Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Job Demands and Work Engagement on Job Satisfaction of KOPINDOSAT Employees in Jakarta

The purpose of this study is to find out how the influence of job demands and work engagement on job satisfaction among KOPINDOSAT employees in Jakarta. This research uses survey method with ex post facto approach. The data used is quantitative data using technical path analysis. The population in this study were all employees of the Indosat Cooperative, amounting to 100 people. All members of the population were used as a sample of 100 people. The results obtained: 1) There is a negative and significant effect of job demands on job satisfaction. 2) There is a negative and significant influence of job demands on work engagement. 3) There is an influence and positive and significant work engagement to job satisfaction. 4) There is a negative influence of job demands on job satisfaction through work engagement.
Antibody-drug conjugates (ADCs) targeting trophoblast cell surface antigen 2 (Trop-2) and precision treatment of breast cancer

© Annals of Translational Medicine. All rights reserved. Ann Transl Med 2022;10(21):1184 | https://dx.doi. org/10.21037/atm-22-4581 With the development of new molecular technologies, the landscape of cancer therapy is changing from unspecific, systemic “one strategy fits all” therapy towards a more personalized strategy. Antibody-drug conjugates (ADC) are precision cancer treatments that combines the potential of more or less tumor specific antigen targeted therapy with drugs that are already on label for treatment for cancer (e.g., irinotecan/SN-38), or drugs that are too toxic for normal anticancer use (as e.g., emtansine). By conjugating these drugs to antigen targeting antibodies, it is possible to reduce the plasma concentration of the anticancer drug and at the same time deliver a higher dose of the drug to the antigen expressing cancer cells (1-3). A successful example is the publication in April 2021 in the New England Journal of Medicine on the results from therapy with sacituzumab govitecan (Trodelvy) in relapsed or refractory metastatic Triple-Negative Breast Cancer (TNBC) patients (4). Sacituzumab govitecan is an ADC composed of a monoclonal antibody targeting the human trophoblast cellsurface antigen 2 (Trop-2), which is expressed in more than 90% of breast cancer cells but only scarcely in normal cells, coupled to SN-38 [a topoisomerase I (Top I) inhibitor] through a proprietary hydrolyzable linker (4). From 2013 to 2021 about 12 ADC’s including sacituzumab govitecan, have been approved in the treatment of hematological cancers, breast cancer, urothelial tumors and cervical cancer. In the beginning of 2022, more than 15 ADC’s are in clinical phase II or III trials with indications such as hematological diseases, non-small and small cell lung cancer, prostate cancer, glioblastoma, mesothelioma, ovarian cancer and renal cell carcinoma and other (3). The caveats of ADC therapy are related to the mode of action. The duality in the mode of action is also one of the limitations of the potential treatment indication. The tumor cells must have some degree of expression of the targeted antigen (as e.g., the more than 90% expression of Trop-2 in breast cancer (4), and the cytotoxic conjugates must be active against the tumor type in question. One of the major quests is to find an antigen with increased expression on the tumor cells and minimal expression on normal healthy cells and targeting this with an antibody combined with a cytotoxic drug (or radioactive isotope, or another drug attracting for instance the immune cells) that will then mainly be released in the specific tumor cells. If the ADC targets and release its cytotoxic conjugate on vulnerable and essential normal cells (e.g., in the gut) the toxicity may be limiting the clinical use of the ADC. If the linking of the toxic drug conjugate to the antibody is weak Editorial Commentary
Seroepidemiology of Tetanus among Healthy People Aged 1–59 Years Old in Shaanxi Province, China

