Miracle-dz/UniFAR-FTUs huggingface dataset:
Pharmacological Characterization of P626, a Novel Dual Adenosine A2A/A2B Receptor Antagonist, on Synaptic Plasticity and during an Ischemic-like Insult in CA1 Rat Hippocampus

In recent years, the use of multi-target compounds has become an increasingly pursued strategy to treat complex pathologies, including cerebral ischemia. Adenosine and its receptors (A1AR, A2AAR, A2BAR, A3AR) are known to play a crucial role in synaptic transmission either in normoxic or ischemic-like conditions. Previous data demonstrate that the selective antagonism of A2AAR or A2BAR delays anoxic depolarization (AD) appearance, an unequivocal sign of neuronal injury induced by a severe oxygen-glucose deprivation (OGD) insult in the hippocampus. Furthermore, the stimulation of A2AARs or A2BARs by respective selective agonists, CGS21680 and BAY60-6583, increases pre-synaptic neurotransmitter release, as shown by the decrease in paired-pulse facilitation (PPF) at Schaffer collateral-CA1 synapses. In the present research, we investigated the effect/s of the newly synthesized dual A2AAR/A2BAR antagonist, P626, in preventing A2AAR- and/or A2BAR-mediated effects by extracellular recordings of synaptic potentials in the CA1 rat hippocampal slices. We demonstrated that P626 prevented PPF reduction induced by CGS21680 or BAY60-6583 and delayed, in a concentration-dependent manner, AD appearance during a severe OGD. In conclusion, P626 may represent a putative neuroprotective compound for stroke treatment with the possible translational advantage of reducing side effects and bypassing differences in pharmacokinetics due to combined treatment.
Reviving a Classic Antigen with a Cutting-Edge Approach: Nanobodies for HER2+ Breast Cancer

The serendipitous discovery of nanobodies (NBs) around two decades ago opened the door to new possibilities for innovative strategies, particularly in cancer treatment. These antigen-binding fragments are derived from heavy-chain-only antibodies naturally found in the serum of camelids and sharks. NBs are an appealing agent for the progress of innovative therapeutic strategies because they combine the advantageous assets of smaller molecules and conventional monoclonal antibodies (mAbs). Moreover, the possibility to produce NBs using bacterial systems reduces manufacturing expenses and speeds up the production process, making them a feasible option for the development of new bio-drugs. Several NBs have been developed over the past 10 years and are currently being tested in clinical trials for various human targets. Here, we provide an overview of the notable structural and biochemical characteristics of NBs, particularly in their application against HER2, an extracellular receptor that often gets aberrantly activated during breast cancer tumorigenesis. The focus is on the recent advancements in diagnostic and therapeutic research up to the present date.
Subgraph Learning for Topological Geolocalization with Graph Neural Networks

One of the challenges of spatial cognition, such as self-localization and navigation, is to develop an efficient learning approach capable of mimicking human ability. This paper proposes a novel approach for topological geolocalization on the map using motion trajectory and graph neural networks. Specifically, our learning method learns an embedding of the motion trajectory encoded as a path subgraph where the node and edge represent turning direction and relative distance information by training a graph neural network. We formulate the subgraph learning as a multi-class classification problem in which the output node IDs are interpreted as the object’s location on the map. After training using three map datasets with small, medium, and large sizes, the node localization tests on simulated trajectories generated from the map show 93.61%, 95.33%, and 87.50% accuracy, respectively. We also demonstrate similar accuracy for our approach on actual trajectories generated by visual-inertial odometry. The key benefits of our approach are as follows: (1) we take advantage of the powerful graph-modeling ability of neural graph networks, (2) it only requires a map in the form of a 2D graph, and (3) it only requires an affordable sensor that generates relative motion trajectory.
Research and Design of a Decentralized Edge-Computing-Assisted LoRa Gateway

