Supply Adjustment Research Articles

Good personality traits in bad times: Does conscientiousness mitigate the adverse effects of graduating in a recession?

This paper studies whether and how conscientiousness, a personality trait, helps individuals mitigate the adverse effects of graduating during a recession on early career outcomes. By analyzing college-educated individuals who graduated in the 1980s, we find that conscientiousness reduces the income losses of workers who graduated during a recession. This effect results mainly from workers’ adjustments in the labor supply. When graduating during a recession, college graduates high in conscientiousness are more likely to find full-time jobs and work more hours per week than their counterparts low in conscientiousness. Regarding the other four Big Five personality traits, while agreeableness has a modest effect on mitigating the effects of adverse labor market entry conditions on hourly wages, extraversion, openness to experience, and emotional stability do not appear to buffer against such early career losses. Additionally, cognitive ability does not offset the challenges posed by graduating during a recession.

Impairing Globalization: The Russo-Ukrainian War, Western Economic Sanctions and Asset Seizures

The potency of economic sanctions imposed on nations depends on demand and supply adjustment possibilities. Adverse GDP impacts will be maximal when import, export, production, distribution and finance are inflexible (universal non-substitution). This paper elaborates on these conditions and quantifies the maximum GDP loss that Western sanctions could have inflicted on Russia in 2022–2023. It reports the World Bank’s predictions, contrasts them with the results and draws inferences about the efficiency of Russia’s workably competitive markets. This paper shows that Russia’s economic system exhibits moderate universal substitutability and is less vulnerable to punitive discipline than Western policymakers suppose. The likelihood that economic sanctions will compel the Kremlin to restore Ukraine’s territorial integrity ceteris paribus is correspondingly low, even though war reduces Russia’s quality of existence. Western economic sanctions serve narrow geostrategic ends that are reconcilable with Pareto-efficient free trade and globalization, if precision-targeted, but as the Russo-Ukrainian war intensifies, an expanded array of novel and dubiously legal sanctions is degrading free trade, and spurring de-globalization and anti-Western coalitions. If this armed combat is prolonged, the goals of free trade and globalization could be set back for decades.

Designing a collaborative maintenance planning mechanism between airline and maintenance company using a bilevel model – Considering flexible maintenance schedule and service charges

Periodic aircraft Maintenance Repair and Overhaul (MRO) activities are compulsory. To capture the features of MRO operations between airline and maintenance company under MRO outsourcing mode, we consider a collaborative aircraft maintenance planning problem, in which the airline outsources its self-operated maintenance checks to an independent maintenance company. Under such context, MRO planning conflicts between two collaborates exists especially during maintenance peak period, as airline aims to maximize flight operations revenues by receiving timely MRO service. On the other hand, maintenance company strives to accomplish heterogenous demands without causing tardiness and involving excessive MRO resources cost. Therefore, finding an effective mechanism to eliminate the conflicts between maintenance demands (from airline company) and maintenance service supply capability (from maintenance company) is indispensable for collaboration. A bi-level optimization model is formulated to describe the conflicting objectives and maintenance planning features of two independent stakeholders. To facilitates a synchronization of demand and supply and reconcile MRO conflicts, flexible maintenance schedules and service charges decisions from two independent collaborators is involved in the model, enabling a maintenance planning negotiation for finding mutual beneficial maintenance plan. An iterative algorithm deploying bounding updating strategy is developed, which generates a series of convergent-oriented bounding constraints along the iterative negotiation and guides the adjustment of maintenance demand and supply towards equilibrium. Based on the computational results in solving various maintenance planning scenarios, the impacts of different features (e.g. resource availability, resource demands level, and penalty cost of service tardiness) on airline and service company’s planning performance are analysed, revealing that maintenance service company’s own interest can be assured and maintained though it is a follower in the collaboration framework Afterwards, the managerial insights for facilitating the maintenance collaboration are further discussed.

The Impact of Monetary Policy on Economic Growth in Vietnam

This article focuses on investigating the impact of monetary policy on economic growth in Vietnam in both the short and long term using the Vector Error Correction Model (VECM) over the period from 2005 to 2023. The research results indicate that, in the long term, both M2 money supply and exchange rates have a positive impact on economic growth. Among these, the influence of the M2 money supply on growth is greater than that of exchange rates, suggesting that adjustments in the M2 money supply allow for immediate and comprehensive effects on the economy compared to adjustments in exchange rates. Conversely, real interest rates have an inverse effect on GDP in the long term.

