Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of ozone on ceramic membranes for application to secondary treated effluent

As the global warming and population growth in urbanized areas lead to pressures on the accessibility of potable water resources, water recycling is regarded as one of the most viable solutions in Australia and overseas. Recycling wastewater can help in relieving the demand on existing high quality potable water supplies while at the same time protecting remaining water sources from contamination. Among the different wastewater treatment processes to raise wastewater quality to a suitable standard for recycling, membrane filtration has become a common operation due to its ability to provide high quality water at high efficiency. Despite the wide spread application of membranes made of polymeric materials, membranes made instead from ceramic materials can be operated with lower maintenance and operational requirements because of their stronger mechanical structure, superior chemical durability and better physical strength. In practice, these translate to their ability to be operated under high temperature, pressure and pH condition without concern for compaction, delamination, damage or swelling of the membrane. Such benefits are known to offset the higher material cost of ceramics, but are also useful in water recycling where the membrane functions as a reliable barrier to water-borne pathogens. Meanwhile, the material robustness enables ceramic membranes to be operated in combination with more effective pretreatment options like ozonation.
Characteristic optimization of MWCNTs using MPCVD system

Microwave Plasma Chemical Vapor Deposition (MPCVD) method can be used to grow various kinds of diamond films and carbon nanotubes at various temperatures. However, it is usually only the hand-on experience that can be relied on to obtain the nearly satisfactory plasma in the MPCVD system. Therefore, this study set up the reflected power sensor as a reference parameter and used a CCD (Charge Coupled Device) to observe the plasma image. Manufacturing parameters, such as gas flow rate, input microwave power, working distance, deposition time, chamber pressure and substrate temperature, were all fixed to grow MWCNTs. The controlled adjustments, as the independent variables, are the positions of E-H tuner along x-axis and y-axis which directly affect the conditions of the plasma. In order to grow multiwalled carbon nanotubes (MWCNTs) of better quality with a self-assembled MPCVD system, the quality indexes of MWCNTs, which are the aspect ratio of MWCNTs and the ID/IG intensity ratio of the Raman spectrum of MWCNTs, were analyzed. With the established database, it is found that there exist the optimized positions of E-H tuner along x-axis and y-axis for growing MWCNTs of high quality. Moreover, we used PCA (Principle Component Analysis) method to analysis these data, and a relationship between manufacturing parameters was found.
Enhancing Hate Speech Detection in the Digital Age: A Novel Model Fusion Approach Leveraging a Comprehensive Dataset

In the era of digital communication, social media platforms have experienced exponential growth, becoming primary channels for information exchange. However, this surge has also amplified the rapid spread of hate speech, prompting extensive research efforts for effective mitigation. These efforts have prominently featured advanced natural language processing techniques, particularly emphasizing deep learning methods that have shown promising outcomes. This article presents a novel approach to address this pressing issue, combining a comprehensive dataset of 18 sources. It includes 0.45 million comments sourced from various digital platforms spanning different time frames. There were two models utilized to address the diversity in the data and leverage distinct strengths found within deep learning frameworks: CNN and BiLSTM with an attention mechanism. These models were tailored to handle specific subsets of the data, allowing for a more targeted approach. The unique outputs from both models were then fused into a unified model. This methodology outperformed recent models, showcasing enhanced generalization capabilities even when tested on the largest and most diverse dataset. Our model achieved an impressive accuracy of 89%, while maintaining a high precision of 0.88 and recall of 0.91.
Comparing simulated glacial climate and paleodata: A reexamination

