Relative Performance Research Articles

Relative Phenotypic Performance of Crossbred Chicken as Step in Synthetic Breed Development in Ethiopia: A Review

The present review article aims to provide and summarize synthesized information regarding some of economically important traits on reproductive and productive performance of crossbred chicken to develop both adaptive and sustainable breed to the intended beneficiaries. Growth traits, egg production traits, reproductive traits and other economically important traits of crossbred chicken were assessed in comparison to their counterparts purebred breed both native and exotic parents. In the majority of crossbreeding studies, the hybrids surpassed the original native parental breeds in various traits studied, including body weight, feed conversion ratio, age at first egg, egg production, egg weight, and egg mass. The majority of hybrids achieved sexual maturity at an earlier age, laid more eggs, and produced a greater egg mass when compared to local chickens. Eggs from the hybrids were also heavier than those from the local chickens in certain crossbreeding experiments. In overall, crossbred chickens that combine the blood of exotic and local breeds tend to perform relatively better than indigenous chickens, which are typically characterized in low production due genetics. The frequent production of F1 crossbred demands in subsequent importation of exotic parent due to produced offspring chicken are terminal genetically. Also, the degree of heterosis retained in the crossbred decreased as generation increased due recombinant ad segregations effects. To overcome such problem producing adaptive and sustainable chicken breed through synthetic breeding is crucial for developing countries like Ethiopia.

The power of relative performance information in competing communications

ABSTRACT The public administration literature has long recognized the importance of reference points in interpreting performance information. However, little is known about whether invoking reference points can change citizens’ perceptions of performance in competitive information environments. Across three survey experiments with Chinese respondents, we showed that providing informational cues about China outperforming other countries improve citizens’ ratings of government performance. Moreover, competing information does not balance the positive effects. Findings from an independent experiment refute the likelihood that the treatment effect is an artefact of demand characteristics, thus strengthening the internal validity of our findings.

The impact of intellectual capital on local authorities performance in property tax reassessment: the mediating role of process innovation

PurposeThis study aims to investigate the factors influencing property tax reassessment performance in West Malaysia. It specifically examines intangible aspects, such as intellectual capital and process innovation among valuation officers. The primary concern in this study is the variability in how effectively local authorities carry out property tax reassessment, with a significant number of them not conducting revaluations regularly.Design/methodology/approachThe data was collected using self-administered and electronic questionnaires using a purposive sampling method. The 154 useable responses were further analysed using partial least squares structural equation modelling in SmartPLS 4.FindingsThe result shows that process innovation mediates the relationship between structural capital and property tax reassessment performance as well as the relationship between relational capital and property tax reassessment performance. This suggests that local authority systems and policies are indirectly related to reassessment practises by introducing new methods of reassessment in the form of administration and technology. The result shows that building good relationships with stakeholders and other institutions encourages staff to develop innovative ideas for their reassessment activities, thus enhance the performance of property tax reassessment.Practical implicationsThe study provides insightful information for local authorities managers and stakeholders in crafting a better policy for periodic property tax reassessment. The study suggests the need for new administration and technological innovation in developing effective property tax reassessment strategies through the integration of organisational structure and relationship building.Originality/valueThe study developed a new model for property tax reassessment performance that incorporates intangible assets with the introduction of process innovation as a mediator.

Performance-Aware Trust Modeling within a Human–Multi-Robot Collaboration Setting

In this study, a novel time-driven mathematical model for trust is developed considering human–multi-robot performance for a Human–Robot Collaboration (HRC) framework. For this purpose, a model is developed to quantify human performance considering the effects of physical and cognitive constraints and factors such as muscle fatigue and recovery, muscle isometric force, human (cognitive and physical) workload, workloads due to the robots’ mistakes, and task complexity. The performance of multi-robot in the HRC setting is modeled based upon the rate of task assignment and completion as well as the mistake probabilities of the individual robots. The human trust in HRC setting with single and multiple robots is modeled over different operation regions, namely unpredictable region, predictable region, dependable region, and faithful region. The relative performance difference between the human operator and the robot is used to analyze the effect on the human operator’s trust in robots’ operation. The developed model is simulated for a manufacturing workspace scenario considering different task complexities and involving multiple robots to complete shared tasks. The simulation results indicate that for a constant multi-robot performance in operation, the human operator’s trust in robots’ operation improves whenever the comparative performance of the robots improves with respect to the human operator performance. The impact of robot hypothetical learning capabilities on human trust in the same HRC setting is also analyzed. The results confirm that a hypothetical learning capability allows robots to reduce human workloads, which improves human performance. The simulation result analysis confirms that the human operator’s trust in the multi-robot operation increases faster with the improvement of the multi-robot performance when the robots have a hypothetical learning capability. An empirical study was conducted involving a human operator and two collaborator robots with two different performance levels in a software-based HRC setting. The experimental results closely followed the pattern of the developed mathematical models when capturing human trust and performance in terms of human–multi-robot collaboration.

