Ideal Situations Research Articles

Determination of Surface Roughness Throughout CNC Turning of ASTM 316 Steel Expending Taguchi Method

Plan of experiment involving Taguchi method got developed and executed to gauge impact of various machining variables (V, F and D) on surface roughness throughout CNC turning of ASTM 316 steel using coated carbide insert. Research findings through different mathematical analyses provided the effective guideline for choosing appropriate machine settings to realize surface roughness within the recommended range during stated turning operation. Ideal machining situations got determined to minimize the surface roughness (here surface roughness factors Ra with Rz) in turning of the same. Feed remains observed as paramount momentous variable for workpiece surface roughness. Furthermore, cutting speed remains observed as subsequent paramount momentous variable for workpiece surface roughness. Additionally, depth of cut remains observed as least paramount momentous variable for workpiece surface roughness, Rz only, however, depth of cut got absolutely insignificant impression on Ra. Present investigation clearly reveals that multicoated carbide inserts performed splendidly at optimal machining variables combination of V = 150 m/min, F = 0.10 mm/rev with D = 0.4 mm. Calculated ideal limit of sample surface unevenness, Ra and Rz are 0.16 μm ≤ Ra ≤ 0.52 μm and 1.4 μm ≤ Rz ≤ 3.1 μm, respectively. Moreover, surface roughness, Ra is also within stipulated precarious limit of 1.5 μm (i.e. Ra < 1.5 μm) for turning with coated carbide inserts.

Redes sociales: Recursos interactivos y la información sobre salud

Dentro del ámbito sanitario, la evolución de la Web 2.0 también se ha hecho patente, y con el paso de los años se observa un cambio hacia una sociedad cada vez más informada sobre salud en Internet, hasta el punto de adoptar nuevos términos para nuestro vocabulario como el de eSalud. La llegada de las redes sociales (RR. SS.) digitales -consideradas el principal estandarte de este nuevo entorno digital- supuso una nueva vuelta de tuerca en la evolución de la comunicación hipermedia y en los modelos de comunicación tradicionales.Las RR. SS. y la salud han establecido una fuerte relación. Y, es que no hay duda de que los social media están afectando a la forma en la que las personas, de los países con índices de desarrollo humano más altos, gestionan su salud. En el ámbito poblacional, el análisis de patrones y tendencias de las búsquedas en plataformas digitales pueden proporcionar información valiosa sobre el comportamiento relacionado con la salud de las poblaciones.En la atención domiciliaria paciente y familia pasan de espectadores a protagonistas, asumen una posición más activa tanto en la comunicación como en la toma de decisiones. Se podría pensar que las RR. SS. son dominio exclusivo de la generación más joven. Sin embargo, muchos son los adultos, incluso de edad avanzada, que las han adoptado con entusiasmo para mantenerse al día, así como para relacionarse con sus conocidos y familiares.Como ya se ha estudiado, las RR. SS. han demostrado su potencial en la provisión remota de supervisión clínica. No obstante, es importante prestar especial atención a tres importantes circunstancias: la proporción del adecuado aprendizaje, el adecuado proceso de uso y su supervisión.Se puede concluir que en “situaciones ideales” las RR. SS. presentan beneficios para todas las partes implicadas en el cuidado domiciliario de la salud.

Optimal rail system design with multiple layers of fault and event trees

A rail system comprises several subsystems and corresponding components. Each element has its life cycle cost (LCC), reliability, and consequences of failure (as described by historical data or an event tree). Determining the optimal rail system design reveals different trends in these characteristics. This research develops an optimization process using two modules to assist the operator in deciding such optimal design. The conversion module first transforms multiple fault tree layers into a simple structure and avoids nonlinear formulation in the optimization model. Then, the optimal system design module identifies the optimal investment plan for rail systems according to available alternatives. Two empirical cases demonstrate the applicability of the proposed optimization process. The first case proves that the conversion module efficiently transforms a fault tree structure. Note that considering data uncertainty into the failure rate requires additional budget allocation to reduce delay costs under ideal and practical situations. The second case indicates that the optimization model can solve a multi-objective problem while considering the LCC and consequences of failure, as well as assist the operator in deciding the appropriate requirement according to their demand.

