a safety evaluation index system for this training is constructed from four aspects: human, machine, environment, and management. The index weight is established using the AHP and the evaluation model is established base of the gray-fuzzy evaluation method. Based on the combination of the two methods, the quantitative results on training safety was obtained and the most important factor that have the greatest impact on training safety was found. Using this new assessment method, the safety of an industrial accident training scenario for a domestic emergency training facility are assessed, the defects in its emergency capacity are determined, and measures and suggestions are recommended to provide scientific and effective basis for improving emergency capacity.

Abstract Background The accelerated growth of elderly population is creating a heavy burden to the healthcare system in many developed countries and regions. Electrocardiogram (ECG) analysis has been recognized as effective approach to cardiovascular disease diagnosis and widely utilized for monitoring personalized health conditions. Method In this study, we present a novel approach to forecasting one-day-forward wellness conditions for community-dwelling elderly by analyzing single lead short ECG signals acquired from a station-based monitoring device. More specifically, exponentially weighted moving-average (EWMA) method is employed to eliminate the high-frequency noise from original signals at first. Then, Fisher-Yates normalization approach is used to adjust the self-evaluated wellness score distribution since the scores among different individuals are skewed. Finally, both deep learning-based and traditional machine learning-based methods are utilized for building wellness forecasting models. Results The experiment results show that the deep learning-based methods achieve the best fitted forecasting performance, where the forecasting accuracy and F value are 93.21% and 91.98% respectively. The deep learning-based methods, with the merit of non-hand-crafted engineering, have superior wellness forecasting performance towards the competitive traditional machine learning-based methods. Conclusion The developed approach in this paper is effective in wellness forecasting for community-dwelling elderly, which can provide insights in terms of implementing a cost-effective approach to informing healthcare provider about health conditions of elderly in advance and taking timely interventions to reduce the risk of malignant events.

BackgroundClinical mobility and balance assessments identify older adults who have a high risk of falls in clinics. In the past two decades, sensors have been a popular supplement to mobility and balance assessment to provide quantitative information and a cost-effective solution in the community environment. Nonetheless, the current sensor-based balance assessment relies on manual observation or motion-specific features to identify motions of research interest. ObjectiveThe objective of this study was to develop an automatic motion data analytics framework using signal data collected from an inertial sensor for balance activity analysis in community-dwelling older adults. MethodsIn total, 59 community-dwelling older adults (19 males and 40 females; mean age = 81.86 years, SD 6.95 years) were recruited in this study. Data were collected using a body-worn inertial measurement unit (including an accelerometer and a gyroscope) at the L4 vertebra of each individual. After data preprocessing and motion detection via a convolutional long short-term memory (LSTM) neural network, a one-class support vector machine (SVM), linear discriminant analysis (LDA), and k-nearest neighborhood (k-NN) were adopted to classify high-risk individuals. ResultsThe framework developed in this study yielded mean accuracies of 87%, 86%, and 89% in detecting sit-to-stand, turning 360°, and stand-to-sit motions, respectively. The balance assessment classification showed accuracies of 90%, 92%, and 86% in classifying abnormal sit-to-stand, turning 360°, and stand-to-sit motions, respectively, using Tinetti Performance Oriented Mobility Assessment-Balance (POMA-B) criteria by the one-class SVM and k-NN. ConclusionsThe sensor-based approach presented in this study provided a time-effective manner with less human efforts to identify and preprocess the inertial signal and thus enabled an efficient balance assessment tool for medical professionals. In the long run, the approach may offer a flexible solution to relieve the community’s burden of continuous health monitoring.

Falls have been recognized as the major cause of accidental death and injury in people aged 65 and above. The timely prediction of fall risks can help identify older adults prone to falls and implement preventive interventions. Recent advancements in wearable sensor-based technologies and big data analysis have spurred the development of accurate, affordable, and easy-to-use approaches to fall risk assessment. The objective of this study was to systematically assess the current state of wearable sensor-based technologies for fall risk assessment among community-dwelling older adults. Twenty-five of 614 identified research articles were included in this review. A comprehensive comparison was conducted to evaluate these approaches from several perspectives. In general, these approaches provide an accurate and effective surrogate for fall risk assessment. The accuracy of fall risk prediction can be influenced by various factors such as sensor location, sensor type, features utilized, and data processing and modeling techniques. Features constructed from the raw signals are essential for predictive model development. However, more investigations are needed to identify distinct, clinically interpretable features and develop a general framework for fall risk assessment based on the integration of sensor technologies and data modeling.

