Absence of magnetically-induced fractional quantization in atomic contacts

Using the mechanically controlled break junction technique at low temperatures and under cryogenic vacuum conditions we have studied atomic contacts of several magnetic (Fe, Co and Ni) and non-magnetic (Pt) metals, which recently were claimed to show fractional conductance quantization. In the case of pure metals we see no quantization of the conductance nor half-quantization, even when high magnetic fields are applied. On the other hand, features in the conductance similar to (fractional) quantization are observed when the contact is exposed to gas molecules. Furthermore, the absence of fractional quantization when the contact is bridged by H_2 indicates the current is never fully polarized for the metals studied here. Our results are in agreement with recent model calculations.Comment: 4 pages, 3 figure

Effect of bonding of a CO molecule on the conductance of atomic metal wires

We have measured the effect of bonding of a CO molecule on the conductance of Au, Cu, Pt, and Ni atomic contacts at 4.2 K. When CO gas is admitted to the metal nano contacts, a conductance feature appears in the conductance histogram near 0.5 of the quantum unit of conductance, for all metals. For Au, the intensity of this fractional conductance feature can be tuned with the bias voltage, and it disappears at high bias voltage (above $\sim$ 200 mV). The bonding of CO to Au appears to be weakest, and associated with monotomic Au wire formation.Comment: 6 figure

Newly Licensed RNs Describe What They Like Best about Being a Nurse

About 25% of newly licensed registered nurses (NLRNs) leave their first job within two years, but only 2% leave the nursing profession in this same timeframe. Therefore, the researchers sought to discover what new nurses like best about being a nurse, in hopes of gaining information that might help facilities to reduce turnover rates. Data were collected between January and March 2009 from 1,152 NLRNs licensed in 15 US states. Krippendorff's method was used to analyze survey responses. Five themes emerged: “providing holistic patient care,” “having an autonomous and collaborative practice,” “using diverse knowledge and skills to impact patient outcomes,” “receiving recognition,” and “having a job that is secure and stimulating.” Strategies are discussed that organizations might employ in helping NLRNs to realize what they best like about their work, which might lead to improved retention rates

Effects of Phytogenic Feed Additive and Enzyme on Growth Performance of Broilers Fed Diets with Reduced Energy Concentrations

The effects of dietary supplementation with phytogenic feed additives (PFA) and enzyme (E) on performance parameters were investigated using Ross 308 as hatched broilers fed standard diets or diets with reduced energy concentrations. Birds were assigned to 5 treatments with 5 replications each and fed either a standard basal diet or a re-formulated basal diet with reduced energy concentrations. Reduction was made according to enzyme matrix (Ronozyme WX, DSM). Treatments were: (1) Standard diet; (2) Negative control (NC) – 4% reduction in ME (3) NC + E; (4) NC + PFA (5) NC + E + PFA. Body weight and feed consumption were recorded weekly. Mortality was recorded on daily basis. Foot pad lesions were scored at day 35 using scale from 0 (no lesion) to 2 (lesion extending through skin). The results showed that birds fed Negative control diets had a significantly lower body weights (P0.05). Mortality and FCR did not differ significantly between treatments. Average foot pad lesion score was the highest in Negative control (1.05) and the lowest in NC+E (0.55). In conclusion, re-formulation of diets for 4% energy reduction decreased broiler growth rate. Supplementation of diets with PFA improved live weight especially in combination with enzyme, hence confirming a growth-promoting effect of both phytogenics and enzymes in broilers

Compressive, tensile and thermal properties of epoxy grouts subjected to underwater conditioning at elevated temperature

Oil and gas pipes are susceptible to failure initiated by corrosion due to their operating pressure under adverse atmospheric conditions. Repairs, comprising a composite shell assembled around the pipe with a small gap, which is then infilled with grout, are considered a suitable option for corroded pipelines. This paper presents the investigation on the mechanical (compression, tension) properties and glass transition temperatures of two infill grouts, after 1000 hour of hot/wet conditioning. An extended investigation on the moisture absorption behaviour was also carried out, revealing the highest absorption to be about 6% after 2520 hours of immersion. The glass transition temperatures of the grouts are reduced by approximately 20ºC. The results suggest that the grouts underwent significant reduction of strength and stiffness due to hot/wet conditioning when tested at an elevated temperature, compared to room temperature. This reduced strength and stiffness is the result of the grouts being tested in close proximity to their glass transition temperatures

