Miracle-dz/UniFAR-FTUs huggingface dataset:
Occurrence and ingestion of microplastics by zooplankton in Kenya's marine environment: first documented evidence

Microplastics can be ingested by marine organisms and may lead to negative impacts at the base of marine food chains. This study investigated the occurrence and composition of microplastics in the sea-surface water and sought evidence of ingestion by zooplankton. Surface seawater was collected using a stainless-steel bucket and sieved directly through a stainless-steel sieve (250-µm mesh), while a 500-μm mesh net was towed horizontally to collect zooplankton, at 11 georeferenced stations off the Kenyan coast in February 2017, on board the national research vessel RV Mtafiti. Microplastic particles were sorted and characterised using an Optika dissecting microscope. Polymer types were identified using an ALPHA Platinum attenuated total reflection—Fourier-transform infrared (ATR-FTIR) spectrometer. A total of 149 microplastic particles, with an average abundance of 110 particles m–3, were found in the surface seawater. A total of 129 particles were found ingested by zooplankton groups, where Chaetognatha, Copepoda, Amphipoda and fish larvae ingested 0.46, 0.33, 0.22 and 0.16 particles ind. –1, respectively. Filaments dominated both the surface-water microplastics and the ingested microplastics, contributing 76% and 97% to those compositions, respectively. White particles were prevalent in the water (51%), whereas black was the colour found most commonly (42%) across the zooplankton groups. The sizes of particles that were in the water were in the range of 0.25–2.4 mm, and those ingested ranged between 0.01 and 1.6 mm. Polypropylene was predominant in the surface water, whereas low-density polyethylene was the most-ingested polymer type. The results provide the first documented evidence of the occurrence, composition and ingestion of microplastics by zooplankton in Kenya's marine environment, indicating that microplastics have the potential to enter pelagic food webs and cause pollution in the study area.
Insights into the molecular regulation of growth and carbon flux in marine diatoms

Author(s): Abbriano Burke, Raffaela | Advisor(s): Hildebrand, Mark | Abstract: Diatoms are a highly productive group of phytoplankton collectively responsible for up to 40% of the annual organic carbon production in the world’s oceans. Photosynthetic carbon fixation by diatoms sustains diverse marine ecosystems and contributes significantly to the global carbon cycle. The natural productivity of diatoms, coupled with high hydrocarbon yield, makes this group an attractive option for the production of next-generation biofuels and other valuable bioproducts. The need for a renewable alternative to fossil fuels has recently become apparent due to the environmental and political costs of petroleum production, including the inevitability of peak oil, the costs of obtaining foreign fuel sources, and rising atmospheric CO2 levels that exacerbate climate change. However, an increased understanding of the molecular mechanisms that control intracellular carbon partitioning in diatom cells is critical to develop successful strategies to optimize future production strains. Our current understanding of the organization and regulation of carbon metabolism in diatoms relies heavily on genomic information from a few model species. However, recent advancements in ‘omics’ analyses are expanding our understanding the dynamics of diatom metabolism based on gene expression, protein abundance, and metabolite levels. Despite increasing accessibility to these strategies, much remains to be understood about the molecular mechanisms and their regulation that underlie diatom growth productivity. Therefore, the broad objective of my dissertation is to gain further insight into the controls of intracellular carbon assimilation, partitioning, and storage in diatoms. This will be accomplished using several different approaches: a bioinformatics refinement of gene models and analysis of splicing during diatom cell cycle arrest and progression (Chapter 1), an investigation into the organization of proteins involved in photorespiratory metabolism (Chapter 2), and an investigation of the influence of a regulatory protein (6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase) on intracellular carbon partitioning (Chapter 3).
Discovery of Natural Phenol Catechin as a Multitargeted Agent Against SARS-CoV-2 For the Plausible Therapy of COVID-19

