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This research aimed to study whether Enteromorpha polysaccharide-zinc (EP-Zn) can act as an alternative to antibiotics in weaned piglet feeds. Two hundred and twenty-four weaned piglets from 14 pens were randomly assigned into 1 of 2 groups according to their body weight and litter size (7 pens/group). The piglets in the antibiotics group were fed with olaquindox at 400 mg/kg and enduracidin at 800 mg/kg basal diet, and piglets in the EP-Zn group were fed with EP-Zn at 800 mg/kg basal diet. One piglet per pen was selected to collect samples after 14 d of feeding. Results showed that EP-Zn supplementation significantly increased the plasma anti-oxidants level compared with the antibiotics group. However, a nonsignificant difference was observed in growth performance between treatment groups. Additionally, the intestinal tight junction (TJ) protein expression and the histopathologic evaluation data showed that EP-Zn contributed to improving intestinal development. Further, piglets in the EP-Zn group had a lower level of intestinal inflammation-related cytokines including IL-6 (P

Products and services empowered by artificial intelligence (AI) are becoming widespread in today’s marketplace. However, consumers have mixed feelings about AI technologies due to the numerous ethical challenges associated the development and deployment of AI. Drawing upon prior research on the moral significance of technology and the emerging literature on AI, we delineate three key dimensions of AI-enabled products (i.e., multi-functionality, interactivity, and AI intelligence stage) that have relevance for ethical implications and adopt a socio-technical approach to provide a multi-layered ethical analysis of AI products at the product-, consumer-, and society-levels. Some key ethical issues identified in the paper include AI biases, ethical design, consumer privacy, cybersecurity, individual autonomy and wellbeing, and unemployment. Companies need to engage in corporate social responsibility (CSR) to shape the future of ethical AI; drawing upon stakeholder theory and institutional theory, we develop a conceptual framework on AI-related CSR, highlighting the product-, company-, and institutional environment-specific factors that influence firms’ socially responsible actions in the domain of AI and discussing the subsequent outcomes for firm, consumers, and the society. We include a section on future research agenda for AI ethics and firm CSR in this important domain.

In the present study, we aimed to evaluate the effects of maternal yeast-based nucleotide (YN) supplementation on the intestinal immune response and barrier function in neonatal pigs, as well as the diarrhoea rate and growth performance in suckling piglets. Sixty-four late-gestation sows were assigned to the following groups: the CON (fed a basal diet) and YN groups (fed a basal diet with 4 g YN/kg diet). The experiment started on d 85 of gestation and ended on d 20 of lactation. Diarrhoea rate and average daily gain of the piglets were recorded, and samples of blood and intestines from neonatal piglets were collected before they consumed colostrum during farrowing. Compared with the CON group, maternal YN supplementation increased the weaning weight of litter and decreased the diarrhoea rate (P

Objective Based on the technical acceptance model, expectation confirmation model, and perceived risk theory, this study aims to analyze the factors and their effects on shared nurse users' continuance intention in the process of e-health consumption. Methods This research established a measurement tool that fits the topic of this study and a model of shared nurse continuance. From January to May 2020, 373 valid samples from elderly individuals living in urban areas of Jiangxi Province, China, were collected by convenience sampling in order to analyze through empirical research their continuance intentions of selecting shared nurses. The theoretical models and research hypotheses were verified by structural equation modeling with AMOS 25 software. Results The measurement model indicated that the theoretical constructs have adequate reliability and validity, while the structured equation model is illustrated as having a high model fit for empirical data. The hypothesis test results showed that expectation confirmation positively affects perceived ease of use; both of them have positive effects on perceived usefulness and satisfaction. Perceived usefulness and satisfaction play an intermediary role in expectation confirmation and continuance intention. Perceived ease of use and perceived usefulness positively affect continuance intention. Perceived risk negatively affects perceived usefulness and continuance intention. Conclusion This study expanded the application of the technology acceptance model, expectation confirmation model, and perceived risk model in e-health by investigating the factors that influence elderly users' continued intention to use shared nurses. Based on these empirical findings, we derived implications for the design and operation of the shared nurse platform, and suggestions on relevant management departments and incentive structures for using e-health. The results of this study provide important implications for further research and practice of mobile health care.

Objectives Intensive care unit (ICU) patients are at high risk of medical device related pressure injury (MDRPI). This study aims to ascertain the MDRPI prevalence in ICU patients and analyse the risk factors of MDRPI. Background The occurrence of MDRPI not only increases hospitalisation time with pain and economic burden, but also causes medical disputes. A better understanding of this condition will increase knowledge and facilitate the ability to recognise and prevent MDRPI for clinical nursing staff. However, there are few multicentre studies of MDRPI prevalence in ICU patients in China. Design A cross-sectional study design was employed. Methods Data from 694 patients in 66 adult ICU at 30 hospitals in China were included between October 2018 and March 2019. The stage of each MDRPI was determined according to the definitions of National Pressure Ulcer Advisory Panel. The study methods were followed by the STORBE guidelines. Results The overall prevalence rate of MDRPI was 13.1% (91/694), with 98 anatomic locations in total. The most common stages of MDRPI were stage 1 (54.1%, 53/98), stage 2 (15.3%, 15/98) and mucosal membrane pressure injury (15.3%, 15/98). MDRPI mainly occurred in the finger (32.7%, 32/98), followed by nose (18.4%, 18/98). The prevalence rate of MDRPI caused by CPAP or BiPAP masks (25%) was highest. Lower Braden scores and having skin oedema were risk factors for MDRPI in adult ICU patients. Conclusion The prevalence of MDRPI in this study was still high. Nurses should take these related factors into consideration when taking care of ICU patients, and appropriate prevention measures should be adopted to decrease the prevalence of MDRPI. Relevance to clinical practice The study can help to improve the PI prevention efforts in ICU patients specific to medical device related PI.

