Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy Threshold Setting With Bounded Performance for Sensing and Communications Under the η-μ Model

Characterization of the energy statistic (ES) plays a fundamental role in sensing and communications systems for signal detection (e.g., in spectrum sensing or noncoherent radar detection) as well as performance assessment. Specifically, simple closed-form expressions for the exceedance probability (EP) of ES are desirable for real-time evaluation of KPI such as probability of false alarm and outage probability, but these are not available for general non-Gaussian models as the $\eta - \mu$ distribution. In this work we investigate upper bounds that can be (approximately) computed in terms of simple functions only, thus providing a reduced-complexity way to energy threshold setting that guarantees bounded EP performance.
Mimicking Protein Kinase C Phosphorylation Inhibits Arc/Arg3.1 Palmitoylation and Its Interaction with Nucleic Acids

Activity-regulated cytoskeleton-associated protein (Arc) plays essential roles in diverse forms of synaptic plasticity, including long-term potentiation (LTP), long-term depression (LTD), and homeostatic plasticity. In addition, it assembles into virus-like particles that may deliver mRNAs and/or other cargo between neurons and neighboring cells. Considering this broad range of activities, it is not surprising that Arc is subject to regulation by multiple types of post-translational modification, including phosphorylation, palmitoylation, SUMOylation, ubiquitylation, and acetylation. Here we explore the potential regulatory role of Arc phosphorylation by protein kinase C (PKC), which occurs on serines 84 and 90 within an α-helical segment in the N-terminal domain. To mimic the effect of PKC phosphorylation, we mutated the two serines to negatively charged glutamic acid. A consequence of introducing these phosphomimetic mutations is the almost complete inhibition of Arc palmitoylation, which occurs on nearby cysteines and contributes to synaptic weakening. The mutations also inhibit the binding of nucleic acids and destabilize high-order Arc oligomers. Thus, PKC phosphorylation of Arc may limit the full expression of LTD and may suppress the interneuronal transport of mRNAs.
The Minimum Target Diameter and the Harvest Age of Oak Natural Secondary Forests in Different Sites Conditions: Case Study in Hunan Province, China

Maintaining permanent forest canopy cover and eventually harvesting timber by predetermined target diameter are often considered as a prototype for future management of the oak natural forest. However, target diameters and harvest age based on average forest growth rates from wide geographical areas often hamper improved management of oak forests. In this study, based on the sampling of 129 target trees from 51 oak natural secondary forest plots in Hunan Province, China, an individual-tree DBH (diameter at breast height) growth model of oak target trees was developed, and the site type (41 levels) was related to the model as random effects by a nonlinear mixed-effects approach. Moreover, the 41 site types were clustered into four site type groups (STG1, STG2, STG3, and STG4) by the K-means clustering algorithm to improve the model performance and practicality. With the help of the model, the five target diameters (including 24, 30, 40, 50, and 60 cm) were simulated in each of the four STGs, and the minimum target diameter was determined for each STG based on the theory of quantitative maturity. In the four STGs, the harvest age of the 24 cm diameter target ranged from 30 to 51 years; the harvest age of the 60 cm target diameter ranged from 131 to 220 years, with the oaks failing to reach 60 cm in the lowest-quality STG4; the minimum target diameter ranged from 21 cm to 29 cm. Results showed that lower-quality sites exclude higher target diameters from optimal harvesting strategies, in contrast to the higher target diameter as a more reasonable strategy in higher quality sites, and that the minimum target diameter is significantly influenced by site conditions. Therefore, it is necessary to develop a diverse target-diameter-harvesting strategy adapted for the complex site conditions of oak forests in Hunan Province towards site-specific timber management to improve the sustainability of timber production in oak forests.
ECONOMIC EFFICIENCY OF FIELD CROP PRODUCTION ON FAMILY FARMS IN THE AUTONOMOUS PROVINCE OF VOJVODINA

