Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-State Occupancy Model Estimates Probability of Detection of an Aquatic Parasite Using Environmental DNA: Pseudoloma neurophilia in Zebrafish Aquaria

ABSTRACT Detecting the presence of important parasites within a host and its environment is critical to understanding the dynamics that influence a pathogen's ability to persist, while accurate detection is also essential for the implementation of effective control strategies. Pseudoloma neurophilia is the most common pathogen reported in zebrafish (Danio rerio) research facilities. The only assays currently available for P. neurophilia are through lethal sampling, often requiring euthanasia of the entire population for accurate estimates of prevalence in small populations. We present a non-lethal screening method to detect P. neurophilia in tank water based on the detection of environmental DNA (eDNA) from this microsporidium, using a previously developed qPCR assay that was adapted to the digital PCR (dPCR) platform to complement current surveillance protocols. Using the generated dPCR data, a multi-state occupancy model was also implemented to predict the probability of detecting the microsporidium in tank water under different flow regimes and pathogen prevalence. The occupancy model revealed that samples collected in static conditions were more informative than samples collected from flow-through conditions, with a probability of detection at 80% and 47%, respectively. There was also a positive correlation between the frequency of detection in water and prevalence in fish based on qPCR.
Dissociable roles of theta and alpha in sub-second and supra-second time reproduction: An investigation of their links to depression and anxiety

The Striatal Beat Frequency model (Matell & Meck, 2004) suggests that multiple cortical oscillators contribute to human temporal cognition. Based on the theory, the current study examined the interactions between interval timing and neural oscillations, as predicted by timing deficits found in neuropsychiatric conditions. The interaction is predicted to manifest in frontal-midline theta and occipital alpha oscillations, which are two important cortical oscillatory sources engaged in working memory and time perception. Therefore, the main goal of the study is to examine how depression and anxiety modulate frontal-midline theta and occipital data during the encoding of sub- and supra-second intervals. In the current study, participants reproduced sub- (400, 600, 800ms) and supra-second (1600, 1800, 2000ms) intervals while they underwent scalp EEG recordings. Anxiety and depression levels were measured via self-report psychometrics. We found that higher levels of self-reported anxiety and depression were associated with shorter reproduction of lengths of durations. Further, time-frequency analysis of scalp EEG revealed a dissociation where state anxiety altered the links between frontal-midline theta power and sub-second interval reproduction, while depression and trait anxiety altered the association between occipital alpha power and supra-second interval reproduction. Our results suggest that anxiety and depression alter time perception, and this differentially relates to frontal-midline theta and occipital alpha as substrates for sub- and supra-second interval timing.
Immune cell regulation in stem cell niche contacting glioblastomas

Glioblastomas (GBM) are tumors for which immune-targeted therapies have failed to show clinical benefit and for which few biomarkers provide context for meaningful therapeutic stratification. Radiographic contact of GBM tumors with the lateral ventricle stem cell niche correlates with worse patient prognosis; however, the extent to which proximity to the ventricle impacts antitumor immunity remains unknown. We demonstrate that T cell checkpoint receptor expression is elevated in ventricle-contacting GBM as is the abundance of a specific, suppressive CD32+CD44+HLADhigh myeloid population suggesting a distinct immunoregulatory influence on antitumor immunity in proximity to the lateral ventricle. Phospho-specific mass cytometric profiling revealed extensively impaired immune signaling in ventricle-contacting GBM in response to inflammatory cytokine stimulation, further supporting a suppressive milieu influencing immunity at the lateral ventricle. Collectively, we identify a regulatory impact of ventricle contact on antitumor immunity in the brain, and reveal novel clinically targetable mechanisms of immunomodulation in patients with glioblastoma. Significance Statement We demonstrate that the immune microenvironment of glioblastoma tumors contacting the lateral ventricle differs from non-contacting tumors. This work connects immune-biology to a radiographically detectable feature, the lateral ventricle, and highlights non-invasive imaging as a means to identify targetable immune features in glioblastoma tumors.
Therapeutic resistance to FLT3 inhibition is driven by a novel ATM/mTOR pathway regulating oxidative phosphorylation

