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The purpose of the research is to present the realised forecasts of Ukraine's economic power in order to find reserves for the recovery of the national economy and opportunities for the formation of digital entrepreneurship on the basis of innovative functioning, which will lead to economic growth in the medium and long term. The object of scientific research is the expenditure on SRD and S&T development by types of work in Ukraine from 2010 to 2022 and the analysis of indicators of GDP the influence of time, employment and inflation factors; expansion of digital capabilities of entrepreneurship due to the conducted R&D, which will become a guarantee of the emergence of breakthrough innovations as one of the key reserves of innovative and digital development of the country during the war and post-war reconstruction of Ukraine. Methodology. A study was conducted utilising dialectical, systematic, mathematical and statistical methods to investigate the R&D expenses by types of work in Ukraine from 2010 to 2022 and the GDP from 2011 to 2023. This analysis determined the prospective existing reserve of economic strength with positive dynamics and highlighted the necessity for a strategic format of digital business work based on innovation. A CRA was conducted to determine the strength of the relationship between SRD expenditures and time (i.e., a set of factors that consistently influence SRD funding and drive its growth trend). Fisher's test was calculated, and an econometric analysis was performed based on GDP indicators over 56 quarters, establishing the dependence of the GDP volume on the time factor and the cyclicality of seasonal fluctuations. Resluts. The conditions for accelerating the digitisation of business processes at domestic enterprises are, in particular, the presence of highly qualified S&R personnel, innovators and researchers in the country, the development of new institutes of innovative and digital development, and the transformation and adaptation of old institutes of development to the existing conditions. The obtained data of CRA show that there is a close relationship between the GDP of Ukraine and the time factor, and the direction of the relationship is direct, i.e., linear, which in this case is a positive fact. It is determined that in pursuit of the goal of restoring the innovative potential of the national economy in the post-war period and further active development of digital entrepreneurship in Ukraine, it is necessary to continue financial support for scientific research and scientific and technical developments carried out in various sectors of the economy. Practical implications. The analysed statistical data had a positive impact on the professionalism of the forecast calculations and allowed to state that in 2027, with a probability of error of 6.29%, the volume of expenditures on research and development is projected to range from 20,202.74 to 29,201.18 million UAH. The results of the CRA show that the multiple correlation coefficient (R) is 0.94, which indicates a close overall relationship between the country's GDP and three independent variables (inflation rate, unemployment rate, time factor). The linear regression equation fits the sample data well and the model is qualitative. The results of the forecast are as follows: Ukraine has the potential for post-war recovery and can develop models for post-war economic reconstruction and changes in its structure. Government officials can develop institutional instruments to attract investment and provide effective mechanisms for the future transformation of the existing labour market and human capital institution. Value / Originality. Having conducted a thorough analysis of the statistical data on the dynamics of spending on S&T development and implementation of the SRD in Ukraine in 2010-2022, the authors managed to determine the relative error of approximation – a criterion for assessing the reliability of the forecast, which amounted to 8.74% and considered the approximation to be qualitative, and the forecast for 2027 is reliable. It is determined that the regression equation is most accurate when R2 approaches its maximum value, that is, 1, and in this case, it is 0.9096, which is a good result and means that the linear regression equation fits the sample data well and the model is of high quality. And for Ukraine's economy, which is under martial law, such positive expectations for GDP and the possibility of increasing R&D spending give hope that Ukraine's economic strength is real, as confirmed by the forecast calculations.

Abstract Aim To describe the associations of psychological burnout and time factors on hospital nurses' medication errors. Design A cross‐sectional survey design was used. Methods A structured questionnaire pertaining to psychological burnout, time factors and medication error was administered to 200 bedside nurses working at two tertiary university hospitals in Korea. The associations between the psychological burnout, time factor and medication error were analysed with the zero‐inflated negative binomial regression for over‐dispersed and over‐abundant zeros count data. Results Higher psychological burnout, shorter meal time during duty and longer weekly overtime were associated with an increased likelihood of medication error of nurses working in tertiary university hospitals. For medication safety, nurse managers should provide appropriate administrative support to nurses to cope with psychological burnout of nurses. Work time management should also be considered as human factors to satisfy the needs of nurses, such as securing meal times and maintaining a low level of weekly overtime.

In fault diagnosis of gas turbines, it is necessary to determine the exact time when the fault occurs, so as to obtain the operating and environmental conditions of the turbine. However, the health and fault data of the turbine are mixed and hard to be distinguished because of the noise disturbance. In order to eliminate the influence of noise on clustering results, the time factor was introduced based on the traditional t-SNE algorithm. Then, a two-dimensional grid clustering method was used to process the dimension-reduced data of the t-SNE algorithm, so as to rapidly distinguish the health status of different data to determine the exact time of failure. Besides, a simulation dataset for the performance attenuation of compressors was created with the performance attenuation mechanism model of a compressor established in Matlab Simulink, and based on that, the t-SNE algorithm with a time factor was verified. The results indicate that the new algorithm is superior to other processing methods. The fault diagnosis method of gas turbines based on the t-SNE algorithm with time factor could rapidly and accurately determine the exact time when the fault of the turbine occurs, thus providing technical support to the health condition monitoring and fault diagnosis of gas turbines.

