Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of Soybean Meal Fermentation for Aqua-Feed with Bacillus subtilis natto Using the Response Surface Methodology

This study aimed to improve the nutritional value of soybean meal (SBM) by solid-state fermentation (SSF) using Bacillus subtilis natto (B. s. natto) to overcome the limitations of SBM usage in aquafeed. The response surface methodology (RSM) was employed to explore the relationships of fermentation conditions, such as temperature, time, water-substrate ratio, and layer thickness, on the degree of protein hydrolysis (DH) and the crude protein (CP) content. The optimum conditions for achieving the higher DH (15.96%) and CP (55.76%) were 43.82 °C, 62.32 h, 1.08 of water-substrate ratio, and a layer thickness of 2.02 cm. CP and DH in the fermented soybean meal (FSM) increased by 9.8% and 177.1%, respectively, and crude fiber decreased by 14.1% compared to SBM. The protein dispersibility index (PDI) decreased by 29.8%, while KOH protein solubility (KPS) was significantly increased by 17.4%. Flavonoids and total phenolic acid content in FSM were increased by 231.0% and 309.4%, respectively. Neutral protease activity (NPA) also reached a high level (1723.6 U g−1). Total essential amino acids (EAA) in FSM increased by 12.2%, higher than the 10.8% increase of total non-essential amino acids (NEAA), while the total free amino acids content was 12.76 times higher than that of SBM. Major anti-nutritional factors in SBM were significantly reduced during the process, and almost all SBM protein macromolecules were decomposed. Together with the cost-effectiveness of SSF, B. s. natto-fermented SBM products have great potential to improve the plant composition and replace high-cost ingredients in aquafeed, contributing to food security and environmental sustainability.
Effect of laser diode phase noise on coherent sensing systems

The laser frequency noise is of crucial importance in coherent sensing applications. Indeed, the frequency noise of a laser has a direct influence on the lineshape and the linewidth, farther influence on the measuring accuracy. This topic is particularly interesting for laser diodes (LD), which optical properties make them key-devices for optical communications and Coherent Sensing systems. Phase noise in LD and the related problems that arise when such lasers are employed in coherent optical sensing systems are investigated. Applications to metrology and to new sensing schemes are described, experimental results are reported and the overall performances of the sensors are assessed.
Junior doctors' experiences with interprofessional collaboration: Wandering the landscape

The transition from medical student to junior doctor is challenging. Junior doctors need to become part of the physician community of practice (CoP), while dealing with new responsibilities, tasks and expectations. At the same time, they need to learn how to navigate the frontiers and intersections with the other communities of practice that form the Landscape of Practice (LoP). This study aims to understand how junior doctors experience interprofessional collaboration (IPC) and what elements shape these experiences considering their transition to clinical practice.
Hierarchical Boosting Dual-Stage Feature Reduction Ensemble Model for Parkinson’s Disease Speech Data

As a neurodegenerative disease, Parkinson’s disease (PD) is hard to identify at the early stage, while using speech data to build a machine learning diagnosis model has proved effective in its early diagnosis. However, speech data show high degrees of redundancy, repetition, and unnecessary noise, which influence the accuracy of diagnosis results. Although feature reduction (FR) could alleviate this issue, the traditional FR is one-sided (traditional feature extraction could construct high-quality features without feature preference, while traditional feature selection could achieve feature preference but could not construct high-quality features). To address this issue, the Hierarchical Boosting Dual-Stage Feature Reduction Ensemble Model (HBD-SFREM) is proposed in this paper. The major contributions of HBD-SFREM are as follows: (1) The instance space of the deep hierarchy is built by an iterative deep extraction mechanism. (2) The manifold features extraction method embeds the nearest neighbor feature preference method to form the dual-stage feature reduction pair. (3) The dual-stage feature reduction pair is iteratively performed by the AdaBoost mechanism to obtain instances features with higher quality, thus achieving a substantial improvement in model recognition accuracy. (4) The deep hierarchy instance space is integrated into the original instance space to improve the generalization of the algorithm. Three PD speech datasets and a self-collected dataset are used to test HBD-SFREM in this paper. Compared with other FR algorithms and deep learning algorithms, the accuracy of HBD-SFREM in PD speech recognition is improved significantly and would not be affected by a small sample dataset. Thus, HBD-SFREM could give a reference for other related studies.
Linear response of Venice storm gates to incident waves

