Miracle-dz/UniFAR-FTUs huggingface dataset:
Prognostic Association Between Perioperative Red Blood Cell Transfusion and Postoperative Cardiac Surgery Outcomes

Objective: To investigate the correlation between red blood cell transfusion and clinical outcome in patients after cardiac surgery. Methods: Demographic, clinical characteristics, treatment with/without transfusion, and outcomes of patients after cardiac surgery from the Medical Information Mart for Intensive Care—III database were collected. Patients were divided into two groups according to perioperative transfusion. A multivariable logistic regression analysis was utilized to adjust for the effect of red blood cell transfusion on outcomes for baseline and covariates and to determine its association with outcomes. Results: In total, 6,752 patients who underwent cardiac surgery were enrolled for the analysis. Among them, 2,760 (40.9%) patients received a perioperative transfusion. Compared with patients without red blood cell transfusion, transfused patients demonstrated worse outcomes in inhospital mortality, 1-year mortality, and all-cause mortality. Adjusting odds ratios (ORs) for the significant characteristic, patients with perioperative transfusion remained significantly associated with an increased risk of inhospital mortality [OR = 2.8, 95% confidence interval (CI) 1.5–5.1, P = 0.001], 1-year mortality (OR = 2.0, 95% CI 1.4–2.7, P < 0.001), and long-term mortality (OR = 2.2, 95% CI 1.8–2.8, P < 0.001). Conclusion: Perioperative red blood cell transfusion is associated with a worse prognosis of cardiac surgery patients. Optimal perioperative management and restricted transfusion strategy might be considered in selected patients.
The Role of Economic Policy Uncertainty in Renewable Energy-Growth Nexus: Evidence From the Rossi-Wang Causality Test

This paper examines the causal relationship between renewable energy consumption and economic growth in four countries: Brazil, Germany, Japan, and the United States. Unlike previous papers, we control economic policy uncertainty’s effects to capture the role of capabilities on the renewable energy-growth nexus. The recent Vector Autoregression (VAR)-based Granger-causality test of Rossi-Wang shows a bidirectional causal relationship between renewable energy and the economic growth in Brazil and Germany. There is also a significant causality from renewables to economic growth in the United States.
Developing Multiple Dimensional Vibrational Spectroscopy for Molecular Conformation Determinations and New Catalysts Design

Developing Multiple Dimensional Vibrational Spectroscopy for Molecular Conformation Determinations and New Catalysts Design by Yufan Zhang Understanding molecular structures can play a critical role in revealing many important chemical and biological phenomena. X-ray crystallography and NMR methods, two of the most common structural tools, cannot reveal all unknown molecular structures due to the restriction of sample form or low time resolution, respectively. Motivated by the need of a new approach to reveal structures that are currently not feasible by these traditional techniques, this thesis has developed a uniquely designed ultrafast multiple-mode multiple-dimensional vibrational spectroscopy (MDVS) to conquer the limitations of traditional methods. The MDVS technique has also been applied to study molecular structures under various condensed phases, and facilitate the understanding of various chemical mechanisms in this thesis. Chapter 1 gave a brief review of the current common structure tools that have been used by chemists. Their advantages and disadvantages were compared to bring up the challenges that a new generation of structure tool needs to conquer. Chapter 2 gave a detailed description of the new design of our multiple dimensional vibrational spectroscopy and its theoretical basis on how it can be used to reveal molecular structures. Chapter 3 gave an example of how the MDVS reveals the molecular conformations for molecules in various condensed phases. Chapter 4 showed another application of MDVS in revealing an intermediate’s structure during a real catalytic reaction for hydrogen generation. Chapter 5 was inspired by the potential application of formic acid as a great hydrogen chemical storage material demonstrated in Chapter 4, we continued working on developing and optimizing hydrogenation catalysts with even better efficiency and long lifetime.
On the kinetics of protein aggregation

