Miracle-dz/UniFAR-FTUs huggingface dataset:
Moral distress during COVID-19: The importance of perceived organizational support for hospital nurses

Moral distress, or the inability to act congruent with moral beliefs, has been of concern for healthcare professionals especially since the COVID-19 pandemic. Hospital nurses are particularly affected in their roles with mounting administrative pressures and demands. We examined whether general and COVID-specific support in employing healthcare organizations predicted moral distress in a sample of inpatient hospital nurses. A total of 248 nurses completed the Measure of Moral Distress for Healthcare Professionals, Survey of Perceived Organizational Support, COVID Organizational Support survey, and the Hospital Ethical Climate Scale. We found that general and COVID-related organizational support were predictors of moral distress after controlling for age, gender, working in an intensive care unit setting, and ethical climate. Findings support the need for a comprehensive strategy to address moral distress, including institutional efforts to convey support and commitment. Strategies moral distress may be experienced differently based on gender identity.
Methamphetamine-associated pulmonary arterial hypertension

Purpose of review Methamphetamine use is increasing in popularity globally, and chronic users suffer from various drug toxicities, including the development of pulmonary arterial hypertension. Although it was previously thought to be a possible cause of pulmonary arterial hypertension, as of the sixth World Symposium on Pulmonary Hypertension, methamphetamine use is now recognized as a definite cause of pulmonary arterial hypertension. This review will discuss the history of methamphetamine use, the link between methamphetamine use and pulmonary arterial hypertension, and the clinical characteristics of patients with pulmonary hypertension from methamphetamine use. Recent findings The mechanism by which methamphetamine abuse leads to pulmonary hypertension is unclear. However, recent studies have suggested that reduced expression of carboxylesterase 1 may be implicated due to maladaptation to the environmental injury of methamphetamine abuse. Based on the report of two recent cohort studies, patients with methamphetamine-associated pulmonary arterial hypertension have a worse functional class, less favorable hemodynamics, impaired health-related quality of life, increased health-care utilization, and attenuated survival, as compared to those with idiopathic pulmonary arterial hypertension. Summary Future studies are needed to better understand the mechanism by which methamphetamine use leads to pulmonary arterial hypertension. Methamphetamine-associated pulmonary arterial hypertension likely represents a more advanced disease state than idiopathic pulmonary arterial hypertension, however, it is treated less aggressively in clinical practice.
“Are You Sure It’s Not the Corona Vaccine?” An Ebola Vaccine Trial During COVID-19 in DRC

ABSTRACT The COVID-19 pandemic began as an Ebola epidemic was unfolding in the Democratic Republic of the Congo. In this article, we examine how COVID-19 influenced experiences of an Ebola vaccine trial and attitudes towards medical research in Goma. First, critical debates about vaccine research became a forum in which to contest ineffective local governance and global inequality. Second, discussions about new COVID-19 therapeutics reignited critique of Western biomedical colonialism. Third, rumors were made powerful through everyday observations of the unexpected adaption of Ebola trial procedures in the pandemic. This illustrates the difficulties of maintaining participants’ trust, when circumstances dictate protocol alterations mid-trial.
Kalman-based interacting multiple-model wind speed estimator for wind turbines

: The use of state estimation technique oﬀers a means of inferring the rotor-eﬀective wind speed based upon solely standard measurements of the turbine. For the ease of design and computational concerns, such estimators are typically built based upon simpliﬁed turbine models that characterise the turbine with rigid blades. Large model mismatch, particularly in the power coeﬃcient, could lead to degradation in estimation performance. Therefore, in order to eﬀectively reduce the adverse impact of parameter uncertainties in the estimator model, this paper develops a wind sped estimator based on the concept of interacting multiple-model adaptive estimation. The proposed estimator is composed of a bank of extended Kalman ﬁlters and each ﬁlter model is developed based on diﬀerent power coeﬃcient mapping to match the operating turbine parameter. Subsequently, the algorithm combines the wind speed estimates provided by each ﬁlter based on their statistical properties. In addition, the proposed estimator not only can infer the rotor-eﬀective wind speed, but also the uncertain system parameters, namely, the power coeﬃcient. Simulation results demonstrate the proposed estimator achieved better improvement in estimating the rotor-eﬀective wind speed and power coeﬃcient compared to the standard Kalman ﬁlter approach.
Forgetting in visual working memory: Internal noise explains decay of feature representations