Background: Hyperthyroidism is a condition in which the thyroid gland is overreactive and produces excess amounts of thyroid hormone. Tripterygium glycosides, traditional Chinese medicine has been widely used in the treatment of rheumatoid arthritis, nephrotic syndrome, hyperthyroidism and other diseases due to its anti-inflammatory and immunosuppressive effects. Evidence-based research is becoming popular especially with the application of Chinese traditional medicine. This paper systematically reviews and evaluates existing clinical data on the efficacy and safety of Tripterygium glycosides in the treatment of hyperthyroidism. Materials and methods: PubMed, Cochrane library and EMBase, Chinese biomedical literature database (CBM), Chinese journal full-text database (CNKI), Wan fang digital periodical full-text database and China Science and Technology Journal Database (VIP) were searched based on the defined inclusion and exclusion criteria. Data extraction, research quality assessment and meta-analysis were conducted with RevMan5.3 software. Trial sequential analysis (TSA) was used to evaluate information size and treatment benefits. Results: Seventeen randomized controlled clinical trials with 1536 participants were included in the systematic review. In the meta-analysis, there were two subgroups: Tripterygium glycosides combined with thiamazole and prednisone group; Tripterygium glycosides combined with thiamazole group. The study results revealed that the degree of exophthalmos, FT3, FT4, BGP, and AKP decreased while TSH, SOD, GSH-PX increased after the addition of Tripterygium glycosides. This study results suggested that Tripterygium glycosides combined with western medicine are an effective therapy for hyperthyroidism. Conclusion: This study indicates that Tripterygium glycosides enhances the effect of thiamazole and prednisone in the treatment of hyperthyroidism and without increasing the risk of adverse events.

Objective. To investigate the effects of emodin on nitric oxide (NO) secretion induced by high glucose in human umbilical vein endothelial cells (HUVECs) through the p-Akt signaling pathway. Methods. Sensitivity of cells to emodin was determined by MTT assay to establish the experimental concentrations; then, HUVECs were treated with high-dose (33.3 mmol/L) glucose (HG), HG + emodin (HG + E), HG + the Akt phosphorylation inhibitor LY294002 (HG + LY), or HG + E + LY. The p-Akt (Ser 473) expression in 48 h was analyzed using Western blot. NO effect on the secretion of HUVECs was analyzed using nitrate reductase assay. Results. The sensitive emodin concentration for HUVECs growth was 10 mol/L (P<0.05). Compared with the HG group, NO secretion was significantly higher in the HG + E group (P<0.05), whereas it was lowest in the HG + LY group (P<0.05). Compared with the HG + LY group, NO secretion was increased in the HG + E + LY group (P<0.05). The p-Akt protein expression was decreased in the HG + LY group when compared to the HG group (P<0.05), while it significantly increased in the HG + E group (P<0.05). Compared with HG + LY group, p-Akt protein expression was significantly higher in the HG + E + LY group (P<0.05). Conclusion. Emodin could improve the NO secretion of HUVECs by high glucose through the p-Akt signaling pathway.

BACKGROUND Recent research related to phase-feeding programs for pig nutrition do not always account for the variation among individuals, and feeds are usually formulated to optimize the performance of the whole pig population. This study aimed at measuring the effects of a daily 3-meal pattern with different dietary protein contents on pig growth performance, carcass and muscle quality traits. RESULTS The results showed that compared with the 3C treatment, ADG of pigs in the HCL treatment increased by 14.75% (P < 0.05) during period 1. The carcass weight (P = 0.006) and slaughter weight (P = 0.021) in the HCL group increased when compared with those in the 3C and LCH treatments. Moreover, the LCH feeding sequences contributed to reduce the drip loss in longissimus dorsi (LD) muscle (P < 0.05) when compared with the 3C treatment. The HCL or LCH feeding sequence contributed to increase the meat quality when compared with those receiving the 3C treatment. CONCLUSION Collectively, our results indicate that feeding high protein meal in the morning and a gradual reduction of the protein content in meals over the day may improve muscle quality characteristics, maximize performance, and reduce the pig feed cost.

BACKGROUND Nucleotides play an important role in the regulation of cellular energy and protein homeostasis, which facilitate the repair, recovery and repletion of tissue function. This study tested the effects of maternal uridine (UR) supplementation during late pregnancy and lactation of sows on the immune function of the small intestine in neonatal and suckling piglets. RESULTS Results showed that compared to the control group, maternal dietary UR supplementation significantly decreased incidence of diarrhea in suckling piglets (P

