Miracle-dz/UniFAR-FTUs huggingface dataset:
Profiling neurotransmitter-evoked glial responses by RNA-sequencing analysis

Fundamental properties of neurons and glia are distinctively different. Neurons are excitable cells that transmit information, whereas glia have long been considered as passive bystanders. Recently, the concept of tripartite synapse is proposed that glia are structurally and functionally incorporated into the synapse, the basic unit of information processing in the brains. It has then become intriguing how glia actively communicate with the presynaptic and postsynaptic compartments to influence the signal transmission. Here we present a thorough analysis at the transcriptional level on how glia respond to different types of neurotransmitters. Adult fly glia were purified from brains incubated with different types of neurotransmitters ex vivo. Subsequent RNA-sequencing analyses reveal distinct and overlapping patterns for these transcriptomes. Whereas Acetylcholine (ACh) and Glutamate (Glu) more vigorously activate glial gene expression, GABA retains its inhibitory effect. All neurotransmitters fail to trigger a significant change in the expression of their synthesis enzymes, yet Glu triggers increased expression of neurotransmitter receptors including its own and nAChRs. Expressions of transporters for GABA and Glutamate are under diverse controls from DA, GABA, and Glu, suggesting that the evoked intracellular pathways by these neurotransmitters are interconnected. Furthermore, changes in the expression of genes involved in calcium signaling also functionally predict the change in the glial activity. Finally, neurotransmitters also trigger a general metabolic suppression in glia except the DA, which upregulates a number of genes involved in transporting nutrients and amino acids. Our findings fundamentally dissect the transcriptional change in glia facing neuronal challenges; these results provide insights on how glia and neurons crosstalk in a synaptic context and underlie the mechanism of brain function and behavior.
Immunogenicity of High-Dose Versus MF59-Adjuvanted Versus Standard Influenza Vaccine in Solid Organ Transplant Recipients: The Swiss/Spanish Trial in Solid Organ Transplantation on Prevention of Influenza (STOP-FLU Trial)

Abstract Background The immunogenicity of the standard influenza vaccine is reduced in solid-organ transplant (SOT) recipients, so new vaccination strategies are needed in this population. Methods Adult SOT recipients from 9 transplant clinics in Switzerland and Spain were enrolled if they were >3 months after transplantation. Patients were randomized (1:1:1) to a MF59-adjuvanted or a high-dose vaccine (intervention), or a standard vaccine (control), with stratification by organ and time from transplant. The primary outcome was vaccine response rate, defined as a ≥4-fold increase of hemagglutination-inhibition titers to at least 1 vaccine strain at 28 days postvaccination. Secondary outcomes included polymerase chain reaction–confirmed influenza and vaccine reactogenicity. Results A total of 619 patients were randomized, 616 received the assigned vaccines, and 598 had serum available for analysis of the primary endpoint (standard, n = 198; MF59-adjuvanted, n = 205; high-dose, n = 195 patients). Vaccine response rates were 42% (84/198) in the standard vaccine group, 60% (122/205) in the MF59-adjuvanted vaccine group, and 66% (129/195) in the high-dose vaccine group (difference in intervention vaccines vs standard vaccine, 0.20; 97.5% confidence interval [CI], .12–1); P < . 001; difference in high-dose vs standard vaccine, 0.24 [95% CI, . 16–1]; P < . 001; difference in MF59-adjuvanted vs standard vaccine, 0.17 [97.5% CI, . 08–1]; P < . 001). Influenza occurred in 6% of the standard, 5% in the MF59-adjuvanted, and 7% in the high-dose vaccine groups. Vaccine-related adverse events occurred more frequently in the intervention vaccine groups, but most of the events were mild. Conclusions In SOT recipients, use of an MF59-adjuvanted or a high-dose influenza vaccine was safe and resulted in a higher vaccine response rate. Clinical Trials Registration Clinicaltrials.gov NCT03699839.
Silicon waveguide integrated MoTe2-Ti Schottky Photodetectors at 1600 nm with high linearity