Glacial sea surface temperatures (SSTs) simulated by an atmosphere-mixed layer ocean model are compared with those reconstructed by the Climate: Long-Range Investigation, Mapping, and Prediction (CLIMAP) Project using planktonic microfossils. Two methods of comparison are employed. The first is global and uses the subjectively analyzed (i.e., hand contoured, then digitized) data set published by CLIMAP. The second is restricted to only those discrete locations where the CLIMAP sediment cores were taken. Both methods indicate that many aspects of the reconstructed glacial SST changes are simulated reasonably well by the model, although there are areas of disagreement. The extent of the disagreement appears smaller when the SSTs are sampled at discrete locations, because the largest discrepancies occur in the subtropical Pacific where data are sparse. When examined separately for each ocean, the magnitude of the disagreement in low latitudes roughly corresponds to the magnitude of the uncertainties in SST estimation using planktonic microfossils, being largest in the Pacific and smallest in the Atlantic. Because the largest discrepancies occur where uncertainties in estimation are large, no clear determination of whether the climate model exaggerates or underestimates low-latitude climate sensitivity appears possible. Nonetheless, sampling at discrete locations may be the best procedure for evaluating climate model performance, because errors associated with extending analyses to data-void areas can be avoided and uncertainties associated with inadequate spatial sampling made more evident.
DNA‐Dependent DNA Polymerases

This unit presents characteristics and reaction conditions of the DNA‐dependent DNA polymerases, including E. coli DNA polymerase I and its Klenow fragment, T4 DNA polymerase, native and modified T7 DNA polymerase, phi29 DNA polymerase, Bst DNA polymerase, and Taq DNA polymerase. The unit also provides overviews of other classes of thermophilic DNA polymerases used in PCR applications (described fully in UNIT 15.1), and the rapidly expanding class of lesion‐bypass DNA polymerases that play a role in DNA damage repair. Curr. Protoc. Mol. Biol. 84:3.5. 1‐3.5. 19. © 2008 by John Wiley & Sons, Inc.
An Investigation into Spectral Efficiency Enhancement of Fiber-Optic Communication via High-Speed Spectrum Management

This research appears into the effectiveness of high-pace spectrum management as a way to beautify the spectral performance of fiber-optic conversation. that is finished by means of forecasting a dynamic optical visitors arrival pattern to reduce carrier-degree blocking off opportunity, and with the aid of allocating the maximum green bandwidth to every request based totally on a non-blocking priority-based totally scheduling algorithm. This study assesses the overall performance of modern-day systems, analyzes their shortcomings, and uses experimental consequences to evaluate their effectiveness for improving spectral efficiency. The findings endorse that there's ability for improvement in spectral efficiency with excessive-speed spectrum control.
Binary classification of running fatigue using a single inertial measurement unit

The popularity of running has increased in recent years. A rise in the incidence of running-related overuse musculoskeletal injuries has occurred parallel to this. This study investigates the capability of using data from a single inertial measurement unit (IMU) to differentiate between running form in a non-fatigued and fatigued state. Data was captured from an IMU placed on the lumbar spine, right shank and left shank in 21 recreational runners (10 male, 11 female) during separate 400m running trials. The trials were performed prior to and following a fatiguing protocol. Following stride segmentation, IMU signal features were extracted from the labelled (non-fatigued vs fatigued) sensor data and used to train both a Global and Personalised classifier for each individual IMU location. A single IMU on the Lumbar spine displayed 75% accuracy, 73% sensitivity and 77% specificity when using a Global Classifier. A single IMU on the Right Shank displayed 100% accuracy, 100% sensitivity and 100% specificity when using a Personalised Classifier. These results indicate that a single IMU has the potential to differentiate between non-fatigued and fatigued running states with a high level of accuracy.
Measuring plasma fatty acid oxidation with intravenous bolus injection of 3H- and 14C-fatty acid

