Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of Covid-19 on labour migration in the CIS

This study responds to the need for measures to mitigate the effects of national actions to slow the spread of Covid-19. National responses are dynamic processes and thus an elusive, albeit important, object of study. The governments of most CIS countries acted promptly and decisively in countering the pandemic. The comprehensive measures have had a serious impact on citizens’ mobility and employment situation. Among the affected are millions of migrants working in the CIS. This article offers a comparative analysis, followed by synthesis, of the negative effects of the Covid-19 pandemic as seen through the prism of employment and the situation of migrant workers in the CIS. Another focus is the restriction and support measures and how they have affected migrants. A range of qualitative and quantitative data was collated on the situation of migrant workers during Covid-19 restriction in the Russian Federation and across the CIS. The findings suggest that the lack of international coordination in tackling Covid-19 has complicated the situation of migrant workers, who suffer from the closure of borders and the absence of adequate social support. The article explores problems faced by migrant workers in the current crisis and proposes measures to alleviate them.
Steady-State Modeling of a Dual-Active Bridge AC–DC Converter Considering Circuit Nonidealities and Intracycle Transient Effects

Steady-state operation of dual active bridge (DAB) ac–dc converters can show a high dependence on the circuit nonidealities and on the transient nature of the consistently changing phase-shifts necessary to achieve ac–dc operation. These aspects are not fully captured using traditional modeling approaches derived from dc–dc DAB converter analyses. To address these issues, this article presents a unified modeling approach comprising of hybrid frequency and time-domain analyses that encompass the transient nature of the ac–dc converter while providing the advantages of steady-state frequency-domain analysis. The limitations of conventional modeling approaches are quantified and addressed. Additionally, a comprehensive analysis of modeling error trends with converter parameters is presented, which demonstrates the effectiveness of the proposed method over conventional methods. Finally, using the proposed modeling approach, a numerical optimization routine is proposed to find the optimal-conduction-loss modulation trajectory. The effectiveness of the method is verified by experimental testing on a 1 kW, 230–28 V fully GaN-based single-phase DAB ac–dc converter.
Concurrent Modified Constant Modulus Algorithm and Decision Directed Scheme With Barzilai-Borwein Method

At present, in robot technology, remote control of robot is realized by wireless communication technology, and data anti-interference in wireless channel becomes a very important part. Any wireless communication system has an inherent multi-path propagation problem, which leads to the expansion of generated symbols on a time scale, resulting in symbol overlap and Inter-symbol Interference (ISI). ISI in the signal must be removed and the signal restores to its original state at the time of transmission or becomes as close to it as possible. Blind equalization is a popular equalization method for recovering transmitted symbols of superimposed noise without any pilot signal. In this work, we propose a concurrent modified constant modulus algorithm (MCMA) and the decision-directed scheme (DDS) with the Barzilai-Borwein (BB) method for the purpose of blind equalization of wireless communications systems (WCS). The BB method, which is two-step gradient method, has been widely employed to solve multidimensional unconstrained optimization problems. Considering the similarity of equalization process and optimization process, the proposed algorithm combines existing blind equalization algorithm and Barzilai-Borwein method, and concurrently operates a MCMA equalizer and a DD equalizer. After that, it modifies the DD equalizer's step size (SS) by the BB method. Theoretical investigation was involved and it demonstrated rapid convergence and improved equalization performance of the proposed algorithm compared with the original one. Additionally, the simulation results were consistent with the proposed technique.
Semi-Direct Monocular SLAM With Three Levels of Parallel Optimizations

