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Beam Division Multiple Access (BDMA) with hybrid precoding has recently been proposed for multi-user multiple-input multiple-output (MU-MIMO) systems by simultaneously transmitting multiple digitally precoded users’ data-streams via different beams. In contrast to most existing works that assume the number of radio frequency (RF) chains must be greater than or equal to that of data-streams, this work proposes a novel BDMA downlink system by first grouping transmitting data-streams before digitally precoding data group by group. To fully harvest the benefits of this new architecture, a greedy user grouping algorithm is devised to minimize the inter-group interference while two digital precoding approaches are developed to suppress the intra-group interference by maximizing the signal-to-interference-and-noise ratio (SINR) and the signal-to-leakage-and-noise ratio (SLNR), respectively. As a result, the proposed BDMA system requires less RF chains than the total number of transmit data-streams. Furthermore, we optimize the power allocation to satisfy each user’s quality of service (QoS) requirement using the D.C. (difference of convex functions) programming technique. Simulation results confirm the effectiveness of the proposed scheme.

PurposeAgainst the backdrop of dynamic capabilities theory, this research examines the relationship between knowledge and marketing agility in the context of big data marketing analytics (BDMA). The relevant knowledge constructs under investigation are business/marketing, relational, technological and technology management. The level of BDMA deployment is also examined to determine its impact on these relationships.Design/methodology/approachA survey was used to gather data from marketing professionals working in firms with at least limited experience in big data (BD) deployment in the United States and Canada. The results were analyzed using partial least squares structural equation modeling (PLS-SEM) with a sample of 236 responses.FindingsThe results indicate that marketing professionals perceived the knowledge and marketing agility constructs differently than the previous research on IT professionals. The knowledge construct was perceived as a two-dimensional construct consisting of broad knowledge skills and specific technical knowledge skills. Only the broad knowledge skills construct was significantly related to the marketing agility construct, with progressively high predictive validity and relevance when the deployment of BDMA progresses.Originality/valueThe paper's originality stems from the different conceptualizations of the knowledge and marketing agility constructs due to the use of a novel sample of marketing professionals in this study. The research also contributes to the dynamic capabilities theory by emphasizing the critical role of vital knowledge when aiming to enhance marketing agility.

Despite analytical advancements, firms have yet to realize the full potential of big data marketing analytics (BDMA) because the poor quality data restricts customer predictions and insightful decisions. Technology and market uncertainty create challenges in understanding business needs, choosing analytical tools, determining customer insights, and market trends. This study aims to assess the quality of marketing analytics, including technology and information quality. Data were collected from 236 North American respondents working in firms with at least limited experience in the deployment of BDMA. The analysis tool was PLS-SEM. The findings supported the hypothesis that technology and market uncertainty negatively influence the quality of analytical outcomes. This study makes a significant theoretical and methodological contribution to BDMA literature by assessing the quality of analytics as an integrated formative construct.

Against the backdrop of the resource-based and dynamic capabilities view, this paper examines the impact of technology and information quality on marketing agility and the effect of the decision-making role on technology and information quality in the context of big data marketing analytics. Data were acquired from 236 marketing professionals in the U.S. and Canada working in companies with at least limited experience in big data deployment and analyzed with PLS-SEM. The findings indicate that both the information and technology quality are related to the marketing agility of the firms. Moreover, the result also shows a positive and significant association between decision-making role and information quality. This research provides an understanding of the impact of the quality of BDMA on marketing agility as it relates to the quality of information and a firm's technology, as well as the positive relationship of the decision-making on the aforementioned relationships.

Despite its historical contribution, Heather sees the Brain Disease Model of Addiction (BDMA) as failing to relieve stigma, increasing fatalism, and fundamentally wrong. He also sees \"choice\" as partly volitional and partly unconscious, implying no moral violation. I agree on all counts. Heather then presents a disorder-of-choice (DOC) model of addiction, highlighting the failure of self-regulation with respect to immediate goals. Not only do I endorse such modeling, but the neural mechanisms I describe may help to explicate it more thoroughly.

