Miracle-dz/UniFAR-FTUs huggingface dataset:
An Energy Supervisor Architecture for Energy-Harvesting Applications

Energy-harvesting designs typically include highly entangled app-lication-level and energy-management subsystems that span both hardware and software. This tight integration makes developing sophisticated energy-harvesting systems challenging, as developers have to consider both embedded system development and intermit-tent energy management simultaneously. Even when successful, solutions are often monolithic, produce suboptimal performance, and require substantial effort to translate to a new design. Instead, we propose a new energy-harvesting power management architecture, Altair that offloads all energy-management operations to the power supply itself while making the power supply programmable. Altair introduces an energy supervisor and a standard interface to enable an abstraction layer between the power supply hardware and the running application, making both replaceable and recon-figurable. To ensure minimal resource conflict on the application processor, while running resource-hungry optimization techniques in the supervisor, we implement the Altair design in a lower power microcontroller that runs in parallel with the application. We also develop a programmable power supply module and a software library for seamless application development with Altair. We evaluate the versatility of the proposed architecture across a spectrum of IoT devices and demonstrate the generality of the plat-form. We also design and implement an online energy-management technique using reinforcement learning on top of the platform and compare the performance against fixed duty-cycle baselines. Results indicate that sensors running the online energy-manager perform similar to continuously powered sensors, have a l0x higher event generation rate than the intermittently powered ones, 1.8-7x higher event detection accuracy, experience 50% fewer power failures, and are 44% more available than the sensors that maintain a constant duty-cycle.
Scrutinizes the Sustainable Role of Halophilic Microbial Strains on Oxygen-Evolving Complex, Specific Energy Fluxes, Energy Flow and Nitrogen Assimilation of Sunflower Cultivars in a Suboptimal Environment

Environmental extremes such as hypersaline conditions are significant threats to agricultural productivity. The sustainable use of halophilic microbial strains was evaluated in plant in a salt stress environment. Oxygen-evolving complex (OEC), energy compartmentalization, harvesting efficiencies (LHE), specific energy fluxes (SEF), and nitrogen assimilation of oilseed crops (Sunflower cultivars) in a suboptimal environment was examined. Plants were grown in a plastic pot (15 ×18 cm2) containing sterilized (autoclaved at 120°C for 1 h) soil. Twenty-five ml suspension (107 CFU/ml) each of Bacillus cereus strain KUB-15 and KUB-27 (accession number NR 074540.1) and Bacillus licheniformis strain AAB9 (accession number MW362506), were applied via drenching method. Month-old plants were subjected to salt stress via gradual increment method. The energy compartmentalization of microbial inoculated plants exposed to salt stress revealed higher photosystem II (PSII) activity at the donor side, lesser photo-inhibition, and increased performance of oxygen-evolving complex compared to control. High potassium (K+) and low sodium (Na+) ions in treated leaves with the activated barricade of the antioxidant system stimulated by Bacillus strains favored enhanced photochemical efficiency, smooth electron transport, and lesser energy dissipation in the stressed plants. Moreover, the results reveal the increased activity of nitrite reductase (NiR) and nitrate reductase (NR) by microbial inoculation that elevated the nitrogen availability in the salt-stressed plant. The current research concludes that the application of bio-inoculants that reside in the hyper-saline environment offers substantial potential to enhance salt tolerance in sunflowers by modulating their water uptake, chlorophyll, nitrogen metabolism, and better photochemical yield.
Portable Wideband Directional Antenna Scheme with Semicircular Corrugated Reflector for Digital Television Reception