Analysis and Application of Modified ZNN Design With Robustness Against Harmonic Noise

The Zhang neural network (ZNN) has recently realized remarkable success in solving time-varying problems. Harmonic noise widely exists in industrial applications and can severely affect the solution computed by ZNN models. This article attempts to solve the aforementioned limitations by providing the first ZNN design with an inherent capability to prohibit harmonic noise. Moreover, it opens new opportunities to shift the research on ZNNs in ideal situations to that with theoretical consideration on nonideal working environments. We establish a modified ZNN design formula in a noisy environment by incorporating the dynamics of harmonic signals. Theoretical analysis shows the convergence of the proposed ZNN design. An application case study for the new ZNN model verifies its effectiveness for time-varying matrix inversion in the presence of harmonic noise. The simulation further substantiates the effectiveness, superiority, and application prospects of the proposed ZNN design.

Interlude of metastability in the melting of polymer crystals.

We have studied the process of melting of polymer crystals using Langevin dynamics simulations with a coarse-grained united atom model. We have considered two ideal situations: one in which a single crystal melts and the other in which a multichain crystal melts. We show that the melting of the single crystal proceeds through a globular metastable state, which is followed by expansion to a more random coil-like state. Similarly, the melting of the multichain crystal reveals a special mechanism comprising two steps: one in which a long-lived partially molten metastable state is formed, followed by a second step in which the chains peel off from the crystalline core to a free state. We elucidate the nature of the metastable state close to the equilibrium melting temperature and show that the multichain crystals equilibrate to states of intermediate order, with the extent of ordering decreasing as we increase the melting temperature. We quantify the kinetics of melting by estimating a free energy landscape using parallel tempering Langevin dynamics simulations. These simulations reveal a metastable state in the single molecule systems, allowing us to estimate the free energy barriers. Additionally, the melting of the multichain crystals reveals the existence of two barriers, with the preference for the intermediate state reducing with increasing temperature. We compare our findings to the existing experimental evidence and find qualitative agreements.

OR-Skip-Net: Outer residual skip network for skin segmentation in non-ideal situations

Skin segmentation is one of the most important tasks for human activity recognition, video monitoring, face detection, hand gesture recognition, content-based detection, adult content filtering, human tracking, and robotic surgeries. Skin segmentation in ideal situations is easy to accomplish because it is with similar backgrounds. However, the skin segmentation in non-ideal situations is complicated due to difficult background illuminations, the presence of skin-like pixels, and environmental changes. The current studies are handling the mentioned challenges by adding the preprocessing stages in their methods, which increases the overall cost of the system. In addition, prevailing segmentation studies have ignored black skin and mainly focused on white skin for their experiments. To deal with skin segmentation in challenging environments irrespective of skin color, and to eliminate the cost of the preprocessing, this paper proposes an outer residual skip connection-based deep convolutional neural network (OR-Skip-Net) which innovatively empowers the features by transferring the direct edge information from the initial layer to the end of the network.Experiments were performed on the following eight open datasets for skin segmentation in different environments: hand gesture recognition dataset, event detection dataset, laboratoire d'informatique en image et systèmes d'information dataset, in-house dataset, UT-interaction dataset, augmented multi-party interaction dataset, Pratheepan dataset, and black skin people dataset. In addition, two other experiments were performed for gland segmentation from colon cancer histology images for the diagnosis of colorectal cancer using the Warwick-QU dataset and for iris segmentation using the Noisy Iris Challenge Evaluation - Part II dataset to explore the possibility of applying our method to different applications. Experimental results showed that the proposed OR-Skip-Net outperformed existing methods in terms of skin, gland, and iris segmentation accuracies.

FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions

The analog signals generated in the read-out electronics of particle detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital filters, which provides information about the energy deposited in the detector. The classical digital filters have a good performance in ideal situations with Gaussian electronic noise and no pulse shape distortion. However, high-energy particle colliders, such as the Large Hadron Collider (LHC) at CERN, can produce multiple simultaneous events, which produce signal pileup. The performance of classical digital filters deteriorates in these conditions since the signal pulse shape gets distorted. In addition, this type of experiments produces a high rate of collisions, which requires high throughput data acquisitions systems. In order to cope with these harsh requirements, new read-out electronics systems are based on high-performance FPGAs, which permit the utilization of more advanced real-time signal reconstruction algorithms. In this paper, a deep learning method is proposed for real-time signal reconstruction in high pileup particle detectors. The performance of the new method has been studied using simulated data and the results are compared with a classical FIR filter method. In particular, the signals and FIR filter used in the ATLAS Tile Calorimeter are used as benchmark. The implementation, resources usage and performance of the proposed Neural Network algorithm in FPGA are also presented.