The bone marrow (BM) microenvironment has been shown to promote drug resistance in leukemic cells. In the present study, we demonstrate that BM stromal cells induce alterations in gene expression and signaling pathways in FLT3-dependent acute myeloid leukemia (AML) cells that impact the efficacy of FLT3-targeted therapy. Specifically, we discovered that restoration of mTOR signaling by BM stromal factors mediates protection of AML cells from apoptosis following FLT3 inhibition through increased expression and selective translation of oxidative phosphorylation transcripts. Addition of an mTOR inhibitor to FLT3-targeted therapy not only significantly reduced leukemic burden in the BM in vivo, but also prevented relapse. We further determined that ATM (ataxia-telangiectasia mutated) plays an essential role in BM stroma-mediated survival as a key upstream regulator of mTOR signaling. These studies reveal how the BM microenvironment promotes survival of AML cells in the face of FLT3 inhibition through maintenance of oxidative phosphorylation. SIGNIFICANCE Our results uncover a novel pathway activated by the BM microenvironment that provides protection of AML cells from therapeutic elimination following FLT3 inhibition. These studies identify candidates for combinatorial therapies designed to overcome the protective effects of BM and improve outcomes for AML patients.
Land use change through the lens of macroecology: insights from Azorean arthropods and the Maximum Entropy Theory of Ecology

Human activity and land management practices, in particular land use change, have resulted in the global loss of biodiversity. These types of disturbance affect the shape of macroecological patterns, and therefore analyzing these patterns can provide insights into how ecosystems are affected by land use change. We here use arthropod census data from 96 sites at Terceira Island in the Azores archipelago across four different land uses of increasing management intensity: native forest, exotic forest, semi-natural pasture, and intensive pasture, to examine the effects of land use type on three macroecological patterns: the species abundance distribution, the metabolic rate distribution of individuals, and the species–area relationship. The Maximum Entropy Theory of Ecology (METE) has successfully predicted these patterns across habitats and taxa in undisturbed ecosystems, and thus provides a null expectation for their shapes. Across these patterns, we find that the forest habitats are the best fit by METE predictions, while the semi-natural pasture is consistently the worst fit, and the intensive pasture is intermediately well fit. We show that the direction of failure of the METE predictions at the pasture sites is likely due to the hyper-dominance of introduced spider species present there. We hypothesize that the particularly poor fit for the semi-natural pasture is due to the mix of arthropod communities out of equilibrium, leading to greater heterogeneity in composition and complex dynamics that violate METE’s assumption of static state variables. The comparative better fit for the intensive pasture plausibly results from more homogeneous arthropod communities that are well adapted to intensive management, and thus whose state variables are less in flux. Analyzing deviations from theoretical predictions across land use type provides useful information about how land use and disturbance affect ecosystems, and such comparisons could be useful across other habitats and taxa.
Behaviour-based Malware Detection in Mobile AndroidPlatforms Using Machine Learning Algorithms

During the last few years, several approaches have been proposed for detection of Android malware Apps, each usually using its own dataset. Generating a representative Android malware dataset to evaluate malware detection approaches is a challenging task. Recently, the Canadian Institute for Cy-bersecurity released the CICAndMal2017 dataset, which includes recent and sophisticated Android samples spanning between ﬁve distinct categories: Adware, Ransomware, SMS malware, Scareware, and Benign. The best classiﬁcation result obtained for this dataset was with a Precision of 95.3%, achieved with the Random Forest algorithm, using Permissions and Intents as static features. In this paper, we investigate the usage of nine machine learning algorithms to classify malware in the above mentioned dataset. The comparison of the obtained results is performed with the ones obtained with Random Forest, including performance evaluation (in terms of Precision, Recall, F-Measure, and Accuracy) and resource usage (in terms of execution time and CPU and memory consumption). Besides, we also investigate the use of a non-sliding Bag of System Calls algorithm with the above mentioned machine learning algorithms. It is shown that the Adaboost algorithm, using the Random Forest as a base estimator, leads to the best classiﬁcation results with an Accuracy of 98.24%, a Precision of 99.31% (for malware), and an F1-Measure of 95.05% (for malware), at the cost of a larger execution time than Random Forest.
Impacts of Corporate Network Building and Strategic Learning for Environmental Management on Business Performance

This study discovered the effects of strategic learning and network building on a company’s environmental management performance. According to the results, the environmental awareness of the company and competition threats within the industry did not significantly affect the establishment of environmental strategy, whereas the consumer's sensitivity to the environment and the environmental regulation of the government did. The environmental awareness of the company and the consumer's sensitivity to the environment were found to greatly impact a company’s network building. which is closely related with the utilization of multimedia system and technology. In addition, it was found that the establishment of corporate environmental strategy had a significant effect on network building and strategic learning, but network building did not significantly affect strategic learning, indicating a difference. Finally, corporate strategic learning affected environmental management performance, suggesting an importance in accumulating strategic learning capabilities to increase environmental management performance.
ADAPTIVE MODULATION FOR COGNITIVE RADIO

