Daily Updates Research Articles

Different Approaches for Evaluation and Modeling of the Effective Thermal Resistance of Groundwater-Filled Boreholes

Groundwater-filled boreholes are a common solution in Scandinavian installations of ground source heat pumps (GSHP) due to the particular hydro-geological conditions with existing bedrock, and groundwater levels close to the surface. Different studies have highlighted the advantage of water-filled boreholes compared with their grouted counterparts since the natural convection of water within the borehole tends to decrease the effective thermal resistance Rb*. In this study, several methods are proposed for the evaluation and modeling of the effective thermal resistance of groundwater-filled boreholes. They are based on distributed temperature sensing (DTS) measurements of six representative boreholes within the irregular 74-single-U 300 m-deep borehole field of Aalto New Campus Complex (ANCC). These methods are compared with the recently developed correlations for groundwater-filled boreholes, which are implemented within the python-based simulation toolbox Pygfunction. The results from the enhanced Pygfunction simulation with daily update of Rb* show very good agreement with the measured mean fluid temperature of the first 39 months of system operation (March 2018–May 2021). It is observed that in real operation the effective thermal resistance Rb* can vary significantly, and therefore it is concluded that the update of Rb* is crucial for a reliable long-term simulation of groundwater-filled boreholes.

MirrorME: implementation of an IoT based smart mirror through facial recognition and personalized information recommendation algorithm.

We are living in the era of the fourth industrial revolution, which also treated as 4IR or Industry 4.0. Generally, 4IR considered as the mixture of robotics, artificial intelligence (AI), quantum computing, the Internet of Things (IoT) and other frontier technologies. It is obvious that nowadays a plethora of smart devices is providing services to make the daily life of humans easier. However, in the morning most people around the globe use a traditional mirror while preparing themselves for daily tasks. The aim is to build a low-cost intelligent mirror system that can display a variety of details based on user recommendations. Therefore, in this article, Internet of Things (IoT) and AI-based smart mirror is introduced that will support the users to receive the necessary daily update of weather information, date, time, calendar, to-do list, updated news headlines, traffic updates, COVID-19 cases status and so on. Moreover, a face detection method also implemented with the smart mirror to construct the architecture more secure. Our proposed MirrorME application provides a success rate of nearly 87% in interacting with the features of face recognition and voice input. The mirror is capable of delivering multimedia facilities while maintaining high levels of security within the device.

Optimizing the workload of production units of a make-to-order manufacturing system

This paper proposes a production planning approach for a job shop type manufacturing company in electronics sector that operates with make-to-order (MTO) convention and has a high-mix production range. A novel Mixed Integer Linear Programming (MILP) model is proposed that finds workload-dependent planning horizon by making order acceptance decisions. Partial acceptance of orders and delayed internal target deliveries contribute to the novelty of the proposed model. We establish the complexity of the problem and solve real-life problem instances of a medium-size manufacturing company in the south of The Netherlands. Our computational results show that the proposed MILP model can allocate desired workload to work centers by dynamically adjusting the time horizon for production plans. Our approach can practically be used within reasonable times for daily updates of internal production targets. We perform a sensitivity analysis to show how the time horizon is determined with varying system conditions. The obtained workload amounts satisfy minimum requirements of production units, as this cannot be achieved by the current practice.

A Markov model of COVID-19 susceptibilities, infections, recoveries and fatalities: evidence from Nigeria

PurposeThe purpose of this study is to determine the proportion of the population that will be susceptible to the COVID-19 pandemic, as well as the proportions of infections, recoveries and fatalities from the COVID-19 pandemic.Design/methodology/approachThe design was a longitudinal survey of COVID-19 infections, recoveries and fatalities in Nigeria using the data on the daily updates of the Nigeria Centre for Disease Control for the period 1 May to 23 August 2020. Markov chain analysis was performed on the data.FindingsThe results showed that in the long run, 8.4% of the population will be susceptible to COVID-19 infections, 26.4% of them will be infected, 61.2% of the infected will recover and 4% will become fatal. Thus, if this pattern of infections and recoveries continue, the majority of the infected people in Nigeria will recover whilst a very small proportion of the infected people will die.Research limitations/implicationsA dearth of the extant literature on the problem, especially from the management science perspective.Practical implicationsResults of the study will facilitate policymakers’ response to the curtailment of the pandemic in Nigeria.Social implicationsCurtailing the pandemic through the results of this study will assist in easing the social consequences of the pandemic.Originality/valueThe proposed adjustment to the susceptibilities, infections and recoveries model through the introduction of a fourth state (fatality) to get the susceptibilities, infections, recoveries and fatalities model, signalling a point of departure from previous studies.