This research proposed a portable wideband horizontally-polarized directional antenna scheme with a radome for digital terrestrial television reception. The operating frequency band of the proposed antenna scheme is 470–890 MHz. The portable antenna scheme was an adaptation of the Yagi-Uda antenna, consisting of a folded bowtie radiator, a semicircular corrugated reflector, and a V-shaped director. Simulations were carried out, and an antenna prototype was fabricated. To validate, experiments were undertaken to assess the antenna performance, including the impedance bandwidth (|S11| ≤ −10 dB), gain, and unidirectionality. The measured impedance bandwidth was 75.93%, covering 424–943 MHz, with a measured antenna gain of 2.69–4.84 dBi. The radiation pattern was of unidirectionality for the entire operating frequency band. The measured xz- and yz-plane half-power beamwidths were 150°, 159°, 160° and 102°, 78°, 102° at 470, 680, and 890 MHz, with the corresponding cross-polarization below −20 dB and −40 dB. The radome had a negligible impact on the impedance bandwidth, gain, and radiation pattern. The power obtained for the outdoor test, at 514 MHz, was 38.4 dBµV (−70.4 dBm) with a carrier-to-noise ratio (C/N) of 11.6 dB. In addition, the power obtained for the indoor test was 26.6 dBµV (−82.2 dBm) with a C/N of 10.9 dB. The novelty of this research lies in the concurrent use of the Yagi-Uda and bowtie antenna technologies to improve the impedance bandwidth and directionality of the antenna for digital terrestrial television reception.
Exploiting Duplications for Efficient Task Offloading in Multi-User Edge Computing

The proliferation of IoT applications has pushed the horizon of edge computing, which provides processing ability at the edge of networks. Task offloading is one of the most important issues in edge computing and has attracted continuous research attention in recent years. With task offloading, end devices can offload the entire task or only subtasks to the edge servers to meet the delay and energy requirements. Most existing offloading schemes are limited by the increasing complexity of task topologies, as considerable time is wasted for local/edge subtasks to wait for their precedent subtasks being executed at the edge/local device. This problem becomes even worse when the dependencies among subtasks become complex and the number of end-users increases. To address this problem, our key methodology is to exploit subtask duplications to reduce the inter-subtask delay and shorten the task completion time. Based on this, we propose a Duplication-based and Energy-aware Task Offloading scheme (DETO), which duplicates critical subtasks that have a large impact on the completion time and thus enhances the parallelism between local and edge computing. In addition, among numerous choices of subtask duplications, DETO evaluates the gain/cost ratio for each possible duplication and chooses the most efficient ones. As a result, the extra resource for duplications is greatly reduced. We also design a distributed DETO algorithm to support multi-user, multi-server edge computing. Extensive evaluation results show that DETO can effectively reduce the task completion time (by 12.22%) and improve the resource utilization (by 15.17%), in particular for multi-user edge computing networks.
A&B: AI and Block-Based TCAM Entries Replacement Scheme for Routers

With the ever-increasing deployment of 5G and IoT, the number of end-hosts/terminals is increasing rapidly, so that routers have to cache more and more forwarding entries to guarantee communication reachability of these terminals, which makes Ternary Content Addressable Memory (TCAM)-based routers keep expanding resource requirements. However, the design and implementation of large-capacity TCAM-based routers are faced with such challenges: difficult circuit design, high production cost and energy consumption, thereby posing an urgent requirement on a lightweight TCAM that can still maintain those massive communication connections. In this paper, we aim to design a lightweight router with small storage requirement while still retaining the original communication connection performance, which is not straightforward due to the following two challenges: First, under the condition of massive sequential flow data, it’s difficult to accurately and timely select the entries to cache for a small capacity TCAM. Second, given the strict prefix matching principle, how to efficiently insert the selected entries into TCAM is also challenging. To address these problems, we propose A&B: an AI-based Routing entry prediction strategy (AIR) and a Block-based entry Insertion Tactic (BIT). AIR can precisely select entries by conducting accurate entry predictions, which converts dynamic flow-based prediction into stable and parallelizable entry-based prediction by decoupling spatio-temporal characteristics. BIT optimizes entry insertion by isolating TCAM into several blocks, thus eliminating the time-consuming entry movements. The experiment results based on real backbone traffic show that our lightweight A&B achieves comparable performance compared to the traditional schemes by using only 1/8 TCAM storage.
An Intelligent Two-Layer Intrusion Detection System for the Internet of Things