Protein (mis)folding into highly ordered, fibrillar structures, amyloid fibrils, is a hallmark of several, mainly neurodegenerative, disorders. The mechanism of this supra-molecular self-assembly reaction, as well as its relationship to protein folding are not well understood. In particular, the molecular origin of the metastability of the soluble state of proteins with respect to the aggregated states has not been clearly established. In this dissertation, it is demonstrated, that highly accurate kinetic experiments, using a novel biosensing method, can yield fundamental insight into the dynamics of proteins in the region of the free energy landscape corresponding to protein aggregation. First, a section on Method development describes the extension and elaboration of the previously established kinetic assay relying on quartz crystal microbalance measurements for the study of amyloid fibril elongation (Chapter 3). This methodology is then applied in order to study in great detail the origin of the various contributions to the free energy barriers separating the soluble state of a protein from its aggregated state. In particular, the relative importance of residual structure, hydrophobicity (Chapter 4) and electrostatic interactions (Chapter 5) for the total free energy of activation are discussed. In the last part of this thesis (Chapter 6), it is demonstrated that this biosensing method can also be used to study the binding of small molecules to amyloid fibrils, a very useful feature in the framework of the quest for potential inhibitors of amyloid formation. In addition, it is shown that Thioflavin T, to-date the most frequently employed fluorescent label molecule for bulk solution kinetic studies, can in the presence of potential amyloid inhibitor candidates be highly unreliable as a means to quantify the effect of the inhibitor on amyloid formation kinetics. In summary, the work in this thesis contributes to both the fundamental and the applied aspects of the field of protein aggregation.
Akurasi Sistem Face Recognition OpenCV Menggunakan Raspberry Pi Dengan Metode Haar Cascade

Face recognition systems is developing very quickly with various methods and algorithms. Face recognition system is an identification system that is developed based on differences in facial features biometrics on body parts or even human behavior. Face is used by systems to recognize someone because faces have different shapes and textures. Information about a person's face can be extracted from the image that has been detected. However, detection system still needs to be developed to obtain better results. Based on that background, this research formulated how much accuracy is generated in the face recognition detection system using the Haar Cascade algorithm, using a webcam camera and Python as its programming language. In this study, Raspberry Pi is used as a Single Board Computer to run a face recognition program and Open Computer Vision (OpenCV) as a face recognition library. This system called FaceTrix and from the results of testing the accuracy of the system, the best accuracy of the system is at a distance of 40 cm and 60 cm which was 100% and distance of 80 cm which was 91%. Based on overall system testing, the detection system's accuracy was 97% with an average time of 1.779 FPS.
Sampled‐data implementation of extended PID control using delays

We study the sampled‐data implementation of extended PID control using delays for the nth‐order stochastic nonlinear systems. The derivatives are approximated by finite differences giving rise to a delayed sampled‐data controller. An appropriate Lyapunov–Krasovskii (L‐K) method is presented to derive linear matrix inequalities (LMIs) for the exponential stability of the resulting closed‐loop system. We show that with appropriately chosen gains, the LMIs are always feasible for small enough sampling period and stochastic perturbation. We further employ an event‐triggering condition that allows to reduce the number of sampled control signals used for stabilization and provide L2 ‐gain analysis. Finally, three numerical examples illustrate the efficiency of the presented approach.
Memristive Phase Change Memory

The paper presents study on and simulation of resistive nonvolatile phase change memory (PCM) cell in NGSpice programming environment. The chalcogenide alloy based PCM cell model demonstrates switching between amorphous and crystalline phases. The crystalline factor, responsible for the phase change process, is programmed by applied variable electrical pulse. Parameters phase change, range of operating temperature, the crystalline factor are mapped and presented.
Enhanced encryption technique for secure iot data transmission