Accurate measures of plasma FA oxidation can improve our understanding of diseases characterized by impaired FA oxidation. We describe and compare the 24 h time-courses of FA oxidation using bolus injections of [1-14C]palmitate versus [9,10-3H]palmitate under postabsorptive, postprandial, and walking conditions. Fifty-one men and 95 premenopausal women participated in one condition (postabsorptive, postprandial, or walking), one tracer (14C- or 3H-labeled), and an acetate or palmitate study. Groups were matched for sex, age, and body mass index (BMI). At 24 h, cumulative [3H]acetate recovery as 3H2O was 80 ± 6%, 78 ± 2%, and 81 ± 6% in the postabsorptive, postprandial, and walking conditions, respectively (not significant). Model-predicted maximum [1-14C]acetate recovery as expired 14CO2 was 59 ± 12%, 52 ± 8%, and 65 ± 10% in the postabsorptive, postprandial, and walking condition, respectively (one way ANOVA, P = 0.12). When corrected with the corresponding acetate recovery factors, 24 h time-courses of FFA oxidation were similar between [1-14C]palmitate and [9,10-3H]palmitate in all three conditions. In contrast to previous meal ingestion studies, an acetate-hydrogen recovery factor was needed to achieve comparable oxidation rates using an intravenous bolus of [3H]palmitate. In conclusion, intravenous boluses of [9,10-3H]palmitate versus [1-14C]palmitate gave similar estimates of 24 h cumulative FFA oxidation in age-, sex- and BMI-matched individuals.
A Mach-Zehnder Photonic MEMS Microphone with High Sensitivity, 1/F Noise Suppression, and Broadband Response

We propose a photonic MEMS microphone based on a fiber Mach-Zehnder interferometer (MZI) which optically transducers the membrane mounted at the end of a fiber under incident acoustics. As a result of the optical transduction, an outstanding sensitivity to weak acoustic waves is shown compared to commercial capacitive MEMS microphones. In addition, a flat noise spectrum with suppressed 1/f noise is demonstrated, which has been rarely reported before. It is also experimentally shown that the photonic MEMS microphone exhibits a broadband response from 20 Hz to 20 KHz, with the highest signal-to-noise ratio (SNR) up to 60.33 dB at 2 KHz. This is achieved using simple small-size photonic components without any amplification and processing circuits, showing its promising applications for high-sensitive sound detection.
Consistent Sampling and Reconstruction of Signals in Noisy UnderDetermined Case

We propose a sampling theorem that reconstructs a consistent signal from noisy under-determined samples. Consistency in the context of sampling theory means that the reconstructed signal yields the same measurements as the original ones. The conventional consistent sampling theorems for the underdetermined case reconstruct a signal from noiseless samples in a complementary subspace L in the reconstruction space of the intersection between the reconstruction space and the orthogonal complement of the sampling space. To obtain a good reconstruction result, one has to determine L effectively. To this end, we first extend the sampling theorem for a noisy case. Since the reconstructed signal is scattered in L, we propose to reconstruct a signal so that the variance is minimized provided that the average of the signals agrees with the noiseless reconstruction. Note that the minimum variance depends on the subspace L. Therefore, we next propose to determine L so that the minimum variance is further minimized in terms of L. We show that such L can be chosen if and only if L includes a subspace determined by the noise covariance matrix. By computer simulations, we demonstrate that there is a considerable difference between the minimum and non-minimum variance reconstructions.
Ionotropic Glutamate Receptors IR64a and IR8a Form a Functional Odorant Receptor Complex In Vivo in Drosophila

Drosophila olfactory sensory neurons express either odorant receptors or ionotropic glutamate receptors (IRs). The sensory neurons that express IR64a, a member of the IR family, send axonal projections to either the DC4 or DP1m glomeruli in the antennal lobe. DC4 neurons respond specifically to acids/protons, whereas DP1m neurons respond to a broad spectrum of odorants. The molecular composition of IR64a-containing receptor complexes in either DC4 or DP1m neurons is not known, however. Here, we immunoprecipitated the IR64a protein from lysates of fly antennal tissue and identified IR8a as a receptor subunit physically associated with IR64a by mass spectrometry. IR8a mutants and flies in which IR8a was knocked down by RNAi in IR64a+ neurons exhibited defects in acid-evoked physiological and behavioral responses. Furthermore, we found that the loss of IR8a caused a significant reduction in IR64a protein levels. When expressed in Xenopus oocytes, IR64a and IR8a formed a functional ion channel that allowed ligand-evoked cation currents. These findings provide direct evidence that IR8a is a subunit that forms a functional olfactory receptor with IR64a in vivo to mediate odor detection.
Generation of Synthetic Data for Medical Decision Support Applications