The Internet of Things (IoT) has become an enabler paradigm for different applications, such as healthcare, education, agriculture, smart homes, and recently, enterprise systems. Significant advances in IoT networks have been hindered by security vulnerabilities and threats, which, if not addressed, can negatively impact the deployment and operation of IoT-enabled systems. This article addresses IoT security and presents an intelligent two-layer intrusion detection system for IoT. The system's intelligence is driven by machine learning techniques for intrusion detection, with the two-layer architecture handling flow-based and packet-based features. By selecting significant features, the time overhead is minimized without affecting detection accuracy. The uniqueness and novelty of the proposed system emerge from combining machine learning and selection modules for flow-based and packet-based features. The proposed intrusion detection works at the network layer, and hence, it is device and application transparent. In our experiments, the proposed system had an accuracy of 99.15% for packet-based features with a testing time of 0.357 μs. The flow-based classifier had an accuracy of 99.66% with a testing time of 0.410 μs. A comparison demonstrated that the proposed system outperformed other methods described in the literature. Thus, it is an accurate and lightweight tool for detecting intrusions in IoT systems.
Housing allowance and the perverse theory of housing outcomes

ABSTRACT This paper challenges economic theory applied within empirical literature on housing allowances for rent. The arguments challenged are (i) subsidy is a price drop, which increases demand, (ii) allowance is income, where housing is a normal good, which raises demand, (iii) higher subsidy increases willingness to pay more for housing, and (iv) allowance incentivises optimal consumption to their highest achievable value. In practice, tenants remain unaware of price discounts for the distribution of rents, rendering revealed preference/demand theory inconsistent. Not incomes, allowances (in New Zealand) unfold as a(regressive) negative income and wealth tax unique to each recipients resources.
Network Pharmacology and Molecular Docking on the Molecular Mechanism of Jiawei-Huang Lian-Gan Jiang Decoction in the Treatment of Colorectal Adenomas

Purpose Jiawei-Huang Lian-Gan Jiang decoction (JWHLGJD) was developed to treat and prevent the patients with colorectal adenomas (CRA) in China. This study is aimed to discover JWHLGJD's active compounds and demonstrate mechanisms of JWHLGJD against CRA through network pharmacology and molecular docking techniques. Methods All the components of JWHLGJD were retrieved from the pharmacology database of Traditional Chinese Medicine Systems Pharmacology (TCMSP). The GeneCards database, the Online Mendelian Inheritance in Man database (OMIM), the DrugBank database, and PharmGKB were used to obtain the genes matching the targets. Cytoscape created the compound-target network. The network of target protein-protein interactions (PPI) was constructed using the STRING database. Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways involved in the targets were analyzed by using the DAVID database. Cytoscape created the component-target-pathway (C-T-P) network. AutoDock Vina software was used to verify the molecular docking of JWHLGJD components and key targets. Core genes linked with survival and tumor microenvironment were analyzed through the Kaplan–Meier plotter and TIMER 2.0 databases, respectively. Results Compound-target network mainly contained 38 compounds and 130 targets of the JWHLGJD associated with CRA. TP53, MAPK1, JUN, HSP90AA1, and AKT1 were identified as core targets by the PPI network. KEGG pathway shows that the pathways in cancer, lipids, and atherosclerosis, PI3K-Akt signaling pathway and MAPK signaling pathway, are the most relevant pathways to CRA. The C-T-P network suggests that the active component in JWHLGJD is capable of regulating target genes of these related pathways. The results of molecular docking showed that berberine and stigmasterol were the top two compounds of JWHLGJD, which had high affinity with TP53 and MAPK1, respectively. And, MAPK1 exerted a more significant effect on the prognosis of adenocarcinoma, for it was highly associated with various immune cells. Conclusion Findings in this study provided light on JWHLGJD's active components, prospective targets, and molecular mechanism. It also gave a potential way to uncovering the scientific underpinning and therapeutic mechanism of traditional Chinese medicine (TCM) formulas.
Stability Analysis of Impulsive Switched Nonlinear Systems With Double State-Dependent Delays

