Mississippi Valley State University

The importance of justice perceptions in fostering positive job attitudes and value–creating behaviors in organizations is well established in the literature. Despite this, only a handful of studies have addressed justice in family firms, and none have presented a theoretical model illustrating how nonfamily employees’ justice perceptions may be influenced by family involvement in family firms. Here, we suggest that the level of family influence impacts the justice perceptions of nonfamily employees primarily through its effect on the human resource (HR) practices within family firms. Specifically, we propose that low levels of family influence tend to have little impact on the fairness of HR practices, that moderate levels of family influence tend to have positive effects on the fairness of HR practices, and that high levels of family influence tend to have negative effects on the fairness of HR decision processes and outcomes. Accordingly, we present and provide a conceptual support for a model that outlines the proposed relationships among family influence, family firms’ HR practices, and the justice perceptions of nonfamily employees.

A cyber physical system (CPS) is a complex system that integrates computation, communication, and physical processes. Digital manufacturing is a method of using computers and related technologies to control an entire production process. Industry 4.0 can make manufacturing more efficient, flexible, and sustainable through communication and intelligence; therefore, it can increase the competitiveness. Key technologies such as the Internet of Things, cloud computing, machine-to-machine (M2M) communications, 3D printing, and Big Data have great impacts on Industry 4.0. Big Data analytics is very important for cyber-physical systems (CPSs), digital manufacturing, and Industry 4.0. This paper introduces technology progresses in CPS, digital manufacturing, and Industry 4.0. Some challenges and future research topics in these areas are also presented.

Heterogeneity is one of major features of big data and heterogeneous data result in problems in data integration and Big Data analytics. This paper introduces data processing methods for heterogeneous data and Big Data analytics, Big Data tools, some traditional data mining (DM) and machine learning (ML) methods. Deep learning and its potential in Big Data analytics are analysed. The benefits of the confluences among Big Data analytics, deep learning, high performance computing (HPC), and heterogeneous computing are presented. Challenges of dealing with heterogeneous data and Big Data analytics are also discussed.

This paper examines the narratives of 11 Black women in Computer Science (CS) to explore and understand their intersectional experiences (academic, professional, familial, etc.) in the field of Computing. We video-recorded the participants as they engaged in semi-structured interviews to explore and understand their experiences as Black women in Computing. Four coders engaged in content analysis on the video-recordings as well as transcripts of the video data in two rounds. Overall, our analysis revealed that the women in our study experienced discrimination, expectations from others that are too high or too low, isolation, sexism, and racism; yet they still choose to stay in the discipline. Remaining true to their personal and professional goals, having effective mentors, and inspiration from their fathers all contributed to their successful pathways and strategies of resistance.

In this paper, we describe a recent trend in the introductory computer science curriculum which advocates conceptualizing computation primarily as coordinated concurrent activities [8], [9], [10]. Consistent with this philosophy is the focus on the event-driven model of computation [7]. While one can utilize these approaches with any thread and/or event supporting object-oriented language (e.g. Java) in a desktop programming environment, they become particularly worthwhile when used in conjunction with physical robots. This paper argues the case for the benefits of this approach and provides sample exercises that illustrate the use of this pedagogy using Lego Mindstorms RCX bricks programmed in Java for use in introductory programming.

Abstract Simple and portable methods for assessing the physiological state of channel catfish Ictalurus punctatus would be valuable tools in field situations where problems with blood storage and transportation occur. This study compared the use of handheld lactate and glucose meters with established laboratory methods in stressed (fatigued) and unstressed (control) channel catfish fingerlings. The results obtained from the Accutrend (Roche Diagnostics Corp.) lactate meter and the Accu-Chek Advantage (Roche Diagnostics) glucose meter were consistently lower (P < 0.05) than those obtained with the laboratory reference method. However, significant differences (P < 0.0001) were found between the control and fatigued fish for both lactate and glucose, regardless of the method of analysis. Both handheld meters were found to be reliable and suitable for use in field or laboratory situations where relative measurements are acceptable. The costs associated with using the handheld meters were higher than those associated with accepted laboratory methods; however, the initial capital investment was lower for the handheld meters. Ease of use, portability, and rapidity of sample analysis make the handheld meters attractive alternatives to traditional laboratory methods.

