Inappropriate Allocation Research Articles

NIMG-07. GLIOBLASTOMA AS A MIMIC OF ACUTE ISCHEMIC STROKE: AN UNDERRECOGNIZED PHENOMENON AND THE IMPACT ON PATIENT OUTCOMES

Abstract BACKGROUND Glioblastoma may present similarly to acute ischemic stroke. This study aims to determine characteristics and outcomes of patients with glioblastoma presenting with stroke-like symptoms. Our objective is to characterize patients with glioblastoma who present as mimics of acute ischemic stroke and identify differences in outcomes when compared to those diagnosed with glioblastoma only. METHODS The 2016-2019 National Inpatient Sample (NIS) database was queried for all patients who had a new diagnosis of glioblastoma. Patients with new glioblastoma who carried an admission diagnosis of acute ischemic stroke, but did not undergo thrombectomy, chemical thrombolysis, or hemicraniectomy were categorized as “GBM-Stroke Mimic”. The characteristics and comorbidities between GBM-Stroke Mimic and new glioblastoma patients were compared. Primary outcomes analyzed were discharge disposition and mortality. RESULTS Of 61,755 patients newly diagnosed with glioblastoma, 1,000 (1.6%) were GBM-Stroke Mimics. GBM-Stroke Mimic patients more commonly presented with aphasia (P < 0.001) and hemiplegia (P < 0.001). Age greater than 65, atrial fibrillation, diabetes mellitus, hypertension, hyperlipidemia, and long-term anticoagulation/antiplatelet therapy were more commonly associated with GBM-Stroke Mimic patients (all P < 0.001). GBM-Stroke Mimic patients were more likely to be discharged to skilled nursing facility, (p < 0.001), and a diagnosis of GBM-Stroke Mimic was an independent risk factor for inpatient death (P < 0.001). CONCLUSION To our knowledge, this is the first study formally investigating the clinical outcomes of glioblastoma when initially diagnosed as stroke. When this misdiagnosis is made, we found an association with increased inpatient mortality, delays of care, and inappropriate resource allocation.

Maladaptive behaviors in disasters: case study evaluation of Hurricane Hugo, Hurricane Katrina and the Haiti Earthquake.

Maladaptive behaviors during a disaster refer to actions that do not benefit the individual or society. Quarantelli highlights several maladaptive behaviors myths associated with disasters: widespread antisocial behavior, passivity, role conflict or abandonment, and sudden widespread mental health breakdowns (1). Despite early work reporting these myths, the common perception is that maladaptive behaviors such as rioting, looting, panic, and criminal conduct are prevalent in the wake of disasters. This is despite research by de Ville de Goyet and Arnold which has called on public officials and the media to stop propagating false disaster myths (2, 3). The classic academic response has been that this is a misconception and that, in fact, such behaviors are a very small part of the overall disaster and are mostly non-existent. Misconceptions about the prevalence of maladaptive behaviors can lead to inappropriate resource allocation, such as allocating extra police officers to prevent looting when the overall crime rate for the most part, decreases during disasters (4). Furthermore, while there are several persistent maladaptive behaviors myths, this is confounded by the presence of actual negative behaviors post disaster: false damage claims, insurance fraud, illegally obtaining relief supplies, failure to provide contracted repair services, hoarding of essential items, psychological trauma (which can lead to intergenerational transmission of the disaster memory) and medications and price gouging (5).When reading lay-press articles about recent disasters, it appears that these behaviors are on the rise. This raises the question: Has there been a change in the basic human reaction to disasters and are maladaptive behaviors on the rise? This review article focuses on case studies from three natural disasters: Hurricanes Hugo and Katrina, and the Haiti Earthquake. The goal of this review article is to evaluate these three natural disasters for evidence of maladaptive behaviors.

Patronage Pattern and Accessibility of Healthcare Facilities in Urban Slums and Informal Settlements in Ibadan Metropolis