The global pandemic crisis, COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed the lives of millions of people across the world. Development and testing of anti-SARS-CoV-2 drugs or vaccines, are not turned to be realistic in the timeframe needed to combat this pandemic. Thus, rigorous efforts are still ongoing for the drug repurposing as a clinical treatment strategy to control COVID-19. Here we report a comprehensive computational approach to identify the multi-targeted drug molecules against the SARS-CoV-2 proteins, which are crucially involved in the viral-host interaction, replication of the virus inside the host, disease progression and transmission of coronavirus infection. Virtual screening of 72 FDA approved potential antiviral drugs against the target proteins: Spike (S) glycoprotein, human angiotensin-converting enzyme 2 (hACE2), 3-chymotrypsin-like cysteine protease (3CLpro), Cathepsin L, Nucleocapsid protein, RNA-dependent RNA polymerase (RdRp) and nonstructural protein 6 (NSP6) resulted in the selection of seven drugs which preferentially binds to the target proteins. Further, the molecular interactions determined by MD simulation, free energy landscape and the binding free energy estimation, using MM-PBSA revealed that among 72 drug molecules, catechin (flavan-3-ol) can effectively bind to 3CLpro, Cathepsin L, RBD of S protein, NSP-6, and Nucleocapsid protein. It is more conveniently involved in key molecular interactions, showing binding free energy (ΔGbind) in the range of -5.09 kcal/mol (Cathepsin L) to -26.09 kcal/mol (NSP6). At the binding pocket, catechin is majorly stabilized by the hydrophobic interactions, displays ΔEvdW values -7.59 to -37.39 kcal/mol. Thus, the structural insights of better binding affinity and favourable molecular interaction of catechin towards multiple target proteins, signifies that catechin can be potentially explored as a multitargeted agent in the rational design of effective therapies against COVID-19.
The Influence of Extrafloral Nectaries on Arboreal Ant Species Richness in Tree Communities

Studies investigating the role of resource availability in the species richness patterns can elucidate ecological processes and contribute to conservation strategies. In this study, we test two hypotheses: i) arboreal ant species richness increases with abundance of extrafloral nectaries-bearing trees; and ii) arboreal ant species richness increases with the diversity of extrafloral nectaries-bearing trees. We used data of ant sampling and tree inventories from 30 plots of Brazilian Cerrado. Arboreal ant species richness was positively influenced by the proportional abundance of extrafloral nectaries-bearing trees, total tree density and total tree diversity. There was no effect of species richness of extrafloral nectaries-bearing trees. Coefficient of determination of proportional abundance of extrafloral nectaries-bearing trees was larger when compared to coefficient obtained using tree density as explanatory variable. These results suggest that variation in arboreal ant species richness is better explained by extrafloral nectaries-bearing tree abundance than total tree density. Generalist foraging behavior of sampled ant species may explain their association with proportional abundance of extrafloral nectariesbearing trees and their non-significant relation with proportional richness of extrafloral nectaries-bearing tree species. Extrafloral nectaries-bearing trees abundance may be a specific estimate of the amount of food resource available in plots. Thus, this is a more specific way to quantify which resources may explain variation of the arboreal ant species richness in tree communities. We hope these results will be helpful to understanding the local variation in ant species richness and as criteria to biodiversity conservation.
Sudden death and hypertrophic cardiomyopathy: A review.

Hypertrophic cardiomyopathy is a genetic disease that affects the cardiac sarcomere, resulting in myocardial hypertrophy and disarray. Affected patients have a predisposition for malignant ventricular tachyarrhythmias and, consequently, sudden cardiac death. With the availability of therapeutic measures that prevent sudden death, the identification of high-risk patients is now of greater importance. The clinical electrophysiological study is of limited use for stratifying these patients. More recently, increased attention has been given to the degree of echocardiographically documented left ventricular hypertrophy and prognostically significant genetic mutations. Once a high-risk patient is identified, prophylactic treatment is warranted. Tools are now available to identify and treat high-risk patients with hypertrophic cardiomyopathy
Use of highway culverts by the water opossum (Chironectes minimus) in southeastern Brazil