As a narrowband communication technology, long-range (LoRa) contributes to the long development of Internet of Things (IoT) applications. The LoRa gateway plays an important role in the IoT transport layer, and security and efficiency are the key issues of the current research. In the centralized working model of IoT systems built by traditional LoRa gateways, all the data generated and reported by end devices are processed and stored in cloud servers, which are susceptible to security issues such as data loss and data falsification. Edge computing (EC), as an innovative approach that brings data processing and storage closer to the endpoints, can create a decentralized security infrastructure for LoRa gateway systems, resulting in an EC-assisted IoT working model. Although this paradigm delivers unique features and an improved quality of service (QoS), installing IoT applications at LoRa gateways with limited computing and memory capabilities presents considerable obstacles. This article proposes the design and implementation of an “EC-assisted LoRa gateway” using edge computing. Our proposed latency-aware algorithm (LAA) can greatly improve the reliability of the network system by using a distributed edge computing network technology that can achieve maintenance operations, such as detection, repair, and replacement of failures of edge nodes in the network. Then, an EC-assisted LoRa gateway prototype was developed on an embedded hardware system. Finally, experiments were conducted to evaluate the performance of the proposed EC-assisted LoRa gateway. Compared with the conventional LoRa gateway, the proposed edge intelligent LoRa gateway had 41.1% lower bandwidth utilization and handled more end devices, ensuring system availability and IoT network reliability more effectively.
Bidirectional Charging for BEVs with Reconfigurable Battery Systems via a Grid-Parallel Proportional-Resonant Controller

This paper investigates the potential of bidirectional charging using modular multilevel inverter-based reconfigurable battery systems via grid-parallel control. The system offers several advantages such as modularity, scalability, and fault-tolerance over conventional battery electric vehicle systems. It is designed for seamless integration with the grid, allowing bidirectional power flow and efficient energy storage. Within this study, the battery system is first simulated in Matlab/Simulink and later implemented into a hardware setup. Eventually, the simulation results and the measurements have been compared and evaluated. Thereby, startup sequences and constant current scenarios were investigated. It has been shown that the system is fully capable to charge and discharge the batteries in the grid-parallel connection, thus enabling bidirectional charging with close to full drive system power. The current total harmonic distortion complies with grid regulations and can potentially improve the grid quality. The proposed system offers significant potential for grid-integrated energy storage systems, addressing the challenges associated with renewable energy integration, grid stability, and energy management. In comparison to other publications on this topic, the proposed approach does not need additional dedicated power electronic hardware and has more degrees of freedom for current control.
Solar-blind field-emission diamond ultraviolet detector

We report our studies on the responsivity of sulfur-doped diamond films to ultraviolet radiation using two types of device configurations: the planar configuration with electrodes directly on the diamond surface, and the electron field emission configuration with a bias electrode suspended above the diamond surface. Diamond films of different grain sizes were employed: microcrystalline diamond, sub-microcrystalline diamond, and nanocrystalline diamond. The responsivity values of diamond films in the field emission configuration reached ∼10 mA/W at around 220 nm, which is ∼40% higher than that of the planar configuration. These responsivity values of diamond films are comparable to those of commercially available photodiodes in the wavelength range of 210–300 nm, but with the advantage of being solar blind. The responsivity data were correlated with the bandgap structure of sulfur-doped diamond.
Synthesis and Properties of Fully Biobased Crosslinked Starch Oleate Films

Starch oleate (degree of substitution = 2.2) films were cast and crosslinked in the presence of air using UV curing (UVC) or heat curing (HC). A commercial photoinitiator (CPI, Irgacure 184) and a natural photoinitiator (NPI, a mixture of biobased 3-hydroxyflavone and n-phenylglycine) were used for UVC. No initiator was used during HC. Isothermal gravimetric analyses, Fourier Transform Infrared (FTIR) measurements, and gel content measurements revealed that all three methods were effective in crosslinking, with HC being the most efficient. All methods increased the maximum strengths of film, with HC causing the largest increase (from 4.14 to 7.37 MPa). This is consistent with a higher degree of crosslinking occurring with HC. DSC analyses showed that the Tg signal flattened as film crosslink densities increased, even disappearing in the case of HC and UVC with CPI. Thermal gravimetric analyses (TGA) indicated that films cured with NPI were least affected by degradation during curing. These results suggest that cured starch oleate films could be suitable for replacing the fossil-fuel-derived plastics currently used in mulch films or packaging applications.
Oral Microbial Signature of Rheumatoid Arthritis in Female Patients