Analyzing reading habit of newspaper transforming the information for their daily updates

Analyzing reading habit of newspaper transforming the information for their daily updates

The Spread of COVID-19 in Nigeria: The Influence of Transportation and Economic Zones

The novel coronavirus (2019-nCoV) now known as Covid-19 was first detected in the city of Wuhan, China in December 2019. The disease rapidly spread to other cities in China and to other parts of the world. The aim of this study is to investigate the contribution which the economic zones and movement of people into the country and from city to city and State to State within the country have on the spread of the disease in Nigeria. Data of the daily update of Covid-19 occurrence in Nigeria as given by the NCDC Covid-19 Situation report were assembled. The data of the first index in each State between February 27 and March 28, 2020 with the status of whether they were from foreign travel or from within the community was compiled. The results show that economic zones and human movement contribute to the early spread of the disease. The initial spatial spread in Nigeria was observed to follow closely behind the test laboratory distribution pattern. This may suggest that samples from the locations far from the laboratories were not obtained, hence the suggestion for early aggressive country-wide-large scale testing to cover almost everyone should be started very early before the spread is everywhere. The test labs should cover the whole country with the tests made free and mandatory to encourage and force people to come out for it and the restriction protocols should strictly be adhered to. The boarders of the country should be closed early to stop further import of the disease from the high risk countries. When the airports are later re-opened, they should not be to the high-risk countries of the disease. There is also a need for a national policy on responding to and managing any future public health crisis such as Covid-19 pandemic before its occurrence. This policy will help the government to know what to start doing quickly when there is any occurrence. Government should also look inward to mobilize the scientists inside the country by providing research grants purposely to combat the pandemic. Such grants will enable our scientists to make their contribution in addition to the ones made by the scientists outside the country.

Administrative Restrictions in Ports: Practice of Crew Rotations During COVID-19 Pandemic

The article describes changes in imposing administrative restrictions for crew rotations in ports worldwide under the ongoing pandemic COVID-19 situation. The first part of the article provides a brief overview of the impact of the COVID-19 pandemic on seafarers’ well-being, considering the key role of seafarers in providing international trade, maritime security, and protection of the environment. The second part of the article describes the national and regional experience in addressing COVID-19 under crew rotations; highlights the main tendencies of strengthening/easing restrictions in seaports. The most typical restrictive administrative measures in crew rotations include dockage during the crew change off the port, ensuring social distancing, strict health monitoring, and the negative coronavirus test result, proof of being quarantined or staying on board given period. Furthermore, international organizations were considered efforts to minimize the impact of the pandemic on the stability of crew changes in ports. The recommended measures primarily focus on simplifying and stabilizing the crew changes procedures, including the unification of rotation procedures, adopting multilateral global management in the sphere, effective information exchange, etc. Lack of consolidated information about all administrative restrictions world’s largest ports has become a complex issue. In that regard, the non-state actors play an essential role in the information support of seafarers. However, such efforts can be enhanced by adding imperative rules, like daily updating of information by governments and implementing the control system with a possibility of sanctions implementation in ship detentions under Port State Control procedures.

