Optimal Balance Research Articles

Are the Bayesian Information Criterion (BIC) and the Akaike Information Criterion (AIC) Applicable in Determining the Optimal Fit and Simplicity of Mechanistic Models?

ABSTRACT Over the past three decades, the discourse on the mechanistic approach to scientific modelling and explanation has notably sidestepped the topic of simplicity and fit within the process of model selection. This paper aims to rectify this disconnect by delving into the topic of simplicity and fit within the context of mechanistic explanations. More precisely, our primary objective is to address whether simplicity metrics hold any significance within mechanistic explanations. If they do, then our inquiry extends to the suitability of the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), and related criteria in determining the optimal balance of fit and simplicity of mechanistic models. As our main claims, we argue that mechanistic models inherently lend themselves to considerations of simplicity, and that the AIC and BIC and related criteria are applicable to some submodels of certain kinds of mechanistic models. However, these criteria and related criteria designed for curve fitting and causal modelling are of little help for a comparative assessment of full mechanistic models, and a fundamentally different approach is needed to make determinations of this kind.

Building Energy Governance: Statutes and Guides on Retro-Commissioning in China and the United States

Reducing building energy use, a linchpin of climate change mitigation, is a daunting challenge across the world. Gaining increasing attention, retro-commissioning (RCx) is a systematic process that can improve building energy performance. Using a techno-legal lens to review statutes and guides on RCx, this study reveals that in China, a national standard on building commissioning has taken effect yet RCx statutes are hitherto not found. The United States has RCx statutes enacted over 14 states; scrutinizing the statutes of five cities unveils similarities and differences in their scope of control and compliance requirements. In the absence of a specific RCx statute, the guide of Hong Kong, China provides detailed guidance for energy saving practices. While these findings can serve as reference for other places planning to formulate laws or guidance on RCx, the need to further study the effectiveness of mandating RCx for reducing building energy use is highlighted. A conceptual analysis of cost variation with statutory control, which could help policymakers consider from an economic perspective whether or to what extent statutory RCx requirements should be imposed, is also illustrated. This not only contributes insights to the pursuit of an optimal balance between statutory control and voluntary action for energy reduction but also adds to the debate on building energy policies.

Fracture behavior and constitutive relations of Sn-3.0Ag-0.5Cu solder alloy at cryogenic temperature

The mechanical behavior, underlying fracture mechanism and constitutive relations of Sn-3.0Ag-0.5Cu (SAC305) solder alloy at cryogenic temperature through in-situ uniaxial tensile experiments were investigated over a wide temperature range of 293 K–77 K. The activation of deformation twin in the solder alloy contributes to improve the tensile strength and quasi-static toughness, and maintains the fracture elongation at 35–45% with the decline of ambient temperature. SAC305 solder alloy with a mixed mode of ductile and brittle fracture achieves the optimal balance of strength, ductility and toughness at 123 K, and the large mismatch between twins thickening rate (∼13 μm/s) and dislocation slip velocity (∼3.6 μm/s) finally leads to the brittle fracture at 77 K. In addition, Anand model as a unified viscoplastic constitutive law has been employed to describe the constitutive relations of SAC305 solder alloy and fails in fitting the stress-strain curves at invalid temperature below 233 K. Hollomon equation is conducted to perfectly characterize the constitutive relations of the alloy at temperatures lower than 233 K. The method for controlling the formation of deformation twins in the solder alloy and solder joints is really beneficial to solve the reliability problems for cryogenic electronics.

Covalent Benzenesulfonic Functionalization of a Graphene Nanopore for Enhanced and Selective Proton Transport.