Most of the field crop production of Serbia is located in the region of the Autonomous Province of Vojvodina. About 52% of the cereal-growing area and more than 92% of the industrial crop-growing area of Serbia are located in the Vojvodina Province. Corn, wheat, sunflower, soybean and sugar beet predominate in the sowing structure. The study focused on the economic efficiency of field crop production on family farms in Vojvodina during the period 2005-2009. The aim was to analyze family farms 6-20 ha in size oriented to the production of some major field crops. Although these farms accounted for only 16.4% of the total number of family farms in Vojvodina, they used about 45% of the total arable land. The survey method was used to sample the data on some major production parameters on the 50 family farms focused primarily on field crop production in Vojvodina during the five-year period (2005-2009). The data were used for calculation the gross margin for the field crops analyzed in order to determine the changes of the economic efficiency of the production of some major field crops.
Relapses and Serious Infections in Patients with Neuromyelitis Optica Spectrum Disorder Treated with Rituximab: A Swedish Single-Center Study

Neuromyelitis optica spectrum disorder (NMOSD) is a rare immune-mediated relapsing-remitting disease of the central nervous system. The usage of rituximab, as relapse-preventive therapy, in NMOSD is common. We performed a single-center retrospective cohort study to assess the risk of relapses and severe infectious events (SIEs) in rituximab-treated NMOSD patients. This study included 24 aquaporin-4 IgG+ (AQP4+), 8 myelin-oligodendrocyte-protein IgG+ (MOG+), and 10 double-seronegative NMOSD patients. Relapses were observed in 50% of all patients during a mean treatment time of 4.0 (range: 0.5–8.25) years. The incidence risk ratio (IRR) of relapse was three times higher in MOG+ compared to AQP4+ patients (IRR: 3.0, 95% confidence interval (CI); 1.2–7.7). SIEs occurred in 40% of all patients during follow-up. AQP4+ patients conferred an increased risk of SIEs compared to MOG+ patients (IRR; 5.3, 95% CI; 1.2–24.3). Incomplete CD19+ B-lymphocyte suppression was not correlated with relapse risk (hazard ratio; 1.9, 95% CI; 0.7–5.2), and there was no correlation between IgG-levels and SIE risk (odds ratio; 2.0, 95% CI; 0.8–4.8). In conclusion, considerable risks of both relapses and SIEs were observed in NMOSD patients exposed to rituximab, which underlines the need for close clinical vigilance of disease activity and infections during treatment.
Change in dust seasonality as the primary driver for orbital‐scale dust storm variability in East Asia

Glacial periods are recognized to be dustier than interglacials, but the conditions leading to greater dust mobilization are poorly defined. Here we present a new high‐resolution dust record based on 230Th‐normalized 4He flux from Ocean Drilling Program site 882 in the Subarctic North Pacific covering the last 170,000 years. By analogy with modern relationships, we infer the mechanisms controlling orbital‐scale dust storm variability in East Asia. We propose that orbital‐scale dust flux variability is the result of an expansion of the dust season into summer, in addition to more intense dust storms during spring and fall. The primary drivers influencing dust flux include summer insolation at subarctic latitudes and variable Siberian alpine glaciation, which together control the cold air reservoir in Siberia. Changes in the extent of the Northern Hemisphere ice sheets may be a secondary control.
The influence of the combined impairments and apical mesh surgery on the biomechanical behavior of the pelvic floor system

