Alpha-GPT 2.0: Human-in-the-Loop AI for Quantitative Investment

Recently, we introduced a new paradigm for alpha mining in the realm of quantitative investment, developing a new interactive alpha mining system framework, Alpha-GPT. This system is centered on iterative Human-AI interaction based on large language models, introducing a Human-in-the-Loop approach to alpha discovery. In this paper, we present the next-generation Alpha-GPT 2.0 \footnote{Draft. Work in progress}, a quantitative investment framework that further encompasses crucial modeling and analysis phases in quantitative investment. This framework emphasizes the iterative, interactive research between humans and AI, embodying a Human-in-the-Loop strategy throughout the entire quantitative investment pipeline. By assimilating the insights of human researchers into the systematic alpha research process, we effectively leverage the Human-in-the-Loop approach, enhancing the efficiency and precision of quantitative investment research

Fault diagnosis for hydraulic pump based on EEMD-KPCA and LVQ

Hydraulic pump is regarded as the heart of hydraulic system. Achieving the real-time fault diagnosis of hydraulic pump is of great importance for the maintenance of the entire system. An accurate fault clustering solution with self-adaptive signal processing is needed for extracting performance degradation information hidden in the nonlinear and non-stationary signals of hydraulic pumps. Therefore, a fault diagnosis approach based on ensemble empirical mode decomposition (EEMD), kernel principal component analysis (KPCA), and learning vector quantization (LVQ) network is proposed in this study. First, EEMD is employed to acquire more significant intrinsic mode functions (IMFs), thus overcoming the drawback of empirical mode decomposition, and further extracting the energy values of each IMF to form the feature vector. Second, KPCA, a nonlinear dimension reduction method, is used to remove redundancies of the extracted feature vector for high accuracy of fault diagnosis. Finally, LVQ is employed to classify faults based on the reduced feature vector. The efficiency and accuracy of the proposed method is validated by a case study based on the vibration dataset of a plunger pump

A system dynamics model for urban taxi price simulation

Urban taxi services have been developing year on year, playing an increasingly important role in the economy and the transportation markets of each city. This increases interest in measuring their performance. This paper analysed the relationship among the four stakeholders (including administrative department, operational companies, taxi drivers and customers) for urban taxi passenger transport system in China, and applied System Dynamics (SD) model to explore the dynamic characteristics of urban taxi price system. The main achievements of this paper are as follows, firstly, this paper adopted stakeholder mapping to describe the relationships among the four stakeholders. Then analysed the causal flow diagrams and the different variables of urban taxi passenger transport system operation, and presented the SD model, which considers factors that affect the taxi operation. With the combination of taxi operation data of Harbin city, we simulated eleven urban taxi operation scenarios and proposed kinds of suggestions to improve urban taxi passenger transport system operation, which can provide a good basis for recommending policy decisions for urban taxi market

Development and Characterization of Supercooled Polyethylene Naphthalate

The utilization of undercooled or supercooled polymers presents a promising approach for the creation of single-polymer composites (SPCs), applicable not only to compaction processing but also to extrusion, injection molding, and 3D printing techniques. This study focuses on the development and characterization of supercooled polyethylene naphthalate (PEN) through differential scanning calorimetry (DSC) and rheological measurements. By employing predetermined conditions, a supercooling degree of 50 ˚C for PEN was achieved. The impact of maximum heating temperature, cooling rate, and shear rate on the supercooling degree was examined, revealing that higher supercooling degrees of PEN can be attained by increasing these factors. Additionally, the flow behavior of supercooled polymer melts at various temperatures was analyzed. The supercooling state of PEN exhibited remarkable stability for a minimum duration of half an hour at temperatures exceeding 250 ˚C

Systematic Analysis of Impact of Sampling Regions and Storage Methods on Fecal Gut Microbiome and Metabolome Profiles.

The contribution of human gastrointestinal (GI) microbiota and metabolites to host health has recently become much clearer. However, many confounding factors can influence the accuracy of gut microbiome and metabolome studies, resulting in inconsistencies in published results. In this study, we systematically investigated the effects of fecal sampling regions and storage and retrieval conditions on gut microbiome and metabolite profiles from three healthy children. Our analysis indicated that compared to homogenized and snap-frozen samples (standard control [SC]), different sampling regions did not affect microbial community alpha diversity, while a total of 22 of 176 identified metabolites varied significantly across different sampling regions. In contrast, storage conditions significantly influenced the microbiome and metabolome. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles. Sample storage in RNALater showed a significant level of variation in both microbiome and metabolome profiles, independent of the storage or retrieval conditions. The effect of RNALater on the metabolome was stronger than the effect on the microbiome, and individual variability between study participants outweighed the effect of RNALater on the microbiome. We conclude that homogenizing stool samples was critical for metabolomic analysis but not necessary for microbiome analysis. Short-term room temperature storage had a minimal effect on the microbiome and metabolome profiles and is recommended for short-term fecal sample storage. In addition, our study indicates that the use of RNALater as a storage medium of stool samples for microbial and metabolomic analyses is not recommended.IMPORTANCE The gastrointestinal microbiome and metabolome can provide a new angle to understand the development of health and disease. Stool samples are most frequently used for large-scale cohort studies. Standardized procedures for stool sample handling and storage can be a determining factor for performing microbiome or metabolome studies. In this study, we focused on the effects of stool sampling regions and stool sample storage conditions on variations in the gut microbiome composition and metabolome profile

The influence of street layouts and viaduct settings on daily carbon monoxide exposure and intake fraction in idealized urban canyons

Environmental concerns have been raised on the adverse health effects of vehicle emissions in micro-scale traffic-crowded street canyons, especially for pedestrians and residents living in near-road buildings. Viaduct design is sometimes used to improve transportation efficiency but possibly affects urban airflow and the resultant exposure risk, which have been rarely investigated so far. The personal intake fraction (P_IF) is defined as the average fraction of total emissions that is inhaled by each person of a population (1ppm=1×10-6), and the daily carbon monoxide (CO ) pollutant exposure (Et) is estimated by multiplying the average concentration of a specific micro-environment within one day. As a novelty, by considering time activity patterns and breathing rates in various micro-environments for three age groups, this paper introduces IF and Et into computational fluid dynamic (CFD) simulation to quantify the impacts of street layouts (street width/ building height W/H=1, 1.5, 2), source location, viaduct settings and noise barriers on the source-exposure correlation when realistic CO sources are defined. Narrower streets experience larger P_IF (1.51-5.21 ppm) and CO exposure, and leeward-side buildings always attain higher vehicular pollutant exposure than windward-side. Cases with a viaduct experience smaller P_IF (3.25-1.46 ppm) than cases without a viaduct (P_IF=5.21-2.23 ppm) if the single ground-level CO source is elevated onto the viaduct. With two CO sources (both ground-level and viaduct-level), daily CO exposure rises 2.80-3.33 times but P_IF only change slightly. Noise barriers above a viaduct raise concentration between barriers, but slightly reduce vehicular exposure in near-road buildings. Because people spend most of their time indoors, vehicular pollutant exposure within near-road buildings can be 6-9 times that at pedestrian level. Although further studies are still required to provide practical guidelines, this paper provides effective methodologies to quantify the impacts of street/viaduct configurations on human exposure for urban design purpose