Return Time Research Articles

Factors Influencing the Uptake of Cervical Cancer Screening Services among Women Attending Gynecological OPD at KIUTH, Ishaka-Bushenyi, South Western Uganda

This work aimed to determine the factors influencing uptake of cervical cancer screening services among women attending gynecologic OPD at KIUTH, Ishaka-Bushenyi, South-western Uganda. A cross sectional study design and Quantitative approach was used. 100 women attending gynecologic OPD at KIUTH were selected using Kish Leslie formular. Data collected using a questionnaire was entered and analyzed using SPSS, presented in frequency, percentage and P-values tables. 41.2% were aged 25-31 years and the minority 2.0% being >45 years. 65.7% coming away from Ishaka; married 73.7% for 1-5 or 11-20 years each accounting for 32.5%. 37.4% while 30(30.3%) reached tertiary education level. 42.4% were unemployed whereas 7.1% were simply housewives. 50.0% had 2-4 children, and only 18.3% had <2 children. 86.9% were aware while 13.1% who weren’t. 56.8% got their information concerning cervical cancer and its screening from health facility compared to 3.7% from press. 34.7% had knowledge on screening recommendation among adult women who specified it being 22.1% every three years and 12.6% yearly. 88.4% specified it to be treatable if detected early with a P-value=<0.01*, 73.5% knows a local health facility offering the services; p-value=0.05, 53(62.4%) of 62.2% claim that results return time could influence the testing uptake, pvalue=0.18, also, 89.2% agreed that Recommendation/counseling affects the uptake of cervical cancer screening/testing p-Value=0.05, as well as having tested before 43.4% already tested had a p-value=0.05. Long distance to HF affects 75.9% aware of screening of 77.1% p-value=0.49, cervical test cost affect with 75.6% aware of the services p-value=0.55, and Gender of HW where 39.5% who were aware of the services out of 47.5% agreed that it affects uptake p-value=<0.001. According to the study findings, awareness/knowledge of cervical cancer screening/testing services among women attending KIUTH stands at 86.9%; whose info is mostly from health facility and Television/Radio. Early detection; availing of local health facility, short results return time, Recommendation/counselling and having tested before increases uptake whereas the long distance to the health facility, cervical test cost and longest distances reduces uptake of cervical cancer and screening services/testing. Keywords: Cervical cancer, Screening services, Healthy facility, Women, OPD.

Sosialisasi dan Problem Solving Keterlambatan Pengembalian Berkas Rekam Medis dengan Diagram Fishbone

The problem of delays in returning inpatient medical record files in the Ashoka Room in December was the highest with a return time of 18 days. This service aims to provide an understanding of the flow of returning medical records and solving the problem of delays in returning medical record files. This service activity is carried out in several stages. The results obtained by participants were able to understand the flow of returning inpatient medical record files which had been socialized and became a poster output product in this service and were also presented in the socialization regarding problem solving for delays in returning inpatient medical record files at Bangil Regional Hospital using a Fishbone diagram. Suggestion: It is necessary to make efforts to monitor and evaluate the implementation of the SOP for returning medical record files, resocialize the SOP to remind health workers about the time to return medical record files, provide motivation or praise in the form of a certificate of appreciation to health workers who are responsible for returning medical record files on time.

IDV Typer: An Automated Tool for Lineage Typing of Influenza D Viruses Based on Return Time Distribution.

Influenza D virus (IDV) is the most recent addition to the Orthomyxoviridae family and cattle serve as the primary reservoir. IDV has been implicated in Bovine Respiratory Disease Complex (BRDC), and there is serological evidence of human infection of IDV. Evolutionary changes in the IDV genome have resulted in the expansion of genetic diversity and the emergence of multiple lineages that might expand the host tropism and potentially increase the pathogenicity to animals and humans. Therefore, there is an urgent need for automated, accurate and rapid typing tools for IDV lineage typing. Currently, IDV lineage typing is carried out using BLAST-based searches and alignment-based molecular phylogeny of the hemagglutinin-esterase fusion (HEF) gene sequences, and lineage is assigned to query sequences based on sequence similarity (BLAST search) and proximity to the reference lineages in the tree topology, respectively. To minimize human intervention and lineage typing time, we developed IDV Typer server, implementing alignment-free method based on return time distribution (RTD) of k-mers. Lineages are assigned using HEF gene sequences. The server performs with 100% sensitivity and specificity. The IDV Typer server is the first application of an RTD-based alignment-free method for typing animal viruses.