Abstract Background The potential effects of time factor and albuminuria on the morbid alterations in patients with type 2 diabetes (T2D) and COVID-19 are still unclear. We aimed to address the morbid alterations and the potential effects of time factor and albuminuria on the patients’ characteristics before, during, and 1 year after COVID-19 recovery. Methods 83 patients with T2D were included, at Mansoura University Hospital, Egypt (July 2021-December 2021). Data of detailed history, physical examination, laboratory tests were recruited from files of the patients. Diagnosis and resolution of COVID-19 were established by Real time polymerase chain reaction (RT-PCR) test of SARS-CoV2. Complete blood count (CBC), renal and hepatic function tests, multiple measures of morning spot urine albumin to creatinine ratio (urine ACR), glycosylated hemoglobin (HBA1c), lipid profile, erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), Ferritin, neutrophil to lymphocyte ratio (NLR), vitamin D3, intact parathyroid hormone (intact PTH), serum calcium were applied to all participants. Results Our participants had a mean age of 45 years, 60.2% male, 56.6% were hospitalized, and 25.3% were admitted to ICU for severe COVID-19. Albuminuria was prevalent in 71.1% before, 98.8% during, and 92.8% after COVID-19 recovery. Patients with albuminuria showed older age, longer duration of T2D, more frequent severe COVID-19 and hospitalization (p = 0.03, p

This paper uses big data analysis to determine user similarity and calculate the bias in selecting nearest neighbors. The temporal factor is introduced to fully reflect the changing status of users’ interest degrees so that the recommendation accuracy can be significantly improved. According to the nearest neighbors’ rating of experimental teaching resources, the collected data on the effectiveness of vocal music teaching in colleges and universities are clustered, and the results are reflected using degree weights and biases for updating. It was discovered that seven samples had actual student vocal rating values above 0.5, and the overall vocal test scores could reach 86 or higher. To be more energetic in contemporary times, vocal music teaching in colleges and universities should be reformed and innovated to incorporate big data analysis technology.

In order to have a qualitative improvement in the education management of universities in the background of the era of big data technology, it is necessary to integrate information technology and technological means in the process of education management. Based on this background, this paper constructs an informatization education management platform. In the process of platform architecture, the cloud storage module obtains the exact nearest neighbors by the time factor, optimizes the construction process by using the weighting function and hybrid coordination filtering algorithm, and simplifies the teaching management process. In the teaching management system, the fixed rules of the feature selection algorithm are used to achieve teaching resource selection prediction in the optimal feature subset and establish the best classification surface. Finally, the performance of the platform proposed in this paper is verified from two levels: resource recommendation and education management. The experimental results show that the MAE (Mean Absolute Error) value of this platform is always under 0.7, with a mean value of 0.523, and the experimental teaching resource recommendation effect is better than that of the IE virtual experiment teaching platform and data platform. And the maximum number of visits that the platform can bear is 884, and the maximum amount of government processing can reach 839, which is much larger than the number of 800 users of experimental teaching in the university and fully meets the needs of university education management.

This study considers learning in international military operations. It explores these questions: What are the obstacles to learning in a military context? How did these obstacles manifest themselves in contribution made by the Royal Norwegian Air Force (RNoAF) in Mali? How effective in overcoming these obstacles were the formal and informal learning processes that took place? And what does this tell us about how learning might be improved in a military context? Norway has supported the United Nations Multidimensional Integrated Stabilization Mission in Mali (MINUSMA) since 2013. The RNoAF contribution began in January 2016 and continued periodically until May 2021. The contribution consisted of a Hercules C130 transport aircraft with crew and other support personnel. The detachment from Norway consisted of approximately 60–70 women and men with backgrounds in various fields of expertise (aviators, navigators, cargo masters, technicians, security personnel, and other support personnel) required to execute the mission. Based on in-depth interviews of key personnel, this study looks at learning that took place among the various constellations of personnel from the force protection responsible for security during the operation. Much of the learning took place through last-minute efforts because of tight schedules and other pressing tasks. The study has resulted in a conceptual model for facilitating and better supporting the acquisition of knowledge through a continuous process rather than at the last minute. This will require top-down and bottom-up processes, both formal and informal.

“Learning” is a complex event.Individual's learning effect is affected by many factors.Moreover, different individuals have different learning habits.Therefore, it is challenging for students to plan their learning schedule reasonably according to their own characteristics.Although some general theoretical strategies for task management have been proposed, the differences among individuals are usually neglected.Furthermore, existing research cannot provide a calculation method to form a specific task mana-gement schedule.To this end, this paper tries to explore students'learning characteristics by deeply studying the relation between learning efficiency and time factor through data analysis.Based on this, it quantifies personalized learning efficiency.Furthermore, it exploits the bipartite graph method to construct the learning task assignment scenario, and designs adaptive utility function according to different learning goals.Then, a dynamic allocation algorithm TLTA based on transfer learning is proposed to formulate a reasonable schedule for students.Finally, a large number of experiments are carried out on real learning datasets, and the results validate the effectiveness and applicability of the proposed work.

