Frequent and accurate inspections of industrial components and equipment are essential because failures can cause unscheduled downtimes, massive material, and financial losses or even endanger workers. In the mining industry, belt idlers or rollers are examples of such critical components. Although there are many precise laboratory techniques to assess the condition of a roller, companies still have trouble implementing a reliable and scalable procedure to inspect their field assets. This article enumerates and discusses the existing roller inspection techniques and presents a novel approach based on an Unmanned Aerial Vehicle (UAV) integrated with a thermal imaging camera. Our preliminary results indicate that using a signal processing technique, we are able to identify roller failures automatically. We also proposed and implemented a back-end platform that enables field and cloud connectivity with enterprise systems. Finally, we have also cataloged the anomalies detected during the extensive field tests in order to build a structured dataset that will allow for future experimentation.With the deepening of the research and development in the field of embedded devices, the paradigm of the Internet of things (IoT) is gaining momentum. Its technology's widespread applications increasing the number of connected devices constantly. IoT is built on sensor networks, which are enabling a new variety of solutions for applications in several fields (health, industry, defense, agrifood and agro sectors, etc.). Wireless communications are indispensable for taking full advantage of sensor networks but implies new requirements in the security and privacy of communications. Security in wireless sensor networks (WSNs) is a major challenge for extending IoT applications, in particular those related to the smart-agro. Moreover, limitations on processing capabilities of sensor nodes, and power consumption have made the encryption techniques devised for conventional networks not feasible. In such scenario, symmetric-key ciphers are preferred for key management in WSN; key distribution is therefore an issue. In this work, we provide a concrete implementation of a novel scalable group distributed key management method and a protocol for securing communications in IoT systems used in the smart agro sector, based on elliptic curve cryptography, to ensure that information exchange between layers of the IoT framework is not affected by sensor faults or intentional attacks. In this sense, each sensor node executes an initial key agreement, which is done through every member's public information in just two rounds and uses some authenticating information that avoids external intrusions. Further rekeying operations require just a single message and provide backward and forward security.The major drawback of oxide-based sensors is the lack of selectivity. In this context, SnxTi1-xO2/graphene oxide (GO)-based materials were synthesized via a simple hydrothermal route, varying the titanium content in the tin dioxide matrix. Then, toluene and acetone gas sensing performances of the as-prepared sensors were systematically investigated. Specifically, by using 321 SnO2/GO and 321 TiO2/GO, a greater selectivity towards acetone analyte, also at room temperature, was obtained even at ppb level. However, solid solutions possessing a higher content of tin relative to titanium (as 321 Sn0.55Ti0.45O2/GO) exhibited higher selectivity towards bigger and non-polar molecules (such as toluene) at 350 °C, rather than acetone. A deep experimental investigation of structural (XRPD and Raman), morphological (SEM, TEM, BET surface area and pores volume) and surface (XPS analyses) properties allowed us to give a feasible explanation of the different selectivity. Moreover, by exploiting the UV light, the lowest operating temperature to obtain a significant and reliable signal was 250 °C, keeping the greater selectivity to the toluene analyte. Hence, the feasibility of tuning the chemical selectivity by engineering the relative amount of SnO2 and TiO2 is a promising feature that may guide the future development of miniaturized chemoresistors.Mesenchymal stromal cells (MSCs) can self-renew, differentiate into specialised cells and have different embryonic origins-ectodermal for dental pulp-derived MSCs (DPSCs) and mesodermal for adipose tissue-derived MSCs (ADSCs). Data on DPSCs adipogenic differentiation potential and timing vary, and the lack of molecular and genetic information prompted us to gain a better understanding of DPSCs adipogenic differentiation potential and gene expression profile. While DPSCs differentiated readily along osteogenic and chondrogenic pathways, after 21 days in two different types of adipogenic induction media, DPSCs cultures did not contain lipid vacuoles and had low expression levels of the adipogenic genes proliferator-activated receptor gamma (PPARG), lipoprotein lipase (LPL) and CCAAT/enhancer-binding protein alpha (CEBPA). To better understand this limitation in adipogenesis, transcriptome analysis in undifferentiated DPSCs was carried out, with the ADSC transcriptome used as a positive control. In total, 14,871 transcripts were common to DPSCs and ADSCs, some were unique (DPSCs 471, ADSCs 1032), and 510 were differentially expressed genes.  https://www.selleckchem.com/products/dbet6.html  Detailed analyses of overrepresented transcripts showed that DPSCs express genes that inhibit adipogenic differentiation, revealing the possible mechanism for their limited adipogenesis.GNSS information is vulnerable to external interference and causes failure when unmanned aerial vehicles (UAVs) are in a fully autonomous flight in complex environments such as high-rise parks and dense forests. This paper presents a pan-tilt-based visual servoing (PBVS) method for obtaining world coordinate information. The system is equipped with an inertial measurement unit (IMU), an air pressure sensor, a magnetometer, and a pan-tilt-zoom (PTZ) camera. In this paper, we explain the physical model and the application method of the PBVS system, which can be briefly summarized as follows. We track the operation target with a UAV carrying a camera and output the information about the UAV's position and the angle between the PTZ and the anchor point. In this way, we can obtain the current absolute position information of the UAV with its absolute altitude collected by the height sensing unit and absolute geographic coordinate information and altitude information of the tracked target. We set up an actual UAV experimental environment.