Communication-Efficient Federated Learning for LEO Satellite Networks Integrated with HAPs Using Hybrid NOMA-OFDM

Space AI has become increasingly important and sometimes even necessary for government, businesses, and society. An active research topic under this mission is integrating federated learning (FL) with satellite communications (SatCom) so that numerous low Earth orbit (LEO) satellites can collaboratively train a machine learning model. However, the special communication environment of SatCom leads to a very slow FL training process up to days and weeks. This paper proposes NomaFedHAP, a novel FL-SatCom approach tailored to LEO satellites, that (1) utilizes high-altitude platforms (HAPs) as distributed parameter servers (PS) to enhance satellite visibility, and (2) introduces non-orthogonal multiple access (NOMA) into LEO to enable fast and bandwidth-efficient model transmissions. In addition, NomaFedHAP includes (3) a new communication topology that exploits HAPs to bridge satellites among different orbits to mitigate the Doppler shift, and (4) a new FL model aggregation scheme that optimally balances models between different orbits and shells. Moreover, we (5) derive a closed-form expression of the outage probability for satellites in near and far shells, as well as for the entire system. Our extensive simulations have validated the mathematical analysis and demonstrated the superior performance of NomaFedHAP in achieving fast and efficient FL model convergence with high accuracy as compared to the state-of-the-art

One-Shot Federated Learning For LEO Constellations That Reduces Convergence Time From Days To 90 Minutes

A Low Earth orbit (LEO) satellite constellation consists of a large number of small satellites traveling in space with high mobility and collecting vast amounts of mobility data such as cloud movement for weather forecast, large herds of animals migrating across geo-regions, spreading of forest fires, and aircraft tracking. Machine learning can be utilized to analyze these mobility data to address global challenges, and Federated Learning (FL) is a promising approach because it eliminates the need for transmitting raw data and hence is both bandwidth and privacy friendly. However, FL requires many communication rounds between clients (satellites) and the parameter server (PS), leading to substantial delays of up to several days in LEO constellations. In this paper, we propose a novel one-shot FL approach for LEO satellites, called LEOShot, that needs only a single communication round to complete the entire learning process. LEOShot comprises three processes: (i) synthetic data generation, (ii) knowledge distillation, and (iii) virtual model retraining. We evaluate and benchmark LEOShot against the state of the art and the results show that it drastically expedites FL convergence by more than an order of magnitude. Also surprisingly, despite the one-shot nature, its model accuracy is on par with or even outperforms regular iterative FL schemes by a large margin

Optimizing Federated Learning In LEO Satellite Constellations Via Intra-Plane Model Propagation And Sink Satellite Scheduling

The advances in satellite technology developments have recently seen a large number of small satellites being launched into space on Low Earth orbit (LEO) to collect massive data such as Earth observational imagery. The traditional way which downloads such data to a ground station (GS) to train a machine learning (ML) model is not desirable due to the bandwidth limitation and intermittent connectivity between LEO satellites and the GS. Satellite edge computing (SEC), on the other hand, allows each satellite to train an ML model onboard and uploads only the model to the GS which appears to be a promising concept. This paper proposes FedLEO, a novel federated learning (FL) framework that realizes the concept of SEC and overcomes the limitation (slow convergence) of existing FL-based solutions. FedLEO (1) augments the conventional FL\u27s star topology with \u27horizontal\u27 intra-plane communication pathways in which model propagation among satellites takes place; (2) optimally schedules communication between \u27sink\u27 satellites and the GS by exploiting the predictability of satellite orbiting patterns. We evaluate FedLEO extensively and benchmark it with the state of the art. Our results show that FedLEO drastically expedites FL convergence, without sacrificing-in fact it considerably increases-the model accuracy

S-Methylcysteine (SMC) Ameliorates Intestinal, Hepatic, and Splenic Damage Induced by Cryptosporidium parvum Infection Via Targeting Inflammatory Modulators and Oxidative Stress in Swiss Albino Mice