Online services of product delivery apps are more critical than ever. The COVID-19 pandemic has irrevocably altered internet purchasing habits. Customers are getting comfortable using the apps for services to order and do the shopping via their smartphone using the apps. The pandemic has quickened the transition to a more digital world. However, the debate remains as to what elements influence customers' purchase intentions toward using Delivery Services Apps (DSA). This research is therefore carried out to examine the key factors affecting the intention of customers to use delivery services apps among household customers in Malaysia during Covid-19 in 2020 to 2021. The research explored the most significant factors that influence the customer purchase intention on using DSA. There are 4 independent variables which we are focusing on: time factor (TF), price factor (PF), and convenience motivation factor (CMF) and product illustration factor (PIF). From the research, we have found out that convenience motivation factor is the most important exogenous variable that can influence purchase intention directly, sequentially through shopping motivations. The other factors that have a significant impact on a customer's purchase intentions are price factor and time factors. The least important factor that influences a customer’s purchase intention is the product illustrations. The study is carried out by gathering responses from over 167 participants in Malaysia. The objective of the study is to examine the use of online delivery services apps (DSA) to run the businesses efficiently and more effectively in order to attract household customer’s purchase intention. The novelty of this study is by giving the strategies and opportunities to the online business entrepreneurs to enhance and boost their sales by using social media as a platform of online delivery services apps to the community.

This study employs a mixed design to investigate the effects of time factor and clause type on Chinese EFL learners’ implicit and explicit knowledge of relative clauses. Eighty Chinese EFL learners were randomly assigned to one of two-time factor conditions and then tested on a grammaticality judgment task as well as on a sentence combination task to elicit their implicit and explicit knowledge of three types of relative clauses. It was found that, the learners had more accurate performance in untimed tasks than in timed ones; this finding is consistent with some previous studies’ findings. Clause type exerts a significant effect on Chinese EFL learners’ implicit and explicit knowledge of relative clauses, besides time factor and clause type had interaction effects. According to these findings, the article deepens the study of NPAH and it is suggested that multiple timed and untimed tasks could be designed to measure learners’ implicit and explicit knowledge.

In order to solve the problem of low accuracy of traditional network security situation awareness research methods in the case of complex network information,combined with deep learning,this paper proposes a network security situation assessment model based on time factor and composite CNN structure,which combines volume integral solution technology and deep separable technology to form a four layer series composite optimal unit structure.The one-dimensional network data are transformed into two-dimensional matrix and loaded into the neural network model in the form of gray value,so as to give full play to the advantages of convolution neural network.In order to make full use of the time-series relationship between data,time factor is introduced to form fusion data,which makes the network to learn the original data and fusion data with time-series relationship at the same time,the feature extraction ability of the model is increased,the spatial mapping of time-series data is established by using time factor and point convolution,and the integrity of the model structure is increased.Experimental results show that the accuracy of the proposed model on two datasets is 92.89% and 92.60% respectively,which is 2%～6% higher than randomfo-rest and LSTM algorithm.

Background: This study aimed to investigate the natural growth history of peripheral small-cell lung cancer (SCLC) using CT imaging. Methods: A retrospective study was conducted on 27 patients with peripheral SCLC who underwent at least two CT scans. Two methods were used: Method 1 involved direct measurement of nodule dimensions using a calliper, while Method 2 involved tumour lesion segmentation and voxel volume calculation using the “py-radiomics” package in Python. Agreement between the two methods was assessed using the intraclass correlation coefficient (ICC). Volume doubling time (VDT) and growth rate (GR) were used as evaluation indices for SCLC growth, and growth distribution based on GR and volume measurements were depicted. We collected potential factors related to imaging VDT and performed a differential analysis. Patients were classified into slow-growing and fast-growing groups based on a VDT cut-off point of 60 days, and univariate analysis was used to identify factors influencing VDT. Results: Median VDT calculated by the two methods were 61 days and 71 days, respectively, with strong agreement. All patients had continuously growing tumours, and none had tumours that decreased in size or remained unchanged. Eight patients showed possible growth patterns, with six possibly exhibiting exponential growth and two possibly showing Gompertzian growth. Tumours deeper in the lung grew faster than those adjacent to the pleura. Conclusions: Peripheral SCLC tumours grow rapidly and continuously without periods of nongrowth or regression. Tumours located deeper in the lung tend to grow faster, but further research is needed to confirm this finding.

Electric load forecasting is crucial for the metallurgy industry because it enables effective resource allocation, production scheduling, and optimized energy management. To achieve an accurate load forecasting, it is essential to develop an efficient approach. In this study, we considered the time factor of univariate time-series data to implement various deep learning models for predicting the load one hour ahead under different conditions (seasonal and daily variations). The goal was to identify the most suitable model for each specific condition. In this study, two hybrid deep learning models were proposed. The first model combines variational mode decomposition (VMD) with a convolutional neural network (CNN) and gated recurrent unit (GRU). The second model incorporates VMD with a CNN and long short-term memory (LSTM). The proposed models outperformed the baseline models. The VMD–CNN–LSTM performed well for seasonal conditions, with an average RMSE of 12.215 kW, MAE of 9.543 kW, and MAPE of 0.095%. Meanwhile, the VMD–CNN–GRU performed well for daily variations, with an average RMSE value of 11.595 kW, MAE of 9.092 kW, and MAPE of 0.079%. The findings support the practical application of the proposed models for electrical load forecasting in diverse scenarios, especially concerning seasonal and daily variations.