Why Trusting Nigeria Centre for Disease Control Information Is Difficult: A Study of The Awareness, Knowledge and Perceptions of Nigerians Hesitant Towards COVID-19 Management by NCDC in Nigeria

As the world battles the novel Coronavirus pandemic ravaging lives and destroying economies, many nations have entrusted the detection, handling and management of confirmed coronavirus cases to their leading public health institutions. For Nigeria, the Nigeria Centre for Disease Control (NCDC), charged with the said responsibility, faces a worrisome myriad of backlash from citizens' who regard their daily update of confirmed cases as misleading. In this survey, the researchers purposively study this category of sceptic individuals to understand their level of awareness of the virus and their perceptions about the government agency, to determine the factors responsible for the lack of confidence in the reportage, and how their confidence level may be boosted. The study adopted a mixed-method to recruit some 425 respondents that fit the profile of 'those who lack confidence in the NCDC daily reports'. Findings revealed that even the aware, educated, and high-income Nigerians equally constitute those with misperceptions and scepticism about the NCDC. Key reasons for the distrust include inconsistent reporting, secrecy about patients' database, and perceived corruption tendencies. Recommendations based on the findings call for increased openness and access to compelling information about activities to curtail the infection, especially transparency in treatment and budget spending.

Impact of COVID-19 lockdown on undergraduate nursing and medical students of a medical college in Pokhara, Nepal

Introduction: Coronavirus disease 2019 (COVID-19) is a highly infectious disease declared a pandemic on March 11, 2020, by WHO. As a preventive measure, Nepal was put into lockdown from 24 March to 21 July, 2020 for the first wave of COVID-19 infection. Sudden lockdown prompted the widespread closure of educational institutions. This study aimed to assess the academic and social impact due to COVID-19 lockdown on undergraduate students. Method: A web based cross sectional study was conducted among 403 undergraduate students of Manipal College of Medical Sciences (MCOMS), Pokhara Nepal using the total enumeration method after the ethical approval from Institutional Review Committee (IRC), Manipal Teaching Hospital. Data was collected through online self-administered questionnaires by using Microsoft Form. Analysis of the results was done by using descriptive and inferential statistics. Result: High academic (55.6%) and social (53.8%) impact was seen in the students. Female (OR: 1.76; CI 1.1-2.82), Nepalese students (OR: 2.05; CI 1.19-3.51), data pack users (OR: 2.09; CI 1.16-3.78) were more likely to have a high academic impact. Foreign students (OR: 1.88; CI 1.11-3.11) and students having a daily update of COVID-19 (OR: 2.2; CI 1.03-4.66) were more likely to have a high social impact. Conclusion: Academic impact was seen more in female and Nepalese students while the social impact was high among foreign students. Educational activities need to continue in this critical situation. Concerned authorities need to focus on the improvement of digital infrastructure and technology along with the continuation of clinical learning with safety precautions during this pandemic time for better learning among students.

Targeted literature review of the burden of illness in patients with chronic kidney disease and type 2 diabetes.

Chronic kidney disease (CKD) is increasingly prevalent among patients with type 2 diabetes (T2D). CKD is associated with increased mortality rates, clinical and humanistic burden, and substantial health care costs in the T2D population. The objective of this review was to summarize the burden of illness among patients with CKD and T2D, including the profile of patients, incidence, prevalence, mortality, progression, diagnosis and screening rates, and cardiovascular (CV) events. A targeted literature review of published studies was conducted using Embase; Medline; Medline In-Process Citations, Daily Update, and Epub Ahead of Print; Igaku Chuo Zasshi databases; and 7 websites. Methods recommended by the Cochrane collaboration handbook, the Centre for Reviews and Dissemination, and the Joanna Briggs Institute critical appraisal checklist were employed. A total of 1290 full-text articles were reviewed for eligibility and 73 were included in this analysis. Patient profiles indicated older age was associated with more severe disease and number of comorbidities. The definition of kidney disease varied between studies reporting incidence and prevalence, with reported values up to 37.0% and 43.5% for incidence and prevalence, respectively. CKD among patients with T2D contributed to higher mortality rates. Higher disease progression rates were associated with higher albuminuria and lower estimated glomerular filtration rate levels. The available literature suggested annual screening rates for CKD declined over time. CV events were reported to have a substantial effect on morbidity and resource use. This review highlights the burden of CKD among patients with T2D and underscores a need for new treatment alternatives to reduce the burden of disease.