The extent of mixing in the stabilization process and the control of the cement content (C) and water content (w) in the mixture are key to the outcome of the engineering performance of a cement-stabilized subgrade. Intelligent Compaction (IC) quality control has improved quality control and management practices during construction. Intelligent Compaction Measurement Values (ICMVs) selected to evaluate the stiffness properties of cement-stabilized soils do not directly relate to the stiffness properties of the cement-stabilized subgrade and do not consider w and C. Additional tests need to be conducted for calibration of ICMVs. In this study, our solution is the development of a resistivity plate loading test. The resistivity plate loading test features the flexibility in determining the soil stiffness, w, C, and other important factors, such as the time of test effect (hydration) (T) and dry density (ρd). To verify the accuracy of the testing method, laboratory experimental studies were conducted on cemented soils considering ρd, w, C, and T at different factor levels. Multiple response studies based on grey rational analysis (GRA) were conducted. Analysis of the input factors was performed, and their effects on the measured responses were quantified. According to the study, the ρ measured by the device was a powerful indicator of stiffness, ρd, w, C, and T, which showed that the device can be useful equipment for quality control and an advancement in the in situ testing technologies and test equipment. A statistical regression model based on the linear and linear plus interaction terms among the factors is proposed to predict the average responses.

A sedimentary valley has a visible amplification effect on a seismic response, and the current 2D topographies cannot truthfully reflect the twists and turns of a large-scale river valley. Taking a sinusoidal curved valley site as a model, the dynamic finite element analysis method and the introduction of a viscoelastic artificial boundary were developed to study the 3D seismic response of the dimensional topographies in the homogeneous curved valley to vertical incident P, SV, and SH waves. The results showed that the bending sedimentary valley site earthquake presented significant features simultaneously, depending on the number of valley bends, the frequency of the excitations, the shear wave velocity of sedimentary soil, and the depth of the river valley. The surface displacement amplitudes of three-dimensional meandering sedimentary valleys are significantly different from those of sedimentary basins. The amplification area of the meandering valley is related to the angle between the valley axis and wave vibration direction, and the amplification effect is significant when the angle is small. The movement in the main direction showed a center focus, and the secondary y-direction displacement showed both a central focus and an edge effect. When the frequency of the incident wave was close to the natural vibration frequency in a specific direction, the movement in this direction significantly increased because of the resonance effect. The displacement amplitude of the surface was proportional to the depth of the river valley, and the surface displacement was presented in different forms based on the frequency of the excitations. The results provided some guidance for the earthquake resistance of the curved valley site.

Due to the increased surface to volume ratios, topological nanomaterials can enhance contributions from the topological surface states in transport measurements, which is critical for device applications that exploit the topological properties. It is particularly important for topological semimetals in which bulk carriers are unavoidable to make them into nanostructures to reveal the nature of the topological surface states, such as the Fermi arcs or nodal lines. Here, we report the nanostructure synthesis of the recently discovered triple-point topological metal MoP by direct conversion of MoO3 nanostructures and study their transport properties. We observe that the initial size of the MoO3 templates critically determines the crystalline quality of the resulting MoP nanostructures: large MoO3 flakes lead to porous MoP flakes, while narrow MoO3 nanowires lead to MoP nanowires without pores. The size-dependent porosity observed in MoP nanostructures is attributed to the volume change during the conversion reaction and nanoscale confinement effects. For MoO3 nanowires with diameters less than 10 nm, the resulting MoP nanowires are single crystalline. The resistivity values of MoP nanostructures are higher than the reported values of MoP bulk crystals owing to the porous nature. However, despite the high porosity present in MoP flakes, the residual resistance ratio is ∼2 and the temperature-dependent resistivity curves do not show any strong surface or grain-boundary scattering. Demonstration of the facile synthesis of MoP nanostructures provides opportunities for careful investigations of the surface states in transport measurements and exploration of future electronic devices, including nanoscale interconnects.

The catalytic conversion of carbon dioxide into value-added products requires an understanding of the active species present under working conditions. Here, the authors discover copper-containing complexes to reversibly transform during electrocatalysis into methane-producing copper nanoclusters.