Background Studies on the hypertensive effect of long-term exposure to air pollution are mixed, and sparse evidence exists regarding its effects on homocysteine (Hcy), another crucial risk factor for cardiovascular disease (CVD). Methods We collected data from 23,256 participants aged 18–74 years at baseline (years 2017–2018) from a community-based cohort in China. A linear combination of concentrations from monitoring stations at the participants’ home and work addresses, weighted by the time, was used to estimate two-year exposures to particulate matter with fine particles≤2.5 μm (PM2.5), aerodynamic diameter≤10 μm (PM10), nitrogen dioxide (NO2) and sulfur dioxide (SO2). Generalized linear regressions and logistic regressions were conducted to examine the associations between air pollution and systolic blood pressure (SBP), diastolic blood pressure (DBP), Hcy, hypertension and co-occurrence of hypertension and hyperhomocysteinemia (HHcy). Results The results showed that each interquartile range (IQR) increase in PM2.5 (16.1 μg /m3), PM10 (19.3 μg /m3) and SO2 (3.9 μg /m3) was significantly associated with SBP (changes: 0.64–1.86 mmHg), DBP (changes: 0.35–0.70 mmHg) and Hcy (changes: 0.77–1.04 μ mol/L) in the fully adjusted model. These air pollutants were also statistically associated with the prevalence of co-occurrence of hypertension and HHcy (ORs: 1.22–1.32), which were stronger than associations with the prevalence of hypertension (ORs: 1.09–1.19). The hypertensive effects of exposure to PM2.5, PM10 and SO2 were more pronounced among elder participants, obese participants, those with established CVD or a high 10-year CVD risk and those with a family history of hypertension. However, interaction analyses of Hcy showed different patterns. Additionally, moderate level of physical activity and active travel mode benefited individuals in resisting the health impacts of air pollution on both blood pressure (BP) and Hcy. Conclusions Our study supports a positive relationship between air pollution and BP and Hcy among adults in Beijing, and close attention to vulnerable populations and healthy lifestyles could effectively benefit further cardiovascular health.

Background Both multimorbidity and activities of daily living (ADL) disability and instrument activities of daily living (IADL) disability are common among elderly individuals. ADL/IADL disability may reduce individuals’ capacities for independent living and quality of life. This study aimed to examine the association between multimorbidity and ADL/IADL disability. Methods A multi-stage cluster sample of 2058 residents aged 80 or older was investigated in Shanghai, China. Multimorbidity was defined as the simultaneous presence of two or more chronic diseases with ten common chronic conditions under consideration. Subjects who responded that they “need partial or full assistance” to any ADL/IADL items were defined as having ADL/IADL disability. We examined the association of multimorbidity with ADL/IADL disability, adjusted for socio-demographic characteristics by using logistic regression. Results Of respondents, 23.23 % had ADL disability, 37.90 % had IADL disability, and 49.17 % had multimorbidity. After adjusted socio-demographic characteristics, a graded association was showed between ADL disability and the quantity of chronic conditions: odds ratio (OR) for 1 condition, 1.53(95 % confidence interval [CI], 1.04-2.24); OR for 2 conditions, 2.06(95 % CI, 1.43-2.96); OR for 3 conditions, 3.23(95 % CI, 2.14-4.86); OR for 4 or more conditions, 5.61(95 % CI, 3.26-9.66). Similar associations were also observed between the quantity of chronic conditions and IADL disability. Conclusions The quantity of chronic conditions had relatively strong association with both ADL and IADL disability. Initiating prevention of additional chronic conditions and interventions on clusters of diseases may decrease the potential risk of ADL/IADL disability. Additionally, more attention should been given to the older low-income women living with relatives/non-relatives with multimorbidity.

Dementia has been increasingly paid attention by policymakers in China. However, the majority of the public has an indistinct concept of dementia and its diagnostic criteria. Therefore, many abnormal characteristics and actions of older people are labeled as having dementia while diagnosed without dementia. We examined a multi-stage cluster sample of 11,223 participants aged 60 years and above who have been clinically confirmed by general practitioners as not having dementia in 2013, and 7,861 participants were willing to participate the following study and were followed-up in 2014. To assess the differences of status of older people who were mistakenly labeled as having dementia or not, we asked main caregivers 'Do you think this older person suffers from dementia?', and found out that 244 participants had been mistakenly labeled as having dementia since 2013. Related effects were measured using international generic scales as well, and the results showed that participants with better physical status deteriorated more rapidly if they were mistakenly labeled as having dementia. Additionally, the mental health of these 244 participants also deteriorated more quickly. Older adults that were not labeled as having dementia were more willing to participate in social activities relative to their labeled counterparts. In conclusion, being mistakenly labeled as having dementia without a medical diagnosis impaired older adults' physical functioning and mental health. Moreover, the reduction of social activities of labeled older people leads to separation and social exclusion.

To investigate effects of Ca level varying with feeding time daily in sows during late pregnancy on placental lipid metabolism and transport in pigs, sixty pregnant sows were assigned to 3 groups: the CON group was fed low-Ca diet with 11.25 g CaCO3 at 0600 h and 1500 h, H-L group was fed low-Ca diet with 22.5 g CaCO3 at 0600 h and low-Ca diet at 1500 h, and L-H group was fed low-Ca diet at 0600 h and low-Ca diet with 22.5 g CaCO3 at 1500 h, respectively. Serum from sows and umbilical cord and placenta were collected during delivery. Results showed that, compared with the CON group, H-L feeding significantly increased maternal serum total triglyceride (TG) and umbilical serum high-density lipoprotein (HDL) (P 0.05). The results showed that long chain fatty acid (FA) contents in placenta were significantly increased in H-L and L-H groups (P 0.05). Experiments on genes involved in glycolipid metabolism showed that H-L or L-H feeding inhibited mRNA expression of GLUT3, GLUT4, FAS, FABP1, FABPpm, FAT/CD36, while activated the mRNA expression of FASD1, FASD2 and SCD in placenta (P 0.05). In addition, experiments on genes involved in biological clock showed that L-H feeding sequence activated the mRNA expression of per1 and clock, while H-L and L-H feeding sequence inhibited mRNA expression of per2 in placenta (P 0.05). It is concluded that maternal supplementation with Ca varying with feeding time daily during late pregnancy affects placental lipid metabolism and transport in pigs by regulating the mRNA expression related to lipid metabolism and the circadian clock.