In practical applications, how to use the complementary strengths of the direct and the feature-based methods for effective fusion may be the main challenge of simultaneous localization and mapping (SLAM). To solve this challenge, we propose the DO-SLAM, a novel fast and accurate semi-direct visual SLAM framework, which can maintain the direct method’s fast performance and the high precision and loop closure capability of the feature-based method. The direct method is used as the first half of the DO-SLAM to track the camera pose rapidly and robustly. The feature-based method is used as the second half of the DO-SLAM to refine the keyframe poses, perform loop closures, and build a globally consistent, long-term, sparse feature map that can be reused. The proposed pipeline fuses direct odometry and feature-based SLAM to perform three levels of parallel optimizations: (1) In the direct method module, the keyframe poses are estimated by minimizing the photometric error, (2) In the feature-based module, using the poses calculated by the inter-frame matching to correct and fuse the poses calculated by the direct method module as the initial poses, and the initial poses are optimized by the motion-only bundle adjustment, and (3) A pose graph optimization is used to achieve global map consistency in the presence of loop closures. Experimental evaluation on two benchmark datasets demonstrates that the proposed approach achieves higher accuracy and robustness on motion estimation compared to the other state-of-the-art methods.
Real-world experience with tramadol plus dexketoprofen fixed-dose combination in postoperative pain management: A series of case studies from Asia

Background: Early and effective treatment of postoperative pain is vital for minimizing pain severity and optimizing patient outcomes and satisfaction. The efficacy and tolerability data of tramadol 75 mg plus dexketoprofen 25 mg fixed-dose combination (TRAM/DKP FDC) are reported in clinical trials but the data on real-world experience in postoperative pain management in the Asian population is limited. Objectives: This series of case studies reviews clinicians’ experience and outcomes of postoperative pain management in Asian patients using a TRAM/DKP FDC in the real-world setting. Methods: Clinicians compiled, shared and discussed case studies of their experience using a TRAM/DKP FDC during two case studies expert meetings. A total of 13 case studies were shared across orthopaedic, soft tissue and laparoscopic surgery. Results: All cases reported well-tolerated postoperative pain management with good pain relief with TRAM/DKP FDC. Conclusions: TRAM/DKP FDC is an effective and well-tolerated option for the management of acute moderate-to-severe postoperative pain in Asian patients.
Fault Diagnostics by Conceptors-Aided Clustering

Fault diagnostics in practice faces the challenge of dealing with unlabelled time series that have long-term temporal dependencies. Inspired by the idea of representing temporal patterns by a mechanism of neurodynamical pattern learning, called Conceptors, we propose an unsupervised clustering method for identifying the degradation state of industrial equipment. Conceptors are used to represent the dynamic behaviour of the degradation trajectories and spectral clustering is used to group the Conceptors in homogenous classes of similar degradation states. The proposed method is applied to a case study of literature. The results show that the accuracy of the fault diagnosis is satisfactory.
Ultra thin ZnO on metal substrates: An ab initio study

In the context of catalysis and hybrid inorganic/organic systems, metal supported ultra-thin ZnO can be used as model systems within the surface science approach. However, it is not clear to what degree the ZnO films resemble the surfaces of ZnO or whether they exhibit significantly different properties. To this purpose we investigate the structure of ultra-thin ZnO films (1 to 4 layers) on the (111) surfaces of Ag, Cu, Ni, Rh, Pd, and Pt by means of density-functional theory. The free-standing ZnO mono-layer adopts an α-BN structure. This structure prevails on the metal substrates, and we obtain coincidence structures in good agreement with experiment. Thicker ZnO layers, preferentially grow in the c-direction and adopt a wurtzite structure. The films exhibit a large random corrugation. The electronic structure is modified by the intrinsic polar nature of ZnO. The induced field leads to an upwards shift of the surface electronic states relative to the Fermi level with increasing film thickness. The states are eventually pinned at the Fermi level provided by the metal substrate, leading to an effective p-type doping of the thin film surface. Metal supported ultra-thin films might thus be a way to achieve the much coveted p-type doping of ZnO. To investigate the thermodynamic stability of ZnO on the metal substrates we take the chemical potentials of Zn, O2, H2, and H2O environments into consideration by means of ab initio thermodynamics. Up to three layers of unreconstructed ZnO are predicted to be stable on the metal substrates at experimentally accessible pressure ranges. A hydrogen over-layer with 50% coverage is formed at chemical potentials that range from low vacuum to ultra-high vacuum H2 pressures. The surface structure and the density of states of these hydrogen passivated ZnO thin films agree well with those of the ZnO (0001̄)–(2× 1)–H surface. ZnO ultra-thin films without hydrogen exhibit interesting and unique properties, whereas, the (2×1)–H reconstructed films can be regarded as good ZnO surface models. The hydrogen chemical potential provides a handle to select and potentially switch between those two surface terminations. We also include OH-reconstructions, Zn/O defects and sparse ring structures in our approach to draw up an extensive surface phase diagram that will guide future work on ultra-thin ZnO on metal substrates. For example, our calculations allow us to identify the ultra-thin films grown by Shiotari et al. on Ag as hydrogen-free ZnO double-layers. In a joined effort with the group of A. Knorr at TU Berlin, “hybrid Bloch equations” based on a density-matrix formalism are parametrized by ab initio results. The parameterizations are based on dipole matrix elements and partial charges fitted to the electrostatic potential. Both methods were implemented as part of this Phd into the FHI-aims code to investigate exitonic process at ZnO/organic interfaces. The interaction of substrate and molecule was found to be strongest at low coverages and for a parallel alignment between the molecule and the surface dipole.
Thermal Field Calculation and Analysis of Gas Insulated Busbars Based on Fluid Multiple Species Transport

