Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards microwave based ion trap quantum technology

Scalability is a challenging yet key aspect required for large scale quantum computing and simulation using ions trapped in radio-frequency (rf) Paul traps. In this thesis 171Yb+ ions are used to demonstrate a magnetic field insensitive qubit which has a measured coherence time of 1.5 s, making it an ideal candidate to use for storing quantum information. A magnetic field sensitive qubit is also characterised which can be used for the implementation of multi-qubit gates using a potentially very scalable scheme based on microwaves in conjunction with a static magnetic field gradient instead of using lasers. However, the measured coherence time is limited by magnetic field fluctuations and will prohibit high fidelity gate operations from being performed. To address this issue, the preparation of a dressed-state qubit using a microwave based stimulated rapid adiabatic passage (STIRAP) pulse sequence will be presented. This qubit is protected against the noisy environment making it less sensitive to magnetic field fluctuations. The lifetime of this qubit is measured to demonstrate its suitability for storing quantum information. A powerful method for manipulating the dressed-state qubit will be presented and is used to measure a coherence time of the qubit of 500 ms which is two orders of magnitude longer compared to the magnetic field sensitive qubit. It will also be shown that our method allows for the implementation of arbitrary rotations of the dressed-state qubit on the Bloch sphere using only a single rf field. This substantially simplifies the experimental setup for single and multi-qubit gates. Furthermore, this thesis will present a experimental setup capable of successfully operating microfabricated surface ion traps. This setup is then used to operate and characterise the first two-dimensional (2D) lattice of ion traps on a microchip. A unique feature of the microfabrication technique used for this device is the extremely large voltage that can be applied which allows long ion lifetimes along with large secular frequencies to be measured, demonstrating the robustness of this device. Rudimentary shuttling between neighbouring lattice sites will be shown which could be used as part of a efficient scheme to load a large lattice of ions. One of the many applications of a 2D lattice of ions lies in the field of quantum simulations where many-body systems such as quantum magnetism, high temperature superconductivity, the fractional quantum hall effect and synthetic gauge fields can be simulated. It will be shown how making only minor modifications to the microchip the ion-ion separation can be reduced sufficiently to offer an exciting platform for the successful implementation of 2D quantum simulations. A theoretical investigation on the optimal 2D ion trap lattice geometry will also be presented with the aim to maximise the ratio of ion-ion coupling strength to decoherence from motional heating of the ions and to laser induced off-resonant coupling.
Average heat-transfer characteristics of a row of circular air jets impinging on a concave surface

A study of the average heat-transfer characteristics of air jets impinging on the concave side of a right-circular semicylinder is reported. Results from existing correlating are compared with each other and with experimental heat-transfer data for a row of circular jets. Two correlations available in the literature are recommended for use in designing cooled turbine vanes and blades.
A Stylistic Analysis of Junctures in Relation to Pauses in Doctor Strange and Aladdin Movies

The study has investigated and examined different types of pauses, both filled (hesitations) and nonfilled (silent pauses) in terms of phonology in both Aladdin and Doctor Strange movies. It has been found that filled pauses (i.e. hesitations) have been used in the movies mainly to provide only lengthening, repeat and self-correction. Yet, there are other features of hesitations which are called interjection hesitations which are (oh, uh, uh-huh, mm, er, and well). All of these pauses have been demonstrated and clarified by junctures that connect sounds that precede and follow them in the subsequent utterances. These junctures, in turn, are of two types: open and close. Open junctures, which sense pauses, provide purposeful stoppage or delay in speech, whereas close ones appear along with the flow of the speech and they do not sense pauses but they appear prominently along with the speech. Strikingly significant, both these open and close junctures appear along with rhythm and intonation because they are presented for a meaning. The two types also appear with filled and non-filled pauses. Phonologically speaking, junctures can be presented as a technical term for pauses, so the term pause is rather an umbrella term under which come juncture; therefore, the title pause subsumes all types of pauses. It has been found that these pauses have been used in both movies to reflect the different psychological states and the different contexts whereby they are produced. Strikingly impressive, these pauses can be perceived as important stylistic markers in the movies and they have peculiar effects on text production and comprehension. Hence, this thesis attempts to accomplish the following aims:
Millimeter-wave Interferometric Sensing

Abstract : Millimeter-wave sensing systems designed for imaging almost always produce inferior images compared to their infrared and visible wavelength counterparts for a variety of fundamental reasons. These reasons include low detector/pixel count, poor signal-to-noise ratio, artifacts introduced by illumination, and issues arising from calibration or scanning schemes. This research effort is intended to address the issue of low-detector-count focal-plane arrays (FPA). Radio astronomers have dealt with this issue for many decades by using interferometry, or coherence imaging. This report details how interferometric imaging techniques can be used in the millimeter-wave regime for terrestrial applications.
Midnight Sun to Polar Night: A Model of Seasonal Light in the Barents Sea

