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Modern agriculture urgently requires viable alternatives to synthetic chemical substances, such as pesticides and fertilizers, to comply with new and stringent international regulations and meet the growing demands of consumers who prefer chemical-free food. Consequently, organic agriculture has garnered increasing interest over time.
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Modern agriculture urgently requires viable alternatives to synthetic chemical substances, such as pesticides and fertilizers, to comply with new and stringent international regulations and meet the growing demands of consumers who prefer chemical-free food. Consequently, organic agriculture has garnered increasing interest over time. To compensate for yield reduction resulting from opting out of the use mineral fertilizers, research has focused on the use of biostimulants to sustain the productivity of horticultural crops. To this end, a greenhouse experiment was conducted to assess the effects of three nonmicrobial biostimulants (a plant extract, vegetable protein hydrolysate, and a seaweed extract) and an untreated control on the production and mineral content of wild rocket (Diplotaxis tenuifolia (L.) DC.) cultivated under organic conditions and harvested three times during the growth cycle. In general, the nitrate content, which defines the commercial quality of wild rocket, was not influenced by the application of biostimulants. At each harvest, the application of biostimulants resulted in improved production performance, although this was not always accompanied by an increase in mineral content. Specifically, the best results were obtained with the use of plant-derived protein hydrolysate and plant extract, which led to an improvement in total yield of 32.1% and 27.2%, respectively compared to that of control plants. These results reconfirm that biostimulants represent a valid and indispensable tool for organic growers.
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D2D edge computing is a promising solution to address the conflict between limited network capacity and increasing application demands, where mobile devices can offload their tasks to other peer devices/servers for better performance. Task offloading is critical to the performance of D2D edge
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D2D edge computing is a promising solution to address the conflict between limited network capacity and increasing application demands, where mobile devices can offload their tasks to other peer devices/servers for better performance. Task offloading is critical to the performance of D2D edge computing. Most existing works on task offloading assume the task processing time is known or can be accurately estimated. However, the processing time is often uncertain until it is finished. Moreover, the same task can have largely different execution times under different scenarios, which leads to inaccurate offloading decisions and degraded performance. To address this problem, we propose a game-based probabilistic task offloading scheme with an uncertain processing time in D2D edge networks. First, we characterize the uncertainty of the task processing time using a probabilistic model. Second, we incorporate the proposed probabilistic model into an offloading decision game. We also analyze the structural properties of the game and prove that it can reach a Nash equilibrium. We evaluate the proposed work using real-world applications and datasets. The experimental results show that the proposed probabilistic model can accurately characterize the uncertainty of completion time, and the offloading algorithm can effectively improve the overall task completion rate in D2D networks.
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Deep learning, a crucial technique for achieving artificial intelligence (AI), has been successfully applied in many fields. The gradual application of the latest architectures of deep learning in the field of time series forecasting (TSF), such as Transformers, has shown excellent performance and
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Deep learning, a crucial technique for achieving artificial intelligence (AI), has been successfully applied in many fields. The gradual application of the latest architectures of deep learning in the field of time series forecasting (TSF), such as Transformers, has shown excellent performance and results compared to traditional statistical methods. These applications are widely present in academia and in our daily lives, covering many areas including forecasting electricity consumption in power systems, meteorological rainfall, traffic flow, quantitative trading, risk control in finance, sales operations and price predictions for commercial companies, and pandemic prediction in the medical field. Deep learning-based TSF tasks stand out as one of the most valuable AI scenarios for research, playing an important role in explaining complex real-world phenomena. However, deep learning models still face challenges: they need to deal with the challenge of large-scale data in the information age, achieve longer forecasting ranges, reduce excessively high computational complexity, etc. Therefore, novel methods and more effective solutions are essential. In this paper, we review the latest developments in deep learning for TSF. We begin by introducing the recent development trends in the field of TSF and then propose a new taxonomy from the perspective of deep neural network models, comprehensively covering articles published over the past five years. We also organize commonly used experimental evaluation metrics and datasets. Finally, we point out current issues with the existing solutions and suggest promising future directions in the field of deep learning combined with TSF. This paper is the most comprehensive review related to TSF in recent years and will provide a detailed index for researchers in this field and those who are just starting out.
