Current Portfolio Research Articles

A Comparison of Financial Risk-Tolerance Assessment Methods in Predicting Subsequent Risk Tolerance and Future Portfolio Choices

This study explores the effectiveness of various methods for measuring risk tolerance, with the aim to better understand the risk-taking attitudes and behaviors of financial decision-makers. Using data collected between October 2020 and March 2021, the research investigates three key areas: (a) the stability of risk tolerance over a six-month period, (b) the individual and household characteristics that predict future risk tolerance, and (c) the predictive accuracy of various risk-tolerance assessment methods in relation to portfolio choices made by financial decision-makers. The results show that risk-tolerance scores derived from a psychometrically developed scale provide the most accurate insights into future risk-taking attitudes and portfolio decisions. For those looking for a simple way to assess both current and future risk tolerance and portfolio choices, a stated-preference item can be effective. Although less consistent, a revealed-preference test can also be used to predict risk tolerance and risk-taking behavior. Findings provide guidance for financial decision-makers and financial advisors by comparing the key features of the three primary risk-tolerance assessment methods evaluated in this study. The study also establishes a foundational basis for selecting the most appropriate evaluation approach, based on the variables identified in the findings.

An integrated binary metaheuristic approach in dynamic unit commitment and economic emission dispatch for hybrid energy systems

The current generation portfolio is obligated to incorporate zero-emissions energy sources, predominantly wind and solar, due to the depletion of fossil fuels and the alarming rate of global warming. In the current scenario, power engineers must devise a compromised solution that not only advocates for the adoption of renewable energy sources (RES) but also efficiently schedules all conventional power generation units to balance the increasing load demand while simultaneously minimizing fuel costs and harmful emissions that are currently addressed by Unit Commitment (UC) and Combined Economic Emission Dispatch (CEED) problem solutions. However, the integration of renewable energy resources (RES) further complicates the UC-CEED problem due to their intermittent nature. Recently, metaheuristic algorithms are acquiring momentum in resolving constrained UC-CEED problems due to their improved global solution ability, adaptability, and derivative-free construction. In this research, a computationally efficient binary hybrid version of crow search algorithm and improvised grey wolf optimization is proposed, namely Crow Search Improved Binary Grey Wolf Optimization Algorithm (CS-BIGWO) by inclusion of nonlinear control parameter, weight-based position updating, and mutation approach. Statistical results on standard mathematical functions prove the supremacy of the proposed algorithm over conventional algorithms. Further, a novel optimization strategy is devised by integrating enhanced lambda iteration with the CS-BIGWO algorithm (CS-BIGWO-λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document}) to solve a day-ahead UC-CEED problem of the hybrid energy system incorporating cost functions of RES. For the model, a day-ahead forecast of wind power and solar photovoltaic power is obtained by using the Levy-Flight Chaotic Whale Optimization Algorithm optimized Extreme Learning Machines(LCWOA-ELM). The proposed algorithm is tested for the UC-CEED solution of an IEEE-39 bus system with two distinct cases: (1) without RES integration and (2) with RES integration. Several independent trial runs are executed, and the performance of the algorithms is assessed based on optimal UC schedules, fuel cost, emission quantization, convergence curve, and computational time. For case 1, the proposed algorithm resulted in a percentage reduction of 0.1021% in fuel cost and 0.7995% in emission. In contrast, for test case 2, it resulted in a percentage reduction of 0.12896% in fuel cost and 0.772% in emission with the proposed algorithm. The results validate the dominance of the proposed methodology over existing methods in terms of lower fuel costs and emissions.

Programmed RNA editing with an evolved bacterial adenosine deaminase.

