Simulation and Economic Study of the MED-TVC Units at Umm Al Nar Desalination Plant

A rigorous mathematical model has been used to develop a steady state simulation program MEDNAR to analyze the multi-effect thermal vapor compression desalination (MED-TVC) plant at Umm Al-Nar power and desalination plant. The effect of thermodynamic losses on the thermal performance ratio, the specific heat transfer area and the specific flow rate of the cooling water are taken into account. The losses contemplated are the boiling point elevation and the temperature depression corresponding to the pressure drop during the vapor condensation process. The MEDNAR also takes into consideration the variation in the physical properties of the seawater with temperature and salt concentration, and the effect of the presence of non-condensable gases on the heat transfer coefficients in the evaporators. Sensitivity analyses, using this software, were conducted to study the effect of a number of process variables on the plant performance. As a part of this thesis, an economic study has been carried out to determine the total water unit cost. This includes a cost break down in details for capital investment and production costs. Also an economic sensitivity analysis was performed to investigate the relationships between the fuel cost, plant production rate, operation and maintenance cost and plant running factor, and the total water unit cost

Recombinant expression of the Aryl Hydrocarbon Receptor

Aryl Hydrocarbon Receptor (AhR) mediates drug and toxin action. The AhR proteins have been characterised in several mammalian species, and are soluble proteins found in various tissues. The AhR is normally found in the cytoplasm in a complex with 90 KDa heat shock protein (hsp90) and cellular chaperones such as ARA9 (AIP or XAP2) and p23. However, there has not been a systematic analysis of the proteins which chaperone the AhR ligand-binding domain (LBD). This work investigates the interaction between ligands and the AhR, the protein composition of the AhR ligand-binding domain (LBD) complex, by establishing translation of AhR LBD in reticulocyte lysate, which contains molecular chaperones such as hsp90, and p23 that stabilise the ligand binding form of AhR. EGFP (Enhanced Green Fluorescent Protein) has been coupled to the mouse AhR b-1 LBD, to enable fluorescence analytical techniques of ligand-binding to the AhR. The Glutathione S-Transferase (GST) affinity tag was fused to EGFP (GST-EGFP), then fused to AhR.LBD with one or two EGFP (GST-EGFP-AhR.LBD and GST-EGFP-AhR.LBD-EGFP) to enable rapid one-step purification of AhR fusion proteins, and associated chaperone proteins. Proteins were expressed in E.coli (BL21(DE3)plysS). The GST protein is soluble, and not fluorescent, and GST-EGFP and GST-EGFP-AhR.LBD-EGFP was soluble and fluoresecent. The GST-EGFP-AhR.LBD was an insoluble fluorescent protein. Thus, the AhR proteins were purified from bacteria to test the specificity of the pulldown system under conditions which do not yield functional Ah Receptor. The tagged AhR constructs were translated with [35S]-methionine in reticulocyte lysate and translation products were ~36, 66, 84 and 109 kDa on SDS-PAGE. Reticulocyte lysate programmed with GST-EGFP-AhR.LBD and GST-EGFP-AhR.LBD-EGFP both bound ~800 d.p.m 2,3,7,8-[1,6-3H]tetrachlorodibenzo-p-dioxin (a ligand for the AhR), while lysate programmed with GST.EGFP showed binding of ~15 d.p.m, indistinguishable from unprogrammed lysate. The AhR proteins were purified from reticulocyte lysate and subsequent pulldown experiments will enable proteomic analysis of the proteins associated with the AhR LBD

Recombinant expression of the Aryl Hydrocarbon Receptor

Aryl Hydrocarbon Receptor (AhR) mediates drug and toxin action. The AhR proteins have been characterised in several mammalian species, and are soluble proteins found in various tissues. The AhR is normally found in the cytoplasm in a complex with 90 KDa heat shock protein (hsp90) and cellular chaperones such as ARA9 (AIP or XAP2) and p23. However, there has not been a systematic analysis of the proteins which chaperone the AhR ligand-binding domain (LBD). This work investigates the interaction between ligands and the AhR, the protein composition of the AhR ligand-binding domain (LBD) complex, by establishing translation of AhR LBD in reticulocyte lysate, which contains molecular chaperones such as hsp90, and p23 that stabilise the ligand binding form of AhR. EGFP (Enhanced Green Fluorescent Protein) has been coupled to the mouse AhR b-1 LBD, to enable fluorescence analytical techniques of ligand-binding to the AhR. The Glutathione S-Transferase (GST) affinity tag was fused to EGFP (GST-EGFP), then fused to AhR.LBD with one or two EGFP (GST-EGFP-AhR.LBD and GST-EGFP-AhR.LBD-EGFP) to enable rapid one-step purification of AhR fusion proteins, and associated chaperone proteins. Proteins were expressed in E.coli (BL21(DE3)plysS). The GST protein is soluble, and not fluorescent, and GST-EGFP and GST-EGFP-AhR.LBD-EGFP was soluble and fluoresecent. The GST-EGFP-AhR.LBD was an insoluble fluorescent protein. Thus, the AhR proteins were purified from bacteria to test the specificity of the pulldown system under conditions which do not yield functional Ah Receptor. The tagged AhR constructs were translated with [35S]-methionine in reticulocyte lysate and translation products were ~36, 66, 84 and 109 kDa on SDS-PAGE. Reticulocyte lysate programmed with GST-EGFP-AhR.LBD and GST-EGFP-AhR.LBD-EGFP both bound ~800 d.p.m 2,3,7,8-[1,6-3H]tetrachlorodibenzo-p-dioxin (a ligand for the AhR), while lysate programmed with GST.EGFP showed binding of ~15 d.p.m, indistinguishable from unprogrammed lysate. The AhR proteins were purified from reticulocyte lysate and subsequent pulldown experiments will enable proteomic analysis of the proteins associated with the AhR LBD