Flood Frequency Analysis Using Gumbel Distribution Method: A Case of Robigumero River, Abay Basin, Ethiopia

Hydraulic structures like weirs, dams, spillways, and bridges require precise estimation of flood peaks at the intended return period in order to be planned, built, and maintained. In this paper, the findings of a study conducted on the Robigumoro River and the flow measurements taken are presented. The flood frequency analysis of the Robigumoro River was performed using the Gumbel distribution, which is a probability distribution commonly used for modeling river flows. This analysis is crucial as it aims to safeguard the lives and properties located downstream from the catchment area. The Gumbel distribution was employed to model the highest annual river flow over a span of 20 years (1990-2009). The investigation was carried out by the Ethiopian water and energy office, Abay Basin Development Authority. The Robigumoro River's maximum annual discharge over a 20-year period (1990–2009) was modeled using Gumbel distribution technique. From the trend line equation, R<sup>2</sup> value of 0.935 which shows that Gumbel’s distribution is suitable for predicting expected flow in the river. It can be concluded that the Gumbel distribution can accurately forecast expected river flow. The flood peak values were calculated using the same procedure for various return times. This helps with storm management in the research region. The estimated discharges obtained using the Gumbel's distribution and return periods (T) of 2 years, 10 years, 50 years, 100 years, 150 years, 200 years, 300 years and 400 years are 177.327m<sup>3</sup>/s, 320.784m<sup>3</sup>/s, 446.553m<sup>3</sup>/s, 499.722m<sup>3</sup>/s, 530.727m<sup>3</sup>/s, 552.698m<sup>3</sup>/s, 583.38m<sup>3</sup>/s, and 605.577m<sup>3</sup>/s respectively. The accuracy of flood forecasts in the basin indicates their potential use in various applications such as the design of crucial hydraulic structures, river reach planning, construction of bridges, and conservation efforts for Robigumoro watershed.

Hybrid architecture to support the intelligent mapping and redesign of organizational processes

The objective of this article was to develop and apply a Hybrid Architecture (HA) based on Business Process Management (BPM), Enterprise Architecture (EA) with TOGAF and Process Mining (PM) to support the intelligent mapping and redesign of organizational processes. The experiments were carried out in four phases: company selection, data selection, computational experiments and comparison of results. The comparison of the results showed that with the application of AH the mapping time was reduced by 60%, the number of people involved by 50% and a 20% reduction in the return time to the customer. The number of activities mapped with AH increased from 19 to 27, that is, 42% more than in the traditional method. It was concluded that AH contributed intelligence, agility and discovery of knowledge not perceptible with other methods to support intelligent mapping and redesign of organizational processes.

ASYMMETRIC GARCH-TYPE AND HALF-LIFE VOLATILITY MODELLING IN EXCHANGE RATES OF EURASIAN ECONOMIC UNION MEMBERS

The variability in the price of a financial asset is called volatility and is often measured with a standard deviation. Empirical studies have shown that many financial asset returns exhibit fat tails (leptokurtosis) and are often characterized by volatility clustering and asymmetry. The aim of this study is to determine the asymmetric GARCH-type modeling of the exchange rates of Belarus, Armenia, Kazakhstan, Kyrgyzstan, and Russia, which constitute the Eurasian Economic Union as of January 1, 2015, as well as to determine the return time to the mean after the shocks. The return series obtained over the daily closing prices of the exchange rates of the countries in question between December 31, 2018 and June 30, 2023 were analyzed using the EGARCH method and the return to mean were calculated.