Abstract The water opossum (Chironectes minimus) is a semi-aquatic mammal that is infrequently sampled in Atlantic rainforest areas in Brazil. Here we report on new records of C. minimus in the state of São Paulo, southeastern Brazil, and comment on its behavior and ecology. We placed nine camera traps in culverts and cattle boxes under a highway, between 2017 and 2019. From a total of 6,750 camera-trap-days, we obtained 16 records of C. minimus (0.24 records/100 camera-trap-days) in two cameras placed in culverts over streams. Most of the records were made between May and August, in the dry season and in the first six hours after sunset. The new records are from a highly degraded area with some riparian forests. The records lie approximately 30 km away from the nearest protected area where the species is known to occur. We suggest that C. minimus has some tolerance to degraded habitats, as long as the water bodies and riparian forests are minimally preserved. The new records presented here also fill a distribution gap in western São Paulo state.
Heterogeneous Real-Time Co-Emulation for Communication-Enabled Global Control of AC/DC Grid Integrated With Renewable Energy

The information, and communication technologies (ICTs) are increasingly merging with the conventional power systems. For the design, and development of modern AC/DC grids with integrated renewable energy sources, the system-level control schemes with ICTs involved should be evaluated in a co-simulation framework. In this work, a heterogeneous hardware real-time co-emulator composed of FPGAs, many-core GPU, and multi-core CPU devices is proposed to study the communication-enabled global control schemes of hybrid AC/DC networks. The electromagnetic transient (EMT) power system emulation is conducted on the Xilinx FPGA boards to provide nearly continuous instantaneous waveforms for cyber layer sampling; the communication layer is simulated on the ARM CPU cores of the embedded NVIDIA Jetson platform for flexible computing, and programming;, and the control functions for modular multi-level converters are executed on GPU cores of the Jetson platform for parallel calculation. The data exchange between FPGAs, and Jetson is achieved via the PCI express interface, which simulates the sampling operation of the AC phasor measurement unit (PMU), and DC merging unit (DC-MU). The power overflow, and DC fault cases are investigated to demonstrate the validity, and effectiveness of the proposed co-emulation hardware architecture, and global control schemes.
An Artificial Swan Formation Using the Finsler Measure in the Dynamic Window Control

This paper studies the swarm formation control for a large number of unmanned robots (artificial swans) to expel invading objects (geese) in applications such as airport bird control. This control algorithm extends the existing DWA (Dynamic Window Algorithm) control by inserting a new term using the Finsler measure in the objective function during the optimization process. As demonstrated and proven with the simulation section and derivation in the appendix, the Finsler measure can gauge the degree of local collaboration among unmanned robots and therefore allow us to form a statistical collaboration strategy to control a swarm formation to expel invading objects. It also allows fast optimization and therefore real-time formation control of a large number of robots without seeing the robots to collide with each other or with obstacles along their moving path, because the new term in the objective function allows the trade-off between swan group moving speed and its group watch-out coverage. Our performance evaluation and analysis of different performance metrics via simulations demonstrate the feasibility of this control algorithm.
Quality analysis and popularization on Turbo brunneus meat pickle

Mollusks have been recognized as a seafood of high nutritive value and good delicacy. A pickle was prepared from Turbo brunneus. This study designed to prepare pickle from two different oils using underutilized mollusks resource. The study was conducted for a period of 7 days. Results indicated that pickle prepared from groundnut oil showed better quality compared to pickle prepared from mustard oil. The present work also demonstrated to popularize the T. brunneus pickle using small amounts of ingredients.
Investigating Frequency Scaling, Nonvolatile, and Hybrid Memory Technologies for On-Chip Routers to Support the Era of Dark Silicon