A fundamental understanding of proton transport through graphene nanopores, defects, and vacancies is essential for advancing two-dimensional proton exchange membranes (PEMs). This study employs ReaxFF molecular dynamics, metadynamics, and density functional theory to investigate the enhanced proton transport through a graphene nanopore. Covalently functionalizing the nanopore with a benzenesulfonic group yields consistent improvements in proton permeability, with a lower activation barrier (≈0.15 eV) and increased proton selectivity over sodium cations. The benzenesulfonic functionality acts as a dynamic proton shuttle, establishing a favorable hydrogen-bonding network and an efficient proton transport channel. The model reveals an optimal balance between proton permeability and selectivity, which is essential for effective proton exchange membranes. Notably, the benzenesulfonic-functionalized graphene nanopore system achieves a theoretically estimated proton diffusion coefficient comparable to or higher than the current state-of-the-art PEM, Nafion. Ergo, the benzenesulfonic functionalization of graphene nanopores, firmly holds promise for future graphene-based membrane development in energy conversion devices.

Testing of Portfolio Optimization by Timor-Leste Portfolio Investment Strategy on the Stock Market

An efficient and effective portfolio provides maximum return potential with minimum risk by choosing an optimal balance among assets. Therefore, the objective of this study is to analyze the performance of optimized portfolios in minimizing risk and achieving maximum returns in the dynamics of Timor-Leste’s equity portfolio in the international capital market for the period from January 2006 to December 2019. The empirical findings of this study indicate that the correlation matrix showed that JPM has a very strong positive correlation with one of the twenty assets, namely BAC (0.80). Moreover, the optimal portfolio of the twenty stocks exceeding 10% consists of four consecutive stocks, namely DGE.L (10.69%), NSRGY (10.37%), JPM (10.04%), and T (10.03%). In addition, the minimum portfolio consists of two stocks with a minimum variance of more than 10%, namely SAP.DE (11.20%) and DGE.L (10.39%). The evaluation of the optimal portfolio using Markowitz parameters also showed that the highest expected return and the lowest risk were 1.22% and 3.12%, respectively.

Особенности конструирования портфеля финансовых инструментов на основе оценки бета-коэффициентов

The article focuses on a variant of the development of the classical portfolio theory based on coefficients. The role of beta coefficients in financial decisionmaking is analyzed, and a portfolio optimization option is presented in the form of a linear programming problem with respect to the price shares of financial instruments acting as variables. Special attention is paid to the mathematical approaches underlying portfolio theory. Such approaches include statistical analysis to assess the expected profitability and coefficients of various financial instruments, as well as optimization methods to determine the optimal balance between the profitable and risky characteristics of the portfolio. Due to the choice of various options for the value of the beta coefficient of the portfolio, the fundamental possibility of designing optimal portfolios taking into account investment goals, risk level and desired profitability is demonstrated. Three investment strategies have been formulated based on the inclusion in the portfolio of financial instruments with high coefficient values; inclusion in the portfolio of financial instruments with low coefficient values and inclusion in the portfolio of financial instruments with average coefficient values. Based on real financial data, the differences in financial results resulting from the choice of each of these strategies are demonstrated. From a methodological point of view, the material of the article can be useful for improving the content of mathematical disciplines related to the quantitative justification of financial decisions.

Dynamic models for developing reference scenarios of energy system in the low-carbon transition

The proposed study is aimed at the development of dynamic input-output models in relation to energy development systems. The main task is to find optimal scenarios, defined as sequences of optimal balances between production and capital investment. These models are rooted in Leontief's conceptual concept of input-output, which emphasizes the timing of the introduction of new production systems. The article discusses the economic interpretation and mathematical conditions of intersectoral models, and examines their application to problems related to energy. The model uses the concept of balanced equilibrium growth, in which the ratio of consumption to net release is the same for all resources, and the reserve of at least one resource is fully utilized. The growth rate of the system is the most important parameter that determines the trajectory of balanced growth. Solving the system of inequalities yields balanced growth trajectories in which the dominant root and the associated vector of characteristics plays a key role. A balanced equilibrium growth rate has the properties of a minimax with the presence of a saddle point, which indicates its importance in achieving market equilibrium while preventing a reduction in inventories. The practical application of the model is described. The results of calculations of pessimistic, reference and optimistic scenarios of electricity production in the IPS of Ukraine are presented. Official statistical information and economic forecasts are used, and various restrictions are taken into account. The model aims to minimize the total cost of electricity generation while respecting environmental and operational constraints. The proposed model provides a comprehensive basis for understanding the dynamics of resource reserves, consumption and growth of electricity production of the IPS of Ukraine. It offers decision-makers a valuable tool to optimize electricity generation strategies, taking into account a range of scenarios and constraints, for the sustainable and cost-effective operation of the energy system. Keywords: Dynamic input-output models, optimal scenarios, balanced equilibrium growth, growth rate of the system.