Slums and informal settlements are residential areas physically and socially disintegrated. In spite of this, inadequate health-related data on slum areas and informal settlements has led to inappropriate and unrealistic allocation of healthcare resources by the public and private health providers. This study investigates the patronage pattern and accessibility of healthcare facilities to residents of urban slums and Informal settlements in Ibadan Metropolis, a rapidly growing urban area in Nigeria facing challenges related to urbanization and healthcare infrastructure. Data were collected from both primary and secondary sources. Structured questionnaire was administered on 1,389 residents of the slummy neighbourhoods and informal settlements in Ibadan metropolis, and obtained data were analyzed using descriptive and inferential statistics. Results revealed that out of 109 neighbourhoods, 42.1% were categorized as slummy neighbourhoods, 36.7% as slums/informal settlements, while 21.2% were informal settlement using slummy and informality conditions respectively. Results revealed that distance to health facility (β= -0.353, p<0.05), educational qualification (β=-0.063, p<0.05) and household size (β= -0.052, p<0.05) had an inverse relationship with patronage of health facilities, while age (β=0.086, p< 0.05) had a positive relationship. It was also revealed that access to PHC and dispensary/clinic in slummy neighbouhoods and slum/informal settlements is higher compared to informal settlements in the study area. The study therefore recommends implementation of slum improvement program for the slummy and slums/informal neighbourhoods, provision of additional healthcare facilities to be located especially in the slummy neighbourhoods and informal settlements to ensure equitable distribution.

Why should imminent international funds for solar photovoltaics go to families and the private sector and not to the government to stop the electricity crisis in Lebanon?

In Lebanon, the failure to supply oil-based electricity was mostly due to flawed management, increasing costs of bills of private generators, the rise of fuel prices, and the absence of subsidies. In response, individuals have started funding small-scale rooftop PV (RPV) to increase the solar share beyond the national target while the government has struggled for years to pass bidding phases for 12 utility-scale PV (USPV). In addition to publicly unavailable details, specifications, assessments, and termination plans about the 12 solar farms, their geographical sitting was not technically evaluated. Therefore, this study mapped USPV suitability in Lebanon using a multi-criteria decision-making algorithm. Although the highly suitable lands can supply 40% of the total land needed to cover the peak demand, the areas were not equally distributed throughout the governorates. Even if USPV can help reach national solar targets, investing in public-related projects can be perilous, especially with historical patterns of inappropriate allocation of funding, political instability, and absence of accountability. Thus, investing in RPV can be more attractive due to its efficiency, grid independence, and flexibility and should be oriented primarily towards low-income families and small entrepreneurs and later to wealthier people to ensure social equity and welfare.

The Effect of Comprehension on Omissions in English-Arabic Simultaneous Interpreting

This study aims to investigate the relationship between comprehension, based on the problem triggers as an indicator, and accuracy, based on the criterion of omission during English-Arabic simultaneous interpreting. In these cases, the less comprehension, the more omissions in the interpretation, the lower the accuracy. The performances of 5 MA students at the Department of Translation, College of Arts, University of Mosul, are transcribed and analyzed using the hybrid model of Larson’s (1984) “Translation Quality Assessment” and Gile’s (2009) “Effort” Models. Having analyzed the accuracy of the interpretations, a significant number of omissions were noticed due to inappropriate allocation of the processing capacity for comprehension. The study concludes that comprehension is the essential processing capacity effort and a vital determinant of the accuracy of the interpretation. The different levels of exercising the comprehension processing capacity measured by the SL problem triggers lead to different accuracy levels starting with high accuracy and ending with inaccuracy.

Durasi Observasi Ideal untuk Penentuan Kebutuhan Tenaga Non Kesehatan Rumah Sakit dengan Metode WISN: Tinjauan Literatur

The increasing need for trained healthcare workers is currently faced by most hospitals in developing countries. Hospitals as health service providers need to plan policies that ensure the availability and sufficiency of human resources. Inappropriate proportions and allocation of human resources can have a negative impact on service quality. The WISN methodology helps determine the number of health workers of a particular type needed to cover the workload. However, in the guidelines, there is no ideal limit for the duration of observations carried out by institutions to obtain accurate and representative data. The purpose of this article is to determine the duration of observation to determine the need for non-health hospital personnel using the WISN method. The method used in this literature review is library research sourced from online databases such as Mendeley and Google Scholar. This study focuses on analyzing the workload of non-health human resources within hospitals and the ideal duration of observation in research by searching using keywords with boolean approach. We found 92 articles and after evaluation, five articles were selected for this study. From various studies, we found that there is still an excessive workload in several institutions so it could be a consideration to increase staff number according to the WISN method. According to the duration of observation, in research with a duration of ten days, the description of activities that can be recorded cannot represent the entire activity and some problems cannot be completely identified due to time limitations.

