Miracle-dz/UniFAR-FTUs huggingface dataset:
Cyclical Patterns and a Regime Shift in the Character of Phytoplankton Blooms in a Restricted Sub-Tropical Lagoon, Indian River Lagoon, Florida, United States

This paper examines the character of phytoplankton blooms in a restricted sub-tropical lagoon along the Atlantic coast of central Florida. The results of the 23-year study (1997–2020) provide evidence for multiple types of variability in bloom activity, including cyclical patterns, stochastic events, and most prominently a regime shift in composition and intensity. Cyclical patterns (e.g., El Niño/La Niña periods) and stochastic events (e.g., tropical storms) influenced rainfall levels, which in turn impacted nutrient concentrations in the water column and the timing and intensity of blooms. In 2011, a major change occurred in the character of blooms, with a dramatic increase in peak biomass levels of blooms and the appearance of new dominant taxa, including the brown tide species Aureoumbra lagunensis and other nanoplanktonic species. Results of quantitative analyses reveal system behavior indicative of a regime shift. The shift coincided with widespread losses of seagrass community and reduced drift algae biomass. A combination of exceptionally low water temperatures in the winters of 2009/2010 and 2010/2011, hypersaline conditions associated with drought conditions, and high light attenuation caused by blooms appear to have contributed to the widespread and protracted decline in seagrass and drift macroalgal communities in the lagoon, leading to shifts in distribution of internal and external nutrient sources toward phytoplankton.
Modified Protocol to Enable the Study of Hemorrhage and Hematoma in a Traumatic Brain Injury Mouse Model

To date, many studies using the controlled cortical impact (CCI) mouse model of traumatic brain injury (TBI) have presented results without presenting the pathophysiology of the injury-core itself or the temporal features of hemorrhage (Hrr). This might be owing to the removal of the injury-core during the histological procedure. We therefore developed a modified protocol to preserve the injury-core. The heads of mice were obtained after perfusion and were post-fixed. The brains were then harvested, retaining the ipsilateral skull bone; these were post-fixed again and sliced using a cryocut. To validate the utility of the procedure, the temporal pattern of Hrr depending on the impacting depth was analyzed. CCI-TBI was induced at the following depths: 1.5 mm (mild Hrr), 2.5 mm (moderate Hrr), and 3.5 mm (severe Hrr). A pharmacological study was also conducted using hemodynamic agents such as warfarin (2 mg/kg) and coagulation factor VIIa (Coa-VIIa, 1 mg/kg). The current protocol enabled the visual observation of the Hrr until 7 days. Hrr peaked at 1–3 days and then decreased to the normal range on the seventh day. It expanded from the affected cortex (mild) to the periphery of the hippocampus (moderate) and the brain ventricle (severe). Pharmacological studies showed that warfarin pre-treatment produced a massively increased Hrr, concurrent with the highest mortality rate and brain injury. Coa-VIIa reduced the side effects of warfarin. Therefore, these results suggest that the current method might be suitable to conduct studies on hemorrhage, hematoma, and the injury-core in experiments using the CCI-TBI mouse model.
Coexistence for Whom?

This perspective essay considers ethical and conceptual questions around who coexistence is for, who it affects, and who is to make it happen. The introduction considers some approaches to thinking about human-wildlife coexistence, debates on the utility of the concept and reasons for its current emergence into the mainstream. It next outlines the preliminary conception of coexistence informing this essay. The discussion considers challenges for a narrow conservation-oriented framing of human-wildlife coexistence, and offers insights from the literatures on stewardship and relational values for tackling these.
Protocol for an observational cohort study investigating personalised medicine for intensification of treatment in people with type 2 diabetes mellitus: the PERMIT study