Objective: The prolapse mechanism of multifactorial impairment of the female pelvic floor system and the mechanics of the pelvic floor after apical suspension surgery are not yet understood, so we developed biomechanical models of the pelvic floor for the normal physiological state (0°) and 90° pathological state. Methods: Under different types and levels of the impairments and uterosacral suspensions, the possible changes in the morphometric characteristics and the mechanical characteristics of suspension and support functions were simulated based on the biomechanical models of the pelvic floor. Results: After the combined impairments, the descending displacement of the pelvic floor cervix and the stress and displacement of the perineal body reached maximum values. After surgical mesh implantation, the stresses of the normal pelvic floor were concentrated on the uterine fundus, cervix, and top of the bladder and the stresses of the 90° pathological state pelvic floor were concentrated on the uterine fundus, uterine body, cervix, middle of the posterior vaginal wall, and bottom of the perineal body. Conclusion: After the combined impairments, the biomechanical support of the bladder and sacrococcyx in the anterior (0°) and 90° pathological state pelvic floor system is diminished, the anterior vaginal wall dislodges from the external vaginal opening, and the posterior vaginal wall forms “kneeling” profiles. The pelvic floor system may evolve with a tendency toward the cervical prolapse with anterior and posterior vaginal wall prolapse and eventually prolapse. After surgical mesh implantation, the cervical position can be better restored; however, the load of combined impairment of the pelvic floor is mainly borne by the surgical mesh suspension, the biomechanical support function of pelvic floor organs and sacrococcyx was not repaired by the physiological structure, and the results of uterosacral suspension alone may be poor.
High-Resolution SAR Image Road Extraction Based on MRF Model

As an important ground object, remote sensing image road extraction is a very popular research subject and widely used. With the continuous development of SAR imaging technology, its spatial resolution has become higher and higher, and the road in the image is no longer displayed as a linear feature in low resolution, but a narrow and long planar feature, which leads to the previous low resolution road extraction method cannot be effectively used in high resolution, and a new high resolution road extraction method is needed. In this paper, a high-resolution SAR image road extraction method based on MRF model is proposed. The Contourlet threshold filter is used to reduce the impact of speckle noise, image segmentation is performed using MRF model, and road edge information is extracted based on Canny operator. Finally, geometric feature constraints and edge connections are performed. The results verify the accuracy and stability of the road extraction method proposed in this paper.
The development of new cyber security and networking solutions using Artificial Intelligence and machine learning

The convergence of Artificial Intelligence (AI) and Machine Learning (ML) has ushered in a revolutionary period in networking as well as cybersecurity. This paper explores the important impact of ML and AI on certain fields. Data shows that their use has increased dramatically, particularly in threat detection and predictive modelling. Security measures have been significantly strengthened by automated incident response systems and behavioural analysis powered by AI. The integration of threat intelligence and artificial intelligence has transformed the battle against cyberattacks, whereas real-time data analysis facilitates proactive maintenance. As long as privacy, and surveillance, alongside prejudice concerns, exist, the moral implementation of AI will remain a major worry. This analysis emphasizes the critical importance of ethical AI development. Future scope will include increased integration and more accurate threat detection, but there will also be issues with data quality, and privacy, including the requirement for strong ethical standards. It is of the utmost importance to strike a balance between these difficulties and the amazing promise of AI and ML in order to shape networking and cybersecurity in the future.
ICT adoption by mompreneurs during the COVID-19 pandemic: The role of entrepreneurial orientation

Information and Communication Technologies (ICTs) can benefit mompreneurs, empowering them to start and expand their business. ICTs became even more important for mompreneurs during the COVID-19 pandemic when small business owners had to reinvent themselves and seek alternative ways of maintaining their sales and remaining in the market. In this context, this paper aims to investigate factors related to ICT adoption by Brazilian mompreneurs. The data were collected during the first months of COVID-19 pandemic and were analyzed through structural equation modelling. The descriptive analysis shows that mompreneurs are adopting innovative technologies such as electronic payments, cloud computing, social networks, video conferencing, and others to manage their business. Moreover, the results indicate that two dimensions of Entrepreneurial Orientation (proactiveness and risk-taking) have a significant effect on perceived ease-of-use and an indirect effect on ICT adoption.
High-resolution imaging in acoustic microscopy using deep learning