Programmed RNA editing presents an attractive therapeutic strategy for genetic disease. In this study, we developed bacterial deaminase-enabled recoding of RNA (DECOR), which employs an evolved Escherichia coli transfer RNA adenosine deaminase, TadA8e, to deposit adenosine-to-inosine editing to CRISPR-specified sites in the human transcriptome. DECOR functions in a variety of cell types, including human lung fibroblasts, and delivers on-target activity similar to ADAR-overexpressing RNA-editing platforms with 88% lower off-target effects. High-fidelity DECOR further reduces off-target effects to basal level. We demonstrate the clinical potential of DECOR by targeting Van der Woude syndrome-causing interferon regulatory factor 6 (IRF6) insufficiency. DECOR-mediated RNA editing removes a pathogenic upstream open reading frame (uORF) from the 5' untranslated region of IRF6 and rescues primary ORF expression from 12.3% to 36.5%, relative to healthy transcripts. DECOR expands the current portfolio of effector proteins and opens new territory in programmed RNA editing.

Advanced assisted reproduction technologies in endangered mammalian species.

A new synergistic approach of classical conservation strategies combined with advanced assisted reproduction technologies (aART) allows for protection and rescue of endangered keystone species at the brink of extinction, which can help to safeguard complex ecosystems. Reproduction biology and management in mammal species is not only challenging in regards to their diverging sizes, anatomy, and often unknown physiology; it also requires customized training or chemical restraint protocols for safe handling. Besides these general challenges, there are several new assisted reproduction techniques (ART) specifically tailored to critically endangered mammals. The current portfolio of ART in these mammalian taxa is ranging from sexual cycle characterization and manipulation, semen collection and cryopreservation, artificial insemination, biobanking of living cells, oocyte collection, invitro fertilization (IVF), and embryo production, embryo transfer as well as stem cell-derived invitro gametogenesis for generating gametes in culture. The article covers advanced assisted reproduction technologies (aART), success and challenges, as well as ethical implications.

Pathway for a fully renewable power sector of Africa by 2050: Emphasising on flexible generation from biomass

The climate crisis coupled with energy poverty and injustice in Africa requires strategic measures to proffer sustainable solutions. A transition to a defossilised power sector is obtained for Africa by 2050, evolutionarily developed to fulfil the Paris Agreement. With the LUT Energy System Transition Model, the role of biomass in a least-cost power sector for Africa is investigated from 2020 to 2050 in five-year time steps. Techno-economic assumptions of employed technologies are applied. The study considers the current generation portfolio, lifespan of power plant technologies, and the current and future electricity demand to ascertain the best generation mix by 2050. Biomass potential of 334 TWh (17.5%) of the total African biomass potential of 1911 TWh is applied to the African power sector to develop two Best Policy Scenarios: a scenario without bioenergy (BPS-1) and a scenario with bioenergy (BPS-2). The results indicate a positive impact of bioenergy on the power sector: The total generation, total installed capacity, grid utilisation, levelised cost of electricity, and storage output decreased by 8.6%, 8.4%, 12.9%, 10.2%, 47.1% by 2050 respectively in BPS-2 relative to the BPS-1. In addition, flexible generation from biomass offers balancing to enhance variable renewable energy resources integration onto the power sector.

Modeling multi-market coupling effects considering the consumption above quota trading market in renewable portfolio standards: An agent-based perspective

The current renewable portfolio standards (RPS) mechanism implemented in China requires electricity consumers to comply with quota obligations by consuming renewable electricity, purchasing tradeable green certificates (TGCs), or engaging in consumption above quota (CAQ) transactions. However, most existing studies on RPS policy seldom consider the CAQ market and ignore the dynamic interactions among microlevel obligated entities, which limits the model from considering the heterogeneity among obligated entities and weakens the capture of macrolevel emergence properties. To fill this research gap, a novel agent-based model for China's RPS policy is established, in which the microlevel obligated subjects' complex interactions and decision-making process in coordinating three compliance approaches, i.e., electricity consumption, TGC consumption and CAQ transactions, are depicted, and the dynamic macrolevel emergence in the electricity market, TGC market and CAQ market in terms of multimarket coupling trading, multimarket price-linkage, renewable energy electricity diffusion and RPS target compliance are captured. Notably, a genetic algorithm-based training stage is structured to calibrate and stabilize the heterogeneous behavioral parameters of obligated entities. The results illustrate that 1) the existence of the CAQ market in RPS policy can significantly stimulate obligated entities to consume more renewable energy electricity earlier, promote individual and aggregate profits, and improve the overall compliance rate and RPS implementation effectiveness and 2) a combined penalty–reward mechanism with an effective reward interval is highly important for promoting RE consumption diffusion and the effective operation of the CAQ market.