The dual-channel graph collaborative filtering recommendation algorithm (DCCF) suppresses the over-smoothing problem and overcomes the problem of expansion in local structures only in graph collaborative filtering. However, DCCF has the following problems: the fixed threshold of transfer probability leads to a decrease in filtering effect of neighborhood information; the K-means clustering algorithm is prone to trapping clustering results into local optima, resulting in incomplete global interaction graphs; and the impact of time factors on the predicted results was not considered. To solve these problems, a dual-channel feature enhanced collaborative filtering recommendation algorithm (DCFECF) is proposed. Firstly, the self-attention mechanism and weighted average method are used to calculate the threshold of neighborhood transition probability for each order in local convolutional channels; secondly, the K-means++ clustering algorithm is used to determine the clustering center in the global convolutional channel, and the fuzzy C-means clustering algorithm is used for clustering to solve the local optimal problem; then, time factor is introduced to further improve predicted results, making them more accurate. Comparative experiments using normalized discounted cumulative gain (NDCG) and recall as evaluation metrics on three publicly available datasets showed that DCFECF improved by up to 2.3% and 4.1% on two metrics compared to DCCF.

Submerged pile groups are important components of complex piers in hydraulic engineering and are analogs for a range of subsea structures. These may sustain severe damages from local scour. The velocity intensity (U / Uc, the ratio of critical velocity to mean velocity) and aspect ratio (H / Dp, the ratio of pile height to pile diameter) are critical variables in this scour process. However, previous studies on scour around submerged pile groups were conducted in clear-water conditions (U / Uc < 1). In addition, many research studies are being conducted in shallow water flow conditions, which cannot eliminate the effect of the water depth on the scour process. Thus, these research studies cannot directly be applied to live-bed scour around submerged structures. To expand the velocity intensity and aspect ratio of scour around submerged pile groups, flume experiments were conducted with uniform quartz sand in both clear-water and live-bed conditions. Pile groups with different heights are adopted as experimental models. An improved time factor for both clear-water and live-bed scour around submerged structures is determined with the present experiments to extrapolate the scour depth of the present work to the equilibrium scour depth. This new time factor is then tested with experimental data from the literature. The tests demonstrate that this new time factor can reliably predict the scour process and equilibrium scour depth for submerged structures. Empirical relationships to demonstrate the effects of the studied variables including the equilibrium scour depth, scour area, and scour volume are presented. Different methods to predict the effects of the velocity intensity and aspect ratio on the scour depth are compared based on the present work. Furthermore, a correction coefficient is proposed to illustrate the effect of aspect ratio on scour depth. Then, equations of scour area and volume are derived according to the present experiments.

Solid backfill mining (SBM) is a form of green mining, the core of which is to control and minimize the deformation and movement of strata above longwall coal mines. Establishing a mechanical model that can reliably describe roof deformation by considering the viscoelastic properties of waste gangue is important as it assists in improving mine designs and reducing the environmental impact on the surface. In this paper, the time-dependent deformation characteristics of gangue under different stress levels were obtained by using lateral confinement compression, that reliably represents the compaction of goaf. The viscoelastic foundation model for gangue mechanical response is different from the traditionally used elastic foundation model, as it considers the time factor and viscoelasticity. A mechanical model using a thin plate on a fractional viscoelastic foundation was established, and the roof deflection, bending moment, time-dependent, viscous and other characteristics of SBM were included and analyzed. Compared with the existing elastic foundation model, the proposed fractional order viscoelastic foundation model has higher accuracy with laboratory data. The plate deflection increases by 50.9% and the bending moment increases by 37.9% after 100 days, which the elastic model would not have been able to predict.

The acquisition of professional knowledge is a core issue in the formation of auditor industry expertise; however, previous literature has neglected the time required for auditors to acquire professional knowledge. We examine the audit quality and fees of audit firms in different stages of an auditor acquiring professional knowledge and find that, in the initial stage of the process of knowledge acquisition, audit quality and audit fees decrease. However, in the long run, knowledge learning has a more obvious effect on the improvement of audit quality and audit fees. Specifically, knowledge learning has a positive effect on the development of audit firms.

A multi-objective full-parameter optimization particle swarm optimization (MOFOPSO) algorithm is proposed in this paper to overcome the drawbacks of poor accuracy, low efficiency, and instability of the existing algorithms in the inverse kinematics(IK) solution of the manipulator. In designing the multi-objective function, the proposed algorithm considers the factors such as position, posture, and joint. To improve PSO, the proposed algorithm comprehensively analyzes all factors affecting the global and local searching abilities. Based on this, the initial population is designed following the localized uniform distribution method. Meanwhile, the inertia weight, asynchronous learning factor, and time factor are respectively designed by introducing the iteration factor. Finally, this paper tests the performance of MOFOPSO with three typical functions to obtain a better inverse kinematics solution of the 6-DOF manipulator. Also, six other algorithms are taken for performance comparison. The experimental results indicate that the proposed method not only ensures the stability of the manipulator but also achieves high accuracy and efficiency in solving the inverse kinematics of the 6-DOF manipulator.