Mixed-method study on the association between inclusion to conditional cash transfer program and the multiple faces of malnutrition in children and adolescents aged 3 to 19 years: a school-based evidence from Caraga Region, the Philippines

BackgroundThis study aimed to investigate the association between inclusion to Pantawid Pamilyang Pilipino Program (4Ps), a CCT program in the Philippines, and malnutrition in children and adolescents and examine the perceptions and experiences of parents and other stakeholders on how 4Ps influenced child nutrition.MethodsA concurrent mixed-method study was conducted in the Caraga Region, Philippines. Quantitative data from 5541 children and adolescents aged 3 to 19 were analyzed using multilevel mixed-effect logistic models. To allow in-depth understanding of the programmatic components that support the findings from the quantitative study, eight focused group discussions (FGDs) were concurrently conducted, cumulating 33 participants, including 4Ps parents, school coordinators/teachers, and school nurses. A constructivist grounded theory approach was used for analysis, and joint displays were employed to integrate quantitative and qualitative results.ResultsQuantitative findings revealed high rates of malnutrition, with significant rates of stunting (12.0%), wasting/thinness (9.4%), and overweight/obesity (16.4%) among children and adolescents. 4Ps beneficiaries had higher odds of stunting and overweight/obesity compared to non-4Ps beneficiaries (AOR = 1.43, 95%CI: 1.08–1.91; AOR = 1.21, 95%CI: 1.01–1.45, respectively). However, no significant association was observed between inclusion to 4Ps and concurrent stunting and wasting/thinness or overweight/obesity (AOR = 1.05, 95%CI: 0.72–1.55). Geographic variations were observed, with 4Ps children in Agusan del Sur having lower odds of stunting than those in Agusan del Norte (AOR = 0.41, 95%CI: 0.23–0.71). Age and gender also showed significant associations with malnutrition. The qualitative analysis provided insights into the challenges contributing to malnutrition, including child labor, sickness, long distances to school, limited access to healthy food, and larger families. Unintended consequences such as cash card mismanagement, inappropriate cash grant allocation, and falsification of school attendance were identified. However, teachers and parents demonstrated resilience by implementing adaptive approaches to enhance child nutrition.ConclusionsWhile 4Ps beneficiaries exhibit higher odds of stunting and overweight/obesity, the program’s association with malnutrition was significantly influenced by geographic variations. It is crucial for social protection programs to prioritize comprehensive support strategies that effectively counter unintended consequences and challenges faced by beneficiaries and other stakeholders and address malnutrition in children and adolescents.

A Coordinated Allocation Method for Right-Turn Strategy at Signalized Intersections with Optimal Pedestrian and Vehicle Delays

With strict enforcement of pedestrian right of way at all intersections, the inappropriate right-turn resource allocation from a spatial and temporal perspective will lead to a reduction in the operational efficiency of the intersection. In this paper, three spatiotemporal resource allocation schemes for right-turning vehicles are proposed, considering the vehicle and pedestrian traffic efficiency in all directions of the intersection. To minimize vehicle and pedestrian delay at the intersection individually, an optimization model is established with the effective green time of each phase and three schemes as decision variables. A right-turn vehicle and pedestrian conflict delay model is developed based on the pedestrian-vehicle interaction behavior as the constraints of the optimization model. The NSGA-II algorithm is used to solve the model, and the quantitative criteria for the exclusive right-turn lane and phase are obtained by sensitivity analysis. The results of this paper can be used as a guide for traffic design and for planning and controlling the operation of right-turning vehicles at intersections.

Trajectories of soil microbial recovery in response to restoration strategies in one of the largest and oldest open-pit phosphate mine in Asia

Southwestern China has the largest geological phosphorus-rich mountain in the world, which is seriously degraded by mining activities. Understanding the trajectory of soil microbial recovery and identifying the driving factors behind such restoration, as well as conducting corresponding predictive simulations, can be instrumental in facilitating ecological rehabilitation. Here, high-throughput sequencing and machine learning-based approaches were employed to investigate restoration chronosequences under four restoration strategies (spontaneous re-vegetation with or without topsoil; artificial re-vegetation with or without the addition of topsoil) in one of the largest and oldest open-pit phosphate mines worldwide. Although soil phosphorus (P) is extremely high here (max = 68.3 mg/g), some phosphate solubilizing bacteria and mycorrhiza fungi remain as the predominant functional types. Soil stoichiometry ratios (C:P and N:P) closely relate to the bacterial variation, but soil P content contributes less to microbial dynamics. Meanwhile, as restoration age increases, denitrifying bacteria and mycorrhizal fungi significantly increased. Significantly, based on partial least squares path analysis, it was found that the restoration strategy is the primary factor that drives soil bacterial and fungal composition as well as functional types through both direct and indirect effects. These indirect effects arise from factors such as soil thickness, moisture, nutrient stoichiometry, pH, and plant composition. Moreover, its indirect effects constitute the main driving force towards microbial diversity and functional variation. Using a hierarchical Bayesian model, scenario analysis reveals that the recovery trajectories of soil microbes are contingent upon changes in restoration stage and treatment strategy; inappropriate plant allocation may impede the recovery of the soil microbial community. This study is helpful for understanding the dynamics of the restoration process in degraded phosphorus-rich ecosystems, and subsequently selecting more reasonable recovery strategies.