This study aimed to identify the oral microbial signature of Kazakh female rheumatoid arthritis (RA) patients. A total of 75 female patients who met the American College of Rheumatology 2010 classification criteria for RA and 114 healthy volunteers were included in the study. Amplicons of the 16S rRNA gene were sequenced to analyze the microbial composition. We identified significant differences in bacterial diversity and abundance between the RA and control groups, as measured by Shannon (p value = 0.0205) and Simpson (p value = 0.00152) indices. The oral samples from RA patients had higher bacterial diversity than those from non-RA volunteers. The RA samples had a higher relative abundance of Prevotellaceae and Leptotrichiaceae, but a lower content of butyrate and propionate-producing bacteria compared to the control group. The samples from patients in remission had a higher abundance of Treponema sp. and Absconditabacteriales (SR1), whereas those with low disease activity had higher levels of Porphyromonas and those with high RA activity had higher levels of Staphylococcus. A positive correlation was found between the taxa Prevotella_9 and serum levels of antibodies to cyclic citrullinated peptide (ACPA) and rheumatoid factor (RF). The predicted functional pattern of the ACPA+/RF− and ACPA+/RF+ seropositive groups was characterized by increased ascorbate metabolism, degradation of glycosaminoglycans, and reduced biodegradation of xenobiotics. These findings suggest that the functional pattern of the microflora should be considered when selecting a therapeutic strategy for RA in order to provide a personalized approach.
Effect of Scale-Up on Residence Time and Uranium Extraction on Annular Centrifugal Contactors (ACCs)

This work reports the effect of scaling up annular centrifugal contactors (ACCs) upon the residence time distribution and the efficiency of extraction of uranium. The experiments were carried out in a multi-scale ACC platform of three ACCs with rotor diameters of 12, 25, and 40 mm. To enable direct comparison across all three scales of ACC, the residence time distributions were acquired by injecting dye into the solvent phase at a constant relative volume related to the ACC liquid holdup. Across all scales and flowrates, there was little difference in residence time distribution (<6 residence volumes), except for the smallest 12 mm rotor diameter ACC with a high solvent/aqueous feed ratio, which required 12 residence volumes, potentially due to internal circulation in the annulus. At low flowrates, the stage efficiency in all cases was >95%, and it improved further in larger rotor diameter ACCs.
MicroRNA Regulation in Infectious Diseases and Its Potential as a Biosensor in Future Aquaculture Industry: A Review

An infectious disease is the most apprehensive problem in aquaculture as it can lead to high mortality in aquatic organisms and massive economic loss. Even though significant progress has been accomplished in therapeutic, prevention, and diagnostic using several potential technologies, more robust inventions and breakthroughs should be achieved to control the spread of infectious diseases. MicroRNA (miRNA) is an endogenous small non-coding RNA that post-transcriptionally regulates the protein-coding genes. It involves various biological regulatory mechanisms in organisms such as cell differentiation, proliferation, immune responses, development, apoptosis, and others. Furthermore, an miRNA also acts as a mediator to either regulate host responses or enhance the replication of diseases during infection. Therefore, the emergence of miRNAs could be potential candidates for the establishment of diagnostic tools for numerous infectious diseases. Interestingly, studies have revealed that miRNAs can be used as biomarkers and biosensors to detect diseases, and can also be used to design vaccines to attenuate pathogens. This review provides an overview of miRNA biogenesis and specifically focuses on its regulation during infection in aquatic organisms, especially on the host immune responses and how miRNAs enhance the replication of pathogens in the organism. In addition to that, we explored the potential applications, including diagnostic methods and treatments, that can be employed in the aquaculture industry.
Non linear vibration of irregular structures