Practical Considerations for Accuracy Evaluation in Sensor-Based Machine Learning and Deep Learning.

Accuracy evaluation in machine learning is based on the split of data into a training set and a test set. This critical step is applied to develop machine learning models including models based on sensor data. For sensor-based problems, comparing the accuracy of machine learning models using the train/test split provides only a baseline comparison in ideal situations. Such comparisons won’t consider practical production problems that can impact the inference accuracy such as the sensors’ thermal noise, performance with lower inference quantization, and tolerance to sensor failure. Therefore, this paper proposes a set of practical tests that can be applied when comparing the accuracy of machine learning models for sensor-based problems. First, the impact of the sensors’ thermal noise on the models’ inference accuracy was simulated. Machine learning algorithms have different levels of error resilience to thermal noise, as will be presented. Second, the models’ accuracy using lower inference quantization was compared. Lowering inference quantization leads to lowering the analog-to-digital converter (ADC) resolution which is cost-effective in embedded designs. Moreover, in custom designs, analog-to-digital converters’ (ADCs) effective number of bits (ENOB) is usually lower than the ideal number of bits due to various design factors. Therefore, it is practical to compare models’ accuracy using lower inference quantization. Third, the models’ accuracy tolerance to sensor failure was evaluated and compared. For this study, University of California Irvine (UCI) ‘Daily and Sports Activities’ dataset was used to present these practical tests and their impact on model selection.

Observation of topological gravity-capillary waves in a water wave crystal

The discovery of topological phases of matter, initially driven by theoretical advances in quantum condensed matter physics, has been recently extended to classical wave systems, reaching out to a wealth of novel potential applications in signal manipulation and energy concentration. Despite the fact that wave propagation in many realistic media (metals at optical frequencies, polymers at ultrasonic frequencies) is inherently dispersive, topological wave transport in photonic and phononic crystals has so far been limited to ideal situations and proof-of-concept experiments involving dispersionless media. Here, we report the first experimental demonstration of topological edge states in a classical water wave system supporting highly dispersive wave propagation, in the intermediate regime of gravity-capillary waves. We use a stochastic method to rigorously take into account the inherent dispersion and devise a water wave crystal insulator supporting valley-selective transport at topological domain walls. Our measurements, performed with a high-speed camera under stroboscopic illumination, unambiguously demonstrate the possibility of valley-locked transport of water waves.

Interest-free monetary policy and its impact on inflation and unemployment rates

Purpose This paper aims to examine the effects of interest-free and interest-based monetary policy on inflation and unemployment rates for two groups of countries where in one group, interest-free monetary policy (IFMP) was pursued, while in the other group, interest-based monetary policy (IBMP) was followed. Design/methodology/approach This study involves a sample of 23 developed countries divided into two groups. The authors measure economic performance by misery index (MI), and MI is calculated as unemployment rate plus inflation rate. A group of countries, where MI is lower, performs better compared to the other group where MI is relatively higher. Findings The results reveal that in group of 12 countries where IFMP is adopted, the MI is lower and thus performs better compared to a group of countries where IBMP is pursued. Research limitations/implications The findings of this study have profound implications for the policymakers and government leaders who look for a solution to maintain both low inflation and unemployment rates. The findings in this study clearly portray that such ideal situations can only be achieved by pursuing IFMP. No wonder the countries which have been historically pursuing IFMP such as Japan, Switzerland, Sweden, the Netherlands and Denmark have been able to contain both inflation and unemployment rates compared to their counterparts among the English-speaking countries. Originality/value This is one of the most recent tests on the differences in economic performance between IFMP and IBMP. These results have significant value for policymakers and central bankers who have been struggling to maintain lower MI for decades.

(Mis)Communicating with Geographic Information System Mapping: Part 2—Determining Data Cutoffs

The increasing use of geographic information system (GIS) technology in various fields suggests the need for professionals, including those in Extension, to be mindful of communicating data accurately and effectively. This article examines approaches to creating classes or groupings within data as well as the weaknesses of each approach. Data break units discussed in the article include equal intervals, quantiles, and units resulting from natural breaks. Ideal situations for each type of data break are presented. The article emphasizes the need for Extension professionals to consider the effects of data grouping to avoid miscommunication when using GIS mapping.