Introduction For people with type 2 diabetes mellitus (T2DM) who require an antidiabetic drug as an add-on to metformin, there is controversy about whether newer drug classes such as dipeptidyl peptidase-4 inhibitors (DPP4i) or sodium-glucose co-transporter-2 inhibitors (SGLT2i) reduce the risk of long-term complications compared with sulfonylureas (SU). There is widespread variation across National Health Service Clinical Commissioning Groups (CCGs) in drug choice for second-line treatment in part because National Institute for Health and Care Excellence guidelines do not specify a single preferred drug class, either overall or within specific patient subgroups. This study will evaluate the relative effectiveness of the three most common second-line treatments in the UK (SU, DPP4i and SGLT2i as add-ons to metformin) and help target treatments according to individual risk profiles. Methods and analysis The study includes people with T2DM prescribed one of the second-line treatments-of-interest between 2014 and 2020 within the UK Clinical Practice Research Datalink linked with Hospital Episode Statistics and Office of National Statistics. We will use an instrumental variable (IV) method to estimate short-term and long-term relative effectiveness of second-line treatments according to individuals’ risk profiles. This method minimises bias from unmeasured confounders by exploiting the natural variation in second-line prescribing across CCGs as an IV for the choice of prescribed treatment. The primary outcome to assess short-term effectiveness will be change in haemoglobin A1c (%) 12 months after treatment initiation. Outcome measures to assess longer-term effectiveness (maximum ~6 years) will include microvascular and macrovascular complications, all-cause mortality and hospital admissions during follow-up. Ethics and dissemination This study was approved by the Independent Scientific Advisory Committee (20-064) and the London School of Hygiene & Tropical Medicine Research Ethics Committee (21395). Results, codelists and other analysis code will be made available to patients, clinicians, policy-makers and researchers.
Case Based Diagnosis in Histopathology of Breast Tumours

Relevant knowledge and decision making process in histopathology is mostly included in typical pathological cases encountered by the expert. In this article we address the issue of exploiting this knowledge in the diagnosis process. We present the first steps of a Case-Based-Reasoning (CBR) system that uses the previously resolved pathological cases in order to facilitate decision making and diagnosis formulation of a new case. The work has been performed in two phases. Firstly, an object-oriented model of the domain was developed and 35 pathological cases of breast tumours were represented within this model. Secondly, the functional architecture of the CBR system was designed and the main procedure, the selection of similar cases, was achieved. The selection procedure is based on an original similarity measure that takes into account both semantic and structural resemblances and differences between the cases. A first evaluation of the system was performed on several cases of the data base. The interest of the CBR approach in situations where heuristic rules cannot be clearly defined is discussed.
A Time Series Model to Forecast Covid-19 Infection rate in Nigeria Using Box-Jenkins Method

Coronavirus declared as a global pandemic by WHO has emerged as the most aggressive disease negatively affecting more than 90% countries of the world. Nigeria, one of the most populated countries in Africa is not an exception. This study focuses on analyzing the intrinsic patterns in the COVID-19 spread in Nigeria using the Box-Jenkins procedure. Data of daily confirmed cases of COVID-19 in Nigeria was retrieved from Nigeria Centre for Disease Control (NCDC) official website from February 27, 2020 to October 31, 2020 to identify the series components, estimate parameters, develop an appropriate stochastic predictive model and use the model to forecast future trend of the deadly virus. The Autoregressive Integrated Moving Average (ARIMA) of order (0,1,1) was identified as the most suitable model based on the analysis of the autocorrelation (ACF), partial autocorrelation functions (PACF) and Akaike Information Correction (AICc) value. R software version 4.0. 3 was used to analyze the trend which moothen the series by using 8-point moving average to extract the irregular component as wellas differencing the series one step further to obtain a stationary series. We performed the Augmented Dickey-Fuller Unit root test, parameter estimation and Ljung-Box test to check the proposed model’s conformity to the stationary univariate process. A 85 – day (1st Oct., 2020 – 24th Jan., 2020)forecast shows a gradual decline in the successive number of confirmed cases of infection indicating the effectiveness of the intervention strategies employed by the Task Force to contain the virus. The concerned authorities can apply the forecasted trend to make further informed decisions on the measures to be put in place to reduce diffusion of the deadly virus into the country.
Improving Business Pages Recommendation in Social Network Using Link Prediction Methods

