Perfect Substitutes Research Articles

Training Characteristics and Competitive Demands in Women Road Cyclists: A Systematic Review.

To identify the main training characteristics and competitive demands in women's road cycling. A systematic search was conducted on 5 databases according to PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines. The articles had to be primary studies, written after 1990 with a sample of competitive women between the ages of 15 and 50. The Quality Assessment Tool for Quantitative Studies and the Oxford Levels of Evidence scales were used. The search yielded 1713 articles, of which 20 were included. Studies on training and competitive demands (n = 5) found that both external and internal loads are higher in women than in men. Studies on strength and endurance training (n = 5) showed that both velocity-based and heavy-load strength training programs performed at least 2days per week and including 3 to 4 lower-body exercises improved performance. Altitude-training studies (n = 3) found that "Live High-Train Low" was effective to increase performance during the first 9days after the training camp. The 7 remaining studies focused on a range of topics. The methodological quality was strong for 12 studies and moderate for 8. In contrast, the level of evidence was high in 7 and low in the other 13. Endurance training and competitive demands in women's road cycling are higher than those of men. Strength training is effective in women when the frequency, intensity, and number of exercises are appropriate, while altitude training should be completed a few days before competing. Further studies are warranted to better define the participants' competitive level, using a methodological design with a higher level of evidence.

Analysis of Service Quality Dimensions: Towards a Student Satisfaction Model in the “New Normal”

The recent pandemic compelled universities and colleges worldwide to provide services different from usual. This change and the increasing competitive intensities demand higher performance levels globally in Higher Education Institutions (HEIs). To achieve the desired performance levels, universities and colleges must identify well-performing areas and areas needing improvement. One way to identify these areas is by surveying students’ satisfaction. Many studies have been conducted on student satisfaction in public and private universities worldwide. However, students’ satisfaction with the “new normal” has not been fully explored. This study conceptualizes student satisfaction by developing a framework that integrates the service quality dimensions in the “new normal.” Results, conclusions, and recommendations are discussed.

On designing and developing single‐step second‐order implicit methods with dissipation control and zero‐order overshoots via subsidiary variables

AbstractHilber and Hughes gave several competitive demands on the implicit methods in 1978. However, there are no such integration methods in the traditional algorithm design. Via imposing subsidiary variables, this article proposes two novel implicit methods to splendidly achieve these competitive demands without increasing computational costs. The two novel methods are self‐starting, unconditionally stable, single‐solve, identically second‐order accurate, controllably dissipative, and non‐overshooting. The novel methods achieve the maximal dissipation of auxiliary variables in the high‐frequency limit, although such the design is not a must. The first novel method uses auxiliary velocity and acceleration variables, whereas the second one employs two auxiliary acceleration variables. After embedding desired numerical characteristics, the novel methods employ four eigenvalues of amplification matrices in the high‐frequency limit as user‐specified parameters to flexibly control numerical high‐frequency dissipation. To reduce the number of use‐specified parameters, this article gives some recommended sub‐families of algorithms, such as optimal low‐frequency dissipation schemes. The article further refines the error analysis to analytically calculate amplitude and phase errors for some implicit methods. The error analysis technique can be applied to almost all direct time integration methods. Comparisons of amplitude and phase errors highlight the superiority of the novel methods over the published algorithms. In addition, some classical measures, such as numerical damping ratios and relative period errors, are analyzed and compared. Numerical examples are solved to show the novel methods' superiority.