Multiqubit matter-wave interferometry under decoherence and the Heisenberg scaling recovery

Most matter-wave interferometry (MWI) schemes for quantum sensing are so far evaluated in ideal situations without noises. In this work, we provide assessments of generic multiqubit MWI schemes under Markovian dephasing noises. We find that for certain classes of the MWI schemes with scale factors that are nonlinearly dependent on the interrogation time, the optimal precision of maximally entangled probes \emph{decreases} with increasing the particle number $N$, for both independent and collective dephasing situations. This result challenges the conventional wisdom found in dephasing Ramsey-type interferometers. We initiate the analyses by investigating the optimal precision of multiqubit Sagnac atom interferometry for rotation sensing. And we show that due to the competition between the unconventional interrogation-time quadratic phase accumulation and the exponential dephasing processes, the Greenberger-Horne-Zeilinger (GHZ) state, which is the optimal input state in noiseless scenarios, leads to vanishing quantum Fisher information in the large-$N$ regime. Then our assessments are further extended to generic MWI schemes for quantum sensing with entangled states and under decoherence. Finally, a quantum error-correction logical GHZ state is tentatively analyzed, which could have the potential to recover the Heisenberg scaling and improve the sensitivity.

Hunting great white sharks could motor but prefer to mosey

Yuuki Watanabe has always been fascinated by speed and power. As a child, he recalls being transfixed by the space shuttle, bullet trains and the raw strength of great white sharks (Carcharadon carcharias). ‘They look cool’ says Watanabe, from the National Institute of Polar Research, Japan. However, he now has another reason for being in awe of these charismatic predatory sharks: ‘they are an endothermic fish’, he says. In other words, they maintain a warmer body temperature than the surrounding water – in contrast to most fish, which simply go with the thermal flow. This relatively warm-bodied lifestyle should place the sharks’ energy requirements somewhere between those of true warm-blooded (endothermic) creatures – such as birds and mammals – and genuinely cold-blooded (ectothermic) fish. It should also allow them to swim at much higher speeds than their cold-blooded contemporaries. Yet, no one had successfully recorded the great white's behaviour to find out how their relatively warm lifestyle influences their activity. Would their warm muscles allow them to live up to their high-speed reputation, or would the sharks reserve their warm-blooded power for other activities?Heading to the Neptune Islands Group (Ron and Valerie Taylor) Marine Park off South Australia – popular with tourists keen to dive with the great whites, which congregate there to dine on seals – Watanabe and his colleagues, Nicholas Payne, Jayson Semmens, Andrew Fox and Charlie Huveneers, prepared tags equipped with sensors to detect the sharks’ movements, swim speeds and depth. However, Watanabe admits that tagging the colossal fish could be frustrating. ‘They needed to swim nice and slow, close to the boat with their dorsal fins breaking the surface, but we rarely had such ideal situations’, he smiles. And when the team wanted to get in alongside the sharks to determine their size and sex, Huveneers explains that they had to climb into a cage for protection. ‘When seen from the boat, they look very aggressive, but I was surprised how elegantly they swim when seen underwater’, says Watanabe.After the tags detached automatically a couple of days later, the team successfully retrieved nine from the water, with the 10th eventually washing ashore several weeks later. Although one shark did manage to hit the higher speeds (2 m s−1) that the team anticipated – presumably when commuting between the islands – Watanabe was surprised that the sharks that lingered near the seal colony were swimming quite sluggishly (0.8 to 1.35 m s−1). He adds that this was unexpected, because swimming becomes costly and inefficient at very low speeds. However, Watanabe suggests that the animals may benefit from their profligacy when moseying along by increasing their chance of encountering a fat seal to dine on.‘This strategy is as close to a ‘sit-and-wait’ strategy as is possible for perpetual swimmers, such as white sharks’, says Watanabe, who also analysed the sharks' manoeuvres when they dived. Noticing that the animals were clearly gliding as they descended, he compared the amount of energy consumed by the sharks during dives with their exertions when swimming at the surface, and it was clear that diving is a far more economical mode of transport than battling through waves at the surface. However, Watanabe suspects that instead of diving to conserve energy, sharks descend primarily in pursuit of seals.So, even though great white sharks are capable of swimming fast thanks to their warm muscles, living fast may not always be a benefit when waiting for dinner, and Watanabe is now keen to find out how often the super predators successfully snatch a seal for a fat snack.