The article is devoted to the problems of public placement of companies on the Russian stock market. The arguments proving necessity of raising capital through public offering in the Russian Federation have been presented. Foreign and domestic researches of the influence of the time factor during public offering have been considered. The necessity of taking into account the time factor when making a decision on the company’s IPO has been identified and justified. The Russian stock market and its main trends have been analysed, the possibility of applying foreign experience on the Russian market has been assessed. Based on the conducted research, it has been proposed to promote the creation of favorable «Windows», which will help eliminate weaknesses, as well as provide evidence-based regulation in order to create favorable conditions for IPO.

With the popularization of Internet of Things (IOT) technology, a large number of multi-source heterogeneous data are constantly generated and collected by cloud platforms, which indicates that the problem of large data in IOT has become increasingly prominent, especially for massive tags and information in IOT which is urgent to use appropriate data mining algorithms to mine the value of these data. A collaborative filtering recommendation algorithm based on multi-information source fusion (CFR-MIF) is proposed where a feature vector and time weight function are introduced to improve the accuracy of top-N recommendation. It can conveniently and effectively process the IoT data, and furthermore integrate, manage and store the massive data collected from different industries and data formats. Besides, It also provides data mining services in the whole IoT realizing prediction and decision-making, which reverses control these sensor networks, so as to control the movement and development process of objective in the Internet of Things. The experimental results based on DeviceLens 1M data set show that the proposed algorithm greatly improves the accuracy of recommendation results, recall rate and F1 value compared with other advanced algorithms.

The Collaborative Filtering (CF) recommendation algorithm, one of the most popular algorithms in Recommendation Systems (RS), mainly includes memory-based and model-based methods. When performing rating prediction using a memory-based method, the approach used to measure the similarity between users or items can significantly influence the recommendation performance. Traditional CFs suffer from data sparsity when making recommendations based on a rating matrix, and cannot effectively capture changes in user interest. In this paper, we propose an improved hybrid collaborative filtering algorithm based on tags and a time factor (TT-HybridCF), which fully utilizes tag information that characterizes users and items. This algorithm utilizes both tag and rating information to calculate the similarity between users or items. In addition, we introduce a time weighting factor to measure user interest, which changes over time. Our experimental results show that our method alleviates the sparsity problem and demonstrates promising prediction accuracy.

The article deals with topical issues of ensuring the financial stability of the organization on the basis of the unity of all aspects of business. The authors consider the mathematical model of profitability of financial flows of the company. The relationship between the equation of profitability of the company’s financial flows and the capital circulation equation, developed by K. Marx is held. The analysis of these equations is given. The role of the time factor in economic activity is shown.

Since China’s reform and opening up, the country’s rapid marketization process has been accompanied by the rapid growth of inequality, which has been significant for all classes of society. In terms of its impact, housing inequality is particularly noticeable. In this paper, we discuss the influence of real-estate purchase time, organization, human capital, and political capital on the value of real estate and the appreciation of real estate in China by using a conditional mean model and a quantile regression model. The differences in the degree of influence of these factors on different quantile levels are also investigated. We found that, after adding the time factor, the prior possession of resources in the early stage of market transformation will benefit the long-term marketization process. Organizations that can penetrate “market-redistribution” and professions that directly participate in the distribution of real-estate resources also have significant advantages in this regard.

Author analyzes the role of politics and the time factor for estimating constitutional stability. She draws a conclusion that the Constitution should be not a tool for politics, but a bound, framework for it. Moreover, the constitutional developments should express not the current political preferences and interests, but be superior to them and define fundamental legal framework for political actors and events. Moreover, taking into consideration the Author’s viewpoint concerning the interrelations between the stability of the Constitution and time, she considers that it isn’t expedient to mention a concrete period of time, in conditions of which the Constitution should stay in force to be considered stable.

Relevance. Bottomhole formation zone treatment experience analysis shows that oil production stimulation operations success on average amounts to 50 %. Alongside with this, there are moments that do not allow interpreting unequivocally success and effectiveness due to the application of different evaluation criteria. These criteria often contradict each other and create uncertainty in the results in terpretation, as a consequence, make it difficult to solve the problem of increasing the effectiveness of bottomhole zone impact. The aim of the research is to eliminate various kinds of uncertainties in the wells and technologies justification and selection, taking in to account the geological and technological features of the development zones. Methods. Based on the canonical discriminant analysis, the experience of various types of oil production stimulation on hard-to-recover terrigenous reservoirs was studied. Results. The authors obtained the apparatus based on the use of canonical discriminant functions equations, the wells groups representation by the treatment types in the axes of these functions, and their confinement areas identification, allowing eliminating a number of uncertainties in solving the tasks of increasing the efficiency of diagnosis and impact on bottomhole zone. Conclusions. The results allow in the analyzed and similar zones conditions: according to the geological and technological parameters determining the belonging of the well to a certain group; to eliminate the «pseudo-effect» influence when estimating the results of impact; to transfer the wells from the «pseudo-effect» zones to the uniquely positive effect zones changing the technological impact parameters; to make a management decision promptly and use the experience in treating the group to which the particular well belongs; to adapt the impact technology to specific geological conditions and address the bottomhole zone impact, taking into account the time factor (development stages).

