Prioritization of intellectual capital indicators in knowledge-based industries: Evidence from pharmaceutical industry

During the last decade, intellectual capital (IC) and intangible assets have been widely considered as critical tool to deliver successful business in an intensive-knowledge environment. Accordingly, the main goal of this paper is therefore to develop and prioritize the most important indicators of intellectual capital in knowledge-based industries. Based on an extensive literature review, a valid and reliable questionnaire was designed. In order to data gathering, it was sent out to participants from both academic and university who qualified well in pharmaceutical practice. In order to exact prioritization of indicators, fuzzy TOPSIS technique as a MADM model was used. The fuzzy TOPSIS results revealed participants remark high concerns especially about knowledge and skills of managers and employees regarding to human capital, high concerns particularly about positive climate, ratio of investment in R&D and numbers of R&D projects according to structural capital, while considering the relational capital, more attention was paid to customers and strategic cooperation such as alliances and licensing.     

Older Women and Lower Self-Rated Health

Several studies have found that older women report lower self-rated health than men. However, it is not clear why older women are more likely to report poor self-rated health than older men. Data for this study came from a national cross-sectional survey, Mental Health and Quality of Life of Older Malaysians (MHQoLOM). Included in the survey were 2980 respondents consisting of Malaysians aged 60 years and over, with both men (n = 1428) and women (n = 1552) represented. Results of t-tests showed older men expressed significantly higher levels of self-rated health and self-esteem than women (p < .01). Separate multivariate regression by gender revealed that age, life-threatening problems, and self-esteem were highly significant predictors of self-rated health among older men and women and explained 18.4% of variance in self-rated health for men and 18.2% for women. In the last step we examined the main effects of gender on self-rated health using General Linear Models (GLM) Univariate by adjusting for age, life-threatening problems, and self-esteem. Results showed an insignificant difference in self-rated health between older men and women (F _(1,2715) = 2.26, P = 0.13) only after adjusting for self-esteem. It can be concluded that self-esteem affects responses to self-rated health of older men and women.     

Linear-constant log-map,a fast accurate algorithm for map decoding

This paper proposes a new approximation to be used for the correction function in the turbo decoding algorithm, called Linear-Constant-log Map. Max-log Map, Linear-log Map and Constant-log Map are the well known simplified versions of Jacobi-log Map (Maximum a Posteriori) algorithm already in use but they cannot meet a proper performance in term of output BER and clock consumption of the CPU decoding encoded bits. The proposed algorithm first breaks the correction function domain of the Jacobi logarithm to three subsections by determining the border points between these sections and then uses a linear function and two constant values as an approximation of this function. Using an AWGN channel model, simulation results show that the new algorithm is almost more than six times faster than Jacobi-log Map algorithm with a Bit Error Rate (BER) very close to it.     

Network Organizations: Symmetric Cooperation or Multivalent Negotiation?

The network model of organization plays a central role in recent sociological accounts of the information economy. This model is also often presented in organization and information and communication technologies (ICT) literature with an air of enthusiasm that underscores its advantages—flexibility, cooperative culture, innovativeness, and knowledge and technology intensity. Such themes are usually based on a “networking logic” that assumes the trustful cooperation of large and small production firms in a rapidly changing economic environment. We believe that both the logic and the themes based upon it are too narrow to be able to explain the complex dimensions of interorganizational networking. Using Enron as a case study, our goal in this article is to enrich the logic just described and to develop an extended model of the network enterprise. We argue that this is only possible by extending the unit of analysis beyond the production firm, to include, among others, subsidiaries, banks, investors, auditors, and government agencies. The proposed extended model allows the broadening of many of the aforementioned themes, making it possible to arrive at a realistic picture of the complexities of the network enterprise. The managerial advantages of the model are also discussed.     

Child maltreatment among school children in the Kurdistan Province, Iran

OBJECTIVE: This study examines the determinants of three types of child maltreatment: physical maltreatment, mental maltreatment, and child neglect among school children in the Kurdistan Province of Iran. The analysis examines the impact of socioeconomic, familial, demographic, and household dynamic factors on the three child maltreatment outcomes, and compares the differential impact of these factors across the three types of child maltreatment. A greater understanding of the factors associated with child maltreatment has the potential to inform public health interventions aimed at reducing specific forms of maltreatment and at identifying at risk populations. METHODS: Data were collected from 1,370 school students, age 11-18. Separate logistic models are fitted for six binary outcomes examining self-reported experiences of physical maltreatment in the home or school, mental maltreatment in the home or school, and child neglect in the home or school. RESULTS: Male children were more likely to report experiencing any kind of child maltreatment than girls. Residency in a rural area, poor parental relationships and the use of addictive substances by household members were associated with increased odds of reporting child maltreatment. Poor school performance was associated with the reporting of experiencing maltreatment at school. CONCLUSION: Each of the forms of child maltreatment is highly correlated with socioeconomic, demographic, and living condition factors. The results point to the strong influence that familial factors have in shaping a child's likelihood of reporting maltreatment. Characteristics of the mother were associated with maltreatment, but not characteristics of the father. The results highlight a number of mechanisms through which public health interventions may seek to reduce the prevalence of child maltreatment in Kurdistan; different approaches are needed to reduce child maltreatment in the home and school environments.     