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Edna Rocio Riaño-Castillo, Juan Carlos Rodríguez-Ortiz, Hye-Ji Kim, María de la Luz Guerrero González, María Fernanda Quintero-Castellanos and Pablo Delgado-Sánchez
Horticulturae2024, 10(5), 497; https://doi.org/10.3390/horticulturae10050497 (registering DOI) - 11 May 2024
Sedimentable solids generated in aquaponic systems are mainly composed of organic waste, presenting molecules such as phytate, which can be a potential source of inorganic nutrients through mineralization. This work aimed to isolate and identify phytase-producing bacteria and evaluate the inoculation effects of
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Sedimentable solids generated in aquaponic systems are mainly composed of organic waste, presenting molecules such as phytate, which can be a potential source of inorganic nutrients through mineralization. This work aimed to isolate and identify phytase-producing bacteria and evaluate the inoculation effects of pure strains on mineralization and nutrient release from solid waste generated in aquaponic systems at different oxygen and temperature conditions. The bacteria were isolated from the settleable solids of a commercial aquaponic system and molecularly identified by amplifying the 16S rRNA gene. Subsequently, two tests were carried out: 1. Test for the biochemical identification of phytase-producing bacteria; 2. In vitro mineralization test, where the ability to mineralize phytate and release nutrients under different oxygen conditions [0 rpm (2.1 mg L−1) and 200 rpm (7.8 mg L−1)] and temperatures (24 and 37 °C) were evaluated. Our findings show that two pure strains of Lysinibacillus mangiferihumi can mineralize phytate under conditions of 200 rpm and 24 °C, mainly increasing the mineralization of PO4- and Ca, a property that has not yet been reported for this species. On the other hand, at 0 rpm and 24 °C, an increase in K was observed (control conditions), while the conditions of 200 rpm and 24 °C, regardless of bacterial inoculation, favored a rise in S, Mg, and Fe. The Lysinibacillus strains obtained in this investigation are of great importance due to their application in agriculture and the optimization of mineralization in aquaponic systems. A proper combination of oxygen and temperature will lead to a greater availability of nutrients for the growth and development of vegetables.
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Despite the rapid progression of organic semiconductors, developing high-air-stability n-type organic semiconductors are still challenging. Herein, novel strong acceptors based on benzothiadiazoloimidazole units are reported. The results reveal that the strong acceptor BTI-NDI-BTI-a has good solubility and high electron affinity (3.94 eV), accompanied
[...] Read more.
Despite the rapid progression of organic semiconductors, developing high-air-stability n-type organic semiconductors are still challenging. Herein, novel strong acceptors based on benzothiadiazoloimidazole units are reported. The results reveal that the strong acceptor BTI-NDI-BTI-a has good solubility and high electron affinity (3.94 eV), accompanied by 1D slipped-stacking crystals. Notably, the material presents promising potential for developing into air-stable n-type organic semiconductor materials.
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Plastic pollution in the ocean is a severe environmental problem worldwide because rivers carry plastic waste from human activities, harming the ocean’s health, ecosystems, and people. Therefore, monitoring the amount of plastic waste flowing from rivers and streams worldwide is crucial. In response
[...] Read more.
Plastic pollution in the ocean is a severe environmental problem worldwide because rivers carry plastic waste from human activities, harming the ocean’s health, ecosystems, and people. Therefore, monitoring the amount of plastic waste flowing from rivers and streams worldwide is crucial. In response to this issue of river-floating waste, our present research aimed to develop an automated waste measurement method tailored for real rivers. To achieve this, we considered three scenarios: clear visibility, partially submerged waste, and collective mass. We proposed the use of object detection and tracking techniques based on deep learning architectures, specifically the You Only Look Once (YOLOv5) and Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT). The types of waste classified in this research included cans, cartons, plastic bottles, foams, glasses, papers, and plastics in laboratory flume experiments. Our results demonstrated that the refined YOLOv5, when applied to river-floating waste images, achieved high classification accuracy, with 88% or more for the mean average precision. The floating waste tracking using DeepSORT also attained F1 scores high enough for accurate waste counting. Furthermore, we evaluated the proposed method across the three different scenarios, each achieving an 80% accuracy rate, suggesting its potential applicability in real river environments. These results strongly support the effectiveness of our proposed method, leveraging the two deep learning architectures for detecting and tracking river-floating waste with high accuracy.
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Miguel A. Ortega, Luis M. Garcia-Puente, Oscar Fraile-Martinez, Tatiana Pekarek, Cielo García-Montero, Julia Bujan, Leonel Pekarek, Silvestra Barrena-Blázquez, Raquel Gragera, Inmaculada C. Rodríguez-Rojo, Patrocinio Rodríguez-Benitez, Laura López-González, Raul Díaz-Pedrero, Melchor Álvarez-Mon, Natalio García-Honduvilla, Juan A. De León-Luis, Coral Bravo and Miguel A. Saez
Antioxidants2024, 13(5), 591; https://doi.org/10.3390/antiox13050591 (registering DOI) - 11 May 2024
Preeclampsia, a serious and potentially life-threatening medical complication occurring during pregnancy, is characterized by hypertension and often accompanied by proteinuria and multiorgan dysfunction. It is classified into two subtypes based on the timing of diagnosis: early-onset (EO-PE) and late-onset preeclampsia (LO-PE). Despite being
[...] Read more.
