The particle surface of spinning test particles

In this work, inspired by the definition of the photon surface given by Claudel, Virbhadra, and Ellis, we give an alternative quasi-local definition to study the circular orbits of single-pole particles. This definition does not only apply to photons but also to massive point particles. For the case of photons in spherically symmetric spacetime, it will give a photon surface equivalent to the result of Claudel, Virbhadra, and Ellis. Meanwhile, in general static and stationary spacetime, this definition can be regarded as a quasi-local form of the effective potential method. However, unlike the effective potential method which can not define the effective potential in dynamical spacetime, this definition can be applied to dynamical spacetime. Further, we generalize this definition directly to the case of pole-dipole particles. In static spherical symmetry spacetime, we verify the correctness of this generalization by comparing the results obtained by the effective potential method.Comment: 12pages, no figures; accepted by The European Physical Journal C; the title has been revies

Design of a Robust Radio-Frequency Fingerprint Identification Scheme for Multimode LFM Radar

International audienceRadar is an indispensable part of the Internet of Things (IoT). Specific emitter identification is essential to identify the legitimate radars and, more importantly, to reject the malicious radars. Conventional methods rely on pulse parameters that are not capable to identify the specific emitter as two radars may have the same configuration or a malicious radar can perform spoofing attacks. Radio frequency fingerprint (RFF) is the unique and intrinsic hardware characteristic of devices resulted from hardware imperfection, which can be used as the device identity. This paper proposes a robust and reliable radar identification scheme based on the RFF, taking linear frequency modulation (LFM) radar as a case study. This scheme first classifies the operation mode of the pulses, then eliminates the noise effect, and finally identifies the radar emitters based on the transient and modulation-based RFF features. Experimental results verify the effectiveness of our radar identification scheme among three real LFM radars (same model) operating at four modes, each mode with 2,000 pulses from each radar. The identification rates of the four modes are all higher than 90% when the signal-tonoise ratio (SNR) is about 5 dB. In addition, mode 3 achieves almost 100% identification accuracy even when the SNR is as low as-10 dB

Design of a Hybrid RF Fingerprint Extraction and Device Classification Scheme

Radio frequency (RF) fingerprint is the inherent hardware characteristics and has been employed to classify and identify wireless devices in many Internet of Things (IoT) applications. This paper extracts novel RF fingerprint features, designs a hybrid and adaptive classification scheme adjusting to the environment conditions, and carries out extensive experiments to evaluate the performance. In particular, four modulation features, namely differential constellation trace figure (DCTF), carrier frequency offset, modulation offset and I/Q offset extracted from constellation trace figure (CTF), are employed. The feature weights under different channel conditions are calculated at the training stage. These features are combined smartly with the weights selected according to the estimated signal to noise ratio (SNR) at the classification stage. We construct a testbed using universal software radio peripheral (USRP) platform as the receiver and 54 ZigBee nodes as the candidate devices to be classified, which are the most ZigBee devices ever tested. Extensive experiments are carried out to evaluate the classification performance under different channel conditions, namely line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. We then validate the robustness by carrying out the classification process 18 months after the training, which is the longest time gap. We also use a different receiver platform for classification for the first time. The classification error rate is as low as 0.048 in LOS scenario, and 0.1105 even when a different receiver is used for classification 18 months after the training. Our hybrid classification scheme has thus been demonstrated effective in classifying a large amount of ZigBee devices

The efficacy of homestyle rehabilitation on negative symptoms in chronic schizophrenia: A randomized controlled trial

ObjectiveSchizophrenia is a debilitating mental disorder with a high disability rate that is characterized by negative symptoms such as apathy, hyperactivity, and anhedonia that can make daily life challenging and impair social functioning. In this study, we aim to investigate the effectiveness of homestyle rehabilitation in mitigating these negative symptoms and associated factors.MethodsA randomized controlled trial was conducted to compare the efficacy of hospital rehabilitation and homestyle rehabilitation for negative symptoms in 100 individuals diagnosed with schizophrenia. The participants were divided randomly into two groups, each persisting for 3 months. The primary outcome measures were the Scale for Assessment of Negative Symptoms (SANS) and Global Assessment of Functioning (GAF). The secondary outcome measures included the Positive Symptom Assessment Scale (SAPS), Calgary Schizophrenia Depression Scale (CDSS), Simpson-Angus Scale (SAS), and Abnormal Involuntary Movement Scale (AIMS). The trial aimed to compare the effectiveness of the two rehabilitation methods.ResultsHomestyle rehabilitation for negative symptoms was found to be more effective than hospital rehabilitation, according to the changes in SANS (T = 2.07, p = 0.04). Further analysis using multiple regression indicated that improvements in depressive symptoms (T = 6.88, p < 0.001) and involuntary motor symptoms (T = 2.75, p = 0.007) were associated with a reduction in negative symptoms.ConclusionHomestyle rehabilitation may have greater potential than hospital rehabilitation in improving negative symptoms, making it an effective rehabilitation model. Further research is necessary to investigate factors such as depressive symptoms and involuntary motor symptoms, which may be associated with the improvement of negative symptoms. Additionally, more attention should be given to addressing secondary negative symptoms in rehabilitation interventions

