State transfer in dissipative and dephasing environments

By diagonalization of a generalized superoperator for solving the master equation, we investigated effects of dissipative and dephasing environments on quantum state transfer, as well as entanglement distribution and creation in spin networks. Our results revealed that under the condition of the same decoherence rate $\gamma$, the detrimental effects of the dissipative environment are more severe than that of the dephasing environment. Beside this, the critical time $t_c$ at which the transfer fidelity and the concurrence attain their maxima arrives at the asymptotic value $t_0=\pi/2\lambda$ quickly as the spin chain length $N$ increases. The transfer fidelity of an excitation at time $t_0$ is independent of $N$ when the system subjects to dissipative environment, while it decreases as $N$ increases when the system subjects to dephasing environment. The average fidelity displays three different patterns corresponding to $N=4r+1$, $N=4r-1$ and $N=2r$. For each pattern, the average fidelity at time $t_0$ is independent of $r$ when the system subjects to dissipative environment, and decreases as $r$ increases when the system subjects to dephasing environment. The maximum concurrence also decreases as $N$ increases, and when $N\rightarrow\infty$, it arrives at an asymptotic value determined by the decoherence rate $\gamma$ and the structure of the spin network.Comment: 12 pages, 6 figure

Teleportation of the one-qubit state with environment-disturbed recovery operations

We study standard protocol $\mathcal{P}_0$ for teleporting the one-qubit state with both the transmission process of the two qubits constitute the quantum channel and the recovery operations performed by Bob disturbed by the decohering environment. The results revealed that Bob's imperfect operations do not eliminate the possibility of nonclassical teleportation fidelity provided he shares an ideal channel state with Alice, while the transmission process is constrained by a critical time $t_{0,c}$ longer than which will result in failure of $\mathcal{P}_0$ if the two qubits are corrupted by the decohering environment. Moreover, we found that under the condition of the same decoherence rate $\gamma$, the teleportation protocol is significantly more fragile when it is executed under the influence of the noisy environment than those under the influence of the dissipative and dephasing environments.Comment: 8 pages, 4 figure

Various correlations in a Heisenberg XXZ spin chain both in thermal equilibrium and under the intrinsic decoherence

In this paper we discuss various correlations measured by the concurrence (C), classical correlation (CC), quantum discord (QD), and geometric measure of discord (GMD) in a two-qubit Heisenberg XXZ spin chain in the presence of external magnetic field and Dzyaloshinskii-Moriya (DM) anisotropic antisymmetric interaction. Based on the analytically derived expressions for the correlations for the cases of thermal equilibrium and the inclusion of intrinsic decoherence, we discuss and compare the effects of various system parameters on the correlations in different cases. The results show that the anisotropy Jz is considerably crucial for the correlations in thermal equilibrium at zero temperature limit but ineffective under the consideration of the intrinsic decoherence, and these quantities decrease as temperature T rises on the whole. Besides, J turned out to be constructive, but B be detrimental in the manipulation and control of various quantities both in thermal equilibrium and under the intrinsic decoherence which can be avoided by tuning other system parameters, while D is constructive in thermal equilibrium, but destructive in the case of intrinsic decoherence in general. In addition, for the initial state $|\Psi_1(0) > = \frac{1}{\sqrt{2}} (|01 > + |10 >)$, all the correlations except the CC, exhibit a damping oscillation to a stable value larger than zero following the time, while for the initial state $|\Psi_2(0) > = \frac{1}{\sqrt{2}} (|00 > + |11 >)$, all the correlations monotonously decrease, but CC still remains maximum. Moreover, there is not a definite ordering of these quantities in thermal equilibrium, whereas there is a descending order of the CC, C, GMD and QD under the intrinsic decoherence with a nonnull B when the initial state is $|\Psi_2(0) >$.Comment: 8 pages, 7 figure

Control and manipulation of entanglement between two coupled qubits by fast pulses

We have investigated the analytical and numerical dynamics of entanglement for two qubits that interact with each other via Heisenberg XXX-type interaction and subject to local time-specific external kick and Gaussian pulse-type magnetic fields in x-y plane. The qubits have been assumed to be initially prepared in different pure separable and maximally entangled states and the effect of the strength and the direction of external fast pulses on concurrence has been investigated. The carefully designed kick or pulse sequences are found to enable one to obtain constant long-lasting entanglement with desired magnitude. Moreover, the time ordering effects are found to be important in the creation and manipulation of entanglement by external fields.Comment: 18 pages, 6 figure

State transfer in intrinsic decoherence spin channels

By analytically solving the master equation, we investigate quantum state transfer, creation and distribution of entanglement in the model of Milburn's intrinsic decoherence. Our results reveal that the ideal spin channels will be destroyed by the intrinsic decoherence environment, and the detrimental effects become severe as the decoherence rate $\gamma$ and the spin chain length $N$ increase. For infinite evolution time, both the state transfer fidelity and the concurrence of the created and distributed entanglement approach steady state values, which are independent of the decoherence rate $\gamma$ and decrease as the spin chain length $N$ increases. Finally, we present two modified spin chains which may serve as near perfect spin channels for long distance state transfer even in the presence of intrinsic decoherence environments $\mathcal {F}{[\rho(t)]}$.Comment: 11 pages, 11 figure

