Toxic gases such as NO2 and irritant gases such as NH3 are two of the harshest aspects that trigger the exacerbation of the respiratory system for asthma patients. Monitoring and recording high‐risk gases are very important for tracking disease and alerting patients because humans can be exposed to a vulnerable environment with inconspicuous gases. Current detectors suffer from lack of portability and cannot provide daily real‐time detection. This work develops a light, inexpensive epidermal gas sensor based on ultralarge MoSe2 nanosheets. MoSe2 nanosheets are obtained using a gold‐assisted exfoliation method and the electrical and optical properties of the film are characterized. A high‐performance gas sensor for NO2 and NH3, which can be integrated onto human skin, is fabricated and shows great stability with up to 30% tensile strain. In particular, the device is able to detect down to 1 part per million with fast response (<200 s). The system is effective in providing timely warnings and the sensing data are uploaded to a cloud‐based terminal so that a medical institute can easily access them and provide a more accurate diagnosis.

Non-invasive continuous alcohol monitoring has potential applications in both population research and in clinical management of acute alcohol intoxication or chronic alcoholism. Current wearable monitors based on transdermal alcohol content (TAC) sensing are relatively bulky and have limited quantification accuracy. Here we describe the development of a discreet wearable transdermal alcohol (TAC) sensor in the form of a wristband or armband. This novel sensor can detect vapor-phase alcohol in perspiration from 0.09 ppm (equivalent to 0.09 mg/dL sweat alcohol concentration at 25 °C under Henry's Law equilibrium) to over 500 ppm at oneminute time resolution. The TAC sensor is powered by a 110 mAh lithium battery that lasts for over 7 days. In addition, the sensor can function as a medical "internet-of-things" (IoT) device by connecting to an Android smartphone gateway via Bluetooth Low Energy (BLE) and upload data to a cloud informatics system. Such wearable IoT sensors may enable largescale alcohol-related research and personalized management. We also present evidence suggesting a hypothesis that perspiration rate is the dominant factor leading to TAC measurement variabilities, which may inform more reproducible and accurate TAC sensor designs in the future.

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Mechanistic studies of pediatric asthma require objective measures of environmental exposure metrics correlated with physiological responses. Here we report a cloud-based wearable IoT sensor system which can measure an asthma patient's exposure to aldehydes, a known class of airway irritants, in real-life settings. The wrist-watch shaped sensor can measure formaldehyde levels in air from 30ppb to 10ppm using fuel cell technology, and continuously operate over 7 days without recharging. The sensor wirelessly uploads data to an Android smartphone via Bluetooth Low Energy (BLE). The smartphone also functions as a gateway to a cloud-based informatics system which handles sensor data storage, management and analytics. Potential applications of this IoT sensor system include epidemiological studies of asthma development and exacerbations, personalized asthma management and environmental monitoring.

We introduce a simple method for detecting outliers in Data Envelopment Analysis. The method is based on two scalar measures. The first is the relative frequency with which an observation appears in the construction of the frontier when testing the efficiency of other observations, and the second is the cumulative weight of an observation in the construction of the frontier. We provide a link to computer programming code for implementing the procedure.