Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracellular Vesicles in Neurodegenerative Diseases: An Update

Neurodegenerative diseases affect millions of people worldwide. The likelihood of developing a neurodegenerative disease rises dramatically as life expectancy increases. Although it has drawn significant attention, there is still a lack of proper effective treatments for neurodegenerative disease because the mechanisms of its development and progression are largely unknown. Extracellular vesicles (EVs) are small bi-lipid layer-enclosed nanosized particles in tissues and biological fluids. EVs are emerging as novel intercellular messengers and regulate a series of biological responses. Increasing evidence suggests that EVs are involved in the pathogenesis of neurodegenerative disorders. In this review, we summarize the recent findings of EVs in neurodegenerative diseases and bring up the limitations in the field.
The Effects of Nitrate Supplementation on Performance as a Function of Habitual Dietary Intake of Nitrates: A Randomized Controlled Trial of Elite Football Players

Nitrates are an effective ergogenic supplement; however, the effects of nitrate supplements based on habitual dietary nitrate intake through diet alone are not well understood. We aimed to assess this in a group of 15 highly trained football players from Slovenian football’s First Division. Participants underwent two separate Cooper performance tests either with nitrate supplementation (400 mg nitrates) or placebo while having their nutrition assessed for nitrate intake, as well as energy and macronutrient intake. Nitrate supplementation had a statistically significant positive effect on performance if baseline dietary nitrate intake was below 300 mg (p = 0.0104) in both the placebo and intervention groups. No effects of nitrate supplementation when baseline dietary nitrate intake was higher than 300 mg in the placebo group could be concluded due to the small sample size. Nitrate supplementation did not have a significant effect on perceived exertion. The daily nitrate intake of the participants was measured at 165 mg, with the majority of nitrates coming from nitrate-rich vegetables.
Minimum 1D velocity models in Central and Southern Italy: a contribution to better constrain hypocentral determinations

We computed one-dimensional ( I D) velocity models and station corrections for Centrai and Southern Italy, in- verting re-picked P-wave alTival times recorded by the Istituto Nazionale di Geofisica seismic network. The re-picked data yield resolved P-wave velocity results and proved to be more suited than bulletin data for de- tailed tomographic studies. Using the improved velocity models, we relocated the most significant earthquakes which occurt.ed in the Apennines in the past 7 years, achieving constrained hypocentral determinations for events within most of the Apenninic belt. The interpretation of the obtained lD velocity models allows us to infer interesting features on the deep structure of the Apennines. Smooth velocity gradients with depth and low P-wave velocities are ob,'ierved beneath the Apennines. We believe that our results are effective to constrain hypocentral locations in Italy and may represent a first step towards more detailed seismotectonic analyses.
High-Resolution Ratoon Rice Monitoring under Cloudy Conditions with Fused Time-Series Optical Dataset and Threshold Model

Ratoon rice, an effective rice cultivation system, allows paddy rice to be harvested twice from the same stubble, playing an important role in ensuring food security and adapting to climate change with its unique growth characteristics. However, there is an absence of research related to remote-sensing monitoring of ratoon rice, and the presence of other rice cropping systems (e.g., double-season rice) with similar characteristics poses a hindrance to the accurate identification of ratoon rice. Furthermore, cloudy and rainy regions have limited available remote-sensing images, meaning that remote-sensing monitoring is limited. To address this issue, taking Yongchuan District, a typical cloud-prone region in Chongqing, China, as an example, this study proposed the construction of a time-series optical dataset using the Modified Neighborhood Similar Pixel Interpolator (MNSPI) method for cloud-removal interpolation and the Flexible Spatiotemporal DAta Fusion (FSDAF) model for fusing multi-source optical remote-sensing data, in combination with vegetation index features and phenological information to build a threshold model to map ratoon rice at high-resolution (10 m). The mapping performance of ratoon rice was evaluated using independent field samples to obtain the overall accuracy and kappa coefficient. The findings indicate that the combination of the MNSPI method and FSDAF model had a stable and effective performance, characterized by high correlation coefficient (r) values and low root mean square error (RMSE) values between the restored/predicted images and the true images. Notably, it was possible to effectively capture the distinct characteristics of ratoon rice in cloudy and rainy regions using the proposed threshold model. Specifically, the identified area of ratoon rice in the study region was 194.17 km2, which was close to the official data (158–180 km2), and the overall accuracy and kappa coefficient of ratoon rice identification result were 90.73% and 0.81, respectively. These results demonstrate that our proposed threshold model can effectively distinguish ratoon rice during vital phenological stages from other crop types, enrich the technical system of rice remote-sensing monitoring, and provide a reference for agricultural remote-sensing applications in cloudy and rainy regions.
New Insight into the Potential Protective Function of Sulforaphene against ROS−Mediated Oxidative Stress Damage In Vitro and In Vivo