Preeclampsia, a serious and potentially life-threatening medical complication occurring during pregnancy, is characterized by hypertension and often accompanied by proteinuria and multiorgan dysfunction. It is classified into two subtypes based on the timing of diagnosis: early-onset (EO-PE) and late-onset preeclampsia (LO-PE). Despite being less severe and exhibiting distinct pathophysiological characteristics, LO-PE is more prevalent than EO-PE, although both conditions have a significant impact on placental health. Previous research indicates that different pathophysiological events within the placenta may contribute to the development of preeclampsia across multiple pathways. In our experimental study, we investigated markers of oxidative stress, ferroptosis, and lipid peroxidation pathways in placental tissue samples obtained from women with LO-PE (n = 68) compared to healthy control pregnant women (HC, n = 43). Through a comprehensive analysis, we observed an upregulation of specific molecules associated with these pathways, including NADPH oxidase 1 (NOX-1), NADPH oxidase 2 (NOX-2), transferrin receptor protein 1 (TFRC), arachidonate 5-lipoxygenase (ALOX-5), acyl-CoA synthetase long-chain family member 4 (ACSL-4), glutathione peroxidase 4 (GPX4) and malondialdehyde (MDA) in women with LO-PE. Furthermore, increased ferric tissue deposition (Fe3+) was observed in placenta samples stained with Perls’ Prussian blue. The assessment involved gene and protein expression analyses conducted through RT-qPCR experiments and immunohistochemistry assays. Our findings underscore the heightened activation of inflammatory pathways in LO-PE compared to HC, highlighting the pathological mechanisms underlying this pregnancy disorder.
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The research included 120 specimens of Pinna nobilis cultivated at a commercial park for oyster (Ostrea edulis) and black mussel (Mytilus galloprovincialis) cultivation. Research was carried out from 2012 to 2016, prior to the start of the mass extinction
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The research included 120 specimens of Pinna nobilis cultivated at a commercial park for oyster (Ostrea edulis) and black mussel (Mytilus galloprovincialis) cultivation. Research was carried out from 2012 to 2016, prior to the start of the mass extinction of fan mussel in the Mediterranean During the study period, the average sea temperature at a depth of 3 m was 14.87 ± 4.22 °C, ranging from 7.83 to 24.90 °C. The age of the specimens at the beginning of sexual maturity was approximately three years. The average length of the specimens throughout the study was 293.01 ± 16.58 mm. Gonad status was monitored monthly by sampling. The gender ratio in the study was 46 females (38.4%), 50 males (41.6%), and 24 undetermined individuals (20%). In our study, the results showed that males mature slightly earlier than females. The main spawning season occurred during the warmer part of the year when seawater exceeded 18 °C, starting in May and lasting until November. During the study, the GSI varied as expected and peaked in June (12.1), increasing from May to September.
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Emma J. Leacy, Jia Wei Teh, Aoife M. O’Rourke, Gareth Brady, Siobhan Gargan, Niall Conlon, Jennifer Scott, Jean Dunne, Thomas Phelan, Matthew D. Griffin, Julie Power, Aoife Mooney, Aifric Naughton, Rachel Kiersey, Mary Gardiner, Caroline O’Brien, Ronan Mullan, Rachael Flood, Michael Clarkson, Liam Townsend, Michelle O’Shaughnessy, Adam H. Dyer, Barry Moran, Jean M. Fletcher, Lina Zgaga and Mark A. Littleadd
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Int. J. Mol. Sci.2024, 25(10), 5239; https://doi.org/10.3390/ijms25105239 (registering DOI) - 11 May 2024
Immunosuppressive treatment in patients with rheumatic diseases can maintain disease remission but also increase risk of infection. Their response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination is frequently blunted. In this study we evaluated the effect of immunosuppression exposure on humoral
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Immunosuppressive treatment in patients with rheumatic diseases can maintain disease remission but also increase risk of infection. Their response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination is frequently blunted. In this study we evaluated the effect of immunosuppression exposure on humoral and T cell immune responses to SARS-CoV-2 infection and vaccination in two distinct cohorts of patients; one during acute SARS-CoV-2 infection and 3 months later during convalescence, and another prior to SARS-CoV-2 vaccination, with follow up sampling 6 weeks after vaccination. Results were compared between rituximab-exposed (in previous 6 months), immunosuppression-exposed (in previous 3 months), and non-immunosuppressed groups. The immune cell phenotype was defined by flow cytometry and ELISA. Antigen specific T cell responses were estimated using a whole blood stimulation interferon-γ release assay. A focused post-vaccine assessment of rituximab-treated patients using high dimensional spectral cytometry was conducted. Acute SARS-CoV-2 infection was characterised by T cell lymphopenia, and a reduction in NK cells and naïve CD4 and CD8 cells, without any significant differences between immunosuppressed and non-immunosuppressed patient groups. Conversely, activated CD4 and CD8 cell counts increased in non-immunosuppressed patients with acute SARS-CoV-2 infection but this response was blunted in the presence of immunosuppression. In rituximab-treated patients, antigen-specific T cell responses were preserved in SARS-CoV-2 vaccination, but patients were unable to mount an appropriate humoral response.