Internet of things is the latest booming innovation in the current period, which lets the physical entity to process and intervene with the virtual entities. As all the entities are connected with each other, it generates load of data, which lacks proper security and privacy standards. Cryptography is one of the domains of Network Security, which is one such mechanism that helps the data transmission process to be secure enough over the wireless or wired channel and along with that, it provides authenticity, confidentiality, integrity of data and prevents repudiation. In this paper, we have proposed an alternate enhanced cryptographic solution combing the characteristic of symmetric, asymmetric encryption algorithms and Public Key Server. Here, the key pairs of end points (User’s Device and IoT device) are generated using Elliptic Curve Cryptography and the respective public keys are registered in Public Key Server along with their unique MAC address. Thereafter, both the ends will agree on one common private secret key, which will be the base for further cryptographic process using AES algorithm. This model can be called as multi-phase protection mechanism. It will make the process of data transmission secure enough that no intermediate can tamper the data.
Towards Generalization of Cardiac Abnormality Classification Using ECG Signal

In the PhysioNet/Computing in Cardiology Challenge 2021, our team, DrCubic, develops a novel approach to classify cardiac abnormalities using reduced-lead ECG recordings. In our approach, we incorporate peak detection as a self-supervised auxiliary task. We build the model based on SE-ResNet, and integrate models of different input lengths and sampling rates. Inspired by last year's challenge results, we investigate various settings and techniques, and select the best ones, considering the intra-source performance and inter-source generalization simultaneously. Our classifiers receive scores of 0.49, 0.50, 0.50, 0.51, and 0.48 (ranked 9th, 8th, 7th, 5th, and 9th out of 39 scored teams) for the 12 -lead, 6-lead, 4-lead, 3-lead, and 2 -lead versions of the hidden test sets with the Challenge evaluation metric.
Towards Accurate and Model-Free QT Correction

In the electrocardiogram (ECG), the QT interval is an important metric of risk for various adverse cardiovascular events and a key measure in cardiotoxicology. The main challenge in the interpretation of the QT measurement is its dependence on the heart rate, i.e., the RR intervals. To correct the QT interval for heart rate, a multitude of approximative methods have been developed, e.g., the power-law formulas of Bazett and Fridericia that are still in clinical use. However, these methods are known to under- or overcorrect the QT intervals, and none of the methods developed to date are universally applicable to different conditions. Here we present a QT correction method that is not based on models or empirical data, but directly utilizes information transfer between the RR and QT intervals during the measurement. The method dynamically adapts to a multitude of previous RR intervals and gives the QT correction as an output. We outline the essential principles of the method and provide a set of test results that demonstrate the stability of the corrected QT values in comparison with the conventional correction methods.
Change Management Process in a Mining Company: Kotter’s 8-Step Change Model

This study assessed the change management process of a mining company following the 8-step change model advocated by Kotter in 1996. It investigated the association between change readiness factors which comprised job satisfaction, job uncertainty and organizational commitment and the change perception of the entire organization. The study employed a quantitative descriptive survey research design to methodically describe the observed change procedures, analyzed the association between change readiness factors and organizational change perception. Of the 192 mining company employees and stakeholders, 134 were randomly chosen through stratified sampling technique representing the operations division, support division and the organizational design group. Primary data were collected through survey questionnaires to stakeholders’ respondents holding various positions. The finding revealed that about 78 percent of the respondents agreed to step 8 of Kotter’s theory as instrumental in accomplishing the “make the change stick to the company’s culture”. They noted that the 8 steps from Kotter’s theory resulted to greater than 75 percent increase in productivity. There was a highly significant correlation (α < 0.01) between change readiness factors (job satisfaction, job uncertainty and organizational commitment) and the change perception of stakeholders. The higher the mining company adheres to change readiness factors, the more likely it can achieve success of change initiatives. In conclusion, the three identified change factors had direct bearing on the company stakeholders’ change perception. We recommend for a similar study to be pursued which could include other pertinent variables other than job satisfaction, job uncertainty and organizational commitment
Relationship Between Cardiac Isochrones and its Mean Anatomical Position in the Heart: The CineECG