N-carbamylglutamate (NCG) is a metabolically stable analog of N-acetylglutamate that activates carbamyl phosphate synthase-1, a key arginine synthesis enzyme in enterocytes. It is a promising feed additive in swine in China. In this study, we assessed the acute and sub-acute toxicity of NCG in Sprague-Dawley (SD) rats. All rats survived until they were killed at a scheduled time point. No adverse effects or mortality was observed following acute oral administration of 5000 mg/kg NCG to SD rats. No biologically significant or test substance-related differences were observed in body weights, feed consumption, clinical signs, a functional observational battery, organ weights, histopathology, ophthalmology, hematology, coagulation, and clinical chemistry parameters in any of the treatment groups in sub-acute doses of NCG at target concentrations corresponding to 500, 2000, and 3000 mg/kg/day for 28 days neither. In addition, no evidence of mutagenicity or genotoxicity was found, either in vitro in bacterial reverse mutation assay or in vivo in mice bone marrow micronucleus assay and sperm shape abnormality assay. On the basis of our findings, we conclude that NCG is a non-toxic substance with no genotoxicity.

Disability, which has been proved to be associated with suicide and suicidal ideation, has received little attention in relation to suicidal attempts among the elderly. The aim of this study was to explore the influence of disability on attempted suicide within this demographic.A multi-stage cluster sample of 8399 residents aged 60 or more was investigated from 15 communities in Shanghai, China. Disability was measured using the Lawton instrumental activities of daily living (IADL) scale.The prevalence of attempted suicide in the elderly was 0.75%. Specific IADL disabilities, including shopping (OR = 3.01, 95% CI = 1.56-5.81), preparing meals (OR = 4.12, 95% CI = 2.12-8.00), housekeeping (OR = 2.48, 95% CI = 1.01-6.06), doing laundry (OR = 2.82, 95% CI = 1.09-7.35), using transport (OR = 3.10, 95% CI = 1.36-6.99) and medical care (OR = 4.41, 95% CI = 2.10-9.17), were significantly and independently associated with attempted suicide in the elderly. The presence of at least one such disability was associated with an almost threefold increase in the attempted suicide rate, and the presence of five or more IADL disabilities was associated with an approximate fivefold increase in the attempted suicide rate.Specific IADL disabilities, such as preparing meals or dealing with medical care, may be significant predictive factors for risk of suicidal attempts among the elderly. Therefore, elderly people with certain disabilities should be considered for suicide prevention interventions and should be supported in IADL as much as possible.

Ethnopharmacological relevance Persimmon (Diospyros kaki L.) leaves, known as Shi Ye (in Chinese), have a long history as a Chinese traditional medicine for the treatment of ischemia stroke, angina, internal hemorrhage, hypertension, atherosclerosis and some infectious diseases, etc. Additionally, persimmon leaves could be used as healthy products, cosmetics and so on, which have become increasingly popular in Asia, such as Japan, Korea and China etc. Aim of the review The present paper reviewed the ethnopharmacology, phytochemistry, analytical methods, biological activities and toxicology of persimmon leaves in order to assess the ethnopharmacological use and to explore therapeutic potentials and future opportunities for research. Materials and methods Information on persimmon leaves were gathered via the Internet (using Google Scholar, Baidu Scholar, Elsevier, ACS, Pudmed, Web of Science, CNKI and EMBASE) and libraries. Additionally, information was also obtained from some local books. Results Persimmon leaves have played an important role in Chinese system of medicines. The main compositions of persimmon leaves were flavonoids, terpenoids, etc. Scientific studies on extracts and formulations revealed a wide range of pharmacological activities, such as, antioxidative, hypolipidemic, antidiabetic, antibacterial, hemostasis activities and effects on cardiovascular system. Based on the pharmacological activities, persimmon leaves were widely used in clinic including treatment of cardiovascular disease, hemostasis, antibacterial, anti-inflammatory and beauty treatment. Conclusions Persimmon leaves probably have therapeutic potential in the prevention and treatment for cerebral arteriosclerosis, diabetes, hypertension. It showed significant neuroprotection against ischemia/reperfusion injury in vivo and in vitro. Moreover, it can regulate immune function and inhibite inflammation. Further investigations are needed to explore individual bioactive compounds responsible for these pharmacological effects in vitro and in vivo and the mode of actions. Further safety assessments and clinical trials should be performed before it can be integrated into medicinal practices.

For the disadvantage of contact method in range finding, such as physical effects, high requirements of envi- ronment, operating errors and so on, a different method is proposed as required--digital image processing for range find- ing. This non-contact method could be finished after the collection and handling of laser spots by USB camera, the extrac- tion of feature information of image, and the building the Quantitative relationship between feature and measured dis- placement. It is available and practical by experiment without the complex marking procession of camera system.

The need for formal care among the elderly population has been increasing due to their greater longevity and the evolution of family structure. We examined the determinants of the use and expenses of formal care among in-home elderly adults in Shanghai. A two-part model based on the data from the Shanghai Long-Term Care Needs Assessment Questionnaire was applied. A total of 8428 participants responded in 2014 and 7100 were followed up in 2015. The determinants of the probability of using formal care were analyzed in the first part of the model and the determinants of formal care expenses were analyzed in the second part. Demographic indicators, living arrangements, physical health status, and care type in 2014 were selected as independent variables. We found that individuals of older age; women; those with higher Activities of Daily Living (ADL) scores; those without spouse; those with higher income; those suffering from stroke, dementia, lower limb fracture, or advanced tumor; and those with previous experience of formal and informal care were more likely to receive formal care in 2015. Furthermore, age, income and formal care fee in 2014 were significant predictors of formal care expenses in 2015. Taken together, the results showed that formal care provision in Shanghai was not determined by ADL scores, but was instead more related to income. This implied an inappropriate distribution of formal care among elderly population in Shanghai. Additionally, it appeared difficult for the elderly to quit the formal care once they begun to use it. These results highlighted the importance of assessing the need for formal care, and suggested that the government offer guidance on formal care use for the elderly.