Arctic marine ecosystems are strongly influenced by the extreme seasonality of light in the region. Accurate determination of light is essential for building a comprehensive understanding of the dynamics of animal and aquatic algae populations. Current approaches to underwater light field parameterisations rely upon shortwave radiation (300–3000 nm) estimates from satellites or surface radiometry measurements to populate full radiative transfer software. Due to the inaccessibility of many regions in the Arctic, measured data is not widely available. This study presents a model of spectrally resolved underwater light in ice‐free conditions in the Barents Sea. Given a location and time, the model accounts for downwelling spectral irradiance in the photosynthetically active radiation (PAR, 400–700 nm) range (ED PAR) at the ocean surface from solar, lunar, and galactic light sources, modulated by local cloud cover. We demonstrate the ability to extend over the full year into the period of Polar Night, validated in both broadband PAR and spectral domains. Using a bio‐optical model of diffuse attenuation developed for the Barents Sea, we show accurate calculations to depth for inhomogeneous water columns over a spatial‐temporal range, validated against time series irradiance data from the ArcLight observatory in Ny‐Ålesund, Svalbard and in‐situ irradiance sensors deployed in the Barents Sea. Finally, in comparison to state‐of‐the‐art radiative transfer models, averaged over the water column we demonstrate a typical mean absolute error of <1 μmol m−2 s−1 in ED PAR for overcast conditions (<6 μmol m−2 s−1 for clear‐sky) and reduced execution time of factor 20.
Role of MORE AXILLARY GROWTH2 (MAX2) protein in regulation of karrikin and strigolactone signalling pathways

Recommended Citation SINGH, SARIKA; UDDIN, MOIN; KHAN, M. MASROOR A. ; CHISHTI, SOBIA AMAN; SINGH, SANGRAM; and BHATT, UROOJ HASSAN (2022) "Role of MORE AXILLARY GROWTH2 (MAX2) protein in regulation of karrikin and strigolactone signalling pathways," Turkish Journal of Botany: Vol. 46: No. 5, Article 2. https://doi.org/10.55730/1300-008X.2720 Available at: https://journals.tubitak. gov.tr/botany/vol46/iss5/2
KLHDC8A Expression in Association with Macrophage Infiltration and Oxidative Stress Predicts Unfavorable Prognosis for Glioma

Background The tumor immune microenvironment (TME) is associated with cancer progression and immune escape. Although KLHDC8A has been reported in glioma in vitro, the expression and clinical significance of this gene in clinical samples are unknown. Methods The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases were used to evaluate the mRNA expression level of KLHDC8A and its significance in the glioma TME. Tissue microarray-based multiple immunohistochemical staining was conducted to determine KLHDC8A protein levels and characterize the immune signature of tumor-infiltrating immune cells in gliomas. Results Tumor cells and tumor-associated macrophages expressed KLHDC8A. The expression of KLHDC8A was higher in glioma tissues than in normal brain tissues and was associated with patient clinical characteristics. Gliomas exhibited a high abundance of macrophages, neutrophils, regulatory T cells, and the immune checkpoint PD-L1, as well as high KLHDC8A expression. Cox regression analysis showed that KLHDC8A+CD68+ macrophages and KLHDC8A predicted unfavorable survival in patients with glioma. Finally, protein-protein interaction network analysis showed that the KLHDC8A expression was associated with hypoxia and oxidative stress. Conclusions KLHDC8A is a potential marker for the clinical diagnosis of glioma. The immune characteristics of macrophages play a crucial role in predicting patients with glioma, providing a new avenue for targeted glioma therapy.
A Dual-Port Single-Dipole MIMO Antenna Pair Based on Selective Modal Excitation for 5G Metal-Rimmed Terminals

This study presents a dual-port single-dipole MIMO antenna pair, which is accomplished by selectively exciting the dominant dipole-type current mode and the second higher current mode of a single suspended metal strip. A magnetic coupling method based on a feeding loop is implemented at the current maximum portion of the dominant mode of the suspended metal strip, such that the suspended metal strip operates as a half-wavelength dipole radiator. An electrical coupling method based on a feeding capacitor, otherwise, excites the wavelength dipole mode of the suspended metal strip, and this higher mode resonance is further controlled by a tuning capacitor. In this way, the suspended metal strip involves a dual-port MIMO antenna pair, and both antennas operate as dipole-type radiators while having high port-to-port isolation because of the modal orthogonality. Therefore, the operation mechanism of the proposed technique is straightforward, and the implementation is simple, free of any additional decoupling components or a complex excitation network. This feature makes the proposed technique an attractive solution in metal-rimmed terminals for 5G applications, so $4\times $ 4 MIMO antennas operating at the N78 band were constructed and verified in both simulation and measurement.
An LSTM-PINN Hybrid Method to Estimate Lithium-Ion Battery Pack Temperature