In the era of dark silicon, several components on the chip [i.e., cores, memory, and network on chip (NoC)] need to be powered-off or run in low-power mode. This is mainly due to the increased leakage power consumption at smaller technology nodes. Other than the power consumed by cores and caches, power and performance of the interconnects is a significant factor as the communication network consumes a considerable share of the power budget. In particular, the buffers used at every port of the NoC router consume considerable dynamic as well as static power. To support dark silicon and save energy, a popular approach is to power off the routers and wake them up when needed. However, this affects the packet latency, and we need to observe the traffic through the nodes to decide turning the routers ON–OFF. In this article, we propose to keep the routers always powered ON to maintain constant connectivity and investigate various approaches. One proposal is to frequency scale the routers connected to powered OFF nodes, and the other proposals are to use a combination of SRAM and nonvolatile spin-transfer torque random access memory-based VCs in the routers. By managing which VCs to be active at a given time, we achieve energy savings. The proposals are evaluated by varying the percentage of dark nodes on the chip. The experimental results show that all proposals yield significant energy savings while maintaining connectivity.
Multilokales Leben von Studierenden in Karlsruhe

Fur ein Studium verlassen viele junge Menschen ihr Elternhaus, wobei sie haufig dort noch uber ein Zimmer verfugen und somit multilokal leben. Die Ergebnisse einer Befragung von Studierenden des Karlsruher Instituts fur Technologie zeigen, dass immerhin ein Viertel der Befragten mit einem Zweitwohnsitz am Studienort auch im Melderegister als Multilokale zu erkennen ist. De facto halt sich aber rund ein Drittel wahrend der vorlesungsfreien Zeit hauptsachlich nicht am Studienort auf. Wahrend des Studiums verschiebt sich der Anteil derjenigen, die ein multilokales Leben praktizieren, zunehmend zugunsten derer, die sich ausschlieslich am Studienort aufhalten. Dies schlagt sich auch in den Besuchsrhythmen am elterlichen Wohnort nieder, was auf eine kontinuierliche Ablosung vom elterlichen Umfeld hinweist. Eine raumliche Konzentration der Multilokalen in der Nahe der Hochschule fuhrt zu typischen Nutzungsmustern in diesen Quartieren.
Automatic Method to Identify E-Learner Emotions Using Behavioral Cues

In this article, we offer and test a nonsurvey-based method to characterize learner emotions. Our method, instead of using surveys, uses logs of learner behaviors in learning management systems (LMS) to reason about the emotional state of the e-learner. We use the control value theory (CVT) as the theoretical base of measuring emotions. Using this theory, learner emotions are directly tied to their achievements. We develop two fuzzy inference systems, one to measure academic self-efficacy (ASE), that we call ASEMEL, and another to measure task value, TAVAMEL. These two factors, according to the CVT, can identify the prospective outcome emotions in a learning environment. We conducted our experiment in an LMS with a sample of 30 students and validated the performance of our nonsurvey-based systems by comparing the results with the measures of an equivalent survey-based method. Finally, by linking our ASEMEL and TAVAMEL results, our system anticipated “hopelessness,” “anticipated relief” and “no emotion” with 97% accuracy, “hope/anxiety” with 77% accuracy, and “anticipatory joy” with 87% accuracy compared with the self-reports of the students.
Haemophilus, Antibiotic Therapy and the Airway Microbiome in Chronic Obstructive Pulmonarydisease

Chronic obstructive pulmonary disease (COPD) is a smoking-related illness affecting 64 million people worldwide. Airway infection drives recurrent exacerbations and lung function decline. Prophylactic antibiotics may prevent exacerbations but their use is a significant cause of population antimicrobial resistance. We characterised the sputum microbiome by 16S rRNA gene analysis using 138 samples collected during a randomised controlled trial of prophylactic antibiotics in 71 patients with stable COPD. On comparing the profile of the microbiome obtained by sequencing to the isolates grown from samples using standard culture, there were similarities overall, although with a much narrower spectrum of genera on culture with under-representation of certain genera including Veillonella and Prevotella. There was concordance in the most abundant genera within samples and the number of isolates cultured reflected the measured bacterial diversity. We found that at baseline the microbiota of 17 (24%) patients were dominated by Haemophilus influenzae, accompanied by narrowed microbial diversity and higher levels of sputum inflammatory cytokines. Different H. influenzae strains co-existed within individuals. Opportunistic whole genome sequencing of six H. influenzae isolates obtained during the study revealed that all were non-typeable H. influenzae (NTHI), with a range of different antibiotic resistance gene profiles, but an identical complement of virulence genes. Administration of 13 weeks prophylaxis with moxifloxacin, azithromycin or doxycycline revealed distinctive changes in microbial communities for each group. Haemophilus numbers reduced by 90% compared to placebo only after moxifloxacin, and significant reduction in sputum cytokines occurred in patients dominated by Haemophilus at baseline. Haemophilus influenzae dominance defines COPD patients with active disease who may particularly benefit from antibiotics or vaccination.
“Emotions are the Great Captains of Our Lives”: Measuring Moods Through the Power of Physiological and Environmental Sensing