Raw Jackfruit (Artocarpus heterophyllus) Seedmeal: Effect on Growth Performance, Organ Weight, Carcass Yield, and Economic Production of Guinea Fowl Keets

Ensuring food security and sustainable agriculture is vital as the global population expands, leading to increased protein demand. However, competitive demand for feed ingredients such as maize and soybeans has driven up costs. As a result, alternative feed sources, including Jackfruit by-products like seeds, have been explored. This study aimed to assess the effects of incorporating raw jackfruit seedmeal (JSM) into the diet of guinea fowl keets, specifically regarding growth performance, carcass yield, organ weights, and economic production. The seven-week study involved 120 keets divided into different treatments, each replicated three times. Treatments 2, 3, and 4 included JSM at 10%, 15%, and 20%, respectively, while treatment one served as the control without JSM. Increasing the level of JSM resulted in a consistent decline in all relevant indicators, as observed through proximate analysis. Treatment four, which included 20% JSM, exhibited the best performance in terms of final weight (745g) and daily weight gain (15g). Notably, the gizzard was the most significant parameter among carcass features, with treatment four showing the highest value (3.95%), while the control diet had the lowest value (2.83%). Diets containing 15% and 20% JSM had the most favorable outcomes in terms of feed cost per weight gain, with the 20% JSM diet demonstrating the highest gross margin and revenue. Importantly, dietary inclusion of JSM did not significantly impact the performance of guinea fowl keets, and incorporating 20% JSM into their diet resulted in a significant increase in productivity and feed utilization.

QUAS-R: An SLC1A5-mediated glutamine uptake assay with single-cell resolution reveals metabolic heterogeneity with immune populations

System-level analysis of single-cell data is rapidly transforming the field of immunometabolism. Given the competitive demand for nutrients in immune microenvironments, there is a need to understand how and when immune cells access these nutrients. Here, we describe a new approach for single-cell analysis of nutrient uptake where we use in-cell biorthogonal labeling of a functionalized amino acid after transport into the cell. In this manner, the bona fide active uptake of glutamine via SLC1A5/ASCT2 could be quantified. We used this assay to interrogate the transport capacity of complex immune subpopulations, both invitro and invivo. Taken together, our findings provide an easy sensitive single-cell assay to assess which cells support their function via SLC1A5-mediated uptake. This is a significant addition to the single-cell metabolic toolbox required to decode the metabolic landscape of complex immune microenvironments.

The non-Markovian nature of nested logit choice

Discrete choice models are widely used for understanding how customers choose between a variety of substitutable goods. We investigate the relationship between two well studied choice models, the Nested Logit (NL) model and the Markov choice model. Both models generalize the classic Multinomial Logit model and admit tractable algorithms for assortment optimization. Previous evidence indicates that the NL model may be well approximated by, or be a special case of, the Markov model. We establish that the Nested Logit model, in general, cannot be represented by a Markov model. Further, we show that there exists a family of instances of the NL model where the choice probabilities cannot be approximated to within a constant error by any Markov choice model.

Merging Athletic Development With Skill Acquisition: Developing Agility Using an Ecological Dynamics Approach

ABSTRACT Agility has commonly been regarded as a physical quality, and strength and conditioning practitioners have typically used a closed environment approach for developing agility. This closed environment approach involves the decoupling of perception and action, where actions are trained in isolation from perception. Previous studies have shown, however, that when perception or action is trained in isolation, behavior changes. Therefore, agility is complex and multifactorial in nature. Through ecological dynamics, specifically the principle of representative learning design, practitioners should design training tasks that align more closely with the demands of competition. Representative learning design ensures that perception and action remain coupled to promote greater transfer of performance from training to competition. Another key principle for agility task design is coadaptation, and this can be operationalized through manipulation of opposing players. With these 2 key principles, we offer examples of agility tasks in 3 team invasion sports including soccer, rugby union, and Australian rules football.

Policy reinvention in diffusion: Evidence from municipal solid waste classification policy in China

AbstractWhile research on policy diffusion has gained significant interest among scholars worldwide, little attention has been given to policy reinvention in diffusion. This study aims to investigate the influencing factors and combination paths of policy reinvention in the Municipal Solid Waste Classification Policy (MSWCP). To achieve this, a theoretical framework encompassing internal factors, intergovernmental relations, and external influence has been constructed. Empirical analysis has been conducted on the MSWCP of 31 large‐ and medium‐sized cities in China using Qualitative Comparative Analysis. Through this analysis, several combination paths that prompted local governments to reinvent policies have been identified. Furthermore, the study has clarified the various roles of six conditions—financial resources, government attention, policy experience, peer competition, organizational learning, and social demand—in achieving policy reinvention. These findings are expected to provide new theoretical and practical insights into the field of policy reinvention research.

