Using ChatGPT and other LLMs in Professional Environments

Large language models like ChatGPT, Google’s Bard, and Microsoft’s new Bing, to name a few, are developing rapidly in recent years, becoming very popular in different environments, and supporting a wide range of tasks. A deep look into their outcomes reveals several limitations and challenges that can be further improved. The main challenge of these models is the possibility of generating biased or inaccurate results, since these models rely on large amounts of data with no access to unpublic information. Moreover, these language models need to be properly monitored and trained to prevent generating inappropriate or offensive content and to ensure that they are used ethically and safely. This study investigates the use of ChatGPT and other large language models such as Blender, and BERT in professional environments. It has been found that none of the large language models, including ChatGPT, have been used in unstructured dialogues. Moreover, involving the models in professional environments requires extensive training and monitoring by domain professionals or fine-tuning through API

The protective effects of cerium oxide nanoparticles against hepatic oxidative damage induced by monocrotaline

Kamal A Amin1, Mohamed S Hassan2, El-Said T Awad3, Khalid S Hashem11Department of Biochemistry, 2Department of Internal Medicine, Faculty of Veterinary Medicine, Beni-Suef University, Beni-Suef, Egypt; 3Department of Biochemistry, Faculty of Veterinary Medicine, Cairo University, Cairo, EgyptObjective: The objective of the present study was to determine the ability of cerium oxide (CeO2) nanoparticles to protect against monocrotaline (MCT)-induced hepatotoxicity in a rat model.Method: Twenty male Sprague Dawley rats were arbitrarily assigned to four groups: control (received saline), CeO2 (given 0.0001 nmol/kg intraperitoneally [IP]), MCT (given 10 mg/kg body weight IP as a single dose), and MCT + CeO2 (received CeO2 both before and after MCT). Electron microscopic imaging of the rat livers was carried out, and hepatic total glutathione (GSH), glutathione reductase (GR), glutathione peroxidase (GPX), glutathione S-transferase (GST), superoxide dismutase (SOD), and catalase (CAT) enzymatic activities were quantified.Results: Results showed a significant MCT-induced decrease in total hepatic GSH, GPX, GR, and GST normalized to control values with concurrent CeO2 administration. In addition, MCT produced significant increases in hepatic CAT and SOD activities, which also ameliorated with CeO2.Conclusions: These results indicate that CeO2 acts as a putative novel and effective hepatoprotective agent against MCT-induced hepatotoxicity.Keywords: monocrotaline, ceruim oxide nanoparticle, hepatotoxicity, oxidative stres

Membrane techniques for removal detergents and petroleum products from carwash effluents: a review

One of the most significant urban services is the carwash, which generates large amounts of wastewater containing a variety of pollutants, including sand, gravel, suspended solids, surfactants, oil products, diesel cleaners, etc., that may cause environmental pollution when transferred to the sewage system without any treatment. The effective treatment is crucial to prevent environmental pollution as well as to recycle the water source. Contaminants are removed from carwash effluent using a variety of treatment technologies. This review focuses on identifying and comparing efficiency of using advanced commercial and modified membrane filtration techniques, meeting discharge standard regulations, to treat carwash impurities, especially detergents/surfactants (anionic surfactant) and petroleum products (oil/grease). The results of this review indicate that ultrafiltration membrane (UF) is the most common membrane filtration technology for carwash wastewater treatment. Additionally, the adoption of traditional pre-treatment processes may be advantageous before utilization of membrane process for treating carwash wastewater; although conventional treatment processes can produce a high quality of effluent, they are less effective than membrane systems

Higher Dimensional Kerr-AdS Black Holes and the AdS/CFT Correspondence

Using the counterterm subtraction technique we calculatehe stress-energy tensor, action, and other physical quantities for Kerr-AdS black holes in various dimensions. For Kerr-AdS_5 with both rotation parameters non-zero, we demonstrate that stress-energy tensor, in the zero mass parameter limit, is equal to the stress tensor of the weakly coupled four dimensional dual field theory. As a result, the total energy of the generalKerr-AdS_5 black hole at zero mass parameter, exactly matches the Casimir energy of the dual field theory. We show that at high temperature, the general Kerr-AdS_5 and perturbative field theory stress-energy tensors are equal, up to the usual factor of 3/4. We also use the counterterm technique to calculate the stress tensors and actions for Kerr-AdS_6, and Kerr-AdS_7 black holes, with one rotation parameter, and we display the results. We discuss the conformal anomalies of the field theories dual to the Kerr-AdS_5 and Kerr-AdS_7 spacetimes. In these two field theories, we show that the rotation parameters break conformal invariance but not scale invariance, a novel result for a non-trivial field theory. For Kerr-AdS_7 the conformal anomalies calculated on the gravity side and the dual (0,2) tensor multiplet theory are equal up to 4/7 factor. We expect that the Casimir energy of the free field theory is the same as the energy of the Kerr-AdS_7 black hole (with zero mass parameter), up to that factor.Comment: 18 pages, LaTex (v3: references added. footnote added

