In What Mood Are You Today?

The mood of individuals in the workplace has been well-studied due to its influence on task performance, and work engagement. However, the effect of mood has not been studied in detail in the context of microtask crowdsourcing. In this paper, we investigate the influence of one's mood, a fundamental psychosomatic dimension of a worker's behaviour, on their interaction with tasks, task performance and perceived engagement. To this end, we conducted two comprehensive studies; (i) a survey exploring the perception of crowd workers regarding the role of mood in shaping their work, and (ii) an experimental study to measure and analyze the actual impact of workers' moods in information findings microtasks. We found evidence of the impact of mood on a worker's perceived engagement through the feeling of reward or accomplishment, and we argue as to why the same impact is not perceived in the evaluation of task performance. Our findings have broad implications on the design and workflow of crowdsourcing systems

Performance Evaluation of DTC, MPDTC and DDTC Methods for Drive of a SPMSM

This paper investigates three different direct torque control strategies for permanent magnet synchronous machines (PMSM), namely direct torque control (DTC), model predictive torque control (MPTC), and duty ratio modulated direct torque control (DDTC). The basic principle of the mentioned control strategies are presented. Then, using a PMSM fed by a two level voltage source inverter, all of the control strategies are simulated. Based on the obtained results, their performance are compared

Fenofibrate reduces the severity of neuroretinopathy in a type 2 model of diabetes without inducing peroxisome proliferator-activated receptor alpha-dependent retinal gene expression

Fenofibrate slows the progression of clinical diabetic retinopathy (DR), but its mechanism of action in the retina remains unclear. Fenofibrate is a known agonist of peroxisome proliferator-activated receptor alpha (PPARα), a transcription factor critical for regulating metabolism, inflammation and oxidative stress. Using a DR mouse model

A neonatal presentation of factor V deficiency: A case report

BACKGROUND: Factor V deficiency is a rare autosomal recessive coagulation disorder. Awareness of presenting features and management is important to avoid bleeding complications associated with mortality and neurodisability. CASE PRESENTATION: A 6-day-old Pakistani boy was admitted with bleeding from the left nipple. His parents were first cousins. A coagulation screen showed a prothrombin time of 41 s (control 14 s), a partial thromboplastin time of 132 s (control 33 s) and a normal thrombin time of 15 s (control 14 s). Factor V activity was <0.01 IU/ml. Oral tranexamic acid was started. At 5 weeks of age the child presented with irritability, lethargy and reduced feeding and a drop of hemoglobin to 5.6 g/dl. A cranial computed tomography scan showed a right intra-cerebral bleed extending from the frontal lobe to the parieto-occipital region with shift of the midline to the left. A regime of 20 ml/kg of fresh frozen plasma four times a week was instituted and has prevented further bleeds up to the present age of 21 months. Neurodevelopment remained normal. CONCLUSION: This case illustrates that in an unusually bleeding newborn of consanguineous parents rare severe homozygous bleeding disorders need to be considered. Nipple bleeding may be the first presentation of a congenital bleeding disorder. In cases of factor V deficiency where factor concentrates are not available long term use of fresh frozen plasma can prevent potentially life threatening bleeding

Bias in data-driven artificial intelligence systems—An introductory survey

Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: Commercial, Legal, and Ethical Issues &gt; Fairness in Data Mining Commercial, Legal, and Ethical Issues &gt; Ethical Considerations Commercial, Legal, and Ethical Issues &gt; Legal Issues

Bias in data-driven artificial intelligence systems - An introductory survey

Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: Commercial, Legal, and Ethical Issues > Fairness in Data Mining Commercial, Legal, and Ethical Issues > Ethical Considerations Commercial, Legal, and Ethical Issues > Legal Issues

The Effectiveness of Resonant Harmonic Filters of Ac Arc Furnaces in Uneasy Mode

Resonant harmonic filters are commonly installed on the primary side of the arc furnace transformer, and conse-quently, the transformer is exposed to the furnace generated current harmonics, the furnace reactive and unbalanced currents. The effectiveness of resonant harmonic filters installed directly at the furnace terminals, i.e., on the secondary side of the furnace transformer, is investigated in this paper. Such filters operate in conditions of fast varying parameters of the furnace. This can cause a decline in the filter effectiveness of harmonics reduction and a decline in the effectiveness of the power factor improvement. This paper investigates the effectiveness of resonant harmonic filters in an uneasy mode of an arc furnace operation. This study should enable us to draw some quantitative conclusions on the usefulness of resonant harmonic filters installed directly on the furnace

Why the Electric Arc Nonlinearity Improves the Power Factor of Ac Arc Furnaces?

The arcs in ac arc furnaces are stabilized by line inductors, at the cost of the power factor decline. It seems that in common opinions also the arc nonlinearity contributes to this decline. It occurs, however, that at the same parameters, the furnace, regarded as a linear device, has a lower power factor as compared to its value, when the arc nonlinearity is taken into account. The value of ac arc furnaces power factor (PF) is estimated in this paper at the assumption that the dc voltage on the arc has a constant value and a furnace is in a steady state. The PF of ac arc furnaces was evaluated for three states of the furnace operation, namely, for a balanced operation; for a two-arcs operation and for a furnace with a unidirectional arc. The analysis presented in the paper and modeling demonstrate that the arc nonlinearity improves the furnace power factor