The precision of visual working memory (VWM) representations decreases as time passes. It is often assumed that VWM decay is random and caused by internal noise accumulation. However, forgetting in VWM could occur systematically, such that some features deteriorate more rapidly than others. There exist only a few studies testing these two models of forgetting, with conflicting results. Here, decay of features in VWM was thoroughly tested using signal detection theory methods: psychophysical classification images, internal noise estimation, and receiver operant characteristic (ROC). A modified same–different memory task was employed with two retention times (500 and 4000 ms). Experiment 1 investigated VWM decay using a compound grating memory task, and Experiment 2 tested shape memory using radial frequency patterns. Memory performance dropped some 15% with increasing retention time in both experiments. Interestingly, classification images showed virtually indistinguishable weighting of stimulus features at both retention times, suggesting that VWM decay is not feature specific. Instead, we found a 77% increase in stimulus-independent internal noise at the longer retention time. Finally, the slope of the ROC curve plotted as z-scores was shallower at the longer retention time, indicating that the amount of stimulus-independent internal noise increased. Together these findings provide strong support for the idea that VWM decay does not result from a systematic loss of some stimulus features but instead is caused by uniformly increasing random internal noise.
Feasibility of 99mTc-MIP-1404 for SPECT/CT Imaging and Subsequent PSMA-Radioguided Surgery in Early Biochemically Recurrent Prostate Cancer: A Case Series of 9 Patients

Visual Abstract This case series evaluated the feasibility of prostate-specific membrane antigen (PSMA)–radioguided surgery (RGS) with 99mTc-MIP-1404 in recurrent prostate cancer. Methods: Nine patients with PSMA-positive lesions on PET/CT received 99mTc-MIP-1404 (median, 747 MBq; interquartile range [IQR], 710–764 MBq) 17.2 h (IQR, 16.9–17.5 h) before SPECT/CT and 22.3 h (IQR, 20.8–24.0 h) before RGS. Results: Seventeen PSMA-positive lesions were detected on PET/CT (median short-axis diameter, 4 mm; IQR, 3–6 mm; median SUVmax, 8.9; IQR, 5.2–12.6). Nine of 17 (52.9%) were visible on SPECT/CT (median SUVmax, 13.8; IQR, 8.0–17.9). Except for 2 foci, all PET/CT-positive findings demonstrated intraoperative count rates above the background level (median count, 31; IQR, 17–89) and were lymph node metastases. Moreover, PSMA-RGS identified 2 additional metastases compared with PET/CT. Prostate-specific antigen values decreased after RGS in 6 of 9 patients (67%). Conclusion: PSMA-RGS with 99mTc-MIP-1404 identified lymph node metastases in all patients, including 2 additional lesions compared with PET/CT.
Unveiling biogeographical patterns in the worldwide distributed Ceratitis capitata (medfly) using population genomics and microbiome composition

