Multi-label prediction method for lithology, lithofacies and fluid classes based on data augmentation by cascade forest

Predicting the lithology, lithofacies and reservoir fluid classes of igneous rocks holds significant value in the domains of CO2 storage and reservoir evaluation. However, no precedent exists for research on the multi-label identification of igneous rocks. This study proposes a multi-label data augmented cascade forest method for the prediction of multilabel lithology, lithofacies and fluid using 9 conventional logging data features of cores collected from the eastern depression of the Liaohe Basin in northeastern China. Data augmentation is performed on an unbalanced multi-label training set using the multi-label synthetic minority over-sampling technique. Sample training is achieved by a multi-label cascade forest consisting of predictive clustering trees. These cascade structures possess adaptive feature selection and layer growth mechanisms. Given the necessity to focus on all possible outcomes and the generalization ability of the method, a simulated well model is built and then compared with 6 typical multi-label learning methods. The outperformance of this method in the evaluation metrics validates its superiority in terms of accuracy and generalization ability. The consistency of the predicted results and geological data of actual wells verifies the reliability of our method. Furthermore, the results show that it can be used as a reliable means of multi-label prediction of igneous lithology, lithofacies and reservoir fluids.Document Type: Original articleCited as: Han, R., Wang, Z., Guo, Y., Wang, X., A, R., Zhong, G. Multi-label prediction method for lithology, lithofacies and fluid classes based on data augmentation by cascade forest. Advances in Geo-Energy Research, 2023, 9(1): 25-37. https://doi.org/10.46690/ager.2023.07.0

Mitigating Pooling Bias in E-commerce Search via False Negative Estimation

Efficient and accurate product relevance assessment is critical for user experiences and business success. Training a proficient relevance assessment model requires high-quality query-product pairs, often obtained through negative sampling strategies. Unfortunately, current methods introduce pooling bias by mistakenly sampling false negatives, diminishing performance and business impact. To address this, we present Bias-mitigating Hard Negative Sampling (BHNS), a novel negative sampling strategy tailored to identify and adjust for false negatives, building upon our original False Negative Estimation algorithm. Our experiments in the Instacart search setting confirm BHNS as effective for practical e-commerce use. Furthermore, comparative analyses on public dataset showcase its domain-agnostic potential for diverse applications.Comment: Submitted to WWW'24 Industry Trac

LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models

The carbon footprint associated with large language models (LLMs) is a significant concern, encompassing emissions from their training, inference, experimentation, and storage processes, including operational and embodied carbon emissions. An essential aspect is accurately estimating the carbon impact of emerging LLMs even before their training, which heavily relies on GPU usage. Existing studies have reported the carbon footprint of LLM training, but only one tool, mlco2, can predict the carbon footprint of new neural networks prior to physical training. However, mlco2 has several serious limitations. It cannot extend its estimation to dense or mixture-of-experts (MoE) LLMs, disregards critical architectural parameters, focuses solely on GPUs, and cannot model embodied carbon footprints. Addressing these gaps, we introduce \textit{LLMCarbon}, an end-to-end carbon footprint projection model designed for both dense and MoE LLMs. Compared to mlco2, LLMCarbon significantly enhances the accuracy of carbon footprint estimations for various LLMs

Seed Germination Responses to Seasonal Temperature and Drought Stress Are Species‐Specific but Not Related to Seed Size in a Desert Steppe: Implications for Effect of Climate Change on Community Structure

Investigating how seed germination of multiple species in an ecosystem responds to environmental conditions is crucial for understanding the mechanisms for community structure and biodiversity maintenance. However, knowledge of seed germination response of species to environmental conditions is still scarce at the community level. We hypothesized that responses of seed germination to environmental conditions differ among species at the community level, and that germination response is not correlated with seed size. To test this hypothesis, we determined the response of seed germination of 20 common species in the Siziwang Desert Steppe, China, to seasonal temperature regimes (representing April, May, June, and July) and drought stress (0, −0.003, −0.027, −0.155, and −0.87 MPa). Seed germination percentage increased with increasing temperature regime, but Allium ramosum, Allium tenuissimum, Artemisia annua, Artemisia mongolica, Artemisia scoparia, Artemisia sieversiana, Bassia dasyphylla, Kochia prastrata, and Neopallasia pectinata germinated to \u3e60% in the lowest temperature regime (April). Germination decreased with increasing water stress, but Allium ramosum, Artemisia annua, Artemisia scoparia, Bassia dasyphylla, Heteropappus altaicus, Kochia prastrata, Neopallasia pectinata, and Potentilla tanacetifolia germinated to near 60% at −0.87 MPa. Among these eight species, germination of six was tolerant to both temperature and water stress. Mean germination percentage in the four temperature regimes and the five water potentials was not significantly correlated with seed mass or seed area, which were highly correlated. Our results suggest that the species‐specific germination responses to environmental conditions are important in structuring the desert steppe community and have implications for predicting community structure under climate change. Thus, the predicted warmer and dryer climate will favor germination of drought‐tolerant species, resulting in altered proportions of germinants of different species and subsequently change in community composition of the desert steppe