Computer vision has the potential to accelerate decision support in a variety of medical applications, but a paucity of high-quality, open-source datasets hinders the development of decision support applications for open medical environments (i.e., non-laparoscopic). Synthetic data holds promise as a solution for difficult-to-obtain data, such as images from high stress environments or complicated by privacy concerns associated with medical imagery. Modern applications of synthetic data generation such as digital twins (DT) can create high-fidelity and photo-realistic images the surpass traditional data augmentation practices. Moreover, synthetic data is cost-effective, efficient, and highly scalable after initial creation of the assets and environment. This study presents a framework to synthetically generate annotated images from digital 3-D assets in random perspectives and orientations for use in computer-vision (CV) for open medical applications. Datasets of 1,000 annotated synthetic images and 681 real-world images of six object classes were employed in a transfer learning toolkit for an experiment to determine the feasibility of utilizing synthetic data to train models on CV applications to augment or replace training with real-world data. The experiment tested model performance based on three datasets: 1. Synthetic data only; 2. Real-world data only; 3. Training with synthetic data for evaluation with real-world data. Results showed that training on synthetic data to evaluate real-world data met or exceeded the performance of training on real-world data in four of six classes within the datasets utilized. Results show promise for utilizing synthetic data as an alternative to costly, time consuming, and difficult to obtain data types with many areas for further study, such as more detailed and comprehensive environments and assets as well as methodology for noise injection to improve model performance.
Dissociable neural activity to self‐ vs. externally administered thermal hyperalgesia: a parametric fMRI study

Little is known regarding how cognitive strategies help to modulate neural responses of the human brain in ongoing pain syndromes to alleviate pain. Under pathological pain conditions, any self‐elicited contact with usually non‐painful stimuli may become painful. We examined whether the human brain is capable of dissociating self‐controlled from externally administered thermal hyperalgesia in the experimental capsaicin model. Using functional magnetic resonance imaging, 17 male subjects were investigated in a parametric design with heat stimuli at topically capsaicin‐sensitized skin. In contrast to external stimulation, self‐administered pain was controllable. For both conditions application trials without noticeable thermal stimulation were introduced and used as high‐level baseline (HLB) to account for the capsaicin‐induced ongoing pain and other covariables. Following subtraction of the HLB, the anterior insula and the anterior cingulate cortex (ACC) but not the somatosensory cortices maintained parametric neural responses to thermal hyperalgesia. A stronger pain‐related activity increase during self‐administered stimuli was observed in the posterior insula. In contrast, prefrontal cortex showed stronger increases to uncontrollable external heat stimuli. In the state of ongoing pain (capsaicin), pain‐intensity‐encoding regions (anterior insula, ACC) but not those with sensory discriminative functions (SI, SII) showed graded, pain‐intensity‐related neural responses in thermal hyperalgesia. Some areas were able to dissociate between self‐ and externally administered stimuli in thermal hyperalgesia, which might be related to differences in perceived controllability. Thus, neural mechanisms maintain the ability to dissociate external from self‐generated states of injury in thermal hyperalgesia. This may help to understand how cognitive strategies potentially alleviate chronic pain syndromes.
Glial fibrillary acidic protein as a brain injury biomarker in children undergoing extracorporeal membrane oxygenation*