This brief addresses the problem of global asymptotic stability for impulsive switched nonlinear systems (ISNSs) with double state-dependent delays (DSDDs), where the state-dependent delays exist in both subsystem functions and impulsive functions. The innovations of our results are that: 1) Due to the ubiquitous asynchronous phenomenon between the switches and impulses in many practical systems, we investigate the asynchronous phenomenon for ISNSs with DSDDs. 2) Meanwhile, the stabilizing and destabilizing effects of state-dependent delays impulses are fully considered. 3) By utilizing multiple Lyapunov functions, the switching strategy and the impulsive strategy, based on the asynchronous phenomenon, some stability criteria on global asymptotic stability are presented for ISNSs with DSDDs. As a result, the existing results are improved and can be regarded as a special case of the stability criteria in this brief. A simulation example is provided to verify the effectiveness of the developed methods.
Stochastic Analysis of the Marginal and Dependence Structure of Streamflows: From Fine-Scale Records to Multi-Centennial Paleoclimatic Reconstructions

The identification of the second-order dependence structure of streamflow has been one of the oldest challenges in hydrological sciences, dating back to the pioneering work of H.E Hurst on the Nile River. Since then, several large-scale studies have investigated the temporal structure of streamflow spanning from the hourly to the climatic scale, covering multiple orders of magni-tude. In this study, we expanded this range to almost eight orders of magnitude by analysing small-scale streamflow time series (in the order of minutes) from ground stations and large-scale streamflow time series (in the order of hundreds of years) acquired from paleocli-matic reconstructions. We aimed to determine the fractal behaviour and the long-range de-pendence behaviour of the streamflow. Additionally, we assessed the behaviour of the first four marginal moments of each time series to test whether they follow similar behaviours as sug-gested in other studies in the literature. The results provide evidence in identifying a common stochastic structure for the streamflow process, based on the Pareto–Burr–Feller marginal dis-tribution and a generalized Hurst–Kolmogorov (HK) dependence structure.
Mitochondrial genome assembly and phylogenetic analysis of Upeneus japonicus (Houttuyn, 1782) from the East China Sea

Abstract The mitochondrial genome of Upeneus japonicus was successfully assembled by high-throughput sequencing data in this study. This is the first report on the complete mitochondrial genome of U. japonicus, with a total length of 16,535 bp, including 13 protein-coding genes (PCGs), two ribosomal RNA genes (rRNAs), 22 transfer RNA genes (tRNAs), and a control region (D-loop). The overall base composition is 26.05% A, 26.10% T, 29.14% C, and 18.71% G. Phylogenetic analysis showed that U. japonicus was grouped with its sister species U. tragula. The mitochondrial complete genome study of U. japonicus would lay the foundation for further studies in population genetics and evolutionary analysis.
Patient Advocacy in Vascularized Composite Allotransplantation

Over the last two and a half decades vascularized composite allotransplantation (VCA) has developed into a promising therapeutic option for persons who have suffered the loss of limbs, major facial disfigurement, substantial damage to the abdominal wall, primary uterine infertility and other conditions.1 Candidates considering VCA face a difficult choice between continuing to live with their current condition, with its substantial negative impact on their quality of life, or taking on the substantial risks and burdens of a transplant. Furthermore, the outcomes of upper extremity and facial VCA are highly dependent on the capacity and will of the patient to live with an awareness of the risks, cope with the burdens and persist in careful adherence to immunosuppression and physiotherapy. Despite certain advantages of upper extremity and facial VCA in terms of function and cosmesis, the practice has elicited a great deal of ethical concern, including concern that candidates and patients may require special protections because they are especially vulnerable (Hartman, 2007; Perpich, 2010). This essay aims to argue that upper extremity and facial VCA candidates are rightly considered to be especially vulnerable and then explore how the provision of a patient advocate can provide protections during the screening, selection, decision-making process and post-surgical period. This argument will review the use of the concepts of vulnerability and patient advocacy in health care, describe how patient advocates were involved in some of the earliest upper limb transplantations in the United States and suggest how patient advocates in the context of upper extremity and facial VCA may be able to offset some of the concern about the vulnerability of candidates and patients.
The Changes in Microbiotic Composition of Different Intestinal Tracts and the Effects of Supplemented Lactobacillus During the Formation of Goose Fatty Liver

