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No significant increase was detected in the number of chromosomally damaged cells in bone marrow of Chinese hamsters after either inhalation exposure to 300 ppm styrene or oral intake of 15% ethanol in drinking water (exposure time 4 days or 3 weeks). In combined exposure, a slight increase of chromosomal aberrations was observed in the group exposed for 4 days (2.0% aberrant cells vs. 0.0% in controls). The group exposed for 3 weeks to combined treatment showed no response (0.3% aberrant cells vs. 0.7% in controls).

No significant increase was detected in the number of chromosomally damaged cells in bone marrow of Chinese hamsters after either inhalation exposure to 300 ppm styrene or oral intake of 15% ethanol in drinking water (exposure time 4 days or 3 weeks). In combined exposure, a slight increase of chromosomal aberrations was observed in the group exposed for 4 days (2.0% aberrant cells vs. 0.0% in controls). The group exposed for 3 weeks to combined treatment showed no response (0.3% aberrant cells vs. 0.7% in controls).

Our previous studies have shown that dietary xylitol supplementation diminishes bone resorption in rats, as well as protects against ovariectomy-induced increase of bone resorption during experimental osteoporosis. Interestingly, ethanol, when given simultaneously with xylitol, is known to increase blood concentration of xylitol. On the other hand, ethanol, when given alone, has been shown to increase bone resorption. The aim of the present study was to evaluate the effects of a simultaneous dietary administration of 10% xylitol and 10% ethanol on bone resorption. Bone resorption was determined using measurement of urinary excretion of hydrogen 3 (3H) radioactivity in 3H-tetracycline prelabeled rats. Already 4 days after the beginning of dietary supplementations, excretion of 3H was about 15% lower in the xylitol group (diet supplemented with 10% xylitol) and about 25% lower in the xylitol-ethanol group (diet supplemented with 10% xylitol and 10% ethanol) as compared to the controls. The excretion of 3H in these groups remained smaller than that of the controls throughout the entire study period of 40 days. The excretion of 3 H in the xylitol-ethanol group remained also smaller than that of the xylitol group. Bone mineral density and bone mineral content were determined with a peripheral quantitative computed tomography (pQCT) system from the rat tibiae at the end of the experiment. Trabecular bone mineral density and trabecular bone mineral content were significantly greater in the xylitol group and in the xylitol-ethanol group compared to the controls. They were also greater in the xylitol-ethanol group as compared to the xylitol group. Cortical bone mineral density and cortical bone mineral content did not differ significantly between the groups. In conclusion, a simultaneous dietary supplementation with 10% xylitol and 10% ethanol seems to diminish bone resorption and to increase trabecular bone mineral density and trabecular bone mineral content in rats. These effects seem to be stronger than the effects induced by 10% xylitol supplementation alone.

Our previous studies have shown that dietary xylitol supplementation diminishes bone resorption in rats, as well as protects against ovariectomy-induced increase of bone resorption during experimental osteoporosis. Interestingly, ethanol, when given simultaneously with xylitol, is known to increase blood concentration of xylitol. On the other hand, ethanol, when given alone, has been shown to increase bone resorption. The aim of the present study was to evaluate the effects of a simultaneous dietary administration of 10% xylitol and 10% ethanol on bone resorption. Bone resorption was determined using measurement of urinary excretion of hydrogen 3 (3H) radioactivity in 3H-tetracycline prelabeled rats. Already 4 days after the beginning of dietary supplementations, excretion of 3H was about 15% lower in the xylitol group (diet supplemented with 10% xylitol) and about 25% lower in the xylitol-ethanol group (diet supplemented with 10% xylitol and 10% ethanol) as compared to the controls. The excretion of 3H in these groups remained smaller than that of the controls throughout the entire study period of 40 days. The excretion of 3 H in the xylitol-ethanol group remained also smaller than that of the xylitol group. Bone mineral density and bone mineral content were determined with a peripheral quantitative computed tomography (pQCT) system from the rat tibiae at the end of the experiment. Trabecular bone mineral density and trabecular bone mineral content were significantly greater in the xylitol group and in the xylitol-ethanol group compared to the controls. They were also greater in the xylitol-ethanol group as compared to the xylitol group. Cortical bone mineral density and cortical bone mineral content did not differ significantly between the groups. In conclusion, a simultaneous dietary supplementation with 10% xylitol and 10% ethanol seems to diminish bone resorption and to increase trabecular bone mineral density and trabecular bone mineral content in rats. These effects seem to be stronger than the effects induced by 10% xylitol supplementation alone.