We propose and demonstrate a silicon waveguide integrated MoTe2-Ti Schottky photodetector. The device has shown a responsivity of 23mA/W when operates at 1600 nm, and has a large linear dynamic range of 0.4mW-1.6mW.
Numerical Simulation of Aerodynamics Performance of NERL S826 Airfoil

In this study, the aerodynamic coefficients of NERL S826 airfoil, used for small-scale wind turbines, are numerically computed. To account for high skewness at a high angle of attack, an unstructured mesh with two different turbulence models, namely The k- $\omega$ SSt and Spalert-Allmaras was implemented using the OpenFOAM-2206 tool. The simulation results are validated against wind tunnel experimental data obtained in the same flow conditions. Moreover, the results also are compared with other numerical simulations conducted for the same type of airfoil using an OpenFOAM-06 with a structured mesh. Additionally, blade element theory (BET) was considered in the comparison of the aerodynamic characteristics. It was found that the results for the drag coefficients achieved by OpenFOAM-2206 simulation for both turbulence models are in less agreement with the experiment in comparison with those obtained by OpenFOAM06, particularly for the AOA in the range of $0^{\circ}-12^{\circ}$. However, a better prediction of the drag coefficients was achieved for higher AOA by OpenFOAM-2206 simulation with the k- $\omega S S T$ model and unstructured mesh compared with the other methods. On the other hand, an excellent agreement between OpneFOAM-2206 results in the lift coefficients with the experiment was obtained in comparison with the other methods.
Biocompatible Snowman-like Dimer Nanoparticles for Improved Cellular Uptake in Intrahepatic Cholangiocarcinoma

Intrahepatic cholangiocarcinoma (ICC) is one of the most aggressive types of human cancers. Although paclitaxel (PTX) was proven to exert potent anti-tumor effects against ICC, the delivery of PTX is still challenging due to its hydrophobic property. Nanoparticle (NP)-based carriers have been proven to be effective drug delivery vehicles. Among their physicochemical properties, the shape of NPs plays a crucial role in their performance of cellular internalization and thus anti-tumor efficacy of loaded drugs. In this study, dumbbell-like and snowman-like dimer NPs, composed of a polylactic acid (PLA) bulb and a shellac bulb, were designed and prepared as drug nanocarriers to enhance the efficiency of cellular uptake and anti-tumor performance. PLA/shellac dimer NPs prepared through rapid solvent exchange and controlled co-precipitation are biocompatible and their shape could flexibly be tuned by adjusting the concentration ratio of shellac to PLA. Drug-loaded snowman-like PLA/shellac dimer NPs with a sharp shape exhibit the highest cellular uptake and best cell-killing ability against cancer cells in an in vitro ICC model over traditional spherical NPs and dumbbell-like dimer NPs, as proven with the measurements of flow cytometry, fluorescent confocal microscopy, and the CCK8 assay. The underlying mechanism may be attributed to the lower surface energy required for the smaller bulbs of snowman-like PLA/shellac dimer NPs to make the initial contact with the cell membrane, which facilitates the subsequent penetration through the cellular membrane. Therefore, these dimer NPs provide a versatile platform to tune the shape of NPs and develop innovative drug nanocarriers that hold great promise to enhance cellular uptake and therapeutic efficacy.
Real-time enhancement of a climatology or forecast of ocean thermal structure using observed ocean temperatures.