Sulforaphene (SFE) is a kind of isothiocyanate isolated from radish seeds that can prevent free-radical-induced diseases. In this study, we investigated the protective effect of SFE on oxidative-stress-induced damage and its molecular mechanism in vitro and in vivo. The results of cell experiments show that SFE can alleviate D-gal-induced cytotoxicity, promote cell cycle transformation by inhibiting the production of reactive oxygen species (ROS) and cell apoptosis, and show a protective effect on cells with H2O2-induced oxidative damage. Furthermore, the results of mice experiments show that SFE can alleviate D-galactose-induced kidney damage by inhibiting ROS, malondialdehyde (MDA), and 4-hydroxyalkenals (4-HNE) production; protect the kidney against oxidative stress-induced damage by increasing antioxidant enzyme activity and upregulating the Nrf2 signaling pathway; and inhibit the activity of pro-inflammatory factors by downregulating the expression of Toll-like receptor 4 (TLR4)—mediated inflammatory response. In conclusion, this research shows that SFE has antioxidant effects, providing a new perspective for studying the anti−aging properties of natural compounds.
Personalising Climate Change on Instagram

This article is a comparative study of how three Danish climate celebrities – an activist, an influencer, and a politician – personalise climate change on Instagram. They engage in personal storytelling about the issue in a way that is closely connected to their public presentation of self and their choice of visual genres. The theoretical framework combines theories of social media aesthetics and publics (Serafinelli, 2018; Papacharissi, 2015), self-presentation (Marshall, 2010), authenticity (Enli, 2015a; Marwick, 2015), and emotion in political communication (Wahl- Jorgensen, 2019). The method is a qualitative case study comparing the three profiles and their overall curational strategy for addressing climate change through particular visual genres and how their personal storytelling is based on performing authenticity, emotion, and connecting with affective publics. The analysis demonstrates how personalising climate change can be performed as coping with climate anxiety, feel-good sustainable consumption, or enthusiastic promotion of Danish green solutions.
Analysis and Implementation of Controlled Semiconductor Switch for Ultra-Wideband Radar Sensor Applications

All ultra-wideband (UWB) sensor applications require hardware designed directly for their specific application. The switching of broadband radio frequency and microwave signals is an integral part of almost every piece of high-frequency equipment, whether in commercial operation or laboratory conditions. The trend of integrating various circuit structures and systems on a chip (SoC) or in a single package (SiP) is also related to the need to design these integrated switches for various measuring devices and instruments in laboratories, paradoxically for their further development. Another possible use is switching high-frequency signals in telecommunications devices, whether mobile or fixed networks, for example, for switching signals from several antennas. Based on these requirements, a high-frequency semiconductor integrated switch with NMOS transistors was designed. With these transistors, it is possible to achieve higher integration than with bipolar ones. Even though MOSFET transistors have worse frequency characteristics, we can compensate them to some extent with the precise design of the circuit and layout of the chip. This article describes the analysis and design of a high-frequency semiconductor integrated switch for UWB applications consisting of three series-parallel switches controlled by CMOS logic signals. They are primarily intended for UWB sensor systems, e.g., when switching and configuring the antenna MIMO system or when switching calibration tools. The design of the switch was implemented in low-cost 0.35 µm SiGe BiCMOS technology with an emphasis on the smallest possible attenuation and the largest possible bandwidth and isolation. The reason for choosing this technology was also that other circuit structures of UWB systems were realized in this technology. Through the simulations, individual parameters of the circuit were simulated, the layout of the chip was also created, and the parameters of the circuit were simulated with the parasitic extraction and the inclusion of parasitic elements (post-layout simulations). Subsequently, the chip was manufactured and its parameters were measured and evaluated. Based on these measurements, the designed and fabricated UWB switch was found to have the following parameters: a supply current of 2 mA at 3.3 V, a bandwidth of 6 GHz, an insertion loss (at 1 GHz) of −2.2 dB, and isolation (at 1 GHz) of −33 dB, which satisfy the requirements for our UWB sensor applications.
A Framework for Predicting X-Nuclei Transmitter Gain Using 1H Signal