INFLAMMATORY BOWEL DISEASE: CLINICAL FEATURES AND MANIFESTATIONS BEYOND THE BOWEL

Inflammatory bowel disease (IBD) encompasses a spectrum of diseases, with Crohn's disease (CD) and ulcerative colitis (UC) representing the two broadest subtypes of IBD. Multiple extraintestinal manifestations (EIMs) are more frequent in (IBD); 5% –50% of the patients might be affected. The most often implicated sites of manifestations are musculoskeletal and dermatological structures. However, while some symptoms like peripheral arthritis and erythema nodosum correlate with IBD progression, others have their own course of disease like axial arthropathy, gangrenosis of the pioderma and primary sclerosic cholangitis. This review would provide a summary of the most frequent EIMs and their prevalence.                                       Peer Review History: Received 31 May 2020; Revised 7 June; Accepted 4 July, Available online 15 July 2020 Academic Editor: Dr. Muhammad Zahid Iqbal, AIMST University, Malaysia, [email protected] UJPR follows the most transparent and toughest ‘Advanced OPEN peer review’ system. The identity of the authors and, reviewers will be known to each other. This transparent process will help to eradicate any possible malicious/purposeful interference by any person (publishing staff, reviewer, editor, author, etc) during peer review. As a result of this unique system, all reviewers will get their due recognition and respect, once their names are published in the papers. We expect that, by publishing peer review reports with published papers, will be helpful to many authors for drafting their article according to the specifications. Auhors will remove any error of their article and they will improve their article(s) according to the previous reports displayed with published article(s). The main purpose of it is ‘to improve the quality of a candidate manuscript’. Our reviewers check the ‘strength and weakness of a manuscript honestly’. There will increase in the perfection, and transparency. Received file:                Reviewer's Comments: Average Peer review marks at initial stage: 5.5/10 Average Peer review marks at publication stage: 7.0/10 Reviewer(s) detail: Dr. Md. Parwez Ahmad, National Medical College, Birgunj, Nepal, [email protected] Dr. George Zhu, Tehran University of Medical Sciences, Tehran, Iran, [email protected]

PRECIPITATION OF LIGNOSULPHONATES FROM SPORL LIQUID BY CALCIUM HYDROXIDE TREATMENT

Precipitation of lignosulphonates from the liquor for sulfite pretreatment to overcome recalcitrance of lignocellulose (SPORL) by addition of Ca(OH)2 was investigated in this work. The experiment was conducted in a reaction temperature range of 20 to 75oC for 90 minutes with Ca(OH)2 charge varying from 20 to 90 g/L and a range of liquid enrichment ratio of 1 to 5. It was found that increased Ca(OH)2 charge, duration time, reaction temperature, and liquor concentration each tended to improve lignosulphonates precipitation, but tended to hurt fermentable sugars conservation. Application of Ca(OH)2 20 g/L to SPORL liquid without enrichment at 30oC for 90 minutes could be an optimal condition. Under this condition, 25.95% of the lignosulphonates was precipitated for further utilization, while calculated amounts of 106.46% of glucose and 60.25% of xylose were conserved for further fermentation

Defective PrO_x for Efficient Electrochemical NO₂⁻-to-NH₃ in a Wide Potential Range

Electrocatalytic reduction of nitrite (NO2−) is a sustainable and carbon-neutral approach to producing green ammonia (NH3). We herein report the first work on building defects on PrOx for electrochemical NO2− reduction to NH3, and demonstrate a high NH3 yield of 2870 μg h−1 cm−2 at the optimal potential of –0.7 V with a faradaic efficiency (FE) of 97.6% and excellent FEs of >94% at a wide given potential range (−0.5 to −0.8 V). The kinetic isotope effect (KIE) study suggested that the reaction involved promoted hydrogenation. Theoretical calculations clarified that there was an accelerated rate-determining step of NO2− reduction on PrOx. The results also indicated that PrOx could be durable for long-term electrosynthesis and cycling tests

Comparative Study on Immune Function of the Head and Trunk Kidney in Rainbow Trout Responding to IHNV Infection

A teleost’s kidney was divided into head kidney and trunk kidney. The head kidney is an important lymphatic organ, while the trunk kidney mainly performs osmotic pressure regulation and excretion functions. Previous studies have shown that the teleost’s head kidney exerts a strong immune response against pathogen invasion, while the mechanism of immune response in the trunk kidney is still rarely reported. Therefore, in this study, we established an Infectious hematopoietic necrosis virus (IHNV) immersion infection model to compare the similarities and differences of immune response mechanisms between the head kidney and trunk kidney against viral infection. The results showed that IHNV infection causes severe tissue damage and inflammatory reaction in the head and trunk kidney, triggers a series of interferon cascade reactions, and produces strong immune response. In addition, the transcriptome data showed that the head kidney and trunk kidney had similar immune response mechanisms, which showed that the NOD-like receptor signaling pathway and Toll-like receptor signaling pathway were activated. In conclusion, despite functional differentiation, the teleost’s trunk kidney still has a strong immune response, especially the interferon-stimulated genes, which have stronger immune response in the trunk kidney than in the head kidney when responding to IHNV infection. This study contributes to a more comprehensive understanding of the teleost immune system and enriches the theory of kidney immunity in teleosts