On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning

Generating a Chain of Thought (CoT) has been shown to consistently improve large language model (LLM) performance on a wide range of NLP tasks. However, prior work has mainly focused on logical reasoning tasks (e.g. arithmetic, commonsense QA); it remains unclear whether improvements hold for more diverse types of reasoning, especially in socially situated contexts. Concretely, we perform a controlled evaluation of zero-shot CoT across two socially sensitive domains: harmful questions and stereotype benchmarks. We find that zero-shot CoT reasoning in sensitive domains significantly increases a model's likelihood to produce harmful or undesirable output, with trends holding across different prompt formats and model variants. Furthermore, we show that harmful CoTs increase with model size, but decrease with improved instruction following. Our work suggests that zero-shot CoT should be used with caution on socially important tasks, especially when marginalized groups or sensitive topics are involved.Comment: ACL 2023 Main Conferenc

What are NLRP3-ASC specks? an experimental progress of 22 years of inflammasome research

Speck assembly is the hallmark of NLRP3 inflammasome activation. The 1µm structure comprising of NLRP3 and ASC is the first observable phenotype of NLRP3 activation. While the common consensus is that the specks are the site of inflammasome activity, no direct experimental evidence exists to support this notion. In these 22 years, since the inflammasome discovery, several research studies have been published which directly or indirectly support or refute the idea of speck being the inflammasome. This review compiles the data from two decades of research to answer a long-standing question: “What are NLRP3-ASC specks?

Grounding or Guesswork? Large Language Models are Presumptive Grounders

Effective conversation requires common ground: a shared understanding between the participants. Common ground, however, does not emerge spontaneously in conversation. Speakers and listeners work together to both identify and construct a shared basis while avoiding misunderstanding. To accomplish grounding, humans rely on a range of dialogue acts, like clarification (What do you mean?) and acknowledgment (I understand.). In domains like teaching and emotional support, carefully constructing grounding prevents misunderstanding. However, it is unclear whether large language models (LLMs) leverage these dialogue acts in constructing common ground. To this end, we curate a set of grounding acts and propose corresponding metrics that quantify attempted grounding. We study whether LLMs use these grounding acts, simulating them taking turns from several dialogue datasets, and comparing the results to humans. We find that current LLMs are presumptive grounders, biased towards assuming common ground without using grounding acts. To understand the roots of this behavior, we examine the role of instruction tuning and reinforcement learning with human feedback (RLHF), finding that RLHF leads to less grounding. Altogether, our work highlights the need for more research investigating grounding in human-AI interaction.Comment: 16 pages, 2 figure

Assessing generation y readiness to meet job demand: A case study of internship students at large government invested company

This paper will discuss the survey that was carried out in Large Government Invested Company.Every year, the organization accepted more than 100 internship student placement ranging from various public and private higher learning institutions (HLI) in the country. Those internship students are categorized as generation y.This generation will take over current job position when the baby boomer generation reaches their retirement ages.Survey was conducted to access the readiness of internship students towards job demand.Data were collected through online survey that was developed on the Microsoft SharePoint Portal.The result of the survey will be used to create a profile of future recruitment and developing new working surrounding for generation y in the organization

Quantum simulation of quantum mechanical system with spatial noncommutativity

Quantum simulation has become a promising avenue of research that allows one to simulate and gain insight into the models of High Energy Physics whose experimental realizations are either complicated or inaccessible with current technology. We demonstrate the quantum simulation of such a model, a quantum mechanical system with spatial noncommutativity, which is inspired by the works in Noncommutative Geometry and Noncommutative Field theory for a universal quantum computer. We use the novel group theoretical formalism to map the Hamiltonian of such a noncommutative quantum system into the ordinary quantum mechanical Hamiltonian and then carry out the quantum simulation using the Trotter-Suzuki product formula. Furthermore, we distinguish the impact of the noncommutativity parameter on the quantum simulation, especially on the Trotter error, and point out how its sizable value affects the simulation.Comment: Discussion on entanglement entropy and noisy simulation added, accepted versio