Cryptosporidiosis has been proposed to be one of the major causes of diarrhoeal disease in humans worldwide that possesses zoonotic concern. Thereby, this study investigated the potential effects of s-Methylcysteine (SMC) on the parasite in vivo followed by the measurement of cytokines, oxidative stress parameters, and an investigation of the major histopathological changes. Sixty male Swiss albino mice weighing 20–25 g were allocated equally into five groups and orally administered saline only (control), SMC only (SMC50) (50 mg/kg b.w.), and 104 Cryptosporidium parvum oocysts per mouse via an esophageal tube (C + ve untreated). The fourth and fifth groups (C + SMC25, C + SMC50) administrated 104 C. parvum oocysts combined with SMC25 (low dose) and 50 (high dose) mg/kg b.w., respectively. At days 7 and 14 post-infection (PI), the feces was collected from each group in order to count C. parvum oocysts. After two weeks of treatment, the animals were euthanized and the serum was collected for biochemical analysis. Next, the intestinal, spleen, and liver sections were dissected for histopathological examination. The results revealed lower oocyst numbers in the C + SMC25 and C + SMC50 groups compared to the infected untreated group. Moreover, higher doses of SMC treatment significantly reduced the enteritis induced by C. parvum in a dose-dependent manner. The hepatic lesions were also mitigated as demonstrated in C + SMC25 and C + SMC50 groups unlike the infected group via lowering the serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) enzymes and increasing albumin and globulin serum levels. SMC administration also reduced cytokines production (SAP, TNF-α, IL-6, and IFN-γ) mediated by Cryptosporidium infection in contrast to the infected untreated group. There were marked lymphoid depletion and amyloidosis observed in the infected untreated group, while the treated groups showed obvious increase in the lymphoid elements. Moreover, the scoring of intestinal parasites, hepatic, and splenic lesions in the SMC-treated groups exhibited significantly lower pathological lesions in different organs in a dose-dependent manner, compared to the infected untreated group. Our results also revealed a significant change in the malondialdehyde content with an elevation of glutathione and superoxide dismutase in the intestines collected from C + SMC25 and C + SMC50 mice relative to the untreated group. Taken together, our results indicated that SMC could be a promising effective compound for treating and declining C. parvum infestation via restoring structural alterations in different tissues, enhancing antioxidant enzymes, and suppressing the cytokines liberation

A Brain-Computer Interface Augmented Reality Framework with Auto-Adaptive SSVEP Recognition

Brain-Computer Interface (BCI) initially gained attention for developing applications that aid physically impaired individuals. Recently, the idea of integrating BCI with Augmented Reality (AR) emerged, which uses BCI not only to enhance the quality of life for individuals with disabilities but also to develop mainstream applications for healthy users. One commonly used BCI signal pattern is the Steady-state Visually-evoked Potential (SSVEP), which captures the brain's response to flickering visual stimuli. SSVEP-based BCI-AR applications enable users to express their needs/wants by simply looking at corresponding command options. However, individuals are different in brain signals and thus require per-subject SSVEP recognition. Moreover, muscle movements and eye blinks interfere with brain signals, and thus subjects are required to remain still during BCI experiments, which limits AR engagement. In this paper, we (1) propose a simple adaptive ensemble classification system that handles the inter-subject variability, (2) present a simple BCI-AR framework that supports the development of a wide range of SSVEP-based BCI-AR applications, and (3) evaluate the performance of our ensemble algorithm in an SSVEP-based BCI-AR application with head rotations which has demonstrated robustness to the movement interference. Our testing on multiple subjects achieved a mean accuracy of 80\% on a PC and 77\% using the HoloLens AR headset, both of which surpass previous studies that incorporate individual classifiers and head movements. In addition, our visual stimulation time is 5 seconds which is relatively short. The statistically significant results show that our ensemble classification approach outperforms individual classifiers in SSVEP-based BCIs