Local adaptation, plasticity, and evolved resistance to hypoxic cold stress in high-altitude deer mice.

A fundamental question in evolutionary biology concerns the relative contributions of phenotypic plasticity vs. local adaptation (genotypic specialization) in enabling wide-ranging species to inhabit diverse environmental conditions. Here we conduct a long-term hypoxia acclimation experiment to assess the relative roles of local adaptation and plasticity in enabling highland and lowland deer mice (Peromyscus maniculatus) to sustain aerobic thermogenesis at progressively increasing elevations. We assessed the relative physiological performance capacities of highland and lowland natives as they were exposed to progressive, stepwise increases in hypoxia, simulating the gradual ascent from sea level to an elevation of 6000 m. The final elevation of 6000 m far exceeds the highest attainable elevations within the species' range, and therefore tests the animals' ability to tolerate levels of hypoxia that surpass the prevailing conditions within their current distributional limits. Our results demonstrate that highland natives exhibit superior thermogenic capacities at the most severe levels of hypoxia, suggesting that the species' broad fundamental niche and its ability to inhabit such a broad range of elevational zones is attributable to a combination of genetically based local adaptation and plasticity. Transcriptomic and physiological measurements identify evolved changes in the acclimation response to hypoxia that contribute to the enhanced thermogenic capacity of highland natives.

Adsorption of dihydroxybenzene isomers over Schiff-based network-1-derived nitrogen-enriched carbon: Effective and favorable adsorption of hydroquinone

Urbanization and modernization through intense industrial activity led to the disposal of harmful and non-biodegradable organic substances including dihydroxybenzene isomers such as hydroquinone, catechol, and resorcinol. A covalent-organic polymer Schiff-based network-1, SNW1 was synthesized, pyrolyzed, and subsequently carbonized again, after mixing with KOH, at 800 °C. The obtained carbon, prepared in two-step-carbonization (named as SNW1-2DC), was applied to the adsorption of dihydroxybenzene isomers; showed remarkable performance in hydroquinone adsorption with the maximum adsorption capacity (Q0) of 1060 mg/g at neutral conditions. This Q0 is 6.0 and 5.5 times that of activated carbon and the carbon obtained from the simple pyrolysis of SNW1, respectively; of note, this value represents the highest compared to any previously reported findings. Moreover, the regenerated adsorbent, with simple ethanol washing, performed well for up to 5 cycles. This material could be suggested as a promising adsorbent in hydroquinone removal from water. The adsorption mechanism, including hydrogen bonding, could be suggested. Interestingly, the performance of SNW1-2DC in the adsorptive removal of catechol and resorcinol was very low in comparison with that of hydroquinone. The relative adsorption performances of SNW1-2DC for dihydroxybenzene isomers could be explained with density functional theory calculation and thermodynamic parameters. The most favorable hydroquinone adsorption (among the three dihydroxybenzene isomers) over SNW1-2DC might be because of less endothermic adsorption and more effective H-boning interaction between hydroquinone and SNW1-2DC than that between catechol or resorcinol and the adsorbent.