(Invited) Engineering Porous Electrodes for Redox Flow Batteries – Leveraging Computational and Synthetic Platforms

Porous electrodes are critical components in redox flow batteries where they are responsible for multiple critical functions in the cell, such as providing surfaces for electrochemical reactions, an open structure for fluid flow and mass transport, and the conductive scaffold for electronic and thermal conduction. However, our current portfolio of materials is limited to carbon-fiber-based electrodes which are assembled using various mechanical methods (e.g., paper making, weaving, hydro-entangling) resulting in distinct structures such as papers, cloths, and felts (1). These fabrication methods involve multiple complex subprocessing steps impacting the final product cost and limiting the achievable range of electrode properties, which ultimately restricts device performance (2). Thus, there is a need to develop new material sets with precise control over microstructure and surface composition while employing synthetic methods that are compatible with large-scale manufacturing.In this lecture, I will discuss our efforts to design tailored electrodes for redox flow batteries, which hold promise for long-duration stationary energy storage (3). First, I will introduce a pore network modeling framework that captures electrochemical performance in complex microstructures with low computational requirements (4), and then show the coupling of this framework with a genetic algorithm to enable bottom-up electrode design (5). In our most recent effort, we are building topology optimization models of porous electrodes using multi-scale modeling of redox flow batteries, coupling computational macro- and meso-scale models of transport processes constructed using finite element and finite volume methods. We then couple these approaches with upscaling strategies that enable manufacturability of the structures. Second, I will describe a new approach to synthesizing porous electrodes based on non-solvent induced phase separation (NIPS) (6). NIPS is a simple and versatile fabrication method that can be used to synthesize morphologically-diverse electrode microstructures (e.g., isoporous, pore-size gradients, and multimodal porosity) by tuning simple parameters in the polymer solution, such as polymer concentration, solvent type, and temperature. Using a suite of microscopic, spectroscopic, and electrochemical diagnostic tools, I will present synthesis-property-performance relationships of the NIPS electrodes (7). Third and finally, I will highlight our efforts to functionalize porous electrode interfaces with organic molecules to impart targeted functional properties including hydrophilicity, kinetic activity (8), and selectivity (e.g. H2 evolution suppression). References A. Forner-Cuenca, F. R. Brushett, Curr. Opin. Electrochem. 18, 113–122 (2019).C. Minke, U. Kunz, T. Turek, J. Power Sources. 342, 116–124 (2017).M. L. Perry, K. E. Rodby, F. R. Brushett, ACS Energy Lett. 7, 659–667 (2022).M. van der Heijden, R. van Gorp, M. A. Sadeghi, J. Gostick, A. Forner-Cuenca, J. Electrochem. Soc. 169, 040505 (2022).R. van Gorp, M. van der Heijden, M. A. Sadeghi, J. Gostick, A. Forner-Cuenca, Chem. Eng. J. 455, 139947 (2023).C. T. Wan et al., Adv. Mater. 33, 2006716 (2021).R. R. Jacquemond et al., Cell Reports Phys. Sci. 3, 100943 (2022).E. B. Boz, P. Boillat, A. Forner-Cuenca, ACS Appl. Mater. Interfaces. 14, 41883–41895 (2022).