In laboratory experiments, it is known that the mobile storm barriers designed for Venice inlets can be excited subharmonically by incident waves to oscillate in modes that can reduce the efficiency of protection against storm tides. Based on the idealization that a barrier is composed of many gates across the middle of an infinitely long channel, resonance of the articulated structure has been shown to originate from the existence of trapped modes, and is possible only via a nonlinear mechanism. In reality, the inlet geometry is different in that two parallel jetties are present only on the sea side; the barrier faces a large open space in the lagoon. Here we give a linear scattering theory for such a geometry. An energy identity is derived to provide a global check for numerical computations. Gate responses are first carried out for a wide range of incident wave frequencies. Resonances are found at frequencies close to the natural frequencies predicted recently by Li and Mei (Li & Mei 2003 Appl. Ocean Res. 25, 115–126). Responses to random incident waves described by JONSWAP spectrum are discussed.
Simultaneous measurement of strain and temperature based on clover microstructured fiber loop mirror

In this work, an all-fiber loop mirror using a clover microstructured fiber for the simultaneous measurement of temperature and strain is presented. The sensing head is formed by a short piece of clover microstructured fiber with 35 mm length. The geometry of the fiber allowed observing different interferences created by the microstructured fiber core section. Different sensitivities to temperature and strain were obtained and, using a matrix method, it is possible to discriminate both physical parameters. Resolutions of ±2ºC and ±11 με, for temperature and strain, respectively, were attained.
Implications of shorted turn faults in bar wound PM machines

The paper discusses the effect of single turn short-circuits in the windings of fault tolerant permanent magnet machines. It is shown that previously recognised methods for dealing with shorted turns do not work for larger bar-wound machines, and a new method for protecting the windings against single turn faults is therefore proposed. The new method depends on rapid detection of the fault and injection of a current (of appropriate magnitude and phase) into the faulted winding. The paper gives a theoretical analysis supported by finite element simulations of the fault conditions and illustrates these with a case study taken from the aerospace industry.
On the use of nonlinear impact oscillators in vibrating electromagnetic based energy harvesters

This work investigates the use of impact-oscillators in nonlinear electro-magnetic cantilever based broad bandwidth frequency energy harvester. The electro-mechanical model includes the dynamical equations of the nonlinear impact-oscillators, the nonlinear frequency resonant cantilever beam equation of the harvester, and the Lorenz magnetic force resulting from the surrounding nonlinear magnetic field. The simulated results of the harvested power show a band of resonant frequencies of the vibrating cantilever beam extended beyond its fundamental natural frequency. Due to the strong nonlinearity of both the impact oscillators’ forces and the magnetic flux, the harvested power of the enhanced system shows wider bands in its respective frequency response. Moreover, the harvested power of the cantilever beam shows that considering two magnets in repulsion generates higher values mainly due to the strong nonlinear transient magnetic flux, resulting into few times more power as compared to the case of considering only one magnet in the system.
Exploring Persistent Racial and Ethnic Representation Disparity in U.S. Geography Doctoral Programs: The Disciplinary Underrepresentation Gap