Previous work by Touze [1] has indicated that the presence of small irregularities in vibrating plates give rise to quadratic non-linearities in the equations of motion, not otherwise present for large-amplitude vibration. These allow appreciable energy to be coupled between the system's modes. Experimental results emphasise how the presence of irregular curvature in a structure changes the leading order coupling from cubic to quadratic and allows energy scattering to occur at relatively small amplitudes A perturbation analysis of the proposed equations of motion reveals the presence of a power law governing the growth of energy at higher frequencies, and experimental data is presented that supports the existence of this universal result. Further work in this area aims to extract non-linear coupling parameters from the experimental results.
Exploring the Applicability of Physiological Monitoring to Manage Physical Fatigue in Firefighters

Physical fatigue reduces productivity and quality of work while increasing the risk of injuries and accidents among safety-sensitive professionals. To prevent its adverse effects, researchers are developing automated assessment methods that, despite being highly accurate, require a comprehensive understanding of underlying mechanisms and variables’ contributions to determine their real-life applicability. This work aims to evaluate the performance variations of a previously developed four-level physical fatigue model when alternating its inputs to have a comprehensive view of the impact of each physiological variable on the model’s functioning. Data from heart rate, breathing rate, core temperature and personal characteristics from 24 firefighters during an incremental running protocol were used to develop the physical fatigue model based on an XGBoosted tree classifier. The model was trained 11 times with different input combinations resulting from alternating four groups of features. Performance measures from each case showed that heart rate is the most relevant signal for estimating physical fatigue. Breathing rate and core temperature enhanced the model when combined with heart rate but showed poor performance individually. Overall, this study highlights the advantage of using more than one physiological measure for improving physical fatigue modelling. The findings can contribute to variables and sensor selection in occupational applications and as the foundation for further field research.
High-Speed Hardware Architecture Based on Error Detection for KECCAK

The hash function KECCAK integrity algorithm is implemented in cryptographic systems to provide high security for any circuit requiring integrity and protect the transmitted data. Fault attacks, which can extricate confidential data, are one of the most effective physical attacks against KECCAK hardware. Several KECCAK fault detection systems have been proposed to counteract fault attacks. The present research proposes a modified KECCAK architecture and scrambling algorithm to protect against fault injection attacks. Thus, the KECCAK round is modified so that it consists of two parts with input and pipeline registers. The scheme is independent of the KECCAK design. Iterative and pipeline designs are both protected by it. To test the resilience of the suggested detection system approach fault attacks, we conduct permanent as well as transient fault attacks, and we evaluate the fault detection capabilities (99.9999% for transient faults and 99.999905% for permanent faults). The KECCAK fault detection scheme is modeled using VHDL language and implemented on an FPGA hardware board. The experimental results show that our technique effectively secures the KECCAK design. It can be carried out with little difficulty. In addition, the experimental FPGA results demonstrate the proposed KECCAK detection scheme’s low area burden, high efficiency and working frequency.
Derivation of a linear, robust H2 controller for systems with parametric uncertainty

