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Purpose This study aims to review the degree to which fraud and other unethical practices especially in the digital space have affected the Nigerian banking industry both in the past and present, and how it will be a growing concern in the imminent future. The objective of the study was to examine the impact of electronic fraud on the quality of assets and return on assets of Nigerian deposit money banks. Design/methodology/approach The research used secondary data for the periods 2006 till 2018, which were collected from the Nigeria Deposit Insurance Corporation annual reports. Descriptive analysis and the ordinary least square method of regression analysis were used for data analysis. Findings Findings revealed that electronic fraud cases increased progressively over most of the years of study, which can be attributed to the increased bank products that are electronic-based. Originality/value Many of the reviewed literature examined electronic fraud and its impact on bank profitability but this study examined the cause of electronic fraud and what can be done to curtail it.

Proton pump inhibitors (PPI) are widely used and implicated in the progression of chronic kidney disease (CKD). We evaluated the relation between chronic PPI use in veterans with CKD G3a to G4 and the rate of decline in renal function.We accessed the Veteran Affairs Informatics and Computing Infrastructure national database to evaluate the relation between chronic PPI use and rate of decline in renal function in veterans with CKD (eGFR60 ml/min1.73 m2). We applied Propensity Score Matching to match the PPI group and the no-PPI control group on age, sex, race, and Charlson Comorbidity Index. The final sample included 1406 patients (age: 62.07±7.82, 62.02% Caucasian) in the PPI cohort with a median 4.7 years follow-up and 1425 patients (age: 65.45±6.58, 71.16% Caucasian) in the control cohort with a median 3.9 years follow-up. Kaplan-Meier curve and Cox regression were performed to analyze the associations of PPI use with dialysis, all-cause mortality, metabolic acidosis, and CKD progression.The PPI group had a significantly increased risk of CKD progression, dialysis and all-cause mortality (aHR, 1.83; 95% CI, 1.53 to 2.19; aHR, 1.84; 95% CI, 1.26 to 2.67; and aHR, 1.34; 95% CI, 1.08 to 1.65, respectively). The PPI cohort also had a trend for development of metabolic acidosis (aHR, 1.34; 95% CI, 0.998 to 1.80), although the difference was not statistically significant.The data suggest that chronic PPI use accelerates progression of kidney disease and is associated with increased mortality in CKD patients.

A substantial number of epileptic patients are resistant to the current medication thus necessitating the search for alternative therapies for intractable forms of the disease. Previous studies demonstrated the acute anticonvulsant properties of the methanol extract of the stem bark of Psychotria camptopus (MEPC) in rats. This study investigated the effects of MEPC on pentylenetetrazole-kindled Wistar rats. Kindling was induced by intraperitoneal injection of pentylenetetrazole (37.5 mg/kg) on every alternate day, 1 h after each daily oral pretreatment of rats (8 ≤ n ≤ 10) with MEPC (40, 80 and 120 mg/kg), vehicle or diazepam (3 mg/kg) for 43 days. The kindling development was monitored based on seizure episodes and severity. Rats’ brains were collected on day 43 for the determination of oxidative stress parameters. The histomorphological features and neuronal cell viability of the prefrontal cortex (PFC) and hippocampus were also assessed using H&E and Cresyl violet stains. Chronic administration of pentylenetetrazole time-dependently decreased the latency to myoclonic and generalized seizures, and increased seizure scores and the number of kindled rats. MEPC and diazepam significantly increased the latencies to myoclonic jerks and generalized tonic-clonic seizures. These substances also reduced seizure score and the number of rats with PTZ-kindling. MEPC improved glutathione status and decreased lipid peroxidation in the brains of kindled rats. MEPC also exhibited neuroprotection against pentylenetetrazole-induced hippocampal and PFC neuronal damages. These results suggest that P. camptopus has antiepileptogenic activity, which might be related to the augmentation of antioxidant and neuroprotective defense mechanisms, and further confirm its usefulness in the management of epilepsy.

The human capital crisis, reflected in the weak global competitiveness of African education, has questioned the effectiveness of public spending in increasing educational outcomes on the continent. Thus, this article examines the impact of government education expenditure on educational outcomes in 31 sub‐Saharan African (SSA) countries from 2000 to 2019 based on a generalized method of moments (GMM). The study sheds light on the priorities of government education spending on the continent. Findings showed that the effect of government education spending on educational outcomes in SSA was driven by the measure of educational outcome used. Government spending in Africa had focused mainly on primary and secondary education to the detriment of tertiary education because it is convenient and generates political gains. Due to institutional rigidities that emanate from the governance structure, the inequitable allocation of government funding had made higher education in Africa less responsive to the changes in global knowledge and labour market demands. Therefore, the following policy agenda becomes imperative in SSA: (i) government education spending should equitably target all education levels to improve the aggregate human capital development indicators in the region; (ii) there is a need to enhance government institutions' capacity to increase their level of effectiveness and performance.

Purpose: Globalization is the reality of our day and age. Globalization connotes the increasing economic, social, technical, cultural, and political interdependence between nations. People are more inter-connected now than ever. The availability of worldwide communication systems through rapid improvements in communication technology and the internet has led to more international trade and cultural exchange. Methodology: A qualitative study and research was carried out to consider the dynamics and diverse ways globalization has affected our lives and with its own attendant challenges, including the need to design effective multinational organizations, and to identify and select appropriate leaders to manage those organizations with their culturally diverse employees (Northouse,2013). Findings: The research discovered that it is now incumbent on organizational leaders to understand how cultural differences affect their leadership performance and their leadership development systems. Adler and Bartholomew (1992) assert that organizational leaders need to understand various business, political, and cultural environments globally, learn the perspectives, tastes, trends, and technologies of many other cultures, learn how to work with people from many cultures simultaneously, adapt to living and communicating in other cultures, and learn to relate with people from diverse cultural origins from a position of equality rather than cultural superiority. Unique Contribution to theory, practice and policy (Recommendation): Every Successful leaders across borders in the globalized world are expected to embrace diversity by rising above cultural issues such as perceptual bias, discrimination, stereotyping, ethnocentrism, and prejudice. This white paper explores the basic concepts of global leadership, the development of cultural agility, and the process of leadership development across borders.

Purpose: Millennials are multiplying into the workforce population today as they are reaching their peak employment years. They are giving new insight into office life and the structure among employees and employers. They are the next generation to be leaders in the workplace and will be the generation that shapes the future of leadership. There are not many millennial role models that potential leaders can follow and emulate. Nevertheless, the literature regarding millennials and the workforce has been developed primarily in the context of next generation. Less research has been done on ways to building leadership core competencies and capacities for the potential of these millennial leaders, particularly in today’s workforce. Methodology: A qualitative study and research to consider the best practices for enhancing the number of millennials leaders that will lead their company in the upcoming future was carried out. It was also done to seek ways in educating the senior leaders on the importance of changing with the trends and accepting the millennials as the future. By exploring the workplace profile of Millennials, the use of technology, their workplace engagement style, and the ultimate impact they have on organizational success. Findings: The research discovered that to cultivate and enhance the number of millennial leaders, it is important first to understand the attitudes and behaviors of the generation. The primary traits of the millennial generation that may manifest as elements of millennial leadership styles are collaboration, integration, multitasking, experimentation and nomadic behaviors. There are three things leaders can do to assure these millennials will achieve success on the job, despite generational differences. First, is giving them the big picture. Second, leaders need to help the millennials find the “me” in team. Lastly, millennials need to be mentored on career-building behaviors. Career- building is one area in which beginning workers may be deficient compared to the older or more experienced employees. Millennials have many positive leadership traits of which a company should take advantage; they are great multi-taskers, embrace diversity, innovative, flexible, innovate, and willing to put in the extra hours to move toward success. Incorporating these factors while also providing the future leaders with a strong sense of the company’s programs, goals and vision are all important when developing this generation of leaders. Unique Contribution and Recommendation: Today’s workplace is undergoing dramatic shifts due to the growth of Millennials within the workforce and the insertion of their ideals, values, and identity in organizations. Therefore, management should implement some practices to promote these cultures, like flexible work hours and schedules, Employee engagement( work parties, Work outings, work event and gatherings), Clear Career path and opportunities, Open communication, Give them purpose and also acknowledge their work. Developing such skills may require more time and a deeper level of engagement and collaboration than is typically invested in efforts to strengthen the workplace