The Extraordinary March 2022 East Antarctica “Heat” Wave. Part I: Observations and Meteorological Drivers

Abstract Between 15 and 19 March 2022, East Antarctica experienced an exceptional heat wave with widespread 30°–40°C temperature anomalies across the ice sheet. This record-shattering event saw numerous monthly temperature records being broken including a new all-time temperature record of −9.4°C on 18 March at Concordia Station despite March typically being a transition month to the Antarctic coreless winter. The driver for these temperature extremes was an intense atmospheric river advecting subtropical/midlatitude heat and moisture deep into the Antarctic interior. The scope of the temperature records spurred a large, diverse collaborative effort to study the heat wave’s meteorological drivers, impacts, and historical climate context. Here we focus on describing those temperature records along with the intricate meteorological drivers that led to the most intense atmospheric river observed over East Antarctica. These efforts describe the Rossby wave activity forced from intense tropical convection over the Indian Ocean. This led to an atmospheric river and warm conveyor belt intensification near the coastline, which reinforced atmospheric blocking deep into East Antarctica. The resulting moisture flux and upper-level warm-air advection eroded the typical surface temperature inversions over the ice sheet. At the peak of the heat wave, an area of 3.3 million km2 in East Antarctica exceeded previous March monthly temperature records. Despite a temperature anomaly return time of about 100 years, a closer recurrence of such an event is possible under future climate projections. In Part II we describe the various impacts this extreme event had on the East Antarctic cryosphere. Significance Statement In March 2022, a heat wave and atmospheric river caused some of the highest temperature anomalies ever observed globally and captured the attention of the Antarctic science community. Using our diverse collective expertise, we explored the causes of the event and have placed it within a historical climate context. One key takeaway is that Antarctic climate extremes are highly sensitive to perturbations in the midlatitudes and subtropics. This heat wave redefined our expectations of the Antarctic climate. Despite the rare chance of occurrence based on past climate, a future temperature extreme event of similar magnitude is possible, especially given anthropogenic climate change.

Approach to mediastinal masses: a comparison of open surgery and uniportal video-assisted thoracoscopic surgery techniques

Aims: This study aimed to compare perioperative and postoperative outcomes in patients who underwent uniportal video-assisted thoracoscopic surgery (U-VATS) and open surgery for mediastinal mass resection. Methods: A total of 62 patients who underwent mediastinal mass resection in the Thoracic Surgery Clinic were included. The patients were separated into the open surgery group (n=30) and the U-VATS group (n=32). The groups were compared in terms of perioperative and postoperative outcomes including operative time, blood loss, chest tube removal time, drainage volume, pain, and hospital stay. Results: The distributions of age and gender were similar between the groups. Median operation time (120 vs. 180 minutes, P < 0.001), median intraoperative blood loss (50 vs. 100 mL, P < 0.001), median time of chest drain removal (4 vs. 6 days, P < 0.001) and median postoperative drainage volumes were lower in the U-VATS group than the open surgery group. The U-VATS group exhibited a lower VAS score, return time to daily activity (1 vs. 4 days, P < 0.001) and length of hospital stay (4 vs. 6 days, P < 0.001). A postoperative myasthenic crisis was not observed in all cases. One thymoma patient in the open surgery group had a recurrence, but not in the U-VATS group. Conclusion: The U-VATS approach had better intraoperative safety and lower postoperative outcomes than open surgery. U-VATS, which has the potential to enhance postoperative recovery and quality of life, may be a safe and effective treatment option for patients with mediastinal mass resection.