The study aims to determine the seroprevalence of antibodies against tetanus among healthy people aged 1–59 years old in Shaanxi province. IgG against tetanus in serum samples were detected by ELISA. 6,439 subjects were enrolled. The positive rate (≥0.01 IU/mL) was 84.39% and GMC was 0.03 IU/mL. There were significant differences in positive rates (χ2 = 308.944, p < 0.01) and GMC (Z = 5,200,000, p < 0.01) among different age groups. The positive rates (χ2 = 304.3, p < 0.01) and GMCs (χ2 = 146.417, p < 0.01) showed regional differences. Both full protection rate (≥0.1 IU/mL) (χ2 = 36.834, p < 0.01) and GMC (Z = 688,000, p < 0.01) increased with the doses of tetanus-toxoid-containing vaccines (TTCVs) administered. The positive rate (χ2 = 54.136, p < 0.01) and GMC (Z = 140,200, p < 0.01) decreased gradually with the time interval after full immunization with TTCVs. The full protection rate (≥0.1 IU/mL) (χ2 = 176.201, p < 0.01) and GMC (Z = 629,900, p < 0.01) decreased with the interval (years) since the last dose of TTCVs. There were significant differences in the positive rates and GMCs for different ages, regions, immunization histories of TTCVs, and doses of TTCVs administered. The full protection rate and GMC decreased with the interval following full immunization with TTCVs and the interval since the last dose of TTCVs. The importance of using tetanus booster doses should be emphasized in adolescents and adults.
An FFT-based CNN-transformer encoder for semantic segmentation of radar sounder signal

Radar Sounders (RSs) are sensors operating in the nadir-looking geometry (with HF or VHF bands) by transmitting modulated electromagnetic (EM) pulses and receiving the backscattering response from different subsurface targets. Recently, convolutional neural network (CNN) architectures were established for characterizing RS signals under the semantic segmentation framework. In this paper, we design a Fast Fourier Transform (FFT) based CNN-Transformer encoder to effectively capture the long-range contexts in the radargram. In our hybrid architecture, CNN models the high-dimensional local spatial contexts, and the Transformer establishes the global spatial contexts between the local spatial ones. To overcome Transformer complex self-attention layers by reducing learnable parameters; - we replace the self-attention mechanism of the Transformer with unparameterized FFT modules as depicted in FNet architecture for Natural Language Processing (NLP). The experimental results on the MCoRDS dataset indicate the capability of the CNN-Transformer encoder along with the unparameterized FFT modules to characterize the radargram with limited accuracy cost and by reducing the time consumption. A comparative analysis is carried out with the state-of-the-art Transformer-based architecture.
Deep Learning Hybrid Techniques for Brain Tumor Segmentation

Medical images play an important role in medical diagnosis and treatment. Oncologists analyze images to determine the different characteristics of deadly diseases, plan the therapy, and observe the evolution of the disease. The objective of this paper is to propose a method for the detection of brain tumors. Brain tumors are identified from Magnetic Resonance (MR) images by performing suitable segmentation procedures. The latest technical literature concerning radiographic images of the brain shows that deep learning methods can be implemented to extract specific features of brain tumors, aiding clinical diagnosis. For this reason, most data scientists and AI researchers work on Machine Learning methods for designing automatic screening procedures. Indeed, an automated method would result in quicker segmentation findings, providing a robust output with respect to possible differences in data sources, mostly due to different procedures in data recording and storing, resulting in a more consistent identification of brain tumors. To improve the performance of the segmentation procedure, new architectures are proposed and tested in this paper. We propose deep neural networks for the detection of brain tumors, trained on the MRI scans of patients’ brains. The proposed architectures are based on convolutional neural networks and inception modules for brain tumor segmentation. A comparison of these proposed architectures with the baseline reference ones shows very interesting results. MI-Unet showed a performance increase in comparison to baseline Unet architecture by 7.5% in dice score, 23.91% insensitivity, and 7.09% in specificity. Depth-wise separable MI-Unet showed a performance increase by 10.83% in dice score, 2.97% in sensitivity, and 12.72% in specificity as compared to the baseline Unet architecture. Hybrid Unet architecture achieved performance improvement of 9.71% in dice score, 3.56% in sensitivity, and 12.6% in specificity. Whereas the depth-wise separable hybrid Unet architecture outperformed the baseline architecture by 15.45% in dice score, 20.56% in sensitivity, and 12.22% in specificity.
The LX-T and LX-σ Relationships for Galaxy Clusters Revisited