Prior Knowledge based Advanced Persistent Threats Detection for IoT in a Realistic Benchmark

The number of Internet of Things (IoT) devices being deployed into networks is growing at a phenomenal level, which makes IoT networks more vulnerable in the wireless medium. Advanced Persistent Threat (APT) is malicious to most of the network facilities and the available attack data for training the machine learning-based Intrusion Detection System (IDS) is limited when compared to the normal traffic. Therefore, it is quite challenging to enhance the detection performance in order to mitigate the influence of APT. Therefore, Prior Knowledge Input (PKI) models are proposed and tested using the SCVIC-APT- 2021 dataset. To obtain prior knowledge, the proposed PKI model pre-classifies the original dataset with unsupervised clustering method. Then, the obtained prior knowledge is incorporated into the supervised model to decrease training complexity and assist the supervised model in determining the optimal mapping between the raw data and true labels. The experimental findings indicate that the PKI model outperforms the supervised baseline, with the best macro average F1-score of 81.37%, which is 10.47% higher than the baseline.Comment: IEEE Global Communications Conference (Globecom), 2022, 6 pages, g figures, 6 table

Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats

Despite its technological benefits, Internet of Things (IoT) has cyber weaknesses due to the vulnerabilities in the wireless medium. Machine learning (ML)-based methods are widely used against cyber threats in IoT networks with promising performance. Advanced persistent threat (APT) is prominent for cybercriminals to compromise networks, and it is crucial to long-term and harmful characteristics. However, it is difficult to apply ML-based approaches to identify APT attacks to obtain a promising detection performance due to an extremely small percentage among normal traffic. There are limited surveys to fully investigate APT attacks in IoT networks due to the lack of public datasets with all types of APT attacks. It is worth to bridge the state-of-the-art in network attack detection with APT attack detection in a comprehensive review article. This survey article reviews the security challenges in IoT networks and presents the well-known attacks, APT attacks, and threat models in IoT systems. Meanwhile, signature-based, anomaly-based, and hybrid intrusion detection systems are summarized for IoT networks. The article highlights statistical insights regarding frequently applied ML-based methods against network intrusion alongside the number of attacks types detected. Finally, open issues and challenges for common network intrusion and APT attacks are presented for future research.Comment: ACM Computing Surveys, 2022, 35 pages, 10 Figures, 8 Table

Expression of A152T human tau causes age-dependent neuronal dysfunction and loss in transgenic mice.

A152T-variant human tau (hTau-A152T) increases risk for tauopathies, including Alzheimer's disease. Comparing mice with regulatable expression of hTau-A152T or wild-type hTau (hTau-WT), we find age-dependent neuronal loss, cognitive impairments, and spontaneous nonconvulsive epileptiform activity primarily in hTau-A152T mice. However, overexpression of either hTau species enhances neuronal responses to electrical stimulation of synaptic inputs and to an epileptogenic chemical. hTau-A152T mice have higher hTau protein/mRNA ratios in brain, suggesting that A152T increases production or decreases clearance of hTau protein. Despite their functional abnormalities, aging hTau-A152T mice show no evidence for accumulation of insoluble tau aggregates, suggesting that their dysfunctions are caused by soluble tau. In human amyloid precursor protein (hAPP) transgenic mice, co-expression of hTau-A152T enhances risk of early death and epileptic activity, suggesting copathogenic interactions between hTau-A152T and amyloid-β peptides or other hAPP metabolites. Thus, the A152T substitution may augment risk for neurodegenerative diseases by increasing hTau protein levels, promoting network hyperexcitability, and synergizing with the adverse effects of other pathogenic factors

A Software-Agnostic Agent-based Platform for Modelling Emerging Mobility Systems

Due to the rapidly accelerated innovation cycle in transport and the emergence of new mobility concepts and technologies, public authorities, policy makers, and transport planners are currently in need of the tools for sustainable spatial and transport planning in the new mobility era. In this paper, a new modular, software-agnostic and activity-based spatial and transport planning platform is designed, i.e, the HARMONY Model Suite, that facilitates a novel integration of new and existing spatial and transport modelling tools. The paper focuses on describing the architecture of the platform and its passenger mobility simulation framework, which integrates -in an interoperable manner- activity-based models, mobility service management, and traffic simulation tools for evaluating new mobility system dynamics. The service management controllers for new mobility concepts are discussed in more detail with regards to their functionality and applicability