Slow Tourism in the Sustainability of Local Culture

The essence of slow tourism is the sustainability of the locals. Slow tourism includes tourism activities by visiting slow cities, tasting slow food, and enjoying the moment, avoiding the worry of uploading photos to social media accounts while experiencing all these. Slow tourism is based on the need to experience travel within the framework of sustainability and to prioritize the locals during these travels. What is important in this tourism activity is not how long a destination is spent or how many destinations are visited, but how productive time is spent at the destination and the emotions that emerge afterward. In addition to these, many practices are carried out to ensure the sustainability of local culture, especially in slow cities, within the scope of slow tourism. Practices such as the continuation of local handicrafts, ensuring the continuity of local life under the influence of ancient civilizations, and sustainability of the local architectural style are included in slow city destinations. The essence of all this is to ensure the continuity of the local culture.

Immunocytochemical Labelling of Haematological Samples Using Monoclonal Antibodies

I reflect on my experience working with David Y. Mason in the Leukaemia Research Laboratories in the Nuffield Department of Pathology at the University of Oxford in the early 1980s. This was soon after the first monoclonal antibodies had been produced, which led to an exciting and productive time in biological discovery and pathology diagnostics. A specific focus in the laboratory was the development of immunoenzymatic staining methods that would enable monoclonal antibodies to be applied in diagnostic practice. This paper describes the work that led to the performance of immuno-alkaline phosphatase staining on blood and bone marrow smears, the success of which changed leukaemia diagnosis.

The research and development of technical and technological solutions for the operation of oil wells with increased gas content

In the practice of oil production, there are oil deposits with high values of gas content (gas factor), from tens to hundreds of cubic meters of gas per one ton of oil produced. Gas dissolved in oil and coming from the reservoir into the well along with the liquid phase (oil, water), under certain thermodynamic conditions, is capable of forming hydrates, which complicate the operation of downhole pumping equipment, reduce the efficiency of pumps and well flow rate. The formation of gas hydrate plugs in the well requires the total overhaul, which leads to an increase in non-productive time, financial costs and an increase in lost profits on lost oil. Considered in the article technologies and devices that prevent the formation of gas hydrates in marginal wells with a high gas content in oil have shown their unreliability and low efficiency. The authors propose for the consideration a new effective technology for the operation of such wells, which makes it possible to avoid the formation of hydrates. Keywords: well; gas content; hydrates; production; oil; valve; coupling; pump.

High-Performance-Low-Invasion Fluids Technology Enhances, Optimizes Drilling Efficiency in the Gulf of Suez - Egypt

High Performance Low-Invasion Fluids Technology Enhances, Optimizes Drilling Efficiency in the Gulf of Suez – Egypt Objectives / Scope: The main objective of this paper is to characterize the drilled shale formation in order to select and propose a "tailored" High Performance Low Invasion Fluids (HPLIF) system aided by Bridging Particles Optimization Tool (BPOT)(5),(6)(9)(11), capable of maximize hole stability in pressure depleted sands, allowing optimized well design through reactive and dispersible shale formations(7)(8) that eliminated one casing section, and to replace Oil Base Mud (OBM) and avoid its HSE issues related to use it, consequently, reduce formation damage, eliminate waste management cost, minimizing Non Productive Time (NPT) and finally enhances Drilling performance. Methods, Procedures, Process: This paper explain the reactivity information about Shale Samples recovered from different wells drilled in the-GOS-Egypt followed by extensive laboratory testing done(1) in order to characterize the main clay minerals presented in the samples using X-Ray Diffraction-(XRD) technology and their meso-and micro-structure by Scanning-Electron-Microscope-(SEM) and their reactivity to compare the inhibition efficiency of the proposed-(HPLIF)-System with Blank and Conventional Water-Base-Fluid-System. The reactivity of the cuttings was assessed by Dispersion, Swelling and Hardness tests. Field application experienced (HPLIF) System combined with Well-Bore Strengthening Materials (WSM) gives the required protection against induced losses and reducing the risk of differential sticking problems when mud overbalance is above 2500 psi(5), (6)(9)(11). Results, Observations, Conclusions: Compared with the use of conventional fluid systems, Field data demonstrated the successful application of (HPLIF) System combined with (WSM) and shows a great success during drilling through reactive clays, dispersive shale, naturally micro fractured(8), and depleted sand formations in many wells drilled in the GOS(2), (3), (4). Drilling operations reported no differential sticking, or wellbore instability issues even at highly mud overbalance or at highly deviated wells. The first challenged well R1-63 was drilled about 2391 ft, through 8.5" hole using 9.8-10.01 ppg using (HPLIF) system, penetrating through Thebes, Esna Shale, Sudr, Brown Lime Stone, Matulla, Nubia"A" Sand and Nubia "B" without any down-hole losses. Additionally, there was no sticking tendency experienced during drilling or while recording pressure points. The Non Productive Time NPT showed a reduction by about 19.2%. Finally, it ran and was cemented the "7" Liner in open hole successfully without problem. For the second challenged case well # 2, the Open hole was exposed to (HPLIF) water based mud system for a long period of time while rig repairing, rig switching, and during drilling operation. The well had 6" hole from 12,752 To/14,945 (2193.0ft) through Red bed, Thebes Esna, Sudr, Matulla and Nubia Sand formations with max inclination 68.6° and bottom hole temperature 325°F using 10.0-10.5 ppg (HPLIF) system, the 4.5"liner successfully was ran, cemented without any problems. The-HPLIF-System has also been shown to give excellent wellbore stability in brittle shales Fm where bedding planes or micro-fractures can become pressurized with mud, leading to wellbore instability. This innovation avoids induced lost circulation and differential sticking when the mud overbalance is expected to be greater than ±2500 psi. Additionally, the proposed solution enhances the drilling operation, reduces the waste management costs, eliminates a possible additional casing string, and finally minimizes the (NPT) which reflects on the overall cost of drilling these challenged wells.