The excellent physical and chemical properties of ultra-high temperature ceramics make them suitable for many high-temperature structural components, while their poor toughness and high sintering temperature become key limitations to their application. Laminated toughening has long been considered an effective toughening method to improve the mechanical properties of ceramics. In this study, laminated ZrB2-Mo5SiB2 ceramics with an Mo-Mo5SiB2 interlayer were fabricated by tape casting and hot press sintering at 1900 °C for 2 h. Different layer thickness ratios between the matrix layer and the interlayer were designed to illustrate the toughening mechanism. Both the fracture toughness and flexural strength of the laminated ceramics showed a trend of first increasing and then decreasing with the increase of the layer thickness ratio. High fracture toughness (9.89 ± 0.26 MPa·m1/2) and flexural strength (431.6 ± 15.1 MPa) were obtained when the layer thickness ratio was 13. The improvement in fracture toughness of the laminated ceramics could be attributed to the generation of the residual stress, the deflection and the bifurcation of the cracks. Residual stress that developed in the laminated ceramics was also evaluated.

Abstract Background Vibrio campbellii is widely distributed in the marine environment and is an important pathogen of aquatic organisms such as shrimp, fish, and mollusks. An isolate of V. campbellii carrying the pirAB vp gene, causing acute hepatopancreatic necrosis disease (AHPND), has been reported. There are no previous reports about the complete genome of V. campbellii causing AHPND (VCAHPND). To extend our understanding of the pathogenesis of VCAHPND at the genomic level, the genome of V. campbellii 20130629003S01 isolated from a shrimp with AHPND was sequenced and analysed. Results The complete genome sequence of V. campbellii 20130629003S01 was generated using the PacBio RSII platform with single molecule, real-time sequencing. The 20130629003S01 strain consists of two circular chromosomes (3,621,712 bp in chromosome 1 and 2,245,751 bp in chromosome 2) and four plasmids of 70,066, 204,531, 143,140, and 86,121 bp. The genome contains a total of 5855 protein coding genes, 134 tRNA genes and 37 rRNA genes. The average nucleotide identity value of 20130629003S01 and other reference V. campbellii strains was 97.46%, suggesting that they are closely related. Conclusions The genome sequence of V. campbellii 20130629003S01 and its comparative analysis with other V. campbellii strains that we present here are important for a better understanding of the genomic characteristics of VCAHPND.

Electrochemical reduction of carbon dioxide is a sustainable way of producing carbon-neutral fuels. Here, the authors take a combined nanoscale and molecular approach to develop a highly active and selective cobalt phthalocyanine/carbon nanotube hybrid electrocatalyst for carbon dioxide reduction to carbon monoxide.

Breast cancer frequently metastasizes to bone, where it leads to poor clinical prognosis. Due to the peculiarity of the bone microstructure, the uptake of drugs often happens at non-targeted sites, which produces a similar cytotoxicity in both cancerous and healthy cells. In this study, a rational strategy was implemented to take advantage of a combination of both an octapeptide with eight repeating sequences of aspartate (Asp8) and folate to create a more selective and efficient drug delivery system to target cancer cells in bone tissue. Asp8 and folate were conjugated to the distal ends of DSPE-PEG2000-maleimide and DSPE-PEG2000-amine to create DSPE-PEG2000-Asp8 and DSPE-PEG2000-Folate, respectively, which were incorporated onto the surface of a doxorubicin (DOX)-loaded liposomes (A/F-LS). Asp8, similar to the hydroxyapatite-binding domains of osteopontin and osteocalcin, has been used as bone-targeting moieties for exclusive delivery of drugs to bone. The folate moiety binds selectively to folate receptor-positive tumors. The dual-targeting effects were evaluated by both in vitro and in vivo experiments. By taking advantages of dual-targeting drug delivery, the dual-modified liposomal drug system could relieve pain and improve survival. Inspired by its enhanced therapeutic efficacy and low toxicity, DOX-loaded A/F-LS could serve as an effective drug system for targeted therapy of bone metastases.