The Impact of Monetary Policy, Inflation Rates, and Foreign Direct Investment on Economic Growth in Developing Countries

This study explores the intricate relationships between monetary policy, inflation rates, and foreign direct investment (FDI) and their collective impact on economic growth in developing countries. Utilizing a comprehensive review of existing literature, this research aims to provide a nuanced understanding of how these macroeconomic factors interact to influence economic development. Monetary policy, often implemented through adjustments in interest rates and money supply, is critical in shaping economic stability and growth. The study reveals that effective monetary policy in developing countries can stimulate economic activity by fostering an environment conducive to investment and consumption. However, the impact of such policies is contingent upon the stability and credibility of the governing institutions, which are often variable in developing regions. Inflation rates, which reflect the general rise in price levels, were found to have a complex relationship with economic growth. Moderate inflation can stimulate spending and investment by reducing the real burden of debt and encouraging consumption. In contrast, high inflation can erode purchasing power and deter both domestic and foreign investment, thereby stifling growth. This study underscores the importance of maintaining inflation within a manageable range to support sustainable economic growth. Foreign direct investment is identified as a key driver of economic development, providing capital, technology transfer, and employment opportunities. The research highlights that FDI can significantly enhance economic growth by supplementing domestic capital, improving infrastructure, and fostering industrial diversification. However, the benefits of FDI are maximized when complemented by stable economic policies and a favorable investment climate. In conclusion, the interplay between monetary policy, inflation, and FDI is crucial in shaping the economic trajectories of developing countries. The study suggests that balanced and coherent policy frameworks are essential to harnessing these factors for sustained economic growth. Future research should explore country-specific dynamics to better understand the differential impacts across various developing economies.

A study of European wheat price series forecasting based on multiple variants of Holt-Winters and LSTM models

Given the importance of wheat in global food security and agricultural economy, accurate price forecasts are of significant practical significance for growers, the food chain, and government macro-control. Four different time series forecasting models were used in this study, including the traditional Holt-Winters three-parameter exponential smoothing method and three improved models based on the Long Short-Term Memory Network (LSTM): the CNN-LSTM, the GRU, and the VMD-LSTM. By comparing the forecasting effects of these models under the same training and test sets, this study aims to select the best models using the best model for predicting European wheat prices from 2010 to 2023 after training. The results show that the CNN-LSTM model performs the best in predicting the European wheat price series, and the future wheat price will show a slow downward trend, and the CNN-LSTM model combines the feature extraction ability of convolutional neural network and the long-term dependency learning ability of LSTM, which can effectively capture the fluctuation characteristics of the price series and the trend characteristics. The GRU model also shows a better prediction ability, especially in dealing with long-term dependencies. in dealing with long-term dependencies. However, the VMD-LSTM model has certain shortcomings in its prediction effect when facing time series data with large fluctuations in the later period. In addition, the Holt-Winters model predicts that after a period of slow decline, wheat prices may rebound, which may be related to the adjustment of market supply and demand and changes in external factors.

The limits of right-sizing: analyzing social housing strategies in French shrinking cities

ABSTRACT Right-sizing is becoming an increasingly relevant topic within the burgeoning literature on shrinking cities, specifically as a means for cities to cope with population loss. It encompasses various measures, such as demolishing vacant housing, consolidating urban development, and reusing vacant land for community gardens. Right-sizing promises to reduce financial concerns and increase quality of life. However, several studies have pointed out the limitations of its application, as it is bound by the principles of austerity. Recent research has argued for a more nuanced interpretation of the concept, as right-sizing can have differing impacts and outcomes depending on the local context. Following these recent contributions, this paper aims to deconstruct the right-sizing approach by analyzing social housing strategies in two shrinking cities in France (Le Creusot and Montluçon). The analysis shows that these two cities have been implementing strategies that include some quantitative adjustments of supply to demand. However, the strategies adopted are considerably more complex than mere quantitative adjustment and include a variety of synergistic lines of action. Thus, the aim of this paper is twofold: first, to highlight the limitations of right-sizing as an analytical concept, and second, to contribute to identifying appropriate social housing policies for shrinking cities.

Research on Knitted Garment Design and Innovation Countermeasures--Tongxiang Puyuan Knitwear Industry as an Example

As an important knitted garment production area in China, Tongxiang knitted garment market has a good production base. However, with the adjustment of supply and demand and changes in consumer demand, the existing knitted garment industry needs to adapt to the development of the times to carry out the corresponding industrial upgrading. This paper focuses on the existing knitted garment industry problems, such as: lack of innovation in knitted garment design, lack of brand competitiveness in the knitted garment market and inaccurate industrial positioning. Try to put forward to the use of design innovation, increase research and development efforts to improve the comprehensive ability of knitted garment enterprises; training of professional knitted garment design talent, and increase investment in science and technology so as to improve product quality and market taste; will be the neighboring regions of the garment industry organically combined together to drive the upgrading of the development of industrial proposals and countermeasures. Design and innovation as the driving force, better development of knitted garment industry in Tongxiang City.