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Infertility is a globally underestimated public health concern affecting almost 190 million people, i.e., about 17.5% of people during their lifetime, while the prevalence of male factor infertility is about 7%. Among numerous other causes, the prevalence of male genital tract infections reportedly
[...] Read more.
Infertility is a globally underestimated public health concern affecting almost 190 million people, i.e., about 17.5% of people during their lifetime, while the prevalence of male factor infertility is about 7%. Among numerous other causes, the prevalence of male genital tract infections reportedly ranges between 10% and 35%. Leukocytospermia is found in 30% of infertile men and up to 20% in fertile men. Bacterial infections cause an inflammatory response attracting leukocytes, which produce reactive oxygen species (ROS) and release cytokines, both of which can cause damage to sperm, rendering them dysfunctional. Although leukocytospermia and bacteriospermia are both clinical conditions that can negatively affect male fertility, there is still debate about their impact on assisted reproduction outcomes and management. According to World Health Organization (WHO) guidelines, leukocytes should be determined by means of the Endtz test or with monoclonal antibodies against CD15, CD68 or CD22. The cut-off value proposed by the WHO is 1 × 106 peroxidase-positive cells/mL. For bacteria, Gram staining and semen culture are regarded as the “gold standard”, while modern techniques such as PCR and next-generation sequencing (NGS) are allowing clinicians to detect a wider range of pathogens. Whereas the WHO manual does not specify a specific value as a cut-off for bacterial contamination, several studies consider semen samples with more than 103 colony-forming units (cfu)/mL as bacteriospermic. The pathogenic mechanisms leading to sperm dysfunction include direct interaction of bacteria with the male germ cells, bacterial release of spermatotoxic substances, induction of pro-inflammatory cytokines and ROS, all of which lead to oxidative stress. Clinically, bacterial infections, including “silent” infections, are treatable, with antibiotics being the treatment of choice. Yet, non-steroidal antiphlogistics or antioxidants should also be considered to alleviate inflammatory lesions and improve semen quality. In an assisted reproduction set up, sperm separation techniques significantly reduce the bacterial load in the semen. Nonetheless, contamination of the semen sample with skin commensals should be prevented by applying relevant hygiene techniques. In patients where leukocytospermia is detected, the causes (e.g. infection, inflammation, varicocele, smoking, etc.) of the leukocyte infiltration have to be identified and addressed with antibiotics, anti-inflammatories or antioxidants in cases where high oxidative stress levels are detected. However, no specific strategy is available for the management of leukocytospermia. Therefore, the relationship between bacteriospermia and leukocytospermia as well as their specific impact on functional sperm parameters and reproductive outcome variables such as fertilization or clinical pregnancy must be further investigated. The aim of this narrative review is to provide an update on the current knowledge on leukocytospermia and bacteriospermia and their impact on male fertility.
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Residual drug pollutants in water environments represent a severe risk to human health, so developing a cheap, environmentally friendly, and effective photocatalyst to deal with them has become a hot topic. Herein, a magnetically separable Fe3O4@TiO2/g-C3 [...] Read more.