Relevance. Bottomhole formation zone treatment experience analysis shows that oil production stimulation operations success on average amounts to 50 %. Alongside with this, there are moments that do not allow interpreting unequivocally success and effectiveness due to the application of different evaluation criteria. These criteria often contradict each other and create uncertainty in the results in terpretation, as a consequence, make it difficult to solve the problem of increasing the effectiveness of bottomhole zone impact. The aim of the research is to eliminate various kinds of uncertainties in the wells and technologies justification and selection, taking in to account the geological and technological features of the development zones. Methods. Based on the canonical discriminant analysis, the experience of various types of oil production stimulation on hard-to-recover terrigenous reservoirs was studied. Results. The authors obtained the apparatus based on the use of canonical discriminant functions equations, the wells groups representation by the treatment types in the axes of these functions, and their confinement areas identification, allowing eliminating a number of uncertainties in solving the tasks of increasing the efficiency of diagnosis and impact on bottomhole zone. Conclusions. The results allow in the analyzed and similar zones conditions: according to the geological and technological parameters determining the belonging of the well to a certain group; to eliminate the «pseudo-effect» influence when estimating the results of impact; to transfer the wells from the «pseudo-effect» zones to the uniquely positive effect zones changing the technological impact parameters; to make a management decision promptly and use the experience in treating the group to which the particular well belongs; to adapt the impact technology to specific geological conditions and address the bottomhole zone impact, taking into account the time factor (development stages).

The subject of this paper is widely used in all economically developed countries, marginal approach. The purpose of this work is to study changes in the threshold of profitability in the time dynamics and identifying opportunities for application of the results obtained in the practice of financial managers.

Objective: To evaluate the hardness (KHN), color stability (DE), and superficial micromorphology of two categories of composites after immersion in either distilled water or grape juice for up to 45 days. MATERIAL AND METHODS: Cylindrical specimens (6 mm diameter x 2 mm thick) were obtained according to the factors: composite [Opallis (FGM) and Filtek Z350XT (3M ESPE)]; immersion solution (distilled water and grape juice); and evaluation time: 24 h and 7, 14, 21, 28, and 45 days. After photoactivation, the specimens were stored at 37ºC for 24 h. KHN (50 g/15 s) and ΔE were then repeatedly assessed according to the immersion solutions. Data were analyzed (three-way ANOVA/Tukey's test). Scanning electron microscopy (SEM) topographic analysis was also performed. RESULTS: In general, KHN of both composites reduced after 24 h, irrespective of the immersion solution and time. A significantly lower KHN was noted for Opallis compared with Filtek Z350XT in all parameters. An increase in ΔE over time was noted for both composites, irrespective of the immersion solution. Significantly higher ΔE was noted for Filtek Z350XT immersed in grape juice compared with Opallis, regardless of the evaluation time. The grape juice caused significantly higher DE compared with water in all periods. SEM analysis showed eroded areas for Filtek Z350XT but not for Opallis. CONCLUSIONS: The compositions and immersion solutions influence the composite hardness and the color stability. In spite of the higher hardness, the nanofilled composite is more susceptible to color change than the microhybrid when immersed in an acidic dyed solution.

The following paper is focused on employee’s performance measurement. The aim of this paper is to realize an expert resources search in the frame of this issue. In the next step an approach to human resources performance measurement will be designed through the synthesis of acquired knowledge. Emphasis will be placed on the temporal aspect of this measurement because the concentration on current performance rating does not correspond with the strategic approach to the concept of human resources management. Production capacity in the future is a key factor in maintaining and enhancing competitiveness, it is very important to pay attention to its measurement and evaluation. In addition, the next dimensions of performance will be identified to respect the current comprehensive approach to this issue.

Background Rapid reviews expedite the knowledge synthesis process with the goal of providing timely information to healthcare decision-makers who want to use evidence-informed policy and practice approaches. A range of opinions and viewpoints on rapid reviews is thought to exist; however, no research to date has formally captured these views. This paper aims to explore evidence producer and knowledge user attitudes and perceptions towards rapid reviews. Methods A Q methodology study was conducted to identify central viewpoints about rapid reviews based on a broad topic discourse. Participants rank-ordered 50 text statements and explained their Q-sort in free-text comments. Individual Q-sorts were analysed using Q-Assessor (statistical method: factor analysis with varimax rotation). Factors, or salient viewpoints on rapid reviews, were identified, interpreted and described. Results Analysis of the 11 individual Q sorts identified three prominent viewpoints: Factor A cautions against the use of study design labels to make judgements. Factor B maintains that rapid reviews should be the exception and not the rule. Factor C focuses on the practical needs of the end-user over the review process. Conclusion Results show that there are opposing viewpoints on rapid reviews, yet some unity exists. The three factors described offer insight into how and why various stakeholders act as they do and what issues may need to be resolved before increase uptake of the evidence from rapid reviews can be realized in healthcare decision-making environments.