Crowdfunding performance prediction using feature‐selection‐based machine learning models

AbstractBackgroundCrowdfunding is increasingly favoured by entrepreneurs for online financing. Predicting crowdfunding success can provide valuable guidance for stakeholders. It is a new attempt to evaluate the relative performance of different machine learning algorithms for crowdfunding prediction.ObjectivesThis study aims to identify the key factors of crowdfunding, and find the different performance and usage of machine learning algorithms for crowdfunding prediction.MethodWe crawled data from MoDian.com, a Chinese crowdfunding platform, and predicted the crowdfunding performance using four machine learning algorithms, which is a new exploration in this area. Most of the existing literature focuses on empirical analysis. This work solves the problem of predicting crowdfunding performance using a dataset with a minimal number of highly contributive features, which has higher accuracy compared to the regression analysis.ResultsThe experiment results show that feature‐selection‐based machine learning models are effective and beneficial in crowdfunding prediction.ConclusionFeature selection can significantly improve the prediction performance of the machine learning models. KNN achieved the best prediction results with five features: number of backers, target amount, number of project likes, number of project comments, and sponsor fans. The prediction accuracy was improved by 16%, the precision was improved by 13.23%, the recall was improved by 22.66%, the F‐score was improved by 18.48%, and the AUC was improved by 14.9%.

Contributing factors for reduction in maternal mortality ratio in India

Maternal mortality ratio (MMR) estimates have been studied over time for understanding its variation across the country. However, it is never sufficient without accounting for presence of variability across in terms of space, time, maternal and system level factors. The study endeavours to estimate and quantify the effect of exposures encompassing all maternal health indicators and system level indicators along with space–time effects influencing MMR in India. Using the most recent level of possible -factors of MMR, maternal health indicators from the National Family Health Survey (NFHS: 2019–21) and system level indicators from government reports a heatmap compared the relative performance of all 19 SRS states. Facet plots with a regression line was utilised for studying patterns of MMR for different states in one frame. Using Bayesian Spatio-temporal random effects, evidence for different MMR patterns and quantification of spatial risks among individual states was produced using estimates of MMR from SRS reports (2014–2020). India has witnessed a decline in MMR, and for the majority of the states, this drop is linear. Few states exhibit cyclical trend such as increasing trends for Haryana and West Bengal which was evident from the two analytical models i.e., facet plots and Bayesian spatio- temporal model. Period of major transition in MMR levels which was common to all states is identified as 2009–2013. Bihar and Assam have estimated posterior probabilities for spatial risk that are relatively greater than other SRS states and are classified as hot spots. More than the individual level factors, health system factors account for a greater reduction in MMR. For more robust findings district level reliable estimates are required. As evident from our study the two most strong health system influencers for reducing MMR in India are Institutional delivery and Skilled birth attendance.

Dynamic Monitoring of Tall Buildings

There has been an increasing demand on tall and high-rise buildings. In response, structural engineers have become more interested in improving the design of these newly constructed buildings as well as extending the life of the existing and aging ones. Field dynamic monitoring is the best method that engineers can rely on to measure the current performance of tall buildings in order to make critical decisions regarding the improvement of their designs or regarding the planning of their retrofitting and maintenance. Radar interferometry is a novel remote monitoring technique that has appeared to be exceptionally suitable for monitoring of tall buildings. However, the performance and capabilities of this system relative to other conventional sensors in not fully understood. This paper reviews the radar system and other commonly used sensors with a focus on their current status and application. A model for evaluating the relative performance of the different sensors for tall buildings is constructed and it demonstrates that the radar has unmatched capabilities for monitoring of high-rise buildings, The comparative case study on the Soul Tower, which is the first of its kind on such high-rise building, further confirms this conclusion.. Consequently, engineers are advised to always consider employing the interferometric radar for dynamic monitoring of tall buildings.

Galaxy merger challenge: A comparison study between machine learning-based detection methods