Abstract : Vertical temperature profiles observed in the eastern North Pacific were used to examine the feasibility of extrapolating an observation from one location to another. The technique, referred to as simple enhancement, is a special case of the Gandin (1963) optimum interpolation methodology. Application to Navy ASW (Antisubmarine Warfare) operations is considered. The technique requires the use of a trial value and a local observation. Trial values are obtained from a climatology and a synoptic analysis/forecast system provided by the Fleet Numerical Oceanography Center. An enhanced temperature profile is calculated by adding an observed anomaly (i.e., observation minus trial value) to the trial value at the desired location. Calculations of mean and RMS errors indicate that simple enhancement can provide a closer estimate to actual conditions than unenhanced climatology. The mixed layer depth cannot be extrapolated accurately to new locations presumably due to mesoscale eddies, fronts, internal waves and small scale fluctuations at the base of the mixed layer. Experiments at different locations and seasons would be required for a complete assessment of the application to ASW operations. Originator supplied keywords include: Ocean thermal structure; Optimal interpolation; Mixed layer; Ocean analysis; Ocean prediction.
Exploring the Challenges of SDGs Localisation by Rural Local Government Institutions in Bangladesh: A Policy Implementation Perspective

The Sustainable Development Goals (SDGs) are a master plan to achieve a sustainable future by 2030, and the government of Bangladesh has been working relentlessly to achieve its targets. Since each country is supposed to take ownership of the goals and tailor policies according to their needs, in the localisation process of the SDGs, the local government institutions play a significant role in implementation. Similarly, in Bangladesh, Rural Local Government Institutions (RLGIs) are likely to play an essential role in the localisation of the SDGs, since they remain close to the most marginalized and often vulnerable rural people and can impact them directly. However, the RLGIs have not made a notable contribution in the localisation of the SDGs so far, and the deadline is approaching. This paper aims to understand the limitation of localising the SDGs by the RLGIs in Bangladesh by exploring the challenges they face that lead to policy implementation failure. From qualitative data collected from six different RLGIs, the paper finds that RLGIs suffer from four broad challenges: financial, political and administrative, behavioural and planning challenges that are causing SDGs localisation implementation failure. The paper concludes that these issues are unlikely to be overcome in a short time, so the future of SDGs localisation within the given timeframe is questionable. Social Science Review, Vol. 39(3), Dec 2022 Page 93-111
People Counting System Using MmWave MIMO Radar with 3D Convolutional Neural Network

In recent years, the number of people counting systems in deployment has been increasing significantly. People counting systems can be used to automate the data collection for advertisement, and revenue projections as well as reduce energy costs using adaptive HVAC operations. However, a naive implementation of people counting systems may result in revealing some unintended information about the users/customers and higher power consumption from operating the systems continuously. In this paper, we study a mmWave Multiple Input Multiple Output (MIMO) radar sensor system for detecting the number of people in a confined space with the aims of low power consumption and minimal leakage of user information. In particular, we showed that a 3D convolutional neural network can accurately determine up to 4 people in a typical size room using a surprisingly minimal number of mmWave signatures ( less than 10 ) as its inputs.
Robust Water-Management Strategies for the California Water Plan Update 2013

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Computer-Aided Bleeding Detection Algorithms for Capsule Endoscopy: A Systematic Review

Capsule endoscopy (CE) is a widely used medical imaging tool for the diagnosis of gastrointestinal tract abnormalities like bleeding. However, CE captures a huge number of image frames, constituting a time-consuming and tedious task for medical experts to manually inspect. To address this issue, researchers have focused on computer-aided bleeding detection systems to automatically identify bleeding in real time. This paper presents a systematic review of the available state-of-the-art computer-aided bleeding detection algorithms for capsule endoscopy. The review was carried out by searching five different repositories (Scopus, PubMed, IEEE Xplore, ACM Digital Library, and ScienceDirect) for all original publications on computer-aided bleeding detection published between 2001 and 2023. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) methodology was used to perform the review, and 147 full texts of scientific papers were reviewed. The contributions of this paper are: (I) a taxonomy for computer-aided bleeding detection algorithms for capsule endoscopy is identified; (II) the available state-of-the-art computer-aided bleeding detection algorithms, including various color spaces (RGB, HSV, etc.), feature extraction techniques, and classifiers, are discussed; and (III) the most effective algorithms for practical use are identified. Finally, the paper is concluded by providing future direction for computer-aided bleeding detection research.
Mobile Edge Computing and AI Enabled Web3 Metaverse over 6G Wireless Communications: A Deep Reinforcement Learning Approach