Commercial human MR scanners are optimised for proton imaging, containing sophisticated prescan algorithms with setting parameters such as RF transmit gain and power. These are not optimal for X-nuclear application and are challenging to apply to hyperpolarised experiments, where the non-renewable magnetisation signal changes during the experiment. We hypothesised that, despite the complex and inherently nonlinear electrodynamic physics underlying coil loading and spatial variation, simple linear regression would be sufficient to accurately predict X-nuclear transmit gain based on concomitantly acquired data from the proton body coil. We collected data across 156 scan visits at two sites as part of ongoing studies investigating sodium, hyperpolarised carbon, and hyperpolarised xenon. We demonstrate that simple linear regression is able to accurately predict sodium, carbon, or xenon transmit gain as a function of position and proton gain, with variation that is less than the intrasubject variability. In conclusion, sites running multinuclear studies may be able to remove the time-consuming need to separately acquire X-nuclear reference power calibration, inferring it from the proton instead.
Inspection and maintenance of industrial infrastructure with autonomous underwater robots

Underwater infrastructure, such as pipelines, requires regular inspection and maintenance including cleaning, welding of defects and valve-turning or hot-stabbing. At the moment, these tasks are mostly performed by divers and Remotely Operated Vehicles (ROVs) but the use of intervention Autonomous Underwater Vehicles (intervention-AUVs) can greatly reduce operation time, risk, and cost. However, autonomous underwater manipulation has not yet reached a high technological readiness and is an intensively researched topic. This review identifies key requirements based on necessary inspection and maintenance methods, linking them to the current technology and deriving major challenges which need to be addressed in development. These include the handling of tools, where a separation between handheld and mounted tools is detected in already employed underwater intervention vehicles such as the Sabertooth by Saab Seaeye or the Aquanaut by Nauticus robotics, two vehicles capable of semi-autonomous intervention. The main challenge identified concerns high level autonomy, i.e., the process of decision-making. This process includes detecting the correct point of interest, maximizing the workspace of the manipulator, planning the manipulation considering required forces, and monitoring the progress to allow for corrections and high quality results. In order to overcome these issues, reliable close range sensing and precise end point navigation is needed. By identifying these persisting challenges, the paper provides inspiration for further development directions in the field of autonomous underwater intervention.
Toward an understanding of “teaching in the making”: Explaining instructional decision making by analyzing a geology instructor’s use of metaphors

Research shows that teachers presented with new curricula designed to be more student-centered do not usually implement that curricula as intended, even when they receive associated professional development. To date, researchers have examined the implementation issue by focusing on ­teachers’ beliefs, knowledge, and motivations to explain their practices, although results are complex and sometimes contradictory. Similarly, this case study ­research investigates how a geology instructor (Eric, a pseudonym) chose to implement a student-centered, inquiry-rich, discussion-focused curriculum by using traditional teacher-centered strategies instead. Classroom observations and multiple audio-recorded meetings with Eric were a means to understand why he chose and amended certain parts of the proposed curriculum. The object of focus is Eric’s spontaneous use of metaphor when talking about teaching, learning, and knowledge to understand and explain the factors involved in his instructional decision making. Analyzing Eric’s conversations and teaching through an embodied cognition theoretical framework shows that he structured his teaching with two metaphors: the jigsaw puzzle metaphor and the fieldtrip metaphor. These parallel metaphors worked in concert to shape how Eric perceived his role, his students’ role, and the role and nature of knowledge; thus, they structured what and how he taught. Understanding teachers’ conceptual metaphors can aid curriculum designers to develop content with a higher likelihood of implementation, just as collaboration and communication between designers and teachers will support teaching-in-the-making.
Assessment of Nutritional Composition of Shrimps Using Different Smoking Method