The article proposes the use of a smartwatch-based system for measuring the emotions of individuals in a classroom setting with respect to five mood variables: Activation, Tiredness, Pleasance, Quality of Presentation and Understanding. Internal (body) and external (environment) data such as movement, heart rate, noise, temperature and humidity were collected through the built-in sensors of the smartwatch. The system was verified by means of a longitudinal study that has been carried out in a series of workshops and lectures. Through experience-based sampling, participants were polled at periodic time intervals asking them to enter a self-assessment of the aforementioned mood states directly on the smartwatch. The goal was to demonstrate whether sensor data can be used to effectively predict the five moods. By resorting to a machine learning approach our system was able to predict the moods with an accuracy ranging between 89-95 percent for single-output classification, 92-99 percent for the chain classification task and of approximately 93 percent for the multi-output analysis. Our results showed also that body signals are better predictors compared to the external environmental variables. These results demonstrate and verify the potential of smartwatches in collecting and predicting human emotions, enabling dynamic feedback loops to enhance user experience.
Sparse Blind Deconvolution Method for Wall Parameters Estimation

The information of wall parameters is very important for the imaging performance of through-the-wall radar imaging (TWRI). The existing estimation methods usually require the calibration procedure to ensure the accuracy of the estimated wall parameters. To avoid the time-consuming calibration procedure, a sparse blind deconvolution method for wall parameters estimation is proposed in this letter. The proposed method uses the time-delay-only estimation (TDOE) strategy with the hybrid bistatic–monostatic measurement configuration to retrieve the unknown thickness, relative permittivity, and conductivity of the wall. In the estimation process, the sparse blind deconvolution algorithm is developed to retrieve the time delays of echoes reflected from the wall. The proposed sparse blind deconvolution method can precisely extract the time delays of echoes in the time domain without the calibration procedure to obtain the shape of the transmitted pulse and the frequency response of the antennas. The estimation results from the full-wave synthetic data have shown that the proposed method can also improve the estimation accuracy of the wall parameters.
Carboxymethyllysine and carboxyethyllysine in multiple sclerosis patients

Introduction: Advanced glycation end-products (AGE) are involved in the pathogenesis of many diseases, including neurodegenerative diseases such as multiple sclerosis (MS). The aim of the study was to evaluate the intensity of the protein glycation process in patients with multiple sclerosis and its possible involvement in disease activity. Material and methods: The study group (n = 45) consisted of patients suffering from MS, and the control group (n = 31) consisted of healthy adults. Concentrations of selected glycation markers such as carboxymethyllysine (CML) and carboxyethyllysine (CEL) in sera of patients with MS and healthy volunteers were determined by enzyme-linked immunosorbent assay (ELISA). Results: Serum CML and CEL concentrations in patients with MS were higher than in healthy volunteers but only for CML the difference was statistically significant. CML concentrations positively correlated with CEL concentrations only in the healthy persons. In MS patients the serum CML and CEL concentrations did not differ significantly depending on the duration of the disease and depending on the EDSS (Expanded Disability Status Scale) score. Conclusions: Multiple sclerosis is accompanied by an intensification of protein glycation processes, especially within the pathways leading to the formation of carboxymethyllysine. The duration of the disease and the degree of motor impairment do not appear to affect the progression of the glycation processes. However, the disease process associated with multiple sclerosis may affect the relationship between CML and CEL concentrations.