Objective: To determine whether, in children, plasma glial fibrillary acidic protein is associated with brain injury during extracorporeal membrane oxygenation and with mortality. Design: Prospective, observational study. Setting: Pediatric intensive care unit in an urban tertiary care academic center. Patients: Neonatal and pediatric patients on extracorporeal membrane oxygenation (n = 22). Interventions: Serial blood sampling for glial fibrillary acidic protein measurements. Measurements and Main Results: Prospective patients age 1 day to 18 yrs who required extracorporeal membrane oxygenation from April 2008 to August 2009 were studied. Glial fibrillary acidic protein was measured using an electrochemiluminescent immunoassay developed at Johns Hopkins. Control samples were collected from 99 healthy children (0.5–16 yrs) and 59 neonatal intensive care unit infants without neurologic injury. In controls, the median glial fibrillary acidic protein concentration was 0.055 ng/mL (interquartile range, 0–0.092 ng/mL) and the 95th percentile of glial fibrillary acidic protein was 0.436 ng/mL. In patients on extracorporeal membrane oxygenation, plasma glial fibrillary acidic protein was measured at 6, 12, and every 24 hrs after cannulation. We enrolled 22 children who underwent extracorporeal membrane oxygenation. Median age was 7 days (interquartile range, 2 days to 9 yrs), and primary extracorporeal membrane oxygenation indication was: cardiac failure, six of 22 (27.3%); respiratory failure, 12 of 22 (54.5%); extracorporeal cardiopulmonary resuscitation, three of 22 (13.6%); and sepsis, one of 22 (4.6%). Seven of 22 (32%) patients developed acute neurologic injury (intracranial hemorrhage, brain death, or cerebral edema diagnosed by imaging). Fifteen of 22 (68%) survived to hospital discharge. In the extracorporeal membrane oxygenation group, peak glial fibrillary acidic protein levels were higher in children with brain injury than those without (median, 5.9 vs. 0.09 ng/mL, p = .04) and in nonsurvivors compared with survivors to discharge (median, 5.9 vs. 0.09 ng/mL, p = .04). The odds ratio for brain injury for glial fibrillary acidic protein >0.436 ng/mL vs. normal was 11.5 (95% confidence interval, 1.3–98.3) and the odds ratio for mortality was 13.6 (95% confidence interval, 1.7–108.5). Conclusions: High glial fibrillary acidic protein during extracorporeal membrane oxygenation is significantly associated with acute brain injury and death. Brain injury biomarkers may aid in outcome prediction and neurologic monitoring of patients on extracorporeal membrane oxygenation to improve outcomes and benchmark new therapies.
Pseudoalteromonas Bacteria Are Capable of Degrading Paralytic Shellfish Toxins

ABSTRACT Marine bacterial isolates cultured from the digestive tracts of blue mussels (Mytilus edulis) contaminated with paralytic shellfish toxins (PSTs) were screened for the ability to reduce the toxicity of a PST mixture. Seven isolates reduced the overall toxicity of the algal extract by ≥90% within 3 days. These isolates shared at least 99% 16S rRNA gene sequence similarity with five Pseudoalteromonas spp. Phenotypic tests suggested that all are novel strains of Pseudoalteromonas haloplanktis.
Calculation of Pore Scattering in Transparent Ceramics

Light scattering caused by pores detrimentally affects the optical transparency of transparent ceramics. Herein, Mie theory has been used to calculate the cross-section of pore scattering in transparent ceramics, and the influence of wavelength, pore size distribution and refractive index has been discussed in detail. For wavelength between 200 nm and 2000 nm, the scattering cross-section decreases with increasing wavelength, which means that pore scattering is more detrimental to short-wavelength transparency. With ZOLD function simulating the pore size distribution inside the ceramic, it has been found that the scattering is strongest when the most-probable diameter dm equals the incident light wavelength λ. And FWHM (full width at half maximum) parameter a also affects the scattering cross-section. a between 0.003 and 0.7 is necessary for obtaining high optical transparency in visible wavelength range. The method presented in this work is available for the estimation of scattering effect in different kinds of materials, which may be useful for future design of high-transparency ceramics.
Cooperative Coevolution with global search for large scale global optimization

To improve the performance of EAs on large scale numerical optimization problems, a number of techniques have been invented, among which, Cooperative Coevolution (CC in short) is obviously a promising one. But sometimes CC is easy to lead to premature convergence in large scale global optimization. In this paper, a Cooperative Coevolution Evolutionary Algorithm (CCEA in short) with global search (CCGS) is presented to handle large scale global optimization (LSGO) problems. The performance of CCGS is evaluated on the test functions provided for the CEC 2012 competition and special session on Large Scale Global Optimization. The experiment results show that this technique is more effective than CCEAs without global search.