Temporary gains and permanent costs in methamphetamine precursor control

James Cunningham and co-authors did pioneering work in evaluating the impact of precursor control on methamphetamine markets and related harms. We discuss their studies, as well as others that followed, and review what is known of precursor control's short-run and long-run impacts. We interpret the evidence to suggest that precursor control was likely cost-effective initially. However, long-run supply adjustments by illicit meth producers weakened the controls' efficacy. Meanwhile, regulations on legal consumers of cold medications were permanent and unavoidable, which may have closed the gap on the positive net benefits that had accrued initially in the short run. Our review underscores the challenges policymakers face in achieving their goals when supply can adjust long-term, but non-participants in illegal markets cannot.

Assessing Inequality in Urban Green Spaces with Consideration for Physical Activity Promotion: Utilizing Spatial Analysis Techniques Supported by Multisource Data

Urban green spaces (UGSs) play a significant role in promoting public health by facilitating outdoor activities, but issues of spatial and socioeconomic inequality within UGSs have drawn increasing attention. However, current methods for assessing UGS inequality still face challenges such as data acquisition difficulties and low identification accuracy. Taking Harbin as a case study, this research employs various advanced technologies, including Python data scraping, drone imagery collection, and Amap API, to gather a diverse range of data on UGSs, including photos, high-resolution images, and AOI boundaries. Firstly, elements related to physical activity within UGSs are integrated into a supply adjustment index (SAI), based on which UGSs are classified into three categories. Then, a supply–demand improved two-step floating catchment area (SD2SFCA) method is employed to more accurately measure the accessibility of these three types of UGSs. Finally, using multiple linear regression analysis and Mann–Whitney U tests, socioeconomic inequalities in UGS accessibility are explored. The results indicate that (1) significant differentiation exists in the types of UGS services available in various urban areas, with a severe lack of small-scale, low-supply UGSs; (2) accessibility of all types of UGSs is significantly positively associated with housing prices, with higher-priced areas demonstrating notably higher accessibility compared to lower-priced ones; (3) children may be at a disadvantage in accessing UGSs with medium-supply levels. Future planning efforts need to enhance attention to vulnerable groups. This study underscores the importance of considering different types of UGSs in inequality assessments and proposes a method that could serve as a valuable tool for accurately assessing UGS inequality.

Enhancing thermal comfort prediction in high-speed trains through machine learning and physiological signals integration

Heating, Ventilation, and Air Conditioning (HVAC) systems in high-speed trains (HST) are responsible for consuming approximately 70% of non-operational energy sources, yet they frequently fail to ensure provide adequate thermal comfort for the majority of passengers. Recent advancements in portable wearable sensors have opened up new possibilities for real-time detection of occupant thermal comfort status and timely feedback to the HVAC system. However, since occupant thermal comfort is subjective and cannot be directly measured, it is generally inferred from thermal environment parameters or physiological signals of occupants within the HST compartment. This paper presents a field test conducted to assess the thermal comfort of occupants within HST compartments. Leveraging physiological signals, including skin temperature, galvanic skin reaction, heart rate, and ambient temperature, we propose a Predicted Thermal Comfort (PTC) model for HST cabin occupants and establish an intelligent regulation model for the HVAC system. Nine input factors, comprising physiological signals, individual physiological characteristics, compartment seating, and ambient temperature, were formulated for the PTS model. In order to obtain an efficient and accurate PTC prediction model for HST cabin occupants, we compared the accuracy of different subsets of features trained by Machine Learning (ML) models of Random Forest, Decision Tree, Vector Machine and K-neighbourhood. We divided all the predicted feature values into four subsets, and did hyperparameter optimisation for each ML model. The HST compartment occupant PTC prediction model trained by Random Forest model obtained 90.4% Accuracy (F1 macro = 0.889). Subsequent sensitivity analyses of the best predictive models were then performed using SHapley Additive explanation (SHAP) and data-based sensitivity analysis (DSA) methods. The development of a more accurate and operationally efficient thermal comfort prediction model for HST occupants allows for precise and detailed feedback to the HVAC system. Consequently, the HVAC system can make the most appropriate and effective air supply adjustments, leading to improved satisfaction rates for HST occupant thermal comfort and the avoidance of energy wastage caused by inaccurate and untimely predictive feedback.