Background The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification. Methods Training cohorts comprised 1276 patients admitted to King’s College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020. External validation cohorts included 6237 patients from five UK NHS Trusts (Guy’s and St Thomas’ Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals, University Hospitals Birmingham), one hospital in Norway (Oslo University Hospital), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID-19 disease (transfer to intensive care unit (ICU) or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity, and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. Results A baseline model of ‘NEWS2 + age’ had poor-to-moderate discrimination for severe COVID-19 infection at 14 days (area under receiver operating characteristic curve (AUC) in training cohort = 0.700, 95% confidence interval (CI) 0.680, 0.722; Brier score = 0.192, 95% CI 0.186, 0.197). A supplemented model adding eight routinely collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, C-reactive protein, estimated glomerular filtration rate, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI 0.715, 0.757), and these improvements were replicated across seven UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. Conclusions NEWS2 score had poor-to-moderate discrimination for medium-term COVID-19 outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.

This study reviewed literatures on lean management. Many industries faced different challenges due to advent of globalization that led to low productivity which by extension depleted the profitability level of firms operating in global market. Lean management is among the management strategies that are gaining currency at reversing this declining organisational profitability. The way and manner in which lean management is implemented in service industry differs from manufacturing. Hence, one of the simplest methods for addressing the issue of customers’ satisfaction is to apply the method of LM. The objective of this study is to do a review of literature on the subject matter by explores the different positions of scholars on the issues relating to the adoption of LMP in an organisations. The outcome of this paper has shown that for every industry to gain competitive advantage and remain profitable, it is necessary to adopt lean management practice and thus, it will improve customer satisfaction. And also, these approaches will help managers to reduce or eliminate waste, inventory reduction, reduced lead time, less rework and financial savings. It is recommended for all organisations either manufacturing or Services industries to adopt lean management practice in view of stiff global competition and increasing cost on the local environment.

This paper has been to able to ascertain the significant influence of risk attitude on SMEs market share vis-à-vis a relationship between insurance patronage and their financial earnings in the metropolis of Lagos. Descriptive survey design was adopted cum single-stage cluster sampling technique. 256 sample representation produced robust responses through structured questionnaire. Data analytical approach used in this field work were Kolmogorov-Smirnov test method. The research work unravels the significant influence of SMEs’ risk attitude on their market share but at low level. It thus showcased the significant but low relationship between insurance patronage and financial earnings of SMEs in Lagos metropolis. The study recommends therefore that the development of formidable risk management strategies that will help contain subsisting recessionary economic downturn in Nigeria. More so, Stakeholders such as government, insurance practitioners, academics and business tycoons should collaborate and integrate their knowledge, regulatory and financial based resources to help incorporate, implement and fund insurance education curriculum that will facilitate progress, steady growth and development of the youths.

Background: A defining feature of any university is its dedication to scholarly activities, leading to the generation of knowledge and ideas Research productivity is a measure of achievement of a scholar. The number of research publications in peer-reviewed journals is an important criterion for assessing productivity and prestige in the academia. Aims and Objectives: This cross-sectional descriptive study assessed the level of research productivity (RP) among junior faculty at the College of Medicine, University of Lagos, and investigated factors affecting their research output prior to the implementation of a 5-year training grant funded by the National Institutes of Health. Methods: Seventy junior faculty members attended a pre-program training, and the self-reported number of peer-reviewed publications (PRPs) was used as an indicator. Intrinsic and extrinsic factors influencing RP among the attendees were assessed and ranked. Results: The majority (42/70, 60%) of the respondents had

Lassa virus (LASV) is the causative agent of Lassa fever (LF), an often-fatal hemorrhagic disease. LF is endemic in Nigeria, Sierra Leone and other West African countries. Diagnosis of LASV infection is challenged by the genetic diversity of the virus, which is greatest in Nigeria. The ReLASV Pan-Lassa Antigen Rapid Test (Pan-Lassa RDT) is a point-of-care, in vitro diagnostic test that utilizes a mixture of polyclonal antibodies raised against recombinant nucleoproteins of representative strains from the three most prevalent LASV lineages (II, III and IV). We compared the performance of the Pan-LASV RDT to available quantitative PCR (qPCR) assays during the 2018 LF outbreak in Nigeria. For patients with acute LF (RDT positive, IgG/IgM negative) during initial screening, RDT performance was 83.3% sensitivity and 92.8% specificity when compared to composite results of two qPCR assays. 100% of samples that gave Ct values below 22 on both qPCR assays were positive on the Pan-Lassa RDT. There were significantly elevated case fatality rates and elevated liver transaminase levels in subjects whose samples were RDT positive compared to RDT negative.

Background: Attention Deficit and Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder associated with pre-fronto-cortical (PFC) cognitive dysfunctions. Ethanol is a psychoactive agent and its foetal exposure is employed in the modelling of ADHD. Objective: To determine the curative roles of Nigella sativa in the PFC functions of mice induced with ADHD-like symptoms. Method: Twelve BALB/c mice pups each from four groups of dams were studied. Normal saline was administered to the control (CTRL) dams, ethanol to the ETH dams, Nigella Sativa to the NS dams, and Nigella sativa followed with ethanol to the NSE dams. Novel object recognition test was used to assess recognition memory in the pups 15 days after weaning. Histological illustration of PFC was conducted using haematoxylin and eosin (H&E) stain. Results: ETH mice exhibited the least recognition memory while Nigella sativa prevented this deficit in NSE mice by eliciting much higher recognition memory. This indicates the neuroprotective role of Nigella sativa despite prenatal exposure. NS pups also had the highest weight gain, as well as the glutamate and Glutathione, peroxidase (GPX) levels, while raising these levels in the ETH-exposed mice which had the lowest levels, indicating a neurochemical potentiation. The results of the histological analysis showed the protective roles of Nigella sativa on the PFC neuronal densities. Conclusion: This study suggests the protective effects of Nigella sativa on the prefronto-cortical functions in mice ADHD model following maternal exposure to ethanol.