Underrepresentation among U.S. citizen racial and ethnic minorities in geography has a long history, one perpetuated through—and readily measurable by—its doctoral degree–granting record. This article examines the history of efforts to redress underrepresentation since the 1960s, explores modern underrepresentation, measures the degree of its persistence in the discipline and within individual departments, and identifies drivers that exacerbate the racial and ethnic representation disparity among U.S. citizens in geography doctoral programs. To quantify the degree to which the discipline is underperforming demographically, we contrasted the rate of domestic underrepresented minority doctoral degree conferrals with those of White doctoral recipients in geography, the social sciences, and the entire academy over a twenty-three-year period from 1997 through 2019. During that span, geography consistently trailed the social sciences and the academy: This underrepresentation gap has widened in the past decade. Four drivers were identified: (1) lack of dedicated funding for underrepresented minority doctoral students, (2) minimal prior exposure to academic and professional geography, (3) passive recruitment strategies, and (4) pervasive Whiteness of departments. We conclude with a call to action for geographers to meet the moral imperative of racial and ethnic representational equity by becoming agents of measurable change.
Methodology for flammable gas evaluations

There are 177 radioactive waste storage tanks at the Hanford Site. The waste generates flammable gases. The waste releases gas continuously, but in some tanks the waste has shown a tendency to trap these flammable gases. When enough gas is trapped in a tank`s waste matrix, it may be released in a way that renders part or all of the tank atmosphere flammable for a period of time. Tanks must be evaluated against previously defined criteria to determine whether they can present a flammable gas hazard. This document presents the methodology for evaluating tanks in two areas of concern in the tank headspace:steady-state flammable-gas concentration resulting from continuous release, and concentration resulting from an episodic gas release.
DIOR: A Hardware-Assisted Weather Denoising Solution for LiDAR Point Clouds

The interest in developing and deploying fully autonomous vehicles on our public roads has come to a full swing. Driverless capabilities, widely spread in modern vehicles through advanced driver-assistance systems (ADAS), require highly reliable perception features to navigate the environment, being light detection and ranging (LiDAR) sensors a key instrument in detecting the distance and speed of nearby obstacles and in providing high-resolution 3D representations of the surroundings in real-time. However, and despite being assumed as a game-changer in the autonomous driving paradigm, LiDAR sensors can be very sensitive to adverse weather conditions, which can severely affect the vehicle’s perception system behavior. Aiming at improving the LiDAR operation in challenging weather conditions, which contributes to achieving higher driving automation levels defined by the Society of Automotive Engineers (SAE), this article proposes a weather denoising method called Dynamic light-Intensity Outlier Removal (DIOR). DIOR combines two approaches of the state-of-the-art, the dynamic radius outlier removal (DROR) and the low-intensity outlier removal (LIOR) algorithms, supported by an embedded reconfigurable hardware platform. By resorting to field-programmable gate array (FPGA) technology, DIOR can outperform state-of-the-art outlier removal solutions, achieving better accuracy and performance while guaranteeing the real-time requirements.
Energy Management Strategy for Hybrid Multimode Powertrains: Influence of Inertial Properties and Road Inclination

Multimode hybrid powertrains have captured the attention of automotive OEMs for their flexible nature and ability to provide better and optimized efficiency levels. However, the presence of multiple actuators, with different efficiency and dynamic characteristics, increases the problem complexity for minimizing the overall power losses in each powertrain operating condition. The paper aims at providing a methodology to select the powertrain mode and set the reference torques and angular speeds for each actuator, based on the power-weighted efficiency concept. The power-weighted efficiency is formulated to normalize the efficiency contribution from each power source and to include the inertial properties of the powertrain components as well as the vehicle motion resistance forces. The approach, valid for a wide category of multimode powertrain architectures, is then applied to the specific case of a two-mode hybrid system where the engagement of one of the two clutches enables an Input Split or Compound Split operative mode. The simulation results obtained with the procedure prove to be promising in avoiding excessive accelerations, drift of powertrain components, and in managing the power flow for uphill and downhill vehicle conditions.
Effect of Sensory Deprivation of Nasal Respiratory on Behavior of C57BL/6J Mice