The Metaverse is gaining attention among academics as maturing technologies empower the promises and envisagements of a multi-purpose, integrated virtual environment. An interactive and immersive socialization experience between people is one of the promises of the Metaverse. In spite of the rapid advancements in current technologies, the computation required for a smooth, seamless and immersive socialization experience in the Metaverse is overbearing, and the accumulated user experience is essential to be considered. The computation burden calls for computation offloading, where the integration of virtual and physical world scenes is offloaded to an edge server. This paper introduces a novel Quality-of-Service (QoS) model for the accumulated experience in multi-user socialization on a multichannel wireless network. This QoS model utilizes deep reinforcement learning approaches to find the near-optimal channel resource allocation. Comprehensive experiments demonstrate that the adoption of the QoS model enhances the overall socialization experience.
Improving RNN Transducer Acoustic Models for English Conversational Speech Recognition

In this paper we investigate several techniques for improving the performance of RNN transducer (RNNT) acoustic models for conversational speech recognition and report state-of-the-art word error rates (WERs) on the 2000-hour Switchboard dataset. We show that n-best label smoothing and length perturbation which show improved performance on the smaller 300-hour dataset are also very effective on large datasets. We further give a rigorous theoretical interpretation of the n-best label smoothing based on stochastic approximation for training RNNT under the maximum likelihood criterion. Random quantization is also introduced to improve the generalization of RNNT models. On the 2000-hour Switchboard dataset, we report a single model performance of 4.9% and 7.7% WERs on the Switchboard and CallHome portions of NIST Hub5 2000, 7.1% on NIST Hub5 2001 and 6.8% on NIST RT03, without using external LMs.
Semantics-Aware Multi-UAV Cooperation for Age-Optimal Data Collection: An Adaptive Communication based MARL Approach

Due to the superior flexibility and extensive coverage, multiple unmanned aerial vehicles (UAVs) cooperation is a promising approach for data collection in improving the information freshness. In this paper, we consider a multi-UAV-assisted Internet of Things (IoT) network, where UAVs are deployed to collect data from sensor nodes (SNs) and transmit data back to the BS via wireless links so as to improve the information freshness, measured by the age of information (AoI). It is of great challenge to achieve effective cooperation under distributed decision-making because of the time-varying and stochasticity of the environment and the limited communication range of UAVs. To address this issue, we formulate the problem of joint trajectory plan, SN scheduling, and transmission scheduling as a decentralized partially observable markov decision process (Dec-POMDP), and develop an adaptive communication based multi-agent deep reinforcement learning (AC-MARL) algorithm to solve it. By applying our proposed AC-MARL algorithm, a more effective cooperation can be achieved by exploiting the benefits of semantic-aware communications among UAVs.
Towards fiber-coupled plasmonic perfect absorber superconducting nanowire photodetectors for the near- and mid-infrared

: Modern photon-based technologies are in need for fast detectors with the ability to detect photons in the near-and mid-IR efficiently. Superconducting nanowire photon detectors, which use the resistivity change upon photon incidence caused by a state transition from their superconducting to normal conducting phase, are state-of-the-art detectors. However, detectors usually suffer from low efficiency in the IR, due to their low intrinsic absorption in this spectral range. To enhance the detection efficiency, we use a plasmonic perfect absorber geometry, which utilizes a localized surface plasmon resonance and a spacer/mirror combination. We present superconducting niobium plasmonic perfect absorber nanostructures, featuring near-unity absorption, tailorable up to wavelengths of 4 µm. Further, we confirm the working principle of the plasmonic perfect absorber for wavelengths in the near-IR, which manifests itself as a polarization-dependent detector response. Finally, we demonstrate an approach of coupling the detector directly to a fiber. This might also enable ultrasensitive sensing application in the near-and mid-IR in the future.
Financial Management Practices and the Performance of Listed Manufacturing Companies in Nigeria

