Ultrasonic assisted machining

A commercially available DMG MORI ULTRASONIC 65 monoBLOCK machining centre was installed in WMG in 2013 and has been primarily used to machine aerospace grade materials such as carbon fibre reinforced plastic (CFRP) and titanium alloy Ti 6Al-4V (individually and stacked) and 2000 / 6000 series aluminium alloys. Rather than discuss a single set of experimental work in detail, this paper discusses some of the issues that have been encountered when applying the technique of ultrasonic assisted machining (UAM) and some of the effects that have been observed using examples from the research conducted so far to illustrate some of the more important findings

An Environmentally Stable and Lead-Free Chalcogenide Perovskite

Organic-inorganic halide perovskites are intrinsically unstable when exposed to moisture and/or light. Additionally, the presence of lead in many perovskites raises toxicity concerns. Herein is reported a thin film of BaZrS3, a lead-free chalcogenide perovskite. Photoluminescence and X-ray diffraction measurements show that BaZrS3 is far more stable than methylammonium lead iodide (MAPbI3) in moist environments. Moisture- and light-induced degradations in BaZrS3 and MAPbI3 are compared by using simulations and calculations based on density functional theory. The simulations reveal drastically slower degradation in BaZrS3 due to two factors - weak interaction with water, and very low rates of ion migration. BaZrS3 photo-detecting devices with photo-responsivity of ~46.5 mA W-1 are also reported. The devices retain ~60% of their initial photo-response after 4 weeks in ambient conditions. Similar MAPbI3 devices degrade rapidly and show ~95% decrease in photo-responsivity in just 4 days. The findings establish the superior stability of BaZrS3 and strengthen the case for its use in optoelectronics. New possibilities for thermoelectric energy conversion using these materials are also demonstrated

Visual Programming: Compositional visual reasoning without training

We present VISPROG, a neuro-symbolic approach to solving complex and compositional visual tasks given natural language instructions. VISPROG avoids the need for any task-specific training. Instead, it uses the in-context learning ability of large language models to generate python-like modular programs, which are then executed to get both the solution and a comprehensive and interpretable rationale. Each line of the generated program may invoke one of several off-the-shelf computer vision models, image processing routines, or python functions to produce intermediate outputs that may be consumed by subsequent parts of the program. We demonstrate the flexibility of VISPROG on 4 diverse tasks - compositional visual question answering, zero-shot reasoning on image pairs, factual knowledge object tagging, and language-guided image editing. We believe neuro-symbolic approaches like VISPROG are an exciting avenue to easily and effectively expand the scope of AI systems to serve the long tail of complex tasks that people may wish to perform

Spectral domain optical coherence tomography changes following intravitreal dexamethasone implant, Ozurdex® in patients with uveitic cystoid macular edema.

PURPOSE: To correlate the structural and functional changes following intravitreal injection of dexamethasone 0.7 mg (Ozurdex®) implant in patients with recalcitrant uveitic cystoid macular edema (CME). MATERIALS AND METHODS: In a prospective, interventional, nonrandomized study, 30 eyes (27 patients) with uveitic CME received Ozurdex® implant and were followed-up for 24 weeks at periodic intervals to monitor structural alterations seen on spectral domain optical coherence tomography (SD-OCT). The outcome measures included change in central macular thickness (CMT) and best-corrected visual acuity (BCVA) as well as structural alterations seen on OCT such as change in the height of cystoid spaces (CSs) and sub-foveal serous retinal detachment (SSRD). The integrity of external limiting membrane and inner-outer segment junction was assessed at baseline and follow-up visits. RESULTS: Mean age of the patients was 46.09 ± 15.66 years. The mean CMT decreased by 96 μm at 1-day, 231.64 μm at 1-week, 254.21 μm at 4 weeks and 249.14 μm at 12 weeks (P \u3c 0.001) compared with baseline. BCVA improved from a baseline mean of 0.62 LogMAR units to 0.49 on day 1 to 0.31 at 24 weeks (P \u3c 0.001). A decrease in the mean height of CS, that is, 133.28 μm from a baseline of 317.71 μm was noted on the 1 st day (P \u3c 0.001). 4 eyes demonstrated the presence of CS at 4 weeks, 1 eye at 6 weeks and 3 eyes at 12 weeks. At baseline, 16 eyes (53.33%) demonstrated the presence of SSRD. Among these, 11 eyes showed resolution of SSRD on day 1. SSRD resolved in all patients at 4 weeks and was maintained up to 24 weeks. CONCLUSIONS: Ozurdex® implant improves the visual outcome of patients with recalcitrant uveitic CME. Reversibility of retinal changes may be possible following treatment with dexamethasone implant. Thus final visual outcome may be independent of pretreatment CMT, the height of CS or SSRD