Aims. Various galaxy merger detection methods have been applied to diverse datasets. However, it is difficult to understand how they compare. Our aim is to benchmark the relative performance of merger detection methods based on machine learning (ML). Methods. We explore six leading ML methods using three main datasets. The first dataset consists of mock observations from the IllustrisTNG simulations, which acts as the training data and allows us to quantify the performance metrics of the detection methods. The second dataset consists of mock observations from the Horizon-AGN simulations, introduced to evaluate the performance of classifiers trained on different, but comparable data to those employed for training. The third dataset is composed of real observations from the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) survey. We also compare mergers and non-mergers detected by the different methods with a subset of HSC-SSP visually identified galaxies. Results. For the simplest binary classification task (i.e. mergers vs. non-mergers), all six methods perform reasonably well in the domain of the training data. At the lowest redshift explored 0.1 < ɀ < 0.3, precision and recall generally range between ~70% and 80%, both of which decrease with increasing ɀ as expected (by ~5% for precision and ~10% for recall at the highest ɀ explored 0.76 < ɀ < 1.0). When transferred to a different domain, the precision of all classifiers is only slightly reduced, but the recall is significantly worse (by ~20–40% depending on the method). Zoobot offers the best overall performance in terms of precision and F1 score. When applied to real HSC observations, different methods agree well with visual labels of clear mergers, but can differ by more than an order of magnitude in predicting the overall fraction of major mergers. For the more challenging multi-class classification task to distinguish between pre-mergers, ongoing-mergers, and post-mergers, none of the methods in their current set-ups offer good performance, which could be partly due to the limitations in resolution and the depth of the data. In particular, ongoing-mergers and post-mergers are much more difficult to classify than pre-mergers. With the advent of better quality data (e.g. from JWST and Euclid), it is of great importance to improve our ability to detect mergers and distinguish between merger stages.

Personal protective equipment impacts firefighters' anaerobic fitness.

Personal protective equipment (PPE) is vital for firefighters' safety and effectiveness during daily operations. However, concerns have emerged about its potential impact on firefighters' anaerobic fitness (AF), which is crucial for their operational readiness. The Physical Ability Test (PAT) is used to assess readiness, but there is inconsistency among fire departments regarding whether PAT is conducted with full PPE or regular exercise clothing. This variation in testing conditions may exacerbate the stress on firefighters' AF. To analyse differences in firefighters' AF performance while wearing full PPE compared to regular exercise clothing. We studied two cohorts totalling 62 firefighters from specific fire departments in South Florida. We conducted occupation-specific AF tests, including handgrip dynamometry (HG), vertical jump (VJ), Margaria-Kalamen (MK), and a 300-yard shuttle run (300YD), both with full PPE (WPPE) and without PPE (NPPE). We adjusted AF variables for body weight (e.g. NPPE) and occupational weight (e.g. WPPE) and used a repeated-measures design in Jamovi (P < 0.05). Wearing WPPE significantly reduced relative HG strength by 59%, VJ peak power by 11%, and MK mean power by 49%, while increased 300YD completion time by 18%. The study reveals that PPE substantially impairs firefighters' anaerobic performance during occupation-specific tests. This emphasizes the need for tailored AF training programs to support the anaerobic system and related performance while wearing PPE, acknowledging the significance of occupational specificity in assessing firefighters' fitness components.

Radiomic-based prediction of lesion-specific systemic treatment response in metastatic disease

Despite sharing the same histologic classification, individual tumors in multi metastatic patients may present with different characteristics and varying sensitivities to anticancer therapies. In this study, we investigate the utility of radiomic biomarkers for prediction of lesion-specific treatment resistance in multi metastatic leiomyosarcoma patients. Using a dataset of n=202 lung metastases (LM) from n=80 patients with 1648 pre-treatment computed tomography (CT) radiomics features and LM progression determined from follow-up CT, we developed a radiomic model to predict the progression of each lesion. Repeat experiments assessed the relative predictive performance across LM volume groups. Lesion-specific radiomic models indicate up to a 4.5-fold increase in predictive capacity compared with a no-skill classifier, with an area under the precision-recall curve of 0.70 for the most precise model (FDR = 0.05). Precision varied by administered drug and LM volume. The effect of LM volume was controlled by removing radiomic features at a volume-correlation coefficient threshold of 0.20. Predicting lesion-specific responses using radiomic features represents a novel strategy by which to assess treatment response that acknowledges biological diversity within metastatic subclones, which could facilitate management strategies involving selective ablation of resistant clones in the setting of systemic therapy.