The relationships between the X-ray-determined bolometric luminosity, LX, the temperature, T, of the intracluster gas, and the optical measured velocity dispersion, σ, of the cluster galaxies are updated for galaxy clusters using the largest sample of 256 clusters drawn from literature. The newly established relationships, based on the doubly weighted orthogonal distance regression (ODR) method, are justified by both their self-consistency and co-consistency, which can then be used to test the theoretical models of cluster formation and evolution. The observationally determined LX-T and LX-σ relationships, LX ∝ T2.72±0.05 ∝ σ5. 24±0.29, are marginally consistent with those predicted by the scenario in which both intracluster gas and galaxies are in isothermal and hydrostatic equilibrium with the underlying gravitational potential of clusters. A comparison between these observed and predicted LX-T relationships also suggests that the mean cluster baryon fraction, fb, remains approximately constant among different clusters, fb ≈ 0.17, which gives rise to a low mass density universe of Ωm ≈ 0.3.
Homotopic routing methods

is NP-complete, even for planar graphs, both in the vertex-disjoint and in the edgedisjoint case (Lynch [26)). In some special cases, however, there is a polynomialtime method for (1). These cases usually also give rise to a theorem characterizing the existence of a solution as required. Moreover, if G is planar, one can design a heuristic or enumerative approach based on the topology of the plane. It amounts to selecting a, possibly small, set of faces Ii, . ,Ip of G so that each of the vertices r 1,s1,. ,rk,Sk is incident with at least one of these faces. Next we choose (or enumerate) for each pair r;, s; a curve C; in 1R.2\(I1 u . u Ip) connecting r; and s;. Our problem then is to find pairwise disjoint paths Pi. , Pk so that P; is homotopic to C; in the space 1R.2\(I1 u . u Ip)· If such P; are found, we have solved our original problem. Otherwise, we choose other curves C; (i.e., representing other homotopies), and try again. So in this approach (proposed by Pinter [31)) we must solve the following problem:
How modernization theory has stumbled in China: A political interception perspective

ABSTRACT Economic development fails to greatly increase demand for liberal democracy in China. Is China an exception to modernization theory? If so, why? This paper studies these questions by analysing five waves of Asian Barometer Survey data from 2002 to 2019. We have three major findings. First, the shift of political values exhibits an inverted U-shaped curve with the mid-2010s as its turning point. Second, the better educated and more media exposed turned conservative much faster than the rest after the mid-2010s. Third, to trace the mechanism of this unusual reversal and divergence, we resort to a Difference-In-Differences model, taking political indoctrination, measured by media exposure and education, as treatment and the post-2013 era as treatment time, finding that political indoctrination significantly explains political cultural backsliding. Our findings enrich modernization theory by identifying the “interceptive” power of the state between economic development and cultural shifts.
Graph Theoretical Analysis of EEG Functional Connectivity Patterns and Fusion with Physiological Signals for Emotion Recognition

Emotion recognition is a key attribute for realizing advances in human–computer interaction, especially when using non-intrusive physiological sensors, such as electroencephalograph (EEG) and electrocardiograph. Although functional connectivity of EEG has been utilized for emotion recognition, the graph theory analysis of EEG connectivity patterns has not been adequately explored. The exploitation of brain network characteristics could provide valuable information regarding emotions, while the combination of EEG and peripheral physiological signals can reveal correlation patterns of human internal state. In this work, a graph theoretical analysis of EEG functional connectivity patterns along with fusion between EEG and peripheral physiological signals for emotion recognition has been proposed. After extracting functional connectivity from EEG signals, both global and local graph theory features are extracted. Those features are concatenated with statistical features from peripheral physiological signals and fed to different classifiers and a Convolutional Neural Network (CNN) for emotion recognition. The average accuracy on the DEAP dataset using CNN was 55.62% and 57.38% for subject-independent valence and arousal classification, respectively, and 83.94% and 83.87% for subject-dependent classification. Those scores went up to 75.44% and 78.77% for subject-independent classification and 88.27% and 90.84% for subject-dependent classification using a feature selection algorithm, exceeding the current state-of-the-art results.
Tomographic Separation of Composite Spectra. VIII. The Physical Properties of the Massive Compact Binary in the Triple Star System HD 36486 (δ Orionis A)