Abstract The world population is expected to grow from 7.8 billion at present to 9.7 billion by 2050 and 10.9 billion by the end of the century. The growth is especially expected in urban areas of the countries with a low, medium, and high human development index (HDI) in Africa and Asia. Especially because of the on‐going increase in farm sizes in the rural areas of the countries with a medium, high, and very high HDI, a reduction in population in these areas may be expected. In the countries with a low HDI, this reduction is expected to start at a later stage. Globally, prospects of increasing the gross cultivated area are limited by the decrease of suitable sites for land reclamation or large‐scale irrigation and drainage projects. Therefore, increase in food production will largely rely on a more accurate application of the crop water requirements and modernization or improved operation and maintenance of irrigation and drainage systems. These issues have to be analysed in light of the expected impacts of climate change and environmental sustainability. This paper presents the relevant impacts of these issues on the need to increase food production and for sustainable irrigation and drainage system development and management. In light of this, the goals and objectives of the International Commission on Irrigation and Drainage (ICID) Strategic Action Plan are presented.

Big Data can unify all patient related data to get a 360-degree view of the patient to analyze and predict outcomes. It can improve clinical practices, new drug development and health care financing process. It offers a lot of benefits such as early disease detection, fraud detection and better healthcare quality and efficiency. This paper introduces the Big Data concept and characteristics, health care data and some major issues of Big Data. These issues include Big Data benefits, its applications and opportunities in medical areas and health care. Methods and technology progress about Big Data are presented in this study. Big Data challenges in medical applications and health care are also discussed.

Machine learning is an artificial intelligence method of discovering knowledge for making intelligent decisions. Big Data has great impacts on scientific discoveries and value creation. This paper introduces methods in machine learning, main technologies in Big Data, and some applications of machine learning in Big Data. Challenges of machine learning applications in Big Data are discussed. Some new methods and technology progress of machine learning in Big Data are also presented.

Certain applications have recently appeared in industry where a traditional bar code printed on a label will not survive because the item to be tracked has to be exposed to harsh environments. Laser direct-part marking is a manufacturing process used to create permanent marks on a substrate that could help to alleviate this problem. In this research, a 532 nm Nd:YAG laser was utilized to produce Data Matrix symbols onto carbon steel substrates. The quality of the laser marked Data Matrix symbol was then evaluated according to the ISO/IEC 16022 bar code technology specification for Data Matrix. Several experiments were conducted to explore the effects that different parameters have on the quality of the laser direct-part marked symbols. Parameters such as type of carbon steel, percent of laser tool path overlap, profile speed, average power, and frequency were found to have significant effects on the quality of the Data Matrix symbols produced with the laser. The analysis of the results indicated that contrast and print growth were the critical ISO/IEC 16022 standard performance measures that limited the laser marked Data Matrix symbols from achieving a higher final grade.