Using ChatGPT and other LLMs in Professional Environments

Large language models like ChatGPT, Google’s Bard, and Microsoft’s new Bing, to name a few, are developing rapidly in recent years, becoming very popular in different environments, and supporting a wide range of tasks. A deep look into their outcomes reveals several limitations and challenges that can be further improved. The main challenge of these models is the possibility of generating biased or inaccurate results, since these models rely on large amounts of data with no access to unpublic information. Moreover, these language models need to be properly monitored and trained to prevent generating inappropriate or offensive content and to ensure that they are used ethically and safely. This study investigates the use of ChatGPT and other large language models such as Blender, and BERT in professional environments. It has been found that none of the large language models, including ChatGPT, have been used in unstructured dialogues. Moreover, involving the models in professional environments requires extensive training and monitoring by domain professionals or fine-tuning through API

Lifshitz spacetimes from AdS null and cosmological solutions

We describe solutions of 10-dimensional supergravity comprising null deformations of $AdS_5\times S^5$ with a scalar field, which have $z=2$ Lifshitz symmetries. The bulk Lifshitz geometry in 3+1-dimensions arises by dimensional reduction of these solutions. The dual field theory in this case is a deformation of the N=4 super Yang-Mills theory. We discuss the holographic 2-point function of operators dual to bulk scalars. We further describe time-dependent (cosmological) solutions which have anisotropic Lifshitz scaling symmetries. We also discuss deformations of $AdS\times X$ in 11-dimensional supergravity, which are somewhat similar to the solutions above. In some cases here, we expect the field theory duals to be deformations of the Chern-Simons theories on M2-branes stacked at singularities.Comment: Latex, 29pgs, v3. references, minor clarifications (subsection on Lifshitz geometry seen by scalar probes) added, to appear in JHE

Probe Branes, Time-dependent Couplings and Thermalization in AdS/CFT

We present holographic descriptions of thermalization in conformal field theories using probe D-branes in AdS X S space-times. We find that the induced metrics on Dp-brane worldvolumes which are rotating in an internal sphere direction have horizons with characteristic Hawking temperatures even if there is no black hole in the bulk AdS. The AdS/CFT correspondence applied to such systems indeed reveals thermal properties such as Brownian motions and AC conductivities in the dual conformal field theories. We also use this framework to holographically analyze time-dependent systems undergoing a quantum quench, where parameters in quantum field theories, such as a mass or a coupling constant, are suddenly changed. We confirm that this leads to thermal behavior by demonstrating the formation of apparent horizons in the induced metric after a certain time.Comment: LaTeX, 47 pages, 14 figures; Typos corrected and references added (v2); minor corrections, references added(v3

Deep Learning versus Classical Regression for Brain Tumor Patient Survival Prediction

Deep learning for regression tasks on medical imaging data has shown promising results. However, compared to other approaches, their power is strongly linked to the dataset size. In this study, we evaluate 3D-convolutional neural networks (CNNs) and classical regression methods with hand-crafted features for survival time regression of patients with high grade brain tumors. The tested CNNs for regression showed promising but unstable results. The best performing deep learning approach reached an accuracy of 51.5% on held-out samples of the training set. All tested deep learning experiments were outperformed by a Support Vector Classifier (SVC) using 30 radiomic features. The investigated features included intensity, shape, location and deep features. The submitted method to the BraTS 2018 survival prediction challenge is an ensemble of SVCs, which reached a cross-validated accuracy of 72.2% on the BraTS 2018 training set, 57.1% on the validation set, and 42.9% on the testing set. The results suggest that more training data is necessary for a stable performance of a CNN model for direct regression from magnetic resonance images, and that non-imaging clinical patient information is crucial along with imaging information.Comment: Contribution to The International Multimodal Brain Tumor Segmentation (BraTS) Challenge 2018, survival prediction tas