Objectives It is currently thought that most—but not all—individuals infected with SARS-CoV-2 develop symptoms, but that the infectious period starts on average two days before the first overt symptoms appear. It is estimated that pre- and asymptomatic individuals are responsible for more than half of all transmissions. By detecting infected individuals before they have overt symptoms, wearable devices could potentially and significantly reduce the proportion of transmissions by pre-symptomatic individuals. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests [to determine if there are antibodies against the SARS-CoV-2 in the blood] or SARS-CoV-2 infection tests such as polymerase chain reaction [PCR] or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for the following two algorithms to detect first time SARS-CoV-2 infection including early or asymptomatic infection: the algorithm using Ava bracelet data when coupled with self-reported Daily Symptom Diary data (Wearable + Symptom Data Algo; experimental condition) the algorithm using self-reported Daily Symptom Diary data alone (Symptom Only Algo; control condition) In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. Trial design The trial is a randomized, single-blinded, two-period, two-sequence crossover trial. All subjects will participate in an initial Learning Phase (varying from 2 weeks to 3 months depending on enrolment date), followed by two contiguous 3-month test phases, Period 1 and Period 2. Each subject will undergo the experimental condition (the Wearable + Symptom Data Algo) in one of these periods and the control condition (Symptom Only Algo) in the other period. The order will be randomly assigned, resulting in subjects being allocated 1:1 to either Sequence 1 (experimental condition first) or Sequence 2 (control condition first). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. Participants The trial will be conducted in the Netherlands. A target of 20,000 subjects will be enrolled. Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence. This results in approximately 6,500 normal-risk individuals and 3,500 high-risk individuals per sequence. Subjects will be recruited from previously studied cohorts as well as via public campaigns and social media. All data for this study will be collected remotely through the Ava COVID-RED app, the Ava bracelet, surveys in the COVID-RED web portal, and self-sampling serology and PCR kits. During recruitment, subjects will be invited to visit the COVID-RED web portal (www.covid-red.eu). After successfully completing the enrolment questionnaire, meeting eligibility criteria and indicating interest in joining the study, subjects will receive the subject information sheet and informed consent form. Subjects can enrol in COVID-RED if they comply with the following inclusion and exclusion criteria. Inclusion criteria: Resident of the Netherlands At least 18 years old Informed consent provided (electronic) Willing to adhere to the study procedures described in the protocol Must have a smartphone that runs at least Android 8.0 or iOS 13.0 operating systems and is active for the duration of the study (in the case of a change of mobile number, study team should be notified) Be able to read, understand and write Dutch Exclusion criteria: Previous positive SARS-CoV-2 test result (confirmed either through PCR/antigen or antibody tests; self-reported) Previously received a vaccine developed specifically for COVID-19 or in possession of an appointment for vaccination in the near future (self-reported) Current suspected (e.g., waiting for test result) COVID-19 infection or symptoms of a COVID-19 infection (self-reported) Participating in any other COVID-19 clinical drug, vaccine, or medical device trial (self-reported) Electronic implanted device (such as a pacemaker; self-reported) Pregnant at time of informed consent (self-reported) Suffering from cholinergic urticaria (per the Ava bracelet’s User Manual; self-reported) Staff involved in the management or conduct of this study Intervention and comparator All subjects will be instructed to complete the Daily Symptom Diary in the Ava COVID-RED app daily, wear their Ava bracelet each night and synchronise it with the app each day for the entire period of study participation. Provided with wearable sensor and/or self-reported symptom data within the last 24 hours, the Ava COVID-RED app’s underlying algorithms will provide subjects with a real-time indicator of their overall health and well-being. Subjects will see one of three messages, notifying them that: no seeming deviations in symptoms and/or physiological parameters have been detected; some changes in symptoms and/or physiological parameters have been detected and they should self-isolate; or alerting them that deviations in their symptoms and/or physiological parameters could be suggestive of a potential COVID-19 infection and to seek additional testing. We will assess intraperson performance of the algorithms in the experimental condition (Wearable + Symptom Data Algo) and control conditions (Symptom Only Algo). Main outcomes The trial will evaluate the use and performance of the Ava COVID-RED app and Ava bracelet, which uses sensors to measure breathing rate, pulse rate, skin temperature, and heart rate variability for the purpose of early and asymptomatic detection and monitoring of SARS-CoV-2 in general and high-risk populations. Using laboratory-confirmed SARS-CoV-2 infections (detected via serology tests, PCR tests and/or antigen tests) as the gold standard, we will determine the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for each of the following two algorithms to detect first-time SARS-CoV-2 infection including early or asymptomatic infection: the algorithm using Ava Bracelet data when coupled with the self-reported Daily Symptom Diary data, and the algorithm using self-reported Daily Symptom Diary data alone. In addition, we will determine which of the two algorithms has superior performance characteristics for detecting SARS-CoV-2 infection including early or asymptomatic infection as confirmed by SARS-CoV-2 virus testing. The protocol contains an additional seventeen secondary outcomes which address infection incidence rates, health resource utilization, symptoms reported by SARS-CoV-2 infected participants, and the rate of breakthrough and asymptomatic SARS-CoV-2 infections among individuals vaccinated against COVID-19. PCR or antigen testing will occur when the subject receives a notification from the algorithm to seek additional testing. Subjects will be advised to get tested via the national testing programme, and report the testing result in the Ava COVID-RED app and a survey. If they cannot obtain a test via the national testing programme, they will receive a nasal swab self-sampling kit at home, and the sample will be tested by PCR in a trial-affiliated laboratory. In addition, all subjects will be asked to take a capillary blood sample at home at baseline (Month 0), and at the end of the Learning Phase (Month 3), Period 1 (Month 6) and Period 2 (Month 9). These samples will be used for SARS-CoV-2-specific antibody testing in a trial-affiliated laboratory, differentiating between antibodies resulting from a natural infection and antibodies resulting from COVID-19 vaccination (as vaccination will gradually be rolled out during the trial period). Baseline samples will only be analysed if the sample collected at the end of the Learning Phase is positive, and samples collected at the end of Period 1 will only be analysed if the sample collected at the end of Period 2 is positive. When subjects obtain a positive PCR/antigen or serology test result during the study, they will continue to be in the study but will be moved into a so-called “COVID-positive” mode in the Ava COVID-RED app. This means that they will no longer receive recommendations from the algorithms but can still contribute and track symptom and bracelet data. The primary analysis of the main objective will be executed using data collected in Period 2 (Month 6 through 9). Within this period, serology tests (before and after Period 2) and PCR/antigen tests (taken based on recommendations by the algorithms) will be used to determine if a subject was infected with SARS-CoV-2 or not. Within this same time period, it will be determined if the algorithms gave any recommendations for testing. The agreement between these quantities will be used to evaluate the performance of the algorithms and how these compare between the study conditions. Randomisation All eligible subjects will be randomized using a stratified block randomization approach with an allocation ratio of 1:1 to one of two sequences (experimental condition followed by control condition or control condition followed by experimental condition). Based on demographics, medical history and/or profession, each subject will be stratified at baseline into a high-risk and normal-risk group within each sequence, resulting in equal numbers of high-risk and normal-risk individuals between the sequences. Blinding (masking) In this study, subjects will be blinded as to study condition and randomization sequence. Relevant study staff and the device manufacturer will be aware of the assigned sequence. The subject will wear the Ava bracelet and complete the Daily Symptom Diary in the Ava COVID-RED app for the full duration of the study, and they will not know if the feedback they receive about their potential infection status will only be based on data they entered in the Daily Symptom Diary within the Ava COVID-RED app or based on both the data from the Daily Symptom Diary and the Ava bracelet. Numbers to be randomised (sample size) 20,000 subjects will be recruited and randomized 1:1 to either Sequence 1 (experimental condition followed by control condition) or Sequence 2 (control condition followed by experimental condition), taking into account their risk level. This results in approximately 6,500 normal-risk and 3,500 high-risk individuals per sequence. Trial Status Protocol version: 1.2, dated January 22nd, 2021 Start of recruitment: February 22nd, 2021 End of recruitment (estimated): April 2021 End of follow-up (estimated): December 2021 Trial registration The trial has been registered at the Netherlands Trial Register on the 18th of February, 2021 with number NL9320 (https://www.trialregister.nl/trial/9320) Full protocol The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Background In the absence of a vaccine or effective treatment for COVID-19, countries have adopted nonpharmaceutical interventions (NPIs) such as social distancing and full lockdown. An objective and quantitative means of passively monitoring the impact and response of these interventions at a local level is needed. Objective We aim to explore the utility of the recently developed open-source mobile health platform Remote Assessment of Disease and Relapse (RADAR)–base as a toolbox to rapidly test the effect and response to NPIs intended to limit the spread of COVID-19. Methods We analyzed data extracted from smartphone and wearable devices, and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the United Kingdom, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, the maximum number of Bluetooth-enabled nearby devices (as a proxy for physical distancing), step count, average heart rate, sleep duration, bedtime, phone unlock duration, and social app use duration. We performed Kruskal-Wallis tests followed by post hoc Dunn tests to assess differences in these features among baseline, prelockdown, and during lockdown periods. We also studied behavioral differences by age, gender, BMI, and educational background. Results We were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between prelockdown and during lockdown periods (P Conclusions RADAR-base, a freely deployable data collection platform leveraging data from wearables and mobile technologies, can be used to rapidly quantify and provide a holistic view of behavioral changes in response to public health interventions as a result of infectious outbreaks such as COVID-19. RADAR-base may be a viable approach to implementing an early warning system for passively assessing the local compliance to interventions in epidemics and pandemics, and could help countries ease out of lockdown.