The operation status of gas insulated busbars(GIBs) is relative to the heat dissipation ability and temperature rise property.Finite element method(FEM) was employed to calculate the joule losses in the conductors and eddy current loss in the tank.According to the fluid dynamic theories,the fluid multiple species transport model was used to investigate the fluid field and the thermal field distribution of the GIBs.Eddy current field results were indirectly coupled with fluid and thermal fields by the element mapping method.In addition to convection and radiation effects at the fluid-solid interfaces,the temperature dependent characteristics of fluid parameters were considered.Steady state and transient state thermal fields of isolated phase GIB and three phase in one tank type GIB were analyzed.Heat dissipation proportions by convection and radiation at the fluid-solid interfaces,heat transfer coefficient distribution and temperature change with load currents and time were investigated.The model is validated by comparison with the traditional engineering algorithm,the single species model and experimental results.
Machine learning: Brief overview for biomedical researchers

Machine learning is a sub-field of artificial intelligence. It is a field that involves computer algorithms that are given the capability to learn from data. This results in model generation of complex rules from the data itself, rather than from relying on strict rubrics inputted manually. Relationships between inputted data [variables such as demographics, physiological data, laboratory values, etc.] and outcomes [mortality, presence of infection, acute kidney injury, etc.] can be uncovered even when not immediately obvious to a trained expert. In recent years, there has been a surge of literature using machine learning in healthcare research; some articles are highlighted in Table 1 [3-7].
Acetylation stabilizes chloride intracellular channel 1 that exerts a tumor-promoting role by activation of nuclear factor kappa B in cervical cancer

Background: Cervical cancer remains a major cause of cancer-related death in women, especially in developing countries. Previously, we identified that acetylation levels of chloride intracellular channel 1 (CLIC1) at lysine 131 were increased in cervical cancer tissues by using the label-free proteomics approach. The aim of this study was further to determine the role of CLIC1 expression and its acetylation in cervical cancer. Methods: CLIC1 expression and its implications on prognosis in cervical cancer were analyzed using Gene Expression Profiling Interactive Analysis (GEPIA) database (gepia.cancer-pku.cn). The effect of CLIC1 on cells was evaluated by Cell Counting Kit (CCK)-8, flow cytometry, wound healing assay, transwell assay, western blotting, and co-immunoprecipitation (Co-IP). In vivo tumor growth was assessed in mouse xenograft models. Results: We found that CLIC1 expression was increased in cervical cancer tissues and cells. The knockdown of CLIC1 significantly reduced cell proliferation, migration, invasion, and in vivo tumorigenesis of cervical cancer cells. Molecularly, nuclear factor kappa B (NF-κB) activity was positively regulated by CLIC1. Pyrrolidine dithiocarbamate (PDTC), an inhibitor of NF-κB activation, attenuated the tumor-promoting effect of CLIC1. Moreover, CLIC1 acetylation at K131 was upregulated in cervical cancer, which stabilized CLIC1 by inhibiting ubiquitylation. The substitution of K131 inhibited CLIC1 ubiquitylation and promoted cell proliferation, migration, and invasion, and tumor growth. In addition, we identified that acetyltransferase HAT1 was responsible for CLIC1 acetylation at K131. Conclusion: This finding shows that CLIC1 is a tumor promoter in cervical cancer, indicating a potential strategy to treat cervical cancer by regulating CLIC1 expression or acetylation.
Evaluation of Lens Culinaris Agglutinin-Reactive α-Fetoprotein in Diagnosis of Malignant Tumors.