Design of a Generic Dynamically Reconfigurable Convolutional Neural Network Accelerator with Optimal Balance

In many scenarios, edge devices perform computations for applications such as target detection and tracking, multimodal sensor fusion, low-light image enhancement, and image segmentation. There is an increasing trend of deploying and running multiple different network models on one hardware platform, but there is a lack of generic acceleration architectures that support standard convolution (CONV), depthwise separable CONV, and deconvolution (DeCONV) layers in such complex scenarios. In response, this paper proposes a more versatile dynamically reconfigurable CNN accelerator with a highly unified computing scheme. The proposed design, which is compatible with standard CNNs, lightweight CNNs, and CNNs with DeCONV layers, further improves the resource utilization and reduces the gap of efficiency when deploying different models. Thus, the hardware balance during the alternating execution of multiple models is enhanced. Compared to a state-of-the-art CNN accelerator, Xilinx DPU B4096, our optimized architecture achieves resource utilization improvements of 1.08× for VGG16 and 1.77× for MobileNetV1 in inference tasks on the Xilinx ZCU102 platform. The resource utilization and efficiency degradation between these two models are reduced to 59.6% and 63.7%, respectively. Furthermore, the proposed architecture can properly run DeCONV layers and demonstrates good performance.

Magnesium and the Hallmarks of Aging.

Magnesium is an essential ion in the human body that regulates numerous physiological and pathological processes. Magnesium deficiency is very common in old age. Age-related chronic diseases and the aging process itself are frequently associated with low-grade chronic inflammation, called 'inflammaging'. Because chronic magnesium insufficiency has been linked to excessive generation of inflammatory markers and free radicals, inducing a chronic inflammatory state, we formerly hypothesized that magnesium inadequacy may be considered among the intermediaries helping us explain the link between inflammaging and aging-associated diseases. We show in this review evidence of the relationship of magnesium with all the hallmarks of aging (genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, disabled autophagy, dysbiosis, and chronic inflammation), which may positively affect the human healthspan. It is feasible to hypothesize that maintaining an optimal balance of magnesium during one's life course may turn out to be a safe and economical strategy contributing to the promotion of healthy aging. Future well-designed studies are necessary to further explore this hypothesis.

Oil Palm Leaves Phenotyping using Biomarkers Derived from Raman Spectra

The efficient production of oil from oil palm trees is heavily dependent on their health status, reflected in the oil extraction rate (OER). The 17th frond of the oil palm trees contains a significant amount of organic compounds that directly influence the overall health of the tree. Achieving an optimal balance of essential nutrients such as nitrogen (N), phosphorus (P), and potassium (K) is crucial for classifying a tree as healthy, as it results in an increased oil to bunch and fruit to bunch ratio. To accurately assess the health level of oil palm trees, this study explores the application of Raman spectroscopy, a non-invasive technique in determining the molecular fingerprint of an organic sample. In this research, Raman spectroscopy is employed to determine the health level of oil palm trees, and a machine learning-based health level classification algorithm is developed. The algorithm analyzes the organic compounds found in oil palm leaves, which were collected from 20 different trees. The extracted spectral features from these leaves are used to classify them into two health levels: healthy and not healthy. For this purpose, 31 machine learning models are tested to identify the most accurate classifier. The findings reveal that the Tree and fine K-Nearest Neighbors (KNN) classifier demonstrates the highest overall accuracy of 95% using three significant features, namely the Raman intensity, Full Width at Half Maximum (FWHM), and area under the curve. This result signifies the potential of Raman spectroscopy as a reliable and promising method for non-invasively phenotyping oil palm leaves, enabling precise prediction of the health status of oil palm trees.

Response to comment on 'The clinical pharmacology of tafenoquine in the radical cure of Plasmodium vivax malaria: An individual patient data meta-analysis'.

