Improving the Energy Efficiency of Petrochemical Plant Operations: A Measurement and Verification Case Study Using a Balanced Wave Optimizer

The Chinese petrochemical industry is facing pressure to meet strict targets of energy consumption and carbon emission reductions. Water pumps are the primary equipment used in most chemical and agrochemical industries sectors since water is commonly used for cooling and heating purposes, but these pumps also consume a large amount of energy. Other uses of water pumps in these industries include producing steam for heating, preparing reaction media or absorptive reagents, rinsing products, and distilling. As for the electrical components of the water pump systems, current technologies of variable frequency drives and superconducting transmission lines are unable to increase the energy efficiency of these systems with a fixed load. However, the Balanced Wave Technology (BWT) is offered as a solution to overcome these limitations. In this report, a case study using a BWT optimizer is conducted on a closed loop water circulation system. Two BWTs are added to the individual motor-controlled section of each pump that is being used on the switchboard. For the first time, a detailed example was provided on how to implement option B of the International Performance Measurement and Verification Protocol (IPMVP) in China by evaluating the performance of BWT as an energy conservation measure. The evaluated periods included those of the baseline, post-installation, and actual performance of the optimizers. An average saving of energy of about 10.46% is recorded in a 5-week reporting period. On this basis, that annual electricity saved is estimated to be 66,447.18 kWh, which is equivalent to the emission of 68.94 metric tons of CO2e. This case study demonstrates in detail how option B of IPMVP can be implemented for BWTs applied on pumping systems. In addition to petrochemical production plants, other industries like textile and clothing sections, which are heavy users of water and electrical energy with fixed loads in the production processes of raw materials, fiber, yarn, and fabric, as well as textile-dyeing and final treatment, could benefit from applying this new technology

A Randomized Controlled Trial of Auricular Transcutaneous Electrical Nerve Stimulation for Managing Posthysterectomy Pain

Background. A patient- and assessor-blinded randomized controlled trial was conducted to examine the effectiveness of auricular transcutaneous electrical nerve stimulation (TENS) in relieving posthysterectomy pain. Method. Forty-eight women who had undergone a total abdominal hysterectomy were randomly assigned into three groups (n = 16 each) to receive either (i) auricular TENS to therapeutic points (the true TENS group), (ii) auricular TENS to inappropriate points (the sham TENS group), or (iii) 20 minutes of bed rest with no stimulation (the control group). The intervention was delivered about 24 hours after the operation. A visual analogue scale was used to assess pain while resting (VAS-rest) and upon huffing (VAS-huff) and coughing (VAS-cough), and the peak expiratory flow rate (PEFR) was assessed before and at 0, 15, and 30 minutes after the intervention. Result. As compared to the baseline, only the true TENS group reported a significant reduction in VAS-rest (P = .001), VAS-huff (P = .004), and VAS-cough (P = .001), while no significant reduction in any of the VAS scores was seen in the sham TENS group (all P > .05). In contrast, a small rising trend was observed in the VAS-rest and VAS-huff scores of the control group, while the VAS-cough score remained largely unchanged during the period of the study. A between-group comparison revealed that all three VAS scores of the true TENS group were significantly lower than those of the control group at 15 and 30 minutes after the intervention (all P < .02). No significant between-group difference was observed in PEFR at any point in time. Conclusion. A single session of auricular TENS applied at specific therapeutic points significantly reduced resting (VAS-rest) and movement-evoked pain (VAS-huff, VAS-cough), and the effects lasted for at least 30 minutes after the stimulation. The analgesic effects of auricular TENS appeared to be point specific and could not be attributed to the placebo effect alone. However, auricular TENS did not produce any significant improvement in the performance of PEFR

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Improving the Energy Efficiency of Petrochemical Plant Operations: A Measurement and Verification Case Study Using a Balanced Wave Optimizer