Predictive Analysis for Optimizing Port Operations

Maritime transport is a pivotal logistics mode for the long-distance and bulk transportation of goods. However, the intricate planning involved in this mode is often hindered by uncertainties, including weather conditions, cargo diversity, and port dynamics, leading to increased costs. Consequently, accurately estimating vessel total (stay) time at port and potential delays becomes imperative for effective planning and scheduling in port operations. This study aims to develop a port operation solution with competitive prediction and classification capabilities for estimating vessel Total and Delay times. This research addresses a significant gap in port analysis models for vessel Stay and Delay times, offering a valuable contribution to the field of maritime logistics. The proposed solution is designed to assist decision-making in port environments and predict service delays. This is demonstrated through a case study on Brazil ports. Additionally, feature analysis is used to understand the key factors impacting maritime logistics, enhancing the overall understanding of the complexities involved in port operations.Comment: 13 pages, 9 figures, 4 Tables. Submitted at IEEE IJCNN 202

Synthetic Polymer Based Coating of Fodder Cowpea Seeds Enhances Germination and Vigour

In Indian arid and semi-arid conditions, comparatively less fertile lands are allotted to forage crops. In addition, erratic weather condition makes the situation more complex where proper seedling emergence and establishment of pastures with economic use of input remains a big question. Our view is that crop seedling production from seed sown into arid or semiarid environments could be significantly enhanced by the use of simple seed coating technologies. Such approaches would make use of newly synthesised seed coat-applied polymers that could be used to hold the desired supplements like powerful germination enhancement chemicals and plant protectants with seed to support both germination and seedling establishment under the crucial stages. This approach would be expected to increase the rate and speed of germination, thereby bringing the uniformity in plant population even under stressful (drought) growing conditions. On the other hand, cowpea seed are highly susceptible to insect pest during storage in addition to seed borne diseases. Hence, coating of seed was envisaged in order to protect the seeds from pest attack and boost initial seedling vigour

Study of cutting speed on ultrasonic assisted drilling of carbon fibre reinforced plastics

Workpiece damage generated during conventional drilling (CD) of carbon fibre reinforced plastics (CFRP) (such as delamination, matrix cracking, fibre pull out etc.) results in reduced fatigue strength, poor assembly tolerance and compromised structural integrity of the component. Avoidance of such damage during drilling of CFRP is a challenge for the aircraft and aerospace industries. At present, it requires a lot of resources and huge cost in order to generate damage free holes in CFRP in the industries. Therefore, the industries (such as BAE Systems) are looking for alternative hole producing processes for damage free drilling. It has been reported that thrust force during drilling should be reduced in order to reduce exit delamination. Ultrasonic assisted drilling (UAD) has been found to reduce the cutting and thrust forces during drilling of metals when compared to CD. Although limited attempts employing UAD indicate a reduction in thrust and cutting forces and damage when machining CFRP, this process has not been examined in detail with respect to optimising machining parameters in relation to machining theory. In addition, there has been limited research regarding the effect of the UAD process on overall workpiece damage as a result of drilling of CFRP. The focus of this research was the identification of the mechanism responsible for thrust force reduction in UAD in comparison to CD during drilling of CFRP which would help in selecting the machining parameters resulting in minimum workpiece damage. Consequently, the cutting speeds resulting in reduced forces and damage were investigated. As a fundamental concept in machining theory, higher rake angles result in lower cutting forces and improved surface roughness. Calculations of effective normal rake angle at the cutting edge of a twist drill in UAD revealed a maximum of 62° and 49° effective rake angle at 10 and 100 m/min (40160 Hz, 7.3 μm peak-to-peak amplitude) respectively for a new tool. Employing knowledge of the effective rake angle, experiments were performed at specific cutting speeds in order to examine the effects of UAD on forces and damage during drilling of CFRP and compared to CD. Further work employed a pilot hole to remove the contribution of chisel edges so that influence of effective rake angles at the cutting edges could be examined. Through-hole drilling tests, comparing UAD and CD, employing a constant feed rate of 0.05 mm/rev and two cutting speeds (10 and 100 m/min) were carried out. At 10 m/min, there was a reduction in thrust force and torque of 55 % and 45 %, respectively when utilising UAD with a new tool. 40 % reduction in thrust force and 46 % in torque with 52 μm of tool wear corresponded to 36 % reduction in entrance delamination and 22 % reduction in exit delamination at 10 m/min. At 100 m/min, 20 % reduction in thrust force and 30 % in torque was obtained respectively; however, this did not yield a significant reduction in entrance or exit delamination. Analysis of internal damage did, however, reveal a 55 % reduction in internal damage (i.e. fibre pull-out and fibre disorientation) at 100 m/min. Thus, the key contribution of this research is that low cutting speed is required in UAD in order to achieve the greatest reduction in machining forces (and hence, delamination) at entrance and exit of a hole in comparison to CD. The reason for this was discovered to be higher effective rake angle at low cutting speed in UAD causing the reduction in thrust force and torque. Furthermore, reduction of internal damage in a hole required higher cutting speed in UAD. The results imply that the cutting speed should be varied during drilling a hole in CFRP. In UAD, the cutting speed should be lower at entrance and exit of a hole and higher for drilling the intermediate part. Whereas in CD, the cutting speed should be higher at entrance and exit and lower during drilling of intermediate part keeping the feed rate constant in order to achieve the minimum workpiece damage during drilling of CFRP. The proposed variation of cutting speed during drilling of a hole is possible in the machine used in the present research