Recently Social Network has become one of the favorite means for a modern society to perform social interaction and exchange information via the internet. Link prediction is a common problem that has broad application in such social networks, ranging from predicting unobserved interaction to recommending related items. In this paper, we investigate link recommendations over business pages on Facebook Social Network. More specifically, given a company in thenetwork, we want to recommend potential companies to connect with. We start by introducing existing work in link recommendations and some link prediction models as our baseline. We then talk about the Graph Neural Network model SEAL to make a link recommendations in the network. Our results show that SEAL outperformed the compared baseline model while reaching above 94% Area Under Curve accuracy in link recommendations.
Prognostication Based on Texture Analysis of Baseline 18F Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Nonsmall-Cell Lung Carcinoma Patients Who Underwent Platinum-Based Chemotherapy as First-Line Treatment

Objective: Our study aims to establish the potential for tumor heterogeneity evaluated using 18F fluorodeoxyglucose positron emission tomography/computed tomography (F-18 FDG PET/CT) texture analysis in nonsmall-cell lung carcinoma (NSCLC) patients who underwent platinum-based chemotherapy to provide an independent marker for overall survival (OS) of more than 1-year. Materials and Methods: A total of 42 patients (34 male and 8 female) with biopsy-proven NSCLC and mean age 55.33 ± 10.71 years who underwent a baseline F-18 FDG PET/CT and received platinum-based chemotherapy as first-line treatment were retrospectively included in the study. Ten first order, 21 s order texture parameters and 7 SUV and metabolic tumor volume (MTV) based metabolic parameters were calculated. All these parameters were compared between the two survival groups based on OS ≥1 year and OS <1 year. Cut-offs of significant parameters were determined using receiver operating characteristic curve analysis. Survival patterns were compared by log-rank test and presented using Kaplan-Meier curves. Cox proportion hazard model was used to determine the independent prognostic marker for 1 year OS. Results: In univariate survival analysis, 3 first order texture parameters (i.e. mean, median, root mean square with hazard ratios [HRs] 2.509 [P = 0.034], 2.590 [P = 0.05], 2.509 [P = 0.034], respectively) and 6 s order texture parameters (i.e. mean, auto correlation, cluster prominence, cluster shade, sum average and sum variance with HRs 2.509 [P = 0.034], 2.509 [P = 0.034], 3.929 [0.007], 2.903 [0.018], 2.954 [0.016] and 2.906 [0.014], respectively) were significantly associated with 1 year OS in these patients. Among the metabolic parameters, only metabolic tumor volume whole-body was significantly associated with 1 year OS. In multivariate survival analysis, cluster prominence came out as the independent predictor of 1 year OS. Conclusion: Texture analysis based on F-18 FDG PET/CT is potentially beneficial in the prediction of OS ≥1 year in NSCLC patients undergoing platinum-based chemotherapy as first-line treatment. Thus, can be used to stratify the patients which will not be benefitted with platinum-based chemotherapy and essentially needs to undergo some other therapy option.
Analgesic efficacy of dexamethasone versus dexmedetomidine as an adjuvant to ropivacaine in ultrasound-guided transversus abdominis plane block for post-operative pain relief in caesarean section: A prospective randomised controlled study