Objective: The goal of this study was to investigate all the potential routes to Child/Adolescent Psychiatry Clinic-University Hospital Center (CAPC-UHC) in Tirana. The article provides demographic data, as well as further information on the types and amounts of services children/adolescents received during the process of seeking help related to different diagnoses .Method: The study was conducted in CAPC-UHC in Tirana, during September 2006-September 2007. Data were collected from 162 children and their parents using Strengths and Difficulties Questionnaire (SDQ) and Pathways Encounter Form. The sample consisted of 53.1% (86) males and 46.9% (76) females. The mean age was 9.5 + 4.4 years .Results: Out of the total number of cases that sought care to CAPC; 55, 6% were referred by parents themselves, while the rest were referred by others. There was a significant effect of gender to intervals from the onset of problem to the first career (F = 10.803, p=0.001), as well as a significant effect of gender to total time intervals from the onset till the specialist of child mental health problem (F = 6.742, p=0.01).Conclusions: This is the first study investigating the help seeking process to psychiatric care in CAPC Tirana-Albania and may serve as a good start in generating evidence based on child/adolescent mental health service. Further multicentre studies will enhance the values of the findings, since the present study was performed in a single service, and in a setting lacking previous works with similar scope that could have served as references.

The article presents the comparative research of some items of prescriptions of institution of criminal proceedings according to Russian and foreign criminal codes. In particular, the maximal and minimal terms are analyzed; methods of their calculation and some issues of their calculation are viewed, depending on the gravity and category of the crime.

Background/Aim. Despite numerous research of Lyme disease (LD), there are still many concerns about environmental of infectious agent of LD, as well as its prophylaxis, diagnosis and treatment. The aim of this work was to determine the risk of LD in relation to the way of removing ticks and duration of tick attachment. Methods. In the period from 2000 to 2007 a prospective study was conducted including persons with tick bite referred to the Institute of Epidemiology, Military Medical Academy, and followed for the occurrence of early Lyme disease up to six months after a tick bite. Epidemiological questionnaire was used to collect relevant information about the place and time of tick bites, the way of a removing tick, duration of tick attachment, remnants of a tick left in the skin (parts of the mouth device) and the signs of clinical manifestations of LD. Duration of tick attachment was determined on the basis of size of engorged tick and epidemiological data. Removed ticks were determined by the key of Pomerancev. Professional removing of attached tick was considered to be removing of tick with mechanical means by healthcare personnel. Fisher's exact test, Chi squares test and calculation of the relative risk (RR) were used for data analysis. Results. Of 3 126 patients with tick bite, clinical manifestations of LD were demonstrated in 19 (0.61%). In the group of subjects (n = 829) in which a tick was not removed professionally there were 17 (2.05%) cases with LD, while in the group of respondents (n=2 297) in who a tick was removed professionally there were 2 (0.09%) cases with LD after tick bite (RR, 23.55; p < 0.0001). The disease was most frequent in the group of respondents with incompletely and unprofessionally removed ticks (2.46%). In the groups of patients with unprofessionally but completely removed ticks LD occurred in 0.89%, while in the group of subjects with a tick removed by an expert, but incompletely in 0.78% cases. The disease occurred rarely in the group with a tick removed completely and professionally (0.05%). There was no case of LD in the group of patients with a tick removed within 24 hours. The longer time of exposure after 24 hours, the higher absolute risk of disease was reported. Conclusion. In prevention of Lyme disease it is important to urgent remove a tick, to use a correct procedure of removing and to remove the whole tick without any remnants.

Studies have shown that weekend or night admissions to intensive care units (ICUs) are associated with increased mortality in critically ill patients. Our study aimed to evaluate the effects of admission time and day on patient outcomes in a medical ICU equipped with patient management guidelines, and staffed by intensivists on call for 24 hours, who led the morning rounds on all days of the week but did not stay in-house overnight. The study enrolled 611 consecutive patients admitted to a 26-bed medical ICU in a university hospital during a 7-month period. We divided them into two groups, which we labeled as “office hours” (08:00–18:00 on weekdays) and “non-office hours” (18:00–08:00 on weekdays, and all times on weekends) according to their ICU admission times. The clinical outcomes were compared between the groups. The effects of admission on weekends, at night, and various days of the week on hospital mortality were also evaluated. Our results showed that there were no significant differences in ICU and hospital mortalities between patients admitted during office hours and those admitted during non-office hours (27.2% vs. 27.4%, p = 1.000; 38.9% vs. 37.6%, p = 0.798). The ICU length of stay, ICU-free time within 21 days, and length of stay in the hospital were also comparable in both groups. Among the 392 patients requiring mechanical ventilation, the ventilator outcomes were not significantly different between those in the office-hour group and the non-office-hour group. Multivariate logistic regression analyses showed that the adjusted odds of hospital mortality were not significantly higher for patients admitted to our ICU on weekends, at night, or on any days of the week. In conclusion, our results showed that non-office-hour admissions to our medical ICU were not associated with poorer ICU, hospital, and ventilator outcomes, compared with office-hour admissions. Neither were time of day and day of the week admissions to our ICU associated with significant differences in hospital mortality.