CineECG is a novel approach to ECG analysis relating average cardiac electrical activity to the cardiac anatomy. Since its introduction CineECG has been reported to be reliable for the detection of Brugada Type-1 and conduction disorders, but the relationship between cardiac isochrones and CineECG remains unexplored. To describe this relation, fourteen distinct activation sequences were simulated and resulting ECGs were used to compute the CineECG. The average isochrone position was used as ground truth to compare to CineECG trajectories. The average distance between the CineECG and AIP was $24\pm 3$ mm, with significantly better agreement for the terminal QRS segment. Quantitatively, CineECG captures significant features of underlying activation sequences and its direct relation to cardiac anatomy provides additional insight into electrical cardiac pathology.
Metagenomes from Coastal Marine Sediments Give Insights into the Ecological Role and Cellular Features of <italic toggle='yes'>Loki</italic>- and <italic toggle='yes'>Thorarchaeota</italic>

The genomes of Asgard Archaea, a novel archaeal proposed superphylum, share an enriched repertoire of eukaryotic signature genes and thus promise to provide insights into early eukaryote evolution. However, the distribution, metabolisms, cellular structures, and ecology of the members within this superphylum are not well understood. Here we provide a meta-analysis of the environmental distribution of the Asgard archaea, based on available 16S rRNA gene sequences. Metagenome sequencing of samples from a salt-crusted lagoon on the Baja California Peninsula of Mexico allowed the assembly of a new Thorarchaeota and three Lokiarchaeota genomes. Comparative analyses of all known Lokiarchaeota and Thorarchaeota genomes revealed overlapping genome content, including central carbon metabolism. Members of both groups contained putative reductive dehalogenase genes, suggesting that these organisms might be able to metabolize halogenated organic compounds. Unlike the first report on Lokiarchaeota, we identified genes encoding glycerol-1-phosphate dehydrogenase in all Lokiand Thorarchaeota genomes, suggesting that these organisms are able to synthesize bona fide archaeal lipids with their characteristic glycerol stereochemistry. IMPORTANCE Microorganisms of the superphylum Asgard Archaea are considered to be the closest living prokaryotic relatives of eukaryotes (including plants and animals) and thus promise to give insights into the early evolution of more complex life forms. However, very little is known about their biology as none of the organisms has yet been cultivated in the laboratory. Here we report on the ecological distribution of Asgard Archaea and on four newly sequenced genomes of the Lokiarchaeota and Thorarchaeota lineages that give insight into possible metabolic features that might eventually help to identify these enigmatic groups of archaea in the environment and to culture them.
Impact of baseline drift removal on ECG beat classification and alignment

Accurate beat classification and alignment is fundamental to any signal averaging method. The objective of this study was to investigate the accuracy of different beat classification and alignment methods, and the impact of pre-processing methods on these algorithms. Experimental data came from a human-shaped torso tank, with 256 body surface ECG recorded during sinus rhythm (SR) and left ventricular pacing (LVP) (n=4). “Gold-standard” classification and alignment were defined from recorded cardiac electrograms. Six different methods of baseline drift removal (BDR) were applied to ECG. Subsequently, 3 different beat segmentation methods were used to extract QRS complexes and align them, and four different beat classification methods. Pre-processing methods had only a small impact on beat classification and alignment compared to the segmentation and classification methods themselves. However, baseline drift removal over the whole QRS does appears to be important in providing the most accurate final averaged beat.
Antibacterial and antifungal activities of hydroalcoholic hands products sold in Côte d’Ivoire during covid-19