The success of listed manufacturing companies is impacted by financial management practices. In this study, the return on equity of 40 listed manufacturing companies in Nigeria was compared to the effects of financial management practices. Finding out whether there is a significant correlation between financial management practices (via working capital practices, capital structure practices, and corporate governance practices) and the return on equity (ROE) of listed manufacturing companies in Nigeria is the specific goal of this study. The study adopted a correlational research design. In addition, the corporate annual reports and website for the periods 2017-2021 were utilized as the main sources of secondary data. In testing the research hypotheses and ascertaining the significant effect of the variables, the study utilized panel estimation technique methods of data analysis. The research found a strong correlation between working capital management, capital structure, corporate governance, and business performance as measured by return on equity (ROE). In order to improve the performance of Nigerian manufacturing companies, the study advised listed manufacturing companies in Nigeria to make sure that working capital practices, capital structure practices, and corporate governance practices are maintained in all aspects of the organizational decision. To stabilize and enhance return on equity, control factors should also be added to the analysis.
GHz-bandwidth Silicon Photonics Multichannel Filter for Super-Channel Transceiver

We propose and demonstrate a novel GHz-bandwidth multichannel optical filter (MOF) design using a resonator-assisted discrete-Fourier-transform interferometer topology. By employing ultra-low-loss silicon waveguides and low-phase-error phase-tuning elements, the present reconfigurable MOF is able to be implemented on silicon platform, which is challenge for realizing GHz-bandwidth filters due to the large waveguide propagation loss. In particular, the proposed MOF is capable of performing some specific filtering responses with e.g. near-rectangular shape as well as sinc shape. We successfully demonstrated the generation of WDM super-channel comprising four 10-Gaud subchannels using the designed MOF.
3D Simulation of Debris Flows with the Coupled Eulerian–Lagrangian Method and an Investigation of the Runout

In landslide risk management, it is important to estimate the run-out distance of landslides (or debris flows) such that the consequences can be estimated. This research presents an innovative array of dimensionless equations that effectively estimate run-out distances, supported by both experimental data and numerical simulations. We employ the coupled Eulerian–Lagrangian (CEL) method to confront the challenges presented in large deformations during landslides. The soil is modelled using the Mohr–Coulomb model, and the failure of cohesionless soil slopes (e.g., sand slopes) is studied. The simulation results are used to study the characteristics of flows and run-out distances. We suggest a normalized run-out and introduce new scaling relationships for it under different conditions such as different plane angles and material properties. The granular flows under different scales can be compared directly with this new scaling law. The new relationships are validated by both experimental and numerical data. Our analysis reveals that the normalized run-out distance in debris flows is contingent on the initial geometry, plane angle, and material properties. An increase in debris volume and plane angle can contribute to an increase in the normalized run-out distance, while a rise in friction angles causes a decrease. In the case of landslides, the normalized run-out distance depends on material properties and the slope angle. An increase in slope angle leads to a corresponding increase in the normalized run-out distance.
Characterization of 5G mmWave High-Accuracy Positioning Services for Urban Road Traffic

The ongoing development towards autonomous traffic requires detailed context information, including highly accurate position estimates. The 5G standard has therefore extended its feature support for positioning and defined six service levels (SLs) to cater to the various commercial use cases. User positioning at millimeter-waves (mmWaves) is considered particularly promising due to the inherent support for angle measurements and the contiguous broad bands. However, in the literature, a comprehensive classification of the achievable SLs with different positioning algorithms under different parameter measurement errors is missing. Based on ray-tracing data, we find that only the lower SLs can be achieved in an urban scenario, whereas SLs 4 to 6 are hard to meet due to the high availability requirements. For such use cases, hybrid positioning is needed to shorten the tail of the error distribution further: We show that positioning with a single base station (BS) is particularly well-suited because the identified network time synchronization problem is bypassed, thus attaining high accuracy at low overhead. Service availability can be improved further by integrating satellite-based estimates.