Secure and Efficient Federated Learning in LEO Constellations using Decentralized Key Generation and On-Orbit Model Aggregation

Satellite technologies have advanced drastically in recent years, leading to a heated interest in launching small satellites into low Earth orbit (LEOs) to collect massive data such as satellite imagery. Downloading these data to a ground station (GS) to perform centralized learning to build an AI model is not practical due to the limited and expensive bandwidth. Federated learning (FL) offers a potential solution but will incur a very large convergence delay due to the highly sporadic and irregular connectivity between LEO satellites and GS. In addition, there are significant security and privacy risks where eavesdroppers or curious servers/satellites may infer raw data from satellites' model parameters transmitted over insecure communication channels. To address these issues, this paper proposes FedSecure, a secure FL approach designed for LEO constellations, which consists of two novel components: (1) decentralized key generation that protects satellite data privacy using a functional encryption scheme, and (2) on-orbit model forwarding and aggregation that generates a partial global model per orbit to minimize the idle waiting time for invisible satellites to enter the visible zone of the GS. Our analysis and results show that FedSecure preserves the privacy of each satellite's data against eavesdroppers, a curious server, or curious satellites. It is lightweight with significantly lower communication and computation overheads than other privacy-preserving FL aggregation approaches. It also reduces convergence delay drastically from days to only a few hours, yet achieving high accuracy of up to 85.35% using realistic satellite images

Feline Leishmaniosis in Northwestern Italy: Current Status and Zoonotic Implications

Leishmaniasis remains one of the major neglected tropical diseases. The epidemiological profile of the disease comprises a wide range of hosts, including dogs and cats. Despite several studies about feline Leishmaniosis, the role of cats in disease epidemiology and its clinical impact is still debated. The present study raises awareness about the impact of leishmaniasis in cats from an endemic region in of Northwestern Italy (Liguria). A total number of 250 serum and 282 blood samples were collected from cats, then assessed for Leishmania infantum (L. infantum) serologically using western blot (WB) and molecularly using polymerase chain reaction (PCR). We also tested the association of Leishmania infection with some infectious agents like haemotropic Mycoplasma, Feline immunodeficiency virus (FIV) and Feline leukemia virus (FeLV) together with the hematobiochemical status of the examined animals. Interestingly, all tested animals were asymptomatic and out of 250 examined serum samples, 33 (13.20%) samples (confidence interval (CI) 95% 9.56–17.96%) were positive at WB for L. infantum, whereas of the 282 blood samples, 80 (28.36%) returned a positive PCR (CI 95% 23.43–33.89%). Furthermore, there was a statistical association between PCR positivity for L. infantum and some hematological parameters besides FIV infection as well as a direct significant correlation between Mycoplasma infection and WB positivity. Taken together, the present findings report high prevalence of L. infantum among cats, which reinforces the significance of such positive asymptomatic animals and confirms the very low humoral response in this species. In addition, the laboratory values provide evidence that infection by the parasite is linked to alteration of some hematological parameters and is correlated to some infectious agents. These data are of interest and suggest future research for accurate diagnosis of such zoonosis

Diagnosis of leishmaniasis

This work was supported by EK Elmahallawy, who has a PhD scholarship (number 736) from Erasmus Mundus Scholarship Programme (ELEMENT Action 1 First call).Leishmaniasis is a clinically heterogeneous syndrome caused by intracellular protozoan parasites of the genus Leishmania. The clinical spectrum of leishmaniasis encompasses subclinical ( not apparent), localized (skin lesion), and disseminated (cutaneous, mucocutaneous, and visceral) infection. This spectrum of manifestations depends on the immune status of the host, on the parasite, and on immunoinflammatory responses. Visceral leishmaniasis causes high morbidity and mortality in the developing world. Reliable laboratory methods become mandatory for accurate diagnosis, especially in immunocompromised patients such as those infected with HIV. In this article, we review the current state of the diagnostic tools for leishmaniasis, especially the serological test.Erasmus Mundus Scholarship Programme (ELEMENT Action 1 First call) 73