Russo–Ukrainian war: Limits of Western economic sanctions

AbstractThe potency of economic sanctions imposed on nations depends on demand and supply adjustment possibilities. Adverse GDP impacts will be maximal when import, export, production, distribution and finance are inflexible (universal non-substitution). This paper elaborates these conditions, and quantifies the maximum GDP loss that Western sanctions could have inflicted on Russia in 2022–2023. It reports the World Bank's predictions, contrasts them with results and draws inferences about the efficiency of Russia's workably competitive markets. The paper shows that Russia's economic system exhibits moderate universal substitutability and is less vulnerable to punitive discipline than Western policymakers suppose. The likelihood that the Kremlin will restore Ukraine's territorial integrity, ceteris paribus, is correspondingly low. The authors also observe that unintended adverse side effects from sanctions and counter-sanctions were excessive because policymakers chose to maximize GDP-damage to Russia instead of optimizing Western and third-party net benefits. Given moderate substitutability, Western policymakers can switch to smart net benefit maximizing sanctions that enhance Western and third-party welfare without significantly bolstering Russia's military industrial productivity and war-waging capabilities by retaining embargoes on weapons, technology and critical components, while selectively softening other restrictions. Smart sanctions might facilitate a negotiated settlement of the Russo–Ukrainian war.

Part-time employment opportunities and labour supply of older workers

I investigate the links between the part-time employment opportunities and the labour supply adjustments of older workers, focusing on both the extensive and intensive margins. Utilising data for 30 European countries in the period from 2011 to 2021, I construct a quasi-panel that compares individuals aged 60–64 with those aged 55–59 from five years prior. I find that the employees in sectors offering more part-time jobs are more likely to stay in employment, and that the total hours worked by these employees decrease at a slower rate than those of the employees in sectors imposing more rigid hours constraints. These results are most pronounced for women in manual types of occupation, but are significant across almost all examined worker categories. The positive relationship between the part-time employment opportunities and the total hours worked of older employees is robust to various modifications in the empirical setup. However, this relationship is heterogeneous across countries, and is least pronounced in the countries with a high availability of part-time jobs.

Job Loss and Household Labor Supply Adjustments in Developing Countries: Evidence from Argentina

Abstract Using longitudinal data for Argentina, this paper estimates the labor supply reaction of spouses and children, as well as the interactions between them, following the job loss of their husband or father. The findings show that job loss by the household head has a positive and significant impact on the labor supply of other household members. However, it increases the likelihood of spouses to switch to informal and downgraded employment, and of children to drop out from education. While effects are stronger among vulnerable households, coverage of social security does not provide enough support in coping with unemployment shocks. Mothers’ labor participation, however, may allow their daughters to continue their education.

Short Communication: Indian Public Sector Commercial Banks: An Empirical Analysis of Bank-Specific Determinants of Credit Risk

The public sector banks dominate India’s financial sector and play a crucial role. Commercial banks are indispensable in the processes of capital circulation, capital integration, capital resource allocation, and overall societal demand and supply adjustment. But performing these vital roles, the commercial banks are associated with different risks out of which credit risk hampers them a lot. This risk attacks the major pillar of the banking industry i.e., solvency on which the industry survives. In this paper, a modest attempt is made to identify the bank-specific determinants of credit risk in the public sector commercial banks in India. Data was collected from the RBI database for the period 2005 to 2020 for 13 banks. Variables pertaining to credit risk, bank size, capital adequacy ratio, profitability, liquidity and diversification were taken. These variables were analysed with the help of different panel data analytical tools. The size of the bank, represented by the log of total assets, and diversification, measured as the ratio of non-interest income to total income, were found to positively and significantly influence credit risk in public sector commercial banks. The Return on Asset, Loan-deposit ratio, and Capital adequacy ratio were found to be negatively correlated with credit risk.

Analysis Of 4-Bit Absolute Value Detector for ECG Signal Comparation

In the present era, where numerous heart conditions are prevalent, the significance of monitoring cardiac electrical signals has surged within the medical realm. Within this study, we leverage Complementary Metal Oxide Semiconductor (CMOS) and Pass-transistor Logic (PTL) methodologies for crafting and refining a 4-bit absolute value detection mechanism. This mechanism serves to identify and juxtapose electrocardiogram (ECG) signals. The 4-bit absolute value detection system is bifurcated into two core segments: one for absolute value identification and the other for comparative analysis. This setup facilitates a binary input's comparison with a predetermined threshold, thereby yielding a corresponding comparative outcome. Subsequently, a meticulous assessment is conducted on the lengthiest pathway, which is then subject to refinement through gate sizing and voltage supply (Vdd) adjustments. The findings unveil a delay of 34.13tp0 and an energy dissipation of 184.832 C. The resultant 4-bit absolute value detection mechanism, borne from this research institution's efforts, emerges as an invaluable asset in the medical domain, attributed to its exceptional optimization with respect to minimal delay and energy outlay.