We analyzed the effects of acute and chronic oral administration of monosodium l-glutamate (MSG) on serum iron (Fe) levels and total iron-binding capacity (TIBC) in piglets. In the first experiment, 12 piglets were randomly assigned to two groups: one fed a standard diet (SD) and the other fed an SD containing MSG (10 g/kg). On day 30, serum, liver, kidney, and spleen samples were collected to determine the Fe levels. In the second experiment, six pigs were surgically fitted with a catheter in the jugular artery and vein to investigate the dynamic changes of serum Fe and TIBC. Blood samples were taken from each pig via the catheter every 30 min, for a period of 4 h. The results show that MSG increases Fe levels in the spleen (P < 0.05) and in serum obtained from the jugular artery (P < 0.01). In addition, TIBC in serum obtained from the jugular artery demonstrated an increasing trend in pigs fed the MSG diet; however, this trend was not observed in the jugular vein. In conclusion, MSG increases Fe retention by enhancing TIBC in serum.

Purpose – In Brazil, bacalhau dishes represent strong cultural, religious and traditional values. The purpose of this paper is to propose a theoretical perspective integrating theories on social identity, role‐based identity, and cultural capital to explore multi‐phase bacalhau prosumption. The aim is to understand how consumers maintain their social identity and role‐based identity in this process.Design/methodology/approach – Data gathering is based on focus‐group discussions. A total of 13 focus‐group discussions were developed with 104 consumers from five different cities in Brazil. Discussions of all five phases of bacalhau prosumption reveal how people maintain and reinforce their social identity and role‐based identity.Findings – It was found that consumers achieve their social identity through comparison with both in‐group and out‐group members in what they prosume and how they prosume. Consumers also try to maintain their role‐based identity through continuously comparing their actual behaviour w...

Background Since 2009, the Hemorrhagic Fever with Renal Syndrome (HFRS) Targeted Expanded Program on Immunization (EPI) has been carried out in the 16-60 age population in Yichun City of Jiangxi Province. However, the annual reported incidences of HFRS in Yichun City Increased significantly from 2009 to 2013. Material/methods The information on HFRS reported cases were obtained from the China Information System for Disease Control and Prevention (CISDCP), and demographic data was collected from the Basic Information System. Hantavirus-specific antigen and antibody of rodent specimens were tested by enzyme-linked immunosorbent assay (ELISA) or immune fluorescent assay. Results The annual HFRS incidences among all age subgroups presented growth tendencies in non-EPI targeted regions and EPI targeted regions, except for the EPI target population. The annual incidences of EPI target population were stable at around 10 per 100,000 population from 2008 to 2013. HFRS annual incidence was significantly related to rat virus index among all age subgroups in non-EPI targeted regions and >60 age subgroup in EPI targeted regions. Conclusions HFRS vaccine implement has had a notable effect in HFRS prevention and control.

PurposeThe purpose of this study is to develop new knowledge on corporate branding from a corporate social responsibility (CSR) perspective. The paper is particularly concerned with how environmental awareness can function as a specific CSR activity, and how environmental awareness can impact corporate brand. The paper also investigates the role of personal leadership, both within the company and externally, in developing an environmentally responsible company.Design/methodology/approachThe paper uses an explorative research method and studies one company within the Norwegian offshore oil and gas industry. The analysis is based on qualitative interview data.FindingsThe study shows how the founder's role as “cultural architect” has a positive impact on how external constituents assess the image of the company, especially with regard to the company's innovations and its awareness of environmental issues, in two ways: first, it shapes, coordinates, energizes and leverages employees' attitudes and behaviors in relation to environmental issues; second, it thereby enforces a positive external reputation for the company, especially as a “green innovator”.Research limitations/implicationsThe findings are induced from a case study of one company in a particular industry. The results may therefore not be applicable or generalizable to other companies or other industries.Practical implicationsThe study suggests that companies may gain reputational advantages and differentiation in integrating corporate social responsibility and environmental awareness as a core element of their business strategy.Originality/valueThe paper contributes to the corporate branding literature by exploring the role of CSR, and in particular concern for environmental issues and personal leadership, in building corporate reputation and developing a strong corporate brand.

An iron-deficient rat model was established and used to determine the effects of different iron sources on iron metabolism and absorption. Iron-deficient rats were assigned to one of three treatment groups, and their diet was supplemented with deionized water (control), Fe-CGly, or FeSO4 for 8 days via intragastric administration. Blood samples were obtained for analysis of iron-related properties, and the small intestine and liver were removed for quantitative reverse transcription PCR of genes related to iron metabolism. The serum total iron-binding capacity (TIBC) levels of rats in Fe-CGly and FeSO4 supplementation groups was lower (P

To solve the problem of energy waste caused by fixed luminance of common lamps, a new fluorescent lamp system is designed which is based on STC SCM. In this system, Light gathering is used to collect and analyzes the light luminance outside by STC; the circuit composed by the PWM is controlled the fluorescent light intensity, which can automatic adjust light luminance according to different environment. It reduces greatly the power of fluorescent lamp and energy waste, and could be applied widely.

