The virus of distrust: How one victim‐sensitive group member can affect the entire group's outcomes

Infant’s feeding patterns are important for development and growth; therefore babies are very sensitive to toxic elements, mainly through their food, so in the present study, the concentrations and daily intake of some Toxic Elements (TEs); Lead (Pb), Arsenic (As), Cadmium (Cd), Mercury (Hg) and Aluminum (Al) were measured in different and random 60 dried infant foods {30 infant formula (0-6 months) and 30 milk-cereal based infant formula (6 months)} which obtained from various supermarkets and pharmacies. The analysis was done using Inductive Coupled Plasma - Mass Spectrometer (ICP-MS). It could be determined the lead, arsenic, cadmium, mercury and aluminum by mean values of 0.424±0.006, 0.205±0.003, 0.014±0.0001, 0.298±0.007and 0.464±0.029 mg/Kg in the examined infant milk formula samples and a ranged minimum to maximum concentrations of 0.114-0.177, 0.155-0.293, 0.014-0.015, 0.282-0.310 and 0.287-0.437 mg/kg, respectively in the examined milk-cereal based infant formula. Present study indicates that, the greater level of contamination of examined infant formula samples with toxic elements (lead and mercury) surpasses the maximum limit and Provisional Tolerable Daily Intake (PTDI) of these elements. Mercury is over PTDI (0.0005 mg/kg bw/day) in all milk-cereal based infant formula samples, also arsenic in all examined samples of this type of formula was exceed the maximum limit (0.05 mg/kg) of Indian standard. This investigation shows such types of infant formula need more amendment to set limit of more toxic metals for this sensitive group of population.

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Executive Compensation When a Firm is a Business Group Member

SSRN Electronic Journal ◽

10.2139/ssrn.2571504 ◽

2015 ◽

Author(s):

Hyungseok Kim ◽

Woochan Kim

Keyword(s):

Executive Compensation ◽

Business Group ◽

Group Member

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Growth Characteristics of Activated Sludges Acclimated to para-Nitrophenol in Batch and Continuous Modes

Water Science & Technology ◽

10.2166/wst.1994.0359 ◽

1994 ◽

Vol 29 (7) ◽

pp. 327-333

Author(s):

Y. Matsui ◽

F. Yamaguchi ◽

Y. Suwa ◽

Y. Urushigawa

Keyword(s):

Growth Characteristics ◽

The Other ◽

Operational Mode ◽

Continuous Mode ◽

Relative Resistance ◽

Batch Mode ◽

The Given ◽

Operational Modes ◽

Very High ◽

Sensitive Group

Activated sludges were acclimated to p-nitrophenol (PNP) in two operational modes, a batch and a continuous. The operational mode of the PNP acclimation of activated sludges strongly affected the physiological characteristics of predominant microorganisms responsible for PNP degradation. Predominant PNP degraders in the sludge in batch mode (Sludge B) had lower PNP affinity and were relatively insensitive to PNP concentration. Those of the sludge in continuous mode (Sludge C), on the other hand, had very high PNP affinity and were sensitive to PNP. MPN enumeration of PNP degraders in sludge B and C using media with different PNP concentrations (0.05, 0.2,0.5 and 2.0 mM) supported the above results. Medium with 0.2 mM of PNP did not recover PNP degraders in sludge C well, while it recovered PNP degraders in sludge B as well as the medium with 0.05 mM did. When switching from one operational mode to the other, the predominant population in sludge B shifted to the sensitive group, but that of sludge C did not shift at the given loading of PNP, showing relative resistance to inhibitive concentration.

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Epistemic Free Riding

10.1093/oso/9780198779681.003.0014 ◽

2018 ◽

Cited By ~ 1

Author(s):

Jeffrey Dunn

Keyword(s):

Problem Solving ◽

Empirical Evidence ◽

Free Riding ◽

Group Problem ◽

Group Problem Solving ◽

Division Of Cognitive Labor ◽

Group Member

Free riding occurs in the practical domain when some action is rational for each group member to perform but such that when everyone performs that action, it is worse overall for everyone. Dunn argues that some surprising empirical evidence about group problem-solving reveals that groups will often face cases where it is epistemically best for each individual to believe one thing, even though this is ultimately epistemically worse for the group that each member believes in this way. Dunn’s work is thus an extension of work on the division of cognitive labor and ways that group inquiry might differ from individual inquiry.

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Evaluating Group Member Behaviour Under Individualist and Collectivist Norms

Small Group Research ◽

10.1177/1046496414525479 ◽

2014 ◽

Vol 45 (2) ◽

pp. 217-228 ◽

Cited By ~ 8

Author(s):

Martin S. Hagger ◽

Panagiotis Rentzelas ◽

Severine Koch

Keyword(s):

Group Member

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A New Approach to Group Multi-Objective Optimization under Imperfect Information and Its Application to Project Portfolio Optimization

Applied Sciences ◽

10.3390/app11104575 ◽

2021 ◽

Vol 11 (10) ◽

pp. 4575

Author(s):

Eduardo Fernández ◽

Nelson Rangel-Valdez ◽

Laura Cruz-Reyes ◽

Claudia Gomez-Santillan

Keyword(s):

Portfolio Optimization ◽

Imperfect Information ◽

Model Parameters ◽

Final Decision ◽

Project Portfolio ◽

Objective Functions ◽

Multi Objective Optimization ◽

New Approach ◽

Multi Objective ◽

Group Member

This paper addresses group multi-objective optimization under a new perspective. For each point in the feasible decision set, satisfaction or dissatisfaction from each group member is determined by a multi-criteria ordinal classification approach, based on comparing solutions with a limiting boundary between classes “unsatisfactory” and “satisfactory”. The whole group satisfaction can be maximized, finding solutions as close as possible to the ideal consensus. The group moderator is in charge of making the final decision, finding the best compromise between the collective satisfaction and dissatisfaction. Imperfect information on values of objective functions, required and available resources, and decision model parameters are handled by using interval numbers. Two different kinds of multi-criteria decision models are considered: (i) an interval outranking approach and (ii) an interval weighted-sum value function. The proposal is more general than other approaches to group multi-objective optimization since (a) some (even all) objective values may be not the same for different DMs; (b) each group member may consider their own set of objective functions and constraints; (c) objective values may be imprecise or uncertain; (d) imperfect information on resources availability and requirements may be handled; (e) each group member may have their own perception about the availability of resources and the requirement of resources per activity. An important application of the new approach is collective multi-objective project portfolio optimization. This is illustrated by solving a real size group many-objective project portfolio optimization problem using evolutionary computation tools.

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