Wrinkle-free membranes through spatioselective exposure

The extreme flexibility-induced wrinkling significantly hampers the promising engineering applications of membranes, while the existing wrinkling-suppression approaches have challenges for area loss, weight increase and interfacial delamination. Here we propose a facile wrinkle-free technique that enables stiffness modulation through spatioselective ultraviolet (UV) exposure, regulates stress distribution to eliminate compressive stresses and achieves robust wrinkle-free membranes. A small-deformation theoretical model with the Marguerre function is implemented to evaluate the wrinkling capability of a stiffness-modulated membrane, the non-gradient particle swarm optimization (PSO) algorithm is performed to obtain the optimal material distribution, and the related robust wrinkle-free performance is verified through both finite-deformation post-buckling analyses and physical experiments. In addition, an empirical wrinkle-free solution is also given without the requirement of excessive optimization. This wrinkle-free approach, with neither area loss, weight increase nor interfacial delamination, provides useful guidance for the research on wrinkle-free membranes.

Privatization of SOEs and its innovation performance: A reexamination

AbstractThe empirical literature comparing the innovation performance of state‐owned enterprises (SOEs) and private firms in China often yields conflicting results. To shed new light on this debate, we construct an extensive dataset by linking the Annual Survey of Industrial Enterprises (ASIE) dataset with patent quality data. Our analysis focuses on the impact of privatization on the innovation performance of former SOEs. Our findings suggest that the privatization of SOEs generally results in a decrease in innovation performance. This adverse effect is particularly pronounced for firms situated in regions characterized by low levels of market development or those grappling with high financial constraints. This supports the hypothesis that SOEs can serve as a mechanism to address institutional deficiencies in China's context. Our study contributes to a deeper understanding of the relative innovation performance of SOEs and private enterprises and has significant policy implications for ongoing SOE reforms in China and other developing countries.

"Thin" Structure of Relations in MCDM Models. Equivalence of the MABAC, TOPSIS(L1) and RS Methods to the Weighted Sum Method

This paper introduces the conceptual framework of the multi-criteria decision-making (MCDM) rank model, which embodies the integration and harmonization of the aggregation method, the weighing method, the decision matrix normalization technique, and the selection of distance metrics. This definition serves to broaden the spectrum of acceptable MCDM methodologies for problem-solving and specifiing the associated tools. A Multi-Method Model (3M) approach is employed for multi-criteria selection to enhance the reliability of the results. The methodology is outlined for adjusting the rankings of alternatives to account for the distinguishability of ratings in a particular MCDM model using the Relative Performance Indicator (RPI) of alternatives. Through RPI, four methods are established for aggregating individual characteristics of alternatives that yield identical results: Weighted Sum Model (WSM), Multi-Attributive Border Approximation area Comparison (MABAC), Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS (L1)), and Ratio System approach (RS), eliminating the need to duplicate these methods in the 3M approach. A comprehensive comparison of numerous multi-criteria methods is conducted based on two lists: ranking and rating. Additionally, a method for step-by-step linear transformation of alternative ratings obtained from various MCDM models is defined, facilitating comparison and aggregation of ratings.

Choice between Sustainable versus Conventional Investments—Relative Efficiency Analysis from Global and Regional Stock Markets

We use the daily data from 1 October 2010 to 1 March 2021 on the stock prices of several global, regional, and country-specific ESG indices of the Dow Jones Sustainability Index family (DJSI) and MSCI family to analyse the relative performance of sustainable indices (ESG) and corresponding conventional benchmarks. In terms of classic risk and return characteristics and modern portfolio metrics, we report mixed evidence with some sustainability indices marginally outperforming the traditional benchmarks and others staying at parity. Regionally, the evidence is heterogeneous; the Pan Arab, the Middle East (including Israel), the United States, Emerging Markets, and Europe indices reported a slightly superior performance and those belonging to Asia Pacific, Emerging Africa, and Latin America marginally underperformed compared to their conventional counterparts. The findings of this study imply that sustainable investments appear to be an encouraging investment option, although their progress has not been substantial. For an appreciable outperformance of sustainable investments, a more conducive regulatory framework should be established, including robust incentivizing policies concerning tax rebates or low capital costs.

The relationship between asymmetrical grip strength criteria and fall incidence among middle-aged and older Chinese adults.