We present the first double-lined spectroscopic orbital elements for the central binary in the massive triple δ Orionis A. The solutions are based on fits of cross-correlation functions of IUE high-dispersion UV spectra and He I λ6678 profiles. The orbital elements for the primary agree well with previous results, and in particular, we confirm the apsidal advance with a period of 224.5 ± 4.5 yr. We also present tomographic reconstructions of the primary and secondary stars' spectra that confirm the O9.5 II classification of the primary and indicate a B0.5 III type for the secondary. The relative line strengths between the reconstructed spectra suggest magnitude differences of Δm = -2.5 log(Fs/Fp) = 2.6 ± 0.2 in the UV and Δm = 2.5 ± 0.3 at 6678 Å. The widths of the UV cross-correlation functions are used to estimate the projected rotational velocities, V sin i = 157 ± 6 and 138 ± 16 km s-1 for the primary and secondary, respectively (which implies that both the primary and the secondary rotate faster than the orbital motion). We used the spectroscopic results to make a constrained fit of the Hipparcos light curve of this eclipsing binary, and the model fits limit the inclination to the range i = 67°-77°. The lower limit corresponds to a near Roche-filling configuration that has an absolute magnitude that is consistent with the photometrically determined distance to Ori OB1b, the Orion Belt cluster in which δ Ori resides. The i = 67° solution results in masses of Mp = 11.2 and Ms = 5.6 M☉, both of which are substantially below the expected masses for stars of their luminosity. The binary may have experienced a mass ratio reversal caused by case A Roche lobe overflow or the system may have suffered extensive mass loss through a binary interaction (perhaps during a common envelope phase) in which most of the primary's mass was lost from the system rather than transferred to the secondary. We also made three-component reconstructions to search for the presumed stationary spectrum of the close visual companion δ Ori Ab (Hei 42 Ab). There is no indication of the spectral lines of this tertiary in the UV spectrum, but a broad and shallow feature is apparent in the reconstruction of He I λ6678 indicative of an early B-type star. The tertiary may be a rapid rotator (V sin i ≈ 300 km s-1) or a spectroscopic binary.
Decision support tools for grass-based fodder management on Walloon dairy farms: current adoption and perspectives

Description of the subject. Many decision support tools (DSTs) have been developed to help dairy farmers optimally manage the high variability in the quality and availability of grass-based fodder, but their adoption rate remains low. Objectives. The objective was to characterize and understand the adoption rate of DSTs related to using grass-based fodder. Methodology. A sample of 61 Walloon (Belgium) dairy farmers responded to an online survey concerning their current use of 23 DSTs related to using grass-based fodder either directly (pasture or grassland) or indirectly (feeding or techno-economic), as well as barriers to and incentives for adopting them, their current interest in DSTs, and satisfaction with the guidance on using these DSTs. Results. Pasture management DSTs were used the least, even though farmers were the most interested in them. Farmers used simple indicators rather than software or automated tools. Farmers indicated that DSTs were too expensive and time consuming, even if they could ultimately save them time and money. Continuing education is lacking. Four types of users were identified who influence the use of DSTs: high user no grazing (H-NG), high user traditional or technical grazing (H-T/TG), low user traditional grazing (L-TG), and moderate user organic (M-ORG). Conclusions. Communicating with end-users during each step of DST development would help (1) identify the specific needs of a diverse set of dairy farmers and (2) develop DSTs that better correspond to their practices. More long-term guidance is required to inform farmers about existing DSTs and to transfer the knowledge required to use them.
Shapley Mapping and Its Axiomatizations in n-Person Cooperative Interval Games

Interval games are an extension of cooperative coalitional games, in which players are assumed to face payoff uncertainty. Characteristic functions thus assign a closed interval, instead of a real number. In this paper, we first examine the notion of solution mapping, a solution concept applied to interval games, by comparing it with the existing solution concept called the interval solution concept. Then, we define a Shapley mapping as a specific form of the solution mapping. Finally, it is shown that the Shapley mapping can be characterized by two different axiomatizations, both of which employ interval game versions of standard axioms used in the traditional cooperative game analysis such as efficiency, symmetry, null player property, additivity and separability.
Stage-Dependent Regulation of Dental Pulp Stem Cell Odontogenic Differentiation by Transforming Growth Factor-β1