This thesis examines the benefits of using adaptive modulation in terms of spectral efficiency and probability of bit error for cognitive radio networks. In channels that fluctuate dynamically over time, systems that are based upon the conventional methods of fixed modulation formats do not perform well. Adaptive modulation provides many parameters that can be adjusted relative to the channel fading, including data rate, transmit power, instantaneous BER, symbol rate, and channel code rate or scheme. In this thesis, a systematic study on the increase in spectral efficiency obtained by optimally varying combinations of the modulation formats for a cognitive radio is provided. It has been assumed, that the transmitter has a perfect knowledge of the channel conditions and the resulting adaptive modulation system is subject to an average BER constraint. Simulations show how adaptively changing the modulation schemes improves the performance of the system by meeting a BER constraint over a range of SNR. This thesis also walks through the basic concepts of cognitive radio including its definition and operation. Various techniques of sensing the electromagnetic spectrum for finding possible vacant bands of frequency and the challenges faced therein have also been discussed.
Mucormycosis - The black menace in COVID-19

The current outbreak of second wave of COVID-19 in India has seen the rise of opportunistic infections, a deadly one being mucormycosis or “black fungus. ” As of now, there are over 9000 cases of this deadly disease which have been reported from several states in India. Nine states in India including Punjab, Uttar Pradesh, Rajasthan, and Bihar have declared mucormycosis as an epidemic. There are five types of mucormycosis – rhino-orbital-cerebral, pulmonary, gastrointestinal, cutaneous, and disseminated. Out of these, rhino-orbital-cerebral and pulmonary mucormycoses are most common in post-COVID patients. The clinical presentation of such patients include cough, fever, breathlessness, chest pain, sinusitis, pain on one side of the face with lack of sensation and proptosis of eye. Diagnosis could be done through analysis of clinical findings, direct microscopy, serum antigen tests, culture, histopathology, radio imaging, and polymerase chain reaction/matrix-assisted laser desorption ionization time-of-flight. Treatment will include preventive measures taken at home or at hospital for post-COVID patients. Medical treatment of mucormycosis mainly includes installing a central catheter (line), maintaining adequate systemic hydration, and infusion of normal intravenous saline before antifungal amphotericin B infusion. Since amphotericin is nephrotoxic, alternative drugs, such as posaconazole or isavuconazole, can be suggested. Adjuvant therapy with caspofungin, deferasirox, statins, aspirin, and hyperbaric oxygen may have to be considered as well. Extensive surgical debridement can also be suggested to remove all necrotic tissues. This review emphasizes the different aspects of mucormycosis such as epidemiology, etiopathogenesis, risk factors, diagnosis, preventive measures, and treatment strategies that can be adopted to tackle this fungal menace in COVID-19.
An Analysis of Effective Factors in Public Awareness Campaigns through Facebook: Focus on Fine Dust Issues

In this study, we analyzed the factors that affect public awareness campaigns on social media platforms and developed an integrated model for measuring the persuasiveness of environmental social media campaigns. A survey questionnaire was created and distributed on Facebook with the goal of reaching individuals in their 20s and 40s in Vietnam, and 395 valid replies were gathered. The findings showed that the STOPS was reconfirmed as a suitable theoretical framework for analyzing the public's behaviour intention to conduct information related to the issue of fine dust, especially on social media. Furthermore, it also showed that social media efficacy has a moderating effect on the relationship between public’s situational recognition and informational behaviour intention. This suggested that through social media platforms, personal characteristics play a vital part in developing effective environmental campaigns. Implications for both theory and practice were discussed.
Bio-Fermentation Improved the Nutritional Values of Chromolena odorata Utilization as Bali Cattle Feed Source

Objectives: The aims of this study were to analyze the effects of bio-fermentation of C/N30 ratio using different soluble rates of carbohydrate sources on in vitro physical quality, nutrition, anti-nutrient, digestibility, NH3 and VFA rumen fluid of Chromolaena odorata silage. Method: A Completely Randomized Design with 3 treatments and 6 replications was used in this study. The treatments were: (CO30_GC): CO with C/N30 of liquid palm sugar + 10% rumen content; (CO30_PTK): CO with C/N30 of palm pith flour or putak flour (Corypha gebanga) + 10% rumen content; (CO30_JP): CO with C/N30 of rice straw flour + 10% rumen content. Providing liquid palm sugar as carbohydrate source increased the physical quality of Chromolaena odorata silage (color, odor, pH texture, presence of fungus) compared with the other treatments. Results: There were an increased (P < 0.01) in feed composition, dry matter digestibility, organic matter digestibility, pH, NH3 concentration, VFA concentration, tannin content, but lower saponin and lower crude fiber compared with the other treatments when rice straw flour was added to the Chromolaena odorata. Conclusion: This study demonstrated that bio-fermentation during 21 days is better when adding rice straw flour as carbohydrate source with a C/N30 ratio to increase the utilization Chromolaena odorata as animal feed. However, if using other digestible carbohydrates sources then it is better biofermentation just before 21 days.
Insights on electric vehicle adoption: Does attitude play a mediating role?