Pengaruh Pembiayaan Murabahah dan Lama Pengembalian Pembiayaan terhadap Perkembangan UMKM pada PNM Mekaar Syariah

The aim of this research is to find out whether murabahah financing and the length of murabahah repayment have an effect on the development of UMKM. This research method is quantitative research, the research location studied is PT Permodalan Nasional Madani Mekaar Syariah Percut Sei Tuan Branch. The population in this study were 100 customers of PT Permodalan Nasional Madani Mekaar Syariah Percut Sei Tuan Branch, the samples taken were customers of PT Permodalan Nasional Madani Mekaar Syariah Percut Sei Tuan Branch, the data analysis technique used in this research was multiple linear regression analysis. The results of this research are that murabahah financing has an influence on the development of UMKM, we can see this from the calculated t-value for the financing variable (X1) of 5.813 > t-table value of 1.66071 and the significance is smaller than 0.05 (0.0491 < 0 .05). For the murabahah return time variable, the t-calculated value for the return time variable (X2) is 3.825 > t-table value 1.66071 and the significance is smaller than 0.05 (0.005 < 0.05). Based on the results, the calculated F is 8.370 and the F table is 3.09 while the significance is 0.004. It can be seen that the significance value from the table above is smaller than the value 0.05, which means that murabahah financing and the length of repayment together have an influence on the development of UMKM.

Variance reflects resilience to disturbance along a stress gradient: Experimental evidence from coastal marshes.

Quantifying ecosystem resilience to disturbance is important for understanding the effects of disturbances on ecosystems, especially in an era of rapid global change. However, there are few studies that have used standardized experimental disturbances to compare resilience patterns across abiotic gradients in real-world ecosystems. Theoretical studies have suggested that increased return times are associated with increasing variance during recovery from disturbance. However, this notion has rarely been explicitly tested in field, in part due to the challenges involved in obtaining long-term experimental data. In this study, we examined resilience to disturbance of 12 coastal marsh sites (five low-salinity and seven polyhaline [=salt] marshes) along a salinity gradient in Georgia, USA. We found that recovery times after experimental disturbance ranged from 7 to >127 months, and differed among response variables (vegetation height, cover and composition). Recovery rates decreased along the stress gradient of increasing salinity, presumably due to stress reducing plant vigor, but only when low-salinity and polyhaline sites were analyzed separately, indicating a strong role for traits of dominant plant species. The coefficient of variation of vegetation cover and height in control plots did not vary with salinity. In disturbed plots, however, the coefficient of variation (CV) was consistently elevated during the recovery period and increased with salinity. Moreover, higher CV values during recovery were correlated with slower recovery rates. Our results deepen our understanding of resilience to disturbance in natural ecosystems, and point to novel ways that variance can be used either to infer recent disturbance, or, if measured in areas with a known disturbance history, to predict recovery patterns.

Comparative analyses of arthroscopic and open repairs of lateral ligament complex injuries of the ankle: a systematic review and meta-analysis of the medium-term outcomes.

Little is known regarding the comparative analyses of the medium-term outcomes (with a mean minimum follow-up period of 24months), between arthroscopic and open repairs of lateral ligament complex (LLC) injuries of the ankle. Thus, in this study, we aimed to explore the comparative analyses regarding the medium-term follow-up outcomes of these repairs, by conducting a systematic review and meta-analysis. The systematic review and meta-analysis were performed as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines; data were extracted from the PubMed and Google Scholar databases. From an initial search, a total of 1182 abstracts (280 and 902 abstracts, from PubMed and Google Scholar, respectively) were found and screened in accordance with the eligibility criteria. Subsequently, six articles were found to be eligible for further review. A total of 419 patients underwent surgical repairs; 205 and 214 patients underwent arthroscopic and open repairs, respectively. The mean minimum follow-up period was 29.2months. The medium-term follow-up for arthroscopic LLC repairs was found to be superior to that of open LLC repairs, with more favorable outcomes; as evidenced by better clinical scores, lower pooled complication rates, earlier return times to pre-injury sport, and higher early sport ratios. The findings of this systematic review and meta-analysis support near-future developments validating arthroscopic repair as the new gold standard for LLC repairs, similarly to arthroscopic ligament and tendon repairs, as well as arthroscopic reconstruction surgeries, of the knee and shoulder.