Introduction:infants in the first six months of life are relatively protected from malaria. Emerging reports from endemic regions however are showing increasing malaria susceptibility in this age group. This study set out to determine the prevalence, parasite density and predictive factors for malaria parasitaemia in ill young infants at the Wesley Guild Hospital (WGH), Ilesa, Nigeria. Methods:ill infants aged one to six months were consecutively recruited over an 11-month period in a hospital based cross-sectional study. History of illness, sociodemographic and perinatal history were obtained; clinical examination and results of venous blood for thick and thin film malaria parasite examinations were recorded and analyzed. Results:the mean (SD) age of the 350 infants was 3.4 (1.6) months with male:female (M:F) of 1.2:1. The prevalence of malaria parasitaemia (all plasmodium falciparum) was 19.1% while parasite density ranged from 24.0 to 400,000 parasites/µl, median (IQR) 900 (250-4,588)/µl. Sixteen (4.6%) had heavy malaria parasitaemia (>5000/µl). Low social class (OR=2.457; 95%CI 1.404-4.300; p=0.002), suboptimal antenatal care (OR=2.226; 95%CI 1.096-4.522; p=0.027), low birth weight infants (OR=4.818; 95%CI 2.317-10.018; p=

Screening, Brief Intervention, and Referral to Treatment (SBIRT) is an evidence-based model for managing patients with substance use disorders (SUD). Historically, SUD were seen as a criminal issue and access to treatment was limited, but that paradigm is shifting and substance abuse is now being recognized as a disease state and the management of patients with SUD is increasingly within the healthcare system starting with primary healthcare settings including dental facilities. In a new training initiative, first-year dental students (DDS1) attended a 90-minute SBIRT training. An Attitudes and Opinion Survey (AOS) consisting of 8 questions that separately assesses DDS1 attitudes toward alcohol and drug use disorders was utilized to evaluate the training. Assenting DDS1 anonymously completed the AOS before and following the training. Over 3 years, we analyzed changes in the AOS of 230 DDS1 using Chi-squared test for bivariate comparison. We then applied a Bonferroni correction to the P-values. Response rate was 95.5%. The SBIRT training improved DDS1 attitudes and opinions toward patients with SUD with respect to all AOS questions. There was a statistically significant improvement (P < 0.003) in DDS1 attitudes and opinions with respect to whether other patients care suffers because of time and resources spent on patients with SUD and whether the SBIRT training provided adequate education to prepare DDS1 to manage patients with SUD. SBIRT training is relevant to dental education. It fills an important educational gap and is a suitable model for other dental schools.

Every retiree is expected to have confidence in government compensation after active service but unfortunately the situation has changed to the extent that senior citizens are now expected to determine alternative investment that can enrich the sustainability of potential retiree lecturers. Most studies on retirees were generally on workers but not potential retiree lecturers in Nigeria. The study was carried out to determine the impact of investment marketability on the retirement investment goals of steady income stream of potential retiree lecturers in Nigeria academia. The study adopted survey research design. The study used 5,805 lecturers from both public and private tertiary institutions that were Universities and Polytechnics. A sample of 487 was determined using Taro Yamane formula. Validated questionnaire was used in collecting primary data with Cronbach’s alpha reliability coefficients ranged from 0.70 to 0.75. The study recorded retrieval rate of 83.4%. The study adopted descriptive and inferential statistics for data analysis which was done using SPSS version 20. The study showed that investment marketability had significant effect on future sustainability of potential retiree lecturers because the result showed that there was a significant relationship between investment marketability and retirement investment goals (β1 = 0.278, R2 = 12.4%, p< 0.05).The study concluded that investment marketability lead to future sustainability of potential retiree lecturers and equally recommended that government should encourage every individual to plan means to invest in financial asset due to high rate of convertibility for employee, especially lecturers.

Background The development and spread of artemisinin-resistant Plasmodium falciparum malaria in Greater Mekong Subregion has created impetus for continuing global monitoring of efficacy of artemisinin-based combination therapies (ACTs). This post analyses is aimed to evaluate changes in early treatment response markers 10 years after the adoption of ACTs as first-line treatments of uncomplicated falciparum malaria in Nigeria. Methods At 14 sentinel sites in six geographical areas of Nigeria, we evaluated treatment responses in 1341 children under 5 years and in additional 360 children under 16 years with uncomplicated malaria enrolled in randomized trials of artemether-lumefantrine versus artesunate-amodiaquine at 5-year interval in 2009–2010 and 2014–2015 and at 2-year interval in 2009–2010 and 2012–2015, respectively after deployment in 2005. Results Asexual parasite positivity 1 day after treatment initiation (APPD1) rose from 54 to 62% and 2 days after treatment initiation from 5 to 26% in 2009–2010 to 2014–2015 (P = 0.002 and P 75 000 μl− 1, haematocrit > 27% 1 day post-treatment initiation, treatment with artemether-lumefantrine and enrolment in 2014–2015 independently predicted APPD1. In parallel, Kaplan-Meier estimated risk of recurrent infections by day 28 rose from 8 to 14% (P = 0.005) and from 9 to 15% (P = 0.02) with artemether-lumefantrine and artesunate-amodiaquine, respectively. Mean asexual parasitaemia half-life increased significantly from 1.1 h to 1.3 h within 2 years (P