Bibliometric analysis of international publication trends in impacted third molar surgery research (2000–2020)

In scientific fields, various methods of statistical analysis such as bibliometric analysis have been used to determine the effectiveness of journals, research, and articles. The aim of this study was to conduct a bibliometric analysis to systematically and understandably characterise publications on impacted third molar surgery (ITMS) from 2000 to 2020. The articles were retrieved on the same day (1 January 2021) from the Web of Science Core Collection (WoSCC) database of the Web of Science to prevent bias due to daily updates of the databases. A total of 3326 publications from 2000 to 2020 were analysed. The United States of America (USA) had the highest number of publications and h-index value. The highest number of co-citations were of Pell GJ. ITMS research was collected under nine ‘clusters’. In this study, developments, the most influential publications, journals, and countries in the research of ITMS were determined based on the evidence gained through bibliometric analysis.

Admissions to Norwegian Hospitals during the COVID-19 Pandemic.

In mid-March 2020, the Norwegian government implemented measures to contain the coronavirus disease 2019 (COVID-19) pandemic, and hospitals prepared to handle an unpredictable inflow of patients with COVID-19. The study was performed to describe the changes in hospital admissions during the first phase of the pandemic. The Norwegian Institute of Public Health established a national preparedness register with daily updates on COVID-19 cases and the use of health services. We used individual-level information on inpatients from the electronic journal systems for all hospitals in Norway to estimate daily hospital admissions. Before the onset of the pandemic in March, there was an average of 2400 inpatient admissions per day in Norway, which decreased to approximately 1500 in the first few days after lockdown measures were implemented. The relative magnitudes of the decreases were similar in men and women and across all age groups. The decreases were substantial for both elective (54%) and emergency (29%) inpatient care. The admission rate gradually increased and reached pre-pandemic levels in June. However, the reductions in admissions for pneumonia and chronic obstructive pulmonary disease seemed to persist. The elective and emergency inpatient admission rates were substantially reduced a few days after the pandemic response measures were implemented. The ways in which the lack or postponement of care may have affected the health and well-being of patients is an important issue to be addressed in future research.

Systematic Literature Review and Meta-Analysis of Sacral Neuromodulation (SNM) in Patients with Neurogenic Lower Urinary Tract Dysfunction (nLUTD): Over 20Years' Experience and Future Directions.

IntroductionSacral neuromodulation (SNM) has been used in carefully selected patients with neurogenic lower urinary tract dysfunctions (nLUTD) for over two decades.MethodsThe aim of the current work was to perform a systematic literature review and meta-analysis of studies reporting the safety and effectiveness of SNM in patients with nLUTD (neurogenic detrusor overactivity, non-obstructive urinary retention, or a combination of both). For this purpose a systematic literature research was conducted using Embase (OvidSP), MEDLINE (OvidSP), MEDLINE In-Process Citations & Daily Update (OvidSP), MEDLINE (OvidSP) e-Pub ahead of print, Cochrane Central Register of Controlled Trials (CENTRAL), NIH Clinicaltrials.gov, and WHO International Clinical Trials Registry Platform (ICTRP) between 1998 and March 2020, supplemented by a hand search.ResultsForty-seven studies were included in the systematic literature review. Twenty-one studies comprising a total of 887 patients were included in the meta-analysis of test SNM. The pooled success rate of SNM test stimulation was 66.2% (95% CI 56.9–74.4). Depending on neurogenic conditions test success rates varied greatly. Twenty-four studies with a total of 428 patients were included in the meta-analysis of permanent SNM. The success rate of pooled permanent SNM was 84.2% (95% CI 77.8–89.0). Among the identified studies, the most common adverse events (AEs) were loss of effectiveness, infection, pain at implant site, and lead migration with AE rates of 4.7%, 3.6%, 3.2%, and 3.2%, respectively. Limitations entail lower level of evidence (Oxford classification 3–4) of included studies, significant risk of bias, small sample sizes in some studies, the inclusion of retrospective case series, substantial between-study heterogeneity, heterogeneous patient populations, insufficient disease classification, and variations in terms of outcome parameters as well as techniques. Furthermore, long-term data are limited.ConclusionThis meta-analysis supports not only the benefits of permanent SNM for various nLUTDs but also high overall success rates, similar to idiopathic patients. Current data of the analyzed studies showed that SNM is safe for these patients. However, more vigorous studies and/or registries are needed before definitive conclusions can be drawn.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12325-021-01650-9.