Residual drug pollutants in water environments represent a severe risk to human health, so developing a cheap, environmentally friendly, and effective photocatalyst to deal with them has become a hot topic. Herein, a magnetically separable Fe3O4@TiO2/g-C3N4 photocatalyst with a special heterojunction structure was fabricated, and its photocatalytic performance was assessed by degrading tetracycline (TC). Compared to Fe3O4@TiO2, the synthesized Fe3O4@TiO2/g-C3N4 exhibited superior TC degradation performance, which was primarily ascribed to the heterojunction formed between TiO2 and g-C3N4 and its ability to enhance the visible light absorption capacity and reduce the photoinduced electron/hole recombination rate. Moreover, a free radical capture experiment further confirmed that·O2− and h+ are the predominant components in the TC degradation reaction. Under UV–Vis irradiation, the TC degradation rate escalated to as high as 98% within 120 min. Moreover, Fe3O4@TiO2/g-C3N4 was demonstrated to be easily recovered by magnetic separation without any notable loss even after five cycles, showing exceptional stability and reusability. These findings indicate that Fe3O4@TiO2/g-C3N4 is a promising photocatalyst for environmental remediation that may provide a sustainable approach to degrading antibiotic pollutants in wastewater.
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Bimetallic AuCu/SiO2 nanosized catalysts were prepared using the wet chemical reduction technique. From among Au0.1–1.5Cu10/SiO2 catalysts, the Au0.5Cu10/SiO2 catalyst gave the highest yield of calcium lactate of 87% at a glycerol conversion
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Bimetallic AuCu/SiO2 nanosized catalysts were prepared using the wet chemical reduction technique. From among Au0.1–1.5Cu10/SiO2 catalysts, the Au0.5Cu10/SiO2 catalyst gave the highest yield of calcium lactate of 87% at a glycerol conversion of 96% when the reaction of glycerol with calcium hydroxide at a mole ratio of calcium hydroxide to glycerol of 0.8:1 was conducted under an anaerobic atmosphere at 200 °C for 2 h. The interactions between metallic Au0 and Cu0 nanoparticles facilitate calcium lactate formation. The simulation of glycerol consumption rate with an empirical power-function reaction kinetics equation yielded a reaction activation energy of 44.3 kJ∙mol−1, revealing that the catalytic reaction of glycerol with calcium hydroxide to calcium lactate can be conducted by overcoming a mild energy barrier. The synthesis of calcium lactate through the catalytic reaction of glycerol with calcium hydroxide on a bimetallic AuCu/SiO2 nanosized catalyst under a safe anaerobic atmosphere is an alternative to the conventional calcium lactate production technique through the reaction of expensive lactic acid with calcium hydroxide.
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Due to their advantages of good stability, adaptability, and flexibility, multi-legged robots are increasingly important in fields such as rescue, military, and healthcare. This study focuses on the millipede, a multi-segmented organism, and designs a novel multi-segment biomimetic robot based on an in-depth
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Due to their advantages of good stability, adaptability, and flexibility, multi-legged robots are increasingly important in fields such as rescue, military, and healthcare. This study focuses on the millipede, a multi-segmented organism, and designs a novel multi-segment biomimetic robot based on an in-depth investigation of the millipede’s biological characteristics and locomotion mechanisms. Key leg joints of millipede locomotion are targeted, and a mathematical model of the biomimetic robot’s leg joint structure is established for kinematic analysis. Furthermore, a central pattern generator (CPG) control strategy is studied for multi-jointed biomimetic millipede robots. Inspired by the millipede’s neural system, a simplified single-loop CPG network model is constructed, reducing the number of oscillators from 48 to 16. Experimental trials are conducted using a prototype to test walking in a wave-like gait, walking with a leg removed, and walking on complex terrain. The results demonstrate that under CPG waveform input conditions, the robot can walk stably, and the impact of a leg failure on overall locomotion is acceptable, with minimal speed loss observed when walking on complex terrain. The research on the structure and motion control algorithms of multi-jointed biomimetic robots lays a technical foundation, expanding their potential applications in exploring unknown environments, rescue missions, agriculture, and other fields.
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Identifying brain-tissue types holds significant research value in the biomedical field of non-contact brain-tissue measurement applications. In this paper, a layered metastructure is proposed, and the second harmonic generation (SHG) in a multilayer metastructure is derived using the transfer matrix method. With the
[...] Read more.
Identifying brain-tissue types holds significant research value in the biomedical field of non-contact brain-tissue measurement applications. In this paper, a layered metastructure is proposed, and the second harmonic generation (SHG) in a multilayer metastructure is derived using the transfer matrix method. With the SHG conversion efficiency (CE) as the measurement signal, the refractive index ranges that can be distinguished are 1.23~1.31 refractive index unit (RIU) and 1.38~1.44 RIU, with sensitivities of 0.8597 RIU−1 and 1.2967 RIU−1, respectively. It can distinguish various brain tissues, including gray matter, white matter, and low-grade glioma, achieving the function of a second harmonic mode sensor (SHMS). Furthermore, temperature has a significant impact on the SHG CE, which can be used to define the switch signal indicating whether the SHMS is functioning properly. When the temperature range is 291.4~307.9 Kelvin (K), the temperature switch is in the “open” state, and the optimal SHG CE is higher than 0.298%, indicating that the SHMS is in the working state. For other temperature ranges, the SHG CE will decrease significantly, indicating that the temperature switch is in the “off” state, and the SHMS is not working. By stimulating temperature and using the response of SHG CE, the temperature-switch function is achieved, providing a new approach for temperature-controlled second harmonic detection.