Physics-based models for battery temperature prediction are often not suitable for online applications due to the large number of fitted parameters, low fidelity results from parameter inaccuracy and unaccounted model dynamics, limited high quality experimental data, and slow convergence of predictions from unknown initial conditions. On the other hand, data-driven models require much less computational power but a large dataset to learn the time dependent behavior. This paper proposes a physics-informed neural network (PINN) to take full advantage of both physics-based and data-driven models. Four comparative studies were performed to investigate the effectiveness of including chamber temperature with two different activation functions, the optimal number of neurons and hidden layers, the dependance on reversible heat generation, and the performance of long short-term memory (LSTM)-PINN model. The results show that the LSTM-PINN with chamber temperature as one of the inputs delivers better prediction accuracy. The LSTM-PINN with an exponential activation function for the chamber temperature has a more accurate prediction for the direct current fast charge (DCFC) test profile and similar prediction accuracy for the grade load (GL) 100 test profile. The root mean square errors (RMSEs) of the LSTM-PINN are 0.57°C for DCFC and 0.52°C for GL 100, respectively. In addition, having 55 neurons and 4 hidden layers gives the lowest prediction error. Furthermore, the improvement by having reversible heat generation is negligible. At last, the LSTM-PINN model has less prediction error than the LSTM model, especially when the battery temperature range is enormous.
Inverse inference in the asymmetric Ising model

Recent experimental techniques in biology made possible the acquisition of overwhelming amounts of data concerning complex biological networks, such as neural networks, gene regulation networks and protein-protein interaction networks. These techniques are able to record states of individual components of such networks (neurons, genes, proteins) for a large number of configurations. However, the most biologically relevantinformation lies in their connectivity and in the way their components interact, information that these techniques aren't able to record directly. The aim of this thesis is to study statistical methods for inferring information about the connectivity of complex networks starting from experimental data. The subject is approached from a statistical physics point of view drawing from the arsenal of methods developed in the study of spin glasses. Spin-glasses are prototypes of networks of discrete variables interacting in a complex way and are widely used to model biological networks. After an introduction of the models used and a discussion on the biological motivation of the thesis, all known methods of network inference are introduced and analysed from the point of view of their performance. Then, in the third part of the thesis, a new method is proposed which relies in the remark that the interactions in biology are not necessarily symmetric (i.e. the interaction from node A to node B is not the same as the one from B to A). It is shown that this assumption leads to methods that are both exact and efficient. This means that the interactions can be computed exactly, given a sufficient amount of data, and in a reasonable amount of time. This is an important original contribution since no other method is known to be both exact and efficient.
Study on Wear of Electromagnetic Railgun

Sliding friction wear of high-speed current-carrying is a key factor limiting the engineering of electromagnetic railgun, and is also a hot spot and difficult area for current research. In this paper, we simulate the internal ballistic dynamics and electrical contact characteristics based on multi-physics field effects and consider the actual working conditions such as Lorentz force, friction force and interference fit to simulate the motion of the armature in the bore. Based on the Archard wear model, a finite element simulation method combining HyperMesh and ANSYS is proposed to realize the wear prediction. The simulation results are compared with the experimental results to verify the accuracy of the prediction model. The results show that under the single firing condition, the wear is mainly concentrated at the end of the armature arm, and the rail wear is relatively light; with the increase of electromagnetic thrust, the increase of armature wear volume does not change much and is approximately equal; the armature wear volume is influenced by the wear coefficient, in which the armature wear volume increases about 190 times when the wear coefficient increases from $1\times 10^{-6}$ to $1\times 10^{-3}$ . Therefore, in order to reduce the degree of wear between the armature and rails, the lubrication conditions should be improved as much as possible. This study provides a simulation method for the wear prediction of electromagnetic rail launcher, which is important for the engineering application of electromagnetic rail launcher.
A hybrid recommender system based on description/dialetheic logic and linked data