Purpose The purpose of this paper is to examine how the quality of big data marketing analytics (BDMA) impact the satisfaction, perceived value for money and intentions to reinvest as perceived by marketing managers, i.e. the users of BD. Design/methodology/approach Survey data was collected with the help of a marketing research company – mainly among Canadian and US marketing professionals with experience in BDMA deployment (N = 236). The structural model was analyzed with partial least squares structural equation modeling. Findings Findings indicate that the quality of technology has a significant and positive impact on perceived value for money but not on the satisfaction levels of those who use the data (marketing professionals). Furthermore, information quality is significantly and positively related to satisfaction for marketing professionals – but not the perceived value for money. Both perceived value for money and satisfaction are positively linked to intentions to reinvest in big data. Originality/value This paper examined separately the significance of the technology and information quality of BDMA in assessing its importance on user satisfaction and perceived value for money and, ultimately, on intentions to reinvest among marketing managers. It is noteworthy that the users of the BD (marketing managers) appear to be much more critical of BD than the data generators (BD analysts).

This study addresses the liquid-liquid extraction behavior of phosphorus from a sulfuric acid solution using benzyl dimethyl amine (BDMA) in kerosene. The extraction equilibria investigated with varied BDMA concentrations could reveal the formation of 3 [ BDMA ] ⋅ [ H 3 PO 4 ] ¯ complex in the organic phase. The thermodynamic properties determined at various temperatures indicated that the process was exothermic with a calculated enthalpy (Δ H ⊖ ) of −24.0 kJ·mol −1 . The organic-to-aqueous phase (O/A) volume ratio was varied to elucidate the quantitative extraction of phosphorus. The McCabe-Thiele diagram plotted for the extraction isotherm was validated for the requirement of three counter-current stages in the extraction at an O/A volume ratio of 2.0/3.5. The back-extraction of phosphorus from the loaded organic phase was quantitatively achieved by contacting 4.0 mol·L −1 H 2 SO 4 solution in three stages of counter-current contact at an O/A volume ratio of 3/2. This study can be applied to remove phosphorus from the sulfuric acid leach solutions of monazite processing, and many other solutions.

People struggling with addiction are neither powerless over their addiction, nor are they fully in control. Lewis vigorously objects to the brain disease model of addiction (BDMA), because it makes people lose belief in their self-efficacy, and hence hinders their recovery. Although he acknowledges that there is a compulsive state in addiction, he objects to the claim that this compulsion is carved in stone. Lewis argues that the BDMA underestimates the agency of addicted people, and hence hinder their recovery. Lewis's work offers us a very much to be welcomed neurobiology of recovery. It offers addicted people a hopeful and respectful narrative for their recovery that treats them as agents rather than as damaged brains. However, I argue that overestimating people's agency can also result in people losing belief in their self-efficacy. Lewis's strong focus on the agency of addicted people might not match their experiences of struggle, hence reinforcing their feelings of guilt when they fail to control their use. I propose to replace the notion of addiction as a disease with a notion of a disease-like stage in addiction. I call this stage the duress stage in addiction, in which the addictive behaviour is largely impervious to the agent's values and to available techniques of self-control. However, the agent can overcome this stage by developing new techniques of self-control, by building on their self-concept and belief in self-efficacy, by changing their environments and habits, and by engaging in projects that are meaningful to the agent.

In this introduction we set out some salient themes that will help structure understanding of a complex set of intersecting issues discussed in this special issue on the work of Marc Lewis: (1) conceptual foundations of the disease model, (2) tolerating the disease model given socio-political environments, and (3) A third wave: refining conceptualization of addiction in the light of Lewis's model.

Massive capacity and connectivity are the main boundaries towards standing the Internet of Everything (IoE) basis and defining modern wireless generation requirements. These needs cannot be achieved by already deployed phased array antenna in terms of distributed and oriented geometry, dimensions and design. We propose in the present paper an innovating massive multiple input multiple output (MIMO) spherical array network aiming to draw a new three-dimensional configuration to enhance the beam steering, improve bandwidth, total capacity and the scan flexibility. Resolved issues in concordance with 5G requirements are adaptive massive MIMO by using millimeter-wave antenna arrays, small cell design and definition of recommended operational frequency considering the International Telecommunication Union (ITU) norms and directives. The new geometric forms of spherical smart antenna could easily scan all 3D space, ensure higher capacity and reach tens of Giga bit per second (Gbps) value besides eradicating energy wastage aspect of Beam Division Multiple Access (BDMA) in base stations. Mathematical design is detailed and performed simulation results are presented using MATLAB software Tool.