Invasive species are among the most important, growing threats to food security and agricultural systems. The Mediterranean medfly, Ceratitis capitata, is one of the most damaging representatives of a group of rapidly expanding species in the family Tephritidae, due to their wide host range and high invasiveness potential. Here, we used restriction site‐associated DNA sequencing (RADseq) to investigate the population genomic structure and phylogeographical history of medflies collected from six sampling sites, including Africa (South Africa), the Mediterranean (Spain, Greece), Latin America (Guatemala, Brazil) and Australia. A total of 1907 single nucleotide polymorphisms (SNPs) were used to identify two genetic clusters separating native and introduced ranges, consistent with previous findings. In the introduced range, all individuals were assigned to one genetic cluster except for those in Brazil, which showed introgression of an additional genetic cluster that also appeared in South Africa, and which could not be previously identified using microsatellite markers. Moreover, we assessed the microbial composition variations in medfly populations from selected sampling sites using amplicon sequencing of the 16S ribosomal RNA (V4 region). Microbiome composition and structure were highly similar across geographical regions and host plants, and only the Brazilian specimens showed increased diversity levels and a unique composition of its microbiome compared to other sampling sites. The unique SNP patterns and microbiome features in the Brazilian specimens could point to a direct migration route from Africa with subsequent adaptation of the microbiota to the specific conditions present in Brazil. These findings significantly improve our understanding of the evolutionary history of the global medfly invasions and their adaptation to newly colonized environments.
Teaching biology students data exploration and visualization in a data‐driven world

As biologists accumulate or encounter increasingly large and complex data sets, our field creates the need for students to develop skills in data exploration and visualization. Many biology courses lack the time for students to develop the skills needed to parse complex datasets and visualize them appropriately. We developed a new upper‐level undergraduate biology course to focused on data exploration and communication without requiring previous coding experience. We emphasized data visualization principles and best practices and taught students how to manage and visualize data via Tableau and R. We also explored scientific ethics, how to refute misinformation, and inequities that can occur in data collection and usage.
Electrocardiogram Collection, Pattern Recognition, and Classification Sensor System Supporting a Mobile Cardiovascular Disease Detection Aid

— Current mobile monitoring solutions do not offer the ability to recognize cardiac problems without human interpretation. A combination of electrocardiogram (ECG) detection and classification software running on a mobile cardiovascular disease detection sensor is proposed to replace the need for human interpretation. The ECG is filtered using the Wavelet Transform; the ECG wave points detected using a modified version of the Pan Tompkins rule set and the cardiac rhythm is classified using an N-ary tree. The wireless mobile application is designed on a custom printed circuit board (PCB). Testing results show autonomous classifications are possible using a three lead ECG system while the patient is at rest. The proposed solution serves as a stepping stone towards a fully reliable patient disease management teaching tool with the potential to serve as an aid to the cardiovascular healthcare industry.
Coordinated Beamforming and Common Message Decoding for Intercell Interference Mitigation in Multicell Networks

Coordinated Beamforming and Common Message Decoding for Intercell Interference Mitigation in Multicell Networks Hayssam Dahrouj Doctor of Philosophy Graduate Department of Electrical and Computer Engineering University of Toronto 2010 Conventional multicell wireless systems operate with out-of-cell interference treated as background noise; consequently, their performance faces two major limitations: 1) Signal processing is performed on a per-cell basis; and 2) Intercell interference detection is infeasible as intercell interference, although significantly above the noise level, is typically quite weak. In this thesis, we consider a multicell downlink scenario, where base-stations are equipped with multiple transmit antennas, the remote users are equipped with a single antenna, and multiple remote users are active simultaneously via spatial division multiplexing. We propose solutions for the above limitations by considering techniques for mitigating interference. The first part of the thesis proposes solutions for the first limitation. It considers the benefit of coordinating base-stations across multiple cells, where multiple base-stations may jointly optimize their respective beamformers to improve the overall system performance. It focuses on the design criteria of minimizing either the total weighted transmitted power or the maximum per-antenna power across the base-stations subject to signal-to-interference-and-noise-ratio (SINR) constraints at the remote users. The main contribution of this part is an efficient algorithm for finding the joint globally optimal beamformers across all base-stations. The proposed algorithm is based on a generalization of uplink-downlink duality to the multicell setting using the Lagrangian duality
CT generation from unpaired data