Differences In Player Load Of Professional Basketball Players As A Function Of Distance To The Game Day During A Competitive Season

Purpose: The aim of this study was to investigate the dynamics of external training load (eTL), internal training load (iTL), and well-being status, during a regular season week with one game, and to examine the differential workloads of players depending on their distance from game day during a competitive season. Method: Subjects were 10 full-time professional basketball players (24.6 ± 4.9 years old; 204.2 ± 16.8 cm; 97.9 ± 10.4 kg). Workload was recorded and classified as total duration training and duration of full game during a competitive season. A wearable tracking system collected eTL via Player Load (PL) and Player Load per minute (PL/min). Training sessions were classified based on days before a match (four days before the match day = MD-4, MD-3, MD-2, and MD-1), and MD. Session rate of perceived exertion (sRPE) and rate of perceived exertion (RPE) were used for iTL. In addition, the Hooper index (HI) was used for well-being. Results: A significant difference was found between MD-1 and MD workload, MD workload being the highest of all variables: RPE (p < .001), PL/min (p <.001), PL (p <.001), and sRPE (p <.001). Regarding Hooper’s categories, significant differences between training days and match were only found in soreness (p <.001). Conclusion: The results show that MD provides a unique stimulus in terms of volume and intensity. Consequently, coaches must incorporate specific training exercises to adapt players to the demands of competition. Finally, special attention should be paid to MD-2 and MD-1 in terms of potential accumulated fatigue and thus to ensure appropriate recovery time for athletes to adapt before the match.

The impact of the collaborative innovation network embeddedness on enterprise green innovation performance

As the market environment becomes increasingly competitive, enterprises that rely solely on internal research and development innovation are no longer sufficient to meet the demands of competition. Consequently, enterprises have broken down organizational boundaries and shifted from closed innovation to open collaborative innovation. The flow of knowledge across organizations facilitates the acquisition of heterogeneous resources from partners, promotes the integration and configuration of internal and external knowledge, thereby enhances the competitiveness of enterprises. However, some scholars argued that collaborative innovation does not always achieve win-win outcomes, and the existence of substitution effects between enterprises and their partners may hinder the innovation level of the focal enterprise. Therefore, based on the resource-based theory and the network embeddedness theory, this study constructs a theoretical model to investigate the effects of network embeddedness, network experience and partner diversity on enterprise green innovation performance in the Chinese green collaborative innovation network. The impact of network embeddedness on innovation performance is examined from two dimensions: structural embeddedness and relational embeddedness. The moderating effects of network experience and partner diversity are analyzed to further explain this phenomenon. Using Chinese green patent data from 2000 to 2015 as the research object, the collaborative innovation network of enterprises is constructed, and the network characteristic variables are calculated using social network analysis methods. Finally, negative binomial regression and robustness tests are conducted using STATA software. The research findings provide managerial implications for Chinese enterprises to achieve competitiveness and sustainable development.

A multi-objective optimization algorithm for flow shop group scheduling problem with sequence dependent setup time and worker learning

The optimization of production systems has become increasingly important in manufacturing industries due to the growing competition and market demands. One of the overriding concerns of managers is the efficient exploitation of workers' learning to increase output and decrease downtime. The learning effect symbolizes the improvement of workers' ability and performance through the repetition of similar jobs. On the other hand, it is a critical requirement for decision-makers to have effective management of the transportation phase to achieve an optimal production plan. This paper considers a flow shop sequence-dependent group scheduling problem (FSDGS) with a learning effectto minimize two contradictory objective functions, namely makespan and energy consumption.A mixed-integer linear programming model is proposed to find optimal jobs, group schedules, and appropriate production and transportation speeds to enhance the overall performance of the system. Due to the complexity of the planning process, we propose lower bounds and an efficient resolution method based on multi-objective simulated annealing metaheuristic (MOSA), enhanced by a local search procedure to tackle this problem. The proposed method is evaluated through several experiments based on a real case study, using different learning rates and setup time ratio levels. The obtained results demonstrate the effectiveness of the algorithm in improving the performance of production systems by reducing processing time and energy consumption. These findings have significant implications for the design and optimization of production systems in manufacturing industries.