Nasal breathing is a dynamic cortical organizer involved in various behaviors and states, such as locomotion, exploration, memory, emotion, introspection. However, the effect of sensory deprivation of nasal respiratory breath (NRD) on behavior remain poorly understood. Herein, general locomotor activity, emotion, learning and memory, social interaction, and mechanical pain were evaluated using a zinc sulfate nasal irrigation induced nasal respiratory sensory deprivation animal model (ZnSO4-induced mouse model). In the open field test, the elevated O-maze test, and forced swim test, NRD mice exhibited depressive and anxiety-like behaviors. In memory-associated tests, NRD mice showed cognitive impairments in the hippocampal-dependent memory (Y maze, object recognition task, and contextual fear conditioning (CFC)) and amygdala-dependent memory (the tone-cued fear conditioning test (TFC)). Surprisingly, NRD mice did not display deficits in the acquisition of conditional fear in both CFC and TFC tests. Still, they showed significant memory retrieval impairment in TFC and enhanced memory retrieval in CFC. At the same time, in the social novelty test using a three-chamber setting, NRD mice showed impaired social and social novelty behavior. Lastly, in the von Frey filaments test, we found that the pain sensitivity of NRD mice was reduced. In conclusion, this NRD mouse model showed a variety of behavioral phenotypic changes, which could offer an important insight into the behavioral impacts of patients with anosmia or those with an impaired olfactory bulb (OB) (e.g., in COVID-19, Alzheimer’s disease, Parkinson’s disease, etc.).
Fission of megamitochondria into multiple smaller well-defined mitochondria in the ageing zebrafish retina

Mitochondria are essential adenosine triphosphate (ATP)-generating cellular organelles. In the retina, they are highly numerous in the photoreceptors and retinal pigment epithelium (RPE) due to their high energetic requirements. Fission and fusion of the mitochondria within these cells allow them to adapt to changing demands over the lifespan of the organism. Using transmission electron microscopy, we examined the mitochondrial ultrastructure of zebrafish photoreceptors and RPE from 5 days post fertilisation (dpf) through to late adulthood (3 years). Notably, mitochondria in the youngest animals were large and irregular shaped with a loose cristae architecture, but by 8 dpf they had reduced in size and expanded in number with more defined cristae. When investigating temporal gene expression of several mitochondrial-related markers, they indicated fission as the dominant mechanism contributing to these changes observed over time. This is likely to be due to continued mitochondrial stress resulting from the oxidative environment of the retina and prolonged light exposure. We have characterised retinal mitochondrial ageing in a key vertebrate model organism, that provides a basis for future studies of retinal diseases that are linked to mitochondrial dysfunction.
Thin-film silicon solar cells using an adhesive bonding technique

Thin-film silicon solar cells using an adhesive bonding technique have been investigated. Surface passivation effect due to the developed adhesive is observed and a very low surface recombination velocity is obtained. A 10-/spl mu/m-thick single-crystalline silicon solar cell is fabricated by adhesive bonding of a near-Lambertian alumina ceramic substrate. Open circuit voltage of 602 mV and short circuit current of 25.8 mA/cm/sup 2/ are obtained. Incident light is effectively confined by the adhesive bonding technique. The results obtained indicate that the adhesive bonding technique is suitable for realizing high-efficiency, low-cost, thin-film cell.
Permittivity-Inspired Microwave Resonator-Based Biosensor Based on Integrated Passive Device Technology for Glucose Identification