Outside the library: Early career researchers and use of alternative information sources in pandemic times

Presents findings from a study into the attitudes and practices of pandemic-era early career researchers (ECRs) in regard to obtaining access to the formally published scholarly literature, which focused on alternative providers, notably ResearchGate and Sci-Hub. The study is a part of the Harbingers project that has been exploring the work lives and scholarly communication practices of ECRs in pre-pandemic times and during the pandemic, and utilizes data from two rounds of interviews with around 170 ECRs from the sciences and social sciences in eight countries. Findings show that alternative providers, as represented by ResearchGate and Sci-Hub, have become established and appear to be gaining ground. However, there are considerable country- and discipline-associated differences. ECRs' country-specific level of usage of the alternative providers is partly traceable to the adequacy of library provisions, although there are other factors at play in shaping ECRs' attitudes and practices, most notably convenience and time saving, as well as the fact that these platforms have become embedded in the scholarly dashboard. There is a dearth of evidence of the impact of the pandemic on ECRs' ways of obtaining scholarly papers.     

Using Active Learning Methods to Strategically Select Essays for Automated Scoring

Research on Automated Essay Scoring has become increasing important because it serves as a method for evaluating students’ written responses at scale. Scalable methods for scoring written responses are needed as students migrate to online learning environments resulting in the need to evaluate large numbers of written-response assessments. The purpose of this study is to describe and evaluate three active learning methods that can be used to minimize the number of essays that must be scored by human raters while still providing the data needed to train a modern Automated Essay Scoring system. The three active learning methods are the uncertainty-based, the topological-based, and the hybrid method. These three methods were used to select essays included in the Automated Student Assessment Prize competition that were then classified using a scoring model that was trained with the bidirectional encoder representations from a transformer language model. All three active learning methods produced strong results, with the topological-based method producing the most efficient classification. Growth rate accuracy was also evaluated. The active learning methods produced different levels of efficiency under different sample size allocations but, overall, all three methods were highly efficient and produced classifications that were similar to one another.     

Variations in cadmium and nitrate co-accumulation among water spinach genotypes and implications for screening safe genotypes for human consumption

Vegetables are important constituents of the human diet. Heavy metals and nitrate are among the major contaminants of vegetables. Consumption of vegetables and fruits with accumulated heavy metals and nitrate has the potential to damage different body organs leading to unwanted effects. Breeding vegetables with low heavy metal and nitrate contaminants is a cost-effective approach. We investigated 38 water spinach genotypes for low Cd and nitrate co-accumulation. Four genotypes, i.e. JXDY, GZQL, XGDB, and B888, were found to have low co-accumulation of Cd (<0.71 mg/kg dry weight) and nitrate (<3100 mg/kg fresh weight) in the edible parts when grown in soils with moderate contamination of both Cd (1.10 mg/kg) and nitrate (235.2 mg/kg). These genotypes should be appropriate with minimized risk to humans who consume them. The Cd levels in the edible parts of water spinach were positively correlated with the concentration of Pb or Zn, but Cd, Pb, or Zn was negatively correlated with P concentration. These results indicate that these three heavy metals may be absorbed into the plant in similar proportions or in combination, minimizing the influx to aerial parts. Increasing P fertilizer application rates appears to prevent heavy metal and nitrate translocation to shoot tissues and the edible parts of water spinach on co-contaminated soils.     

The Big Deal — ten years on

This paper describes the highlights of an exploratory deep log analysis of journal usage on OhioLINK, conducted as part of the MaxData project. OhioLINK, the original ‘Big Deal’, provides a single digital platform of nearly 6,000 full‐text journals for more than 600,000 people in Ohio and the investigation aimed to assess it after approximately 10 years. The data was generated from an SPSS analysis of the raw (unprocessed) server logs for June 2004 to December 2004. Approximately 1,215,000 items were viewed on campus in October 2004 and 1,894,000 items viewed off campus between June and December 2004. There are a number of usage analyses including: demand and activity; number and name of journal; date of publication; subject/discipline of journal and method of searching/navigating.