BACKGROUND Geriatric Trauma Outcomes Score (GTOS) predicts in-patient mortality in geriatric trauma patients and has been validated in a prospective multicenter trial and expanded to predict adverse discharge (GTOS II). We hypothesized that these formulations actually underestimate the downstream sequelae of injury and sought to predict longer-term mortality in geriatric trauma patients. METHODS The Parkland Memorial Hospital Trauma registry was queried for patients 65 years or older from 2001 to 2013. Patients were then matched to the Social Security Death Index. The primary outcome was 1-year mortality. The original GTOS formula (variables of age, Injury Severity Score [ISS], 24-hour transfusion) was tested to predict 1-year mortality using receiver operator curves. Significant variables on univariate analysis were used to build an optimal multivariate model to predict 1-year mortality (GTOS III). RESULTS There were 3,262 patients who met inclusion. Inpatient mortality was 10.0% (324) and increased each year: 15.8%, 1 year; 17.8%, 2 years; and 22.6%, 5 years. The original GTOS equation had an area under the curve of 0.742 for 1-year mortality. Univariate analysis showed that patients with 1-year mortality had on average increased age (75.7 years vs. 79.5 years), ISS (11.1 vs. 19.1), lower GCS score (14.3 vs. 10.5), more likely to require transfusion within 24 hours (11.5% vs. 31.3%), and adverse discharge (19.5% vs. 78.2%; p < 0.0001 for all). Multivariate logistic regression was used to create the optimal equation to predict 1-year mortality: (GTOSIII = age + [0.806 × ISS] + 5.55 [if transfusion in first 24 hours] + 21.69 [if low GCS] + 34.36 [if adverse discharge]); area under the curve of 0.878. CONCLUSION Traumatic injury in geriatric patients is associated with high mortality rates at 1 year to 5 years. GTOS III has robust test characteristics to predict death at 1 year and can be used to guide patient centered goals discussions with objective data. LEVEL OF EVIDENCE Prognostic, level III.

Rapid industrialisation through sector-led industrial policies, prohibitive tariffs and aggressive subsidies has become commonplace in many African countries. In Africa’s largest economy, Nigeria, one of the flagship industries cited as a success story of successful industrialisation is the cement industry. However, the Nigerian cement industry manifests certain industry peculiarities such as oligopoly and bulky mass, that is not easily replicable across sectors. The aim of this paper is to isolate the key market characteristics and industry incentives granted to the cement sector so as to identify the most important determinants of the recorded phenomenal growth. Based on previous studies, four industry variables: concentration ratio, capital intensity, installed capacity and demand-supply gap were identified. In addition, four other macroeconomic variables that impacted production costs: financing costs, tax rate, real exchange rate and effective rate of protection; were also tested in the model. Data was obtained for the cement industry from 1980 to 2015 for the cointegration model. The results indicate that tariff protection was the most significant determinant of the growth in cement production. Subsidies, in form of tax holidays and cheaper financing, were only minimally important. The findings of this study underscore the huge cost of supporting the growth of industrialisation in African countries through various instruments.

The use of the improved cancer treatment model predicted the population changes in the normal and cancer cells during radiotherapy. The simulated radiation doses are 15 Gy, 18 Gy, 20 Gy and 24 Gy administered 5 times for each dose. The population of the cancer cells reduced from 40 % of the carrying capacity to 10.72%, 23.25 %, 1.61 % and 3.72 % of the carrying capacity for the respective doses. The population of the normal cells reduced from 70% of the carrying capacity to 65.50%, 62.48%, 68.49% and 67.59% of the carrying capacity for the respective doses. During the no treatment stage (0 Gy), the model predicted an increase in the population of cancer cells and a decrease in the population of normal cells.

Africa has the largest number and proportion of fragile states in the world. Fragile states are characterized by slower economic growth, higher incidences of poverty, and persistent inequality. Thus, there is a circular relationship between fragility, inequality, and slow economic growth. This study examines the relationship between fragility, financial inequalities, and inclusive growth in African countries. We introduce a novel way of examining inclusive growth in African countries by developing a unified measure of inclusive growth that captures the two dimensions of inclusive growth: income growth and income distribution. This enables us to adequately assess not just increased opportunities arising from economic growth, but also see how those new opportunities are distributed across all segments of the population. We captured the fragile status of African countries by using an index of fragility. We measured financial inequalities using new data on financial inclusion. The data analysis suggested negative relationships between fragility and inclusive growth in African countries. In addition, the results suggest positive relationships between financial inclusion and inclusive growth. Thus, inclusive growth can be fostered through policies that reduce financial inequalities. Therefore, a less fragile environment is conducive to inclusive growth both directly and indirectly through financial inclusion.

Nigeria adopted the Structural Adjustment Programme (SAP) in 1986 after the crash in world oil price in the early 1980s. Financial reforms are part of the reforms implemented during the SAP. Since industrialisation is seen as an engine of growth, we conduct an empirical assessment of the effects of financial sector reforms on industrialisation in Nigeria using an annual time series data over 1981–2015. Using an autoregressive distributed lag model, our findings show that financial reforms have a positive and significant impact on industrialisation.

Background:Personal protective equipment (PPE) supply shortages were a big issue in the fight against COVID-19 around the world at the onset of the pandemic, requiring all communities to find innovative ways to make and supply PPE for health workers, vulnerable people and the general public. To this end and in line with the WHO’s call for 40% raise in PPE production across the world, we sought to alleviate the PPE shortage and to support our local communities using 3D printing (additive manufacturing) and free and open-source hardware (FOSH). Methods:Utilising a 3D printer and off-the-shelf components, reusable face shields and face masks were produced based on open source designs. Off-the-shelf components included transparent polyvinyl chloride (PVC) visor, ribbon tapings and elastic bands for the face shields, as well as cushioning pads (clothed foams) and filters (sensitive tissues) for the face masks. Hygienic measures employed during fabrication included the assembly following safety protocols, disinfection of products with ultraviolet bactericidal lamps, ensuring hygiene during collection and distribution. Users’ real-life experience and feedback were utilised to modify and improve on quality and adaptability of the designs.Results:In a period of three months, over 400 reusable 3D-printed face shields and face masks were produced by a team of academics, for health practitioners, other professionals and people across the Olabisi Onabanjo University community and other cities within Ogun and Lagos states. Conclusions:More awareness is generally required on the potentials of 3D printing and FOSH in the global south, particularly in universities and research institutions where innovative alternatives to expensive equipment remain vital. Our feat corroborated and advocated these potentials in a low-income setting like Nigeria, where the immediate response and synergy between academics, and researchers yielded a substantial number of PPE to front line workers, in a timely manner at the peak of the viral transmission and lockdowns- a period wherein manufacturers of PPEs struggled to establish their commercial logistics. We emphasize the need for university managements to support academics and researchers strongly to deliver on much needed community support in crises time, and encourage governmental and non-governmental bodies to consider investing in this innovative self-reliant perspective through their research funding and managemnt programmes in a bid to achieving a lot more with the less funds.Trial registration:Not applicable.

Background Lagos state is the industrial nerve centre of Nigeria and was the epicentre of the 2014 Ebola outbreak in Nigeria as it is now for the current Coronavirus Disease (COVID-19) outbreak. This paper describes how the lessons learned from the Ebola outbreak in 2014 informed the emergency preparedness of the State ahead of the COVID-19 outbreak and guided response. Discussion Following the Ebola outbreak in 2014, the Lagos State government provided governance by developing a policy on emergency preparedness and biosecurity and provided oversight and coordination of emergency preparedness strategies. Capacities for emergency response were strengthened by training key staff, developing a robust surveillance system, and setting up a Biosafety Level 3 laboratory and biobank. Resource provision, in terms of finances and trained personnel for emergencies was prioritized by the government. With the onset of COVID-19, Lagos state was able to respond promptly to the outbreak using the centralized Incident Command Structure and the key activities of the Emergency Operations Centre. Contributory to effective response were partnerships with the private sectors, community engagement and political commitment. Conclusion Using the lessons learned from the 2014 Ebola outbreak, Lagos State had gradually prepared its healthcare system for a pandemic such as COVID-19. The State needs to continue to expand its preparedness to be more resilient and future proof to respond to disease outbreaks. Looking beyond intra-state gains, lessons and identified best practices from the past and present should be shared with other states and countries.