NASA's Use of MBSE and SysML Modeling to Architect the Future of Human Exploration

AbstractOne of the key roles of National Aeronautics and Space Administration (NASA) is to help mitigate the risk and lower expenses associated with space exploration, science, and discovery to the point where industry and international partners are willing and able to profitably take on larger, more complex missions. To do this, the Agency must undertake a transformation to a more modern integrated Digital Engineering approach to mission definition and planning. This paper highlights NASA's journey in understanding what this Digital Engineering Transformation means for the Agency, the benefits of this transformation to human exploration definition and planning, and the benefits to the current Artemis campaign engineering capability portfolio.

Capacidad transmedia de los VTubers: expansión narrativa y de producción de contenidos a partir de la intersección con la cultura fan por parte de la agencia Hololive

The present article proposes to analyze the transmedia capacity of VTubers, content creators, independent or under agencies, who interact with the audience via a virtual 2D or 3D avatar generated by computer graphics and controlled by human movement capture. For the course of this work, through the perspective of a marketing strategy composed of collective construction, the analysis found an opportunity to prove that, through the use of moe sentiments, kawaii aesthetics, and incentives towards the participative culture of other social actors, VTubers have the ability to expand their media market beyond that of their original live streams in media platforms. To prove such a hypothesis, case studies of the current portfolio of cultural products from Hololive, one of the biggest international VTuber agencies, and of the consumer/fan productions of these content creators under the Hololive brand were promoted. Other than proving the initial hypothesis, the results show that the agency’s interface with the consumers/fans, constructed via providing infrastructural and financial incentives by the company, takes it to promising corporate results, indicative that such actions represent the birth of a new transmedia perspective.

Wall-Immobilized Biocatalyst vs. Packed Bed in Miniaturized Continuous Reactors: Performances and Scale-Up.

Sustainable biocatalysis syntheses have gained considerable popularity over the years. However, further optimizations - notably to reduce costs - are required if the methods are to be successfully deployed in a range of areas. As part of this drive, various enzyme immobilization strategies have been studied, alongside process intensification from batch to continuous production. The flow bioreactor portfolio mainly ranges between packed bed reactors and wall-immobilized enzyme miniaturized reactors. Because of their simplicity, packed bed reactors are the most frequently encountered at lab-scale. However, at industrial scale, the growing pressure drop induced by the increase in equipment size hampers their implementation for some applications. Wall-immobilized miniaturized reactors require less pumping power, but a new problem arises due to their reduced enzyme-loading capacity. This review starts with a presentation of the current technology portfolio and a reminder of the metrics to be applied with flow bioreactors. Then, a benchmarking of the most recent relevant works is presented. The scale-up perspectives of the various options are presented in detail, highlighting key features of industrial requirements. One of the main objectives of this review is to clarify the strategies on which future study should center to maximize the performance of wall-immobilized enzyme reactors.

An Escherichia coli-Based Phosphorylation System for Efficient Screening of Kinase Substrates.

Posttranslational modifications (PTMs), particularly phosphorylation, play a pivotal role in expanding the complexity of the proteome and regulating diverse cellular processes. In this study, we present an efficient Escherichia coli phosphorylation system designed to streamline the evaluation of potential substrates for Arabidopsis thaliana plant kinases, although the technology is amenable to any. The methodology involves the use of IPTG-inducible vectors for co-expressing kinases and substrates, eliminating the need for radioactive isotopes and prior protein purification. We validated the system's efficacy by assessing the phosphorylation of well-established substrates of the plant kinase SnRK1, including the rat ACETYL-COA CARBOXYLASE 1 (ACC1) and FYVE1/FREE1 proteins. The results demonstrated the specificity and reliability of the system in studying kinase-substrate interactions. Furthermore, we applied the system to investigate the phosphorylation cascade involving the A. thaliana MKK3-MPK2 kinase module. The activation of MPK2 by MKK3 was demonstrated to phosphorylate the Myelin Basic Protein (MBP), confirming the system's ability to unravel sequential enzymatic steps in phosphorylation cascades. Overall, this E. coli phosphorylation system offers a rapid, cost-effective, and reliable approach for screening potential kinase substrates, presenting a valuable tool to complement the current portfolio of molecular techniques for advancing our understanding of kinase functions and their roles in cellular signaling pathways.