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Currently, one of the main causes of death in the world is cancer; therefore, it is urgent to obtain a precocious diagnosis, as well as boost research and development of new potential treatments, which should be more efficient and much less invasive for
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Currently, one of the main causes of death in the world is cancer; therefore, it is urgent to obtain a precocious diagnosis, as well as boost research and development of new potential treatments, which should be more efficient and much less invasive for the patient. Magnetic hyperthermia (MH) is an emerging cancer therapy using nanoparticles, which has proved to be effective when combined with chemotherapy, radiotherapy and/or surgery, or even by itself, depending on the type and location of the tumor’s cells. This article presents the results obtained by using a previously developed economic homemade hyperthermia device with different types of magnetite nanoparticles, with sizes ranging between 12 ± 5 and 36 ± 11 nm and presenting different shapes (spherical and cubic particles). These magnetic nanoparticles (MNPs) were synthesized by three different methods (co-precipitation, solvothermal and hydrothermal processes), with their final form being naked, or possessing different kinds of covering layers (polyethylene glycol (PEG) or citric acid (CA)). The parameters used to characterize the heating by magnetic hyperthermia, namely the Specific Absorption Rate (SAR) and the intrinsic loss power (ILP), have been obtained by two different methods. Among other results, these experiments allowed for the determination of which synthesized MNPs showed the best performance concerning hyperthermia. From the results, it may be concluded that, as expected, the shape of MNPs is an important factor, as well as the time that the MNPs can remain suspended in solution (which is directly related to the concentration and covering layer of the MNPs). The MNPs that gave the best results in terms of the SAR were the cubic particles covered with PEG, while in terms of total heating the spherical particles covered with citric acid proved to be better.
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Karolina Bogacka, Piotr Sowiński, Anastasiya Danilenka, Francisco Mahedero Biot, Katarzyna Wasielewska-Michniewska, Maria Ganzha, Marcin Paprzycki and Carlos E. Palau
Electronics2024, 13(10), 1888; https://doi.org/10.3390/electronics13101888 (registering DOI) - 11 May 2024
Currently, deploying machine learning workloads in the Cloud–Edge–IoT continuum is challenging due to the wide variety of available hardware platforms, stringent performance requirements, and the heterogeneity of the workloads themselves. To alleviate this, a novel, flexible approach for machine learning inference is introduced,
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Currently, deploying machine learning workloads in the Cloud–Edge–IoT continuum is challenging due to the wide variety of available hardware platforms, stringent performance requirements, and the heterogeneity of the workloads themselves. To alleviate this, a novel, flexible approach for machine learning inference is introduced, which is suitable for deployment in diverse environments—including edge devices. The proposed solution has a modular design and is compatible with a wide range of user-defined machine learning pipelines. To improve energy efficiency and scalability, a high-performance communication protocol for inference is propounded, along with a scale-out mechanism based on a load balancer. The inference service plugs into the ASSIST-IoT reference architecture, thus taking advantage of its other components. The solution was evaluated in two scenarios closely emulating real-life use cases, with demanding workloads and requirements constituting several different deployment scenarios. The results from the evaluation show that the proposed software meets the high throughput and low latency of inference requirements of the use cases while effectively adapting to the available hardware. The code and documentation, in addition to the data used in the evaluation, were open-sourced to foster adoption of the solution.
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Acute ischemic stroke (AIS) is a challenging disease, which needs urgent comprehensive management. Endovascular thrombectomy (EVT), alone or combined with iv thrombolysis, is currently the most effective therapy for patients with acute ischemic stroke (AIS). However, only a limited number of patients are
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Acute ischemic stroke (AIS) is a challenging disease, which needs urgent comprehensive management. Endovascular thrombectomy (EVT), alone or combined with iv thrombolysis, is currently the most effective therapy for patients with acute ischemic stroke (AIS). However, only a limited number of patients are eligible for this time-sensitive treatment. Even though there is still significant room for improvement in the management of this group of patients, up until now there have been no alternative therapies approved for use in clinical practice. However, there is still hope, as clinical research with novel emerging therapies is now generating promising results. These drugs happen to stop or palliate some of the underlying molecular mechanisms involved in cerebral ischemia and secondary brain damage. The aim of this review is to provide a deep understanding of these mechanisms and the pathogenesis of AIS. Later, we will discuss the potential therapies that have already demonstrated, in preclinical or clinical studies, to improve the outcomes of patients with AIS.