VaR and ES forecasting via recurrent neural network-based stateful models

Due to the widespread and quickly escalating effects of large negative returns, as well as due to the increase in the importance of regulatory framework for financial institutions, the accurate measurement of financial risks has become a relevant question in the academia and industry. This paper proposes three novel models based on stateful Recurrent Neural Networks (RNN) and Feed-Forward Neural Networks (FNN) to build forecasts for Value-at-Risk (VaR) and Expected Shortfall (ES). We apply the models to six asset return time series spanning over more than 20 years. Our results reveal that the RNN-based stateful models generally outperform the non-stateful RNN models and econometric benchmark models including rolling window models, Generalized AutoRegressive Conditional Heteroskedasticity (GARCH)-type models, and Generalized Autoregressive Score (GAS) models, in terms of VaR and ES forecasting.

Symptom presentation and evolution in the first 48 hours after injury are associated with return to play after concussion in elite Rugby Union

BackgroundReturn to play (RTP) in elite rugby is managed using a 6-stage graduated RTP protocol, which can result in clearance to play within 1 week of injury. We aimed to explore how symptom, cognitive, and balance presentation and evolution during concussion screens 2 h (head injury assessment (HIA) 2) and 48 h (HIA3) after injury were associated with time to RTP) to identify whether a more conservative graduated RTP may be appropriate. MethodsA retrospective cohort study was conducted in 380 concussed rugby players from elite men's rugby over 3 consecutive seasons. Players were classified as shorter or longer returns, depending on whether RTP occurred within 7 days (allowing them to be considered to play the match 1 week after injury) or longer than 8 days, respectively. Symptom, cognitive, and balance performance during screens was assessed relative to baseline (normal or abnormal) and to the preceding screen (improving or worsening). Associations between sub-test abnormalities and RTP time were explored using odds ratios (OR, longer vs. shorter). Median day absence was compared between players with abnormal or worsening results and those whose results were normal or improving. ResultsAbnormal symptom results during screens 2 h and 48 h after concussion were associated with longer return time (HIA2: OR = 2.21, 95% confidence interval (95%CI): 1.39–3.50; HIA3: OR = 3.30, 95%CI: 1.89–5.75). Worsening symptom number or severity from the time of injury to 2 h and 48 h post-injury was associated with longer return (HIA2: OR = 2.49, 95%CI: 1.36–4.58; HIA3: OR = 3.34, 95%CI: 1.10–10.15. Median days absence was greater in players with abnormal symptom results at both HIA2 and HIA3. Cognitive and balance performance were not associated with longer return and did not affect median days absence. ConclusionSymptom presentation and evolution within 48 h of concussion were associated with longer RTP times. This may guide a more conservative approach to RTP, while still adhering to individualized concussion management principles.

Estimating the Hausdorff measure using recurrence

AbstractWe show a new method of estimating the Hausdorff measure of a set from below. The method requires computing the subsequent closest return times of a point to itself.

Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm

Droughts pose a severe environmental risk in countries that rely heavily on agriculture, resulting in heightened levels of concern regarding food security and livelihood enhancement. Bangladesh is highly susceptible to environmental hazards, with droughts further exacerbating the precarious situation for its 170 million inhabitants. Therefore, we are endeavouring to highlight the identification of the relative importance of climatic attributes and the estimation of the seasonal intensity and frequency of droughts in Bangladesh. With a period of forty years (1981–2020) of weather data, sophisticated machine learning (ML) methods were employed to classify 35 agroclimatic regions into dry or wet conditions using nine weather parameters, as determined by the Standardized Precipitation Evapotranspiration Index (SPEI). Out of 24 ML algorithms, the four best ML methods, ranger, bagEarth, support vector machine, and random forest (RF) have been identified for the prediction of multi-scale drought indices. The RF classifier and the Boruta algorithms shows that water balance, precipitation, maximum and minimum temperature have a higher influence on drought intensity and occurrence across Bangladesh. The trend of spatio-temporal analysis indicates, drought intensity has decreased over time, but return time has increased. There was significant variation in changing the spatial nature of drought intensity. Spatially, the drought intensity shifted from the northern to central and southern zones of Bangladesh, which had an adverse impact on crop production and the livelihood of rural and urban households. So, this precise study has important implications for the understanding of drought prediction and how to best mitigate its impacts. Additionally, the study emphasizes the need for better collaboration between relevant stakeholders, such as policymakers, researchers, communities, and local actors, to develop effective adaptation strategies and increase monitoring of weather conditions for the meticulous management of droughts in Bangladesh.