Melatonin Enhances the Mitochondrial Functionality of Brown Adipose Tissue in Obese—Diabetic Rats

Developing novel drugs/targets remains a major effort toward controlling obesity-related type 2 diabetes (diabesity). Melatonin controls obesity and improves glucose homeostasis in rodents, mainly via the thermogenic effects of increasing the amount of brown adipose tissue (BAT) and increases in mitochondrial mass, amount of UCP1 protein, and thermogenic capacity. Importantly, mitochondria are widely known as a therapeutic target of melatonin; however, direct evidence of melatonin on the function of mitochondria from BAT and the mechanistic pathways underlying these effects remains lacking. This study investigated the effects of melatonin on mitochondrial functions in BAT of Zücker diabetic fatty (ZDF) rats, which are considered a model of obesity-related type 2 diabetes mellitus (T2DM). At five weeks of age, Zücker lean (ZL) and ZDF rats were subdivided into two groups, consisting of control and treated with oral melatonin for six weeks. Mitochondria were isolated from BAT of animals from both groups, using subcellular fractionation techniques, followed by measurement of several mitochondrial parameters, including respiratory control ratio (RCR), phosphorylation coefficient (ADP/O ratio), ATP production, level of mitochondrial nitrites, superoxide dismutase activity, and alteration in the mitochondrial permeability transition pore (mPTP). Interestingly, melatonin increased RCR in mitochondria from brown fat of both ZL and ZDF rats through the reduction of the proton leak component of respiration (state 4). In addition, melatonin improved the ADP/O ratio in obese rats and augmented ATP production in lean rats. Further, melatonin reduced mitochondrial nitrosative and oxidative status by decreasing nitrite levels and increasing superoxide dismutase activity in both groups, as well as inhibited mPTP in mitochondria isolated from brown fat. Taken together, the present data revealed that chronic oral administration of melatonin improved mitochondrial respiration in brown adipocytes, while decreasing oxidative and nitrosative stress and susceptibility of adipocytes to apoptosis in ZDF rats, suggesting a beneficial use in the treatment of diabesity. Further research regarding the molecular mechanisms underlying the effects of melatonin on diabesity is warranted.SAF2016-79794-R from the Ministerio de Ciencia e Innovación (Spain)European Regional Development Fund (ERDF

Mitotic Arrest-Deficient 2 Like 2 (MAD2L2) Interacts with Escherichia coli Effector Protein EspF

Enteropathogenic (EPEC) and Enterohemorrhagic (EHEC) Escherichia coli are considered emerging zoonotic pathogens of worldwide distribution. The pathogenicity of the bacteria is conferred by multiple virulence determinants, including the locus of enterocyte effacement (LEE) pathogenicity island, which encodes a type III secretion system (T3SS) and effector proteins, including the multifunctional secreted effector protein (EspF). EspF sequences differ between EPEC and EHEC serotypes in terms of the number and residues of SH3-binding polyproline-rich repeats and N-terminal localization sequence. The aim of this study was to discover additional cellular interactions of EspF that may play important roles in E. coli colonization using the Yeast two-hybrid screening system (Y2H). Y2H screening identified the anaphase-promoting complex inhibitor Mitotic Arrest-Deficient 2 Like 2 (MAD2L2) as a host protein that interacts with EspF. Using LUMIER assays, MAD2L2 was shown to interact with EspF variants from EHEC O157:H7 and O26:H11 as well as EPEC O127:H6. MAD2L2 is targeted by the non-homologous Shigella effector protein invasion plasmid antigen B (IpaB) to halt the cell cycle and limit epithelial cell turnover. Therefore, we postulate that interactions between EspF and MAD2L2 serve a similar function in promoting EPEC and EHEC colonization, since cellular turnover is a key method for bacteria removal from the epithelium. Future work should investigate the biological importance of this interaction that could promote the colonization of EPEC and EHEC E. coli in the host