The study assessed the effects of smoking on the nutrient attributes of penaeus notialis shrimps in Ghana. Terminalia ivorensis, Petersianthus macrocarpus and Albizia zygia were used as fuel woods to smoolder the shrimps. Descriptive and experimental research designs were adopted to guide the entire study. A Random sampling technique was used to select 88 second year students of the Catering and Hospitality Department at the Kumasi Technical University. Frequency and percentage were used to analyse the background information of the respondents. One way Analysis of variance (ANOVA) was used to test for significant differences among the types of wood used. The study revealed that seven nutrients (Dry Matter, Moisture, Ash, Protein, Fibre, Fat/Oil and Carbohydrate) were found. There is a significant difference in nutritional and chemical properties of the shrimps based on the types of wood used for smoking. The study, therefore, recommended that, care must be taken not to use any wood for fuel in smoking shrimps.
Status and distribution of the Kittlitz's murrelet Brachyramphus brevirostris in Kenai Fjords, Alaska

The Kittlitz’s Murrelet Brachyramphus brevirostris is a noncolonial, diving seabird of the Alcidae family . Its breeding range is limited to coastal Alaska and the Russian Far East, where it nests inland on talus slopes in glacial alpine areas or on unvegetated mountain slopes in deglaciated areas (Day et al . 1999) . The species’ strong association with glaciated or recently deglaciated habitats, and its highly aggregated distribution at sea, suggest vulnerability to large-scale disturbance of nesting and foraging habitats from global warming (Piatt et al . 1990, Kuletz et al . 2003) . Localized threats include commercial fishing (bycatch), oil spills, and vessel traffic (Romano et al . 2007, Agness et al . 2008) .
Aztreonam is a novel chemical inducer that promotes Agrobacteium transformation and lateral root development in soybean

Agrobacterium-mediated soybean transformation is the simplest method of gene transfer. However, the low transformation due to the intractable nature of soybean genotypes hinders this process. The use of biochemicals (acetosyringone, cinnamic acid, flavonoids, etc.) plays an important role in increasing soybean transformation. These biochemicals induce chemotaxis and virulence gene activation during the infection process. Here we identified a biochemical, aztreonam (a monobactam), for high agrobacterium-mediated transformation in soybean. The soybean explants from three genotypes were inoculated with A. tumefaciens (GV3101) harboring the pMDC32 vector containing hpt or the GmUbi-35S-GUS vector containing the GUS gene during two separate events. High transient GUS expression was obtained during cotyledon explant culture on MS media supplemented with 2.5 mg/L aztreonam. The aztreonam-treated explants showed high efficiency in transient and stable transformation as compared to the untreated control. The transformation of aztreonam-treated explants during seed imbibition resulted in an average of 21.1% as compared to 13.2% in control by using the pMDC32 vector and 28.5 and 20.7% while using the GUS gene cassette, respectively. Based on these findings, the metabolic analysis of the explant after aztreonam treatment was assessed. The high accumulation of flavonoids was identified during an untargeted metabolic analysis. The quantification results showed a significantly high accumulation of the four compounds, i.e., genistein, apigenin, naringenin, and genistin, in cotyledon explants after 18 hours of aztreonam treatment. Alongside this, aztreonam also had some surprising effects on root elongation and lateral root formation when compared to indole-3-butyric acid (IBA). Our findings were limited to soybeans. However, the discovery of aztreonam and its effect on triggering flavonoids could lead to the potential role of aztreonam in the agrobacterium-mediated transformation of different crops.
A White Shark Equilibrium Optimizer with a Hybrid Deep-Learning-Based Cybersecurity Solution for a Smart City Environment