Both MRI and CT imaging are commonly used and combined in medical imaging because of their complementary information about soft tissue and bone respectively. However, CT imaging relies on harmful ionizing radiation. Thus medical imaging scientists are working on transferring harmless MRI scans to CT-like images where using deep learning methods are the current state of the art. Most deep learning methods however require large amounts of paired data to train the transfer systems, which is why we try to perform the transfer using an unpaired method, CycleGANs. Using ex-vivo dog hip MRI and CT scan pairs we trained a Cycle-GAN and a U-Net using both registered and poorly registered data. We also further investigated the effect of discriminator’s receptive ﬁeld size in a CycleGAN as well as introduced a novel NMI loss component to its generators. Performance of said systems was evaluated by calculating MAE and Dice scores. We show that Cy-cleGAN’s performance is sensitive to its discriminator’s receptive ﬁeld size and can even generate unwanted structrures in the CT-like images. Also, we show that adding NMI loss component with the right weight can improve the system’s performance. The results of comparing the pairwise and unpaired method show that a CycleGAN will only outperform the U-Net when transferring poorly registered data. This suggest that, whenever paired registered data is available, it is better to use a pairwise transfer approach. However, the results of the experiment where the NMI loss component was added suggest that transfer from MRI scans to CT-like images can become more accurate and encourage further research. Finally, this means in certain cases CT scans could be avoided, providing a more harmless medical imaging future.
A Comparative Study of Performance Analysis of Empirical Propagation Models for NB-IoT Protocol in Suburban Scenarios

— Among the protocols available for Internet of Things (IoT) applications, the Narrow Band-Internet of Things (NB-IoT) is one of the most relevant for presenting advantages, such as long range, low latency and low energy consumption. One of the points questioned for every protocol is the ability to serve applications that are in a mobile environment. To validate the possibility of the protocol working in this scenario, it is necessary to evaluate its performance in different propagation environments. This article presents field measurements that were made on an NB-IoT operational network in a suburban environment. The measurement results were compared with the results calculated on three propagation models used to predict loss of propagation in a mobile environment: Cost-231 Hata, ITU-1225 and Erceg Greenstein. Comparisons show that the Cost-231 Hata model offers the best performance in predicting propagation loss in the considered scenarios. These results provide relevant information about the performance of the propagation models used, applied to the NB-IoT protocol in a suburban environment.
Left ventricular shape predicts arrhythmic risk in fibrotic dilated cardiomyopathy

Abstract Aims Remodelling of the left ventricular (LV) shape is one of the hallmarks of non-ischaemic dilated cardiomyopathy (DCM) and may contribute to ventricular arrhythmias and sudden cardiac death. We sought to investigate a novel three dimensional (3D) shape analysis approach to quantify LV remodelling for arrhythmia prediction in DCM. Methods and results We created 3D LV shape models from end-diastolic cardiac magnetic resonance images of 156 patients with DCM and late gadolinium enhancement (LGE). Using the shape models, principle component analysis, and Cox-Lasso regression, we derived a prognostic LV arrhythmic shape (LVAS) score which identified patients who reached a composite arrhythmic endpoint of sudden cardiac death, aborted sudden cardiac death, and sustained ventricular tachycardia. We also extracted geometrical metrics to look for potential prognostic markers. During a follow-up period of up to 16 years (median 7.7, interquartile range: 3.9), 25 patients met the arrhythmic endpoint. The optimally prognostic LV shape for predicting the time-to arrhythmic event was a paraboloidal longitudinal profile, with a relatively wide base. The corresponding LVAS was associated with arrhythmic events in univariate Cox regression (hazard ratio = 2.0 per quartile; 95% confidence interval: 1.3–2.9), in univariate Cox regression with propensity score adjustment, and in three multivariate models; with LV ejection fraction, New York Heart Association Class III/IV (Model 1), implantable cardioverter-defibrillator receipt (Model 2), and cardiac resynchronization therapy (Model 3). Conclusion Biomarkers of LV shape remodelling in DCM can help to identify the patients at greatest risk of lethal ventricular arrhythmias.
EVALUATION OF THE INHIBITORY EFFECT OF A CANNABIDIOL DERIVATIVE AGAINST THE PLASMODIUM FALCIPARUM DIHYDROFOLATE REDUCTASE