Objective: The goal of this study was to investigate all the potential routes to Child/Adolescent Psychiatry Clinic-University Hospital Center (CAPC-UHC) in Tirana. The article provides demographic data, as well as further information on the types and amounts of services children/adolescents received during the process of seeking help related to different diagnoses . Method: The study was conducted in CAPC-UHC in Tirana, during September 2006-September 2007. Data were collected from 162 children and their parents using Strengths and Difficulties Questionnaire (SDQ) and Pathways Encounter Form. The sample consisted of 53.1% (86) males and 46.9% (76) females. The mean age was 9.5 + 4.4 years . Results: Out of the total number of cases that sought care to CAPC; 55, 6% were referred by parents themselves, while the rest were referred by others. There was a significant effect of gender to intervals from the onset of problem to the first career (F = 10.803, p=0.001), as well as a significant effect of gender to tot l time intervals from the onset till the specialist of child mental health problem (F = 6.742, p=0.01). Conclusions: This is the first study investigating the help seeking process to psychiatric care in CAPC Tirana-Albania and may serve as a good start in generating evidence based on child/adolescent mental health service. Further multicentre studies will enhance the values of the findings, since the present study was performed in a single service, and in a setting lacking previous works with similar scope that could have served as references.

Literary Re-translation: How, When and Why? This article deals with the issue of literary re-translation, its causes and characteristics. The analysis is illustrated by means of examples mainly derived from Swedish literary texts that have been translated and retranslated into French. Here, I aim to examine the particular premises of retranslation, as opposed to those of first translation, and the different roles which, depending on these premises, the individual translator faces in the translation process. The article stresses the importance of the “subjective traces” that every translator leaves in his/her translation. My analysis takes into account a number of factors liable to provoke the retranslation of a literary work: ageing, interpretative variety, fidelity, translational style, etc. Further, the article discusses translation problems with respect to such concepts as spoken language, dialect, and the language of poetry and of drama; all of which are important causes for retranslation. It also addresses the concept of censorship, which, in the history of literary translation, has frequently deformed and sometimes even mutilated important original literary texts and which, consequently, has been a determining factor in the decision to submit an already translated text for new translation. Finally, the article briefly touches upon the concept of revised translation, which can be said to occupy a middle position between the existing translation of a literary text and its retranslation. In connection with this concept, the article also mentions the recourse to translation from a language other than the original language. It seems inevitable that the intermediate language inflicts a number of semantic, stylistic and pragmatic losses upon the translation in relation to the original text, and it is only natural that this type of translation should be a common cause for retranslation.

The role of the time factor in management is increasing. Change directs attention to the time factor from the point of view of the organisation,and management does the same from that of the person. I examined the time management practice of managers of organisations related to agribusiness, and the reaction time characterising the adaption ability of the organisations through a questionnaire survey. I analysed the collected data with scientifically established statistical methods. During studying resources, managing tasks, change, reaction time and effect I explored the features of time as resource, the significance of the time factor, the improvability of time efficiency in the different managing functions, the factors supporting and hindering the quick reaction of organisations, and what rearrangements can be seen in management work nowadays.

OBJETIVO: Com a introdução de marcadores radiopacos para avaliação do tempo de trânsito intestinal, tornou-se possível mensurar não apenas o tempo de trânsito total, como também o segmentar. Visando a simplificação da técnica, especialmente no que diz respeito à diminuição da exposição à irradiação, foi descrito novo método com número menor de radiografias. Os autores apresentam estudo do tempo de transito colônico total e segmentar em indivíduos normais. MÉTODO: Quinze voluntários adultos e assintomáticos, oito do sexo feminino e sete do masculino, foram submetidos a exame radiológico com marcadores radiopacos para medida do tempo de trânsito colônico total e segmentar (cólon direito, esquerdo e retossigmóide). RESULTADOS: A média do tempo de trânsito colônico total foi de 36,61 ± 3,48 horas. Dos tempos de trânsito segmentares obtivemos as médias de 11,51 ± 2,28 horas para o cólon direito; de 12,14 ± 2,19 horas para o cólon esquerdo; e de 12,96 ± 2,23 horas para o retossigmóide. CONCLUSÕES: A técnica descrita é método simples e útil para a avaliação do tempo de trânsito colônico total e segmentar e quando aplicada a indivíduos assintomáticos reproduziu resultados comparáveis aos da literatura e aos obtidos a partir de outras técnicas.

Many scholars describe time as a factor in war. It is particularly the case regarding asymmetric conflicts, in which time is said to favor the weak. As for democracies, the longer the war, the more they are expected to lose. War is a complex process, and it is difficult to know precisely what factors determine its outcomes. Therefore scholars are in a situation of uncertainty. They are able to identify some tendencies, but it is hard to isolate the relevant factors in play. Consequently, rather than untangling those factors, they sometimes argue that time is a factor in itself. Here, time is nothing more than a default concept. In reality, time is on no one’s side. It is not a factor in war, but a dimension in which factors play. This ultimately leads to major confusion when authors attempt to compare the ‘time factor’ to other elements in war, forgetting that time is not located at the same level of analysis. The same problem arises for those who carelessly translate their variable into temporal terms and believe they can measure its relevance thanks to hazardous objectifications.