How Far From Meritocracy? A Cross-National Longitudinal Analysis of European Countries

This figure describes the distance from meritocracy in 36 European countries between 2002 and 2017. Following Krauze and Slomczynski, the author defines meritocratic allocation of individuals by education to occupational status groups as a situation when more educated persons do not have jobs with lower status than less educated persons. Using data from the European Social Survey rounds 1 to 8, for each country-round, the author identifies the theoretical meritocratic joint distribution of education and occupational status, as well as the theoretical distribution under statistical independence, and measures the distance of empirical distributions to these two ideal situations. The author finds that the distance to meritocracy varies substantially across European countries, with some countries being closer to allocation under independence than to meritocratic allocation. In terms of cross-country differences, the distance to meritocracy is smaller in postcommunist countries than in Western Europe, with some convergence observable over time.

Component Based Systems: A Novel Methodology in Software Engineering

Background/Objectives: The component based systems make the possibility to develop a better quality system in a faster way in order to satisfy the customer needs. Component based software development is the new technology in software engineering. Component based methods phases the importance of reusing the existing components in software engineering thereby, ensuring lower cost which leads to a versatile development approach. Method/Statistical Analysis: In this study, a novel methodology of Component Based Software Development, its various issues, advantages and limitations in developing software is proposed. This study also focuses on component-based software engineering and to reveal how it can be utilised efficiently and effectively to develop high-quality software products. Findings: Under ideal situations, with minimal testing efforts, integration of reliable software components should produce high-quality software. It additionally, it provides a short summary of the various factors; its models and additionally highlights a number of points regarding the performance and quality factors that are necessary for a software development. Application/Improvements: Feature enhancements in this can be a new technology that could overcome the existing drawbacks Keywords: Component Deployment, Reliable Software, Object Oriented Software, Software Engineering

Do wearable alcohol-based handrub dispensers increase hand hygiene compliance? - a mixed-methods study

BackgroundHand Hygiene (HH) compliance was shown to be poor in several studies. Improving the availability of alcohol-based hand rub (ABHR) is a cornerstone for increasing HH compliance.MethodsIn this study, we introduced wearable dispensers for ABHR in an Emergency Department (ED) well equipped with mounted ABHR dispensers and accompanied this single-modal intervention by a quasi-experimental mixed-method study. The study was performed in the ED of the University Hospital Zurich, Switzerland, a 950-bed tertiary teaching hospital. During a five-week baseline period and a seven-week intervention period, we observed HH compliance according to the WHO ‘Five Moments’ concept, measured ABHR consumption, and investigated perceived ABHR availability, self-reported HH compliance and knowledge of HH indications by questionnaire. Multivariable logistic regression was used to identify independent determinants for HH compliance. In addition, semi-structured interviews were conducted and thematically analyzed to assess barriers and facilitators for the use of the newly introduced dispensers.ResultsAcross 811 observed HH opportunities, the HH compliance for all moments was 56% (95% confidence interval (CI), 51–62%) during baseline and 64% (CI, 59–68%) during intervention period, respectively. In the multivariable analysis adjusted for sex, profession, and WHO HH moment, there was no difference in HH compliance between baseline and intervention (adjusted Odds ratio: 1.22 (0.89–1.66), p = 0.22), No significant changes were observed in consumption and perceived availability of ABHR. During intervention, 7.5% ABHR was consumed using wearable dispensers. HCP perceived wearable dispensers as unnecessary since mounted dispensers were readily accessible. Poor ergonomic design of the wearable dispenser emerged as a main barrier, especially its lid and fastening mechanism. Interviewees identified two ideal situations for wearable dispensers, HCP who accompany patients from ED to other wards, and HCP approaching a patient from a non-patient areas in the ED such as the central working station or the meeting room.ConclusionThe introduction of wearable dispensers did not increase observed hand hygiene compliance or ABHR consumption in an ED already well equipped with mounted dispensers. For broader acceptance and use, wearable dispensers might benefit from an optimized ergonomic design.