Smart grids (SGs) play a vital role in the smart city environment, which exploits digital technology, communication systems, and automation for effectively managing electricity generation, distribution, and consumption. SGs are a fundamental module of smart cities that purpose to leverage technology and data for enhancing the life quality for citizens and optimize resource consumption. The biggest challenge in dealing with SGs and smart cities is the potential for cyberattacks comprising Distributed Denial of Service (DDoS) attacks. DDoS attacks involve overwhelming a system with a huge volume of traffic, causing disruptions and potentially leading to service outages. Mitigating and detecting DDoS attacks in SGs is of great significance to ensuring their stability and reliability. Therefore, this study develops a new White Shark Equilibrium Optimizer with a Hybrid Deep-Learning-based Cybersecurity Solution (WSEO-HDLCS) technique for a Smart City Environment. The goal of the WSEO-HDLCS technique is to recognize the presence of DDoS attacks, in order to ensure cybersecurity. In the presented WSEO-HDLCS technique, the high-dimensionality data problem can be resolved by the use of WSEO-based feature selection (WSEO-FS) approach. In addition, the WSEO-HDLCS technique employs a stacked deep autoencoder (SDAE) model for DDoS attack detection. Moreover, the gravitational search algorithm (GSA) is utilized for the optimal selection of the hyperparameters related to the SDAE model. The simulation outcome of the WSEO-HDLCS system is validated on the CICIDS-2017 dataset. The widespread simulation values highlighted the promising outcome of the WSEO-HDLCS methodology over existing methods.
Pterobranchites Kozłowski, 1981- an aberrant graptolite?

The periderm of Ordovician Pterobranchites antiquus Kozlowski, 1967 has been examined with SEM. Four components have been recognized within the thecal wall: outer lining, cortex, fusellum and inner lining. The cortex material is composed of thick, straight, unbranched fibrils arranged in several layers as in cortical layer of the graptolite periderm. P. antiquus, previously referred to cephalodiscid pterobranchs, is identified as an aberrant graptolite of uncertain taxonomic position.
MFNet:Real-Time Motion Focus Network for Video Frame Interpolation

As a popular research topic in computer vision, video frame interpolation is widely used in video processing tasks. However, this task is often limited by slow processing speed or high memory consumption in practical applications. To address these drawbacks, a frame interpolation network focusing on motion regions named MFNet is proposed, which consists of a sampler for adaptive and efficient separation of motion regions from the background, a fine-grained module for direct approximation of intermediate streams, and a lightweight module for bi-directional optical stream fusion. Extensive experiments show that our MFNet achieves optimal accuracy on some frame interpolation tasks and is much faster than other state-of-the-art methods. In addition, transplantation of the core components of MFNet to other frame interpolation networks can significantly improve the performance.
WELCOME TO THE DAWN OF THE FOURTH INDUSTRIAL REVOLUTION: ARE HR PROFESSIONALS PREPARED FOR THE IMPACT OF FUTURE OF WORK?

Propelled by the socio-economic disturbances and the COVID-19 pandemic, advanced technologies such as artificial intelligence (AI), Internet of Things (IoT), robotics, and Web3, which are characteristic of the Fourth Industrial Revolution (FIR), have gained significant ground globally, including the developing countries. As organizations face the array of opportunities and challenges of adopting these technologies, human resource (HR) professionals are tasked with trailblazing the digital transformation of workplaces. Yet, a gap in scientific research regarding the preparedness of HR professionals for this task exists, especially in developing countries like North Macedonia. With this research, the authors aim at addressing this gap and exploring the impact of FIR-related technologies on Macedonian workplaces, employees, their skills, and jobs, as well as, the level of readiness of HR professionals to step up in line with these advanced technologies. The authors build upon a review of the existing literature and use a quantitative online survey distributed to a selected group of HR professionals, operating on the territory of North Macedonia. The findings will contribute to a better understanding of the preparedness of HR professionals to steer organizations in the direction of working in the new era of automation and digital transformation.