In this research, we developed a hybrid recommender system based on description/dialetheic logic, which provides an innovative architecture for the recommendation based on ambiguous reasoning. In addition, our approach allows enriching the knowledge during the reasoning using the linked data paradigm. Thus, the architecture allows the integration of linked data, in order to be exploited by the recommender. On the other hand, the reasoning mechanisms of dialetheic logic allow handling situations of contradiction or inconsistency, to determine the information to offer to users. According to the reviewed literature, our proposal is the first that implements a dialetheic engine in a Recommender System. In general, there are a lot of works about the utilization of linked open data (LOD) to improve the Recommender Systems, for example, to enrich the information to recommend or to solve the cold start problem. However, there are no proposals to deal with the problems of ambiguity, incoherence or incompleteness of the information in these environments extended with LOD. In this way, this paper proposes a hybrid reasoning engine that uses the linked data paradigm for the knowledge extraction, and dialetheic logic for the management of inconsistency/ambiguity information, in order to obtain recommendations. Particularly, the information extracted with Linked Data is processed with the Dialetheic Logic reasoner to solve ambiguous cases. Thus, each recommendation is enriched with related content extracted from the linked data sources, which has been disambiguated. The results are very promising since our hybrid reasoning mechanism allows obtaining more precise recommendations, considering the different classical states of ambiguity in dialetheic logic (contingent statements about the future, failure of a presupposition, vagueness, counterfactual reasoning), according to various metrics of quality used to evaluate the recommendations achieved.
Family Structure and Family Climate in Relation to Health and Socioeconomic Status for Older Adults: A Longitudinal Moderated Mediation Analysis

Family characteristics are associated with individuals’ health and wellbeing. However, the link between family structure (e.g., operationalized via marital status) and health outcomes is ambiguous, and whether family climate mediates the relationship is unclear. This study uses the Biobehavioral Family Model (BBFM) to investigate the association of older adults’ family structure with later health, the mediating role of family climate and mental health and how these links vary by socioeconomic status (SES). Using data from n = 29,457 respondents aged over 50 in Waves 4, 5 and 6 (2011, 2013 and 2015) of the Survey of Health, Retirement and Ageing in Europe (SHARE), the BBFM was applied in a longitudinal mediation analysis of family structure and health, including both indicators of mental and physical health. Structural equation modeling was applied, and a multigroup analysis was performed to test the role of SES in a moderated mediation. Family climate and mental health mediated the relationship between family structure and subsequent physical health. Good levels of family climate were found to be consistently associated with improved mental and physical health. These relationships were significantly moderated by SES, showing that the association of family climate and health was weaker for those in low SES positions. Family climate and mental health should be considered as potential mechanisms linking family structure to later physical health outcomes across time; however, these associations are diminished for those with low SES.
A DFT study of the adsorption of F atoms on germanene nanoribbons

In the paper, we investigate the structure and electronic properties of the pristine germanene nanoribbon and four adsorption configurations of 1F and 2F on the substrate of germanene nanoribbon. We obtained the parameters of the most stable structures of pristine germanene nanoribbon and four adsorption configurations. The band structure and the density of state and the part density of state for each element were also obtained. Findings show the adsorption configuration of 1F-GeNR.bridge has no band structure, while other configurations are semimetals with band gap from 0.175eV to 0.67eV; both four adsorption configurations are chemisorption and non-magnetic. The charge distribution of all configurations also was investigated; it showed that there is a charge shift from Ge atoms towards F atoms due to their electronegativity difference.
A Nomogram to Identify Hyperkalemia Risk in Patients with Advanced CKD

Key Points Tools for diagnosis or prediction of hyperkalemia in CKD are limited, especially in patients not using RAASi. This study constructed a convenient nomogram and online calculator to identify the risk of hyperkalemia within 6 months in patients with advanced CKD. Patients with CKD who are identified as high risk of hyperkalemia by the tool may benefit from intensive monitoring and early triage. Visual Abstract Background Hyperkalemia is a common and life-threatening complication of CKD. We aimed to develop and validate a nomogram that could identify the risk of hyperkalemia (≥5.5 mmol/L) in patients with CKD. Methods A retrospective cohort study was performed in adult patients with predialysis advanced CKD (stages ≥3) in 2020–2021 for the outcome of hyperkalemia within 6 months. The training set was used to identify risk factors of hyperkalemia. Then a nomogram was developed by multivariable logistic regression analysis. C-statistics, calibration curves, and decision curve analysis (DCA) were used, and the model was validated in the internal and two external validation sets. Results In total, 847 patients with advanced CKD were included. In 6 months, 28% of patients had hyperkalemia (234 out of 847). Independent risk factors were: age ≥75 years, higher CKD stages, previous event of serum potassium ≥5.0 mmol/L within 3 months, and comorbidities with heart failure, diabetes, or metabolic acidosis. Then the nomogram on the basis of the risk factors adding the use of renin-angiotensin-aldosterone system inhibitors was constructed. The C-statistic of the model was 0.76 (95% CI, 0.70 to 0.78), and was stable in both the internal validation set (0.73; 95% CI, 0.63 to 0.82) and external validation sets (0.88; 95% CI, 0.84 to 0.95 and 0.82; 95% CI, 0.72 to 0.92). Calibration curves and DCA analysis both found good performances of the nomogram. Conclusion A feasible nomogram and online calculator were developed and validated to evaluate the risk of hyperkalemia within 6 months in patients with advanced CKD. Patients with CKD and a high risk of hyperkalemia may benefit from intensive monitoring and early triage.