Background Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data. Methods Remote Assessment of Disease and Relapse – Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse – Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months. Results Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had > 50% data available across all data types. Conclusions RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group.

Oil and gas operations in sedimentary basins have revealed the occurrence of significant temperature anomalies at depth, raising the possibility of major geothermal resource potential in the sedimentary sequences. The efficient development of such a resource may require enhancement by hydraulic stimulation. However, effective stimulation relies on an initial assessment of in situ mechanical properties and a model of the rock response. Here, we examine the distribution of mechanical properties (unconfined compressive strength, UCS; ultrasonic velocity-derived Poisson ratio, ν; and, scratch toughness, Ks) along the cored interval of a sedimentary formation with a known low-to-medium temperature geothermal anomaly in the Permian Basin, U.S. Our results reveal the presence of mechanical stratigraphy along the core, demonstrated by the alternation of distinct soft–hard (i.e.,less stiff-to-stiff) mechanical zone couplets composed of: (1) mechanically softer 0.17-m-thick Zone-A and 0.18-m-thick Zone-C with mean values of UCS = 110 MPa, ν = 0.25, Ks = 1.89 MPa·√m; and (2) mechanically harder 0.41-m-thick Zone-B and 0.15-m-thick Zone-D which show mean values of UCS = 166 MPa, ν = 0.22, and Ks = 2.87 MPa·√m. Although X-ray diffraction analyses of the samples suggest that the entire rock matrix is dominated by dolomite, the harder zones show an abundance of quartz cement (> 30%) and relatively lower phyllosilicate mineral content (

Background Sleep problems tend to vary according to the course of the disorder in individuals with mental health problems. Research in mental health has associated sleep pathologies with depression. However, the gold standard for sleep assessment, polysomnography (PSG), is not suitable for long-term, continuous monitoring of daily sleep, and methods such as sleep diaries rely on subjective recall, which is qualitative and inaccurate. Wearable devices, on the other hand, provide a low-cost and convenient means to monitor sleep in home settings. Objective The main aim of this study was to devise and extract sleep features from data collected using a wearable device and analyze their associations with depressive symptom severity and sleep quality as measured by the self-assessed Patient Health Questionnaire 8-item (PHQ-8). Methods Daily sleep data were collected passively by Fitbit wristband devices, and depressive symptom severity was self-reported every 2 weeks by the PHQ-8. The data used in this paper included 2812 PHQ-8 records from 368 participants recruited from 3 study sites in the Netherlands, Spain, and the United Kingdom. We extracted 18 sleep features from Fitbit data that describe participant sleep in the following 5 aspects: sleep architecture, sleep stability, sleep quality, insomnia, and hypersomnia. Linear mixed regression models were used to explore associations between sleep features and depressive symptom severity. The z score was used to evaluate the significance of the coefficient of each feature. Results We tested our models on the entire dataset and separately on the data of 3 different study sites. We identified 14 sleep features that were significantly (P Conclusions We demonstrated that several derived sleep features extracted from consumer wearable devices show potential for the remote measurement of sleep as biomarkers of depression in real-world settings. These findings may provide the basis for the development of clinical tools to passively monitor disease state and trajectory, with minimal burden on the participant.

In most organizations, the strategic planning process is an annual exercise at best. It ensures that leaders pause at some point to take stock in their organizations, look out over the horizon, assess the external environment and establish their team’s priorities and goals. It’s a valuable process. However, it doesn’t typically happen frequently or fast enough to address the challenges and complexities of the present-day corporate world. That’s why leaders with strategic thinking skills have the edge in navigating organizational change. This article addresses the current scenario and realities of organizations and proffered some recommendations.

Rapid assessments of the impacts of the COVID-19 crisis on the seed sector were conducted by a coalition of partners in Ethiopia, Myanmar, Nigeria, and Uganda in May and June 2020. The method was rapid, iterative, inclusive and valuable in revealing threats to the availability and timely access of farmers to quality seed and to food, nutrition and income security, and in advocating for remedial and preventative action. Via mobile application and web survey, and focus group discussions on virtual conferencing platforms a panel of 36 or more local experts operating particularly in formal seed systems in each country identified potential disruptions to activities in the seed sector and recommended immediate practical action to ensure continuity in performance. Recommendations, and the stakeholders best positioned to propel their action, were proposed to and approved by senior leadership in the sector. The entire process from survey to publication of a seed alert in each iteration was completed within two weeks. Due to the highly seasonal nature of agriculture, and recognition that activities are time-bound, quick turnaround on assessments was essential. Dashboards indicated where impact was felt the hardest, also showing how dynamic the situation was. Countries were at different stages in their agricultural seasons, which made the data highly contextual, but also interesting for getting a glimpse into the future. Lessons were offered from one country to another. Reduced mobility was the root cause of many disruptions in supplying seed to farmers. Disruptions caused seed and related industry to operate at reduced capacity. The cost of transactions and doing business during these times may have increased the scarcity and price of inputs beyond what farmers can recover. Sales of quality seed in formal markets were perceived to decline due to delays in distribution, weakened promotion efforts and fewer farmers present. Farmers are less likely to benefit from investments in crop improvement for more seasons to come due to delays in the development and release of new varieties. Social distancing prevents stakeholders from meeting to exchange goods, services and information, but the sector is gradually getting up to speed with information technology. For all concerns, practical options were offered and often implemented. The pandemic has exacerbated structural weaknesses in the organization of the seed sector, for which reforms are not only justified, but overdue.

PTD photoresists are still the main type of photoresists used for tight pitch layers in advanced patterning. Recent experimental results show evidence that the same mechanical deformation behaviors seen in NTD photoresist process also exist in PTD photoresist processes. These PTD photoresist deformation behaviors cause CD differences which significantly impact CD control budgets in modern technology nodes. Therefore, there is a strong need to accurately model PTD photoresist deformation effects in compact OPC models. In this paper we discuss the polymer physics relevant to physical deformation in PTD photoresists in comparison to NTD photoresists

Most smartphones and wearables are nowadays equipped with location sensing (using Global Positioning System and mobile network information) that enable continuous location tracking of their users. Several studies have reported that the amount of time an individual experiencing symptoms of Major Depressive Disorder (MDD) spends at home a day (i.e., home stay), as well as various mobility related metrics, are associated with symptom severity in MDD. Due to the use of small and homogeneous cohorts of participants, it is uncertain whether the findings reported in those studies generalize to a broader population of individuals with the MDD symptoms. In the present study, we examined the relationship between overall severity of the depressive symptoms, as assessed by the eight-item Patient Health Questionnaire (PHQ-8), and median daily home stay over the two weeks preceding the completion of a questionnaire in individuals with MDD. We used questionnaire and geolocation data of 164 participants collected in the observational Remote Assessment of Disease and Relapse – Major Depressive Disorder (RADAR-MDD) study. Participant age and severity of the MDD symptoms were found to be significantly related to home stay, with older and more severely affected individuals spending more time at home. The association between home stay and symptom severity appeared to be stronger on weekdays than on weekends. Furthermore, we found a significant modulation of home stay by occupational status, with employment reducing home stay. Our findings suggest that home stay is associated with symptom severity in MDD and demonstrate the importance of accounting for confounding factors in future MDD studies.