A new boredom-aware dual-resource constrained flexible job shop scheduling problem using a two-stage multi-objective particle swarm optimization algorithm

Dual-resource constrained flexible job shop scheduling problem has become a hot research field in recent years. However, few studies have considered workers’ boredom sensations when allocating resources and scheduling tasks, leading to inappropriate task allocation and negative effects such as efficiency reductions and absenteeism. Therefore, a new boredom-aware dual-resource constrained flexible job shop scheduling problem is investigated in this study, which considers the increase in workers’ boredom caused by repetitive job assignments and constructs an efficiency function to characterize the impact of workers’ boredom. For this problem, a bi-level lexicographic model, which takes the effective completion of all manufacturing tasks as the primary optimization objective and higher worker job satisfaction as the secondary optimization objective, is established. A two-stage multi-objective particle swarm optimization algorithm with a three-dimensional representation scheme is presented to solve this model. In this algorithm, a new position-updating mechanism and a local search strategy are devised to effectively evolve the solution, and a decomposition strategy with a self-adaptive neighborhood size and a boundary exploration mechanism are embedded to obtain a uniformly distributed Pareto front. Experimental results confirm the superiority of the presented model and algorithm.

Leveraging Cost Accounting to Manage Earnings: Evidence from Toshiba’s Semiconductor Business

ABSTRACT This case pertains to the interplay of cost accounting, performance measurement, and financial reporting issues in Toshiba’s semiconductor business. It addresses how Toshiba manipulated its reported profits by inappropriately allocating its budgeted fixed overheads and not recognizing inventory losses in a timely manner in the financial statements. These manipulations overstated profits of the semiconductor business by ¥36.0 billion, almost a quarter of the total of Toshiba Corporation’s ¥151.8 billion profit overstatement. The investigation report indicated that the profit manipulations were a likely outcome of top management’s unrealistic expectations. For the semiconductor business of Toshiba, the timely recognition of inventory losses would have offset the profit misstatements resulting from the inappropriate allocation of budgeted fixed overheads. Alternatively, proper allocation of budgeted fixed overheads would have reduced or even avoided the need to recognize inventory losses. The case provides an integrative view of cost and financial accounting.

Experience and Resilience of Japanese Public Health Nurses during the COVID-19 Pandemic and Their Impact on Burnout.

Japanese public health nurses (PHNs) at public health centers (PHCs) have played critical roles in infection prevention and control during the COVID-19 pandemic. This study aimed to examine the actual pandemic-related experiences of PHNs and the relation between their experiences, individual resilience, two components of organizational resilience (system and human resilience), and burnout. An analysis of the responses of 351 PHNs revealed that mid-level PHNs scored higher in experience and lower in organizational resilience compared with those in other positions. More than 80% of respondents experienced inappropriate staff allocation. Multiple regression revealed that burnout was positively associated with the components of the experience of PHNs and negatively with individual and human resilience. In hierarchical multiple regression with depersonalization as the dependent variable, the sign of system resilience reversed from negative to positive when human resilience was added. The results highlight the need to prepare for future health crises including establishing a system with enough personnel, promoting human resilience such as collaboration among staff members, and burnout prevention measures, especially among mid-level PHNs. The study also described alternative approaches to comprehend system resilience-namely, a suppression variable of human resilience, promotion of depersonalization, and multicollinearity-and the need for further research on organizational resilience.

Assessing the risk of endogeneity bias in health and mortality inequalities research using composite measures of multiple deprivation which include health-related indicators: A case study using the Scottish Index of Multiple Deprivation and population health and mortality data.