Acoustic microscopy is a cutting-edge label-free imaging technology that allows us to see the surface and interior structure of industrial and biological materials. The acoustic image is created by focusing high-frequency acoustic waves on the object and then detecting reflected signals. On the other hand, the quality of the acoustic image's resolution is influenced by the signal-to-noise ratio, the scanning step size, and the frequency of the transducer. Deep learning-based high-resolution imaging in acoustic microscopy is proposed in this paper. To illustrate 4 times resolution improvement in acoustic images, five distinct models are used: SRGAN, ESRGAN, IMDN, DBPN-RES-MR64-3, and SwinIR. The trained model's performance is assessed by calculating the PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index) between the network-predicted and ground truth images. To avoid the model from over-fitting, transfer learning was incorporated during the procedure. SwinIR had average SSIM and PSNR values of 0.95 and 35, respectively. The model was also evaluated using a biological sample from Reindeer Antler, yielding an SSIM score of 0.88 and a PSNR score of 32.93. Our framework is relevant to a wide range of industrial applications, including electronic production, material micro-structure analysis, and other biological applications in general.
PS 2D Seismic Lines Reprocessing Us ing Prestack Time Migration: Case Study of the Solimões Basin*

After the discovery of hydrocarbons in the maritime basins, investment in the exploration of hydrocarbons in Brazilian land sedimentary basins was reduced, which has led to a relative lack of information today. In most cases, there is little seismic data coverage, or the data are old and were processed using obsolete techniques. The Solimões Basin is an exception among the Paleozoic basins in terms of coverage and has reasonable line quality. In economic terms, this basin is now producing oil near the Urucú River (discovered in 1986) and gas near the Juruá River (discovered in 1978). This work presents the results of the reprocessing of the 2D seismic lines of the Solimões Basin, to which modern processing techniques were applied to improve the seismic image quality of data acquired in the 1970s and 1980s. A Kirchoff algorithm was applied to the prestack time migration. reprocessing static correction (first break pick and residuals), parameters applied to recover the amplitudes, deconvolution, noise reduction process, and three-velocity analysis. The results show final sessions with high quality and resolution, and better signal-to-noise ratio below the second door-sill, and deliver relevant benefits to the interpreters.
Inductive and Capacitive Hysteresis of Current-Voltage Curves: Unified Structural Dynamics in Solar Energy Devices, Memristors, Ionic Transistors, and Bioelectronics

Hysteresis observed in the current-voltage curves of both electronic and ionic devices is a phenomenon where the curve’s shape is altered on the basis of the measurement speed. This eﬀect is driven by internal processes that introduce a time delay in the response to an external stimulus, leading to measurements being dependent on the history of the past disturbances. This hysteresis eﬀect has posed challenges, particularly in solution-processed photovoltaic devices such as halide perovskite solar cells, where it sig-niﬁcantly complicates the evaluation of performance quality. In other devices, such as memristors and organic electrochemical transistors for neuromorphic applications, hysteresis is an inherent aspect of their functionality, facilitating transitions between diﬀerent conductivity states. Natural and artiﬁcial ionically conducting channels also exhibit pronounced hysteresis, a crucial component for generating action potentials in neurons. In this study, we aim to categorize various forms of hysteresis by identifying shared elements among diverse physical, chemical, and biological conducting systems. Our method involves examining hysteresis from multiple angles, using simpliﬁed models that capture essential response types. We analyze system behavior using techniques such as linear sweep voltammetry and impedance spectroscopy and transient currents resulting from small voltage steps. Our investigation reveals two primary hysteresis types based on how current responds to rapid sweep rates: capacitive hysteresis and inductive hysteresis. These terms correspond to the dominant component in the equivalent circuit, determining the transient time response. Remarkably, these concepts provide insights into vastly diﬀerent systems, spanning solar cells, capacitors, transistors, electroﬂuidic nanopores, and protein ion channels. The consistency in electrical responses across the diﬀerent cases enables the identiﬁcation of the primary cause of hysteresis. We also elucidate the frequency dependence of hysteresis and the stepwise responses of solar cells, illustrating how fundamental relaxations contribute to the overall surplus or deﬁcit of current during extensive voltage sweeps that deﬁne the current-voltage curve.
Unraveling the Phylogenetic Relationships and Taxonomic Status of a Puzzling Freshwater Mussel Genus Inversidens (Bivalvia, Unionidae) through Multilocus Phylogeny and Mitochondrial Phylogenomics