In the midst of the COVID-19 pandemic, hydroalcoholic products are widely used for hand disinfection. Côte d'Ivoire has also opted for this barrier measure. Ivorian markets and supermarkets have been filled with new hydroalcoholic products of various compositions and colors, certified or not by the Ivorian standardization agency. It was important to verify the antimicrobial efficacy of these hydroalcoholic products. To do this, we tested 16 hydroalcoholic products collected from supermarkets in Abidjan. The microbial load on the hands of 144 volunteers was determined before and after hand rubbing. These hydroalcoholic products were also tested for antibacterial activity against Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumonia and Proteus mirabilis; and antifungal activity against Aspergillus fumigatus and Penicillium chrysogenum. The results of this study showed that hydroalcoholic products tested significantly reduced the microbial load on the hands after friction. The germ inhibition rate was between 94.99 and 99.97%. Of the 16 hydroalcoholic products, only 3 showed antibacterial and antifungal activity on all indicator strains. In contrast, 4 showed no antibacterial and antifungal activity on these strains. The low efficacy of hydroalcoholic products tested in vitro is an indicator of the lack of quality control of these products. Some of them could not therefore guarantee the health security of the populations.
Wide Distribution of Closely Related, Antibiotic-Producing <named-content content-type='genus-species'>Arthrobacter</named-content> Strains throughout the Arctic Ocean

Matthias Wietz, Maria Månsson, Jeff S. Bowman, Nikolaj Blom, Yin Ng, and Lone Gram National Food Institute, Technical University of Denmark, Kgs. Lyngby, Denmark; Center for Microbial Biotechnology, Department of Systems Biology, Technical University of Denmark, Kgs. Lyngby, Denmark; School of Oceanography and Astrobiology Program, University of Washington, Seattle, Washington, USA; and Novo Nordisk Foundation Center for Biosustainability & Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kgs. Lyngby, Denmark
Development of Novel Continuous and Interval Exercise Programs by Applying the FITT-VP Principle in Dogs

Although proper exercise training induces positive physiological effects, improper exercise can lead to injury, fatigue, and poor performance. 2e frequency, intensity, time/duration, type, volume, and progression (FITT-VP) are the essential components of exercise training to maintain or improve physical fitness and health. 2e purpose of this study was to develop specific exercise programs by applying the FITT-VP principle and to examine the effects on heart rate (HR) and hematological and biochemical parameters in dogs. 2e healthy male Beagles (n� 4) included in this study performed continuous and interval exercises, comprising 12 protocols. 2e HR monitoring elicited an affirmative response to activities but varied depending on the protocols. 2e hematologic parameters (e.g., red blood cell count, white blood cell count, hemoglobin, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration) were within the reference ranges both before and after exercise.2e creatine kinase level significantly increased, and the cholesterol level decreased after exercises. In conclusion, the continuous and interval exercise program elicits an appropriate HR reaction, has no adverse effects on the serum parameters, and provides valuable insight for healthcare in dogs.
Longitudinal and survival data analysis for rheumatic diseases’ prognosis

Rheumatic diseases are one of the most common chronic diseases worldwide. Among them, spondyloarthritis (SpA) is a group of highly debilitating diseases, with an early onset age, significantly impacting patients’ quality of life, health care systems, and society in general. Recent treatment options consist of using biologic therapies, and establishing the most beneficial one according to the patient’s characteristics is a challenge that needs solving. Simultaneously, the emerging availability of electronic medical records (EMR) urges the development of methods that can extract insightful information while handling all the challenges of dealing with complex, real-world data. Our goal is to better understand SpA therapy responses and identify the predictors that affect them, enabling the prognosis of therapy success or failure. Moreover, we aim at achieving a usable dataset for future studies by pre-processing the data. A sensitivity analysis of the results to the different steps of this process will be performed. Joint models for the survival analysis of the biologic therapy failure are used, considering the information of both baseline and time-varying variables extracted from the EMR of SpA patients from the database Reuma.pt. Possible predictors of biologic drug survival were identified. It was verified that the approach used for handling data influenced the selection of variables and, consequently, the results. Furthermore, joint models proved to be a highly valuable tool for this type of analysis.