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The evolving technologies regarding Unmanned Aerial Vehicles (UAVs) have led to their extended applicability in diverse domains, including surveillance, commerce, military, and smart electric grid monitoring. Modern UAV avionics enable precise aircraft operations through autonomous navigation, obstacle identification, and collision prevention. The structures
[...] Read more.
The evolving technologies regarding Unmanned Aerial Vehicles (UAVs) have led to their extended applicability in diverse domains, including surveillance, commerce, military, and smart electric grid monitoring. Modern UAV avionics enable precise aircraft operations through autonomous navigation, obstacle identification, and collision prevention. The structures of avionics are generally complex, and thorough hierarchies and intricate connections exist in between. For a comprehensive understanding of a UAV design, this paper aims to assess and critically review the purpose-classified electronics hardware inside UAVs, each with the corresponding performance metrics thoroughly analyzed. This review includes an exploration of different algorithms used for data processing, flight control, surveillance, navigation, protection, and communication. Consequently, this paper enriches the knowledge base of UAVs, offering an informative background on various UAV design processes, particularly those related to electric smart grid applications. As a future work recommendation, an actual relevant project is openly discussed.
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Multiple microbial detections in stool samples of indigenous individuals suffering from chronic gastroenteric disorder of a likely infectious origin, characterized by recurring diarrhea of variable intensity, in the rural north-east of Colombia are common findings, making the assignment of etiological relevance to individual
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Multiple microbial detections in stool samples of indigenous individuals suffering from chronic gastroenteric disorder of a likely infectious origin, characterized by recurring diarrhea of variable intensity, in the rural north-east of Colombia are common findings, making the assignment of etiological relevance to individual pathogens challenging. In a population of 773 indigenous people from either the tribe Wiwa or Kogui, collider bias analysis was conducted comprising 32 assessed microorganisms including 10 bacteria (Aeromonas spp., Campylobacter spp., enteroaggregative Escherichia coli (EAEC), enteropathogenic Escherichia coli (EPEC), enterotoxigenic Escherichia coli (ETEC), Salmonella spp., Shiga toxin-producing Escherichia coli (STEC), Shigella spp./enteroinvasive Escherichia coli (EIEC), Tropheryma whipplei and Yersinia spp.), 11 protozoa (Blastocystis spp., Cryptosporidium spp., Cyclospora spp., Dientamoeba fragilis, Entamoeba coli, Entamoeba bangladeshi/dispar/histolytica/moshkovskii complex, Entamoeba histolytica, Endolimax nana, Giardia duodenalis, Iodamoeba buetschlii and Pentatrichomonas hominis), 8 helminths (Ascaris spp., Enterobius vermicularis, Hymenolepis spp., Necator americanus, Schistosoma spp., Strongyloides spp., Taenia spp. and Trichuris spp.), microsporidia (Encephalocytozoon spp.) and fungal elements (microscopically observed conidia and pseudoconidia). The main results indicated that negative associations potentially pointing towards collider bias were infrequent events (n = 14), while positive associations indicating increased likelihood of co-occurrence of microorganisms quantitatively dominated (n = 88). Microorganisms showing the most frequent negative associations were EPEC (n = 6) and Blastocystis spp. (n = 3), while positive associations were most common for Trichuris spp. (n = 16), Dientamoeba fragilis (n = 15), Shigella spp./EIEC (n = 12), Ascaris spp. (n = 11) and Blastocystis spp. (n = 10). Of note, positive associations quantitively dominated for Blastocystis spp. In conclusion, collider bias assessment did not allow clear-cut assignment of etiological relevance for detected enteric microorganisms within the assessed Colombian indigenous population. Instead, the results suggested complex microbial interactions with potential summative effects. Future studies applying alternative biostatistical approaches should be considered to further delineate respective interactions.