Background and Aims: Transversus abdominis plane (TAP) block is commonly used to treat post-operative pain after lower abdominal surgeries. The aim of this randomised controlled study was to assess the efficacy of addition of dexmedetomidine or dexamethasone to ropivacaine in TAP block and compare the two for post-operative pain relief in caesarean section. Methods: A hundred parturients (18–45 years) undergoing caesarean section under spinal anaesthesia received ultrasound-guided (USG) bilateral TAP block with 50ml of 3mg/kg ropivacaine along with 0.1mg/kg dexamethasone (Group A) or 1μg/kg dexmedetomidine (Group B) in this prospective, randomised, double-blind study. Time to initial self-reporting of post-operative pain, time to first rescue analgesic demand, visual analogue scale (VAS) for pain haemodynamic parameters and adverse effects if any were noted, anda P value < 0.005 was considered as statistically significant. Results: Time to initial self-reporting of post-operative pain (411.35 vs. 338.20 min, P < 0.005) and time to first rescue analgesic (474.30 vs. 407.30 min, P < 0.005) were significantly longer in group B as compared to group A. VAS score at the time of initial self-reporting of pain was significantly lower in group B. No significant haemodynamic changes or side-effects were noted. Conclusion: Addition of dexmedetomidine to ropivacaine as compared with dexamethasone in bilateral TAP block following caesarean section prolongs the time to initial post-operative pain and time to first rescue analgesic consumption.
“When virtuality merges with reality:” Application of virtual reality and augmented reality in dentistry - A literature review

The term “virtuality” has been quoted as “real but not actual, ideal but not abstract” by Marcel Proust. Visual-based reality is gaining popularity in dentistry because of its use in dealing with image-guided and robot-assisted surgery. It has provided a new approach for improving the treatments and delivering education in dentistry. The major throwback was the use of images registration by endoscope camera devices in the form of a video which can be presented on a monitor where the operator is able to observe the site inside the patient. The technologies of modern science have amazed and also fascinate our vision regarding working with patients. This literature review provides only a glance at the future of intelligence science.
Concentration of the PM2.5 according to the sampling areas associated with the concentration of heavy metals and anions in Penang

Particulate matter (PM) was identified as the main air pollutants in Malaysia which directly impose a treat to human health and understanding this pollutant is also crucial for its mitigation and control. This study aims to determine and characterize the PM2.5 with the influence of meteorological parameters. The PM2.5 samples were collected at Perai, Nibong Tebal and highway of Penang Bridge represented the industrial, residential, and roadside areas of Mainland Penang, respectively. The descriptive statistical analysis was conducted to understand the variations of PM2.5 concentration on the study areas, while its relationship with meteorological parameters were tested using Pearson correlation. Eleven heavy metals and three anions were determined using mass spectrometry (ICP-MS) and Ion Chromatography, respectively. Results showed that the mean concentration of PM2.5 are 10.88 ? g/m³, 31.96 ? g/m³, and 39.35 g/m³ for residential area, industrial area, and roadside, respectively. The results revealed that mean concentrations of PM2.5 (39.35 ? g/m³) in the roadside are significantly higher than NAAQG 24-h average of 35 ? g/m³. Result also suggested that meteorological parameters were lest significant in controlling the PM2.5 concentrations as only the air pressure was found to be significant with the value of correlation coefficient of 0.476. The major components such as SO42-, K and Na account for about 70-90% of the PM2.5.
Restructuring State - Local Relations in Nigeria: Issues and Perspectives

Federations thrived where levels of government exist and function based on shared rule and self-rule concurrently. Thus, a key defining feature of federalism is the assignment of responsibilities between component units such that each unit is assigned specific responsibilities within its jurisdiction. However, in Nigeria, the disproportionate distribution of responsibilities and resources amongst the component units had resulted in a dysfunctional federation. By virtue of the provision of section 7 of 1999 Constitution, Supreme Court's judgements and extra-judicial pronouncements, local governments are under the "supervisory control" of the State Governments (SGs). However, the extent to which this supervisory control is exercised has been at the front burner of every discourse on Nigerian politics and particular governance challenges. While examining state-local governments relations from both legal and operational viewpoints, this paper illustrates how the SGs wore away the intent of the framers of the Constitution, which is to institute a system of local government that is properly organised, monitored supervised by the SGs. A qualitative research approach was used. Data was collected via official documents, relevant literature, and interviews from officials of the SGs and local governments and experts selected purposively and conveniently. The paper established that local governments are failing simply because the SGs have failed to perform their responsibilities per the spirit of the Constitution and other extant laws. The article finally advocates for an efficient and effective local government system premise on the federal decentralise system. In doing that, it is important to stress that the existing legal aspect does require slight adjustment especially granting the Houses of Assembly of State and state judiciary reasonable autonomy to checkmate the excesses of the SGs. Moreover, accomplishing this will significantly restructure and improve the operational aspect of the relationship for a virile local government system.
Molecular Docking interaction of Kaempferol-3-o-α-l- rhamnoside isolated from Cardiospermum halicacabum Linn with molecular targets involved in blood glucose homeostasis