Transforming growth factor-β1 (TGF-β1) is an important multifunctional cytokine with dual effects on stem cell differentiation. However, the role of TGF-β1 on odontogenic differentiation of dental pulp stem cells (DPSCs) remains to be entirely elucidated. In the present study, we initially investigated the effect of TGF-β1 at a range of concentrations (0.1-5 ng/mL) on the proliferation, cell cycle, and apoptosis of DPSCs. Subsequently, to determine the effect of TGF-β1 on odontogenic differentiation, alkaline phosphatase (ALP) activity and Alizarin Red S (ARS) staining assays at different concentrations and time points were performed. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot analysis were used to determine the levels of odonto-/osteo-genic differentiation-related gene and protein expression, respectively. For in vivo studies, newly formed tissue was assessed by Masson's trichrome and von Kossa staining. Data indicated that TGF-β1 inhibited DPSCs proliferation in a concentration-and time-dependent manner (p < 0.05) and induced cell cycle arrest but did not affect apoptosis. ALP activity was enhanced, while ARS reduced gradually with increasing TGF-β1 concentrations, accompanied by increased expression of early marker genes of odonto-/osteo-genic differentiation and decreased expression of late-stage mineralization marker genes (p < 0.05). ALP expression was elevated in the TGF-β1-treatment group until 14 days, and the intensity of ARS staining was attenuated at days 14 and 21 (p < 0.05). Compared with the control group, abundant collagen but no mineralized tissues were observed in the TGF-β1-treatment group in vivo. Overall, these findings indicate that TGF-β1 promotes odontogenic differentiation of DPSCs at early-stage while inhibiting later-stage mineralization processes.
Numerical analysis of two ensemble eddy viscosity numerical regularizations of fluid motion

This report analyzes an efficient ensemble regularization algorithm for under‐resolved and convection dominated flows (including ones at higher Reynolds numbers). Computing an ensemble simultaneously allows each realization to access ensemble data. This allows use of means and fluctuations in regularizations used for each realization. The combined approach of ensemble time stepping and ensemble regularizations allows direct calculation of the turbulent viscosity coefficient and gives an unconditionally stable algorithm. It also suggests reconsidering an old but not as well‐developed definition of the mixing length. This mixing length vanishes at solid walls without van Driest damping, increases stability, and improves flow predictions in our preliminary tests. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 31: 630–651, 2015
Effects of filtering on the purity of heralded single photons from parametric sources

Optical quantum protocols are reliant on the production of highly pure single photons. However, most parametric heralded single-photon sources possess spectral correlations, limiting the purity of the produced photon. The most common method for restoring the purity is with narrowband spectral filtering, which comes at the cost of reducing the rate of heralding detection. Here, we characterize this trade-off analytically for a large class of parametric sources. It is possible to achieve up to 20% heralding success probabilities with 90% heralded photon purities.
Health promotion: Exercise

Physical activity can have a transformational positive impact on both individual and public health outcomes. It can be used to positively and proactively manage many common chronic conditions, as well as reducing the risk of developing them. However, in the UK, over one-in-four adults is physically inactive, and one-in-three children do less than half the physical activity recommended for their age. This article looks at the benefits of physical activity, UK government recommendations for physical activity in different age groups, and how to support patients in primary care to become more active.
General blow-ups of the projective plane

We study linear series on a projective plane blown up in a bunch of general points. Such series arise from plane curves of fixed degree with assigned fat base points. We give conditions (expressed as inequalities involving the number of points and the degree of the plane curves) on these series to be base point free, i.e. to define a morphism to a projective space. We also provide conditions for the morphism to be a higher order embedding. In the discussion of the optimality of obtained results we relate them to the Nagata Conjecture expressed in the language of Seshadri constants and we give a lower bound on these invariants.