The interplay between product development failures and alliance portfolio properties in the formation of exploration versus exploitation alliances

We investigate the role of product development failure as an important behavioral driver of explorative (vs. exploitative) search in interfirm collaborations. We also suggest that the effect of product development failure on the level of exploration in subsequent alliances hinges on the properties of the firm’s existing alliance portfolio. We suggest and show that the positive association between a firm’s product development failures and the level of exploration alliances is mitigated when the firm faces a high level of relational embeddedness. We also demonstrate that the positive association is amplified when the firm has a low level of technological diversity in its current alliance portfolio. We test our hypotheses using established firms’ alliances in the biopharmaceutical industry and find evidence that supports our arguments.

Production and Immunogenicity Assessment of LTp50: An Escherichia coli-Made Chimeric Antigen Targeting S1- and S2-Epitopes from the SARS-CoV-2/BA.5 Spike Protein.

Subunit vaccines stand as a leading approach to expanding the current portfolio of vaccines to fight against COVID-19, seeking not only to lower costs but to achieve long-term immunity against variants of concern and have the main attributes that could overcome the limitations of the current vaccines. Herein a chimeric protein targeting S1 and S2 epitopes, called LTp50, was designed as a convenient approach to induce humoral responses against SARS-CoV-2. LTp50 was produced in recombinant Escherichia coli using a conventional pET vector, recovering the expected antigen in the insoluble fraction. LTp50 was purified by chromatography (purity > 90%). The solubilization and refolding stages helped to obtain a stable protein amenable for vaccine formulation. LTp50 was adsorbed onto alum, resulting in a stable formulation whose immunogenic properties were assessed in BALB/c mice. Significant humoral responses against the S protein (BA.5 variant) were detected in mice subjected to three subcutaneous doses (10 µg) of the LTp50/alum formulation. This study opens the path for the vaccine formulation optimization using additional adjuvants to advance in the development of a highly effective anti-COVID-19 vaccine directed against the antigenic regions of the S protein, which are less prone to mutations.

Antimicrobial Resistance in Sexually Transmitted Infections: Current Trends

The review article discusses current trends in antibiotic resistance in bacterial and protozoal sexually transmitted infections (STIs). Antimicrobial resistance in STIs has increased significantly in recent decades due to the overuse and misuse of antibiotics, fueled by population migration and the high incidence of STIs worldwide. While emerging cephalosporin-resistant strains of Neisseria gonorrhoeae are one of the most pressing problems in the world, other pathogenic STIs that are resistant to antibiotics, such as Mycoplasma genitalium and Chlamydia trachomatis, are increasingly being reported. The emergence of multidrugresistant strains of bacterial STIs is of particular concern for researchers. The emerging global crisis in STI treatment is the result of neglect and inattention to repeated warnings from researchers about the emergence of STI strains resistant to the existing antibiotics, as well as shifting priorities in the pharmaceutical industry, which limited the development of new antibiotics. The current antimicrobial portfolio does not provide cause for optimism, as it contains few new antibiotics, and most developments are in the early stages of clinical trials. Experts have suggested that the failure of existing STI treatment regimens is largely inevitable and have called for the creation of entirely new classes of antimicrobial drugs that would take decades to develop. Currently, there are several promising alternative strategies for the treatment of antibiotic-resistant STIs. The use of phage therapy, antimicrobial peptides, and hydrolytic enzymes are particularly promising directions.

Snakebite drug discovery: high-throughput screening to identify novel snake venom metalloproteinase toxin inhibitors.