The inclusion of health-related indicators in composite measures of multiple deprivation introduces a risk of endogeneity bias when using the latter in health inequalities research. This bias may ultimately result in the inappropriate allocation of healthcare resources and maintenance of preventable health inequalities. Mitigation strategies to avoid this bias include removing the health-related indicators or using single constituent domains (such as income or employment class) in isolation. These strategies have not been widely validated. This study used population-level health and mortality data with a contemporary composite measure of multiple deprivation (Scottish Index of Multiple Deprivation; SIMD) to assess these mitigation strategies. The differences between deprivation methods (original, health excluded, and income domain) were negligible. The results of quantitative research on health inequalities are unlikely to be affected by endogeneity bias.

COVID-19 emerging risk assessment for the construction industry of developing countries: evidence from Iraq

In developing countries, the construction industry has been one of the hardest hit by the COVID-19 pandemic. The impact of the pandemic has created a whole new set of risks, causing workforce-related issues, supply chain disruptions, and legal and contractual implications. This research aims to identify and quantitatively analyse COVID-19 emerging risks in the construction industry of Iraq. A mixed method approach was used for data collection and analysis, including a focus group session to identify COVID-19 emerging risks, a survey to rate the identified risks, and the development of a fuzzy-based risk assessment model to analyse the level of riskiness of the identified risks. Results indicate that the most critical COVID-19 risks are (1) contract suspension, (2) contractor bankruptcy, (3) materials price escalation, (4) construction contract claims, (5) inappropriate risk allocation, (6) non-compliance with social distancing guidelines, (7) skills shortage, and (8) poor site and virtual communication. This paper contributes to the body of knowledge by providing academics and industry practitioners with a more comprehensive understanding of the risks arising from the COVID-19 pandemic. Moreover, this paper presents a novel model for analysing risks related to extreme conditions, such as the COVID-19 pandemic and future pandemics.

Design and Implementation of an Improved Automatic DC Motor Speed Control Systems Using Microcontroller

Energy wastage is one of the major challenges that is facing the world now as there is insufficient supply of energy and the little ones supplied was not appropriately used. This energy wastage has made many researchers to engage more on the research to stop this energy waste as a result of inappropriate allocation of energy to some devices even when they don’t need it. This research work was able to design and implement an improved automated DC Motor speed controller system using microcontroller successfully. The software used for this research work were Fritzing software and Arduino Nano. This project was able to improve on the working system of the DC Motors and energy was automatically and successfully saved. The system runs entirely on Bluetooth technology which consumes less power than other devices. The Android application is user-friendly with enhanced Wireless communication. This design was successfully developed and implemented with 80% accuracy. The design was able to work effectively by increasing the cutting speed when the softness of the material decreases and as the cutting tool material becomes stronger, the cutting speed increases. This showed that the design is effectively and efficiently developed with less energy/power consumption which is the earnest desire of an Engineer as it reduces cost. Keywords: Microcontroller, Improved Automatic DC Motor, Energy, Arduino, PWM

Blunted pupil light reflex is associated with negative symptoms and working memory in individuals with schizophrenia

Two largely separate lines of research have documented altered pupillary dynamics in individuals diagnosed with schizophrenia. An older set of studies has demonstrated reductions in the pupillary light reflex (PLR) in individuals with schizophrenia; however, clinical and cognitive correlates of this blunted PLR have been relatively unexplored. More recently, a large body of work has demonstrated reductions in pupillary dilation in response to cognitive demands in individuals with schizophrenia, and the degree of this blunted pupil dilation has been related to more severe cognitive deficits and motivational negative symptoms. These clinically relevant alterations in the cognitive modulation of pupil size have been interpreted as reflecting insufficient information processing resources or inappropriate effort allocation. To begin to bridge these two lines of work, we investigated the PLR in 34 individuals with schizophrenia and 30 healthy controls and related the amplitude of the PLR to motivational negative symptoms and cognitive performance. Consistent with prior work, we found that the PLR was reduced in individuals with schizophrenia, and furthermore, that these measurements were highly reliable across individuals. Blunted constriction was associated with more severe motivational negative symptoms and poorer working memory among individuals with schizophrenia. These observed correlates provide a bridge between older literature documenting an altered PLR and more recent work reporting associations between negative symptoms, cognition, and blunted pupillary dilation in response to cognitive demands in individuals with schizophrenia. We provide possible mechanistic interpretations of our data and consider a parsimonious explanation for reduced cognitive- and light-related modulation of pupil size.