Intestinal bacteria play an important role in the formation of fatty liver in animals by participating in the digestion and degradation of nutrients, producing various metabolites, and altering the barrier effect of the intestine. However, changes in the gut microbiota during the formation of goose fatty liver are unclear. In this study, 80 healthy Landes geese with similar body weights at 70 days of age were randomly divided into two groups: the control group (n = 48; fed ad libitum) and the overfeeding group (n = 32; overfed). The intestinal contents were collected at 0, 12, and 24 days of overfeeding. The 16S rRNA and metagenomic sequencing analyses showed that the dominant phyla were Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. At the genus level, Phyllobacterium, Bacteroides, Helicobacter, Lactobacillus, Enterococcus, and Romboutsia were the dominant genera in the goose intestine, and most of them were probiotics. In the control group, the relative abundance of Firmicutes in the jejunum and ileum gradually decreased with time, while that of Proteobacteria increased, whereas in the overfeeding group, the relative abundance of Firmicutes in the jejunum and ileum decreased and then increased with time, while that of Proteobacteria showed an opposite trend. In addition, supplementing Lactobacillus to the diet reduced body weight and fatty liver weight in overfed geese, but increased the weight of abdominal fat, suggesting that Lactobacillus supplementation might affect the transport of nascent fat from the liver to abdominal fat. In conclusion, the species of intestinal-dominant bacteria in the geese are relatively stable, but their relative abundance and function are affected by a number of factors. Overfeeding promotes the metabolism of nutrients in the jejunum and ileum and increases bacterial adaptability to environmental changes by enhancing their ability to process environmental and genetic information more efficiently. These findings suggest that the effect of overfeeding on the composition of intestinal microbiota may indirectly influence the formation of goose fatty liver through the gut/liver axis.
Comparative Analysis of Neurodegeneration and Axonal Dysfunction Biomarkers in the Cerebrospinal Fluid of Patients with Multiple Sclerosis

Background: Given the significant role of neurodegeneration in the progression of multiple sclerosis (MS) and insufficient therapies, there is an urgent need to better understand this pathology and to find new biomarkers that could provide important insight into the biological mechanisms of the disease. Thus, the present study aimed to compare different neurodegeneration and axonal dysfunction biomarkers in MS and verify their potential clinical usefulness. Methods: A total of 59 patients, who underwent CSF analysis during their diagnostics, were enrolled in the study. Quantitative analysis of neurodegeneration biomarkers was performed through immunological tests. Oligoclonal bands were detected by isoelectric focusing on agarose gel, whereas the concentrations of immunoglobulins and albumin were measured using nephelometry. Results: Our studies showed that NfL, RTN4, and tau protein enabled the differentiation of MS patients from the control group. Additionally, the baseline CSF NfL levels positively correlated with the tau and MRI results, whereas the RTN4 concentrations were associated with the immunoglobulin quotients. The AUC for NfL was the highest among the tested proteins, although the DeLong test of the ROC curves showed no significant difference between the AUCs for NfL and RTN4. Conclusion: The CSF NfL, RTN-4, and tau levels at the time of diagnosis could be potential diagnostic markers of multiple sclerosis, although NfL seems to have the best clinical value.
THE PERTURBED GENERALIZED TIKHONOV'S ALGORITHM

We work on the research of a zero of a maximal monotone operator on a real Hilbert space. Following the recent progress made in the context of the proximal point algorithm devoted to this problem, we introduce simultaneously a variable metric and a kind of relaxation in the perturbed Tikhonov's algorithm studied by P. Tossings. So, we are led to work in the context of the variational convergence theory.