BACKGROUND To assess the potential of AFP-L3% for the utility to diagnose malignant tumors. METHODS AFP-L3 was concentrated from clinically-collected serum samples via the Hotgen Biotech glycosyl capture spin columns and then measured through the protein microarrays. The levels of AFP and AFP-L3 were detected by electrochemiluminescence immunoassay. In this retrospective study, 266 patients with the level of serum AFP-L3 over 1 ng/mL were recruited from December 2014 through April 2019. Among them, 155 patients were clinically diagnosed/confirmed with malignant tumors, including 101 hepatocellular carcinomas, 47 stomach malignant tumors, and 7 other malignant tumors; and the rest of 111 patients were nonmalignant tumors. RESULTS Patients with serum AFP-L3 level of greater than 1 ng/mL were mainly detected in hepatic diseases, including hepatocellular carcinoma, cirrhosis and chronic hepatitis. In patients with no tumors, the levels of serum AFP-L3 over 1 ng/mL were only observed in liver disease. The levels of AFP-L3 in blood were substantially greater in patients with HCC. Among the malignant tumor patients with the level of serum AFP-L3 over 1 ng/mL, HCC accounted for 60%, gastric cancer for nearly 40%. The AFP, AFP-L3, and AFP-L3% in blood were increased significantly in patients with liver malignancy, chronic liver disease, and cirrhosis. However, the elevation of AFP-L3 and AFP-L3% in the malignant cohort was more evident than that in the nonmalignant counterpart. CONCLUSIONS AFP-L3 is likely to contribute to the differential diagnosis of HCC as well as other hepatic diseases. AFP-L3% is a reliable indicator for diagnosing benign and malignant tumors.
A low workload operation method for SDN switch replacement that prevents wiring mistakes

: In order to dramatically reduce the operation work needed for switch replacement, we propose a new operation method that allows connections among arbitrary port pairs. We build and test a system that implements our proposal. The system detects wiring mistakes, and supports replacement with different or same switch models. A wiring experiment shows our proposal can enhance wiring efficiency.
Some Compounds from Neem leaves extract exhibit binding affinity as high as -14.3 kcal/mol against COVID-19 Main Protease (Mpro): A Molecular Docking Study

Currently the new Coronavirus "COVID-19", also known as SARS-CoV-2, has infected nearly 3 million patients and nearly 200,000+ people have lost their lives due to this pandemic. There is an urgent need to find an antiviral agent that may slow down the spread of the virus. The aim of this study is to assess and evaluate compounds present in leaves of Neem tree (Azadirachta Indica) as potential inhibitors for COVID-19 Main Protease (Mpro) (PDB code: 6LU7). This will be done by blind molecular docking using PyRx and Auto Vina software. The compounds Hydroxychloroquine and Remdesivir were used for comparative study. The binding energies obtained from the docking of 6LU7 with meliacinanhydride, nimocinol, isomeldenin, nimbolide, zafaral, nimbandiol, nimbin, nimbinene, desacetylnimbin were -14.3, -12.4, -12.3, -12.2, -11.9, -11.8, -11.7, -11.7, -11.4 kcal/mol respectively. Therefore Meliacinanhydride (Ki=33.36 pM) and the compounds from Neem leaves may be a potential treatment option against COVID-19. In addition to that the leaves contain others compounds like Quercetin, Zinc,Vitamin A,Vitamin B1,B2,B6, Vitamin C,Vitamin E etc., which may boost immunity also (Garba, 2019) . Further investigation is needed to evaluate the results of this study to consider Neem leaves as potential treatment option as it might inhibit the virus and boost immunity also
Knowledge as the Currency of Managing Risk: a Novel Framework to Unite Quality Risk Management and Knowledge Management