Vehicles are classified as a mobile source of pollution worldwide. This problem is compounded in countries like India, where the population is enormous, and the number of automobiles increases quickly. To overcome this issue, governments and individuals must adopt electric vehicles and maximize the use of eco-friendly vehicles. However, the adoption of electric vehicles in India is gradual. One of the reasons is the attitude towards traditional and electric vehicles. This study’s primary objective is to determine how attitude influences the adoption of electric vehicles. The topic is vital since the attitude provided by numerous studies influences the intention to buy anything. This study considered one dependent variable (electric vehicle adoption) and one mediating variable (attitude) along with five independent variables. The data collection method was straightforward, and the sample size was 366 respondents. Exploratory factor analysis (EFA), structural equation modeling (SEM), and mediation analysis were used to analyze the data. All adopted constructs were trustworthy, with average variance extracted exceeding 0.55, composite reliability exceeding 0.75, and factor loadings exceeding 0.70 for most. The model fit indices were also found to be significant on several parameters. Among all other variables, only financial incentives affect electric vehicle adoption. In other circumstances, opinions did not influence customer uptake of electric vehicles.
The Instrumentation and Flight Testing of a Rotorcraft Vehicle for Undergraduate Flight Control Research

The University of Texas at San Antonio Control, Computation, and Cybernetics Laboratory has recently began an Undergraduate Researchers Control Program with the goal of recruiting, training, and retaining talented undergraduate students and exposing them to projects which reinforce their knowledge of control and system theory. The objective of this paper is to present the current results in the development and instrumentation of the Raptor 90 remote-controlled helicopter which is part of the Undergraduate Researchers Control Program. This paper will present the overall approach to down selecting, constructing, flight-testing, and outfitting a remote controlled helicopter for undergraduate flight control research. For the research currently being investigated at the C3 Laboratory, the Raptor 90 made by Thunder Tiger was selected for its relatively low price, large payload, and affordable maintenance. The construction of the Raptor 90 had to be weighed against financial constraints. The basic Raptor 90 Airframe already has a very aggressive flight envelope, yet by upgrading a series of Raptor 90 parts, the performance envelope was increased. Flight training for the Raptor 90 was performed by extensive flight time on the RealFlight G3 flight simulator. A Dynamic Testbed was built at the C3 Laboratory for both static and limited range hover testing during the initial flight testing of the Raptor 90. A flight test program was initiated for data collection and analysis of the Raptor 90. The Raptor 90 was instrumented with the Crossbow MicroNav IMU System and Stargate Processing Board. The Stargate allows the Raptor 90 to communicate wirelessly back to a base station and provide telemetry data of the Raptor 90’s states. Finally, by using a nonlinear MATLAB Simulation of the Raptor 50 that was modified for the Raptor 90, a pseduospectral open loop controller was implemented.
Comment on gmd-2021-422

Efficient improved the Abstract (L20): “This approach was tested on the newly-implemented migration module of the state-of-the-art DGVM LPJ-GM, focusing on European forests. ”, and in the Introduction (L120): “In this study, we present an efficient uncertainty assessment of model selection and parameter estimates for the newly-implemented migration module of LPJ-GM. We focus our assessment on European forests as estimates of migration rates from paleo-records are available for most major European tree taxa (see Sect. 2.1). ”
Review of Commercially Available Supraglottic Airway Devices for Prehospital Combat Casualty Care.

BACKGROUND Airway obstruction is the second leading cause of potentially survivable death on the battlefield. The Committee on Tactical Combat Casualty Care lists airway optimization among the top 5 battlefield research and development priorities; however, studies show that combat medics lack access to the recommended supraglottic airway (SGA) devices. SGA devices are an alternative airway management technique to endotracheal tube intubation. Reports have shown SGA devices are easier to use and take fewer attempts to provide patent airflow to the patient when compared to endotracheal tube intubation. Military settings require a higher degree of skill to perform airway management on patients due to the environment, limited availability of equipment, and potential chaos of the battlefield. Finding the optimal SGA device for the military setting is an unmet need. The International Organization for Standardization describes basic functional requirements for SGA devices, as well as patient configurations and size limitations. Beyond that, no SGA device manufacturer states that their devices are intended for military settings. MATERIALS AND METHODS We conducted a market review of 25 SGA devices that may meet inclusion into the medics' aid bag. The company's official "Instructions for Use" document, Google Scholar, and FDA reports were reviewed to obtain information for each SGA device. RESULTS Twenty-five commercially available SGA devices are explored from manufacturer online sources. A commercially available device list is shown later in this paper, which provides the device's features, indications, and contraindications based on the manufacturer's product information documentation. CONCLUSIONS There are a variety of devices that require further testing to determine whether they should be included in sets, kits, and outfits.