Application of Artificial Intelligence and Machine Learning to Detect Drilling Anomalies Leading to Stuck Pipe Incidents

This project used predictive analytics and machine learning-based modeling to detect drilling anomalies, namely stuck pipe events. Analysis focused on historical drilling data and real-time operational data to address the limitations of physics-based modeling. This project was designed to enable drilling crews to minimize downtime and non-productive time through real-time anomaly management. The solution used data science techniques to overcome data consistency/quality issues and flag drilling anomalies leading to a stuck pipe event. Predictive machine learning models were deployed across seven wells in different fields. The models analyzed both historical and real-time data across various data channels to identify anomalies (difficulties that impact non-productive time). The modeling approach mimicked the behavior of drillers using surface parameters. Small deviations from normal behavior were identified based on combinations of surface parameters, and automated machine learning was used to accelerate and optimize the modeling process. The output was a risk score that flags deviations in rig surface parameters. During the development phase, multiple data science approaches were attempted to monitor the overall health of the drilling process. They analyzed both historical and real-time data from torque, hole depth and deviation, standpipe pressure, and various other data channels. The models detected drilling anomalies with a harmonic model accuracy of 80% and produced valid alerts on 96% of stuck pipe and tight hole events. The average forewarning was two hours. This allowed personnel ample time to make corrections before stuck pipe events could occur. This also enabled the drilling operator to save the company upwards of millions of dollars in drilling costs and downtime. This project introduced novel data aggregation and deep learning-based normal behavior modeling methods. It demonstrates the benefits of adopting predictive analytics and machine learning in drilling operations. The approach enabled operators to mitigate data issues and demonstrate real-time, high-frequency and high-accuracy predictions. As a result, the operator was able to significantly reduce non-productive time.

STEP Change in Preventing Stuck Pipe and Tight Hole Events Using Machine Learning

Wellbore stability problems, such as stuck pipe and tight spots, are one of the most critical risks that impact drilling operations. Over several years, Oil and Gas Operator in Middle East has been facing problems associated with stuck pipe and tight spot events, which have a major impact on drilling efficiency, well cost, and the carbon footprint of drilling operations. On average, the operator loses 200 days a year (Non-Productive Time) on stuck pipe and associated fishing operations. Wellbore stability problems are hard to predict due to the varying conditions of drilling operations: different lithology, drilling parameters, pressures, equipment, shifting crews, and multiple well designs. All these factors make the occurrence of a stuck pipe quite hard to mitigate only through human intervention. For this reason, The operator decided to develop an artificial intelligence tool that leverages the whole breadth and depth of operator data (reports, sensor data, well engineering data, lithology data, etc.) in order to predict and prevent wellbore stability problems. The tool informs well engineers and rig crews about possible risks both during the well planning and well execution phase, suggesting possible mitigation actions to avoid getting stuck. Since the alarms are given ahead of the bit, several hours before the possible occurrence of the event, the well engineers and rig crews have ample time to react to the alarms and prevent its occurrence. So far, the tool has been deployed in a pilot phase on 38 wells giving 44 true alarms with a recall of 94%. Since mid-2021 operator has been rolling out the tool scaling to the whole drilling operations (over 40 rigs).