Daily Routine Recognition for Hearing Aid Personalization

This work focuses on daily routine recognition to personalize the hearing aid (HA) configuration for each user. So far, there is only one public data set containing the data of two acceleration sensors taken under unconstrained real-life conditions of one person. Therefore, we create a realistic and extensive data set with seven subjects and a total length of 63449 min. For the recordings, the HA streams the acceleration and audio data to a mobile phone, where the user simultaneously annotates it. This builds the grounds for our comprehensive simulations, where we train a set of classifiers in an offline and online manner to analyze the model generalization abilities across subjects for high-level activities. To achieve this, we build a feature representation, which describes the recurring daily situations and environments well. For the offline classification, the deep neural network, multi-layer perceptron (MLP), and random forest (RF) trained in a person-dependent manner show the significantly best F-measure performance of 86.6%, 87.1%, and 87.3%, respectively. We confirm that for high-level activities the person-dependent model outperforms the independent one. In our online experiments, we personalize a model that was pretrained in a person-independent manner by daily updates. Thereby, multiple incremental learners and an online RF are tested. We demonstrate that MLP and RF improve the F-measure compared to the offline baselines.

Dashboard COMPRIME_COMPRI_MOv: Multiscalar Spatio-Temporal Monitoring of the COVID-19 Pandemic in Portugal

Due to its novelty, the recent pandemic of the coronavirus disease (COVID-19), which is associated with the spread of the new severe acute respiratory syndrome coronavirus (SARS-CoV-2), triggered the public’s interest in accessing information, demonstrating the importance of obtaining and analyzing credible and updated information from an epidemiological surveillance context. For this purpose, health authorities, international organizations, and university institutions have published online various graphic and cartographic representations of the evolution of the pandemic with daily updates that allow the almost real-time monitoring of the evolutionary behavior of the spread, lethality, and territorial distribution of the disease. The purpose of this article is to describe the technical solution and the main results associated with the publication of the COMPRIME_COMPRI_MOv dashboard for the dissemination of information and multi-scale knowledge of COVID-19. Under two rapidly implementing research projects for innovative solutions to respond to the COVID-19 pandemic, promoted in Portugal by the FCT (Foundation for Science and Technology), a website was created. That website brings together a diverse set of variables and indicators in a dynamic and interactive way that reflects the evolutionary behavior of the pandemic from a multi-scale perspective, in Portugal, constituting itself as a system for monitoring the evolution of the pandemic. In the current situation, this type of exploratory solutions proves to be crucial to guarantee everyone’s access to information while simultaneously emerging as an epidemiological surveillance tool that is capable of assisting decision-making by public authorities with competence in defining control policies and fight the spread of the new coronavirus.

COVID-19 and Disenfranchised Grief.

Although death is an inherent part of life, for many it is a terrifying event, which awareness is often to be avoided at all costs (1). However, with the daily updates of COVID-19 cases and deaths, the confrontation with human mortality and physical fragility is unavoidable. Over 100 million confirmed cases and over 2 million confirmed deaths worldwide have been recorded (2). The COVID-19 pandemic is a health crisis unprecedented in contemporary history. Furthermore, an estimate of 9 bereaved family members results from each COVID-19 death (3). Recent evidence indicates that, due to the circumstances in which deaths in the COVID era occur—unexpected and shocking deaths, social distancing, restrictions in visits in healthcare facilities and in funerals—another epidemic is on the rise: prolonged grief disorder (PGD) [e.g., (4)]. PGD is characterized by persistent and pervasive longing for, or preoccupation with the lost one, as well as severe emotional pain (such as, guilt, anger, or sadness), difficulty accepting the death, emotional numbness, a sense that a part of them has been lost, an inability to experience positive mood and difficulty participating in social activities (International Classification of Diseases-11, (5)). With each death that occurs, there are loved ones who will be deeply impacted by the loss, particularly at a time when, due to sanitary restrictions, they may experience limited autonomy, and resourcefulness when coping with their grief. The awareness of these limitations heighten the risk of grievers experiencing their grief as disenfranchised to a degree. Kenneth Doka first formally introduced the notion of disenfranchised grief in 1989 and defined it as the process in which the loss is felt as not being “openly acknowledged, socially validated, or publicly mourned” (1989, p. xv). This experience of grief might pose difficulties in terms of emotional processing and expression, as one may not recognize his/her right to grieve, and in terms of social support, by diminishing the opportunity to freely express their emotions, and to obtain expressions of compassion and support (6). Given the challenges that the disenfranchisement of grief might add to the bereavement experience, it is important to reflect on the risk for this experience in the context of the COVID-19 circumstances. In this opinion paper we aim to frame this in light of the felt limitations in autonomy and resourcefulness in the COVID-19 bereaved, either imposed externally, or internally (self-disenfranchisement).