Acute hepatopancreatic necrosis disease (AHPND) has caused sharp declines in aquaculture industries of whiteleg shrimp Penaeus vannamei in Asia and the Americas since 2010. Vibrio parahaemolyticus, V. campbellii, V. owensii, and V. punensis have been proved to cause AHPND. However, the mechanisms underlying the burgeoning number of Vibrio species that cause AHPND is not known. All of AHPND-causing Vibrio bacteria (VAHPND) harbor a highly homologous plasmid (designated as pVA1-type) carrying pirABvp toxin genes. In this study, we demonstrate conclusively that the pVA1-type plasmid can be transferred from VAHPND to non-pathogenic bacteria. We constructed a pVPGX1-Cmr plasmid (a pVA1-type plasmid) by adding a chloramphenicol resistance gene as a marker in a donor AHPND-causing V. parahaemolyticus 20130629002S01 (Vp2S01). Horizontal transfer of this plasmid was successfully performed from the AHPND-Vp2S01 to a non-pathogenic strain of V. campbellii at the transfer efficiency of 2.6×10−8 transconjugant/recipient, and DNase I treatment did not eliminate the transfer. The recipient V. campbellii acquired the pVA1-type plasmid and was shown to produce pirABvp RNA and proteins. Challenge studies using the transconjugant caused 100% mortality in exposed groups of P. vannamei. The challenged shrimp, infected with the transconjugant bacteria, showed typical gross signs and histological lesions of AHPND. These results demonstrated the conjugative transfer of an AHPND pVA1-type plasmid. It provides timely information for explaining the increased species of AHPND-causing Vibrio bacteria and will be useful in the development of management strategies leading to the prevention and control of AHPND.

Earth represents an ecological building material that is thought to reduce the carbon footprint at a point in its life cycle. However, it is very important to eliminate the undesirable properties of soil in an environmentally friendly way. Cement-stabilized rammed earth, as a building material, has gradually gained popularity due to its higher and faster strength gain, durability, and availability with a low percentage of cement. This paper covers a detailed study of hollow compressed cement-stabilized earth-block masonry prisms to establish the strength properties of hollow compressed cement-stabilized earth-block masonry. The test results for masonry prisms constructed with hollow compressed cement-stabilized blocks with two different strength grades and two earth mortars with different strengths are discussed.

In order to improve the shear behavior of hollow concrete block masonry, precast concrete anti-shear blocks were proposed to enhance the shear strength of hollow concrete block masonry. Four groups of hollow concrete block masonry triplets with precast concrete anti-shear blocks were tested under shear loading, and their behaviors were compared with a control group. The results show that as the height of precast concrete anti-shear blocks increases, the shear strength of the masonry increases. The maximum shear strength of masonry triplets with precast concrete anti-shear blocks was 234.48 percent higher than that of the control specimens. The shear strength of masonry triplets was mainly determined by the failure of hollow concrete block unit. The majority of specimens exhibited double shear failures; however, these failures showed characteristics of ductile failure to a certain extent. Based on the experimental results, a equation for calculating the shear strength of masonry with precast concrete anti-shear blocks was proposed.

Estimating blood pressure via combination analysis with electrocardiogram and photoplethysmography signals has attracted growing interest in continuous monitoring patients’ health conditions. However, most wearable/portal monitoring devices generally acquire only one kind of physiological signals due to the consideration of energy cost, device weight and size, etc. In this study, a novel adaptive weight learning-based multitask deep learning framework based on single lead electrocardiogram signals is proposed for continuous blood pressure estimation. Specifically, the proposed method utilizes a 2-layer bidirectional long short-term memory network as the sharing layer, followed by three identical architectures of 2-layer fully connected networks for task-specific blood pressure estimation. To learn the importance of task-specific losses automatically, an adaptive weight learning scheme based on the trend of validation loss is proposed. Extensive experiment results on Physionet Multiparameter Intelligent Monitoring in Intensive Care (MIMIC) II waveform database demonstrate that the proposed method using electrocardiogram signals obtains estimating performance of 0.12±10.83 mmHg, 0.13±5.90 mmHg, and 0.08±6.47 mmHg for systolic blood pressure, diastolic blood pressure, and mean arterial pressure, respectively. It can meet the requirements of the British Hypertension Society standard and US Association of Advancement of Medical Instrumentation standard with a considerable margin. Combined with a wearable/portal electrocardiogram device, the proposed model can be deployed to a healthcare system to provide a long-term continuous blood pressure monitoring service, which would help to reduce the incidence of malignant complications to hypertension.

Rational design and synthesis are important for the development of materials for energy applications. Here, the authors sequentially synthesize pyrite structured cobalt phosphosulfide nanoparticles on carbon nanotubes, probing the role of phosphorous substitution on catalyst stability and durability.