STUDI KASUS ANALISIS BEBAN KERJA BERDASARKAN WAKTU KERJA KARYAWAN PADA UNIT PEMANENAN AFDELING 1 DI KEBUN KELAPA SAWIT PT. XYZ

The importance of quality human resources in oil palm plantations in the field of harvesting to achieve high productivity, the success of harvesters is also very much determined by the pressure of the workload that is owned by workers, the workload depends on the job description compiled by the company. also the possibility of a workload that is too high. This study aims to analyze the working time of harvest employees and determine the productive, unproductive and personal time of harvest employees and analyze the number of harvest employees needed at PT. XYZ. This research was conducted at PT. XYZ Tanjung Batu Village, Derawan Island District, Berau Regency, East Kalimantan. This research was conducted using work sampling data collection method, namely observing the working time of harvest employees with 10 minutes intervals for 7 working hours by noting productive time, unproductive time and personal time. The results from the observations of researchers through the characteristics of harvest workers that affect the characteristics of age and height characteristics, it is proven that the age of 20 - 29 years is faster to reach the target or basis compared to the age of 30 - 49 years. And the characteristics of height have an effect on reaching the target, it is proven that height 170 - 179 cm reaches the target or base faster than 150 - 159 cm. And the observations of researchers from 16 respondents harvest productive working time an average of 73.52%, 17.20% unproductive time and 9.28% personal time. Calculation of the need for harvest workers in 1 division (763.33 ha) results in 33,644 rounded up to 34 harvest workers, the results needed in 1 division (763.33 ha) through the calculation of the time of completion of tasks (WPT).

Time Is Relative: How Framing of Time Estimation Affects the Accuracy of Cost Information

Accurate cost information is critical to effective decision making within organizations. Cost computations often rely on subjective judgments by employees regarding the amount of time that different tasks consume. In an experimental setting, we examine the accuracy of two common approaches to eliciting subjective time estimates vital for accurate cost information. Specifically, we compare estimation error when employees estimate (i) the total time for all iterations of a task (the pool approach) versus (ii) the average time for one iteration of a task (the unit approach). These two approaches have received interest by both practitioners and researchers and are at the heart of the difference between conventional activity-based costing (ABC) and time-driven ABC. While mathematically equivalent, we hypothesize and find that the two approaches evoke different cognitive processes that lead to differences in estimation error. Relative to the unit approach, the pool approach produces larger error in the allocation of time among different tasks, but only when the number of iterations per task varies across tasks. Further, the pool approach results in overestimation of productive time, whereas the unit approach leads to underestimation of productive time. Our findings are robust to different response modes of the pool approach (estimates in absolute time units and in percentages). This study is relevant for designers and users of cost and performance-measurement systems in that allocation errors lead to cost cross-subsidization and poor resource-allocation decisions, while overall errors undermine capacity utilization decisions. This paper was accepted by Brian Bushee, accounting.

Generating Labour Cost Budget for a Construction-Oriented Fabrication Facility: Simulation-based Resource Scheduling Approach

A novel labour-hour budgeting methodology is proposed by integrating productivity concepts in project scheduling and budgeting to enhance the accuracy of labour cost budgeting for planning labour-intensive projects. The proposed methodology applies discrete event simulation approach to represent crew formation, labour resource utilization and labour resource flowing between consecutive activities, which allows for quantitatively characterizing the impact of labour semi-productive time on labour cost budgeting as a time-dependent variable. Simulation-based assessment of variations in crew sizes and labour allocations is conducive to reducing semi-productive time and thus enhancing the cost performance of the whole project. The proposed methodology is then applied in a real-world case study for planning steel girder fabrication projects in construction of highway bridges. Not limited to budgeting for labour resources in construction-oriented fabrication facility, the research contributions are also significant to other construction planning settings where limited resources are shared and utilized among different activities.

Relation Between Hormonal Contraception with Menopause

Menopause is a process of transition from a productive period heading slowly to the non-productive time due to reduced estrogen and progesterone. There are many factors associated with menopause. Factors contraceptives may affect the occurrence of menopause, which in women who use hormonal contraseption to have compromised menopause compared to those using a non-hormonal contraception. The purpose of this study was to determine the relationship between hormonal contraception and menopause. The research method uses a Systematic Literature Review. The independent variable is hormonal contraception. The dependent variable is Menopause Age. The population is all research journals with the topic of the relationship between hormonal contraception and age menopause. The sample is a journal of research results of the relationship between hormonal contraception and age menopause. Sample inclusion criteria in this study include: 1). Subjects of the study were postmenopausal women, 2). The type of research is case control and cross sectional 4). National and international journals of the10 years last. The results of the study found that hormonal contraception was associated with age at menopause. Suggestions for women postmenopausal to have a healthy lifestyle and have regular the health check posyandu or to health care facilities. Keywords: contraception, hormonal, menopause