In our recent paper on the clinical pharmacology of tafenoquine (Watson et al., 2022), we used all available individual patient pharmacometric data from the tafenoquine pre-registration clinical efficacy trials to characterise the determinants of anti-relapse efficacy in tropical vivax malaria. We concluded that the currently recommended dose of tafenoquine (300 mg in adults, average dose of 5 mg/kg) is insufficient for cure in all adults, and a 50% increase to 450 mg (7.5 mg/kg) would halve the risk of vivax recurrence by four months. We recommended that clinical trials of higher doses should be carried out to assess their safety and tolerability. Sharma and colleagues at the pharmaceutical company GSK defend the currently recommended adult dose of 300 mg as the optimum balance between radical curative efficacy and haemolytic toxicity (Sharma et al., 2024). We contend that the relative haemolytic risks of the 300 mg and 450 mg doses have not been sufficiently well characterised to justify this opinion. In contrast, we provided evidence that the currently recommended 300 mg dose results in sub-maximal efficacy, and that prospective clinical trials of higher doses are warranted to assess their risks and benefits.

Tailoring precipitate distribution in 2024 aluminum alloy for improving strength and corrosion resistance

For the traditional peak-aged (PA) AA2024 alloy, the formation of large S-phase precipitates within the grains, wide precipitate-free zones (PFZs) near the grain boundaries (GBs), and continuous distribution of grain boundary precipitates (GBPs) can be observed. As a result, the PA alloy exhibits relatively high strength but poor corrosion resistance. However, with the application of cyclic plasticity treatment, high-density 1–2 nm clusters form within the matrix, and no PFZs form near GBs. In this study, this treatment yields the optimal balance between strength–elongation characteristics and corrosion resistance. By combining cyclic plasticity and ageing heat treatment with different heating rates, the nanoscale clusters play a crucial role as heterogeneous nucleation sites, resulting in the formation of finer and higher number density of S precipitates within the matrix. Additionally, the presence of these clusters reduces the formation of GBPs and minimizes the width of PFZs. Consequently, compared to the traditional PA sample, this approach achieves a significantly higher yield strength (increased by 46 %) and ultimate tensile strength (increased by 18 %), along with superior corrosion resistance. Although the influence of ageing heat treatment with different rates on mechanical properties is not significant, it notably affects the formation of GBPs and corrosion resistance. Specifically, a slower heating rate leads to an increase in the spacing between adjacent GBPs, resulting in improved corrosion resistance. In summary, cyclic strengthening, as a novel method for alloy strengthening, when combined with ageing heat treatment, modulates the distribution of S precipitates within the matrix and GBs. This optimization maximizes the effects of precipitation strengthening and breaks the inverse relationship between strength and corrosion resistance.

Enhancing multiplication efficiency: Harnessing Booth algorithm and Wallace tree synergy for 32-bit signed multipliers

This paper focuses on exploring performance optimization strategies for 32-bit signed multipliers in the realm of digital computation. The ingenious combination of the Booth algorithm and the Wallace tree takes center stage as the core of this research. Through a thorough analysis of this combined technique, the paper unveils its multifaceted advantages in multiplication operations. The unique contribution of the Booth algorithm is elaborately discussed, which involves streamlining the multiplication process by reducing the number of addition operations. Subsequently, the exceptional performance of the Wallace tree in accelerating the merging of partial products is highlighted. Through the synergistic interplay of these two techniques, the efficiency of multiplication operations is significantly enhanced, particularly suited for domains necessitating high-speed arithmetic computations, such as graphics processing and digital signal processing. The paper delves further into the significance of optimizing resource utilization, particularly in the field of integrated circuit design. By minimizing addition operations and optimizing parallel processing, the complexity of hardware implementation is reduced, leading to a notable decrease in resource requirements. This advantage proves invaluable in modern integrated circuit design, aiding designers in striking an optimal balance between spatial efficiency and power consumption.

Unraveling the dynamics of hepatitis C virus adaptive mutations and their impact on antiviral responses in primary human hepatocytes.