In a manner of speaking, knowledge is the currency of managing risk and an organization that is risk-focused will want to apply the best of what it knows to assess those risks, identify appropriate risk controls and evaluate the performance of those controls. An organization that effectively manages knowledge should be able to recognize and proactively apply new learnings to better anticipate risks. This is particularly important in the manufacture of medicinal products. Since the publication of ICH Q10 in 2010, QRM and KM have been positioned as coenablers to the Pharmaceutical Quality System. However, in practice these two disciplines have remained largely distinct and disconnected. This paper presents a novel way to consider Quality Risk Management (QRM) and Knowledge Management (KM) which represents their true interdependencies, and which has the potential to deliver more effective and risk-based control strategies in a more synergistic and effective manner. This paper advocates for the need to strengthen the relationship between QRM and KM. In order to better understand the synergistic relationship between QRM and KM, a Knowledge Management process model is first proposed to envision KM akin to the familiar representation of QRM in ICH Q9 . Following this model, a framework is presented in the form of a Risk-Knowledge Infinity Cycle which serves to visualise and understand the QRM-KM relationship. It is the authors belief that treating QRM and KM in this way has a variety of potential benefits for biopharmaceutical companies, including improved risk-based decision making, facilitating evidence-based risk reduction and increased process knowledge, leading to less uncertainty and subjectivity in QRM outputs. This should ultimately result in more effective risk-based control strategies and more reliable manufacturing processes, which potentially lead to increased protection – and other benefits including product availability and value – for patients. 1 Lipa et al.: knowledge as currency Published by ARROW@TU Dublin, 2020 Level3 Issue 17, December 2020 Technological University of Dublin
Topography-mediated Control of Cellular Response: Migration, Intracellular Crowding, and Gene-delivery

Biophysical stimuli including topography play a crucial role in regulation of cell morphology, adhesion, migration, and cytoskeleton organization, and have been known to be important in biomaterials design for tissue engineering. However, little is known about the individual effects of topographic direction, structure repetition and feature size of the substrate on which wound healing occurs. We report on the design of a topographical gradient with wave-like features that gradually change in wavelength and amplitude which provides an efficient platform for an in vitro wound healing assay to investigate fibroblast migration. The wound coverage rate was measured on selected areas with wavelength sizes of 2 μm , 5 μm , and 8 μm in perpendicular and parallel orientation. Furthermore, a method was developed to produce independently controlled wavelength and amplitude and study which parameter have greater influence. Cell movement was guided by the topographical properties, the smaller wrinkle wavelength (2 μm) elic iting fastest migration speed and the migration speed increased with decreasing amplitude. However, when the amplitudes were matched, cells migrated faster on the larger wavelength. This study also highlights the sensitivity of fibroblasts to topographic orientation with cells moving faster in parallel direction of the topography. The overall behaviour indicated that the wavelength and amplitude both play an important role in directing cell migration. The collective cell migration was found not to be influenced by altered cell proliferation. These findings provide key insights into topography triggered cell migration and indicates the necessity for better understanding of material-directed wound healing for designing bio-inductive biomaterials.
FREQUENCY RECONFIGURABLE ANTENNA WITH DUAL-BAND AND DUAL-MODE OPERATION

A frequency reconfigurable antenna with dual-band operation is presented. The antenna has a circular radiating patch loaded with an annular slot, and the slotted patch is shorted to the ground plane with four conducting posts. The antenna has three feed ports. Two of the ports are used to excite the slot mode resonant at a lower frequency, and broadside radiation with dual orthogonal linear polarizations can be obtained. The other port is used to excite the monopolar-patch mode resonant at a higher frequency, and conical radiation with vertical polarization can be yielded. To reconfigure the operation frequencies, four varactors are symmetrically placed across the annular slot. The simulated results indicate that the resonant frequency of the slot mode can be tuned from 1.62 to 1.17 GHz when the capacitance of the varactors is varied from 0.6 to 1.8 pF; besides, for each capacitance value, the impedance bandwidth of the antenna operating in the monopolar-patch mode can cover the frequencies from 2.4 to 2.5 GHz. Experiments are also carried out to validate the simulated data.