An HLA-DRA-DRB1*0101-restricted T-cell epitope in the factor VIII (FVIII) C2 domain occurred in a mild haemophilia A patient with missense substitution FVIII-A2201P. His T cells responded to synthetic peptides FVIII(2186-2205) and FVIII(2194-2213) (J Thromb Haemost 2007; 5: 2399). T cells from family members with genotype FVIII-A2201P were analysed to determine if FVIII-specific T cells occur in individuals with a haemophilic mutation but no clinically significant inhibitor response. Fluorescent MHC class II tetramers corresponding to subjects'HLA-DRB1 types were loaded with 20-mer peptides and utilized to label antigen-specific CD4+ T cells. T-cell responses to peptides spanning the FVIII-C2 sequence were evaluated. T cells recognizing specific peptides were cloned, and antigen specificity was verified by proliferation assays. Plasma and/or purified IgG samples were tested for FVIII inhibitory activity. CD4+ T cells and T-cell clones from two brothers who shared the DRB1*0101 allele responded to FVIII(2194-2213). A haemophilic cousin's HLA-DRA-DRB1*1104-restricted response to FVIII(2202-2221) was detected only when CD4+CD25+ cells were depleted. A great uncle and two obligate carriers had no detectable FVIII-C2-specific T cells. Concentrated IgG from the brother without a clinical inhibitor response showed a low-titre FVIII inhibitor. FVIII-specific T cells and inhibitory IgG were found in a previously infused, haemophilic subject who had a sub-clinical FVIII inhibitor. CD4+CD25+ depleted T cells from a non-infused haemophilic cousin recognized an overlapping FVIII epitope, indicating a latent HLA-DRA-DRB1*1104-restricted T-cell response to FVIII. Specific T-cell responses to FVIII can occur without clinically significant inhibitors.

This article analyzes a unique panel data set to assess the effect of militarism on per capita carbon dioxide emissions. We extend previous research examining the effects of military expenditures on carbon emissions by including in our analyses over 30 years of additional data. In addition, we compare our preliminary results to those obtained from other estimation procedures. Specifically, we report and visually illustrate the results of 54 cross-sectional models (one for each year) and 36 unique panel regression models on both balanced and unbalanced panels. We assess how this relationship has changed over time by testing for interactions between military spending and time and by systematically re-analyzing our data across 180 panel regressions with varying time frames. A strong and enduring association between military spending and per capita carbon emissions is indicated in cross-sectional comparisons. Our panel analyses reveal a much weaker and varying relationship that has become stronger in recent decades. Moreover, we find that the effect of military spending on per capita carbon emissions is moderated by countries’ level of economic development, with military spending of more wealthy countries having relatively larger net effects on carbon emissions. We partially confirm previous findings on the temporal stability of the environmental impacts of militarism. Our analyses show, however, that this temporal stability has emerged relatively recently, and that the relationship between military expenditures and carbon emissions is weaker prior to the 1990s.

"Castellated beam" is a name commonly used for a type of expanded beam. It is made by expanding a standard rolled shape in a manner which creates a regular pattern of holes in the web. The name is derived from this pattern of web holes, because castellated means "built like a castle, having battlements, or regular holes in the walls, like a castle". Fig. 1 illustrates a castellated beam. It is made by separating a standard rolled shape into two halves by cutting the web in a regular alternating pattern as shown. The halves are rejoined by welding, after offsetting one portion so that the high points of the web pattern come into contact. Some design conditions make it advantageous to increase the depth even more. This is done by adding web plates between high points of the tee sections. These added plates are called "increment plates".

An interdisciplinary relationship, defined as 2 or more disciplines collaborating to accomplish a common goal, is considered a general and broad form of collaboration.[1][1] For example, an automobile company and a computer software company can work in partnership to offer specific automotive

Correctional staff are a necessary and valuable resource for correctional institutions, in both Western and Nonwestern nations; however, studies of correctional staff in Nonwestern nations, particularly those in Africa, are lacking. Improving the job satisfaction and organizational commitment of these staff are imperative, as both of these job attitudes have been linked to many salient beneficial outcomes. Most of the existing empirical research on correctional staff organizational justice explores only the effects of procedural and distributive justice and ignores interpersonal justice. Additionally, there has been little research on how procedural, distributive, and interpersonal justice affect correctional staff in Nonwestern correctional organizations. The current study explored the effects of all three forms of organizational justice on the job satisfaction and organizational commitment of staff at a medium security prison in southeast Nigeria. Based on Ordinary Least Squares (OLS) regression, all three forms of justice had significant positive effects on commitment. Procedural and interpersonal justice had positive effects on job satisfaction, while distributive justice had nonsignificant effects. Correctional administrators need to be aware the importance of procedural, distributive, and interpersonal justice and attempt to improve perceptions of these organizational justice variables.