Hepatitis C virus (HCV) infection remains a global health burden with 58 million people currently chronically infected. However, the detailed molecular mechanisms that underly persistence are incompletely defined. We utilized a long-term cell culture-adapted HCV, exhibiting enhanced replicative fitness in different human liver cell lines, in order to identify molecular principles by which HCV optimizes its replication fitness. Our experimental data revealed that cell culture adaptive mutations confer changes in the host response and usage of various host factors. The latter allows functional flexibility at different stages of the viral replication cycle. However, increased replicative fitness resulted in an increased activation of the innate immune system, which likely poses boundary for functional variation in authentic hepatocytes, explaining the observed attenuation of the adapted virus population in primary hepatocytes.

Artificial intelligence applied in water optimization in agricultural crops (OTIMAGRI)

This study introduces an innovative optimization system for agriculture, utilizing the Particle Swarm Optimization (PSO) algorithm. This system focuses on maximizing net revenue in agricultural contexts while simultaneously minimizing the consumption of natural resources and inputs, with particular attention to the efficient use of water. A distinctive feature of the system is its versatility and accessibility, being designed for easy implementation on smartphones, which broadens its reach to a variety of users, from small to large-scale farmers. The efficiency and speed in obtaining results are key aspects of this system, facilitating a more agile and informed decision-making process in the agricultural sector. The PSO algorithm, which forms the basis of the system, effectively identifies the optimal balance between input consumption and crop productivity. This study validated the system through comparisons with available literature data, focusing on specific crops such as iceberg lettuce and melon. The results not only showed consistency with existing data but in some cases, exceeded expectations. In conclusion, this system represents a significant contribution to modern agriculture, offering a reliable and easily accessible tool for economic decision-making. The ability to quickly adapt to different types of inputs, compatibility with mobile devices, and the ease of incorporating new production functions, regardless of complexity or the number of inputs, highlight the flexibility and practical relevance of this technological innovation.

Simplifying the injector's armamentarium: An international consensus regarding the use of gel science to differentiate hyaluronic acid fillers and guide treatment recommendations.

The Restylane portfolio of soft tissue fillers spans a wide range of indications, due in part to their complementary manufacturing technologies [non-animal stabilized hyaluronic acid (NASHA) and Optimal Balance Technology (OBT/XpresHAn)]. Using an array of products, injectors can achieve a holistic, natural looking effect for their patients. However, with a wide range of products it may be difficult to choose an optimal combination. Simplify and align global use recommendations for NASHA versus OBT products. Two pre-meeting surveys were completed by 11 key opinion leaders with international representation, with the goal of collecting information regarding their current injection practices for various anatomical regions of the face (i.e., temporal region, forehead, tear trough, lateral zygoma, anteromedial cheek, nose, pyriform aperture, nasolabial fold, perioral area, lips, labiomental crease, marionette lines, chin, and jawline). The data collected from these surveys was subsequently discussed in a consensus group meeting involving 11 voting members and 3 nonvoting members. Top product recommendations were identified for each anatomical area, along with secondary and tertiary recommendations that can also be used under defined circumstances. Recommendations were provided based on a consideration of elements such as patient features (e.g., skin thickness, bone structure), the desired aesthetic outcome, experience of the injector, and the preferred injection technique. A majority consensus regarding the top NASHA versus OBT product choice for each anatomical region of the face was reached. These recommendations represent international agreement regarding the use of Restylane products.

Managing the exploitation/exploration paradox: the role of digital transformation

ABSTRACT Ambidexterity, characterized by persistent tensions between exploration and exploitation, requires dynamic management. This study explores the impact of digital transformation (DT) on balancing these elements, revealing an inverted U-shaped relationship between exploration proportion in innovation ambidexterity and performance; as firms advance in DT, the optimal balance point between exploration and exploitation shifts towards exploitation.

Screening for sarcopenia with SARC-F in older patients hospitalized with cardiovascular disease.