Emerging Microbes & Infections (2017) 6, e2; doi:10.1038/emi.2016.131; published online 4 January 2017

Background/Aims. Hepatic ischemia-reperfusion (I/R) injury is a serious concern during hepatic vascular occlusion. The objectives of this study were to assess effects of three techniques for hepatic vascular occlusion on I/R injury and to explore the underlying mechanisms. Methods. Liver cirrhotic rats had undertaken Pringle maneuver (PR), hemihepatic vascular occlusion (HH), or hepatic blood inflow occlusion without hemihepatic artery control (WH). Levels of tumor necrosis factor alpha (TNF-α), nuclear factor kappa B (NF-κB), toll-like receptor 4 (TLR4), TIR-domain-containing adapter-inducing interferon-β (TRIF), and hemeoxygenase 1 (HMOX1) were assayed. Results. The histopathologic analysis displayed that liver harm was more prominent in the PR group, but similar in the HH and WH groups. The HH and WH groups responded to hepatic I/R inflammation similarly but better than the PR group. Mechanical studies suggested that TNF-α/NF-κB signaling and TLR4/TRIF transduction pathways were associated with the differential effects. In addition, the HH and WH groups had significantly higher levels of hepatic HMOX1 (P

Rammed earth (RE) constructions are widespread in underdeveloped rural areas in developing countries. However, these RE constructions are often susceptible to earthquake damage due to their poor seismic performance. Precast concrete tie columns and ring beam (tie bars) were proposed to improve the seismic behavior of RE constructions. Four RE walls, including a traditional RE wall and three RE walls with precast concrete tie columns and ring beam (tie bars), were tested under reversed cyclic loading, and the seismic behavior of these tested specimens was evaluated in terms of failure pattern, energy dissipation, displacement ductility, and stiffness degradation. The results showed that a significant increase of the load-bearing and deformation capacity could be achieved with the application of precast concrete tie columns in combination with RE. The load-bearing capacity and deformation capacity of traditional RE wall were increased by an average of 113% and 417%, respectively. These test results could provide reference to the design and construction of the environmental-friendly structures in rural areas.

Rammed earth is widely utilized in both developed and developing countries due to its low embodied energy and good natural moisture buffering of indoor environments. However, its application in seismic active regions was limited owing to its intrinsically low resistance to dynamic actions. This paper presents the test results of four cement-stabilized rammed earth walls with confining tie-column elements under cyclic loading, aiming at assessing the cyclic behavior of proposed rammed earth walls with confining tie-column elements. The test results revealed that the proposed confining tie-column elements could significantly improve the cyclic behavior of cement-stabilized rammed earth wall, exhibiting good strength and ductility.

Acute hepatopancreatic necrosis disease (AHPND) is a severe shrimp disease originally shown to be caused by virulent strains of Vibrio parahaemolyticus (VPAHPND). Rare cases of AHPND caused by Vibrio species other than V. parahaemolyticus were reported. We compared an AHPND-causing V. campbellii (VCAHPND) and a VPAHPND isolate from the same AHPND-affected pond. Both strains are positive for the virulence genes pirABvp. Immersion challenge test with Litopenaeus vannamei indicated the two strains possessed similar pathogenicity. Complete genome comparison showed that the pirABvp-bearing plasmids in the two strains were highly homologous, and they both shared high homologies with plasmid pVA1, the reported pirABvp-bearing plasmid. Conjugation and DNA-uptake genes were found on the pVA1-type plasmids and the host chromosomes, respectively, which may facilitate the dissemination of pirABvp. Novel variations likely driven by ISVal1 in the genetic contexts of the pirABvp genes were found in the two strains. Moreover, the VCAHPND isolate additionally contains multiple antibiotic resistance genes, which may bring difficulties to control its future outbreak. The dissemination of the pirABvp in non-parahaemolyticus Vibrio also rises the concern of missing detection in industrial settings since the isolation method currently used mainly targeting V. parahaemolyticus. This study provides timely information for better understanding of the causes of AHPND and molecular epidemiology of pirABvp and also appeals for precautions to encounter the dissemination of the hazardous genes.

Because of its mild reaction condition, relatively high denitrification efficiency and ability of combined removal of various pollutants, the flue gas denitrification technology based on oxidation theory has become a new and feasible method for flue gas denitrification. The technology has been applied extensively and studied in depth. This paper reviews the influencing factors, reaction mechanism, reaction products and subsequent absorption reaction of the oxidation of NO in flue gas with gas phase and liquid phase oxidants at high and low temperatures. On this basis, the shortcoming of the technology and the key research directions for the future are analyzed and discussed, laying the basis for industrial applications of the denitrification technology based on oxidation theory.