A fundamental fact of private equity (PE) is that it has a definite time horizon, usually 5 to 10 years, within which the investment is expected to reach its maturity and return profits to the investors. The key ambitions are exit and profit. So, PE investors aim to avoid locking themselves into investment decisions from which they cannot conveniently disencumber themselves if their personal or business circumstances change or their investment objectives have been realized. Conversely, founders and other shareholders are also wary of PE exits that could negatively affect the quality of their investment and shareholding in a company and so seek to protect their interests as far as practicable. This brings to the fore the need to pay attention to provisions relating to exit in the composite package of documents forming a private equity investment. In this context, therefore, this article explores preemption rights, drag-along rights and tag-along rights, being some of the key provisions in private equity investments that may impact the exit strategies of PE investors in Nigeria and the interests of their co-shareholders, bearing in mind the relevant provisions of the Companies and Allied Matters Act 2020.

Internet users have been faced with a lot of threats with the growth of malware around the world. Ransomware, one of the significant types of malware, encrypts sensitive information and will not release the files until the user paid a ransom. Internet of Things (IoT) structure is an extensive area of Internet-associated instruments with additional computational capabilities with storage capacities that have the potential to be harmed by ransomware developers. The IoT has been speedily becoming more intense over the earlier years, and meanwhile, in these phases, one of the weakest areas is security. Security affairs had continued to be a crucial worry for businesses, despite the efficiency and prevalence of IoT growth. Therefore, the paper presents a machine learning model to detect ransomware attacks on IoT devices. The study used Power—to track and review the power consumption in 500 ms internals of all operating processes. The paper used three devices to perform the experiments, namely: Android device, Laptop computer, and Projector. The model was used to the monitoring power consumption of IoT devices using various procedures to categorize Ransomware outside non-malicious operations. Comparing the proposed system with the existing model outperforms concerning correctness ratio, precision ratio, recall ratio, and F-measure were considered.

The ease of in-the-wild speech recording using smartphones has sparked considerable interest in the combined application of speech, remote measurement technology (RMT) and advanced analytics as a research and healthcare tool. For this to be realised, the acceptability of remote speech collection to the user must be established, in addition to feasibility from an analytical perspective. To understand the acceptance, facilitators, and barriers of smartphone-based speech recording, we invited 384 individuals with major depressive disorder (MDD) from the Remote Assessment of Disease and Relapse - Central Nervous System (RADAR-CNS) research programme in Spain and the UK to complete a survey on their experiences recording their speech. In this analysis, we demonstrate that study participants were more comfortable completing a scripted speech task than a free speech task. For both speech tasks, we found depression severity and country to be significant predictors of comfort. Not seeing smartphone notifications of the scheduled speech tasks, low mood and forgetfulness were the most commonly reported obstacles to providing speech recordings., Comment: Accepted to Interspeech 2021. Formatting changes + minor language edits

Background: In April 2020, a community-based active case search surveillance system of coronavirus disease 2019 (COVID-19) was developed by the emergency outbreak committee in Lagos State. This followed the evidence of community transmission of coronavirus disease in the twenty Local Government Areas in Lagos State. This study assessed the value of respiratory and other symptoms in predicting positive SARS-CoV-2 using reverse transcription-polymerase chain reaction (RT-PCR). It is hoped that if symptoms are predictive, they can be used in screening before testing. Methods: Communities were included based on the alerts from community members through the rumour alert system set up by the state. All members of the households of the communities from where the alert came were eligible. Household members who declined to participate were excluded from the study. A standardised interviewer-administered electronic investigation form was used to collect sociodemographic information, clinical details and history for each possible case. Data was analysed to see the extent of agreement or correlation between reported symptoms and the results of PCR testing for SARS-COV-2. Results: A total of 12,739 persons were interviewed. The most common symptoms were fever, general weakness, cough and difficulty in breathing. Different symptoms recorded different levels of sensitivity as follows: fever, 28.9%; cough, 21.7%; general body weakness, 10.9%; and sore throat, 10.9%. Sensitivity and specificity for fever, the most common symptom, were 28.3% and 50.2%, respectively, while similar parameters for general body weakness, the next most common symptom, were 10.9% and 73.2%, respectively. Conclusion: From these findings, the predictive ability of symptoms for COVID-19 diagnosis was extremely weak. It is unlikely that symptoms alone will suffice to predict COVID-19 in a patient. An additional measure, such as confirmatory test by RT-PCR testing, is necessary to confirm the disease.

This chapter studies the illegal import, export, and transfer of ownership of movable cultural objects. Illicit trafficking in cultural property has been going on for decades. The exponential increase in the 1960s raised concern, and this coincided with the wave of independence being granted to several African countries and Asian countries. Codes of ethics and international treaties are two important elements of the current, major international effort to prevent the damage caused by the illegal trade in cultural objects that continue to blossom. Another key element is increased globalization of cultural heritage law. Finally, the creation of national cultural heritage police units by all countries is very important.

The National Health Insurance Scheme (NHIS) is designed to provide a cost- effective comprehensive health care delivery system for employees of formal sectors, self-employed, poor and vulnerable groups. Oyo state government approved the establishment of her health insurance scheme and there after sent an executive bill to the legislature for a swift consideration and approval. This study assessed the knowledge and perceived benefit of NHIS among civil servants in Oyo state, Nigeria. The study was a cross-sectional study conducted amongst 200 state civil servants. Participants were selected using convenient sampling technique and data was obtained using a structured questionnaire. Data was analyzed with SPSS v.25 to obtain frequencies, means and standard deviation. Respondents had good knowledge with a mean of 16.4±1.0 on an 18- point scale about NHIS while respondents had fair perceived benefit of the NHIS with a mean of 18.3±3.1 on a 35-point rating scale. Results denote knowledgeable end users who perceive to be benefiting from the scheme. The State Government is encouraged to expand the NHIS to other sectors to enable fuller coverage. More emphasis should be made on the benefits of enrollment to prompt high level willingness to enroll.

The implementation of governmental Non-Pharmaceutical Interventions (NPIs) has been the primary means of controlling the spread of the COVID-19 disease. The intended effect of these NPIs has been to reduce mobility. A strong reduction in mobility is believed to have a positive effect on the reduction of COVID-19 transmission by limiting the opportunity for the virus to spread in the population. Due to the huge costs of implementing these NPIs, it is essential to have a good understanding of their efficacy. Using global mobility data, released by Apple and Google, and ACAPS NPI data, we investigate the proportional contribution of NPIs on i) size of the change (magnitude) of transition between pre- and post-lockdown mobility levels and ii) rate (gradient) of this transition. Using generalized linear models to find the best fit model we found similar results using Apple or Google data. NPIs found to impact the magnitude of the change in mobility were: Lockdown measures (Apple, Google Retail and Recreation (RAR) and Google Transit and Stations (TS)), declaring a state of emergency (Apple, Google RAR and Google TS), closure of businesses and public services (Google RAR) and school closures (Apple). Using cluster analysis and chi square tests we found that closure of businesses and public services, school closures and limiting public gatherings as well as border closures and international flight suspensions were closely related. The implementation of lockdown measures and limiting public gatherings had the greatest effect on the rate of mobility change. In conclusion, we were able to quantitatively assess the efficacy of NPIs in reducing mobility, which enables us to understand their fine grained effects in a timely manner and therefore facilitate well-informed and cost-effective interventions., 16 pages, 6 figures