SARC-F ≥ 4 points are used for detecting sarcopenia; however, finding a lower SARC-F cut-off value may lead to early detection of sarcopenia. We investigated the SARC-F score with the highest sensitivity and specificity values to identify sarcopenia in older patients with cardiovascular disease (CVD). Motor performances were also examined for each SARC-F score. This retrospective cross-sectional study examined the sensitivity and specificity of every 1-point increase in the SARC-F score to predict sarcopenia. Eligible participants included patients with CVD (≥65 years old) who were admitted for acute CVD treatment and participated in cardiac rehabilitation. Patients completed the SARC-F questionnaire and the sarcopenia assessment. Area under the curves (AUCs) were investigated for the ability to predict sarcopenia. Multivariable linear regression was used to compare the mean value of physical functions (e.g. walking speed, leg strength, and 6 min walking distance) of each SARC-F score. A total of 1066 participants (63.8% male; median age: 76 years) were included. Sarcopenia was present in 401 patients. A SARC-F cut-off ≥2 presented the optimal balance between sensitivity (68.3%) and specificity (55.6%) to detect sarcopenia (AUCs = 0.658; 95% confidence interval: 0.625-0.691). When the patients had low scores (1-3), every 1 point increase in the SARC-F score was associated with lower physical functions such as lower muscle strength and shorter walking distance (all P < 0.001). A SARC-F cut-off ≥2 was optimal for screening sarcopenia, and even a low SARC-F score is useful in detecting sarcopenia and low physical function at an early stage in patients with CVD.

Predictability of implant sizes during cruciate-retaining total knee arthroplasty using an image-free hand-held robotic system.

The use of appropriately sized implants is critical for achieving optimal gap balance following total knee arthroplasty (TKA). Inappropriately sized implants could result in several complications. Robot-assisted TKA (RA-TKA) using CT-based pre-operative planning predicts implant sizes with high accuracy. There is scant literature describing the accuracy of image-free RA-TKA in predicting implant sizes. The purpose of this study was to assess the accuracy of an image-free robotic system in predicting implant sizes during RA-TKA. Patients who underwent cruciate-retaining RA-TKA for primary osteoarthritis, using an image-free hand-held robotic system were studied. The predicted and implanted sizes of the femoral component, tibial component and polyethylene insert, for 165 patients, were recorded. Agreement between robot-predicted and implanted component sizes was assessed in percentages, while reliability was assessed using Cohen's weighted kappa coefficient. The accuracy of the robotic system was 63% (weighted-kappa = 0.623, P < 0.001), 94% (weighted-kappa = 0.911, P < 0.001) and 99.4% (weighted-kappa = 0.995, P < 0.001), in predicting exact, ± 1 and ± 2 sizes of the femoral component, respectively. For the tibial component, an accuracy of 15.8% (weighted-kappa = 0.207, P < 0.001), 55.8% (weighted-kappa = 0.378, P < 0.001) and 76.4% (weighted-kappa = 0.568, P < 0.001) was noted, for predicting exact, ± 1 and ± 2 sizes respectively. An accuracy of 88.5%, 98.2% and 100%, was noted for predicting exact, ± 1 and ± 2 sizes of the polyethylene insert respectively. Errors in predicting accurate implant sizes could be multi-factorial. Though the accuracy of image-free RA-TKA with respect to alignment and component positioning is established, the surgeon's expertise should be relied upon while deciding appropriate implant sizes.

Determinants of Work life Balance on Lecturer Performance mediated by Work Engagement

In a dynamic and demanding academic environment, achieving optimal work-life balance is crucial for the well-being and performance of faculty members. This research investigates the determinants of work-life balance among lecturers and explores the mediating role of work engagement in influencing lecturer performance. The study employs a quantitative method with a systematic review. A questionnaire-based survey was designed to test the model based on a dataset from 98 private lecturers in Banten. The partial results indicate that Work-Life Balance (WLB) and Work Engagement (WE) have a positive and significant impact on Lecturer Performance (EP). The research also reveals that WE plays a crucial mediating role, influencing the relationship between work-life balance and lecturer performance. This study is one of the few that explores the interconnections among WLB, Lecturer Performance, and Work Engagement (WE) as a crucial mediating variable.