Current handgrip strength (HGS) protocols employ a variety of criteria, affecting the assessment of asymmetric HGS. The impact of these different criteria on fall prediction is understudied. This study was devised to compare the relative performance of average and maximum HGS asymmetry criteria as tools to predict fall incidence among middle-aged or older adults in China. 9627 Chinese adults 50 + years of age who were participants in the China Health and Retirement Longitudinal Study (2013-2015 waves) were evaluated. The measurement of HGS was achieved based on either the maximum recorded value (HGSmax) or the average (HGSave), and these values were employed for the calculation of HGS asymmetry. Fall incidence over a 2-year period was evaluated based on self-reported data. Logistic regression analyses were utilized to determine the predictive performance of HGSmax asymmetry or HGSave asymmetry when gaging 2-year fall risk. Significant differences in overall rates of HGS asymmetry and the rates of subdivisions thereof were observed when comparing the HGSmax and HGSave criteria, with moderate consistency (kappa = 0.599, p < 0.001). Over the 2-year follow-up period, 1743 fall incidents were recorded. Adjusted logistic regression models indicated that only HGSmax asymmetry > 30.0% was significantly related to fall risk (p = 0.034, odds ratio = 1.36, 95% confidence interval: 1.02-1.81). These findings highlight the importance of HGS criteria in detecting HGS asymmetry, and suggest that HGSmax is a more robust criterion for predicting fall risk among Chinese adults 50 + years of age.

Sprinting performance and behavior of adult shortnose sturgeon (Acipenser brevirostrum)

Swimming ability and performance are central to the ecology of aquatic species and to the design of structures intended to promote access to habitat. This is particularly important for migratory species traveling over significant distances. Here, we present results of a study of swimming behaviors of adult shortnose sturgeon ( Acipenser brevirostrum). Sturgeon were presented with velocity challenges of 0.5–2.5 m·s‒1 in a 35 m long flume that they were allowed to enter and ascend volitionally. Attempt rate was greatest among large sturgeon, at warm temperatures, and at low flow velocities. Sturgeon swam for shorter distances and durations against high-velocity flows; larger sturgeon had greater overall performance and endurance, but when velocities were standardized to body lengths the relative performance was reduced with increased body size. Overall, however, sturgeon were able to swim at much greater speeds than previously predicted, consistent with other studies showing that volitional performance exceeds that of data collected in common laboratory apparatus.

The Gene Expression Landscape of Disease Genes.

Fine-mapping and gene-prioritisation techniques applied to the latest Genome-Wide Association Study (GWAS) results have prioritised hundreds of genes as causally associated with disease. Here we leverage these recently compiled lists of high-confidence causal genes to interrogate where in the body disease genes operate. Specifically, we combine GWAS summary statistics, gene prioritisation results and gene expression RNA-seq data from 46 tissues and 204 cell types in relation to 16 major diseases (including 8 cancers). In tissues and cell types with well-established relevance to the disease, the prioritised genes typically have higher absolute and relative (i.e. tissue/cell specific) expression compared to non-prioritised 'control' genes. Examples include brain tissues in psychiatric disorders (P-value < 1×10-7), microglia cells in Alzheimer's Disease (P-value = 9.8×10-3) and colon mucosa in colorectal cancer (P-value < 1×10-3). We also observe significantly higher expression for disease genes in multiple tissues and cell types with no established links to the corresponding disease. While some of these results may be explained by cell types that span multiple tissues, such as macrophages in brain, blood, lung and spleen in relation to Alzheimer's disease (P-values < 1×10-3), the cause for others is unclear and motivates further investigation that may provide novel insights into disease etiology. For example, mammary tissue in Type 2 Diabetes (P-value < 1×10-7); reproductive tissues such as breast, uterus, vagina, and prostate in Coronary Artery Disease (P-value < 1×10-4); and motor neurons in psychiatric disorders (P-value < 3×10-4). In the GTEx dataset, tissue type is the major predictor of gene expression but the contribution of each predictor (tissue, sample, subject, batch) varies widely among disease-associated genes. Finally, we highlight genes with the highest levels of gene expression in relevant tissues to guide functional follow-up studies. Our results could offer novel insights into the tissues and cells involved in disease initiation, inform drug target and delivery strategies, highlighting potential off-target effects, and exemplify the relative performance of different statistical tests for linking disease genes with tissue and cell type gene expression.

Collusive Stability with Relative Performance and Network Externalities

Collusive Stability with Relative Performance and Network Externalities