In-Game Workload Demands of Position Players in Major League Baseball.

Athletes who are well prepared for the physical demands of competition are less susceptible to injury. Defining and then preparing athletes for these in-game demands is critical to athlete health and performance. The injury burden within Major League Baseball (MLB) is significant and differs by position. Despite its importance, the workload demands have not been described for position players in MLB. That running demands would be significantly higher for outfielders, followed by infielders, and catchers, respectively, while batting and baserunning metrics would be similar across positions. Cohort study. Level 3. Total and high-speed running distance (>75% Vmax), high-speed running count, hard accelerations (>2.78 m/s/s), defensive and baserunning minutes, total and hard throws (>75% max), and bat swing counts were calculated from Statcast data. Players with 100 games or more in the 2018 season (n = 126) were included for analysis. All offensive and baserunning metrics were similar across positions; however, significant positional differences were observed for defensive and overall workload metrics. High-speed running was highest among outfielders (F1,7 = 27.1, P < 0.01), followed by infielders, then catchers. Hard accelerations (F1,7 = 12.9, P < 0.01) were highest among first basemen, then outfielders, remaining infielders, and catchers. Total throws (F1,7 = 17.7, P < 0.01) were highest among middle infielders. Hard throws (P < 0.01) were highest among shortstops and third basemen. In-game workloads differ significantly by defensive position in MLB. These differences in running, throwing, and hitting volumes have significant implications for physical preparation and injury return-to-play progressions to optimize performance and minimize injury and reinjury risk for these athletes. These data provide insight into how best to prepare athletes of different positions for the demands of the game both in terms of preseason preparation as well as return-to-play benchmarks following injury. These data should also serve as a platform for future research into the relationship between workload and injury among professional baseball players.

Impact of Continuing Education on Stable Employment and Wages of Men and Women in Serbia

This paper examines whether continuing education and training contribute to overall job security and to narrowing the gender wage gap, thereby mitigating the potential effects of employer discrimination. Data from the Serbian Survey on Income and Living Conditions are used, focusing on 2020 and estimating wage regressions. The main results show that participation in continuing education and training has a positive effect on wages and contributes to reducing the wage gap, especially for individuals who were previously unemployed and participated in some form of additional training. This paper contributes to the understanding of the importance of training and its impact on employment stability and workers' wages in the post-transition economy. The findings presented in this paper are advisory to both policy makers and management. In general, it can be stated that trained employees are better suited to work tasks and, especially if they are satisfied with the knowledge acquired in the company, contribute to a stable environment that makes it easier for them to meet the demands of competition. On the other hand, this implies the empirically confirmed assumption that competition may be negatively correlated with employer discrimination. However, employee participation in continuing education and training in Serbia is still below the optimal level.

Is Regulatory Approval without Autonomous Operation for Natural Extract Manufacturing under Economic Competitiveness and Climate-Neutrality Demands Still Permissible?

Natural extracts are broadly utilized as remedies, nutrition additives, cosmetics or flavors as well as natural pesticides, fungicides or herbicides. Green manufacturing technologies are of added market value and are sustainable towards the climate neutrality politically demanded for 2045. The concept of digital twins involves experimentally distinct validated process models combined with process analytical technology that is to be adapted to the existing operations. This is a key technology for the autonomous operations in industry 4.0. This paper exemplifies this approach and evaluates the results of the application and implementation efforts of regulated industries. A conductivity sensor for the measurement of the dry residue content and/or Fourier-transformed infrared spectroscopy for marker/lead or reference substance concentration determination are the most feasible and straight forward solutions. Different process control concepts from simple PID controllers (proportional, integral and differential) to advanced process control using digital twin models are evaluated and discussed in terms of industrialization efforts and benefits. The global warming potential CO2 equivalent per kg of natural product could be decreased by a factor of 5–10 as well as the cost of goods, which makes the pay-out time for the industrialization investment less than 1 year and the approach highly competitive. The success rate of the extraction process under regulatory constraints can be raised to 100%, reducing waste, overall solvent consumption, personnel efforts and energy requirements to a minimum.