Summary box Over the past decades, health systems have experienced major transformation. The role of ministries of health has changed, progressively shifting from direct provision of health services to overall stewardship of the health sector, including financing and oversight of private providers.1 Health reforms have triggered that shift, fostering new institutions, such as national medicines agencies, public health agencies, disease control agencies (eg, National Cancer Agencies) or health financing organisations responsible for risk and fund pooling, purchasing of health services, or targeting the poor or vulnerable groups. Shocks such as political or financial crises, natural disasters or epidemics have also affected the governing of the health system …

AIMS: The SARS-CoV-2 virus binds to the angiotensin-converting enzyme 2 (ACE2) receptor for cell entry. It has been suggested that angiotensin-converting enzyme inhibitors (ACEi) and angiotensin II receptor blockers (ARB), which are commonly used in patients with hypertension or diabetes and may raise tissue ACE2 levels, could increase the risk of severe COVID-19 infection. METHODS AND RESULTS: We evaluated this hypothesis in a consecutive cohort of 1200 acute inpatients with COVID-19 at two hospitals with a multi-ethnic catchment population in London (UK). The mean age was 68 ± 17 years (57% male) and 74% of patients had at least one comorbidity. Overall, 415 patients (34.6%) reached the primary endpoint of death or transfer to a critical care unit for organ support within 21 days of symptom onset. A total of 399 patients (33.3%) were taking ACEi or ARB. Patients on ACEi/ARB were significantly older and had more comorbidities. The odds ratio for the primary endpoint in patients on ACEi and ARB, after adjustment for age, sex and co-morbidities, was 0.63 (95% confidence interval 0.47-0.84, P < 0.01). CONCLUSIONS: There was no evidence for increased severity of COVID-19 in hospitalised patients on chronic treatment with ACEi or ARB. A trend towards a beneficial effect of ACEi/ARB requires further evaluation in larger meta-analyses and randomised clinical trials.

Introduction Success in curtailing the pandemic coronavirus disease (COVID-19) depends largely on a sound understanding of the epidemiologic and clinical profile of cases in a population as well as the case management approach. This study documents the presenting characteristics, treatment modalities and outcomes of the first 32 COVID-19 patients in Nigeria. Methods This retrospective study used medical records of the first 32 patients admitted and discharged from the Mainland Hospital, Lagos State, southwest Nigeria between February 27 and April 6, 2020. The outcomes of interest were death, promptness of admission process and duration of hospitalization. Results The mean age of the patients was 38.1 years (SD: 15.5) and 66% were male. Three-quarters (75%) of the patients presented in moderately severe condition while 16% were asymptomatic. The most common presenting symptoms were fever (59%) and dry cough (44%). The mean time between a positive test result and admission was 1.63 days (SD: 1.31). Almost all (97%) the patients were treated with lopinavir-ritonavir with no recorded death. The median duration of hospital stay was 12 days (IQR: 9-13.5). Conclusion In this preliminary analysis of the first COVID-19 cases in Nigeria, clinical presentation was mild to moderate with no mortality. Processes to improve promptness of admission and reduce hospital stay are required to enhance the response to COVID-19 in Nigeria.

Recent studies have shown that an automated, lifespan-inclusive, transdiagnostic, and clinically based, individualized risk calculator provides a powerful system for supporting the early detection of individuals at-risk of psychosis at a large scale, by leveraging electronic health records (EHRs). This risk calculator has been externally validated twice and is undergoing feasibility testing for clinical implementation. Integration of this risk calculator in clinical routine should be facilitated by prospective feasibility studies, which are required to address pragmatic challenges, such as missing data, and the usability of this risk calculator in a real-world and routine clinical setting. Here, we present an approach for a prospective implementation of a real-time psychosis risk detection and alerting service in a real-world EHR system. This method leverages the CogStack platform, which is an open-source, lightweight, and distributed information retrieval and text extraction system. The CogStack platform incorporates a set of services that allow for full-text search of clinical data, lifespan-inclusive, real-time calculation of psychosis risk, early risk-alerting to clinicians, and the visual monitoring of patients over time. Our method includes: 1) ingestion and synchronization of data from multiple sources into the CogStack platform, 2) implementation of a risk calculator, whose algorithm was previously developed and validated, for timely computation of a patient's risk of psychosis, 3) creation of interactive visualizations and dashboards to monitor patients' health status over time, and 4) building automated alerting systems to ensure that clinicians are notified of patients at-risk, so that appropriate actions can be pursued. This is the first ever study that has developed and implemented a similar detection and alerting system in clinical routine for early detection of psychosis.

Automated kinetic profiling is a valuable tool for providing insights into key mechanistic features of complex catalytic systems. In an attempt to optimize a palladium-catalyzed Suzuki cross-coupling reaction, automated kinetic profiling was utilized with offline liquid chromatography to monitor reaction progress. Upon uncovering analytical sample instability issues, an online HPLC capability was developed and implemented through integration of a Chemspeed liquid handling robot with an Agilent HPLC to facilitate automated reaction set-up and monitoring. Application of this capability resulted in the observation that precatalyst activation was a key factor influencing the reaction rate. Leveraging this mechanistic insight, a more efficient method to access the active catalyst was developed. This change resulted in a five-fold increase in the reaction rate.

BackgroundThe National Early Warning Score (NEWS2) is currently recommended in the United Kingdom for risk stratification of COVID outcomes, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for severe COVID outcome and identify and validate a set of routinely-collected blood and physiological parameters taken at hospital admission to improve the score.MethodsTraining cohorts comprised 1276 patients admitted to King’s College Hospital NHS Foundation Trust with COVID-19 disease from 1st March to 30th April 2020. External validation cohorts included 5037 patients from four UK NHS Trusts (Guys and St Thomas’ Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID disease (transfer to intensive care unit or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models.ResultsA baseline model of ‘NEWS2 + age’ had poor-to-moderate discrimination for severe COVID infection at 14 days (AUC in training sample = 0.700; 95% CI: 0.680, 0.722; Brier score = 0.192; 95% CI: 0.186, 0.197). A supplemented model adding eight routinely-collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI: 0.715, 0.757) and these improvements were replicated across five UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites.ConclusionsNEWS2 score had poor-to-moderate discrimination for medium-term COVID outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.Key messagesThe National Early Warning Score (NEWS2), currently recommended for stratification of severe COVID-19 disease in the UK, showed poor-to-moderate discrimination for medium-term outcomes (14-day transfer to ICU or death) among COVID-19 patients.Risk stratification was improved by the addition of routinely-measured blood and physiological parameters routinely at hospital admission (supplemental oxygen, urea, oxygen saturation, CRP, estimated GFR, neutrophil count, neutrophil/lymphocyte ratio) which provided moderate improvements in a risk stratification model for 14-day ICU/death.This improvement over NEWS2 alone was maintained across multiple hospital trusts but the model tended to be miscalibrated with risks of severe outcomes underestimated in most sites.We benefited from existing pipelines for informatics at KCH such as CogStack that allowed rapid extraction and processing of electronic health records. This methodological approach provided rapid insights and allowed us to overcome the complications associated with slow data centralisation approaches.