Assessing Multi-Temporal Global Urban Land-Cover Products Using Spatio-Temporal Stratified Sampling

In recent years, the availability of multi-temporal global land-cover datasets has meant that they have become a key data source for evaluating land cover in many applications. Due to the high data volume of the multi-temporal land-cover datasets, probability sampling is an efficient method for validating multi-temporal global urban land-cover maps. However, the current accuracy assessment methods often work for a single-epoch dataset, and they are not suitable for multi-temporal data products. Limitations such as repeated sampling and inappropriate sample allocation can lead to inaccurate evaluation results. In this study, we propose the use of spatio-temporal stratified sampling to assess thematic mappings with respect to the temporal changes and spatial clustering. The total number of samples in the two stages, i.e., map and pixel, was obtained by using a probability sampling model. Since the proportion of the area labeled as no change is large while that of the area labeled as change is small, an optimization algorithm for determining the sample sizes of the different strata is proposed by minimizing the sum of variance of the user’s accuracy, producer’s accuracy, and proportion of area for all strata. The experimental results show that the allocation of sample size by the proposed method results in the smallest bias in the estimated accuracy, compared with the conventional sample allocation, i.e., equal allocation and proportional allocation. The proposed method was applied to multi-temporal global urban land-cover maps from 2000 to 2010, with a time interval of 5 years. Due to the spatial aggregation characteristics, the local pivotal method (LPM) is adopted to realize spatially balanced sampling, leading to more representative samples for each stratum in the spatial domain. The main contribution of our research is the proposed spatio-temporal sampling approach and the accuracy assessment conducted for the multi-temporal global urban land-cover product.

Optimizing protection resource allocation for traffic-driven epidemic spreading.

Optimizing the allocation of protection resources to control the spreading process in networks is a central problem in public health and network security. In this paper, we propose a comprehensive adjustable resource allocation mechanism in which the over allocation of resources can be also numerically reflected and study the effects of this mechanism on traffic-driven epidemic spreading. We observe that an inappropriate resource allocation scheme can induce epidemic spreading, while an optimized heterogeneous resource allocation scheme can significantly suppress the outbreak of the epidemic. The phenomenon can be explained by the role of nodes induced by the heterogeneous network structure and traffic flow distribution. Theoretical analysis also gives an exact solution to the epidemic threshold and reveals the optimal allocation scheme. Compared to the uniform allocation scheme, the increase in traffic flow will aggravate the decline of the epidemic threshold for the heterogeneous resource allocation scheme. This indicates that the uneven resource allocation makes the network performance of suppressing epidemic degrade with the traffic load level. Finally, it is demonstrated that real-world network topology also confirms the results.

Triage Errors in Primary and Pre-Primary Care.

Triage errors are a major concern in health care due to resulting harmful delays in treatments or inappropriate allocation of resources. With the increasing popularity of digital symptom checkers in pre–primary care settings, and amid claims that artificial intelligence outperforms doctors, the accuracy of triage by digital symptom checkers is ever more scrutinized. This paper examines the context and challenges of triage in primary care, pre–primary care, and emergency care, as well as reviews existing evidence on the prevalence of triage errors in all three settings. Implications for development, research, and practice are highlighted, and recommendations are made on how digital symptom checkers should be best positioned.

Load Balancing Optimization of In-Memory Database for Massive Information Processing of Internet of Things (IoTs)

Based on the analysis of the key technologies of the Internet of Things service platform architecture, a load balancing optimization scheme of in-memory database based on the massive information processing of the Internet of Things service platform is proposed. This scheme firstly proposes a system model that can satisfy the mass sensor information processing under the open platform environment and designs several functional unit modules of the system. By combining these functional units, the service can be configured for thousands of services and tenants. This paper presents an adaptive strategy selection method, which can automatically select the optimization strategy by dividing the position and querying the selection rate to improve the efficiency of the adaptive index algorithm. The index structure is initialized by parallel sorting algorithm, and the query statement is executed and the index structure is optimized by thread level parallel and radix sort methods. An elastic pipeline technique is proposed, which includes an elastic iterator model and a dynamic scheduler. The elastic iterator model is an upgrade of the traditional iterator model, adding the characteristics of dynamic multicore execution. In the process of query processing, dynamic scheduler monitors the load of each node in real time and dynamically adjusts the parallelism, so as to realize the load balance of in-memory database and maximize the utilization of hardware resources. The elastic pipeline realizes the isolation of parallelism from query compilation to avoid inappropriate parallelism allocation caused by missing and insufficient information during query compilation.