Abstract Localized HVAC systems with the task-ambient conditioning concept represent a promising option towards energy-saving in buildings. The design of such systems needs to involve evaluation of the local thermal comfort that corresponds to different body segments. In this work, an experimental technique using a thermal manikin was developed to determine the optimum configuration(s) among different variants of localized floor-heating systems for a single seated person. The experimented variants had different geometries or surface areas. Their surface temperatures were experimentally found subject to thermal comfort criteria and under a lowered ambient temperature. In the experiments, the thermal manikin was regulated in a dynamic mode using a model of human thermoregulation and was employed to evaluate the fulfillment of the thermal comfort criteria. The experimental setup was constructed to simulate a task area in a large hall space that may be feasible for shopping mall's application. The energy consumption of the floor-heating systems was measured to evaluate the energy performance of the different system variants. The results showed that in large hall space under lowered ambient temperature around 18 °C, a heated floor with certain geometries and a surface area of nearly 1 m 2 could fulfill the comfort criteria and represented the optimum configuration.

Abstract Localized HVAC systems with the task-ambient conditioning concept represent a promising option towards energy-saving in buildings. The design of such systems needs to involve evaluation of the local thermal comfort that corresponds to different body segments. In this work, an experimental technique using a thermal manikin was developed to determine the optimum configuration(s) among different variants of localized floor-heating systems for a single seated person. The experimented variants had different geometries or surface areas. Their surface temperatures were experimentally found subject to thermal comfort criteria and under a lowered ambient temperature. In the experiments, the thermal manikin was regulated in a dynamic mode using a model of human thermoregulation and was employed to evaluate the fulfillment of the thermal comfort criteria. The experimental setup was constructed to simulate a task area in a large hall space that may be feasible for shopping mall's application. The energy consumption of the floor-heating systems was measured to evaluate the energy performance of the different system variants. The results showed that in large hall space under lowered ambient temperature around 18 °C, a heated floor with certain geometries and a surface area of nearly 1 m 2 could fulfill the comfort criteria and represented the optimum configuration.

The question “Where has my battery gone?” remains a common source of frustration for many smartphone users. With the increased complexity of smartphone applications, and the increasing number of system settings affecting them, understanding and optimizing battery use has become a difficult chore. The present paper develops a novel approach for constructing energy models from crowdsourced measurements. In contrast to previous approaches, which have focused on the effect of a specific sensor, system setting or application, our approach can simultaneously capture relationships between multiple factors, and provide a unified view of the energy state of the mobile device. We demonstrate the validity of using crowdsourced measurements for constructing battery models through a combination of large-scale analysis of a dataset containing battery discharge and system state measurements, and hardware power measurements. The results indicate that the models captured by our approach are both in line with previous studies on battery consumption and empirical measurements, providing a cost-effective way to construct energy models during normal operations of the device. The analysis also provides several new insights about battery consumption. For example, our analysis reveals the combined effect of high CPU activity and automatic screen brightness to be higher (resulting in 9 min shorter battery lifetime on average) than the effect of medium CPU load and manual screen brightness; a Wi-Fi signal strength drop of one bar can shorten battery life by over 13%; and a smartphone sitting in direct sunlight can witness over 50% shorter battery life than one indoors in cool conditions. Based on the crowdsourced energy models, we develop Constella, a novel recommender system for system settings. Constella provides actionable and human-readable recommendations on how to adjust system settings in order to reduce overall battery drain. We validate the effectiveness of Constella through a hardware power measurement experiment carried out using three application case studies. The results of the evaluation demonstrate that Constella is capable of generating recommendations that can provide up to 61% improvements in battery life.

The question “Where has my battery gone?” remains a common source of frustration for many smartphone users. With the increased complexity of smartphone applications, and the increasing number of system settings affecting them, understanding and optimizing battery use has become a difficult chore. The present paper develops a novel approach for constructing energy models from crowdsourced measurements. In contrast to previous approaches, which have focused on the effect of a specific sensor, system setting or application, our approach can simultaneously capture relationships between multiple factors, and provide a unified view of the energy state of the mobile device. We demonstrate the validity of using crowdsourced measurements for constructing battery models through a combination of large-scale analysis of a dataset containing battery discharge and system state measurements, and hardware power measurements. The results indicate that the models captured by our approach are both in line with previous studies on battery consumption and empirical measurements, providing a cost-effective way to construct energy models during normal operations of the device. The analysis also provides several new insights about battery consumption. For example, our analysis reveals the combined effect of high CPU activity and automatic screen brightness to be higher (resulting in 9 min shorter battery lifetime on average) than the effect of medium CPU load and manual screen brightness; a Wi-Fi signal strength drop of one bar can shorten battery life by over 13%; and a smartphone sitting in direct sunlight can witness over 50% shorter battery life than one indoors in cool conditions. Based on the crowdsourced energy models, we develop Constella, a novel recommender system for system settings. Constella provides actionable and human-readable recommendations on how to adjust system settings in order to reduce overall battery drain. We validate the effectiveness of Constella through a hardware power measurement experiment carried out using three application case studies. The results of the evaluation demonstrate that Constella is capable of generating recommendations that can provide up to 61% improvements in battery life.