In this study, we propose a high-performance resonator-based biosensor for mediator-free glucose identification. The biosensor is characterized by an air-bridge capacitor and fabricated via integrated passive device technology on gallium arsenide (GaAs) substrate. The exterior design of the structure is a spiral inductor with the air-bridge providing a sensitive surface, whereas the internal capacitor improves indicator performance. The sensing relies on repolarization and rearrangement of surface molecules, which are excited by the dropped sample at the microcosmic level, and the resonance performance variation corresponds to the difference in glucose concentration at the macroscopic level. The air-bridge capacitor in the modeled RLC circuit serves as a bio-recognition element to glucose concentration (εglucoseC0), generating resonant frequency shifts at 0.874 GHz and 1.244 GHz for concentrations of 25 mg/dL and 300 mg/dL compared to DI water, respectively. The proposed biosensor exhibits excellent sensitivity at 1.38 MHz per mg/dL with a wide detection range for glucose concentrations of 25–300 mg/dL and a low detection limit of 24.59 mg/dL. Additionally, the frequency shift and concentration are highly linear with a coefficient of determination of 0.98823. The response time is less than 3 s. We performed multiple experiments to verify that the surface morphology reveals no deterioration and chemical binding, thus validating the reusability and reliability of the proposed biosensor.
The Science of Natural Resource Damage Assessments

The process for conducting natural resource damage assessments (NRDAs) is supported by important scientific investigation components. The degree to which science forms the basis of NRD settlements varies by case, but all NRDAs depend to varying extents on scientific studies. While some of these investigation components have been discussed in previous papers and agency guidance, many of the scientific components remain anecdotal and poorly supported. This article presents each of several scientific components as an integrated investigation approach and gives recommendations and examples of the methodological features.
Low-cost Artificial Intelligence Enhanced Hardware Design for Data Augmentation

This paper presents a novel low-cost hardware implementation of data augmentation using artificial neural networks for a low-power, low-cost Water Quality Indexing application. Multilayer Perceptron (MLP) feedforward network with backpropagation learning has been designed to predict the data of DO and EC using pH and ORP as the input vector. This reduces the requirement for costly sensor electrodes, decreasing the design's cost. The design has been implemented on both ASIC and Embedded platforms. The Augmentation ANN predicts DO and EC with a 98% accuracy rate and achieves a 92% reduction in cost. The results have been presented and compared with standard WQI device.
MS-222 and Propofol Sedation during and after the Simulated Transport of Nile tilapia (Oreochromis niloticus)

Simple Summary Sedation has been shown to reduce stress and damage during live fish transportation. However, there is a lack of information regarding MS-222 alternatives. The present study aimed at assessing the effects of propofol during a 6-h simulated transportation of Nile tilapia (Oreochromis niloticus) focusing on physiology, histology, behavior, and meat integrity. Fluctuations in water chemistry, glucose, hematological parameters, and behavioral response were found in propofol-treated animals (although it was normalized after the recovery period). In general, the findings highlight the potential use of propofol as a beneficial mediator of transportation-induced stress in fish contributing to improve fish welfare. Abstract The use of anesthetics has been suggested as a strategy to hamper live fish transport-induced stress. Still, there is insufficient data available on the use of alternative anesthetics to MS-222. This study investigated the use of propofol to mitigate stress in Nile tilapia (Oreochromis niloticus, 143.8 ± 20.9 g and 20.4 ± 0.9 cm) during a 6 h simulated transport. Individuals (n = 7) were divided into three groups: control, 40 mg L−1 MS-222, and 0.8 mg L−1 propofol. A naïve group non-transported was also considered. During the 6 h transport and 24 h after, the response to external stimuli, opercular movements, water quality parameters, behavior, blood hematology and other physiological values, the histopathology of the gills, the quality of the fillet, and oxidative-stress changes in gills, muscle, brain, and liver were evaluated. Propofol increased swimming activity of fish but decreased opercular movements and responses to external stimuli, indicating oscillations of the sedation depth. Water pH and glucose levels increased, while hematocrit (HCT) and lactate decreased in propofol groups at 6 h. At this time-point, MS-222 also induced a decrease in the HCT and lactate levels while increasing cortisol levels. Despite these effects, the stress-related behaviors lessened with anesthetics compared to the control group. After the recovery period, physiological responses normalized in animals from both anesthetic groups, but the control still had high cortisol levels. Overall, propofol is a good alternative for the transportation of this species, showing efficient sedation without compromising health or fillet quality. However, further pharmacodynamics and pharmacokinetics knowledge is required to support its use in aquaculture settings.