Giant mobile coralliths from the Florida Keys, USA

Coralliths are spherical, free-living (motile), scleractinian colonies inhabiting present day and ancient coral reefs. They form by the coral rolling on the seabed which can occur through biological and/or physical processes. While diving and snorkeling in nearshore environments in the upper Florida Keys, we observed hundreds of coralliths of varying sizes and species. This included colonies of Porites astreoides, Siderastrea radians, and Solenastrea bournoni. The largest coralliths we observed were all S. bournoni and ranged between 0.5 and 1.4 m in diameter. The exceptionally large colonies identified (>1 m) may be the largest and oldest spherical coralliths described to date. Relatively frequent movement of a corallith is key to their formation as all colony surfaces must be exposed to sunlight and currents periodically to maintain their spherical shape. Intuitively, the larger a corallith grows, the stronger the current energy must be to initiate movement. Considering the shallow depth of the corallith habitat and the high frequency of tropical storms and hurricanes impacting south Florida, we hypothesized that the forces generated by shoaling, breaking storm waves would be sufficient to cause the formation of these giant coralliths. Calculations based on hydrodynamic forces and field observations after the passage of a storm support the efficacy of storm-generated waves and surge to move and roll these giant coralliths. The tropical storm/hurricane return time where we found these large colonies in the Florida Keys is one in every seven years. This return time is apparently frequent enough to maintain their spherical morphology and assist in the formation of these giant coralliths.

Outcome of combined anatomic reconstruction of the anterior cruciate ligament with anterolateral ligament reconstruction versus with iliotibial band tenodesis

Abstract Background Isolated anterior cruciate ligament (ACL) tears without anterolateral structures injuries are treated successfully by isolated reconstruction of ACL. However, most ACL injuries are associated with the injuries of anterolateral stabilizers of the knee; mainly the iliotibial tract (ITB) and the anterolateral ligament (ALL). If ACL is only reconstructed in such a case, the incidence of postoperative rotational instability reaches 18%. New directions guided towards combined ACL reconstruction with extraarticular anatomical and nonanatomical reconstructions to improve knee rotation and translation and prevent pivot shift phenomena. Patients and methods We retrospectively reviewed all patients operated on for combined injuries of ACL and anterolateral stabilizers from February 2019 to February 2021. Preoperatively and postoperatively, all patients were examined clinically by knee stability tests: anterior drawer, Lachman, and pivot shift tests, applying the International Knee Documentation Committee score and return time to the sport. Results Forty patients were included with a mean age of 28 ± 8.33 years (range, 18–44 years). Patients were divided into two groups, group A 20 patients (18 males and two females) were treated by combined ACL with ALL reconstruction, and group B 20 patients (18 males and two females) were treated by combined ACL with ITB tenodesis. Sports injuries were the cause in 15 patients in group A and 14 in group B, while five injuries were due to nonsport activity in group A and six in group B. The mean follow-up period was 33.5 ± 2.1 months. Median postoperative subjective International Knee Documentation Committee scores in groups A and B were 95.4 and 94.25, respectively, without any statistically significant difference. Group A shows better postoperative improvement in pivot shift and one-leg hop test than group B with a significant difference (P<0.05). Conclusion No significant difference between ALL reconstruction or ITB tenodesis with ACL reconstruction according to subjective knee functions but there was a significant difference according to objective functions, also lateral knee pain was reported in group B and not observed in group A.