Snakebite envenoming results in ∼100,000 deaths per year, with close to four times as many victims left with life-long sequelae. Current antivenom therapies have several limitations including high cost, variable cross-snake species efficacy and a requirement for intravenous administration in a clinical setting. Next-generation snakebite therapies are being widely investigated with the aim to improve cost, efficacy, and safety. In recent years several small molecule drugs have shown considerable promise for snakebite indication, with oral bioavailability particularly promising for community delivery rapidly after a snakebite. However, only two such drugs have entered clinical development for snakebite. To offset the risk of attrition during clinical trials and to better explore the chemical space for small molecule venom toxin inhibitors, here we describe the first high throughput drug screen against snake venom metalloproteinases (SVMPs)-a pathogenic toxin family responsible for causing haemorrhage and coagulopathy. Following validation of a 384-well fluorescent enzymatic assay, we screened a repurposed drug library of 3,547 compounds against five geographically distinct and toxin variable snake venoms. Our drug screen resulted in the identification of 14 compounds with pan-species inhibitory activity. Following secondary potency testing, four SVMP inhibitors were identified with nanomolar EC50s comparable to the previously identified matrix metalloproteinase inhibitor marimastat and superior to the metal chelator dimercaprol, doubling the current global portfolio of SVMP inhibitors. Following analysis of their chemical structure and ADME properties, two hit-to-lead compounds were identified. These clear starting points for the initiation of medicinal chemistry campaigns provide the basis for the first ever designer snakebite specific small molecules.

Natural Fractures Help Unlock Tight Carbonates in Oman

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 211336, “Natural Fractures Help Unlock Tight Carbonates: Redeveloping the Natih B Reservoir in a Giant Field in the Sultanate of Oman,” by Loic Bazalgette, Nawal Aamri, SPE, and Chris Field, Petroleum Development Oman, et al. The paper has not been peer reviewed. _ Within the stratigraphy of one of the largest fields in north Oman is the Natih B reservoir. The development of the reservoir has undergone several challenges over the past decades because of the complexity of the reservoir setting and difficulties in locating the natural fractures. Success in developing such tight carbonates depends on the integration of high-quality seismic, borehole imagery, petrophysics, and dynamic data. The objective of the complete paper is to develop an integrated technical approach that can be used to unlock one of the largest undeveloped resources in the operator’s current portfolio. Introduction With approximately 1 billion bbl of oil originally in place in the development area of interest, Natih B is a significant undeveloped resource in the operator’s portfolio. Attempts were made during the 1980s and 1990s to produce from Natih B, but production was uneconomical because of low productivity or early gas breakthrough. The low matrix permeability of Natih B organic-rich carbonates negatively affected the flow of the early Natih B producers, but the presence of large-scale, vertically persistent fracture corridors and fault-damage zones allowed gas from the Natih A reservoir above to shortcut into these wells. The opportunity to redevelop Natih B was initiated in late 2018. The initiative involved a tight collaboration between the operator’s fractured-reservoir specialist and subject-matter experts of the structural geology of fractured reservoirs and of carbonate reservoir geology. Overview of Natih B Properties The Natih carbonate reservoir is composed of multiple units named Natih A, B, C, D, E, F, and G from top to bottom. In the field of interest, these are structured as a fault-bounded, northeast-dipping monocline (Fig. 1). In this structure, the reservoir is shallow. The initial reservoir pressure is 61 bar at 400 m true vertical depth subsea (TVDSS). All reservoir units are in pressure communication through cross-cutting fracture corridors and have a common free water level at approximately 550 m TVDSS. Current production is from all reservoir units with the exception of Natih B. In the outcrops of the Salakh Arch area (north Oman), the Natih B unit is divided into five subunits. Under Natih B reservoir conditions, this subdivision scheme can be simplified to four well-correlatable subunits with relatively small thickness variations (Natih B1 to B4). In the area of interest, the subunit thickness is approximately 15 m for B1, 30 m for B2, 10–15 m for B3, and 15–20 m for B4. Facies show a cyclicity of clean limestone and organic-rich layers, which is more pronounced in the B1 and B2 subunits. Natih B4 isolates the Natih B reservoir unit from the underlying Natih C reservoir. Above the free water level, the porosity of Natih B subunits B1, B2, and B3 ranges generally between 0.15 and 0.30. The permeability of Natih B is low and ranges from 0.2 to 5 md, with an average of approximately 1 md.