Incorporating Ion-Specific van der Waals and Soft Repulsive Interactions in the Poisson-Boltzmann Theory of Electrical Double Layers

Electrical double layers (EDLs) arise when an electrolyte is in contact with a charged surface, and are encountered in several application areas including batteries, supercapacitors, electrocatalytic reactors, and colloids. In the modeling of EDLs, a prominent knowledge gap has been the exclusion of van der Waals (vdW) and soft repulsive interactions in modified Poisson-Boltzmann (PB) theories. Although more short-ranged as compared to electrostatic interactions, we show here that vdW interactions can play an important role in determining the structure of the EDL via the formation of a Stern layer and in modulating the differential capacitance of an electrode in solution. To this end, we incorporate ion-ion and wall-ion vdW attraction and soft repulsion via a 12-6 Lennard-Jones (LJ) potential, resulting in a modified PB-LJ approach. The wall-ion LJ interactions were found to have a significant effect on the electrical potential and concentration profiles, especially close to the wall. However, ion-ion LJ interactions do not affect the EDL structure at low bulk ion concentrations (< 1 M). We also derive dimensionless numbers to quantify the impact of ion-ion and wall-ion LJ interactions on the EDL. Furthermore, in the pursuit of capturing ion-specific effects, we apply our model by considering various combinations of ions. We observe how varying parameters such as the electrolyte concentration and electrode potential affect the structure of the EDL due to the competition between ion-specific LJ and electrostatic interactions. Lastly, we show that the inclusion of vdW and soft repulsion interactions as well as hydration effects lead to a better qualitative agreement of the PB models with experimental double-layer differential capacitance data. Overall, the modified PB-LJ approach presented herein will lead to more accurate theoretical descriptions of EDLs in various application areas

Optimal Load Shedding for Public Safety Power Shutoffs

Public utilities are faced with situations where high winds can bring trees and debris into contact with energized power lines and other equipments, which could ignite wildfires. As a result, they need to turn off power during severe weather to help prevent wildfires. This is called Public Safety Power Shutoff (PSPS). We present a method for load reduction using a multi-step genetic algorithm for Public Safety Power Shutoff events. The proposed method optimizes load shedding using partial load shedding based on load importance (critical loads like hospitals, fire stations, etc). The multi-step genetic algorithm optimizes load shedding while minimizing the impact on important loads and preserving grid stability. The effectiveness of the method is demonstrated through network examples. The results show that the proposed method achieves minimal load shedding while maintaining the critical loads at acceptable levels. This approach will help utilities to effectively manage PSPS events and reduce the risk of wildfires caused by the power lines.Comment: 10 pages, 5 figures, 3 Tables. Accepted at IEEE ETFG 202

SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image Understanding

Remote sensing images are useful for a wide variety of planet monitoring applications, from tracking deforestation to tackling illegal fishing. The Earth is extremely diverse -- the amount of potential tasks in remote sensing images is massive, and the sizes of features range from several kilometers to just tens of centimeters. However, creating generalizable computer vision methods is a challenge in part due to the lack of a large-scale dataset that captures these diverse features for many tasks. In this paper, we present SatlasPretrain, a remote sensing dataset that is large in both breadth and scale, combining Sentinel-2 and NAIP images with 302M labels under 137 categories and seven label types. We evaluate eight baselines and a proposed method on SatlasPretrain, and find that there is substantial room for improvement in addressing research challenges specific to remote sensing, including processing image time series that consist of images from very different types of sensors, and taking advantage of long-range spatial context. Moreover, we find that pre-training on SatlasPretrain substantially improves performance on downstream tasks, increasing average accuracy by 18% over ImageNet and 6% over the next best baseline. The dataset, pre-trained model weights, and code are available at https://satlas-pretrain.allen.ai/.Comment: ICCV 202