Enhancing Biodiesel Production from Soybean Oil Using Ultrasonics

Our objective was to determine the effect of ultrasonics on biodiesel production from soybean oil. In this study, ultrasonic energy was applied in two different modes: pulse and continuous sonication. Soybean oil was mixed with methanol and a catalytic amount of sodium hydroxide, and the mixture was sonicated at three levels of amplitude (60, 120, and 180 μmpp) in pulse mode (5 s on/25 s off). In the continuous mode, the same reaction mixture was sonicated at 120 μmpp for 15 s. The reaction was monitored for biodiesel yield by stopping the reaction at selected time intervals and analyzing the biodiesel content by thermogravimetric analysis (TGA). The results were compared to a control group, in which the same reactant composition was allowed to react at 60 °C for intervals ranging from 5 min to 1 h without ultrasonic treatment. It was observed that ultrasonic treatment resulted in a 96% by weight isolated yield of biodiesel in less than 90 s using the pulse mode, compared to 30−45 min for the unsonicated control sample with comparable yields (83−86%). In the pulse mode, the highest yield (96%) was obtained by sonicating the mixture at 120 μmpp amplitude. In the continuous sonication mode, the highest biodiesel yield was 86% by weight, which was obtained in 15 s

Federated Learning-based Collaborative Wideband Spectrum Sensing and Scheduling for UAVs in UTM Systems

In this paper, we propose a data-driven framework for collaborative wideband spectrum sensing and scheduling for networked unmanned aerial vehicles (UAVs), which act as the secondary users (SUs) to opportunistically utilize detected "spectrum holes". Our overall framework consists of three main stages. Firstly, in the model training stage, we explore dataset generation in a multi-cell environment and training a machine learning (ML) model using the federated learning (FL) architecture. Unlike the existing studies on FL for wireless that presume datasets are readily available for training, we propose a novel architecture that directly integrates wireless dataset generation, which involves capturing I/Q samples from over-the-air signals in a multi-cell environment, into the FL training process. Secondly, in the collaborative spectrum inference stage, we propose a collaborative spectrum fusion strategy that is compatible with the unmanned aircraft system traffic management (UTM) ecosystem. Finally, in the spectrum scheduling stage, we leverage reinforcement learning (RL) solutions to dynamically allocate the detected spectrum holes to the secondary users. To evaluate the proposed methods, we establish a comprehensive simulation framework that generates a near-realistic synthetic dataset using MATLAB LTE toolbox by incorporating base-station~(BS) locations in a chosen area of interest, performing ray-tracing, and emulating the primary users channel usage in terms of I/Q samples. This evaluation methodology provides a flexible framework to generate large spectrum datasets that could be used for developing ML/AI-based spectrum management solutions for aerial devices.Comment: This is a preprint version submitted to IEEE Transactions on Machine learning in Communications and Networking. arXiv admin note: text overlap with arXiv:2308.0503

Molecular Chemistry to the Fore: New Insights into the Fascinating World of Photoactive Colloidal Semiconductor Nanocrystals

Colloidal semiconductor nanocrystals possess unique properties that are unmatched by other chromophores such as organic dyes or transition-metal complexes. These versatile building blocks have generated much scientific interest and found applications in bioimaging, tracking, lighting, lasing, photovoltaics, photocatalysis, thermoelectrics, and spintronics. Despite these advances, important challenges remain, notably how to produce semiconductor nanostructures with predetermined architecture, how to produce metastable semiconductor nanostructures that are hard to isolate by conventional syntheses, and how to control the degree of surface loading or valence per nanocrystal. Molecular chemists are very familiar with these issues and can use their expertise to help solve these challenges. In this Perspective, we present our group\u27s recent work on bottom-up molecular control of nanoscale composition and morphology, low-temperature photochemical routes to semiconductor heterostructures and metastable phases, solar-to-chemical energy conversion with semiconductor-based photocatalysts, and controlled surface modification of colloidal semiconductors that bypasses ligand exchange

RRC connection establishment for NB-IoT

RRC layer specification is defined in TS 36.331 [1] , and for NB-IoT, the RRC layer specifications are slightly different from that of LTE. In general, RRC connection establishment for LTE and NB-IoT are relatively simple. RRC connection establishment is a 3-way handshake between UE and eNodeB, which is used to make the transition of UE from RRC Idle mode to RRC Connected mode. UE must make the transition to RRC Connected mode before transferring any application data, or completing any signalling procedures. RRC connection establishment procedure has mainly 3 steps. RRC connection request message sent by UE, RRC connection setup sent by enodeB, RRC setup complete messages send by UE. The RRC connection establishment procedure is always initiated by the UE but can be triggered by either the UE or the network. For example, the UE triggers RRC connection establishment if the end-user starts an application to browse the internet, or to send an email. Similarly, the UE triggers RRC connection establishment if the UE moves into a new Tracking Area and has to complete the Tracking Area Update signalling procedure. The network triggers the RRC connection establishment procedure by sending a Paging message. This could be used to allow the delivery of an incoming SMS or notification of an incoming voice call. The initial Non-Access Stratum (NAS) message is transferred as part of the RRC connection es- tablishment procedure [2] to reduce connection establishment delay. RRC connection establishment configures Signalling Radio Bearer (SRB) 1 and (SRB1 bis) allows subsequent signalling to use the Dedicated Control Channel (DCCH) rather than the Common Control Channel (CCCH) used by SRB 0