Cloud computing resource load prediction based on improved VMD and attention mechanism

Dynamic adjustment of resource supply according to users’ resource load is one of the important technologies to achieve efficient management of cloud computing resources. In order to accurately obtain users’ demand for resource load in the future, based on quantum particle swarm optimization (QPSO), a prediction model QVMD_AM_LSTM was proposed to optimize variational mode decomposition (VMD) and to add attention mechanism to AM_LSTM. A comparative experiment was conducted on the open-source dataset cluster-trace-v2018 from Alibaba Cloud. The outcomes show that compared with LSTM, AM-LSTM, GRU-LSTM, Refined-LSTM, Stacked-LSTM and other existing prediction models, the mean square error of the QVMD_AM_LSTM model proposed in this article decreases by 8-14, and the correlation coefficient rises by 6%-11%. QVMD_AM_LSTM model has higher prediction accuracy.

TCI Tester: A Chip Tester for Inductive Coupling Wireless Through-Chip Interface

The building block computation system is constructed by stacking various chips three-dimensionally. The stacked chips incorporate the same TCI IP (Through Chip Interface Intellectual Property) but cannot provide identical characteristics, requiring adjustments in power supply and bias voltage. However, providing characteristics measurement hardware for all chips is difficult due to the limitation of chip area or pin numbers. To address this problem, we developed TCI Tester, a small chip to measure electric characteristics by stacking on TCI of every chip. By stacking two TCI Tester chips, it appears that the up-directional data transfer has a stricter condition than down directional one on power supply voltage and operational frequency. Also, the transfer performance is poorer than designed. Similar measurement results are obtained by stacking TCI Tester on other chips with TCI IP. To investigate the reason, we analyzed the power grid resistance of various chips with the TCI IP. Results also showed that the chips with higher resistance have a narrow operational condition and poorer performance. The results suggest that the power grid design is important for keeping the performance through the TCI channel.

Research on the air supply adjustment technology of breath-following powered air-purifying respirators

In the hope of reducing the air supply flow of the powered air-purifying respirator (PAPR) and extending the service life of the filter, a breath-following powered air-purifying respirator (BF-PAPR) that can dynamically adjust the air supply flow according to the breathing flow is proposed. The BF-PAPR changes the air supply flow by adjusting the speed of the variable-frequency centrifugal fan according to the air velocity at the half mask outlet (vhm) monitored by the modular wind speed transmitter. In the study, the air supply flow adjustment model of the BF-PAPR is developed. It is found that the filtration resistance barely influences vhm. In addition, under the same mean inhalation flow, the minimum outlet air velocity increases first and then decreases with the increase of the duty cycle variation coefficient (λ), while the maximum outlet air velocity decreases first and then increases. Moreover, the minimum air supply flow of the BF-PAPR is achieved when the standard value of the air velocity is 13.4 m/s and the value of λ is 1. The BF-PAPR can reduce the air supply flow by 6.5%-8.6% and the energy consumption by approximately 20% compared with the PAPR, which is beneficial for reducing the usage cost and extending the continuous working time.

Molecular Study on Twin Cohort with Discordant Birth Weight.

The increased rate of twinning has pointed out newer challenges in clinical practices related to gestational complications, intrauterine growth restriction, perinatal mortality, and comorbidities. As a twin pregnancy progresses, the increased demand for oxygen supply can easily disrupt the redox homeostasis balance and further impose a greater challenge for the developing fetuses. A substantial birth-weight difference acts as an indicator of a deficit in oxygenation or blood flow to one of the fetuses, which might be related to a low bioavailable nitric oxide level. Therefore, in this study, we focused on networks involved in the adjustment of oxygen supply, like the activation of inducible and endothelial nitric oxide synthase (NOS3) along with free radical and lipid peroxide formation in mature twin pairs with high birth-weight differences. The selected parameters were followed by immunofluorescence staining, fluorescence-activated cell sorting analysis, and biochemical measurements in the umbilical cord vessels and fetal red blood cells. Based on our data set, it is clear that the lower-weight siblings are markedly exposed to persistent intrauterine hypoxic conditions, which are connected to a decreased level in NOS3 activation. Furthermore, the increased level of peroxynitrite aggravates lipid peroxidation and induces morphological and functional damage and loss in redox homeostasis.