The mediating role of negative symptoms in “secondary factors” determining social functioning in chronic schizophrenia

BackgroundChronic schizophrenia is significantly influenced by negative symptoms, with several known contributors to secondary negative symptoms. However, the impact of these factors and negative symptoms on social functioning warrants further exploration.MethodsWe assessed the clinical symptoms, antipsychotic adverse reactions, and social functioning of 283 hospitalized patients with chronic schizophrenia using various standardized interviews and scales. We conducted multiple regression and mediation analyses to elucidate the impact of secondary factors on negative symptoms, and the relationship among these “secondary factors,” negative symptoms, and social functioning.ResultsOur findings identified depressive symptoms, extrapyramidal symptoms, and positive symptoms as significant contributors to secondary negative symptoms. We found that negative symptoms play a notable mediating role in the effect of depressive and positive symptoms on social functioning. However, the relationship between positive symptoms, negative symptoms, and social functioning proved to be intricate.ConclusionOur findings propose that negative symptoms act as pivotal mediators in the correlation between “secondary factors” (including the depressive symptoms and positive symptoms) and social functioning. The treatment of chronic schizophrenia necessitates focusing on key factors such as depressive and positive symptoms, which might significantly contribute to the development of secondary negative symptoms. Further research is essential to clarify the complex relationship among positive symptoms, negative symptoms, and social functioning in schizophrenia

Transcriptome sequencing of olfactory-related genes in olfactory transduction of large yellow croaker (Larimichthy crocea) in response to bile salts

Fish produce and release bile salts as chemical signalling substances that act as sensitive olfactory stimuli. To investigate how bile salts affect olfactory signal transduction in large yellow croaker (Larimichthy crocea), deep sequencing of olfactory epithelium was conducted to analyse olfactory-related genes in olfactory transduction. Sodium cholates (SAS) have typical bile salt chemical structures, hence we used four different concentrations of SAS to stimulate L. crocea, and the fish displayed a significant behavioural preference for 0.30% SAS. We then sequenced olfactory epithelium tissues, and identified 9938 unigenes that were significantly differentially expressed between SAS-stimulated and control groups, including 9055 up-regulated and 883 down-regulated unigenes. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses found eight categories linked to the olfactory transduction pathway that was highly enriched with some differentially expressed genes (DEGs), including the olfactory receptor (OR), Adenylate cyclase type 3 (ADCY3) and Calmodulin (CALM). Genes in these categories were analysed by RT-qPCR, which revealed aspects of the pathway transformation between odor detection, and recovery and adaptation. The results provide new insight into the effects of bile salt stimulation in olfactory molecular mechanisms in fishes, and expands our knowledge of olfactory transduction, and signal generation and decline

HECT, UBA and WWE domain containing 1 represses cholesterol efflux during CD4+ T cell activation in Sjögren’s syndrome

Introduction: Sjögren’s syndrome (SS) is a chronic autoimmune disorder characterized by exocrine gland dysfunction, leading to loss of salivary function. Histological analysis of salivary glands from SS patients reveals a high infiltration of immune cells, particularly activated CD4+ T cells. Thus, interventions targeting abnormal activation of CD4+ T cells may provide promising therapeutic strategies for SS. Here, we demonstrate that Hect, uba, and wwe domain containing 1 (HUWE1), a member of the eukaryotic Hect E3 ubiquitin ligase family, plays a critical role in CD4+ T-cell activation and SS pathophysiology.Methods: In the context of HUWE1 inhibition, we investigated the impact of the HUWE1 inhibitor BI8626 and sh-Huwe1 on CD4+ T cells in mice, focusing on the assessment of activation levels, proliferation capacity, and cholesterol abundance. Furthermore, we examined the therapeutic potential of BI8626 in NOD/ShiLtj mice and evaluated its efficacy as a treatment strategy.Results: Inhibition of HUWE1 reduces ABCA1 ubiquitination and promotes cholesterol efflux, decreasing intracellular cholesterol and reducing the expression of phosphorylated ZAP-70, CD25, and other activation markers, culminating in the suppressed proliferation of CD4+ T cells. Moreover, pharmacological inhibition of HUWE1 significantly reduces CD4+ T-cell infiltration in the submandibular glands and improves salivary flow rate in NOD/ShiLtj mice.Conclusion: These findings suggest that HUWE1 may regulate CD4+ T-cell activation and SS development by modulating ABCA1-mediated cholesterol efflux and presents a promising target for SS treatment