In this short paper, we derive a linear, robust H2 controller for a linear system with parametric uncertainty as introduced in [1]. We prove that the linear, robust control law proposed in [1] minimizes the H2 norm of the linear, uncertain system. Thus we provide the proof for Theorem 1 in the mentioned paper. I. PROBLEM DEFINITION Let x ∈ R and u ∈ R denote the system states and inputs of a linear, discrete-time system. In the general framework of robust control (see Fig. 1), the objective is to minimize an error signal, z ∈ R, caused by a disturbance, w ∈ R , for all possible uncertainties introduced via an uncertain signal, p ∈ R , while maintaining stability (cf. [2]). This uncertain system can be represented by xk+1 = Axk + Buk + Bwwk + Bppk (1) zk = Czxk + Dzuk (2) qk = Cqxk + Dquk (3) pk = α∆qk, (4) where the subscript k indicates the time step. The diagonal matrix ∆ = diag(δ1, . . . , δf ) with uncertain elements |δi| ≤ 1, i = 1, . , f , together with Cq , Dq , and Bp represent the uncertainty in the system. The matrices A and B are the nominal system matrices, and α is a scalar, which is nominally set to α = 1, but can be used to reduce the uncertainty if no robust controller can be found for α = 1. The matrices Bw,Cz and Dz define the control objective to be minimized by the robust controller, see [2]. A popular measure for the error signal, z, is theH2 system norm. The corresponding optimization problem is min K max ∆ ‖Tzw‖2, (5) where the transfer function from wk to zk, Tzw, depends on the controller K and on the uncertainty matrix ∆. This problem is a generalization of the well-known Linear Quadratic Regulator problem, which also minimizes the H2 system norm for systems without uncertainty. Methods to solve such problems are given in [2]. The computations in this paper are based on [3], which derives a controller that guarantees stability and performance for all possible ∆. While the method in [3] is potentially more conservative than others in [2], it obtains the discrete-time controller by solving a convex optimization problem in terms Felix Berkenkamp is with ETH Zurich, Switzerland. Email: befelix@ethz.ch . Angela P. Schoellig is with the Dynamic Systems Lab (www.dynsyslab.org) at the University of Toronto Institute for Aerospace Studies (UTIAS), Canada. Email: schoellig@utias.utoronto. ca . K xk uk Plant zk qk pk ∆
Is organic photovoltaics promising for indoor applications

This work utilizes organic photovoltaics (OPV) for indoor applications, such as powering small electronic devices or wireless connected Internet of Things. Three representative polymer-based OPV systems, namely, poly(3-hexylthiophene-2,5-diyl), poly[N-9′-heptadecanyl-2,7-carbazole-alt-5,5-(4′,7′-di-2-thienyl-2′,1′,3′-benzothiadiazole)], and poly[[4,8-bis[(2-ethylhexyl)oxy]benzo[1,2-b:4,5-b′]dithiophene-2,6-diyl][3-fluoro-2-[(2-ethylhexyl)carbonyl]thieno[3,4-b]thiophenediyl]], were selected as the donor materials in blend with fullerene derivatives for comparison under low light level condition using fluorescent lamps. PCDTBT based devices are found to be the best performing system, generating 13.9 μW/cm2 corresponding to 16.6% power conversion efficiency at 300 lx, although PTB7 based devices show the highest efficiency under one sun conditions. This high performance suggests that OPV is competitive to the other PV technologies under low light condition despite much lower performance under one sun conditi.
Discrimination of Adulterated Milk Using NPLS-DA Combined with Two-dimensional Correlation Near-infrared Spectroscopy

In order to develop a rapid,cost-effective and high-throughput analysis method for detecting adulterants in milk,adulterated milk discriminant models are established by combing two-dimensional(2D) correlation near-infrared spectroscopy with multi-way partial least squares-discriminant analysis(NPLS-DA). 40 adulterated milk samples with melamine(0.01~3 g/L)and 40 adulterated milk samples with urea(1~20 g/L)are prepared respectively,then the absorption spectra of all samples are measured.Based on quantization of 2D correlation spectrum,the NPLS-DA models of urea-tainted milk,melamine-tainted milk and two types adulterated milk are constructed.The recognition rates of unknown samples are 95%,90%,and 92.5% by calibration models individually.At the same time,PLS-DA and OPLS-DA models are established.The results show that NPLS-DA model has better predictive ability than PLS-DA model and OPLS-DA model,and this method can also be applied to other food safety detection areas.