: Introduction: The alarming rate of drug failure against malaria necessitates the development and deployment of novel and highly efficacious antimalarial drugs. The use of natural plant remedies in curtailing the malaria catastrophe remains uncertain, as only a small fraction of plants has been evaluated and developed for their medicinal potentials. However, many communities in malaria-affected regions still rely on natural plants and herbs, despite documented concerns about efficacy and adverse effects. One plant of continuous controversy is Cannabis sativa , known mainly for its psychoactive effects but possesses other activities. Cannabidiol, an isolated constituent of cannabis has been reported to possess moderate antimalarial activity in vitro. Materials and Methods: The Autodock Vina software was used in carrying out a molecular docking study on cycloguanil, cannabidiol and its C 2 H 5 analogue against the Plasmodium falciparum dihydrofolate reductase. The physiochemical analysis, lipophilicity, solubility, pharmacokinetics and Lipinski drug likeness of these molecules were also evaluated through extensive structure-activity relationship study. Results: The free binding energies of cycloguanil, cannabidiol and its modified analogue were -8.0, -8.9 and -8.9Kcal/mol respectively. The low binding score (more negative value) exhibited by cannabidiol and its C 2 H 5 analogue shows they are respectively the better antimalarial agents. The inability of the C 2 H 5 analogue of cannabidiol to cross the blood brain barrier as displayed in the structure-activity relationship results shows it poses no threat to normal brain function which makes it the most ideal antimalarial agent against the P. falciparum DHFR. All the experimental ligands exhibited high gastrointestinal absorption rates and are also moderately soluble in water. Conclusion: The results showed that the C 2 H 5 analogue of gedunin might be the most ideal antimalarial agent haven exhibited a low binding score and no interference with the CNS through BBB permeation. The laboratory synthesis and preclinical study on this compound is therefore recommended in order to confirm itsantimalarial potentials.
Predicting Student Performance to Forecast University Enrollment

Not all universities have dedicated registrar departments, nor access to specific software to keep track of student enrollment to forecast future enrollment. The ability to develop reliable student forecast brings multiple benefits in regard to both university finances and student investment. This study explores prior student data from the Institution Tecnologico de Chihuahua (ITCH), with the intent to develop such forecast models. This is achieved through an ensemble of different predictive models such as a Support Vector Machine (SVM) binary classification, ordinary least squares linear regression (OLS), and Holt-Winter Exponential Smoothing.
Phytochemical profile, total phenolic content and antioxidant activity of ethanolic extract of fumitory ( Fumaria capreolata L.) from Algeria

: Fumitory or Fumaria capreolata L. is a medicinal plant, spontaneous and widely distributed in North Africa, particularly in Algeria. It has been recognized for centuries for its therapeutic virtues, and it is used in traditional medicine in the treatment of hepatobiliary diseases, gastrointestinal disorders and in the treatment of skin diseases. The phytochemical screening carried out on the aerial part of the species F. capreolata L. , revealed the richness of this plant in secondary metabolites, such as alkaloids, catechic tannins, sterols and terpenes. On the other hand, we noticed the absence of cardinolides, leuco-anthocyanins, quinones and starch in all parts of the plant. Quantitative spectrophotometric analysis allowed us to detect the levels of total polyphenols using the reagent of Folin-Ciocalteu, according to the results obtained we find that the species F. capreolata is rich in these compounds (14.27 ± 1.65 mg GAE/g). The evaluation of the antioxidant activity was carried out using the DPPH method, indicated that the ethanolic extract of F. capreolata L. showed significant antioxidant activity, with an IC 50 = 0.27 mg/ml. And it also has a strong inhibitory activity of the coupled oxidation of linoleic acid and β -carotene, with a percentage of 88.46 ± 1.02% at a concentration of 0.5 mg/ml. In addition, the crude extract of F. capreolata L. , also exhibits a good iron reduction capacity, with a maximum optical density of 0.349 at a concentration of 0.5 mg/ml.