The Chinese petrochemical industry is facing pressure to meet strict targets of energy consumption and carbon emission reductions. Water pumps are the primary equipment used in most chemical and agrochemical industries sectors since water is commonly used for cooling and heating purposes, but these pumps also consume a large amount of energy. Other uses of water pumps in these industries include producing steam for heating, preparing reaction media or absorptive reagents, rinsing products, and distilling. As for the electrical components of the water pump systems, current technologies of variable frequency drives and superconducting transmission lines are unable to increase the energy efficiency of these systems with a fixed load. However, the Balanced Wave Technology (BWT) is offered as a solution to overcome these limitations. In this report, a case study using a BWT optimizer is conducted on a closed loop water circulation system. Two BWTs are added to the individual motor-controlled section of each pump that is being used on the switchboard. For the first time, a detailed example was provided on how to implement option B of the International Performance Measurement and Verification Protocol (IPMVP) in China by evaluating the performance of BWT as an energy conservation measure. The evaluated periods included those of the baseline, post-installation, and actual performance of the optimizers. An average saving of energy of about 10.46% is recorded in a 5-week reporting period. On this basis, that annual electricity saved is estimated to be 66,447.18 kWh, which is equivalent to the emission of 68.94 metric tons of CO2e. This case study demonstrates in detail how option B of IPMVP can be implemented for BWTs applied on pumping systems. In addition to petrochemical production plants, other industries like textile and clothing sections, which are heavy users of water and electrical energy with fixed loads in the production processes of raw materials, fiber, yarn, and fabric, as well as textile-dyeing and final treatment, could benefit from applying this new technology

Plasma Circulating mRNA Profile for the Non-Invasive Diagnosis of Colorectal Cancer Using NanoString Technologies

Colorectal cancer (CRC) is one of the most prevalent cancers and the second leading cause of cancer deaths in developed countries. Early CRC may have no symptoms and symptoms usually appear with more advanced diseases. Regular screening can identify people who are at increased risk of CRC in order to offer earlier treatment. A cost-effective non-invasive platform for the screening and monitoring of CRC patients allows early detection and appropriate treatment of the disease, and the timely application of adjuvant therapy after surgical operation is needed. In this study, a cohort of 71 plasma samples that include 48 colonoscopy- and histopathology-confirmed CRC patients with TNM stages I to IV were recruited between 2017 and 2019. Plasma mRNA profiling was performed in CRC patients using NanoString nCounter. Normalized data were analyzed using a Mann–Whitney U test to determine statistically significant differences between samples from CRC patients and healthy subjects. A multiple-group comparison of clinical phenotypes was performed using the Kruskal–Wallis H test for statistically significant differences between multiple groups. Among the 27 selected circulating mRNA markers, all of them were found to be overexpressed (gene expression fold change > 2) in the plasma of patients from two or more CRC stages. In conclusion, NanoString-based targeted plasma CRC-associated mRNAs circulating the marker panel that can significantly distinguish CRC patients from a healthy population were developed for the non-invasive diagnosis of CRC using peripheral blood samples

Freshwater Microscopic Algae Detection Based on Deep Neural Network with GAN-Based Augmentation for Imbalanced Algal Data

Identifying and quantifying algal genera in images are crucial for understanding their ecological impact. Algal data are often imbalanced, limiting detection model accuracy. This paper presents a novel data augmentation method using StyleGAN2-ADA to enhance algal image instance segmentation. StyleGAN2-ADA generates artificial single-algal images to address data scarcity and imbalance. We train a Cascaded Mask R-CNN with Swin Transformer on a combined data set of real and artificial multigenera algal images and evaluate performance using the COCO mAP metric. The approach improves bounding box detection performance by 17.9% on all genera and 32.1% on rare genera compared with the baseline model. Additionally, 50% more artificial data yield significant enhancements without excessive artificial data use. The GAN-based augmentation technique shows a performance improvement in both Swin-Tiny and ResNet-50 backbone models, suggesting adaptability for various machine learning models. The increased mAP leads to the accurate identification of harmful algae genera, allowing for better prevention and mitigation. This method offers a superior data augmentation solution for accurate algal instance segmentation and can benefit applications challenged by imbalanced and scarce data