Accurate phylogenetic reconstructions are crucial for comprehending the evolutionary histories, reproductive traits, and ecological habits of organisms. The subfamily Gonideinae of freshwater mussels is currently thought to include eight tribes. However, due to inadequate taxon sampling and molecular data, the assignment of the freshwater mussel genus Inversidens at the tribe level has been unstable. Additionally, the lack of phylogenetic data has hindered efforts to understand the basic biology and implementation of conservation efforts of Inversidens rentianensis, an endemic species to China. Here, we first present the complete mitochondrial genome of Inversidens rentianensis and offer a detailed description of its anatomical morphology. Based on DNA sequence data from five genes (COI, ND1, 16S rRNA, 18S rRNA, and 28S rRNA) and complete mitochondrial genomes, we investigated the phylogenetic position of Inversidens using various analytical methods. Both the concatenated five-gene and mitogenome datasets strongly supported that Inversidens classified to the tribe Gonideini in Gonideinae and formed a basal clade within the tribe Gonideini. Molecular dating analysis suggested that Inversidens originated during the mid-Cretaceous era (102.73 Mya, 95% highest posterior density HPD=72.22‐137.03 Mya) and underwent diversification in the Late Paleogene era (37.92 Mya, 95% HPD=20.39‐60.59 Mya). Moreover, based on the Quantitative Assessment of Species for Conservation (QASCP), Inversidens rentianensis is ranked as second priority, providing valuable insights for its management and conservation efforts. Taken together, this study provides a comprehensive understanding of the systematic position and evolutionary history of Inversidens within the currently accepted subfamily Gonideinae classification framework. These findings establish a solid foundation for future investigations on the ecology, reproductive behavior patterns, and conservation biology of this taxonomic group.
Impact of prenatal marijuana exposure on adolescent brain structural and functional connectivity and behavioural outcomes

Abstract There has been an increase in the number of women using marijuana whilst pregnant. Previous studies have shown that children with prenatal marijuana exposure have developmental deficits in memory and decreased attentiveness. In this study, we assess whether prenatal marijuana exposure is associated with alterations in brain regional morphometry and functional and structural connectivity in adolescents. We downloaded behavioural scores and subject image files from the Adolescent Brain Cognitive DevelopmentSM Study. A total of 178 anatomical and diffusion magnetic resonance imaging files (88 prenatal marijuana exposure and 90 age- and gender-matched controls) and 152 resting-state functional magnetic resonance imaging files (76 prenatal marijuana exposure and 76 controls) were obtained. Behavioural metrics based on the parent-reported child behavioural checklist were also obtained for each subject. The associations of prenatal marijuana exposure with 17 subscales of the child behavioural checklist were calculated. We assessed differences in brain morphometry based on voxel-based and surface-based morphometry in adolescents with prenatal marijuana exposure versus controls. We also evaluated group differences in structural and functional connectivity in adolescents for region-to-region connectivity and graph theoretical metrics. Interactions of prenatal marijuana exposure and graph networks were assessed for impact on behavioural scores. Multiple comparison correction was performed as appropriate. Adolescents with prenatal marijuana exposure had greater abnormal or borderline child behavioural checklist scores in 9 out of 17 subscales. There were no significant differences in voxel- or surface-based morphometry, structural connectivity or functional connectivity between prenatal marijuana exposure and controls. However, there were significant differences in prenatal marijuana exposure–graph network interactions with respect to behavioural scores. There were three structural prenatal marijuana exposure–graph network interactions and seven functional prenatal marijuana exposure–graph network interactions that were significantly associated with behavioural scores. Whilst this study was not able to confirm anatomical or functional differences between prenatal marijuana exposure and unexposed pre-adolescent children, there were prenatal marijuana exposure–brain structural and functional graph network interactions that were significantly associated with behavioural scores. This suggests that altered brain networks may underlie behavioural outcomes in adolescents with prenatal marijuana exposure. More work needs to be conducted to better understand the prognostic value of brain structural and functional network measures in prenatal marijuana exposure.