Two-dimensional (2-D) face recognition (FR) is of interest in many verification (1:1 matching) and identification (1:N matching) applications because of its nonintrusive nature and because digital cameras are becoming ubiquitous. However, the performance of 2-D FR systems can be degraded by natural factors such as expressions, illuminations, pose, and aging. Several FR algorithms have been proposed to deal with the resulting appearance variability. However, most of these methods employ features derived in the image or the space domain whereas there are benefits to working in the spatial frequency domain (i.e., the 2-D Fourier transforms of the images). These benefits include shift-invariance, graceful degradation, and closed-form solutions. We discuss the use of spatial frequency domain methods (also known as correlation filters or correlation pattern recognition) for FR and illustrate the advantages. However, correlation filters can be computationally demanding due to the need for computing 2-D Fourier transforms and may not match well for large-scale FR problems such as in the Face Recognition Grand Challenge (FRGC) phase-II experiments that require the computation of millions of similarity metrics. We will discuss a new method [called the class-dependence feature analysis (CFA)] that reduces the computational complexity of correlation pattern recognition and show the results of applying CFA to the FRGC phase-II data

The general practitioner (GP) system has been widely applied around the world and experimented with in Shanghai, China. To analyze some of the influencing factors on patient-GP contracts, we developed a questionnaire and conducted site investigations in 2011 and 2012 to 1200 patients by random sampling from 6 pilot community health service (CHS) centers in Pudong, Shanghai. The t test, χ2 test, factor analysis, and logistic regression analysis were used to analyze the data. The factors influencing patients’ contract behavior were age (OR = 1.03; 95%CI = 1.02-1.04), education level (OR = 0.83; 95% CI = 0.75-0.93), social interaction of social capital (OR = 1.34; 95% CI = 1.15-1.56), acceptance of first contact in community (OR = 3.25; 95% CI = 2.07-5.12), the year of investigation (OR = 2.58; 95% CI = 1.92-3.47), and the exposure to publicity (OR = 1.60; 95% CI = 1.39-1.85). Elderly patients formed a focus group to sign contracts with GPs. To increase trust in GPs by patients, it is recommended to improve the level of CHSs, strengthen publicity, and cultivate social capital among patients.

This is the accepted version of the following article: Strategizing for environmentally sustainable praxis : the case of "green operations", Beta. Scandinavian Journal of Business Research 2014, 28(2):154-172, which has been published in final form at https://www.idunn.no/beta/2014/02/strategizing_for_environmentally_sustainable_praxis_-_the_c. © Universitetsforlaget The paper investigates how a strategic idea to operate offshore service vessels in an environmentally sustainable way was transformed into practical realities. The research case was a campaign to reduce the consumption of diesel-fuel, in the paper referred to as the case of “green operations”. Our findings were seven key practices for realizing environmentally sustainable praxis. The practices were the creation and promotion of a strategic idea, concretizing how the idea could be transformed into practical realities, the construction of a goal-oriented and innovative contractual arrangement, encouraging the enactment of fuel-saving operations whenever possible, acknowledging middle managers on board the offshore service vessels as key strategy makers, and organizing the campaign as a competition among the vessels in carrying-out the most fuel-saving “green operations”. Finally, but not in the least, corporate managers following-up, supporting, and facilitating strategic activities, were identified as crucial.

The results of some studies involving animal models of obesity induced by monosodium glutamate are not conclusive

Kernel methods have been applied to many linear feature analysis classifiers to generate nonlinear classifiers for improved classification performance. The recently proposed kernel class-dependence feature analysis (KCFA) method extends linear correlation filter technology to kernel correlation filters, greatly improving the classification performance. In this paper, we compare the KCFA method with the kernel discriminant analysis {KDA) method and show that the KCFA and the KDA result in the same representation subspace and the relationship between them is similar to the relationship between the orthogonal and the simplex signal representations in digital communications. We present face recognition results to illustrate that the KCFA method is preferable to the KDA method.

Reliable person recognition is important for secure access and commercial applications requiring human identification. Face recognition (FR) is an important technology being developed for human identification. Algorithms and systems for large population face recognition (LPFR) are of significant interest in applications such as watch lists and video surveillance. In this paper, we present correlation filter-based feature analysis methods that effectively exploit available generic training data to represent a large number of subjects and thus improve the performance for LPFR. We first introduce a general framework - class-dependence feature analysis (CFA), which uses correlation filters to provide a discriminant feature representation for LPFR. We then introduce two variants of the correlation filter-based CFA methods: 1) the kernel correlation filter CFA (KCFA) that generates nonlinear decision boundaries and significantly improves the recognition performance without greatly increasing the computational load, and 2) the binary coding CFA that uses binary coding to reduce the number of correlation filters and applies error control coding (ECC) to improve the recognition performance. These two variants offer ways to tradeoff between the computational complexity and the recognition accuracy of the CFA methods. We test our proposed algorithms on the face recognition grand challenge (FRGC) database and show that the correlation filter-based CFA approach improves the recognition rate and reduces the computational load over the conventional correlation filters.

A new frequency domain face recognition method using wavelet decomposition and quaternion correlation filters is proposed. The wavelet decomposition of the face image leads to a wavelet subband representation, which contains four subband images corresponding to four orthogonal channels. These four subbands can be encoded into a 2D quaternion number array. The quaternion correlation filter method is developed to perform pattern recognition jointly on multichannel 2D signals. The proposed method has been shown to achieve significant improvement in face recognition results compared to the traditional advanced correlation filter method for handling illumination variations of face images. We experimented with the CMU PIE database consisting of 65 people with 21 illumination variations per person, showing that our method can achieve close to 100% recognition accuracy using just a single training image of a person under neutral frontal lighting and testing on all other unseen harsh illumination conditions.