Big Data helps facilitate information visibility and process automation in design and manufacturing engineering. It also helps analyze trends through analytics and predict inventory, manufacturing output and equipment lifespan and cycles, etc. This paper introduces Big Data, its characteristics and a number of issues of Big Data in design and manufacturing engineering. These issues include design and manufacturing data, Big Data benefits and impacts and its applications and opportunities. Methods, technologies and some technology progress around Big Data are presented in this study. General challenges of Big Data and Big Data challenges in design and manufacturing engineering are also discussed.

Big Data helps improve visibility throughout the supply chain, provides an integrated view of operational performance and customer interaction and gives businesses real-time insights that help make critical decisions. Big Data also has a potential to yield new management principles. This paper introduces the Big Data concept, its characteristics and some major issues of Big Data in supply chain management and business administration. These issues include supply chain and business data, Big Data benefits and its applications and opportunities. Methods and technology progress about Big Data are presented in this study. General challenges of Big Data and Big Data challenges in supply chain management and business administration are also discussed.

Additive manufacturing (AM) can produce parts with complex geometric shapes and reduce material use and weight. However, there are limited materials available for AM processes; the speed of production is slower compared with traditional manufacturing processes. Big Data analytics helps analyze AM processes and facilitate AM in impacting supply chains. This paper introduces advantages, applications, and technology progress of AM. Cybersecurity in AM and barriers to broad adoption of AM are discussed. Big data in AM and Big Data analytics for AM are also presented.

Harmful algal blooms (HABs), harmful microorganisms (pathogens) and toxic metals represent three major agents of water quality deterioration. Water quality of three northern lakes (Sardis, Enid, and Grenada) and a central lake (Ross Barnett Reservoir) of Mississippi, USA were examined in this study. While all these lakes are heavily used for recreational purposes, the Ross Barnett Reservoir serves additionally as the primary water supply for the City of Jackson, the capital city of Mississippi. The main goal of this study was to comprehensively assess the water quality of these lakes employing field and satellite data, and evaluate the potential human and aquatic health impacts. A time-series of true color images derived from satellite data indicated that algal blooms have been a recurring phenomenon in these lakes. Cyanobacteria, the algal group that predominantly occur in freshwater and form toxic blooms, were always present in these lakes and were most abundant on many occasions. The most toxic cyanotoxin, microcystin-LR, was found in all lakes, and its concentrations exceeded federal drinking water guidelines for children under six years of age many times. Potential bioaccumulation and biomagnification of microcystin-LR may pose serious risk to the aquatic ecosystem and human health including adults. Nutrient measurements indicated that all four lakes were eutrophic. Among bacterial populations, total coliforms and enterococci exceeded guideline values on several occasions. Arsenic, cadmium, chromium, and lead were found in the water of all the lakes, with arsenic exceeding the guideline values at two sites in Ross Barnett Reservoir. While it is apparent from this study that these lakes face many water quality issues, data across all seasons will be required to document potential trends and to devise management strategies. Use of remote sensing technology is recommended to monitor some of the water quality parameters such as suspended particulate matter and algal blooms, especially cyanobacterial blooms.

This paper introduces network attacks, intrusion detection systems, intrusion prevention systems, and intrusion detection methods including signature-based detection and anomaly-based detection. Intrusion detection/prevention system (ID/PS) methods are compared. Some data mining and machine learning methods and their applications in intrusion detection are introduced. Big data in intrusion detection systems and Big Data analytics for huge volume of data, heterogeneous features, and real-time stream processing are presented. Challenges of intrusion detection systems and challenges posed by stream processing of big data in the systems are also discussed.