Developing a High-Quality, Modern Labor Market in Vietnam

The labor market in Vietnam has experienced significant changes due to global trends and the demand for competitiveness in the region. This study investigates the evolving Vietnamese labor market, considering the obstacles presented by the Covid-19 pandemic and the fourth industrial revolution. The paper underscores the significance of adhering to international labor laws and standards to effectively tackle these challenges. By examining the influence of these external factors and their repercussions on labor standards, this research offers valuable insights for policymakers, employers, and workers in Vietnam. The findings emphasize the need to align domestic labor policies with international standards in order to establish a just and sustainable labor market in Vietnam amidst the evolving global landscape.

Porous Host-Guest MOF-Semiconductor Hybrid with Multisites Heterojunctions and Modulable Electronic Band for Selective Photocatalytic CO2 Conversion and H2 Evolution.

Optimizing catalysts for competitive photocatalytic reactions demand individually tailored band structure as well as intertwined interactions of light absorption, reaction activity, mass, and charge transport. Here, a nanoparticulate host-guest structure is rationally designed that can exclusively fulfil and ideally control the aforestated uncompromising requisites for catalytic reactions. The all-inclusive model catalyst consists of porous Co3 O4 host and Znx Cd1- x S guest with controllable physicochemicalproperties enabled by self-assembled hybrid structure and continuously amenable band gap. The effective porous topology nanoassembly, both at the exterior and the interior pores of a porous metal-organic framework (MOF), maximizes spatially immobilized semiconductor nanoparticles toward high utilization of particulate heterojunctions for vital charge and reactant transfer. In conjunction, the zinc constituent band engineering is found to regulate the light/molecules absorption, band structure, and specific reaction intermediates energy to attain high photocatalytic CO2 reduction selectivity. The optimal catalyst exhibits a H2 -generation rate up to 6720µmol g-1 h-1 and a CO production rate of 19.3µmol g-1 h-1 . These findings provide insight into the design of discrete host-guest MOF-semiconductor hybrid system with readily modulated band structures and well-constructed heterojunctions for selective solar-to-chemical conversion.

Positional Differences in Absolute vs. Relative Training Loads in Elite Academy Soccer Players.

Weekly training loads are typically reported using absolute values and are not individualized according to competition positional demands (relative values). The aim of this study was to evaluate absolute and relative training loads and compare across playing positions during a full in-season in an elite soccer academy. 24 elite academy soccer players, categorized into five positions (CD: central defender [n = 4]; FB: full back [n = 5]; CM: central midfielder [n = 6]; WM: wide midfielder [n = 5]; FW: forward [n = 4]), were monitored using a global positioning system. Absolute training load was calculated using the total distance, the distance at moderate-speed ([15-20[ km·h-1), high-speed ([20-25[ km·h-1), sprint (> 25 km·h-1), the total number of accelerations (> 3 m·s-2) and decelerations (< -3 m·s-2). Relative training load was calculated by dividing absolute training loads by mean values from the competitive matches. Training loads were determined daily according to their distance from match day (MD). One-way ANOVAs were performed to evaluate differences between playing positions. Absolute moderate-speed distance was greater for WM compared to CD (p = 0.015, and p = 0.017), while the opposite was shown for relative values (p = 0.014, and p < 0.001) on MD-4 and MD-3, respectively. The absolute moderate-speed distance was not different between CD, FB, CM, and FW, whereas relative values were greater for CD on MD+2 and MD-4 (p < 0.05). FB and WM performed greater absolute high-speed distance than CD on MD-4 and MD-3 (p < 0.05) while no difference was highlighted for relative values.Our results demonstrated that in the present academy players, training load for CD was underestimated using absolute training loads for moderate and high-speed distances. In contrast, relative training loads highlighted WM as an underloaded position. Therefore, relative training loads are recommended as they contextualize training loads according to competitive demands and favor training individualization.

