Occupational exposure to low-frequency electromagnetic fields (EMF) was studied in 250 leukemia patients and 261 brain-tumor cases, diagnosed in 1983-87 and compared with a control group of 1,121 randomly selected men, from the mid-region of Sweden, 1983-87. We based the exposure assessment on measurements from 1,015 different workplaces. On the basis of the job held longest during the 10-year period before diagnosis, we found an association between the average, daily, mean level of EMF and chronic lymphocytic leukemia (CLL). The risk increased with increasing level of exposure. The odds ratios (OR) and the 95 percent confidence interval (CI) for three consecutive levels of exposure were: 1.1 (CI = 0.5-2.3); 2.2 (CI = 1.1-4.3); 3.0 (CI = 1.6-5.8), respectively. No association was observed for acute myeloid leukemia (OR = 1.0, CI = 0.5-1.8; OR = 0.8, CI = 0.4-1.6; OR = 1.0, CI = 0.6-1.9). For brain tumors, the corresponding risk estimates were 1.0 (CI = 0.7-1.6); 1.5 (CI = 1.0-2.2); 1.4 (CI = 0.9-2.1). Different EMF indices were tested. Tasks with frequent or large variations between high and low field-densities (high standard deviation) were more common among CLL subjects. For brain tumors, a prolonged high level (high median values) showed the strongest association. Confounding by place of residence, smoking, benzene, ionizing radiation, pesticides, and solvents was evaluated, and these factors did not seem to have a decisive influence on the associations. We also analyzed other potential sources of bias. For CLL, there were indications of an excess number of low-exposure subjects among non-responders, which, to some extent, may have enhanced but not caused the risk estimates obtained. Our conclusion is that the study supports the hypothesis that occupational EMF exposure is a hazard in the development of certain cancers.

This study introduces a corpus of 260 naturalistic human nonlinguistic vocalizations representing nine emotions: amusement, anger, disgust, effort, fear, joy, pain, pleasure, and sadness. The recognition accuracy in a rating task varied greatly per emotion, from <40% for joy and pain, to >70% for amusement, pleasure, fear, and sadness. In contrast, the raters' linguistic-cultural group had no effect on recognition accuracy: The predominantly English-language corpus was classified with similar accuracies by participants from Brazil, Russia, Sweden, and the UK/USA. Supervised random forest models classified the sounds as accurately as the human raters. The best acoustic predictors of emotion were pitch, harmonicity, and the spacing and regularity of syllables. This corpus of ecologically valid emotional vocalizations can be filtered to include only sounds with high recognition rates, in order to study reactions to emotional stimuli of known perceptual types (reception side), or can be used in its entirety to study the association between affective states and vocal expressions (production side).

Recent research on human nonverbal vocalizations has led to considerable progress in our understanding of vocal communication of emotion. However, in contrast to studies of animal vocalizations, this research has focused mainly on the emotional interpretation of such signals. The repertoire of human nonverbal vocalizations as acoustic types, and the mapping between acoustic and emotional categories, thus remain underexplored. In a cross-linguistic naming task (Experiment 1), verbal categorization of 132 authentic (non-acted) human vocalizations by English-, Swedish- and Russian-speaking participants revealed the same major acoustic types: laugh, cry, scream, moan, and possibly roar and sigh. The association between call type and perceived emotion was systematic but non-redundant: listeners associated every call type with a limited, but in some cases relatively wide, range of emotions. The speed and consistency of naming the call type predicted the speed and consistency of inferring the caller’s emotion, suggesting that acoustic and emotional categorizations are closely related. However, participants preferred to name the call type before naming the emotion. Furthermore, nonverbal categorization of the same stimuli in a triad classification task (Experiment 2) was more compatible with classification by call type than by emotion, indicating the former’s greater perceptual salience. These results suggest that acoustic categorization may precede attribution of emotion, highlighting the need to distinguish between the overt form of nonverbal signals and their interpretation by the perceiver. Both within- and between-call acoustic variation can then be modeled explicitly, bringing research on human nonverbal vocalizations more in line with the work on animal communication.Electronic supplementary materialThe online version of this article (doi:10.1007/s10919-017-0267-y) contains supplementary material, which is available to authorized users.

Contagious yawning is a well-documented phenomenon in humans and has recently attracted much attention from developmental and comparative sciences. The function, development and underlying mechanisms of the phenomenon, however, remain largely unclear. Contagious yawning has been demonstrated in dogs and several non-human primate species, and theoretically and empirically associated with empathy in humans and non-human primates. Evidence of emotional closeness modulating contagious yawning in dogs has, nonetheless, been contradictory. Humans show a developmental increase in susceptibility to yawn contagion, with typically developing children displaying a substantial increase at the age of four, when a number of cognitive abilities (e.g. accurate identification of others' emotions) begin to clearly manifest. Explicit tests of yawn contagion in non-human animals have, however, thus far only involved adult individuals. Here, we report a study of the ontogeny of domestic dogs' (Canis lupus familiaris) susceptibility to yawn contagion, and whether emotional closeness to the yawning model affects this. Thirty-five dogs, aged 4-14 months, observed a familiar and unfamiliar human repeatedly yawn or gape. The dogs yawned contagiously, but emotional closeness with the model did not affect the strength of contagion, raising questions as to recent evidence of emotionally modulated auditory contagious yawning in dogs. The dogs showed a developmental effect, with only dogs above 7 months evidencing contagion. The results support the notion of a developmental increase in dogs' attention to others and identification of others' emotional states and suggest that yawn contagion is underpinned by developmental processes shared by humans and other animals.

Exposures to extremely-low-frequency magnetic fields were assessed by taking personal measurements with a dosimeter calibrated at 50 Hz with a bandwidth of 40-400 Hz. The study group was a population-based random sample of 1,098 Swedish men. Exposures were determined as workday mean, median, maximum, and standard deviation, and the time fraction of the day when exposures exceeded 0.20 µT. For workday means, the 50th percentile was 0.17 µT, and the 75th percentile was 0.27 µT. For median values, the 50th percentile was 0.11 µT and the 75th percentile was 0.16 µT. The strongest correlation (Spearman rank correlation = r&infs;) found was between the workday mean and the fraction of time above 0.20 µT (r&infs; = 0.89). The authors used the same data to estimate exposures for the 100 most common occupations according to the 1990 Swedish census. A minimum of four independent measurements for each occupation was required. Among occupations with low workday mean values were earth-moving machine operator, health care worker, and concrete worker. Among occupations with high workday mean exposures were welder and electrical or electronics engineer or technician. High exposure levels were also found in occupations outside the study base, such as train engine driver and glass, ceramic, or brick worker. Exposures to magnetic fields vary widely, since levels of exposure are strongly affected by factors such as duration of exposure and distance from the source. Large variations often found between individuals within occupations could reflect variations in tasks across different workdays for the particular occupations and/or local conditions such as tools and installations, and/or how the work is organized and performed.