In face recognition, the goal is to assign a class label for a test image of a subject from N classes in the database, when binary classifiers are used, the commonly used method is the one-per-class (OPC) i.e., one classifier per subject. A drawback of the OPC method is that when the number of classes is large, it takes very long time to make a classification decision. In place of the computationally-demanding OPC method, we propose a new feature extraction method "face class code" (FCC) based on binary classifiers. For example, correlation filters and support vector machines can be used to generate feature vectors to deal with large number of classes. The FCC method encodes each class label into a binary string, and we design classifiers to discriminate '1' or '0' for each bit in the sequence, to determine the class label. Thus, we will need as few as [log/sub 2/(N)] binary classifiers to achieve an N-class recognition problem. This binary coding framework also opens the whole world of error control codes (ECC), which can be used to improve the recognition performance. The proposed method is verified through experiments on the PIE database and the AR database.

Recently, Direct Linear Discriminant Analysis (D-LDA) and Gram-Schmidt LDA methods have been proposed for face recognition. By also utilizing some of the null-space of the within-class scatter matrix, they exhibit better performance compared to Fisherfaces and Eigenfaces. However, these linear subspace methods may not discriminate faces well due to large nonlinear distortions in the face images. Redundant class dependence feature analysis (CFA) method exhibits superior performance compared to other methods by representing nonlinear features well. We show that with a proper choice of kernel parameters used with the proposed Kernel Correlation Filters within the CFA framework, the overall face recognition performance is significantly improved. We present results of this proposed approach on a large scale database from the Face Recognition Grand Challenge (FRGC) which contains over 36,000 images.

In this paper we investigate how to perform face recognition on the hardest experiment (Exp4) in Face Recognition Grand Challenge(FRGC) phase-II data which deals with subjects captured under uncontrolled conditions such as harsh overhead illumination, some pose variations and facial expressions in both indoor and outdoor environments. Other variations include the presence and absence of eye-glasses. The database consists of a generic dataset of 12,776 images for training a generic face subspace, a target set of 16,028 images and a query set of 8,014 images are given for matching. We propose to use our novel face recognition algorithm using Kernel Correlation Feature Analysis for dimensionality reduction (222 features) coupled with Support Vector Machine discriminative training in the Target KCFA feature set for providing a similarity distance measure of the probe to each target subject. We show that this algorithm configuration yields the best verification rate at 0.1% FAR (87.5%) compared to PCA+SVM, GSLDA+SVM, SVM+SVM, KDA+SVM. Thus we explore with our proposed algorithm which facial regions provide the best discrimination ability, we analyze performing partial face recognition using the eye-region, nose region and mouth region. We empirically find that the eye-region is the most discriminative feature of the faces in FRGC data and yields a verification rate closest to the holistic face recognition of 83.5% @ 0.1% FAR compared to 87.5%. We use Support Vector Machines for fusing these two to boost the performance to ~90@0.1 % FAR on the first large-scale face database such as the FRGC dataset.

Many feature space methods have been investigated for appearance-based face recognition. In this paper we compare a new feature space face recognition method - the class-dependence feature analysis (CFA) with three other popular methods, namely, the principal component analysis (PCA), the linear discriminant analysis (LDA) and the independent component analysis (ICA), for appearance-based 2-D face recognition. The numerical results on the face recognition grand challenge (FRGC) show that the CFA outperforms the other three method

The Face Recognition Grand Challenge (FRGC) dataset is one of the most challenging datasets in the face recognition community, in this dataset we focus on the hardest experiment under the harsh un-controlled conditions. In this paper we compare how other popular face recognition algorithms like Direct Linear Discriminant Analysis (D-LDA) and Gram-Schmidt LDA methods compare to traditional eigenfaces, and fisherfaces. However, we also show that all these linear subspace methods can not discriminate faces well due to large nonlinear distortions in the face images. Thus we present our proposed Class dependence Feature Analysis (CFA) method which we demonstrate to produce superior performance compared to other methods by representing nonlinear features well. We perform this by extending the traditional CFA framework to use Kernel Methods and propose a proper choice of kernel parameters which improves the overall face recognition performance is significantly over the competing face recognition algorithms. We present results of this proposed approach on a large scale database from the Face Recognition Grand Challenge (FRGC)v2 which contains over 36,000 images focusing on Experiment 4 which poses the harshest scenario containing images captured under un-controlled indoor and outdoor conditions yielding significant illumination variations.

In this paper we propose a new method called redundant class-dependence feature analysis (CFA) based on the advanced correlation filters to perform robust face recognition on the Face Recognition Grand Challenge (FRGC) data set. The FRGC contains a large corpus of data and a set of challenge problems. The data is divided into training and validation partitions, with the standard still-image training partition consisting of 12,800 images, and the validation partition consisting of 16,028 controlled still images, 8,014 uncontrolled stills, and 4,007 3D scans. We have tested the proposed CFA method and compared it with the PCA and LDA methods in a recognition scenario on the FRGC2.0 data. The preliminary results show that the CFA outperforms the other two compared methods in our experiments. We also show the improved performance of the CFA method on the FRGC experiments #1 and #4.

Human face recognition is currently a very active research area with focus on ways to perform robust biometric identification. Many face recognition algorithms have been proposed, among the different approaches, frequency domain methods, like advanced correlation filters have been shown to exhibit better tolerance to illumination variations than traditional methods. In this paper, we propose a new frequency domain face recognition method which combines the Gabor transforms and a quaternion correlation filter for face recognition when the illumination conditions are changed. The Gabor transform provides optimally localized spatial and frequency domain representation of the original face images, and the quaternion correlation filters can jointly process multi-channel subbands for more robust face recognition. The numerical experiments show that the proposed method outperforms the previously compared advanced correlation filter methods.