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Electroporation is pivotal in bioelectrochemistry for cellular manipulation, with prominent applications in drug delivery and cell membrane studies. A comprehensive understanding of pore generation requires an in-depth analysis of the critical pore size and the corresponding energy barrier at the onset of cell
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Electroporation is pivotal in bioelectrochemistry for cellular manipulation, with prominent applications in drug delivery and cell membrane studies. A comprehensive understanding of pore generation requires an in-depth analysis of the critical pore size and the corresponding energy barrier at the onset of cell rupture. However, many studies have been limited to basic models such as artificial membranes or theoretical simulations. Challenging this paradigm, our study pioneers using a microfluidic electroporation chip array. This tool subjects live breast cancer cell species to a diverse spectrum of alternating current electric field conditions, driving electroporation-induced cell rupture. We conclusively determined the rupture voltages across varying applied voltage loading rates, enabling an unprecedented characterization of electric cell rupture dynamics encompassing critical pore radius and energy barrier. Further bolstering our investigation, we probed cells subjected to cholesterol depletion via methyl-β-cyclodextrin and revealed a strong correlation with electroporation. This work not only elucidates the dynamics of electric rupture in live cell membranes but also sets a robust foundation for future explorations into the mechanisms and energetics of live cell electroporation.
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Many organisms facultatively produce different phenotypes depending on their environment, yet relatively little is known about the genetic bases of such plasticity in natural populations. In this study, we describe the genetic variation underlying an extreme form of plasticity––resource polyphenism––in Mexican spadefoot toad
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Many organisms facultatively produce different phenotypes depending on their environment, yet relatively little is known about the genetic bases of such plasticity in natural populations. In this study, we describe the genetic variation underlying an extreme form of plasticity––resource polyphenism––in Mexican spadefoot toad tadpoles, Spea multiplicata. Depending on their environment, these tadpoles develop into one of two drastically different forms: a carnivore morph or an omnivore morph. We collected both morphs from two ponds that differed in which morph had an adaptive advantage and performed genome-wide association studies of phenotype (carnivore vs. omnivore) and adaptive plasticity (adaptive vs. maladaptive environmental assessment). We identified four quantitative trait loci associated with phenotype and nine with adaptive plasticity, two of which exhibited signatures of minor allele dominance and two of which (one phenotype locus and one adaptive plasticity locus) did not occur as minor allele homozygotes. Investigations into the genetics of plastic traits in natural populations promise to provide novel insights into how such complex, adaptive traits arise and evolve.
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Objective: This paper explores machine learning methods for exercise-induced laryngeal obstruction (EILO) diagnostics. Traditional diagnostic approaches like CLE scoring face subjectivity, limiting precise objective assessments. Machine learning is introduced as a theoretical solution to potentially overcome these limitations and improve diagnostic precision. Methods: [...] Read more.
Objective: This paper explores machine learning methods for exercise-induced laryngeal obstruction (EILO) diagnostics. Traditional diagnostic approaches like CLE scoring face subjectivity, limiting precise objective assessments. Machine learning is introduced as a theoretical solution to potentially overcome these limitations and improve diagnostic precision. Methods: A narrative review was conducted to explore the integration of machine learning techniques in the diagnostics of EILO. Result: Three machine learning methods for the segmentation of laryngeal images were discovered: fully convolutional network, Mask R-CNN, and 3D VOSNet. Our findings reveal that the integration of machine learning with EILO diagnostics remains a largely untapped research domain, providing significant room for further exploration. Conclusions: The integration of ML techniques for EILO diagnostics has the potential to be a helpful tool for clinicians. The application of computer vision ML methods, such as image segmentation, to delineate laryngeal structures paves the way for a more objective assessment. While challenges persist, especially in differences in patients’ laryngeal anatomy, the synergy of ML and medical expertise is an important field to explore in the years to come.
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China faces a challenge in the sustainable development of the coal industry due to pneumoconiosis problems. Dust control technologies are crucial for safe production and miners’ health, ensuring the industry’s longevity. This article reviews the development process of dust prevention and control in
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China faces a challenge in the sustainable development of the coal industry due to pneumoconiosis problems. Dust control technologies are crucial for safe production and miners’ health, ensuring the industry’s longevity. This article reviews the development process of dust prevention and control in underground coal mines in China, summarizes various technologies, and divides them into dust suppression, open-space dust reduction, and mine dust collectors according to different stages and environments of use. In dust suppression technologies, coal-seam water injection can reduce total dust generation by 60%, wet rock drilling can reduce drilling dust in the presence of stable water sources and high-pressure bearing equipment, and water-seal blasting can reduce blasting dust by 50–70%. In open-space dust reduction technologies, spray dust suppression can remove total dust by 50–95% and the removal efficiencies of foam dedusting for total and respirable dust are reported to reach 95% and 85% under the right conditions, respectively. In dust collector technologies, dry collectors can remove 80–95% of total dust. Wet collectors achieve up to 90% efficiency, dependent on water supply and waste processing. This article also discusses vapor heterogeneous condensation technology as a promising method for improving respirable dust removal in humid mine environments.
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