Optimized charging-station placement and UAV trajectory for enhanced uncertain target detection in intelligent UAV tracking systems

Unmanned Aerial Vehicle (UAV) technology is proposed to improve social safety, provide specialized services, and improve overall well-being in crowded indoor spaces. The deployment of drones in indoor environments can improve emergency response time, offer various wireless services, allow efficient tracking, and improve awareness in crowded scenarios. In this paper, we propose a UAV-based tracking framework that relies on energy-limited UAVs that attempts to determine the appropriate placement of UAV charging stations (CHSs) and design a UAV path planning strategy to effectively carry out detection/tracking tasks of uncertain phenomena. The proposed framework comprises a CHS placement method and a UAV path planning algorithm. The CHS placement method attempts to find the optimal placement of a given number of available CHSs so that the energy consumed by a UAV to reach the nearest CHS is reduced. This, consequently, preserves the UAV’s energy, reducing the time required to return to the CHS and the period of none-tracking during the return time to the CHS. This can extend the tracking mission time and enhance detection performance. Based on the obtained optimal CHS placement, we design a reinforcement learning (RL)–based UAV trajectory algorithm to effectively detect and track a target (event of interest) with unknown behavior. The proposed RL-based UAV trajectory algorithm leverages long-term spatio-temporal behavior knowledge of uncertain targets (i.e., observed and learned events) to improve detection accuracy. Improving the detection of uncertain targets leads to better decision-making, faster responses, and improved security, safety, and efficiency in applications such as surveillance, defense, and search and rescue. The simulation results demonstrate the superior detection accuracy achieved by the proposed framework. Compared to a reference RL-based approach, the proposed algorithm achieves up to 65% higher detection accuracy in symmetric monitored areas and 20% increased accuracy in asymmetric monitored areas.

New computational results for integrated production and outbound distribution scheduling problems for a product with a short lifespan

In this paper, we consider an integrated production and outbound distribution scheduling problem with a single production site, and its extension to multiple plants. A set of orders must be satisfied such that the required pieces from a single product must be first processed on a single machine in a plant, then must be delivered to the customers before their lifespan expire using a single vehicle. The goal is to minimize the makespan of the solution, which is the return time of the vehicle after its last trip. We propose an elementary variable neighborhood search to solve the problem, using two new local search operators. Our computational results show that this simple procedure outperforms the existing, sometimes complex approaches on the widely used benchmark dataset. We also review the existing computational results, and demonstrate that in some cases the comparisons in the literature are invalid due to the use of different rounding of the data. By re-evaluating the accessible solutions we provide a fair comparison for each rounding method. We also consider the extension of the problem to multiple plants, and adapt our solution approach for this extension. Our experiments show that our method is competitive in terms of solution quality with the existing solution approach for the problem.

THE (IN)EFFICIENCY OF USA EDUCATION GROUP STOCKS: BEFORE, DURING AND AFTER COVID-19

This paper represents a pioneering effort to investigate multifractal dynamics that exclusively encompass the return time series of USA Education Group Stocks concerning two non-overlapping periods (before, during, and after COVID-19). Given this, we employ the Multifractal Detrended Fluctuations Analysis (MF-DFA). In this sense, we investigate the generalized Hurst exponent [Formula: see text] and the Rényi exponent [Formula: see text] for each asset and quantify their statistical properties, which allowed us to observe separately the contributing small scale (primarily via the negative moments [Formula: see text]) and the large scale (via the positive moments [Formula: see text]). We perform a fourth-degree polynomial regression fit to estimate the complexity parameters that describe the degree of multifractality of the underlying process. Also, we shall apply the inefficiency multifractal index to assess the COVID-19 shock for both periods. Our findings show that for both periods, the majority of these assets are marked by multifractal dynamics associated with persistent behavior [Formula: see text], a higher degree of multifractality and the dominance of large fluctuations. At the same time, most of these assets show asymmetry parameter [Formula: see text] for both periods, indicating that large fluctuations contributed more to multifractality in the time series of returns.