Aim: Molecular docking has become a progressively vital tool for drug discovery and development area. This technique is widely used to screen most potent drugs. The potency of isolated compounds from medicinal plants were assessing through docking. Diabetes mellitus being a most common endocrine disorder with the highest rates of prevalence and mortality, supplement of isolated compounds from herbal plants will be effective in the management of the disease. Hence in the present study the efficiency of the derivative of Kaempferol, a well-known flavonoid isolated from Cardiospermum halicacabum leaf extract in the management of diabetes been assessed through docking with various blood glucose regulating enzymes. Methods: Molecular docking studies of the ligand with selected proteins were performed using PatchDock techniques used in Computer Vision. Results: In the current research Kaempferol30αlrhamnoside showed good affinity with all the proteins. It showed highest binding affinity with much lesser binding energy with glycogen synthase kinase and glycogen phosphorylase. It also showed good quality of binding with Glucokinase, α-amylase and aldose reductase with relatively less binding energy. Conclusion: The present study provides scientific evidence for the antidiabetic potential of Kaempferol30αlrhamnoside and anticipated to be useful in guiding the rational design of novel and robust drug for the treatment of diabetes.
Unsupervised Minimum Redundancy Maximum Relevance Feature Selection for Predictive Maintenance

Identifying and selecting optimal prognostic health indicators in the context of predictive maintenance is essential to obtain a good model and make accurate predictions. Several metrics have been proposed in the past decade to quantify the relevance of those prognostic parameters. Other works have used the well-known minimum redundancy maximum relevance (mRMR) algorithm to select features that are both relevant and non-redundant. However, the relevance criterion is based on labelled machine malfunctions which are not always available in real life scenarios. In this paper, we develop a prognostic mRMR feature selection, an adaptation of the conventional mRMR algorithm, to a situation where class labels are a priori unknown, which we call unsupervised feature selection. In addition, this paper proposes new metrics for computing the relevance and compares different methods to estimate redundancy between features. We show that using unsupervised feature selection as well as adapting relevance metrics with the dynamic time warping algorithm help increase the effectiveness of the selection of health indicators for a rotating machine case study.
Analysis of changes in public behavior regarding 3M health protocols during the Covid-19 pandemic in Indonesia

The Covid-19 pandemic has occurred in Indonesia since March 2020. The pandemic period required adjustments in all sectors of life, including changes in people's behavior, namely spending more time at home. Changes in people’s behavior are needed to break the chain of Covid-19 transmissions, one of which is the implementation of Health protocols. Research on the behavior of the Indonesian people in dealing with the Covid-19 pandemic includes public knowledge and understanding, compliance in implementing the 3M health protocols, and the important factors that influence changes in people's behavior to comply with the health protocol. Data was collected by distributing online questionnaires, surveys to crowd locations and FGDs. National online and offline surveys are divided into 3 regions, namely Java, West Indonesia and East Indonesia. The analysis was carried out using statistical methods, namely dependency analysis, factor analysis, and multinomial regression. The conclusion is that people who have implemented the 3M protocol and have confidence in the effectiveness of 3M tend to believe that the 3M protocol is important to continue to be implemented. In addition, it is known that social media, TV, and online media almost always ranked in the top three of the most media respondents to get information about the importance of implementing health protocols.
T HE E FFECT OF B IAS IN T RAINING D ATA

– Machine learning is only as good as the data that creates it and given the mistrust of AI and big data by the public recently, it is useful to explore scenarios where machine learning might give misleading results. In this RET study, I will study how data can be biased in multiple ways to demonstrate to students how this can be demonstrated in the confusion matrix and corresponding scatter plots.