Real-Time Bibliometrics: Dimensions as a Resource for Analyzing Aspects of COVID-19.

Dimensions was built as a platform to allow stakeholders in the research community, including academic bibliometricians, to more easily create and understand the context of different types of research object through the linkages between these objects. Links between objects are created via persistent identifiers and machine learning techniques, while additional context is introduced via data enhancements such as per-object categorisations and person and institution disambiguation. While these features make analytical use cases accessible for end users, the COVID-19 crisis has highlighted a different set of needs to analyze trends in scholarship as they occur: Real-time bibliometrics. The combination of full-text search, daily data updates, a broad set of scholarly objects including pre-prints and a wider set of data fields for analysis, broadens opportunities for a different style of analysis. A subset of these emerging capabilities is discussed and three basic analyses are presented as illustrations of the potential for real-time bibliometrics.

'Timing' of letters to patients may be causing low COVID-19 vaccination booking rates for pharmacy sites

The “timing of sending and arrival” of letters sent to patients eligible for COVID-19 vaccination may be the cause of low booking rates in some community pharmacy-led sites, the NHS has said. In a daily update sent to vaccination sites on 27 January 2021, NHS England also advised community pharmacy sites to check their settings — such […]

Analysis and Forecasting COVID-19 Outbreak in Pakistan Using Decomposition and Ensemble Model

COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world. Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce the number of new cases. In this study, we apply the decomposition and ensemble model to forecast COVID-19 confirmed cases, deaths, and recoveries in Pakistan for the upcoming month until the end of July. For the decomposition of data, the Ensemble Empirical Mode Decomposition (EEMD) technique is applied. EEMD decomposes the data into small components, called Intrinsic Mode Functions (IMFs). For individual IMFs modelling, we use the Autoregressive Integrated Moving Average (ARIMA) model. The data used in this study is obtained from the official website of Pakistan that is publicly available and designated for COVID-19 outbreak with daily updates. Our analyses reveal that the number of recoveries, new cases, and deaths are increasing in Pakistan exponentially. Based on the selected EEMD-ARIMA model, the new confirmed cases are expected to rise from 213,470 to 311,454 by 31 July 2020, which is an increase of almost 1.46 times with a 95% prediction interval of 246,529 to 376,379. The 95% prediction interval for recovery is 162,414 to 224,579, with an increase of almost two times in total from 100802 to 193495 by 31 July 2020. On the other hand, the deaths are expected to increase from 4395 to 6751, which is almost 1.54 times, with a 95% prediction interval of 5617 to 7885. Thus, the COVID-19 forecasting results of Pakistan are alarming for the next month until 31 July 2020. They also confirm that the EEMD-ARIMA model is useful for the short-term forecasting of COVID-19, and that it is capable of keeping track of the real COVID-19 data in nearly all scenarios. The decomposition and ensemble strategy can be useful to help decision-makers in developing short-term strategies about the current number of disease occurrences until an appropriate vaccine is developed.

Power User Taging System Based on Micro-service

With the rapid development of the electronic channel of State Grid Corporation of China, the electric power user taging system, one of the back-end support systems of the electronic channel, is also expanding. In this paper, a micro-service-based power user taging system is proposed, and the micro-service function requirement analysis is introduced. The micro-service of the electric power user taging system designed in this paper run independently to meet the needs of daily operation, update and expansion of the application.