Optimized deep neural network architecture for robust detection of epileptic seizures using EEG signals

ObjectiveAutomatic detection of epileptic seizures based on deep learning methods received much attention last year. However, the potential of deep neural networks in seizure detection has not been fully exploited in terms of the optimal design of the model architecture and the detection power of the time-series brain data. In this work, a deep neural network architecture is introduced to learn the temporal dependencies in Electroencephalogram (EEG) data for robust detection of epileptic seizures. MethodsA deep Long Short-Term Memory (LSTM) network is first used to learn the high-level representations of different EEG patterns. Then, a Fully Connected (FC) layer is adopted to extract the most robust EEG features relevant to epileptic seizures. Finally, these features are supplied to a softmax layer to output predicted labels. ResultsThe results on a benchmark clinical dataset reveal the prevalence of the proposed approach over the baseline techniques; achieving 100% classification accuracy, 100% sensitivity, and 100% specificity. Our approach is additionally shown to be robust in noisy and real-life conditions. It maintains high detection performance in the existence of common EEG artifacts (muscle activities and eye movement) as well as background noise. ConclusionsWe demonstrate the clinical feasibility of our seizure detection approach achieving superior performance over the cutting-edge techniques in terms of seizure detection performance and robustness. SignificanceOur seizure detection approach can contribute to accurate and robust detection of epileptic seizures in ideal and real-life situations.

Interactions Between Facultative Symbionts Hamiltonella and Cardinium in Bemisia tabaci (Hemiptera: Aleyrodoidea): Cooperation or Conflict?

Maternally-inherited facultative symbionts are widespread in most insect species, and it is common that several symbionts coexist in the same host individual. Hence, the symbionts may compete or share for the limited resources and space in the host. The whitefly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodoidea), harbors a diverse array of facultative symbionts, among which Hamiltonella sp. and Cardinium sp. are abundant species. Hamiltonella alone increases host fitness, while Cardinium alone confers lower fitness. Locking those different partners together creates ideal situations for the evolution of interactions between symbionts. In this study, we compared the fitness effects of whiteflies infected with only Hamiltonella to Hamiltonella-Cardnium co-infected whiteflies and measured the density of Hamiltonella and Cardinium during host aging, aiming to explore Hamiltonella-Cardinium interactions in B. tabaci. Our results illustrated that Hamiltonella-Cardinium coinfection induced lower fecundity, egg hatchability and number of female offspring, leading to a male-biased sex ratio in offspring, while there is no evidence for reproductive incompatibility between the infections. We also found an antagonistic interaction between Hamiltonella and Cardinium given that the density of the latter increased across time and led to a decrease of Hamiltonella density, which may be the underlying causes of the fitness cost in double-infected B. tabaci. Exploring the ecological consequences of co-infections of these different symbionts helps us to understand the nature of host-symbiont interactions in this species and potential for evolutionary conflict.

Designing next generation platforms for recombinant protein production by genome engineering of Escherichia coli

The epithelial cells lining the mammalian lung are subjected to constant interaction with the external environment, necessitating robust regeneration strategies to deal with cell loss due to natural turnover or damage arising from inhaled agents or disease. Since lung epithelial function extends beyond respiratory gas exchange to include roles such as immune defense and mucociliary clearance, a diverse complement of epithelial cell types exists that are regionally distributed along the respiratory tree and extensive surface area of the alveolar interface. Although steady-state turnover of the epithelium appears to be relatively low in ideal situations, the vital role of the lung requires stem and progenitor cell populations that can promptly respond to the loss or damage of epithelial tissues. The identity and role of stem cell populations that carry out repair and replacement in the lung has begun to be clarified in recent years, led by cell lineage tracking experiments in the mouse lung, which have revealed a complex interplay of differentiation, transdifferentiation, and dedifferentiation between lung stem cells and functional respiratory cell populations. In this review article, we present the current understanding of the stem cell populations within the pulmonary epithelium and describe ongoing efforts to use these stem cell populations to generate models for exploring lung function and disease.

Retirement concerns and planning of cooperative members: a study in the Dutch healthcare sector

Retirement planning is a key component in achieving goals and fulfilling expectations. Although several socioeconomic and psychological factors associated with retirement planning have been reported in the literature, little is known about the influence that specific retirement-related issues have on retirement planning. We examine the influence of five concerns—the individual’s financial situation, living situation, care provision, health condition, and loneliness—on retirement planning. In addition, we investigate the influence of these concerns on individuals’ perceptions of their ideal post-retirement situations in terms of financial standards. Our dataset is derived from a 2010 web-based survey of the care and well-being sector in the Netherlands.