NOAA National Sea Grant College Program’s Support of Aquaculture and Its Current Aquaculture Investment Portfolio

The NOAA National Sea Grant College Program, through national, state, and territory-​based investments, has a long history of supporting coastal, marine, and Great Lakes aquaculture development in the United States. Since Sea Grant’s inception over 55 years ago, its support of aquaculture has focused on topics that include production methods and systems, nutrition, diseases, physiology, genetics, workforce development and training, processing, food safety, business development, economics and marketing, site selection, permitting, and stock enhancement/​restoration. To summarize Sea Grant’s history of supporting aquaculture, an expert panel was convened in 2019, resulting in the development of 17 aquaculture phylogenies. The advancement of various segments of the US aquaculture industry due to Sea Grant’s support is evident in increasing production of Eastern oysters (Crassostrea virginica) and development of recirculating aquaculture systems. Sea Grant’s investments in aquaculture have also proven to have substantial economic and scholarly impact. While most of Sea Grant’s historical support of aquaculture has been through investments made at the state and territory level, in recent years, the national Sea Grant aquaculture investment portfolio has been expanded significantly, offering innovative and varied funding opportunities, while retaining the ability to be nimble and flexible.

Empirical Research on Optimizing Company Investment Strategy Based on Asset Portfolio Strategy -Taking the Pharmaceutical Industry as an Example

In recent years, the pharmaceutical industry has developed rapidly due to the COVID-19. At the same time, with the development of modern asset theory, a variety of asset portfolio strategies can be used by people. In the capital market, the pharmaceutical industry has also become an emerging ideal investment industry, and various related investment portfolio products and trading methods are constantly being updated and improved. This article is based on modern asset portfolio strategies, through relevant worldwide asset allocation models, sharpe theory and CPAM model, and uses the optimal selection of asset portfolios and market portfolios in Markowitz asset portfolio theory to conduct empirical research on the current stock investment portfolio products in the pharmaceutical industry. To test, use Python and Excel to process and analyze two years of stock data and group assets into groups to test the combination to verify the effectiveness of the model for fund investment portfolios in the pharmaceutical industry and better optimize the asset allocation, thereby effectively avoiding risks and increasing returns.

Machine learning and deep learning for mineralogy interpretation and CO2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin

Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO2) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. The study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.

Climate change transformation in built environments – A policy instrument framework

Built environments are key spaces for social and economic activities. They are critical sources of greenhouse gas emissions and will be important locations for adaptation to climate change impacts. To transform built environments to adequately address climate change, necessary policy instruments must be identified and activated. However, the application of ‘policy instrument’ typologies to empirical research and analysis of the built environment holistically is limited. We present a ‘built environment policy framework’ consisting of a policy instrument typology (strategies, laws, regulations, guidelines, voluntary instruments and programs) and a built environment policy setting (governance level, sector, property type, life stage, timeframe). The framework was tested in an Australian context, and used to map and visually represent built environment policy instruments. The results highlight the suitability of the framework for understanding the policy portfolio of a built environment context. The mapping identified that strategies were the dominant policy instrument. Fewer policy instruments were found to directly address the built environment's later life stages, and there were fewer at federal and international levels of governance. This new framework makes a theoretical contribution to policy instrument development for built environments – by applying a holistic and complex approach. It also makes a practical contribution, to assist built environment professionals and governments assess their current policy instrument portfolio to inform policy development that progresses climate change transformation.