Face image recognition has been an active research topic for many years, and many algorithms have been proposed for the grayscale face images. However, only a few methods are devoted to color face images, even though most cameras produce color images. Color can be important for face recognition. Among the proposed color face recognition methods, most treat the three color channels separately and apply some grayscale face recognition methods to each of the channels and combine the results. In this paper we propose the quaternion correlation filter techniques for color face recognition by processing all color channels jointly. Quaternion numbers are the generalization of the complex numbers and can be considered as a number with a real part and three orthogonal imaginary parts. A color image (e.g., in RGB) may be represented using quaternion by encoding the three color components to the imaginary parts of the quaternion number. The quaternion correlation filter is extended from the standard correlation filter based on the recently developed concepts of quaternion Fourier transform (QFT), quaternion convolution (QCV), and quaternion correlation (QC). Face recognition is performed by cross-correlating (QC) an input face image with a designed filter. Numerical results show that quaternion correlation filters can improve the recognition performance over conventional face recognition methods.

In this paper we explore performing robust face verification using Advanced Correlation Filters on Bijective-Mapping preprocessed face images. We show that using the proposed Bijective-Mapping preprocessing method we can increase verification performance (at 0.1% FAR) significantly in our experiments using the Face Recognition Grand Challenge (FRGC) database collected by the University of Notre Dame consisting of 152 subjects. This recognition experiment is challenging as the results reported on these experiments utilize only a single gallery image from each subject during the training phase and the probe images are captured in different time-lapsed sessions which vary mostly in pose and facial expression.

Face image is an attractive biometric for person verification and identification because face images can be obtained non-intrusively, even without the knowledge of the subject in some cases. But in the case that the subject is non-cooperative (in the sense of providing a predefined view for testing), the still-to-still face verification method may have difficulty in matching face images from two different view angles. In this paper we propose a still-to-video face verification method based on the optimal tradeoff synthetic discriminant function (OTSDF) filter technology for the scenario where the video sequence of a subject is available for testing. The system consists of face detection and tracking component, frame level face matching component and the evidence accumulation component. We also investigate the part-based correlation method.© (2004) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

In this paper we propose to use the technology of multiple correlation filters to address the issues involved in still-reference-to-video-sequence face verification. In particular, we assume that the gallery consists of one or a few digital images of a person's face as reference and the probe set consists of video sequences as test data. The test data consists of a sequence of face images of a naturally moving person, captured from one or more cameras. An automatic face recognition system involves face/head tracking and cropping, correlation filter based face matching, and combining the evidence from multiple frames of the face images.

3D target recognition is of significant interest because representing the object in 3D space couuld essentially provide a solution to pose variation and self-occlusion problems that are big challenges in 2D pattern recognition. Correlation filers have been used in a variety of 2D pattern matching applications and many correlation filter designs have been developed to handle problems such as rotations. Correlation filters also offer other benefits such as shift-invariance, graceful degradation and closed-form solutions. The 3D extension of correlation filter is a natural extension to handle 3D pattern recognition problem. In this paper, we propose a 3D correlation filter design method based on cylindrical circular harmonic function (CCHF) and use LADAR imagery to illustrate the good performance of CCHF filters.

Biometric verification refers to the process of matching an input biometric to stored biometric information. In particular, biometric verification refers to matching the live biometric input from an individual to the stored biometric template of that individual. Examples of biometrics include face images, fingerprint images, iris images, retinal scans, etc. Thus, image processing techniques prove useful in biometric recognition. In particular, composite correlation filters have proven to be effective. In this paper, we will discuss the application of composite correlation filters to biometric verification.

Biometric recognition refers to the process of matching an input biometric to stored biometric information. In particular, biometric verification refers to matching the live biometric input from an individual to the stored biometric template about that individual. Examples of biometrics include face images, fingerprint images, iris images, retinal scans, etc. Thus, image processing techniques prove useful in the biometric recognition. We discuss spatial frequency domain image processing methods useful for biometric recognition.

Iris patterns are believed to be an important class of biometrics suitable for subject verification and identification applications. Earlier methods proposed for iris recognition were based on generating iris codes from features generated by applying Gabor wavelet processing to iris images. Another approach to image recognition is the use of correlation filters. Correlation filter methods differ from many image-based recognition approaches in that two-dimensional Fourier transforms of the images are used in this approach. In correlation filter methods, normal variations in an authentic iris image can be accommodated by designing a frequency-domain array (called a correlation filter) that captures the consistent part of iris images while deemphasizing the varying parts. Correlation filters also offer other benefits such as shift-invariance, graceful degradation and closed-form solutions. In this paper, we discuss the basics of correlation filters and show how they can be used for iris verification.

Verifying a user’s identity is critical in access control applications. Most current authentication systems are password based making them susceptible to problems such as forgetting the password and passwords being stolen. One way to overcome these problems is to employ biometric recognition which typically involves two stages; a training stage and a recognition stage. During the training, samples of a subject’s biometric signatures are used to create a biometric template. During recognition, the subject’s live biometric is matched against a database of stored templates to identify the subject. In a highly controlled setting where the training and recognition environments are very similar, biometric matching can be relatively easy leading to good recognition performance. However, the reality is that the biometrics from the same person may differ considerably between training and recognition. For example, a face image might appear very differently because the illumination levels between an indoor enrollment session and an outdoor verification session may be extremely different.