Experimental characterisation of textile compaction response: A benchmark exercise

This paper reports the results of an international benchmark exercise on the measurement of fibre bed compaction behaviour. The aim was to identify aspects of the test method critical to obtain reliable results and to arrive at a recommended test procedure for fibre bed compaction measurements. A glass fibre 2/2 twill weave and a biaxial (±45°) glass fibre non-crimp fabric (NCF) were tested in dry and wet conditions. All participants used the same testing procedure but were allowed to use the testing frame, the fixture and sample geometry of their choice. The results showed a large scatter in the maximum compaction stress between participants at the given target thickness, with coefficients of variation ranging from 38% to 58%. Statistical analysis of data indicated that wetting of the specimen significantly affected the scatter in results for the woven fabric, but not for the NCF. This is related to the fibre mobility in the architectures in both fabrics. As isolating the effect of other test parameters on the results was not possible, no statistically significant effect of other test parameters could be proven. The high sensitivity of the recorded compaction pressure near the minimum specimen thickness to changes in specimen thickness suggests that small uncertainties in thickness can result in large variations in the maximum value of the compaction stress. Hence, it is suspected that the thickness measurement technique used may have an effect on the scatter

Advances in Electronic-Nose Technologies Developed for Biomedical Applications

The research and development of new electronic-nose applications in the biomedical field has accelerated at a phenomenal rate over the past 25 years. Many innovative e-nose technologies have provided solutions and applications to a wide variety of complex biomedical and healthcare problems. The purposes of this review are to present a comprehensive analysis of past and recent biomedical research findings and developments of electronic-nose sensor technologies, and to identify current and future potential e-nose applications that will continue to advance the effectiveness and efficiency of biomedical treatments and healthcare services for many years. An abundance of electronic-nose applications has been developed for a variety of healthcare sectors including diagnostics, immunology, pathology, patient recovery, pharmacology, physical therapy, physiology, preventative medicine, remote healthcare, and wound and graft healing. Specific biomedical e-nose applications range from uses in biochemical testing, blood-compatibility evaluations, disease diagnoses, and drug delivery to monitoring of metabolic levels, organ dysfunctions, and patient conditions through telemedicine. This paper summarizes the major electronic-nose technologies developed for healthcare and biomedical applications since the late 1980s when electronic aroma detection technologies were first recognized to be potentially useful in providing effective solutions to problems in the healthcare industry

The Potential of a CT-Based Machine Learning Radiomics Analysis to Differentiate Brucella and Pyogenic Spondylitis

Parhat Yasin,1 Muradil Mardan,2 Dilxat Abliz,3 Tao Xu,1 Nuerbiyan Keyoumu,4 Abasi Aimaiti,4 Xiaoyu Cai,1 Weibin Sheng,1 Mardan Mamat1 1Department of Spine Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, People’s Republic of China; 2School of Medicine, Tongji University, Shanghai, 200092, People’s Republic of China; 3Department of Orthopedic, The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, People’s Republic of China; 4Department of Anesthesiology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054, People’s Republic of ChinaCorrespondence: Mardan Mamat, Tel +86 0991-4365316, Email [email protected]: Pyogenic spondylitis (PS) and Brucella spondylitis (BS) are common spinal infections with similar manifestations, making their differentiation challenging. This study aimed to explore the potential of CT-based radiomics features combined with machine learning algorithms to differentiate PS from BS.Methods: This retrospective study involved the collection of clinical and radiological information from 138 patients diagnosed with either PS or BS in our hospital between January 2017 and December 2022, based on histopathology examination and/or germ isolations. The region of interest (ROI) was defined by two radiologists using a 3D Slicer open-source platform, utilizing blind analysis of sagittal CT images against histopathological examination results. PyRadiomics, a Python package, was utilized to extract ROI features. Several methods were performed to reduce the dimensionality of the extracted features. Machine learning algorithms were trained and evaluated using techniques like the area under the receiver operating characteristic curve (AUC; confusion matrix-related metrics, calibration plot, and decision curve analysis to assess their ability to differentiate PS from BS. Additionally, permutation feature importance (PFI; local interpretable model-agnostic explanations (LIME; and Shapley additive explanation (SHAP) techniques were utilized to gain insights into the interpretabilities of the models that are otherwise considered opaque black-boxes.Results: A total of 15 radiomics features were screened during the analysis. The AUC value and Brier score of best the model were 0.88 and 0.13, respectively. The calibration plot and decision curve analysis displayed higher clinical efficiency in the differential diagnosis. According to the interpretation results, the most impactful features on the model output were wavelet LHL small dependence low gray-level emphasis (GLDN).Conclusion: The CT-based radiomics models that we developed have proven to be useful in reliably differentiating between PS and BS at an early stage and can provide a reliable explanation for the classification results.Keywords: Brucella spondylitis, Pyogenic spondylitis, machine learning, radiomics, model interpretatio