Conservation agriculture reduces climate change impact of a popcorn and wheat crop rotation.

Urgent action is needed to ensure humanity's future under climate change. Agriculture faces major challenges as it is both influenced by and contributes to climate change. Conservation agriculture sequesters carbon (C) in the soil due to practices such as reduced tillage and planting of cover crops. This study assessed effects of an innovative conservation agriculture popcorn (Zea mays) and wheat (Triticum aestivum) crop rotation in south-western France on soil C sequestration, GHG emissions and several environmental impacts. Two complementary approaches were used: i) a comparison based on field data and expert judgement to assess short-term effects and ii) modelling of three scenarios to quantify long-term outcomes. In both approaches Life cycle assessment (LCA) was used to compare popcorn and wheat rotations. The conventional rotation used ploughing, and its soil was bare between wheat harvest and popcorn sowing. Conservation agriculture used reduced tillage, cover crops, and compost of green waste. Impacts of compost production were allocated mainly to its waste treatment function, based on waste treatment cost and compost price. Simulation modelling of soil C was used to estimate the amount of C sequestered by the conservation and conventional crop rotations. LCA was combined with soil C modelling over 100 years to assess the long-term climate change impact of three scenarios for the popcorn and wheat rotation. These scenarios were 1) Conventional agriculture, 2) Conservation agriculture with cover crops only, 3) Conservation agriculture with cover crops + compost. Mean annual C sequestration and net climate change impact were -0.24 t/ha and 3867 kg CO2-eq./ha, respectively, for the conventional rotation and 0.91 t/ha and 434 kg CO2-eq./ha, respectively, for the conservation rotation. The climate change impact of the conservation rotation depended strongly on the allocation of composting impacts between the waste treatment and compost production functions. Compared to the conventional rotation, the conservation rotation had a lower marine eutrophication impact (-7%) but higher impacts for terrestrial acidification (+9%), land competition (+3%), and cumulative energy demand (+2%). Modelling over 100 years revealed that, at near soil C equilibrium, a conventional scenario lost 9% of soil C, whereas conservation agriculture scenarios gained 14% (only cover crop) and 26% of soil C (cover crop + compost). Conservation agriculture resulted in soil C sequestration over several decades, until a new soil C equilibrium was reached.

An extension of the hypothetical extraction method: endogenous consumption and the armington treatment of imports

The hypothetical extraction method (HEM) is the tool of choice for identifying underlying economic interdependencies. It provides critical information to policymakers regarding the strategic role of different sectors. However, the standard implementation of the HEM does not include the impact that falls on the price structure as a result of the substitution between domestic and imported products that takes place after the extraction of a sector or industry, in this case. We propose to overcome this limitation by extending the HEM using an Armington-Leontief model with endogenous consumption. Unlike the perfect substitution assumption typical of the standard HEM, the Armington assumption with endogenous consumption implies that the shift from domestic inputs to imports affects the cost functions. Therefore, both quantities and prices become endogenous in the ‘post-extraction' equilibrium. We also argue that HEM indicators should be expanded beyond the typical output-related indicators, i.e. value-added, employment, or pollutant levels, so that summary indices of the type more commonly used in economics, such as welfare indicators, are used. We implement this novel approach using the latest input–output data for Spain in 2016.

HUMAN CAPITAL SEBAGAI BAGIAN DARI INTELLIGENT CAPITAL DALAM DAYA SAING PERUSAHAAN

Human Capital as a part of Intelligent Capital in Company Competitiveness. Every single company’s final goal is to make a profit business. Company market competitiveness is a manifestation of its both performance and quality. The competition demands a well – arranged company resources and capitals include its Intelligent Capital which contain Human Capital. A good Intelligent Capitaled Company indicates by its competent Human Capital, to make sure the company are qualified and well performed enough to be a strong competitor in the market.